ALBERT

Description: Peelle’s Pertinent Puzzle (PPP) was described in 1987 in the context of estimating fundamental parameters that arise in nuclear interaction experiments. In PPP, generalized least squares (GLS) parameter estimates fell outside the range of the data, which has raised concerns that GLS is somehow flawed and has led to suggested alternatives to GLS estimators. However, there have been no corresponding performance comparisons among methods, and one suggested approach involving simulated data realizations is statistically incomplete. Here we provide performance comparisons among estimators, introduce approximate Bayesian computation (ABC) using density estimation applied to simulated data realizations to produce an alternative to the incomplete approach, complete the incompletely specified approach, and show that estimation error in the assumed covariance matrix cannot always be ignored.

Description: In 2009, just 27% of American teens with mobile phones reported using their devices to access the internet. However, teens from lower income families and minority teens were significantly more likely to use their phones to go online. Together, these surprising trends suggest a potential narrowing of the digital divide, offering internet access to those without other means of going online. This is an important move, as, in today’s society, internet access is central to active citizenship in general and teen citizenship in particular. Yet the cost of this move toward equal access is absorbed by those who can least afford it: Teenagers from low income households. Using survey and focus group data from a national study of “Teens and Mobile Phone Use” (released by Pew and the University of Michigan in 2010), this article helps identify and explain this and other emergent trends for teen use (as well as non-use) of the internet through mobile phones.

Description: As a member of the Annex 1 countries to the Kyoto Protocol of the United Nations Framework Convention on Climate Change, Japan is committed to reducing 6% of the greenhouse gas emissions. In order to achieve this commitment, Japan has undertaken several major mitigation measures, one of which is the domestic measure that includes ecologically friendly lifestyle programs, utilizing natural energy, participating in local environmental activities, and amending environmental laws. Mitigation policies could be achieved if public responses were strong. As the internet has increasingly become an online platform for sharing environmental information, public responses to the need for reducing greenhouse gas emissions may be assessed using available online tools. We used Google Insights for Search, Google AdWords Keyword Tool, and Google Timeline View to assess public responses in Japan based on the interest shown for five search terms that define global climate change and its mitigation policies. Data on online search interests from January 04, 2004 to July 18, 2010 were analyzed according to locations and categories. Our study suggests that the search interests for the five chosen search terms dramatically increased, especially when new mitigation policies were introduced or when climate change related events were organized. Such a rapid increase indicates that the Japanese public strongly responds to climate change mitigation policies.

Description: Multimedia streaming means delivering continuous data to a plethora of client devices. Besides the actual data transport, this also needs a high degree of content adaptation respecting the end users’ needs given by content preferences, transcoding constraints, and device capabilities. Such adaptations can be performed in many ways, usually on the media server. However, when it comes to content editing, like mixing in subtitles or picture-in-picture composition, relying on third party service providers may be necessary. For economic reasons this should be done in a service-oriented way, because a lot of adaptation modules can be reused within different adaptation workflows. Although service-oriented architectures have become widely accepted in the Web community, the multimedia environment is still dominated by monolithic systems. The main reason is the insufficient support for working with continuous data: generally the suitability of Web services for handling complex data types and state-full applications is still limited. In this paper we discuss extensions of Web service frameworks, and present a first implementation of a service-oriented framework for media streaming and digital item adaptation. The focus lies on the technical realization of the services. Our experimental results show the practicality of the actual deployment of service-oriented multimedia frameworks.

Description: Usually, test automation scripts for a web application directly mirror the actions that the tester carries out in the browser, but they tend to be verbose and repetitive, making them expensive to maintain and ineffective in an agile setting. Our research has focussed on providing tool-support for business-level, example-based specifications that are mapped to the browser level for automatic verification. We provide refactoring support for the evolution of existing browser-level tests into business-level specifications. As resulting business rule tables may be incomplete, redundant or contradictory, our tool provides feedback on coverage.

Description: Since 1997, the Victorian Resources Online (VRO) website (http://www.dpi.vic.gov.au/vro) has been a key means for the dissemination of landscape-based natural resources information via the internet in Victoria, Australia. The website currently consists of approximately 11,000 web pages, including 1900 maps and 1000 downloadable documents. Information is provided at a range of scales—from statewide and regional overviews to more detailed catchment and sub-catchment levels. At all these levels of generalisation, information is arranged in an organisationally agnostic way around key knowledge “domains” (e.g., soil, landform, water). VRO represents a useful model for the effective dissemination of a wide range of natural resources information; relying on partnerships with key subject matter experts and data custodians, including a “knowledge network” of retired land resource assessment specialists. In this paper, case studies are presented that illustrate various approaches to information and knowledge management with a focus on presentation of spatially contexted soil and landscape information at different levels of generalisation. Examples are provided of adapting site-based information into clickable maps that reveal site-specific details, as well as “spatialising” data from specialist internal databases to improve accessibility to a wider audience. Legacy information sources have also been consolidated and spatially referenced. More recent incorporation of interactive visualisation products (such as landscape panoramas, videos and animations) is providing interactive rich media content. Currently the site attracts an average of 1190 user visits per day and user evaluation has indicated a wide range of users, including students, teachers, consultants, researchers and extension staff. The wide range of uses for information and, in particular, the benefits for natural resource education, research and extension has also been identified.

Description: Virtual globes, i.e., geobrowsers that integrate multi-scale and temporal data from various sources and are based on a globe metaphor, have developed into serious tools that practitioners and various stakeholders in landscape and community planning have started using. Although these tools originate from Geographic Information Systems (GIS), they have become a different, potentially interactive and public tool set, with their own specific limitations and new opportunities. Expectations regarding their utility as planning and community engagement tools are high, but are tempered by both technical limitations and ethical issues [1,2]. Two grassroots campaigns and a collaborative visioning process, the Kimberley Climate Adaptation Project case study (British Columbia), illustrate and broaden our understanding of the potential benefits and limitations associated with the use of virtual globes in participatory planning initiatives. Based on observations, questionnaires and in-depth interviews with stakeholders and community members using an interactive 3D model of regional climate change vulnerabilities, potential impacts, and possible adaptation and mitigation scenarios in Kimberley, the benefits and limitations of virtual globes as a tool for participatory landscape planning are discussed. The findings suggest that virtual globes can facilitate access to geospatial information, raise awareness, and provide a more representative virtual landscape than static visualizations. However, landscape is not equally representative at all scales, and not all types of users seem to benefit equally from the tool. The risks of misinterpretation can be managed by integrating the application and interpretation of virtual globes into face-to-face planning processes.

Description: In order to be able to capture effects from co-transcriptional folding, we extend stochastic context-free grammars such that the probability of applying a rule can depend on the length of the subword that is eventually generated from the symbols introduced by the rule, and we show that existing algorithms for training and for determining the most probable parse tree can easily be adapted to the extended model without losses in performance. Furthermore, we show that the extended model is suited to improve the quality of predictions of RNA secondary structures. The extended model may also be applied to other fields where stochastic context-free grammars are used like natural language processing. Additionally some interesting questions in the field of formal languages arise from it.

Description: Radio Frequency Interference (RFI) detection and mitigation algorithms based on a signal’s spectrogram (frequency and time domain representation) are presented. The radiometric signal’s spectrogram is treated as an image, and therefore image processing techniques are applied to detect and mitigate RFI by two-dimensional filtering. A series of Monte-Carlo simulations have been performed to evaluate the performance of a simple thresholding algorithm and a modified two-dimensional Wiener filter.

Description: The smallest grammar problem—namely, finding a smallest context-free grammar that generates exactly one sequence—is of practical and theoretical importance in fields such as Kolmogorov complexity, data compression and pattern discovery. We propose a new perspective on this problem by splitting it into two tasks: (1) choosing which words will be the constituents of the grammar and (2) searching for the smallest grammar given this set of constituents. We show how to solve the second task in polynomial time parsing longer constituent with smaller ones. We propose new algorithms based on classical practical algorithms that use this optimization to find small grammars. Our algorithms consistently find smaller grammars on a classical benchmark reducing the size in 10% in some cases. Moreover, our formulation allows us to define interesting bounds on the number of small grammars and to empirically compare different grammars of small size.

Description: We propose a framework for the exact probabilistic analysis of window-based pattern matching algorithms, such as Boyer–Moore, Horspool, Backward DAWG Matching, Backward Oracle Matching, and more. In particular, we develop an algorithm that efficiently computes the distribution of a pattern matching algorithm’s running time cost (such as the number of text character accesses) for any given pattern in a random text model. Text models range from simple uniform models to higher-order Markov models or hidden Markov models (HMMs). Furthermore, we provide an algorithm to compute the exact distribution of differences in running time cost of two pattern matching algorithms. Methodologically, we use extensions of finite automata which we call deterministic arithmetic automata (DAAs) and probabilistic arithmetic automata (PAAs) [1]. Given an algorithm, a pattern, and a text model, a PAA is constructed from which the sought distributions can be derived using dynamic programming. To our knowledge, this is the first time that substring- or suffix-based pattern matching algorithms are analyzed exactly by computing the whole distribution of running time cost. Experimentally, we compare Horspool’s algorithm, Backward DAWG Matching, and Backward Oracle Matching on prototypical patterns of short length and provide statistics on the size of minimal DAAs for these computations.

Description: In an asynchronous data stream, the data items may be out of order with respect to their original timestamps. This paper studies the space complexity required by a data structure to maintain such a data stream so that it can approximate the set of frequent items over a sliding time window with sufficient accuracy. Prior to our work, the best solution is given by Cormode et al. [1], who gave an O (1/ε log W log (εB/ log W) min {log W, 1/ε} log |U|)- space data structure that can approximate the frequent items within an ε error bound, where W and B are parameters of the sliding window, and U is the set of all possible item names. We gave a more space-efficient data structure that only requires O (1/ε log W log (εB/ logW) log log W) space.

Description: Given a directed graph G with non-negative cost on the arcs, a directed tour cover T of G is a cycle (not necessarily simple) in G such that either head or tail (or both of them) of every arc in G is touched by T. The minimum directed tour cover problem (DToCP), which is to find a directed tour cover of minimum cost, is NP-hard. It is thus interesting to design approximation algorithms with performance guarantee to solve this problem. Although its undirected counterpart (ToCP) has been studied in recent years, in our knowledge, the DToCP remains widely open. In this paper, we give a 2 log2(n)-approximation algorithm for the DToCP.

Description: Two goodness-of-fit tests for copulas are being investigated. The first one deals with the case of elliptical copulas and the second one deals with independent copulas. These tests result from the expansion of the projection pursuit methodology that we will introduce in the present article. This method enables us to determine on which axis system these copulas lie as well as the exact value of these very copulas in the basis formed by the axes previously determined irrespective of their value in their canonical basis. Simulations are also presented as well as an application to real datasets.

Description: Techniques in image similarity can be used to improve the classification of breast cancer images. Breast cancer images in the mammogram modality have an abundance of non-cancerous structures that are similar to cancer, which make classification of images as containing cancer especially difficult to work with. Only the cancerous part of the image is relevant, so the techniques must learn to recognize cancer in noisy mammograms and extract features from that cancer to appropriately classify images. There are also many types or classes of cancer with different characteristics over which the system must work. Mammograms come in sets of four, two images of each breast, which enables comparison of the left and right breast images to help determine relevant features and remove irrelevant features. In this work, image feature clustering is done to reduce the noise and the feature space, and the results are used in a distance function that uses a learned threshold in order to produce a classification. The threshold parameter of the distance function is learned simultaneously with the underlying clustering and then integrated to produce an agglomeration that is relevant to the images. This technique can diagnose breast cancer more accurately than commercial systems and other published results.

Description: Several variants of the edit distance problem with block deletions are considered. Polynomial time optimal algorithms are presented for the edit distance with block deletions allowing character insertions and character moves, but without block moves. We show that the edit distance with block moves and block deletions is NP-complete (Nondeterministic Polynomial time problems in which any given solution to such problem can be verified in polynomial time, and any NP problem can be converted into it in polynomial time), and that it can be reduced to the problem of non-recursive block moves and block deletions within a constant factor.

Description: Increasingly encompassing models have been suggested for our world. Theories range from generally accepted to increasingly speculative to apparently bogus. The progression of theories from ego- to geo- to helio-centric models to universe and multiverse theories and beyond was accompanied by a dramatic increase in the sizes of the postulated worlds, with humans being expelled from their center to ever more remote and random locations. Rather than leading to a true theory of everything, this trend faces a turning point after which the predictive power of such theories decreases (actually to zero). Incorporating the location and other capacities of the observer into such theories avoids this problem and allows to distinguish meaningful from predictively meaningless theories. This also leads to a truly complete theory of everything consisting of a (conventional objective) theory of everything plus a (novel subjective) observer process. The observer localization is neither based on the controversial anthropic principle, nor has it anything to do with the quantum-mechanical observation process. The suggested principle is extended to more practical (partial, approximate, probabilistic, parametric) world models (rather than theories of everything). Finally, I provide a justification of Ockham’s razor, and criticize the anthropic principle, the doomsday argument, the no free lunch theorem, and the falsifiability dogma.

Description: We compare univariate L1 interpolating splines calculated on 5-point windows, on 7-point windows and on global data sets using four different spline functionals, namely, ones based on the second derivative, the first derivative, the function value and the antiderivative. Computational results indicate that second-derivative-based 5-point-window L1 splines preserve shape as well as or better than the other types of L1 splines. To calculate second-derivative-based 5-point-window L1 splines, we introduce an analysis-based, parallelizable algorithm. This algorithm is orders of magnitude faster than the previously widely used primal affine algorithm.

Description: Non-preemptive schedulers, despite their many discussed drawbacks, remain a very popular choice for practitioners of real-time and embedded systems. The non-preemptive ‘thrift’ cyclic scheduler—variations of which can be found in other application areas—has recently received considerable attention for the implementation of such embedded systems. A thrift scheduler provides a flexible and compact implementation model for periodic task sets with comparatively small overheads; additionally, it can overcome several of the problems associated with traditional ‘cyclic executives’. However, severe computational difficulties can still arise when designing schedules for non-trivial task sets. This paper is concerned with an optimization version of the offset-assignment problem, in which the objective is to assign task offsets such that the required CPU clock speed is minimized whilst ensuring that task overruns do not occur; it is known that the decision version of this problem is complete for Σ2p. The paper first considers the problemof candidate solution verification—itself strongly coNP-Complete—and a fast, exact algorithm for this problem is proposed; it is shown that for any fixed number of tasks, its execution time is polynomial. The paper then proposes two heuristic algorithms of pseudopolynomial complexity for solving the offset-assignment problem, and considers how redundant choices of offset combinations can be eliminated to help speed up the search. The performance of these algorithms is then experimentally evaluated, before conclusions are drawn.

Description: The Encyclopedia of Algorithms provides a comprehensive set of solutions to important algorithmic problems for students and researchers, including high-impact solutions from the most recent decade. [...]

Description: An adaptive mesh refinement strategy is proposed for local damage models that often arise from internal state variable based continuum damage models. The proposed algorithm employs both the finite element method and the finite difference method to integrate the equations of motion of a linear elastic material with simple isotropic microcracking. The challenges of this problem include the time integration of coupled partial differential equations with time-dependent coefficients, and the proper choice of solution spaces to yield a stable finite element formulation. Discontinuous elements are used for the representation of the damage field, as it is believed that this reduction in regularity is more consistent with the physical nature of evolving microcracking. The adaptive mesh refinement algorithm relies on custom refinement indicators, two of which are presented and compared. The two refinement indicators we explore are based on the time rate of change of the damage field and on the energy release rate, respectively, where the energy release rate measures the energy per unit volume available for damage to evolve. We observe the performance of the proposed algorithm and refinement indicators by comparing the predicted damage morphology on different meshes, hence judging the capability of the proposed technique to address, but not eliminate, the mesh dependency present in the solutions of the damage field.

Description: The symmetric-convolution multiplication (SCM) property of discrete trigonometric transforms (DTTs) based on unitary transform matrices is developed. Then as the reciprocity of this property, the novel multiplication symmetric-convolution (MSC) property of discrete trigonometric transforms, is developed.

Description: In geometric models with high-valence vertices, current subdivision wavelets may not deal with the special cases well for good visual effect of multiresolution surfaces. In this paper, we present the novel biorthogonal polar subdivision wavelets, which can efficiently perform wavelet analysis to the control nets with polar structures. The polar subdivision can generate more natural subdivision surfaces around the high-valence vertices and avoid the ripples and saddle points where Catmull-Clark subdivision may produce. Based on polar subdivision, our wavelet scheme supports special operations on the polar structures, especially suitable to models with many facets joining. For seamless fusing with Catmull-Clark subdivision wavelet, we construct the wavelets in circular and radial layers of polar structures, so can combine the subdivision wavelets smoothly for composite models formed by quadrilaterals and polar structures. The computations of wavelet analysis and synthesis are highly efficient and fully in-place. The experimental results have confirmed the stability of our proposed approach.

Description: The emergence of novel sensing elements, computing nodes, wireless communication and integration technology provides unprecedented possibilities for the design and application of intelligent systems. Each new application system must be designed from scratch, employing sophisticated methods ranging from conventional signal processing to computational intelligence. Currently, a significant part of this overall algorithmic chain of the computational system model still has to be assembled manually by experienced designers in a time and labor consuming process. In this research work, this challenge is picked up and a methodology and algorithms for automated design of intelligent integrated and resource-aware multi-sensor systems employing multi-objective evolutionary computation are introduced. The proposed methodology tackles the challenge of rapid-prototyping of such systems under realization constraints and, additionally, includes features of system instance specific self-correction for sustained operation of a large volume and in a dynamically changing environment. The extension of these concepts to the reconfigurable hardware platform renders so called self-x sensor systems, which stands, e.g., for self-monitoring, -calibrating, -trimming, and -repairing/-healing systems. Selected experimental results prove the applicability and effectiveness of our proposed methodology and emerging tool. By our approach, competitive results were achieved with regard to classification accuracy, flexibility, and design speed under additional design constraints.

Description: With the aim of classifying sperm whales, this report compares two methods that can use Gaussian functions, a radial basis function network, and support vector machines which were trained with two different approaches known as C-SVM and ν-SVM. The methods were tested on data recordings from seven different male sperm whales, six containing single click trains and the seventh containing a complete dive. Both types of classifiers could distinguish between the clicks of the seven different whales, but the SVM seemed to have better generalisation towards unknown data, at the cost of needing more information and slower performance.

Description: We consider the problem of all-to-one selfish routing in the absence of a payment scheme in wireless sensor networks, where a natural model for cost is the power required to forward, referring to the resulting game as a Locally Minimum Cost Forwarding (LMCF). Our objective is to characterize equilibria and their global costs in terms of stretch and diameter, in particular finding incentive compatible algorithms that are also close to globally optimal. We find that although social costs for equilibria of LMCF exhibit arbitrarily bad worst-case bounds and computational infeasibility of reaching optimal equilibria, there exist greedy and local incentive compatible heuristics achieving near-optimal global costs.

Description: A compressed full-text self-index for a text T is a data structure requiring reduced space and able to search for patterns P in T. It can also reproduce any substring of T, thus actually replacing T. Despite the recent explosion of interest on compressed indexes, there has not been much progress on functionalities beyond the basic exact search. In this paper we focus on indexed approximate string matching (ASM), which is of great interest, say, in bioinformatics. We study ASM algorithms for Lempel-Ziv compressed indexes and for compressed suffix trees/arrays. Most compressed self-indexes belong to one of these classes. We start by adapting the classical method of partitioning into exact search to self-indexes, and optimize it over a representative of either class of self-index. Then, we show that a Lempel- Ziv index can be seen as an extension of the classical q-samples index. We give new insights on this type of index, which can be of independent interest, and then apply them to a Lempel- Ziv index. Finally, we improve hierarchical verification, a successful technique for sequential searching, so as to extend the matches of pattern pieces to the left or right. Most compressed suffix trees/arrays support the required bidirectionality, thus enabling the implementation of the improved technique. In turn, the improved verification largely reduces the accesses to the text, which are expensive in self-indexes. We show experimentally that our algorithms are competitive and provide useful space-time tradeoffs compared to classical indexes.

Description: We consider a pursuit-evasion problem where some lions have the task to clear a grid graph whose nodes are initially contaminated. The contamination spreads one step per time unit in each direction not blocked by a lion. A vertex is cleared from its contamination whenever a lion moves to it. Brass et al. [5] showed that n/2 lions are not enough to clear the n x n-grid. In this paper, we consider the same problem in dimension d 〉 2 and prove that Θ(nd-1/√d) lions are necessary and sufficient to clear the nd-grid. Furthermore, we analyze a problem variant where the lions are also allowed to jump from grid vertices to non-adjacent grid vertices.

Description: The fluorescence properties of tryptophan residues are sensitive to the microenvironment of fluorophores in proteins. Therefore, fluorescence characteristics are widely used to study structural transitions in proteins. However, the decoding of the structural information from spectroscopic data is challenging. Here we present a review of approaches developed for the decomposition of multi-component protein tryptophan fluorescence spectra and correlation of these spectral parameters with protein structural properties.

Description: Online OVSF code assignment has an important application to wireless communications. Recently, this problem was formally modeled as an online problem, and performances of online algorithms have been analyzed by the competitive analysis. The previous best upper and lower bounds on the competitive ratio were 10 and 5/3, respectively. In this paper, we improve them to 7 and 2, respectively. We also show that our analysis for the upper bound is tight by giving an input sequence for which the competitive ratio of our algorithm is 7 ― ε for an arbitrary constant ε 〉 0.

Description: This paper reviews the basics and recent researches of computer-aided diagnosis (CAD) systems for assisting neuroradiologists in detection of brain diseases, e.g., asymptomatic unruptured aneurysms, Alzheimer's disease, vascular dementia, and multiple sclerosis (MS), in magnetic resonance (MR) images. The CAD systems consist of image feature extraction based on image processing techniques and machine learning classifiers such as linear discriminant analysis, artificial neural networks, and support vector machines. We introduce useful examples of the CAD systems in the neuroradiology, and conclude with possibilities in the future of the CAD systems for brain diseases in MR images.

Description: Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other networks such as radial basis function, recurrent network, feedback network, and unsupervised Kohonen self-organizing network. These networks, especially the multilayer perceptron network with a backpropagation training algorithm, have gained recognition in research and applications in various scientific and engineering areas. In order to accelerate the training process and overcome data over-fitting, research has been conducted to improve the backpropagation algorithm. Further, artificial neural networks have been integrated with other advanced methods such as fuzzy logic and wavelet analysis, to enhance the ability of data interpretation and modeling and to avoid subjectivity in the operation of the training algorithm. In recent years, support vector machines have emerged as a set of high-performance supervised generalized linear classifiers in parallel with artificial neural networks. A review on development history of artificial neural networks is presented and the standard architectures and algorithms of artificial neural networks are described. Furthermore, advanced artificial neural networks will be introduced with support vector machines, and limitations of ANNs will be identified. The future of artificial neural network development in tandem with support vector machines will be discussed in conjunction with further applications to food science and engineering, soil and water relationship for crop management, and decision support for precision agriculture. Along with the network structures and training algorithms, the applications of artificial neural networks will be reviewed as well, especially in the fields of agricultural and biological engineering.

Description: We present a coupled finite element, Kalman filter approach to foresee impactinduced delamination of layered composites when mechanical properties are partially unknown. Since direct numerical simulations, which require all the constitutive parameters to be assigned, cannot be run in such cases, an inverse problem is formulated to allow for modeling as well as constitutive uncertainties. Upon space discretization through finite elements and time integration through the explicit ®¡method, the resulting nonlinear stochastic state model, wherein nonlinearities are due to delamination growth, is attacked with sigma-point Kalman filtering. Comparison with experimental data available in the literature and concerning inter-laminar failure of layered composites subject to low-velocity impacts, shows that the proposed procedure leads to: an accurate description of the failure mode; converged estimates of inter-laminar strength and toughness in good agreement with experimental data.

Description: The proportional integral controller, commonly used in engineering applications for process control, has been implemented for the tuning of the stepsizes in Metropolis Monte Carlo simulations. Similarly to the recent application for tuning the chemical potential parameter in grand-canonical ensemble simulation, the process-control approach was found to work well for the problem of selecting the stepsize for each torsion angle that results in a targeted acceptance rate during the simulation of an octapeptide in aqueous environment.

Description: Wireless sensor networks (WSN) have attracted much attention in recent years for its unique characteristics and wide use in many different applications. Routing protocol is one of key technologies in WSN. In this paper, the position-based routing protocols are surveyed and classified into four categories: flooding-based, curve-based, grid-based and ant algorithm-based intelligent. To each category, the main contribution of related routing protocols is shown including the relationship among the routing protocols. The different routing algorithms in the same category and the different categories are compared based on popular metrics. Moreover, some open research directions in WSN are also discussed.

Description: In this study different approaches based on multilayer perceptron neural networks are proposed and evaluated with the aim to retrieve tropospheric profiles by using GPS radio occultation data. We employed a data set of 445 occultations covering the land surface within the Tropics, split into desert and vegetation zone. The neural networks were trained with refractivity profiles as input computed from geometrical occultation parameters provided by the FORMOSAT-3/COSMIC satellites, while the targets were the dry and wet refractivity profiles and the dry pressure profiles obtained from the contemporary European Centre for Medium-Range Weather Forecast data. Such a new retrieval algorithm was chosen to solve the atmospheric profiling problem without the constraint of an independent knowledge of one atmospheric parameter at each GPS occultation.

Description: This paper presents a method for self-organization of the distributed systems operating in a dynamic context. We propose the use of a simple biologically (cognitive neuroscience) inspired method for system configuration that allows allocating most of the computational load to off-line in order to improve the scalability property of the system. The method proposed has less computational burden at runtime than traditional system adaptation approaches.

Description: The research project “Grassroots GIS” focuses on the development of low-cost mapping and publishing methods for slums and slum-upgrading projects in Manila. In this project smartphones, collaborative mapping and 3D visualization applications are systematically employed to support landscape architectural analysis and design work in the context of urban poverty and urban informal settlements. In this paper we focus on the description of the developed methods and present preliminary results of this work-in-progress.

Description: For fixed k ≥ 2 and fixed data alphabet of cardinality m, the hierarchical type class of a data string of length n = kj for some j ≥ 1 is formed by permuting the string in all possible ways under permutations arising from the isomorphisms of the unique finite rooted tree of depth j which has n leaves and k children for each non-leaf vertex. Suppose the data strings in a hierarchical type class are losslessly encoded via binary codewords of minimal length. A hierarchical entropy function is a function on the set of m-dimensional probability distributions which describes the asymptotic compression rate performance of this lossless encoding scheme as the data length n is allowed to grow without bound. We determine infinitely many hierarchical entropy functions which are each self-affine. For each such function, an explicit iterated function system is found such that the graph of the function is the attractor of the system.

Description: This article presents a comparison of main characteristics of the Next Generation Networks (NGN) and Future Generation Internet (FGI). The aim is to discuss and compare two approaches to Future Networks (FN) and services: the evolution of NGN, and the revolutionary approach of a new FGI. We present both frameworks from the services point of view as they are delivered to the end-user, as well as from the architectural point of view. We compare selected properties of both approaches to explain commonalities and differences. Their challenges are similar: managing the quality of experience, mobility, security, scalability and providing openness to applications. Based on this comparison, we evaluate possible areas for future convergence in the approach of the two architectures to the Future Network concept. Our analysis shows that despite their different backgrounds, the internet’s FGI and telco’s NGN are not that different after all. The convergence of the two approaches therefore seems the only logical way forward.

Description: In this article, a security extension for the HiiMap Next Generation Internet Architecture is presented. We regard a public key infrastructure which is integrated into the mapping infrastructure of the locator/identifier-split addressing scheme. The security approach is based on Threshold Cryptography which enables a sharing of keys among the mapping servers. Hence, a more trustworthy and fair approach for a Next Generation Internet Architecture as compared to the state of the art approach is fostered. Additionally, we give an evaluation based on IETF AAA recommendations for security-related systems.

Description: Enterprises are now connected internally and externally to other Enterprises via the Internet in ways that are increasingly difficult to manage, especially as these interconnections become more dynamic. Current methods of coordinating the effects of change as they propagate through these networks of connections are not likely to scale. What is needed is a new paradigm for how the Internet supports such coordination. Indeed, the Internet should and could provide fundamental coordination functions that are missing today. In this paper, we describe how such a “Coordinated Internet” would work (this paper is an expanded version of [1]). The key functionality of a Coordinated Internet would be that the Internet actively watches what people do (analogous to search completion on desktops today), correlates these activities, and actively notifies people when and how their current tasks affect and are affected by the activities of other people. This would be accomplished by standard coordination functions implemented as a common Internet layer that can be used as a utility by more specialized applications. Such a Coordinated Internet would revolutionize enterprise management, for all enterprises, large and small, corporate and personal. For example, static workflows would become obsolete for all but the the most routine processes. Some solutions provide existence proofs of such a coordination substrate, such as the Redux solution in concurrent engineering, which we describe herein. However, foundational research remains to be done in the new field of Coordination Engineering in order to reach the goal of a future Internet in which coordination functions are fundamental.

Description: Networks are evolving toward a ubiquitous model in which heterogeneous devices are interconnected. Cryptographic algorithms are required for developing security solutions that protect network activity. However, the computational and energy limitations of network devices jeopardize the actual implementation of such mechanisms. In this paper, we perform a wide analysis on the expenses of launching symmetric and asymmetric cryptographic algorithms, hash chain functions, elliptic curves cryptography and pairing based cryptography on personal agendas, and compare them with the costs of basic operating system functions. Results show that although cryptographic power costs are high and such operations shall be restricted in time, they are not the main limiting factor of the autonomy of a device.

Description: This paper analyzes how recommender systems can be applied to current e-learning systems to guide learners in personalized inclusive e-learning scenarios. Recommendations can be used to overcome current limitations of learning management systems in providing personalization and accessibility features. Recommenders can take advantage of standards-based solutions to provide inclusive support. To this end we have identified the need for developing semantic educational recommender systems, which are able to extend existing learning management systems with adaptive navigation support. In this paper we present three requirements to be considered in developing these semantic educational recommender systems, which are in line with the service-oriented approach of the third generation of learning management systems, namely: (i) a recommendation model; (ii) an open standards-based service-oriented architecture; and (iii) a usable and accessible graphical user interface to deliver the recommendations.

Description: This study assesses differences within the African American population with respect to internet activity. Using survey data, we find wide variations within the population. While some segments of African Americans are indeed less likely to perform certain activities on the internet, we note that certain segments of the African American population are reporting more internet activity than other racial groups. These ‘haves’ score high not just in comparison to their African American peers, but to the US American population as a whole. We suggest a move away from the digital divide/digital inequality models and a move towards thinking of greater or lesser Information and Communication Technology (ICT) usage as conditioned by the instrumental needs of population groups. We term this a digital practice model.

Description: The problem of compressed pattern matching, which has recently been treated in many papers dealing with free text, is extended to structured files, specifically to dictionaries, which appear in any full-text retrieval system. The prefix-omission method is combined with Huffman coding and a new variant based on Fibonacci codes is presented. Experimental results suggest that the new methods are often preferable to earlier ones, in particular for small files which are typical for dictionaries, since these are usually kept in small chunks.

Description: Generalized least squares (GLS) for model parameter estimation has a long and successful history dating to its development by Gauss in 1795. Alternatives can outperform GLS in some settings, and alternatives to GLS are sometimes sought when GLS exhibits curious behavior, such as in Peelle’s Pertinent Puzzle (PPP). PPP was described in 1987 in the context of estimating fundamental parameters that arise in nuclear interaction experiments. In PPP, GLS estimates fell outside the range of the data, eliciting concerns that GLS was somehow flawed. These concerns have led to suggested alternatives to GLS estimators. This paper defends GLS in the PPP context, investigates when PPP can occur, illustrates when PPP can be beneficial for parameter estimation, reviews optimality properties of GLS estimators, and gives an example in which PPP does occur.

Description: We present a car traffic simulation prototype for complex networks, that is formed by a collection of roads and junctions. Traffic load evolution is described by a model based on fluid dynamic conservation laws, deduced from conservation of the number of cars. The model contains some additional hypothesis in order to reproduce specific car traffic features such as route based car distribution at nodes and the presence of right-of-way at the crossroads. A complete implementation of this model is then presented, together with computational results on case studies.

Description: Several measurements are used to describe the behavior of a diabetic patient’s blood glucose. We describe a new, wavelet-based algorithm that indicates a new measurement called a PLA index could be used to quantify the variability or predictability of blood glucose. This wavelet-based approach emphasizes the shape of a blood glucose graph. Using continuous glucose monitors (CGMs), this measurement could become a new tool to classify patients based on their blood glucose behavior and may become a new method in the management of diabetes.

Description: Chris Langton proposed a model of an artificial life that he named “ant”: an agent- called ant- that is over a square of a grid moves by turning to the left (or right) accordingly to black (or white) color of the square where it is heading, and the square then reverses its color. Bunimovich and Troubetzkoy proved that an ant’s trajectory is always unbounded, or equivalently, there exists no repeatable configuration of the ant’s system. On the other hand, by introducing a new type of color where the ant goes straight ahead and the color never changes, repeatable configurations are known to exist. In this paper, we prove that determining whether a given finite configuration of generalized Langton’s ant is repeatable or not is PSPACE-hard. We also prove the PSPACE-hardness of the ant’s problem on a hexagonal grid.

Description: Specialized intelligent systems can be found everywhere: finger print, handwriting, speech, and face recognition, spam filtering, chess and other game programs, robots, et al. This decade the first presumably complete mathematical theory of artificial intelligence based on universal induction-prediction-decision-action has been proposed. This informationtheoretic approach solidifies the foundations of inductive inference and artificial intelligence. Getting the foundations right usually marks a significant progress and maturing of a field. The theory provides a gold standard and guidance for researchers working on intelligent algorithms. The roots of universal induction have been laid exactly half-a-century ago and the roots of universal intelligence exactly one decade ago. So it is timely to take stock of what has been achieved and what remains to be done. Since there are already good recent surveys, I describe the state-of-the-art only in passing and refer the reader to the literature. This article concentrates on the open problems in universal induction and its extension to universal intelligence.

Description: Basics of Bayesian statistics in inverse problems using the maximum entropy principle are summarized in connection with the restoration of positive, additive images from various types of data like X-ray digital mammograms. An efficient iterative algorithm for image restoration from large data sets based on the conjugate gradient method and Lagrange multipliers in nonlinear optimization of a specific potential function was developed. The point spread function of the imaging system was determined by numerical simulations of inhomogeneous breast-like tissue with microcalcification inclusions of various opacities. The processed digital and digitized mammograms resulted superior in comparison with their raw counterparts in terms of contrast, resolution, noise, and visibility of details.

Description: Within the framework of multifield continua, we move from the model of elastic microcracked body introduced in (Mariano, P.M. and Stazi, F.L., Strain localization in elastic microcracked bodies, Comp. Methods Appl. Mech. Engrg. 2001, 190, 5657–5677) and propose a few novel variational formulations of mixed type along with relevant mixed FEM discretizations. To this goal, suitably extended Hellinger-Reissner principles of primal and dual type are derived. A few numerical studies are presented that include an investigation on the interaction between a single cohesive macrocrack and diffuse microcracks (Mariano, P.M. and Stazi, F.L., Strain localization due to crack–microcrack interactions: X–FEM for a multifield approach, Comp. Methods Appl. Mech. Engrg. 2004, 193, 5035–5062).

Description: Greenhouse-grown butter lettuce (Lactuca sativa L.) can potentially be stored for 21 days at constant 0°C. When storage temperature was increased to 5°C or 10°C, shelf life was shortened to 14 or 10 days, respectively, in our previous observations. Also, commercial shelf life of 7 to 10 days is common, due to postharvest temperature fluctuations. The objective of this study was to establish neural network (NN) models to predict the remaining shelf life (RSL) under fluctuating postharvest temperatures. A box of 12 - 24 lettuce heads constituted a sample unit. The end of the shelf life of each head was determined when it showed initial signs of decay or yellowing. Air temperatures inside a shipping box were recorded. Daily average temperatures in storage and averaged shelf life of each box were used as inputs, and the RSL was modeled as an output. An R2 of 0.57 could be observed when a simple NN structure was employed. Since the "future" (or remaining) storage temperatures were unavailable at the time of making a prediction, a second NN model was introduced to accommodate a range of future temperatures and associated shelf lives. Using such 2-stage NN models, an R2 of 0.61 could be achieved for predicting RSL. This study indicated that NN modeling has potential for cold chain quality control and shelf life prediction.

Description: The discovery of gene regulatory elements requires the synergism between computational and experimental techniques in order to reveal the underlying regulatory mechanisms that drive gene expression in response to external cues and signals. Utilizing the large amount of high-throughput experimental data, constantly growing in recent years, researchers have attempted to decipher the patterns which are hidden in the genomic sequences. These patterns, called motifs, are potential binding sites to transcription factors which are hypothesized to be the main regulators of the transcription process. Consequently, precise detection of these elements is required and thus a large number of computational approaches have been developed to support the de novo identification of TFBSs. Even though novel approaches are continuously proposed and almost all have reported some success in yeast and other lower organisms, in higher organisms the problem still remains a challenge. In this paper, we therefore review the recent developments in computational methods for transcription factor binding site prediction. We start with a brief review of the basic approaches for binding site representation and promoter identification, then discuss the techniques to locate physical TFBSs, identify functional binding sites using orthologous information, and infer functional TFBSs within some context defined by additional prior knowledge. Finally, we briefly explore the opportunities for expanding these approaches towards the computational identification of transcriptional regulatory networks.

Description: An algorithm for the suppression of the radiation and scattering fields created by vibration of the smooth closed surface of a body of arbitrary shape placed in a liquid is designed and analytically explored. The frequency range of the suppression allows for both large and small wave sizes on the protected surface. An active control system is designed that consists of: (a) a subsystem for fast formation of a desired distribution of normal oscillatory velocities or displacements (on the basis of pulsed Huygens' sources) and (b) a subsystem for catching and targeting of incident waves on the basis of a grid (one layer) of monopole microphones, surrounding the surface to be protected. The efficiency and stability of the control algorithm are considered. The algorithm forms the control signal during a time much smaller than the minimum time scale of the waves to be damped. The control algorithm includes logical and nonlinear operations, thus excluding interpretation of the control system as a traditional combination of linear electric circuits, where all parameters are constant (in time). This algorithm converts some physical body placed in a liquid into one that is transparent to a special class of incident waves. The active control system needs accurate information on its geometry, but does not need either prior or current information about the vibroacoustical characteristics of the protected surface, which in practical cases represents a vast amount of data.

Description: The proposed Autonomous Stress Indicator (ASI) is a device that monitors the contents of the protection relays on a suspect weak power system bus and generates a performance level related to the degree of system performance degradation or instability. This gives the system operators some time (minutes) to take corrective action. In a given operating area there would not likely be a need for an ASI on every bus. Note that the ASI does not trip any breakers; it is an INFORMATION ONLY device. An important feature is that the system operator can subsequently interrogate the ASI to determine the factor(s) that led to the performance level that has been initially annunciated, thereby leading to a course of action. This paper traces the development of the ASI which is an ongoing project. The ASI could be also described as a stress-alert device whose function is to alert the System Operator of a stressful condition at its location. The characteristics (or essential qualities) of this device are autonomy, selectivity, accuracy and intelligence. These will fulfill the requirements of the recommendation of the Canada –US Task Force in the August 2003 system collapse. Preliminary tests on the IEEE 39-bus model indicate that the concept has merit and development work is in progress. While the ASI can be applied to all power system operating conditions, its principal application is to the degraded state of the system where the System Operator must act to restore the system to the secure state before it migrates to a stage of collapse. The work of ASI actually begins with the Areas of Vulnerability and ends with the Predictive Module as described in detail in this paper. An application example of a degraded system using the IEEE 39-bus system is included.

Description: The algorithm here described concerns generation, visualization, and modification of molecular nanostructures of single-walled nanotubes (NTs) of particular configurations (armchair, zipper, multiple zipper, zigzag, or chiral) by means of a Graphical User Interface (GUI). NTs are made from a carbon graphene sheet created according to certain parameters defining required nanostructures. Generated NTs can easily be modified by replacing carbon atoms for nitrogen or boron, visualized and exported into a standard format useful as input to be analyzed and submitted to other applications in order to get optimized geometries and to carry out further calculations of molecular and electronic properties.

Description: We consider grammar-based text compression with longest first substitution (LFS), where non-overlapping occurrences of a longest repeating factor of the input text are replaced by a new non-terminal symbol. We present the first linear-time algorithm for LFS. Our algorithm employs a new data structure called sparse lazy suffix trees. We also deal with a more sophisticated version of LFS, called LFS2, that allows better compression. The first linear-time algorithm for LFS2 is also presented.

Description: Recently a Delaunay refinement algorithm has been proposed that can mesh piecewise smooth complexes which include polyhedra, smooth and piecewise smooth surfaces, and non-manifolds. However, this algorithm employs domain dependent numerical predicates, some of which could be computationally expensive and hard to implement. In this paper we develop a refinement strategy that eliminates these complicated domain dependent predicates. As a result we obtain a meshing algorithm that is practical and implementation-friendly.

Description: The performance of microwave radiometers can be seriously degraded by the presence of radio-frequency interference (RFI). Spurious signals and harmonics from lower frequency bands, spread-spectrum signals overlapping the “protected” band of operation, or out-of-band emissions not properly rejected by the pre-detection filters due to the finite rejection modify the detected power and the estimated antenna temperature from which the geophysical parameters will be retrieved. In recent years, techniques to detect the presence of RFI have been developed. They include time- and/or frequency domain analyses, or statistical analysis of the received signal which, in the absence of RFI, must be a zero-mean Gaussian process. Current mitigation techniques are mostly based on blanking in the time and/or frequency domains where RFI has been detected. However, in some geographical areas, RFI is so persistent in time that is not possible to acquire RFI-free radiometric data. In other applications such as sea surface salinity retrieval, where the sensitivity of the brightness temperature to salinity is weak, small amounts of RFI are also very difficult to detect and mitigate. In this work a wavelet-based technique is proposed to mitigate RFI (cancel RFI as much as possible). The interfering signal is estimated by using the powerful denoising capabilities of the wavelet transform. The estimated RFI signal is then subtracted from the received signal and a “cleaned” noise signal is obtained, from which the power is estimated later. The algorithm performance as a function of the threshold type, and the threshold selection method, the decomposition level, the wavelet type and the interferenceto-noise ratio is presented. Computational requirements are evaluated in terms of quantization levels, number of operations, memory requirements (sequence length). Even though they are high for today’s technology, the algorithms presented can be applied to recorded data. The results show that even RFI much larger than the noise signal can be very effectively mitigated, well below the noise level.

Description: The goal of this study was to develop a computer-aided therapeutic response (CADrx) system for early prediction of drug treatment response for glioblastoma multiforme (GBM) brain tumors with diffusion weighted (DW) MR images. In conventional Macdonald assessment, tumor response is assessed nine weeks or more post-treatment. However, we will investigate the ability of DW-MRI to assess response earlier, at five weeks post treatment. The apparent diffusion coefficient (ADC) map, calculated from DW images, has been shown to reveal changes in the tumor’s microenvironment preceding morphologic tumor changes. ADC values in treated brain tumors could theoretically both increase due to the cell kill (and thus reduced cell density) and decrease due to inhibition of edema. In this study, we investigated the effectiveness of features that quantify changes from pre- and post-treatment tumor ADC histograms to detect treatment response. There are three parts to this study: first, tumor regions were segmented on T1w contrast enhanced images by Otsu’s thresholding method, and mapped from T1w images onto ADC images by a 3D region of interest (ROI) mapping tool using DICOM header information; second, ADC histograms of the tumor region were extracted from both pre- and five weeks post-treatment scans, and fitted by a two-component Gaussian mixture model (GMM). The GMM features as well as standard histogram-based features were extracted. Finally, supervised machine learning techniques were applied for classification of responders or non-responders. The approach was evaluated with a dataset of 85 patients with GBM under chemotherapy, in which 39 responded and 46 did not, based on tumor volume reduction. We compared adaBoost, random forest and support vector machine classification algorithms, using ten-fold cross validation, resulting in the best accuracy of 69.41% and the corresponding area under the curve (Az) of 0.70.

Description: A general review of the extended finite element method and its application to the simulation of first-order phase transitions is provided. Detailed numerical investigations are then performed by focusing on the one-dimensional case and studying: (i) spatial and temporal discretisations, (ii) different numerical techniques for the interface-condition enforcement, and (iii) different treatments for the blending elements. An embeddeddiscontinuity finite element approach is also developed and compared with the extended finite element method, so that a clearer insight of the latter can be given. Numerical examples for melting/solidification in planar, cylindrical, and spherical symmetry are presented and the results are compared with analytical solutions.

Description: Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks.

Description: Spatial registration of multidate or multisensorial images is required for many applications in remote sensing. Automatic image registration, which has been extensively studied in other areas of image processing, is still a complex problem in the framework of remote sensing. In this work we explore an alternative strategy for a fully automatic and operational registration system capable of registering multitemporal and multisensorial remote sensing satellite images with high accuracy and avoiding the use of ground control points, exploiting the maximum reliable information in both images (coastlines not occluded by clouds), which have been coarsely geometrically corrected only using an orbital prediction model. The automatic feature-based approach is summarized as follows: i) Reference image coastline extraction; ii) Sensed image gradient energy map estimation and iii) Contour matching, mapping function estimation and transformation of the sensed images. Several experimental results for single sensor imagery (AVHRR/3) and multisensorial imagery (AVHRR/3-SeaWiFS-MODIS-ATSR) from different viewpoints and dates have verified the robustness and accuracy of the proposed automatic registration algorithm, demonstrating its capability of registering satellite images of coastal areas within one pixel.

Description: The Web Graph is a large-scale graph that does not fit in main memory, so that lossless compression methods have been proposed for it. This paper introduces a compression scheme that combines efficient storage with fast retrieval for the information in a node. The scheme exploits the properties of the Web Graph without assuming an ordering of the URLs, so that it may be applied to more general graphs. Tests on some datasets of use achieve space savings of about 10% over existing methods.

Description: Wireless sensor networks are a relatively new area where technology is developing fast and are used to solve a great diversity of problems that range from museums’ security to wildlife protection. The geometric optimisation problem solved in this paper is aimed at minimising the sensors’ range so that every point on a polygonal region R is within the range of at least two sensors. Moreover, it is also shown how to minimise the sensors’ range to assure the existence of a path within R that stays as close to two sensors as possible.

Description: The automated approximation of solutions to differential equations which involve discontinuities across evolving surfaces is addressed. Finite element technology has developed to the point where it is now possible to model evolving discontinuities independently of the underlying mesh, which is particularly useful in simulating failure of solids. However, the approach remains tedious to program, particularly in the case of coupled problems where a variety of finite element bases are employed and where a mixture of continuous and discontinuous fields may be used. We tackle this point by exploring the scope for employing automated code generation techniques for modelling discontinuities. Function spaces and variational forms are defined in a language that resembles mathematical notation, and computer code for modelling discontinuities is automatically generated. Principles underlying the approach are elucidated and a number of two- and three-dimensional examples for different equations are presented.

Description: A cascade correlation learning architecture has been devised for the first time for radial basis function processing units. The proposed algorithm was evaluated with two synthetic data sets and two chemical data sets by comparison with six other standard classifiers. The ability to detect a novel class and an imbalanced class were demonstrated with synthetic data. In the chemical data sets, the growth regions of Italian olive oils were identified by their fatty acid profiles; mass spectra of polychlorobiphenyl compounds were classified by chlorine number. The prediction results by bootstrap Latin partition indicate that the proposed neural network is useful for pattern recognition.

Description: Calls from 14 species of bat were classified to genus and species using discriminant function analysis (DFA), support vector machines (SVM) and ensembles of neural networks (ENN). Both SVMs and ENNs outperformed DFA for every species while ENNs (mean identification rate – 97%) consistently outperformed SVMs (mean identification rate – 87%). Correct classification rates produced by the ENNs varied from 91% to 100%; calls from six species were correctly identified with 100% accuracy. Calls from the five species of Myotis, a genus whose species are considered difficult to distinguish acoustically, had correct identification rates that varied from 91 – 100%. Five parameters were most important for classifying calls correctly while seven others contributed little to classification performance.

Description: Considerable importance in molecular biophysics is attached to influencing by mutagenesis the specific properties of a protein family. The working hypothesis is that mutating residues at few selected positions can affect specificity. Statistical analysis of homologue sequences can identify putative specificity determining positions (SDPs) and help to shed some light on the peculiarities underlying their functional role. In this work, we present an approach to identify such positions inspired by state of the art mutual information-based SDP prediction methods. The algorithm based on this approach provides a systematic procedure to point at the relevant physical characteristics of putative SPDs and can investigate the effects of correlated mutations. The method is tested on two standard benchmarks in the field and further validated in the context of a biologically interesting problem: the multimerization of the Intrinsically Fluorescent Proteins (IFP).

Description: The theoretical Quantum Key-Distribution scheme of Bennett and Brassard (BB84) has been proven secure against very strong attacks including the collective attacks and the joint attacks. Though the latter are the most general attacks, collective attacks are much easier to analyze, yet, they are conjectured to be as informative to the eavesdropper. Thus, collective attacks are likely to be useful in the analysis of many theoretical and practical schemes that are still lacking a proof of security, including practical BB84 schemes. We show how powerful tools developed in previous works for proving security against the joint attack, are simplified when applied to the security of BB84 against collective attacks whilst providing the same bounds on leaked information and the same error threshold.

Description: This paper presents an adaptive PSO algorithm whose numerical parameters can be updated following a scheduled protocol respecting some known criteria of convergence in order to enhance the chances to reach the global optimum of a hard combinatorial optimization problem, such those encountered in global optimization problems of composite laminates. Some examples concerning hard design problems are provided, showing the effectiveness of the approach.

Description: An image tracking algorithm, which was originally used with the particle image velocimetry (PIV) to determine velocities of buoyant solid particles in water, is modified and applied in the presented work to detect motion of fire ant on a planar surface. A group of fire ant workers are put to the bottom of a tub and excited with vibration of selected frequency and intensity. The moving fire ants are captured with an image system that successively acquires image frames of high digital resolution. The background noise in the imaging recordings is extracted by averaging hundreds of frames and removed from each frame. The individual fire ant images are identified with a recursive digital filter, and then they are tracked between frames according to the size, brightness, shape, and orientation angle of the ant image. The speed of an individual ant is determined with the displacement of its images and the time interval between frames. The trail of the individual fire ant is determined with the image tracking results, and a statistical analysis is conducted for all the fire ants in the group. The purpose of the experiment is to investigate the response of fire ants to the substrate vibration. Test results indicate that the fire ants move faster after being excited, but the number of active ones are not increased even after a strong excitation.

Description: Complexity of failure is reflected from sensitivity of strength to small defects and wide scatter of macroscopic behaviors. In engineering practices, spatial information of materials at fine scales can only be partially measurable. Random field (RF) models are important to address the uncertainty in spatial distribution. To transform a RF of micro-cracks into failure probability at full structural-scale crossing a number of length scales, the operator representing physics laws need be implemented in a multiscale framework, and to be realized in a stochastic setting. Multiscale stochastic modeling of materials is emerging as a new methodology at this research frontier, which provides a new multiscale thinking by upscaling fine-scale RFs. In this study, a preliminary framework of probabilistic upscaling is presented for bottom-up hierarchical modeling of failure propagation across micro-meso-macro scales. In the micro-to-meso process, the strength of stochastic representative volume element (SRVE) is probabilistically assessed by using a lattice model. A mixed Weibull-Gaussian distribution is proposed to characterize the statistical strength of SRVE, which can be used as input for the subsequent meso-to-macro upscaling process using smeared crack finite element analysis.

Description: As the rapid advance of digital imaging technologies, the content-based image retrieval (CBIR) has became one of the most vivid research areas in computer vision. In the last several years, developing computer-aided detection and/or diagnosis (CAD) schemes that use CBIR to search for the clinically relevant and visually similar medical images (or regions) depicting suspicious lesions has also been attracting research interest. CBIR-based CAD schemes have potential to provide radiologists with “visual aid” and increase their confidence in accepting CAD-cued results in the decision making. The CAD performance and reliability depends on a number of factors including the optimization of lesion segmentation, feature selection, reference database size, computational efficiency, and relationship between the clinical relevance and visual similarity of the CAD results. By presenting and comparing a number of approaches commonly used in previous studies, this article identifies and discusses the optimal approaches in developing CBIR-based CAD schemes and assessing their performance. Although preliminary studies have suggested that using CBIR-based CAD schemes might improve radiologists’ performance and/or increase their confidence in the decision making, this technology is still in the early development stage. Much research work is needed before the CBIR-based CAD schemes can be accepted in the clinical practice.

Description: Functional mapping of dynamic traits measured in a longitudinal study was originally derived within the maximum likelihood (ML) context and implemented with the EM algorithm. Although ML-based functional mapping possesses many favorable statistical properties in parameter estimation, it may be computationally intractable for analyzing longitudinal data with high dimensions and high measurement errors. In this article, we derive a general functional mapping framework for quantitative trait locus mapping of dynamic traits within the Bayesian paradigm. Markov chain Monte Carlo techniques were implemented for functional mapping to estimate biologically and statistically sensible parameters that model the structures of time-dependent genetic effects and covariance matrix. The Bayesian approach is useful to handle difficulties in constructing confidence intervals as well as the identifiability problem, enhancing the statistical inference of functional mapping. We have undertaken simulation studies to investigate the statistical behavior of Bayesian-based functional mapping and used a real example with F2 mice to validate the utilization and usefulness of the model.

Description: Although the electrolarynx (EL) provides an important means of voice reconstruction for patients who lose their vocal cords by laryngectomies, the radiated noise and additive environment noise reduce the intelligibility of the resulting EL speech. This paper proposes an improved spectrum subtract algorithm by taking into account the non-uniform effect of colored noise on the spectrum of EL speech. Since the over-subtraction factor of each frequency band can be adjusted in the enhancement process, a better noise reduction effect was obtained and the perceptually annoying musical noise was efficiently reduced, as compared to other standard speech enhancement algorithms.

Description: The author surveys algorithms used in star identification, commonly used in star trackers to determine the attitude of a spacecraft. Star trackers are a staple of attitude determination systems for most types of satellites. The paper covers: (a) lost-in-space algorithms (when no a priori attitude information is available), (b) recursive algorithms (when some a priori attitude information is available), and (c) non-dimensional algorithms (when the star tracker calibration is not well-known). The performance of selected algorithms and supporting algorithms are compared.

Description: The problem of protein structure prediction is one of the long-standing goals of Computational Biology. Although we are still not able to provide first principle solutions, several shortcuts have been discovered to compute the protein three-dimensional structure when similar protein sequences are available (by means of comparative modeling and remote homology detection). Nonetheless, these approaches can assign structures only to a fraction of proteins in genomes and ab-initio methods are still needed. One relevant step of ab-initio prediction methods is the reconstruction of the protein structures starting from inter-protein residue contacts. In this paper we review the methods developed so far to accomplish the reconstruction task in order to highlight their differences and similarities. The different approaches are fully described and their reported performances, together with their computational complexity, are also discussed.

Description: In this work the optimal design of sensor networks for chemical plants is addressed using stochastic optimization strategies. The problem consists in selecting the type, number and location of new sensors that provide the required quantity and quality of process information. Ad-hoc strategies based on Tabu Search, Scatter Search and Population Based Incremental Learning Algorithms are proposed. Regarding Tabu Search, the intensification and diversification capabilities of the technique are enhanced using Path Relinking. The strategies are applied for solving minimum cost design problems subject to quality constraints on variable estimates, and their performances are compared.

Description: In this work we focus on the energy efficiency challenge in wireless sensor networks, from both an on-line perspective (related to routing), as well as a network design perspective (related to tracking). We investigate a few representative, important aspects of energy efficiency: a) the robust and fast data propagation b) the problem of balancing the energy dissipation among all sensors in the network and c) the problem of efficiently tracking moving entities in sensor networks. Our work here is a methodological survey of selected results that have already appeared in the related literature. In particular, we investigate important issues of energy optimization, like minimizing the total energy dissipation, minimizing the number of transmissions as well as balancing the energy load to prolong the system’s lifetime. We review characteristic protocols and techniques in the recent literature, including probabilistic forwarding and local optimization methods. We study the problem of localizing and tracking multiple moving targets from a network design perspective i.e. towards estimating the least possible number of sensors, their positions and operation characteristics needed to efficiently perform the tracking task. To avoid an expensive massive deployment, we try to take advantage of possible coverage overlaps over space and time, by introducing a novel combinatorial model that captures such overlaps. Under this model, we abstract the tracking network design problem by a covering combinatorial problem and then design and analyze an efficient approximate method for sensor placement and operation.

Description: In this paper, a block-based watermarking scheme based on the Singular Value Decomposition (SVD) is proposed. Our watermark, a pseudo-random Gaussian sequence, is embedded by modifying the angles formed by the right singular vectors of each block of the original image. The orthogonality property of the right singular vector matrix is preserved during the embedding process. Several experiments have been carried out to test the performance of the proposed scheme against different attack scenarios. We conclude that the proposed scheme is resistant against common signal processing operations and attacks, while it preserves the quality of the original image.

Description: The performance of Radio-Isotope Identification (RIID) algorithms using NaI-based γ spectroscopy is increasingly important. For example, sensors at locations that screen for illicit nuclear material rely on isotope identification using NaI detectors to distinguish innocent nuisance alarms, arising from naturally occurring radioactive material, from alarms arising from threat isotopes. Recent data collections for RIID testing consist of repeat measurements for each of several measurement scenarios to test RIID algorithms. It is anticipated that vendors can modify their algorithms on the basis of performance on chosen measurement scenarios and then test modified algorithms on data for other measurement scenarios. It is therefore timely to review the current status of RIID algorithms on NaI detectors. This review describes γ spectra from NaI detectors, measurement issues and challenges, current RIID algorithms, data preprocessing steps, the role and current quality of synthetic spectra, and opportunities for improvements.

Description: Unlike protein folding, the process by which a large RNA molecule adopts a functionally active conformation remains poorly understood. Chemical mapping techniques, such as Hydroxyl Radical (·OH) footprinting report on local structural changes in an RNA as it folds with single nucleotide resolution. The analysis and interpretation of this kinetic data requires the identification and subsequent optimization of a kinetic model and its parameters. We detail our approach to this problem, specifically focusing on a novel strategy to overcome a factorial explosion in the number of possible models that need to be tested to identify the best fitting model. Previously, smaller systems (less than three intermediates) were computationally tractable using a distributed computing approach. However, for larger systems with three or more intermediates, the problem became computationally intractable. With our new enumeration strategy, we are able to significantly reduce the number of models that need to be tested using non-linear least squares optimization, allowing us to study systems with up to five intermediates. Furthermore, two intermediate systems can now be analyzed on a desktop computer, which eliminates the need for a distributed computing solution for most mediumsized data sets. Our new approach also allows us to study potential degeneracy in kinetic model selection, elucidating the limits of the method when working with large systems. This work establishes clear criteria for determining if experimental ·OH data is sufficient to determine the underlying kinetic model, or if other experimental modalities are required to resolve any degeneracy.

Description: In this paper a hybrid semi-analytical Finite Element formulation is proposed to efficiently calculate the time dependent response due to stress waves propagating in a slender solid with uniform cross-section when excited by impulsive forces. The formulation takes advantage of the direct and inverse Fourier transform to formulate and solve the governing wave equation. The framework is applied to an octagonal viscoelastic isotropic steel bar.

Description: Security should be integrated into future networks from the beginning, not as an extension. Secure identities and authentication schemes are an important step to fulfill this quest. In this article, we argue that home networks are a natural trust anchor for such schemes. We describe our concept of home networks as a universal point of reference for authentication, trust and access control, and show that our scheme can be applied to any next generation network. As home networks are no safe place, we apply Trusted Computing technology to prevent the abuse of identities, i.e., identity theft.

Description: Sensor nodes are characterized by a small size, a low cost, an advanced communication technology, but also a limited amount of energy. Energy efficient strategies are required in such networks to maximize network lifetime. In this paper, we focus on a solution integrating energy efficient routing and node activity scheduling. The energy efficient routing we propose, called EOLSR, selects the route and minimizes the energy consumed by an end-to-end transmission, while avoiding nodes with low residual energy. Simulation results show that EOLSR outperforms the solution selecting the route of minimum energy as well as the solution based on node residual energy. Cross-layering allows EOLSR to use information from the application layer or the MAC layer to reduce its overhead and increase network lifetime. Node activity scheduling is based on the following observation: the sleep state is the least power consuming state. So, to schedule node active and sleeping periods, we propose SERENA that colors all network nodes using a small number of colors, such that two nodes with the same color can transmit without interfering. The node color is mapped into a time slot during which the node can transmit. Consequently, each node is awake during its slot and the slots of its one-hop neighbors, and sleeps in the remaining time. We evaluate SERENA benefits obtained in terms of bandwidth, delay and energy. We also show how cross-layering with the application layer can improve the end-to-end delays for data gathering applications.

Description: Pervasive wireless systems have significantly improved end-users’ quality of life. As manufacturing costs decrease, communications bandwidth increases, and contextual information is made more readily available, the role of next generation wireless systems in facilitating users’ daily activities will grow. Unique security and privacy issues exist in these wireless, context-aware, often decentralized systems. For example, the pervasive nature of such systems allows adversaries to launch stealthy attacks against them. In this review paper, we survey several emergent personal wireless systems and their applications. These systems include mobile social networks, active implantable medical devices, and consumer products. We explore each system’s usage of contextual information and provide insight into its security vulnerabilities. Where possible, we describe existing solutions for defendingagainst these vulnerabilities. Finally, we point out promising future research directions for improving these systems’ robustness and security

Description: This paper describes a follow-up Web 2.0 approach to a technology enhanced master course for students of Graz University of Technology. The lecture “Social Aspects of Information Technology” has a long tradition for using new didactical scenarios as well as modern e-Learning technologies. After using a blogosphere one year ago, this year microblog channels helped to expand the traditional lecture. Students choose (on a voluntary basis) whether they want to participate in a blogging/microblogging group instead of using conventional methods called Scientific Writer/Scientific Reviewer. This study addresses the question whether this method can change the learning outcome into a more reflective one. Furthermore, peer-reviewing groups judge the quality of essays and blog contributions. In this paper we examine if microblogging can be an appropriate technology for assisting the process. This publication comes to the conclusion that an amazing potential and a new way to work with information is opened when using microblogging. Students seem to be more engaged, reflective and critical in as much as they presented much more personal statements and opinions than years before.

Description: In this paper, Web 2.0 open content mashups or combinations are explored. Two case studies of recent initial teacher training programmes are reviewed where blogs and wikis were blended to create new virtual learning spaces. In two separate studies, students offer their views about using these tools, and reflect on the strengths and weaknesses of this approach. There is also discussion about aggregation of content and a theorization of how community and personal spaces can create tension and conflict. A new ‘learning spaces’ model will be presented which aids visualization of the processes, domains and territories that are brought into play when content and Web 2.0 tools are mashed up within the same space.

Description: Service platforms using text-based protocols need to be protected against attacks. Machine-learning algorithms with pattern matching can be used to detect even previously unknown attacks. In this paper, we present an extension to known Support Vector Machine (SVM) based anomaly detection algorithms for the Session Initiation Protocol (SIP). Our contribution is to extend the amount of different features used for classification (feature space) by exploiting the structure of SIP messages, which reduces the false positive rate. Additionally, we show how combining our approach with attribute reduction significantly improves throughput.

Description: Security should be integrated into future networks from the beginning, not as an extension. Secure identities and authentication schemes are an important step to fulfill this quest. In this article, we argue that home networks are a natural trust anchor for such schemes. We describe our concept of home networks as a universal point of reference for authentication, trust and access control, and show that our scheme can be applied to any next generation network. As home networks are no safe place, we apply Trusted Computing technology to prevent the abuse of identities, i.e., identity theft.

Description: CWM Global Search is a meta-search engine allowing chemists and biologists to search the major chemical and biological databases on the Internet, by structure, synonyms, CAS Registry Numbers and free text. A meta-search engine is a search tool that sends user requests to several other search engines and/or databases and aggregates the results into a single list or displays them according to their source [1]. CWM Global Search is a web application that has many of the characteristics of desktop applications (also known as Rich Internet Application, RIA), and it runs on both Windows and Macintosh platforms. The application is one of the first RIA for scientists. The application can be started using the URL http://cwmglobalsearch.com/gsweb.

Description: With the increasing availability of Internet type services on mobile devices and the attractive flat rate all-you-can-eat billing system, cellular telecommunication networks are experiencing a tremendous growth in data usage demand. However, there are increasing concerns that current network deployment trends (including more efficient radio access techniques and increased spectrum allocation strategies), will be unable to support the increased Internet traffic in a sustainable way. The delay tolerant nature of mobile Internet traffic allows for a large degree of flexibility in optimizing network performance to meet different design objectives and it’s a feature that has mostly gone unexplored by the research community. In this paper, we introduce a novel message forwarding mechanism in cellular networks that benefits from the inherent delay tolerance of Internet type services to provide flexible and adjustable forwarding strategies for efficient network operation while guaranteeing timely deliveries. By capitalizing on the elasticity of message delivery deadlines and the actual mobility of nodes inside the cell, considerable performance gains can be achieved by physically propagating information messages within the network.

Description: The success of the Content Delivery Networks (CDN) in the recent years has demonstrated the increased benefits of the deployment of some form of “intelligence” within the network. Cloud computing, on the other hand, has shown the benefits of economies of scale and the use of a generic infrastructure to support a variety of services. Following that trend, we propose to move away from the smart terminal-dumb network dichotomy to a model where some degree of intelligence is put back into the network, specifically at the edge, with the support of Cloud technology. In this paper, we propose the deployment of an Edge Cloud, which integrates a variety of user-side and server-side services. On the user side, surrogate, an application running on top of the Cloud, supports a virtual client. The surrogate hides the underlying network infrastructure from the user, thus allowing for simpler, more easily managed terminals. Network side services supporting delivery of and exploiting content are also deployed on this infrastructure, giving the Internet Service Providers (ISP) many opportunities to become directly involved in content and service delivery.

Description: Web Search Engines provide a huge number of answers in response to a user query, many of which are not relevant, whereas some of the most relevant ones may not be found. In the literature several approaches have been proposed in order to help a user to find the information relevant to his/her real needs on the Web. To achieve this goal the individual Information Behavior can been analyzed to ’keep’ track of the user’s interests. Keeping information is a type of Information Behavior, and in several works researchers have referred to it as the study on what people do during a search on the Web. Generally, the user’s actions (e.g., how the user moves from one Web page to another, or her/his download of a document, etc.) are recorded in Web logs. This paper reports on research activities which aim to exploit the information extracted from Web logs (or query logs) in personalized user ontologies, with the objective to support the user in the process of discovering Web information relevant to her/his information needs. Personalized ontologies are used to improve the quality of Web search by applying two main techniques: query reformulation and re-ranking of query evaluation results. In this paper we analyze various methodologies presented in the literature aimed at using personalized ontologies, defined on the basis of the observation of Information Behaviour to help the user in finding relevant information.

Description: Mobile Ad hoc networks (MANET) and Peer-to-Peer (P2P) networks share central characteristics such as their distributed and decentralized nature. Combining both networking paradigms results in a Mobile Peer-to-Peer (MP2P) system that operates independently from a preexisting infrastructure. Securing MP2P networks in terms of availability and robustness as basic demands in envisioned application scenarios like first responder operations is a challenging task. In this article, we present a survey of selected threats and of state of the art countermeasures for MANETs and P2P networks. Further, we discuss the efficiency of MANET and P2P security mechanisms when applied in MP2P networks.

Description: Optical burst switching provides a feasible paradigm for the next IP over optical backbones. However its burst loss performance can be highly affected by burst contention. In this paper we discuss traffic engineering approaches for path selection with the objective tominimize contention using only topological information. The discussed strategies are based on balancing the traffic across the network in order to reduce congestion without incurring into link state protocol penalties. The routing strategies are evaluated by simulation on an optical burst switching model specifically developed for the purpose with OMNeT++. Results show that our strategies outperform the traditionally used shortest path routing to an extent that depends on the network connectivity.

Description: Scientific writing is an essential part of a student’s and researcher’s everyday life. In this paper we investigate the particularities of scientific writing and explore the features and limitations of existing tools for scientific writing. Deriving from this analysis and an online survey of the scientific writing processes of students and researchers at the University of Paderborn, we identify key principles to simplify scientific writing and reviewing. Finally, we introduce a novel approach to support scientific writing with a tool called SciFlow that builds on these principles and state of the art technologies like cloud computing.