ALBERT

Description: by Johnatan Aljadeff, Ronen Segev, Michael J. Berry, Tatyana O. Sharpee Many biological systems perform computations on inputs that have very large dimensionality. Determining the relevant input combinations for a particular computation is often key to understanding its function. A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs. In systems neuroscience, the corresponding method is known as spike-triggered covariance (STC). This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems. So far, most studies used the STC method with weakly correlated Gaussian inputs. However, it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment. In such cases, the stimulus covariance matrix has one (or more) outstanding eigenvalues that cannot be easily equalized because of sampling variability. Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs. In many cases, these modes obscure the significant dimensions. We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more. This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode(s). Analyzing the responses of retinal ganglion cells probed with Gaussian noise, we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons.

Description: In cognitive radio networks, the secondary users (SUs) switch the data transmission to another empty spectrum band to give priority to primary users (PUs). In this paper, channel switching in cognitive radio mobile ad hoc networks (CR-MANETs) through an established route is modeled. The probability of channel availability in this route is calculated based on the PU's activity, SU's mobility, and channel heterogeneity. Based on the proposed model, the channel and link availability time are predicted. These predictions are used for channel assignment in the proposed channel allocation scheme. A handoff threshold as well as a life time threshold is used in order to reduce the handoff delay and the number of channel handoffs originating from the short channel usage time. When the channel handoff cannot be done due to the SU's mobility, the local flow handoff is performed to find an appropriate node in the vicinity of a potential link breakage and transfer the current data flow to it. The local flow handoff is performed to avoid possible flow disruption and also to reduce the delay caused by the link breakage. The study reveals that the channel heterogeneity and SU's mobility must be considered as important factors, which affect the performance of the handoff management in the CR-MANETs. The results emphasize on the improvement of the route maintenance probability after using the local flow handoff. It is also stated that the amounts of handoff requirement and handoff delay are decreased after using the predicted channel usage life time and handoff threshold time.

Description: Norms are used in open Multi-Agent Systems as a formal specification of deontic statements aimed at regulating the actions of agents and the interactions among them. In this paper, we propose a set of services facilitating the development of both non-normative and normative agents for norm-governed MAS. Specifically, we propose to provide agents with norm reasoning services. These services will help agent designers/developers to programme agents that consider norm reasoning without having to implement the needed mechanisms to reason about norms by themselves. This article shows how these services perform as well as the results of the experiments that we conducted to evaluate their performance.

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Description: We present here a work that applies an automatic construction of ensembles based on the Clustering and Selection (CS) algorithm for time series forecasting. The automatic method, called CSELM, initially finds an optimum number of clusters for training data set and subsequently designates an Extreme Learning Machine (ELM) for each cluster found. For model evaluation, the testing data set are submitted to clustering technique and the nearest cluster to data input will give a supervised response through its associated ELM. Self-organizing maps were used in the clustering phase. Adaptive differential evolution was used to optimize the parameters and performance of the different techniques used in the clustering and prediction phases. The results obtained with the CSELM method are compared with results obtained by other methods in the literature. Five well-known time series were used to validate CSELM. Content Type Journal Article Pages 191-203 DOI 10.3233/HIS-130176 Authors Tiago P.F. Lima, Centro de Informática, Universidade Federal de Pernambuco, Recife, Brazil Teresa B. Ludermir, Centro de Informática, Universidade Federal de Pernambuco, Recife, Brazil Journal International Journal of Hybrid Intelligent Systems Online ISSN 1875-8819 Print ISSN 1448-5869 Journal Volume Volume 10 Journal Issue Volume 10, Number 4 / 2013

Description: For all you readers who want the inside dope on how to be an architect, you've come to the right place. Here's a real-life story of the evolution of an E2E architect who has shared her lessons learned with us. There's clear insight here. She describes her realization that it's not just about knowledge of the domain or technical skill, but also about communication and learning. The Web extra at http://youtu.be/_RujP0FIjhY is an audio podcast in which Bett Correa and Russ Miller discuss contextual design (CD), a user-centered design process created by Hugh Beyer and Karen Holtzblatt. CD helps software architects and developers better connect with the needs of their users and enables them to more easily "re-imagine" the solution they create for users.

Description: Articles regarding the many faces of software analytics highlight the power of analytics for different types of organizations: large organizations and open source projects, as well as small- to medium-sized projects.

Description: Free, open source software development communities can become large and complex. They can also be a focus of interest for competing companies relying on their outcomes, with employees joining the development and maintenance effort. In those cases, it's especially important for both companies and communities to understand how this collaboration is working and how it matches their policies and expectations. This articles looks at two cases (OpenStack and WebKit) that the authors studied using analytics techniques. They conclude that such analytics can improve factual knowledge about how development communities are performing in aspects that are of interest to companies.

Description: Finding yourself in a situation with a working and a buggy system is quite common. Differential debugging methodically can help by comparing a known good system with a buggy one, working toward the problem source. Some simple steps include applying differential debugging by looking at log files and increasing a system's log verbosity when needed. If the system doesn't offer a sufficiently detailed logging mechanism, you can tease out its runtime behavior with tools that trace calls to the operating system or that trace network packets. You can also compare carefully the two environments where the systems operate. The Web extra at http://youtu.be/qnXS6b4hakg is an audio podcast of author Diomidis Spinellis reading his Tools of the Trade column, in which he discusses how comparing a good system with a buggy one can help locate the source of the problem.

Description: Amisoft, a Chilean software company with 43 employees, successfully uses software analytics in its projects. These support a variety of strategic and tactical decisions, resulting in less overwork of employees. However, the analytics done at Amisoft are very different from the ones used in larger companies.

Description: With smartphones being the primary handheld device for more than a billion people, mobile Web apps are a necessity in both technical and commercial fields. There are several approaches to developing mobile Web apps, but given the fast speed of mobile software evolution, in which the leading companies become marginal in months and new gadgets continually appear, it's crucial to understand the basic technologies. Authors Nicolás Serrano, Josune Hernantes, and Gorka Gallardo examine current development approaches that can enhance the decision-making process.

Description: Software analytics guide practitioners in decision making throughout the software development process. In this context, prediction models help managers efficiently organize their resources and identify problems by analyzing patterns on existing project data in an intelligent and meaningful manner. Over the past decade, the authors have worked with software organizations to build metric repositories and predictive models that address process-, product-, and people-related issues in practice. This article shares their experience over the years, reflecting the expectations and outcomes both from practitioner and researcher viewpoints.

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Description: Agile processes seek "just enough" requirements. However, this focus on simple software solutions can come at the expense of solutions that meet more creative requirements. To explore alternatives, this article reports results from extending one agile process with creativity techniques in a project for a large media organization. Domain experts ranked the requirements generated with the process as more novel than baseline epics from the product backlog of the same project, while the requirements' usefulness increased overall after incubation over the duration of a sprint.

Description: As the last standardization effort was done in 2004, the software engineering curriculum is currently being revised. Haven't we reached the point where agile development should be part of all software engineering curricula? And if so, shouldn't new curriculum standards ensure that it is?

Description: Component-based development is a relatively new paradigm for software development, compared to more established approaches such as object-oriented analysis and design. The authors conducted a study to examine the ease-of-reuse perceptions of analysts in modeling business systems using a library of components versus a library of objects. A survey of the IT professionals who participated in the study showed that perceived components to be much easier to reuse than objects. Users also expressed significantly higher satisfaction with components and, by a large majority, a preference for reusing components to reusing objects.

Description: The Visual Computer Managed Security (Vicoms) framework assists programmers in coding access control for Java applications. Vicoms provides a transparent way of managing security aspects in enterprise-level applications, including legacy ones. It has been embedded within the Eclipse open source integrated development environment and used experimentally in several case studies, one of which is described in the article.

Description: With software analytics, software practitioners explore and analyze data to obtain insightful, actionable information for tasks regarding software development, systems, and users. The StackMine project produced a software analytics system for Microsoft product teams. The project provided lessons on applying software analytics technologies to positively impact software development practice. The lessons include focusing on problems that practitioners care about, using domain knowledge for correct data understanding and problem modeling, building prototypes early to get practitioners' feedback, taking into account scalability and customizability, and evaluating analysis results using criteria related to real tasks.

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Description: In the field of rheology, properties of non-Newtonian fluids have been traditionally represented on graphs such as viscosity curves. In this paper, we propose a visualizer to express the fluid properties as visualized fluid motions in a rotating cylinder. To highlight different fluid motions, three patterns of rotation were given to the cylinder: rapid start of constant rotation (spin-up), rapid stop from constant rotation (spin-down), and periodic rotation. Relationships between fluid motion and fluid properties are discussed by comparing velocity profiles for three fluids: silicone oil, yogurt, and a polyacrylamide (PAA) solution. Ultrasonic velocity profiler (UVP) was used to obtain spatio-temporal velocity maps. The velocity maps reflect essential rheological properties, such as shear thinning, yield stress, and elasticity. Two additional display modes are proposed to explore fluid motions due to viscoelasticity of the PAA solution and yogurt: a grid deformation field and a shear rate field. These two visualizations can provide intuitive understanding of viscoelasticity because deformation and shear rate determine elastic and viscous stresses, respectively. In spin-down tests, the recovery of deformed grids, which is caused by elasticity, can be explicitly observed. Further, the shear rate distributions indicate that kinetic energy of the fluid dissipates near the lateral wall right after the wall stops rotating. In short, these two quantity fields visualize energy conversion among kinetic, elastic, and thermal energy; such energy conversions are characteristic of viscoelastic fluids. Graphical Abstract

Description: Background: The process of creating and designing Virtual Patients for teaching students of medicine is an expensive and time-consuming task. In order to explore potential methods of mitigating these costs, our group began exploring the possibility of creating Virtual Patients based on electronic health records. This review assesses the usage of electronic health records in the creation of interactive Virtual Patients for teaching clinical decision-making. Methods: The PubMed database was accessed programmatically to find papers relating to Virtual Patients. The returned citations were classified and the relevant full text articles were reviewed to find Virtual Patient systems that used electronic health records to create learning modalities. Results: A total of n = 362 citations were found on PubMed and subsequently classified, of which n = 28 full-text articles were reviewed. Few articles used unformatted electronic health records other than patient CT or MRI scans. The use of patient data, extracted from electronic health records or otherwise, is widespread. The use of unformatted electronic health records in their raw form is less frequent. Patient data use is broad and spans several areas, such as teaching, training, 3D visualisation, and assessment. Conclusions: Virtual Patients that are based on real patient data are widespread, yet the use of unformatted electronic health records, abundant in hospital information systems, is reported less often. The majority of teaching systems use reformatted patient data gathered from electronic health records, and do not use these electronic health records directly. Furthermore, many systems were found that used patient data in the form of CT or MRI scans. Much potential research exists regarding the use of unformatted electronic health records for the creation of Virtual Patients.

Description: Background: Human resources are an important building block of the health system. During the last decade, enormous investment has gone into the information systems to manage human resources, but due to the lack of a clear vision, policy, and strategy, the results of these efforts have not been very visible. No reliable information portal captures the actual state of human resources in Pakistan's health sector. The World Health Organization (WHO) has provided technical support for the assessment of the existing system and development of a comprehensive Human Resource Information System (HRIS) in Pakistan. Methods: The questions in the WHO-HRIS Assessment tool were distributed into five thematic groups. Purposively selected (n=65) representatives from the government, private sector, and development partners participated in this cross sectional study, based on their programmatic affiliations. Results: Fifty-five percent of organizations and departments have an independent Human Resources (HR) section managed by an establishment branch and are fully equipped with functional computers. Forty-five organizations (70%) had HR rules, regulations and coordination mechanisms, yet these are not implemented. Data reporting is mainly in paper form, on prescribed forms (51%), registers (3%) or even plain papers (20%). Data analysis does not give inputs to the decision making process and dissemination of information is quite erratic. Most of the organizations had no feedback mechanism for cross checking the HR data, rendering it unreliable. Conclusion: Pakistan is lacking appropriate HRIS management. The current HRIS indeed has a multitude of problems. In the wake of 2011 reforms within the health sector, provinces are even in a greater need for planning their respective health department services and must work on the deficiencies and inefficiencies of their HRIS so that the gaps and HR needs are better aligned for reaching the 2015 UN Millennium Development Goals (MDGs) targets.

Description: Quality-of-experience-oriented mechanisms, not currently available in traditional database management systems, allow a system to take into consideration user-specified requirements and to adjust its operations accordingly, based on user expectations.

Description: Just as technological innovations enable identity science researchers to develop better recognition systems, they can also create novel challenges for such systems.

Description: We don't have satisfactory answers to questions that ask what we must share with our neighbor for our common good and the rights we retain in the process. Yet such answers will be the legacy of our age. The Web extra at http://youtu.be/U0piYSt35YU is a video segment in which author David Alan Grier expands on his Errant Hashtag column, in which he discusses how the idea of "smart cities" makes more sense than the idea of "smart homes."

Description: Spaces that encourage the mix of academic instruction with practical professional experience beyond the traditional computing classroom can significantly increase students' motivation to learn and to share their learning with others.

Description: Measuring student learning in computer science education presents particular challenges, making objective assessment elusive to educators and researchers. Development and validation of the FCS1 and CAS assessment tools demonstrate both the feasibility and benefits of validated assessment instruments in this discipline.

Description: Multi-processor HPC tools have become commonplace in industry and research today. Evolutionary algorithms may be elegantly parallelized by broadcasting a whole population of designs to an array of processors in a computing cluster or grid. However, issues arise due to synchronization barriers: subsequent iterations have to wait for the successful execution of all jobs of the previous generation. When other users load a cluster or a grid, individual tasks may be delayed and some of them may never complete, slowing down and eventually blocking the optimization process. In this paper, we extend the recent “Futures” concept permitting the algorithm to circumvent such situations. The idea is to set the default values to the cost function values calculated using a high-quality surrogate model, progressively improving when “exact” numerical results are received. While waiting for the exact result, the algorithm continues using the approximation and when the data finally arrives, the surrogate model is updated. At convergence, the final result is not only an optimized set of designs, but also a surrogate model that is precise within the neighborhood of the optimal solution. We illustrate this approach with the cluster optimization of an A/C duct of a passenger car, using a refined CFD legacy software model along with an adaptive meta-model based on Proper Orthogonal Decomposition (POD) and diffuse approximation.

Description: This paper presents a methodology to repair flawed migrated models that are designed with knowledge-guided NURBS (KGN). Incompatible traditional CAD packages that are based on NURBS technology have been for many years carrying out the exchange of models and data through either neutral file formats (IGES or STEP) or proprietary formats. The exchange process most often produces poor quality data and results in errors in the migrated CAD models costing the industry billions of dollars every year. While previous studies by large focus on finding means to repair migrated models through patching, we propose to repair errors in CAD models which are generated using KGN through a reconstructing process instead of patching. We have implemented a prototype system to show that employing the right tools on the stored knowledge and data a designer can reconstruct a migrated model based on new local requirements of the receiving system without having to repair it, avoiding delay and corrective processes that only produce patched-up design bases and limiting the effective use of such models.

Description: Multiple interval graphs are variants of interval graphs where instead of a single interval, each vertex is assigned a set of intervals on the real line. We study the complexity of the MAXIMUM CLIQUE problem in several classes of multiple interval graphs. The MAXIMUM CLIQUE problem, or the problem of finding the size of the maximum clique, is known to be NP-complete for t -interval graphs when t ≥3 and polynomial-time solvable when t =1. The problem is also known to be NP-complete in t -track graphs when t ≥4 and polynomial-time solvable when t ≤2. We show that MAXIMUM CLIQUE is already NP-complete for unit 2-interval graphs and unit 3-track graphs. Further, we show that the problem is APX-complete for 2-interval graphs, 3-track graphs, unit 3-interval graphs and unit 4-track graphs. We also introduce two new classes of graphs called t -circular interval graphs and t -circular track graphs and study the complexity of the MAXIMUM CLIQUE problem in them. On the positive side, we present a polynomial time t -approximation algorithm for MAXIMUM WEIGHTED CLIQUE on t -interval graphs, improving earlier work with approximation ratio 4 t .

Description: Background: Decision support systems for differential diagnosis have traditionally been evaluated on the basis of criteria how sensitively and specifically they are able to identify the correct diagnosis established by expert clinicians.DiscussionThis article questions whether evaluation criteria pertaining to identifying the correct diagnosis are most appropriate or useful. Instead it advocates evaluation of decision support systems for differential diagnosis based on the criterion of maximizing value of information.SummaryThis approach quantitatively and systematically integrates several important clinical management priorities, including avoiding serious diagnostic errors of omission and avoiding harmful or expensive tests.

Description: Background: High-throughput sequencing technologies are improving in quality, capacity and costs, providing versatile applications in DNA and RNA research. For small genomes or fraction of larger genomes, DNA samples can be mixed and loaded together on the same sequencing track. This so-called multiplexing approach relies on a specific DNA tag or barcode that is attached to the sequencing or amplification primer and hence appears at the beginning of the sequence in every read. After sequencing, each sample read is identified on the basis of the respective barcode sequence.Alterations of DNA barcodes during synthesis, primer ligation, DNA amplification, or sequencing may lead to incorrect sample identification unless the error is revealed and corrected. This can be accomplished by implementing error correcting algorithms and codes. This barcoding strategy increases the total number of correctly identified samples, thus improving overall sequencing efficiency. Two popular sets of error-correcting codes are Hamming codes and Levenshtein codes.ResultLevenshtein codes operate only on words of known length. Since a DNA sequence with an embedded barcode is essentially one continuous long word, application of the classical Levenshtein algorithm is problematic. In this paper we demonstrate the decreased error correction capability of Levenshtein codes in a DNA context and suggest an adaptation of Levenshtein codes that is proven of efficiently correcting nucleotide errors in DNA sequences. In our adaption we take the DNA context into account and redefine the word length whenever an insertion or deletion is revealed. In simulations we show the superior error correction capability of the new method compared to traditional Levenshtein and Hamming based codes in the presence of multiple errors. Conclusion: We present an adaptation of Levenshtein codes to DNA contexts capable of correction of a pre-defined number of insertion, deletion, and substitution mutations. Our improved method is additionally capable of recovering the new length of the corrupted codeword and of correcting on average more random mutations than traditional Levenshtein or Hamming codes.As part of this work we prepared software for the flexible generation of DNA codes based on our new approach. To adapt codes to specific experimental conditions, the user can customize sequence filtering, the number of correctable mutations and barcode length for highest performance.

Description: There is much interest in using high-throughput DNA sequencing methodology to monitor microorganisms, complex plant and animal communities. However, there are experimental and analytical issues to consider before applying a sequencing technology, which was originally developed for genome projects, to ecological projects. Many of these issues have been highlighted by recent microbial studies. Understanding how high-throughput sequencing is best implemented is important for the interpretation of recent results and the success of future applications. Addressing complex biological questions with metagenomics requires the interaction of researchers who bring different skill sets to problem solving. Educators can help by nurturing a collaborative interdisciplinary approach to genome science, which is essential for effective problem solving. Educators are in a position to help students, teachers, the public and policy makers interpret the new knowledge that metagenomics brings. To do this, they need to understand, not only the excitement of the science but also the pitfalls and shortcomings of methodology and research designs. We review these issues and some of the research directions that are helping to move the field forward.

Description: We believe that undergraduate biology students must acquire a foundational background in computing including how to formulate a computational problem; develop an algorithmic solution; implement their solution in software and then test, document and use their code to explore biological phenomena. Moreover, by learning these skills in the first year, students acquire a powerful tool set that they can use and build on throughout their studies. To address this need, we have developed a first-year undergraduate course that teaches students the foundations of computational thinking and programming in the context of problems in biology. This article describes the structure and content of the course and summarizes assessment data on both affective and learning outcomes.

Description: Bioinformatics is an integral part of modern life sciences. It has revolutionized and redefined how research is carried out and has had an enormous impact on biotechnology, medicine, agriculture and related areas. Yet, it is only rarely integrated into high school teaching and learning programs, playing almost no role in preparing the next generation of information-oriented citizens. Here, we describe the design principles of bioinformatics learning environments, including our own, that are aimed at introducing bioinformatics into senior high school curricula through engaging learners in scientifically authentic inquiry activities. We discuss the bioinformatics-related benefits and challenges that high school teachers and students face in the course of the implementation process, in light of previous studies and our own experience. Based on these lessons, we present a new approach for characterizing the questions embedded in bioinformatics teaching and learning units, based on three criteria: the type of domain-specific knowledge required to answer each question (declarative knowledge, procedural knowledge, strategic knowledge, situational knowledge), the scientific approach from which each question stems (biological, bioinformatics, a combination of the two) and the associated cognitive process dimension (remember, understand, apply, analyze, evaluate, create). We demonstrate the feasibility of this approach using a learning environment, which we developed for the high school level, and suggest some of its implications. This review sheds light on unique and critical characteristics related to broader integration of bioinformatics in secondary education, which are also relevant to the undergraduate level, and especially on curriculum design, development of suitable learning environments and teaching and learning processes.

Description: Next-generation sequencing (NGS) is increasingly being adopted as the backbone of biomedical research. With the commercialization of various affordable desktop sequencers, NGS will be reached by increasing numbers of cellular and molecular biologists, necessitating community consensus on bioinformatics protocols to tackle the exponential increase in quantity of sequence data. The current resources for NGS informatics are extremely fragmented. Finding a centralized synthesis is difficult. A multitude of tools exist for NGS data analysis; however, none of these satisfies all possible uses and needs. This gap in functionality could be filled by integrating different methods in customized pipelines, an approach helped by the open-source nature of many NGS programmes. Drawing from community spirit and with the use of the Wikipedia framework, we have initiated a collaborative NGS resource: The NGS WikiBook. We have collected a sufficient amount of text to incentivize a broader community to contribute to it. Users can search, browse, edit and create new content, so as to facilitate self-learning and feedback to the community. The overall structure and style for this dynamic material is designed for the bench biologists and non-bioinformaticians. The flexibility of online material allows the readers to ignore details in a first read, yet have immediate access to the information they need. Each chapter comes with practical exercises so readers may familiarize themselves with each step. The NGS WikiBook aims to create a collective laboratory book and protocol that explains the key concepts and describes best practices in this fast-evolving field.

Description: Neurons are spatially extended structures that receive and process inputs on their dendrites. It is generally accepted that neuronal computations arise from the active integration of synaptic inputs along a dendrite between the input location and the location of spike generation in the axon initial segment. However, many application such as simulations of brain networks use point-neurons—neurons without a morphological component—as computational units to keep the conceptual complexity and computational costs low. Inevitably, these applications thus omit a fundamental property of neuronal computation. In this work, we present an approach to model an artificial synapse that mimics dendritic processing without the need to explicitly simulate dendritic dynamics. The model synapse employs an analytic solution for the cable equation to compute the neuron’s membrane potential following dendritic inputs. Green’s function formalism is used to derive the closed version of the cable equation. We show that by using this synapse model, point-neurons can achieve results that were previously limited to the realms of multi-compartmental models. Moreover, a computational advantage is achieved when only a small number of simulated synapses impinge on a morphologically elaborate neuron. Opportunities and limitations are discussed.

Description: Due to interference between co-located wireless networks, obtaining accurate channel assessment becomesincreasingly important for wireless network configuration. This information is used, amongothers, for cognitive radio solutions and for intelligent channel selection in wireless networks. Solutionssuch as spectrum analyzers are capable of scanning a wide spectrum range, but are not dedicatedfor channel occupation assessment because they are extremely costly and not able to perform continuousrecording for a time period longer than a few seconds. On the other hand, low-cost solutionslack the flexibility and required performance in terms of configuration and sensing efficiency. To remedythe situation, this paper presents an alternative for channel assessment on top of a commercialsoftware-defined radio platform. Although there exist software solutions for performing spectrumsensing on such platforms, to the best of our knowledge, continuous spectrum sensing and long-termrecording remain challenging. We propose a pioneering solution that is capable of seamless spectrumsensing over a wide spectrum band and guarantees sufficient flexibility in terms of configurations. Theproposed solution is validated experimentally. We demonstrate two advantages of seamless spectrumsensing: the capability of accurate channel occupancy measurement and detecting transient signalssuch as Bluetooth.

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Description: IEEE Computer Graphics and Applications editor in chief Gabriel Taubin welcomes the magazine's incoming EIC Miguel Encarnação and bids farewell to editorial-board members David Kasik, Kari Pulli, and Diego Gutierrez.

Description: The winners of the 2012 IEEE Visualization Contest combined methods from molecular, flow, and scalar data visualization to reveal the characteristics and processes in the contest data. Because the simulated material didn't behave according to theory from textbooks, one challenge was to find meaningful visualizations to facilitate exploratory analysis. The contest winners created an interactive visual-analysis application based on MegaMol, their visualization framework. The tailored visualizations revealed data characteristics such as thermal vibrations and the spatial distribution of polarization domains. Domain expert knowledge verified the results. This video at http://youtu.be/RXnNKekY7VE shows the dataset used and the development of vector clusters over time.

Description: The next generation of VR simulators could take into account a novel input: the user's mental state, as measured with electrodes and a brain-computer interface. One illustration of this promising path is a project that adapted a guidance system's force feedback to the user's mental workload in real time. A first application of this approach is a medical training simulator that provides virtual assistance that adapts to the trainee's mental activity. Such results pave the way to VR systems that will automatically reconfigure and adapt to their users' mental states and cognitive processes.

Description: In conventional vehicle teleoperation systems, using low-bandwidth, high-delay transmission links causes a serious problem for remote control of the vehicles. To solve this problem, a proposed teleoperation system employs 3D maps and GPS time synchronization. Two GPS receivers measure the transmission delay, which the system uses to estimate the vehicle's location and orientation. Field experiments show that the 3D-map-based interface lets users easily comprehend the remote environment while navigating a vehicle. The experiments also show that taking communication delays into account improves maneuverability.

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Description: Should broadband be treated as a public utility or be left solely to the private sector? Should state or municipal governments provide basic services, act as anchor tenants, or simply monitor progress? Whichever side of the debate you stand on, there is a growing consensus on the importance of high-quality broadband connections for everyone to ensure sustainable social and economic growth. Policy makers, legal scholars, and CEOs have shared their perspective. It's time for computer scientists to join the conversation.

Description: The Internet's growth, and the proliferation of online collaboration tools and platforms and the federated systems that support them, have enabled ad hoc processes in which people interact in a dynamic collective way. Such activities are characterized by their flexibility and data-driven nature, which makes them more difficult to analyze and support than traditionally rigid processes. Systems that handle dynamic collective work activities must address three main challenges: finding patterns in ad hoc execution behavior, handling concurrent users and concurrently executing tasks, and providing operational support. This special issue provides a snapshot of ongoing work in this area that addresses these challenges.

Description: MailOfMine aims at automatically building a set of workflow models--which represent the artful processes behind knowledge workers' activities--on top of a collection of email messages. Such models formalize the unspecified agile processes that knowledge workers autonomously perform: because these models aren't defined a priori by experts but are rather inferred from real-life scenarios, they're guaranteed to respect true workflow executions. Moreover, knowledge workers can share, compare, and preserve such models to put in evidence their best practices and thus benefit the entire business. Finally, workers and organizations can analyze such processes to determine bottlenecks and delays in actual executions. MailOfMine describes workflow models according to a declarative approach, with a specific visual notation.

Description: Organizations require tools that can assess their online reputations as well as the impact of their marketing and public outreach activities. The Media Watch on Climate Change is a Web intelligence and online collaboration platform that addresses this requirement. It aggregates large archives of digital content from multiple stakeholder groups and enables the co-creation and visualization of evolving knowledge archives. Here, the authors introduce the base platform and a context-aware document editor as an add-on that supports concurrent authoring by multiple users. While documents are being edited, semantic methods analyze them on the fly to recommend related content. The system computes positive or negative sentiment automatically to provide a better understanding of third-party perceptions. The editor is part of an interactive dashboard that uses trend charts and map projections to show how often and where relevant information is published, and to provide a real-time account of concepts that stakeholders associate with a topic.

Description: Casebook embraces social and collaboration technology, analytics, and intelligence to advance the state of the art in case management from systems of record to a system of engagement for knowledge workers. It addresses complex, inefficient work practices, information loss during hand offs between teams, and failure to learn from previous case experience. Intelligent agents help people adapt to changing work practices by tracking process evolution and providing updates and recommendations. Social collaboration surrounding cases integrates communication with information and supports collaborative roadmapping to enable people to work as they collaborate, thus accelerating how quickly and accurately they handle cases.

Description: As large energy consumers, base stations need energy-efficient wireless access networks. This article compares the design of Long-Term Evolution (LTE) networks to energy-efficient LTE-Advanced networks. LTE-Advanced introduces three new functionalities--carrier aggregation, heterogeneous networks, and extended multiple-input, multiple-output (MIMO) support. The authors develop a power consumption model for LTE and LTE-Advanced macrocell and femtocell base stations, along with an energy efficiency measure. They show that LTE-Advanced's carrier aggregation and MIMO improve networks' energy efficiency up to 400 and 450 percent, respectively.

Description: In a previous article, the authors demonstrated that effectively discovering Web services helps developers avoid several common design errors in Web Service Description Language (WSDL) documents. Their proposed guidelines are unfortunately applicable only when publishers follow the top-down, or contract-first, method of building services, which isn't very popular due to its inherent costs. Here, they present an approach for preventing such errors when using a counterpart method--namely, bottom-up or code-first--and measure the approach's impact on service discovery. The rationale behind the study is that because code-first service interfaces are automatically generated by tools that--given a service implementation--deterministically map programming language constructs onto WSDL elements, the measurable properties of service implementations could influence resulting service interfaces.

Description: In this article, the authors propose a new approach to distributed computing with Web browsers and introduce the WeevilScout prototype framework. The proliferation of Web browsers and the performance gains being achieved by current JavaScript virtual machines raises the question whether Internet browsers can become yet another middleware for distributed computing. With 2 billion users online, computing through Internet browsers has the potential to amass immense resources, thus transforming the Internet into a distributed computer ideal for common classes of distributed scientific applications such as parametric studies. As a proof of concept, the authors demonstrate how a cluster of globally distributed Internet browsers is used to compute thousands of bio-informatics tasks.

Description: Very large datasets, also known as big data, originate from many domains, including healthcare, energy, weather, business, and social networks. Deriving knowledge is more difficult than ever when we must do it by intricately processing big data. Organizations rely on third-party, commodity computing resources or clouds to gather the computational resources required to manipulate data of this magnitude. Although social networks are perhaps among the largest big data producers, the collaboration that results from leveraging this paradigm could help to solve big data processing challenges. Here, the authors explore using personal ad hoc clouds comprised of individuals in social networks to address such challenges.

Description: Cloud computing services are traditionally deployed on centralized computing infrastructures confined to a few data centers, while cloud applications run in a single data center. However, the cloud's centralized nature can be limiting in terms of performance and cost for applications where users, data, and computation are distributed. The authors present an overview of distributed clouds that might be better suited for such applications. They briefly describe the distributed cloud landscape and introduce Nebula, a highly decentralized cloud that uses volunteer edge resources. The authors provide insights into some of its key properties and design issues, and describe a distributed MapReduce application scenario to illustrate the benefits and trade-offs of using distributed and decentralized clouds for distributed data-intensive computing applications.

Description: In current architectures for infrastructure networks, a single (logically centralized) network element is in charge of managing mobility. As new requirements arise from the widespread use of sophisticated end-user devices, new standard solutions are emerging that challenge the status quo and aim for an evolution toward distributed mobility management.

Description: Recent sensing-based systems involve a multitude of users, devices, and places. These types of systems challenge existing approaches for conducting valid system evaluations. Here, the author discusses such evaluation challenges and revisits existing system evaluation methodologies.

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Description: After 40 years of relational databases and of cohabitation between flat tables and object-oriented programming, a new generation of data stores is emerging. Sometimes referred to as NoSQL, this new generation supports hierarchical, heterogeneous data such as XML, JavaScript Object Notation, and Binary JSON. While the abstract querying primitives of the relational algebra (join, selection, projection, and so on) also make a lot of sense in the NoSQL world, a need exists for a tailor-made language for querying hierarchical, heterogeneous datasets. This article briefly summarizes the history of databases, then describes the JSONiq language. JSONiq was designed from the ground up to support JSON data and run against all JSON- or BSON-based data stores, turning them into full-fledged databases.

Description: Passwords are an old-fashioned authentication mechanism that remains ubiquitous, but modern processing hardware with massive parallelism has suddenly undercut the security of the traditional eight-character password. Administrators and users need to understand the increased risks and to find ways to use and protect longer passwords.

Description: Douglas Engelbart, J.C.R. Licklider, DARPA, augmented human intellect, Google Glass, and silicon sapience: what a fascinating amalgam of leaders, devices, and concepts! With today's cloud computing and with the legacy of giants like Engelbart and Licklider, we are at the beginning of a new age in machine intelligence that could result in a remarkable partnership between computers and humans, reinforcing the strengths of both.

Description: 2013-2014 Editorial Calendar

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Description: This special issue features three articles on interactive 3D developments for the Web. Two articles discuss exploiting GPU ubiquity and performance; the other applies current Web3D languages to a real-world education challenge.

Description: Until recently, a major drawback of declarative-3D approaches for the Web was the encoding of scene-graph-related structured data along with a text-based description of unstructured vertex data. Loading times were long, and 3D Web content wasn't available until the full page had completely loaded. To overcome this limitation requires external mesh data containers that are referenced in the scene description. In particular, sequential image geometry containers and explicit binary containers align well with GPU buffer structures, thus enabling fast decoding and GPU uploads. Furthermore, progressive binary geometry enables simple, yet highly progressive transmission of arbitrary mesh data on the Web.

Description: This issue's article examines the digital artwork of Michael Frank.

Description: Image retargeting adjusts images to arbitrary sizes such that they can be viewed on different displays. Content-aware image retargeting has been receiving increased attention. In particular, researchers have improved a patch-wise scaling method for image retargeting at the object level. The scaling partitions the image into rectangular patches of adaptive sizes, which are comparable to the sizes of the salient objects in the image. This partitioning is based on a visual-saliency map; accordingly, the method labels the patches as important or unimportant. Then, the method scales the important patches as uniformly as possible and stretches or squeezes the unimportant patches to fit the target size. A patch-based image-similarity measure finds the optimal set of scaling factors. In experiments, the improved method performed well for three image types: lines and edges, foreground objects, and geometric structures.

Description: The LiverAnatomyExplorer is a real-time surgical teaching tool based on state-of-the-art Web technologies such as SVG (Scalable Vector Graphics), X3D (Extensible3D), and WebGL (Web Graphics Library). Unlike other medical e-learning systems, the LiverAnatomyExplorer combines traditional clinical 2D imagery with interactive Web-based 3D models derived from patient-specific image data. The tool is enhanced by surgical videos, a self-assessment tool, and an online authoring tool with which instructors can manage the presented case studies and create multiple-choice quizzes.

Description: Long-term monitoring of an environment is a fundamental requirement for most wireless sensornetworks. Owing to the fact that the sensor nodes have limited energy budget, prolonging theirlifetime is essential in order to permit long-term monitoring. Furthermore, many applications requiresensor nodes to obtain an accurate estimation of a point-source signal (for example, an animal call orseismic activity). Commonly, multiple sensor nodes simultaneously sample and then cooperate toestimate the event signal. The selection of cooperation nodes is important to reduce the estimationerror while conserving the network's energy. In this paper, we present a novel method for sensor dataacquisition and signal estimation, which considers estimation accuracy, energy conservation, andenergy balance. The method, using a concept of 'virtual clusters,' forms groups of sensor nodes withthe same spatial and temporal properties. Two algorithms are used to provide functionality. The'distributed formation' algorithm automatically forms and classifies the virtual clusters. The 'roundrobin sample scheme' schedules the virtual clusters to sample the event signals in turn. Theestimation error and the energy consumption of the method, when used with a generalized sensingmodel, are evaluated through analysis and simulation. The results show that this method can achievean improved signal estimation while reducing and balancing energy consumption.

Description: We study the problem of achieving maximum network throughput with fairness among the flows at the nodes in a wireless mesh network, given their location and the number of their half-duplex radio interfaces. Our goal is to find the minimum number of non-overlapping frequency channels required to achieve interference-free communication. We use our existing Select x for less than x topology control algorithm (TCA) to build the connectivity graph (CG), which enhances spatial channel reuse to help minimize the number of channels required. We show that the TCA-based CG approach requires fewer channels than the classical approach of building the CG based on the maximum power. We use multi-path routing to achieve the maximum network throughput and show that it provides better network throughput than the classical minimum power-based shortest path routing. We also develop an effective heuristic method to determine the minimum number of channels required for interference-free channel assignment.

Description: One-dimensional second-order hyperbolic telegraph equation was formulated using Ohm’s law and solved by a recent and reliable semianalytic method, namely, the reduced differential transform method (RDTM). Using this method, it is possible to find the exact solution or a closed approximate solution of a differential equation. Three numerical examples have been carried out in order to check the effectiveness, the accuracy, and convergence of the method. The RDTM is a powerful mathematical technique for solving wide range of problems arising in science and engineering fields.

Description: Background: Patient Data Management Systems (PDMS) support clinical documentation at the bedside and have demonstrated effects on completeness of patient charting and the time spent on documentation. These systems are costly and raise the question if such a major investment pays off. We tried to answer the following questions: How do costs and revenues of an intensive care unit develop before and after introduction of a PDMS? Can higher revenues be obtained with improved PDMS documentation? Can we present cost savings attributable to the PDMS? Methods: Retrospective analysis of cost and reimbursement data of a 25 bed Intensive Care Unit at a German University Hospital, three years before (2004--2006) and three years after (2007--2009) PDMS implementation. Results: Costs and revenues increased continuously over the years. The profit of the investigated ICU was fluctuating over the years and seemingly depending on other factors as well. We found a small increase in profit in the year after the introduction of the PDMS, but not in the following years. Profit per case peaked at 1039 [euro sign] in 2007, but dropped subsequently to 639 [euro sign] per case. We found no clear evidence for cost savings after the PDMS introduction. Our cautious calculation did not consider additional labour costs for IT staff needed for system maintenance. Conclusions: The introduction of a PDMS has probably minimal or no effect on reimbursement. In our case the observed increase in profit was too small to amortize the total investment for PDMS implementation.This may add some counterweight to the literature, where expectations for tools such as the PDMS can be quite unreasonable.

Description: Probabilistic model-building algorithms (PMBA), a subset of evolutionary algorithms, have been successful in solving complex problems, in addition providing analytical information about the distribution of fit individuals. Most PMBA work has concentrated on the string representation used in typical genetic algorithms. A smaller body of work has aimed to apply the useful concepts of PMBA to genetic programming (GP), mostly concentrating on tree representation. Unfortunately, the latter research has been sporadically carried out, and reported in several different research streams, limiting substantial communication and discussion. In this paper, we aim to provide a critical review of previous applications of PMBA and related methods in GP research, to facilitate more vital communication. We illustrate the current state of research in applying PMBA to GP, noting important perspectives. We use these to categorise practical PMBA models for GP, and describe the main varieties on this basis.

Description: We give a memoryless scale-invariant randomized algorithm ReMix for Packet Scheduling that is e /( e −1)-competitive against an adaptive adversary. ReMix unifies most of previously known randomized algorithms, and its general analysis yields improved performance guarantees for several restricted variants, including the s -bounded instances. In particular, ReMix attains the optimum competitive ratio of 4/3 on 2-bounded instances. Our results are applicable to a more general problem, called Item Collection , in which only the relative order between packets’ deadlines is known. ReMix is the optimal memoryless randomized algorithm against adaptive adversary for that problem.

Description: Der Lehrstuhl für Datenbanksysteme der Technischen Universität München beschäftigt sich in der Forschung mit der Entwicklung, Optimierung und Anwendung „moderner“ Datenbanktechnologie. Die Schwerpunkte der letzten Jahre lagen in der Entwicklung von Multi-Tenancy-fähigen Datenbanken, eScience-Datenbankanwendungen, Workload-Management für heterogene Anwendungen, RDF-Datenbanken und, insbesondere, Hauptspeicher-Datenbanken für hybride OLTP&OLAP-Anwendungen.

Description: Radio frequency identification (RFID) is a promising wireless technology for using tiny, remotely powered chips as identifiers. The number of RFID applications is rapidly increasing because RFID technology is convenient, fast, and contactless. However, collisions occur when multiple tags simultaneously transmit their IDs. Therefore, an efficient anti-collision algorithm is needed to accelerate tag identification. In some applications, the reader may repeatedly identify staying tags, which constantly exist in the reader's range. The adaptive query splitting algorithm (AQS) was proposed for reserving information obtained from the last identification process to enable rapid re-identification of staying tags. However, since AQS is a non-blocking algorithm that allows newly arriving tags to use the slots reserved for staying tags, collisions among them are problematic. Thus, semi-blocking AQS (SBA) proposed in this study is designed to reduce the collisions between arriving tags and staying tags by applying a semi-blocking technique in which only a minority of arriving tags use the slots reserved for staying tags. By counting the number of minor arriving tags, SBA estimates the number of unrecognized arriving tags and generates proper queries to minimize their collisions. The identification delay of SBA is analyzed, and simulation results show that SBA significantly outperforms AQS.

Description: Learning is a task that generalizes many of the analyses that are applied to collections of data, in particular, to collections of sensitive individual information. Hence, it is natural to ask what can be learned while preserving individual privacy. Kasiviswanathan et al. (in SIAM J. Comput., 40(3):793–826, 2011 ) initiated such a discussion. They formalized the notion of private learning , as a combination of PAC learning and differential privacy, and investigated what concept classes can be learned privately. Somewhat surprisingly, they showed that for finite, discrete domains (ignoring time complexity), every PAC learning task could be performed privately with polynomially many labeled examples; in many natural cases this could even be done in polynomial time. While these results seem to equate non-private and private learning, there is still a significant gap: the sample complexity of (non-private) PAC learning is crisply characterized in terms of the VC-dimension of the concept class, whereas this relationship is lost in the constructions of private learners, which exhibit, generally, a higher sample complexity. Looking into this gap, we examine several private learning tasks and give tight bounds on their sample complexity. In particular, we show strong separations between sample complexities of proper and improper private learners (such separation does not exist for non-private learners), and between sample complexities of efficient and inefficient proper private learners. Our results show that VC-dimension is not the right measure for characterizing the sample complexity of proper private learning. We also examine the task of private data release (as initiated by Blum et al. in STOC, pp. 609–618, 2008 ), and give new lower bounds on the sample complexity. Our results show that the logarithmic dependence on size of the instance space is essential for private data release.

Description: Machine learning is traditionally formalized and investigated as the study of learning concepts and decision functions from labeled examples, requiring a representation that encodes information about the domain of the decision function to be learned. We are interested in providing a way for a human teacher to interact with an automated learner using natural instructions , thus allowing the teacher to communicate the relevant domain expertise to the learner without necessarily knowing anything about the internal representations used in the learning process. In this paper we suggest to view the process of learning a decision function as a natural language lesson interpretation problem , as opposed to learning from labeled examples. This view of machine learning is motivated by human learning processes, in which the learner is given a lesson describing the target concept directly and a few instances exemplifying it. We introduce a learning algorithm for the lesson interpretation problem that receives feedback from its performance on the final task, while learning jointly (1) how to interpret the lesson and (2) how to use this interpretation to do well on the final task. traditional machine learning by focusing on supplying the learner only with information that can be provided by a task expert. We evaluate our approach by applying it to the rules of the solitaire card game. We show that our learning approach can eventually use natural language instructions to learn the target concept and play the game legally. Furthermore, we show that the learned semantic interpreter also generalizes to previously unseen instructions.

Description: Motivation: Pyrosequencing technology provides an important new approach to more extensively characterize diverse sequence populations and detect low frequency variants. However, the promise of this technology has been difficult to realize, as careful correction of sequencing errors is crucial to distinguish rare variants (~1%) in an infected host with high sensitivity and specificity. Results: We developed a new approach, referred to as Indel and Carryforward Correction (ICC), to cluster sequences without substitutions and locally correct only indel and carryforward sequencing errors within clusters to ensure that no rare variants are lost. ICC performs sequence clustering in the order of (i) homopolymer indel patterns only, (ii) indel patterns only and (iii) carryforward errors only, without the requirement of a distance cutoff value. Overall, ICC removed 93–95% of sequencing errors found in control datasets. On pyrosequencing data from a PCR fragment derived from 15 HIV-1 plasmid clones mixed at various frequencies as low as 0.1%, ICC achieved the highest sensitivity and similar specificity compared with other commonly used error correction and variant calling algorithms. Availability and implementation: Source code is freely available for download at http://indra.mullins.microbiol.washington.edu/ICC . It is implemented in Perl and supported on Linux, Mac OS X and MS Windows. Contact: jmullins@uw.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: In this dissertation, we propose solving methods for the job shop scheduling problem with sequence-dependent setup times, considering four different objective functions. The formal properties of the problem are studied. Two new neighborhood structures are proposed, with their respective feasibility and non-improving conditions, as well as an algorithm for fast neighbors' cost estimation. These structures are embedded in local search procedures, and their hybridization with a genetic algorithm is also studied. The experimental results show that the proposed methods obtain excellent results, improving in many cases the state of the art. Content Type Journal Article Category Thesis Pages 419-421 DOI 10.3233/AIC-130571 Authors Miguel A. González, Computing Technologies Group, Department of Computing, Artificial Intelligence Center, University of Oviedo, Campus of Viesques, 33271 Gijón, Spain. E-mail: mig@uniovi.es Journal AI Communications Online ISSN 1875-8452 Print ISSN 0921-7126 Journal Volume Volume 26 Journal Issue Volume 26, Number 4 / 2013

Description: : Tiki proteins appear to antagonize Wnt signalling pathway by acting as Wnt proteases, thereby affecting Wnt solubility by its amino-terminal cleavage. Tiki1 protease activity was shown to be metal ion-dependent and was inhibited by chelating agents and thus was tentatively proposed to be a metalloprotease. Nevertheless, Tiki proteins exhibit no detectable sequence similarity to previously described metalloproteases, but instead have been reported as being homologues of TraB proteins (Pfam ID: PF01963), a widely distributed family of unknown function and structure. Here, we show that Tiki proteins are members of a new superfamily of domains contained not just in TraB proteins, but also in erythromycin esterase (Pfam ID: PF05139), DUF399 (domain of unknown function 399; Pfam ID: PF04187) and MARTX toxins that contribute to host invasion and pathogenesis by bacteria. We establish the core fold of this enzymatic domain and its catalytic residues. Contact: luis.sanchezpulido@dpag.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The research area metabolomics achieved tremendous popularity and development in the last couple of years. Owing to its unique interdisciplinarity, it requires to combine knowledge from various scientific disciplines. Advances in the high-throughput technology and the consequently growing quality and quantity of data put new demands on applied analytical and computational methods. Exploration of finally generated and analyzed datasets furthermore relies on powerful tools for data mining and visualization. Results: To cover and keep up with these requirements, we have created MeltDB 2.0, a next-generation web application addressing storage, sharing, standardization, integration and analysis of metabolomics experiments. New features improve both efficiency and effectivity of the entire processing pipeline of chromatographic raw data from pre-processing to the derivation of new biological knowledge. First, the generation of high-quality metabolic datasets has been vastly simplified. Second, the new statistics tool box allows to investigate these datasets according to a wide spectrum of scientific and explorative questions. Availability: The system is publicly available at https://meltdb.cebitec.uni-bielefeld.de . A login is required but freely available. Contact: nkessler@cebitec.uni-bielefeld.de