ALBERT

Description: This paper presents a novel evaluationary approach to extract color-texture features for image retrieval application namely Color Directional Local Quinary Pattern (CDLQP). The proposed descriptor extracts the individual R, G and B channel wise directional edge information between reference pixel and its surrounding neighborhoods by computing its grey-level difference based on quinary value (−2, −1, 0, 1, 2) instead of binary and ternary value in 0°, 45°, 90°, and 135° directions of an image which are not present in literature (LBP, LTP, CS-LBP, LTrPs, DExPs, etc.). To evaluate the retrieval performance of the proposed descriptor, two experiments have been conducted on Core-5000 and MIT-Color databases respectively. The retrieval performances of the proposed descriptor show a significant improvement as compared with standard local binary pattern LBP, center-symmetric local binary pattern (CS-LBP), Directional binary pattern (DBC) and other existing transform domain techniques in IR system.

Description: This paper reviews photogrammetric error sources and their impacts on modeling and surveying for construction quantity takeoff, quality control, and site safety monitoring applications. These error sources include camera internal parameters (i.e., type, principal point, principal distance, and camera lens distortion coefficients), imaging settings (i.e., shooting distances, baselines, percentage of photo overlaps, number of overlapping photos, camera intersection angles, and angles of incidence), and processing software programs. To augment the body of knowledge on photogrammetric modeling errors, this paper further conducts experiment, which concerns characterization of the behavior of different strategies in selecting reference lines for fixing absolute scale of photogrammetric models. In construction photogrammetric surveying, it is imperative to convert the relative scale of a 3D model into absolute measurements so geometric measurements can be taken. Previous work suggests this can be done through the determination of a reference line in absolute units; however, the position and quantity of reference lines has not been investigated. This experiment attempts to tackle this issue. The result shows that one horizontal reference line in the middle of the object performed with consistent accuracy, but if a specific area on the object needs more accurate measurements, it is best to select a reference line in that area. The review and the experimental findings may help construction professionals better understand the performance of the photogrammetric surveying and apply it in their real-world projects.

Description: Background: Incorrect snake identification from the observable visual traits is a major reason for death resulting from snake bites in tropics. So far no automatic classification method has been proposed to distinguish snakes by deciphering the taxonomy features of snake for the two major species of snakes i.e. Elapidae and Viperidae. We identify 38 different taxonomically relevant features to develop the Snake database from 490 sample images of Naja Naja (Spectacled cobra), 193 sample images of Ophiophagus Hannah (King cobra), 88 images of Bungarus caeruleus (Common krait), 304 sample images of Daboia russelii (Russell’s viper), 116 images of Echis carinatus (Saw scaled viper) and 108 images of Hypnale hypnale (Hump Nosed Pit Viper). Results: Snake identification performances with 13 different types of classifiers and 12 attribute elevator demonstrate that 15 out of 38 taxonomically relevant features are enough for snake identification. Interestingly, these features were almost equally distributed from the logical grouping of top, side and body views of snake images, and the features from the bottom view of snakes had the least role in the snake identification. Conclusion: We find that only few of the taxonomically relevant snake features are useful in the process of snake identification. These discriminant features are essential to improve the accuracy of snake identification and classification. The presented study indicate that automated snake identification is useful for practical applications such as in medical diagnosis, conservation studies and surveys by interdisciplinary practitioners with little expertise in snake taxonomy.

Description: Methods and tools to conduct authorship analysis of web contents is of growing interest to researchers and practitioners in various security-focused disciplines, including cybersecurity, counter-terrorism, and other fields in which authorship of text may at times be uncertain or obfuscated. Here we demonstrate an automated approach for authorship analysis of web contents. Analysis is conducted through the use of machine learning methodologies, an expansive stylometric feature set, and a series of visualizations intended to help facilitate authorship analysis at the author, message, and feature levels. To operationalize this, we utilize a testbed containing 506,554 forum messages in English and Arabic, source from 14,901 authors that participated in an online web forum. A prototype portal system providing authorship comparisons and visualizations was then designed and constructed in order to support feasibility analysis and real world value of the automated authorship analysis approach. A preliminary user evaluation was performed to assess the efficacy of visualizations, with evaluation results demonstrating task performance accuracy and efficiency was improved through use of the portal.

Description: Mobile Ad-hoc Network one of the prominent area for the researchers and practitioners in assorted domains including security, routing, addressing and many others. A Mobile Ad-hoc Network (MANET) refers to an autonomous group or cluster of mobile users that communicate over relatively bandwidth constrained wireless links. Mobile ad hoc network refers to the moving node rather than any fixed infrastructure, act as a mobile router. These mobile routers are responsible for the network mobility. The history of mobile network begin after the invention of 802.11 or WiFi they are mostly used for connecting among themselves and for connecting to the internet via any fixed infrastructure. Vehicles like car, buses and trains equipped with router acts as nested Mobile Ad-hoc Network. Vehicles today consists many embedded devices like build in routers, electronic devices like Sensors PDAs build in GPS, providing internet connection to it gives, information and infotainment to the users. These advances in MANET helps the vehicle to communicate with each other, at the time of emergency like accident, or during climatic changes like snow fall, and at the time of road block, this information will be informed to the nearby vehicles. Now days technologies rising to provide efficiency to MANET users like providing enough storage space, as we all know the cloud computing is the next generation computing paradigm many researches are conducting experiments on Mobile Ad-hoc Network to provide the cloud service securely. This paper attempts to propose and implement the security based algorithmic approach in the mobile adhoc networks.

Description: Agents often try to convince others to hold certain beliefs. In fact, many network security attacks can actually be framed in terms of a dishonest that is trying to get an honest agent to believe some particular, untrue claims. While the study of belief change is an established area of research in Artificial Intelligence, there has been comparatively little exploration of the way one agent can explicitly manipulate the beliefs of another. In this paper, we introduce a precise, formal notion of a belief manipulation problem. We also illustrate that the meaning of a message can be parsed into different communicative acts, as defined in discourse analysis theory. Specifically, we suggest that each message can be understood in terms of what it says about the world, what it says about the message history, and what it says about future actions. We demonstrate that this kind of dissection can actually be used to discover the goals of an intruder in a communication session, which is important when determining how an adversary is trying to manipulate the beliefs of an honest agent. This information will then help prevent future attacks. We frame the discussion of belief manipulation primarily in the context of cryptographic protocol analysis.

Description: The word “Paedophilia” has come a long way from its Greek origin of child-companionship to a Mental Disorder, Social Taboo and Criminal Offence. Various laws are in place to help control such behaviour, protect the vulnerable and restrain related criminal offences. However, enforcement of such laws has become a significant challenge with the advent of social media creating a new platform for this old crime. This move necessitates consideration of approaches that are suited to this new platform and the way in which it affects the Cycle of Entrapment. This paper reviews definitions of, and features of, paedophilia and other related –philias, and sexual offences against children, and seeks through the understanding of these to determine where specific detection approaches are effective. To this end, we present our own detection approach which is geared towards predatory behaviours, which can be a precursor to sexual offences against children, and which directly references this Cycle of Entrapment. Our approach has shown early promise with an F1 score of 0.66 for training data but only achieving 0.48 for testing data on a collection of chat logs of sexual predators. The results were later improved to achieve an F1 score of 0.77 for train and 0.54 for test data based on the approach.

Description: The nature of identity has changed dramatically in recent years and has grown in complexity. Identities are defined in multiple domains: biological and psychological elements strongly contribute, but biographical and cyber elements also are necessary to complete the picture. Law enforcement is beginning to adjust to these changes, recognizing identity’s importance in criminal justice. The SuperIdentity project seeks to aid law enforcement officials in their identification tasks through research of techniques for discovering identity traits, generation of statistical models of identity and analysis of identity traits through visualization. We present use cases compiled through user interviews in multiple fields, including law enforcement, and describe the modeling and visualization tools design to aid in those use cases.

Description: E-mail communication has become an essential part of collaborative tasks in enterprises. However, when conventional e-mail applications are used for collaborative tasks, problems with task-related resources management arise. In this paper, we present a task context-aware e-mail platform that helps users to send e-mails quickly and efficiently. This platform also automatically extracts data from reply e-mail messages. It enables users to automatically classify task-related information and user support services using a task context model. The task context model is built based on ontology as a semantic representation of the associations between task and task-related e-mail processes. This paper describes the design and implementation of this system on the basis of the task context model. To verify the efficacy of the prototype system, we conducted experiments that demonstrate the systems effective task awareness and user support services.

Description: The language of influence or propaganda has been studied for a century but its predictions (simplification, deceptiveness, manipulation) can now be examined empirically using corpus analytics. Semantic models for intensity of belief and use of gamification as a strategy allow novel aspects of influence to be taken into account as well. We develop a semi-automated approach to assess the quality of the language of influence using semantic models, and singular value decomposition as a middle ground between high-level abstract analysis and simple word counting.We then apply this approach in a significant intelligence application: examining the use of the language of influence in the jihadist magazines Inspire and Azan. These magazines have attracted attention from intelligence organizations because of their avowed goal of motivating lone-wolf attacks in Western countries. Our approach enables us to address questions like: How good are the authors and editors of these magazines at producing influential language (and so how great is the impact of these magazines likely to be)? How does this change with time, and as a reaction to world events, and what does this tell us about competence and strategic goals? What is the impact of changes in authorship?

Description: The paper explores the use of concepts in cognitive psychology to evaluate the spread of misinformation, disinformation and propaganda in online social networks. Analysing online social networks to identify metrics to infer cues of deception will enable us to measure diffusion of misinformation. The cognitive process involved in the decision to spread information involves answering four main questions viz consistency of message, coherency of message, credibility of source and general acceptability of message. We have used the cues of deception to analyse these questions to obtain solutions for preventing the spread of misinformation. We have proposed an algorithm to effectively detect deliberate spread of false information which would enable users to make informed decisions while spreading information in social networks. The computationally efficient algorithm uses the collaborative filtering property of social networks to measure the credibility of sources of information as well as quality of news items. The validation of the proposed methodology has been done on the online social network ‘Twitter’.

Description: Background: Building deteriorations instigated by material degradations or moisture intrusions are the primary causes for energy inefficiency in many existing buildings. For choosing appropriate retrofits, it is important to carefully diagnose and analyze building areas in need of improvements. In addition to reliable sensing and analysis of as-is energy performance, an intuitive recording and visualization of energy diagnostic outcomes are also critical to effectively illustrate the as-is building conditions to homeowners during retrofit decision-making processes.MethodToward this goal, this paper presents a thermography-based method to visualize the actual thermal resistance and condensation problems in 3D while taking static occlusions into account. First, several overlapping digital and thermal images are collected from the building areas under inspection. Using a computer vision method? consisting of image-based 3D point cloud and mesh modeling algorithms? actual 3D spatio-thermal models are generated where surface temperature can be queried at the level of 3D points. Based on the resulting 3D spatio-thermal models and by measuring the reflected and dew point temperatures, the actual R-values of building assemblies are calculated, and the condensation issues are analyzed. Taking static occlusions into account, (1) the distribution of the actual thermal resistance over each building assembly, (2) the detected building areas with condensation problems, and (3) the corresponding geometrical and thermal characteristics are jointly visualized within a 3D environment. Results: To validate the method and investigate the perceived benefits, four experiments have been conducted in existing buildings. Surveys are also conducted by professional energy auditors. The proposed method provides 3D visual representation of the actual thermal resistance distributions and building areas associated with condensation issues at the level of 3D points across geometrical forms while taking static occlusions into account. Conclusions: The experimental results and the feedback received from the professionals show the promise of the proposed method in facilitating systematic post-examination of building deteriorations and support retrofit decision-makings. Ultimately, converting surface temperature data obtained from an IR camera into 3D visualization of energy performance metrics and possible condensation problems enables practitioners to better understand the as-is building conditions.

Description: Acoustic environment leaves its characteristic signature in the audio recording captured in it. The acoustic environment signature can be modeled using acoustic reverberations and background noise. Acoustic reverberation depends on the geometry and composition of the recording location. The proposed scheme uses similarity in the estimated acoustic signature for acoustic environment identification (AEI). We describe a parametric model to realize acoustic reverberation, and a statistical framework based on maximum likelihood estimation is used to estimate the model parameters. The density-based clustering is used for automatic AEI using estimated acoustic parameters. Performance of the proposed framework is evaluated for two data sets consisting of hand-clapping and speech recordings made in a diverse set of acoustic environments using three microphones. Impact of the microphone type variation, frequency, and clustering accuracy and efficiency on the performance of the proposed method is investigated. Performance of the proposed method is also compared with the existing state-of-the-art (SoA) for AEI.

Description: We demonstrate how one can generate predictions for several thousand incidents of Latin American civil unrest, often many days in advance, by surfacing informative public posts available on Twitter and Tumblr.The data mining system presented here runs daily and requires no manual intervention. Identification of informative posts is accomplished by applying multiple textual and geographic filters to a high-volume data feed consisting of tens of millions of posts per day which have been flagged as public by their authors. Predictions are built by annotating the filtered posts, typically a few dozen per day, with demographic, spatial, and temporal information.Key to our textual filters is the fact that social media posts are necessarily short, making it possible to easily infer topic by simply searching for comentions of typically unrelated terms within the same post (e.g. a future date comentioned with an unrest keyword). Additional textual filters then proceed by applying a logistic regression classifier trained to recognize accounts belonging to organizations who are likely to announce civil unrest.Geographic filtering is accomplished despite sparsely available GPS information and without relying on sophisticated natural language processing. A geocoding technique which infers non-GPS-known user locations via the locations of their GPS-known friends provides us with location estimates for 91,984,163 Twitter users at a median error of 6.65km. We show that announcements of upcoming events tend to localize within a small geographic region, allowing us to forecast event locations which are not explicitly mentioned in text.We annotate our forecasts with demographic information by searching the collected posts for demographic specific keywords generated by hand as well as with the aid of DBpedia.Our system has been in production since December 2012 and, at the time of this writing, has produced 4,771 distinct forecasts for events across ten Latin American nations. Manual examination of 2,859 posts surfaced by our method revealed that only 108 were discussing topics unrelated to civil unrest. Examination of 2,596 forecasts generated between 2013-07-01 and 2013-11-30 found 1,192 (45.9%) matched exactly the date and within a 100 km radius of a civil unrest event reported in traditional news media.

Description: Background: Mobile cranes overturn due to excessive lifting, heavy wind, or when appropriate ground contact pressure is not secured. Such accidents can be prevented by reviewing the force conveyed from the outrigger to the ground upon lifting, as well as the soil bearing force. The stability review of mobile crane overturn is classified into the following stages: reviewing lifting conditions, mobile crane selection and reviewing ground contact stability. However, a precise review of ground contact stability requires expertise and is extremely time-consuming. Thus, this study develops automatic design algorithms for securing the ground stability of mobile cranes for easy and quick stability reviews. Methods: The stability review method and the algorithm models are created in connection with the proposed conceptual process. The algorithms proposed in this study conduct simulations for all possible candidate cases, save the results in a database, review practical alternatives, and select the solution that minimizes cost. To verify the effectiveness of the automatic design model, a case project was selected and the algorithm was applied assuming several conditions.ResultsDeveloped algorithms can select candidate cranes according to lifting conditions and design plates through simulations easily and quickly, and design components required for ground contact plate design are collected to build the database that allows easier and quicker stability review. Conclusion: The algorithms proposed in this study conduct simulations for all possible candidate cases, save the results in a database, review practical alternatives, and select the solution that minimizes cost. Developed processes are useful for analyzing correlations of mobile crane performance, ground contact and soil bearing force reinforcement designs and so forth, and for systematically selecting optimal mobile cranes.

Description: Wireless mesh networks are highly susceptible to Distributed Denial-of-Service attacks due to its self-configuring property. Flooding DDOS attack is one form of collaborative attacks and the transport layer of such networks are extremely affected. In this paper we propose ColShield, an effective and collaborative protection shield which not only detects flooding attacks but also prevents the flooding attacks through clever spoof detection. ColShield consists of Intrusion Protection and Detection Systems (IPDS) located at various points in the network which collaboratively defend flooding attacks. ColShield detects the attack node and its specific port number under attack. In order to reduce the burden on a single global IPDS, the system uses several local IPDS for the collaborative mitigation of flooding attacks. The evaluation of ColShield is done using extensive simulations and is proved to be effective in terms of false positive ratio, packet delivery ratio, communication overhead and attack detection time.

Description: Background: Pipeline maintenance is becoming an important issue in modern construction and building information model (BIM) research. An understanding of pipeline accessibility considerations in terms of operation and maintenance is essential for planning and management. Previous studies have highlighted the complexity of multi-pipes including mechanical, electrical and plumbing (MEP) pipelines and the importance of information visualization, but few have proposed a way to consider accessibility problems during operation and maintenance. Methods: Therefore, this study develops a systematic method to evaluate accessibility with respect to pipeline maintenance. We first divided pipeline accessibility into three categories: (1) visual accessibility—the visibility for an inspector to view; (2) approachable accessibility—the difficulty for an inspector to approach; and (3) operational accessibility—the pipeline that can be operated by the inspectors. We created mathematical models and discussed the ergonomic details about each category. We then developed a user interface, VAO Checker, in which V, A and O stand for visual, approachable and operational respectively, to display visual information about pipeline accessibility. Through instantaneous analysis, the system visualizes the accessibility of the pipelines. We visually represent the intersection and union of these three categories to illustrate the varying accessibility of pipe elements. Results: A usability test was conducted to validate the system’s effectiveness. The results of the usability analysis show that users have higher correctness when using VAO Checker than 2D plan drawing and 3D model, and they evaluate the performance of this tool better than 2D plan drawing. Conclusion: Pipeline designers can benefit by using this tool to sketch a suitable traffic flow for engineers to investigate. Furthermore, the substantial amount of information saved in the layout database could be referenced for future optimization.

Description: Current research on fear of crime reveals a recurrent theme of disorder in explanations of fear of crime and perceptions of security. This disorder is scalable, ranging from proximal cues associated with specific encounters between people or defined micro locations through to distal feelings of fear about areas, activity nodes, or major pathways. The research presented here compares two samples (n = 235) of businesses surveyed during the summer of 2012 in Grandview-Woodland, a diverse neighborhood, in the City of Vancouver, Canada. A visualization technique is presented to demonstrate how aggregate cognitive maps about perception of crime can be created and used by civic agencies when determining strategies aimed at reducing fear of crime. The results show that although both samples are taken from the same geographical neighborhood, their specific location within the community generates two very distinct perceptual patterns. Differences between the impact of proximal and distal cues on perception is explored. Other variations in perception are studied including differences between males and females, business owners and employees and those who have been victims of property crime versus personal crime. The results are presented and future research directions discussed.

Description: This paper addresses cognitive implications and research needs surrounding the problem of cyber friendly fire (FF). We define cyber FF as intentional offensive or defensive cyber/electronic actions intended to protect cyber systems against enemy forces or to attack enemy cyber systems, which unintentionally harms the mission effectiveness of friendly or neutral forces. We describe examples of cyber FF and discuss how it fits within a general conceptual framework for cyber security failures. Because it involves human failure, cyber FF may be considered to belong to a sub-class of cyber security failures characterized as unintentional insider threats. Cyber FF is closely related to combat friendly fire in that maintaining situation awareness (SA) is paramount to avoiding unintended consequences. Cyber SA concerns knowledge of a system’s topology (connectedness and relationships of the nodes in a system), and critical knowledge elements such as the characteristics and vulnerabilities of the components that comprise the system and its nodes, the nature of the activities or work performed, and the available defensive and offensive countermeasures that may be applied to thwart network attacks. We describe a test bed designed to support empirical research on factors affecting cyber FF. Finally, we discuss mitigation strategies to combat cyber FF, including both training concepts and suggestions for decision aids and visualization approaches.

Description: Background: Pipeline maintenance is becoming an important issue in modern construction and building information model (BIM) research. An understanding of pipeline accessibility considerations in terms of operation and maintenance is essential for planning and management. Previous studies have highlighted the complexity of multi-pipes including mechanical, electrical and plumbing (MEP) pipelines and the importance of information visualization, but few have proposed a way to consider accessibility problems during operation and maintenance. Methods: Therefore, this study develops a systematic method to evaluate accessibility with respect to pipeline maintenance. We first divided pipeline accessibility into three categories: (1) visual accessibility?the visibility for an inspector to view; (2) approachable accessibility?the difficulty for an inspector to approach; and (3) operational accessibility?the pipeline that can be operated by the inspectors. We created mathematical models and discussed the ergonomic details about each category. We then developed a user interface, VAO Checker, in which V, A and O stand for visual, approachable and operational respectively, to display visual information about pipeline accessibility. Through instantaneous analysis, the system visualizes the accessibility of the pipelines. We visually represent the intersection and union of these three categories to illustrate the varying accessibility of pipe elements. Results: A usability test was conducted to validate the system?s effectiveness. The results of the usability analysis show that users have higher correctness when using VAO Checker than 2D plan drawing and 3D model, and they evaluate the performance of this tool better than 2D plan drawing. Conclusion: Pipeline designers can benefit by using this tool to sketch a suitable traffic flow for engineers to investigate. Furthermore, the substantial amount of information saved in the layout database could be referenced for future optimization.

Description: This paper adopts the metaphor of representational fluency and proposes an auto linking approach to help analysts investigate details of suspicious sections across different cybersecurity visualizations. Analysis of spatiotemporal network security data takes place both conditionally and in sequence. Many visual analytics systems use time series curves to visualize the data from the temporal perspective and maps to show the spatial information. To identify anomalies, the analysts frequently shift across different visualizations and the original data view. We consider them as various representations of the same data and aim to enhance the fluency of navigation across these representations. With the auto linking mechanism, after the analyst selects a segment of a curve, the system can automatically highlight the related area on the map for further investigation, and the selections on the map or the data views can also trigger the related time series curves. This approach adopts the slicing operation of the Online Analytical Process (OLAP) to find the basic granularities that contribute to the overall value change. We implemented this approach in an award-winning visual analytics system, SemanticPrism, and demonstrate the functions through two use cases.

Description: Human face processing and evaluation is a problem due to variations in orientation, size, illumination, expression, and disguise. The goal of this work is threefold. First, we aim to show that the variant of polar transformation can be used to register face images against changes in pose and size. Second, implementation of fusion of thermal and visual face images in the wavelet domain to handle illumination and disguise and third, principal component analysis is applied in order to tackle changes due to expressions up to a particular extent of degrees. Finally, a multilayer perceptron has been used to classify the face image. Several techniques have been implemented here to depict an idea about improvement of results. Methods started from the simplest design, without registration; only combination of PCA and MLP as a method for dimensionality reduction and classification respectively to the range of adaptive polar registration, fusion in wavelet transform domain and final classification using MLP. A consistent increase in recognition performance has been observed. Experiments were conducted on two separate databases and results yielded are very much satisfactory for adaptive polar registration along with fusion of thermal and visual images in the wavelet domain.

Description: The idea of multiple antenna arrays has evolved into multiple-input multiple-output (MIMO) system, which provides transmit and receive diversities. It increases robustness of the effect of multipath fading in wireless channels, besides yielding higher capacity, spectral efficiency and better bit error rate (BER) performance. The spatial diversity gain is obtained by transmitting or receiving multiple copies of a signal through different antennas to combat fading and improves the system BER performance. However, the computational complexity of MIMO system is inevitably increased. Space-time coding (STC) technique such as Alamouti’s space-time block code (STBC) that combines coding, modulation and signal processing has been used to achieve spatial diversity. Vertical Bell Laboratories Layered Space-Time (V-BLAST) uses antenna arrays at both the transmitter and receiver to achieve spatial multiplexing gain. Independent data streams that share both frequency bands and time slots are transmitted from multiple antennas and jointly detected at the receiver. The theoretical capacity of V-BLAST increases linearly with the number of antennas in rich scattering environments. It's well-known that maximization of spatial diversity gain leads to degradation of spatial multiplexing gain or vice versa. In order to achieve spatial multiplexing and diversity gains simultaneously, the V-BLAST/STBC scheme has been introduced. This hybrid scheme increases MIMO system capacity and maintains reliable BER performance at the same time. However, both V-BLAST and STBC layers, in this hybid scheme, assume each other as an interferer. Thus, the symbols must be decoded with a suitable detection mechanism. In this paper, a new low complexity detection mechanism for V-BLAST/STBC scheme based on QR decomposition, denoted as low complexity QR (LC-QR) decomposition, is presented. The performance of the proposed LC-QR decomposition detection mechanism in V-BLAST/STBC transceiver scheme is compared with other detection mechanisms such as ZF, MMSE and QR decomposition. It is shown that the BER performance in V-BLAST/STBC scheme is better than V-BLAST scheme while its system capacity is higher than orthogonal STBC scheme when the LC-QR decomposition detection mechanism is exploited. Moreover, the computational complexity of proposed LC-QR decomposition mechanism is significantly lower than other abovementioned detection mechanisms.

Description: In this paper, a novel approach for head pose estimation in gray-level images is presented. In the proposed algorithm, two techniques were employed. In order to deal with the large set of training data, the method of Random Forests was employed; this is a state-of-the-art classification algorithm in the field of computer vision. In order to make this system robust in terms of illumination, a Binary Pattern Run Length matrix was employed; this matrix is combination of Binary Pattern and a Run Length matrix. The binary pattern was calculated by randomly selected operator. In order to extract feature of training patch, we calculate statistical texture features from the Binary Pattern Run Length matrix. Moreover we perform some techniques to real-time operation, such as control the number of binary test. Experimental results show that our algorithm is efficient and robust against illumination change.

Description: Background: An extensive body of knowledge indicated the positive impact of the Advanced Computer based Management Systems (ACMS) on various aspects of project management, while highlighting barriers that hinder adoption, diffusion, and utilization of the ACMS by the construction industries around the world. Remote projects have their unique management problems and these are caused mainly by the remoteness of the project. Little research was undertaken concerning this issue, particularly in the Persian Gulf region, and it has highlighted few unique communications and management problems such as the loose control, lack of human resources, infrastructure and experience. Methods: This research investigated the use of ACMS by large companies in the Eastern province, Kingdom of Saudi Arabia (KSA), and how it would help these companies sorting out a number of present projects' management problems. Subsequently, a field study i.e. a questionnaire survey and interviews was carried out.Result: The field study revealed significant association between frequent management problems with little use of ACMS and the domination of use of traditional communications and management systems. This paper argues that the use of traditional systems and the traditional way of sorting out construction problems limit the applicability of ACMS. Conclusion: The present researchers recommend the use of customized ACMS associated with the application of lean and sustainable management principals as these would help overcoming barriers and providing intelligent solution for the strategic, technical, and social issues of the remote construction sites.

Description: Insurgency emerges from many interactions between numerous social, economical, and geographical factors. Adequately accounting for the large number of potentially relevant interactions, and the complex ways in which they operate, is key to creating valuable models of insurgency. However, this has long been a challenging endeavour, as insurgency imposes specific limitations on the data that could speak to these interactions: quantitative data is limited by the difficulties of systematic collection in war, while qualitative data may include vague or conflicting insights from direct observers. In this paper, we designed a computational framework based on Fuzzy Cognitive Maps and Complex Networks to face these limitations. A software solution fully implements this framework and allows analysts to conduct simulations, in order to better understand the current dynamics of insurgency or test 'what-if' scenarios. Two approaches are presented to guide analysts in developing models based on our framework, either through a nuanced reading of the literature, or by aggregating the knowledge of domain experts.

Description: Wireless Mesh Networks (WMNs) distinguish for their low cost nature that makes them very attractive for providing wireless Internet connectivity. Such infrastructures can be used to deploy community networks, metropolitan area networks, municipal and corporative networks, and to support applications for urban areas, medical, transport and surveillance systems. The main issues in WMNs are achievement of network connectivity and stability as well as QoS in terms of user coverage. In this paper, we deal with the effect of changes in population size and number of generations for node placement problem in WMNs for Normal distribution of mesh clients. We consider two population sizes 8 and 512 and for every population size the number of generations are 200 and 20,000. As evaluation metrics we used size of giant component and number of covered users. The simulation results have shown that the increase of the population size results in better performance. Best results are obtained for the number of generation 20,000. However, when the number of generation is increased, the computation time is also increased.

Description: No description available

Description: Background: In a construction site, the safety of workers can be better secured if vehicle or robot can be properly maneuvered by using image-based gesture guidance. This kind of semi-automatic motion control is based on the features extracted in colors, outlines, textures, and motion intentions. Among these features, detecting worker?s skin color on face and hands could serve as an essential method for enabling robot to determine the region of interest (ROI). However, the performance of skin detection is usually unreliable due to interferences from reflections and shadows. Although many efficient skin color detection methods had been developed in past years, those are mostly based on complicated learning and statistical processes and are unsuitable for embedded systems. The exploration of a concise and efficient skin color detector, therefore, becomes a challenge for applications in mobile robots.MethodIn this paper, we propose a novel adaptive skin detector on face and hands as a fundamental capability of a gesture tracking system. This approach enhances the detection performance of traditional HSV color space but only requires a low computing power. For the design criteria of small size, low-power, low-cost, and minimum computing resource usages on mobile robots, the entire detecting system is built on single field-programmable-gate-array (FPGA) chip. Meanwhile, besides the contributions of adaptive algorithms and FPGA chip designs, the proposed skin detector also employs a touch screen to designate expected skin color of worker as the human-robot interaction (HRI) in real-time. Results: The chip design of the FPGA is based on hardware circuits in register-transfer-level (RTL) for real-time image processing. A reasonable amount of hardware resource usages of FPGA have consumed 8% of logic elements (LEs) and 1.4% for embedded random access memory (RAM). Demonstrations with various pictures had indicated that sufficient ROI can be efficiently identified by using the proposed adaptive skin color detector. Conclusions: According to our experimental results, the proposed adaptive skin detection can work well for non-ideal illumination. It has demonstrated the reliability and feasibility on supporting the embedded robotic control in the future.

Description: Background: Poor engineering information provided to construction crews results in inefficient communication of design, leading to construction rework, disputes, and lower worker morale. The resulting errors, omissions, and misinterpretations indicates that a significant opportunity exists to improve the traditional documentation of engineering information that craft professionals use to complete their work. Historically, physical three dimensional (3D) models built by hand provided 3D physical representations of the project to assist in sequencing, visualization, and planning of critical construction activities. This practice has greatly diminished since the adoption of three dimensional CAD (computer-aided design) and BIM (building information modeling) technologies. Recently, additive manufacturing technologies have allowed for three dimensional printing of 3D CAD models. Methods: The effectiveness of 2D drawings, a 3D computer model, and a 3D printed model in delivering engineering information to an end-user are scientifically measured. Results: The 3D printed model outperformed the 2D drawings and 3D computer interface in productivity and workload measures. Conclusions: A physical model has the ability to improve communication of spatial design for certain tasks. This could lead to improved productivity, reduction of errors, and better quality for construction tasks. This paper?s primary contribution to the body of knowledge is that it identifies how different mediums of engineering information impact the communication of spatial engineering information.

Description: Background: Recently multi-use environmental sensors became affordable and easy to control. This improvement enabled us to measure the broad range of indoor environments by using low-priced and controllable sensor devices. As the data set acquired by widely installed environmental sensors increased significantly, the need for making effective use of the data has become of importance. We developed an integrated visualization mechanism to express larger amounts of sensor data.MethodThe mechanism for visualization on floor plan described in this paper consists of the following modules: 1) the sensor module; 2) the data collection module; 3) the data processing module; 4) the spatial data module; 5) the sensor location module; and 6) the data visualization module. A demonstration following the mechanism is introduced in this paper for evaluating the integrated visualization approach. We set up a test-purposed and versatile toolkit that is cheaper, smaller and more controllable than conventional tools. We collect indoor environmental data set composed of sequential numeric data so as to use them as parameters for visualization. We inspected three major issues in the process: 1) indoor temperature data of a specific room collected at a second interval; 2) such a data set can be varied by subdivided spots of interest using multiple toolkits; 3) as a result, the collection of data is regarded as one type of parameter for visualization on top of the room?s floor plan, e.g. a sudden change of sequential numbers. Results: Indoor environment such as temperature changes are shown as colors overlapped on the floor plan. In this way it may be easier to understand the state of indoor environment and factors which influence the environment. The floor plan based visualization of an indoor environmental element seems intuitive compared to just listing the numeric information. Conclusion: This paper introduces and demonstrates an integrated approach for visualizing the indoor environment on a floor plan with an actual test case. Combined with the building model, the visualized data can be used for recognition of the factors affecting to the target environmental element. We expect floor plan-based visualization to be used for decision-making.

Description: Teams are at the heart of today’s organizations and their performance is crucial for organizational success. It is therefore important to understand and monitor team processes. Traditional approaches employ questionnaires, which have low temporal resolution or manual behavior observation, which is labor intensive and thus costly. In this work, we propose to apply mobile behavior sensing to capture team coordination processes in an automatic manner, thereby enabling cost-effective and real-time monitoring of teams. In particular, we use the built-in sensors of smartphones to sense interpersonal body movement alignment and to detect moving sub-groups. We aggregate the data on team level in form of networks that capture a) how long team members are together in a sub-group and b) how synchronized team members move. Density and centralization metrics extract team coordination indicators from the team networks. We demonstrate the validity of our approach in firefighting teams performing a realistic training scenario and investigate the link between the coordination indicators and team performance as well as experienced team coordination. Our method enables researchers and practitioners alike to capture temporal and spatial team coordination automatically and objectively in real-time.

Description: As mobile technologies become widespread, new challenges are facing the research community to develop lightweight learning services adapted to the learner’s profile, context, and task at hand. This paper attempts to solve some of these challenges by proposing a knowledge-driven recommender for mobile learning on the Semantic Web. The contribution of this work is an approach for context integration and aggregation using an upper ontology space and a unified reasoning mechanism to adapt the learning sequence and the learning content based on the learner’s activity, background, used technology, and surrounding environment. Whenever context change occurs, the system identifies the new contextual features and translates them into new adaptation constraints in the operating environment. The proposed system has been implemented and tested on various mobile devices. The experimental results show many learning scenarios to demonstrate the usefulness of the system in practice.

Description: With the increasing application of wireless communication devices, mobile phone handsets are used by peoples of various age groups. This paper make an effort to asses the mobile phone radiation exposure effect on 4 years old, 8 years old children and an adult head model. Here, human head is modeled as a three layered sphere composed of skin, skull and brain. Hand held device model (with and without resistive sheet) having dipole antenna enclosed by plastic cover is used for human interaction. The software simulation performed by General Electro Magnetic Simulator, based on Finite Difference Time Domain technique yields Specific Absorption Rate and 3D-thermal distribution on spherical human head. Comparison of 1 g SAR, 10 g SAR values for adult and children head show that, children head absorbs more power than adult. Further, the application of resistive sheet on handset shows effective decrement in coupled power.

Description: This study is a successful proof of concept of using automated text analysis to accurately classify transcribed 911 homicide calls according to their veracity. Fifty matched, caller-side transcripts were labeled as truthful or deceptive based on the subsequent adjudication of the cases. We mined the transcripts and analyzed a set of linguistic features supported by deception theories. Our results suggest that truthful callers display more negative emotion and anxiety and provide more details for emergency workers to respond to the call. On the other hand, deceivers attempt to suppress verbal responses by using more negation and assent words. Using these features as input variables, we trained and tested several machine-learning classification algorithms and compared the results with the output from a statistical classification technique, discriminant analysis. The overall performance of the classification techniques was as high as 84% for the cross-validated set. The promising results of this study illustrate the potential of using automated linguistic analyses in crime investigations.

Description: We study the survivable network design problem (SNDP) for simultaneous unicast and anycast flows in networks where the link cost follows All Capacities Modular Cost (ACMC) model. Given a network modeled by a connected, undirected graph and a set of flow demands, this problem aims at finding a set of connections with a minimized network cost in order to protect the network against any single failure. This paper proposes a new Genetic Algorithm with an efficient encoding to solve the SNDP in networks with ACMC model (A-SNDP). Our encoding scheme is simple and allows large search space. Extensive simulation results on real large topology instances show that the proposed algorithm is much more efficient than the Tabu Search and other conventional Genetic Algorithm in terms of minimizing the network cost.

Description: One of the key factors influencing how people react to and behave during a crisis is their digital or non-digital social network, and the information they receive through this network. Publicly available online social media sites make it possible for crisis management organizations to use some of these experiences as input for their decision-making. We describe a methodology for collecting a large number of relevant tweets and annotating them with emotional labels. This methodology has been used for creating a training dataset consisting of manually annotated tweets from the Sandy hurricane. Those tweets have been utilized for building machine learning classifiers able to automatically classify new tweets. Results show that a support vector machine achieves the best results with about 60% accuracy on the multi-classification problem. This classifier has been used as a basis for constructing a decision support tool where emotional trends are visualized. To evaluate the tool, it has been successfully integrated with a pan-European alerting system, and demonstrated as part of a crisis management concept during a public event involving relevant stakeholders.

Description: Global competition and the transdisciplinary nature of evolving Architecture-Engineering-Construction (AEC) activities makes it progressively important to educate new AEC professionals with appropriate skill sets. These skills include the ability and capability of not only developing routine projects, but also delivering novel design solutions and construction processes (some of which may be unknown), to feasible, surprising, or potentially patentable solutions. For example, despite recent innovations in immersive visualisation technologies and tele-presence decision-support toolkits, the AEC sector as a whole has not yet fully understood these technologies, nor embraced them as an enabler. Given this, this paper proposes a new approach for delivering education and training to address this shortcoming. This approach focuses on doing traditional (routine) work with creative thinking in order to address these challenges. This rationale is based on the principles of Successful Education as a new paradigm for engineering education, which is inspired by the Theory of Successful Intelligence, by the Medici Effect and Leonardo da Vinci's Seven Principles. The paper presents the educating AEC professionals is presented the AEC sector. The Theory of Successful Intelligence and its three forms of intelligence (Practical, Analytical, and Creative), are supported by lessons learned from the Renaissance, including the Medici Effect and da Vinci's Seven Principles. Based on these theoretical pillars, a new approach to educating AEC professionals is presented with a proof-of-concept prototype that uses a game-like virtual reality (VR) visualisation interface supported by Mind Mapping is introduced as an exemplar. The developed interface in this study applies Game Theory to non-collocated design teams in accordance with Social Sciences Theory (social rules) and Behavioural Science Theory (decision making). It contributes by supporting new insights into AEC actor involvement, pedagogy, organisational behaviour, and the social constructs that support decision making.

Description: Background: Children are very curious. They like to play games but lack reading fluency. Conventional interfaces for information-seeking in digital libraries are unsuitable for children because they are rigid, text-based, and task-oriented. Thus, this study developed a customized interface for a digital library. To facilitate children in online searches, the design concepts included user-friendly target icons, icon recognition, and way-finding in a two-dimensional visualized environment. Methods: In this study, the criteria used to develop visualization tools that children can use for information retrieval were based on theories of human perception related to graphical interfaces for information visualization systems, including iconic representations and information density on visualized displays. Databases widely used by children in the National Library of Public Information were linked to the suggested database frame. The database frame was classified into five major subject categories: Natural Sciences, Fine Arts and Music, Health and Athletics, History and Culture, and Treasure of Knowledge. The web interface was designed according to way-finding concepts and map-structure hierarchies. Information searches in the main frame, sub-frames, and linked database were designed to be simple and intuitive for use by children. Results: Information search efficiency was measured in 104 children assigned to search the virtual environment for icons (databases) that adequately supported their studies. Statistical analyses showed that, compared to the text-lined interface, the graphical interface improved the success and speed of searches by children. Conclusions: Incorporating theories of spatial memory and representative icons in designs for visualized retrieval systems helps children to recognize different categories of knowledge content and improves their efficiency in information retrieval. To improve database search efficiency in children, information recommendation issues require further study. However, further research is also needed to identify factors that affect patterns of information-seeking behavior in children.

Description: Training Programs to enhance Math Solving Skills, Memory, Visualization, etc in children are gaining popularity worldwide. Any skill is better acquired, when attention, the basic cognitive ability of the trainee is improved. This study makes an attempt to devise a technique in the form of a Brain Computer Interface (BCI) Game, to assist the trainers in monitoring and evaluating the attention levels of the trainees, at regular intervals during the training period.The gaming environment is designed using Open Source Graphics Library (OpenGL) package and the game control is through the player’s brain waves using the BCI technology. The players control the movement of an object from a source to a destination location on the screen by focussing their thought processes. The time taken to complete one game can be recorded. More the time taken, lesser would be the attention sustaining capacity of the player.Thirteen subjects under different levels of the ABACUS Math Solving training program controlled the ball movement while solving math problems mentally, the time taken reduced for most of the subjects as they reached higher levels of their training course, indicating the benefit of such training programmes. The game was also played by eight non-abacus literates. The evaluation procedure was found to be very easy and fast.