Query: Privacy preserving big data mining: association rule hiding using fuzzy logic approach

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Data-intensive applications, challenges, techniques and technologies: A survey on Big Data <=SEP=> It is already true that Big Data has drawn huge attention from researchers in information sciences, policy and decision makers in governments and enterprises. As the speed of information growth exceeds Moore’s Law at the beginning of this new century, excessive data is making great troubles to human beings. However, there are so much potential and highly useful values hidden in the huge volume of data. A new scientific paradigm is born as dataintensive scientific discovery (DISD), also known as Big Data problems. A large number of fields and sectors, ranging from economic and business activities to public administration, from national security to scientific researches in many areas, involve with Big Data problems. On the one hand, Big Data is extremely valuable to produce productivity in businesses and evolutionary breakthroughs in scientific disciplines, which give us a lot of opportunities to make great progresses in many fields. There is no doubt that the future competitions in business productivity and technologies will surely converge into the Big Data explorations. On the other hand, Big Data also arises with many challenges, such as difficulties in data capture, data storage, data analysis and data visualization. This paper is aimed to demonstrate a close-up view about Big Data, including Big Data applications, Big Data opportunities and challenges, as well as the state-of-the-art techniques and technologies we currently adopt to deal with the Big Data problems. We also discuss several underlying methodologies to handle the data deluge, for example, granular computing, cloud computing, bio-inspired computing, and quantum computing. 2014 Elsevier Inc. All rights reserved.

Data quality management, data usage experience and acquisition intention of big data analytics <=SEP=> Big data analytics associated with database searching, mining, and analysis can be seen as an innovative IT capability that can improve firm performance. Even though some leading companies are actively adopting big data analytics to strengthen market competition and to open up new business opportunities, many firms are still in the early stage of the adoption curve due to lack of understanding of and experience with big data. Hence, it is interesting and timely to understand issues relevant to big data adoption. In this study, a research model is proposed to explain the acquisition intention of big data analytics

The 8 requirements of real-time stream processing <=SEP=> Applications that require real-time processing of high-volume data steams are pushing the limits of traditional data processing infrastructures. These stream-based applications include market feed processing and electronic trading on Wall Street, network and infrastructure monitoring, fraud detection, and command and control in military environments. Furthermore, as the "sea change" caused by cheap micro-sensor technology takes hold, we expect to see everything of material significance on the planet get "sensor-tagged" and report its state or location in real time. This sensorization of the real world will lead to a "green field" of novel monitoring and control applications with high-volume and low-latency processing requirements.Recently, several technologies have emerged---including off-the-shelf stream processing engines---specifically to address the challenges of processing high-volume, real-time data without requiring the use of custom code. At the same time, some existing software technologies, such as main memory DBMSs and rule engines, are also being "repurposed" by marketing departments to address these applications.In this paper, we outline eight requirements that a system software should meet to excel at a variety of real-time stream processing applications. Our goal is to provide high-level guidance to information technologists so that they will know what to look for when evaluation alternative stream processing solutions. As such, this paper serves a purpose comparable to the requirements papers in relational DBMSs and on-line analytical processing. We also briefly review alternative system software technologies in the context of our requirements.The paper attempts to be vendor neutral, so no specific commercial products are mentioned.

Data privacy through optimal k-anonymization <=SEP=> Data de-identification reconciles the demand for release of data for research purposes and the demand for privacy from individuals. This paper proposes and evaluates an optimization algorithm for the powerful de-identification procedure known as k-anonymization. A k-anonymized dataset has the property that each record is indistinguishable from at least k - 1 others. Even simple restrictions of optimized k-anonymity are NP-hard, leading to significant computational challenges. We present a new approach to exploring the space of possible anonymizations that tames the combinatorics of the problem, and develop data-management strategies to reduce reliance on expensive operations such as sorting. Through experiments on real census data, we show the resulting algorithm can find optimal k-anonymizations under two representative cost measures and a wide range of k. We also show that the algorithm can produce good anonymizations in circumstances where the input data or input parameters preclude finding an optimal solution in reasonable time. Finally, we use the algorithm to explore the effects of different coding approaches and problem variations on anonymization quality and performance. To our knowledge, this is the first result demonstrating optimal k-anonymization of a non-trivial dataset under a general model of the problem.

Privacy-preserving trajectory data publishing by local suppression <=SEP=> The pervasiveness of location-aware devices has spawned extensive research in trajectory data mining, resulting in many important real-life applications. Yet, the privacy issue in sharing trajectory data among different parties often creates an obstacle for effective data mining. In this paper, we study the challenges of anonymizing trajectory data: high dimensionality, sparseness, and sequentiality. Employing traditional privacy models and anonymization methods often leads to low data utility in the resulting data and ineffective data mining. In addressing these challenges, this is the first paper to introduce local suppression to achieve a tailored privacy model for trajectory data anonymization. The framework allows the adoption of various data utility metrics for different data mining tasks. As an illustration, we aim at preserving both instances of location-time doublets and frequent sequences in a trajectory database, both being the foundation of many trajectory data ∗Corresponding author Email addresses: ru_che@encs.concordia.ca (Rui Chen), fung@ciise.concordia.ca (Benjamin C. M. Fung), no_moham@encs.concordia.ca (Noman Mohammed), bcdesai@cs.concordia.ca (Bipin C. Desai) Preprint submitted to Information Sciences April 10, 2011 mining tasks. Our experiments on both synthetic and real-life data sets suggest that the framework is effective and efficient to overcome the challenges in trajectory data anonymization. In particular, compared with the previous works in the literature, our proposed local suppression method can significantly improve the data utility in anonymous trajectory data.

Scholarly use of information: graduate students' information seeking behaviour <=SEP=> Introduction. This study explored graduate students' information behaviour related to their process of inquiry and scholarly activities. Method. In depth, semi-structured interviews were conducted with one hundred graduate students representing all disciplines and departments from Carnegie Mellon University. Analysis. Working in pairs, we coded transcripts of interviews into meaningful categories using ATLAS.ti software. The combined use of quantitative and qualitative analysis aimed to reduce subjectivity. Results. Graduate students often begin with a meeting with professors who provide direction, recommend and provide resources. Other students help to shape graduate students' research activities, and university library personnel provide guidance in finding resources. The Internet plays a major role, although students continue to use print resources. Convenience, lack of sophistication in finding and using resources and course requirements affect their information behaviour. Findings vary across disciplines and between programmes. Conclusion. Libraries can influence students' information behaviour by re-evaluating their instructional programmes and provision of resources and services. They can take a lead by working with academic staff to guide students.

Music and language side by side in the brain: a PET study of the generation of melodies and sentences. <=SEP=> Parallel generational tasks for music and language were compared using positron emission tomography. Amateur musicians vocally improvised melodic or linguistic phrases in response to unfamiliar, auditorily presented melodies or phrases. Core areas for generating melodic phrases appeared to be in left Brodmann area (BA) 45, right BA 44, bilateral temporal planum polare, lateral BA 6, and pre-SMA. Core areas for generating sentences seemed to be in bilateral posterior superior and middle temporal cortex (BA 22, 21), left BA 39, bilateral superior frontal (BA 8, 9), left inferior frontal (BA 44, 45), anterior cingulate, and pre-SMA. Direct comparisons of the two tasks revealed activations in nearly identical functional brain areas, including the primary motor cortex, supplementary motor area, Broca's area, anterior insula, primary and secondary auditory cortices, temporal pole, basal ganglia, ventral thalamus, and posterior cerebellum. Most of the differences between melodic and sentential generation were seen in lateralization tendencies, with the language task favouring the left hemisphere. However, many of the activations for each modality were bilateral, and so there was significant overlap. While clarification of this overlapping activity awaits higher-resolution measurements and interventional assessments, plausible accounts for it include component sharing, interleaved representations, and adaptive coding. With these and related findings, we outline a comparative model of shared, parallel, and distinctive features of the neural systems supporting music and language. The model assumes that music and language show parallel combinatoric generativity for complex sound structures (phonology) but distinctly different informational content (semantics).

Two-factor authentication for the Bitcoin protocol <=SEP=> We show how to realize two-factor authentication for a Bitcoin wallet. To do so, we explain how to employ an ECDSA adaption of the two-party signature protocol by MacKenzie and Reiter (Int J Inf Secur 2(3–4):218–239, 2004. doi: 10.1007/s10207-004-0041-0 ) in the context of Bitcoin and present a prototypic implementation of a Bitcoin wallet that offers both: two-factor authentication and verification over a separate channel. Since we use a smart phone as the second authentication factor, our solution can be used with hardware already available to most users and the user experience is quite similar to the existing online banking authentication methods.

Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters <=SEP=> Although molecular dynamics (MD) simulations of biomolecular systems often run for days to months, many events of great scientific interest and pharmaceutical relevance occur on long time scales that remain beyond reach. We present several new algorithms and implementation techniques that significantly accelerate parallel MD simulations compared with current state-of-the-art codes. These include a novel parallel decomposition method and message-passing techniques that reduce communication requirements, as well as novel communication primitives that further reduce communication time. We have also developed numerical techniques that maintain high accuracy while using single precision computation in order to exploit processor-level vector instructions. These methods are embodied in a newly developed MD code called Desmond that achieves unprecedented simulation throughput and parallel scalability on commodity clusters. Our results suggest that Desmond's parallel performance substantially surpasses that of any previously described code. For example, on a standard benchmark, Desmond's performance on a conventional Opteron cluster with 2K processors slightly exceeded the reported performance of IBM's Blue Gene/L machine with 32K processors running its Blue Matter MD code.

Cellular IP: a new approach to Internet host mobility <=SEP=> This paper describes a new approach to Internet host mobility. We argue that by separating local and wide area mobility, the performance of existing mobile host protocols (e.g. Mobile IP) can be significantly improved. We propose Cellular IP, a new lightweight and robust protocol that is optimized to support local mobility but efficiently interworks with Mobile IP to provide wide area mobility support. Cellular IP shows great benefit in comparison to existing host mobility proposals for environments where mobile hosts migrate frequently, which we argue, will be the rule rather than the exception as Internet wireless access becomes ubiquitous. Cellular IP maintains distributed cache for location management and routing purposes. Distributed paging cache coarsely maintains the position of 'idle' mobile hosts in a service area. Cellular IP uses this paging cache to quickly and efficiently pinpoint 'idle' mobile hosts that wish to engage in 'active' communications. This approach is beneficial because it can accommodate a large number of users attached to the network without overloading the location management system. Distributed routing cache maintains the position of active mobile hosts in the service area and dynamically refreshes the routing state in response to the handoff of active mobile hosts. These distributed location management and routing algorithms lend themselves to a simple and low cost implementation of Internet host mobility requiring no new packet formats, encapsulations or address space allocation beyond what is present in IP.

Real-time pen-and-ink illustration of landscapes <=SEP=> Non-photorealistic rendering has been proven to be particularly efficient in conveying and transmitting selected visual information. Our paper presents a NPR rendering pipeline that supports pen-and-ink illustration for, but not limited to, complex landscape scenes in real time. This encompasses a simplification framework using clustering which enables new approaches to efficient and coherent rendering of stylized silhouettes, hatching and abstract shading. Silhouette stylization is performed in image-space. This avoids explicit computation of connected lines. Further, coherent hatching of the tree foliage is performed using an approximate view-dependent parameterization computed on-the-fly within the same simplification framework. All NPR algorithms are integrated with photorealistic rendering, allowing seamless transition and combination between a variety of photorealistic and non-photorealistic drawing styles.

Planar Array Antennas with Travelling-Wave Excitation in Millimeter-Wave Band <=SEP=> あらまし ミリ波の周波数帯において指向性走査可能な平面アンテナが望まれている.本論文では,ミリ波の 代表的な二つの平面アンテナである導波管アンテナとマイクロストリップアンテナについて,開発した平面アン テナを紹介する.ペンシルビームが必要な機械走査型アンテナに適した二次元導波管アレーアンテナと,複数の サブアレーの配列からなる電子走査方式のサブアレー平面アンテナ用に,導波管アレーアンテナとマイクロスト リップコムラインアンテナについて開発した例を示す.これらについて,各放射素子で反射特性を低減すること が,特性の向上・設計自由度の拡大に有効であることを示す.また,これらのアンテナについて低損失に給電す る構造を示すと同時に,片端から給電するよりも,中央から給電する方が,周波数帯域幅が広くなることを示す. 更に,これらのアンテナ実現のためのキーとなる進行波励振アレー設計技術について解説する. キーワード ミリ波,アレーアンテナ,平面アンテナ,導波管アンテナ,マイクロストリップアンテナ

Multiview Clustering via Adaptively Weighted Procrustes <=SEP=> In this paper, we make a multiview extension of the spectral rotation technique raised in single view spectral clustering research. Since spectral rotation is closely related to the Procrustes Analysis for points matching, we point out that classical Procrustes Average approach can be used for multiview clustering. Besides, we show that direct applying Procrustes Average (PA) in multiview tasks may not be optimal theoretically and empirically, since it does not take the clustering capacity differences of different views into consideration. Other than that, we propose an Adaptively Weighted Procrustes (AWP) approach to overcome the aforementioned deficiency. Our new AWP weights views with their clustering capacities and forms a weighted Procrustes Average problem accordingly. The optimization algorithm to solve the new model is computational complexity analyzed and convergence guaranteed. Experiments on five real-world datasets demonstrate the effectiveness and efficiency of the new models.

Accelerating Comparative Genomics Workflows in a Distributed Environment with Optimized Data Partitioning <=SEP=> The advent of new sequencing technology has generated massive amounts of biological data at unprecedented rates. High-throughput bioinformatics tools are required to keep pace with this. Here, we implement a workflow-based model for parallelizing the data intensive task of genome alignment and variant calling with BWA and GATK's Haplotype Caller. We explore different approaches of partitioning data and how each affect the run time. We observe granularity-based partitioning for BWA and alignment-based partitioning for Halo type Caller to be the optimal choices for the pipeline. We identify the various challenges encountered while developing such an application and provide an insight into addressing them. We report significant performance improvements, from 12 days to 4 hours, while running the BWA-GATK pipeline using 100 nodes for analyzing high-coverage oak tree data.

ARTINO: A New High Resolution 3D Imaging Radar System on an Autonomous Airborne Platform <=SEP=> The new radar system ARTINO (Airborne Radar for Three-dimensional Imaging and Nadir Observation), developed at FGAN-FHR, allows to image a direct overflown scene in three dimensions. Integrated in a small, mobile, and dismountable UAV (Unmanned Aerial Vehicle) it will be an ideal tool for various applications. This paper gives an overview about the ARTINO principle, the raw data simulation, the image formation, the technical realisation, and the status of the experimental system. I. THE ARTINO PRINCIPLE ARTINO is a new radar system integrated in a small and dismountable low-wing UAV, which allows to image the direct overflown scene in three dimensions (Figure 1). Fig. 1. Artist impression of an imaging mission using ARTINO. This new system can image the direct overflown scene in three dimensions. General side-looking SAR systems are constraint by shading effects which can hide essential information in the explored scene. The downward-looking concept of ARTINO overcomes this restriction and enables imaging of street canyons and deep terrain in mountainous areas. Moreover, the 3D imaging capability together with the small and mobile platform is an ideal tool of close in time data acquisitions of fast changing terrains, like snow slopes (danger of avalanches) and active volcanoes. This new system could be used for various applications, like DEM (Digital Elevation Model) generation, surveying, city planing, environmental monitoring, disaster relief, surveillance, and reconnaissance. In contrary to similar concepts (e.g. [1]–[3]) the ARTINO principle works with a sparse antenna array distributed along the wings, with the transmitting elements at the tips and the receiving elements in between. Virtual antenna elements are formed by the mean positions of every couple of single transmit and receive elements. Finally, one gets a fully distributed virtual antenna array. The 3D resolution cells are formed by the appliance of the synthetic aperture and a beamforming operation. A detailed description of the ARTINO principle, the used UAV (Figure 2), and the simulation of raw data can be found in [4]. The image formation using the ARTINO principle is extensively discussed in [5]. A detailed description of the technical realization and its status is given in [6]. This paper gives an overview of the concept, the processing, some first simulation results, and the technical realisation. Fig. 2. Photo of the low wing UAV ARTINO. The new radar system will be integrated in the fuselage and the wings. II. MODEL OF THE ARTINO CONCEPT A. Geometrical consideration and signal model ARTINO is supposed to fly at the altitude h along the x-axis with the velocity v. The virtual antenna is composed of Nvirt elements, which are centered at the y-axis and regularly spaced along this axis. The position of the i-th virtual antenna element with i ∈ [−Nvirt−1 2 ; Nvirt−1 2 ] is given by ηi = (x, yi, h). The transpose operator is denoted by the superscript . T denotes the pulse-to-pulse time and t the fast time. The antenna position along the x-axis at time T is given by x = v·T . Figure 3 shows the geometry of the ARTINO principle. The distance d between the virtual antenna elements was determined by simulations in order to optimize the antenna beam (reduction of grating lobes) of the whole array (Figure 4). For the demonstration of the feasibility of this new radar concept, a pulse radar is assumed. To obtain a distinct assignment of each virtual antenna element, it will be necessary for the experimental system that the real antenna elements transmit with a time multiplex from pulse to pulse. In the simulation, all virtual antenna elements transmit simultaneously. A point scatterer P is positioned at ξ = (ξx, ξy, ξz) with the reflectivity α(ξ) (Figure 3). The signal assigned to the 0-7803-9510-7/06/$20.00 © 2006 IEEE 3825 Fig. 3. Geometry for the ARTINO principle −3 −2 −1 0 1 2 3 −40 −30 −20 −10 0

A Performance Evaluation of Local Descriptors <=SEP=> 

An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometer. <=SEP=> The aim of this investigation was to develop and test two artificial neural networks (ANN) to apply to physical activity data collected with a commonly used uniaxial accelerometer. The first ANN model estimated physical activity metabolic equivalents (METs), and the second ANN identified activity type. Subjects (n = 24 men and 24 women, mean age = 35 yr) completed a menu of activities that included sedentary, light, moderate, and vigorous intensities, and each activity was performed for 10 min. There were three different activity menus, and 20 participants completed each menu. Oxygen consumption (in ml x kg(-1) x min(-1)) was measured continuously, and the average of minutes 4-9 was used to represent the oxygen cost of each activity. To calculate METs, activity oxygen consumption was divided by 3.5 ml x kg(-1) x min(-1) (1 MET). Accelerometer data were collected second by second using the Actigraph model 7164. For the analysis, we used the distribution of counts (10th, 25th, 50th, 75th, and 90th percentiles of a minute's second-by-second counts) and temporal dynamics of counts (lag, one autocorrelation) as the accelerometer feature inputs to the ANN. To examine model performance, we used the leave-one-out cross-validation technique. The ANN prediction of METs root-mean-squared error was 1.22 METs (confidence interval: 1.14-1.30). For the prediction of activity type, the ANN correctly classified activity type 88.8% of the time (confidence interval: 86.4-91.2%). Activity types were low-level activities, locomotion, vigorous sports, and household activities/other activities. This novel approach of applying ANNs for processing Actigraph accelerometer data is promising and shows that we can successfully estimate activity METs and identify activity type using ANN analytic procedures.

Crafting a multi-task CNN for viewpoint estimation <=SEP=> Convolutional Neural Networks (CNNs) were recently shown to provide state-of-theart results for object category viewpoint estimation. However different ways of formulating this problem have been proposed and the competing approaches have been explored with very different design choices. This paper presents a comparison of these approaches in a unified setting as well as a detailed analysis of the key factors that impact performance. Followingly, we present a new joint training method with the detection task and demonstrate its benefit. We also highlight the superiority of classification approaches over regression approaches, quantify the benefits of deeper architectures and extended training data, and demonstrate that synthetic data is beneficial even when using ImageNet training data. By combining all these elements, we demonstrate an improvement of approximately 5% mAVP over previous state-of-the-art results on the Pascal3D+ dataset [28]. In particular for their most challenging 24 view classification task we improve the results from 31.1% to 36.1% mAVP.

Analysis on Credit Card Fraud Detection Methods 1 <=SEP=> Due to the theatrical increase of fraud which results in loss of dollars worldwide each year, several modern techniques in detecting fraud are persistently evolved and applied to many business fields. Fraud detection involves monitoring the activities of populations of users in order to estimate, perceive or avoid undesirable behavior. Undesirable behavior is a broad term including delinquency, fraud, intrusion, and account defaulting. This paper presents a survey of current techniques used in credit card fraud detection and telecommunication fraud. The goal of this paper is to provide a comprehensive review of different techniques to detect fraud.

Improving Restaurants by Extracting Subtopics from Yelp Reviews <=SEP=> In this paper, we describe latent subtopics discovered from Yelp restaurant reviews by running an online Latent Dirichlet Allocation (LDA) algorithm. The goal is to point out demand of customers from a large amount of reviews, with high dimensionality. These topics can provide meaningful insights to restaurants about what customers care about in order to increase their Yelp ratings, which directly affects their revenue. We used the open dataset from the Yelp Dataset Challenge with over 158,000 restaurant reviews. To find latent subtopics from reviews, we adopted Online LDA, a generative probabilistic model for collections of discrete data such as text corpora. We present the breakdown of hidden topics over all reviews, predict stars per hidden topics discovered, and extend our findings to that of temporal information regarding restaurants peak hours. Overall, we have found several interesting insights and a method which could definitely prove useful to restaurant owners.

Children ’ s Eye Movements during Listening : Developmental Evidence for a Constraint-Based Theory of Sentence Processing <=SEP=> Many comprehension studies of grammatical development have focused on the ultimate interpretation that children assign to sentences and phrases, yielding somewhat static snapshots of children's emerging grammatical knowledge. Studies of the dynamic processes underlying children's language comprehension have to date been rare, owing in part to the lack of online sentence processing techniques suitable for use with children. In this chapter, we describe recent work from our research group, which examines the moment-by-moment interpretation decisions of children (age 4 to 6 years) while they listen to spoken sentences. These real-time measures were obtained by recording the children's eye movements as they visually interrogated and manipulated objects in response to spoken instructions. The first of these studies established some striking developmental differences in processing ability, with the youngest children showing an inability to use relevant properties of the referential scene to resolve temporary grammatical ambiguities (Trueswell, Sekerina, Hill, & Logrip, 1999). This finding could be interpreted as support for an early encapsulated syntactic processor that has difficulty using non-syntactic information to revise parsing commitments. However, we will review evidence from a series of follow-up experiments which suggest that this pattern arises from a developing interactive parsing system. Under this account, adult and child sentence comprehension is a " perceptual guessing game " in which multiple statistical cues are used to recover detailed linguistic structure. These cues, which include lexical-distribution evidence, verb semantic biases, and referential scene information, come " online " (become automated) at different points in the course of development. The developmental timing of these effects is related to their differential reliability and ease of detection in the input.

Development and natural history of mood disorders <=SEP=> To expand and accelerate research on mood disorders, the National Institute of Mental Health (NIMH) developed a project to formulate a strategic research plan for mood disorder research. One of the areas selected for review concerns the development and natural history of these disorders. The NIMH convened a multidisciplinary Workgroup of scientists to review the field and the NIMH portfolio and to generate specific recommendations. To encourage a balanced and creative set of proposals, experts were included within and outside this area of research, as well as public stakeholders. The Workgroup identified the need for expanded knowledge of mood disorders in children and adolescents, noting important gaps in understanding the onset, course, and recurrence of early-onset unipolar and bipolar disorder. Recommendations included the need for a multidisciplinary research initiative on the pathogenesis of unipolar depression encompassing genetic and environmental risk and protective factors. Specifically, we encourage the NIMH to convene a panel of experts and advocates to review the findings concerning children at high risk for unipolar depression. Joint analyses of existing data sets should examine specific risk factors to refine models of pathogenesis in preparation for the next era of multidisciplinary research. Other priority areas include the need to assess the long-term impact of successful treatment of juvenile depression and known precursors of depression, in particular, childhood anxiety disorders. Expanded knowledge of pediatric-onset bipolar disorder was identified as a particularly pressing issue because of the severity of the disorder, the controversies surrounding its diagnosis and treatment, and the possibility that widespread use of psychotropic medications in vulnerable children may precipitate the condition. The Workgroup recommends that the NIMH establish a collaborative multisite multidisciplinary Network of Research Programs on Pediatric-Onset Bipolar Disorder to achieve a better understanding of its causes, course, treatment, and prevention. The NIMH should develop a capacity-building plan to ensure the availability of trained investigators in the child and adolescent field. Mood disorders are among the most prevalent, recurrent, and disabling of all illnesses. They are often disorders of early onset. Although the NIMH has made important strides in mood disorders research, more data, beginning with at-risk infants, children, and adolescents, are needed concerning the etiology and developmental course of these disorders. A diverse program of multidisciplinary research is recommended to reduce the burden on children and families affected with these conditions.

Clique Graphs and Overlapping Communities <=SEP=> It is shown how to construct a clique graph in which properties of cliques of a fixed order in a given graph are represented by vertices in a weighted graph. Various definitions and motivations for these weights are given. The detection of communities or clusters is used to illustrate how a clique graph may be exploited. In particular a benchmark network is shown where clique graphs find the overlapping communities accurately while vertex partition methods fail. PACS numbers: 89.75.Hc, 89.75.Fb, 89.75.-k

Document Image Quality Assessment: A Brief Survey <=SEP=> To maintain, control and enhance the quality of document images and minimize the negative impact of degradations on various analysis and processing systems, it is critical to understand the types and sources of degradations and develop reliable methods for estimating the levels of degradations. This paper provides a brief survey of research on the topic of document image quality assessment. We first present a detailed analysis of the types and sources of document degradations. We then review techniques for document image degradation modeling. Finally, we discuss objective measures and subjective experiments that are used to characterize document image quality.

Linear codes over Z4+uZ4: MacWilliams identities, projections, and formally self-dual codes <=SEP=> Linear codes are considered over the ring Z 4 + uZ 4 , a non-chain extension of Z 4. Lee weights, Gray maps for these codes are defined and MacWilliams identities for the complete, symmetrized and Lee weight enumer-ators are proved. Two projections from Z 4 + uZ 4 to the rings Z 4 and F 2 + uF 2 are considered and self-dual codes over Z 4 +uZ 4 are studied in connection with these projections. Finally three constructions are given for formally self-dual codes over Z 4 + uZ 4 and their Z 4-images together with some good examples of formally self-dual Z 4-codes obtained through these constructions.

Online Anomaly Detection in Crowd Scenes via Structure Analysis <=SEP=> Abnormal behavior detection in crowd scenes is continuously a challenge in the field of computer vision. For tackling this problem, this paper starts from a novel structure modeling of crowd behavior. We first propose an informative structural context descriptor (SCD) for describing the crowd individual, which originally introduces the potential energy function of particle's interforce in solid-state physics to intuitively conduct vision contextual cueing. For computing the crowd SCD variation effectively, we then design a robust multi-object tracker to associate the targets in different frames, which employs the incremental analytical ability of the 3-D discrete cosine transform (DCT). By online spatial-temporal analyzing the SCD variation of the crowd, the abnormality is finally localized. Our contribution mainly lies on three aspects: 1) the new exploration of abnormal detection from structure modeling where the motion difference between individuals is computed by a novel selective histogram of optical flow that makes the proposed method can deal with more kinds of anomalies; 2) the SCD description that can effectively represent the relationship among the individuals; and 3) the 3-D DCT multi-object tracker that can robustly associate the limited number of (instead of all) targets which makes the tracking analysis in high density crowd situation feasible. Experimental results on several publicly available crowd video datasets verify the effectiveness of the proposed method.

BER analysis of optical eU-OFDM transmission over AWGN <=SEP=> Enhanced unipolar orthogonal frequency-division multiplexing (eU-OFDM) was recently introduced to improve the power-spectral efficiency trade-off of intensity-modulated direct-detection (IM/DD) optical OFDM transmission schemes. This is accomplished by superimposing unipolar signals over several layers. Bit-error-rate (BER) analysis for each layer however, is eluded by error-propagation from previous layers in the eU-OFDM receiver. This paper presents a general mathematical model for eU-OFDM transmission. From the model, we introduce successive interference cancellation using soft-symbol estimates, which leads to slight performance improvement compared to the original hard-decision counterpart. More importantly, by using soft-symbol estimates we derive analytically tractable expressions that accurately predict the system's performance.

A comprehensive study on security attacks on SSL/TLS protocol <=SEP=> Secure Socket Layer (SSL) protocol was introduced in 1994 and was later renamed as transport layer security (TLS) protocol for securing transport layer. SSL/TLS protocol is used for securing communication on the network by ensuring data confidentiality, data integrity and authenticity between the communicating party. Authentication of the communicating party and securing transfer of data is done through certificates, key exchange and cipher suites. Security issues were found during evolutionary development of SSL/TLS protocol. The paper gives a detailed chronological order of attacks of past 22 years on SSL/TLS protocol.

Post-Punching Behavior of Flat Slabs by <=SEP=> Reinforced concrete flat slabs are a common structural system for cast-in-place concrete slabs. Failures in punching shear near the column regions are typically governing at ultimate. In case no punching shear or integrity reinforcement is placed, failures in punching develop normally in a brittle manner with almost no warning signs. Furthermore, the residual strength after punching is, in general, significantly lower than the punching load. Thus, punching of a single column of a flat slab overloads adjacent columns and can potentially lead to their failure on punching, thus triggering the progressive collapse of the structure. Over the past decades, several collapses have been reported due to punching shear failures, resulting in human casualties and extensive damage. Other than placing conventional punching shear reinforcement, the deformation capacity and residual strength after punching can also be enhanced by placing integrity reinforcement to avoid progressive collapses of flat slabs. This paper presents the main results of an extensive experimental campaign performed at the Ecole Polytechnique Fédérale de Lausanne (EPFL) on the role of integrity reinforcement by means of 20 slabs with dimensions of 1500 x 1500 x 125 mm (≈5 ft x 5 ft x 5 in.) and various integrity reinforcement layouts. The performance and robustness of the various solutions is investigated to obtain physical explanations and a consistent design model for the load-carrying mechanisms and strength after punching failures. INTRODUCTION Over the past decades, several collapses due to punching shear failure have been reported in Europe and America,

User Interface Menu Design Performance and User Preferences: A Review and Ways Forward <=SEP=> This review paper is about menus on web pages and applications and their positioning on the user screen. The paper aims to provide the reader with a succinct summary of the major research in this area along with an easy to read tabulation of the most important studies. Furthermore, the paper concludes with some suggestions for future research regarding how menus and their positioning on the screen could be improved. The two principal suggestions concern trying to use more qualitative methods for investigating the issues and to develop in the future more universally designed menus. Keywords—Menus; navigation of interfaces; universal design;