title: Qualitative Research: Getting Started

abstract: As scientifically trained clinicians, pharmacists may be more familiar and comfortable with the concept of quantitative rather than qualitative research. Quantitative research can be defined as “the means for testing objective theories by examining the relationship among variables which in turn can be measured so that numbered data can be analyzed using statistical proce dures”. 1 Pharmacists may have used such methods to carry out audits or surveys within their own practice settings; if so, they may have had a sense of “something missing” from their data. What is missing from quantitative research methods is the voice of the participant. In a quantitative study, large amounts of data can be collected about the number of people who hold certain attitudes toward their health and health care, but what qualitative study tells us is why people have thoughts and feelings that might affect the way they respond to that care and how it is given (in this way, qualitative and quantitative data are frequently comple mentary). Possibly the most important point about qualitative research is that its practitioners do not seek to generalize their findings to a wider population. Rather, they attempt to find examples of behaviour, to clarify the thoughts and feelings of study participants, and to interpret participants’ experiences of the phenomena of interest, in order to find explanations for human behaviour in a given context.


title: PolyFit: Polygonal Surface Reconstruction from Point Clouds

abstract: We propose a novel framework for reconstructing lightweight polygonal surfaces from point clouds. Unlike traditional methods that focus on either extracting good geometric primitives or obtaining proper arrangements of primitives, the emphasis of this work lies in intersecting the primitives (planes only) and seeking for an appropriate combination of them to obtain a manifold polygonal surface model without boundary.,,We show that reconstruction from point clouds can be cast as a binary labeling problem. Our method is based on a hypothesizing and selection strategy. We first generate a reasonably large set of face candidates by intersecting the extracted planar primitives. Then an optimal subset of the candidate faces is selected through optimization. Our optimization is based on a binary linear programming formulation under hard constraints that enforce the final polygonal surface model to be manifold and watertight. Experiments on point clouds from various sources demonstrate that our method can generate lightweight polygonal surface models of arbitrary piecewise planar objects. Besides, our method is capable of recovering sharp features and is robust to noise, outliers, and missing data.


title: Information-Centric Networking in next-generation communications scenarios

abstract: Next-generation networking environments, characterized by the overlapping of wireless networks of different types, are emerging as a new and extremely interesting scenario. Their high dynamicity and heterogeneity present significant challenges from the communications perspective, which call for the adoption of new paradigms based on opportunistic and Information-Centric Networking (ICN) approaches. Applications operating in next-generation environments have peculiar characteristics that could benefit from ICN-based middleware solutions. This paper presents ICeDiM, a middleware we designed for ICN communications in next-generation scenarios, which builds on top of the innovative concept of Application-level Dissemination Channels (ADCs) with tunable permeability levels. A thorough and in-depth experimental evaluation of ICeDiM in a next-generation environment realistically simulated using ICeONE, a modified version of the well-known ONE simulator, demonstrates that our approach can achieve very good performance levels in terms of delivery ratio and network resource consumption.


title: Digital poly-victimization: The increasing importance of online crime and harassment to the burden of victimization

abstract: ABSTRACTMany forms of victimization, including bullying and property crime, are increasingly moving online, but most studies of poly-victimization still primarily focus on in-person crime and violence. Few studies have examined the importance of incorporating technology-based victimizations for assessing the true burden of violence. The purpose of this study is to explore whether digital poly-victimization contributes to post-traumatic stress and anxiety/dysphoria symptoms after controlling for in-person poly-victimization. Given that technology use and technology-based victimization are changing rapidly, a mixed methods approach was adopted. In the first two phases, focus groups and cognitive interviews (89 total participants) were used to identify the range of digital victimization and develop the Digital Poly-Victimization Scale. In the third phase, the new measure was included in a community survey (n = 478, 57.5% female; 62.6% earning under $50,000 per year) in a rural Southern region, along with mea...


title: Dialog History Construction with Long-Short Term Memory for Robust Generative Dialog State Tracking

abstract: One of the crucial components of dialog system is the dialog state tracker, which infers user’s intention from preliminary speech processing. Since the overall performance of the dialog system is heavily affected by that of the dialog tracker, it has been one of the core areas of research on dialog systems. In this paper, we present a dialog state tracker that combines a generative probabilistic model of dialog state tracking with the recurrent neural network for encoding important aspects of the dialog history. We describe a two-step gradient descent algorithm that optimizes the tracker with a complex loss function. We demonstrate that this approach yields a dialog state tracker that performs competitively with top-performing trackers participated in the first and second Dialog State Tracking Challenges.


title: Clustering Memes in Social Media

abstract: The increasing pervasiveness of social media creates new opportunities to study human social behavior, while challenging our capability to analyze their massive data streams. One of the emerging tasks is to distinguish between different kinds of activities, for example engineered misinformation campaigns versus spontaneous communication. Such detection problems require a formal definition of meme, or unit of information that can spread from person to person through the social network. Once a meme is identified, supervised learning methods can be applied to classify different types of communication. The appropriate granularity of a meme, however, is hardly captured from existing entities such as tags and keywords. Here we present a framework for the novel task of detecting memes by clustering messages from large streams of social data. We evaluate various similarity measures that leverage content, metadata, network features, and their combinations. We also explore the idea of pre-clustering on the basis of existing entities. A systematic evaluation is carried out using a manually curated dataset as ground truth. Our analysis shows that pre-clustering and a combination of heterogeneous features yield the best trade-off between number of clusters and their quality, demonstrating that a simple combination based on pairwise maximization of similarity is as effective as a non-trivial optimization of parameters. Our approach is fully automatic, unsupervised, and scalable for real-time detection of memes in streaming data.


title: Specificity of Acceleration, Maximum Speed and Agility in Professional Soccer Players

abstract: High-speed actions ::: are known to impact soccer performance and can be categorized ::: into actions requiring maximal speed, acceleration, or ::: agility. Contradictory findings have been reported as to the extent ::: of the relationship between the different speed components. ::: This study comprised 106 professional soccer players who were ::: assessed for 10-m sprint (acceleration), flying 20-m sprint (maximum ::: speed), and zigzag agility performance. Although performances ::: in the three tests were all significantly correlated (p , ::: 0.0005), coefficients of determination (r2) between the tests were ::: just 39, 12, and 21% for acceleration and maximum speed, acceleration ::: and agility, and maximum speed and agility, respectively. ::: Based on the low coefficients of determination, it was concluded ::: that acceleration, maximum speed, and agility are specific ::: qualities and relatively unrelated to one another. The findings ::: suggest that specific testing and training procedures for ::: each speed component should be utilized when working with ::: elite players.


title: Expression of the p53 oncogene in acute myeloblastic leukemia

abstract: We have investigated whether the p53 oncogene is expressed in the blast cells of patients with acute myeloblastic leukemia. p53 protein was detected in the blast cells of 19 out of 34 patients, but not in normal myelopoietic cells. We find a highly significant correlation between p53 protein synthesis in leukemic blast cells and the secondary plating efficiency of these cells (p = 0.0001). The latter provides an estimate for the self renewal capacity of progenitor cells in the blast population. These data indicate that p53 may be involved in leukemic stem cell renewal.


title: In vivo accuracy of multipectral magnetic resonance imaging for identifying lipid-rich necrotic cores and intraplaque hemorrhage in advanced human carotid plaques

abstract: BACKGROUND ::: High-resolution MRI has been shown to be capable of identifying plaque constituents, such as the necrotic core and intraplaque hemorrhage, in human carotid atherosclerosis. The purpose of this study was to evaluate differential contrast-weighted images, specifically a multispectral MR technique, to improve the accuracy of identifying the lipid-rich necrotic core and acute intraplaque hemorrhage in vivo. ::: ::: ::: METHODS AND RESULTS ::: Eighteen patients scheduled for carotid endarterectomy underwent a preoperative carotid MRI examination in a 1.5-T GE Signa scanner using a protocol that generated 4 contrast weightings (T1, T2, proton density, and 3D time of flight). MR images of the vessel wall were examined for the presence of a lipid-rich necrotic core and/or intraplaque hemorrhage. Ninety cross sections were compared with matched histological sections of the excised specimen in a double-blinded fashion. Overall accuracy (95% CI) of multispectral MRI was 87% (80% to 94%), sensitivity was 85% (78% to 92%), and specificity was 92% (86% to 98%). There was good agreement between MRI and histological findings, with a value of kappa=0.69 (0.53 to 0.85). ::: ::: ::: CONCLUSIONS ::: Multispectral MRI can identify the lipid-rich necrotic core in human carotid atherosclerosis in vivo with high sensitivity and specificity. This MRI technique provides a noninvasive tool to study the pathogenesis and natural history of carotid atherosclerosis. Furthermore, it will permit a direct assessment of the effect of pharmacological therapy, such as aggressive lipid lowering, on plaque lipid composition.


title: Evaluation of the Minstrel rate adaptation algorithm in IEEE 802.11g WLANs

abstract: Rate adaptation varies the transmission rate of a wireless sender to match the wireless channel conditions, in order to achieve the best possible performance. It is a key component of IEEE 802.11 wireless networks. Minstrel is a popular rate adaptation algorithm due to its efficiency and availability in commonly used wireless drivers. However, despite its popularity, little work has been done on evaluating the performance of Minstrel or comparing it to the performance of fixed rates. In this paper, we conduct an experimental study that compares the performance of Minstrel against fixed rates in an IEEE 802.11g testbed. The experiment results show that whilst Minstrel performs reasonably well in static wireless channel conditions, in some cases the algorithm has difficulty selecting the optimal data rate in the presence of dynamic channel conditions. In addition, Minstrel performs well when the channel condition improves from bad quality to good quality. However, Minstrel has trouble selecting the optimal rate when the channel condition deteriorates from good quality to bad quality.


title: Correlation-Based Tracking of Multiple Targets With Hierarchical Layered Structure

abstract: Visual target tracking is one of the most important research areas in the field of computer vision. Within this realm, multiple targets tracking (MTT) under complicated scene stands out for its great availability in real life applications, such as urban traffic surveillance and sports video analysis. However, in MTT, main difficulties arise from large variation in target saliency and significant motion heterogeneity, which may result in the failure of tracking weak targets. To tackle this challenge, a novel hierarchical layered tracking structure is proposed to perform tracking sequentially layer-by-layer. Upon this layered structure, we establish an intertarget mutual assistance mechanism on basis of intertarget correlation exploited among targets. The tracking results of a subset of targets can be utilized as additional prior information for tracking other targets. Specifically, a nonlinear motion model as well as a target interaction model basing on the intertarget correlation are proposed to effectively estimate the possible target region-of-interest to facilitate the prediction-based tracking. Moreover, the concept of motion entropy is introduced to quantitatively measure the degree of motion heterogeneity within the tracking scene for layer construction. Compared to other existing methods, extensive experiments demonstrated that the proposed method is capable of achieving higher tracking performance in complicated scenes, where targets are characterized with great heterogeneity.


title: Vision Based Railway Track Monitoring using Deep Learning

abstract: Computer vision based methods have been explored in the past for detection of railway track defects, but full automation has always been a challenge because both traditional image processing methods and deep learning classifiers trained from scratch fail to generalize that well to infinite novel scenarios seen in the real world, given limited amount of labeled data. Advancements have been made recently to make machine learning models utilize knowledge from a different but related domain. In this paper, we show that even though similar domain data is not available, transfer learning provides the model understanding of other real world objects and enables training production scale deep learning classifiers for uncontrolled real world data. Our models efficiently detect both track defects like sunkinks, loose ballast and railway assets like switches and signals. Models were validated with hours of track videos recorded in different continents resulting in different weather conditions, different ambience and surroundings. A track health index concept has also been proposed to monitor complete rail network.


title: Constructing Test cases using Natural Language Processing

abstract: Testing of product is perform to discover or detect the errors and defects in the developed system. But testing is usually time consuming especially when complex projects are canvass. Testing of a product lead off with generation of test cases. The Test case generation are based on three parts coding, design and specification. The Specification based testing deals with generation of test cases from the functional requirements. The proposed system deals with automatic generation of test cases from functional requirement using Natural Language Processing (NLP). The proposed system constructs test cases based on keywords in context from functional requirement of Software Requirement Specification document. The proposed system is beneficial as it can automatically analyze the functional requirement from Software Requirement Specification in order to extract test cases for testing. The goal of the proposed system is to reduce effort and time consumed by software tester to test the product.


title: Character Recognition Using Hierarchical Vector Quantization and Temporal Pooling

abstract: In recent years, there has been a cross-fertilization of ideas between computational neuroscience models of the operation of the neocortex and artificial intelligence models of machine learning. Much of this work has focussed on the mammalian visual cortex, treating it as a hierarchically-structured pattern recognition machine that exploits statistical regularities in retinal input. It has further been proposed that the neocortex represents sensory information probabilistically, using some form of Bayesian inference to disambiguate noisy data. ::: ::: In the current paper, we focus on a particular model of the neocortex developed by Hawkins, known as hierarchical temporal memory (HTM). Our aim is to evaluate an important and recently implemented aspect of this model, namely its ability to represent temporal sequences of input within a hierarchically structured vector quantization algorithm. We test this temporal pooling feature of HTM on a benchmark of cursive handwriting recognition problems and compare it to a current state-of-the-art support vector machine implementation. We also examine whether two pre-processing techniques can enhance the temporal pooling algorithm's performance. Our results show that a relatively simple temporal pooling approach can produce recognition rates that approach the current state-of-the-art without the need for extensive tuning of parameters. We also show that temporal pooling performance is surprisingly unaffected by the use of preprocessing techniques.


title: Timing of the brain events underlying access to consciousness during the attentional blink

abstract: In the phenomenon of attentional blink, identical visual stimuli are sometimes fully perceived and sometimes not detected at all. This phenomenon thus provides an optimal situation to study the fate of stimuli not consciously perceived and the differences between conscious and nonconscious processing. We correlated behavioral visibility ratings and recordings of event-related potentials to study the temporal dynamics of access to consciousness. Intact early potentials (P1 and N1) were evoked by unseen words, suggesting that these brain events are not the primary correlates of conscious perception. However, we observed a rapid divergence around 270 ms, after which several brain events were evoked solely by seen words. Thus, we suggest that the transition toward access to consciousness relates to the optional triggering of a late wave of activation that spreads through a distributed network of cortical association areas.


title: Iterative Refinement for Machine Translation

abstract: Existing machine translation decoding algorithms generate translations in a strictly monotonic fashion and never revisit previous decisions. As a result, earlier mistakes cannot be corrected at a later stage. In this paper, we present a translation scheme that starts from an initial guess and then makes iterative improvements that may revisit previous decisions. We parameterize our model as a convolutional neural network that predicts discrete substitutions to an existing translation based on an attention mechanism over both the source sentence as well as the current translation output. By making less than one modification per sentence, we improve the output of a phrase-based translation system by up to 0.4 BLEU on WMT15 German-English translation.


title: W-band SPDT switches in planar and tri-gate 100-nm gate-length GaN-HEMT technology

abstract: This paper reports on W-band (75 to 110 GHz) single-pole double-throw (SPDT) switch millimeter-wave integrated circuits (MMICs) based on a planar and a tri-gate 100-nm gate-length GaN high-electron-mobility transistor (HEMT) technology. The SPDT switches utilize the well-established quarter-wave stub topology with shunt transistors. For an improved wideband performance, an optimized layout approach is used that connects the shorted stub for the compensation of the capacitance of a shunt transistor at the center of the transistor. The presented SPDT switch MMIC demonstrates for both technology versions a measured average insertion loss of 1.3 dB over the entire W-band with a peak insertion loss of 1.2 and 1.1 dB in the center of the W-band for planar and tri-gate HEMTs, respectively. The one-dB bandwidth is for both MMICs almost an octave. For an input power of at least 25 dBm, both SPDT switches do not show an indication of compression.


title: Design of intelligent telephone billing system based on AT89C52

abstract: In the design, the MCU AT89C52 is the core of the system. The system can send and receive the DTMF signal, which can identify the city telephone number or the long-distance telephone number. According the number, it can billing and show call duration and call cost. It can realize automatically the conversion between the full price and the discount price. It can billing accurately and conveniently query ticket information. It is configurable product and resets rate by pressing a button. It is low cost and low power consumption.


title: Finger exoskeleton for treatment of tendon injuries

abstract: A finger exoskeleton has been developed to aid treatment of tendon injuries. The exoskeleton is designed to assist flexion/extension motions of a finger within its full range, in a natural and coordinated manner, while keeping the tendon tension within acceptable limits to avoid gap formation or rupture of the suture. In addition to offering robot assisted operation modes for tendon therapies, the exoskeleton can provide quantitative measures of recovery that can help guide the physical therapy program. Usability studies have been conducted and efficacy of exoskeleton driven exercises to reduce muscle requitement levels has been demonstrated.


A GENERALIZED DIRECT APPROACH FOR DESIGNING FUZZY LOGIC CONTROLLERS IN MATLAB / SIMULINK GUI ENVIRONMENT


Security of Feistel Schemes with New and Various Tools


title: Inter-turn fault tolerant control system in brushless DC motor by using yoke winding

abstract: A fault tolerant control is mightily important in industrial and electrical vehicles. A shutdown of these motors should not happen due to its direct relationship to enormous loss to life and property, even if inter-turn fault of a winding occur. This paper proposed an inter-turn fault (ITF) tolerant control system using new-design brushless DC (BLDC) motor, which has teeth and yoke winding connected in parallel for fault tolerant control. The special point of new-design BLDC motor is that back electromotive force of teeth and yoke winding have nearly similar value and phase. In addition, we used a fault detection using input impedance algorithm. It can distinguish the ITF condition using variation of input impedance, which is obtained by monitoring of input voltage and current. After that, a fault tolerant control can prevent the spread of the fault by cutting off the three-phase winding and maintain partial output characteristics in proposed BLDC motor. The system has a special advantage that can use existing inverter without additional control device. Finally, we analyzed characteristics of the ITF tolerant control system in proposed BLDC motor using finite element method.


title: A machine learning approach for linux malware detection

abstract: The increasing number of malware is becoming a serious threat to the private data as well as to the expensive computer resources. Linux is a Unix based machine and gained popularity in recent years. The malware attack targeting Linux has been increased recently and the existing malware detection methods are insufficient to detect malware efficiently. We are introducing a novel approach using machine learning for identifying malicious Executable Linkable Files. The system calls are extracted dynamically using system call tracer Strace. In this approach we identified best feature set of benign and malware specimens to built classification model that can classify malware and benign efficiently. The experimental results are promising which depict a classification accuracy of 97% to identify malicious samples.


title: The rise (and fall?) of parental vaccine hesitancy

abstract: Parental vaccine hesitancy is a growing problem affecting the health of children and the larger population. This article describes the evolution of the vaccine hesitancy movement and the individual, vaccine-specific and societal factors contributing to this phenomenon. In addition, potential strategies to mitigate the rising tide of parent vaccine reluctance and refusal are discussed.


title: Towards Digital Refocusing from a Single Photograph

abstract: This paper explores an image processing method for synthesizing refocused images from a single input photograph containing some defocus blur. First, we restore a sharp image by estimating and removing spatially-variant defocus blur in an input photograph. To do this, we propose a local blur estimation method able to handle abrupt blur changes at depth discontinuities in a scene, and we also present an efficient blur removal method that significantly speeds up the existing deconvolution algorithm. Once a sharp image is restored, refocused images can be interactively created by adding different defocus blur to it based on the estimated blur, so that users can intuitively change focus and depth-of-field of the input photograph. Although information available from a single photograph is highly insufficient for fully correct refocusing, the results show that visually plausible refocused images can be obtained.


title: A General Design Method of Primary Compensation Network for Dynamic WPT System Maintaining Stable Transmission Power

abstract: Dynamic wireless power transmission (DWPT) is considered as a solution to the problems encountered in the development of electrical vehicle (EV), such as range anxiety resulted from battery bottleneck and the difficulty of convenient charging. However, the requirement of DWPT, maintaining almost constant transmission power with constant voltage load in effective movement process, is quite different from Stationary WPT. The power fluctuation is easily brought by the coupling coils over large misalignment in movement. A general design method of primary compensation network from the perspective of DWPT is presented in this paper. Under the premise of ensuring high transmission efficiency and soft switching, a novel T-type compensation network for DWPT is proposed, which maintains a stable output characteristic over a wide misalignment, companied with an inherent current limiting ability under no-load operation. A WPT prototype with a fixed frequency operation based on the T-type compensation network is built. The output power is kept almost stable even though magnetic coupling coefficient varies twice showing the effectiveness of the design method.


Determinants of supply chain coordination of milk and dairy industries in Ethiopia: a case of Addis Ababa and its surroundings


title: Persistent Roles in Online Social Networks

abstract: Users in online social networks often have very different structural positions which may be attributed to a latent factor: roles. In this paper, we analyze dynamic networks from two datasets (Facebook and Scratch) to find roles which define users’ structural positions. Each dynamic network is partitioned into snapshots and we independently find roles for each network snapshot. We present our role discovery methodology and investigate how roles differ between snapshots and datasets. Six persistent roles are found and we investigate user role membership, transitions between roles, and interaction preferences.


title: Spatio-Temporal Detection of Divided Attention in Reading Applications Using EEG and Eye Tracking

abstract: Reading is central to learning and communicating, however, divided attention in the form of distraction may be present in learning environments, resulting in a limited understanding of the reading material. This paper presents a novel system that can spatio-temporally detect divided attention in users during two different reading applications: typical document reading and speed reading. Eye tracking and electroencephalography (EEG) monitor the user during reading and provide a classifier with data to decide the user's attention state. The multimodal data informs the system where the user was distracted spatially in the user interface and when the user was distracted. Classification was evaluated with two exploratory experiments. The first experiment was designed to divide the user's attention with a multitasking scenario. The second experiment was designed to divide the users attention by simulating a real-world scenario where the reader is interrupted by unpredictable audio distractions. Results from both experiments show that divided attention may be detected spatio-temporally well above chance on a single-trial basis.


title: Modeling Coherence for Discourse Neural Machine Translation

abstract: Discourse coherence plays an important role in the translation of one text. However, the previous reported models most focus on improving performance over individual sentence while ignoring cross-sentence links and dependencies, which affects the coherence of the text. In this paper, we propose to use discourse context and reward to refine the translation quality from the discourse perspective. In particular, we generate the translation of individual sentences at first. Next, we deliberate the preliminary produced translations, and train the model to learn the policy that produces discourse coherent text by a reward teacher. Practical results on multiple discourse test datasets indicate that our model significantly improves the translation quality over the state-of-the-art baseline system by +1.23 BLEU score. Moreover, our model generates more discourse coherent text and obtains +2.2 BLEU improvements when evaluated by discourse metrics.


title: Yield optimization using advanced statistical correlation methods

abstract: This work presents a novel yield optimization methodology based on establishing a strong correlation between a group of fails and an adjustable process parameter. The core of the methodology comprises three advanced statistical correlation methods. The first method performs multivariate correlation analysis to uncover linear correlation relationships between groups of fails and measurements of a process parameter. The second method partitions a dataset into multiple subsets and tries to maximize the average of the correlations each calculated based on one subset. The third method performs statistical independence test to evaluate the risk of adjusting a process parameter. The methodology was applied to an automotive product line to improve yield. Five process parameter changes were discovered which led to significant improvement of the yield and consequently significant reduction of the yield fluctuation.


title: A linear regression analysis of the effects of age related pupil dilation change in iris biometrics

abstract: Medical studies have shown that average pupil size decreases linearly throughout adult life. Therefore, on average, the longer the time between acquisition of two images of the same iris, the larger the difference in dilation between the two images. Several studies have shown that increased difference in dilation causes an increase in the false nonmatch rate for iris recognition. Thus, increased difference in pupil dilation is one natural mechanism contributing to an iris template aging effect. We present an experimental analysis of the change in genuine match scores in the context of dilation differences due to aging.


title: Analysis of Minimum Distances in High-Dimensional Musical Spaces

abstract: We propose an automatic method for measuring content-based music similarity, enhancing the current generation of music search engines and recommended systems. Many previous approaches to track similarity require brute-force, pair-wise processing between all audio features in a database and therefore are not practical for large collections. However, in an Internet-connected world, where users have access to millions of musical tracks, efficiency is crucial. Our approach uses features extracted from unlabeled audio data and near-neigbor retrieval using a distance threshold, determined by analysis, to solve a range of retrieval tasks. The tasks require temporal features-analogous to the technique of shingling used for text retrieval. To measure similarity, we count pairs of audio shingles, between a query and target track, that are below a distance threshold. The distribution of between-shingle distances is different for each database; therefore, we present an analysis of the distribution of minimum distances between shingles and a method for estimating a distance threshold for optimal retrieval performance. The method is compatible with locality-sensitive hashing (LSH)-allowing implementation with retrieval times several orders of magnitude faster than those using exhaustive distance computations. We evaluate the performance of our proposed method on three contrasting music similarity tasks: retrieval of mis-attributed recordings (fingerprint), retrieval of the same work performed by different artists (cover songs), and retrieval of edited and sampled versions of a query track by remix artists (remixes). Our method achieves near-perfect performance in the first two tasks and 75% precision at 70% recall in the third task. Each task was performed on a test database comprising 4.5 million audio shingles.


title: Hominins and the emergence of the modern human brain.

abstract: Evidence used to reconstruct the morphology and function of the brain (and the rest of the central nervous system) in fossil hominin species comes from the fossil and archeological records. Although the details provided about human brain evolution are scarce, they benefit from interpretations informed by interspecific comparative studies and, in particular, human pathology studies. In recent years, new information has come to light about fossil DNA and ontogenetic trajectories, for which pathology research has significant implications. We briefly describe and summarize data from the paleoarcheological and paleoneurological records about the evolution of fossil hominin brains, including behavioral data most relevant to brain research. These findings are brought together to characterize fossil hominin taxa in terms of brain structure and function and to summarize brain evolution in the human lineage.


title: ProgTest: An environment for the submission and evaluation of programming assignments based on testing activities

abstract: Programming foundations is not an easy subject to be taught — many students have difficulties understanding the abstract concepts of programming and have a wrong view about the programming activity. In order to address these problems, experiences have suggested the integrated teaching of programming concepts and software testing in introductory CS courses. Shortly, the idea is that testing can contribute to enhance the students' capabilities of understanding and analysis. However, such perspective requires tools to provide an adequate feedback to evaluate the students' performance concerning programming and testing activities. In this paper we describe ProgTest — a web-based tool for the submission and automatic evaluation of practical programming assignments based on testing activities. Results from a preliminary validation of ProgTest are also presented. Such results provide evidences on the practical use of ProgTest as a supporting mechanism for the integrated teaching of programming foundations and software testing.


title: Core Losses and Torque Ripple in IPM Machines: Dedicated Modeling and Design Tradeoff

abstract: The proper combination of stator and rotor slot numbers is pursued in the design of interior permanent-magnet (IPM) motors with wide constant-power speed range. At high speed, in the flux-weakening region, the arising of stator and rotor iron losses due to magnetomotive-force (MMF) spatial harmonics limits the IPM motor performance. Torque ripple is another problem for this kind of machines, both at low and high speed. The numbers of stator slots and rotor equivalent slots have a major impact on both the loss and ripple aspects. A simplified model is proposed here in order to evaluate both problems with a general approach and point out the possible design tradeoff. With respect to previous models in the literature, both stator and rotor losses are included, and a more comprehensive approach is followed in the description of the rotor MMF harmonics. The model's effectiveness is tested through finite element analysis simulations and some experimental results. The proposed approach is useful for the selection of the IPM machine structure according to the specific requirements of the application.


title: A modified edge-based region growing segmentation of geometric objects

abstract: Region growing and edge detection are two popular and common techniques used for image segmentation. Region growing is preferred over edge detection methods because it is more robust against low contrast problems and effectively addresses the connectivity issues faced by edge detectors. Edgebased techniques, on the other hand, can significantly reduce useless information while preserving the important structural properties in an image. Recent studies have shown that combining region growing and edge methods for segmentation will produce much better results. This paper proposed using edge information to automatically select seed pixels and guide the process of region growing in segmenting geometric objects from an image. The geometric objects are songket motifs from songket patterns. Songket motifs are the main elements that decorate songket pattern. The beauty of songket lies in the elaborate design of the patterns and combination of motifs that are intricately woven on the cloth. After experimenting on thirty songket pattern images, the proposed method achieved promising extraction of the songket motifs.


title: Transformational planning for mobile manipulation based on action-related places

abstract: Opportunities for interleaving or parallelizing actions are abundant in everyday activities. Being able to perceive, predict and exploit such opportunities leads to more efficient and robust behavior. In this paper, we present a mobile manipulation platform that exploits such opportunities to optimize its behavior, e.g. grasping two objects from one location simultaneously, rather than navigating to two different locations. To do so, it uses a general least-commitment representation of place, called ARPLACE, from which manipulation is predicted to be successful. Models for ARPLACEs are learned from experience using Support Vector Machines and Point Distribution Models, and take into account the robot's morphology and skill repertoire. We present a transformational planner that reasons about ARPLACEs, and applies transformation rules to its plans if more robust and efficient behavior is predicted.


Health System Reform in China 6 Reform of how health care is paid for in China : challenges and opportunities


title: Comparing static and dynamic code scheduling for multiple-instruction-issue processors

abstract: This paper examines two alternative approaches to supporting code scheduling for multiple-instruction-issue processors. One is to provide a set of non-trapping instructions so that the compiler can perform aggressive static code scheduling. The application of this approach to existing commercial architectures typically requires extending the instruction set. The other approach is to support out-of-order execution in the microarchitecture so that the hardware can perform aggressive dynamic code scheduling. This approach usually does not require modifying the instruction set but requires complex hardware support. In this paper, we analyze the performance of the two alternative approaches using a set of important nonnumerical C benchmark programs. A distinguishing feature of the experiment is that the code for the dynamic approach has been optimized and scheduled as much as allowed by the architecture. The hardware is only responsible for the additional reordering that cannot be performed by the compiler. The overall result is that the dynamic and static approaches are comparable in performance. When applied to a four-instruction-issue processor, both methods achieve more than two times speedup over a high performance single-instruction-issue processor. However, the performance of each scheme varies among the benchmark programs. To explain this variation, we have identi ed the conditions in these programs that make one approach perform better than the other.


title: Finding usability problems through heuristic evaluation

abstract: Usability specialists were better than non-specialists at performing heuristic evaluation, and “double experts” with specific expertise in the kind of interface being evaluated performed even better. Major usability problems have a higher probability than minor problems of being found in a heuristic evaluation, but more minor problems are found in absolute numbers. Usability heuristics relating to exits and user errors were more difficult to apply than the rest, and additional measures should be taken to find problems relating to these heuristics. Usability problems that relate to missing interface elements that ought to be introduced were more difficult to find by heuristic evaluation in interfaces implemented as paper prototypes but were as easy as other problems to find in running systems.


title: A Dynamic Approach for MPE and Weighted MAX-SAT

abstract: The problem of Most Probable Explanation (MPE) arises in the scenario of probabilistic inference: finding an assignment to all variables that has the maximum likelihood given some evidence. We consider the more general CNF-based MPE problem, where each literal in a CNF-formula is associated with a weight. We describe reductions between MPE and weighted MAX-SAT, and show that both can be solved by a variant of weighted model counting. The MPE-SAT algorithm is quite competitive with the state-of-the-art MAX-SAT, WCSP, and MPE solvers on a variety of problems.


title: A Framework for Ontology Evolution in Collaborative Environments

abstract: With the wider use of ontologies in the Semantic Web and as part of production systems, multiple scenarios for ontology maintenance and evolution are emerging. For example, successive ontology versions can be posted on the (Semantic) Web, with users discovering the new versions serendipitously; ontology-development in a collaborative environment can be synchronous or asynchronous; managers of projects may exercise quality control, examining changes from previous baseline versions and accepting or rejecting them before a new baseline is published, and so on. In this paper, we present different scenarios for ontology maintenance and evolution that we have encountered in our own projects and in those of our collaborators. We define several features that categorize these scenarios. For each scenario, we discuss the high-level tasks that an editing environment must support. We then present a unified comprehensive set of tools to support different scenarios in a single framework, allowing users to switch between different modes easily.


title: A 240mW 2.1GS/s 12b pipeline ADC using MDAC equalization

abstract: This paper introduces MDAC equalization, a digital correction technique for pipeline ADCs that corrects MDAC gain and settling errors using successive digital FIR filters operating on sub-ADC output samples. This technique reduces the required MDAC residue amplifier (RA) bandwidth relative to the sampling frequency, thereby reducing ADC power. MDAC equalization is demonstrated in a 240mW 2.1GS/s 12b ping-pong pipeline ADC in 40nm CMOS where MDAC RA power is reduced from 175mW to 53mW by 70%.


Vanishing Point Detection For Architectural Photogrammetry


title: The impact of age and shopping experiences on the classification of search, experience, and credence goods in online shopping

abstract: This study explores how age and consumers' Web shopping experience influence the search, experience, and credence (SEC) ratings of products and services in online shopping. Using the survey data collected from 549 consumers, we investigated how they perceived the uncertainty of product quality on six search, experience, and credence goods. The ANOVA results show that age and the Web consumers' shopping experience are significant factors. A generation gap is identified for all but one experience good. Web shopping experience is not a significant factor for search goods but is for experience and credence goods. There is an interaction effect between age and Web shopping experience for one credence good. Implications of these results are discussed.


title: Chapter 10 PRIVACY IN SOCIAL NETWORKS: A SURVEY

abstract: In this chapter, we survey the literature on privacy in social networks. We focus both on online social networks and online affiliation networks. We formally define the possible privacy breaches and describe the privacy attacks that have been studied. We present definitions of privacy in the context of anonymization together with existing anonymization techniques.


Outlier Detection for Text Data


title: 3-D Printer Based Lens Design Method for Integrated Lens Antennas

abstract: We propose a new and straightforward dielectric lens design method to increase the gain of integrated lens antennas (ILAs). Our lens is divided into several cone-shaped radial sections. Each section consists of specific permittivity to provide desired phase delays for the waves passing through the section. Our method does not depend on the operating frequencies and the physical appearance of the lens, because all the radial sections share one common phase center as a starting point. Accordingly, to change the main beam direction, we only need to rearrange the sections. However, the required permittivity is all different in every section, which is extremely difficult to be realized using conventional dielectric materials. To fabricate the required permittivity based on an effective medium theory, we use a cutting-edge three-dimensional printing technology. Consequently, we can obtain all the required permittivity using only one base printing material. Through experiments, we can show that our lens not only can form a desired beam but also can increase gain in the target direction, which proves the validity of our lens design method.


Callisthene inundata, a new species of the Vochysiaceae and the first record of the family in the state of Rio Grande do Sul, Brazil.


title: Synchronization in Small-World Systems

abstract: We quantify the dynamical implications of the small-world phenomenon by considering the generic synchronization of oscillator networks of arbitrary topology. The linear stability of the synchronous state is linked to an algebraic condition of the Laplacian matrix of the network. Through numerics and analysis, we show how the addition of random shortcuts translates into improved network synchronizability. Applied to networks of low redundancy, the small-world route produces synchronizability more efficiently than standard deterministic graphs, purely random graphs, and ideal constructive schemes. However, the small-world property does not guarantee synchronizability: the synchronization threshold lies within the boundaries, but linked to the end of the small-world region.


title: An empirical study of just-in-time defect prediction using cross-project models

abstract: Prior research suggests that predicting defect-inducing changes, i.e., Just-In-Time (JIT) defect prediction is a more practical alternative to traditional defect prediction techniques, providing immediate feedback while design decisions are still fresh in the minds of developers. Unfortunately, similar to traditional defect prediction models, JIT models require a large amount of training data, which is not available when projects are in initial development phases. To address this flaw in traditional defect prediction, prior work has proposed cross-project models, i.e., models learned from older projects with sufficient history. However, cross-project models have not yet been explored in the context of JIT prediction. Therefore, in this study, we empirically evaluate the performance of JIT cross-project models. Through a case study on 11 open source projects, we find that in a JIT cross-project context: (1) high performance within-project models rarely perform well; (2) models trained on projects that have similar correlations between predictor and dependent variables often perform well; and (3) ensemble learning techniques that leverage historical data from several other projects (e.g., voting experts) often perform well. Our findings empirically confirm that JIT cross-project models learned using other projects are a viable solution for projects with little historical data. However, JIT cross-project models perform best when the data used to learn them is carefully selected.


title: Synthetic polymers in the marine environment: a rapidly increasing, long-term threat.

abstract: Synthetic polymers, commonly known as plastics, have been entering the marine environment in quantities paralleling their level of production over the last half century. However, in the last two decades of the 20th Century, the deposition rate accelerated past the rate of production, and plastics are now one of the most common and persistent pollutants in ocean waters and beaches worldwide. Thirty years ago the prevailing attitude of the plastic industry was that "plastic litter is a very small proportion of all litter and causes no harm to the environment except as an eyesore" [Derraik, J.G.B., 2002. The pollution of the marine environment by plastic debris: a review. Mar. Pollut. Bull. 44(9), 842-852]. Between 1960 and 2000, the world production of plastic resins increased 25-fold, while recovery of the material remained below 5%. Between 1970 and 2003, plastics became the fastest growing segment of the US municipal waste stream, increasing nine-fold, and marine litter is now 60-80% plastic, reaching 90-95% in some areas. While undoubtedly still an eyesore, plastic debris today is having significant harmful effects on marine biota. Albatross, fulmars, shearwaters and petrels mistake floating plastics for food, and many individuals of these species are affected; in fact, 44% of all seabird species are known to ingest plastic. Sea turtles ingest plastic bags, fishing line and other plastics, as do 26 species of cetaceans. In all, 267 species of marine organisms worldwide are known to have been affected by plastic debris, a number that will increase as smaller organisms are assessed. The number of fish, birds, and mammals that succumb each year to derelict fishing nets and lines in which they become entangled cannot be reliably known; but estimates are in the millions. We divide marine plastic debris into two categories: macro, >5 mm and micro, <5 mm. While macro-debris may sometimes be traced to its origin by object identification or markings, micro-debris, consisting of particles of two main varieties, (1) fragments broken from larger objects, and (2) resin pellets and powders, the basic thermoplastic industry feedstocks, are difficult to trace. Ingestion of plastic micro-debris by filter feeders at the base of the food web is known to occur, but has not been quantified. Ingestion of degraded plastic pellets and fragments raises toxicity concerns, since plastics are known to adsorb hydrophobic pollutants. The potential bioavailability of compounds added to plastics at the time of manufacture, as well as those adsorbed from the environment are complex issues that merit more widespread investigation. The physiological effects of any bioavailable compounds desorbed from plastics by marine biota are being directly investigated, since it was found 20 years ago that the mass of ingested plastic in Great Shearwaters was positively correlated with PCBs in their fat and eggs. Colonization of plastic marine debris by sessile organisms provides a vector for transport of alien species in the ocean environment and may threaten marine biodiversity. There is also potential danger to marine ecosystems from the accumulation of plastic debris on the sea floor. The accumulation of such debris can inhibit gas exchange between the overlying waters and the pore waters of the sediments, and disrupt or smother inhabitants of the benthos. The extent of this problem and its effects have recently begun to be investigated. A little more than half of all thermoplastics will sink in seawater.


title: Image morphing for space-time interpolation

abstract: The human brain automatically attempts to interpret the physical visual inputs from our eyes in terms of plausible motion of the viewpoint and/or of the observed object or scene [Ellis 1938; Graham 1965; Giese and Poggio 2003]. In the physical world, the rules that define plausible motion are set by temporal coherence, parallax, and perspective projection. Our brain, however, refuses to feel constrained by the unrelenting laws of physics in what it deems plausible motion. Image metamorphosis experiments, in which unnatural, impossible in-between images are interpolated, demonstrate that under certain circumstances, we willingly accept chimeric images as plausible transition stages between images of actual, known objects [Beier and Neely 1992; Seitz and Dyer 1996]. Or think of cartoon animations which for the longest time were hand-drawn pieces of art that didn't need to succumb to physical correctness. The goal of our work is to exploit this freedom of perception for space-time interpolation, i.e., to generate transitions between still images that our brain accepts as plausible motion in a moving 3D world.


title: 3D hand posture recognition using MultiCam

abstract: This paper presents the hand posture recognition in 3D using the MultiCam, a monocular 2D/3D camera developed by Center of Sensorsystems (ZESS). The MultiCam is a camera which is capable to provide high resolution of color data acquired from CMOS sensors and low resolution of distance (or range) data calculated based on time-of-flight (ToF) technology using Photonic Mixer Device (PMD) sensors. The availability of the distance data allows the hand posture to be recognized in z-axis direction without complex computational algorithms which also enables the program to work in real-time processing as well as eliminates the background effectively. The hand posture recognition will employ a simple but robust algorithm by checking the number of fingers detected around virtually created circle centered at the Center of Mass (CoM) of the hand and therefore classifies the class associated with a particular hand posture. At the end of this paper, the technique that uses intersection between the circle and fingers as the method to classify the hand posture which entails the MultiCam capability is proposed. This technique is able to solve the problem of orientation, size and distance invariants by utilizing the distance data.


title: Role of Prefrontal Persistent Activity in Working Memory

abstract: The prefrontal cortex is activated during working memory, as evidenced by fMRI results in human studies and neurophysiological recordings in animal models. Persistent activity during the delay period of working memory tasks, after the offset of stimuli that subjects are required to remember, has traditionally been thought of as the neural correlate of working memory. In the last few years several findings have cast doubt on the role of this activity. By some accounts, activity in other brain areas, such as the primary visual and posterior parietal cortex, is a better predictor of information maintained in visual working memory and working memory performance; dynamic patterns of activity may convey information without requiring persistent activity at all; and prefrontal neurons may be ill-suited to represent non-spatial information about the features and identity of remembered stimuli. Alternative interpretations about the role of the prefrontal cortex have thus been suggested, such as that it provides a top-down control of information represented in other brain areas, rather than maintaining a working memory trace itself. Here we review evidence for and against the role of prefrontal persistent activity, with a focus on visual neurophysiology. We show that persistent activity predicts behavioral parameters precisely in working memory tasks. We illustrate that prefrontal cortex represents features of stimuli other than their spatial location, and that this information is largely absent from early cortical areas during working memory. We examine memory models not dependent on persistent activity, and conclude that each of those models could mediate only a limited range of memory-dependent behaviors. We review activity decoded from brain areas other than the prefrontal cortex during working memory and demonstrate that these areas alone cannot mediate working memory maintenance, particularly in the presence of distractors. We finally discuss the discrepancy between BOLD activation and spiking activity findings, and point out that fMRI methods do not currently have the spatial resolution necessary to decode information within the prefrontal cortex, which is likely organized at the micrometer scale. Therefore, we make the case that prefrontal persistent activity is both necessary and sufficient for the maintenance of information in working memory.


title: The Aberrant Behavior Checklist: A Behavior Rating Scale for the Assessment of Treatment Effects.

abstract: The development of a scale to assess drug and other treatment effects on severely mentally retarded individuals was described. In the first stage of the project, an initial scale encompassing a large number of behavior problems was used to rate 418 residents. The scale was then reduced to an intermediate version, and in the second stage, 509 moderately to profoundly retarded individuals were rated. Separate factor analyses of the data from the two samples resulted in a five-factor scale comprising 58 items. The factors of the Aberrant Behavior Checklist have been labeled as follows: (I) Irritability, Agitation, Crying; (II) Lethargy, Social Withdrawal; (III) Stereotypic Behavior; (IV) Hyperactivity, Noncompliance; and (V) Inappropriate Speech. Average subscale scores were presented for the instrument, and the results were compared with empirically derived rating scales of childhood psychopathology and with factor analytic work in the field of mental retardation.


title: Relations between abundance of potential geosmin- and 2-MIB-producing organisms and concentrations of these compounds in water from three Australian reservoirs

abstract: Relationships between the abundance of potential geosmin- and 2-methylisoborneol-producing (2-MIB) cyanobacteria and bacteria, and concentrations of the two taste and odour compounds (T&Os) were examined in a 7 day incubation of natural water from the surface and bottom of three reservoirs in southeast Queensland, Australia. Only a single known T&O-producing cyanobacterium ( Geitlerinema spp.) was detected by microscopy at low density, and only in one reservoir. Densities of potential T&O-producing Streptomyces (determined by quantitative polymerase chain reaction (qPCR) assay) were highest in the bottom water and varied from 0.7 × 103 to 775 × 103 cells L−1. Geosmin ranged from 6 to 59 ng L−1 (with the highest concentrations in the bottom water), while 2-MIB varied from 6 to 47 ng L−1 (with the highest concentration in surface water). Concentrations of both compounds declined during the incubation under both light and dark conditions. Presence of the geosmin synthase gene, geoA, in cyanobacteria and Streptomyces was examined by different PCR approaches. Cloning of PCR products from amplification of geoA showed a high similarity to geoA in cyanobacteria, but not to streptomycetes. Our results demonstrate that more research on the ecology and molecular biology of T&O producers is required to better understand the dynamics of T&Os and to monitor emerging T&O episodes.


title: Advanced DC-SF Cell Technology for 3-D NAND Flash

abstract: Advanced dual control gate with surrounding floating gate (DC-SF) cell process and operation schemes are successfully developed for 3-D nand flash memories. To improve performance and reliability of DC-SF cell, new metal control gate last (MCGL) process is developed. The MCGL process can realize a low resistive tungsten (W) metal wordline, a low damage on tunnel oxide/inter-poly dielectric (IPD), and a preferable floating gate (FG) shape. Also, new read and program operation schemes are developed. In the new read operation, the higher and lower Vpass-read are alternately applied to unselected control gates to compensate lowering FG potential to be a pass transistor. In the new program scheme, the optimized Vpass are applied to neighbor WL of selected WL to prevent program disturb and charge loss through IPD. Thus, by using the MCGL process and new read/program schemes, the high performance and reliability of the DC-SF cell can be realized for 3-D nand flash memories.


title: eAGROBOT — A robot for early crop disease detection using image processing

abstract: Management of crops from early stage to mature harvest stage involves identification and monitoring of plant diseases, nutrient deficiency, controlled irrigation and controlled use of fertilizers and pesticides. Although the number of remote sensing solutions is increasing, the availability and ground visibility during critical growth stages of crops continue to be major concerns. eAGROBOT (a prototype) is a ground based agricultural robot that overcomes challenges existing in large and complex satellite based solutions and helpdesk form of solutions available as m-Services. It provides a small, portable and reliable platform to automatically survey farmland, detect diseases as well as spray the pesticide. In future, the farmer can obtain a consolidated view of the farm along with decision support statistics for planning purposes. The development of eAGROBOT, real time testing results obtained from cotton and groundnut plantations and future focus has been detailed in this paper.


title: Follicular development of canine ovaries stimulated by a combination treatment of eCG and hCG

abstract: Ovarian follicular dynamics is not well known in dogs. Imaging of ovaries is technically difficult; however, ovaries clamped at a subcutaneous site can more easily be monitored using ultrasound imaging. This study investigated the follicular development of canine ovaries stimulated by hormone treatment using ultrasound imaging of the ovaries clamped at a subcutaneous site. Oestrus was induced using subcutaneous administration of 500 IU equine chorionic gonadotropin (eCG) and 1000 IU human chorionic gonadotropin (hCG) (eCG/hCG). Five bitches were given 1000 IU hCG 11 days after eCG/hCG administration. Examinations with ovarian ultrasonography using a 7.5-MHz sector transducer, vaginal cytology, and assays of serum oestrogen and progesterone were performed daily until 20 days after eCG/hCG administration. Serosanguineous vaginal discharges and vaginal cytology of two of the bitches were observed. New follicular growth (>1.0 mm in diameter) was observed in all bitches from 2 to 8 days after eCG/hCG administration. The mean diameter of follicles and maximum numbers of follicles per ovary ranged from 2.8 to 5.5 mm and 4 to 16, respectively. The elevation in oestrogen concentrations after eCG/hCG administration was observed in all bitches, and elevation in progesterone concentration (>2 ng mL-1 ) was observed in three bitches. However, no follicles ovulated until 9 days after hCG administration. In conclusion, although the number of examined bitches were limited, follicular growth in ovaries clamped at a subcutaneous site can be monitored using ultrasound imaging. Ovarian ultrasonography showed that eCG/hCG administration induced new follicular growth and hCG administration induced increases in oestrogen concentrations but not ovulation by hCG administration.


title: Evaluation of Multi Criteria Decision Making Methods for Potential Use in Application Security

abstract: With an upsurge in number of available smart phones, tablet PCs etc. most users find it easy to access Internet services using mobile applications. It has been a challenging task for mobile applica ...


title: Visual SLAM by Single-Camera Catadioptric Stereo

abstract: In this paper, we present a robust simultaneous localization and mapping (SLAM) framework using a single camera catadioptric stereo system composed of vertically aligned two hyperboloidal mirrors and a CCD camera. In the SLAM, conventional stereo cameras have some problems due to their narrow field of view, for example, the data association problem which occurs in the featureless homogeneous regions or dynamic environments where moving persons or objects exist and error accumulation when the robot moves for a long time. However, a single camera catadioptric stereo system which gives not only a full horizontal field of view but the 3D locations of the landmarks helps to solve the above problems. For more accurate motion estimation, we propose the outlier detection algorithm to eliminate mismatched or incorrectly tracked features. We also propose the rectification algorithm that makes the mirrors and a camera parallel each other to satisfy single viewpoint (SVP). We analyze the proposed methodology through various experiments and have shown the robustness of the proposed SLAM algorithm


title: Impact of land use on river systems in Ghana

abstract: Rivers play significant roles in the provision of water for domestic and industrial purposes. Nevertheless, land use dynamics continue to impact on river catchments which have negative repercussions for river health. This study focuses on land use change in the Okyeman Traditional Area, which encompasses three major river basins namely, the Densu, the Birim and the Ayensu. The study was aimed at investigating causes and impacts of land use change within the three river catchments and how these impacts could be curtailed to safeguard river health and sustainable water supply. Data for the study was derived from analysis of remotely sensed Landsat 7 ETM satellite imagery, and from questionnaire administration. Additional information was culled from the existing literature on land use, land use change, land cover change and related subjects. One major finding was that most of the river basins have undergone massive transformation over the last three decades as a result of various land use activities. The dominant land use types in the basins presently are agriculture, urban development, grazing, residential and transportation and fishing. The study also revealed that mining, indiscriminate waste disposal, water extraction and deforestation for fuel wood and other domestic uses, excessive use of chemical fertilizers and land degradation due to improper agricultural practices are also major land use activities that impact negatively on the river systems. The study concluded that there is the need to streamline land use activities, conserve vital ecosystems like watershed areas and maintain buffers along stream channels as a matter of policy to ensure adequate protection of aquatic fauna and to ensure sustainable water supply.


title: Cognitive processes , models and metaphors in decision research

abstract: Decision research in psychology has traditionally been influenced by the \textit{homo oeconomicus} metaphor with its emphasis on normative models and deviations from the predictions of those models. In contrast, the principal metaphor of cognitive psychology conceptualizes humans as `information processors', employing processes of perception, memory, categorization, problem solving and so on. Many of the processes described in cognitive theories are similar to those involved in decision making, and thus increasing cross-fertilization between the two areas is an important endeavour. A wide range of models and metaphors has been proposed to explain and describe `information processing' and many models have been applied to decision making in ingenious ways. This special issue encourages cross-fertilization between cognitive psychology and decision research by providing an overview of current perspectives in one area that continues to highlight the benefits of the synergistic approach: cognitive modeling of multi-attribute decision making. In this introduction we discuss aspects of the cognitive system that need to be considered when modeling multi-attribute decision making (e.g., automatic versus controlled processing, learning and memory constraints, metacognition) and illustrate how such aspects are incorporated into the approaches proposed by contributors to the special issue. We end by discussing the challenges posed by the contrasting and sometimes incompatible assumptions of the models and metaphors.


title: A diary study of password usage in daily life

abstract: While past work has examined password usage on a specific computer, web site, or organization, there is little work examining overall password usage in daily life. Through a diary study, we examine all usage of passwords, and offer some new findings based on quantitative analyses regarding how often people log in, where they log in, and how frequently people use foreign computers. Our analysis also confirms or updates existing statistics about password usage patterns. We also discuss some implications for design as well as security education.


title: Normally OFF Trench CAVET With Active Mg-Doped GaN as Current Blocking Layer

abstract: A normally OFF trench current aperture vertical electron transistor (CAVET) was designed and successfully fabricated with Mg-doped p-GaN current blocking layers. The buried Mg-doped GaN was activated using a postregrowth annealing process. The source-to-drain body diode showed an excellent p-n junction characteristics, blocking over 1 kV, sustaining a maximum blocking electric field of 3.8 MV/cm. Three-terminal breakdown voltages of trench-CAVETs, measured up to 225 V, were limited by dielectric breakdown. This paper highlights the achievement of the well-behaved buried p-n junction that has been a formidable challenge in the success of vertical GaN devices.


title: Flywheel: Google's data compression proxy for the mobile web

abstract: Mobile devices are increasingly the dominant Internet access technology. Nevertheless, high costs, data caps, and throttling are a source of widespread frustration, and a significant barrier to adoption in emerging markets. This paper presents Flywheel, an HTTP proxy service that extends the life of mobile data plans by compressing responses in-flight between origin servers and client browsers. Flywheel is integrated with the Chrome web browser and reduces the size of proxied web pages by 50% for a median user. We report measurement results from millions of users as well as experience gained during three years of operating and evolving the production service at Google.


title: Slope One Predictors for Online Rating-Based Collaborative Filtering

abstract: Rating-based collaborative filtering is the process of predicting how a user would rate a given item from other user ratings. We propose three related slope one schemes with predictors of the form f(x) = x + b, which precompute the average difference between the ratings of one item and another for users who rated both. Slope one algorithms are easy to implement, efficient to query, reasonably accurate, and they support both online queries and dynamic updates, which makes them good candidates for real-world systems. The basic slope one scheme is suggested as a new reference scheme for collaborative filtering. By factoring in items that a user liked separately from items that a user disliked, we achieve results competitive with slower memory-based schemes over the standard benchmark EachMovie and Movielens data sets while better fulfilling the desiderata of CF applications.


Balancedenergy sleep scheduling scheme for high density cluster-based sensor networks


title: Fuzzing the Linux kernel

abstract: The development of Linux is one of the most prominent examples of free and open-source software collaboration. The kernel is used in many projects including Android which has over 82% in market share worldwide. Therefore, Linux's kernel security has a lot of impact on IT&C industry.


Workflow Management: Models, Methods, and Systems


title: A Haptic Tool for Group Work on Geometrical Concepts Engaging Blind and Sighted Pupils

abstract: In the study presented here, two haptic and visual applications for learning geometrical concepts in group work in primary school have been designed and evaluated. The aim was to support collaborative learning among sighted and visually impaired pupils. The first application is a static flattened 3D environment that supports learning to distinguish between angles by means of a 3D haptic device providing touch feedback. The second application is a dynamic 3D environment that supports learning of spatial geometry. The scene is a room with a box containing geometrical objects, which pupils can pick up and move around. The applications were evaluated in four schools with groups of two sighted and one visually impaired pupil. The results showed the support for the visually impaired pupil and for the collaboration to be satisfying. A shared understanding of the workspace could be achieved, as long as the virtual environment did not contain movable objects. Verbal communication was crucial for the work process but haptic guiding to some extent substituted communication about direction. When it comes to joint action between visually impaired and sighted pupils a number of interesting problems were identified when the dynamic and static virtual environments were compared. These problems require further investigation. The study extends prior work in the areas of assistive technology and multimodal communication by evaluating functions for joint haptic manipulation in the unique setting of group work in primary school.


title: Fast defocus map estimation

abstract: This paper presents a fast algorithm for deriving the defocus map from a single image. Existing methods of defocus map estimation often include a pixel-level propagation step to spread the measured sparse defocus cues over the whole image. Since the pixel-level propagation step is time-consuming, we develop an effective method to obtain the whole-image defocus blur using oversegmentation and transductive inference. Oversegmentation produces the superpixels and hence greatly reduces the computation costs for subsequent procedures. Transductive inference provides a way to calculate the similarity between superpixels, and thus helps to infer the defocus blur of each superpixel from all other superpixels. The experimental results show that our method is efficient and able to estimate a plausible superpixel-level defocus map from a given single image.


title: Feature Selection by Joint Graph Sparse Coding

abstract: This paper takes manifold learning and regression simultaneously into account to perform unsupervised spectral feature selection. We first extract the bases of the data, and then represent the data sparsely using the extracted bases by proposing a novel joint graph sparse coding model, JGSC for short. We design a new algorithm TOSC to compute the resulting objective function of JGSC, and then theoretically prove that the proposed objective function converges to its global optimum via the proposed TOSC algorithm. We repeat the extraction and the TOSC calculation until the value of the objective function of JGSC satisfies pre-defined conditions. Eventually the derived new representation of the data may only have a few non-zero rows, and we delete the zero rows (a.k.a. zero-valued features) to conduct feature selection on the new representation of the data. Our empirical studies demonstrate that the proposed method outperforms several state-of-the-art algorithms on real datasets in term of the kNN classification performance.


title: Digital multiphase buck converter with current balance/phase shedding control

abstract: This paper presents a 2-phase interleaved buck converter which both has current balance and phase shedding control. These methods have been incorporated into high current multiphase converters in the past. But in this paper, it operates under low current situation which meets the portable device specification. A voltage mode digital controller in FPGA implementation is described. Experimental results are obtained for a 1 MHz, 1V/0.8A 2-phase voltage mode buck regulator.


title: Information diffusion and external influence in networks

abstract: Social networks play a fundamental role in the diffusion of information. However, there are two different ways of how information reaches a person in a network. Information reaches us through connections in our social networks, as well as through the influence external out-of-network sources, like the mainstream media. While most present models of information adoption in networks assume information only passes from a node to node via the edges of the underlying network, the recent availability of massive online social media data allows us to study this process in more detail. We present a model in which information can reach a node via the links of the social network or through the influence of external sources. We then develop an efficient model parameter fitting technique and apply the model to the emergence of URL mentions in the Twitter network. Using a complete one month trace of Twitter we study how information reaches the nodes of the network. We quantify the external influences over time and describe how these influences affect the information adoption. We discover that the information tends to "jump" across the network, which can only be explained as an effect of an unobservable external influence on the network. We find that only about 71% of the information volume in Twitter can be attributed to network diffusion, and the remaining 29% is due to external events and factors outside the network.


title: Brain activity and connectivity during poetry composition: Toward a multidimensional model of the creative process

abstract: Creativity, a multifaceted construct, can be studied in various ways, for example, investigating phases of the creative process, quality of the creative product, or the impact of expertise. Previous neuroimaging studies have assessed these individually. Believing that each of these interacting features must be examined simultaneously to develop a comprehensive understanding of creative behavior, we examined poetry composition, assessing process, product, and expertise in a single experiment. Distinct activation patterns were associated with generation and revision, two major phases of the creative process. Medial prefrontal cortex (MPFC) was active during both phases, yet responses in dorsolateral prefrontal and parietal executive systems (DLPFC/IPS) were phase-dependent, indicating that while motivation remains unchanged, cognitive control is attenuated during generation and re-engaged during revision. Experts showed significantly stronger deactivation of DLPFC/IPS during generation, suggesting that they may more effectively suspend cognitive control. Importantly however, similar overall patterns were observed in both groups, indicating the same cognitive resources are available to experts and novices alike. Quality of poetry, assessed by an independent panel, was associated with divergent connectivity patterns in experts and novices, centered upon MPFC (for technical facility) and DLPFC/IPS (for innovation), suggesting a mechanism by which experts produce higher quality poetry. Crucially, each of these three key features can be understood in the context of a single neurocognitive model characterized by dynamic interactions between medial prefrontal areas regulating motivation, dorsolateral prefrontal, and parietal areas regulating cognitive control and the association of these regions with language, sensorimotor, limbic, and subcortical areas distributed throughout the brain. Hum Brain Mapp 36:3351–3372, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc..


title: Exploring the Value of Online Product Reviews in Forecasting Sales: The Case of Motion Pictures

abstract: The growing popularity of online product review forums invites the development of models and metrics that allow firms to harness these new sources of information for decision support. Our work contributes in this direction by proposing a novel family of diffusion models that capture some of the unique aspects of the entertainment industry and testing their performance in the context of very early postrelease motion picture revenue forecasting. We show that the addition of online product review metrics to a benchmark model that includes prerelease marketing, theater availability and professional critic reviews substantially increases its forecasting accuracy; the forecasting accuracy of our best model outperforms that of several previously published models. In addition to its contributions in diffusion theory, our study reconciles some inconsistencies among previous studies with respect to what online review metrics are statistically significant in forecasting entertainment good sales.


title: For a social network analysis of computer networks: a sociological perspective on collaborative work and virtual community

abstract: When computer networks link people as well as machines, they become social networks. Social network analysis provides a useful approach to moving beyond the concept of “group” in studying virtual communities and computer supported cooperative work and telework. Such computer supported social networks (CSSNS) sustain strong, intermediate and weak ties that provide information and social support in both specialized and broadly-based relationships. They foster informal workplace communities that are usually partial and narrowly-focused, although some do become encompassing and broadly-based. CSSNS connect workers within and between organizations who often are physically dispersed. The nature of the medium both constrains and facilitates management control. Although many relationships function offline as well as online, CSSNS have developed their own norms and structures. They have strong societal implications, fostering situations that combine global connectivity, the fragmentation of solidarities and the de-emphasis of local organization, and the importance of home bases.


title: Two Fast Methods for High-Quality Line Visibility

abstract: Lines drawn over or in place of shaded 3D models can often provide greater comprehensibility and stylistic freedom than shading alone. A substantial challenge for making stylized line drawings from 3D models is the visibility computation. Current algorithms for computing line visibility in models of moderate complexity are either too slow for interactive rendering, or too brittle for coherent animation. We introduce two methods that exploit graphics hardware to provide fast and robust line visibility. First, we present a simple shader that performs a visibility test for high-quality, simple lines drawn with the conventional implementation. Next, we offer a full optimized pipeline that supports line visibility and a broad range of stylization options.


title: Migrant Workers in the Construction Industry: The Experience of Tunisians in Modena

abstract: The purpose of this chapter is to explore the class position of migrant workers and their location within the labour market in the construction industry in the northern Italian city of Modena, and in Italy in general. It exposes the relationship between the discrimination and exclusionary practices that these workers have faced, their political vulnerability, and cultural and ethnic diversity. The chapter also describes how the mechanisms of marginalization within the employment relationship, which were utilized against southern emigrants after the Second World War, have been imposed on the incoming migrants. It attempts to locate racism and discrimination against migrant workers within both a cultural and a political economy framework. Cultural and economic dimensions of racism perpetuate the exploitation of the ‘new’ working class - migrants, particularly from North Africa, form a new reservoir of secondary labour. Employers engage migrant workers not only to overcome shortages of labour, particularly in the secondary labour market, but also in an attempt to displace or substitute southern Italian emigrants within the primary market.


title: Power of consumers using social media: Examining the influences of brand-related user-generated content on Facebook

abstract: This study examined the influences of positive brand-related user-generated content (UGC)1 shared via Facebook on consumer response. The model tested was derived from the S-O-R consumer response model (Mehrabian & Russell, 1974) that depicts the effects of environmental/informational stimuli on consumer response. Specific research objectives were to investigate whether brand-related UGC acts as a stimulus to activate consumer behavior in relation to brand and examine the processes by which brand-related UGC influences consumer behavior. Using the S-O-R model, brand-related UGC was treated as stimulus, pleasure and arousal as emotional responses, and perceived information quality as cognitive response. Information pass-along, impulse buying, future-purchase intention, and brand engagement were treated as behavioral responses. Participants (n?=?533) resided in the U.S. and had a Facebook account. Mock Facebook fan pages including brand-related UGC were developed as visual stimuli and presented via an online self-administered questionnaire. SEM was used to analyze the data. Brand-related UGC activated consumers' emotional and cognitive responses. Emotional and cognitive responses significantly influenced behavioral responses. Positive brand-related UGC exerts a significant influence on brand as it provokes consumers' eWOM behavior, brand engagement, and potential brand sales. A model examining the influence of brand-related UGC on consumer was proposed.The process by which brand-related UGC influences consumer was examined.Brand-related UGC activated pleasure as emotional response.Brand-related UGC influenced perceived information quality as cognitive response.Brand-related UGC influences eWOM, brand engagement, and potential brand sales.


title: Treatment of Trigeminal Neuralgia by Posterior-Fossa Microvascular Decompression

abstract: A series of 109 cases of microvascular decompression for intractable trigeminal neuralgia was reviewed. Operations were performed by a single surgeon and cases were reviewed independently by the one author. The failure rate in this study was 17.6%. A further 6.5% of cases endured brief recurrences not requiring treatment. Two-thirds of significant recurrences occurred within the initial 12 months. Long-term complications were experienced in 7.4% of cases. There was one postoperative mortality occumng in a patient with a large fibroblastic meningioma invading the brain stem. The classic Jannetta approach was modified following the first 32 cases allowing the cerebellum to be depressed inferiorly with a subsequent decline in the rate of loss of hearing from 12.5 to 3.7%. In over 70% of cases an aberrant superior cerebellar artery was found compressing the fifth cranial nerve. Patients had dental work performed in an attempt to control the pain prior to operation in 44% of cases.


title: Object pointing: A complement to bitmap pointing in GUIs

abstract: Pointing has been conceptualized and implemented so far as the act of selecting pixels in bitmap displays. We show that the current technique, which we call bitmap pointing (BMP), is often sub-optimal as it requires continuous information from the mouse while the system often just needs the discrete specification of objects. The paper introduces object pointing (OP), a novel interaction technique based on a special screen cursor that skips empty spaces, thus drastically reducing the waste of input information. We report data from 1D and 2D Fitts' law experiments showing that OP outperforms BMP and that the performance facilitation increases with the task's index of difficulty. We discuss the implementation of OP in current interfaces.


title: Deep Reinforcement Learning for Autonomous Driving

abstract: Reinforcement learning has steadily improved and outperform human in lots of traditional games since the resurgence of deep neural network. However, these success is not easy to be copied to autonomous driving because the state spaces in real world are extreme complex and action spaces are continuous and fine control is required. Moreover, the autonomous driving vehicles must also keep functional safety under the complex environments. To deal with these challenges, we first adopt the deep deterministic policy gradient (DDPG) algorithm, which has the capacity to handle complex state and action spaces in continuous domain. We then choose The Open Racing Car Simulator (TORCS) as our environment to avoid physical damage. Meanwhile, we select a set of appropriate sensor information from TORCS and design our own rewarder. In order to fit DDPG algorithm to TORCS, we design our network architecture for both actor and critic inside DDPG paradigm. To demonstrate the effectiveness of our model, We evaluate on different modes in TORCS and show both quantitative and qualitative results.


title: Motion reconstruction using sparse accelerometer data

abstract: The development of methods and tools for the generation of visually appealing motion sequences using prerecorded motion capture data has become an important research area in computer animation. In particular, data-driven approaches have been used for reconstructing high-dimensional motion sequences from low-dimensional control signals. In this article, we contribute to this strand of research by introducing a novel framework for generating full-body animations controlled by only four 3D accelerometers that are attached to the extremities of a human actor. Our approach relies on a knowledge base that consists of a large number of motion clips obtained from marker-based motion capturing. Based on the sparse accelerometer input a cross-domain retrieval procedure is applied to build up a lazy neighborhood graph in an online fashion. This graph structure points to suitable motion fragments in the knowledge base, which are then used in the reconstruction step. Supported by a kd-tree index structure, our procedure scales to even large datasets consisting of millions of frames. Our combined approach allows for reconstructing visually plausible continuous motion streams, even in the presence of moderate tempo variations which may not be directly reflected by the given knowledge base.


title: The implications for visual simulation and analysis of temporal variation in the visibility of wind turbines

abstract: Abstract The visual impact of wind turbines is a central issue in their public acceptance. New wind farm proposals are commonly subject to visual simulation and visual impact assessment. Guidelines for both these processes are already used in a number of jurisdictions and there is widespread interest in making simulation and impact assessments as meaningful as possible. To a large degree the guidelines for both processes tend to be based on worst-case (full-frontal) conditions. There are two quite good reasons for this. Firstly, the worst-case sets a boundary for visual impact. Secondly, we seldom know enough about how visibility or visual impact changes over time and what ‘typical’ conditions are like – or how the range of conditions is distributed. This paper argues that if we can address this knowledge gap, then we may also be able to take a more nuanced approach to simulation and analysis. It should be possible, using widespread atmospheric visibility data, to determine the temporal distribution of visual impacts at a particular location rather computing a single estimate. It may also be valid to create simulations of both worst-case and more typical conditions. This paper explores the key variables affecting visual impacts – visual magnitude and color difference – and how they may be monitored and analyzed efficiently and effectively. A wind farm in southern Victoria, Australia is used as the case study. Recommendations are made on how the approaches could be used more widely.


title: Automated Edge Detection Using Convolutional Neural Network

abstract: The edge detection on the images is so important for image processing. It is used in a various fields of applications ranging from real-time video surveillance and traffic management to medical imaging applications. Currently, there is not a single edge detector that has both efficiency and reliability. Traditional differential filter-based algorithms have the advantage of theoretical strictness, but require excessive post-processing. Proposed CNN technique is used to realize edge detection task it takes the advantage of momentum features extraction, it can process any input image of any size with no more training required, the results are very promising when compared to both classical methods and other ANN based methods


title: Clustering Sensors in Wireless Ad Hoc Networks Operating in a Threat Environment

abstract: Sensors in a data fusion environment over hostile territory are geographically dispersed and change location with time. To collect and process data from these sensors, an equally flexible network of fusion beds (i.e., clusterheads) is required. To account for the hostile environment, we allow communication links between sensors and clusterheads to be unreliable. We develop a mixed-integer linear programming (MILP) model to determine the clusterhead location strategy that maximizes the expected data covered minus the clusterhead reassignments, over a time horizon. A column generation (CG) heuristic is developed for this problem. Computational results show that CG performs much faster than a standard commercial solver, and the typical optimality gap for large problems is less than 5%. Improvements to the basic model in the areas of modeling link failure, consideration of bandwidth capacity, and clusterhead changeover cost estimation are also discussed.


title: Communicating emotions in online chat using physiological sensors and animated text

abstract: We present a chat system that uses animateddynamic text associated with emotional information to show the affective state of the user. The system obtains the affective state of a chat user from a physiological sensor attached to the user's body. This paper describes preliminary experiments and provides examples of possible applications of our chat system. Observations from informal experiments comparing our animated chat system with a conventional system suggest that an online interface that conveys emotional information helps online users to interact with each other more efficiently.


title: Design Activity Framework for Visualization Design

abstract: An important aspect in visualization design is the connection between what a designer does and the decisions the designer makes. Existing design process models, however, do not explicitly link back to models for visualization design decisions. We bridge this gap by introducing the design activity framework, a process model that explicitly connects to the nested model, a well-known visualization design decision model. The framework includes four overlapping activities that characterize the design process, with each activity explicating outcomes related to the nested model. Additionally, we describe and characterize a list of exemplar methods and how they overlap among these activities. The design activity framework is the result of reflective discussions from a collaboration on a visualization redesign project, the details of which we describe to ground the framework in a real-world design process. Lastly, from this redesign project we provide several research outcomes in the domain of cybersecurity, including an extended data abstraction and rich opportunities for future visualization research.


Hindi Subjective Lexicon : A Lexical Resource for Hindi Polarity Classification


title: Comparison between security majors in virtual machine and linux containers

abstract: Virtualization started to gain traction in the domain of information technology in the early 2000s when managing resource distribution was becoming an uphill task for developers. As a result, tools like VMWare, Hyper V (hypervisor) started making inroads into the software repository on different operating systems. VMWare and Hyper V could support multiple virtual machines running on them with each having their own isolated environment. Due to this isolation, the security aspects of virtual machines (VMs) did not differ much from that of physical machines (having a dedicated operating system on hardware). The advancement made in the domain of linux containers (LXC) has taken virtualization to an altogether different level where resource utilization by various applications has been further optimized. But the container security has assumed primary importance amongst the researchers today and this paper is inclined towards providing a brief overview about comparisons between security of container and VMs.