title: Semantic trajectories modeling and analysis

abstract: Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for: (i) constructing trajectories from movement tracks, (ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and (iii) using data mining to analyze semantic trajectories and extract knowledge about their characteristics, in particular the behavioral patterns of the moving objects. Last but not least, the article surveys the new privacy issues that arise due to the semantic aspects of trajectories.


title: Schools and Obesity Prevention: Creating School Environments and Policies to Promote Healthy Eating and Physical Activity

abstract: Context: Research consistently shows that the majority of American children do not consume diets that meet the recommendations of the Dietary Guidelines for Americans, nor do they achieve adequate levels of daily physical activity. As a result, more children are overweight today than at any other time in U.S. history. Schools offer many opportunities to develop strategies to prevent obesity by creating environments in which children eat healthfully and engage regularly in physical activity. Methods: This article discusses the role of schools in obesity prevention efforts. Currentissuesinschools’foodandphysicalactivityenvironmentsareexamined, as well as federal, state, and local policies related to food and physical activity standards in schools. The article is organized around four key areas: (1) school food environments and policies, (2) school physical activity environments and policies, (3) school body mass index measurements, and (4) school wellness policies. Recommendations for accelerating change also are addressed. Findings: The article found that (1) competitive foods (foods sold outside of federally reimbursed school meals) are widely available in schools, especially secondary schools. Studies have related the availability of snacks and drinks sold in schools to students’ high intake of total calories, soft drinks, total fat and saturated fat, and lower intake of fruits and vegetables; (2) physical activity can be added to the school curriculum without academic consequences and also can offer physical, emotional, and social benefits. Policy leadership has come


title: Adapting boosting for information retrieval measures

abstract: We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empirically optimal for a widely used information retrieval measure. Our algorithm is based on boosted regression trees, although the ideas apply to any weak learners, and it is significantly faster in both train and test phases than the state of the art, for comparable accuracy. We also show how to find the optimal linear combination for any two rankers, and we use this method to solve the line search problem exactly during boosting. In addition, we show that starting with a previously trained model, and boosting using its residuals, furnishes an effective technique for model adaptation, and we give significantly improved results for a particularly pressing problem in web search--training rankers for markets for which only small amounts of labeled data are available, given a ranker trained on much more data from a larger market.


title: A Communication Researchers’ Guide to Null Hypothesis Significance Testing and Alternatives

abstract: This paper offers a practical guide to use null hypotheses significance testing and its alternatives. The focus is on improving the quality of statistical inference in quantitative communication research. More consistent reporting of descriptive statistics, estimates of effect size, confidence intervals around effect sizes, and increasing the statistical power of tests would lead to needed improvements over current practices. Alternatives including confidence intervals, effect tests, equivalence tests, and meta-analysis are discussed.


title: An algorithmic solution of N-person games

abstract: Two-person, perfect information, constant sum games have been studied in Artificial Intelligence. This paper opens up the issue of playing n-person games and proposes a procedure for constant sum or non-constant sum games. It is proved that a procedure, maxn, locates an equilibrium point given the entire game tree. The minimax procedure for 2-person games using look ahead finds a saddle point of approximations, while maxn finds an equilibrium point of the values of the evaluation function for n-person games using look ahead. Maxn is further analyzed with respect to some pruning schemes.


Attention Based CLDNNs for Short-Duration Acoustic Scene Classification.


title: FlyJacket: An Upper Body Soft Exoskeleton for Immersive Drone Control

abstract: Most human-drone interfaces, such as joysticks and remote controllers, require attention and developed skills during teleoperation. Wearable interfaces could enable a more natural and intuitive control of drones, which would make this technology accessible to a larger population of users. In this letter, we describe a soft exoskeleton, so called FlyJacket, designed for naive users that want to control a drone with upper body gestures in an intuitive manner. The exoskeleton includes a motion-tracking device to monitor body movements, an arm support system to prevent fatigue, and is coupled to goggles for first-person-view from the drone perspective. Tests were performed with participants flying a simulated fixed-wing drone moving at a constant speed; participants' performance was more consistent when using the FlyJacket with the arm support than when performing the same task with a remote controller. Furthermore, participants felt more immersed, had more sensation of flying, and reported less fatigue when the arm support was enabled. The FlyJacket has been demonstrated for the teleoperation of a real drone.


Emotion Recognition using Acoustic and Lexical Features


title: Social Brand Value and the Value Enhancing Role of Social Media Relationships for Brands

abstract: Due to the social media revolution and the emergence of communities, social networks, and user generated content portals, prevalent branding concepts need to catch up with this reality. Given the importance of social ties, social interactions and social identity in the new media environment, there is a need to account for a relationship measure in marketing and branding. Based on the concept of social capital we introduce the concept of social brand value, defined as the perceived value derived by exchange and interactions with other users of the brand within a community. Within a qualitative study marketing experts were interviewed and highlighted the importance towards social media activities, but also indicated that they do not have a clear picture on how strategies should look like and how their success can be measured. A second quantitative study was conducted which demonstrates the influence the social brand value construct has for consumers brand evangelism and willingness to pay a price premium and hence the value contribution of the social brand value for consumers.


E-CRISP: fast CRISPR target site identification


title: High‐Dimensional Single‐Cell Mapping of Central Nervous System Immune Cells Reveals Distinct Myeloid Subsets in Health, Aging, and Disease

abstract: Individual reports suggest that the central nervous system (CNS) contains multiple immune cell types with diverse roles in tissue homeostasis, immune defense, and neurological diseases. It has been challenging to map leukocytes across the entire brain, and in particular in pathology, where phenotypic changes and influx of blood-derived cells prevent a clear distinction between reactive leukocyte populations. Here, we applied high-dimensional single-cell mass and fluorescence cytometry, in parallel with genetic fate mapping systems, to identify, locate, and characterize multiple distinct immune populations within the mammalian CNS. Using this approach, we revealed that microglia, several subsets of border-associated macrophages and dendritic cells coexist in the CNS at steady state and exhibit disease-specific transformations in the immune microenvironment during aging and in models of Alzheimer's disease and multiple sclerosis. Together, these data and the described framework provide a resource for the study of disease mechanisms, potential biomarkers, and therapeutic targets in CNS disease.


title: Constraint-Based refactoring with foresight

abstract: Constraint-based refactoring tools as currently implemented generate their required constraint sets from the programs to be refactored, before any changes are performed. Constraint generation is thus unable to see -- and regard -- the changed structure of the refactored program, although this new structure may give rise to new constraints that need to be satisfied for the program to maintain its original behaviour. To address this problem, we present a framework allowing the constraint-generation process to foresee all changes a refactoring might perform, generating -- at the outset of the refactoring -- all constraints necessary to constrain these changes. As we are able to demonstrate, the computational overhead imposed by our framework, although threatening viability in theory, can be reduced to tractable sizes.


title: Online Belief Propagation for Topic Modeling

abstract: The batch latent Dirichlet allocation (LDA) algorithms play important roles in probabilistic topic modeling, but they are not suitable for processing big data streams due to high time and space compleixty. Online LDA algorithms can not only extract topics from big data streams with constant memory requirements, but also detect topic shifts as the data stream flows. In this paper, we present a novel and easy-to-implement online belief propagation (OBP) algorithm that infers the topic distribution from the previously unseen documents incrementally within the stochastic approximation framework. We discuss intrinsic relations between OBP and online expectation-maximization (OEM) algorithms, and show that OBP can converge to the local stationary point of the LDA's likelihood function. Extensive empirical studies confirm that OBP significantly reduces training time and memory usage while achieves a much lower predictive perplexity when compared with current state-of-the-art online LDA algorithms. Due to its ease of use, fast speed and low memory usage, OBP is a strong candidate for becoming the standard online LDA algorithm.


title: Representation, Analysis, and Recognition of 3D Humans: A Survey

abstract: Computer Vision and Multimedia solutions are now offering an increasing number of applications ready for use by end users in everyday life. Many of these applications are centered for detection, representation, and analysis of face and body. Methods based on 2D images and videos are the most widespread, but there is a recent trend that successfully extends the study to 3D human data as acquired by a new generation of 3D acquisition devices. Based on these premises, in this survey, we provide an overview on the newly designed techniques that exploit 3D human data and also prospect the most promising current and future research directions. In particular, we first propose a taxonomy of the representation methods, distinguishing between spatial and temporal modeling of the data. Then, we focus on the analysis and recognition of 3D humans from 3D static and dynamic data, considering many applications for body and face.


title: Towards a Quality Metric for Dense Light Fields

abstract: Light fields become a popular representation of three-dimensional scenes, and there is interest in their processing, resampling, and compression. As those operations often result in loss of quality, there is a need to quantify it. In this work, we collect a new dataset of dense reference and distorted light fields as well as the corresponding quality scores which are scaled in perceptual units. The scores were acquired in a subjective experiment using an interactive light-field viewing setup. The dataset contains typical artifacts that occur in light-field processing chain due to light-field reconstruction, multi-view compression, and limitations of automultiscopic displays. We test a number of existing objective quality metrics to determine how well they can predict the quality of light fields. We find that the existing image quality metrics provide good measures of light-field quality, but require dense reference light-fields for optimal performance. For more complex tasks of comparing two distorted light fields, their performance drops significantly, which reveals the need for new, light-field-specific metrics.


title: Approximating Betweenness Centrality

abstract: Betweenness is a centrality measure based on shortest paths, widely used in complex network analysis. It is computationally-expensive to exactly determine betweenness; currently the fastest-known algorithm by Brandes requires O(nm) time for unweighted graphs and O(nm + n2 log n) time for weighted graphs, where n is the number of vertices and m is the number of edges in the network. These are also the worstcase time bounds for computing the betweenness score of a single vertex. In this paper, we present a novel approximation algorithm for computing betweenness centrality of a given vertex, for both weighted and unweighted graphs. Our approximation algorithm is based on an adaptive sampling technique that significantly reduces the number of single-source shortest path computations for vertices with high centrality. We conduct an extensive experimental study on real-world graph instances, and observe that our random sampling algorithm gives very good betweenness approximations for biological networks, road networks and web crawls.


title: Pursuits: eye-based interaction with moving targets

abstract: Eye-based interaction has commonly been based on estimation of eye gaze direction, to locate objects for interaction. We introduce Pursuits, a novel and very different eye tracking method that instead is based on following the trajectory of eye movement and comparing this with trajectories of objects in the field of view. Because the eyes naturally follow the trajectory of moving objects of interest, our method is able to detect what the user is looking at, by matching eye movement and object movement. We illustrate Pursuits with three applications that demonstrate how the method facilitates natural interaction with moving targets.


title: An ultrawideband coplanar waveguide-fed tapered ring slot antenna

abstract: In this paper, we present a new coplanar waveguide-fed tapered ring slot antenna for ultrawideband (UWB) applications. This antenna consists of a 50 /spl Omega/ coplanar waveguide feeding line, wideband coplanar waveguide-to-slotline transition, and a pair of curved radiating slots. The impedance bandwidth with VSWR<2 is from 3.1 GHz to more than 12 GHz. The actual operating bandwidth is, however, limited by the distortion of radiation patterns. Such pattern distortion can be attributed to the antenna mode transition and is investigated in this paper with the help of the radiation patterns in the traditional sense as well as a dimensionless normalized antenna transfer function. By suitably allocating such mode-transition phenomenon to the notched band in a UWB radio, we demonstrate that antennas with desirable radiation characteristics in both UWB low and high bands can be readily achieved. The system responses of a transceiving antenna system in free space are addressed as well.


A COMPREHENSIVE SURVEY OF FINGER PRINT RECOGNITION TECHNIQUES


title: Development of a robot finger for five-fingered hand using ultrasonic motors

abstract: A robot finger is developed for five-fingered robot hand having equal number of DOF to human hand. The robot hand is driven by a new method proposed by authors using ultrasonic motors and elastic elements. The method utilizes restoring force of elastic element as driving power for grasping an object, so that the hand can perform the soft and stable grasping motion with no power supply. In addition, all the components are placed inside the hand thanks to the ultrasonic motors with compact size and high torque at low speed. Applying the driving method to multi-DOF mechanism, a robot index finger is designed and implemented. It has equal number of joints and DOF to human index finger, and it is also equal in size to the finger of average adult male. The performance of the robot finger is confirmed by fundamental driving test.


title: Neural evidence for the interplay between language, gesture, and action: A review

abstract: Co-speech gestures embody a form of manual action that is tightly coupled to the language system. As such, the co-occurrence of speech and co-speech gestures is an excellent example of the interplay between language and action. There are, however, other ways in which language and action can be thought of as closely related. In this paper we will give an overview of studies in cognitive neuroscience that examine the neural underpinnings of links between language and action. Topics include neurocognitive studies of motor representations of speech sounds, action-related language, sign language and co-speech gestures. It will be concluded that there is strong evidence on the interaction between speech and gestures in the brain. This interaction however shares general properties with other domains in which there is interplay between language and action.


title: Improving Usability of Integrated Emergency Response Systems: The SoKNOS Approach

abstract: Implementing systems for emergency response poses various challenges. Information from various sources and systems needs to be integrated, processed, aggregated, and visualized in a dynamic and consistent fashion. Amongst all those challenges, one key issue is the development of an optimal user interface, which allows for intuitive operation with different information as well as supports collaborative work, even in stressful situations. In this paper, we introduce the SoKNOS system, an emergency response system addressing those challenges and putting special emphasis on usability. We illustrate how integration on the user interface level enables both efficient engineering and improved usability for emergency management systems, and how collaborative interaction in emergency situations is supported by SoKNOS.


title: Applications and Challenges of Wearable Visual Lifeloggers

abstract: Advances in the manufacturing of miniaturized low-power embedded systems are paving the way for ultra-lightweight wearable cameras that can visually log the minute details of people's daily lives. This survey highlights the possible applications of wearable cameras, from industrial to personal, and outlines the main challenges in realizing their full potential.


Supporting Fast Iteration in Model Building


title: Visual Analysis of MOOC Forums with iForum

abstract: Discussion forums of Massive Open Online Courses (MOOC) provide great opportunities for students to interact with instructional staff as well as other students. Exploration of MOOC forum data can offer valuable insights for these staff to enhance the course and prepare the next release. However, it is challenging due to the large, complicated, and heterogeneous nature of relevant datasets, which contain multiple dynamically interacting objects such as users, posts, and threads, each one including multiple attributes. In this paper, we present a design study for developing an interactive visual analytics system, called iForum, that allows for effectively discovering and understanding temporal patterns in MOOC forums. The design study was conducted with three domain experts in an iterative manner over one year, including a MOOC instructor and two official teaching assistants. iForum offers a set of novel visualization designs for presenting the three interleaving aspects of MOOC forums (i.e., posts, users, and threads) at three different scales. To demonstrate the effectiveness and usefulness of iForum, we describe a case study involving field experts, in which they use iForum to investigate real MOOC forum data for a course on JAVA programming.


title: Building castles out of mud: practical access pattern privacy and correctness on untrusted storage

abstract: We introduce a new practical mechanism for remote data storage with efficient access pattern privacy and correctness. A storage client can deploy this mechanism to issue encrypted reads, writes, and inserts to a potentially curious and malicious storage service provider, without revealing information or access patterns. The provider is unable to establish any correlation between successive accesses, or even to distinguish between a read and a write. Moreover, the client is provided with strong correctness assurances for its operations -- illicit provider behavior does not go undetected. We built a first practical system -- orders of magnitude faster than existing implementations -- that can execute over several queries per second on 1Tbyte+ databases with full computational privacy and correctness.


title: On the use of windows for harmonic analysis with the discrete Fourier transform

abstract: This paper makes available a concise review of data windows and their affect on the detection of harmonic signals in the presence of broad-band noise, and in the presence of nearby strong harmonic interference. We also call attention to a number of common errors in the application of windows when used with the fast Fourier transform. This paper includes a comprehensive catalog of data windows along with their significant performance parameters from which the different windows can be compared. Finally, an example demonstrates the use and value of windows to resolve closely spaced harmonic signals characterized by large differences in amplitude.


title: Road Sign Detection and Recognition using Colour Segmentation, Shape Analysis and Template Matching

abstract: The paper presents a system for detection and recognition of road signs with red boundaries and black symbols inside. The detection is invariant to varying lighting conditions and shadows. The algorithm is tested on RGB images taken from camera. These images are converted to HSV colour space. Colour segmentation for red regions is applied on the whole image. All red regions are labeled forming objects. Each of the red objects is tested for its shape. Final image contains only those red objects which are triangular or circular in shape. Finding the black regions within the accepted red objects area, results in extraction of pictogram. This pictogram is then matched with templates in database, hence recognizing the meaning of road sign. The paper presents a revised edition of fuzzy shape detector and a recognition module that uses template matching to recognize rotated and affine transformed road signs.


title: ShapeTex: Implementing Shape-Changing Structures in Fabric for Wearable Actuation

abstract: Research in smart textiles and garments has mostly focused on integrating sensing technology. In order to make garments that are truly interactive it is also essential to develop technologies for actuating smart garments and textiles. This paper introduces ShapeTex, a thermal shape changing fabric that uses laminate thermal expansion to actuate textiles. We present the design process and rationale for ShapeTex; we explain the fabrication process we have developed for making ShapeTex accessible to fashion designers and interaction designers. Based on co-creation sessions with designers we discuss requirements derived from this material. Finally we present a number of concept prototypes created to explore and illustrate the potential applications of ShapeTex.


Disinflation and Labor Market Distortions: Lessons from Slovenia


title: Sample size calculation for the proportional hazards model with a time-dependent covariate

abstract: The Cox proportional hazards (PH) model with time-dependent covariates (referred to as the extended PH model) has been widely used in medical and health related studies to investigate the effects of time-varying risk factors on survival. Theories and practices regarding model estimation and fitting have been well developed for the extended PH model. However, little has been done regarding sample size calculations in survival studies involving a time-varying risk factor. A novel sample size formula based on the extended PH model is proposed by investigating the asymptotic distributions of the weighted log-rank statistics under the null and local alternative hypotheses. The derived sample size formula is an extension of the sample size formula for the standard Cox PH model. The performance of the proposed formula is evaluated by extensive simulations, and examples based on real data are given to illustrate the applications of the proposed methods.


title: DESIGN AND ECONOMICAL OF ROOF TRUSSES & PURLINS (COMPARISON OF LIMIT STATE AND WORKING STRESS METHOD)

abstract: For a structural design to be satisfactory, generally four major objectives – utility, safety, economical and elegance must be fulfilled. This paper presents a study on behaviour and economical of roof trusses and purlins by comparison of limit state and working stress method. Roof trusses and purlins are therefore an integral part of an industrial building and the like for supporting the roofing system. This paper presents a study on behaviour and economical of fink type roof trusses, channel section purlins by comparison of limit state and working stress method. This study involves in examination of theoretical investigations of specimens in series. Overall two methods were designed and comparison of all the internal force, economical, and hence, to evaluate the coexisting moments and shear forces at the critical cross-section with same configuration area by keeping all other parameters constant. The theoretical data are calculated using Indian Standard code IS 875-1975 (part III), IS 800 – 2007 using limit state method, IS 800- 1984 using working stress method and the section properties of the specimens are obtained using steel table. The specimens are designed under uniformly distributed loading with simply supported condition. The research project aims to provide which method is economical, high bending strength, more load carrying capacity and high flexural strength. The studies reveal that the theoretical investigations limit state method design is high bending strength, high load caring capacity, minimum deflection and minimum local buckling& distortional buckling compare to the working stress method. But working stress method is most economical compare to the limit state method design.


Towards a 15.5W Si-LDMOS Energy Efficient Balanced RF Power Amplifier for 5G-LTE Multi-carrier Applications


title: Hybrid algorithms for recommending new items

abstract: Despite recommender systems based on collaborative filtering typically outperform content-based systems in terms of recommendation quality, they suffer from the new item problem, i.e., they are not able to recommend items that have few or no ratings. This problem is particularly acute in TV applications, where the catalog of available items (e.g., TV programs) is very dynamic. On the contrary, content-based recommender systems are able to recommend both old and new items but the general quality of the recommendations in terms of relevance to the users is low. In this article we present two different approaches for building hybrid collaborative+content recommender systems, whose purpose is to produce relevant recommendations, while overcoming the new item issue. The approaches have been tested on two datasets: a version of the well--known Movielens dataset enriched with content meta--data, and an implicit dataset collected from 15'000 IPTV users over a period of six months.


The Experts in the Crowd : The Role of Reputable Investors in a Crowdfunding Market


title: Review of dynamic recovery effects on ion irradiation damage in ionic-covalent materials

abstract: Abstract Single crystalline samples of highly ionic Ca2La8(SiO4)6O2 and covalent 6H–SiC have been irradiated with different ions/energies to study the effects of dose, temperature, damage-energy density, and in-cascade ionization rate on the dynamics of irradiation-induced amorphization. Above temperatures of 100–150 K, the dose for complete amorphization, D, increases with temperature in a single stage and exhibits a strong dependence on the ratio of in-cascade recovery to displacement cross sections, σr/σd. A fit of a dynamic model for amorphization to these data indicates that irradiation-induced dynamic recovery occurs with an activation energy of 0.15 ± 0.02 and 0.12 ± 0.01 eV for Ca2La8(SiO4)6O2 and 6H–SiC, respectively. Analysis of these data reveals that ionization processes are the dominant contributor to in-cascade recovery in Ca2La8(SiO4)6O2; while in 6H–SiC, ionization processes are less dominant.


title: Efficient and Customizable Data Partitioning Framework for Distributed Big RDF Data Processing in the Cloud

abstract: Big data business can leverage and benefit from the Clouds, the most optimized, shared, automated, and virtualized computing infrastructures. One of the important challenges in processing big data in the Clouds is how to effectively partition the big data to ensure efficient distributed processing of the data. In this paper we present a Scalable and yet customizable data PArtitioning framework, called SPA, for distributed processing of big RDF graph data. We choose big RDF datasets as our focus of the investigation for two reasons. First, the Linking Open Data cloud has put forwards a good number of big RDF datasets with tens of billions of triples and hundreds of millions of links. Second, such huge RDF graphs can easily overwhelm any single server due to the limited memory and CPU capacity and exceed the processing capacity of many conventional data processing software systems. Our data partitioning framework has two unique features. First, we introduce a suite of vertexcentric data partitioning building blocks to allow efficient and yet customizable partitioning of large heterogeneous RDF graph data. By efficient, we mean that the SPA data partitions can support fast processing of big data of different sizes and complexity. By customizable, we mean that the SPA partitions are adaptive to different query types. Second, we propose a selection of scalable techniques to distribute the building block partitions across a cluster of compute nodes in a manner that minimizes inter-node communication cost by localizing most of the queries on distributed partitions. We evaluate our data partitioning framework and algorithms through extensive experiments using both benchmark and real datasets. Our experimental results show that the SPA data partitioning framework is not only efficient for partitioning and distributing big RDF datasets of diverse sizes and structures but also effective for processing big data queries of different types and complexity.


title: Joint models for extracting adverse drug events from biomedical text

abstract: Extracting adverse drug events receives much research attention in the biomedical community. Previous work adopts pipeline models, firstly recognizing drug/disease entity mentions and then identifying adverse drug events from drug/disease pairs. In this paper, we investigate joint models for simultaneously extracting drugs, diseases and adverse drug events. Compared with pipeline models, joint models have two main advantages. First, they make use of information integration to facilitate performance improvement; second, they reduce error propagation in pipeline methods. We compare a discrete model and a deep neural model for extracting drugs, diseases and adverse drug events jointly. Experimental results on a standard ADE corpus show that the discrete joint model outperforms a state-of-the-art baseline pipeline significantly. In addition, when discrete features are replaced by neural features, the recall is further improved.


title: Archaeobotanical consideration of the development of Pre-Roman Iron Age crop growing in the region of Hesse, Germany, and the question of agricultural production and consumption at hillfort sites and open settlements

abstract: Archaeobotanical investigations into centralisation processes and related social developments between 800 and 400 b.c. are part of a supra-regional interdisciplinary research program. A diachronous approach is used to reconstruct Late-Bronze Age/Early Iron Age agriculture and food production and to investigate agricultural developments. In addition the results from assumed “central places”, the hillfort sites, are compared with those of open rural settlements in their surroundings. The charred plant assemblages give evidence of an increase in diversity of crop species at the beginning of the 5th century b.c. This change may indicate an alteration in the agricultural system to allow an increase in and/or a minimisation of risk to food production.


title: Delimitation of permanent protected areas of rivers in Brazil

abstract: This paper presents a methodology to determine the permanent protected areas (PPA) of the the riverbanks. The amount of protected area depends on the river width and the size of each property which have a river running through or by it, as stated in the Brazilian forest code law. The rules are: 30 meters for rivers up to 10 meters wide, 50m for rivers 10 to 50m wide, 100m for rivers 50 to 200m wide, 200m for rivers 200 to 600m wide, and 500m, to rivers wider than 600m. The steps to determine the PPA buffer along the river are (1) construction of the triangular grid (TIN) that constitutes the basis for the calculation of the central axis of the river; (2) definition of the points representing the central axis of the river, called skeletonization; (3) definition of the river width; (4) calculation of the buffer for each river segment. PPA is defined by overlaying the river protected area polygon with the property polygon. A PPA area of a property can be reduced according to its size and according to public improvements like roads, permanent protected areas, for example. At the end the area to be preserved in a property is delimited.


title: Characteristic analysis of an ironless linear synchronous motor with novel halbach magnet array

abstract: A novel ironless synchronous permanent magnet linear motor with Halbach array is proposed. The operation principle and structure of this linear motor are introduced. Based on magnetic vector potential equation and boundary conditions, flux density distribution induced by the permanent magnet array is analysed analytically. And then the expression of the air-gap flux density distribution was derived. Characteristics such as thrust and back-EMF are obtained analytically and compared with the finite element simulation results. A prototype machine is manufactured and some experimental study is carried out, which validate the analytical and simulated results.


title: English phonology and morphology

abstract: A self-contained portable cryogenic apparatus that operates at the temperature (of the order of -78 DEG C. at atmospheric pressure) reached by reducing the pressure of carbon dioxide (CO2) or equivalent in liquid/solid phase, comprising a reservoir of pressurized liquefied CO2, the drawing off head being connected to a liquid/solid CO2 pressure reduction and ejection system, and comprising a control device, a pressure reduction device and a device for checking the temperature in the area to which it is applied, remarkable in that the top of the CO2 reservoir is arranged on the apparatus such that during the entire usage period, only the liquid part of the CO2 inside the reservoir comes into contact with the head so that it is drawn off and forced towards the application area through a pressure reduction and ejection system. The apparatus is particularly suitable for use in sports medicine in the form of a spray gun.


title: A Scheduling Strategy on Load Balancing of Virtual Machine Resources in Cloud Computing Environment

abstract: The current virtual machine(VM) resources scheduling in cloud computing environment mainly considers the current state of the system but seldom considers system variation and historical data, which always leads to load imbalance of the system. In view of the load balancing problem in VM resources scheduling, this paper presents a scheduling strategy on load balancing of VM resources based on genetic algorithm. According to historical data and current state of the system and through genetic algorithm, this strategy computes ahead the influence it will have on the system after the deployment of the needed VM resources and then chooses the least-affective solution, through which it achieves the best load balancing and reduces or avoids dynamic migration. This strategy solves the problem of load imbalance and high migration cost by traditional algorithms after scheduling. Experimental results prove that this method is able to realize load balancing and reasonable resources utilization both when system load is stable and variant.


title: A Survey of App Store Analysis for Software Engineering

abstract: App Store Analysis studies information about applications obtained from app stores. App stores provide a wealth of information derived from users that would not exist had the applications been distributed via previous software deployment methods. App Store Analysis combines this non-technical information with technical information to learn trends and behaviours within these forms of software repositories. Findings from App Store Analysis have a direct and actionable impact on the software teams that develop software for app stores, and have led to techniques for requirements engineering, release planning, software design, security and testing. This survey describes and compares the areas of research that have been explored thus far, drawing out common aspects, trends and directions future research should take to address open problems and challenges.


title: Beyond accuracy: what data quality means to data consumers

abstract: Poor data quality (DQ) can have substantial social and economic impacts. Although firms are improving data quality with practical approaches and tools, their improvement efforts tend to focus narrowly on accuracy. We believe that data consumers have a much broader data quality conceptualization than IS professionals realize. The purpose of this paper is to develop a framework that captures the aspects of data quality that are important to data consumers.A two-stage survey and a two-phase sorting study were conducted to develop a hierarchical framework for organizing data quality dimensions. This framework captures dimensions of data quality that are important to data consumers. Intrinsic DQ denotes that data have quality in their own right. Contextual DQ highlights the requirement that data quality must be considered within the context of the task at hand. Representational DQ and accessibility DQ emphasize the importance of the role of systems. These findings are consistent with our understanding that high-quality data should be intrinsically good, contextually appropriate for the task, clearly represented, and accessible to the data consumer.Our framework has been used effectively in industry and government. Using this framework, IS managers were able to better understand and meet their data consumers' data quality needs. The salient feature of this research study is that quality attributes of data are collected from data consumers instead of being defined theoretically or based on researchers' experience. Although exploratory, this research provides a basis for future studies that measure data quality along the dimensions of this framework.


The Wechsler intelligence scales


title: RFID-Cloud smart cart system

abstract: The main purpose of this work is in reducing the queuing delays in major supermarkets or other shopping centers by means of an Electronic Smart Cart System which will introduce an intellectual approach to billing process through RFID technology. Smart Cart System is a cooperative performance of three separate systems: a website developed for the shopping market, electronic smart cart device and anti-theft RFID gates. This project focuses on developing the electronic smart cart device itself. It involves an embedded electronic hardware that consists of an OLED display, Arduino Mega 2560 board, a specifically designed PCB, a Wi-Fi module, 13.56 MHz HF RFID reader, a power supply and a shopping cart.


title: Melanoma detection by analysis of clinical images using convolutional neural network

abstract: Melanoma, most threatening type of skin cancer, is on the rise. In this paper an implementation of a deep-learning system on a computer server, equipped with graphic processing unit (GPU), is proposed for detection of melanoma lesions. Clinical (non-dermoscopic) images are used in the proposed system, which could assist a dermatologist in early diagnosis of this type of skin cancer. In the proposed system, input clinical images, which could contain illumination and noise effects, are preprocessed in order to reduce such artifacts. Afterward, the enhanced images are fed to a pre-trained convolutional neural network (CNN) which is a member of deep learning models. The CNN classifier, which is trained by large number of training samples, distinguishes between melanoma and benign cases. Experimental results show that the proposed method is superior in terms of diagnostic accuracy in comparison with the state-of-the-art methods.


title: A functional model for affordance-based agents

abstract: Today's mobile artificial agents, such as mobile robots, are based on an object-oriented paradigm. They partition their environment into various objects and act in relation to individual properties of these objects. Such perception and acting is insufficient for goal-directed behavior in dynamic environments, which requires action-relevant information in the form of affordances. Affordances describe action possibilities with respect to a specific agent. In this paper, we propose a functional model for affordance-based agents. This model integrates an adjusted version of the HIPE theory of function and an extended theory of affordances. We demonstrate the applicability of the functional model by relating it to two different cases of mobile robot interaction and outline an affordanceoriented robot architecture.


title: Multilevel resilience analysis of transportation and communication networks

abstract: For many years the research community has attempted to model the Internet in order to better understand its behaviour and improve its performance. Since much of the structural complexity of the Internet is due to its multilevel operation, the Internet’s multilevel nature is an important and non-trivial feature that researchers must consider when developing appropriate models. In this paper, we compare the normalised Laplacian spectra of physical- and logical-level topologies of four commercial ISPs and two research networks against the US freeway topology, and show analytically that physical level communication networks are structurally similar to the US freeway topology. We also generate synthetic Gabriel graphs of physical topologies and show that while these synthetic topologies capture the grid-like structure of actual topologies, they are more expensive than the actual physical level topologies based on a network cost model. Moreover, we introduce a distinction between geographic graphs that include degree-2 nodes needed to capture the geographic paths along which physical links follow, and structural graphs that eliminate these degree-2 nodes and capture only the interconnection properties of the physical graph and its multilevel relationship to logical graph overlays. Furthermore, we develop a multilevel graph evaluation framework and analyse the resilience of single and multilevel graphs using the flow robustness metric. We then confirm that dynamic routing performed over the lower levels helps to improve the performance of a higher level service, and that adaptive challenges more severely impact the performance of the higher levels than non-adaptive challenges.


title: Bridging Space Over Time: Global Virtual Team Dynamics and Effectiveness

abstract: Global virtual teams are internationally distributed groups of people with an organizational mandate to make or implement decisions with international components and implications. They are typically assigned tasks that are strategically important and highly complex. They rarely meet in person, conducting almost all of their interaction and decision making using communications technology. Although they play an increasingly important role in multinational organizations, little systematic is known about their dynamics or effectiveness. This study built a grounded theory of global virtual team processes and performance over time. We built a template based on Adaptive Structuration Theory (DeSanctis and Poole 1994) to guide our research, and we conducted a case study, observing three global virtual teams over a period of 21 months. Data were gathered using multiple methods, and qualitative methods were used to analyze them and generate a theory of global virtual team dynamics and effectiveness. First, we propose that effective global virtual team interaction comprises a series of communication incidents, each configured by aspects of the team's structural and process elements. Effective outcomes were associated with a fit among an interaction incident's form, decision process, and complexity. Second, effective global virtual teams sequence these incidents to generate a deep rhythm of regular face-to-face incidents interspersed with less intensive, shorter incidents using various media. These two insights are discussed with respect to other literature and are elaborated upon in several propositions. Implications for research and practice are also outlined.


title: Advanced Deep-Learning Techniques for Salient and Category-Specific Object Detection: A Survey

abstract: Object detection, including objectness detection (OD), salient object detection (SOD), and category-specific object detection (COD), is one of the most fundamental yet challenging problems in the computer vision community. Over the last several decades, great efforts have been made by researchers to tackle this problem, due to its broad range of applications for other computer vision tasks such as activity or event recognition, content-based image retrieval and scene understanding, etc. While numerous methods have been presented in recent years, a comprehensive review for the proposed high-quality object detection techniques, especially for those based on advanced deep-learning techniques, is still lacking. To this end, this article delves into the recent progress in this research field, including 1) definitions, motivations, and tasks of each subdirection; 2) modern techniques and essential research trends; 3) benchmark data sets and evaluation metrics; and 4) comparisons and analysis of the experimental results. More importantly, we will reveal the underlying relationship among OD, SOD, and COD and discuss in detail some open questions as well as point out several unsolved challenges and promising future works.


title: Bioinspired Soft Actuation System Using Shape Memory Alloys

abstract: Abstract: Soft robotics requires technologies that are capable of generating forces even though the bodies are composed of very light, flexible and soft elements. A soft actuation mechanism was developed in this work, taking inspiration from the arm of the Octopus vulgaris , specifically from the muscular hydrostat which represents its constitutive muscular structure. On the basis of the authors’ previous works on shape memory alloy (SMA) springs used as soft actuators, a specific arrangement of such SMA springs is presented, which is combined with a flexible braided sleeve featuring a conical shape and a motor-driven cable. This robot arm is able to perform tasks in water such as grasping, multi-bending gestures, shortening and elongation along its longitudinal axis. The whole structure of the arm is described in detail and experimental results on workspace, bending and grasping capabilities and generated forces are presented. Moreover, this paper demonstrates that it is possible to realize a self-contained octopus-like robotic arm with no rigid parts, highly adaptable and suitable to be mounted on underwater vehicles. Its softness allows interaction with all types of objects with very low risks of damage and limited safety issues, while at the same time producing relatively high forces when necessary.


title: The processing-speed theory of adult age differences in cognition.

abstract: A theory is proposed to account for some of the age-related differences reported in measures of Type A or fluid cognition. The central hypothesis in the theory is that increased age in adulthood is associated with a decrease in the speed with which many processing operations can be executed and that this reduction in speed leads to impairments in cognitive functioning because of what are termed the limited time mechanism and the simultaneity mechanism. That is, cognitive performance is degraded when processing is slow because relevant operations cannot be successfully executed (limited time) and because the products of early processing may no longer be available when later processing is complete (simultaneity). Several types of evidence, such as the discovery of considerable shared age-related variance across various measures of speed and large attenuation of the age-related influences on cognitive measures after statistical control of measures of speed, are consistent with this theory.


title: A Wideband Dual-Mode SIW Cavity-Backed Triangular-Complimentary-Split-Ring-Slot (TCSRS) Antenna

abstract: A cavity-backed triangular-complimentary-split-ring-slot (TCSRS) antenna based on substrate integrated waveguide (SIW) is proposed in this communication. Proposed antenna element is designed and implemented at 28 and 45 GHz for the fifth generation (5G) of wireless communications. The principle of the proposed antenna element is investigated first then the arrays with two and four elements are designed for high-gain operation. Antennas prototype along with their arrays are fabricated using standard printed circuit board (PCB) process at both frequencies—28 and 45 GHz. Measured result shows that the 16.67% impedance bandwidth at 28 GHz and 22.2% impedance bandwidth at 45 GHz is achieved, while maintaining the same substrate height at both frequencies. The measured peak gains of the $2\times 2$ antenna array at 30 or 50 GHz are 13.5 or 14.4 dBi, respectively.


title: The prevalence of intellectual disabilities among 12,000 prisoners - a systematic review.

abstract: Abstract There are 9 million prisoners worldwide, but it is uncertain what proportion have intellectual disabilities. Such prisoners have been identified as a vulnerable group at risk of victimization and mental illness. Psychiatric surveys based on interviews of unselected prison populations were sought, involving diagnoses of intellectual disabilities. The search was performed by computer-assisted searches, scanning of relevant reference lists, hand-searching of journals, and correspondence with authors of relevant reports. Prevalence rates of intellectual disabilities by gender and other potentially relevant study characteristics were abstracted from publications, supplemented by information from authors of reports. Ten relevant surveys from four different countries were identified that included a total of 11,969 prisoners (mean age: 29 years; 92% male; 23% violent offenders). No formal calculation of a summary estimate of prevalence was undertaken due to substantial heterogeneity. The results suggest that typically 0.5–1.5% of prisoners were diagnosed with intellectual disabilities (range 0% to 2.8% across studies). We conclude that the number of prisoners with intellectual disabilities is considerable and discuss implications for policy and practice.


title: Expert Systems and Probabilistic Network Models

abstract: Artificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods for incorporating uncertainty into models. This book is devoted to providing a thorough and up-to-date survey of this field for researchers and students.


title: Scalable, high performance ethernet forwarding with CuckooSwitch

abstract: Several emerging network trends and new architectural ideas are placing increasing demand on forwarding table sizes. From massive-scale datacenter networks running millions of virtual machines to flow-based software-defined networking, many intriguing design options require FIBs that can scale well beyond the thousands or tens of thousands possible using today's commodity switching chips. This paper presents CuckooSwitch, a software-based Ethernet switch design built around a memory-efficient, high-performance, and highly-concurrent hash table for compact and fast FIB lookup. We show that CuckooSwitch can process 92.22 million minimum-sized packets per second on a commodity server equipped with eight 10 Gbps Ethernet interfaces while maintaining a forwarding table of one billion forwarding entries. This rate is the maximum packets per second achievable across the underlying hardware's PCI buses.


title: Virtual-View-Assisted Video Super-Resolution and Enhancement

abstract: A 3-D multiview video gives users an experience that is different from that provided by a traditional video; however, it puts a huge burden on limited bandwidth resources. Mixed-resolution video in a multiview system can alleviate this problem by using different video resolutions for different views. However, to reduce visual uncomfortableness and to make this video format more suitable for free-viewpoint television, the low-resolution (LR) views need to be super-resolved to the target full resolution. In this paper, we propose a virtual-view-assisted super-resolution algorithm, where the inter-view similarity is used to determine whether the missing pixels in the super-resolved frame need to be filled by virtual-view pixels or by spatial interpolated pixels. The decision mechanism is steered by the texture characteristics of the neighbors of each missing pixel. Furthermore, the inter-view similarity is used, on the one hand, to enhance the quality of the virtual-view-copied pixels by compensating the luminance difference between different views and, on the other hand, to enhance the original LR pixels in the super-resolved frame by reducing their compression distortion. Thus, the proposed method can recover the details in regions with edges while maintaining good quality at smooth areas by properly exploiting the high-quality virtual-view pixels and the directional correlation of pixels. The experimental results demonstrate the effectiveness of the proposed approach with a peak signal-to-noise ratio gain of up to 3.85 dB.


title: On the performance of percolation graph matching

abstract: Graph matching is a generalization of the classic graph isomorphism problem. By using only their structures a graph-matching algorithm finds a map between the vertex sets of two similar graphs. This has applications in the de-anonymization of social and information networks and, more generally, in the merging of structural data from different domains. One class of graph-matching algorithms starts with a known seed set of matched node pairs. Despite the success of these algorithms in practical applications, their performance has been observed to be very sensitive to the size of the seed set. The lack of a rigorous understanding of parameters and performance makes it difficult to design systems and predict their behavior. In this paper, we propose and analyze a very simple percolation - based graph matching algorithm that incrementally maps every pair of nodes (i,j) with at least r neighboring mapped pairs. The simplicity of this algorithm makes possible a rigorous analysis that relies on recent advances in bootstrap percolation theory for the G(n,p) random graph. We prove conditions on the model parameters in which percolation graph matching succeeds, and we establish a phase transition in the size of the seed set. We also confirm through experiments that the performance of percolation graph matching is surprisingly good, both for synthetic graphs and real social-network data.


title: GridSolve : The Evolution of A Network Enabled Solver

abstract: GridSolve is a stubless RPC-based client-agent-server system for remotely accessing hardware and software resources. GridSolve emphasizes ease-of-use for the user and includes resource monitoring, scheduling and service-level fault-tolerance. In addition to providing Fortran and C clients, GridSolve enables scientific computing environments (such as Matlab) to be used as clients, so domain scientists can use Grid resources from within their preferred environments. GridSolve is a more highly evolved version of the earlier NetSolve project, and it is based on the emerging GridRPC standard. This paper will discuss the changes and improvements involved in the evolution from NetSolve to GridSolve.


title: Mitigating Address Spoofing Attacks in Hybrid SDN

abstract: Address spoofing attacks like ARP spoofing and DDoS attacks are mostly launched in a networking environment to degrade the performance. These attacks sometimes break down the network services before the administrator comes to know about the attack condition. Software Defined Networking (SDN) has emerged as a novel network architecture in which date plane is isolated from the control plane. Control plane is implemented at a central device called controller. But, SDN paradigm is not commonly used due to some constraints like budget, limited skills to control SDN, the flexibility of traditional protocols. To get SDN benefits in a traditional network, a limited number of SDN devices can be deployed among legacy devices. This technique is called hybrid SDN. In this paper, we propose a new approach to automatically detect the attack condition and mitigate that attack in hybrid SDN. We represent the network topology in the form of a graph. A graph based traversal mechanism is adopted to indicate the location of the attacker. Simulation results show that our approach enhances the network efficiency and improves the network security.


title: Wideband Tapered-Slot Antenna with Corrugated Edges for GPR Applications

abstract: A novel wideband tapered-slot antenna for GPR applications is proposed. A conventional approach to reduce unwanted interactions between the antenna and the ground surface requires extensive microwave absorbers treatment. For the same purpose we propose to use corrugations along the antenna edges. The corrugations improve directivity and wideband matching of the antenna with free space retaining also good radiation efficiency. Further improvement of the antenna performance has been achieved by patching the corrugated areas of the antenna with the resistance card strips. The elimination of the foam-type absorbers makes the antenna more robust and easier in fabrication.


title: Extracting Semantic Orientations Of Words Using Spin Model

abstract: We propose a method for extracting semantic orientations of words: desirable or undesirable. Regarding semantic orientations as spins of electrons, we use the mean field approximation to compute the approximate probability function of the system instead of the intractable actual probability function. We also propose a criterion for parameter selection on the basis of magnetization. Given only a small number of seed words, the proposed method extracts semantic orientations with high accuracy in the experiments on English lexicon. The result is comparable to the best value ever reported.


title: Energy from gasification of solid wastes.

abstract: Gasification technology is by no means new: in the 1850s, most of the city of London was illuminated by "town gas" produced from the gasification of coal. Nowadays, gasification is the main technology for biomass conversion to energy and an attractive alternative for the thermal treatment of solid waste. The number of different uses of gas shows the flexibility of gasification and therefore allows it to be integrated with several industrial processes, as well as power generation systems. The use of a waste-biomass energy production system in a rural community is very interesting too. This paper describes the current state of gasification technology, energy recovery systems, pre-treatments and prospective in syngas use with particular attention to the different process cycles and environmental impacts of solid wastes gasification.


title: Adaptive robust control of skid steer mobile robot with independent driving torque allocation

abstract: Skid-steered mobile robot has been widely used in different fields. In most of existing controllers for skid-steered mobile robots, the wheel velocities are controlled independently to track the desired velocities from the remote manipulation or high level computer. However, this kind of control method may lead to chattering phenomenon of skid steer mobile robots in practice. In this paper, the cause of chattering phenomenon is analyzed. And to solve this problem, a two level adaptive robust control law integrated with torque allocation technique is proposed. In the high level, an adaptive robust control law is developed such that the minimum velocity on the same side track the desired velocity. In the low level, a torque allocation technique is developed for regulating driving torque of each motor. Moreover, a novel control law with consideration of the error of each wheel on the same side is proposed to avoid the spin of wheels when the wheel is lifted from ground. Comparative experiments are carried out to verify the excellent performance of the proposed scheme. The results show that the proposed controller will achieve a good performance and adapt well with the ground condition.


title: Analyzing basketball games by a support vector machines with decision tree model

abstract: Support vector machines (SVMs) are an emerging and powerful technique in coping with classification problems. However, a lack of rule generation is a weakness of the SVM model, especially in analyzing sporting results. This investigation developed a hybrid model integrating the SVM technique and a decision tree approach (HSVMDT) to predict the results of basketball games, and to provide rules to aid coaches in developing strategies. The HSVMDT model employed the unique strength of SVM and decision tree in generating rules and predicting the outcomes of games. With predicted outcomes of games, and rules yielded from the HSVMDT model, coaches can easily and quickly learn essential factors increasing the chances to win games. Empirical results showed that the proposed HSVMDT model can obtain relatively satisfactory prediction accuracy and therefore is a promising alternative for analyzing the results of basketball competitions.


title: Evaluating Induced CCG Parsers on Grounded Semantic Parsing

abstract: We compare the effectiveness of four different syntactic CCG parsers for a semantic slot-filling task to explore how much syntactic supervision is required for downstream semantic analysis. This extrinsic, task-based evaluation provides a unique window to explore the strengths and weaknesses of semantics captured by unsupervised grammar induction systems. We release a new Freebase semantic parsing dataset called SPADES (Semantic PArsing of DEclarative Sentences) containing 93K cloze-style questions paired with answers. We evaluate all our models on this dataset. Our code and data are available at https://github.com/sivareddyg/graph-parser.


title: Fingertip force control with embedded fiber Bragg grating sensors

abstract: We describe the dynamic testing and control results obtained with an exoskeletal robot finger with embedded fiber optical sensors. The finger is inspired by the designs of arthropod limbs, with integral strain sensilla concentrated near the joints. The use of fiber Bragg gratings (FBGs) allows for embedded sensors with high strain sensitivity and immunity to electromagnetic interference. The embedded sensors are useful for contact detection and for control of forces during fine manipulation. The application to force control requires precise and high-bandwidth measurement of contact forces. We present a nonlinear force control approach that combines signals from an optical interrogator and conventional joint angle sensors to achieve accurate tracking of desired contact forces.


title: The Object Detection Based on Deep Learning

abstract: The object detection based on deep learning is an important application in deep learning technology, which is characterized by its strong capability of feature learning and feature representation compared with the traditional object detection methods. The paper first makes an introduction of the classical methods in object detection, and expounds the relation and difference between the classical methods and the deep learning methods in object detection. Then it introduces the emergence of the object detection methods based on deep learning and elaborates the most typical methods nowadays in the object detection via deep learning. In the statement of the methods, the paper focuses on the framework design and the working principle of the models and analyzes the model performance in the real-time and the accuracy of detection. Eventually, it discusses the challenges in the object detection based on deep learning and offers some solutions for reference.


title: 3D Scene Understanding at Urban Intersection Using Stereo Vision and Digital Map

abstract: The driving behavior at urban intersections is very complex. It is thus crucial for autonomous vehicles to comprehensively understand challenging urban traffic scenes in order to navigate intersections and prevent accidents. In this paper, we introduce a stereo vision and 3D digital map based approach to spatially and temporally analyze the traffic situation at urban intersections. Stereo vision is used to detect, classify and track obstacles, while a 3D digital map is used to improve ego-localization and provide context in terms of road-layout information. A probabilistic approach that temporally integrates these geometric, semantic, dynamic and contextual cues is presented. We qualitatively and quantitatively evaluate our proposed technique on real traffic data collected at an urban canyon in Tokyo to demonstrate the efficacy of the system in providing comprehensive awareness of the traffic surroundings.


title: Orchestrating BigData Analysis Workflows

abstract: Data analytics has become not only an essential part of day-to-day decision making, but also reinforces long-term strategic decisions. Whether it is real-time fraud detection, resource management, tracking and prevention of disease outbreak, natural disaster management or intelligent traffic management, the extraction and exploitation of insightful information from unparalleled quantities of data (BigData) is now a fundamental part of all decision making processes. Success in making smart decisions by analyzing BigData is possible due to the availability of improved analytical capabilities, increased access to different data sources, and cheaper and improved computing power in the form of cloud computing. However, BigData analysis is far more complicated than the perception created by the recent publicity. For example, one of the myths is that BigData analysis is driven purely by the innovation of new data mining and machine learning algorithms. While innovation of new data mining and machine learning algorithms is critical, this is only one aspect of producing BigData analysis solutions. Just like many other software solutions, BigData analysis solutions are not monolithic pieces of software that are developed specifically for every application. Instead, they often combine and reuse existing trusted software components that perform necessary data analysis steps. Furthermore, in order to deal with the large variety, volume and velocity of BigData, they need to take advantage of the elasticity of cloud and edge datacenter computation and storage resources as needed to meet the requirements of their owners.


title: A universal toolkit for cryptographically secure privacy-preserving data mining

abstract: The issue of potential data misuse rises whenever it is collected from several sources. In a common setting, a large database is either horizontally or vertically partitioned between multiple entities who want to find global trends from the data. Such tasks can be solved with secure multi-party computation (MPC) techniques. However, practitioners tend to consider such solutions inefficient. Furthermore, there are no established tools for applying secure multi-party computation in real-world applications. In this paper, we describe Sharemind--a toolkit, which allows data mining specialist with no cryptographic expertise to develop data mining algorithms with good security guarantees. We list the building blocks needed to deploy a privacy-preserving data mining application and explain the design decisions that make Sharemind applications efficient in practice. To validate the practical feasibility of our approach, we implemented and benchmarked four algorithms for frequent itemset mining.


title: Character-based Neural Embeddings for Tweet Clustering

abstract: In this paper we show how the performance of tweet clustering can be improved by leveraging character-based neural networks. The proposed approach overcomes the limitations related to the vocabulary explosion in the word-based models and allows for the seamless processing of the multilingual content. Our evaluation results and code are available on-line at this https URL


title: Use of negative capacitance to provide voltage amplification for low power nanoscale devices.

abstract: It is well-known that conventional field effect transistors (FETs) require a change in the channel potential of at least 60 mV at 300 K to effect a change in the current by a factor of 10, and this minimum subthreshold slope S puts a fundamental lower limit on the operating voltage and hence the power dissipation in standard FET-based switches. Here, we suggest that by replacing the standard insulator with a ferroelectric insulator of the right thickness it should be possible to implement a step-up voltage transformer that will amplify the gate voltage thus leading to values of S lower than 60 mV/decade and enabling low voltage/low power operation. The voltage transformer action can be understood intuitively as the result of an effective negative capacitance provided by the ferroelectric capacitor that arises from an internal positive feedback that in principle could be obtained from other microscopic mechanisms as well. Unlike other proposals to reduce S, this involves no change in the basic physics of t...


title: C60 field effect transistor with electrodes modified by La@C82

abstract: Abstract C 60 field effect transistors (FETs) with interfacial modifications of electrodes using endohedral fullerene, C 60 /La@C 82 -FETs, are reported. An FET operation is observed without any annealing processes even once the fabricated devices are exposed to air, which has not ever seen in the conventional C 60 FETs. Another improvement in the field effect mobilities is also observed with little change in the threshold voltage. The interfacial surface modifications on the electrodes using endohedral fullerene analogues with large number of carriers are effective in reducing the trapping levels at the interface between C 60 thin film surface and the gold electrodes.


Multiple Paraphilic Diagnoses among Sex Offenders Gene


Graph Coloring Problems and Their Applications in Scheduling


title: A real-time portable sign language translation system

abstract: In this paper, a wireless hand gesture recognition glove is proposed for real-time translation of Taiwanese sign language. To discriminate between different hand gestures, we have flex and inertial sensors embedded into the glove so that the three most important parameters, i.e., the posture of fingers, orientation of the palm, and motion of the hand, defined in Taiwanese Sign Language can be recognized without ambiguity. The finger flexion postures acquired by flex sensors, the palm orientation acquired by G-sensor, and the motion trajectory acquired by gyroscope are used as the input signals of the proposed system. The input signals will be acquired and examined periodically to see if it is a legal sign language gesture or not. Once the sampled signal can last longer than a predefined clock cycles, it is regarded as a valid gesture and will be sent to cell phone via Bluetooth for gesture discrimination and speech translation. With the proposed architecture and algorithm, the accuracy for gesture recognition is quite satisfactory. As we can see in experiments that an accuracy rate up to 94% on sensitivity for gesture recognition can be achieved which justifies the superiority of the proposed architecture.


title: Case Reports of Combined treatment of Onbaek-won on two Soeumin stroke patients with Cb-inf who have Constipation

abstract: 1. Objectives: The purpose of this case is to report the effects of Onbaek-won which is based on Sasang Constitutional Medicine for constipation in Soeumin. 2. Methods: We treated two Soeumin patients with Constipation. We prescribed Onbaek-won for their physical symptoms. The improvement of their diseases were checked from their stool and other physical symptoms. 3. Results: After the Sasang constitutional medication of Onbaek-won were given, constipation and their physical symptoms were improved. 4. Conclusions: This case study show an efficient result of using Onbaek-won in constipation of Soeumin. Onbaek-won was used instead of Semen Tiglii(巴豆).


title: Deep Emotion: A Computational Model of Emotion Using Deep Neural Networks

abstract: Emotions are very important for human intelligence. For example, emotions are closely related to the appraisal of the internal bodily state and external stimuli. This helps us to respond quickly to the environment. Another important perspective in human intelligence is the role of emotions in decision-making. Moreover, the social aspect of emotions is also very important. Therefore, if the mechanism of emotions were elucidated, we could advance toward the essential understanding of our natural intelligence. In this study, a model of emotions is proposed to elucidate the mechanism of emotions through the computational model. Furthermore, from the viewpoint of partner robots, the model of emotions may help us to build robots that can have empathy for humans. To understand and sympathize with people's feelings, the robots need to have their own emotions. This may allow robots to be accepted in human society. The proposed model is implemented using deep neural networks consisting of three modules, which interact with each other. Simulation results reveal that the proposed model exhibits reasonable behavior as the basic mechanism of emotion.


title: A Wideband U-Shaped Slot Antenna and Its Application in MIMO Terminals

abstract: A wideband microstrip multiple-input-multiple-output (MIMO) antenna with U-shaped slot is presented in this letter. To widen the impedance bandwidth, uniform and stepped U-shaped slot antennas are sequentially investigated. Two types of resonant modes are excited, including slot mode and monopole mode. Then, additional multiple slots embedded inside the U-shaped slot are employed to further widen the bandwidth. The proposed slot antenna features wide bandwidth (109%) and compact slot size ( 0.16λ ::: g ::: ×0.27λ ::: g ::: , where λ ::: g ::: is the guided wavelength at the lowest operating frequency) simultaneously. The proposed slot antenna element is then applied in the MIMO antenna system. Both the two antennas are suitable for handheld devices, covering GPS/GSM1800/LTE/UMTS/WLAN/WiMAX/UWB (lower) band.


title: e-Tourism: A Tourist Recommendation and Planning Application

abstract: e-Tourism is a tourist recommendation and planning application to assist users on the organization of a leisure and tourist agenda. First, a recommender system offers the user a list of the city places that are likely of interest to the user. This list takes into account the user demographic classification, the user likes in former trips and the preferences for the current visit. Second, a planning module schedules the list of recommended places according to their temporal characteristics as well as the user restrictions; that is the planning system determines how and when to realize the recommended activities. Having the list of recommended activities organized as an agenda (i.e. an executable plan), is a relevant characteristic that most recommender systems lack.


title: Kinematic motion studies of an OmniDirectional mobile robot

abstract: Actuator failure may severely affect the performance of mobile robots and vehicles. This study serves to evaluate how a mobile system responds under various actuator failure modes to determine appropriate methods to satisfy performance objectives. We evaluate a kinematically symmetric holonomic mobile robot while fully actuable (with no motor/wheel failures), as well as under actuator failure conditions. Closed-loop state feedback is applied to the system to observe performance and self-correction under both nominal and failure mode conditions, and resulting performance is evaluated. Observations of these conditions motivate the need to address failure modes within the controller architecture.


title: Highly Automated Agile Testing Process: An Industrial Case Study

abstract: This paper presents a description of an agile testing process in a medium size software project that is developed using Scrum. The research methods used is the case study were as follows: surveys, quantifiable project data sources and qualitative project members opinions were used for data collection. Challenges related to the testing process regarding a complex project environment and unscheduled releases were identified. Based on the obtained results, we concluded that the described approach addresses well the aforementioned issues. Therefore, recommendations were made with regard to the employed principles of agility, specifically: continuous integration, responding to change, test automation and test driven development. Furthermore, an ecient testing environment that combines a number of test frameworks (e.g. JUnit, Selenium, Jersey Test) with custom-developed simulators is presented.


title: Design and estimation of state-charging applied for lithium-ion battery based on Matlab-Simulink

abstract: For green technology applications, the lithium-ion battery is widely adopted as energy storage system due to high power and high energy density. However, there is a drawback on the storage system on charging interval time, particularly on electric vehicle applications. To accelerate, the multi-state current technique becomes a solution. In this paper, the state-charging of the lithium ion battery modeled by Matlab/Simulink is discussed. The state-of-charge (SOC) is measured and applied to evaluate the battery's charge/discharge characteristic. The multiple charging states applied for filling the battery capacity are evaluated in order to achieve high efficiency. In addition, the configurable three-state current design manipulated by a 8-bit microcontroller is introduced with a constant voltage at 20V and variable current from 5A to 60A. The investigation results are illustrated that, operating on Lithium-ion Ferro battery 12V 30Ah, the interval time of fill-up is reduced approximately 30% with working temperature 35° C.


title: Cooperative grasping and transport using multiple quadrotors

abstract: In this paper, we consider the problem of controlling multiple quadrotor robots that cooperatively grasp and transport a payload in three dimensions.We model the quadrotors both individually and as a group rigidly attached to a payload. We propose individual robot control laws defined with respect to the payload that stabilize the payload along three-dimensional trajectories. We detail the design of a gripping mechanism attached to each quadrotor that permits autonomous grasping of the payload. An experimental study with teams of quadrotors cooperatively grasping, stabilizing, and transporting payloads along desired three-dimensional trajectories is presented with performance analysis over many trials for different payload configurations.


title: Does my password go up to eleven?: the impact of password meters on password selection

abstract: Password meters tell users whether their passwords are "weak" or "strong." We performed a laboratory experiment to examine whether these meters influenced users' password selections when they were forced to change their real passwords, and when they were not told that their passwords were the subject of a study. We observed that the presence of meters yielded significantly stronger passwords. We performed a followup field experiment to test a different scenario: creating a password for an unimportant account. In this scenario, we found that the meters made no observable difference: participants simply reused weak passwords that they used to protect similar low-risk accounts. We conclude that meters result in stronger passwords when users are forced to change existing passwords on "important" accounts and that individual meter design decisions likely have a marginal impact.


title: Fast tile-binning method by detecting 1D-overlapped primitives

abstract: Mobile 3D graphics use tile-based rendering algorithm in order to lower power consumption. For rendering tile by tile in the tile-based rendering, tile-binning process is inevitable and has to store the results of geometry processing into scene buffer, which causes memory access severely. Several methods were proposed to reduce memory bandwidth for tile-binning process. However, these memory-bandwidth reduction methods require more computations. Hsieh et al. attempted to eliminate edges in order to decrease the number of overlap test. Their method could only eliminate 0.02% of edges because the edges parallel to the axes can be eliminated. In this study, we propose a simple method to reduce the number of the overlap test by detecting 1D-tile overlapped primitives, which are overlapped with only one-dimensional tiles while keeping low memory bandwidth.


title: Attention-based Few-Shot Person Re-identification Using Meta Learning

abstract: In this paper, we investigate the challenging task of person re-identification from a new perspective and propose an end-to-end attention-based architecture for few-shot re-identification through meta-learning. The motivation for this task lies in the fact that humans, can usually identify another person after just seeing that given person a few times (or even once) by attending to their memory. On the other hand, the unique nature of the person re-identification problem, i.e., only few examples exist per identity and new identities always appearing during testing, calls for a few shot learning architecture with the capacity of handling new identities. Hence, we frame the problem within a meta-learning setting, where a neural network based meta-learner is trained to optimize a learner i.e., an attention-based matching function. Another challenge of the person re-identification problem is the small inter-class difference between different identities and large intra-class difference of the same identity. In order to increase the discriminative power of the model, we propose a new attention-based feature encoding scheme that takes into account the critical intra-view and cross-view relationship of images. We refer to the proposed Attention-based Re-identification Metalearning model as ARM. Extensive evaluations demonstrate the advantages of the ARM as compared to the state-of-the-art on the challenging PRID2011, CUHK01, CUHK03 and Market1501 datasets.


title: IMU aided RGB-D SLAM

abstract: In recent years, a low-cost range sensing technology (such as Kinect) has attracted many researchers in vision community. Despite being promising for indoor navigation, continuous operation in a challenging environments is still a fundamental problem. This paper presents a real-time approach of combining range-color (RGB-D) cues with inertial information in a loosely-coupled framework for Simultaneous Localization and Mapping (SLAM). The method handles the degenerate cases arises in the RGB-D approaches i.e limited range of Kinect (approx. 4m), texture-less/planar environmental ambiguities. Experimental results are provided for indoor lab environment and evaluated against a centimeter-level accurate ground truth data. We showed that the proposed approach significantly reduces error in RGB-D pose estimation by bounding the errors implicitly by the inertial gravity vectors and accelerometer data.


title: QARAB: A: Question Answering System To Support The Arabic Language

abstract: We describe the design and implementation of a question answering (QA) system called QARAB. It is a system that takes natural language questions expressed in the Arabic language and attempts to provide short answers. The system's primary source of knowledge is a collection of Arabic newspaper text extracted from Al-Raya, a newspaper published in Qatar. During the last few years the information retrieval community has attacked this problem for English using standard IR techniques with only mediocre success. We are tackling this problem for Arabic using traditional Information Retrieval (IR) techniques coupled with a sophisticated Natural Language Processing (NLP) approach. To identify the answer, we adopt a keyword matching strategy along with matching simple structures extracted from both the question and the candidate documents selected by the IR system. To achieve this goal, we use an existing tagger to identify proper names and other crucial lexical items and build lexical entries for them on the fly. We also carry out an analysis of Arabic question forms and attempt a better understanding of what kinds of answers users find satisfactory. The paucity of studies of real users has limited results in earlier research.


title: Detecting activities of daily living in first-person camera views

abstract: We present a novel dataset and novel algorithms for the problem of detecting activities of daily living (ADL) in firstperson camera views. We have collected a dataset of 1 million frames of dozens of people performing unscripted, everyday activities. The dataset is annotated with activities, object tracks, hand positions, and interaction events. ADLs differ from typical actions in that they can involve long-scale temporal structure (making tea can take a few minutes) and complex object interactions (a fridge looks different when its door is open). We develop novel representations including (1) temporal pyramids, which generalize the well-known spatial pyramid to approximate temporal correspondence when scoring a model and (2) composite object models that exploit the fact that objects look different when being interacted with. We perform an extensive empirical evaluation and demonstrate that our novel representations produce a two-fold improvement over traditional approaches. Our analysis suggests that real-world ADL recognition is “all about the objects,” and in particular, “all about the objects being interacted with.”


Joint Entity Recognition and Disambiguation


title: Attenuation of Conducted EMI Emissions From an Inverter-Driven Motor

abstract: This paper provides theoretical and experimental discussions on conducted electromagnetic interference (EMI) emissions from an inverter-driven motor rated at 400 V and 15 kW. It focuses on a line EMI filter and its combination with a motor EMI filter, along with their effects on attenuation of conducted emission voltage. When no EMI filter is connected, the motor drive cannot meet the conducted emission limits prescribed by Category 3 in the IEC61800-3 regulations. The reason is that the common-mode voltage generated by a voltage-source pulse width modulation (PWM) inverter causes a common-mode leakage current flowing into the ground wire lead through parasitic capacitors inside the motor. When the line EMI filter is connected, the motor drive can meet Category 3. The motor EMI filter eliminates the common-mode voltage from the motor terminals, thus bringing a drastic reduction to the leakage current. The combination of the two EMI filters can comply with the limits prescribed by Category 2, which are much stricter than those by Category 3.


title: DFVR: Deformable finger vein recognition

abstract: Although some developments have been achieved in finger vein recognition recently, the image deformation problem has received relatively less attention and still intractable. In this paper, the reason and the harmfulness of this problem are analyzed firstly. And then, a deformable finger vein recognition framework is proposed to deal with this problem, consisting of the improved vein PCA-SIFT feature and bidirectional deformable spatial pyramid matching (BDSPM). Furthermore, we build a finger vein deformation database to imitate image deformation in real application. The experimental results, on the self-built deformation database and one public database, prove the effectiveness of the proposed framework for dealing with the image deformation problem.


title: Micro-MOPSO: A Multi-Objective Particle Swarm Optimizer That Uses a Very Small Population Size

abstract: In this chapter, we present a multi-objective evolutionary algorithm (MOEA) based on the heuristic called “particle swarm optimization” (PSO). This multi-objective particle swarm optimizer (MOPSO) is characterized for using a very small population size, which allows it to require a very low number of objective function evaluations (only 3000 per run) to produce reasonably good approximations of the Pareto front of problems of moderate dimensionality. The proposed approach first selects the leader and then selects the neighborhood for integrating the swarm. The leader selection scheme adopted is based on Pareto dominance and uses a neighbors density estimator. Additionally, the proposed approach performs a reinitialization process for preserving diversity and uses two external archives: one for storing the solutions that the algorithm finds during the search process and another for storing the final solutions obtained. Furthermore, a mutation operator is incorporated to improve the exploratory capabilities of the algorithm. The proposed approach is validated using standard test functions and performance measures reported in the specialized literature. Our results are compared with respect to those generated by the Nondominated Sorting Genetic Algorithm II (NSGA-II), which is a MOEA representative of the state-of-the-art in the area.


title: Climate variability and vulnerability to climate change: a review

abstract: The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here, we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades.


title: Fractal Dimension Of Landscape Silhouette Outlines As A Predictor Of Landscape Preference

abstract: Abstract The aim of this study was to explore the suggestion that fractal characteristics may play a role in aesthetic experiences by providing possible empirical evidence for connections between landscape preference and fractal properties. This approach was motivated by the knowledge that many natural forms are fractal and that, in preference research, naturalness has been found an important predictor. For reasons described in the paper, in this study we chose to focus on landscape silhouette outlines. The results indicate that there is a relationship between preference and the fractal dimension, which in turn gives rise to the hypothesis that the fractal dimension could provide part of the explanation to the well-documented connection between preference and naturalness.


Poverty During Early Childhood


title: When more is too much: Operationalizing technology overload and exploring its impact on knowledge worker productivity

abstract: Individuals within organizations are beginning to make an important realization: more information technology (IT) usage in the workplace can, at times, lead to productivity losses. We conceptualize this frequently observed, but largely ignored phenomenon as technology overload, when additional technology tools begin to crowd out one's productivity instead of enhancing it. We found support for three main factors contributing technology-based productivity losses through information overload, communication overload, and system feature overload. Interestingly, these factors are a function of the individuals who use the technology, not the technology itself. In this paper, we present the results from three studies that (1) develop and pre-test a scale measurement for technology overload and its distinct dimensions, (2) validate the instrument, and (3) explore the relationship between technology overload and knowledge worker productivity. Our findings demonstrate the relationship between information technology usage and knowledge worker productivity, and they suggest how tradeoffs can be managed to ameliorate technology overload.


title: FPGA Implementations of Neural Networks-a Survey of a Decade of Progress

abstract: The ferst successful FPGA implementation [1] of artificial neural networks (ANNs) was published a little over a decade ago. It is timely to review the progress that has been made in this research area. This brief survey provides a taxonomy for classifying FPGA implementations of ANNs. Different implementation techniques and design issues are discussed. Future research trends are also presented.


title: Low-Complexity MMSE Precoding for Coordinated Multipoint With Per-Antenna Power Constraint

abstract: We propose a low-complexity minimum mean square error (MMSE) transmit filter design for the coordinated beamforming (CB) in the coordinated multipoint (CoMP) under the practical per-antenna power constraint (PAPC). The proposed design is based on the nonlinear Gauss-Seidel type algorithm in which the transmit filters for given receive filters are computed by iteratively updating the beamformer of each transmit antenna using simple closed-form expressions. The proposed approach can significantly reduce the overall complexity of the alternating optimization while preserving the optimality in the MSE sense.


title: Corpus Specific Stop Words to Improve the Textual Analysis in Scientometrics

abstract: With the availability of vast collection of research articles on internet, textual analysis is an increasingly important technique in scientometric analysis. While the context in which it is used and the specific algorithms implemented may vary, typically any textual analysis exercise involves intensive pre-processing of input text which includes removing topically uninteresting terms (stop words). In this paper we argue that corpus specific stop words, which take into account the specificities of a collection of texts, improve textual analysis in scientometrics. We describe two relatively simple techniques to generate corpus-specific stop words; stop words lists following a Poisson distribution and keyword adjacency stop words lists. In a case study to extract keywords from scientific abstracts of research project funded by the European Research Council in the domain of Life sciences, we show that a combination of those techniques gives better recall values than standard stop words or any of the two techniques alone. The method we propose can be implemented to obtain stop words lists in an automatic way by using author provided keywords for a set of abstracts. The stop words lists generated can be updated easily by adding new texts to the training corpus. Conference Topic Methods and techniques


Haar-Feature Based Gesture Detection of Hand-Raising for Mobile Robot in HRI Environments