title: Spanning-tree based coverage of continuous areas by a mobile robot

abstract: The paper considers the problem of covering a continuous planar area by a square-shaped tool attached to a mobile robot. Using a tool-based approximation of the work-area, we present an algorithm that covers every point of the approximate area. The algorithm, called spanning tree covering (STC), subdivides the work-area into disjoint cells corresponding to the square-shaped tool, then follows a spanning tree of the graph induced by the cells, while covering every point precisely once. We present and analyze three versions of the STC algorithm. The first version is an off-line algorithm that computes an optimal covering path in linear time O(N), where N is the number of cells comprising the approximate area. The second version is an online or sensor based algorithm, that completes an optimal covering path in time O(N), but requires O(N) memory for its implementation. The third version of STC is "ant"-like, where the robot may leave pheromone-like markers during the coverage process. The ant-like STC algorithm runs in time O(N) and requires only O(1) memory. We present simulation results of the three STC algorithms, demonstrating their effectiveness in cases where the tool size is significantly smaller than the work-area characteristic dimension.


title: An FPGA-Accelerated Design for Deep Learning Pedestrian Detection in Self-Driving Vehicles

abstract: With the rise of self-driving vehicles comes the risk of accidents and the need for higher safety, and protection for pedestrian detection in the following scenarios: imminent crashes, thus the car should crash into an object and avoid the pedestrian, and in the case of road intersections, where it is important for the car to stop when pedestrians are crossing. Currently, a special topology of deep neural networks called Fused Deep Neural Network (F-DNN) is considered to be the state of the art in pedestrian detection, as it has the lowest miss rate, yet it is very slow. Therefore, acceleration is needed to speed up the performance. This project proposes two contributions to address this problem, by using a deep neural network used for object detection, called Single Shot Multi-Box Detector (SSD). The first contribution is training and tuning the hyperparameters of SSD to improve pedestrian detection. The second contribution is a new FPGA design for accelerating the model on the Altera Arria 10 platform. The final system will be used in self-driving vehicles in real-time. Preliminary results of the improved SSD shows 3% higher miss-rate than F-DNN on Caltech pedestrian detection benchmark, but 4x performance improvement. The acceleration design is expected to achieve an additional performance improvement significantly outweighing the minimal difference in accuracy.


title: BioMechatronic Design and Control of an Anthropomorphic Artificial Hand for Prosthetics and Robotic Applications

abstract: The paper proposes a biomechatronic approach to the design of an anthropomorphic artificial hand. The hand is conceived to be applied to prosthetics and biomedical robotics; hence, anthropomorphism is a fundamental requirement to be addressed both in the physical aspect and in the functional behavior. As regards the hand mechanics, a cable-driven underactuation is proposed in order to enlighten the structure, allow anthropomorphic self-adaptation to the object to be grasped, and simplify the control. Two simple PD control systems are formulated and evaluated in a common task of grasping a cylindrical object. The reference input for the control is derived from data on human subjects performing the same task and extracted by the literature. The paper reports simulation results about the comparison with the human case when both control systems are used to close the finger, so to derive specific indications for the improvement of the hand design


abstract: Solving the Credit Assignment Problem: The interaction of Explicit and Implicit learning with Internal and External State Information Wai-Tat Fu (wfu@cmu.edu) Human Factors Division and Beckman Institute University of Illinois at Urbana-Champaign 1 Airport Road, Savoy, IL 61874, USA John R. Anderson (ja+@cmu.edu) Department of Psychology Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA 15213 USA recognition of external state information (signs on the walls). Indeed, many have argued that real-world skills often involve the interplay between cognition (internal), perception, and action (external) that the understanding of these interactive skills requires careful study of how internal (memory) and external information (cues in the environment) are processed in the learning processes (Ballard, 1997; Fu & Gray, 2000; 2004; Gray & Fu, 2004; Larkin, 1989; Gray, Sims, Fu, & Schoelles, in press). The navigation problem above is an example of one of the most difficult situations in skill learning: when the learner has to perform a sequence of actions but only gets feedback on their success at the end of the sequence (e.g., when the destination is reached). This creates a credit-assignment problem, in which the learner has to assign credits to earlier actions that are responsible for eventual success. When actions are interdependent, either memory of previous actions or recognition of the correct problem state in the external environment is required to properly assign credits to the appropriate actions. In this article, we present results from an experiment in which we study how people learn to solve the credit-assignment problem in a simple but challenging example of such a situation. Our focus is on the recent proposal that humans exhibit two distinct learning processes and we apply it to learning of action sequences with delayed feedback: an explicit process (with awareness) that requires memory for actions and outcomes, and an implicit process (without awareness) that does not require such memory. We will first review research in some related areas that informed the design of our experiment. Abstract In most problem-solving activities, feedback is received at the end of an action sequence. This creates a credit-assignment problem where the learner must associate the feedback with earlier actions, and the interdependencies of actions require the learner to either remember past choices of actions (internal state information) or rely on external cues in the environment (external state information) to select the right actions. We investigated the nature of explicit and implicit learning processes in the credit-assignment problem using a probabilistic sequential choice task with and without external state information. We found that when explicit memory encoding was dominant, subjects were faster to select the better option in their first choices than in the last choices; when implicit reinforcement learning was dominant subjects were faster to select the better option in their last choices than in their first choices. However, implicit reinforcement learning was only successful when distinct external state information was available. The results suggest the nature of learning in credit assignment: an explicit memory encoding process that keeps track of internal state information and a reinforcement-learning process that uses state information to propagate reinforcement backwards to previous choices. However, the implicit reinforcement learning process is effective only when the valences can be attributed to the appropriate states in the system – either internally generated states in the cognitive system or externally presented stimuli in the environment. Introduction Consider a person navigating in a large office building. The person has to decide when to turn left or right at various hallway intersections. The sequence of decisions is interdependent – e.g., turning left at a particular hallway intersection will affect the decisions at the next intersections. The person may therefore need to keep track of previous actions to inform what actions to take in the future. In reality, memory of previous actions (internal state information) may not be necessary as people can explicitly seek information in the environment (external state information) to know where one is located or which direction to go to reach a destination (Fu & Gray, 2006). Learning to navigate is therefore likely to involve both the retention of internal state information (memory) and the Explicit and Implicit Learning Probability Learning and Classification There have been numerous studies on the learning of the probabilistic relationship between choices and their consequences. The simplest situation is the probability- learning experiment in which subjects guess which of the alternatives occurs and then receives feedback on their guesses (e.g., Estes, 1964). One robust finding is that subjects often “probability match”; that is, they will choose a particular alternative with the same probability that it is reinforced (e.g., Friedman et al., 1964). This leads many to propose that probability matching is the result of an implicit


title: Counselling Utilization Experiences among Methadone Maintenance Treatment Clients in Rural and Small Urban Communities/Expériences De L'utilisation Du Counseling Parmi Les Clients Subissant Un Traitement De Maintien À la Méthadone Dans Les Communautés Rurales et Les Petites Communautés Urbaines

abstract: The association between opiate dependence and methadone maintenance treatment (MiMiT) has been extensively investigated, and research literature suggests it is an effective means of treatment (Ffealth Canada, 2002; New Brunswick Department of Ffealth, 2005; Ponizovsky & Grinshpoon, 2007). Methadone is a medical synthetic opioid agonist appropriate for maintenance therapy because it is an efficient and long-lasting method of relieving the intense cravings and withdrawal symptoms associated with opiate detoxification. Although the effec- tiveness of MMT is well documented, little research has been conducted on the utilization of counselling by MMT participants. Furthermore, the majority of existing research has been completed in large urban centres, potentially limiting the transferability of findings into smaller urban and rural settings. Taking into consideration the rising rates of opiate dependence experienced within Atlantic Canada in the past decade, the present study aimed to expand this research to examine the counselling experiences of MMT participants living in small urban and rural communities within Atlantic Canada.COUNSELLING AND METHADONE MAINTENANCE TREATMENTA small body of literature suggests there are additional benefits experienced by MMT clients who access counselling services as part of their opiate dependence treatment (Fischer, Chin, Kuo, Kirst, & Vlahov, 2002; Gossop, Stewart, & Marsden, 2003, 2006; New Brunswick Department of Health, 2005; Vigilant, 2008). Furthermore, many studies have found that better treatment outcomes occur when clients include some form of counselling as part of their recovery plan rather than relying solely on methadone to treat their opiate dependence (Gossop et al., 2003, 2006). Addiction and psychiatric focused counselling, including individual, group, couple, or family counselling, may contribute to providing important support, education, coping strategies, and skill development to the methadone maintained clients (Fals-Stewart, O'Farrell, & Birchler, 2001; Gossop et al., 2003; New Brunswick Department of Health, 2005). Furthermore, the behavioural and cognitive changes that occur when MMT is implemented have been found to be strongly associated with increased access to counselling services (Gossop et ah, 2006; Sigmon & Stitzer, 2005).Fischer et al. (2002) and Quigley (2003) found that MMT clients believed that counselling participation was an important element of their recovery efforts. However, attendance in counselling among the MMT population often remains very low. Sigmon and Stitzer (2005) reported only one third of the MMT population they surveyed accessed counselling services regularly. It has been suggested that low attendance may be the result of MMT participants wanting flexibility and active involvement in the decision-making process with regard to the counselling they receive (Fischer et al., 2002; Quigley, 2003). When given a choice in their counselling, opiate-dependent clients reported they felt the process was empowering. In addition, clients favoured counsellors who were flexible in their availability to schedule appointments. MMT participants stated they preferred a counsellor who could be available for them both physically and psychologically, with an understanding of the special needs of their population (Quigley, 2003). These participants felt that methadone gave them the ability to address their concerns therapeutically, examining their addictions in greater detail and offering a chance to rebuild important relationships hurt by their addictions (Vigilant, 2008).COUNSELLING SERVICES AND RURAL COMMUNITIESThe literature has repeatedly noted that individuals living in smaller urban and rural communities may face additional challenges to accessing counselling services for their substance abuse. Sexton, Carlson, Leukefeld, and Booth (2008) categorized these barriers into five areas: physical, financial, societal, organizational, and psychological. …


title: Psychopathy and instrumental aggression: Evolutionary, neurobiological, and legal perspectives

abstract: In the study of aggression, psychopathy represents a disorder that is of particular interest because it often involves aggression which is premeditated, emotionless, and instrumental in nature; this is especially true for more serious types of offenses. Such instrumental aggression is aimed at achieving a goal (e.g., to obtain resources such as money, or to gain status). Unlike the primarily reactive aggression observed in other disorders, psychopaths appear to engage in aggressive acts for the purpose of benefiting themselves. This is especially interesting in light of arguments that psychopathy may represent an alternative life-history strategy that is evolutionarily adaptive; behaviors such as aggression, risk-taking, manipulation, and promiscuous sexual behavior observed in psychopathy may be means by which psychopaths gain advantage over others. Recent neurobiological research supports the idea that abnormalities in brain regions key to emotion and morality may allow psychopaths to pursue such a strategy—psychopaths may not experience the social emotions such as empathy, guilt, and remorse that typically discourage instrumentally aggressive acts, and may even experience pleasure when committing these acts. Findings from brain imaging studies of psychopaths may have important implications for the law.


title: Prosody conversion from neutral speech to emotional speech

abstract: Emotion is an important element in expressive speech synthesis. Unlike traditional discrete emotion simulations, this paper attempts to synthesize emotional speech by using "strong", "medium", and "weak" classifications. This paper tests different models, a linear modification model (LMM), a Gaussian mixture model (GMM), and a classification and regression tree (CART) model. The linear modification model makes direct modification of sentence F0 contours and syllabic durations from acoustic distributions of emotional speech, such as, F0 topline, F0 baseline, durations, and intensities. Further analysis shows that emotional speech is also related to stress and linguistic information. Unlike the linear modification method, the GMM and CART models try to map the subtle prosody distributions between neutral and emotional speech. While the GMM just uses the features, the CART model integrates linguistic features into the mapping. A pitch target model which is optimized to describe Mandarin F0 contours is also introduced. For all conversion methods, a deviation of perceived expressiveness (DPE) measure is created to evaluate the expressiveness of the output speech. The results show that the LMM gives the worst results among the three methods. The GMM method is more suitable for a small training set, while the CART method gives the better emotional speech output if trained with a large context-balanced corpus. The methods discussed in this paper indicate ways to generate emotional speech in speech synthesis. The objective and subjective evaluation processes are also analyzed. These results support the use of a neutral semantic content text in databases for emotional speech synthesis


title: Perforator patterns of the anteromedial thigh flap.

abstract: BACKGROUND ::: The vascular anatomy of the anteromedial thigh flap has not been well defined. The purpose of this study was to determine the perforator patterns and vascular anatomy of this flap. ::: ::: ::: METHODS ::: The perforators of the anteromedial thigh flaps and their origins were prospectively explored, documented, and mapped. ::: ::: ::: RESULTS ::: Twenty-one of 100 thighs had no anteromedial thigh perforators. For the remaining thighs, there were two sources of perforators: the rectus femoris branch of the descending branch of the lateral circumflex femoris artery, and the superficial femoral artery. Perforators from the latter were short and small and thus less useful. Anteromedial thigh flaps based on rectus femoris branch perforators shared the same vascular pedicle as the anterolateral thigh flap and were thus clinically useful. These rectus femoris branch perforators, however, were present in only 51 percent of the patients. Their surface locations follow a similar pattern as the anterolateral thigh flap, with the majority of perforators near the midpoint, but an average of 3.2 cm medial to a line connecting the anterior superior iliac spine and the superolateral patella. Forty-three thighs had a single rectus femoris branch perforator and eight had two perforators. Sixty-six percent were septocutaneous and the rest traversed a thin layer of the rectus femoris muscle. ::: ::: ::: CONCLUSIONS ::: The perforator patterns of the anteromedial thigh flap were examined and defined. It is best to plan the anteromedial thigh flap to complement the anterolateral thigh rather than to be the primary flap.


title: Bacterial Cellulose Production by Acetobacter xylinum Strains from Agricultural Waste Products

abstract: Bacterial cellulose is a biopolysaccharide produced from the bacteria, Acetobacter xylinum. Static batch fermentations for bacterial cellulose production were studied in coconut and pineapple juices under 30 °C in 5-l fermenters by using three Acetobacter strains: A. xylinum TISTR 998, A. xylinum TISTR 975, and A. xylinum TISTR 893. Experiments were carried out to compare bacterial cellulose yields along with growth kinetic analysis. Results showed that A. xylinum TISTR 998 produced a bacterial cellulose yield of 553.33 g/l, while A. xylinum TISTR 893 produced 453.33 g/l and A. xylinum TISTR 975 produced 243.33 g/l. In pineapple juice, the yields for A. xylinum TISTR 893, 975, and 998 were 576.66, 546.66, and 520 g/l, respectively. The strain TISTR 998 showed the highest productivity when using coconut juice. Morphological properties of cellulose pellicles, in terms of texture and color, were also measured, and the textures were not significantly different among treatments.


title: 5.4 A 32nW bandgap reference voltage operational from 0.5V supply for ultra-low power systems

abstract: Most systems require a voltage reference independent of variation of power supply, process, or temperature, and a bandgap voltage reference (BGR) often serves this purpose. For ultra-low power (ULP) systems, the BGR may constitute a significant component of standby power, and the system start-up voltage is often determined by the voltage, V in , at which the BGR becomes operational. Lowering V in can also allow an ULP system to continue operation longer as its battery or energy harvested input voltage decreases. The minimum V in for state-of-the-art BGRs is restricted by V EB +V DS [1], where V EB is the emitter-base voltage of a pnp transistor, and V DS is the drain-source saturation voltage of a MOS transistor. Recent work brings the V in voltage down to 700mV [2]. There is a need to reduce the standby power and V in of a BGR to increase the lifetime of ULP systems. This paper presents a BGR circuit with measured minimum operating V in of 500mV, reducing the V in of [2] by 1.4x. Further, the power consumption of the proposed circuit is 32nW, which is 1.6x lower than the non-duty cycled BGR reported in [2]. A 2x-charge pump based bandgap core, a switched-capacitor network (SCN), and a current controlled oscillator and clock doubler circuit enable a BGR with a temperature variation of 75ppm/°C and power supply rejection (PSR) of up to −52dB at DC.


title: Automating Mappings between Use Case Diagrams and Feature Models for Software Product Lines

abstract: Features have been widely used by the product line community to model variability. They represent the common and variable characteristics of the members of a product line. They are very well suited for the configuration of product line members. Outside the product line community, use cases are also widely used to model the functionality of systems at a similar level of abstraction but from a user perspective. Significant work has been done by several authors regarding the possible relationship between these two perspectives of a system. Nonetheless, this has been done in an informal way. In this paper we explore the relationships between these two perspectives and describe a possible approach to automate the transformation from UML use case to feature models.


title: Video Synthesis from a Single Image and Motion Stroke

abstract: In this paper, we propose a new method to automatically generate a video sequence from a single image and a user provided motion stroke. Generating a video sequence based on a single input image has many applications in visual content creation, but it is tedious and time-consuming to produce even for experienced artists. Automatic methods have been proposed to address this issue, but most existing video prediction approaches require multiple input frames. In addition, generated sequences have limited variety since the output is mostly determined by the input frames, without allowing the user to provide additional constraints on the result. In our technique, users can control the generated animation using a sketch stroke on a single input image. We train our system such that the trajectory of the animated object follows the stroke, which makes it both more flexible and more controllable. From a single image, users can generate a variety of video sequences corresponding to different sketch inputs. Our method is the first system that, given a single frame and a motion stroke, can generate animations by recurrently generating videos frame by frame. An important benefit of the recurrent nature of our architecture is that it facilitates the synthesis of an arbitrary number of generated frames. Our architecture uses an autoencoder and a generative adversarial network (GAN) to generate sharp texture images, and we use another GAN to guarantee that transitions between frames are realistic and smooth. We demonstrate the effectiveness of our approach on the MNIST, KTH, and Human 3.6M datasets.


title: The GPU-based Parallel Ant Colony System

abstract: Abstract The Ant Colony System (ACS) is, next to Ant Colony Optimization (ACO) and the MAX–MIN Ant System (MMAS), one of the most efficient metaheuristic algorithms inspired by the behavior of ants. In this article we present three novel parallel versions of the ACS for the graphics processing units (GPUs). To the best of our knowledge, this is the first such work on the ACS which shares many key elements of the ACO and the MMAS, but differences in the process of building solutions and updating the pheromone trails make obtaining an efficient parallel version for the GPUs a difficult task. The proposed parallel versions of the ACS differ mainly in their implementations of the pheromone memory. The first two use the standard pheromone matrix, and the third uses a novel selective pheromone memory. Computational experiments conducted on several Traveling Salesman Problem (TSP) instances of sizes ranging from 198 to 2392 cities showed that the parallel ACS on Nvidia Kepler GK104 GPU (1536 CUDA cores) is able to obtain a speedup up to 24.29x vs the sequential ACS running on a single core of Intel Xeon E5-2670 CPU. The parallel ACS with the selective pheromone memory achieved speedups up to 16.85x, but in most cases the obtained solutions were of significantly better quality than for the sequential ACS.


PolySearch2: a significantly improved text-mining system for discovering associations between human diseases, genes, drugs, metabolites, toxins and more


title: Fabrication of interconnected pore forming α-tricalcium phosphate foam granules cement

abstract: Interconnected pore forming calcium phosphate cement is useful for the reconstruction of bone defects as well as scaffold fabrication in tissue engineering. In this study, interconnected pore forming calcium phosphate cement was fabricated using α-tricalcium phosphate (α-TCP) foam granules. When α-TCP foam granules were mixed with acidic calcium phosphate solution prepared from monocalcium phosphate monohydrate (MCPM) and phosphoric acid solution, brushite crystals were precipitated. These crystals bridged the α-TCP foam granules immediately upon mixing. As a result of the brushite bridge between the α-TCP foam granules, fully interconnected macroporous α-TCP was obtained. The amount of brushite precipitate and the mechanical strength of the set cement increased with acidic calcium phosphate concentration.


Recognition of Invoices from Scanned Documents


title: Mapping kernel objects to enable systematic integrity checking

abstract: Dynamic kernel data have become an attractive target for kernel-mode malware. However, previous solutions for checking kernel integrity either limit themselves to code and static data or can only inspect a fraction of dynamic data, resulting in limited protection. Our study shows that previous solutions may reach only 28% of the dynamic kernel data and thus may fail to identify function pointers manipulated by many kernel-mode malware. To enable systematic kernel integrity checking, in this paper we present KOP, a system that can map dynamic kernel data with nearly complete coverage and nearly perfect accuracy. Unlike previous approaches, which ignore generic pointers, unions and dynamic arrays when locating dynamic kernel objects, KOP (1) applies inter-procedural points-to analysis to compute all possible types for generic pointers (e.g., void*), (2) uses a pattern matching algorithm to resolve type ambiguities (e.g., unions), and (3) recognizes dynamic arrays by leveraging knowledge of kernel memory pool boundaries. We implemented a prototype of KOP and evaluated it on a Windows Vista SP1 system loaded with 63 kernel drivers. KOP was able to accurately map 99% of all the dynamic kernel data. To demonstrate KOP's power, we developed two tools based on it to systematically identify malicious function pointers and uncover hidden kernel objects. Our tools correctly identified all malicious function pointers and all hidden objects from nine real-world kernel-mode malware samples as well as one created by ourselves, with no false alarms.


title: Adaptive Fraud Detection

abstract: One method for detecting fraud is to check for suspicious changes in user behavior. This paper describes the automatic design of user profiling methods for the purpose of fraud detection, using a series of data mining techniques. Specifically, we use a rule-learning program to uncover indicators of fraudulent behavior from a large database of customer transactions. Then the indicators are used to create a set of monitors, which profile legitimate customer behavior and indicate anomalies. Finally, the outputs of the monitors are used as features in a system that learns to combine evidence to generate high-confidence alarms. The system has been applied to the problem of detecting cellular cloning fraud based on a database of call records. Experiments indicate that this automatic approach performs better than hand-crafted methods for detecting fraud. Furthermore, this approach can adapt to the changing conditions typical of fraud detection environments.


title: A New Broadband Marchand Balun Using Slot-Coupled Microstrip Lines

abstract: In this letter, a new broadband Marchand balun is proposed using slot-coupled microstrip lines. The developed balun is connected by two sections of diamond-shape slot-coupled microstrips with short- and open-circuited terminations at specified ports. To achieve the broadband operation, the simple formulas have been derived to convert the conventional rectangular-shape slot-coupled microstrip to the diamond-shape counterpart. The measured results of the developed balun not only agree with the full-wave simulation results very well, but also resemble the calculated results by ideal coupled lines. The new Marchand balun developed in this letter has a 10 dB return loss bandwidth of 90%, while in this frequency range the amplitude imbalance varies from -0.37 dB to 0.32 dB, and the phase difference in the range of -180.4° ~ -181.8°.


title: Causes and consequences of endoplasmic reticulum stress in rheumatic disease

abstract: &NA; Rheumatic diseases represent a heterogeneous group of inflammatory conditions, many of which involve chronic activation of both innate and adaptive immune responses by multiple genetic and environmental factors. These immune responses involve the secretion of excessive amounts of cytokines and other signalling mediators by activated immune cells. The endoplasmic reticulum (ER) is the cellular organelle that directs the folding, processing and trafficking of membrane‐bound and secreted proteins, including many key components of the immune response. Maintaining homeostasis in the ER is critical to cell function and survival. Consequently, elaborate mechanisms have evolved to sense and respond to ER stress through three main signalling pathways that together comprise the unfolded protein response (UPR). Activation of the UPR can rapidly resolve the accumulation of misfolded proteins, direct permanent changes in the size and function of cells during differentiation, and critically influence the immune response and inflammation. Recognition of the importance of ER stress and UPR signalling pathways in normal and dysregulated immune responses has greatly increased in the past few years. This Review discusses several settings in which ER stress contributes to the pathogenesis of rheumatic diseases and considers some of the therapeutic opportunities that these discoveries provide.


title: Admittance control for physical human-quadrocopter interaction

abstract: This paper analyzes the application of admittance control to quadrocopters, focusing on physical human-vehicle interaction. Admittance control allows users to define the apparent inertia, damping, and stiffness of a robot, providing an intuitive way to physically interact with it. In this work, external forces acting on the quadrocopter are estimated from position and attitude information and then input to the admittance controller, which modifies the vehicle reference trajectory accordingly. The reference trajectory is tracked by an underlying position and attitude controller. The characteristics of the overall control scheme are investigated for the near-hover case. Experimental results complement the paper, demonstrating the suitability of the method for physical human-quadrocopter interaction.


title: Design and Comparison of 4-kV Neutral-Point-Clamped, Flying-Capacitor, and Series-Connected H-Bridge Multilevel Converters

abstract: This paper describes the design of a (4-kV, 4.16-MVA) three-level neutral-point-clamped-, three-level flying-capacitor-, four-level flying-capacitor-, and nine-level seriesconnected H-bridge voltage-source converter on the basis of state-of-the-art 6.5-, 4.5-, 3.3- and 1.7-kV insulated gate bipolar transistors. The semiconductor loss distribution and the design of semiconductors and passive components are compared for a medium switching frequency assuming a constant converter efficiency of about 99%. To evaluate the converter characteristics in high switching frequency applications, a second comparison is realized for the maximum switching frequencies assuming a constant expense of semiconductors in all converters.


title: Android based heart rate monitoring and automatic notification system

abstract: In this paper, the design of an integrated portable device that can monitor heart rate (HR) continuously and send notifications through short message service (SMS) over the cellular network using Android application is presented. The primary goal of our device is to ensure medical attention within the first few critical hours of an ailment of the patient with poor heart condition, hence boost chances of his or her survival. In situations where there is an absence of doctor or clinic nearby (e.g., rural area) and where the patient cannot realize their actual poor heart condition, is where our implemented system is of paramount importance. The designed system shows the real time HR on the mobile screen through Android application continuously and if any abnormal HR of the patient is detected, the system will immediately send a message to the concerned doctors and relatives whose numbers were previously saved in the Android application. This device ensures nonstop monitoring for cardiac events along with notifying immediately when an emergency strikes.


title: A study of the knowledge base requirements for passing an elementary science test

abstract: Our long-term interest is in machines that contain large amounts of general and scientific knowledge, stored in a "computable" form that supports reasoning and explanation. As a medium-term focus for this, our goal is to have the computer pass a fourth-grade science test, anticipating that much of the required knowledge will need to be acquired semi-automatically. This paper presents the first step towards this goal, namely a blueprint of the knowledge requirements for an early science exam, and a brief description of the resources, methods, and challenges involved in the semi-automatic acquisition of that knowledge. The result of our analysis suggests that as well as fact extraction from text and statistically driven rule extraction, three other styles of automatic knowledge base construction (AKBC) would be useful: acquiring definitional knowledge, direct 'reading' of rules from texts that state them, and, given a particular representational framework (e.g., qualitative reasoning), acquisition of specific instances of those models from text (e..g, specific qualitative models).


title: Embedded system for a Ballbot robot

abstract: This paper presents an embedded system for a ballbot robotic platform, which is a balanced omnidirectional mobile robot that moves on a sphere. It provides a higher degree of maneuverability compared to the wheeled mobile robots. The robot balances it on a ball and gives to the system only one contact point with the ground. This allows to reduce the friction and the space needed by the system to turn around a point. This is a major feature for a mobile vehicle, considering that most of them rotate their whole body to obtain a change in direction. The proposed platform is self-contained with on-board sensing and computation, it uses only off-the-shelf components and is designed to perform maneuvers when operating in tight spaces as in the human environments. The proposed embedded system is based on a general pourpose embedded board equipped with a 32bit microcontroller which is able to manage all the basic tasks of this robotic platform: sensing, actuation, control and communication. The proposed system is described and initial experimental results are introduced, furthermore the challenges faced are presented.


title: From A to Z: Supervised Transfer of Style and Content Using Deep Neural Network Generators

abstract: We propose a new neural network architecture for solving single-image analogies - the generation of an entire set of stylistically similar images from just a single input image. Solving this problem requires separating image style from content. Our network is a modified variational autoencoder (VAE) that supports supervised training of single-image analogies and in-network evaluation of outputs with a structured similarity objective that captures pixel covariances. On the challenging task of generating a 62-letter font from a single example letter we produce images with 22.4% lower dissimilarity to the ground truth than state-of-the-art.


title: Modelling and correction of multipath interference in time of flight cameras

abstract: This paper presents an algorithm that automatically corrects the distortion caused by multipath interference (MpI) in depth measurements obtained with time of flight cameras (ToF cameras). A radiometric model that explains, under some mild simplifications, the working principle of a ToF camera including a model for MpI is proposed. Using this model we demonstrate that all the information needed for compensating the influence of MpI on the scene captured by the camera is self-contained in the measurements (depth and amplitude of infrared signal). We propose an iterative optimization method that, based on the measurements contaminated with MpI, gives depth correction for each pixel. Results are shown in artificially generated time of flight scenes using the radiometric model. In addition, the system has been validated in real scenes using a commercial ToF camera providing good results.


title: Hidden Markov Model Based Events Detection in Soccer Video

abstract: This paper presents an algorithm developed based on hidden Markov model for cues fusion and event inference in soccer video. Four events, shoot, foul, offside and normal playing, are defined to be detected. The states of the events are employed to model the observations of the five cues, which are extracted from the shot sequences directly. The experimental results show the algorithm is effective and robust in inferring events from roughly extracted cues.


title: Co-learning of Word Representations and Morpheme Representations

abstract: The techniques of using neural networks to learn distributed word representations (i.e., word embeddings) have been used to solve a variety of natural language processing tasks. The recently proposed methods, such as CBOW and Skip-gram, have demonstrated their effectiveness in learning word embeddings based on context information such that the obtained word embeddings can capture both semantic and syntactic relationships between words. However, it is quite challenging to produce high-quality word representations for rare or unknown words due to their insufficient context information. In this paper, we propose to leverage morphological knowledge to address this problem. Particularly, we introduce the morphological knowledge as both additional input representation and auxiliary supervision to the neural network framework. As a result, beyond word representations, the proposed neural network model will produce morpheme representations, which can be further employed to infer the representations of rare or unknown words based on their morphological structure. Experiments on an analogical reasoning task and several word similarity tasks have demonstrated the effectiveness of our method in producing high-quality words embeddings compared with the state-of-the-art methods.


title: Fashion 10000: an enriched social image dataset for fashion and clothing

abstract: In this work, we present a new social image dataset related to the fashion and clothing domain. The dataset contains more than 32000 images, their context and social metadata. Furthermore the dataset is enriched with several types of annotations collected from the Amazon Mechanical Turk (AMT) crowdsourcing platform, which can serve as ground truth for various content analysis algorithms. This dataset has been successfully used at the Crowdsourcing task of the 2013 MediaEval Multimedia Benchmarking initiative. The dataset contributes to several research areas such as Crowdsourcing, multimedia content and context analysis as well as hybrid human/automatic approaches. In this paper, the dataset is described in detail and the dataset collection strategy, statistics, applications of dataset and its contribution to MediaEval 2013 is discussed.


title: Changes in skin mucus of common carp, Cyprinus carpio L., after exposure to water with a high bacterial load.

abstract: Water in aquaculture systems may contain a high load of microorganisms. Reduction in overall bacterial tank water load improves fish health and growth parameters. In this study, the effect of an increase of overall bacterial load in tank water on carp skin mucus was assessed. Intracellular and released high molecular weight glycoproteins (HMGs) of carp skin mucus were analysed for changes using histological, histochemical and biochemical techniques. Increase of bacterial load did not induce obvious clinical responses in carp, but the skin of exposed carp responded quickly. The amount of skin mucus HMGs isolated increased as well as their total glycosylation. An increased goblet cell number was observed for all carbohydrate stainings, but most clearly for acidic glycoconjugates. A change in the terminal presence of some sugars was also seen. After the initial response of carp, an adaptation to the higher bacterial load in the water appeared to occur as mucins had a higher glycosylation. The changes observed suggest that these skin mucus adaptations are part of a primary defence mechanism of mucosal epithelia, even at a low pathogenic pressure.


title: Mean Hilbert Envelope Coefficients (MHEC) for robust speaker recognition

abstract: The recently introduced mean Hilbert envelope coefficients (MHEC) have been shown to be an effective alternative to MFCCs for robust speaker identification under noisy and reverberant conditions in relatively small tasks. In this study, we investigate the effectiveness of these acoustic features in the context of a state-of-the-art speaker recognition system. The i-vectors are used to represent the acoustic space of speakers, while modeling is performed via probabilistic linear discriminant analysis (PLDA). We report speaker verification performance on the NIST SRE-2010 extended telephone and microphone trials for both female and male genders. Experimental results confirm consistent superiority of MHECs to traditional MFCCs within i-vector speaker verification, particularly under microphone and telephone training-test mismatch conditions. In addition, fusion of subsystems trained with the individual front-ends proves that the two acoustic features (i.e., MHEC and MFCC) provide complimentary information for recognizing speakers.


title: Adaptive Hypermedia

abstract: Adaptive hypermedia is a relatively new direction of research on the crossroads of hypermedia and user modeling. Adaptive hypermedia systems build a model of the goals, preferences and knowledge of each individual user, and use this model throughout the interaction with the user, in order to adapt to the needs of that user. The goal of this paper is to present the state of the art in adaptive hypermedia at the eve of the year 2000, and to highlight some prospects for the future. This paper attempts to serve both the newcomers and the experts in the area of adaptive hypermedia by building on an earlier comprehensive review (Brusilovsky, 1996; Brusilovsky, 1998).


title: Rumination as a Mechanism Linking Stressful Life Events to Symptoms of Depression and Anxiety: Longitudinal Evidence in Early Adolescents and Adults

abstract: Rumination is a well-established risk factor for the onset of major depression and anxiety symptomatology in both adolescents and adults. Despite the robust associations between rumination and internalizing psychopathology, there is a dearth of research examining factors that might lead to a ruminative response style. In the current study, we examined whether social environmental experiences were associated with rumination. Specifically, we evaluated whether self-reported exposure to stressful life events predicted subsequent increases in rumination. We also investigated whether rumination served as a mechanism underlying the longitudinal association between self-reported stressful life events and internalizing symptoms. Self-reported stressful life events, rumination, and symptoms of depression and anxiety were assessed in 2 separate longitudinal samples. A sample of early adolescents (N = 1,065) was assessed at 3 time points spanning 7 months. A sample of adults (N = 1,132) was assessed at 2 time points spanning 12 months. In both samples, self-reported exposure to stressful life events was associated longitudinally with increased engagement in rumination. In addition, rumination mediated the longitudinal relationship between self-reported stressors and symptoms of anxiety in both samples and the relationship between self-reported life events and symptoms of depression in the adult sample. Identifying the psychological and neurobiological mechanisms that explain a greater propensity for rumination following stressors remains an important goal for future research. This study provides novel evidence for the role of stressful life events in shaping characteristic responses to distress, specifically engagement in rumination, highlighting potentially useful targets for interventions aimed at preventing the onset of depression and anxiety. Language: en


title: High-Speed and Lightweight Humanoid Robot Arm for a Skillful Badminton Robot

abstract: Sports, especially badminton, require participants to perform dynamic and skillful motions. Previous robots have had difficulty in performing like a human because of their severe limitations of low operating speed, heavy bodies, and simplistic mechanisms. In this letter, we propose a new robot design that consists of a structure integrated with pneumatic actuators and noninterfering many-degree-of-freedom joints, for the realization of a high-speed and lightweight humanoid robot. We made a four-degree-of-freedom robot arm for badminton, which is an especially dynamic sport, aiming for maximum speed while meeting geometric requirements. The robot swung with a racket-head speed of 21 m/s, which is a value higher than speeds achieved by previous robotic arms. The robot also realized a skillful shot, namely the spin net shot, which cannot be performed by previous badminton robots having simple mechanisms. A pneumatic robot is considered difficult to control, especially in terms of feedback control. We found that the reproducibility of the robot was as fine as 10-40 mm at the racket head for four kinds of strong swings. Using feedforward control, we also conducted an experiment in which the robot hits a flying shuttle, and achieved a high hitting rate of 69.7% for powerful swings. We believe that this research expands the possibilities of the pneumatic robot and is the first step toward developing a skillful humanoid badminton robot.


title: Multi-Branch Fully Convolutional Network for Face Detection

abstract: Face detection is a fundamental problem in computer vision. It is still a challenging task in unconstrained conditions due to significant variations in scale, pose, expressions, and occlusion. In this paper, we propose a multi-branch fully convolutional network (MB-FCN) for face detection, which considers both efficiency and effectiveness in the design process. Our MB-FCN detector can deal with faces at all scale ranges with only a single pass through the backbone network. As such, our MB-FCN model saves computation and thus is more efficient, compared to previous methods that make multiple passes. For each branch, the specific skip connections of the convolutional feature maps at different layers are exploited to represent faces in specific scale ranges. Specifically, small faces can be represented with both shallow fine-grained and deep powerful coarse features. With this representation, superior improvement in performance is registered for the task of detecting small faces. We test our MB-FCN detector on two public face detection benchmarks, including FDDB and WIDER FACE. Extensive experiments show that our detector outperforms state-of-the-art methods on all these datasets in general and by a substantial margin on the most challenging among them (e.g. WIDER FACE Hard subset). Also, MB-FCN runs at 15 FPS on a GPU for images of size 640 x 480 with no assumption on the minimum detectable face size.


title: On Pairwise Cost for Multi-Object Network Flow Tracking

abstract: Multi-object tracking has been recently approached with the min-cost network flow optimization techniques. Such methods simultaneously resolve multiple object tracks in a video and enable modeling of dependencies among tracks. Min-cost network flow methods also fit well within the "tracking-by-detection" paradigm where object trajectories are obtained by connecting per-frame outputs of an object detector. Object detectors, however, often fail due to occlusions and clutter in the video. To cope with such situations, we propose to add pairwise costs to the min-cost network flow framework. While integer solutions to such a problem become NP-hard, we design a convex relaxation solution with an efficient rounding heuristic which empirically gives certificates of small suboptimality. We evaluate two particular types of pairwise costs and demonstrate improvements over recent tracking methods in real-world video sequences.


title: Silicone Migration and Silicone- Induced Granulomas following Injection in the Buttocks of an HIV Patient: a Case Report and Review of Management

abstract: Background: The use of liquid injectable silicone for soft tissue augmentation is a controversial practice because this material has been implicated in a variety of adverse reactions, sometimes with latent periods of decades, when the patient does not remember which product was injected. The histopathologic findings may allow the identification of the injected filler and is considered the gold standard for diagnosis. Method: We report the case of a 43-year-old homosexual men with medical history of HIV (CD4 >900 UI/ml, viral load < 40cp/ml, on HAART) and hepatitis C who presented with a painful lumbosacral mass 7 years after a soft-tissue augmentation of the buttocks with an unknown product. The medical treatment was insufficient until the patient assessment. It was unclear what the mass represented, and he underwent surgical excision under general anaesthesia, with the histopathologic examination of the biopsy specimen. After surgery the patient presented no complications and was discharged on POD 1. Results: Histopathologic evaluation revealed the liquid injectable silicone migration accompanied by a granulomatous response and presence of cells with collection of lipid-containing cytoplasmic vacuoles resembling lipoblasts. This pattern can be clinically and histologically confusing for a liposarcoma, especially when this occurrence appears years after injection. Conclusions: Migration and granulomatous reaction to silicone may occur as much as 10-20 years after injection and the patient often does not initially divulge a history of silicone augmentation, making diagnosis difficult. Complete surgical excision of the mass and histopathologic evaluation resulted in complete resolution and identification of the responsible filler. Abundant empty vacuoles that distort the nuclear contours in the cells that imbibed silicon may be a confounding factor with adipose neoplasms, such a liposarcoma and this diagnosis must be ruled out.


title: The Effects of Beef, Chicken, or Whey Protein After Workout on Body Composition and Muscle Performance

abstract: The purpose of this study was to determine the effects of post-workout consumption of beef protein isolate (Beef), hydrolyzed chicken protein (Chx) or whey protein concentrate (WPC), compared to a control on lean mass and strength during 8 weeks of resistance training. Forty-one males and females were randomized into four groups: WPC (m=5, f=5; Age (yrs)=19 ± 2, Height (cm)=171 ± 10, Mass (kg)= 74.60 ± 14.19), Beef (m=5, f=5; Age (yrs)=22 ± 4, Height (cm)=170 ± 7, Mass (kg)=70.13 ± 8.16), ChxC(m=5, f=6; Age (yrs)=21 ± 2, Height (cm)=169 ± 9, Mass (kg)=74.52 ± 13.83) and Maltodextrin (control) (m=4, f=6; Age (yrs)= 21 ± 2, Height (cm)=170 ± 9, Mass (kg)= 73.18 ± 10.96). Subjects partook in an 8-week periodized resistance-training program. Forty-six grams of protein or a control were consumed immediately following training or at similar times on off-days. Dual energy x-ray absorptiometry (DXA) was used to determine changes in body composition. Maximum strength were assessed by one repetition maximum (1RM) for bench press (upper body) and deadlift (lower body). Power output was measured using cycle ergometer. WPC (52.48 ± 11.15 to 54.96 ± 11.85), Beef (51.68 ± 7.61kg to 54.65 ± 8.67kg) and Chx (52.97 ± 12.12kg to 54.89 ± 13.43kg) each led to a significant increase in lean body mass compared with baseline (p<0.0001) while the control condition did not (53.14 ± 11.35kg to 54.19 ± 10.74kg). Fat loss was also significantly decreased at 8 weeks compared to baseline for all protein sources (WPC: 18.70 ± 7.38kg to 17.16 ± 7.18kg; Beef: 16.43 ± 5.71kg to 14.65 ± 5.41kg; Chx: 17.58 ± 5.57kg to 15.87 ± 6.07kg), but not the control condition (16.29 ± 7.14kg to 14.95 ± 7.72) (p<0.0001). One repetition maximum for both deadlift and bench-press were significantly increased for all treatment groups when compared to baseline. No differences in strength were noted between conditions. Overall, the results of this study demonstrate that consuming quality sources of protein from meat or WPC lead to significant benefits in body composition compared to control.


title: Low-Profile, Multi-Element, Miniaturized Monopole Antenna

abstract: A low-profile, electrically small antenna with omnidirectional vertically polarized radiation similar to a short monopole antenna is presented. The antenna features less than lambda/40 dimension in height and lambda/10 or smaller in lateral dimension. The antenna is matched to a 50 Omega coaxial line without the need for external matching. The geometry of the antenna is derived from a quarter-wave transmission line resonator fed at an appropriate location to maximize current through the short-circuited end. To improve radiation from the vertical short-circuited pin, the geometry is further modified through superposition of additional resonators placed in a parallel arrangement. The lateral dimension of the antenna is miniaturized by meandering and turning the microstrip lines into form of a multi-arm spiral. The meandering between the short-circuited end and the feed point also facilitates the impedance matching. Through this technique, spurious horizontally polarized radiation is also minimized and a radiation pattern similar to a short dipole is achieved. The antenna is designed, fabricated and measured. Parametric studies are performed to explore further size reduction and performance improvements. Based on the studies, a dual-band antenna with enhanced gain is realized. The measurements verify that the proposed fabricated antennas feature excellent impedance match, omnidirectional radiation in the horizontal plane and low levels of cross-polarization.


title: Full 3-D Printed Microwave Termination: A Simple and Low-Cost Solution

abstract: This paper describes the realization and characterization of microwave 3-D printed loads in rectangular waveguide technology. Several commercial materials were characterized at X-band (8–12 GHz). Their dielectric properties were extracted through the use of a cavity-perturbation method and a transmission/reflection rectangular waveguide method. A lossy carbon-loaded Acrylonitrile Butadiene Styrene (ABS) polymer was selected to realize a matched load between 8 and 12 GHz. Two different types of terminations were realized by fused deposition modeling: a hybrid 3-D printed termination (metallic waveguide + pyramidal polymer absorber + metallic short circuit) and a full 3-D printed termination (self-consistent matched load). Voltage standing wave ratio of less than 1.075 and 1.025 were measured over X-band for the hybrid and full 3-D printed terminations, respectively. Power behavior of the full 3-D printed termination was investigated. A very linear evolution of reflected power as a function of incident power amplitude was observed at 10 GHz up to 11.5 W. These 3-D printed devices appear as a very low cost solution for the realization of microwave matched loads in rectangular waveguide technology.


title: A constant voltage maximum power point tracking method for solar powered systems

abstract: A constant voltage maximum power point (MPP) algorithm that automatically adjusts the reference voltage to account for varying environmental conditions is presented. A simple (and inexpensive) analog feedforward PWM controller is developed to continuously track the MPP of a solar cell array as the weather conditions vary. The solar array source is configured such that its open-circuit voltage is sampled without breaking the entire source from the load as is the case with other constant voltage MPP algorithms. MATLAB/Simulink simulations are presented to demonstrate the performance of the proposed MPP algorithm. The simulations correlated well with experimental results using a pure resistive load.


title: Enumerating the Non-Isomorphic Assembly Configurations of Modular Robotic Systems

abstract: A modular robotic system consists of standardized joint and link units that can be assembled into a number of different kinematic configurations to meet various task requirements. Owing to typical symmetries in module design, different assembly configurations may lead to robotic structures that are geometrically identical, or isomorphic. This paper focuses on the problem of enumerating the set of kinematically distinct modular robot assembly configurations from a given set of modules. The authors first consider how to enumerate the nonisomorphic (or geometrically unique) assembly configurations of a modular robotic system. The scheme is based on a novel representation of a modular robot assembly configuration as an assembly incidence matrix (AIM). Equivalence relations based on symmetries in module geometry and graph isomorphisms are defined on the AIMs. An enumeration algorithm to generate nonisomorphic assembly configurations based on this equivalence relation is proposed. They then present an algorithm to identify the kinematically equivalent robots. The application of these two algorithms will result in the set of kinematically unique assembly configurations. Examples demonstrate that this method is a significant improvement over a brute-force enumeration process.


title: Competency-based medical education: implications for undergraduate programs

abstract: Changes in educational thinking and in medical program accreditation provide an opportunity to reconsider approaches to undergraduate medical education. Current developments in competency-based medical education (CBME), in particular, present both possibilities and challenges for undergraduate programs. CBME does not specify particular learning strategies or formats, but rather provides a clear description of intended outcomes. This approach has the potential to yield authentic curricula for medical practice and to provide a seamless linkage between all stages of lifelong learning. At the same time, the implementation of CBME in undergraduate education poses challenges for curriculum design, student assessment practices, teacher preparation, and systemic institutional change, all of which have implications for student learning. Some of the challenges of CBME are similar to those that can arise in the implementation of any integrated program, while others are specific to the adoption of outcome frameworks as an organizing principle for curriculum design. This article reviews a number of issues raised by CBME in the context of undergraduate programs and provides examples of best practices that might help to address these issues.


title: The UBIRIS.v2: A Database of Visible Wavelength Iris Images Captured On-the-Move and At-a-Distance

abstract: The iris is regarded as one of the most useful traits for biometric recognition and the dissemination of nationwide iris-based recognition systems is imminent. However, currently deployed systems rely on heavy imaging constraints to capture near infrared images with enough quality. Also, all of the publicly available iris image databases contain data correspondent to such imaging constraints and therefore are exclusively suitable to evaluate methods thought to operate on these type of environments. The main purpose of this paper is to announce the availability of the UBIRIS.v2 database, a multisession iris images database which singularly contains data captured in the visible wavelength, at-a-distance (between four and eight meters) and on on-the-move. This database is freely available for researchers concerned about visible wavelength iris recognition and will be useful in accessing the feasibility and specifying the constraints of this type of biometric recognition.


title: A novel compact single-feed dual-band circular polarization antenna

abstract: A new compact single-feed dual-band square-ring patch CP antenna with an unequal cross-slot ground plane is proposed. The size of the new antenna is compact and the simulated results show good performance. Also, it achieves a small frequency ratio.


title: The impact of informational incentives and social influence on consumer behavior during Alibaba's online shopping carnival

abstract: Abstract Alibaba's annual global online shopping carnival (OSC) held every November 11 (also known as Double 11 Day or Single's Day) is well known for being the most successful and largest online promotion campaign since its Chinese debut in 2009. We have witnessed the power of online herd behavior exhibited by a frenzy of consumers purchasing, sharing and interacting with each other during Alibaba's global OSC. This shopping carnival brought the entire Chinese electronic commerce industry an astonishing record volume of transactions worth 120.7 billion RMB and 1.04 billion transactions on Singles' Day in 2016. This study explores what facilitates consumer OSC behavior on Singles' Day. Drawing upon carnival theory and herd behavior, we develop an explanatory model to explain how informational incentives and social influence affect OSC consumer behavior. Data gathered from a large-scale online survey of consumers that participated during the Singles' Day period is used to test the model. The conceptual model was validated using the partial least squares (PLS) technique. The empirical results show that (1) participation, interaction and pleasure together define OSC consumer behavior; (2) informational incentives and social influence are two crucial preconditions for OSC consumer behavior. The results provide good support for the proposed research model and hypotheses and yield interesting insights about the important roles of informational incentives and social influence collectively facilitating OSC consumer behavior during the Singles' Day period in China.


abstract: Witnessing the emergence of Twitter, we propose a Twitter-based Event Detection and Analysis System (TEDAS), which helps to (1) detect new events, to (2) analyze the spatial and temporal pattern of an event, and to (3) identify importance of events. In this demonstration, we show the overall system architecture, explain in detail the implementation of the components that crawl, classify, and rank tweets and extract location from tweets, and present some interesting results of our system.


title: Factors affecting ERP system adoption: A comparative analysis between SMEs and large companies

abstract: Purpose – Proposes providing an insight about enterprise resource planning (ERP) adoption, highlighting contact points and significant differences between the way small to medium‐sized enterprises (SMEs) and large companies approach such a task.Design/methodology/approach – The research is based on a wide literature review, focused on the identification of a taxonomy of business and organizational factors influencing ERP adoption. The deriving research model was incorporated in a questionnaire that was preliminarily tested and finally provided to a sample of 366 companies of any size. Responses were collected through personal interviews made by a dedicated team to a top manager.Findings – The analysis of the empirical data shows that business complexity, as a composed factor, is a weak predictor of ERP adoption, whereas just company size turns out to be a very good one. In other words, companies seem to be disregarding ERP systems as an answer to their business complexity. Unexpectedly, SMEs disregard fin...


title: A wirelessly controlled implantable LED system for deep brain optogenetic stimulation

abstract: In recent years optogenetics has rapidly become an essential technique in neuroscience. Its temporal and spatial specificity, combined with efficacy in manipulating neuronal activity, are especially useful in studying the behavior of awake behaving animals. Conventional optogenetics, however, requires the use of lasers and optic fibers, which can place considerable restrictions on behavior. Here we combined a wirelessly controlled interface and small implantable light-emitting diode (LED) that allows flexible and precise placement of light source to illuminate any brain area. We tested this wireless LED system in vivo, in transgenic mice expressing channelrhodopsin-2 in striatonigral neurons expressing D1-like dopamine receptors. In all mice tested, we were able to elicit movements reliably. The frequency of twitches induced by high power stimulation is proportional to the frequency of stimulation. At lower power, contraversive turning was observed. Moreover, the implanted LED remains effective over 50 days after surgery, demonstrating the long-term stability of the light source. Our results show that the wireless LED system can be used to manipulate neural activity chronically in behaving mice without impeding natural movements.


title: A Distributed Operating System Network Stack and Device Driver for Multicores

abstract: With the advances in network speeds a single processor cannot cope anymore with the growing number of data streams from a single network card. Multicore processors come at a rescue but traditional SMP OSes, which integrate the software network stack, scale only to a certain extent,limiting an application's ability to serve more connections while increasing the number of cores. On the other hand, kernel bypass solutions seem to scale better, but limit resource flexibility and control. We propose attacking these problems with a distributed OS design, using multiple network stacks (one per kernel) and relying on multi-queue hardware and hardware flow steering. This creates a single-socket abstraction among kernels while minimizing inter-core communication. We introduce our design, consisting of a distributed network stack, a distributed device driver, and a load-balancing algorithm. We compare our prototype, NetPopcorn, with Linux, Affinity Accept, FastSocket. NetPopcorn accepts between 5 to 8 times more connections and reduces the tail latency compared to these competitors. We also compare NetPopcorn with mTCP and observe that for high core counts, mTCP accepts only 18% more connections yet with higher tail latency than NetPopcorn.


title: Feature Selection by Maximizing Independent Classification Information

abstract: Feature selection approaches based on mutual information can be roughly categorized into two groups. The first group minimizes the redundancy of features between each other. The second group maximizes the new classification information of features providing for the selected subset. A critical issue is that large new information does not signify little redundancy, and vice versa. Features with large new information but with high redundancy may be selected by the second group, and features with low redundancy but with little relevance with classes may be highly scored by the first group. Existing approaches fail to balance the importance of both terms. As such, a new information term denoted as Independent Classification Information is proposed in this paper. It assembles the newly provided information and the preserved information negatively correlated with the redundant information. Redundancy and new information are properly unified and equally treated in the new term. This strategy helps find the predictive features providing large new information and little redundancy. Moreover, independent classification information is proved as a loose upper bound of the total classification information of feature subset. Its maximization is conducive to achieve a high global discriminative performance. Comprehensive experiments demonstrate the effectiveness of the new approach.


title: Reinforcement learning based visual attention with application to face detection

abstract: Visual attention is the cognitive process of directing our gaze on one aspect of the visual field while ignoring others. The mainstream approach to modeling focal visual attention involves identifying saliencies in the image and applying a search process to the salient regions. However, such inference schemes commonly fail to accurately capture perceptual attractors, require massive computational effort and, generally speaking, are not biologically plausible. This paper introduces a novel approach to the problem of visual search by framing it as an adaptive learning process. In particular, we devise an approximate optimal control framework, based on reinforcement learning, for actively searching a visual field. We apply the method to the problem of face detection and demonstrate that the technique is both accurate and scalable. Moreover, the foundations proposed here pave the way for extending the approach to other large-scale visual perception problems.


title: Understanding Probabilistic Sparse Gaussian Process Approximations

abstract: Good sparse approximations are essential for practical inference in Gaussian Processes as the computational cost of exact methods is prohibitive for large datasets. The Fully Independent Training Conditional (FITC) and the Variational Free Energy (VFE) approximations are two recent popular methods. Despite superficial similarities, these approximations have surprisingly different theoretical properties and behave differently in practice. We thoroughly investigate the two methods for regression both analytically and through illustrative examples, and draw conclusions to guide practical application.


Articulate 2 : Toward a Conversational Interface for Visual Data Exploration


title: Zero-Current Switching Switched-Capacitor Zero-Voltage-Gap Automatic Equalization System for Series Battery String

abstract: The series battery string or supercapacitor string automatic equalization system based on quasi-resonant switched-capacitor converter is presented in this paper. It realizes the zero-voltage gap between cells and allows maximum energy recovery in a series battery system or supercapacitor system. It not only inherits the advantage of conventional switched-capacitor battery cell balancing system, but also overcomes the drawback of conduction loss, switching loss, and finite voltage difference among battery cells. All switches are MOSFET and controlled by just a pair of complementary signals in synchronous trigger pattern and the resonant tanks operate alternatively between the two states of charging and discharging. Zero-current switching and zero-voltage gap are achieved in this paper. Different resonant tank designs can meet the needs of different balancing time to meet the needs of different energy storage devices. Experimental results indicate that the efficiency of the system is high exceeding 98%. The system is very suitable for balancing used in battery management system.


title: A Survey of Trust in Computer Science and the Semantic Web

abstract: Trust is an integral component in many kinds of human interaction, allowing people to act under uncertainty and with the risk of negative consequences. For example, exchanging money for a service, giving access to your property, and choosing between conflicting sources of information all may utilize some form of trust. In computer science, trust is a widely used term whose definition differs among researchers and application areas. Trust is an essential component of the vision for the Semantic Web, where both new problems and new applications of trust are being studied. This paper gives an overview of existing trust research in computer science and the Semantic Web.


title: Experimental validation of circuit models for bulk current injection (BCI) test on shielded coaxial cables

abstract: In order to validate, by means of measurement, some existing equivalent circuit models for the bulk current injection (BCI) test, a procedure is proposed to develop a proper circuit model for the injection clamp and the obtained circuit is introduced into the global one representing the overall cable. A suitable experimental set-up has been built and used. The measured induced voltages at the terminations of shielded coaxial cables are compared with those computed by the equivalent circuit. Upper and lower bounds are quantified in order to assess the order of accuracy of the predicted results.


Analog Module Architecture for Space-Qualified Field-Programmable Mixed-Signal Arrays,” http://bach.ece.jhu.edu/~tim/research/fpaa/mapld/mapld.html


title: From a Competition for Self-Driving Miniature Cars to a Standardized Experimental Platform: Concept, Models, Architecture, and Evaluation

abstract: Context: Competitions for self-driving cars facilitated the development and research in the domain of autonomous vehicles towards potential solutions for the future mobility. ::: Objective: Miniature vehicles can bridge the gap between simulation-based evaluations of algorithms relying on simplified models, and those time-consuming vehicle tests on real-scale proving grounds. ::: Method: This article combines findings from a systematic literature review, an in-depth analysis of results and technical concepts from contestants in a competition for self-driving miniature cars, and experiences of participating in the 2013 competition for self-driving cars. ::: Results: A simulation-based development platform for real-scale vehicles has been adapted to support the development of a self-driving miniature car. Furthermore, a standardized platform was designed and realized to enable research and experiments in the context of future mobility solutions. ::: Conclusion: A clear separation between algorithm conceptualization and validation in a model-based simulation environment enabled efficient and riskless experiments and validation. The design of a reusable, low-cost, and energy-efficient hardware architecture utilizing a standardized software/hardware interface enables experiments, which would otherwise require resources like a large real-scale test track.


A Customizable Editor for Text Simplification


title: Neural Network vs. Linear Models for Stock Market Sectors Forecasting

abstract: The majority of work on forecasting the stock market has focused on individual stocks or stock indexes. In this study we consider the problem of forecasting stock sectors (or industries). We have found no study that considers this problem. Stock sectors are indexes that group several stocks covering a specific sector in the economy, for example the banking sector, the retail sector, etc. It is important for investment allocation purposes to know where each sector is going. In this study we apply linear models, such as Box-Jenkins methodology and multiple regression, as well as neural networks on the sector forecasting problem. As it turns out neural networks yielded the best forecasting performance.


title: Robust SIMD: Dynamically Adapted SIMD Width and Multi-Threading Depth

abstract: Architectures that aggressively exploit SIMD often have many data paths execute in lockstep and use multi-threading to hide latency. They can yield high through-put in terms of area- and energy-efficiency for many data-parallel applications. To balance productivity and performance, many recent SIMD organizations incorporate implicit cache hierarchies. Examples of such architectures include Intel's MIC, AMD's Fusion, and NVIDIA's Fermi. However, unlike software-managed streaming memories used in conventional graphics processors (GPUs), hardware-managed caches are more disruptive to SIMD execution, therefore the interaction between implicit caching and aggressive SIMD execution may no longer follow the conventional wisdom gained from streaming memories. We show that due to more frequent memory latency divergence, lower latency in non-L1 data accesses, and relatively unpredictable L1 contention, cache hierarchies favor different SIMD widths and multi-threading depths than streaming memories. In fact, because the above effects are subject to runtime dynamics, a fixed combination of SIMD width and multi-threading depth no longer works ubiquitously across diverse applications or when cache capacities are reduced due to pollution or power saving. To address the above issues and reduce design risks, this paper proposes Robust SIMD, which provides wide SIMD and then dynamically adjusts SIMD width and multi-threading depth according to performance feedback. Robust SIMD can trade wider SIMD for deeper multi-threading by splitting a wider SIMD group into multiple narrower SIMD groups. Compared to the performance generated by running every benchmark on its individually preferred SIMD organization, the same Robust SIMD organization performs similarly -- sometimes even better due to phase adaptation -- and out per-forms the best fixed SIMD organization by 17%. When D-cache capacity is reduced due to runtime disruptiveness, Robust SIMD offers graceful performance degradation, with 25% polluted cache lines in a 32 KB D-cache, Robust SIMD performs 1.4× better compared to a conventional SIMD architecture.


title: Graph nodes clustering based on the commute-time kernel

abstract: This work presents a kernel method for clustering the nodes of a weighted, undirected, graph. The algorithm is based on a two-step procedure. First, the sigmoid commute-time kernel (KCT), providing a similarity measure between any couple of nodes by taking the indirect links into account, is computed from the adjacency matrix of the graph. Then, the nodes of the graph are clustered by performing a kernel kmeans or fuzzy k-means on this CT kernel matrix. For this purpose, a new, simple, version of the kernel k-means and the kernel fuzzy k-means is introduced. The joint use of the CT kernel matrix and kernel clustering appears to be quite successful. Indeed, it provides good results on a document clustering problem involving the newsgroups database.


title: Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions

abstract: Big data has potential to unlock novel groundbreaking opportunities in power grid that enhances a multitude of technical, social, and economic gains. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data. In particular, computational complexity, data security, and operational integration of big data into power system planning and operational frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. In this context, suitable big data analytics combined with visualization can lead to better situational awareness and predictive decisions. This paper presents a comprehensive state-of-the-art review of big data analytics and its applications in power grids, and also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps and presents insights on future research directions to integrate big data analytics into power system planning and operational frameworks. Detailed information for utilities looking to apply big data analytics and insights on how utilities can enhance revenue streams and bring disruptive innovation are discussed. General guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations are also provided.


title: The Power of Personality: The Comparative Validity of Personality Traits, Socioeconomic Status, and Cognitive Ability for Predicting Important Life Outcomes.

abstract: The ability of personality traits to predict im- portant life outcomes has traditionally been questioned because of the putative small effects of personality. In this article, we compare the predictive validity of personality traits with that of socioeconomic status (SES) and cogni- tive ability to test the relative contribution of personality traits to predictions of three critical outcomes: mortality, divorce, andoccupationalattainment.Onlyevidence from prospective longitudinal studies was considered. In addi- tion, an attempt was made to limit the review to studies that controlled for important background factors. Results showed that the magnitude of the effects of personality traits on mortality, divorce, and occupational attainment wasindistinguishablefrom the effectsofSES and cognitive ability on these outcomes. These results demonstrate the influence of personality traits on important life outcomes, highlight the need to more routinely incorporate measures of personality into quality of life surveys, and encourage further research about the developmental origins of per- sonality traits and the processes by which these traits in- fluence diverse life outcomes.


title: Minimal Requirements for the Emergence of Learned Signaling

abstract: The emergence of signaling systems has been observed in numerous experimental and real-world contexts, but there is no consensus on which (if any) shared mechanisms underlie such phenomena. A number of explanatory mechanisms have been proposed within several disciplines, all of which have been instantiated as credible working models. However, they are usually framed as being mutually incompatible. Using an exemplar-based framework, we replicate these models in a minimal configuration which allows us to directly compare them. This reveals that the development of optimal signaling is driven by similar mechanisms in each model, which leads us to propose three requirements for the emergence of conventional signaling. These are the creation and transmission of referential information, a systemic bias against ambiguity, and finally some form of information loss. Considering this, we then discuss some implications for theoretical and experimental approaches to the emergence of learned communication.


title: Induction of early flowering in Cymbidium niveo-marginatum Mak in vitro

abstract: Many orchids take several years to flower. We have been able to induce early flowering in the temperate orchid Cymbidium niveo-marginatum Mak in vitro. The combined treatment of cytokinin (6-benzylaminopurine), restricted nitrogen supply with phosphorus enrichment, and root excision (pruning) induced transition of the Cymbidium shoot from a vegetative to a reproductive stage. Nearly 100% of the plants flowered within 90 days only when the combined treatment was applied. When root excision and/or 6-benzylaminopurine were omitted from the combined treatments, flower induction was significantly reduced. The auxin transport inhibitor, 2,3,5-triiodobenzoic acid prevented flowering of Cymbidium in vitro, although auxin (α-naphthaleneacetic acid) itself did not induce flowering. Gibberellic acid markedly delayed flowering in C. niveo-marginatum even when the flower-promoting treatment was applied. Paclobutrazol, an anti-gibberellin agent, totally blocked the inductive effects of either cytokinin or pruning. These observations suggest that concerted actions of auxin, cytokinin, and gibberellin, as well as nutrient concentration and putative promoting/suppressing agents, determine the timing of Cymbidium orchid transition from the vegetative to reproductive stage.


title: Beam Division Multiple Access Transmission for Massive MIMO Communications

abstract: We study multicarrier multiuser multiple-input multiple-output (MU-MIMO) systems, in which the base station employs an asymptotically large number of antennas. We analyze a fully correlated channel matrix and provide a beam domain channel model, where the channel gains are independent of sub-carriers. For this model, we first derive a closed-form upper bound on the achievable ergodic sum-rate, based on which, we develop asymptotically necessary and sufficient conditions for optimal downlink transmission that require only statistical channel state information at the transmitter. Furthermore, we propose a beam division multiple access (BDMA) transmission scheme that simultaneously serves multiple users via different beams. By selecting users within non-overlapping beams, the MU-MIMO channels can be equivalently decomposed into multiple single-user MIMO channels; this scheme significantly reduces the overhead of channel estimation, as well as, the processing complexity at transceivers. For BDMA transmission, we work out an optimal pilot design criterion to minimize the mean square error (MSE) and provide optimal pilot sequences by utilizing the Zadoff-Chu sequences. Simulations demonstrate the near-optimal performance of BDMA transmission and the advantages of the proposed pilot sequences.


title: Addressing ambiguity in multi-target tracking by hierarchical strategy

abstract: This paper presents a novel hierarchical approach for the simultaneous tracking of multiple targets in a video. We use a network flow approach to link detections in low-level and tracklets in high-level. At each step of the hierarchy, the confidence of candidates is measured by using a new scoring system, ConfRank, that considers the quality and the quantity of its neighborhood. The output of the first stage is a collection of safe tracklets and unlinked high-confidence detections. For each individual detection, we determine if it belongs to an existing or is a new tracklet. We show the effect of our framework to recover missed detections and reduce switch identity. The proposed tracker is referred to as TVOD for multi-target tracking using the visual tracker and generic object detector. We achieve competitive results with lower identity switches on several datasets comparing to state-of-the-art.


title: Clear-cut methodology for Arabic OCR and post-correction with low technical skilled annotators

abstract: This paper describes an efficient and straightforward methodology for OCR-ing and post-correcting Arabic text material on Islamic embryology collected for the COBHUNI project. As the target texts of the project include diverse diachronic stages of the Arabic language, the team of annotators for performing the OCR post-correction requires well-trained experts on language skills. While technical skills are also desirable, highly trained language experts typically lack enough technical knowledge. Furthermore, a relatively small portion of the target texts needed to be OCR-ed, as most of the material was already on some digital form. Thus, the OCR task could only require a small amount of resources in terms of time and work complexity. Both the low technical skills of the annotators and the resource constraints made it necessary for us to find an easy-to-develop and suitable workflow for performing the OCR and post-correction tasks. For the OCR phase, we chose Tesseract Open Source OCR Engine, because it achieves state-of-the-art levels of accuracy. For the post-correction phase, we decided to use the Proofread Page extension of the MediaWiki software, as it strikes a perfect balance between usability and efficiency. The post-correction task was additionally supported by the implementation of an error checker based on simple heuristics. The application of this methodology resulted in the successful and fast OCR-ing and post-correction of a corpus of 36,132 tokens.


title: 3D Face Reconstruction from Light Field Images: A Model-free Approach

abstract: Reconstructing 3D facial geometry from a single RGB image has recently instigated wide research interest. However, it is still an ill-posed problem and most methods rely on prior models hence undermining the accuracy of the recovered 3D faces. In this paper, we exploit the Epipolar Plane Images (EPI) obtained from light field cameras and learn CNN models that recover horizontal and vertical 3D facial curves from the respective horizontal and vertical EPIs. Our 3D face reconstruction network (FaceLFnet) comprises a densely connected architecture to learn accurate 3D facial curves from low resolution EPIs. To train the proposed FaceLFnets from scratch, we synthesize photo-realistic light field images from 3D facial scans. The curve by curve 3D face estimation approach allows the networks to learn from only 14K images of 80 identities, which still comprises over 11 Million EPIs/curves. The estimated facial curves are merged into a single pointcloud to which a surface is fitted to get the final 3D face. Our method is model-free, requires only a few training samples to learn FaceLFnet and can reconstruct 3D faces with high accuracy from single light field images under varying poses, expressions and lighting conditions. Comparison on the BU-3DFE and BU-4DFE datasets show that our method reduces reconstruction errors by over 20% compared to recent state of the art.


title: The information bottleneck method

abstract: We define the relevant information in a signal $x\in X$ as being the information that this signal provides about another signal $y\in \Y$. Examples include the information that face images provide about the names of the people portrayed, or the information that speech sounds provide about the words spoken. Understanding the signal $x$ requires more than just predicting $y$, it also requires specifying which features of $\X$ play a role in the prediction. We formalize this problem as that of finding a short code for $\X$ that preserves the maximum information about $\Y$. That is, we squeeze the information that $\X$ provides about $\Y$ through a `bottleneck' formed by a limited set of codewords $\tX$. This constrained optimization problem can be seen as a generalization of rate distortion theory in which the distortion measure $d(x,\x)$ emerges from the joint statistics of $\X$ and $\Y$. This approach yields an exact set of self consistent equations for the coding rules $X \to \tX$ and $\tX \to \Y$. Solutions to these equations can be found by a convergent re-estimation method that generalizes the Blahut-Arimoto algorithm. Our variational principle provides a surprisingly rich framework for discussing a variety of problems in signal processing and learning, as will be described in detail elsewhere.


title: A Logic-Based Theory of Deductive Arguments

abstract: Abstract We explore a framework for argumentation (based on classical logic) in which an argument is a pair where the first item in the pair is a minimal consistent set of formulae that proves the second item (which is a formula). We provide some basic definitions for arguments, and various kinds of counter-arguments (defeaters). This leads us to the definition of canonical undercuts which we argue are the only defeaters that we need to take into account. We then motivate and formalise the notion of argument trees and argument structures which provide a way of exhaustively collating arguments and counter-arguments. We use argument structures as the basis of our general proposal for argument aggregation. There are a number of frameworks for modelling argumentation in logic. They incorporate formal representation of individual arguments and techniques for comparing conflicting arguments. In these frameworks, if there are a number of arguments for and against a particular conclusion, an aggregation function determines whether the conclusion is taken to hold. We propose a generalisation of these frameworks. In particular, our new framework makes it possible to define aggregation functions that are sensitive to the number of arguments for or against. We compare our framework with a number of other types of argument systems, and finally discuss an application in reasoning with structured news reports.


title: Two supervised learning approaches for name disambiguation in author citations

abstract: Due to name abbreviations, identical names, name misspellings, and pseudonyms in publications or bibliographies (citations), an author may have multiple names and multiple authors may share the same name. Such name ambiguity affects the performance of document retrieval, Web search, database integration, and may cause improper attribution to authors. We investigate two supervised learning approaches to disambiguate authors in the citations. One approach uses the naive Bayes probability model, a generative model; the other uses support vector machines (SVMs) [V. Vapnik (1995)] and the vector space representation of citations, a discriminative model. Both approaches utilize three types of citation attributes: coauthor names, the title of the paper, and the title of the journal or proceeding. We illustrate these two approaches on two types of data, one collected from the Web, mainly publication lists from homepages, the other collected from the DBLP citation databases.


title: Electronic popables: exploring paper-based computing through an interactive pop-up book

abstract: We have developed an interactive pop-up book called Electronic Popables to explore paper-based computing. Our book integrates traditional pop-up mechanisms with thin, flexible, paper-based electronics and the result is an artifact that looks and functions much like an ordinary pop-up, but has added elements of dynamic interactivity. This paper introduces the book and, through it, a library of paper-based sensors and a suite of paper-electronics construction techniques. We also reflect on the unique and under-explored opportunities that arise from combining material experimentation, artistic design, and engineering.


title: A Survey of Resource Management in Multi-Tier Web Applications

abstract: Web applications are mostly designed with multiple tiers for flexibility and software reusability. It is difficult to model the behavior of multi-tier Web applications due to the fact that the workload is dynamic and unpredictable and the resource demand in each tier is different. Those features also cause the task of resource allocation for multi-tier Web applications very challenging. In order to meet service level agreements (SLAs) with minimal resource costs, Web service providers should dynamically allocate appropriate resources to each tier. This is particularly important to minimize the monetary cost in the pay-as-you-go cloud computing environments. Recently, a number of rule and model based approaches have been proposed for resource provisioning in cloud computing. In this survey, we identify challenges of the resource allocation problem and conduct a comparative review on those rule and model based approaches for resource allocation in multi-tier Web sites. Given the analysis on their advantages and limitations, we outline research directions to further improve the effectiveness of resource management in multi-tier Web applications.


title: Diversity and Distribution of Heavy Metal-Resistant Bacteria in Polluted Sediments of the Araça Bay, São Sebastião (SP), and the Relationship Between Heavy Metals and Organic Matter Concentrations

abstract: Heavy metals influence the population size, diversity, and metabolic activity of bacteria. In turn, bacteria can develop heavy metal resistance mechanisms, and this can be used in bioremediation of contaminated areas. The purpose of the present study was to understand how heavy metals concentration influence on diversity and distribution of heavy metal-resistant bacteria in Araça Bay, São Sebastião, on the São Paulo coast of Brazil. The hypothesis is that activities that contribute for heavy metal disposal and the increase of metals concentrations in environment can influence in density, diversity, and distribution of heavy metal-resistant bacteria. Only 12 % of the isolated bacteria were sensitive to all of the metals tested. We observed that the highest percentage of resistant strains were in areas closest to the São Sebastião channel, where port activity occurs and have bigger heavy metals concentrations. Bacterial isolated were most resistant to Cr, followed by Zn, Cd, and Cu. Few strains resisted to Cd levels greater than 200 mg L(-1). In respect to Cr, 36 % of the strains were able to grow in the presence of as much as 3200 mg L(-1). Few strains were able to grow at concentrations of Zn and Cu as high as 1600 mg L(-1), and none grew at the highest concentration of 3200 mg L(-1). Bacillus sp. was most frequently isolated and may be the dominant genus in heavy metal-polluted areas. Staphylococcus sp., Planococcus maritimus, and Vibrio aginolyticus were also isolated, suggesting their potential in bioremediation of contaminated sites.


Italian VerbNet: A Construction-based Approach to Italian Verb Classification


title: Game User Experience Evaluation

abstract: In a nutshell: This course comprehensively covers important user experience (UX) evaluation methods as well as opportunities and challenges of UX evaluation in the area of entertainment and games. The course is an ideal forum for attendees to gain insight into state-of-the art user experience evaluation methods going way-beyond standard usability and user experience evaluation approaches in the area of human-computer interaction. It surveys and assesses the efforts of user experience evaluation of the gaming and human computer interaction communities during the last 15 years.