title: Working with the television on: an investigation into media multitasking

abstract: Many people can now bring the office home in the evening and work on a laptop computer while watching television. We conducted a lab-study to investigate the impact that this media multitasking habit has on stress and our ability to stay engaged with the content of a television show. Participants were required to complete a stressful mental arithmetic task, designed to simulate a demanding work-related activity, while watching a segment of a television documentary. To reflect the different ways that people can media multitask, participants were asked either to perform the work task continuously (concurrent multitasking), or during bursts (sequential multitasking). Results show that working on the stressful task was stressful ' it did not matter whether the television was on or not, nor did it matter how the tasks were interleaved. There was some evidence that sequentially interleaving tasks allowed participants to maintain their engagement with the television show. Overall though the results of this preliminary study suggest that if people want to relax and become engrossed in a television show they should avoid working on a secondary device at the same time.


title: 3D TSV system in package (SiP) for aerospace applications

abstract: In the frame of its future needs for aerospace market, Sagem has designed a 3D electronic function based on a TSV silicon interposer from IPDiA. This paper deals with motivations and technologies retained to give Sagem opportunities to integrate "downscaling features" in future aerospace equipment's electronic. Saving space and weight are critical objectives for aerospace equipment's due to nowadays fast growing energy prices. On each project we are involved on, we need to have in mind that each extra kilogram coming from our equipment is a direct loss in term of revenues for our customers. However, increasing power density in such a way needs to be carefully done, managing also thermal and cost aspects. In this way a silicon TSV interposer was chosen to design and manufacture a system in package for aeronautic applications. This paper will describe all aspects of the SiP project that involved designers in the frame of aerospace applications. Second part will describe SiP technology and how we plan to test and use this component on electronic boards.


title: Lyapunov Design for Safe Reinforcement Learning Control

abstract: We propose a general approach to safe reinforcement learning control based on Lyapunov design methods. In our approach, a Lyapunov function—a special form of domain knowledge—is used to formulate the action choices available to a reinforcement learning agent. A learning agent choosing among these actions provably enjoys performance guarantees, and satisfies safety constraints of various kinds. We demonstrate the general approach by applying it to several illustrative pendulum control problems.


title: The learning curve in head and neck reconstruction with microvascular free flaps: a retrospective review

abstract: Abstract Background: Tissue defect around the head and neck region is a great challenge for reconstructive surgeons. Successful outcomes of surgery is influenced by many factors such as surgical technique in recipient and donor site, meticulous microvascular anastomosis, position of vascular pedicle, and post-surgery monitoring. The learning curve is important for any new microvascular surgeons. Objectives: Evaluate the quality of training for a new otolaryngologist, head and neck surgeon, on their performance of free flaps in facial plastic and reconstructive surgery using a retrospective review. Methods: Nineteen microvascular free flaps in patients from the ENT Center of Rajavithi Hospital were reviewed between November 2008 and October 2009. Incidences of free flap survival, and partial and complete necrosis were examined. Results: Eighteen patients with microvascular free flaps had head and neck cancer. 88.9% of the patients had squamous cell carcinoma. There were nine radial forearm free flaps, five anterolateral thigh free flaps, two rectus abdominis free flap, two iliac-free flap, and one fibular-free flap. The overall success rate of the free flap reconstructions was 84%. One partial and three total necrosis were done on the 19 flaps. Conclusion: Causes of free flap failure were similar and not dependent on the experienced of the surgeons. The postgraduate training program in facial plastic and reconstructive surgery is effective in providing new microvascular surgeons the skills to perform successful microvascular and reconstructive surgeries.


title: Shape Analysis Using the Auto Diffusion Function

abstract: Scalar functions defined on manifold triangle meshes is a starting point for many geometry processing algorithms such as mesh parametrization, skeletonization, and segmentation. In this paper, we propose the Auto Diffusion Function (ADF) which is a linear combination of the eigenfunctions of the Laplace-Beltrami operator in a way that has a simple physical interpretation. The ADF of a given 3D object has a number of further desirable properties: Its extrema are generally at the tips of features of a given object, its gradients and level sets follow or encircle features, respectively, it is controlled by a single parameter which can be interpreted as feature scale, and, finally, the ADF is invariant to rigid and isometric deformations. ::: ::: We describe the ADF and its properties in detail and compare it to other choices of scalar functions on manifolds. As an example of an application, we present a pose invariant, hierarchical skeletonization and segmentation algorithm which makes direct use of the ADF.


title: Dodona: automated oracle data set selection

abstract: Software complexity has increased the need for automated software testing. Most research on automating testing, however, has focused on creating test input data. While careful selection of input data is necessary to reach faulty states in a system under test, test oracles are needed to actually detect failures. In this work, we describe Dodona, a system that supports the generation of test oracles. Dodona ranks program variables based on the interactions and dependencies observed between them during program execution. Using this ranking, Dodona proposes a set of variables to be monitored, that can be used by engineers to construct assertion-based oracles. Our empirical study of Dodona reveals that it is more effective and efficient than the current state-of-the-art approach for generating oracle data sets, and can often yield oracles that are almost as effective as oracles hand-crafted by engineers without support.


title: Critical Infrastructure Protection: having SIEM technology cope with network heterogeneity

abstract: Coordinated and targeted cyber-attacks to Critical Infrastructures (CIs) are becoming more and more frequent and sophisticated. This is due to: i) the recent technology shift towards Commercial Off-The-Shelf (COTS) products, and ii) new economical and socio-political motivations. In this paper, we discuss some of the most relevant security issues resulting from the adoption in CIs of heterogeneous network infrastructures (specifically combining wireless and IP trunks), and suggest techniques to detect, as well as to counter/mitigate attacks. We claim that techniques such as those we propose here should be integrated in future SIEM (Security Information and Event Management) solutions, and we discuss how we have done so in the EC-funded MASSIF project, with respect to a real-world CI scenario, specifically a distributed system for power grid monitoring.


title: M.: Object Constraint Language (OCL): A Definitive Guide

abstract: The Object Constraint Language (OCL) started as a complement of the UML notation with the goal to overcome the limitations of UML (and in general, any graphical notation) in terms of precisely specifying detailed aspects of a system design. Since then, OCL has become a key component of any model-driven engineering (MDE) technique as the default language for expressing all kinds of (meta)model query, manipulation and specification requirements. Among many other applications, OCL is frequently used to express model transformations (as part of the source and target patterns of transformation rules), well-formedness rules (as part of the definition of new domain-specific languages), or code-generation templates (as a way to express the generation patterns and rules). ::: ::: This chapter pretends to provide a comprehensive view of this language, its many applications and available tool support as well as the latest research developments and open challenges around it.


title: CCSP: A compressed certificate status protocol

abstract: Trust in SSL-based communications is provided by Certificate Authorities (CAs) in the form of signed certificates. Checking the validity of a certificate involves three steps: (i) checking its expiration date, (ii) verifying its signature, and (iii) ensuring that it is not revoked. Currently, such certificate revocation checks are done either via Certificate Revocation Lists (CRLs) or Online Certificate Status Protocol (OCSP) servers. Unfortunately, despite the existence of these revocation checks, sophisticated cyber-attackers, may trick web browsers to trust a revoked certificate, believing that it is still valid. Consequently, the web browser will communicate (over TLS) with web servers controlled by cyber-attackers. Although frequently updated, nonced, and timestamped certificates may reduce the frequency and impact of such cyber-attacks, they impose a very large overhead to the CAs and OCSP servers, which now need to timestamp and sign on a regular basis all the responses, for every certificate they have issued, resulting in a very high overhead. To mitigate this overhead and provide a solution to the described cyber-attacks, we present CCSP: a new approach to provide timely information regarding the status of certificates, which capitalizes on a newly introduced notion called signed collections. In this paper, we present the design, preliminary implementation, and evaluation of CCSP in general, and signed collections in particular. Our preliminary results suggest that CCSP (i) reduces space requirements by more than an order of magnitude, (ii) lowers the number of signatures required by 6 orders of magnitude compared to OCSP-based methods, and (iii) adds only a few milliseconds of overhead in the overall user latency.


title: Compact Ultra-Wideband (UWB) Bandpass Filter With Ultra-Narrow Dual- and Quad-Notched Bands

abstract: In this paper, compact ultra-wideband (UWB) bandpass filters with ultra-narrow dual- and quad-notched bands are proposed using the broadside-coupled microstrip/coplanar waveguide (CPW) structure. The multiple-modes UWB operation is obtained through the CPW detached-mode resonator (DMR) and broadside-coupled microstrip/CPW transition. To avoid the existing interferences such as the wireless local-area network signals (i.e., 5.2- and 5.8-GHz bands) in the UWB passband simultaneously, dual-notched bands can be finely employed and independently adjusted by the embedded quarter-wavelength (λ/4) CPW resonators and the λ/4 meander slot-line inserted in the DMR, respectively. To further cancel the interferences from the 3.5-GHz worldwide interoperability for microwave access and 6.8-GHz RF identification communication, the λ/4 meander defected microstrip structure is employed. Based on the structures mentioned above, a series of UWB bandpass filters with dual- and quad-notched bands are then designed and fabricated. With good passband/stopband performances, compact size, and low cost, the proposed filters are attractive for the practical applications.


title: Deadbeat Dissipative FIR Filtering

abstract: In this paper, we propose a new deadbeat dissipative filter with a finite impulse response (FIR) structure for linear discrete-time systems with external disturbance; this filter is called a deadbeat dissipative FIR filter (DDFF). The new filter ensures $(Q,S,R)\text{--}\alpha$ -dissipativity and the deadbeat property based on three slack matrix variables. By tuning the weighting parameters provided by the $(Q,S,R)\text{--}\alpha$ -dissipativity in the proposed DDFF, we present $H_{\infty}$ and passive FIR filters in a unified framework and investigate ways of improving the $l_{2}$ stability, bounded-disturbance bounded-error stability, and robustness of FIR filters. The gain matrix of the proposed DDFF is obtained by solving a convex problem using the linear matrix inequality approach. Two numerical examples are provided to demonstrate the effectiveness and advantages of the obtained theoretical results.


title: Stealthy malware detection through vmm-based "out-of-the-box" semantic view reconstruction

abstract: An alarming trend in malware attacks is that they are armed with stealthy techniques to detect, evade, and subvert malware detection facilities of the victim. On the defensive side, a fundamental limitation of traditional host-based anti-malware systems is that they run inside the very hosts they are protecting ("in the box"), making them vulnerable to counter-detection and subversion by malware. To address this limitation, recent solutions based on virtual machine (VM) technologies advocate placing the malware detection facilities outside of the protected VM ("out of the box"). However, they gain tamper resistance at the cost of losing the native, semantic view of the host which is enjoyed by the "in the box" approach, thus leading to a technical challenge known as the semantic gap. In this paper, we present the design, implementation, and evaluation of VMwatcher - an "out-of-the-box" approach that overcomes the semantic gap challenge. A new technique called guest view casting is developed to systematically reconstruct internal semantic views (e.g., files, processes, and kernel modules) of a VM from the outside in a non-intrusive manner. Specifically, the new technique casts semantic definitions of guest OS data structures and functions on virtual machine monitor (VMM)-level VM states, so that the semantic view can be reconstructed. With the semantic gap bridged, we identify two unique malware detection capabilities: (1) view comparison-based malware detection and its demonstration in rootkit detection and (2) "out-of-the-box" deployment of host-based anti-malware software with improved detection accuracy and tamper-resistance. We have implemented a proof-of-concept prototype on both Linux and Windows platforms and our experimental results with real-world malware, including elusive kernel-level rootkits, demonstrate its practicality and effectiveness.


title: Through the eye of the PLC: semantic security monitoring for industrial processes

abstract: Off-the-shelf intrusion detection systems prove an ill fit for protecting industrial control systems, as they do not take their process semantics into account. Specifically, current systems fail to detect recent process control attacks that manifest as unauthorized changes to the configuration of a plant's programmable logic controllers (PLCs). In this work we present a detector that continuously tracks updates to corresponding process variables to then derive variable-specific prediction models as the basis for assessing future activity. Taking a specification-agnostic approach, we passively monitor plant activity by extracting variable updates from the devices' network communication. We evaluate the capabilities of our detection approach with traffic recorded at two operational water treatment plants serving a total of about one million people in two urban areas. We show that the proposed approach can detect direct attacks on process control, and we further explore its potential to identify more sophisticated indirect attacks on field device measurements as well.


title: High Performance Ka-Band VPIN Limiters

abstract: The purpose of this paper is to demonstrate the successful design of passive high power multi-stage limiters operating from 33 to 36 GHz using a high-yielding GaAs Vertical PIN diode process. Measured CW data shows that a two stage design achieves less than 0.5 dB insertion loss while achieving a flat leakage of about 21 dBm. A three stage design achieves 0.8 dB small signal insertion loss and 19 dBm flat leakage. A key to achieving the performance was the accurate large signal modeling of the PIN diodes.


title: Research on instructional design model for VR supported skill training

abstract: Virtual reality, with support of high interactivity, can present a virtual environment that resembles the real world. Its application in training opens new opportunities for effectively training workers with low cost and fewer hazards, and has been used in business training widely. An appropriate instructional design model that guides the development of a VR supported training environment is imperative because it is the instructional implementation of the technology that determines training outcomes. On the ground of psychological theories of skill acquisition, taking VR features into account and making reference to other ID models, this paper proposes an ID model for VR supported skill training. Overall, this model is divided into five phases: analysis, design, development, implementation, evaluation. Here, more attention will be paid on phases of analysis, design and evaluation. Further research is needed to testify the effectiveness of this model.


title: The Knowledge Accelerator: Big Picture Thinking in Small Pieces

abstract: Crowdsourcing offers a powerful new paradigm for online work. However, real world tasks are often interdependent, requiring a big picture view of the difference pieces involved. Existing crowdsourcing approaches that support such tasks -- ranging from Wikipedia to flash teams -- are bottlenecked by relying on a small number of individuals to maintain the big picture. In this paper, we explore the idea that a computational system can scaffold an emerging interdependent, big picture view entirely through the small contributions of individuals, each of whom sees only a part of the whole. To investigate the viability, strengths, and weaknesses of this approach we instantiate the idea in a prototype system for accomplishing distributed information synthesis and evaluate its output across a variety of topics. We also contribute a set of design patterns that may be informative for other systems aimed at supporting big picture thinking in small pieces.


MIT-MEDG at SemEval-2018 Task 7: Semantic Relation Classification via Convolution Neural Network


title: A single sensor based PFC Zeta converter Fed BLDC motor drive for fan applications

abstract: A novel PFC (Power Factor Corrected) Converter using Zeta DC-DC converter feeding a BLDC (Brush Less DC) motor drive using a single voltage sensor is proposed for fan applications. A single phase supply followed by an uncontrolled bridge rectifier and a Zeta DC-DC converter is used to control the voltage of a DC link capacitor which is lying between the Zeta converter and a VSI (Voltage Source Inverter). Voltage of a DC link capacitor of Zeta converter is controlled to achieve the speed control of BLDC motor. The Zeta converter is working as a front end converter operating in DICM (Discontinuous Inductor Current Mode) and thus using a voltage follower approach. The DC link capacitor of the Zeta converter is followed by a VSI which is feeding a BLDC motor. A sensorless control of BLDC motor is used to eliminate the requirement of Hall Effect position sensors. A MATLAB/ Simulink environment is used to simulate the developed model to achieve a wide range of speed control with high PF (power Factor) and improved PQ (Power Quality) at the supply.


3D user interface design


Towards Automatic Identification of Fake News : Headline-Article Stance Detection with LSTM Attention Models


title: Deep learning approach for Fourier ptychography microscopy.

abstract: Convolutional neural networks (CNNs) have gained tremendous success in solving complex inverse problems. The aim of this work is to develop a novel CNN framework to reconstruct video sequences of dynamic live cells captured using a computational microscopy technique, Fourier ptychographic microscopy (FPM). The unique feature of the FPM is its capability to reconstruct images with both wide field-of-view (FOV) and high resolution, i.e. a large space-bandwidth-product (SBP), by taking a series of low resolution intensity images. For live cell imaging, a single FPM frame contains thousands of cell samples with different morphological features. Our idea is to fully exploit the statistical information provided by these large spatial ensembles so as to make predictions in a sequential measurement, without using any additional temporal dataset. Specifically, we show that it is possible to reconstruct high-SBP dynamic cell videos by a CNN trained only on the first FPM dataset captured at the beginning of a time-series experiment. Our CNN approach reconstructs a 12800×10800 pixel phase image using only ∼25 seconds, a 50× speedup compared to the model-based FPM algorithm. In addition, the CNN further reduces the required number of images in each time frame by ∼ 6×. Overall, this significantly improves the imaging throughput by reducing both the acquisition and computational times. The proposed CNN is based on the conditional generative adversarial network (cGAN) framework. We further propose a mixed loss function that combines the standard image domain loss and a weighted Fourier domain loss, which leads to improved reconstruction of the high frequency information. Additionally, we also exploit transfer learning so that our pre-trained CNN can be further optimized to image other cell types. Our technique demonstrates a promising deep learning approach to continuously monitor large live-cell populations over an extended time and gather useful spatial and temporal information with sub-cellular resolution.


title: Coping with child sexual abuse among college students and post-traumatic stress disorder: The role of continuity of abuse and relationship with the perpetrator

abstract: Objective: The purpose of this study was to examine the effects of child sexual abuse (CSA) on the use of coping strategies and post-traumatic stress disorder (PTSD) scores in young adults, as well as the role of avoidance and approach coping strategies in those PTSD scores in CSA victims. The role of coping strategies was studied by considering their possible interactive effect with the continuity of abuse and the relationship with the perpetrator; the effect of coping strategies on PTSD was also compared between CSA victim and non-CSA victim participants. Method: The sample was comprised of 138 victims of CSA and another 138 participants selected as a comparison group. Data about child sexual abuse were obtained from a questionnaire developed for this purpose. Coping strategies were assessed with the How I Deal with Things Scale (Burt & Katz, 1987), while PTSD scores were assessed with the “Escala de Gravedad de Sintomas del Trastorno de Estres Postraumatico” (Severity of Symptoms of PTSD Scale; Echeburua et al., 1997). Results: Participants who had been victims of CSA showed significantly higher PTSD scores and lower approach coping strategies scores. However, differences in avoidance coping strategies between groups were not consistent and did not always follow the expected direction. Only the use of avoidance coping strategies was related to PTSD, participants who used these showing higher scores. The effects of avoidance strategies were stronger in continued than in isolated abuse, in intrafamilial than in extrafamilial abuse and in CSA victims than in non-victims. Conclusions: These results confirm the idea of CSA as a high-risk experience that can affect the victim’s coping strategies and lead to PTSD to a lesser or greater extent depending on the coping strategy used. Moreover, the role of these strategies varies depending on whether or not the participant is a victim of CSA and on the characteristics of abuse (continuity and relationship with the perpetrator). Practice implications: In terms of intervention, a reduction of avoidance-type strategies appears to have a beneficial effect, especially in the case of intrafamilial and/or continued CSA victims. The encouragement of “spontaneous” approach strategies (devised by the victim herself, without counseling) would probably not lead to more positive outcomes in terms of PTSD symptomatology. However, encouraging CSA survivors to engage in therapy aimed at developing effective approach strategies, as other studies have suggested, may


title: OpenML: networked science in machine learning

abstract: Many sciences have made significant breakthroughs by adopting online tools that help organize, structure and mine information that is too detailed to be printed in journals. In this paper, we introduce OpenML, a place for machine learning researchers to share and organize data in fine detail, so that they can work more effectively, be more visible, and collaborate with others to tackle harder problems. We discuss how OpenML relates to other examples of networked science and what benefits it brings for machine learning research, individual scientists, as well as students and practitioners.


title: Towards Adjusting Mobile Devices to User's Behaviour

abstract: Mobile devices are a special class of resource-constrained embedded devices. Computing power, memory, the available energy, and network bandwidth are often severely limited. These constrained resources require extensive optimization of a mobile system compared to larger systems. Any needless operation has to be avoided. Timeconsuming operations have to be started early on. For instance, loading files ideally starts before the user wants to access the file. So-called prefetching strategies optimize system's operation. Our goal is to adjust such strategies on the basis of logged system data. Optimization is then achieved by predicting an application's behavior based on facts learned from earlier runs on the same system. In this paper, we analyze system-calls on operating system level and compare two paradigms, namely server-based and device-based learning. The results could be used to optimize the runtime behaviour of mobile devices.


title: RECOGNITION OF PARTIALLY OCCLUDED PLANT LEAVES USING A MODIFIED WATERSHED ALGORITHM

abstract: Occlusion is an obstacle to two-dimensional machine vision recognition of plants in natural outdoor scenes. Five ::: modifications to the Watershed algorithm were investigated for separating occluded plant leaves, in an attempt to reduce the ::: excessive object fragmentation associated with the original Watershed algorithm. The best modified algorithm improved the ::: recognition of occluded tomato cotyledons and tomato true leaves improved by a factor of 3 and 2, respectively, after it was ::: applied to occluded plant leaves in natural outdoor scenes. Two of the modified Watershed algorithms required about 11% ::: less computation time than the original.


title: Two-Dimensional Scanning Antenna Array Driven by Integrated Waveguide Phase Shifter

abstract: A Butler matrix-fed two-dimensional (2-D) scan linearly polarized 2 × 2 microstrip ring antenna array (MRAA) is proposed and validated in low-cost substrate integrated waveguide (SIW) technology for Ka-band applications. The highly efficient, compact, and passive beam forming network (BFN) consists of SIW cruciform couplers as coupling unit, and its special topology is well adapted for feeding planar arrays. The wideband and high radiation efficiency antenna elements are aperture-coupled through slots etched on the top of a high permittivity SIW feed substrate. Such four antenna elements are used to construct 2 × 2 MRAA and to form four fixed beams, one in each quadrant at an elevation angle of 20 ° from the broad side array axis. A triangular grid arrangement is chosen to avoid grating lobes in the visible space. A 50- Ω grounded coplanar waveguide (GCPW) to SIW transition is used to avoid spurious input feed radiation loss. The array is measured to exhibit 3-dB beam width of 30 ° in both of the orthogonal planes, radiation efficiency of 70% for each port, and stable radiation pattern bandwidth of 7.6% at 26.5 GHz. The physical size of the demonstrated 2 × 2 array is 2.86λo×2.86λo×0.22λo.


title: Goal Oriented Requirement Engineering: A Critical Study of Techniques

abstract: The term "Goal" is increasingly being used in Requirement Engineering. Goal-Oriented requirement engineering (GORE) provides an incremental approach for elicitation, analysis, elaboration & refinement, specification and modeling of requirements. Various Goal Oriented Requirement Engineering (GORE) methods exist for these requirement engineering processes like KAOS, GBRAM etc. GORE techniques are based on certain underlying concepts and principles. This paper presents and synthesizes the underlying concepts of GORE with respect to coverage of requirement engineering activities. The advantages of GORE claimed in the literature are presented. This paper evaluates GORE techniques on the basis of concepts, process and claimed advantages.


title: ASN: A Dynamic Barrier-Based Approach to Confirmation of Deadlocks from Warnings for Large-Scale Multithreaded Programs

abstract: Many large-scale multithreaded programs incur deadlock bugs. Existing deadlock warning detection techniques only report warning scenarios, which may or may not be real deadlocks. Each warning should be further verified on whether it may manifest into a real deadlock. For this purpose, a number of active randomized testing schedulers have been developed to trigger them, and yet pervious experiments show that their deadlock confirmation probability can be low. This paper presents ASN, a novel barrier-based randomized scheduler that triggers real deadlocks with high probabilities. We exploit the insights that in a confirmation run, the threads involved in a real deadlock should properly acquire one or more sets of locks prior to deadlocking. ASN automatically identifies three interesting sets of such positions. It guides the threads participating in a given warning to stay at these position sets in turn. When all the threads are staying at the last position set, ASN checks whether any deadlock that matches with the given warning has been triggered. We have evaluated ASN on 15 deadlock bugs in a suite of real-world multithreaded programs. The results show that ASN either confirms more deadlocks from the benchmark suite or triggers the same deadlocks with significantly higher probabilities than existing schedulers.


title: The effects of handwriting experience on functional brain development in pre-literate children

abstract: In an age of increasing technology, the possibility that typing on a keyboard will replace handwriting raises questions about the future usefulness of handwriting skills. Here we present evidence that brain activation during letter perception is influenced in different, important ways by previous handwriting of letters versus previous typing or tracing of those same letters. Preliterate, five-year old children printed, typed, or traced letters and shapes, then were shown images of these stimuli while undergoing functional MRI scanning. A previously documented “reading circuit” was recruited during letter perception only after handwriting—not after typing or tracing experience. These findings demonstrate that handwriting is important for the early recruitment in letter processing of brain regions known to underlie successful reading. Handwriting therefore may facilitate reading acquisition in young children.


Virtual Reality and Augmented Reality in Education


title: Lexical Coherence Graph Modeling Using Word Embeddings

abstract: Coherence is established by semantic connections between sentences of a text which can be modeled by lexical relations. In this paper, we introduce the lexical coherence graph (LCG), a new graph-based model to represent lexical relations among sentences. The frequency of subgraphs (coherence patterns) of this graph captures the connectivity style of sentence nodes in this graph. The coherence of a text is encoded by a vector of these frequencies. We evaluate the LCG model on the readability ranking task. The results of the experiments show that the LCG model obtains higher accuracy than state-of-the-art coherence models. Using larger subgraphs yields higher accuracy, because they capture more structural information. However, larger subgraphs can be sparse. We adapt Kneser-Ney smoothing to smooth subgraphs’ frequencies. Smoothing improves performance.


title: Linear Latent Force Models Using Gaussian Processes

abstract: Purely data-driven approaches for machine learning present difficulties when data are scarce relative to the complexity of the model or when the model is forced to extrapolate. On the other hand, purely mechanistic approaches need to identify and specify all the interactions in the problem at hand (which may not be feasible) and still leave the issue of how to parameterize the system. In this paper, we present a hybrid approach using Gaussian processes and differential equations to combine data-driven modeling with a physical model of the system. We show how different, physically inspired, kernel functions can be developed through sensible, simple, mechanistic assumptions about the underlying system. The versatility of our approach is illustrated with three case studies from motion capture, computational biology, and geostatistics.


title: Making Memristive Neural Network Accelerators Reliable

abstract: Deep neural networks (DNNs) have attracted substantial interest in recent years due to their superior performance on many classification and regression tasks as compared to other supervised learning models. DNNs often require a large amount of data movement, resulting in performance and energy overheads. One promising way to address this problem is to design an accelerator based on in-situ analog computing that leverages the fundamental electrical properties of memristive circuits to perform matrix-vector multiplication. Recent work on analog neural network accelerators has shown great potential in improving both the system performance and the energy efficiency. However, detecting and correcting the errors that occur during in-memory analog computation remains largely unexplored. The same electrical properties that provide the performance and energy improvements make these systems especially susceptible to errors, which can severely hurt the accuracy of the neural network accelerators. This paper examines a new error correction scheme for analog neural network accelerators based on arithmetic codes. The proposed scheme encodes the data through multiplication by an integer, which preserves addition operations through the distributive property. Error detection and correction are performed through a modulus operation and a correction table lookup. This basic scheme is further improved by data-aware encoding to exploit the state dependence of the errors, and by knowledge of how critical each portion of the computation is to overall system accuracy. By leveraging the observation that a physical row that contains fewer 1s is less susceptible to an error, the proposed scheme increases the effective error correction capability with less than 4.5% area and less than 4.7% energy overheads. When applied to a memristive DNN accelerator performing inference on the MNIST and ILSVRC-2012 datasets, the proposed technique reduces the respective misclassification rates by 1.5x and 1.1x.


title: Investigation on the control strategy of soft wearable robotic hand with slack enabling tendon actuator

abstract: A soft wearable robot, which is an emerging type of wearable robot, can take advantage of tendon-driven mechanisms with a Bowden cable. These tendon-driven mechanisms benefits soft wearable robots because the actuator can be remotely placed and the transmission is very compact. However, it is difficult to compensate the friction along the Bowden cable which makes it hard to control. This study proposes the use of a position-based impedance controller, which is robust to the nonlinear dynamics of the system and provides compliant interaction between robot, human, and environment. Additionally, to eliminate disturbances from unexpected tension of the antagonistic wire arising from friction, this study proposes a new type of slack enabling tendon actuator. It can eliminate friction force along the antagonistic wire by actively pushing the wire while preventing derailment of the wire from the spool.


title: Multi-view object class detection with a 3D geometric model

abstract: This paper presents a new approach for multi-view object class detection. Appearance and geometry are treated as separate learning tasks with different training data. Our approach uses a part model which discriminatively learns the object appearance with spatial pyramids from a database of real images, and encodes the 3D geometry of the object class with a generative representation built from a database of synthetic models. The geometric information is linked to the 2D training data and allows to perform an approximate 3D pose estimation for generic object classes. The pose estimation provides an efficient method to evaluate the likelihood of groups of 2D part detections with respect to a full 3D geometry model in order to disambiguate and prune 2D detections and to handle occlusions. In contrast to other methods, neither tedious manual part annotation of training images nor explicit appearance matching between synthetic and real training data is required, which results in high geometric fidelity and in increased flexibility. On the 3D Object Category datasets CAR and BICYCLE [15], the current state-of-the-art benchmark for 3D object detection, our approach outperforms previously published results for viewpoint estimation.


title: Quasi-Z-Source Inverter With a T-Type Converter in Normal and Failure Mode

abstract: This paper presents a three-phase multilevel quasi-Z-source inverter (qZSI) topology operating in normal and fault-tolerant operation mode. This structure is composed by two symmetrical quasi-Z-source networks and a three-phase T-type inverter. Besides the intrinsic advantages of multilevel voltage source inverters, the proposed structure is also characterized by their semiconductor fault tolerance capability. This feature is only obtained through changes on the modulation scheme after the semiconductor fault and does not require additional extra-phase legs or collective switching states. In certain fault types, the reduction of the output power capacity will be compensated by the boost characteristic of the qZSI. The fault-tolerant behavior of the proposed topology is demonstrated by several simulation results of the converter in normal and fault condition. To validate the characteristics of this multilevel qZSI, an experimental prototype was also built to experimentally confirm the results.


title: Depth Estimation of Video Sequences With Perceptual Losses

abstract: 3-D vision plays an important role in intelligent perception of robot, while it requires extra 3-D sensors. Depth estimation from monocular videos provides an alternative mechanism to recover the 3-D information. In this paper, we propose an unsupervised learning framework that uses the perceptual loss for depth estimation. Depth and pose networks are first trained to estimate the depth and the camera motion of the video sequence, respectively. With the estimated depth and pose of the original frame, the adjacent frame can be reconstructed. The pixel-wise differences between the constructed frame and the original frame are used as per-pixel loss. Meanwhile, reconstructed views and original views can be used to extract advanced features from a pre-trained network to define and optimize perceptual loss functions to assess the quality of reconstructions. We combine the respective advantages of these two methods and present an approach of generating a depth map by training the feed-forward network with per-pixel loss function and perceptual loss function. The experimental results show that our method can significantly improve the estimation accuracy of depth map.


title: Intelligent Gate Drive for Fast Switching and Crosstalk Suppression of SiC Devices

abstract: This paper presents an intelligent gate drive for silicon carbide (SiC) devices to fully utilize their potential of high switching-speed capability in a phase-leg configuration. Based on the SiC device's intrinsic properties, a gate assist circuit consisting of two auxiliary transistors with two diodes is introduced to actively control gate voltages and gate loop impedances of both devices in a phase-leg configuration during different switching transients. Compared to conventional gate drives, the proposed circuit has the capability of accelerating the switching speed of the phase-leg power devices and suppressing the crosstalk to below device limits. Based on Wolfspeed 1200-V SiC MOSFETs, the test results demonstrate the effectiveness of this intelligent gate drive under varying operating conditions. More importantly, the proposed intelligent gate assist circuitry is embedded into a gate drive integrated circuit, offering a simple, compact, and reliable solution for end-users to maximize benefits of SiC devices in actual power electronics applications.


Importance of Requirement Management : Requirement Engineering Concern


title: Passive Bistatic Radar and Waveform Diversity

abstract: Abstract : This tutorial describes the basis of passive bistatic radar (PBR) systems, and in particular the nature of the waveforms of illuminators of opportunity that they exploit. It shows that there is a wide variety of such waveforms, from broadcast, communications and radionavigation transmissions, and that in general they are not optimum for radar purposes. In addition, they usually vary significantly as a function of time, with the imposed modulation. It is therefore necessary to understand the effect of the waveform on the performance of the passive bistatic radar, so as to be able to choose the most appropriate illuminator, and to use the waveform in the optimal way, and it is in this sense that PBR forms a part of the subject of waveform diversity. The tutorial presents a short summary of the properties of bistatic radar, then goes on to consider the specific case of passive bistatic radar. Next, two brief sections provide a review of the radar equation for bistatic radar and of the ambiguity function for bistatic radar, before considering the properties of a variety of different waveforms that may be used for passive bistatic radar purposes and how best to exploit them. Finally, a description is given of some practical passive bistatic radar systems and examples of results.


title: Modern B-tree techniques

abstract: In summary, the core design of B-trees has remained unchanged in 40 years: balanced trees, pages or other units of I/O as nodes, efficient root-to-leaf search, splitting and merging nodes, etc. On the other hand, an enormous amount of research and development has improved every aspect of B-trees including data contents such as multi-dimensional data, access algorithms such as multi-dimensional queries, data organization within each node such as compression and cache optimization, concurrency control such as separation of latching and locking, recovery such as multi-level recovery, etc. Gray and Reuter believed in 1993 that “B-trees are by far the most important access path structure in database and file systems.” It seems that this statement remains true today. B-tree indexes are likely to gain new importance in relational databases due to the advent of flash storage. Fast access latencies permit many more random I/O operations than traditional disk storage, thus shifting the break-even point between a full-bandwidth scan and a B-tree index search, even if the scan has the benefit of columnar database storage. We hope that this tutorial of B-tree techniques will stimulate research and development of modern B-tree indexing techniques for future data management systems.


title: Simulink/ModelSim co-simulation of sensorless PMSM speed controller

abstract: Based on Simulink/Modelsim co-simulation technology, the design of a sensorless control IP (Intellectual Property) for PMSM (Permanent Magnet Synchronous Motor) drive is presented in this paper. Firstly, a mathematical model for PMSM is derived and the vector control is adopted. Secondly, a rotor flux position is estimated by using a sliding mode observer (SMO). These estimated values are feed-backed to the current loop for vector control and to the speed loop for speed control. Thirdly, the Very-High-Speed IC Hardware Description Language (VHDL) is adopted to describe the behavior of the sensorless speed control IP which includes the circuits of space vector pulse width modulation (SVPWM), coordinate transformation, SMO, fuzzy controller, etc. Fourthly, the simulation work is performed by MATLAB/Simulink and ModelSim co-simulation mode, provided by Electronic Design Automation (EDA) Simulator Link. The PMSM, inverter and speed command are performed in Simulink and the sensorless speed control IP of PMSM drive is executed in ModelSim. Finally, the co-simulation results validate the effectiveness of the sensorless PMSM speed control system.


title: Violence against transgender people: A review of United States data !

abstract: Transgender people face many challenges in a society that is unforgiving of any system of gender that is not binary. However, there are three primary sources of data in the United States for discerning the rates and types of violence that transgender people face throughout their lives — self-report surveys and needs assessments, hot-line call and social service records, and police reports. Data from each of these sources are discussed in length, as well as some of the methodological issues for these types of data sources. All three sources indicate that violence against transgender people starts early in life, that transgender people are at risk for multiple types and incidences of violence, and that this threat lasts throughout their lives. In addition, transgender people seem to have particularly high risk for sexual violence. Future research considerations, such as improving data collection efforts, are discussed.


title: A general framework for never-ending learning from time series streams

abstract: Time series classification has been an active area of research in the data mining community for over a decade, and significant progress has been made in the tractability and accuracy of learning. However, virtually all work assumes a one-time training session in which labeled examples of all the concepts to be learned are provided. This assumption may be valid in a handful of situations, but it does not hold in most medical and scientific applications where we initially may have only the vaguest understanding of what concepts can be learned. Based on this observation, we propose a never-ending learning framework for time series in which an agent examines an unbounded stream of data and occasionally asks a teacher (which may be a human or an algorithm) for a label. We demonstrate the utility of our ideas with experiments that consider real-world problems in domains as diverse as medicine, entomology, wildlife monitoring, and human behavior analyses.


title: Undergraduates’ attitudes to text messaging language use and intrusions of textisms into formal writing

abstract: Students’ increasing use of text messaging language has prompted concern that textisms (e.g., 2 for to, dont for don’t, ☺) will intrude into their formal written work. Eighty-six Australian and 150 Canadian undergraduates were asked to rate the appropriateness of textism use in various situations. Students distinguished between the appropriateness of using textisms in different writing modalities and to different recipients, rating textism use as inappropriate in formal exams and assignments, but appropriate in text messages, online chat and emails with friends and siblings. In a second study, we checked the examination papers of a separate sample of 153 Australian undergraduates for the presence of textisms. Only a negligible number were found. We conclude that, overall, university students recognise the different requirements of different recipients and modalities when considering textism use and that students are able to avoid textism use in exams despite media reports to the contrary.


title: Mammoth: Gearing Hadoop Towards Memory-Intensive MapReduce Applications

abstract: The MapReduce platform has been widely used for large-scale data processing and analysis recently. It works well if the hardware of a cluster is well configured. However, our survey has indicated that common hardware configurations in small- and medium-size enterprises may not be suitable for such tasks. This situation is more challenging for memory-constrained systems, in which the memory is a bottleneck resource compared with the CPU power and thus does not meet the needs of large-scale data processing. The traditional high performance computing (HPC) system is an example of the memory-constrained system according to our survey. In this paper, we have developed Mammoth, a new MapReduce system, which aims to improve MapReduce performance using global memory management. In Mammoth, we design a novel rule-based heuristic to prioritize memory allocation and revocation among execution units (mapper, shuffler, reducer, etc.), to maximize the holistic benefits of the Map/Reduce job when scheduling each memory unit. We have also developed a multi-threaded execution engine, which is based on Hadoop but runs in a single JVM on a node. In the execution engine, we have implemented the algorithm of memory scheduling to realize global memory management, based on which we further developed the techniques such as sequential disk accessing, multi-cache and shuffling from memory, and solved the problem of full garbage collection in the JVM. We have conducted extensive experiments to compare Mammoth against the native Hadoop platform. The results show that the Mammoth system can reduce the job execution time by more than 40 percent in typical cases, without requiring any modifications of the Hadoop programs. When a system is short of memory, Mammoth can improve the performance by up to 5.19 times, as observed for I/O intensive applications, such as PageRank. We also compared Mammoth with Spark. Although Spark can achieve better performance than Mammoth for interactive and iterative applications when the memory is sufficient, our experimental results show that for batch processing applications, Mammoth can adapt better to various memory environments and outperform Spark when the memory is insufficient, and can obtain similar performance as Spark when the memory is sufficient. Given the growing importance of supporting large-scale data processing and analysis and the proven success of the MapReduce platform, the Mammoth system can have a promising potential and impact.


title: Development of Simulation Framework UASNSF for Underwater Acoustic Sensor Networks

abstract: Simulation is a major method for researching Underwater Acoustic Sensor Networks(UASNs).This paper presents UASNSF,a simulation framework for UASNs,based on the summarization of current simulators,and describes the architecture,composing models,application scenarios of the framework briefly.The practicability of the framework is validated finally through a typical simulation application of UASNs.The simulation results show that,UASNSF meets the requirement of both the accuracy and efficiency,and the full-scale emulation of the UASNs can be achieved.


title: Injecting Social Diversity in Multi-objective Genetic Programming: The Case of Model Well-Formedness Rule Learning

abstract: Software modelling activities typically involve a tedious and time-consuming effort by specially trained personnel. This lack of automation hampers the adoption of the Model Driven Engineering (MDE) paradigm. Nevertheless, in the recent years, much research work has been dedicated to learn MDE artifacts instead of writing them manually. In this context, mono- and multi-objective Genetic Programming (GP) has proven being an efficient and reliable method to derive automation knowledge by using, as training data, a set of examples representing the expected behavior of an artifact. Generally, the conformance to the training example set is the main objective to lead the search for a solution. Yet, single fitness peak, or local optima deadlock, one of the major drawbacks of GP, remains when adapted to MDE and hinders the results of the learning. We aim at showing in this paper that an improvement in populations’ social diversity carried out during the evolutionary computation will lead to more efficient search, faster convergence, and more generalizable results. We ascertain improvements are due to our changes on the search strategy with an empirical evaluation featuring the case of learning well-formedness rules in MDE with a multi-objective genetic algorithm. The obtained results are striking, and show that semantic diversity allows a rapid convergence toward the near-optimal solutions. Moreover, when the semantic diversity is used as for crowding distance, this convergence is uniform through a hundred of runs.


title: White matter hyperintensities, cognitive impairment and dementia: an update

abstract: White matter hyperintensities (WMHs) are frequently seen on brain MRI in older people, and are thought to result from chronic ischaemia associated with cerebral small vessel disease. Prins and Scheltens provide a timely Review on WMHs, including their relationship with cognitive decline and dementia. The authors also discuss how WMHs might provide a therapeutic target to prevent the onset and progression of dementia.


title: Design and Control of the MINDWALKER Exoskeleton

abstract: Powered exoskeletons can empower paraplegics to stand and walk. Actively controlled hip ab/adduction (HAA) is needed for weight shift and for lateral foot placement to support dynamic balance control and to counteract disturbances in the frontal plane. Here, we describe the design, control, and preliminary evaluation of a novel exoskeleton, MINDWALKER. Besides powered hip flexion/extension and knee flexion/extension, it also has powered HAA. Each of the powered joints has a series elastic actuator, which can deliver 100 Nm torque and 1 kW power. A finite-state machine based controller provides gait assistance in both the sagittal and frontal planes. State transitions, such as stepping, can be triggered by the displacement of the Center of Mass (CoM). A novel step-width adaptation algorithm was proposed to stabilize lateral balance. We tested this exoskeleton on both healthy subjects and paraplegics. Experimental results showed that all users could successfully trigger steps by CoM displacement. The step-width adaptation algorithm could actively counteract disturbances, such as pushes. With the current implementations, stable walking without crutches has been achieved for healthy subjects but not yet for SCI paraplegics. More research and development is needed to improve the gait stability.


title: A coherent projection approach for direct volume rendering

abstract: Direct volume rendering offers the opportunity to visualize all of a three-dimensional sample volume in one image. However, processing such images can be very expensive and good quality high-resolution images are far from interactive. Projection approaches to direct volume rendering process the volume region by region as opposed to ray-casting methods that process it ray by ray. Projection approaches have generated interest because they use coherence to provide greater speed than ray casting and generate the image in a layered, informative fashion. This paper discusses two topics: First, it introduces a projection approach for directly rendering rectilinear, parallel-projected sample volumes that takes advantage of coherence across cells and the identical shape of their projection. Second, it considers the repercussions of various methods of integration in depth and interpolation across the scan plane. Some of these methods take advantage of Gouraud-shading hardware, with advantages in speed but potential disadvantages in image quality.


title: Supervised nonlinear dimensionality reduction for visualization and classification

abstract: When performing visualization and classification, people often confront the problem of dimensionality reduction. Isomap is one of the most promising nonlinear dimensionality reduction techniques. However, when Isomap is applied to real-world data, it shows some limitations, such as being sensitive to noise. In this paper, an improved version of Isomap, namely S-Isomap, is proposed. S-Isomap utilizes class information to guide the procedure of nonlinear dimensionality reduction. Such a kind of procedure is called supervised nonlinear dimensionality reduction. In S-Isomap, the neighborhood graph of the input data is constructed according to a certain kind of dissimilarity between data points, which is specially designed to integrate the class information. The dissimilarity has several good properties which help to discover the true neighborhood of the data and, thus, makes S-Isomap a robust technique for both visualization and classification, especially for real-world problems. In the visualization experiments, S-Isomap is compared with Isomap, LLE, and WeightedIso. The results show that S-Isomap performs the best. In the classification experiments, S-Isomap is used as a preprocess of classification and compared with Isomap, WeightedIso, as well as some other well-established classification methods, including the K-nearest neighbor classifier, BP neural network, J4.8 decision tree, and SVM. The results reveal that S-Isomap excels compared to Isomap and WeightedIso in classification, and it is highly competitive with those well-known classification methods.


title: Obesity and the brain: how convincing is the addiction model?

abstract: An increasingly influential perspective conceptualizes both obesity and overeating as a food addiction accompanied by corresponding brain changes. Because there are far-reaching implications for clinical practice and social policy if it becomes widely accepted, a critical evaluation of this model is important. We examine the current evidence for the link between addiction and obesity, identifying several fundamental shortcomings in the model, as well as weaknesses and inconsistencies in the empirical support for it from human neuroscientific research.


title: Outdoor Thermal Comfort in a Transitional Space of Canopy in Schools in the UK

abstract: There has been a significant increase in opportunities to improve school environments in the UK. There has, however, been little study on the design of sheltered transitional spaces, despite growing architectural demand for this, examples of which can be easily found in most primary schools in the UK. Computer simulations (Rayman, Ecotect and Winair4) were performed to identify the influence of different parameters: that of having a canopy; the effect of the transmissivity of the canopy material (three transparencies 0%, 50% and 90% were considered); orientation (four orientations—north, east, south and west—were considered); and location (three cities: London, Manchester and Glasgow). The combined effects of canopy transparency and orientation were shown to be critical design considerations in affecting comfort conditions in outdoor spaces. It was found that outdoor comfort conditions in the transitional space can be enhanced by 41.5% in August by choosing a canopy of 0% transparency, compared with a canopy of 90% transparency in London. The fixed canopy with a higher transparency helped to increase outdoor thermal comfort in Glasgow, while one with a lower transparency showed better performance during summer in London. This research will help design environmentally sophisticated transitional spaces in schools.


title: A multi-DOF two wheeled inverted pendulum robot climbing on a slope

abstract: Two wheeled inverted pendulum (TWIP) robot is widely used in various applications for its zero turning radius, small footprint and other advantages. However, the traditional TWIP robot can not keep upright when climbs or descends on a slope, which makes the operator sitting on the robot feel unsafe and uncomfortable. This paper introduces a Multi-DOF TWIP robot, which adding a movable weight to the standard TWIP robot. This robot can maintain the robot body upright when the robot climbs or descends a slope, also when accelerate or decelerate. The complex full dynamics model of the robot is derived from the Largrange's method, and then a simplified method is proposed. Controllers for balance and velocity control are designed separately based on the simplified model. Simulation and real experiment demonstrates that this method proposed in this paper is effective.


title: Role and users’ approach to social networking sites (SNSs): a study of universities of North India

abstract: Purpose – The purpose of this paper is to evaluate and assess the awareness and extent of the use of social networking sites (SNSs) by the students and research scholars of universities of North India. Design/methodology/approach – The study is a questionnaire-based survey on the usage of SNSs among the students and research scholars of the universities of North India. The data of the study were collected through questionnaires, which were personally distributed to the identified population, i.e. undergraduate students, postgraduate students and research scholars, by the authors. The survey was based on a sample of 610 questionnaires; of which, 486 questionnaires were received, having a response rate of 79.67 per cent. Findings – The study showed that all the respondents were found to be aware of and making use of such applications in their academic affairs. It was revealed from the study that Facebook is the most popular SNS by all categories of respondents. To determine the purpose of SNSs, it emerged that SNSs are mostly used for entertainment and communication. The study also found that the majority of respondents were aware about the security aspects of SNSs. It signifies that excessive time consumption and fear of misusing personal information were the major hurdles in the way of accessing SNSs. Research limitations/implications – The study covers the students and research scholars of select universities of North India. It also signifies the use of SNSs in their research and academic environment. Originality/value – The paper provides reliable and authentic data. The study is worth, justifiable and enlightens the salient findings on the topic, which will be very useful for researchers in this area.


title: Source code generator for automating business rule implementation

abstract: Business rules can be implemented on business processes, business behavior, people, or software in an organization. Aligned with software development, business rules are captured from requirement elicitation and analysis, then designed and implemented in the software. The changes of business environment may affect business rules. The changes of the business rules may bring impact in the software, so that the software needs to be redeveloped. In this paper, we present a source code generator to automate business rule implementation using business rule approach. We propose a Domain Specific Language (DSL) of business rule to help expressing business rules in a business-friendly language. We also develop a business rule generator to generate source codes based on a DSL script for expressing the business rules. The proposed solution has been tested in two case studies. It is shown that the generator can help the implementation of the business rules in source codes and that the generated code can be used in business applications.


title: Design of a compact winding for an axial-flux permanent-magnet brushless DC motor used in an electric two-wheeler

abstract: This paper describes the design of a compact winding for an axial-flux permanent-magnet brushless dc motor used in an electric two-wheeler. Once the motor design is carried out using the conventional method and the dimensions of the motor, magnet, etc. are determined, the electric loading and the magnetomotive force (MMF) required to obtain the peak torque can be calculated. From the knowledge of the MMF requirement, a compact and efficient winding configuration has been achieved using a parametric study. The factors considered for the winding design are: 1) operating voltage; 2) number of poles; 3) cross-sectional area available for the winding; 4) conductor size; 5) number of parallel paths; 6) length of mean turn; 7) and the peak torque for a given value of AT/pole/phase. The motor voltage is decided based on the speed of the motor and aspects of the battery and the controller. The selected winding configuration for an 80-Nm peak torque, 48-V, three-phase motor is having 48 coils with each coil of 18 turns made out of 15 standard wire gauge copper wire. The resistance per phase is calculated as 0.0203 /spl Omega/.


title: Within-study measurement invariance of the UTAUT instrument: An assessment with user technology engagement variables

abstract: Establish within-study measurement invariance with variables within a single study.Analyzed invariance of UTAUT scales with six users' technology engagement variables.Conducted the full suite of seven different measurement invariance tests.Identified invariant UTAUT scale items that can be safely used in future studies.Also provide guidelines for conducting within-study measurement invariance analyses. We assess within-study invariance of key UTAUT scales considering a total of six respondent group characteristics: five variables pertaining to users' two technology engagement facets (prior technology knowledge and technology usage pattern) and one variable pertaining to their gender. Data collected from 250 respondents about their perceptions and usage of online blogs were analyzed to test six invariance hypotheses. The results indicate that the UTAUT instrument showed full or partial invariance for respondents' technology usage pattern and gender. With respect to prior IT knowledge, the UTAUT scales were found to be invariant for general IT knowledge but non-invariant for specific IT knowledge.


title: Sesame: A User-Transparent Optimizing Framework for Many-Core Processors

abstract: With the integration of more computational cores and deeper memory hierarchies on modern processors, the performance gap between naively parallel zed code and optimized code becomes much larger than ever before. Very often, bridging the gap involves architecture-specific optimizations. These optimizations are difficult to implement by application programmers, who typically focus on the basic functionality of their code. Therefore, in this thesis, I focus on answering the following research question: "How can we address architecture-specific optimizations in a programmer-friendly way?'' As an answer, I propose an optimizing framework for parallel applications running on many-core processors (\textit{Sesame}). Taking a simple parallel zed code provided by the application programmers as input, Sesame chooses and applies the most suitable architecture-specific optimizations, aiming to improve the overall application performance in a user-transparent way. In this short paper, I present the motivation for designing and implementing Sesame, its structure and its modules. Furthermore, I describe the current status of Sesame, discussing our promising results in source-to-source vectorization, automated usage of local memory, and auto-tuning for implementation-specific parameters. Finally, I discuss my work-in-progress and sketch my ideas for finalizing Sesame's development and testing.


title: A Pose-Sensitive Embedding for Person Re-Identification with Expanded Cross Neighborhood Re-Ranking

abstract: Person re identification is a challenging retrieval task that requires matching a person's acquired image across non overlapping camera views. In this paper we propose an effective approach that incorporates both the fine and coarse pose information of the person to learn a discriminative embedding. In contrast to the recent direction of explicitly modeling body parts or correcting for misalignment based on these, we show that a rather straightforward inclusion of acquired camera view and/or the detected joint locations into a convolutional neural network helps to learn a very effective representation. To increase retrieval performance, re-ranking techniques based on computed distances have recently gained much attention. We propose a new unsupervised and automatic re-ranking framework that achieves state-of-the-art re-ranking performance. We show that in contrast to the current state-of-the-art re-ranking methods our approach does not require to compute new rank lists for each image pair (e.g., based on reciprocal neighbors) and performs well by using simple direct rank list based comparison or even by just using the already computed euclidean distances between the images. We show that both our learned representation and our re-ranking method achieve state-of-the-art performance on a number of challenging surveillance image and video datasets. ::: The code is available online at: this https URL


title: Gut bacteria selectively promoted by dietary fibers alleviate type 2 diabetes

abstract: The gut microbiota benefits humans via short-chain fatty acid (SCFA) production from carbohydrate fermentation, and deficiency in SCFA production is associated with type 2 diabetes mellitus (T2DM). We conducted a randomized clinical study of specifically designed isoenergetic diets, together with fecal shotgun metagenomics, to show that a select group of SCFA-producing strains was promoted by dietary fibers and that most other potential producers were either diminished or unchanged in patients with T2DM. When the fiber-promoted SCFA producers were present in greater diversity and abundance, participants had better improvement in hemoglobin A1c levels, partly via increased glucagon-like peptide-1 production. Promotion of these positive responders diminished producers of metabolically detrimental compounds such as indole and hydrogen sulfide. Targeted restoration of these SCFA producers may present a novel ecological approach for managing T2DM.


title: Toward a Principled Framework to Design Dynamic Adaptive Streaming Algorithms over HTTP

abstract: Client-side bitrate adaptation algorithms play a critical role in delivering a good quality of experience for Internet video. Many studies have shown that current solutions perform suboptimally, and despite the proliferation of several proposals in this space, both from commercial providers and researchers, there is still a distinct lack of clarity and consensus w.r.t. several natural questions: (1) What objectives does/should such an algorithm optimize? (2) What environment signals such as buffer occupancy or throughput estimates should an algorithm use in its control loop? (3) How sensitive is an algorithm to operating conditions (e.g., bandwidth stability, buffer size, available bitrates)? This work attempts to bring clarity to this discussion by casting adaptive bitrate streaming as a model-based predictive control problem. We demonstrate the initial promise of shedding light on these questions using this control-theoretic abstraction.


title: Stacked Denoising Autoencoder-Based Deep Collaborative Filtering Using the Change of Similarity

abstract: Recommender systems based on deep learning technology pay huge attention recently. In this paper, we propose a collaborative filtering based recommendation algorithm that utilizes the difference of similarities among users derived from different layers in stacked denoising autoencoders. Since different layers in a stacked autoencoder represent the relationships among items with rating at different levels of abstraction, we can expect to make recommendations more novel, various and serendipitous, compared with a normal collaborative filtering using single similarity. The results of experiments using MovieLens dataset show that the proposed recommendation algorithm can improve the diversity of recommendation lists without great loss of accuracy.


title: Affective understanding in film

abstract: Affective understanding of film plays an important role in sophisticated movie analysis, ranking and indexing. However, due to the seemingly inscrutable nature of emotions and the broad affective gap from low-level features, this problem is seldom addressed. In this paper, we develop a systematic approach grounded upon psychology and cinematography to address several important issues in affective understanding. An appropriate set of affective categories are identified and steps for their classification developed. A number of effective audiovisual cues are formulated to help bridge the affective gap. In particular, a holistic method of extracting affective information from the multifaceted audio stream has been introduced. Besides classifying every scene in Hollywood domain movies probabilistically into the affective categories, some exciting applications are demonstrated. The experimental results validate the proposed approach and the efficacy of the audiovisual cues.


title: On the Quantitative Analysis of Decoder-Based Generative Models

abstract: The past several years have seen remarkable progress in generative models which produce convincing samples of images and other modalities. A shared component of some popular models such as generative adversarial networks and generative moment matching networks, is a decoder network, a parametric deep neural net that defines a generative distribution. Unfortunately, it can be difficult to quantify the performance of these models because of the intractability of log-likelihood estimation, and inspecting samples can be misleading. We propose to use Annealed Importance Sampling for evaluating log-likelihoods for decoder-based models and validate its accuracy using bidirectional Monte Carlo. Using this technique, we analyze the performance of decoder-based models, the effectiveness of existing log-likelihood estimators, the degree of overfitting, and the degree to which these models miss important modes of the data distribution.


title: Self-Supervised Visual Planning with Temporal Skip Connections

abstract: In order to autonomously learn wide repertoires of complex skills, robots must be able to learn from their own autonomously collected data, without human supervision. One learning signal that is always available for autonomously collected data is prediction: if a robot can learn to predict the future, it can use this predictive model to take actions to produce desired outcomes, such as moving an object to a particular location. However, in complex open-world scenarios, designing a representation for prediction is difficult. In this work, we instead aim to enable self-supervised robotic learning through direct video prediction: instead of attempting to design a good representation, we directly predict what the robot will see next, and then use this model to achieve desired goals. A key challenge in video prediction for robotic manipulation is handling complex spatial arrangements such as occlusions. To that end, we introduce a video prediction model that can keep track of objects through occlusion by incorporating temporal skip-connections. Together with a novel planning criterion and action space formulation, we demonstrate that this model substantially outperforms prior work on video prediction-based control. Our results show manipulation of objects not seen during training, handling multiple objects, and pushing objects around obstructions. These results represent a significant advance in the range and complexity of skills that can be performed entirely with self-supervised robotic learning.


title: Comparison of energy cost in transtibial amputees using "prosthesis" and "crutches without prosthesis" for walking activities.

abstract: BACKGROUND ::: In a survey of 100 transtibial amputees (TTA) in the study place, it was noticed that nearly 30% of total activities performed by crutches. It was recorded nearly 52% of the amputees were totally independent, 39% had to use a crutch or cane and only 9% need not used any devices simply because they are unaware of current technology or availability. Out of 39 TTA, nine used crutches only for performing daily activities while 30 used both prosthesis and crutch. Walking is a major activity in lower limb amputees and therefore it is imperative to know the energy cost in both the mobility devices (prosthesis and crutches without prosthesis) for walking activities. ::: ::: ::: OBJECTIVES ::: The purpose of this study was to quantify and compare the difference in energy cost between the two most commonly used assistive devices (prosthesis and axillary crutches) in adults with Transtibial amputation by indirect calorimetric method at the self-selected speed in plane surface walking. ::: ::: ::: METHODS ::: Thirty adults who had a unilateral transtibial amputation participated in this study. Oxygen consumption was measured with a Cosmed K4 b(2) oxygen analysis telemetry unit (Rome, Italy) as the participants walked over level ground for 30 meters at a self-selected speed. The variables that were analyzed were VO(2) rate (mL/min), VO(2) cost (mL/kg/m), heart rate (bpm), self-selected walking velocity (m/min) and energy expenditure per minute (Kcal/min). ::: ::: ::: RESULTS ::: It was observed that VO(2) uptake rate and EE comparisons were highly significant for both prosthesis and crutches without prosthesis walking in adults with transtibial amputation (P<0.025). There was significant difference between prosthesis walking and crutches without prosthesis walking in terms of VO(2) uptake rate (P<0.005) and EE/min (P<0.00001). It was noticed the adults with transtibial amputation using prosthesis walked with 21% more efficient in terms of VO(2) uptake rate and 92% more efficient in terms of EE/min as compared to crutches without prosthesis. ::: ::: ::: CONCLUSIONS ::: The data on energy cost indicates that all below knee amputee groups walk with less effort by using prosthesis. It may be concluded that crutches without prosthesis may not be used as a permanent rehabilitative measure in transtibial amputations.


title: Exploring the Processing-in-Memory design space

abstract: With the emergence of 3D-DRAM, Processing-in-Memory has once more become of great interest to the research community and industry. Here we present our observations on a subset of the PIM design space. We show how the architectural choices for PIM core frequency and cache sizes will affect the overall power consumption and energy efficiency. We include a detailed power consumption breakdown for an ARM-like core as a PIM core. We show the maximum possible number of PIM cores we can place in the logic layer with respect to a predefined power budget. Additionally, we catalog additional sources of power consumption in a system with PIM such as 3D-DRAM link power and discuss the possible power reduction techniques. We describe the shortcomings of using ARM-like cores for PIM and discuss other alternatives for the PIM cores. Finally, we explore the optimal design choices for the number of cores as a function of performance, utilization, and energy efficiency.


title: Topic-based PageRank on author cocitation networks

abstract: Ranking authors is vital for identifying a researcher's impact and standing within a scientific field. There are many different ranking methods (e.g., citations, publications, h-index, PageRank, and weighted PageRank), but most of them are topic-independent. This paper proposes topic-dependent ranks based on the combination of a topic model and a weighted PageRank algorithm. The author-conference-topic (ACT) model was used to extract topic distribution of individual authors. Two ways for combining the ACT model with the PageRank algorithm are proposed: simple combination (I_PR) or using a topic distribution as a weighted vector for PageRank (PR_t). Information retrieval was chosen as the test field and representative authors for different topics at different time phases were identified. Principal component analysis (PCA) was applied to analyze the ranking difference between I_PR and PR_t. © 2011 Wiley Periodicals, Inc.


title: Seeing it all: Convolutional network layers map the function of the human visual system

abstract: ABSTRACT Convolutional networks used for computer vision represent candidate models for the computations performed in mammalian visual systems. We use them as a detailed model of human brain activity during the viewing of natural images by constructing predictive models based on their different layers and BOLD fMRI activations. Analyzing the predictive performance across layers yields characteristic fingerprints for each visual brain region: early visual areas are better described by lower level convolutional net layers and later visual areas by higher level net layers, exhibiting a progression across ventral and dorsal streams. Our predictive model generalizes beyond brain responses to natural images. We illustrate this on two experiments, namely retinotopy and face‐place oppositions, by synthesizing brain activity and performing classical brain mapping upon it. The synthesis recovers the activations observed in the corresponding fMRI studies, showing that this deep encoding model captures representations of brain function that are universal across experimental paradigms. Graphical abstract Figure. No Caption available. HighlightsConvolutional network layer image representations explain ventral stream fMRI.This mapping follows the known hierarchical organisation.Results from both static images and video stimuli.A full brain predictive model synthesizes brain maps for other visual experiments.Only deep models can reproduce observed BOLD activity.


title: Novel T/R switch architectures for MIMO applications

abstract: In this paper, we present new architectures for three kinds of RF switches (DPDT, DP4T, 4P4T) with very simple control logics and high power handling capabilities. Implementation of DPDT, DP4T, and 4P4T switch matrix for multi-input-multi-output (MIMO) applications is demonstrated with measurements. The suggested DPDT, DP4T, and 4P4T switch architectures require only one, two and three control lines, respectively, regardless of semiconductor technology. The developed DPDT switch demonstrates 1.0 dB of insertion loss, 19 dB of isolation, and 31 dBm of input P0.1 dB, 34.5 dBm of input P1 dB in 3/0 V operation at 5.8 GHz. The DP4T, 4P4T switches exhibit 1.8 dB, 2.8 dB of insertion loss, and 23/37 dB, 20/35/55 dB of isolation, respectively, and 31 dBm of input P0.1 dB, 35 dBm of input P1 dB in 3/0 V operation at 5.8 GHz. The MMICs are developed in a commercial 0.25-/spl mu/m GaAs pHEMT process. These switch architectures are preferable for the Si-based processes because the substrate vias are not required due to their generic topologies. To the best of our knowledge, this is the first report on the simple architectures for RF switch matrix for MIMO applications.


title: Toxicity profile of approved anti-PD-1 monoclonal antibodies in solid tumors: a systematic review and meta-analysis of randomized clinical trials

abstract: PURPOSE ::: Nivolumab and pembrolizumab are antibodies against the programmed-death-receptor- 1 (PD-1) which are associated with distinct immune related adverse effects (AEs). This meta-analysis of randomized clinical trials aims to summarize current knowledge regarding the toxicity profile of these agents. ::: ::: ::: METHODS ::: PubMed search was conducted in February of 2016. The randomized trials needed to have at least one of the study arms consisting of nivolumab or pembrolizumab monotherapy and a control arm containing no anti-PD-1 therapy. Data were analyzed using random effects meta-analysis for risk ratios. Heterogeneity across studies was analyzed using Q and I2 statistics. ::: ::: ::: RESULTS ::: Nine randomized trials and 5,353 patients were included in our meta-analysis. There was evidence of significant heterogeneity between studies. The pooled relative risk (RR) for treatment-related all grade AEs and grade 3/4 AEs was 0.88 (95% CI 0.81-0.95;P=0.002) and 0.39 (95% CI 0.29-0.53; P<0.001) respectively favoring anti-PD-1 therapy versus standard of care approach. The RR of treatment-related death was 0.45 (95% CI 0.19-1.09; P=0.076). Patients treated with PD-1 inhibitors had an increased risk of hyperthyroidism [RR of 3.44 (95% CI 1.98-5.99; P<0.001)] and hypothyroidism [RR of 6.79 (95% CI 3.10-14.84; P<0.001)]. All grade pruritus and vitiligo were also more common among these patients. The pooled absolute risks of pneumonitis and hypophysitis were 2.65% and 0.47% respectively. ::: ::: ::: CONCLUSION ::: Approved PD-1 inhibitors are well tolerated, associated with significant low risk of severe treatment-related AEs and increased risk of thyroid dysfunction, pruritus, and vitiligo.


title: Multimedia traffic scheduling in DVB-S2 networks with mobile users

abstract: DVB-S2 is a second-generation standard for satellite transmissions, developed to improve the performance of DVB-S. Recently, research efforts have been devoted to extend this standard for mobile usage. In this paper we consider a scenario composed of a Ku-band GEO bent-pipe satellite, a gateway and some mobile users. The interest is here in investigating the performance of a scheduling scheme to manage DVB-S2 resources on the forward channel for the delivery of video CBR and FTP traffic flows to mobile users. A novel scheduler scheme, called UBMT, has been proposed that aims to manage CBR packet transmission deadlines while maximizing the aggregated goodput. Simulation runs have permitted to validate the optimal performance achieved by UBMT in comparison with other schemes. The impact of different TCP versions has been investigated as well showing the good results obtained with the SACK option.


title: 3DCLIMBER: A climbing robot for inspection of 3D human made structures

abstract: 3DCLIMBER is a running project in the University of Coimbra for developing a climbing robot with the capability of manipulating over 3D human-made structures. This paper mainly discuss the conceptual and detailed design and development of a Pole Climbing robot with minimum degrees of freedom which can climb over 3D structures with bends and branches followed by Preliminary test results of the robot performance. Electronics architecture and control algorithms are briefly described. The paper finishes with discussion of the current results and identifies some future works.


title: Millimeter-wave radar systems on-chip and in package: Current status and future challenges

abstract: In this work, we give an overview on recent developments that have been made in the field of mm-wave systems which are integrated on chip or in package. Several aspects like waveforms and signal generation, multi-channel systems for beamforming applications as well as integration of antennas into packages will be discussed. The focus of this work is put on approaches which are suitable for on-chip and in-package integration. The restrictions imposed by the integration into single devices are discussed and several prototype systems are presented.


Ontology Visualization: A Systematic Literature Analysis


title: The Limits of Genetic Influence: A Behavior‐Genetic Analysis of Infant–Caregiver Relationship Quality and Temperament

abstract: This report presents data on 9-month-old twin pairs (nMZ=172; nDZ=333) from the Early Childhood Longitudinal Study, demonstrating that the role of genetic variation among infants is trivial and the shared and nonshared environment is substantial in accounting for the observed quality of infant–caregiver relationships. In contrast, maternal reports of temperament were best accounted for by genetic variation and nonshared environmental influences. Interestingly, however, shared environmental effects were documented for observations of temperament. Consistent with a growing database, the current study calls into question the ubiquity of heritability effects in all domains of psychological inquiry. It also bolsters consensus in the field of developmental psychology that shared environmental effects are not as elusive as had once been thought.


title: Spectral 3D mesh segmentation with a novel single segmentation field

abstract: We present an automatic mesh segmentation framework that achieves 3D segmentation in two stages, hierarchical spectral analysis and isoline-based boundary detection. During the hierarchical spectral analysis stage, a novel segmentation field is defined to capture a concavity-aware decomposition of eigenvectors from a concavity-aware Laplacian. Specifically, a sufficient number of eigenvectors is first adaptively selected and simultaneously partitioned into sub-eigenvectors through spectral clustering. Next, on the sub-eigenvectors level, we evaluate the confidence of identifying a spectral-sensitive mesh boundary for each sub-eigenvector by two joint measures, namely, inner variations and part oscillations. The selection and combination of sub-eigenvectors are thereby formulated as an optimization problem to generate a single segmentation field. In the isoline-based boundary detection stage, the segmentation boundaries are recognized by a divide-merge algorithm and a cut score, which respectively filters and measures desirable isolines from the concise single segmentation field. Experimental results on the Princeton Segmentation Benchmark and a number of other complex meshes demonstrate the effectiveness of the proposed method, which is comparable to recent state-of-the-art algorithms.


title: Learning the semantic structure of objects from Web supervision

abstract: While recent research in image understanding has often focused on recognizing more types of objects, understanding more about the objects is just as important. Recognizing object parts and attributes has been extensively studied before, yet learning large space of such concepts remains elusive due to the high cost of providing detailed object annotations for supervision. The key contribution of this paper is an algorithm to learn the nameable parts of objects automatically, from images obtained by querying Web search engines. The key challenge is the high level of noise in the annotations; to address it, we propose a new unified embedding space where the appearance and geometry of objects and their semantic parts are represented uniformly. Geometric relationships are induced in a soft manner by a rich set of nonsemantic mid-level anchors, bridging the gap between semantic and non-semantic parts. We also show that the resulting embedding provides a visually-intuitive mechanism to navigate the learned concepts and their corresponding images.


title: J. Cosmet. Sci.,59, 127-137 (March/April 2008)ï¿½Why women use makeup: Implication of psychological traits in makeup functions

abstract: Synopsis ::: ::: Makeup acts and stimulates three of our senses: touch (which encompasses all sensations from the body surface), smell (fragrance), and sight (the process of becoming and looking beautiful). The positive stimulation of these senses by makeup can induce sensory as well as psychological pleasure. In order to understand the relationship of women to their makeup, we interviewed different groups of women on their quality of life and makeup habits. Then, through four standard well-validated psychometric self-questionnaires, we examined the possible relation between the need to make up oneself and specific psychological features. Our first results clearly showed that makeup could support two opposite ‘up’ functions, i.e., ‘camouflage’ vs. ‘seduction.’ Concerning their psychological profiles, results showed that women of the functional class ‘camouflage’ are more anxious, defensive, and emotionally unstable compared to those of the functional class ‘seduction,’ who appear to be more sociable, assertive, and extroverted. Further analyses revealed a division of the two classes into subclasses of volunteers with opposed personality and psychological profiles. This new classification allowed us to define more precisely the relations existing within the subjective experience of women during the makeup process. In conclusion, our study revealed that beyond the simple application of colorful products on the face, makeup has two major functional implications depending on specific psychological profiles of women.


title: Neurophysiology of gait: from the spinal cord to the frontal lobe.

abstract: Locomotion is a purposeful, goal-directed behavior initiated by signals arising from either volitional processing in the cerebral cortex or emotional processing in the limbic system. Regardless of whether the locomotion initiation is volitional or emotional, locomotion is accompanied by automatic controlled movement processes, such as the adjustment of postural muscle tone and rhythmic limb movements. Sensori-motor integration in the brainstem and the spinal cord plays crucial roles in this process. The basic locomotor motor pattern is generated by spinal interneuronal networks, termed central pattern generators (CPGs). Responding to signals in proprioceptive and skin afferents, the spinal interneuronal networks modify the locomotor pattern in cooperation with descending signals from the brainstem structures and the cerebral cortex. Information processing between the basal ganglia, the cerebellum, and the brainstem may enable automatic regulation of muscle tone and rhythmic limb movements in the absence of conscious awareness. However, when a locomoting subject encounters obstacles, the subject has to intentionally adjust bodily alignment to guide limb movements. Such an intentional gait modification requires motor programming in the premotor cortices. The motor programs utilize one's bodily information, such as the body schema, which is preserved and updated in the temporoparietal cortex. The motor programs are transmitted to the brainstem by the corticoreticulospinal system, so that one's posture is anticipatorily controlled. These processes enable the corticospinal system to generate limb trajectory and achieve accurate foot placement. Loops from the motor cortical areas to the basal ganglia and the cerebellum can serve this purpose. © 2013 International Parkinson and Movement Disorder Society


title: Longitudinal Data Analysis

abstract: Preface. Acknowledgments. Acronyms. 1. Introduction. 1.1 Advantages of Longitudinal Studies. 1.2 Challenges of Longitudinal Data Analysis. 1.3 Some General Notation. 1.4 Data Layout. 1.5 Analysis Considerations. 1.6 General Approaches. 1.7 The Simplest Longitudinal Analysis. 1.8 Summary. 2. ANOVA Approaches to Longitudinal Data. 2.1Single-Sample Repeated Measures ANOVA. 2.2 Multiple-Sample Repeated Measures ANOVA. 2.3 Illustration. 2.4 Summary. 3. MANOVA Approaches to Longitudinal Data. 3.1 Data Layout for ANOVA versus MANOVA. 3.2 MANOVA for Repeated Measurements. 3.3 MANOVA of Repeated Measures-s Sample Case. 3.4 Illustration. 3.5 Summary. 4. Mixed-Effects Regression Models for Continuous Outcomes. 4.1 Introduction. 4.2 A Simple Linear Regression Model. 4.3 Random Intercept MRM. 4.4 Random Intercept and Trend MRM. 4.5 Matrix Formulation. 4.6 Estimation . 4.7 Summary. 5. Mixed-Effects Polynomial Regression Models. 5.1 Introduction. 5.2 Curvilinear Trend Model. 5.3 Orthogonal Polynomials. 5.4 Summary. 6. Covariance Pattern Models. 6.1 Introduction. 6.2 Covariance Pattern Models. 6.3 Model Selection. 6.4 Example. 6.5 Summary. 7. Mixed Regression Models with Autocorrelated Errors. 7.1 Introduction. 7.2 MRMs with AC Errors. 7.3 Model Selection. 7.4 Example. 7.5 Summary. 8. Generalized Estimating Equations (GEE) Models. 8.1 Introduction. 8.2 Generalized Linear Models (GLMs). 8.3 Generalized Estimating Equations (GEE) Models. 8.4 GEE Estimation. 8.5 Example. 8.6 Summary. 9. Mixed-Effects Regression Models for Binary Outcomes. 9.1 Introduction. 9.2 Logistic Regression Model. 9.3 Probit Regression Models. 9.4 Threshold Concept. 9.5 Mixed-Effects Logistic Regression Model. 9.6 Estimation. 9.7 Illustration. 9.8 Summary. 10. Mixed-Effects Regression Models for Ordinal Outcomes. 10.1 Introduction. 10.2 Mixed-Effects Proportional Odds Model. 10.3 Psychiatric Example. 10.4 Health Services Research Example. 10.5 Summary. 11. Mixed-Effects Regression Models for Nominal Data. 11.1 Mixed-Effects Multinomial Regression Model. 11.2 Health Services Research Example. 1 1.3 Competing Risk Survival Models. 11.4 Summary. 12. Mixed-effects Regression Models for Counts. 12.1 Poisson Regression Model. 12.2 Modified Poisson Models. 12.3 The ZIP Model. 12.4 Mixed-Effects Models for Counts. 12.5 Illustration. 12.6 Summary. 13. Mixed-Effects Regression Models for Three-Level Data. 13.1 Three-Level Mixed-Effects Linear Regression Model. 13.1.1 Illustration. 13.2 Three-Level Mixed-Effects Nonlinear Regression Models. 13.3 Summary. 14. Missing Data in Longitudinal Studies. 14.1 Introduction. 14.2 Missing Data Mechanisms. 14.3 Models and Missing Data Mechanisms. 14.4 Testing MCAR. 14.5 Models for Nonignorable Missingness. 14.6 Summary. Bibliography. Topic Index.


title: Response of Scots pine (Pinus sylvestris L.) to stress induced by different types of pollutants – testing the fluctuating asymmetry

abstract: Damage caused to pine forests by industrial pollution is observed even several decades after emissions have stopped down. A simple morphological feature – the leaf fluctuating asymmetry – was used for assessing the condition of Scots pine (Pinus sylvestris) stands growing in a heavily degraded area. In 2011, a study was performed on the developmental instability of needles in four naturally reforested Polish populations of P. sylvestris. Studies were conducted within the protective zone at a zinc smelter, a copper smelter, a cement plant and train tracks. All selected areas manifested a high extent of anthropogenic pollution-induced environmental degradation until the end of the 90s. Currently, a reduced level of environmental pollution is recorded at these sites. Control group was a natural population of Scots pine from the region of National Park of Wielkopolska. The results confirm the usefulness of fluctuating asymmetry as a highly sensitive indicator of non-specific stress. Also, it was shown that in areas degraded by human activity, poor condition of Scots pine persists that the stress factor has been eliminated. This tendency occurs particularly to areas contaminated by heavy metals.