title: Development of an individual work performance questionnaire

abstract: Design/methodology/approach - After pilot-testing, the 47-item IWPQ was field-tested amongst a representative sample of 1,181 Dutch blue, pink, and white collar workers. Factor analysis was used to examine whether the four-dimensional conceptual framework could be confirmed. Rasch analysis was used to examine the functioning of the items in more detail. Finally, it was examined whether generic scales could be constructed. Findings - A generic, three-dimensional conceptual framework was identified, in which individual work performance consisted of task performance, contextual performance, and counterproductive work behavior. Generic, short scales could be constructed that fitted the Rasch model. Research implications – A generic, short questionnaire can be used to measure individual work performance across occupational sectors. In future versions of the IWPQ, more difficult items should be added to improve discriminative ability at the high ranges of the scale. Originality/value - This study shows that, using Rasch analysis, a generic and short questionnaire can be used to measure individual work performance.


title: A new input method for human translators: integrating machine translation effectively and imperceptibly

abstract: Computer-aided translation (CAT) system is the most popular tool which helps human translators perform language translation efficiently. To further improve the efficiency, there is an increasing interest in applying the machine translation (MT) technology to upgrade CAT. Post-editing is a standard approach: human translators generate the translation by correcting MT outputs. In this paper, we propose a novel approach deeply integrating MT into CAT systems: a well-designed input method which makes full use of the knowledge adopted by MT systems, such as translation rules, decoding hypotheses and n-best translation lists. Our proposed approach allows human translators to focus on choosing better translation results with less time rather than just complete translation themselves. The extensive experiments demonstrate that our method saves more than 14% time and over 33% keystrokes, and it improves the translation quality as well by more than 3 absolute BLEU scores compared with the strong baseline, i.e., post-editing using Google Pinyin.


title: Evolution and generalization of a single neurone: I. Single-layer perceptron as seven statistical classifiers

abstract: Abstract Unlike many other investigations on this topic, the present one considers the non-linear single-layer perceptron (SLP) as a process in which the weights of the perceptron are increasing, and the cost function of the sum of squares is changing gradually. During the backpropagation training, the decision boundary of of SLP becomes identical or close to that of seven statistical classifiers: (1) the Euclidean distance classifier, (2) the regularized linear discriminant analysis, (3) the standard Fisher linear discriminant function, (4) the Fisher linear discriminant function with a pseudoinverse covariance matrix, (5) the generalized Fisher discriminant function, (6) the minimum empirical error classifier, and (7) the maximum margin classifier. In order to obtain a wider range of classifiers, five new complexity-control techniques are proposed: target value control, moving of the learning data centre into the origin of coordinates, zero weight initialization, use of an additional negative weight decay term called “anti-regularization”, and use of an exponentially increasing learning step. Which particular type of classifier will be obtained depends on the data, the cost function to be minimized, the optimization technique and its parameters, and the stopping criteria.


title: Video SnapCut: robust video object cutout using localized classifiers

abstract: Although tremendous success has been achieved for interactive object cutout in still images, accurately extracting dynamic objects in video remains a very challenging problem. Previous video cutout systems present two major limitations: (1) reliance on global statistics, thus lacking the ability to deal with complex and diverse scenes; and (2) treating segmentation as a global optimization, thus lacking a practical workflow that can guarantee the convergence of the systems to the desired results. ::: We present Video SnapCut, a robust video object cutout system that significantly advances the state-of-the-art. In our system segmentation is achieved by the collaboration of a set of local classifiers, each adaptively integrating multiple local image features. We show how this segmentation paradigm naturally supports local user editing and propagates them across time. The object cutout system is completed with a novel coherent video matting technique. A comprehensive evaluation and comparison is presented, demonstrating the effectiveness of the proposed system at achieving high quality results, as well as the robustness of the system against various types of inputs.


title: Coherent Citation-Based Summarization of Scientific Papers

abstract: In citation-based summarization, text written by several researchers is leveraged to identify the important aspects of a target paper. Previous work on this problem focused almost exclusively on its extraction aspect (i.e. selecting a representative set of citation sentences that highlight the contribution of the target paper). Meanwhile, the fluency of the produced summaries has been mostly ignored. For example, diversity, readability, cohesion, and ordering of the sentences included in the summary have not been thoroughly considered. This resulted in noisy and confusing summaries. In this work, we present an approach for producing readable and cohesive citation-based summaries. Our experiments show that the proposed approach outperforms several baselines in terms of both extraction quality and fluency.


title: Musical instrument sound classification with deep convolutional neural network using feature fusion approach

abstract: A new musical instrument classification method using convolutional neural networks (CNNs) is presented in this paper. Unlike the traditional methods, we investigated a scheme for classifying musical instruments using the learned features from CNNs. To create the learned features from CNNs, we not only used a conventional spectrogram image, but also proposed multiresolution recurrence plots (MRPs) that contain the phase information of a raw input signal. Consequently, we fed the characteristic timbre of the particular instrument into a neural network, which cannot be extracted using a phase-blinded representations such as a spectrogram. By combining our proposed MRPs and spectrogram images with a multi-column network, the performance of our proposed classifier system improves over a system that uses only a spectrogram. Furthermore, the proposed classifier also outperforms the baseline result from traditional handcrafted features and classifiers.


R-SpamRank: A Spam Detection Algorithm Based on Link Analysis


title: Time-Varying Moth-Inspired Algorithm for Chemical Plume Tracing in Turbulent Environment

abstract: In this study, we propose a robust chemical plume tracing (CPT) algorithm for various environments. We developed this algorithm based on the behavior of insects that have CPT abilities globally. However, it is difficult to accurately estimate the behavior pattern from trajectory data because the trajectory contains a high level of measurement noise. We employed flight muscle electromyograms, whose motor commands were assumed to be generated in the same ganglion as the behavior, to estimate the behavior pattern using a support vector machine. By using the estimated results, we modeled the time-varying behavioral change of insects and verified the effectiveness of the phenomenon for CPT using the constructive approach. We named this time-varying CPT algorithm as time-varying moth-inspired algorithm. From the CPT experiment results using the robot, we found that the localization success rate improved by changing the behavior in a time-variant manner.


title: Semi-Autoregressive Neural Machine Translation

abstract: Existing approaches to neural machine translation are typically autoregressive models. While these models attain state-of-the-art translation quality, they are suffering from low parallelizability and thus slow at decoding long sequences. In this paper, we propose a novel model for fast sequence generation --- the semi-autoregressive Transformer (SAT). The SAT keeps the autoregressive property in global but relieves in local and thus is able to produce multiple successive words in parallel at each time step. Experiments conducted on English-German and Chinese-English translation tasks show that the SAT achieves a good balance between translation quality and decoding speed. On WMT'14 English-German translation, the SAT achieves 5.58$\times$ speedup while maintains 88\% translation quality, significantly better than the previous non-autoregressive methods. When produces two words at each time step, the SAT is almost lossless (only 1\% degeneration in BLEU score).


On the Geometry of the Latent Space of Deep Generative Models


title: Multicopter unmanned aerial vehicle for automated inspection of wind turbines

abstract: A concept for a multicopter unmanned aerial vehicle (UAV) automatically performing inspection flights at a wind turbine is proposed. Key aspects of the concept are (1) a priori 3D mapping of the plant and (2) spline-based flight path planning as well as (3) a collision avoidance and distance control system. A quadrotor UAV prototype and its dynamical model are presented. Validation of the different aspects is carried out in simulation and partially in indoor tests using Robot Operating System (ROS). Existence of a 3D map is an essential precondition for path planning and collision-free flight. A brief initial flight preceding the actual inspection with a 2D LiDAR sensor yields a point cloud of the plant which is used for 3D mapping. This map is efficiently generated and represented using octrees, a hierarchical data structure that can be used for 3D maps. Subsequently a smooth and collision-free flight path is generated using splines. For redundancy's sake navigation tasks not only rely on GPS but also on the LiDAR sensor mentioned before. The sensor allows for continuous estimation of the distance between multicopter and wind turbine. A distance control algorithm guarantees collision-free flight.


title: Better static memory management: improving region-based analysis of higher-order languages

abstract: Static memory management replaces runtime garbage collection with compile-time annotations that make all memory allocation and deallocation explicit in a program. We improve upon the Tofte/Talpin region-based scheme for compile-time memory management[TT94]. In the Tofte/Talpin approach, all values, including closures, are stored in regions. Region lifetimes coincide with lexical scope, thus forming a runtime stack of regions and eliminating the need for garbage collection. We relax the requirement that region lifetimes be lexical. Rather, regions are allocated late and deallocated as early as possible by explicit memory operations. The placement of allocation and deallocation annotations is determined by solving a system of constraints that expresses all possible annotations. Experiments show that our approach reduces memory requirements significantly, in some cases asymptotically.


title: Deep Multi-Modal Image Correspondence Learning

abstract: Inference of correspondences between images from different modalities is an extremely important perceptual ability that enables humans to understand and recognize cross-modal concepts. In this paper, we consider an instance of this problem that involves matching photographs of building interiors with their corresponding floorplan. This is a particularly challenging problem because a floorplan, as a stylized architectural drawing, is very different in appearance from a color photograph. Furthermore, individual photographs by themselves depict only a part of a floorplan (e.g., kitchen, bathroom, and living room). We propose the use of a number of different neural network architectures for this task, which are trained and evaluated on a novel large-scale dataset of 5 million floorplan images and 80 million associated photographs. Experimental evaluation reveals that our neural network architectures are able to identify visual cues that result in reliable matches across these two quite different modalities. In fact, the trained networks are able to even outperform human subjects in several challenging image matching problems. Our result implies that neural networks are effective at perceptual tasks that require long periods of reasoning even for humans to solve.


title: Distance based modeling of interactions in structured regression

abstract: Graphical models, as applied to multi-target prediction problems, commonly utilize interaction terms to impose structure among the output variables. Often, such structure is based on the assumption that related outputs need to be similar and interaction terms that force them to be closer are adopted. Here we relax that assumption and propose a feature that is based on distance and can adapt to ensure that variables have smaller or larger difference in values. We utilized a Gaussian Conditional Random Field model, where we have extended its originally proposed interaction potential to include a distance term. The extended model is compared to the baseline in various structured regression setups. An increase in predictive accuracy was observed on both synthetic examples and real-world applications, including challenging tasks from climate and healthcare domains.


title: Etymo: A New Discovery Engine for AI Research

abstract: We present Etymo (this https URL), a discovery engine to facilitate artificial intelligence (AI) research and development. It aims to help readers navigate a large number of AI-related papers published every week by using a novel form of search that finds relevant papers and displays related papers in a graphical interface. Etymo constructs and maintains an adaptive similarity-based network of research papers as an all-purpose knowledge graph for ranking, recommendation, and visualisation. The network is constantly evolving and can learn from user feedback to adjust itself.


title: Real time zero current detection with low quiescent current for synchronous DC-DC converter

abstract: This paper presents a real time zero current detecting (ZCD) method for synchronous DC-DC converter operating in discontinuous conduction mode (DCM). A comparator with adjustable offset is utilized to sense the polarity of the inductor current. By monitoring the state of the switching node through a flip-flop, the offset of the comparator is automatically adjusted to achieve ZCD. Since the flip-flop consumes no static bias current and the offset comparator has lower demands for static current than a high speed one, the quiescent power dissipation is reduced. In addition, since there is little static power losses, the sampling circuits can remain always on to realize a real time detection, which is sensitive to the changes of regulator conditions. The proposed ZCD method is implemented in a boost converter with 50-mΩ NMOS power stage. Measured accuracy of the detection is in order of <10 mA. With the ZCD method a maximum boost converter efficiency of about 92% can be achieved.


Retinal Image Analysis : A Review


title: A Vision-Based Approach for Rail Extraction and its Application in a Camera Pan–Tilt Control System

abstract: Rail extraction, i.e., determining the position of the rails ahead of a train, is one of the basic tasks of vision-based driver support in railways. This paper introduces an approach that extracts rails by matching edge features to candidate rail patterns modeled as sequences of parabola segments. Patterns are precomputed in a semiautomatic offline stage for areas near the camera and generated on the fly for more distant regions. Our approach was designed to address the challenges posed by the open environment without requiring explicit knowledge about train speed or camera parameters/position and running fast enough for practical use without specialized hardware. Evaluation was performed on hours of video captured under real operation conditions, considering the requirements of a system in which a camera with zoom lens mounted on a pan-tilt unit captures images from the area ahead with increased resolution.


title: Types of radical hysterectomies From Thoma Ionescu and Wertheim to present day

abstract: The treatment for cervical cancer is a complex, multidisciplinary issue, which applies according to the stage of the disease. The surgical elective treatment of cervical cancer is represented by the radical abdominal hysterectomy. In time, many surgeons perfected this surgical technique; the ones who stood up for this idea were Thoma Ionescu and Ernst Wertheim. There are many varieties of radical hysterectomies performed by using the abdominal method and some of them through vaginal and mixed way. Each method employed has advantages and disadvantages. At present, there are three classifications of radical hysterectomies which are used for the simplification of the surgical protocols: Piver-Rutledge-Smith classification which is the oldest, GCG-EORTC classification and Querlow and Morrow classification. The last is the most evolved and recent classification; its techniques can be adapted for conservative operations and for different types of surgical approaches: abdominal, vaginal, laparoscopic or robotic.


title: Is Huffman coding dead?

abstract: In recent publications about data compression, arithmetic codes are often suggested as the state of the art, rather than the more popular Huffman codes. While it is true that Huffman codes are not optimal in all situations, we show that the advantage of arithmetic codes in compression performance is often negligible. Referring also to other criteria, we conclude that for many applications, Huffman codes should still remain a competitive choice.


title: Adaptive Convolutional ELM For Concept Drift Handling in Online Stream Data

abstract: In big data era, the data continuously generated and its distribution may keep changes overtime. These challenges in online stream of data are known as concept drift. In this paper, we proposed the Adaptive Convolutional ELM method (ACNNELM) as enhancement of Convolutional Neural Network (CNN) with a hybrid Extreme Learning Machine (ELM) model plus adaptive capability. This method is aimed for concept drift handling. We enhanced the CNN as convolutional hiererchical features representation learner combined with Elastic ELM (E$^2$LM) as a parallel supervised classifier. We propose an Adaptive OS-ELM (AOS-ELM) for concept drift adaptability in classifier level (named ACNNELM-1) and matrices concatenation ensembles for concept drift adaptability in ensemble level (named ACNNELM-2). Our proposed Adaptive CNNELM is flexible that works well in classifier level and ensemble level while most current methods only proposed to work on either one of the levels. ::: We verified our method in extended MNIST data set and not MNIST data set. We set the experiment to simulate virtual drift, real drift, and hybrid drift event and we demonstrated how our CNNELM adaptability works. Our proposed method works well and gives better accuracy, computation scalability, and concept drifts adaptability compared to the regular ELM and CNN. Further researches are still required to study the optimum parameters and to use more varied image data set.


title: On the Importance of Synchronization Primitives with Low Consensus Numbers

abstract: The consensus number of a synchronization primitive is the maximum number of processes for which the primitive can solve consensus. This has been the traditional measure of power of a synchronization primitive. Thus, the compare-and-swap primitive, which has infinite consensus number, is considered most powerful and has been the primitive of choice for implementing concurrent data structures. In this work, we show that the synchronization primitives with low consensus numbers can also be potentially powerful by using them along with the compare-and-swap primitive to design an O (√n) time wait-free and linearizable concurrent queue. The best known time bound for a wait-free and linearizable concurrent queue using only the compare-and-swap primitive is O(n). Here, n is the total number of processes that can access the queue. The queue object maintains a sequence of elements and supports the operations enqueue(x) and dequeue(). The wait-free property implies that every call to enqueue(x) and dequeue() finishes in a bounded number of steps irrespective of the schedule of other n --1 processes. The linearizable property implies that the enqueue(x) and dequeue() calls appear to be instantaneously applied within the duration of respective calls. We design a wait-free and a linearizable concurrent queue using shared memory registers that support the compare-and-swap primitive and two other primitives of consensus number one and two respectively. The enqueue(x) and dequeue() operations take O (√n) steps each. The total number of registers required are O(nm) of O (max{log n, log m }) bits each, where m is a bound on the total number of enqueue(x) operations.


title: Detection of Retinal Vessel Bifurcations by Means of Multiple Orientation Estimation Based on Regularized Morphological Openings

abstract: This paper describes an approach to detect vessel bifurcations and crossovers in retinal images. This approach is based on an novel method to estimate multiple orientations at each pixel of a gray image. The main orientations are provided by directional openings whose outputs are regularized in order to extend the orientation information to the whole image. The detection of vessel bifurcations is based on the coexistence of two or more than two different main orientations in the same pixel. Results on retinal images show the robustness and accuracy of the proposed method to detect vessel bifurcations.


title: URL normalization for de-duplication of web pages

abstract: Presence of duplicate documents in the World Wide Web adversely affects crawling, indexing and relevance, which are the core building blocks of web search. In this paper, we present a set of techniques to mine rules from URLs and utilize these learnt rules for de-duplication using just URL strings without fetching the content explicitly. Our technique is composed of mining the crawl logs and utilizing clusters of similar pages to extract specific rules from URLs belonging to each cluster. Preserving each mined rules for de-duplication is not efficient due to the large number of specific rules. We present a machine learning technique to generalize the set of rules, which reduces the resource footprint to be usable at web-scale. The rule extraction techniques are robust against web-site specific URL conventions. We demonstrate the effectiveness of our techniques through experimental evaluation.


title: 3D Snap Rounding

abstract: Let PP\mathcal{P} be a set of nnn polygons in R3R3\mathbb{R}^3, each of constant complexity and with pairwise disjoint interiors. We propose a rounding algorithm that maps PP\mathcal{P} to a simplicial complex QQ\mathcal{Q} whose vertices have integer coordinates. Every face of PP\mathcal{P} is mapped to a set of faces (or edges or vertices) of QQ\mathcal{Q} and the mapping from PP\mathcal{P} to QQ\mathcal{Q} can be done through a continuous motion of the faces such that (i) the L∞L∞L_\infty Hausdorff distance between a face and its image during the motion is at most 3/2 and (ii) if two points become equal during the motion, they remain equal through the rest of the motion. In the worse the size of QQ\mathcal{Q} is O(n15)O(n15)O(n^{15}) and the time complexity of the algorithm is O(n19)O(n19)O(n^{19}) but, under reasonable hypotheses, these complexities decrease to O(n5)O(n5)O(n^{5}) and O(n6n−−√)O(n6n)O(n^{6}\sqrt{n}).


title: From GPS Traces to a Routable Road Map

abstract: This paper presents a method for automatically converting raw GPS traces from everyday vehicles into a routable road network. The method begins by smoothing raw GPS traces using a novel aggregation technique. This technique pulls together traces that belong on the same road in response to simulated potential energy wells created around each trace. After the traces are moved in response to the potential fields, they tend to coalesce into smooth paths. To help adjust the parameters of the constituent potential fields, we present a theoretical analysis of the behavior of our algorithm on a few different road configurations. With the resulting smooth traces, we apply a custom clustering algorithm to create a graph of nodes and edges representing the road network. We show how this network can be used to plan reasonable driving routes, much like consumer-oriented mapping Web sites. We demonstrate our algorithms using real GPS data collected on public roads, and we evaluate the effectiveness of our approach on public roads, and we evaluate the effectiveness of our approach by comparing the route planning results suggested by our generated graph to a commercial route planner.


title: Relationship between the Manner of Mobile Phone Use and Depression, Anxiety, and Stress in University Students

abstract: Objectives: There is insufficient evidence regarding the potential risk of mobile phone use on mental health. Therefore, the aim of this research was to examine the relationship between mobile phone use and mental health by measuring the levels of depression, anxiety, and stress among university students in Serbia and Italy. Methods: This cross-sectional study was carried out at two distinguished universities in Serbia and Italy from March to May of the 2015/2016 academic year and included 785 students of both genders. The questionnaire was compiled and developed from different published sources regarding the manner and intensity of mobile phone use, along with the Depression Anxiety Stress Scale (DASS 42) for measuring psychological health. The statistical analysis of the data included the application of binary logistic regression and correlation tests. Results: Statistical analysis indicates that anxiety symptoms are somewhat more present in younger students (odds ratio (OR) = 0.86, 95% confidence interval (CI): 0.76–0.96), in those who send more text messages SMSs (OR = 1.15, 95% CI: 1.11–1.31), and in those who browse the internet less frequently (OR = 0.84, 95% CI: 0.73–0.95). Stress is more common in students who make fewer calls a day (OR = 0.79, 95% CI: 0.64–0.97), as well in those who spend more time talking on the mobile phone per day (OR = 1.28, 95% CI: 1.12–1.56). The strongest predictor of high stress levels was keeping the mobile phone less than 1 m away during sleeping (OR = 1.48, 95% CI: 1.12–2.08). Conclusions: The results indicated that the intensity and modality of mobile phone use could be a factor that can influence causal pathways leading to mental health problems in the university student population.


title: Exact indexing of dynamic time warping

abstract: The problem of indexing time series has attracted much interest. Most algorithms used to index time series utilize the Euclidean distance or some variation thereof. However, it has been forcefully shown that the Euclidean distance is a very brittle distance measure. Dynamic time warping (DTW) is a much more robust distance measure for time series, allowing similar shapes to match even if they are out of phase in the time axis. Because of this flexibility, DTW is widely used in science, medicine, industry and finance. Unfortunately, however, DTW does not obey the triangular inequality and thus has resisted attempts at exact indexing. Instead, many researchers have introduced approximate indexing techniques or abandoned the idea of indexing and concentrated on speeding up sequential searches. In this work, we introduce a novel technique for the exact indexing of DTW. We prove that our method guarantees no false dismissals and we demonstrate its vast superiority over all competing approaches in the largest and most comprehensive set of time series indexing experiments ever undertaken.


title: HPCS 2011 tutorials: Tutorial I: Distributed software transactional memories: Foundations, algorithms and tools

abstract: Parallel programming (PP) used to be an area once confined to scientific and high-performance computing applications. However, with the proliferation of multicore processors, parallel programming has definitely become a mainstream concern. Transactional Memories (TMs) answer the need to find a better programming model for PP, capable of boosting developers' productivity and allowing ordinary programmers to unleash the power of parallel and distributed architectures avoiding the pitfalls of manual, lock based synchronization.


title: A SiGe MMIC 6-bit PIN diode phase shifter

abstract: A 6-bit PIN diode phase shifter has been successfully demonstrated at microwave frequencies in a SiGe bipolar technology. A post-silicon polymer dielectric interconnect technology is implemented to achieve low loss microstrip structures on the silicon substrate. The monolithic microwave integrated circuit exhibits flat phase shift, low VSWR, and low insertion loss variation, over the 7- to 11-GHz band. This phase shifter demonstrates the feasibility of integrating SiGe technology into microwave systems.


title: In search of durable positive psychology interventions: Predictors and consequences of long-term positive behavior change.

abstract: A number of positive psychology interventions have successfully helped people learn skills for improving mood and building personal resources (e.g., psychological resilience and social support). However, little is known about whether intervention activities remain effective in the long term, or whether new resources are maintained after the intervention ends. We address these issues in a 15-month follow-up survey of participants from a loving-kindness meditation intervention. Many participants continued to practice meditation, and they reported more positive emotions (PEs) than those who had stopped meditating or had never meditated. All participants maintained gains in resources made during the initial intervention, whether or not they continued meditating. Continuing meditators did not differ on resources at baseline, but they did show more PE and a more rapid PE response to the intervention. Overall, our results suggest that positive psychology interventions are not just efficacious but of significant ...


title: Design of clock distribution networks in presence of process variations

abstract: Tolerance to process-induced skew remains one of the major concerns in the design of large-area and highspeed clock distribution networks. Indeed, despite the availability of some efficient exact-zero skew algorithms that can be applied during circuit design, the clock skew remains an important performance limiting factor after chip manufacturing, and is of increasing concern for sub-micron technologies. This tutorial reviews the importance of the problem, its sources, as well as typical examples of existing solutions. Solutions range from design rule strategies to built-in self-compensation methods.


title: The effect of a six-week osteopathic visceral manipulation in patients with non-specific chronic low back pain and functional constipation: study protocol for a randomized controlled trial

abstract: BACKGROUND ::: The aim of the proposed study is to analyze the effect of a six-week osteopathic visceral manipulation (OVM) program on the flexion-relaxation phenomenon in individuals with non-specific chronic low back pain (LBP) and functional constipation. ::: ::: ::: METHODS/DESIGN ::: An assessor-blinded, two-arm, randomized, placebo-controlled trial will be conducted. The sample will comprise 76 individuals with non-specific chronic LBP who have functional intestinal constipation, aged 18-65 years. The participants will be randomly allocated to two groups: (1) OVM and (2) sham OVM (SOVM). Evaluations will involve an interview, the Oswestry Disability Index, Fear-Avoidance Beliefs Questionnaire, functional constipation according to Rome III criteria, Biering-Sorensen test to normalize electromyographic (EMG) data, T12-L1 paraspinal level of the EMG signal during the flexion-relaxation phenomenon, 11-point numeric pain rating scale and fingertip-to-floor test. OVM and SOVM will be performed once per week for six weeks. Group 1 will receive OVM for 15 min and Group 2 will receive a sham visceral technique. Evaluations will be performed before and after the first session, after six weeks of treatment, and three months after randomization (follow-up). The findings will be analyzed statistically considering a 5% significance level (p ≤ 0.05). The limitation of the study is that the therapist will not be blinded. ::: ::: ::: DISCUSSION ::: This will be the first trial to analyze the clinical response and electromyographic signals during the flexion-relaxation phenomenon after OVM. ::: ::: ::: TRIAL REGISTRATION ::: Brazilian Clinical Trial Registry, RBR-7sx8j3 . Registered on 26 October 2017.


title: Segmentation of digitized dermatoscopic images by two-dimensional color clustering

abstract: In this paper a color-based segmentation scheme applied to dermatoscopic images is proposed. The RGB image is processed in the L* u* v* color space. A two-dimensional (2-D) histogram is computed with the two principal components and then smoothed with a Gaussian low-pass filter. The maxima location and a set of features are computed from the histogram contour lines. These features are the number of enclosed pixels, the surface of the base, and the height of the maximum. They allow for the selection of valid clusters which determine the number of classes. The image is then segmented using a modified version of the fuzzy c-means (FCM) clustering technique that takes into account the cluster orientation. Finally, the segmented image is cleaned using mathematical morphology, the region borders are smoothed, and small components are removed.


title: Page placement in hybrid memory systems

abstract: Phase-Change Memory (PCM) technology has received substantial attention recently. Because PCM is byte-addressable and exhibits access times in the nanosecond range, it can be used in main memory designs. In fact, PCM has higher density and lower idle power consumption than DRAM. Unfortunately, PCM is also slower than DRAM and has limited endurance. For these reasons, researchers have proposed memory systems that combine a small amount of DRAM and a large amount of PCM. In this paper, we propose a new hybrid design that features a hardware-driven page placement policy. The policy relies on the memory controller (MC) to monitor access patterns, migrate pages between DRAM and PCM, and translate the memory addresses coming from the cores. Periodically, the operating system updates its page mappings based on the translation information used by the MC. Detailed simulations of 27 workloads show that our system is more robust and exhibits lower energy-delay2 than state-of-the-art hybrid systems.


title: Markov topic models

abstract: We develop Markov topic models (MTMs), a novel family of generative probabilistic models that can learn topics simultaneously from multiple corpora, such as papers from different conferences. We apply Gaussian (Markov) random fields to model the correlations of different corpora. MTMs capture both the internal topic structure within each corpus and the relationships between topics across the corpora. We derive an efficient estimation procedure with variational expectation-maximization. We study the performance of our models on a corpus of abstracts from six different computer science conferences. Our analysis reveals qualitative discoveries that are not possible with traditional topic models, and improved quantitative performance over the state of the art.


title: Calibration of Confidence Measures in Speech Recognition

abstract: Most speech recognition applications in use today rely heavily on confidence measure for making optimal decisions. In this paper, we aim to answer the question: what can be done to improve the quality of confidence measure if we cannot modify the speech recognition engine? The answer provided in this paper is a post-processing step called confidence calibration, which can be viewed as a special adaptation technique applied to confidence measure. Three confidence calibration methods have been developed in this work: the maximum entropy model with distribution constraints, the artificial neural network, and the deep belief network. We compare these approaches and demonstrate the importance of key features exploited: the generic confidence-score, the application-dependent word distribution, and the rule coverage ratio. We demonstrate the effectiveness of confidence calibration on a variety of tasks with significant normalized cross entropy increase and equal error rate reduction.


title: The Smart Bookshelf: A Study of Camera Projector Scene Augmentation of an Everyday Environment

abstract: Recent research in projector-camera systems has overcome many of the obstacles to deploying and using intelligent displays for a wide range of applications. In parallel with these developments, projector costs continue to decline with corresponding increase in resolution, brightness and contrast ratio. In light of this trend, we are exploring the unique capabilities that camera-projector systems can offer to intelligent environments and ubiqutous computing. Our initial step towards environments that are intelligently augmented by projector-camera devices, is a smart bookshelf application. The system utilizes a camera pair and a projector to monitor the state of a real world library shelf. As books are added to the shelf a foreground detection algorithm which takes into account the projected information yields new pixels in each view that are then verified using a planar parallax constraint across both cameras to yield the book spine. Using a simple calibration scheme, the homography induced by the world plane in which book spines approximately lie is estimated. Users are then able to query for the presence of a book through a user interface and book spines are highlighted by transforming image pixels to their corresponding points in the projector's frame via the known homography. The system also can display the state of the bookshelf at any time in the past. Projected information can also be used to enhance the image-processing tasks at hand and we briefly explore this in this work.


title: Load-Commutated SCR Current-Source-Inverter-Fed Induction Motor Drive With Sinusoidal Motor Voltage and Current

abstract: Current source inverter (CSI) is an attractive solution in high-power drives. The conventional gate turn-off thyristor (GTO) based CSI-fed induction motor drives suffer from drawbacks such as low-frequency torque pulsation, harmonic heating, and unstable operation at low-speed ranges. These drawbacks can be overcome by connecting a current-controlled voltage source inverter (VSI) across the motor terminal replacing the bulky ac capacitors. The VSI provides the harmonic currents, which results in sinusoidal motor voltage and current even with the CSI switching at fundamental frequency. This paper proposes a CSI-fed induction motor drive scheme where GTOs are replaced by thyristors in the CSI without any external circuit to assist the turning off of the thyristors. Here, the current-controlled VSI, connected in shunt, is designed to supply the volt ampere reactive requirement of the induction motor, and the CSI is made to operate in leading power factor mode such that the thyristors in the CSI are autosequentially turned off. The resulting drive will be able to feed medium-voltage, high-power induction motors directly. A sensorless vector-controlled CSI drive based on the proposed configuration is developed. The experimental results from a 5 hp prototype are presented. Experimental results show that the proposed drive has stable operation throughout the operating range of speeds.


title: Axial stresses and texture development during the torsion testing of Al, Cu and α-Fe

abstract: Abstract Polycrystalline samples of Al, Cu and α-Fe of commercial purity were tested in torsion over the temperature range 20–400, 500 and 800°C, respectively. The axial forces induced were measured: at low temperatures and small strains, these were compressive in all three metals; as the temperature and strain were increased, they dropped to small compressive values (Al), or became tensile (Cu and α-Fe). The textures developed were also determined: at low temperatures and small strains, the {111} 〈110〉/{111} 〈110〉 set predominated in the Al, was present in conjunction with the {112} 〈110〉/{l12} 〈110〉 set in the Cu and the two sets {112} 〈111〉/{112}〈111〉 and {011}〈111〉/{OT1K111} were observed jointly in the α-Fe. As the temperature and strain were increased, the {112} 〈110〉/{112} 〈110〉 set became progressively more dominant in the Al; it, together with the {111} 〈110〉/{111} 〈110〉 in the Cu; and the single {112} 〈111〉 component in the α-Fe. Depending on the temperature and strain range, the individual ideal orientations are observed to be rotated about the r axis parallel to, or in the sense opposite to, the shear. It is shown that compressive axial stresses are associated with the rotation of {001} 〈110〉 in the sense of the shear, or with the rotation of {111} 〈110〉/{111} 〈110〉 in the sense opposed to the shear. Conversely, tensile axial stresses are associated with shear oriented rotations of the {111} 〈110〉/{111} 〈110〉 combination.


title: Assessment of pediatric dysphagia and feeding disorders: Clinical and instrumental approaches

abstract: Assessment of infants and children with dysphagia (swallowing problems) and feeding disorders involves significantly more considerations than a clinical observation of a feeding. In addition to the status of feeding in the child, considerations include health status, broad environment, parent–child interactions, and parental concerns. Interdisciplinary team approaches allow for coordinated global assessment and management decisions. Underlying etiologies or diagnoses must be delineated to every extent possible because treatment will vary according to history and current status in light of all factors that are often interrelated in complex ways. A holistic approach to evaluation is stressed with a primary goal for every child to receive adequate nutrition and hydration without health complications and with no stress to child or to caregiver. Instrumental swallow examinations that aid in defining physiological swallowing status are needed for some children. Successful oral feeding must be measured in quality of meal time experiences with best possible oral sensorimotor skills and safe swallowing while not jeopardizing a child's functional health status or the parent–child relationship. © 2008 Wiley-Liss, Inc. Dev Disabil Res Rev 2008;14:118–127.


title: A puzzle over several decades: eye anomalies with FRAS1 and STRA6 mutations in the same family.

abstract: Fraser syndrome (FS) and microphthalmia syndromic 9 (MCOPS9) are autosomal recessive conditions with distinct, and some overlapping features affecting the ocular, respiratory and cardiac systems. Mutations in FRAS1 and FREM2 occur in FS, and mutations in STRA6 occur in MCOPS9. We report two sibships, in the same family, where four deceased offspring had ocular, respiratory and cardiac abnormalities. Two sibs with microphthalmia had syndactyly and laryngeal stenosis, suggesting a clinical diagnosis of FS. Our results indicate that they were compound heterozygotes for novel FRAS1 mutations, p.Cys729Phe and p.Leu3813Pro. The other two sibs, first cousins to the first sib pair, had anophthalmia, lung hypoplasia and cardiac anomalies, suggesting a retrospective diagnosis of MCOPS9. Our results indicate compound heterozygous STRA6 mutations, a novel frameshift leading to p.Tyr18* and a p.Thr644Met mutation. The one surviving individual from these sibships is heterozygous for the p.Tyr18*STRA6 mutation and has bilateral ocular colobomata and microphthalmia. This work emphasises the need for careful phenotypic characterisation to determine genes for assessment in ocular syndromic conditions. It also indicates that heterozygous STRA6 mutations may rarely contribute to microphthalmia and coloboma.


title: Control of microgrids: Aspects and prospects

abstract: A microgrid is a controllable component of the smart grid defined as a part of distribution network capable of supplying its own local load even in the case of disconnection from the upstream network. Microgrids incorporate large amount of renewable and non-renewable distributed generation (DG) that are connected to the system either directly or by power electronics (PE) interface. The diversity of technologies used in DGs and loads, high penetration of DGs, economic operation of DGs, dynamics of low-inertia conventional DGs and PE interfaced inertialess DGs and smart operation by means of enhanced communication infrastructure have raised challenges in widespread utilization of microgrids as basis of smart grids. Power quality, protection, economic and secure operation, active management, communication, dynamics and control of microgrids are among the most important issues under research both in academy and industry. Technical concerns over dynamics of microgrids especially in autonomous (island) mode necessitate revision of current paradigms in control of energy systems. This paper addresses current challenges towards controlling microgrids and surveys dynamic modeling, stability and control of microgrids. Future trends in realizing smart grids through aggregation of microgrids and research needs in this path are discussed at the end of this paper.


title: Power control in AC autonomous and isolated microgrids with renewable energy sources and energy storage systems

abstract: This paper presents a new strategy to control the generated power that comes from the energy sources existing in autonomous and isolated Microgrids. In this particular study, the power system consists of a power electronic converter supplied by a battery bank, which is used to form the AC grid (grid former converter), an energy source based on a wind turbine with its respective power electronic converter (grid supplier converter), and the power consumers (loads). The main objective of this proposed strategy is to control the state of charge of the battery bank limiting the voltage on its terminals by controlling the power generated by the energy sources. This is done without using dump loads or any physical communication among the power electronic converters or the individual energy source controllers. The electrical frequency of the microgrid is used to inform to the power sources and their respective converters the amount of power they need to generate in order to maintain the battery-bank state of charge below or equal its maximum allowable limit. It is proposed a modified droop control to implement this task.


title: Training to Compete at Altitude:Natural Altitude or Simulated Live High:Train Low?

abstract: Purpose: To compare the effects of natural altitude training (NAT) and simulated (SIM) live high:train low altitude training on road-race walking performance (min), as well as treadmill threshold w...


title: A patient-calibrated individual wax-up as an essential tool for planning and creating a patient-oriented treatment concept for pathological tooth wear.

abstract: Tooth wear is generally a physiological process; however, it can also be a pathological condition associated with attrition, abrasion, and erosion processes in which the quantity of tooth loss is atypical for the patient's age. Tooth substance loss often causes functional problems, symptoms of discomfort/pain, and esthetic impairments. Patients presenting this condition frequently need restorative treatment, combined with an increase in the vertical dimension of occlusion (VDO). A diagnostic wax-up (DWU) provides assistance in determining a new occlusal plane and VDO, and is a fundamental tool considering the backward planning involved in the execution of a complex rehabilitation. In cases of severe tooth wear, preventive measures must be taken. Yet, when a restorative intervention is needed, the use of a DWU, in conjunction with a mock-up, helps to achieve a predictable and satisfactory outcome. This article presents a case report of a young female patient with pathological tooth wear, related symptomatology, and esthetic complaints. Initially, a DWU and a diagnostic mock-up were created. After esthetic and functional corrections, a second DWU was generated and transferred to the patient's mouth by means of a therapeutic mock-up. This mock-up was used as a trial restoration for the pretreatment phase, to evaluate the new VDO/esthetics/function and to guide tooth preparation. Lithium disilicate (LS2) occlusal onlays were used to stabilize the VDO, and anterior LS2 and feldspathic veneers, combined with direct composite restorations, were executed to reach the planned minimally invasive result.


title: Validation of electrical discharge machining electrodes made with rapid tooling technologies

abstract: Abstract Rapid tooling technologies allow tools and moulds to be manufactured in a short time and with complex geometry. The main aim of this research is to develop new electrical discharge machining (EDM) electrode testing and manufacturing by applying rapid prototyping (RP) and electroforming technologies. Copper electroformed shells allow complex electrodes to be obtained with a high dimensional precision and with the required texture according to the RP model. The main novelties of this work are the following: • A new copper electroformed shell testing methodology starting from plastic prototypes has been formulated. The composition, electrolytic bath additives, metallic structure of shells, internal stresses, hardness, pitting, dimensional precision and roughness relating to the model have been analysed. • A new tool for copper shells subjected to the EDM machine has been designed. Standardization of these tools is very important for their industrial viability and it is possible to assemble different shells in the same standard tool in a few seconds. • Different manufactured electrodes have been tested in an EDM machine and compared with conventional electrolytic copper electrodes. Results have shown good behaviour relative to conventional electrodes. Lower weight and better refrigeration conditions are also an advantage.


title: Anonymous and Lightweight Authentication for Secure Vehicular Networks

abstract: Authentication is an important issue in vehicular ad hoc network. However, existing studies have not addressed some issues like efficiency and anonymity. In this paper, we propose an anonymous and lightweight authentication based on smart card (ASC) protocol to address this issue. To accomplish this goal, ASC employs low-cost cryptographic operations to authenticate the legitimacy of users (vehicles) and validation of data messages. Compared to existing methods, our protocol can reduce more than 50% of the cost in terms of communication and computational cost. A login identity, which is changed dynamically, is proposed to prevent an attacker from linking a target vehicle with the specific identity. Thus, our protocol can be anonymous. In addition, ASC provides a method for password change, which does not rely on the trusted authority. Thus, it can resist offline password guessing attack. Finally, a formal security model is designed to prove that our protocol is secure under the assumption of the computational Diffie–Hellman problem. The simulations further illustrate that the proposed ASC has superior performance in terms of communication/computational cost, packet loss ratio, latency, etc.


title: INFLUENCE OF SALINITY ON THE HABITAT USE OF OYSTER REEFS IN THREE SOUTHWEST FLORIDA ESTUARIES

abstract: Abstract To gauge the influence of salinity on the habitat value of oyster reefs, spatial and seasonal patterns of the presence of reef-resident fishes and decapods were assessed in the Caloosahatchee, Estero, and Faka-Union estuaries of Southwest Florida. Lift nets (1 m2) containing 5 L of oyster clusters were deployed on intertidal reefs at three sites along the salinity gradient of each estuary. Nets were deployed during three seasonally dry and three seasonally wet months for a period of 30 d. Oyster densities were estimated at each site and a number of community metrics were calculated as a measure of habitat use (e.g., organism density, biomass, diversity, dominance, richness). Several metrics increased downstream in one or more systems (e.g., organism density, biomass, diversity) and in general appeared to be more related to salinity than to the density of living oysters present. Although organism density was higher during the wet season for all three systems, biomass was higher during the dry seas...


title: Developing adaptive exergames for adolescent children

abstract: Thanks to progression in ubiquitous technologies, exergames have emerged with the potential to motivate and facilitate exercise within an enjoyable context. While early research has shown the potential of the genre, little work has been done on systems that specifically target adolescent children, with their unique requirements and needs. In order to develop well suited exergames, capable of adapting to the situation of the player, work must me done to better understand the exergame experience. In this research we investigate how different demographics (gender, gaming backgrounds, exercise backgrounds) of adolescent children react to an exergame in order to begin understanding what contributes to an affective exergame experience, and how this differs between users. This work forms the first steps in modelling children within exergames with the goal of developing systems capable of adapting to the unique needs of the player.


title: Compact implementation of SHA3-512 on FPGA

abstract: In this work we present a compact design of newly selected Secure Hash Algorithm (SHA-3) on Xilinx Field Programable Gate Array (FPGA) device Virtex-5. The design is logically optimized for area efficiency by merging Rho, Pi and Chi steps of algorithm into single step. By logically merging these three steps we save 16 % logical resources for overall implementation. It in turn reduced latency and enhanced maximum operating frequency of design. It utilizes only 240 Slices and has frequency of 301.02 MHz. Comparing the results of our design with the previously reported FPGA implementations of SHA3-512, our design shows the best throughput per slice (TPS) ratio of 30.1.


title: Learning Analytics Architecture to Scaffold Learning Experience through Technology-based Methods

abstract: The challenge of delivering personalized learning experiences is often increased by the size of classrooms and online learning communities. Serious Games (SGs) are increasingly recognized for their potential to improve education. However, the issues related to their development and their level of effectiveness can be seriously affected when brought too rapidly into growing online learning communities. Deeper insights into how the students are playing is needed to deliver a comprehensive and intelligent learning framework that facilitates better understanding of learners' knowledge, effective assessment of their progress and continuous evaluation and optimization of the environments in which they learn. This paper discusses current SOTA and aims to explore the potential in the use of games and learning analytics towards scaffolding and supporting teaching and learning experience. The conceptual model (ecosystem and architecture) discussed in this paper aims to highlight the key considerations that may advance the current state of learning analytics, adaptive learning and SGs, by leveraging SGs as an suitable medium for gathering data and performing adaptations.


title: Detection of ulcerative colitis severity in colonoscopy video frames

abstract: Ulcerative colitis (UC) is a chronic inflammatory disease characterized by periods of relapses and remissions affecting more than 500,000 people in the United States. The therapeutic goals of UC are to first induce and then maintain disease remission. However, it is very difficult to evaluate the severity of UC objectively because of non-uniform nature of symptoms associated with UC, and large variations in their patterns. To address this, we objectively measure and classify the severity of UC presented in optical colonoscopy video frames based on the image textures. To extract distinct textures, we are using a hybrid approach in which a new proposed feature based on the accumulation of pixel value differences is combined with an existing feature such as LBP (Local Binary Pattern). The experimental results show the hybrid method can achieve more than 90% overall accuracy.


title: Millimeter-wave Gbps Broadband Evolution towards 5G: Fixed Access and Backhaul

abstract: As wireless communication evolves towards 5G, both fixed broadband and mobile broadband will play a crucial part in providing the Gbps infrastructure for a connected society. This paper proposes a Millimeter-wave Gbps Broadband (MGB) system as the solution to two critical problems in this evolution: last-mile access for fixed broadband and small cell backhaul for mobile broadband. The key idea is to use spectrum that is already available in the millimeter wave bands for fixed wireless access with optimized dynamic beamforming and massive MIMO infrastructure to achieve high capacity with wide area coverage. This paper explains the MGB concept and describes potential array architectures for realizing the system. Simulations demonstrate that with 500 MHz of bandwidth (at 39 GHz band) and 28 dBm transmission power (55 dBm EIRP), it is possible to provide more than 11 Gbps backhaul capacity for 96 small cells within 1-km radius.


title: 1 Reverse Engineering of Real PCB Level Design Using VERILOG HDL

abstract: The repair or replacement of components nearing obsolescence and the lack of accuracy in technical information is a very common problem. Updating these systems is possible now with sophisticated CAE tools and the Hardware Description Languages. Here we consider the conversion process of a real board design from TTL implementation to newer technology. This process is performed through an Automatic Verilog HDL Model Generator, which includes an image analysis system, for component identification(integrated circuits) and their connections. On the basis of the information obtained, the system is able to generate a circuit graph that corresponds to a primitive schematic circuit of the board. The circuit graph is translated to VERILOG HDL. The tests were performed in Verilog XL simulator. Therefore the system is capable to reverse engineer a board level design performed with a nondestructive procedure.


title: Does Food Color Influence Taste and Flavor Perception in Humans

abstract: In this paper, we review the empirical literature concerning the important question of whether or not food color influences taste and flavor perception in humans. Although a superficial reading of the literature on this topic would appear to give a somewhat mixed answer, we argue that this is, at least in part, due to the fact that many researchers have failed to distinguish between two qualitatively distinct research questions. The first concerns the role that food coloring plays in the perception of the intensity of a particular flavor (e.g., strawberry, banana, etc.) or taste attribute (e.g., sweetness, saltiness, etc.). The second concerns the role that food coloring plays in the perception of flavor identity. The empirical evidence regarding the first question is currently rather ambiguous. While some researchers have reported a significant crossmodal effect of changing the intensity of a food or drink’s coloring on people’s judgments of taste or flavor intensity, many others have failed to demonstrate any such effect. By contrast, the research findings concerning the second question clearly support the view that people’s judgments of flavor identity are often affected by the changing of a food or drink’s color (be it appropriate, inappropriate, or absent). We discuss the possible mechanisms underlying these crossmodal effects and suggest some of the key directions for future research in order to move our understanding in this area forward.


title: Bipolar disorder and the endocannabinoid system.

abstract: OBJECTIVE ::: Bipolar disorder (BD) is a debilitating, lifelong neuropsychiatric illness characterised by unsteady mood states which vacillate from (hypo)mania to depression. Despite the availability of pharmaceutical agents which can be effective in ameliorating the acute affective symptoms and prevent episodic relapse, BD is inadequately treated in a subset of patients. The endocannabinoid system (ECS) is known to exert neuromodulatory effects on other neurotransmitter systems critical in governing emotions. Several studies ranging from clinical to molecular, as well as anecdotal evidence, have placed a spotlight on the potential role of the ECS in the pathophysiology of BD. In this perspective, we present advantages and disadvantages of cannabis use in the management of illness course of BD and provide mechanistic insights into how this system might contribute to the pathophysiology of BD. ::: ::: ::: RESULTS ::: We highlight the putative role of selective cannabinoid receptor 2 (CB2) agonists in BD and briefly discuss findings which provide a rationale for targeting the ECS to assuage the symptoms of BD. Further, data encourage basic and clinical studies to determine how cannabis and cannabinoids (CBs) can affect mood and to investigate emerging CB-based options as probable treatment approaches. ::: ::: ::: CONCLUSION ::: The probable role of the ECS has been almost neglected in BD; however, from data available which suggest a role of ECS in mood control, it is justified to support conducting comprehensive studies to determine whether ECS manipulation could positively affect BD. Based on the limited available data, we suggest that activation of CB2 may stabilise mood in this disorder.


title: Enforcing network-wide policies in the presence of dynamic middlebox actions using flowtags

abstract: Middleboxes provide key security and performance guarantees in networks. Unfortunately, the dynamic traffic modifications they induce make it difficult to reason about network management tasks such as access control, accounting, and diagnostics. This also makes it difficult to integrate middleboxes into SDN-capable networks and leverage the benefits that SDN can offer. ::: ::: In response, we develop the FlowTags architecture. FlowTags-enhanced middleboxes export tags to provide the necessary causal context (e.g., source hosts or internal cache/miss state). SDN controllers can configure the tag generation and tag consumption operations using new FlowTags APIs. These operations help restore two key SDN tenets: (i) bindings between packets and their "origins," and (ii) ensuring that packets follow policy-mandated paths. ::: ::: We develop new controller mechanisms that leverage FlowTags. We show the feasibility of minimally extending middleboxes to support FlowTags. We also show that FlowTags imposes low overhead over traditional SDN mechanisms. Finally, we demonstrate the early promise of FlowTags in enabling new verification and diagnosis capabilities.


title: Vision-based approach towards lane line detection and vehicle localization

abstract: Localization of the vehicle with respect to road lanes plays a critical role in the advances of making the vehicle fully autonomous. Vision based road lane line detection provides a feasible and low cost solution as the vehicle pose can be derived from the detection. While good progress has been made, the road lane line detection has remained an open one, given challenging road appearances with shadows, varying lighting conditions, worn-out lane lines etc. In this paper, we propose a more robust vision-based approach with respect to these challenges. The approach incorporates four key steps. Lane line pixels are first pooled with a ridge detector. An effective noise filtering mechanism will next remove noise pixels to a large extent. A modified version of sequential RANdom Sample Consensus) is then adopted in a model fitting procedure to ensure each lane line in the image is captured correctly. Finally, if lane lines on both sides of the road exist, a parallelism reinforcement technique is imposed to improve the model accuracy. The results obtained show that the proposed approach is able to detect the lane lines accurately and at a high success rate compared to current approaches. The model derived from the lane line detection is capable of generating precise and consistent vehicle localization information with respect to road lane lines, including road geometry, vehicle position and orientation.


Introduction to Convolutional Neural Networks


title: A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure

abstract: For many complex diseases, there is a wide variety of ways in which an individual can manifest the disease. The challenge of personalized medicine is to develop tools that can accurately predict the trajectory of an individual's disease, which can in turn enable clinicians to optimize treatments. We represent an individual's disease trajectory as a continuous-valued continuous-time function describing the severity of the disease over time. We propose a hierarchical latent variable model that individualizes predictions of disease trajectories. This model shares statistical strength across observations at different resolutions-the population, subpopulation and the individual level. We describe an algorithm for learning population and subpopulation parameters offline, and an online procedure for dynamically learning individual-specific parameters. Finally, we validate our model on the task of predicting the course of interstitial lung disease, a leading cause of death among patients with the autoimmune disease scleroderma. We compare our approach against state-of-the-art and demonstrate significant improvements in predictive accuracy.


title: Stacking Classifiers For Anti-Spam Filtering Of E-Mail

abstract: We evaluate empirically a scheme for combining classifiers, known as stacked generalization, in the context of anti-spam filtering, a novel cost-sensitive application of text categorization. Unsolicited commercial e-mail, or "spam", floods mailboxes, causing frustration, wasting bandwidth, and exposing minors to unsuitable content. Using a public corpus, we show that stacking can improve the efficiency of automatically induced anti-spam filters, and that such filters can be used in real-life applications.


title: The ant larvae of the myrmicine tribe Solenopsidini.

abstract: nests in natural plant cavities in humid neotropical forests; the sexual larvae are markedly different from the worker larvae. Several genera are workerless social parasites: Anergates, Anergatides, Bruchomyrma, Epixenus, Epoecus, Hagioxenus, Trichomyrmex and Wheeleriella. The largest genus in the tribe is MVionomorium; next is Solenopsis. These two genera have provided mankind with several of its annoying pests. Three are common household pests in the United States: Monomorium minimum, M. pharaonis and Solenopsis molesta. Concerning the polymorphic species, Solenopsis geminata and S. saevissima, Creighton2 has written: Fire ants of another species (Solenopsis xyloni) are similarly injurious and sometimes also become house pests. Several of the small monomorphic species of Solenopsis are known to be thief anits; they nest near the galleries of larger ants and steal the food and brood of the latter. Wheeler3 once wrote that the tribe Solenopsidini was "very unsatisfactorily defined." After studying the larvae, we heartily agree, for they are a very heterogeneous lot. To be sure, the larvae of Monomorium s. str. can scarcely be distinguished from those of Solenopsis; but aside from these two, we can detect no afrinities. The nine genera studied might just as well be in eight different tribes. We have not been able to find any characters common to all the genera; hence we have not even attempted a characterization of the tribe.


title: 25 A Methodology for the Extraction of Reader’s Emotional State Triggered from Text Typography

abstract: Writing is employed by humans in order to communicate, exchange ideas or store facts and descriptions. A well known Latin phrase is “verba volant, scripta manent” i.e. “spoken words fly away, written words remain”. Humans in prehistoric years, used figurations to describe several events and express their fear or their admiration, the ancient Egyptians used papyrus to write down their ideas and the Chinese, in 11th Century, went beyond handwriting using typography with moveable type to create multiple copies of their documents. Through centuries typography has evolved and nowadays is one of the major manners to exchange ideas and information. Using computers, typography and the way we write has changed radically. We have a plethora of software tools, e.g. for writing a plain text (like NotePad in MS Windows), word processors (e.g. Open Office) for text editing as well as for more elegant visual appearance of the documents and professional tools for the creation of posters, advertisements e.t.c. (e.g. Adobe’s Tools and Editors). Utilising these tools, computer users have the ability not only to write a plain text, but also to format the text and arrange it in the page. In newspapers, for example, the page designer distinguishes the title from the body of text at the top of the page or the article, with larger font size. Also, when an editor wishes to emphasize a specific word or phrase he uses bold or italics typesetting. A writer can convey a message, a felling or an idea not only by the meaning of the content but also by the way the text is visually presented to the reader. Page layout affects the way a newspaper is read (Holmqvist & Wartenberg, 2005; Holmberg, 2004; Kupper, 1989; Wartenberg & Holmqvist, 2005). The use of the WWW and the web page creation and design, introduced a new perception for the meaning of documents and publishing. In web pages, the text and background color combinations have impact on the readability and aesthetics (Porat et al., 2007; Richard & Patrick, 2004; Hill & Scharff, 1997) and a well designed graphical web document can be reader friendly (Borchers et al., 1996). Humans express their emotions in every personal or social occasion. Everything they do or make is followed by or follows an emotional expression. For example, some people are afraid of being among many people. So they act accordingly by avoiding congestion. If they cannot, they are feeling anxious and nervous. Another example of the role of the emotions in


title: Findings of the 2015 Workshop on Statistical Machine Translation

abstract: This paper presents the results of the WMT15 shared tasks, which included a standard news translation task, a metrics task, a tuning task, a task for run-time estimation of machine translation quality, and an automatic post-editing task. This year, 68 machine translation systems from 24 institutions were submitted to the ten translation directions in the standard translation task. An additional 7 anonymized systems were included, and were then evaluated both automatically and manually. The quality estimation task had three subtasks, with a total of 10 teams, submitting 34 entries. The pilot automatic postediting task had a total of 4 teams, submitting 7 entries.


title: Lattice-based motion planning for a general 2-trailer system

abstract: Motion planning for a general 2-trailer system poses a hard problem for any motion planning algorithm and previous methods have lacked any completeness or optimality guarantees. In this work we present a lattice-based motion planning framework for a general 2-trailer system that is resolution complete and resolution optimal. The solution will satisfy both differential and obstacle imposed constraints and is intended as a driver support system to automatically plan complicated maneuvers in backward and forward motion. The proposed framework relies on a precomputing step that is performed offline to generate a finite set of kinematically feasible motion primitives. These motion primitives are then used to create a regular state lattice that can be searched for a solution using standard graph-search algorithms. To make this graph-search problem tractable for real-time applications a novel parametrization of the reachable state space is proposed where each motion primitive moves the system from and to a selected set of circular equilibrium configurations. The approach is evaluated over three different scenarios and impressive real-time performance is achieved.


title: Deep Learning Advances on Different 3D Data Representations: A Survey.

abstract: 3D data is a valuable asset in the field of computer vision as it provides rich information about the full geometry of sensed objects and scenes. With the recent availability of large 3D datasets and the increase in computational power, it is today possible to consider applying deep learning to learn specific tasks on 3D data such as segmentation, recognition and correspondence. Depending on the considered 3D data representation, different challenges may be foreseen in using existent deep learning architectures. In this paper, we provide a comprehensive overview of various 3D data representations highlighting the difference between Euclidean and non-Euclidean ones. We also discuss how deep learning methods are applied on each representation, analyzing the challenges to overcome.


title: Fast prototyping of a DSP core

abstract: This paper describes the UTS-DSP (University of Tehran and SAMA Research Center) IC design process. Using CISC architecture, UTS-DSP has an efficient pipeline to cover a complete instruction set as a high-performance DSP processor. This paper has mainly focused on major parts of UTS-DSP design process, modeling and verification as a fast and efficient process to design DSP cores. Modeling of the UTS-DSP is done by VHDL hardware description language and then synthesized for test implementation via FPGAs. A dedicated hardware has been developed for FPGA implementation with 250,000 logic gates and over five million memory bits.


title: Assessment of the dimensionality of the Wijma delivery expectancy/experience questionnaire using factor analysis and Rasch analysis

abstract: Background ::: Fear of childbirth has negative consequences for a woman's physical and emotional wellbeing. The most commonly used measurement tool for childbirth fear is the Wijma Delivery Expectancy Questionnaire (WDEQ-A). Although originally conceptualized as unidimensional, subsequent investigations have suggested it is multidimensional. This study aimed to undertake a detailed psychometric assessment of the WDEQ-A; exploring the dimensionality and identifying possible subscales that may have clinical and research utility.


title: NORTH- HOLLAND String Alignment With Substitution, Insertion, Deletion, Squashing, and Expansion Operations*

abstract: Abstract Let X and Y be any two strings of finite length. The problem of transforming X to Y using the edit operations of substitution, deletion, and insertion has been extensively studied in the literature. The problem can be solved in quadratic time if the edit operations are extended to include the operation of transposition of adjacent characters, and is NP-complete if the characters can be edited repeatedly. In this paper we consider the problem of transforming X to Y when the set of edit operations is extended to include the squashing and expansion operations. Whereas in the squashing operation two (or more) contiguous characters of X can be transformed into a single character of Y , in the expansion operation a single character in X may be expanded into two or more contiguous characters of Y . These operations are typically found in the recognition of cursive script. A quadratic time solution to the problem has been presented. This solution is optimal for the infinite-alphabet case. The strategy to compute the sequence of edit operations is also presented.


title: Aesthetic Emotions and Aesthetic People: Openness Predicts Sensitivity to Novelty in the Experiences of Interest and Pleasure

abstract: There is a stable relationship between the Openness/Intellect domain of personality and aesthetic engagement. However, neither of these are simple constructs and while the relationship exists process based evidence explaining the relationship is still lacking. The current research looked to clarify the relationship by evaluating the influence of the Openness and Intellect aspects on several different aesthetic emotions. Two studies looked at the between- and within-person differences in the emotions of interest, pleasure and confusion in response to visual art. The results suggest that Openness, as opposed to Intellect, was predictive of greater interest and pleasure, while both aspects explained less confusion. Differences in Openness were associated with within-person emotion appraisal contingencies, particularly greater novelty-interest and novelty-pleasure relationships. Those higher in Openness were particularly influenced by novelty in artworks. For pleasure this relationship suggested a different qualitative structure of appraisals. The appraisal of novelty is part of the experience of pleasure for those high in Openness, but not those low in Openness. This research supports the utility of studying Openness and Intellect as separate aspects of the broad domain and clarifies the relationship between Openness and aesthetic states in terms of within-person appraisal processes.


title: The C-loss function for pattern classification

abstract: This paper presents a new loss function for neural network classification, inspired by the recently proposed similarity measure called Correntropy. We show that this function essentially behaves like the conventional square loss for samples that are well within the decision boundary and have small errors, and L0 or counting norm for samples that are outliers or are difficult to classify. Depending on the value of the kernel size parameter, the proposed loss function moves smoothly from convex to non-convex and becomes a close approximation to the misclassification loss (ideal 0-1 loss). We show that the discriminant function obtained by optimizing the proposed loss function in the neighborhood of the ideal 0-1 loss function to train a neural network is immune to overfitting, more robust to outliers, and has consistent and better generalization performance as compared to other commonly used loss functions, even after prolonged training. The results also show that it is a close competitor to the SVM. Since the proposed method is compatible with simple gradient based online learning, it is a practical way of improving the performance of neural network classifiers. HighlightsWe propose a new classification method.The method is based on the recently proposed similarity measure called Correntropy.The method is robust against overfitting and less sensitive to system parameters.We obtain better performance as compared to several conventional classifiers.


A neurofuzzy color image segmentation method for wood surface defect detection


title: Association of genes to genetically inherited diseases using data mining

abstract: Although approximately one-quarter of the roughly 4,000 genetically inherited diseases currently recorded in respective databases (LocusLink, OMIM) are already linked to a region of the human genome, about 450 have no known associated gene. Finding disease-related genes requires laborious examination of hundreds of possible candidate genes (sometimes, these are not even annotated; see, for example, refs 3,4). The public availability of the human genome draft sequence has fostered new strategies to map molecular functional features of gene products to complex phenotypic descriptions, such as those of genetically inherited diseases. Owing to recent progress in the systematic annotation of genes using controlled vocabularies, we have developed a scoring system for the possible functional relationships of human genes to 455 genetically inherited diseases that have been mapped to chromosomal regions without assignment of a particular gene. In a benchmark of the system with 100 known disease-associated genes, the disease-associated gene was among the 8 best-scoring genes with a 25% chance, and among the best 30 genes with a 50% chance, showing that there is a relationship between the score of a gene and its likelihood of being associated with a particular disease. The scoring also indicates that for some diseases, the chance of identifying the underlying gene is higher.


title: A New Rank Based Version of the Ant System - A Computational Study

abstract: The ant system is a new meta-heuristic for hard combinatorial optimization problems. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem (TSP), but has been also successfully applied to problems such as quadratic assignment, job-shop scheduling, vehicle routing and graph coloring.In this paper we introduce a new rank based version of the ant system and present results of a computational study, where we compare the ant system with simulated annealing and a genetic algorithm on several TSP instances. It turns out that our rank based ant system can compete with the other methods in terms of average behavior, and shows even better worst case behavior. (author's abstract)


Neural Attention Reader for Video Comprehension


title: An Efficient Algorithm for Graph Isomorphism

abstract: A procedure for determining whether two graphs are isomorphic is described. During the procedure, from any given graph two graphs, the representative graph and the reordered graph, are derived. The representative graph is a homomorphic image of the original graph; the reordered graph is constructed from the representative graph to be isomorphic to the given graph. Unique labels are assigned to the vertices of both derived graphs. It follows that two repre- sentative graphs or two reordered graphs are isomorphic if and only if they are identical. A conjecture states that the representative graphs exhibit the automorphism partitioning of the given graph. The representative graphs form a necessity condition for isomorphism; namely, if the representative graphs are not identical, then the given graphs are not isomorphic. The converse is true for trees and follows from the conjecture for other types of graphs. It is also shown that the reordered graphs form a sufficiency condition for isomorphism; namely, if the reordered graphs are identical, then the given graphs are isomorphic. The converse follows from the conjecture. The time required to determine both derived graphs depends on a power of n, the order of the given graph. This power is a function of an adjacency property known as the strong regu- larity of the given graph. For graphs that do not contain a strongly regular transitive sub- graph, the power is, at worst, five.


title: Gene Selection for Cancer Classification using Support Vector Machines

abstract: DNA micro-arrays now permit scientists to screen thousands of genes simultaneously and determine whether those genes are active, hyperactive or silent in normal or cancerous tissue. Because these new micro-array devices generate bewildering amounts of raw data, new analytical methods must be developed to sort out whether cancer tissues have distinctive signatures of gene expression over normal tissues or other types of cancer tissues. ::: ::: In this paper, we address the problem of selection of a small subset of genes from broad patterns of gene expression data, recorded on DNA micro-arrays. Using available training examples from cancer and normal patients, we build a classifier suitable for genetic diagnosis, as well as drug discovery. Previous attempts to address this problem select genes with correlation techniques. We propose a new method of gene selection utilizing Support Vector Machine methods based on Recursive Feature Elimination (RFE). We demonstrate experimentally that the genes selected by our techniques yield better classification performance and are biologically relevant to cancer. ::: ::: In contrast with the baseline method, our method eliminates gene redundancy automatically and yields better and more compact gene subsets. In patients with leukemia our method discovered 2 genes that yield zero leave-one-out error, while 64 genes are necessary for the baseline method to get the best result (one leave-one-out error). In the colon cancer database, using only 4 genes our method is 98% accurate, while the baseline method is only 86% accurate.


title: Software Defined Network (SDN) Based Internet of Things (IoT): A Road Ahead

abstract: Internet of Things (IoT) and Software Defined Network (SDN) are two emerging technologies. The IoT aims to connect objects over the Internet and the SDN provides orchestration for network management by decoupling the control plane and the data plane. The number of connected objects is in billions, and its management and control is a complex task for a large distributed network. The SDN provides flexibility and programmability in the IoT network without troubling underlying architecture of existing implementations. In this paper, we study different IoT application and domains, and the generalized IoT-SDN solutions over the period of 2012-2016. Furthermore, this paper provides a critical view of the IoT and the SDN technologies, current trends in research and the futuristic contributing factors. A comparative analysis of the existing solutions of SDN-based IoT implementations provides an easy and concise view of the emerging trends.


title: Underwater Acoustic Target Tracking: A Review

abstract: Advances in acoustic technology and instrumentation now make it possible to explore marine resources. As a significant component of ocean exploration, underwater acoustic target tracking has aroused wide attention both in military and civil fields. Due to the complexity of the marine environment, numerous techniques have been proposed to obtain better tracking performance. In this paper, we survey over 100 papers ranging from innovative papers to the state-of-the-art in this field to present underwater tracking technologies. Not only the related knowledge of acoustic tracking instrument and tracking progress is clarified in detail, but also a novel taxonomy method is proposed. In this paper, algorithms for underwater acoustic target tracking are classified based on the methods used as: (1) instrument-assisted methods; (2) mode-based methods; (3) tracking optimization methods. These algorithms are compared and analyzed in the aspect of dimensions, numbers, and maneuvering of the tracking target, which is different from other survey papers. Meanwhile, challenges, countermeasures, and lessons learned are illustrated in this paper.


title: Automobile ECU Design to Avoid Data Tampering

abstract: Modern embedded vehicle systems are based on network architectures. Vulnerabilities from in-vehicle communications are significant. Privacy and security measures are required for vehicular Electronic Control Units (ECUs). We present a security vulnerability analysis, which shows that the vulnerability mainly lies in the ubiquitous on-board diagnostics II (OBD-II) interface and the memory configuration within ECU. Countermeasures using obfuscation and encryption techniques are introduced to protect ECUs from data sniffing and code tampering. A security scheme of deploying lures that look like ECU vulnerabilities to deceive lurking intruders into installing rootkits is proposed. We show that the interactions between the attacker and the system can be modeled as a Markov decision process (MDP).


title: Multisensory Flavor Perception

abstract: The perception of flavor is perhaps the most multisensory of our everyday experiences. The latest research by psychologists and cognitive neuroscientists increasingly reveals the complex multisensory interactions that give rise to the flavor experiences we all know and love, demonstrating how they rely on the integration of cues from all of the human senses. This Perspective explores the contributions of distinct senses to our perception of food and the growing realization that the same rules of multisensory integration that have been thoroughly explored in interactions between audition, vision, and touch may also explain the combination of the (admittedly harder to study) flavor senses. Academic advances are now spilling out into the real world, with chefs and food industry increasingly taking the latest scientific findings on board in their food design.


title: A targeted real-time early warning score (TREWScore) for septic shock

abstract: Sepsis is a leading cause of death in the United States, with mortality highest among patients who develop septic shock. Early aggressive treatment decreases morbidity and mortality. Although automated screening tools can detect patients currently experiencing severe sepsis and septic shock, none predict those at greatest risk of developing shock. We analyzed routinely available physiological and laboratory data from intensive care unit patients and developed "TREWScore," a targeted real-time early warning score that predicts which patients will develop septic shock. TREWScore identified patients before the onset of septic shock with an area under the ROC (receiver operating characteristic) curve (AUC) of 0.83 [95% confidence interval (CI), 0.81 to 0.85]. At a specificity of 0.67, TREWScore achieved a sensitivity of 0.85 and identified patients a median of 28.2 [interquartile range (IQR), 10.6 to 94.2] hours before onset. Of those identified, two-thirds were identified before any sepsis-related organ dysfunction. In comparison, the Modified Early Warning Score, which has been used clinically for septic shock prediction, achieved a lower AUC of 0.73 (95% CI, 0.71 to 0.76). A routine screening protocol based on the presence of two of the systemic inflammatory response syndrome criteria, suspicion of infection, and either hypotension or hyperlactatemia achieved a lower sensitivity of 0.74 at a comparable specificity of 0.64. Continuous sampling of data from the electronic health records and calculation of TREWScore may allow clinicians to identify patients at risk for septic shock and provide earlier interventions that would prevent or mitigate the associated morbidity and mortality.


title: ForeGraph: Exploring Large-scale Graph Processing on Multi-FPGA Architecture

abstract: The performance of large-scale graph processing suffers from challenges including poor locality, lack of scalability, random access pattern, and heavy data conflicts. Some characteristics of FPGA make it a promising solution to accelerate various applications. For example, on-chip block RAMs can provide high throughput for random data access. However, large-scale processing on a single FPGA chip is constrained by limited on-chip memory resources and off-chip bandwidth. Using a multi-FPGA architecture may alleviate these problems to some extent, while the data partitioning and communication schemes should be considered to ensure the locality and reduce data conflicts. In this paper, we propose ForeGraph, a large-scale graph processing framework based on the multi-FPGA architecture. In ForeGraph, each FPGA board only stores a partition of the entire graph in off-chip memory. Communication over partitions is reduced. Vertices and edges are sequentially loaded onto the FPGA chip and processed. Under our scheduling scheme, each FPGA chip performs graph processing in parallel without conflicts. We also analyze the impact of system parameters on the performance of ForeGraph. Our experimental results on Xilinx Virtex UltraScale XCVU190 chip show ForeGraph outperforms state-of-the-art FPGA-based large-scale graph processing systems by 4.54x when executing PageRank on the Twitter graph (1.4 billion edges). The average throughput is over 900 MTEPS in our design and 2.03x larger than previous work.


title: ANDRUBIS -- 1,000,000 Apps Later: A View on Current Android Malware Behaviors

abstract: Android is the most popular smartphone operating system with a market share of 80%, but as a consequence, also the platform most targeted by malware. To deal with the increasing number of malicious Android apps in the wild, malware analysts typically rely on analysis tools to extract characteristic information about an app in an automated fashion. While the importance of such tools has been addressed by the research community, the resulting prototypes remain limited in terms of analysis capabilities and availability. In this paper we present ANDRUBIS, a fully automated, publicly available and comprehensive analysis system for Android apps. ANDRUBIS combines static analysis with dynamic analysis on both Dalvik VM and system level, as well as several stimulation techniques to increase code coverage. With ANDRUBIS, we collected a dataset of over 1,000,000 Android apps, including 40% malicious apps. This dataset allows us to discuss trends in malware behavior observed from apps dating back as far as 2010, as well as to present insights gained from operating ANDRUBIS as a publicly available service for the past two years.


title: Success Factors in a Reward and Equity Based Crowdfunding Campaign

abstract: As the world changes, financial sector changes with it, and alternative finance emerge. Crowdfunding is part of this evolution and its use is becoming more widespread day by day. As more entrepreneurs and organizations seek crowdfunding to fund their ventures, and to solve the most important obstacle to achieve a successful crowdfunding campaign, which is not the information available about how to create a successful campaign, but rather its dispersion, it becomes of uttermost importance to create a framework to help them to succeed raising finance. It is, therefore, the main goal of this paper, to provide a valuable guide to help entrepreneurs in the hard task of raising finance through crowdfunding, mainly those using equity and reward crowdfunding. To accomplish the purposed goal, it is important to understand the underlying motivations of those investing in crowdfunding, in order to offer them what they seek and what motivates them. It is also essential to identify which kind of crowdfunding fits better the entrepreneur's goals and which one increases the likelihood of achieving them. Finally, is crucial to understand the specific success factors for a successful crowdfunding campaign. One of the main findings of this work, is that the motivations for investors in equity and reward crowdfunding are similar. This is very important, since it solves the problem of the scarcity of data for the equity model. With similar motivations it is possible to apply the data available for reward crowdfunding to equity crowdfunding, since both campaign can be design to answer the same needs and motivations.


title: Comparison of compression efficiency between HEVC/H.265 and VP9 based on subjective assessments

abstract: Current increasing effort of broadcast providers to transmit UHD (Ultra High Definition) content is likely to increase demand for ultra high definition televisions (UHDTVs). To compress UHDTV content, several alter- native encoding mechanisms exist. In addition to internationally recognized standards, open access proprietary options, such as VP9 video encoding scheme, have recently appeared and are gaining popularity. One of the main goals of these encoders is to efficiently compress video sequences beyond HDTV resolution for various scenarios, such as broadcasting or internet streaming. In this paper, a broadcast scenario rate-distortion performance analysis and mutual comparison of one of the latest video coding standards H.265/HEVC with recently released proprietary video coding scheme VP9 is presented. Also, currently one of the most popular and widely spread encoder H.264/AVC has been included into the evaluation to serve as a comparison baseline. The comparison is performed by means of subjective evaluations showing actual differences between encoding algorithms in terms of perceived quality. The results indicate a dominance of HEVC based encoding algorithm in comparison to other alternatives if a wide range of bit-rates from very low to high bit-rates corresponding to low quality up to transparent quality when compared to original and uncompressed video is considered. In addition, VP9 shows competitive results for synthetic content and bit-rates that correspond to operating points for transparent or close to transparent quality video.


U. S. business abroad and political risks


title: Semi-supervised Ensemble Learning with Weak Supervision for Biomedical Relationship Extraction

abstract: Natural language understanding research has recently shifted towards complex Machine Learning and Deep Learning algorithms. Such models often outperform their simpler counterparts significantly. However, their performance relies on the availability of large amounts of labeled data, which are rarely available. To tackle this problem, we propose a methodology for extending training datasets to arbitrarily big sizes and training complex, data-hungry models using weak supervision. We apply this methodology on biomedical relation extraction, a task where training datasets are excessively time-consuming and expensive to create, yet has a major impact on downstream applications such as drug discovery. We demonstrate in two small-scale controlled experiments that our method consistently enhances the performance of an LSTM network, with performance improvements comparable to hand-labeled training data. Finally, we discuss the optimal setting for applying weak supervision using this methodology.


SEQUENTIAL MINIMAL OPTIMIZATION IN SUPPORT VECTOR MACHINE