title: Ultra Fast H.264/AVC to HEVC Transcoder

abstract: The emerging High Efficiency Video Coding (HEVC) standard achieves significant performance improvement over H.264/AVC standard at a cost of much higher complexity. In this paper, we propose a ultra fast H.264/AVC to HEVC transcoder for multi-core processors implementing Wave front Parallel Processing (WPP) and SIMD acceleration, along with expedited motion estimation (ME) and mode decision (MD) by utilizing information extracted from the input H.264/AVC stream. Experiments using standard HEVC test bit streams show that the proposed transcoder achieves 70x speed up over the HEVC HM 8.1 reference software (including H.264 encoding) at very small rate distortion (RD) performance loss.


title: A simple speckle smoothing algorithm for synthetic aperture radar images

abstract: Speckles appearing in synthetic aperture radar (SAR) images are generated by the coherent processing of radar signals. Basically the speckles have the nature of a multiplicative noise. A simple and effective method of smoothing speckle-corrupted images by a digital computer is discussed, based on the recently developed sigma filter. The sigma filter is motivated by the sigma probability of a Gaussian distribution. The pixel to be processed is replaced by an advantage of those neighboring pixels having their gray level within two noise standard deviations from that of the concerned pixel. Consequently the speckles are suppressed without blurring edges and fine detail. Several Seasat SAR images are used for illustration, and comparisons are made with several noise-smoothing algorithms. Extensions of this algorithm to contrast enhancement and signal-dependent noise filtering are also presented. This algorithm is computationally efficient, and has the potential to achieve real or near real-time processing.


title: Application of Data Mining for Enterprise Digital Marketing Strategy Making

abstract: With the popularity of broadband Internet and the booming development of network technology in recent years, the traditional marketing is also gradually moving to digital marketing. The dissemination of information through the internet is different from traditional marketing. In today's competitive market, there are various products made by enterprises, how to stand out in a highly competitive environment, and how to go with marketing tactics and product through the product advertising to cause high degree of customer purchase intentions and interests effectively, is one of the important keys. Furthermore, due to the international business environment and intense competition, it is necessary to response and satisfies market and customer demand immediately, and use information technology to assist enterprises in doing business marketing. Therefore, in order to grasp market characteristics and consumer preferences to select the appropriate products marketing strategies. In this study, the structure of digital marketing is proposed aims to provide the enterprise relevant marketing information, to identify appropriate marketing practices of market segment, and thus to achieve the majority of the responses or purchase intention in marketing effectiveness.


title: Statistical selection of relevant subspace projections for outlier ranking

abstract: Outlier mining is an important data analysis task to distinguish exceptional outliers from regular objects. For outlier mining in the full data space, there are well established methods which are successful in measuring the degree of deviation for outlier ranking. However, in recent applications traditional outlier mining approaches miss outliers as they are hidden in subspace projections. Especially, outlier ranking approaches measuring deviation on all available attributes miss outliers deviating from their local neighborhood only in subsets of the attributes. In this work, we propose a novel outlier ranking based on the objects deviation in a statistically selected set of relevant subspace projections. This ensures to find objects deviating in multiple relevant subspaces, while it excludes irrelevant projections showing no clear contrast between outliers and the residual objects. Thus, we tackle the general challenges of detecting outliers hidden in subspaces of the data. We provide a selection of subspaces with high contrast and propose a novel ranking based on an adaptive degree of deviation in arbitrary subspaces. In thorough experiments on real and synthetic data we show that our approach outperforms competing outlier ranking approaches by detecting outliers in arbitrary subspace projections.


title: Adverse childhood experiences, epigenetics and telomere length variation in childhood and beyond: a systematic review of the literature.

abstract: A systematic review following PRISMA guidelines was conducted to answer the question: What epigenetic, telomeric and associated biological changes are associated with exposure to adverse childhood experiences (ACEs) in the under 12s? Using PRISMA guidelines, appropriate databases were searched. 190 papers were returned with 38 articles fully reviewed. Articles were each independently quality rated by two authors using the Crowe Critical Appraisal Tool and data were extracted. Of the 38 articles, 23 were rated as very high quality. Most study participants were adults (n = 7769) with n = 727 child participants. Only seven of the very/high-quality studies were prospective and involved children. Methylation was the most studied method of epigenetic modification. There is some evidence supporting epigenetic modification of certain markers in participants exposed to ACEs measured in adulthood. Research is lacking on non-coding aspects of the epigenome and on coding aspects other than DNA methylation. There is some evidence of a more powerful effect on telomere length if physical neglect was involved. Much further work is required to model biological and psychological effects of epigenetic changes during childhood using prospective study designs. The effect of ACEs on the cellular ageing process during childhood is inadequately investigated and relies solely on measure of telomere length. Future research suggestions are proposed.


title: A multi-level framework to identify HTTPS services

abstract: The development of TLS-based encrypted traffic comes with new challenges related to the management and security analysis of encrypted traffic. There is an essential need for new methods to investigate, with a proper level of identification, the increasing number of HTTPS traffic that may hold security breaches. In fact, although many approaches detect the type of an application (Web, P2P, SSH, etc.) running in secure tunnels, and others identify a couple of specific encrypted web pages through website fingerprinting, this paper proposes a robust technique to precisely identify the services run within HTTPS connections, i.e. to name the services, without relying on specific header fields that can be easily altered. We have defined dedicated features for HTTPS traffic that are used as input for a multi-level identification framework based on machine learning algorithms. Our evaluation based on real traffic shows that we can identify encrypted web services with a high accuracy.


Should Syntactic N-grams Contain Names of Syntactic Relations?


title: Systemic high-dose corticosteroid treatment does not improve the outcome of ipilimumab-related hypophysitis: a retrospective cohort study.

abstract: PURPOSE ::: To examine the onset and outcome of ipilimumab-related hypophysitis and the response to treatment with systemic high-dose corticosteroids (HDS). ::: ::: ::: EXPERIMENTAL DESIGN ::: Twenty-five patients who developed ipilimumab-related hypophysitis were analyzed for the incidence, time to onset, time to resolution, frequency of resolution, and the effect of systemic HDS on clinical outcome. To calculate the incidence, the total number (187) of patients with metastatic melanoma treated with ipilimumab at Dana-Farber Cancer Institute (DFCI; Boston, MA) was retrieved from the DFCI oncology database. Comparisons between corticosteroid treatment groups were performed using the Fisher exact test. The distributions of overall survival were based on the method of Kaplan-Meier. ::: ::: ::: RESULTS ::: The overall incidence of ipilimumab-related hypophysitis was 13%, with a higher rate in males (16.1%) than females (8.7%). The median time to onset of hypophysitis after initiation of ipilimumab treatment was 9 weeks (range, 5-36 weeks). Resolution of pituitary enlargement, secondary adrenal insufficiency, secondary hypothyroidism, male secondary hypogonadism, and hyponatremia occurred in 73%, 0%, 64%, 45%, and 92% of patients, respectively. Systemic HDS treatment did not improve the outcome of hypophysitis as measured by resolution frequency and time to resolution. One-year overall survival in the cohort of patients was 83%, and while it was slightly higher in patients who did not receive HDS, there was no statistically significant difference between treatment arms. ::: ::: ::: CONCLUSION ::: Systemic HDS therapy in patients with ipilimumab-related hypophysitis may not be indicated. Instead, supportive treatment of hypophysitis-related hormone deficiencies with the corresponding hormone replacement should be given.


Study of Preference Based Page Ranking Algorithm


title: BROADBAND RADIAL WAVEGUIDE POWER COMBINER WITH IMPROVED ISOLATION AMONG ADJACENT OUTPUT PORTS

abstract: An eight-way waveguide-based power combiner/divider is presented and investigated in the frequency range 7.5{10.5GHz. A simple approach is proposed for design purposes. The measured combiner shows a good agreement between the simulated and measured results. Insertion loss is about i0:3dB, return loss is less than i15dB and isolation between adjacent output ports is better than i11dB at 8.5GHz and reaches about i14dB at 9.5GHz.


title: Miniaturized Microstrip-to-Waveguide Transition Using Capacitance-Compensated Broadside-Coupled Microstrip Line

abstract: In this paper, a compact microstrip-to-waveguide transition using the quarter-wavelength broadside-coupled microstrip line (BCML) is proposed. The 15-dB fractional bandwidth of this transition is 20.95%, which could only cover part of the X-band (8.2-12.4 GHz). In order to enhance the bandwidth, the capacitance-compensated BCML is used to replace the quarter-wavelength BCML. The microstrip-to-waveguide transition using the capacitance-compensated BCML, which is as compact as the transition using the quarter-wavelength BCML, has 37.33% 15-dB fractional bandwidth, almost covering the whole X-band. To verify the simulation results, back-to-back microstrip-to-waveguide transitions using the quarter-wavelength BCML or the capacitance-compensated BCML are fabricated and measured where the measurement results are in good agreement with the simulation results for both designs.


title: Predicting Anchor Links between Heterogeneous Social Networks

abstract: People usually get involved in multiple social networks to enjoy new services or to fulfill their needs. Many new social networks try to attract users of other existing networks to increase the number of their users. Once a user (called source user) of a social network (called source network) joins a new social network (called target network), a new inter-network link (called anchor link) is formed between the source and target networks. In this paper, we concentrated on predicting the formation of such anchor links between heterogeneous social networks. Unlike conventional link prediction problems in which the formation of a link between two existing users within a single network is predicted, in anchor link prediction, the target user is missing and will be added to the target network once the anchor link is created. To solve this problem, we propose an effective general meta-path-based approach called Connector and Recursive Meta-Paths (CRMP). By using those two different categories of meta-paths, we model different aspects of social factors that may affect a source user to join the target network, resulting in the formation of a new anchor link. Extensive experiments on real-world heterogeneous social networks demonstrate the effectiveness of the proposed method against the recent methods.


title: Enhancing System Thinking in Education Using System Dynamics

abstract: System thinking skills are a prerequisite for acting successfully and responsibly in a complex world. However, traditional education largely fails to enhance system thinking skills whereas learnerc...


title: A Foundation for Actor Computation

abstract: We present an actor language which is an extension of a simple functional language, and provide an operational semantics for this extension. Actor configurations represent open distributed systems, by which we mean that the specification of an actor system explicitly takes into account the interface with external components. We study the composability of such systems. We define and study various notions of testing equivalence on actor expressions and configurations. The model we develop provides fairness. An important result is that the three forms of equivalence, namely, convex, must, and may equivalences, collapse to two in the presence of fairness. We further develop methods for proving laws of equivalence and provide example proofs to illustrate our methodology.


title: Time Management and Home-Based Parent Involvement in Head Start Families

abstract: Head Start programs encourage parents’ involvement in children’s learning and development. To help accomplish this objective, teachers in one program sent a developmentally appropriate activity, linked to the classroom curriculum, home each week for parents and children to do together. This study used focus groups to examine how parents made the time to complete these “homework” activities and the obstacles they faced in doing so. Parents ( n = 22) reported using a variety of time management strategies and supports, described the obstacles they faced in managing time, and discussed the management of the homework activities themselves. Although the results are limited by sample size and characteristics, this study adds to the very limited knowledge about time management strategies in low-income families. Asking parents how they make time to be involved with their children may result in information that can be shared with other families struggling with this issue.


title: Depression, loneliness and Internet addiction: How important is low self-control?

abstract: Abstract This study aimed to explore both the direct and indirect relationships between depression, loneliness, low self-control, and Internet addiction in a sample of Turkish youth, based on a cognitive-behavioral model of generalized problematic Internet use. Data for the present study were collected from 648 undergraduate students with a mean age of 22.46 years (SD = 2.45). Participants completed scales for depression, loneliness, self-control and Internet addiction. Structural equation modeling was used to test the model in which depression and loneliness predicted Internet addiction through low self-control. The findings revealed that of the two factors, only loneliness was related to Internet addiction through low self-control. The results are discussed in terms of the cognitive-behavioral model of generalized problematic Internet use, and implications for practice are considered.


title: Design and Implementation of Self-Oscillating Flyback Converter With Efficiency Enhancement Mechanisms

abstract: This paper presents a self-oscillating flyback converter with efficiency enhancement mechanisms using lossless snubber and the energy recovery winding. The conventional self-oscillating flyback converter with resistor–capacitor–diode snubber has the issues of low conversion efficiency and high no-load power loss. Furthermore, in order to fulfill the $95\ \mbox{V}_{\mathrm{p-p}}$ voltage limitation of the IEC62684 Common-Mode (CM) Standard, the parasitic capacitor of a transformer between the primary and secondary windings has to be reduced, which leads to large leakage inductance for the transformer. However, the larger leakage inductance stores more energy to cause the high voltage spike on the main switch during the turnoff transition period. Therefore, the lossless snubber is employed to suppress the voltage spike and increase the conversion efficiency. In order to increase more conversion efficiency, the energy recovery winding is employed to recycle the energy discharged from the gate–source capacitor of the main switch. Furthermore, the burst-mode control mechanism is utilized to reduce the power consumption at the no-load and light-load conditions. Finally, a prototype circuit of the 7.5-W self-oscillating flyback converter with efficiency enhancement mechanisms is built to verify the performance feasibility, such as the CM voltage, the voltage stress on the switch, the conversion efficiency, and the no-load power loss.


title: Empirical Study of Agile Software Development Methodologies: A Comparative Analysis

abstract: In today's software industry, technological prowess and ever-evolving customer requirements have led to more complex software demands. Agile based software development is increasingly being adopted by the software practitioners as it assures early software development and high quality software products. Also, it offers responsiveness to changes in user requirements, providing for their quick absorption during software development. In this paper, we elaborate the significance, benefits and increasing adoption of Agile methodologies in context of today's complex and evolving software demands. The main objective of this paper is to conduct an empirical study into the choice among the most popular Agile methodologies, Scrum, Extreme Programming and Kanban. Further, this paper provides for a comparative analysis among various agile software development methodologies. Our survey results reveal higher adoption of Scrum based development in present-day software industry as compared to Extreme Programming and Kanban methodologies.


title: 13.56 MHz 1.3 kW resonant converter with GaN FET for wireless power transfer

abstract: This paper presents a 1.3 kW resonant power amplifier using a Gallium Nitride (GaN) device at 13.56 MHz for wireless power transfer (WPT). The power amplifier driving the power transmitting coils is based on a Class Φ 2 inverter, a single switch topology with low switch voltage stress and fast transient response. This implementation utilizes a recently available GaN device in a low inductance package that is compatible with operation in the 10's of MHz switching frequency. These power GaN switching devices have low gate resistance RG and low capacitance C GS which greatly reduces the power requirements of the gate drive circuitry. This paper shows experimental measurements of the inverter in a WPT application and characterization of the system performance over various distances and operating conditions.


Biometric identification


title: Evolution Towards 5G Multi-tier Cellular Wireless Networks: An Interference Management Perspective

abstract: The evolving fifth generation (5G) cellular wireless networks are envisioned to overcome the fundamental challenges of existing cellular networks, for example, higher data rates, excellent end-to-end performance, and user-coverage in hot-spots and crowded areas with lower latency, energy consumption, and cost per information transfer. To address these challenges, 5G systems will adopt a multi-tier architecture consisting of macrocells, different types of licensed small cells, relays, and device-to-device (D2D) networks to serve users with different quality-of-service (QoS) requirements in a spectrum and energy-efficient manner. Starting with the visions and requirements of 5G multi-tier networks, this article outlines the challenges of interference management (e.g. power control, cell association) in these networks with shared spectrum access (i.e. when the different network tiers share the same licensed spectrum). It is argued that the existing interference management schemes will not be able to address the interference management problem in prioritized 5G multi-tier networks where users in different tiers have different priorities for channel access. In this context a survey and qualitative comparison of the existing cell association and power control schemes is provided to demonstrate their limitations for interference management in 5G networks. Open challenges are highlighted and guidelines are provided to modify the existing schemes in order to overcome these limitations and make them suitable for the emerging 5G systems.


Evaluation Of Noise Cancellation Using LMS And NLMS Algorithm


Classification of Medical Images Using Support Vector Machine


Spanner: Google’s globally-distributed database


title: Improving Person Re-identification by Body Parts Segmentation Generated by GAN

abstract: Person re-identification(ReID) is a task of associating persons that cross the non-overlapping camera views at different locations and times. It is a challenging task due to the large variations in person pose, background, luminance, occlusion, low resolution, etc. How to extracting a powerful features representation is the prime problem in ReID and is still unsolved. In this paper, we propose a cascade network architecture combined with a generative adversarial networks(GANs) and a convolutional neural network(CNN) to improve the performance of person re-identification. The GANs first generates the person body parts segmentation from the person image, and then inputs the segmentation label into the connected CNN together with the original person image. Finally obtain a discriminative and robust feature representation for ReID task. The body parts segmentation partitioning the person image into multiple segments, such as background, head, face, arms, lags, etc. The body parts segmentation information contains accurate borders and category attributes for body parts, which makes the our model more accurate compared to other predefined rigid parts alignment models. Experiments are conduced on the CUHK03, Market1501, DukeMTMC-ReID datasets and the results demonstrate that this approach outperforms several existing state-of-the-art methods.


title: Test Case Generation for Program Repair: A Study of Feasibility and Effectiveness

abstract: Among the many different kinds of program repair techniques, one widely studied family of techniques is called test suite based repair. Test-suites are in essence input-output specifications and are therefore typically inadequate for completely specifying the expected behavior of the program under repair. Consequently, the patches generated by test suite based program repair techniques pass the test suite, yet may be incorrect. Patches that are overly specific to the used test suite and fail to generalize to other test cases are called overfitting patches. In this paper, we investigate the feasibility and effectiveness of test case generation in alleviating the overfitting issue. We propose two approaches for using test case generation to improve test suite based repair, and perform an extensive evaluation of the effectiveness of the proposed approaches in enabling better test suite based repair on 224 bugs of the Defects4J repository. The results indicate that test case generation can change the resulting patch, but is not effective at turning incorrect patches into correct ones. We identify the problems related with the ineffectiveness, and anticipate that our results and findings will lead to future research to build test-case generation techniques that are tailored to automatic repair systems.


title: Design & study of a low power high speed full adder using GDI multiplexer

abstract: This paper proposes a new method for implementing a low power full adder by means of a set of Gate Diffusion Input (GDI) cell based multiplexers. Full adder is a very common example of combinational circuits and is used widely in Application Specific Integrated Circuits (ASICs). It is always advantageous to have low power action for the sub components used in VLSI chips. The explored technique of realization achieves a low power high speed design for a widely used subcomponent-full adder. Simulated outcome using state-of-art simulation tool shows finer behavioral performance of the projected method over general CMOS based full adder. Power, speed and area comparison between conventional and proposed full adder is also presented.


title: Transparent Data Deduplication in the Cloud

abstract: Cloud storage providers such as Dropbox and Google drive heavily rely on data deduplication to save storage costs by only storing one copy of each uploaded file. Although recent studies report that whole file deduplication can achieve up to 50% storage reduction, users do not directly benefit from these savings-as there is no transparent relation between effective storage costs and the prices offered to the users. In this paper, we propose a novel storage solution, ClearBox, which allows a storage service provider to transparently attest to its customers the deduplication patterns of the (encrypted) data that it is storing. By doing so, ClearBox enables cloud users to verify the effective storage space that their data is occupying in the cloud, and consequently to check whether they qualify for benefits such as price reductions, etc. ClearBox is secure against malicious users and a rational storage provider, and ensures that files can only be accessed by their legitimate owners. We evaluate a prototype implementation of ClearBox using both Amazon S3 and Dropbox as back-end cloud storage. Our findings show that our solution works with the APIs provided by existing service providers without any modifications and achieves comparable performance to existing solutions.


title: An Iterative Global Structure-Assisted Labeled Network Aligner

abstract: Integrating data from heterogeneous sources is often modeled as merging graphs. Given two or more "compatible'', but not-isomorphic graphs, the first step is to identify a graph alignment, where a potentially partial mapping of vertices between two graphs is computed. A significant portion of the literature on this problem only takes the global structure of the input graphs into account. Only more recent ones additionally use vertex and edge attributes to achieve a more accurate alignment. However, these methods are not designed to scale to map large graphs arising in many modern applications. We propose a new iterative graph aligner, gsaNA, that uses the global structure of the graphs to significantly reduce the problem size and align large graphs with a minimal loss of information. Concretely, we show that our proposed technique is highly flexible, can be used to achieve higher recall, and it is orders of magnitudes faster than the current state of the art techniques.


title: A Fully Progressive Approach to Single-Image Super-Resolution

abstract: Recent deep learning approaches to single image super-resolution have achieved impressive results in terms of traditional error measures and perceptual quality. However, in each case it remains challenging to achieve high quality results for large upsampling factors. To this end, we propose a method (ProSR) that is progressive both in architecture and training: the network upsamples an image in intermediate steps, while the learning process is organized from easy to hard, as is done in curriculum learning. To obtain more photorealistic results, we design a generative adversarial network (GAN), named ProGanSR, that follows the same progressive multi-scale design principle. This not only allows to scale well to high upsampling factors (e.g., 8x) but constitutes a principled multi-scale approach that increases the reconstruction quality for all upsampling factors simultaneously. In particular ProSR ranks 2nd in terms of SSIM and 4th in terms of PSNR in the NTIRE2018 SISR challenge [34]. Compared to the top-ranking team, our model is marginally lower, but runs 5 times faster.


Data services leveraging Bing's data assets


RN / 15 / 07 Causal Impact Analysis Applied to App Releases in Google Play and Windows Phone Store December 16 , 2015


title: Quick Access: Building a Smart Experience for Google Drive

abstract: Google Drive is a cloud storage and collaboration service used by hundreds of millions of users around the world. Quick Access is a new feature in Google Drive that surfaces the most relevant documents when a user visits the home screen. Our metrics show that users locate their documents in half the time with this feature compared to previous approaches. The development of Quick Access illustrates many general challenges and constraints associated with practical machine learning such as protecting user privacy, working with data services that are not designed with machine learning in mind, and evolving product definitions. We believe that the lessons learned from this experience will be useful to practitioners tackling a wide range of applied machine learning problems.


title: Deep Location-Specific Tracking

abstract: Convolutional Neural Network (CNN) based methods have shown significant performance gains in the problem of visual tracking in recent years. Due to many uncertain changes of objects online, such as abrupt motion, background clutter and large deformation, the visual tracking is still a challenging task. We propose a novel algorithm, namely Deep Location-Specific Tracking, which decomposes the tracking problem into a localization task and a classification task, and trains an individual network for each task. The localization network exploits the information in the current frame and provides a specific location to improve the probability of successful tracking, while the classification network finds the target among many examples generated around the target location in the previous frame, as well as the one estimated from the localization network in the current frame. CNN based trackers often have massive number of trainable parameters, and are prone to over-fitting to some particular object states, leading to less precision or tracking drift. We address this problem by learning a classification network based on 1 × 1 convolution and global average pooling. Extensive experimental results on popular benchmark datasets show that the proposed tracker achieves competitive results without using additional tracking videos for fine-tuning. The code is available at https://github.com/ZjjConan/DLST


title: Correlating NBA Team Network Centrality Measures with Game Performance

abstract: Basketball is an inherently social sport, which implies that social dynamics within a team may influence the team's performance on the court. As NBA players use social media, it may be possible to study the social structure of a team by examining the relationships that form within social media networks. This paper investigates the relationship between publicly available online social networks and quantitative performance data. It is hypothesized that network centrality measures for an NBA team's network will correlate with measurable performance metrics such as win percentage, points differential and assists per play. The hypothesis is tested using exponential random graph models (ERGM) and investigating correlation between network and performance variables. The results show that there are league-wide trends correlating certain network measures with game performance, and also quantifies the effects of various player attributes on network formation.


Collective Event Detection via a Hierarchical and Bias Tagging Networks with Gated Multi-level Attention Mechanisms


title: Stacking Bagged and Boosted Forests for Effective Automated Classification

abstract: Random Forest (RF) is one of the most successful strategies for automated classification tasks. Motivated by the RF success, recently proposed RF-based classification approaches leverage the central RF idea of aggregating a large number of low-correlated trees, which are inherently parallelizable and provide exceptional generalization capabilities. In this context, this work brings several new contributions to this line of research. First, we propose a new RF-based strategy (BERT) that applies the boosting technique in bags of extremely randomized trees. Second, we empirically demonstrate that this new strategy, as well as the recently proposed BROOF and LazyNN_RF classifiers do complement each other, motivating us to stack them to produce an even more effective classifier. Up to our knowledge, this is the first strategy to effectively combine the three main ensemble strategies: stacking, bagging (the cornerstone of RFs) and boosting. Finally, we exploit the efficient and unbiased stacking strategy based on out-of-bag (OOB) samples to considerably speedup the very costly training process of the stacking procedure. Our experiments in several datasets covering two high-dimensional and noisy domains of topic and sentiment classification provide strong evidence in favor of the benefits of our RF-based solutions. We show that BERT is among the top performers in the vast majority of analyzed cases, while retaining the unique benefits of RF classifiers (explainability, parallelization, easiness of parameterization). We also show that stacking only the recently proposed RF-based classifiers and BERT using our OOB-based strategy is not only significantly faster than recently proposed stacking strategies (up to six times) but also much more effective, with gains up to 21% and 17% on MacroF1 and MicroF1, respectively, over the best base method, and of 5% and 6% over a stacking of traditional methods, performing no worse than a complete stacking of methods at a much lower computational effort.


title: Optimal exponential synchronization of general chaotic delayed neural networks: an LMI approach.

abstract: This paper investigates the optimal exponential synchronization problem of general chaotic neural networks with or without time delays by virtue of Lyapunov-Krasovskii stability theory and the linear matrix inequality (LMI) technique. This general model, which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator, covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks (CNNs), bidirectional associative memory (BAM) networks, and recurrent multilayer perceptrons (RMLPs) with or without delays. Using the drive-response concept, time-delay feedback controllers are designed to synchronize two identical chaotic neural networks as quickly as possible. The control design equations are shown to be a generalized eigenvalue problem (GEVP) which can be easily solved by various convex optimization algorithms to determine the optimal control law and the optimal exponential synchronization rate. Detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.


1 IMPLEMENTING TOTAL PRODUCTIVE MAINTENANCE IN NIGERIAN


title: A novel wideband waveguide-to-microstrip transition with waveguide stepped impedance transformer

abstract: A novel wideband waveguide-to-microstrip transition is presented in this paper. A printed fan-shaped probe is used, while a waveguide stepped impedance transformer is utilized to broaden the bandwidth further. With an optimized design, a relative bandwidth of 27.8% for −20dB return loss with a center frequency of 15GHz is achieved. The simulated insertion loss in this bandwidth is less than 0.29dB. A back-to-back transition is fabricated and measured. The measured result is similar to that of simulation.


title: A DC to 22GHz, 2W high power distributed amplifier using stacked FET topology with gate periphery tapering

abstract: This paper describes a high power (2W) distributed amplifier (DA) MMIC. DA MMIC was fabricated using an Lg=0.25µm GaAs PHEMT process. DA MMIC contains an impedance transformer and heavily tapered gate periphery design for constant output power performance over 0.1 to 22GHz operational frequency. To obtain high voltage operation, the DA MMIC employed a three stacked FET topology. A 7-section DA demonstrated 2 W saturated output power and 12 dB small signal gain from 0.1 GHz to 22 GHz with peak output power of 3.5 W with power added efficiency (PAE) of 27%. Those test results exceeded recently reported GaN based power DA performance [4] with large margins.


title: Adaptive Fingerprint Image Enhancement With Emphasis on Preprocessing of Data

abstract: This article proposes several improvements to an adaptive fingerprint enhancement method that is based on contextual filtering. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Five processing blocks comprise the adaptive fingerprint enhancement method, where four of these blocks are updated in our proposed system. Hence, the proposed overall system is novel. The four updated processing blocks are: 1) preprocessing; 2) global analysis; 3) local analysis; and 4) matched filtering. In the preprocessing and local analysis blocks, a nonlinear dynamic range adjustment method is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of the updated processing blocks is presented in the evaluation part of this paper. The algorithm is evaluated toward the NIST developed NBIS software for fingerprint recognition on FVC databases.


title: A comparison of area pointing and goal crossing for people with and without motor impairments

abstract: Prior work has highlighted the challenges faced by people with motor impairments when trying to acquire on-screen targets using a mouse or trackball. Two reasons for this are the difficulty of positioning the mouse cursor within a confined area, and the challenge of accurately executing a click. We hypothesize that both of these difficulties with area pointing may be alleviated in a different target acquisition paradigm called "goal crossing." In goal crossing, users do not acquire a confined area, but instead pass over a target line. Although goal crossing has been studied for able-bodied users, its suitability for people with motor impairments is unknown. We present a study of 16 people, 8 of whom had motor impairments, using mice and trackballs to do area pointing and goal crossing. Our results indicate that Fitts' law models both techniques for both user groups. Furthermore, although throughput for able-bodied users was higher for area pointing than for goal crossing (4.72 vs. 3.61 bits/s), the opposite was true for users with motor impairments (2.34 vs. 2.88 bits/s), suggesting that goal crossing may be viable for them. However, error rates were higher for goal crossing than for area pointing under a strict definition of crossing errors (6.23% vs. 1.94%). Subjective results indicate a preference for goal crossing among motor-impaired users. This work provides the empirical foundation from which to pursue the design of crossing-based interfaces as accessible alternatives to pointing-based interfaces.


title: Offline Arabic handwriting recognition: a survey

abstract: The automatic recognition of text on scanned images has enabled many applications such as searching for words in large volumes of documents, automatic sorting of postal mail, and convenient editing of previously printed documents. The domain of handwriting in the Arabic script presents unique technical challenges and has been addressed more recently than other domains. Many different methods have been proposed and applied to various types of images. This paper provides a comprehensive review of these methods. It is the first survey to focus on Arabic handwriting recognition and the first Arabic character recognition survey to provide recognition rates and descriptions of test data for the approaches discussed. It includes background on the field, discussion of the methods, and future research directions.


title: Graph Database Indexing Using Structured Graph Decomposition

abstract: We introduce a novel method of indexing graph databases in order to facilitate subgraph isomorphism and similarity queries. The index is comprised of two major data structures. The primary structure is a directed acyclic graph which contains a node for each of the unique, induced subgraphs of the database graphs. The secondary structure is a hash table which cross-indexes each subgraph for fast isomorphic lookup. In order to create a hash key independent of isomorphism, we utilize a code-based canonical representation of adjacency matrices, which we have further refined to improve computation speed. We validate the concept by demonstrating its effectiveness in answering queries for two practical datasets. Our experiments show that for subgraph isomorphism queries, our method outperforms existing methods by more than an order of magnitude.


Dynamic Bayesian Networks: Representation, Inference and Learning


title: Methodological rigour within a qualitative framework

abstract: Aim. This paper discusses the literature on establishing rigour in research studies. It describes the methodological trinity of reliability, validity and generalization and explores some of the issues relating to establishing rigour in naturalistic inquiry. ::: ::: Background. Those working within the naturalistic paradigm have questioned the issue of using validity, reliability and generalizability to demonstrate robustness of qualitative research. Triangulation has been used to demonstrate confirmability and completeness and has been one means of ensuring acceptability across paradigms. Emerging criteria such as goodness and trustworthiness can be used to evaluate the robustness of naturalistic inquiry. ::: ::: Discussion. It is argued that the transference of terms across paradigms is inappropriate; however, if we reject the concepts of validity and reliability, we reject the concept of rigour. Rejection of rigour undermines acceptance of qualitative research as a systematic process that can contribute to the advancement of knowledge. Emerging criteria for demonstrating robustness in qualitative inquiry, such as authenticity, trustworthiness and goodness, need to be considered. Goodness, when not seen as a separate construct but as an integral and embedded component of the research process, should be useful in assuring quality of the entire study. Triangulation is a tried and tested means of offering completeness, particularly in mixed-method research. When multiple types of triangulation are used appropriately as the ‘triangulation state of mind’, they approach the concept of crystallization, which allows for infinite variety of angles of approach. ::: ::: Conclusion. Qualitative researchers need to be explicit about how and why they choose specific legitimizing criteria in ensuring the robustness of their inquiries. A shift from a position of fundamentalism to a more pluralistic approach as a means of legitimizing naturalistic inquiry is advocated.


title: Initial reliability and validity of a new retrospective measure of child abuse and neglect.

abstract: OBJECTIVE: This report presents initial findings on the reliability and validity of a new retrospective measure of child abuse and neglect, the Childhood Trauma Questionnaire. METHOD: Two hundred eighty-six drug- or alcohol-dependent patients were given the Childhood Trauma Questionnaire as part of a larger test battery, and 40 of these patients were given the questionnaire again after an interval of 2 to 6 months. Sixty-eight of the patients were also given a structured interview for child abuse and neglect, the Childhood Trauma Interview, that was developed by the authors. RESULTS: Principal-components analysis of responses on the Childhood Trauma Questionnaire yielded four rotated orthogonal factors: physical and emotional abuse, emotional neglect, sexual abuse, and physical neglect. Cronbach's alpha for the factors ranged from 0.79 to 0.94, indicating high internal consistency. The Childhood Trauma Questionnaire also demonstrated good test-retest reliability over a 2- to 6-month interval (intraclass correlation = 0.88), as well as convergence with the Childhood Trauma Interview, indicating that patients' reports of child abuse and neglect based on the Childhood Trauma Questionnaire were highly stable, both over time and across type of instruments. CONCLUSIONS: These findings provide strong initial support for the reliability and validity of the Childhood Trauma Questionnaire. Language: en


title: Cell death in the central division of the medial preoptic nucleus of male and female lamb fetuses

abstract: The medial preoptic area of the adult sheep contains an ovine sexually dimorphic nucleus (oSDN) that is larger and has more neurons in males than in females. In the lamb fetus, the nascent oSDN occupies the central division of the medial preoptic nucleus (MPNc) and consists of a cluster of cells that is organized by the action of testosterone during gestational days 60-90 of a 147 day term pregnancy. The current study sought to determine whether programmed cell death contributes to the emergence of the oSDN. Male and female lamb fetuses were euthanized at different ages spanning the period during which the oSDN is organized. The expression of the pro- and anti-apoptotic genes bcl-2 and bax, respectively, was measured by quantitative RT-PCR to assess possible sex differences in neuron vulnerability to programmed cell death. The appearance of DNA-fragmentation was detected by terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) and used to estimate the occurrence of apoptotic cell death. We found that bcl-2 and bax mRNA expression in the medial preoptic area of the developing lamb fetus decreased during the last half of the 147-day gestation. The ratio of bcl-2/bax gene expression was highest at gestational day 85 but was equivalent between males and females. TUNEL staining in the MPNc was very low and although it decreased significantly with age, it was not significantly different between sexes. These results using two different methods to assess cell death indicate that a sex difference in the incidence of cell death is not a primary mechanism leading to sexual differentiation of the oSDN.


title: Robust techniques for background subtraction in urban traffic video

abstract: Identifying moving objects from a video sequence is a fundamental and ::: critical task in many computer-vision applications. A common approach ::: is to perform background subtraction, which identifies moving objects ::: from the portion of a video frame that differs significantly from a ::: background model. There are many challenges in developing a good ::: background subtraction algorithm. First, it must be robust against ::: changes in illumination. Second, it should avoid detecting ::: non-stationary background objects such as swinging leaves, rain, snow, ::: and shadow cast by moving objects. Finally, its internal background ::: model should react quickly to changes in background such as starting ::: and stopping of vehicles. In this paper, we compare various background subtraction algorithms for detecting moving vehicles and pedestrians in urban traffic video sequences. We consider approaches varying from simple techniques such as frame differencing and adaptive median filtering, to more sophisticated probabilistic modeling techniques. While complicated techniques often produce superior performance, our experiments show that simple techniques such as adaptive median filtering can produce good results with much lower computational complexity.


title: Mechatronic Aeropendulum: Demonstration of Linear and Nonlinear Feedback Control Principles With MATLAB/Simulink Real-Time Windows Target

abstract: This paper presents a low-cost hands-on experiment for a classical undergraduate controls course for non-electrical engineering majors. The setup consists of a small dc electrical motor attached to one of the ends of a light rod. The motor drives a 2-in propeller and allows the rod to swing. Angular position is measured by a potentiometer attached to the pivot point. A custom-designed circuit board produces the controlled voltage input to the motor. The target board is powered and communicates with the PC through its USB port using a virtual RS-232 port. A simple MATLAB/Simulink module has been created to read the pendulum angle and send a command signal to the motor. The module is based on Real-time Windows Target software, which allows a sampling rate of up to 200 Hz. Students are able to design and test classical PID and phase lead-lag controllers, as well as modern controllers, including state-space controller design combined with feedback linearization. A semester-long series of assignments is described that can be carried out without the need for a specialized laboratory or teaching assistants. The project was tested in a classical control systems design class of senior-level mechanical engineering students. Student feedback and survey data on the effectiveness of the modules are also presented.


title: Vertical partitioning algorithms for database design

abstract: This paper addresses the vertical partitioning of a set of logical records or a relation into fragments. The rationale behind vertical partitioning is to produce fragments, groups of attribute columns, that “closely match” the requirements of transactions. Vertical partitioning is applied in three contexts: a database stored on devices of a single type, a database stored in different memory levels, and a distributed database. In a two-level memory hierarchy, most transactions should be processed using the fragments in primary memory. In distributed databases, fragment allocation should maximize the amount of local transaction processing. Fragments may be nonoverlapping or overlapping. A two-phase approach for the determination of fragments is proposed; in the first phase, the design is driven by empirical objective functions which do not require specific cost information. The second phase performs cost optimization by incorporating the knowledge of a specific application environment. The algorithms presented in this paper have been implemented, and examples of their actual use are shown.


title: Automated silkworm eggs count

abstract: Counting the number of objects from an image is an essential part of image processing. Detecting the number of objects from an image is useful for further analysis in global application. Producing and counting silkworm eggs is very complicated process and requires large man power also extra time will be required so to reduce man power and efforts that required for counting silkworm eggs a method automated silkworm eggs count is useful. Convential method is by using calculator and manually which is erroneous and also waste of time. In this paper, we introduced method for automatically counting the number of silkworm eggs from an image. The objective of proposed method is detecting an eggs portion for counting and eliminating non egg portion from silkworm DFL sheet. We presented image segmentation technique for detecting egg portion, area based thresholding for removing small noise and barriers. Number of objects can be calculated by using object counting functions present in MATLAB.


title: Harmony: A Hand Wash Monitoring and Reminder System using Smart Watches

abstract: Hand hygiene compliance is extremely important in hospitals, clinics and food businesses. Caregivers' compliance with hand hygiene is one of the most effective tools in preventing healthcare associated infections (HAIs) in hospitals and clinics. In food businesses, hand hygiene compliance is essential to prevent food contamination, and thus food borne illness. Washing hands properly is the cornerstone of hand hygiene. However, the hand wash compliance rate by the workers (care givers, waiters, chefs, food processors and so on) is not up to the mark. Monitoring hand wash compliance along with a reminder system increases the compliance rate significantly. Quality of a hand wash is also important which can be achieved by washing hands in accordance with standard guidelines. In this paper, we present Harmony, a hand wash monitoring and reminder system that monitors hand wash events and their quality, provides real time feedback, reminds the person of interest when he/she is required to wash hands, and stores related data in a server for further use. Worker worn smart watches are the key components of Harmony that can differentiate hand wash gestures from other gestures with an average accuracy of about 88%. Harmony is robust, scalable, and easy to install, and it overcomes most of the problems of existing related systems.


title: Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization

abstract: The lack of sufficient labeled Web pages in many languages, especially for those uncommonly used ones, presents a great challenge to traditional supervised classification methods to achieve satisfactory Web page classification performance. To address this, we propose a novel Nonnegative Matrix Tri-factorization (NMTF) based Dual Knowledge Transfer (DKT) approach for cross-language Web page classification, which is based on the following two important observations. First, we observe that Web pages for a same topic from different languages usually share some common semantic patterns, though in different representation forms. Second, we also observe that the associations between word clusters and Web page classes are a more reliable carrier than raw words to transfer knowledge across languages. With these recognitions, we attempt to transfer knowledge from the auxiliary language, in which abundant labeled Web pages are available, to target languages, in which we want classify Web pages, through two different paths: word cluster approximations and the associations between word clusters and Web page classes. Due to the reinforcement between these two different knowledge transfer paths, our approach can achieve better classification accuracy. We evaluate the proposed approach in extensive experiments using a real world cross-language Web page data set. Promising results demonstrate the effectiveness of our approach that is consistent with our theoretical analyses.


title: Patent Holdup and Royalty Stacking

abstract: We study several interconnected problems that arise under the current U.S. patent system when a patent covers one component or feature of a complex product. This situation is common in the information technology sector of the economy. Our analysis applies to cases involving reasonable royalties but not lost profits. First, we show using bargaining theory that the threat to obtain a permanent injunction greatly enhances the patent holder's negotiating power, leading to royalty rates that exceed a natural benchmark range based on the value of the patented technology and the strength of the patent. Such royalty overcharges are especially great for weak patents covering a minor feature of a product with a sizeable price/cost margin, including products sold by firms that themselves have made substantial research and development investments. These royalty overcharges do not disappear even if the allegedly infringing firm is fully aware of the patent when it initially designs its product. However, the holdup problems caused by the threat of injunctions are reduced if courts regularly grant stays to permanent injunctions to give defendants time to redesign their products to avoid infringement when this is possible. Second, we show how holdup problems are magnified in the presence of royalty stacking, i.e., when multiple patents read on a single product. Third, using third-generation cellular telephones and Wi-Fi as leading examples, we illustrate that royalty stacking can become a very serious problem, especially in the standard-setting context where hundreds or even thousands of patents can read on a single product standard. Fourth, we discuss the use of "reasonable royalties" to award damages in patent infringement cases. We report empirical results regarding the measurement of reasonable royalties by the courts and identify various practical problems that tend to lead courts to overestimate reasonable royalties in the presence of royalty stacking. Finally, we make suggestions for patent reform based on our theoretical and empirical findings. I. Introduction The patent system is designed with a paradigm invention in mind - a new device or machine covered by a single patent. Historically, this paradigm was a fairly accurate portrayal of the typical patent.1 As Robert Merges put it, "for Jefferson, if you put technology in a bag and shook it, it would make some noise."2 In the last few decades that has begun to change markedly. Not only have patents on chemical, biotechnological, hardware, and software inventions proliferated, but more and more products incorporate not a single new invention but a combination of many different components, each of which may be the subject of one or more patents.3 In the information technology sector in particular, modern products such as microprocessors, cell phones, or memory devices can easily be covered by dozens or even hundreds of different patents. As a striking example, literally thousands of patents have been identified as essential to the proposed new standards for 3G cellular telephone systems.4 The fact that a great many patents can read on a single product, and that this is common in certain critical industries, creates numerous practical problems for the operation of the patent system.5 We focus here on two critical, interacting areas in which problems arise: injunction threats and royalty stacking. We are especially interested in how these problems affect the royalties that will be negotiated between patent holders and downstream firms that produce products that may infringe those patents. After all, since far more patents are licensed or settled than litigated to judgment, the primary economic effect of rules governing patent litigation arises through the effect of those rules on the licensing terms that are negotiated in the shadow of litigation. The threat that a patent holder will obtain an injunction that will force the downstream producer to pull its product from the market can be very powerful. …


title: Towards enhancing stacked extreme learning machine with sparse autoencoder by correntropy

abstract: Abstract The stacked extreme learning machine (S-ELM) is an advanced framework of deep learning. It passes the ‘reduced’ outputs of the previous layer to the current layer, instead of directly propagating the previous outputs to the next layer in traditional deep learning. The S-ELM could address some large and complex data problems with a high accuracy and a relatively low requirement for memory. However, there is still room for improvement of the time complexity as well as robustness while using S-ELM. In this article, we propose an enhanced S-ELM by replacing the original principle component analysis (PCA) technique used in this algorithm with the correntropy-optimized temporal PCA (CTPCA), which is robust for outliers rejection and significantly improves the training speed. Then, the CTPCA-based S-ELM performs better than S-ELM in both accuracy and learning speed, when dealing with dataset disturbed by outliers. Furthermore, after integrating the extreme learning machine (ELM) sparse autoencoder (AE) method into the CTPCA-based S-ELM, the learning accuracy is further improved while spending a little more training time. Meanwhile, the sparser and more compact feature information are available by using the ELM sparse AE with more computational efforts. The simulation results on some benchmark datasets verify the effectiveness of our proposed methods.


P.: Improving adaptive game AI with evolutionary learning


title: A rule-based approach of stemming for inflectional and derivational words in Bengali

abstract: Stemming is the process for reducing inflectional or derived words to its stem or root form. This paper presents an approach for finding out the stems from text in Bengali, which is highly inflectional in nature. In our process, we first stripped off the suffix part from Bengali words using some suffix stripping rules, depending upon the type of suffixes. Then we checked for the validity of the suffix stripped word as root word, using a Bengali dictionary. We have tested the process on Bengali collection of the FIRE 2010 data set with 50 queries using Lucene as the search engine and it gives a quite satisfactory result in terms of recall and MAP value.


title: Video Game User Experience: To VR, or Not to VR?

abstract: Virtual reality (VR) has become an alternative medium for entertainment purposes, ranging from watching a movie to playing video games. Given the increasing use of VR for video gaming, the current study investigated whether VR gaming might affect the video gaming user experience (UX). We compared three different gaming platforms, namely desktop computer, Oculus Rift, and HTC Vive, in terms of gaming UX satisfaction. A total of 48 participants were randomly assigned to one of the three gaming platforms. Participants played a first-person shooter video game for ten minutes and provided game UX satisfaction ratings. Results revealed no statistically significant differences across the three platforms in video game UX satisfaction levels. Participants, however, rated desktop gaming as significantly more usable, when compared to the two VR conditions. In addition, sense of presence was a strong predictor of game UX satisfaction. Taken together, these results indicate that VR gaming may not always be a better alternative to traditional desktop gaming in terms of video game UX satisfaction, while at the same time providing further support for the putative role sense of presence plays in game satisfaction.


title: Transmission line approach of left-handed (LH) materials and microstrip implementation of an artificial LH transmission line

abstract: A transmission line (TL) approach of left-handed (LH) materials is proposed. The transmission characteristics of an ideal LH-TL are presented, the constitutive parameters of an equivalent LH material are derived and shown to be negative, and some LH-transmission paradoxes are explained. Next, a method to design an artificial LH-TL in the form of an ideal lumped-elements ladder network is described and illustrated with simulation results. It is shown that, in this line, left-handedness can be achieved without losses over an unlimited bandwidth, from the cutoff of the resulting high-pass filter to infinity, with excellent agreement with theory. Finally, a microstrip implementation of the LH line for microwaves, using interdigital capacitors and stub inductors, is demonstrated, with moderate insertion loss and a broad bandwidth of the order of 100%.


title: Spatially-weighted Anomaly Detection

abstract: Many types of anomaly detection methods have been proposed recently, and applied to a wide variety of fields including medical screening and production quality checking. Some methods have utilized images, and, in some cases, a part of the anomaly images is known beforehand. However, this kind of information is dismissed by previous methods, because the methods can only utilize a normal pattern. Moreover, the previous methods suffer a decrease in accuracy due to negative effects from surrounding noises. In this study, we propose a spatially-weighted anomaly detection method (SPADE) that utilizes all of the known patterns and lessens the vulnerability to ambient noises by applying Grad-CAM, which is the visualization method of a CNN. We evaluated our method quantitatively using two datasets, the MNIST dataset with noise and a dataset based on a brief screening test for dementia.


title: Title

abstract: This paper reviews the state-of-the-art in automatic genre classification of music collections through three main paradigms: expert systems, unsupervised classification, and supervised classification. The paper discusses the importance of music genres with their definitions and hierarchies. It also presents techniques to extract meaningful information from audio data to characterize musical excerpts. The paper also presents the results of new emerging research fields and techniques that investigate the proximity of music genres


title: An improved TF-IDF approach for text classification

abstract: This paper presents a new improved term frequency/inverse document frequency (TF-IDF) approach which uses confidence, support and characteristic words to enhance the recall and precision of text classification. Synonyms defined by a lexicon are processed in the improved TF-IDF approach. We detailedly discuss and analyze the relationship among confidence, recall and precision. The experiments based on science and technology gave promising results that the new TF-IDF approach improves the precision and recall of text classification compared with the conventional TF-IDF approach.


title: The marketplace of ideology: “Elective affinities” in political psychology and their implications for consumer behavior

abstract: Abstract An abundance of research in political psychology demonstrates that leftists and rightists (or liberals and conservatives) diverge from one another in terms of: (a) personality characteristics; (b) cognitive processing styles; (c) motivational interests and concerns; (d) the prioritization of personal values; and (e) neurological structures and physiological functions. In this article, I summarize these findings and discuss some of their implications for persuasion, framing, and advertising; consumer choice, judgment, decision-making, and behavior; and customer satisfaction/dissatisfaction and politically motivated boycotts. I conclude that the theory and practice of consumer psychology will be enriched by taking into account ideological asymmetries and the ways in which human behavior both reflects and gives rise to left–right divergence in political orientation—not only in terms of beliefs, opinions, and values but also in terms of underlying psychological processes.


Developmental anomalies of teeth and their applications in Forensic Odontology


Scaling in biology: patterns and processes, causes and consequences


title: Unscented Kalman Filter: Aspects and Adaptive Setting of Scaling Parameter

abstract: This technical note deals with the unscented Kalman filter for state estimation of nonlinear stochastic dynamic systems with a special focus on the scaling parameter of the filter. Its standard choice is analyzed and its impact on the estimation quality is discussed. On the basis of the analysis, a novel method for adaptive setting of the parameter in the unscented Kalman filter is proposed. The results are illustrated in a numerical example.


title: Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos

abstract: The task of video grounding, which temporally localizes a natural language description in a video, plays an important role in understanding videos. Existing studies have adopted strategies of sliding window over the entire video or exhaustively ranking all possible clip-sentence pairs in a pre-segmented video, which inevitably suffer from exhaustively enumerated candidates. To alleviate this problem, we formulate this task as a problem of sequential decision making by learning an agent which regulates the temporal grounding boundaries progressively based on its policy. Specifically, we propose a reinforcement learning based framework improved by multi-task learning and it shows steady performance gains by considering additional supervised boundary information during training. Our proposed framework achieves state-of-the-art performance on ActivityNet'18 DenseCaption dataset and Charades-STA dataset while observing only 10 or less clips per video.


title: The Future of Sex and Gender in Psychology: Five Challenges to the Gender Binary

abstract: The view that humans comprise only two types of beings, women and men, a framework that is sometimes referred to as the "gender binary," played a profound role in shaping the history of psychological science. In recent years, serious challenges to the gender binary have arisen from both academic research and social activism. This review describes 5 sets of empirical findings, spanning multiple disciplines, that fundamentally undermine the gender binary. These sources of evidence include neuroscience findings that refute sexual dimorphism of the human brain; behavioral neuroendocrinology findings that challenge the notion of genetically fixed, nonoverlapping, sexually dimorphic hormonal systems; psychological findings that highlight the similarities between men and women; psychological research on transgender and nonbinary individuals' identities and experiences; and developmental research suggesting that the tendency to view gender/sex as a meaningful, binary category is culturally determined and malleable. Costs associated with reliance on the gender binary and recommendations for future research, as well as clinical practice, are outlined. (PsycINFO Database Record (c) 2019 APA, all rights reserved).


title: A taxonomy for requirements engineering and software test alignment

abstract: Requirements Engineering and Software Testing are mature areas and have seen a lot of research. Nevertheless, their interactions have been sparsely explored beyond the concept of traceability. To fill this gap, we propose a definition of requirements engineering and software test (REST) alignment, a taxonomy that characterizes the methods linking the respective areas, and a process to assess alignment. The taxonomy can support researchers to identify new opportunities for investigation, as well as practitioners to compare alignment methods and evaluate alignment, or lack thereof. We constructed the REST taxonomy by analyzing alignment methods published in literature, iteratively validating the emerging dimensions. The resulting concept of an information dyad characterizes the exchange of information required for any alignment to take place. We demonstrate use of the taxonomy by applying it on five in-depth cases and illustrate angles of analysis on a set of thirteen alignment methods. In addition, we developed an assessment framework (REST-bench), applied it in an industrial assessment, and showed that it, with a low effort, can identify opportunities to improve REST alignment. Although we expect that the taxonomy can be further refined, we believe that the information dyad is a valid and useful construct to understand alignment.


title: Adaptive game level creation through rank-based interactive evolution

abstract: This paper introduces Rank-based Interactive Evolution (RIE) which is an alternative to interactive evolution driven by computational models of user preferences to generate personalized content. In RIE, the computational models are adapted to the preferences of users which, in turn, are used as fitness functions for the optimization of the generated content. The preference models are built via ranking-based preference learning, while the content is generated via evolutionary search. The proposed method is evaluated on the creation of strategy game maps, and its performance is tested using artificial agents. Results suggest that RIE is both faster and more robust than standard interactive evolution and outperforms other state-of-the-art interactive evolution approaches.


title: Text Mining on Player Personality for Game Recommendation

abstract: Recommender systems have emergedrecently in many aspects due to enormous amount of information or items existed in e-commerce or social network services. Users find it convenient if the service can recommend interesting items to them automatically. Past systems adopted users' preference or social connections for such recommendation. In this work, we will try to identify a game player's personality traits and use them to recommend games that may be interested by the player. The personality traits of a player is identified by applying a text mining process on textual contents related to the player. The same process is also applied on the comments of the games to identified the personality traits of games. Recommendation is then performed based on the similarity between the traits of the user and the game. We performed experiments on 63 players and 2050 games and obtained promising results which may demonstrate the plausibility of personality-based recommender systems.


title: A model of stateful firewalls and its properties

abstract: We propose the first model of stateful firewalls. In this model, each stateful firewall has a variable set called the state of the firewall, which is used to store some packets that the firewall has accepted previously and needs to remember in the near future. Each stateful firewall consists of two sections: a stateful section and a stateless section. Upon receiving a packet, the firewall processes it in two steps. In the first step, the firewall augments the packet with an additional field called the tag, and uses the stateful section to compute the value of this field according to the current state of the firewall. In the second step, the firewall compares the packet together with its tag value against a sequence of rules in the stateless section to identify the first rule that the packet matches: the decision of this rule determines the fate of the packet. Our model of stateful firewalls has several favorable properties. First, despite its simplicity, it can express a variety of state tracking functionalities. Second, it allows us to inherit the rich results in stateless firewall design and analysis. Third, it provides backward compatibility such that a stateless firewall can also be specified using our model. This paper goes beyond proposing this stateful firewall model itself. A significant portion of this paper is devoted to analyzing the properties of stateful firewalls that are specified using our model. We outline a method for verifying whether a firewall is truly stateful. The method is based on the three properties of firewalls: conforming, grounded, and proper. We show that if a firewall satisfies these three properties, then the firewall is truly stateful.


title: Monocular vision and IMU based navigation for a small unmanned helicopter

abstract: Focusing on the problem of autonomous flight for a small unmanned helicopter in GPS-denied environments, this paper proposes a navigation system which combines monocular visual and inertial measurements. The homography based visual odometry, as well as the inertial measurement from an IMU, can estimate the motion of a small unmanned helicopter. An extended Kalman filter is used to fuse the estimations of both visual and inertial sensors to provide the available navigation data. Finally, the effectiveness of this system is verified by real experiments. The Vision/IMU navigation has almost the same performance as the traditional GPS/IMU navigation.


title: Pedestrian navigation based on inertial sensors, indoor map, and WLAN signals

abstract: As satellite signals, e.g. GPS, are severely degraded indoors or not available at all, other methods are needed for indoor positioning. In this paper, we propose methods for combining information from inertial sensors, indoor map, and WLAN signals for pedestrian indoor navigation. We present results of field tests where complementary extended Kalman filter was used to fuse together WLAN signal strengths and signals of an inertial sensor unit including one gyro and three-axis accelerometer. A particle filter was used to combine the inertial data with map information. The results show that both the map information and WLAN signals can be used to improve the pedestrian dead reckoning estimate based on inertial sensors.


title: Fog computing: from architecture to edge computing and big data processing

abstract: Cloud computing plays a vital role in processing a large amount of data. However, with the arrival of the Internet of Things, huge data are generated from these devices. Thus, there is the need for bringing characteristics of cloud closer to the request generator, so that processing of these huge data takes place at one-hop distance closer to that end user. This led to the emergence of fog computing with the aim to provide storage and computation at the edge of the network that reduces network traffic and overcomes many cloud computing drawbacks. Fog computing technology helps to overcome challenges of big data processing. The paper discusses the taxonomy of fog computing, how this is different from cloud computing and edge computing technologies, its applications, emerging key technologies (i.e., communication technologies and storage technologies) and various challenges involved in fog technology.


title: Hand-drawn grayscale image colorful colorization based on natural image

abstract: This paper presents a novel colorization technique for hand-drawn grayscale images, such as cartoons and sketches, based on reference natural images and simple user interactions, which can generate colorful and natural results. Firstly, to solve the problem of inputting complex color scribbles by simple interactions, we introduce a region thinning method for generating color scribbles and then map these scribbles to the corresponding regions in the hand-drawn image via region mapping method based on the scanning line. Secondly, to maintain the color fidelity, a luminance downward modification method is proposed. Next, a optimization method for colorization is proposed, where the feature vectors are adjusted by a smooth feature map, thus maintaining smooth color transitions in the smooth areas and controlling the color overflow in the texture areas. Thirdly, to fuse the colorized image with a highlight effect, a luminance upward modification method by weights, which are determined by color distance and boundary distance, is proposed. The experimental results of the proposed algorithm show the smooth color transition in the intensity-continuity areas, color overflow controlling in the texture-continuity areas and natural effect of light and shadow.


title: Do Positive Psychology Exercises Work? A Replication of Seligman et al. ()

abstract: Objectives ::: The current work replicated a landmark study conducted by Seligman and colleagues (2005) that demonstrated the long-term benefits of positive psychology exercises (PPEs). In the original study, two exercises administered over 1 week (“Three Good Things” and “Using your Signature Strengths in a New Way”) were found to have long-lasting effects on depression and happiness (Seligman, Steen, Park, & Peterson, 2005). ::: ::: Design ::: These exercises were tested here using the same methodology except for improvements to the control condition, and the addition of a second “positive placebo” to isolate the common factor of accessing positive, self-relevant constructs. This component control design was meant to assess the effect of expectancies for success (expectancy control), as well the cognitive access of positive information about the self (positive placebo). ::: ::: Results ::: Repeated measures analyses showed that the PPEs led to lasting increases in happiness, as did the positive placebo. The PPEs did not exceed the control condition in producing changes in depression over time. ::: ::: Conclusions ::: Brief, positive psychology interventions may boost happiness through a common factor involving the activation of positive, self-relevant information rather than through other specific mechanisms. Finally, the effects of PPEs on depression may be more modest than previously assumed.


title: What is a participatory design result?

abstract: In this paper we discuss what the result of a Participatory Design (PD) process is and how it can be described and evaluated. We look at several PD projects and discuss if they have a participatory result and how we know that it is participatory. We also ask if the users recognize their contribution, and if the designers have to 'take side'. We also identify impediments to achieving a participatory result, looking at issues like: conflicting views that are difficult to voice, issues that are difficult to negotiate, how real-life complexities cannot be addressed in the project (or by the artifact). These issues are linked to earlier discussions on power and politics in PD. We conclude that achieving a participatory design result is important in PD and gives meaning and direction to PD processes.


title: Profanity in Media Associated With Attitudes and Behavior Regarding Profanity Use and Aggression

abstract: We hypothesized that exposure to profanity in media would be directly related to beliefs and behavior regarding profanity and indirectly to aggressive behavior. METHODS: We examined these associations among 223 adolescents attending a large Midwestern middle school. Participants completed a number of questionnaires examining their exposure to media, atti- tudes and behavior regarding profanity, and aggressive behavior. RESULTS: Results revealed a positive association between exposure to profanity in multiple forms of media and beliefs about profanity, pro- fanity use, and engagement in physical and relational aggression. Spe- cifically, attitudes toward profanity use mediated the relationship be- tween exposure to profanity in media and subsequent behavior involving profanity use and aggression. CONCLUSIONS: The main hypothesis was confirmed, and implications for the rating industry and research field are discussed. Pediatrics 2011;128:000


title: Measuring Prerequisite Relations Among Concepts

abstract: A prerequisite relation describes a basic relation among concepts in cognition, education and other areas. However, as a semantic relation, it has not been well studied in computational linguistics. We investigate the problem of measuring prerequisite relations among concepts and propose a simple link-based metric, namely reference distance (RefD), that effectively models the relation by measuring how differently two concepts refer to each other. Evaluations on two datasets that include seven domains show that our single metric based method outperforms existing supervised learning based methods.


HERTSMI-2 and ERMI : Correlating Human Health Risk with Mold Specific qPCR in Water-Damaged Buildings


Deep Semantic Role Labeling: What Works and What’s Next


title: A Dielectric-Modulated Tunnel-FET-Based Biosensor for Label-Free Detection: Analytical Modeling Study and Sensitivity Analysis

abstract: In this paper, an analytical model for a p-n-p-n tunnel field-effect transistor (TFET) working as a biosensor for label-free biomolecule detection purposes is developed and verified with device simulation results. The model provides a generalized solution for the device electrostatics and electrical characteristics of the p-n-p-n-TFET-based sensor and also incorporates the two important properties possessed by a biomolecule, i.e., its dielectric constant and charge. Furthermore, the sensitivity of the TFET-based biosensor has been compared with that of a conventional FET-based counterpart in terms of threshold voltage (Vth) shift, variation in the on-current (Ion) level, and Ion/Ioff ratio. It has been shown that the TFET-based sensor shows a large deviation in the current level, and thus, change in Ion can also be considered as a suitable sensing parameter. Moreover, the impacts of device parameters (channel thickness and cavity length), process variability, and process-induced damage on the sensitivity of the biosensor have also been discussed.


title: Northwestern University What's Basic About Basic Emotions?

abstract: A widespread assumption in theories of emotion is that there exists a small set of basic emotions. From a biological perspective, this idea is manifested in the belief that there might be neurophysiological and anatomical substrates corresponding to the basic emotions. From a psychological perspective, basic emotions are often held to be the primitive building blocks of other, nonbasic emotions. The content of such claims is examined, and the results suggest that there is no coherent nontrivial notion of basic emotions as the elementary psychological primitives in terms of which other emotions can be explained. Thus, the view that there exist basic emotions out of which all other emotions are built, and in terms of which they can be explained, is questioned, raising the possibility that this position is an article of faith rather than an empirically or theoretically defensible basis for the conduct of emotion research. This suggests that perhaps the notion of basic emotions will not lead to significant progress in the field. An alternative approach to explaining the phenomena that appear to motivate the postulation of basic emotions is presented.


title: Solid State Marx Generator

abstract: This work was supported in part by DOE Grant Marx generators can produce high voltage pulses using multiple identical stages that operate at a fraction of the total output voltage, without the need for a step-up transformer that limits the pulse risetimes and lowers the efficiency of the system. Each Marx stage includes a capacitor or pulse forming network, and a high voltage switch. Typically, these switches are spark gaps resulting in Marx generators with low repetition rates and limited lifetimes. The development of economical, compact, high voltage, high di/dt, and fast turn-on solid-state switches make it easy to build economical, long lifetime, high voltage Marx generators capable of high pulse repetition rates. We have constructed a Marx generator using our 24 kV thyristor based switches, which are capable of conducting 14 kA peak currents with ringing discharges at > 25 kA/?s rate of current risetimes. The switches have short turn-on delays, less than 200 ns, low timing jitters, and are triggered by a single 10 V isolated trigger pulse. This paper will include a description of a 4-stage solid-state Marx and triggering system, as well as show data from operation at 15 kV charging voltage. The Marx was used to drive a one-stage argon ion accelerator.


title: A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

abstract: Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.


title: A Survey on Open Information Extraction

abstract: We provide a detailed overview of the various approaches that were proposed to date to solve the task of Open Information Extraction. We present the major challenges that such systems face, show the evolution of the suggested approaches over time and depict the specific issues they address. In addition, we provide a critique of the commonly applied evaluation procedures for assessing the performance of Open IE systems and highlight some directions for future work.


Periodic Markets and Traveling Traders in Uganda


title: A Multi-Index Analysis Approach to Heavy Metal Pollution Assessment in River Sediments in the Ponce Enríquez Area, Ecuador

abstract: The area of Ponce Enriquez, Southern Ecuador, is one of the most important artisanal and small scale gold mining (ASGM) areas in the country, where informal mining operations can be found using amalgamation technique, even though it has been prohibited since 2010. Considering the potential impact of these mining operations, the present research focused on heavy metal pollutants in subsurface sediments at 214 sampling locations from several detailed sampling campaigns in the rivers Fermin, Fermin Norte, Guanache, Villa, and Siete. Four parameters were calculated to evaluate the geochemical composition of the river sediment and heavy metal concentrations: The enrichment factor (EF), the geo-accumulation index (Igeo), the contamination factor (Cf) and the pollution load index (PLI). The analyzed elements were Cu, Pb, Zn, Ni, As, Cd, Sb, Sr, and Hg. Due to the lack of standards for pollution levels in sediments in Ecuador, Canadian guidelines were used as interim sediment quality guidelines (ISQG) in this research for comparison with the obtained results in subsurface sediments. The multi-index geochemical analysis indicated elevated heavy metal concentrations in all subsurface sediments in the studied river ecosystems.


title: Kinetics of testosterone recovery in clinically localized prostate cancer patients treated with radical prostatectomy and subsequent short-term adjuvant androgen deprivation therapy.

abstract: Androgen deprivation therapy (ADT) is a standard treatment for metastatic, recurrent and locally advanced prostate cancer (PCa). The aim of this study is to investigate the timing and extent of testosterone recovery in clinically localized PCa patients treated with radical prostatectomy (RP) and subsequent short-term adjuvant ADT. A total of 95 localized PCa patients underwent RP and 9-month adjuvant ADT were included in this prospective study. Serum testosterone level was measured before adjuvant ADT, at ADT cessation, and at 1, 3, 6, 9 and 12 months after cessation of ADT. A Cox proportional hazards model was used to assess variables associated with the time of testosterone normalization. The results showed that median patient age was 67 years and median testosterone level before adjuvant ADT was 361 (230-905) ng dl(-1). All patients finished 9-month adjuvant ADT and achieved castrate testosterone level. At 3 months after ADT cessation, testosterone recovered to supracastrate level in 97.9% patients and to normal level in 36.9% patients. The percentage of patients who recovered to normal testosterone level increased to 66.3%, 86.3% and 92.6% at 6, 9 and 12 months, respectively. Cox regression model found that higher baseline testosterone level (≥ 300 ng dl(-1)) was the only variable associated with a shorter time to testosterone normalization (hazard ratio: 1.98; P = 0.012). In conclusion, in most patients, testosterone recovered to supracastrate level at 3 months and to normal level at 12 months after 9-month adjuvant ADT cessation. Patients with higher baseline testosterone level need shorter time of testosterone normalization.


title: A Kinematic Turing Machine.

abstract: A Turing Machine in a three dimensional discrete space environment containing movable cubic parts is described. All of the cubic parts are identical in function. The only function that a part performs is to move a neighbouring part by one unit. Parts can be connected to neighbouring parts. When one part moves, parts that it is connected to also move. An example program for the Turing Machine is given.


title: Vector space model of information retrieval: a reevaluation

abstract: In this paper we, in essence, point out that the methods used in the current vector based systems are in conflict with the premises of the vector space model. The considerations, naturally, lead to how things might have been done differently. More importantly, it is felt that this investigation will lead to a clearer understanding of the issues and problems in using the vector space model in information retrieval.


title: The Logic of Violence in Civil War

abstract: Introduction 1. Concepts and definitions 2. Pathologies 3. Barbarism 4. A theory of irregular war I: collaboration 5. A theory of irregular war II: control 6. The logic of indiscriminate violence 7. A theory of selective violence 8. Empirics I: comparative evidence 9. Empirics II: microcomparative evidence 10. Intimacy 11. Cleavage and agency Conclusion.


title: Closed-loop regulated power supply for ozone generation based on buck converter and current-fed push-pull resonant inverter

abstract: In this paper the design, implementation and experimental results of a high-voltage power supply for ozone generation are presented. The power stage is formed by a buck converter plus a current-fed parallel-resonant push-pull inverter. The buck converter is used to both regulate the output power against the line voltage variation, and to control the power delivered to the ozone generator (OG). The push-pull inverter assures safe operation of the OG by working at the parallel resonant frequency given by the high-voltage transformer plus OG characteristic. In this paper, the closed-loop operation of the proposed converter is analyzed and implemented as a method to compensate variations in the line voltage and in the OG. A low cost commercial UC3872 integrated circuit is used to control both the push-pull inverter and the buck converter, providing OG power control and regulation via buck converter duty cycle. Protections against short circuit and no load operation are also implemented. Experimental results for a 100W prototype are shown and discussed.


title: Hierarchical wind farm control for power/load optimization

abstract: This paper introduces the two leveled hierarchical control concept for wind farm power/load optimization. The high level controller uses the coupling between the wind turbines through the wakes to obtain the optimal wind farm operating point, while the low level controller dynamically optimizes wind farm behavior. The algorithmic solution for the low level controller is presented. To minimize the on-line computational effort the control design procedure replaces the on-line optimization with the off-line optimization approach via multiparametric programming. The simulation results of typical scenarios are reported.


Evaluation of Computer Games Developed by Primary School Children to Gauge Understanding of Programming Concepts


title: CoCoSpec: A Mode-Aware Contract Language for Reactive Systems

abstract: Contract-based software development has long been a leading methodology for the construction of component-based reactive systems, embedded systems in particular. Contracts are an effective way to establish boundaries between components and can be used efficiently to verify global properties by using compositional reasoning techniques. A contract specifies the assumptions a component makes on its context and the guarantees it provides. Requirements in the specification of a component are often case-based, with each case describing what the component should do depending on a specific situation (or mode) the component is in. We introduce CoCoSpec, a mode-aware assume-guarantee-based contract language for embedded systems built as an extension of the Lustre language. CoCoSpec lets users specify mode behavior directly, instead of encoding it as conditional guarantees, thus preventing a loss of mode-specific information. Mode-aware model checkers supporting CoCoSpec can increase the effectiveness of the compositional analysis techniques found in assume-guarantee frameworks and improve scalability. Such tools can also produce much better feedback during the verification process, as well as valuable qualitative information on the contract itself. We presents the CoCoSpec language and illustrate the benefits of mode-aware model-checking on a case study involving a flight-critical avionics system. The evaluation uses Kind \(2\), a collaborative, parallel, SMT-based model checker extended to fully support CoCoSpec.


title: The physical impacts of microplastics on marine organisms: a review.

abstract: Plastic debris at the micro-, and potentially also the nano-scale, are widespread in the environment. Microplastics have accumulated in oceans and sediments worldwide in recent years, with maximum concentrations reaching 100 000 particles m(3). Due to their small size, microplastics may be ingested by low trophic fauna, with uncertain consequences for the health of the organism. This review focuses on marine invertebrates and their susceptibility to the physical impacts of microplastic uptake. Some of the main points discussed are (1) an evaluation of the factors contributing to the bioavailability of microplastics including size and density; (2) an assessment of the relative susceptibility of different feeding guilds; (3) an overview of the factors most likely to influence the physical impacts of microplastics such as accumulation and translocation; and (4) the trophic transfer of microplastics. These findings are important in guiding future marine litter research and management strategies.


title: A 16 Kb Spin-Transfer Torque Random Access Memory With Self-Enable Switching and Precharge Sensing Schemes

abstract: Spin-transfer torque magnetic random access memory (STT-MRAM) is considered one of the most promising non-volatile memory candidates thanks to its excellent performance in terms of access speed, endurance, and compatibility to CMOS. However, high power supply voltage is required in the conventional STT-MRAM writing circuit, which results in high power consumption (e.g., ${\sim}{10}~{\rm pJ}/{\rm bit}$ ). In addition, it suffers from stochastic switching behavior and process voltage temperature variations. These make power-efficient and reliable write/read circuits become critical challenges. In this paper, we present novel circuits and architectures to build a 16 kb STT-MRAM design with low power and high reliability. For example, the self-enable switching scheme reduces the power consumption effectively and the fore-placed sense amplifier improves the robustness to process variation. Using an accurate compact model of 65 nm STT-MRAM and a commercial CMOS design kit, mixed transient and statistical simulations have been performed to validate this design.