Miracle-dz/UniFAR-FTUs huggingface dataset:
657 THE PROPER PLACE OF MEN AND MACHINES IN LANGUAGE TECHNOLOGY . PROCESSING RUSSIAN WITHOUT ANY LINGUISTIC KNOWLEDGE

The paper describes several experiments aimed at designing tools for processing Russian texts, namely for Part-Of-Speech tagging, lemmatisation and syntactic parsing, exploiting exclusively statistical approaches without coding any linguistic rules specifi cally for Russian. While not claiming any new ground for machine learning research, the results demonstrate the possibility to create state-of-the-art tools for Russian in very short time using only machine learning and no hard-coded linguistic knowledge. One of the results of this study is a set of publicly available resources which can be used in standard pipelines for processing Russian. However, they also demonstrate hidden costs associated with the use of purely statistical methods and the need to integrate linguistic parameters into statistical procedures.
Proposition D’un Instrument De Mesure De La Qualité De Service Perçue Par Les Usagers Des Administrations Publiques Marocaines

The objective of this article is to describe the development of a measurement scale to assess user perceptions in Moroccan public administrations about the quality of service. The measures were built from a survey of 302 users in the Casablanca-Settat region. The methodology is based on the steps recommended by the paradigm of Churchill (1979). Our contribution focuses on the exploratory phase of development of the ladder allowing the emergence of a factor structure of the theoretical variable quality. After presenting the conceptualization of this construct, the article describes the procedures used to construct a multi-item measure of this concept scale. He then states, from analysis of empirical data, the scale of properties in terms of factor structure and reliability. The results thus show a factorial structure of the quality of service perceived by the users of four components with a total variance explained 69.53%. Only the first component: Justice and equal treatment restores 43% of the total variance. The analysis of the reliability of the scales of the principal components shows that the items of each scale are correlated and coherent with each other with reliability indices varying between 0,77 and 0,89. It is the same for the reliability of the total scale of which Cronbach's alpha was 0,9.
An Improved Control System for Modular Multilevel Converters with New Modulation Strategy and Voltage Balancing Control

Modular multilevel converter (MMC) has become one of the most promising converter topologies for future high-power applications. A challenging issue of the MMC is the voltage balancing among arm capacitors. A good overall control system is also vital for the MMC, which should be based on sound mathematical model, readily adaptable for different applications, and capable of high performance. This paper presents a general control structure for MMC inverters, which is suitable for both voltage-based and energy-based control methods, and includes voltage balancing between the upper and lower arms. A new method for voltage balancing among arm capacitors, which is based on an improved pulse-width modulation, is also presented. The proposed method avoids some major disadvantages found in present voltage balancing methods, such as dependence on computation-intensive voltage sorting algorithms, extra switching actions, interference with output voltage, etc. Furthermore, all switching actions are evenly distributed among power devices. The proposed control system as a whole can serve as a promising solution for practical applications, especially when the number of submodules is fairly high. Simulation and experimental results verify the effectiveness of the proposed methods.
Workload prediction of wireless sensor network based on linear prediction

Wireless sensor network has been widely used in remote monitoring applications. However, energy efficiency of sensor nodes becomes an important issue as there are powered by batteries. This is because most of the sensor nodes are inaccessible once they have been deployed in the physical environment. Therefore, a good energy saving scheme of sensor nodes is essential in order to provide a long operational life for at least up to 2 years. Dynamic Voltage Scaling (DVS) scheme can be used to dynamically scaling the voltage level based on CPU's workload in order to save energy. In this paper, a linear prediction model is proposed to adjust the voltage level relating to its workload.
Hardware accelerator design for data centers

As the size of available data is increasing, it is becoming inefficient to scale the computational power of traditional systems. To overcome this problem, customized application-specific accelerators are becoming integral parts of modern system on chip (SOC) architectures. In this paper, we summarize existing hardware accelerators for data centers and discuss the techniques to implement and embed them along with the existing SOCs.
Visual feedback leader-following pose synchronization: Convergence analysis

This paper investigates visual feedback pose synchronization on SE(3) in leader-follower type visibility structures. After defining visual robotic networks to be controlled, we propose a visual feedback pose synchronization law combining a vision-based observer with the pose synchronization law presented in our previous works. We then prove that the visual robotic network with the control law achieves visual feedback pose synchronization in the absence of communication or any other measurements of the states. Finally, the validity of the proposed control law is demonstrated through experiments.
How Good Are These UML Diagrams? An Empirical Test of the Wand and Weber Good Decomposition Model

In 1989, Wand and Weber proposed a formal model of systems decomposition based on ontology. Chidamber and Kemerer (1994) soon applied this model to develop complexity metrics for object-oriented design (OOD). Chidamber and Kemerer’s OOD metrics suite continues to receive interest in software engineering (Bansiya and Davis 2002; Basili et al. 1996). To date, however, Wand and Weber’s good decomposition model has received almost no application in information systems (IS). For three reasons, we believe the theory might assist IS researchers. First, object-oriented analysis (OOA) has not been as successful in practice as OOD or OO programming (Chuang and Yadav 2000). The good decomposition model may help IS researchers investigate improvements to OOA. Second, Johnson (2002) recently lamented how few OOA studies employ any theory. Wand and Weber’s theory may, therefore, be a useful approach. Third, many believe OOA is a revolutionary step away from traditional approaches (Sircar et al. 2001). Practicing analysts could benefit from theory-based principles to guide their use of this “revolutionary” technique. In this study, we report an experiment to determine the utility of the good decomposition model in OOA. We operationalized each condition of Wand and Weber’s model in a set of UML diagrams and tested participants’ understanding of the diagrams across three levels. Our results lend support to Wand and Weber’s theory, but only across dependent variables that tested participants’ actual understanding. The impact on participants’ perceptions of their understanding remained equivocal.
Pr Rogram M Proceeding Gs Program Chairs

Building a research implementation of a new algorithm and validating it for a small set of benchmarks is a key component of pushing the state of the art of design and verification tools. Moreover, if the algorithm works, it is often also the most exciting phase of the long journey to have a new idea used by many people. The less exciting and often more painful part includes the productization of the research into a form that can be applied by hundreds or thousands of users on a daily basis. In this talk we discuss some of the challenges that developers encounter in a product development environment from prototyping to code maintenance. The presentation will cover practical aspects of developing software in larger teams from product planning to deployment and support. We will also elaborate on some of the opportunities for new research to help the practical deployment and maintenance of software products.
Influence of Hamstring Tightness in Pelvic, Lumbar and Trunk Range of Motion in Low Back Pain and Asymptomatic Volunteers during Forward Bending

Study Design Cross-sectional study. Purpose To verify the association of hamstring tightness and range of motion in anterior pelvic tilt (PT), lumbar motion (LM), and trunk flexion (TF) during forward bending. Overview of Literature Increased hamstring stiffness could be a possible contributing factor to low back injuries. Clinical observations have suggested that hamstring tightness influences lumbar pelvic rhythm. Movement restrictions or postural asymmetry likely lead to compensatory movement patterns of the lumbar spine, and subsequently to increased stress on the spinal soft tissues and an increased risk of low back pain (LBP). Methods Hamstring muscle tightness was measured using the self-monitored active knee extension (AKE) test. A bubble inclinometer was used to determine the range of motion of PT, LM, and TF during forward bending. Statistical analysis included descriptive statistics, comparisons between groups and a correlation between hamstring tightness (AKE) and anterior PT, TF, and regional LM with p≤0.05. Results The LBP group was composed of 36 participants, and the asymptomatic group consisted of 32 participants. The mean for PT in the control group was 66.7°, 64.5° for LM and 104.6° for TF. Respective values in the symptomatic group were 57.0°, 79.8°, and 82.2°. Conclusions Participants with LBP showed restriction in the pelvis and TF range of motion, but had higher amplitudes in the lumbar spine during forward bending.
Nattokinase improves blood flow by inhibiting platelet aggregation and thrombus formation

The effects of nattokinase on the in vitro platelet aggregation and in vivo thrombosis were investigated in comparison with aspirin. Rabbit platelet-rich plasma was incubated with nattokinase and aggregation inducers collagen and thrombin, and the platelet aggregation rate was analyzed. Nattokinase significantly inhibited both the collagen- and thrombin-induced platelet aggregations. Nattokinase also reduced thromboxane B2 formation from collagen-activated platelets in a concentration-dependent manner. Rats were orally administered with nattokinase for 1 week, and their carotid arteries were exposed. Arterial thrombosis was induced by applying 35% FeCl3-soaked filter paper for 10 min, and the blood flow was monitored with a laser Doppler probe. Nattokinase delayed the FeCl3-induced arterial occlusion in a dose-dependent manner, doubling the occlusion time at 160 mg/kg. In addition, a high dose (500 mg/kg) of nattokinase fully prevented the occlusion, as achieved with aspirin (30 mg/kg). The results indicate that nattokinase extracted from fermented soybean inhibit platelet aggregation by blocking thromboxane formation, and thereby delay thrombosis following oxidative arterial wall injury. Therefore, it is suggested that nattokinase could be a good candidate without adverse effects for the improvement of blood flow.
EventBuilder: Real-time Multimedia Event Summarization by Visualizing Social Media

Due to the ubiquitous availability of smartphones and digital cameras, the number of photos/videos online has increased rapidly. Therefore, it is challenging to efficiently browse multimedia content and obtain a summary of an event from a large collection of photos/videos aggregated in social media sharing platforms such as Flickr and Instagram. To this end, this paper presents the EventBuilder system that enables people to automatically generate a summary for a given event in real-time by visualizing different social media such as Wikipedia and Flickr. EventBuilder has two novel characteristics: (i) leveraging Wikipedia as event background knowledge to obtain more contextual information about an input event, and (ii) visualizing an interesting event in real-time with a diverse set of social media activities. According to our initial experiments on the YFCC100M dataset from Flickr, the proposed algorithm efficiently summarizes knowledge structures based on the metadata of photos/videos and Wikipedia articles.
Approximate Bayesian Computation: A Nonparametric Perspective

Approximate Bayesian Computation is a family of likelihood-free inference techniques that are well suited to models defined in terms of a stochastic generating mechanism. In a nutshell, Approximate Bayesian Computation proceeds by computing summary statistics sobs from the data and simulating summary statistics for different values of the parameter Θ. The posterior distribution is then approximated by an estimator of the conditional density g(Θ|sobs). In this paper, we derive the asymptotic bias and variance of the standard estimators of the posterior distribution which are based on rejection sampling and linear adjustment. Additionally, we introduce an original estimator of the posterior distribution based on quadratic adjustment and we show that its bias contains a fewer number of terms than the estimator with linear adjustment. Although we find that the estimators with adjustment are not universally superior to the estimator based on rejection sampling, we find that they can achieve better performance when there is a nearly homoscedastic relationship between the summary statistics and the parameter of interest. To make this relationship as homoscedastic as possible, we propose to use transformations of the summary statistics. In different examples borrowed from the population genetics and epidemiological literature, we show the potential of the methods with adjustment and of the transformations of the summary statistics. Supplemental materials containing the details of the proofs are available online.
Wireless Sensor Network Operating System Design Rules Based on Real-World Deployment Survey

Wireless sensor networks (WSNs) have been a widely researched field since the beginning of the 21st century. The field is already maturing, and TinyOS has established itself as the de facto standard WSN Operating System (OS). However, the WSN researcher community is still active in building more flexible, efficient and user-friendly WSN operating systems. Often, WSN OS design is based either on practical requirements of a particular research project or research group's needs or on theoretical assumptions spread in the WSN community. The goal of this paper is to propose WSN OS design rules that are based on a thorough survey of 40 WSN deployments. The survey unveils trends of WSN applications and provides empirical substantiation to support widely usable and flexible WSN operating system design.
A Vanishing Rural School Advantage? Changing Urban/Rural Student Achievement Differences in Latin America and the Caribbean

In 1997, a cross-national assessment of educational achievement in Latin America and the Caribbean found that rural schools in Colombia outperformed urban schools in tests of reading and mathematics, except in very large cities. Given a long history of urban/rural inequality in the region, Colombia’s rural school advantage attracted substantial attention. Yet by 2006, a follow-up to the 1997 assessment found that Colombia’s rural school advantage had vanished. This study’s objective is to determine whether, after adjusting for relevant background factors, Colombia’s rural school advantage persisted in 2006. We find that rural schools in Colombia retained their advantage in a limited way: all else equal, rural schools in Colombia outperformed marginally urban schools in mathematics, when comparing each type of school to urban schools. Analysis of the 2006 data finds that rural schools in several countries outperformed urban schools in tests of math and reading, after adjusting for student background.
Structural Basis for the Identification of the N-Terminal Domain of Coronavirus Nucleocapsid Protein as an Antiviral Target

Coronaviruses (CoVs) cause numerous diseases, including Middle East respiratory syndrome and severe acute respiratory syndrome, generating significant health-related and economic consequences. CoVs encode the nucleocapsid (N) protein, a major structural protein that plays multiple roles in the virus replication cycle and forms a ribonucleoprotein complex with the viral RNA through the N protein’s N-terminal domain (N-NTD). Using human CoV-OC43 (HCoV-OC43) as a model for CoV, we present the 3D structure of HCoV-OC43 N-NTD complexed with ribonucleoside 5′-monophosphates to identify a distinct ribonucleotide-binding pocket. By targeting this pocket, we identified and developed a new coronavirus N protein inhibitor, N-(6-oxo-5,6-dihydrophenanthridin-2-yl)(N,N-dimethylamino)acetamide hydrochloride (PJ34), using virtual screening; this inhibitor reduced the N protein’s RNA-binding affinity and hindered viral replication. We also determined the crystal structure of the N-NTD–PJ34 complex. On the basis of these findings, we propose guidelines for developing new N protein-based antiviral agents that target CoVs.
Gravure as an Industrially Viable Process for Printed Electronics

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Abstract In order for low-cost printed electronics to become ubiquitous, a suitable printing technique must be found. Gravure is a high-speed roll-to-roll printing technique which has many of the characteristics necessary for an industrially viable process for printed electronics. In gravure printing, an engraved cylinder is submerged in an ink fountain and then rolled over a flexible substrate such as plastic or paper. A tightly pressed blade, called the doctor blade, wipes off excess ink from the non-image areas of the cylinder surface before contact with the substrate. Gravure has the advantages of high throughput, long print runs, uniformity, and versatility. We explore the construction of a gravure printing system, including the design of a laboratory size printer and cylinder making techniques. Industrial best practices are presented along with techniques discovered in the laboratory. We discuss the choice of cylinder material, as well as different metrics for determining acceptable cylinders. Next, we compare four methods of patterning cylinders and discuss challenges in scaling to an industrial printing system. Next, we consider the theoretical considerations necessary to develop a printing process to deposit conductive lines less than 20 microns wide, suitable for bottom-gate thin film transistors (TFTs). We discuss the physical principles governing the gravure printing process, which can be separated into the two actions of cell emptying and drop spreading. We demonstrate gravure-printed nanoparticle lines and present techniques for optimizing the printed line quality by varying print parameters such as cell spacing and viscosity. Finally, we discuss possible routes to printed TFTs and future work. ii Acknowledgements
Quantization effects in implementation of distributions from the cohen class

The paper presents an analysis of the finite register length influence on the accuracy of results obtained by the time-frequency distributions (TFDs). In order to measure quality of the obtained results, the variance of the proposed model is found, signal-to-quantization noise ratio (SNR) is defined and appropriate expressions are derived. Floating- and fixed-point arithmetic are considered. It is shown that commonly used reduced interference distributions (RID) exhibit similar performance with respect to the SNR. We have also derived the expressions establishing relationship between the number of bits and required quality of representation (defined by the SNR), which may be used for register length design in hardware implementation of TFDs.
A Transfer-Aware Runtime System for Heterogeneous Asynchronous Parallel Execution

This paper presents a novel resource management approach for efficiently managing the computation and the data movements between the host and its accelerators in a heterogeneous platform. Our approach is based on OmpSs, with support for multi-core CPUs, GPGPUs and Maxeler Data Flow Engines based on FPGA technology; it exploits data locality, data transfer costs and data dependencies. The proposed approach is supported by an offline learning process coupled with online monitoring, allowing performance to be estimated while learning from past observations during execution. Its performance is compared against the current OmpSs scheduler using five benchmarks: matrix multiplication, bitonic sort, N-body simulation, Cholesky decomposition and AdPredictor. The results show the proposed approach can achieve up to 4.25 times speed-up for Cholesky decomposition. Moreover, an evaluation with AdPredictor indicates that the FPGA version is up to 46 times faster than the CPU version for large task sizes.
On Genetic Algorithm and Multiple Preprocessors Assisted Feature Boosting for Electronic Nose Signal Processing

The paper presents a method for feature extraction that explores data space through different preprocessing strategies in combination with principal component analysis (PCA) and genetic algorithm (GA). A preprocessor/PCA combination transforms data space into feature space; a change in preprocessor results in an alternate feature space. The proposed method first fuses the feature spaces by simple concatenation of the alternate feature vectors then allows them to evolve genetically. The genetic evolution of each fused feature vector is based on treating the feature vector as chromosome and the feature components as genes. The initial population is created on the basis of a probability distance metric. The fitness and ranking is done by using PCA generated variances as measure of significance. In the terminal population the frequency of a gene (principal component) occurrence is interpreted as a measure of its significance in defining the feature vector. Finally, the feature components are given additional weight according to ( ) j j ij ij p p z z 2 log 1− = where ij z denotes j-th feature component of i-th sample in fused feature space and j p denotes the probability of j-th component occurring in the terminal population. In order to demonstrate the efficacy of this idea we employed only two well known preprocessing methods: vector autoscaling and dimensional autoscaling. The feature vectors defined in this manner were used as input a radial basis neural network classifier for validation. Several benchmark datasets (both chemical and non-chemical) available from open sources were used in the analysis for validation. It is found that the scheme of feature fusion and weighting enhances classification rate in most cases analyzed.