Reviewerly/exHarmony huggingface dataset:
State Dependent Riccati Equation (SDRE) controller design for moving obstacle avoidance in mobile robot

In this paper, a new navigating method for a non-holonomic wheeled moving robot in a dynamic environment with the moving obstacles is proposed. This method is indeed the combination of the nonlinear optimal controller based on State-Dependent Riccati Equation (SDRE) and an obstacle avoidance algorithm named artificial potential field (APF). The corresponding cost function of the SDRE is obtained of APF algorithm. APF algorithm forces the robot to approach the target as an attracting (low-potential) point and to get away from the obstacle as a repulsing (high-potential) point. This method calculates the best path from origin to destination which also implicitly guaranties the stability. The obtained path is the best according to the both amount of traveled distance and input energy. Moreover, this approach not only avoid both fixed and moving obstacle, but also create a smooth path in presence of them. Keeping the nonlinear structure of the system instead of eliminating them during the linearization process is the advantage of SDRE method. Here, the robot navigation is done in the presence of the three different movements of obstacle: (1) fixed speed, (2) fixed acceleration and (3) non-uniform circular. The represented simulation results indicate a suitable performance of the proposed algorithm.
Schemas and the frequency/acceptability mismatch: Corpus distribution predicts sentence judgments

Abstract A tight connection between competence and performance is a central tenet of the usage-based model. Methodologically, however, corpus frequency is a poor predictor of acceptability – a phenomenon known as the “frequency/acceptability mismatch”. This article argues that the mismatch arises from a “methodological mismatch”, when simple frequency measures are mapped onto complex grammatical units. To illustrate, we discuss the results of acceptability judgments of go / come- v . The construction is subject to a formal constraint ( Go see the doctor! vs. *He goes sees the doctor ), which results from its mandative semantics (directives, commissives). While a formal model makes no prediction with regard to gradient acceptability of bare (“grammatical”) go / come - v , the usage-based view assumes that acceptability is a function of compatibility with an abstract schema. The experimental ratings are compared with a number of corpus-derived measures: while acceptability is largely independent of (raw) frequency, it is not independent of frequency- related usage distribution. The results add to recent suggestions that the frequency/acceptability mismatch is substantially reduced if the syntactic complexity of a unit is appropriately captured in usage data.
Infrared Pedestrian Detection Based on Attention Mechanism

Abstract Pedestrian detection is one of the key technologies in computer vision, and plays an important role in surveillance and automatic driving. Compared with visible cameras, infrared cameras are more suitable for all-weather and all-day work. Recently, a number of methods have been proposed for infrared pedestrian detection, but cannot achieve a satisfactory performance in the case of small pedestrians. In this paper, we propose an improved RefineDet algorithm to solve the aforementioned problem. First, the aspect ratio in our method is modified to the range of an average person. Second, an attention mechanism is introduced to address the small spatial size of pedestrian. In addition, we develop a new dataset which includes small pedestrian for performance evaluation. Experiments demonstrated that our method can achieve a superior performance as compared to SSD and RefinDet methods.
Exploring Baselines for Combining Full Plots into Multiple-plot Stories

Abstract Many of the stories at the core of narrative entertainment involve a number of plot lines that combine to give them interest. The present paper sets out to solve the problem of how several different plot lines, each one of them complete in its own sense, can be combined into a single linear sequence that works reasonably well as a plot. Starting from a brief review of how existing storytelling systems address the task, a representation for plots and plot templates is proposed that allows the combination of several subplots into a single-plot line. Four strategies for weaving plots are proposed, two taken from literary studies and two computational baselines, and a formative evaluation of a set of stories produced by these solutions is presented. Finally, open issues, promising avenues of future work and the relation to previous work, are discussed.
Covid-19 forecasting in Morocco using FBprophet Facebook's Framework in Python

Coronavirus Disease COVID-19 is a virus identified as the cause of an outbreak of severe acute respiratory syndrome detected first in Wuhan, China, On 31 December 2019.It has already taken a pandemic form, affecting over 200 countries in a few months.On March 3rd, 2020, the Moroccan Minister of Health announced the first case of coronavirus on March 2nd in Morocco, which was a Moroccan citizen who was returning from a trip to Italy.Then the pandemic spread has grown exponentially with more than 100,000 confirmed cases as of September 23th, 2020.After the partial lifting of containment in Morocco, the number of new cases reported daily is rising day by day.This study gives an indication of forecasting the spread of COVID-19 in the coming 4 months by Facebook Framework (FBprophet) using in python.This might be helpful for decision-makers and health authorities to evaluate risks and take proper precautions and strategies to minimize the spread of infectious diseases.
Dialogic Communication between Teachers and Students as a Condition for Interaction of Subjects of the Higher School Educational Process

The article is devoted to the issue of educational interaction and cooperation between teachers and students. The purpose of the study is to show the need for dialogic communication in educational activities, form knowledge, and develop educational cooperation skills, allowing students to take an active position in the educational process to help them adapt to interactive learning. The study's methodological base is the technology of sign-contextual learning, the implementation of which involves the use of active teaching methods. The article gives definitions of the concepts "communication", "dialogic communication", "subject". The principles of dialogic communication are highlighted. Experimental work was carried out in pedagogical classes with students of non-pedagogical specialties. Based on the thesaurus, questions, and tasks of the module, "Teaching Methods" were compiled, training was carried out using active methods. Systematic control was achieved by combining different types of work; however, a special role was played by testing, including computer testing. The result of developing communication-dialogue was the emergence of the participants' subjective positions in the dialogue, the formation of their experience of dialogic communication.
Robust 3D Hand Detection from a Single RGB-D Image in Unconstrained Environments

Three-dimensional hand detection from a single RGB-D image is an important technology which supports many useful applications. Practically, it is challenging to robustly detect human hands in unconstrained environments because the RGB-D channels can be affected by many uncontrollable factors, such as light changes. To tackle this problem, we propose a 3D hand detection approach which improves the robustness and accuracy by adaptively fusing the complementary features extracted from the RGB-D channels. Using the fused RGB-D feature, the 2D bounding boxes of hands are detected first, and then the 3D locations along the z-axis are estimated through a cascaded network. Furthermore, we represent a challenging RGB-D hand detection dataset collected in unconstrained environments. Different from previous works which primarily rely on either the RGB or D channel, we adaptively fuse the RGB-D channels for hand detection. Specifically, evaluation results show that the D-channel is crucial for hand detection in unconstrained environments. Our RGB-D fusion-based approach significantly improves the hand detection accuracy from 69.1 to 74.1 comparing to one of the most state-of-the-art RGB-based hand detectors. The existing RGB- or D-based methods are unstable in unseen lighting conditions: in dark conditions, the accuracy of the RGB-based method significantly drops to 48.9, and in back-light conditions, the accuracy of the D-based method dramatically drops to 28.3. Compared with these methods, our RGB-D fusion based approach is much more robust without accuracy degrading, and our detection results are 62.5 and 65.9, respectively, in these two extreme lighting conditions for accuracy.
Designing a personalized educational model while working with digital technologies

The problem and the aim of the study. The transformation of the educational environment identified the following development priorities for the didactic system: support for lifelong learning; personal orientation and taking into consideration the individual students’ personality structure; use of digital technologies to provide training of the sought-after professionals of the future. The authors propose to implement these requirements with the means and capabilities of modern information technologies that maximally take into account the characteristics of personification. Research methods. Theoretical and methodological analysis and generalization of fundamental scientific works on the research problem, processing of test results, problem solving, student’s choice (digital technology, appropriate software, functionality, sequence of tasks) were applied. The pedagogical experiment was attended by 101 students (35% of girls and 65% of boys) of the Law Institute of Vyatka State University of Kirov, Russia. The Fisher's criterion (angular transformation) was used as a statistical processing method. Results. The essence of the concepts "personal educational trajectory", "personal educational route" has been clarified. The challenges associated with the digital educational environment and a focus on training of the required professionals of the future were taken into account. The problems of personalization of learning (awareness of choice, determination of characteristic factors of the educational model, gradation of the task system) are identified, the content of which is described from the standpoint of the formal scheme of information interaction. An example of designing a personalized educational model is presented by studying the technology of processing spreadsheets (a system of educational problems that guide the trajectory of cognitive performance). At the control stage of the experiment, statistically significant differences were revealed between the experimental and control groups in terms of the level of formation of digital skills and skills that are in demand in the information society (φcrit=1.64&lt;φemp=2.492). Conclusion. Work with digital technologies offers the opportunity to take into account the orientation of the modern educational space towards personalization, the continuity of learning due to the implementation of the described formal scheme of information interaction between a teacher and a student in educational and cognitive activities; designing a differentiated system of tasks; supporting the student's informed choice; social and professional orientation of action.
Understanding Server Authentication in WPA3 Enterprise

In December 2019, the Wi-Fi Alliance published version 2 of WPA3, the new certification program for Wi-Fi devices that updates WPA2. This new version of WPA3 addresses, amongst other things, one of the crucial weaknesses of WPA2: in many practical deployments of enterprise Wi-Fi networks—i.e., networks in which users have personalized credentials—a device may easily be attacked by fraudulent access points claiming to have the name of the targeted network (evil twins). In this work, we present the mechanisms that WPA3 version 2 has introduced for mitigating these risks, which have become more and more relevant in recent years. We discuss the defensive power and potential impact of the various options available. Understanding the resulting scenario is important because WPA3 will determine the behavior of such a fundamental and widespread technology as enterprise Wi-Fi for many years, yet WPA3 enterprise networks may still be configured in a way that could not provide much better defensive power than WPA2.
Learning Geometry-Dependent and Physics-Based Inverse Image Reconstruction

Deep neural networks have shown great potential in image reconstruction problems in Euclidean space. However, many reconstruction problems involve imaging physics that are dependent on the underlying non-Euclidean geometry. In this paper, we present a new approach to learn inverse imaging that exploit the underlying geometry and physics. We first introduce a non-Euclidean encoding-decoding network that allows us to describe the unknown and measurement variables over their respective geometrical domains. We then learn the geometry-dependent physics in between the two domains by explicitly modeling it via a bipartite graph over the graphical embedding of the two geometry. We applied the presented network to reconstructing electrical activity on the heart surface from body-surface potential. In a series of generalization tasks with increasing difficulty, we demonstrated the improved ability of the presented network to generalize across geometrical changes underlying the data in comparison to its Euclidean alternatives.
Maximum likelihood estimation-assisted ASVSF through state covariance-based 2D SLAM algorithm

The smooth variable structure filter (ASVSF) has been relatively considered as a new robust predictor-corrector method for estimating the state. In order to effectively utilize it, an SVSF requires the accurate system model, and exact prior knowledge includes both the process and measurement noise statistic. Unfortunately, the system model is always inaccurate because of some considerations avoided at the beginning. Moreover, the small addictive noises are partially known or even unknown. Of course, this limitation can degrade the performance of SVSF or also lead to divergence condition. For this reason, it is proposed through this paper an adaptive smooth variable structure filter (ASVSF) by conditioning the probability density function of a measurement to the unknown parameters at one iteration. This proposed method is assumed to accomplish the localization and direct point-based observation task of a wheeled mobile robot, TurtleBot2. Finally, by realistically simulating it and comparing to a conventional method, the proposed method has been showing a better accuracy and stability in term of root mean square error (RMSE) of the estimated map coordinate (EMC) and estimated path coordinate (EPC).
DBpedia Archivo: A Web-Scale Interface for Ontology Archiving Under Consumer-Oriented Aspects

Abstract While thousands of ontologies exist on the web, a unified system for handling online ontologies – in particular with respect to discovery, versioning, access, quality-control, mappings – has not yet surfaced and users of ontologies struggle with many challenges. In this paper, we present an online ontology interface and augmented archive called DBpedia Archivo, that discovers, crawls, versions and archives ontologies on the DBpedia Databus. Based on this versioned crawl, different features, quality measures and, if possible, fixes are deployed to handle and stabilize the changes in the found ontologies at web-scale. A comparison to existing approaches and ontology repositories is given .
Experimental entanglement-assisted weak measurement of phase shift

Weak value amplification is a popular method in quantum metrology for enhancing the sensitivity at the expense of the signal intensity. Recently, it was suggested that the trade-off between signal intensity and sensitivity can be improved by using an entangled auxiliary system. Here, we experimentally investigate such entanglement-assisted weak measurement of small conditional phase shifts induced by an interaction between ancilla and meter qubits. We utilize entangled photon pairs and implement the required three-qubit quantum logic circuit with linear optics. The circuit comprises a two-qubit controlled phase gate and a three-qubit controlled-controlled phase gate with fully tunable conditional phase shifts. We fully characterize the output states of our circuit by quantum state tomography and perform a comprehensive analysis of the trade-off between the measurement sensitivity and the success probability of the protocol. The observed experimental results are in good qualitative agreement with theoretical predictions, but the overall performance of our setup is limited by various experimental imperfections. We provide a detailed theoretical analysis of the influence of dephasing of the entangled ancilla state, which is one of the main sources of imperfections in the experiment. We also discuss the ultimate scaling with the dimension of the entangled ancilla system.
Investigating How Smartphone Movement is Affected by Lying Down Body Posture

In this paper, we investigated how "lying down'' body postures affected the use of the smartphone user interface (UI) design. Extending previous research that studied body postures, handgrips, and the movement of the smartphone. We have done this in three steps; (1) An online survey that examined what type of lying down postures, participants, utilized when operating a smartphone; (2) We broke down these lying down postures in terms of body angle (i.e., users facing down, facing up, and on their side) and body support; (3) We conducted an experiment questioning the effects that these body angles and body supports had on the participants' handgrips. What we found was that the smartphone moves the most (is the most unstable) in the "facing up (with support)'' condition. Additionally, we discovered that the participants preferred body posture was those that produced the least amount of motion (more stability) with their smartphones.
A GAN‐based data augmentation method for human activity recognition via the caching ability

Sensor‐based human activity recognition (HAR) provides vital information for an ocean of health care and entertainment applications. However, data acquisition of such studies usually requires huge time and manpower, which delays the progress of the whole project. Data augmentation is a promising way to solve this issue. In this paper, we expand the origin dataset via a GAN‐based augmentation neural network. The experimental results suggest that the generated data has a certain substitution and complementary effect in terms of the real data based on the caching deployment ability. In addition, the quasi‐real data also gains good performance on identifying certain activities.
Robust supervised and semi-supervised twin extreme learning machines for pattern classification

In this paper, we first propose a novel robust loss function called adaptive capped Lθε-loss. The Lθε-loss has some interesting properties, such as robustness, non-convexity, and boundedness. During the learning process, for different problems, we can choose different loss functions through adaptive parameter θ. Then, a new robust twin extreme learning machine (RTELM) framework is presented by applying Lθε-loss and capped L1-norm distance metric. Compared with the twin extreme learning machine (TELM), RTELM overcomes the disadvantages of L2-norm distance metric and hinge loss, especially for the problem with outliers, while inherits the advantages of TELM. Further, we present a new Laplacian RTELM (Lap-RTELM for short) by introducing manifold regularization terms into RTELM. Intuitively, the Lap-RTELM can effectively utilize geometric information embedded in unlabeled samples and merge them as manifold regularization terms to learn a more reasonable classifier for semi-supervised classification (SSC) problems. Finally, two effective iterative algorithms are designed to solve the challenges brought by the non-convex optimization problems RTELM and Lap-RTELM, and theoretically guarantee the convergence, local optimality, and computational complexity of algorithms. Experiments on multiple datasets show that the proposed RTELM and Lap-RTELM are competitive with existing methods.
Vulnerability Assessment and Penetration Testing (VAPT) Framework: Case Study of Government’s Website

Information security often neglected by individual or employee or even by the enterprise, with there is no proper strategy to raise awareness, promote consistency and maintain performance regarding protect sensitive, confidential, and critical data. One of the common techniques used is a vulnerability assessment and penetration testing (VAPT) to assure the security strategy has been implemented into the computer system by analyzing both its strength and weakness. SQL plays an essential role in the Relation Database Management System (RDBMS) and its relationship to the existence of a website and its flexible operation because of its simplicity and integrity. To anticipate these types of threats or other Internet attacks, a goal-oriented penetration test that has a framework is recommended to identify specific types of vulnerabilities that lead to business concessions and to avoid the risks that adversely affect the enterprise Thus. This study conducts VAPT to uncover the possibility of threats and evaluate the potential impact to be reported to the system owner through a proper engagement framework that allows systematic measurement. Government websites have been identified for this purpose of the research to show the current trend that occurred in cyber communities, especially in Indonesia. This study has found various vulnerabilities lies in the directory listing, full path disclosure, PHP info disclosure, folder webserver disclosure, and other potential threats, which present 2 (two) critical, 6 (six) medium, and 2 (two) low level of risk.
Ontologies Supporting Research-Related Information Foraging Using Knowledge Graphs: Literature Survey and Holistic Model Mapping

We carried out a literature survey on ontologies dealing with the scholarly and research domains, with a focus on modeling the knowledge graphs that would support information foraging by researchers within the different roles they fulfill during their career. We identified 43 relevant ontologies, of which 35 were found sufficiently documented to be reusable. At the same time, based on the analysis of extensive CVs and activity logs of two senior researchers, we formulated a structured set of competency questions that could be answered through information foraging on the web, and created a high-level conceptual model indicating the data structures that would provide answers to these questions via a holistic knowledge graph. We then studied the retrieved ontologies and mapped them on the entities and relationships from our conceptual model. We identified many overlaps between the ontologies, as well as a few missing features. Preliminary proposals for dealing with some of the overlaps and gaps were formulated.