Reviewerly/exHarmony huggingface dataset:
Low latency streaming and multi DRM with dash.js

Video streaming applications account for 60% of today's global internet traffic. The trend to consume videos over the internet lead to a high demand for sophisticated and robust video players. dash.js is an open source DASH player of the DASH-Industry-Forum written in JavaScript utilizing the native browser APIs Media Source Extensions (MSE) and Encrypted Media Extensions (EME). This paper gives a general overview of the player and presents two specific features namely low-latency streaming and multi DRM playback. For that purpose, we illustrate how CMAF chunks in combination with the corresponding dash.js APIs and additional manifest parameters enable low latency streaming in the browser. For DRM support we focus on the interaction between dash.js, the EME and the underlying Content Decryption Module (CDM) of the browser.
Paraphrasing to improve the performance of Electronic Health Records Question Answering.

This paper describes a paraphrasing approach to improve the performance of question answering (QA) for electronic health records (EHRs). QA systems for structured EHR data usually rely on semantic parsing, which aims to generate machine-understandable logical forms from free-text questions. Training semantic parsers requires large datasets of question-logical form (QL) pairs, which are labor-intensive to create. Considering the scarcity of large QL datasets in the clinical domain, we propose a framework for expanding an existing dataset using paraphrasing. We experiment with different heuristics for multiple sample sizes and iterations to assess the effect of adding paraphrasing to the task of semantic parsing. We found that adding paraphrases to an existing dataset based on TERTHRESHOLD scores results in an improved performance in the majority (74%) of the experimental runs. Hence, the proposed paraphrasing-based framework has the potential to improve the performance of QA systems using a limited set of existing QL annotations.
Beyond Symbolic Heaps: Deciding Separation Logic With Inductive Definitions

Symbolic-heap separation logic with inductive definitions is a popular formalism for reasoning about heap-manipulating programs. The fragment SLIDbtw introduced by Iosif, Rogalewicz and Simacek, is one of the most expressive fragments with a decidable entailment problem. In recent work, we improved on the original decidability proof by providing a direct model-theoretic construction, obtaining a 2-Exptime upper bound. In this paper, we investigate separation logics built on top of the inductive definitions from SLIDbtw, i.e., logics that feature the standard Boolean and separation-logic operators. We give an almost tight delineation between decidability and undecidabilty. We establish the decidability of the satisfiability problem (in 2-Exptime) of a separation logic with conjunction, disjunction, separating conjunction and guarded forms of negation, magic wand, and septraction. We show that any further generalization leads to undecidabilty (under mild assumptions).
Increasing data storage of coloured QR code using compress, multiplexing and multilayered technique

Quick response (QR) code is a printed code of black and white squares that is able to store data without the use of any of the electronic devices. There are many existing researches on coloured QR code to increase the storage capacity but from time to time the storage capacity still need to be improved. This paper proposes the use ofcompress, multiplexing and multilayered techniques, as an integrated technique known as CoMM, to increase the storage of the existing QR code. The American Standard Code for Information Interchange (ASCII) text characters are used as an input and performance is measured by the number of characters that can be stored in a single black and white QR code version 40. The experiment metrics also include percentage of missing characters, number of produced QR code, and elapsed time to create the QR code. Simulation results indicate that the proposed algorithm stores 24 times more characters than the black and white QR code and 9 times more than other coloured QR code. Hence, this shows that the coloured QR code has the potential of becoming useful mini-data storage as it does not rely on internet connection.
Recursive Template-based Frame Generation for Task Oriented Dialog

The Natural Language Understanding (NLU) component in task oriented dialog systems processes a user’s request and converts it into structured information that can be consumed by downstream components such as the Dialog State Tracker (DST). This information is typically represented as a semantic frame that captures the intent and slot-labels provided by the user. We first show that such a shallow representation is insufficient for complex dialog scenarios, because it does not capture the recursive nature inherent in many domains. We propose a recursive, hierarchical frame-based representation and show how to learn it from data. We formulate the frame generation task as a template-based tree decoding task, where the decoder recursively generates a template and then fills slot values into the template. We extend local tree-based loss functions with terms that provide global supervision and show how to optimize them end-to-end. We achieve a small improvement on the widely used ATIS dataset and a much larger improvement on a more complex dataset we describe here.
Risk Factors of Lifestyle Diseases – Analysis by Decagonal Linguistic Neutrosophic Fuzzy Cognitive Map

Lifestyle (LS) diseases are the outcomes of undesirable customs incorporated by the upcoming generation. The people of developed and developing nations are battling to procrastinate the epoch of mortality caused by LS diseases. The change in one’s health state is characterized by the extensive role of the respective internal and external environment. Contemporary social structure, occupational scenario, behavioural change, and recklessness of dietetics altogether have yielded a shallow health. This study considers the predominant lifestyle diseases and its risk factors in comprehensive perspective. Decagonal Linguistic Neutrosophic Fuzzy cognitive map facilitates the representation of indeterminacy and linguistic representation between the risk factors. This research work aims in developing a new methodology to determine the impact of one risk factor over the other by alleviating the indeterminacy.
Automatic video mosaicking algorithm via dynamic key-frame

Automatic video mosaicking is a challenging task in computer vision. Current researches consider either panoramic or mapping tasks on short videos. In this paper, an automatic mosaicking algorithm is proposed for both mapping and panoramic tasks based on the adapted key-frame on videos of any length. The speeded up robust features (SURF) and the grid motion statistic (GMS) algorithm are used for feature extraction and matching between consecutive frames, which are used to compute the transformation. In order to reduce the influence of the accumulated error during image stitching, an evaluation metric is put forward for the transformation matrix. Besides, a self-growth method is employed to stitch the global image for long videos. The algorithm is evaluated by using aerial-view and panoramic videos respectively on the graphic processing unit (GPU) device, which can satisfy the real-time requirement. The experimental results demonstrate that the proposed algorithm is able to achieve a better performance than the state-of-art.
Quantum polar decomposition algorithm

The polar decomposition for a matrix $A$ is $A=UB$, where $B$ is a positive Hermitian matrix and $U$ is unitary (or, if $A$ is not square, an isometry). This paper shows that the ability to apply a Hamiltonian $\pmatrix{ 0 &amp; A^\dagger \cr A &amp; 0 \cr} $ translates into the ability to perform the transformations $e^{-iBt}$ and $U$ in a deterministic fashion. We show how to use the quantum polar decomposition algorithm to solve the quantum Procrustes problem, to perform pretty good measurements, to find the positive Hamiltonian closest to any Hamiltonian, and to perform a Hamiltonian version of the quantum singular value transformation.
USAGE OF VIRTUAL REALITY IN THE EDUCATIONAL PROCESS AND VOCATIONAL GUIDANCE ON THE EXAMPLE OF “VRANALYTICS” SOFTWARE

The present article delves into one of the most promising computer technologies in education - virtual reality. Current usage of virtual reality technology in education is quite low, though it has a large number of advantages compared to other modern information technologies and provides possibilities that other technologies do not have. You can find a small amount of articles that highlight usage of virtual reality technology in different fields of education and almost no articles about possibility of using virtual reality technology for vocational guidance in school. Therefore, the main objectives of this article are, first, to describe and analyze potential possibility of usage of virtual reality technology in the modern educational process and vocational guidance. Second, to consider a virtual reality software product “VRAnalytics” that is currently under development. The main three objectives of “VRAnalytics” are: 1. Serve as an information environment aimed at informing the user about the modern world of professions and different specialties that exist nowadays. 2. Create tasks for the user in the form of a set of different puzzles that he/she needs to solve in the virtual reality. The purpose of such tasks is to provide the user with knowledge of the specificities of various professions and information about his/her abilities and skills, as well as their level of development in these skills. 3. Analyze and storage received information for further usage in vocational guidance and counselling. In addition, in the article we compare VR technology with other modern computer technologies and describe advantages and disadvantages of using virtual reality technology in educational process and vocational guidance, such as visibility, security, interactivity, immersion and focusing.
Optimizing Queries over Video via Lightweight Keypoint-based Object Detection

Recent advancements in convolutional neural networks based object detection have enabled analyzing the mounting video data with high accuracy. However, inference speed is a major drawback of these video analysis system because of the heavy object detectors. To address the computational and practicability challenges of video analysis, we propose FastQ, a system for efficient querying over video at scale. Given a target video, FastQ can automatically label the category and number of objects for each frame. We introduce a novel lightweight object detector named FDet to improve the efficiency of query system. First, a difference detector filters the frames whose difference is less than the threshold. Second, FDet is employed to efficiently label the remaining frames. To reduce inference time, FDet detects a center keypoint and a pair of corners from the feature map generated by a lightweight backbone to predict the bounding boxes. FDet completely avoid the complicated computation related to anchor boxes. Compared with state-of-the-art real-time detectors, FDet achieves superior performance with 29.1% AP on COCO benchmark at 25.3ms. Experiments show that FastQ achieves 150 times to 300 times speed-ups while maintaining more than 90% accuracy in video queries.
Scientific article as a means of effective communication: recommendations for writing and formatting

The role of the scientific journal in the process of solving strategic tasks of information and educational activities is shown. The significance of a scientific article as a publication genre depending on the level of the scientific community and communication goals is revealed. Recommendations for writing and formatting a scientific article from both a substantive and formal point of view are given. The levels of novelty, radicality and originality of scientific articles are justified. The principles of compiling a list of references when writing a scientific article are highlighted.
EXPLORATION OF VIDEO E-LEARNING CONTENT WITH SMARTPHONES

Nowadays computer users prefer to learn or complement their studies with video materials.While there are many video e-learning resources available on the internet, video sharing platforms such as YouTube which provide these resources, do not structure the presented material in the prerequisite order.Furthermore, they do not track the background of the users when recommending the next material to watch.Our aim is to overcome this limitation of the existing video on demand systems.In this paper we describe the architecture of the e-learning system that we are developing which allows users to search and watch video materials organized with respect to their background and presented in prerequisite order.One of the key features of our e-learning platform is to enable users to explore the video content with mobile devices.We propose a new visual metaphor based on lists for mobile devices which reflect the prerequisite graph structure, utilizing the limited screen size more effectively.
Digital universities in Russia: digitization with extra speed

The education sector is subject to significant changes due to the increasingly active spread of digital technologies. Usually, the trends in the implementation of digital technologies in educational and research activities are set by commercial organizations – private universities, business schools, corporate universities. But public universities and institutions start to think more and more about digital transformation. However, evolutionary path of universities’ digitization was destroyed by the spread of Coronavirus (COVID-19). It was decided to completely close universities, all students started to study from home. In this paper, we aimed to start a discussion about distance learning satisfaction among professors and lecturers; understand their vision about e-learning and the current stage of universities’ digitization. After examination of the current state of university digitization, we have identified major problems which become an obstacle during pandemic.
onto2problog: A Probabilistic Ontology-Mediated Querying System using Probabilistic Logic Programming

Abstract We present onto2problog , a tool that supports ontology-mediated querying of probabilistic data via probabilistic logic programming engines. Our tool supports conjunctive queries on probabilistic data under ontologies encoded in the description logic $$\mathcal{ELH}^{dr}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow><mml:mi>ELH</mml:mi></mml:mrow><mml:mrow><mml:mi>dr</mml:mi></mml:mrow></mml:msup></mml:math> , thus capturing a large part of the OWL 2 EL profile.
Firewall Technology in Computer Network Security in 5G Environment

Abstract in the Process of Computer Network Security Maintenance, Firewall Technology is the Main Security Maintenance Approach and Can Play an Effective Protection Role. Due to the Popularity and Widespread Use of Computer Technology, Network Security Has Received Widespread Attention from All Walks of Life. the Purpose of This Article is to Study Firewall Technology in Computer Network Security Based on 5G Environment. 5G Mobile Networks Also Have Some Shortcomings, Such as Weak Network Penetration Capabilities. Once the Base Station is Not Fully Deployed, There Will Be Gaps in the Borders of Communication Cells, Resulting in Network Data Transmission Interruption. in Order to Solve the Above Problems, This Paper Proposes Mobile Network Optimization Measures. Based on Many Years of Practice and Exploration, It Focuses on Describing the Complex Communication Application Scenarios in Cities, and Introduces a Variety of Mobile Network Optimization Technologies to Achieve Seamless Network Coverage and Ensure That People Can Use Mobile Communication Networks Normally. the High-Speed, Large-Capacity, Low-Latency, and High-Reliability Services Brought by 5G Will Have an Impact on the Local Optical Cable Architecture and Core Utilization. According to the Experimental Results, the Effective Application of Firewall Technology Can Greatly Improve the Security of Computer Networks and Ensure the Security of Computer Networks to a Great Extent.
A Publicly Available, High Resolution, Unbiased CT Brain Template

Clinical imaging relies heavily on X-ray computed tomography (CT) scans for diagnosis and prognosis. Many research applications aim to perform population-level analyses, which require images to be put in the same space, usually defined by a population average, also known as a template. We present an open-source, publicly available, high-resolution CT template. With this template, we provide voxel-wise standard deviation and median images, a basic segmentation of the cerebrospinal fluid spaces, including the ventricles, and a coarse whole brain labeling. This template can be used for spatial normalization of CT scans and research applications, including deep learning. The template was created using an anatomically-unbiased template creation procedure, but is still limited by the population it was derived from, an open CT data set without demographic information. The template and derived images are available at https://github.com/muschellij2/high_res_ct_template .
Multi-Graph Group Collaborative Filtering

The task of recommending an item or an event to a user group attracts wide attention. Most existing works obtain group preference by aggregating personalized preferences in the same group. However, the groups, users, and items are connected in a more complex structure, e.g.the users in the same group may have different preferences. Thus, it is important to introduce correlations among groups, users, and items into embedding learning. To address this problem, we propose Multi-Graph Group Collaborative Filtering (MGGCF), which refines the group, user and item representations according to three bipartite graphs. Moreover, since MGGCF refines the group, user and item embeddings simultaneously, it would benefit both the group recommendation tasks and the individual recommendation tasks. Extensive experiments are conducted on one real-world dataset and two synthetic datasets. Empirical results demonstrate that MGGCF significantly improves not only the group recommendation but also the item recommendation. Further analysis verifies the importance of embedding propagation for learning better user, group, item representations, which reveals the rationality and effectiveness of MGGCF.
Using Self-Training to Improve Back-Translation in Low Resource Neural Machine Translation

Improving neural machine translation (NMT) models using the back-translations of the monolingual target data (synthetic parallel data) is currently the state-of-the-art approach for training improved translation systems. The quality of the backward system - which is trained on the available parallel data and used for the back-translation - has been shown in many studies to affect the performance of the final NMT model. In low resource conditions, the available parallel data is usually not enough to train a backward model that can produce the qualitative synthetic data needed to train a standard translation model. This work proposes a self-training strategy where the output of the backward model is used to improve the model itself through the forward translation technique. The technique was shown to improve baseline low resource IWSLT'14 English-German and IWSLT'15 English-Vietnamese backward translation models by 11.06 and 1.5 BLEUs respectively. The synthetic data generated by the improved English-German backward model was used to train a forward model which out-performed another forward model trained using standard back-translation by 2.7 BLEU.
Minimum-Fuel Ascent of Hypersonic Vehicle considering Control Constraint Using the Improved Pigeon-Inspired Optimization Algorithm

Trajectory optimization problem for hypersonic vehicles has long been recognized as a difficult problem. This paper brings control constraints into the trajectory optimization to make the optimal trajectory meet the requirements of control performance. The strong nonlinear characteristic of the ascent phase aerodynamics makes the trajectory optimization problem difficult to be solved by the optimal control theory. A trajectory optimization algorithm based on the improved pigeon-inspired optimization (PIO) algorithm is proposed to solve the complex trajectory optimization problem under multiple constraints. To overcome the obstacle of premature convergence and deceptiveness, the evolutionary strategy of qubit in quantum evolutionary algorithm (QEA) is introduced into the PIO to maintain population diversity and judge the optimal solution. To handle constraints, the penalty function is used to construct the fitness function. The optimal ascent trajectory is obtained by utilizing the improved PIO algorithm. Then, the trajectory inverse algorithm is used to verify the feasibility of the optimal trajectory to ensure that a feasible optimal trajectory is obtained. The comparison results show that the proposed algorithm outperforms particle swarm optimization (PSO) and standard PIO on trajectory optimization. Meanwhile, the simulation result shows that the performance of the optimal ascent trajectory with control constraints is improved and the trajectory is feasible. Therefore, the method is potentially feasible for solving the ascent trajectory optimization problem under control constraint for hypersonic vehicles.
A Simplified Implementation of the Fixed-Function Graphics Pipeline: DRM Approach

In modern computer graphics architecture, the graphics processing unit (GPU) has a major role.Since GPU instructions and memory managements are hard to be directly controlled by application programmers, three-dimensional graphics application libraries, including OpenGL and DirectX, are widely used.In the Linux-family operating systems, they provide a set of kernel-level supporting modules.In this paper, we use those modules, such as the direct rendering manager (DRM) module, the kernel mode setting (KMS) module, and the graphics execution manager (GEM) module, to implement a fixed-function graphics pipeline.Our prototype system shows that those DRM modules can provide the full 3D graphics features without 3D graphics libraries and graphics window systems.Our detailed design and implementation schemes are presented.
Information and communication technologies in the professional development of vocational school teachers

The paper elaborates on the professional development of the vocational school teachers by using the information and communication technologies. It describes a qualitative research which included 20 teachers of vocational schools in the territory of the Republic of Serbia. The main aim of the research was to explore the vocational teachers' professional development which involves using the information and communication technologies and to provide answers to the following questions: To what extent are the vocational school teachers prepared in terms of their education for using the information and communication technologies in their professional development? What are the opinions of these teachers regarding the use of the information and communication technologies in their professional development? What are the forms of using these technologies in the vocational school teachers' professional development? The research findings indicate that there are several types of teachers' narratives regarding the above-mentioned questions and that these types vary relative to teachers' years of work experience. All teachers expressed positive attitudes towards using the information and communication technologies in their professional development. They have been trained to use these technologies, but the scope and intensity, as well as the preferred forms, of using these technologies for the purpose of professional development vary among the teachers.