Reviewerly/exHarmony huggingface dataset:
Discriminative Regions Erasing Strategy for Weakly-Supervised Temporal Action Localization

Weakly-supervised temporal action localization (WTAL) has recently attracted attentions. Many of the state-of-the-art methods usually utilize temporal class activation map (T-CAM) to obtain target action temporal regions. However, class-specific T-CAM tends to cover only the most discriminative part of the actions, not the entire action. In this paper, we propose an erasing strategy for mining discriminative regions in weakly-supervised temporal action localization (DRES). DRES achieves better performance with action localization, which can be attribute to two aspects. First, we employ the salient detection module, which suppresses the background to obtain the most discriminative regions. Second, we design the eraser module to discover the missed action regions by the salient detection module, which complements action regions. Based on experiments, we demonstrate that DRES improve the state-of-the-art performance on THUMOS'14.
Automated Transliteration of Late Egyptian Using Neural Networks: An Experiment in “Deep Learning”

We apply Deep Learning techniques to the task of automated transliteration of Late Egyptian. After a brief presentation of the technology used, we examine the result to highlight the capabilities of the system, which is able to deal with a wide range of problems, including grammatical and phraseological ones. We then proceed to extract signs values from what the system has automatically learnt.
Deep and Wide Neural Networks Covariance Estimation

It has been recently shown that a deep neural network with i.i.d. random parameters is equivalent to a Gaussian process in the limit of infinite network width. The Gaussian process associated to the neural network is fully described by a recursive covariance kernel determined by the architecture of the network, and which is expressed in terms of expectation. We give a numerically workable analytic expression of the neural network recursive covariance based on Hermite polynomials. We give explicit forms of this recursive covariance for the cases of neural networks with activation function the Heaviside, ReLU and sigmoid.
Enhancement of Risk Prevention Ability of Students Funding Subjects in the Age of All Media

The all-media is an important manifestation of technological development and conceptual progress in the new era, and plays an important role in the daily learning and life of college students. Various subjects of student funding work have made full use of modern multimedia technologies and methods, and have made many new attempts at improving funding effectiveness and reducing funding risks. Education authorities use data sharing to avoid fair risks, border colleges and universities use real-time multimedia tools to avoid procedural risks, recipients obtain funding information through information platforms to avoid beneficiary risks, and local student credit loan banks strictly abide by loan application procedures to avoid review risks. Through the establishment of a joint risk prevention and control mechanism for funding entities, the establishment of a sound scientific and standardized risk management system, and the strengthening of guidance and education for funding recipients, various measures have been taken to further enhance funding risk prevention capabilities.
PETA DISTRIBUSI FREKUENSI KASUS TB PARU DI PUSKESMAS PURWOYOSO TAHUN 2017-2018

Indonesia is still a high burden countries (HBC) based on 3 indicators, namely pulmonary TB / TB/HIV, and MDR-TB. The number of TB cases in Indonesia 2017 was 420,994 cases, 63 people died because of TB in Semarang, Purwoyoso Primary Healthcare is one of the healthcare center in Semarang that had not used GIS (Geographic Information Systems)-based reporting. This research is a descriptive study. The object of this study was the medical record of patients with pulmonary TB cases and pulmonary TB case reports in Purwoyoso Primary Healthcare. Mapping of pulmonary TB cases was made with MapInfo. The design of the Geographic Information System with the MapInfo application presents a report on pulmonary TB cases at Purwoyoso Primary Healthcare. Based on the comparison of the number of pulmonary TB cases in the Purwoyoso Primary Healthcare region between 2016-2017 and 2017-2018, the number of pulmonary TB cases decreased in Kelurahan Purwoyoso, Pulmonary TB cases in Kelurahan Purwoyoso decreased by 6%, from 53% cases in 2015 -2016 to 47% cases in 2017-2018, while cases of Pulmonary TB in Kelurahan Kalipancur increased from 25% cases in 2015-2016 to 75% cases in 2017-2018. Purwoyoso Primary Healthcare should use a geographic information system so that the reporting process can be more effective. Keywords: Pulmonary TB, Geographic Information System, Purwoyoso Primary Healthcare
Transferability of Natural Language Inference to Biomedical Question Answering

Biomedical question answering (QA) is a challenging task due to the scarcity of data and the requirement of domain expertise. Pre-trained language models have been used to address these issues. Recently, learning relationships between sentence pairs has been proved to improve performance in general QA. In this paper, we focus on applying BioBERT to transfer the knowledge of natural language inference (NLI) to biomedical QA. We observe that BioBERT trained on the NLI dataset obtains better performance on Yes/No (+5.59%), Factoid (+0.53%), List type (+13.58%) questions compared to performance obtained in a previous challenge (BioASQ 7B Phase B). We present a sequential transfer learning method that significantly performed well in the 8th BioASQ Challenge (Phase B). In sequential transfer learning, the order in which tasks are fine-tuned is important. We measure an unanswerable rate of the extractive QA setting when the formats of factoid and list type questions are converted to the format of the Stanford Question Answering Dataset (SQuAD).
El uso de las TIC en el entrenamiento deportivo: una propuesta operativa ante la COVID-19/The TICs usage in the sport training: an operative proposal during COVID-19

It has become accustomed to the practice of sport in a face-to-face, in-situ relationship, but the social distance inherent in the confinement produced by the COVID-19 dismissed face-to-face, generating distance between the coach and his athlete. The objective of this article is to offer a conceptual and operational resource with examples of the approach to the use of ICTs as an alternative solution for sports training. The phenomenological-hermeneutic method was used, applying the interview technique and the bibliographic review, whose instruments were validated by experts' judgment; the first one was applied to eight coaches of collective sports whose sports work is developed in the province of Tungurahua, whose function was to obtain empirical information that serves as a complement to the review, both allowed a critical analysis of two categories: the labor implications on the presential distance and virtual approach and the needs for sports training generated by the crisis of COVID-19. It was concluded that facing the crisis could be worrying initially, but the examples presented will help to direct a new way of managing and conducting training by applying ICTs giving a real alternative solution.
Regenerating Image Caption with High-Level Semantics

Automatically describing an image with a sentence is a challenging task in the crossing area of computer vision and natural language processing. Most existing models generate image captions by an encoder-decoder process based on convolutional neural network (CNN) and recurrent neural network (RNN). However, such a process employs low level pixel-level feature vectors to generate sentences, which may lead to rough captions. Therefore, in this paper, we introduce high-level semantics to generate better captions, and we propose a two-stage image captioning model: (1) generate initial captions and extract high-level semantic information about images; (2) refine initial captions with the semantic information. Empirical tests show that our model achieves better performance than different baselines.
Mobile Learning Application With NativeScript Framework For Learning Material

University is a place for the learning process and develops creativity in accordance with its own major program. There for an application is needed to fulfill those requirements. The application is not limited to the time and place as the result they could be used anywhere and anytime to support creativity between student and teacher. Mobile learning is one of the most suitable applications to support learning process and creativity development. Through Mobile Learning the teaching and learning process especially to acquire the teaching material can be easily access without limited time and place so communication between student and teacher can be more routine, efficient and can create learning process more focus and have an purposes balance with the lesson plan . Mobile learning application uses java script, css and native script framework that will make the next development for this application can be more easier, because nativescript framework already separate each module in accordance with its function. Finally, it facilitates the development of mobile application, so it is expected to be the first step in the mobile software future development.
Ubiquitous Display: Research on Interaction Design Based on Flexible Display

From a cathode ray tube (CRT) based graphical user interface (GUI) to a flat panel liquid crystal display (LCD) based natural user interface (NUI), From e-ink based e-readers to organic light-emitting diode (OLED) based consumer electronics products, and virtual space display based on VR/AR technology, etc. The development of display technology promotes the development of information carriers towards more diverse characteristics. We will find that the carrier displayed on the interface changes from fixed to movable, from real to virtual. Imagine that the carrier of future information will eventually surpass our traditional screen, and develop from ubiquitous computing to ubiquitous display. This article describes the product morphological characteristics and interaction design challenges in flexible user interfaces. Based on literature research and design case analysis, the key points in the design of flexible display interfaces are introduced in three aspects: the dimensions of the information architecture, the form of information display, and the definition of interaction behavior. Finally, the article explores future ubiquitous display application scenarios, and proposes design possibilities such as the integration of information space and physical space, the extension of design objects, and more ecologically intelligent feedback.
포스트 코로나를 대비하는 예술교육: 언택트 시대의 몸교육에 관한 소고

This study began as a pandemic shock urging us to change our way of life. Is body-based education in the age of untouched a crisis or an opportunity? It summarize an idea of arts education combined with technology that will be divided before and after COVID-19.
A data analysis framework for motion sickness recognition

Motion sickness arises when the brain receives discordant sensory information from the body, eyes and vestibular system. People who suffer from this disorder experience nausea, fatigue and general discomfort when they travel by plane, car, ship, but also in amusement park rides and in virtual reality environments. The aim of this thesis project is to preventively detect this state of illness when travelling, in order to improve the travel experience, but also to prevent any negative effects on their own health. To achieve this objective, different techniques of data analysis are adopted. These physiological signals are recorded during a driving simulation carried out in a laboratory. Data relating to the dermal conductivity of the subjects examined are processed. In the framework outlined by this thesis work, the first point addressed is that of data pre-processing, in order to accurately extract the features that characterize the behaviour of the selected signal. The extraction of the features of the dermal conductivity signal of each subject is performed on overlapping time windows, in order to monitor in detail the physiological response of the subject to each perceived stimulus. During the simulation the individuals provides information about their state of health. To each window corresponds a label assigned on the basis of this information supplied, allowing the classification process. The label identifies whether the subject is in a state of sickness or not in that time window. The proposed solution compares different classification algorithms aiming to build a machine learning model to recognize and therefore predict the motion sickness. The experimental evaluation shows that it is feasible to develop a promising model in order to achieve the explained purpose.
Analysis of Weibull Statistic Features Impact on Image Degradation Measurement

The traditional concept of quality of service (QoS) which focuses on network performance (e.g. packet loss, throughput, and transmission delay), recently has been grown towards the modern concept of quality of experience (QoE). This reflects all user practice including accessing and service provided. In order to maintain the required QoE, it’s necessary for the service provider to recognize and measure image degradation. This study provides different features in order to assess degraded image quality blindly depending on Weibull statistics. Also, it presents a comparison analysis to give the more performing one. The introduced features are originated from the gist of natural scenes (NS) using Weibull distribution of Log-derivatives. These measuring features were collected through both sharper and rich edging regions of the images. Besides, Weibull features were developed by maximum likelihood estimation (MLE) parameters to improve the quality assessment. LIVE database used to calibrate the proposed features achievement. Experiments prove Weibull statistics the best among popular full-reference peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) methods. Also, they show Weibull features extracted by means of sharper regions are the best when assess the prediction monotonicity. While applying the prediction accuracy evaluation come up with a good performs when taking the improved Weibull features via sharper regions.
Characteristics of Web References in Journal of Computer-Mediated Communication

The present paper explores the characteristics of web references in the Journal of Computer Mediated Communication during the year 2008–2017. A total of 337 articles were downloaded and 17946 references were extracted. Out of 4548 web citations, DOIs were found in 2360 references, 2178 references contained URLs and 10 references contained others like arXiv, etc. The study investigated the characteristic features of display and destination URLs like the path depth, URL length, file format, and top-level domain. It was found from the study that the most widely used file format in the references were the HTML file formats. URLs with path depth 2 and character length of 41 to 50 were cited frequently and it can also be noted from the study that the most used top-level domain in the references was the organizational top-level domain. Further, it was observed that there was a difference in the characteristic features of display and destination URLs.
Video Generative Adversarial Networks: A Review.

With the increasing interest in the content creation field in multiple sectors such as media, education, and entertainment, there is an increasing trend in the papers that uses AI algorithms to generate content such as images, videos, audio, and text. Generative Adversarial Networks (GANs) in one of the promising models that synthesizes data samples that are similar to real data samples. While the variations of GANs models, in general, have been covered to some extent in several survey papers, to the best of our knowledge, this is among the first survey papers that reviews the state-of-the-art video GANs models. This paper first categorized GANs review papers into general GANs review papers, image GANs review papers, and special field GANs review papers such as anomaly detection, medical imaging, or cybersecurity. The paper then summarizes the main improvements in GANs frameworks that are not initially developed for the video domain but have been adopted in multiple video GANs variations. Then, a comprehensive review of video GANs models is provided under two main divisions according to the presence or non-presence of a condition. The conditional models then further grouped according to the type of condition into audio, text, video, and image. The paper is concluded by highlighting the main challenges and limitations of the current video GANs models. A comprehensive list of datasets, applied loss functions, and evaluation metrics is provided in the supplementary material.
How KOHA OPAC can be Designed and used as Library Website: A Practical Approach

This work is intended to provide HTML and CSS Codes to design the effective OPAC page to use as Library OPAC as well as Library website. The main objective of the study was to define easy to adopt steps to design OPAC. Authors have tried to demonstrate design of Library website by using KOHA OPAC page with help of HTML and CSS code (Annexure 1).
Pembelajaran bahasa Indonesia aktif berbasis aplikasi Sarpu (smart crossword puzzle)

Purposes -  This journal was created as an outline of the Student Creativity Program in the field of community service. The purpose of this program is to implement the Sarpu (Smart Crossword Puzzle) application in active Indonesian learning activities. Methods -  Implementation of Active Indonesian Learning Based on the Sarpu (Smart Crossword Puzzle) Application conducted in several stages: (1) Planning, (2) Socialization, (3) Implementation, and (4) Program evaluation. The equipment used in implementing this program are: (1) Laptops, and (2) Smartphones. The objects in this program are Middle School Students in Medan City.Finding -  This program is carried out by implementing the Sarpu (Smart Crossword Puzzle) application in Indonesian language learning activities. Student responses are very good, this is seen in their interest in using the Sarpu (Smart Crossword Puzzle) application. So the team can conclude that active learning activities in Indonesian using the Sarpu (Smart Crossword Puzzle) Application are achieved.Keyword  -  Active Learning, Indonesian, Sarpu (Smart Crossword Puzzle)
Multi-scale spatio-temporal context visual tracking algorithm based on target model adaptive update

It is well known that achieving a robust visual tracking task is quite difficult, since it is easily interfered by scale variation, illumination variation, background clutter, occlusion and so on. Nevertheless, the performance of spatio-temporal context algorithm is remarkable, because the spatial context information of target is effectively employed in this algorithm. However, the capabilities of discriminate target and adjust to scale variation need to promote in complex scene. Furthermore, due to lack of an appropriate target model update strategy, its tracking capability also deteriorates. In the interest of tackling these problems, a multi-scale spatio-temporal context visual tracking algorithm based on target model adaptive update is proposed. Firstly, the histogram of oriented gradient features are adopted to describe the target and its surrounding regions to improve its discriminate ability. Secondly, a multi-scale estimation method is applied to predict the target scale variation. Then, the peak and the average peak to correlation energy of confidence map response are combined to evaluate the visual tracking status. When the status is stable, the current target is expressed in a low rank form and a CUR filter is learned. On the contrary, the CUR filter will be triggered to recapture the target. Finally, the experimental results demonstrate that the robustness of this algorithm is promoted obviously, and its overall performance is better than comparison algorithms.
A Privacy-protection Device Using a Directional Backlight and Facial Recognition

A novel privacy-protection device to prevent visual hacking is realized by using a directional backlight and facial recognition. The proposed method is able to overcome the limitations of previous privacy-protection methods that simply restrict the viewing angle to a narrow range. The accuracy of user tracking is accomplished by the combination of a time-of-flight sensor and facial recognition with no restriction of detection range. In addition, an experimental demonstration is provided to verify the proposed scheme.
Energy-saving control method of electric heating film temperature for urban zero energy consumption building heating

Aiming at the problem of high energy consumption of electrothermal membrane in building heating, the energy-saving control method of zero energy consumption building electrothermal membrane temperature is proposed. By using multithread parallel learning technology and temperature steady-state response to construct decoupling regulation method, the object model of building heating electric membrane temperature regulation is constructed; through the control increment analysis and correction of building heating electric membrane temperature regulation, the energy-saving control of building heating electric membrane is carried out, and the fault-tolerant optimisation analysis of building heating electric membrane is carried out. The energy-saving control model is used to control the heating film temperature of zero energy consumption building, and the fuzzy feedback adaptive control model is established. The experimental results show that the energy consumption of the proposed method is small and the temperature output has strong robustness and stability.
Effects of Picture Books Intervention on Language Learning Skills of Pupils with Learning Disabilities in Jos, Plateau State

This study examined the effects of picture books on language learning skills of pupils with learning disabilities. Quasi experimental research design was adopted for the study; specifically, the non-equivalent pretest-posttest control group design was used. The population of the study comprised of seventy eight primary two pupils with learning disabilities. Purposive sampling technique was used to select forty pupils as sample for the study. An adapted Functional Diagnostic Test of Language Assessment Instrument (FDTLA) and Assessment of Language Ability (ALA) score sheet were used to collect data which helped to answer the research questions and test the hypotheses raised. Data for the research was collected through administration of pretest on the experimental and control groups. After the pretest, the experimental group was exposed to an intervention using picture books, while the control group was taught using the conventional oral method in their regular classroom. Two research questions were answered using mean scores. Three hypotheses were formulated and two were tested using t-test for independent samples at 0.05 level of significance and one hypothesis was tested using ANCOVA. The results showed that picture books improved the language skills of the pupils significantly as shown in the performance of the experimental group who were subjected to an intervention using picture books as against pupils (control group) who were taught using the conventional method. In the same vein, the results also showed that there was no significant difference between the language learning skills of boys and girls after exposure to picture books.Keywords:  Picture Book, Intervention, Language Skills, Pupils with Learning Disabilities