Reviewerly/exHarmony huggingface dataset:
Signed Coreference Resolution

Coreference resolution is key to many natural language processing tasks and yet has been relatively unexplored in Sign Language Processing.In signed languages, space is primarily used to establish reference.Solving coreference resolution for signed languages would not only enable higher-level Sign Language Processing systems, but also enhance our understanding of language in different modalities and of situated references, which are key problems in studying grounded language.In this paper, we: (1) introduce Signed Coreference Resolution (SCR), a new challenge for coreference modeling and Sign Language Processing; (2) collect an annotated corpus of German Sign Language with gold labels for coreference together with an annotation software for the task; (3) explore features of hand gesture, iconicity, and spatial situated properties and move forward to propose a set of linguistically informed heuristics and unsupervised models for the task; (4) put forward several proposals about ways to address the complexities of this challenge effectively 1 .
Development of Problem Based Learning Based E-modules in the form of Flipbooks on Environmentally Friendly Technology Materials As an Independent Learning Material for Students Especially Online Learning

Problem solving skills are important to have in the 21st century. In the online learning period, students are required to be able to learn independently from home. However, in fact the motivation of students' learning has decreased. To facilitate students' self-learning during online learning, improving learning motivation and problem solving skills, teachers need to provide interesting learning materials. Therefore, this research aims to develop self-learning materials in the form of problem based learning e-module flipbooks on Environmentally Friendly Technology materials. This research is research and development with Lee Owens development model namely analysis, design, development and evaluation. The data collected in the form of qualitative data in the form of comments and suggestions validators and quantitative data in the form of validation scores of material experts, media and readability. The data collection instruments used are material expert validation test sheets, media experts, teachers and readability tests. Data analysis techniques are descriptive analysis. The results showed that the e-module flipbook developed has a succession of feasibility percentages from the validation tests of material experts, media experts and teachers, namely 84.03, 84.62 and 95.00%. Meanwhile, the percentage of readability tests to students was 87.81%. Teachers and students showed a response that the developed flipbook was interesting and suitable for self-learning during the pandemic. It can be concluded that, the e-module flipbook developed falls into the category of very valid (worth using) and excellent. It is expected to test the effectiveness of flipbooks to learning and develop flipbooks for other materials
Adaptive Assessment Model in Online Teaching Practices for English Teacher Education Programs

This study aimed to design an assessment model in response to the enactment of policies regarding the use of Elearning at all educational institutions including English teacher education programs.The policies are considered rather fresh but have a very broad fundamental impact on the quality of teaching and learning, especially at English teacher education programs.The lack of accommodating assessment guidelines is exclusively important to be paid serious attention to as it is directly related to achieving the desired learning outcomes.Therefore, the study and development of an appropriate and practical model like this are needed for an assessment reference or guideline that is not fixated on conventional teaching methods but is adaptive to the use of technological innovations as indicated by policies regarding the employment of E-learning at teacher education programs.This is an effort to improve the quality of teaching and learning that is more applicable and contextual to support the transition of learning modes and styles that adopt technological innovations at teacher education programs, particularly with the presence of Covid-19 which has urged all to transition to online teaching and learning.RCFES (Reflective, Collaborative, Formative, E-Portfolio, Summative) model is expected to contribute further to the development of a more widely usable adaptive assessment model or framework for online teaching and learning.
Deep learning inspired continuous estimation framework for Scrum projects

IT companies are embracing Agile methodologies for their current and upcoming software projects. The most challenging aspect is project management. Many CASE tools came up as solution to handle dynamic specificities of Scrum based projects. The present state reveals companies rely on the traditional ways of handling estimation issues of software projects which suffers from individual bias and subjective assessment. Scrum projects are volatile and as per the Agile Manifesto incur changes in the various phases. Story point is a relative metric of measuring effort of desired user stories in Scrum. It has been classified and predicted using traditional and machine learning techniques. In this paper, we have proposed a novel framework for story point classification in Scrum projects using deep learning. The proposed framework is end-to-end trainable and lays the foundation of a continuous estimation framework.
PERSEPSI MAHASISWA STIKES HARAPAN IBU JAMBI TERHADAP PEMBELAJARAN DARING VIA ZOOM PADA MASA PANDEMI COVID-19

The purpose of this study was to determine the perceptions of Sekolah Tinggi Ilmu Kesehatan Ibu Jambistudents towards online learning via Zoom during the Covid-19 pandemic. Method. This research used descriptive method. The sample was collected using a non-probability sampling technique with an accidental sampling approach. The results of this study indicated that students' expectations of the use of zoom were to make online learning easier, used in theory learning and also for discussion with friends.
Models and Tasks for Human-Centered Machine Translation

In this talk, I will describe current research directions in my group that aim to make machine translation (MT) more human-centered.Instead of viewing MT solely as a task that aims to transduce a source sentence into a wellformed target language equivalent, we revisit all steps of the MT research and development lifecycle with the goal of designing MT systems that are able to help people communicate across language barriers.I will present methods to better characterize the parallel training data that powers MT systems, and how the degree of equivalence impacts translation quality.I will introduce models that enable flexible conditional language generation, and will discuss recent work on framing machine translation tasks and evaluation to center human factors.
Application of Virtual Reality Technology in Film and Television Animation Based on Artificial Intelligence Background

The application of artificial intelligence technology in the film and television field has profoundly changed the content and production methods of television programs and promoted the development and production of a new generation of artificial intelligence television. The popularization of artificial intelligence technology is conducive to improving the quality of television program content, innovating content categories, reducing television program production cost, and improving production efficiency. Due to the popularization and the use of virtual reality (VR) technology in scientific research and social life, the application of VR technology has been studied from the perspective of film and television animation (FTA) teaching, hoping to promote the development of FTA education. First, the existing dynamic environment modeling technology, real-time three-dimensional (3D) graphic generation technology, stereoscopic display, and sensor technology and other VR technologies are combined to carry out teaching design. In view of the current situation of the teaching process of FTA major, the research on these four aspects has been carried out. VR technology is used as an auxiliary teaching tool to complete the basic course teaching of FTA; the 3D animation course and VR technology are combined to improve the teaching effect of professional skill courses. Then, in the application effect, classroom satisfaction, comprehensive quality evaluation, and professional core curriculum effect are compared and analyzed. The results show that the students’ comprehensive quality evaluation in VR technology group is significantly improved, and the satisfaction of classroom atmosphere, teaching mode, and teaching facilities are 75%, 61%, and 81%, respectively. The students in this group can better integrate the new design method into the animation modeling and complete the course design task with high quality. Compared with the traditional teaching mode, the students’ satisfaction is higher and the harvest is greater. Therefore, the use of VR technology in FTA teaching can stimulate students’ interest in learning, improve learning efficiency, and promote the mastery of professional knowledge and skills. The application mode and effect analysis of the proposed VR technology provide a reference for the application of VR technology in FTA teaching.
Detection of Phishing Attacks using Content Analysis in the Cloud

In the world of internet and technology, technical advancement is widely accepted by both types of users - with and without technical knowledge. Advancement in technologies also brings in different risks involved along with it. These risks involve risks of being compromised at any point of time, leading to identity theft or financial loss or loss of very confidential information. Phishing attacks are one such kind of attack which can trap anyone into it, let it be a novice user or a sophisticated user. This paper involves what phishing attacks are, how the phishers target cloud services, how they deceive users, how the phishers send phish sites to its target. It also includes the background process that happens in normal scenarios and during phishing, a proposed mechanism which can be used for detection, safety measures which if taken can reduce the chances of falling in the trap and mechanisms used by researchers in order to detect and prevent phishing sites.
Fast and Accurate Deep Learning Architecture on Vehicle Type Recognition

Vehicle Type Recognition has a significant problem that happens when people need to search for vehicle data from a video surveillance system at a time when a license plate does not appear in the image. This paper proposes to solve this problem with a deep learning technique called Convolutional Neural Network (CNN), which is one of the latest advanced machine learning techniques. In the experiments, researchers collected two datasets of Vehicle Type Image Data (VTID I &amp; II), which contained 1,310 and 4,356 images, respectively. The first experiment was performed with 5 CNN architectures (MobileNets, VGG16, VGG19, Inception V3, and Inception V4), and the second experiment with another 5 CNNs (MobileNetV2, ResNet50, Inception ResNet V2, Darknet-19, and Darknet-53) including several data augmentation methods. The results showed that MobileNets, when combine with the brightness augmented method, significantly outperformed other CNN architectures, producing the highest accuracy rate at 95.46%. It was also the fastest model when compared to other CNN networks. &nbsp; Keywords: Vehicle Type Image Recognition; image classification; Convolutional Neural Network; deep learning; pattern recognition; image recognition *Corresponding author: Tel.: (+66) 43-754359 &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;E-mail: olarik.s@msu.ac.th
DESIGN AND BUILD VIRTUAL TOUR PANORAMA 360 HOSPITALITY CENTER UNP AS PROMOTIONAL MEDIA

Abstract:The UNP Hospitality Center virtual tour application aims to help promote to potential visitors, and as an interactive promotional media. Hospitality Center UNP is an inn located in the Padang State University area and has various types of rooms and meeting facilities. Based on interviews with the UNP Hospitality Center internal parties, the promotions used are still using brochures. This tool only provides a little information to potential visitors about the rooms and facilities, namely only with photos and writing, this makes limited information that can be conveyed because with a brochure prospective visitors can only see one picture of each existing facility. The data collection stage was carried out by the method of interviews and direct observation. The next stage for developing the author's application uses the Multimedia Development Life Cycle (MLDC) method. consists of Concept, Design, Material Collecting, Assembly, Testing, and Distribution. The main features of this application are: hospitality profile, panorama list, location, floorplan and usage information. With these main features, it is found that by using the UNP Hospitality Center virtual tour application, it can make it easier to promote to prospective UNP Hospitality Center guests.&#x0D; &#x0D;
Internet technology as one of distance education during pandemic

The article aims at allowing you to deepen the knowledge of the program material on computer science and, as a consequence, will increase the efficiency of the educational process as a whole during a pandemic, will increase the motivation of students to the subject; will allow developing students' abilities for self-development, self-education. Based on the purpose, subject, hypothesis of the research, the following tasks were solved: scientific methodological and pedagogical literature on the topic of research was studied; revealed the content and essence of Internet technologies; an Internet resource has been developed that allows organizing the process of distance learning in informatics; tested the effectiveness of its use in the process of teaching computer science to students. The practical significance of the study lies in the creation of an educational Internet resource that allows students to acquire the skills to independently create a Web site. This Internet resource can be used for forms of work in informatics in any educational institution during a pandemic.
Application Of 3D Technology In Criminal Proceedings

Under current conditions, there is practical demand for the introduction of 3D technology into law enforcement activities, which can be used to solve a wide range of criminal proceedings.Based on positive examples of foreign experience in application of this technology in combating crime, there were practical opportunities of 3D technology in activities of the investigator, expert, in criminal proceedings including those with the participation of jurors.It was revealed that the application of 3D technology in the criminal proceedings in Russia is currently at the stage of formation.The reason is in a complex of problems of logistical, ethical-legal nature, as well as the lack of a proper methodological support.The creation of new and improvement of existing computer programs for creating a 3D model of objects related to the committed crime, depending on the specific tasks of criminal proceedings was proposed.The need for the settlement of legal issues of the possibility of using information and communication technologies in pre-trial and trial investigations was indicated.The organization of training of investigators, experts, prosecutors on the methodology of using 3D technologies was proposed in specific areas of their activities at the advanced training courses, etc.
Personal Assistant Robot

Since the boom in science and technology, humans have been trying to invent machines that could reduce their efforts in day to day activities. In this paper, we develop a personal assistant robot that could pick up objects and return it to the user. The robot is controlled using an android application in mobile phones. The robot can listen to user’s command and then respond in the best way possible. The user can command the robot to move to given location, capture images and pick objects. The robot is equipped with ultrasonic sensor and web camera that helps it to move to different location effectively. It is also equipped with sleds that play important role in object picking process. The robot uses a tiny YOLOv3 model which is rigorously trained on several images of the object. There are some possible improvements that can be achieved which could help this robot to be used in several other fields as well.
Opinion Mining Analytics for Spotting Omicron Fear-Stimuli Using REPTree Classifier and Natural Language Processing

Abstract: Data has indisputably proven overtime to have a better idea and with the surge of big data in the era of coronavirus, research initiatives in the field of data mining continues to leverage computational methodologies. Owing to the dreadful nature of the Omicron-variant, a fight or flight dilemma readily pervades college communities far reaching implications on work ethics of academic front-liners. This study therefore aim to gain insights from academia-sourced data to unravel fear-stimulus in college communities. The predictive analytics is carried out on college-based opinion poll. The Valence Aware Dictionary for Sentiment Reasoning algorithm is deployed for emotion analytics while the Latent Dirichlet Allocation (LDA) and Latent Semantic Indexing (LSI) are employed for topic modelling. The REPTree algorithm models the fear-spotting decision tree using 10-fold cross-validation. Experimental results shows a high performance metrics of 94.68% on Recall and Precision as the hand-washing attribute is returned as the most significant variable with highest information gain. Results of topic modelling likewise returns non-clinical precautionary measures as fear stimulus while the Vader sentiment analysis shows a 22.47%, 25.8%, and 51.73% positive, negative, and neutral polarity scores respectively, indicative of the academic front-liners’ pessimism towards effective safety measure compliance with non-clinical regulations. Keywords: COVID-19, Omicron, Sentiment Analysis, Topic Modelling.
Digital Library Development: a Case Study of Ta Quang Buu Library of Hanoi University of Science and Technology

The purpose of the article is to introduce some theoretical issues of digital transformation related to the development of digital libraries and propose measures such as evaluating library users, creating digital collections from endogenous and exogenous sources, upgrading digital infrastructure of the library to enrich digital data sources for university's digital library Research motivation:The article aims to improve the service quality of the library of higher education institutions based on developing the university's digital library system by combining the existing traditional library with the digital library system as well as other databases in the country and abroad under the booming of digitalization and digital transformation. Research design, approach and method:The systematic literature review approach was applied in this study to briefly review the appearance and nature of the concepts of digital transformation; methods of comparative analysis and case study are used to analyze the survey data to find out the shortcomings of Ta Quang Buu Library in particular HEIs' libraries, and then discuss the obtained results to propose useful recommendations. Main findings:The case study of Ta Quang Buu Library of Hanoi University of Science and Technology shows that in order to improve service quality, it is necessary to focus on the characteristics and habits of users, and improve the capacity and skills of users.librarian, develop digital resources, finance IT infrastructure development as well as build database for E-learning in the long term in cooperation with other libraries and databases. Practical/managerial implications:The article focuses on the development of university digital libraries in the digital era and look at solutions to create digital libraries to improve the quality of library services.
Development of the Digital Banking Customer Retention Model (DBCRM) through the Evaluation of Service Dimensions: The Case Study of Lloyds Bank, United Kingdom

Technology is a change agent in the banking industry in order to transition conventional banking towards digital banking.To be successful in digital banking, both positive and negative effects need to be studied.Furthermore, significant dimensions need to be identified to provide better digital services and to retain customers.Nine digital banking effects: accessibility, usefulness, ease of use, availability, efficiency & effectiveness, reliability, responsiveness, cost effectiveness and security have been discussed from the customer satisfaction, loyalty and retention perspectives by reviewing the existing literatures.To collect the data, to apply and test how these service dimensions, particularly, impact customer retention, customers of Lloyds bank plc in the United Kingdom have been selected.Data analysis using Binary Logistic Regression has resulted key factors: less cost-effectiveness, less availability, less accessibility and less security which impact customer switching intention in Lloyd's bank.Therefore, Digital Banking Customer Retention Model (DBCRM) was introduced with the appropriate recommendations to enhance the customer retention.
John Senior and Éva Gyarmathy: AI and Developing Human Intelligence, Future Learning and Educational Innovation

AI is a branch of computer science that emphasises the development of intelligent machines that think and work like humans. Examples of AI applications are speech recognition, natural language processing, image recognition etc. The term ML represents the application of AI to enable systems’ ability to learn and improve based on experience, without the explicit need for programming, using various problem-solving algorithms. For example, in machine learning, computers learn based on the data they process, not program instructions