Reviewerly/exHarmony huggingface dataset:
The Effect of TGT Model on Student Cognitive Learning Outcomes: The Concept of Relay Running

TGT cooperative type learning, as a game-based learning methodology, provides opportunities for students to develop skills in group interactions in small groups and work together with others. The world of learning today needs phenomena like this. This study aimed to determine the effect of the TGT cooperative type learning model on students' cognitive learning outcomes on the topic of relay running. This quantitative study was a quasi-experimental pretest-posttest design. The samples involved were 70 students from two different experimental and control classes. The data collection instrument in this study was 10 essay test questions validated and tested. The results showed an effect of the TGT cooperative type learning model on students' cognitive learning outcomes. The achievement test score for the TGT group was 81.67, while the control group was 75.75. It implies that the TGT group performed superior in cognitive learning outcomes when compared to the control group. Thus, it is concluded that the TGT cooperative type learning model can be recommended in improving students' cognitive learning outcomes on the concept of relay running.
Counter-Contrastive Learning for Language GANs

Generative Adversarial Networks (GANs) have achieved great success in image synthesis, but have proven to be difficult to generate natural language.Challenges arise from the uninformative learning signals passed from the discriminator.In other words, the poor learning signals limit the learning capacity for generating languages with rich structures and semantics.In this paper, we propose to adopt the counter-contrastive learning (CCL) method to support the generator's training in language GANs.In contrast to standard GANs that adopt a simple binary classifier to discriminate whether a sample is real or fake, we employ a counter-contrastive learning signal that advances the training of language synthesizers by (1) pulling the language representations of generated and real samples together and (2) pushing apart representations of real samples to compete with the discriminator and thus prevent the discriminator from being overtrained.We evaluate our method on both synthetic and real benchmarks and yield competitive performance compared to previous GANs for adversarial sequence generation.
Cadets' Perception in English Online Learning during Covid - 19 Pandemic

Indonesia has implemented online learning as part of its education reforms in an effort to contain the spread of the Covid – 19 virus. Study participants' perceptions of online learning during the Covid-19 pandemic are examined in this research. It was a descriptive quantitative study. Questionnaires (Google forms) and in-depth interviews were used to collect data. One hundred fifty-five cadets responded to the survey. Covid–19 pandemic showed that the cadets had an excellent view of online learning. Amid this pandemic, they discovered that online learning was helpful but not entirely efficient. Online learning by lecturers was effective, efficient, varied, helped cadets understand the material, independent learning, and increased students' involvement in learning activities. Additionally, this study gathered information from students in the form of constructive feedback on how to improve online learning. Covid – 19 pandemic cadets also discovered a number of obstacles related to online learning, such as barriers to students' accessing online learning platforms. In the context of the Covid-19 pandemic, the need for further research into the extent of the digital divide is necessitated by this study.
Law Enforcement The Crime Of Corruption Abuse Of School Operational Assistance Funds

With the existence of school operational assistance funds (BOS), it is hoped that public access to quality education is expected can be achieved. However, in practice the use of BOS funds is not always what is expected. This is because there are irresponsible elements who often misuse the BOS funds. Individuals who use BOS funds not in accordance with the guidelines for the use of BOS funds can be held legally responsible. The occurrence of corruption in the misuse of school operational assistance funds is caused by several factors, namely the school operational assistance management team that should have been formed by the school principal has never been formed, so that the management of school operational assistance funds is not transparent and accountable. Another factor is the weakness of the control system in the management of the School Operational Assistance Fund, which creates opportunities for managers to use BOS funds for personal interests. Perpetrators of criminal acts of corruption misuse of school operational assistance funds have been processed by law enforcement officials. The process starts from the stages of investigation, prosecution and trial and has obtained a final and binding decision. Even the perpetrator who was convicted and has served the sentence imposed on him. In the process, law enforcement officers have carried out the law enforcement process and have provided legal certainty for the actions of the perpetrators. However, the results of the process are still far from the principles of justice and benefits for the community
Knowledge-Enriched Natural Language Generation

Knowledge-enriched text generation poses unique challenges in modeling and learning, driving active research in several core directions, ranging from integrated modeling of neural representations and symbolic information in the sequential/hierarchical/graphical structures, learning without direct supervisions due to the cost of structured annotation, efficient optimization and inference with massive and global constraints, to language grounding on multiple modalities, and generative reasoning with implicit commonsense knowledge and background knowledge. In this tutorial we will present a roadmap to line up the state-of-the-art methods to tackle these challenges on this cutting-edge problem. We will dive deep into various technical components: how to represent knowledge, how to feed knowledge into a generation model, how to evaluate generation results, and what are the remaining challenges?
A Comparison of Gesture and Controller-based User Interfaces for 3D Design Reviews in Virtual Reality

We present a custom virtual reality (VR) hand-tracking user interface developed in Unity, and compare it with a similar industry level application (CTRL Elements) utilising controllers.Both applications afford spawning, relocating, reorienting, and rescaling 3D models within a virtual environment in addition to horizontal, vertical, and rotational user movement options.The interfaces are tested with Oculus Quest 2 VR headset, which is also responsible for the hand-tracking.Our main motivation is to gain an insight into whether hand-tracking UIs could provide added value to industrial design review solutions.We also pinpoint the major advantages and flaws in the controllerless approach and report which of our gesture-based controls are the most intuitive and usable.
The Effect of Performance Appraisal Systems on Employees and Organizations in Omani Private and Governmental Institutions

The aim of the research is to identify the impacts and outcomes of employee appraisal system on both employees and institutions for the Omani public and private organizations. The quantitative research method has been implemented via a survey approach for employees in both Omani public and private institutions. Data was collected from employees in Omani private and public sector companies. Data was analyzed using SPSS version 25.0. The investigation found that Omani employees are at above medium level of satisfaction towards the “used appraisal techniques” and the “duration of appraisal process” while they have less satisfaction towards the “Methods of appraisal reports” and “The responsible for the preparation of performance reports”. The investigation found high effectiveness of the appraisal systems implemented in their institutions towards the development of personal career of employees and the achievement of the organizations’ objectives.No significant difference found for the impact of implemented performance appraisal system different This study is important for the management of Omani organizations, as it pays the attention to the need to make some improvements in different sides of the currently implemented appraisal systems even in private or public sector organizations.
Sparse Representation-Based Discriminative Metric Learning for Brain MRI Image Retrieval

Magnetic resonance imaging (MRI) can have a good diagnostic function for important organs and parts of the body. MRI technology has become a common and important disease detection technology. At the same time, medical imaging data is increasing at an explosive rate. Retrieving similar medical images from a huge database is of great significance to doctors' auxiliary diagnosis and treatment. In this paper, combining the advantages of sparse representation and metric learning, a sparse representation-based discriminative metric learning (SRDML) approach is proposed for medical image retrieval of brain MRI. The SRDML approach uses a sparse representation framework to learn robust feature representation of brain MRI, and uses metric learning to project new features into the metric space with matching discrimination. In such a metric space, the optimal similarity measure is obtained by using the local constraints of atoms and the pairwise constraints of coding coefficients, so that the distance between similar images is less than the given threshold, and the distance between dissimilar images is greater than another given threshold. The experiments are designed and tested on the brain MRI dataset created by Chang. Experimental results show that the SRDML approach can obtain satisfactory retrieval performance and achieve accurate brain MRI image retrieval.
“Are You Ready?” Revisiting Needs Analysis for ESP Online Conversation Course

It is common to be found in an ESP class where the students are not fully engaged in the learning activities due to their lack of interests toward English. To attract the ESP students’ interests, authentic materials and meaningful activities need to be provided. Online learning can bring authentic materials to ESP students and give them meaningful activities as they can interact with native speakers of English through many online platforms. To fit the students’ online learning situations to their learning experiences, as well as the materials and activities to be given, a needs analysis should be carried out. The study focuses on discovering the ESP students’ preparedness in performing an online English conversation course by conducting a needs analysis. Questionnaires were given to 82 students and an interview was performed with 17 students to gain the data. The data collected in the form of percentages were analyzed by describing them qualitatively. From the analysis, it can be concluded that the ESP students were prepared to join the online English conversation course.
Explaining the Entombed Algorithm

In [1], John Aycock and Tara Copplestone pose an open question, namely the explanation of the mysterious lookup table used in the Entombed Game's Algorithm for two dimensional maze generation. The question attracted media attention (BBC etc.) and was open until today. This paper answers this question, explains the algorithm and extends it to three dimensions.
A Drift Indication of Unearthing in Face Detection and Feature Extraction

Nowadays analysis of research on face recognition has explored to extracting auxiliary data from varied biometric techniques like fingerprints, face, iris, palm, voice etc. Research on face recognition, face detection and feature extraction has a long history, and even may be derived back to the nineteenth century. However, the first face detection in the main reckons on a priori information of bound folks and might not free itself from human intervention. Until the looks of high speed, superior computers, the face detection methodology makes a big burst through. Face detection has been a quick growing, difficult and fascinating space in real time applications. Facial detection and feature extraction becomes an interesting research topic. A large range of face detection and feature extraction algorithms are developed in last decades. In this paper a shot is created to review a good vary of strategies used for face recognition comprehensively. This paper contributes a huge survey of varied face detection and feature extraction techniques. At the moment, there are loads of face detection and feature extraction techniques and algorithms found and developed round the world.
On Validating Cognitive Diagnosis Models for the Arithmetic Skills of Elementary School Students

Cognitive diagnosis models (CDMs) have been shown to provide detailed evaluations of students' achievement in terms of proficiency of individual cognitive attributes.Attribute hierarchy model (AHM), a variant of CDM, takes the hierarchical structure of those cognitive attributes to provide more accurate and interpretable measurements of learning achievement.However, advantages of the richer model come at the expense of increased difficulty in designing the hierarchy of the cognitive attributes and developing corresponding test sets.In this study, we propose quantitative tools for validating the hierarchical structures of cognitive attributes.First, a method to quantitatively compare alternative cognitive hierarchies is established by computing the inconsistency between a given cognitive hierarchy and students' responses.Then, this method is generalized to validate a cognitive hierarchy without real responses.Numerical simulations were performed starting from an AHM designed by experts and responses of elementary school students.Results show that the expert-designed cognitive attribute explains the students' responses better than most of alternative hierarchies do, but not all; a superior cognitive hierarchy is identified.This discrepancy is discussed in terms of internalization of cognitive attributes.
LIFI BASED INDOOR NAVIGATION SYSTEM FOR THE VISUALLY IMPAIRED PEOPLE

Localization and navigation system are practically viable and can easily be used but are not commonly used in real time.According to world health organization there were 285 million visually impaired people and 39 million were blind.Various technologies like RFID, ZigBee have been suggested but they all possess serious drawbacks and hence are not practically used.In this paper an indoor navigation and information system that is easy to implement and use has been proposed, because it uses visible light communication (VLC), which is an ideal technology for an application like this.Visually impaired people confront unique challenges in their day-to-day life when navigating in unfamiliar public locations.The proposed system focuses on designing a device for visually impaired people that is comfortable, user friendly and also helps travelling independently.A VLC navigation system is useful for assisting blind people.This system aims to provide location information in the absence of explicit instructions and can be a supporting method for users who travel in buildings.The transmitter section contains LED lights emitting visible lights that contain positional information to provide direction to the user.In the receiver section the embedded system calculates the optimal path to a designation and speaks to the person through a headphone or speaker.In addition to the basic navigation capabilities, the proposed system also aims to provide the user certain information on the nearby points-of-interest (POI) and accessibility issues such as stairs, drain, etc.The voice or data is used as an output result of transmission of LED lights.
The use of augmented reality for the formation of multicultural competence of undergraduates

The problem and the aim of the study. The system Higher education of Russian Education adapts to the challenges of globalization and new priorities of society, the values of students from different countries, expands the range of pedagogical technologies and ways to include them in the educational process. For the training of highly qualified specialists, the development of multicultural competence as an integrated personal quality, mixed learning, 3D modeling, augmented and virtual reality are actively used in higher education. The purpose of the article is to investigate the features of the use of augmented reality for the formation of multicultural competence of undergraduates. Research methods. The theoretical analysis and generalization of scientific literature are used to identify the problems of using innovative pedagogical technologies for the development of professional and general cultural competencies of university graduates in the conditions of digitalization of society. The main idea is determined by the principle of multicultural education, which involves obtaining of new knowledge, intercultural interaction, the formation of a worldview, etc. in an environment of augmented reality. The Zome application is used as a software tool. The study of augmented reality and software implemented in the format of a quest. The experiment involved 42 students of the Vyatka State University of the training program 44.04.01 Pedagogical education (level of magistracy). As a method of statistical processing of the experimental data, the χ2 (chi-square) Pearson test was used. Results. In the experimental group, undergraduates used the tools of the AR-application to studies of fundamental theory, consolidations of professional skills, intercultural communications and joint activities. The assessment of the levels of digital literacy formation was made and statistically significant differences in the qualitative changes that occurred in the pedagogical system were revealed, χ2obs. 2 &gt; χ2crit0.05 (6, 27 &gt; 5,99). In conclusion, the features of the use of augmented reality as a new pedagogical technology for the formation of multicultural competence of undergraduates and improving the quality of education are summarized.
Pengukuran Kepuasan Pengguna Website Politeknik ATI Padang Berdasarkan Persepsi Pengguna Internal

Website is an important part of any organization namely in the government, business, health and education sectors. In the world of higher education, website can be used to disseminate information related to campus life as well as a medium for promoting the existence of the campus to the outside world. As a higher education institution, Polytechnic ATI Padang own a website which is used to display various information about campus academic activities. In its management, the level of user satisfaction of the website of Polytechnic ATI Padang has never been measured. The Webqual 4.0 method used in this study aims to measure the satisfaction of internal website users by looking at the dimensions of Usability, Information Quality, Interaction Quality and Customer Satisfaction. Measurements performed by using a questionnaire instrument with Likert scale then calculated with the help of SPSS software. The results obtained that the independent variables, namely Usability, Information Quality, Interaction Quality have an influence on the dependent variable Customer Satisfaction of 70.1% and there are still 29.9% of other independent variables that can affect the dependent variable Customer Satisfaction. Furthermore, based on the results of the calculation of the satisfaction level with Likert scale, it was found that the variables of Usability, Information Quality, Interaction Quality and Customer Satisfaction received a satisfied interpretation, so it can be concluded that the Polytechnic ATI Padang website provides good service to its users.
Dataset Evaluation for Multi Vehicle Detection using Vision Based Techniques

Vehicle detection is one of the primal challenges of modern driver-assistance systems owing to the numerous factors, for instance, complicated surroundings, diverse types of vehicles with varied appearance and magnitude, low-resolution videos, fast-moving vehicles. It is utilized for multitudinous applications including traffic surveillance and collision prevention. This paper suggests a Vehicle Detection algorithm developed on Image Processing and Machine Learning. The presented algorithm is predicated on a Support Vector Machine(SVM) Classifier which employs feature vectors extracted via Histogram of Gradients(HOG) approach conducted on a semi-real time basis. A comparison study is presented stating the performance metrics of the algorithm on different datasets.
Informed Sampling for Diversity in Concept-to-Text NLG

Deep-learning models for language generation tasks tend to produce repetitive output.Various methods have been proposed to encourage lexical diversity during decoding, but this often comes at a cost to the perceived fluency and adequacy of the output.In this work, we propose to ameliorate this cost by using an Imitation Learning approach to explore the level of diversity that a language generation model can reliably produce.Specifically, we augment the decoding process with a metaclassifier trained to distinguish which words at any given timestep will lead to high-quality output.We focus our experiments on conceptto-text generation where models are sensitive to the inclusion of irrelevant words due to the strict relation between input and output.Our analysis shows that previous methods for diversity underperform in this setting, while human evaluation suggests that our proposed method achieves a high level of diversity with minimal effect to the output's fluency and adequacy.
EXPRESSIVE SPEECH ACTS ON NETIZENS’ COMMENTS IN JOE BIDEN’S INSTAGRAM ACCOUNT

United States presidential election 2020 is the most awaited event for the citizens of the United States. People usually want to get to know how good the presidential candidates are by searching for information about the presidential candidates. Checking the presidential candidates’ social media is one way to find outtheirprofiles.Joe Biden as one of the presidential candidates uses the growing popularity of Instagram to gain public attention by posting some of his responses to current issues and promoting himself as the next President of the United States. It made Joe Biden’s Instagram account is filled with netizens’ comments. This research aims to identify the expressive speech acts that appear in Joe Biden's comments published on September 13, 2020, to January 20, 2021, and to describe the reasons for their use of these expressive speech acts. The instrument of this research is a document. The data were collected by browsing the comments on Joe Biden’s Instagram post, then the data were selected, and identified the expressive speech acts used by netizens, then the research showed the findings of the research by presenting data and analysis. There are 26 data contained an expressive speech act, in which 10 data as expressive of thanking, 3data as expressive of congratulating, 5 data as expressive of wishing, 8 data as expressive of attitude. The expressive speech act of thanking is the most dominant type of expressive speech act found on the netizens’ comments of Joe Biden Instagram post. In conclusion, netizens’ comments contained the expressive speech act of thanking since netizens appreciated the good things that Joe Biden had planned when he ran for President of the United States. Joe Biden frequently posts his thoughts on various issues and promises a good solution in the future. Netizens expressed their gratitude for Joe Biden because they felt they had found a leader who cared about society.