Reviewerly/exHarmony huggingface dataset:
Visual Object Tracking with Online Updating for Car Sharing Services

In this paper, we address the problem of online updating of visual object tracker for car sharing services. The key idea is to adjust the updating rate adaptively according to the tracking performance of the current frame. Instead of setting a fixed weight for all the frames in the updating of the object model, we assign the current frame a larger weight if its corresponding tracking result is relatively accurate and unbroken and a smaller weight on the contrary. To implement it, the current estimated bounding box’s intersection over union (IOU) is calculated by an IOU predictor which is trained offline on a large number of image pairs and used as a guidance to adjust the updating weights online. Finally, we imbed the proposed model update strategy in a lightweight baseline tracker. Experiment results on both traffic and nontraffic datasets verify that though the error of predicted IOU is inevitable, the proposed method can still improve the accuracy of object tracking compared with the baseline object tracker.
Analisis Faktor yang Mempengaruhi Gamers PC dan Konsol Beralih ke Game Mobile menggunakan Metode K-Means Clustering

This research was conducted because of the trend that has occurred in the last 5 years in Indonesia, namely the emergence of mobile-based games that are played by many people in Indonesia from small children to adults. With the emergence of mobile-based games in Indonesia, the appeal of PC and console-based games has become less attractive. This study aims to analyze the factors that influence PC and console-based gamers to switch to mobile-based games. The method used in this study is K-means Clustering and the supporting data from this study include the age factor of the game players and the duration of playing the game as a parameter. The technique of collecting data is through a google form questionnaire. The subject of the research is the Indonesian gamers forum contained in facebook forums.
D. S. MEREZHKOVSKY AS A STUDENT OF THE THIRD GYMNASIUM (COMMENTATOR’S NOTES) PART 2

The article introduces the academic community to a vast collection of the unknown documents from the archives of the Third Gymnasium (Classical School) and from Merezhkovsky’s personal foundation, which contains the experiments of his early years. As the result, a picture emerges that depicts the school routine, featuring the portraits of the professors and the analysis of the studies in humanities. Besides, a detailed commentary on the «Gymnasium» fragments of the autobiographical poem The Ancient Octaves is offered, and conclusions are drawn regarding the reliability of the assessments of education contained in it.
A Scalable Code for Reducing Quantum Errors

A new scheme could offer a technologically viable solution for remedying computational errors in near-term quantum devices.
Challenges and Prospects of Covid-19 Pandemic for Education in Africa

This paper explores the consequences posed, in education, by the adoption of Covid-19 containment measures such as digitization of educational instruction to enable social distancing.It outlines the underlying assumptions in the implementation of online learning, and suggests possible remedies in form of recommendations for future actions.The papers observes that Covid-19 pandemic and its containment measures has affected every aspect of life by providing us a whole new experience in socializing with each other and how we generally conduct our affaires in society.The effect of the pandemic has greatly affected the socio-economic sphere, and the education sector has been worse hit.To counter rapid spread of the virus in educational institutions, closure became the immediate response with most countries adopting online teaching and learning as a means for mitigating the challenges that can be posed to learning when learners are detached from the face-to-face process for long period.The adoption of remote learning for most institutions was largely informed by the decisions reached by individual country experts in pursuant of health guideline of social distancing by the World Health Organization.However, the unforeseen consequences of the containment measures may linger on for many years to come.Thus, this Paper raises our consciousness to the resultant situation in education and proposes remedies for action.The paper is largely based on recent library research, but also utilizes actual instances to contextualize the issues raised, with the aim of drawing practical implications for both education research and policy.
Sentiment Analysis in Myanmar Language using Convolutional LSTM Neural Network

In recent years, there has been an increasing use of social media among people in Myanmar and writing review on social media pages about the product, movie, and trip are also popular among people. Moreover, most of the people are going to find the review pages about the product they want to buy before deciding whether they should buy it or not. Extracting and receiving useful reviews over interesting products is very important and time consuming for people. Sentiment analysis is one of the important processes for extracting useful reviews of the products. In this paper, the Convolutional LSTM neural network architecture is proposed to analyse the sentiment classification of cosmetic reviews written in Myanmar Language. The paper also intends to build the cosmetic reviews dataset for deep learning and sentiment lexicon in Myanmar Language.
ImageBased Modelling Restitution: Pipeline for Accuracy Optimisation

The paper presents an innovative approach to support survey methods by applying AI algorithms to improve the accuracy of point clouds generated from UAV imagery.The work analyses different photogrammetric accuracy parameters in a first step, such as reprojection error and the intersection angle between homologous rays, verifying that a single parameter is enough to evaluate the accuracy of the photogrammetric restitution.Therefore, some of the calculated parameters were analysed through a Self-Organizing Map (SOM) to reach a compromise between the value of the variables analysed and the noise reduction associated with the 3D model definition.In the case study, it has been observed that the parameter that most influences the noise in the photogrammetric point clouds is the intersection angle.
A Deep Convolutional Neural Network Approach to Sign Alphabet Recognition

In this paper, we present an application that has been developed to be used as a tool for the purposes of learning sign language for beginners that utilizes hand detection as part of the process. It uses a skin-color modelling technique, such as explicit thresholding in the skin-color space, which is based on modeling skin-color spaces. This predetermined range of skin-colors is used to determine how pixels (hand) will be extracted from non-pixels (background). To classify the images, convolutional neural networks (CNN) were fed the images for the creation of the classifier. The training of the images was done using Keras. A uniform background and proper lighting conditions enabled the system to achieve a test accuracy of 93.67%, of which 90.04% was attributed to ASL alphabet recognition, 93.44% for number recognition and 97.52% recognition of static words, surpassing other studies of the type. An approach which is based on this technique is used for fast computation as well as real-time processing. Deaf-dumb people face a number of social challenges as the communication barrier prevents them from accessing basic and essential services of the life that they are entitled to as members of the hearing community. In spite of the fact that a number of factors have been incorporated into the innovations in the automatic recognition of sign language, an adequate solution has yet to be reached because of a number of challenges. As far as I know, the vast majority of existing works focus on developing vision based recognizers by deriving complex feature descriptors from captured images of the gestures and applying a classical pattern analysis technique. Although utilizing these methods can be effective when dealing with small sign vocabulary captures with a complex and uncontrolled background, they are very limited when dealing with large sign vocabulary. This paper proposes a method for analyzing and representing hand gestures, which acts as the core component of the vocabulary for signing languages, using a deep convolutional neural networks (CNN) architecture. On two publicly accessible datasets (the NUS hand posture dataset and the American fingerspelling A dataset), the method was demonstrated to be more accurate in recognizing hand postures.
Human Capital and Higher Education as a Catalyst for the Development of Knowledge Economy in Northern Nigeria

Developing human capital through higher education is a stepping stone for moulding of unskilled people, workers in a society with a view to developing a country's potential economically and technologically.For these to be achieved, Igbokwe-Ibeto, Agbodike and Osakede (2018) argued that, the right entrepreneurial curriculum and qualified teachers must be in place to perform this vital function as education is crucially important for many of the policy outcomes that citizens and political leaders of today care about.At an individual level, our education affects our earnings, our employability, and our chance of succeeding in life, especially among the disadvantaged people in the society.It also affects standard of living and well-being of a society and human development achievement.From the county's perspective, the level of educational development also matters for its progress and advancement.The distribution of skills as argued by Burges ( 2016) is a pointer to discrimination in terms of employment or other opportunities with regards to educational achievement and hence to the degree of social or intergenerational mobility.The world today is experiencing another form of production which is called knowledge economy.A knowledge economy is an economy in which the production of goods and services is based primarily upon knowledge-intensive activities involving the collection, analysis, and synthesis of information (Abdussalam, Okezie& Agbo, 2003).It is the most advanced form of productionwhereby intangible assets, such as knowledge and information management, become the new core of competencies.Hadad (2017) opines that knowledge assets (also known as intellectual capital) are the most powerful prodders of wealth, sidelining the importance of land, the volume of labour and physical of financial capital which if deployed effectively will energizes the country's economy.However, instead of this phenomenon to spread widely, it is restricted to few countries of the world.This is because knowledge economy depends on continually learning and improving skills and expertise of people and organizations to promote innovation.The success of a country developmental agenda depends on human innovative ideas and creativity (Johnson, 2011).Campbell (2013), posits that to produce people with highly intellectual capital and skills in the face of globalization requires the need to pay more attention on information and computer technology (ICT) and the application of knowledge to serves as creative thinking for nations development.The author further argued that organization requires people with advanced skills and knowledge with view to assist its growth and the nation's developmental stride.Higher Education therefore is expected to play an important and increasing role in the molding of the intellectual capital of a nation.
Dynamic Pathfinding for Non-Player Character Follower on Game

Artificial Intellegences in video game are important things that can challenge game player. One of them is creating character or NPC Follower (Non-player character Follower) inside the video game, such as real human/animal attitude. Artificial Intelligences have some techniques in which pathfinding is one of Artificial Intellegence techniques that is more popular in research than other techniques. The ability to do dynamic pathfinding is Dynamic Particle Chain (DPC) algorithm. This algorithm has the ability of flocking behavior called boid to explore the environment. But, the algoritm method moves from one boid’s point to another according to the nearest radius, then it will be able to increase computation time or needed time toward the target. To finish higher computation problem in dynamic pathfinding, the researcher suggests an algorithm that is able to handle dynamic pathfinding process through attractive potential field function of Artificial Potential Field to start pathfinding toward the target and flocking behavior technique to avoid the obstacle. Based on the test result by simulation of moving environment and complex, the computation time of algorithm is faster than comparison algorithms, DPC and Astar. It concludes that the suggested method can be used to decrease computation level in dynamic pathfinding.
Analysis and development of company business processes using business process model notation (case study of PT Datacomm Diangraha)

Companies in supporting activities that can achieve competitive advantage require a description of the right activities or commonly called business processes. To evaluate existing business processes so as to improve business productivity performance, every company needs to conduct business process analysis so that it is easy to understand the ongoing business processes and can improve them if needed. An important stage of business process analysis is modeling. The purpose of writing this journal is to identify business processes at PT Datacomm Diangraha and make modeling of ongoing business processes (As-Is Model). The Business Process Model Notation (BPMN) method which is a technique or method for understanding, designing and analyzing a business process is used in this research. This study uses observation, interviews and literature review to obtain data. The results obtained are the business processes at PT Datacomm consisting of the contract making process, the work design submission process, the process of paying service fees in stages (30%, 60%, 10%), providing a guarantee period, and customer service and process improvement.
Current Aspects of Using Artificial Intelligence in Digital Games and Computer Graphics Content Control

The extraordinary size and influence of gaming industry on contemporary (digital) markets creates a vast pool of resources (material and abstract) that is constantly refilled and used in order to make modern digital games of all kinds and genres as attractive and performant as possible.A key component of almost every complex digital game that is developed today is its artificial intelligence module.Due to the variety of problems that can be and are solved by using artificial intelligence in digital games its functionality is practically essential.The paper describes the application of artificial intelligence methods, its implementation in the content generation process, as well as modelling the gameplay.The game design directly conditions the complexity and performance of artificial intelligence module.It should be noted that the digital games that so far used mode advanced artificial intelligence techniques had variable success, which implies that this area of application still needs to be fully defined, and that the future technological/software progress will further determine the level of freedom that game designers will have in their creativity.
Web-Based Teacher Performance Assessment Information System Using Simple Additive Weighting Method

SMP IT Nurul Huda Batujaya is one of the educational institutions for school students in Batujaya District, Karawang Regency. The research objective is to develop teacher performance appraisal. The research method using qualitative methods aims to describe the data analysis in a narrative manner. Methods of data collection by observation, interviews, and literature study. Teacher performance assessment is still done manually by using Microsoft Excel and Microsoft Word. Other problems are needed, namely, the high cost of printing documents from each teacher, the documents submitted to the administration department are often damaged and confused, the assessment team must carry a lot of documents during the assessment, and errors during the assessment recapitulation. This can have an impact on delays in the teacher performance assessment process. The system development method uses the waterfall, Hypertext Preprocessor (PHP) programming language, MySQL, and the Simple Additive Weighting (SAW) method. The results achieved in this study can create and design a teacher performance appraisal information system to help the assessment process quickly and correctly to reduce the occurrence of errors.
An Adaptive Variable Structured-Based Filter Using Multiple Models

The Kalman filter (KF) is the most well-known estimation strategy which yields the optimal solution in terms of error to the linear quadratic estimation problem for linear, known systems in the presence of Gaussian noise.While the KF is effective under the stated conditions, it lacks robustness to disturbances which are prevalent in real-world applications.Since its inception 60 years ago, there have been numerous variants of the KF developed to accommodate nonlinear systems, non-Gaussian noise, and modeling uncertainties.The smooth variable structure filter (SVSF) is as an alternative to the KF with improved robustness, especially in the case of external disturbances.It is based on sliding mode techniques that offer robustness at the cost of optimality.The static multiple models estimator incorporates several possible operating modes and generates an estimation that is weighted based on the likelihood of each mode.This paper introduces an adaptive formulation of the SVSF based on static multiple models, and applies the developed strategy on an electrohydrostatic actuator.
ON PSEUDO-PARTICIPIAL IN NOMINAL GROUP

In nominal group, noun is the central word or as a modified word. It can be modified by several elements. One modification of a noun is by a noun added with –ed ending, then labelled pseudoparticipial. Pseudo-participial as modifier is not frequently used, but it exists. The objectives of this study are to identify the formation and to find out the meaning of pseudo-participial. The method used in this study is descriptive qualitative. She analyzed the data and described them based on the theories of Systemic Functional Grammar (SFG). The data were collected from Corpus of Contemporary American English (COCA). The results reveals that the formation of pseudo-participial is placed before head named as pre-head modifier, it can be preceded by its own sub-modifier, such as intensifier or adjective, and it functions as epithet in nominal group structure. Pseudo-participial means having which can be elaborated using finite clause, non-finite clause, or prepositional phrase.
A comparative analysis of us and Indian laws against phishing attacks

Phishing attacks employ websites and email addresses that claim to be from a recognizable and reputable company in order to manipulate people into providing financial or personal data online at the fraudulent sites. Phishing attacks exploit the numerous vulnerabilities that occur in processes and structures as a function of the human element. There are several cyber-attacks that use multiple techniques or approaches to propagate. They take advantage of the flaws identified in end users, rendering the users the most vulnerable part in terms of protection. The phishing issue is vast, and there is no one solution that can easily address all of the current fatal flaws.
Topic modeling of researchers based on their interests from Google Scholar

The article proposes an algorithm for topic modeling of researchers based on their interests from Google Scholar profiles. The algorithm uses the set of fields of research from research classification system ANZSRC. An information resource for topic modeling is a corpus of categorized publications from Dimensions. Interests from researchers’ profiles are used as search queries to Dimensions that outputs distributions of documents over categories. To reduce information noise these distributions are taken through a few stages of processing. The article also compares the results of topic modeling based on interests from Google Scholar profiles and based on a categorized list of publications from Dimensions. The comparison is done using modified Czekanowski metric that takes into account the similarity between categories. The results of comparing the topic modeling outputs based on different information sources show a good match.
Professional competence of future primary school teachers in the context of the covid19 pandemic

Reforming the current sphere of primary education predetermines the need to modernize the process of training future teachers in pedagogical universities. In particular, there is an urgent need to adapt the traditionally established system of training future specialists in general secondary education institutions in the regulatory and organizational changes in the field of higher education, to the prospects for the development of the profession and the expectations of society. The article analyzes the studies that reveal the content and features of the formation of professional competence of a future primary school teacher in the context of today's educational realities. The results of research are presented, substantiating various approaches to defining the essence of this integrated concept. The conditions for the effective formation of professional competence are disclosed, in particular, the effectiveness of the educational environment for the professional training of a future primary school teacher.
Suport visual details of X-ray image with plain information

The objective of content-based image retrival (CBIR) is to retrieve relevant medical images from the medical database with reference to the query image in a shorter span of time. All the proposed approaches are different, yet the research goal is to attain better accuracy in a reasonable amount of time. The initial phase of this research presents a feature selection technique that aims to improvise the medical image diagnosis by selecting prominent features. The second phase of the research extracts features and the association rules are formed by the proposed classification based on highly strong association rules (CHiSAR). Finally, the rule subset classifier is employed to classify between the images. The last pert of our work extracts the features from the kidney images and the association rules are reduced for better performance. The image relevance inference is performed and finally, binary and the best first search classification is employed to classify between the images.