Reviewerly/exHarmony huggingface dataset:
A Grey Wolf Optimizer based Support Vector Machine for Classification of Finger Movement

Finger development acknowledgment framework is generally connected in numerous apply autonomy and assistive hand gadgets.The efficiency of the recognition system depends on their accuracy which highly related to their classification technique in this system.Among the classification, the most establish and outstanding method is Support Vector Machine (SVM).However, the efficiency of SVM can be optimizes by identification of optimizes of their parameter.The newest popular swarm intelligent is grey wolf optimizer (GWO).This GWO is popular because their efficiency in exploration and exploitations.In this study, we mainly concentrate on the parameter optimization of SVMs, which has gained great attentions in the past several years.This paper exhibits a creative arrangement framework for hand signals utilizing 2-channel surface electromyography investigation.The framework created utilizes the Support Vector Machine classifier, for which the piece capacity and parameter streamlining are directed moreover by the Grey Wolf Optimizer.The experimental result in this study is based on accuracy compared between the ten fingers movement based on SVM and proposed hybrid GWO-SVM and GWO-SVM result based on three different feature extraction methods.The results show that hybrid GWO-SVM obtained better accuracy compared to the others.
Time-Based Change Visualization Techniques Survey

Sets of numerical values changing over time are one of the most common forms of recorded data.Time-varying phenomena are essential to many areas of human activity and there is often a need to simultaneously display or compare a large number of time series data.Visualizations that improve the speed and accuracy with which humans can read and compare time-varying data are of great practical benefit.Effective presentation of multiple time series is one of the basic problems in visualization research: increasing the amount of data with which human operators can effectively work.This study surveys visualization techniques for time-series data with their major pattern and quantitative qualities compared.All covered visualizations are implemented in 'Visualization Laboratory' project and use common format to handle time-series data.
Design of Educational Administration Comprehensive Information Management System Based on Thinkphp

In view of the low efficiency of teaching management in traditional colleges and universities and the duplication of tasks, this paper realizes the educational administration information management system based on ThinkPHP open source framework technology. The system mainly completed the management of the school’s information statistics, student experimental reports and graduation papers, effectively improved the efficiency of teaching managers, and more scientific and standardized the management of students’ experimental reports and graduation papers.
Joint Demographic Features Extraction for Gender, Age and Race Classification based on CNN

Automatic verification and identification of face from facial image to obtain good accuracy with huge dataset of training and testing to using face attributes from images is still challengeable.Hence proposing efficient and accurate facial image identification and classification based of facial attributes is important task.The prediction from human face image is much complex.The proposed research work for automatic gender, age and race classification is based on facial features and Convolutional Neural Network (CNN).The proposed study uses the physical appearance of human face to predict age, gender and race.The proposed methodology consists of three sub systems, Gender, Ageing and Race.Therefore different feature are extracted for every sub system.These features are extracted by using Primary, Secondary features, Face Angle, Wrinkle Analysis, LBP and WLD.The accuracy of classification is based on these features.CNN used to classify by using these features.The proposed study has been evaluated and tested on large database MORPH II and UTKF.The performance of proposed system is compared with state of art techniques.
User position tracking system using marker-based AR for exploring VR museum galleries

This study examines the user position tracking system using marker-based AR on smartphones camera. The tracking system uses a homographic algorithm integrated into the Galeri Museum VR application. In the test, the user performed exploration interactions by 6 degrees of freedom in ten different positions in the museum gallery. The physical space used in this study was 4 x 4 m2 and a marker attached to the wall in front of the user. This system results in errors in XYZ field (0.102 m, 0.047 m, 0.044 m). If the camera's orientation is not directing to the marker and the user is moving, jitter appears because of the untracked marker. The use of marker-based AR successfully applied to track the position of users who perform natural locomotion interactions in the VR environment.
Analysis of Security Algorithms for a Distributed Database

We analyzed the security of a database considering the environment of distributed systems, there are several security mechanisms that are applied to the different types of data that are saved; this research identifies several problems for mitigating the security of a distributed database. The objective is to define a basic scheme and an abstract algorithm through algorithms using flowchart techniques for a security process in a DDB. The deductive method and the exploratory investigation were used to analyze the information of the articles of the reference. It resulted in a basic structure based on a three-level architecture, with 3DES encryption algorithm applied to the request and response; SQL-based encryption for data processing; FPE encryption algorithm for storage in the database; the scheme was presented with its scope and possible limitations; and a prototype of an abstract algorithm expressed with flowchart techniques was obtained. It was concluded that the basic scheme and abstract algorithm presented as an alternative to control access to resources, to provide improved security in a distributed database.
Using Emoji to Improve Female Students' Coherence in Writing at Qassim University

Writing is considered a very important learning tool for all content areas. There is no doubt that writing skill is essential for any kind of learning either at the school or the university level. Therefore, the present study attempted to explore the possibility of improving university students’ one of writing sub-skills, known as coherence through emoji. Coherence in the students’ writing was measured according to the students ability to a) use repetition to link ideas, sentences, and paragraphs, b)use transitional expressions to link ideas, sentences, and paragraphs, c) use pronouns to link sentences, d)use synonyms to link ideas and create variety, e) use parallel structures to link ideas, sentences, and paragraphs. The sample of this study was randomly selected from the Third Level female students joining the Department of English at one Saudi public university. The selected subjects were assigned randomly into control group and experimental group. After administrating the pretest for the two groups, the experimental group was given a six-week treatment of emoji meant for improving the writing sub-skill, while the control group was taught writing without using emoji. One week after the treatment, a posttest was administered to the two groups. Results revealed significant difference between the students’ scores in writing in favor of using emoji to improve students’ writing skills. Thus, the findings show the effectiveness of using emoji in improving students’ coherence in writing. The results were used to draw some conclusions and to suggest some recommendations for teaching writing using emoji. The results also recommend further researches to be done on using emoji to improve other language skills and sub-skills.
A Novel Computer-Aided Emotion Recognition of Text Method Based on WordEmbedding and Bi-LSTM

Emotional analysis in literary and artistic art is a current research hotspot, while emotional-based fiction classification is more complicated than other literary forms. Emotional detection is usually done from the perspective of voice or facial images. Most of the existing text-based research uses typical binary or ternary classification methods. Therefore, how to extract information of emotion from the novel text and classify it is still a problem to be solved. In this paper, a Bi-directional Long Short-Term Memory Language Model (BiLSTM-LM) is proposed. The text sequence is divided into six different emotional categories. Word Embedding method is used to encode vocabulary, and the text is represented as word feature representation and character feature representation respectively. The final emotional output is estimated by combining content words and emotional function words. Experimental results show that the training of the model in this paper can quickly converge, and the detection accuracy is up to 64.09%, which is 4 percentage points higher than the current best model, and basically can effectively classify novels.
CULTURE SHOCK EXPERIENCES OF INDONESIAN UNIVERSITY STUDENTS IN TEACHING PRACTICE AND COMMUNITY SERVICE IN THAILAND

This study was designed to explore culture shock experiences faced by Indonesian university students in doing teaching practice and community service in southern border province Thailand, and to describe the strategies used to deal with cultural differences and problems. There were thirty eight students of university from twelve universities in Indonesia who responded to the open-ended questionnaires sent by the writer through google docs link. The data were analysed using grounded theory code as basis for the thematic analysis. The findings revealed that there were six culture shock experienced by Indonesian university students, namely: language and communication problems, life style and cultural differences, social support and making friends, positive experiences, academic problems, and psychological problems. The most dominant shock experience faced by Indonesian university students was positive experiences. As for the strategies to deal with cultural differences and problems, there were found four strategies used by Indonesian university students, namely: self-confidence and optimism, accepting new culture, seeking social support, and language training. The most strategy mentioned by Indonesian university students was accepting new culture.
A Method for Automated Segmentation of Speech Signals to Determine Temporal Patterns of Naturally Expressed Psycho-Emotional States

A method for automated segmentation to determine temporal patterns of speech signals reflecting naturally expressed psycho-emotional states has been developed. The nature of the method is the segmentation of speech into informative areas using adaptive decomposition and energy analysis of intrinsic mode functions, and determining patterns of temporal intervals of voiced, unvoiced, and pause sections. A research using the formed base of speech signals of 100 subjects, experiencing natural positive and negative emotions, was conducted. The research results were evaluated in comparison with the known methods of segmentation, followed by the determination of temporal patterns. In accordance with the determination results of psycho-emotional states, it was concluded that the developed automated method more accurately determines the boundaries of informative areas, due to the advantages of the energy analysis of empirical modes obtained by the method of improved complete ensemble empirical mode decomposition with adaptive noise.
The Use of Politeness Strategies in the Indonesia’s 2019 Presidential Campaign Teams on Online News Media

The politeness strategy can be found in daily conversations and in debating events.One of the debates of concern for this study is the debate between two presidential election campaign teams in Indonesia.This article sought to describe the strategies used by both groups on online news media and to find out whether there is any significant difference between in the use of positive and negative politeness strategies.This research used descriptive qualitative methods to analyze sixteen articles of media coverage of news with high political salience from two important national online news media having opposite ideology, MediaIndonesia.comand Kompas.com.Discussion primarily draws upon Brown and Levinson's politeness theory.The result of the research shows that each groups of election campaign team used various politeness strategies projected by three context-driven politeness strategies.This implies that each teams should consider politeness attracts positive attention, gives tough situations a chance to turn around.
Comparison of Resilience and Subjective Well-being to Fathers and Mothers Who Have Postlingual Deafness Children

This study aims to compare the resilience and subjective well-being of fathers with mothers who have postlingual deafness children. Participants in this study were 336 parents (168 fathers and 168 mothers) who had postlingual deafness children, were biological fathers and mothers of postlingual deafness children, lived with their partners and children who experienced postlingual deafness, were able to communicate verbally and in writing using Indonesian good, domiciled in West Java. This research uses a comparative study approach. The instrument used in this study is the CD-RISC which has been modified into Indonesian by Lamsinar &amp; Ratna (2011) and subjective well-being instruments constructed by researchers based on the Diener theory. The findings in this study reveal that there are significant differences in resilience and subjective well-being between fathers and mothers who have postlingual deafness children. Based on the average resilience and average subjective well-being seen in the group, the group of fathers who have postlingual deafness children has a higher score compared to the group of mothers who have postlingual deafness children.
Blended-Keyframes for Mobile Mediated Reality Applications

With the recent developments of Mixed Reality (MR) devices and advances in 3D scene understanding, MR applications on mobile devices are becoming available to a large part of the society. These applications allow users to mix virtual content into the surrounding environment. However the ability to mediate (i.e., modify or alter) the surrounding environment remains a difficult and unsolved problem that limits the degree of immersion of current MR applications on mobile devices. In this paper, we present a method to mediate 2D views of a real environment using a single consumer-grade RGB-D camera and without the need of pre-scanning the scene. Our proposed method creates in real-time a dense and detailed keyframe-based 3D map of the real scene and takes advantage of a semantic instance segmentation to isolate target objects. We show that our proposed method allows to remove target objects in the environment and to replace them by their virtual counterpart, which are built on-the-fly. Such an approach is well suited for creating mobile Mediated Reality applications.
Corpus-based Study of Identifying Verb Patterns Used in Pakistani Newspaper Headlines

Newspaper headlines are an important subgenre of media genre and enjoy much significance in news discourse. Headlines are ascribed different functions as they are the opening section to their respective text. This corpus-driven study strives to identify those verb patterns which have been used in Pakistani newspaper headlines. To identify different verb patterns used in newspaper headlines, the researcher compiled a corpus of 3135 newspaper headlines consisting of 28646 words drawn from three on-line Pakistani English newspapers which include The Dawn, The Nation and The News. The researcher tagged this corpus by using the software TagAnt and analyzed this corpus with the help of corpus tool AntConc to identify the verb patterns used in these Pakistani English newspaper headlines. To this end, the researcher analyzed the compiled corpus in accordance with the POS Tags given by Tree Tagger Tag Set. This study has found different verb patterns which have been used in newspaper headlines.
IMPLEMENTASI KNOWLEDGE MANAGEMENT DALAM KEMENKEU CORPORATE UNIVERSITY

Learning from the Ministry of Finance Corporate University utilizes the Ministry of Finance Learning Center as a Knowledge Management. This paper wants to know and analyze how Knowledge Management is implemented in the Ministry of Finance Learning Center. The method used is qualitative with inductive logic analysis. The results of the study indicate that it is implemented using the internet. The formation of knowledge sharing habits has been implemented, but there are still many learning videos with few viewers, it should be made based on the eyes of the training in the Pusdiklat or subjects in PKN STAN. The making of learning videos is still dominated by Widyaiswara, officials or employees of the Directorate General of Taxes as very little Group Owner Skills, so rules need to be made that require officials or employees of the Directorate General of Tax to make learning videos based on best practice and tacit knowledge. Knowledge Management regulation umbrella is the Regulation of the Head of the Financial Education and Training Agency and Minister of Finance Regulation. The Knowledge Management strategy in the Ministry of Finance Learning Center is aligned with the Ministry of Finance's change management strategy because it is one of the central themes of the strategic initiative of the Ministry of Finance's bureaucratic reform program and institutional transformation. Keywords: Corporate University, Knowledge Management, Skill Group Owner. Abstrak
Document-level emotion detection using graph-based margin regularization

Sentiment analysis aims to automatically detect the underlying attitudes that users express. For the documents with complex unstructured data, such as reviews, emojis and surveys, it is usually hard to precisely identify the real emotion. Thus, it becomes urgent, yet challenging, to develop a technique that can process and make use of the unstructured information. In this article, we consider sentiment classification for those unstructured features extracted from texts. We propose a regularization-based framework to pursue better classification performance by (1) introducing polarity shifters assembled with sentiment words to create novel bigram features and (2) simultaneously constructing a constraint graph to encode the relative polarity among unstructured features to improve the parameter estimation procedure. Under these settings, our approach can uncover the intrinsic semantic information from the unstructured text data. Theoretically, we justify its underlying equivalent connection with the standard Bayes classifier, which is ideally optimal when the sample distribution is known. Moreover, we show that our new method yields better generalization ability due to the reduced solution search space and the appealing asymptotic consistency. The superior performance from real data experiments demonstrates the robustness and effectiveness of the proposed method.
Hybrid robust controller based on interval type 2 fuzzy neural network and higher order sliding mode for robotic manipulators

Industrial arms should be able to perform their duties in environments where unpredictable conditions and perturbations are present. In this paper, controlling a robotic manipulator is intended under significant external perturbations and parametric uncertainties. Type-2 fuzzy logic is an appropriate choice in the face of uncertain environments, for various reasons, including utilizing fuzzy membership functions. Also, using the neural network (NN) can increase robustness of the controller. Although neural network does not basically need to build its type-2 fuzzy rules, the initial rules based on sliding surface of higher order sliding mode controller (HOSMC) can improve the system's performance. In addition, self-regulation feature of the controller, which is based on the existence of the neural network in the central type-2 fuzzy controller block, increases the robustness of the method even more. Effective performance of the proposed controller (IT2FNN-HOSMC) is shown under various perturbations in numerical simulations.
ARE CORRUPTION, DEMOGRAPHIC PRESSURES AND BRAIN DRAIN DAMAGING THE QUALITY OF EDUCATION? EVIDENCE FROM ASIA

The importance of education cannot be denied in any region of the world because it is the aspect on which the future and growth of the country is based.There are many aspects that are found to have impacts on quality of education, however in this study; the author has used corruption, demographic pressure and brain drain along with control variables i.e. population and per capita income and the impacts of all the above mentioned variables on quality of education have been studied.The approaches such as unit root test, cointegration test and coefficient estimation test have been used by the author for the data analysis purpose.The author has found out the order of integration, cointegrated relationships presence as well as their measurement by using all these approaches.The data in this case was collected from eight countries of Asian region for 26 years and the above-mentioned tests were run on it.The results obtained indicate that corruption and brain drain have significant impact on quality of education along with the control variables, population and per capita income.The author has also discussed some theoretical, practical and policy making implications and some of the limitations of this study.
Experiences and Perceptions of Multicultural Education by Pre-service Teachers Participating in an Overseas Education Service Program

이 연구는 해외 교육봉사 프로그램에 참여한 예비교사의 다문화교육 경험과 그에 대한 인식을 확인하여 다문화교육 방안으로서의 가능성을 탐색하는 데 목적이 있다. 이를 위해, S여대 교직과정의 해외 교육봉사 프로그램 참여자를 대상으로 심층면담을 실시하였고, 활동계획서, 성찰일지, 평가자료 등을 면담 자료와 함께 반복적 비교분석방법으로 분석하는 질적 연구를 수행하였다. 분석 결과, 연구참여자들은 교육자 자격 갖추기, 수업 경험하기, 성장을 위해 도전하기, 가치로운 삶 살기 등의 동기에서 참여하고, 진짜 수업해보기, 협력적 문제해결, 두 배로 훈련하기, 교사로서의 자신감을 경험했으며, 활동을 통해 교사역할, 차이와 한국인 선생님, 거대한 도전의 프로젝트로서 수업을 인식하고, 본 프로그램을 다양한 경험과 성찰 기회, 글로벌 역량 함양의 특별경험, 변화의 터닝포인트로 인식하는 것으로 나타났다. 이러한 결과가 다문화교육 방안으로서 해외 교육봉사 프로그램의 가능성을 가진다고 결론 내리고, 다문화교육 교육과정에 이 프로그램을 편성·운영하는 것에 관한 시사점을 제시하였다.The purpose of this study is to analyze the experiences and perceptions of multicultural education of pre-service teachers who participated in an overseas education service program. To this end, in-depth interviews were conducted with the program participants in S Women s University, and a qualitative study was conducted using an repeated comparative analysis method by collecting activity plans, reflection journals, and evaluation data. The results showed that participants participated in the motivation of becoming educators, experiencing the classroom, challenging for growth, and living a worthy life, experiencing real lessons, collaborative problem solving, double training, and confidence as a teacher. Through the activities, they recognized the role of teachers, differences and the meanings of Korean teachers and classes, and perceived the overall program as various experiences, reflection opportunities, special experiences in the development of global skills, and turning points for change. This result concluded that there are possibilities of overseas education service program as a multicultural education plan, and suggested implications for organizing and operating this program in multicultural education curriculum.