Reviewerly/exHarmony huggingface dataset:
Maximum Correntropy Two-Filter Smoothing

This paper presents recursive two-filter smoothing (TFS) in the criterion of maximizing the correntropy (MC) instead of minimizing the mean square error, to pursue robustness for outlier rejections caused by non-Gaussian noises and obtain high-precision state estimate, which is motivated by non-cooperative target backtracking. Here, non-cooperative target tracking often needs to consider non-Gaussian noises. The MC-based recursive TFS (abbreviated as MRTFS) is put forward, where both the forward and backward filters are performed independently and recursively in the criterion of MC. Meanwhile, an MC-based fusion rule is further designed to obtain the final smoothed estimate by fusing the forward filtered estimate and backward predicted estimate step by step, in order to improve estimation accuracy. A target backtracking example with non-Gaussian noises is simulated to show the advantage of estimation accuracy of the proposed MRTFS over Kalman filter/smoothers, MC-based Kalman filter/Rauch-Tung-Striebel smoother, in terms of different kernel bandwidths and levels of process noises.
A Model of Digital Vo-Book with Crossword for Teaching and Learning Vocabulary in Seventh Grade Junior High School t Blitar: Research and Development

This research objectives are to develop a model of Digital Vo-Book with Crossword for Teaching and Learning Vocabulary, to find out the appropriateness of Digital Vo-Book with Crossword for Teaching and Learning Vocabulary, and to know the teachers' and students' perceptions toward the use of development Digital Vo-Book with Crossword for Teaching and Learning Vocabulary in Seventh Grade Junior High School. This research adapted Sugiyono's R &amp; D model. These research problems consisted of six steps: (1) data collections and finding potential and problem, (2) design and development, (3) expert validation and revision, (4) teachers’ and students’ perceptions, (5) evaluation by experts and revision, and (6) final product and publication. The result of material validation 90.6% and media validation 85.7% included in the "Very Valid" category. The result of the teacher's perception of 88.2% and the student’s perception 86.98% included in the "Very Good" category. It means that Vo-Book can be applied as an alternative media for teaching and learning vocabulary to seventh-grade students in Junior High School. The final product of the model consisted of a digital Vo-Book with a crossword, and 3 guidebooks for student, teacher, and public.
DEVELOPING HOPSCOTCH BOARD FOR LEARNING READING OF DESCRIPTIVE TEXT IN JUNIOR HIGH SCHOOL

The aims of this research are to develop a hopscotch board for learning reading of a descriptive text in junior high schools, know the validity of the developed hopscotch board for learning reading of the descriptive text, and gain the teachers’ and students’ responses toward the developed hopscotch board for learning reading of the descriptive text. This research adapted Research and Development (R&amp;D) design based on Sugiyono’s model, which includes: (1) Finding potential and problem solution; (2) Design and development; (3) Experts validation and revision; (4) Teachers’ and students’ responses; (5) Evaluation by experts and revision; and (6) Final product. The findings revealed that: (1) the model of developed hopscotch board for learning reading descriptive text consisted of a hopscotch board, markers, ownership signs, how to play (for one group instruction and more than one group instruction), cards (reading descriptive cards, exercise cards, a key answer of exercise cards, punishment cards, and key answer of punishment cards), and 2 guidebooks (for teacher and students). (2) The developed hopscotch board was valid, it was proved by the result of material experts’ validation of 95% (very valid), and media experts’ validation of 95% (very valid). Furthermore, (3) Students and teachers gave positive responses toward the developed hopscotch board as learning media for learning to read the descriptive text as reflected in the result of the questionnaire given in which got 89% (very good) from students and 90% (very good) from the teachers. From the result above, we can infer that the developed hopscotch board was valid and appropriate to be used as an alternative media for learning reading of the descriptive text in junior high schools.
Metaverse : Media Pembelajaran di Era Society 5.0 untuk Meningkatkan Kualitas Pendidikan Indonesia

Metaverse is a three-dimensional virtual technology renewal or innovation that can be used as a learning medium in the era of society 5.0 and can improve the quality of education in Indonesia. This research study discusses the metaverse that can be used as a learning medium in the era of society 5.0 to improve the quality of Indonesian education in the future. The research method used is a literature study by collecting library data from various scientific journal sources relevant to the use of the metaverse from 2020-2022. The results show that the metaverse has developed rapidly from 2020 to 2002, considering that the metaverse is an interconnected social network, an immersive network environment within a platform with many persistent users. The forms of metaverse that have been implemented such as augmented reality and virtual reality, which are present to answer the problems during the pandemic and also the needs of the era of society 5.0, in an effort to improve the quality of education in Indonesia by utilizing augmented reality and virtual reality in skills learning processes. very helpful at full term and in order to realize the quality of education in the era of society 5.0. The use of metaverse in Indonesia is generally widely used at the high school and university level in their learning. The use of metaverse with management that is in accordance with current needs, can be one of the factors supporting the success of applying metaverse to improve the quality of education in Indonesia in the next 10 to 15 years.&#x0D;
Investigation on the influence of a new trapezoidal-triangular membership function in IT2FLS with type-reductions for a manufacturing application

The performance of Interval type-2 fuzzy logic system (IT2FLS) can be affected by many factors including the type of reduction methodology followed and the kind of membership function applied. Further, a particular membership function is influenced by its construction, the type of optimisation and adaptiveness applied, and the learning scheme adopted. The available literature lags in providing detailed information about such factors affecting the performance of IT2FLS. In this work, an attempt has been made to comprehensively study the factors affecting the performance of IT2FLS by introducing a new trapezoidal-triangular membership function (TTMF). A real-time application of drilling operation has been considered as an example for predicting temperature of the job, which is considered as one of the key state variables to evaluate. A detailed comparison based on membership functions (MFs) such as triangular membership function (TrMF), trapezoidal membership function (TMF), the newly introduced trapezoidal-triangular membership function (TTMF), semi-elliptic membership function (SEMF), and Gaussian membership function (GMF) has been performed and presented. Further, the average error rate obtained with two “type-reduction” methods such as “Wu-Mendel” uncertainty bounds and Center of sets type reduction (COS TR) has also been discussed. This study provides information for selecting a particular MF and “type reduction” scheme for the implementation of IT2FLS. Also, concludes that MF having fewer parameters such as GMF and SEMF possess significant advantages in terms of computation complexity compared to others.
UNI-CERT: A Unified Computer Emergency Response Teams Model for Malware Information Sharing Platform

Sharing and exchanging information on threats and incidents among Educational institutions is a significant block of the cybersecurity strategy in the Educational sector in Jordan. Usually, this security workflow (receiving Indicators of compromise (IoCs), checking traffic, and blocking harmful traffic) is processed manually. Thus, the workload of the workflow becomes a lot heavier as the number of IoCs increases. In this paper, we propose an automated system for the efficient indicator to store, normalize, correlate, and share IoCs of targeted attacks, threat intelligence, educational fraud information, and vulnerability information handling by combining Trusted Automated Exchange of Indicator Information (TAXII) and Systematic Threat Information Expression (STIX). As the system receives indicators in STIX format, it modifies them and updates network configuration dynamically to block traffic to malicious hosts.
Developing a multicultural family case management system based on smart work

본 연구의 목적은 스마트워크 기반의 다문화가정 사례관리 시스템을 개발하여 적용한 후 사례관리 시스템의 성과를 파악하는 것이다. 이를 위해 J지역에 위치한 복지관 1곳을 기반으로 2022년 8월부터 2022년 12월까지 업무분석, 스토리보드 제작, 데이터베이스 구축, PC앱 개발, 외부연락 API연결, 스마트폰 앱 개발을 진행하여 사례관리 업무 등에 적용하였다. 그 결과 스마트워크 기반 다문화가정 사례관리 시스템을 구축하였고 관련 내용에 대하여 사례관리자와 이용자가 보는 화면이 다르게 데이터를 시각화하도록 연동하였다. 또한 스마트폰 앱을 개발하여 언제, 어디서든 사례관리 진행과정을 기록할 수 있도록 하였고 데이터 스튜디오를 활용하여 데이터 시각화를 구축하였다. 사례관리 시스템의 원활한 활용을 위해 스마트워크 도입을 위한 직원들의 디지털 역량강화 교육 진행과 개인정보 보호를 위한 시스템 보안에 대한 관리, 기 구축된 사회복지 정보시스템과의 연계를 제언하였다.The purpose of this study is to develop and implement a multicultural family case management system utilizing smart work principles, while also evaluating the effectiveness of this new system. In view of this, a welfare center located in the J region undertook a project spanning from August 2022 to December 2022. It encompassed work analysis, storyboard creation, database construction, PC application development, integration with external contact API, and the creation of a smartphone application. These components were incorporated into case management tasks. Consequently, we have built a multicultural family case management system based on the principles of smart work, and integrated it to visualize data differently for case managers and clients. Additionally, a smartphone app was developed to track the progress of case management anytime and from anywhere, and a data visualization framework was established using data studio. To facilitate smooth utilization of the case management system, several suggestions were made for enhancing the digital capabilities of social workers for smart work adoption, managing system security measures to safeguard personal information, and establishing linkage with the existing social welfare information system.
BIGaze: An eye-gaze action-guided Bayesian information gain framework for information exploration

Bayesian information gain (BIG) framework-based information exploration studies have generally focused on explicit interactions, such as user browsing via keyboard and mouse. However, if implicit information, such as eye-gaze data, is implemented in the BIG framework alongside explicit interactions, the system can accurately respond and proactively provide target information to the user. We, therefore, propose the BIGaze system, which uses real-time eye-gaze data to predict and recommend target information by analyzing the browsing and gazing action patterns corresponding to information searched by the user. To validate the performance of the proposed system within the information exploration process, we performed comparative user experiments with BIGaze, BIGbase (a BIG system without gaze data), and a non-BIG system. The experimental results reveal that BIGaze proactively captures user exploration targets, confidently generates user-intended recommendations, and assists a wide range of user exploration patterns.
Aspect-Based Sentiment Classification Using Deep Learning and Hybrid of Word Embedding and Contextual Position

Aspect-based sentiment analysis aims to detect and classify the sentiment polarities as negative, positive, or neutral while associating them with their identified aspects from the corresponding context. In this regard, prior methodologies widely utilize either word embedding or tree-based representations. Meanwhile, the separate use of those deep features such as word embedding and tree-based dependencies has become a significant cause of information loss. Generally, word embedding preserves the syntactic and semantic relations between a couple of terms lying in a sentence. Besides, the tree-based structure conserves the grammatical and logical dependencies of context. In addition, the sentence-oriented word position describes a critical factor that influences the contextual information of a targeted sentence. Therefore, knowledge of the position-oriented information of words in a sentence has been considered significant. In this study, we propose to use word embedding, tree-based representation, and contextual position information in combination to evaluate whether their combination will improve the result’s effectiveness or not. In the meantime, their joint utilization enhances the accurate identification and extraction of targeted aspect terms, which also influences their classification process. In this research paper, we propose a method named Attention Based Multi-Channel Convolutional Neural Network (Att-MC-CNN) that jointly utilizes these three deep features such as word embedding with tree-based structure and contextual position information. These three parameters deliver to Multi-Channel Convolutional Neural Network (MC-CNN) that identifies and extracts the potential terms and classifies their polarities. In addition, these terms have been further filtered with the attention mechanism, which determines the most significant words. The empirical analysis proves the proposed approach’s effectiveness compared to existing techniques when evaluated on standard datasets. The experimental results represent our approach outperforms in the F1 measure with an overall achievement of 94% in identifying aspects and 92% in the task of sentiment classification.
Janus: Toward preventing counterfeits in supply chains utilizing a multi-quorum blockchain

The modern pharmaceutical supply chain lacks transparency and traceability, resulting in alarming rates of counterfeit products entering the market. These illegitimate products cause harm to end users and wreak havoc on the supply chain itself, costing billions of dollars in profit loss. In this paper, in response to the Drug Supply Chain Security Act (DSCSA), we introduce Janus, a novel pharmaceutical track-and-trace system that utilizes blockchain and cloning-resistant hologram tags to prevent counterfeits from entering the pharmaceutical supply chain. We designed a multi-quorum consensus protocol that achieves load balancing across the network. We perform a security analysis to show robustness against various threats and attacks. The implementation of Janus proves that the system is fair, scalable, and resilient.
Robust video watermarking algorithm based on motion frames and encryption

Rapidly growing technologies over the internet are used to transfer digital media content at a high rate nowadays. The growth in these technologies results in the creation of identical copies of original multimedia data easily. The creation of these identical copies states the false claim of the ownership of digital media by any malicious user. The proposed method suggests protecting these types of the false claim by inserting a watermark into selected motion frames. Before embedding the watermark, it is scrambled by using an algorithm having a secret key. With help of this key, the scrambled watermark will be reconstructed whenever it is required. With the help of DWT method along with using SVD technique watermark is inserted into the selected frame from the original media. The results of the proposed algorithm show that the scheme is secure and robust against different types of attacks whether it is intentional and unintentional. The proposed scheme is found more secure for the protection of false claims of malicious users over digital media.
Sentiment Analysis on Twitter Social Media Regarding Depression Disorder Using the Naive Bayes Method

Depression disorder is a serious issue in mental health that affects many individuals worldwide. This research analyzes the sentiments related to depression disorder on Twitter using the Naïve Bayes method. Depression-related tweet data was collected through snscrape and processed to eliminate irrelevant information. Three Naïve Bayes methods, namely Multinomial, Gaussian, and Bernoulli, were compared to classify positive, negative, or neutral sentiments in each tweet. The results of the study indicate that Multinomial Naïve Bayes exhibited the best performance with an accuracy rate of 90.13%, followed by Gaussian Naïve Bayes (88.38%), and Bernoulli Naïve Bayes (85.37%).
Generic Structure and Attitude of Closing Ceremony Speeches in International Seminars

Nowadays there are a lot of international seminars in various fields of subjects conducted around the world to share ideas, research results, new regulations, a new decree, new theory, and so on. Most of the time the representative of the committee in the international seminar finds it difficult to shape the best guidance for the speech text at the closing ceremony. People tend to search for other examples of closing speech to shape their closing ceremony speech text to be the better one because every speech is an opportunity to affect people’s behaviours, beliefs, or actions by the attitude. However, there is no standard called generic structure and attitude which is quite special only for closing speech type. For that reason, the research objectives are to analyse the structures and attitude resources in closing speeches; and to analyse the relationship between structures and attitudes in closing ceremony speeches through the SFL approach. This is a qualitative study that employs the theory of appraisal and a basic understanding of generic structure in the SFL perspective. There are several structures generally found in each closing speech, namely addressee, identification of the speaker, encapsulation of event, valuation of event, wish/hope, special thank, and final thank. The positive valuations are the highest attitude resources found in the closing speeches. The result of this research is benefited to ELT in which the English language teacher can enrich the types of potential generic structure of the text, especially closing speech text.
The Effect of English Songs to Improve Students Listening Ability

This study aims to determine the student’s listening improvement by using instructional media for English Song, students grade VIII MTs. Muhammadiyah 13 Tanjung Morawa. The lack of students’ listening ability through was caused by the learning condition which was not using media so that the learning process run so monotonous and it impact to the students anthusiasm. This case made the students felt boring. In order to achieve the goals that have been determined, then this study uses a two group pretest and posttest experimental research methods. The number of samples in this research were 20 students. The result of t-observed was 5.8 and t-table was 1.68 it means that t-observed higher than t-table. Because the result of t-observed is higher than t-table, it means that by using the media English songs can showed a significant affect on the improvement of listening VIII MTs. Muhammadiyah 13 Tanjung Morawa. The reseacher sincerely expected that enthusiasm are able to try and apply the appropriate media and in accordance with the material to be taught, one of them is the use of English song media for listening improvement.
Pengaruh Sistem Informasi Akuntansi Dan Pengendalian Internal Terhadap Kualitas Laporan Keuangan Pemerintah Daerah

Financial reports are considered qualified if they are relevant, comparable, understandable and reliable. With the existence of an accounting information system, of course it will help effectiveness, relevance, efficiency and can make a report accurate. An accounting information system that does not use an internal control system is likely to have little benefit. The purpose of establishing an internal control system is to provide reliable and reliable financial reports. This study aims to examine the effect of accounting information systems and internal control systems on the quality of local government financial reports. The population in this study is the local government of Kupang City. The sample for this study used a non-probability sampling technique obtained from the finance department at 23 official offices in Kupang City. There are 69 respondents in this study. Data was collected by distributing questionnaires directly to 23 offices in Kupang City. The data analysis technique used is multiple regression analysis, partial test (t), and simultaneous test (f) using SPSS 29. The results of this study state that the Accounting Information System has no effect on the Quality of Financial Statements, the Internal Control System has an effect on the Quality of the Financial Reports of the Regional Government of Kupang CityKeywords: Accounting Information System, Internal Control System, Report Quality, Quality of the Financial Reports of the Regional Government of Kupang City
The effect of steam education using ICT on creative personality in young children

본 연구의 목적은 ICT 기반의 유아 STEAM 교육이 유아의 창의적 인성에 미치는 영향에 대해 알아보는 것이다. 본 연구는 서울시 S구에 위치한 C유치원의 만5세 유아들을 대상으로 2022년 5월 3일부터 7월 8까지 10주 동안 총 36명을 대상으로 실시하였다. 연구대상 2학급 중 실험집단 18명(남아 9명, 여아 9명)과 통제집단 18명(남아 8명, 여아 10명)을 대상으로 실험집단에게 연구자가 구성한 ICT 매체를 활용한 유아 STEAM 활동을 실시하였다. 두 집단에게 유아 창의적 인성 검사를 사전·사후 각 각 진행하였고 t검정을 실시하였다. 그 결과 ICT를 활용한 유아 STEAM 교육은 유아의 창의적 인성 총점과 그 하위 요인인 ‘독특성/호기심’, ‘개방성/유머’, ‘민감성/다양한 흥미’, ‘상상력/놀이성’, ‘독립성/몰두’ 점수에서 유의미한 효과가 있는 것으로 나타났다. The purpose of this study is to construct a STEAM education using ICT for young children aged five years old. The research question established to complete the purpose of the study is what are the effects on creative personalities for young children. The study was conducted for ten weeks from May 3rd to July 8th, 2022, targeting five-year-old children from C Kindergarten located in Seoul. The researcher conducted the STEAM education using ICT on 18 members of the experimental group (nine boys and nine girls) and 18 members of the comparative group (eight boys and ten girls). As a result of analyzing the effect of the developed program on young children's creative personality, the experimental group showed significantly higher scores on all of the creative personality criteria. This shows that STEAM education using ICT is effective for promoting young children's creative personality.
ANALISIS KARAKTER GEMAR MEMBACA TERHADAP KEMAMPUAN LITERASI DIGITAL SISWA SMP

The idea for this research is the low reading interest in digital literacy skills (DLS) among students whose houses have a very weak signal for Internet access. Students' DLS can be improved through increased library usage and technological advancements that are presently evolving due to the availability of several platforms for social media (learning sites). This research aims to analyze reading interest character on the studentsâ€™ DLS during an odd semester at State Senior High School 2 of Bilar Hilir (SMPN 2 Bilah Hilir). This research included the students from classes VII-1, VII-5, VIII-2, VIII-6, IX-3 and IX-4 by employing a quantitative descriptive method of investigation. The data collection was done through questionnaire by approaching descriptive statistics analysis. The research results show that students' reading interest must be improved by increasing their DLS, which are quite effective and may effectively counter technological advancements. The results of the questionnaire indicate that the students' reading interest is still low, however the results of the questionnaire demonstrate that students' DLS give good results.