Reviewerly/exHarmony huggingface dataset:
Development of OnlineWeb-Based New Student Graduation Application in Junior High School

The student graduation information system is integral to managing and carrying out school information system activities. Especially in Junior High Schools (SMP) today, many still have not used a website-based information system due to the new internet network entering this area. In meeting the admin’s need, in particular, to deal with the problem of passing the distribution of receiving information or announcements, documentation of activities, teaching materials, and registration of new student participants have not run optimally as expected. In the system development method in this research, the author uses the System Development Life Cycle (SDLC) with the Waterfall model approach, which consists of 5 stages: analysis, design, implementation, testing, and implementation. The system design tool uses the UML (Unified Modeling Language) method using use-case diagrams according to system requirements. In developing the SDLC method in this study, the authors used it until the design stage. The results obtained from this research are a Web-based application system for new students’ graduation. With this tool, several related files will be generated. This new system can improve the quality of further student admissions, graduation information and school information through the website.
Multilingual Transformers for Named Entity Recognition

Different methods for automatic named entity recognition (NER) have been researched for many years.Today, the most common technique for training named entity recognition models is a fine-tuning of large pre-trained language models.In this paper, we investigate the performance of various multilingual NER models in the state-of-the-art natural language processing framework Flair and compare them against the multilingual NER solution of the MAPA anonymization toolkit and BERT multilingual model, fine-tuned for NER.We demonstrate that in multilingual settings the best results could be achieved with fine-tuned XLM-R model, while in the case of Latvian (monolingual settings), the more targeted LitLat BERT model leads to the best results.
High-Performance Computing Framework for Virtual Memory Using CNN

One of the most interesting machine learning techniques is reinforcement learning. Image identification, language understanding, and language processing seem to be just a few of the various applications where supervised learning is applied. Deep neural networks are developed to increase learning efficiency by (a) raising several levels & (b) expanding the number of variables in huge modeling. That means the networked intelligent machines must adapt to (c) deal with large/complex, deep learning models and (d) analyze a massive testing dataset utilizing high-performance computational power. The study introduces the Safe Memory Unit (SMU), a new digital main memory architecture that allows distributed operations in networks to access the storage of external networks in terms of improving data communication through parameter sharing. The transmission rate of machine learning utilizing a suggested SMU was 2.1 considerably quicker than the Message Passing Interface (MPI)., according to information performance evaluation findings. Moreover, based on machine learning techniques & also the number of computational intelligence employees, the transmission period of the SMU-based asynchronous variable update is 2−7, significantly faster than MPI.
An Error Analysis on Dialogue Script Written by Eighth Grade of SMPN 3 Kota Jambi

In learning English especially in writing, the students made errors to write dialogue. They have lack of vocabulary and less idea in writing English sentence. They also need to consider about the grammatical components of English that differ from Indonesian language. The aim of this research was to describe errors made by the students in writing dialogue script. Thirty students from Eighth grade of SMPN 3 Kota Jambi were asked to write about free essay in dialogue script. All students writing are, then, analyzed in order to investigate students' errors. Based on findings of this research in linguistic category and surface strategy, it can be concluded that the students have difficulties in grammar (tenses, preposition, agreement, article), lexicon (vocabulary and spelling), punctuation for linguistic category and addition (double marking, regularization, simple addition), omission, misformation (regularization, archi- form, alternating form), misordering for surface strategy. Most students tend to have difficulties in spelling and omission.
Time–Frequency Domain Analysis

This chapter introduces the time-frequency domain analysis, including the motivation of applying time-frequency domain analysis, the short-time Fourier transform and wavelet transform.
An Integrated Model of Social Capital and Open Innovation: Examining the Mediation Effect of Knowledge Acquisition and Knowledge Integration

Purpose: Understanding the various effects that exist among social capital, knowledge acquisition, knowledge integration, and open innovation is the main purpose of this study.&#x0D; Design/methodology/approach: Data were gathered from 137 managers from Malaysian SMEs.&#x0D; Findings: The results of the analysis revealed that SC dimensions had insignificant impact on OI practices. The results also showed that, knowledge integration influence OI practices and mediate the relationship between SC dimensions and OI practices. This study also found that there is a significant positive relationship between SC dimensions and OI thru knowledge integration. The findings of this study thus provide many benefits for researchers and practitioners despite the presence of some limitations.&#x0D; Originality/value: This paper is original&#x0D; Paper type: Research article
MULTIMEDIA CLOUD COMPUTING IN VEHICLES

Intelligent Transportation Systems (ITSs) means services to improve safety and traffic efficiency. For example, vehicle-to-vehicle communication for road safety. In ITSs, vehicles are equipped with a number of sensors which provide different functions like weather forecast, temperature, GPS etc. All these features make the drive better and smooth. As a result, these vehicles produce a large amount of multimedia related data, which is critical and delay-sensitive, and requires on-time processing. The standalone devices embedded in the vehicles cannot do the required fast-processing due to their limited computation facilities. Cost minimisation, Quality of Experience, and resource allocation are some more problems related to multimedia related content processing, which have arrived in recent times. Thus, the concept of merging cloud computing with vehicles has emerged. Still conventional cloud computing is not suitable for this critical and delaysensitive multimedia related data. So a new computing paradigm called Multimedia Cloud Computing (MCC) has emerged. Thus, in this paper, a Dynamic Priority-based Efficient Resource Allocation and Computing scheme is proposed to overcome the above-mentioned issues.
Deixis Analysis in The Song Lyrics of Taylor Swift “22”

ThisresearchaimstoanalyzefourtypesofdeixisbyusingtheoryofAlanCruse(2000), interpretthereferencemeaningofdeixisandfindoutthemostdominanttypeofdeixis thatfoundinthesonglyricsofTaylorSwift“22”.itconsistsofsuchdeictic wordsthat has reference meanings. Therefore, the song lyrics can be analyzed using pragmatic approach,specifically about deixis. This study was conducted by using descriptive qualitative method. The data which is used is the song of Taylor Swift “22” and then itisclassifiedintothetypesofdeixis.Thefindingsshowedthatthetypesofdeixislike persondeixis,spatialdeixis,temporaldeixis,anddiscoursedeixisareusedinthesong lyrics of Taylor Swift “22”. Based on discussion and finding can be concluded that all deixisarefoundinallsongs,personaldeixisisthemostbeingfound(15Deicticwords or 51,7%) the word “I, Me, You and We dominate all songs. in the second position DiscourseDeixisisfound(8deicticwordsor27,6%)andSpatialDeixis(5deicticwords or 17,2%), in the last position is Temporal Deixis (1 Deictic words or 3,4%)Keywords: pragmatics, deixis, song lyric
Universal Graph based Distantly Supervised Relation Extraction

This paper explores how the Distantly Supervised Relation Extraction (DS-RE) can benefit from the use of a Universal Graph (UG), the combination of a Knowledge Graph (KG) and a large-scale text collection. A straightforward extension of a current state-of-the-art neural model for DS-RE with a UG may lead to degradation in performance. We first report that this degradation is associated with the difficulty in learning a UG and then propose three training strategies: (1) Path Type Adaptive Pretraining, which sequentially trains the model with different types of UG paths; (2) Path Type-wise Local Loss, which is an alternative approach of the Path Type Adaptive Pretraining to generate UG path type-wise local error signals so as to prevent the reliance on a single type of UG path; and (3) Complexity Ranking Guided Attention mechanism, which restricts the attention span according to the complexity of UG paths so as to force the model to extract features not only from simple UG paths but also from complex ones. Experimental results on both biomedical and NYT10 datasets prove the robustness of our methods and achieve a new state-of-the-art result on the commonly used NYT10 dataset. The code and datasets used in this paper are available at https://github.com/baodaiqin/UGDSRE. In addition, a DS-RE toolkit developed based on this work is available at https://github.com/baodaiqin/UKG-RE.
Genomic: Combining Genetic Algorithms and Corpora to Evolve Sound Treatments

Genomic is Python software that evolves sound treatments and produce novel sounds. It offers features that have the potential to serve sound designers and composers, aiding them in their search for new and interesting sounds. This paper lays out the rationale and some design decisions made for Genomic, and proposes several intuitive ways of both using the software and thinking about the techniques that it enables for the modification and design of sound.
Decoupling Graph Convolutional Network with Adaptive Normalization

In order to improve the accuracy of action recognition, a decoupling graph convolutional network combined with adaptive normalization is proposed, which replaces the batch normalization module in the graph convolution part of the network with a normalization module that can learn spontaneously. The weight coefficients obtained by training perform weighted summation on various normalization results to obtain better normalization results, thereby improving the overall effect of the network. The results on the NTU-RGBD-120 skeleton dataset show that the model achieves higher action recognition accuracy (86.8 X-sub, 88.4 X-setup).
Evolving a Boolean Masked Adder Using Neuroevolution

The modular addition is a popular building block when designing lightweight ciphers. While algorithms mainly based on the addition can reach very high performance, masking their implementations results in a huge penalty. Since efficient protection against side-channel attacks is a requirement in lots of use cases, we focus on optimizing the Boolean masking of the modular addition. Contrary to recent related work, we target evolving a masked full adder instead of parts of a parallel prefix adder. We study how techniques typically found in neural network evolution and genetic algorithms can be adapted in order to help in evolving an efficiently masked adder. We customize a well-known neuroevolution algorithm, develop an optimized masked adder with our new approach and implement the ChaCha20 cipher on an ARM Cortex-M3 controller. We compare the performance of the protected neuroevolved implementation to solutions found by traditional search methods. Moreover, the leakage of our new solution is validated by a t-test conducted with a leakage simulator. We present under which circumstances our masked implementation outperforms related work and prove the feasibility of successfully using neuroevolution when searching for complex Boolean networks.
Predicting liver disease using automatic classification model

Liver disease records around two million per annum worldwide. One million owing to cirrhosis and one Million owing to viral hepatitis and hepatocellular carcinoma. Presently, Cirrhosis is the eleventh most common cause of death and liver cancer is the leading cause of death. To uphold the treatment it is necessary to detect the cause and range of liver damage. In this study, a group of blood tests called liver function tests (LFTs) is utilized to diagnose the liver disease. To contour the diagnostic method in day to day life and avoid misdiagnosis, strategies of artificial intelligence can be employed. The objective of this study is to enhance the accuracy in LFTs datasets using Artificial Neural Network ( machine learning) . Back propagation algorithm is used in this study as leading learner. The experimental results exhibit accuracy of 74%.
PELAKSANAAN INTERAKSI EDUKATIF DALAM PEMBELAJARAN EKONOMI

AbstractThis thesis entitled "Implementation of Educational Interaction Economic Learning". The problem in this research is How to Implement Educational Interaction Economic Learning. The method used is descriptive method. The form of research is qualitative description. Data collection techniques in this study are: direct communication with data collection tools, interview guides, direct observation with data collection tools, observation sheets, documentary studies using data collection tools, school data archives. With the following research results: 1). Based on the results of research conducted in economic learning has been applied, in two directions the teacher and students. 2) Based on the results of research that occurred in the implementation of educational interactions in teaching and learning activities in economic learning The first obstacle is from the aspect teachers, students and servants come from the environment, 3) Efforts are made based on the results of research using the learning method, are more diligent in learning and preparing material first before teaching and learning activities.Keyword : Economic Educational Implementation Interaction, Learning Of.
CryptoArcade: A Cloud Gaming System with Blockchain-based Token Economy

Cloud gaming is a novel service provisioning technology that offloads parts of game software from terminals to powerful cloud infrastructures. However, the commercial charging model for cloud gaming is still in its infancy. In this paper, we reveal the deficiencies of existing cloud gaming pricing models and propose CryptoArcade, a token-based cloud gaming system that adopts cryptocurrency as a payment method. Using cryptocurrency, CryptoArcade provides a transparent and resource-aware pricing method, enabling a time irrelevant silent payment on the floating price to protect players' interests, which avoids the Quality of Experience (QoE) degradation caused by traditional dynamic models. While CryptoArcade can solve the problem of pricing strategies, players still face decision headaches caused by having commission overhead and pre-deposit amounts on blockchains. To better understand players' trading behaviors in this decision-making, we consider a marketplace where players trade tokens through smart contracts before gaming sessions. Considering the uncertainty of future token consumption, we use Prospect Theory (PT) in modeling and obtain the optimal solution in closed form. When comparing with the benchmark expect utility theory (EUT), we show that with the same external factors, EUT players are more likely to buy tokens than PT ones.
PENINGKATAN KETERAMPILAN MENYIMAK ANAK USIA 5-6 TAHUN MELALUI PERMAINAN BISIK BERANTAI DI TK AALAM KIDS KUBU RAYA

AbstractThe background of this research that children are not yet capable enough to listen actively, learning in class is more about giving assignments while listening skills are not paid enough attention and many parents consider listening skilss to be less important. The method used in this research is an experimental type of classroom action research with a quantitative approach and the research design is pre-experimental design one group pretest-posttest. The subjects in this study were 8 children in group B of TK Aalam Kids Kubu Raya. The data collection technique used is observation and documentation. The results from before being given a chain wishper game in cycle 1 were BSH 37,5% and BSB 0%, while after being given a chain whisper game in cycle 1 were BSH 87,5% and BSB 12,5%. So it can be concluded that there is an increase in the listening skills of children aged 5-6 years through a series of whispering games in TK Aalam Kids Kubu Raya.Keywords: Game, Listening Skill, Whispering Chain
Police Reforms' Impacts on Nigeria Police Leadership

Purpose: The study's goal was to ascertain how leadership within the Nigerian police force was affected by police reforms with regard to the Directorate of Criminal Investigation. &#x0D; Methodology: Based on functional leadership theory, the study was conducted. Police officers and members of the public completed questionnaires that were used to collect data. Descriptive statistics created with SPSS were used to evaluate quantitative data. The examination of qualitative data using content analysis. Edited and coded data were entered into SPSS for efficient analysis. Frequency tables and graphs were used to portray the quantitative data for rapid and simple comprehension. In prose, the qualitative data was given. &#x0D; Results: The study found that the leadership in the police service was influenced by organizational structure, police education, organizational culture, and relationships with the local police force. According to the respondents, the organizational structure of the police department, police officer training, organizational culture, and the interaction between the police and the community all had a significant impact on police leadership. These elements benefited police leadership. The police leadership further had difficulties with the recent reforms. According to the responders, police leadership had not developed any plans to lessen the difficulties they were encountering. &#x0D; Conclusion: According to the study's findings, the leadership at FCID headquarters is significantly influenced by organizational structure, police officer education levels, organizational culture, police-community interactions, and organizational structure. &#x0D; Recommendations: According to the report, the oversight committee in charge of Nigeria's police reforms has to establish a culture of organizational change in order to deal with the dynamic leadership issues that are impeding the reform process as a whole. The public should be made aware of the importance of adopting a community policing policy through extensive advertisements. The study suggests that a follow-up study be done, but this time to examine how county commissioners' influence police leadership in a decentralized system.
Dynamic Polymorphism without Inheritance: Implications for Education

Polymorphism is a core OO concept.Despite the rich pedagogical experience in teaching it, there are still difficulties in its correct and multifaceted perception by students.In this article, a method about a deeper study of the concept of polymorphism is offered by extending the learning content of the CS2 C++ Programming course with an implementation variant of dynamic polymorphism by type erasure, without using inheritance.The research is based on an inductive approach with a gradual expansion of functionalities when introducing new concepts.The stages of development of such a project and the details of the implementation of each functionality are traced.The results of experimental training showed higher scores of the experimental group in mastering the topics related to polymorphism.Based on these findings, recommendations for the construction of the lecture course and the organization of the laboratory work are suggested.
An Analysis of the Language Styles Used in Conversation between Craft Traders and Foreigners in Sukawati Market

People will never use the same language to communicate because they have their own style. The way they choose the words or language style can be influenced by the setting of the conversation. Therefore, This study aims to analyze the style of language used by handicraft traders and foreign tourists in their conversation, the language style most often used, and the language function used by handicraft traders at the Sukawati market. This research was descriptive qualitative research. The subjects were two craft traders and twenty foreigners. Methods of collecting data by interview and observation. The research instrument was the researcher, observation sheet, interview, and voice recorder. The data analysis technique is descriptive qualitative analysis. The results of this study showed that the language styles used were the colloquial, casual, and consultative styles. From those styles, the consultative style was dominantly used by craft traders and foreigners. Moreover, the function of the language style used in the conversation was to persuade the foreigners to buy their merchandise, to make the speaker’s ideas clearer, to get foreigners’ attention, to create mood, and increase foreigners’ tastes or feeling.
RHETORICAL ANALYSIS OF CONTESTANT’S SPEECHES IN SPEECH CONTEST OF "STEC FESTIVAL BAHASA" COMPETITION AT IAIN KUDUS

Conducting speech contest in the college belongs to learning process in developing language skill. It is a kind of public speaking as realization of communicative competence in teaching and learning process. It conveys the message delivered to the audience. Message must be prepared in written form before it is performed . then the teacher must guide the students in constructing the text in delivering the message. Speech was performed has to fulfill the structure of organization and supplementary components. One of the strategic in delivering good speech is rethorical language. Rethorical languge consist of suppoting language developed in the speech for example hyperbole, alliteration, metaphor, repetition, irony, metonymies and rethorical question. This study conducted the the reseach to determine the importance speech in the teaching and learning proses. This study analysed the structure of the text. Moreover this study also revealed the rethorical language of the winner of speech competition held in IAIN Kudus. It was conducted using descriptive qualitative method in which the data anlysis used content anaysis. Based the analysis ,It was found that there were 9 items of rethorical language from the speech text that consist of 5 metaphors and 4 rethorical questions.
Prediksi Promosi Jabatan Karyawan JNE Pematangsiantar Dengan Algoritma C4.5

This study predicts employee promotions using employee data from PT. JNE Pematangsiantar. The purpose of this research is to obtain a rule model in classifying predictions of promotions in the company. By knowing this prediction, decision makers can choose employees who will be promoted according to the rules that apply in the company. The method used in this research is Data Mining Algorithm C4.5, with employee data used as many as 20 employees. The variables used in this study include: Job Knowledge, Competence, Teamwork, Communication and Job Quality. The results of the study obtained 9 rules or rule models for this prediction classification with 5 rules with the final result being Promoted and 4 rules with the final result not being Promoted. With an accuracy rate of 71.43% and a classification error of 28.57%