Reviewerly/exHarmony huggingface dataset:
Sistem Pakar Mendiagnosa Penyakit Keputihan Pada Wanita Dengan Metode Teorema Bayes

Leucorrhoea is a discharge other than blood from the vaginal canal, if abnormal vaginal discharge is left untreated, as a result the infection can spread, enter the uterus, fallopian tubes, and can infect the ovaries. The application of an expert system in the health sector will greatly assist in survival someone. Expert systems can help diagnose a type of disease based on their own symptoms quickly and precisely. An expert system that is designed as a tool to diagnose the type of leucorrhoea, especially in women who experience vaginal discharge, but often they feel able to recognize themselves that they are suffering from vaginal discharge without feeling the need to go to a doctor for a more detailed examination, and only treat themselves with medication. Free-sale vaginal discharge medication. This expert system will display a selection of symptoms that can be selected by the user, then get the final result with the Bayes theorem method by providing a diagnosis result in the form of a probability value for the emergence of each type of disease and solution. Expert system applications are built on a web basis using HTML, PHP, CSS using the mysql database.
On the Application of Computer Science and Technology in Computer Education

The computer has become an indispensable and important tool in people's daily life and work. It brings more convenience to people and provides important conditions for human survival and development. Therefore, the application of computer science and technology to computer education can enable students to have a correct understanding of computer application concepts and practical operations, thereby improving the level of computer education. This article mainly analyzes the advantages and significance of the application of computer science and technology in computer education, and proposes the measures to be used, hoping to provide certain references and suggestions for the cultivation of computer talents.
Joint Cross-document Information for Named Entity Recognition with Multi-task Learning

Named entity recognition (NER) is an essential task in information extraction and knowledge graph construction. Numerous traditional methods for NER are sentence-level, which only utilize all the information in one sentence and predict entities inconsistently sometimes. Recently, researchers observe that the relationship between sentences in a document is helpful for the NER task, therefore they consider to conduct documentlevel approaches which capture context information within a document. Though these methods are effective and have been widely used, they ignore correlations between sentences in different documents. To make full use of the cross-document context information, we design an attention mechanism to model the semantic association between occurrences of the same word in different documents. In addition, we find that it is extremely helpful to add a multi-classification auxiliary task, which focuses on coarse-grained entity information. The multi-objective optimization is implemented by weighted summation and an autonomous approach using the homoscedastic uncertainty of each task. Extensive experiments in different datasets show that our approach is effective, and our models achieve better results than the sentence-level and document-level NER approaches.
Editing Taiwan divination Verses with controlled Language Strategies: Machine-Translation-Mediated Effective Communication

Editing Taiwan divination Verses with controlled Language Strategies: Machine-Translation-Mediated Effective Communication Chung-ling Shih Abstract Aimed at fostering machine-translation-mediated communication across languages and cultures, this paper proposes editing Taiwan divination verses from the natural into controlled language to improve the comprehensibility of machine translation (MT) outputs. After editing 160 divination verses, and evaluating the semantic and grammatical accuracy of their English MTs that are produced by online Google Translate (a neural MT system for free), the author has identified several controlled language strategies. The lexical strategies include replacement of archaic Chinese words with vernacular Chinese ones, paraphrasing of culture references and insertion of explanations for metaphors. Grammatical strategies are the use of articles, determiners and possessive cases, and syntactical ones include the addition of conjunctions and the restoration of missing subjects or/and objects. The MT outputs of edited and unedited divination verses are compared. The findings show that the English MT outputs of edited texts have greatly improved their semantic, grammatical and syntactic accuracy, so the effectiveness of controlled language strategies is justified. Due to the effectiveness of editing verses with controlled language strategies, the goal of MT-enabled web-based communication across cultures is achieved. The practical significance is also discussed including culture acquisition and cost reduction. Full Text: PDF DOI: 10.15640/jflcc.v8n2a2
A Blockchain based P2P Transaction Model

With the growing demand for information technology, the digital economy is developing at a large pace. Blockchain (BT) is the medium, which connects the world's economy to the digital economy. Blockchain has importance in these applications, which manage finance and cryptocurrencies etc. Blockchain technology provides distributed management of ledgers with secure and smart transactions. In existing studies, there is no reasonable proposal for P2P transactions in Blockchain technology. The proposed work is implemented a peer-to-peer (P2P) application in Python programming language with blockchain technology. The secure transaction is ensured in the proposed system using SHA hash techniques. The proposed work used BT to create smart transactions between any number of Peers and creates an association between digital transactions and physical transactions. The proposed work ensures data security and provides trust among p2p network transactions. All peer nodes in the blockchain calculate or can mine a block and create the remaining amount in parallel, and then summarize the results. This makes good use of the vast resources of the processing unit resources in the blockchain and makes the calculation precious.
Implementation of reduced induction machine fuzzy logic control based on dSPACE-1104 R&amp;D controller board

In this paper, we present our contribution in Induction Machine control field. The control we designed is based on fuzzy logic theory, this choice is motivated by the fact that this technique of control is suitable for the control of systems characterized by its parameters uncertainties and variations. The proposed control is optimized by using a genetic algorithm for fuzzy logic controller (FLC) gains tuning and by a good choice of calculation techniques used in FLC. Three versions of IM fuzzy logic control were validated by simulation. After that in order to be able to experimentally implement this control on dSPACE-1104, we proposed an optimized and reduced structure of the control. The experimental results proof the effectiveness and the satisfied performance of the proposed IM fuzzy control.
IMPROVING STUDENTS’ ABILITY IN WRITING DESCRIPTIVE TEXT BY USING REALIA MEDIA

The aim of this research was to investigate whether the use of realia is effective in improving tenth grades ability in writing descriptive text or not. The research conducted at SMA Negeri 1 Tompaso, North Sulawesi, Indonesia, in which X MIPA 1 was chosen as the sample. This class consists of twenty-nine students. This quantitative research used a pre-experimental design with one group pre-test and post-test design. Pre-test has given before the treatment. After the writer gave a treatment, the writer collected the data for post-test. The result of this research showed that the mean score of pre-test is 4.86 and post-test is 7.48. This means that the result of post-test is higher than pre-test. In other words, this result may lead to conclusion that using realia media was considered to improve students’ ability writing descriptive. Keywords: Realia Media, Writing, Descriptive Text
PROTOTYPE APLIKASI USAHA MIKRO BANK SAMPAH SYARIAH KEMUNING BERBASIS ANDROID

The Kemuning waste bank micro business is a concept built on the basic idea and a form of public concern for the environment to overcome the management of household waste in residential areas. The management of the Kemuning waste bank that is currently running is still semi-computerized, namely customer data is still recorded in a ledger then inputted to the computer using Microsoft Excel, waste data is not recorded properly so that it is not known how much waste has been received by the waste bank in 1 year, and customer savings data recorded in the customer's savings book so that customers must look at the savings book to find out their savings balance. To overcome this, a system for managing savings and transaction data as well as information on sorting waste for new customers is needed, namely the Android-based Islamic waste bank application. The expected end result is that this Android-based application can overcome the problems of the current system so that it can maximize the processing of waste data, transactions and savings and make monthly reports easier and become a form of waste bank micro business unit that can become supporting the economic growth of the people of Kemuning. Keywords: Micro Business, Application, Sharia Waste Bank, Android
Needs Analysis of The Traffic Safety Training Hyper Content Module at The Ministry of Transportation

Traffic safety training whose material needed a concrete visualization aspect. To accommodate this, teaching materials were needed to support the learning process. This study aims to describe the results of needs analysis which is the first step of the Research &amp; Development process conducted with a qualitative approach. Data collection techniques are done by conducting research through documentation, observation, and interviews. The results of the needs analysis have been found several problems, that is the heterogeneous characteristics from training participants, limited experience of training participants, limited training time, lack of teaching materials, and training implementation locations throughout Indonesia. Hyper content-based printing modules are a great alternative because they can bring related factual aspects of traffic safety to training participants. In the next research, it is expected to develop a hyper content-based traffic safety training module.
Multi-source Transformer for Automatic Post-Editing of Machine Translation Output

Automatic post-editing (APE) of machine translation (MT) is the task of automatically fixing errors in a machine-translated text by learning from human corrections.Recent APE approaches have shown that best results are obtained by neural multi-source models that correct the raw MT output by also considering information from the corresponding source sentence.In this paper, we pursue this objective by exploiting Transformer (Vaswani et al. 2017), the stateof-the-art architecture in MT.Our approach presents several advantages over previous APE solutions, both from the performance perspective and from an industrial deployment standpoint.Indeed, besides competitive results, our Transformer-based architecture is faster to train (thanks to parallelization) and easier to maintain (thanks to the reliance on a single model rather than a complex, multi-component architecture).These advantages make our approach particularly appealing for the industrial sector, where scalability and cost-efficiency are important factors, complementary to pure performance.Besides introducing a novel architecture, we also validate the common assumption that training neural APE systems with more data always results in stronger models.Along this direction, we show that this assumption does not always hold, and that fine-tuning the system only on small in-domain data can yield higher performance.Furthermore, we try different strategies to better exploit the in-domain data.In particular, we adapt reinforcement learning (RL) techniques to optimize our models by considering task-specific metrics (i.e.BLEU and TER) in addition to maximum likelihood.Our experiments show that, alone, the multi-source approach achieves slight improvements over a competitive APE system based on a recurrent neural network architecture.Further gains are obtained by the full-fledged system, fine-tuned on in-domain data and enhanced with RL optimization techniques.Our best results (with a single multi-source model) significantly improve the performance of the best (and much more complex) system submitted to the WMT 2017 APE shared task.
Librarians and Repository Data

This study aims to determine the librarian's understanding of data repository which include benefits, engagement of librarians in repository management, and repository implementation. The study has surveyed librarians at the Indonesian Institute of Sciences located in Jakarta, Bogor, Cibinong, and Serpong by distributing 45 questionnaires, but only 36 returned. The data were tabulated and analyzed using graphs/diagrams. The respondents of the study were female (61.1%) and male (38.9%). The education background of the respondents was undergraduate (50%), the most working period is between 20-30 years (38.9%), and the most work locations were in Jakarta (70.6%). The study showed that respondents with an undergraduate background and those who work in Jakarta have the highest understanding of the repository (69%). The most involved in repository management were those with bachelor's degrees and working in Jakarta (52%). Respondents who were involved in the socialization of the data repository were 47%, and those who were not involved were 44%. As many as 44% of respondents stated that the data repository has been implemented, and the remaining 56% said it has not been implemented. In conclusion, most respondents understand the data repository, especially those with a bachelor's degree, and were working in Jakarta. The data repository has not been implemented properly due to lack of outreach to researchers and their low trust in the data repository.
SEAUNet:Domain Adaptation for Biomedical Image Segmentation

Semantic segmentation plays an important role in biomedical image analysis applications. Convolutional neural networks (CNN) have become a promising approach to segment biomedical images. Nevertheless, the accuracy of these methods is highly dependent on the training data. These models may not generalize well to unseen image domains due to the phenomenon of domain shift. We propose a self-ensembling attention networks to address domain shift for biomedical image segmentation. There are two main components in the proposed network: a student network which plays a role of the base networks and a teacher network which plays a role of the ensemble networks. As the iteration goes on, the student network becomes more accurate, and the ensemble predictions in the teacher network also get closer to the correct labels in the target domain. In this way, domain-invariant features can be learnt correspondingly. We use the DRIVE, STARE, HRF and CHASEDB eye vasculature segmentation datasets and show that our approach can significantly improve results where we only use labels of one domain in training and test on the other domain.
The Antecedents and Consequences of Legitimate Corporate Participation in the DarkNet: A Preliminary Model

The DarkNet is a purposefully hidden collection of disconnected web sites that are not indexed by conventional or mainstream search engines, are not accessible by conventional means, and requires specialised software, specific knowledge, and authorisation to gain access.While typically associated with illegality and criminality, there are an increasing number of legitimate organizations active on the DarkNet.While explored widely in Computer Science, Humanities and Social Science, Engineering and Medicine, there is a paucity of research in the business and IS disciplines.The objective of this paper is to introduce the DarkNet and DarkNet Commerce, summarise extant business and IS research, albeit limited, and outline a proposed model to explore a previously unexplored relationship in the business and IS literature, namely the antecedents and consequences of the participation of legitimate organisations on the DarkNet.
Reflection of Character Education Value through Depictions of Characters in Oka Rusmini's Koplak Novel

This research aims to describe the character education value reflection through characters' depiction in Oka Rusmini's novel Koplak. This research is descriptive qualitative research. The approach used in this research is psychological. The data collection technique used was a documentary study. The data source in this research is the novel Koplak by Oka Rusmini. This study's data are character education value reflections through the depiction of the character in the data source, that is Koplak novel by Oka Rusmini. The data were collected using the reading technique and note-taking technique. The data analysis uses an interactive-analysis method. This study results indicate that there are reflections of character education value through the character depiction in Oka Rusmini's novel Koplak, namely honest, caring, and attention.
RESEARCH OF ABILITIES IN LEARNING WORK WITH STUDENTS-PSYCHOLOGISTS

The article highlights the features and course of application of the research approach to the study of abilities in educational work with students-psychologists. A review of scientific publications on the selected topic; approaches to the study of abilities are clarified. Features of studying of abilities from positions of various approaches are considered. The specifics of involving students in the study of abilities are highlighted. The research consisted in the development and implementation of an optimal approach to acquainting students with the study of abilities, which would combine existing knowledge on this topic on a rational basis, present them in an appropriate logical sequence, based on their needs for such knowledge, existing level of knowledge and current requirements for professional training of psychologists. The study provides both analytical and practical components; it is organized and conducted by the teacher, but with the fullest possible involvement of students. In the analytical part of the study, the material on this topic was processed: unclear provisions were clarified, certain points were clarified and concretized, etc. Students must show the ability to independently process the material intended for study, as well as to be involved in the process of resolving issues submitted for consideration. The practical part of the study implements the demonstration of the possibilities of working with abilities in the practice of a professional psychologist: both the diagnosis of features and the development of indicators; performed mainly during practical classes. There is also an opportunity, if necessary, to ask students individual creative tasks for extracurricular activities. The result of the research work was that students not only better understood the role of abilities in everyday life, educational and professional activities, their purpose, features and manifestations, but also found out the possibilities of developing and applying abilities in future professional activities. They mastered the approaches and theories, which were introduced in lectures, in practical activities, which is close to the daily work of a psychologist. The conclusions from the carried-out work are made and prospects of the further researches in this direction are outlined. Key words: educational process, training of future professional psychologists, research of abilities, research approach in educational activity, development of abilities.
Method of encryption of text information based on LSFR

The article is devoted to the development of an LFSR-based method for encrypting text information. A method for encrypting information using a Linear Feedback Shift Register (LFSR) and dynamic keys is proposed. The long period and good statistical characterization of the sequence generated by the LFSR, while performing simple shift and addition operations, ensures high reliability and speed of the encryption process. In the proposed system, it is assumed to use several registers at the same time, the number of which is determined by the bit depth of the encrypted character. The cryptographic key used is a concatenation of the values Ki (i=1,2,...,8) entered in the shift registers: K= K1K2...K8. And the values Ki are calculated based on the components of the session key (i=1,2,...,8) and the system time parameter. It is possible to extend the cryptographic key by increasing the bit depth of the registers. In a system with 32-bit registers, the total key length is l=25*23=28= 256 bits, and with 64-bit registers, 512 bits. The proposed method can be implemented in hardware, software, and hardware-software combination. The maximum speed of the process is achieved in a system with a hardware implementation, since the encryption of a single character in such a system is performed in just one clock cycle. It is also possible to increase the speed of the process by encrypting several characters at the same time, using the appropriate number of registers for this purpose. The resistance of the proposed cryptosystem to brute force attacks is quite high, since when using 32-bit registers, the key length will be 256 bits and the key area will be equal to 2256. Enhancing the key domain and applying dynamically changing cryptographic keys provides the necessary level of encryption process. The system is implemented to encrypt text information, but it can also be used to encrypt information in other formats.
Application of Blended Learning (Discovery Learning, Role Play &amp; Simulation, Cooperative Learning, and Collaborative Learning) to Increase Activity and Achievement in Public Speaking Course

Public speaking courses have taught that the importance of communicating well and can communicate with the public by being a good public
Web-Based Kanji Characters Learning: Undergraduate Students’ Conception

The use of web-applications in online learning has rapidly developed during the COVID-19 pandemic.In higher education, these internet-based educational technologies have been believed to play a significant role as an agent for quality learning improvement.This study reports on undergraduates' conception of the use of web-based applications on learning Kanji characters.It seeks to identify Mrs. Kanji's application effects on students' capability to retain both the visual forms of the Kanji characters and their meaning.Considering the pandemic situation, data was collected by administering a set of online questionnaires to 186 undergraduate students who learn Japanese in six universities located in different geographical areas in Indonesia.The quantitative analyses showed that the students had firm beliefs that the application had helped them retain the forms and meanings of the kanji characters.This study suggests the significance of utilizing the application to improve students' reading performance.
Validated Trajectory Tracking using Flatness

The problem of a safe trajectory tracking is addressed in this paper. It consists in using the results of a validated path planner providing a set of safe trajectories to produce the set of controls to apply to remain inside this set of planned trajectories while avoiding static obstacles. This computation is performed using the differential flatness of many dynamical systems. The method is illustrated in the case of the Dubins car.