Reviewerly/exHarmony huggingface dataset:
Creating a General-Purpose Procedural Language for Programming in Kannada

Abstract: To build a general-purpose procedural programming language in Kannada and the corresponding header file that understands the language and pre-processes the code typed in Kannada into C++ programming language which can then be compiled by a C++ compiler and produce corresponding output in Kannada. The entire compilation of the language will be built in a single and Integrated Development Environment (IDE) i.e. Microsoft Visual Studio which can be downloaded by anyone and start learning to code in Kannada by including the header file. Any programming logic can be typed entirely in Kannada, the syntax is created such that it is similar to C-syntax. Any person knowing Kannada and with little effort on understanding the language’s syntax can start coding in Kannada without any prior knowledge in English or programming. This paper aims mainly at providing its users a programming experience in a regional language “Kannada”. The users can edit, complier and thus observe the results also in Kannada. The user has to abide by a set of syntactic rules and thus program accordingly for better results.
DETEKSI RODA KENDARAAN DENGAN CIRCLE HOUGH TRANSFORM (CHT) DAN SUPPORT VECTOR MACHINE (SVM)

In the digital image processing, many methods have been developed, the purpose of developing these methods is how computers can detect and recognize objects in an image with a precisely and process them in a relatively short time. Wheels are components that are always present in every vehicle, whether the vehicle is a bus, car or truck, it must have wheels with the same shape. If a wheel can be detected and recognized then the vehicle recognition and classification can be determined. This research focuses on capturing circle images, detecting wheel circles by applying Circle Hough Transformation (CHT). This transformation is able to recognize the object based on its boundaries and is resistant to noise. After obtaining the image of the circle, the next step is to classify it into Wheels and Non Wheels using the Support Vector Machine (SVM) method. The development of the wheel circle detection model on the side view image of this vehicle can be used as one of the first steps in research on wheel-based automatic vehicle recognition and classification systems.
Open University Chinese Language and Literature Teaching Model Based on NLP Technology and Mobile Edge Computing

With the further improvement of comprehensive national strength, both cultural soft power and international status have increased significantly. The Chinese language has also become one of the languages eagerly studied in all countries in the world. However, the teaching resources of Chinese as a foreign language are far from enough to meet the rapid growth of learning needs. With the continuous improvement of the network environment of high-performance, low-latency, and high-bandwidth mobile edge computing, using computer network technology to assist Chinese language learning is an effective way to meet the needs. Under this circumstance, this paper proposed to design and build a Chinese language learning system based on NLP (natural language processing) technology. The built system modules could be roughly divided into three parts: the basic module of the system, the learning module, and the tool module combined with NLP technology. And, through the rational use of these three modules, it provided learners with the basic teaching of the Chinese language and also collected a large number of relevant documents on the Chinese language and culture through the system, which was more convenient for learners to learn. Research showed that the learning system basically met the learning needs. According to the data survey on the use of international students, more than 90% of the international students who have used the system believed that the content expressed by the learning system was clear and scientific. The results showed that the design of the Chinese learning system met the learning needs of learners.
Analysis of Accounting Information System in Sales Decision Making in PT. Nusantara IV Adolina Tebing Tinggi

This study aims to examine and determine the sales information system in decision making sales applied by PT. Nusantara IV Adolina Plantation. The sample in this study was the procedures and criteria for sales accounting information system and decision making sales at PT. Nusantara IV Plantation Adolina North Sumatra. Data was collected by observation and interview methods. The analysis was conducted with qualitative and quantitative methods. Bay comparing theory with actual practice occurred, as well as the testing of the relevant documents. In the sales system, part of marketing and procrument functions accept mail orders from byers, edit orders from customers to add any missing information in the letter of the order, request credit anuthorization, specify the delivery date and of the warchouse where the goods will be shipped and fill mail order delivery as the winning bidder. Based on the analysis conducted, PT. plantation Nusantara IV Adolina transparency and validity of the data presented must meet the standards that exist, so trustworthy and can be used by the marketing as a support and decisions making. Thus PT Plantation Nusantara IV Adolina is able to earn profits as well as expand the market and increase greater sales.
EFFECTIVENESS OF STEGO IMAGE CALIBRATION VIA FEATURE VECTORS RE-PROJECTION INTO HIGH-DIMENSIONAL SPACES

Context. The topical problem of sensitive information protection during data transmission in local and global communication systems was considered. The case of detection of stego images formed according to novel steganographic (embedding) methods was analyzed. The object of research is special methods of stego images features pre-processing (calibration) that are used for improving detection accuracy of modern statistical stegdetectors. Objective. The purpose of the work is performance analysis of applying special types of image calibration methods, namely divergent reference techniques, for revealing stego images formed according to adaptive embedding methods. Method. The considered divergent reference methods are aimed at search an appropriate transformation for cover and stego images features that allows increasing Euclidean distance between them. This can be achieved by re-projection of estimated features into a high-dimensional space where cover and stego features may have higher inter-cluster distances. The work is devoted to analysis of such methods, namely by applying the inverse Fast Johnson-Lindenstrauss transform for estimation preimages of cover and stego images features. The transform allows considerably decreasing computation complexity of features calibration procedure while providing a fixed level of relative positions changes for cover and stego images features vectors, which is of particular interest in steganalysis. Results. The dependencies of detection accuracy, namely Matthews correlation coefficient, on cover image payload and dimensionality of estimated preimages for feature vector were obtained. The case of usage state-of-the-art HUGO, S-UNIWARD, MG and MiPOD embedding methods for message hiding into a cover image was considered. Also, the variants of stego image features preprocessing by full access to stego encoder for a steganalytic as well as limited a prior information about used embedding method were analyzed. Conclusions. The obtained experimental results proved effectiveness of proposed approach in the most difficult case of limited a prior information about used embedding method and low cover image payload (less than 10%). The prospects for further research may include investigation of applying special methods for features preimages estimation in a high-dimensional space for improving detection accuracy for advanced embedding methods.
Approaches to Easy-To-Read Discourses: a case study

In 2017, the organisation for Economic Cooperation and Development estimated that around 25 per cent of the population experiences difficulties in reading comprehension. The World Health Organisation (2021) has indicated that around 15 per cent of the world population faces functional impairment-related problems, which limit sufficient access to information unless the resources are adapted for meeting the needs of this layer of society. Considering the increasing numbers of the population who suffer from impairments at the language perception level, the present study has attempted to examine selected approaches that might serve for developing easy-to-read (EtR) discourses. Limited research has been conducted in the above-mentioned field, and the contributions that exist so far have focused on the linguistic and design features considered when producing EtR discourses; however, other central components that govern the adaptation of authentic texts for EtR needs seem to be neglected. Therefore, the present study aims to examine selected discourse-pragmatic approaches that can be applied for adapting texts to an EtR language. The present research is a qualitative case study targeted at EtR text developers and seeks to answer the research question: which discourse-pragmatic approaches should be considered to produce easy-to-read discourses? In conclusion, the paper offers the implications of the findings and reflects on the value of using discourse-pragmatic approaches to EtR discourse and cognitive load reduction.
Machine Learning for Smart Tourism and Retail

The unprecedented growth in the amount and variety of data we can store about the behaviour of customers has been parallel to the popularization and development of machine learning algorithms. This confluence of factors has created the opportunity of understanding customer behaviour and preferences in ways that were undreamt of in the past. In this chapter, the authors study the possibilities of different state-of-the-art machine learning algorithms for retail and smart tourism applications, which are domains that share common characteristics, such as contextual dependence and the kind of data that can be used to understand customers. They explore how supervised, unsupervised, and recommender systems can be used to profile, segment, and create value for customers.
Implementasi Long Short-Term Memory pada Chatbot Informasi Akademik Teknik Informatika Unila

The times have made technology develop rapidly and rapidly, one of which is artificial intelligence. According to an Accenture survey, s can help organizations with up to 30% operational costs and users enjoy having 24/7 instant access to the answers they order. However, there are many organizations and companies that have not used s to facilitate business, one of which is the Informatics Engineering Study Program, University of Lampung (PSTI Unila). The purpose of this research is to able to apply the Long Short-Term Memory (LSTM) algorithm to the academic information at PSTI Unila and demonstrate the accuracy of the algorithm. Broadly speaking, this research consists of 4 stages: data collection and exploration, data preparation, building model and training, and testing the model. The model is tested using the user validation method which gets an accuracy of 99%. With these accurate results, this model is quite feasible to be used as a place for students to ask questions about PSTI Unila academic information.
ENHANCING MATHEMATICAL SKILLS OF THE STUDENTS THROUGH DIGI-TECH APPS

The study aimed to determine the effect of using Digi-tech apps on the mathematical skills of selected Grade 8 students of Lumban National High School, Lumban, Laguna, School Year 2021-2022.It determined the level of the attributes of Digi-tech apps, student's mathematical skills, the significant difference on the level of students' mathematical skills before and after the utilization of Digi-tech apps, and the significant effect on the mathematical skills of the students.The level of the attributes of Digi-tech apps used in the study is Very High.The student's mathematical skills used in this study the scores revealed that the post-test scores of the students are higher than the pre-test scores.The test of difference between the scores of the students on the assessment tool for the mathematical skills before and after the utilization of the Digi-tech apps of the respondents resulted in rejecting the null hypothesis.This implies that there is a significant difference on the mathematical skills of students.Moreover, it shows how the Digi-tech apps significantly affect the mathematical skills of students in terms of their analytical skills, computational skills, graphing skills, and problem-solving skills.It will motivate the students to create an interest and attitude towards mathematics to learn at their own pace.It is highly recommended the continuous utilization of Digi-tech Apps used in this study as additional learning tools of the students especially those who are under the modular distance learning modality.The utilization of Digi-tech apps as a tool may help the students to learn and improve their Mathematical skills.The continuous advancement of technology leading to new learning tools must be applied to the learning setting to ensure the provision of quality education.Further studies may be conducted in line with the new normal education that may improve the teaching-learning process.
Research and Practice on Testing Methods for Mobile Robot Positioning Accuracy

To solve the problem of low positioning precision of mobile robot in conventional manual test with low test efficiency,and pose measurement based on high-precision pose measurement tools show deficiency in a low degree of automation, which fails to be directly used to evaluate test results. This paper proposes a position precision based on high precision position measuring tool automation testing methods, which can not only solve the low conventional manual test precision, and when the positioning accuracy is required to reach a higher standard, the error caused by manual measurement makes the measurement result fails to be used as the evaluation benchmark.In addition, it can automatically collect pose points in the process of repeated autonomous movement of mobile robots, and then automatically analyze the pose error when reaching a specific position point every time. It is suitable for repeated testing in industrial scenes for a long time, and achieves the purpose of improving test efficiency and productivity.
Arduino-Based Anti-Theft System in Mosque Charity Box

The high level of criminal cases makes people have to be more vigilant. One of them is theft. Theft does not only occur in private areas such as homes, but often occurs in public locations, namely places of worship. There are many cases of theft of charity boxes at mosques or other places of worship. In this study, a security system was designed that was applied to the charity box. This tool is expected to reduce the rate of loss of donations in charity boxes. The charity box has an RFID sensor installed to unlock it and a motion sensor to detect movement if a thief tries to unlock the box.
A Question Answering Framework Based on Hybridization of Deep Learning and Semantic Web Techniques

The question answering (QA) system has been existing for several years. QA systems are divided into different processes such as question processing, document processing, paragraph extraction, answer extraction, question analysis, phrase mapping, disambiguation, query construction, querying the Knowledge Base (KB), and result ordering on user response respectively. Based on these processes, many models have been developed using approaches ranging from linguistic, statistical, and pattern matching. Popular models are Feedback, Refinement and Extended VocabularY Aggregation (FREyA), PowerAqua, SemSek, Semantic Interpretation of User Queries for QA on Interlinked Data (SINA), DEep Answers for maNy Naturally Asked questions (DEANNA), gAnswer, SemGraph, OKBQA (Open Knowledge Base and Question Answering) and Semantic Question Answering (SQA), for performance evaluation, these mostly focus on higher precision, recall, and/or F-measure. However, most of these models are constrained in the following operations: the combination of knowledge bases from different sources, formalism for knowledge representation to support interoperability, optimization of query construction and generation, ranking of responses, and support for set operations (union, sorting, comparison, and aggregation on user query) during query generation. This research proposes a hybrid of recurrent neural network and semantic-web-based question answering as the (RNNSQA) framework that combines heterogeneous knowledge sources and improves on state-of-the-art query generation mechanisms to allow for integration of comprehensive question-type operations, and set-based operations listed above. First, there would be a combination of techniques that is Natural Language Processing (NLP) and Recurrent Neural Network (RNN) techniques in classifying questions into types. Secondly, the semantic web technique is then employed in generating (SPARQL Protocol and RDF (Resource Description Framework) Query Language) SPARQL-based candidate queries. The result of this study is an enhanced QA framework with improved query translation and construction capability.
A segmentally informed solution to automatic accent classification and its advantages to forensic applications

Traditionally, work in automatic accent recognition has followed a similar research trajectory to that of language identification, dialect identification and automatic speaker recognition. The same acoustic modelling approaches that have been implemented in speaker recognition (such as GMM-UBM and i-vector-based systems) have also been applied to automatic accent recognition. These approaches form models of speakers’ accents by taking acoustic features from right across the speech signal without knowledge of its phonetic content. Particularly for accent recognition, however, phonetic information is expected to add substantial value to the task. The current work presents an alternative modelling approach to automatic accent recognition, which forms models of speakers’ pronunciation systems using segmental information. This article claims that such an approach to the problem makes for a more explainable method and therefore is a more appropriate method to deploy in settings where it is important to be able to communicate methods, such as forensic applications. We discuss the issue of explainability and show how the system operates on a large 700-speaker dataset of non-native English conversational telephone recordings.
An Analysis of Speaking English Routine on Students’ Competences at Basic Level of Genta English Course Pare-Kediri

This study aims at improving the speaking competence of the basic level students of Genta English Course Pare Kediri. Speaking English routine were used in this study. This study is an action research study which comprised a class. It involved me as the researcher, the principle of Genta English Course, the English teacher, and 10 students of the basic level students of Genta English Course Pare Kediri. The steps of this study were observation, questionnaire, and documentation. The data of this study is qualitative. The qualitative data were obtained by observing the students’ competences in speaking English routine. The data were collected in the forms of field notes and questionnaire paper. And the last is by documentation, the data were collected in the performances in learning process. The research finding shows that the use of the speaking English routine is effective to improve students' speaking competence. English routine is accompanied with other actions such as using English classroom/dormitory, memorizing vocabularies, doing English language in any activities, giving feedback, giving rewards, and doing English program. The indicators of the success of the implementation are that: (1) the students are more active in the speaking English routine than they were; (2) the students are more enthusiastic in doing speaking English routine; and (3) the students' self-confidence and motivation to speak English improve. Furthermore, the findings are also supported by the means of the students' competences which have increased.&#x0D; Keywords : Speaking, English Routine, and Students’ Competences
The Relationship Between Leisure Time use and Life Satisfaction of the Elderly from Foreign Studies and Policy Implications for Vietnam

Leisure time use has many benefits for personal and social development. Therefore, leisure time use of the elderly also has positive signification for their lives. By literature review method, the article identifies the current status of leisure time use and its benefits to the elderly's life. The article clearly shows that participating in free time activities helps the elderly reduce depression, improve health and reduce loneliness. Hence, the more active old people participate in leisure activities (exercise, social and cultural activities, etc,…), the higher the life satisfaction is. On this basis, some recommendations with policy implications are proposed to help the elderly have a better life in their final years.
School Bullying in the Aspect of Future Teacher's Readiness for its Prevention

This article deals with the problem of bullying in the educational environment among students and teachers.Some knowledge about the bullying problem was revealed, with the help of a special survey, among 70 college 3-4 year undergraduate students.There were developed ways of studying the problem of bullying among college students.The research shows features of bullying in educational institutions, types and causes of occurrence; some work was also conducted to determine the body of knowledge about the bullying problem among college students and to suggest recommendations to college undergraduates on the problem of bullying.The author considered scientific works of home and foreign scholars.This article presents the results of a research aimed at identifying awareness of the bullying problem among future teachers.The results of the study will benefit the administration of the educational institution, as well as educational psychologists, teachers, teachers, and social pedagogues.They will also be useful to teachers when they conduct various individual and group conversations, class hours, parent meetings, etc.The psychological and socio-pedagogical literature is analyzed, in order to obtain it as a methodological basis to the study.The phenomenon of the aggression between a school child and a major adult is under study; so, there have been identified factors that provoke that kind of bullying among school-age children and significant adults.The study revealed two main forms of bullying manifestation among school-age children and teachers.The article discusses five roles that bullying participants take on in the course if the conflict.The author examined real examples of bullying situations.
Local Applications of Logics via Model-Theoretic Interpretations

This paper analyses the notion of ‘interpretation’, which is often tied to the semantic approach to logic, where it is used when referring to truth-value assignments, for instance. There are, however, other uses of the notion that raise interesting problems. These are the cases in which interpreting a logic is closely related to its justification for a given application. The paper aims to present an understanding of interpretations that supports the model-theoretic characterization of validity to the detriment of the proof-theoretic one. This is done by making use of the hierarchy of ST-related logics. Finally, a localist conception of logic is defended as the natural view stemming from the model-theoretic approach.