Reviewerly/exHarmony huggingface dataset:
Image semantic segmentation algorithm based on a multi-expert system

Deeplab series semantic segmentation algorithms extract target semantic features using deep layers of a convolutional neural network, resulting in target features lacking detailed information, such as edges and shapes extracted by shallow layers. Deeplabv3plus uses atrous convolution to obtain feature maps, which lose some image information. All of the above have an impact on segmentation performance improvement. In response to these issues, which reduce segmentation performance, we propose an image semantic segmentation algorithm based on a multi-expert system that builds multiple expert models based on the Deeplabv3plus network architecture. For the target image, each expert model makes independent judgments, and the segmentation results are obtained through the ensemble learning of these expert models. Expert model 1 employs the proposed attention-based atrous spatial pyramid pooling (C-ASPP) module to capture richer global semantic information via a parallel attention mechanism and ASSP module. Expert model 2 designs a feature fusion-based decoder that uses a feature fusion approach to obtain detailed information. Expert model 3 introduces a loss function in the Deeplabv3plus network for supervised detailed information loss. The final segmentation results are generated by adjudicating the results derived by the different expert models, which improves the segmentation performance by compensating for the loss of detailed information and enhancing the semantic features. Evaluated on the commonly used semantic segmentation datasets PASCAL VOC 2012 and CamVid, the algorithm’s mIoU reached 82.42% and 69.18%, respectively, which were 2.46% and 1.82% higher than Deeplabv3plus, proving the better segmentation performance of the algorithm.
Meningkatkan Kemampuan Matematika Siswa Kelas I dengan Menggunakan Media Pembelajaran Sempoa di SDN 17/I Rantau Puri

The reason mathematics is considered an important subject is because mathematics is able to equip students to think logically and analyze. The purpose of this study was to improve the math skills of grade 3 students at SDN 17/I Rantau Puri by using the abacus media. The research method used is Classroom Action Research (CAR). The research subjects were grade 3 SDN 17/I Rantau Puri with observation, interview and documentation data collection techniques involving class teachers and grade 3 students. The research process was passed through Cycle I and Cycle II with components namely planning, action, observation, and reflection. From the results of this study, we can see that using Sempoa media can improve math skills in grade 3 students at SDN 17/I Rantau Suri. This can be seen from the teacher's activities which were initially in the sufficient and good category in cycle I so that they received a very good category in cycle II. While student activity also increased with the very good category.
A Topic Model based on Weighted Word Co-Occurrence Matrix and user Topic Relationships

Various industries have widespread adopted the intelligent customer service, thus how to understand customer intent more accurately and extract key information has become a current research hotspot. However, the features that customer service dialog texts are short length, specialization and sparse lead to the poor performance of traditional topic extraction. Based on the above background and characteristics, this paper proposes a topic model WCMUT-HDP, which is based on a weighted word co-occurrence matrix and user topic relations. In the WCMUT-HDP model, this paper introduces a semantically weighted word co-occurrence matrix to mine the statistical and semantic features of customer service texts and optimize the effect of clustering. For the structure of customer service dialogues, this paper introduces temporal and author attributes of customer service dialog into the topic recognition of customer service texts. This method helps us to accurately extracts the user's intention. WCMUT-HDP is based on the Dirichlet process, and does not need to specify the number of topics in advance, which saving the time overhead of parameter experiments and evaluation. In the end of this paper, the experimental results show that the WCMUT-HDP model can effectively identify the topics of customer service conversations, and the extracted topics can accurately reflect the user's conversational intent.
Question-Type Identification for Academic Questions in Online Learning Platform

Online learning platforms provide learning materials and answers to students' academic questions by experts, peers, or systems. This paper explores question-type identification as a step in content understanding for an online learning platform. The aim of the question-type identifier is to categorize question types based on their structure and complexity, using the question text, subject, and structural features. We have defined twelve question-type classes, including Multiple-Choice Question (MCQ), essay, and others. We have compiled an internal dataset of students' questions and used a combination of weak-supervision techniques and manual annotation. We then trained a BERT-based ensemble model on this dataset and evaluated this model on a separate human-labeled test set. Our experiments yielded an F1-score of 0.94 for MCQ binary classification and promising results for 12-class multilabel classification. We deployed the model in our online learning platform as a crucial enabler for content understanding to enhance the student learning experience.
A Customer Service Text Label Recognition Method based on Sentence-Level Pre-Training Technology

Customer service text data is known as the dialogue text data between users and customer service provider, and it contains a large amount of user information. The effective use of customer service text content can bring great business plan optimization to the service provider. Based on the traditional machine reading comprehension model, this paper builds a customer service text user's attribute label recognition model, and proposes a model pre-training method based on sentence-level pre-training technology: aiming at the background of poor performance of the model in answering comprehensive full-text content analysis questions such as user intent and text sentiment analysis. This paper extracts text summaries based on the T5-pegasus model, constructing a text summaries dataset for model pre-training. Then build a text summarization model including an ERNIE pre-training model, train the model's ability to understand the full text, and improve the model's ability to answer questions that need to be combined with full-text content understanding, such as user intent and sentiment analysis. Use the pre-trained model to solve customer service text label recognition tasks based on machine reading comprehension tasks. The test results based on the data set show that the improved model has an improvement in performance of customer service text label recognition task.
Ablo Application for Indonesian English as Foreign Language Learners

This research aims to describe the Ablo application which is a Social Network Site as the learning medium for Indonesian EFL learners. It used descriptive qualitative research to describe how the Ablo application and its features are to learn the four English skills, the feasibility of this application as a Mobile-Assisted Language Learning (MALL), and the learners' interest in this application. This research used participatory observations on the features of the Ablo application and interviews with 30 users who had been using this application in Indonesia. The results of this research showed that Ablo as an application can be used to learn four language skills in English for EFL learners in Indonesia. As feasibility of MALL, it also fulfills the main characters such as portability, social interactivity, context sensitivity, connectivity, and individuality. While the interest of learning in Ablo is very positive.
A Psychological Approach into the Hypermodernity Aspects of the Netflix Series &amp;quot;Dark&amp;quot;

Dark is a Netflix series that explores the interesting idea of time travel, which is very famous in popular culture.This paper is trying to interpretate the notion of time travel, as a literary theme, in its psychological aspects, in relation to the Dark Netflix series, using statistical analysis of the duration of every scene in each episode of the first season of Dark.The authors are using statistical analysis to explore (a) the conflicting relations between major characters and (b) their relationship with space and time.Our research estimated the duration of each scene in every episode of the first season in Dark.Each episode "broke down" into scenes, the duration of each scene and the duration of the timeline of each character (in every scene, sequence, episode respectively).Εach character's relation with specific space (i.e.Winden, police station, school etc.) and time (1953, 1986, 2019 2052) was statistically measured.In addition, we measured the duration of the conflict of each character in every scene in every space and time.The duration of every scene, characters timeline and conflict time was calculated and then clustered into first order factors such as, NATURE, CIVILIZATION, CONFLICT, TIME etc.Other first order factors were clustered, such as the total duration of a character's appearance in specific space and in certain time Statistical analysis showed that there is no significant difference in any of the 1 st order factors examined.This finding highlights key aspects of hypermodernity, a key term that outlines the current human condition by describing the deeper connection of an individual with space and time.The authors are arguing that time travel theme in Dark is very close to the theoretical construct of hypermodernity because it is expressing the profound ways in which individuals are related, intertwined, and reflecting upon their own experience with space and time.This experience of space and time is a core element in today's hypermodernity state.In addition, this paper is also trying to articulate a psychoanalytical reading of the Dark series, which further highlights the hypermodernity aspect of this narration.Under this scope, the authors are arguing that "Dark" should be considered as one of the most prominent hypermodern television series.
Phishing Website Detection using Machine Learning Techniques

Phishing refers to the fraudulent attempt to obtain sensitive information such as a user's username and password, as well as details about a checking account or credit card, for the purpose of using that information for malevolent purposes. It's possible that phishing scams are the most common form of cybercrime utilised today. Phishing attacks can be launched against victims in a variety of contexts, including the online payment industry, webmail, financial institutions, file hosting or cloud storage, and many more. Phishing may be detected quite effectively through the use of machine learning. Additionally, it eliminates the problem that was caused by the prior method. This study focuses on the application of machine learning technology to the problem of identifying phishing URLs. Specifically, it extracts and compares numerous characteristics of real and fraudulent URLs. By utilising the Support Vector Machine technique as well as the Random Forest technique, the project intends to identify URLs that lead to phishing websites.
Analysis of Computational Algebra for Cryptography and Coding Theory Applications

Secure communication is essential in many areas of today's interconnected society, from online commerce to international affairs. The foundation of data security is made up of encryption and decryption algorithms, and effective execution calls for an organised approach rather than a chance procedure. This study analyses several encryption techniques with an emphasis on those that apply algebraic coding theory to cryptography. These algebraic coding theory-based cryptographic systems are particularly significant for the future of data security because, in contrast to many existing systems, they provide resistance against attacks from quantum computers.This essay emphasises the necessity of an organised approach while outlining the essential concepts of encryption and decryption. It examines several encryption techniques, including symmetric and asymmetric encryption, pointing out their advantages and disadvantages.The study then explores how algebraic coding theory is used in cryptography. It explores the fundamental mathematical concepts that underlie algebraic coding methods, including finite fields and polynomial arithmetic. The McEliece cryptosystem and Niederreiter cryptosystem are two examples of unique algebraic coding theory-based cryptographic schemes that are the subject of this examination, which also highlights their benefits in terms of security and resilience to quantum assaults. These methods' computational complexity is also analysed, taking into account things like key sizes and encryption speed.With the help of the knowledge gleaned from this investigation, strong encryption systems that can survive upcoming developments in computing technology can be created, guaranteeing the secrecy and integrity of critical data in daily life.
CONTEMPORARY AUDIOVISUAL TECHNOLOGIES IN SYNTHESIZED MUSIC AND ART PROJECTS

The current state and needs of the contemporary mass culture and the technical and scientific progress that went through an especially drastic development in the second half of the 20 th century, passing the stage of informational and later electronic revolution and now moving on to the stage of 'nano revolution', have not only created the preconditions for the emergence and development of new types and genres of art, first of all, in the mass culture domain, but also changed the very process of creation and realization of works of art.The contemporary technologies contribute to the unification and thus globalization of the art-making processes.Nowadays, one can speak of the emergence of new formats of consumption of art 'products', of putting them on the cultural and art market.This is facilitated by an intensive development of mass media and technologies.New audiovisual means have made it possible to bring to a higher level the preparation and realization of such phenomena of artistic culture as mass music events, concerts, festivities, music and art programs.Aim of the article: characterizing the contemporary audiovisual technologies in synthesized music and art projects.In the context of the spread of new technologies, the article reveals the latest development of the already classical genre of concert in all its types.Quite a number of absolutely new mass genres have emerged, such as musical light show, electronic extravaganza, pyrotechnic show, etc.In order to create such art products, a new interdisciplinary community of professionals has emerged in addition to authors and performers, including sound engineers, lighting directors, video directors, specialists in electronic and computer technologies, special effects, etc.By analogy with technical disciplines, the process of planning, creation and realization of an aggregate of synthesized music and art products united by a common conception is called a project.Identifying the peculiarities of their functioning and their types, which combine various types and genres of art, performance styles and technologies of creation and realization, broadens the existing knowledge about this art phenomenon in the contemporary art studies.The study of this phenomenon as an important component of cultural life of the contemporary society reveals the specificity of this art phenomenon and enriches the knowledge of the peculiarities of development of mass culture in the early 21 st century.
Impact of Covid-19 Pandemic on Primary Education in Saudi Arabia: TAM Implementation on MADRASATI System

The routineness of human activities of multiple sectors has been compromised since Coronavirus (COVID-19) appears.Many governments have applied mobility restrictions due to this pandemic to maintain the confinement social distancing, closing borders between countries.COVID-19 pandemic changed the whole world.The increase of COVID-19 diagnoses incidents pushes countries to use the technologies to tackle the adverse effect of COVID-19, which were swift on all education aspects.Worldwide, the regular classroom setting changed to online virtual classes.In Saudi Arabia, during the pandemic, a new system for teaching was created and implemented by the Ministry of Education called MADRASATI.Such a platform can introduce that distance learning can be conducted in an organized, effective, and pedagogically sound manner, as it can be adopted in future teaching activities.Also, it will be a perfect alternative solution to overcome school interruption problems on any day after the pandemic ends.The acceptance level of these platforms of education can lead to having an alternative approach to education in the future.To study how students, teachers, and parents are acting toward this MADRASATI platform, a Technology Acceptance Model (TAM) will be applied.Technology Acceptance Model is one of the most famous theories that is used widely to explain the usage of information systems.TAM is majorly describing, estimating, and understanding the acceptance of the use of the system to predict its acceptability and help to identify the changes that need to be made or users' approval [1].In this research, we will cover the impact of COVID-19 in the primary education sector in Saudi Arabia and how the technology has been utilized during the social distance.The research will be conducted through questionnaires and observations and later opinions from teachers and parents which will be acquired for studying the Challenges and opportunities towards in MADRASATI platform.The main focus of this study is to apply the technology acceptance model (TAM) on Madrasiti application to identify the use and acceptance of computer technology using empirical data collected from Madrasiti users.
INTEGRATED TECHNIQUE SEARCHING CAUSES OF QUALITY INCOMPATIBILITIES

Achieving the expectation quality products level is possible among others, by using adequate management techniques, which allow or identify incompatibilities, its sources, and above all, the reasons for its occurrence and ways of its elimination.Applying in this aim singe technique is common, but it was turned out that a lack is integrated connection between selected techniques.The purpose of the study is to propose a technique consisting of cyclical use: brainstorming (BM), relationship diagram, cause and effect diagram, multiple voting, and the AHP method.The technique was verified in the nondestructive testing process.The analysis was performed for often occurring incompatibilities in mechanical sealers for 410 steel.The identified incompatibilities of the analyzed mechanical sealers were the most frequent porosity, which was identified by fluorescent method (FPI).The effectiveness of the proposed technique was shown.The main advantage of its use was to improve the process of decision-making referred to incompatibility causes.It is possible to effectively use this method to analyze another type of incompatibility and products in production and service enterprises.
Virtual Reality Experience In Indonesian Tourism

The shift in the pattern of the tourism industry is inseparable from technological developments. In recent times, a concept known as virtual reality has developed in the tourism sector. The purpose of this study is to determine the antecedents of tourist experience satisfaction, which in turn will shape tourist attitudes. The author explores further the relationship of each variable studied using the Stimulus Organism Response (SOR) framework. The method used in this research is experimental. Respondents were determined as many as 100 people with certain requirements. The data that has been collected is processed using SEM-PLS software. The results of the study stated that all the hypotheses tested were positive, but not all were significant. The author finds that tourist interactions with tourist destinations carried out in the realm of virtual reality are not sufficient to provide significant satisfaction. Another finding in this study shows that the experience satisfaction felt by tourists does not always encourage tourists' attitudes to visit tourist destinations.
International Standardization of Blockchain and Distributed Ledger Technology: Overlaps, Gaps and Challenges

As one of the most concerned digital technologies in recent years, blockchain and distributed ledger technology are an important driving force for a new round of technological development.It is currently in the process of accelerating its evolution and maturity, and has gradually integrated with other digital technologies.It has been applied in many industries, providing decentralized solutions for various industries, realizing innovative storage models, and building a new trust system.As blockchain technology is officially incorporated into China's new information infrastructure category, the application fields of blockchain have expanded rapidly, gradually extending from the financial field and government affairs to other fields in the real economy.At the same time, with the continuous development of the globalized economy, blockchain technology will also have a profound impact on international technological and economic development.Therefore, for the healthy and orderly development and real implementation of the blockchain industry, standardize the application of blockchain, effectively break through the cognitive and technical barriers between different countries, industries and systems on a global scale, prevent application risks, the development of the global blockchain industry needs standardization basis, which is particularly important and urgent.A sound standard system is an important key to the successful development of technology, and formulating the right standard at the right time for technology development helps ensure the ease of use and interoperability of the technology.From the perspective of international standardization, this article first introduces the general situation of ISO, ITU-T, IEEE, W3C and other international standardization organizations, and sorts out the status quo of the blockchain standardization working groups of mainstream international standardization organizations.All blockchain-related standards under development have been analyzed for the characteristics of international blockchain technology standards and industry application standards.Through data analysis, the overlaps, differences and conflicts in the field of international blockchain standard formulation are sorted out, and suggestions for blockchain standardization work in the application and development of blockchain technology standardization by international organizations and industries are put forward.The plans and layouts of future international standards are summarized to help the development of the international standardization of blockchain.