bluuebunny/crossref_metadata_2025 huggingface dataset:
Fatal Flaws in Voice Research and How to Avoid Them, Part Two: Qualitative Studies
Authors: Meyer David , Goss John R.
Published: February 2024

Abstract: This article is the second part of a two-part series examining so-called “fatal flaws” in voice science, with an emphasis on qualitative studies. This type of research looks for evidence to explore real-world phenomena, and asks questions like, “why?” or “I wonder what, or how?” The most common errors noted in qualitative studies include researchers’ overestimation of their expertise, failure to practice intellectual humility, failure to control for researcher bias, and privileging the “expert in the room” rather than participants’ perspectives. Interview protocols are examined, including a common method for ensuring trustworthiness called “member checking.” Recommendations for avoiding common errors in survey research, both qualitative and quantitative, are discussed.
Features of the relationship between accentuations of character and indicators of academic performance and attendance of high school students
Authors: Костарева К.Д.
Published: February 2024

В статье рассматривается проблема формирования акцентуаций характера у старшеклассников и их влияние на процессы обучения и воспитания. Авторы утверждают, что у некоторых школьников акцентуации характера могут иметь негативное влияние, а у некоторых - положительное влияние на школьную успеваемость. Взаимосвязь между акцентуациями характера и показателями школьной успеваемости может быть различной в зависимости от типа акцентуации и конкретных особенностей ученика. Отмечается, что негативные проявления акцентуаций характера могут оказывать отрицательное влияние на школьную успеваемость, а положительные проявления могут способствовать ее улучшению. В качестве предположения высказывается мысль, что хотя бы одна акцентуация характера может оказать специфическое влияние на возможности подростка обучаться и посещать занятия. Гипотеза исследования заключается в предположении, что существуют особенности взаимосвязи акцентуации характера и показателей успеваемости и посещаемости у обучающихся ГБПОУ «Пермского колледжа предпринимательства и сервиса». В исследовании были использованы методы: «Методика изучения акцентуаций личности К. Леонгарда», а также метод анализа документов. В результате исследования были установлены особенности взаимосвязи акцентуаций характера и показателей успешности при обучении и воспитании старшеклассников.

The article deals with the problem of the formation of character accentuations in high school students and their influence on the processes of education and upbringing. The authors argue that for some schoolchildren, character accentuations can have a negative impact, and for some, a positive impact on school performance. The relationship between character accentuations and indicators of school performance may be different depending on the type of accentuation and the specific characteristics of the student. It is noted that negative manifestations of character accentuations can have a negative impact on school performance, and positive manifestations can contribute to its improvement. As an assumption, it is suggested that at least one accentuation of character can have a specific impact on the ability of a teenager to study and attend classes. The hypothesis of the study lies in the assumption that there are features of the relationship between the accentuation of the nature and indicators of academic performance and attendance among students of the Perm College of Entrepreneurship and Service. The following methods were used in the study: "Methodology for studying personality accentuations of K. Leonhard", as well as the method of document analysis. As a result of the study, the features of the relationship between character accentuations and success rates in the education and upbringing of high school students were established.
Monitoring the quality of preschool education: experience in the region
Authors: Михалева О.С. , Колмогорова Т.В.
Published: February 2024

Оценка качества дошкольного образования является важным инструментом для повышения эффективности образовательного процесса и улучшения условий обучения дошкольников. В статье приводятся причины, по которым оценка качества дошкольного образования является важной. Одной их них выступает возможность оценить эффективность образовательного процесса, выявить его сильные и слабые стороны, а также определить области, требующие дополнительного развития. Рассматриваются основные объекты мониторинга качества дошкольного образования. Особый акцент в статье делается на Региональной концепции мониторинга по оценке механизмов управления качеством дошкольного образования в Республике Саха (Якутия). Основная цель Региональной концепции - обеспечение высокого качества образования в дошкольных учреждениях на территории региона. Региональная концепция мониторинга по оценке механизмов управления качеством дошкольного образования включает в себя методы и инструменты мониторинга, которые могут быть использованы для оценки качества дошкольного образования и управления им, такие как анкетирование, опросы, интервьюирование, наблюдение, анализ документов. В 2022 году в мониторинге по оценке механизмов управления качеством дошкольного образования в Республике Саха (Якутия) приняли участие 701 дошкольное образовательное учреждение. В статье описаны выявленные благополучные и проблемные зоны образовательной среды, приведены выводы по результатам исследования.

Assessment of the quality of preschool education is an important tool for improving the efficiency of the educational process and improving the learning environment for preschoolers. The article gives reasons why the assessment of the quality of preschool education is important. One of them is the opportunity to evaluate the effectiveness of the educational process, identify its strengths and weaknesses, and identify areas that require additional development. The main objects of monitoring the quality of preschool education are considered. Particular emphasis in the article is placed on the Regional monitoring concept for assessing the mechanisms for managing the quality of preschool education in the Republic of Sakha (Yakutia). The main goal of the Regional Concept is to ensure the high quality of education in preschool institutions in the region. The regional monitoring concept for evaluating the quality management mechanisms of preschool education includes monitoring methods and tools that can be used to assess the quality of preschool education and manage it, such as questionnaires, surveys, interviews, observation, document analysis. In 2022, 701 preschool educational institutions took part in the monitoring to assess the quality management mechanisms of preschool education in the Republic of Sakha (Yakutia). The article describes the identified prosperous and problematic areas of the educational environment, and draws conclusions based on the results of the study.
Methods of working with the body in the system of classes of the theater group
Authors: Андреева Н.П. , Никифорова В.И.
Published: February 2024

В центре внимания статьи находится проблема физического воспитания актеров современного драматического театра, участников театральных студий, студентов профильных ВУЗов. Занятия по сценическому движению помогают участникам театрального коллектива развивать коммуникативные навыки и умение работать в команде, что является важным для успешной работы в театральном коллективе. Определены преимущества техник работы с телом в системе занятий в театральном коллективе среди которых: повышение качества актерской игры, развитие творческого мышления и умение находить нестандартные решения. Рассматриваются традиционные и инновационные методики работы с телом. Отмечается, что программа развития пластики тела в детской студии направлена на развитие физических, эмоциональных и творческих способностей детей через работу с телом. Приводятся элементы программы развития пластики тела в детской театральной студии как основной элемент подготовки будущего актера. Особой проблемой является процесс формирования выразительности движения. Уточняется, что действие и движения как основные элементы работы с телом и пластикой становятся формой передачи эмоций и информации.

The focus of the article is the problem of physical education of actors of the modern drama theater, participants in theater studios, students of specialized universities. Stage movement classes help members of the theater team develop communication skills and the ability to work in a team, which is important for successful work in a theater team. The advantages of working with the body techniques in the system of classes in the theater group are determined, among which are: improving the quality of acting, developing creative thinking and the ability to find non-standard solutions. Traditional and innovative methods of working with the body are considered. It is noted that the program for the development of body plastics in the children's studio is aimed at developing the physical, emotional and creative abilities of children through work with the body. The elements of the program for the development of body plasticity in the children's theater studio are given as the main element in the preparation of the future actor. A special problem is the process of forming the expressiveness of movement. It is clarified that action and movements, as the main elements of work with the body and plasticity, become a form of transferring emotions and information.
Continuity of generational experience in analysing the meaningful context of education
Authors: Грохольская О.Г.
Published: February 2024

В статье актуализируется смысловой контекст проблем сближения поколений, который обусловлен социокультурной динамикой, конфликтами между поколениями, изменением ценностных систем и факторов, которые на это влияют. В статье выделены риски, связанные с глобальной трансформацией мирового сообщества, приводящие к разрушению механизма преемственности опыта поколений. Уточнено, что одним из рисков выступает снижение требований к уровню образованности личности, который может иметь ряд негативных последствий: ограничение потенциала личности, увеличение неравенства в обществе, ухудшение экономических перспектив. В контексте размышлений о смысловом контексте сближения поколений, составляющими которого являются воспитание патриотизма, вера в справедливость и светлое начало, формирование установки на созидательный труд, уважение к семейным традициям, почитание многовековой народной мудрости, автором обозначен методологический инструментарий обновления образования. Особо отмечается важность восстановления механизма преемственности, передачи знаний и опыта через взаимодействие поколений, преодоление разрыва в понимании молодежью собственных целей развития и ключевых жизненных стратегий. Обозначена необходимость расширенного понимания процесса воспитания, результатом которого станет разработка новых подходов к определению возможностей саморазвития и самореализации личности.

The article actualizes the semantic context of the problems of rapprochement of generations, which is conditioned by socio-cultural dynamics, conflicts between generations, changes in value systems and factors that affect it. The article highlights the risks associated with the global transformation of the world community, leading to the destruction of the mechanism of continuity of generational experience. It is specified that one of the risks is the reduction of requirements to the level of education of a person, which can have a number of negative consequences: limitation of personal potential, increase of inequality in society, deterioration of economic prospects. In the context of thinking about the meaningful context of the rapprochement of generations, the components of which are the education of patriotism, faith in justice and a bright beginning, the formation of the attitude to creative work, respect for family traditions, reverence for centuries-old folk wisdom, the author outlines the methodological tools for the renewal of education. The author emphasizes the importance of restoring the mechanism of continuity, transfer of knowledge and experience through the interaction of generations, overcoming the gap in the understanding of young people's own development goals and key life strategies. The need for an expanded understanding of the process of upbringing, the result of which will be the development of new approaches to identifying opportunities for self-development and self-realization of the individual is highlighted.
Implementasi Media Boneka Tangan Pada Pembelajaran Bahasa Inggris
Authors: Susilowati Retno , Sophya Ida Vera
Published: February 2024

Boneka tangan karena ukurannya lebih besar dari boneka jari dan bisa dimasukkan ke tangan. Berdasarkan hasil penelitian peneliti berkesimpulan Peran guru mata pelajaran bahasa inggris dalam membuat media boneka tangan sangat penting. Boneka tangan digunakan sebagai media pembelajaran sehingga bisa memotivasi siswa untuk belajar bahasa Inggris. langkah-langkah yang dilakukan oleh guru dalam mengajar bahasa Inggris dengan menggunakan media boneka tangan adalah dengan story telling misalnya tema binatang. tema ini siswa bisa mengenal ciri-ciri binatang sesuai dengan boneka tangan yang ada. Diawal pembelajaran, guru memberi contoh cara mempraktekan secara langsung dan bercerita menggunakan bahasa Inggris. Faktor pendukung adalah peran aktif guru. Selain tugas guru sebagai pengajar, guru harus bisa menjadi fasilitator. Faktor penghambat siswa yang kurang aktif dalam berkomunikasi. Sedangkan faktor penghambat dalam implementasi penggunaan boneka tangan pada pembelajaran bahasa Inggris mengakibatkan siswa susah dalam berkomunikasi.
Science Development Trends with the Metaphor of the Tree of Science State Islamic University of Maulana Malik Ibrahim Malang
Authors: Khoiriyah Siti , Fuad Ah Zakki , Bakar M Yunus Abu
Published: February 2024

This study aims to identify and analyze trends in science development using the metaphor of "Tree of Science" within Maulana Malik Ibrahim State Islamic University Malang (UIN Malang). This metaphor is used as a conceptual framework to understand the development of various disciplines at the university. This research uses content analysis methods against official documents, such as university development plans, curricula, and scientific publications related to academic programs. The results showed that UIN Malang has adopted and developed the metaphor of "Tree of Science" as a strategic foundation in the development of science. There are three trends in the development of science at UIN Malang including: 1) using the integrative curriculum model of ma'had al-Jami'ah. 2) through the Arabic and English Language Development Program. 3) Through character education based on ulul albab.
Improving Problem Solving Skills through Problem Based Learning (PBL) for Students at SMAN 1 Jogorogo
Authors: Rini Agustina Fajar , Murtafiah Wasilatul , Setyowati Rini
Published: February 2024

The implementation of the “Merdeka” curriculum requires students to have high-level thinking skills such as problem-solving skills. However, in reality, this is in contrast to the students’ability in solving the real problem. The purpose of this study is to describe the effect of the Problem Based Learning (PBL) model in improving students' problem-solving skills. The Problem Based Learning is a learning model that syntaxes on the problem-solving process, so that students are able to provide solutions and familiarize themselves with the skills of problems analysis, collaboration, communication, creativity and critical thinking. Problem solving indicators that will be measured are connecting information/data to understand the problem, evaluating alternative problem solving presented, and making a design to solve the problem. This research is a Classroom Action Research (CAR) which took place in SMAN 1 Jogorogo with the subject of tenth grade (XA) students totaling 40 on the material of environmental change. The data were collected through observation, written test Daily Test (DT) and documentation which were then analyzed through comparing the average results of each indicator. The results showed that the initial data regarding the indicator of connecting information/data to understand the problem was 76.8%, increased in the first cycle to 82.2%, and in the second cycle to 86.25%. The indicator of evaluating alternative problem-solving initial data was 77.5%, increased in the first cycle to 85% and the second cycle to 87.5%. The indicator of making a design to solve the problem in the initial data was 80% and increased to 82.5% in the first cycle and 85% in the second cycle. From the various explanations above, it shows students’ problem solving skills has increased as seen from the Daily Test (DT) scores. Keywords: Problem Based Learning (PBL), problem solving, Classroom Action Research (PTK). Environmental Change.
The Implementation of Amtsilati Learning Method to Improve the Ability of Reading Kitab Kuning in the Amtsilati Class Group at Bustanu 'Usyyaqil Qur'an Elementary School Betengan Demak
Authors: Musawamah Mualamatul
Published: February 2024

The aim of this study is to reveal the implementation of Amtsilati learning method in improving the ability of reading Kitab Kuning in the Amtsilati group class at Bustanu 'Usysyaqil Qur'an Betengan Demak Elementary School. This research used a qualitative approach with data collection techniques using interview, observation and documentation. The results showed that the implementation of the Amstilati learning method at SD BUQ Demak included: learning planning, including: objectives, methods, materials, media, evaluation. teaching preparation, preliminary activities, core activities, closing activities. While the learning process in practical classes in improving the ability to read Kitab Kuning is carried out by conducting tests with very good results. Evaluation of learning includes: daily evaluation, volume increase evaluation, midterm evaluation, end of semester evaluation. While the evaluation for practical classes is carried out mid-semester daily and written and oral tests that have met the KKM.
Madrasah Tsanawiyah Strategy Based on Islamic Boarding Schools Implementing Religious Moderation Values in Blora Regency
Authors: Partono Partono , Falah Ahmad
Published: February 2024

This research describes and analyzes the habituation of religious moderation values in the learning of Islamic Religious Education during the pandemic study of madrasah tsanawiyah based on Islamic boarding schools in Blora district with a research focus on how the forms, processes, and strategies of habituation of religious moderation values in PAI learning, and what are the implications for student. This research is a qualitative research using postpositivism paradigm. This type of research uses case studies, data collection uses three methods, namely: interviews, observation, and documentation. The data analysis techniques in this study used the stages of data reduction, data presentation, and drawing conclusions. The results of this study indicate that: (1) the form of habituation of the moderation value of religion in PAI learning during the pandemic during the pesantren-based madrasah studies in Blora district was carried out in the form of: through Islamic learning activities in the classroom and through religious activities. The values of religious moderation that are habituated in PAI learning are the values of justice (a'dalah), balance (tawazun), and tolerance (tasamuh). (2) The habituation process of religious moderation values in PAI learning during the pandemic during the pesantren-based madrasah tsanawiyah study in Bloradi district was carried out through: the stages of value transformation, the stages of value transactions, and the stages of value transhabituation. (3) The strategy used to habituate the value of religious moderation in Islamic Religious Education learning during the pandemic during the pesantren-based madrasah tsanawiyah study in Blora district, namely: introduction, habituation, example, and practice. (4) The implications of habituation of the value of religious moderation on the social attitudes of students during the pandemic during the Islamic boarding school-based madrasah studies in Blora district, namely being accustomed to worship, respecting teachers and friends, social care, tolerance, discipline, responsiveness to the environment, and obedience to regulations
The Implementation of School Administrative Management in State Madrasah Tsanawiyah 4 Sragen
Authors: Abbas Ngatmin , Suryanto Lilis , Fatimah Meti , Suparman Fatah
Published: February 2024

This study aims to analyze the implementation of administrative management at MTs Negeri 4 Sragen, with a focus on human resources management, financial management, curriculum management, facilities and infrastructure, as well as extracurricular programs. Document analysis is used to collect data from documents related to administrative management at MTs Negeri 4 Sragen. The research subjects are the headmaster, teachers, and administrative staff involved in the implementation process. The data sources used are documents related to administrative management, such as handbooks, financial reports, and school policies. Data collection techniques include document analysis and interviews. Descriptive analysis is employed to analyze the data. The results show that the implementation of administrative management at MTs Negeri 4 Sragen is carried out in a structured and systematic manner. The quality of human resources, government policies, and organizational culture influence the success of administrative management implementation. Training and socialization, facilities provision, and the use of information technology are efforts made to overcome obstacles in the implementation process. Monitoring and evaluation are conducted periodically to assess the success of administrative management implementation and identify improvements needed in the future. In conclusion, the implementation of administrative management at MTs Negeri 4 Sragen has been successfully carried out well-structured, with efforts to overcome challenges that arise during the implementation process.
Motivation Levels and Affecting Factors In Students Enrolling In Surgical Diseases Nursing Course During The Pandemic
Authors: Yavuz Karamanoğlu Ayla , Gök Özer Fadime , Yeşilyaprak Tuğçe
Published: February 2024

Introduction: Motivation plays a key role in adaptation of nursing students to their education programs. Many factors affect motivation. One of those factors appearing recently is the COVID-19 pandemic. However, the effect of the pandemic on motivation levels of nursing students is unclear.
Methods: The study has a descriptive and cross-sectional design. The study was carried out in a nursing department at a university in Turkey. The study sample included 145 students enrolling in Surgical Diseases Nursing Course during the spring term of the 2020-2021 academic year. A sociodemographic data form and Motivation’s Resources and Problems Scale were used for data collection.
Results: The mean scores of the students on Motivation’s Resources and Problems Scale and its subscales intrinsic motivation, extrinsic motivation and negative motivation were 90.84±11.35, 43.59±6.67, 21.50±2.61 and 25.75±5.66 respectively. Intrinsic motivation and extrinsic motivation of the students had a positive relation with their perceived nursing profession during the pandemic.
Conclusions: Students’ feeling afraid and worried during the caregiving process in the COVID-19 pandemic increased their motivation. Their perceptions about nursing during the pandemic also increased their motivation levels.
Advanced Time Series Forecasting Models for Electricity Demand Prediction: A Comparative Study
Authors:   Faculty of Computers and Information, Mansoura University, Egypt, Hamsa Hamsa ,   Faculty of Computers and Information, Mansoura University, Egypt,   Faculty of Computers and Information, Mansoura University, Egypt, Asem Aziza , El-Bakry Hazem El
Published: February 2024

Electrical loading prediction is a key aspect of the power system governing, operating, and scheduling. Energy suppliers can control the running system cost by using a lot of information it provides thereby optimizing the power system operation performance. The demand for the electricity well forcasted means more than half of their energy efficiency. Implementation of this work traces out an in-depth detail of integrated quality time series forecasting models on the prediction of electrical consumption. The primary goal of the study is to assess the performance of two state-of-the-art forecasting models: Deep LSTM version and long short-term memory (LSTM) neural networks, Seasonal autoregressive integrated ma. The main task is to evaluate the models’ precision in predicting daily energy consumption based on the historical demand data, holiday data and other time-related lines of evidence. The performance of the models is assessed based on the Mean Absolute Percentage Error (MAPE). The method covers feature engineering, the data preparation, model selection, and assessment. The generated MAPE values illuminated the performance of the models— SARIMA performed relatively inaccurately, and LSTM and deep LSTM significantly improved, obtaining a very good MAPEs of 7.5% and 7.45%, respectively. Notably, the deep LSTM version shows a superiority in prediction compared to other models, with particular emphasis on capturing the temporal relationships. This study makes a great contribution to the field of energy forecasting as it shows applicability of LSTM- and SARIMA- based models for the very good forecast of the consumption power. It captures the attention on how the LSTM networks at 20% of depth; may help in improving prediction accuracy when there are complex patterns and long-distance dependence is a concern. To utility companies, the grid operators and lawmakers who are out to harness every energy resource, to cut the costs, and ensure a continuous flow of electricity; such results are so very helpful.
Application of artificial intelligence and machine learning in financial forecasting and trading
Authors: Zhu Guanyu
Published: February 2024

Artificial Intelligence (AI) and Machine Learning (ML) have been employed in the field of financial forecasting for many years. Existing scientific research has substantiated the effectiveness of AI/ML in the financial market. Currently, approximately 35% of the total capitalization of the US stock market is influenced by quantitative analysis, primarily consisting of AI/ML methodologies and their variants. This paper reviews classical advanced methodologies of AI/ML in financial forecasting and automated trading. Specifically, it focuses on discussing representative methods from three categories: statistical approach (including ARIMA-GARCH), machine learning approach (including SVM and LSTM), and the logistic approach (including the Fuzzy System). In detail, this paper delves into the fundamental aspects of each method and illustrates their effectiveness through existing results from relevant papers. The structure of this paper begins with the introduction of each method, followed by their applications, and a discussion of their pros and cons. Furthermore, this paper offers an outlook on the hotspots and prospects for the development of this research topic.
Conversational agent in HCI a review
Authors: Zhao Yixuan , Lin Tianbo , Wang Yize
Published: February 2024

Nowadays, AI technology is developing rapidly and slowly covering all areas of life. AI facilitates different parts of our lives and provides us with a lot of help. For example, in learning, students can acquire knowledge more conveniently through AI, and buyers can find suitable goods more conveniently through AI when shopping. At the same time, more and more technology is used in the field of voice agents, which allows humans to enjoy a lot of better services. In this article, we will study to better understand "how to understand human natural language and how the repository of knowledge is built." In the article we build with examples and deep learning models (CNN and RNN) through databases. Through repeated research and analysis, we can find that there are some limitations in this paper, such as the single learning model and the insufficient elaboration of data analysis and signal system technology. But at the same time, we also found a lot of future application prospects that voice agents can develop, it can be applied in many fields, such as finance, medical care, education and so on. For example, in children's education, parents can use voice agents to set time limits and monitor their children's progress. Existing digital interactive storytelling systems have limitations in terms of available storybooks and hand-crafted issues. Voice agents are becoming more popular in everyday scenarios, and more users are adopting devices like Siri and Google Assistant. In the future, conversational agents are expected to play an important role in oral communication with users.
Breast cancer classification based on hybrid machine learning model
Authors: Lin Zhe
Published: February 2024

This study proposes a hybrid model that combines K-Means clustering and Random Forest classification as an approach for breast cancer classification. The objective is to exploit the advantages of unsupervised clustering and supervised classification techniques to enhance the accuracy and robustness of classification models. The dataset underwent preprocessing procedures encompassing the handling of missing values, feature normalization, and feature selection. Missing values were addressed through appropriate methods, and features were scaled and selected based on variance threshold or correlation analysis. Subsequently, K-Means clustering was applied to the preprocessed data to assign cluster labels to each sample. The study then proceeded to train a Random Forest classifier by incorporating both the cluster labels and the raw gene eigenvalues as mixed features. This integration of gene expression values and cluster labels provides supplementary information to the classifier, enabling the capture of more intricate patterns within the data. The Random Forest classifier was trained using optimized parameters determined through parameter tuning, including the number of trees, maximum depth, and minimum number of split samples. Extensive experiments and evaluations conducted in this study revealed that the hybrid model outperformed the standalone Random Forest classification. The incorporation of K-Means clustering facilitated the discovery of underlying data structures and patterns, ultimately enhancing the classifier's discriminatory ability. The hybrid model exhibited superior accuracy, precision, recall, and F1 scores, demonstrating its efficacy in accurately classifying breast cancer samples.
The metamorphosis of machine translation: The rise of neural machine translation and its challenges
Authors: Chen Yuduo
Published: February 2024

Machine translation refers to the process of using computers to translate source language into target language, which has undergone significant transformations since its inception, with the current mainstream neural machine translation achieving satisfactory translation performance. This paper overviews the three developmental stages of machine translation: rule-based machine translation, statistical machine translation, and neural machine translation, with a focus on neural machine translation. It introduces the key models that emerged in the development process of neural machine translation, namely the recurrent neural network encoder-decoder model, recurrent neural network search model, and Transformer, and compares their strengths and limitations. Other relevant technologies and models developed alongside neural machine translation are also discussed. Addressing the current challenges of neural machine translation, the paper delves into issues of overfitting, low-resource translation, structural optimization of Transformer models, and enhancement of neural machine translation interpretability. Finally, the paper explores the prospects of applying neural machine translation to multimodal translation.
Current study on interaction design in automotive intelligent cockpit
Authors: Tian Kean
Published: February 2024

In recent years, with the rapid development of Internet communication digital technology represented by artificial intelligence, Internet of Things, big data, the human-computer interaction of automobiles has also been further developed, showing a new look. As the main part of automotive interaction design, the digital, intelligent and Internet-oriented characteristics of intelligent cockpit are becoming increasingly obvious, especially in recent years, the intelligent cockpit design of new energy vehicles has broken the traditional interaction mode of automobile cockpit in the era of industrial machinery, and more intelligent and immersive interaction design is adopted. And the cockpit of the car not only has a single function for driving, but also provides a space for leisure and entertainment for the driver. Key technologies and design cases of cockpits and its interaction design were sorted out and summarized, and then the problems that cockpits interaction design faces and its future development were analyzed in this paper.
Model-based reinforcement learning for service mesh fault resiliency in a web application-level
Authors: Meng Fanfei , Jagadeesan Lalita , Thottan Marina
Published: February 2024

Microservice-based architectures enable different aspects of applications to be created and updated independently, even after deployment. Associated technologies such as service mesh provide fault resiliency through attribute configurations that govern self-adaptive application-level behavior in response to failures, in a manner transparent to the application and constituent microservices. While this provides tremendous flexibility, the configured values of these attributes and the relationships among them can significantly affect the performance and fault resilience of the overall application. It is thus important to perform fault injection and load testing on the application, prior to full deployment. However, given a large number of possible attribute combinations and the complexities of the distributed system underlying microservices and service mesh architectures, it is virtually impossible to determine through traditional software development practices the worst combinations of attribute values and load settings with respect to self-adaptive application-level fault resiliency. To this end, we present a model-based reinforcement learning approach that determines the combinations of attribute and load settings that result in the most significant fault resilience behaviors at an application level. We validate our approach through a case study on a simple request-response service using the Istio service mesh. Our analysis shows that, even for a simple service, our model-based reinforcement learning approach outperforms a baseline selection of action parameters. Further, we show that communicative multi-agent reinforcement learning improves the performance of both the non-communicative single and multi-agent learning paradigms.
Automated arduino robot design with multi-level natural language processing chains
Authors: Zhang Shengqi
Published: February 2024

This research explores the potential of leveraging OpenAIs GPT-3.5-Turbo API for automating Arduino robot design through a structured multi-level language processing chain termed LangChain. The system breaks down the design process into six stages, from preliminary design sketching to failure analysis. Each stage generates robot design components using user inputs, progressively building upon the previous outputs. The results highlight the models capabilities in generating functional preliminary designs, suggesting hardware and software components, and offering assembly instructions. While demonstrating a commendable level of technical knowledge, the system requires further refinement in numerical analysis and design reviews. This approach provides a foundational framework for bridging the knowledge gap between amateurs and professionals in robotic design.
The design of relational database and NoSQL database in travel agency database system
Authors: Xu Chenxi
Published: February 2024

The information management systems of travel companies are experiencing greater challenges and expectations as a result of the tourism industrys rapid growth and travellers rising demand for personalized and interactive experiences. This paper aims to study the customer management system of travel agencies, taking into full consideration the characteristics and development trends of the tourism industry. Traditional customer management system uses relational database for data storage and related operations, which cannot fully meet the needs of customers and complex data in the new era. By analysing and comparing relational databases and NoSQL databases, according to their own advantages, a combined solution is proposed, which uses relational databases to store structured data and NoSQL databases to store unstructured data. On the basis of maintaining the original system management function, this solution greatly enhances the storage and processing of interactive data such as images and videos, and better meets the new demand of travel agency customers for sharing and interactive communication.
Research on challenges and solutions in 5G application
Authors: Yu Jingzuo
Published: February 2024

5G technology is a new type of wireless communication technology with the characteristics of high speed, low delay, large connection, etc. It brings new opportunities and challenges to economic, social and industrial development. This article focuses on the application and value of 5G technology in smart cities, as well as the opportunities and challenges faced by 5G technology in smart cities. This article uses the method of literature reading and analysis to explore the role and functions of 5G technology in smart cities from the fields of smart homes, smart transportation, smart grids, smart security, etc. and analyzes the application scenarios and cases of 5G technology in smart cities, demonstrating the practical effects and social benefits of 5G technology in smart cities. This article evaluates the opportunities and challenges faced by 5G technology in smart cities, such as policy support, network construction, security, user needs, etc., and provides strategic suggestions for the promotion and application of 5G technology in smart cities. This article aims to improve the knowledge and understanding of 5G technology and smart cities, promote the coordinated development of 5G technology and smart cities, and provide technical support and innovation power for building a new digital, networked, and intelligent city.
Research on the application of personalized recommendation
Authors: Han Yichu
Published: February 2024

With the development of the Internet, people have more opportunities to be exposed to personalized recommendations, and the heat of related topics has increased. The purpose of this paper is to summarize the application principle and use of personalized recommendations by analyzing the relevant data, so that people can have a better understanding of personalized recommendations and make preparations for future related research. This paper first introduces the general development context of the personalized recommendation system and its uniqueness. The analysis finds that personalized recommendations can provide users with the most relevant and valuable information, goods, or services according to their interests, preferences, and behaviors. Secondly, this paper explores the application scenarios of personalized recommendation systems in different fields, including but not limited to video content, e-commerce, and online learning. In addition, this paper also lists the application of YouTube and Netflix in video content recommendation, as well as personalized recommendation services in e-commerce and online learning platforms. In particular, the rise of intelligent adaptive online learning systems and their adaptability in the field of education and training are analyzed in detail. Through this research, it can be found that a personalized recommendation system is very beneficial to people's production and life, but at present, personalized recommendation is still in the development stage, and there are many problems to be solved.
The development and application of autonomous driving technology
Authors: Liu Jiaming
Published: February 2024

Autonomous driving technology is emerging as a prominent subject within the realm of modern technology. This technology is increasingly being applied to daily life and is seen as an innovative technology with enormous potential. The application of autonomous driving technology has expanded but still faces issues such as immature technology, incomplete laws, and low user acceptance. The objective of this paper is to comprehensively examine the developmental trajectory, application domains, and obstacles faced by this technology, as well as to anticipate its prospects. To that end, this paper initially provides an overview of the background and relevant concepts pertaining to autonomous driving technology. Subsequently, the developmental history of autonomous driving technology, along with its current application domains, is analyzed. Moreover, the challenges encompassing technical, legal, and ethical aspects of autonomous driving technology are thoroughly explored. Lastly, this paper offers prognostications regarding the future progress of autonomous driving technology, as well as furnishes recommendations for advancing its implementation. It is found that although the research on autonomous driving has been very popular in the past few years, there is still a lack of research on the application and challenges of autonomous driving technology in some fields. Therefore, this paper summarizes the application in different fields, hoping to propose a general direction for the application of autonomous driving in the future.
A review on neuromorphic computing circuits
Authors: Jin Chen
Published: February 2024

Computational power is measured in terms of the time required for resolutions. The faster, the better. Due to its physical implementation, the conventional computing device used currently in computers is reaching its limit in computational power, and an essential innovation is required in order to break this limit. Neuromorphic circuits, which is inspired by neurology and simulates human biological brain and have higher functional efficiency to consume less energy and perform highly complicated tasks, is introduced and developed. This paper explains the principles of neuromorphic computing, which is representing ions in the biological neural system with electron in the circuit and adopting capacitors and resistors as counterparts of cellular membranes of the neural cells and the ion channel respectively. This paper gives some examples of neuromorphic circuits developed by several different corporations and laboratories. Algorithms mentioned in a certain research is exemplified and explained. Comparison of the difference between conventional and neuromorphic circuits is given to emphasize the advantage of neuromorphic circuits over the conventional ones. Several possible applications in a range of fields are also provided to depict the future prospect of this technology, including artificial intelligence, statistical calculation and information analysis. The conclusion is that the neuromorphic computers will replace the conventional Von Neumann computers, boosting the further development in computing power, breaking its limit.
Gameful interaction: How principles of game design can be applied to enhance user experiences in non-game applications
Authors: Zhi Xiaotong
Published: February 2024

In the era of digital transformation, the integration of game design and interaction design has become an important trend, and its scope of application has gone beyond purely entertaining applications. This thesis investigates the principles of gamified interaction with a focus on how game design elements can be utilized to enhance the user experience in non-game applications. The research objective of this thesis is to investigate the effectiveness and limitations of gamification design in a variety of contexts when incorporating it into educational, business, health, and other types of applications. The study employs a mixed research methodology, which includes analysis and comparison of the literature, as well as a specific case study of the Chinese fitness app "Keep" to demonstrate real-world applications. The data for this study came from existing academic papers, app analysis, user feedback and design evaluation. This thesis finds that gamified interactions have a significant impact on user engagement and motivation, providing valuable insights for designers to create more engaging digital environments.
Transformers: Statistical interpretation, architectures and applications
Authors: Meng Fanfei , Wang Yuxin
Published: February 2024

Transformers have been widely recognized as powerful tools to analyze multiple tasks due to its state-of art multi-head attention spaces, such as Natural Language Processing (NLP), Computer Vision (CV) and Speech Recognition (SR). Inspired by its abundant designs and strong functions on analyzing input data, we would like to start from the various architectures, further proceed to the investigation on its statistical mechanism and inference and then introduce its applications on dominant tasks. The underlying statistical mechanisms arouse our interests and intrigue us to investigate it in a higher level, and this surveys will focus on its mathematical foundations and then use the principles to try to analyze the reasons for its excellent performance on many recognition scenarios.
Improvement of post BER performance in computer communication on Viterbi algorithm
Authors: Li Bowen
Published: February 2024

Computer communication is the pivotal exchange of information and data among computing devices, exerting substantial influence over network communication quality. The conventional approach has typically centred on enhancing Bit Error Rate (BER) performance to bolster information quality during the transmission process. However, our research pioneers a novel strategy, focusing on post-BER improvement. Our innovative method prioritizes enhancing information quality at the receiver's end by implementing a unique approach. We employ the Viterbi algorithm to elevate the quality of individual words, ensuring accurate word recognition and precise comprehension. The ultimate goal is to provide end-users with an unambiguous and accurate understanding of transmitted words. Our simulation results conclusively demonstrate the effectiveness of this approach. Following the reception of words, we successfully attain the correct word information with remarkable accuracy. This approach transforms word-level information processing, safeguarding against inaccuracies and ambiguities that may otherwise compromise the integrity of data transfer. In summary, our research introduces a paradigm shift in optimizing information quality within computer communication networks. By focusing on post-BER improvements and harnessing the power of the Viterbi algorithm, we enable the receiver to decode words with precision and clarity. This breakthrough promises to enhance the overall quality and reliability of information exchange, further solidifying the foundation of modern computer communication.