bluuebunny/crossref_metadata_2025 huggingface dataset:
Efektifitas Pemberian Terapi Essensial Oil Lemon, Jahe dan Peppermint terhadap Penurunan Ketidaknyamanan Ibu Hamil dengan Emesis Gravidarum
Authors: Sumiyati Sumiyati
Published: July 2024

Introduction: Discomfort in the first trimester of pregnancy is often experienced, one of which is nausea and vomiting, nausea, and vomiting frequently occur due to several causes, including hormonal changes in the body such as an increase in estrogen and HcG hormones. In this condition, treatment can be done by pharmacological or nonpharmacological means. Pharmacological therapy will have side effects on the condition of the mother and fetus. Providing artificial substances (unnatural) has implications for the poor health of the fetus, this is because the fetus is still vulnerable to environmental threats, especially drugs given to pregnant women, which can also enter the fetal body through the placenta and potentially affect the baby's body system.
Objectives: This study aims to determine the effectiveness of giving essential therapy oils lemon, ginger, and peppermint to reduce the discomfort of pregnant women with emesis gravidarum in Hospital H
Method: This type of research is a quasi-experimental non-equivalent control group design, The population taken is first-trimester pregnant women who experience emesis gravidarum and make antenatal visits at H Hospital in March 2022 and samples are taken from a total of 40 respondents. Data collection was carried out directly using questionnaires. Data analysis used the chi-square statistical test
Result: Chi-Square statistical test results obtained results that there is an effect of Essential Oil Lemon, Ginger and Peppermint on reducing emesis gravidarum (p-value = 0.007)
Conclusion: The results of the research conducted by the author show that there is effectiveness of Lemon, Ginger, and Peppermint Essential Oil therapy against the insecurity of First Trimester Emesis Gravidarum at Hospital H in 2022.
Nine years on from the Serious Crime Act 2015: Reflections on hopes, fears, progress and challenges around coercive control within a legislative framework, and on the importance of a feminist analysis of domestic abuse… in conversation with Polly Neate
Authors: Bytheway Siouxsie
Published: July 2024

Polly Neate is the CEO of Shelter, the housing and homelessness charity, and was previously the CEO of Women’s Aid from 2013 to 2017. Under her leadership Women’s Aid campaigned for, and helped bring legislation criminalising coercive and controlling behaviours in intimate and family relationships into law in England and Wales with The Serious Crime Act 2015. She has sat on several panels advising on domestic abuse in the UK, and is a regular commentator on women’s rights and social justice issues.
English Teachers’ Challenges and Method in Building Learners’ Speaking Skills During Merdeka Curriculum in Junior High School
Authors: Ningsih Ina Wahyu Priyanti , Ahmad Tauchid Ahmad , Eka Nanin Verina Widya Putri
Published: July 2024

This research is based on the problems teachers have faced. where teachers must be able to create a more effective and active learning atmosphere. In the independent curriculum, the teacher is a facilitator who helps students to achieve learning goals. In this case, a learning strategy is very necessary to support learning achievement. The urgency of this research raises existing problems at this school this problem will be followed up later That. the main aim of this research is to explain the method used in special learning for teaching English with the Merdeka curriculum in junior high schools and also the challenges as an English teacher in the Merdeka curriculum. This research will utilize descriptive qualitative research. This research will later be carried out at one of the junior high schools in Bojonegoro in the 2023-2024 academic years. In this research, the researcher will use observation, an interview instrument to collect the data. In this research, the researcher will analyze the data using three concurrent flows including data reduction, data display, and drawing conclusion/verification. the result of previous chapter, there are six challenges faced by teachers, namely method do teachers, mother tongue, motivation, lack of vocabulary, facilities, learning material. All of these challenges have been overcome well, namely by providing vocabulary since sitting in the seventh grade class, then providing student motivation during learning, using strategy group discussions to develop interaction between friends. In learning, of course, it is not always as expected, there are many obstacles faced by teachers. By providing motivation when learning, it is hoped that students will be able to be more active in studying
Hubungan Kepribadian Guru PAK dengan Karakter Peserta Didik
Authors: Zebua Afolo , Saragih Nova Yulita , Sadarita Andi , Situmorang Maston
Published: July 2024

Personality is the identity of a person that can be expressed in general because it is a presentation of the mental color that is read and can be judged by others and even that personality can be assumed as a complete human appearance. A teacher with a teaching profession is required to have a good personality and by his personality, the teacher can function as a moral reformer for the students he teaches. One of the goals of writing this journal is so that through the personality shown by the teacher, it can become a good moral shaper for students. Because the personality of a person reflects the style and way to interact with other people and their environment. When a teacher deals with students, then the whole existence of his personality becomes the center of attention of students. Therefore, the teacher as the center of attention of students in their efforts to transfer knowledge, then all the rules of his personality must be accounted for. The research method in this journal is a quantitative approach method, finding whether there is a relationship between the teacher's personality and the morale of the students.Keywords: teacher personality, caracter AbstrakKepribadian adalah identitas dari seseorang yang dapat diekspresikan secara umum karena merupakan presentatif dari warna kejiawaan yang terbaca dan dapat dinilai oleh orang lain dan bahkan kepribadian itu bias diasumsikan sebagai penampakan manusia seutuhnya. Seorang guru dengan profesi sebagai pengajar dituntut untuk memiliki kepribadian baik dan oleh kepribadiannya itu, guru dapat berfungsi sebagai pembaharu moral bagi siswa yang diajarnya. Salah satu tujuan dari penulisan jurnal ini adalah, agar melalui kepribadian yang ditunjukkan oleh guru dapat menjadi pembentuk moral yang baik bagi siswa. Karena kepribadian dari seseorang mencerminkan gaya dan caranya untuk berinteraksi dengan orang lain dan lingkungannya. Ketika seorang guru berhadapan dengan siswa, maka seluruh keberadaan kepribadiannya menjadi pusat perhatian siswa. Oleh karena itu guru sebagai pusat perhatian siswa dalam usahanya mentransfer ilmu pengetahuan, maka seluruh kaidah-kaidah kepribadiannya harus dapat dipertanggungjawabkan. Adapaun metode penelitian dalam jurnal ini adalah metode pendekatan kuantitatif, menemukan apakah ada hubungan kepribadian guru dengan moral peserta didik.Kata Kunci: kepribadian guru,  karakter
Dampak Pemahaman Siswa tentang Pendidikan Agama Kristen menurut 2 Timotius 3:14-17 Terhadap Minat Belajar
Authors: Zebua Afolo , Barus Jamli , Sembiring Rasmalem Raya , Sinaga Resie VM , Turnip Genti
Published: July 2024

Interest in learning is influenced by external factors and internal factors. Interest in learning is motivated by intelligence, learning motivation, family environment and selected friends. Students' understanding of Christian religious education according to 2 Timothy 3:14-17 includes spirituality, namely holding the truth and knowing the scriptures and with behavior in terms of guiding life and doing good. The method used is quantitative research with survey methods. The research method used is a type of quantitative research with survey methods. The research was conducted on 40 respondents. As a result, the effect of students' understanding of Christian religious education according to 2 Timothy 3:14-17 on interest in learning is significant with a correlation value of 0.627 with a good category; and the contribution is 0.393 or 39.9%, and the linear regression equation Y = 29, 18 + 0.47 X is significant. Consistently increasing the role of parents to motivate their children; increasing the teacher's role in teaching students' understanding of Christian Religious Education seriously, and being careful in choosing friends will increase interest in learning. The more students understand about Christian religious education according to 2 Timothy 3:14-17, it will have an impact on increasing student interest in learning significantly.Keywords: impact, understanding, interest of learning AbstrakMinat belajar dipengaruhi oleh faktor eksternal dan internal. Minat belajar dipengaruhi oleh kecerdasan, motivasi belajar, lingkungan keluarga dan teman. Pemahaman siswa tentang pendidikan agama Kristen menurut 2 Timotius berkaitan dengan spiritualitas, yaitu berpegang pada kebenaran dan mengetahui kitab suci dan terkait dengan perilaku yaitu membimbing hidup dan berbuat baik. Metode penelitian yang digunakan adalah jenis penelitian kuantitatif dengan metode survey. Penelitian dilakukan terhadap 40 responden. Hasil penelitian diperoleh pemahaman siswa Pendidikan Agama Kristen tentang pendidikan agama Kristen menurut 2 Timotius 3:14-17 pada minat siswa adalah signifikan dengan korelasi 0,627 dalam kategori baik, dengan kontribusi 0,393 atau 39,3% dengan persamaan regresi linier Y = 29, 18 + 0,47 X signifikan. Peningkatan peran orang tua yang secara konsisten memotivasi anaknya, peningkatan pemahaman siswa oleh guru secara serius, dan pemilihan teman yang cermat akan meningkatkan minat belajar siswa. Semakin tinggi pemahaman siswa terhadap pendidikan agama Kristen, menurut 2 Timotius 3:14-17, maka secara signifikan akan meningkatkan minat siswa terhadap Pendidikan Kristen.Kata Kunci: dampak, pemahaman, minat belajar
Membangun Kredibiltas Kekristenan Dalam Menghadapi Ajaran Sesat Berdasarkan 1 Yohanes 4:1-6
Authors: Tambunan Fernando , Ambarita Heri Victor
Published: July 2024

Since the beginning of the first century until now there have been many teachings that deviate from the Bible. Unhealthy teaching can undermine the faith and trust of Christians. This can happen if God's congregation is not properly equipped and taught the truth of God's Word. This study aims at how Christians build the credibility of Christianity in the face of heresies. The method used in this research is descriptive method. In this study it was found that in 1 John 4:1-6, the apostle John provides a solution in building the credibility of believers when facing heresies. First: test the spirit; second: knowing the Spirit of God, and third: knowing the status of a child of God.
Pemahaman Jemaat Gereja Baptis Antiokhia Medan Berdasarkan Filipi 1:27-30 dalam Hal Kesetiaan Beribadah
Authors: Sipayung Gerhard Eliasman , Hia Sona , Silaban Petrus Posma , Hutabarat Jepri , Sinaga Resie VM , Hutagalung Sophian
Published: July 2024

Worship is a relationship between God's people and God as a binding relationship. The bond is applied because of the right understanding and is shown in terms of loyalty to worship God. Medan Antioch Baptist Church as a place to grow for believers in God, faces many challenges to be faithful in worship, especially pre-pandemic-post-pandemic. This research uses a quantitative survey method. And found, First the understanding of loyalty to Allah in the moderate category. Second, the understanding of perseverance in worship is in the low category. Third, there is a significant influence between the variables of understanding of perseverance on loyalty to God. The influence of the understanding of perseverance on faithfulness to God in worship can be made if, first, live according to the gospel; second, stand together in the gospel; third, not afraid to face threats: fourth, suffer for GodKeywords: Church, Worship, Faithfulness  AbstrakBeribadah merupakan hubungan antara umat Tuhan dengan Tuhan sebagai hubungan yang mengikat. Ikatan itu diaplikasikan karena pemahaman yang benar dan ditunjukkan dalam hal kesetiaan untuk beribadah kepada Tuhan. Gereja Baptis Antiokhia Medan sebagai salah satu tempat untuk bertumbuh bagi orang percaya didalam Tuhan, menghadapi banyak tantangan untuk setia dalam beribadah secara khusus pra pandemi-pasca pandemi. Penelitian ini menggunakan kuantitaf dengan metode survey. Dan ditemukan, Pertama pemahaman tentang kesetiaan kepada Allah dalam kategori sedang. Kedua pemahaman tentang ketekunan dalam beribadah ada pada kategori rendah, Ketiga terdapat pengaruh yang signifikan antara variabel pemahaman tentang ketekunan terhadap kesetiaan kepada Allah. Pengaruh pemahaman tentang ketekunan terhadap kesetiaan kepada Allah dalam beribadah dapat dilakukan jika, pertama, hidup sesuai dengan Injil; kedua, berdiri bersama dalam Injil; ketiga, tidak gentar menghadapi ancaman: keempat, menderita untuk TuhanKata Kunci: Jemaat, Beribadah,Kesetiaan
Pemahaman Mengenai Penghukuman Allah Yang Menegakkan Keadilan: Teologi Kitab Ratapan
Authors: Gulo Mainyer
Published: July 2024

Artikel ini merupakan sebuah hasil penelitian dari kitab Perjanjian Lama yaitu kitab Ratapan. Kitab Ratapan ini merupakan sebuah kitab yang sangat unik, dimana isi dari kitab ini memuat berbagai keluh kesah atas penderitaan yang sedang dialami. Dalam kitab ini menceritakan bagaimana kehancuran kota Yerusalem atas penghukuman Allah karena dosa-dosa mereka. Allah menghukum umat-Nya bukan karena Dia tidak mengasihi, tetapi Allah menginginkan umat-Nya menyadari perbuatan dosa mereka. Dalam artikel ini penghukuman Allah diartikan sebagai wujud keadilan-Nya kepada umat manusia, sehingga manusia meletakkan pengharapannya kepada Allah. Dalam Ratapan ini umat manusia masih mempunyai pengharapan ditengah penderitaan yang mempunyai keyakinan, bahwa Allah tetap setiap kepada umat-Nya, yang mendorong tindakan mereka dalam meminta belas kasihan Allah. Penulisan artikel ini, penulis menggunakan kajian literatur dalam menggali makna teologi dalam kitab Ratapan. Oleh karena itu, artikel ini memberikan pemahaman bahwa Allah memberikan penghukuman agar umat manusia menyadari dosanya dan berbalik kepada Allah sesuai dengan konteks kitab Ratapan.
ANAYASA MAHKEMESİNİN İPTAL KARARLARININ YÜRÜRLÜĞÜNÜN ERTELENMESİ KURUMU VE CUMHURBAŞKANLIĞI KARARNAMELERİNDE GÖRÜNÜMÜ
Authors: Barın Taylan , Uslu Muhammet Tayyib
Published: July 2024

Anayasa’nın 153. maddesine göre Anayasa Mahkemesi; Kanun, Cumhurbaşkanlığı Kararnamesi veya Türkiye Büyük Millet Meclisi İçtüzüğü hükümlerini iptal etmesi halinde, iptal kararının Resmî Gazete’de yayımlanmasıyla iptal edilen hükümler yürürlükten kalkar. Anılan maddenin devamında Mahkemeye, gereken hallerde iptal hükmünün yürürlüğe gireceği tarihi iptal kararının yayımlandığı tarihten itibaren bir yılı geçmemek üzere ayrıca kararlaştırabilme yetkisi verilmiştir. Mahkeme’nin iptal kararları incelendiğinde iptal kararlarının yaklaşık yarısında iptal kararının yürürlüğe gireceği tarihi ayrıca kararlaştırdığı/ertelediği görülmüştür. Mahkeme bu yetkisini Cumhurbaşkanlığı Kararnamelerine dair vermiş olduğu kararlarda daha yoğun kullanmaktadır. Ancak bu kararların hemen hepsi iptal edilen Cumhurbaşkanlığı Kararnamesi kuralının konu bakımından yetkisizlik gerekçesiyle iptal edildiği kararlardır. Başka bir ifadeyle Mahkeme, Cumhurbaşkanının iptal edilen konuda düzenleme yetkisi olmadığı gerekçesiyle iptal etmiştir. Bu ayrıksı durum, iptal kararlarının yürürlüğe girişinin ertelenmesine dair kanunlara ilişkin uygulamalardan farkını ortaya koymaktadır. Bu çalışmada genel olarak iptal kararlarının yürürlüğünün ertelenmesi kuralı tahlil edilecek, ardından Cumhurbaşkanlığı Kararnamelerine dair verilen iptal kararlarında erteleme kurumunun uygulanabilirliği tartışılacaktır.
ASSESSMENT OF BURNOUT OF NURSES AND ITS IMPACT ON RESILIENCE IN MAJOR HOSPITAL DEPARTMENTS
Authors: NAWAZ N , AHMED F , MUMTAZ A
Published: July 2024

Burnout among nurses is a critical issue that can significantly affect their professional performance and overall well-being. Personal resilience has been suggested as a potential mitigating factor for burnout symptoms. Understanding the relationship between burnout and resilience can inform interventions to support nurses in high-stress environments. Objective: To assess the burnout levels of nurses working in central hospital departments and their association with personal resilience. Methods: A cross-sectional study was conducted in the Nursing Department of a tertiary care hospital from April 2023 to April 2024. A total of 200 registered and licensed nurses from major departments who were directly involved in patient care were selected through convenience sampling. Data were collected using an anonymous questionnaire written in both English and Urdu. The survey comprised three sections: demographic details, the Maslach Burnout Inventory General Survey, and the Connor-Davidson Resilience Scale. Statistical analysis was performed using SPSS version 25. Descriptive statistics were used to summarize the data, and Pearson correlation analysis was conducted to assess the association between burnout and resilience variables. Results: The mean scores of burnout variables were 2.50 ± 1.30 for emotional exhaustion, 2.18 ± 1.18 for cynicism, and 2.21 ± 1.08 for reduced professional performance. The mean scores for resilience variables were 33.08 ± 7.15 for tenacity, 22.68 ± 5.63 for strength, and 10.82 ± 2.36 for optimism. A significant negative association was found between resilience levels and burnout symptoms; higher resilience scores were associated with lower burnout symptoms, though these associations were not statistically significant. Conclusion: The study identified high burnout and moderate resilience levels among nurses. Burnout and resilience were negatively associated, suggesting that enhancing resilience may play a role in mitigating burnout among nurses. Interventions aimed at building resilience could be beneficial in reducing burnout and improving professional performance.
Detect and Prevent Attacks of Intrusion in IOT Devices using Game Theory with Ant Colony Optimization (ACO)
Authors: S S ,   Assistant professor, Department of Computational Intelligence, SRM Institute of Science and Technology, Kattankulathur-603203, Tamilnadu, India,   Assistant professor,Sri krishna college of Engineering and Technology, Coimbatore, India,   Assistant Professor (SG), Department of ECE, Nehru Institute of Engineering and Technology, Coimbatore, India,   Assistant Professor, Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam. Tamil Nadu, India,   Associate Professor, Department of CSE, Hindusthan Institute of Technology, Coimbatore, India, N Kalaivani , M Mohammedkasim , .. D. Prabha , Thirumangaialwar E.Babu
Published: July 2024

A more extensive attack surface for cyber incursions has resulted from the fast expansion of Internet of Things (IoT) devices, calling for more stringent security protocols. This research introduces a new method for protecting Internet of Things (IoT) networks against intrusion assaults by combining Game Theory with Ant Colony Optimization (ACO). Various cyber dangers are becoming more common as a result of the networked nature and frequently inadequate security measures of IoT devices. Because these threats are ever-changing and intricate, traditional security measures can't keep up. An effective optimization method for allocating resources and pathfinding is provided by ACO, which takes its cues from the foraging behavior of ants, while Game Theory provides a strategic framework for modeling the interactions between attackers and defenders. Attackers and defenders in the proposed system are modeled as players in a game where the objective is to maximize their payout. Minimizing damage by anticipating and minimizing assaults is the defender's task. The monitoring pathways are optimized and resources are allocated effectively with the help of ACO. In response to changes in network conditions, the system dynamically modifies defensive tactics by updating the game model in real time. The results of the simulation show that the suggested method successfully increases the security of the Internet of Things. Compared to 87.4% using conventional approaches, the detection accuracy increased to 95.8%. From 10.5 seconds down to 7.3 seconds, the average reaction time to identified incursions was cut in half. Furthermore, there was a 20% improvement in resource utilization efficiency, guaranteeing that defensive and monitoring resources were allocated optimally. Internet of Things (IoT) network security is greatly improved by combining Game Theory with Ant Colony Optimization. In addition to enhancing detection accuracy and reaction times, this combination method guarantees resource efficiency. The results demonstrate the practicality of this approach, which offers a solid foundation for protecting Internet of Things devices from ever-changing cyber dangers.
The main directions of improving the legal mechanisms of budget administration
Authors: Титов Г.А.
Published: July 2024

В статье рассмотрены основные направления совершенствования правовых механизмов бюджетного администрирования, касающихся развития законодательства в области бюджетного управления, а также отдельные вопросы и направления совершенствования бюджетного администрирования.

The article discusses the main directions of improving the legal mechanisms of budget administration related to the development of legislation in the field of budget management, as well as individual issues and directions of improving budget administration.
Religion and National Values: A Cross-Cultural Comparison of Denmark, Iran, South Korea, and Thailand
Authors: Wu Xian
Published: July 2024

This paper analyses a comparative analysis of the national cultures of Denmark, Iran, South Korea, and Thailand, utilizing Hofstedes, GLOBE, and World Values Survey (WVS) cultural dimensions. It details how each country's predominant religionChristianity in Denmark, Islam in Iran, Confucianism in South Korea, and Buddhism in Thailandinfluences various cultural metrics such as power distance, individualism, and uncertainty avoidance. Denmark is highlighted for its low power distance and high individualism, indicative of a culture that values equality and individual rights. Iran is depicted as highly collectivistic, emphasizing family and community cohesion. South Korea is described as valuing hierarchical order and community well-being, reflecting its Confucian roots. Thailand is recognized for its high humane orientation and respect for social hierarchies, influenced by Buddhist teachings. The analysis points out the significant implications these cultural dimensions have for international business practices, stressing the need for cultural sensitivity and adaptability in global market strategies.
The Impact of Teachers' Emotional Labor on Teachers and Students: A Literature Review
Authors: Yu Jingjing
Published: July 2024

Emotional labor (EL) is a significant component of teachers' daily work. During their daily teaching activities, teachers experience various emotional responses. However, they do not always express their genuine emotions, but rather adopt different strategies to regulate their feelings. This process is referred to as emotional labor. Previous studies on teachers' EL have typically focused on a single aspect concerning either teachers or students. Therefore, this study synthesizes the effects of various EL strategies on both the cognitive and emotional well-being of teachers, as well as on students' academic and emotional development. By reviewing prior research on teachers' EL, we summarize the impact of EL on both teachers and students across different dimensions, aiming to provide a more comprehensive understanding of its effects. This review highlights the importance of recognizing and addressing EL in teaching.
The Intergenerational Theoretical Perspective on Motivation in the Medical Workplace, a Literature Review
Authors: Tu Yangming
Published: July 2024

Psychodynamics profoundly influences society, where intrinsic motivations, extrinsic motivations, job engagement, and orientations toward public service play key roles in shaping organizational structures. This review article explores the intersections of psychodynamic principles and generational theory, particularly their applications in the medical field during the COVID-19 pandemic. By referencing academic databases such as Frontiers in Psychology, MDPI, GALE ACADEMIC ONEFILE, IEEE Xplore, and Oregon State University Library, this study delves into how intrinsic and extrinsic motivational factors, along with job resources and motivations for public service, impact job engagement and occupational well-being across different generations. The article highlights the unique attitudes and expectations of Generations Y and Z, gathering observed changes in their career values and work-life balance preferences. The study examines how these intergenerational theoretical views interact with motivational dynamics, especially under the prolonged pressures of the pandemic. Integrating psychodynamic theories with empirical data on motivational factors and generational differences, this review aims to provide insights into the evolving nature of job engagement and its implications for future workforce management.
A Study on the Employment Dilemmas and Paths of Chinas English Majors in the Context of Education Internationalization
Authors: Sun Shihong
Published: July 2024

Employment is not only related to economic and social development, but also related to social stability and harmony, and involves many issues such as education reform. In the 21st century, the trend of education internationalization has presented fresh chances and difficulties for the job market of English department. Unemployment upon graduation is a common nightmare for English majors in China. Therefore, it is urgent to analyze the employment situation of English majors and put forward feasible strategies. This study aims to investigate the dilemmas and paths of Chinese English majors within the framework of education internationalization. This study discusses the dilemma of Chinese English majors in the job market, analyzes influencing factors, discusses several contradictions between the separation of profession and discipline, the weakening of English in basic education and the large demand, the academic English teaching and humanistic quality education, as well as graduates' immature career outlook and the real needs of society, and points out the countermeasures and suggestions to redefine compound talents, reduce the scale of schools, develop special training programs, balance the "humanism" and "instrumentality" of English Majors and enhance the students' professional ability and guide the correct career view.
A Study of People's Impulse Spending Psychology under the Influence of Online Social Media
Authors: Xie Renjie
Published: July 2024

Nowadays, with the growth of social networks, countless advertisers advertise and promote their products through social media. Some media content is directly labelled as advertising and promotes their products. Some media content will not be labelled as such, but will reveal the product subliminally and demonstrate its benefits through social media platforms or blogger videos, so that consumers unconsciously desire to buy the product. Regardless of the content of the adverts, advertisers are having great success with social media platforms these days, while at the same time making people do a lot of unnecessary spending. this study will do a series of research on this phenomenon. By looking up relevant psychological literature, setting up questionnaires and collecting and analysing data, this study will analyse and study the psychology involved in some impulsive consumption behaviours that occur when people use social networks. This way, people who make impulse purchases of products advertised by advertisers can be clear about the psychology that drove them to make impulse purchases, and can better prevent impulse purchases in the future.
A Study on the Obstacles and Countermeasures of Implementing the Double Reduction Policy under the Guidance of Educational Goals
Authors: Hu Mingjun
Published: July 2024

In China, the situation where students face excessive academic pressure and there are too many extracurricular tutoring classes has received widespread attention, but there are still some obstacles during the implementation of the Double Reduction Policy. Based on these, this study mainly discusses the issues teachers and parents should pay more attention to in implementing this policy. It has been analyzed that students' learning enthusiasm still needs to be stimulated, lessons need to be designed better, teachers have not received enough training, the interaction with teachers needs to be strengthened, and cooperation between parents and teachers needs to be more tacit. Based on this, the study also puts forward some potential solutions to address the problems from the perspective of teachers, students, and parents, specifically focusing more on the effectiveness of lessons, the needs of different kinds of students, and strengthening the correct understanding of the policy by both teachers and parents.
Advancing financial crisis prediction: Big data, AI, and economic theories
Authors: Li Shirui
Published: July 2024

This paper explores the theoretical foundations of financial crisis early warning systems, focusing on the integration of big data, ensemble learning, and various financial crisis theories. It begins with defining key concepts such as big data, financial crisis, and ensemble learning, highlighting the evolution and significance of these terms in the context of financial crisis management. The literature review covers extensive research on financial crisis early warning indicators and models, tracing the development from traditional statistical methods to advanced artificial intelligence approaches, including neural networks, decision trees, and machine learning algorithms. The paper critically assesses the current methodologies and emphasizes the necessity of incorporating big data and machine learning for more accurate and comprehensive early warning systems. Theoretical foundations related to financial crises, such as information asymmetry, behavioral economics, economic cycle theory, and contingency theory, are discussed to understand their impact on financial crisis prediction and management. The conclusion synthesizes the findings and suggests future research directions, emphasizing the integration of diverse methodologies and interdisciplinary approaches to enhance the early warning capabilities of enterprises.
Statistical analysis and prediction of data for Alzheimer's disease and mild cognitive impairment based on multiple machine learning algorithms
Authors: Lan Zijun
Published: July 2024

This paper focuses on the characteristics and diagnostic methods of two neurodegenerative diseases, Alzheimer's disease and mild cognitive impairment, as well as the application of machine learning in the medical field. Firstly, through the statistical analysis of patients' age and gender, it is found that patients with Alzheimer's disease tend to be older than patients with mild cognitive impairment, while the number of female patients are both larger than that of male. These results provide an important basis for subsequent classification prediction. Next, this paper uses a variety of machine learning algorithm models for prediction, including Decision Tree, Random Forest, Logistic Regression, Naive Bayes, KNN, and SVM. These models are all based on different algorithmic principles and data processing methods to achieve classification prediction of patients with Alzheimer's disease and mild cognitive impairment. By comparing the prediction accuracy of each model, it is found that Decision Tree and Naive Bayes models have the best prediction effect, with a prediction accuracy of 75%; while Random Forest and Logistic Regression models also show high prediction accuracy. In contrast, the KNN and SVM models had a poor prediction effect of 69.2%. These results suggest that the use of decision tree or Naive Bayes models for prediction should be prioritised when classifying patients with Alzheimer's disease and mild cognitive impairment. Finally, this paper highlights the importance of machine learning in the medical field. By analysing and processing large amounts of medical data, machine learning can help doctors diagnose diseases more accurately and provide more effective treatment options. The application of these techniques will help improve the quality of life of patients and advance the field of medicine.
Predict credit risk with XGBoost
Authors: Wang Wenhao , Zuo Xiyi , Han Dantong
Published: July 2024

The risk of credit loan exists when the bank issues a loan to the borrower, because the borrower has no way to repay the amount or defaults, which exposes the financial institution to the risk of loss. This causes financial institutions to suffer from effects that affect their creditworthiness, loss of capital and increased management and collection of loans. Factors of such risk include, but are not limited to, the creditworthiness of the borrower, the repayment ability of the borrower, and fluctuations in interest rates. With the development of economy, the credit loan risk of financial industry increases, and the harm is greater. After comparing KNN (K Nearest Neighbors), random forest and logistic regression using machine learning methods, we found that the model established by eXtreme Gradient Boosting method (XGBoost) can more accurately identify the risk of credit loans based on the characteristics of the borrower. Our research found that while the XGBoost model has better accuracy, there are also some areas that need improvement.
Research and application of Chinese semantic understanding teaching system based on knowledge graph and deep learning
Authors: Ma Xinyue , Hu Yandong , Li Min
Published: July 2024

Text data in network environments has been increasingly emphasized. However, text data in network environments exhibit atypical characteristics, posing significant challenges to users. Through research on text classification, information extraction, semantic computation, and other aspects, natural language processing can rapidly and accurately extract valuable information from massive texts, providing an effective approach for addressing this problem. Nevertheless, existing machine learning methods suffer from issues such as reliance on complex feature construction, insufficient flexibility of traditional models, inability to model various text sets, and error-prone pipeline models. This paper discusses a Chinese semantic understanding teaching system based on knowledge graph and deep learning. Deep learning represents a novel approach to natural language processing, overcoming shortcomings of traditional methods, including allowing network models to flexibly model text under massive parameter conditions, providing new research ideas for machine translation and effectively avoiding the propagation of generalization errors. Experimental results demonstrate that, in different operation instances, the systems CPU (Central Processing Unit), memory operation, and GPU (Graphics Processing Unit) operate within the ranges of 2~4GHz, 15~19GB, and 8~10GB, respectively. For applications requiring extensive computation such as scientific computing, data analysis, and deep learning, CPUs with higher frequencies, generally exceeding 3.5GHz or even higher, are typically required. It can be observed that the systems resource utilization is relatively low, and the system exhibits good operational performance.
A hierarchical urban power grid disaster response method based on automatic voice warning technology
Authors: Huangfu Hancong , Wang Yongcai , Li Muxu
Published: July 2024

This article proposes a hierarchical and graded urban power grid disaster response method based on automatic voice warning technology. This method combines automatic speech technology and hierarchical classification methods to achieve fast and accurate information transmission and response. This article first introduces the background and significance of this method, and then introduces the current research status in China. Next, this article elaborates in detail on the experimental dataset and preprocessing, CNN and RNN algorithm model design, experimental results and analysis, and the implementation of speech warning using TTS speech synthesis technology. Finally, this article summarizes the main work and contributions of this article, and points out future research directions.
Self-calibrated transit service monitoring using automated collected data
Authors: Guo Hongyu
Published: July 2024

This paper proposes a self-calibrated transit service monitoring framework that aims to obtain the performance of a transit system using automated collected data. We first introduce an event-based transit simulation model, which allows the detailed simulation of passenger travel behavior in a transit system, including boarding, alighting, and transfer walking. To estimate passenger path choices, we assume the path choices can be modeled using a C-logit model, and propose a simulation-based optimization model to estimate the path choice parameters based on automated fare collection and automated vehicle location data. The path choices can be estimated on a daily basis, which enables the simulation model to adapt to dynamic passenger behavior changes, and output more accurate network performance indicators for regular service monitoring such as train load, passenger travel time, and crowding at platforms. The proposed system eliminates the need for conventional monitoring equipment such as cameras at platforms and scaling/weighing systems on trains. The Hong Kong Mass Transit Railway (MTR) system is used as the case study. Results show that the model can well estimate the path choice behavior of passengers in the system. The output passenger exit flows are closer to the actual one compared to the two benchmark models (shortest path and uniform path choice).
Detection and classification of pests and diseases in rice leaf images based on deep learning algorithms
Authors: Cao Yiran
Published: July 2024

Rice is one of the important food crops worldwide, but it is susceptible to various pests and diseases during its growth process, leading to yield reduction and even death. Therefore, it is very important to detect and categorize rice pests and diseases in a timely and accurate manner. In this paper, we use the dataset from Kaggle public database, which is divided into two categories of images: "normal leaves" and "infested by pests and diseases", and configure AlexNet, Vgg and MobileNetV2 models based on Pytorch framework to detect and classify rice pests and diseases in a timely and accurate manner. MobileNetV2 model was configured based on Pytorch framework to detect and classify pests and diseases in rice leaf images. Through the changes of the loss and Accuracy curves of AlexNet, Vgg and MobileNetV2 models, we found that all three deep learning models have good training effect and can well predict whether the rice leaf images are infested by pests and diseases. The final results show that the prediction accuracy of all three sets of deep learning models reaches more than 97%, and they can detect pests and diseases on rice leaf images very accurately. This means that we can use these models to quickly and accurately detect and categorize rice pests and diseases, so that timely measures can be taken to prevent the spread of pests and diseases and improve the yield and quality of rice.
Enhancing software engineering with visual design and multimedia: An empirical and theoretical exploration
Authors: Wang Yidan
Published: July 2024

This article delves into the critical role of visual design and multimedia integration within software engineering, emphasizing their significance in enhancing user engagement, comprehension, and collaboration among stakeholders. Through a comprehensive analysis of theoretical frameworks, quantitative research findings, and practical applications, this study elucidates the benefits and challenges associated with embedding visual and multimedia elements in software systems. It presents empirical evidence from controlled studies and case analyses to demonstrate the tangible improvements in software usability, educational efficacy, and project management efficiency. Moreover, the article explores future directions, highlighting emerging technologies and methodologies that promise to further revolutionize the integration of visual design in software engineering. The findings underscore the pivotal role of visual and multimedia elements in bridging communication gaps, fostering collaborative environments, and enhancing the overall software development process.
Electrical fault detection and classification based on multiple machine learning algorithms
Authors: Liu Hailang , Liu Xuanyu
Published: July 2024

Electrical faults in the power system refer to a variety of abnormalities in the power equipment, and these faults may lead to equipment damage or even cause dangerous events such as fires and explosions, which pose a serious threat to people's lives and property. Therefore, it is very important to find and deal with these faults in time. In this paper, based on the electrical fault dataset of power system, SVM, decision tree, KNN and random forest model are used to detect electrical faults. After the confusion matrix results are analyzed, most of the predictions of the four models are correct, and only a few instances that should not be predicted as electrical faults are predicted as electrical faults. All the four machine learning models achieved more than 99% accuracy in detecting electrical faults in the power system and were able to detect electrical faults very accurately. Among them, the SVM model has the highest prediction accuracy of 99.6%, followed by the KNN model prediction accuracy of 99.5%. In summary, this paper adopts machine learning method to detect electrical faults in power systems, and achieves better results in the experimental results. This method can help power system supervisors find and deal with faults in time, and improve the safety and stability of the power system. In the future, we can further study how to optimize the model to improve the detection accuracy and apply it in practical production.
Optimal design of bus schedule timing based on PID system
Authors: Xu Yancheng
Published: July 2024

With more and more attention paid to the concept of low-carbon travel, public transport has gradually become the mainstream mode of travel. Nowadays many people will choose bus as a means of transportation. But how to make a reasonable bus departure schedule is a very complicated problem. Sometimes the departure interval is long, which leads to passengers having to wait for a long time, and sometimes there are not many passengers or even empty cars, resulting in a waste of resources. The purpose of this paper is to create a Proportional Integral Derivative (PID) controlled automated control system, which can adjust the bus departure schedule by the number of passengers on the bus in real time, to make a more reasonable bus schedule. Shorten the departure interval when the number of people is large and extend the departure interval when the number of people is small. This can greatly reduce the waiting time for passengers and reduce the waste of public resources when there are fewer people.
Evaluasi Penilaian Kinerja Guru dan Sistem Pembelajaran
Authors: Putri Suci Ramadhan  , Desi Fitri Yani Sembiring  , Ella Nurmaini  , Dessy Masliani Lubis  , Muhammad Iqbal
Published: July 2024

Evaluation of the performance of educators is an important process in assessing the effectiveness of the education system in achieving educational goals that have been set. Assessment of educator performance not only focuses on academic aspects, but also involves various other aspects, including social aspects, skills, and student character. In this study, will be discussed some key aspects in the evaluation of the performance of educators from the definition of performance evaluation of educators, basic concepts of performance evaluation, evaluation objectives, ways and tools of performance evaluation, formative and summative evaluation, as well as the involvement of teachers in the evaluation process, at the conclusion of this discussion, the authors get the results that the evaluation of the performance of educators can be done through a variety of methods and evaluation tools, such as standardized tests, formative assessment, observation, and interviews. The purpose of this evaluation is to identify strengths and weaknesses in the education system, as well as provide relevant information for improvement. Evaluation of educator performance is an important tool in improving the quality of education. By engaging various stakeholders and using appropriate evaluation methods, the education system can continue to evolve and provide better education for future generations
Kitab Yeremia: Penyesalan dan Pertobatan, Harapan dan Pengharapan, serta Keadilan dan Hukuman
Authors: Salendra Tandiawo Buyung
Published: July 2024

Artikel ini merupakan sebuah tafsiran yang mendalam tentang Kitab Yeremia, salah satu kitab dalam Alkitab. Tafsiran ini membahas dengan rinci konteks sejarah dan budaya saat Kitab Yeremia ditulis, serta menggali makna dan aplikasi pesan-pesan yang terkandung di dalamnya. Dalam tafsiran ini, penulis mengungkapkan latar belakang sejarah yang melatarbelakangi penulisan Kitab Yeremia.  Dalam hal ini juga mengulas pesan-pesan yang terkandung dalam Kitab Yeremia, seperti penyesalan dan pertobatan, harapan dan pengharapan, serta keadilan dan hukuman. Penulis menggali makna dan implikasi dari pesan-pesan ini, mengajak pembaca untuk merenungkan dan mengaplikasikan ajaran-ajaran yang terkandung dalam Kitab Yeremia ke dalam kehidupan sehari-hari. Dalam hal ini memberikan pemahaman yang lebih mendalam tentang Kitab Yeremia, mengaitkan pesan-pesan nabi Yeremia dengan konteks sejarah dan budaya pada saat itu, dan mengajak pembaca untuk merefleksikan dan mengaplikasikan ajaran-ajaran ini dalam kehidupan sehari-hari.
Kata kunci: Kitab Yeremia, tafsiran, nabi Yeremia, pesan-pesan, nubuat, bangsa Israel, Alkitab.
Enhancement DTC Control for SEIG in Variable-Speed Wind Turbines, Associated with an Energy Storage System
Authors: Berabez Kahina , Hacini Ismail , Hamoudi Farid , Idjdarene Kassa
Published: July 2024

This research focuses on the application of the Direct Torque Control (DTC) strategy to manage the terminal voltage of a Self-excited induction generator (SEIG) that supplies power to an autonomous load. The SEIG is connected to a three-level Neutral Point Clamped (3L_NPC) converter. The utilization of the 3L_NPC converter ensures the increase in generated voltage levels, leading to improved current waveform quality and reducing the Total Harmonic Distortion (THD) in the stator currents. To ensure a more stable and dependable power supply, this study also introduces an Energy Storage System (EESS) consisting of batteries (BT) along with a management algorithm designed to oversee power flows between different storage devices. Furthermore, the dynamic model of the SEIG incorporates the saturation effect of magnetic materials and is conducted in the  frame using the Concordia transform. The efficacy of the proposed control strategy is verified through simulation tests conducted in MATLAB/Simulink.