bluuebunny/crossref_metadata_2025 huggingface dataset:
Perceived Stress and Resilience of Criminology Teachers and Students during Covid-19 Pandemic
Authors: Liza Joy B. Barican
Published: April 2024

Due to the COVID-19 pandemic, education has undergone rapid and profound changes, leading to feelings of uncertainty, anxiety, social isolation, and potentially detrimental behaviors that undermine well-being. In this situation, it is essential to understand the link between perceived stress and resilience among vulnerable populations, including teachers and students, as society navigates the new normal in delivering high-quality education. Furthermore, since little scholarly attention has been invested in understanding the impact of the pandemic on Criminology teachers and students, targeted studies are necessary. Thus, this descriptive-correlation study assesses the perceived stress and resilience among Criminology teachers and students in Negros Occidental (Western Visayas, Philippines) during the pandemic. To this end, a total of 2000 respondents voluntarily answered the survey questionnaire used by the researcher – 124 Criminology teachers using the total enumeration technique and 1876 students using the simple random process among the eleven schools in Negros Occidental offering Criminology Program. The data was collected through Google Forms because travel restrictions and quarantine were still imposed during the study. The study used the frequency and percentage in terms of the profile of the respondents, mean and standard deviation to determine the level of perceived stress and resilience, and coefficient correlations for significant correlations and disparity. The findings revealed that Criminology teachers had a moderate level of perceived stress and resilience, indicating their ability to manage stress and cope with teaching challenges during the pandemic. Conversely, students experienced a high-stress level, particularly among females, while demonstrating moderate resilience. Furthermore, a notable disparity was found between teachers' and students' stress levels and resilience, affirming that the latter are more resilient, albeit more stressed, because finishing their degree during the pandemic signifies a remarkable achievement for them. These results underscore the need for tailored interventions that effectively manage stress and promote the development of coping mechanisms. By acknowledging the unique stressors Criminology students face and harnessing their inherent resilience, educational institutions would be able to support their success and well-being during these challenging times.
The Impact of Management Information System’s Organizational Slack to Syngenta Company
Authors: Harvey T. Ong
Published: April 2024

Management information systems (MIS) is the usage of information systems at the operational, tactical, and strategic levels so that businesses are aided in the achievement of goals. (Oprea, 2007) While the use of MIS is already quite common, its many benefits have lately piqued the interest of researchers particularly on the phenomenon of slack. Companies typically prefer to remove slack as it has suffered from a negative reputation.  However, recent studies by Bae and Rhee (2014) as well as by Heng, Ding, Guo, and Luo (2014) have shown that slack actually leads to innovation.  It is because of these interesting discoveries that pushed the proponent to conduct a study on the contribution of organizational slack towards the innovative performance of Syngenta company. Survey were gathered to provide the needed information. Key informants were likewise interviewed in order to generate additional insights about the variables under investigation. The results showed convincingly that slack affects the innovation of the company.  However, some effects of the slacks were positive and some were negative. The recommendations put forward by this research is that JDI should maximize its innovation, they should reduce both absorbed and unabsorbed slack as much as possible since slack and innovation are inversely proportional in JDI’s case.  As long as they cut back on excessive spending on equipment and make use of their spare resources like reserve funds, then the innovation the company will surely improve.
Moth Flame Algorithm to Optimize the Size and Location of Energy Storage Units in a Radial Distribution Network to mitigate Power Loss
Authors: Suresh Babu Maddina
Published: April 2024

The ideal placements and capacities for Battery Energy Storage Systems (BESS) sources in a distributed generation (DG) environment have an impact on power losses in the distribution network. Therefore, engineers are quite concerned with DG and BESS. The output from DG is, however, typically unpredictable and inconsistent. The secure and stable functioning of the power system will be impacted to varying degrees when it is connected to various sites, capabilities, and power grids. To provide a safer, more stable, more dependable, as well as more effective power grid operation, power grid planners must take the impact of capacity, type, and location into account while choosing the best BESS accessibility method. The objective is to choose bus stops with the right potential and minimal loss. This study demonstrates how to use a Moth Flame Optimization Algorithm (MFOA) to establish the appropriate battery energy storage system (BESS) sizing in a hybrid solar and wind energy conversion system (WECS) generation integrated in a radial distribution network. This research investigates the optimal capacities and allotment of the BESSs within a 33-bus and 69-bus radial network of distribution for the maximum power dissipation reduction. This research also provides a framework for carrying out conservation voltage reduction (CVR) when distributed energy resources like solar photovoltaic (PV) systems, WECS, and energy storage systems (ESSs) are connected into distribution networks. The simulation has been conducted using Matlab code and the suggested method's output is compared with Firefly Algorithm (FA), Genetic Algorithm (GA) and Ant Colony Algorithms (ACA) and evaluated against other results.
A Multifaceted Approach for Enhancing Anomaly Detection in Industrial Systems with Adaptive Synthetic Sampling and Machine Learning Evaluation
Authors: G.Malarselvi
Published: April 2024

Anomalies in industrial systems refer to deviations from expected behaviour, indicating potential malfunctions, faults, or security breaches. These anomalies can disrupt operations, compromise safety, and lead to costly downtime, making their detection and mitigation critical for industrial reliability and security. This research addresses the imperative task of enhancing anomaly detection within industrial systems by integrating a multifaceted approach encompassing various techniques and methodologies. A primary challenge in anomaly detection, the imbalanced distribution of data, is tackled by employing Adaptive Synthetic Sampling (ADASYN), which dynamically generates synthetic samples for minority classes. This effectively mitigates the impact of class imbalance and substantially enhances detection performance. Additionally, filter-based feature selection methods are utilized, incorporating statistical measures like the Chi-Square Test and ANOVA F-Value to identify pertinent features essential for anomaly detection. The study further delves into supervised anomaly detection approaches, leveraging machine learning algorithms such as Support Vector Machines (SVM) and Gradient Boosting (GB) to differentiate between normal and anomalous activities. These algorithms undergo rigorous evaluation within a Virtual Testing Environment (VTE) simulator, meticulously replicating industrial processes for comprehensive assessment. By leveraging the VTE simulator, this research ensures thorough evaluations across diverse operational scenarios, thereby fortifying anomaly detection systems and advancing the security of industrial systems. The research evaluates anomaly detection models for industrial systems using performance metrics like precision, recall, F1-score, and AUC-ROC. It compares Support Vector Machine (SVM) and Gradient Boosting (GB) models, finding GB outperforms SVM in discrimination ability. Both models show effective anomaly detection with minimal false positives and false negatives. A comparative analysis of key performance metrics aids in selecting the most suitable approach for enhancing system reliability and safety.
Enhancing Facial Recognition Accuracy in Low-Light Conditions Using Convolutional Neural Networks
Authors: S. Swapna Rani
Published: April 2024

Facial recognition technology has become increasingly everywhere in various domains, from security and surveillance to personal device authentication. However, its effectiveness can be significantly hindered in low-light conditions, where images often lack sufficient illumination for accurate recognition. This study proposes a novel approach to enhance facial recognition accuracy in low-light conditions using Convolutional Neural Networks (CNNs), Deep Retinex Decomposition Network (DRDN), and CenterFace algorithm. The methodology leverages CNNs for robust feature extraction, while DRDN corrects illumination by decomposing images. CenterFace integrates feature fusion and denoising layers for discriminative facial features and noise mitigation. Experimental results demonstrate a remarkable improvement in recognition performance, exceeding 80% accuracy. This approach showcases the potential of CNN-based methods with advanced techniques to enhance reliability in real-world facial recognition applications, particularly in low-light environments.
Analysing The Development of Web-Based Multimedia Piano Playing Teaching Design Using Multiple Linear Regression Algorithm
Authors: Xueying Liu
Published: April 2024

The popularity of piano lessons has increased recently, and many individuals are taking the instrument. Using Web technology as its backbone and high-performance streaming media technology, this platform for teaching piano playing can efficiently address the issues of a limited audience, a steep learning curve, and a shortage of available materials in today's online education landscape. This kind of instruction may help bring the classroom closer together. The goals of this study are to increase the effectiveness of communicating via online text, to make it easier for students to get expert guidance from teachers, to satisfy students' interest in learning, to elevate students' piano effectiveness and creation, and to promote the widespread use of the piano. Using a Multiple Linear Regression Algorithm (MLRA), this study makes recommendations for designing an intelligent piano-playing teaching system, looks into the implementation of the piano-teaching system, and offers a technique to evaluate piano-playing using the MLRA model for the difficulties of online piano training. Teaching the piano is greatly aided by this paper's portrayal of an instructor encouraging students to keep up with their practice. The study results stated that MLRA's recognition accuracy is 95% and its mean square error rate is 12%.
Application of LSTM Feature Extraction Model in the Construction of Opera Audio Database
Authors: Wei Zhou
Published: April 2024

Chinese traditional music plays a greater role in ideal society governed by rites and rituals. The musical culture of China is both ancient and modern. Throughout history, musicians have created several musical genres and used countless instruments. In order to appreciate Chinese traditional music, it is helpful to have a basic familiarity with three "keynotes": the classical traditional music of the elites; folk and ethnic music, and the most popular traditional Chinese instruments. In general, an opera audio database consists of audio recordings of opera performances. These recordings may be utilized for a variety of reasons, including research, education, and entertainment. To establish such a database, pertinent features must be extracted from the audio recordings to allow for effective storage, retrieval, and analysis of the data. Improvements in audio signal processing over the last several years have qualified for creating feature extraction methods that improve the quality and accuracy of the retrieved features. We first gather the audio recordings of opera performances using an appropriate recording device to build an opera audio database. Data preprocessing then eliminates noise and other undesired signals from the audio recordings to enhance the data quality. After that, to extract useful features from the audio recordings that may be utilized to define the sound's rates, the Long Short Term Memory (LSTM) technique is used. The components must then be organized and stored in a database for fast retrieval and analysis once extracted. A suitable database management system may be used to build the database. The database should be created to make it simple to search and filter the data using different criteria. The study results stated that building an opera audio database using novel feature extraction approaches is a challenging process that requires an understanding of opera music, database administration, and audio signal processing. The experimental results stated that the proposed model has provided an accuracy of 96%.
Encapsulation of Energy Efficient, Clustering Algorithm and Spectrum Sensing for Cognitive Radio Based Internet of Things Networks
Authors: Pravin Jaronde
Published: April 2024

Since the two decade the Internet of Things (IoT) plays an important role in the field of communication technology. Out of maximum of IoT devices are battery operated. So there should be energy efficient devices that can operate more functions with less power consumption. The main power constraints in the IoT devices are in the communication like spectrum selection, data transmission, etc. To perform communication between the two nodes the spectrum must be available. But as spectrums are limited and a lot of data is to be transmitted there may the issue of spectrum scarcity. The dynamic spectrum access is done using Cognitive Radio (CR) technology that can overcome spectrum scarcity issue. This paper gives the research work on energy efficient, clustering algorithm and spectrum sensing for CR based IoT networks in terms of the methods, merits, demerits and implementation. For efficiency in the spectrum sensing and energy consumption in 5G wireless communication network and data transfer between the IoT devices this study is essential. The biblometric analysis is shown by using VOSviewer to visualize the bibliometric information and the result as an analysis of ROC curve for Rayleigh and Rician channel is plotted using Matlab.
Metaheuristic Optimization Algorithms Comparison Adopted for the Profit Maximization of Electricity Market Participants
Authors: Sumit Banker
Published: April 2024

The electricity market faces numerous challenges due to the growing demand for energy, increasing penetration of renewable energy sources, and the need for grid reliability and efficiency. To address these challenges, optimization algorithms have emerged as essential tools for optimizing various aspects of the electricity market, including generation, transmission, distribution, and demand-side management. The review can be done by providing an overview of the key components and challenges of the electricity market, including generation dispatch, unit commitment, economic dispatch, transmission network optimization, and demand response management. It then systematically examines a wide range of optimization techniques employed in addressing these challenges, including linear programming, mixed-integer linear programming, nonlinear programming, dynamic programming, genetic algorithms, particle swarm optimization, simulated annealing, and machine learning-based approaches. This paper presents a comparison of optimization algorithms, RCEDUMDA (Ring-Cellular Encode-Decode Univariate Marginal Distribution Algorithm) and CL_HC2RCEDUMDA (Hill Climbing to Ring Cellular Encode-Decode Univariate Marginal Distribution Algorithm) for the profit maximization of Electricity Market consumers & prosumers.
Analysing the Techno-Economic Viability of Different Solar Heating Systems in South African Beverage Plants
Authors: Koke Johannes , Rozon Francois , McGregor Craig
Published: April 2024

With ongoing real-term reductions in the cost of renewable energy technologies, opportunities to reduce carbon emissions within industry have improved. While the South African industrial sector has been investing in photovoltaics to meet electricity requirements, little has been done to replace fossil fuels used for the generation of process heat, representing two-thirds of the energy consumed. While previous studies have demonstrated the benefits and limitations of solar thermal (ST) energy solutions for industrial applications, recent developments in high-temperature heat pumps (HTHP) offer opportunities for novel configurations, including the use of renewable energy like photovoltaics (PV). This study compares the techno-economic benefits of solar thermal energy systems with PV-supported HTHP systems within the South African beverage sector. After a general consideration, simulation calculations are presented for selected applications. The cost of heat is determined for PV-heat pump systems operating on a stand-alone basis and with heat storage. The study finds that the levelised cost of heat of US$0.050-0.073/kWhth is at least twice that of coal-fired steam boilers. The study, therefore, calls for further work on optimising systems minimising steam requirements, and thereby improving the economics of heat pumps and for a coordinated effort to support the development and financing of high-temperature heat pumps for industrial applications.
KIRSAL KALKINMA ÜZERİNE BİR LİTERATÜR ARAŞTIRMASI
Authors: Ata Ahmet Yılmaz , Dallı Tuğçe
Published: April 2024

Ekonomik kalkınma, niceliksel olarak milli gelirin artırılmasının yanı sıra niteliksel olarak da toplumların ekonomik, sosyal, siyasi ve kültürel alanlarda refah seviyesinin iyileştirilmesini hedefleyen dinamik bir süreci ifade etmektedir. Bu kapsamda, günümüz ekonomilerinde belki de en hayati unsur toplumların refah düzeyinin artırılmasıdır. Kalkınmanın alt dallarından biri olan kırsal kalkınma ise kırsal toplulukların ekonomik, sosyal, kültürel ve daha pek çok yönden yerinde kalkındırılmasıdır.
Bu çalışmanın amacı geçmişten günümüze kırsal kalkınma üzerine gerçekleştirilen literatürdeki çalışmaların genel perspektifini ortaya koymaktır. Bu amaç doğrultusunda hazırlanan bu çalışmada kırsal kalkınma üzerine yapılan çalışmalar çeşitli alt başlıklar altında incelenmiştir. Kırsal kalkınma üzerine yapılan çalışmaların genellikle kırsal turizm ve coğrafi işaretli ürünler üzerine yoğunlaştığı gözlenmiştir.
The use of AI in physical therapy
Authors: Mahto Rajendra kumar , Kumari Anchal , Kumari Shweta
Published: April 2024

Following the invention of the steam engine, human social and economic systems saw unprecedented growth and development. More recently, artificially intelligent machines have emerged, enabling human cognitive capacity to recognize previously hidden patterns within massive data sets. These changes are having an impact on every facet of society, including but not limited to our legal, moral, educational, health, and social systems. In comparison to the steam engine-driven mechanical revolution, these changes may have a greater lasting effect on human progress. Physicians will soon have to deal with massive information networks, which will necessitate the use of artificial intelligence (AI) in patient care. This paper aims to describe the potential impacts and range of applications of AI-based technologies on the field of physiotherapy, as well as the resulting changes that physiotherapy education will need to undergo in order to produce graduates qualified to work in a 21st-century healthcare system.
Knowledge Management And Its Relationship To Entrepreneurial Orientation An Exploratory Study On The Opinions Of A Sample The University Of Mosul
Authors: Rakan Mohammed Altyar Ahmed , Mellouli Dr. Samir
Published: April 2024

There are many and diverse forms of leadership, but it aims to strengthen the innovative capacity of knowledge management by increasing its initiative and willingness to adopt risks. To provide outstanding performance, the research community was chosen as a sample of two teachers in one of the university’s colleges by distributing (25) questionnaires to the individuals surveyed at their work sites, which included several questions. According to the study attempt, the statistical program (SPSS) was used to calculate the frequency distribution, percentages, arithmetic mean, and standard deviation. The research reached a number of conclusions, the most prominent of which was that knowledge management has a positive impact on entrepreneurial orientation, as it contributes to increasing the growth of projects to become medium and large projects in the country. the future.
Attitudes Of Tenth Degree Students Towards The Blended Learning In The Directorate Of Education- Qabatia
Authors: H. Al-Qassim Dr. Hussam , . Nazzal Hiba O.
Published: April 2024

The study aimed to identify the attitudes of tenth degree students towards the blended Learning in the Directorate of Education of Qabatia, and to identify the effectiveness of the blended Learning system from the learner's point of view, as well as the role of some variables (Gender, educational orientation, educational achievement). In order to achieve the aim of this study, a questionnaire consisting of (29) statements were prepared, divided into three areas (student-related, teaching-related, teacher-related) and given to the study sample of (476), (212) male students and (264) female students. 10 female students were interviewed. The results of the study showed that the attitudes of tenth degree students towards the blended Learning in the Directorate of Education of Qabatia were high. It was found that the field related to the teacher was ranked first in terms of the attitudes of tenth degree students towards the blended Learning in Qabatia Directorate of Education, while the field related to teaching was ranked second, and the field related to the student was ranked third. The results also showed that there were statistically significant differences in the attitudes of tenth degree students towards the blended Learning in the Directorate of Education of Qabatia, due to the variables of (gender, educational orientation, and academic achievement). The results of the interview questions also showed that blended learning is appropriate for some of the subjects, and that there are some difficulties facing the blended learning. Within the framework of these difficulties, the students agreed on a set of suggestions to solve these difficulties. The study also found through its results (questionnaire and interview) the most important recommendations to promote the concepts of blended learning among students in the educational process because of its importance in dealing with the problems facing the current century, and to reconsider the nature of curricula and courses, and mold them in a way that is compatible with e-learning.
UNVEILING THE TRANSFORMATIVE POTENTIAL OF TEACHER EDUCATION IN PROMOTING PEACEBUILDING: A PHENOMENOLOGICAL STUDY
Authors: Jamshaid Amber , Akram Tanzeela , Baber Shafia
Published: April 2024

Recognizing the crucial role of teachers as catalysts for societal change, the study aimed to explore the lived experiences and perspectives of teachers engaged in peace-building initiatives within their educational contexts. Through a phenomenological lens, this research sought to uncover essence and meaning of these experiences to shed light on transformative power of teacher education in fostering peace with specific aims, to understand the essence and meaning of teacher educators' experiences in peace-building, focusing on their perceptions, beliefs, & values related to peace education. Using qualitative method, include in-depth interviews data, was collected through a purposive sample from five senior teacher educators who were actively involved in peace-building efforts. The findings of this research demonstrated the positive impact of teacher education in peacebuilding and preventing youth from extremist conduct and conflicts in educational institutions. By unveiling transformative potential of teacher education in promoting peacebuilding, this study inspires educational stakeholders to recognize and harness power of teachers in building peaceful and inclusive societies.
ROLE OF ENVIRONMENT & INSTRUCTIONAL STRATEGIES IN PROMOTING ENGLISH LANGUAGE SKILLS OF HIGH SCHOOL STUDENTS
Authors: Khan Allah Noor , Yasmin Azra , Majid Abdul
Published: April 2024

The study was conducted to examine the role of environment & instructional strategies in enhancing the English language skills i.e., reading, listening, writing and speaking skills among students in higher secondary schools in the Southern Districts of Khyber Pakhtunkhwa, Pakistan. The population of this qualitative study constitutes both male and female principals of public sector higher secondary schools. A total of 32 principals, consisting of two males and two females from each district, were selected through convenient sampling technique for in-depth interviews. A semi-structured interview was conducted to explore effect of environment and instructional strategies that influence English language skills. The study reveals that environment is loud and overcrowded and outdated teaching methods are used in public sector schools. Study concludes that a supportive environment and relevant instructional strategies are vital to enhancing students' language skills. The study stresses the need to foster a culture of ongoing improvement in English books, ensuring sustained continuous professional development of teachers’ English language education. Interview results were abridged as narrative summary.
Celebrating Our Volunteer Leaders: A Heartfelt Thank You
Authors: Allan Diana
Published: April 2024

Abstract: Outgoing NATS President, Diana Allan, expresses gratitude to the numerous volunteer leaders who play pivotal roles in the success of NATS. President Allan emphasizes the immense responsibilities shouldered by national officers, region, district, and chapter leaders, and auditions chairs, as well as donors and thought leaders—highlighting their vital roles in upholding the values NATS holds dear. The President celebrates these leaders for their dedication, passion, and unwavering commitment, emphasizing their roles as the backbone of NATS. In conclusion, President Allan looks forward to continuing her service in the role of Past President and supporting new President, Alexis Davis-Hazell.
Stop Teaching! And Other Graduation Advice
Authors: Helding Lynn
Published: April 2024

Abstract: The season of this article's publication—spring—brings forth flowers, graduations, joy and student performances. But the season Editor in Chief Lynn Helding calls "Recital Season" can also bring farewells, stress, and the psychological phenomenon called "burnout" for teachers. Helding suggests a surprising solution based on principles from cognitive science which can blunt teacher burnout while simultaneously enhancing students' learning. By stopping teaching during "Recital Season," teachers may ironically provide singers what they actually need for optimal performance. Helding also announces a new future JOS column and a call for three new JOS writers.
The Anatomy of a Bokken Strike: Breaking Through Mental Blocks for Whole Body Breath Support
Authors: Ewart Daniel L.
Published: April 2024

Abstract: This article details a voice training method that stems from a traditional Japanese budo ("way of war")" called Yoshokai Aikido . The method involves safely teaching the use of a bokken ("wooden sword") strike to overcome both the mental blocks that produce under-energized breath support in singing, and the fight-or-flight cascade that causes fear and choking. The article describes the physiology of the respiratory and cognitive mechanics affected by the proper use of a bokken strike, and the philosophy of Yoshokai Aikido that can benefit singers.
Choosing and Assessing Vocal Repertoire: A Comparative Study of Grading Rubrics to Determine Difficulty
Authors: Christensen Bradley
Published: April 2024

Abstract: An issue that voice teachers face, particularly in the early stages of their career or when encountering a unique compositional style, is determining the difficulty level of a song. Various voice pedagogues have developed grading rubrics to guide teachers in making informed repertoire decisions. Two small comparative studies of six grading rubrics were conducted in order to understand how songs are currently evaluated, what criteria are used, what the challenges are for assessing difficulty, and to determine whether or not there should be a standardized grading rubric. The utility of tailoring a rubric to a specific composer or genre is also considered.
Critical Appraisal of Science-Informed Voice Pedagogy Publications
Authors: Herbst Christian T. , Meyer David
Published: April 2024

Abstract: This column proposes a six-question framework to help the voice teacher critically appraise science-informed voice pedagogy publications. The evaluation framework addresses: (1) the Singing-Voice-Production-Chain (SVPC) describing the teacher's possibilities for affecting the student's voice production; (2) descriptive, correlational, and causal types of observations; (3) subjective versus objective information; (4) factual correctness; (5) describing how singing is or how it should be; and (6) usefulness of the information in a teaching situation. This framework will empower the reader to scrutinize the structure and quality of science-informed voice pedagogy texts more deeply, thus helping to move toward evidence-based information.
Considering Crossover and the Collaborative Pianist
Authors: d'Amato Alison , Puccinelli Elvia
Published: April 2024

Abstract: The term "crossover" in classical vocal music has generally been used to refer to a classically-oriented artist's forays into non-classical styles or genres. In the singers' world, crossover not only exists, but is increasingly accepted as an important part of the twenty-first century singer's training and preparation. But what of the singer's partner, the pianist and/or coach who will work with them side-by-side? How are pianists and voice coaches affected by the new trends in vocal repertoire? The authors talked with coach-conductors Kathleen Kelly and Stephanie Rhodes Russell about navigating crossover trends as pianists and coaches.
Bookshelf
Authors: Greschner Debra
Published: April 2024

Abstract: Debra Greschner reviews four recent publications. The Cambridge Companion to Amy Beach , which is comprised of contributions by editor E. Douglas Bomberger and ten other authors, provides an overview of the life and music of this American composer. Patricia Caicedo offers biographical information about two South American composers in collections of their art songs. The complete works of Argentinian Irma Urteaga and a song cycle by Colombian Jaime León include phonetic transcriptions and interpretative guidance. Advice for Young Musicians by Ian Howell is a collection of counsel for music students.
The Media Gallery
Authors: Berg Gregory
Published: April 2024

Abstract: This installment of "The Media Gallery" begins with a discussion about the pod-cast "Aria Code" hosted by Rhiannon Giddens. That is followed by a review of "The Reaction," a CD of art songs by Black composers with baritone Carl DuPont. The column concludes with the "Stilled Voices" section, remembrances of several important singers who died during 2023: Renata Scotto, Grace Bumbry, Virginia Zeani, Mildred Miller and Gabriele Schnaut.
МИФТІК КЕЙІПКЕРЛЕРМЕН КЕЗДЕСУ МОТИВІНІҢ КӨРКЕМ ШЫҒАРМАДАҒЫ ҚОЛДАНЫСЫ
Authors: Мусабекова С.Е. , Аймұхамбет Ж.Ә.
Published: April 2024

Бұл мақалада мифологиялық кейіпкерлермен кездесу мотивінің мистикалық шығармалардағы көрінісі талданады. Авторлар елесті, жезтырнақты, сайтанды, вампирді, пері қызын және вендигоны көркем туынды құрылымына енгізген қаламгерлердің шеберлігі мен авторлық идеясын анықтауға тырысады. Осы мотивті қолданған шетелдік авторлардың шығармаларымен салыстыра талдай отырып, олардың ұқсастықтары мен ерекшеліктері айқындалды. Зерттеу еңбектеріне сүйене отырып, мистикалық әдебиеттің шығу тарихы мен оның қоғам өміріндегі маңызына шолу жасалды. Әдебиеттегі мистиканың рөліне қатысты жарияланған отандық және шетелдік ғалымдардың зерттеулерін негізге ала отырып, мистицизмнің табиғатына қатысты тұжырымдар жасалды. Бір мистикалық мотивтің бірнеше халық әдебиетінде бір мақсатта қолданылатыны, әйтсе де әр жазушының өз ұлттық ерекшеліктерін сақтап қалатыны айқындалып отыр. Сонымен қатар әр дәуірде жазылған көркем шығармаларды талдау арқылы елеспен кездесу мотивінің қазақ әдебиетінде жылдар өте шеберлікпен қолданылып келе жатқаны дәлелденді. Зерттеу нысанына Ж.Аймауытовтың, М.Жұмабаевтың, М.Мағауиннің, Қ.Мүбарактың, Ш.Бейсенованың, С.Кингтің мифологиялық кейіпкерлермен кездесу мотивіне құрылған туындылары алынып отыр. Аталған жазушылардың шығармашылығында мифологиялық кейіпкермен кездесу арқылы авторлық позиция анықталды. Сонымен қатар ағылшын әдебиетінде жиі ұшырасатын вендигомен кездесу мотивінің тарихына тоқталып, оның көркем шығармадағы рөліне сипаттама берілді.
АБАЙДЫҢ ӘДЕБИ МЕКТЕБІ ЖӘНЕ КӨРКЕМ АУДАРМА МӘСЕЛЕЛЕРІ
Authors: Ердембеков Б.А. , Абсадык А.А. , Смагулова А.А.
Published: April 2024

Абайдың әдеби мектебі – қазақ әдебиетінде жаңашыл дәстүр әкелген, ұстаз бен шәкірт арасындағы шығармашылық байланысты дамытқан өнер мектебі. Сол арқылы ақын ізбасарларының әдебиеттегі орны айқындалды. Абайдың ақындық мектебі өкілдерінің аудармаға ден қоюы да тікелей ұстазының бағыт-бағдар беруімен жүргізілгені анық. Қазақ сахарасы алғаш рет Абай аудармалары арқылы орыс және батыс ақындарымен таныса бастаса, ақын шәкірттері осы дәстүрді жалғастырды. Мақалада Абайдың әдеби мектеп өкілдерінің көркем аудармаларына сараптама жұмысы жүргізілген. Абайдың көркем аударма жасауда көрсеткен үлгісі, аударма мәтіндердің көркемдік ерекшеліктері зерттеу жұмысының негізгі нысаны ретінде қарастырылған. Зерттеу барысында тарихи-салыстырмалы, диахроникалық талдау, идеографиялық зерттеу, сандық-сапалық контент анализ, библиографиялық параллель тәсілдері қолданылды. Абайдың «Евгений Онегин», Уәйіс Шондыбайұлының «Иванушка-дурачок», Шәкәрім Құдайбердіұлының «Дубровский», Турағұл Абайұлының «Челкаш» сынды  көркем аударма мәтіндеріне түпнұсқамен салыстырмалы талдау жасалып, зерттеу нәтижесінде «Иванушка-дурачок» поэмасының түпнұсқа авторы анықталып, Абайдың әдеби мектебі қазақ аударма саласының іргетасын қалаған алғашқы аударма мектебі ретінде нақтыланды. Сондай-ақ, Шәкәрім-Толстой шығармаларындағы рухани үндестік айқындалып, Турағұл Абайұлы аудармаларының көркемдік ерекшеліктері сараланды және Абайдың ақындық мектебі өкілі ретінде Жақын Садырбаевтың өмірі мен шығармашылығына, көркем аудармаларына қатысты тың мәліметтер ғылыми айналымға енді.
Incorporating the Time-synchronous Averaging Method into Vibration Analysis Methodologies for the Detection and Localization of Bearing Defects
Authors:   Electrical Engineering Department, University Mohamed Boudiaf, M'sila, Algeria, Ghemari Zine , Belkhiri Salah ,   Electrical Engineering Department, University Mohamed Boudiaf, M'sila, Algeria, Saad Salah ,   Electromechanical Department, Badji Mokhtar University, Annaba, Algeria
Published: April 2024

Objective: The objectives of this paper are to highlight the significance of vibration analysis, especially in predictive maintenance for rotating machinery, and to emphasize the importance of detecting bearing defects that may result in machinery failure. Methods: The proposed methodology combines the use of time-synchronous averaging (TSA) with existing vibration analysis techniques. TSA involves aligning vibration data with specific events or phases in the machinery's operation, such as shaft rotation. By synchronizing the data in this way, the methodology aims to reduce noise and enhance the signal related to bearing defects, making them more distinguishable. Additionally, the methodology incorporates well-established vibration analysis techniques. These techniques may include frequency analysis, amplitude modulation analysis, waveform analysis, and others commonly used in the field of condition monitoring and predictive maintenance. Results: The results of the analysis begin with waveform analysis, which involves examining the shape and pattern of vibration signals captured from the pinion. This analysis provides valuable insights into the dynamic behavior of the pinion gear, including any variations or abnormalities in its motion. Moreover, the use of synchronized waveforms is crucial in this analysis. By aligning the vibration data with specific events or phases in the gear mesh cycle, such as tooth engagement, the analysis can pinpoint moments when potential faults or wear in the machinery may occur. This synchronization allows for a more precise assessment of the vibration signals, enabling the detection of irregularities that may indicate underlying issues with the pinion or other components of the machinery. Conclusion: A pivotal aspect of the methodology involves envelope spectra analysis, significantly enhancing diagnostic capabilities. This analysis identifies fault patterns that might not be readily apparent in conventional vibration analysis. The incorporation of envelope spectra proves instrumental in proactive maintenance, enabling early detection of potential issues. This, in turn, contributes to the overall reliability and optimization of machinery performance.
Can ESG Ratings impact Accounting Performance: Evidence from Chinese Companies
Authors: Fang Yi
Published: April 2024

ESG (Environmental, Social, and Governance) considerations play a pivotal role as they epitomize a company's commitment to responsible practices and ethical conduct. The significance of ESG scores extends to their impact on accounting performance, serving as barometers of a company's adeptness in risk management, operational efficiency, and the cultivation of stakeholder trust. This research undertakes a comprehensive exploration into the influence of heightened ESG scores on the enhancement of accounting performance. The primary focus of this study revolves around the inquiry into whether elevated ESG scores yield tangible improvements in financial outcomes. By meticulously scrutinizing the dataset of A-share companies in China, the research aims to elucidate the correlation between elevated ESG scores and favorable financial results. The outcomes of this investigation firmly establish a positive nexus between elevated ESG scores and the attainment of superior accounting performance. It is evident that ESG practices wield a transformative influence on a company's operational landscape. By fostering enhanced efficiency, mitigating risks, and bolstering stakeholder confidence, these practices synergistically augment a company's overall operational framework. Moreover, this paper underscores the existing research gap in understanding the intricate relationship between ESG scores and accounting performance, underscoring the urgency for further exploration in this domain. The implications of these findings are profound, particularly for enterprises striving to optimize their financial success while upholding conscientious and ethical standards. As businesses navigate an increasingly complex global landscape, the integration of robust ESG practices emerges not only as a moral imperative but also as a strategic pathway to enduring financial prosperity.
A Preliminary Analysis of the Role of Intermediary Institutions in Capital Markets
Authors: Xie Tianjun , Xia Ran , Jin Qichen , Dong Haoran
Published: April 2024

On February 17, 2023, a substantial paradigm shift was ushered into the Chinese capital market as the China Securities Regulatory Commission declared a sweeping reform of the registration system. Under this fresh framework, the success of a company's listing and refinancing endeavors hinges not solely on its own operational vitality but also heavily relies on the expert services extended by a multitude of intermediary institutions. These include securities firms, legal counsel, accounting professionals, and appraisers. This research aims to penetrate the workings of these intermediary bodies, to gain a profound understanding of their pivotal role in the listing and refinancing processes of firms, and their instrumental position in fostering sustained growth and fortification of companies within the capital market. Our investigation endeavors to furnish both practitioners and scholars with a fresh perspective on the function of intermediary institutions amidst the backdrop of capital market transformations. The goal is to spur more effective and transparent market operations.
Digital Transformation and Firm Innovation Quality: Empirical Evidence Based on Listed Companies in China, 2011-2021
Authors: Chu Haiyu
Published: April 2024

The development of science, technology, and social progress has made digital development a new driving force for social development. National policies have driven the development of the digital economy and enterprise digital transformation. This paper examines the impact of enterprise digital transformation on the quality of innovation b using an Ordinary Least Squares (OLS) model and fixed effect model. The sample used includes A-share listed companies in Shanghai and Shenzhen from 2011 to 2021. The findings indicate that enterprise digital transformation can improve the quality of innovation in enterprises, and the results pass a series of robustness tests. This research analyzes the effect of digital transformation on the quality of innovation and its mechanisms at the level of listed companies. The analysis enriches the theory of enterprise digital transformation in innovation quality and provides research support for the high-quality development of enterprises.
Stake of shares, Stock liquidity and Listed company information disclosure violations
Authors: Chen Xuan
Published: April 2024

In recent years, due to the rapid development of China's domestic market economy, the financing method of equity pledge has played a very important position and influence among the main financing methods of listed companies due to its strong flexibility, simple transaction method and high efficiency. Based on the panel information of A-share non-financial listed companies in Shanghai and Shenzhen from 2016 to 2022, this paper studies the impact of equity pledge of controlling shareholders on corporate information disclosure violations, and explores whether equity pledge will affect corporate information disclosure violations by affecting stock liquidity. The results show that the equity pledge of the controlling shareholder will significantly improve the liquidity of stocks, thereby aggravating the company's information disclosure violations, and the stock liquidity will enhance the inducing effect of equity pledge on the company's information disclosure violations. Moreover, in non-state-owned enterprises, the impact of equity pledge of controlling shareholders on corporate information disclosure violations is more significant.
Research on the Influence of Sellers’ Responses on Brand Avoidance of Potential Consumers
Authors: Zhang Zixuan
Published: April 2024

In recent years, the development of online platforms has significantly expanded the dissemination of online reviews at an astonishing speed. The undeniable impact it has on consumers and sales necessitates addressing the issue of reducing brand avoidance behavior caused by negative reviews, which remains a prominent concern among academics and sellers. To enhance communication between sellers and consumers while minimizing misunderstandings, numerous platforms have introduced the sellers' responses function. With various types of sellers' responses available, different response strategies yield distinct effects. This paper aims to investigate how diverse seller replies influence potential consumers' brand avoidance by examining their classification and impact in conjunction with previous literature on factors influencing brand avoidance.
Research on the Contribution of Regional Digital Financial inclusion Based on PCA-ANN-MLP Algorithm
Authors: Su Pengyu , Wan Shijia , Zhu Dafu
Published: April 2024

Digital Financial Inclusion is a hot topic under the theme of China's economy today. Digital Financial Inclusion is an important supplement and extension of traditional Financial inclusion. Its core idea is to reduce the threshold of financial services and ease the financing difficulties of low-income groups, small and micro enterprises, and other vulnerable groups by providing low-cost and efficient financial services to the public. The empirical results of much literature show that digital Financial inclusion has narrowed the gap between the rich and the poor, which plays a vital role in the high-quality development of China's economy. Therefore, it is important to explore it's influencing factors and analyze the influencing mechanism. This study focuses on the three provinces in eastern China and applies the grounded theory approach. Utilizing data from the Peking University database, 17 factors influencing the level of digital inclusive finance are selected. PCA (principal component analysis) is used to reduce dimensions, and ANN-MLP (artificial neural network multi-layer perceptron) algorithm is used to explore the contribution factors of Digital Financial Inclusion, explore important factors, and put forward relevant suggestions. The significance of this study is that taking the three provinces in eastern China as an example, it explores the factors influencing the development of DFI in China, and makes an important contribution to the issue of how to promote the rapid development of digital Financial inclusion in China.
Product order-demand prediction model based on random forest
Authors: Wang Hao , Zhang He , Zhao Jia , Liu Xinyi , Feng Xinyue , Sun Yinuo
Published: April 2024

This study aims to develop a decision support model based on product order data analysis and demand forecasting. By analyzing the shipment data of a large manufacturing enterprise from September 2015 to December 2018, we establish an accurate prediction model for the demand in the next three months of a large manufacturing enterprise. Quarterly and monthly variables capture trends and seasonal variation by adjusting hyperparameters and cross-validation using a random forest algorithm. The results show that the mean absolute error (MAE) on the test set is 8.965, the root mean square error (RMSE) is 11.369, the relative mean absolute error (MAPE) is 8.256%, and the coefficient of determination (R²) is 0.826. These indicators confirm that the model can accurately predict the target variable, with little difference from the true value, and show good predictive power and fit. The monthly model has high accuracy and stability and can effectively support production and supply chain planning to meet future needs. This study confirms the potential of product order data analysis and demand prediction models to improve the efficiency and competitiveness of enterprises and provides a valuable reference for the research and practice in related fields.
Decision Analysis on Operation of Commercial Banks Based on the Application of Credit CDS
Authors: Wu Gengyue , Xia Kaiqian , Shao Jiayi , Tong Jingyi
Published: April 2024

Affected by the new crown epidemic, it is difficult for Chinese small and medium-sized enterprises to ensure the normal operation of the industrial chain in terms of business operation and development, which may lead to the inability to repay their loans in commercial banks in time, triggering credit default incidents. CDS is a new credit derivative instrument, which can alleviate the default risk held by creditors to a certain extent and enhance the trust of both borrowers and lenders. This paper tries to apply the CDS mechanism to the Chinese market, using the TOPSIS model to score some companies, and explore what types of corporate loans commercial banks need to use CDS products for risk mitigation. It is found that enterprises with poor profitability, small development prospects, high credit risk and weak solvency need to pay special attention to bank loans.