bluuebunny/crossref_metadata_2025 huggingface dataset:
Strengthening Wireless Network Security: Supervised Machine Learning-Based Intrusion Detection for Enhanced Threat Mitigation
Authors: Mohammad Taghi Sadeghi
Published: April 2024

With the wireless networks deemed vital to our laced and unetched world, it has become fundamental to safeguard these networks against the various cyber threats that are on the rise. As a research proposal I show concern about the application of a Supervised Machine Learning-Based Intrusion Detection system, making use of Multilayer Perceptron (MLP), Support Vector Machine (SVM), and Logistic Regression (LR) algorithms. The survey begins with the introduction of an intrusive inter-dataset technology that merges two catalytic datasets into a single efficient model that can address both model security and data sensitivity concerns. The evaluation of several machine learning algorithms within the proposed framework is a core component of the analysis. The accuracy measure as well as others such as recall, precision, and F1 score, are applied to evaluate the algorithms' level in detecting intrusions from different datasets.The investigation shows that the intra-dataset routing noticeably improves the detecting modules' efficiency. Notably, the model of MLP algorithm has enhanced recall which in turn shows the enhancement of the positive instance identification. SVM shows increased precision, which accounts for the improved accuracy since correct names of positive cases are produced more often. LR finds it overall enhance the precisions thus attesting to its efficiency in correct deductions. The research documents the multifaceted nature of IDS, prompting the intervention of the machine learning algorithms with ddoswdelcome intrusion detection system. A study which provides a practical guide for network administrators and security professionals hinting on how to select algorithms to meet the distinct security needs in their enterprises. These findings contribute to the open discourse on wireless network security and serve as a base for future study of this engaging research topic in constantly developing field of intrusion detection.
Enhancing Safety Management in UAE Construction Sites through Site Manager Performance Evaluation
Authors: Alzarooni Abdulla Omar
Published: April 2024

The construction industry is one of the most high-risk domains, having the highest number of occupational accidents compared to other industries globally. One of the main reasons for worker injuries and deaths is the site managers’ unsafe behaviour on the construction sites, which creates an environment that normalizes further unsafe acts and leads to the personnel's inability to recognize and identify various hazards within the construction site. This research aims to investigate and evaluate the site manager's contribution towards safety through specific indicators that include their safety-oriented performance, provision of safety equipment, and conduction of safety training. Data was collected from the workers and managers on construction sites through a comprehensive survey that constituted the three main mentioned indicators. The surveyed sample included 174 participants from different construction organizations across the UAE. The data was then analyzed using the 3-way ANOVA technique to study the relationship between the named three variables. Monte Carlo Simulation was used to study the uncertainty and variability of the interactions of the three factors in the construction site. The obtained results showed that the three factors were all statistically significant, indicating that the three independent variables had a positive effect on the safety score of the site manager. The interaction effect between the safety-oriented performance & provision of safety equipment was significant indicating that there was a combined effect between them on the safety score. A set of recommendations are provided to ensure more safety methods are implemented across the entire UAE construction sector.
A Note On Lie Symmetry Analysis, Optimal System,New Solitary Wave Solutions And Conservation Laws Of The Pavlov Equation
Authors: Hind Al-Bderi
Published: April 2024

In this essay, based on the Lie group analysis method, the investigation has been carried out on the symmetry properties of the (2 + 1)-dimensional Pavlov equation. Its maximal symmetry group in Lie's sense and the corresponding one-dimensional optimal system of subgroups are presented. Furthermore, by using Ibragimov's method which is a generalization of Noether's theorem, the conservation laws for the intended equation are determined. Finally, utilizing the traveling wave solutions method, some exact solutions of this nonlinear partial differential equation are constructed.
EEG-based Emotion Recognition: Assessing Misclassification Rates Using Machine Learning Techniques
Authors: CH Narsimha Reddy
Published: April 2024

Everyday human interaction heavily relies on emotions, which play a pivotal role in fostering genuine human-machine interaction. Emotional equilibrium is crucial for individual well-being, with regular meditation being a widely acknowledged means to achieve it. This study delves into the effect of meditation on emotional responses using Electroencephalography (EEG) technology. EEG can establish correlations between mental attributes and emotional states, with four emotions (Thrilled, Angry, Sad, and Relax) used as categorized stimuli based on valence-stimulation.

Functional connectivity in EEG brainwave activity is compared during these four emotions both before and after meditation sessions. Results demonstrate that meditation promotes more cohesive emotional experiences, albeit with a reduction in classification accuracy observed after an 8-week meditation regimen. This research utilizes EEG data to develop a classification system for discerning familiarity levels within EEG signals, employing the Hjorth Descriptor to condense signal characteristics into three distinct criteria. A Multilayer Perceptron classifier, leveraging input parameters, achieves a peak accuracy of 96% through a combined application of three functions.
Sun Stats: An IoT Node MCU Integrated Web Application with Real-Time Energy Monitoring and Cost Forecasting
Authors: Luizabelle V. Espenido
Published: April 2024

Rising global concerns about energy consumption and its environmental impact have fueled interest in renewable and sustainable energy sources, with solar energy emerging as a promising solution. In response to climate change challenges and the depletion of finite fossil fuel resources, there is a pressing need for innovative energy management solutions. This paper introduces "SunStats," an IoT NodeMCU integrated web application designed for real-time energy monitoring and cost (consumption) forecasting.

SunStats combines weather data and cost forecasting to provide tailored capabilities for local residential users. Integrating smart technologies and data-driven approaches, it aims to empower consumers with valuable insights into their energy consumption patterns.

It has a real-time energy monitoring feature, facilitated by the use of NodeMCU, allowing users to continuously track their energy consumption patterns. The user-friendly interface enables consumers to access real-time data on their electricity usage, facilitating informed decisions about energy management. Additionally, the application's integration of weather data offers contextual insights into how weather conditions influence energy usage, empowering users to adjust their consumption behavior accordingly.

Beyond real-time energy monitoring and weather integration, SunStats incorporates cost forecasting. Utilizing historical energy usage patterns and weather data, the application predicts future energy consumption for users. This forecasting feature provides consumers with valuable information about potential fluctuations in energy consumption, enabling effective planning and informed decision-making.

The primary goal of SunStats is to empower users to become proactive energy managers, offering transparency into real-time energy data, weather insights, and cost forecasts. This knowledge enables users to implement energy-saving strategies, optimize efficiency, and contribute to a more sustainable future.
Society 5.0 in Strategic Management Studies: A Systematic Literature Review (SLR)
Authors: Sulastini
Published: April 2024

The research abstract section should provide a brief overview of the main points discussed in the research review. This abstract of a systematic research review regarding the strategic management study of society 5.0 aims to provide an overview of the main themes, findings and implications of previous research in this area. This study focuses on conducting a systematic literature review regarding strategic management of society 5.0, following established methodology and guidelines. The research review aims to identify, study, evaluate and interpret all available research on strategic management of society 5.0 to understand the current state of knowledge in this field and identify potential research gaps. This review follows a systematic eight-step guide to conducting a literature review of information systems research. Society 5.0 is a new concept that refers to the integration of digital technology with society to overcome social challenges and improve the quality of life. Society 5.0 strategic management involves planning, coordinating, and implementing strategies to effectively utilize digital technology for the benefit of society. The abstract highlights the main objectives of a systematic research review regarding the strategic management of Society 5.0, including identification of research questions, selection and analysis of relevant research articles, and synthesis of qualitative findings.
Analyze of Education and Training Using Ship Engine Simulators at STIP Jakarta Indonesia
Authors: Abdul Rachman
Published: April 2024

On this research paper, we analyze Cadet Engineer, junior engineer, senior level Operational engineers, and senior management level engineers will carry out experiments using speed data from various scenarios on the ship engine simulator and then the experimental results will use educational and training analysis on the ship engine simulator to find out the right time. Later analysis also revealed that human errors occur due to the following reasons: Lack of knowledge of the overall system and fundamental operations, Insufficient confirmation of operations and Incomplete knowledge of the sequence of operations. the role of the instructor will be explained to reduce the causes of human error  and to improve educational performance according to the implementation and development of each scenario based on expert justification and reference to IMO and SOLAS Standards. various safety procedure scenarios for all Engineers in the hope of minimizing accidents that cause loss of life at sea. For the purpose of training engine plant operations using a PC-based Engine Room Simulator (ERS), describe the features of human errors by incompetent trainees in marine engine plant operations and demonstrate the necessary improvements in training to reduce such errors from an educational technology point of view. Examination of these data has shown that errors occur primarily due to errors of omission and inadvertent action. Further analysis was carried out on these errors by the engineer trainees to determine the characteristics of errors caused in the process of acquiring procedural knowledge for operations according to the implemented development of various safety scenarios.
Impact of Social Media Marketing on Brand Loyalty, through the mediating role of customer experience: An Applied Study in the Egyptian Private Hospitals
Authors: Mohamed Wagih Abd El Aziz
Published: April 2024

Social media marketing has developed rapidly in the world's contemporary highly competitive business environment in order to gain patient loyalty and competitive advantage by providing prompt services. For research scholars and practitioners, the marketing strategy that incorporates technological advancements has taken center stage. Effective communication and interaction between stakeholders are crucial to the success of a business, and social media platforms provide the venue for such communication and interaction. Thus, the benefits and risks of scientific communication on social media during COVID-19 are understood, and social media may be employed in such emergency scenarios. The purpose of this research is to empirically investigate the impact of social media marketing on brand loyalty with mediation role of customer experience in the Egyptian private hospitals. A questionnaire tool was employed to gather required data from a convienacne sample of 416 Customer of Egyptian private hospitals and structural equation modelling technique (SEM) was utilized for analysis using Spss 28 & AMOS26 software. The main conclusions drawn from this study are the direct effect between social media marketing and Brand Loyalty is statistically significant, the direct effect between Social Media Marketing and customer experience is statistically significant. The direct effect between customer experience and brand loyalty is statistically significant. Finally, the study found that there is partial mediation effect of the customer experience between the relationship of social media marketing and brand loyalty in the Egyptian private hospitals.
Reinforcement Learning Based Metaheuristic Algorithm For Optimized Load Balancing In Cloud Environment
Authors: Saravanakumar. K
Published: April 2024

In cloud computing, workload balancing remains a difficult issue, as overburdened or underburdened servers are capable of causing issues with computation speed or even cause an entire network to collapse, subsequently this is a scenario that is never supposed to occur when using the cloud. Therefore, in order to avoid these issues, the system should be load balanced—that is, allocate job across each of the accessible computing assets by taking into account an acceptable schedule of utilization. The Virtual Machines are supposed to be used effectively, in response to the distributed load mechanism. In this work, a multifaceted load balancing optimization based on the Enhanced Firefly algorithm (EFA) with a Partial Order Markov Decision (POMD) process algorithm is proposed as an autonomous job allocation strategy in cloud computing. In order to overcome the limits of concurrent considerations, the suggested solution seeks to maximise VM productivity, streamline task allocation and the use of resources, and provide load balancing amongst virtual machines based on Time to Finish, expenditure, and consumption of resources. Using CloudSim, the performance study of the suggested approach was contrasted with the load balancing algorithms now in use in datasets like Google Cloud Jobs (GoCJ). According to the trial results, the suggested POMD-EFA strategy performed better than the other algorithms in terms of decreasing the Time to Finish, minimizing expenses, and increasing the efficiency in the application of resources.
Underwater Imagery Enhancement with Multi-Channel Histogram Equalization, Depth-Adaptive Correction, and Deep Reinforcement Learning
Authors: S.Daniel Madan Raja
Published: April 2024

Underwater imagery plays a pivotal role in various scientific, industrial, and recreational applications, ranging from marine biology and oceanography to underwater archaeology and resource exploration. However, capturing high-quality images in underwater environments poses unique challenges due to factors such as light attenuation, color distortion, and particulate matter suspended in the water. In recent years, significant advancements have been made in the development of advanced techniques for enhancing underwater imagery aimed at improving perceptual quality, sharpness, and detail preservation. This research explores state-of-the-art enhancement techniques, focusing on multi-channel histogram equalization and depth-adaptive correction in the context of deep reinforcement learning (DRL) and variational autoencoders (VAE). The research presents a comprehensive analysis of the performance of these techniques using numerical metrics such as perceptual quality, sharpness, and detail preservation, derived from experimental evaluations. The findings demonstrate the effectiveness of VAE in enhancing perceptual quality and sharpness, with underwater image dehazing exhibiting commendable results as well. Furthermore, Convolutional Neural Networks (CNN) emerge as a promising approach for detail preservation in underwater images. By advancing the capabilities of underwater image enhancement techniques, this research contributes to the broader goal of unlocking the full potential of underwater exploration and understanding. The findings reveal significant improvements in image quality achieved by these techniques. VAE exhibits the highest perceptual quality scores, averaging around 0.84, with sharpness scores reaching approximately 0.91.
Enhancing Healthcare Data Security Using Quantum Cryptography for Efficient and Robust Encryption
Authors: C. Bagath Basha
Published: April 2024

Healthcare requires data encryption to safeguard sensitive patient information from unauthorized access or breaches. Encryption ensures that data is encoded into a secure format, making it unreadable to anyone without the decryption key. This helps maintain patient privacy, protects against identity theft, and ensures compliance with data protection regulations like HIPAA (Health Insurance Portability and Accountability Act.). With encryption, healthcare organizations can mitigate the risk of data breaches and uphold trust with patients by ensuring the confidentiality and integrity of their medical records and personal information. Quantum cryptography emerges as a revolutionary solution, offering unparalleled encryption for healthcare data. This process initiates with the meticulous crafting of quantum states to encapsulate healthcare data securely, ensuring precise encoding. Subsequently, quantum entanglement is established between sender and receiver, creating a secure communication channel resistant to interception attempts. Quantum key distribution then generates a secure key leveraging entangled quantum states, becoming the cornerstone of encryption. Quantum encryption shields healthcare data in an impenetrable veil of secrecy, leveraging the complexities of quantum mechanics to thwart unauthorized decryption attempts. The decryption process, facilitated by the shared secure key, unveils the encrypted healthcare data exclusively to authorized parties, preserving confidentiality with unparalleled precision. The result reveals quantum cryptography's superiority in healthcare data encryption. At 150-bit key length, quantum cryptography takes 352,237 milliseconds vs. AES's 310,285 milliseconds. For a 14 KB input, quantum cryptography requires 7 milliseconds compared to AES's 12 milliseconds. These metrics highlight quantum cryptography's efficiency gains and transformative potential in healthcare data security, promising both enhanced security and efficiency benefits.
Dynamic Object Detection in Surveillance Videos using Temporal Convolutional Networks and Federated Learning in Edge Computing Environments
Authors: J.J.Jayakanth
Published: April 2024

This research addresses the importance of advancing dynamic object detection in surveillance videos by introducing a novel framework that integrates Temporal Convolutional Networks (TCNs) and Federated Learning (FL) within edge computing environments. This research is motivated by the critical need for real-time threat response, enhanced security measures, and privacy preservation in dynamic surveillance scenarios. Leveraging TCNs, the system captures temporal dependencies, providing a comprehensive understanding of object movements. FL ensures decentralized model training, mitigating privacy concerns associated with centralized approaches. Current challenges in real-time processing, privacy preservation, and adaptability to dynamic environments are addressed through innovative solutions. Model optimization techniques optimize TCN efficiency, ensuring real-time processing. Advanced privacy-preserving mechanisms secure FL, addressing privacy concerns. Transfer learning and data augmentation enhance adaptability to dynamic scenarios. The proposed system not only addresses existing challenges but also contributes to the evolution of surveillance technology. Comprehensive metrics, including accuracy, sensitivity, specificity, and real-time processing metrics, provide a thorough evaluation of the system's performance. This research introduces an approach to dynamic object detection, combining TCN and FL in edge computing environments. Results show accuracy exceeding 97%, sensitivity and specificity at 97% and 98%, and F1 score reaching 96%.
Optimizing Energy-Efficient Communication Protocols for IoT Devices in Smart Cities Using Narrowband IoT and LTE-M Technology
Authors: D.Hemanand
Published: April 2024

In the context of optimizing energy-efficient communication protocols for IoT devices in smart cities, this research addresses the pressing need for sustainable and reliable solutions. The research provides a comprehensive understanding of the strategies that contribute to minimizing energy consumption in smart city IoT deployments, with a specific focus on Narrowband IoT (NB-IoT) technology. Employing a structured framework and an integrated system architecture, incorporating LTE-M technology and an application server, the research leverages various optimization strategies. These include Adaptive Power Control, Duty Cycling, Data Aggregation, Protocol Optimization, and Network Topology Optimization. Methodologically, the study adopts a quantitative approach, utilizing metrics such as duty cycle percentages and energy consumption reductions. Data is collected through simulations and experiments, and the analysis involves assessing the impact of each optimization strategy on energy efficiency. Key findings demonstrate significant reductions in energy consumption, ranging from 15% to 25%, depending on the specific strategy employed. Adaptive Power Control and Network Topology Optimization emerge as particularly effective approaches. The implications of these findings underscore the importance of adopting tailored optimization strategies in smart city IoT deployments to achieve both energy efficiency and reliability. The study discusses the broader significance of these results and acknowledges potential limitations, paving the way for future research endeavors in the realm of sustainable and resource-conserving smart cities.
The Application of Flipped Classroom Based on the Fias Analysis Model in the Online Teaching of Piano Art Instruction
Authors: Xueying Liu
Published: April 2024

This research investigates the use of the Flipped Classroom (FC) approach, based on the Flanders Interaction Analysis System (FIAS) analysis model, in the online teaching of piano art instruction. The FIAS analysis model is used to analyze the key factors that influence the effectiveness of the flipped classroom approach. The study uses a mixed-methods research design, combining surveys and interviews with students and teachers to gather data on the effectiveness of the flipped classroom approach. The study used piano theory for analysing the interaction analysis. The results indicate that the FC approach, based on the FIAS analysis model, can significantly improve student engagement and learning outcomes in online piano art instruction. The study also identifies several challenges and limitations of the approach, such as the need for adequate preparation time and the need for students to have access to suitable technology and resources. In this study, we have used ANOVA method to analyse the data. Overall, the study provides insights into the potential benefits and challenges of the FC approach in online piano art instruction and offers recommendations for future research and practice.
Wireless Power Transfer System for the Intelligent Video Monitoring and Analysis Based on the Safety of Power Grid Construction Site
Authors: Feng Zhang
Published: April 2024

This study describes a power grid construction site surveillance system that includes wireless power transmission and an improved Yolo V3 detection model. An artificial intelligence and wireless power transfer methodology is employed used for continuous monitoring. Improved Yolo V3 detection is optimized using Hierarchical Particle Swarm Optimization (HPSO) for enhanced efficacy in detecting power grid development threats. The methodology is compared to existing methods in terms of precision, accuracy, recall, and speed. The findings indicate that the proposed method is achieved a real-time and accurate power grid development site monitoring. Experiments on test sets in various situations improved the detection accuracy, and indicate that the proposed technique is quite robust. Also the detection accuracy and speed of the proposed method have improved over existing approaches, indicate that the strategy provides superior detection efficacy. This method considerably improves risk source detection, that's critical for assuring safety on power grid building sites.
End Effect Reduction by Modification Design of End Teeth for Linear Induction Motor
Authors: Syafitri Ainil
Published: April 2024

Using linear induction motors for magnetic trains has challenges in maintaining stability and safety, namely the emergence of holding forces. The force arises due to the magnetic flux interaction between the permanent magnet and the iron core. One source of resisting force is due to the dotted lines, which creates a finishing effect and generates vibration and noise from the system. Previous research has carried out several works, one of which is designing the shape of a gear at the end of a tooth with a convex curved shape in a linear synchronous motor which has succeeded in reducing the effect of the tip of the tooth. This study aims to determine the results of the effectiveness of calculations using MATLAB, which can produce much less resistance. This research uses descriptive research with a qualitative approach. In this study the calculations to redesign the shape of the dental arch at the end of the track were carried out by making a model with a parabolic approach. Plane dimensions X, Y, Z 660mm x 360mmx 360 mm. Magnetic density data were collected using Ansys software and 10 mm meshing, while the magnitude of the resistive force based on mathematical equations was carried out using MATLAB software. Investigation of the effect of curvature for the final effect value has been carried out using 6 models with different arcs. From the simulation, it is concluded that the sharpener for bow curvature gives the smallest resistance force value. The smallest result from the calculation A=A_x+y^' A_y  gives the smallest detention force value. The smallest computation of A=A_x+y^' A_y  with the sharpest curvature is a challenge to build and use for real activities.
Russian operational art for attrition in Ukraine
Authors: Çakıroğlu Ali Cenk
Published: April 2024

Originally intended as a swift regime-change operation by the Russian leadership, the Russo-Ukrainian War has evolved into a prolonged war of attrition. In that sense, this paper reassesses the transformation of the Russian way of warfare during the war through a focus on the battles of Severodonetsk-Lysychansk, Kharkiv, Kherson, Bakhmut, Avdiivka, and the Ukrainian Summer Offensive. Accordingly, the theoretical underpinnings of Russian strategy, particularly the enduring influence of Soviet-era legacy, are highlighted in the first part. In the second part, this research offers insights into the Russian military praxis during the war by drawing on various sources, including Telegram channels. It is shown that the Russian army has focused on the combined employment of a new reconnaissance-fire system (ROS), reconnaissance-strike system (RUS), infantry assaults, and umbrella of integrated air defence and electronic warfare systems for force protection and attrition during costly offensives like Bakhmut and Avdiivka. Consequently, this paper asserts that the Russian war machine effectively responded to the necessities of attrition warfare by updating its operational art, drawing on the Soviet legacy.
Complications following surgical treatment of ankle fractures in the elderly: can they be avoided?
Authors: Welzel Lukas , Omar Mohamed , Müller Christian Walter
Published: April 2024

Background

Following surgical treatment of ankle fractures, geriatric patients face high complication rates (CR) in literature. Commonly used diagnostic and treatment algorithms fail to consider requirements of ageing patients which increases the risk of postoperative complications.

Objective

Present study critically evaluated surgical management of ankle fractures in patients over 65 years old, with focus on identifying modifiable risk factors and effective comorbidity management strategies.

Methods

We conducted a retrospective single-center study on patients who underwent surgical treatment of an ankle fracture. Based on their age, participants were divided into non-geriatric patients (NGP<65y) and geriatric patients (GP≥65y). We analyzed overall CR and number of minor and major complications in relation to timing of surgery, biological sex, injury pattern, osteosynthesis, pre-existing medical conditions, and postoperative care.

Results

402 patients were included. GP encountered significantly higher overall (p<0.001), minor (p<0.001) and major (p=0.003) complications. They presented more complex, displaced and open fractures. Predominant factor contributing to higher CR in NGP and markedly in GP was concomitant diseases, presenting a strong OR of 19,290 (p<0.001) and 17,022 (p<0.001). Delaying surgery and managing comorbidities preoperatively had a favorable impact.

Conclusion

We revealed a high significant correlation between pre-existing medical conditions and postoperative results. To ascertain viability of delayed surgery in facilitating additional diagnostics and treatment of comorbidities, further comparative trials with a larger cohort are imperative.
Developing a Guide for a Mathematics Teacher Preparation Program: An Evaluation Study
Authors: Saleh Shoeb , ALALI Rommel
Published: April 2024

This study aims to evaluate and develop the mathematics teacher preparation program at the College of Education in Sohag, utilizing a set of national and international standards. The primary objectives include diagnosing the current state of the program, establishing clear goals, standards, and skills for mathematics teacher preparation, and identifying strengths and weaknesses. The evaluation results highlight notable strengths, such as the presence of experienced faculty members with diverse backgrounds and the program's success in fostering positive attitudes towards the teaching profession. Additionally, the availability of various laboratories enhances students' academic and professional readiness. However, the study also identifies important weaknesses, including a traditionalist approach that fails to keep pace with current advancements. The objectives and standards of the program are found to be unclear and general, lacking specificity in the desired skills and competencies for teacher preparation. The study further reveals a lack of comprehensive descriptions and objectives for academic courses, insufficient emphasis on incorporating educational innovations into the curriculum, and a weak connection between the scientific content of the program and practical teaching applications. Additionally, the evaluation methods employed in the current program are deemed in need of development and diversification, as they primarily focus on rote memorization rather than measuring deeper understanding and application of knowledge. The creation of a comprehensive guide for the "Mathematics Teacher Preparation Program" underscores the crucial role of teachers as fundamental elements in the educational process. The guide has been meticulously developed using scientific methods, aiming to address a gap in the internal regulations of the College of Education in Sohag. It serves as a valuable resource for all individuals involved in the preparation of Mathematics Division students at the college, particularly those who will graduate and embark on careers as mathematics teachers. The guide presents the methodological components of mathematics teacher preparation in a manner that reflects systemic thinking, ensuring a cohesive and well-rounded approach to training future educators in the field of mathematics
Toward re-founding the learning of literature fn the competence approach
Authors: Damyanova Adriana
Published: April 2024

The paper examines 181 comparisons of the interpretations of a given themes in two literature texts, one of which is unstudied, carried out by high school students, insofar as it is assumed that it is through such tasks that the degree of mastery of a specific competence can be assessed. Several typical skill deficits manifested in task performance are differentiated, their causes are sought, and some opportunities for optimizing the assessment toolkit are suggested – with the hope of supporting efforts to reoriented literature education from learning and reproducing knowledge to mastery of literary competences.
A model for reading instruction to students with limited proficiency in Bulgarian language
Authors: Radkova Antonia
Published: April 2024

The article analyzes the characteristics of the reading the context when the reader lacks complete communicative and language proficiency. Within this framework, the text introduces a motivating and instructional reading model tailored for this specific audience. It further offers various reading strategies and practices designed to assist both educators and students who are learning Bulgarian in environments where language exposure is limited or absent.
Interaction between language diciplines in secondary school to improve students’ reading skills
Authors: Milanova Evelina
Published: April 2024

The article explores the possibilities of implementing cross-curricular connections in language disciplines in secondary school in order to improve students’ skills in perceiving information from written texts. An approved methodical version of a lesson is presented where students in the 12th grade solve communicative tasks, based on their knowledge of the Bulgarian language, first and second foreign language and civic education.
ANALYZING THE PERCEPTION OF STUDENTS ABOUT HYBRID LEARNING PROGRAM IN UNIVERSITIES
Authors: Munir Hina , Mumtaz Huma , Naseer Samra
Published: April 2024

The study's objective was to determine how students felt about university blended learning programs. This study looked at evidence showing how blended learning affects students' perceptions. The study's population of concern included all social sciences students from 2-universities in Multan district (Bahauddin Zakariya University & Women University). Sample of study comprised 360 students from social sciences faculty, 30 students were selected from each department. Questionnaire was developed for students. The questionnaire contains 25 items for students' perception and a five-point Likert scale was used for scoring. Statistical methods were applied to obtain findings about student reactions like %, mean, frequency and SD was used to apply and examine the perception of students about blended learning program. It was found that majority of participants believe that blended learning helps make students independent, inspired, confident & more effective. Students should participate in training program to improve ability to use technology in blended learning & regular feedback sessions should be encouraged.
THE EFFECT OF CSR ON EARNINGS MANAGEMENT: MODERATING ROLE OF BOARD DIVERSITY IN PAKISTANI LISTED FIRMS
Authors: Ashfaq Khurram , Anjum Muhammad Naeem , Zafar Muhammad Raza
Published: April 2024

This study examines Corporate Social Responsibility (CSR) and Earnings Management (EM) relationship with moderating role of board diversity of two types, i.e., female and foreign directorships on board. Content analysis is used for measurement of CSR through a data sample of 274 firms from the non-financial sector listed on Pakistan stock exchange for years 2012, 2014, and 2015. However, EM is measured over three discretionary accruals models Jones, Modified Jones, and Kothari models. Based on the results of descriptive analysis, it has been found that the level of CSR reporting has been improved in the post-CSR guidelines period as compared to the pre-CSR guidelines period. While results of regression analysis report that the higher CSR level of an organization the lesser would be the EM activities. This study suggests managers to concentrate upon CSR and board diversity for better earning management. Impact of board diversity on relationship as a moderator makes this study more novel because, as far as our research and previous literature is concerned, there has been very limited literature on this topic.
ЖАҢЫЛТПАШТАРДАҒЫ КӨНЕРГЕН СӨЗДЕРДІҢ ЭТНОПОЭТИКАЛЫҚ МӘНІ ЖӨНІНДЕ
Authors: Дәуітұлы Т. , Матыжанов К.С. , Жылқыбекұлы Б.
Published: April 2024

Мақалада жаңылтпаштар табиғатында жиі кездесетін көнерген сөздердің (архизмдер) мәтінінің ұлттық ерекшеліктерін көрсететін этонпоэтикалық маңызы қарастырылады. Бір қарағанда жаңылтпаштардағы мұндай этнолингвистикалық мазмұнға бай сөздер ұйқас үшін алынған сияқты көрінгенмен, шын мәнінде олар мәтіннің этнопоэтикалық мәнін айқындауға ерекше қызмет етеді. Жаңылтпаштарда көшпелі өмірдің мәдени-әлеуметтік, қарым-қатынас құралы ретінде қолданылатын сөздердің, бұл күнде көп бөлімі қолданыстан түсіп архизм сөздерге айнала бастады. Бүгінгі жаһандану заманында халықтың әдет-ғұрпы, салт-дәстүрі, діні, қолөнерінің күнделіктегі өмірдегі қолданыстан ығысуына байланысты, оларға қатысты ұғым-түсініктер де қазіргі лексикада сирек айтылатын болды. Міне осындай ұлттық тілдің тарихи ерекшеліктерін білдіретін сөздер жаңылтпаштар құрамында жиі кездеседі. Мұндай сөздер балаларға тілдің нәрін түсіндіріп, ұлттық ділді қалыптастыруға  қызмет етеді. Демек жаңылтпаш фольклорлық жанр ретінде, ең алдымен, ұлттың дәстүрлі дүниетанымынан, тарихи ерекшеліктерінен тамыр тартқан этнолингвистикалық сөздік қорымен суарылған шығармашылық болып табылады. Сол антропологиялық мифология дәуірінен кейін мал шаруашылығын толық игеріп, нақты өмірлік түсініктер қалыптасқан кезеңде, өмірге келген фольклорлық жаңылтпаштардағы:  «қалаш, сыпыра, ұшқат, бақан, желмая, серке, торта, мосы, бурыл, қулық, торы, боқжама, құрық, баспақ» сияқты сөздердің ерекшеліктері, әлеуметтік мәні, көркемдік айшықтары, бір-бірімен ара қатынасы, мазмұны нақты мысалдармен дәйектеледі. Сондай-ақ, жаңылтпаштар мазмұнындағы сөздердің тарихи тамырластығы, архетиптік негізі мен тек-тамырының бірлігі анықталады.
THE ISSUE OF MODERN KAZAKH POSTMODERNISM AND NEO-MYTHOLOGISM IS IN THE ASPECT OF NATIONAL KNOWLEDGE (BASED ON THE STORIES OF A. KEMELBAYEVA)
Authors: Abdullina А.В. , Yildiz N. , Sarsenbayeva Zh.B.
Published: April 2024

The article considers the development of the postmodernism in Kazakh, Russian, and French literature. The research is based on M. Epstein’s theory about the formation of the direction of post-Soviet postmodernism. The theoretical basis of the study was considered in the light of the opinions of such researchers as N. Kuchina, S. Sheyanova, Ye. Zinurova, M. Gontar, A. Maulenov, S. Takirov, S. Altybayeva, N.Syzdykbayev, D. Kaliakbar, B. Syzdykova, A. Kairbekova, B. Orazova. The practical significance of the article is determined within the framework of studying the direction of postmodernism in modern Kazakh literature. The means of the direction of postmodernism which have social, philosophical significance, were considered through the phenomenon of intertext. The main means of the phenomenon of intertextuality are the transfer of methods of simulacrum, reminiscence and postmodernism through mythical plots. The stories “Konyrkaz (Grey goose)”, “Tyrnak (Claw)”, “Yesim (Name)”, “Kosmos (Space)” by A. Kemelbayeva, who contributed to the development of postmodernism in Kazakh literature, are analyzed. The techniques of flexible postmodernism dictate the writer's ability to portray society. The paper describes the role as a national code and highlights the ethnographic character while examining issues with folk understanding, national knowledge, and legendary beliefs in the stories of A. Kemelbayeva from the perspective of intertextuality. The author’s use of mythological knowledge in her novels is examined within the context of contemporary postmodern literature and the neomiphologism dilemma. Postmodernism’s foundational concepts of mythical cognition and understanding are portrayed in a nostalgic, retrospective light, taking into account the unique characteristics of the narrative form. The article’s fundamental thesis is that the theory of the hybrid genre in the contemporary narrative system, transformation, is based on the field of neomyphologism.
Analysis of Jewelry Brand Marketing Management Strategies Based on Consumer Psychology
Authors: Parfonova Sophia
Published: April 2024

With the continuous improvement of China's economic level, non essential goods such as jewelry have entered households, and the output value of the jewelry industry has been increasing year by year. Jewelry consumption has played a crucial role in people's livelihood consumption. At the same time, under the conditions of economic globalization, brand marketing has always played an important role as an important medium for interaction and communication between enterprises and consumers. The development of technology has gradually diversified the forms of information dissemination, and corporate marketing methods are also catering to the changes in the Internet. With the development of the times and the popularization of e-commerce, consumers' psychology and behavior have undergone significant changes, which will directly affect the development of traditional jewelry business models. Consumer psychology plays a crucial role in the development of marketing activities, and it is necessary to fully consider the actual needs of the situation, conduct research on consumer psychology in different eras, populations, and geographical environments, provide corresponding information support for marketing activities, and ensure the effectiveness of marketing work. Based on this, this article analyzes the marketing management strategies of jewelry brands under the influence of consumer psychology.
The essence of accounting under the sustainable development view
Authors: Tao Feng
Published: April 2024

About the nature of accounting, different people have different opinions in the academic circle. The classic theories mainly include management activity theory, information system theory, business language theory and so on. With the prosperity of economy and the progress of society, sustainable development has gradually become the goal pursued by enterprises and society. Under the concept of sustainable development, society's expectation on accounting has also changed, and only reflecting economic value can no longer meet the needs of enterprises and society. Enterprises and society expect accounting to provide sustainable value that fully reflects the combined benefits of environment, society and governance. Therefore, under the concept of sustainable development, accounting in essence should be a tool to comprehensively determine the sustainability value of an organization by measuring the input of economic capital, environmental capital and social capital and the value created by each of them in a special way. The understanding of the essence of accounting has also expanded from the traditional economic management system to a larger sustainable system.
Risk Management Case Analysis of ICBC's "Crude Oil Treasure" Incident
Authors: Wang Zeyuan
Published: April 2024

Driven by the marketization of interest rates and technological innovation, commercial banks in China continue to innovate various financial services businesses and devote more attention to attracting customers to purchase various investment and wealth management products in order to expand sources of bank performance and gain more benefits. In 2018, paper crude oil-linked wealth management products emerged. Paper crude oil products are linked to the prices of international crude oil futures contracts. The products feature controllable risks and relatively high returns, which are very popular among large numbers of customers. However, despite the continuous expansion of China's financial derivatives trading volume, the categories of derivative products and regulation still have many limitations. The development of innovative paper crude oil-linked products is not perfect and has many potential risks, which are highly susceptible to market fluctuations. Taking China Bank's "Crude Oil Treasure" product as the research focus, this paper analyzes the massive loss incident that occurred in late April 2020 through case study analysis and qualitative analysis methods. It is divided into four parts. The introduction part explains the research background, significance, content, methods and innovations and inadequacies of this paper. The first part sorts out the background and process of the "Crude Oil Treasure" case at China Bank and elaborates on the operating principles of this product. The second part analyzes the "Crude Oil Treasure" case in detail. It first focuses on the problems in the product's trading liquidity, domestic and international time differences and product promotion. Then it focuses on the internal and external causes of the case, discussing external factors such as international crude oil market turmoil and futures trading characteristics, and internal factors such as product design, risk control and lack of experience. It also evaluates the hedging strategy, contract design and compliance of the "Crude Oil Treasure" product. The third part mainly analyzes the impacts of the "Crude Oil Treasure" rollover incident and China Bank's subsequent response measures. The fourth part puts forward certain countermeasures and suggestions from the perspectives of bank management, investors and regulatory agencies to prevent such incidents from recurring based on the case analysis.
A study on the innovation efficiency of high-tech listed companies in China - Analysis based on three-stage DEA with Malmquist index
Authors: Guo Guanlin , Chen Zixin , Xu Tongchun
Published: April 2024

In order to adapt to the changing market environment, enterprises need to continuously conduct innovative R&D activities, and innovation efficiency has become a key factor for high-tech enterprises to capture the market. This paper uses a three-stage DEA model and the Malmquist index to measure and analyze the technical efficiency of 60 high-tech enterprises in China from 2013-2021. The findings show that environmental factors have a significant impact on the technical efficiency of enterprises, pure technical efficiency is underestimated and scale efficiency is overestimated, and scale efficiency should be improved by expanding production scale; high-tech enterprises face contradictions between scale efficiency and technical efficiency, and policies drive the technical level to improve, but the comprehensive technical efficiency does not grow. Technological innovation during the epidemic has improved the technical level and utilization efficiency, but the comprehensive technical efficiency still declined. This paper is of great significance in assessing the efficiency of high-tech enterprises between technological inputs and market output, helping them to identify room for improvement and enhance innovation efficiency and competitiveness.