bluuebunny/crossref_metadata_2025 huggingface dataset:
AIGC Fusion Exploration: The Intersecting Path of Digital Humanities and Artificial Intelligence
Authors: Jing Sun
Published: April 2024

The burgeoning field of Digital Humanities has experienced remarkable growth, catalyzed by advances in computing technology and the increasing digitization of cultural artifacts. This paper delves into the dynamic interplay between digital humanities and artificially intelligent generated content (AIGC), exploring their intersection and transformative potential. Through a comprehensive literature review, we highlight the multifaceted landscape surrounding AIGC, including biases, ethical considerations, technological advances, and societal implications. Drawing on insights from cutting-edge studies, we propose a methodology for fusion exploration that aims to elucidate the synergies between digital humanities and AIGC. Our proposed methodology integrates an overview of AIGC with copyright issues, emphasizing the ethical dimensions and regulatory frameworks necessary for responsible content creation. We also delineate the intersection of digital humanities and artificial intelligence, focusing on two key aspects: the ideographic qualities of literary language and the expression of literary language through digital rhetoric. By synthesizing insights from the diverse scholarly endeavors, we underscore the transformative potential of integrating Digital Humanities and AIGC, paving the way for innovative research paradigms and collaborative engagement in academia and beyond.
Application of computer data model in the characteristics and evolution of ceramic decorative painting
Authors: Wang Wei
Published: April 2024

With the rapid development of computer technology, computer information technology has made intelligent transformation to all industries. It is particularly important to optimize the computerization of ceramic painting. This paper analyzes the development of ceramic decorative painting and the basic principle of computer data model, determines the method of combining ceramic decorative painting with computer data model, and establishes a computer data model for feature extraction of ceramic decorative painting. And 1015 images of self-made ceramic decorative paintings are applied to carry out simulation analysis. The results show that compared with the traditional classification algorithm based on non deep learning and the partial classification algorithm based on deep learning, the average F1 value of the hybrid neural network model is 96.4%, which is 1.5% higher than the best traditional model. This shows that the designed computer data model for feature extraction of ceramic decorative painting has a good effect on the classification and feature recognition of ceramic painting. This has laid a certain foundation for the computerized optimization of ceramic decorative painting and provided a good support for the healthy development of ceramic decorative painting in the information age.
Masked Statement Classification in Conversational Text
Authors: Shivanshu Singh, Vidushi Singh, Yogesh Nikita Singhal, Rupali Bagate, Devansh Bhadauria,
Published: April 2024

Sarcasm can be really tricky for computer programs that analyze text to understand people’s feelings and opinions. This is because sarcasm involves saying something with the opposite meaning of what you actually feel, often to make fun of a situation. When computers analyze text, they focus on the words used rather than the intended meaning, which can lead to mistakes in how the text is categorized. Sarcasm also creates problems when trying to figure out the author’s true emotions in tasks like sentiment analysis. So, there is a need of a way to identify sarcasm in text and correct the sentiment it conveys. Recent studies have employed deep learning and machine learning methods to identify sarcasm. Deep learning is quite powerful, but traditional machine learning methods are still widely used and can work as well if trained properly. This study aims to compare different algorithms like Long Short Term Memory (LSTM), K-Nearest Neighbors (KNN), Computational Neural Network(CNN), and Artificial Neural Network(ANN) etc to see how well they work in sarcasm detection. The survey examined several systems and algorithms for detecting sarcasm, as well as any faults or drawbacks associated with these approaches. It also discusses various important challenges and future directions for sarcasm detection research in order to provide useful insights in this field
Examining the Advantages, Limitations, Opportunities, and Challenges of AI Implementation in Libraries
Authors: Ashsish Kumar Dubey Priyadarshini,
Published: April 2024

Libraries will benefit greatly from the incorporation of artificial intelligence (AI), but they will also face substantial hurdles. It is therefore essential to carry out a thorough SWOT analysis that assesses the organization's opportunities, threats, weaknesses, and strengths. This abstract explores the potential uses, hazards, restrictions, and advantages of artificial intelligence in library environments. The study intends to provide useful insights into the strategic factors that libraries must take into account while implementing AI technologies by carefully examining these aspects.The study attention to the challenging terrain of integrating AI in libraries and stresses the significance of taking a comprehensive approach to fully utilize its potential while managing related dangers. Important tactics include improving system efficiency and tackling issues with algorithmic bias and privacy.Essentially, the goal of this study is to clarify the many ways that AI is being used in libraries. It emphasizes how important it is for libraries to thoroughly consider the effects of implementing AI and to create solid plans to maximize its benefits while avoiding any negative effects. By doing this, libraries can ensure responsible and ethical implementation processes while simultaneously positioning themselves to take advantage of the revolutionary prospects presented by AI.
Enhancing Automated Test Case Generation Through KNN algorithm in Software Testing
Authors: Suhaila Zainudin Abdulrahman Ahmed Khudhur, Ibrahim Mohamed,
Published: April 2024

In the ever-evolving world of software development, assuring the stability and resilience of software systems remains a vital task. This study aims to tackle this problem by suggesting a novel method for generating automated test cases. It involves incorporating the robust KNN algorithm into the domain of data mining methods. The research intends to exploit previous testing data to detect patterns and trends, increasing the production of effective and targeted test scenarios.

The literature study highlights the increasing overlap between data mining and software testing, underscoring the need for sophisticated methods to address the requirements of contemporary, ever-changing applications. In this regard, our study presents the KNN algorithm as a new addition to the collection of data mining tools for software testing. The process entails gathering extensive historical testing data, including information on test cases, errors, and the attributes of tested software applications. By using rigorous preprocessing and feature selection techniques, the KNN method is used to examine the correlations between various variables and the probability of flaws. The KNN model is trained and optimized using the dataset, and the resultant predictions are then used in an automated system for generating test cases. The experimental results confirm the efficacy of the suggested method in finding crucial test scenarios and prioritizing test cases according to past fault trends. The practical usefulness and advantages of incorporating the KNN algorithm into the automated test case-generating process are further confirmed by real-world case studies. In conclusion, this study expands the discourse on data mining in software testing by proposing the KNN algorithm as a vital component in automated test case development. By using KNN, testing teams can adjust to the ever-changing characteristics of contemporary applications, leading to enhanced efficiency and effectiveness in testing procedures. The results of this research enhance the continuous development of software quality assurance methods and provide opportunities for additional investigation at the convergence of machine learning and software testing
Exploring AI-driven Innovations in Image Communication Systems for Enhanced Medical Imaging Applications
Authors: Satyanarayan Kanungo, Tolu Adedoja, Sourabh Sharma Suresh Dodda,  Suman Narne, Sathishkumar Chintala,
Published: April 2024

Artificial intelligence (AI) has emerged as a promising avenue for enhancing medical imaging systems and improving clinical workflows. This research explores innovative applications of AI and deep learning for image communication networks in healthcare. Specifically, we develop an intelligent image compression framework that optimizes data transmission and speeds interpretation of radiology scans. Our approach combines convolutional neural networks, generative adversarial networks, and specialized image filters to balance communication efficiency, diagnostic accuracy, and system latency. Rigorous experiments validate superior performance over traditional methods and commercial products across modalities including MRI, CT, and ultrasound. Crucially, the proposed methods demonstrate expert-level precision in anatomy labeling and pathology detection. By intelligently streamlining image transfer and analytics, this AI-powered system could facilitate ubiquitous, real-time diagnostics via telemedicine. Enhanced connectivity between imaging devices and clinical specialists can improve patient outcomes and reduce healthcare costs. Our solutions set the stage for more advanced AI integration in imaging networks and data-intensive medicine
Impact of Network Size on Routing Protocols Performance in Wireless Sensor Network: A Simulation
Authors: Kanojia Sindhuben Babulal, Bobby Sharma, Vikas Rathi Prasanta Pratim Bairagi, Gaurav Kataria, Mala Dutta,
Published: April 2024

Wireless sensor networks (WSNs) are a decentralized kind of network which is equipped with sensor nodes and is rapidly being utilized to intelligently monitor different environmental conditions at a minimal cost. Sensor nodes are often battery-powered and the essential issue to address is how to decrease node energy consumption so that the network lifetime may be prolonged to realistic lengths. Routing is one of the primary operations performed within the network which consumes a sufficient amount of energy. Therefore, it is very much essential to consider the finest routing protocol so that it consumes less energy. In this article, we look at several routing protocols used in WSNs, including AODV, DSDV, DSR, OSLR and M-GEAR. Furthermore, we studied the execution of selected protocols based on network factors such as network latency, packet delivery ratio, and network throughput against multiple network sizes. The simulation findings show that protocol performance varies depending on network size and that selecting the optimum protocol based on network parameters is also crucial.
AUTOMATED GARBAGE SEPARATION USING AI BASED ROBOTIC ARM
Authors: Rajeshree Shinde, Shridevi Vasekar, Vaishali A. Patil Jayashree P. Tamkhade, Anup Ingale, Ketki P. Kshirsagar,
Published: April 2024

This paper aims to present an automated garbage separation system using a deep learning approach and integrating it with a robotic arm. The system is designed to separate different types of garbage, such as plastics, metals, and glass, based on images captured by sensors and analyzed using a deep learning model. The system is then integrated with a robotic arm that picks up and sorts the garbage based on the model's predictions. This system involves data collection, preprocessing, model building, training, testing, and deployment, as well as robotics engineering and sensor technology. The system has potential applications in waste management and recycling, including municipal waste management, recycling facilities, industrial waste management, landfills, and smart cities. It aims to improve the efficiency, accuracy, and safety of waste management systems and promote sustainability.
Multi-camera Vehicle Tracking and Recognition with Multimodal Contrastive Domain Sharing GAN and Topological Embeddings
Authors: D.S. Rao Rakhi Madhukararao Joshi,
Published: April 2024

Tracking vehicles across a city using a network of multiple cameras are pivotal for enhancing urban and traffic management systems. However, this task is riddled with challenges such as wide geographical coverage, frequent view obstructions, and the diverse appearances of vehicles from various angles.

To address these complexities, the proposed solution, dubbed Overlapped Vehicle Detection and Tracking using Multimodal Contrastive Domain Sharing Generative Adversarial Network optimized with Efficient Multi-camera system (MCDS-GAN), leverages cutting-edge techniques from computer vision, image processing, machine learning, and sensor fusion. This advanced system detects and tracks vehicles even in scenarios where multiple camera views overlap, making it applicable across domains like traffic management, surveillance, and autonomous vehicles.

The methodology involves utilizing datasets like Common Objects in Context and ImageNet for training. Detection and tracking are performed using the Multimodal Contrastive Domain Sharing Generative Adversarial Network, followed by vehicle re-identification facilitated by the Topological Information Embedded Convolution Neural Network (TIE-CNN).

Moreover, optimization techniques are employed to ensure synchronization and efficiency within the system. Implemented in Python, the effectiveness of MCDS-GAN is rigorously evaluated using metrics such as Accuracy, Precision, Recall, Latency, Response Time, and Scalability. Simulation results showcase its superiority, achieving significantly higher accuracy rates compared to existing methods such as OC-MCT-OFOV, MT-MCT-VM-CLM, and TI-VRI.
Deep Learning and Natural Language Processing Technology Based Display and Analysis of Modern Artwork
Authors: Yongjun Li Xiongfei Li,
Published: April 2024

The modern artwork analysis display system, empowered by natural language processing (NLP) technology, revolutionizes the way audiences interact with and understand art. By integrating NLP algorithms, this system offers a dynamic and user-friendly platform for analyzing and displaying artwork. Utilizing NLP, visitors can engage in interactive conversations with the system, asking questions or making inquiries about the artwork on display. The system processes these inquiries, extracting relevant information from curated databases and scholarly sources to provide insightful and context-rich responses. Additionally, NLP algorithms can analyze textual descriptions, artist statements, and critical reviews to offer nuanced interpretations and historical context for each artwork. This paper presents the design and implementation of an innovative modern artwork analysis and display system, leveraging deep learning and natural language processing (NLP) technology, integrated with Multi-Feature Extraction Fuzzy Classification (MFEFC). The system offers a comprehensive platform for analyzing and presenting modern artworks, enhancing user engagement and understanding. Deep learning algorithms are employed to extract high-level features from visual artworks, allowing for automatic recognition of artistic styles, genres, and themes. Concurrently, NLP techniques process textual descriptions, artist biographies, and critical reviews to provide contextual information and interpretative insights. The integration of MFEFC enables precise classification of artworks based on multiple features extracted from both visual and textual sources, facilitating accurate analysis and categorization. Simulation of the NLP techniques demonstrated an average precision of 90% in extracting relevant contextual information from textual descriptions and artist biographies. Furthermore, MFEFC achieved a classification accuracy of 88% in categorizing artworks based on combined visual and textual features.
Cloud Based Ccmc Model for Application of Genetic Algorithm Based on Cloud Computing in Art Product Design
Authors: Ouyang An
Published: April 2024

Art design has entered a new era with the integration of cloud computing technology, revolutionizing the creative process and expanding artistic possibilities. By leveraging the vast computational power and storage capabilities of cloud platforms, artists can explore innovative techniques, collaborate with peers remotely, and access a wealth of digital resources from anywhere in the world. Cloud computing enables artists to work with large-scale datasets, create complex visualizations, and render high-resolution artworks with ease. Moreover, cloud-based tools and applications offer flexibility and scalability, allowing artists to experiment freely and iterate rapidly. Whether creating digital paintings, 3D animations, or interactive installations, cloud computing empowers artists to push the boundaries of their creativity and bring their visions to life in ways previously unimaginable. This paper presents an innovative application of genetic algorithm (GA) leveraging cloud computing technology for art product design, with a focus on the Centralized Clustering Middle Chain (CCMC) framework. By harnessing the computational power and scalability of cloud platforms, GA facilitates the optimization of design parameters to generate novel and aesthetically pleasing art products. The CCMC framework streamlines the design process by centralizing data clustering and analysis, enabling efficient exploration of design space and identification of optimal solutions. Through simulated experiments and empirical evaluations, the effectiveness of the GA-based approach in art product design is assessed. Results demonstrate significant improvements in design quality and efficiency, with the GA-enabled cloud computing solution achieving a 40% reduction in design iteration time and a 30% increase in product innovation compared to traditional methods.
Virtual Simulation Experimental Teaching of E-Commerce Course Based on Short Video
Authors: Xiangping Wang Lili Sun,
Published: April 2024

The e-commerce course based on short videos offers a dynamic and accessible learning experience tailored to the fast-paced world of online business. Through concise and engaging video modules, students gain practical insights into various aspects of e-commerce, including market analysis, digital marketing strategies, website development, and customer relationship management. This papers explores the implementation of virtual simulation experimental teaching in an e-commerce course, utilizing short video modules as the primary instructional tool, enhanced by Stacked Ranking Regression Classifier (SRRC). The research aims to enhance student engagement and comprehension by integrating virtual simulations with short video content, providing an immersive and interactive learning experience. Through simulated experiments and empirical validations, the efficacy of SRRC-enhanced virtual simulation teaching methods is evaluated. Results demonstrate significant improvements in student performance and satisfaction compared to traditional teaching approaches. Simulation analysis of students exposed to SRRC-enhanced virtual simulation teaching reported a 25% increase in comprehension levels and a 30% improvement in engagement metrics. Additionally, the SRRC model facilitates personalized learning experiences tailored to individual student needs, leading to enhanced learning outcomes. These findings underscore the potential of virtual simulation experimental teaching with SRRC in revolutionizing e-commerce education and fostering student success.
An Effective Energy Production and Analysis In A Solar Tracking System
Authors: D. Menaka Praveen P. N.,
Published: April 2024

PV cells are widely used for the purpose of capturing solar energy and converting it into electricity. Throughout the day, as we know, the Earth moves from west to east and the seasons change, the angle at which its radiation from Sun hits the Earth also changes. Consequently, the output power of PV panels fluctuates. When PV panels are oriented parallel to the sun's path, their output voltage increases. The aim of this research is to enhance the efficiency of solar tracking systems by minimizing mechanical tracking errors and reducing energy consumption. To achieve this, a PID controller is employed, which is based on the Oppositional-based Chimp Optimization Algorithm (OChOA). The system implements and simulates four energy-saving strategies. The simulation results illustrates that the proposed controller achieves a tracking error of 0.0541o and an energy consumption of 3.56879 Wh, surpassing the performance of existing techniques.
Form Check: Exercise Posture Correction Application
Authors: Phani Varma Gadiraju, Dhruvraj Tondanoorthy Morarjee Kolla,
Published: April 2024

Weightlifting is a popular sport and a hobby of millions; however, the risk of injury is high, primarily when performed with incorrect form/posture due to voluntary or involuntary reasons. It results in a significant loss of strength and hinders progress. The gradual strain on tendons and ligaments causes wear and tear. This paper aims to develop a deep learning model that detects incorrect posture and provides insight into remedial steps that need to be taken to correct the same, thereby providing increased safety and efficiency. Our Form Check model detects a user's form, vector geometry of posture is evaluated and corrected. A graphical representation of the exercise is provided as feedback to the user. Object detection, pose estimation, and action recognition algorithms infer the human skeleton and recognize the exercise. The inconsistency in the exercise performed is determined and mapped to specific imperfections in the stance of users during the exercise through Graph
Multi-Objective Optimal Allocation of Hybrid Photovoltaic Distributed Generators and Distribution Static Var Compensators in Radial Distribution Systems Using Various Optimization Algorithms
Authors: Zellagui M., Belbachir N., El-Sehiemy R.A., El-Bayeh C.Z.
Published: April 2024

In recent years, considerable growth was about the integration of renewable energy sources in the Radial Distribution Systems (RDS), as Photovoltaic Distributed Generators (PVDG) due to their importance in achieving plenty desired technical and economic benefits. Implementation of the Distribution Static Var Compensator (DSVC) in addition to the PVDG would be one of the best choices that may provide the maximum of those benefits. Hence, it is crucial to determine the optimal allocation of the devices (PVDG and DSVC) into RDS to get satisfactory results and solutions. This paper is devoted to solve the allocation problem (locate and size) of hybrid PVDG and DSVC units into the standards test systems IEEE 33-bus and 69-bus RDSs. Solving the formulated problem of the optimal integration of hybrid PVDG and DSVC units is based on minimizing the proposed Multi-Objective Function (MOF) which is represented as the sum of the technical-economic parameters of Total Active Power Loss (TAPL), Total Reactive Power Loss (TRPL), Total Voltage Deviation (TVD), Total Operation Time (TOT) of the overcurrent relays (OCRs) installed in the RDS, the Investment Cost of PVDGs (ICPVDG) and the Investment Cost of DSVCs (ICDSVC), by applying various recent metaheuristic optimization algorithms. The simulation results reveal the superiority and the effectiveness of the Slime Mould Algorithm (SMA) in providing the minimum of MOF, including minimization of the power losses until 16.209 kW, and 12.11 kVar for the first RDS, 4.756 kW and 7.003 kVar for the second RDS, enhancing the voltage profiles and the overcurrent protection system. Moreover, the ability to reach the optimal allocation of PVDG and DSVC and maintain the voltage profiles in the allowable limit, whatever the load demand variation.
Homonym Detection Using WordNet and Modified Lesk Approach for English Language
Authors: D. V. Kodavade Madhuri P. Karnik
Published: April 2024

Word sense disambiguation (WSD) is a basic and persistent problem that has existed since its inception in the natural language processing (NLP) area. The process of determining the accurate meaning of a word within a specific context is referred to as word sense disambiguation, commonly known as WSD. In NLP, a single word can have two or more meanings, with each meaning being distinguished by its context. This is known as word polysemy. Its applications span a wide range of fields, such as question answering systems, machine translation, information retrieval (IR) etc. Ontology and NLP are still struggling with ambiguity. Homonyms, which are ubiquitous in most languages, are words that have the same spelling but a different meaning. This method's fundamental premise is to select the appropriate sense by comparing a word's context in a sentence to contexts generated from WordNet.  The primary goal of this study is to employ WordNet and the Lesk algorithm for WSD. After the algorithm was put into practice and tested on a collection of sentences that included ambiguous words, the synset was able to determine the proper interpretation for most of the sentences. The Lesk algorithm relies on finding the highest number of shared words (maximum overlap) between a word’s context, prepositions and the definitions for its different meanings(glosses). This approach helps in identifying the most accurate interpretation for a given word within a specific context. According to experimental findings, the suggested strategy considerably boosts performance while identifying homonyms.
Auto encoders with Cellular Automata for Anomaly Detection
Authors: SSSN Usha Devi N Pokkuluri  Kiran Sree,Prasun Chakrabarti,Martin Margala,
Published: April 2024

This work combines auto encoders with cellular automata (CA) to present a novel hybrid strategy for anomaly identification. For feature learning, auto encoders are used to identify spatial patterns in the input data. Simultaneously, temporal and geographical dependencies are captured by CA, which improves the model's capacity to identify complicated anomalies. Training on spatially altered data, the auto encoder-CA hybrid model makes use of CA's temporal evolution to reveal dynamic patterns. Reconstruction errors between the input data and its decoded representation are computed to identify anomalies. A comprehensive framework for anomaly identification is provided by the synergy between spatial-temporal analysis of CA and auto encoder-based feature learning. Performance is optimized by fine-tuning the model's parameters, which include the auto encoder architecture and CA setup. The hybrid model's dynamic adaptation ensures robustness over time by accommodating changing data distributions. Evaluation measures show how well the suggested method captures abnormalities that appear in both temporal and geographical dimensions. A promising method for identifying abnormalities in complicated datasets with detailed spatial and temporal patterns is presented by this novel combination of auto encoders and cellular automata. The proposed method is evaluated with various parameters like reconstruction error, precision , recall, F1 score and Area Under the Receiver Operating Characteristic (ROC-AUC). The average accuracy is reported as 97.36% which is promising when compared with baseline methods.
Unraveling The Trifecta of Governance, Sustainability, And Technological Advancements in India
Authors: Dr. Raja Roy Choudhury *Ms. Isha Joshi, Dr. Pratima Jain,
Published: April 2024

This paper delves into the complex interplay of innovation, governance, sustainability, and technological advancements within the unique context of India, aiming to unravel the intricate dynamics that define the nation's development landscape. As India positions itself on the global stage, understanding the synergies and challenges inherent in these three critical domains becomes imperative for sustainable socio-economic progress. The status paper commences by introducing the significance of the status paper, emphasizing the symbiotic relationships between innovation, governance, sustainability, and technological advancements. The multifaceted exploration encompasses historical perspectives, contemporary policies, and case studies that exemplify the nation's endeavors to create a robust innovation ecosystem. Examining the evolution of innovation and governance in India, the paper highlights pivotal policies such as "Make in India" and "Startup India," showcasing the government's commitment to fostering a culture of innovation. The review also scrutinizes sustainability challenges faced by India, underscoring environmental concerns and resource depletion. However, it reveals instances where sustainability has been seamlessly integrated into innovation ecosystems, citing examples like the National Solar Mission and waste management initiatives. The status paper concludes by summarizing the paper's key findings, emphasizing the need for an integrated approach to policymaking and industry practices. This research contributes valuable insights to policymakers, researchers, and industry stakeholders, guiding India toward a more sustainable and innovative future.
The effect of the European Central Bank’s asset purchase programmes on Spain’s public finances
Authors: Aguilar Pablo A. , Alloza Mario , Costain James , Hurtado Samuel , Martínez-Martín Jaime
Published: April 2024

This paper empirically quantifies the effect on Spain’s public finances of the asset purchase programmes implemented in the euro area between 2015 and 2022. Specifically, it evaluates the impact of the ECB’s Asset Purchase Programme (APP) and Pandemic Emergency Purchase Programme (PEPP) on Spanish public revenue, expenditure, deficit and debt. The results suggest that these programmes have had a significant cumulative downward effect on the level of public debt.
Popularity of Social Networks Among Armenian Users
Authors: Karapetyan A. A.
Published: April 2024

Now there is active debate about the influence of virtual (online) communication on real (offline) communication. Do online and offline communications complement each other, or will online communication gradually completely replace real (offline) communication, including in the professional and personal life of a modern person? If people stay at home and go about their daily activities without interacting with other members of society and this suit them, then they will not make efforts to create social connections outside the online sphere, and the field of real (offline) relationships is completely or significantly transformed. The article discusses: the spread of social networks among Armenian users, online and/or offline communication preferences of Armenian users in one or another area of life, depending on age, gender and the subject of communication. As a result of the study, conducted by questionnaire, preferences were identified on the basis of which users build online communication, which determines the purposes of using social networks in Armenia.

The research was carried out with the financial support of Yerevan State University according to the scientific project “Mechanisms of dissemination and consumption of fake news in social networks”, 2022-2024. The article was prepared according to the International Academic Mobility Program, organized by the National Research Institute of the Communications Development for young scientists from foreign countries.
Features of Socio-Political Processes in Abkhazia (Abkhaz ASSR) in the 1930–1940s
Authors: Kobakhia K. D.
Published: April 2024

The article examines Stalin’s repressions in Abkhazia in the 1930s and 1940s. The author revealed the specifics of socio-political processes that took place under the influence of Stalinism. As a result of the study, the main directions of Stalin’s repressive policies in Abkhazia were identified. Attempts to destroy the political and cultural elite, infringe on the rights of Abkhazians and other peoples living in Abkhazia are described in detail. Official data on the forced change of the ethnic composition of the population and the persecution of representatives of the political elite are provided, as well as the conditions of Georgian-Abkhazian interaction during this period are analyzed. The author drew a conclusion about the tragic impact of Stalin’s repressions on the development of the Abkhazian statehood, the preservation of national identity, as well as the construction of Georgian-Abkhazian relations.

The article was prepared according to the International Academic Mobility Program, organized by the National Research Institute of the Communications Development (Moscow) for young scientists from foreign countries.
Iskanderkul Expedition of 1870: Contribution of the Russian Orientalist A.L.Kuhn to the Preparation and Editing of the «Diary of the Iskanderkul Expedition» by A.Mustajir
Authors: Odinaev A. N.
Published: April 2024

The article is devoted to the analysis of the Iskanderkul expedition of 1870, organized with the aim of exploring little-known territories along the eastern border of the Zarafshan district and the southern border of the Syrdarya region. The main attention is paid to the role of the orientalist A.L.Kuna in conducting the expedition and his contribution to the preparation of the “Diary of the Iskanderkul Expedition” Mirza Mullah “Abd ar-Rahaman, son of Muhammad Latif Mustajir. The article notes the strategic importance of this expedition for Tsarist Russia and emphasizes the role of A.L.Kuhn, who has deep knowledge of Eastern cultures and languages. He paid special attention to the language and culture of the Tajiks of the Zarafshan Valley. The article highlights the relevance of cooperation between Russian researchers and local authors for the study and preservation of the cultural heritage of Central Asia in the context of geopolitics, ethnography and language studies. The Iskanderkul expedition and A.Mustajir’s “Diary” are important sources for the study of history, ethnography, spiritual culture and socioeconomic conditions of life in the upper reaches of Zarafshan in the second half of the 19th century. This study is relevant for understanding the historical and cultural context of Central Asia, especially the upper reaches of Zarafshan.
The Impact of the Cold War on the Afghan Society
Authors: Poghosyan V. A.
Published: April 2024

The article is devoted to the policies of the global players of the Cold War using the example of Afghanistan. Noting the features of the Afghan policy of the Cold War, the author highlighted the key content of the very concept of the Cold War, political events in Afghanistan, internal and external challenges, ethnic problems and the problem of women during the Cold War. The influence of geopolitical processes on the development, internal and external interests of Afghan society in the 20th century, the social, economic and political consequences of the Cold War, features of the development of the political system and political culture of Afghanistan, ethnic problems in Afghan public discourse, etc. are considered. The author concludes that “The Cold War of the superpowers had a direct impact on internal political developments in Afghanistan, where parties and public organizations emerged as political structures with secular or Islamic ideology. The author comes to the conclusion that the internal political unity of Afghan society was not ensured for the reason that the Afghan elite was unable to form an ideology expressing national unity, and its individual parts preferred to serve the interests of one or another player without supporting the national interests of Afghanistan.

The article was prepared according to the International Academic Mobility Program, organized by the National Research Institute of the Communications Development (Moscow) for young scientists from foreign countries.
Foreign Policy Directions of the Republic of Azerbaijan
Authors: Ayvazyan D. S.
Published: April 2024

The article examines the key directions of the foreign policy of the Republic of Azerbaijan. The main foreign policy partners of Azerbaijan (Russia, the Republic of Turkey, Iran, the USA and the European Union) were identified, and current issues of interaction with these countries were analyzed. A conclusion is drawn about the multidirectional nature of Azerbaijan’s foreign policy and the desire for pragmatic economic cooperation at the regional and macro-regional levels. In the field of security, military and militarytechnical cooperation, Azerbaijan, in followup the 44-day war in Nagorno-Karabakh in 2020 and then the dissolution of the unrecognized Nagorno-Karabakh Republic, after January 1, 2024, strengthens cooperation with the Republic of Turkey. For Azerbaijan, the importance of creating regional transport communications and intensifying economic cooperation with its closest neighbors has increased.
Russia and South Ossetia: Factors Influencing Cooperation in the Field of Education
Authors: Gagieva A. L. , Komleva V. V.
Published: April 2024

The article analyzes Russian-South Ossetian cooperation in the field of education, in which great importance is paid to integration and internationalization. Characteristics are given to the official documents that make up the legal framework of this cooperation. The role of ministries and departments in the development of international educational interaction is shown. Various forms of cooperation are considered: scientific projects, the opportunity to enter Russian universities, joint Olympiads, competitions, conferences. The article pays more attention to the role of South Ossetian State University in the development of educational, scientific and social cooperation. The article reveals the role of interuniversity interaction in the development of Russian-South Ossetian cooperation. Non-governmental organizations and their projects play an important role in this process. Russian-South Ossetian cooperation demonstrates a wide range of opportunities and the growing potential for mutually beneficial activities in the field of education.

The article uses the materials of the annual monitoring of the communication regimes of post-Soviet countries. Monitoring is provided by the National Research Institute for the Communications Development (Moscow).
Crystal sediment profile in the urine of public transportation drivers on route 2 in Kupang city
Authors: Ledoh Yaksem Yohanis , Djuma Agustina Welhelmina , Kapitan Lely Adel Violin
Published: April 2024

Background: Drivers have a profession that requires prolonged sitting, leading to the release of bone calcium into the bloodstream, which can trigger the formation of urinary stones or nephrolithiasis. Urinary stone (nephrolithiasis) is a condition where stones form in the urinary tract. Objectives: The aim of this study was to describe the crystal sediment profile in the urine of public transportation drivers on Route 2 in Kupang City. Materials and Methods: This descriptive study involved 16 public transportation drivers on Route 2 in Kupang City as research subjects. Data were collected through interviews.  Results: The results showed the presence of various crystals in the urine sediment, including Calcium Oxalate crystals (25%), Calcium Carbonate crystals (18.75%), Uric Acid crystals (12.5%), and Amorphous crystals (6.25%).  Conclusions: Based on the characteristics and habits of the respondents, it was found that frequent urinary retention, drinking less than 1 liter of water per day, and consuming supplemented or carbonated drinks were the three main factors affecting urine sedimentation in public transportation drivers on Route 2 in Kupang City.
AMERİKA’DA AİLE VE BOŞANMA ARABULUCULUĞUNA YÖNELİK UYGULAMA MODEL STANDARTLARI
Authors: Fırat Erhan
Published: April 2024

Alternatif uyuşmazlık çözüm yöntemlerinden arabuluculuk Amerikan hukuk sisteminde önemli bir yer tutmaktadır. Bu anlamda, bireyler arasındaki uyuşmazlıkların çözümünde aile arabuluculuğu da sıkça tercih edilen yöntemlerden biridir. Nitekim Amerika’da eyalet hukukları incelediğinde aile arabuluculuğu müesesesine ilişkin düzenlemelere sıklıkla rastlamak mümkündür. Söz konusu düzenlemelerde aile arabuluculuğunun kapsamlı bir şekilde ele alındığı görülmektedir. Diğer taraftan, eyalet hukukları dışında aile arabulucuğuna dair çok sayıda özel düzenleme de bulunmaktadır. Bu özel düzenlemelerden biri de çalışmamızın konusunu oluşturan Aile ve Boşanma Arabuluculuğuna Yönelik Uygulama Model Standartları adlı hukuki düzenlemedir. Bu düzenleme Amerikan Barolar Birliği Delegeler Meclisi tarafından son değişikleriyle birlikte 2001 yılında yayınlanmıştır. Bilindiği üzere aile arabuluculuğu ülkemiz açısından da uzunca bir süredir gündemdedir. Dolayısıyla çalışmamızda bu düzenlemenin tarihsel gelişim sürecine ve hükümlerine değinilerek Türk hukuku için böyle bir düzenlenin yararlı olup olmayacağı üzerinde durulacaktır.
MARKA KORUMASINDA TESCİL VE ÖNCELİK İKİLEMİ ÜZERİNE YARGITAY VE ABAD KARARLARI IŞIĞINDA BİR İNCELEME
Authors: Bozgeyik Hayri , Tabur Fatih  Mehmet
Published: April 2024

Çatışan fikri mülkiyet haklarından hangisine üstünlük tanınacağı sorunu marka hukuku açısından önemini korumaktadır. Marka hukukunun temel ilkelerinden olan öncelik, SMK 155’in yürürlüğe girmesinden sonra tescil ilkesi karşısında daha üstün bir hak olarak kabul edilmiştir. Bu çalışmada marka kavramı ile tescil ve öncelik ilkeleri incelenmiş ve marka hakkının mahiyeti ile bunun bir başka tescili engelleme etkisi araştırılmıştır. Konu SMK öncesi dönemdeki yargı uygulaması, bu dönemde ileri sürülen görüşler, karşılaştırmalı hukuktaki uygulamalar ve Avrupa Birliği Adalet Divanı kararları çerçevesinde ele alınmış ve nihayet SMK 155 ile birlikte ortaya çıkması muhtemel sorunlar irdelenerek, çeşitli önerilerde bulunulmuştur.
YAPI DENETİM FİRMALARININ DEPREM NEDENİYLE ÜÇÜNCÜ KİŞİLERİN UĞRADIĞI ZARARLARDAN SORUMLULUĞU
Authors: Bölükbaşı Özge
Published: April 2024

Yapı denetimi, can ve mal güvenliğini temin etmek maksadıyla, yapıların yürürlükteki yapı mevzuatına, mevcut standartlara ve teknik kurallara uygun olarak inşasının denetim yoluyla sağlanmasıdır. Denetimler, 29.06.2001 tarihinde kabul edilen 4708 sayılı “Yapı Denetimi Hakkında Kanun” gereği yapı denetim firmaları tarafından gerçekleştirilmektedir. 4708 sayılı Kanun’da yer alan düzenlemeler sebebiyle, daha ziyade yapı denetim firmalarının yapı malikine ve idareye karşı sorumlulukları tartışılmaktadır. Zira, Kanun’un üçüncü maddesinde firmaların, yapı denetimi hizmet sözleşmesi ile borçlandıkları denetim faaliyetlerine aykırı davranmaları halinde, yapı malikine ve idareye karşı verdikleri zararlardan hukuken sorumlu oldukları düzenlenmektedir. Oysa ki, yapıların sağlıklı ve güvenli inşası sadece yapı malikini değil, yapıdan zarar görme ihtimali olan herkesi ilgilendirmektedir. Özellikle firmaların özensiz ve eksik denetimi nedeniyle yapının depremde zarar görmesi, o yapı ile hukuki bağı bulunan kimseleri maddi ve manevi olarak etkilemektedir. Bu sebeple çalışmamızda, yapı denetim firmalarının, denetim faaliyetleri sebebiyle depremde hasar alan yapıların üçüncü kişilere verdiği zararlardan doğan hukuki sorumluluğunu araştırmak, bu sorumluluğa dikkat çekmek ve etki eden diğer halleri de göz önünde tutarak sorumluluğu her açıdan değerlendirmek amaçlanmaktadır.
Research on the impact of human capital on economic growth in China 's provinces based on panel data model
Authors: Dai Yan , Zhou Shuchang
Published: April 2024

Because human capital can promote economic development, promote social progress and achieve sustainable development, it plays an important role in Chinese modernization. Therefore, it is of great significance to study the impact of human capital on economic growth. This paper first constructs the index system, and uses the Topsis entropy weight method to comprehensively score the indicators ; then, a 25-year panel data model of 31 provinces ( cities ) in China from 1997 to 2021 is established. Through F test, Breusch-Pagan test and Hausman test, a variety of panel data models are selected. It is found that the individual time point double fixed effect model has a good regression fitting effect on the relevant data. Therefore, this model is selected to analyze the impact of education human capital and health human capital on economic growth, and it is found that both education human capital and health human capital have a significant role in promoting economic growth, but the role of education human capital is more obvious. When education human capital changes 1 unit, China 's economic growth will change 0.105 units. When health human capital changes 1 unit, China 's economic growth will change 0.09 units.
Research on the Enhancement of Technological Innovation Ability in Greater Bay Area By Computer Science and Technology Talent Resource Sharing
Authors: Ji Wei , Chen Biaoxin , Gan Hanying
Published: April 2024

The Greater Bay Area Science and technology talent Pool system developed in this paper is a Web database system, its purpose is to realize the sharing of science and technology talent resources in the Greater Bay Area. Improve the efficiency and informatization of scientific and technological personnel management. Using JAVA based JSP, Java Servlet, Java Bean and JDBC technology, the separation of application presentation layer, application layer and data layer is realized. This system uses the "connection buffer pool" technology to improve the efficiency of database access.
Research on the Reform of College Students' Employment Guidance Curriculum from the Perspective of the Internet
Authors: Liang Zhao , Zhang Xiaolin
Published: April 2024

This paper explores the optimisation path of college students' career development and employment guidance courses in the context of the Internet era. With the advent of the Internet era, college students' employment faces more opportunities and challenges. This article first analyses the impact of the Internet on college students' employment, including more employment and entrepreneurship opportunities, more diversified employment choices, higher employment ability requirements, and more comprehensive employment guidance. Then, the article points out the major problems in the construction of career development and employment guidance courses for college students, including the lack of awareness of the importance of employment guidance courses for college students in colleges and universities, the vague content of the courses, the imperfect system, the unified form of teaching, the lack of practical teaching, and the lack of capacity of teaching staff. Finally, this paper puts forward the optimisation path for the construction of college students' career development and employment guidance courses in the Internet era, including deepening teaching reform, strengthening team building, cultivating a good campus culture and other suggestions. Through the research of this paper, we aim to provide effective ways and strategies for colleges and universities to improve the quality of talent cultivation and solve the employment difficulties of college students.