bluuebunny/crossref_metadata_2025 huggingface dataset:
Nutzung von Machine Learning in der intelligenten Fabrik
Authors: Gutsche Katja , Peric Benjamin , Hummel Jonas , Engler Michael
Published: May 2024

The use of machine learning is associated with great hopes for the realization of a smart factory. This article aims to highlight the Potenzial and obstacles to the use of machine learning in real-life industrial manufacturing scenarios in the European economic area. Technical, organizational and current legal framework conditions are categorized. Finally, the article presents a tool that, based on the current technical regulations and recommendations for action, allows component and system manufacturers to carry out an initial risk assessment of AI applications in their products.
Manufacturing Data Analytics: Wege zur Steigerung der Wettbewerbsfähigkeit
Authors: Hinrichs Marcos Padrón , Beckschulte Sebastian , Huebser Louis , Schmitt Robert H.
Published: May 2024

Data analytics offers great potential for gaining valuable insights from data. But what is the current status of the implementation maturity of data analytics in manufacturing companies in the DACH region? This question was the subject of an empirical study. Based on the results of the study, recommendations for action to increase the competitiveness of manufacturing companies are presented. Further identified fields of action for the implementation of Data Analytics provide an outlook on future development directions.
Datengetriebene Produktion durch Digitale Plattformen
Authors: Giese Tim , Hock Fabian , Meldt Leonie , Herrmann Julian , Wünschel Willi , Metternich Joachim , Anderl Reiner , Schleich Benjamin
Published: May 2024

Due to the constant advance of digitalization, ever-increasing amounts of data are being generated. Making decisions based on detailed data analysis promises great potential. Digital platforms play a key role, as their use allows data to be collected, analyzed and used for efficient production in real time. This article will therefore first describe digital ecosystems and digital platforms in more detail and then illustrate their application for data-driven production using an application example. The use of digital platforms represents a significant step forward in creating flexible production networks and helps companies to remain competitive.
PROTAGORAS’IN AVUKAT PARADOKSUNUN MANTIKSAL VE HUKUKSAL ANALİZİ
Authors: Aydoğdu Burçin
Published: May 2024

Protagoras’a mal edilen paradoks iki kişi arasındaki bir sözleşmenin mahkemeye götürüldüğünde doğacak ikilime ilişkindir. Bir sözleşmenin hüküm doğurması, mahkeme tarafından verilmesi muhtemel bir kararın varlığına bağlıyken o mahkemenin vereceği karar da söz konusu sözleşmenin içeriğine bağlı olduğu takdirde doğacak olan ikilem ilk çağ mantık metinlerinde bir ikilem örneği olarak verilmiştir. Bununla birlikte aydınlanma çağı ve sonrasında mahkeme kararı normatif açıdan sözleşmeden üstün tutularak söz konusu hikayenin bir ikilem oluşturmadığı ileri sürülmüştür. Bu çalışma Protagoras’a izafe edilen bu hikayedeki ikilemi mantıksal açıdan analiz edip Leibniz tarafından ileri sürülen antitezini özetledikten sonra bu paradoksu modern hukuk açısından ele alacak ve son olarak, hikayedeki çatışmanın varlığının ön kabulüyle ilk çağ hukuk anlayışında sözleşmenin mahkeme kararıyla aynı güçte oluşu ve bunun modern hukuk için geçerli olup olmayabileceği irdelenecektir.
Phenomenological Study on Religious Values Development in Children of Muslim Migrant Workers Families in Lombok Island
Authors: Fakhri Mohammad
Published: May 2024

The purpose of this study is to investigate the phenomenological aspects of religious value development in the children of Muslim migrant worker households on Lombok Island and determine the tactics they employ to maintain their religious identity. This study employed a descriptive qualitative research method based on observations and interviews. This study's fundamental information was derived from primary data collected through in-depth interviews with several children (aged 4 to 10 years) from Muslim migrants' households. The findings emphasized the complex link between religious principles, cultural identity, and societal elements in the development of Muslim children. Meanwhile, this study will help us better understand the complex connection between migration, religion, and cultural identity and provide valuable insights into the challenges and opportunities that migrant families face when keeping their religious beliefs.
Exploring Internal Reverse Migration Patterns in Cumilla District, Bangladesh: A Case Study During the COVID-19 Pandemic
Authors: Rezvi Minhazur Rahman , Nuruzzaman Mr , Khan Bayezid , Hussain Shuhail , Mahim Mahmud Hasan
Published: May 2024

The study possesses two-fold objectives: first, to explain the nature of internal reverse migration in Bangladesh during the COVID-19 pandemic, and second, to explore the push-pull factors of it. This study used a qualitative analysis tool and conducted 04 case studies and 10 In-depth interviews of reverse migrants for case study-based analysis. the study found that the pandemic triggered the reverse migration of informal workers, particularly female workers. Livelihood crisis, food insecurity, unexpected shocks, health insecurity, low living costs, and fear of infection are push-pull factors of reverse migration during COVID-19. Furthermore, these push-pull factors have motivated informal workers to migrate from urban to rural areas during COVID-19. The findings recommend that policymakers should address the vulnerability of informal workers in policy decisions. Policymakers should introduce new programs, i.e., social protection, and emergency economic schemes to provide support to the informal workers during emergencies like COVID-19.
Successful Collaborative Governance Building Permanent Residence Post-Natural Disaster in Palu City
Authors: Hasbullah Hasbullah
Published: May 2024

This study analyses the success of Collaborative Governance in the Construction of Phase I Permanent Residential in the Tondo sub-district after the Earthquake, Tsunami, and Liquefaction on September 28 2018, in Palu City. This research used qualitative methods by collecting data through observation, interviews, and documentation. Data analysis was carried out in the stages of data collection, condensation, display, and conclusion. The theory applied was the Collaborative Governance Model from 1) Face-to-face dialogue, 2) Trust Building, 3) Commitment to process, 4) shared understanding, and 5) Intermediate Outcomes.  The result showed that from the theoretical aspect, the triumph achieved in collaborative governance of permanent housing was because, since the beginning of the direct conversation, an agreement on the division of authority had been reached, wherein the Provincial Nasional Disaster Management Agency (NDMA) prepared the land for the project, the Palu City NDMA was responsible for providing the infrastructure, and the Tzu Chi Buddhist Foundation has the competence to build the constant home. The accomplishment of establishing this initial covenant was followed up well, along with the consistency toward trust building, commitment to the process, and shared understanding to attain good intermediate outcomes.
A Cutting-Edge Data Science Model Leveraging Cloud Computing
Authors: G Archana , R Kamalraj
Published: May 2024

In today's data-rich environment, organizations are increasingly relying on sophisticated data science models to derive meaningful insights from complex datasets. The emergence of cloud computing has become crucial, providing the necessary scalability and flexibility for processing large datasets. This study presents a novel data science model that leverages cloud computing infrastructure to analyse and extract insights from extensive datasets. By utilizing cutting-edge machine learning algorithms, the model can detect patterns, trends, and relationships, enabling organizations to make informed decisions based on data. Additionally, the study delves into the benefits of using cloud computing for data science, such as its cost-effectiveness, scalability, and ease of access. It emphasizes the collaborative potential of combining data science and cloud computing to drive innovation and achieve organizational goals.
Smart Medicine Box
Authors: Vavhal Sanika , Palave Nilesh , Panchal Harshita , Darekar Ujwala
Published: May 2024

Our project's primary objective is to develop a Smart Medicine Box tailored for individuals who require regular medication intake, particularly those with lengthy prescriptions or elderly patients prone to forgetfulness. We observed the challenges faced by patients, caregivers and Nurses in managing complex medication schedules, especially for chronic conditions such as diabetes, hypertension, respiratory ailments, heart diseases, and cancer. Our solution addresses these issues by incorporating features that ensure timely medication adherence and reminders. When it's time to take medication, the system emits a distinctive notification sound and illuminates the corresponding pill box with a bright light, making it easy for the patient to identify the medication to be taken. All medication compartments are pre-loaded into the system according to the prescribed schedule. One distinguishing feature of our system is its ability to detect whether the patient has retrieved the pills from the box or not, significantly enhancing medication adherence. Ultimately, our innovative system aims to expedite patient recovery and improve health outcomes by facilitating proper medication management.
Future Navigator: Machine Learning Approaches to Career Planning
Authors: K V Monishaa , V Srikanth
Published: May 2024

This study presents a comprehensive approach to guiding individuals in selecting suitable career paths following higher secondary education. By leveraging a diverse dataset and employing a combination of handcrafted rules, clustering algorithms, and different modelling, we offer personalized career development recommendations. Additionally, we introduce a computerized career counselling system that utilizes objective assessments to predict optimal career paths based on factors such as skills assessment, interests, and academic performance. Our approach aims to minimize the likelihood of individuals choosing unsuitable career paths, thus enhancing the decision-making process for transitioning from education to the workforce. Through the integration of machine learning algorithms and objective assessments, this research contributes to advancing career guidance methodologies and empowering individuals in making informed career decisions..
Advancements in AI Driven Perception Systems for Agricultural Robotics
Authors: L Gunavardhini , V Srikanth
Published: May 2024

Robots have become increasingly important over the years. Ever- increasing demands for production, labour fatigue, reduced labour and environmental safety have brought robotics to the forefront of scientific advances. The same approach is used with agro-robots, where similar solutions are feasible. help farmers farm faster, safer and more profitably This paper evaluates the prevailing level of mind-based vision in agricultural robots and field applications, specifically weed identification, crop identification, classification, disease detection, vision- based navigation, harvesting, and propagation. This paper analyzes the present level of mind-based vision in agricultural robots in field applications, specifically weed recognition, crop identification, phenotyping, disease detection, vision-based navigation, harvesting, and propagation. The survey demonstrated an extensive curiosity in drawing vision-based solutions.in agricultural robotics, where the most popular RGB cameras and sensors optionally can have promising outcomes, and no particular algorithm leads all others. Instead, artificial intelligence gives specific benefits for performing certain issues associated with agriculture.
Data Plants: Growing Insights in Agriculture through Data Science
Authors: R Akash , R Kamalraj
Published: May 2024

Data Science blends different scientific methods to extract valuable insights from large sets of data. Agriculture is crucial for India's economy because more than half of its population relies on it as their main source of income. Research and Extension systems are key in developing and spreading agricultural technologies to boost farmers' earnings. Recently, the use of data has become a game-changer in farming, transforming traditional practices and promoting sustainability efforts. This paper investigates how data-driven methods like machine learning, remote sensing, and predictive analytics are reshaping farming operations and decision-making processes. It also discusses the challenges hindering the widespread adoption of data-driven approaches in farming, such as data security issues and lack of infrastructure. Despite these challenges, there are many opportunities for further exploration and innovation, emphasizing the importance of collaboration across disciplines and policy interventions to maximize the benefits of data-driven approaches for sustainable food production. In summary, this study highlights the significant role of data in farming and its importance in addressing global food security and environmental sustainability challenges.
Decoding E-Commerce: Data Science and Machine Learning Explorations
Authors: Nair Devika D , R Kamalraj
Published: May 2024

In the world, the growth of e-commerce is been rapidly increasing day by day. The availability of the products and the demands of customers are highly notable. Here we can use the emerging models of data science and machine learning to build a data driven strategies in developing e-commerce platform. This paper delves into the pivotal role of data science and machine learning in the e-commerce, exploring the applications, advantages, and challenges. Through a better understanding of existing papers, literatures and case studies, it investigates how the data science methodologies and machine learning are utilized for many different applications using different methodologies across the various e-commerce platforms.
Green Cloud Computing: Innovating for Sustainable, Low-Impact Data Management.
Authors: Chandan P H , Bargavi S.K. Manju
Published: May 2024

Cloud computing is the internet-based provision of computer services. The usage of some cloud services by individuals and businesses is expanding quickly. The rising demand for cloud infrastructure has led to a notable rise in the energy consumption of data centers. Reducing energy usage is essential to lowering carbon dioxide emissions, hence it must be addressed. Given that green cloud computing's main objective is to maximize energy efficiency, it is acknowledged as a potential solution to this issue. This paper presents green cloud computing alternatives for energy savings in addition to defining cloud computing with the key cloud service models, deployment strategies, and computing platforms. After that, these solutions were categorized based on how well they reduced energy.
Combating the Hidden Threat: A Survey of Cryptojacking
Authors: B Bhuvanesh , R Murugan
Published: May 2024

The illicit use of computer resources for mining cryptocurrencies, or "cryptojacking," has become a common cyberthreat in the online world. This analysis explores the various aspects of cryptojacking and the sly methods that attackers use. We look at how malicious scripts can be hidden and used to steal processing power for nefarious purposes in seemingly authentic websites or ads. We also look into how cryptojacking affects people, companies, and vital infrastructure, pointing out possible issues including service interruptions, data breaches, and performance degradation. The study concludes by examining mitigating techniques, such as network segmentation for enterprises, user education, and strong security software, to counter this growing threat. We can protect our digital assets and negotiate the always shifting danger landscape by being aware of the techniques, effects, and possible countermeasures against cryptojacking.Cryptojacking can lead to performance degradation, increased energy bills, and data breaches
Quantum Computing: Simplifying the Future of Communication
Authors: Danish Md , Rengarajan A.
Published: May 2024

Quantum computing is like having a supercharged computer that can do many things at once, thanks to some mind-bending physics tricks. Regular computers use bits that are either 0 or 1. But in quantum computers, we have qubits that can be both 0 and 1 at the same time. It's like having a magic coin that's both heads and tails until you look at it. These qubits can also be connected in a special way called entanglement. Imagine having two magic coins that always show the same side, no matter how far apart they are. This helps quantum computers solve problems crazy fast. The hardware of a quantum computer is made of super-cool stuff like tiny particles kept in special conditions. This keeps them in their magical quantum states. Why is this exciting? Because quantum computers can tackle huge problems much faster than regular ones. They can help us discover new medicines, create better materials, and even make our online data safer with super-secure codes. In short, quantum computing is like having a superhero computer that does things in a whole new, super-fast, and super-cool way because of the strange rules of quantum physics!
AI in Transportation: Implementing Artificial Intelligence in Transportation for Automate Vehicle Tracking Systems
Authors: Patil Jotiba A , . Srikanth V
Published: May 2024

This research paper delves into the transformative potential of artificial intelligence (AI) within transportation tracking systems, spotlighting its profound impact on the industry. With the transportation landscape continually evolving, the integration of AI-powered automation in tracking processes heralds a paradigm shift in how vehicles are monitored and managed. Through a meticulous examination of cutting-edge techniques, persistent challenges, and notable benefits, this paper unveils the pivotal role of AI in optimizing operational efficiency, elevating tracking accuracy, and fortifying safety standards across transportation networks. Real-world case studies and technological breakthroughs are scrutinized, offering concrete illustrations of AI's capacity to reshape tracking systems. These examples underscore the diverse possibilities AI presents, from predictive analytics to dynamic routing algorithms. As AI's capabilities are harnessed, the transportation sector stands poised for a future defined by seamless, effective, and intelligent tracking solutions, fostering enhanced reliability and agility in the face of evolving demands.
The New Era of Voting Using Blockchain Technology
Authors: Madani Mohsin , . Srikanth V
Published: May 2024

The use of technology has become important at this point in helping to meet human needs. Due to the increasing use of technology, new challenges are brought in the process of democracy as most people today don’t trust their governments, making elections is very important in modern democracy. Electronic voting or e-voting has been used in varying forms since 1970s with fundamental benefits over paper based systems such as increased efficiency and reduced errors. However, there remain challenges to achieve wide spread adoption of such systems especially with respect to improving their resilience against potential faults. Blockchain is a disruptive technology of current era and promises to improve the overall resilience of e-voting systems. This paper presents an effort to leverage benefits of blockchain such as cryptographic foundations and transparency to achieve an effective scheme for e- voting. The proposed scheme conforms to the fundamental requirements for e-voting schemes and achieves end-to-end verifiability. The paper presents details of the proposed e-voting scheme along with its implementation using Multichain platform. The paper presents in-depth evaluation of the scheme which successfully demonstrates its effectiveness to achieve an end –to–end verifiable e-voting scheme.
Blockchain Integration in Cyber Security: Strengthening Defenses and Ensuring Data Integrity
Authors: Musthafa Nabeel , Bargavi S K Manju
Published: May 2024

The rapid advancement of digital technologies has introduced both remarkable opportunities and challenges to cybersecurity. Traditional security measures often prove inadequate against the increasingly sophisticated cyber threats. Blockchain technology has surfaced as a compelling solution for ensuring security in recent times cybersecurity defenses and boost data integrity. This paper delves into the integration of blockchain technology within cybersecurity frameworks, exploring its potential advantages and hurdles. Through a comprehensive examination of existing literature and case studies, this study illustrates how blockchain can alleviate various cybersecurity risks, encompassing data breaches, unauthorized access, and tampering. Additionally, it discusses the outcomes of blockchain adoption across diverse industries and outlines potential avenues for future research in this dynamic domain.
Technological Transformation of Work: Navigating Automation Technologies and Skill Evolution on Employment
Authors: A S M Noorul Ameen , Bargavi S.K. Manju V
Published: May 2024

The relentless march of technology is fundamentally reshaping the world of work, with a profound impact on job roles across all industries. This paper delves into the multifaceted influence of technology on job design, encompassing automation, skill requirements, job creation, and ethical considerations. It examines the rise of automation and its potential for job displacement, highlighting the challenges faced by workers in adapting to these changes. The paper further analyses how technology is transforming existing job roles and the emergence of new skillsets critical for success in the digital era. It emphasizes the importance of upskilling and reskilling to ensure job sustainability. Additionally, the paper explores the potential for technology to create new job opportunities and foster innovation and entrepreneurship. Furthermore, it addresses the ethical considerations surrounding technology-driven job roles, emphasizing the need for fairness, transparency, and data privacy. Finally, the paper analyses the future outlook of technology's role in job design and the challenges in balancing automation with human workforce integration.
Sustainable Software Development: A Scrum and Kanban Approach
Authors: C S Divya , R Kamalraj
Published: May 2024

This The ever-increasing demand for robust software solutions requires continuous improvements in software development techniques. Despite the tremendous positive impact software has on society, it is important not to overlook its negative impact on the environment. With climate change becoming more apparent, it is important to understand and address the environmental impacts of software development.This research seeks to explore ways to integrate sustainable development into existing software development methodologies, with a particular focus on Scrum and Kanban. The research basically consists of two parts: a comprehensive review of existing literature to identify solutions and guidelines for sustainable software development,followed by interviews with developers and managers using Scrum and Kanban methodologies on a regular basis. The goal is to assess the sustainability of their practices and identify opportunities for improvement. Through a literature review, a taxonomy of key characteristics recommended for consideration throughout the software development process was established. Combining these factors with the insights gleaned from the interviews, the study aims to propose the enhancement of software-related planning and development within the framework of Scrum and Kanban, thereby providing factors a sustainability has improved.
A Study of Improving Quality of Care and Patient Satisfaction through Effective Hospital Management with Reference to Select Hospitals in Delhi
Authors: Kaushik Rishab , M Radhakrishna
Published: May 2024

This study examines how effective hospital management can improve the quality of care and patient satisfaction at AIIMS, MAX HOSPITAL, and SRI BALAJI ACTION MEDICAL INSTITUTE in Delhi. Using a combination of quantitative and qualitative methods, the research looks at current management systems, identifies areas for improvement, and proposes specific actions to take. It focuses on three main areas: putting patients first, getting staff involved, and using technology wisely. By studying both how hospitals are run and what patients think, the research offers practical advice on how to keep getting better and making sure patients are happy
The Adoption Process of Cryptocurrencies
Authors: . Nisha , Pandey Anupama , Yadav Bajrang
Published: May 2024

Cryptocurrencies have emerged as a truoblemaking technology with the prospective to reform the financial landscape. This research study future aim to explore and evaluate the topic of the adoption process of cryptocurrencies from many perspectives. This research study is based on secondary data possessed by researchers from various sources i.e journal, articles, magazines, newpapers, and papers reviewed by the researcher. It was shown in secondary data that the cryptocurrency landscape continues to mature and overcome the challenges it faces, and the prospect of bitcoin and other cryptocurrencies revolutionizing the worldwide financial framework and redesigning how we engage in transaction, preserve wealth, and obtain financial affordable appears more plausible. A digital currency centric environment can offer openings for fresh participants in the market and support new businesses by streamlining the fundraising procedure. Initial coin offerings allow entrepreneurs and investors to fund new ventures without relying on intermediaries and approvals from conventional investors and financial institutions. Cryptocurrency represents an ongoing progression guiding by a varied and fervent community encompassing developers, innovators, financiers, and adopters. The route of monetary evolution undergoes reinterpretation, with digital currencies like Bitcoin assuming a very important role in this dynamic metamorphosis.
Data Mining for Dynamic Customer Segmentation: Unraveling Insights
Authors: Srinivasa Prerana , Bargavi S.K. Manju
Published: May 2024

Effective decision-making is essential for every firm to earn high income. These days, there is intense rivalry, and every company is advancing using a unique set of techniques. We ought to make an informed choice based on evidence. Since each client is unique, we have no idea what they enjoy or what they purchase. But by using a variety of algorithms on the dataset, one may use machine learning techniques to filter through the data and identify the target group. In the absence of this, identifying a group of individuals with like interests and personalities within a sizable dataset will be exceedingly challenging and no better methods exist. The use of K-Mean clustering for customer segmentation aids in grouping data with comparable characteristics, which benefits the firm the most. We will use the elbow approach to determine the number of clusters, and then we will visualize the results.
A Comparative Study on Investment Behaviour between Government Employees & Business Person
Authors: Jain Sahil , Chaudhary Anita
Published: May 2024

This study investigates the investment habits of government employees and business individuals, aiming to discern variations in investment approaches, risk tolerance levels, and decision-making methodologies within these distinct groups. By conducting empirical research and analysis, it endeavors to uncover how factors such as income stability, financial knowledge, and resource accessibility influence investment choices. Furthermore, the research examines the impact of psychological factors, societal norms, and economic conditions on investment behaviors within each demographic. The outcomes of this investigation contribute to a deeper comprehension of the complexities surrounding investment decision-making and offer valuable insights for policymakers, financial advisors, and individuals seeking to optimize their investment strategies.
A Study and Analysis on Recent Mergers in India
Authors: Maheshwari Apoorv , Goyal Akhil
Published: May 2024

This research paper aims to provide a comprehensive study and analysis of recent merger and demerger activities in India. It examines the motivations, strategies, and impacts of mergers and demergers on the Indian corporate landscape. Through a detailed analysis of recent case studies, the paper delves into the key factors driving these corporate restructuring activities, including regulatory changes, market dynamics, and strategic imperatives. Additionally, it evaluates the financial performance, market reactions, and implications for stakeholders involved in such transactions. The research contributes to the understanding of the merger and demerger trends in India, offering insights into the evolving corporate strategies and their implications for the Indian economy. Furthermore, it explores the legal and regulatory framework surrounding mergers and demergers, providing a holistic view of the process and its challenges.
Empowering Growth: Leveraging Training Needs Analysis for Companies Success
Authors: Shukla Tannu , Prakash Yerragola
Published: May 2024

Employees are critical to the delivery of high-quality service and the retention of satisfied and loyal consumers. Among the various factors that contribute to this end, work engagement among employees has captured the interest of practitioners and academics in the fields of business, human resource development, and organizational psychology, on the grounds that engaged employees are more likely to exhibit high-quality performance in the workplace. Meanwhile. Training and Development (T&D) practices are thought to add to employee’s engagement in their workplace. The current study sought to explore the impact of Training and Development practices on overall employee engagement as well as various employee engagement characteristics. Job Satisfaction, Organizational Commitment, Advocacy, Pride, Intention to Stay, and Emotional Connect are the factors. Primary data from 101 respondents was collected via a self- administered questionnaire. The study's findings demonstrated that training and development have a substantial impact on job satisfaction, organizational commitment, advocacy, pride, intention to stay, and total employee engagement score. An engaged employee with the proper attitude, abilities, and expertise is regarded critical for organizational success. It does, however, acknowledge a dearth of significant research findings that show the positive or negative impact of training on employee impression.
A Study of “The Impact of AI and Machine Learning in Digital Marketing”
Authors: Bhati Ashish , M Radhakrishna
Published: May 2024

Recent improvements in artificial intelligence (AI) and machine learning (ML) have significantly impacted a number of sectors, such as digital marketing. The influence of AI and ML on digital marketing strategies and implications for businesses are examined in this study. To do this, this paper first highlights the abilities and prospective uses of AI and ML by providing a brief description thereof. The upcoming discussion will outline how AI and ML have transformed important aspects of digital marketing such as customer segmentation, personalized targeting, content creation, customer experience optimization and any other relevant topic under study. The paper also explores the advantages as well as the disadvantages that come with incorporating AI and ML methods in digital marketing strategies. Moreover, some ethical issues coupled with possible prejudices related to using AI and ML. Using computers and robots to help perform Human tasks in the present-day era is referred to as Artificial intelligence. There are numerous everyday obligations that are easily carried out by computers and robots instead of people. For efficient use of green computer systems, Artificial intelligence makes it less complicated to carry out tasks that need human brains.
From Angels to Artificial Agents? AI as a Mirror for Human (Im)perfections
Authors: Haselager Pim
Published: May 2024

Artificial intelligence (AI) systems paradoxically combine high levels of certain types of intelligence and cognitive capacities (pattern recognition, reasoning, learning, memory, perception, etc.) with an absence of understanding and sentience (feeling, emotion). Apparently, it is possible to make great progress in modeling smartness without making progress towards genuinely understanding what all the clever reasoning is about. This is relevant when dealing with AI programs that produce potentially convincing propositional output on religious topics. This article suggests that smartness without genuine understanding cannot amount to authentic religiosity. Comparing ourselves with other entities, (in)animate or (super)natural, has always been a way for humans to understand ourselves better. Throughout the ages, many different types of beings and agents have functioned as tools for self-examination, presenting us with mirrors that reflect at least some of our characteristics, capacities, and (im)perfections. The recent progress in AI provides exciting, though sometimes worrisome, cases for a newly informed look at ourselves. Thus, AI may have profound effects on how we regard others and ourselves. The proud claim that humans are the smartest species on the planet may turn out not to mean all that much. Inspired by the example of Thomas Aquinas, the comparison of humans to our nearest neighbors in a newly extended great chain of being—namely, animals, angels, and AI—may deepen our appreciation of the features of homo sapiens that we share with many other organisms.
INTRODUCTORY PREFACE: Publication Patterns of the Central European Public Administration Review – A Bibliometric Analysis
Authors: Bunescu Liliana , Klun Maja
Published: May 2024

On the 20th anniversary of the Central European Public Administration Review (CEPAR), this study underscores the significance of the journal’s inclusion in indexing. Employing scient metrics, bibliometric techniques, and knowledge mapping, the analysis offers a comprehensive overview of CEPAR’s evolution over the past two decades, the challenges encountered following the journal’s indexing in Web of Science, and the distinctivecharacteristics of authorship patterns. The data used in bibliometric analysis was extracted from Web of Science and covers the period 2018– 2023 (103 papers), while the data for authoring analysis was collectedfrom the archives of journal volumes covering the period 2003–2023 (425 papers). Over its 21 years of existence, CEPAR has published a total of 425 articles with an average of 20 articles per year. These contributions represent the collaborative efforts of 684 authors from different countries, with the average article written by 1.61 authors. The trend in annual citations is positive, with citations increasing tenfold following indexation in Web of Science. The publications in the sample (bibliometric analysis) were written by 175 authors affiliated with 75 institutions, of which 84% contributed a single article to CEPAR’s evolution. In the five years since its indexing in Web of Science, CEPAR has garnered about 200 citations, approximately 33 per year. The most frequent topics include studies on performance, public administration, comparative analysis, e-government, administrative courts, and access to information.
Revitalizing Ukrainian Cities: The Role of Public-Private Partnerships in Smart Urban Development
Authors: Kruhlov Vitalii , Dvorak Jaroslav , Moroz Volodymyr , Tereshchenko Dina
Published: May 2024

Purpose: The article examines the role of public-private partnership (PPP) as a key tool for urban infrastructure restoration and the development of Ukrainian cities within the framework of the Smart City concept. It underscoresthe urgent need for effective mechanisms to restore urban infrastructure, especially in light of the challenges associated with the Russian military aggression and the resulting destruction in Ukrainian cities. The study explores key aspects of smart cities development, including the integration of digital technologies, the use of data, and innovative business models aimed at optimizing city functions.Design/Methodology/Approach: The research employs a multi-stage methodological approach, encompassing elements such as gauging urban population satisfaction with municipal services, graphical analysis using CIMI, assessing the relevance of revitalizing Ukrainian cities and the need for mobilizing business resources, sociological surveys, developing a Smart City model based on PPP project outcomes, and formulating key elements of the national Smart City development strategy.Findings: Emphasizing the importance of strategic planning and cooperation between public and private sectors, the study demonstrates the advantages offered by PPP-based projects. The obtained results highlight the pivotal role of PPPs in promoting urban development initiatives basedon the Smart City concept. The study emphasises the potential of PPPs in shaping stable and prosperous smart cities in Ukraine. Through effective PPP utilisation, local governments can restore urban infrastructure,improve service quality, and enhance the quality of life for their citizens.Practical Implications: The research results can serve as the basis for strategic planning and investment in infrastructure projects necessary for the creation of a smart city. The envisioned strategy will allow for the improvement of legislative acts covering a wide range of aspects of smart cities development while promoting collaboration between public and private entities. This includes bolstering the transportation system, deploying digital technologies, modernizing social institutions, and enhancing the efficiency of urban resource management.Originality/Value: The originality and value of the study lie in its multifaceted approach to assessing and promoting the Smart City concept in Ukrainian urban development. It combines various research methods, including satisfaction assessments, CIMI-based graphical analyses, sociological surveys, and the development of a Smart City model based on PPP project results. This approach not only provides a comprehensive understanding of the state of urban infrastructure and citizen satisfaction but also offers a strategic framework for smart cities development.
Talent Management in the Public Sector – Empirical Evidence from the Emerging Economy of Romania
Authors: Graham Barrington Everton
Published: May 2024

Purpose: This paper aims to investigate how talent management is conceptualized and practised within Romanian public sector organizations. Just like their private sector counterparts, public sector organizations need talented employees or high performers to support their operations and enhance public service delivery. However, research on talent management in the public sector, particularly in Eastern European countries, remains limited.Design/Methodology/Approach: The study was conducted through a series of semi-structured interviews with employees in public sector organizations. The results were analysed using thematic analysis.Findings: The study reveals that talent management practices in the public sector are still in a nascent state of development. Furthermore, there appears to be a lack of understanding of talent management among HR practitioners, and implementation efforts have yielded less-than-desirable results.Practical Implications: The results of our study suggest that while talent management practices are widely embraced by a growing number of private sector companies, their conceptualization and implementation in the public sector differ. In the case of Romania, implementation is hindered by the bureaucratic structure of the public sector and the legacy of previous communist regime.Originality/Value: The study represents one of the initial attempts to investigate the impact of talent management practices in the Romanian public sector, leveraging empirical evidence to support its findings.
Comparison of early postoperative outcomes for breast conservative surgery and modified radical mastectomy in breast cancer in a tertiary hospital: A prospective observational study
Authors: JM Cyriac , J Mathew , AN Oommen
Published: May 2024

Breast cancer is the most common malignant tumour in women in the world, with an incidence of 13.5% in India. For patients diagnosed with breast cancer, surgical options include breast conserving therapy (BCT) or modified radical mastectomy (MRM). This study aims to compare early post-operative complications in carcinoma breast patients undergoing MRM vs BCS at a tertiary care center in India. Patients undergoing BCS and MRM for carcinoma breast were prospectively studied over an 18-month period and postoperatively followed up for 3 months. Incidence of early post-operative complications such as seroma, flap necrosis, wound dehiscence and quality of life (QOL) were compared between the two groups. 106 patients were included in this study, of which 75 underwent MRM and 31 underwent BCS. There was no significant difference noted between these two groups with respect to the following; seroma formation (16.1% BCS vs. 13.3% MRM; p value =0.710), flap necrosis (3.2% vs. 2.7%; p value =0.87), wound dehiscence (3.2% vs. 5.3%; p value =0.63), wound infection (6.5% vs. 5.3% p value =0.823), average number of days of lymphorrhoea (15 ±9.76 vs. 15.7 ±7.49) and QOL post-surgery. Comparison of cost (> Rs.50,000) showed that expense of surgical treatment was significantly higher in MRM (24.0%) compared to BCS (9.7%). Early postoperative complications seen in BCS and MRM are comparable, with the most common early complication being seroma and lymphorroea. Patients should be educated regarding breast conservative surgery, its comparable results with MRM and social and physical impact irrespective of age and menstrual status.
A comparative study between misoprostol combined with oxytocin versus oxytocin alone in reducing post-partum blood loss
Authors: A Selvaraj , K Subramanian , S Periyasamy , R Shankar
Published: May 2024

Background: Oxytocin remains as the first line utero-tonic drug used in the management of postpartum hemorrhage (PPH). Because of its certain disadvantages, another cost effective uterotonic drug which can be used orally or vaginally with good absorption is misoprostol, which is a prostaglandin E1 analogue. The study aimed to compare and evaluate the effectiveness of oxytocin versus oxytocin plus misoprostol in the prevention of PPH. Materials and methods: A prospective randomized interventional study was conducted on 160 term pregnant women from February 2019 to August 2019. The study subjects were randomized into two groups of 80 each. During the active management of third stage of labour, all patients in the study group were administered with standard drug treatment of 10 IU of oxytocin through intramuscular route along with 600µg of misoprostol given sublingually, whereas the patients in the control group were given only 10IU of oxytocin alone. Results: The average postpartum blood loss and the need for blood transfusion were significantly higher among the control group compared to the study group. The overall incidence of PPH was found to be 28.5% among the control group and it was 6.4% among the study group. Adverse events such as fever, shivering, nausea, vomiting and diarrhoea were more among the study group than that of the control. Conclusion: A single dose of 600µg of sublingual misoprostol as an adjunct to standard 10 units of intramuscular oxytocin was found to be more effective in reducing blood loss than using 10 units of intramuscular oxytocin alone in the Active Management of Third Stage of Labour.
Evaluation of pseudoexfoliation syndrome in eyes undergoing cataract surgery in tertiary care centre of Uttarakhand
Authors: A Kundu , P Gupta , V Vats
Published: May 2024

Background: Pseudoexfoliation (PEX) syndrome, an age related microfibrillopathy having varied prevalence and associated with dense cataract, poorly dilating pupil resulting in challenging cataract surgeries. The present study aimed to evaluate pseudoexfoliation syndrome in eyes undergoing cataract surgery in tertiary care centre of Uttarakhand. Materials and methods: A hospital based prospective study carried out from January 2021 to June 2022 and approved by the Institutional Ethical Committee. A total of 1000 eyes of 1000 patients to be operated underwent complete ophthalmic evaluation including refraction, tonometry, gonioscopy, slit lamp biomicroscopy for presence of pseudoexfoliation, cataract grading, and fundus examination. Patients with PEX were diagnosed and data analysed. Results: A total of 54 PEX cases were diagnosed with 29 (53.7%) males and 25(46.3%) were females having mean age of 67.48 + 9.79 years, mean CCT was 528.46 + 18.49 micron and mean IOP was 19.81 + 5.88 mmHg. Prior to cataract surgery, an IOP of more than 21 mm Hg was noted in 40.7% (n=54) of pseudoexfoliative eyes. PXM on pupillary margin present in 51 (94.4%), on anterior lens capsule in 37 (68.5%), on iris in 31 (57.4%), on cornea in 5 (9.3%), phacodonesis in 6 (11.1%), Iris transillumination defect in 3 (5.6%), PXM on trabecular meshwork in 24 (44.4%) and sampaolesi line in 13 (24.1%). Conclusion: PEX presents challenges that necessitate thorough preoperative planning for a safe surgery and a satisfactory postoperative result. Therefore, dilated anterior segment evaluation should be emphasised in daily practise to avoid early PEX patients from being undiagnosed.
Biochemical evaluation of thyroid hormone level in infertile women: A case control study
Authors: K Borgaonkar , R Patil
Published: May 2024

Introduction: Infertility in women is an important health problem which imposes psychological stress and affects the wellbeing of couples. Thyroid disorders is the most frequently encountered endocrine problem among the women in the age reproductive and it can lead to infertility and miscarriage. The objective of the study was to evaluate the thyroid hormone level in infertile women and compared to the healthy controls. Materials and methods: The study was conducted on 50 infertile women (cases) and 50 fertile healthy women (controls). Thyroid stimulating hormones (TSH), free triiodothyronine (fT3), free thyroxine (fT4) and Anti-thyroid peroxidase (Anti-TPO) levels were estimated and compared between the cases and controls. Results: The mean TSH level was significantly higher in infertile women (cases) as compared controls (6.76±0.87 vs 2.54±0.12mIU/L; p=0.002).The prevalence of hypothyroidism among the infertile women in the present study was 28%. The anti-TPO antibody level was significantly higher was in infertile women as compared to controls (4.87±0.8 vs 2.32±0.05 IU/ml; p=0.000). In addition the number of positive Anti-TPO antibody cases was higher in infertile women as compared to controls (24% vs 4%; p=0.02). Conclusion: Therefore, women planning for pregnancy and infertile women must be evaluated for thyroid profile and if there are any abnormalities they should undergo proper treatment for better pregnancy outcome.