In the current times, the field of education is undergoing a drastic change especially with the various rankings. If we concern about rankings, we have the QS-World rankings of educational universities. In the Indian context, we have the Atal, NIRF, and a score of other rankings carried out by private bodies like The Times, B-School, etc. The educational universities and or the educational institutes hope and target for a better reputation among the contemporaries which can help them to sustain in the competition. There are various parameters with which the institutes are ranked. These are not same for the world and Indian ranking standards. The main entities in an education process are the educational institute, the teachers or faculties, the students, the quality governing bodies, and the policy-making bodies. The ranking of the institutes helps the educational institutes to attain good quality of students. This indirectly helps in attaining quality for the institutes in terms of performance and the institutional rankings. Hence, we can say that the selection process in the educational institutes can be a crucial, pivotal step in attaining the final institutional rankings. In this paper, we have discussed the importance of selection process of candidates for an educational institute. We have also presented the significance of various attributes of students in the selection process. The fast advancing domain of AI and its impact on this process is also considered.

Phishing has evolved into a critical digital menace that takes advantage of human weaknesses by using deceptive emails while also creating fake websites and fraudulent communications in the contemporary digital age. Hackers execute such attacks with the goal of stealing sensitive data which includes credentials together with credit card information and personal information for their harmful objectives. Phishing has become complex enough to warrant real-time security solutions because the threat now exists at an alarming frequency. The research investigates the multiple attack methods in phishing campaigns along with an examination of standard protection approaches’ weaknesses. The research investigates sophisticated artificial intelligence (AI) and machine learning (ML) systems because they present improved detection and faster prevention capabilities against phishing attempts. The paper delivers a complete examination of AI-based cyber defense systems while analyzing their position in enhancing business cybersecurity structures. The research adopts a position that intelligent adaptive defenses ought to be integrated because AI technologies serve as a proactive method to reduce risks in modern phishing attacks.

The rising digitization of India's healthcare system has raised the demand for Electronic Health Record (EHR) systems. These systems are dependable, scalable, and interoperable. This demand was accelerated by the pandemic. It highlighted the value of EHR to the entire community and all of its stakeholders. Globally also this trend is observed. Governmentbacked initiatives like the Ayushman Bharat Digital Mission (ABDM) and the National Digital Health Mission (NDHM) have made the use of EHRs in India a basic necessity rather than a choice. This study compares a number of well-known EHR software programs in India, including Practo Ray, HealthPlix, and Bahmni. A systematic review approach is used to assess the EHR systems, taking into consideration elements such as costeffectiveness, interoperability, AI-driven analytics, mobile accessibility, and compliance with national requirements. The findings highlight the present shortcomings in India's health IT system as well as its technological advancements. It demonstrates notable platform-to-platform variance in capability and adaptability. The report concludes with strategic recommendations for lawmakers, software providers, and healthcare providers to maximize EHR deployment and selection for better healthcare delivery and digital integration.

The “connected automobiles” is all about private passenger cars that are connected to the internet in some form or another. Most of the contemporary road cars, including buses and Lorries, are themselves more and more advanced computer-filled systems connected to the “internet of things” (IoT). As they become more and more connected and automated, malicious individuals could easily employ numerous different kinds of attacks that put CAVs (Connected and Autonomous vehicles) in danger of being compromised. The interconnected communication systems between vehicles and infrastructure give hostile attackers remote access to attack with the purpose of taking advantage of system vulnerabilities. The added connectivity and autonomous functionality represent a powerful threat to the enormous socioeconomic gains CAVs promise. Large amounts of publicly accessible literature are reviewed and classified herein based on the discovered vulnerabilities and the countermeasures applied. This analysis demonstrates that the majority of research is reactive and that friendly opponents, or “white-hat” hackers, are frequently the ones to discover vulnerabilities. Several flaws in the knowledge base were discovered. These knowledge gaps should be addressed to minimize future cyber security issues in the connected and autonomous car industry.

This paper focuses on how AI has influenced military technology and how new ideas are enhancing these effects for the military, contributing to the development of this constantly progressing area. AI is not the improvement of the current technologies in military systems but a change in paradigm on how such systems should be developed, employed, and managed. Using a structural approach, this study assesses how AI advances are providing complete autonomy of systems' decision-making processes, shifting long-held military conceptions and approaches. The paper also comprises the concrete cases and examples of using AI in modern operation context, proving thus its applicability to the real-life situations. Therefore, our analysis is not restricted to the sphere of computer science only but also includes aspects of military tactics and international relations so that we gain a future-oriented outlook on possible or emerging tendencies. This inclusive analysis demonstrates how technology and strategy are intertwined and focusing on this interplay is very useful for any researcher, policy maker or a military planner. In line with the previous studies, our analysis in this paper highlights the innovative role that AI plays in enhancing the capabilities of modern warfare, stressing its current and possible impacts in the future.

Generative AI (GAI) is an upcoming field and its impact on marketing is indisputable. Very little evidence in academic literature is present regarding the factors affecting the usage of GAI in Digital Marketing (DM). This study addresses this gap by exploring the key drivers and barriers associated with using GAI in DM. Leveraging Behavioral Reasoning Theory (BRT), the research validates prior findings and introduces a conceptual model outlining factors that shape attitudes toward adopting GAI in DM to enhance customer experiences.A qualitative inductive approach was undertaken by conducting expert interviews to investigate the “reasons for” and ‘reasons against’ using GAI in DM and its impact on customer experience. The transcripts generated were manually coded and a deductive thematic analysis was done using the BRT as the theoretical framework.The findings indicate four significant themes for adopting GAI in digital marketing viz: innovation, creative communication and content creation, speed, efficiency and timesaving, enhanced customization and personalization; predictive analytics and simulation. It also indicates five significant themes related to the key barriers were also identified viz: ethics and infringement of Intellectual Property; security and deepfake; learning ecosystem for the adoption of new technology; quality of data; reduced manpower requirement. The study further highlights how GAI influences customer experience in DM.This study contributes to the field by (a) proposing a conceptual framework for applying GAI in DM to improve customer experiences, (b) examining the drivers and challenges of GAI adoption in DM, and (c) presenting a research agenda to guide future studies. These insights offer value to researchers, marketing practitioners, and academics navigating the dynamic intersection of GAI and Digital Marketing

The release of ChatGPT by OpenAI in November, 2022, has stimulated great discussion focusing on applications of AI technology in many areas, such as academics, business, and society. While AI has been applied in a number of places for once, the spread of Generative AI (GAI) programs such ChatGPT, Jasper, and DALL-E generated the perception that it is a turning point in the development of AI technology due to its user-friendliness, ease of use, and impressive performance. GAI is the way of creating variety of content, which can be texts, images, music, code, and videos. This has a number of implications for businesses that depend on them more, and touch upon the role of BMI. What follows is a BMI-based overview of how GAI can influence enterprises and the next sections contain three case studies, including software engineering, healthcare, and financial services. This research features a qualitative content analysis, such as peer-reviewed publications, company reports, press releases, interview transcripts, and podcasts. Therefore, the study will be able to contribute to the increasing academic debate on the impact of AI development in the management scholar's field while enriching the understanding of the actual implementation of AI in order to develop or improve business models.

The world industrial environment is in a growing demand to use energy efficiently and save money. The old metering systems, which are being used and work on 4G or Wi-Fi, do not have the real-time data transfer that is necessary to dynamically price and manage the load. The introduction of the 5G technology with Ultra-Reliable Low-Latency Communication (URLLC) and Enhanced Mobile Broadband (eMBB) can provide a way out. This paper examines how 5Gbased smart meters can be combined with artificial intelligence to support dynamic pricing and effective load optimization in industries. In the literature reviews, simulations of NS3 and a pilot implementation in a medium-sized manufacturing facility, we analyze the data latency, pricing response time, energy costsaving, and load-shifting effectiveness. Findings indicate that 5 G has the ability to reduce the latency by up to 80 percent compared to the legacy systems, adjust the prices dynamically, resulting in a cost reduction of 12 percent, and load-shift benefits of up to 20 percent. Issues, such as high infrastructure rates, cybersecurity issues, and legacy system integration, are examined. Secure and scalable suggestions in terms of deployment in industrial settings are offered.

Healthcare digitization is now a worldwide necessity rather than a pipe dream. The Electronic Health Record (EHR), is a technology that has developed from basic data storage to an intelligent, networked platform. It influences the direction of healthcare. EHRs have become essential in recent years for improving care coordination, expediting clinical procedures, and providing real-time access to patient data. This is true for patient data across borders and institutions. As healthcare systems around the world faced previously unheard-of difficulties, the COVID-19 pandemic further increased need for interoperable, secure, and scalable EHR systems. However, despite tremendous advancements in the technology and EHR enduring obstacles still exist. Usability issues, data privacy worries, and interoperability gaps still prevent EHRs from being widely adopted and optimized. This study examines the global importance of EHR in the modern era, emphasizing how it advances patient-centered care, fortifies public health infrastructure. The newer advancements through cutting-edge technologies like blockchain, artificial intelligence, and mobile health also play a crucial role in the shaping of EHRs. In order to create robust, data-driven healthcare systems, the study ends by highlighting the main issues, policy considerations, and future research avenues.

Asian IT (Information Technology) market and economy is impacted by DevOps progression significantly, hence research of DevOps is necessary to bring innovation and improvements in DevOps methods and IT projects. Hence as the commencement to IT industry applicable research of DevOps in future, we started with research of this bibliometric study. It is supported with thorough literature review and in-depth bibliometric analysis of DevOps research studies to understand trends in DevOps. In long run DevOps is impacting IT market which is an important economic aspect in Asia and globally. The Asia Pacific DevOps Market is predicted to grow at a Compounded Annual Growth Rate (CAGR) of 20.2. Bibliometric measures conducted includes author search, citation counts, etc. This research study is spanned across research years 1999–2020. Bibliometric scrutiny is conducted with Scopus, Google Scholar, and the tools like Gephi, etc.

Social engineering is the manipulation of people’s virtual belongings and misusing them by unauthorised access. This article looks at aspects for pertinent to value, losses, social practices and then offers a defence mechanism framework. Social engineering can cause considerable damage to an individual or an organisation before they are detected. Consequently, ample defence mechanisms should be in place to prevent such attacks. Information security threats are as much technical as they are social. Social engineering attacks aim to gain unauthorised access to information. A hacker’s cunning manipulation of an individual’s nature of trust to obtain information would grant the hacker unauthorised access to the virtual data of an individual for a predatory stance. Social engineering can take place over various platforms, and social media and social networking are among them. Social platforms, with their distracting, defocussing potential combined with the fact that is can also be used as a means for executing a social media attack. The proposed framework in the paper targets threats in social engineering; it is about tricking people into providing access to information. It addresses the serious losses the attacks can create and the necessity of defences. Psychological motives are the focus of the framework, and a novel method based on AI prevents these threats. This study fist explores the psychological modes and offers a contextual AI-based solution framework which counter the social engineering mechanisms and with their integration into cyber security policies, these can defect deep levels of intrusions. This research benefits society by raising awareness of social engineering risks and enhancing cybersecurity measures to safeguard information.

Mobile learning environments increasingly demand sophisticated interactive technologies capable of delivering engaging educational experiences while overcoming traditional hardware limitations. This integrative literature review examines cloud gaming infrastructure advancements for mobile learning. Results from both technical research and practical educational experiences are compared to understand how technology supports learning. Analysis reveals that hardware-assisted GPU virtualisation frameworks achieve substantial performance improvements on mobile devices, enabling sophisticated educational simulations. Video codec optimisations significantly reduce latency and bandwidth consumption, while touchscreen controls and haptic systems enhance learning effectiveness. Recognition of pedagogical innovations across different domains highlights their tremendous potential. STEM simulation platforms utilising molecular modelling and mathematical visualisation demonstrate significantly higher student engagement. Medical training applications enable learners. Collaborative learning environments facilitate enhanced problem-solving through shared virtual spaces, while language learning applications demonstrate superior vocabulary retention. The analysis establishes cloud gaming infrastructure as a transformative enabler for mobile learning, democratising access to sophisticated educational tools.

The importance of internal audit is ever increasing. Internal audit has to be efficient and effective and as facts show, there is a constant need for it. However, in present technological context, artificial intelligence (AI) presents a positive and viable method. Internal auditing is an essential function tasked with providing assurance over the reliability, legal requirement, and economy of an organization’s financial and operational activities. The internal auditors act as crucial agents in exercising risk management within an organization. They discover problems which involved in detailed studies which put into monetary loss or inefficient running of the business. Their expertise helps in prevention and detection of fraud thus ensuring the company does not violate any existing law or corporation control policies. They protect the overall welfare of the organization, and help the decision-making process by highlighting some areas that can be improved and recommending the possible solutions. This proactive and strategic role improves overall governance by giving useful insights for ongoing improvement inside the organization. AI is transforming internal auditing by aligning operations with powerful data analytics and automation. Machine learning enables auditors to swiftly evaluate enormous datasets, discover patterns, and detect potential loopholes in real time. Advanced technologies driven by artificial intelligence ease ordinary and repetitive tasks leaving auditors to handle tough analysis and decision-making. Therefore, internal audit is a more intelligent function and adaptable in providing efficiencies and enhanced control in a growing environment. This paper discusses the AI which allow for automation of various internal audit processes and the various forms of AI Tools. Three principal areas of automation—the data extraction, analysis, reporting of business data and the task of sampling weighing the benefits of lower workspace and higher precision is included.

Worldwide disasters continue to endanger populations and urban facilities while destroying local economies because of global warming alongside swift urban population growth. Integrating Internet of Things (IoT) technology into disaster management systems creates a strong platform to improve the readiness and readiness response capabilities along with recovery operations. An innovative IoT-based Disaster Management Framework exists as a proposal to acquire real-time data and achieve situation awareness through optimized emergency operation capabilities. The framework’s design employs environmentally monitoring devices with sensors which measure water levels and seismic activity and air quality simultaneously. The framework enhances disaster detection effectiveness because it operates through continuous monitoring activities that produce rapid alert protocols. Emergency teams receive a complete view of damaged areas because the framework consolidates all data onto a single platform that promotes quick informed responses. The system enables protected dialogues between responders and stakeholders to achieve an organized and efficient resource distribution. The system provides three main capabilities to track responders and survivors more accurately and perform automated damage inspections and distribute IoT-based awareness materials to communities. The paper elaborates on how the framework works and its structural design along with its implementation strategies and analyzes operational challenges in various geographic characteristics with socioeconomic differences. The paper discusses the limitations IoT encounters when applied in disaster situations while giving guidance to future research efforts. The research provides a novel viewpoint for disaster response using IoT implementation that builds communities that are more resilient to stress and get faster relief and more awareness.

Software testing (ST) holds a crucial role in the software development process, serving as a linchpin for ensuring the reliability and quality of the final product. This research explores the increasing significance of artificial intelligence (AI) within the realm of ST, shedding light on its transformative potential. The paper initiates by examining the contemporary challenges faced in ST, such as the diverse array of platforms and the substantial requirements for test coverage. It then delves into how AI has the potential to revolutionize testing procedures. Emphasis is placed on the capacity of AI-driven test automation frameworks to expedite testing processes, enhance precision, and broaden the scope of test coverage. The paper also discusses the contributions of AI in the creation and optimization of test cases, with a focus on its role in intelligently selecting test cases to make testing more efficient and ultimately reduce resource demands. Furthermore, the study investigates the effectiveness of AI in anomaly detection and defect prediction, leveraging machine learning (ML) and natural language processing (NLP) as exemplars of AI-powered approaches that facilitate early fault identification, thereby improving software reliability. Ethical and practical considerations pertaining to data privacy and bias prevention in AI-driven testing are also addressed. Additionally, the paper underscores the significance of collaborative human-AI testing methodologies. It substantiates its findings with case studies and real-world examples from industry, showcasing the successful deployment of AI in ST to enhance software quality, reduce testing expenses, and expedite time-to-market. In conclusion, this study underscores AI’s transformative impact on the field of ST, offering valuable insights for practitioners and researchers seeking to harness its advantages.