Institute of Information Technology & Management
AI-Driven Predictive Models for Infrastructure Health Monitoring and Failure Prediction
I would like to start my paper with a focus on a rising concern. The concern is related to the infrastructure industry, which faces challenges due to aging infrastructure, urbanization, and environmental pressures. While traditional maintenance methods rely on occasional maintenance checks, AI-based predictive models utilize machine learning and structural health monitoring (SHM) to provide a comprehensive solution, detecting errors and predicting failures. The failure to detect the errors is clearly seen in the I-35W bridge collapse of 2007. Our article will dive deep to know the potential of AI in improving the infrastructure reliability in bridges, dams, and buildings in the United States, India, and Canada. We will use six case studies, like as the Golden Gate Bridge, Tehri Dam, and Confederation Bridge, to study the results of monitoring time, maintenance costs, and safety incidents. We will study the data integration, environmental variability, and regulatory hurdles as key challenges. Along with this, technical advancements such as deep learning and digital twins are also studied, based on their scalability and adaptability. Our study also covers the global application of AI technologies in civil engineering. This will help us to know about the future developments of generative AI and the integration with Internet of Things (IoT) technology. These topics play a major role in sustainable and great infrastructure.
Copyright (c) 2026 IITM Journal of Management and IT https://creativecommons.org/licenses/by-nc-nd/4.0
Towards Resilient PLM Architectures: Cyber Threats,Security Mechanisms, and Industrial Implications
Implementation of Product Life cycle Management (PLM) systems in firms from aerospace, automotive, and manufacturing industries helps in efficiently managing design, production, as well as the maintenance information of the company. PLMs help in managing the information at different levels and stages of the company. However, Exploitation of cloud computing, Internet of Things (IoT), and advanced supply chains poses these industries to multiple cyber threats. This document highlights the PLM applications life cycle from design and development to production, maintenance, and eventual decommissioning, highlighting the impact of significant cyber attacks at each stage. We focus on real-world vulnerabilities and attack vectors, like CVE-2021-37161 and Team center’s CAD file tampering, SQL in PTC Windchill, supply chain insider threats, and cloud misconfigurations. Analyzing breaches and defense frameworks reveals the application of ZTA (Zero Trust Architecture), AI-driven anomaly detection, and blockchain with integrity verification as viable countermeasure frameworks. We highlight the pressing importance of embedding security-by-design methodologies in PLM ecosystems while addressing the risks of AI-augmented cyber assaults and quantum computing. This research provides groundwork to aid industries and academicians in strengthening cyber defenses for PLM systems in the scope of a converging industry 4.0.
Copyright (c) 2025 IITM Journal of Management and IT https://creativecommons.org/licenses/by-nc-nd/4.0
A Survey on Secure and Scalable Cross-chain Provenance Techniques For Digital Forensics
Investigations of cybercrime today require forensic architectures that natively traverse multiple blockchains with ease while protecting and scaling evidence processing. Although blockchains support tamper- evident logs, their original single-chain architecture limits cross-platform interoperability and forensic scaling. Recent developments overcome these limitations such as zero-knowledge proofs supporting private but verifiable evidence verification, sharding architectures splitting state without compromising latency, and AI-based anomaly detectors identifying subtle tampering. But challenges remains like zero- knowledge proofs are computationally expensive, sharding poses intricate state- consistency problems and AI models need to be retrained constantly, incurring operational burden. Future research needs to make these pieces work for real- time, large-scale forensic applications by designing light-weight zero-knowledge constructs, self-tuning shard governance systems and compact AI with incremental-update threads. Integrating such abilities into single frameworks will offer privacy, scalability and security, supporting forensic processes for which courts will give credit in various, changing block-chain environments.
Human Activity Recognition in Smart Homes: Advancements and Future Trends With Edge Computing Integration and Ethical Frameworks
Human Activity Recognition (HAR) in smart homes is a vital breakthrough in constructing intelligent systems for monitoring Activities of Daily Living (ADL). It improves healthcare, security, and minimizes energy requirements. This study utilizes ARAS data to construct and test sophisticated predictive models for multi- resident activity systems based on state-of-the-art machine learning classifiers, ensemble approaches, and deep neural network structures.We utilize advanced feature extraction and selection methods such as Information Gain, Recursive Feature Elimination (RFE), and Random Forest Importance to balance model performance and computational efficiency. Our work involves incorporating edge computing paradigms with ethical frameworks to respond to privacy issues and real-time processing needs. The hybrid architecture we put forth showcases improved performance with accuracy of 99.6% and 99.8% for households A and B respectively, while being low in latency and energy consumption. Additionally, we present thorough ethical guidelines and privacy- preserving methods to promote ethical deployment of HAR systems in home environments. Experimental verification on a variety of scenarios ensures the scalability and robustness of our method, qualifying it as a potential solution for next-generation smart home systems.
Review of Hybrid Deep Learning Techniques For Robust ECG Signal Classification by Addressing Noise and Class Imbalance
This review paper presents a comprehensive analysis of recent advancements in hybrid deep learning techniques for automated electrocardiogram (ECG) signal classification, with a central focus on overcoming challenges such as signal noise and class imbalance. Given the pivotal role of ECG analysis in the early detection of cardiovascular diseases, there is a growing demand for intelligent, robust, and clinically deployable systems. The paper examines hybrid model architectures that integrate Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and attention mechanisms to effectively capture both spatial and temporal features of ECG signals. Key studies are reviewed in terms of their preprocessing strategies, feature optimization methods, and noise mitigation techniques. In addition to architectural insights, the paper outlines a structured taxonomy of hybrid approaches based on model composition, preprocessing methods, imbalance handling techniques, evaluation metrics, and deployment environments. It also explores emerging application areas, including real-time monitoring systems, telecardiology platforms, and clinical decision support tools. Common research limitations—such as computational complexity, limited interpretability, and real-world generalizability—are critically discussed. The review concludes with recommendations to guide future work toward scalable, explainable, and clinically relevant deep learning frameworks, ultimately aiming to support the next generation of intelligent cardiovascular healthcare systems.
ECG Signal Classification, Hybrid Deep Learning, Noise Resilience Class Imbalance
Human-ai Collaboration Models in Operations and Supply Chain Management
The integration of Artificial Intelligence (AI) into operational and supply chain processes is transforming traditional management models, creating new paradigms of Human-AI collaboration. This study investigates how different collaboration models enhance efficiency, decision-making, and resilience in operations and supply chain management (OSCM). Using a mixed-methods approach, including expert interviews (n=5) and a survey of 200 professionals, we develop the Adaptive Human–AI Collaboration Model (AHACM), a novel framework that explains how assistive, augmentative, and autonomous collaboration modes evolve with organizational data maturity and governance capacity. Through a literature review and analysis of case studies from manufacturing, logistics, and procurement, we identify three dominant models: AI-assisted decision- making, human-in-the-loop optimization, and autonomous AI-driven operations with human oversight. Key findings show that AI-assisted models improve forecasting and inventory control, human-in-the-loop systems enhance adaptability, transparency, and ethical compliance, and autonomous models strengthen real- time logistics and dynamic demand sensing. Challenges remain in data integration, workforce up skilling, and algorithmic transparency, influencing adoption across industries. The study concludes that the optimal Human-AI collaboration model depends on organizational maturity, data infrastructure, and strategic alignment. A hybrid approach, combining human intuition with AI-driven insights, emerges as the most effective strategy. By introducing AHACM, this paper offers both a conceptual and practical tool for assessing readiness and designing collaborative Human-AI systems in OSCM.
Stock Market Reaction to Merger Announcements in Indian Public Sector Banking: An Event Study Approach
Purpose: The study aims to analyze the stock market reaction to the merger and acquisitions announcement in the Indian Banking Sector. Design/Methodology: The Event-Study methodology was used in order to check the short-term reaction of the investors over a 21-day event window. The market model was used for calculation of expected return with the benchmark index as Nifty50. Statistical tests, including the Shapiro-Wilk test and t-tests (two-tailed), were applied to analyze whether the resultant Abnormal Return was significant. Findings: The findings indicate that no bank has a significant abnormal return on Day 0. However, on Day +1, 4 banks have showcased abnormal returns. Indian Bank continued to show a reaction on Day +2, and Union Bank again on Day +6. However, Bank of Baroda did not show any market reaction. It suggests that investors either expected the news or quickly adjusted to it. Originality/Value: The study contributes to the growing literature on M&A by offering empirical insights into investor behavior and sentiment, and the semi- strong form of EMH in the Indian context.
Women-LED Startups and Atmanirbhar Bharat
The vision of Atmanirbhar Bharat (Self-reliant India) emphasizes entrepreneurship, innovation, and inclusive growth, with women-led startups playing a transformative role. Women entrepreneurs are emerging as significant contributors to India’s socio-economic development, yet they continue to face systemic barriers in terms of finance, market access, social norms, and digital inclusion. This study explores the dynamics of women-led startups within the Atmanirbhar Bharat framework, identifies key challenges, and provides actionable recommendations for policymakers and stakeholders. Using secondary data, government reports, and thematic analysis, the research highlights funding gaps, limited mentorship, and inadequate policy outreach as primary barriers. The paper argues that enabling ecosystems, gender-sensitive financial products, and digital empowerment can accelerate women’s participation in nation-building.
Women Entrepreneurs, Startups, Atmanirbhar Bharat, Gender Equality, Innovation, Financial Inclusion, India
Maximizing Gen Z Engagement: A Modern Approach to it Sector Talent Management
Crisis in Generation Z Employee Retention in the IT Industry due to the rapid digital transformation witnessed in the IT industry, the challenge of retaining the Generation Z employee has become more pronounced, whose workplace expectations and career interests are different from the previous generations. This research aims to obtain better information on combination of AHP (Analytic Hierarchy Process) into talent management systems regarding Gen Z retention in IT ventures. AHP, which stands for Analytic Hierarchy Process, is one of several multi- criteria decision-making (MCDM) methods users can employ to structure their thoughts in a systematic manner, allowing them to prioritize factors affecting Gen Z retention, including work-life balance, career growth, workplace culture and compensation. By doing so, organizations can tailor retention strategies that meet Gen Z expectations by weighting key variables. This study demonstrates a model to solve with AHP and highlights that how AHP model is applicable to find out employee engagement and satisfaction drivers while providing HR leaders a structured perspective. The analysis indicates that a methodical AHP-based talent management strategy will improve job satisfaction lower attrition rate and create a flexible/ socialized workplace environment. Furthermore, this study highlights the importance of providing continuous feedback mechanisms and personalized career development plans in reinforcing Gen Z retention initiatives. The framework presented will provide relevant and useful information to IT companies for designing HR policies aiming for long-term workforce stability.
AI-Driven Digital Transformation in Business Process Optimization
Artificial Intelligence (AI) has emerged as a transformative force in modern business and industries, known as digital transformation, necessitates a fundamental shift in traditional understanding of a business process optimization and human resilience to turbulent socio economic and technological environment. AI emerges as a disruptive force, with immense potential to effect businesses and individuals on an unprecedented scale and exponential pace. This paper is to present AI-driven digital transformation in business process optimization through the theoretical fundamentals of the concept, business process management (BPM) by AI, finance and accounting and HR by AI-powered digital transformation for a business optimization perspective. AI accelerate how work gets done, making organizations organized, avoiding refusal, and increasing efficiency at scale.
AI, AI-Powered, Digital, Block Chain, Ecological Need
Information and Communication Technology Adoption: A Case study of Nigerian Tertiary Education Regulatory Agency
This research study examines the factors that influence adoption of ICT in an organisation that regulates tertiary education in Nigeria based on UTAUT model. Loading factor and Kaiser-Meyer-Olkin (KMO) were used to validate the model. The results of the study show that social factors have positive significant impact on the intention to adopt ICT. The study found that organisational, economic and individual factors are not statistically significant with intention to adopt ICT. This suggests that public organisations should encourage use of social networks to perform their mandates and encourage employees to interact freely to enhance their skills.
Copyright (c) 2020 IITM Journal of Management and IT https://creativecommons.org/licenses/by-nc-nd/4.0
There are number of overwhelming choices over the internet therefore there is a need to filter and efficiently deliver the relevant information so that we can overcome the information overload problem, a potential problem of many internet users. Thus recommender systems provide users the solution to this problem. They search through a huge volume of dynamically generated information to provide users with their choice of content, what they want to see. Various techniques have been proposed and many software have been developed for a different no. of applications. This paper therefore reviews and explore up to date applications of recommender system, different characteristics and types of prediction techniques in recommendation systems.
Usage of Internet of Things in Education
In the forthcoming years, technology will control the learning practice in many ways. Internet of Things (IoT) continues to approve its important location in the perspective of Information and Communication Technologies and the development of society. Now a day's one of the advance word in the information technology is Internet of Things (IoT). The main objective of IoT is to transform real world objects to the artificial intelligent virtual objects. IoT will provide everything in the real world object to provide shared infrastructure to control the things around the state of the things. In recent times this study represents IoT concepts by researcher's scholars, expert system, corporate white papers and online databases. Moreover this research paper will present definitions, issues of internet things, basic requirements and characteristics of IoT. The main goal of research paper is to provide a complete overview of advance technologies associated with their usage of ICT in higher education. However new research will provide goal comprehension and assist accumulation effectively.
Intrusion Detection Techniques for Mobile Cloud Computing in Heterogeneous 5g
As the importance of distributed computers is rapidly growing, they are becoming the target of more and more crime. Intrusion may be defined as the set of attempts to compromise computer network security. Besides the several security services, Intrusion Detection System/Techniques are taken into point that strengthen the system security and is more powerful in preventing internal and external attacks. This technique is considered to be very efficient in preventing wireless communication in Fifth Generation. In this paper we will discuss what Mobile Cloud Computing is and various Intrusion Detection Techniques for mobile computing along with challenges faced by each technique.
The purpose of this paper is to present an idea of machine learning tools that are currently in use or are being studied globally. This work explains the detailed explanation of what is machine learning. This paper introduces a machine learning study by various authors. This work is summarizing the various machine learning tools and their comparisons and recent studies of machine learning tools respectively. The material presented in this paper is the result of a literature review of different research papers and books. This work compares the various tools of machine learning.
Cross-layer security solution for secure communication of sensorsin Wireless Sensor Networks
Safe path-finding is extremely necessary for multihop wireless systems such as Wireless Sensor Networks. Multihop wireless systems are more unprotected to safety outbreaks as associated to single-stage wireless networks. Cross-layer design production is a precise significant character for wireless sensor Advanced security network is significant submissions. for the achievement of announcement among sensor nodes in wireless sensor network because the numbers composed is regularly less and the network is most vulnerable. Numerous Security methods have been suggested to deliver safety resolutions besides numerous threats to the Cross layer modification techniques in Wireless sensor networks. In this paper we overview the existing schemes for the security of cross-layer design in wireless sensor networks. The proposed Security model will provide more security between sensor nodes and the base station in wireless sensor network. Security is important for the success of the wireless sensor network because the data collected are often sensitive and the network is particularly vulnerable. In the cross-layer design, constraints are substituted between changed layers to protect the well-organized use of energy. In this paper, we propose a secure security model that is based on cross-layer design. It uses a cross layer optimization Machine Reproduction consequences confirm that our proposed safety model better in many situations and in unpromising violence-disposed to the situation.
Performance Analysis of Feature-Based Automated Measurement of Mouse Social Behavioral
Automated social behavior analysis in the mammalian animal has become an increasingly popular and attractive alternative to traditional manual human annotation with the advancement of machine learning and video tracking system for automatic detection. In this work, we study a framework of how different features perform on the different classifiers to analyze automatic mice behavior. We conducted experiments on the Caltech Resident-Intruder Mouse (CRIM13) dataset, which provides two types of features: trajectory features and spatio-temporal features. With this feature, we train AdaBoost and Random Decision Forest (TreeBagger) classifiers to classify different mouse behaviors to show which features perform best on which classifier. The experimental result shows that the trajectory features are more informative and provide better accuracy than the widely used spatio-temporal features, and AdaBoost classifier shows better performance than the TreeBagger on these features.
Managing Mental Health during COVID- 19 Pandemic and Beyond
The novel coronavirus disease 2019 (COVID-19) pandemic is a global public health crisis of a scale not previously experienced in modern times. The whole of humanity is sharing a problem that is changing the world, and humans are living under more uncertainty. Most people have been feeling intense anxiety related to COVID-19 and the aftermath the world will leave in its wake. The paper intends to put up a deeper understanding of the anxiety reaction about various aspects of current life. Clear strategies for managing and turning off the anxiety response for short periods is developed based on the understanding of how one’s brain reacts to crises along with some powerful tools for managing the pandemic. The paper explores some of the strategies to address mental health during COVID-19.
A Qualitative Study to Identify the Issues of Employers Employing Migrant Workers
The present study is the identification of issues of employers by employing migrant workers. The study was conducted in the steel manufacturing companies in Kerala. This is a qualitative study used semi- structured questionnaire to identify the issues from the respondents. The respondents was HR managers of the company. Thematic analysis was utilised to evaluate the interview data.The study found that the employers were faced with 1. Job related issue2. Individual issue 3. Managerial issue 4. Performance issue 5. Relationship issue 6. Behavioural issue.
A Study on Causes of Occupational Stress at Small Scale Manufacturing Units in Selected Industry of South Gujarat
Stress management refers to the procedure of various methods to manage a person’s intensity of stress, especially never-ending stress, to develop smooth functioning of the person. The main purpose of this paper is to the study the stress management practices adopted by small scale manufacturing units, analyze the factors in uencing stress. The sample size of 107 employees of selected from various small scale manufacturing units in selected industry of South Gujarat. The primary data was collected through questionnaire. Analysis was done by using Chi-square. The result of the study proves that the employees of various ages have no signi cant difference of feeling stress at workplace; it does have impact on the level of stress among the employees on age. This result proves that age of the employees have signi cant impact on the level of stress among the employees.
Non-executive-Independent Directors, Pay-performance Sensitivity Analysis of Bombay Stock Exchange (BSE)-260 Firms
There are plethoras of studies on CEO’s compensation unlike non-executive independent director compensation; this study uses data of independent director compensation to examine the relation between independent director compensation and  rm performance by using perspective from agency and institution theory. The design of the study is for two years 2005 and 2010, from BSE-500 companies listed in India because these two years are crucial for testing the corporate governance policy related to independent directors compensation. The  ndings provide opportunistic behavior on part of Independent director in relation to their compensation and shareholders wealth as well weak institution norms with respect to compensation structure.
Job Satisfaction among Millennials: The Role of Procedural, Distributive, and Interactional Justice
The authors examined the relationship between organizational justice and job satisfaction among millennial managerial employees. Three forms of justice: the procedural, distributive and interactional were individually investigated questionnaires to predict job satisfaction among 303 employees of  ve bank employees. The study shows a positive association between organizational justice and job satisfaction. All the three forms of justice: procedural, distributive and interactional forms showed a signi cant relationship with job satisfaction. The data reveals job satisfaction among millennial junior managerial employees depends upon organizational justice. Though the study was conducted in Mumbai Metropolitan multi-cultural environment, it may be expected that the  ndings may have relevance on a broader scale to other sectors and may be attempted to develop a new organizational justice model for millennial employees.
A Study on Mobile Applications in Education
Mobile applications are the gateway to transfer human knowledge. Learning is a continuous process and the focus has now completely shifted to eLearning. Due to the mobile phones and the various feature-oriented applications, students can learn at their pace and take their time at understanding things, as everything is just a click away. Integration of Mobile in teaching learning process have generated a new era in education. It makes teaching learning process more interactive and effective. It can help to bring quality education to everyone from everywhere. The implementation of mobile Apps and technologies as a whole, can offer many benefits to the university learning environment. This paper discusses the use of mobile applications in higher education sector and the subject specific mobile applications.
Is CSR aligned to SDGs? – A Study of CSR Programs in Education
In 2013, Corporate Social Responsibility (CSR) was made mandatory to encourage public-private participation in sustainable development aimed at reducing income inequalities. Corporates invest CSR in education, healthcare, and rural development, thus supporting public welfare. CSR spend has steadily increased over the years. The study was conducted to understand the trends in CSR spend and how CSR is mapped or linked to Sustainable Development Goals (SDGs). The study examines the qualitative and quantitative aspects of CSR and examines how corporates map CSR to SDGs. The study examined the  nancial reports of ten corporates to analyze the nature of CSR spend. To determine whether CSR is aligned to SDGs, the CSR interventions in Education were examined and analyzed against the country speci c SGD - 4 targets set by the United Nations. The study reveals that Education is the biggest benefactor of CSR spend. CSR interventions in Education are aligned with the SDG targets. However, due to challenges in interpreting data an exact measurement is not possible. Gaps exist in implementation of CSR. A collaboration approach adopted by Government will help corporates to ef ciently invest CSR in the SDG targets.
Need of Optimum Faculty-Student Rapport and Wise Use of Technology in Classroom Environment: An Empirical Study Conducted in Private Institutions of NCR, India
It is very disappointing to see that attraction towards engineering colleges among students of India is declining. Management education seems to promise more to the students. National newspapers of India have given space to headlines sharing closure and shut down of many private institutions and colleges. This situation needs serious thought. Are all the engineering and management institutions fairing bad in terms of admissions or some are more insecure than others? Market situations, pressures of globalization, competition cannot be controlled however, what can be nurtured well is our existing set of students so that their performance and results speaks for itself and so does their behaviour. Engineering and management institutions boast a lot about collaboration with foreign universities from developed countries however; one thing to learn from these foreign universities is their optimum level of faculty-student relationship as well as classroom environment that prevails in their institutions. This research paper, primarily based on primary research conducted in private institutions imparting engineering and management education, recommends a need to focus on optimum faculty-student rapport and wise use of technology to gain disciplined classroom environment.
Research in the field of crowd funding has been emerging in India over past few years. This is due to the release of the consultation paper by SEBI in June 2014. Crowd funding is a newly introduced concept in India highlighting the use of technology. This concept has helped a lot of emerging startups and SMES raise funds for commencement of their businesses. It is a digital platform for the people willing to invest and for the people who wants investment, whereby the whole process is conducted over the internet having worldwide reach. Crowd funding though beneficial, investors in India have adapted themselves to the traditional way of funding making them reluctant to switch to new methods of raising finance. This article aims at examining the entire concept of crowd funding in India and the factors hindering its growth.
Copyright (c) 2019 IITM Journal of Management and IT https://creativecommons.org/licenses/by-nc-nd/4.0
Impact of Organizational Culture on Employee Engagement and Effectiveness in Indian Manufacturing Company
Engagement of employees is considered as a robust indicator of outcomes that are highly valued by any business in any sector of the industry. Therefore, employee engagement and effectiveness could prove to be an excellent parameter to assess the health of the organization as such with regards to satisfaction, innovation, commitment, retention and productivity. Organizations that are observed to have a positive organizational culture tend to offer rewards to their employees which in turn leads to the creation of an environment that is enabling, allowing employees to grow, develop and function at their utmost potential. This particular study was carried out to understand the impact of organizational culture on employee engagement and effectiveness within the Indian manufacturing sector. This study was outlined on the basis of the structural approach theory and adopted a secondary research methodology where the data for the study was gathered through secondary sources derived from researches conducted by researchers in the past and available from scholarly sites. The study outlines four types of organizational culture which included; power culture, role culture, achievement culture and support culture. Each of the said cultures had a varying impact on the engagement and effectiveness of the employees. The findings of this research indicated that the culture of the organization had a largely positive and significant impact on engagement and effectiveness of employees. It was also observed that employees who were empowered to utilize their discretion at their organizations tend to project higher levels of enthusiasm and this is clearly a trait of an employee who is thoroughly engaged
There are different types of encryption techniques used to ensure the privacy of data transmitted over internet. Digital Signature is a mathematical scheme that ensures the privacy of conversation, integrity of data, authenticity of digital message/sender and non-repudiation of sender. Digital Signature is embedded in some hardware device or also exits as a file on a storage device. Digital Signature are signed by third party some certifying authority. This paper describes the different key factor of digital signature with the working, through various methods and procedures involved in signing the data or message by using digital signature. It introduces algorithms used in digitalsignatures. Many traditional and newer businesses and applications have recently been carrying out enormous amounts of electronic transactions, which have led to a critical need for protecting the information from being maliciously altered, for ensuring the authenticity, and for supporting nonrepudiation. Just as signatures facilitate validation and verification of the authenticity of paper documents, digital signatures serve the purpose of validation and authentication of electronic documents. This technology is rather new and emerging and expected to experience growth and widespread use in the coming years.
ICT Initiatives and Tools in Higher Education
ICT has changed the picture of Indian higher education system as more and more technological intervention is being infused with the usual ways of teaching. ICT plays a vital role by making available the knowledge resources to every learner as per his/her convenience and just in time. ICT has tremendously upgraded the quality of education through various mechanisms like elearning, blended learning and distance education. It has increased the access of and imparted equity in higher education through increasing digitization and quality teaching learning which benefits not just students' learning but also has open ways to build capacity of educational personnel. This paper is a descriptive analysis of the increasing use of and various initiatives in the field of education pertaining to the use of ICT in India and its contribution in imparting quality in education and its subsequent benefits.
A Brief Survey of Cryptocurrency Systems
Information and communication Technology (ICT) have change the state of life from the last few years because many activities of daily life have been merged online and they become more productive. Cryptocurrency is specific type of virtual currency which works on the principles of cryptography and electronic medium communication. It gain lots of attention in the recent years. Cryptocurrency has decentralized control and is controlled by non-government bodies. It opposes the centralized digital currency and central banking system because of its decentralized feature. It revolutionizes the digital trade market by creating a free flow trading system which works without any third party. The usage of virtual money or currency has widespread in recent years. this paper highlight the introduction of cryptocurrency, its history , some aspects of it ,working of cryptocurrency and also highlight the future of cryptocurrency in India.