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How blockchain enables financial transactions in the banking sector
Blockchain technology is the most important technological revolution of the second decade of the 21st century. The banking sector is one of the major sectors where blockchain has played a significant role in recording and processing various financial transactions, inter-bank transfers, and digital format agreements through a distributed ledger system. It harms the transactional costs, which influence the financial markets. The global financial system being the most popular sector is prone to many errors and frauds. Blockchain technology can help prevent these problems by enabling a decentralised network that permits all parties to review. The present study attempted to analyse the problems in existing banking financial transactions, understand the importance of transparency and study the usage of blockchain in the banking sector. It suggests a research model for solving financial transaction problems by applying blockchain technology. The study uplifts the security and transparency of blockchain technology throughout the paper. Copyright 2022 Inderscience Enterprises Ltd. -
Neuro-Leadership: A New Paradigm in Leadership Thought
Leadership is not a static occurrence. It is a dynamic one that constantly evolves. Leadership is seen as a means to enhance ones personal, professional, and social lives. Organizations believe that leaders bring in unique assets to the organization; which contribute to the bottom line of the company. The conclusions drawn from research findings on leadership portray an image of a process that is far more sophisticated and complex than the condensed view, popularly accepted. This chapter will provide a comprehensive evaluation of different approaches to leadership and highlight the importance of a new paradigm. Ground breaking insights have started to surface regarding neurosciences and brain functioning that has significantly influenced leadership thought. The traditional approaches of leadership could not adapt to the world of unlimited information which needed continuous evolution; however, our brain can adapt and change leading to the emergence of neuro-leadership. The chapter will trace the journey of neuroleadership and its increasing relevance in the current scenario, especially in terms of employee and organization performance. 2024 by Nova Science Publishers, Inc. -
A Novel Deep Learning Approach for Retinopathy Prediction Using Multimodal Data Fusion
In contemporary research on mild cognitive disorders (MCI) and Alzheimer's disease (AD), the predominant approach involves the utilization of double data modalities for making predictions related to AD stages. However, there is a growing recognition of the potential benefits that could be derived from the fusion of multiple data modalities to obtain a more comprehensive perspective in the analysis of AD staging. To address this, we have employed deep learning techniques to holistically assess data from various sources, including, genetic (single nucleotide polymorphisms (SNPs)), imaging (magnetic resonance imaging (MRI)), and clinical tests, with the objective of categorizing patients into distinct groups: AD, MCI, and controls (CN). For the analysis of imaging data, convolutional neural networks have been employed. Moreover, we have introduced a novel approach for data interpretation, enabling the identification of the most influential features learned by these deep models. This interpretation process incorporates clustering and perturbation analysis, shedding light on the crucial aspects of the data contributing to our classification results. Our experimentation, conducted on the dataset (i.e., ADNI), has yielded compelling results. Furthermore, our findings have underscored the significant advantage of integrating multi-modality data over solely relying on double modality models, as it has led to improvements in terms of accuracy, precision, recall, and mean F1 scores. 2024, Ismail Saritas. All rights reserved. -
Economic and sustainable management of wastes from rice industry: combating the potential threats
Rice is one of the imperative staple foods, particularly in the developing countries. The exponential boom in human population has resulted in the continuous expansion in the rice industry in order to meet the food demands. The various stages of paddy processing release huge quantity of solid wastes, mainly rice husk, rice husk ash and liquid wastes in the form of rice industry wastewater. The discharge of the rice industry wastewater imparts a substantial threat to the aquatic bodies and the nearby surrounding and, thus, consequently demands eco-benign treatment plan. As a result, different strategies are needed to enhance the effluent quality and minimize the operational cost of the treatment process. Therefore, efficient technological approach targeting the minimization of pollution as well as assuring the economic prosperity should be implemented. In this review article, several aspects related to the rice industry discussing the significant challenges involved in the generation of both solid and liquid wastes, mitigation experiments and future prospects have been meticulously elaborated. Furthermore, the article also focuses on the various processes utilized for reducing the pollution load and promoting the practice of reuse and recycle of waste rather than the discharge action for the sake of sustainability and the emergence of novel techniques for the generation of energy and value-added products. 2017, Springer-Verlag GmbH Germany. -
Enhanced Secure Technique for Detecting Cyber Attacks Using Artificial Intelligence and Optimal IoT
The Internet of Things (IoT) is a broad term that refers to the collection of information about all of the items that are linked to the Internet. It supervises and controls the functions from a distance, without the need for human interaction. It has the ability to react to the environment either immediately or via its previous experiences. In a similar vein, robots may learn from their experiences in the environment that is relevant to their applications and respond appropriately without the need for human interaction. A greater number of sensors are being distributed across the environment in order to collect and evaluate the essential information. They are gaining ground in a variety of industries, ranging from the industrial environment to the smart home. Sensors are assisting in the monitoring and collection of data from all of the real-time devices that are reliant on all of the different types of fundamental necessities to the most advanced settings available. This research study was primarily concerned with increasing the efficiency of the sensing and network layers of the Internet of Things to increase cyber security. Due to the fact that sensors are resource-constrained devices, it is vital to provide a method for reacting, analysing, and transmitting data collected from the sensors to the base station as efficient as possible. Resource requirements, such as energy, computational power, and storage, vary depending on the kind of sensing devices and communication technologies that are utilised to link real-world objects together. Sensor networks' physical and media access control layers, as well as their applications in diverse geographical and temporal domains, are distinct from one another. Transmission coverage range, energy consumption, and communication technologies differ depending on the application requirements, ranging from low constraints to high resource enrich gadgets. This has a direct impact on the performance of the massive Internet of Things environment, as well as the overall network lifetime of the environment. Identifying and communicating matching items in a massively dispersed Internet of Things environment is critical in terms of spatial identification and communication. 2022 Anand Kumar et al. -
Organizational contributions to emergency preparedness and response in Varanasi: A comprehensive analysis
India's unique geographical diversity and status as the world's most populous nation make it exceptionally susceptible to a wide array of hazards, both natural and human-induced. This vulnerability is further compounded by the intersection of diverse disasters and the dense population, leading to significant human and material losses. In response to these challenges, effective emergency preparedness plans are indispensable, requiring meticulous risk assessments, strategic resource allocation, capacity building initiatives, and active engagement of community-oriented organizations. Continuous monitoring and adaptation are essential for bolstering resilience and safeguarding socio-economic stability. Furthermore, the examination of developmental and disaster-specific organizations' roles in preparedness and response necessitates a systematic shift towards proactive paradigms, fostering an anticipatory culture rather than a reactive one. This study aims to dissect the intricate web of organizational efforts crucial for emergency preparedness in Varanasi, one of the world's oldest cities. By delving into these critical mechanisms, our goal is to enhance collective readiness against potential emergencies, safeguarding the city's rich heritage and its inhabitants. Through a mixed-method approach, this research illuminates the multifaceted involvement of organizations across various sectors, unraveling a complex tapestry of challenges that impede practical disaster preparedness. We scrutinize the coordination among governmental and non-governmental entities, funding dynamics, and grassroots alliances, revealing untapped resources for disaster resilience. Additionally, we analyze the strategies adopted by the national emergency preparedness and response force, highlighting both successes and shortcomings. Moreover, this study underscores the unique competencies of individuals involved in disaster preparedness, while identifying structural and functional gaps within organizational frameworks. Conversely, non-profit organizations face distinct challenges, including fundraising constraints and donor-imposed limitations, hindering their ability to develop comprehensive emergency preparedness and response capacities compared to public and private entities. In summary, this research serves as a comprehensive exploration of organizational dynamics in emergency preparedness within Varanasi, offering valuable insights into the complexities of disaster management efforts. By addressing these challenges, we aim to pave the way for more effective and inclusive disaster preparedness strategies, ultimately enhancing the resilience of Varanasi and similar communities globally. 2024 Elsevier Ltd -
Democratising Intelligent Farming Solutions to Develop Sustainable Agricultural Practices
In this chapter, the transformative potential of democratising intelligent farming solutions is discussed, primarily in the context of the sustainable farming. Technologies including the Internet of Things (IoT), global positioning systems (GPS), Unmanned Aerial Vehicles (UAVs), computer vision, and artificial intelligence (AI) have redefined farming activities. Such advances have allowed decision-making and optimised resource utilisation to be driven by real-time data. The democratisation of AI tools are meant to make AI-driven agriculture accessible to all. As such, this chapter discusses the interplay of bottom-up and top-down approaches, highlighting their roles in promoting the accessibility of AI tools and their benefits to farmers. The integration of such AI tools would transform contemporary agriculture into agriculture 4.0. This revolution would be characterised by real-time data, predictive analytics, and precision farming techniques. Further, the integration of technology such as wireless networks and the global navigation satellite system (GNSS) increases precision and the ability to monitor farming activities. The idea of democratising intelligent farming solutions is meant to herald agriculture 4.0, which would improve crop quality, climate resilience of crops, and the income of farmers. It would also improve broader macroeconomic aspects by promoting education and information and communication technology (ICT) skills and potentially reducing income inequality gap while promoting socio-economic well-being. 2025 selection and editorial matter, Sirisha Potluri, Suneeta Satpathy, Santi Swarup Basa, and Antonio Zuorro; individual chapters, the contributors. All rights reserved. -
Improved Acceptance model: Unblocking Potential of Blockchain in Banking Space
Over the past ten years, blockchain has emerged as the new buzzword in the banking sector.The new technology is being adopted globally in many industries, including the business sector,because of its unique uses and features. However, no adoption model is available to help with this process.This research paper examines the new technology known as blockchain, which powers cryptocurrencies like Bitcoin and others. It looks at what blockchain technology is, how it works especially in the banking sector, and how it can change and upend the financial services sector. It outlines the features of the technology and discusses why these can have a significant effect on the financial industry as a whole in areas like identity services, payments, and settlements in addition to spawning new products based on things like 'smart contracts'. The adoption variables found in the literature study were used to gather, test, and evaluate the official papers that are currently available from regulatory organizations, practitioners, and research bodies. This study was able to classify adoption factors into three categories - supporting, impeding, and circumstantial - identify a new adoption factor, and determine the relative relevance of the factors. Consequently, an institutional adoption paradigm for blockchain technology in the banking sector is put out. In light of this, it is advised to conduct additional research on using the suggested model at banks using the new technology in order to assess its suitability. 2024 IEEE. -
A scientometric analysis of social entrepreneurship
Impactful studies in social entrepreneurship area has garnered attention of the researchers in recent times. The interest and importance is generated in this area because of its nature in addressing social problems and welfare of the communities and societies. The study aims at providing insight on scientometric analysis in the domain of social entrepreneurship. The study further identifies researchers exploring sub domai ns considering parameters like publication language, outlook of publication patterns that changed every year, contextual journals to perform a literature review, primary subject areas in which research is being conducted, most productive institutes/universities, most productive countries where research is being conducted in the domain of social entrepreneurship and the most prolific authors in the area of social entrepreneurship. This study is a pathfinder for researchers with plans to conduct studies in social entrepreneurship domain by leading them to relevant scholarly journals and authors for greater impact. IJSTR 2019. -
Verification and validation of MapReduce program model for parallel K-means algorithm on Hadoop cluster
With the development of information technology, a large volume of data is growing and getting stored electronically. Thus, the data volumes processing by many applications will routinely cross the petabyte threshold range, in that case it would increase the computational requirements. Efficient processing algorithms and implementation techniques are the key in meeting the scalability and performance requirements in such scientific data analyses. So for the same here, we have p analyzed the various MapReduce Programs and a parallel clustering algorithm (PKMeans) on Hadoop cluster, using the Concept of MapReduce. Here, in this experiment we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Means Clustering Algorithm. We have found that as the number of nodes increases the execution time decreases, but also some of the interesting cases has been found during the experiment and recorded the various performance change and drawn different performance graphs. This experiment is basically a research study of above MapReduce applications and also to verify and validate the MapReduce Program model for Parallel K-Means algorithm on Hadoop Cluster having four nodes. 2013 IEEE. -
Experimenting with resilience and scalability of wifi mininet on small to large SDN networks
Today everything is getting digitized where people want to be wireless by all aspects. There is a high demand of WiFi in every sector. Highest influence on network planning of newly developed network infrastructure is of SDN to meet the futuristic needs of upcoming technology. As a result, newly developed networks have become more adaptive to dynamic circumstances along with enhanced flexibility. Being globally connected, it is inevitable to obtain adequate services from data centers through Wi-Fi support on SDN Networks, which is still a dream. Thus, the target of the experiment performed and presented by the authors of this paper is to implement WiFi support on SDN. Further, authors have also demonstrated the scalability and resilience of SDN based WiFi Network on Mininet by testing performance parameters in various dynamic scenarios. This paper will have a high impact on the end users as SDN technology can be implemented as last mile technology using WiFi SDN. BEIESP. -
Impact of Abuse on Mental Health and Happiness Among Students: Mediating Role of Family Environment
Background: Child abuse and neglect is an issue of concern for public health professionals. The impact of abuse may lead to poor physical and mental health conditions. Family environment may impact coping and recovery among victims of abuse. The association between child abuse, mental health, happiness, and family environment is complex. The study examines the association and pathways between child abuse exposure, mental health and happiness, while exploring the potentially mediating effect of the family environment. Methods: Data were collected from 571 high school students from Kerala, India, by using various tools, including a semi-structured questionnaire, Depression and Anxiety Youth Scale, and happiness scale. A mediation analysis using structural equation modeling (SEM) was carried out to test the objectives of the study. Results: The analysis shows that mental health, happiness, and family environment are correlated with abuse experience. The mediation analysis further shows that the indirect effect of abuse on mental health via the family environment was significant (? = 0.013, 95% CI [0.002, 0.033]). The indirect effect of abuse on happiness via the family environment was significant (? = 0.019, 95% CI [0.044, 0.003]). Furthermore, the total effect of abuse on mental health (? = 0.266, 95% CI [0.164, 0.354]) and abuse on happiness (? = 0.152, 95% CI [0.259, 0.050]) was significant. Conclusion: The study reveals that abuse experiences impact happiness and mental health outcomes among students. The family environment mediates the relationship between child abuse and mental health, and between child abuse and happiness. 2023 The Author(s). -
Evaluation of forecasting accuracy of an equity valuation model: a case of ZEE
Investing can prove to be a very enriching and enjoyable experience if one sticks to certain principles and guidelines. The research is based on secondary data pulled out from Money Control website for ZEE Entertainment Enterprises Limited (ZEEL). The identification of target prices is important and involves precision in the price points that are forecasted. The expected growth rate for the next year is figured out to forecast the financial statement for the next year. Regression analysis has been used to estimate growth rate. Regression analysis was done on the income data for the past years for the media entertainment company, and the target prices have been identified. By taking a careful look at the forecasted prices and the prevailing prices, an investor can figure out whether the stock is under-priced or over-priced. 2023 Inderscience Enterprises Ltd. -
Magnetohydro-convective instability in a saturated DarcyBrinkman medium with viscous dissipation
The influence of dissipation with viscosity on magnetohydro-convective instability in a saturated DarcyBrinkman medium is examined. The bottom boundary is designated as adiabatic, whereas the top boundary is isothermal. Numerical linear stability analysis investigates normal modes that disturb the horizontal base flow at different inclinations. The case study shows that the most unstable disturbances are horizontal rolls, normal modes characterized by a wave vector perpendicular to the main flow direction. The horizontal rolls are the favored instability mode. Barletta et al. also showed that horizontal rolls are more unstable than any other oblique roll mode in the hydromagnetic scenario. This finding provides insights into the behavior of MHD fluid flow and heat transfer in porous media, with implications for applications in geoscience, engineering, and environmental science. Graphical abstract: (Figure presented.) The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Optimized Load Balancing Technique for Software Defined Network
Software-defined networking is one of the progressive and prominent innovations in Information and Communications Technology. It mitigates the issues that our conventional network was experiencing. However, traffic data generated by various applications is increasing day by day. In addition, as an organization's digital transformation is accelerated, the amount of information to be processed inside the organization has increased explosively. It might be possible that a Software-Defined Network becomes a bottleneck and unavailable. Various models have been proposed in the literature to balance the load. However, most of the works consider only limited parameters and do not consider controller and transmission media loads. These loads also contribute to decreasing the performance of Software- Defined Networks. This work illustrates how a software-defined network can tackle the load at its software layer and give excellent results to distribute the load. We proposed a deep learning-dependent convolutional neural networkbased load balancing technique to handle a software-defined network load. The simulation results show that the proposed model requires fewer resources as compared to existing machine learning-based load balancing techniques. 2022 Tech Science Press. All rights reserved. -
An IOT based system to track feasible business model /
Patent Number: 202241051204, Applicant: Amrita Chaurasia.
E-commerce that spans international borders makes it possible for smaller businesses to more swiftly penetrate many international marketplaces. The purpose of this article is to investigate the ways in which effective market creation influences the international performance of small and medium-sized businesses (SMEs) that are involved in international e-commerce. Using the effectuation theory as a foundation, we propose that businesses can generate demand in foreign markets by developing innovative new ways for customers to interact and engage with them in the digital world. -
Woman safety hidden malicious hcip using IOT based tracking technology /
Patent Number: 202241040276, Applicant: Dr.R. Beaulah Jeyavathana.
The personal safety and tracking device that is the focus of this innovation is a wearable, multisensory system that detects changes in the wearer's voice, pulse, emotions, impact, motion, and device status in order to make accurate predictions about potential threats. In dangerous scenarios, the wearable gadget will activate an SOS signal, an alarm, an electric shock, and pepper spray, and it will also begin photographing and recording audio for the wearer's protection. The device connects to the internet using GPRS in order to keep track of the person who is wearing it. -
Influence of human resource management (HRM) practices in job satisfacton and career developemt /
Patent Number: 202141048060, Applicant: Arumugam Ranjith.
In any organization, human resources are the most important resource for gaining a competitive advantage. Managing human resources is extremely difficult in comparison to managing technology or capital; therefore, a company's human resource management system must be effective. When it comes to human resource management, it's critical to have a solid system in place as well as solid practices. A human resource management practice is anything that an organization does to manage a group of human resources and ensure that resources are used effectively. -
Financial market data establishment for effective finance data system /
Patent Number: 202111056642, Applicant: Nitin Kulshrestha.
The present invention relates to a financial market data establishment for effective finance data system. Herein matching engine message stream generator of an electronic exchange platform generates protocol-specific market data messages use and includes a first interface created on a reconfigurable logic device that receives matching engine message(s) with a source specific format from a matching engine. -
IOT based application to detect fall with a measured force
Fall of patients and aged individuals may end up deadly if unnoticed in time. A fall detection framework has been developed which sends caution notification to the concerned individuals or to the specialist, at the time of occurrence. To limit the consequences of associated wounds/damage caused by the fall, such a device has been developed. The model in this study, detects the fall and measures the force of the fall without using the force sensor and the direction of the fall. In this study, the body posture is obtained from change of increasing speed in three axes, which is measured with a triaxial accelerometer (ADXL335). The sensor is set on the lumbar area to interpret the tilt point. The value obtained from the sensor is compared with the threshold given to diminish the false cautions and furthermore provides the force by which the individual has fallen and the direction in which the person has fallen. The threshold value is computed by the execution of various trials on subjects in different directions of fall. The sensor data is collected on the fall is computed and analyzed in the Audrino microcontroller. The location of fall is detected by GPS beneficiary, which is customized to trace the subject persistently. On detecting the fall, the gadget sends an instant message through GSM module to the emergency contact. The developed model is tested on 7 volunteers who replicated falls in different direction with varying forces. Out of 28 trials, 80% of exactness is accomplished with zero false cautions for dayto-day activities like sitting, lying down on bed and grabbing objects. IAEME Publication.