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An Outlook on Sustainable Business Practices through Virtual Reality Marketing
Technologies and businesses blend progressively and work towards creating a sustainable future through the company's marketing strategies. The purpose of the study is to find out the various sustainable outcomes of Virtual Reality Marketing (VRM). The exploratory research identified immersive experience, experiential economy, positive image creation, positive travel decisions, and repeat purchase as the constructs of VRM, and a total of 418 people were surveyed to analyze those constructs. The data were analyzed through statistical tests such as t-test, One-way ANOVA, and Chi-square with the help of SPSS software. The study shows a positive relationship between customers and virtual reality marketing. The results predict that businesses that have incorporated VRM tend to likely have a high-profit margin and more sustainable returns compared to their peer competitors. 2024 IEEE. -
A Study on Factors Enhancing Immersive Virtual Reality Experiences
The objective of this study is to identify the various influential factors of immersive virtual reality (VR) experiences and examine the relationship between the immersion factors (technology, visuals, sound, interaction, and sound) and virtual reality experiential outcomes (satisfaction and loyalty). The survey comprises 412 participants who experienced VR games at the Orion Mall in Bangalore. The study has identified the prominent factors for enhancing the immersive experience. The factors are technology, visuals, sound, interaction, and sound. It also identified that there exists a positive association between VR experiential satisfaction and technology, visuals, sound, interaction, and sound. The results imply that service providers should focus on elevating immersive experience as it is closely associated with VR experiential satisfaction and VR experiential loyalty. This will increase the revisit intention and spread positive word of mouth about the virtual experiences. This paper provided valuable insights that pay way to analyze the association between immersion factors and VR experiential outcomes. 2024 IEEE. -
Evaluation of Virtual Reality Experiential Dimensions using Sentiment Analysis
Experiential technologies like Virtual Reality (VR) are revitalizing the gaming industries through higher immersive and interactive gaming experiences. The immersive technology has a considerable impact on the industry and will evolve simultaneously as the technology continues to update and improve further. Indian tech cities Bangalore, Delhi NCR, Mumbai, Kolkata, Chennai, Pune, and Hyderabad were chosen for the study and the user-generated content was scraped from the top gaming centers of each city. User Generated Content analysis is gaining immense interest among businesses for devising better decision-making and marketing strategies. The study devised an integrated framework comprised of web data scraping, data cleaning, data pre-processing, AI model designing, sentiment analysis, logistic regression model, and support vector machine model. Logistic Regression predicted the sentiment of the text and the Support Vector Machine classified the VR experiential dimensions and helped in understanding the most important dimension for customer satisfaction. The study has found that VR experiences are gaining positive responses among the customers and illusion emerges as the most significant dimension for their satisfaction. 2024 IEEE. -
Data: A Key to HR Analytics for Talent Management
The past few years have witnessed a significant rise in job openings across various industries worldwide. This trend has highlighted the need for companies to plan and recruit better talent to keep up with the demand for skilled employees. As a result, Human Resource (HR) professionals are now using workforce planning and HR analytics to address the challenges of finding and retaining the right employees. With the help of technological advancements in HR systems, businesses are leveraging data and insights to understand workplace dynamics better. Workforce planning has thus become crucial for organizations of all sizes to ensure they have the necessary talent to achieve their goals in the present and future. This chapter delves deeper and examines the importance of workforce planning and how HR analytics can help companies achieve their strategic objectives. Talent Management is about analyzing the workforce skill requirements of the organization. It needs a strategic plan to ensure the appropriate people are in the right roles at the right times. Talent Management is a crucial element of every businesss performance. In this process, data play a pivotal role in evaluating the existing workforce and planning for future workforce needs. Based on this, a strategy is developed to fill gaps or prospective shortages. Organizations can achieve their goals by using talent planning and collecting data about upcoming projects and skill requirements based on market needs. For example, talent planning is essential in the healthcare sector to guarantee that hospitals and clinics have enough doctors, nurses, and other healthcare workers to fulfill the rising demand for healthcare services. HR analytics is the key to talent management, enabling organizations to stay competitive, enhance productivity, and achieve long-term strategic objectives. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
A Revised Study of Stability Issues in Mobile Ad-Hoc Networks
Adhoc or short live network has developed tremendously in the recent time, which can work without any access point or mobile towers. That means it is an infrastructure less network. Mobile Ad-hoc Networks can be referred as MANETs. The locations can be changed, and it can discover the path dynamically. In other words, the nodes move dynamically leading to the update of the topology, frequent change in topology, optimization of routing and fading the interference of multiuser are few issues connected with MANETs that affects the efficiency of the data transfer. The purpose of this survey is to reveal the various types of mechanisms which can be used to resolve the problem of routing performance related issues in MANETs. This paper also presents the classification of link stability, route repair and stable path algorithms in tabular format. 2020, Springer Nature Switzerland AG. -
PSA-MP: Path Selection Algorithm for MANET depends on Mobility Prediction to Enhance Link Stability
Link failure is a much crucial issue to be addressed for improving the stability of the routing. Selection of a stable path is an important task since nodes are mobile. The instability of a link leads to frequent link failure, which further causes to link re-establishment. In this paper, a Path Selection Algorithm based on Mobility Prediction (PSA-MP) is proposed that uses Mobility, Direction and Link Expiration Time (LET) as metrics to evaluate the link stability. In the existing algorithm, if any link gets fails during the link-establishment phase, it informs the previous node for selecting alternate link. But, in PSA-MP the alternate link is selected before a link fails by predicting Mobility, Direction and LET of nodes. As a result, it reduces link re-establishment delay. Ultimately, PSA-MP reduces E2Edelay, which in turn boosts Packet Delivery Ratio (PDR). Eventually, link stability is enhanced in MANETs, which is the focus of this paper. Published under licence by IOP Publishing Ltd. -
Scalable, Cost Effective IoT Based Medical Oxygen Monitoring System for Resource Constrained Hospital Environment
Oxygen therapy is one of the critical treatments employed in epidemics, pandemics, and natural calamities. Recent covid pandemic worldwide witnessed many deaths due to improper management, delayed delivery, and wastage of medical oxygen. Therefore, efficient utilization of available oxygen is very important. To monitor and manage oxygen, several hospitals employ IoT-based systems. Scalability is an essential feature in such monitoring systems in order to cater to the needs of a sudden surge in the number of patients requiring oxygen. The most commonly employed technique to monitor and manage an oxygen cylinder uses a pressure sensor where scaling up is an issue. Therefore, in this paper, a scalable solution that efficiently measures and monitors the available oxygen in the cylinder is proposed. The approach measures oxygen level using a weight sensor module and raises alerts during critical conditions such as low oxygen level and blockage or leakage of oxygen. The proposed system is a cost-effective, plug-and-play system that aids rapid deployment thereby providing timely care to the patients. Also, it does not require any change in the existing infrastructure making it suitable for a resource-constrained environment. The proposed system supports a web-based dashboard and mobile app that can be remotely accessed. 2022 IEEE. -
Narrowband and Wideband Directional Beamformer with Reduced Side Lobe Level
In this paper, the synthesis of narrow and wideband beamformers with reduced side lobe level and wide beam steering capability is presented. A closed form expression with slope equalization technique is derived for array factor of the beamformer to meet the desired beam-pattern specifications of Half Power Beam-Width (HPBW)and Side Lobe Level (SLL). The proposed beamformer design is adaptable to any bandwidth and null placement in the desired direction. The slope equalization method improves the SLL of the beamformer. Compared to Kaiser, Chebyshev, DPSS and Taylor beamformers, the proposed narrowband and wideband beamformers exhibit lower and tapered side lobes, hence improved First Null to Last Null (FNLN)ratio. The proposed wideband beamformer exhibits superior performance in the wideband frequency range of 1-3GHz. 2019 IEEE. -
A Study of Financialization of Commodity Markets in India
For numerous financial institutions, Commodity Futures (CF) has emerged as a widespread asset class since the 2000s. From 2000 to 2010, the estimation of the number of commodity index traders quadrupled, also, the number of hedge funds tripled. Recently, it has been noticed that in India, there occurs a vast inflow of investment toward the CF. Simultaneously, there occurs a problem of extremely higher prices along with volatility in commodity prices in India. However, studies on the financialization of the Commodity Market (CM) in India are not sufficient. This study was presented for analyzing the role of the financialization of CMs in India. Analyzing the association betweenCMs and equities markets in India is the major intention behind this study. Here, the Indian- MCX of India, the NSE of India, and the S&P500 Index are the sources from where the data has been gleaned. The outcome has been evaluated by utilizing a vector autoregression. The output demonstrated that no positive interdependence was exhibited by the correlation betwixt MCX Comdex returns and CNX Nifty. Consequently, a higher percentage of the mean value was attained by the commodity of daily returns of metal of commodity of agriculture. 2023 EDP Sciences. All rights reserved. -
DPETAs: Detection and Prevention of Evil Twin Attacks on Wi-Fi Networks
Numerous types of threats could become vulnerable to Wi-Fi networks. In terms of preventing and reducing their effect on the networks, it has become an imperative activity of any user to understand the threats. Even after thoroughly encrypting them, the route between the attackers device and the victims device may even be vulnerable to security attacks on Wi-Fi networks. It has also been noted that there are current shortcomings on Wi-Fi security protocols and hardware modules that are available in the market. Any device connected to the network could be a possible primary interface for attackers. Wi-Fi networks that are available in the transmission range are vulnerable to threats. For instance, if an Access Point(AP) has no encrypted traffic while it is attached to a Wi-Fi network, an intruder may run a background check to launch the attack.And then, attackers could launch more possible attacks in the targeted network, in which the Evil Twin attack have become the most prominent. This Evil Twin attack in a Wi-Fi network is a unique outbreak mostly used by attackers to make intrusion or to establish an infection where the users are exploited to connect with a victims network through a nearby access point. So, there are more chance to get users credentials by the perpetrators. An intruder wisely introduces a fake access point that is equivalent to something looks like an original access point near the network premises in this case. So, an attacker is capable of compromising the network when a user unconsciously enters by using this fake access point. Attackers could also intercept the traffic and even the login credentials used after breaching insecure networks. This could enable monitoring the users and perhaps even manipulating the behavior patterns of an authorized network user smoother for attackers. The key consideration of this research paper is the identification and avoidance of the Evil Twin attack over any Wi-Fi networks. It is named as DPETAs to address the strategies that intruders use to extract identities and what users need to do to keep them out of the networks. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Co-MoS2 nanoflower coated carbon fabric as a flexible electrode for supercapacitor
Cobalt doped MoS2 (Co-MoS2) nanoflowers have been successfully synthesized via a simple one-step hydrothermal method for supercapacitor applications. To identify the crystalline nature and morphology, the as-prepared material is characterized by XRD, SEM, and TEM measurements. The material exhibits a specific capacitance value of 86 F g-1 at a current density of 1 Ag-1 in symmetric two-electrode configuration with excellent cyclic stability of 98.5% even after 10,000 chargedischarge cycles. The results suggest the suitability of Co-MoS2 as an efficient electrode material for supercapacitors. 2021 Elsevier Ltd. All rights reserved. -
Assessment of Battery Technologies for Future of Electro-Mobility in Emerging Markets
In the outset of economic growth, the emerging country like India faces challenges due to rapid urbanization, infrastructure and city-congestion. The increased demand for mobility and a pivotal role of internal combustion engines from decades in the transportation segment have led to two influencing factors i.e., increased dependency on the oil import from fuel rich countries and alarming levels of emission. Hence it is essential for a country like India to venture into newer technologies to reform the transportation segment, reduce the dependency on the oil import and also has a positive impact on the pollutants. There are few technological barriers for the development of electric vehicles over internal combustion (IC) engines in terms of cost and performance of the vehicle. Along with the reduction of emissions, the electric vehicles should exhibit considerably good specific energy density and specific power density to emulate over the conventional (IC) engines. The three major constituents of electric vehicles are the battery, electric engine and the controller. The energy storage device forms the crux of the electric vehicle and has a significant role in its performance as well as forms the expensive component of the vehicle. Hence this paper involves the evaluation of various battery technologies, their performance requirements and options feasible for electric vehicles of the future. 2018 IEEE. -
STREE: A Secured Tree based Routing with Energy Efficiency in Wireless Sensor Network
The Wireless Sensor Network (WSN) applications are today not only limited to the research stage rather it has been adopted practically in many defense as well as general civilians applications. It has been witness that extensive research have been conducted towards energy efficient routing and communication protocols and it has been reached to an acceptable stages, but without having a secure communications wide acceptance of the application is not likely. Due to unique characteristics of WSN, the security schemes suggested for other wireless networks are not applicable to WSN. This paper introduces an novel tree based technique called as Secure Tree based Routing with Energy Efficiency or STREE using clustering approximation along with lightweight key broadcasting mechanism in hierarchical routing protocol. The outcome of the study was compared with standard SecLEACH to find that proposed system ensure better energy efficiency and security. 2015 IEEE. -
Assessing and Exploring Machine Learning Techniques for Cardiovascular Disease Prediction using Cleveland and Framingham Datasets
Heart disease prediction using machine learning has garnered significant attention due to its potential for early diagnosis and intervention. This study presents an analysis of various machine learning algorithms applied to HD prediction across multiple research papers. The goal of this study is to analyze the performance and predictive capabilities of various machine learning algorithms in predicting heart disease across different datasets and research papers. Algorithms such as Logistic Regression, Random Forest, Support Vector Machine, Decision Tree, Naive Bayes, and Gradient Boosting were evaluated using diverse datasets and parameters. In the Cleveland dataset, both Random Forest and Decision Tree classifiers achieved perfect accuracy 100%. Conversely, in the Framingham dataset, Random Forest exhibited the highest accuracy at 94%, followed by SVM at 87.45%, and Decision Tree at 85.23%. While specific algorithm performance varies depending on the dataset and parameters considered, ensemble methods like Random Forest often demonstrate superior performance. These findings underscore the effectiveness of machine learning in HD prediction and emphasize the significance of algorithm selection in developing accurate predictive models for cardiovascular health. 2024 IEEE. -
An approach for efficient capacity management in a cloud
Cloud computing is an emerging technology where computing resources such as software and hardware are accessed over the internet as a service to customers. In the past, due to less demand, cloud capacity management was not critical. However, with the increase in demand, capacity management has become critical. Cloud customers can frequently use web-based portals to provision and de-provision virtual machines on demand. Due to dynamic changes as per the demand, managing capacity becomes a challenging task. In this paper, we discuss the emergence of cloud computing, traditional versus cloud computing, and how capacity management can be efficiently handled in a cloud. A detail on high availability of virtual machines in a cloud using the N+1 model is discussed in this paper. With templates, many repetitive installation and configuration tasks can be avoided. We discuss the sizing of templates and the overheads of using virtual machines. We suggest ideal combinations of sizing templates to create virtual machines with optimum utilization of blades. Finally we discuss a few benefits of efficient capacity management in cloud computing. 2017 IEEE. -
Design and Development of Mobile Robot Manipulator for Patient Service During Pandemic Situations
Time and manpower are important constraints for completing large-scale tasks in this rapidly growing civilization. In most of the regular and often carried out works, such as welding, painting, assembly, container filling, and so on, automation is playing a vital part in reducing human effort. One of the key and most commonly performed activities is picking and placing projects from source to destination. Constant monitoring of patient bodily indicators such as temperature, pulse rate, and oxygen level and service of the patients becomes challenging in the current pandemic condition to the nurses and medical staffs. In consideration to this, a mobile robot with an integrated robotic arm has been designed and developed which can be available for service of patients continuously alongside monitoring them in general ward as well as in ICU of hospitals. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Automatic Weld Features Identification and Weld Quality Improvement in Laser Sensor Integrated Robotic Arc Welding
In this study, an integration of point laser sensor in robotic arc welding has been performed for achieving robotic positional accuracy automatically in every welding cycle. With the help of defined focal length of laser sensor, weld seam positions as well as weld gap have been found automatically for any newly positioned work-piece. If there is any change in robot positioning compared to the master job, the shift in every axis is sent as signal to the robot controller so that robot end effector will adjust the shift amount automatically. The welding process parameters are set at optimal values. Taguchi approach so that maximum values of weld quality in terms of depth of penetration, yield strength and ultimate strength can be achieved in every welding cycle. Overall, with the proposed approach, a smart and productive way of operating industrial welding robot has been proposed which can be implemented in any medium to large scale industries for obtaining welding joints with minimum defects. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Non-Alcoholic Fatty Liver Disease Prediction with Feature Optimized XGBoost Model
Non-alcoholic fatty liver disease (NAFLD) is an expanding health threat, posing significant risks for long-term complications. Early detection and intervention are crucial, but traditional diagnostic methods can be expensive and invasive.This study investigates the utilization of machine learning models for predicting liver diseases from various out-sourced datasets..We employed Decision Trees, Random Forests, and Support Vector Machines (SVMs) to predict NAFLD based on various clinical and demographic features. Model performance was evaluated by calculating accuracy, precision,deviation and accuracy-score.All these models achieved promising accuracy levels, ranging from 80% to 90%, showcasing their potential for NAFLD prediction. Among them, XG-Boost demonstrated the highest performance, with an accuracy of 90% and more.This study demonstrates the effectiveness of machine learning models in predicting NAFLD with high accuracy using readily available data. Further research with larger sized and more varied datasets will vindicate these models for real-world application in clinical settings. 2024 IEEE. -
Development of LIDAR-SLAM Integrated Low Cost Health Care Monitoring Robot with Sustainable Material
Beyond the global pandemic, healthcare has faced a myriad of challenges, from rising costs and accessibility issues to the need for precision in patient care and efficient medication delivery. This project embodies a visionary response to the multifaceted challenges faced by healthcare systems in health centers located in rural areas. The proposed research work focused on design and development of a health care monitoring robot with integration of 3D LIDAR Simultaneous Localization and Mapping (SLAM) based navigation approach, introduction of sustainable materials like bamboo and wood composites for development of robotic arm and robotic body frames. Also, from the initial tests it has been observed that with the developed mobile robot functions like precision medicine delivery, Open AI-Enabled continuous monitoring, hospital environment sanitization and emergency oxygen supply can be performed efficiently. 2024 IEEE. -
Influence of cryogenic treatment of cutting tool inserts on tool wear and surface roughness during milling of Inconel 718
Inconel 718 is a superalloy which is a hard to difficult machining material. It is widely used in industries such as aerospace, defence, energy production, biomechanical and marine. It is used at elevated temperatures and areas where thermal and fatigue stress is high. Due to its superior quality and hard surface, machining of this material becomes a challenge. Cutting tools have failed enormously in milling this material. However, tungsten carbide and ceramics have found some effective features in creating a better machinability. In this paper, microstructure of the inserts have been studied during machining to determine low surface roughness on the material. Cryogenic treatment of the inserts has been carried out to improve tool life and compared with the untreated inserts. 2020 Author(s).