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SmartHealth: Personalized Diet and Exercise Plans Using Similarity Modeling
Due to the growing prevalence of chronic diseases stemming from unhealthy lifestyles, a personalized approach to patient care is crucial. This paper delves into a system that utilizes cosine similarity and Pearson correlation to generate tailored diet and exercise plans, effectively managing chronic diseases. The system focuses on common chronic conditions like diabetes, hypertension, and thyroid disorders. Through sophisticated similarity modeling for diet and exercise, the proposed system provides integrated and personalized lifestyle recommendations, outperforming non-personalized or basic rule-based systems. 2024 IEEE. -
HULA: Dynamic and Scalable Load Balancing Mechanism for Data Plane of SDN
Multi-rooted topologies are used in large-scale networks to provide greater bisectional bandwidth. These topologies efficiently use a higher degree of multipathing, probing, and link utilization. An end-to-end load balancing strategy is required to use the bisection bandwidth effectively. HULA (Hop-by-hop Utilization-aware Load balancing Architecture) monitors congestion to determine the best path to the destination but, needs to be evaluated in terms of scalability. The authors of this paper through artifact research methodologies, stretch the scalability up to 1000 nodes and further evaluate the performance of HULA on software defined network platform over ONOS controller. A detailed investigation on HULA algorithm is analysed and compared with four proficient large-scale load balancing mechanisms including: connection hash, weighted round-robin, Data Plane Devlopment Kit (DPDK) technique, and a Stateless Application-Aware Load-Balancer (SHELL). 2023 IEEE. -
P4 based Load Balancing Strategies for Large Scale Software-Defined Networks
To meet the large demands of future networks, several large-scale Software Defined Networking (SDN) test-beds have been designed. The increasing complexity of networks has resulted in convoluted methods for managing and orchestrating efficiently across a wide range of network environments. The load balance function is impaired when the controller fails to connect with the switches. A traditional Load Balancer (LB) must decapsulate layers one by one and get the information needed to run load balancing algorithms. For instance, OpenFlow, NetConf, Programming Protocol-independent Packet Processors (P4), and Data Plane Developement Kit (DPDK) provide network programmability at both the control and data plane levels. In this paper, authors implement load balancing using the P4 programming language without the need of a controller, the P4 load balancer can operate on its own. Controller's support is used to keep track on the health of the web servers. In this situation, the controller can identify a server failure and notify the P4 load balancer, which will restrict requests to the malfunctioning server, lowering the dispatching failure rate. A detailed investigation of various load balancing mechanisms is analysed in this paper followed by the identification of four potential approaches to large-scale SDN tests, including connection hash, weighted round-robin, DPDK technique, a Stateless Application-Aware Load-Balancer (SHELL). 2022 IEEE. -
Application of Artificial Intelligence on Smart Tourism Eco Space: An Integrated Approach in Post-COVID-19 Era
The AI-integrated approach in recent times has evolved with innovative techniques and gained much importance in the post-COVID-19 scenario. This chapter extends contemporary and exponential research findings for Smart Tourism Practices and the Application of AI-enabled systems for the Tourism Ecosystem. It highlights for various service segments like hotels, motels, resorts, restaurants, cafes, airlines, and destinations under this large umbrella known as the hospitality sector. Smart tourism eco space capacitates an ICT-enabled system consolidates tourism resources and information technologies. Perhaps, with multiple challenges, a successful implementation of smart tourism approaches empowers and supports a smart system in place. The tourism eco space is highly vulnerable, and this situation in the service sector creates an intense requirement of a comprehensive view of digitally enabled smart tourism eco space with innovative mechanisms to remain contact-free with less human intervention. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Impact of Rupee Volatility on the Financials of the Indian IT Companies
International Journal of Advanced Research in Economics and Commerce, Vol-1 (1), pp. 1-8. ISSN-2320-7248 -
Analysis on techniques used to recognize and identifying the Human emotions
Facial expression is a major area for non-verbal language in day to day life communication. As the statistical analysis shows only 7 percent of the message in communication was covered in verbal communication while 55 percent transmitted by facial expression. Emotional expression has been a research subject of physiology since Darwins work on emotional expression in the 19th century. According to Psychological theory the classification of human emotion is classified majorly into six emotions: happiness, fear, anger, surprise, disgust, and sadness. Facial expressions which involve the emotions and the nature of speech play a foremost role in expressing these emotions. Thereafter, researchers developed a system based on Anatomic of face named Facial Action Coding System (FACS) in 1970. Ever since the development of FACS there is a rapid progress in the domain of emotion recognition. This work is intended to give a thorough comparative analysis of the various techniques and methods that were applied to recognize and identify human emotions. This analysis results will help to identify proper and suitable techniques, algorithms and the methodologies for future research directions. In this paper extensive analysis on various recognition techniques used to identify the complexity in recognizing the facial expression is presented. Copyright 2020 Institute of Advanced Engineering and Science. All rights reserved. -
Product specific determinants of electronic gadget purchase intention - a case of the purchase behaviour of Indian youth
This study investigated the impact of product specific features of electronic gadgets on the purchase intention on the Indian youth. The study was quantitative in nature and data was collected from 650 young electronic gadget consumers in Bengaluru, India using structured questionnaires. Descriptive statistics and structural equation modelling (SEM) were used for data analysis. Brand image, product design, and country of origin are referred as product evaluation attributes; and corporate identity were identified as the determinants of purchase intention. Respondents were neutral regarding the role of product evaluation attributes and corporate identity in their purchases, but acknowledged these factors' importance. Findings implied a positive and significant influence of product evaluation attributes on the corporate identity of companies, and purchase intention of the youth. However, corporate identity did not influence purchase intention, clearly indicating that only product specific features, such as brand, design and country of origin are considered when youngsters purchase gadgets. Copyright 2022 Inderscience Enterprises Ltd. -
Load Balancing Strategy for Large Scale Software Defined Networks
Programmability has left its mark on every facet of business, with technology playing newlinean integral role. Social networking industry trends underscore technology s ubiquity in newlinenearly every business transaction. Traditional networks grapple with numerous challenges, rendering them ill-equipped to process and handle the demands of the modern newlinelandscape effectively. The lack of programming in these networks leads to stagnation, newlineinhibiting their ability to evolve or enhance performance. The advent of Software Defined Networks (SDN) has introduced increased flexibility into conventional networks, newlineopening avenues for creating innovative services. newlineSDN technology addresses challenges in large-scale networks, offering solutions for newlinehigh throughput, virtualization, fault detection, and load balancing, providing effective network management. The rapid expansion of network services and applications newlinein SDN environments demands sophisticated load-balancing solutions that adapt to newlinedynamic traffic patterns and varying service requirements. This study presents a pioneering algorithm, the Dynamic Load Balancing Algorithm (DLBA), which utilizes the newlineProgramming Protocol-independent Packet Processors (P4) language. The algorithm is newlinespecifically crafted to tackle the issues associated with optimizing traffic distribution in newlinethe data plane of SDN. newlineP4 programming language, recognized as one of the most robust languages, addresses newlinethe limitations of traditional networking, enhancing programmability and agility by newlinedistributing the load across the network. The research implements a novel quotDynamic newlineLoad Balancing Algorithmquot using the P4 language to instill dynamism and achieve load newlinebalance in large-scale networks. The P4-based implementation showcases dynamicity, scalability, flexibility, and adaptability. This research commences with thoroughly newlineexamining existing load-balancing algorithms implemented using the P4 language, followed by a comparative analysis between these algorithms and DLBA. -
Optimized score card for mentoring student using artificial intelligence and methods thereof /
Patent Number: 202011040658, Applicant: Dr Priti Verma.
The invention discloses a mentoring system capable of improving student™s performance in the field of Learning in Theoretical, practical, behavioral, sports, cultural activities and life skills for the betterment of the life of an individual. -
Grading of facial emotions using multimodal approach /
Patent Number: 202141020173, Applicant: Mr Praveen Kulkarni.
Emotion analysis is an area which is been widely used in forensic crime detection domain, mentoring device for depressed students, psychologically affected patient treatment. Although significant work has been done in this area, the current system helps only in identifying the emotions but not in identifying the level of emotions like whether an individual is truly happy/sad or pretending to be happy/sad. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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). -
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.