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Wheat Yield Prediction using Temporal Fusion Transformers
In precision framing, Machine Learning models are an essential decision-making tool for crop yield prediction. They aid farmers with decisions like which crop to grow and when to grow certain crops during the sowing season. Many Machine Learning algorithms have been used to support agriculture yield prediction research, but it is observed that Deep Learning models outperform the benchmark Machine Learning algorithms with a significant difference in accuracy. However, though these Deep Learning models perform better, they are not preferred or widely used in place of Machine Learning models. This is because Deep Learning methods are black box methods and are not interpretable, i.e., they fail to explain the magnitude of the impact of the features on the output, and this is unsuitable for our use case.In this paper, we propose using Temporal Fusion Transformer (TFT), a novel approach published by Google researchers for wheat yield prediction viewed as a Time Series Forecasting problem statement. TFT is the state-of-the-art attention-based Deep Learning architecture, which combines high-performance forecasting with interpretable insights and feature importance. We have used TFT to perform wheat yield prediction and compare its performance with various Machine Learning and Deep Learning algorithms. 2023 IEEE. -
Spoken Language Identification using Deep Learning
A crucial problem in natural language processing is language identification, which has applications in speech recognition, translation services, and multilingual content. The five main Indian languages that are the subject of this study are Hindi, Bengali, Tamil, English, and Gujarati. A Deep Neural Network is introduced in the paper which is specifically made to use Mel-Frequency Cepstral Coefficients (MFCCs) for sophisticated language categorization. The suggested architecture of the model, which includes batch normalisation and tightly linked layers, helps it to be adept at identifying complex linguistic patterns. Comparing the research to the source work [18], promising improvements are shown, highlighting the potential of the model in language detection. 2024 IEEE. -
QUALITY OF WORK LIFE IN RELATION TO PEOPLE CAPABILITY MATURITY MODEL IN IT AND ITES ORGANIZATIONS
The new found concern for Quality of Work Life in corporate life perhaps has been due to the realization that human resource is the most important asset which must be released and developed. Management viewed QWL programs as a way of reducing costs and improving productivity. The success of any organization depends on how it attracts recruits, motivates and retains its workforce. Human capital is clearly emerging as a key engine of economic growth, and it is evident that the skills and competencies of the workforce impact positively on productivity and competitiveness. In this regard investment in human capital would appear to be a prerequisite to economic success .In this new scenario People capability maturity model offers unlimited potential to develop and maximize human capital and organizational competence in the interest of the firm ,the employee ,the consumer ,the shareholder and not least the family. People capability maturity model is a maturity framework developed at the software engineering institute that guides the organizations in improving the ability to attract, develop, motivate, organize and retain talent.. Economies of the world over and companies facing tough domestic and international markets have been posing a serious challenge to all concerned. This coupled with every changing technology and increased access to information has necessitated studying organization with respect to productivity, efficiency and quality of service rendered. All this demands a new work culture, employee motivation, commitment to the job and organizational goals. Some organizations in the service sector have implemented PCMM to address all these organizational issues. However we have very little information at the grass root level to comprehend QWL, and very little research on QWL Life in relation to PCMM hence this study. Based on the objectives of the study a detailed questionnaire was constructed by the researcher. The questionnaire has three parts measuring demographics, implementation of PCMM and six dimensions of QWL. It was measured on a 5 point likert scale 1 indicating strongly disagree to 5 indicating strongly agree. The Cronbachs alpha reliability for the PCMM and the QWL for the present sample was .80 and above. The questionnaire was completed by 230 respondents using judgmental sampling technique from PCMM implemented and non implemented IT and ITES organizations. It was found that Quality of work life was not significantly higher in companies that implemented People capability maturity model as compared to other companies. Amongst all the dimensions of Quality of work life the only dimension influenced and affected by People capability maturity model was self evaluation of performance .It was found that there was a variation of 20.1% in the Quality of work life. In terms of correlation, the study indicated that there was significant intra relationship between the 6 dimensions of Quality of work Life; significant intra relationship between the People Capability Maturity Model related items and significant interrelationship between 6 dimensions of Quality of Work Life and the People capability maturity model related items. Amongst all the 6 dimensions of Quality of Work Life the only dimension that was significantly different across gender was self evaluation of performance. Females had higher self evaluation of performance as compared to the male counterparts. On the basis of the results attained from the current study we can clearly imply that Quality of work life dimensions is definitely positively influenced, affected and correlated with People Capability Maturity Model though there is no difference in Quality of Work Life among People Capability Maturity Model implemented and Non implemented IT and ITES organizations. The results from the study will have significant implications on the companies that have not implemented People Capability Maturity Model to join the group of People capability maturity model implemented companies as this will help the organizations to prepare the employees psychologically to meet the demands and challenges which otherwise may risk a poor Quality of work life program implementation. Key Words: Organizational behavior, Human Resource Management, People Capability Maturity Model, Quality of Work Life, General linear model. -
An iot based wearable device for healthcare monitoring
Nowadays IoT (Internet of Things) devices are popularly used to monitor humans remotely in the healthcare sector. There are many IoT devices that are being introduced to collect data from human beings in a different scenario. These devices are embedded with sensors and controllers in them to collect data. These devices help to support many applications like a simple counting step to an advanced rehabilitation for athletes. In this research work, a mini wearable device is designed with multiple sensors and a controller. The sensors sense the environment and the controller collects data from all the sensors and sends them to the cloud in order to do the analysis related to the application. The implemented wearable device is a pair of footwear, that consists of five force sensors, one gyroscope, and one accelerometer in each leg. This prototype is built using a Wi-Fi enabled controller to send the data remotely to the cloud. The collected data can be downloaded as xlsx file from the cloud and can be used for different analyses related to the applications. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Enhancements to randomized web proxy caching algorithms using data mining classifier model
Web proxy caching system is an intermediary between the users and servers that tries to alleviate the loads on the servers by caching selective web pages, behaves as the proxy for the server, and services the requests that are made to the servers by the users. In this paper, the performance of a proxy system is measured by the number of hits at the proxy. The higher number of hits at the proxy server reflects the effectiveness of the proxy system. The number of hits is determined by the replacement policies chosen by the proxy systems. Traditional replacement policies that are based on time and size are reactive and do not consider the events that will possibly happen in the future. The outcomes of the paper are proactive strategies that augment the traditional replacement policies with data mining techniques. In this work, the performance of the randomized replacement policies such as LRU-C, LRU-S, HARM, and RRGVF are adapted by the data mining classifier based on the weight assignment policy. Experiments were conducted on various data sets. Hit ratio and byte hit ratio were chosen as parameters for performance. Springer Nature Singapore Pte Ltd. 2019. -
Enhancements to Content Caching Using Weighted Greedy Caching Algorithm in Information Centric Networking
Information-Centric Networks (ICN) or Future Internet is the revolutionary concept for the existing infrastructure of the internet that changes the paradigm from host-centric networks to data-centric networks. Caching in Information-Centric Networks (ICN) has become one of the most critical research areas in today's world, especially for the leading in content delivery over Internet companies like Netflix, Facebook, Google, etc. This paper is intended to propose a novel Caching strategy called Weighted Greedy Dual Size Frequency for caching in Information-Centric networks. In this paper, the WGDSF considers multiple critical factors for maintaining the Web Content efficiently in ICN Caching Router. Simulation is done for the various performance metrics like Cache Hit ratio, Link load, Path Stretch, and Latency for WGDSF cache replacement algorithm, and results shown that WGDSF outperforms well compared with LRU, LFU, and RAND Caching Strategies. 2020 The Authors. Published by Elsevier B.V. -
Enhancing greedy web proxy caching using weighted random indexing based data mining classifier /
Egyptian Informatics Journal, Vol.20, Issue 2, pp. 117-130, ISSN No. 1110-8665. -
Enhancements to greedy web proxy caching algorithms using data mining method and weight assignment policy /
International Journal of Innovative Computing, Information And Control, Vol.14, Issue 4, pp.1311-1326, ISSN No. 1349-4198. -
Detection of cyber crime based on facial pattern enhancement using machine learning and image processing techniques
Cybercrime has several antecedents, including the rapid expansion of the internet and the wide variety of users around the world. It is now possible to use this data for a variety of purposes, whether for profit, non-profit, or purely for the benefit of the individual. As a result, tracing and detecting online acts of terrorism requires the development of a sound technique. Detection and prevention of cybercrime has been the subject of numerous studies and investigations throughout the years. An effective criminal detection system based on face recognition has been developed to prevent this from happening. Principle component analysis (PCA) and linear discriminant analysis (LDA) algorithms can be used to identify criminals based on facial recognition data. Quality, illumination, and vision are all factors that affect the efficiency of the system. The goal of this chapter is to improve accuracy in the facial recognition process for criminal identification over currently used conventional methods. Using proposed hybrid model, we can get the accuracy of 99.9.5%. 2022, IGI Global. All rights reserved. -
Photocatalytic Degradation of Textile Dyes Using Artemisia stelleriana Besser Mediated Nanoparticles
Artemisia stelleriana is widely used as an ornamental plant and belongs to the family Asteraceae. In the current study, A. stelleriana-mediated Zinc oxide newlinenanoparticles (AS-ZnONPs), Silver nanoparticles (AS-AgNPs) and Silver/Zinc oxide bimetallic nanoparticles (AS-Ag/ZnONPs) were synthesised using one-pot method. The UV-Vis spectral analysis revealed characteristic peaks at 358 nm for AS-ZnONPs, newline425 nm for AS-AgNPs, and 357 nm and 473 nm for AS-Ag/ZnONPs. Fourier transform infrared spectroscopy (FTIR) analysis identified phytoconstituents taking part in newlinenanoparticle synthesis, manifesting the presence of alkaloids, phenols, saponins, and newlineflavonoids. The synthesised AS-ZnONPs, AS-AgNPs, and AS-Ag/ZnONPs have a crystalline nature and were confirmed using X-ray diffraction (XRD) analysis. The crystallite sizes of the AS-ZnONPs, AS-AgNPs, and AS-Ag/ZnONPs were 22.54 nm, 18.67 nm, and 10.4 nm, respectively. Spherical-shaped Ag nanoparticles and hexagonal, cylindrical, and spherical-shaped ZnO nanoparticles were synthesized from the leaf extract of A. stelleriana. The average size of the synthesised nanoparticles was 37.6 nm and 71.2 nm for AS-ZnONPs and AS-AgNPs, respectively. On the other hand, spherical-shaped AS-Ag/ZnONPs were synthesized with an average size of 35.3 nm. The photocatalytic degradation activity of AS-ZnONPs showed 93.44%, 47%, 94.76%, 99.9%, and 74.82% degradation for Reactive Blue 220 (RB220), Reactive Blue 222A (RB222A), Reactive Red 120 (RR120), Reactive Yellow 145 (RY145) and newlineReactive Yellow 86 (RY86) dyes respectively after 320 min of UV light exposure. ASZnONPs showed positive results for all five dyes and a better percentage of degradation was observed in a 5 ppm concentration of dye treated with 1 mg/mL concentration of newlineAS-ZnONPs. In the case of AS-AgNPs, RB220 and RB222A dyes showed positive results but no degradation was observed in the remaining three dyes. After 320 min of UV light exposure, AS-AgNPs showed 95.98%, and 100% degradation of RB220 and RB222A dyes respectively. -
Reinforcement Learning based Autoscaling for Kafka-centric Microservices in Kubernetes
Microservices and Kafka have become a perfect match for enabling the Event-driven Architecture and this encourages microservices integration with various opensource platforms in the world of Cloud Native applications. Kubernetes is an opensource container orchestration platform, that can enable high availability, and scalability for Kafkacentric microservices. Kubernetes supports diverse autoscaling mechanisms like Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA) and Cluster Autoscaler (CA). Among others, HPA automatically scales the number of pods based on the default Resource Metrics, which includes CPU and memory usage. With Prometheus integration, custom metrics for an application can be monitored. In a Kafkacentric microservices, processing time and speed depends on the number of messages published. There is a need for auto scaling policy which can be based on the number of messages processed. This paper proposes a new autoscaling policy, which scales Kafka-centric microservices deployed in an eventdriven deployment architecture, using a Reinforcement Learning model. 2022 IEEE. -
Enhancing Kubernetes Auto-Scaling: Leveraging Metrics for Improved Workload Performance
Kubernetes is an open-source production-grade container orchestration platform, that can enable high availability and scalability for various types of workloads. Maximizing the performance and reducing the cost are two major challenges modern applications encounter. To achieve this, resource management and proactively deploying resources to meet specific application requirements becomes utmost important. Adopting Kubernetes auto-scaler to fit one's needs are important to maximize the performance. This study aims to perform a comprehensive analysis of Kubernetes auto-scaling policies. This paper also lists out the various parameters considered for auto-scaling, and prediction methods used to efficiently handle resource requirements of applications. The research findings reveal a scarcity in the existing work regarding the variety of workload based auto-scaling and custom metrics. This paper provides a concise overview of a forthcoming research endeavor that explores the utilization of custom metrics in conjunction with auto-scaling. 2023 IEEE. -
A study of thinking style, teacher effectiveness and emotional intelligence of secondary school teachers of Bangalore city
Education is a social process by which knowledge is transferred to students through the intermediaries, the teachers. It can be had from non - formal and formal systems of Education. All formal systems are based on the classroom teaching. "The destiny of India is being shaped in her classroom", has been pointed out by the Indian Education Commission (KOTHARI COMMISSION) (1964-66) and to that, it may be safely added that the destiny of these classrooms is being shaped by the teachers. According to the American Commission, the quality of the nation depends upon the quality of the citizens. The quality of its citizens depends, not exclusively, but in critical measure upon the quality of their Education. The quality of their education depends more upon the quality of teachers. Humayun Kabir rightly said once, "Without good teachers even the best of system is bound to fall, with good teachers, even the defects of a system can be largely overcome". The teacher is the flywheel of the whole educational machine. Elaborate blue prints, modern school plans, the best equipment, the newest of the new
media or progressive methods will remain dead fossils unless there is the right use of teachers. The document, Challenge of Education -A Policy Perspective (1985) has highlighted that teacher performance is the most crucial input in Education. No development has reached the threshold of development of new technology which is likely to revolutionize the classroom teaching. -
Smart internet of things (IOT) enabled agricultural farming system /
"Patent Number: 202241047525, Applicant: Justin Joy.
Smart Internet of Things (IoT) enabled agricultural farming system that aims to extract the values of soil parameters by using IoT sensors and appropriately control the watering of crops. Thus, this system allows crop cultivation even in a hot and dry climate. Crops can be watered remotely and temperature controlled to be maintained within an appropriate range. Automated irrigation systems using WSN (Wireless Sensor Networks) and GPRS (General Packet Radio Service) modules assist in optimizing water use for agriculture crops. This system comprises a distributed wireless sensor network with soil moisture and temperature sensor in WSN. -
A Study on Restrained Geodetic Domination in Graphs
In a graph G = (V, E), the shortest path between any two vertices u and v in G is u and#8722; v geodesic. This distance concept leads to the introduction of geodetic set and geodetic number which has wide applications in location theory and convexity theory. A vertex subset S of a graph G is said to be a geodetic set, if all vertex in G is in u and#8722; v geodesic for some pair of vertices u and v in S. The minimum cardinality of such a set is the geodetic number and is denoted as g(G). A vertex subset M of a graph G is said to be a dominating set of G if for all vertex v and#8712; V (G), either v and#8712; M or v is adjacent to a vertex in M. The minimum cardinality of such a set is the domination number and is denoted by and#947;(G). In general, the geodetic set and newlinethe dominating set of a graph need not be the same. This led to the study of the geodetic dominating set. If a geodetic set S is a dominating set of a graph G, then S is called a geodetic dominating set. The minimum cardinality of such a set is the geodetic domination number, which is represented by and#947;g(G). There are several studies done on the geodetic and domination concepts so far. In the present study, we have explored the concept of restrained geodetic domination and its structural properties in graphs particularly in product graphs and derived graphs. A vertex subset S of a graph G = (V, E) is called a restrained geodetic dominating set if S is a geodetic dominating set of G and lt V and#8722; S gt has no isolated vertex. The minimum cardinality of such a set is called restrained geodetic domination number, which is denoted by and#947;gr(G). We have studied this concept for diand#64256;erent classes of graphs and concerning the graph operations such as Cartesian product, corona product, and join of graphs. Further, the study is extended to restrained geodetic domination in derived graphs such as edge subdivision graph, line graph and power of a graph. Also, investigated the properties of graphs with the restrained geodetic domination number equal to the order of the graph. -
Acculturation and adaptation experiences of third generation adolescent migrants of Andaman and Nicobar islands
Andaman and Nicobar Islands saw movement from 1857 amid the reformatory settlement design of the British Government followed by Independent relocation after 1947. The relocation makes a heritage of acculturation and adaptation experiences of the migrants and their descendants. The administration stretched out certain facilities to the migrants like job reservation, simple access to government jobs in the Islands, reservation for higher education and so forth amid the 50's, 60's and 70's. The number of inhabitants in the Islands has now come to a disturbing level and the facilities and opportunities have contracted down, yet individuals have not changed their outlook rather and for them, everything stays in and around the Islands. This study aims to understand the acculturation and adaptation experiences of the third generation adolescent migrants of Andaman and Nicobar Islands. The study proposes to follow the methodology based on grounded theory. Using Theoretical sampling method, third generation adolescent migrants of the Islands were recruited for the study. The average age of the participants recruited for this study is 18.6 years with 83% of them are male and the remaining 17% are female. Individual interview sessions, lasting approximately 45 to 90 minutes were conducted with the participants to know how their acculturation and adaptation experiences. The transcripts of the interviews were thematically analyzed with the help of Nvivo 10. The transcripts were dissected and 1950 codes from 7903 text segments which became the main foundation for the analysis of data. The codes were further reduced into 54 basic themes, again into 21 organizing themes and finally into 05 global themes. The process of acculturation, psychological adaptation, socio-cultural adaptation, influencing factors and academic aspiration were the global themes which became the building block for five thematic networks addressing the main and specific objectives of the study. -
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IoT Based Risk Monitoring System
The Internet of things (IoT) aims at connecting different objects, things using internet. The IoT is expanding rapidly and this motivates to apply for the food preservation domain such as preserve the standard of the veggies and fruits. In this paper we have worked on a cold storage system to analyze the environmental conditions under which the food item is being stored. The proposed system senses the temperature, moisture, gas parameters of surrounding environment as these parameters affect nutritional values of food items. An Arduino-based system is created and put into operation; it serves as both a central hub and a network layer for the refrigerated holding tank. It is also linked to the cloud, where an open-source application server supports digital storage functions. By establishing a connection to the database (DB) via its IP address, the measured variables are delivered to the base station (BS) from the cloud and stored there. Then, a cooperative sensing model that uses many observed information as input and one merged informational item or action to be performed as output is tried. As a result, numerous inputs, such as temperature and humidity, were combined and averaged to provide a tightly integrated result. Last, the system integrated an android mobile application which is used to facilitate user interaction and connect through IoT based system that is station or gateway and the internet. GPS is Used to track the remote cold storage and transport container live locations. 2022 IEEE. -
Transforming workplace stress: The importance of neuroleadership for building resilient work environment
Workplace stress is a common issue that can significantly impact both employees and employers. This study explores the dynamic intersection of workplace stress and the emerging field of neuroleadership, offering insights into fostering resilient work environments. Drawing on the principles of neuroleadership, the chapter highlights how an understanding of neuroscience can inform leadership practices and contribute to creating resilient workplaces. This chapter discusses the neurological basis of stress and the role of leaders in mitigating its effects. It explores emotional intelligence in leadership and the impact of organisational culture on stress resilience. The chapter suggests practical interventions like mindfulness practices and supportive work environment initiatives grounded in neuroscience to cultivate a culture of wellbeing. By adopting resilient leadership strategies and understanding the neuroscience of stress, organisations can create environments that promote employee wellbeing and navigate the challenges of the modern workplace. 2024, IGI Global. All rights reserved.