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Improved dhoa-fuzzy based load scheduling in iot cloud environment
Internet of things (IoT) has been significantly raised owing to the development of broadband access network, machine learning (ML), big data analytics (BDA), cloud computing (CC), and so on. The development of IoT technologies has resulted in a massive quantity of data due to the existence of several people linking through distinct physical components, indicating the status of the CC environment. In the IoT, load scheduling is realistic technique in distinct data center to guarantee the network suitability by falling the computer hardware and software catastrophe and with right utilize of resource. The ideal load balancer improves many factors of Quality of Service (QoS) like resource performance, scalability, response time, error tolerance, and efficiency. The scholar is assumed as load scheduling a vital problem in IoT environment. There are many techniques accessible to load scheduling in IoT environments.With this motivation, this paper presents an improved deer hunting optimization algorithm with Type II fuzzy logic (IDHOA-T2F) model for load scheduling in IoT environment. The goal of the IDHOA-T2F is to diminish the energy utilization of integrated circuit of IoT node and enhance the load scheduling in IoT environments. The IDHOA technique is derived by integrating the concepts of Nelder Mead (NM) with the DHOA. The proposed model also synthesized the T2L based on fuzzy logic (FL) systems to counterbalance the load distribution. The proposed model finds useful to improve the efficiency of IoT system. For validating the enhanced load scheduling performance of the IDHOA-T2F technique, a series of simulations take place to highlight the improved performance. The experimental outcomes demonstrate the capable outcome of the IDHOA-T2F technique over the recent techniques. 2022 Tech Science Press. All rights reserved. -
Improved Deep Learning Model for Detection and Classification of Pneumonia from X-Ray Images
Pneumonia is a severe respiratory disease that can lead to inflammation, fluid accumulation in lungs and breathing difficulties, which needs immediate and accurate diagnosis. Chest X-Ray images are a necessary tool to diagnose pneumonia because manual interpretation poses challenges, particularly for radiologists with less expertise. Artificial intelligence (AI), specifically Convolutional Neural Networks (CNNs), has become a significant in the field of pneumonia detection within chest X-Ray images in recent years. This research presents SarNet, a neural network model developed for the identification of pneumonia in chest X-Ray images. The study involved the compilation of dataset containing chest X-Ray images categorized as normal, pneumonia, and COVID-19 pneumonia cases, each accompanied by appropriate annotations. This dataset was employed as the basis for training and assessing SarNet's performance, underscoring its promise in transforming the diagnosis of pneumonia. SarNet proved highly effective, achieving good accuracy, sensitivity, and specificity compared to traditional diagnostic methods. The model's simplicity, with 41 layers, strikes a balance between depth and computational complexity, enhancing efficiency and ensuring accurate pneumonia detection. Furthermore, the study expanded its scope to include COVID-19 pneumonia detection. SarNet achieved an accuracy of 99.15% in binary classification and 94.9% in multiclass classification, including healthy, pneumonia, and COVID-19 pneumonia cases. -
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Improved Crypto Algorithm for High-Speed Internet of Things (IoT) Applications
Modern technologies focus on integrated systems based on the Internet of Things (IoT). IoT based devices are unified with various levels of high-speed internet communication, computation process, secure authentication and privacy policies. One of the significant demands of present IoT is focused on its secure high-speed communication. However, traditional authentication and secure communication find it very difficult to manage the current need for IoT applications. Therefore, the need for such a reliable high-speed IoT scheme must be addressed. This proposed title introduces an enhanced version of the Rijndael Cryptographic Algorithm (Advanced Encryption Standard AES) to obtain fast-speed IoT-based application transmission. Pipeline-based AES technique promises for the high-speed crypto process, and this secure algorithm targeted to fast-speed Field Programmable Gate Array (FPGA) hardware. Thus, high-speed AES crypto algorithms, along with FPGA hardware, will improve the efficiency of future IoT design. Our proposed method also shows the tradeoff between High-Speed communications along with various FPGA platforms. 2020, Springer Nature Switzerland AG. -
Improved Computer Vision-based Framework for Electronic Toll Collection
The world is moving towards artificial intelligence and automation because time is the most crucial asset in today's scenario. This paper proposes an automatic vehicle fingerprinting system that avoids long waiting times in toll plazas with the help of computer vision. The number plate recognition and vehicle re-identification focus on this research. Day/night IR cameras are used to get the images of the vehicle and its number plate. The VeRi776 datum, which contains real-world vehicle images, is used to facilitate the research of vehicle re-identification. The proposed framework employs Siamese model architecture to identify the attributes such as color, model, and type of vehicle. The Car License Plate Detection datum is used to evaluate the efficiency of the proposed license plate recognition system. An ensemble of image localization techniques using CNNs and application of the OCR model on the localized snapshot is used to recognize the vehicle's license plate. A combination of license plate recognition and vehicle re-identification techniques is used in the proposed framework to improve the efficiency of identifying vehicles in toll plazas 2022 IEEE. -
Improved Collaborative Filtering using Evolutionary Algorithm based Feature Extraction
International Journal of Computer Applications Vol.64,No.20, pp.20-26 ISSN No. 0975-8887 -
Improved Bald Eagle Search for Optimal Allocation of D-STATCOM in Modern Electrical Distribution Networks with Emerging Loads
Currently, modern electrical distribution networks (EDNs) are experiencing high demand with emerging electric vehicle loads and are being planned for specific load requirements such as agricultural loads. In this connection, characterization and optimization of their performance become essential in planning studies. In this paper, optimal reactive power compensation using a distribution-static synchronous compensator (D-STATCOM) is proposed with the aim of loss reduction, voltage profile improvement and voltage stability enhancement different types of loads including agricultural and electric vehicle loads. A recent efficient meta-heuristic approach, improved bald eagle search (IBES), is implemented for solving the proposed optimization problem considering different operational and planning constraints. The simulation results are performed on IEEE 33-bus for different types of load modelling. The computational efficiency of IBES is compared with basic BES and other literature works. From the results, IBES has shown superior computational characteristics than all compared works. On the other hand, the optimal location and size of D-STATCOM caused significant loss reduction, voltage profile improvement and voltage stability enhancement for kinds of loads as experiencing in the modern EDNs 2022,International Journal of Intelligent Engineering and Systems.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. -
Imprint of Fertiliser Policies on Farming Practices Evidence from the Top Five Consuming States
The policies related to the use of nitrogen fertilisers since independence are reviewed using primary and secondary databases to derive the present status of nitrogen, phosphorus, and potassium fertiliser use among farmers. Recommendations for increasing nitrogen use efficiency in agriculture for sustainability are provided. 2023 Economic and Political Weekly. All rights reserved. -
Imposter detection with canvas and WebGL using Machine learning.
Authentication offers a way to confirm the legitimacy of a user attempting to access any protected information that is hosted on the web as organizations are moving their applications online. It has long been believed that IP addresses and Cookies are the most reliable digital fingerprints used to authenticate and track people online. But after a while, things got out of hand when modern web technologies allowed interested organizations to use new ways to identify and track users. There are many new reliable digital fingerprints that can be used such as canvas and WebGL. The canvas and WebGL render the image which is dependent on the software and hardware of the system. In our work with the generated hash value value from canvas and WebGL we create a model using KNN to identify the imposters. The model has proved to be accurate in authentication of user with an accuracy of 89%. 2023 IEEE. -
Importance of Sustainable Marketing Initiatives for Supporting the Sustainable Development Goals
Businesses that engage in sustainable marketing can benefit both the world and their bottom line. Earlier, companies could satisfy many customers by simply providing low pricing and high-quality goods. However, peoples concern for the environment and other social concerns have grown, and so has their desire to support groups that share their beliefs. Because they often generate strong market returns and demonstrate durability during economic downturns, many investors want to support businesses that use sustainable business methods. Also, these businesses are more likely to comply with social and environmental laws. Several companies use sustainable marketing to succeed in todays ethical and ecologically sensitive marketplace. Organizations must finance sustainability programs in order to practice sustainable marketing. But, it can also improve employee engagement, promote regulatory compliance, raise revenues, and build brand loyalty. 2023 by IGI Global. -
Importance of positive emotions in software developers performance: a narrative review
Software development depends heavily on human efforts and collaborations, which are simultaneously influenced by human emotions, and it is considered among the most difficult tasks. Software developers are susceptible to various health concerns such as burnout, anxiety and depression due to the work nature and demands of the software industry, and this may have detrimental effects on their performance. However, evidence portray significant beneficial effects of positive emotions on well-being, growth, and success. Accordingly, this paper investigates the relevance of positive emotions among software developers and strives to understand how positive emotions benefit developers performance. It surveys literature that examine the importance of affect among developers and the benefits of positive emotions on human well-being and employs a narrative style to present these aspects. This review discusses the potential mechanisms that underlie the association between frequent experiences of positive emotions and improved performance and suggests that positive emotions benefit developers performance. This emotional awareness has the potential to enhance the developer efficacy, thus contributing to the discipline of ergonomics. Findings also have positive implications for organisational counsellors as they help in developing and maintaining a positive organisational climate. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Importance of political cartoons to newspapers /
Political cartoons are an important part in any newspaper. Political cartoons adorn a small part of a newspaper, often in a corner. The position of this piece although small the impact is huge. A cartoon conveys a lot of information in very few words. The emotions behind the political cartoons are genuine and although harsh, are taken with a sense of humour. While incomparison editorials are, firstly for the elite masses who understand the highly intellectual content of the piece, also editorials have a tendency to be politically correct and hold back, unlike cartoons. Cartoons are generally blatant about their stand on the issue. There have been controversial cartoons like JyllandsPostenthe Mohammad cartoon and the effective yet less controversial R.K.Laxman. -
IMPORTANCE OF POLITICAL CARTOONS TO NEWSPAPERS
Political cartoons are an important part in any newspaper. Political cartoons adorn a small part of a newspaper, often in a corner. The position of this piece although small the impact is huge. A cartoon conveys a lot of information in very few words. The emotions behind the political cartoons are genuine and although harsh, are taken with a sense of humour. While incomparison editorials are, firstly for the elite masses who understand the highly intellectual content of the piece, also editorials have a tendency to be politically correct and hold back, unlike cartoons. Cartoons are generally blatant about their stand on the issue. There have been controversial cartoons like JyllandsPostenthe Mohammad cartoon and the effective yet less controversial R.K.Laxman. The dissertation will concentrate on how political cartoon are infact one of the most important parts of any newspaper. It will try to understand the effectiveness of political cartoons over editorials. How political cartoons are a means of communication. The researcher will also try to understand how R.K.Laxman and the common man have become symbols for the ??aamaadmi??. The methods of research will include a qualitative analysis of political cartoons by interview and a quantitative analysis by questionnaire method to understand how people perceive cartoons over editorials. The researcher having completed the researcher is in a position to make comments about the effectiveness and popularity of cartoons. -
Importance of Genetic Model in Huntingtons Disease
Huntingtons disease (HD) is the first defect-mapped autosomal-dominant, progressive neurodegenerative disorder with a distinct phenotype found in 1983, which contributed to the concept of human genome project. Thus, the search for genetic defects pioneered various mapping and gene study technological prototypes that culminated in identification of distinct disorders. Huntingtons disease has many symptoms, including chorea and dystonia, incoordination, cognitive decline and dementia, and behavioral difficulties. This disease can manifest any time over the age of 30 years, with the first sign and symptom being behavioral changes, which might include lack of emotions, periods of aggression, excitement, and anger. HD duration varies, ranging from 10 to 25 years or more depending on the individual. It is caused by a single gene defect on chromosome number 4, wherein a person requires only a single copy of the defected gene to show the symptoms; that is, a person with parent with the HD gene has a 50% chance of suffering. The disease becomes prominent in a human being as a result of mutations in a gene called Huntington that is located on the p arm (short arm) of chromosome 4 (4p 16.3). This chapter discusses the genetic model of Huntingtons disease and its importance. An increase in the normal number of repeat CAG (cytosine, adenine, and guanine) segments, (i.e. > 35 CAG) is seen in the Huntington (HTT) mutation that causes the disease. The severity of the disease depends on the sized expansion (i.e. increasing CAG repeats will accelerate the age of onset of the disease). Continuing studies of genetic modifiers-genes whose natural polymorphic variation contribute to the alteration and development of the D gene-offers to open new gateways for early diagnosis by unlocking the biochemical changes that occur years before diagnosis, thereby providing validated target protein and pathways for rational therapeutic interventions. This is also added as a section in this chapter. 2025 selection and editorial matter, Sachchida Nand Rai, Sandeep Singh, Santosh Kumar Singh. -
Importance of brain-based learning in effective teaching process
Neuroscience plays an important role to inform about brain functioning and corresponding behaviors. While scientists have continuously studied about brain in its entirety, several other fields in science, arts, and humanities are drawing applications from these neuroscientific studies. Similarly, in terms of education too, there are several applications. Once such is brain-based learning. This is to learn and teach with an understanding about brain's capability and functioning to increase one's learning potential. In order to do so, effective teaching is required. This particular chapter thus focuses on different teaching strategies which adopt brain-based learning and are evidence-based. The chapter initially informs about neuroscience and cognitive science interaction and its impact on effective teaching-learning process. After which evidence-based teaching strategies in classrooms, their importance via evidence-based studies, and techniques to incorporate them in classroom settings are explained. Finally, the chapter concludes with challenges and benefits. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Importance Of Artificial Intelligence in Improving Human Resource Management For Companies To Find Suitable Candidature
The efficient use of pertinent human resources both inside and outside the company via management structures guided by economic and humanistic principles is known as human resource management. It is a catch-all word for a set of actions that guarantee the accomplishment of group objectives and the optimization of member growth. Employers need the correct recruitment tools to fill available positions since traditional recruiting approaches are not up to par in the global talent battle. First, as the digital tool redesigns business, we look at how talent acquisition has evolved from digital 1.0 to 3.0 (AI-enabled). Artificial intelligence technology has made recruiting more efficient and made recruiters' daily tasks easier. Additionally, the analysis in the paper shows that artificial intelligence (AI) is crucial to every step of the hiring process, including promotion, application, screening, evaluation, and coordination. This study demonstrates how organizations are realizing the value of talent management in gaining a competitive edge as the need for higher-level talent grows. Even though some HR managers are using AI for talent acquisition, our research shows that there is still an opportunity for development. 2024 IEEE. -
Importance of Artificial Intelligence (AI) and Robotic Process Automation (RPA) in the Banking Industry: A Study from an Indian Perspective
The papers primary focus is intelligence creation by AI and fast implementation by RPA. It starts with the applicability of the Turing test propounded by Alan Turing, the father of Artificial Intelligence (AI). At the backdrop lies various events, namely the recent motivation addition of various bank account holders. These factors fuelled the demand for AI and RPA implementation in the banking industry. It pitched how AI and RPA work in real-time scenarios such as financial fraud and money laundering. It discusses how AI builds the knowledge graph and recommends products and services for each customer. This knowledge is implemented and delivered using RPA. The AI application gained prominence in every banking business segment, such as equity, personal, investment and loan. The application of RPA is present in all business segments, although the percentage is increasing yearly. The AI and RPA can help banks to convert the challenges to opportunities. There have been various challenges, and the application of AI and RPA combinations is the key to solving the inefficiencies. Advanced analytical techniques on open-source data have been used in this paper. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Implications of Goods and Services Tax on Indian Micro, Small and Medium Enterprises
This research explores the impact and provides implications of Goods and newlineServices Tax , a comprehensive indirect tax reform on the growth of Indian newlineMSMEs, the fundamental drivers of economic progress and employment in India. newlineThe purpose is to assess the relationships and impact of the knowledge of GST, newlineInput tax credit (ITC), Revenue neutral rate (RNR), and GST compliance on the newlinegrowth of Indian MSMEs. Also, the research focuses on the interceding role of GST newlinecompliance in the relationship between GST knowledge, ITC, RNR and MSMEs newlinegrowth, as well as to discover facets that impede the implementation of effective newlinetax policies, particularly in the context of MSMEs. This study is based on a Crosssectional Survey with 531 MSME participants who are registered under Regular newlinescheme. Structural Equation Modelling - Partial Least Squares (SEM-PLS) in newlineSmart PLS4 was utilized to examine the relationships amongst the variables, assess newlinethe impact of each variable on the outcome variable, either directly or indirectly and newlineto test the research hypotheses. The results show, GST knowledge, ITC, and RNR newlinehave significant positive effects on GST compliance and on perceived growth of newlineMSMEs. Also, the study found, GST compliance has a complementary partial newlinemediating role in the relation between these factors and perceived growth of newlineMSMEs. Furthermore, GST knowledge, ITC, and RNR have positive effect on newlineperceived MSMEs satisfaction with the GST system. But, the effect of GST newlineknowledge and ITC on perceived satisfaction of MSMEs through GST Compliance newlinewas not significant. This hints that, while knowledge of GST and ITC are important, newlinecomplications in claiming ITC and burdensome compliance requisites can newlineunpleasantly impact compliance and satisfaction with GST. The study also newlineobserved significant variations in perceptions of GST knowledge, ITC, RNR, GST newlineCompliance, MSMEs satisfaction, and MSMEs growth across different newlinedemographic variables. -
