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                <text>Customer preferences to select a restaurant through smart phone applications: An exploratory study</text>
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                <text>The increasing number of Smart Phone Applications (SPA) user and fast growing restaurant industry proves the great potential of using SPA as business marketing opportunity in Malaysia. The constant growth in mobile technology has created a prospect for the restaurant industry to use SPA as a restaurant promotion tool. The growing attention of use of SPA among the Malaysian customer, marketing research remains understudied in the field of SPA based restaurant promotion activities. The aim of this study is to explore the increase in customer acceptance to use SPA based restaurant promotion and to identify the customer preference to use SPA to select the restaurant. Thus, this paper mainly focuses on restaurant information on product and promotion as antecedents of customer acceptance of smart phone apps by underpinning the Unified theory of acceptance and use of technology (UTAUT) model. A conceptual model and hypotheses are tested with a sample of 116 students from a private university at Selangor district, Malaysia. The findings indicate that there is a positive relationship to increase customer acceptance level through SPA based restaurant product information and also strong relationship with the restaurant promotion information. It also indicates that customer acceptance of SPA through experience and satisfaction has a positive significant effect on customer preference to select a restaurant. Based on the results, this paper rounds off with conclusion, recommendations for future marketing research and provides a new marketing strategy to formulate among the restaurant business sector.  2015 American Scientific Publishers. All rights reserved.</text>
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                <text>Advanced Science Letters, Vol-21, No. 5, pp. 1489-1493.</text>
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                <text>Balasubramanian K., School of Tourism, Hospitality and Culinary Arts, Taylors University, Malaysia, Karpagam University, Coimbatore, 641402, India; Balraj A., Coimbatore, 641402, India; Kumar J., School of Tourism, Hospitality and Culinary Arts, Taylors University, Malaysia; Jaykumar, School of Hospitality Management, Christ University, Bangalore, 560029, India</text>
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                <text>Customer Segmentation and Future Purchase Prediction using RFM measures</text>
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                <text>Classification; Clustering; Customer Segmentation; E-Commerce; K-means; Machine Learning; RFM</text>
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                <text>Winning in the E-Commerce business race at a competitive age like this requires proper usage of Customer data. Using that database and grouping it in similar segments in terms of spending expenditure, observation time, sex, and location so that every customer falls in a segment of characteristics. This mechanism is called Customer Segmentation. In the modern era of highly compatible technological advancements, Machine Learning Algorithms are being vastly used to bring solutions to these difficult yet essential services. In the field of research methods like simple clustering based on purchase behaviour, buyer targeting or automated customer promotion mechanism by dividing into two major categories, have been worked on. However, ensemble algorithms have come handy where different clustering algorithms are combined to deliver best segmentation. Lately combination techniques like clustering and classification mechanism have also delivered good results where, not only segmentation is done but also classification of existing and new customers are possible into the clusters. Depending on that an effective customer relationship management can really benefit the company to a huge extent. Unlike other studies where clustering was performed directly on RFM table, a different approach was taken in this study where, one dimensional clustering was done individually on Recency, Frequency, Monetary columns, then an overall score was calculated and customers were classified into three segments. However, for a new customer depending on his purchase behaviour he/she also can be classified into any of the categories.  2022 IEEE.</text>
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                <text>Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022, pp. 753-759.</text>
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                <text>Patra A., Christ University, Department of Data Science, Lavasa, Pune, India; Khan R., Christ University, Department of Data Science, Lavasa, Pune, India; Vijayalakshmi S., Christ University, Department of Data Science, Lavasa, Pune, India</text>
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                <text>Customer Segmentation in the Field of Marketing</text>
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                <text>Agglomerative algorithm; Business; Characteristics; Customer Segmentation; DBSCAN algorithm; k-Means algorithm; Machine Learning Models; Neural Networks</text>
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                <text>The motive of this work is to classify and categorize customers depending on their familiar traits/characteristics so as to enable a company or a firm to adequately market their products to each category more attractively and competently. It is imperative for a firm to educate themselves with each and every detail about the customer, such as age group, sexuality, social class, purchase pattern etc as it paves way for customer segmentation. Businesses may utilize segmentation to make better use of their marketing resources, get a competitive advantage over competitors, and, most importantly, display a deeper understanding of their consumers' requirements and desires. Customer segmentation, when combined with customer targeting and positioning, creates the foundation for strategic marketing. A manager can find new marketing possibilities and create or adjust the product to satisfy the demands of potential clients using the notion of strategic marketing. The product's quality level determines its position in the market's overall offering. It's a crucial aspect in selecting which market segment a collection will target. The commercial world has gotten more competitive over time, as enterprises like these have to fulfil their consumers' demands and aspirations, attract new customers, and enhance their bottom lines. In this research, I have put the spotlight on the information used by firms for the purpose of customer segmentation in the most valuable manner. In addition to that, I have portrayed different models of customer segmentation and the benefits reaped by a business in implementing them.   2022 IEEE.</text>
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                <text>Thomas J.; Preethi N.</text>
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                <text>4th International Conference on Recent Trends in Computer Science and Technology, ICRTCST 2021 - Proceedings, pp. 401-405.</text>
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                <text>&lt;a href="https://doi.org/10.1109/ICRTCST54752.2022.9781964" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICRTCST54752.2022.9781964&lt;/a&gt;
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                <text>Thomas J., Christ University, Department Of Data Science, India; Preethi N., Christ University, Department Of Data Science, India</text>
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                <text>Customers response to online food delivery services during COVID-19 outbreak using binary logistic regression</text>
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                <text>binary logistic regression; COVID-19; health belief model; online food delivery services; purchase decision</text>
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                <text>This study aims to empirically measure the distinctive characteristics of customers who did and did not order food through Online Food Delivery services (OFDs) during the COVID-19 outbreak in India. Data are collected from 462 OFDs customers. Binary logistic regression is used to examine the respondents characteristics, such as age, patronage frequency before the lockdown, affective and instrumental beliefs, product involvement and the perceived threat, to examine the significant differences between the two categories of OFDs customers. The binary logistic regression concludes that respondents exhibiting high-perceived threat, less product involvement, less perceived benefit on OFDs and less frequency of online food orders are less likely to order food through OFDs. This study provides specific guidelines to create crisis management strategies.  2020 John Wiley &amp;amp; Sons Ltd</text>
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                <text>Mehrolia S.; Alagarsamy S.; Solaikutty V.M.</text>
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                <text>International Journal of Consumer Studies, Vol-45, No. 3, pp. 396-408.</text>
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                <text>Blackwell Publishing Ltd</text>
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                <text>&lt;a href="https://doi.org/10.1111/ijcs.12630" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1111/ijcs.12630&lt;/a&gt;
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                <text>All Open Access; Green Open Access</text>
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                <text>ISSN: 14706423</text>
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                <text>Mehrolia S., School of Business and Management, Christ University, Bangalore, India; Alagarsamy S., School of Business and Management, Christ University, Bangalore, India; Solaikutty V.M., The American College, Madurai, India</text>
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                <text>Customers satisfaction towards online banking services of public sector banks</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="125046">
                <text>Banking services; Customer preference; Customer satisfactions; Online banking</text>
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                <text>At present the banking industry around the world has been undergoing a rapid transformation. The deepening of information technology has facilitated better tracking and fulfillment of commitments, multiple delivery channels for online customers and faster resolution of issues. Customer satisfaction is important criteria for banks sustenance, now banks are offers online banking services according to the customer needs and requirements. This study analysed customers satisfactions towards online banking services of public sector banks in Tiruchirappalli district. It is understand from the present study that bank websites and technology platforms has to offer various knowledge features on financial services. To retain the existing customers, banks has to conduct regular surveys on the customer satisfaction. The results of the study shows that variables like prompt response, security and Website design and ease of use are top three factors affected customer satisfaction.  IJSTR 2020.</text>
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                <text>Kiran G.; Appasaba L.V.; Raja M.; Muthu Gopalakrishnan M.; Chotai N.</text>
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                <text>International Journal of Scientific and Technology Research, Vol-9, No. 4, pp. 3368-3372.</text>
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                <text>Kiran G., Welingkar Institute of Management, India; Appasaba L.V., Department of MBA, VTU  Belagavi, India; Raja M., Research Department of Commerce, Bharathidasan University Constituent College, Tiruchirappalli, Kumulur, Lalgudi, India; Muthu Gopalakrishnan M., School of Business Studies and Social Sciences Christ (Deemed to be University, Bengaluru, 567006, India; Chotai N., Jain University, Bengaluru, India</text>
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                <text>In image scene, text contains high-level of important information that helps to analyze and consider the particular environment. In this paper, we adapt image mask and original identification of the mask region based convolutional neural networks (R-CNN) to allow recognition at 3 levels such as sequence, holistic and pixel-level semantics. Particularly, pixel and holistic level semantics can be utilized to recognize the texts and define the text shapes, respectively. Precisely, in mask and detection, we segment and recognize both character and word instances. Furthermore, we implement text detection through the outcome of instance segmentation on 2-D feature-space. Also, to tackle and identify the text issues of smaller and blurry texts, we consider text recognition by attention-based of optical character recognition (OCR) model with the mask R-CNN at sequential level. The OCR module is used to estimate character sequence through feature maps of the word instances in sequence to sequence. Finally, we proposed a fine-grained learning technique that trains a more accurate and robust model by learning models from the annotated datasets at the word level. Our proposed approach is evaluated on popular benchmark dataset ICDAR 2013 and ICDAR 2015.  2023 Institute of Advanced Engineering and Science. All rights reserved.</text>
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                <text>International Journal of Electrical and Computer Engineering, Vol-13, No. 1, pp. 413-424.</text>
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                <text>Channegowda R.H., Department of Electronics and Communication Engineering, K S School of Engineering and Management, Ghousia College of Engineering, Visvesvaraya Technological University, Karnataka, India; Karthik P., Department of Electronics and Communication Engineering, K S School of Engineering and Management, Visvesvaraya Technological University, Karnataka, India; Srinivasaiah R., Department of Computer science and Engineering, Christ Deemed to be University, Karnataka, Bengaluru, India; Shivaraj M., Department of Electronics and Communication Engineering, Ghousia College of Engineering, Visvesvaraya Technological University, Ramanagaram, Karnataka, India</text>
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                <text>The uncertainty in life plans, restrictions on physical classrooms, loss of jobs, large number of infections and deaths due to COVID-19 are some significant causes of concern for the public as well as Governments all over the globe. Moreover, the exponential increase in the number of infected people in a short time is responsible for the collapse of the health industry during the pandemic caused by COVID-19. The health experts recommended that the quick and early diagnosis followed by treatment of patients in isolation is a way to minimize its spread and save lives. The objective of this research is to propose a customized SEIR model to predict the trends of vaccination in the USA. The experimental results prove that the Moderna vaccine reports the efficacy of 93%, which is higher than the Pfizer and Johnson and Johnson vaccines.  2022 ACM.</text>
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                <text>ACM International Conference Proceeding Series, pp. 77-80.</text>
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                <text>Alluhaidan A.S., Department of Information Systems, College of Computer and Information Science, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia; Poonia R.C., Department of Computer Science, CHRIST (Deemed to Be University), Karnataka, Bangalore, India; Prabu P., Department of Computer Science, CHRIST (Deemed to Be University), Karnataka, Bangalore, India; Alluhaidan M.S., Ministry of Defense, Riyadh, Saudi Arabia</text>
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                <text>Cutting across the Durand: Water dispute between Pakistan and Afghanistan on river Kabul</text>
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                <text>All nations firmly believe in the absolute sovereignty over the waters flow in their areas and that only riparian states have any legal right, apart from an agreement, to use the water from the shared river. To address some of their water concerns, the co-riparian states compete to have more quantity of waters. Significantly, no water agreement exists between upper riparian Afghanistan and lower riparian Pakistan, despite sharing nine big and small rivers. The simmering water dispute between them on the River Kabul is rarely noted mainly because it is overshadowed by their political tensions, differences, and the dispute over the Durand Line. Using an analytical framework, this article examines three aspects of the River Kabul water dispute: its context, identifying the challenges that hinder a formalized bilateral agreement from being implemented, and its future.  2020 Policy Studies Organization</text>
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                <text>World Water Policy, Vol-6, No. 2, pp. 246-258.</text>
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                <text>Ranjan A., Institute of South Asian Studies, National University of Singapore, Singapore, Singapore; Chatterjee D., Christ University, Bengaluru, India</text>
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                <text>The main objective of this chapter is to enhance security system in network communication by using machine learning algorithm. Cyber security network attack issues and possible machine learning solutions are also elaborated. The basic network communication component and working principle are also addressed. Cyber security and data analytics are two major pillars in modern technology. Data attackers try to attack network data in the name of man-in-the-middle attack. Machine learning algorithm is providing numerous solutions for this cyber-attack. Application of machine learning algorithm is also discussed in this chapter. The proposed method is to solve man-in-the-middle attack problem by using reinforcement machine learning algorithm. The reinforcement learning is to create virtual agent that should predict cyber-attack based on previous history. This proposed solution is to avoid future cyber middle man attack in network transmission.  2022 by IGI Global. All rights reserved.</text>
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                <text>Cybersecurity in civil aviation is becoming increasingly critical as the aviation industry in India continues to grow and evolve. With the increasing use of technology and automation in aviation, there is a growing risk of cyber threats that can affect the safety and security of civil aviation operations. This paper provides a critical analysis of the current state of cybersecurity in civil aviation in India. It examines the various cyber threats facing the aviation industry, the legal and regulatory framework for cybersecurity in India, and the measures that can be taken to enhance cybersecurity in civil aviation. The analysis highlights the need for a comprehensive and proactive approach to cybersecurity in civil aviation in India, including the implementation of robust cybersecurity policies and procedures, the adoption of international best practices, and the establishment of a dedicated cybersecurity framework for the aviation industry.</text>
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                <text>Sensitive data protection has been a top priority in the healthcare industry. This has led to the investigation of safe data storage and transaction. Despite various attempts to address this issue, data breaches continue to plague the healthcare industry. This study aims to investigate prevalent storage practices and security methodologies in the healthcare, recognizing the need for a robust framework. The work further extends with design of new security framework for healthcare industry. This framework identifies critical data and implement measures to prevent unauthorized access and data tempering. The industrial hype towards the implementation of adaptive machine learning craves the need for hybrid machine learning approaches to be adapted in the cyber secure framework. In order to improve security and confidentiality in the healthcare sector. Blockchain is used in the proposed cyber secure framework promising integrity of data with the features of immutability. This proposal aims to provide a comprehensive solution to the ongoing problem of protecting medical data.  Grenze Scientific Society, 2024.</text>
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                <text>15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024, Vol-2, pp. 3824-3832.</text>
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                <text>2021 and 2022 have been the years of frequent cyberattacks. India remains in the top 25 countries severely affected by the continuous cyber-attacks and tops the list. The healthcare department is amongst the most affected area. In 2020, the healthcare department suffered a severe impact with around 348K cyber-attacks alone on Indian healthcare infrastructure. The recent occurrence of cyber-attack on AIIMS hospital in December 2022 followed by several other incidences of data breaches have made the concerned authorities pro-active on exercising vigilance and reforming the legal and technical system to protect the health infrastructure. This paper has been developed on extensive literature and focuses on describing the nature of electronic health records, the risks they are exposed to along with as to why they are so susceptible to these cyber-risks. Furthermore, the paper also deals with different kinds of threats affecting the privacy and security of electronic health records specifically. The paper analyzes Indian legal framework, briefly compares it with international legal framework (specifically US &amp;amp; EU) and highlights the shortcomings in Indian legislative framework followed by laying down certain recommendations primarily highlighting the possible changes required in Indian legal framework and practices that can be adopted at organizational level to overcome and mitigate such risks.  N. Raizada, P. Srivastava, 2024.</text>
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                <text>Kutafin Law Review, Vol-11, No. 3, pp. 452-490.</text>
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                <text>Raizada N., CHRIST University, Bengaluru, India; Srivastava P., Rashtriya Raksha University, Gandhinagar, India</text>
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                <text>Phrases that scarcely existed a decade ago are now a part of our day-to-day lifestyle, as criminals use malicious new technologies to commit cyber attacks against businesses, individuals, and governments. These crimes cause serious harm and impose real threats to victims worldwide either physically or virtually. There are no borders in cyberspace. Attacks can come from any place and at any time. Cybercrime can take many forms, but they all have a digital platform/environment in common. It can be done with both good and bad intentions. But, nowadays, the most common types of cybercrime activities such as phishing scams, identity theft, Internet frauds, online intellectual property or patent infringements, online harassment, and cyber stalking are sadly very widespread in todays associated world. Cyber bullying and online harassment activities spread casually in social media posts and comments or through direct messages and also via emails. The main motive of these messages is to threaten either an individual or a group. Such kinds of cybercrime activities are extremely damaging to the victims mental health. Government agencies working to investigate cybercrimes have reported multiple records of victims developing mental illnesses and even ending up committing suicide. On the other hand we have phishing scams, one of the widespread crime activities. Organizations have detected an increase in the ratio of phishing emails to professional emails from unknown or anonymous service providers appending fake attachments and invoices. These files and attachments may contain malicious payloads to scam people and to create a backdoor in that system, so the attacker can gain access to the system anytime and from anywhere without the victims knowledge. This has been considered as one of the major advantages for the attacker. Cybercrimes have not restricted to only these forms of criminal activities. A wide variety of new attacks have been created and have spread all over the world through commonly used platforms such as social media sites, blogs, and news portals. We are living in a digital world where all our activities are being monitored by someone, somewhere - even keystrokes are being monitored using keyloggers. Nothing seems to be secret and protected unless you are tech savvy. National agencies are keeping a close watch on all individual online activities to prevent illegal activities from happening. No longer the delete option is possible in this digital world; rather, only migration of data from one location to another or from a local server to a cloud server is possible. In our day-to-day lives, several new viruses and attack mechanisms are triggered by attackers by following very new tactics with the help of more complex algorithms. So, its time to advance our knowledge on protecting our valuable assets by spending time in learning and following proper online practices.  2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors.</text>
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