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                <text>Patent Number: 202121042792, Applicant: Dr. S. Vijayalakshmi.&#13;
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                <text>The exchange of information from one person to another is called communication. Telecommunication makes it possible with electronic devices and their tools. The scientist Alexander Graham Bell has invented the basic telephone in 1876 in the USA. Telephones now have the new format in the form of mobile phones, which are the primary media for communicating and transmitting data. We are using 5th-generation mobile network standards. Still, there are some requirements for the users that are believed to be solved in the 6th-generation mobile network standards. By 2030, all of the people would be using 6G. The computing model in the cloud is not dependent on either the location or any specific device that would provide the service. It is an on-demand computational service-oriented mechanism. Combining these two technologies as mobile cloud computing provides customized options with more flexible implementations. Artificial intelligence is being used in devices in many fields. AI can be used in mobile network services (MNS) to provide more reliable and customized services to the users, such as network operation monitoring, network operation management, fraud detection, and reduction in mobile transactions and security to the cyber devices. Combining cloud with AI in mobile network services in the 6th generation would improve human beings' lives, such as zero road accidents, advanced level special health care, and zero crime rates in society. However, the most vital needs for sixth-generation standards are the capability to manage large volumes of records and excessive-statistics-fee connectivity in step with gadgets. The sixth-generation mobile network is under development. This generation has many exciting features. Security is the central issue that needs to be sorted out using appropriate forensic mechanisms. There is a need to approach high-performance computing for improved services to the end-user. Considering three-dimensional research methodologies (technical dimension, organizational dimension, and applications hosted on the cloud) in a high-performance computing environment leads to two different cases such as real-time stream processing and remote desktop connection and performance test. By 'narrowing the targeted worldwide audience with a wide range of experiential opportunities,' this paper is aimed at delivering dynamic and varied resource allocation for reliable and justified on-demand services.   2022 Srinivasa Rao Gundu et al.</text>
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                <text>Gundu S.R., Government Degree College Sithaphalmandi, Telangana, Hyderabad, India; Charanarur P., School of Cyber Security and Digital Forensic, National Forensic Sciences University, Goa Campus, Goa, India; Chandelkar K.K., School of Cyber Security and Digital Forensic, National Forensic Sciences University, Goa Campus, Goa, India; Samanta D., Department of Computer Science, CHRIST (Deemed to Be) University, Karnataka, Bengaluru, 560029, India; Poonia R.C., Department of Computer Science, CHRIST (Deemed to Be) University, Karnataka, Bengaluru, 560029, India; Chakraborty P., Department of Computer Science and Engineering, Comilla University, Cumilla, 3506, Bangladesh</text>
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                <text>Quantum-inspired meta-heuristic approaches for a constrained portfolio optimization problem</text>
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                <text>Portfolio optimization has long been a challenging proposition and a widely studied topic in finance and management. It involves selecting and allocating the right assets according to the desired objectives. It has been found that this nonlinear constraint problem cannot be effectively solved using a traditional approach. This paper covers and compares quantum-inspired versions of four popular evolutionary techniques with three benchmark datasets. Genetic algorithm, differential evolution, particle swarm optimization, ant colony optimization, and their quantum-inspired incarnations are implemented, and the results are compared. Experiments have been carried out with more than 10 years of stock price data from NASDAQ, BSE, and Dow Jones. This work proposes several enhancements to allocate funds efficiently, such as improved crossover techniques and dynamic and adaptive selection of parameters. Furthermore, it is observed that the quantum-inspired techniques outperform the classical counterparts.  The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.</text>
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                <text>Gunjan A.; Bhattacharyya S.</text>
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                <text>Evolutionary Intelligence, Vol-17, No. 4, pp. 3061-3100.</text>
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                <text>Gunjan A., Christ (Deemed to be University), Bangalore, India; Bhattacharyya S., VSB Technical University of Ostrava, Ostrava, Czech Republic, Algebra University College, Zagreb, Croatia</text>
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                <text>A brief review of portfolio optimization techniques</text>
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                <text>Deep learning; Evolutionary techniques; Machine learning; Portfolio optimization; Quantum computing; Reinforcement learning; Statistical measures</text>
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                <text>Portfolio optimization has always been a challenging proposition in finance and management. Portfolio optimization facilitates in selection of portfolios in a volatile market situation. In this paper, different classical, statistical and intelligent approaches employed for portfolio optimization and management are reviewed. A brief study is performed to understand why portfolio is important for any organization and how recent advances in machine learning and artificial intelligence can help portfolio managers to take right decisions regarding allotment of portfolios. A comparative study of different techniques, first of its kind, is presented in this paper. An effort is also made to compile classical, intelligent, and quantum-inspired techniques that can be employed in portfolio optimization.  2022, The Author(s), under exclusive licence to Springer Nature B.V.</text>
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                <text>Gunjan A.; Bhattacharyya S.</text>
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                <text>Artificial Intelligence Review, Vol-56, No. 5, pp. 3847-3886.</text>
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                <text>Optimization of portfolios has an additional level of complexity and has been an area of interest for both financial leaders and artificial intelligence experts. In this article, a quantum-inspired version of an improved genetic algorithm is proposed for the task of portfolio optimization. An effort is made to implement two different genetic versions along with their extension in the quantum-inspired space. Improvements to the popular crossover techniques, viz. (i) arithmetic and (ii) heuristic crossover are proposed to reduce computational time.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>The discovery of antibiotics had been a major breakthrough in the field of medicine. Apart from its use in treating disease, it is been used extensively in agricul-tural fields and animal husbandry to improve livestock and crop yield. Improper and overuse of antibiotics have found a route in the food chain and has accumulated in environmental resources like water and soil. This is of serious concern as it leads to the development of drug-resistant microorganisms which is a global threat and also alters the microbial diversity as they are bacteriostatic and bactericidal. Bioaugmen-tation and Biostimulation approaches are effective in the degradation of antibiotics in soil. For enhanced degradation of antibiotics consortia, engineered microbes and enzyme-mediated methods are feasible methods for effective remediation of antibi-otics in soil. Currently, extensive research on the bioremediation of antibiotics is carried out as they are cost-effective and eco-friendly. The present chapter deals with various contamination sources of antibiotics in soil, adverse effects of antibiotics in soil, different bioremediation approaches, and mechanisms, and regulations in the use of antibiotics.  The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.</text>
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                <text>Gupta A., Department of Life Sciences, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India; Bhatt Y., Department of Life Sciences, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India; Rais N., Department of Pharmacy, Bhagwant University, Rajasthan, Ajmer, 305004, India; Nagella P., Department of Life Sciences, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India; Vasantha V.L., Department of Life Sciences, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India</text>
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                <text>clustering; computer programming; educational data mining; regression; student programming patterns</text>
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                <text>In present educational era, teaching programming to the undergraduates is challenging. For an instructor, focusing on each of the aspect of programming like coding language, logical reasoning, debugging errors, troubleshooting code and problem solving is very daunting task. So, educational researchers are identifying ways to easily identify the student's struggles during programming so that timely assistance can be provided. Using programming platforms or software, a lot of programming data is generated in the form of activity logs or clickstream data. Using machine learning along with data analytics over this programming data can reveal programming patterns of students that may help in early interventions. This study focusses on identifying programming patterns of the students through clustering and groups the students into three major categories namely low performers, strugglers, and high scorers. Further, relevant features like test case success, code compile success and failure, finish test etc. that majorly contribute towards the student programming scores are identified through regression analysis. Through this research, educators can early categorize the students based on their programming patterns and provide timely intervention when necessary, ensuring that no student gets left behind in the fast-paced world of programming education.   2024 IEEE.</text>
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                <text>Proceedings - International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024, pp. 1153-1158.</text>
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                <text>Gupta A., Bennett University, Scset, Greater Noida, India; Jindal M., Christ (Deemed to Be University), School of Business and Management, Bangalore, India; Goyal A., Bennett University, Scset, Greater Noida, India</text>
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                <text>A method to secure FIR system using blockchain</text>
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                <text>In India, we can see that technology has touched in every aspect of our life. There exist technology in all the fields e.g. education, agricultural, business, government etc. and we can also understand how beneficial it is, as it saves the time, money and human power. In spite of being technologically advanced, the system lacks in security perspective. When we talk about today, India has moved to the era of digitalization after the launch of the campaign Digital India, the Indian Police Department has replaced the manual system with the centralized online process to register the complaint. The main objective of this paper is to provide a method to secure the FIR system using blockchain technology. This introduces to the essential principal of blockchain technology and its future in the police department of India. Blockchain technology will also explain to protect the FIR from the malfeasance.  BEIESP.</text>
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                <text>International Journal of Recent Technology and Engineering, Vol-8, No. 1, pp. 626-629.</text>
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                <text>The Indian information technology (IT) sector faces a unique challenge of managing their knowledge workers. Workplace spirituality, defined as recognising employees as a spiritual being, is seen as a new solution to the challenges faced by the IT sector. There are many conceptual models, but very few empirical ones to measure spirituality at work in the Indian context. The present study aims to develop an instrument that measures workplace spirituality. In-depth interviews were conducted with 20 IT professionals and seven themes emerged from these interviews, based on which a 66-item questionnaire was developed which was further reduced to 33 items as per recommendations from experts. The questionnaire was administered to 172 Indian IT professionals and its reliability and construct validity were determined using convergent and discriminant validity. As a future scope, the questionnaire could be tested in other sectors and suitable changes be generalised in the Indian context. Copyright  2022 Inderscience Enterprises Ltd.</text>
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                <text>World Review of Science, Technology and Sustainable Development, Vol-18, No. 45750, pp. 309-323.</text>
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                <text>Gupta A., Office School of Business and Management, Christ University, Room No. 294, Central Block, Second Floor, Hosur Road, Bangalore, 560029, India; Kumar A.A., Office School of Business and Management, Christ University, Room No. 294, Central Block, Second Floor, Hosur Road, Bangalore, 560029, India</text>
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                <text>Demand and supply forecasts serve as the backbone of strategic decision-making in todays rapidly changing business environment, assisting organizations in optimizing inventory levels, production planning, and pricing strategies. The ability to forecast demand and supply accurately is critical for effective supply chain and retail management. This chapter provides a comprehensive overview of supply chain and retail demand and supply forecasts. It discusses various forecasting methods and techniques, as well as related concepts. In addition, the chapter emphasizes the significance of accurate forecasting in optimizing supply chain and retail operations, as well as emerging trends and future directions in demand and supply forecasting.  2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar.</text>
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                <text>Artificial Intelligence in Forecasting: Tools and Techniques, pp. 333-340.</text>
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                <text>Gupta A., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Maharashtra, Lavasa, Pune, India; Nanjundan P., Department of Data Science, CHRIST (Deemed to be University), Pune, Lavasa, India; George J.P., Department of Data Science, CHRIST (Deemed to be University), Pune, Lavasa, India</text>
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                <text>Interplay between personality and attitude towards emotions with creative self concept among young adults</text>
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            <description>The topic of the resource</description>
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              <elementText elementTextId="74104">
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            <description>An account of the resource</description>
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                <text>Creative self-concept, intimately intertwined with the personality traits and plays a pivotal role in shaping individuals behavioral tendencies. Personality traits are largely responsible to influence how people perceive and navigate their creative abilities and self-expression. Moreover, attitudes towards emotions are another key facet of ones psychological landscape, impacting their inclination to perceive, process, and manage emotional experiences. Keeping this view, the present research attempts to explore the interconnectedness of creative self-concept, personality traits, and attitudes towards emotions among young adults, as well as focuses on exploring the predictors of creative self concept. For this purpose participants consisted of 200 young adults with a mean age of 21.20 years. Statistical outcomes revealed that creative self concept is a significant positive correlate of openness, conscientiousness, extraversion, agreeableness, attitude towards sadness, and attitude towards fear. Additionally, stepwise multiple regression analysis confirmed that openness (R2 = 27%), neuroticism (R2 = 2%) and attitude towards sadness (R2 = 2%) emerged as the significant predictors of creative self concept. Findings from the current research concludes that for young adults to have self-perception in the realm of creativity, personality traits and attitude towards emotions are significant contributing factors. By recognizing and employing these connections, individuals, educators, counselors, and practitioners can contribute to the cultivation of creativity and personal development.  The Author(s) 2024.</text>
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                <text>Gupta A.; Pathak S.; Panwar N.</text>
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                <text>BMC Psychology, Vol-12, No. 1</text>
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 20507283; PubMed ID: 39609701</text>
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                <text>Gupta A., Department of Psychology, Christ University, Delhi, NCR, India; Pathak S., Department of Psychology, Christ University, Delhi, NCR, India; Panwar N., Department of Psychology, Christ University, Delhi, NCR, India</text>
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                <text>Predictive Modeling for Uber Ride Cancellation and Price Estimation: An Integrated Approach</text>
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                <text>decision tree algorithms; fare estimation; gradient boosting; logistic regression; machine learning; predictive modeling; ride cancellation prediction; rideshare; transportation efficiency; Uber</text>
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                <text>In the realm of ridesharing services, exemplified by Uber, two formidable challenges have surfaced: ride cancellations and precise fare estimation. This research introduces an innovative, integrated approach that leverages predictive modeling to address both issues. By analyzing historical ride data, we identify the intricate factors influencing cancellations, and through machine learning techniques, we develop predictive models to forecast cancellation likelihood. Additionally, we pioneer a dynamic approach to fare estimation by considering historical data alongside real-time variables. By unifying these strategies, we aim to enhance user satisfaction, optimize driver allocation, and promote trust and transparency within the ridesharing ecosystem.   2024 IEEE.</text>
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                <text>Gupta A., Christ (Deemed to Be University), School of Science, Lavasa, India; Pipaliya A., Christ (Deemed to Be University), School of Science, Lavasa, India; Jacob L., Christ (Deemed to Be University), Department of Data Science, Lavasa, India; Balagangadhar K., Christ (Deemed to Be University), Department of Data Science, Lavasa, India</text>
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                <text>Voices of the Future: Generation Zs Views on AIs Ethical and Social Impact</text>
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                <text>As artificial intelligence (AI) becomes increasingly integral to modern society, its profound implications are coming to the forefront of discussions. This research paper investigates the perspective of Generation Z on the multifaceted societal and ethical impacts of AI. Gen Z is the first generation to fully embrace AI across all facets of life. Therefore, understanding their attitudes, concerns, and expectations towards AI is imperative for cultivating a responsible, adaptable, and ethically conscious society in the AI-driven era. This study addresses a significant research gap by exploring Gen Zs perceptions of the challenges associated with AI, such as issues related to privacy, data security, transparency, bias, public fear and more. It also examines the impact of AI on employment dynamics, specifically on job displacement and the necessity for reskilling in the face of AI-driven automation. The paper adopts a global perspective, acknowledging the variations in perception influenced by cultural, economic, and historical factors. Leveraging a sample size of approximately 200250 respondents aged 1825years, the research aims to provide a comprehensive view of Gen Zs viewpoints on AIs ethical and societal ramifications. Findings emphasize the need for transparent and accountable AI systems, as Gen Z is uncomfortable with the ambiguity in AI algorithms. Concerns about privacy and data security highlight the necessity for robust safeguards. They also advocate for strategies to address job displacement and ensure harmonious coexistence between humans and AI. In education, Gen Z sees AI as transformative, endorsing personalized learning. They stress the importance of regulatory frameworks to combat AI bias. They recognize AIs potential to enhance human connections and combat social isolation. The studys findings contribute to policy discussions, educational strategies, and business practices, offering insights into how to harness AIs benefits while mitigating its potential pitfalls.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.</text>
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                <text>Gupta A.; Pranathy R.S.; Binny M.; Chellasamy A.; Nagarathinam A.; Pachiyappan S.; Bhagat S.</text>
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                <text>Studies in Systems, Decision and Control, Vol-223, pp. 367-386.</text>
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                <text>ISSN: 21984182</text>
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                <text>Gupta A., School of Business and Management, BBAH, CHRIST(Deemed to be University), Bengaluru, India; Pranathy R.S., School of Business and Management, BBAH, CHRIST(Deemed to be University), Bengaluru, India; Binny M., School of Business and Management, BBAH, CHRIST(Deemed to be University), Bengaluru, India; Chellasamy A., School of Business and Management, CHRIST(Deemed to be University), Bengaluru, India; Nagarathinam A., School of Business and Management, CHRIST(Deemed to be University), Bengaluru, India; Pachiyappan S., School of Business and Management, CHRIST(Deemed to be University), Bengaluru, India; Bhagat S., School of Business and Management, CHRIST(Deemed to be University), Bengaluru, India</text>
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                <text>Machine Learningcloud-Based Approach to Identify and Classify Disease</text>
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                <text>Healthcare; Hybrid Decision Making; Internet of Things; Machine Learning Model</text>
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                <text>The term "Internet of Things"(IoT) describes the process of creating and modeling web-related physical objects across computing systems. IoT-based healthcare applications have offered multiple real-time products and benefits in recent years. For millions of people, these programmers provide hospitalization can get regular medical records and healthy lives. The introduction of IoT devices in the health sector has several technological developments. This study uses the IoT to construct a disease diagnostic system. Wearable sensors in this system initially monitor the patient's sympathy impulses. The impulses are then sent by a network environment to a server. In addition, a new hybrid approach to evaluation decision-making was presented as part of this research. This technique starts with the development of a set of features of the patient's pulses. Based on a learning approach qualifications are neglected. A fuzzy neural model was used as a diagnostic tool. A specific diagnosis of a particular ailment, such as the diagnosis of a patient's normal and abnormal pulse or the assessment of insulin issues, would be modeled to assess this technology.  2022 IEEE.</text>
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                <text>Gupta B.; Alagdeve V.D.; Padmaja P.; Coumaressin T.; Reddy V.N.K.; Kumar R.G.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Gupta B., Siddhant College of Engineering, Department of I.T., Pune, India; Alagdeve V.D., Yeshwantrao Chavan College of Engineering, Department of Electronics Engineering, Nagpur, India; Padmaja P., Teegala Krishna Reddy Engineering College, Department of Electronics and Communication Engineering, Hyderabad, India; Coumaressin T., Sri Manakula Vinayagar Engineering College, Puducherry, India; Reddy V.N.K., Shri Jagdishprasad Jhabarmal Tibrewala University, Department of Computer Science &amp;amp; Engineering, Jhunjhunu, India; Kumar R.G., School of Engineering and Technology Christ (Deemed to Be University), Computer Science and Engineering, Bangalore, India</text>
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                <text>Knowledge or Personality: An Empirical Analysis of Behavioural Finance and Investor Cognitive Biases</text>
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                <text>Big Five; Cognitive Biases; Decision Making; Disposition Effect; Investor Behaviour; Personality Traits</text>
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                <text>This research attempts to analyze to what extent knowledge and tactics or enduring personality traits predict investor behaviour and cognitive biases in portfolio investment. This study is based on exploring a wide-ranging dataset: responses to a questionnaire survey together with transactional data of the same individual customers of an Indian stock company. From the questionnaire survey, the authors estimate measures of domain-general personality traits, such as the big five, as compared to the knowledge, financial literacy, competency, and attitude specific to investor equity trading. The results show the dominance of knowledge and tactics measures over personality-related measures when predicting nine different dependent variables of investment performance, investor cognitive biases, and portfolio investment activity. This research concludes with the discussion of the findings and with insights into theory and managerial implications. Copyright  2022, IGI Global.</text>
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                <text>International Journal of Cyber Behavior, Psychology and Learning, Vol-12, No. 1</text>
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