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An augmented artificial bee colony algorithm for data aggregation in wireless sensor networks
As wireless sensor networks comprise of a vast number of resource constrained tiny sensor nodes which are designed to operate for a long period of time, it is inevitable to efficiently utilize the available resources. Even though energy harvesting approaches exist, energy efficiency in these networks remains the primary concern. Innovative data collection methods help in the optimal utilization of the confined resources like energy, memory and processing capabilities. Majority of the energy is consumed for data transmission in contrast to sensing and processing. Adopting self-organizing system intelligence of the nature for modern advancements is effective and efficient. This paper provides a gist of the existing bio-inspired routing algorithms and describes a new energy efficient data collection strategy with mobile sinks in wireless sensor networks. IAEME Publication. -
Neurodiversity at the Workplace: The new paradigm of talent acquisition and retention
The importance of neurodiversity in the workplace has gained popularity in recent years. Companies can access a pool of distinctive skills and viewpoints that can stimulate innovation, creativity, and productivity by embracing neurodiversity in the workplace. This chapter examines the idea of neurodiversity in relation to hiring and retaining talent, emphasizing the advantages for both companies and workers. It covers methods for establishing welcoming environments at work that support neurodiverse workers and help them reach their full potential. It also looks at how corporate culture, HR regulations, and leadership all contribute to creating a welcoming workplace for individuals who are neurodiverse. Companies can promote diversity, equity, and inclusion at the workplace in addition to attracting and retaining neurodiverse employees (NDEs). A conceptual framework has been proposed to demonstrate the influence of various factors like awareness, perceived benefits, accommodation, organizational policy, stigma, and unconscious bias on retention of NDEs. 2024, IGI Global. -
Role of AI in Enhancing Customer Experience in Online Shopping
AI-powered tools and applications may provide customers with a positive, effective, and customized purchasing experience. By studying client preferences and behaviours, AI systems can anticipate future customer needs, improving and personalizing the shopping experience. The main aim of this study is to examine the role of artificial intelligence (AI) on enhancing customer experience. The results of this study revealed that there is a positive significant relationship between AI features like perceived convenience, personalization and AI-enabled service quality and Customer experience. A total of 416 responses were analysed using a structured questionnaire. The findings indicate significant role of trust as factor, mediating the effects of independent variables on customer experience. Data was analysed using T-test, ANOVA and regression. 2024 IEEE. -
Consumer Characteristics and Consumption Patterns of Soft Drinks
A soft drink is generally treated as very common product aimed at a very casual consumption. Normally, not much of attention is paid to this product, which has almost become 'commoditized'. But, a deeper and more careful observation would reveal that soft drinks are strong demographic descriptors of their consumers. Key insights into the characteristics and consumption patterns of consumers can be obtained through an incisive study of the soft drinks market. This research paper makes a concerted effort at unearthing the demographic details and consumption contours of the soft drink users in Kanpur, Agra, Varanasi, Allahabad, and Lucknow - the five representative cities of Uttar Pradesh, the most populous state of India. It has been conclusively established through this research that the residents of these five cities - which are demographically similar in nature - exhibit varying consumption patterns when it comes to soft drinks. It was also found that demographic variables like age, gender, educational qualification, income, and marital status do not significantly impact the consumption of soft drinks, whereas employment status is a key influencer of the same. 2021 IEEE. -
Time Efficient Hash Key Generation for Blockchain Enabled Framework
Blockchain, in general, helps organizations to improve the transparency and governance by removing its shortfalls and building better control overall. Blockchain network, public or private, is a competent technology when used in order with an optimized hashing technique. In a blockchain network, one of the common issues is performance while registering any transactions. Blockchain must need to do some preliminary checks to avoid double-spending before registering the transaction. Here, we implement one of the optimization aspects of the hashing technique, which can contribute to the blockchain mining processes and save time. It enables the blockchain to perform efficiently and reliably. In addition, we examine how well different hashing algorithms perform when added to the blockchain network's processes. In this research, we analyze several hashing techniques that are employed in the blockchain and are also applied in the supply chain domain due to their efficacy in mitigating past attacks. Our proposed hashing technique allows a blockchain network to improve security and its overall processes. The proposed hashing technique achieves approx. 10-90% performance gain improvements over other existing technique. Our proposed hashing technique allows a blockchain network to improve security and its overall processes. The study also examines how the supply chain management contributes in increasing of overall lead time where process optimization or technological enhancement plays key roles in minimizing the time of some or all the processes. Lead time is one of the common issues of supply chain which impacts on overall order delivery time. We address on how the conjunction of blockchain with optimized hashing technique can address supply chain lead time issues. 2013 IEEE. -
A Brief Review on the Role of Blockchain in Supply Chain Management
Blockchain is a proficient technology when used in combination with other intelligent technologies which gives an opportunity to an organization to rethink about improvement of their supply chain internal and external processes. It helps in improvement of transparency and provenance by removing shortfalls and building a better organizational control overall. However, blockchain faces numerous challenges, e.g., transaction speed, decentralization, scalability, interoperability, and lack of standardization that could affect its adoption across organizations. However, a greater number of research are required to overcome the governance, standardization, and technological challenges involved within. Concisely, blockchain in supply chain is still in initial phase, many improvements are needed for better adaptation of blockchain using Machine Learning, Neural Network algorithms to make optimized computation decision of blockchain framework. In this paper, we studied and discussed about blockchain and its type, consensus mechanism, blockchain in supply chain, key issues of blockchain and supply chain and intelligence in blockchain. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Unveiling the pattern of PhishingAttacks using the Machine Learning approach
This study introduces a unique approach to strengthening cybersecurity by combining advanced models for real-time detection of phishing websites. A classifier is trained to discern patterns associated with legitimate and phishing URLs, leveraging a carefully organized labeled dataset. The model in this paper forms the foundation for a real-time detection system, providing users with real-time information on potential phishing threats. Integrating an adaptive decision-making algorithm improves decision-making adaptability, particularly in scenarios challenging the model's confidence. A user feedback loop ensures the continuous learning and refinement of the system, aligning it more closely with user expectations. The future scope of this research involves exploring advanced models, improving explainability, and incorporating dynamic features for enhanced detection. Adaptive policies, large-scale deployment, and ethical implications are pivotal for real-world applicability. In conclusion, this study contributes to advancing phishing detection methodologies and lays the groundwork for future innovations in cybersecurity. The collaborative efforts of academia, industry, and cybersecurity stakeholders arenecessaryfor realizing the full potential of this paper and ensuring a safer online platform for users. 2024 IEEE. -
Teaching as a political act: The role of critical pedagogical practices and curriculum /
Human Affairs, Vol.26, ISSN: 1337-401X. -
Rethinking interdisciplinarity in social sciences: Is it a new revolution or paradox? /
Journal Of Interdisciplinary Studies In Eductaion, Vol.4, Issue 2, pp.44-66, ISSN: 2166-2681 (Print), 2690-0408 (Online). -
Decolonizing social psychology in India: Exploring its role as emancipatory social science /
Psychology & Society, Vol.8, Issue 1, pp.57-74, ISSN: 2041-5893. -
The social representations of academic achievement and failure /
Psychological Studies, Vol.60, Issue 2, pp.231-241, ISSN No: 0974-9861 (Online) 0033-2968 (Print) -
Rethinking the place of socioeconomic status identity in students' academic achievement /
European Journal of Psychology & Educational Studies, Vol.2, Issue 2, pp.242-249, ISSN No: 2395-2555 (Online) -
A smart attendance system and method for permission inventory during the class /
Patent Number: 202111060922, Applicant: Shivani Chaudhry.
A smart attendance system (1). The system (1) comprises a smart lecture stand (2), which having an electronic unit (2A) which is connected to the other smart door, smart bench, and smart chair of the system; a smart bench (3), which having an electronic unit (3A), which is connected to the other smart door, smart stand, and smart chair of the system; a smart chair (4) comprises which having an electronic unit (4A); which is connected to the other smart door, smart bench, and smart stand of the system; a smart door (5) comprises a electronic unit (5A), which is connected to the other smart door, smart bench, and smart chair of the system. -
Models of cuber security and data privacy analysis for Indian consumer's e-commerce decision making /
Patent Number: 202211043969, Applicant: Priyanka Kaushik.
Even though it is clear that e-commerce meets the requirements of customers, businesses and the clients they serve continue to be susceptible to cyberattacks, which may already be in progress against them. In this study, a comprehension of the antecedent elements that generate concerns among Indian consumers while using ecommerce websites is presented. It seeks to quantify the perceived hazards and data privacy issues that influence an individual's approach to making a risk-informed purchasing decision. The sake of this investigation, a quantitative method of approach has been used. -
A smart attendance system and method for permission inventory during the class /
Patent Number: 202111060922, Applicant: Shivani Chaudhry.
A smart attendance system (1). The system (1) comprises a smart lecture stand (2), which having an electronic unit (2A) which is connected to the other smart door, smart bench, and smart chair of the system; a smart bench (3), which having an electronic unit (3A), which is connected to the other smart door, smart stand, and smart chair of the system; a smart chair (4) comprises which having an electronic unit (4A); which is connected to the other smart door, smart bench, and smart stand of the system; a smart door (5) comprises a electronic unit (5A), which is connected to the other smart door, smart bench, and smart chair of the system. -
Analyzing students academic performance using multilayer perceptron model
Identification of the students behavior in the class room environment is very important. It helps the lecturer to identify the needs of the students. It also aids in identifying the strength and weakness of the individual and guide them to improve on their performance. Observing and supervising the students regularly can improve their performance. The data has been collected from 120 students who took the common the course taught by two different lectures. The students were observed based on the internal assignments and quizzes and the model exam given by the respective lecturers. In this paper the students are categorized into different groups based on their performance using Multilayer Perceptron (MLP) and also different factors which are influencing the performance of the students are identified. BEIESP. -
Assessing Human Stress Through Smartphone Usage
Stress occurs in a human being when they are faced with exigent situations in life. Assessing stress has been always challenging. Smartphones have become a part of everyones day-to-day activity in the present time. Considering humansmartphone interaction, sensing of stress in an individual can be assessed as todays youth spends most of their time with smartphones. Taking this into consideration, a study is carried out in this paper on assessing stress of an individual based on their interaction with the smartphone. In this work, humansmartphone interaction features, like swipe, scroll, and text input, are examined. Text input is incorporated by disabling the autocorrection and spelling checker features of the keyboard. Moreover, sensor data is used by Google activity recognition API to analyze the physical activity of the individual to assess the stress level. 2019, Springer Nature Singapore Pte Ltd. -
Development of smart energy monitoring using NB-IOT and cloud
IoT-based applications are growing in popularity nowadays because they offer effective answers to numerous current problems. In this research, With the aim of decreasing human efforts for monitoring the power units and increasing users' knowledge of excessive electricity usage, an IoT-based electric metre surveillance system utilising an Android platform has been developed. With the help of an Arduino Uno and an optical sensor, the electric analyser pulse is captured. To reduce human mistake and the expense of energy usage, a low-cost wireless network of sensors for digital energy metres is implemented alongside a smartphone application that can autonomously read the metre of the unit. In this research, an intelligent power monitoring system with effective communication modules has been developed to make wise use of the electricity. The controller, NB-IoT connection module, and cloud are the three main components of an IOT-based smart energy metre system. The controller is essential for maintaining the functionality of each component. This solution reduces the need for human involvement in electricity maintenance by connecting energy metres to the cloud using an NB-IoT communication module. The IoT-based metre reading system in the proposed work is created to monitor and analyse the metre reading, and the service provider can cut off the source of electricity whenever the customer fails to pay the monthly bill. It also eliminates the need for human intervention, provides accurate metre reading, and guards against billing errors. The proposed SPM improves the overall accuracy ranges of 7.42, 27.83, and 20% better than DR, OREM, and SLN respectively. 2023 -
The role of big data in predicting consumer behavior
Consumer behavior prediction is a significant task, and it is a prerequisite for marketing activities. Regardless of the product type/market type, predicting consumer behavior plays a vital role in determining the target market. The activities involved in identifying a target market include the tasks of analyzing the offerings, conducting market research, identifying market segments to create consumer profiles, and assessing the competition. In order to complete all four tasks mentioned above, it needs to have comprehensive and precise data/dataset in hand. It also means that the data/fact is the primary source of predicting consumer behavior. In today's digital world, sources of source (data) are multifold. During the process of data collection, if the repository is accepting data from such sources, then all five "V" (Volume, Velocity, Variety, Veracity, and Value) of data should be considered. The role of big data in predicting consumer behavior is inevitable. Machine learning models shall be deployed to analyze data from big data. In this chapter, benchmark datasets, and machine learning, are used to demonstrate the usage of artificial intelligence in analyzing, forecasting, and predicting consumer behavior. Before concluding the chapter, the performance of algorithms is evaluated and compared to find the most suitable models for predicting consumer behavior. Benchmark datasets are used in this chapter to represent the role of big data in predicting consumer behavior. 2023 Nova Science Publishers, Inc. All rights reserved. -
Assessing Academic Performance Using Ensemble Machine Learning Models
Artificial Intelligence (AI) shall play a vital role in forecasting and predicting the academic performance of students. Societal factors such as family size, education and occupation of parents, and students' health, along with the details of their behavioral absenteeism are used as independent variables for the analysis. To perform this study, a standardized dataset is used with data instances of 1044 entries and a total of 33 unique variables constituting the feature matrix. Machine learning (ML) algorithms such as Support Vector Machine (SVM), Random Forest (RF), Multilayer Perceptron (MLP), LightGBM, and Ensemble Stacking (ES) are used to assess the specified dataset. Finally, an ES model is developed and used for assessment. Comparatively, the ES model outclassed other ML models with a test accuracy of 99.3%. Apart from accuracy, other parameters of metrics are used to evaluate the performance of the algorithms. 2023 IEEE.