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Text Summarization Using Combination of Sequence-To-Sequence Model with Attention Approach
In daily life, we come across tons and tons of information which can be related to news articles or any kind of social media posts or customer reviews related to product. It is difficult to read all the content due to time constraint. Being able to develop the software that can identify and automatically extract the important information. There are two types of summarization methods. Extractive text summarization is the method where it picks the important content from the source text and gives same in the form of short summary, and on the other hand, abstractive summarization is the technique where it gets the context of the source text, and based on that context, it regenerates small and crisps summary. In this paper, we use the concept of neural network with attention layer to deal with abstractive text summarization that generates short summary of a long piece of text using review dataset. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Comparative Study of Machine Learning Techniques for Credit Card Customer Churn Prediction
A customer is a churner when a customer moves from one service provider to another. Nowadays, with an increasing number of severe competition with inside the market, essential banks pay extra interest on customer courting management. A robust and real-time credit card holders churn evaluation is vital and valuable for bankers to preserve credit cardholders. Much research has been observed that retaining an old customer is more than five times easier compared to gaining a new customer. Hence, this paper proposes a method to predict churns based on a bank dataset. In this work, Synthetic Minority Oversampling Technique (SMOTE) has been used for handling the imbalanced dataset. Credit card customer churn is predicted using random forest, k-nearest neighbor, and two boosting algorithms, XGBoost and CatBoost. Hyperparameter tuning using grid search has been used to increase the accuracy. The experimental result shows Catboost has achieved an accuracy of 97.85% and tends to do better than the other models. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Gamification in Education and Its Impact on Student MotivationA Critical Review
In education, gamification refers to including game characteristics and design ideas in the classroom setting. Over the previous five years, gamification has increased student motivation and academic performance. This study will examine the previous literature to see how gamification will disseminate over time, educational level (from nursery to college), causes, and the most frequently used game elements. A systematic literature review will search interdisciplinary databases for quantitative experimental studies examining educational gamification and providing information on current research lines. According to the findings of a comprehensive research study, gamification can be advantageous at all academic levels, from elementary school to college. Following systematic research, gamified learning can increase students motivation and intellectual accomplishment. Student learning may be made more pleasurable via gamification, which is the first advantage of this type of instruction. When used in the classroom, gamification can assist students who are weak in motivation and performing poorly academically. Because of the diversity of challenges and rewards that gaming parts provide, incorporating gaming elements into the classroom may serve as a motivational tool for students to learn. In the study's findings, students who enrolled in educational gamification courses were shown to be more interested and participatory than students enrolled in regular classrooms, on average. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
E-learning During COVID-19Challenges and Opportunities of the Education Institutions
As part of the COVID-19 lockdown, educational institutions were closed and adopted e-learning to keep the learning process going. Due to the COVID-19 pandemic, e-learning has become a required component of all educational institutions such as schools, colleges, and universities worldwide. This pandemic has thrown the offline teaching process into chaos. This chapter discusses the concept and role of e-learning during the pandemic and various challenges and opportunities of e-learning encountered by educational institutions. Three broad challenges identified in e-learning are inaccessibility, self-inefficacy, and technical incompetency. E-learning opportunities are no geographic barriers, flexibility, creativity, and critical learning incorporation increased utilization of online resources and reinforced distance learning. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Blockchain and Its Integration in IoT
IoT devices have become an integral part of our lives. The world has witnessed an exponential growth in the number of IoT devices. Managing these devices and the data generated by them has become very crucial. Data security and users privacy are becoming more difficult as the number of devices grows. Blockchain, the technology behind Bitcoin, is known for data security and managing and efficiently maintaining huge amounts of data. Blockchain stores data in a chronological manner and in an immutable way. Integration of blockchain in IoT infrastructure has many advantages. This paper discusses various applications and challenges in blockchain. It highlights the adoption of blockchain in IoT infrastructure and reviews recent papers in this field. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Artificial Intelligence-Monitored Procedure for Personal Ethical Standard Development Framework in the E-Learning Environment
The changes in the lifestyle of human beings due to the pandemic COVID-19 have affected all walks of human life. As a pillar of human development, the arena of education has a vital role to play in this changing world. The humongous and disruptive technologies that had made inroads into the educational scene as E-learning paved the way for ethical concerns in an unimaginable manner. Artificial intelligence is prudently incorporated for developing an ethical lifestyle for students all over the world. The Personal Ethical Standard Framework would work as a vaccine for the pandemic of the cancerous growth of the unethical habits of learners. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Conception of Blockchain Platform for Milk and Dairy Products Supply Chain in an Indian Context
The potential for adulteration in the Indian dairy supply chain process is immense. The possibility of incorrect information recorded by middlemen cannot be ruled out and found to be rampant. The reality is that the data required to assess the safety and quality of milk produced is inadequate in the existing setup. The current set of checks and balances to fight adulteration of milk and dairy products in India is studied and articulated. An elaborate and daunting set of procedures marks these checks and is still significantly found wanting. To increase the product's safety and traceability of the product an alternate pathway to deploy Blockchain technology in the milk and dairy product supply chain has been proposed. Despite the proposal requiring drastic changes in the milk and dairy industry, the authors believe the benefits of implementing a Blockchain platform far outweigh the challenges involved. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Clustering Faculty Members fortheBetterment ofResearch Outcomes: A Fuzzy Multi-criteria Decision-Making Approach inTeam Formation
From a talent-pool of people, choosing an efficient team is tough. Faculty members of a higher education institution constitute the talent-pool. Teams have to be formed from them so that research output of each team is maximum. Amongst numerous research skills, thirteen are identified as most desirable skills. The level of these thirteen skills, viz., concept articulation, formatting according to templates/style sheets, identifying the relevant literature, initiative, logical reasoning, patience, problem formulation/problem finding, proof reading skills/identifying mistakes in written communication, searching/browsing skills/quick search techniques, sense of positive criticism, statistical knowledge, the ability to stay calm, and written communication skills, varies from person to person. Historical ranking of these skills and self-evaluation of the level of acquisition of these skills is used along with the years of experience, educational qualification, gender, marital status, etc., to rank individual faculty members. The fuzzy ranking of the faculty members thus obtained is used to cluster them into teams that are efficient in complementary skills. Each team thus formed is involved in collaborative research leading to research publication. The model is successfully implemented in a university department with 40 faculty members. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Comparative Analysis of Different Machine Learning Prediction Models for Seasonal Rainfall and Crop Production in Cultivation
Agriculture is one of the strengths of India, from the last few years, gradually the agriculture growth is going downwards in other side the population growth is upwards. Reason for agricultural downward growth depends on so many parameters. The rainfall is one of the main parameters which affects the crop yield. Because of this, the farmers are also facing the loss. If they know this information in prior, the farmers can plan accordingly the type of crop suited for the particular season and it helps the farmer to get good profit out of it. Machine learning scientific and statistical methods are used for predicting the rain fall and crop yield. Kharif and Rabi are two seasons taken for analysis. The regressor predicting models are constructed to predict the seasonal rainfall and crop yield. This study primarily focuses on seasonal crop production prediction, which is dependent on rainfall. The different types of machine learning regression method are used to achieve better results. The performance of comparison models is evaluated using different metrics. Finally, the linear regression and Bayesian linear regression models comparatively produce the best result in terms of accuracy for rainfall prediction. The boosted decision tree regression model is achieving the better result for crop prediction. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Volatility Clustering in Nifty Energy Index Using GARCH Model
Volatility has become increasingly important in derivative pricing and hedging, risk management, and portfolio optimisation. Understanding and forecasting volatility is an important and difficult field of finance research. According to empirical findings, stock market returns demonstrate time variable volatility with a clustering effect. Hence, there is a need to determine the volatility in Indian stock market. The authors use Nifty Energy data to analyse volatility since the Nifty Energy data can to be used to estimate the behaviour and performance of companies that represents petroleum, gas, and power sector. The results reflect that Indian stock market has high volatility clustering. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Integration of sustainability in business through finance
[No abstract available] -
Introduction: Tourism at a crossroads
[No abstract available] -
Improving organizational environmental performance through green training
It is necessary to equip employees with green abilities as well as to develop their dedication towards green behaviour in order to improve an organization's environmental performance. The purpose of this research is to evaluate the direct impact of green training on organizational environmental performance (OEP) and the mediating effect of organizational citizenship behaviour on the environment (OCBE). The study is based on responses from 107 employees of the IT sector in India. The findings suggest that green training has a significant positive impact on the organizational environmental performance and that the impact is strengthened by organizational citizenship behaviour towards the environment. The findings are of particular importance given the growing importance of sustainability in the organizational context. 2023, IGI Global. All rights reserved. -
A Comparison of Similarity Measures in an Online Book Recommendation System
To assist users in identifying the right book, recommendation systems are crucial to e-commerce websites. Methodologies that recommend data can lead to the collection of irrelevant data, thus losing the ability to attract users and complete their work in a swift and consistent manner. Using the proposed method, information can be used to offer useful information to the user to help enable him or her to make informed decisions. Training, feedback, management, reporting, and configuration are all included. Our research evaluated user-based collaborative filtering (UBCF) and estimated the performance of similarity measures (distance) in recommending books, music, and goods. Several years have passed since recommendation systems were first developed. Many people struggle with figuring out what book to read next. When students do not have a solid understanding of a topic, it can be difficult determining which textbook or reference they should read. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Biomass-derived carbonaceous materials: Synthesis and photocatalytic applications
[No abstract available] -
Introduction to blockchain for internet of things
[No abstract available] -
Microbial fuel cells for electricity generation and environmental bioremediation
The environmental impact on the use of fossil fuels and their unsustainable nature has led to the development of techniques using renewable energy and fuel cells. The recent decade has captured the attention of scientists towards the importance of microbial fuel cells (MFCs) with the role of microbial ability in converting organic wastes directly to electricity through microbially catalyzed anodic reactions along with microbial/enzymatic cathodic electrochemical reactions. MFC represents an environmental friendly approach for the use of generating electricity using wastewater, thus ensuring a bioremedial approach for effluent treatment with the achievement of chemical oxygen demand (COD) of about 50% chemical oxygen demand and power densities. This MFC utilises microbial metabolism for electricity generation. The overall performance of electricigens or MFC is based on the reactor design, operating conditions, electrode material used, types of substrates, and microorganisms involved. The optimization parameters studies for commercial production and their applications for MFC need to be intensified. Microbes have applications as biopolymer electrolytes that can be variously used in the applications of batteries, fuel cells and dye-sensitized solar cells. The use of MFCs has many advantages as they are eco-friendly, they have high performance abilities and they are costeffective and therefore can be used for modern applications. 2022 by Nova Science Publishers, Inc. -
Differential query execution on privacy preserving data distributed over hybrid cloud
Hybrid cloud is proposed as a solution for ensuring security and privacy for data outsourced to cloud. Hybrid cloud uses a mix of both private and public cloud with distribution of sensitive information to private cloud and insensitive information to public cloud. Though data distributed over multi storage provides enhanced security and privacy, query performance is distorted. This work proposes a privacy preserving data distribution with goal of ensuring reduced query latency for data distributed over hybrid clouds without any compromise to the security and privacy. The proposed solution also provides different queries results for the query depending on the access control provided to the users. 2022 Scrivener Publishing LLC.