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A multi-preference integrated algorithm for deep learning based recommender framework
Nowadays, the online recommender systems based collaborative filtering methods are widely employed to model long term user preferences (LTUP). The deep learning methods, like recurrent neural networks (RNN) have the potential to model short-term user preferences (STUP). There is no dynamic integration of these two models in the existing recommender systems. Therefore, in this article, a multi-preference integrated algorithm (MPIA) for deep learning based recommender framework (DLRF) is proposed to perform the dynamic integration of these two models. Moreover, the MPIA addresses improper data and to improve the performance for creating recommendations. This algorithm is depending on an enhanced long short term memory (LSTM) with additional controllers to consider relative information. Here, experiments are carried out by Amazon benchmark datasets, then obtained outcomes are compared with other existing recommender systems. From the comparison, the experimental outcomes show that the proposed MPIA outperforms existing systems under performance metrics, like area under curve, F1-score. Consequently, the MPIA can be integrated with real time recommender systems. 2022 John Wiley & Sons, Ltd. -
Blockchain for Securing Healthcare Data Using Squirrel Search Optimization Algorithm
The Healthcare system is an organization that consists of important requirements corresponding to security and privacy, for example, protecting patients medical information from unauthorized access, communication with transport like ambulance and smart e-health monitoring. Due to lack of expert design of security protocols, the healthcare system is facing many security threats such as authenticity, data sharing, the conveying of medical data. In such situa-tion, block chain protocol is used. In this manuscript, Efficient Block chain Network for securing Healthcare data using Multi-Objective Squirrel Search Optimization Algorithm (MOSSA) is proposed to generate smart and secure Healthcare system. In this the block chain is a decentralized and the distributed ledger device that consists of various blocks linked with digital signature schemes, consensus mechanisms and chain of hashing, offers highly reliable storage capabilities. Further the block chain parameters, such as block size, transac-tion size and number of block chain channels are optimized with the help of MOSSA. With the evolution of the MOSSA provide new features for enhancing security and scalability. The simulation process is executed in the JAVA platform. The experimental result of the proposed method shows higher throughput of 26.87%, higher efficiency of 34.67%, lowest delay of 22.97%, lesser computational overhead of 37.03%, higher storage cost of 34.29% when compared to the existing method such as Block chain-ECIES-HSO, Block chain-hybrid GO-FFO, Block chain-SDN-HSO algorithm for healthcare technologies. 2022, Tech Science Press. All rights reserved. -
IoT Infrastructure to Energize Electromobility
Mobile technology is becoming more sophisticated as it advances. A comparison of different mobility scenarios was conducted. This chapter examined how electric vehicles interact with local energy systems in Stuttgart. Utilizing a travel demand model, a charging profle based on mobility patterns was generated for electric vehicles. During a quarter, charging demand and standard household load profles were used to analyze peak hour load fow for 349 households. Considering that peak loads and charging capacity are usually separated in time, greater charging capacity might lead to lower utilization of transformers. Furthermore, a study was conducted to determine if the existing infrastructure was adequate for future demand, focusing on substation transformer reserves. Electromobility is a rapidly growing and evolving application domain of the Internet of Things, with a huge market potential in various areas. It incorporates many stakeholders from manufacturers to the players of the energy market with all sorts of physical and virtual resources. It is essential to allow these devices and systems to collaborate to create advanced e-mobility services. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
Machine Learning in Cyber Threats Intelligent System
Cybercriminals disrupt services, exfiltrate sensitive data, and exploit victim machines and networks to perform malicious activities against organizations. A malicious adversary seeks to steal, destroy, or compromise business assets that have a specific financial, reputational, or intellectual value. As a result, organizations are complementing their perimeter defenses with threat intelligence platforms to address these security challenges and eliminate security blind spots for their systems. Any type of information useful for identifying, assessing, monitoring, and responding to cyber threats is considered cyber threat intelligence. Organizations can benefit from increased visibility into cyber threats and policy violations. An organizations threat intelligence allows them to prevent or mitigate various types of cyberattacks. The use of machine learning and artificial intelligence is a key component of cybersecurity conflict, which together allows attackers and defenders to function at new speeds and scales. In spear-phishing attacks, relatively frivolous machine learning algorithms have been used to overwhelming effect as adversarial artificial intelligence. This chapter discusses the various cyber threats, cyber security attack types, publicly available datasets for research work, and machine learning techniques in cyber-physical systems. 2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors. -
Applications of Digital Technologies and Artificial Intelligence in Cryptocurrency - A Multi-Dimensional Perspective
The paradigm shift requires spreading the light of decentralized ledger technology, extraordinarily implementing cryptocurrencies, and being visible as a game-changer. Blockchain technology, along with cryptocurrencies like Bitcoin, Ethereum, and Litecoin, is a tool for global economic transformation that is rapidly gaining traction in the finance industry. However, these technologies have had low popularity in the consumer market. Many platforms have been misunderstood and ignored when there is an obvious hole in among them. The basic idea behind cryptocurrency is that it is a network-based, totally virtual exchange medium that utilizes cryptographic algorithms such as Secure Hash Algorithm 2 (SHA-2) and Message Digest 5 (MD5) to secure the data. Transactions within the blockchain era are secure, transparent, traceable, and irreversible. Cryptocurrencies have gained a reputation in practically all sectors, including the monetary sector, due to these properties. The uncertainty and dynamism of their expenses, however, hazard investments substantially despite cryptocurrencies growing popularity amongst approval bodies. Studying cryptocurrency charge prediction is fast becoming a trending subject matter in the global research community. Several device mastering and deep mastering algorithms, like Gated Recurrence Units (GRUs), Neural nets (NNs), and nearly short-term memory, were employed by the scientists to analyze and forecast cryptocurrency prices. As a part of this chapter, we discuss numerous aspects of cryptographic protection and their related issues. Specifically, the research addresses the state-of-the-art by examining the underlying consensus mechanism, cryptocurrency, attack style, and applications of cryptocurrencies from a unique perspective. Secondly, we investigate the usability of blockchain generation by examining the behavioral factors that influence customers decision to use blockchain-based technology. To identify the best crypto mining strategy, the research employs an Analytic Hierarchy Process (AHP) and Fuzzy-TOPSIS hybrid analytics framework. Furthermore, it identifies the top-quality mining methods by evaluating providers overall performance during cryptocurrency mining. 2023 Scrivener Publishing LLC. -
Classification of Breast Invasive Ductal Carcinomas Using Histopathological Images Based on Deep Learning Techniques
Women suffer from cancer, which is the main reason for death for females around the world. With the use of artificial intelligence, it is possible to predict and detect all types of cancers in the near future. It is not just women who can heal, and most breast cancers are caused by the most vulnerable type of breast. Eighty percent of all diagnoses of carcinoma are invasive ductal carcinomas (IDCs). In this paper, deep learning techniques are extended to support visible semantic evaluation of tumor areas, using convolutional neural networks (CNNs).A CNN is skilled ended a large number of photo covers (tissue areas) after Whole Slide Images (WSI) to study ranked part-based total image. About 600 normal image patches and 200 breast invasive ductal carcinomas are selected for the experiment. It was intended to amount classifier correctness in the detection of IDC tissue areas in Whole Slide Images. We achieved excellent measurable outcomes for an automated finding of IDC areas with our technique. The results are evaluated based on performance measures and compared with a different number of neurons, and the results are highlighted. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Effects of a Mindfulness-based Intervention on Well-being Among Rural Adolescents with Academic Anxiety
Background: Academic anxiety revolves around scholastic work and performance and can be detrimental to students health and overall subjective well-being. It has been found to be significantly high in adolescents, leading to consequences that prove to be detrimental to their academic performance, focus, and overall self-esteem. This phenomenon acts as a vicious cycle impacting all aspects of a students life. Method: The current study aimed to explore mindfulness-based intervention (MBI) as a possible option to deal with academic anxiety in rural adolescent students and improve their overall subjective well-being. A total of 600 students were screened for academic anxiety and a total of 47 students were subjected to an eight-week MBI. MBI aims to bring more present-moment awareness and cultivate overall well-being and thereby works against anxiety. Mixed repeated measures ANOVA was carried out to compare pre, post, and follow-up scores. Result: The results indicated a significant effect of MBI on adolescents, suggesting a significant decline in academic anxiety from pre-to-post and an increase in mindfulness and subjective well-being from pre-to-post and follow-up assessments. Conclusion: Academic anxiety and subjective well-being improved significantly with the MBI intervention, thereby implication that MBI is a feasible option for rural adolescents with academic anxiety. 2024 The Author(s). -
Smart Metering System with Google Assistant
This paper presents a unique research problem in the area of automation system by using IoT. The mentioned approach utilizes Google assistant, which is incorporated within Google home which uses voice-controlled inputs and voice feedbacks. This paper discusses a new method to develop a smart energy meter at a distributor level and to make use of this technology to monitor the power consumption of each device individually which can help the user to monitor the electricity usage in real time and thus helps to save electricity and reduce cost on your electricity bill. 2020, Asian Research Association. All rights reserved. -
One Pot Hydrothermal Synthesis and Application of Bright-yellow-emissive Carbon Quantum Dots in Hg2+ Detection
Carbon quantum dots (CQD) have drawn great interest worldwide for their extensive application as sensors due to their extraordinary physical and chemical characteristics, good biocompatibility, and high fluorescence in nature. Here, we demonstrate a technique for detecting mercury (Hg2+) ion using a fluorescent CQD probe. Ecology is concerned about the accumulation of heavy metal ions in water samples due to their harmful effects on human health. Sensitive identification and removal of metal ions from water samples are required to reduce heavy metals risk. To find out Mercury in the water sample, carbon quantum dots were used and synthesized by 5-dimethyl amino methyl furfuryl alcohol and o-phenylene diamine through the hydrothermal technique. The synthesized CQD shows yellow emission when exposed to UV irradiation. Mercury ion was used to quench carbon quantum dots, and it was found that the detection limit was 5.2 nM with a linear range of 15100 M. The synthesized carbon quantum dots were demonstrated to efficiently detect Mercury ions in real water samples. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Green Synthesis of Bioinspired Nanoparticles Mediated from Plant Extracts of Asteraceae Family for Potential Biological Applications
The Asteraceae family is one of the largest families in the plant kingdom with many of them extensively used for significant traditional and medicinal values. Being a rich source of various phytochemicals, they have found numerous applications in various biological fields and have been extensively used for therapeutic purposes. Owing to its potential phytochemicals present and biological activity, these plants have found their way into pharmaceutical industry as well as in various aspects of nanotechnology such as green synthesis of metal oxide nanoparticles. The nanoparticles developed from the plants of Asteraceae family are highly stable, less expensive, non-toxic, and eco-friendly. Synthesized Asteraceae-mediated nanoparticles have extensive applications in antibacterial, antifungal, antioxidant, anticancer, antidiabetic, and photocatalytic degradation activities. This current review provides an opportunity to understand the recent trend to design and develop strategies for advanced nanoparticles through green synthesis. Here, the review discussed about the plant parts, extraction methods, synthesis, solvents utilized, phytochemicals involved optimization conditions, characterization techniques, and toxicity of nanoparticles using species of Asteraceae and their potential applications for human welfare. Constraints and future prospects for green synthesis of nanoparticles from members of the Asteraceae family are summarized. 2023 by the authors. -
Bioactive nanoparticles derived from marine brown seaweeds and their biological applications: a review
The biosynthesis of novel nanoparticles with varied morphologies, which has good implications for their biological capabilities, has attracted increasing attention in the field of nanotechnology. Bioactive compounds present in the extract of fungi, bacteria, plants and algae are responsible for nanoparticle synthesis. In comparison to other biological resources, brown seaweeds can also be useful to convert metal ions to metal nanoparticles because of the presence of richer bioactive chemicals. Carbohydrates, proteins, polysaccharides, vitamins, enzymes, pigments, and secondary metabolites in brown seaweeds act as natural reducing, capping, and stabilizing agents in the nanoparticles synthesis. There are around 2000 species of seaweed that dominate marine resources, but only a few have been reported for nanoparticle synthesis. The presence of bioactive chemicals in the biosynthesized metal nanoparticles confers biological activity. The biosynthesized metal and non-metal nanoparticles from brown seaweeds possess different biological activities because of their different physiochemical properties. Compared with terrestrial resources, marine resources are not much explored for nanoparticle synthesis. To confirm their morphology, characterization methods are used, such as absorption spectrophotometer, X-ray diffraction, Fourier transforms infrared spectroscopy, scanning electron microscope, and transmission electron microscopy. This review attempts to include the vital role of brown seaweed in the synthesis of metal and non-metal nanoparticles, as well as the method of synthesis and biological applications such as anticancer, antibacterial, antioxidant, anti-diabetic, and other functions. Graphical abstract: (Figure presented.). The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Bioactive Compounds and Biological Activities of Arrowroot (Maranta arundinacea L.)
Arrowroot is one of the most widely studied herbal species belonging to the family Marantaceae, which originated from South America and is mainly found in tropical areas. Species belonging to the Maranta genus attaining worldwide attention due to the bioactive compounds are present in their rhizomes. The nutritional values of the Maranta arundinacea plant parts were explored in traditional medicine and culinary practices. Maranta arundinacea flour is a good source of fiber, starch, and carbohydrate and is extensively utilized as a major ingredient in food products. It is also used as an alternative to wheat as the flour is gluten-free. Dietary fibers present in the Maranta arundinacea are beneficially used in the treatment of digestive disorders such as celiac disease and immune disorders. Its known to stimulate the production of IgM by immune cells. Maranta arundinacea is commonly used for weight management as it is protein-rich and has fewer calories. The rhizome contains substantial amounts of sodium, magnesium, phosphorus, potassium, calcium, iron, and zinc. The processed starch from the Maranta arundinacea rhizomes is broadly used in nutritional food products as well as in pharmacological applications. The bioactive compounds present in the Maranta arundinacea rhizome make it the subject of novel pharmaceutical studies. The current chapter tries to emphasize the general morphology, nutritional benefits and processing, bioactive compounds, and biological activities of the Maranta arundinacea. Springer Nature Switzerland AG 2024. -
Artemisia stelleriana-mediated ZnO nanoparticles for textile dye treatment: a green and sustainable approach
Textile effluents being one of the major reasons for water pollution raises major concern for water bodies and the habitation surrounding them. The lack of biologically safer treatment solutions creates a major concern for the disposal of these effluents. The present study focuses on the degradation of textile dyes using leaf extract of Artemisia stelleriana-assisted nanoparticles of zinc oxide (ZnO-NPs). ZnO NPs synthesized were confirmed using spectroscopic, X-ray diffraction and microscopic analysis. The current research utilizes widely used major textile dyes, Reactive Yellow-145 (RY-145), Reactive Red-120 (RR-120), Reactive Blue-220 (RB-220) and Reactive Blue-222A (RB-222A), which are released accidentally or due to the non-availability of cost-effi-cient, dependable and environment-friendly degradation methods, making this work a much-needed one for preventing the discharge before treatment. The biosynthesized ZnO-NPs were top-notch catalysts for the reduction of these dyes, which is witnessed by a gradual decrease in absorbance maximum values. After 320 min, ZnO-NPs under UV light exposure showed 99, 95, 94 and 45% degradations of RY-145, RR-120, RB-220 and RB-222A dyes, respectively. The phytotoxicity study conducted at two trophic levels revealed that the A. stelleriana-mediated ZnO-NPs have great potential for the degradation of textile dyes, allowing them to be scaled up to large-scale treatments. 2023 The Authors. -
A modified approach for extraction and association of triplets
In this paper we present an enhanced algorithm with modified approach to extricate various Triplets i.e. subject-predicate-object from Natural language sentences. The Treebank Structure and the Typed Dependencies obtained from Stanford Parser are used to elicit multiple triplets from English Sentences. Typed Dependencies represents grammatical connections among the words of any sentence and represents how triplets are associated. The intended interpretation behind the extraction of Triplets is that the subject is acting on the object in a way described by the predicate. In graphical form it can be considered that subject and object will be acting as nodes i.e. entities and predicate as edges i.e. relationship. The resulting triplets and relations can be useful for building and analysis of a social network graph and for generating communication pattern and Information retrieval. 2015 IEEE. -
Into the Dark World of User Experience: A Cognitive Walkthrough Study
In this age of AI, the unison of man and machine is going to be more prominent than ever, thus creating a need to understand the underlying framework that is adopted by app designers and developers from a psychological point of view. Research on the various benefits and harmful effects of user experience design and furthermore developing interventions and regulations to moderate the use of dark strategies in digital tools is the need of the hour. This paper calls for an ethical consideration of designing the experience of users by looking at the unethical practices that exist currently. The purpose of the study was to understand the cognitive, behavioural and affective experience of dark patterns in end users. There is a scarcity in the scientific literature with regard to dark patterns. This paper adopts the methodology of user cognitive walkthrough with 6 participants whose transcripts were analysed using thematic network analyses. The results are presented in the form of a thematic network. A few examples of the themes found are the experience of manipulation in users, rebellious attitudes, and automatic or habitual responses. These findings provide a basis for an in-depth understanding of dark patterns in user experience and provide themes that will help future researchers and designers develop ethical and more enriching user experiences for users. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Synthesis, Characterization of Chromium Oxide Powders and Coatings
The chromium oxide powders are transformed into plasma sprayable particles by using synthetic polymers for agglomeration. In order to carry out the agglomeration process, spray drying technique was employed. This research work highlights the significance of the process variables that control the synthesis of plasma spray powder and consequently, the properties that were suited for plasma sprayoating. Energy Dispersive Spectroscopy (EDS) was used to characterize the elemental composition, while scanning electron microscopy (SEM) was used to analyse the morphology and powder grain sizes and X-ray diffraction (XRD) was used to identify the phase structure. And for the development of coatings on the substrates, Atmospheric plasma spray (APS) technique was used. The plasma sprayable powders were created with the intention of investigating for use as corrosion-resistant coatings. 2023 Trans Tech Publications Ltd, All Rights Reserved. -
The changing role of marketing: Industry 5.0 - the game changer
The preceding revolution, Industry 4.0, surfaced by way of the influx of digital and automation technologies. Industry 5.0 followed the suit and the world is on the threshold of this new evolution. Industry 5.0 attempts to bring together the competency of smart machines and the exceptional ingenious potentials of the human workforce. Industry 5.0 is humanizing the digital and automated systems. It recognizes both automated technology and the human innovative skills on an equal platform. Marketing in its new role revolves on the axis of automation and cyber technology of Industry 5.0. This new makeover of marketing processes generates superior marketing actions, restructures marketing workflows, and assesses the results of marketing promotions. Industry 5.0 tools make available a fundamental marketing catalog for all marketing content and communications, thus assisting marketers to fashion a fragmented, customized, and favorable marketing experiences for prospective buyers. These systems and spaces offer automation attributes across numerous phases of marketing including videos, blogs, emails, social media, lead generation, direct mails, digital advertising, and more. This chapter aims to introduce the concept of Industry 5.0, where robots and machines are interweaved with the human intellect and labor as teammate instead of opponent. The objective of the chapter is to examine and explore the different facets of marketing in the face of Industry 5.0. The chapter describes the challenges and future trends and practices in marketing field in the wake of Industry 5.0 as the way forward for the companies for sustainability and resilience. 2023 by Sunanda Vincent Jaiwant. All rights reserved. -
3Rs management: Advances and innovations in waste management and treatment
The increasing industrialisation and fast growth do not only pose problems related to the allocation of resources and powers, but also severely challenge the natural environment. Environmental degradation such as contaminated water, sinking groundwater levels, unhealthy soils, and polluted air has become a harsh reality in many parts of the world. One result of a rapid urbanisation, a slowly reducing gap between urban and rural, changing consumption patterns, and a growing population is the problem of waste. However, although it is the duty of the urban local bodies (ULBs) to address the issue of waste, tight budgets, inefficient organisation, has rendered a situation that has little hope for alleviation in the near future. This chapter aims to understand the concept of waste management through 3Rs. The focus is to identify the contemporary 3Rs practices and also develop advanced strategies for the same. 2024 by IGI Global. -
Smart City Governance and Citizen Engagement
The smart city idea has been put into practice in numerous nations as a response to urban issues. With the ultimate goal of improving quality of life and well-being, smart cities are more and more eager to engage in fruitful dialogue with their residents, better understand their demands, and develop digital platforms for inciting collaborative initiatives between authorities and people. Prior researches have noted challenges with execution and the importance of smart citizens as key components of a smart city. Using an internet-based social platform, this project intends to learn more about how smart cities are implemented and how citizens are involved. Smart city development should be modified to account for local conditions. Local expertise, transformative leadership, sustainability, and political content are the key success criteria for the implementation. Through an online social network, city residents have been participating in the implementation of the smart city. In order to make sure that city citizens are motivated to address the citys challenges, a sort of incentive structure remains necessary. Previous research efforts were conducted in an effort to measure the projects effectiveness by achieving benefits. The people of that country are the end users of public infrastructure projects. Nevertheless, communities all throughout the world have struggled to achieve genuine citizen engagement. This component of citizen engagement has been highlighted as a crucial goal to be accomplished. This chapter examines the role of AI in citizen engagement and participation in the smart city implementation. The chapter also intends to analyse the relevant research works to examine the trends in smart city governance and AI. This study will provide also insights into emerging issues and challenges. 2025 selection and editorial matter Pawan Whig, Pavika Sharma, Nagender Aneja, Ahmed A. Elngar and Nuno Silva; individual chapters, the contributors. -
Servant leadership and diversity: A focus on ethnic and cultural diversity
Business organizations becoming global is nothing new in the current world due to the ever-shrinking physical and communication boundaries. Going global has its benefits and limitations. Benefits would be less expensive land, labor, and resources and reduced transportation cost by being present in countries with vast requirements for an organization's products or services. At the same time, the limitations would be to manage people or lead them toward shared organizational goals. India being a country with enormous opportunities has diverse cultures and practices. Thus, leading various people as employees would be a challenge. What may work in the Western countries may not work in India due to its vast diversity in culture, language, and ethnicity. This research aims to understand the servant leadership approach and if it would be applicable in India. In the context of diverse cultures, the authors analyze the servant leader's role in an organization and compare the practices of servant leadership in various other countries. 2023 by IGI Global. All rights reserved.