Browse Items (11810 total)
Sort by:
-
ENVIRONMENTAL JURISPRUDENCE IN INDIA: A JOURNEY TOWARDS ATTAINING ECO-CENTRIC IDEALS
Environmental Law has had a long, arduous journey in India, but has been able to keep up with the many changes that have taken place, around the globe, and has helped shape India's environmental legal regime. By tracing the growth of environmental law, through different ages, and by highlighting some of those factors, which have contributed immensely to its growth, the idea is to identify certain false grounds and figure out ways to make environmental law more effective. By looking at it through a sociocultural lens, the aim is to examine as to whether culture, tradition and rituals can be imbibed into law or given a legal recognition, and thereby giving more power to law. The development of Earth Jurisprudence principles and the way in which it is sought to be imbibed in India and the challenges that it faces too are discussed. 2022 Universitat Rovira i Virgili. All right reserved. -
Behavioural drivers of access-based consumption among millennial and generation Z in India
The world of consumerism is very dynamic, and technology driven changes in the field of consumerism are unavoidable especially among new generation customers millennial and generation Z. The customers, especially in urban areas, gradually move from ownership-based consumption to access-based consumption. The purpose of this study is to explore the behavioural drivers of new generation customers towards access-based consumption. The study is descriptive in nature and employed a survey method for data collection. The drivers identified are tested through a quantitative study and the primary data are collected using online questionnaires. The study has also analysed the impact of behavioural drivers on current usage of access-based consumption as well as on willingness to use access-based consumption in the future. The study has found that sustainability is the only driver that significantly motivates access-based consumption in Indian urban areas. Copyright 2022 Inderscience Enterprises Ltd. -
Role of Need for Achievement on Decision making and Life Orientation of Young Adults
Purpose-To assess the role of need for achievement on decision making and life orientation of young adults. Design/methodology/approach-The data was collected from the participants using a questionnaire. The sample size is 100 young adults. The sampling technique used is convenience sampling, and the research design is a cross-sectional survey. It was hypothesised that individuals high in achievement motivation will also be high in life orientation level and there will be a positive correlation between achievement motivation and decision making. Findings The results of the study indicate that an individual high in achievement motivation will also be high in life orientation level and a positive correlation is found between achievement motivation and decision making. The other findings are that optimising decision-making styles is positively correlated with achievement motivation and a significant difference in achievement motivation between males and females is found, indicating a higher need for achievement in females as compared to males. Social Implications-The findings of the study are considerable with respect to the personal, professional, and educational development of young adults. As the research suggests, there is a positive relationship between decision-making styles, achievement motivation, and orientation towards life. Therefore, various decision-making styles can be introduced in the behavioural sciences subject domain. Higher achievement needs in females indicate their potential in various professional realms, and such platforms, if provided, can increase women's participation in the workforce, resulting in economic, social, and personal development for women as well as society. Originality/ Value The youth of a country are its greatest assets, and for an aspirational country, there is a need for a highly motivated task force. The research topic focuses on how motivated behaviour occupies a central position in personality and its relationship with decision-making style and orientation towards life. This study focuses on the need of the hour, which is harnessing our youth and exploring more about the achievement-oriented behaviour and optimistic outlook of young adults, which is the demographic dividend of the country. 2022 RESTORATIVE JUSTICE FOR ALL. -
Automated Risk Management Based Software Security Vulnerabilities Management
An automated risk assessment approach is explored in this work. The focus is to optimize the conventional threat modeling approach to explore software system vulnerabilities. Data produced in the software development processes are better leveraged using Machine Learning approaches. A large amount of industry knowledge around security vulnerabilities can be leveraged to enhance current threat modeling approaches. Work done here is in the ecosystem of software development processes that use Agile methodology. Insurance business domain data are explored as a target for this study. The focus is to enhance the traditional threat modeling approach with a better quantitative approach and reduce the biases introduced by the people who are part of software development processes. This effort will help bridge multiple data sources prevalent across the software development ecosystem. Bringing these various data sources together will assist in understanding patterns associated with security aspects of the software systems. This perspective further helps to understand and devise better controls. Approaches explored so far have considered individual areas of software development and their influence on improving security. There is a need to build an integrated approach for a total security solution for the software systems. A wide variety of machine learning approaches and ensemble approaches will be explored. The insurance business domain is considered for the research here. CWE (Common Weaknesses Enumeration) mapping from industry knowledge are leveraged to validate the security needs from the industry perspective. This combination of industry and company data will help get a holistic picture of the software system's security. Combining the industry and company data helps lay down the path for an integrated security management system in software development. The risk management framework with the quantitative threat modeling process is the work's uniqueness. This work contributes toward making the software systems secure and robust with time. 2013 IEEE. -
A Sampling-Based Stack Framework for Imbalanced Learning in Churn Prediction
Churn prediction is gaining popularity in the research community as a powerful paradigm that supports data-driven operational decisions. Datasets related to churn prediction are often skewed with imbalanced class distribution. Data-level solutions, like over-sampling and under-sampling, have been commonly used by researchers to address this problem. There are limited number of case studies that attempt to evolve these data-level solutions by integrating them with computationally advanced frameworks, like ensembles. Ensembles primarily employ algorithmic diversity using a fixed set of training instances to achieve superior performance. This study aims to introduce algorithmic diversity in ensembles by modifying the fixed set of training instances using diverse sampling strategies to increase predictive performance in imbalanced learning. Data is acquired from the world's largest open hotel commerce platform company. A four-part series of experiments is conducted to analyze the effectiveness of sampling techniques and ensemble solutions on model performance. A new sampling-based stack framework called 'Stacking of Samplers for Imbalanced Learning' is proposed. The framework combines the prediction capabilities of sampling solutions to stimulate the information gain of the meta features in ensemble. It is observed that the proposed framework leads to improvement in model performance with AUC of 86.4% and top-decile lift of 4.7 for customers of the hotel technology provider. Additionally, results show that the framework records a higher information gain for meta features used in a stack, compared to commonly used stack frameworks. 2013 IEEE. -
LGBTQIA+ rights, mental health systems, and curative violence in India
This commentary examines the spaceattitudeadministrative complex of mainstream mental health systems with regard to its responses to decriminalisation of nonheteronormative sexual identities. Even though the Supreme Court, in its 2018 order, instructed governments to disseminate its judgment widely, there has been no such attempt till date. None of the governmentrun mental health institutions has initiated an LGBTQIA+ rights-based awareness campaign on the judgment, considering that lack of awareness about sexualities in itself remains a critical factor for a noninclusive environment that forces queer individuals to end their lives. That the State did not come up with any awareness campaign as mandated in the landmark judgment reflects an attitude of queerphobia in the State. Drawing on the concept of biocommunicability, analysing the public interfaces of staterun mental health institutions, and the responses of mental health systems to the death by suicide of a queer student, I illustrate how mental health institutions function to further antiLGBTQIA+ sentiments of the state by churning out customerpatients out of structural violence and systemic inequalities, benefitting the mental health economy at the cost of queer citizens on whom curative violence is practised. Indian Journal of Medical Ethics 2022. -
A privatised approach in enhanced spam filtering techniques using TSAS over cloud networks
Major problem over cloud networks is the effect of malicious code that protrudes its own activity without intend of network user in resource sharing. One such activity is the spam-filtering techniques which assumes the data with training and testing sets and also rely on fundamental classification through distribution. A privatised spam filtering approach is a classic problem which automatically recognises user context and incoming mail information relevance. To filter mail contents learning based methods, probabilistic based method trying to improve their accuracy but they cannot attain an improvement in identifying suspicious contents and also in segregating legitimate mail entries. Here a novel representation of structured abstraction scheme (SAS) used to generate abstraction in e-mail process using HTML tag content in e-mail and its algorithm for filtering such process of spam filtering is depicted. In this SAS methodology near duplicate matching process with HTML tag ordering will be processed and newly assigned position ordering were deliberated. The experimental setup shows that there will be a great improvement while filtering spam in accuracy of e-mail content while sharing in cloud networks. Copyright 2022 Inderscience Enterprises Ltd. -
Multi-layer Stacking-based Emotion Recognition using Data Fusion Strategy
Electroencephalography (EEG), or brain waves, is a commonly utilized bio signal in emotion detection because it has been discovered that the data recorded from the brain seems to have a connection between motions and physiological effects. This paper is based on the feature selection strategy by using the data fusion technique from the same source of EEG Brainwave Dataset for Classification. The multi-layer Stacking Classifier with two different layers of machine learning techniques was introduced in this approach to concurrently learn the feature and distinguish the emotion of pure EEG signals states in positive, neutral and negative states. First layer of stacking includes the support vector classifier and Random Forest, and the second layer of stacking includes multilayer perceptron and Nu-support vector classifiers. Features are selected based on a Linear Regression based correlation coefficient (LR-CC) score with a different range like n1, n2,n3,n4 a, for d1 used n1 and n2 dataset,for d2 dataset, combined dataset of n3 and n4 are used and developed a new dataset d3 which is the combination of d1 and d2 by using the feature selection strategy which results in 997 features out of 2548 features of the EEG Brainwave dataset with a classification accuracy of emotion recognition 98.75%, which is comparable to many state-of-the-art techniques. It has been established some scientific groundwork for using data fusion strategy in emotion recognition. 2022. International Journal of Advanced Computer Science and Applications. All Rights Reserved. -
Aquila Optimizer Based Optimal Allocation of Soft Open Points for Multi-Objective Operation in Electric Vehicles Integrated Active Distribution Networks
The appropriate position and sizing of soft open points (SOPs) for reducing the detrimental impact of electric vehicle (EV) load penetration and renewable energy (RE) variation on active distribution networks (ADNs) are provided in this study. Soft open points (SOPs) have been used to create a multi-objective framework that considers loss minimization and voltage profile enhancement. The non-linear multi-variable complicated SOP allocation problem is solved for the first time using a modern meta-heuristic Aquila optimizer (AO). The modified IEEE 33-bus benchmark and IEEE 69-bus ADNs are used in the simulations. Before SOPs, the average real power loss in IEEE 33-bus AND was 370.329 kW, but after SOPs, it was reduced to 259.356 kW (i.e., 29.96 percent reduction). Similarly, effective SOPs integration in the IEEE 69-bus resulted in a loss reduction of 81.07 percent. AO's computational efficiency is also compared to that of multiobjective particle swarm optimization (MOPSO), particle swarm optimization (PSO), and cuckoo search algorithm (CSA). The AO has produced better results in terms of lower losses, improved voltage profile despite variations in EV load penetration, and RE and load volatility in ADNs, according to the results 2022. International Journal of Intelligent Engineering and Systems.All Rights Reserved -
Secured personal health records using pattern-based verification and two-way polynomial protocol in cloud infrastructure
This present research proposes the digitalised healthcare system that enables patients to generate, aggregate and store in the form of personal health records (PHRs). This requires more attention on cost effectiveness and less response time on public cloud platform. The existing cloud platforms have failed to implement the systemic approach for immediate verification and correction models on increasing PHR datasets. The storage and computation are two prime factors. Moreover, cloud systems need more attention on security and privacy breaches. In this proposed model the publisher-observer pattern-based healthcare systems allow the patients to verify and correct the PHRs before any type of computations. The cloud system acts as a backend framework that offers openness and easy accessibility. The experimental segment ensures the computational cost and response time for multiple polynomial PHR variations. The details evaluation also ensures the security and privacy preservation on sensitive healthcare datasets. Copyright 2022 Inderscience Enterprises Ltd. -
Facile synthesis of novel SrO 0.5:MnO 0.5 bimetallic oxide nanostructure as a high-performance electrode material for supercapacitors
Perovskite bimetallic oxides as electrode material blends can be an appropriate method to enhance the supercapacitor properties. In the present research, SrO 0.5:MnO 0.5 nanostructures (NS) were synthesized by a facile co-precipitation method and calcinated at 750800C. Crystal structure of SrO 0.5:MnO 0.5 NS were characterized by X-ray diffraction, surface chemical composition and chemical bond analysis, and dispersion of SrO into MnO was confirmed by X-ray photoelectron spectral studies. Structural morphology was analyzed from scanning electron microscopy. Optical properties of SrO 0.5:MnO 0.5 NS were studied using UV-Visible spectrophotometer and SrO 0.5 and MnO 0.5 NS showed ?75nm grain, ? 64nm grain boundary distance, with two maxima at 261nm and 345nm as intensity of absorption patterns, respectively. The synthesized SrO 0.5:MnO 0.5 NS exhibited high specific capacitance of 392.8F/g at a current density of 0.1A/g. Electrochemical impedance spectroscopy results indicated low resistance and very low time constant of 0.2s ?73% of the capacitance was retained after 1000 galvanostatic charge-discharge (GCD) cycles. These findings indicate that SrO 0.5:MnO 0.5 bimetallic oxide material could be a promising electrode material for electrochemical energy storage systems. The Author(s) 2022. -
Psychometric Properties of the Interpersonal Emotion Regulation Questionnaire Among Couples in India
The aim of the present study was to translate the Interpersonal Emotion Regulation Questionnaire (IERQ) into the Tamil language and examine its psychometric properties in the Indian cultural context. Data were collected from a dyadic sample of 340 married heterosexual couples (N = 680) currently residing in India. The mean age of husbands was 39.57 (SD = 6.10; 26 ? range ? 58), and the wives was 35.33 (SD = 5.72; 23 ? range ? 54). Descriptive results indicated that husbands and wives reported similar levels of interpersonal emotion regulation. Confirmatory factor analysis showed a 20-item model with four factorsenhancing positive affect, perspective-taking, soothing and social modeling, similar to the original version, fits the data well. Furthermore, the multiple-group analysis indicated robust measurement invariance across gender (husbands vs. wives), family type ( joint vs. nuclear) and marriage type (arranged vs. love), indicating that the Tamil version of the IERQ operates similarly across these groups. Besides, the Tamil version of the IERQ showed good convergent and discriminant validity with measures of dyadic coping and relationship satisfaction. Implications for research and couples therapy in the Indian cultural context are discussed. 2022, PsychOpen. All rights reserved. -
Theoretical Study of Convective Heat Transfer in Ternary Nanofluid Flowing past a Stretching Sheet
A new theoretical tri-hybrid nanofluid model for enhancing the heat transfer is presented in this article. This model explains the method to obtain a better heat conductor than the hybrid nanofluid. The tri-hybrid nanofluid is formed by suspending three types of nanoparticles with different physical and chemical bonds into a base fluid. In this study, the nanoparticles TiO2, Al2O3 and SiO2 are suspended into water thus forming the combination TiO2-SiO2-Al2O3-H2O. This combination helps in decomposing harmful substances, environmental purification and other appliances that requires cooling. The properties of tri-hybrid nanofluid such as Density, Viscosity, Thermal Conductivity, Electrical Conductivity and Specific Heat capacitance are defined mathematically in this article. The system of equations that governs the flow and temperature of the fluid are converted to ordinary differential equations and are solved using RKF-45 method. The results are discussed through graphs and it is observed that the tri-hybrid nanofluid has a better thermal conductivity than the hybrid nanofluid. 2022. Shahid Chamran University of Ahvaz, Ahvaz, Iran. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0 license) (http://creativecommons.org/licenses/by-nc/4.0/). -
A Neuro Fuzzy with Improved GA for Collaborative Spectrum Sensing in CRN
Cognitive Radio Networks (CRN) have recently emerged as an important solution for addressing spectrum constraint and meeting the stringent criteria of future wireless communication. Collaborative spectrum sensing is incorporated in CRNs for proper channel selection since spectrum sensing is a critical capability of CRNs. According to this viewpoint, this study introduces a new Adaptive Neuro Fuzzy logic with Improved Genetic Algorithm based Channel Selection (ANFIGA-CS) technique for collaborative spectrum sensing in CRN. The suggested methods purpose is to find the best transmission channel. To reduce spectrum sensing error, the suggested ANFIGA-CS model employs a clustering technique. The Adaptive Neuro Fuzzy Logic (ANFL) technique is then used to calculate the channel weight value and the channel with the highest weight is selected for transmission. To compute the channel weight, the proposed ANFIGA-CS model uses three fuzzy input parameters: Primary User (PU) utilization, Cognitive Radio (CR) count and channel capacity. To improve the channel selection process in CRN, the rules in the ANFL scheme are optimized using an updated genetic algorithm to increase overall efficiency. The suggested ANFIGA-CS model is simulated using the NS2 simulator and the results are investigated in terms of average interference ratio, spectrum opportunity utilization, average throughput, Packet Delivery Ratio (PDR) and End to End (ETE) delay in a network with a variable number of CRs. 2022, Tech Science Press. All rights reserved. -
Stock Market Efficiency and COVID-19 with Multiple Structural Breaks: Evidence from India
The objective of the study is to investigate the influence of the coronavirus pandemic (endogenous crisis) on the stock market efficiency of India during the multiple break periods. The empirical analysis is performed using conditional heteroscedasticity and a small sample robust wild bootstrap automatic variance ratio test and automatic portmanteau test on a daily stock return data of two benchmark indices, that is, NIFTY and SENSEX. The empirical results demonstrate that the stock return of two indices deviates from market efficiency during some periods of the analysis, notably during the nationwide lockdown and peak periods of coronavirus cases in India. These findings indicate that changing stock market behaviour becomes more speculative and earns abnormal profits. To the best of the authors knowledge, this study provides the first evidence of investigating the variations in the stock market efficiency of India in response to this endogenous crisis. 2022 International Management Institute, New Delhi. -
Deep fake detection using cascaded deep sparse auto-encoder for effective feature selection
In the recent research era, artificial intelligence techniques have been used for computer vision, big data analysis, and detection systems. The development of these advanced technologies has also increased security and privacy issues. One kind of this issue is Deepfakes which is the combined word of deep learning and fake. DeepFake refers to the formation of a fake image or video using artificial intelligence approaches which are created for political abuse, fake data transfer, and pornography. This paper has developed a Deepfake detection method by examining the computer vision features of the digital content. The computer vision features based on the frame change are extracted using a proposed deep learning model called the Cascaded Deep Sparse Auto Encoder (CDSAE) trained by temporal CNN. The detection process is performed using a Deep Neural Network (DNN) to classify the deep fake image/video from the real image/video. The proposed model is implemented using Face2Face, FaceSwap, and DFDC datasets which have secured an improved detection rate when compared to the traditional deep fake detection approaches. 2022. Balasubramanian et al. -
Antenna Array Miniaturization using a Defected Ground Structure
A novel Defected Ground Structure (DGS) is proposed to miniaturize a 2 Modified Corporate Feed Planar Antenna Array (M-CFPA) with a modified corporate feeding network. The DGS altered the surface current distribution and shifted the resonance frequency to the lower side. After running a parametric sweep of length and width of the patch antenna element, achieved the miniaturized antenna array resonating at 2.4 GHz frequency. The proposed antenna array is designed using Rogers/RT Duroid 5,880 (2.2) substrate with a thickness of 1.6 mm. The overall dimensions of the proposed Planar Array with DGS (PA-DGS) is 25.2723 % lesser than M-CFPA. The M-CFPA has a peak gain of 11.53 dB with a-10 dB reflection coefficient bandwidth of 118 MHz. The proposed PA-DGS array exhibits a peak gain of 9.51 dB with 100 MHz-10 dB bandwidth. 2022, Walailak University. All rights reserved. -
Optimization and Design of a Sustainable Industrial Grid System
Electricity is a multifaceted form of energy and is used globally, with a continuously growing demand. Electrical power grids are there for more than 150 years. The generated electrical power is delivered to different industrial, commercial, and residential sectors, thereby fulfilling the ever-growing demand. In this research paper, the design and optimization of an industrial grid for various electrical loads is discussed. The electrical grid ensures a stable power supply to the loads by providing quality power with the minimum total harmonic distortion (THD) possible. A complete study of the short circuit current has been done in two different electrical grid systems, as it is seen that the short circuit current depends on the impedance of the transformer which feeds the load. These two designs of a single diagram will be simulated by using a power system analyzer, the Electrical Transient Analyzer Program (ETAP) software. The different electrical parameters, like choosing the optimised rated generator, cables, and transformers, are done. Load flow analysis is performed on both the design to evaluate the THD, short circuit fault, as well as to choose the right protection circuit for the system. 2022 Samat Iderus et al. -
The merging odyssey of trade, investment and partnership: a linkage model of India and Korea interactions
With the rising presence of India as a global power and Korea as an advanced economy, the collaborative alliance between two nations is of growing research interest. India and Korea are vastly different in terms of demographics, cultural traditions and historical experiences. However, they are unusually compatible for their shared vision and amazingly comparable in their unique positions in the dynamic world that involves strong coordinating linkage mechanisms and constructive influences. This paper aims to examine how India and Korea come to forge strategic alliance both in business relationships and national interests. We briefly review the history of interactions between India and Korea and define a unique model of linkage roles. After discussing network theory of interactions in liberal international order, propositions explain step by step how India and Korea merge to create better future for countless people through trade, investment, and partnerships. Growth stages of global firms for domestic advantage and global competitiveness are presented as well. Managerial implications and future research issues are discussed. Copyright 2022 Inderscience Enterprises Ltd. -
Investigation of fluorescence enhancement and antibacterial properties of nitrogen-doped carbonized polymer nanomaterials (N-CPNs)
Carbonized Polymer Nanomaterials (CPNs) have acquired substantial research interest in recent years due to their budding applications in various optical and electrochemical studies like electrocatalysis, solar cells, biosensing, etc. Due to their stability and toxicity, the enhancement of CPNs' properties was the primary cause of concern. Herein, we synthesized Nitrogen-doped (N-doped) N-CPNs using the one-step hydrothermal approach of PVA and PVDF polymers with Nitric acid (HNO3) as the nitrogen source. The luminescence intensity was observed to be enhanced by increasing nitrogen doping concentration. The synthesized fluorescent samples exhibited significant antibacterial properties, making them useful in biomarkers, sensing strategies, drug delivery, etc. Doped PVA samples exhibited negligible antibacterial activity, but nitrogen-doped PVDF samples displayed considerable biocidal activity against gram-positive bacteria, according to antibacterial research. Each sample's growth inhibition was distinct and species-specific. 2022 Taylor & Francis Group, LLC.