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Diagnose Diabetic Mellitus Illness Based on IoT Smart Architecture
Obtaining a quick remote diagnosis of heart disease has proven problematic in recent days. To overcome such issues in e-Healthcare systems, Internet of Things (IoT) applications have been deployed using cloud computing (CC) approaches. There are still a number of disadvantages to using CC, including latency, bandwidth, energy usage, and security and privacy concerns. Fog computing (FC), a CC development, may be able to overcome these obstacles. DiaFog enabling remote users for real-time diagnosis of diabetic mellitus disease (DMD) has been proposed in this study, which is based on the combined ideas of IoT, cloud, and fog computing, as well as an ensemble deep learning (EDL) technique. The proposed system is trained with EDL approaches on the integrated dataset of two diabetes mellitus disease datasets (DMDDs), namely, Pima Indians Diabetes Dataset (PIDD) and Hospital Frankfurt Germany Diabetes Dataset (HFGDD), obtained from the UCI-ML and Kaggle repository, respectively, and the integrated dataset of these two. The suggested system has been used to demonstrate accuracy, precision, recall, F-measure, latency, arbitration time, jitter, processing time, throughput, energy consumption, bandwidth utilization, network utilization, scalability, and more. In the remote instantaneous diagnosis of diabetic patients, the integration of IoT-fog-cloud is useful. The results of the trials show the value of employing FC principles and their applicability for speedy diabetic patient remote diagnosis. PACS-key is describing text of that key PACS-key describing text of that key. 2022 Abhilash Pati et al. -
The challenge of gender stereotyping in Indian courts
Womens negotiations towards achieving justice are elusive due to patriarchal, cultural and caste norms. The expectation of compromise permeates Courts, even in rape cases. In spite of the prevalence of well-formulated substantive and procedural aspects of law, the constitutional promise of equality is still a distant dream for women. Intersectional factors like tradition, caste, religion and cultureall act as impediments to securing justice for women in India. In fact, gender bias plagues the criminal justice administration. This paper relies on landmark cases to demonstrate the biases exhibited by Courts, in matters of sexual assault and rape. The paper will also rely on feminist ideas to highlight the need for the law to understand the deep-rooted historical and socio-political contexts from which issues related to gender originate. The paper concludes by giving suggestions as to how gender bias can be done away with, by Courts. Law has to act as a transformative instrument if gender justice has to be achieved. Lawyers and judges should not be carried away by personal biases and prejudices and need to be socially sensitive while handling cases of crimes against women. 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Fate of AI for Smart City Services in India: A Qualitative Study
With the rollout of the smart city initiative in India, this study explores potential risks and opportunities in adopting artificial intelligence (AI) for citizen services. The study deploys expert interview technique, and the data collected from various sources are analyzed using qualitative analysis. It was found that AI implementation needs a critical examination of various socio-technological factors to avoid any undesirable impacts on citizens. Fairness, accountability, transparency, and ethics (FATE) play an important role during the design and execution of AI-based systems. This study provides vital insights into AI implications to smart city managers, citizen groups, and policymakers while delivering promised smart city experience. The study has social implications in terms of ensuring that proper guidelines are developed for using AI technology for citizen services, thereby bridging the ever-critical trust gap between citizens and city administration. Copyright 2022, IGI Global. -
Physical Abuse in the Absence of Ubuntu
Students in Africa and worldwide should learn about Ubuntu at the school, secondary school, college, and university levels. It should be incorporated into the educational process. Tobacco-free days, alcohol-free (dry days), and drug-free days could all be ways to commemorate Ubuntu. Female smokers are at a higher risk than male smokers. Following such measures may aid in raising awareness. Legislators in Africa need to employ incentives to amend legislation to fully integrate Ubuntu into society. It is possible to prevent violence against women and children by instilling Ubuntu principles in the community and society. It is sufficient to refer to the existing Ubuntu documentation to design and validate the necessary training programme. Still, in the case of Ubuntu, more experimental research should be encouraged. Such research must be funded by both the government and the private sector. Even though Ubuntu started in Africa, it can be globalized. Nevertheless, Ubuntu has not been adopted to its full potential in the current situation. The Zulu people of South Africa is well-known for its kindness and hospitality, and it is to them that we owe the concept of Ubuntu. According to Ubuntu, we are people not because of who we are but because of how we connect with other people. This implies that relationships are essential. With over three thousand diverse African tribes, diversity management is critical, and Ubuntu can be a driving force in bringing all the diversity under one umbrella. There are cultural mechanisms in all African traditions and events that exist to unite, but this aspect of unity is within the community, and Ubuntu can be implemented to lead the same element of harmony with various communities. There are ways to integrate Ubuntu as a cultural event into the calendar, bringing together diverse African communities as one force, culture, nation, and identity. Regardless of the level of diversity, the most important thing is to include everyone and give them the recognition they deserve. 2022. Journal of International Womens Studies -
A Modified Seven-Level Inverter with Inverted Sine Wave Carrier for PWM Control
The conventional multilevel inverter necessitates more active switching devices and high dc-link voltages. To minimalize the employment of switching devices and dc-link voltages, a novel topology has been proposed. In this paper, a novel minimum switch multilevel inverter is established using six switches and two dc-link voltages in the proportion of 1: 2. In addition, the proposed topology is proficient in making seven-level voltages by appropriate gate signals. The PWM signals were produced using several inverted sine carriers and a single trapezoidal reference. When compared to other existing inverters, this configuration needs fewer components, as well as fewer gate drives. Furthermore, this module can generate a negative level without the use of a supplementary circuit such as an H-Bridge. As a result, overall cost and complexity are greatly reduced. The proposed minimum switch multilevel inverter operation is validated through simulations followed by experimental results of a prototype. 2022 Arun Vijayakumar et al. -
INDUCED nK2 DECOMPOSITION OF INFINITE SQUARE GRIDS AND INFINITE HEXAGONAL GRIDS
The induced nK2 decomposition of infinite square grids and hexagonal grids are described here. We use the multi-level distance edge labeling as an effective technique in the decomposition of square grids. If the edges are adjacent, then their color difference is at least 2 and if they are separated by exactly a single edge, then their colors must be distinct. Only non-negative integers are used for labeling. The proposed partitioning technique per the edge labels to get the induced nK2 decomposition of the ladder graph is the square grid and the hexagonal grid. 2022, Krasovskii Institute of Mathematics and Mechanics. All rights reserved. -
Micro Borrowing an Amalgam of Structure and Strategy: Evidence from India
Micro borrowing was either an outcome of structure in the credit environment (termed the outreach stream), or a strategic response of the borrowers (termed the sustainability stream). Furthermore, borrower personal effects drove borrowing behaviour. This study draws variables from both the streams of literature and tests them against the amount borrowed and purposes loans are borrowed for. Results show how borrowing behaviour is neither an outcome of pure structure nor pure strategy, but rather, is an interplay of both, and further influenced by personal effects. The survey data (consisting of 839 rural borrower responses, from four districts of erstwhile Andhra Pradesh in South India) was subjected to a rigorous statistical analysis. Results show how a larger number of banks in the villages (a structural constraint), enabled the borrowers to receive larger loans, who defaulted more (a strategic response). Men borrowed larger sums (a personal effect). A similar amalgam of structure, strategy and personal effects drive borrowing behaviour even after controlling for loan purpose and district fixed effects. Yet, when district effects are introduced, amount borrowed is agnostic to personal effects, and is driven purely by structure and strategy. JEL Classifications: C25, C83, G51, Z13 2022 SAGE Publications India Pvt. Ltd. -
GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force
Walking (gait) irregularities and abnormalities are predictors and symptoms of disorder and disability. In the past, elaborate video (camera-based) systems, pressure mats, or a mix of the two has been used in clinical settings to monitor and evaluate gait. This article presents an artificial intelligence-based comprehensive investigation of ground reaction force (GRF) pattern to classify the healthy control and gait disorders using the large-scale ground reaction force. The used dataset comprised GRF measurements from different patients. The article includes machine learning- and deep learning-based models to classify healthy and gait disorder patients using ground reaction force. A deep learning-based architecture GaitRec-Net is proposed for this classification. The classification results were evaluated using various metrics, and each experiment was analysed using a fivefold cross-validation approach. Compared to machine learning classifiers, the proposed deep learning model is found better for feature extraction resulting in high accuracy of classification. As a result, the proposed framework presents a promising step in the direction of automatic categorization of abnormal gait pattern. 2022 Chandrasen Pandey et al. -
Influence of teacher occupational stress on self-efficacy: Evidences from the pre-and during-covid-19 periods
The teaching profession is undergoing a revolutionary change due to the compulsive integration of technology into education. There is a growing interest in understanding teachers occupational stress and efficacy in online teaching. The participants of this study were schoolteachers in Bengaluru, India. The measures from teachers occupational stress and self-efficacy scales investigate the influence of occupational stress and self-efficacy during two periods before and during COVID-19. The findings of the study reflected that the influence of occupational stress on self-efficacy doubled during COVID-19. Classroom management and resources for online teaching mainly influenced selfefficacy during COVID-19, whereas classroom management and administration proved to influence self-efficacy before COVID-19. Online learning strategies adopted by educational institutions will certainly make an impression on the education system post COVID-19. The current research contributes a significant component in the formation of teacher professional identity. 2022 IGI Global. All rights reserved. -
Impact of social media conversations on consumers online purchase intention
The objective of this paper is to explain how social media has impacted the consumer decision process as heavy use of social media has created a new landscape which lays out a new avenue for personal connections. The paper also explores how individuals are seeking information on social media and how they are processing and selecting the information before making the final purchase. The empirical data for the study has been gathered using a structured questionnaire. The descriptive statistics were performed for the select parameters of the survey instrument. The findings confirm that there is significant variance between age, income, occupation, and gender with online purchase intention of consumers. Also, the results confirm that social conversation is a significant predictor of online purchase intentions. The research findings suggest that consumers in India are actively utilising social media platforms as a key tool in validating their purchase decision. The research also explains various indicators that can be utilised by potential companies to analyse the decision-making process via social media sites. 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. -
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. -
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. -
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. -
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. -
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. -
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. -
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/). -
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. -
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.