Browse Items (11855 total)
Sort by:
-
THE BELT AND ROAD INITIATIVE: DYNAMICS FOR LATIN AMERICA AND THE CARIBBEAN REGION
The Belt and Road Initiative (BRI) is increasingly turning out to become a global endeavor and has recently been extended to Latin America and the Caribbean (LAC) region. The diversity in the makeup of the nation-states in the region poses several challenges concerning the regions association with the BRI. For instance, Venezuela has borrowed heavily from China while being mired in economic troubles. The Venezuelan example serves as a caution to others as well as China on the intricacies of debt management and lending. This paper aims to study the challenges and risks arising from the Belt and Road Initiative extending to Latin America and the Caribbean region. This paper also tries to analyze as to whether a win-win outcome can be achieved for both China and the LAC nation-states and as to what China seeks from the region. An attempt has been made to evaluate the role that the global environment might play in this evolving relationship between China and the LAC nation-states. The paper also analyzes the post pandemic BRI investment in the LAC region 2022, Austral: Brazilian Journal of Strategy and International Relations.All Rights Reserved. -
Machine Learning and Artificial Intelligence Techniques for Detecting Driver Drowsiness
The number of automobiles on the road grows in lock-step with the advancement of vehicle manufacturing. Road accidents appear to be on the rise, owing to this growing proliferation of vehicles. Accidents frequently occur in our daily lives, and are the top ten causes of mortality from injuries globally. It is now an important component of the worldwide public health burden. Every year, an estimated 1.2 million people are killed in car ac-cidents. Driver drowsiness and weariness are major con-tributors to traffic accidents this study relies on computer software and photographs, as well as a Convolutional Neural Network (CNN), to assess whether a motorist is tired. The Driver Drowsiness System is built on the Multi-Layer Feed-Forward Network concept CNN was created using around 7,000 photos of eyes in both sleepiness and non-drowsiness phases with various face layouts. These photos were divided into two datasets: training (80% of the images) and testing (20% of the images). For training purposes, the pictures in the training dataset are fed into the network. To decrease information loss as much as feasible, backpropagation techniques and optimizers are applied. We developed an algorithm to calculate ROI as well as track and evaluate motor and visual impacts. 2022, Industrial Research Institute for Automation and Measurements. All rights reserved. -
Can mobile banking apps usage contribute towards the environmental sustainability: a mediation analysis
In digital transformation, digital finance has emerged as an alternative to conventional financial services. Currently, digital financial aspects and environmental sustainability are urgent issues receiving research attention for environmental mitigation. This empirical research addresses digital finance on environmental sustainability through mobile banking app usage. It is among the convenient digital financial technologies developed in recent years for the benefit of various stakeholders. The current model integrated UTAUT2 with perceived security and environmental sustainability. The partial least square structural equation modelling was used to test the hypothesis and other statistical power. This paper provides sustainable perspectives encouraging the Indian tribals to adopt digital technology in financial transactions. The findings have several important policy implications for developing countries, particularly vulnerable populace and those settled in remote areas. This research confirms the positive relations of mobile banking app usage on environmental sustainability through a cross-sectional approach. Copyright 2022 Inderscience Enterprises Ltd. -
Correlation Between Evaluative Beliefs of Patients, Reminder and Medication Adherence
Patients often fail to comply with the instructions given by their physicians. They miss the timing, forget, neglect, or procrastinate taking their medication. This deteriorates the health and causes financial burden to the patient and family. Reminders have been successfully used in many phases of day-to-day activities, increasing the efficiency and productivity. This paper tries to identify the relationship between reminder and the perception of importance of medication based on 15 different factors. These factors have been further assessed to find their relationship with adherence of medication. Hence, with a two-way approach, the studies use exploratory factor analysis method to identify the latent factors, and these latent factors have been used to find the correlation between reminder and adherence through confirmatory factor analysis. It was found that there is positive and significant correlation between reminder and the latent factors and also between the latent factors and adherence. 2022 IGI Global. All rights reserved. -
Impact of COVID-19 Pandemic on Beach Tourism in India
COVID-19 Pandemic has a profound Impact on the Indian tourism sector, especially on beach tourism. Research shows significant changes in the pattern of the ecological terrain of coastal areas and on the community dependent on tourism business and marine life, due to the imposition of lockdown for several months. The paper discusses the change in behavioral patterns of people during Pre and Post COVID-19 for visiting any beach destination in near future in terms of preferences in accommodation, selection of beaches based on crowd and other factors that will be considered in post pandemic days. This study brings out various key indicators shaping the pattern of beach holidays in the future based on the survey conducted among tourists belonging to youth population. The survey considered the tourists preferences of visits and factors they would look upon to choose beach holidaying in the Post COVID-19 years. The influence of the pandemic on quality of beaches, visitorswillingness to visit beaches in future, Post Pandemic opportunities and strategies of destinations for shaping tourism further have also been examined. Copyright IJHTS. -
Using Academic Performance Indicator to Evaluate the Cost to Company of Management Graduates
As the placement season hits CBS Business School, India, the pressure to get placed is at its peak. As the placement season draws to a close, the unplaced students storm the Directors office complaining about unfair treatment in the process. They lay blame on the random shortlisting followed by the Placement co-ordinator. Concerned with these allegations, the Director calls on faculty to investigate the situation. During the conversation one of the students, Rachit, expresses regret in not focusing solely on academics and instead on developing a more well-rounded profile. He feels that that is the reason for his failure to get placed. A fundamental question arises of how closely academic performance and Cost to Company (CTC) are related. Data is collected to examine the validity of the long-held belief that higher academic performance leads to higher paying job placement. 2022 NeilsonJournals Publishing. -
Clustering-Based Recommendation System for Preliminary Disease Detection
The catastrophic outbreak COVID-19 has brought threat to the society and also placed severe stress on the healthcare systems worldwide. Different segments of society are contributing to their best effort to curb the spread of COVID-19. As a part of this contribution, in this research, a clustering-based recommender system is proposed for early detection of COVID-19 based on the symptoms of an individual. For this, the suspected patients symptoms are compared with the patient who has already contracted COVID-19 by computing similarity between symptoms. Based on this, the suspected person is classified into either of the three risk categories: high, medium, and low. This is not a confirmed test but only a mechanism to alert the suspected patient. The accuracy of the algorithm is more than 85%. 2022 IGI Global. All rights reserved. -
Routing Protocol for Low Power and Lossy Network Using Energy Efficient Priority Based Routing
Internet of Thing (IoT) collects huge amount of data from the surrounding by monitoring and sensing. Further, transferring these data from IoT devices to cloud environment seems is very challenging. Such that, this paper concentrates on energy consumption, in which the energy efficient routing and priority dependent techniques are proposed. This technique depends upon the RPL network (Routing Protocol for Low power and Lossy), which efficiently predicts routing over contents. Every network slot utilizes timing pattern while forwarding image data, audio data. The proposed method enhances the strength of routing protocol and also avoids congestion. The outcomes of the study illustrates that proposed Energy efficient priority based routing (EEPR) technique minimize overheads on mesh, energy consumption and end-end delay. Also, the proposed method outperforms the existing QRPL methods in IoT platform. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
An enhanced network intrusion detection system for malicious crawler detection and security event correlations in ubiquitous banking infrastructure
Purpose: In the recent era, banking infrastructure constructs various remotely handled platforms for users. However, the security risk toward the banking sector has also elevated, as it is visible from the rising number of reported attacks against these security systems. Intelligence shows that cyberattacks of the crawlers are increasing. Malicious crawlers can crawl the Web pages, crack the passwords and reap the private data of the users. Besides, intrusion detection systems in a dynamic environment provide more false positives. The purpose of this research paper is to propose an efficient methodology to sense the attacks for creating low levels of false positives. Design/methodology/approach: In this research, the authors have developed an efficient approach for malicious crawler detection and correlated the security alerts. The behavioral features of the crawlers are examined for the recognition of the malicious crawlers, and a novel methodology is proposed to improvise the bank user portal security. The authors have compared various machine learning strategies including Bayesian network, support sector machine (SVM) and decision tree. Findings: This proposed work stretches in various aspects. Initially, the outcomes are stated for the mixture of different kinds of log files. Then, distinct sites of various log files are selected for the construction of the acceptable data sets. Session identification, attribute extraction, session labeling and classification were held. Moreover, this approach clustered the meta-alerts into higher level meta-alerts for fusing multistages of attacks and the various types of attacks. Originality/value: This methodology used incremental clustering techniques and analyzed the probability of existing topologies in SVM classifiers for more deterministic classification. It also enhanced the taxonomy for various domains. 2021, Emerald Publishing Limited. -
Turbulent Flow in Forced Convection Heat Transfer-Numerical Validation
Forced convective heat transfer of airflow through circular pipe with constant heat input and different free stream velocities is numerically validated. The significance of the present work is that the suction flow has been employed in the forced convection set up domain kept in the wind tunnel. From first law of thermodynamics and applying the energy balance equation, experimental heat transfer coefficient is determined. Further correlations are used to validate the experimental results. Although correlations provide reasonable estimates from the point of feasibility and accuracy, computational methods are used to estimate the convective heat transfer coefficient. Hence in this paper experimental, theoretical and computational analysis is carried out. The results reveal that the numerical validation is an effective tool from the point of feasibility and accuracy to determine the convective heat transfer coefficient. 2022. MechAero Foundation for Technical Research & Education Excellence. -
Study of Natural Convection with Local Thermal Non Equilibrium Effects in Nanoliquid-Saturated Low Porosity Enclosures
Natural convection of nanoliquid in densely packed vertical porous enclosure is studied by subjecting the vertical walls to constant heat flux under local thermal non-equilibrium (LTNE) assumptions. Water, copper nanoparticles and porous material made of aluminum foam, glass balls and sand are considered for the study. The governing equations are modelled using single-phase model. Thermophysical properties of nanoliquid and nanoliquid-saturated porous medium are calculated using phenomenological laws and mixture theory. An analytical expression for velocity and temperature profiles of nanoliquid (base liquid+nanoparticles) and solid (porous medium) phases has been obtained. Weighted average Nusselt number is expressed as a function of aspect ratio, volume fraction, and properties concerning LTNE effects. LTNE effect is shown to be a heat transfer enhancing mechanism. The presence of nanoparticles is to enhance the heat transfer in water. Local thermal equilibrium results are obtained as a limiting case of the present study and so obtained results are compared with previously published paper in the literature. 2022, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Intelligent Diagnostic Prediction and Classification Models for Detection of Kidney Disease
Kidney disease is a major public health concern that has only recently emerged. Toxins are removed from the body by the kidneys through urine. In the early stages of the condition, the patient has no problems, but recovery is difficult in the later stages. Doctors must be able to recognize this condition early in order to save the lives of their patients. To detect this illness early on, researchers have used a variety of methods. Prediction analysis based on machine learning has been shown to be more accurate than other methodologies. This research can help us to better understand global disparities in kidney disease, as well as what we can do to address them and coordinate our efforts to achieve global kidney health equity. This study provides an excellent feature-based prediction model for detecting kidney disease. Various machine learning algorithms, including k-nearest neighbors algorithm (KNN), artificial neural networks (ANN), support vector machines (SVM), naive bayes (NB), and others, as well as Re-cursive Feature Elimination (RFE) and Chi-Square test feature-selection techniques, were used to build and analyze various prediction models on a publicly available dataset of healthy and kidney disease patients. The studies found that a logistic regression-based prediction model with optimal features chosen using the Chi-Square technique had the highest accuracy of 98.75 percent. White Blood Cell Count (Wbcc), Blood Glucose Random (bgr), Blood Urea (Bu), Serum Creatinine (Sc), Packed Cell Volume (Pcv), Albumin (Al), Hemoglobin (Hemo), Age, Sugar (Su), Hypertension (Htn), Diabetes Mellitus (Dm), and Blood Pressure (Bp) are examples of these traits. 2022 by the authors. -
Numerical approach to generalized coupled fractional Ramani equations
The main goal of this study is to find solutions for the generalized coupled Ramani equation with the fractional order using the fractional natural decomposition method (FNDM). Four distinct cases are chosen to illustrate and validate the effectiveness of the considered method. The simulations in terms of numeric have been illustrated to confirm the reliability and proficiency of the projected scheme. Moreover, the behavior of the obtained results is captured for distinct fractional order. The comparison study is illustrated to verify the accuracy of the projected procedure. The achieved results exemplify that the projected solution procedure offers a simple algorithm and is also very efficient to analyze the nature of the coupled differential equations with arbitrary order situated in associated areas of Science and Engineering. 2022 World Scientific Publishing Company. -
Nano- from nature to nurture: A comprehensive review on facets, trends, perspectives and sustainability of nanotechnology in the food sector
Nanotechnology has underpinned vital progress in current research and has immensely promoted the food production chain. This review projected the critical intervention of nano-based technologies like modern advancements of nano-based biosensors in detecting mycotoxins, microbial contaminations, antibiotics, pesticides, food additives, and dyes. It also highlighted the starring roles of nanotechnology in terms of active, intelligent food packaging and food safety. These approaches have certainly intensified the strength of food processing technology and improved food quality and maintenance standards during shelf life. Apart from these trending facets, this review throw light on the utilisation of food waste for the biogenic synthesis of nanoparticles and the application of nano-based materials for the recycling process in food production units to ensure a complete cleaner technology. However, monitoring the chronic exposure of food contact nanomaterials should be critically evaluated to ensure food safety. Nanotechnology embraced an influential role in the food sector by providing effective avenues for energy conservation, sustainability, and cues to improve the capital funds well. 2021 Elsevier Ltd -
Exploring perspectives on risks to mental health problems in adolescents: A dual method approach
This study explores different perspectives on the risk factors of mental health problems among adolescents using a dual method approach. 12 mental health professionals were interviewed using a semi-structured interview guide. Nine Focus Group Discussions were conducted with parents, teachers and school going adolescents (aged 12-18). Data were transcribed and analysed using content analysis. Common codes and categories were extracted from both the methodologies thus, representing triangulation and trustworthiness of findings. The results show seven major coding categories including self concept, coping mechanisms, parenting principles and family dynamics, teacher-student dynamics, peer interaction and media. Participants across the groups described the relevance of these categories in the mental health of adolescents. The findings were illustrated using Bronfenbrenners ecological systems theory framework. The findings have important implications in terms of identification and management of mental health difficulties in adolescents especially from a preventive perspective. The findings conclude that risk factors exist within the individual as well the contextual systems which make an adolescent vulnerable to a number of mental health problems. The findings can be included in the primary prevention framework by identifying and modifying these risk factors and therefore, delaying the progression of mental health difficulties into a major disorder. 2022 RESTORATIVE JUSTICE FOR ALL. -
Fractional p()-Kirchhoff Type Problems Involving Variable Exponent Logarithmic Nonlinearity
In this paper, we investigate a fractional p()-Kirchhoff type problem involving variable exponent logarithmic nonlinearity. With the help of the Nehari manifold approach, the existence and multiplicity of nontrivial weak solutions for the above problem are obtained. The main aspect and challenges of this paper are the presence of double non-local terms and logarithmic nonlinearity. 2022 by the authors. Licensee MDPI, Basel, Switzerland. -
Optimization of graded catalyst layer to enhance uniformity of current density and performance of high temperature-polymer electrolyte membrane fuel cell
The optimal use of catalyst materials is essential to improve the performance, durability and reduce the overall cost of the fuel cell. The present study is related to spatial distributions of current and overpotential for various graded catalyst structures in a high temperature-polymer electrolyte membrane fuel cell (HT-PEMFC). The effect of catalyst gradient across the catalytic layer (CL) thickness and along the channel and their combination on cell performance and catalyst utilization is investigated. The graded catalytic structure comprises two, three, or multiple layers of catalyst distribution. For a total cathode catalyst loading of 0.35 mg/cm2, higher loading near the membrane presents improved cell performance and catalyst utilization due to reduced limitations caused by oxygen and ion diffusions. However, non-uniformity in the current distribution is significantly increased. The increase in the catalyst loading along the reactant flow provides a substantially uniform current density but lower cell performance. The synergy of varying catalytic profiles across the CL thickness and along the cathode flow direction is investigated. The results emphasize the importance of a rational design of cathode structure and mathematical functions as a strategic tool for functional grading of a CL towards improved uniform current distribution and catalyst utilization. 2021 Hydrogen Energy Publications LLC -
Content-Based Music Recommendation Using Non-Stationary Bayesian Reinforcement Learning
This paper presents a music recommendation system for the offline libraries of songs that employs the concepts of reinforcement learning to obtain satisfactory recommendations based on the various content-based parameters. In order to obtain insights about the effectiveness of the generated recommendations, parallel instances of single-play multi-arm bandit algorithms are maintained. In conjunction to this, the concepts of Bayesian learning are considered to model the user preferences by assuming the environment's reward generating process to be non-stationary and stochastic. The system is designed to be simple, easy to implement, and on-par with user satisfaction within the bounds of the input data capabilities. Copyright 2021, IGI Global. -
Examining psychometric properties of the Interpersonal Needs Questionnaire among college students in India
Background: With the second-highest population in the world, suicide-related deaths in India are high, and adults under 30 are particularly at an increased risk. However, empirical examinations of factors contributing to suicide in India and assessments of reliability and validity of self-report measures assessing these constructs are rare. Aims: The present study examined the psychometric properties of the Interpersonal Needs Questionnaire (INQ). Materials & Methods: Undergraduate students in India (N=432) completed the INQ and questionnaires assessing suicidal ideation, depression, fearlessness about death, and pain tolerance. Results: Confirmatory factor analyses of the 15-item INQ indicated that after removing three items assessing perceived burdensomeness, the two-factor structure of INQ demonstrated acceptable fit with good internal consistency for each of the subscales (?=.84.90). In line with the interpersonal-psychological theory of suicidal behavior (IPTS), thwarted belongingness and perceived burdensomeness interacted to predict suicidal ideation. Additionally, these constructs were positively associated with suicidal ideation and depression, and weakly correlated with fearlessness about death and pain tolerance. Discussion: Results support the relevance of the IPTS for understanding suicidal ideation among college students in India. Conclusion: The results suggest that modified INQ demonstrates strong internal consistency, as well as good construct, criterion, and discriminant validity among Indian college students. 2021 The American Association of Suicidology. -
Strength and leaching characteristics of red mud (bauxite residue) as a geomaterial in synergy with fly ash and gypsum
Red mud (Bauxite residue) comprises microscopic particles and other chemical constituents that pose a major threat to the environment. The most common solution to resolve issues related to any solid waste is its reuse in construction. This paper delves into the possibility of using red mud as a geomaterial in synergy with fly ash and gypsum. In this regard upon finding the geotechnical properties of virgin red mud, it is strengthened with fly ash by replacing 10, 20, and 30% of red mud by its dry weight and to these combinations gypsum was added by 0.5% and 1% and prepared various combinations. The impact of these material additions on the characteristics of red mud were investigated using the Unconfined compressive strength and California bearing ratio values and their environmental compatibility was further studied by conducting the leaching characteristics using Toxicity Characteristics Leaching Procudure (TCLP) method. The findings of the tests indicated that fly ash and gypsum significantly enhanced the strength qualities of red mud as compared to unstabilized red mud. The stabilization helps red mud to attain a minimum strength required to use as a subgrade material. Furthermore, leaching investigations performed on stabilised samples have revealed that the vast majority of leaching heavy metals are within the WHO's authorised threshold for toxicity. 2022