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Rendering View of Kitchen Design Using Autodesk 3Ds Max
The method of creating a 3D kitchen design model is clarified, including setting up the sources, working with editable poly, information in the inside of the kitchen design, and applying turbo-smooth and symmetry modifier. The way materials are introduced to the model which is defined in addition to lighting the environment and setting up the renderer. Rendering methods and procedures are also defined. Multiple images were drawn to create the final rendering. The goal of our research is to produce a kitchen design that uses materials to enhance models. Cylinder, sphere, box, plane, and splines were the shapes employed. Editable poly, editable spline, and UVW map are the modifiers. Finally, we enhanced the model using a material editor and target lighting. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Renewable energy integration: Storage solutions for a sustainable future
This chapter describes how energy storage technologies provide critical services for the integration of renewable energy sources, as those sources are variable and intermittent (e.g. solar and wind). It reviews different types of storage solutions - electrochemical, mechanical and thermal - including their relative advantages and drawbacks, as well as their appropriateness for various applications. It highlights the importance of adopting different energy storage types that are tailored to different energy needs. Global Sustainability and Energy Storage: Discussing the broader implications of energy storage systems for global sustainability, such as reducing reliance on fossil fuels, lowering carbon emissions, and improving access to energy in underserved regions. Energy storage technologies are crucial to a reliable, sustainable, low- carbon energy future. 2025, IGI Global Scientific Publishing. All rights reserved. -
Renewable Musa Sapientum derived porous nano spheres for efficient energy storage devices
Biomass-based carbonaceous materials derived from Musa Sapientum have gained much attention in recent years for their application in energy storage devices, especially supercapacitors. In the present work, we synthesized carbonaceous material from banana peel as the biomass precursor by using a pyrolysis method carried out at various temperatures (600, 800, and 1000 C). The characterization of the prepared carbonaceous materials BP600, BP800 and BP1000 was done by using different characterization techniques such as FTIR, XRD, FE-SEM, and TEM, studies. The electrochemical study of the synthesized material was carried out by cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) electrochemical impedance spectroscopy (EIS). The supercapacitive performance of the material was studied using a 3-electrode system with 3M KOH as an electrolyte. As a result, the BP600 exhibited a better specific capacitance with higher energy and power densities along with a maximum cyclic stability of 16,000 cycles. To show the practical applicability of the material BP 600, two electrode system studies were carried out as well, which showed preferentially good values for specific capacitance with appreciable power and energy density values. The study provides us with a green approach for the fabrication of non-toxic, low-cost, and environmentally friendly potential porous carbonaceous electrode materials by converting bio-waste into a clean and renewable source of energy. 2024 The Author(s). Published by IOP Publishing Ltd. -
Repercussions of global turbulence and market volatility in spot & futures market: India preparedness
This article examines the repercussions of global turbulence and market volatility in Indian Capital market for the period spanning from January 1, 2003 to August 31, 2013 with a total of 2654 observations and it is broken into pre-crisis and post-crisis respectively. The study employed Generalized Autoregressive Conditional Heteroskedasticity (1,1) model to measure the volatility persistence by employing dummy variables. Cointegrating Regression Augmented Dickey Fuller (CRADF) and Vector Error Correction Model (VECM) was employed to investigate the casual nexus between spot and futures market in both short and long run equilibrium. The squared residuals of VECM were applied to investigate the lead-lag relationship between the bivariate variables. Our findings indicate that there was a significant change in the post crisis period for spot and futures market volatility. Our result suggests that nothing can be learned and new regulation can only do more harm. Apart from this, nobody knows which financial instrument will be at the centre of the next crisis. Overall, the comprehensive financial sector reform like Credit Default Swap, Valuation Assumptions and Basel II Accord can create more problems and make the investors more complex to meet the global challenges environment. IJER Serials Publications. -
Representation of Cancer in the Digital Space
[No abstract available] -
Reproductive health vs overall well-being: systematic review of studies on women migration and health care utilization
Purpose: Sustainable development goals (SDGs) recognize the importance and interrelation between health and migration. Women migration and health is well researched, yet less attention is paid to their healthcare utilization, especially with regard to overall health and well-being. This paper aims to highlight the gap in the existing literature on health care utilization by women migrants. Design/methodology/approach: A systematic review was carried out following the PRISMA guideline. For the review, the literature was taken from three electronic databases, which were Springer Link, Taylor and Francis and PubMed. From a total of 1,575 studies, seven studies cleared the eligibility screening. Findings: Of seven studies, five were found to focus on the sexual and reproductive health of the women migrants than their general health and well-being, and less attention is paid to health promotion and illness prevention beyond reproductive and sexual health. While, studies on general health have focused on the influence of health status on health care utilization and the influence of health insurance in health care utilization. The review has revealed the disparities faced by migrant women in different countries while seeking health care. Originality/value: Studies on women migration and health care utilization have largely focused on the reproductive and sexual health needs of women, and this overemphasis often undermines their accessibility and affordability to overall health and well-being. Therefore, the present study has moved away from the concept of sexual and reproductive health tot that of overall health and well-being of women migrants. 2021, Emerald Publishing Limited. -
Rescue Operation with RF Pose Enabled Drones in Earthquake Zones
The main objective of this research is to use machine learning algorithms to locate people stranded by an earthquake or other big disasters. Disasters are often unpredictable, they can result in significant economic loss, and the survivors may struggle with despair and other mental health issues. The time, the victim's precise location, the possible condition of the victim, the resources and manpower on hand are the main challenges the rescue team must deal with. This article examines a model that gathers data and, using that data, predicts risk analysis and probability of finding the shortest distance to reach the person in need. Using a drone equipped with RF-pose technology and EHT sensors, it will be able to locate any individuals trapped inside a collapsed structure. To determine the dataset's extreme points and the shortest route to the victim's location by using the Dijkstra's algorithms. The primary aim of this article is to discuss the idea of applying these ML (Machine Learning) algorithms and creating a model that aids in rescuing those trapped beneath collapsed buildings. Devices that are part of the Internet of Things (IoT) have grown in popularity over the past few years as a result of their capacity for data collection and transmission. Particularly in disaster management, search and rescue operations, and other related disciplines, drones have shown to be useful IoT devices. These tools are perfect for emergency response circumstances because they can be utilized to access locations that are hard to get to or too dangerous for humans. Drones with cameras and other sensors can be used in disaster management to gather data in real-time on the severity of the damage caused by earthquakes and other disasters. The afflicted area may be mapped out with their help, and they can also be used to find survivors and spot dangerous places that should be avoided. The rescue operation can then be planned and the resource allocation made more efficient using this information. Drones can be used in search and rescue operations to find and follow people who are stuck or lost. Drones can be equipped with the RF-pose sensors used in the research described in the abstract to assist in locating people who are buried under debris. Thermal camera-equipped drones can also be used to locate people in low-light or night-time conditions by detecting their body heat. The capacity of drones to offer real-time data is one of the benefits particularly disaster management. 2023 IEEE. -
Research & development premium in the Indian equity market: An empirical study
This article aims to investigate the research and development (R&D) premium and explore the three most prominent asset pricing models: capital asset pricing and the three-and five-factor models (Fama & French, 1993; 2015). The results show that India's annualized average R&D premium is significantly higher than the existing value, market, profitability, size and investment premiums, implying that the R&D premium is a more significant concern for Indian investors, particularly for high R&D firms. It was also observed that by applying the GRS test and the Fama and MacBeth (1973) two-pass procedure, the R&D risk factor augmented the CAPM, FF3F and FF5F models outperforming the existing CAPM, FF3F and FF5F models, respectively. We can also report that R&D is, unquestionably, a priced ingredient and a critical factor in developing pricing models for developing markets such as India. The paper's conclusions add to the current literature in R&D and asset pricing and assist investment professionals in developing better investment and trading strategies. 2021 AESS Publications. All Rights Reserved. -
Research Advancements In Autism Spectrum Disorder Using Neuroimaging
Autism Spectrum Disorder (ASD) is a complex neurological condition that manifests as a spectrum of symptoms at varying levels of severity.. Insufficient data and heterogeneous characteristics of ASD are the primary causes of it being a complex, challenging, and intriguing field of research. ASD is declared one of the fastest-growing mental disorders affecting the normal life of subjects at various levels of severity and stages of age. Recent research work observed a significant change in brain structure, functional connectivity, and network using neuroimaging resources. Each autistic brain is as unique as a fingerprint for typically developed subjects. Magnetic Resonance Imaging (MRI) is accepted as an excellent diagnostic technology for numerous disorders with a satisfactory amount of information by medical experts. Cognitive deficits brain MRI modalities contain microscopic information, which is time-consuming and needs experts to interpret. Artificial intelligence (AI) strategies (Machine Learning and Deep Learning) are implemented with various imaging modalities to decrypt the information for diagnosis and to support computer-added solutions for appropriate treatment. The research aims to discover the various evolutionary impacts of artificial intelligence for the diagnosis of Autism syndrome disorder using neuroimaging. To automate the diagnosis using artificial intelligence methodologies, medical imaging has proved to be of immense use. Though neuroimaging and AI produced satisfactory diagnostic solutions for many mental disorders, research is required to explore the autistic brain for more neuroimaging information to be used for further investigation. Some of the Internet of Things (IoT) solutions for detection and training are also invented but not with the use of Neuroimaging. Autism is a neurological condition that affects the brain, and hence more research is advised using imaging and AI techniques to support the community to enjoy a normal life. 2023 American Institute of Physics Inc.. All rights reserved. -
Research Advances on Foreign Portfolio Investments: A Bibliometric and Thematic Analysis
[No abstract available] -
Research aligned analysis on web access behavioral pattern mining for user identification
Human activity understanding includes activity recognition and activity pattern discovery. Monitoring human activity and finding abnormality in their activities used by many field like medical applications, security systems etc. Basically it helps and support in decision making systems. Mining user activity from web logs can helps in finding hidden information about the user access pattern which reveals the web access behaviour of the users. Clustering and Classification techniques are used for web user identification. Clustering is the task of grouping similar patterns for web user identification. Classification is the process of classifying web patterns for user identification. In this paper we have implemented the existing works and discussed the results here to find the limitations. In existing methods, many data mining techniques were introduced for web user behaviour identification. But, the user identification accuracy was not improved and time consumption was not reduced. Our objective is to study the existing work and explore the possibility to improve the identification accuracy and reduce the time consumption using machine learning and deep learning techniques. BEIESP. -
Research article toxicological evaluation of ethanolic leaf and fruit extracts of phaseolus vulgaris l. Treated with wastewater in danio rerio hamilton (zebrafish)
Background and Objective: The cultivation of Vegetables in the world is facing a shortage of water so that the farmers are forced to use sewage wastewater for cultivation in underdeveloped countries. Therefore, the present study was an attempt to examine the toxicity level of accumulated heavy metals in the vegetables irrigated with sewage water and treated sewage water. The concentration-dependent changes in toxicity of ethanolic leaf and fruit extracts of Phaseolus vulgaris treated with wastewater in Zebrafish were analysed in this study. Materials and Methods: For the experiment, finely ground powders of leaves and fruits of Phaseolus vulgaris were extracted with ethanol. Using different concentrations of these extracts, a toxicity test was done with Danio rerio as per the OECD guidelines 203. Results: Using AAS, heavy metals like lead and manganese were found in higher concentrations in untreated wastewater than in distilled water and treated wastewater. The results indicated that ethanolic leaf extracts of treated wastewater irrigated Phaseolus vulgaris does not induce toxicity when used at a dose below 400 mg LG1. Leaf extracts of Phaseolus vulgaris grown with wastewater showed the lowest and highest mortality at 100 and 400 mg LG1, respectively, when compared to other plant extracts. Histopathological variations were also observed in the fishes exposed to the lethal concentrations of plant extracts. Statistical evaluation of the correlation between concentration and mortality percentage was carried out using SPSS. Conclusion: The present study revealed that the leaf and fruit extracts of Phaseolus vulgaris grown with untreated wastewater were more toxic to Danio rerio than other extracts used in the experiment. 2022 Aleesa Augustine and Jobi Xavier. -
Research asset creation (RAC) model for PhD awarding universities in India
Importance of higher education and research is becoming more prominent and admission for PhD is increasing year by year in India. Most of the time Research done as part of PhD ends with the submission and acceptance of thesis in Universities. This research future work or extension work might be picked by other PhD candidate in the same or from the different Universities but not sure when it will happen. Also not sure the research completed has achieved its end objective and University is fine to stop that research after spending so much of time and resources of University. This paper insists on continuous research with PhD candidates every year in Universities until the completion of research and scope for reducing the waste of resources and time. This paper considers the importance and effectiveness of Indexing parameters, Indexing agencies, review methods, Journals and relevant concepts. Considering the usefulness and facts of the same to research community building a standard process with procedures to control quality, performance and original research in place, I have built a Research Asset Creation (RAC) model for universities offering PhDs in India by making use of University level Indexing, Indexing parameters, Inter and Intra University peer review methods and University Journal as magazine and as well as Indexing agency. Research cannot be considered just for the award of degree. There is a need for making use of research, resources of University and time spent on research till the objective of the research is accomplished. This can be accomplished by adopting Research Asset Creation model. Complete details of the model, components of the model, implementation, its benefits and usage is discussed in this paper. This is a generalized Model and fit for all Countries which are looking for effective use of research and resources in a progressive manner. BEIESP. -
Research challenges in self-driving vehicle by using internet of things (IoT)
This article summarizes the benefits, safety hazards, and limitations of owning a self-driving vehicle. Finding a way to use an SDV(Self Driving Vehicle) is minimizing the risk for an accident is important for public and road safety. The actual rate of accidents for self-driving vehicles are lower than that for regular vehicles since the total number of miles of self-driving vehicles combined is nowhere close to that of regular fossil-fueled vehicles. Even though there is no proof that self-driving vehicles will not cause accidents, it is important to know that self-driving vehicles weren't the cause in all the cases they have been involved. That is, it will not be purely considered as the machine's mistake. The safety level of self-driving vehicles has been proven to be one of the best and that has led to the number of serious accident-related wounds in self-driving vehicles to remain lower than the standard level. Nevertheless, Internet of Things plays a major role in developing the self-driving vehicle concept. 2021 IEEE. -
Research Initiative on Sustainable Education System: Model of Balancing Green Computing and ICT in Quality Education
Green Computing Practices (GCP) convey the revolutionary changes of the modern education system. The education system is transforming into a hybrid mode of operations in effective teaching and learning procedure. In the modern era, computer devices are playing a foremost role in performing ICT based teaching and learning (ICT-BTL). The GCP and ICT-BTL are the creative and innovative practices that can ensure the eco-friendly enactment and safeguard from various harmful environmental impacts. The motive of projecting the present research outcome is to address the impact of GCP on ICT-BTL activities. The creative and innovative practices of ICT-BTL support the implementation of GCP towards a sustainable education system. A sustainable education system interconnects the teachers, learners, institutions, and industrial experts through eco-friendly electronic and computer devices that ensure maximum efficiency in education with minimum environmental impacts. 2022 IEEE. -
RESEARCH INSIGHTS ON TEACHER EDUCATION
Teacher education is an important academic domain, as it determines the quality of school education through the teachers produced by teacher education. The changing demands and nature of learners at school force teachers to adapt themselves constantly. This requires change in the methods of teacher training and its curriculum. Thus, researchers specialised in the area of teacher education must find innovative approaches to train preservice and in-service teachers to meet the changing demands. The present chapter presents the research conducted on the developmental aspects of teacher education across the globe in the last two decades. The chapter organises the research inputs in five different areas for ease of understanding: research related to the application of sociological, psychological and technological theories to teacher education practices, research related to transformational changes, research on teacher and teaching competence and research pertaining to teacher reflection. This would help teacher educators, schoolteachers, trainee teachers and policy makers to organise and implement effective teacher training programmes. 2023 selection and editorial matter G.S. Prakasha and Anthony Kenneth; individual chapters, the contributors. -
Research Intention Towards Incremental Clustering
Incremental clustering is nothing but a process of grouping new incoming or incremental data into classes or clusters. It mainly clusters the randomly new data into a similar group of clusters. The existing K-means and DBSCAN clustering algorithms are inefficient to handle the large dynamic databases because, for every change in the incremental database, they simply run their algorithms repeatedly, taking lots of time to properly cluster those new ones coming data. It takes too much time and has also been realized that applying the existing algorithm frequently for updated databases may be too costly. So, the existing K-means clustering algorithm is not suitable for a dynamic environment. Thats why incremental versions of K-means and DBSCAN have been introduced in our work to overcome these challenges.To address the aforementioned issue, incremental clustering algorithms were developed to measure new cluster centers by simply computing the distance of new data from the means of current clusters rather than rerunning the entire clustering procedure. Both the K-means and the DBSCANDBSCAN algorithms use a similar approach. As a result, it specifies the delta change in the original database at which incremental K-means or DBSCANDBSCAN clustering outperforms prior techniques. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Research methodologies and practical applications in psychoneuroimmunology
Research methodologies in psychoneuroimmunology (PNI) are diverse, incorporating a blend of experimental, clinical, and observational approaches to study the complex mechanisms underlying the brain-immune relationship. Techniques range from molecular and genetic analyses to neuroimaging, psychophysiological assessments, and behavioral interventions. The practical applications of PNI impact areas like stress management, mental health treatment, chronic disease prevention, and immune system functioning. By examining how psychological factors, such as stress and emotions, can affect immune responses and overall well-being, PNI offers valuable insights into personalized healthcare and the development of therapeutic strategies for holistic treatment. Research Methodologies and Practical Applications in Psychoneuroimmunology explores PNI, the interactions between behavior, the nervous system, the endocrine system, and the immune system. It examines theoretical frameworks, research methodologies, and practical applications within the field, offering insights into the mechanisms underlying health and disease. This book covers topics such as immunology, cognitive function, and neuroscience, and is a useful resource for psychologists, medical professionals, policymakers, healthcare workers, scientists, academicians, and researchers. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Research Methodology and Quantitative Techniques: A Guide for Interdisciplinary Research
Research Methodology and Quantitative Techniques is a guide tailored for students and research scholars navigating the intricate landscape of research degrees across various disciplines. From clearing coursework to formulating research synopses, selecting methodologies, conducting analysis and penning impactful theses, this book is a roadmap for every stage of the research journey. It empowers scholars to undertake original, quality research that not only fulfills academic requirements but also contributes to the burgeoning pool of knowledge in diverse fields. Uniquely structured to address the specific needs of researchers, this guide goes beyond traditional boundaries, delving into areas like IPRs and research ethics often overlooked in discipline-oriented texts. By offering comprehensive support, from topic selection to publication, it aims to be the go-to resource for researchers seeking a seamless path from inception to dissemination. This book, Research Methodology and Quantitative Techniques, addresses every facet of research with clarity and insight and serves as both a companion and a vital tool for scholars poised to make a meaningful research impact in their fields. 2025 K.A. Varghese, B.R. Ranwah, Nisha Varghese and Nikhil Varghese. -
Research of Approaches to Assessing the Information Security Risks of an Organization:Qualitative Risk Assessment Methods
This article explores modern approaches to assessing information security risks within organizations, focusing on qualitative, quantitative, and hybrid risk management methodologies. The study examines the core principles of each approach, their practical applicability in different organizational contexts, the tools and frameworks commonly employed, and key implementation challenges. A comparative analysis of these methods highlights their respective strengths and limitations, providing insights for selecting the most suitable risk assessment strategy based on organizational needs, industry requirements, and available resources. 2026 by IGI Global Scientific Publishing. All rights reserved.