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A Review of Algorithms for Mental Stress Analysis Using EEG Signal
Mental stress is an enduring problem in human life. The level of stress increases exponentially with an increase in the complexity of work life. Hence, it is imperative to understand the causes of stress, a prerequisite of which is the ability to determine the level of stress. Electroencephalography (EEG) has been the most widely used signal for understanding stress levels. However, EEG signal is useful only when appropriate algorithms can be used to extract the properties relevant to stress analysis. This paper reviews algorithms for preprocessing, feature extraction and learning, and classification of EEG, and reports on their advantages and disadvantages for stress analysis. This review will help researchers to choose the most effective pipeline of algorithms for stress analysis using EEG signals. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A review of alternative proteins for vegan diets: Sources, physico-chemical properties, nutritional equivalency, and consumer acceptance
Alternate proteins are gaining popularity as a more sustainable and environmentally friendly alternative to animal-based proteins. These proteins are often considered healthier and are suitable for people following a vegetarian or vegan diet. Alternative proteins can be recovered from natural sources like legumes, grains, nuts, and seeds, while single cell proteins (mycoproteins), and algal proteins are being developed using cutting-edge technology to grow fungus, yeast and algal cells in a controlled environment, creating a more sustainable source of protein. Although, the demand for alternative protein products is increasing, there still happens to be a large gap in use among the general consumers mainly stemming from its lower bioavailability, lack of nutritional equivalency and reduced digestibility compared to animal proteins. The focus of the review is to emphasize on various sources and technologies for recovering alternative proteins for vegan diets. The review discusses physicochemical properties of alternative proteins and emphasise on the role of various processing technologies that can change the digestibility and bioavailability of these proteins. It further accentuates the nutritional equivalency and environmental sustainability of alternative protein against the conventional proteins from animals. The food laws surrounding alternative proteins as well as the commercial potential and consumer acceptance of alternative protein products are also highlighted. Finally, key challenges to improve the consumer acceptability and market value of plant-based proteins would be in achieving nutrient equivalency and enhance bioavailability and digestibility while maintaining the same physicochemical properties, taste, texture, as animal proteins, has also been highlighted. 2023 The Authors -
A Review of biophilic design at Kuttikattoor school for the children
The objective of this paper is the creation of a school to help the children of Kutikatoor live a more accessible and simpler life: students in the concentration range from 4 to 16 (Play School - - Grade 10). The proposed location, which is around 18.3 acres in size, lies in Kuttikattoor, Kozhikode, and Kerala. The land is surrounded by greenery and situated in a mountainous area. The study will concentrate on how biophilic architecture and design may enhance students' lives. This paper will discuss how biophilic design may benefit schools by creating circulation and spatial connections between the built and natural environments. The biophilic design can have quantifiable beneficial effects on student performance and well-being by including natural components. It is necessary to thoroughly analyze the biophilic design in relation to the learning environment for students, using ideas of ecological, visual, and spatial integration. By fostering a soothing atmosphere, lowering anxiety, and boosting physical fitness, biophilic design, which incorporates natural light, greenery, and nature vistas, can increase attention, decrease stress, stimulate creativity, and improve academic accomplishment. The school's design will be implemented by incorporating the architectural design into the contoured regions and using the idea of biophilic design patterns. Depending on the climate and the site's orientation, the design will be implemented such that locally accessible materials are employed in a hilly area. This detailed analysis of the case study and literature review for the school design will help us to design and conceptualize as an architect. Further, the study will also emphasize biophilic design which is aligned with the built environment in school design. The Authors, published by EDP Sciences. -
A review of buoyancy driven underwater gliders
In the past few years, several techniques and approaches have been developed by researchers for the ocean survey. An autonomous underwater vehicle primarily known as the glider is vastly used for oceanographic study and survey. With the help of these vehicles now it possible to have a study on the effects of pesticides, metal, biological toxins, or chemicals on the living organisms of the sea. Additionally, monitoring of threats such as biological weapons, radioactive leakage, and detection of mines is a very important parameter for keeping safety in check. Considering these parameters autonomous vehicles primarily known as glider are vastly used by oceanographers as they are relatively inexpensive, reusable, and have long mission durations. Such vehicle uses advanced sensors to perform automated monitoring and fast data acquisition. Since their inception in the 1980s, there have been considerable developments that have led to the augmentation of scientifically and commercially focused products. A comprehensive analysis of various underwater gliders and their working principle has been done here, emphasizing their architecture and working capabilities. 2022 Author(s). -
A review of challenges and solutions in the preparation and use of magnetorheological fluids
This review of MRF (magnetorheological fluids or MR fluids) brings out the challenges in methods of preparation, difficulties encountered in storage and use, and possible solutions to overcome the challenges. Magnetorheological fluid in the rheological fluid domain has found use due to its ability to change its shear strength based on the applied magnetic field. Magnetorheological fluids are composed of magnetizable micron-sized iron particles and a non-magnetizable base or carrier fluid along with additives to counter sedimentation and agglomeration. Magnetorheological fluids can respond to external stimuli by undergoing changes in physical properties thus enabling several improved modifications in the existing technology enhancing their application versatility and utility. Thus, magnetorheological fluid, a rheological material whose viscosity undergoes apparent changes on application of magnetic field, is considered as a smart material. Such materials can be used for active and semi-active control of engineering systems. Many studies on the designs of systems incorporating MR fluids, mainly for vibration control and also for other applications including brakes, clutches, dynamometers, aircraft landing gears, and helicopter lag dampers, have emerged over last couple of decades. However, the preparation as well as the maintenance of magnetorheological fluids involves several challenges. Sedimentation is a major challenge, even when stored for moderate periods of time. A comprehensive review is made on the problems confronted in the preparation of magnetorheological fluids as well as sustenance of the properties, for use, over a long period of time. Other problems encountered include agglomeration and in-use thickening (IUT) as well as rusting and crusting. Of interest is the mitigation of these problems so as to prepare fluids with satisfactory properties, and such solutions are reviewed here. The control of magnetorheological fluids and the applications of interest are also reviewed. The review covers additives for overcoming challenges in the preparation and use of magnetorheological fluids that include incrustation, sedimentation, agglomeration, and also oxidation of the particles. The methodology to prepare the fluid along with the process for adding selected additives was reviewed. The results showed an improvement in the reduction of sedimentation and other problems decreasing comparatively. A set of additives for addressing the specific challenges has been summarized. Experiments were carried out to establish the sedimentation rates for compositions with varying fractions of additives. The review also analyzes briefly the gaps in studies on MR fluids and covers present developments and future application areas such as haptic devices. 2019, The Author(s). -
A Review of Channel Estimation Mechanisms in Wireless Communication Networks
The fluctuating nature of wireless networks influences network performance. Estimation of channel condition is essential for many reasons. The accurate estimation and prediction help to improve the performance, like better rate adaptation in Wi-Fi, improved video streaming, reduce energy consumption, and better scheduling. There are many different approaches introduced past two decades. In this paper, we are focusing on providing a brief review of different channel estimation approaches and their importance in improving performance. 2021 IEEE. -
A review of cobalt-based catalysts for sustainable energy and environmental applications
In a bid to tackle the degrading climate conditions, the new age research in catalysis is predominantly focused on sustainable technologies associated with renewable energy conversion and environment purification. One of the primary motivations for the research in catalysis is the use of low-cost, earth-abundant materials that can fulfill the scale-up needs of respective technologies. Cobalt (Co) based catalysts have been an indispensable part of almost all areas of catalysis and they are often looked at as low-cost substitutes for precious metal-based catalysts. In the context of energy and environmental applications, Co-based catalysts are more commonly used for reactions such as hydrogen evolution reaction (HER), oxygen evolution reaction (OER), hydrolysis of chemical hydrides, CO2 reduction reaction (CO2RR) and advanced oxidation processes (AOPs). Co-based catalysts are interesting compounds as Co plays a diverse role in facilitating different reactions. This review provides a brief account of the significance of Co-based catalysts and elaborates their advancement in each of the above-mentioned applications and presents future research directions with the use of Co-based catalysts. An in-depth analysis to gain a deeper understanding of the Co-based systems is highly desired to promote breakthroughs in catalysis. 2023 The Authors -
A Review of Comprehension and Operation of DC/DC Converters Precisely Voltage Multiplier and Voltage Lift Converters
Converters in power electronics play a significant part in the power conversion of distributed generation and grid-connected systems. This paper gives comprehension analysis and operation of various non-isolated step-up DC/DC converters for renewable energy applications using voltage multiplier or/and voltage lift techniques to attain higher voltage gain. An isolated converter structure mainly comprises a transformer which is associated with high cost, complexity, leakage inductance, losses and EMI problems with the decrease in the efficiency of the converter, hence the operation of several DC/DC converters precisely voltage multiplier and voltage lift converters are discussed with relative simulation results obtained. 2022 Seventh Sense Research Group. -
A Review of Deep Learning Methods in Automatic Facial Micro-expression Recognition
Facial expression analysis to understand human emotion is the base for affective computing. Until the last decade, researchers mainly used facial macro-expressions for classification and detection problems. Micro-expressions are the tiny muscle moments in the face that occur as responses to feelings and emotions. They often reveal true emotions that a person attempts to suppress, hide, mask, or conceal. These expressions reflect a persons real emotional state. They can be used to achieve a range of goals, including public protection, criminal interrogation, clinical assessment, and diagnosis. It is still relatively new to utilize computer vision to assess facial micro-expressions in video sequences. Accurate machine analysis of facial micro-expression is now conceivable due to rapid progress in computational methodologies and video acquisition methods, as opposed to a decade ago when this had been a realm of therapists and assessment seemed to be manual. Even though the research of facial micro-expressions has become a longstanding topic in psychology, this is still a comparatively recent computational science with substantial obstacles. This paper a provides a comprehensive review of current databases and various deep learning methodologies to analyze micro-expressions. The automation of these procedures is broken down into individual steps, which are documented and debated. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Review of Deep Learning Methods in Cervical Cancer Detection
Cervical cancer is one of the most widespread and lethal malignancy that affects women aged 25 to 55 across the globe. Early detection of cervical cancer reduces burden of living and mortality drastically. Cervical cancer is caused through human papillomavirus transmitted sexually. Since the hereditary aspect is absent in cervical cancer, it can be cured completely if diagnosed early. Cervix cell image analysis is gold standard for classifying cervical cancer. Also known as pap smear, this histopathological test can provide dependable, and accurate diagnostic support. The current study examines the most recent research breakthroughs in deep learning models to classify cervical cancer. Three benchmark datasets are comprehensively described. Selective key classification models were implemented and comparative analysis was conducted on their performance. The findings of this study will allow researchers, publishers, and professionals to examine developing research patterns. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
A review of hierarchical nanostructures of TiO2: Advances and applications
In the past few decades, extensive studies have been carried out on TiO2 nanostructures having hierarchical morphologies and their applications in diverse fields. By controlling the size and composition of the different TiO2 morphologies, new and improved properties have been realized, leading to significant advancements in materials chemistry, in the broad areas of energy and environment. The improved efficiency and wide applications of these materials are attributed to their physicochemical properties such as stability, efficient electronic and ionic charge transfer, higher specific surface area, etc. In this review, we discuss the different morphologies of hierarchical TiO2 nanoparticles and the properties that have been influenced by these morphologies, enabling their diverse applications. Several composites using the different TiO2 hierarchical forms have been synthesized which too find wide applications. The excellent physical properties of zero, one, two, and three-dimensional TiO2 nanostructures, the relationship between the morphologies of TiO2 nanostructures, and their activities in energy and environment applications have been discussed. 2021 The Author(s) -
A Review of Historical Context and Current Research on Cannabis Use in India
Background: The cultivation and use of cannabis is historically rooted in the Indian subcontinent and this rich heritage of cannabis use dates back to at least two thousand years. Cannabis remains an illicit substance in India despite its changing status globally with many countries legalizing cannabis use in recent years. Scientific research on cannabis use in India has also been sparse. Method: Extensive search of online databases resulted in the identification of 29 original research studies pertaining to one of three areas of cannabis research; a) prevalence of cannabis use b) psychological correlates of cannabis use, c) cannabis use in substance use treatment settings. Findings: We found that most Indian studies used very basic quantitative research designs and had poor scientific rigor. Samples were small, region specific and included only males. Data analyses were limited to descriptive methods. The criteria for cannabis use in most of the reviewed studies were not rigorous and prone to biases. Conclusion & Implications: With changing attitudes and loosening of restrictions on cannabis use, the prevalence of new users is rising dramatically particularly in the college going population. This presents a strong need for research on motivations and attitudes to cannabis use and how those can influence patterns of use, and also the short- and long-term effects of use. More studies with stronger research designs (both cross sectional and longitudinal) are required for the study of cannabis use and this knowledge will be critical for managing the growing substance epidemic, generating public health solutions as well as formulating effective policy frameworks. 2022 The Author(s). -
A review of innovative bond instruments for sustainable development in Asia
Purpose: Advancing the economies in Asia toward meeting sustainable development goals (SDGs) needs an unprecedented investment in people, processes and the planet. The participation of the private sector is necessary to bridge the financing gap to attain this objective. Engaging the private sector can contribute significantly to attaining the 2030 agenda for SD. However, the financial markets in Asian economies are yet to realize this potential. In this context, this paper aims to discuss the state of finance for SD in Asia and identifies innovative financial instruments for attracting private investments for SDs in these economies. Design/methodology/approach: This study relies on published articles, reports and policy documents on financing mechanisms for SD. The literature review covered journal data sources, reports from global institutions such as the UN, World Bank, International Monetary Fund and think-tanks operating in the field of climate change policies. Though the topic was specific to financial market instruments, a broader search was conducted to understand the different sources of sustainable finance available, particularly in Asia. Findings: The investments that are required for meeting the SDGs remain underfunded. Though interest in sustainability is growing in the Asian economies, the financial markets are yet to transition to tap the growing interest in sustainable investing among global investors. This paper concludes that to raise capital from private investors the Asian economies should ensure information availability, reduce distortions and unblock regulatory obstacles. It would also need designing policies and introducing blended financing instruments combining private and public funds. Research limitations/implications: Though the study has grouped Asian economies, the financing strategy for SDGs should be developed at the country-level considering the domestic financial markets, local developmental stage, fiscal capacity and nationally determined contributions. Further research can focus on developing country-specific strategies for using innovative financial instruments. Originality/value: Mobilizing funds for implementing the 2030 Agenda for SD is a major challenge for Asian economies. The paper is addressed to national policymakers in Asian economies for developing strategies to raise capital for SD through private participation. It provides opportunities for revisiting national approaches to sustainable finance in these economies. 2021, Emerald Publishing Limited. -
A Review of Optimization Algorithms Used in Proportional Integral Controllers (PID) for Automatic Voltage Regulators
The voltage in electrical grids is maintained at its nominal value by automatic voltage regulators (AVR). In AVR systems, proportional-integral-derivative (PID) is the most popular controllers due to their robust performance and simplicity. Controlling the parameters of proportional-integral-derivative (PID) controllers, which are used in AVR technology, is a nonlinear optimization problem. Optimization issues are of great importance to both the industrial and scientific worlds. A PID controller's objective function is designed to minimize the settling time, rise time, and overshoot of the step response of the resultant voltage. This paper presents the performance comparison of six optimization algorithms such as Enhanced Crow Search Algorithm (ECSA-PID), Slime Mould algorithm (SMA-PID), Future Search Algorithm (FSA-PID), Whale Optimization Algorithm (WOAPID), Equilibrium Optimizer (EO-PID) and Archimede's Optimization algorithm (AOA-PID) used in recent literatures. The Electrochemical Society -
A review of reinforcement learning approaches for autonomous systems in industry 4.0
[No abstract available] -
A Review of Smart Grid Management Systems Using Machine Learning Algorithms for Efficient Energy Distribution
The smart grid is an intelligent electricity network that uses digital technology to improve the efficiency, reliability, and sustainability of power delivery. Machine learning is a type of artificial intelligence that can be used to analyze data and learn from it. This makes it a valuable tool for the smart grid, as it can be used to solve a variety of problems, such asorecasting energy demand, detecting, and preventing outages, optimizing power flows, managing distributed energy resources, ensuring grid security.In this article, we will review the use of machine learning in the smart grid. We will discuss the different machine learning algorithms that are being used, the challenges that need to be addressed, and the future of machine learning in the smart grid.. The Authors, published by EDP Sciences, 2024. -
A Review of the Detection of Pulmonary Embolism from Computed Tomography Images Using Deep Learning Methods
Medical imaging has been evolving at a steady pace generating enormous amounts of health data, and the use of deep learning (DL) has helped a great deal in processing the detailed data. Deep learning-based methods are used in different medical imaging tasks to detect and diagnose diseases. For example, medical imaging is used to diagnose pulmonary embolism (PE), a commonly occurring cardiovascular disease with high mortality and prevalence and a low diagnosis rate. According to medical experts, PE has resulted in many deaths because of missed diagnoses for the medical condition. Another critical aspect of the disease is the possibility of permanent lung damage if left untreated. The use of deep learning methods in medical imaging is attributed to their ability to use learning-based methods to process enormous amounts of data. However, there are some unique challenges in the detection of PE. PE is not specific in its clinical presentation and is easily ignored, making it difficult to diagnose. Deep learning-based detection methods help a great deal in the disease detection in miniature sub-branches of the alveoli, and images with noisy artifacts easily compared to manual diagnosis. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Review of Various Line Segmentation Techniques Used in Handwritten Character Recognition
Segmentation is a very critical stage in the character recognition process as the performance of any character recognition system depends heavily on the accuracy of segmentation. Although segmentation is a well-researched area, segmentation of handwritten text is still difficult owing to several factors like skewed and overlapping lines, the presence of touching, broken and degraded characters, and variations in writing styles. Therefore, researchers in this area are working continuously to develop new techniques for the efficient segmentation and recognition of characters. In the character recognition process, segmentation can be implemented at the line, word, and character level. Text line segmentation is the first step in the text/character recognition process. The line segmentation methods used in the character recognition of handwritten documents are presented in this paper. The various levels of segmentation which include line, word, and character segmentation are discussed with a focus on line segmentation. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Review on Advanced Nanomaterials for Antibacterial Applications
The management of infectious diseases is one of the major public health challenges of the 21st century. Mutation of the microbes, biofilm formation, and other structural-morpholo-gical behaviors have resulted in pathogens acquiring multi-drug resistance. The development of advanced materials that can provide long-lasting and effective protection against harmful microbes is becoming a need of the hour. Biocompatibility, efficient microbial inactivation, thermal and chemical stability of nanomaterials help to reduce the excessive use of antibiotics and, thus, to overcome antimicrobial resistance. Metal and metal oxide nanostructures, graphene, carbon dots, and other two-dimensional materials exhibit excellent antimicrobial properties. This review provides a comprehensive overview of antibacterial mechanisms and factors that help to inactivate the bacteria by nanomaterials. It also points out the enhanced antibacterial behaviors of the modified nanomaterials for future research concerns. 2023 Bentham Science Publishers. -
A review on anti-cancer plants of India
India has a high level of endemism and a diverse range of floral species. Cancer is one of the most significant challenges facing global health today. The indigenous peoples and residents who live in India have, for a very long time, made use of specific medicinal plants to fight cancer. This practice is still prevalent today. Several different drugs may be utilized in the treatment of cancer. Because of the potential drawbacks associated with such treatments and the development of drug resistance, the quest for new therapies that are both safer and much more effective is still the most challenging field of study. Several cancer medicines used today come from natural sources. We're returning to our old ways because medicinal plants are a good, natural way to make medicines that prevent cancer without causing major side effects. Within the scope of this study, a few herbs traditionally used to treat cancer are looked at to see what they might be good for. The cytotoxicity of these plants, the processes that lead to them, and the different compounds they make were looked into. This study has tried to focus on how these plants fight cancer. The Author(s).