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Identification Of Quality Of Tea Leaves By Using Artificial Intelligence Techniques: A Review
This paper summarizes the outcome of the survey carried out for quality identification of a tea leaf and eventually price prediction. Quality identification can allow to categorizing leaf in different grades, which helps the buyer and seller to acquire suitable quality to their need. Price prediction is an important feature, which can bring certainty at price and farmers can be benefitted more for their good quality. Additionally, if the leaf disease is identified at the initial stage that would also allow farmers to timely resolve the concerned issues and save their corps. In the field of agriculture, this has been always a research area to identify and predict the quality of tea leaves. Various artificial intelligence techniques are hot topics in the field of recognition and their effective combination can not only solve the problem but also enhance recognition accuracy. Therefore, there is an imminent need for a detailed survey on compiling techniques used for the identification of different varieties of tea plants. In this research, we aim to propose a review of the various techniques which can be utilized for determining the quality and price prediction. The Survey is hybrid with a combination of different artificial techniques, which is a suitable approach to target effective tea leaf identification. Further for the classification of tea leaf images, various algorithms can be combined as well to obtain better results and different algorithms can be used for feature extraction based on texture extraction, color extraction, and shape extraction. The Electrochemical Society -
Comprehensive Review on Video Watermarking Security Threats, Challenges and its Applications
Data is a crucial resource for every business, and it must be protected both during storage and transmission. One efficient way of securing data and transferring it is through digital watermarking, where data is hidden inside a medium like text, audio, or video. Video watermarking is visible or invisible embedded data on a video in a logo, text, or video copyright disclaimer. In this proposed paper, the goal is to analyze the characteristics of video watermarking algorithms and the different metrics used for them. It deals with the extent to which the different requirements can be fulfilled, taking into consideration the conflicts between them and the practical challenges of video watermarking in terms of attacks like geometric attacks and non-geometric attacks. It also focuses on the process of watermarking a video. Recent advances in data security indicate that employing a video watermarking technology to transmit private data will be an effective method of transmitting sensitive data. The Electrochemical Society -
Media and Urban Governance: The Quest for Sustainable Cities and Communities
Connectivity becomes the hallmark of network society facilitated by digital technologies. Cities are fundamentally well-connected, fast-growing, communicative, and global in outlook. Cities are also known for media concentration, as the structures and people there extensively create and exchange messages - social, political, economic, and cultural. The urban communication landscape is very complex, and therefore, a robust media and communication infrastructure is required to form, reform, and transform urban communities from a sustainable development perspective. Media not only perform the responsibilities of information dissemination and community building but also facilitate urban governance and public discourses on policies. The policy-making process that consists of policy inputs, policy processes, and policy outputs - is heavily influenced by the public discourses triggered by the media. Media can establish a policy issue at the center of the public sphere, set the policy agenda, and create public opinion. It inevitably leads to the mediatization of public policy. Media can effectively place SDGs at the center of the policy discourse and serve as a tool for urban governance by enhancing citizens' participation and helping to solve complex urban problems. This research paper explores various aspects of the governance-media interface in an urban landscape to create sustainable cities and communities. The Electrochemical Society -
Gender as a Predictor in the Perception of Sexual Harassment Definition
Sexual harassment is a pervasive problem across the globe and it is generally viewed subjectively. The review of the literature suggests that individual perception, history of past sexual harassment and other personal factors influence beliefs concerning the seriousness of the problem. The present study aims to explore the role of socio demographic variables in the definition of sexual harassment. One hundred and sixty-one college students volunteered for this study. Personal profile sheet and Sexual Harassment Definition Questionnaire were used to collect the data. The results of the chi-square test suggested that girls and students who already experienced sexual harassment found larger social incidents as harassment. However, the results of logistic regression found gender as a strong predictor of sexual harassment definition and the history of past harassment was failed to provide a statistical significance. Educating men on male privilege, violence against women and identifying behaviours in them that are not acceptable by women will be helpful. The Electrochemical Society -
Threat Intelligence Model to Secure IoT Based Body Area Network and Prosthetic Sensors
This research work proposes a threat intelligence model for Internet-of-Things (IoT) sensors-based Body Area Network (BAN). It is focused primarily to be used in healthcare monitoring of vital parameters of critically ill patients and on the contrary performance measurement system for healthy sportspersons. The end-point control based applications are growing enormously with the advent of IoT based sensors and actuators being used in intelligent real-time systems. At the same time, it is expected to keep the ecosystem safe for the user while delivering the constant updates. However, the process for the monitoring health and wellness parameters of a patient, or measuring endurance and performance of a sportsperson, it remains vulnerable without a secure environment. Using the proposed model, the entire healthcare ecosystem may be designed for the personalized medication of a patient who are using sophisticated life-saving device like prosthetic heart valve or an elderly person dependent on medical-aided ambulatory devices or a sportsperson on performance measurement system. The Electrochemical Society -
Towards a Smarter Connected Society by Enhancing Internet Service Providers' QoS metrics using Data Envelopment Analysis
This paper analyses wireline broadband Quality of Service (QoS) metrics of India's small and medium Internet Service Providers (ISPs). Key Performance Indicators (KPIs) used in this analysis are - Fault repair (>90% in 1 working day and >=99% in 3 working days), Response time to customer for voice-to-voice operator assistance (in 60 sec. >60% and in 90 sec. >90%), Broadband connection speed from ISP to node (Download speed) and Service availability/uptime. Benchmarks are arrived at, using the Slack Based Measure (SBM) in Data Envelopment Analysis (DEA). Twenty Decision Making Units (DMUs - ISPs) were used in the analysis with eight of them needing to improve their QoS on some of the mentioned parameters. Relative benchmark providers for all providers needing improvement with their weightage are found and optimal targets by each QoS metric is mathematically arrived at. The Electrochemical Society -
Exploring Sustainable and affordable Cancer Care using Artificial Intelligence
Now, in recent decades AI and ML have become a major part in developing and maintaining the healthcare system. Now, by using AI and ML in healthcare, it can provide a massive help for the healthcare workers.AI and ML help the healthcare workers for making better decisions, In some practical areas, it may take the place of human action for making decisions such as radiology, it can help to Gather medical knowledge or information from different journals, textbooks, or clinics which will help in reducing time for study and research. AI and ML help in predicting the early diagnosis of disease based on the patient's data and even help to prevent that dis-ease. Breast cancer is the most frequent category with an estimation of 2, 38,908 by 2025. Breast cancer is followed by lung cancer (1, 11,328); followed by mouth cancer (90,060). These statistics have triggered this research. Breast cancer is found in every one women among eight woman. Sustainable care shall help to fight with the disease. Sustainable care includes affordable cancer care and it's possible through early prediction of cancer. In this research we are using artificial intelligence based techniques for early prediction of cancer. Future direction of work will focus on usage of transfer learning and other models of AI-ML to help the society and mothers of nations to fight against the in-creasing spread of cancers. The Electrochemical Society -
Sustainable Interior Designing in the 21st Century - A Review
The concept of Sustainable interior designing has gained recognition in recent times. The study focuses on the history, growth and the future of sustainable interior designing. The main aim of the research was to review 102 select journal articles from various Sustainability, Interior designing and combined fields from 2001 all through to 2020, to provide an apprehension on the frequency, study methods, data collection and analysis procedures of the reviewed articles; Alongside providing the readers with an insight on the functionality, aesthetic appeal, client satisfaction and benefits to both environment and the clients. The study also sheds light on the important concepts of Biomimicry, Biophilia and Natural Luxury. The Electrochemical Society -
A Feminist Perspective on the Food and Gender based Marketing Narrative
Nutrition to the body is a basic element for sustenance and growth biologically, provided through food. This paper aims to understand why there is a difference between foods that are marketed gender-specifically to males and females separately. There have been a lot of participative changes in the household kitchen activities since the birth of the concept. However, certain things have continued to remain the same either as a result of tradition, preference, or systemic societal loop. This paper aims to categorically understand this patterned behaviour behind gender based food marketing and the consequent consumptions so as to find a more sustainable and inclusive approach for food marketing for the firms of this industry. The aim is also to shed light on the impact of such practices on the psychological level of the individual buyer that stems to form a pattern, creating a recurring practice out of habit, over internal choice. The Electrochemical Society -
Residual stress analysis on functionally graded 8% Y2O3-ZrO2 and NiCrAlY thermal barrier coatings
Thermal Barrier Coatings (TBCs) protect metallic components that operate in high temperature environments and enhance their service life. The conventional two-layered TBC system consists of a duplex ceramic top coat (TC) fabricated from 8 wt% yttria stabilized zirconia (8-YSZ) and an underlying bond coat (BC) comprised of intermetallic layers such as NiAl or MCrAlY (M = Co, Ni) etc. In the present study, functionally graded material (FGM) TBCs were fabricated by introducing a third blend layer of 8-YSZ and NiCrAlY, in between the BC and TC in order to enhance the thermal fatigue life of the TBC. The blend layer in FGM TBCs provides a smoother transition in thermal expansion properties between the metallic substrate and the top ceramic coat (8YSZ) which have widely different thermal expansion characteristics compared with each other. In service, thermal fatigue introduces severe tensile stresses between the coated layers and the substrates leading to ultimate detachment of the coatings from the substrates. In this work, residual stress analysis by Cos ? method was carried out as a non-destructive assessment tool to foresee the likelihood of onset of failure in the TBCs, well before the damage was visible. The two-layered (conventional) and three-layered (FGM) TBCs were synthesized on Inconel 718 substrates by atmospheric plasma spray (APS) technique. The TBCs were subjected to thermal fatigue tests between 1200? (by using gas flame) and ambient temperature and evaluated for residual stress analysis at different stages of thermal fatigue testing. The goal was to assess if residual stress analysis could be used to determine if the TBC was about to fail well before the delamination occurred and the catastrophic failure could be avoided. The tests conducted and results obtained are presented. 2022 -
A Comprehensive Study on Electric Vehicle Charging Infrastructure
Issues of global warming and hike in the fuel price have taken electric vehicles (EVs) to be popular among the ordinary people. But the main drawbacks are related to the vehicle price and the scarcity of charging infrastructure. In this paper, a review of various charging infrastructures of electric vehicles that are existing and emerging are discussed. The paper also gives an overview of the charging standards for EVs. The Electrochemical Society -
IMPACT OF ARTIFICIAL INTELLIGENCE ON E-BANKING AND FINANCIAL TECHNOLOGY DEVELOPMENT
Artificial intelligence has a significant impact on financial technologies. Machine learning is an important field of artificial intelligence. Machine learning is a subset of artificial intelligence. According to client knowledge gathered by machine learning, data structures may be more easily comprehended and changed. Machine learning, although still being employed in the IT business, has its own set of benefits. They are used by computer program to explain or solve a typical issue because they are a set of well-written instructions. Data inputs for factual research may be prepared by computers using master learning algorithms that can deliver results within a certain range. Computers are used to model test data, and frameworks are used to make automated decisions based on input data. Banks and financial institutions may benefit from the use of machine learning. This article discusses applications of machine learning in banking and finance sector. The Electrochemical Society -
eHED2SDG: A Framework Towards Sustainable Professionalism & Attaining SDG through Online Holistic Education in Indian Higher Education
To enable sustainable development of society it is essential to train the leaders and professionals of tomorrow. Developing a sustainable society and holistically developed future for budding professional is a significant objective of higher education Institutions. Every professional course learner is expected to utilize his skills, knowledge and time to contribute towards the development of society. Fostering sustainability in various domains of development is a requirement for Sustainable Development Goals (SDG). This research is inspired by multiple mental health related problems among professionals, inability to cope up with stress, quick dissatisfaction and frustrations, suicide, poor happiness quotient measured through multiple psychological tests and many other negative mental status which have paved the path for more serious approaches towards holistic development of young professions. This research addresses the SDG goal 4, Quality Education directly. Indirectly it can work as a catalyst to ignite the interest and create awareness about all the sustainable development goals. The Electrochemical Society -
A Systematic Review on Prognosis of Autism Using Machine Learning Techniques
Quality of life (QoL) and QoL predictors have become crucial in the pandemic. Neurological anomalies are at the highest level of QoL threats. Autism is a multisystem disorder that causes behavioural, neurological, cognitive, and physical differences. Recent studies state that neurological disorders can result in dysfunction of the brain or whole nervous system which may cause other symptoms of Autism. The paper focuses on reviewing various Machine Learning techniques used for diagnosing Autism at an early age with the help of multiple datasets. The study of brain Magnetic Resonance Imaging (MRI) provides astute knowledge of brain structure that helps to study any minor to significant changes inside the brain that have emerged due to the disorder. Early diagnosis leads to a healthy life by getting timely treatment and training. "Early diagnosis of autism spectrum disorder" is an objective and one of the prime goals of health establishments worldwide. The research paper aims to systematically review and find which machine learning algorithms are efficient for the prognosis of autism. The Electrochemical Society -
Perceived Reality of Self and Others with Two Childhood Trauma Survivors - An Idiographic Case Study
Impacts of childhood trauma can be crucial in understanding personality traits and psychological distress. However, it could be hard to predict if these individuals develop posttraumatic stress or growth. Several quantitative research studies have concluded the connections between childhood trauma and psychopathology or maladaptive personality traits. Various researchers have discovered the negative consequences of early childhood trauma and its long-term effects which may be rudimentary in understanding the causation of life-long psychological and medical deficiencies. This has been very elementary in understanding trait patterns and psychopathology for outcome generalizability and implementing prevention and intervention models. However, these studies still fail to spotlight the importance of the lived experiences of trauma survivors. Nevertheless, the present study is an idiographic single-case study research design used in the exploration of the lived experiences and perceived reality of self and others with two childhood trauma survivors. The Electrochemical Society -
Blockchain Enabled Model for Minimizing Post Harvest Losses
Post-harvest loss (PHL) leads to both decline in quantity and quality of food processing output from harvest to consumption. They can be caused by a wide range of circumstances, from growth conditions to retail handling. As storage loss is considered one among the detrimental factors, in this study, 25 data units were collected from a cold storage facility to analyze and focus specifically on post-harvest losses of vegetables. Various data analysis was carried out using SPSS tool. It was found that majority of losses were due to pest infection, weight losses due to climatic conditions, and transportation losses. On the other hand, block chain being a trend setter in the recent technology evolution which is providing fruitful outcomes in all the integrated fields, we have chosen the same for obtaining a better solution for the afore mentioned problem. Integrating blockchain technology into the structure can significantly reduce storage losses and support producer-consumer lines. The Electrochemical Society -
Ethnic Food: The Food Way Forward
In the context of food security, two things are significant. To ensure availability, affordability and accessibility of adequate food to people throughout the country. Also, to promote entrepreneurship for sustainable food production and supply. This paper highlights differences between food security and food insecurity. The global population in 2050 is predicted at 9 billion in which case the output must double considering the dwindling and degrading resources. This may be a challenge for agronomists and policy-makers. Considering that food security must be achieved at individual, household, district, national and global levels, India may need an Integrated Farming System (IFS) to take agriculture further. There are numerous challenges besides the environment that must be considered for this. It is important to ensure that the dignity of the farmer is not compromised while strategizing food security. Currently, private-public partnerships are being introduced in some places as a potential model. However, all stakeholders in food security have their task cut out (1). This paper is a review of existing literature to understand the level of information we have documented. It tries to highlight ways in which consumption of ethnic food could be a way forward in terms of food security and sustainability. The Electrochemical Society -
Effects of the Doctrine of Discovery: A Strive to build Sustainable and Peaceful Communities in North East India
The article analyses the Doctrine of Discovery which advocates racial superiority and colonisation of indigenous lands. Indigenous people of North East India continually strives for sustainable and peaceful situation. A strong relational bond between the ethnic tribes and the environment is fundamental for self-determination, sustainability and peace. Consequently, humans bond with land stirs a readiness to sacrifice their lives for their motherland juxtaposed in the precarious context of international boundaries and past colonial annexations. The colonial-influenced literature has moulded their ethnic identity. This further leads to an upsurge of emic historical and anthropological perspective writings, framing their history, interaction with the environment, the rise of ethnic consciousness and identity politics. There is a continuous struggle to free themselves from the colonial enslavement of the Doctrine of Discovery that has ultimately encroached on their land and culture. The Electrochemical Society -
Valorization of Fish Waste for Chitosan Production: A Sustainable Approach
Fish waste can be used as an ideal substrate for extraction of commercially important bio-polymers like chitosan. Chitosan is a versatile biopolymer with various biological and chemical properties such as biocompatibility, biodegradability and antimicrobial properties and can be a major applicant in different industries. The present research work focuses on extracting chitosan from fish scale waste through chemical extraction methods. Demineralization in this study is done using 1% HCl for 36 hours at 150 rpm and deproteinization is done using dilute 0.5N NaOH for 18 hours at 150 rpm. The final step deacetylation is done using a concentrated 40% NaOH solution at 90?C for 6 hours. The extracted chitosan had a yield of 12% per 100g of fish scale and characterization was done using FTIR, XRD, TGA and DSC. Further the possibility of fabrication of chitosan films followed by assessing their biodegradability will be the future scope of the work. The Electrochemical Society -
Impact of Childhood Trauma on Psychological Distress and Personality Pathology in Young Adults
Adulthood is a time of change, thus stressful. A predetermining factor to this is a provision for a safe environment during the crucial years of life (childhood). Children make meanings of everything and are more dynamic in the early developmental years. It is a basis for their overall development and defines their coping mechanisms during adulthood. Therefore, if they develop faulty meanings of themselves, others, and the world at large, it can alter their abilities to function during adulthood. It is fundamental to understand the psychological well-being and personality traits in adulthood by this very nature of traumatic experiences in childhood. This paper is a conceptual framework discussing a three-tier model to retrospectively understand the impact of childhood trauma on psychological distress and personality pathology in adulthood. This paper suggests future research to focus on developing intervention and prevention models for young adults (childhood trauma survivors) on positive parenting practices. The Electrochemical Society