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The hesitant Pythagorean fuzzy ELECTRE III: An adaptable recycling method for plastic materials
In this research article, introduce a novel decision making method called HPF-ELECTRE method by extending the ELECTRE III (ELimination and Choice Expressing REality) method with HPF (Hesitant Pythagorean Fuzzy) set. The efficiency of the new method is testing in the plastic recycling problem. One of the most hazardous domestic materials is plastic. The low biodegradability nature of plastic is a serious threat to the environment and to human life. Plastic is a synthetic chemical that do not belong to the natural world. Owing to the non-biodegradability, the only way to deal with this modern-world problem is recycling. Finding a suitable recycling method for disposing and recycling plastic materials is a major research issue. Propose the HPF-ELECTRE III method to find out the adaptable recycling method for plastics materials. The outranking in HPF-ELECTRE III method expand on concordance and discordance acceptability value values. Established method is an effective tool for decision making problems. 2020 Elsevier Ltd -
Smart Online Oxygen Supply Management though Internet of Things (IoT)
We are surrounded by oxygen in the air we We cannot even exist without the ability to breathe. The need for oxygen has increased during the COVID19 pandemic, and although there is enough oxygen in our country, the main issue is getting it to hospitals or those in need on time. This is simply due to a significant communication gap between suppliers and hospitals, so we plan to implement an idea that will close this gap using real-time tracking as we can track the movement of oxygen tankers by gathering the requirements. We are using an ESP32 Wi-Fi module, a MEMS pressure sensor that enables the combination of precise sensors, potential processing, and wireless communication, such as Wi-Fi, Bluetooth, IFTTT, and MQTT protocols, to implement it successfully. The pressure sensor publishes the value of oxygen remaining from the location to the MQTT broker. 2022 IEEE. -
A Precise Computational Method for Hippocampus Segmentation from MRI of Brain to Assist Physicians in the Diagnosis of Alzheimer's Disease
Hippocampus segmentation on magnetic resonance imaging is more significant for diagnosis, treatment and analyzing of neuropsychiatric disorders. Automatic segmentation is an active research field. Previous state-of-the-art hippocampus segmentation methods train their methods on healthy or Alzheimer's disease patients from public datasets. It arises the question whether these methods are capable for recognizing the hippocampus in a different domain. Therefore, this study proposes a precise computational method for hippocampus segmentation from MRI of brain to assist physicians in the diagnosis of Alzheimer's disease (HCS-MRI-DAD-LBP). Initially, the input images are pre-processed by Trimmed mean filter for image quality enhancement. Then the pre-processed images are given to ROI detection, ROI detection utilizes Weber's law which determines the luminance factor of the image. In the region extraction process, Chan-Vese active contour model (ACM) and level sets are used (UACM). Finally, local binary pattern (LBP) is utilized to remove the erroneous pixel that maximizes the segmentation accuracy. The proposed model is implemented in MATLAB, and its performance is analyzed with performance metrics, like precision, recall, mean, variance, standard deviation and disc similarity coefficient. The proposed HCS-MRI-DAD-LBP method attains in OASIS dataset provides high disc similarity coefficient of 12.64%, 10.11% and 1.03% compared with the existing methods, like HCS-DAS-MLT, HCS-DAS-RNN and HCS-DAS-GMM and in ADNI dataset provides high precision of 20%, 9.09% and 1.05% compared with existing methods like HCS-MRI-DAD-CNN-ADNI, HCS-MRI-DAD-MCNN-ADNI and HCS-MRI-DAD-CNN-RNN-ADNI, respectively. 2022 World Scientific Publishing Europe Ltd. -
IoT innovation in COVID-19 crisis
The COVID-19 pandemic is a current global threat that surpasses provincial and radical boundaries. Due to the onset of the pandemic disease, the whole world turned entirely in a couple of weeks. Its consequences have come across the personal and professional life of human beings. The current situation focuses on precautions such as wearing a mask, maintaining social distancing, and sanitizing hands regularly. An innovative platform, and smart and effective IoT technology may be applied to follow these steps. This platform fulfills all critical challenges at the time of lockdown situations. IoT technology is more helpful in capturing real-time patient data and other essential information. IoT allows the tracing of infected people and suspicious cases and helps diagnose and treat patients remotely. It also paves the way to deliver essential medical devices and medicines to quarantined places. In the present ongoing crisis, IoT technology is inevitable in monitoring patients infected with COVID-19 through sensors and intertwined networks. The consultations are given to the patients digitally through video conferencing without meeting the medical expert in person. After the diagnosis is made digitally, IoT devices are used to track health data. Smart thermometers are used instead of traditional ones to collect valuable health data and share it with experts. The IoT robots are now a proven technology used for cleaning hospitals, disinfecting medical devices, and delivering medicines, thus giving more time to healthcare workers to treat patients. 2023 Bentham Science Publishers. All rights reserved. -
Impact of Risk Perception on Use and Satisfaction with Online Pharmacies and Proposed Use of IoT to Minimize Risks
This study investigates consumer risk perceptions regarding online pharmacies and their impact on usage frequency and satisfaction. The growing popularity of online pharmacies offers benefits such as accessibility, cost savings, and privacy. However, significant risks, including the potential for counterfeit drugs and insufficient medical oversight, raise concerns. This study has measured consumer perceptions of risk, satisfaction, and usage frequency through a survey conducted in Northeast India, excluding Sikkim (online) and Sikkim (offline). The findings reveal that the fear of receiving counterfeit medications is a significant risk factor, negatively influencing both the frequency of use and consumer satisfaction. Despite this, the impact is relatively weak, suggesting that while risk perception is a concern, it does not significantly deter online pharmacy usage. The study suggests that integrating advanced technologies such as IoT, RFID, and blockchain can mitigate these risks by ensuring the authenticity of medications in the supply chain. 2024 IEEE. -
Inter-relational dynamics of factors affecting the emergence of orphan drugs; [Dynamique interrelationnelle des facteurs influennt lergence des micaments orphelins]
Orphan drugs are medications that are produced for the treatment of rare diseases. As there is less number of patients, the drug manufacturing companies are not keen in producing these drugs. Due to high costs of research and development and low profitability, companies do not want to invest in manufacturing of orphan drugs. Several laws have been passed by Governments of different nations to encourage the development of orphan drugs and make it available to patients. This study explores the interrelation dynamics of factors that has resulted in the greater availability of orphan drugs in recent times. Ten factors: internet technology, legislation, online patient support groups, government subsidiary, biotechnological advancements, corporate social responsibility, awareness and diagnosis of rare diseases and exclusive budgeting by pharmaceutical industries for orphan drugs related research and development and production were taken for the study. With a sample size of 38 experts, the technique of decision-making trial and evaluation laboratory (DEMATEL) was used for the study. It was found that information technology, legislation, support groups, and budget were the causes and the factors awareness, diagnosis, medicine availability, subsidiary, CSR and biotechnology emerged to be the effect. 2024 Acadie Nationale de Pharmacie -
Kerala Development and the Attapadi Adivasi
The development experience of the state of Kerala in southwest India is based generally on democratic principles of equality and popular participation. This article focuses on the lives of the Adivasi1 people of Attapadi in the Palakkad district of Kerala. It argues that the state of Kerala largely treats the Adivasis as secondary citizens and ignores their right to be socially and economically empowered. The state of Kerala takes pride in its positive ranking on human development and social progress indexes but has not done enough to stop Adivasi infants from dying of malnutrition, and Adivasis demands for land rights have been disregarded. As a result, they are forced to live obscure lives in poverty and generally unable to influence their sociopolitical sphere. 2023 The Author(s). -
The Kerala, India Experience of Facing the COVID-19 Pandemic
Kerala, a southwestern state of India, reported the first COVID-19 case in India. Its alert health department went into a detailed preparation to face the pandemic and its related effects. Kerala soon earned international attention for its handling of the COVID-19 emergency. Some of the factors that are outstanding about Kerala, apart from its achievements in education and healthcare, are decentralized governance, active public involvement, and a high level of womens participation. This chapter explores Keralas COVID-19 crisis management during the first phase of the pandemic. It explains how the welfare system of Kerala, which is the outcome of the years of accountable governance, has worked to provide a protective safety net to the people of Kerala. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022. -
Surface-engineering of carbon fibre paper electrode through molecular imprinting technique towards electrochemical sensing of food additive in shrimps
Excessive usage of food additives needs to be extensively examined and regulated. Herein, we report the development of an exceptionally proficient and practical electrochemical sensor for the quantitative determination of 4-hexylresorcinol (4-HR) in shrimps using a molecularly imprinted conducting polymer. By electropolymerizing 2-aminothiazole (AT) on the surface of a carbon fibre paper electrode (CFP) in the presence of 4-HR imprinted polymer films were developed. Bulk-electrolysis was used to produce definite imprinting sites and regulate the release of 4-hexylresorcinol templates. Voltammetric study reveals that the synthesized conducting polymer has outstanding electroactivity towards 4-HR and enables quick electron transfer kinetics. This MIP sensor has a detection limit of 6.03 nM for 4-HR. The modified CFP electrode has been found to be extremely selective to 4-HR due to its intensive contact via intermolecular hydrogen bonding. The modified electrodes were characterized by Scanning Electron Microscopy, Fourier Transform Infrared spectroscopy, Optical profilometry, and X-ray Photoelectron Spectroscopy. 2022 Elsevier B.V. -
Platinum decorated phosphorous doped graphitic carbon nitride supported molecularly imprinted carbon fibre electrode as a nano-interface for the detection of butylated hydroxy anisole
This research generated an electrochemical sensor using a carbon fibre (CFP) paper electrode coated using platinum-decorated phosphorous doped graphitic carbon nitride (Pt/PgCN). This sensor was designed to detect butylated hydroxy anisole (BHA) selectively and sensitively. The molecularly imprinted polymers (MIPs) were synthesized onto the Pt/PgCN coated CFP surface through electropolymerization using BHA as a template and 3-thiophene acetic acid as monomer. Numerous analytical methods were used to characterise the sensor electrode, including cyclic voltammetry, impedance spectroscopy, and electron microscopy. The results showed that the synergetic effect of PgCN, Pt nanoparticles, and PTAA, PgCN and Pt had a positive impact on the electrochemical detection, the sensor's linear range was determined to be between 5 10?10 M and 2.1 10?7 M. The sensor demonstrated excellent stability, good reproducibility, and high selectivity for detecting BHA. Moreover, the proposed sensor successfully detected BHA in real samples. 2024 Elsevier Ltd -
Single-monomer dual templated MIP based electrochemical sensor for tartrazine and brilliant blue FCF
In this study, a dual-templated molecularly imprinted polymer-based electrochemical sensor was developed for the simultaneous analysis of two food additive dyes, brilliant blue FCF and tartrazine. Using a 3-aminophenyl boronic acid (3-APBA) monomer and the dual templates of brilliant blue FCF (BB) and tartrazine (TZ), the molecularly imprinted polymer (MIP) layer was electropolymerized on the carbon fibre paper (CFP) electrode. By using BB and TZ as template molecules along the electro-polymerization of 3-APBA, then removing both template molecules, the MIP film was generated on the surface of the CFP electrode. Due to the high surface area provided by modification, several complementary binding sites for template molecules are formed on the surface of the MIP sensor during this process of sensor fabrication. On the MIP/CFP electrode, the electrochemical behavior of BB and TZ was assessed. The monomer/template ratio, pH values, and influencing parameters like the electro-polymerization scanning cycles were all optimized. This sensor was applied to detect brilliant blue FCF and tartrazine in beverage and food samples using MIPAPBA/CFP electrode. 2023 -
VNPR system using artificial neural network
Vehicle number plate recognition (VNPR) is a technique used to extract the license plate from a sequence of images. The extracted information in the database can be used in the applications like electronic payment systems such as toll payment, parking lots etc. An effective VNPR can be implemented based on the quality of the acquired images. It is used for real time application and it has to recognize the number plates of all types under different environmental conditions. Different algorithms has been used which depends on the features present in the images. It should be generalised to extract different types of license plate from the images. In this paper we propose a new method which is robust enough to recognize the characters from the number plates with help of artificial neural network. This algorithm is practical for the front view and rear view of orientation of the vehicle. 2016 IEEE. -
Design optimisation and fabrication of amino acid based molecularly imprinted sensor for the selective determination of food additive tartrazine
In this work, we developed a new molecularly imprinted polymer detector for tartrazine's rapid and selective detection. Electropolymerisation using L-Methionine resulted in the polymer immobilised on the carbon fibre paper electrode's surface. MIP film was formed by electropolymerisation in the presence of the template tartrazine. The polymer frame comprises cavities after template removal, which can specifically bind to the analyte molecule. Without pre-treatment, the developed sensor MIPMet/CFP detects tartrazine in beverage samples precisely and rapidly. The sensor has a linear response in the concentration range of 0.6 nM- 160 nM, high sensitivity (601964 AM-1cm?2), and a low detection limit of 27 pM under optimum conditions. MIPMet/CFP sensor displayed the ability to distinguish target analyte from interferants selectively. The performance of the MIPMet/CFP sensor in assessing tartrazine in different saffron powder and packed juice samples suggests that it could be used to detect tartrazine fast and effectively. 2022 Elsevier Ltd -
A Deep Learning Method for Autism Spectrum Disorder
The present study uses deep learning methods to detect autism spectrum disorder (ASD) in patients from global multi-site database Autism Brain Imaging Data Exchange (ABIDE) based on brain activity patterns. ASD is a neurological condition marked by repetitive behaviours and social difficulties. A deep learning-based approach using transfer learning for automatic detection of ASD is proposed in this study, which uses characteristics retrieved from the intracranial brain volume and corpus callosum from the ABIDE data set. T1-weighted MRI scans provide information on the intracranial brain volume and corpus callosum. ASD is detected using VGG-16 based on transfer learning. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Marital Stress and Domestic Violence during the COVID- 19 Pandemic
Marital stress and domestic violence is prevalent in every society around the world. It has become a major concern during the Covid-19 pandemic. Governments have resorted to lockdown measures in order to contain the pandemic. The pandemic has made the weaker and more vulnerable people in a household more exposed to abusive partners. Social isolation and home confinement have detrimental effects on ones mental and physical well-being. Women have been shown to be at a very high risk from violence during The Covid19 pandemic. The research paper aims to understand the factors which compel women to stay in abusive and stressful marriages and the ways in which they can be empowered to lead their life with dignity and self-respect. The cultural contexts of most societies force women to stay in abusive marriages as the woman is often portrayed as the symbol of unity in families. Understanding the cultural bindings of women trapped in abusive households during the COVID-19 pandemic is a very crucial aspect as this can help in understanding the fear and apprehensions of women trapped in destructive marriages. This can be a key factor which can make it easier for support groups while providing counselling and other kinds of support to women trapped in abusive marriages. The paper also discusses the impact of abusive relationships on children and how it negatively shapes their personality and their emotional well- being. 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Cognitive technology for the Indian higher education: A Language teaching and Learning application
Past decade witnessed a technological boom in the world. Regardless of the age every person in the world owns a mobile device which can be connected to internet. The technologies and applications for these mobile devices are one of the inevitable part people's day to day lives. The past decade also evidenced the development of Artificial Intelligence, Machine Learning (ML), Natural Language Processing (NLP), Image Processing (IP), Speech Recognition (SR) and Big DataAnalytics (BDA), etc. which lead to the development of Intelligent applications for the fields like business, health care, weather, media, etc. The field which uses the technology in a slow pace is education system. This paper is majorly focused on the Indian higher education system and the technologies used in their teaching and learning. One of the major drawbacks of Indian higher education system is the traditional teacher centric teaching and learning process. The usage of technology in their education system limited to chock and board to power point presentation. Some of the elite Universities in India uses Massive Online Open Courses (MOOC) but majority of the education institution still follows the old method of teaching and learning. This paper profiles cognitive technology based applications which can be used for the betterment of current system. The proposed model in this paper is for the language course learning. The application is centered on ML and NLP. Copyright 2019 American Scientific Publishers All rights reserved. -
Psychological capital as an antecedent of employee engagement and its relationship with intention to stay
Employee engagement is an evolving concept in human resources (HR). Most organizations strive to attain employee engagement because of the various organization-related outcomes. It is important for employees to feel engaged emotionally, socially, and intellectually with the work and organization. Various antecedents affect employee engagement and, in turn, result in an organization-related positive outcome. This chapter discusses in-depth PsyCap as an antecedent of employee engagement and how it relates to intent to stay regarding employees working in travel organizations in India and aims to build relevant theoretical frameworks based on the findings. The chapter also discusses some strategies organizations can implement to achieve employee engagement based on the findings. 2022, IGI Global. -
Social Characteristics and Its Relationship with Intent to Stay-with Reference to Financial Sectors
One of the challenging tasks of the HR management of the organization is to design the job in such a way that facilitates a good work culture/atmosphere for the employees to ensure their stay in the organization. The present study analyzed the role of social characteristics of the job with their intention to leave among the employees working in the finance sector. Primary data were collected from 250 employees working at all levels of management in the finance and banking sector in Indias southwest region through the Convenience sampling method. Morgeson and Humphrey (2006) developed the work design questionnaire which was adopted and used for data collection. Hierarchical multiple regression used for applied for data analysis. The results show that social characteristics cannot predict intent to stay. Also, age and gender do not have a significant role as mediating factors to social characteristics and intent to stay. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Health informatics and its contribution to health sectors
In most developed countries, healthcare sectors take more than 10% of the GDP, and it is one of the most significant and most rapidly growing sectors globally. With such growth of the healthcare department, data management becomes challenging; a robust platform helps to address these challenges. Health Informatics (HI) is an upcoming development, an interdisciplinary field in healthcare sectors; it combines the Internet of Things (IoT) and Artificial Intelligence (AI) in the healthcare software, which helps boost the overall operational efficiency of the healthcare departments. These AI algorithms integrated into IoT devices help acquire, store, retrieve, and use health and medical-related data. Patient data are enormous in healthcare sectors, and it is required for various purposes by hospital administrators, insurance agents, doctors, nurses, and other health departments. Accessing and managing these datasets often becomes challenging; HI is one of those innovations that has helped address these challenges to a large extent. The chapter discusses informatics, related definitions, HI, and its relation with other disciplines. The chapter also provides an educational overview of the evolution of HI, different HI technologies, benefits and challenges of HI to its various stakeholders. It ends with some thoughts on HI's future growth. The Institution of Engineering and Technology 2023. All rights reserved. -
Quarantined effects and strategies of college students COVID-19
Purpose: The world is battling with one of the biggest health crisis caused by novel COVID-19. This paper aims to understand the effect of quarantine on the psychological health of college students and the coping strategies adopted by them. Design/methodology/approach: The study adopted the interview method and focused on two crucial open-ended questions: how quarantine has impacted and what are the strategies adopted to overcome the same. The response was recorded through email and phone from a sample of 30 students. Findings: Most of the students stated that they are going through issues like anxiety, depression, infection fear, ambiguity due to this pandemic and the lockdown related to it. However, they engage themselves with various activities that help them to combat this situation. Practical implications: Education institutions can focus on conducting online fest and other events to engage students more productively. They can also focus on developing a wellness application to support these students. They can provide solutions and tips to balance mental health and wellness during these times. Originality/value: Everyone knows about COVID-19 and the measures taken related to it, but not much about the impact of it on mental health. This paper discusses the negative impact of quarantine on students and coping strategies adopted by them. The strategies mentioned in the study can guide quarantined people, student community, parents, counsellors and academic facilitators to handle the situation in a better way. 2020, Emerald Publishing Limited.