Design for an Intelligent Waste Classifying System: A Case Study of Plastic Bottles

The use of plastic bottles has become a significant environmental concern, and recycling them has become a priority. Small and medium-sized recycling companies must collect and categorize large volumes of plastic bottles and sell them to larger recycling firms, a process that is time-consuming, costly, and labor-intensive. This manual sorting process can pose health risks, particularly during the COVID-19 pandemic, and can affect worker productivity. To address these issues, this study proposes the development of an automated conveyor belt system that can rapidly and accurately separate plastic bottles by type. The system utilizes an opaque and transparent plastic bottle separation platform, which saves time, cost, and manpower. This system design provides recycling SMEs with a competitive advantage by serving as a practical application model and a prototype with an easy-to-use concept. Key tools employed in this research include product design development (PDD), Kansei engineering, manufacturing process design, controlling system, and fault tree analysis (FTA). The light sensors are critical components in the separation process, detecting the opacity or transparency of the bottles' surfaces. The proposed prototype's reliability will be assessed by FTA, which considers all potential failures. This study contributes to the body of knowledge surrounding the integration of conveyor systems and provides valuable information for businesses seeking to optimize their sorting processes. The guidelines developed in this study can serve as a starting point for further research on the integration of conveyors in waste sorting plants. © 2013 IEEE.

Design and Development of Toroidal Core Winding Machine with Digital Interface

The small size and inherent superior electrical characteristics of a toroid has made it the first choice for many Original Equipment Manufacturers (OEMs). However, the lack of knowledge regarding the toroidal coil winding equipment is still hampering the growth of toroid as the first choice for transformers, inductors and other electrical applications. Additionally, due to Covid-19 pandemic and lockdown situation, small scale companies are lacking skilled manpower for the high precision task of toroidal core winding and taping. Although the machine is readily available in the market, the cost is still very high. Toroidal core winding machine is an equipment used for the purpose of winding toroidal cores which is used in various electrical machines such as current transformers, power transformers, isolation transformers, inductors and chokes, auto transformers, etc. This project aims to develop a low-cost toroidal winding machine with a user-friendly digital interface for selection of winding parameters as per the user input. The winding machine developed in this project is efficient and reliable with high-speed performance and negligible error. © 2022 IEEE.

DESIGN AND DEVELOPMENT OF ROBO MEDICAL ASSISTANT

The history of the medical robot is not very far from the first experiment in the 1980s. Nowadays robot in the medical sector plays a vital role in monitoring patient's health condition from distance. This paper aimed at developing an auxiliary medical solution that could provide a wide range of non-invasive diagnoses carried out by an automated robot whose motion can also be controlled manually using either a mobile application or voice command. The authors also incorporate modern features of video conferences and automated patient data management systems using the Internet of Things (IoT) which eventually facilitate medical practitioners in proper investigation from distance. The results of the clinical trial among 6 persons indicated that the robot could measure different health parameters properly using the proposed non-invasive method. The non-invasive results are verified by standard testing equipment and conventional clinical investigation and are also presented in this paper. The developed medical robot having a wide range of functionality could play a significant role in reducing human workload and ensuring timely medical assistance during a challenging crisis pandemic period like COVID-19. © 2023 IEEE.

Fluorine-a small magic bullet atom in the drug development: perspective to FDA approved and COVID-19 recommended drugs.

During the last twenty years, organic fluorination chemistry established itself as an important tool to get a biologically active compound. This belief can be supported by the fact that every year, we are getting fluorinated drugs in the market in extremely significant numbers. Last year, also ten fluorinated drugs have been approved by FDA and during the COVID-19 pandemic, fluorinated drugs played a very crucial role to control the disease and saved many lives. In this review, we surveyed all ten fluorinated drugs approved by FDA in 2021 and all fluorinated drugs which were directly-indirectly used during the COVID-19 period, and emphasis has been given particularly to their synthesis, medicinal chemistry, and development process. Out of ten approved drugs, one drug pylarify, a radioactive diagnostic agent for cancer was approved for use in positron emission tomography imaging. Also, very briefly outlined the significance of fluorinated drugs through their physical, and chemical properties and their effect on drug development.

Design and Development of Human Temperature Measuring System Using Drone Based Multispectral and Thermal Images

People's failure to maintain a social distance is causing the COVID19 virus to spread. We have used the drone thermal images for a maximum of 10 km of coverage to detect temperature and reduce virus spread areas. The part of the work is based on utilizing disinfectant spraying drones, disinfectant testing with the guidance of doctors, setting the path planning of drones for surveying the temperature of people, and monitoring the infected place using GPS. When the thermal camera of the drone detects the temperature values using remote sensing images, the drone covers crowded places like hospitals, cinemas, and temples using remote sensing images. One drone model is designed to provide present results using thermal images. The Proposed drone can cover an affected area of up to 16,000 square meters per hour for capturing remote sensing images. It predicts affected areas using faster CNN algorithms with 2100 thermal images. Thermal mapping is used to monitor the social distance between people, alert people that a virus is spreading, and reduce the risk factor of people's movement. In this paper, remote sensing images are analysed and detect higher temperature areas using thermal mapping (Messina and Modica in Remote Sensing 12:1491, 2020). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Mariotel: A web-based virtual remote computer science lab

This paper reports on the design, development and first use experience of Mariotel: a free-software project for deploying virtual remote computer science labs simply accessible from ordinary web browsers. Mariotel platform has been developed during the first generalized lockdown period due the Covid-19 pandemic situation. Simplicity has been the main principle that guided the design and development process of Mariotel. We show that this principle has largely contributed to the quick adoption of this new platform. The system has been successfully used at USPN since 2020. 42 different teachers have used the platform in order to supply ensure 9989 lab sessions, each has in average three hour duration. © 2022 IEEE.

Design and Development of Polymer-Based Optical Fiber Sensor for GAIT Analysis

In the present scenario like COVID-19 pandemic, to maintain physical distance, the gait-based biometric is a must. Human gait identification is a very difficult process, but it is a suitable distance biometric that also gives good results at low resolution conditions even with face features that are not clear. This study describes the construction of a smart carpet that measures ground response force (GRF) and spatio-temporal gait parameters (STGP) using a polymer optical fiber sensor (POFS). The suggested carpet contains two light detection units for acquiring signals. Each unit obtains response from 10 nearby sensors. There are 20 intensity deviation sensors on a fiber. Light-emitting diodes (LED) are triggered successively, using the multiplexing approach that is being employed. Multiplexing is dependent on coupling among the LED and POFS sections. Results of walking experiments performed on the smart carpet suggested that certain parameters, including step length, stride length, cadence, and stance time, might be used to estimate the GRF and STGP. The results enable the detection of gait, including the swing phase, stance, stance length, and double supporting periods. The suggested carpet is dependable, reasonably priced equipment for gait acquisition in a variety of applications. Using the sensor data, gait recognition is performed using genetic algorithm (GA) and particle swarm optimization (PSO) technique. GA- and PSO-based gait template analyses are performed to extract the features with respect to the gait signals obtained from polymer optical gait sensors (POGS). The techniques used for classification of the obtained signals are random forest (RF) and support vector machine (SVM). The accuracy, sensitivity, and specificity results are obtained using SVM classifier and RF classifier. The results obtained using both classifiers are compared. © 2023 Mamidipaka Hema et al.

Virtual Laboratory, a Learning Resource for Distance Education

Distance education programs have grown rapidly in recent years and have become even more massive because of the restrictions on movement due to the covid 19 pandemic. The development of information technologies has helped this teaching modality to have good results due to its autonomy and flexibility, however, it has some points of improvement especially in activities of practical nature. Virtual laboratories appear as a tool to support this type of activities. The success of these laboratories depends on several factors, not only imitating a face-to-face laboratory. This article proposes a methodology to guide the process of design and development of immersive experiences that allow the realization of laboratory activities in distance education mode. The objective is to ensure that the development of this type of experience becomes a resource to help the teaching-learning process, ensuring its contribution to the achievement of learning outcomes, allowing the validation of the knowledge acquired by students and helping the professor in the teaching of the course. The proposed methodology considers the opinion of the coordinating committee of the distance education program, students and professors. Its application is presented through a case study of a distance education program of an industrial engineering school in a Chilean university. © 2022 IEEE.

The Role of Natural Products as Sources of Therapeutic Agents for Innovative Drug Discovery

Emerging threats to human health require a concerted effort in search of both preventive and treatment strategies, placing natural products at the center of efforts to obtain new therapies and reduce disease spread and associated mortality. The therapeutic value of compounds found in plants has been known for ages, resulting in their utilization in homes and in clinics for the treatment of many ailments ranging from common headache to serious conditions such as wounds. Despite the advancement observed in the world, plant based medicines are still being used to treat many pathological conditions or are used as alternatives to modern medicines. In most cases, these natural products or plant-based medicines are used in an un-purified state as extracts. A lot of research is underway to identify and purify the active compounds responsible for the healing process. Some of the current drugs used in clinics have their origins as natural products or came from plant extracts. In addition, several synthetic analogues are natural product-based or plant-based. With the emergence of novel infectious agents such as the SARS-CoV-2 in addition to already burdensome diseases such as diabetes, cancer, tuberculosis and HIV/AIDS, there is need to come up with new drugs that can cure these conditions. Natural products offer an opportunity to discover new compounds that can be converted into drugs given their chemical structure diversity. Advances in analytical processes make drug discovery a multi-dimensional process involving computational designing and testing and eventual laboratory screening of potential drug candidates. Lead compounds will then be evaluated for safety, pharmacokinetics and efficacy. New technologies including Artificial Intelligence, better organ and tissue models such as organoids allow virtual screening, automation and high-throughput screening to be part of drug discovery. The use of bioinformatics and computation means that drug discovery can be a fast and efficient process and enable the use of natural products structures to obtain novel drugs. The removal of potential bottlenecks resulting in minimal false positive leads in drug development has enabled an efficient system of drug discovery. This review describes the biosynthesis and screening of natural products during drug discovery as well as methods used in studying natural products. © 2022 Elsevier Inc. All rights reserved

Introducing Ethics by Design in Engineering Education: Designing COVID-19 Tracing Apps

Including ethical concepts and considerations in engineering education has attracted significant interest in recent years, mainly due to the impact of some AI applications in different areas of our life. The use of case studies in teaching ethics is a well-known and useful approach. The debate related with a given case study helps students think about the implications, motivations and foreseeable impact of the technologies. This fact is in contrast with the common easy-thinking that technologies are neutral and that an engineer should not bother about ethics and does not have any responsibility at all. While many basic technologies may be considered neutral, more developed and complex systems are not so neutral;they have a motivation and some foreseeable impact and consequences. Thence, the main message is that engineers have a responsibility when developing these systems. This paper presents a case study used in a course for Ph.D. students in a Technical University to introduce the concept of ethics by design and to stress the idea of responsible conduct in engineering. The case under study is the design and development of tracing applications for fighting against the Covid-19 pandemic in 2020. The analysis of the case requires to understand the basic technologies proposed, the different alternatives considered at that time, the basic facts related with the contagion chain and the main factors to be addressed, the consideration of the balance between public health rights and individual privacy rights, and the social aspects related with the acceptability by citizens. © 2022 SEFI 2022 - 50th Annual Conference of the European Society for Engineering Education, Proceedings. All rights reserved.

Formal Concept Analysis Applications in Bioinformatics

The bioinformatics discipline seeks to solve problems in biology with computational theories and methods. Formal concept analysis (FCA) is one such theoretical model, based on partial orders. FCA allows the user to examine the structural properties of data based on which subsets of the dataset depend on each other. This article surveys the current literature related to the use of FCA for bioinformatics. The survey begins with a discussion of FCA, its hierarchical advantages, several advanced models of FCA, and lattice management strategies. It then examines how FCA has been used in bioinformatics applications, followed by future prospects of FCA in those areas. The applications addressed include gene data analysis (with next-generation sequencing), biomarkers discovery, protein-protein interaction, disease analysis (including COVID-19, cancer, and others), drug design and development, healthcare informatics, biomedical ontologies, and phylogeny. Some of the most promising prospects of FCA are identifying influential nodes in a network representing protein-protein interactions, determining critical concepts to discover biomarkers, integrating machine learning and deep learning for cancer classification, and pattern matching for next-generation sequencing. [ FROM AUTHOR]

Design and Development of Virtual Autopsy System for Teaching Medical Undergraduates

In recent decades, the utilization of autopsies as a teaching tool in undergraduate medical education is facing many challenges due to the nature of the medico legal issues. Aside from that, school closures and remote or hybrid learning environments manifested during Covid-19 pandemic have created more challenges for educators. Students are missing out the autopsy-based teaching, which provide various advantages. Moreover, it is difficult to assess students in ways that encourage and empower them to progress. Fortunately, the technology has the potential to provide a virtual museum with an interactive cadaver of several case studies, each with its own history and narrative beside, quizzes and assessments that give educational reasoning, analyze and track the user's learning. The objective of this research is to establish a virtual system for teaching the basis of Forensic medicine to medical students. The system is developed as a web based system, moreover this research uses Agile development approach as the methodology for this system development, the platform is developed to provide a single platform for material, assessment and feedback. Therefore, including 3 stages of the teaching and learning process, the system include scope for educators and learners as well. © 2022 IEEE.

Long COVID Diary - Design and Development of a Support Application for People with Long COVID

Due to the COVID pandemic more and more people suffer from mid-to long-term problems associated with it. COVID can also cause a wide range of health issues over a longer period of time, which has been called Long COVID. Due to the wide range of symptoms and the fact that Long COVID is relatively new, there is a lack of applications supporting Long COVID patients. In this paper, a newly developed solution of a Long COVID patient support application is being discussed. It is based on the previous identification of requirements from questionnaires of patients with Long COVID, where they expressed their needs and wishes for such a solution with additional identified ones. This paper focuses on designing and developing an application containing the respective derived requirements to help and support people suffering from Long COVID. © 2022 IEEE.

Formal Concept Analysis Applications in Bioinformatics

The bioinformatics discipline seeks to solve problems in biology with computational theories and methods. Formal concept analysis (FCA) is one such theoretical model, based on partial orders. FCA allows the user to examine the structural properties of data based on which subsets of the dataset depend on each other. This article surveys the current literature related to the use of FCA for bioinformatics. The survey begins with a discussion of FCA, its hierarchical advantages, several advanced models of FCA, and lattice management strategies. It then examines how FCA has been used in bioinformatics applications, followed by future prospects of FCA in those areas. The applications addressed include gene data analysis (with next-generation sequencing), biomarkers discovery, protein-protein interaction, disease analysis (including COVID-19, cancer, and others), drug design and development, healthcare informatics, biomedical ontologies, and phylogeny. Some of the most promising prospects of FCA are identifying influential nodes in a network representing protein-protein interactions, determining critical concepts to discover biomarkers, integrating machine learning and deep learning for cancer classification, and pattern matching for next-generation sequencing.

Virtual Reality Environment as a University Online Education Platform

The recent COVID-19 epidemics resulted into much more extensive online distance education at all universities. The growing power of Information and Communication Technologies allowed considering educational approaches unimaginable recently. The return to the previous stage is many university educators' desire. At the same time, no one can exclude similar emergency situations in the future. The universities and their educators have to be better prepared for them. In this paper, we outline a solution: the creation of a 'mirror' image of a real campus in a Virtual Reality Environment. The quotation marks indicate the fact that the VRE should not only replicate the study programs but imitate the university climate. Design and development of such campus is undergoing;the first pilot projects had run and are now evaluated. The paper analyses the key advantages it offers and drawbacks it may bring. © 2022 IEEE.

Design and Development Integrated Sensor System for Measuring Body Temperature and Heart Rate

Heart rate and body temperature are some of the important components of a person's main vital signs that need to be monitored regularly and periodically. The detection system technology continues to develop which allows a person to detect his own condition, to avoid exposure to COVID-19. However, the tools that are developing in the market are quite expensive and sometimes complex in operation because they are external products, so that it becomes a difficulty in itself. For this reason, it is important to design a detection device with sensor components that exist in the country and with a simple design so that it is easy to operate and inexpensive. In this paper, utilizing pulse sensors and AD8232 sensors to detect heart rate and MLX90614 sensors to measure body temperature, then NodeMCU ESP8266 to process sensor signals received and will be forwarded to the Display (LCD) to display the results carry out the design and development of an integrated sensor system. From the research results, the accuracy of the MLX90614 temperature sensor is very good with the achievement of 99.24% and the pulse sensor with the achievement of 98.86%. For the test results on each sample obtained accuracy values of 98.4% and 99% for the temperature sensor, and 92.3% and 92.2% for the pulse sensor, respectively. From these results, it is very clear that the sensor design deserves to be promoted as a quality product. © 2022 IEEE.

Design and Development of Virtual Lab Environment for Embedded System and IoT Applications

In recent years, the education officials have been forced to cancel classes and close the doors of the campus across the world in response to the growth of coronavirus outbreak. Due to the development of e-learning, a significant transformation is happening in education. Digital platforms are used in e-learning for giving instructions remotely. The faculty chose to take video conference classes using one platform and the resources are uploaded in another platform which are accessed by students. But while coming to laboratory classes, the hands-on experience of students on the equipment and components are totally missed. Resources are in the colleges and students are at home. This separation creates a long gap in the education. At KPR Institution of Engineering and Technology (KPRIET), a virtual lab setup with controllers and essential hardware modules was implemented in the Internet of Things (IoT) laboratory of Electronics and Communication Engineering (ECE) Department, where students can access and control it from their current location using secured login credentials.Virtual setup provides an easy access for the students to get hands-on experience with the academic laboratory sessions. These sessions are very useful for the students to gain more relevant and keen knowledge of their laboratories. This project provides a greater number of students to engage with their academic theory and practical laboratory sessions. We use server software and addons along with Remote Desktop Protocol (RDP) as well as Virtual Network Computing (VNC). © 2022 IEEE.

6th KidRec Workshop: Information Retrieval Systems for Children in the COVID-19 Era

The role that technology plays in supporting children at school and at home is more prominent than ever before due to the global COVID-19 pandemic. This has prompted us to focus the 6th International and Interdisciplinary Perspectives on Children & Recommender and Information Retrieval Systems (KidRec) workshop on what the lasting changes will be to the design and development of child information retrieval systems. After two years, are information retrieval systems used more in and out of the classroom? Are they more interactive, more or less personalized? What is the impact on the research and business community? Are there long-term and unexpected changes on the design, ethics, and algorithms? The primary goal of our workshop continues to be to build community by bringing together researchers, practitioners, and other stakeholders from various backgrounds and disciplines to understand and advance information retrieval systems for children. © 2022 Owner/Author.

Design and Development of Pulse Oximeter Using Internet of Things

With the recent Covid-19 pandemic put break, people are becoming more conscious on checking their SpO2 (Percentage of Oxygen in our blood) and heart rate levels. The pulse oximeter is a widely used clinical instrument for performing effortless testing via a non-intrusive method. The proposed system is a smart device that has been used to monitor the health vitals and monitoring these vitals can help us to track the SpO2 and heart rate. The proposed device comprises of simple components such as a MAX30100 pulse oximeter sensor and an ESP8266 Node MCU. This device can be connected to Blynk App to monitor the regularly updated data through the web by connecting to a Wi-Fi. In addition to this, the SpO2 percentage and heart rate can also be observed on the OLED Display. The proposed system can assist in detecting the health abnormalities like pneumonia, asthma, and many other respiratory diseases. © 2022 IEEE.

Design and Development of Machine Learning Techniques for Disease Prediction

Machine Learning is ever advancing field and as more and more research is being done in the field, more applications are being developed for this field and it is now being used in all fields. Also, nowadays people are facing multiples diseases posing danger to human life. This prompted researchers to critically analyse and work to apply Machine learning in the use of prediction of these diseases and using this analysis to assist the medical industry. The idea is to find various datasets of different Diseases like Dengue, Covid-19. Perform analysis on the datasets of these diseases to understand more about them and how much they affect us. There are various models available like KNN, SVM, etc. The task is to work with different models and find out how they perform with data of different diseases and which models are most affective and accurate. © 2022 IEEE.