Volume 11 | Issue 5

 Abstract

The handloom industry has a rich history and cultural significance in many countries around the world, but it also faces numerous challenges in today's global marketplace. This article provides a comprehensive overview of the handloom industry, including its historical development, market trends, government policies, challenges, success stories, and opportunities for growth. The article also explores the role of NGOs and community-based organizations in supporting handloom weavers and provides recommendations for promoting the sustainable development of the handloom industry, including the use of innovation, technology, and marketing strategies. The article highlights the importance of collaborative efforts between governments, the industry, NGOs, and consumers to preserve this important cultural tradition and ensure that handloom weavers around the world can continue to thrive in the 21st century.

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 Keywords

Handloom industry, Traditional craft, Market trends, Government policies,, Challenges, Success stories, Innovation, Technology, Marketing strategies, NGOs.

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Today, it is quite challenging for people who are autarkic to take their medications. Therefore, the purpose of this study is to remind patients to take their prescribed medications on time and to track their medication adherence. The suggested system makes use of sensors and smart devices to monitor medicine use and inform patients via different means, such as voice assistants or mobile applications. By analysing the collected data, healthcare professionals may see trends and possible problems with drug administration and take necessary action. The medicine reminder system using IoT has the potential to improve medication adherence, reduce healthcare costs, and improve patient outcomes.

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IoT mobile app, LCD Display, IR Sensors, Node MCU, Battery, Speaker, Keypad, Potentiometer, APR9600

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A Secure Message Transfer Using ECC Algorithm is a web based application. The Elliptical Curve Cryptography(ECC) algorithm enables secure message sharing by encrypting and decrypting data using elliptic curve over finite fields. Compared to more established public- key cryptography algorithms like RSA,ECC is a kind of PKC that is thought to be more efficient and safe. Using encryption technology to transform messages into unreadable formats that can only be decoded by the intended receiver with right decryption key is a common practice in secure message sharing. Even if the message is intercepted by an attacker, encryption ensures that they won't able to read it. When sending private or sensitive information like financial information, medical records, or personal details, secure message sharing is very crucial. Data protection benefits both people and organization from data breaches and other forms of cyber attacks.

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 Keywords

Encryption,Decryption,ECC,PKC

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pumpkin (cucurbitacae) has been considered as an important nutritional and medicinal plant due to its health-promoting properties .It is growth in North America about 9000 years ago. The region was pumpkin are cultivated in India: Madhya Pradesh, Orissa and Uttar Pradesh .Its peels are present to investigate functional and nutraceutical constituents. It is rich source of nutritional components like oils, proteins, carbohydrates and minerals. Compounds including phenolics, flavonoids, tocopherols and carotenoids. The aim of study was to standardize the various food products pumpkin peel flour is incorporated with oats meal flour. Oats flour was such ingredients as crude protein, fat, crude fibre and ash. Due to their many benefits such as lowering blood sugar and cholesterol levels. Product was prepared by pumpkin peel powder, oats flour and All-purpose flour. This product was evaluated by a sensory panel member

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pumpkin peel, oats meal flour, mixing and baking

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Reading skill is the bedrock of almost all process of learning which necessitates learners not only to acquire language, but also to learn other subjects. It is an indispensable skill every child needs to acquire in primary school before entering secondary school. Unfortunately, majority of our children in primary schools cannot read effectively before proceeding to secondary school. The current piece of research delineates the levels of teacher competencies in developing pre-reading, while-reading ,post-reading and total reading skills of Secondary school learners in the State of Telangana with special reference to their gender. The sample constitutes Seven hundred (700) teachers working in the Secondary Schools of the State of Telangana. Simple random sampling technique was employed to elicit information from the selected sample. A self-designed questionnaire was developed keeping in view the objectives and hypotheses of the study. It was composed of two parts. Part- A was designed to gather the profile variates of the teacher-respondents in terms of the following personal characteristics: gender; qualification; experience. Part -B appraised the perceptions of the teacher-respondents toward teaching of reading skills. It contained fifty statements which were employed by the teacher-respondents using the Five-point Likert Scale. No significant difference was found between the levels of teacher competencies in developing pre- reading, while-reading, post-reading and total reading skills among Secondary school learners in the State of Telangana with special reference to their gender. Educational implications were drawn from the findings and also suggestions were made for future research.

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Reading skills; pre- reading, while-reading, post-reading ,total reading skills, Secondary School learners.

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Credit card fraud is a big issue in the financial services industry. Every year, billions of dollars are lost due to credit card theft. Due to confidentiality concerns, there is a scarcity of research studies analysing real-world credit card data. Machine learning techniques are employed to detect credit card fraud in this article. Standard models are initially employed. Then, hybrid methods based on Ada Boost and majority voting are used. A publicly available credit card data set is used to assess the model's performance. Following that, a real-world credit card data set obtained from a financial institution is analysed. In addition, noise is introduced into the data samples to test the robustness of the algorithms. The experimental results show that the majority voting method provides high accuracy rates in detecting credit card fraud.

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Credit card fraud, Ada Boost, Hybrid Models, Machine Learning Algorithm, Confidentiality, Financial Services.

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 Abstract

Underwater Sensor Networks (UWSNs) are capable to explore the many unrevealed natural resources beneath the water, such as lakes, ponds, rivers, seas, and oceans. Futher there are so many challenges to be faced during the design of UWSN system due to the random nature of water waves. But, perhaps the most significant challenge in UWSNs is how to transfer the packets efficiently with minimum energy cost to the surface sink through the water waves. This can be achieved by employing geographic and opportunistic routing schemes to transfer the packets at the surface sink reliably in cooperation with relay nodes. In this paper, a new routing protocol called the Reputation based Geographic and Cooperative Opportunistic Routing Protocol (RGCORP) is developed using NS2, where data packets are routed from source node to the surface sink with the aid of relay nodes. In RGCORP protocol, initially, a relay forwarding set is being determined by the source node on basis of depth data, then weighting scheme is used to choose the best relay node from the relay forwarding set. The weight calculation is performed on normalized energy, packet delivery probability and normalized distance of the forwarding node to the known surface sink. The main purpose of developing the RGCORP protocol is to enhance packet delivery by using reputation values. Further the performance metrics of RGCORP are examined.

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Underwater Sensor Networks, Reputation based Geographic and Cooperative Opportunistic Routing Protocol, relay forwarding set, enhance packet delivery.

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 Abstract

The traffic indicators or signs being present is essential for guaranteeing a safe and efficient flow of traffic. The traffic signs that are visible while we are driving significantly affect our daily lives. They offer fundamental information to clients that approach them on the street. They are consequently gradually being encouraged to alter their driving behaviour and make sure they strictly abide by the current traffic laws without harming other drivers or pedestrians.Therefore, in this project, we suggest a model for classifying traffic signs using deep networks that employs Python as its base language and a number of Python modules to train the CNN model [5].The interclass samples from the submitted dataset will be accurately classified using this model, which consists of multiple CNN layers. Real-time traffic sign identification and sign class identification using this technique.

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Traffic sign, Deep learning, CNN, Classification.

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 Abstract

Shreshth Bhaarat Nirman Mein Shaastrokt Nyaay Sandarsh

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Shreshth Bhaarat Nirman Mein Shaastrokt Nyaay Sandarsh

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The challenges that we're facing in our day-to-day life is parking of the car. When we visit colorful public places similar as office, shopping boardwalk, legion cinema halls etc. it's veritably hard to search the vacuity of parking area. This situation calls for the need for a smart car parking system which is equipped with detectors (Infrared) and microcontrollers (Arduino- uno) to automatically count the cars situated in the lot. In this paper we're going to design and apply a prototype of Smart Car Parking System which is grounded on Internet of effects. This paper proposes a system that helps druggies to automatically find the vacant available space in the parking area through the infrared detectors which are located in each parking space and the stoner can find the vacant parking places through an web application on internet via server. In other words, we can say that it's a new way of communication between the humans and the effects. These all effects are done with the help of rearmost technology grounded on IoT.

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 Keywords

Internet of Things (IOT), Sensors, Microcontroller, WebApplication, Smart Car Parking System.

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This study focuses on the impact of Non-Performing Assets on the Profitability of the State bank of India. This can contribute to economic growth and development of the country. The motive of this study is to analyze the Non -performing assets of State Bank of India and its impact on profitability of the bank. The study uses the annual reports of State bank of India for the period of ten years from 2011-12 to 2020-21. The data has been analyzed by using graph and coefficient of correlation. From this analysis it is noted that decrease in NPA is necessary to improve profitability of State Bank of India. While analyzing the impact of NPA level of State bank of India the researcher derived the conclusion that there is a negative relation between NPA and Net Profits of SBI. It simply means that as NPA increase Net profits decrease. It is because of the mismanagement on the side of bank.The purpose of study is to investigate whether there is a significant relationship between non- performing assets and the performance of bank.

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Non-Performing Assets, RBI, State Bank of India, Net Profit,

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 Abstract

"Risk and Resilience Management in Supply Chain" :In Next Normal As Corporate Strategy.

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AI, ML, RM, SCM, SUPPLIAR

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Betel vine leaves diseases caused by regular endangerment to bacteria which causes a huge yield loss globally. In recent years, deep learning has shown great potential in the field of image classification. Machine learning, the latest breakthrough in computer vision, is encouraging for fine-grained disease classification, as the method uses SVM classifier and Gaussian mixture model for image segmentation. Disease detection and classifications are considered as the two hardest works to the recognition of Betel vine disease. Betel vine is an important crop in many tropical countries and its classification is important for various applications such as variety recognition and quality control. However, due to its complex and diverse structures, betel vine classification remains a challenging task. One popular deep learning architecture is ResNet, which has been widely used for image classification tasks and has achieved good performance on various benchmark datasets. Thus, this work uses ResNet architecture to identify and classify the betel vine disease. Dataset of betel vine images and preprocessed the data to prepare it for use with the ResNet101 architecture. ResNet101 architecture is a promising method for betel vine classification. The model performs well in terms of precision and recall demonstrating its effectiveness for betel vine classification.

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ResNet, SVM, Convolutional Neural Network, Gaussian Mixture Model, Histogram Equalization

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Norwegian Wood is a fiction which has been predominantly studied as a love tale of mixed feelings, entangled between Toru, Naoko and Midori. It has a signature narrative technique of Murakami where the story thrives between past and present creating the peculiar Murakami-esque effect. In the present research paper, the researchers are trying to revisit the story of Toru in the light of fate acting as the ultimate authority. One can consider it as deus ex machina. Deus ex machina or God in the form of machine is a classical terminology which has been used by writers for ages. Here, Murakami has used it as a 'red string of fate' in order to reach the climax. Fate has a unique mechanism for each individual. It may not be the same as it is equal to that of his deeds. God has plans for every individual and fate is the string through which He implements his plans. Fate is the greatest leveller that adjudicates the deeds of a man and reciprocates the same treatment by different means which the researchers name it as deus ex machina.

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fate, deus-ex machina, destiny, love, Norwegian Wood, Haruki Murakami.

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In the past few years, there have been several accidents of children falling into abandoned bore wells in India. Abandoned bore wells that have turned into death pits for children. The problem is all over India. Rescue teams spend hours and sometimes days in futile attempts to save these little kids. A lot of money is also spent in these missions. In most cases they are unable to save the kids. Such events have happened umpteen times in the past, and every time either the government or the bureaucracy is blamed. The rescue process to save the child from bore well is a long and complicated process now. The rescue team tries to approach the victim from a parallel well that take about 20-60 hours to dig. This complicated process makes 70% of the rescue operations fail. The design of handling system is made in such a way that the baby/victim never gets hurt and this rescue system is sent through the same well where the victim is felt inside to bring back the victim safe through an autonomous control of drives. Our design constitutes a best Ergonomic Design and performs safest rescue operation.

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Pneumatic cylinder, Gripper, Battery.

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IOT and raspberry pi-based greenhouse monitoring system in the presence of three sensors is used to detect temperature, light, humidity and soil moisture in the greenhouse. The greenhouse effect is a natural phenomenon and beneficial to human beings. Numerous farmers fail to get good profits from the greenhouse crops for the reason that they can't manage two essential factors, which determines plant growth as well as productivity. Greenhouse temperature should not go below a certain degree, high humidity can result to crop transpiration, condensation of water vapor on various greenhouse surfaces, and water evaporation from the humid soil. To overcome such challenges, this greenhouse monitoring system involves the rescue. This project demonstrates the design and implementation of various sensors for the greenhouse environment monitoring and controlling. This greenhouse control system is powered by Raspberry pi it consists of temperature sensor, light sensor, soil moisture sensor,LCD display module, 12V DC fan, Bulb, and pump.

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Green house

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 Abstract

The main aim of the paper is to design and develop a Sliding mode Controller which can control the speed of Permanent Magnet DC motor drive for EV Applications which represents a novel approach for controlling the speed of a Permanent Magnet DC motor, which is a critical component of an Electric Vehicle (EV). The proposed technique is based on Sliding Mode Control (SMC) and is capable of controlling the speed of the motor accurately and efficiently. The paper begins by providing an overview of the requirements for an EV motor drive system and the existing control methods. It then explains the SMC technique and its advantages over other control methods. Overall, the paper presents a significant contribution to the field of EV motor drive systems, and the proposed SMC-based speed control system has the potential to improve the performance and efficiency of EVs.

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Permanent Magnet, DC Motor, Sliding Mode Controller, SMC, Electric Vehicle

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High blood pressure is a leading chronic disease and has become the main factor for many high-risk diseases such as diabetes, heart attack and cancer. At present there are more than hundred million hyper tension but only 44% of them have been diagnosed, we are going to design a blood pressure measurement system that is completely wireless and uses blood pressure sensors to collect the data of the patient and transfers the information via Bluetooth to a monitor where in the blood pressure of the patient along with the patient details are displayed by this process, blood pressure of the patient can be monitored continuously. The overall procedure can be done within a minute or not more than two minutes. Smart- phones are ubiquitous, so a blood pressure device comprising only the smart-phone can make diagnosis commonly available without the need to procure access to a special blood pressure device. This project reviews recent advances in blood-pressure measurements, specifically with focus on those implemented for smart-phones using Bluetooth.

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Blood pressure sensors, Oscillometric, Smart-phones and Bluetooth

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This art work focuses on a multi-port model predictive controller grounded completely non-isolated (Binary enter and single output) DC/ DC power digital interface grounded on Z- Quasi Resonant (ZQR) community. The motor includes grid and photovoltaic panel (PV) as its input means. Unlike the primary DC/ DC converter, the supported DC/ DC motor calls for smaller switches and gives nonstop slice- edge- day, high benefit in voltage, and minimum voltage stress on motor transfer as lots as 40 obligation cycle thanks to the presence of ZQR community. This specific of the motor makes it to and its software program in electric powered auto (EV) off- board charging wherein inordinate voltage benefit is demanded. In the proposed multi-port ZQR motor, fresh input and affair anchorages could be added without compromising the motor's benefit and overall performance. The evolved motor can characteristic constantly despite the fact that someone of the input things fails to rate the EV. The proposed motor is mathematically modeled the operation of abecedarian felonious pointers that govern the motor average overall performance and anatomized in MATLAB/ Simulink platform underneath colorful operating modes.

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ZQR community, DC/ DC converters, MPC and LED lighting.

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New energy vehicles play a positive role in reducing carbon emissions. To improve the dynamic performance and durability of vehicle powertrain, the hybrid energy storage system of "fuel cell/power battery" is more used in new energy vehicles. Bidirectional DC-DC converters with wide voltage conversion range are essential for voltage matching and power decoupling between battery and vehicle bus, helping to improve the low input voltage characteristics of super capacitors and realize the recovery of feedback energy. In recent years, the topologies of bidirectional converters have been widely investigated and optimized. Aiming to obtain bidirectional DC-DC converters with wide voltage conversion range suitable for hybrid energy storage system, a review of the research status of non-isolated converters based on impedance networks and isolated converters based on transformer are presented. Additionally, an evaluation system for bidirectional DC-DC topologies for hybrid energy storage system is constructed, providing a reference for designing bidirectional DC-DC converters. The performance of eight typical non-isolated converters and seven typical isolated converters are comprehensively evaluated by using this evaluation system. On this basis, issues about DC-DC converters for hybrid energy storage system are discussed, and some suggestions for the future research directions of DC-DC converters are proposed.

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Bidirectional dc/dc converter, main ener energy storage, an auxiliary energy storage, MATLAB/Simulink

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