Volume 12 | Issue 1 |

 Abstract

The chimney structures are tall and generally placed in regions of high gust. The design of chimney has significant effect on wind load bearing characteristics of chimney. The research is intended to investigate the effect of wind load on structural characteristics of chimney. The wind load analysis of chimney structure is conducted using techniques of Computational Fluid Dynamics. The CAD modeling and CFD simulation of chimney is conducted using ANSYS CFX software. The lateral deformation and induced pressure is evaluated for different chimneys. The edge treatment on tapered chimney has significant effect on magnitude of induced pressure and drag force on chimney. By changing the sharp edged chimney to filleted edge chimney the drag force and shear stress reduced significantly.

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 Keywords

Chimney, wind load

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 Abstract

Bronchial asthma is a serious global health problem. 5% to 10% of persons of all ages suffer from this chronic airway disorder. This review article presents homeopathic medicines and treatment of bronchial asthma .Cases summary: This is a case of patients suffering from bronchial asthma having the complaints of cough shortness of breath , wheezing along with itching all over the body . The patients were prescribed indicated constitutional Homeopathic medicines and at the end of treatment showed reasonable improvement in disease as well as in the quality of life.

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HAMSA HOMEOPATHY MEDICAL COLLEGE, HOSPITAL & RESEARCH CENTRE

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The skin is the largest organ in the body, and fungus infections are among the many conditions that affect it. Skin disorders are common worldwide. According to Ayurveda, all skin diseases are categorised under the term Kushtha. In Ayurveda Dadru and Pama is one of the common skin diseases mentioned in Ayurveda. Ayurveda has described 'Samshodhana' (Bio-purification), 'Samshamana' (Pacification) and 'NidanParivarjana' (Avoiding causative factors) as main therapy for many diseases including skin disorders.

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 Keywords

Kushtha, Dadru, Pama, Skin diseases

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Creative Commons Attribution 4.0 and The Open Definition

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: This paper presents a system that embodies the essence of sonic detective work. Like a musician, it first extracts certain features from the sound, identifies individual instruments, checks the notes or sounds they play, and then synchronizes the notes with the music. The end result is like a beautiful piece of music that takes the messy sounds and organizes them into something pleasant. It could be a new music mix or music score. People can listen to it and have a great time enjoying the music. This project is designed for listening to polyphonic music played by a variety of instruments together, and it does a lot of things well. For the purpose to advance the musical field we are developing the system that is capable of identifying instruments from polyphonic instrument sound from the feature extracted using Kernel PCA (Probabilistic Component Analysis) ,the classification is performed using SVM (Support Vector Machine).This allows system to efficiently identify the instruments. Then the pitch is detected from the instruments identified using Cepstrum method which is capable of detecting pitches from detected instruments. The detected pitches are then synchronized to provide a synthesized audio file as output using HMM (Hidden Markov Model) and DTW (Dynamic Time Wrapping).

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 Keywords

Machine Learning, Kernel PCA, Kernel Probabilistic Component Analysis, Support Vector Machine, Hidden Markov Model, Cepstrum, Dynamic Time Wrapping, Tune Detection, Instrument Recognition, Pitch Detection, Synchronization, Classification , Feature Extraction, Audio Preprocessing, Synthesized Audio Generation

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Considering the enormous difficulties that the globe is experiencing in providing food for an ever-increasing population, the incorporation of technology into agricultural practices has become an absolute need. Climate-controlled agricultural facilities, such as greenhouses and hydroponic systems, provide methods of food production that are both effective and environmentally friendly. It is essential to have the capacity to monitor and control plant health in order to get optimal results while optimizing these habitats. The purpose of this study is to investigate the use of machine learning techniques for the categorization of plants in controlled agricultural situations with the intention of improving precision agriculture operations. One of the most important components of a plant is water. Along these lines, the development of plants is extremely dependent on the changes that occur in the amount of water that is contained within the plant. There have been a lot of different approaches that have been developed in order to enhance plant development in times of water scarcity and dry period pressure. The purpose of this study is to organize and construct an intelligent framework that will promote plant development in a constrained water environment. This framework will be based on Support Vector Machine (SVM) and machine vision. Shading, morphological, and textural highlights were finally isolated from a large number of photographs of turf grass, wheat, and rice plants that were taken under pressure circumstances that were typical of the dry season. At that point, an SVM and an ANN were utilized in order to supervise the process of information organization by using them. When the SVM was used as the classifier, the results showed that the general arrangement exactness of ANN was 92%, and greater correctness were obtained when the SVM was used. The general precision of the SVM was 98.00% for both fresh and wilted plant conditions.

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 Keywords

Classification, computer vision, controlled-environment agriculture, image compression, machine learning.

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The method of credit scoring involves a set of decision models that help in granting consumers loan and credit [1]. Since it involves many decisive statements, we employ machine learning models to predict the credit score of a consumer. The following chapter will investigate into the details of machine learning or ML model usages, such as the understanding of model outputs, structure modification, and constant investigation of work [2]. These understandings intend to cultivate the prognostic abilities, donating implicitly to the dominion of credit score forecast. Credit assessment has an essential part in the monetary business, leading the lending choices and handling the danger. Usually, this evaluation depends on physical approaches and comparatively humble scoring representations [3]. By bridging research gaps in credit scoring methodologies, specifically, model interpretability, fairness, and adaptability this project makes substantial contributions to advancing the comprehension and application of machine learning in the realm of credit risk assessment. The system's design prioritizes simplicity and transparency, fostering reproducibility and accommodating future expansions in credit scoring research and practical implementations.

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Credit Score; K-Nearest Neighbours; Support Vector Classifier; Random Forest; confusion matrix; correlation; Min-Max scaling

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The use of electronic voting in elections for public office is becoming more common around the world. This trend can be attributed to the advantages of these systems, such as remote voting capabilities and rapid vote counting. Additionally, electronic voting machines provide greater privacy and increase protection against fraudulent voting. Blockchain technology increases the power of the voting process through an immutable voting process, thus reducing the threat of vote manipulation and maintaining the legitimacy of the election surge. The technology has been adopted by countries such as Germany, Russia, Estonia and Switzerland for use in electronic voting systems. This study provides an overview of blockchain-based electronic voting systems currently used by countries and companies and suggests academic research. Additionally, this study analyzes the challenges faced by blockchain electronic voting systems and identifies areas for future research to improve the reliability of these systems.

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 Keywords

Electronic Voting, Blockchain Technology, Rapid Vote Counting, Privacy Protection, Fraudulent Voting, Immutable Voting Process, Vote Manipulation, Legitimacy of Elections, Blockchain-based Electronic Voting Systems

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Creative Commons Attribution 4.0 and The Open Definition

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Identity verification plays a pivotal role in the contemporary digital landscape, especially within financial and online services. The adoption of Know Your Customer (KYC) processes has become imperative to ensure secure and reliable interactions. This survey paper explores the integration of Optical Character Recognition (OCR) techniques, with a specific focus on the Convolutional Text Proposal Network (CTPN), as a machine learning approach for enhancing KYC verification. Traditional KYC methods often suffer from inefficiencies in terms of speed, accuracy, and scalability. The manual verification processes inherent in these methods not only consume valuable time but are also susceptible to errors. The advent of OCR technology has revolutionized the KYC landscape by automating the extraction and interpretation of textual information from diverse documents such as passports and driver's licenses. The survey begins by highlighting the limitations of conventional KYC methods, underscoring the need for advanced automated solutions. It provides an extensive overview of OCR, elucidating its significance in extracting text from a variety of documents while addressing challenges related to document formats, languages, and image qualities. Machine learning emerges as a critical enabler for OCR, allowing for continuous improvement in accuracy and adaptability to evolving requirements. A substantial portion of the paper is dedicated to introducing and exploring the capabilities of the Convolutional Text Proposal Network (CTPN) as an innovative machine learning approach tailored for OCR-based KYC verification. CTPN's ability to accurately localize and recognize text within images positions it as a promising solution for improving the precision and efficiency of KYC processes. The survey concludes with an evaluation of the current state of OCR-based KYC verification, identifying areas of success and potential challenges. It serves as a roadmap for future research and development, emphasizing the importance of ongoing advancements in machine learning and OCR technologies to meet the evolving demands of identity verification in the digital age.

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 Keywords

Identity Verification, KYC, OCR, CTPN, Machine Learning, Automated Solutions, Document Extraction, Traditional KYC Methods, Efficiency, Challenges

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Creative Commons Attribution 4.0 and The Open Definition

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As consumer consciousness soars and concerns about environmental degradation deepen, regenerative agriculture emerges as a beacon of hope. This study investigates the potential of this transformative approach in Dakshina Kannada District, India, focusing on consumer willingness to pay (WTP) and market impacts. We aimed to assess consumer interest in regenerative products, identify potential drivers of WTP beyond general environmental concerns, and evaluate the economic feasibility for farmers in the region. We employed a quantitative survey of 100 Dakshina Kannada District residents, encompassing questions on product preferences, WTP for regeneratively produced food, and underlying motivations. Statistical analysis, including regressions, explored the determinants of WTP and its variation across demographics and product categories. A remarkable 87% of respondents indicated WTP more for regeneratively grown products, particularly coffee, fruits, and vegetables. However, general environmental concerns lacked explanatory power in predicting WTP. Our analysis suggests alternative drivers, such as trust in producers, specific environmental benefits, and product certifications, warrant further investigation. Farmers face a promising market for regeneratively produced goods. Focusing on high-demand crops, highlighting specific environmental advantages, and building trust with consumers can unlock premium pricing and economic gains. Policymakers must tailor interventions and policies to address the unique motivations of Dakshina Kannada consumers, including supporting infrastructure development, raising awareness, and establishing robust certification standards.

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 Keywords

Regenerative agriculture, Consumer willingness to pay, Environmental sustainability, Dakshina Kannada District

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The sustainable development and inclusive growth of any nation consists in its capacity to inclusively engage every cultural factor and aspect into its comprehensive wholeness. The nation-building process of Canada has been fraught with a series of hostilities in the form of climatic challenges racial dissentions and cultural diversities; but mostly by the fact that the indigenous People such as the First Nations, the Metis and the Inuits are outnumbered by the Euro--American settlers. Consequently the minor aboriginals culturally remained eclipsed and felt a strong sense of alienation from the nation's mainstream modernization. But recognizing the plurality of its cultural artefacts and encouraging a cosy ambience for even the native aboriginals, noticeably for the last few decades, the Canadian statehood has progressively revolutionized itself in strengthening its unified future or hood and solidifying its socio-political strong roots. The greatest testimony to this fact is the recent but rapid rise in the literary output by the native aboriginals who are putting firm feet and looking a lasting corner in the cultural dissemination by profusely writing about their own identity as indigenous.

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 Keywords

native, inclusive, plurality, aboriginals, identity

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Creative Commons Attribution 4.0 and The Open Definition