Volume 12 | Issue 7 |

 Abstract

ABSTRACT Dadru, commonly known as fungal skin infections, presents a significant challenge in dermatological practice due to its recurrent nature and varying response to conventional therapies. This review discusses the holistic perspective of Ayurveda in understanding Dadru, emphasizing the importance of dosha imbalance, immune modulation, and lifestyle modifications in its management and provides an in-depth analysis of two traditional Ayurveda treatment modalities, Raktamokshan and Vidangadi Lepa in the management of Dadru. Vidangadi Lepa, a topical formulation comprising herbs like Vidanga (Embelia ribes) and Haridra (Curcuma longa), has been traditionally employed for its antifungal and antiinflammatory properties. The review examines the pharmacological actions of the individual components and their synergistic effects in combating fungal infections. Additionally, the review delves into the therapeutic approach of Raktamokshana by Jalauka-avcharana, a bloodletting procedure in Ayurveda, for the management of Dadru. Raktamokshana aims to eliminate vitiated blood and toxins from the body, thereby alleviating the underlying imbalance responsible for fungal skin infections. This review aims to fill this gap by providing a thorough description of Raktamokshana and Vidangadi Lepa in the context of Dadru.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Dadru, Dermatophytosis, Fungal infection.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

[The COVID-19 pandemic had a profound and lasting impact on the tourism industry worldwide. The restrictions on movement, lockdowns, and border closures severely disrupted travel plans, leading to a significant decline in tourism activities. Travel was halted, borders were closed, planes were cancelled, and tourism was slowed down by COVID-19 restrictions. The impact on countries that depend significantly on tourism showed the interdependence of the world and the vulnerability of sectors that depend on human mobility. The aim of this paper is to understand the effect of Covid-19 on tourism industry of Dakshina Kannada by analysing the difference between tourist visited the district pre- Covid-19 and post- Covid-19. Moreover, the study considers selected tourist attraction places for the year 2018 and 2021. This research utilizes secondary data gathered from 14 well-known religious and natural tourism destinations in Dakshina Kannada district collected from Tourist Office, Department of Tourism, Mangalore, Dakshina Kannada District and Government of Karnataka. As we had to compare two years' data, the analysis employs the Paired T- test to assess the data.And as a result it is known that there is a lot of difference in tourist arrivals after pandemic and it is mainly due to Covid-19. Through this paper, we would like to suggest that Government and local bodies must concentrate more on improving the tourism places in Dakshina Kannada by providing clean and safer environment. This will give assurance for tourists regarding their visit and hence, Dakshina Kannada can attract more visitors].

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Covid-19, Pandemic, Tourism, Dakshina Kannada, T-test.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

It presents a machine learning based approach for predicting solar power generation. The approach includes data collection, preprocessing, feature selection, training, selection, evaluation, model and deployment. High-quality data from multiple sources, including weather data, and historical solar power generation data, are collected and pre-processed to remove outliers, handle missing values, and normalize the data. Relevant features such as temperature, humidity, wind speed, and solar irradiance are selected for model training. Additionally, the model may consider time-related features such as time of day, day of the week, and seasonal variations. This project leverages advanced machine learning techniques, specifically Random Forest Regression and Gradient Boosting models, to predict solar power output. These models are chosen for their robustness in handling non-linear relationships and their ability to manage large datasets with numerous features. By integrating weather data, historical solar power generation records, and other relevant environmental parameters, the models aim to provide accurate short-term and long-term forecasts of solar energy production. The methodology involves data preprocessing, feature selection, model training, and validation. The performance of the Random Forest Regression and Gradient Boosting models is evaluated using metrics such as Mean Absolute Error (MAE) and R squared. The results demonstrate that machine learning models can significantly enhance the accuracy of solar power generation forecasts.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine learning, Random Forest Regression, Gradient Boosting model, Mean Absolute Error (MAE), R squared, Voting Regressor approach

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Nabarangpur district (Lat: 190 09" and 200 06" North, Long: 810 51" and 820 52" East) is situated in the south-western part of Odisha. It is surrounded by Bastar district of Chhatisgarh in west, Raipur of Chhatisgarh in north, Kalahandi and Koraput district of Odisha in east and south respectively. The district is divided into 10 administrative blocks. Most of its population is tribal and most of the land is forested. The Indravati river is the most prominent river of the district. It is a tributary of the Godavari and sustains perennial flow. It is originates in the Kalahandi district flows through Nabarangpur and Koraput districts and enters into Bastar district of Chhatisgarh. The Tel and Bhaskel are the others rivers flowing through the district. The climate of the district is typically tropical to subtropical with three seasons i.e. summer, winter and monsoon.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Nabarangpur, Bhaskel, Indravati, Temple, Bada, Gandi, Mastaka, Nilakanthesvara, Siva.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In this research project, we present a new system for recognizing medicine strips using Convolutional Neural Networks (CNNs). Our system uses advanced image processing techniques to extract important information like medicine names, quantities, and prices from various images of medicine strips. This automated process eliminates the errors that can occur with manual data entry and greatly improves the accuracy and efficiency of billing.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Medicine strip recognition, Convolutional Neural Networks (CNNs), Image processing, Automated data extraction, Medicine identification, Billing accuracy

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Neoliberalism as a school of thought emphasizes economic liberalization, privatization, and deregulation. The tenets of this theory thus emphasize competition and taking individual responsibility, thereby achieving economic efficiency. Neoliberalism has not left the education system untouched. In the context of education, neoliberal policies favor market-driven values and outcomes, such as employability and economic efficiency. The theory emphasizes competition amongst higher education institutions, consumer choice, and reliance on private funding and partnerships. An evident outcome of the application of neoliberal policy to the legal education system is the sudden emergence of multiple institutes offering legal education. The application of neoliberal thoughts however does not go well to the ethics of teaching and learning. While legal education, no matter liberal to whatever extent, would rely on intellectual exploration, critical thinking, and a deep understanding of principles of legal theory, in contradiction, the neo-liberal theory in disregard to these factors, relies only on market-driven factors such as employability and efficiency. This has resulted in the commodification of the legal education system. Quality of education has taken a back seat while the needs of the market and employers have taken priority. Once a noble profession, the education sector today thrives on exorbitant tuition fees. Critical thinking has been replaced by employability skills alone. The negative effects of neoliberal thoughts on legal education can be seen in the rampant privatization of legal education. Private institutes have mushroomed like never before but are rather infected with the vices of the greed of market consolidation and earning fame, not driven by the spirit of imparting legal understanding and creating good lawyers, judges, or even academicians. There is a casualization of academic labor. Recruitment of faculties is made with disregard to qualifications or experience and are made to work on meagre salaries resulting in a lack of incentive for faculties to enhance their knowledge while also bringing down the graph of intellect. It is argued that a blind inclination to neoliberal principles in legal education is harmful and the negative effects need to be addressed. To maintain the integrity of legal education, it is necessary to actively work on combating the negative effects of neoliberal thoughts on legal education. A balance must be created between the neo-liberal ideas and the ethics of the profession. A potent way of achieving that would be to adopt an interdisciplinary curriculum structure. Enabling a holistic approach to learning for students where they can critically think and ethically reason, thus ensuring that they become socially responsible citizens.The need is to put in place a legal education system that prepares the students for the demands of the legal profession while also equipping them with the knowledge and values necessary to contribute to a democratic society. By working on the tensions between neo-liberal thought and legal ethics, the legal education sector can play a significant role in shaping the future of legal practice and promoting the ideals of justice, fairness, and equality.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Neoliberalism and its Impact on Society, Neoliberalism and impact on education, pros and cons of neoliberal policy, criticism of neo liberal policy

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The haircap is equipped with high-resolution imaging to collect comprehensive data on scalp temperature, moisture levels, pH balance, and hair density. AI algorithms, trained on extensive datasets, analyze this data to detect issues such as dandruff, hair thinning, and dermatitis, enabling early detection and personalized care recommendations. The device also tracks the effectiveness of treatments over time, providing users with valuable insights into their scalp and hair health. This technology represents a significant advancement in non-invasive, real- time monitoring solutions, offering a convenient method for users to manage and improve their scalp and hair health. By enhancing the ability to diagnose and treat scalp and hair conditions, the AI-enhanced haircap contributes to better overall dermatological care and research. This abstract explores the design, functionality, and potential applications of this cutting-edge technology.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI, haircap technology, Raspberry Pi cameras, scalp monitoring, hair health, real-time analysis.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Credit card fraud poses a significant challenge within the financial industry, intensifying with the surge in credit card usage. This predicament not only results in financial losses for individuals and businesses but also erodes trust in the broader financial system. As a countermeasure, an imperative lies in the improvement of a robust fraud detection system. This paper introduces an innovative approach, leveraging algorithms of machine learning to pinpoint fraudulent transactions. By enhancing accuracy and expediting the identification process, our proposed system aims to fortify the resilience against credit card fraud. The escalating threat of the credit card fraud, particularly fuelled by the proliferation of online transactions and vulnerability of sensitive information, necessitates advanced detection methods. Various strategies, including rule-based systems, Algorithms like machine learning and neural networks, have been adopted to combat this menace. In response to this evolving landscape, our paper suggests a hybrid system that amalgamates rule-based and the machine learning approaches. This integration seeks to elevate the precision of fraud detection. Through rigorous evaluation using a comprehensive dataset, our hybrid system demonstrates superior performance note the similarity between existing methodologies.Recognizing the enduring challenges posed by fraudsters and their continual adaptation to circumvent existing systems, our hybrid model is designed to address the dynamic nature of credit card fraud. Incorporating a set of rules to identify common fraud patterns and a algorithms of machine learning to discern intricate anomalies, our system achieves noteworthy results--boasting an accuracy of 99.86%, a precision of 99.68%, and a recall of 81.30%. With a focus on reducing false positive and adeptly detecting both simple and complex fraud patterns, our proposed system stands as a potent defence mechanism. This article not only adds to the ongoing discourse on credit card fraud but also holds implications for the broader financial industry. By mitigating the risks associated with fraud, our approach strives to safeguard the financial interests of individuals and businesses alike. As we delve into the future scope of the research paper, the potential for further advancements in the credit card fraud detection becomes apparent, signalling a pivotal step towards a more secure financial landscape.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Credit card fraud detection, Hybrid system, Machine learning algorithms Rule-based systems, Fraud detection accuracy, Financial industry, Supervised machine learning, Unsupervised techniques, Anomaly detection, Dataset pre-processing, Algorithms like Random Forest , Decision tree , Evaluation metrics, False-positive rate, Financial losses, Novel fraud patterns, Advanced feature engineering, Real-time fraud detection, Deep learning algorithms, Data sources, IP addresses, Device fingerprints, Data

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Desire and Deception: A Psychoanalytic Reading of O'Neill's Classic

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Deception, Freudian Psychoanalytic Theory, Inheritance, legacy, Repressed Emotions.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background: A three-year training program was undertaken by the National AIDS Control Organization (NACO) with the goal of enhancing the knowledge and the upskilling of the program managers of the National AIDS & STD Control Program. An initial Training Needs Assessment (TNA) was conducted to identify the gaps where training and upskilling were necessary amongst the program officials working in the program at various levels. This was followed by the training program, under the name 'Sahyog Project', starting from April 2021 onwards, for training of program managers under the National AIDS Control Program (NACP), at all programmatic and operational levels across the country. Objectives :The objectives of the study were: (i) to assess the level of participation in the training programs; (ii) to assess improvements in knowledge and awareness amongst the training participants and (iii) to evaluate the feedback from the participants of the training program Methods: Cascade training approach was used since a large number of people within the organization had to be trained within the assigned project period. A pool of Master Trainers at the national level and from each State were trained by instructors from the program at the national level, and they in turn conducted training to the last mile including grassroots level functionaries. The participants of the training sessions were given a 20-question test before and after the trainings to assess the effect of the training on their knowledge levels related to various aspects of the National AIDS Control Program. They were also assigned two open ended questions to provide their feedback on the current program and to obtain suggestions on improving future such programs. Results: The program was conducted through cascade training model; wherein master trainers were selected predominantly from the NACP workforce. Majority of the trainings took place at the State and District levels thus ensuring that capacitated personnel were available at the state and district level who could further train the cadres working at grassroots level. A target of 1538 participants, pan India across 35 states/union territories was set against which a total of 1428 (93%) were trained. End term assessment showed that more than 90% of the participants attended the training sessions in over half the states. Pre and post test scores analyzed using statistical tests confirmed improvements in knowledge. Results from the 't 'test showed that the mean score for the pretest was 71.6 and the variance was 131.6. The mean score for the post test was 79.1 and variance was 41.9. The standard deviation was 12.5. It can be inferred that there was a significant improvement in skills of participants post-test with a p <=0.002 with 95% CI. Conclusions: Based on the findings from the TNA, a comprehensive capacity building program for the NACP workforce covering officials of NACO, State AIDS Control Society (SACS), Technical Support Units (TSU), and District AIDS Prevention and Control Units (DAPCU) was carried out pan India. Most of the trainings took place at the state and district levels, thus ensuring that capacitated personnel were available at the state and district level levels who could further train the cadres working at grassroots level. The high participation rates and the observable improvement in the test scores indicated the effectiveness of the capacity building program in upskilling and reinforcing the knowledge of the participants. The master trainers played a pivotal role as is evident from the feedback from participants appreciating the subject knowledge, helpfulness, knowledge and approachability of the facilitators. It was also evident that there was a need to relook at the duration of the sessions, inclusion of more interactive aspects in the training and logistic arrangements while planning for future trainings.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

National AIDS Control Organization, State AIDS Control Units, Technical Support Units, District AIDS Prevention and Control Units, District Integrated Strategy for HIV and AIDS

  License

Creative Commons Attribution 4.0 and The Open Definition