Volume 11 | Issue 11 |

 Abstract

This research introduces a sophisticated sentiment analysis framework tailored specifically for YouTube comments, providing valuable insights for content creators and stakeholders. It comprises four pivotal components: sentiment classification, visualization of sentiment distribution, temporal sentiment analysis, and automated email summaries. The sentiment analysis module employs a Random Forest algorithm (chosen for its adaptability to high-dimensional data and resistance to overfitting) or Naive Baye's (Naive Bayes classifiers have been widely applied for their simplicity and efficiency in handling high-dimensional data, making them a popular choice for sentiment analysis tasks). This enables the system to categorize comments into positive, negative, and neutral sentiments. Additionally, an intuitive visualization feature employs charts and graphs to represent sentiment distribution, allowing users to interpret trends within the comment section. The system also conducts temporal analysis, examining how sentiments change over time about video upload and comment submission dates. This provides content creators with a nuanced understanding of audience feedback dynamics. A key feature is the automated email functionality, streamlining the distribution of sentiment analysis summaries to users. This ensures stakeholders receive timely, actionable insights, enhancing their responsiveness to viewer feedback. By combining these elements, this research introduces a comprehensive sentiment analysis solution tailored for YouTube comments. The framework not only categorizes sentiments but also equips content creators with tools to visualize trends and receive timely summaries, offering a multifaceted approach to deciphering audience feedback.

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 Keywords

Sentiment Analysis, YouTube Comments, Visualization, Temporal Analysis

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Education is the most important factor, which trains students towards social practices and moral ethics. Values are rules from which we make our personal decisions about what is right and what is wrong, good or bad. Values help direct us to what is more important and past what is less important. This helps guide us when making decisions. The moral nature of children is based on imitation. They are good observers and follow others. Many external and internal factors may also affect children personality. Personality traits and many other psychological factors deeply influence their moral reasoning skills. In the presence of morality, their decisions will be in a proper flow, which can help in maintaining healthy relations with society and adjust them parallel to societal changes. The research aims to find the attitude of school going students towards ethical goodness. Survey methodology is chosen to conduct a research. The population for the study consists of all the students studying at 8th class pupils in Guntur district. The sample size of 200 is selected through random sampling. The full paper present the need, objectives, hypotheses, findings and educational implications.

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 Keywords

Education, moral, ethical, values

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ABSTRACT: The Micro, Small and Medium Enterprises play a vital role in the growth of the country. In fact, the small scale sector in India is a natural habitat for entrepreneurs. Most entrepreneurs jumpstart by opening small enterprises and then nurture their units into large industries. The (MSMEs) provides the entrepreneurs with an opportunity to enhance their skills and talents, to experiment, innovate and renovate their ideas into finished goods and services needed by the society. The Micro, Small and Medium Enterprises (MSMEs) in India has grown rapidly over the years and has emerged as a highly energetic and self-motivated sector. It has acquired a crucial place in the socio-economic development of the country. The Micro, Small and Medium Enterprises Development (MSMED) Act was notified in the year 2006 to address policy issues affecting MSMEs as well as the exposure and outlay ceiling of the sector. The Act seeks to facilitate the development of these enterprises as also enhance their effectiveness. It provides the first ever legal framework for recognition of the concept of enterprise which comprises both manufacturing and service entities. It defines medium enterprises for the first time and seeks to integrate the three tiers of these enterprises namely micro, small and medium.

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 Keywords

KEYWORDS:Enterprises,Entrepreneurs,Socio-economic,development,Manufacturing,Service

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The study was carried out to investigate the Effects of Multiple Taxation on Micro Small and Medium Scale Enterprises in Jega Local Government Area of Kebbi State. The research was driven by six objectives and six corresponding research questions to guide the study towards achieving its objectives. A Descriptive survey research design was used. The population of the study was 343 MSMEs in Jega Local Government Area of Kebbi. The instrument used for data collection was questionnaire, it was administered to the respondents with the aid trained research assistants using random sampling method. Data obtained for this study was analyzed using frequency count and simple percentage. Result indicate that Government regulation and tax environment are bewildering and represent a very serious obstacle, to starting a MSMEs in Jega Local Government of Kebbi State. It was observed that there is a high level of government interference in MSMEs operations and 70% of the interference is attributed to Local Government Authorities. It was found that simplified tax and reduction of tax rates ranked highest and second highest respectively among the suggested tax policies that would enhance the growth of MSMEs. The study recommends that all state and Local Government Authorities should comply with national legislation enforced with respect to tax incentives being granted to MSMEs., Independent offices should be setup to monitor the activities of local and Government should develop common strategy to enhance public awareness on what taxes are payable and to whom among others.

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 Keywords

Tax, Multiple Taxation, Micro Small and Medium Enterprises, Jega Local Government Area, Tax Authorities, Tax Payers

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Creative Commons Attribution 4.0 and The Open Definition

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A virtual classroom is an online learning method conducted through the internet, providing communication for distance learners similar to face-to-face classrooms. This educational approach is gaining popularity and is expected to replace traditional education methods as internet-dependent learning becomes more widespread in schools and colleges. There are two main types of virtual classrooms: synchronous and asynchronous. In the synchronous format, online teaching is scheduled, led by a teacher. Students can interact in real-time, asking questions and getting immediate responses, even from remote locations. On the other hand, asynchronous learning allows students to progress at their own pace, choosing when and where to engage with the educational content. This method provides flexibility and is not bound by specific time constraints. Virtual classrooms are advantageous as they enable students to clarify doubts at any time and from any location. A key goal of this approach is to enhance collaboration among teachers and students, fostering a dynamic and interactive learning environment. As internet-based learning continues to grow, virtual classrooms are anticipated to play a significant role in the future of education.

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Virtual classroom, Synchronous, Asynchronous, Education, Challenges

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Background: Vitiligo is an acquired chronic depigmentation disorder characterized by sporadic loss of skin color. This can be physically disfiguring, psychologically devastating, and socially stigmatizing. However, Vitiligo is too often dismissed as a cosmetic condition with trivialization of the patients' distress. While there has been considerable research focused on dermatological approaches to managing Vitiligo, there is notable dearth of studies examining the psychological and emotional challenges associated with the treatment of patients with Vitiligo. Objective: This paper reviews the recent advances that have been made in the management of coping with the psychological impact of disfigurement in individuals with Vitiligo using different psychotherapeutic modalities. Methods: PubMed, Medline and Google Scholar databases were reviewed for studies investigating the effect of various psychotherapeutic techniques for the management of the psychosocial impact on individuals with Vitiligo. A total of 62 articles were obtained out of which 13 titles fit the study criteria and were selected for the purpose of this study. Results: Several studies including RCTS, review papers and semi-experimental studies support the effect of CBT, ACT, MBCT and Support Groups in the management of psychosocial impact of disfigurement cause by Vitiligo. Limitations: Larger prospective studies, especially RCTs are needed with larger sample sizes and a control group. Additionally, most of the participants in these studies were female. Prospective studies that include an equal distribution of male and female participants are required. Conclusion: Several studies have proven the benefits of adjuvant care in the form of CBT, MBCT, ACT and Support Groups for this population. These results potentially suggest that incorporating psychosocial care to the medical management of Vitiligo can exhibit greater results for the patient's general well-being and management of the disease.

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 Keywords

Index Terms- Vitiligo, Disfigurement, Psychosocial impact, Psychological management, Quality of Life.

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Breast cancer is the most common and rapidly developing disease in the world. Breast cancer is most commonly detected in women. Breast cancer can be controlled if it is detected early. Many instances are addressed by early detection, which reduces the death rate. Many studies on breast cancer have been conducted. Machine learning is the most commonly utilised technique in research. There have been numerous previous studies conducted using machine learning. Machine learning techniques such as decision trees, KNN, SVM, nave bays, and others provide superior performance in their respective fields. However, a newly established approach is being utilised to classify breast cancer. Deep learning is a newly developed method. Deep learning is used to compensate for the shortcomings of machine learning. Convolution neural network, recurrent neural network, deep belief network, and other deep learning techniques are commonly utilised in data science. When compared to machine learning, deep learning algorithms produce greater results. It extracts the images' greatest features. CNN is employed to classify photos in our study. Our research is primarily image-based, and CNN is the most widely used technique for image classification. The current document includes reviews of all writers

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Breast Cancer, Machine Learning, Deep Learning, Convolutional Neural Network, SVM

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Creative Commons Attribution 4.0 and The Open Definition

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Pb-contaminated soil acts as a phytotoxic element in environmental rehabilitation and cleaning with hyperaccumilator plants, which can accumulate these contaminants most efficiently and effectively, and serves as a significant and economically advantageous measure for long-term and environmental preservation. Crops such as sunflower (profitable edible oil crop) with high biomass and economically second only to soy bean among vegan oils with high protein content. The sole approach for high biomass and bioenergy for phytoremediation is a strategy for gaining additional benefits in addition to remedial efforts. This study used physiologically matured sunflower pots with concentrations of Pb (50,100,150,200,250 mg/kg-1) from the 30th, 60th and 90th harvesting days. Based on the bioaccumulation coefficient (BAC), bioconcentration factor (BCF), and translocation factor (TF), As a result Pb absorption is larger in the root (+0.58) than in the shoot (+ 0.10)than in the leaves (+0.07).

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Lead chloride, Biochemistry, Helianthus annus L., Phytoremediation.

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The reason of the study was to find out Assessment of unemployed rural youth problems and intervention of physical activities on selected fitness components. The study is formulated as a true random group design, consisting of two phases namely Phase -I : Status Analysis, 500 unemployed youth from the rural area will be selected in Thiruvallur district random through a questionnaire made for this purpose with due Standardization Process. Phase -II: Intervention of physical activities after the status analysis, 50 unemployed rural youth will be selected as subjects random for the experimental group and control group each consisting of 25 will be tested on the selected physical fitness components namely cardiovascular endurance, flexibility, prior to and after the experimental training. The group one participated in the physical activities and group two control group they did not participant any specific training, except their own regular activities. Experimental group one underwent of six weeks physical activities training, section lasted 45 minutes. The fitness components were measured by cardiovascular endurance-12 minutes cooper test, flexibility-sit and reach prior and immediately after the training period. The collected data were analyzed statistically through ANOVA. The result of the study showed that physical activities training shown better significant improvement than the control group.

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Unemployed rural youth assessment, Physical activities, Cardiovascular endurance, Flexibility.

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Creative Commons Attribution 4.0 and The Open Definition

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This article provides an overview of the existing literature on the processing of medical images related to thyroid cancer diagnosis. The primary objective of this survey is to serve as an introduction for those new to this field and as a reference for those seeking specific literature surveys in this area. In today's context, thyroid cancer is a frequently encountered concern due to the potential for malignancies and hyperactivity. Timely diagnosis is crucial in mitigating the increased malignancy of thyroid nodules. To address this, computer-aided detection methods and various image processing techniques are employed to effectively and efficiently classify thyroid nodules. Given the continuous growth of expert observations and the inherent uncertainties in medical knowledge, diagnostic imaging is essential to the medical industry. One often used technique for the precise and unambiguous identification and categorization of anomalies related to the thyroid gland is thyroid ultrasonography imaging. Computerized systems are invaluable tools for extracting features and classifying thyroid nodules, aiming to reduce misdiagnoses and enhance diagnostic accuracy. This paper's primary goal is to review the current approaches and strategies for the automatic classification of nodules in thyroid ultrasound images. It also includes performance metrics for nodule diagnosis in thyroid ultrasound images, emphasising the key differences between the strategies used.

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 Keywords

Thyroid Nodules, Deep Learning, Ultrasonography.Classification

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