Volume 12 | Issue 4 |

 Abstract

Understanding what's happening in traffic scenes is crucial for systems that help control traffic or drive autonomous vehicles. The project focuses on developing an automatic captioning system for traffic images. To do this, we use modern techniques like spotting pedestrians, cars, and recognizing traffic signs. Leveraging computer vision and natural language processing techniques, our system generates descriptive text based on image content and also provides audio. We enhance accessibility by converting these captions into natural-sounding audio descriptions, benefiting visually impaired users. It does this by using special types of computer programs called Convolutional Neural Networks (CNN), You Only Look Once (YOLO) and Long Short-Term Memory (LSTM) models. Our project aims to automate traffic image annotation, bridging the gap between visual content and textual and audio descriptions.

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Convolutional Neural Networks (CNN), You Only Look Once (YOLO), Long Short-Term Memory (LSTM).

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The United Nations has established 17 Sustainable Development Goals (SDGs) in an effort to combat the world's problems facing humanity. Future decision-makers and society stakeholders must value these goals in order for them to be accomplished. Thus, we looked at how significant each of the 17 SDGs was regarded by students in 41 nations that are directly tied to the environmental sector in this study. The SDGs could be divided into three higher-level categories that correspond to the three pillars of sustainability (social, economic, and environmental) based on the examination of these evaluations. In many nations, these three pillars are regarded as having differing degrees of significance. Additionally, we connected these higher-level components' evaluations with indicators unique to each nation, like the Human Development Index. The relationships among the indicators and the higher-level factors revealed that in countries with higher indices, the SDGs are rated as less important compared to in countries with lower indices. These results provide stakeholders with important guidance on how the SDGs should be promoted in their country.

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Sustainable Development, Stakeholders, Pillars Human Development, Indicators,

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The boom of technologies including commercial enterprise technology and monetary technology (FinTech) has caused a large range. Online card transactions every day. Thus, the assault on credit score card fraud has affected card agencies. Merchants and Banks. Therefore, it is crucial to expand mechanisms that aid the security and integrity of credit transactions. In it Research Implementation of a Machine Learning (ML) based totally Platform to Detect Credit Card Fraud Using Diverse Real-World Datasets. European credit card holders are well-known. To address the problem of class inequality, they resampled the dataset with the usage of an artificial approach. Minority Extrapolation Technique (SMOTE). This platform has been evaluated the use of the subsequent device learning methods: Support Vector Machine. (SVM), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Decision Tree (DT), Spanning Tree (ET). These ML algorithms are blended with Adaptive Boosting (AdaBoost) to perform the stepped-forward category. Examples Precision, in mind, precision, Matthew's correlation coefficient (MCC), and location underneath the curve were evaluated. (AUK). The proposed framework generated artificial confidence cardinality of a noticeably skewed fraud dataset to in addition validate the data. The consequences acquired on this study. Test results show that the use of AdaBoost has a tremendous impact Performance of the proposed approach. Additionally, the results acquired the usage of the advanced fashions are better than the prevailing techniques.

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Machine Learning, Strategies, Recognition

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In this solar system the earth is the sole planet which provides life, few unique atmospheric situations are responsible to provide life on earth like rich oxygen, water, atmosphere and a convenient or pleasant surface temperature that is why complex process of evolution took place on earth only. The two planets Mercury and Venus that are situated between sun and earth are not supportive to life. That is why because mercury has no atmosphere while temperature at night may reach to -140 degree Celsius. Data, reports, rationalization, and effects show that temperature change as pollutions is a very important and major issue in today's world. Temperature change is directly concerning and/or several times alternate words used for warming. It's the phrase that's explained as a gradual raise within the mean temperature of the earth's atmosphere and its oceans. This alteration is meant to be evermore modifying the earth's climate. Warming could also be outlined as "The slow heating of the earth's surface, atmosphere moreover as the ocean". Considering all this it is very important to have an awareness regarding climate change among all the general population so as take necessary and corrective actions towards it. Additionally, the study also focuses to find the association between the awareness of climate change with chosen demographic variables.

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Assess, climate change

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Urogenital complications are commonly found in patients with long standing diabetes mellitus. In the vast majority of patients, Diabetic neuropathy and/or angiopathy are the etiologies or most marked co-etiologies of micturition or sexual dysfunctions. As the deterioration of bladder retention and emptying as well as the erectile and ejaculatory dysfunction may have severe organic and psychosocial outcome, their existence (often unclear to the patient) should be thoroughly screened for in the routine diabetic clinic. Given hints of existence, thorough evaluation of the impaired organ system is mandatory. A wide range of various treatment modalities is available and can be individually offered following appropriate diagnosis.

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 Keywords

Bladder dysfunction; Cystopathy; Erectile dysfunction; Female sexual dysfunction; Diabetic neuropathy

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The Indian Preamble states that India that is Bharat to be a '' Sovereign, Socialist, Secular, Democratic, Republic''. Ever wondered why the word Secular is mentioned in the Preamble? What was the need to mention the word? After all the word secular was inserted in the Indian Constitution in 1976 by the 42nd Amendment Act. Let's ask ourselves what is exactly is secularism? Why is Secularism significant in a nation like India? This research paper strives to understand the idea and the notion of Secularism and its successes and challenges! Besides this research paper attempts to find out the role of the Indian Judiciary when it comes to interpreting Secularism.

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Secularism, Preamble, Uniform Civil Code, Fundamental Rights

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Prof.N.Subbureddiar was a Tamil scholar and pioneer writer of Tamil travel writings. N. Subbureddiar was born in a simple agricultural family and lived in small village at, Peroor. He has completed his primary school to college studies and is a Professor and has written books on Tamil literature and religion. He has written more than 50 general articles based on his field studies, explaining the Shiva sites and each sculpture in detail through articles. And also wrote prose pieces for the first five classes. He has written many books and scientific poems. He established the Department of Tamil in 1960.

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9600565509

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Healthcare fraud is a significant problem that results in substantial financial losses and compromises patient care. This paper presents a comprehensive review of machine learning techniques for detecting healthcare fraud. The study focuses on the application of IEEE standards in the development and evaluation of fraud detection models. Various algorithms and methodologies are discussed, along with their advantages and limitations. Experimental results demonstrate the effectiveness of machine learning in identifying fraudulent activities in healthcare systems.

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Healthcare fraud, Machine learning, Fraud detection, Data analytics.

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Teaching competency can be a key to evaluating the teachers' performance. These competencies can impact the whole teaching-learning process. Objective: 1) To study the teaching competency of secondary school teachers. 2) To study the teaching competency of secondary school teachers in the context of gender and area. The Research Area for the study is Educational Psychology. Secondary School Teachers of Cuttack of Odisha were the population of the study. Selection of School was by Simple Random Technique and the selection of teachers was by cluster method. The sample size was 93 teachers. "Survey Method" was selected for study. The General teaching competency scale developed and standardized by Passi N. Lalitha was used for Data Collection. t-test was applied for hypotheses testing. Findings: Most teachers, with 59.14% being classified as "Extremely Low," are male (84.09%) and female (36.73%), with no male teachers in the "High," "Above Average," or "Average" categories. Urban teachers make up 8.70%, 10.87%, and 10.87%, respectively. Urban teachers have a more equitable distribution in the "Below Average" and "Low" categories. Male teachers are better than female teachers in terms of teaching competencies, and urban teachers outperform rural ones in terms of these competencies.

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Teacher Competency, Secondary Schools, Gender, Area

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Machine learning is a branch of artificial intelligence (AI) and computer science. The Primary causes of decreased agriculture production quality and quantity are plant disease. As plant Structure and cultivation method evolve, new disease continue to emerge on plant leaves. Accurately classify and detecting plant leaf disease in their early stage restrict infection spread and promotes the healthy growth of plant production . Detecting plant disease manually is a time consuming and error-prone process. It can be an unreadable method of identifying and preventing the spread of plant disease . The review resolve around two main axes :1. Plant leaf disease detection and classification. 2. AgriRobo Suggested disinfectant and automatically spraying for that plant leaf disease, spraying for that plant leaf disease. Smart Agriculture to produce good crops quality and quantity without harming the healthy plant. A deep CNN(Convloution Neural Network ) model capture the deep feature while LBP (Local Binary Pattern ) effectively extract the local texture information , YOLO algorithm divides an image into the grid system and in that each grid detect object within itself. This review paper explore the recent advancement and methodologies employed in this area, focusing on key techniques, challenge and emerging trends. Various image processing algorithm including Deep Convolution Neural Network (DCNNs) and deep learning architectures, are discussed for their efficiency in automating in automating plant leaves disease detection and classification.

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 Keywords

Machine Learning, Plant leaf disease detec- tion, Classification, AgriRobo, Disinfectant, You Only Look Once(YOLO), Convolutional Neural Networks (CNN), Local Binary Pattern (LBP), Deep Convolutional Neural Networks (DCNN), Deep Learning

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