Volume 12 | Issue 1 |

 Abstract

Every country now has a serious issue with traffic regulation and vehicle ownership identification. Identifying the driver of a car that breaches traffic laws or goes too fast can be challenging at times. Due to the possibility that the traffic official may not be able to obtain the vehicle number from the moving car due to the speed of the vehicle, it is impossible to catch and penalize those types of offenders. Therefore, one of the solutions to this problem is to develop an automatic number plate recognition (ANPR) system. Today, a variety of ANPR systems are accessible. Despite the fact that these systems use various approaches, the work is still quite difficult because to things like the vehicle's rapid speed, non-uniform number plate, and language. The total rate of recognition can be significantly impacted by the quantity and type of lighting. Most systems function with these restrictions. In this work, various ANPR strategies are described while taking into account processing time, success rate, and image size as criteria. An ANPR expansion is proposed at the end of this work. Artificial Neural Network (ANN), Character Segmentation, and Automatic Number Plate Recognition (ANPR) image segmentation, optical character recognition, and license plate analysis.

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 Keywords

Automatic Number Plate Recognition (ANPR), Artificial Neural Network (ANN), Character Segmentation Image Segmentation, Number Plate, Optical Character Recognition

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Key words: Apiary, honey, hills, plains, western ghats, thiamine (B1), riboflavin (B2), niacin (B3), panthothenic acid (B5), pyridoxine (B6) and ascorbic acid (C), wild, Karnataka.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The goal of "AI-Driven Talent Matching: Empowering HR Professionals with Reinforcement Learning" is to transform hiring practices by fostering a mutually beneficial partnership between employers and employees. When HR specialists thoroughly specify Job Descriptions (JDs) on the platform, the project gets underway. Meanwhile, job applicants upload their resumes, resulting in the establishment of profiles summarizing their credentials and experiences. After that, the system gathers essential data to create unique JDs for each seeker. The degree to which these customized JDs resemble the HR's JD is measured by a computed similarity score, guaranteeing a data-driven method of candidate assessment. Based on these scores, candidates are ranked, and Recruiters are then presented with top ranked candidates by applying a threshold. The incorporation of reinforcement learning will improve the recommendation model through learning from recruiter's feedback. Feedback in the form of "yes" or "no" from recruiter reviews of candidates enables the model to dynamically modify the similarity score threshold. This research explores the shifting dynamics of the labor market and makes the case for a datadriven strategy that would enable recruiters to make well-informed choices when hiring and selecting candidates. The process ends with a screening test to make sure applicants have the skills that are needed for the job. Better recruitment outcomes are promised by this cutting-edge approach, which will help both Recruiters and job seekers.

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 Keywords

Reinforcement Learning, Data-Driven, Job Descriptions, Recommendation Engine, Job Seekers

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The study examined the fastness properties of cotton fabric dyed with flowers from Thespesia populnea using various ratios (1:3,1:1, and 3:1) of various mordants. These ratios included myrobolan:nickel sulphate, myrobolan:aluminum sulphate, myrobolan:potassium dichromate, myrobolan:ferrous sulphate, and myrobolan:stannous chloride. We examined the washing, rubbing and sweat fastness of the colored samples. Comparing the color strength and fastness of cotton flowers colored with Thespesia populnea using a combination of mordants. When Thespesia populnea is simultaneously mordanted with a 1:3 mordant combination, the greatest results are obtained when comparing the fastness qualities and color strength of cotton materials that have been dyed.

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 Keywords

Cotton fabric, Dyeing, Thespesia Populnea, Mordants

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Women's empowerment is a process in which women effectively promote their well-being by challenging accepted conventions and culture. Women's empowerment in social and economic dimensions was significantly impacted by their involvement in Self Help Groups (SHGs). In the Karnataka district of Shivamogga, women's empowerment through self-help groups is the subject of this study. Both primary and secondary sources have been used to gather the study's data. The approach used was a multistage random sampling technique. To interpret the data in a way that made sense, average and percentage analysis was done. The Garret ranking method was employed to determine the motivations behind joining the self-help group. To quantify and ascertain the link between the observed variables, factor analysis was performed. The study's findings showed that the SHGs had a higher impact on the recipients' social and economic facts

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Micro Finance, Garret Ranking Technique, Woman Empowerment, SHG, Shivamogga.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract -Present study was carried out to examine the water quality assessment to Tumaria reservoir the observation of physico-chemical parameter of water such as water, temperature, transparency, TDS, PH, DO, alkalinity, chloride, turbidity, velocity. We are determine during study period in order to create the geographic thematic map on, annual variation of physical -chemical parameters. Physico-chemical study on this research paper has help in analyzing the water quality of reservoir in protecting manner to maintain the ecological balance.

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 Keywords

Tumaria reservoir, Physical -chemical parameters, Water quality

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

As far as we are aware, Homo sapiens is the most sentient species on Earth. On the other hand, technology is developing quickly, and it is undeniable that machine learning is now replacing human skills. Arthur McCarthy first used the term artificial intelligence in 1956. The ability of a digital computer or computer-controlled robot to carry out actions typically associated with intelligent beings is known as artificial intelligence (AI). AI has a wide range of applications in the legal field. Technology in the legal field has advanced because of globalization. Artificial Intelligence (AI) is being utilized in courts in nations like the United States and the United Kingdom, where technological advancement has reached incredible heights. The technology is being advanced to assist judges in making decisions. Artificial intelligence is intangible and concentrates on tasks with the help of intelligence techniques such as: But artificial intelligence has the potential to transform everyone's daily life drastically. Whether this is a good or bad thing, we must adhere to the right framework to guarantee that AI has a positive impact.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence (AI), "Intelligence," technology, lawyer, AI Used in Policing

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Nowadays, the usage of credit cards has dramatically increased. As credit cards become the most popular mode of payment for both online and regular purchases, cases of fraud associated with them are also rising. Criminals use fake identification and numerous technologies to attract customers and get cash out of them. Due to the increase in fraud, various techniques and methodologies have been developed for detecting it. In this paper, we discuss the different ways credit card frauds are committed and which machine learning algorithms are used by investigators to detect fraud

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, credit card, fraud detection, SVM, Decision Tree, Logistic regression

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Depression, a primary contributor to the global burden of disease, requires timely identification and intervention to improve outcomes. We propose a multi-modal fusion framework composed of deep convolutional neural network (DCNN) and deep neural network (DNN) models. Our framework considers audio, video and text streams [1]. This study utilizes multimodal fusion, combining text, audio, and visual data, to enhance the detection of depression. Early intervention is crucial in order to prevent long-term consequences, improve treatment response, maintain functionality, reduce the risk of recurrence, prevent symptom escalation, promote physical well-being, and encourage healthy coping mechanisms. Multimodal fusion enables a comprehensive assessment, enhancing accuracy and facilitating the early detection of subtle symptoms. The objective of this research is to create diverse datasets, extract features, develop deep learning models, and evaluate performance, with a focus on contextual understanding. The methodology emphasizes the importance of high-quality and diverse datasets, and various multimodal fusion techniques have shown promising results, achieving high levels of accuracy, sensitivity, specificity, and precision. This research significantly contributes to the advancement of depression detection methodologies, providing a comprehensive solution for this complex mental health disorder.

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 Keywords

Depression, Multimodal fusion, Depression Detection

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In recent years, there has been a lot of interest in study on the growing use of artificial intelligence (AI) in health and medicine. Through the analysis of a patient's medical images and symptoms, AI gives intelligent computer-aided solutions that lead to effective treatment plans and the prediction of future outbreaks. Furthermore, the paucity of studies on the use of AI to certain high-burden diseases points to potential future paths for the field. The purpose of this study is to present real-time examples and issues related to AI in the healthcare sector.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI, Challenges, Healthcare, Real-world Scenarios

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Creative Commons Attribution 4.0 and The Open Definition