Biometric and identification patterns have gained extensive research and application, particularly in iris recognition. The iris harbors a wealth of individual-specific information, making it a vital element in biometric authentication. This article presents a comprehensive study encompassing iris segmentation and identification. We introduce the Weighted Adaptive Hough Ellipsopolar Transform Convolutional Neural Network (WAHET-CNN) as a novel approach for classifying pattern images. Our experimental outcomes demonstrate a commendable 90% accuracy achieved by the proposed WAHET-CNN on the CASIA dataset Version 4.

OBJECTIVES: In exemplar-based image inpainting algorithms, there are often issues with the calculation of patch similarity for matching, suboptimal strategies for selecting matching patches, and low inpainting speed. METHODS: This paper first uses the variable scale cross-scan block line progressive scan to solve the problem of slow scanning speed and invalid priority formula. Then, an improved weight similarity formula is used for searching to solve the problem of poor computing strategy for similar matching patches. The search range of matching patches gradually increases from small to large until globally searching for similar matching patches to improve the efficiency of inpainting. To further improve the correctness of matching patch selection, this paper uses six levels of priority matching criteria for screening. RESULTS: The experimental results show that the inpainting effect of the proposed method is significantly improved in subjective vision, and the structural similarity (SSIM), peak signal-to-noise ratio (PSNR), and inpainting speed of the inpainting results are all improved. CONCLUSION: For different types of images, the proposed method has a better inpainting effect and higher inpainting speed than the other three advanced methods.

Objective: To describe the association of the four main areas of the entrepreneurs' business model with the Business Model Canvas from a systems approach. Methods: Quantitative approach, non-experimental design with descriptive and correlational scope; the sample consisted of 181 entrepreneurs; the instrument used was the questionnaire. Results: The chi-square test showed that there are dependency relationships between the four business areas and the Business Model Canvas (BMC); in addition, there is a positive and significant association between (1) customer interface and the BMC (0.609); (2) product and BMC (0.540); (3) infrastructure management and BMC (0.671) and (4) financial aspects and BMC (0.658). Therefore, the study showed that the four main areas of the entrepreneurs' business model are significantly associated with the nine modules of the Business Model Canvas. Conclusion: Despite the positive and significant association of the areas with the BMC, micro and small business entrepreneurs should seek greater positioning in the market, strengthen their value proposition to be competitive in the market, greater resource planning and key partners, and finally, train and be part of financial inclusion and education.

Exploring the ocean has always been one of the foremost challenges for humankind, and fish classification is one of the crucial tasks in this endeavor. Manual fish classification methods, although accurate, consume significant time, money, and effort, while computer-based methods such as image processing and traditional machine learning often fall short of achieving high accuracy. Recently, deep convolutional neural networks have demonstrated their capability to ensure both time efficiency and accuracy in this task. However, deep convolutional networks typically have a large number of parameters, requiring substantial training time, and the convolutional operations lack attentional mechanisms. Therefore, in this paper, we propose the AttentionConvMixer neural network with Priority Channel Attention (PCA) and Priority Spatial Attention (PSA). The proposed approach exhibits good performance across all three fish classification datasets without introducing any additional parameters, thus demonstrating the effectiveness of our proposed method.

Antisocial behavior (ASB) is one of the ten personality disorders included in ‘The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and falls in the same cluster as Borderline Personality Disorder, Histrionic Personality Disorder, and Narcissistic Personality Disorder. It is a prevalent pattern of disregard for and violation of the rights of others. Online antisocial behavior is a social problem and a public health threat. An act of ASB might be fun for a perpetrator; however, it can drive a victim into depression, self-confinement, low self-esteem, anxiety, anger, and suicidal ideation. Online platforms such as Twitter and Reddit can sometimes become breeding grounds for such behavior by allowing people suffering from ASB disorder to manifest their behavior online freely. In this paper, we propose a proactive approach based on natural language processing and deep learning that can enable online platforms to actively look for the signs of antisocial behavior and intervene before it gets out of control. By actively searching for such behavior, social media sites can prevent dire situations leading to someone committing suicide.

Introduction: lifestyle is an indicator that refers to a set of behaviors and behaviors known as habits that people adopt, and these can be good or bad and this will depend on the life condition of the individual. Aim: to determine the lifestyle of teachers who use ICTs in basic education during COVID-19 in North Lima. Methods: a quantitative, descriptive-cross-sectional study, consisting of a total of 160 patients attending a health facility, who answered a questionnaire of sociodemographic data and the fantastic questionnaire. Results: 5% of the participants have a lifestyle is in danger, 8.1% have a bad lifestyle, 52.5% have a regular lifestyle, 16.3% good lifestyle and 18.1% excellent lifestyle. With respect to the dimension family and friends that, 88.1% have an excellent lifestyle and 11.9% regular lifestyle. With respect to the physical activity dimension, 86.9% have an excellent lifestyle, 2.5% a good lifestyle and 10.6% a bad lifestyle. Conclusions: It is concluded that educational counseling should be implemented on how to maintain a healthy lifestyle and how to prevent risk behaviors that harm health. It is concluded that health should be promoted, since it allows educating people to put into practice how to improve their lifestyle and how to have a healthy diet.

The insufficient number of women in technical occupations has gotten a lot of attention because of the consequences for diversity of genders and creativity in the workplace. The purpose of this research is to critically explore the barriers that prevent women from advancing in technical occupations and to provide ideas for creating a more equitable and welcoming workplace. This study finds important constraints such as gender prejudice, a lack of mentoring, work-life balance issues, and restricted access to leadership chances via a thorough literature analysis. This research looks into the diverse experiences that contribute to these challenges by analysing and interviews with women in technical jobs.Finally, the goal of this study is to equip organisations, governments, and industry stakeholders with practical ideas for implementing evidence-based practises that promote women in technical jobs. By eliminating identified barriers and adopting gender-inclusive initiatives, the tech sector may not only access a larger pool of talent, but also promote an atmosphere favourable to creativity, cooperation, and long-term success.

Sustainable economic development is crucial to secure human welfare and eliminate social inequality. Global leaders have recently made progress towards reaching an agreement on how to convert the current unsustainable economic trends into sustainable green economic growth. The viability of the green economy depends on several variables, including governmental policy, the business climate, and environmental concerns. The presented paper examines the implementation of green economic policies and analyses government strategies and initiatives taken by the government at the national level. The study uses a descriptive-analytical approach. The study finds India is putting many regulations and initiatives into place to encourage the effective use of energy in a variety of economic areas, including green building, equipment, farming, mobility, and fuels. These green growth initiatives lower the economy's carbon intensity and provide a sizable number of green jobs.

INTRODUCTION: The research on the multi-mode fusion of college students' independent learning ability cultivation method is conducive to college students' change of learning mode and learning thinking, improvement of the utilization rate of educational resources, and the development of the academic environment as well as the reform of the educational concept. OBJECTIVES: Aiming at the problems of college students' current independent learning mode, such as the need for more in-depth research and the single study means. METHODS: A method for cultivating college students' autonomous learning ability through the integration of intelligent optimization algorithms and multiple modes has been proposed. Firstly, the practices of analyzing the current college students' autonomous learning mode and multiple learning modes are analyzed; then, using the butterfly optimization algorithm, a weight optimization method for the cultivation of college students' independent learning ability based on the fusion of multiple modes is proposed; finally, the validity and robustness of the proposed method are verified through experimental analysis. RESULTS: The results show that the proposed method has a high cultivation effect. CONCLUSION: Solves the problem of fusion of college students' independent learning ability cultivation modes.

ChatGPT is a cutting-edge language model that has been making waves in the field of natural language processing. However, its capabilities extend far beyond language-based applications. ChatGPT can also be used as a powerful tool for debugging software code. As software applications become increasingly complex, the need for efficient and accurate debugging tools has become more pressing. ChatGPT's ability to analyze and understand code makes it a promising solution to this challenge. Debugging is a critical part of the software development process. Bugs, or errors in code, can have serious consequences for the functionality and security of software applications. Identifying and fixing bugs can be a time-consuming and labor-intensive process, requiring the expertise of experienced developers. ChatGPT has the potential to streamline this process and make it more accessible to a wider range of developers, regardless of their experience level. In this article, we will explore the capabilities of ChatGPT as a debugging tool, the advantages and limitations of using it, and best practices for integrating it into the software development workflow. ChatGPT is a cutting-edge language model that has been making waves in the field of natural language processing. However, its capabilities extend far beyond language-based applications. ChatGPT can also be used as a powerful tool for debugging software code. As software applications become increasingly complex, the need for efficient and accurate debugging tools has become more pressing. ChatGPT's ability to analyze and understand code makes it a promising solution to this challenge. Debugging is a critical part of the software development process. Bugs, or errors in code, can have serious consequences for the functionality and security of software applications. Identifying and fixing bugs can be a time-consuming and labor-intensive process, requiring the expertise of experienced developers. ChatGPT has the potential to streamline this process and make it more accessible to a wider range of developers, regardless of their experience level. In this article, we will explore the capabilities of ChatGPT as a debugging tool, the advantages and limitations of using it, and best practices for integrating it into the software development workflow.