Volume 11 | Issue 11 |

 Abstract

"Quadrocrack?r: A Guid? to Ethical P?n?tration T?sting" is a compr?h?nsiv? handbook d?sign?d to assist individuals and organizations in und?rstanding and conducting ?thical p?n?tration t?sting. P?n?tration t?sting, oft?n r?f?rr?d to as ethical hacking, is a crucial cyb?rs?curity practic? aim?d at id?ntifying vuln?rabiliti?s and w?akn?ss?s in comput?r syst?ms, n?tworks, and applications b?for? malicious actors can ?xploit th?m. This guid? d?lv?s into th? fundam?ntal conc?pts of p?n?tration t?sting, providing a d?tail?d ov?rvi?w of its obj?ctiv?s, m?thodologi?s, and th? ?thical consid?rations that und?rpin this practic?. It ?mphasiz?s th? importanc? of obtaining ?xplicit p?rmission from syst?m own?rs b?for? conducting any p?n?tration t?sting to ?nsur? complianc? with l?gal and ?thical standard.

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 Keywords

quadrocracker, network penetration testing, vulnerabilities, attack.

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 Abstract

The goal of a global strategy on digital health is to encourage wellness and healthy living for all people, in every place, and at all stages of life. National or regional digital health projects need to be supported by a strong strategy that combines organizational, human, economic, and technological assets in order to realize their true potential. Digital Pills are an advanced drug-device technology that enables the association of conventional drugs with a monitoring system that automatically records patient physiological data as well as information regarding medication adherence. Digital adherence technology may offer promising patient-focused approaches to adherence monitoring. A variant of the subsequent generations of antipsychotic aripiprazole that was implanted with a sensor (Abilify MyCite) received FDA approval in November 2017. The study focuses on the digital health strategies and impacts around the pill and offers a thorough analysis of it.

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Abilify MyCite

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Creative Commons Attribution 4.0 and The Open Definition

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Bikers who do not wear helmets pose a major threat to themselves. A UN Motorcycle study done in 2021 showed that around fifteen thousand deaths of bike riders could be avoided annually in India with safety measures. It also mentions that wearing helmets improves the chances of surviving accidents by 42 % and helps riders to avoid injuries by 69 %. Due to large vehicular traffic, manual monitoring of vehicles has become a problem. This can be automated using Deep Learning, which is the purpose of our work. Motorcycles have always been the primary mode of transportation in developing countries. Motorcycle accidents have increased in recent years. One of the main reasons for fatalities in accidents is that a motorcyclist does not wear a protective helmet. The most common way to ensure that motorcyclists wear a helmet is by traffic police to manually monitor motorcyclists at road junctions or through CCTV footage and to penalize those without a helmet. But it requires human intervention and effort. So this system Proposes an automated system for detecting motorcyclists who do not wear a helmet and retrieving their motorcycle number plates from CCTV video footage First, the system classifies moving objects as motorcycling or non motorcycling. In the case of a classified motorcyclist, the head portion is located and classified as a helmet or non-helmet. Finally, for the motorcyclist identified without a helmet, the number plate of the motorcycle is detected and the characters on it are extracted by using the OCR algorithm.

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 Keywords

Helmet Detection, Machine Learning, Opencv, Image Selection, Extraction Ocr

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COPD is a major global health issue, with an increasing morbidity and mortality rate. By 2020, it was estimated to result in over 6 million deaths annually. COPD is associated with various comorbidities, including chronic heart failure, hypertension, diabetes, osteoporosis, and more. Smoking, the primary risk factor for COPD, is also a major contributor to these comorbidities. Smoking not only affects the lungs but also various other organs, leading to cardiovascular complications and other chronic conditions in COPD patients. The number of comorbidities in COPD patients is associated with increased hospital deaths, and these conditions significantly affect the quality of life. Highly prevalent comorbidities, such as heart failure and diabetes, are linked to a decrease in the quality-of-life scores. Traditional lung function tests, like FEV1, inadequately correlate with COPD symptoms and comorbidities. Therefore, new multidimensional indices have been developed to better assess COPD and its comorbidities. The article explores various mechanisms underlying COPD and its comorbidities, including smoking, hypoxia, inflammation, endothelial dysfunction, platelet reactivity, arterial stiffness, and coronary artery disease. The management of COPD and its comorbidities involves long-term oxygen therapy and pharmacologic treatments. Oxygen therapy not only reduces mortality but also improves various aspects of patient health. Corticosteroid treatment approach Leads to multiple chronic disease conditions so alternate drug regimen. The effects of pharmacologic treatments on COPD mortality remain a subject of research. The article concludes by emphasizing the need for a comprehensive and multidisciplinary approach to managing COPD and its comorbidities.

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COPD is a major global health issue, with an increasing morbidity and mortality rate. By 2020, it was estimated to result in over 6 million deaths annually. COPD is associated with various comorbidities, including chronic heart failure, hypertension, diabetes, osteoporosis, and more. Smoking, the primary risk factor for COPD, is also a major contributor to these comorbidities. Smoking not only affects the lungs but also various other organs, leading to cardiovascular complications and other chro

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Autonomous vehicles rely on a multitude of sensors and intelligent systems to navigate safely and efficiently. This paper presents a comprehensive Lane Detection and Speed Breaker Warning System designed to enhance the capabilities of autonomous vehicles using advanced machine learning algorithms. The primary goal is to improve the vehicle's perception of the road environment, specifically focusing on accurate lane detection and timely recognition of speed breakers. The proposed system integrates a combination of computer vision techniques and machine learning algorithms to achieve robust performance in real-world scenarios. For lane detection, a convolutional neural network (CNN) is employed to analyze camera inputs and identify lane boundaries. This enables the vehicle to precisely follow the road markings, ensuring safe navigation within lanes. To address the challenge of speed breaker detection, a machine learning model is trained on a diverse dataset containing images of roads with varying types and conditions of speed breakers. The model is designed to classify road segments and predict the presence of speed breakers ahead. When a speed breaker is detected, the system activates a warning mechanism to alert the autonomous vehicle, allowing it to adjust its speed and suspension settings accordingly. The effectiveness of the proposed system is evaluated through extensive simulations and real-world testing scenarios. The results demonstrate a significant improvement in lane-keeping accuracy and the ability to anticipate and respond to speed breakers proactively. The Lane and Speed Breaker Warning System contributes to the overall safety and reliability of autonomous vehicles, making them better equipped to handle diverse road conditions.

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 Keywords

Autonomous Vehicles, Lane Detection, Speed Breaker Warning, Machine Learning, Convolutional Neural Network, Computer Vision, Road Safety.

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Efficiency in the manufacturing industry is paramount for ensuring competitiveness, cost-effectiveness, and overall business success. This research paper presents a comprehensive analysis of the factors contributing to employee efficiency losses in the manufacturing sector, along with strategies to enhance productivity. The study draws on both qualitative and quantitative research methodologies, including surveys, interviews, and performance data analysis. The paper begins by identifying the primary causes of efficiency losses, which encompass factors such as outdated equipment, inadequate training, workplace distractions, lack of motivation, and suboptimal production processes. Through the examination of real-world case studies and data collected from various manufacturing firms, the paper quantifies the extent of efficiency losses and their impact on overall productivity and profitability. In the second part of the study, the paper discusses various improvement strategies and interventions that manufacturing organizations can adopt to mitigate efficiency losses. These strategies include the implementation of advanced manufacturing technologies, investing in employee training and skill development, creating a supportive and motivating work environment, and streamlining production processes. The study underscores the importance of a holistic approach, recognizing that there is no one-size-fits-all solution, and a combination of strategies tailored to the specific needs of each organization is often the most effective. The research also highlights the role of leadership and management in driving and sustaining employee efficiency improvements. Effective leadership, clear communication, and strategic alignment are essential components of a successful efficiency enhancement strategy. Ultimately, this research paper provides valuable insights for manufacturing industry professionals, policymakers, and researchers. It underscores the significance of addressing efficiency losses and offers a roadmap to better understand, quantify, and address these challenges, ultimately leading to enhanced competitiveness and sustainable growth in the manufacturing sector.

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 Keywords

Efficiency, Employee, losses, manufacturing

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

MENTAL HEALTH AND DEFENCE MECHANISM

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MENTAL HEALTH AND DEFENCE MECHANISM

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E-Learning is the delivery of educational materials, online courses, training, and lessons through laptops, smartphones, and tablets. It allows students to receive the necessary information anytime from any part of the world. E-Learning, or electronic learning, is the delivery of learning and training through digital resources. Although eLearning is based on formalized learning, it is provided through electronic devices such as computers, tablets and even cellular phones that are connected to the internet. This makes it easy for users to learn anytime, anywhere, with few, if any, restrictions. Basically, eLearning is training, learning, or education delivered online through a computer or any other digital device. Different studies have found that participants learn five times more material in online learning courses using multimedia content than in traditional face to face courses. Because online courses give students full control over their own learning, students are able to work at their own speed. This paper explores the current rising rates of online learning in higher education. It examines issues and challenges are activated differently online and the impact of this on learning and teaching through the internet and the accessibility of two of the most popular learning management systems, Blackboard and Moodle, and the different approaches, benefits and problems associated with each system. It then explores the eLearning environment beyond the structure of a LMS to a broader digital campus that includes social networks, video hosting sites and micro blogging, where students and staff are increasingly expanding the learning and social environment in higher education..

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e-Learning, Higher Education, Learning Management Systems

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Creative Commons Attribution 4.0 and The Open Definition

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Mutual fund industry has veterana radical growth in the earlier periodof two decades.Raise in the number of schemes with improved mobilization of funds in the past fewyears notes the importance of Indian mutual funds industry. To fulfill the potential ofmillions of retail investors, the mutual funds are requisite to function as successfulinstitutional investors. Proper evaluation of various fund performance and theircomparison with other funds helps retail investors for creating investment decisions. The main aim of this paper is to evaluate the performance of mutual fundschemes ranked 1 by CRISIL and associate these returns with SBI domestic term depositrates. Bearing in mind the interest of retail investors simple statistical techniques likeaverages and rate of returns are used. The results achieves from the study clearly represents that, in most of the cases the mutual fund schemes have failed even to provide the return of SBI domestic term deposits.

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Mutual Fund Schemes, Performance, Returns, CRISIL, Credit Rating Agency, SBI domestic term deposits.

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Creative Commons Attribution 4.0 and The Open Definition

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The present study focuses on the two versions of Mughal harem. First the culture of purdah, privacy and chastity and the other version of European travelers which is totally based on local gossips and misinformation. The study revolves around the norms, rules and regulations of the harem. The system of surveillance and protection is also being discussed.

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 Keywords

Eunuchs, chaste, purdah, pleasure.

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Creative Commons Attribution 4.0 and The Open Definition