Volume 12 | Issue 5

 Abstract

Abstract-- The first is evaluating and tracking the quality of sleep, recognizing the substantial influence of stress on physical well-being. The study also includes facial landmarks as an extra dimension for stress detection at the same time. The first part is evaluating and tracking the quality of sleep, recognizing the substantial influence of stress on physical well-being. The study also includes facial landmarks as a further dimension for stress detection at the same time. The new tactic is deriving visual information from face emotions using computer vision algorithms. In order to provide a user-friendly experience for stress detection, our technique strives to be non-invasive. The suggested hybrid method uses machine learning techniques to combine information from face landmarks and sleeping patterns to provide a thorough stress prediction. The final objective is to develop an AI model that offers a reliable and comprehensive method of stress detection by fusing the knowledge from facial expressions and sleep-related data. This groundbreaking study confirms the value of multi-modal techniques in comprehending and treating stress-related problems and advances the rapidly developing area of computational psychology.

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Facial Expression, Stress, Sleep Disorders. Convolutional Neural Network (CNN), OpenCV, and Deep Learning.

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The envisioned innovation, a Blockchain-fueled Online Assessment Framework empowered by Smart Contracts, endeavors to redefine conventional examination methodologies through cutting-edge blockchain technology. This pioneering concept envisions an infallible and open assessment ecosystem driven by smart contracts. It aims to grant students the flexibility to undertake exams globally, liberating them from physical test centers. By eliminating reliance on external invigilators, it ensures cost reduction and upholds integrity. The system's architecture comprises four integral facets: the blockchain, smart contracts, a user-friendly interface, and an authentication framework. The blockchain's decentralized ledger forms the bedrock, ensuring tamper resistance crucial for a foolproof examination structure. Smart contracts, programmed for impartial execution, safeguard the fairness and integrity of the examination process. The user interface grants students seamless access to examinations, while the authentication mechanism guarantees entry solely to authorized users. This revolutionary system promises heightened efficiency, fortified security, and unparalleled transparency in examination procedures. It offers educational institutions a robust, secure, and streamlined examination mechanism, augmenting the credibility imperative in today's competitive academic sphere. Moreover, it alleviates expenses linked with traditional exam setups, eradicating the need for physical centers and invigilators. T

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Blockchain, Secure, Smart Contract, Solidity, Metamask, Ganache.

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The Multi Banking System Interface is targeted to the future banking solution for the users who is having multiple bank accounts in multiple banks. This interface integrates all existing banks and provides business solutions for both retail and corporate.This system acts as a standard interface between the clients and all the banks, By using this portal any client who maintain accounts in various banks can directly log on to Multi Banking System Interface and make any kind of transactions. In the back end, system will take care of the entire obligation required in order to carry on transaction smoothly.

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admin ,multi-banking ,customer, module, design, architecture

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Denial-of-Service (DoS) attacks are a constant threat to online services. These attacks aim to overload a target system with junk traffic, like a crowded store entrance that prevents legitimate customers from entering. Attackers exploit weaknesses in internet infrastructure to hijack compromised computers and launch large-scale assaults. Different DoS tactics include flooding servers with useless requests, sending corrupted data packets to crash the system, or taking advantage of software flaws. The paper then explores the reasons behind DoS attacks, which can range from trying to extort money or disrupt critical services for personal gain, to promoting a political agenda. Successful DoS attacks can have serious consequences, causing financial losses, damaging reputations, and interrupting essential services like online banking or communication. Mitigating DoS attacks involves several strategies. Traffic filtering techniques act like security guards, checking incoming traffic for suspicious patterns. Additionally, systems are employed to detect and prevent Denial-of-Service (DoS) attacks, which involve coordinated attacks from many compromised computers. Content Delivery Networks (CDNs) also play a role by distributing traffic across multiple servers, making it harder for attackers to overwhelm a single system. The paper concludes by highlighting the ongoing need to develop better defenses against DoS attacks as attackers constantly adapt their methods. One promising approach is the Random Forest method, a machine-learning technique that uses multiple decision trees to identify malicious traffic. Think of it as a team of experts, each with a slightly different perspective, working together to make a more accurate decision. Random Forest is particularly useful because it can handle complex data and is less prone to errors, making it a valuable tool in the fight against DoS attacks.

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Denial-of-Service (DoS) Attacks, Random Forest Algorithm, Network Traffic Analysis, Intrusion Detection Systems (IDS), Machine Learning in Security, Attack Mitigation Strategies, Internet Protocol (IP) Blocking, Traffic Filtering Techniques

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There are numerous attack types a hacker may carry out these days. One of the popular ones is malware, which can be malicious code or a section of code. It is usually created for the purpose of damaging an operating system of a device. The python programming is the most common form of malware and it is in the form of virus, worm, trojans, ransomware, spyware, adware and more. The machine learning technique is used by the python programming to classify malware samples using a decision tree classifier. It is a kind of supervised learning algorithm that is responsible for data pre-processing first and then identifying experience features. The model is trained on a training dataset and evaluated using a testing dataset, as it parted the data into two parts - for testing and training. Classifier using a decision tree works by recursively dividing feature space, choosing the node on which to base the decision to only consider feature values at each node. Generally, the classifier runs with the default hyperparameters, but these parameters can be adjusted to suit specific needs. The model being evaluated uses an f1-score metric that's convenient to identify what it can classify it as malware (1) or benign (0). The dataset undergone in training and testing of dataset and it show the 99% of accuracy with the decision tree algorithm

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Malware, Benign, Decision tree, Accuracy

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This study aimed to assess the relationships between intrinsic motivation, employee engagement, and organizational commitment among Generation Z employees in India. With Generation Z entering the workforce, understanding their unique motivational drivers and organizational attitudes is crucial for effective talent management. The study employed a quantitative, correlational design, utilizing the Intrinsic Motivation Inventory, Utrecht Work Engagement Scale, and Organizational Commitment Questionnaire. Data was collected from 150 Generation Z working professionals aged 27 or below in India. The results revealed positive and statistically significant correlations between all three variables. Intrinsic motivation was positively correlated with organizational commitment (r=0.477, p<0.01), indicating that intrinsically motivated employees tend to exhibit higher levels of commitment. Employee engagement also showed a positive correlation with organizational commitment (r=0.473, p<0.01), suggesting that engaged employees experience stronger attachment to their organization. Furthermore, regression analysis demonstrated that both intrinsic motivation (?=0.296) and employee engagement (?=0.290) significantly predicted organizational commitment, highlighting their importance in fostering commitment among Gen Z employees. The findings underscore the interconnected nature of these constructs, aligning with theoretical frameworks like Self-Determination Theory and the Job Demands- Resources Model. By nurturing intrinsic motivation and creating engaging work environments, organizations can potentially enhance organizational commitment and address retention challenges with the Generation Z workforce.

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Intrinsic Motivation, Employee Engagement, Organisational Commitment, Generation Z

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A 42-year-old female came to OP with pain in her right shoulder joint that started about 20 years back after an accident. Then she had an injury on the right shoulder joint, a head injury, and a fracture of the right clavicle. Plastic surgery was done for the same. After that took ayurvedic treatment and got temporary relief for all her complaints. Now she complains of pain in the right shoulder joint, right side of neck, and right scapular area with limitation of movement of the right hand. C T Scan of the right shoulder joint showed calcification in the superficial aspect of the right trapezius muscle. Now taking Homoeopathic treatment for the last 3 months. She was admitted in Govt. Homoeopathic Medical College and Hospital Thiruvananthapuram on 08/04/2024 and now her complaints are under control.

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Myositis ossificans, Homoeopathic treatment, Individualization.

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In recent years, there has been a growing interest in incorporating natural ingredients into skincare products due to their perceived safety and potential therapeutic benefits. Bael fruit (Aegle marmelos) is a well-known botanical resource with a rich history in traditional medicine. The utilization of natural ingredients in personal care products has gained significant attention due to their perceived safety and potential therapeutic benefits. This study focuses on the formulation and evaluation of herbal soap enriched with bael fruit pulp, aiming to harness its antimicrobial and skin-nourishing properties. Bael fruit (Aegle marmelos) has been traditionally acclaimed for its medicinal value, containing bioactive compounds with antioxidant and anti-inflammatory attributes. The formulation process involved the integration of bael fruit pulp extract into a soap base, optimizing concentrations to ensure efficacy and stability. Various physicochemical parameters such as pH, moisture content, and foaming ability were assessed to determine the quality of the formulated soap. Results demonstrated that the incorporation of bael fruit pulp extract enhanced the functional properties of the herbal soap, exhibiting satisfactory pH balance, adequate moisture retention, and substantial antimicrobial activity. Furthermore, patch testing revealed promising skin tolerance, indicating the formulation's potential for safe and effective use in personal hygiene. The formulated herbal soap utilizing bael fruit pulp presents a promising natural alternative in the realm of skincare, offering potential benefits in cleansing, moisturizing, and microbial protection, thus warranting further exploration and commercialization in the cosmetics industry.

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Herbal soap, Bael fruit pulp, Formulation, Evaluation, Antimicrobial activity, Skin compatibility

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Creative Commons Attribution 4.0 and The Open Definition

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Diabetes mellitus is a chronic metabolic disorder caused by carbohydrate, fat, and protein metabolism problems. Genetic predispositions and environmental influences contribute to the disease, presenting significant challenges to patients' health. There are two types of diabetes, Type I and Type II. Both lead to elevated blood glucose levels (hyperglycemia). Several complications are associated with persistent hyperglycemia, including microvascular problems affecting the eye, kidneys, and nerves, as well as macrovascular problems like accelerated artery hardening, which increases heart disease, stroke, and peripheral artery disease risks. It is essential to focus on the prevention and management of diabetes-related complications in order to mitigate their impact on micro and macrovascular health. It is important to consider alternative treatment options as these medications can pose undesirable side effects. Medication, dietary adjustments, and regular exercise are all part of comprehensive diabetes management. Our study was aimed of the present study is to explore the anti-oxidant and anti-diabetic activity in the leaves of Stachytarpheta urticifolia. A comprehensive study was conducted to examine Stachytarphata urticifolia, a traditional botanical remedy, for its phytochemical composition, antioxidant potential, and effectiveness against diabetes. In this study, Stachytarphata urticifolia was found to exhibit significant diabetic-fighting and anti-oxidant properties. In addition to phenolic compounds, flavonoids, alkaloids, and terpenoids, Stachytarphata urticifolia contains hundreds of bioactive compounds. Phytochemicals such as these, which possess anti-oxidant and anti-diabetic properties, are considered to be promising therapeutic choices for humans who are suffering from diabetes or metabolic disorders. Stachytarphata urticifolia has shown remarkable antioxidant activity over the past few decades, which has been demonstrated to be helpful in preventing oxidative damage and preventing the onset of chronic diseases like diabetes by battling free radicals and combating oxidative stress. The in vitro studies of S. urticifolia were conducted in order to evaluate its anti-diabetic potential. There have been studies conducted in vitro that examined key enzymes associated with carbohydrate metabolism in an attempt to determine whether Stachytarphata urticifolia inhibits carbohydrate digestion and absorption by inducing moderate inhibitory effects on amylase, glucose oxidase, and glucose uptake. There was no doubt that S. urticifolia is capable of reducing complications associated with diabetes and these findings suggest that it may be useful for patients with diabetes who need to mitigate these complications. As part of this study, we examined S. urticifolia, a well-known traditional plant, for its phytochemical composition and potential anti-oxidant and anti-diabetic effects. The anti-oxidant potential of S. urticifolia and its moderate anti-diabetic activity were also found in our study. Based on the results of this study, S. urticifolia might be of benefit to diabetic patients as a therapeutic agent.

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Antioxidant, Stachytarpheta urtifolia, Anti-Diabetic, Plant Extract.

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ABSTRACT: Coimbatore, a prominent industrial hub in South India, is embarking on a journey towards green sustainability amid mounting environmental challenges. This paper provides an overview of the city's initiatives, challenges, and future directions in pursuit of sustainable development. Key initiatives include the promotion of renewable energy sources, implementation of waste management systems, adoption of eco-friendly transportation solutions, and encouragement of green building practices. However, Coimbatore faces challenges such as rapid urbanization, inadequate infrastructure, and limited public awareness. Despite these obstacles, the city is committed to advancing its sustainability agenda through policy interventions, public-private partnerships, and community engagement. Future directions entail enhancing green infrastructure, fostering innovation in sustainable technologies, and fostering a culture of environmental stewardship.

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Keywords: Coimbatore, sustainability, green initiatives, renewable energy, waste management, urbanization, challenges, future directions.

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The project aims to predict water quality based on nine factors: pH, hardness, solids, chloramines, sulfates, conductivity, organic carbon, trihalomethanes and turbidity. It estimates water by separating it into drinkable and non-drinkable water. If the water is deemed undrinkable, further evaluation will determine whether the water is suitable for agricultural or commercial use. This project uses Python and Flask for front-end integration and Jupyter Notebook for modeling. The random forest algorithm was validated after comparison with SVM, logistic regression, and decision tree algorithms, which proved to be more accurate. The user interface includes a home page with a set of parameters and a parameter value map. Additionally, PDF reports allow direct parsing of parameter values from uploaded files. Once the product is delivered, the model predicts water quality and provides results indicating potential or recommended use.

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Water quality, potable and non-potable, python, random forest, accuracy, crucial parameters.

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The report looks at the development of communication skills and content creation by examining practices such as email composing, content writing, grammar correction, and translation. It demonstrates capabilities to improve competitive performance and accuracy using advanced machine learning algorithms and language processing techniques. Motivations driving AI development include the need to improve processes and increase productivity, as well as challenges such as integrity and ethics. Additionally, the report highlights the role of AI in shaping the future of communication and content creation by helping experts create content that is good and adapted to digital needs. Finally, it aims to provide an overview of the potential of artificial intelligence to support significant advances in these fields.

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AI Tools, Flutter Mobile App, Development Email Generator, Summary Writer ,Grammar Correction ,Translation, Natural Language Processing (NLP) Machine Learning ,Artificial Intelligence Integration, User Interface (UI), User Experience (UX) ,Mobile Application ,Cross-Platform Development ,Automated Content Generation, Language Translation

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plastic contamination is terrible issue nowadays. The oceans are flooded with plastic waste, which even cause it's entering into our food chain. Such bottles are constructed from high density plastics that are typically, bottles used to store liquid such as water, soft drinks, motor oil, cooking oil, medicine, shampoo, milk and ink. they are non-biodegradable and improper disposal of such products will definitely have a huge impact on our environment. Advances in technologies and system for collection, sorting and reprocessing of non recyclable plastics are creating new opportunities for converting such bottles into useful products. This work is an attempt to figure out solution to the disposal of plastic bottles that are usually dumbed into open environment. Bottles that are commonly arrive at disposal sites Poly Ethelyne Terephthalate (PET). We can PET bottles cut into strips, twisted and heated into a rope using an automated machine which consist of a cutting unit, temporary plastic strip storage unit and strip joining unit. This is not only solving the ill effects caused by disposal plastic bottles but also helps our society move towards sustainability. for this use of numerical solutions has been wide spread in a many engineering fields and related areas. One of the main numerical methods used in modeling and simulations is the finite element method (FEM). As result, it is expected greater FEM dissemination in rope making machine for analysis can be used in simulate how entire structure or system behaves and used in order to represent the increasing behavior of rope making machinery.

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Keywords:- Plastic, non-biodegradable, recycle, analysis, plastic bottles, disposal, environment, PET bottles, rope, FEM.

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This paper presents an in-depth exploration of Programmable Logic Controllers (PLCs), covering their hardware and software components, programming languages, advanced techniques, and applications across industries. It begins with an overview of PLC technology, discussing its historical background and fundamental principles. The paper examines PLC hardware, including architecture and I/O modules, and software aspects, such as programming languages like Ladder Logic and Structured Text. Additionally, advanced PLC programming concepts are explored, including modular programming, error handling, and integration with other systems. Recent trends like IoT integration, edge computing, and enhanced HMIs are discussed, along with challenges such as cybersecurity threats and skill shortages. The paper concludes with insights into the future directions of PLC technology, emphasising the importance of addressing current challenges and embracing emerging trends. This paper serves as a valuable resource for researchers, practitioners, and students in the field of industrial automation and control systems, offering comprehensive insights into the evolving landscape of PLC technology.

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PLC, Industrial Automation

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Breast cancer, a complex disease driven by environmental, behavioral, and genetic factors, remains a significant health challenge. Carcinogenesis in breast cancer involves processes such as evasion of apoptosis, limitless proliferation, enhanced angiogenesis, resistance to anti-growth signals, and metastasis. Early detection and effective management are critical for improving survival rates, which vary significantly between high-income and low-income countries. Pathophysiology encompasses genetic and molecular alterations, including mutations in key pathways (P13K/AKT, RAS/MEK/ERK) and abnormal growth factor signaling, leading to uncontrolled cell division and tumor progression. Diagnosis employs techniques such as mammography, MRI, ultrasonography, and biopsies, with mammography being the most prevalent screening method. Risk factors include age, hormonal status, reproductive history, diet, and genetic predispositions. Treatment strategies for non-metastatic breast cancer combine local (surgery, radiation) and systemic therapies (hormonal, chemotherapy, targeted therapies), tailored to tumor subtypes. Advances in systemic therapies, particularly for triple-negative breast cancer, include PARP inhibitors and immunotherapy. Non-coding RNAs also play a crucial role in cancer progression and treatment response. Recent therapeutic advancements emphasize personalized approaches, genomic testing, and fertility preservation for young patients. The integration of multidisciplinary care and ongoing research into targeted and supportive therapies, such as bisphosphonates for bone metastasis, underscores the dynamic and evolving landscape of breast cancer treatment.

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Breast cancer, Screening methods, Genetic mutations, Treatment strategies, Triple-negative breast cancer

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Around 3oo million individuals in the world suffer from osteoporosis, a condition where bones become weak and prone to fractures due to low bone density and poor bone structure. Fractures related to osteoporosis can lead to increased pain, disability, healthcare costs, and even mortality. Diagnosis typically involves measuring bone mineral density using a noninvasive technique called dual-energy X-ray absorptiometry. A systematic review was conducted to know the impact of osteogenic coatings on implant integration in osteoporotic condition.

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Osteoporosis, implant, prosthodontics, bone loss, Dentistry, Bisphosphonates ,bone mineral density

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Creative Commons Attribution 4.0 and The Open Definition

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Because of its reliance on human sight, glaucoma presents significant diagnostic challenges and is the primary cause of irreversible blindness globally. However, recent breakthroughs in deep learning have demonstrated promise for automated review. In this study, we examine current research of the use of retina, corneal optical coherence tomographic imaging, & visual field image in AI-based glaucoma being diagnosed, with a particular emphasis on deep learning approaches. To increase the technique's repeatability, we propose a redesigned taxonomy that categorises it into structural paradigms and connects to accessible source code. We identify shortcomings in performance related to multimodal integration, generalizability, and uncertainty estimates by doing thorough benchmarking on publicly available datasets. Furthermore, our study highlights issues including bias, labelling discrepancies, and size while curating important datasets. We present open research questions and suggest fruitful avenues for further investigation. It is anticipated that this survey will be helpful for ophthalmologists looking to enhance clinical processes and diagnosis utilising the most recent AI outcomes, as well as AI researchers looking to convert breakthroughs into practice.

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Deep learning, fundus pictures, glaucoma, and early diagnosis are the index terms.

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This work describes the use of PLC control and SCADA technology to automate a bottle filling system. The objective of the developed system is to facilitate the process of filling a bottle with liquid substances in manufacturing plants using a controlled process rather than manual operation, which enhances performance, precision and consistency. The PLC is the primary system component, and the sensors and actuators work in conjunction with it to ensure compliance with certain levels and standards for the filling process. The SCADA also provides a means of remotely monitoring and controlling the system, supporting alarms and records, and data acquisition and display. The integration of PLC and SCADA offers a comprehensive solution for bottle filling applications, enhancing productivity and quality while reducing human intervention. Experimental results demonstrate the effectiveness and robustness of the proposed system in industrial environments.

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Bottle filling system, PLC, SCADA

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Creative Commons Attribution 4.0 and The Open Definition

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The aim of the study is to determine the influence of differentiated landscape management on the distribution on abundance of butterfly species. The objective of this study were to asses butterfly communities and to determine the influence of disturbance on butterfly individuals, species richness and composition with in four SGPGI Campus management Area ( A1 Entry Area, A2 Road side Area, A3 Hospital Area ).The survey is conducted between February 2024 to May, 2024 using Photographs and direct seen and observed. The pattern of butterfly abundance and species richness are studied in study areas at SGPGI Campus Lucknow. A total 18 butterfly species found which is belonging to Hesperiidae, Papilionidae, Pieridae, Lycaenidae and Nymphlidae families were recorded at the 4 areas( Biotopes ).However the SGPGI Campus which surrounded by the Anthropogenic activities are due to this human activities butterfly diversity abundance are badly ffected. Therefore it's important to protect habitat and dry season water for the conservation of butterflies.

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Butterflies, SGPGI Campus Sites, Diversity, Abundance, Environment, Habitat, Human activities.

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This study aims to optimize the mechanical properties of 3D printed ABS components through the manipulation of infill patterns, densities, and layer thickness. ABS material was specifically chosen for its superior mechanical properties when compared to standard materials such as PLA and Nylon 6. By investigating various infill patterns (line, triangle, concentric), infill densities (75%, 80%, 85%), and layer thicknesses (0.1 mm, 0.2 mm), a total of 18 experimental conditions were examined, each replicated for tensile and compression tests following ASTM D638 and ASTM D695 standards, respectively. The experimental setup involved the utilization of a Robust Enough 3D printer and Simplify 3D software for precise slicing and printing. The study's outcomes provide valuable insights into optimizing the design and manufacturing processes of 3D printed ABS components, thereby contributing to advancements in additive manufacturing technology. Through a systematic exploration of these key process parameters, this research enhances the understanding of how infill patterns, densities, and layer thickness impact the mechanical performance of 3D printed ABS objects.

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ABS, FDM, FEA, Additive manufacturing, Tensile strength, Compression strength.

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Creative Commons Attribution 4.0 and The Open Definition