Volume 12 | Issue 5

 Abstract

Azithromycin is a commonly self-medicated antibiotic. It is frequently chosen by individuals for self-medication purposes. However, It is vital to remember that self-treatment with azithromycin should be done with caution and under the guidance of a healthcare professional. Azithromycin is primarily utilized for the treatment of bacterial infections in different body areas such as the lungs, sinuses, and skin. It is not effective against viral infections and should not be used as a pain reliever. While The use of it while nursing is typically safe., individuals with cardiac issues ought to stay away from it. It is crucial to take the full course of antibiotics as prescribed by a doctor and refrain from using antibiotics without a prescription to prevent irrational and injudicious use.

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 Keywords

azithromycin , pain- reliever , antibiotic , self-medication , sinuses

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 Abstract

IoT-related and smart home technologies are evolving quickly, and a range of smart gadgets are being created to enable consumers to live more comfortably. Nevertheless, the lack of operating systems to connect the gadgets that make up the smart home environment limits the smart houses that are already in place. This is due to the fact that these devices are built on self-service modules and utilize separate IoT platforms created by the brand or company who created them. If a smart home doesn't have an integrated operating system, managing each device separately becomes a burden for the user. Additionally, this results in address issues like energy waste and high traffic on the smart home network. The development of an integrated management system is required to address these issues. solution that enables inter-IoT device communication. To effectively oversee IoT, we suggest As IoT platform application services for a smart house, three intelligent models are provided. The Intelligence awareness target as a service (IAT), intelligence energy, and three more models' efficiency in the cloud (IE2S) and TAS (intellectual service) (IST). IAT is in charge of "things" phase. IAT gathers data based on the environment by using intelligent learning to develop a situational awareness of the data values produced by things (sensors). Processing the data gathered by IAT, IE2S acts as a server (IoT platform). The server runs on the open-source, worldwide standards-compliant Mobius platform, and artificial intelligence is facilitated by the TensorFlow engine. In order to assist in automatically providing service, IE2S examines and learns from the users' usage habits. IST aids in the provision, management, and control of the service stage. The Internet of Things (IoT) gadgets in a smart home may collaborate with one another thanks to these three clever models.

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 Keywords

IOT, Artificial Intelligence, Automation, Energy efficiency, Smart home, Sensors.

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Heavy metals are among the most important sorts of contaminant in the environment. Heavy metals are responsible for various health hazards in human beings, pertaining to their property of persistence and bio-magnification. Levels of mercury in the environment are increasing due to discharge from hydroelectric, mining, pulp, and paper industries. The most harmful forms are inorganic compounds of Hg, which easily accumulates in organisms through water. Phytoremediationis an effective and affordable technological solution used to extract or remove inactive metals and metal pollutants from contaminated water. Azolla Microphylla bind metals like Zn, Pb, Cu, Cd, Au, Ni, Sr, Cr and Hg has also described the potential of Azolla Microphylla for the removal of Hg from wastewaters. The present review highlights the phytoaccumulation potential of macrophytes with emphasis on utilization of Azolla Microphylla as a promising candidate for phytoremediation. Azolla Microphylla might bio concentrate Hg from contaminated water. However, in natural or real conditions, which may be synergistic or antagonistic with respect to metal uptake in a plant system. High metals content in the biomass suggests the tremendous potential of Azolla microphylla to take up heavy metals, i.e., Hg and may be used as a bio accumulator to polish heavy metals in industrial effluent.

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PHYTOREMEDIATION OF MERCURY USING AQUATIC PLANT Azolla microphylla

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In light of the rapid changes in the knowledge landscape and in order to create 21st-century skills in students to cope with the demanding nature of the world, reforming the education system is crucial. Assessment, as an essential component of the educational system, also needs reformation. Peer assessment is an important means of assessing pupils' development of 21st-century skills by evaluating the work of their peers, students may develop a deeper grasp of the calibre of their work by making use of peer assessment, a student-centered assessment technique. Furthermore, it not only assists students in acquiring knowledge but also assists them in developing cognitive and social abilities. This paper sheds light on the significance of peer assessment and its application as a learning tool. In addition, it also throws light on the benefits and challenges of peer assessment.

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Peer Assessment, Peer Feedback, 21st Century Skills,

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This review paper explores the process of building a real-time dashboard for asset monitoring in Power BI, a powerful business intelligence platform that offers a wide range of features for data visualization, reporting, and analytics. The paper highlights the key features and functionalities of Power BI that are relevant for real-time asset monitoring, including data import, data visualization, and customizable dashboards. The paper also discusses best practices for building a real-time dashboard for asset monitoring in Power BI, including data automation, custom visualizations, and real-time data monitoring. The review paper includes case studies and examples of real-time asset monitoring dashboards in Power BI, as well as future directions and recommendations for building effective real-time dashboards in Power BI. By providing a comprehensive overview of the process of building a real-time dashboard for asset monitoring in Power BI, this review paper aims to offer valuable insights and guidance for power system operators and managers looking to leverage real-time data for improved asset management and performance.

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Real-Time Dashboard, Power Bi, asset monitoring, predictive analytics, data integration, Business Intelligence, Decision Support Systems.

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The paper presents a review of the intricate relationship between resentment and different areas of life. By synthesizing existing research, it examines how resentment often stems from perceived injustices and unfair treatment, manifesting as anger, frustration, and disappointment. The review explores how persistent resentment can lead to chronic stress and inflammation, increasing the risk of health issues such as heart disease, hypertension, and autoimmune disorders. It also considers the impact of resentment on mental health, including its connection to anxiety, depression, and sleep issues. Additionally, resentment can disrupt social relationships by causing strain and limiting support networks. By evaluating current studies, this review identifies patterns, discrepancies, and gaps in the existing research. It highlights opportunities for future investigation to address these gaps, offering potential strategies and interventions to improve our understanding of resentment's role in health and well-being. Ultimately, this paper aims to guide future research efforts and develop interventions to enhance health outcomes related to resentment.

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resentment, frustration, anger, forgiveness

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In the ever-evolving landscape of mobile technology, Android stands as a dominant force, powering billions of devices worldwide. This paper provides a comprehensive analysis of security issues and solutions in Android application development, drawing insights from a multitude of scholarly works and empirical studies. Drawing upon a different array of scholarly research and empirical studies, our analysis encompasses the evolution of Android platforms, the complexities of permission-based security models, and the challenges posed by malware proliferation and unauthorized access. We delve into various methodologies and frameworks proposed to mitigate security risks, ranging from automated security testing methods to innovative approaches for managing app permissions effectively. By synthesizing insights from different sources, we aim to provide a comprehensive understanding of the current state of Android security while offering valuable recommendations for future research directions and practical implementations

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Android security, mobile application development, security vulnerabilities, malware detection, permission-based security models, automated security testing.

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Background: The face of digital assets has been revolutionized with the advent of NFTs, and they offer simply amazing options to both investors and creators. The constant need for the stable and easy utilizing of the NFT marketplace platforms is permanently growing with the increasing enthusiasm about NFTs. This research paper is aimed to bridge the gap by creating an NFT marketplace with Motoko backend, and React frontend technologies on the Internet Computer network using the blockchain technology. Methodology: The research covers all processes in detail including, how to make an application of decentralized type for the purposes of creation of the NFTs and the purchase of them as well as their ownership transformation. Developers should get to know how to set up the project environment, build interfaces required to ensure convenience, include vital features, and eventually launch the program using a detailed method. In the context of coding the blockchain programme, programmers work on code integrity, testing procedures and problem solving in order to guarantee reliability and security of the market Result: The research covers all processes in detail including, how to make an application of decentralized type for the purposes of creation of the NFTs and the purchase of them as well as their ownership transformation. Developers should get to know how to set up the project environment, build interfaces required to ensure convenience, include vital features, and eventually launch the program using a detailed method. In the context of coding the blockchain programme, programmers work on code integrity, testing procedures and problem solving in order to guarantee reliability and security of the market. Conclusion: The study presented has a great importance for developers who are the ones responsible for the development of IC smart contracts for instance. During creation of a NFT market using React frontend and Motoko backend both robustness as scalability are maintained to adopt any dynamism in the digital asset market. The project collates and evaluates a development model so the developers can strengthen their skill, join the project with fresh ideas, and contribute to the development of blockchain technology. This article serves as a guide about how to craft advanced and user-friendly ICP NFT markets. ICP NFT market is crucial for NFT market because of its growth.

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 Keywords

Digital Assets, Decentralized application, Blockchain technology, NFT marketplace, Internet Computer network, Smart Contracts

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Comparitive study on the quality of work life of women in government and private sector

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NA

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ABSTRACT Plastic is used in various industries, including automotive, packaging, and medical. Plastic is used for its ease of manufacturing, handling, and dependability. Plastic goods manufacturers strive to produce high-quality items on a big scale and at a lower cost. Hydraulic machines provide a solution but are prohibitively expensive for small and medium-sized enterprises. This paper focuses on designing and manufacturing a pneumatic injection plastic molding machine. The manually operated machine is turned into a pneumatically operated machine through correct design procedures.

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Prototype, Injection Molding, Design, Plastics

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This study was focused on the evaluation of the ease of doing business and efficient government service delivery at Tarlac State University along with the reengineering of systems and procedures, the composition of the Citizen's Charter, implementation of the Zero-Contact Policy, Ease of Access to Office Services, and Report Card Survey. Based on the challenges encountered by the respondents with the implementing guidelines of RA 11032, this study also seeks to uncover if problems emerge in doing such practices. Finally, this study also proposes an action plan to address underlying challenges and their implications to the field of public administration. As a result, the university is in fact following the directive in the implementing policy, especially with regard to reengineering the government's systems and processes. This is being obtained and maintained by the university through its arm office the Quality Management Unit (QMU) under the University President Office. Also, it consistently follows the mandate of the national government in observing ease of doing business through zero-contact policy implementation. Further, it is complying with the citizen's charter, this because of the compliance of the institutions among the prescribed details in each office, and by providing a justifiable reason in returning the request to the clients in case of disapproval. Lastly, the Report Card Survey assessment is observed by the institution. This is to apply the check and balance in the government, by knowing the feedback of the clienteles on the services provided by the university. This is also in line with the Implementing Rules and Regulations of Republic Act No. 11032 also known as Ease of Doing Business and Efficient Government Service Delivery Act of 2018 assessment particularly in Tarlac State University.

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ARTA, citizen's charter, report card survey

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 Abstract

Cervical cancer is one of the common cancers among women and it causes significant mortality in many developing countries. Diagnosis of cervical lesions is done using pap smear test or visual inspection using acetic acid (staining). Digital colposcopy, an inexpensive methodology, provides painless and efficient screening results. Therefore, automating cervical cancer screening using colposcopy images will be highly useful in saving many lives. Nowadays, many automation techniques using computer vision and machine learning in cervical screening gained attention, paving the way for diagnosing cervical cancer. However, most of the methods rely entirely on the annotation of cervical spotting and segmentation. This paper aims to introduce the Faster Small-Object Detection Neural Networks-Generative adversarial network (FSOD-GAN) to address the cervical screening and diagnosis of cervical cancer and the type of cancer using digital colposcopy images. The proposed approach automatically detects the cervical spot using Faster Region-Based Convolutional Neural Network (FR-CNN) and performs the hierarchical multiclass classification of three types of cervical cancer lesions. Experimentation was done with colposcopy data collected from available open sources consisting of 1,993 patients with three cervical categories, and the proposed approach shows 99% accuracy in diagnosing the stages of cervical cancer.

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Cervical Cancer Diagnostics Healthcare System Using CNN

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In the modern era of digital communication and information exchange, ensuring the confidentiality and integrity of sensitive data has become paramount. Cryptography plays a pivotal role in safeguarding information through the use of encryption and decryption techniques. This paper provides a comprehensive overview of encryption and decryption method methods in cryptography.

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Cryptography, RSA, AES, Triple DES

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Attendance management systems have started to use portable biometric technology to improve their accuracy, efficiency, and security. This paper reviews the approaches and advancements in attendance management systems that use portable biometrics. It highlights the challenges faced by traditional attendance systems and stresses the need for more reliable solutions. It then explains various types of biometrics used in portable attendance systems, such as fingerprint, facial recognition, iris scanning, and voice recognition, along with their pros and cons. The paper also discusses how mobile devices, like smartphones and tablets, have been integrated into attendance systems, making attendance tracking more convenient and widespread. The review addresses security and privacy concerns associated with biometric data storage and transmission in mobile environments, and the regulations governing their implementation. Additionally, the paper examines recent developments in portable biometric technology, such as machine learning algorithms for better recognition accuracy and biometric integration methods for improved reliability. Finally, the review concludes with insights into future research directions and emerging trends in the field, including multimodal biometrics, wearable devices, and the integration of the Internet of Things (IoT) for comprehensive attendance management solutions. Overall, this study provides an in-depth overview of attendance management systems that use portable biometric technology, offering valuable insights to researchers, practitioners, and policymakers in the field.

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Attendance management systems, Portable biometric technology, Mobile devices integration, Security and privacy concerns, Emerging trends

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 Abstract

The objective of this research is to create an AI-based platform aimed at detecting symptoms of trauma from voice and text communications, while also offering direct access to medical professionals. The main aim is to intervene early in mental health issues, especially those related to trauma. By employing cutting-edge algorithms, the system can analyze both voice and text data, providing a thorough insight into the user's mental well-being through a combination of modalities. Through real-time monitoring, the platform ensures timely assistance, while stringent privacy protocols protect user information. The interface is designed to be user-friendly, facilitating smooth communication, and the direct connection to trauma specialists enables immediate support. Additionally, the system incorporates continuous learning mechanisms, allowing it to evolve and enhance its capabilities over time. This initiative addresses the pressing need for innovative approaches in mental health, striving to contribute to early intervention and improved assistance for individuals grappling with trauma.In summation, this project constitutes a significant stride in the realm of mental health intervention, proffering an innovative solution for early detection and support in trauma-related concerns. Through its amalgamation of cutting-edge technology, robust privacy safeguards, and direct access to healthcare professionals, the platform endeavors to address the pressing need for enhanced mental health support. By prioritizing user well-being and harnessing AI-driven insights, this platform endeavors to make substantive contributions to the field of mental health, ultimately striving to ameliorate outcomes for individuals grappling with trauma.

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 Keywords

Trauma, Natural Language Processing (NLP), Speech Processing, Mental Health, AI, Direct Doctor Connection, Privacy, Text Analysis, Voice Analysis, Real-time Support, Emergency Assistance, User Profiling, Sentiment Analysis, Deep Learning

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This paper explores the wide-ranging capabilities of ChatGPT, an advanced AI model, beyond its traditional role of code generation, focusing on its potential to enhance the software development workflow. ChatGPT serves as a versatile tool throughout various stages of software development, helping in ideation, debugging, explanation, and documentation. By leveraging its natural language understanding, developers can engage in interactive conversations to brainstorm ideas and refine concepts collaboratively. Moreover, ChatGPT's ability to analyse error messages and suggest troubleshooting steps streamlines the debugging process, leading to efficient issue resolution. Additionally, ChatGPT excels in providing comprehensive explanations and generating documentation for code segments and technical concepts, fostering knowledge sharing and improving code quality. Integrating ChatGPT into the software development workflow promises to revolutionize the way software is conceptualized, developed, and maintained, driving efficiency, innovation, and collaboration in the digital age

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ChatGPT, software development workflow, AI, testing, documentation, design, bias, security, education, collaboration

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Emergency medical services are critical for saving lives, but instances of ambulance misuse, driven by factors such as commissions, can hinder timely responses. This project introduces a Smart Ambulance Routing System designed to mitigate such issues and optimize emergency response efforts. Leveraging real-time hospital information, GPS technology, and intelligent algorithms, the system guides ambulance drivers to the nearest hospitals, ensuring efficient and patient-centered emergency care. Two-way communication facilitates information exchange, and a user-friendly interface supports manual intervention. Continuous learning algorithms and privacy measures ensure system adaptability and data security. The system aims to revolutionize emergency response through AI-driven optimization and dynamic resource allocation. Ongoing collaboration and monitoring are essential for its effectiveness. The patient's biomedical parameters, such as heart rate, respiration, and body temperature, will be collected by the LSAI48266X Artificial Intelligence board. It will then use an algorithm to process the data and determine which category the patient falls into, i.e., oxygen bed support, ventilator support, or ICU support. The board will do this by utilizing Internet of Things to check the hospital's networked medical system availability. The hospital is informed to the ambulance driver via the Telegram app. The Smart Ambulance Routing System makes use of effective communication protocols, a cloud-based platform for hospital data storage, and NodeMCU for real-time GPS tracking. Hospital distances are dynamically calculated by cloud functions, and the best routes are determined by an onboard algorithm. An alert message is triggered when there is a major delay in the ambulance arrival.

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Emergency Medical Services, Real-time hospital information, cloud based platform, AI driven Optimization

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Behaviour modification is a systematic approach to understanding and changing Behaviour through the application of principles derived from psychology, particularly Behaviourism. This paper explores the theoretical foundations, principles, techniques, and applications of Behaviour modification in various settings. Drawing on principles of operant conditioning, classical conditioning, social learning theory, and cognitive-Behavioural theory, Behaviour modification interventions aim to increase desired Behaviours and decrease undesired ones by manipulating environmental factors and consequences. The paper discusses the importance of functional Behavioural assessment (FBA) in identifying the underlying function of Behaviour and tailoring interventions accordingly. It also examines the role of reinforcement, punishment, shaping, prompting, modelling, and cognitive restructuring in Behaviour modification. Applications of Behaviour modification in clinical psychology, education, parenting, organizational management, and self-improvement programmes are explored, highlighting its effectiveness in addressing a wide range of Behavioural challenges and promoting positive Behaviour change. Finally, the paper discusses ethical considerations, limitations, and future directions in the field of behaviour modification.Behaviour modification is a systematic approach to understanding and changing Behaviour through the application of principles derived from psychology, particularly Behaviourism. It involves identifying target Behaviours, assessing their antecedents and consequences, and implementing interventions to increase desired Behaviours and decrease undesired ones. Key principles include operant conditioning, classical conditioning, social learning theory, and cognitive-behavioural theory. Techniques such as reinforcement, punishment, shaping, prompting, modelling, and cognitive restructuring are commonly used to modify behaviour. Behaviour modification is applied in various settings, including clinical psychology, education, parenting, organizational management, and self-improvement programmes, to address a wide range of behavioural challenges and promote positive behaviour change. Ethical considerations, limitations, and future directions in the field are also important aspects to consider when implementing behaviour modification interventions.

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Behaviour therapy, Applied Behaviour analysis, Operant conditioning, Target Behaviours, Antecedents, Consequences, Reinforcement, Punishment, Shaping, Modelling, Cognitive restructuring, Positive reinforcement, Negative reinforcement, Extinction, Behavioural interventions

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 Abstract

The Local Train commuters in Mumbai face a tremendous amount of crowd while travelling in rush hours of the day, which usually leads to many commuters standing for the entire duration of travel in a cramped space or sitting in awkward postures, for a long time that over a course of period inevitably leads to musculoskeletal pain in some form or another. Objective: To find the joints and areas involved most commonly in local train commuters using Nordic Musculoskeletal Questionnaire and to have a gender biased discrimination on the joints involved. Methods: A cross sectional survey was conducted on 384 local train commuters in Mumbai. Dadar and Thane railway stations were targeted for recruitment of participants. Convenience sampling was used for the same. Both male and female participants above the age of 18, who had been travelling for more than a year and had a single travel route of an hour or more were included in the study. Nordic Musculoskeletal Questionnaire was used to collect the data. Results: A total of 384 responses were collected from local train commuters, amongst which 60% were female and 40% were male participants. 86% commuters experienced pain while 14% did not. Neck was the most affected area (37%) while elbow was the least affected (2%). The gender biased study pointed towards females having more cases of pain in each involved joint. Conclusion: The present study indicates that 86% Mumbai local train commuters have experienced a degree of musculoskeletal pain from travelling.

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Musculoskeletal pain, Mumbai local train commuters

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Creative Commons Attribution 4.0 and The Open Definition

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Machine learning methods have transformed healthcare by enabling precise and prompt disease prediction. Predicting multiple diseases simultaneously can greatly enhance early detection and treatment,improving patient outcomes and lowering healthcare expenses. This system examines the use of machine learning algorithms in predicting multiple diseases, addressing their advantages, obstacles, and future prospects.It provides an overview of various machine learning models and data sources commonly employed for diseaseprediction, emphasizing the significance of feature selection, model assessment, and the fusion of multiple datatypes for improved disease prediction. Research findings underscore the promise of machine learning in multi-disease prediction and its potential to advance public health.

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Machine learning,Emphasizing

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Creative Commons Attribution 4.0 and The Open Definition