VOLUME 12, ISSUE 11, NOVEMBER 2023

Abstract: The utilization of machine learning has significant importance in the identification and prevention of distributed denial of service (DDoS) attacks. Through the examination of network traffic patterns, machine learning algorithms possess the capability to detect anomalous activities that serve as indicators of a Distributed Denial of Service (DDoS) assault in a timely manner. This paper presents a novel hybrid approach for the detection of distributed denial-of-service (DDoS) attacks in network logs, leveraging the strengths of both Random Forest (RF) for feature extraction and Recurrent Neural Network (RNN) for classification. The proposed framework harnesses the discriminative power of RF in identifying salient features from the raw network log data, which are subsequently utilized as input for the RNN classifier. The Random Forest algorithm was employed to extract a comprehensive set of discriminative features from the network log data, enabling the model to capture intricate patterns indicative of DDoS attacks. These features were then employed as input to the RNN classifier, facilitating the utilization of sequential dependencies and temporal patterns within the log data. The hybrid model achieved exceptional performance, with an accuracy of 99.99%. Furthermore, the true positive rate was recorded at an impressive 99.99%, demonstrating the model's proficiency in correctly identifying actual instances of DDoS attacks. The false positive rate was exceptionally low, at 0.0001%, underscoring the model's robustness in minimizing misclassifications. This study represents a significant advancement in the field of DDoS attack detection, offering a powerful and accurate solution that effectively combines the strengths of Random Forest for feature extraction and RNN for classification. The hybrid model's outstanding performance metrics affirm its potential for deployment in real-world network security environments, providing a robust defense against DDoS attacks.

Keywords: Distributed Denial of service, Recurrent Neural Network, Random Forest Classifier, Network Logs. Works Cited: P.S. Ezekiel, O.E. Taylor " A Hybrid Model for The Detection Of APA-DDoS Attacks Using Random Forest with Recurrent Neural Network ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 1-11, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121101

Abstract: A thorough examination of the most recent cutting-edge technologies utilized to support live environments is provided in this survey report. The main technologies covered are Text-to-Speech (TTS) systems for auditory feedback; Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks for object detection and live scene description; real-time processing techniques for continuous feedback; and Optical Character Recognition (OCR) for live text recognition. The significance of user-friendly interfaces in improving user experience and the relevance of different datasets in training these algorithms are also covered in the study. The purpose of this survey is to present a thorough summary of the body of literature, address the benefits and drawbacks of the approaches used now, and make recommendations for possible future research avenues. This work is an important tool for scholars who want to explore and improve existing technologies in live environment assistance systems.

Keywords: Object Detection, Optical Character Recognition, Convolutional Neural Network, Text-to-Speech, Computer Vision, Neural Networks. Works Cited: Prof. M. P. Shinde, Shreyash Dhurupe, Viraj Karanjavane, Sanna Shaikh, Abhishek Suryawanshi " A Comprehensive Survey on the Current State of the Art Technologies used for Live Environment Assistance ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 23-27, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121103

Abstract: The utilization of Information and Communications Technology (ICT) in the educational sector cannot be overemphasized.  Educational system across the globe is under immense pressure to use ICT to improve the system. An Automated Complaint and Report Management System is one of the tools to achieve this goal. Over the years, the method by which complaints and reports are managed in some Nigeria Universities has not been digitalized and automated. This work presents a web-based system for complaint and report management which was developed using PHP, an open source scripting language. The system analysis and design was carried out using the Object Oriented Analysis and Design Methodology (OOADM). The database was created using MySQL and the interface designed employed CSS, JavaScript and HTML. A Supervised Machine Learning algorithm was utilized and basically used for the classification of the complaints. The result obtained shows that the developed system proved to be a better, easier, faster, reliable and more secured method for improving complaint and report handling for fair and prompt response in order to ensure effectiveness and efficiency in tertiary institutions. This is highly recommended to the management of Rhema University, Nigeria as it works towards being among the best 300 universities in the whole world. Keywords: Complaint, Report, ICT, Lodge, Student, Educational System Works Cited: P. C. Nwosu, M. E. Benson-Emenike, N. J. Ifeanyi-Reuben & E. G. Chukwu " AUTOMATED COMPLAINT AND REPORT MANAGEMENT SYSTEM FOR TERTIARY INSTITUTIONS ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 12-22, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121102

Abstract: Measurement of tubewell discharge plays a crucial role in sustainable water resource management. It enables informed decision-making, helps prevent over-extraction, and ensures the long-term availability of groundwater for various essential purposes. Developing applications for monitoring tubewell discharge can contribute to effective and efficient water resource management. Presently, Co-ordinate method is the most common method used to measure tubewell discharge but this method needs some calculations which are beyond the scope of a farmer or non technical person. therefore an attempt has been made to develop an application for the most common platform of android to help farmers and laymen to easily calculate discharge of their tubewell by simply putting the values of co-ordinates of the water jet. The application was developed on freely available MIT app developer web platform.

Keywords: Tube well discharge, water measurement, co-ordinate method, android application Works Cited: Ram Naresh, Mukesh Kumar, Amandeep Singh, Sanjay Kumar " Android based mobile application for estimation of tubewell discharge ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 28-32, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121104

Abstract: With the exponentially increasing demand for wireless communications, the capacity of current cellular systems will soon become incapable of handling the growing traffic. Since radio frequencies diminish natural resources, a fundamental barrier to further capacity increase exists. The solution can be found in adaptive antenna systems. Adaptive antenna systems enable network operators to increase the wireless network capacity, where such networks are expected to experience an enormous increase in traffic. This is due to increased users and the high data rate service and applications. In addition, adaptive antenna systems offer the potential of increased spectrum efficiency, extended range of coverage, and a higher rate of frequency reuse.  This paper aims to overview the technology, the fundamental system model, and the used algorithms.

Keywords: Adaptive antenna, smart antenna, steering vector. Works Cited: Cornelius A. D. Pahalson " ENHANCING CELLULAR NETWORK CAPACITY WITH ADAPTIVE ANTENNAS ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 33-41, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121105

Abstract: Neuroticism is a type of negative personality trait that leads to emotional instability and increasingly experiencing negative emotions.  The primary aim of the research is to compare the   Neuroticism and lie scale between Male and Female Handball players   between male and female state level  Handball players. Total 50 male  and 50 female handball players  were selected as a subject for the present study.  Their age ranged from 21 to 28 years. Data was collected individually through a Eysenck personality inventory from male handball and 50 female handball Players. To analyze the data mean scores, standard deviation and t-ratio were used to comprise Neuroticism and lie scale between Male and Female Handball players. The result reveals that the significance difference was found out in (t=P<.05) neuroticism of Male and Female Handball players, However, No significance difference was found out in (t=1.20) Lie Scale of Male and Female Handball players  

Keywords: Handball, neuroticism, lie-scale Male, Female Works Cited: Dr. Satyajeet Pagare " AN EMPIRICAL STUDY OF NEUROTICISM AND LIE SCALE BETWEEN MALE AND FEMALE HANDBALL PLAYERS ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 42-46, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121106

Abstract: "PlaceInsta: An E-Learning Platform Using Web Development Technology" addresses the critical gap between academic learning and professional readiness for engineering students. In the context of evolving industry demands, the platform provides a multifaceted approach to placement preparation, covering technical skills, soft skills, and company-specific requirements. "PlaceInsta" offers a responsive and interactive learning experience. This research explores the platform's design, implementation, and applications, emphasizing its user-centric approach and commitment to preparing students holistically for successful careers in the tech industry.

Keywords: Placement Preparation, careers, technical skill, tech industry, etc. Works Cited: Harsh Mohod, Harish Uikey, Rohit Gorla, Priti Ghormare, Abhishek Kundu " PlaceInsta: An Placement Preparation Platform ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 47-49, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121107

Abstract: Malware threats targeting PDF and Word documents have become increasingly prevalent, posing significant risks to information security. The review covers signature-based detection, behavior-based analysis, machine-learning approaches, and hybrid models. By examining the strengths and limitations of each technique, this abstract highlights the current state of research and identifies potential avenues for future improvements in malware detection for PDF and Word documents. The current survey serves as a valuable resource for researchers, practitioners, and decision-makers seeking insights into combating malware threats in these widely used file formats.

Keywords: PDF files, Office Documents, malware detection, static analysis, dynamic analysis Works Cited: Mrs.Priyanka Pati, Mrs.Madhuri Gedam " Detection of Malware in PDF and Office Documents using Ensemble learning ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 50-59, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121108

Abstract: The widespread use of mobile devices, especially in Indonesia where 67% of the population owns a mobile device, underscores the rapid advancement of mobile technology. Google's Android, with its open-source nature and extensive application support, has become the leading choice. In the context of increasing reliance on public services, including those provided by notaries and land deed officials, data security is of paramount importance. The development of a mobile notary application addresses this need, offering ease of interaction and reliable data security. This research implements the AES 256 encryption and decryption method, ensuring secure data exchange through the app. The AES algorithm, recognized as a Federal Information Processing Standard, secures data stored in an encrypted MySQL database. This Android-based notary app successfully uses AES-256 in document encryption, making files unreadable to unauthorized parties. The app also aims to build trust between users and notaries while preventing potential misuse of documents. Further development is expected to increase interaction between users and notaries, improving efficiency and accessibility of public services.

Keywords: Cryptography, Mobile Applications, Data Security, Notary. Works Cited: Tegar Rangga Nur Ridawan, RR Hajar Puji Sejati "Data Security Implementation with Advanced Encryption Standard 256 in Notary Mobile Applications", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 60-68, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121109

Abstract: Cloud Computing has revolutionized the way organizations manage their IT infrastructure and rеsourcеs. Apart from its well-known advantages in tеrms of cost efficiency and flеxibility, cloud computing offers inhеrеnt еco-friеndly fеaturеs that contributes to a morе sustainablе IT landscapе. This article dеlvеs into thе еco-friеndly aspеcts of cloud computing, focusing on rеsourcе sharing, scalability, and еnеrgy-еfficiеnt data cеntеr practicеs. It еxplorеs how thеsе fеaturеs can mitigatе thе еnvironmеntal impact of traditional computing modеls and promotе sustainability in thе digital agе.

Keywords: Cloud Computing, Eco-friendly, Data Center, Sustainable, Scalability Works Cited: Sunil Sukumaran Nair, RR Hajar Puji Sejati "Thе Grееn Rеvolution of Cloud Computing: Harnessing Resource Sharing, Scalability, and Enеrgy-Efficiеnt Data Cеntеr Practicеs", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 69-76, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121110

Abstract: This study explores the application of artificial intelligence (AI) in the context of Human Resource Management (HRM), specifically within Talent Acquisition Procedures (TAP). In contrast to prior research, it contributes a significant theoretical model to elucidate the effective implementation of AI in TAP. The study focuses on the underexplored impact of the recruitment phase, incorporating the critical perspective of recruitment professionals. It extends technology adoption theory within information systems by integrating insights from HRM literature. Qualitative findings from this study reveal the suitability of AI in specific TAP phases, such as sourcing, pre-screening/pre-selection, and candidate engagement. Notably, there is a discernible reluctance to adopt AI in the TAP pre-planning and interview stages. The study provides current insights to inform HRM practitioners and organizations seeking to integrate AI into their Talent Acquisition Procedures.

Keywords: Artificial Intelligence, Deep Learning, Employment, Machine Learning, Talent Acquisition Procedures, AI/ML. Works Cited: Divit Gupta, Anushree Srivastava "Investigating the Use of Artificial Intelligence in Talent Acquisition Procedures", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 77-87, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121111

Abstract: The lack of enough labeled data is a great issue when designing a real-life scheme. Data labeling is time-consuming as well as costly. Semi-supervised learning (SSL) is a way to solve the issues of data labeling. SSL uses a tiny quantity of labeled data to find labels of massive quantities of unlabeled data. This paper presents a quantum-classical SSL mechanism named "Iterative Labels Finding (ILF)" by combining the Quantum Support Vector Machine algorithm (QSVM) and Ising Models Based Binary Clustering algorithm. The proposed method performs a matching and iteration process to discover the labels of unlabeled data. ILF is designed for binary classification purposes. We have illustrated the experimental result of ILF with a real-time dataset and with a practical example. From experimental results, we have found ILF as a highly efficient approach for quantum SSL.

Keywords: Quantum Computing, QSVM, Semi-Supervised Learning, QML Works Cited: Reshma Ahmed Swarna, Mohammed Ibrahim Hussain, Md. Sadiq Iqbal, Mohammad Mamun, Safiul Haque Chowdhury " ILF: A Quantum Semi-Supervised Learning Approach for Binary Classification ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 88-96, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121112

Abstract: Micro, Small, and Medium Enterprises (MSMEs) are business units in the economic sector owned by individuals or community-based business entities that make significant contributions to Indonesia's economy. MSMEs are businesses directly embedded within communities, often found in residential areas, and play an essential role in daily life. Financial management poses challenges for MSMEs in running their business operations. This research addresses the challenges faced by entrepreneurs in the MSME sector by employing the Apriori method to support the financial management application system. The method involves identifying the highest frequency of interconnected data needed for business operations. The system is developed as an Android-based application using Android Studio software and a database. This application is designed to draw conclusions from financial data, aiding decision-making in financial management for business units.

Keywords: MSMEs, Management Financial, Apriori, Android. Works Cited: Ade Khoirul Nur Hidayat, Joko Sutopo "Implementation Apriori Method in Financial Management for Micro, Small, And Medium Enterprises", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 97-105, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121113

Keywords: middleware, privacy, security, IoT Works Cited: Yashwant Dongre, Amol Mohadikar " Security and Privacy in Middleware for IoT ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 106-111, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121114

Keywords: Virtual Reality, Unity3D, Geographic Information Systems (GIS), ActiveX Component. Works Cited: Dr. S. Sarumathi, Gokul M, Gokulavelan M, Shimar Roshan R S " A Review on Virtual Environment using Unity Software ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 112-117, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121115

Abstract: The realm of microstrip patch antennas has undergone significant advancements in recent years. In comparison to traditional antennas, microstrip patch antennas offer a myriad of advantages and exhibit promising prospects. These antennas boast characteristics such as reduced weight, compact dimensions, cost-effectiveness, minimal profile, ease of manufacturing, and enhanced conformity. Furthermore, their versatility extends to providing dual and circular polarizations, accommodating dual-frequency operations, displaying frequency agility, possessing broad bandwidth capabilities, enabling feedline flexibility, and facilitating beam scanning with omnidirectional patterning. This paper delves into an extensive exploration of microstrip antennas, encompassing various types, feeding techniques, and applications. The discussion encompasses the advantages and disadvantages of microstrip patch antennas in contrast to conventional microwave antennas. By examining these attributes, the paper aims to elucidate the considerable potential and diverse functionalities offered by microstrip patch antennas across various applications in the field of microwave technology.  Key Words: Microstrip Antenna (MSA), Microstrip patch antenna (MPA), Applications Works Cited: Swati Bhattacharjee, Ammar Saquib, Sourav Kumar, Rishav Gorai, Trisha Kumari "A Survey on Micro strip Patch Antenna and its Applications", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 118-123, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121116

Abstract: This survey paper provides a thorough examination of the rapidly evolving field of prompt engineering, a crucial aspect of natural language processing and artificial intelligence. Prompt engineering involves crafting effective instructions or queries to elicit desired responses from language models. The paper begins by elucidating the foundational concepts of prompt engineering, exploring its historical development, and presenting key methodologies employed in generating prompts for various language models. By synthesizing existing knowledge and highlighting emerging trends, this paper aims to provide researchers, practitioners, and enthusiasts with a comprehensive understanding of the current state and future directions of prompt engineering in natural language processing. Work Cited: Sumaiya. M. S, Yaseen Dada Shaik, Sonia Maria Dsouza "Advancements in Prompt Engineering: A Comprehensive Survey", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 161-167, 2023, Crossref https://doi.org/10.17148/IJARCCE.2023.121117

Abstract: This project examines a tree-based machine learning approach to predict customer behavior outcomes in e-commerce, using a large dataset. The project compares different classification methods to solve three Customer Relationships Management problems: predicting customer satisfaction, churn modeling, and the next product to buy modeling. The analysis is fully automated, making it easy for small e-retailers to implement. The study employs decision tree, random forest, and gradient boosting techniques.

Keywords: machine learning, churn, decision tree, random forest, gradient boosting. Çite: Hind Khalid Alghamdi, Salma Mahjoub Omar, Hanaa Namankani, "Predicting the Customer Behaviour Utilizing Tree Based Machine Learning Algorithms", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 125-130, 2023, Crossref https://doi.org/10.17148/IJARCCE.2023.121118.

Abstract: The main theme of this project is to Enhance and Color Correction for underwater images. This project becomes challenging due to attenuation and scattering of light. In this process, the novel algorithm of deep learning algorithms along with gamma correction. In the procedure of enhancing the texture and structural preservation is more important. In this work, the image enhancement is obtained by using the convolution neural networks. This process involves two stages mainly the training and testing stage. During training process, the dataset is collected, and their up sampled and resized images are stored in a mat file. Then CNN layers are created. Finally, the train the network using the data stored in mat files and CNN layers. After the training process, the test image is given as input to network designed earlier. Then finally the high-resolution image is obtained. This method reduces the loss of textural and structural information when compared to state of art methods.

Keywords: CNN, Deep Learning, Underwater Images. Cite: Varun N, Mrs Shaila V Hegde,"Enhancement For Underwater Images Using Hybrid Deep Learning", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 131-141, 2023, Crossref https://doi.org/10.17148/IJARCCE.2023.121119.

Abstract: In order to categorize people's personalities, this study applies the machine learning approach known as logistic regression. Moreover, machines that use Natural Language Processing (NLP) can comprehend and interact with human language. Several earlier research projects have tried to automatically determine an individual's personality type. Sorting people according to their personality types is one of the most significant uses of machine learning algorithms. There are a lot of advantages to grouping people into categories. Knowing one's personality can be quite beneficial in the modern world with abundant opportunities. Based on these forecasts, anyone can select a job or other interests. Many firms in the modern world utilize these personality assessments to select candidates since it increases productivity because the employee is doing what he or she is best at.

Keywords: Multinomial Logistic Regression, Python, Web Technology, Personality, NLP, IBM Watson (video analysis) Cite: Prof. Amol Chincholkar, Dipti Bhosale, Shivanjali Adsul, Anjali Bodkhe, Rutuja Kadam,"A Comprehensive Survey on Personality Prediction Using Machine Learning Techniques", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 142-147, 2023, Crossref https://doi.org/10.17148/IJARCCE.2023.121120.

Keywords: Autonomous Vehicle, Raspberry Pi, Arduino UNO. Cite: Prof. Nilam Honmane, Aniket Vadar, Zahir Mulla, Sarthak Samgir, Aditya Rakate,"Obstacle Detection And Avoidance In Autonomous Cars", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 148-155, 2023, Crossref https://doi.org/10.17148/IJARCCE.2023.121121.

Abstract: A news aggregator app revolves around the concept to collect, organize and present it to the users. These kind  of app collect news from various source. Keeping the users updated about the news is the main aim of this app. VeriNews also allows the users to verify if the news is real or fake. If the news is real it allows the users to post it in the app and let other users also know about the news.

Keywords: real news, fake news, post, verification, news aggregator. Cite: Mansi Lanjewar, Isha Derkar, Mayura Wadaskar, Pratiksha Kalamkar, Prof.Virendra Yadav,"VeriNews-A news aggregator app to verify and share news", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 156-160, 2023, Crossref https://doi.org/10.17148/IJARCCE.2023.121122.

Abstract: An ethical hacker is the network specialist and computer, who dives into security systems seeking responsibility that could be exploited by a malicious hacker. The purpose of ethical hacking can be to deal with the breaches of cyber security with the knowledge of laws and also can be to build an effective cyber security wall against your organization. An ethical hacker can help the people who are suffered by the malicious hacking. Ethical hacker can analyse the vulnerabilities before the attacker may strike. It can help people to recovery the lost information and to perform penetration testing to strengthen computer and the network security. This paper describes about ethical hacking and aspects of ethical hacking. Keywords: Hacking, Hacker, Ethical Hacking, Security, Ethics Cite: Tamanna Gajanan Shenoy, "ETHICAL HACKING: A SOLUTION FOR THE MOST DANGEROUS THREAT", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 161-167, 2023, Crossref https://doi.org/10.17148/IJARCCE.2023.121124

Abstract: Data control language commands are GRANT and REVOKE which deal with the rights, permissions, and other controls of the database system.

Keywords: DCL data control language. Cite: Swati Bhushan Patil, Rahul Uttam Patil, Vijaya Chavan, Mithun Mhatre,"Data Control Language Commands", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 174-177, 2023, Crossref https://doi.org/10.17148/IJARCCE.2023.121125.

Abstract: The market for Internet of Things (IoT), wearable and flexible electronics, and sustainable development is projected to exceed $500 billion during the next five years. This encompasses a range of technologies such as sensors, micro electro mechanical systems (MEMS), medical instruments, energy harvesting and scavenging devices that enable the IoT, as well as energy-efficient systems. This is owing to our capacity to create materials differing from metals, insulators, metal-oxide, semiconductors and organic polymer materials or hybrid mixed phase materials in diverse stages including amorphous, nanoclusters or various phases of crystallization. Therefore, this allows for the creation and manipulation of materials with diverse characteristics and capabilities on various surfaces, such as flat, flexible, and conformal ones. The primary aim of this research was determined based on a comprehensive examination of existing knowledge, the increasing difficulties, and the practical constraints within the academic setting.

Keywords: IoT, Pressure Sensor, Wearable Electronics, Smart garments. Cite: Dr.M.S.Nidhya, Dr.JayanthilaDevi, "IoT Enabled Respiratory Sensing Device for Pressure Sensor", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, pp. 178-183, 2023, Crossref https://doi.org/10.17148/IJARCCE.2023.121126.

Abstract: This paper explores the integration of Workday AI into the financial accounting close process, highlighting its potential to revolutionize financial management within organizations. By employing machine learning, natural language processing, and predictive analytics, Workday AI automates manual tasks, enhances the accuracy of financial data, and delivers real-time insights. The research emphasizes the importance of transitioning to a zero-day close process, which allows for the immediate closing of financial books at the end of a reporting period, providing organizations with timely financial details essential for rapid decision-making in today's fast-paced business environment. This study assesses the benefits, including improved financial visibility, cost savings, compliance, and accuracy, alongside potential challenges such as data security and integration complexity. Future trends in AI and finance, including the use of blockchain and advanced data analytics, are discussed, underscoring the transformative impact of Workday AI on financial operations, making them more agile, efficient, and strategically focused.

Keywords: Workday AI, Financial Accounting Close Process, Zero-Day Close, Machine Learning, Natural Language Processing, Predictive Analytics, Real-time Financial Reporting, Automation in Finance, Strategic Decision Making, Financial Management Innovation Cite: Jayesh Jhurani, "Achieving Zero Day Close with Workday Artificial Intelligence (AI): Efficiency and Strategic Decision Making", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 11, 2023, Crossref https://doi.org/10.17148/IJARCCE.2024.121127.

Abstract: The Internet of Things (IoT) is a transformative technology with far-reaching impacts across various sectors, including communication, industry, healthcare, and the global economy. By automating tasks, enhancing productivity, and reducing stress, IoT can significantly improve quality of life in diverse settings—from smart cities to educational institutions. However, the widespread adoption of IoT has also introduced new cybersecurity risks. Emerging threats and vulnerabilities have rendered many traditional security approaches insufficient for protecting intelligent IoT systems. To ensure robust protection, future IoT systems must integrate Artificial Intelligence (AI) - especially Machine Learning (ML) and Deep Learning (DL) - to enable adaptive, real-time security solutions. This paper explores the role of AI in strengthening IoT security, focusing on how ML and DL techniques can extract meaningful insights from raw, unstructured data to detect and mitigate cyberattacks. We propose an AI-driven approach for defending IoT networks against a wide range of evolving threats. Additionally, the study highlights key research challenges and outlines future directions for the development of intelligent, self-sustaining IoT security frameworks. This article serves as a valuable technical reference for researchers, professionals, and anyone interested in IoT and cybersecurity.

Keywords: Internet of Things, Cybersecurity, Machine Learning, Deep Learning, Anomaly Detection, Healthcare