International Research Journal of Computer Science is an online Double-Blind Peer Review Journal, basically the aim of this journal to promote the new Innovative ideas in all fields of Computer Science & Engineering and Technology. Basically, this Journal will help to promote all Innovations in Engineering and Technology on one platform so that if anybody wants to integrate their ideas with other field of technology, they can implement it with the help of this Journal. The scope of the IRJCS is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of engineering, science and technology. Original theoretical work and application-based studies, which contributes to a better understanding of engineering, science and technological challenges, are encouraged. Supervisors: Dr.Arul Lawrence Selvakumar
Competent people are a valuable asset for strong businesses. The issue of retaining competent sta... more Competent people are a valuable asset for strong businesses. The issue of retaining competent staff with expertise poses a challenge to business owners. Employee attrition may be costly for businesses since it takes a lot to compensate for their experience attrition utilizing machine learning techniques. processed using standard scalar with Label Encoding method. The dataset features are selected by using modified genetic algorithm Boosting and Extr experimental results are compared with ML algorithms with classification metrics (Accuracy, Precision, recall and f measure).
Currently, video games have become a rapidly growing industry in our globe. However, they are mos... more Currently, video games have become a rapidly growing industry in our globe. However, they are mostly seen as having a detrimental influence on society. This research aims to investigate and analyse the beneficial effects of the gaming business and its potential in addressing various global challenges. The modern environment has seen a significant upsurge in the video gaming business, establishing it as a swiftly expanding sector. This study aims to thoroughly investigate and explore the positive aspects of the gaming business, despite the common belief that video games mostly have negative impacts on society. By doing so, it aims to clarify the ways in which gaming positively helps to addressing various global concerns. These techniques include the areas of Education and Learning, Social Impact and Empathy, and Crowd-Sourcing and Problem Solving. 1. Education & Learning: Video games have the potential to revolutionize academics by providing immersive learning and interactive experiences. It may also aid in envisioning certain levels, which can facilitate a deeper comprehension. 2. Gaming may facilitate the comprehension of many cultures and enhance social awareness, hence contributing to social impact and empathy. Multiplayer connectedness facilitates emotional and mental connection, allowing players to build emotional bonds with game characters inside the gaming environment. 3. Crowd-sourcing and problem solving: Video games facilitate comprehension of global concerns via virtual reality, devoid of any real-world consequences. It enables the connection with a vast number of actors and addressing significant global challenges.
The nexus between artificial intelligence (AI) and human creativity offers a fascinating paradigm... more The nexus between artificial intelligence (AI) and human creativity offers a fascinating paradigm shift in the dynamic field of music composition. To understand the effects on musical composition, production, and performance, this research study, "Harmony in Synthesis: Exploring Human-AI Collaboration in Music," explores the dynamic interplay between human artists and AI systems. The opening establishes the scene by describing the development of AI in the music business and emphasizing the revolutionary possibilities of teamwork. This study addresses current knowledge through a thorough literature assessment, pointing out gaps that our research aims to remedy and adding to the conversation on AI's involvement in creative processes.
Conservation strategies are redefined by smart conservation, which combines wildlife monitoring a... more Conservation strategies are redefined by smart conservation, which combines wildlife monitoring and artificial intelligence (AI). Artificial intelligence (AI) technologies, such as computer vision and machine learning, automate the identification of species through image and audio analysis, making habitat health assessment and population monitoring more effective. By identifying changes in land cover and habitat decline, AI in conjunction with satellite photography enables ongoing habitat monitoring. AI-driven analytics facilitates the integration of various data sources and offers insightful information for well-informed decision-making. By utilizing both historical and current data, predictive modeling helps to guide proactive conservation measures by predicting how changes in the environment will affect animal populations. AI-enabled real-time alerting and monitoring systems improve the effectiveness of actions against illicit activities like poaching. AI-powered solutions facilitate community interaction by encouraging shared responsibility and increasing awareness. Efficient resource allocation is ensured by resource optimization, which is powered by AI analysis of species distribution and habitat circumstances. This all-encompassing strategy highlights the revolutionary potential of AI in protecting biodiversity, resolving environmental issues, and promoting the long-term coexistence of ecosystems and human activity.
Forest fires present a significant threat to ecosystems, endangering both human and animal life w... more Forest fires present a significant threat to ecosystems, endangering both human and animal life while causing irreversible environmental damage. To address this pressing issue in this research paper introduces an innovative & Affordable forest fire detection system that utilises the HSV algorithm and various computer vision libraries with the use of AI. Our advance system aims to detect & respond to forest fires in real-time, mitigating potential harm to flora and fauna. Our proposed System employs deploy camera sensors distributed at the Sensitive Parts of the forest, continually monitoring the environment. The HSV algorithm enhances the system's capability to accurately identify fire-related hues, ensuring reliable fire detection. Upon detecting a fire, an automatic alarm is triggered, initiating a series of measures to protect the ecosystem proactively. In response to a detected fire, the system automatically reroutes animal pathways to minimize their exposure to danger. Concurrently, the system sends immediate notifications to the local fire department and forest authorities via direct email, providing vital information on the fire's location and severity. This rapid communication facilitates timely intervention and improves the chances of successful firefighting efforts. We can put our system at Jim Corbett National Park & at different Sensitive forest Regions. Furthermore, the system features live monitoring capabilities, enabling authorities to observe the fire's real-time progression. This live feed supports informed decision making and facilitates the swift deployment of resources to contain and extinguish the fire. Through the integration of advanced computer vision technology, our system aims to redefine forest fire detection & response mechanisms, ultimately safeguarding the delicate balance of flora and fauna in ecosystems.
Blockchain technology, originating with Nakamoto's seminal whitepaper in 2008, has evolved into a... more Blockchain technology, originating with Nakamoto's seminal whitepaper in 2008, has evolved into a transformative force, promising decentralized, transparent, and secure digital transactions. H impact of blockchain is accompanied by inherent scalability challenges that impede its widespread adoption and efficiency. This study conducts a comparative analysis of scalability challenges within prominent blockchain networks Ethereum, and Binance Smart Chain. Rooted in a holistic understanding of blockchain evolution, the analysis focuses on transaction throughput, latency, consensus mechanisms, network congestion, and resource utilization. mechanisms, serving a the implications of diverse mechanisms Proof to unravel their impact on transacti confirmation times and overall system efficiency. Balancing this congestion requires a nuanced understanding of network dynamics, block sizes, and transaction prioritizat memory, becomes a focal point for sustainable growth. The study scrutinizes the efficiency of resource allocation and its implications for scalability, acknowledging the delicate balan considerations. By juxtaposing these blockchain networks, the comparative analysis aims to discern patterns, evaluate the effectiveness of consensus mechanisms, and provide actionable insights to address scalab considerations underpin the study, ensuring responsible data usage, user privacy, and adherence to ethical standards in blockchain research. This exploration into scalability challenges within blockchain networks contributes to th discourse on decentralized technologies. The findings are poised to inform future developments, providing a roadmap for enhancing scalability while maintaining the core tenets of decentralization, security, and sustainability.
Quantum computing represents a revolution in the ability to process information, and quantum hard... more Quantum computing represents a revolution in the ability to process information, and quantum hardware technology underpins its implementation. This work examines the current landscape of quantum hardware development, focusing specifically on three main technologies: superconducting qubits, trapped ions, and topological qubits. This study provides an in-depth analysis of the current state of each technology, taking into account its strengths, challenges and opportunities. Research is aimed at identifying current limitations and inefficiencies in this quantum hardware. Additionally, this study aims to present new developments and new methods to solve the identified problems. By combining theoretical knowledge and empirical tests, this research aims to handle to the ongoing debate on the development of quantum hardware that pushes the limits of quantum computing capabilities. The results of this work have important implications for the broader quantum computing community and provide insight into the complexity of superconducting qubits, trapped ions and topological qubits. The improvements and new techniques presented lead to the continued development of quantum hardware and help move the field closer to the realization of practical, scalable quantum computers.
In the ever-evolving landscape of digital infrastructure, the adoption of cloud computing has ush... more In the ever-evolving landscape of digital infrastructure, the adoption of cloud computing has ushered in unparalleled opportunities for innovation but has also introduced complex challenges in securing sensitive data. This research, titled "Beyond the Firewall: Understanding and Mitigating Cloud Security Challenges," embarks on a comprehensive exploration of the multifaceted dimensions surrounding cloud security. The study delves into the intricacies of cloud security, transcending traditional boundaries set by firewalls. From elucidating the dynamics of shared responsibility models to dissecting the nuances of identity and access management, the research unravels the complexities inherent in safeguarding data within the expansive digital cosmos. It addresses elusive threats like data breaches and underscores the critical importance of adaptive strategies to navigate the ever-changing threat landscape. This research goes beyond theoretical discourse, offering actionable insights for organizations seeking to fortify their cyber defenses. It emphasizes the need for a paradigm shift in understanding security challenges in the cloud era and advocates for a proactive approach to mitigate potential risks. By illuminating the path "Beyond the Firewall," this study aims to empower stakeholders with practical knowledge, enabling them to establish robust security frameworks that resonate with the dynamic nature of modern digital ecosystems. Join us on this expedition into the heart of cloud security challenges, as we decipher the complexities and chart a course towards a more resilient and secure digital future.
In education, the importance of gathering and understanding student feedback cannot be over state... more In education, the importance of gathering and understanding student feedback cannot be over stated. Traditional methods of gathering feedback through surveys and assessments often suffer from limitations such as low response rates and subjectivity. This paper proposes a new approach to improve the feedback collection process by implementing a Student Feedback Mining System using sentiment analysis. The goal of this system is to automatically analyze and extract sentiment from student feedback and provide educators and institutions with valuable insights into students' overall satisfaction and feelings toward various aspects of their academic experience. The system uses natural language processing (NLP) techniques to process unstructured text data, identify sentiments, and categorize feedback into positive, negative, or neutral feelings. Collecting student feedback through various channels such as online surveys, discussion forums and other feedback mechanisms. Cleaning and preprocessing the collected text data to remove noise, irrelevant information and standardize the format for analysis. Using state of the art NLP algorithms and sentiment analysis techniques to determine the emotional tone of feedback. This includes classifying sentiment as positive, negative, or neutral. Grouping feedback based on specific criteria such as course content, teaching methods, facilities and overall learning experience to provide a comprehensive understanding of the various aspects affecting student satisfaction. Presenting analyzed data through intuitive visualizations and reports, making it easy for educators and administrators to interpret and respond to feedback. Creating feedback that enables continuous improvement by providing actionable insights for educators to improve their teaching methods, curriculum and overall learning environment. The proposed system aims to overcome the limitations of traditional feedback collection methods by automating the analysis process, providing real-time insights and supporting a data-driven approach to improving education. Using sentiment analysis, educators and institutions can proactively solve problems, improve the quality of education, and create a more positive and engaging learning environment.
The main indicator that measures the economic development and power of the country affect the eco... more The main indicator that measures the economic development and power of the country affect the economy. difficult aspects of financial forecasting. Predicting stock prices accurately can make investors profitable. to the complex of the data in the primary objective of this article is to offer insights into forecasting market prices, aiding investors in making well decisions. The methodologies t processing, and sentiment analysis qualitative and quantitative data.
The proposed research paper describes an object System of recognition based on human perception, ... more The proposed research paper describes an object System of recognition based on human perception, which is achieved by feature extraction (components) and pattern analysis. Both strategies are applied to each subpart. Feature extraction is done using shaping and pattern analysis is achieved by creating statistical bins for each pattern of vehicle subparts. Each bin contains general and specific measures, and each measure has a certain weight that contributes to the analysis of each bin to decide on similarity or dissimilarity. Object recognition is an important task in computer vision, with applications in robotics, driverless cars, medical image analysis, and many other applications. This article explores the concept of product analysis using benchmarks, highlighting key concepts, methods and recent developments.
To ensure the accuracy and efficiency of intruder identification, the proposed method is combined... more To ensure the accuracy and efficiency of intruder identification, the proposed method is combined with Haar classifier technology for face detection. When someone comes to the door, the Pi camera captures the image and starts the face detection process. In this research, we implement a facial recognition component to capture human images, comparing them with stored data in a database. Upon a match with an authorized individual, the system unlocks the door through an electromagnetic lock. The demand for a rapid and accurate face recognition system persists, continuously evolving to swiftly identify intruders and restrict unauthorized access to highly secure areas, thereby reducing human error. Facial recognition stands as a crucial component within secure systems, surpassing biometric pattern recognition methods, and finds widespread application across various domains.
In [1], we proposed a modified LoRa using two spreading factors (SF's) in order to independently ... more In [1], we proposed a modified LoRa using two spreading factors (SF's) in order to independently set the frequency difference of adjacent LoRa symbols and the LoRa symbol period, and demonstrated that the use of two spreading factors could make it less sensitive to sampling frequency error while enabling low power transmission. In this paper, as an extension of [1], we will show that our scheme has also robustness to the Doppler rate through computer simulations.
This research paper is introduces as a centralized grievance portal based on Artificial Intellige... more This research paper is introduces as a centralized grievance portal based on Artificial Intelligence (AI) for streamlined and effective complaint resolution. The proposed system manipulates advanced AI techniques to enhance the complaint handling process, providing a user-friendly interface for complainants & optimizing resource utilization for resolution authorities. The integration of machine learning algorithms ensures intelligent analysis of complaints, prioritization, and swift solution, ultimately contributing to an efficient and transparent grievance redressal mechanism
The Smart Hindrance Tracking System for Blind Individuals is a mini-project aimed at enhancing th... more The Smart Hindrance Tracking System for Blind Individuals is a mini-project aimed at enhancing the mobility and safety of visually impaired individuals in navigating their surroundings. Leveraging cutting-edge technologies, this system integrates computer vision, sensor networks, and mobile applications to provide real-time hindrance detection and navigation assistance. The primary objective is to empower blind individuals with a reliable and intelligent solution that enables them to identify and navigate around obstacles in their path. The system utilizes a combination of depth-sensing cameras and ultrasonic sensors to detect obstacles in the user's vicinity. These sensors feed data to a central processing unit, where a computer vision algorithm processes the information in real-time, identifying obstacles and their spatial locations. The processed data is then communicated to the user through a user-friendly mobile application. This research presents the daily challenges faced by visually impaired individuals but also fosters inclusivity and independence. The Smart Hindrance Tracking System stands at the intersection of technology and social impact, offering an innovative solution to improve the lives of those with visual impairments.
The capability to perceive and comprehend human emotions holds significant importance across dive... more The capability to perceive and comprehend human emotions holds significant importance across diverse realms of human interaction, ranging from enhancing human-computer interfaces to assisting in mental health diagnosis. This study presents an innovative Smart Emotion Detector, a resilient system engineered to precisely recognize and categorize facial human expression time. Face Detection entails the system's ability to identify human faces captured by the camera. In this context, we implement a digital attendance management system for classroom students utilizing facial recognition techniques.
This research paper dives into the complexities of a programmed stopping framework and electronic... more This research paper dives into the complexities of a programmed stopping framework and electronic stopping expense assortment, principally founded on vehicle number plate acknowledgment. The essential goal is to plan and carry out a programmed stopping framework that essentially improves the accommodation and security of public parking areas. Additionally, it aims to facilitate parking fee collection without the complexities associated with magnetic cards. The proposed automatic parking system boasts several key features. First and foremost, it minimizes human interaction by eliminating the need for magnetic cards and associated devices. Users can seamlessly enter and exit parking lots without physical tokens, enhancing overall convenience. Furthermore, the system incorporates a parking guidance feature that directs users to available parking spaces. Real-time information about vacant spots ensures efficient utilization of parking areas. The heart of the system lies in its number plate recognition capabilities. The significance of this research extends beyond parking management. It contributes to ongoing efforts to automate and digitize essential services, making them more accessible and user-friendly. By embracing such technological advancements, cities can enhance user experiences, improve efficiency, and pave the way for a future of automated systems in public services.
In recent years, the field of computer vision has witnessed significant advancements, particularl... more In recent years, the field of computer vision has witnessed significant advancements, particularly in image classification, owing to the remarkable progress in deep learning techniques. This research paper presents a study on image classification using architectures, challenges, and potential applications. The primary objective is to analyse the effectiveness of deep lear image classification tasks and provide insights into the current trends and future directions in this rapidly evolving domain
The world's population is expanding quickly every day, and a great number of individuals are movi... more The world's population is expanding quickly every day, and a great number of individuals are moving to big cities and other locations in search of employment, better living conditions, or educational opportunities. The development of rental websites is covered in this paper. Property details can be uploaded by landlords and tenants can rent properties through this website. In this research, we have developed website will assist people in giving or accepting rental properties without the need to interact with apartment brokers in order to ultimately come to a mutually beneficial agreement. Among the one hundred different options, the project's goal is to identify and suggest the PG that a user is most likely to book.
Earthquake early warning systems play a crucial role in minimizing the impact of seismic events o... more Earthquake early warning systems play a crucial role in minimizing the impact of seismic events on human life and infrastructure. This research paper explores the integration of Cloud Computing and Internet of Things (IoT) technologies to enhance the effectiveness of earthquake early warning systems. The proposed system aims to provide real-time data collection, analysis, and dissemination of alerts through a distributed network, leveraging the scalability and flexibility of cloud-based platforms. This paper discusses the architecture, components, and benefits of the proposed system, along with a case study to illustrate its potential in earthquake-prone regions.
Competent people are a valuable asset for strong businesses. The issue of retaining competent sta... more Competent people are a valuable asset for strong businesses. The issue of retaining competent staff with expertise poses a challenge to business owners. Employee attrition may be costly for businesses since it takes a lot to compensate for their experience attrition utilizing machine learning techniques. processed using standard scalar with Label Encoding method. The dataset features are selected by using modified genetic algorithm Boosting and Extr experimental results are compared with ML algorithms with classification metrics (Accuracy, Precision, recall and f measure).
Currently, video games have become a rapidly growing industry in our globe. However, they are mos... more Currently, video games have become a rapidly growing industry in our globe. However, they are mostly seen as having a detrimental influence on society. This research aims to investigate and analyse the beneficial effects of the gaming business and its potential in addressing various global challenges. The modern environment has seen a significant upsurge in the video gaming business, establishing it as a swiftly expanding sector. This study aims to thoroughly investigate and explore the positive aspects of the gaming business, despite the common belief that video games mostly have negative impacts on society. By doing so, it aims to clarify the ways in which gaming positively helps to addressing various global concerns. These techniques include the areas of Education and Learning, Social Impact and Empathy, and Crowd-Sourcing and Problem Solving. 1. Education & Learning: Video games have the potential to revolutionize academics by providing immersive learning and interactive experiences. It may also aid in envisioning certain levels, which can facilitate a deeper comprehension. 2. Gaming may facilitate the comprehension of many cultures and enhance social awareness, hence contributing to social impact and empathy. Multiplayer connectedness facilitates emotional and mental connection, allowing players to build emotional bonds with game characters inside the gaming environment. 3. Crowd-sourcing and problem solving: Video games facilitate comprehension of global concerns via virtual reality, devoid of any real-world consequences. It enables the connection with a vast number of actors and addressing significant global challenges.
The nexus between artificial intelligence (AI) and human creativity offers a fascinating paradigm... more The nexus between artificial intelligence (AI) and human creativity offers a fascinating paradigm shift in the dynamic field of music composition. To understand the effects on musical composition, production, and performance, this research study, "Harmony in Synthesis: Exploring Human-AI Collaboration in Music," explores the dynamic interplay between human artists and AI systems. The opening establishes the scene by describing the development of AI in the music business and emphasizing the revolutionary possibilities of teamwork. This study addresses current knowledge through a thorough literature assessment, pointing out gaps that our research aims to remedy and adding to the conversation on AI's involvement in creative processes.
Conservation strategies are redefined by smart conservation, which combines wildlife monitoring a... more Conservation strategies are redefined by smart conservation, which combines wildlife monitoring and artificial intelligence (AI). Artificial intelligence (AI) technologies, such as computer vision and machine learning, automate the identification of species through image and audio analysis, making habitat health assessment and population monitoring more effective. By identifying changes in land cover and habitat decline, AI in conjunction with satellite photography enables ongoing habitat monitoring. AI-driven analytics facilitates the integration of various data sources and offers insightful information for well-informed decision-making. By utilizing both historical and current data, predictive modeling helps to guide proactive conservation measures by predicting how changes in the environment will affect animal populations. AI-enabled real-time alerting and monitoring systems improve the effectiveness of actions against illicit activities like poaching. AI-powered solutions facilitate community interaction by encouraging shared responsibility and increasing awareness. Efficient resource allocation is ensured by resource optimization, which is powered by AI analysis of species distribution and habitat circumstances. This all-encompassing strategy highlights the revolutionary potential of AI in protecting biodiversity, resolving environmental issues, and promoting the long-term coexistence of ecosystems and human activity.
Forest fires present a significant threat to ecosystems, endangering both human and animal life w... more Forest fires present a significant threat to ecosystems, endangering both human and animal life while causing irreversible environmental damage. To address this pressing issue in this research paper introduces an innovative & Affordable forest fire detection system that utilises the HSV algorithm and various computer vision libraries with the use of AI. Our advance system aims to detect & respond to forest fires in real-time, mitigating potential harm to flora and fauna. Our proposed System employs deploy camera sensors distributed at the Sensitive Parts of the forest, continually monitoring the environment. The HSV algorithm enhances the system's capability to accurately identify fire-related hues, ensuring reliable fire detection. Upon detecting a fire, an automatic alarm is triggered, initiating a series of measures to protect the ecosystem proactively. In response to a detected fire, the system automatically reroutes animal pathways to minimize their exposure to danger. Concurrently, the system sends immediate notifications to the local fire department and forest authorities via direct email, providing vital information on the fire's location and severity. This rapid communication facilitates timely intervention and improves the chances of successful firefighting efforts. We can put our system at Jim Corbett National Park & at different Sensitive forest Regions. Furthermore, the system features live monitoring capabilities, enabling authorities to observe the fire's real-time progression. This live feed supports informed decision making and facilitates the swift deployment of resources to contain and extinguish the fire. Through the integration of advanced computer vision technology, our system aims to redefine forest fire detection & response mechanisms, ultimately safeguarding the delicate balance of flora and fauna in ecosystems.
Blockchain technology, originating with Nakamoto's seminal whitepaper in 2008, has evolved into a... more Blockchain technology, originating with Nakamoto's seminal whitepaper in 2008, has evolved into a transformative force, promising decentralized, transparent, and secure digital transactions. H impact of blockchain is accompanied by inherent scalability challenges that impede its widespread adoption and efficiency. This study conducts a comparative analysis of scalability challenges within prominent blockchain networks Ethereum, and Binance Smart Chain. Rooted in a holistic understanding of blockchain evolution, the analysis focuses on transaction throughput, latency, consensus mechanisms, network congestion, and resource utilization. mechanisms, serving a the implications of diverse mechanisms Proof to unravel their impact on transacti confirmation times and overall system efficiency. Balancing this congestion requires a nuanced understanding of network dynamics, block sizes, and transaction prioritizat memory, becomes a focal point for sustainable growth. The study scrutinizes the efficiency of resource allocation and its implications for scalability, acknowledging the delicate balan considerations. By juxtaposing these blockchain networks, the comparative analysis aims to discern patterns, evaluate the effectiveness of consensus mechanisms, and provide actionable insights to address scalab considerations underpin the study, ensuring responsible data usage, user privacy, and adherence to ethical standards in blockchain research. This exploration into scalability challenges within blockchain networks contributes to th discourse on decentralized technologies. The findings are poised to inform future developments, providing a roadmap for enhancing scalability while maintaining the core tenets of decentralization, security, and sustainability.
Quantum computing represents a revolution in the ability to process information, and quantum hard... more Quantum computing represents a revolution in the ability to process information, and quantum hardware technology underpins its implementation. This work examines the current landscape of quantum hardware development, focusing specifically on three main technologies: superconducting qubits, trapped ions, and topological qubits. This study provides an in-depth analysis of the current state of each technology, taking into account its strengths, challenges and opportunities. Research is aimed at identifying current limitations and inefficiencies in this quantum hardware. Additionally, this study aims to present new developments and new methods to solve the identified problems. By combining theoretical knowledge and empirical tests, this research aims to handle to the ongoing debate on the development of quantum hardware that pushes the limits of quantum computing capabilities. The results of this work have important implications for the broader quantum computing community and provide insight into the complexity of superconducting qubits, trapped ions and topological qubits. The improvements and new techniques presented lead to the continued development of quantum hardware and help move the field closer to the realization of practical, scalable quantum computers.
In the ever-evolving landscape of digital infrastructure, the adoption of cloud computing has ush... more In the ever-evolving landscape of digital infrastructure, the adoption of cloud computing has ushered in unparalleled opportunities for innovation but has also introduced complex challenges in securing sensitive data. This research, titled "Beyond the Firewall: Understanding and Mitigating Cloud Security Challenges," embarks on a comprehensive exploration of the multifaceted dimensions surrounding cloud security. The study delves into the intricacies of cloud security, transcending traditional boundaries set by firewalls. From elucidating the dynamics of shared responsibility models to dissecting the nuances of identity and access management, the research unravels the complexities inherent in safeguarding data within the expansive digital cosmos. It addresses elusive threats like data breaches and underscores the critical importance of adaptive strategies to navigate the ever-changing threat landscape. This research goes beyond theoretical discourse, offering actionable insights for organizations seeking to fortify their cyber defenses. It emphasizes the need for a paradigm shift in understanding security challenges in the cloud era and advocates for a proactive approach to mitigate potential risks. By illuminating the path "Beyond the Firewall," this study aims to empower stakeholders with practical knowledge, enabling them to establish robust security frameworks that resonate with the dynamic nature of modern digital ecosystems. Join us on this expedition into the heart of cloud security challenges, as we decipher the complexities and chart a course towards a more resilient and secure digital future.
In education, the importance of gathering and understanding student feedback cannot be over state... more In education, the importance of gathering and understanding student feedback cannot be over stated. Traditional methods of gathering feedback through surveys and assessments often suffer from limitations such as low response rates and subjectivity. This paper proposes a new approach to improve the feedback collection process by implementing a Student Feedback Mining System using sentiment analysis. The goal of this system is to automatically analyze and extract sentiment from student feedback and provide educators and institutions with valuable insights into students' overall satisfaction and feelings toward various aspects of their academic experience. The system uses natural language processing (NLP) techniques to process unstructured text data, identify sentiments, and categorize feedback into positive, negative, or neutral feelings. Collecting student feedback through various channels such as online surveys, discussion forums and other feedback mechanisms. Cleaning and preprocessing the collected text data to remove noise, irrelevant information and standardize the format for analysis. Using state of the art NLP algorithms and sentiment analysis techniques to determine the emotional tone of feedback. This includes classifying sentiment as positive, negative, or neutral. Grouping feedback based on specific criteria such as course content, teaching methods, facilities and overall learning experience to provide a comprehensive understanding of the various aspects affecting student satisfaction. Presenting analyzed data through intuitive visualizations and reports, making it easy for educators and administrators to interpret and respond to feedback. Creating feedback that enables continuous improvement by providing actionable insights for educators to improve their teaching methods, curriculum and overall learning environment. The proposed system aims to overcome the limitations of traditional feedback collection methods by automating the analysis process, providing real-time insights and supporting a data-driven approach to improving education. Using sentiment analysis, educators and institutions can proactively solve problems, improve the quality of education, and create a more positive and engaging learning environment.
The main indicator that measures the economic development and power of the country affect the eco... more The main indicator that measures the economic development and power of the country affect the economy. difficult aspects of financial forecasting. Predicting stock prices accurately can make investors profitable. to the complex of the data in the primary objective of this article is to offer insights into forecasting market prices, aiding investors in making well decisions. The methodologies t processing, and sentiment analysis qualitative and quantitative data.
The proposed research paper describes an object System of recognition based on human perception, ... more The proposed research paper describes an object System of recognition based on human perception, which is achieved by feature extraction (components) and pattern analysis. Both strategies are applied to each subpart. Feature extraction is done using shaping and pattern analysis is achieved by creating statistical bins for each pattern of vehicle subparts. Each bin contains general and specific measures, and each measure has a certain weight that contributes to the analysis of each bin to decide on similarity or dissimilarity. Object recognition is an important task in computer vision, with applications in robotics, driverless cars, medical image analysis, and many other applications. This article explores the concept of product analysis using benchmarks, highlighting key concepts, methods and recent developments.
To ensure the accuracy and efficiency of intruder identification, the proposed method is combined... more To ensure the accuracy and efficiency of intruder identification, the proposed method is combined with Haar classifier technology for face detection. When someone comes to the door, the Pi camera captures the image and starts the face detection process. In this research, we implement a facial recognition component to capture human images, comparing them with stored data in a database. Upon a match with an authorized individual, the system unlocks the door through an electromagnetic lock. The demand for a rapid and accurate face recognition system persists, continuously evolving to swiftly identify intruders and restrict unauthorized access to highly secure areas, thereby reducing human error. Facial recognition stands as a crucial component within secure systems, surpassing biometric pattern recognition methods, and finds widespread application across various domains.
In [1], we proposed a modified LoRa using two spreading factors (SF's) in order to independently ... more In [1], we proposed a modified LoRa using two spreading factors (SF's) in order to independently set the frequency difference of adjacent LoRa symbols and the LoRa symbol period, and demonstrated that the use of two spreading factors could make it less sensitive to sampling frequency error while enabling low power transmission. In this paper, as an extension of [1], we will show that our scheme has also robustness to the Doppler rate through computer simulations.
This research paper is introduces as a centralized grievance portal based on Artificial Intellige... more This research paper is introduces as a centralized grievance portal based on Artificial Intelligence (AI) for streamlined and effective complaint resolution. The proposed system manipulates advanced AI techniques to enhance the complaint handling process, providing a user-friendly interface for complainants & optimizing resource utilization for resolution authorities. The integration of machine learning algorithms ensures intelligent analysis of complaints, prioritization, and swift solution, ultimately contributing to an efficient and transparent grievance redressal mechanism
The Smart Hindrance Tracking System for Blind Individuals is a mini-project aimed at enhancing th... more The Smart Hindrance Tracking System for Blind Individuals is a mini-project aimed at enhancing the mobility and safety of visually impaired individuals in navigating their surroundings. Leveraging cutting-edge technologies, this system integrates computer vision, sensor networks, and mobile applications to provide real-time hindrance detection and navigation assistance. The primary objective is to empower blind individuals with a reliable and intelligent solution that enables them to identify and navigate around obstacles in their path. The system utilizes a combination of depth-sensing cameras and ultrasonic sensors to detect obstacles in the user's vicinity. These sensors feed data to a central processing unit, where a computer vision algorithm processes the information in real-time, identifying obstacles and their spatial locations. The processed data is then communicated to the user through a user-friendly mobile application. This research presents the daily challenges faced by visually impaired individuals but also fosters inclusivity and independence. The Smart Hindrance Tracking System stands at the intersection of technology and social impact, offering an innovative solution to improve the lives of those with visual impairments.
The capability to perceive and comprehend human emotions holds significant importance across dive... more The capability to perceive and comprehend human emotions holds significant importance across diverse realms of human interaction, ranging from enhancing human-computer interfaces to assisting in mental health diagnosis. This study presents an innovative Smart Emotion Detector, a resilient system engineered to precisely recognize and categorize facial human expression time. Face Detection entails the system's ability to identify human faces captured by the camera. In this context, we implement a digital attendance management system for classroom students utilizing facial recognition techniques.
This research paper dives into the complexities of a programmed stopping framework and electronic... more This research paper dives into the complexities of a programmed stopping framework and electronic stopping expense assortment, principally founded on vehicle number plate acknowledgment. The essential goal is to plan and carry out a programmed stopping framework that essentially improves the accommodation and security of public parking areas. Additionally, it aims to facilitate parking fee collection without the complexities associated with magnetic cards. The proposed automatic parking system boasts several key features. First and foremost, it minimizes human interaction by eliminating the need for magnetic cards and associated devices. Users can seamlessly enter and exit parking lots without physical tokens, enhancing overall convenience. Furthermore, the system incorporates a parking guidance feature that directs users to available parking spaces. Real-time information about vacant spots ensures efficient utilization of parking areas. The heart of the system lies in its number plate recognition capabilities. The significance of this research extends beyond parking management. It contributes to ongoing efforts to automate and digitize essential services, making them more accessible and user-friendly. By embracing such technological advancements, cities can enhance user experiences, improve efficiency, and pave the way for a future of automated systems in public services.
In recent years, the field of computer vision has witnessed significant advancements, particularl... more In recent years, the field of computer vision has witnessed significant advancements, particularly in image classification, owing to the remarkable progress in deep learning techniques. This research paper presents a study on image classification using architectures, challenges, and potential applications. The primary objective is to analyse the effectiveness of deep lear image classification tasks and provide insights into the current trends and future directions in this rapidly evolving domain
The world's population is expanding quickly every day, and a great number of individuals are movi... more The world's population is expanding quickly every day, and a great number of individuals are moving to big cities and other locations in search of employment, better living conditions, or educational opportunities. The development of rental websites is covered in this paper. Property details can be uploaded by landlords and tenants can rent properties through this website. In this research, we have developed website will assist people in giving or accepting rental properties without the need to interact with apartment brokers in order to ultimately come to a mutually beneficial agreement. Among the one hundred different options, the project's goal is to identify and suggest the PG that a user is most likely to book.
Earthquake early warning systems play a crucial role in minimizing the impact of seismic events o... more Earthquake early warning systems play a crucial role in minimizing the impact of seismic events on human life and infrastructure. This research paper explores the integration of Cloud Computing and Internet of Things (IoT) technologies to enhance the effectiveness of earthquake early warning systems. The proposed system aims to provide real-time data collection, analysis, and dissemination of alerts through a distributed network, leveraging the scalability and flexibility of cloud-based platforms. This paper discusses the architecture, components, and benefits of the proposed system, along with a case study to illustrate its potential in earthquake-prone regions.
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Papers by IRJCS Computer Journal
1. Education & Learning: Video games have the potential to revolutionize academics by providing immersive learning and interactive experiences. It may also aid in envisioning certain levels, which can facilitate a deeper comprehension.
2. Gaming may facilitate the comprehension of many cultures and enhance social awareness, hence contributing to social impact and empathy. Multiplayer connectedness facilitates emotional and mental connection, allowing players to build emotional bonds with game characters inside the gaming environment.
3. Crowd-sourcing and problem solving: Video games facilitate comprehension of global concerns via virtual reality, devoid of any real-world consequences. It enables the connection with a vast number of actors and addressing significant global challenges.
1. Education & Learning: Video games have the potential to revolutionize academics by providing immersive learning and interactive experiences. It may also aid in envisioning certain levels, which can facilitate a deeper comprehension.
2. Gaming may facilitate the comprehension of many cultures and enhance social awareness, hence contributing to social impact and empathy. Multiplayer connectedness facilitates emotional and mental connection, allowing players to build emotional bonds with game characters inside the gaming environment.
3. Crowd-sourcing and problem solving: Video games facilitate comprehension of global concerns via virtual reality, devoid of any real-world consequences. It enables the connection with a vast number of actors and addressing significant global challenges.