International Journal of Innovative Research in Information Security is an International peer-reviewed research publishing journal with a laser-beam focal aim of promoting and publishing original high quality research dealing with theoretical and scientific aspects in all disciplines of Information Technology. It is a monthly published online international scientific research journal focusing on issues in information technology research.
All technical or research papers and research results submitted to IJIRIS should be original in nature, never previously published in any journal or presented in a conference or undergoing such process across the globe. All the submissions will be peer-reviewed by the panel of experts associated with particular field. Submitted papers should meet the internationally accepted criteria and manuscripts should follow the style of the journal for the purpose of both reviewing and editing. All of its articles also appear online on public domain Supervisors: Dr.A.Arul L.S Phone: +917402613921 Address: PLOT-9, VARUNA GOLD ENCLAVE,OPP-ANAND ELECTRONICS NEAR-OLD BUS STAND, HOSUR-635109 TAMIL NADU,INDIA
We have increasingly seen that new graduates have difficulty finding a jobs than the ones they gr... more We have increasingly seen that new graduates have difficulty finding a jobs than the ones they graduated from, this may be the lack of pr are very useful and a topic of interest in the field of computer science and artificial intelligence due to their ability to emulate experts in different ap chatbots to provide career advice can be an effective way to provide these services in an environment where counselors work. The lack of good and appropriate vocationa parents have chosen for them, or jobs chosen they are in the person's best interests and not only their personal health but better inform users and help them choose jobs. This will enable them to con more fulfilling and fulfilling than jobs that do not align with their interests. Research and development software was used in this study. According to the research method, the research was conducted to collect info thoughts about research on career guidance was taken into account when creating the basis of the survey. This information is used t develop a chatbot on the Facebook Messenger platform using objects powered using tools such as the Facebook SDK, Messenger Platform API and JavaScript, as well as the Wit.ai API that supports na Chatbots can unders hoped that the results obtained will create a positive impression of the implementation of the system and thus become a valuable asset for any school or i Keywords: This study examines the current state of career counseling and finds that the lack of adequate career counseling at university and solutions for using chatbot career advice that students and graduates can use to help them find career opportunities. Every student's concern afte finding jobs and workers were less interested in the workplace. According to a study by Universum SA, 47% professionals Choosing a job that suits your interests
This research investigates the transformative impact of machine learning (ML) on stock market ana... more This research investigates the transformative impact of machine learning (ML) on stock market analysis, assessing its potential benefits and confronting associated challenges. The study employs various ML models, including regression, classification, clustering, and natural language processing, to analyze extensive datasets comprising historical stock prices, financial indicators, economic data, and sentiment from social media. Key findings reveal that ML models exhibit superior accuracy in forecasting market movements and stock prices compared to traditional methods. Automated anomaly detection algorithms demonstrate proficiency in identifying unusual market behaviour, offering timely warnings for potential market shifts and fraudulent activities. ML-powered risk assessment tools showcase the capacity to personalize investment strategies based on individual preferences, augmenting decision-making for investors. Despite challenges such as data quality, model selection, and ethical considerations, the research underscores the undeniable potential of ML in stock market analysis. Rigorous methodologies, including data preprocessing, feature engineering, and model evaluation, contribute to the robustness of the findings. Ethical considerations, including algorithmic biases and transparency are thoroughly explored to ensure responsible application in the financial domain.
In higher education, the continuous improvement of teaching quality is paramount for fostering a ... more In higher education, the continuous improvement of teaching quality is paramount for fostering a conducive learning environment. This study presents a Faculty Feedback Extraction System (FFES) that utilizes state-of-the-art sentiment analysis techniques to derive actionable insights from faculty feedback. The system uses natural language processing (NLP) and machine learning algorithms to analyze and classify emotions, giving schools a better understanding of teachers' emotions and fostering a culture of continuous improvement. The FFMS employs a multifaceted sentiment analysis approach, considering both textual and contextual features to ensure nuanced interpretation of faculty feedback. Leveraging a diverse dataset of faculty evaluations, the system uses the highest sentiment rating standards to classify emotions into positive, negative or neutral categories. This research focuses on to apply the approach which allows schools to better understand teachers' views and helps influence professional and overall development. FFMS provides deep learning models such as neural network (RNN) and tracking techniques to improve the accuracy and depth of emotion classification. These models enable the system to capture subtle nuances in feedback, providing a more nuanced understanding of faculty sentiments. Additionally, the FFMS facilitates real-time monitoring and analysis through intuitive dashboards, empowering academic administrators to make informed decisions based on the latest feedback trends.
In contemporary military and civilian environments, the role of camouflage patterns in providing ... more In contemporary military and civilian environments, the role of camouflage patterns in providing concealment and protection is paramount. The evolution of traditional camouflage into digital formats has paved the way for innovative design techniques, and the integration of artificial intelligence (AI) has revolutionized the process. This comprehensive review paper delves into the historical context, methodologies, challenges, and prospects of AI-driven digital camouflage pattern generation systems. The review commences with an exploration of the historical development of camouflage patterns, tracing their journey from basic naturalistic designs to the intricacies of digital patterns. It emphasizes the significant shift towards digitalization, enabling greater flexibility, adaptability, and effectiveness in camouflage design. The infusion of AI into this realm has ushered in a new era of possibilities and enhancements. Key components of AI-based camouflage pattern generation are investigated in depth. The paper highlights the crucial role of data collection and preprocessing, emphasizing the necessity of diverse and high-quality datasets to train AI models effectively. It also examines feature extraction methods, showcasing how image analysis, computer vision techniques, and machine learning algorithms aid in identifying relevant patterns and textures present in various natural environments. The core of AI-driven camouflage pattern generation revolves around the selection and application of machine learning algorithms. The review provides comprehensive insights into various AI approaches, including deep learning, genetic algorithms, neural networks, and evolutionary computing, while highlighting their respective strengths and limitations in the context of camouflage pattern design. It underscores the capabilities of convolutional neural networks (CNNs) in recognizing complex patterns and textures and discusses the potential of generative adversarial networks (GANs) in generating realistic and adaptable camouflage designs. Additionally, the review addresses the critical aspect of evaluating the effectiveness of AI-generated camouflage patterns. It discusses common evaluation metrics such as detection and recognition rates, human perception studies, and real-world testing scenarios. The paper acknowledges the challenge of striking a balance between pattern effectiveness, aesthetic appeal, and human factors, emphasizing the need for holistic evaluation criteria. Despite the promise and progress in AI-based camouflage pattern generation, the review acknowledges existing challenges and limitations. These include the need for extensive and diverse training datasets, substantial computational resources, and ethical considerations surrounding the potential misuse of AI-generated camouflage patterns. Furthermore, it underscores the importance of environmental sustainability by considering the ecological impact of camouflage pattern materials and production processes.
This research paper delves into the intricate world of stock market analysis, exploring the appli... more This research paper delves into the intricate world of stock market analysis, exploring the application of machine learning techniques to enhance performance evaluation. The study adopts multifaceted approach, combining historical stock market data, advanced machine learning algorithms, and rigorous back testing to derive insights into market dynamics. The findings aim to contribute to the growing body of literature on financial analytics, providing valuable implications for investors and financial professionals.
Wireless Sensor Networks (WSNs) are self-deploying, dynamic network architecture with extremely c... more Wireless Sensor Networks (WSNs) are self-deploying, dynamic network architecture with extremely confined and organized nodes. Nodes in this environment have limited transmission range, processing capacity, and energy resources. Extending the network's lifetime is dependent on managing energy constraints and improving the usage of sensor node processing capabilities. Effective power management approaches are critical for attaining the objective of decreasing the consumption of energy at the individual sensor node level. Furthermore, adaptive and efficient routing systems have received significant academic interest due to their potential for improving network operation. The inclusion of Soft Computing concepts is an effective strategy for addressing the numerous issues in WSNs. Soft computing methods are well-known for their adaptability and compatibility with WSNs, which are suitable for solving essential complications. This study provides an overview of several Soft Computing-based routing models optimized for WSNs, with a focus on increasing network lifetime. Soft Computing routing models use approaches including fuzzy logic, neural networks, evolutionary algorithms, and swarm intelligence to create routing choices that maximize energy efficiency and network operating duration. These models provide potential solutions to the energy and processing limits in WSNs by intelligently adapting to changing environmental circumstances and network dynamics, thereby enhancing network lifetime and dependability.
Over wireless sensor networks, consumption of energy due to needless transmitting data is a serio... more Over wireless sensor networks, consumption of energy due to needless transmitting data is a serious issue (WSNs). By addressing this issue, any station's lifetime can be extended and system practicality for real world applications can be increased. As a result, for WSN's that use low-powered different sensors, energy-efficient information gathering has become a necessity. Data grouping and forecasting approaches based on symmetrical correlation in sensor information can be utilized in order to downplay the complete utilization of energy consumption of the network for sustained collecting data in these situations. We have integrated a group study of Random Forest(RF) Technique, LSTM technique and Particle Filter (PF) which would be used for a efficient method to evaluate and predict the data required by the Sensor nodes to completely minimize the unnecessary data Transmission. Segmentation and data aggregating to each member nodes are used to effectively make data gathering forecasts in WSNs, primarily to reduce the computational overhead cost associated with constructing the prediction model. Simulation trials, comparison, and performance-based assessment in a variety of scenarios reveal that our approach's forecasting accuracy can exceed traditional ARIMA and Kalman filters with Decision tree models, resulting in improved energy consumption due to fewer packet transmissions.
Additive Manufacturing (AM), commonly known as 3D printing, has revolutionized the field of biome... more Additive Manufacturing (AM), commonly known as 3D printing, has revolutionized the field of biomedical applications by offering innovative solutions for personalized and complex structures. This technology enables the fabrication of patient-specific implants, prosthetics, and tissues with enhanced precision and customization. The versatility of additive manufacturing allows the incorporation of biocompatible materials, fostering the development of implants tailored to individual anatomical requirements. Additionally, the rapid prototyping capabilities of 3D printing facilitate the creation of intricate models for surgical planning and education. The use of bioinks and biomaterials in additive manufacturing has paved the way for the fabrication of functional tissues and organs, advancing the prospects of regenerative medicine. Furthermore, the scalability and cost-effectiveness of 3D printing in the biomedical field hold significant promise for widespread adoption and accessibility. In conclusion, additive manufacturing stands as a transformative force in biomedical applications, offering unparalleled opportunities for personalized healthcare and advancing the frontiers of medical technology.
This project proposes a blockchain-based solution to enhance the regulation and supervision of me... more This project proposes a blockchain-based solution to enhance the regulation and supervision of medical waste disposal, addressing critical loopholes in current management practices. By introducing decentralized system architecture and smart contracts, the model ensures the authenticity and credibility of medical waste data throughout its lifecycle. Digital credentials are employed to protect operator information privacy, while blockchain technology facilitates information sharing and transfer among stakeholders. The integration of digital credentials for physical certificates enhances security and privacy protection. The model offers authoritative evidence for regulatory bodies, supporting the establishment of a new generation of medical waste regulatory information systems. Through insightful discussions and case studies, the practicability of blockchain in waste management is highlighted, paving the way for a more efficient and accountable approach to medical waste disposal.
Exposure to cold temperatures is, often, a neglected problem in ICUs, CT, AND MRI scans it may ca... more Exposure to cold temperatures is, often, a neglected problem in ICUs, CT, AND MRI scans it may cause several discomforts such as shivering, lung diseases, and artifacts in scan reports, etc., one of the leading influences of the overall sensation of cold discomfort is the cooling of the back. This study aimed to evaluate the effect of a heated ambulance mattress-prototype on body temperatures and thermal comfort in an experimental study. The endotherm patient warming mattress and ambulatory patient mattress are the preexisting projects. The Inditherm mattress is designed for use by all patients undergoing anesthesia who may be at risk of inadvertent pre-operative hypothermia, and for any patients who require warming in pre-operative, intra-operative, and postoperative settings the ambulatory mattress is generally a warming mattress. The main disadvantage is that these two technologies are not automated the operator has to set all parameters. In this project, we are designing a mattress that liberates heat depending on room temperature. The Lab VIEW controls on and off of the system it compares the room temperature with the present value and produces a suitable result. The main advantage is the project is fully automated and warms the patient only at the required time.
Rheumatoid arthritis (RA) is a chronic gender, genetics, and environmental exposures. Complicatio... more Rheumatoid arthritis (RA) is a chronic gender, genetics, and environmental exposures. Complications, such as joint damage, rheumatoid vasculitis, and Felty syndrome, underscore the need for effective management. Treatment mod Antirheumatic Drugs (DMARDs) to physical therapy and surgery, aim to alleviate symptoms and prevent further damage. While there is no cure for RA, ongoing research explores emerging therapies and precision medicine a multidisciplinary approach is crucial, tailoring treatment to individual needs for optimal outcomes and improved quality of life. Regular monitoring and adjustments to the treatment plan are essential aspects of RA management. Keywords: Rheuma Rheumatoid arthritis (RA) stands as a formidable challenge in the realm of autoimmune diseases, characterized by chronic inflammation that primarily targets the synovial joints [1 gender, genetics, and environmental factors such as cigarette smoking and exposure to air pollutants. The disease manifests variably in severity among patients, leading to a myriad of complications, including permanent joint damage necessitating arthroplasty, the dev splenectomy if left unaddressed.
Due to a widespread use of electronic goods and an increasing trend towards desk-bound work envir... more Due to a widespread use of electronic goods and an increasing trend towards desk-bound work environments, the prevalence of sedentary behaviors has reached alarming levels in the present rapidly evolving technological landscape. Poor posture, a common result of inactivity, has negative effects on your mental as well as physical wellness and overall quality of life. The third most prevalent reason why people go to the doctor on a worldwide scale is for back pain, which is often caused by poor posture. This paper explores the negative effects of sitting for long periods of time and slouching, and how important it is to maintain good posture for health and well-being in general.
This study presents an innovative IoT - based system for the real-time management of Parkinson's ... more This study presents an innovative IoT - based system for the real-time management of Parkinson's Disease using a combination of Flex Sensor, Node MCU, SCR Sensor, and ADXL335. The Flex Sensor captures hand tremors, the ADXL335 monitors overall motion, and the SCR Sensor measures physiological stress levels. These components collectively enable continuous monitoring of Parkinson's symptoms. The data is wireless transmitted to a centralized server for analysis, allowing healthcare providers to remotely assess patient conditions. Machine learning algorithms offer insights into disease progression and predict potential exacerbation. The system provides timely alerts, enhancing patient care and reducing healthcare costs. This research contributes to the evolving landscape of IoT applications in healthcare for neurodegenerative disorders.
Wireless Body Area Networks (WBANs) integrate diverse sensors like heart rate monitors, electroca... more Wireless Body Area Networks (WBANs) integrate diverse sensors like heart rate monitors, electrocardiograms, pulse oximeters, respiration rate sensors, gyroscopes, and skin conductance sensors into a network for pervasive healthcare delivery. This interconnected system enables real-time monitoring and data fusion, ensuring accurate and comprehensive health assessments. Efficient communication protocols, cloud integration, and power management enhance the reliability and longevity of wearable devices. Security measures and user-friendly interfaces prioritize the protection of sensitive health data and ease of access. Machine learning algorithms contribute to predictive analytics for early detection of health issues. WBANs offer a holistic approach to personalized healthcare, allowing for continuous and remote monitoring of physiological parameters. The seamless integration of these sensors establishes a foundation for timely intervention and improved patient outcomes.
This project aims to develop a system equipped with machine learning algorithm capable of continu... more This project aims to develop a system equipped with machine learning algorithm capable of continuously monitoring respiratory conduct. The system utilizes machine learning to interpret pulmonary function tests, lift the management of respiratory diseases, and potentially deliver improvements in the diagnosis and treatment of various disease states in pulmonary and critical care medicine. Additionally, the system automatically predicts lung function based on acoustic signals from coughing and wheezing, enabling noninvasive monitoring of asthma severity. The project also seeks to forecast lung age and improve the current dataset of audio samples to enhance the accuracy and reliability of the results. The application of machine learning in pulmonary function testing holds significant potential for remote monitoring of high risk patients and the early detection and treatment of lung diseases.
This IoT enhance user adherence and automate dispensing processes. Delivery System utilizing a bu... more This IoT enhance user adherence and automate dispensing processes. Delivery System utilizing a buzzer, RTC DS3231 module, LCD display, IR sensor, and G designed to enhance medication adherence and patient care. The Node MCU and Arduino facilitate seamless integration of components, while the RTC DS3231 module ensures precise timekeeping for medication schedules. An LCD display provides real dosage retrieval. Additionally, a buzzer provides audible alerts for medication reminders. The incorporation of GSM technology allows system aims to improve patient outcomes and simplify medication management.
This project presents a cost-effective IoT-based system designed for monitoring temperature, humi... more This project presents a cost-effective IoT-based system designed for monitoring temperature, humidity, and dust levels in food storage environments to mitigate the risk of food poisoning. Utilizing sensors and a microcontroller, real-time data is collected and transmitted to a cloud platform through a secure communication protocol. The cloud-based solution incorporates a backend server and a database for efficient data processing and storage. A user-friendly web or mobile interface enables stakeholders to monitor conditions, set custom thresholds, and receive timely alerts. The system's design emphasizes scalability, adaptability, and ease of deployment, making it suitable for various food storage facilities. Rigorous testing ensures the reliability and accuracy of the system, and its implementation is intended to enhance food safety practices. Ongoing maintenance and updates are incorporated to ensure the sustained effectiveness of the monitoring solution in preventing food borne illnesses.
This project introduces an IoT environments. Utilizing a variety of sensors, including those for ... more This project introduces an IoT environments. Utilizing a variety of sensors, including those for particulate matter, carbon dioxide, and volatile organic compounds, the system ensures continuous real communication, enabling the transmission of data to a central server or cloud platform. Hospital staff can remotely monitor air quality conditions, receiving threshold alerts in the event of pollutant system integrates a controlling mechanism, allowing for the activation of ventilation systems or air purifiers based on the collected data. Energy efficiency is prioritized through intelligent control of air qualit enables administrators to identify patterns and improve overall air quality management. The system seamlessly integrates with existing hospital infrastructure and is designed for scalability, ensuring adaptability to evo based solution offers a smart and automated approach to maintaining a healthy indoor environment in hospital settings.
Hypersomnia, a sleep disorder characterized by excessive daytime sleepiness and prolonged nocturn... more Hypersomnia, a sleep disorder characterized by excessive daytime sleepiness and prolonged nocturnal sleep, poses significant challenges to individuals' daily functioning. Afflicted individuals struggle to stay awake during waking hours despite extended periods of sleep, often experiencing difficulties waking up in the morning. Cognitive functions, including memory and concentration, may be impaired, leading to social and occupational hindrances. While short naps provide minimal relief, hypersomnia's impact on overall well-being necessitates timely diagnosis and intervention. Diagnosis involves a comprehensive assessment of medical history and, if required, polysomnography. Treatment strategies, ranging from lifestyle modifications to pharmacological interventions, aim to address the underlying causes, which may be primary or secondary to other medical conditions. Timely recognition and management of hypersomnia are crucial to mitigating its adverse effects on daily life and fostering improved sleep quality and daytime alertness.
Traditional cupping therapy (CT) has been around for a long time and is still used today to treat... more Traditional cupping therapy (CT) has been around for a long time and is still used today to treat many different kinds of medical issues. Still, researchers have yet to pin down exactly how (CT) works. Looking at CT through the lens of contemporary medicine, this review set out to determine how it might work and provide some explanations for its effects. A search was conducted using keywords in the English publications in PubMed, Cochrane Library, and Google Scholar. From the 223 articles that were found, 149 records were reviewed and 74 articles were deemed irrelevant and removed. Of the 75 full-text publications that were considered for this review, 64 were ultimately included. There are six competing explanations for the benefits of cupping therapy. Nitric Oxide theory may provide an explanation for the calming effects on muscles, alterations in local tissue structures, and improvements in blood circulation. The Activation of immune system theory may explain the hormonal changes and immunological effects. According to the "Blood Detoxification Theory" heavy metals and waste are eliminated while toxins are released. These theories can complement one another or even be used interchangeably to treat different diseases and ailments. It would appear that the many impacts of cupping cannot be adequately explained by a single theory. The aforementioned theories require further investigation to either confirm or disprove them, and future research should also aim to develop novel conceptualizations of CT.
We have increasingly seen that new graduates have difficulty finding a jobs than the ones they gr... more We have increasingly seen that new graduates have difficulty finding a jobs than the ones they graduated from, this may be the lack of pr are very useful and a topic of interest in the field of computer science and artificial intelligence due to their ability to emulate experts in different ap chatbots to provide career advice can be an effective way to provide these services in an environment where counselors work. The lack of good and appropriate vocationa parents have chosen for them, or jobs chosen they are in the person's best interests and not only their personal health but better inform users and help them choose jobs. This will enable them to con more fulfilling and fulfilling than jobs that do not align with their interests. Research and development software was used in this study. According to the research method, the research was conducted to collect info thoughts about research on career guidance was taken into account when creating the basis of the survey. This information is used t develop a chatbot on the Facebook Messenger platform using objects powered using tools such as the Facebook SDK, Messenger Platform API and JavaScript, as well as the Wit.ai API that supports na Chatbots can unders hoped that the results obtained will create a positive impression of the implementation of the system and thus become a valuable asset for any school or i Keywords: This study examines the current state of career counseling and finds that the lack of adequate career counseling at university and solutions for using chatbot career advice that students and graduates can use to help them find career opportunities. Every student's concern afte finding jobs and workers were less interested in the workplace. According to a study by Universum SA, 47% professionals Choosing a job that suits your interests
This research investigates the transformative impact of machine learning (ML) on stock market ana... more This research investigates the transformative impact of machine learning (ML) on stock market analysis, assessing its potential benefits and confronting associated challenges. The study employs various ML models, including regression, classification, clustering, and natural language processing, to analyze extensive datasets comprising historical stock prices, financial indicators, economic data, and sentiment from social media. Key findings reveal that ML models exhibit superior accuracy in forecasting market movements and stock prices compared to traditional methods. Automated anomaly detection algorithms demonstrate proficiency in identifying unusual market behaviour, offering timely warnings for potential market shifts and fraudulent activities. ML-powered risk assessment tools showcase the capacity to personalize investment strategies based on individual preferences, augmenting decision-making for investors. Despite challenges such as data quality, model selection, and ethical considerations, the research underscores the undeniable potential of ML in stock market analysis. Rigorous methodologies, including data preprocessing, feature engineering, and model evaluation, contribute to the robustness of the findings. Ethical considerations, including algorithmic biases and transparency are thoroughly explored to ensure responsible application in the financial domain.
In higher education, the continuous improvement of teaching quality is paramount for fostering a ... more In higher education, the continuous improvement of teaching quality is paramount for fostering a conducive learning environment. This study presents a Faculty Feedback Extraction System (FFES) that utilizes state-of-the-art sentiment analysis techniques to derive actionable insights from faculty feedback. The system uses natural language processing (NLP) and machine learning algorithms to analyze and classify emotions, giving schools a better understanding of teachers' emotions and fostering a culture of continuous improvement. The FFMS employs a multifaceted sentiment analysis approach, considering both textual and contextual features to ensure nuanced interpretation of faculty feedback. Leveraging a diverse dataset of faculty evaluations, the system uses the highest sentiment rating standards to classify emotions into positive, negative or neutral categories. This research focuses on to apply the approach which allows schools to better understand teachers' views and helps influence professional and overall development. FFMS provides deep learning models such as neural network (RNN) and tracking techniques to improve the accuracy and depth of emotion classification. These models enable the system to capture subtle nuances in feedback, providing a more nuanced understanding of faculty sentiments. Additionally, the FFMS facilitates real-time monitoring and analysis through intuitive dashboards, empowering academic administrators to make informed decisions based on the latest feedback trends.
In contemporary military and civilian environments, the role of camouflage patterns in providing ... more In contemporary military and civilian environments, the role of camouflage patterns in providing concealment and protection is paramount. The evolution of traditional camouflage into digital formats has paved the way for innovative design techniques, and the integration of artificial intelligence (AI) has revolutionized the process. This comprehensive review paper delves into the historical context, methodologies, challenges, and prospects of AI-driven digital camouflage pattern generation systems. The review commences with an exploration of the historical development of camouflage patterns, tracing their journey from basic naturalistic designs to the intricacies of digital patterns. It emphasizes the significant shift towards digitalization, enabling greater flexibility, adaptability, and effectiveness in camouflage design. The infusion of AI into this realm has ushered in a new era of possibilities and enhancements. Key components of AI-based camouflage pattern generation are investigated in depth. The paper highlights the crucial role of data collection and preprocessing, emphasizing the necessity of diverse and high-quality datasets to train AI models effectively. It also examines feature extraction methods, showcasing how image analysis, computer vision techniques, and machine learning algorithms aid in identifying relevant patterns and textures present in various natural environments. The core of AI-driven camouflage pattern generation revolves around the selection and application of machine learning algorithms. The review provides comprehensive insights into various AI approaches, including deep learning, genetic algorithms, neural networks, and evolutionary computing, while highlighting their respective strengths and limitations in the context of camouflage pattern design. It underscores the capabilities of convolutional neural networks (CNNs) in recognizing complex patterns and textures and discusses the potential of generative adversarial networks (GANs) in generating realistic and adaptable camouflage designs. Additionally, the review addresses the critical aspect of evaluating the effectiveness of AI-generated camouflage patterns. It discusses common evaluation metrics such as detection and recognition rates, human perception studies, and real-world testing scenarios. The paper acknowledges the challenge of striking a balance between pattern effectiveness, aesthetic appeal, and human factors, emphasizing the need for holistic evaluation criteria. Despite the promise and progress in AI-based camouflage pattern generation, the review acknowledges existing challenges and limitations. These include the need for extensive and diverse training datasets, substantial computational resources, and ethical considerations surrounding the potential misuse of AI-generated camouflage patterns. Furthermore, it underscores the importance of environmental sustainability by considering the ecological impact of camouflage pattern materials and production processes.
This research paper delves into the intricate world of stock market analysis, exploring the appli... more This research paper delves into the intricate world of stock market analysis, exploring the application of machine learning techniques to enhance performance evaluation. The study adopts multifaceted approach, combining historical stock market data, advanced machine learning algorithms, and rigorous back testing to derive insights into market dynamics. The findings aim to contribute to the growing body of literature on financial analytics, providing valuable implications for investors and financial professionals.
Wireless Sensor Networks (WSNs) are self-deploying, dynamic network architecture with extremely c... more Wireless Sensor Networks (WSNs) are self-deploying, dynamic network architecture with extremely confined and organized nodes. Nodes in this environment have limited transmission range, processing capacity, and energy resources. Extending the network's lifetime is dependent on managing energy constraints and improving the usage of sensor node processing capabilities. Effective power management approaches are critical for attaining the objective of decreasing the consumption of energy at the individual sensor node level. Furthermore, adaptive and efficient routing systems have received significant academic interest due to their potential for improving network operation. The inclusion of Soft Computing concepts is an effective strategy for addressing the numerous issues in WSNs. Soft computing methods are well-known for their adaptability and compatibility with WSNs, which are suitable for solving essential complications. This study provides an overview of several Soft Computing-based routing models optimized for WSNs, with a focus on increasing network lifetime. Soft Computing routing models use approaches including fuzzy logic, neural networks, evolutionary algorithms, and swarm intelligence to create routing choices that maximize energy efficiency and network operating duration. These models provide potential solutions to the energy and processing limits in WSNs by intelligently adapting to changing environmental circumstances and network dynamics, thereby enhancing network lifetime and dependability.
Over wireless sensor networks, consumption of energy due to needless transmitting data is a serio... more Over wireless sensor networks, consumption of energy due to needless transmitting data is a serious issue (WSNs). By addressing this issue, any station's lifetime can be extended and system practicality for real world applications can be increased. As a result, for WSN's that use low-powered different sensors, energy-efficient information gathering has become a necessity. Data grouping and forecasting approaches based on symmetrical correlation in sensor information can be utilized in order to downplay the complete utilization of energy consumption of the network for sustained collecting data in these situations. We have integrated a group study of Random Forest(RF) Technique, LSTM technique and Particle Filter (PF) which would be used for a efficient method to evaluate and predict the data required by the Sensor nodes to completely minimize the unnecessary data Transmission. Segmentation and data aggregating to each member nodes are used to effectively make data gathering forecasts in WSNs, primarily to reduce the computational overhead cost associated with constructing the prediction model. Simulation trials, comparison, and performance-based assessment in a variety of scenarios reveal that our approach's forecasting accuracy can exceed traditional ARIMA and Kalman filters with Decision tree models, resulting in improved energy consumption due to fewer packet transmissions.
Additive Manufacturing (AM), commonly known as 3D printing, has revolutionized the field of biome... more Additive Manufacturing (AM), commonly known as 3D printing, has revolutionized the field of biomedical applications by offering innovative solutions for personalized and complex structures. This technology enables the fabrication of patient-specific implants, prosthetics, and tissues with enhanced precision and customization. The versatility of additive manufacturing allows the incorporation of biocompatible materials, fostering the development of implants tailored to individual anatomical requirements. Additionally, the rapid prototyping capabilities of 3D printing facilitate the creation of intricate models for surgical planning and education. The use of bioinks and biomaterials in additive manufacturing has paved the way for the fabrication of functional tissues and organs, advancing the prospects of regenerative medicine. Furthermore, the scalability and cost-effectiveness of 3D printing in the biomedical field hold significant promise for widespread adoption and accessibility. In conclusion, additive manufacturing stands as a transformative force in biomedical applications, offering unparalleled opportunities for personalized healthcare and advancing the frontiers of medical technology.
This project proposes a blockchain-based solution to enhance the regulation and supervision of me... more This project proposes a blockchain-based solution to enhance the regulation and supervision of medical waste disposal, addressing critical loopholes in current management practices. By introducing decentralized system architecture and smart contracts, the model ensures the authenticity and credibility of medical waste data throughout its lifecycle. Digital credentials are employed to protect operator information privacy, while blockchain technology facilitates information sharing and transfer among stakeholders. The integration of digital credentials for physical certificates enhances security and privacy protection. The model offers authoritative evidence for regulatory bodies, supporting the establishment of a new generation of medical waste regulatory information systems. Through insightful discussions and case studies, the practicability of blockchain in waste management is highlighted, paving the way for a more efficient and accountable approach to medical waste disposal.
Exposure to cold temperatures is, often, a neglected problem in ICUs, CT, AND MRI scans it may ca... more Exposure to cold temperatures is, often, a neglected problem in ICUs, CT, AND MRI scans it may cause several discomforts such as shivering, lung diseases, and artifacts in scan reports, etc., one of the leading influences of the overall sensation of cold discomfort is the cooling of the back. This study aimed to evaluate the effect of a heated ambulance mattress-prototype on body temperatures and thermal comfort in an experimental study. The endotherm patient warming mattress and ambulatory patient mattress are the preexisting projects. The Inditherm mattress is designed for use by all patients undergoing anesthesia who may be at risk of inadvertent pre-operative hypothermia, and for any patients who require warming in pre-operative, intra-operative, and postoperative settings the ambulatory mattress is generally a warming mattress. The main disadvantage is that these two technologies are not automated the operator has to set all parameters. In this project, we are designing a mattress that liberates heat depending on room temperature. The Lab VIEW controls on and off of the system it compares the room temperature with the present value and produces a suitable result. The main advantage is the project is fully automated and warms the patient only at the required time.
Rheumatoid arthritis (RA) is a chronic gender, genetics, and environmental exposures. Complicatio... more Rheumatoid arthritis (RA) is a chronic gender, genetics, and environmental exposures. Complications, such as joint damage, rheumatoid vasculitis, and Felty syndrome, underscore the need for effective management. Treatment mod Antirheumatic Drugs (DMARDs) to physical therapy and surgery, aim to alleviate symptoms and prevent further damage. While there is no cure for RA, ongoing research explores emerging therapies and precision medicine a multidisciplinary approach is crucial, tailoring treatment to individual needs for optimal outcomes and improved quality of life. Regular monitoring and adjustments to the treatment plan are essential aspects of RA management. Keywords: Rheuma Rheumatoid arthritis (RA) stands as a formidable challenge in the realm of autoimmune diseases, characterized by chronic inflammation that primarily targets the synovial joints [1 gender, genetics, and environmental factors such as cigarette smoking and exposure to air pollutants. The disease manifests variably in severity among patients, leading to a myriad of complications, including permanent joint damage necessitating arthroplasty, the dev splenectomy if left unaddressed.
Due to a widespread use of electronic goods and an increasing trend towards desk-bound work envir... more Due to a widespread use of electronic goods and an increasing trend towards desk-bound work environments, the prevalence of sedentary behaviors has reached alarming levels in the present rapidly evolving technological landscape. Poor posture, a common result of inactivity, has negative effects on your mental as well as physical wellness and overall quality of life. The third most prevalent reason why people go to the doctor on a worldwide scale is for back pain, which is often caused by poor posture. This paper explores the negative effects of sitting for long periods of time and slouching, and how important it is to maintain good posture for health and well-being in general.
This study presents an innovative IoT - based system for the real-time management of Parkinson's ... more This study presents an innovative IoT - based system for the real-time management of Parkinson's Disease using a combination of Flex Sensor, Node MCU, SCR Sensor, and ADXL335. The Flex Sensor captures hand tremors, the ADXL335 monitors overall motion, and the SCR Sensor measures physiological stress levels. These components collectively enable continuous monitoring of Parkinson's symptoms. The data is wireless transmitted to a centralized server for analysis, allowing healthcare providers to remotely assess patient conditions. Machine learning algorithms offer insights into disease progression and predict potential exacerbation. The system provides timely alerts, enhancing patient care and reducing healthcare costs. This research contributes to the evolving landscape of IoT applications in healthcare for neurodegenerative disorders.
Wireless Body Area Networks (WBANs) integrate diverse sensors like heart rate monitors, electroca... more Wireless Body Area Networks (WBANs) integrate diverse sensors like heart rate monitors, electrocardiograms, pulse oximeters, respiration rate sensors, gyroscopes, and skin conductance sensors into a network for pervasive healthcare delivery. This interconnected system enables real-time monitoring and data fusion, ensuring accurate and comprehensive health assessments. Efficient communication protocols, cloud integration, and power management enhance the reliability and longevity of wearable devices. Security measures and user-friendly interfaces prioritize the protection of sensitive health data and ease of access. Machine learning algorithms contribute to predictive analytics for early detection of health issues. WBANs offer a holistic approach to personalized healthcare, allowing for continuous and remote monitoring of physiological parameters. The seamless integration of these sensors establishes a foundation for timely intervention and improved patient outcomes.
This project aims to develop a system equipped with machine learning algorithm capable of continu... more This project aims to develop a system equipped with machine learning algorithm capable of continuously monitoring respiratory conduct. The system utilizes machine learning to interpret pulmonary function tests, lift the management of respiratory diseases, and potentially deliver improvements in the diagnosis and treatment of various disease states in pulmonary and critical care medicine. Additionally, the system automatically predicts lung function based on acoustic signals from coughing and wheezing, enabling noninvasive monitoring of asthma severity. The project also seeks to forecast lung age and improve the current dataset of audio samples to enhance the accuracy and reliability of the results. The application of machine learning in pulmonary function testing holds significant potential for remote monitoring of high risk patients and the early detection and treatment of lung diseases.
This IoT enhance user adherence and automate dispensing processes. Delivery System utilizing a bu... more This IoT enhance user adherence and automate dispensing processes. Delivery System utilizing a buzzer, RTC DS3231 module, LCD display, IR sensor, and G designed to enhance medication adherence and patient care. The Node MCU and Arduino facilitate seamless integration of components, while the RTC DS3231 module ensures precise timekeeping for medication schedules. An LCD display provides real dosage retrieval. Additionally, a buzzer provides audible alerts for medication reminders. The incorporation of GSM technology allows system aims to improve patient outcomes and simplify medication management.
This project presents a cost-effective IoT-based system designed for monitoring temperature, humi... more This project presents a cost-effective IoT-based system designed for monitoring temperature, humidity, and dust levels in food storage environments to mitigate the risk of food poisoning. Utilizing sensors and a microcontroller, real-time data is collected and transmitted to a cloud platform through a secure communication protocol. The cloud-based solution incorporates a backend server and a database for efficient data processing and storage. A user-friendly web or mobile interface enables stakeholders to monitor conditions, set custom thresholds, and receive timely alerts. The system's design emphasizes scalability, adaptability, and ease of deployment, making it suitable for various food storage facilities. Rigorous testing ensures the reliability and accuracy of the system, and its implementation is intended to enhance food safety practices. Ongoing maintenance and updates are incorporated to ensure the sustained effectiveness of the monitoring solution in preventing food borne illnesses.
This project introduces an IoT environments. Utilizing a variety of sensors, including those for ... more This project introduces an IoT environments. Utilizing a variety of sensors, including those for particulate matter, carbon dioxide, and volatile organic compounds, the system ensures continuous real communication, enabling the transmission of data to a central server or cloud platform. Hospital staff can remotely monitor air quality conditions, receiving threshold alerts in the event of pollutant system integrates a controlling mechanism, allowing for the activation of ventilation systems or air purifiers based on the collected data. Energy efficiency is prioritized through intelligent control of air qualit enables administrators to identify patterns and improve overall air quality management. The system seamlessly integrates with existing hospital infrastructure and is designed for scalability, ensuring adaptability to evo based solution offers a smart and automated approach to maintaining a healthy indoor environment in hospital settings.
Hypersomnia, a sleep disorder characterized by excessive daytime sleepiness and prolonged nocturn... more Hypersomnia, a sleep disorder characterized by excessive daytime sleepiness and prolonged nocturnal sleep, poses significant challenges to individuals' daily functioning. Afflicted individuals struggle to stay awake during waking hours despite extended periods of sleep, often experiencing difficulties waking up in the morning. Cognitive functions, including memory and concentration, may be impaired, leading to social and occupational hindrances. While short naps provide minimal relief, hypersomnia's impact on overall well-being necessitates timely diagnosis and intervention. Diagnosis involves a comprehensive assessment of medical history and, if required, polysomnography. Treatment strategies, ranging from lifestyle modifications to pharmacological interventions, aim to address the underlying causes, which may be primary or secondary to other medical conditions. Timely recognition and management of hypersomnia are crucial to mitigating its adverse effects on daily life and fostering improved sleep quality and daytime alertness.
Traditional cupping therapy (CT) has been around for a long time and is still used today to treat... more Traditional cupping therapy (CT) has been around for a long time and is still used today to treat many different kinds of medical issues. Still, researchers have yet to pin down exactly how (CT) works. Looking at CT through the lens of contemporary medicine, this review set out to determine how it might work and provide some explanations for its effects. A search was conducted using keywords in the English publications in PubMed, Cochrane Library, and Google Scholar. From the 223 articles that were found, 149 records were reviewed and 74 articles were deemed irrelevant and removed. Of the 75 full-text publications that were considered for this review, 64 were ultimately included. There are six competing explanations for the benefits of cupping therapy. Nitric Oxide theory may provide an explanation for the calming effects on muscles, alterations in local tissue structures, and improvements in blood circulation. The Activation of immune system theory may explain the hormonal changes and immunological effects. According to the "Blood Detoxification Theory" heavy metals and waste are eliminated while toxins are released. These theories can complement one another or even be used interchangeably to treat different diseases and ailments. It would appear that the many impacts of cupping cannot be adequately explained by a single theory. The aforementioned theories require further investigation to either confirm or disprove them, and future research should also aim to develop novel conceptualizations of CT.
In this era of digitization and automation, the life of human being is getting simpler because al... more In this era of digitization and automation, the life of human being is getting simpler because almost everything is automatic where the old manual systems is replaced with the automated system. There is anincrease in demand for the internet and most of the businesses are automated today. At the same time, people are also fully dependent on the internet for day-to-day activites. In this paper, we are proposing an automated tool which controls the operations of Home appliances such as light, cooler, water tank, motion sensor, T.V., smoke detector through the use of mobile phone. This system uses the hardware devices such as arduino, ethernet shield, relay board, PIR sensor, MQ2 sensor; temperature sensor.Internet of things (IOT) provides a platform that allows devices to connectand control remotely across a network infra structured. In this paper, we have proposed an automated system (HAS) using andruino that employee the integration of cloud networking, wireless communication to prov...
This paper aims to provide main advance in the delivering techniques which are adapting to learne... more This paper aims to provide main advance in the delivering techniques which are adapting to learner using multiagent system. Including models and the corresponding methods.It focuses on both datamining and e-learning. Multiagent system is a computer programming based system which is composed by multiple interacting computer programs.MAS can be used to solve the program that are complex or seems impossible for an indivisual program to solve.Multiagent system composed of various entities that have different information or diverging interest.In multiagent system agents are computer program that act on behalf of the users to solve a computer program.
There is no enough sound and solid scientific researches expounding the benefits of using automat... more There is no enough sound and solid scientific researches expounding the benefits of using automated scripts over manual testing (Samuel R. , 2014). The ones available out there are virtuously promotional trailers made for marketing drive (Udin, 2014). This dissertation is made to fill up this gap. To this end, a comparative analysis of the test results achieved from both automated and manual testing have been piloted. Complementary research inputs such as data collected thru questionnaire, interview and group discussion have also been analyzed and synthesized to back up the outcome. Unified Functional Tester (UFT) is used to build test artifacts and execute automated scripts. The conclusion exhibits that using computerized scripts might offer considerable returns in terms of acquiring enhanced efficiency and enriched accuracy over manually testing, provided that the test is labor intensive, time taking and reoccurring.
International Journal of Innovative Research in Information Security, 2020
For several years now, bank customers have become accustomed to Machines (ATM) to transfer money ... more For several years now, bank customers have become accustomed to Machines (ATM) to transfer money between accounts either within the same bank or to different banks. The ATM provides account balance information, enable customers to deposit and withdraw cash from their accounts and perform other transactions without physically meeting bank staff in banking hall for transactions. mobile banking has led to a significant increase in ATM fraud banks transactions and credit card issuers
2007 International Conference on Management Science and Engineering, 2007
Along with the omni-directional opening and mixing management of financial market, some challenge... more Along with the omni-directional opening and mixing management of financial market, some challenges face the banking supervision. The article probes into the problems with the commercial banking supervision in terms of relevant laws, internal control of commercial banks, authority supervision, and supplement supervision and proposes corresponding countermeasures. The author thinks we should establish perfect and organic supervision system, perfecting legal framework, strengthening internal control of commercial bank, functional supervision of bank-supervising authorities, and other external supervision. Such a commercial banking supervision system will ensure effective supervision, and means a lot to the development of banking.
Cloud computing environment is very much prone to intrusion attacks due to modern-days new attack... more Cloud computing environment is very much prone to intrusion attacks due to modern-days new attacks and hence security of cloud computing is very much required. People will move towards cloud services until and unless they are not having full reliance in its security. Although various measures are taken place from time to time but still various attacks like DDOS attacks are glaring. Hence Multiple Dynamic Thresholds based DDOS attack detection mechanism is proposed as statistical algorithms are more stable.
Data dissemination is the process by which queries of data are routed in the sensor network. The ... more Data dissemination is the process by which queries of data are routed in the sensor network. The data collection by sensor nodes has to be communicated to the base station or to any other node interested in the data. Data discovery and dissemination protocol for WSNs is responsible for updating configuration parameters of and distributing management commands, to, the sensor nodes. All existing data discovery and dissemination protocol suffer from two drawbacks. First, they are based on the centralized approach; in centralized approach only the base station can distribute data items, such an approach is not suitable for emergent multi-owner--multi-user wireless sensor networks. Second, those protocols were not designed with security in mind and hence adversaries can easily launch attacks to harm the network. This paper proposes the first secure and distributed data discovery and dissemination protocol called DiDrip. It allows the network owners to authorize multiple network users wit...
Cloud computing has become an integral part of most of the private and public organizations and b... more Cloud computing has become an integral part of most of the private and public organizations and being used for data storage and retrieval. There are many usage of cloud computing and widely used in highly confidential national services like military and treasury for storing confidential information. The cloud computing for example Google drive, Amazon Web Service and Microsoft Azure are beneficial for organizations and end-users. Using Cloud computing and its services, organisation/end-users can store their data. There are multiple challenges while saving organisations highly confidential documents in servers. Hence, the objective of this paper is to provide a high level design for a storage system maximising security and personal privacy. Though servers are highly protected against unauthorized access, there are incidents where confidential files stored on servers are accessed by the maintenance staffs. Hence this research paper provides introductory structure for fully protection ...
Vehicle ad-hoc networks has significantly used in automobiles for an effective communication with... more Vehicle ad-hoc networks has significantly used in automobiles for an effective communication with one another. The de-centralized nature of this network provides an extensive range of applications which makes passenger safety and comfort. Providing security in a physical environment is considered to be the main issue to cope with. Vehicle-to-vehicle communication is the wireless transmission of data between the vehicles. It is more efficient and it enables 360 degree awareness of the surrounding threats. To overcome this issue a popular approach is recommended in VANET, is that cars are connected together via V2V,which are able to share data with one another, so that there is, less possibility of collision and other mischievous behavior i.e. drunken drive. Although there are many proposed solutions for improving securities in VANET but security still remains a delicate research subject. The main objectives of this paper are to improve the security issues in VANET. KeywordsVehicle Ad...
World Wide Web plays an important role in providing various knowledge sources to the world, which... more World Wide Web plays an important role in providing various knowledge sources to the world, which helps many applications to provide quality service to the consumers. As the years go on the web is overloaded with lot of information and it becomes very hard to extract the relevant information from the web. This gives way to the evolution of the Big Data and the volume of the data keeps increasing rapidly day by day. Data mining techniques are used to find the hidden information from the big data. In this paper we focus on the review of Big Data, its data classification methods and the way it can be mined using various mining methods.
Glaucoma is a silent thief of sight which is characterized by elevated intraocular pressure, slow... more Glaucoma is a silent thief of sight which is characterized by elevated intraocular pressure, slow vision loss leads to permanent blindness. Although the disease is incurable but its symptoms can be minimized therefore early detection of the disease is essential. It is a very expensive process to detect the disease using the modern tools as a result of which we are developing a methodology for detection such that it is affordable by all the sections of the society, also it can be detected at the early stage and prevention can be taken. Hence, proposing a novel methodology for primary glaucoma detection by developing software algorithms in Matlab, which focuses on automated detection of glaucoma from fundus images using CDR calculation.
Malicious URLs are harmful to every aspect of computer users. Detecting of the malicious URL is v... more Malicious URLs are harmful to every aspect of computer users. Detecting of the malicious URL is very important. Currently, detection of malicious web pages techniques includes black-list and white-list methodology and machine learning classification algorithms are used. However, the black-list and white-list technology is useless if a particular URL is not in list. In this paper, we propose a multi-layer model for detecting malicious URL. The filter can directly determine the URL by training the threshold of each layer filter when it reaches the threshold. Otherwise, the filter leaves the URL to next layer. We also used an example to verify that the model can improve the accuracy of URL detection.
Wireless Sensor Network is a collection of large number of tiny sensor nodes which are connected ... more Wireless Sensor Network is a collection of large number of tiny sensor nodes which are connected to each other wirelessly having limited energy. These nodes are mobile in nature. These sensor nodes sense the same data and forward it to the sink node. In this way, sink node receives redundant data and more energy is consumed in processing this data. Data Aggregation plays a very crucial role in Wireless Sensor Networks. We will use data aggregation to reduce the energy consumption by removing redundancy. Thus, with the help of data aggregation, we can enhance the lifetime of the network. In this paper, we have proposed a hybrid data aggregation technique to remove redundancy. KeywordsWireless Sensor Network, Data aggregation, sensor nodes, transmission
Localization attacks, in which IP addresses located as sensors comprising Darknet systems are det... more Localization attacks, in which IP addresses located as sensors comprising Darknet systems are detected, are well-known. Attackers can detect sensors in secret by sending probing traffic with concealed signals to the target network. In response to this, we have developed countermeasures using a dynamic monitoring method, in which there is a dynamic switchover of sensors reflected in the published monitoring results. In this study, we will consider a case wherein the attacker is attempting to embed concealed signals between multiple ports within one sensor. Therefore, we propose a countermeasure method in which there is dynamic monitoring of each destination port. In this paper, we have verified the impact on publishable monitoring results when applying the proposed method to the nicter Darknet in Japan. Index Terms – Darknet ; internet security; port scan; localization attack; distributed system; risk management;
Information security policy is one of the most important security controls, and considered as the... more Information security policy is one of the most important security controls, and considered as the foundation of any security regime in an organization. In fact, failure to formulate an information security policy is said to be one of the deadly sins in information security management. It is also evident that many organizations face difficulty constructing this document, its content and structure in particular. In this vein, a number of developed policy frameworks or models in the formulation of information security policy have been proposed and published in academic journals. The purpose of this study, therefore, was to review the actual state of the literature for the last 15 years (2001-2015) focusing on information security policy frameworks and models. This paper has found that there is still limited number of frameworks and models available, supported by empirical surveys. Since the development and implementation of an information security policy involves social, political, eco...
Energy consumption is the critical issue to determine the lifetime of Wireless sensor networks (W... more Energy consumption is the critical issue to determine the lifetime of Wireless sensor networks (WSNs), due to limited batteries power resource of sensor nodes. The optimization of energy consumption is involves reduction of energy consumption in order to prolong the lifetime of the network as much as possible. However, to minimize the overall energy consumption of the sensor network, different types of routing protocols have been proposed. This paper proposes an energy efficient routing protocol using the A-star search algorithm to find the optimal path from the source node to the sink node. Simulation results with Matlab show that our proposed protocol is efficient in terms of total energy consumption and network lifetime compared with fuzzy approach.
<b><i>With online shopping spreading quickly, China ' s e-commerce market is rapi... more <b><i>With online shopping spreading quickly, China ' s e-commerce market is rapidly expanding; the e-commerce distribution bottlenecks gradual emerge. Logistics distribution has restricted the development of Taobao.It is proved that during the process of distributing activity, information processing and dispatching speed can be speeded up with computer, telecommunication and network technologies, so improving efficiency and competence greatly. Alibaba set up rookie network aimed at long-term growth. The necessary of setting up "Rookie network" as well as business models of"Rookie network" were detailed in this article. Last,the effects of Rookie Network on market was analyzed.</i></b>
<b><i>The Mass diffusion of digital media and the explosive growth of telecommunicati... more <b><i>The Mass diffusion of digital media and the explosive growth of telecommunication are reshaping the lifestyles of ordinary people, research and industry. Over the last decades, the rise of digital telecommunication technologies has fundamentally altered how people work, think, communicate, and socialize. Despite the obvious progress of multimedia communications, these developments carry with them a number of risks such as copyright violation, prohibited usage and distribution of digital media, secret communications, and network security. Therefore, security, scalability and manageability amongst other become issues of serious concern, as current solutions do not satisfy anymore the growing demands of multimedia communications. Security has been in a center stage of international attention since we first-handedly witnesses the pervasiveness of terrorism activities. Lately, more and more government and industry resources are located to the researches of security systems. How can we ensure the trustworthiness of multimedia data? How can analysts extract intelligence from enormous video streams? How can visual or audio biometric features help to identity suspects? This research work examines multimedia security, its impact on our society and the place of our law on it, adopting literature review methods. This paper examines the meaning of multimedia security, its usefulness to our society and the place of our law on it and some possible interventions</i></b>
<i>Image steganography is the art of hiding </i><i>a message, image, or file wi... more <i>Image steganography is the art of hiding </i><i>a message, image, or file within another message, image, or file. Likely, an old term in Ancient Greek, Steganography is derived from steganos meaning ―"concealed" and graphein meaning ―"writing", in other word we can say it refers to the science of "invisible" communication. Unlike cryptography, where the goal is to secure communications from an eavesdropper, steganography techniques strive to hide the very presence of the message itself froman observer. In this research paper we deal with hiding a digital message image inside a digital cover image leading us to the stego image. With the combination of Message Preparation using Spatial Domain image modification technique, discrete cosine transforms (DCT) and image scrambled using modified Arnold Transform, an algorithm based on the three technologies is proposed. The effectiveness of the proposed methods has been estimated by computing Mean square error (MSE) and Peak Signal to Noise Ratio (PSNR) and experimental result shows that the proposed algorithm is highly secured with good perceptual invisibility.</i>
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