International Journal on Recent and Innovation Trends in Computing and Communication
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A Categorical Approach to the Study of Non-Commutative Motives
Get PDFWe introduce a novel categorical framework for the study of non-commutative motives, drawing connections between derived categories of non-commutative spaces and classical motives in algebraic geometry. By leveraging advancements in ho-mological algebra and category theory, we develop tools to analyze and classify non-commutative algebraic structures through their associated motives. Our ap-proach provides new insights into the structure of non-commutative spaces and establishes a foundation for further exploration in both algebraic geometry and non-commutative geometry
Intrusion Detection and Irregularity Analysis in 5g Networks using Deep Learning
Get PDFThe proliferation of Internet of Things, or IoT, equipment and the introduction of 5G networks have resulted in an explosion of data that is both copious and highly interconnected. There is an immediate need for strong Intrusion Detection Systems (IDS) designed for IoT ecosystems since this highly linked environment poses serious security risks. In this research, we look at how 5G-enabled IoT environments might benefit from deep learning architectures for intrusion detection system development. It assesses the efficacy of four state-of-the-art models in particular: CNN-BiGRU, TCN + LSTM, CNN-Bidirectional LSTM with Attention and Hierarchical Recurrent Neuronal Networks (HRNN). To find out how well each model can spot irregularities and possible security breaches, we run a thorough comparison study, paying special attention to important performance measures like loss and accuracy. Training performance is best for the TCN + LSTM architecture (with a loss of only 0.03 out of all the models tested), while CNN-BiLSTM + Attention comes in second with 94.2% accuracy & a loss of only 0.06. These results greatly aid in the creation of smart, IDS frameworks powered by deep learning, which improve the robustness and safety of IoT networks in the age of 5G connectivity. Furthermore, the findings provide important information regarding the practical use of these mathematical models for protecting smart environments in the future
Fueling India's Future: Vegetable Oils and Advanced Engine Technologies
Get PDFIndia's energy security is threatened by the rapid depletion of conventional energy sources and increasing demand. The substantial expenditure on importing petroleum-based fuels not only strains the economy but also exposes it to global oil price volatility. Leveraging India's agricultural strengths, vegetable oils derived from oil seeds offer a promising alternative. However, these oils require modification to suit compression ignition (CI) engines through methods like blending, thermal cracking, or transesterification.Despite these efforts, vegetable oil fuels often perform poorly in conventional diesel engines, causing issues like gum formation, filter clogging, and higher emissions. These problems stem from the oils' inherent properties, such as high viscosity and lower volatility. A potential solution lies in utilizing vegetable oils in low heat rejection (LHR) engines, designed to operate at higher temperatures, reducing ignition delay and improving combustion.By incorporating ceramic-insulated components like thermal barrier coatings, LHR engines can enhance thermal efficiency, reduce energy losses, and eliminate complex cooling systems. This technology can significantly improve engine performance with vegetable oil fuels. By adopting LHR technology, India can reduce its dependence on imported fuels, promote sustainable energy solutions, and contribute to a cleaner environment
Design and Implementation of Pid-Based Intelligent Control on a Microcontroller Platform
Get PDFThis research details an experimental setup for applying PID (Proportional-Integral-Derivative) control and other intelligent control algorithms on a microcontroller platform. A high-performance microcontroller, a number of sensors (e.g., temperature, pressure, position, and acceleration), a number of actuators (e.g., motors, valves, and relays), and a number of communication interfaces (e.g., UART, SPI, and I2C) are all part of the setup that can support real-time control applications. Integral to the system's functionality is the microcontroller's ability to operate with appropriate programming environments and neural network-based control algorithms. The output of a system may be controlled using PID control by constantly reducing the error between the actual output and a desired setpoint. Each of the three parts that make up the control signal—proportional, integral, and derivative—contributes in its own special way to the dynamic response of the system. Findings from the experiments prove that the PID algorithm is capable of producing precise and steady control. To reduce oscillations, the control signal is adjusted by the proportional term according to the present error, by the integral term according to the sum of all errors, and by the derivative term according to the trend of future errors
SDAV 1.0: A Low-Cost sEMG Data Acquisition & Processing System For Rehabilitatio
Get PDFOver the last two decades, myoelectric signals have been widely used in fields including rehabilitation devices and human-machine interfaces. This study aimed to develop an algorithm for surface electromyography (sEMG) data acquisition utilizing low-cost hardware and validate its performance using English vowels as silent speech content. The sEMG data were collected from the three facial muscles of one healthy subject. The sEMG signals were pre-processed, and various time-domain and statistical features were extracted in real time. The raw data and features were then used to train and test three customized machine learning classifiers: k-nearest neighbor (KNN), support vector machine (SVM), and artificial neural network (ANN). All customized classifiers achieved almost equivalent accuracy rates of 0.83 ± 0.01 in recognizing the English vowels with an improvement of 27.27% (KNN), 3.75% (SVM), and 51.85% (ANN) utilizing the same low-cost data acquisition hardware. Our findings are substantially closers to the results of commercial hardware setups, which raise the possibility of potential usage of low-cost sEMG data acquisition systems with the proposed algorithm in place of commercial hardware setups for rehabilitation devices and other related sectors of human-machine interaction
Role of Digitalization in Election Voting Through Industry 4.0 Enabling Technologies
Get PDFThe election voting system is one of the essential pillars of democracy to elect the representative for ruling the country. In the election voting system, there are multiple areas such as detection of fake voters, illegal activities for fake voting, booth capturing, ballot monitoring, etc., in which Industry 4.0 can be adopted for the application of real-time monitoring, intelligent detection, enhancing security and transparency of voting and other data during the voting. According to previous research, there are no studies that have presented the significance of industry 4.0 technologies for improving the electronic voting system from a sustainability standpoint. To overcome the research gap, this study aims to present literature about Industry 4.0 technologies on the election voting system. We examined individual industry enabling technologies such as blockchain, artificial intelligence (AI), cloud computing, and the Internet of Things (IoT) that have the potential to strengthen the infrastructure of the election voting system. Based upon the analysis, the study has discussed and recommended suggestions for the future scope such as: IoT and cloud computing-based automatic systems for the detection of fake voters and updating voter attendance after the verification of the voter identity; AI-based illegal, and fake voting activities detection through vision node; blockchain-inspired system for the data integrity in between voter and election commission and robotic assistance system for guiding the voter and also for detecting disputes in the premises of election booth
Critical Analysis on Detection and Mitigation of Security Vulnerabilities in Virtualization Data Centers
Get PDFThere is an increasing demand for IT resources in growing business enterprises. Data center virtualization helps to meet this increasing demand by driving higher server utilization and utilizing un-used CPU cycles without causes much increase in new servers. Reduction in infrastructure complexities, Optimization of cost of IT system management, power and cooling are some of the additional benefits of virtualization. Virtualization also brings various security vulnerabilities. They are prone to attacks like hyperjacking, intrusion, data thefts, denial of service attacks on virtualized servers and web facing applications etc. This works identifies the security challenges in virtualization. A critical analysis on existing state of art works on detection and mitigation of various vulnerabilities is presented. The aim is to identify the open issues and propose prospective solutions in brief for these open issues
Analysis of Image Processing Strategies Dedicated to Underwater Scenarios
Get PDFUnderwater images undergo quality degradation issues of an image, like blur image, poor contrast, non-uniform illumination etc. Therefore, to process these degraded images, image processing come into existence. In this paper, two important image processing methods namely Image restoration and Image enhancement are compared. This paper also discusses the quality measures parameters of image processing which will be helpful to see clear images
Secure Digital Information Forward Using Highly Developed AES Techniques in Cloud Computing
Get PDFNowadays, in communications, the main criteria are ensuring the digital information and communication in the network. The normal two users' communication exchanges confidential data and files via the web. Secure data communication is the most crucial problem for message transmission networks. To resolve this problem, cryptography uses mathematical encryption and decryption data on adaptation by converting data from a key into an unreadable format. Cryptography provides a method for performing the transmission of confidential or secure communication. The proposed AES (Advanced Encryption Standard)-based Padding Key Encryption (PKE) algorithm encrypts the Data; it generates the secret key in an unreadable format. The receiver decrypts the data using the private key in a readable format. In the proposed PKE algorithm, the sender sends data into plain Text to cypher-text using a secret key to the authorized person; the unauthorized person cannot access the data through the Internet; only an authorized person can view the data through the private key. A method for identifying user groups was developed. Support vector machines (SVM) were used in user behaviour analysis to estimate probability densities so that each user could be predicted to launch applications and sessions independently. The results of the proposed simulation offer a high level of security for transmitting sensitive data or files to recipients compared to other previous methods and user behaviour analysis
Automatic System for Detecting Pathologies in the Respiratory System for the Care of Patients with Bronchial Asthma Visualized by Computerized Radiography
Get PDFCOVID-19 is a disease that directly affects the respiratory tract, being harmful in asthmatic patients because this condition causes a lack of oxygen, even to the extent that it requires external equipment to combat drowning. Likewise, it highlights the importance of maintaining a treatment or therapy correctly to prevent your disease from worsening or being exposed to other diseases, putting your health at risk. The diseases that asthmatic patients can acquire can result from pathologies, which have been growing over the years due to lack of equipment or efficient examinations that generate complete information about respiratory conditions about asthmatic patients, therefore, by developing an advanced system, the chances of detecting pathologies prematurely increase considerably, which is an essential tool today. According to the problem exposed, in this research an automatic system of detection of pathologies in the respiratory system was carried out for the care of the patient with bronchial asthma visualized by computerized radiography, so that any pathology can be detected by means of a premature diagnosis in the respiratory system and the doctor can perform a correct treatment on the asthmatic patient. Through the tests carried out by the system, its performance was accurate and efficient, being suitable to be implemented in various hospitals so that the doctor can treat the disease in time, since the system presented a 98.79% efficiency in the detection of pathologies