International Journal on Recent and Innovation Trends in Computing and Communication
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Exploring Internet of Things and its Applications for Enhanced Living, Industry, and Environment
Get PDFThe Internet of Things has changed many facets of our life. This critical analysis evaluates IoT's varied applications and their effects on life, industry, and the environment. The study shows IoT's dynamic role in modern society, its limitations, and its possibilities. It begins with how IoT innovations are redefining better living. This transition is driven by smart homes, healthcare, and wearable tech, boosting convenience and well-being. We discuss IoT's quality-of-life improvements and future advances. It highlights IoT's tremendous applications to boost production. We have also discussed the issues and challenges faced in IoT. This research work gives insights of the IoT regarding its fundamental, Applications and Issues along with future direction for research
Comparative Metabolite Extraction Protocols from Breast Cancer Mouse Lung Tissue for LC-MS/MS Analysis
Get PDFTriple-negative breast cancer (TNBC) stands out for its heightened invasiveness, leading to distant metastasis in nearly 46% of cases, with common targets being the brain, lungs, and bones. This subtype is associated with significantly shorter median survival compared to other breast cancer types. Analyzing metabolic compounds in lung tissues affected by breast cancer metastasis provides valuable insights into biological information and regulatory processes. Despite the recognized severity of TNBC spreading to other sites, there are limited reported studies investigating metabolome information in distant organ tissues, particularly the lungs. Therefore, accurately quantifying the abundance of metabolites requires careful extraction procedures. This study aims to investigate and compare extraction protocols for lung tissue metabolites in TNBC mice using liquid chromatography with tandem mass spectrometry (LC-MS/MS). Left lung tissues were collected from mice xenografted with breast cancer. Three different extraction methods were evaluated to assess their metabolite coverage and biochemical compound classes. Our findings revealed distinct differences in metabolite compositions among the three methods. The extraction solvent comprising isopropanol, acetonitrile, and water in a 3:2:2 ratio proved most suitable for studying breast cancer metastasis to lung tissues. This extraction solvent could serve as a protocol for future studies analyzing the lung cancer metabolome in mice
The Effects of Cloud Computing and Internet of Things on the Next Generation Internet
Get PDFTwo separate yet crucial technologies that are influencing our lives more and more are cloud computing and IoT. It is anticipated that they will be widely adopted, making them essential elements of the Future Internet (FI). IoT improves our daily life by enabling connectivity and communication across several devices. However, flexible network access offered by cloud computing makes it possible to integrate dynamic data from several sources. Nonetheless, there are a number of difficulties in integrating IoT and cloud computing in the FI. Our goal in this research paper is to present and analyze the fundamental ideas behind cloud computing and the Internet of Thing
Fuzzy-based Augmentation of Federated Averaging for Enhanced Decentralized Machine Learning
Get PDFFederated Averaging (FedAvg) is a leading decentralized machine learning approach, prioritizing data privacy. However, it faces challenges like non-identically distributed data, communication bottlenecks, and adversarial attacks. This abstract introduces a fuzzy-based FedAvg, leveraging fuzzy logic to manage uncertainty in decentralized environments. Fuzzy clustering adapts the model to varied data distributions, addressing non-IID challenges. Fuzzy membership functions enhance aggregation by introducing an adaptive weighting scheme, improving convergence and accuracy. The fuzzy approach incorporates privacy-preserving mechanisms, ensuring secure aggregation with homomorphic encryption and differential privacy. Simulations show improved convergence, resilience to non-IID data, and enhanced privacy compared to traditional FedAvg, contributing to more secure decentralized ML systems
Intelligent Transportation Systems: Fusing Computer Vision and Sensor Networks for Traffic Management
Get PDFIntelligent Transportation Systems (ITS) represent a pivotal approach to addressing the complex challenges posed by modern-day urban mobility. By seamlessly integrating computer vision and sensor networks, ITS offer a comprehensive solution for traffic management, safety enhancement, and environmental sustainability. This paper delves into the synergistic fusion of computer vision and sensor networks within the framework of ITS, emphasizing their collective role in optimizing traffic flow, mitigating congestion, and enhancing overall road safety. Leveraging cutting-edge technologies such as machine learning, image processing, and Internet of Things (IoT), ITS harness real-time data acquisition and analytics capabilities to facilitate informed decision-making by transportation authorities. Through a comprehensive review of recent advancements, challenges, and opportunities, this paper illuminates the transformative potential of integrating computer vision and sensor networks in ITS. Furthermore, it presents compelling case studies and exemplary applications, showcasing the tangible benefits of this fusion across diverse traffic management scenarios. Ultimately, this paper advocates for the widespread adoption of integrated ITS solutions as a means to usher in a new era of smarter, safer, and more sustainable urban transportation systems
Image Reconstruction Using Wavelet Transforms and Curve Let Transform
Get PDFDigital signal processing relies heavily on linear transformations and expansions. Compression and denoising are two examples of signal processing applications where the wavelet transform has since proved useful. Instead of appropriately representing images with edges, the Wavelet Transform considers them as smooth functions with discontinuities along the curve. With the Curve let transform, frame components are indexed according to their scale, position, and orientation instead of the wavelet transform. They are scaled in line with an exclusive scalability rule, which specifies that a frame element's support's length is directly proportionate to its width squared. Image processing as well as communication technology like smartphones and tablets have been greatly influenced by it in recent year
Identifying Online Spam Using Artificial Intelligence
Get PDFPreventing spam is becoming increasingly crucial as online commerce and communication grow quickly because it helps to keep people secure and websites reliable. Finding and lowering internet spam increasingly depends critically on artificial intelligence (AI). This paper describes how artificial intelligence detects spam now by use of methods like machine learning, language interpretation, and pattern recognition. AI can combine unsupervised approaches to identify odd behavior with supervised learning using labeled data. Among the difficulties include spotting fresh spam compositions and keeping precise real-time detection. By means of improved spam detection capability of artificial intelligence, researchers want to increase online platform security and thereby influence people's internet use
Intrusion Detection and Prevention for Cloud Security
Get PDFThis paper consultation presents a technique for creating a layered taxonomy of Intrusion Location and Prevention Frameworks (IDPS). The strategy methodically classifies IDPSs based on their utility components, research strategies, layout plans, and mechanical systems. Through the introduction of a comprehensive written study, keynote and real cases, the scientific classification presents an organized system that improves the understanding and application of IDPS in various security situations, and especially emphasizes their contribution to cloud security. This study contributes to the advancement of IDPS classification, advertising experiences in and education research, and the thought of implementing cyber security methods
A Systematic Review on Latest Features of Neural Network Designs for Power Electronic Systems Using Impedance Modeling
Get PDFFor the purpose of this research, the advanced Neural Network (NN) development for the power electronic system’s is discussed with special emphasis on the impedance modeling. Power electronic systems are essential for all today’s electrical networks as a means of energy conversion and management. Recently, used to describe the impedance of these systems, NNs are capable of capturing various relationships between converters, inverters, and related components. That kind of modeling not only increases the system efficiency through the mastery of the energy conversion processes but also allows for controlling the processes that change in response to the changes in the other parameters, thus stabilizing the system’s performance. Also, NNs enable early fault diagnosis and prediction through the analysis of the impedance diagrams, which helps to increase the level of reliability in a system and avoid unnecessary faults. Thus, this paper is concluded by mentioning the current limitations encountered regarding the applicability of NN models for large-scale systems and discussing possible research directions that can enhance model performability, readability, and coexistence with the conventional control strategies for hybrid systems
Study and Design of Microcontroller-Based Automated Voltage Pulses Tester
Get PDFA voltage pulse test is essential for assessing the integrity of electronic components. Traditional methods tend to produce inaccuracies and labor-intensive results. In this paper, we present a low-cost, automated voltage pulse tester that can improve the accuracy and efficiency of its measurements. The system is composed of an Arduino microcontroller, a high-precision voltage sensor, and a user-interface that can be used to visualize and control the data. The automated tester was evaluated in several tests to confirm its performance. Different parameters, such as duration, amplitude, and repeatability, were analyzed to compare its measurements with those from an ordinary oscilloscope. The results indicated that the automated tester was able to provide high accuracy, with only deviations of less than 1%. Consistent repeatability tests were conducted on the automated tester, which indicated its reliability. Its response time of 50 milliseconds provided a satisfactory assurance that it can handle real-world applications. The results of the tests indicated that the automated tester, which is mainly composed of a microcontroller, is a reliable and robust tool for measuring voltage pulse signals. It offers significant advantages over traditional methods, such as ease of use and accuracy