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253 articles for “data layer”
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The DVB-H Standard: Comparative Analysis of the Results Obtained for Various Modulation Techniques and Different Code Rates
Abstract: DVB-H happens to be the technical specification for the transmission of digital TV to mobile telephones and PDAs—handheld receivers. Published as a formal standard, DVB-H is a physical layer specification designed to facilitate the proficient delivery of IP-encapsulated data over terrestrial networks. The making of DVB-H, which is closely associated with DVB-T, also entailed modifications of some other DVB standards dealing with data broadcasting, service Information, etc. It can be …
Published in Recent Trends in Electronics Communication Systems Read article
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Energy Aware Routing and Congestion Control Algorithm in MANET Using Cross Layer Method
Abstract: AbstractIn a mobile ad hoc network, the mobility of a node is fickle. The mobility is well thought-out as distinctiveness of a wireless set of connections. In addition, the vigor frontier of the nodes must also be taken into selflessness of the when crafty routing protocols. This is a vital issue since energy utilization reduces the wireless set-up relationship lifetime. In mobile, link packets are time and again added momentous …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 4, Issue 1, 2017 · pp. 16–19 Read article
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Exploring Practical Applications of Artificial Neural Networks: A Review
Abstract: Computational models called artificial neural networks (ANNs) are modeled after the structure of the human brain. These models are designed to process information and learn from data. Artificial neural networks, or ANNs, are composed of interconnected artificial neurons layered to resemble the brain's neural network.. Through training, ANNs adjust the connections between neurons based on labeled data, enabling them to recognize patterns and perform specific tasks. Despite their efficacy in …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article
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Land Use/Land Cover Change Detection of Indira Sagar Canal Command Area Using Integrated Remote Sensing and GIS Tools
Abstract: In recent years, the significance of spatial data technologies, especially the application of remotely sensed data and geographical information systems (GIS), has been widely used. Land cover/land use is one of the influencing factors when it comes to catchment runoff. Hence, it is necessary to carefully consider both spectral and spatial characteristics of the sensor and accuracy of representative areas of predefined classes. The current study explores the change in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 2, Issue 2, 2013 · pp. 27–35 Read article
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Convolutional Neural Network and its Architectures
Abstract: Convolutional neural network (CNN) is a type of artificial neural network (ANN) with multiple layers. From the past decades, it has been considered as a powerful classification technique as it can handle a huge amount of imagery data. It can be applied in the field of image recognition. The name CNN has been derived from the mathematical linear operation known as convolution which is performed between two matrices. CNN has …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 2, 2021 · pp. 6–14 Read article
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Advancement in Image Classification: Media Player Control Using Hand Gestures
Abstract: We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Prediction of Process Parameters of Friction Stir Welding Using Artificial Neural Network
Abstract: In this paper an artificial neural network (ANN) approach is used to predict the process parameters of friction stir welding (FSW). Initially, the experiments are conducted using the design of experiment (DoE) approach on FSW using L27 orthogonal array. The experiments are conducted using speed, feed, and tool tilt angle as input parameters for DoE and tensile strength, hardness, and ductility as output. ANN is created having 25 neurons and …
Published in Journal of Polymer & Composites · Vol. 11, Issue 3, 2023 · pp. 13–25 Read article
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COVID-19 Detection using Convolutional Neural Network (CNN)
Abstract: Coronavirus disease (COVID-19) is spreading across the whole world and has habitual expressive community spread. The sudden hike in the number of patients with COVID-19, i.e. a new respiration virus has an extreme impact on the healthcare system. There are limited kits for diagnosis, hospital beds for such kind of patients, a limited number of personal protective equipment (PPE) for healthcare temporary staff and limited ventilators. A prediction system based …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 2, 2021 · pp. 22–30 Read article
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Reliable Data Transport in Platform-Based WSN
Abstract: Wireless Sensor networks (WSNs) are being used widely in the data to day life of human. Sensor network is a collection of tiny sensors connected through different Wireless medium. The main aim of sensor networks is to monitor and control of physical environments from remote locations with better accuracy. WSNs are having a wide range of applications areas such as military battle fields, environmental monitoring, health monitoring sensors in network …
Published in Recent Trends in Sensor Research & Technology · Vol. 1, Issue 1, 2014 · pp. 16–21 Read article
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A Study on AI-Driven Multi-Layered Defense in 6G Ecosystems
Abstract: The 6G networks bring about new degrees of possible functions related to connectivity, latency, data throughput, and integration with artificial intelligence (AI). This enables advances within healthcare, autonomous systems, and smart cities. The positive impact of rapid advancements must also be balanced with heightened risks due to the sheer volume of gaps that can be exploited, and the complex nature of the alignments and breaches. This results in the breaches …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Crypto Talk Voice Shield: Secure Speech Communication System Using Arduino
Abstract: In the rapidly evolving landscape of communication security, this study presents a system designed around Arduino Uno technology, specifically engineered for the secure encoding, transmission, and decoding of speech data. By integrating advanced encryption algorithms, the system ensures that speech data is transmitted in segmented bit chunks, each enveloped in multiple layers of security to prevent unauthorized access or interception. This multi-tiered encryption approach establishes a highly secure communication channel, …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 1, 2025 · pp. 23–30 Read article
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Change Detection of Land Use/Land Cover in Upper Ganga Canal Command, India, Using Arc-GIS Tools
Abstract: The rapid growth of urban population in India is a cause of concern among the country’s urban and town planners for efficient urban planning. The drastic growth of urban areas has resulted in sharp land use and land cover changes. In recent years, the significance of spatial data technologies, especially the application of remotely sensed data and geographical information system (GIS) has been widely used. The present study investigates the …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 3, 2013 · pp. 26–32 Read article
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Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 41–49 Read article
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Reconfigurable Industrial WSN in IoT Environment with Smart Sensor Interface Using FPGA
Abstract: IEEE1451 is set of standards developed by IEEE for connecting transducers to microprocessors, instrumentation systems, or control networks. These standards define TEDs for each transducer connected to system. TED stores transducer related information in memory like EEPROM. Wireless sensor network is network of distributed sensors that monitor environmental parameters and cooperatively pass data to main location through network. IEEE1451 defines standards for connecting actuators to processor in WSN. Internet of …
Published in Journal of Electronic Design Technology · Vol. 7, Issue 2, 2016 · pp. 16–23 Read article
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Comparison of Models of Machine Learning and Hyperparameter Optimization Methods on Various Datasets
Abstract: The most likely phase in achieving powerful and robust machine learning models is probably the hyperparameter tuning step. The traditional exhaustive methods of search (grid search and others) ensure that the search space is covered, but are computationally inexpensive; random search is less expensive and can still miss good regions; and lastly, the modern model-based and population-based methods (Bayesian optimization, tree-structured Parzen estimator (TPE), genetic algorithms) are thought to provide …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 · pp. 35–42 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Epilert: Epilepsy Tracker and Detector
Abstract: Epilepsy, affecting over 50 million individuals worldwide, necessitates innovative solutions for effective monitoring and intervention. Current systems face challenges such as inaccuracy, limited accessibility, and discomfort, leaving patients and caregivers vulnerable. Epilert, a wearable device, addresses these gaps by employing advanced sensors and machine-learning algorithms for real-time epilepsy detection and monitoring. The device integrates electromyography (EMG) and motion sensors to capture and analyze physiological and movement data. Preprocessing techniques ensure …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Timely Diabetes Possibility Prediction Using AI Techniques
Abstract: The fastest chronic life-threatening disease affecting more than 422 million people globally is diabetes. The primary causes of type 2 diabetes are lifestyle choices and environmental factors. It is a slowgrowing disease which starts to develop metabolic factors long before they evolve into a disease and is formally diagnosed by a fasting sugar test. There are records of indications related to diabetes from 520 patients in the dataset that was …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 37–47 Read article
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Improved Double Layer Encryption Algorithm of Secret Codes in Steganography
Abstract: Steganography is the way of hiding information to secure data for safer communication to take place. It is a process where the information is hidden in another format may be an image, voice, or video. Various other different file formats can be used, like JPG, JPEG, MP3, etc., but digital images are themost popular and considered the best ones because of the frequency they provide on the Internet to the …
Published in Journal of Web Engineering & Technology · Vol. 8, Issue 1, 2021 · pp. 19–24 Read article