The target of this paper is to recommend a way for Automated classification Fish species. A high accuracy fish required greater understanding behavior in Ichthyology and by marine biologists. Maintaining ledger the number fishes per species marking endangered large small water bodies concerned institutions. Majority available methods focus on outside because underwater poses challenges such as background noises, distortion images, presence other image quality occlusion. This method uses...

Wireless sensor networks are the core of Internet Things and used in healthcare, locations, military, security. Threats to security wireless built on (IoT-WSNs) can come from a variety sources. This study proposes secure attack localization detection IoT-WSNs improve service delivery. The technique blockchain-based cascade encryption trust evaluation hierarchical design generate blockchain values before beacon nodes broadcast data base station. Simulation results reveal that cascading...

The study was conducted to develop a simulated heat stress model for sheep depicting natural environmental conditions and observe its impact on growth, reproductive performance, physiological adaptability, blood metabolites endocrine responses in Malpura ewes. experiment 16 adult ewes period of 35 days. animals were randomly divided into two groups eight each (GI – control, GII stress). exposed different temperature at hours the day i.e. 38°C 1000–1100 hours; 40°C 1100–1200 42°C 1200–1300...

The effective control and management of traffic at intersections is a challenging issue in the transportation system. Various signal systems have been developed to improve real-time flow junctions, but none them resulted smooth continuous for dealing with congestion road intersections. Notwithstanding, procedure synchronizing signals nearby complicated due numerous borders. In traditional systems, direction movement vehicles, variation automobile over time, accidents, passing emergency...

The identification and localization of malicious nodes in wireless sensor networks (WSNs) is a hot area research that can considerably extend the network's lifetime make it more valuable. We use sensors whose positions are known, or anchor nodes, to educated guesses about unknown nodes. Several methods have been developed for precise estimation unknowable So, during network setup process, finding suitable parameters node with requisite accuracy short amount time remains tough task. Due fact...

Security enhancement in wireless sensor networks (WSNs) is significant different applications. The advancement of routing attack localization a crucial security research scenario. Various attacks degrade the network performance by injecting malicious nodes into networks. Sybil are most prominent ones generating false similar to station node. This paper proposed detection and against multiple using based on an optimized multilayer perceptron artificial neural (MLPANN). scheme has two major...

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Energy consumption, secure connection of Sensor Nodes (SNs), and their performance analysis play a major role in Wireless Networks (WSNs) research. Increased case use various Internet Things (IoT) applications has led to the development complicated networks. To address threats security issues faced WSNs, novel combined feature selection method known as Fast Correlation-based Feature Selection (FCBFS) with XG-Boost been proposed for NSL-KDD intrusion detection benchmark dataset. It helps best...

A physiological signal-based Human-Computer Interaction (HCI) system provides a communication link between human emotional states and external devices. Accurately classifying these signals is vital for effective interaction, which requires extracting selecting the most discriminative features to differentiate various states. This paper introduces SMOTETomek-Correlated Interactive Reinforcement Learning (ST-CIRL) framework anxiety classification, leverages meta-descriptive statistics enhance...

The study was conducted to establish the impact of short term exposure different environmental temperature on adaptive capability Malpura ewes in terms changes blood biochemical and endocrine responses. experiment for 21 days 28 ewes, which were randomly divided into 4 groups 7 animals each (G1- control, G 2–23°C, 3–40°C, 4–42°C). exposed a week collection carried out day 0, 1, group. effect studied parameters. Haemoglobin (Hb), packed cell volume (PCV), plasma glucose, total cholesterol,...

Resistive Random Access Memory (RRAM) and Phase Change (PCM) devices have been popularly used as synapses in crossbar array based analog Neural Network (NN) circuit to achieve more energy time efficient data classification compared conventional computers. Here we demonstrate the advantages of recently proposed spin orbit torque driven Domain Wall (DW) device synapse RRAM PCM with respect on-chip learning (training hardware) such NN. Synaptic characteristic DW synapse, obtained by us from...

Visual sensor network design facilitates applications such as intelligent rooms, video surveillance, automatic multi-camera tracking, activity recognition etc. These require an efficient visual layout which provides a minimum level of image quality or resolution. This paper addresses the practical problem optimally placing multiple PTZ cameras to ensure maximum coverage user defined priority areas with optimum values parameters like pan, tilt, zoom and locations cameras. The proposed...

Fish Species classification is of great utility to marine biologists for the understanding underwater ecology and fish behavior as well keep a log endangered species, which assists in fisheries management. Traditional methods being either tedious or too computationally intensive lead requirement an automated method analysis counting. Generally, images challenging due difficulties camera calibrations, distortion, background noise, occlusion image quality name few. This paper proposes novel...

Automatically generating the summary of a video is challenging problem due to its subjective nature. Most previous works in field consider entire extract out important frames. Unlike them, our paper presents MerryGoRoundNet, supervised learning approach solve this an online fashion. We observe that effectively summarize video, one needs take into account both spatial and temporal relations between MerryGoRoundNet utilizes encoder-decoder style architecture convolutional LSTM establish...

This work aims to investigate the performance of Long Short-Term Memory (LSTM) Model for EEG-Based Emotion Recognition. For experimentation, we use publicly available DEAP dataset, which consists preprocessed EEG and physiological signals. Our limits itself study only signals have a scope developing an efficient headgear model real-time monitoring emotions. In this study, extract band power, frequency-domain feature, from compare classification accuracies Valence Arousal domain different...

This paper addresses the problem of EEG-based emotion recognition and classification investigates performance classifiers for subject-independent subject-dependent models separately. The results are compared with other also existing work in concerned domain as well. We perform experiments on publicly available DEAP dataset band power feature accuracies found pertaining to widely accepted Valence-Arousal Model. best were reported by LSTM model case 94.69% 93.13% valence arousal scales...

Optical properties of water distort the quality underwater images. Underwater images are characterized by poor contrast, color cast, noise and haze. These need to be pre-processed so as get some information. In this paper, a novel technique named Fusion Image Enhancement Restoration (FUIER) has been proposed which enhances well restores with target act on all major issues in images, i.e. cast removal, contrast enhancement dehazing. It generates two versions single input image these fused...