
Networking
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This paper investigates the system performance of hybrid time-power switching based relaying (TPSR) energy harvesting enabled in the multisource half-duplex relaying network over the Rayleigh fading channel. The outage probability (OP) of the proposed system model with implementing maximal ratio combining (MRC) and selection combination (SC) technique at the receiver is presented and analyzed.
8p
viling
11-10-2024
5
1
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Electricity demand is increasing, transmission line development can not keep up with it. This puts the power system in a full load state which puts the power system operating near the boundary of stability. This paper applies deep neural networks to predict power system dynamic stability.
10p
viling
11-10-2024
2
1
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In this paper, we propose a wavelet type-2 fuzzy brain imitated controller (WT2FBIC) for nonlinear robotic systems. The suggested method combines a wavelet type-2 fuzzy system (WT2FS) and a brain imitated controller (BIC) to improve learning efficiency.
11p
viling
11-10-2024
1
1
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In this study, we explore the potential of graph neural networks (GNNs), in combination with transfer learning, for the prediction of molecular solubility, a crucial property in drug discovery and materials science. Our approach begins with the development of a GNN-based model to predict the dipole moment of molecules.
8p
viling
11-10-2024
1
1
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This paper presents a technique for integrating battery energy storage systems (BESS) into a distribution network with penetration of wind and solar power in order to improve the operation efficiency of distribution networks, exploit renewable energy capability, and reduce operation issues.
12p
viling
11-10-2024
5
1
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In this study, an RS-485 protocol for Arduino boards that operate in Master-Slave networks was developed. Network operations could be carried out independently on the main thread program, and devices in the network could react quickly to information received.
10p
viling
11-10-2024
2
1
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In this paper, we used Convolution neural network (CNN) that exploits the visual properties of the input data to obtain features from network traffic, thereby achieving good intrusion detection performance.
11p
viling
11-10-2024
3
1
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Trong nghiên cứu này, nhóm tác giả ứng dụng thuật toán FaceNet kết hợp với mạng nơ-ron tích chập đa nhiệm (Multi-task Cascaded Convolutional Networks – MTCNN) để phát hiện và xác định khuôn mặt trong hệ thống chấm công.
16p
viling
11-10-2024
3
1
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In this paper, author uses 8-bit fixed-point quantization to greatly reduce the memory space requirement of the feature maps and weights and the accuracy of LeNet-5 with MNIST dataset is only slightly reduced. In the hardware accelerator, author proposes a highly flexible CNN accelerator with reconfigurable layers.
14p
viling
11-10-2024
3
1
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Ultra-wideband (UWB) radars are getting much attention for maritime applications of smart and luxury ships in which UWB radar could be integrated into Bridge Navigational Watch & Alarm System - BNWAS. One of the interesting applications of UWB radar is vital signs measurement, which is a contactless method. UWB radar measures respiration and heartbeat rate by the motion of thorax for detecting and checking the state of people on the bridge.
5p
vifilm
11-10-2024
3
1
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This paper introduces the application of artificial intelligence to build a security control software system in local military units. This software system uses state-of-the-art convolutional neural networks (CNN SOTA) for facial recognition by testing two of the best facial recognition models currently available: the FaceNet model and the VGGFace model.
8p
vifilm
11-10-2024
6
1
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The process of neural stem cell (NSC) differentiation into neurons is crucial for the development of potential cell-centered treatments for central nervous system disorders. However, predicting, identifying, and anticipating this differentiation is complex. In this study, we propose the implementation of a convolutional neural network model for the predictable recognition of NSC fate, utilizing single-cell brightfield images.
7p
viengfa
28-10-2024
2
2
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In this paper, we propose an effective AMC using deep learning (DL) for flexible and adaptive OFDM-based optical networks. The proposed DL-based AMC is able to classify four typical modulation schemes such as binary phase-shift keying (BPSK), quadrature PSK (QPSK), 8-PSK, and 16- quadrature amplitude modulation (QAM) in dynamic network conditions.
6p
viengfa
28-10-2024
3
2
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This paper is structured as follows. The following section presents related work. Section 3 summarizes the characteristics of the two datasets utilized in the model and the system’s overall architecture for image-based disease diagnosis. Section 4 provides our experimental results that compare the performance metrics with other studies.
6p
viengfa
28-10-2024
3
2
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High quality of service (QoS) requirements in multi-priority wireless sensor networks pose new challenges to the Internet of Things (IoT). In a multi-event wireless sensor network (MWSN), nodes generate different types of data packets with different priority such as urgent (high priority) or normal (low priority), with different traffic proportion.
10p
viengfa
28-10-2024
3
2
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In this study, we propose the application of CycleGAN to generate T2 pulse sequence MRI images of the human brain from T2 Flair pulse sequence images of the same type and vice versa, thereby increasing the number of MRI images of various types.
8p
viengfa
28-10-2024
4
2
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This paper aims to address this limitation by introducing techniques for estimating trustworthiness from a community context. These techniques rely on similarity measures or operators within the framework of path algebra.
8p
viengfa
28-10-2024
3
2
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This study proposes to test a combination model between CNN network and XGBoost algorithm for weather image classification problem. The proposed model uses deep learning network, namely CNN for feature extraction, then feeds the features into the XGBoost classifier to recognize the images.
6p
viengfa
28-10-2024
1
1
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In this paper, we build a quadcopter for target tracking by integrating a embedded computer Raspberry Pi (RPI) with a Pixhawk flight controller. This article also proposes a lightweight Tracking algorithm that can be deployed on Raspberry Pi, this algorithm harnesses advanced image processing and computing capabilities to significantly enhance target tracking performance, thereby reducing the need for human intervention control in unmanned flights.
9p
viengfa
28-10-2024
4
3
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This study presents a novel neural network (NN) framework for developing force fields specific to graphene monolayers, utilizing data obtained from first-principles calculations. The authors analyze three primary force components, force magnitude and the cosines of two angles across different configurations of surrounding carbon atoms.
7p
viengfa
28-10-2024
5
2
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