This paper investigates the classification of low probability of intercept (LPI) radar signals by exploiting the intrinsic advantages of the Vision Transformer (ViT). Due to the characteristics of LPI radar signals, s...
This paper investigates the classification of low probability of intercept (LPI) radar signals by exploiting the intrinsic advantages of the Vision Transformer (ViT). Due to the characteristics of LPI radar signals, such as intrapulse modulation, wide frequency bands, and low transmission power, these signals are challenging to be detected and classified using traditional analytic methods. This has led to the adoption of various deep learning techniques to overcome these limitations. On the one hand, the ViT, originally developed for natural language processing, has demonstrated outstanding performance in computer vision by replacing the structure of the convolutional neural network (CNN) with the transformer, specifically leveraging self-attention. Therefore, this paper explores a method based on the ViT technique for classifying LPI signal images. The simulation results show that the proposed ViT method outperforms the traditional CNN method by 12.8% at −10dB SNR.
Malaria can be spread to human by anopheles female mosquitoes. There are four prevalent Plasmodium species responsible for malaria in humans. One of the four species, Plasmodium vivax or P. vivax, is selected in this ...
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ISBN:
(数字)9798350381559
ISBN:
(纸本)9798350381566
Malaria can be spread to human by anopheles female mosquitoes. There are four prevalent Plasmodium species responsible for malaria in humans. One of the four species, Plasmodium vivax or P. vivax, is selected in this paper. Its infected cell detection system based on image processing is developed. We automatically generate membership functions of inputs using the possibilistic fuzzy C-means. The Wang-Mendel (WM) method is used to automatically generate rules in the Mamdani fuzzy inference system. Although there are misclassifications because of the wrongly classified cells with similar characteristics to the opposite class, the correct classification rate of the training data is 93.65%. Whereas that of the blind test data set is 99.58%.
Position-based protocols in vehicular ad-hoc networks (VANETs) depend on the transmission of periodic beacon messages to keep the nodes informed about the current position of their neighbors. However, an excessive loa...
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Position-based protocols in vehicular ad-hoc networks (VANETs) depend on the transmission of periodic beacon messages to keep the nodes informed about the current position of their neighbors. However, an excessive load of beacons can drastically deteriorate the network performance. This work presents a novel adaptive vehicular traffic-aware strategy to compute the beacon interval in a position-based protocol. The strategy relies on three mobility factors: vehicular density, the mean difference of speed among neighbors, and the spatial distribution of neighbors. Its effectiveness is proven through extensive simulations in an urban mobility scenario using the packet delivery ratio, the average end-to-end delay, overhead, and processing time as the performance metrics. The results show that our approach maintains a high delivery ratio and low End-To-End delay, overhead, and processing time regardless of the density of the surrounding vehicular traffic. The results also show that our method uses the available beacon interval range more efficiently than another traffic-aware approach.
We propose a simple cut-set analysis based method that estimates the capacity bounds of optical networks. The method relies on investigating the wavelength utilization of the cut-sets that are likely to be heavily uti...
We propose a simple cut-set analysis based method that estimates the capacity bounds of optical networks. The method relies on investigating the wavelength utilization of the cut-sets that are likely to be heavily utilized, so it is simple and efficient. A novel cut-set load aware routing and wavelength assignment algorithm is then proposed. Numerical simulations elucidate that the performance of a conventional heuristics, k-shortest path first-fit, often used as a benchmarking alternative, is quite poor. Moreover, the further capacity improvement over the proposed method is limited to just 5-15%. Hence, even if we use a sophisticated algorithm for network design and control, the capacity improvement over best-performing heuristics approaches the capacity bounds.
Steel production worldwide continues to grow and, consequently, also the energy consumption of the steel sector. With the applications of the electric arc furnace route in the steelmaking process, the concern with asp...
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A membership inference attack (MIA) identifies if an instance was included in the victim model's train dataset. Without an appropriate defense mechanism, MIA can result in serious privacy breaches. Although severa...
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Developing a successful dialogue policy for a multi-domain task-oriented dialogue (MDTD) system is a challenging task. Basically, a desirable dialogue policy acts as the decision-making agent who understands the user&...
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We present a numerical simulation on the effect of leakage paths in the regrown GaN layer in the aperture and above the current blocking layer (CBL) of current aperture vertical electron transistor (CAVET) devices. He...
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We present a numerical simulation on the effect of leakage paths in the regrown GaN layer in the aperture and above the current blocking layer (CBL) of current aperture vertical electron transistor (CAVET) devices. Here, a 2D TCAD modeling is employed to simulate a CAVET device structure considering two main origins of parasitic leakage current from CBL/regrown-GaN interface and gate/regrown-GaN bulk and their degree of detrimental effect on the characteristics of AlGaN/GaN CAVETs.
We numerically and experimentally demonstrate a high-throughput and high-port-count OXC architecture based on space and wavelength-granular hybrid switching. Numerical simulations of several network topologies show th...
We numerically and experimentally demonstrate a high-throughput and high-port-count OXC architecture based on space and wavelength-granular hybrid switching. Numerical simulations of several network topologies show the good routing performance of our OXC. Its transmission performance is evaluated through an experiment using C- and L-bands. The net OXC throughput of 4.17 Pbps and the OXC port count of 128 are demonstrated.
A Facial Emotion Recognition (FER) system is an important tool to be implemented in any psychology academic field and beyond. This paper aims to show a system of Facial Emotion Recognition that can be done using the m...
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