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32nd Mediterranean Conference on Control and Automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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Discovering API Directives from API Specifications with Text Classification

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Journal of computer Science & technology 2021年第4期36卷 922-943页

作者： Jing-Xuan Zhang Chuan-Qi Tao Zhi-Qiu Huang Xin Chen College of Compute Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 210016China Key Laboratory of Safety-Critical Software(Nanjing University of Aeronautics and Astronautics) Ministry of Industry and Information TechnologyNanjing 210016China Key Laboratory of Complex Systems Modeling and Simulation(Hangzhou Dianzi University) Ministry of Education Hangzhou 310018China School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou 310018China

Application programming interface(API)libraries are extensively used by *** correctly program with APIs and avoid bugs,developers shall pay attention to API directives,which illustrate the constraints of ***,API directives usually have diverse morphologies,making it time-consuming and error-prone for developers to discover all the relevant API *** this paper,we propose an approach leveraging text classification to discover API directives from API ***,given a set of training sentences in API specifications,our approach first characterizes each sentence by three groups of ***,to deal with the unequal distribution between API directives and non-directives,our approach employs an under-sampling strategy to split the imbalanced training set into several subsets and trains several *** a new sentence in an API specification,our approach synthesizes the trained classifiers to predict whether it is an API *** have evaluated our approach over a publicly available annotated API directive *** experimental results reveal that our approach achieves an F-measure value of up to 82.08%.In addition,our approach statistically outperforms the state-of-the-art approach by up to 29.67%in terms of F-measure.

关键词： Application programming interface(API)directive API specification imbalanced learning text classification

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An Anomaly Detection Method Based on Adaptive Log and Dual Feature Fusion Analysis for Distributed Systems

An Anomaly Detection Method Based on Adaptive Log and Dual F...

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Information Systems and Computing technology (ISCTech), International Conference on

作者： Yijiang Jia Kefei Li Ping Lu Baodi Xie Huayang Wang Jincai Chen School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China National Key Laboratory of Modeling and Simulation for Complex Systems Beijing China

In this study, we present a middleware-based approach for detecting anomalies in distributed systems. Our method facilitates the dynamic collection of logs at various levels of detail and incorporates an a priori dictionary-based compression strategy to process and transmit logs, minimizing the performance impact on distributed systems. Additionally, we utilize a dual feature fusion technique to analyze the logs. We evaluate the effectiveness of our approach by performing anomaly detection in a publish/subscribe distributed system and comparing it with existing methods. The results illustrate that our method outperforms other approaches, demonstrating superior performance.

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CW-YOLO: joint learning for mask wearing detection in low-light conditions

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Frontiers of computer Science 2023年第6期17卷 191-193页

作者： Mingqiang GUO Hongting SHENG Zhizheng ZHANG Ying HUANG Xueye CHEN Cunjin WANG Jiaming ZHANG School of Computer Science China University of GeosciencesWuhan 430074China National Engineering Research Center of Geographic Information System Wuhan 430074China Wuhan Zondy Cyber Technology Co.Ltd. Wuhan 430074China Shenzhen Data Management Center of Planning and Natural Resources Shenzhen 518000China Key Laboratory of Urban Land Resources Monitoring and Simulation(Ministry of Natural Resources) Shenzhen 518000China College of Engineering Boston UniversityBoston 02215USA

1 Introduction With the rapid progress of Artificial Intelligence(AI)technology in object detection and face recognition,deep learning methods for face mask wearing detection have become increasingly mature and continuously take into account the needs of efficiency and ***,these conventional detection methods mostly ignore the complexity of real-world application scenarios,such as extremely darkness and gloomy *** unfavorable conditions lead to a series of image degradations that seriously hamper machine vision *** camera parameter adjustment,auxiliary lighting,or pre-processing enhancement[1]can weaken these negative effects to some extent to promote the detection,they will also result in increased hardware and time costs.

关键词： hardware lighting weather

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Electrical resistivity-temperature characteristics enhancement of insulating cross-linked polyethylene composites by incorporating positive temperature coefficient particles with different Curie temperatures

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High Voltage 2023年第1期8卷 1-11页

作者： Guimin Jiang Yuanxiang Zhou Chenyuan Teng Yunxiao Zhang Xin Huang Lei Xue Luming Zhou The Wind Solar Storage Division of State Key Laboratory of Control and Simulation of Power System and Generation Equipment Xinjiang UniversityUrumqiChina State Key Laboratory of Power System and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijingChina College of Information Engineering Zhejiang University of TechnologyHangzhouChina School of Electronics and Computer Science University of SouthamptonSouthamptonUK

Incorporating positive temperature coefficient(PTC)ceramic particles into polymers provides a prospective alternative solution for suppressing severe electric field distortions caused by negative temperature coefficient(NTC)of electrical resistivity within polymer insulation in high voltage direct current *** effect of the Curie temperature of PTC particles on the inhibition of the NTC effect of cross-linked polyethylene(XLPE)is investigated in this *** temperature coefficient particles with varied Curie temperatures are surface-modified and melt blending with *** modified particles are dispersed on averagely in the *** electrical resistivity,space charge behaviour,and direct current(DC)electrical breakdown strength of the samples are investigated at different temperatures,exploring the effect of the Curie temperature of PTC particles on suppressing the NTC effect of *** is demonstrated that the reduction in Curie temperature can further suppress the NTC effect of XLPE,enhance the DC strength at elevated temperatures,and inhibit the internal space charge *** reduction in the Curie temperatures means that the initiation of the PTC effect advances,exhibiting a higher potential barrier and inhibiting the NTC effect more *** work may give a reference for improving the temperature stability of DC properties for XLPE cable insulation.

关键词： coefficient resistivity insulation

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Impact of intensity variability of the Asian summer monsoon anticyclone on the chemical distribution in the upper troposphere and lower stratosphere

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Atmospheric and Oceanic Science Letters 2022年第3期15卷 25-30页

作者： Kecheng Peng Jiali Luo Jiayi Mu Xiaoqun Cao Hongying Tian Lin Shang Yanan Guo College of Meteorology and Oceanography National University of Defense TechnologyChangshaChina Key Laboratory of Semi-Arid Climate Change and College of Atmospheric Sciences Lanzhou UniversityLanzhouChina College of Computer National University of Defense TechnologyChangshaChina Shandong Provincial Climate Center JinanChina Trainer Simulation Training Center of Naval Aeronautical University HuludaoChina

During the Asian summer monsoon(ASM)season,the process of stratosphere-troposphere exchange significantly affects the concentration and spatial distribution of chemical constituents in the upper troposphere and lower stratosphere(UTLS).However,the effect of the intensity of the Asian summer monsoon anticyclone(ASMA)on the horizontal distribution of chemical species within and around the ASMA,especially on the daily time scale,remains ***,the authors use the MERRA-2 reanalysis dataset and Aura Microwave Limb Sounder observations to study the impact of ASMA intensity on chemical distributions at 100 hPa during the ASM *** intraseasonal variation of ASMA is classified into a strong period(SP)and weak period(WP),which refer to the periods when the intensity of ASMA remains strong and weak,*** relatively low ozone(O_(3))region is found to be larger at 100 hPa during SPs,while its mixing ratio is lower than during WPs in *** June,analysis shows that the O_(3) horizontal distribution is mainly related to the intensity of AMSA,especially during SPs in June,while deep convections also impact the O_(3) horizontal distribution in July and *** results indicate that the intraseasonal variation of the ASMA intensity coupled to deep convection can significantly affect the chemical distribution in the UTLS region during the ASM season.

关键词： Asian summer monsoon anticyclone Intensity index Chemical distribution Deep convection

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Coherent and incoherent laser pump on a five-level atom in a strongly coupled cavity-QED system

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Physical Review A 2022年第1期105卷 013701-013701页

作者： Asha Devi Sarath D. Gunapala Malin Premaratne Advanced Computing and Simulation Laboratory Department of Electrical and Computer Systems Engineering Monash University Clayton Victoria 3800 Australia Jet Propulsion Laboratory California Institute of Technology Pasadena California 91109 USA

We propose a cavity quantum electrodynamic system consisting of a five-level atom coupled to a single mode of the cavity electromagnetic field. The study is focused on the regime of strong coupling between the cavity and atom. Pump laser fields and cavity fields connect the split energy levels of the atom. Instead of the well-known two-level Dicke model obtained by adiabatic elimination of the high-energy levels, we consider the pump lasers' detunings to the atomic transitions to be very small such that we can examine the influence of the higher-energy states. We have studied the effect of an external coherent drive and incoherent pumping on these higher-energy levels and observed the enhancement of intracavity photon numbers due to quantum coherence effects. The amplification of intracavity photons is achieved even without a population inversion. However, the effect of the coherent and incoherent drive is negligible for very large detunings when the higher-energy states are adiabatically eliminated. At zero and small detunings, the system reaches the steady state at an earlier instant of time for higher incoherent pumping. We find an almost agreeable steady-state behavior of the system's exact full quantum dynamics model and its semiclassical approximation. Our model tries to accurately simulate the open system by considering the cavity decay, spontaneous decay, and dephasing of the system.

关键词： Atoms, ions, & molecules in cavities Cavity quantum electrodynamics Nanophotonics

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A real-time, robust and versatile visual-SLAM framework based on deep learning networks

arXiv

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arXiv 2024年

作者： Zhang, Xiao Dong, Hongbin Zhang, Haoxin Zhu, Xiaozhou Li, Shuaixin Deng, Baosong Harbin Engineering University College Of Computer Science And Technology National Engineering Laboratory for E-Government Modeling and Simulation China Intelligent Game and Decision Laboratory Chinese Academy of Military Science Beijing China Sun Yat-sen University China

In this letter, we investigate the paradigm of deep learning techniques to enhance the performance of visual-based SLAM systems, particularly in challenging environments. By leveraging deep feature extraction and matching methods, we propose a robust, versatile hybrid visual SLAM framework, Rover-SLAM, aimed at improving adaptability in adverse conditions, such as dynamic lighting conditions, areas with weak textures, and significant camera jitter. Building on excellent learning-based algorithms of recent years, we designed from scratch a novel system that uses the same feature extraction and matching approaches for all SLAM tasks. Our system supports multiple modes, including monocular, stereo, monocular-inertial, and stereo-inertial configurations, offering flexibility to address diverse real-world scenarios. Through comprehensive experiments conducted on publicly available datasets and self-collected data, we demonstrate the superior performance of our Rover-SLAM system compared to the SOTA approaches. We also conducted an in-depth analysis of the integration of visual SLAM with deep learning methods quantitatively to provide insights for future research endeavors in this domain. The experimental results showcase the system’s capability of achieving higher localization accuracy and robust tracking performance. To facilitate further research and foster community collaboration, we have made the source code of our system publicly available at https://***/zzzzxxxx111/SLslam. Copyright © 2024, The Authors. All rights reserved.

关键词： Textures

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Method for constructing multi-dimensional feature map of malicious code 5

Method for constructing multi-dimensional feature map of mal...

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2020 5th International Seminar on computer technology, Mechanical and Electrical Engineering, ISCME 2020

作者： Ma, Haocong Zhang, Ji Zhou, Junhua Zhai, Xiang Xue, Junjie Ji, Hang State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing100854 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing100854 China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing100854 China

Malicious code is characterized by a large number of types, rapid increase in number, continuous update of transmission routes, and continuous enhancement of back analysis and back detection methods. Therefore, how to effectively detect and analyze malicious code has been a problem of great concern. This paper studies the features of binary file and disassembly file of malicious code, introduces the concept of information gain, and proposes a method to construct the multi-dimensional characteristic graph of malicious code. Finally, the convolutional neural network is used to classify the multi-dimensional feature graph of malicious code, which provides a new idea for the feature extraction of malicious code. © Published under licence by IOP Publishing Ltd.

关键词： Malware

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Detection of Detonators in Baggage Using Deep CNN Architecture: A Comparative Study of Contrast Enhancement and Feature Extraction Methods

Detection of Detonators in Baggage Using Deep CNN Architectu...

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International Conference on Image and Signal Processing and their Applications (ISPA)

作者： Oulhissane Lynda Merah Mostefa Simona Moldovanu Luminita Moraru Laboratory of Signals and Systems LSS Faculty of Science and Technology Abdelhamid Ibn Badis University Mostaganem Algeria MSlab Department of Computer Science and Information Technology Modelling & Simulation Laboratory Faculty of Automation Computers Electrical Engineering and Electronics Dunarea de Jos University of Galati Galati Romania MSlab Department of Chemistry Physics & Environment Modelling & Simulation Laboratory Faculty of Sciences and Environment Dunarea de Jos University of Galati Galati Romania

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

Visual inspection of dual-energy X-ray radiographic images of cabin baggage requires high performance, but is hindered by various challenges such as low target prevalence, variability in target visibility, possible presence of multiple targets, and security personnel fatigue and inattention. Artificial intelligence (AI) techniques, particularly deep convolutional neural networks (CNNs), have shown promise in improving the automatic detection of explosives, even with low-resolution radiographic images, especially in high baggage throughput scenarios. In this paper, we focus on the detection of detonators as components of improvised explosive devices. The proposed approach involves comparing two experiments implemented in a deep CNN architecture using TensorFlow and Keras libraries. In the first experiment, raw dual-energy radiographic images without any enhancement were used. The second experiment includes three methods for contrast enhancement and feature extraction: the Contrast Limited Adaptive Histogram Equalization (CLAHE) method, the wavelet transform-based method, and the mixed CLAHE RGB-Wavelet method. In the latter two methods, Haar, Db2, Coif2, and Sym2 mother wavelet functions at two levels (HH and HL) were employed. The analysis of results focuses on a comparative study of performance measures such as accuracy, precision, recall, and F1 score. It was found that the preprocessing methods used in experiment 2, for the two evaluated classes (detonator and no detonator), achieved higher accuracy compared to the raw radiographic images used in experiment 1 (98.08%). The highest accuracies in experiment 2, with a value of 100%, were obtained with the CLAHE method (green channel in grayscale, blue channel in grayscale, and RGB channels) and the wavelet transform method with Haar mother wavelet at two levels HL

关键词： Wavelet transforms Radiography Visualization Gray-scale Inspection Feature extraction Libraries

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