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Data-driven Distributionally Adjustable Robust Chance-constrained DG Capacity Assessment

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 115-127页

作者： Masoume Mahmoodi Seyyed Mahdi Noori Rahim Abadi Ahmad Attarha Paul Scott Lachlan Blackhall the college of Engineering and computer Science The Australian National UniversityCanberraAustralia

Moving away from fossil fuels towards renewable sources requires system operators to determine the capacity of distribution systems to safely accommodate green and distributed generation(DG).However,the DG capacity of a distribution system is often underestimated due to either overly conservative electrical demand and DG output uncertainty modelling or neglecting the recourse capability of the available *** improve the accuracy of DG capacity assessment,this paper proposes a distributionally adjustable robust chance-constrained approach that utilises uncertainty information to reduce the conservativeness of conventional robust *** proposed approach also enables fast-acting devices such as inverters to adjust to the real-time realisation of uncertainty using the adjustable robust counterpart *** achieve a tractable formulation,we first define uncertain chance constraints through distributionally robust conditional value-at-risk(CVaR),which is then reformulated into convex quadratic *** subsequently solve the resulting large-scale,yet convex,model in a distributed fashion using the alternating direction method of multipliers(ADMM).Through numerical simulations,we demonstrate that the proposed approach outperforms the adjustable robust and conventional distributionally robust approaches by up to 15%and 40%,respectively,in terms of total installed DG capacity.

关键词： Distributed generation(DG)capacity assessment distributionally robust optimisation chance-constrained optimisation distribution system

Towards adaptive graph neural networks via solving prior-data conflicts

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Frontiers of Information Technology & Electronic Engineering 2024年第3期25卷 369-383页

作者： Xugang WU Huijun WU Ruibo WANG Xu ZHOU Kai LU college of computer National University of Defense TechnologyChangsha 410073China

Graph neural networks(GNNs)have achieved remarkable performance in a variety of graph-related *** evidence in the GNN community shows that such good performance can be attributed to the homophily prior;i.e.,connected nodes tend to have similar features and ***,in heterophilic settings where the features of connected nodes may vary significantly,GNN models exhibit notable performance *** this work,we formulate this problem as prior-data confict and propose a model called the mixture-prior graph neural network(MPGNN).First,to address the mismatch of homophily prior on heterophilic graphs,we introduce the non-informative prior,which makes no assumptions about the relationship between connected nodes and learns such relationship from the ***,to avoid performance degradation on homophilic graphs,we implement a soft switch to balance the effects of homophily prior and non-informative prior by learnable *** evaluate the performance of MPGNN on both synthetic and real-world *** show that MPGNN can effectively capture the relationship between connected nodes,while the soft switch helps select a suitable prior according to the graph *** these two designs,MPGNN outperforms state-of-the-art methods on heterophilic graphs without sacrificing performance on homophilic graphs.

关键词： Graph neural networks Heterophily Prior-data conflict

Learning accurate template matching with differentiable coarseto-fine correspondence refinement

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Computational Visual Media 2024年第2期10卷 309-330页

作者： Zhirui Gao Renjiao Yi Zheng Qin Yunfan Ye Chenyang Zhu Kai Xu college of computer National University of Defense TechnologyChangsha 410073China

Template matching is a fundamental task in computer vision and has been studied for *** plays an essential role in manufacturing industry for estimating the poses of different parts,facilitating downstream tasks such as robotic *** methods fail when the template and source images have different modalities,cluttered backgrounds,or weak *** also rarely consider geometric transformations via homographies,which commonly exist even for planar industrial *** tackle the challenges,we propose an accurate template matching method based on differentiable coarse-tofine correspondence *** use an edge-aware module to overcome the domain gap between the mask template and the grayscale image,allowing robust *** initial warp is estimated using coarse correspondences based on novel structure-aware information provided by *** initial alignment is passed to a refinement network using references and aligned images to obtain sub-pixel level correspondences which are used to give the final geometric *** evaluation shows that our method to be significantly better than state-of-the-art methods and baselines,providing good generalization ability and visually plausible results even on unseen real data.

关键词： template matching differentiable homography structure-awareness transformers

Service Migration Algorithm Based on Markov Decision Process with Multiple Service Types and Multiple System Factors

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Chinese Journal of Electronics 2024年

作者： Anhua MA Su PAN Weiwei ZHOU Broadband Wireless communication college Nanjing University of Posts and Telecommunications School of computer Science and Technology Nanjing Tech University

This paper proposes a Markov decision process based service migration algorithm to satisfy quality of service(Qo S) requirements when the terminals leave the original server. Services were divided into real-time services and non-real-time services, each type of them has different requirements on transmission bandwidth and latency,which were considered in the revenue function. Different values were assigned to the weight coefficients of QoS parameters for different service types in the revenue and cost functions so as to distinguish the differences between the two service types. The overall revenue was used for migration decisions, rather than fixed threshold or instant revenue. The Markov decision process was used to maximize the overall revenue of the system. Simulation results show that the proposed algorithm obtained more revenue compared with the existing works.

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Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

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computers, Materials & Continua 2024年第4期79卷 735-759页

作者： Wael M.S.Yafooz Abdullah Alsaeedi Department of computer Science College of Computer Science and EngineeringTaibah UniversityMedina42353Saudi Arabia

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user ***, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.

关键词： Mobile apps issues play store user comments deep learning LSTM bidirectional LSTM

The Effect of Key Nodes on theMalware Dynamics in the Industrial Control Network

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computers, Materials & Continua 2024年第4期79卷 329-349页

作者： Qiang Fu JunWang Changfu Si Jiawei Liu college of computer Science and Technology Shenyang University of Chemical TechnologyShenyang110142China college of computer Science and Engineering Northeastern UniversityShenyang110169China

As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of *** connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security *** paper proposes a model for the industrial control *** includes a malware containment strategy that integrates intrusion detection,quarantine,and ***,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment *** addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction ***,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is *** otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control *** earlier the immunization of key nodes,the *** the time exceeds the threshold,immunizing key nodes is almost *** analysis provides a better way to contain the malware in the industrial control network.

关键词： Key nodes dynamic model industrial control network simulation

Localization for mixed near-field and far-field sources under impulsive noise

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Journal of Systems Engineering and Electronics 2024年第2期35卷 302-315页

作者： GAO Hongyuan ZHANG Yuze DU Ya’nan CHENG Jianhua CHEN Menghan college of Information and communication Engineering Harbin Engineering UniversityHarbin 150001China college of Intelligent Systems Science and Engineering Harbin Engineering UniversityHarbin 150001China

In order to solve the problem that the performance of traditional localization methods for mixed near-field sources(NFSs)and far-field sources(FFSs)degrades under impulsive noise,a robust and novel localization method is *** eliminating the impacts of impulsive noise by the weighted out-lier filter,the direction of arrivals(DOAs)of FFSs can be estimated by multiple signal classification(MUSIC)spectral peaks *** on the DOAs information of FFSs,the separation of mixed sources can be ***,the estimation of localizing parameters of NFSs can avoid two-dimension spectral peaks search by decomposing steering *** Cramer-Rao bounds(CRB)for the unbiased estimations of DOA and range under impulsive noise have been *** experiments verify that the proposed method has advantages in probability of successful estimation(PSE)and root mean square error(RMSE)compared with existing localization *** can be concluded that the proposed method is effective and reliable in the environment with low generalized signal to noise ratio(GSNR),few snapshots,and strong impulse.

关键词： source localization far-field source(NFS) near-field source(FFS) impulsive noise Cramer-Rao bound(CRB)

Ballistic target recognition based on multiple data representations and deep-learning algorithms

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Chinese Journal of Aeronautics 2024年第6期37卷 167-181页

作者： Lixun HAN Cunqian FENG Xiaowei HU Sisan HE Xuguang XU Air and Missile Defense college Air Force Engineering UniversityXi’an 710051China college of Information and communication National University of Defense TechnologyWuhan 430010China

Target recognition is a significant part of a Ballistic Missile Defense System(BMDS).However,most existing ballistic target recognition methods overlook the impact of data representation on recognition *** paper focuses on systematically investigating the influences of three novel data representations in the Range-Doppler(RD)***,the Radar Cross Section(RCS)and micro-Doppler(m-D)characteristics of a cone-shaped ballistic target are ***,three different data representations are proposed:RD data,RD sequence tensor data,and RD trajectory *** accommodate various data inputs,deep-learning models are designed,including a two-Dimensional Residual Dense Network(2D RDN),a three-Dimensional Residual Dense Network-Gated Recurrent Unit(3D RDN-GRU),and a Dynamic Trajectory Recognition Network(DTRN).Finally,an Electromagnetic(EM)computation dataset is collected to verify the performances of the networks.A broad range of experimental results demonstrates the effectiveness of the proposed ***,several key parameters of the proposed networks and datasets are extensively studied in this research.

关键词： Ballistic target Micro-Doppler Deep learning Range-Doppler Radar target recognition

Two-layer Lagrange-based relay network topology and trajectory design for solar system explorations

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Science China(Information Sciences) 2024年第6期67卷 342-358页

作者： Jun CAO Jian JIAO Hao LIU Rongxing LU Qinyu ZHANG Guangdong Provincial Key Laboratory of Aerospace communication and Networking Technology Harbin Institute of Technology (Shenzhen) Faculty of computer Science (FCS) University of New Brunswick

Exploration targeting outer planets and even the edge of the solar system is an emerging direction for the deep-space exploration in the next decades. To address this challenge, a novel two-layer Lagrangebased relay network topology is proposed in this study. Specifically, we utilize the Sun-Mars and Sun-Saturn Lagrange points(LPs) L4 and L5 to build a two-layer backbone relay network, which ensures continuous and high-efficiency communication capability for the exploration of the solar system. Furthermore, we utilize the planetary gravity assist and design the transfer trajectory of backbone relays with the help of planetary celestial body motion equations and Kepler's laws. Moreover, we conduct link budget analysis for multihop relay transmission under Gamma-Gamma distribution, shadowed Rician fading, and additive white Gaussian noise channels in several typical exploration scenarios and validate that the LP relays can effectively support future deep-space exploration missions.

关键词： deep-space communication Lagrangian points backbone relay network transfer trajectory relay selection

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