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DeepGCN based on variable multi‐graph and multimodal data for ASD diagnosis

CAAI Transactions on Intelligence technology 2024年第4期9卷 879-893页

作者： Shuaiqi Liu Siqi Wang Chaolei Sun Bing Li Shuihua Wang Fei Li College of Electronic and Information Engineering Hebei UniversityBaodingChina Machine Vision Technology Innovation Center of Hebei Province BaodingChina The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science and Technology Henan Polytechnic UniversityJiaozuoChina

Diagnosing individuals with autism spectrum disorder(ASD)accurately faces great chal-lenges in clinical practice,primarily due to the data's high heterogeneity and limited sample *** tackle this issue,the authors constructed a deep graph convolutional network(GCN)based on variable multi‐graph and multimodal data(VMM‐DGCN)for ASD ***,the functional connectivity matrix was constructed to extract primary ***,the authors constructed a variable multi‐graph construction strategy to capture the multi‐scale feature representations of each subject by utilising convolutional filters with varying kernel ***,the authors brought the non‐imaging in-formation into the feature representation at each scale and constructed multiple population graphs based on multimodal data by fully considering the correlation between *** extracting the deeper features of population graphs using the deep GCN(DeepGCN),the authors fused the node features of multiple subgraphs to perform node classification tasks for typical control and ASD *** proposed algorithm was evaluated on the Autism Brain Imaging Data Exchange I(ABIDE I)dataset,achieving an accuracy of 91.62%and an area under the curve value of 95.74%.These results demon-strated its outstanding performance compared to other ASD diagnostic algorithms.

关键词： machine learning medical image processing medical signal processing

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Ant Colony Optimization with Simulated Annealing Algorithm for Google Maps 9

Ant Colony Optimization with Simulated Annealing Algorithm f...

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9th International Conference on Advanced Computing and Communication systems, ICACCS 2023

作者： Revanna, Jai Keerthy Chowlur Al-Nakash, Nushwan Yousif Baithoon Harrisburg University of Science and Technology Information Systems Engineering and Manangment Harrisburg United States

ISBN: (纸本)9798350397376

In the article that is being suggested, a brandnew, sophisticated route optimization is created using cuttingedge software that makes use of Google APIs and unsupervised machine learning. Since Google Maps and its API have improved recently, outmoded solutions have been decommissioned. Therefore, route optimization is carried out in this study using a heuristic method by merging three approaches, including ant colony optimization (ACO), simulated annealing algorithm (SA), and updated Google APIs. Along with executing route optimization, these three techniques-based ACO-SA-Google Maps (ASG) API will be contrasted with other approaches including genetic algorithms, K-means clustering, particle swarm optimization (PSO), etc. to assess performance, cost, and carbon emissions. The demand for home delivery, travel, and other necessities is increasing as a result of population increase and a developing technology lifestyle, necessitating the use of contemporary equipment by the average person. To increase performance, the ASG technique will develop route optimization using a modernized methodology. Route optimization eventually aims to be used in a variety of contexts, from uber applications to Amazon deliveries. Variation coefficient and relative percentage difference are two types of statistical indicators that are employed in the process of studying and verifying this model. To display and contrast the findings, the execution times in seconds are also considered. © 2023 IEEE.

关键词： Ant colony optimization

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Revolutionizing Malware Detection: Feature-Based Approach for Targeting Diverse Malware Categories 56

Revolutionizing Malware Detection: Feature-Based Approach fo...

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56th International Carnahan Conference on Security technology, ICCST 2023

作者： Jain, Sanyam Thaseen, Sumaiya School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350315875

In today's digital landscape, the task of identifying various types of malicious files has become progressively challenging. Modern malware exhibits increasing sophistication, often evading conventional anti-malware solutions. The scarcity of data on distinct and novel malware strains further complicates effective detection. In response, this research presents an innovative approach to malware detection, specifically targeting multiple distinct categories of malicious software. In the initial stage, Principal Component Analysis (PCA) is performed and achieved a remarkable accuracy rate of 95.39%. Our methodology revolves around leveraging features commonly accessible from user-uploaded files, aligning with the contextual behavior of typical users seeking to identify malignancy. This underscores the efficacy of the unique feature-based detection strategy and its potential to enhance contemporary malware identification methodologies. The outcomes achieved attest to the significance of addressing emerging malware threats through inventive analytical paradigms. © 2023 IEEE.

关键词： Malware

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Synthesis ofδ-MnO_(2)via ozonation routine for low temperature formaldehyde removal

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Journal of Environmental sciences 2025年第1期147卷 642-651页

作者： Guijun Fan Yacong Guo Shaohua Chai Le Zhang Jian Guan Guojun Ma Ning Han Yunfa Chen State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China College of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China Key Laboratory of Science and Technology on Particle Materials Institute of Process EngineeringChinese Academy of SciencesBeijing 361021China Key Laboratory for Mechanics in Fluid Solid Coupling Systems Institute of MechanicsChinese Academy of SciencesBeijing 100190China School of Petrochemical Engineering&Environment Zhejiang Ocean UniversityZhoushan 316022China

Nowadays,it is still a challenge to prepared high efficiency and low cost formaldehyde(HCHO)removal catalysts in order to tackle the long-living indoor air ***,δ-MnO_(2)is successfully synthesized by a facile ozonation strategy,where Mn^(2+)is oxidized by ozone(O_(3))bubble in an alkaline *** presents one of the best catalytic properties with a low 100%conversion temperature of 85℃for 50 ppm of HCHO under a GHSV of 48,000 mL/(g·hr).As a comparison,more than 6 times far longer oxidation time is needed if O3 is replaced by O_(2).Characterizations show that ozonation process generates a different intermediate of tetragonalβ-HMnO_(2),which would favor the quick transformation into the final productδ-MnO_(2),as compared with the relatively more thermodynamically stable monoclinicγ-HMnO_(2)in the O_(2)***,HCHO is found to be decomposed into CO_(2)via formate,dioxymethylene and carbonate species as identified by room temperature insitu diffuse reflectance infrared fourier transform *** these results show great potency of this facile ozonation routine for the highly activeδ-MnO_(2)synthesis in order to remove the HCHO contamination.

关键词： δ-MnO_(2) Ozone oxidation HCHO oxidation In-situ DRIFTS

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Reduced-search guessing random additive noise decoding of polar codes

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science China(information sciences) 2023年第2期66卷 283-284页

作者： Kefan WANG Yuejun WEI Zhenyuan CHEN Huarui YIN Liping LI Wenyi ZHANG Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education of China Anhui University Huawei Technologies Department of Electronic Engineering and Information Science University of Science and Technology of China

Guessing random additive noise decoding(GRAND) has attracted researchers since its introduction in [1]. For an additive noise channel with hard decision output, the algorithm checks all error patterns, and it schedules its search in descending likelihood order. Ordered reliability bit GRAND(ORBGRAND) [2] is a variant of *** soft channel output is available,

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Novel Darknet traffic data synthesis using Generative Adversarial Networks enhanced with oscillatory Growing Cosine Unit activated convolution layers

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International Journal of Cognitive Computing in engineering 2024年第1期5卷 58-65页

作者： Pradeep C, Antony Amali D, Geraldine Bessie Noel, Mathew Mithra Ghalib, Muhammad Rukunuddin Subramaniam, Prabhakar Rontala Venugopal, Chitra School of Computer Science and Engineering Vellore Institute of Technology Vellore India School of Electrical Engineering Vellore Institute of Technology Vellore India School of Computing De Montfort University Dubai United Arab Emirates Information Systems and Technology Westville South Africa Electrical Engineering & Renewable Energy Oregon Institute of Technology United States

The Darknet is an anonymous, encrypted collection of websites, with a passive listening nature - accepting incoming packets, while not supporting outgoing packets. Thus, it can potentially host criminal or malicious activity and software, becoming a cyber security threat. Network Detection systems are effective in identifying dark net traffic and mitigating its ill effects. However, capturing and extracting data from raw network traffic for training these systems can be time-intensive and costly. Using the CIC-Darknet 2020 dataset, this paper proposes using a Novel Generative Adversarial Networks (GAN) Architecture generating the required training and testing data for these systems. This uses a combination of Growing Cosine Unit (GCU) activated convolution layers and Dense layers for the Generator. Feature selection with statistical correlation methods is used to select the most relevant features. An independently trained Evaluator network is used to evaluate the generated data. The proposed system is compared to other established Tabular data GANs like Conditional Tabular GAN (CTGAN) and Copula GAN with similar parameters and on the same data. The Proposed GAN architecture outperforms CTGAN and CopulaGAN by 20 % and 10 % in ters of accuracy while also taking 90 % and 30 % less time to train respectively. Results from measuring similarity of data using the Inverted Kolmogorov - Smirnov D statistic also show significantly better results for the Proposed GAN Architecture. This shows significant promise in using Generative models to reduce the time and effort costs associated with collecting and formatting data to use in research and for training detection systems. © 2024

关键词： Generative adversarial networks

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A Reflectarray With Low Profile Based on the Method of Choosing the Certain Phase Constant

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IEEE Antennas and Wireless Propagation Letters 2025年第6期24卷 1397-1401页

作者： Li, Wenting Lin, Wenting Li, Ruiyang He, Yejun Gao, Yao Zhang, Chong Gao, Steven State Key Laboratory of Radio Frequency Heterogeneous Integration School of Electronic and Information Engineering Shenzhen University Shenzhen China School of Electrical and Information Engineering Zhengzhou University Zhengzhou China School of Information Engineering Chang'an University Xi'an China School of Information Science and Engineering Shenyang University of Technology Shenyang China Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China

In this letter, a reflectarray antenna with a small focal diameter ratio (F\D) is presented. It is found that when the F\D is extremely small, the phase constant used in calculating the required reflection phase on the reflecting surface significantly affects the radiation pattern. In certain cases, an unsuitable phase constant can even cause the main beam to split. The unit cell is implemented as a stacked patch, and the reflecting surface comprises 14 × 14 elements. The effect of the phase constant on the radiation pattern is analyzed, and two reflectarrays with phase constants of 90° and 180°, both operating at 10 GHz with an F\D of 0.05, are compared. These two reflectarrays are simulated, fabricated, and measured. The measured results show good agreement with the simulations. Within the operating band, the reflectarray with a phase constant of 90° achieves a maximum measured gain of 20.42 dBi, with the first sidelobe level (SLL1) below -10 dB. The radiation pattern of the reflectarray with a phase constant of 180° is totally distorted, resulting in a measured gain of 6.56 dBi at 10 GHz and an SLL1 of -5.8 dB. © 2002-2011 IEEE.

关键词： Reflection

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Performance Analysis of RIS Assisted NOMA Networks over Rician Fading Channels

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Computer Modeling in engineering & sciences 2023年第6期135卷 2531-2555页

作者： Xianli Gong Chongwen Huang Xinwei Yue Zhaohui Yang Feng Liu School of Electronic and Information Engineering Beihang UniversityBeijing100191China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou310027China International Joint Innovation Center Zhejiang UniversityHaining314400China Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking(IPCAN)Hangzhou310027China School of Information and Communication Engineering Beijing Information Science and Technology UniversityBeijing100101China Zhejiang Laboratory Hangzhou311121China

In this paper,we consider a downlink non-orthogonal multiple access(NOMA)network assisted by two reconfigurable intelligent surfaces(RISs)over Rician fading channels,in which each user communicates with the base station by the virtue of a RIS to enhance the reliability of the received *** evaluate the system performance of our proposed RIS-NOMA network,we first derive the exact and asymptotic expressions for the outage probability and ergodic rate of two ***,we derive the exact and asymptotic upper bound expressions for the ergodic rate of the nearby *** on asymptotic analytical results,the diversity orders for the outage probability and the high signal-to-noise ratio(SNR)slopes for the ergodic rate of the two users are obtained in the high SNR ***,we derive the system throughputs of the proposed RIS-NOMA network in delay-limited and delay-tolerant transmission *** results confirm our analysis and demonstrate that:1)The outage probability and ergodic rate of RIS-NOMA networks are superior to that of RIS-assisted orthogonalmultiple access(OMA)networks;2)The RIS-NOMA networks have ability to achieve a larger system throughput compared to RIS-OMA networks;and 3)The system performance of RIS-NOMA networks can be significantly improved as the number of reflecting elements and Rician factor increases.

关键词： Non-orthogonal multiple access reconfigurable intelligent surface outage probability ergodic rate

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IoT-Enabled Ethanol Detection System: A Transformative Stride in Ensuring Food Authenticity

IoT-Enabled Ethanol Detection System: A Transformative Strid...

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2023 International Conference on System, Computation, Automation and Networking, ICSCAN 2023

作者： Deenadayalan, T. Deepakraj, E. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350315127

In the present era, the rapid rise of IoT technology has brought forth innovative solutions, particularly in ensuring food safety. This study introduces an IoT-based ethanol detection system tailored to preserve the quality and security of food products. Ethanol, a key indicator of food spoilage, can endanger consumer well-being in excessive amounts. Food adulteration with hazardous substances like ethanol poses a serious public health challenge;the Food Safety and Standards Authority of India (FSSAI) reported that 30% of tested food samples (2017-2019) exceeded safe ethanol levels. Addressing this, we present an IoTbased Ethanol Detection System (IoTEDS), merging sensitive ethanol sensors and IoT tech. IoTEDS monitors ethanol levels in real-time across the food supply chain, enabling remote data analysis and swift risk detection. Through advanced algorithms, the system processes sensor data, generating precise alerts to prevent compromised product distribution. This tech enhances food safety, cuts losses, and safeguards public health. By incorporating touch-sensitive ethanol sensors with IoT capabilities, this research pioneers modern quality assurance, fostering transparent supply chains and industry accountability. IoTEDS' real-time monitoring, data analysis, and risk mitigation position it as a transformative stride in ensuring food authenticity. © 2023 IEEE.

关键词： Quality control

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Distributed Momentum-Based Frank-Wolfe Algorithm for Stochastic Optimization

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 685-699页

作者： Jie Hou Xianlin Zeng Gang Wang Jian Sun Jie Chen National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081 Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China School of Electronic and Information Engineering Tongji UniversityShanghai 200082and also with the National Key Laboratory of Autonomous Intelligent Unmanned Systemsthe School of AutomationBeijing Institute of TechnologyBeijing 100081China IEEE

This paper considers distributed stochastic optimization,in which a number of agents cooperate to optimize a global objective function through local computations and information exchanges with neighbors over a *** optimization problems are usually tackled by variants of projected stochastic gradient ***,projecting a point onto a feasible set is often *** Frank-Wolfe(FW)method has well-documented merits in handling convex constraints,but existing stochastic FW algorithms are basically developed for centralized *** this context,the present work puts forth a distributed stochastic Frank-Wolfe solver,by judiciously combining Nesterov's momentum and gradient tracking techniques for stochastic convex and nonconvex optimization over *** is shown that the convergence rate of the proposed algorithm is O(k^(-1/2))for convex optimization,and O(1/log_(2)(k))for nonconvex *** efficacy of the algorithm is demonstrated by numerical simulations against a number of competing alternatives.

关键词： Distributed optimization Frank-Wolfe(FW)algorithms momentum-based method stochastic optimization

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