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Cybersecurity 2024年第2期7卷 13-27页

作者： B S Sharmila Rohini Nagapadma Depatment of Electronics and Communication Engineering The National Institute of EngineeringMysoreKarnataka 570008India

In recent years,many researchers focused on unsupervised learning for network anomaly detection in edge devices to identify *** deployment of the unsupervised autoencoder model is computationally expensive in resource-constrained edge *** study proposes quantized autoencoder(QAE)model for intrusion detection systems to detect *** is an optimization model derived from autoencoders that incorporate pruning,clustering,and integer quantization *** autoencoder uint8(QAE-u8)and quantized autoencoder float16(QAE-f16)are two variants of QAE built to deploy computationally expensive Al models into Edge ***,we have generated a Real-Time Internet of Things 2022 dataset for normal and attack *** autoencoder model operates on normal traffic during the training *** same model is then used to reconstruct anomaly traffic under the assumption that the reconstruction error(RE)of the anomaly will be high,which helps to identify the ***,we study the performance of the autoencoders,QAE-u8,and QAE-f16 using accuracy,precision,recall,and F1 score through an extensive experimental *** showed that QAE-u8 outperforms all other models with a reduction of 70.01%in average memory utilization,92.23%in memory size compression,and 27.94%in peak CPU ***,the proposed QAE-u8 model is more suitable for deployment on resource-constrained IoT edge devices.

关键词： IoT constrained system

Influence of BPPV and Meniere's Disease on Cognitive Abilities: A Questionnaire-Based Study

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Journal of Otology 2024年第1期19卷 10-18页

作者： Rohit Bhattacharyya Animesh Barman Freddy Antony All India institute of Speech and Hearing MysoreMysuruIndia

The vestibular system connects the inner ear to the midbrain and subcortical structures and can affect cognition. Patients with vertigo often experience cognitive symptoms such as attention deficits, memory problems, and spatial perception difficulties. This study aimed to explore the cognitive impairments associated with Benign paroxysmal positional vertigo(BPPV) and Meniere's Disease(MD). A non-experimental group comparison design was used with 107 participants divided into three groups: Group I(clinically normal), Group II(BPPV), and Group III(MD). Participants completed a questionnaire with 10 cognition-related questions, and their responses were scored. The data were found to be non-normally distributed. The analysis revealed a significant difference in scores between Group I and both Group II and Group III. Chi-square tests showed that the responses to cognition-related questions varied among the groups, with Group II exhibiting more cognitive problems. Associated conditions like hypertension, diabetes, and hearing loss did not significantly influence the responses within each group. This study suggests a significant relationship between cognitive problems and patients with BPPV and MD. However, there was no association found between the cognitive problems experienced in BPPV and MD patients. These findings align with previous research indicating that vestibular disorders can lead to deficits in spatial memory, attention, and other cognitive functions. By understanding the link between cognition and vestibular disorders, we can improve diagnosis and rehabilitation services to enhance the quality of life for these patients.

关键词： BPPV Meniere's disease Cognition Questionnaire

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Deep Guided Attention Network for Joint Denoising and Demosaicing in Real Image

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Chinese Journal of Electronics 2024年第1期33卷 303-312页

作者： Tao ZHANG Ying FU Jun ZHANG School of Computer Science and technology Beijing Institute of Technology Advanced Reasearch institute of Multidisciplinary Science Beijing Institute of Technology

Denoising(DN) and demosaicing(DM) are the first crucial stages in the image signal processing pipeline. Recently, researches pay more attention to solve DN and DM in a joint manner, which is an extremely undetermined inverse problem. Existing deep learning methods learn the desired prior on synthetic dataset, which limits the generalization of learned network to the real world data. Moreover, existing methods mainly focus on the raw data property of high green information sampling rate for DM, but occasionally exploit the high intensity and signalto-noise(SNR) of green channel. In this work, a deep guided attention network(DGAN) is presented for real image joint DN and DM(JDD), which considers both high SNR and high sampling rate of green information for DN and DM, respectively. To ease the training and fully exploit the data property of green channel, we first train DN and DM sub-networks sequentially and then learn them jointly, which can alleviate the error accumulation. Besides, in order to support the real image JDD, we collect paired raw clean RGB and noisy mosaic images to conduct a realistic dataset. The experimental results on real JDD dataset show the presented approach performs better than the state-of-the-art methods, in terms of both quantitative metrics and qualitative visualization.

关键词： Training Visualization Inverse problems Green products Noise reduction Pipelines Signal processing

Low-temperature graphitization of lignin via Co-assisted electrolysis in molten salt

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Green Energy & Environment 2024年第9期9卷 1449-1458页

作者： Shijie Li Wei-Li Song Xue Han Qingqing Cui Yan-li Zhu Shuqiang Jiao institute of Advanced Structure technology Beijing Institute of Technology State Key Laboratory of Advanced Metallurgy University of Science and Technology Beijing State Key Laboratory of Explosion Science and technology Beijing Institute of Technology

The ever-growing energy demand and environmental issues have stimulated the development of sustainable energy ***,an efficient and environmentally friendly electrochemical transformation technology was proposed to prepare highly graphitized carbon materials from an abundant natural resource-lignin （LG）.The preparation process mainly includes pyrolytic carbonization of raw LG material and electrochemical conversion of amorphous carbon ***,with the assistance of Co catalyst,the graphitization degree of the products was significantly improved,in which the mechanism was the removal of heteroatoms in LG and the rearrangement of carbon atoms into graphite ***,tunable microstructures （nanoflakes） under catalytic effects could also be observed by controlling the electrolytic *** with the products CN1 （without catalyst） and CN5 （with 10%catalyst）,the specific surface area are 158.957 and202.246 m2g-1,*** used as the electrode material for lithium-ion batteries,CN5 delivered a competitive specific capacity of～350 m Ah g-1（0.5 C） compared with commercial *** strategy proposed in this work provides an effective way to extract value-added graphite materials from lignin and can be extended to the graphitization conversion of any other amorphous carbon precursor materials.

关键词： Lignin Graphitic carbon Electrochemical conversion Lithium-ion batteries

Fast Cross-Platform Binary Code Similarity Detection Framework Based on CFGs Taking Advantage of NLP and Inductive GNN

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Chinese Journal of Electronics 2024年第1期33卷 128-138页

作者： Jinxue PENG Yong WANG Jingfeng XUE Zhenyan LIU School of Computer Science and technology Beijing Institute of Technology

Cross-platform binary code similarity detection aims at detecting whether two or more pieces of binary code are similar or not. Existing approaches that combine control flow graphs(CFGs)-based function representation and graph convolutional network(GCN)-based similarity analysis are the best-performing ones. Due to a large amount of convolutional computation and the loss of structural information, the use of convolution networks will inevitably bring problems such as high overhead and sometimes inaccuracy. To address these issues, we propose a fast cross-platform binary code similarity detection framework that takes advantage of natural language processing(NLP)and inductive graph neural network(GNN) for basic blocks embedding and function representation respectively by simulating extracting structural features and temporal features. GNN’s node-centric and small batch is a suitable training way for large CFGs, it can greatly reduce computational overhead. Various NLP basic block embedding models and GNNs are evaluated. Experimental results show that the scheme with long short term memory(LSTM)for basic blocks embedding and inductive learning-based Graph SAGE(GAE) for function representation outperforms the state-of-the-art works. In our framework, we can take only 45% overhead. Improve efficiency significantly with a small performance trade-off.

关键词： Training Semantics Process control Binary codes Feature extraction Natural language processing Graph neural networks

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Synthesis of plant-based biogenic jarosite nanoparticles using Azadirachta indica and Eucalyptus gunni leaf extracts and its application in Fenton degradation of dicamba

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Water Science and Engineering 2024年第2期17卷 157-165页

作者： Shivaswamy Bhaskar Basavaraju Manu Marikunte Yanjarappa Sreenivasa Arlapadavu Manoj Department of Civil Engineering National Institute of Technology CalicutKozhikode 673601KeralaIndia Deparment of Civil Engineering National Instute of Techogy KamatakaSurahalP.Srinivasnaga Mangaore5725Indi Department of Studies in Microbiology University of MysoreMysuru 570006KarnatakaIndia Department of Civil Enginering Siddaganga Institute of TechnologyTumkur 572103India

Bio-jarosite,an iron mineral synthesized biologically using bacteria,is a substitute for iron catalysts in the Fenton oxidation of organic *** nanocatalysts have been widely used as Fenton catalysts because they have a larger surface area than ordinary catalysts,are highly recyclable,and can be treated *** study aimed to explore the catalytic properties of bio-jarosite iron nanoparticles syn-thesized with green methods using two distinct plant species:Azadirachta indica and Eucalyptus *** focus was on the degradation of dicamba via Fenton *** synthesized nanoparticles exhibited different particle size,shape,surface area,and chemical composition *** particles were effective in removing dicamba,with removal efficiencies of 96.8%for *** bio-jarosite iron nano-particles(ABFeNPs)and 93.0%for *** bio-jarosite iron nanoparticles(EBFeNPs)within 120 min of *** the catalyst dosage by 0.1 g/L resulted in 7.6%and 43.0%increases in the dicamba removal efficiency for EBFeNPs and ABFeNPs with rate constants of 0.025 min^(-1) and 0.023 min^(-1),respectively,confrming their catalytic ***,the high efficiency of both catalysts was demonstrated through five consecutive cycles of linear pseudo-first-order Fenton oxidation reactions.

关键词： Acidithiobacillus ferrooxidans Fenton process Jarosite Herbicide Dicamba Azadirachta indica Eucalyptus gunni

Prescribed-time leader-following consensus of linear multi-agent systems by bounded linear time-varying protocols

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Science China(Information Sciences) 2024年第1期67卷 140-153页

作者： Kai ZHANG Bin ZHOU Xuefei YANG Guangren DUAN Center for Control Theory and Guidance technology Harbin Institute of Technology

This paper considers the prescribed-time leader-following consensus problem of input-constrained linear multi-agent systems under generally directed communication topology in two cases:the Laplacian matrix related to the entire communication topology between agents is either known or *** particular,the consensus problem for the former case is solved by a novel bounded linear time-varying(LTV) protocol,where the feedback gain is formulated by the parametric Lyapunov equation and the knowledge of the Laplacian ***,by utilizing a distributed observer,a fully bounded LTV protocol is proposed for the latter *** should be noted that,compared with the existing results,the system under consideration is more general,the designed protocols are linear,and the consensus problem is accomplished even in a fully distributed ***,the effectiveness of the proposed approach is verified by a numerical example.

关键词： leader-following consensus time-vary feedback prescribed-time control fully distributed consensus

Prescribed time control based on the periodic delayed sliding mode surface without singularities

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Science China(Information Sciences) 2024年第7期67卷 256-270页

作者： Bin ZHOU Yi DING Kang-Kang ZHANG Guang-Ren DUAN Center for Control Theory and Guidance technology Harbin Institute of Technology

In this paper, nonsingular prescribed-time control is studied based on periodic delayed sliding mode surfaces. Different from the existing sliding mode control, where either singularity problems may appear or the convergence time depends on the initial state, the proposed sliding mode control approaches can achieve prescribed-time convergence without singularity. The proposed nonsingular sliding mode control approaches can be applied to both second-order and high-order nonlinear systems with prescribed-time convergence. As applications of the proposed sliding mode control approaches, the control of hypersonic vehicle systems is revisited. Numerical simulations on the nonlinear model of the hypersonic vehicle system show the effectiveness of the proposed methods.

关键词： prescribed-time control smooth periodic delayed feedback sliding mode control high-order nonlinear systems hypersonic vehicle systems

A model reduction approach for discrete-time linear time-variant systems with delayed inputs

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Science China(Information Sciences) 2024年第4期67卷 197-217页

作者： Ai-Guo WU Guang-Ren DUAN Yu WANG Jie ZHANG School of Mechanical Engineering and Automation Harbin Institute of Technology(Shenzhen) HIT Wuhu Robot technology Research institute Center for Control Science and technology Southern University of Science and Technology

A model reduction approach is presented for discrete-time linear time-variant input-delayed systems. According to this proposed approach, a dynamical variable is constructed by taking advantage of the current state and historical information of input. It is revealed that the behavior of this dynamical variable is governed by a discrete-time linear delay-free system. It is worth noting that the presented variable transformation does not require the system matrix to be invertible. Based on the reduced delay-free models,stabilizing control laws can be easily obtained for the original delayed system. For the case with a single input delay, the constructed variable is an exact prediction for the future state, and thus the stabilizing control law could be designed by replacing the future state with its prediction. Finally, three discrete-time periodic systems with delayed input are employed to illustrate how to utilize the presented model reduction approaches.

关键词： reduction approach predictor-based feedback time-varying systems delayed input periodic system

Ru-doped functional porous materials for electrocatalytic water splitting

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Nano Research 2024年第3期17卷 982-1002页

作者： Chongao Tian Rui Liu Yu Zhang Wenxiu Yang Bo Wang Beijing Key Laboratory of Photoelectronic/Electrophotonic Conversion Materials Advanced Technology Research Institute(Jinan)Advanced Research Institute of Multidisciplinary ScienceSchool of Chemistry and Chemical EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing institute of technology Library Beijing Institute of TechnologyBeijing 100081China

Electrolytic water splitting(EWS)is an attractive and promising technique for the production of hydrogen ***,the sluggish kinetic rate of hydrogen/oxygen evolution reactions leads to a high overpotential and low energy *** to date,Pt/Ir-based nanocatalysts have become the state-of-the-art EWS catalysts,but disadvantages such as high cost and low earth abundance greatly limit their applications in EWS *** an attractive candidate for the Pt/Ir catalysts,series of Ru-based nanomaterials have aroused much attention for their low price,Pt-like hydrogen bond strength,and high EWS *** particular,Ru-doped functional porous materials have been becoming one of the most representative EWS catalysts,which can not only achieve the dispersion and adjustment for active Ru sites,but also simultaneously solve the problems of mass transfer and catalytic conversion in *** this review,the design and preparation strategies of Ru-doped functional porous materials toward EWS in recent years are summarized,including Ru-doped metal organic frameworks(MOFs),Ru-doped porous organic polymers(POPs),and their ***,detailed structure–activity relationships induced by the tuned geometric/electronic structures of Ru-doped functional porous materials are further depicted in this *** but not least,the challenges and perspectives of Ru-doped functional porous materials catalysts are reasonably proposed to provide fresh ideas for the design of Ru-based EWS catalysts.

关键词： Ru-based catalyst functional porous materials electrolytic water splitting oxygen evolution reaction hydrogen evolution reaction