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Traffic Engineering and Quality of Service in Hybrid Software Defined Networks

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China Communications 2024年第2期21卷 96-121页

作者： Samiullah Mehraban Rajesh Kumar Yadav IOT Lab Department of Computer Science&EngineeringDelhi Technological UniversityDelhi 110042India

For Future networks, many research projects have proposed different architectures around the globe;Software Defined Network(SDN) architectures, through separating Data and Control Layers, offer a crucial structure for it. With a worldwide view and centralized Control, the SDN network provides flexible and reliable network management that improves network throughput and increases link utilization. In addition, it supports an innovative flow scheduling system to help advance Traffic Engineering(TE). For Medium and large-scale networks migrating directly from a legacy network to an SDN Network seems more complicated & even impossible, as there are High potential challenges, including technical, financial, security, shortage of standards, and quality of service degradation challenges. These challenges cause the birth and pave the ground for Hybrid SDN networks, where SDN devices coexist with traditional network devices. This study explores a Hybrid SDN network’s Traffic Engineering and Quality of Services Issues. Quality of service is described by network characteristics such as latency, jitter, loss, bandwidth,and network link utilization, using industry standards and mechanisms in a Hybrid SDN Network. We have organized the related studies in a way that the Quality of Service may gain the most benefit from the concept of Hybrid SDN networks using different algorithms and mechanisms: Deep Reinforcement Learning(DRL), Heuristic algorithm, K path partition algorithm, Genetic algorithm, SOTE algorithm, ROAR method, and Routing Optimization with different optimization mechanisms that help to ensure high-quality performance in a Hybrid SDN Network.

关键词： DRL hSDN QoE QoS SDN TE

Covalent Bond Based Android Malware Detection Using Permission and System Call Pairs

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Computers, Materials & Continua 2024年第3期78卷 4283-4301页

作者： Rahul Gupta Kapil Sharma R.K.Garg Department of Information Technology Delhi Technological UniversityNew Delhi110042India Department of Mechanical Engineering Deenbandhu Chhotu Ram University of Science and TechnologyMurthal131039India

The prevalence of smartphones is deeply embedded in modern society,impacting various aspects of our lives.Their versatility and functionalities have fundamentally changed how we communicate,work,seek entertainment,and access information.Among the many smartphones available,those operating on the Android platform dominate,being the most widely used type.This widespread adoption of the Android OS has significantly contributed to increased malware attacks targeting the Android ecosystem in recent years.Therefore,there is an urgent need to develop new methods for detecting Android malware.The literature contains numerous works related to Android malware detection.As far as our understanding extends,we are the first ones to identify dangerous combinations of permissions and system calls to uncover malicious behavior in Android applications.We introduce a novel methodology that pairs permissions and system calls to distinguish between benign and malicious samples.This approach combines the advantages of static and dynamic analysis,offering a more comprehensive understanding of an application’s behavior.We establish covalent bonds between permissions and system calls to assess their combined impact.We introduce a novel technique to determine these pairs’Covalent Bond Strength Score.Each pair is assigned two scores,one for malicious behavior and another for benign behavior.These scores serve as the basis for classifying applications as benign or malicious.By correlating permissions with system calls,the study enables a detailed examination of how an app utilizes its requested permissions,aiding in differentiating legitimate and potentially harmful actions.This comprehensive analysis provides a robust framework for Android malware detection,marking a significant contribution to the field.The results of our experiments demonstrate a remarkable overall accuracy of 97.5%,surpassing various state-of-the-art detection techniques proposed in the current literature.

关键词： Android malware android security hybrid analysis permission and system call pairs

Understanding Discrepancy of Power System Dynamic Security Assessment with Unknown Faults: A Reliable Transfer Learning-based Method

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 427-431页

作者： Chao Ren Han Yu Yan Xu Zhao Yang Dong School of Computer Science and Engineering Nanyang Technological UniversitySingapore School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore

This letter proposes a reliable transfer learning(RTL)method for pre-fault dynamic security assessment(DSA)in power systems to improve DSA performance in the presence of potentially related unknown faults.It takes individual discrepancies into consideration and can handle unknown faults with incomplete data.Extensive experiment results demonstrate high DSA accuracy and computational efficiency of the proposed RTL method.Theoretical analysis shows RTL can guarantee system performance.

关键词： Adversarial training dynamic security assessment maximum classifier discrepancy missing data transfer learning

Visible Light Indoor Positioning System Based on Pisarenko Harmonic Decomposition and Neural Network

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Chinese Journal of Electronics 2024年第1期33卷 195-203页

作者： Li ZHAO Yi REN Qi WANG Lange DENG Feng ZHANG School of Electronic Information Engineering Xi’an Technological University

Visible-light indoor positioning is a new generation of positioning technology that can be integrated into smart lighting and optical communications. The current received signal strength(RSS)-based visible-light positioning systems struggle to overcome the interferences of background and indoor-reflected noise. Meanwhile, when ensuring the lighting, it is impossible to use the superposition of each light source to accurately distinguish light source information; furthermore, it is difficult to achieve accurate positioning in complex indoor environments. This study proposes an indoor positioning method based on a combination of power spectral density detection and a neural network. The system integrates the mechanism for visible-light radiation detection with RSS theory, to build a back propagation neural network model fitting for multiple reflection channels. Different frequency signals are loaded to different light sources at the beacon end, and the characteristic frequency and power vectors are obtained at the location end using the Pisarenko harmonic decomposition method. Then, a complete fingerprint database is established to train the neural network model and conduct location tests. Finally, the location effectiveness of the proposed algorithm is verified via actual positioning experiments. The simulation results show that, when four groups of sinusoidal waves with different frequencies are superimposed with white noise, the maximum frequency error is 0.104 Hz and the maximum power error is 0.0362 W. For the measured positioning stage, a 0.8 m × 0.8 m × 0.8 m solid wood stereoscopic positioning model is constructed, and the average error is 4.28 cm. This study provides an effective method for separating multi-source signal energies, overcoming background noise, and improving indoor visible-light positioning accuracies.

关键词： Visible-light communication Indoor positioning Frequency estimation Pisarenko harmonic decomposition Back propagation neural network

Distributed Fault-Tolerant Control of Uncertain Multi-Agent Systems with Connectivity Maintenance

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Journal of Systems Science & Complexity 2024年第1期37卷 40-62页

作者： XING Xueyan HU Guoqiang Continental-NTU Corporate Lab Nanyang Technological UniversitySingapore 639798Singapore Continental-NTU Corporate Lab and the School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore

In this paper,a distributed cooperative control protocol is presented to deal with actuator failures of multi-agent systems in the presence of connectivity preservation.With the developed strategy,each agent can track the reference trajectory of the leader in the presence of actuator failures,disturbances and uncertainties.The connectivity of the multi-agent system can always be ensured during the control process.To achieve the aforementioned control objectives,a potential function is introduced to the distributed adaptive fault-tolerant control algorithm to preserve the initial connected network among the agents.The uncertainty of the multi-agent system,which is allowed to be described by discontinuous functions,is approximated and compensated using the fuzzy logic system.The asymptotic stability of the closed-loop system is demonstrated through the use of Cellina’s approximate selection theorem of nonsmooth analysis.Due to the developed adaptive laws,the upper bound of the disturbance is allowed to be uncertain,which facilitates the implementation of the control scheme.Finally,simulation results are provided to verify the effectiveness of the proposed control scheme.

关键词： Actuator failure connectivity maintenance coordination control uncertainties

New insights into the therapeutic approaches for the treatment of tauopathies

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Neural Regeneration Research 2024年第5期19卷 1020-1026页

作者： Himanshi Singh Asmita Das Mohammad Moshahid Khan Tayebeh Pourmotabbed Department of Microbiology Immunology and BiochemistryUniversity of Tennessee Health Science CenterMemphisTNUSA Department of Biotechnology Delhi Technological UniversityShahbad DaulatpurDelhiIndia Department of Neurology College of MedicineUniversity of Tennessee Health Science CenterMemphisTNUSA Neuroscience Institute University of Tennessee Health Science CenterMemphisTNUSA Center for Muscle Metabolism and NeuropathologyDivision of Regenerative and Rehabilitation Sciences and Department of Physical TherapyCollege of Health ProfessionsUniversity of Tennessee Health Science CenterMemphisTNUSA

Tauopathies are a group of neurological disorders,including Alzheimer’s disease and frontotemporal dementia,which involve progressive neurodegeneration,cognitive deficits,and aberrant tau protein accumulation.The development of tauopathies cannot currently be stopped or slowed down by treatment measures.Given the significant contribution of tau burden in primary tauopathies and the strong association between pathogenic tau accumulation and cognitive deficits,there has been a lot of interest in creating therapies that can alleviate tau pathology and render neuroprotective effects.Recently,small molecules,immunotherapies,and gene therapy have been used to reduce the pathological tau burden and prevent neurodegeneration in animal models of tauopathies.However,the major pitfall of the current therapeutic approach is the difficulty of drugs and gene-targeting modalities to cross the blood-brain barrier and their unintended side effects.In this review,the current therapeutic strategies used for tauopathies including the use of oligonucleotide-based gene therapy approaches that have shown a promising result for the treatment of tauopathies and Alzheimer’s disease in preclinical animal models,have been discussed.

关键词： dementia gene therapies immunotherapy neurodegeneration oligonucleotides tau tauopathies therapies

Optimal Coordination of Transportable Power Sources and Repair Crews for Service Restoration of Distribution Networks Considering Uncertainty of Traffic Congestion

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 189-201页

作者： Zhao Shi Yan Xu Dunjian Xie Shiwei Xie Amer M.Y.M.Ghias Nanyang technological university Singapore the School of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108China

This paper proposes a new method for service restoration of distribution network with the support of transportable power sources(TPSs)and repair crews(RCs).Firstly,a coupling model of distribution networks and vehicle routing of TPSs and RCs is proposed,where the TPSs serve as emergency power supply sources,and the RCs are used to repair the faulted lines.Considering the uncertainty of traffic congestion,the probability distribution of the travel time spent on each road is derived based on the Nesterov user equilibrium model,and a two-stage stochastic program is formulated to determine the optimal routings of TPSs and RCs.To efficiently solve the proposed stochastic mixed-integer linear program(MILP),a two-phase scenario reduction method is then developed to scale down the problem size,and an adaptive progressive hedging algorithm is used for an efficient solution.The effectiveness of the proposed methods and algorithms has been illustrated in a modified IEEE 33-bus system.

关键词： Service restoration distribution network traffic uncertainty transportable power source repair crew stochastic program

Spin-based magnetic random-access memory for high-performance computing

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National Science Review 2024年第3期11卷 20-23页

作者： Kaiming Cai Tianli Jin Wen Siang Lew School of Physics Huazhong University of Science and Technology Interuniversity Microelectronics Centre(IMEC) School of Physical and Mathematical Sciences Nanyang Technological University

Memory serves as a critical component in today's electronic systems for data storage and processing. In traditional computer architectures, the logic and memory units are physically separated, due to the performance gap in operational speed and capacity among memories, resulting in the fundamental limitation of the von Neumann computers.

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Heterogeneous integration of 2D materials on Si charge-coupled devices as optical memory

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Science China(Information Sciences) 2024年第6期67卷 190-197页

作者： Zheng BIAN Feng TIAN Zongwen LI Xiangwei SU Tianjiao ZHANG Jialei MIAO Bin YU Yang XU Yuda ZHAO College of Integrated Circuits Hangzhou Global Scientific and Technological Innovation CentreZhejiang University

Optical memory integrates the function of optical sensing in memory devices, remarkably promoting the interconnection between sensory and memory terminals. Silicon charge-coupled photodetectors and floating gate memory have been widely used in imaging and storage technologies, respectively. However,the heterogeneous integration of the two devices requires technological innovation and complex electrical connections. In this work, we adopt a three-dimensional layer stacking method to design a novel optical memory device. On the top of Si charge-coupled photodetectors, we successively deposit two-dimensional graphene,hexagonal boron nitride, and molybdenum disulfide as a floating gate layer, a tunneling layer, and a readout layer, respectively. By applying a gate bias on lightly doped Si, a deep depletion layer is formed with a high voltage potential drop. Under dark conditions, the depletion layer cannot be filled, and the electric field across the h-BN tunnel barrier is relatively small. Under light irradiation, the deep depletion layer is gradually filled, and the h-BN tunneling layer withstands the increasing electric field, resulting in charge storage in the floating gate layer. Based on this mechanism, the device exhibits a gate voltage-dependent operation mode, including an integrated optical sensing-memory mode and an electrically driven storage mode. Under moderate gate voltage, the device can effectively detect the optical information with varied intensity and store the optical information in the floating gate, displaying optically controlled memory characteristics. Our work demonstrates a compact device structure for optical memory and displays excellent optically controlled memory performance, which can be applied in artificial vision systems.

关键词： heterogeneous integration charge-coupled device floating gate optical memory molybdenum disulfide lightly doped silicon