This paper addresses state estimation issues of large-scale systems with measurements subject to deception attacks, where the communication topology among sub-estimators is the same as the physical coupling structure ...
详细信息
This paper addresses state estimation issues of large-scale systems with measurements subject to deception attacks, where the communication topology among sub-estimators is the same as the physical coupling structure of the subsystems. In consideration of the limited channel bandwidth, a novel adaptive event-triggered scheme is proposed for governing the data transmission among sub-estimators. With the help of Lyapunov analysis approaches, sufficient conditions are derived to ensure the input-to-state stability of the dynamics of estimation errors. Meanwhile, the bound of the estimation errors is obtained in the mean-square sense. The desired estimator parameters are presented in an analytical form dependent on the solution of a set of matrix inequalities. The developed scheme is related to the local information of the subsystems and thus satisfies the requirement of scalability. Finally, a simulation example of power systems is given to reveal the usefulness and effectiveness of the developed design scheme.
Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic *** have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volu...
详细信息
Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic *** have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volume of content that CQAs *** clarify the current state of the CQA literature that has used ML and DL,this paper reports a systematic literature *** goal is to summarise and synthesise the major themes of CQA research related to(i)questions,(ii)answers and(iii)*** final review included 133 *** research themes include question quality,answer quality,and expert *** terms of dataset,some of the most widely studied platforms include Yahoo!Answers,Stack Exchange and Stack *** scope of most articles was confined to just one platform with few cross-platform *** with ML outnumber those with ***,the use of DL in CQA research is on an upward trajectory.A number of research directions are proposed.
Optical Character Recognition (OCR) is a technology that automatically extracts textual information from document images. An LLM, a large language model, is a neural network designed to understand, generate, and respo...
详细信息
Cloud workloads are highly dynamic and complex,making task scheduling in cloud computing a challenging *** several scheduling algorithms have been proposed in recent years,they are mainly designed to handle batch task...
详细信息
Cloud workloads are highly dynamic and complex,making task scheduling in cloud computing a challenging *** several scheduling algorithms have been proposed in recent years,they are mainly designed to handle batch tasks and not well-suited for real-time *** address this issue,researchers have started exploring the use of Deep Reinforcement Learning(DRL).However,the existing models are limited in handling independent tasks and cannot process workflows,which are prevalent in cloud computing and consist of related *** this paper,we propose SA-DQN,a scheduling approach specifically designed for real-time cloud *** approach seamlessly integrates the Simulated Annealing(SA)algorithm and Deep Q-Network(DQN)*** SA algorithm is employed to determine an optimal execution order of subtasks in a cloud server,serving as a crucial feature of the task for the neural network to *** provide a detailed design of our approach and show that SA-DQN outperforms existing algorithms in terms of handling real-time cloud workflows through experimental results.
Deep neural networks, especially face recognition models, have been shown to be vulnerable to adversarial examples. However, existing attack methods for face recognition systems either cannot attack black-box models, ...
详细信息
Potholes on roadways pose a significant risk to public safety, leading to numerous accidents and fatalities annually. In this research, we present a custom-trained machine learning model for real-time pothole detectio...
详细信息
The concept of smart houses has grown in prominence in recent *** challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device **...
详细信息
The concept of smart houses has grown in prominence in recent *** challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device *** home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical *** paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in *** have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT *** system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing *** have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache *** feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time *** is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation ***,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber *** trial results support the proposed system and demonstrate its potential for use in everyday life.
Underwater wireless sensor networks(UWSNs)rely on data aggregation to streamline routing operations by merging information at intermediate nodes before transmitting it to the ***,many existing data aggregation techniq...
详细信息
Underwater wireless sensor networks(UWSNs)rely on data aggregation to streamline routing operations by merging information at intermediate nodes before transmitting it to the ***,many existing data aggregation techniques are designed exclusively for static networks and fail to reflect the dynamic nature of underwater ***,conventional multi-hop data gathering techniques often lead to energy depletion problems near the sink,commonly known as the energy hole ***,cluster-based aggregation methods face significant challenges such as cluster head(CH)failures and collisions within clusters that degrade overall network *** address these limitations,this paper introduces an innovative framework,the Cluster-based Data Aggregation using Fuzzy Decision Model(CDAFDM),tailored for mobile *** proposed method has four main phases:clustering,CH selection,data aggregation,and *** CH selection,a fuzzy decision model is utilized to ensure efficient cluster head selection based on parameters such as residual energy,distance to the sink,and data delivery likelihood,enhancing network stability and energy *** the aggregation phase,CHs transmit a single,consolidated set of non-redundant data to the base station(BS),thereby reducing data duplication and saving *** adapt to the changing network topology,the re-clustering phase periodically updates cluster formations and reselects *** results show that CDAFDM outperforms current protocols such as CAPTAIN(Collection Algorithm for underwater oPTical-AcoustIc sensor Networks),EDDG(Event-Driven Data Gathering),and DCBMEC(Data Collection Based on Mobile Edge Computing)with a packet delivery ratio increase of up to 4%,an energy consumption reduction of 18%,and a data collection latency reduction of 52%.These findings highlight the framework’s potential for reliable and energy-efficient data aggregation mobile UWSNs.
We present a lightweight magnetic field simultaneous localisation and mapping (SLAM) approach for drift correction in odometry paths, where the interest is purely in the odometry and not in map building. We represent ...
详细信息
This paper mainly discusses two kinds of coupled reaction-diffusion neural networks (CRNN) under topology attacks, that is, the cases with multistate couplings and with multiple spatial-diffusion couplings. On one han...
详细信息
暂无评论