Fruit safety is a critical component of the global economy, particularly within the agricultural sector. There has been a recent surge in the incidence of diseases affecting fruits, leading to economic setbacks in agr...
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Robots are increasingly being deployed in densely populated environments, such as homes, hotels, and office buildings, where they rely on explicit instructions from humans to perform tasks. However, complex tasks ofte...
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Robots are increasingly being deployed in densely populated environments, such as homes, hotels, and office buildings, where they rely on explicit instructions from humans to perform tasks. However, complex tasks often require multiple instructions and prolonged monitoring, which can be time-consuming and demanding for users. Despite this, there is limited research on enabling robots to autonomously generate tasks based on real-life scenarios. Advanced intelligence necessitates robots to autonomously observe and analyze their environment and then generate tasks autonomously to fulfill human requirements without explicit commands. To address this gap, we propose the autonomous generation of navigation tasks using natural language dialogues. Specifically, a robot autonomously generates tasks by analyzing dialogues involving multiple persons in a real office environment to facilitate the completion of item transportation between various *** propose the leveraging of a large language model(LLM) through chain-of-thought prompting to generate a navigation sequence for a robot from dialogues. We also construct a benchmark dataset consisting of 625 multiperson dialogues using the generation capability of LLMs. Evaluation results and real-world experiments in an office building demonstrate the effectiveness of the proposed method.
In telemedicine applications, it is crucial to ensure the authentication, confidentiality, and privacy of medical data due to its sensitive nature and the importance of the patient information it contains. Communicati...
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In telemedicine applications, it is crucial to ensure the authentication, confidentiality, and privacy of medical data due to its sensitive nature and the importance of the patient information it contains. Communication through open networks is insecure and has many vulnerabilities, making it susceptible to unauthorized access and misuse. Encryption models are used to secure medical data from unauthorized access. In this work, we propose a bit-level encryption model having three phases: preprocessing, confusion, and diffusion. This model is designed for different types of medical data including patient information, clinical data, medical signals, and images of different modalities. Also, the proposed model is effectively implemented for grayscale and color images with varying aspect ratios. Preprocessing has been applied based on the type of medical data. A random permutation has been used to scramble the data values to remove the correlation, and multilevel chaotic maps are fused with the cyclic redundancy check method. A circular shift is used in the diffusion phase to increase randomness and security, providing protection against potential attacks. The CRC method is further used at the receiver side for error detection. The performance efficiency of the proposed encryption model is proved in terms of histogram analysis, information entropy, correlation analysis, signal-to-noise ratio, peak signal-to-noise ratio, number of pixels changing rate, and unified average changing intensity. The proposed bit-level encryption model therefore achieves information entropy values ranging from 7.9669 to 8.000, which is close to the desired value of 8. Correlation coefficient values of the encrypted data approach to zero or are negative, indicating minimal correlation in encrypted data. Resistance against differential attacks is demonstrated by NPCR and UACI values exceeding 0.9960 and 0.3340, respectively. The key space of the proposed model is 1096, which is substantially mor
Smart power grids are vulnerable to security threats due to their cyber-physical nature. Existing data-driven detectors aim to address simple traditional false data injection attacks (FDIAs). However, adversarial fals...
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Knowledge distillation (KD) compresses the network capacity by transferring knowledge from a large (teacher) network to a smaller one (student). It has been mainstream that the teacher directly transfers knowledge to ...
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Multi-user Augmented Reality (MuAR) allows multiple users to interact with shared virtual objects, facilitated by exchanging environment information. Current MuAR systems rely on 3D point clouds for real-world analysi...
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Topology is usually perceived intrinsically immutable for a given *** argue that optical topologies do not immediately enjoy such ***'optical skyrmions'as an example,we show that they will exhibit varying text...
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Topology is usually perceived intrinsically immutable for a given *** argue that optical topologies do not immediately enjoy such ***'optical skyrmions'as an example,we show that they will exhibit varying textures and topological invariants(skyrmion numbers),depending on how to construct the skyrmion vector when projecting from real to parameter *** demonstrate the fragility of optical skyrmions under a ubiquitous scenario-simple reflection off an optical *** topology is not without benefit,but it must not be assumed.
The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific f...
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The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific flows by matching them against a set of dynamic rules. This basic process accelerates the processing of data, so that instead of processing singular packets repeatedly, corresponding actions are performed on corresponding flows of packets. In this paper, first, we address limitations on a typical packet classification algorithm like Tuple Space Search (TSS). Then, we present a set of different scenarios to parallelize it on different parallel processing platforms, including Graphics Processing Units (GPUs), clusters of Central Processing Units (CPUs), and hybrid clusters. Experimental results show that the hybrid cluster provides the best platform for parallelizing packet classification algorithms, which promises the average throughput rate of 4.2 Million packets per second (Mpps). That is, the hybrid cluster produced by the integration of Compute Unified Device Architecture (CUDA), Message Passing Interface (MPI), and OpenMP programming model could classify 0.24 million packets per second more than the GPU cluster scheme. Such a packet classifier satisfies the required processing speed in the programmable network systems that would be used to communicate big medical data.
Scanning microscopy systems, such as confocal and multiphoton microscopy, are powerful imaging tools for probing deep into biological tissue. However, scanning systems have an inherent trade-off between acquisition ti...
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Dear Editor,This letter is concerned with prescribed-time Nash equilibrium(PTNE)seeking problem in a pursuit-evasion game(PEG)involving agents with second-order *** order to achieve the prior-given and user-defined co...
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Dear Editor,This letter is concerned with prescribed-time Nash equilibrium(PTNE)seeking problem in a pursuit-evasion game(PEG)involving agents with second-order *** order to achieve the prior-given and user-defined convergence time for the PEG,a PTNE seeking algorithm has been developed to facilitate collaboration among multiple pursuers for capturing the evader without the need for any global ***,it is theoretically proved that the prescribedtime convergence of the designed algorithm for achieving Nash equilibrium of ***,the effectiveness of the PTNE method was validated by numerical simulation results.A PEG consists of two groups of agents:evaders and *** pursuers aim to capture the evaders through cooperative efforts,while the evaders strive to evade *** is a classic noncooperative *** has attracted plenty of attention due to its wide application scenarios,such as smart grids[1],formation control[2],[3],and spacecraft rendezvous[4].It is noteworthy that most previous research on seeking the Nash equilibrium of the game,where no agent has an incentive to change its actions,has focused on asymptotic and exponential convergence[5]-[7].
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