498 research outputs found

    Automatic emotion perception using eye movement information for E-Healthcare systems.

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    Facing the adolescents and detecting their emotional state is vital for promoting rehabilitation therapy within an E-Healthcare system. Focusing on a novel approach for a sensor-based E-Healthcare system, we propose an eye movement information-based emotion perception algorithm by collecting and analyzing electrooculography (EOG) signals and eye movement video synchronously. Specifically, we extract the time-frequency eye movement features by firstly applying the short-time Fourier transform (STFT) to raw multi-channel EOG signals. Subsequently, in order to integrate time domain eye movement features (i.e., saccade duration, fixation duration, and pupil diameter), we investigate two feature fusion strategies: feature level fusion (FLF) and decision level fusion (DLF). Recognition experiments have been also performed according to three emotional states: positive, neutral, and negative. The average accuracies are 88.64% (the FLF method) and 88.35% (the DLF with maximal rule method), respectively. Experimental results reveal that eye movement information can effectively reflect the emotional state of the adolescences, which provides a promising tool to improve the performance of the E-Healthcare system.Anhui Provincial Natural Science Research Project of Colleges and Universities Fund under Grant KJ2018A0008, Open Fund for Discipline Construction under Grant Institute of Physical Science and Information Technology in Anhui University, and National Natural Science Fund of China under Grant 61401002

    A framework for orchestrating secure and dynamic access of IoT services in multi-cloud environments

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    IoT devices have complex requirements but their limitations in terms of storage, network, computing, data analytics, scalability and big data management require it to be used it with a technology like cloud computing. IoT backend with cloud computing can present new ways to offer services that are massively scalable, can be dynamically configured, and delivered on demand with largescale infrastructure resources. However, a single cloud infrastructure might be unable to deal with the increasing demand of cloud services in which hundreds of users might be accessing cloud resources, leading to a big data problem and the need for efficient frameworks to handle a large number of user requests for IoT services. These challenges require new functional elements and provisioning schemes. To this end, we propose the usage of multi-clouds with IoT which can optimize the user requirements by allowing them to choose best IoT services from many services hosted in various cloud platforms and provide them with more infrastructure and platform resources to meet their requirements. This paper presents a novel framework for dynamic and secure IoT services access across multi-clouds using cloud on-demand model. To facilitate multi-cloud collaboration, novel protocols are designed and implemented on cloud platforms. The various stages involved in the framework for allowing users access to IoT services in multi-clouds are service matchmaking (i.e. to choose the best service matching user requirements), authentication (i.e. a lightweight mechanism to authenticate users at runtime before granting them service access), and SLA management (including SLA negotiation, enforcement and monitoring). SLA management offers benefits like negotiating required service parameters, enforcing mechanisms to ensure that service execution in the external cloud is according to the agreed SLAs and monitoring to verify that the cloud provider complies with those SLAs. The detailed system design to establish secure multi-cloud collaboration has been presented. Moreover, the designed protocols are empirically implemented on two different clouds including OpenStack and Amazon AWS. Experiments indicate that proposed system is scalable, authentication protocols result only in a limited overhead compared to standard authentication protocols, and any SLA violation by a cloud provider could be recorded and reported back to the user.N/

    ChatGPT Is A User-Generated Knowledge-Sharing Killer

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    Large Language Models (LLMs), e.g., ChatGPT, is expected to reshape a broad spectrum of domains. This study examines the impact of ChatGPT on question aksing in Q&A communitits via the natural experiment. Safe-guided by supporting evidence of parallel trends, a difference-in-difference (DID) analysis suggests the launching trigger an average 2.6% reduction of question-asking on Stack Overflow, confirming a lower-search-cost-enabled substitution. Our further analysis suggests that, this substitution effect has resulted in more longer, less readable and less cognitive and hence more sophisticated questions on average. Finally, the insignificant change in the score given by viewers per question suggests no improvement in the question quality and decreased platform-wide engagement. Our moderation analysis further ascertain the types of individuals who are more susceptible to ChatGPT. Taken together, our paper suggests LLMs may threaten the survival of user-generated knowledge-sharing communities, which may further threaten the sustainable learning and long-run improvement of LLMs

    Metal-Free Synthesis of \u3ci\u3eN-Heterocycles via Intramolecular Electrochemical C-H Aminations

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    N-heterocycles are key structural units in many drugs, biologically interesting molecules and functional materials. To avoid the residues of metal catalysts, the construction of N-heterocycles under metal-free conditions has attracted much research attention in academia and industry. Among them, the intramolecular electrochemical C-H aminations arguably constitute environmentally friendly methodologies for the metal-free construction of N-heterocycles, mainly due to the direct use of clean electricity as the redox agents. With the recent renaissance of organic electrosynthesis, the intramolecular electrochemical C-H aminations have undergone much progress in recent years. In this article, we would like to summarize the advances in this research field since 2019. The emphasis is placed on the reaction design and mechanistic insight. The challenges and future developments in the intramolecular electrochemical C-H aminations are also discussed

    Fractional Calculus Guidance Algorithm in a Hypersonic Pursuit-Evasion Game

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    Aiming at intercepting a hypersonic weapon in a hypersonic pursuit-evasion game, this paper presents a fractional calculus guidance algorithm based on a nonlinear proportional and differential guidance law. First, under the premise of without increasing the complexity degree of the guidance system against a hypersonic manoeuvering target, the principle that the differential signal of the line-of-sight rate is more sensitive to the target manoeuver than the line-of-sight rate is employed as the guidelines to design the guidance law. A nonlinear proportional and differential guidance law (NPDG) is designed by using the differential derivative of the line-of-sight rate from a nonlinear tracking differentiator. By using the differential definition of fractional calculus, on the basis of the NPDG, a fractional calculus guidance law (FCG) is proposed. According to relative motions between the interceptor and target, the guidance system stability condition with the FCG is given and quantitative values are also proposed for the parameters of the FCG. Under different target manoeuver conditions and noisy conditions, the interception accuracy and robustness of these two guidance laws are analysed. Numerical experimental results demonstrate that the proposed guidance algorithms effectively reduce the miss distance against target manoeuvers. Compared with the NPDG, a stronger robustness of the FCG is shown under noisy condition

    Transcriptome And Expression Profiling Analysis Link Patterns Of Gene Expression To Antennal Responses In Spodoptera Litura

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    Background: The study of olfaction is key to understanding the interaction of insects with their environment and provides opportunities to develop novel tactics for control of pest species. Recent developments in transcriptomic approaches enable the molecular basis of olfaction to be studied even in species with limited genomic information. Here we use transcriptome and expression profiling analysis to characterize the antennal transcriptome of the noctuid moth and polyphagous pest Spodoptera litura. Results: We identify 74 candidate genes involved in odor detection and recognition, encoding 26 ORs, 21 OBPs, 18 CSPs and 9 IRs. We examine their expression levels in both sexes and seek evidence for their function by relating their expression with levels of EAG response in male and female antennae to 58 host and non-host plant volatiles and sex pheromone components. The majority of olfactory genes showed sex-biased expression, usually male-biased in ORs. A link between OR gene expression and antennal responses to odors was evident, a third of the compounds tested evoking a sex-biased response, in every case also male-biased. Two candidate pheromone receptors, OR14 and OR23 were especially strongly expressed and male-biased and we suggest that these may respond to the two female sex pheromone components of S. litura, Z9E11-14:OAc and Z9E12-14:OAc, which evoked strongly male-biased EAG responses. Conclusions: Our results provide the molecular basis for elucidating the olfactory profile of moths and the sexual divergence of their behavior and could enable the targeting of particular genes, and behaviors for pest management

    Ultrasound-Guided Miniscalpel-Needle Release versus Dry Needling for Chronic Neck Pain: A Randomized Controlled Trial

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    Objective. To compare ultrasound-guided miniscalpel-needle (UG-MSN) release versus ultrasound-guided dry needling (UG-DN) for chronic neck pain. Methods. A total of 169 patients with chronic neck pain were randomized to receive either UG-MSN release or UG-DN. Before treatment and at 3 and 6 months posttreatment, pain was measured using a 10-point visual analogue scale (VAS). Neck function was examined using the neck disability index. Health-related quality of life was examined using the physical component score (PCS) and mental component score (MCS) of the SF-36 health status scale. Results. Patients in the UG-MSN release had greater improvement on the VAS (by 2 points at 3 months and 0.9 points at 6 months) versus in the UG-DN arm; (both P<0.0001). Patients receiving UG-MSN release also showed significantly lower scores on the adjusted neck disability index, as well as significantly lower PCS. No severe complications were observed. Conclusion. UG-MSN release was superior to UG-DN in reducing pain intensity and neck disability in patients with chronic neck pain and was not associated with severe complications. The procedural aspects in the two arms were identical; however, we did not verify the blinding success. As such, the results need to be interpreted with caution

    A CMAC-Based Systematic Design Approach of an Adaptive Embedded Control Force Loading System

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    In this chapter, an adaptive embedded control system is developed to measure yield strength of the material plate with an applied load. A systematic approach is proposed to handle special requirements of embedded control systems which are different from computer-based control systems as there are much less computational power and hardware resources available. Efficient control algorithm has to be designed to remove CPU burden so that the microcontroller has enough power available. A three-step approach is proposed to address the embedded control issue: Firstly, the mathematical description of the whole system is studied using both theoretical and experimental methods. A mathematical model is derived from the physical models of each component used, and an experiment is retrieved by employing Levy’s method and least square estimation to identify specific parameters of the system model. Secondly, an adaptive feedforward plus feedback controller is designed and simulated as a preparation for the embedded system implementation. The Cerebellar Model Articulation Controller (CMAC) is chosen as the feedforward part, and a PD controller is used as the feedback part to train the CMAC. Finally, the proposed algorithm is applied to the embedded system, and experiments are conducted to verify both the identified model and designed controller
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