In this paper, a dual-channel converter with a positive output and negative voltage output is proposed. It integrates a positive voltage output converter and a negative voltage output converter, and shares the same sw...
In this paper, a dual-channel converter with a positive output and negative voltage output is proposed. It integrates a positive voltage output converter and a negative voltage output converter, and shares the same switches. The number of active components can be reduced. In addition, the circuit can achieve dual output voltage control with a single controller and PWM drive signal by appropriately designing the ratio of the number of windings of the coupling inductor. A regulated positive voltage output and negative voltage output can be achieved.
Neurologic function implemented soft organic electronic skin holds promise for wide range of applications,such as skin prosthetics,neurorobot,bioelectronics,human-robotic interaction(HRI),***,we report the development...
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Neurologic function implemented soft organic electronic skin holds promise for wide range of applications,such as skin prosthetics,neurorobot,bioelectronics,human-robotic interaction(HRI),***,we report the development of a fully rubbery synaptic transistor which consists of all-organic materials,which shows unique synaptic characteristics existing in biological *** synaptic characteristics retained even under mechanical stretch by 30%.We further developed a neurological electronic skin in a fully rubbery format based on two mechanoreceptors(for synaptic potentiation or depression)of pressure-sensitive rubber and an all-organic synaptic *** converting tactile signals into Morse Code,potentiation and depression of excitatory postsynaptic current(EPSC)signals allow the neurological electronic skin on a human forearm to communicate with a robotic *** collective studies on the materials,devices,and their characteristics revealed the fundamental aspects and applicability of the all-organic synaptic transistor and the neurological electronic skin.
This paper present the network design and capacity planning of access point (AP) deployment for indoor positioning system. The estimation of WiFi distance is described briefly how to measure the signal strength of AP....
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This research demonstrates the improvement in antenna gain by utilizing an EBG reflector. The EBG reflector includes a unit cell with grooves shaped like the letters M and W to mitigate surface waves at a frequency of...
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ISBN:
(数字)9798331543952
ISBN:
(纸本)9798331543969
This research demonstrates the improvement in antenna gain by utilizing an EBG reflector. The EBG reflector includes a unit cell with grooves shaped like the letters M and W to mitigate surface waves at a frequency of 2.45 GHz. The suggested EBG reflector is constructed on an FR-4 substrate exhibiting a uniform dielectric constant of 4.3, a loss tangent of 0.025, and a thickness of 1.6 mm. Furthermore, the impact of boosting the antenna gain can be analyzed by the reflection phase diagram, which exhibits values ranging from +90° to -90° at the resonant frequency of the reflector. The proposed EBG reflector comprises 5x5 unit cells. The testing results of the reflector's performance, when integrated with a general dipole antenna, indicate that it can effectively respond to the resonant frequency of 2.45 GHz, with a |S 11 | level below -10 dB within the frequency range of 2.2 GHz to 2.6 GHz, thereby adequately covering the IEEE 802.11 b/g/n band. The suggested EBG reflector exhibits a gain of around 6.5 dBi at 2.45 GHz, indicating its efficacy in enhancing gain relative to the standard PEC reflector. Moreover, the radiation pattern is also directional.
Deep learning (DL) has been proposed as a promising solution for network intrusion detection systems (NIDSs). While most DL-based NIDSs focus on high accuracy, they often overlook the critical issue of NIDSs response ...
Deep learning (DL) has been proposed as a promising solution for network intrusion detection systems (NIDSs). While most DL-based NIDSs focus on high accuracy, they often overlook the critical issue of NIDSs response time for intrusion behavior. Recently some existing works presented time-aware evaluation metrics or design DL-based solutions for early intrusion detection, yet they primarily focus on the post-performance of NIDSs, without thoroughly investigating the impact of early intrusion detection on DL-based NIDSs due to the black-box nature of DL models. To address this research gap, we explore the impact of early detection on DL-based models’ detection accuracy and input features. In our empirical study, we implement two different existing deep learning-based NIDSs methods and evaluate them on three published benchmark NIDSs datasets. Based on the experiment results on DL-based NIDSs detection accuracy, we observe that the early detection scenario will lead to the NIDSs model’s detection accuracy decreasing up to 50%. To understand the reasons behind it, we adopt the SHapley Additive exPlanations (SHAP) to analyze the importance of features and we observe the varying feature distributions. The feature importance and feature distribution results show that early intrusion detection may lead to a degradation of feature quality.
Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conven...
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Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conventionally. Supposedly with the advancement of technology and the use of the internet everywhere, learning such as e-learning can be important, especially in the health sector. Until this research was conducted, only 514 academic documents about e-learning in health sciences were found for 20 years from 2001 to 2020, obtained in searching on the Scopus database. This study presents a comprehensive overview of studies related to E-learning in the Health Sciences sector. This study uses bibliometric analysis and indexed digital methods to map scientific publications throughout the world. This research employs the Scopus database to gather information, as well as the Scopus online analysis tool and Vosviewer to show the bibliometric network. The method consists with five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. Among the most published and indexed articles by Scopus, papers published by researchers in the United States have the highest number of publications (80), followed by United Kingdom (63) and Australia with 45 academic publications. The processed data shows the pattern and trend of increasing the number of international publications in E-learning in Health Sciences field, which Scopus index.
This paper considers video and audio transmission in ICN (Information-Centric Networking) CCN (Content- Centric Networking), in which each intermediate node can cache content. LCE (Leave Copy Everywhere) has been know...
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ISBN:
(数字)9781665471039
ISBN:
(纸本)9781665471046
This paper considers video and audio transmission in ICN (Information-Centric Networking) CCN (Content- Centric Networking), in which each intermediate node can cache content. LCE (Leave Copy Everywhere) has been known as a generic cache decision policy. However, because LCE caches at all the intermediate nodes, the cache of intermediate nodes can be duplicated. Therefore, various cache decision policies that eliminate redundancy have been proposed. In this paper, we evaluate the effect of the cache decision policies on QoE of video and audio transmission in ICN/CCN. We assess application-level QoS using a computer simulation with a tree network and QoE by means of subjective experiment.
We consider the use of a domain proxy assisted private citizen broadband radio service (CBRS) network and propose a Maximum Transmission Continuity (MTC) scheme to transmit Internet of Things (IoT) data reliably. MTC ...
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Power quality disturbances can be observed as sags, swells, transients, and harmonics, and can affect customers at varying levels of intensity. It is the responsibility of the utility to supply customers with power, h...
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ISBN:
(纸本)9781665463195
Power quality disturbances can be observed as sags, swells, transients, and harmonics, and can affect customers at varying levels of intensity. It is the responsibility of the utility to supply customers with power, however power quality disruptions can occur during distribution. Traditionally, only voltage information is used to conduct power quality monitoring at the distribution level. It is common to record the RMS values of the bus voltages and to identify abnormal operations based on when a sag or swell occurs. This paper proposes a tool consisting of an algorithm and an accompanying graphical user interface (GUI) that can display historical voltage bus data, analyze the data, and provide the user with information that details voltage behavior outside of a user-defined threshold. The GUI gives the user the interactive ability to import data and set the desired threshold. The algorithm then detects events in the imported data outside of the chosen threshold. It also provides the user with event durations, magnitudes, local maximums, and area. The efficacy of the algorithm was verified by comparing the output determined by the algorithm versus the conclusion drawn by a human observer. Additionally, this paper provides a brief overview of two power quality curves: the computer and Business Equipment Manufacturers' Association (CBEMA) curve, and the Information technology Industry Council (ITIC) curve. These curves have been utilized in past decades as the common mechanisms to identify voltage variations and the duration of disturbances. Although these curves have proven to have great merit for use as tolerance curves, they may not capture all the necessary details of the events for power quality characterization.
Students’ computational thinking and programming skills may grow due to collaborative programming. But as the researchers have noted, students frequently do not use metacognition to manage their cognitive activities ...
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