In this paper, for the first time, deep learning (DL) based artificial neural network (ANN) is applied to model the effects of various random variations: work function fluctuation, random dopant fluctuation, and inter...
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Unmanned aerial vehicle-aided communication (UAB-BS) is a promising solution to establish rapid wireless connectivity in sudden/temporary crowded events because of its more flexibility and mobility features than conve...
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Driving in the wrong direction is one of the main reasons that cause road accidents in Thailand. To efficiently detect wrong direction driving vehicles, we proposed a system that can track those moving vehicles from C...
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The fabrication of InGaN-based blue 4✕4 array micro-LEDs (μLEDs) with 40 μm ✕40 μm chip size and 2✕2 array μLEDs with 80 μm ✕80 μm chip size etching by the inductive coupled plasma reactive ion etching (ICPRIE) ...
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Spiking neural networks (SNNs) have emerged as energy-efficient neural networks with temporal information. SNNs have shown a superior efficiency on neuromorphic devices, but the devices are susceptible to noise, which...
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ISBN:
(纸本)9781665432740
Spiking neural networks (SNNs) have emerged as energy-efficient neural networks with temporal information. SNNs have shown a superior efficiency on neuromorphic devices, but the devices are susceptible to noise, which hinders them from being applied in real-world applications. Several studies have increased noise robustness, but most of them considered neither deep SNNs nor temporal information. In this paper, we investigate the effect of noise on deep SNNs with various neural coding methods and present a noise-robust deep SNN with temporal information. With the proposed methods, we have achieved a deep SNN that is efficient and robust to spike deletion and jitter.
The green transition has brought about a worldwide-shift to the use of renewables as alternative energy sources. Because of this, high voltage DC has been a field of interest in power electronics due to its capability...
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ISBN:
(纸本)9781665491075
The green transition has brought about a worldwide-shift to the use of renewables as alternative energy sources. Because of this, high voltage DC has been a field of interest in power electronics due to its capability in efficiently transmitting power to reach remote areas. Typical DC-DC electronic power converter design has the capability of boosting voltage level to a certain extent but not enough for high-voltage applications. Using the DMAIC Approach of the Six Sigma, quality improvements in the design was proposed to stabilize operating frequency, bring up the output voltage from 100 VDC to 4,000 VDC and provide at least 10% margin of error in the apparent power measured at the output side to offset inherent losses in the electrical design. These proposed quality improvements were sustained by designing a control circuit that would ensure the attainment of the parameters set in the Define Phase of the DMAIC Approach. The result of the study is a practical 12 VDC to 4,000 VDC boost converter design that has incorporated all the proposed quality improvements.
This study surveyed 183 college and senior high school students’ graph-interpretation competence in scientific and daily contexts. Specifically, whether students’ graph interpretation in scientific and daily context...
This study surveyed 183 college and senior high school students’ graph-interpretation competence in scientific and daily contexts. Specifically, whether students’ graph interpretation in scientific and daily contexts differed across educational levels was investigated. Furthermore, the questions of whether students’ graph interpretation competence in scientific contexts might predict their graph interpretation in daily contexts were explored. Other factors including age and gender were also considered and examined to discern significant factor(s) predicting graph interpretation competence in daily contexts. Results indicated that there were statistically significant differences across educational levels in terms of graph interpretation competence in both scientific and daily contexts. Furthermore, the students’ graph interpretation competence was related between scientific and daily contexts. The important factors predicting students’ graph interpretation in daily contexts include age and graph-interpretation in scientific literacy. Implications are discussed.
In recent years, the GAA NS Si MOSFET has been explored as a leading technology. However, the intrinsic parameters of GAA NS Si MOSFETs are affected to varying degrees by various fluctuation sources, Statistically ind...
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In recent years, the GAA NS Si MOSFET has been explored as a leading technology. However, the intrinsic parameters of GAA NS Si MOSFETs are affected to varying degrees by various fluctuation sources, Statistically independent and identically distributed $(iid)$ assumptions on the aforementioned random variables overestimate the variability of high-frequency characteristics, compared with considering all fluctuation factors simultaneously. Notably, the random nanosized metal grains dominates the variations of voltage gain, cut-off frequency, and 3dB frequency because the random work functions strongly alter the channel surface potential.
The emergence of contemporary deepfakes has attracted significant attention in machine learning research, as artificial intelligence (AI) generated synthetic media increases the incidence of misinterpretation and is d...
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Deep Learning has been successfully applied in diverse fields, and its impact on deepfake detection is no exception. Deepfakes are fake yet realistic synthetic content that can be used deceitfully for political impers...
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