Zobrazeno 1 - 10
of 51 992
pro vyhledávání: '"Ing A"'
Autor:
Deckers, Lucas, Vandersmissen, Benjamin, Tsang, Ing Jyh, Van Leekwijck, Werner, Latré, Steven
The proliferation of Artificial Neural Networks (ANNs) has led to increased energy consumption, raising concerns about their sustainability. Spiking Neural Networks (SNNs), which are inspired by biological neural systems and operate using sparse, eve
Externí odkaz:
http://arxiv.org/abs/2409.15849
Nowadays, transit timing variations (TTVs) are proving to be a very valuable tool in exoplanetary science to detect exoplanets by observing variations in transit times. To study the transit timing variation of the hot Jupiter, TrES-2b, we have combin
Externí odkaz:
http://arxiv.org/abs/2409.12069
Autor:
Yang, Fan, Long, Richard J., Kerins, Eamonn, Awiphan, Supachai, Shan, Su-Su, Zhang, Bo, Joshi, Yogesh C., A-thano, Napaporn, Jiang, Ing-Guey, Priyadarshi, Akshay, Liu, Ji-Feng
Hot Jupiters should initially form at considerable distances from host stars and subsequently migrate towards inner regions, supported directly by transit timing variation (TTV). We report the TTV of K2-237b, using reproduced timings fitted from \tex
Externí odkaz:
http://arxiv.org/abs/2409.07865
Autor:
Chen, Ching-Hsiu, Hsu, Wei-Hao, Oishi-Tomiyasu, Ryoko, Lee, Chi-Cheng, Chu, Ming-Wen, Hwang, Ing-Shouh
Water hydrogen bonding is extremely versatile; approximately 20 ice structures and several types of clathrate hydrate structures have been identified. These crystalline water structures form at temperatures below room temperature and/or at high press
Externí odkaz:
http://arxiv.org/abs/2409.00415
Autor:
Eldebiky, Amro, Zhang, Grace Li, Yin, Xunzhao, Zhuo, Cheng, Lin, Ing-Chao, Schlichtmann, Ulf, Li, Bing
Deep neural networks (DNNs) have made breakthroughs in various fields including image recognition and language processing. DNNs execute hundreds of millions of multiply-and-accumulate (MAC) operations. To efficiently accelerate such computations, ana
Externí odkaz:
http://arxiv.org/abs/2407.03738
Publikováno v:
March 2024, MNRAS, 528, 7202
We report the conditional occurrences between three planetary types: super-Earths (m sin i $<$ 10 M$_\oplus$, P $<$ 100 days), warm Jupiters (m sin i $>$ 95 $M_\oplus$, 10 $<$ P $<$ 100 days), and cold Jupiters (m sin i $>$ 95 M$_\oplus$, P $>$ 400 d
Externí odkaz:
http://arxiv.org/abs/2402.17212
We propose a novel energy-aware federated learning (FL)-based system, namely SusFL, for sustainable smart farming to address the challenge of inconsistent health monitoring due to fluctuating energy levels of solar sensors. This system equips animals
Externí odkaz:
http://arxiv.org/abs/2402.10280
Autor:
Fang, Chung-Kai, Chuang, Cheng-Hao, Yang, Chih-Wen, Guo, Zheng-Rong, Hsu, Wei-Hao, Wang, Chia-Hsin, Hwang, Ing-Shouh
Surfaces (interfaces) dictate many physical and chemical properties of solid materials and adsorbates considerably affect these properties. Nitrogen molecules, which are the most abundant constituent in ambient air, are considered to be inert. Our st
Externí odkaz:
http://arxiv.org/abs/2401.16737
Autor:
Jiang, Mengnan, Wang, Jingcun, Eldebiky, Amro, Yin, Xunzhao, Zhuo, Cheng, Lin, Ing-Chao, Zhang, Grace Li
Deep neural networks (DNNs) have demonstrated remarkable success in various fields. However, the large number of floating-point operations (FLOPs) in DNNs poses challenges for their deployment in resource-constrained applications, e.g., edge devices.
Externí odkaz:
http://arxiv.org/abs/2312.05875
Hyperdimensional Computing (HDC) is a brain-inspired and light-weight machine learning method. It has received significant attention in the literature as a candidate to be applied in the wearable internet of things, near-sensor artificial intelligenc
Externí odkaz:
http://arxiv.org/abs/2312.00454