Designing a spiking neural network system for object recognition by Thong, Jing Yuan

“…Widely touted as the 3rd generation of neural networks, Spiking Neural Networks were introduced as an enhanced representation of working memory. …”
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Dissipative solitons with extreme spikes in the normal and anomalous dispersion regimes by Akhmediev, N., Soto-Crespo, J. M., Vouzas, Peter, Devine, N., Chang, Wonkeun

“…In this paper, one recent example is considered—dissipative solitons with extreme spikes (DSESs). It was found that DSESs exist in large regions of the parameter space of the complex cubic–quintic Ginzburg–Landau equation. …”
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Bayesian lesion estimation with a structured spike-and-slab prior by Menacher, A, Nichols, T, Holmes, C, Ganjgahi, H

“…Our method also accounts for underestimation of posterior variance due to variational inference by providing an approximate posterior sampling approach based on Bayesian bootstrap ideas and spike-and-slab priors with random shrinkage targets. …”

Biosorption of silver ions. by Toh, Guanhong.

“…In this project, ECH-chitosan beads, BCD grafted chitosan beads and native chitosan hydrogel beads are tested for adsorption of silver ions. pH is varied across the range of 4 to 8. All three types of chitosan beads are able to adsorb silver ions. …”
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A New Hyperbox Selection Rule and a Pruning Strategy for the Enhanced Fuzzy Min–Max Neural Network by Mohammed, Mohammed Falah, Chee, Peng Lim

“…In this paper, we extend our previous work on the Enhanced Fuzzy Min–Max (EFMM) neural network by introducing a new hyperbox selection rule and a pruning strategy to reduce network complexity and improve classification performance. …”
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Filmwise condensation of steam on pin fin arrays fabricated by selective laser melting by Ho, Jin Yao, Leong, Kai Choong

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Lessons From President Moon Jae In’s Housing Policy and The Road to Affordable Home Ownership in Seoul, South Korea by Cho, Kibong

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FPGA implementation of spiking convolutional neural networks for voice keyword recognition by Ng, Wei Soon

“…The spiking convolutional neural network (SCNN) is a hybrid model of both the spiking neural network (SNN) and convolutional neural network (CNN). …”
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Design of pinned and rigid bolted connections using BS 5950:2000 and Eurocode 3 by Xie, Yunshen.

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Preventing lithium-ion (li-ion) cell fire with an embedded extinguisher by Muhammad Azrie Bin Razale

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On the origin and underappreciated effects of ion doping in silica by Song, Xiaohui, Ding, Tao, Yao, Lin, Lin, Ming, Lee, Rachel Siew Tan, Liu, Cuicui, Sokol, Katarzyna, Yu, Le, Lou, David Xiong Wen, Chen, Hongyu

“…It is realized that, during the synthesis, the silica precursors are essentially ion-paired polyelectrolytes, whose nucleation depends on the concentration of the counter ions, and most importantly, the size/length of the poly(silicic acid). …”
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The role of ion exchange in the passivation of In(Zn)P nanocrystals with ZnS by Cho, Deok-Yong, Xi, Lifei, Boothroyd, Chris, Kardynal, Beata, Lam, Yeng Ming

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Filmwise condensation of steam on sinusoidal pin fin arrays : effects of fin height and fin pitch by Ho, Jin Yao, Leong, Kai Choong, Wong, Teck Neng

“…An experimental investigation on the use of sinusoidal pin fins to enhance filmwise condensation of steam on vertical plates was carried out. …”
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Building fame through tea: the Wu Family and the Manufacture of zisha teapots during the Ming and Qing dynasties by Gao, X, Hein, A

“…By examining the Wu family’s connection with the origin of zisha teapots, this study investigates how Ming literati used material culture to shape family reputation. …”

Bio-inspired categorization using event-driven feature extraction and spike-based learning by Zhao, Bo, Chen, Shoushun, Tang, Huajin

“…Bio-inspired, cortex-like, spikebased features are obtained through event-driven convolution and neural competition. The extracted spike feature patterns are then classified by a network of leaky integrate-and-fire (LIF) spiking neurons, in which the weights are trained using tempotron learning rule. …”
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Morphological learning in spiking neurons: a new hardware efficient maching learning method by Jahagirdar, Kavya

“…The latest developments in the research of spiking neural network models have shown that unlike the classic neural network models, these models communicate via precisely timed neuron spikes, thus making them a closer representation of the biological neurons. …”
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Design of a hybrid neural spike detection algorithm for implantable integrated brain circuits by Zeinolabedin, Seyed Mohammad Ali, Do, Anh Tuan, Yeo, Kiat Seng, Kim, Tony Tae-Hyoung

Subjects: “…Spike…”
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Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893) by Yusoff, Nooraini, Yusof, Yuhanis, Siraj, Fadzilah, Ahmad, Farzana Kabir

“…This study proposes sequence learning for the fish motion trajectory by using the Spike-Time dependent Plasticity (STDP) in the Spiking Neural Networks (SNNs). …”
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Origin of a topotactic reduction effect for superconductivity in infinite-layer nickelates by Zeng, Shengwei, Tang, Chi Sin, Luo, Zhaoyang, Chow, Lin Er, Lim, Zhi Shiuh, Prakash, Saurav, Yang, Ping, Diao, Caozheng, Yu, Xiaojiang, Xing, Zhenxiang, Ji, Rong, Yin, Xinmao, Li, Changjian, Wang, Renshaw Xiao, He, Qian, Breese, Mark B. H., Ariando, A., Liu, Huajun

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Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites by Jin, Tianli, Gan, Weiliang, Tan, Funan, Sernicola, Nicolo Roberto, Lew, Wen Siang, Piramanayagam, S. N.

“…The domain wall motion was controlled with the use of synthetic pinning sites, which were introduced by boron (B+) ion-implantation for local modification of the magnetic properties. …”
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