The Neural Networks (NN) model which is incorporated in the control system design has been studied, and the results show better performance than the mathematical model approach. However, some studies consider that onl...
详细信息
The Neural Networks (NN) model which is incorporated in the control system design has been studied, and the results show better performance than the mathematical model approach. However, some studies consider that only offline NN model learning and does not use the online NN model learning directly on the control system. As a result, the controller's performance decreases due to changes in the system environment from time to time. The Reinforcement Learning (RL) method has been investigated intensively, especially Model-based RL (Mb-RL) to predict system dynamics. It has been investigated and performs well in making the system more robust to environmental changes by enabling online learning. This paper proposes online learning of local dynamics using the Mb-RL method by utilizing Long Short-Term Memory (LSTM) model. We consider Model Predictive Control (MPC) scheme as an agent of the Mb-RL method to control the regulatory trajectory objectives with a random shooting policy to search for the minimum objective function. A nonlinear Mass Spring Damper (NMSD) system with parameter-varying linear inertia is used to demonstrate the effectiveness of the proposed method. The simulation results show that the system can effectively control high-oscillating nonlinear systems with good performance.
A strategy that combines experiment and simulation to design and optimize electromagnetic (EM) metamaterial absorbers containing a periodic porous structure is described. The approach provides the ability to produce a...
A strategy that combines experiment and simulation to design and optimize electromagnetic (EM) metamaterial absorbers containing a periodic porous structure is described. The approach provides the ability to produce absorbers that meet multiple user-specified objectives. Using the measured intrinsic properties of the baseline materials as an input to EM-field based computational modelling and optimization, absorption by the studied metamaterials measured by their reflection loss (RL) increases significantly. The resulting metamaterials have the potential for lower cost and lighter weight while providing greater protection than traditional metal gaskets and foams.
The manufacturing process of all-solid-state batteries necessitates the use of polymer ***,these binders,being ionic insulators by nature,can adversely affect charge transport within composite cathodes,thereby impacti...
详细信息
The manufacturing process of all-solid-state batteries necessitates the use of polymer ***,these binders,being ionic insulators by nature,can adversely affect charge transport within composite cathodes,thereby impacting the rate performance of the *** this work,we aim to investigate the impact of fabrication methods,specifically the solvent-free dry process versus the slurry-cast wet process,on binder distribution and charge transport in composite cathodes of solid-state *** the dry process,the binder forms a fibrous network,while the wet process results in binder coverage on the surface of cathode active *** difference in microstructure leads to a notable 20-fold increase in ionic conductivity in the dry-processed ***,the cells processed via the dry method exhibit higher capacity retention of 89%and 83%at C/3 and C/2 rates,respectively,in comparison to 68%and 58%for the wet-processed cells at the same *** findings provide valuable insights into the influence of fabrication methods on binder distribution and charge transport,contributing to a better understanding of the binder’s role in manufacturing of all-solid-state batteries.
This paper presents a dendrite-like device that discriminates spatiotemporal patterns of pulses for parallel processing in 3D neuromorphic architectures. The device utilizes the ferroelectric layer in a segmented mult...
This paper presents a dendrite-like device that discriminates spatiotemporal patterns of pulses for parallel processing in 3D neuromorphic architectures. The device utilizes the ferroelectric layer in a segmented multi-gate FeFET design to detect a consecutive sequence of input pulses. Experimental results demonstrate successful emulation of highly selective sequence discrimination in dendrites of neurons in the cortex and highlight up to 100× signal-margin (output current differences). This nanodendrite design offers a neuromorphic solution to thermally scalable parallel processing in 3D systems.
Pet owners experience difficulty in understanding their pets' body language and its implications for animal welfare, given that animals cannot utilize human speech to communicate their emotions and health conditio...
Pet owners experience difficulty in understanding their pets' body language and its implications for animal welfare, given that animals cannot utilize human speech to communicate their emotions and health conditions. However, previous experiments for analyzing cat behavior have demonstrated that cats are precisely expressive. DeepCat, a deep-learning approach developed in this study, translates cats' body language signals, enabling owners to discern their feline companions' intended messages and emotional states. Our DeepCat model was trained on a dataset comprising 10,000 cat images, implementing automatic labeling to track key features, including the tail, eyes, and mouth. Presented as a Flutter application, DeepCat can function everywhere, allowing owners to easily monitor their cats and make informed decisions in situations that require caution. This paper discusses the potential benefits and limitations of DeepCat and provides suggestions for future research in this domain.
Bulk switching RRAM devices have emerged to address nonidealities of filamentary RRAM for AI at the edge. However, long retention and high endurance needed for continual on-chip learning have yet to be demonstrated. H...
详细信息
ISBN:
(数字)9798350365429
ISBN:
(纸本)9798350365436
Bulk switching RRAM devices have emerged to address nonidealities of filamentary RRAM for AI at the edge. However, long retention and high endurance needed for continual on-chip learning have yet to be demonstrated. Here, we report a filament-free and multilevel bulk RRAM (b-RRAM) technology with long retention and high endurance. The oxygen vacancy gradient across the $\text{TiO}_{\mathrm{x}}$ switching layer and $\text{Al}_{2}\mathrm{O}_{3}$ tunnel barrier are designed to suppress filament formation and achieve multilevel switching through modulation of oxygen vacancy distribution. AI-Ti-O oxygen barrier enables reliable switching with high uniformity, retention and endurance. We develop a compact model that captures both DC and pulse switching. $\mathrm{M}\Omega$ -level resistance and switching current nonlinearity allow highly accurate read/write operations and matrix vector multiplications (MVM) in selectorless b-RRAM crossbars. A neuro-inspired few-shot learning (FSL) algorithm based on dendritic computation and behavioral time plasticity (BTSP) is mapped onto b-RRAM crossbar arrays. Weights are continuously updated on-chip to learn shortest navigation to reward within a few trials in a 2D maze. We also present FSL of large-size images with hyperdimensional (HD) computing using our b-RRAM model. System-level simulations with 64-level b-RRAM arrays show an increase in accuracy by 5.9 % and 5.4 % for a 5-way 10-shot learning of CIFAR-100 and CUB-200 datasets as compared to the state-of-the-art FSL-HD.
Technologies developed at universities are direct means to conceive a teaching plan for promoting science, technology, engineering and mathematics (STEM) at the K-12 level of education. This work-in-progress develops ...
详细信息
This paper presents a wearable skin patch for wireless measurements of protein biomarkers in dermal interstitial fluid (ISF). ISF is extracted from the skin using a microneedle (MN)-based, vacuum-assisted technique an...
This paper presents a wearable skin patch for wireless measurements of protein biomarkers in dermal interstitial fluid (ISF). ISF is extracted from the skin using a microneedle (MN)-based, vacuum-assisted technique and autonomously transported through the patch via vacuum pressure. This device was used for quantitative measurements of C-X-C motif chemokine ligand 9 (CXCL9), a biomarker for autoimmune diseases and inflammation, which could be detected from 10 pg/mL to 1,000 pg/mL in phosphate-buffered saline (PBS) with a lower limit of detection of 1.33 pg/mL. Proof-of-concept was demonstrated by performing measurements on cadaver porcine skin dermally injected with ISF simulant spiked with CXCL9, which could be detected at 100 and 1,000 pg/mL, thus validating the functionality of this wearable sensor.
This paper presents a design concept of an innovative wearable device for brain wave detection and stimulation to aid sleep. Sleep's importance for a healthy life emphasizes the value of studying the application o...
详细信息
ISBN:
(数字)9798350368239
ISBN:
(纸本)9798350368246
This paper presents a design concept of an innovative wearable device for brain wave detection and stimulation to aid sleep. Sleep's importance for a healthy life emphasizes the value of studying the application of technology to improve sleep quality for individuals unable to receive a good night's rest. Utilizing electroencephalography (EEG) for accurate sleep tracking, the device aims to be portable and efficient. It includes the EEG sensing and processing module, adaptive control and machine learning module, and electronic stimulation module, working together to guide the brain toward relaxation. Preliminary results demonstrate promising performances or necessities of the subsystems of the proposed design.
This manuscript demonstrates the first cantilever actuator for highly targeted and directionally specific delivery of drug-eluting microneedles to the gastrointestinal (GI) tract from ingestible devices. The actuator ...
详细信息
暂无评论