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TechRxiv 2021年

作者： Trindade, Alessandro Galvão, Edilson Cordeiro, Lucas The Post-graduate Program in Electrical Engineering Manaus Brazil Department of Electricity Federal University of Amazonas Manaus Brazil School of Computer Science The University of Manchester United Kingdom

Annual global energy consumption growth is around 1.3% with forecasts until 2040. Photovoltaic systems became a suitable alternative to nuclear and fossil energy generation. In order to support this technology’s dissemination, we develop and evaluate an automated formal synthesis approach that assists in decision-making for off-grid systems. Our proposed approach, called PVz, is based on a variant of the counterexample-guided inductive synthesis;it has a multi-core feature, which can obtain the optimal sizing of photovoltaic systems focusing on Life Cycle Cost analysis. Given the electrical needs of a home, we seek a set of electrical equipment with the best possible combination of devices that meet the specified requirements. We calculate all costs related to maintenance over 20 years. The results presented are based on seven case studies;some of them are real ones from the Amazon region in Brazil. The same case studies were solved by a commercial optimization tool. Our technique and the commercial tool results were validated with popular simulation software to perform a fair comparison. Furthermore, we analyze some topics such as run-time, optimal solution, and configuration of the resulting systems. We claim that our technique is advantageous compared to the existing approaches in the literature. © 2021, CC BY-NC-SA.

关键词： Decision making

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Visuotactile Sensor Enabled Pneumatic Device Towards Compliant Oropharyngeal Swab Sampling

arXiv

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arXiv 2023年

作者： Li, Shoujie He, Mingshan Ding, Wenbo Ye, Linqi Wang, Xueqian Tan, Junbo Yuan, Jinqiu Zhang, Xiao-Ping Tsinghua Shenzhen International Graduate School Shenzhen518055 China The Department of Mechanical Engineering Seoul National University Seoul Korea Republic of The Department of Intelligent Control Qianyuan Institute of Science Hangzhou310024 China Clinical Research Center The Seventh Affiliated Hospital Sun Yat-sen University Guangdong Shenzhen518107 China The Department of Electrical Computer and Biomedical Engineering Ryerson University TorontoONM5B 2K3 Canada

Manual oropharyngeal (OP) swab sampling is an intensive and risky task. In this article, a novel OP swab sampling device of low cost and high compliance is designed by combining the visuo-tactile sensor and the pneumatic actuator-based gripper. Here, a concave visuo-tactile sensor called CoTac is first proposed to address the problems of high cost and poor reliability of traditional multi-axis force sensors. Besides, by imitating the doctor’s fingers, a soft pneumatic actuator with a rigid skeleton structure is designed, which is demonstrated to be reliable and safe via finite element modeling and experiments. Furthermore, we propose a sampling method that adopts a compliant control algorithm based on the adaptive virtual force to enhance the safety and compliance of the swab sampling process. The effectiveness of the device has been verified through sampling experiments as well as in vivo tests, indicating great application potential. The cost of the device is around 30 US dollars and the total weight of the functional part is less than 0.1 kg, allowing the device to be rapidly deployed on various robotic arms. Videos, hardware, and source code are available at: https://***/view/swab-sampling/. Copyright © 2023, The Authors. All rights reserved.

关键词： Pneumatic actuators

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Application of Deep Artificial Neural Network to Model Characteristic Fluctuation of Multi-Channel Gate-All-Around Silicon Nanosheet and Nanofin MOSFETs Induced by Random Nanosized Metal Grains

Application of Deep Artificial Neural Network to Model Chara...

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IEEE Electron Devices Technology and Manufacturing Conference (EDTM)

作者： Sagarika Dash Yiming Li Wen-Li Sung Parallel and Scientific Computing Laboratory National Yang-Ming Chiao Tung University Hsinchu Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang-Ming Chiao Tung University Hsinchu Taiwan Institute of Communications Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Department of Electronics and Electrical Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Institute of Biomedical Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Center for mm Wave Smart Radar System and Technologies National Yang-Ming Chiao Tung University Hsinchu Taiwan

In this work, we propose a deep artificial neural network (D-ANN) to estimate the work function fluctuation (WKF) on 4-channel stacked gate-all-around (GAA) silicon (Si) nanosheet (NS) and nanofin (NF) MOSFET devices for the first time. The 2-layered simple deep model can well predict the transfer characteristics for both NS/NF FET with a large number of (128) input features, utilizing considerably lesser (1100 samples) data uniformly. The resultant model is evaluated by the $\mathrm{R}^{2}$ score and RMSE to witness its competency and the average error is $< 4\%$ . We do also discuss the circuit simulation possibility by applying the ANN approach.

关键词： Semiconductor device modeling MOSFET Gallium arsenide Artificial neural networks Predictive models Logic gates Silicon

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Development of Educational Game for Indonesian History Lesson Focusing on Indonesia Pre-Literacy Relics 'Prehistoria' for Grade X High School Student

Development of Educational Game for Indonesian History Lesso...

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2020 international Conference on computer engineering, Network, and Intelligent Multimedia, CENIM 2020

作者： Nugroho, Supeno Mardi Susiki Rahman, Muhammad Daffa Abiyyu Hariadi, Mochamad Arief, Muhammad Faculty of Intelligent Electrical and Informatics Technology Sepuluh Nopember Institute of Technology Computer Engineering Department Surabaya Indonesia Tokyo University of Technology Media Science Program Graduate School of Bionics Computer and Media Sciences Tokyo Japan

ISBN: (纸本)9781728182834

The development of game technology has opened up new possibilities in learning methods through educational games. However, in Indonesia, the application of this concept is lacking. One lesson that can benefit from educational games is Indonesian History in class X, with a focus on history in the pre-literacy period. This study aims to create a puzzle-Adventure type of digital game that can help educate students about the pre-literacy period, developed with Unity, and uses WebGL as a target device while referring to Indonesia's revised 2013 national curriculum. The result of this research is the creation of a digital game that can be played on average of 254.36 seconds, with potential for educational use. A survey result shows that many of the ancient objects and some of the ages are well-recognized. However, the survey also shows many of the gameplay aspects, such as UI, gameplay features, and adventure elements, need improvements. © 2020 IEEE.

关键词： Surveys

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Terahertz Landau Polaritons in Nano-slots: Ultrastrong Coupling under Extreme Spatial Confinement

Terahertz Landau Polaritons in Nano-slots: Ultrastrong Coupl...

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international Conference on Infrared and Millimeter Waves

作者： Dasom Kim Sunghwan Kim Dukhyung Lee Shuang Liang Fuyang Tay Michael J. Manfra Dai-Sik Kim Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Physics Long-wavelength Nanotechnology Laboratory and Quantum Photonics Institute Ulsan National Institute of Science and Technology (UNIST) Ulsan South Korea Department of Physics and Astronomy Purdue University West Lafayette IN USA Birck Nanotechnology Center Purdue University West Lafayette IN USA Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette IN USA School of Materials Engineering Purdue University West Lafayette IN USA Department of Physics and Astronomy Rice University Houston TX USA Department of Material Science and NanoEngineering Rice University Houston TX USA

We report ultrastrong coupling of the cyclotron resonance of a two-dimensional electron gas in a GaAs quantum well to terahertz cavity photons under extreme confinement to the nanometer scale. This was realized by an array of nano-slots fabricated close to the quantum well layer on the GaAs substrate. Our terahertz magnetospectroscopic measurements revealed two polariton branches as a function of applied magnetic field. While the photon-like part of the two polariton branches was clearly observed, the matter-like part was generally elusive. Our electromagnetic simulations quantitatively reproduce our observation for the upper-polariton branch. However, for the lower-polariton branch, our simulations predict a pronounced resonance, which was absent in experimental spectra. This discrepancy may be a consequence of the breakdown of the dipole approximation in this extreme confinement situation.

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Recurrence plots and convolutional neural networks applied to nonintrusive load monitoring

Recurrence plots and convolutional neural networks applied t...

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2020 IEEE Power and Energy Society General Meeting, PESGM 2020

作者： Cavalca, Diego L. Fernandes, Ricardo A. S. Federal University of São Carlos Graduate Program in Computer Science São Carlos Brazil Federal University of São Carlos Electrical Engineering Department São Carlos Brazil

ISBN: (纸本)9781728155081

The need to increasingly promote the efficient use of electricity for residential consumers motivated some researches to obtain solutions that allow the identification of loads for use in demand response programs and in the energy consumption disaggregation. Recently, the use of Convolutional Neural Networks for load identification has been common. However, it is necessary to transform the temporal signal into an image. In this sense, the present paper proposes a novel feature engineering stage, based on Recurrence Plots, to obtain the images for Nonintrusive Load Monitoring. In order to prove its effectiveness, the Recurrence Plots were compared to the Gramian Angular Difference Fields, which had already been applied in this context. For this purpose, it was used the REDD dataset, in which only the low frequency data measured in the main distribution panel were considered. Individual load measurements were only used for the labelling of the 90-seconds windows. The Convolutional Neural Network was trained and validated, considering two different strategies (multi-label and binary models), obtaining an F1-score of 66.05% and 72.65%, respectively. © 2020 IEEE.

关键词： Machine learning

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Magnetically tuned continuous transition from weak to strong coupling in terahertz magnon polaritons

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Physical Review Research 2023年第1期5卷 L012039-L012039页

作者： Andrey Baydin Kenji Hayashida Takuma Makihara Fuyang Tay Xiaoxuan Ma Wei Ren Guohong Ma G. Timothy Noe, II Ikufumi Katayama Jun Takeda Hiroyuki Nojiri Shixun Cao Motoaki Bamba Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Smalley-Curl Institute Rice University Houston Texas 77005 USA Division of Applied Physics Graduate School of Engineering Hokkaido University Sapporo Hokkaido 060-8628 Japan Department of Physics and Astronomy Rice University Houston Texas 77005 USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas 77005 USA Department of Physics International Center of Quantum and Molecular Structures and Materials Genome Institute Shanghai University 200444 Shanghai China Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama 240-8501 Japan Institute for Materials Research Tohoku University Sendai 980-8577 Japan The Hakubi Center for Advanced Research Kyoto University Kyoto 606-8502 Japan Department of Physics I Kyoto University Kyoto 606-8502 Japan PRESTO Japan Science and Technology Agency Kawaguchi 332-0012 Japan Department of Materials Science and NanoEngineering Rice University Houston Texas 77005 USA

Depending on the relative rates of coupling and dissipation, a light-matter coupled system is either in the weak- or strong-coupling regime. Here, we present a unique system where the coupling rate continuously increases with an externally applied magnetic field while the dissipation rate remains constant, allowing us to monitor a weak-to-strong coupling transition as a function of magnetic field. We observed a Rabi splitting of a terahertz magnon mode in yttrium orthoferrite above a threshold magnetic field of ∼14 T. Based on a microscopic theoretical model, we show that with increasing magnetic field the magnons transition into magnon polaritons through an exceptional point, which will open up new opportunities for in situ control of non-Hermitian systems.

关键词： Antiferromagnetism High magnetic fields Magneto-optics Magnons Polaritons Non-Hermitean systems Terahertz time-domain spectroscopy Transfer matrix method

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Novel diamond shuttle to deliver flexible neural probe with reduced tissue compression

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Microsystems & Nanoengineering 2020年第1期6卷 903-915页

作者： Kyounghwan Na Zachariah J.Sperry Jiaao Lu Mihaly Voroslakos Saman S.Parizi Tim M.Bruns Euisik Yoon John P.Seymour Electrical Engineering&Computer Science Department University of MichiganAnn ArborMI 48105USA Biomedical Engineering Department University of MichiganAnn ArborMI 48105USA Biointerfaces Institute University of MichiganAnn ArborMI 48105USA The Neuroscience Institute New York UniversityNew YorkNY 10016USA Center for Nanomedicine Institute for Basic Science(IBS)Seoul 03722Korea Graduate Program of Nano Biomedical Engineering(Nano BME) Yonsei-IBS InstituteYonsei UniversitySeoul 03722Korea Vivian L Smith Department of Neurosurgery University of Texas Health Science CenterHoustonTX 77030USA Department of Electrical and Computer Engineering Rice UniversityHoustonTX 77005USA

The ability to deliver flexible biosensors through the toughest membranes of the central and peripheral nervous system is an important challenge in neuroscience and neural *** devices implanted through dura mater and thick epineurium would ideally create minimal compression and acute damage as they reach the neurons of *** demonstrate that a three-dimensional diamond shuttle can be easily made with a vertical support to deliver ultra-compliant polymer microelectrodes(4.5-µm thick)through dura mater and thick *** diamond shuttle has 54%less cross-sectional area than an equivalently stiff silicon shuttle,which we simulated will result in a 37%reduction in blood vessel *** also discovered that higher frequency oscillation of the shuttle(200Hz)significantly reduced tissue compression regardless of the insertion speed,while slow speeds also independently reduced tissue *** and recording performance are demonstrated in rat and feline models,but the large design space of these tools are suitable for research in a variety of animal models and nervous system targets.

关键词： sectional neural thick

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EA-CNN: Enhanced attention-CNN with explainable AI for fruit and vegetable classification

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Heliyon 2024年第23期10卷 e40820页

作者： Khan, Zeshan Aslam Waqar, Muhammad Cheema, Khalid Mehmood Bakar Mahmood, Ali Abu Ain, Quratul Chaudhary, Naveed Ishtiaq Alshehri, Abdullah Alshamrani, Sultan S. Zahoor Raja, Muhammad Asif International Graduate Institute of Artificial Intelligence National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin ROC Douliou 64002 Taiwan Department of Electronic Engineering Fatima Jinnah Women University Rawalpindi Pakistan Department of Electrical and Computer Engineering International Islamic University Islamabad 44000 Pakistan Department of Business Management Global Banking School London United Kingdom Future Technology Research Center National Yunlin University of Science and Technology Section 3 123 University Road Yunlin ROC Douliu 64002 Taiwan Department of Information Technology Faculty of Computing and Information Al-Baha University Alaqiq 65779-7738 Saudi Arabia Department of Information Technology College of Computer and Information Technology Taif University Taif 21944 Saudi Arabia

The quality of vegetables and fruits are judged by their visual features. Misclassification of fruits and vegetables lead to a financial loss. To prevent the loss, superstores need to classify fruits and vegetables in terms of size, color and shape. To improve the accuracy of models for classifying fruits and vegetables, researchers have introduced various CNN architectures like VGG16, AlexNet, DenseNet-121 and different attention-based variants by compromising models' complexity leading to high computational cost and overlooking feature's contribution for interpretable predictions. Additionally, the major drawback in most of the existing works is the utilization of the limited dataset and number of classes for fruit and vegetable classification task instead of the benchmark dataset like Fruit-360 which comprises of 141 distinct fruit and vegetable classes. In this study, an explainable artificial intelligence (XAI) driven enhanced attention-CNN (EA-CNN) is proposed for accomplishing the fruit and vegetable classification task accurately and efficiently. The proposed EA-CNN model (a) detects the class of fruits and vegetable accurately through visual features by manipulating undiscover customized pooling technique and enhanced attention feature extraction mechanism, (b) classifies the fruits and vegetables efficiently through a simplified architecture, (c) provides interpretable predictions through XAI approach. By utilizing entire fruit-360 database, this research noteworthily enhances the model's capability to classify wide range of fruits and vegetables, thus providing an effective and reliable solution for practical applications. The proposed study outclasses baseline models with regard to accuracy and computational cost on fruit-360 benchmark dataset. EA-CNN achieves better accuracy of 98.1 % in smaller number of iterations as compared to benchmark models. Moreover, to further prove the efficiency, generalization ability, robustness, scalability and adaptabilit

关键词： Classification Convolutional neural networks Deep learning Explainable AI

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Broadband Coherent Wave Control Through Photonic Collisions at Time Interfaces

arXiv

引用

arXiv 2022年

作者： Galiffi, Emanuele Xu, Gengyu Yin, Shixiong Moussa, Hady Ra'di, Younes Alù, Andrea Photonics Initiative Advanced Science Research Center City University of New York 85 St. Nicholas Terrace New York10031 United States Department of Electrical Engineering City College City University of New York United States Physics Program Graduate Center City University of New York United States Department of Electrical Engineering and Computer Science Syracuse University SyracuseNY13244 United States

Coherent wave control exploits the interference among multiple waves impinging on a system to suppress or enhance outgoing signals based on their relative phase and amplitude. This process inherently requires the combination of non-Hermiticity, in order to enable energy exchanges among the waves, and spatial interfaces in order to tailor their scattering. Here we explore the temporal analogue of this phenomenon, based on time-interfaces that support instantaneous non-Hermitian scattering events for photons. Based on this mechanism, we demonstrate ultra-broadband temporal coherent wave control and the photonic analogue of mechanical collisions with phase-tunable elastic features. We apply them to erase, enhance and reshape arbitrary pulses by suitably tailoring the amplitude and phase of counterpropagating signals. Our findings provide a pathway to effectively sculpt broadband light with light without requiring spatial boundaries, within an ultrafast and low-energy platform. © 2022, CC BY.

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