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arXiv 2023年

作者： Fried, Caleb Jordan Russell, B. Arnault, Ethan G. Huang, Bevin Lee, Gil-Ho Englund, Dirk Henriksen, Erik A. Fong, Kin Chung Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Earth and Planetary Sciences Harvard University CambridgeMA02138 United States Department of Physics Harvard University CambridgeMA02138 United States Raytheon BBN Quantum Engineering and Computing Group CambridgeMA02138 United States Department of Physics Washington University in St. Louis St. LouisMO United States Intelligence Community Postdoctoral Research Fellowship Program Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Pohang University of Science and Technology Pohang790-784 Korea Republic of

In high-sensitivity bolometers and calorimeters, the photon absorption often occurs at a finite distance from the temperature sensor to accommodate antennas or avoid the degradation of superconducting circuitry exposed to radiation. As a result, thermal propagation from the input to the temperature readout can critically affect detector performance. In this report we model the performance of a graphene bolometer, accounting for electronic thermal diffusion and dissipation via electron-phonon coupling at low temperatures in three regimes: clean, supercollision, and resonant scattering. Our results affirm the feasibility of a superconducting readout without Cooper-pair breaking by mid- and near-infrared photons, and provide a recipe for designing graphene absorbers for calorimetric single-photon detectors. We investigate the tradeoff between the input-readout distance and detector efficiency, and predict an intrinsic timing jitter of ∼2.7 ps. Based on our result, we propose a spatial-mode-resolving photon detector to increase communication bandwidth. Copyright © 2023, The Authors. All rights reserved.

关键词： Graphene

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Ferroelectric transistors based on shear-transformation-mediated rhombohedral-stacked molybdenum disulfide

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Nature Electronics 2024年第1期7卷 29-38页

作者： Yang, Tilo H. Liang, Bor-Wei Hu, Hsiang-Chi Chen, Fu-Xiang Ho, Sheng-Zhu Chang, Wen-Hao Yang, Liu Lo, Han-Chieh Kuo, Tzu-Hao Chen, Jyun-Hong Lin, Po-Yen Simbulan, Kristan Bryan Luo, Zhao-Feng Chang, Alice Chinghsuan Kuo, Yi-Hao Ku, Yu-Seng Chen, Yi-Cheng Huang, You-Jia Chang, Yu-Chen Chiang, Yu-Fan Lu, Ting-Hua Lee, Min-Hung Li, Kai-Shin Wu, Menghao Chen, Yi-Chun Lin, Chun-Liang Lan, Yann-Wen Department of Physics National Taiwan Normal University Taipei Taiwan Taiwan Semiconductor Research Institute National Applied Research Laboratories Hsinchu Taiwan Department of Electrophysics National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Physics National Cheng Kung University Tainan Taiwan School of Physics Huazhong University of Science and Technology Wuhan China Institute of Cellular and Organismic Biology Academia Sinica Taipei Taiwan Department of Mathematics and Physics University of Santo Tomas Manila Philippines Program for Semiconductor Devices Materials and Hetero-integration Graduate School of Advanced Technology National Taiwan University Taipei Taiwan Hsinchu Taiwan Department of Physics National Taiwan University Taipei Taiwan Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States

To develop low-power, non-volatile computing-in-memory device using ferroelectric transistor technologies, ferroelectric channel materials with scaled thicknesses are required. Two-dimensional semiconductors, such as molybdenum disulfide (MoS2), equipped with sliding ferroelectricity could provide an answer. However, achieving switchable electric polarization in epitaxial MoS2 remains challenging due to the absence of mobile domain boundaries. Here we show that polarity-switchable epitaxial rhombohedral-stacked (3R) MoS2 can be used as a ferroelectric channel in ferroelectric memory transistors. We show that a shear transformation can spontaneously occur in 3R MoS2 epilayers, producing heterostructures with stable ferroelectric domains embedded in a highly dislocated and unstable non-ferroelectric matrix. This diffusionless phase transformation process produces mobile screw dislocations that enable collective polarity control of 3R MoS2 via an electric field. Polarization–electric-field measurements reveal a switching field of 0.036 V nm−1 for shear-transformed 3R MoS2. Our sliding ferroelectric transistors are non-volatile memory units with thicknesses of only two atomic layers and exhibit an average memory window of 7 V with an applied voltage of 10 V, retention times greater than 104 seconds and endurance greater than 104 cycles. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

关键词： Molybdenum disulfide

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Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence

arXiv

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arXiv 2022年

作者： Jafari, Mahboobeh Shoeibi, Afshin Ghassemi, Navid Heras, Jonathan Ling, Sai Ho Beheshti, Amin Zhang, Yu-Dong Wang, Shui-Hua Alizadehsani, Roohallah Gorriz, Juan M. Acharya, U. Rajendra Rokny, Hamid Alinejad Internship in BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney SydneyNSW2052 Australia Data Science and Computational Intelligence Institute University of Granada Spain Department of Mathematics and Computer Science University of La Rioja La Rioja Spain Australia Data Analytics Lab Department of Computing Macquarie University SydneyNSW2109 Australia School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Deakin University VIC3217 Australia Department of Psychiatry University of Cambridge United Kingdom School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney SydneyNSW2052 Australia UNSW Data Science Hub The University of New South Wales SydneyNSW2052 Australia Research Centre Macquarie University Sydney2109 Australia

Myocarditis is a significant cardiovascular disease (CVD) that poses a threat to the health of many individuals by causing damage to the myocardium. The occurrence of microbes and viruses, including the likes of HIV, plays a crucial role in the development of myocarditis disease (MCD). The images produced during cardiac magnetic resonance imaging (CMRI) scans are low contrast, which can make it challenging to diagnose cardiovascular diseases. In other hand, checking numerous CMRI slices for each CVD patient can be a challenging task for medical doctors. To overcome the existing challenges, researchers have suggested the use of artificial intelligence (AI)-based computer-aided diagnosis systems (CADS). The presented paper outlines a CADS for the detection of MCD from CMR images, utilizing deep learning (DL) methods. The proposed CADS consists of several steps, including dataset, preprocessing, feature extraction, classification, and post-processing. First, the Z-Alizadeh dataset was selected for the experiments. Subsequently, the CMR images underwent various preprocessing steps, including denoising, resizing, as well as data augmentation (DA) via CutMix and MixUp techniques. In the following, the most current deep pre-trained and transformer models are used for feature extraction and classification on the CMR images. The findings of our study reveal that transformer models exhibit superior performance in detecting MCD as opposed to pre-trained architectures. In terms of DL architectures, the Turbulence Neural Transformer (TNT) model exhibited impressive accuracy, reaching 99.73% utilizing a 10-fold cross-validation approach. Additionally, to pinpoint areas of suspicion for MCD in CMRI images, the Explainable-based Grad Cam method was employed. © 2022, CC BY-NC-ND.

关键词： Diseases

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Reduction of interface defects in gate-recessed GaN HEMTs by neutral beam etching

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Materials Today Advances 2024年 23卷

作者： Yu, Chia Hao Chiang, Wei Hsiang Chen, Yi-Ho Samukawa, Seiji Wuu, Dong Sing Chung, Chin-Han Hsiao, Ching-Lien Horng, Ray Hua Institute of Electronics National Yang Ming Chiao Tung University Department of Materials Science and Engineering National Chung Hsing University Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Institute of Comunications Engineering National Yang Ming Chiao Tung University Department of Applied Materials and Optoelectronic Engineering National Chi Nan University International College of Semiconductor Technology National Yang Ming Chiao Tung University Thin Film Physics Division Department of Physics Chemistry and Biology (IFM) Linköping University

This study investigates and compares the impact of different etching techniques on the fabrication of GaN high electron mobility transistors (HEMTs) between the inductively coupled plasma reactive ion etching (ICP-RIE) and the neutral beam etching (NBE) for the gate recess. By conducting direct current analysis, it was found that devices manufactured using the NBE exhibited superior electrical performance as compared with those produced using the ICP-RIE. These enhanced electrical characteristics include a transconductance of up to 100.4 mS/mm, a threshold voltage (V_th) of −2.3 V, an on/off current ratio of 1.1 × 10⁹, a subthreshold swing (S.S.) of 99.63 mV/dec, and a remarkably low gate leakage current. Additionally, we noted varying degrees of hysteresis in the I–V characteristics were related to process disparities possibly leading to interface defects. Multi-frequency capacitance-voltage (C–V) measurements were used to identify the interface defects at the oxide/AlGaN interface of the gate. The results revealed that devices fabricated using the NBE exhibited a lower interface defect density as compared with those fabricated using the ICP-RIE, thereby elucidating the reduced hysteresis observed in the I–V characteristics. These findings indicated the significant advantages of the NBE process in the fabrication of GaN HEMTs. © 2024 The Authors

关键词： GaN HEMTs Gate recess Interface defects Multi-frequency C–V Neutral beam etching

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Case-based cybersecurity incident resolution 31

Case-based cybersecurity incident resolution

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31st International Conference on Software Engineering and Knowledge Engineering, SEKE 2019

作者： Colome, Marcelo Nunes, Raul Ceretta De Lima Silva, Luis Alvaro Graduate Program in Computer Science - PPGCC Applied Computing Department Federal University of Santa Maria Av. Roraima Campus UFSM Camobi Santa Maria RS Brazil

ISBN: (纸本)1891706489

Intelligent computing techniques have a paramount importance to the treatment of cybersecurity incidents. In such Artificial Intelligence (AI) context, while most of the algorithms explored in the cybersecurity domain aim to present solutions to intrusion detection problems, these algorithms seldom approach the correction procedures that are explored in the resolution of cybersecurity incident problems that already took place. In practice, knowledge regarding cybersecurity resolution data and procedures is being under-used in the development of intelligent cybersecurity systems, sometimes even lost and not used at all. In this context, this work proposes to integrate Case-Based Reasoning techniques and IODEF standard in order to retain concrete problem-solving experiences of cybersecurity incident resolution to be reused in the resolution of new incidents. Experimental results so far obtained with a Case-based Cybersecurity Incident Resolution System (CbCSecIRS) implemented show that information security knowledge can be retained in a reusable memory, so improving the resolution of new cybersecurity problems. © 2019 Knowledge Systems institute graduate School. All rights reserved.

关键词： Intrusion detection

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Magneto-optical Spectroscopy with RAMBO: A Table-Top 30 T Magnet

arXiv

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arXiv 2022年

作者： Tay, Fuyang Baydin, Andrey Katsutani, Fumiya Kono, Junichiro Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

Optically probing materials in high magnetic fields can provide enlightening insight into field-modified electronic states and phases, while optically driving materials in high magnetic fields can induce novel nonequilibrium many-body dynamics of spin and charge carriers. While there are high-field magnets compatible with standard optical spectroscopy methods, they are generally bulky and have limited optical access, which prohibit performing state-of-the-art ultrafast and/or nonlinear optical experiments. The Rice Advanced Magnet with Broadband Optics (RAMBO), a unique 30-T pulsed mini-coil magnet system with direct optical access, has enabled previously challenging experiments using femtosecond optical pulses, including time-domain terahertz spectroscopy, in cutting-edge materials placed in strong magnetic fields. Here, we review recent experimental advances made possible by the first-generation RAMBO setup. After summarizing technological aspects of combining optical spectroscopic techniques with the mini-coil magnet, we describe results of magneto-optical studies of a wide variety of materials, providing new insight into the states and dynamics of four types of quasiparticles in solids – excitons, plasmons, magnons, and phonons – in high magnetic fields. Copyright © 2022, The Authors. All rights reserved.

关键词： Magnets

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Explainable and Adaptable Augmentation in Knowledge Attention Network for Multi-Agent Deep Reinforcement Learning Systems

Explainable and Adaptable Augmentation in Knowledge Attentio...

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Artificial Intelligence and Knowledge Engineering (AIKE)

作者： Joshua Ho Chien-Min Wang Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei Taiwan Institute of Information Systems and Applications National Tsing Hua University Hsinchu Taiwan

ISBN: (数字)9781728187082

ISBN: (纸本)9781728187099

The scale of modem Artificial Intelligence systems has been growing and entering more research territories by incorporating Deep Learning (DL) and Deep Reinforcement Learning (DRL) methods. More specifically, multi-agent DRL methods have been widely applied to address the problems of high-dimensional computation, which interpret the conditions that real-world systems mainly encounter and the issues that require resolving. However, the current approaches of DL and DRL are often challenged for their untransparent and time-consuming modeling processes in their attempt to achieve a practical and applicable inference based on human-level perspective and acceptance. This paper presents an explainable and adaptable augmented knowledge attention network for multi-agent DRL systems, which uses game theory simulation to tackle the problem of non-stationarity at the beginning, while improving the learning exploration built upon the strategic ontology to achieve the learning convergence more efficiently for autonomous agents. We anticipate that our approach will facilitate future research studies and potential research inspections of emerging multi-agent DRL systems for increasingly complex and autonomous environments.

关键词： Knowledge engineering Adaptation models Reinforcement learning Ontologies Inspection Modems Game theory

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A prototype of Baby Monitoring Use Raspberry Pi

A prototype of Baby Monitoring Use Raspberry Pi

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International Conference on ICT For Smart Society (ICISS)

作者： Aldy Rudyansyah Harco Leslie Hendric Spits Warnars Ford Lumban Gaol Tokuro Matsuo BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Graduate School of Industrial Technology Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9781665404228

ISBN: (纸本)9781665404235

The security system in monitoring the room or something suspicious activity that can cause crimes in the field of information and technology as in private homes is indispensable. Aims to keep valuables from theft and loved ones like babies from kidnapping or reducing the risk of an accident in an unguarded infant activity. The use of CCTV still has constraints because some functions are still done manually such as should always move the record of the CCTV data every day to different memory so that there is waste in using memory. Moreover, the position of the camera can not be adjusted freely in the placement so that it can easily be destroyed by irresponsible people, and also ordinary CCTV needs electricity that is considerable in its use. This research is done to improve and facilitate the process of monitoring of baby activity and the room where the baby is called sleep or rest, all monitoring activities can be done using only a Web browser that can be accessed by a smartphone or desktop. The monitoring system is created using a program called RPi Cam that is installed on the Raspberry Pi with a Raspberry Camera module as a monitoring camera and a DHT22 sensor module as a room temperature monitor.

关键词： Cameras Monitoring Temperature sensors Pediatrics Temperature measurement Security Tools

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Exploration of Technology Home-based Learning Guidance for Parents and Students during the Covid-19 Pandemic

Exploration of Technology Home-based Learning Guidance for P...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Suzanna Suzanna Sasmoko Sasmoko Ford Lumban Gaol Tanty Oktavia Tokuro Matsuo BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9781728173986

With the sudden attack of the Corona Virus Disease 2019 (COVID-19), some 300 million children in the world have been forced to study at home because of the mass closure of schools that began on March 18, 2020. This has caused many obstacles in the teaching and learning process. Every effort is made to minimize the COVID-19 pandemic while ensuring the teaching and learning process is not interrupted. If the school closures too long and the child is trapped inside the house this will have a negative impact on the physical and mental health of the children. This situation makes parents become worried and look for alternative education in addition to formal schooling for their children. Of the various types of education offers that exist homeschooling or commonly known as home-based learning provides a way out for the current situation. Now children are quarantined in their homes and they will return to school once this epidemic fades. But with this disaster, parents' views on homeschooling or home-based learning can be different from before. They may still be marked if home-based learning can be a long-term education. With the existence of COVID-19, most parents might finally realize that education without formal schooling is not a crisis but an opportunity to take their children to a better future. This research was conducted by utilizing a descriptive qualitative method and within the descriptive qualitative method, the concept of document analysis would be utilized the most. It was expected that the results of this research would explore what type of technology parents could prepare for their children to use to initiate home-based learning.

关键词： COVID-19 Pediatrics Text analysis Pandemics Education Government Mental health

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A multi-agent system for optimizing physiological collection based on adaptive strategies

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Smart Health 2021年 19卷

作者： Aranda, Jorge Arthur Schneider Bavaresco, Rodrigo Simon da Silva Machado, Roger de Carvalho, Juliano Varella Corrêa, Adenauer Yamin Barbosa, Jorge Luis Victória Applied Computing Graduate Program (PPGCA) of University of Vale do Rio dos Sinos (UNISINOS) Av. Unisinos 950 São Leopoldo 93.022-750 RS Brazil Creative and Technological Sciences Institute of Feevale University ERS 239 2755 Novo Hamburgo RS 93525-075 RS Brazil Computer Science Graduate Program of Federal University of Pelotas Gomes Carneiro 1 Pelotas 96010-610 RS Brazil

Wearable devices have emerged from the evolution of communication and information technology, along with the miniaturization of electronic components. These devices monitor the user's physiology on a periodic basis and generally have low battery autonomy. This article proposes the Odin system, a multi-agent system that performs real-time analysis of physiological data in order to adapt the collection according to the user's health condition. Two types of adaptation were proposed in terms of adapting the collection. The first, wait-time adaptation (WTA), consists of collecting physiological data through a sensor defined as the main sensor, where the frequency of the collection is based on the user's condition. Meanwhile, the second, paused sensors adaptation (PSA), manages the activation status of secondary sensors when the main sensor suggests a possible risk to the user's health. An evaluation was implemented through two steps. First, a simulation was performed with requests control to optimize the parameters of the data collection. These results showed an increase of 214% in battery life in the adaptive scenario compared to one with no adaptivity. Second, Odin's adaptivity was evaluated in terms of a real dataset, which allowed for the reduction of the number of requests. This reduction optimized the battery consumption, with a 66% improvement over data collection with no adaptivity. © 2020 Elsevier Inc.

关键词： Adaptive systems Embedded systems Healthcare Wearable Devices

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