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Dynamics of self-hybridized exciton–polaritons in 2D halide perovskites

Light(science & Applications) 2024年第1期13卷 13-22页

作者： Surendra B.Anantharaman Jason Lynch Christopher E.Stevens Christopher Munley Chentao Li Jin Hou Hao Zhang Andrew Torma Thomas Darlington Francis Coen Kevin Li Arka Majumdar PJames Schuck Aditya Mohite Hayk Harutyunyan Joshua R.Hendrickson Deep Jariwala Department of Electrical and Systems Engineering University of PennsylvaniaPhiladelphiaPA19104USA KBR Inc. BeavercreekOH45431USA Air Force Research Laboratory Sensors DirectorateWright-Patterson Air Force BaseOH45433USA Department of Physics University of WashingtonSeattleWA98195USA Department of Physics Emory UniversityAtlantaGA30322USA Department of Chemical and Biomolecular Engineering Rice UniversityHoustonTX77005USA Department of Materials Science and Nanoengineering Rice UniversityHoustonTX77005USA Applied Physics Program Smalley‐Curl InstituteRice UniversityHoustonTX77005USA Department of Mechanical Engineering Columbia UniversityNew YorkNY10027USA Department of Electrical and Computer Engineering University of WashingtonSeattleWA98195USA

Excitons,bound electron–hole pairs,in two-dimensional hybrid organic inorganic perovskites(2D HOIPs)are capable of forming hybrid light-matter states known as exciton-polaritons(E–Ps)when the excitonic medium is confined in an optical *** the case of 2D HOIPs,they can self-hybridize into E–Ps at specific thicknesses of the HOIP crystals that form a resonant optical cavity with the ***,the fundamental properties of these self-hybridized E–Ps in 2D HOIPs,including their role in ultrafast energy and/or charge transfer at interfaces,remain ***,we demonstrate that>0.5µm thick 2D HOIP crystals on Au substrates are capable of supporting multiple-orders of self-hybridized E–P *** E–Ps have high Q factors(>100)and modulate the optical dispersion for the crystal to enhance sub-gap absorption and *** varying excitation energy and ultrafast measurements,we also confirm energy transfer from higher energy E–Ps to lower energy E–***,we also demonstrate that E–Ps are capable of charge transport and transfer at *** findings provide new insights into charge and energy transfer in E–Ps opening new opportunities towards their manipulation for polaritonic devices.

关键词： charge polar excitation

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An Optimal Framework for SDN Based on Deep Neural Network

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computers, Materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

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A 3D Dual-band electrically Small Monopole Antenna for Internet of Sea Applications

A 3D Dual-band Electrically Small Monopole Antenna for Inter...

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2021 IEEE International Symposium on Antennas and Propagation and North American Radio science Meeting, APS/URSI 2021

作者： Liao, Hanguang Bilal, Rana Muhammad Shamim, Atif Electrical and Computer Engineering Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (纸本)9781728146706

Sensing and retrieving data from ocean to land are challenging and expensive tasks, while the Internet of Sea (IoS) concept can help to monitor ocean environment in a low-cost way. In this paper, an electrically Small (ES) dual-band monopole antenna is proposed for the IoS application. Dual-band operation (GSM-900, LoRa, and BLE bands) and vertical polarization are maintained in a very compact size. The proposed antenna operates as a folded monopole antenna at 900MHz, and as a simple monopole antenna at 2.4 GHz, by combining the top-loaded folded monopole antenna and the 2-layer monopole feeding structure. The proposed antenna has ka of 0.45 at the LB, with a decent polarization purity and radiation efficiency of 54%. The proposed antenna is designed with a low-cost additive manufacturing material system. © 2021 IEEE.

关键词： Monopole antennas

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More Efficient Training Strategy to Leverage Neurons in Neural Network

More Efficient Training Strategy to Leverage Neurons in Neur...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Cheng-Fu Liou Yi-Cheng Yu Research Labs (MZAIR Labs) Meta Zen Artificial Intelligence Tainan Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

Comparing the structures of current neural networks and the biological brain, it can be observed that many mechanisms correspond to each other according to their functions. From the perspective of the biological brain, different components have different long-term or short-term memory effects, such as the hippopotamus. However, current neural networks do not pay much attention to this aspect. In this work, we incorporated many hypotheses or theories inspired by the territory of neurobiology to retain the learned knowledge. To start with, we follow the inspiration of the synaptic homeostasis hypothesis (SHY) [1] and add an additional training stage to the training process of the model, which can ensure that only the most important information remains intact and the insignificant synapse can be pruned. In other words, we divide the overall training process into two learning stages: synaptogenesis and synaptic sparsifying. We experimentally demonstrate that our novel learning strategy significantly outperforms the traditional solution in training a sequence of tasks at different times on three public datasets, which supports that the proposed method is more efficient for resource-limited edge devices.

关键词： Training Industrial electronics Neurons Homeostasis Task analysis Biological neural networks Synapses

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Wireless Health Monitoring for Calculating Vitals Device by Using IoT

Wireless Health Monitoring for Calculating Vitals Device by ...

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International Conference on Computational and Characterization Techniques in engineering & sciences (CCTES)

作者： G S Pradeep Ghantasala Mahaveer S Debopriya Ghosh Ananthakrishnan PS Abhishek Basavaraj Masali Susheel Kumar Singh Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bengaluru India Department of Electrical and Electronics Engineering Alliance University Bengaluru India Heera Lal Yadav Balika Degree College Lucknow UP

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

The fast evolution of the Internet of Things (IoT) has paved the way for innovative healthcare solutions. This paper affords the format and implementation of a wireless health monitoring device the use of IoT technology. The tool continuously tracks critical signs and signs along with coronary heart rate, blood pressure, and oxygen saturation, transmitting real-time facts to healthcare providers. The proposed solution enhances affected man or woman care with the useful resource of the usage of allowing early detection of anomalies and properly timed medical intervention. The paper discusses the architecture, hardware components, software program software integration, and functionality challenges, offering insights into future trends in IoT-enabled healthcare.

关键词： Wireless communication Medical services Transforms Propagation losses Market research Real-time systems Software Internet of Things Biomedical monitoring Monitoring

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Reliable Data Transmission through Private CBRS Networks

arXiv

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arXiv 2023年

作者： Kuo, Hsun-Yu Liu, Szu-Yu Huang, Chin-Ya Chen, Yu-Chi Xie, Meng-Hua The Bachelor Degree Program of Applied Science and Technology National Taiwan University of Science and Technology Taiwan The Dept. of Electronic and Computer Engineering National Taiwan University of Science and Technology Taiwan

We consider the use of a domain proxy assisted private citizen broadband radio service (CBRS) network and propose a Maximum Transmission Continuity (MTC) scheme to transmit Internet of Things (IoT) data reliably. MTC dynamically allocates available CBRS channels to sustain the continuity of data transmission without violating the channel access requirements. MTC allocates the granted CBRS channels according to the priority of each user, the instant channel access status, interference among users, and the fairness. The simulation results demonstrate the improvement in managing reliable IoT data transmission in the private CBRS network. Copyright © 2023, The Authors. All rights reserved.

关键词： Internet of things

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electrical Characteristic and Power Fluctuations of GAA Si NS CFETs by Simultaneously Considering Six Process Variation Factors

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 229-238页

作者： Kola, Sekhar Reddy Li, Yiming National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Biomedical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

Characteristic variability induced by process variation effect (PVE) is one of technological challenges in semiconductor industry. In this work, we computationally study electrical characteristic and power fluctuations induced by six factors of PVE of the gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field-effect-transistors (CFETs) which are formed by vertically stacking n-FET on top of p-FET. Among the six factors, NS thickness (TNS), NS width (WNS), and gate length (LG) are identified as crucial factors contributing to large variations in device characteristics. The p-FET exhibits substantial off-state current fluctuation (about 151%) due to the bottom parasitic channel leakages. Compared with the magnitudes of dynamic and short circuit powers, the static power is marginal, but it possesses the largest fluctuation (up to 148%). If we assume that each factor of PVE has the same probability distribution as the others and all are mutually independent, the statistical sum of their power fluctuations will exhibit more than 50% overestimations, compared with the results when all factors are considered simultaneously. © 2020 IEEE.

关键词： III-V semiconductors

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ConvNeXt Model for Breast Cancer Image Classification

ConvNeXt Model for Breast Cancer Image Classification

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Devin Setiawan Andrea Stevens Karnyoto Indo Intan Bens Pardamean Department of Electrical Engineering and Computer Science University of Kansas Lawrence United States Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Informatics Engineering Universitas Dipa Makassar Makassar Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331539603

ISBN: (纸本)9798331539610

Breast cancer is an occurrence of cancer that attacks breast tissue and is the most common cancer among women worldwide, affecting one in eight women. In this modern world, breast cancer image classification simplifies the process of analyzing, providing objective and accurate results. By leveraging machine learning algorithms and computer vision techniques, we developed breast cancer detection. The dataset is histopathology dataset from BreakHis and UNHAS Hospital. We chose the ConvNeXt-Tiny model then modified the classifier head as the proposed method. Before the dataset is processed by the model, we augment the images by applying random horizontal and vertical flips, adjustments to brightness, contrast, saturation, and hue using color jitter. The augmentation process simulates real-world variance and enhances the model's ability to generalize to unseen data. Our proposed model gained better performance (accuracy, F1-Score) results compared two other techniques to VGG16 and SVM. According to our experiments, the F1-Score for the ConvNeXt-Tiny model with classifier head modification is higher at 0.9516, than the gain for VGG16 at 0.9292, and the gain for the SVM at 0.83.

关键词： Support vector machines Accuracy Head Computational modeling Transfer learning Breast cancer Magnetic heads Data models Reliability Image classification

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Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using Random Forest, KNN, Decision Tree and Naïve Bayes 7

Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using ...

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7th IEEE International Conference on Information Technology and Digital Applications, ICITDA 2022

作者： Pohan, Husni Iskandar Suparta, Wayan Heryadi, Yaya Wibowo, Antoni Lukas Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

Dengue Hemorrhagic Fever is an acute viral infectious disease caused by the dengue virus. Transmitted through the bite of Aedes Mosquitoes and divided into 4 severity. Severity 1 and 2 are characterized by a decrease in platelet levels below normal and there is a change in hemoconcentration, while Severity 3 and 4 are included in Dengue Shock Syndrome (DSS). The purpose of the study was to classify the severity of dengue, based on age, gender, platelets, body temperature, bleeding, and also doctor's recommendation. The advancement of information technology is the reason for the development of medical science, especially with artificial intelligence. Abundant medical data becomes a source that can be processed in improving the quality of medical information. The method chosen is Random Forest, kNN, Decision Tree and Naïve Bayes. The dataset used is the medical records of all DHF patients for 30 months in the period Jan 2019 to June 2021, at the Nadhifa Al Ghiffari Clinic in Bojongsoang District, Bandung Regency. © 2022 IEEE.

关键词： Decision trees

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Expanding the Surgical Robotics Community: An Intuitive Sim-to-Real Control Framework for Raven-II with a Budget-Friendly Gamepad Controller

Expanding the Surgical Robotics Community: An Intuitive Sim-...

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International Symposium on Medical Robotics (ISMR)

作者： Mai Bui Natalie Chalfant Cuiling Sun Sean Fabrega Haonan Peng Kevin Huang Yun-Hsuan Su Department of Computer Science Mount Holyoke College South Hadley MA Department of Electrical and Computer Engineering University of Washington Seattle WA Picker Engineering Program Smith College Northampton MA

ISBN: (数字)9798350377118

ISBN: (纸本)9798350377125

This paper proposes a low-cost interface and refined digital twin for the Raven-II surgical robot. Previous simulations of the Raven-II, e.g. via the Asynchronous Multibody Framework (AMBF), presented salient drawbacks, including control inputs inconsistent with Raven-II software, and lack of stable, high-fidelity physical contact simulations. This work bridges both of these gaps, both (1) enabling robust, simulated contact mechanics for dynamic physical interactions with the Raven-II, and (2) developing a universal input format for both simulated and physical platforms. The method furthermore proposes a low cost, commodity game-controller interface for controlling both virtual and real realizations of Raven-II, thus greatly reducing the barrier to access for Raven-II research and collaboration. Overall, this work aims to eliminate the inconsistencies between simulated and real representations of the Raven-II. Such a development can expand the reach of surgical robotics research. Namely, providing end-to-end transparency between the simulated AMBF and physical Raven-II platforms enables a software testbed previously unavailable, e.g. for training real surgeons, for creating digital synthetic datasets, or for prototyping novel architectures like shared control strategies. Experiments validate this transparency by comparing joint trajectories between digital twin and physical testbed given identical inputs. This work may be extended and incorporated into recent efforts in developing modular or common software infrastructures for both simulation and control of real robotic devices, such as the Collaborative Robotics Toolkit (CRTK).

关键词： Training Medical robotics Costs Collaboration Surgery computer architecture Software

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