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Optical Anisotropy in van der Waals materials: Impact on Direct Excitation of Plasmons and Photons by Quantum Tunneling

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Light(science & Applications) 2021年第12期10卷 2387-2398页

作者： Zhe Wang Vijith Kalathingal Thanh Xuan Hoang Hong-Son Chu Christian A.Nijhuis Department of Chemistry National University of Singapore3 Science Drive 3Singapore 117543Singapore Centre for Advanced 2D Materials National University of Singapore6 Science Drive 2Singapore 117564Singapore Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Singapore Department of Electronics and Photonics Institute of High Performance ComputingA*STAR(Agency for ScienceTechnology and Research)1 Fusionopolis WaySingapore 138632Singapore Hybrid Materials for Opto-Electronics Group Department of Molecules and MaterialsMESA+Institute for Nanotechnology and Center for Brain-Inspired Nano SystemsFaculty of Science and TechnologyUniversity of Twente7500 AE EnschedeThe Netherlands

Inelastic quantum mechanical tunneling of electrons across plasmonic tunnel junctions can lead to surface plasmon polariton(SPP)and photon *** far,the optical properties of such junctions have been controlled by changing the shape,or the type of the material,of the electrodes,primarily with the aim to improve SPP or photon emission *** we show that by tuning the tunneling barrier itself,the efficiency of the inelastic tunneling rates can be improved by a factor of *** exploit the anisotropic nature of hexagonal boron nitride(hBN)as the tunneling barrier material in Au//hBN//graphene tunnel junctions where the Au electrode also serves as a plasmonic strip *** this junction constitutes an optically transparent hBN–graphene heterostructure on a glass substrate,it forms an open plasmonic system where the SPPs are directly coupled to the dedicated strip waveguide and photons outcouple to the far *** experimentally and analytically show that the photon emission rate per tunneling electron is significantly improved(~×3)in Au//hBN//graphene tunnel junction due to the enhancement in the local density of optical states(LDOS)arising from the hBN *** the dedicated strip waveguide,SPP outcoupling efficiency is quantified and is found to be∼80%stronger than the radiative outcoupling in Au//hBN//graphene due to the high LDOS of the SPP decay channel associated with the inelastic *** new insights elucidated here deepen our understanding of plasmonic tunnel junctions beyond the isotropic models with enhanced LDOS.

关键词： tunneling strip coupling

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Parking Problem by Oblivious Mobile Robots in Infinite Grids

arXiv

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arXiv 2023年

作者： Chakraborty, Abhinav Mukhopadhyaya, Krishnendu Department of Computer Science and Engineering Institute of Technical Education and Research Siksha O Anusandhan University Odisha Bhubaneswar India Advanced Computing and Microelectronics Unit Indian Statistical Institute 203 B. T. Road West Bengal Kolkata700108 India

In this paper, the parking problem of a swarm of mobile robots has been studied. The robots are deployed at the nodes of an infinite grid, which has a subset of prefixed nodes marked as parking nodes. Each parking node pi has a capacity of ki which is given as input and equals the maximum number of robots a parking node can accommodate. As a solution to the parking problem, robots need to partition themselves into groups so that each parking node contains a number of robots that are equal to the capacity of the node in the final configuration. It is assumed that the number of robots in the initial configuration represents the sum of the capacities of the parking nodes. The robots are assumed to be autonomous, anonymous, homogeneous, identical and oblivious. They operate under an asynchronous scheduler. They neither have any agreement on the coordinate axes nor do they agree on a common chirality. All the initial configurations for which the problem is unsolvable have been identified. A deterministic distributed algorithm has been proposed for the remaining configurations, ensuring the solvability of the problem. Copyright © 2023, The Authors. All rights reserved.

关键词： Mobile robots

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Design of AED Based Drone to Deliver the Medical Kit on an Emergency Basis

Design of AED Based Drone to Deliver the Medical Kit on an E...

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Advancement in Electronics & Communication Engineering (AECE), International Conference on

作者： P. Nagarani Mohd Wazih Ahmad R Shalini Pavitar Parkash Singh Department of Emerging Technologies CVR College of Engineering Hyderabad India Department of Computer Science and Engineering hri Ram Murti Smarak college of Engineering and Technology Bareilly India Department of BCA & IT School of computing sciences Vels Institute of Science Technology and Advanced Studies Chennai India Department of Management Lovely Professional University Phagwara India

Access to reliable modes of transportation is essential. Postal delivery to multi-million-dollar freight transports, practically everything is linked to its connections. Wheeled motor vehicles and manned aeroplanes are now the only options for transporting medical supplies at times of urgent need, which may be expensive, time-consuming, and often impossible if the emergency site is far. Drones are a game-changer in the medical industry because they can transfer vital supplies like blood and medical equipment. Unfortunately, given the state of the art, the drone's battery life is a constraint that may slow down the delivery process. This article details the research into the mechanisms designed for drones to increase their battery life and efficiently deliver first aid supplies. The drone's system safely delivers and drops medical supplies, reducing the drone's takeoffs and landings. The primary goal of this research is to develop a device that can safely transport medical equipment to its destination and then carefully unload it there. Results showed the system could safely transport and deploy first aid supplies during flight and landing.

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Enhancing HIV Drug Resistance Prediction Using Bidirectional LSTM Neural Networks

Enhancing HIV Drug Resistance Prediction Using Bidirectional...

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3rd International Conference on Machine Learning and Data Engineering, ICMLDE 2024

作者： Poojitha, D. Darak, Tanmay Samaddar, Ushnish Vasavi, C.S. Karthikeyan, B. Korlepara, Divya B. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru560035 India Department of Artificial Intelligence Amrita School of Artificial Intelligence Amrita Vishwa Vidyapeetham Bengaluru560035 India Department of Embedded Technology School of Electronics Engineering Vellore Institute of Technology Vellore632014 India Divison of Physics School of Advanced Sciences Vellore Institute of Technology Chennai600127 India

One major obstacle that humanity faces today is the ability of viruses to develop resistance to antibiotics or other drugs used in treating the diseases. In the current study, we utilise a specifically developed Bidirectional Long Short-Term Memory (LSTM) neural network to identify HIV drug resistant strains in an effort to help clinicians identify the most appropriate treatment options so that the development new resistant strains is prevented as much as is possible. By incorporating the Bidirectional LSTM model, temporal dependency analysis is improved and deepened in both forward and backward directions, improving the model's performance and interpretability. The accuracy of the model is measured by MAE and R2 where the result from MAE is 16.151 of PI (Protease Inhibitors), 14.703 of NRTI (Nucleoside Reverse Transcriptase Inhibitors) and 18.815 of NNRTI (Non-Nucleoside Reverse Transcriptase Inhibitors) while result from R2 is 0.914 of PI, 0.942 of NRTI and 0.885 of NNRTI. Consequently, these results suggest the custom model may be useful to refine drug resistance predictions to progress the accuracy of HIV treatment. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Bidirectional LSTM neural networks bioinformatics genetic sequences Non-Nucleoside Reverse Transcriptase Inhibitors Nucleoside Reverse Transcriptase Inhibitors Protease Inhibitors resistant strains

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Thermal relaxation error on QKD: Effect and A Probable Bypass

arXiv

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arXiv 2022年

作者： Aziz, Munsi Afif Gond, Bishwajit Prasad Nandi, Srijita Ray, Soujanya Bhoumik, Debasmita Majumdar, Ritajit Department of Computer Science & Engineering Government College of Engineering and Leather Technology India National Institute of Technology Sikkim India Advanced Computing & Microelectronics Unit Indian Statistical Institute Kolkata India

Quantum cryptography was proposed as a counter to the capacity of quantum computers to break classical cryptosystems. A broad subclass of quantum cryptography, called quantum key distribution (QKD), relies on quantum mechanical process for secure distribution of the keys. Quantum channels are inherently noisy, and therefore these protocols will be susceptible to noise as well. In this paper, we study the performance of two QKD protocols - BB84 and E91 under thermal relaxation error. We show that while E91 protocol loses its security immediately due to loss of entanglement, the performance of BB84 protocol reduces to random guessing with increasing time. Next, we consider the action of an Eve on the BB84 protocol under thermal relaxation noise, who is restricted to guessing the outcome of the protocol only. Under this restriction, we show that Eve can still do better than random guessing when equipped with the characteristics of the noisy channel. Finally, we propose a modification of the BB84 protocol which retains the security of the original protocol, but ensures that Eve cannot get any advantage in guessing the outcome, even with a complete channel information. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum cryptography

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Modeling Chiplet-to-Chiplet (C2C) Communication for Chiplet-based Co-Design

Modeling Chiplet-to-Chiplet (C2C) Communication for Chiplet-...

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ISC High Performance 2025 Research Paper Proceedings (40th International Conference)

作者： Fabian Schätzle Carlos Falquez Nam Ho André Zambanini Johannes van den Boom Estela Suarez Peter Grünberg Institute - Integrated Computing Architectures (ICA — PGI-4) Forschungszentrum Jülich GmbH Jülich Germany Jülich Supercomputing Centre Institute for Advanced Simulation Forschungszentrum Jülich GmbH Jülich Germany SiPEARL Maisons-Laffitte France Computer Science Department University of Bonn Bonn Germany

ISBN: (数字)9783982633619

Chiplet-based processor design, which combines small dies called chiplets to form a larger chip, enables scalable designs at economical costs. This trend has received high attention such that standards for chiplet design have rapidly established, including packaging, protocols, and Chiplet-to-Chiplet (C2C) interfaces. With numerous well-defined chiplet options available, hardware architects would leverage on the co-design process to make optimal decisions on design parameters. An important performance limitation in multi-chiplet designs come from the protocol translation in the C2C communication, needed to maintain cache coherency and avoid risk of deadlocks. When integrating multiple chiplets, deadlocks can happen from both protocol and routing, making deadlock-free designs important. This paper tackles these challenges by introducing a Chiplet-to-Chiplet Gateway (C2CG) architecture, a C2C interface that bridges two chiplet protocols and ensures deadlock-free C2C communication. We also extend the Coherent Hub Interface (CHI) protocol to support cache coherent data sharing among cores across chiplets. The complete design is implemented in the gem5 simulator, constructing a modeling tool for chiplet-based co-design targeting next-generation High-performance computing (HPC) processors. We demonstrate the benefit of the model through a design space exploration of three 64-core Armv8 HPC processor configurations: monolithic, two- and four-chiplet. The exploration, using representative HPC benchmarks, provides insights into C2C parameters and studies the impact of Non-Uniform Memory Access (NUMA) configuration, giving valuable co-design feedback for hardware architects.

关键词： Protocols Translation Chiplets High performance computing Computational modeling computer architecture System recovery Packaging Hardware Topology

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Optimization of Image Transmission in a Cooperative Semantic Communication Networks

arXiv

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arXiv 2023年

作者： Zhang, Wenjing Wang, Yining Chen, Mingzhe Luo, Tao Niyato, Dusit The Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States NTU Singapore

In this paper, a semantic communication framework for image data transmission is developed. In the investigated framework, a set of servers cooperatively transmit image data to a set of users utilizing semantic communication techniques, which enable servers to transmit only the semantic information that accurately captures the meaning of images. To evaluate the performance of studied semantic communication system, a multimodal metric called image-to-graph semantic similarity (ISS) is proposed to measure the correlation between the extracted semantic information and the original image. To meet the ISS requirement of each user, each server must jointly determine the semantic information to be transmitted and the resource blocks (RBs) used for semantic information transmission. Due to the co-channel interference among users associated with different servers, each server must cooperate with other servers to find a globally optimal semantic oriented RB allocation. We formulate this problem as an optimization problem whose goal is to minimize the sum of the average transmission latency of each server while reaching the ISS requirement. To solve this problem, we propose a value decomposition based entropy-maximized multi-agent reinforcement learning (RL) algorithm. The proposed algorithm enables each server to coordinate with other servers in training stage and execute RB allocation in a distributed manner to approach to a globally optimal performance with less training iterations. Compared to traditional multi-agent RL algorithms, the proposed RL framework improves the exploration of valuable action of servers and the probability of finding a globally optimal RB allocation policy based on local observation of wireless and semantic communication environments. Simulation results show that the proposed algorithm can reduce the transmission delay by up to 16.1% and improve the convergence speed by up to 100% compared to the traditional multi-agent RL algorithms. Copyright © 2

关键词： Cooperative communication

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On Relaxed Locally Decodable Codes for Hamming and Insertion-Deletion Errors

arXiv

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arXiv 2022年

作者： Block, Alex Blocki, Jeremiah Cheng, Kuan Grigorescu, Elena Li, Xin Zheng, Yu Zhu, Minshen Department of Computer Science Purdue University United States Center on Frontiers of Computing Studies Peking University United States Advanced Institute of Information Technology Peking University United States Department of Computer Science Johns Hopkins University United States

Locally Decodable Codes (LDCs) are error-correcting codes C: Σn → Σm, encoding messages in Σn to codewords in Σm, with super-fast decoding algorithms. They are important mathematical objects in many areas of theoretical computer science, yet the best constructions so far have codeword length m that is super-polynomial in n, for codes with constant query complexity and constant alphabet size. In a very surprising result, Ben-Sasson, Goldreich, Harsha, Sudan, and Vadhan (SICOMP 2006) show how to construct a relaxed version of LDCs (RLDCs) with constant query complexity and almost linear codeword length over the binary alphabet, and used them to obtain significantly-improved constructions of Probabilistically Checkable Proofs. In this work, we study RLDCs in the standard Hamming-error setting, and introduce their variants in the insertion and deletion (Insdel) error setting. Standard LDCs for Insdel errors were first studied by Ostrovsky and Paskin-Cherniavsky (Information Theoretic Security, 2015), and are further motivated by recent advances in DNA random access bio-technologies (Banal et al., Nature Materials, 2021), in which the goal is to retrieve individual files from a DNA storage database. Our first result is an exponential lower bound on the length of Hamming RLDCs making 2 queries (even adaptively), over the binary alphabet. This answers a question explicitly raised by Gur and Lachish (SICOMP 2021) and is the first exponential lower bound for RLDCs. Combined with the results of Ben-Sasson et al., our result exhibits a "phase-transition"-type behavior on the codeword length for some constant-query complexity. We achieve these lower bounds via a transformation of RLDCs to standard Hamming LDCs, using a careful analysis of restrictions of message bits that fix codeword bits. We further define two variants of RLDCs in the Insdel-error setting, a weak and a strong version. On the one hand, we construct weak Insdel RLDCs with almost linear codeword length and const

关键词： Decoding

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iCOIL: Scenario Aware Autonomous Parking Via Integrated Constrained Optimization and Imitation Learning

arXiv

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arXiv 2023年

作者： Huang, Lexiong Han, Ruihua Li, Guoliang Li, He Wang, Shuai Wang, Yang Xu, Chengzhong Center for Cloud Computing Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences Beijing100049 China Department of Computer Science University of Hong Kong Hong Kong IOTSC University of Macau China

Autonomous parking (AP) is an emering technique to navigate an intelligent vehicle to a parking space without any human intervention. Existing AP methods based on mathematical optimization or machine learning may lead to potential failures due to either excessive execution time or lack of generalization. To fill this gap, this paper proposes an integrated constrained optimization and imitation learning (iCOIL) approach to achieve efficient and reliable AP. The iCOIL method has two candidate working modes, i.e., CO and IL, and adopts a hybrid scenario analysis (HSA) model to determine the better mode under various scenarios. We implement and verify iCOIL on the Macao Car Racing Metaverse (MoCAM) platform. Results show that iCOIL properly adapts to different scenarios during the entire AP procedure, and achieves significantly larger success rates than other benchmarks. Copyright © 2023, The Authors. All rights reserved.

关键词： Constrained optimization

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Efficient COVID-19 detection using data mining algorithms: a comparison of basic and hybrid approaches

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Soft computing 2025年第3期29卷 1437-1451页

作者： Saidi, Mohammad Gheibi, Mohammad Ghazikhani, Adel Lotfata, Aynaz Chahkandi, Benyamin Familsamavati, Sajad Behzadian, Kourosh Department of Computer Science Imam Reza International University Mashhad Iran MS of Software Engineering Information and Communication Technology Unit Mashhad Municipality Fire and Safety Services Organization Mashhad Iran Big Data Lab Imam Reza International University Mashhad Iran Institute for Nanomaterials Advanced Technologies and Innovation Technical University of Liberec Liberec46117 Czech Republic Tallinn10615 Estonia Department of Pathology Microbiology and Immunology School of Veterinary Medicine University of California Davis95616 United States Department of Urban and Regional Planning San Jose State University San Jose95192 United States Faculty of Civil and Environmental Engineering Gdansk University of Technology Narutowicza Street 11/12 80-233 Gdansk Poland Tecnologico de Monterrey Escuela de Ingeniería y Ciencias Monterrey Mexico School of Computing and Engineering University of West London London United Kingdom

Accurate and efficient diagnosis of COVID-19 remains a significant challenge due to the limitations of current detection methods, such as blood tests and chest scans, which can be time-consuming and error-prone. This study aims to compare the performance of basic and hybrid data mining algorithms in diagnosing COVID-19, using blood test results and clinical information to identify the most effective approach. A dataset of 200 records from suspected and infected COVID-19 patients, with 23 characteristics and one diagnostic class, was analysed. Nine data mining algorithms were tested: four basic algorithms (Naive Bayes, Support Vector Machine, Decision Tree, K-Nearest Neighbor) and five hybrid algorithms (Random Forest, AdaBoost, Majority Voting, XGBoost, Bagging). The study also integrated Response Surface Methodology (RSM) and Adaptive-Network-based Fuzzy Inference System (ANFIS) to enhance model performance. The Bagging algorithm demonstrated superior performance with an accuracy of 88%, sensitivity of 74%, and F-criterion of 78%. The integration of RSM and ANFIS further showed that a smart model could be developed for efficient pandemic crisis management, achieving up to 100% accuracy when considering key factors like AST, Albumin, and CRP. The findings suggest that Bagging and hybrid data mining algorithms can significantly improve COVID-19 detection, reducing time and errors in identifying exposed individuals. The study highlights the potential of combining machine learning techniques with RSM-ANFIS models for effective pandemic management and decision-making in medical settings. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Support vector machines

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