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International Conference on Noise and Fluctuations (ICNF)

作者： Janusz Smulko Andrzej Kwiatkowski Katarzyna Drozdowska Lars Österlund Tesfalem Welearegay Adil Rehman Sergey Rumyantsev Faculty of Electronics Telecommunications and Informatics Gdańsk University of Technology Gdańsk Poland Department of Materials Science and Engineering The Angstrom Laboratory Uppsala University Uppsala Sweden CENTERA Laboratories Institute of High Pressure Physics PAS Warsaw Poland

We present results of the probability distribution analysis of flicker noise generated in Au nanoparticle (AuNP) decorated graphene–Si Schottky barrier diodes with and without yellow light illumination (592 nm), close to the localized surface plasmon resonance in the AuNPs (586 nm). The AuNPs occupy imperfections in the single-layer graphene and reduce the flicker noise intensity generated in the graphene layer. The estimated probability distribution exhibited an asymmetry shift when the sample was irradiated by yellow light (a 10-fold increase of the skewness coefficient). This effect is attributed to AuNPs collecting low-frequency fluctuations in the graphene layer and reducing 1/f noise.

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Photon-resolved Floquet theory I: Full-Counting statistics of the driving field in Floquet systems

arXiv

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arXiv 2024年

作者： Engelhardt, Georg Luo, JunYan Bastidas, Victor M. Platero, Gloria Shenzhen Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China International Quantum Academy Shenzhen518048 China Guangdong Provincial Key Laboratory of Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China Department of Physics Zhejiang University of Science and Technology Hangzhou310023 China Physics and Informatics Laboratory NTT Research Inc. 940 Stewart Dr. SunnyvaleCA94085 United States Department of Chemistry Massachusetts Institute of Technology CambridgeMA02139 United States Instituto de Ciencia de Materiales de Madrid ICMM-CSIC Madrid28049 Spain

Floquet theory and other established semiclassical approaches are widely used methods to predict the state of externally-driven quantum systems, yet, they do not allow to predict the state of the photonic driving field. To overcome this shortcoming, the photon-resolved Floquet theory (PRFT) has been developed recently [Phys. Rev. Research 6, 013116], which deploys concepts from full-counting statistics to predict the statistics of the photon flux between several coherent driving modes. In this paper, we study in detail the scaling properties of the PRFT in the semiclassical regime. We find that there is an ambiguity in the definition of the moment-generating function, such that different versions of the moment-generating function produce the same photonic probability distribution in the semiclassical limit, and generate the same leading-order terms of the moments and cumulants. Using this ambiguity, we establish a simple expression for the Kraus operators, which describe the decoherence dynamics of the driven quantum system appearing as a consequence of the light-matter interaction. The PRFT will pave the way for improved quantum sensing methods, e.g., for spectroscopic quantum sensing protocols, reflectometry in semiconductor nanostructures and other applications, where the detailed knowledge of the photonic probability distribution is necessary. © 2024, CC BY.

关键词： Quantum optics

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A Healthcare Pattern Collection for Rural Telemedicine Services

A Healthcare Pattern Collection for Rural Telemedicine Servi...

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International Conference on e-health Networking, Applications and Services (HealthCom)

作者： Po-Hsun Cheng Jer-Junn Luh Ming-Fong Shyu Heng-Shuen Chen Sao-Jie Chen Jin-Shin Lai Feipei Lai Information Systems National Taiwan University Hospital Taipei Taiwan School & Graduate Institute of Physical Therapy College of Medicine National Taiwan University Taipei Taiwan Department of Computer Science & Information Engineering Chao Yang University of Technology Taipei Taiwan Department of Family and Department of Medical Informatics National Taiwan University Hospital Taipei Taiwan Graduate Institute of Electronics Engineering & Depertment of Electrical Engineering National Taiwan University Taipei Taiwan Department of Physical Medicine & Rehabilitation & Department of Medical Informatics National Taiwan University Hospital National Taiwan University College of Medicine Taipei Taiwan Department of Computer Science & Information Engineering National Taiwan University Taipei Taiwan

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Problem formulation for multi-criteria decision analysis: Report of a workshop

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Journal of Multi-Criteria Decision Analysis 1998年第5期7卷 242-262页

作者： French, Simon Simpson, Lisa Atherton, Elizabeth Belton, Valerie Dawes, Robyn Edwards, Ward Hämäläinen, Raimo P. Larichev, Oleg Lootsma, Freerk Pearman, Alan Vlek, Charles School of Informatics University of Manchester Manchester M13 9PL Coupland 1 Oxford Road United Kingdom School of Computer Studies University of Leeds Leeds United Kingdom Department of Management Science University of Strathclyde Strathclyde United Kingdom Department of Social and Decision Sciences Carnegie-Mellon University Pittsburgh PA United States Departments of Psychology and of Industrial and Systems Engineering University of Southern California CA United States Department of Systems Engineering Helsinki University of Technology Helsinki Finland Institute for Systems Analysis Russian Academy of Sciences Moscow Russian Federation Department of Mathematics Technical University of Delft Delft Netherlands Leeds University Business School Leeds University Leeds LS2 9JT United Kingdom Department of Psychology University of Groningen Groningen Netherlands

This paper reports on a workshop on Problem Formulation in Multi-Criteria Decision Analysis held at SPUDM97. The focus of the workshop was the problem formulation phase which occurs between the analyst meeting a person with a ‘mess’ and the time he or she begins to analyse a structured problem with several alternatives scored against several attributes or criteria. The objectives were: to share experience on procedures which might be transferable between the methodologies;to demonstrate different skills used by the analyst in structuring decision problems;and to catalyse a discussion on the problem formulation phase of an analysis. Three analysts, who generally approach problems using multiattribute methods, addressed the same problem. The problem used was constructed to be realistic to three decision makers, who had been trained in the issues of concern. There were two sessions. Each analyst was assigned a decision maker and formulated the problem independently in the first session, held in parallel. They were each observed by two observers and many of the audience at the workshop. The three formulations were presented along with the comments of the observers and discussed at a second plenary session. This paper reports the three formulations and observations, remarking on the ‘tricks of the trade’ employed by the analysts in formulating the problem. The analysts also describe their thinking and their aims in adopting their approach and style of interaction. More general remarks on the process of decision analysis are also offered. © 1998 John Wiley & Sons, Ltd.

关键词： Multi-criteria decision analysis (MCDA) Problem formulation Process of decision analysis

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An Experiment of Geothermal Exploration with an Uas-Tir in Xiaoyoukeng Area of Tatun Volcanoes, Taiwan

An Experiment of Geothermal Exploration with an Uas-Tir in X...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Chun-Jung Lai Jin-King Liu Wei-Chen Hsu Ke-Shu Li Ming-Chee Wu Kuan-Tsung Chang LIDAR Technology Co. Ltd Zhubei City Taiwan LIDAR Technology Co. Ltd Hsinchu County Taiwan Researcher ITRI RAISE project Zhubei City Taiwan National Cheng-Kung University Tainan City Taiwan Department of Civil Engineering and Environmental Informatics Minghsin University of Science and Technology

Geothermal exploration requires thermal images for obtaining the temperature on ground surface for characterizing surface geology and modeling the temperature at the depth. The purpose of this study is to integrate a thermal sensor with a wind-resistant UAV for detecting geothermal anomalies suitable for conducting exploration in a mountainous terrain. The specifications of the UAS-TIR, the experiment at XiaoYoukeng, and the results are presented. It is proved that such a system can be effectively applied in assisting quantitative assessment of geothermal reserves when compared with airborne thermal systems.

关键词： Land surface temperature Temperature sensors Ocean temperature Temperature measurement Remote sensing Drones

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On Performance Prediction of Big Data Transfer in High-performance Networks

On Performance Prediction of Big Data Transfer in High-perfo...

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IEEE International Conference on Communications (ICC)

作者： Wuji Liu Daqing Yun Chase Q. Wu Nageswara S.V. Rao Aiqin Hou Wei Shen Department of Computer Science New Jersey Institute of Technology Newark NJ USA Computer and Information Sciences Program Harrisburg University Harrisburg PA USA Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak Ridge TN USA School of Information Science and Technology Northwest University Xi’an Shaanxi China School of Informatics Science and Technology Zhejiang Sci-Tech University Hangzhou Zhejiang China

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

Big data generated by large-scale scientific and industrial applications need to be transferred between different geographical locations for remote storage, processing, and analysis. High-speed dedicated connections provisioned in High-performance Networks (HPNs) are increasingly utilized to carry out such big data transfer. HPN management highly relies on an important capability of performance (mainly throughput) prediction to reserve sufficient bandwidth and meanwhile avoid over-provisioning that may result in unnecessary resource waste. This capability is critical to improving the resource (mainly bandwidth) utilization of dedicated connections and meeting various user requests for data transfer. Conventional methods conduct performance prediction by fitting prior observed transfer history with predefined loss functions, without considering unobservable latent factors such as competing loads on end hosts. Such latent factors also have a significant impact on the application-level data transfer performance, which may result in an inaccurate prediction model. In this paper, we first investigate the impact of latent factors and propose a clustering-based method to eliminate their negative impact on performance prediction. We then develop a robust machine learning-based performance predictor by: i) incorporating the proposed latent factor elimination method into data preprocessing, and ii) adopting a customized domain guided loss function. Extensive experimental results show that our predictor achieves significantly higher prediction accuracy than several other state-of-the-art methods.

关键词： Data transfer Big Data Throughput Bandwidth Measurement Predictive models Protocols

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Development of a Decision Support Tool for Intelligent Manufacturing using Classification and Correlation Analysis

Development of a Decision Support Tool for Intelligent Manuf...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Dariusz Król Jan Skowroński Maciej Zareba Krzysztof Bartecki Department of Information Systems Faculty of Computer Science and Management Wrocław University of Science and Technology Poland Legnicka 55F 53–203 Wrocław Wrocław University of Science and Technology Poland DSR Legnicka 55F 53—203 Wrocław Poland Institute of Automatic Control Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Poland

The development of the Production Unit Performance Management Tool (PUPMT), a monitoring and diagnostic tool to select basic signals that have a significant impact on output KPIs, is based on a hierarchical analysis of key performance indicators presented in the ISO 22400 standard. The growing number of quantified signals, such as ambient temperature or even the frequency of vibrations makes decision support tools more intelligent. Moreover, they also include predictive analysis in addition to online presentation of the current state of resources. PUPMT tool allows identifying key events that have a significant impact on current or future benefit in production output. It also allows what-if type analysis, running the simulation of the impact of the proposed changes, and the results of this simulation depend on the effects of similar changes that occurred in the past in a given smart manufacturing environment. Thanks to the automatic identification of potential dependencies, the proposed solution adapts to the specifics of a given environment or even a selected production unit. The paper describes the most important methods featured in the tool. Specifically, it considers a signal classification method, a signal correlation analysis and selection of key factors affecting the efficiency of the production process. In order to verify the methods various tests were carried out to calculate and control of OEE index on 20 production units. Finally, we conclude current results and future research directions.

关键词： Conferences Cybernetics

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Dual-Band Planar Microstrip Monopole Antenna Design Using Multi-Objective Hybrid Optimization Algorithm

Dual-Band Planar Microstrip Monopole Antenna Design Using Mu...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： V. Hosseini F. Shapour P. Pinho Y. Farhang K. Majidzadeh Ch. Ghobadi J. Nourinia S. Barshandeh M. Shokri Zh. Amiri M. Jalilirad K. Kaboutari Department of Computer Engineering and Information Technology Payame Noor University Tehran Iran Computer Engineering Department Urmia Branch Islamic Azad University Urmia Iran Instituto de Telecomunicações Aveiro Portugal Department of Electronics Telecommunications and Informatics University of Aveiro Aveiro Portugal Department of Computer Engineering Khoy Branch Islamic Azad University Khoy Iran Department of Electrical Engineering Urmia University Urmia Iran Department of Computer Science School of Engineering Afagh Higher Education Institute Urmia Iran

This research uses a new proposed multi-objective optimization algorithm that utilizes an untested combined chaotic map to integrate Customized Mutated PSO (CM-PSO) with a Modified Genetic Algorithm (MGA) to design an antenna with specific electromagnetic characteristics. The hybrid approach achieves preferred outcomes faster than PSO, CM-PSO, GA, and MGA by avoiding being trapped in local minimums. The proposed Metaheuristic Algorithm (MA) functionality has been authenticated successfully using Benchmark Functions (BFs) like Rastrigin Function (RaF), Ackley Function (AF), Rosenbrock Function (RoF), and Booth Function (BoF). Finally, the validity of the offered approach for electromagnetic applications is demonstrated by optimizing a dual-band planar microstrip monopole antenna with a simple structure, such that its optimized $S_{11}$ be less than -10 dB at two frequency bands encompasses 2.4 to 2.484 and 5.15 to 5.825 GHz for Wireless Local Area Network (WLAN) with IEEE 802.11 standards. The proposed algorithm allows the optimization criteria to be customized. The optimization algorithm developed in MATLAB is used to determine the necessary parameter adjustments in order to achieve expected frequency bands using CM-PSO or an innovative MGA, while high-frequency and electromagnetic simulations are performed using Computer Simulation technology (CST) Studio Suite. The dimensions of the proposed antenna's elements are critical input parameters of the algorithm, named decision variables.

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QoS-aware resource allocation for LTE-A systems with carrier aggregation

QoS-aware resource allocation for LTE-A systems with carrier...

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IEEE Conference on Wireless Communications and Networking

作者： Wang Miao Geyong Min Yuming Jiang Xiaolong Jin Haozhe Wang School of Computing Informatics and Media University of Bradford UK College of Engineering Mathematics and Physical Sciences University of Exeter UK Department of Telematics Norwegian University of Science and Technology Trondheim Norway Chinese Academy of Sciences Institute of Computing Technology Beijing P. R. China

ISBN: (纸本)9781479930845

Carrier Aggregation (CA) has emerged as a promising technique for Long-Term Evolution Advanced (LTE-A) wireless communications to satisfy the ever-increasing bandwidth requirements. However, this technical envisagement puts forward new challenges on radio resource allocation such as serious unbalanced loads among different Component Carriers (CCs). To alleviate this problem, a novel QoS-aware resource allocation scheme, termed as Cross-CC User Migration (CUM) scheme, is proposed in this paper to support real-time services, taking into consideration the system throughput, user fairness and QoS constraints. The experiment results show that the proposed scheme outperforms the well-known Two-Level scheduling scheme in terms of packet loss probability, average queue length and throughput per user.

关键词： Resource management Delays Quality of service Throughput Real-time systems Packet loss

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Machine Learning Algorithms for Prediction of Survival Curves in Breast Cancer Patients

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Applied Bionics and Biomechanics 2021年 2021卷 9338091页

作者： Maabreh, Roqia Saleem Awad Alazzam, Malik Bader Alghamdi, Ahmed S. Prince Al Hussein Bin Abdulla Academy for Civil Protection Jordan Faculty of Computer Science and Informatics Amman Arab University Jordan Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia

Today, cancer is the second leading cause of death worldwide, and the number of people diagnosed with the disease is expected to rise. Breast cancer is the most commonly diagnosed cancer in women, and it has one of the highest survival rates when treated properly. Because the effectiveness and, as a result, survival of the patient are dependent on each case, it is critical to know the modelling of their survival ahead of time. Artificial intelligence is a rapidly expanding field, and its clinical applications are following suit (having surpassed humans in many evidence-based medical tasks). From the inception of since first stable risk estimator based on statistical methods appeared in survival analysis, there have been numerous versions of it created, with machine learning being used in only a few of them. Nonlinear relationships between variables and the impact they have on the variable to be predicted are very easy to evaluate using statistical methods. However, because they are just mathematical equations, they have flaws that limit the quality of their output. The main goal of this study is to find the best machine learning algorithms for predicting the individualised survival of breast cancer patients, as well as the most appropriate treatment, and to propose new numerical variable stratifications. They will still be carried out using unsupervised machine learning methods that divide patients into groups based on their risk in each dataset. We will compare it to standard groupings to see if it has more significance. Knowing that the greatest challenge in dealing with clinical data is its quantity and quality, we have gone to great lengths to ensure their quality before replicating them. We used the Cox statistical method in conjunction with other statistical methods and tests to find the best possible dataset with which to train our model, despite its ease of multivariate analysis. © 2021 Roqia Saleem Awad Maabreh et al.

关键词： Statistical tests

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