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MLEA： A Solution for Users of Android in UTPVirtual

computer Technology and Application 2011年第5期2卷 406-412页

作者： Gisela Torres de Clunie Sergio Crespo Coelho da Silva Pinto Aris Linet Castillo Lucas Monteiro Braz Tasia Serrao Norman Rangel Jeanette Riley Olinda de Barraza Kexy Rodriguez Computer Systems Engineering Department Technological University of Panama Panama 0819 Panama Computer Science Research and Graduate Program in Applied Computing University of the Sinos Valley （UNISINOS） RS 93022-000 Brazil CIDITIC Technological University of Panama Panama 0819 Panama

This paper describes a design of an educational platform for a mobile learning architecture, which is a state of the an topic in distance education. The product will allow users to interact in an efficient, flexible, and transparent fashion with a web-based education environment, in this case Module Object-Oriented Dynamic Learning Environment （Moodle）, using Android mobile devices. In order to provide a strong and lasting architecture, the Service Oriented Architecture （SOA） methodology is used given that it allows easy software re-utilization as well as integration of heterogeneous services. The architecture is based on web services implemented with Representational State Transfer （REST）, as it has been demonstrated to be lighter and less consuming than other protocols, for devices with limited resources such as mobile devices. Web services provide the communication means between the server side and the client side of the architecture, whereas agents are used to deliver the services itself. The authors propose the development of an environment that facilitates the integration of various educational resources to support m-learning. An important aspect of the proposal is the offering of a tool to provide customized alerts for students and teachers, enabling them to remain updated about activities taking place in the courses.

关键词： Distance learning virtual education m-learning service oriented architecture （SOA） mobile learning mobile computing interoperability representational state transfer （REST）.

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Implicit Neural Representations for Deconvolving SAS Images

arXiv

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arXiv 2021年

作者： Reed, Albert Blanford, Thomas Brown, Daniel C. Jayasuriya, Suren School of Electrical Computer and Energy Engineering Arizona State University United States The Applied Research Laboratory United States Graduate Program in Acoustics Pennsylvania State University United States

Synthetic aperture sonar (SAS) image resolution is constrained by waveform bandwidth and array geometry. Specifically, the waveform bandwidth determines a point spread function (PSF) that blurs the locations of point scatterers in the scene. In theory, deconvolving the reconstructed SAS image with the scene PSF restores the original distribution of scatterers and yields sharper reconstructions. However, deconvolution is an ill-posed operation that is highly sensitive to noise. In this work, we leverage implicit neural representations (INRs), shown to be strong priors for the natural image space, to deconvolve SAS images. Importantly, our method does not require training data, as we perform our deconvolution through an analysis-by-synthesis optimization in a self-supervised fashion. We validate our method on simulated SAS data created with a point scattering model and real data captured with an in-air circular SAS. This work is an important first step towards applying neural networks for SAS image deconvolution. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical transfer function

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Intrinsic Raman signatures of pristine hybrid perovskite CH3NH3PbI3 and its multiple stages of structure transformation 44

Intrinsic Raman signatures of pristine hybrid perovskite CH3...

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44th IEEE Photovoltaic Specialist Conference, PVSC 2017

作者： Chen, Qiong Liu, Henan Kim, Hui-Seon Liu, Yucheng Yang, Mengjin Yue, Naili Ren, Gang Zhu, Kai Liu, Shengzhong Frank Park, Nam-Gyu Zhang, Yong Department of Electrical and Computer Engineering Korea Republic of Optical Science and Engineering Graduate Program University of North Carolina at Charlotte CharlotteNC28223 United States School of Chemical Engineering and Department of Energy Science Sungkyunkwan University Suwon440-746 Korea Republic of Key Laboratory of Applied Surface and Colloid Chemistry National Ministry of EducationInstitute for Advanced Energy Materials School of Materials Science and Engineering Shaanxi Normal University Xi'an710062 China Chemical and Materials Science Center National Renewable Energy Laboratory GoldenCO80401 United States Molecular Foundry Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

ISBN: (纸本)9781509056057

By performing spatially resolved Raman and photoluminescence spectroscopy with different illumination conditions, we have achieved a unified understanding towards the spectroscopy signatures of the organic-inorganic hybrid perovskite, transforming from the pristine state (CH3NH3PbI3 or MAPbI3) to fully degraded state (i.e., PbI2), for samples with varying crystalline domain size from mesoscopic scale to macroscopic size, synthesized by three different techniques. © 2017 IEEE.

关键词： Perovskite

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Uncovering why deep neural networks lack robustness: Representation metrics that link to adversarial attacks

arXiv

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arXiv 2019年

作者： Vargas, Danilo Vasconcellos Kotyan, Shashank Matsuki, Moe Faculty of Information Science and Electrical Engineering Kyushu University Japan Department of Computer Science and Engineering Dr. SPM IIIT-NR India Department of Applied Science for Integrated System Engineering Graduate School of Engineering Kyushu Institute of Technology University Japan

Neural networks have been shown vulnerable to adversarial samples. Slightly perturbed input images are able to change the classification of accurate models, showing that the representation learned is not as good as previously thought. To aid the development of better neural networks, it would be important to evaluate to what extent are current neural networks' representations capturing the existing features. Here we propose a test that can evaluate neural networks using a new type of zero-shot test, entitled Raw Zero-Shot. This test is based on the principle that some features are present on unknown classes and that unknown classes can be defined as a combination of previous learned features without learning bias. To evaluate the soft-labels of unknown classes, two metrics are proposed. One is based on clustering validation techniques (Davies-Bouldin Index) and the other is based on soft-label distance of a given correct soft-label. Experiments show that such metrics are in accordance with the robustness to adversarial attacks and might serve as a guidance to build better models as well as be used in loss functions to improve the models directly. Interestingly, the results suggests that dynamic routing networks such as CapsNet have better representation while some DNNs might be trading off representation quality for accuracy. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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Archimedean Spiral Multi-resonator for Chipless RFID Tag Using Frequency-Coded Decimal Method

Archimedean Spiral Multi-resonator for Chipless RFID Tag Usi...

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SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference

作者： Hillner de P. A. Ferreira Alexandre J. R. Serres Georgina Karla de F. Serres Francisco M. de Assis Alfredo Gomes Neto Post-Graduate Program in Electrical Engineering Federal University of Campina Grande Group of Telecom. and Applied Electromagnetism Federal Inst. of Educ. Science and Technology of Paraiba

ISBN: (纸本)9781467394932

A compact electromagnetic multi-resonator is presented in this paper using a new technique for chipless RFID tag data encoding. Employing Archimedean spirals, the information is applied into the spectral signature shifting resonant frequencies in several positions. The multi-resonator tag proposed operates in microwave band (between 3.0-7.0GHz) and has a coding data capacity of up to 100 decimal numbers for two resonant frequencies. The simulated and measured results show a good concordance and a great perspective to use in low-cost RFID chipless tag applications.

关键词： RFID chipless Frequency-Coded Decimal Archimedean spiral Multi-resonator

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UAV-Based Optimization for Fruit Counting in Greenhouses

UAV-Based Optimization for Fruit Counting in Greenhouses

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： João Vítor R. Vasconcelos Thayron M. Hudson André G. dos Santos Martin Saska Alexandre S. Brandão Department of Electrical Engineering Núcleo de Especialização em Robótica Graduate Program on Computer Science Federal Univer-sity of Vicosa Vicosa MG Brazil Graduate Program on Computer Science Federal University of Vicosa Vicosa MG Brazil Department of Cybernetics Multi-robot Systems Group Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This paper presents a solution for counting fruit in agricultural greenhouses using Unmanned Aerial Vehicles (UAV s). Initially, a heuristic based on Simulated Annealing was used to optimize the UAV's trajectory, ensuring efficient coverage of the beds. Next, digital image processing (DIP) techniques were implemented to count the fruit, including depth segmentation, application of bounding boxes, color filtering, and element counting. The DIP accuracy was evaluated in multiple scenarios and the results indicate high reliability in fruit counting, with the potential to optimize agricultural operations and provide valuable information to producers. Possible future improvements could include further refinements in image processing to increase the accuracy of counting other fruits. Ultimately, this work contributes to the advancement of automation in agriculture by offering a viable and efficient solution for counting fruit in greenhouses using UAV s.

关键词： Image segmentation Accuracy Image color analysis Greenhouses Simulated annealing Autonomous aerial vehicles Trajectory

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Signal reconstruction via sampled-data control with multirate filter banks

Signal reconstruction via sampled-data control with multirat...

引用

IEEE Conference on Decision and Control

作者： Y. Yamamoto H. Fujioka P.P. Khargonekar Department of Applied Systems Science Graduate Schoold of Engineering Kyoto University Kyoto Japan Department of Computer-Controled Machinery. Faculty of Engineering Osaka University Osaka Japan Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

An approach to multirate digital signal reconstruction via modern sampled-data control theory is presented. The central emphasis is upon continuous-time sampled-data H/sup /spl infin// design with delay. It is shown that the problem is reducible, in spite of the delay element, to a finite-dimensional single-rate problem under some mild conditions.

关键词： Signal reconstruction Channel bank filters Filter bank Delay Control theory Digital signal processing Encoding Books Digital filters Frequency response

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A Whole Crow Search Algorithm for Solving Data Clustering

A Whole Crow Search Algorithm for Solving Data Clustering

引用

International Conference on Technologies and Applications of Artificial Intelligence (TAAI)

作者： Ze-Xue Wu Ko-Wei Huang Abba Suganda Girsang Department of Electrical Engineering National Kaohsiung University of Science and Technology Kaohsiung City Taiwan R.O.C Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

Data clustering is a well-known data mining approach that usually used to minimizes the intra distance but maximizes inter distance of each data center. The cluster problem has been proved to be an NP-hard problem. In this paper, a hybrid algorithm based on Whole optimization algorithm (WOA) and Crow search algorithm (CSA) is proposed, namely HWCA. The HWCA algorithm has the advantages of the search strategy of the WOA and CSA. In addition to, there are two operators used to improve the quality of solution, namely hybrid individual operator and enhance diversity operator. The hybrid individual operator is used to exchanges individuals from the WOA and CSA systems by using the roulette wheel approach. In other hand, the HWCA performs enhance diversity operator to improve the quality of each system. More over, the HWCA is incorporated with center optimization strategy to enhance diversity of each system. In the performance evaluation, the proposed MPGO algorithm was comparison WOA and CSA algorithm with six well-known UCI benchmarks. The results show that the proposed algorithm has a higher measure of accuracy rate with comparison algorithms.

关键词： Clustering algorithms Optimization Whales Search problems Wheels Benchmark testing Random variables

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Machine learning approaches for fault detection and diagnosis of induction motors

Machine learning approaches for fault detection and diagnosi...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Lamia Belguesmi Mansour Hajji Majdi Mansouri Mohamed-Faouzi Harkat Abdelmalek Kouadri Hazem Nounou Mohamed Nounou Higher institute of Applied Science and Technology of Kasserine University of Kairouan Kasserine Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar

ISBN: (数字)9781728110806

ISBN: (纸本)9781728110813

This paper deals with the problem of monitoring of induction motors (IM) through the development of fault detection and diagnosis (FDD) approach. The developed FDD technique is addressed such that, the principal component analysis (PCA) technique is used for features extraction purposes and the machine learning (ML) classifiers are applied for fault diagnosis. In the proposed FDD approach the most efficient features are extracted and selected through PCA scheme using induction motor data. Besides, their statistical characteristics (mean and variance) are also included. The ML classifiers are applied using the extracted and selected features to perform the FDD problem. The obtained results indicate that the proposed techniques have a wide application area, fast fault detection and diagnosis, making them more reliable for induction motors monitoring.

关键词： Induction motors Machine learning algorithms Fault detection Machine learning Feature extraction Monitoring Principal component analysis

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Multi-hole defect photonic crystals with enhanced surface area for biosensing applications

Multi-hole defect photonic crystals with enhanced surface ar...

引用

Laser science, LS 2013

作者： Hu, S. Kang, C. Zhao, Y. Mares, J.W. Vlasov, Y.A. Assefa, S. Weiss, S.M. Department of Physics and Astronomy Vanderbilt University Nashville TN 37235 United States Interdisciplinary Graduate Program in Materials Science Vanderbilt University Nashville TN 37235 United States Department of Electrical Engineering and Computer Science Vanderbilt University Nashville TN 37235 United States IBM T.J. Watson Research Center Yorktown Heights NY 10536 United States

Multi-hole defect (MHD) photonic crystal cavities functionalized with in situ synthesized DNA bioreceptors are demonstrated for biosensing applications. By significantly increasing light interaction with target biomol... 详细信息

ISBN: (纸本)9781557529879

关键词： Photonic crystals

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