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Automatic melanoma detection using discrete cosine transform features and metadata on dermoscopic images

Journal of King Saud University - computer and Information sciences 2024年第2期36卷

作者： Yousefi, Shamim Najjar-Ghabel, Samad Danehchin, Ramin Band, Shahab S. Hsu, Chung-Chian Mosavi, Amir Department of Computer Engineering University of Mohaghegh Ardabili Ardabil Iran Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Douliu Taiwan John von Neumann Faculty of Informatics Budapest Hungary Ludovika University of Public Service Budapest Hungary

Machine learning contributes in improving the accuracy of melanoma detection. There are extensive studies in classic and deep learning-based approaches for melanoma detection in the literature. Still, they are not accurate or require high learning data. This paper proposes a hybrid mechanism for automated melanoma detection on dermoscopic images based on Discrete Cosine Transform features and metadata. It is composed of three steps. First, extra information/artifacts are deleted;the remaining pixels are standardized for accurate processing. Second, the reliability of the mechanism is improved by the Radon transform, extra data is removed using the Top-hat filter, and the detection rate is increased by Discrete Wavelet Transform and Discrete Cosine Transform. Then, the number of features is reduced by Locality Sensitive Discriminant Analysis. The third step divides the images into learning and test ones to create image-based models using learning data. Finally, the best model is selected based on test data and improved by a metadata-based model. Simulation results show that the decision tree provides the most practical image-based model by improving accuracy and sensitivity. Besides, the comparison results demonstrate that our model improves the F-Value to detect melanoma superior to other approaches. © 2024 The Author(s)

关键词： Artificial intelligence Big data Data science Dermoscopic image Discrete cosine transform features Machine learning Melanoma detection Metadata

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Single-molecule localization microscopy of expanded mammalian centrioles unravels the ultrastructural constitution of distal appendages

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Biophysical journal 2023年第3S1期122卷 17a页

作者： Chang, Ting-Jui B Hsu, Jimmy C-C Yang, Tony Physics National Taiwan University Taipei City Taiwan Nano Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei City Taiwan Electrical Engineering National Taiwan University Taipei City Taiwan Electrical Engineering National Taiwan University Taipei City Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei City Taiwan

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A Large Reservoir Computing Forecasting Method Based on Randomized Fuzzy Cognitive Maps

A Large Reservoir Computing Forecasting Method Based on Rand...

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IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS)

作者： Omid Orang Fabricio J. Erazo-Costa Petrônio C. L. Silva Guilherme de Alencar Barreto Frederico Gadelha Guimarães Department of Computer Science Universidade Federal de Minas Gerais Belo Horizonte Brazil Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Federal Institute of Northern Minas Gerais Januária Campus Brazil Department of Teleinformatics Engineering Universidade Federal do Ceará Fortaleza Brazil

ISBN: (数字)9798350366235

ISBN: (纸本)9798350366242

This paper introduces a novel forecastings technique based on randomized fuzzy cognitive maps (FCM), called LRHFCM (or large reservoir of randomized high-order FCM) for predicting univariate time series. LR-HFCM is a hybrid method combining fuzzy time series (FTS), FCMs, and reservoir computing. It is a type of echo state network (ESN) consisting of the input layer, intermediate (or large reservoir) layer, and output layer, where LASSO regression is applied to train the output layer. The novelty of this approach is that the internal layer includes a very large reservoir, considering different combinations from the sets of concepts and order using a certain number of sub-reservoirs to capture different dynamics of input time series. It is important to highlight that the weights within each sub-reservoir are chosen randomly and remain constant throughout the training process. The validity of the LR-HFCM approach is evaluated across 15 different time series datasets. The results highlight the outperformance of the LR-HFCM technique in comparison to various baseline models.

关键词： Training Adaptation models Adaptive systems Computational modeling Time series analysis Fuzzy cognitive maps Reservoirs

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Non-Hermitian selective thermal emitter for thermophotovoltaics

Non-Hermitian selective thermal emitter for thermophotovolta...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Ciril S. Prasad Samuel C. Raphaelson Gururaj V. Naik Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Material Science and NanoEngineering Rice University Houston TX USA

Selective thermal emitters can boost the efficiency of heat-to-electricity conversion in thermophotovoltaic systems only if their spectral selectivity is high. We demonstrate a non-Hermitian metasurface-based selectiv... 详细信息

ISBN: (纸本)9781957171258

关键词： Emissivity Light intensity Optical constants Silicon Temperature Thermal emission

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Top-Down Fabrication of Diamond Nanostructures

SSRN

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SSRN 2024年

作者： Biswas, Abhijit Li, Chenxi Pieshkov, Tymofii Mei, Zhaobo Xu, Mingfei Li, Tao Murukeshan, Jishnu Vajtai, Robert Zhao, Yuji Ajayan, Pulickel M. Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States

Diamond nanostructures can have exciting applications in electronics and thermal management, but their controlled fabrication can be challenging. Here, we present a top-down approach for the fabrication of diamond nanorod (DNR) clusters, via use of metal masks (Al, Ag, Au, and Cr) and reactive-ion etching (RIE). Prolonged RIE on Ag and Cr masks yields distinct etching profiles, and DNR clusters are selectively formed from Ag masks, with individual nanorods having dimensions of ~100 nm diameter and ~1.5 µm length. Detailed electron microscopy shows thin layer of amorphous carbon (a-C) around single crystalline DNR cores. Chemical analyses also show presence of oxygen on the surface of the DNRs. Fabrication of the DNR clusters with scalable top-down approach could lead to new nanodiamond-based applications. © 2024, The Authors. All rights reserved.

关键词： Nanorods

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Proposal of Close Contact Confirmation Method in Cyberspace for Influencer Marketing

Proposal of Close Contact Confirmation Method in Cyberspace ...

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IEEE Global Conference on Life sciences and Technologies (LifeTech)

作者： Atsushi Isozaki Naoki Suyama Tetsuo Imai Kenichi Arai Toru Kobayashi Computer and Information Science Program Graduate School of Engineering Nagasaki University Nagasaki Japan Computer and Information Science Program School of Engineering Nagasaki University Nagasaki Japan Division of Electrical Engineering and Computer Science Graduate School of Engineering Nagasaki University Nagasaki Japan

ISBN: (数字)9781665418751

ISBN: (纸本)9781665448086

We have developed the system to measure the effectiveness of influencer marketing by a general-purpose method using web browsers and web servers. This system uses the “COVID-19 Contact-Confirming Application” (COCOA) as a reference model. COCOA was developed by the Ministry of Health, Labor and Welfare in response to the epidemic of COVID-19, to detect suspicions of close contact while maintaining anonymity. The same model was applied to the cyberspace, and the “close contact confirmation method in the cyberspace” was considered in this study. We implemented a prototype and confirmed its functional validity while solving implementation problems using the Cross-Storage library.

关键词： COVID-19 Cyberspace Prototypes Web servers Libraries Browsers Proposals

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Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networks

arXiv

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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Shen, Xuemin Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the stochastic nature of diffusion models, the quality and accuracy of the generated content can vary significantly. In wireless edge networks, the transmission of incorrectly generated content may unnecessarily consume network resources. Thus, a dynamic AIGC service provider (ASP) selection scheme is required to enable users to connect to the most suited ASP, improving the users’ satisfaction and quality of generated content. In this article, we first review the AIGC techniques and their applications in wireless networks. We then present the AIGC-as-a-service (AaaS) concept and discuss the challenges in deploying AaaS at the edge networks. Yet, it is essential to have performance metrics to evaluate the accuracy of AIGC services. Thus, we introduce several image-based perceived quality evaluation metrics. Then, we propose a general and effective model to illustrate the relationship between computational resources and user-perceived quality evaluation metrics. To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for the optimal ASP selection. Simulation results show that the proposed algorithm can provide a higher quality of generated content to users and achieve fewer crashed tasks by comparing with four benchmarks, i.e., overloading-avoidance, random, round-robin policies, and the upper-bound schemes. © 2023, CC BY.

关键词： Reinforcement learning

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Chiral exceptional point enhanced active tuning and nonreciprocity in micro-resonators

arXiv

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arXiv 2024年

作者： Lee, Hwaseob Chang, Lorry Kecebas, Ali Mao, Dun Xiao, Yahui Li, Tiantian Alù, Andrea Özdemir, Sahin K. Gu, Tingyi Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States Department of Engineering Science and Mechanics Pennsylvania State University University ParkPA16802 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States Department of Electrical and Computer Engineering Saint Louis University Saint LouisMO63103 United States

Exceptional points (EPs) have been extensively explored in mechanical, acoustic, plasmonic, and photonic systems. However, little is known about the role of EPs in tailoring the dynamic tunability of optical devices. A specific type of EPs known as chiral EPs has recently attracted much attention for controlling the flow of light and for building sensors with better responsivity. A recently demonstrated route to chiral EPs via lithographically defined symmetric Mie scatterers on the rim of resonators has not only provided the much-needed mechanical stability for studying chiral EPs, but also helped reduce losses originating from nanofabrication imperfections, facilitating the insitu study of chiral EPs and their contribution to the dynamics and tunability of resonators. Here, we use asymmetric Mie scatterers to break the rotational symmetry of a microresonator, to demonstrate deterministic thermal tuning across a chiral EP, and to demonstrate EP-mediated chiral optical nonlinear response and efficient electro-optic tuning. Our results indicate asymmetric electro-optic modulation with up to 17dB contrast at GHz and CMOS-compatible voltage levels. Such wafer-scale nano-manufacturing of chiral electro-optic modulators and the chiral EP-tailored tunning may facilitate new micro-resonator functionalities in quantum information processing, electromagnetic wave control, and optical interconnects. © 2024, CC BY.

关键词： Microresonators

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A Distributed Task Allocation Protocol for Cooperative Multi-UAV Search and Rescue Systems

A Distributed Task Allocation Protocol for Cooperative Multi...

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2021 international Conference on Unmanned Aircraft Systems, ICUAS 2021

作者： De Freitas, Edison Pignaton Basso, Maik Da Silva, Antonio Arlis Santos Vizzotto, Marcos Rodrigues Correa, Mateus Schein Cavalheiro Federal University of Rio Grande Do sul Graduate Program in Electrical Engineering Porto Alegre Brazil Federal University of Rio Grande Do sul Graduate Program in Computer Science Porto Alegre91.501-970 Brazil Federal University of Rio Grande Do sul Department of Electric Automation and Energy Porto Alegre Brazil

ISBN: (纸本)9780738131153

Nowadays, applications involving multiple robotic systems connected through a wireless network - to perform tasks together - have an increased research interest. Unmanned Aerial Vehicles (UAVs) are excellent tools for evaluating and surveying distributed robotic systems applications due to their flexibility and three-dimensional mobility capability. Cooperative systems composed of multiples UAVs may have a centralized coordination which assists the members of a team to make their decisions in a distributed manner regarding the tasks to be performed. This paper proposes a system composed of embedded hardware and a high-level communication protocol that serves as a basis for identifying, distributing, and allocating tasks in a simple and distributed way to be used by groups of UAVs. The proposal is evaluated in a search and rescue scenario. The setup is configured with two types of UAVs - namely, searchers (search for new tasks) and workers (execution of tasks). Also, a set of nine simulation experiments covering three different setups were performed. Then the proposal is evaluated by two sets of field experiments with real vehicles. The obtained results in the proposed experiments demonstrate that the system can be successfully used in the proposed scenario for task distribution and allocation. © 2021 IEEE.

关键词： Antennas

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A Novel Resource Allocation in Software-Defined Networks for IoT Application

A Novel Resource Allocation in Software-Defined Networks for...

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international Conference on Software, Telecommunications and computer Networks (SoftCOM)

作者： Alexandre Ladeira de Sousa Ogobuchi Daniel OKey Renata Lopes Rosa Muhammad Saadi Demostenes Zegarra Rodriguez Department of Computer Science Federal University of Lavras Lavras Minas Gerais Brazil Graduate Program in Information Engineering Federal University of ABC Santo Andre Sao Paulo Brazil Department of Electrical Enginnering University of Central Punjab Punjab Pakistan Computer Science Department Federal University of Lavras Lavras Minas Gerais Brazil

The rapid proliferation of Internet of Things (IoT) devices has posed significant challenges for network resource allocation and management. In this paper, we propose a novel methodology for efficient resource allocation in Software-Defined Networks (SDNs) to meet the unique requirements of IoT applications. Our approach leverages the flexibility and programmability of SDN to dynamically allocate network resources based on the specific needs of IoT devices. Our proposal combines reinforcement learning with dynamic resource allocation, demonstrating its effectiveness in optimizing resource allocation and enhancing network performance. The results highlight the potential of our approach to addressing the resource challenges in SDN-based IoT environments. The proposed method obtains results superior to 30% of throughput in comparison to a traditional resource allocation in SDN to IoT applications.

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