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Constructing a Segmentation Model for Patients with Leukoaraiosis Using Deep Learning Algorithms 24

Constructing a Segmentation Model for Patients with Leukoara...

引用

8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Lo, Li-Ting Tsai, Yi-Chia Chang, Yi-Jou Ting, Hsien-Wei Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare New Taipei City242 Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Many patients with leukoaraiosis (LA) exhibit mild and difficult-to-detect symptoms in the early stages, and due to the lack of effective detection methods, the optimal timing for treatment is often missed. This not only makes later treatment more difficult but, in severe cases, can even lead to mild to severe dementia. Therefore, in addition to relying on radiologists to manually interpret magnetic resonance imaging (MRI) scans, finding more effective detection methods has become extremely urgent. This study aimed to combine image processing and deep learning technologies to develop a model capable of accurately identifying and segmenting white matter hyperintensities (WMHs) to assist doctors in the early diagnosis of LA. We first performed efficient preprocessing on MR image slices from two different series and used the ResNet18 model to identify key slices containing WMHs, ultimately achieving precise segmentation of WMH areas with the U-Net model. This research focused on developing innovative preprocessing techniques, improving the accuracy by 12.3% with a limited dataset through preprocessing. Ultimately, the ResNet18 model achieved an F1 score of 0.829, while the U-Net model’s intersection over union (IoU) and Dice coefficient reached 0.750 and 0.857, respectively, showing the potential of this architecture. We propose improvements in the final chapter to construct a more comprehensive model. © 2024 Copyright ACM.

关键词： Deep learning

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Dual sensor for simultaneous measurement of electrical impedance and temperature during ice formation process

Dual sensor for simultaneous measurement of electrical imped...

引用

International Symposium on Instrumentation Systems, Circuits and Transducers (INSCIT)

作者： Jean Paulo Nakatu Longo José Rodolfo Galvão Jean Carlos Cardozo da Silva Cicero Martelli Rigoberto E. M. Morales Marco Jose da Silva Graduate Program in Electrical and Computer Engineering (CPGEI) Universidade Tecnológica Federal do Paraná Multiphase Flow Research Center (NUEM) Universidade Tecnológica Federal do Paraná

Impedance spectroscopy is often applied to characterize solids and fluids since each substance presents its own and sometimes unique impedance spectra. In industrial applications, impedance spectroscopy has the potential to monitor many processes such as those occurring in chemical reactors or liquid transportation in pipelines. In this paper, we introduce a sensor being able to perform measurements of impedance spectra (from few Hz to few MHz) allied to precise temperature measurements based on optical fiber Bragg grating sensors which was applied for monitoring ice formation, as exemplary process. The new sensor is described, calibrated and tested. The system was evaluated by measurements with known substances. Ice formation process was monitored and some findings are presented and discussed.

关键词： Ice Temperature measurement Impedance Temperature sensors Fiber gratings Permittivity

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Doubly Penalized LASSO for Reconstruction of Biological Networks

Doubly Penalized LASSO for Reconstruction of Biological Netw...

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作者： Asadi, Behrang Maurya, Mano Ram Tartakovsky, Daniel M. Subramaniam, Shankar Departments of Bioengineering and Mechanical and Aerospace Engineering University of California San Diego Danaher Labs la Jolla Santa ClaraCA United States San Diego Supercomputer Center Department of Bioengineering University of California San Diego San DiegoCA United States Department of Mechanical Aerospace Engineering University of California San Diego San DiegoCA United States Department of Bioengineering Departments of Computer Science and Engineering Cellular and Molecular Medicine and the Graduate Program in Bioinformatics University of California San Diego San DiegoCA United States

Reconstruction of biological and biochemical networks is a crucial step in extracting knowledge and causal information from large biological data sets. This task is particularly challenging when dealing with time-series data from dynamic networks. We have developed a new method, called doubly penalized least absolute shrinkage and selection operator (DPLASSO), for the reconstruction of dynamic biological networks. Our method consists of two components: statistical significance testing of model coefficients and penalized/constrained optimization. A partial least squares (PLS) with statistical significance testing acts as a supervisory-level filter to extract the most informative components of the network from a data set. Then, LASSO with extra weights on the smaller parameters identified in the first layer is employed to retain the main predictors and to set the smallest coefficients to zero. We present two case studies to compare the relative performance of DPLASSO and LASSO in terms of several metrics, such as sensitivity, specificity, and accuracy. The first case study employs a synthetic data set;it demonstrates that DPLASSO substantially improves network reconstruction in terms of accuracy and specificity. The second case study relies on simulated data sets for cell division cycle of fission yeast and shows that DPLASSO overall outperforms LASSO and PLS in terms of sensitivity, specificity, and accuracy. Combining PLS with statistical significance testing and LASSO provides good performance with respect to several metrics. DPLASSO is well suited for reconstruction of networks with low and moderate density. For high-density networks, high specificity is desired, making PLS a more suitable approach. © 1963-2012 IEEE.

关键词： Least squares approximations

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Fault detection of uncertain nonlinear process using interval-valued data-driven approach

Fault detection of uncertain nonlinear process using interva...

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

作者： Khaled Dhibi Radhia Fezai Kais Bouzrara Majdi Mansouri Abdelmalek Kouadri Mohamed-Faouzi Harkat Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir University of Monastir Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar

ISBN: (数字)9781728110806

ISBN: (纸本)9781728110813

Kernel PCA (KPCA) has been extensively applied in fault detection (FD) field. However, it is constantly not optimal for uncertain systems and is not designed to handle large-scale process monitoring. Thus, a nonlinear fault detection (FD) method based interval reduced KPCA (IRKPCA) is developed for fault detection. The proposed IRKPCA technique uses interval-valued Euclidean distance as a criterion to maintain only the more pertinent measurements. The FD abilities of the IRKPCA technique is assessed using the Tennessee Eastman Process (TEP). The effectiveness of the proposed technique is assessed in terms of computation time (CT), false alarm rate (FAR)and missed detection rate (MDR).

关键词： Uncertain systems Uncertainty Fault detection Tools Nonlinear systems Kernel Principal component analysis

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Customer Service Chatbot Enhanced with Conversational Language Understanding and Knowledge Base

Customer Service Chatbot Enhanced with Conversational Langua...

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IEEE Eurasia Conference on IOT, Communication and engineering (ECICE)

作者： Chin-Chih Chang Wen-Shing Cheng Sean Hsiao Bachelor’s Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan

ISBN: (纸本)9781665482097

A customer service chatbot enhanced with conversational language understanding and knowledge base is developed. Here, we explore LUIS and QnA Maker which are unified as Azure cognitive service for language. LUIS is a cloudbased conversational AI service that responds a user intelligence. QnA maker is a knowledge base for custom question answering. This question-and-answer knowledge base is especially useful for customer dialogs. Hence, by combining the services, we provide a smart response and provide a knowledge base to understand and improve the service. We implement this chatbot on the LINE Bot platform. Users easily access it by simply adding the representative of this chatbot on LINE. In addition, we put marketing information through this chatbot. The experiments are conducted, and the results show the chatbot is feasible and has a high user acceptance.

关键词： Customer services Knowledge based systems Chatbots Question answering (information retrieval)

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Multi-UAVs communication for payload data link enhancement under asynchronous access

Multi-UAVs communication for payload data link enhancement u...

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International Conference on Wireless and Optical Communications ( WOCC)

作者： Yun-Ruei Li Hsin-Piao Lin Li-Chun Wang Abebe Belay Adege Li-Yong Chen Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan Department of Electrical Engineering National Chiao Tung University Hsinchu Taiwan Department of International Graduate Program in Electrical Engineering and Computer Science (EECS) National Taipei University of Technology Taipei Taiwan

Recently, unmanned Aerial Vehicles (UAVs) are widely applied in civilian and commercial areas. In order to rapidly arrange the UAVs in a variable and changeable environment, the technique of maintaining stable and reliable communication link between Ground Control Station (GCS) and UAVs is one of the main issues [1]. However, UAVs deployment can significantly increase the efficiency of missions execution and the flexibility of task allocation. As discussed by different scholars, multi-UAVs have a number of advantages depending on the application areas: disaster areas monitoring, wireless sensor data collection in precision agriculture, and relay-aided of UAVs network topology [2].

关键词： OFDM Resource management Interference Wireless communication Payloads Bandwidth Optical filters

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Stock Price Prediction and Recommendation Approach Based on Machine Learning

Stock Price Prediction and Recommendation Approach Based on ...

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IEEE Eurasia Conference on IOT, Communication and engineering (ECICE)

作者： Chin-Chih Chang Kei-Wen Luo Sean Hsiao Bachelor’s Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan

ISBN: (纸本)9781665482097

Investment is a lifetime work. Investing in stocks is a popular measure. However, investing in stocks is not easy, and losing money is not uncommon. We investigate if there is a systematic way to find buyable stocks and more importantly when to buy and sell them. Nowadays, with the progress of hardwarel, artificial intelligence (AI) has become a feasible solution to many issues. Machine learning and deep learning are two widely adopted methods in AI. In this study, we show how to apply machine learning to stock prediction and recommendation. After trials, we found that LightGBM shows its potential to predict and recommend stocks. We used the data of the Taiwan stock market to validate the method. We compared the prediction and recommendation with the wellknown Taiwan ETFs 0050 and 0056. The results show that the method is feasible, effective, efficient, and has better performance than Taiwan ETFs 0050 and 0056.

关键词： Deep learning Systematics Stock markets Investment

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A low power miniaturized CMOS-based continuous glucose monitoring system

A low power miniaturized CMOS-based continuous glucose monit...

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2013 IEEE International Conference on Body Sensor Networks, BSN 2013

作者： Croce Jr., Robert A. Vaddiraju, Santhisagar Legassey, Allen Wang, Yan Burgess, Diane Papadimitrakopoulos, Fotios Jain, Faquir C. Biorasis Inc. Technology Incubation Program Storrs CT 06269 United States Department of Pharmaceutical Sciences University of Connecticut Storrs CT 06269 United States Dept. of Chemistry Institute of Materials Science University of Connecticut Storrs CT 06269 United States Department of Electrical and Computer Engineering University of Connecticut Storrs CT 06269 United States

ISBN: (纸本)9781479903306

This paper presents the design and fabrication of a highly-miniaturized system for continuous glucose monitoring which holds great promise for patients inflicted with diabetes mellitus. To achieve the realization of a truly implantable system, a variety of issues such as robust electrochemical sensor design, miniaturization of the electronic components and counteracting biofouling and negative tissue response need to be addressed. In this report, we present a highly-miniaturized transcutaneous continuous glucose monitoring system which holistically addresses the aforementioned tribulations associated with implantable devices. Specifically, a high performance amperometric electrochemical glucose sensor is integrated with custom designed complementary metal-oxide-semiconductor electronics. The fabricated electrochemical sensor is Clark-based, and employs stratification of five functional layers to achieve a linear response within the physiological range of glucose concentration (2-22 mM). Furthermore, the sensor is encased with a thick polyvinyl alcohol (PVA) hydrogel containing poly(lactic-co-glycolic acid) (PLGA) microspheres which provides continuous, localized delivery of dexamethasone utilized to combat inflammation and fibrosis. Such miniature size (0.665 mm2) and low power operation (140 μW) of the electronic system render it ideal for continuous glucose monitoring devices and other metabolic sensing systems. © 2013 IEEE.

关键词： CMOS integrated circuits

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Combining function points software estimation model with ADISSA methodology for systems analysis and design

Combining function points software estimation model with ADI...

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Israel Conference on computer Systems and Software engineering

作者： P. Shoval O. Feldman Information Systems Program Department of Industrial Engineering and Management Ben-Gurion University of the Negev Beersheba Israel Department of Mathematics and Computer Science Ben-Gurion University of the Negev Beersheba Israel

The study proposes a combination of the function points model for software estimation with the ADISSA methodology for systems analysis and design. This combined approach, which is supported by a software tool, enables one to estimate various software metrics, such as size, effort, and duration, in the early stages of systems development, by basing them on the products of a thorough system analysis and design process.

关键词： Software measurement System analysis and design Project management Costs programming Mathematical model Software development management Information analysis Management information systems Industrial engineering

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Terahertz Time-Domain Imaging for Radiotherapy Treatment Monitoring in Pancreatic Ductal Adenocarcinoma

Terahertz Time-Domain Imaging for Radiotherapy Treatment Mon...

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CLEO: Applications and Technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Chakraborty, Debamitra Mills, Bradley N. Cheng, Jing Komissarov, Ivan Gerber, Scott Sobolewski, Roman Materials Science Graduate Program University of Rochester RochesterNY14627 United States Laboratory for Laser Energetics University of Rochester RochesterNY14623-1299 United States Department of Surgery University of Rochester Medical Center RochesterNY14642 United States Department of Electrical and Computer Engineering University of Rochester RochesterNY14627-0231 United States

ISBN: (纸本)9781957171395

Terahertz time-domain imaging was performed of stereotactic body radiotherapy-treated murine pancreatic ductal adenocarcinoma (PDAC) with a high spatial resolution. To generate 2D maps of the tissue samples, the refractive index and absorption coefficient were used as imaging markers extracted with the maximum a-posteriori probability (MAP) estimation algorithm. The results were then compared with the terahertz maps of untreated murine PDAC tissue samples and demonstrated that terahertz imaging can probe physical changes with high sensitivity in the tissue post treatment. © Optica Publishing Group 2024, © 2024 The Author(s)

关键词： Tissue

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