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Simpasio em Sistemas Computacionais (WSCAD-SSC)

作者： Henrique Vianna Jorge Barbosa Cristiano Costa Adenauer C. Yamin Applied Computing Graduate Program-PIPCA UNISINOS Sao Leopoldo Brazil Computer Science-Polytechnic Center UCPEL Pelotas Brazil

Accordingly with the World Health Organization, heart disease, chronic respiratory diseases, cancer and diabetes are the most common chronic diseases and one of the leading causes of the mortality in the world. In such cases we need more than patient engagement to help to control of the disease, community and health organizations support is also desirable. These roles must support the patients' self-management activities, making them feel confident and motivated. This support can be accomplished by ubiquitous computing. The ubiquitous computing gives conditions to help chronic diseases patients in the management of their activities, offering support to them anytime, anywhere. In this context, this article presents U'Ductor, a model for supporting ubiquitous chronic care management, whose goal is to help the integration between patient and community resources. The U'Ductor gives a step forward in relation to the studied related works by integrating patients, community resources and community members. Those features were not completely explored in the studied works in the way we employ in U'Ductor. An implementation of the model was evaluated by a chronic patient, which gave a positive feedback about it.

关键词： Monitoring Middleware Biomedical monitoring Computational modeling Diseases Communities Diabetes

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COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach

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computers, Materials & Continua 2021年第7期68卷 391-407页

作者： Aqib Ali Wali Khan Mashwani Samreen Naeem Muhammad Irfan Uddin Wiyada Kumam Poom Kumam Hussam Alrabaiah Farrukh Jamal Christophe Chesneau Department of Computer Science Concordia College BahawalpurBahawalpur63100Pakistan Department of Computer Science&IT Glim Institute of Modern StudiesBahawalpur63100Pakistan Institute of Numerical Sciences Kohat University of Science&TechnologyKohat26000Pakistan Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Program in Applied Statistics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology ThanyaburiThanyaburi12110Thailand Departments of Mathematics Faculty of ScienceCenter of Excellence in Theoretical and Computational Science(TaCS-CoE)&KMUTT Fixed Point Research LaboratoryRoom SCL 802 Fixed Point LaboratoryScience Laboratory BuildingKing Mongkut’s University of Technology Thonburi(KMUTT)Bangkok10140Thailand Department of Medical Research China Medical University HospitalTaichung40402Taiwan College of Engineering Al Ain UniversityAl Ain64141United Arab Emirates Department of Mathematics Tafila Technical UniversityTafila66110Jordan Department of Statistics The Islamia University of BahawalpurBahawalpur63100Pakistan 11Department of MathematicsUniversitéde CaenLMNOCaen14032France

The purpose of this research is the segmentation of lungs computed tomography(CT)scan for the diagnosis of COVID-19 by using machine learning *** dataset contains data from patients who are prone to the *** contains three types of lungs CT images(Normal,Pneumonia,and COVID-19)collected from two different sources;the first one is the Radiology Department of Nishtar Hospital Multan and Civil Hospital Bahawalpur,Pakistan,and the second one is a publicly free available medical imaging database known as *** the preprocessing,a novel fuzzy c-mean automated region-growing segmentation approach is deployed to take an automated region of interest(ROIs)and acquire 52 hybrid statistical features for each ***,12 optimized statistical features are selected via the chi-square feature reduction *** the classification,five machine learning classifiers named as deep learning J4,multilayer perceptron,support vector machine,random forest,and naive Bayes are deployed to optimize the hybrid statistical features *** is observed that the deep learning J4 has promising results(sensitivity and specificity:0.987;accuracy:98.67%)among all the deployed *** a complementary study,a statistical work is devoted to the use of a new statistical model to fit the main datasets of COVID-19 collected in Pakistan.

关键词： COVID-19 machine learning fuzzy c-mean deep learning J4

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Smooth graph signal interpolation for big data

arXiv

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arXiv 2018年

作者： Heimowitz, Ayelet Eldar, Yonina C. Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Faculty of Math and Computer Science Weizmann Institute of Science Rehovot Israel

In this paper we present the Markov variation, a smoothness measure which offers a probabilistic interpretation of graph signal smoothness. This measure is then used to develop an optimization framework for graph signal interpolation. Our approach is based on diffusion embedding vectors and the connection between diffusion maps and signal processing on graphs. As diffusion embedding vectors may be expensive to compute for large graphs, we present a computationally efficient method, based on the Nyström extension, for interpolation of signals over a graph. We demonstrate our approach on the MNIST dataset and a dataset of daily average temperatures around the US. We show that our method outperforms state of the art graph signal interpolation methods on both datasets, and that our computationally efficient reconstruction achieves slightly reduced accuracy with a large speedup. Copyright © 2018, The Authors. All rights reserved.

关键词： Computational efficiency

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Dermatological Diagnostics: A Unified Deep Learning Framework for Skin Lesion and Cancer Classification 1

Dermatological Diagnostics: A Unified Deep Learning Framewor...

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kumar, Vinod Jain, Isha Dongla, Durga Sritha Rai, Shivangi Rastogi, Vani Kaushik, Eva Kaushik, Rohit George Washington University School of Engineering and Applied Science WashingtonDC United States Dr. Akhilesh Das Gupta Institute of Technology and Management Computer Science and Engineering Department New Delhi India Gandhi Institute of Technology and Management Computer Science and Engineering Department Andhra Pradesh Visakhapatnam India Data Scientist DXC Technology Noida India Data Analytics Program University of Illinois CS and Mathematics Department Springfield United States

ISBN: (纸本)9798350356816

Skin pathologies encompass a spectrum of conditions, with malignancies such as melanoma representing a critical diagnostic urgency. This investigation delineates the deployment of Convolutional Neural Networks (CNNs) for the classification of dermatological anomalies, benchmarking CNN diagnostic fidelity against dermatological expert evaluations. The study underscores the efficacy of CNN classifiers in expediting the diagnostic workflow for various cutaneous disorders. Advocating for an automated diagnostic framework, the research introduces a CNN-based system aimed at reducing human diagnostic load, accelerating diagnostic timelines, and enhancing survival outcomes. Utilizing advanced image processing algorithms and deep learning architectures, the research presents an automated classification system for skin pathologies, addressing both benign and malignant presentations. The classification matrix includes nine dermatological conditions: actinic keratosis, basal cell carcinoma, benign keratosis, dermatofibroma, melanoma, nevus, seborrheic keratosis, squamous cell carcinoma, and vascular lesions. The objective is to engineer a CNN model with robust diagnostic performance across a diverse lesion dataset, ensuring accurate identification and categorization of dermatological conditions. © 2024 IEEE.

关键词： Convolutional neural networks

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BPS2025 - Structural basis of potassium selectivity in kalium channelrhodopsins

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Biophysical Journal 2025年第3期124卷 64a-65a页

作者： Seiya Tajima Yoon Seok Kim YoungJu Jo Peter Y. Wang Joseph M. Paggi Charu Ramakrishnan Shunki Takaramoto Takashi Nagata Masae Konno Kota Katayama Hideki Kandori Ron O. Dror Keiichi Inoue Karl Deisseroth Hideaki Kato Research Center for Advanced Science and Technology The University of Tokyo Tokyo Japan Department of Bioengineering Stanford University Stanford CA USA Department of Computer Science Stanford University Stanford CA USA Cracking the Neural Code Program Stanford University Stanford CA USA The Institute for Solid State Physics The University of Tokyo Kashiwa Japan PRESTO Japan Science and Technology Agency Kawaguchi Japan Department of Life Science and Applied Chemistry Nagoya Institute of Technology Nagoya Japan OptoBioTechnology Research Center Nagoya Institute of Technology Nagoya Japan Institute for Computational and Mathematical Engineering Stanford University Stanford CA USA Howard Hughes Medical Institute Stanford University Stanford CA USA Graduate School of Arts and Sciences The University of Tokyo Tokyo Japan

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Achieving compelling student comprehension of complex information structures for both on-site and on-line courses

Achieving compelling student comprehension of complex inform...

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2008 ASEE Annual Conference and Exposition

作者： Uhlig, Ronald Farahani, Alireza Viswanathan, Shekar Evans, Howard Sotelo, Mark National University Department of Computer Science and Information Systems School of Engineering and Technology National University Wireless Communications for the Master ot Science in Wireless Communications Program International Telecommunications Academy School of Engineering and Technology Department of Applied Engineering Lead Faculty for Engineering Management and Homeland Security and Safety Engineering Academic Computing for National University

Teaching engineering and technology subjects involves conveying understanding of abstract information structures and processes such as complex telecommunications protocols, complex mathematical concepts, and data structures. These are multidimensional and can be difficult to grasp quickly. Supported by a Hewlett-Packard (HP) Technology for Teaching grant, the School of Engineering and Technology at National University has embarked on a project to enable students to grasp these complex concepts more quickly and easily, using continuous dialog among students and instructors as the structures are first introduced and then examined from multiple perspectives through real-time interaction among students, small groups, and instructors. HP Wireless Tablet PCs are used to discuss and experiment with diagrams and processes in realtime. This allows combining lectures and problem-solving sessions into a single class session. Our hypothesis is that: 1) an in-depth learning of theory is accomplished, and 2) student engagement is enhanced. Presentation of theory by the instructor is integrated with application while the theory is still in the student's short-term memory. Students no longer have to wait for a separate session such as a recitation session to apply the concepts. This approach often takes less time. In addition to accelerating the learning process, expert instructors find this approach more rewarding as students grasp new concepts more quickly. Analysis of data captured from both students and instructors are presented to support our hypotheses, and our results are compared with similar research carried out by other universities. In addition, the level of interaction enabled by the use of HP Tablets in on-line classes is discussed. The best teaching tools available in existing on-line teaching platforms are compared with the additional tools available in on-site courses when every student has a wireless Tablet PC and specific recommendations are made to on-line teachi

关键词： Students

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GISolve: A grid-based problem solving environment for computationally intensive geographic information analysis

GISolve: A grid-based problem solving environment for comput...

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3rd International Workshop on Challenges of Large Applications in Distributed Environments, CLADE 2005

作者： Wang, Shaowen Armstrong, Marc P. Ni, Jun Liu, Yan Academic Technologies - Research Services of Information Technology Services University of Iowa Iowa City IA 52242 Department of Geography University of Iowa Iowa City IA 52242 Program in Applied Mathematical and Computational Science University of Iowa Iowa City IA 52242 Department of Computer Science University of Iowa Iowa City IA 52242

ISBN: (纸本)0780390431

The purpose of this paper is to demonstrate the design and implementation of GISolve - a Grid-based problem solving environment for computationally intensive geographic information analysis based on geo-middleware. The geo-middleware resides between existing Grid middleware and geographic information analysis applications to manage heterogeneous and dynamic resources on behalf of analysis applications. At the same time, GISolve provides adaptive domain decomposition solutions to parallel geographic information analysis applications. Based on these domain decomposition solutions, GISolve also schedules distributed tasks and manages data transfers. In GISolve, these capabilities are designed as Grid services that are compliant with the open Grid service architecture (OGSA) and are implemented using Grid portal technologies. The GISolve implementation is illustrated based on a case study of a computationally intensive spatial statistic - [Gi(d)] that is used to assess spatial dependence among geographically distributional observations. © 2005 IEEE.

关键词： Problem solving

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Promoting holistic problem-solving in mechanics pedagogy

Promoting holistic problem-solving in mechanics pedagogy

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114th Annual ASEE Conference and Exposition, 2007

作者： Papadopoulos, Chris Bostwick, Josh Dressel, Andrew University of Wisconsin Milwaukee United States Cornell University United States Department of Civil Engineering and Mechanics University of Wisconsin Milwaukee United States UWM Computer Science Engineering and Mathematics Scholarship Program Brazil Department of Theoretical and Applied Mechanics Cornell University United States

The authors propose three strategies that are designed to enhance students' understanding and problem-solving ability in introductory mechanics courses: (1) employing multiple-method problem-solving, in which students solve a given problem using more than one method;(2) organizing systems of linear equations into a standard "tabular" format which resembles matrix format;and (3) emphasizing the discussion and use of assumptions in problem-solving activities. The authors give a rationale for each strategy, present a review of several mechanics textbooks to determine the prevalence of these strategies, and provide local student performance data that, while as yet inconclusive, suggests a possible method for assessment of the strategies' efficacy. © American Society for Engineering Education, 2007.

关键词： Mechanics

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Positive photoresist process simulation over nonplanar substrates

Journal of Vacuum Science & Technology B: Microelectronics P...

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Journal of Vacuum science & Technology B: Microelectronics Processing and Phenomena 1990年第6期8卷 1432-1436页

作者： Eytan Barouch Brian Bradie Uwe Hollerbach Steven A. Orszag Department of Mathematics and Computer Science Clarkson University Potsdam New York 13676 Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544

A three‐dimensional computational simulator of nonplanar substrates coated with positive photoresists is presented. The model includes four major steps: projection printing, exposure, post‐exposure baking (PEB), and dissolution. Projection printing is based on Hopkins’ classical work. The exposure model employs the full nonlinear wave equation coupled with the photoactive compound (PAC) bleaching rate equation. These equations are solved using a spectral element iterative scheme. The PEB is treated as a material diffusion equation employing ideas introduced by Mack and the dissolution algorithm is our LEAD (least action dissolution) algorithm modified for nonplanar substrates. Several realistic examples are presented displaying final profiles at various dissolution times.

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Raman Scattering and X-Ray Diffraction Studies of Gallium Nitride Films Grown on (100) Gallium Arsenide

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MRS Online Proceedings Library 1994年第1期339卷 503-508页

作者： S. W. Brown S. C. Rand C.-H. Hong D. Pavlidis University of Michigan Applied Physics Program Ann Arbor USA Department of Electrical Engineering and Computer Science University of Michigan Solid State Electronics Laboratory Ann Arbor USA

Raman spectroscopy and x-ray diffraction are used to characterize Gallium Nitride (GaN) films grown on (100) Gallium Arsenide (GaAs) substrates. Reflection X-ray diffraction data from (200) planes of GaAs and cubic GaN are presented. The linewidth of the cubic GaN diffraction peak is shown to be a strong function of the growth temperature. Raman spectra are presented for a series of samples grown at different temperatures. Raman scattering is characterized by strong peaks at 560 cm-1 and at 736 cm-1, corresponding to TO and LO phonon modes of cubic GaN, respectively. An additional, unexplained feature at 768 cm-1 is clearly observed in Raman spectra of c-GaN samples grown at lower temperatures. The polarization dependence of the intensity of the GaN LO phonon mode is presented and compared with the GaAs LO phonon mode to establish the relative orientation of the c-GaN epitaxy on GaAs.

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