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A metric for automatic hole characterization

19th International Meshing Roundtable, IMR 2010

作者： German Sanchez, T. Branch, John W. Atencio, Pedro Faculty of Engineering Systems Engineering Program Magdalena University Colombia School of System and Informatics Faculty of Minas National University of Colombia Medellin Colombia

ISBN: (纸本)9783642154133

The correct repair of three-dimensional models is still an open research problem, since acquiring processes (methods and technology) still have limitations. Although a wide range of approaches have been proposed, the main limitation is that user intervention is required to decide which regions of the surface should be corrected. We propose an automatic method for hole characterization enabling the classification of real and false anomalies without user intervention by using an irregularity measure based on two geometrical estimations: the torsion contour's estimation uncertainty, and an approximation of geometrical shape measure surrounding the hole. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Torsional stress

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Influence of blended learning on learning result of algorithm and programming 3

Influence of blended learning on learning result of algorith...

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3rd International Conference on informatics and Computing, ICIC 2018

作者： Anggrawan, Anthony Ibrahim, Nurdin Suyitno, M. Satria, Christofer Informatics Engineering Study Program of College of Informatics Management and Computer Science Bumigora West Nusa Tenggara Indonesia Education Technology Study Program of Jakarta State University Jakarta Indonesia Education Technology Study Program of Jakarta State University Jakarta Indonesia Visual Communication Design Study Program of College of Informatics Management and Computer Science Bumigora West Nusa Tenggara Indonesia

ISBN: (纸本)9781538669204

The advancement of today's learning technology makes the learning process no longer fully bases on face to face learning, but can achieve by online learning. Online learning is not only useful in overcoming deficiencies in conventional classroom learning, but also a means to meet the learning styles of students who are less fond of and/or dislike face-to-face learning. On the other hand, the main disadvantage of online learning is the lack of face-to-face interaction, while the strength of face-to-face learning is the intensity of student interaction with teachers, the ease of cooperative learning and the clarity of learning materials. In turn, the superiorities on face-to-face learning and online self-learning can be acquired by blended learning. However, blended learning is a learning solution by taking the best advantage of face-to-face classroom learning and online learning. Blended learning has been a learning solution of today's learning. In this study, two blended learning that has different learning content portions between the portion of face-to-face learning materials and online self-learning was conducted to find out which blended learning results produce better pedagogy between two blended learning, and how well the learning outcomes of blended learning are, especially for Algorithm and programming subject. The research results showed the blended learning with 60% face-to-face learning content and 40% online self-learning content delivers learning cognitive competency outcomes worse than 40% face-to-face learning content and 60% online self-learning content. The learning outcome of both blended learning is good, that is greater than 60% from the ideal number. © 2018 IEEE.

关键词： Students

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Beyond connectivity-new metrics to evaluate robustness of networks

Beyond connectivity-new metrics to evaluate robustness of ne...

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International Conference on High Performance Switching and Routing

作者： Banerjee, Sujogya Shirazipourazad, Shahrzad Ghosh, Pavel Sen, Arunabha Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University Tempe AZ 85281 United States

ISBN: (纸本)9781424484560

Robustness or fault-tolerance capability of a network is an important design parameter in both wired and wireless networks. Connectivity of a network is traditionally considered to be the primary metric for evaluation of its fault-tolerance capability. However, connectivity (G) (for random faults) or region-based connectivity R(G) (for spatially correlated or region-based faults, where the faults are confined to a region R) of a network G, does not provide any information about the network state, (i.e., whether the network is connected or not) once the number of faults exceeds (G) or R(G). If the number of faults exceeds (G) or R(G), one would like to know, (i) the number of connected components into which G decomposes, (ii) the size of the largest connected component, (iii) the size of the smallest connected component. In this paper, we introduce a set of new metrics that computes these values. We focus on one particular metric called region-based component decomposition number (RBCDN), that measures the number of connected components in which the network decomposes once all the nodes of a region fail. We study the computational complexity of finding RBCDN of a network. In addition, we study the problem of least cost design of a network with a target value of RBCDN. We show that the optimal design problem is NP-complete and present an approximation algorithm with a performance bound of O(log K + 4log n), where n denotes the number of nodes in the graph and K denotes a target value of RBCDN. We evaluate the performance of our algorithm by comparing it with the performance of the optimal solution. Experimental results demonstrate that our algorithm produces near optimal solution in a fraction of time needed to find an optimal solution. © 2011 IEEE.

关键词： Approximation algorithms

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Logistic Regression Model of Relationship between Breast Cancer Pathology Diagnosis with Metastasis 3

Logistic Regression Model of Relationship between Breast Can...

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3rd International Conference on Statistics, Mathematics, Teaching, and Research 2019, ICSMTR 2019

作者： Bustan, M.N. Poerwanto, B. Statistics Study Program Universitas Negeri Makassar Makassar Indonesia Department of Informatics Engineering Universitas Cokroaminoto Palopo Indonesia

Management of breast cancer requires a diagnosis of breast cancer, including an accurate pathology diagnosis to direct the provision of appropriate treatment. Part of inseparable diagnosis of breast cancer itself is determining the presence of metastasis. This study aims to determine the relationship model of pathological diagnosis with the possibility of metastasis to other organs of the breast. Pathology diagnosis results include tumor position, topography, behavior, grade, and tumor status. This study used secondary data from the Hospital Information System (SIRS) of the hospital in Makassar, Indonesia. Data obtained from the results of pathology and clinical examinations of breast tumor as many as 204 patients were hospitalized during the year of 2018. Binary regression analysis modeling was performed to see the relationship between types of pathological diagnosis (laterality, topography, behavior, grade, tumor status) of breast cancer with the possibility of metastases to other organs. The results of the analysis found a significant relationship between the position and status of the tumor with the presence of metastasis. The results of the metastatic binary logistic regression model was L(Y) = 1.330 - 0.670lat1 - 0.779lat2 - 0.724status Chi-square analysis between metastasis with surgery and chemotherapy found the significant relationships between metastasis with surgery (X2 = 15.951;p value = 0.001) and metastasis with chemotherapy (X2 = 20,796;p value = 0.001). The results of this analysis indicate that the position and status of the tumor have a relationship with the likelihood of metastasis. In addition, this metastasis further determines the management of treatment whether surgery or chemotherapy or both. © Published under licence by IOP Publishing Ltd.

关键词： Diagnosis

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Secure and Effective Reengineering Information System and Business Processes of Cross-Border Control between the Republic of Indonesia and the Republic Democratic of Timor-Leste 6

Secure and Effective Reengineering Information System and Bu...

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6th International Conference on Cyber and IT Service Management, CITSM 2018

作者： Fransiskus Tjiptabudi, M.H. Igon, Skolastika Siba Bernardino, Raul Muharram, Asep T. Study Program Information System STIKOM Uyelindo Kupang Indonesia Informatics Engineering Department Pamulang University Banten Indonesia

ISBN: (纸本)9781538654330

Technology disruption had boost every sector to adapt and to adjust an infrastructure and system according to the specific needs and business process which can improve an effective operation for the decision making processes and reporting systems within the workflow, social capability, data integrity, and open standard frameworks. Current administration process for capturing cross-border (traveler) in terrestrial immigration posts are used a conventional or handwriting;-passport information is collected on arrival or departure immigration cards or use of ' Pas Lintas Batas' (PLB) special cards for the inhabitant was living alongside both countries border. It is quite difficult to organize cross-border cards for the archiving, filing system, retrieve data, and recapitulate numbers of cross borders for reporting purposes such as individual activities per cities and aims, daily, weekly, and monthly reports. The research will use waterfall with subprojects method within the mentioned modern framework. The aim of this research is to produce an effective and secure information system application prototype for immigration authorities, especially for terrestrial border control system. © 2018 IEEE.

关键词： Information systems

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Testing Real-Time Applications on Windows 10 IOT Using the Nyquist Theory 1

Testing Real-Time Applications on Windows 10 IOT Using the N...

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1st International Conference on Computer Science and Applied Mathematic, ICCSAM 2018

作者： Syahputa, Zulfahmi Zarlis, M. Nasution, Beny B. Informatics Engineering Study Program Magister Faculty of Computer Science Information Technology Universitas Sumatera Utara Medan Indonesia

Raspberry Pi is a mini-computer that is provided to carry out activities quickly and precisely, but Raspberry Pi was created to not be able to do the real-time system with the support of Windows 10 IoT operating system, so the real-time system can be done on Raspberry Pi. The real-time applied in the application needs to be tested with the Nyquist theory. The purpose of this study was to get real-time system measurements available on Windows 10 IoT. This test is done using the Nyquist theory by calculating the results of measurements on mp3 streaming performed on Windows 10 IoT. © Published under licence by IOP Publishing Ltd.

关键词： Real time systems

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Development of Urban Data Sensing for Smart City Platform 10

Development of Urban Data Sensing for Smart City Platform

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Prabowo, Okyza Maherdy Supangkat, Suhono Harso Mulyana, Eueung Doctoral Program of School of Electrical Engineering and Informatics Institut Teknologi Bandung STMIK AMIK Bandung Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Smart City and Community Innovation Center Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9798350339543

The idea of a 'smart city' is one in which cities may effectively and efficiently manage their resources to raise the standard of living of its residents. Cities are already capable of performing sensing, understanding, and acting at a certain degree because to the existence of information technology as an enabler. Several studies have created various physical sensors for sensing in order to produce data. However, urban data is not limited to factual information on the environment and infrastructure. In order to collect data from the digital world, including social media, online news, and other digital social sensors, this research aims to create an urban data collecting system. The creation of digital urban sensor data can enhance the accuracy of the information that can help decision-makers. © 2023 IEEE.

关键词： Smart city

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Evaluation of an Intelligent Edge Computing System for the Hospital Intensive Care Unit 3

Evaluation of an Intelligent Edge Computing System for the H...

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3rd IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability, ECBIOS 2021

作者： Zida, Serge Ismael Lin, Yue-Der Lee, Cheng Lin Tsai, Yi Lun Program of Electrical and Communications Engineering Feng Chia University Taichung Taiwan Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan

ISBN: (纸本)9781728193045

The evolution of medical technology along with information and communication technologies has accelerated the development and operationalization of smart hospitals recently. Traditionally, such hospitals typically rely on cloud computing platforms for data treatment and processing. However, the expansion and popularization of Internet of Medical Things (IoMT) devices and constant data monitoring have resulted in massive amounts of generated data, leading to the overload of the cloud infrastructure. This results in high power consumption and latency in data transmission, which is critical especially in a healthcare environment where data flow must be particularly responsive. Thus, we proposed and designed a Raspberry Pi-based edge computing system to computer-intensive care unit (ICU) data at the periphery of the network to offload the hospital cloud platform. ICU medical data were simulated from the PhysioNet MIMIC III database and transferred to the edge platform for computation and identification of emergency cases that were then sent to the cloud level. We further discuss the current issues and prospects of edge computing in hospitals. © 2021 ECBIOS 2021. All rights reserved.

关键词： Intensive care units

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Multi-Step-Ahead Prediction of User Movement on 5G Networks Using the Long Short-Term Memory Method 18

Multi-Step-Ahead Prediction of User Movement on 5G Networks ...

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18th International Conference on Telecommunication Systems, Services, and Applications, TSSA 2024

作者： Timoteo, Adriel Benyamin, Fabian Rafinanda Anargyarahman, Naufal Bhanu Iskandar Yuliana, Hajiar School of Electrical Engineering and Informatics Telecommunications Engineering Program Bandung Institute of Technology Bandung Indonesia Jenderal Achmad Yani University Faculty of Engineering Department of Electrical Engineering Cimahi Indonesia

ISBN: (纸本)9798331527686

Since the initial launch of 5G networks in 2018, 5G technology has rapidly expanded to cover about 40% of the world's population, offering higher bandwidth, faster connectivity, and lower latency than 4G. However, due to its higher frequency operation, 5G necessitates more frequent handovers, making efficient handover performance crucial. This research focuses on enhancing handover efficiency by predicting user movement using Long Short-Term Memory (LSTM) models for multi-step-ahead prediction. The model created will utilize 60 seconds of historical data to predict 10 seconds ahead, with a target to achieve an average prediction accuracy of less than 20 meters with a latency under 100 ms. The study employs TensorFlow for model training, leveraging the Grab-Posisi dataset, and utilizes Plotly and TensorBoard for result visualization. Six model variations were trained, with the 16-unit model trained for 3106 epochs performing best, achieving 16.99 meters accuracy and 31 ms latency. The findings suggest that LSTM is effective for predicting user movement in 5G networks, with potential accuracy improvements through extended training epochs. © 2024 IEEE.

关键词： Prediction models

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Tuning the Size and Stiffness of Inflatable Particles

arXiv

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arXiv 2025年

作者： Pashine, Nidhi Wang, Dong Baines, Robert Goyal, Medha Shattuck, Mark D. O’Hern, Corey S. Kramer-Bottiglio, Rebecca Department of Mechanical Engineering Yale University New HavenCT06520 United States Department of Physics BioInspired Institute Syracuse University SyracuseNY13244 United States Department of Physics Benjamin Levich Institute City College of New York New York CityNY10031 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States Graduate Program in Computational Biology & Biomedical Informatics Yale University New HavenCT06520 United States

We describe size-varying cylindrical particles made from silicone elastomers that can serve as building blocks for robotic granular materials. The particle size variation, which is achieved by inflation, gives rise to changes in stiffness under compression. We design and fabricate inflatable particles that can become stiffer or softer during inflation, depending on key parameters of the particle geometry, such as the ratio of the fillet radius to the wall thickness, r/t. We also conduct numerical simulations of the inflatable particles and show that they only soften during inflation when localization of large strains occurs in the regime r/t → 0. This work introduces novel particle systems with tunable size and stiffness that can be implemented in numerous soft robotic applications. © 2025, CC BY.

关键词： Stiffness

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