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Tsunami evacution building model (TEBM) in Teluk Palu (Palu Bay) area

IOP Conference Series: Materials Science and engineering 2022年第1期1212卷

作者： M Bakri R Awalia S Mulyati F Zubaidi M Rusydi A A Kasim R Prawita Department of Architecture Faculty of Engineering Tadulako University PaluIndonesia Department of Physics Faculty of Mathematics and Natural Sciences Tadulako University Palu Indonesia Department of Informatics Faculty of Engineering Tadulako University Palu Indonesia Study Program of Architecture Faculty of Engineering Tadulako University Palu Indonesia

The research was conducted in the coastal area of Palu Bay, Lere Village. Data were collected using observation, interviews, and literature study techniques. The data were analyzed using qualitative descriptive methods and focused on the concept of the design of the tsunami evacuation building on the coast of Palu Bay. Data analysis was carried out to obtain an overview of the problems that occurred at the planning location which was analyzed with the concept of architectural design by considering the existing conditions of the site and the surrounding environment, as well as utilizing the potential of the site so that it has the potential for building functions. The conclusion obtained is based on the results of data analysis, it is necessary to have a building that can function as an evacuation container for the community when a disaster occurs in the coastal area of Palu Bay, thereby reducing the number of casualties. The benefit of this research is that it is a solution for local people to save themselves when the tsunami disaster.

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The design of micro-perforated panel (MPP) on noise case of APU GTCP 331-350 airbus A330 aircraft

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AIP Conference Proceedings 2023年第1期2601卷

作者： Lazuardy Rahendra Pinandhita Thomas Ken Darmastono Study Program of Aerospace Engineering Faculty of Aerospace Technology Adisutjipto Institute of Aerospace Technology Jalan Majapahit Blok-R Lanud Adisutjipto Bantul D.I. Yogyakarta 55198 Indonesia Study Program of Informatics Faculty of Industrial Technology Adisutjipto Institute of Aerospace Technology Jalan Majapahit Blok-R Lanud Adisutjipto Bantul D.I. Yogyakarta 55198 Indonesia

In general, noise is a problem and it can be found everywhere, including at the aero activity such as aircraft maintenance vicinity. The object of the noise case selected in this study is the Auxiliary Power Unit (APU) which is the part of Airbus A330 aircraft with the APU type GTCP 331-350. The noise of APU while operate during maintenance can affect the occupational health and safety conditions of the worker. In this study, a micro-perforated panel (MPP) is used to absorb or reduce the sound intensity. MPP is made of a thin flat material where in this research using acrylic and placing small holes on its surface. Both experimental and numerical method are used in this research. The first step in performing the MPP design is numerically to obtain the geometry according to the absorption coefficient target at the specified noise frequency. For the experimental or testing phase of finished MPP design, a tool called an impedance tube is used. The test procedure refers to the ISO 10534-2 or ASTM E 1050-90 document. There are two types of impedance tube, first in diameter of 10 mm and the second one in 3 cm. The 10 mm impedance tube has the frequency range from low to medium frequency while the 3 mm for the high frequency testing. The absorption coefficient prediction value from numerically MPP design for the targeted frequency of 695 Hz gets 0.8819 versus the actual value after test in impedance tube is 0.8875. Furthermore, the highest absorption coefficient value for design or prediction and actual testing lies at the exact frequency of 750 Hz where for predictions has 0.95 and 1 for actual testing. Based on these results it can be concluded that MPP has the potency to reduce the APU noise. Henceforth it will be interesting to apply the MPP technology directly to the APU compartment on aircraft.

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Development of knowledge management system for determining organizational culture in micro, small and medium enterprises using organizational culture assessment instrument 1

Development of knowledge management system for determining o...

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2017 1st International Conference on engineering and Applied Technology, ICEAT 2017

作者： Aziz, R.Z.A. Azima, M.F. Irianto, S.Y. Informatics Engineering Department Graduate Program Informatics and Business Institute Darmajaya Bandar Lampung Indonesia

Organizations must improve their competitiveness due to global competition and free market. Organizational culture and continuous improvement are one of the main factors used not only to face the competitiveness in the free market but also to improve organizational performance and vision and mission achievement. Moreover, the organizational culture also has an important element for determining the direction of Micro, Small and Medium Enterprises (MSMEs). However, many MSMEs currently do not pay attention to their organizational culture so that difficulties emerge in determining the right direction and policy. To solve the problems, this research aimed to determine the companies' organizational culture by using organizational culture assessment instrument (OCAI) based on knowledge management system (KMS) in order to provide recommendations. In the developing the system, the researchers conducted surveys to several MSMEs and invite experts and practitioners to conduct the process of knowledge capture and literature study and to achieve the best organizational culture recommendations on MSMEs. This research produced a software used for determining the organizational culture based on KMS and OCAI principles. The developed software was tested to several companies and MSMEs to obtain results with a very high level of accuracy in providing recommendations. © Published under licence by IOP Publishing Ltd.

关键词： Competition

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Correlation between digital literacy and environmental literacy of 11th-grade students

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AIP Conference Proceedings 2024年第1期3106卷

作者： Mimien Henie Irawati Al Muhdhar Shinta Amrul Khoirina Muhamad Arjuna Salim Racy Rizky Abdillah Diana Hernawati Diki Muhamad Chaidir Muhammad Iqbal Akbar Lely Mardiyanti Mohammad Qodri Department of Biology Faculty of Mathematics and Sciences Universitas Negeri Malang Malang East Java Indonesia Department of Biologi Education Universitas Siliwangi Tasikmalaya Wesst Java Indonesia Department of Electrical and Informatics Engineering Faculty of Engineering Universitas Negeri Malang Malang East Java Indonesia Study Program of Biological Education Universitas Jambi Jambi Indonesia SMA Negeri 1 Batu Batu East Java Indonesia

The rapid development of technology, information, and communication requires students to master digital literacy. In addition, the rapid development of technology also affects environmental conditions, so it is necessary to master environmental literacy to understand and interpret environmental conditions, as well as build students’ awareness of environmental issues. This study aims to determine the correlation between digital literacy and student environmental literacy. The population in this research includes 11th-grade students of SMAN 1 Batu. The research sample amounted to 102 students, and the sampling technique used was purposive random sampling. Data were collected through digital literacy questionnaires, environmental literacy questionnaires, and environmental literacy tests. The data were tested for normality and homogeneity prerequisites and then analyzed using the Pearson Correlation statistical test. The results obtained show that the average digital literacy score of students is 105.1, including the high category, and the average student environmental literacy score is 279.7, included in the medium category. The high level of digital literacy will make students more critical in accessing technology and digital media. Digital literacy includes the process of finding, using multiple sources, evaluating, and using information to produce original products, with the maximum application of digital literacy, which is expected to support students’ environmental literacy in providing knowledge, understanding, and building an attitude of caring for the environment. The data obtained shows that there is a positive relationship between digital literacy and environmental literacy.

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Machine Learning-Based Prediction of Pulmonary Thromboembolism to Reduce Unnecessary Computed Tomography Scans in Gastrointestinal Cancer Patients: A Retrospective Multicenter Study

SSRN

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SSRN 2023年

作者： Kim, Joo Seong Kwon, Doyun Kim, Kyungdo Lee, Sang Hyub Lee, Seung-Bo Kim, Kwangsoo Kim, Dongmin Lee, Min Woo Park, Namyoung Choi, Jin Ho Jang, Eun Sun Cho, In Rae Paik, Woo Hyun Lee, Jun Kyu Ryu, Ji Kon Kim, Yong-Tae Department of Internal Medicine Liver Research Institute Seoul National University Hospital Seoul National University College of Medicine Seoul Korea Republic of Department of Internal Medicine Dongguk University College of Medicine Dongguk University Ilsan Hospital Goyang-si Korea Republic of Interdisciplinary Program of Medical Informatics Seoul National University College of Medicine Seoul Korea Republic of Department of Biomedical Engineering Pratt School of Engineering Duke University DurhamNC27708 United States Transdisciplinary Department of Medicine & Advanced Technology Seoul National University Hospital Seoul Korea Republic of Department of Medicine Seoul National University College of Medicine Seoul Korea Republic of Department of Medical Informatics Keimyung University School of Medicine Daegu Korea Republic of Biomedical Research Institute Seoul National University Hospital Seoul Korea Republic of Department of Medicine Kyung Hee University Gangdong Hospital Seoul Korea Republic of Department of Medicine Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Korea Republic of Department of Internal Medicine Seoul National University Bundang Hospital Seongnam-si Korea Republic of

Background: Pulmonary thromboembolism (PTE) is one of the most important complications in cancer patients. Gastrointestinal cancers entail an increased risk of PTE. However, there were few research on predicting pulmonary embolism using machine learning (ML) in cancer patients. The purpose of this study was to develop an ML based prediction model for PTE in gastrointestinal cancer ***: We conducted a retrospective, multicenter study in which ML model was developed and subsequently internally and externally validated. We reviewed gastrointestinal cancer patients who had undergone computed tomographic pulmonary angiography (CTPA) from 2010 to 2020. Demographic and predictor variables including the Wells score and D-dimer were investigated. The ML model was based on the random forest model. The area under receiver operating curve (AUROC) was used to evaluate the performance of ML ***: 446 patients in hospital A and 139 patients in hospital B were analyzed in this study. The training set comprised 356 patients in hospital A. The ML model was validated both internally (90 patients) and externally (139 patients). AUROC was 0.736 in hospital A and 0.669 in hospital B. The number of patients classified as requiring CTPA was significantly reduced according to the prediction with ML (hospital A;100.0% vs 91.1%, P Conclusion: Prediction model based on ML might have advantages in reducing the number of CTPA compared to the conventional diagnostic strategy for PTE in patients with gastrointestinal cancer. © 2023, The Authors. All rights reserved.

关键词： Hospitals

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Efficient and scalable neural residual waveform coding with collaborative quantization

arXiv

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arXiv 2020年

作者： Zhen, Kai Lee, Mi Suk Sung, Jongmo Beack, Seungkwon Kim, Minje Indiana University Luddy School of Informatics Computing and Engineering BloomingtonIN United States Indiana University Cognitive Science Program BloomingtonIN United States Electronics and Telecommunications Research Institute Daejeon Korea Republic of

Scalability and efficiency are desired in neural speech codecs, which supports a wide range of bitrates for applications on various devices. We propose a collaborative quantization (CQ) scheme to jointly learn the codebook of LPC coefficients and the corresponding residuals. CQ does not simply shoehorn LPC to a neural network, but bridges the computational capacity of advanced neural network models and traditional, yet efficient and domain-specific digital signal processing methods in an integrated manner. We demonstrate that CQ achieves much higher quality than its predecessor at 9 kbps with even lower model complexity. We also show that CQ can scale up to 24 kbps where it outperforms AMR-WB and Opus. As a neural waveform codec, CQ models are with less than 1 million parameters, significantly less than many other generative models. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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An artificial intelligence method for vessel detection in images of cardiac catheterization

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informatics in Medicine Unlocked 2023年 39卷

作者： Chien, Ting-Ying Ting, Hsien-Wei Li, Hao-Wei Chang, Hsiao-Huang Department of Computer Science and Engineering Yuan Ze University 320 Taoyuan City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University 320 Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University 320 Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare 242 New Taipei City Taiwan Division of Cardiovascular Surgery Department of Surgery Taipei Veterans General Hospital Taipei 11217 Taiwan Department of Surgery School of Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan

Coronary artery disease (CAD) is one of the top ten leading causes of death in countries worldwide. There are several methods used by physicians to diagnose CAD. One common method is the use of X-ray angiogram (XRA) images. When employing a computer-aided automatic analysis method to locate blood vessels in XRA images, problems such as complex background noise, low contrast, and difficulty in separating blood vessels from the background are encountered, especially for blood vessels with a low contrast to the background noise. In this study, we used various image preprocessing methods to highlight blood vessels from complex backgrounds and different types of blood vessel, followed by the employment of four superpixel segmentation methods to partition an image into multiple segments, and finally the utilization of Weighted Voting to determine the best superpixel algorithm. A genetic algorithm was used to identify the best weights by which to determine the locations of blood vessels in images of cardiac catheterization. Our proposed method achieved an average F1-score of 73.4% in the analysis of five patients, which was better than the other superpixel algorithms tested. The results of this research will be helpful for future SYNTAX score analysis. © 2023

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Free vibration of orthotropic Levy-type solution plates by using SEM 7

Free vibration of orthotropic Levy-type solution plates by u...

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7th International Conference on Euro Asia Civil engineering Forum, EACEF 2019

作者： Kiryu, S. Alisjahbana, S.W. Alisjahbana, I. Han, A.L. Gan, B.S. Department of Architecture Graduate School of Engineering Nihon University Koriyama Japan Faculty of Engineering and Informatics Bakrie University Jakarta Indonesia Department of Civil and Environmental Engineering Master Program Student Stanford University CA United States Civil Engineering Department Faculty of Engineering Universitas Diponegoro Semarang Indonesia Department of Architecture College of Engineering Nihon University Koriyama Japan

Orthotropic Levy-type solution plates considering shear deformation were solved by using the Spectral Element Method (SEM). In SEM, the exact solution of structural dynamic related problems can be solved by using the frequency-dependent shape functions. The solutions of SEM are accurate in decreasing the amount of Degree Of Freedoms (DOF) to discard the cost and computational disadvantages in the Finite Element Method (FEM). This study investigates the free vibration problems of orthotropic Levy-type solution plates solutions based on the two variable Refined Plate Theory (RPT). SEM for orthotropic Levy-type solution plates in the frequency domain was formulated to solve free vibration problems. The differential governing equations of the orthotropic plate element in SEM are formulated into the form of transcendental stiffness matrices. The boundary conditions of the spectral element model consist of four edge-type DOFs at each side of the orthotropic Levy-type solution plates. The natural frequencies of the plate are calculated by means of the Wittrick-Williams procedure. The numerical investigations are presented to show the accuracy, efficiency, and effectiveness of SEM without any discretization scheme. © Published under licence by IOP Publishing Ltd.

关键词： Stiffness matrix

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Towards a Visual-Language Foundation Model for Computational Pathology

arXiv

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arXiv 2023年

作者： Lu, Ming Y. Chen, Bowen Williamson, Drew F.K. Chen, Richard J. Liang, Ivy Ding, Tong Jaume, Guillaume Odintsov, Igor Zhang, Andrew Le, Long Phi Gerber, Georg Parwani, Anil V. Mahmood, Faisal Department of Pathology Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Pathology Massachusetts General Hospital Harvard Medical School BostonMA United States Cancer Program Broad Institute of Harvard and MIT CambridgeMA United States Cancer Data Science Program Dana-Farber Cancer Institute BostonMA United States Department of Biomedical Informatics Harvard Medical School BostonMA United States CambridgeMA United States Health Sciences and Technology Harvard-MIT CambridgeMA United States Harvard John A. Paulson School of Engineering And Applied Sciences Harvard University CambridgeMA United States Department of Pathology Wexner Medical Center Ohio State University ColumbusOH United States Harvard Data Science Initiative Harvard University CambridgeMA United States

The accelerated adoption of digital pathology and advances in deep learning have enabled the development of powerful models for various pathology tasks across a diverse array of diseases and patient cohorts1–13. However, model training is often difficult due to label scarcity in the medical domain and the model’s usage is limited by the specific task and disease for which it is trained1–3, 14, 15. Additionally, most models in histopathology leverage only image data, a stark contrast to how humans teach each other and reason about histopathologic entities. We introduce CONtrastive learning from Captions for Histopathology (CONCH), a visual-language foundation model developed using diverse sources of histopathology images, biomedical text, and notably over 1.17 million image-caption pairs via task-agnostic pretraining. Evaluated on a suite of 13 diverse benchmarks, CONCH can be transferred to a wide range of downstream tasks involving either or both histopathology images and text, achieving state-of-the-art performance on histology image classification, segmentation, captioning, text-to-image and image-to-text retrieval. CONCH represents a substantial leap over concurrent visual-language pretrained systems for histopathology, with the potential to directly facilitate a wide array of machine learning-based workflows requiring minimal or no further supervised fine-tuning. © 2023, CC BY-NC-ND.

关键词： Pathology

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An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings

An End-to-End Approach for Recognition of Modern and Histori...

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International Joint Conference on Neural Networks (IJCNN)

作者： Andre G. Hochuli Alceu S. Britto Jean P. Barddal Robert Sabourin Luiz E. S. Oliveira Graduate Program in Informatics (PPGIa) Pontifícia Universidade Católica do Paraná Curitiba PR Brazil System Engineering Dept. (LIVIA) École de Technologie Supérieure Montreal QC Canada Department of Informatics (DInf) Universidade Federal do Paraná Curitiba PR Brazil

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

An end-to-end solution for handwritten numeral string recognition is proposed, in which the numeral string is considered as composed of objects automatically detected and recognized by a YoLo-based model. The main contribution of this paper is to avoid heuristic-based methods for string preprocessing and segmentation, the need for task-oriented classifiers, and also the use of specific constraints related to the string length. A robust experimental protocol based on several numeral string datasets, including one composed of historical documents, has shown that the proposed method is a feasible end-to-end solution for numeral string recognition. Besides, it reduces the complexity of the string recognition task considerably since it drops out classical steps, in special preprocessing, segmentation, and a set of classifiers devoted to strings with a specific length.

关键词： Handwriting recognition Training Feature extraction Computer architecture Proposals Machine learning Task analysis

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