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2024 IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2024

作者： Chang, Shun-Cheng Yu, Hsin-Pei Hsieh, Yi-Hsien Wang, Pochuang Wang, Weichung Su, Tung-Hung Kao, Jia-Horng Lin, Che Taipei10617 Taiwan Department of Computer Science and Information Engineering Ntu Taipei10617 Taiwan Institute of Applied Mathematical Sciences Ntu Taipei10617 Taiwan National Taiwan University Hospital Division of Gastroenterology and Hepatology Department of Internal Medicine Taipei10048 Taiwan Department of Electrical Engineering Ntu Taipei10617 Taiwan Center for Advanced Computing and Imaging in Biomedicine Ntu Taipei10617 Taiwan Smart Medicine and Health Informatics Program Ntu Taipei10617 Taiwan

ISBN: (纸本)9798350351552

Deep learning has revolutionized medical imaging, offering advanced methods for accurate diagnosis and treatment planning. The BCLC staging system is crucial for staging Hepatocellular Carcinoma (HCC), a high-mortality cancer. An automated BCLC staging system could significantly enhance diagnosis and treatment planning efficiency. However, we found that BCLC staging, which is directly related to the size and number of liver tumors, aligns well with the principles of the Multiple Instance Learning (MIL) framework. To effectively achieve this, we proposed a new preprocessing technique called Masked Cropping and Padding(MCP), which addresses the variability in liver volumes and ensures consistent input sizes. This technique preserves the structural integrity of the liver, facilitating more effective learning. Furthermore, we introduced Re ViT, a novel hybrid model that integrates the local feature extraction capabilities of Convolutional Neural Networks (CNNs) with the global context modeling of Vision Transformers (ViTs). Re ViT leverages the strengths of both architectures within the MIL framework, enabling a robust and accurate approach for BCLC staging. We will further explore the trade-off between performance and interpretability by employing TopK Pooling strategies, as our model focuses on the most informative instances within each bag. © 2024 IEEE.

关键词： Convolutional neural networks

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Learning from failure - Development of a Culture of Failure Scale for Higher Education

Learning from failure - Development of a Culture of Failure ...

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World Engineering Education Forum - Global Engineering Deans Council (WEEF-GEDC)

作者： Michael M. Malschützky Ph.D. Jamie R. Gurganus Centre for Teaching Development and Innovation (ZIEL) & Department of Management Sciences Hochschule Bonn-Rhein-Sieg University of Applied Sciences Sankt Augustin Germany Engineering & Computing Education Program Mechanical Engineering & Graduate School University of Maryland Baltimore County Baltimore USA

ISBN: (数字)9781665475280

ISBN: (纸本)9781665475297

Benefits of a failure friendly culture, e.g., learning from failure, are widely known in occupational settings. Validated scales have been developed to measure organizational failure culture and individuals' mind-sets on failure. While research on learning from failure exists in secondary education, scales for higher education are lacking. To support both higher education engineering instructors and students, this contribution aims to develop a Culture of Failure Scale to assess students' and lecturers' handling of failures in engineering higher education settings. This data-driven approach helps inform instructors about aspects of educational settings that are safe and conducive to learning and supports their students to develop a mind-set where failures are seen as a source for improvements and learning. Exemplary application of the developed scale is shown by assessing the failure culture in different groupings, e.g., gender, between two participating German and US institutions.

关键词： Correlation Education Psychology Reliability History Engineering students Principal component analysis

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Women and Technology: Reversing the Trends of Attrition and Obtaining a Balance

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Women's Studies 2008年第3期37卷 173-175页

作者： Leroy, Gondy gondy.leroy@cgu.edu Tolle, Kristin M. Perkins, Linda Assistant Professor School of Information Systems and Technology Claremont Graduate University Claremont California USA Program Manager for Biomedical Computing External Research @ Microsoft Research Redmond Washington USA University Associate Professor and Director of Applied Women''s Studies Claremont Graduate University Claremont California USA

The article discusses various reports published within the issue including one by Louise Soe and Elaine K. Yakura on women's attrition from technical fields of work, and another by Indira Guzman and Jeffrey M. Sta... 详细信息

关键词： WOMEN in technology EQUALITY in the workplace

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Evaluation of Resampling Techniques to Provide Better Synthesized Input Data to Super-Resolution Deep Learning Model Training

Evaluation of Resampling Techniques to Provide Better Synthe...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Vinicius Sales Ademir Marques Graciela Racolte Anderson Nunes Tainá Guimaraes Daniel Zanotta André Spigolon Luiz Gonzaga Mauricio Roberto Veronez Vizlab - X-Reality and GeoInformatics Lab UNISINOS-São Leopoldo RS Brazil Graduate Program in Applied Computing at Vale do Rio dos Sinos University São Leopoldo RS Brazil CENPES - PETROBRAS Rio de Janeiro Brazil

Hyperspectral images often have low spatial resolution due to the sensor sizes required to capture the required spectral response. Super-resolution (SR) techniques try to mitigate this by injecting more detail in the upscaled image, either with numerical methods or deep learning and Convolution Neural Networks. In the deep learning methods, the models learn image details by inferring a high-resolution (HR) image from a synthetic low-resolution (LR) image that simulates the natural degradation of sensors by applying resampling (to reduce the image detail) and noising (to add small errors and interference). Often disregarded in the literature, the resampling method applied to generate the synthetic image can impact greatly the deep learning model training. This work, evaluate several resampling techniques to measure this impact using the Harvard hyperspectral dataset. Results showed that the Lanczos filter was the best among eight other resampling methods. The Nemenyi and Friedman ranking statistical tests also indicated that the Cubic-Spline, Bicubic, and RMS achieved good results.

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Investigating Cases and Clusters-Based Reuse Policies for Card-Playing Agents

Investigating Cases and Clusters-Based Reuse Policies for Ca...

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IEEE Symposium on Computational Intelligence and Games, CIG

作者： Gustavo B. Paulus Daniel P. Vargas Joaquim V. C. Assunção Luis A. L. Silva Federal Institute of Education Science and Technology of Rio Grande do Sul Ibirubá Brazil Graduate Program in Computer Science Federal University of Santa Maria Santa Maria Brazil Applied Computing Department Federal University of Santa Maria Santa Maria Brazil

Computer games continue to present challenging experimental fields for developing Artificial Intelligence (AI) models. With Case-Based Reasoning and Clustering, this work proposes novel cases and clusters-based reuse criteria for implementing card-playing agents with diversified playing skills. Using the game of Truco, a common game in South America, we detail how game actions are reused from past cases selected as query answers for given game problems. In doing so, the majority rule, the probability-based lottery, the probability of victory, and the number of points won reuse policies are used to select a cluster of cases. Then these policies are also used to select game actions from the cases within the selected cluster. Investigating the combined exploration of reuse policies, experiments of different natures evaluate the performance of implemented Truco bots disputing matches against each other. Players in these tournaments are equipped with varied policies and use case bases constructed differently.

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Clustering Fracture Data in 3D Outcrop Models with Hierarchical Agglomerative Clustering and Fisher Statistics

Clustering Fracture Data in 3D Outcrop Models with Hierarchi...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Graciela Racolte Ademir Marques Vinicius Ferreira Sales Daniel Capella Zanotta Delano Menecucci Ibanez Mauricio Roberto Veronez Luiz Gonzaga Vizlab — X-Reality and GeoInformatics Lab UNISINOS São Leopoldo RS Brazil Graduate Program in Applied Computing at Vale do Rio dos Sinos University São Leopoldo RS Brazil CENPES PETROBRAS Rio de Janeiro Brazil

Most fracture properties, such as orientation and density, are acquired by interpreting data obtained at the wellbores, while fracture properties between wells are typically derived from seismic data. However, this information is sparse or has low resolution leading to the study and analysis of outcrops. The data acquisition in outcrops is facilitated by its 3D representation in Digital Outcrop Models (DOM) obtained from LiDAR and Photogrammetry. It also allows virtual interpretation and fracture detection. In either case, the 3D fracture data need to be clustered in fracture sets to allow the statistical analysis necessary to upscale and resample the DFN. This clusterization is carried out by methods like k-means and fuzzy, however with caveats, like the prior definition of the number of clusters. In this work, we propose the use of agglomerative hierarchical clustering to cluster 3D fracture data obtained by a KD-Tree segmentation algorithm. Results showed that when compared to k-means, the proposed method presented more compact clusters and balance when considering Fisher’s statistics of dispersion.

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MILPdM: A Predictive Maintenance Architecture for the Military Domain

MILPdM: A Predictive Maintenance Architecture for the Milita...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Jovani Dalzochio Rafael Kunst Jorge Barbosa Edison Pignaton De Freitas Alécio Binotto Graduate Program in Applied Computing University of Vale do Rio dos Sinos São Leopoldo Brazil Institute of Informatics Federal University of Rio Grande do SuI Porto Alegre Brazil Asset and Edge Optimization IBM Consulting Munich Germany

Equipment monitoring for failure prediction is receiving attention from different sectors of society, such as industry, healthcare, and defense. In the defense domain, assets like military vehicles generate data that one can use to identify behavior changes and anticipate possible real-time failures, avoiding unnecessary maintenance interventions. Failure anticipation is crucial, as assets operated in the military domain perform critical tasks in which unexpected equipment failures result in high material and human costs. Approaches found in the literature typically deal with failure generation, aiming at analyzing the equipment's behavior. This paper proposes a broader approach called MILPdM. This proposal is a failure prediction architecture covering the whole failure prediction and predictive maintenance procedures. We evaluate MILPdM architecture by analyzing an engine-failure scenario where we train models to predict time series by collecting vibration data that describes the degradation of the vehicle's health. Considering the implementation of an LSTM-based neural network and Random Forest, the acquired results lead to a root mean square error of 0.15015 in the best case, which allows to predict the failure status two minutes in advance with only 3 hours of data history. This result shows that MILPdM is capable of anticipating failures with high assertiveness.

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Discovery of novel ancestry specific genes for androgens and hypogonadism in Million Veteran program Men

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Nature Communications 2025年第1期16卷 1-12页

作者： Pagadala, Meghana S. Teerlink, Craig C. Jasuja, Guneet K. Palnati, Madhuri Anglin-Foote, Tori Chang, Nai-Chung N. Deka, Rishi Lee, Kyung M. Agiri, Fatai Y. Amariuta, Tiffany Seibert, Tyler M. Rose, Brent S. Pridgen, Kathryn M. Lynch, Julie A. Carter, Hannah K. Panizzon, Matthew S. Hauger, Richard L. Research Service VA San Diego Healthcare System San Diego CA United States Medical Scientist Training Program University of California San Diego La Jolla CA United States Biomedical Science Program University of California San Diego La Jolla CA United States VA Informatics and Computing Infrastructure (VINCI) VA Salt Lake City Healthcare System Salt Lake City UT United States Department of Internal Medicine Division of Epidemiology University of Utah School of Medicine Salt Lake City UT United States Center for Healthcare Organization and Implementation Research (CHOIR) VA Bedford Healthcare System Bedford MA United States Section of General Internal Medicine Boston University School of Medicine Boston MA United States Department of Health Law Policy and Management Boston University School of Public Health Boston MA United States Department of Radiation Medicine and Applied Sciences University of California San Diego La Jolla CA United States Department of Psychiatry University of California San Diego La Jolla CA United States Department of Medicine University of California San Diego La Jolla CA United States Halicioglu Data Science Institute University of California San Diego La Jolla CA United States Department of Radiology University of California San Diego La Jolla CA United States Department of Bioengineering University of California San Diego La Jolla CA United States Department of Urology University of California San Diego La Jolla CA United States Center for Behavior Genetics of Aging University of California San Diego La Jolla CA United States Center of Excellence for Stress and Mental Health (CESAMH) VA San Diego Healthcare System San Diego CA United States

Given the various roles of testosterone in men’s health, we conducted a multi-ancestral genetic analysis of total testosterone, free testosterone, SHBG, and hypogonadism in men within the Million Veteran program (MVP). Here we identified 157 significant testosterone genetic variants, of which 8 have significant ancestry-specific associations. These variants implicate several genes, including SERPINF2, PRPF8, BAIAP2L1, SHBG, PRMT6, and PPIF, related to liver function. Genetic regulators of testosterone have cell type-specific effects in the testes, liver, and adrenal gland and are associated with disease risk. We conducted a meta-analysis amongst ancestry groups to identify 188 variants significantly associated with testosterone, of which 22 are novel associations. We constructed genetic scores for total testosterone, SHBG levels, and hypogonadism and find that men with higher testosterone genetic scores have lower odds of diabetes, hyperlipidemia, gout, and cardiac disorders. These findings provide insight into androgen regulation and identify novel variants for disease risk stratification. © This is a U.S. Government work and not under copyright protection in the US;foreign copyright protection may apply 2025.

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Breaking the barriers between security mechanisms through the composition of Web Services: Towards a solution for the detection of multistage distributed attacks

Breaking the barriers between security mechanisms through th...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Leonardo Lemes Fagundes Luciano Paschoal Gaspary Postgraduate Program on Applied Computing University of Vale do Rio dos Sinos-UNISINOS Sao Leopoldo Rio Grande do Sul Brazil Institute of Informatics Federal University of Rio Grande do Sul Porto Alegre Rio Grande do Sul Brazil

In recent years, the number of planned and coordinated attacks, such as DDoS (Distributed Denial of Service), has increased significantly. These attacks, also known as multistage attacks, are composed of several stages and originated from multiple sources (hosts). Traditional Intrusion Detection Systems (IDSes) do not tackle adequately such attacks, mainly due to the lack of mechanisms for uniform communication with distinct security systems (e.g., other IDSes, firewalls, etc.) and for the correlation, in a timely manner, of the observed events. In a first attempt to address the aforementioned issues, in this paper we propose a solution for the detection of multistage, distributed attacks based on the creation of security oriented Web Services. The solution comprises two key components: (i) a novel language for the specification of the diverse stages that compose a multistage attack, and (ii) SECCOMPOSE, a service oriented architecture for multistage, distributed attack detection.

关键词： Web services Intrusion detection Web server Computer crime Distributed computing Informatics Communication system security Sockets File systems Information retrieval

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Designing Classical Header Bits for Quantum Wrapper Networking with O-band Quantum Signal

Designing Classical Header Bits for Quantum Wrapper Networki...

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Frontiers in Optics + Laser Science 2023, FiO, LS 203: Part of Frontiers in Optics + Laser Science 2023

作者： Gül, G. Berkay On, M. Singh, S.K. Proietti, R. Kanter, G.S. Yoo, S.J.B. Kumar, P. Graduate Program in Applied Physics Northwestern University 2145 Sheridan Road EvanstonIL60208 United States Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Department of Electronics and Communication Eng. Indian Institute of Technology Roorkee247667 India Department of Electronics and Telecommunications Engineering Politecnico di Torino Italy Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

We investigate the impact of wavelength choice for the classical headers in quantum wrapper networking with O-band quantum payload. We show that a C-band header performs substantially better than an O-band header. ... 详细信息

ISBN: (纸本)9781957171296

关键词： Bandpass filters Beam splitters Bit error rate Entanglement distribution Quantum teleportation Raman scattering

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