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Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI)

作者： Luis A. Souza André G. C. Pacheco Gabriel G. de Angelo Thiago Oliveira-Santos Christoph Palm João P. Papa Graduate Program of Informatics Federal University of Espírito Santo Vitória Brazil OTH Regensburg Regensburg Medical Image Computing (ReMIC) Regensburg Germany Department of Computing São Paulo State Univesity São Paulo Brazil

ISBN: (数字)9798350376036

ISBN: (纸本)9798350376043

Skin cancer is the most common type of cancer in the world, accounting for approximately 30% of all diagnosed tumors. Early diagnosis reduces mortality rates and prevents disfiguring effects in different body regions. In recent years, machine learning techniques, particularly deep learning, have shown promising results in this task, presenting studies that have demonstrated that combining a patient's clinical information with images of the lesion is crucial for improving the classification of skin lesions. Despite that, meaningful use of clinical information with multiple images is mandatory, requiring further investigation. Thus, this project aims to contribute to developing multimodal machine learning-based models to cope with the skin lesion classification task employing a lightweight transformer model. As a main hypothesis, models can take multiple images from different sources as input, along with clinical information from the patient's history, leading to a more reliable diagnosis. Our model deals with the not-trivial task of combining images and clinical information (from anamneses) concerning the skin lesions in a lightweight transformer architecture that does not demand high computation resources but still presents competitive classification results.

关键词： Graphics Computational modeling Computer architecture Transformers Skin Lesions Clinical diagnosis Reliability History Skin cancer

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Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer 24

Predicting Microsatellite Instability from Histology Images ...

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24th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2024

作者： Chen, Yun-Chi Chao, Tung Phandita, Wimaya Nitya Sun, Tzu-Yu Wang, Huai-Zhi Hsieh, Yi-Hsien Hsu, Le-Yin Lin, Che Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan NTU Data Science Degree Program Taipei Taiwan NTU Department of Electrical Engineering Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan NTU Smart Medicine and Health Informatics Program Taipei Taiwan

ISBN: (纸本)9798331518622

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients. © 2024 IEEE.

关键词： Diseases

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Patient Engagement through Mobile Health Interventions of Diabetes: A Systematic Literature Review 33

Patient Engagement through Mobile Health Interventions of Di...

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33rd Australasian Conference on Information Systems: The Changing Face of IS, ACIS 2022

作者： Alhubayshi, Arwa Almutairi, Nawaf Win, Khin Than Information Technology Department Medical Cities Program – MOI Riyadh Saudi Arabia School of Computing and Information Technology University of Wollongong Wollongong Australia Faculty of Public Health and Health Informatics University of Hail Hail Saudi Arabia

This paper aims to review the applicability of the Healthcare Information and Management Systems Society (HIMSS) patient engagement framework and to recognise the patient engagement features presented in current mHealth interventions for improving engagement in diabetes self-management. Scopus, Web of Science and PubMed databases were searched for relevant studies. The selected studies were then analysed using the Healthcare Information and Management Systems Society (HIMSS) patient engagement framework. Twenty engagement features were identified from 29 studies reviewed. Half of the HIMSS patient engagement framework categories were seen in the studies. This review shows that mHealth interventions have achieved the third and fourth phases of the HIMSS patient engagement framework. In addition, this review suggests improvements in patient engagement facilitation, including integrating patient-generated data into electronic health records, collaboration access to the health records, and peer support through online community forums. Finally, the future patient engagement framework is discussed for mHealth technology. Copyright © 2022 Arwa Alhubayshi, Nawaf Almutairi, Khin Than Win.

关键词： mHealth

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CONVERGENCE ANALYSIS OF A SCHRÖDINGER PROBLEM WITH MOVING BOUNDARY

arXiv

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arXiv 2024年

作者： Alfaro Vigo, Daniel G. Gomes, Daniele C.R. Carmo, Bruno A.D.O. Rincon, Mauro A. Institute of Computing Graduate Program in Informatics Federal University of Rio de Janeiro Caixa Postal 68530 RJ Rio de JaneiroCEP 21941-590 Brazil Graduate Program in Informatics Federal University of Rio de Janeiro Caixa Postal 68530 RJ Rio de JaneiroCEP 21941-590 Brazil

In this article, we present the mathematical analysis of the convergence of the linearized Crank-Nicolson Galerkin method for a nonlinear Schrödinger problem related to a domain with a moving boundary. The convergence analysis of the numerical method is carried out for both semi-discrete and fully discrete problems. An optimal error estimate in the L2-norm with order O(τ2 + hs), 2 ≤ s ≤ r, where h is the finite element mesh size parameter, τ is the time step, and r−1 represents the degree of the finite element polynomial basis. Numerical simulations are provided to confirm the consistency between theoretical and numerical results, validating the method and the order of convergence for different degrees p ≥ 1 of the Lagrange polynomials and also for Hermite polynomials (degree p = 3), which form the basis of the approximate solution. © 2024, CC BY-NC-ND.

关键词： Schrodinger equation

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Generating reward structures on a parameterized distribution of dynamics tasks

Generating reward structures on a parameterized distribution...

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2021 Conference on Artificial Life, ALIFE 2021

作者： Leite, Abe Izquierdo, Eduardo J. Cognitive Science Program Indiana University Bloomington United States Luddy School of Informatics Computing and Engineering Indiana University Bloomington United States

In order to make lifelike, versatile learning adaptive in the artificial domain, one needs a very diverse set of behaviors to learn. We propose a parameterized distribution of classic control-style tasks with minimal information shared between tasks. We discuss what makes a task trivial and offer a basic metric, time in convergence, that measures triviality. We then investigate analytic and empirical approaches to generating reward structures for tasks based on their dynamics in order to minimize triviality. Contrary to our expectations, populations evolved on reward structures that incentivized the most stable locations in state space spend the least time in convergence as we have defined it, because of the outsized importance our metric assigns to behavior fine-tuning in these contexts. This work paves the way towards an understanding of which task distributions enable the development of learning. © 2021 ALIFE. All Rights Reserved.

关键词： Multi-task learning

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FluxProg 2.0 - Extended Version of a Visual Tool for Teaching programming Logic Using Flowcharts with Real and Simulated Robots

FluxProg 2.0 - Extended Version of a Visual Tool for Teachin...

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2024 Brazilian Symposium on Robotics (SBR), and 2024 Workshop on Robotics in Education (WRE)

作者： Matheus Biscaya Gutierrez João Alberto Fabro André Cristiano Cordeiro Academic Department of Informatics (DAINF-CT) Federal University of Technology - Paraná (UTFPR) Curitiba PR Brazil Graduate Program on Applied Computing (PPGCA) DAINF-CT - UTFPR Curitiba PR Brazil

ISBN: (数字)9798350391084

ISBN: (纸本)9798350391091

This paper presents a new teaching tool with the goal of facilitating the learning of basic programming concepts among high school students and university freshmen. The tool incorporates a user-friendly visual interface and robotics, expanding on the existing Fluxprog project. New features were implemented, such as variables, logical and mathematical operations, conditional structures, and loops, to motivate students to engage in challenges that promote logical thinking. This paper presents the design, implementation and evaluation of a programming teaching tool using a visual language based on flowcharts, with subsequent data collection through a questionnaire and analysis of preliminary results to evaluate the user's experience while interacting with the tool.

关键词： Visualization Flowcharts Conferences Education Data collection User experience Logic Robots programming profession

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Exploring Security Threats by Hardware-Faults in Approximate Arithmetic computing

Exploring Security Threats by Hardware-Faults in Approximate...

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Annual IEEE Northeast Workshop on Circuits and Systems (NEWCAS)

作者： Morgana M. A. Da Rosa Eduardo A. C. Da Costa Rafael I. Soares Sergio Bampi Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil PPGC & PGMICRO - Informatics Institute Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil

Approximate computing (AxC) emerged as a design alternative to boost design efficiency by leveraging the inherent error resiliency of many applications. Recent literature shows attackers could exploit some AxC mechanisms to create new attack surfaces. This work proposes integrity checking and exclusive logic-based methods detect attacks by hardware faults on AxC systems. During ASIC-based synthesis, we investigate the security vulnerabilities of the Approximate Parallel Prefix Adder (AxPPA). We compare the expected output of the designer with the output netlists of ASIC-based synthesis. We propose a verification methodology consisting of a golden model (GM) described in a Simulink model and the DUT represented at the netlist level in a standard cell library after logic synthesis. Experimental results show that the AxPPA has an error range of 1.263 × 10 −5 to 0.0098 concerning the designer’s expected output under ASIC-based synthesis attacks.

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New Energy-Efficient 3-2 and 4-2 Approximate Adder Compressors Topologies

New Energy-Efficient 3-2 and 4-2 Approximate Adder Compresso...

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Rodrigo Lopes Leonardo Antonietti Morgana M. A. Rosa Eduardo Costa Rafael Soares Sergio Bampi Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil PPGC & PGMICRO - Informatics Institute Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil

Addition units are present across many computational kernels inherent in various error-tolerant applications, including machine learning, signal, image, and video processing. Notably, adder compressors are the target when high speed and low power are the main design concerns. This work introduces energy-efficient structures of 3-2 approximate adder compressors (Ax3-2) and three distinct versions of 4-2 approximate adder compressors (Ax4-2). We compared our proposed Ax3-2 and Ax4-2 compressors with state-of-the-art energy-efficient approximate adder compressors (AxACs). Both Ax3-2 and Ax4-2 models passed through rigorous tests as standalone units. Furthermore, we integrated the Ax4-2 models into an essential application kernel appearing in video coding, i.e., the Sum Squared Differences (SSD) video accelerator. We introduce Ax3-2 and Ax4-2 that yield a new Pareto front concerning both energy-quality and area-quality trade-offs, thereby demonstrating a marked improvement over the prevailing state-of-the-art energy-efficient AxACs.

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An Ultra Low-Energy VLSI Approximate Discrete Haar Wavelet Transform for ECG Data Compression

An Ultra Low-Energy VLSI Approximate Discrete Haar Wavelet T...

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Arthur Cardozo Morgana M. A. Rosa Rafael Soares Eduardo Costa Sergio Bampi Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil PPGC & PGMICRO - Informatics Institute Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil

This work proposes an ultra-low-energy ECG data compression with VLSI DHWT-based (discrete Haar wavelet transform) architecture to enable storage and transmission in resource-constrained environments. We present original, pruned, and approximate DHWT (ODHWT, PDHWT, and AxDHWT, respectively) hardware architectures for ECG data compression at ultra-high energy efficiency. Our best proposal employing the AxDHWT hardware architecture requires just five additions only. Using a PDHWT technique to improve energy efficiency observes the evolution of the signal-to-noise ratio and the ultimate impact on the ECG data compression application. The DHWT-based configurations architecture proposal achieves a minimum compression ratio of 0.125 (i.e., 1/8) and a PRD (percent root difference) <1.34. We implemented the VLSI architectures in 65nm CMOS technology in maximum and fixed frequencies and two different supply voltages. The AxDHWT occupies a die area of 0.64mm 2 . The measured total power is $0.534\mu {\mathrm {W}}$, the higher energy-savings among the ECG data compression architectures.

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach 7

Minimizing the Number of Stunting Prevalence Using the Eucli...

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7th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2023

作者： Zarlis, Muhammad Oktavia, Tanty Buaton, Relita Ernawan, Ferda Andrian, Kevin Bina Nusantara University Information System Management Department BINUS Graduate Program - Master of Information System Management Jakarta11480 Indonesia STMIK Kaputama Informatics Engineering Binjai20714 Indonesia Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan26600 Malaysia BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350360752

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city. © 2023 IEEE.

关键词： Classification (of information)

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