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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Ming-Che Cheng Yi-Hsien Hsieh Te-Cheng Hsu Tung-Hung Su Che Lin Institute of Communications Engineering National Tsing Hua University Hsinchu Taiwan Graduate Institute of Communication Engineering National Taiwan University (NTU) Taipei Taiwan Dept. of Internal Medicine Division of Gastroenterolgy and Hepatology National Taiwan University Hospital Taipei Taiwan Department of Electrical Engineering NTU Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan Smart Medicine and Health Informatics Program NTU Taipei Taiwan

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Electronic Health Records (EHRs) are a cornerstone of modern healthcare analytics, offering rich datasets for various disease analyses through advanced deep learning algorithms. However, the pervasive issue of missing values in EHRs significantly hampers the development and performance of these models. Addressing this challenge is crucial for enhancing clinical decision-making and patient care. Existing methods for handling missing data, ranging from simple imputation to more sophisticated approaches, often fall short of capturing the temporal dynamics inherent in EHRs. To bridge this gap, we introduce the Deep Stochastic Time-series Imputation (Deep STI) algorithm, an innovative end-to-end deep learning model that seamlessly integrates a sequence-to-sequence generative network with a prediction network. Deep STI is designed to leverage the observed time-series data in EHRs, learning to infer missing values from the temporal context with high accuracy. We evaluated Deep STI on the liver cancer data from the National Taiwan University Hospital (NTUH), Taiwan. Our results showed that Deep STI achieved better 5-year hepatocellular carcinoma predictions (19.21% in the area under the precision-recall curve) than extreme gradient boosting (18.15%) and Transformer (18.09%). The ablation study also illustrates the efficacy of our generative architecture design compared to regular imputations. This approach not only promises to improve the reliability of disease analysis in the presence of incomplete data but also sets a new standard for utilizing EHRs in predictive healthcare. Our work aims to advance the field of healthcare analytics and open new avenues for research in deep learning applications to EHRs.

关键词： Deep learning Time series analysis Stochastic processes Predictive models Transformers Imputation Reliability Electronic medical records Standards Diseases

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Effect of electron- and hole-doping on properties of kagomé-lattice ferromagnet Fe3Sn2

arXiv

引用

arXiv 2023年

作者： Adams, Milo Huang, Chen Shatruk, Michael Department of Chemistry and Biochemistry Florida State University TallahasseeFL32306-4390 United States Department of Scientific Computing Florida State University TallahasseeFL32306-4120 United States Materials Science and Engineering Program Florida State University TallahasseeFL32310 United States National High Magnetic Field Laboratory TallahasseeFL32310 United States

We report a theoretical investigation of effects of Mn and Co substitution in the transition metal sites of the kagomé-lattice ferromagnet, Fe3Sn2. Herein, hole- and electron-doping effects of Fe3Sn2 have been studied by density-functional theory calculations on the parent phase and on the substituted structural models of Fe3–xMxSn2 (M = Mn, Co;x = 0.5, 1.0). All optimized structures favor the ferromagnetic ground state. Analysis of the electronic density of states (DOS) and band structure plots reveals that the hole (electron) doping leads to a progressive decrease (increase) in the magnetic moment per Fe atom and per unit cell overall. The high DOS is retained nearby the Fermi level in the case of both Mn and Co substitutions. The electron doping with Co results in the loss of nodal band degeneracies, while in the case of hole doping with Mn emergent nodal band degeneracies and flatbands initially are suppressed in Fe2.5Mn0.5Sn2 but re-emerge in Fe2MnSn2. These results provide key insights into potential modifications of intriguing coupling between electronic and spin degrees of freedom observed in Fe3Sn2. Copyright © 2023, The Authors. All rights reserved.

关键词： Ferromagnetism

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CIMulator: Evaluating Neuromorphic Accelerators with HZO FefinFET-Based Synaptic Device

CIMulator: Evaluating Neuromorphic Accelerators with HZO Fef...

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International Conference on Green Technology and Sustainable Development (GTSD)

作者： Hoang-Hiep Le Hao-Yu Lu Md. Aftab Baig Sourav De Ing-Chao Lin Darsen D. Lu Department of Computer Science and Information Engineering Minghsin University of Science and Technology Hsinchu Taiwan R.O.C Intelligent Computing Industrial Doctorate Program National ChengKung University Tainan Taiwan R.O.C Institute of Microelectronics National ChengKung University Tainan Taiwan R.O.C Department of Computer Science and Information Engineering National ChengKung University Tainan Taiwan R.O.C

ISBN: (数字)9798350386073

ISBN: (纸本)9798350386080

In this study, we use the CIMulator platform to evaluate the performance of neuromorphic accelerators with novel Hf 0.5 Zr 0.5 O 2 (HZO) ferroelectric fin field-effect transistor (FefinFET) as synaptic device. The MNIST handwritten digit dataset is used for training and inference processes in multilayer perceptron (MLP) neural networks. With the highly optimized synaptic device, the results demonstrate high training and inference accuracy, achieving up to 97% for the MLP, approaching the accuracy of software implementations.

关键词： Training Performance evaluation Energy consumption Accuracy Neuromorphic engineering Neural networks Multilayer perceptrons

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An Efficient N-bit 8-2 Adder Compressor with a Constant Internal Carry Propagation Delay

An Efficient N-bit 8-2 Adder Compressor with a Constant Inte...

引用

IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Thomas V. Fontanari Guilherme Paim Leandro M. G. Rocha Patrícia Ücker Eduardo Costa Sergio Bampi Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9781728134277

ISBN: (纸本)9781728134284

Adder compressors (AC) have been extensively used in digital circuits like multipliers and transforms where several multi-bit operands have to be summed in parallel. Most available AC structures on the literature do not handle efficiently the intermediary carry propagation on wider bit-widths, potentially leading to longer critical paths and higher energy consumption. Hence, this paper proposes a novel non-hierarchical 8-2 adder compressor CMOS design with limited and constant carry propagation path for N-bit operands, minimizing both circuit delay and power dissipation. The proposed architecture as well as the state-of-the-art ACs are synthesized in a 65 nm CMOS commercial standard cell library, for multiple operands bit-widths. Logic synthesis results show that our proposed design reaches a maximum operating frequency at least 15.2% higher than current state-fo-th-art ACs, while also achieving up to 13.6% of power dissipation savings, increasing the savings with the bitwidth.

关键词： Adders Power dissipation Computer architecture Logic gates Proposals Propagation delay Transforms

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Microenvironmental Entropy Dynamics Analysis Reveals Novel Insights In Notch-Delta-Jagged Decision-Making Mechanism

SSRN

引用

SSRN 2024年

作者： Pujar, Aditi Ajith Barua, Arnab Dey, Partha Sarathi Singh, Divyoj Roy, Ushasi Jolly, Mohit Kumar Hatzikirou, Haralampos Department of Bioengineering Indian Institute of Science Bangalore560012 India Undergraduate Program Indian Institute of Science Bangalore560012 India Hyderabad500046 India Mathematics Department Khalifa University P.O. Box: 127788 Abu Dhabi United Arab Emirates Technische Univesität Dresden Center for Information Services and High Performance Computing Nöthnitzer Straße 46 P.O. Box: Dresden01062 Germany

Notch-Delta-Jagged (NDJ) signaling among neighboring cells contributes crucially to spatiotemporal pattern formation and developmental decision-making. Many mathematical models capturing detailed biochemical reaction rate parameters have been developed for NDJ signaling. However, the high dimensionality of parameter space in such models limits their analytical treatments, especially in the context of impact of local microenvironmental fluctuations. Here, using the low-dimensional dynamics of the recently postulated least microenvironmental uncertainty principle (LEUP) framework, we showcase how the LEUP formalism recapitulates a noisy NDJ spatial patterning. Our LEUP simulations show that local phenotypic entropy increases for lateral inhibition, but decreases for lateral induction. This distinction allows us to identify a critical parameter that captures the transition from a Notch-Delta driven lateral inhibition to a Notch-Jagged driven lateral induction phenomenon, and suggests random phenotypic patterning in the case of lack of dominance of either Notch-Delta or Notch-Jagged signaling. Our results enable an analytical treatment to map the high-dimensional dynamics of NDJ signaling on tissue-level patterning, and can possibly be generalized to decode operating principles of collective cellular decision-making. © 2024, The Authors. All rights reserved.

关键词： Decision making

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Implementation of a real-time ISDB-TB LDM receiver using SDR

Implementation of a real-time ISDB-TB LDM receiver using SDR

引用

2019 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2019

作者： Rabaca, Ricardo Seriacopi De Oliveira, George Henrique Maranhao Garcia Jerji, Fadi Akamine, Cristiano Electrical Engineering and Computing Program Mackenzie Presbyterian University São Paulo Brazil

ISBN: (纸本)9781728121505

This paper presents an implementation of a realtime ISDB-TB LDM receiver in Software Defined Radio/GNU Radio Companion. The main idea of this work is to provide a hybrid digital TV broadcasting system that can be used as an option in a transition period between the current Brazilian system (ISDB-TB) and a possible new standard, such as a modified version of ATSC 3.0. The Core Layer is fully compatible with ISDB-TB and is multiplexed with an Enhanced Layer using a powerful channel coder, high order modulations and some other ATSC 3.0 features and techniques. With the use of the LDM in such systems, it is possible to deploy UHDTV applications. The implementation is done using the GNU Radio Companion software along with a Software Defined Radio platform to transmit and receive the Radio Frequency signal in real-time. © 2019 IEEE.

关键词： Software radio

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Experimentation of Gamification for Health and Fitness Mobile Application

Experimentation of Gamification for Health and Fitness Mobil...

引用

2019 International Congress on Applied Information Technology, AIT 2019

作者： Buntoro, Ignatius Kenny Kosala, Raymond Computer Science Program Faculty of Computing and Media Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781728158624

Lack of fitness is a growing problem in recent years and it can lead to many non-infectious disease with heart disease as the number one killer. There are many health application available on mobile phones. However, the applications available on the market right now are usually only able to do a specific task, such as calorie tracker or fitness tracker or blood pressure tracker. To maintain or improve health and fitness we need to take into account combination of several factors, which require users to use different applications. In this paper, we developed a mobile application that has combined health-relevant features: a calorie tracker to help user loss or maintain weight, blood pressure and pulse tracker, and fitness tracker. These are three essential factors to help user live a healthy life and prevent heart disease. In addition, we also implemented a simple gamification feature to increase users' motivation to use the application and do the exercises. The experimentation and findings showed that the proposed solution would be beneficial to help people keep a healthy heart and go fit. © 2019 IEEE.

关键词： Blood pressure

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Quantum-Inspired Acceleration for Image Reconstruction on Ising Machines

Quantum-Inspired Acceleration for Image Reconstruction on Is...

引用

Quantum computing and Engineering (QCE), IEEE International Conference on

作者： Yen-Jui Chang Hao-Yuan Chen Ying Chang Lu Lien-Po Yu Chao-Ming Fu Ching-Ray Chang Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City Taiwan Department of Physics National Taiwan University Taipei Taiwan Fujitsu Taiwan Ltd. Taipei Taiwan Department of Computer Science University of London London United Kingdom Institute for Information Industry Taipei Taiwan Fo Guang University Yilan Taiwan Quantum Information Center Chung Yuan Christian University Taoyuan City Taiwan

The study investigates a quantum-inspired approach to image reconstruction using Ising machines and demonstrates its significant improvements over the contrastive divergence method in Restricted Boltzmann Machines tra... 详细信息

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

关键词： Training Quantum computing Image reconstruction

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Framework to Creation of Inclusive and Didactic Digital Material for Elderly 15

Framework to Creation of Inclusive and Didactic Digital Mate...

引用

15th Iberian Conference on Information Systems and Technologies, CISTI 2020

作者： Eliseo, Maria Amelia Oyelere, Solomon Sunday Silva, Camilla Almeida Da Silveira, Ismar Frango Tomczyk, Lukasz Hercovici, Mariana Amato, Cibelle A. De La Higuera Akyar, Ozgur Yasar Martins, Valeria Farinazzo Mackenzie Presbyterian University Computing and Informatics Department São Paulo Brazil University of Eastern Finland School of Computing Joensuu Finland Institute of Educational Studies Pedagogical University of Cracow Cracow Poland Mackenzie Presbyterian University Developmental Disorders Graduate Program São Paulo Brazil Hacettepe University Faculty of Sport Sciences Ankara Turkey

ISBN: (纸本)9789895465903

The elderly population has been increased due better health conditions and quality of life. With a healthier aging, the elderly start to have a more active and participative life in society. They pursue, among other things, to acquire new knowledge and despite being a generation which access to existing technology was restricted, there is an increase in the use of digital technologies, especially in the educational field. However, with advancing age, cognitive and motor skills decrease. Given this scenario, the creation of accessible didactic materials that include the elderly population is necessary. This paper shows a framework to create inclusive digital material for elderly learning. The framework will help teachers to create digital contents that support elderly learners' personalized educational goals. © 2020 AISTI.

关键词： E-learning

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Thermodynamics-inspired Explanations of Artificial Intelligence

arXiv

引用

arXiv 2022年

作者： Mehdi, Shams Tiwary, Pratyush Biophysics Program Institute for Physical Science and Technology University of Maryland College Park20742 United States Department of Chemistry and Biochemistry Institute for Physical Science and Technology University of Maryland College Park20742 United States University of Maryland Institute for Health Computing RockvilleMD United States

In recent years, predictive machine learning methods have gained prominence in various scientific domains. However, due to their black-box nature, it is essential to establish trust in these models before accepting them as accurate. One promising strategy for assigning trust involves employing explanation techniques that elucidate the rationale behind a black-box model’s predictions in a manner that humans can understand. However, assessing the degree of human interpretability of the rationale generated by such methods is a nontrivial challenge. In this work, we introduce interpretation entropy as a universal solution for assessing the degree of human interpretability associated with any linear model. Using this concept and drawing inspiration from classical thermodynamics, we present Thermodynamics-inspired Explainable Representations of AI and other black-box Paradigms (TERP), a method for generating accurate, and human-interpretable explanations for black-box predictions in a model-agnostic manner. To demonstrate the wide-ranging applicability of TERP, we successfully employ it to explain various black-box model architectures, including deep learning Autoencoders, Recurrent Neural Networks, and Convolutional Neural Networks, across diverse domains such as molecular simulations, text, and image classification. © 2022, CC BY.

关键词： Thermodynamics

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