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arXiv 2023年

作者： Feng, Zixuan Guizani, Mariam Gerosa, Marco A. Sarma, Anita School of Electrical Engineering and Computer Science Oregon State University CorvallisOR United States School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAZ United States

Diversity and inclusion (D&I) in open source software (OSS) is a multifaceted concept that arises from differences in contributors’ gender, seniority, language, region, and other characteristics. D&I has received growing attention in OSS ecosystems and projects, and various programs have been implemented to foster contributor diversity. However, we do not yet know how the state of D&I is evolving. By understanding the state of D&I in OSS projects, the community can develop new and adjust current strategies to foster diversity among contributors and gain insights into the mechanisms and processes that facilitate the development of inclusive communities. In this paper, we report and compare the results of two surveys of Apache Software Foundation (ASF) contributors conducted over two years (n=624 & n=432), considering a variety of D&I aspects. We see improvements in engagement among those traditionally underrepresented in OSS, particularly those who are in gender minority or not confident in English. Yet, the gender gap in the number of contributors remains. We expect this study to help communities tailor their efforts in promoting D&I in OSS. Copyright © 2023, The Authors. All rights reserved.

关键词： Open source software

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Enhancing 3T Retinotopic Maps Using Diffeomorphic Registration

Enhancing 3T Retinotopic Maps Using Diffeomorphic Registrati...

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IEEE International Symposium on Biomedical Imaging

作者： Negar Jalili-Mallak Yanshuai Tu Zhong-Lin Lu Yalin Wang School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA Division of Arts and Sciences NYU Shanghai Shanghai China Center for Neural Science and Department of Psychology New York University New York USA NYU-ECNU Institute of Brain and Cognitive Science NYU Shanghai Shanghai China

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Retinotopic mapping aims to uncover the relationship between visual stimuli on the retina and neural responses on the visual cortical surface. This study advances retinotopic mapping by applying diffeomorphic registration to the 3T NYU retinotopy dataset, encompassing analyze-PRF and mrVista data. Diffeomorphic Registration for Retinotopic Maps (DRRM) quantifies the diffeomorphic condition, ensuring accurate alignment of retinotopic maps without topological violations. Leveraging the Beltrami coefficient and topological condition, DRRM significantly enhances retinotopic map accuracy. Evaluation against existing methods demonstrates DRRM’s superiority on various datasets, including 3T and 7T retinotopy data. The application of diffeomorphic registration improves the interpretability of low-quality retinotopic maps, holding promise for clinical applications.

关键词： Visualization Accuracy Oxygen Time series analysis Functional magnetic resonance imaging Retina Iterative methods

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Neonatal Disease Prediction Using Machine Learning Techniques

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Journal of Healthcare engineering 2023年第1期2023卷 3567194页

作者： Robi, Yohanes Gutema Sitote, Tilahun Melak Department of Information Systems College of Computing and Informatics Haromaya University P.O. Box 138 Dire Dawa Ethiopia School of Electrical Engineering and Computing Adama Science and Technology University P.O. Box 1888 Adama Ethiopia

Neonatal diseases are among the main causes of morbidity and a significant contributor to underfive mortality in the world. There is an increase in understanding of the pathophysiology of the diseases and the implementation of different strategies to minimize their burden. However, improvements in outcomes are not adequate. Limited success is due to different factors, including the similarity of symptoms, which can lead to misdiagnosis, and the inability to detect early for timely intervention. In resource-limited countries like Ethiopia, the challenge is more severe. Low access to diagnosis and treatment due to the inadequacy of neonatal health professionals is one of the shortcomings. Due to the shortage of medical facilities, many neonatal health professionals are forced to decide the type of disease only based on interviews. They may not have a complete picture of all variables that have a contributing effect on neonatal disease from the interview. This can make the diagnosis inconclusive and may lead to a misdiagnosis. Machine learning has great potential for early prediction if relevant historical data is available. We have applied a classification stacking model for the following four main neonatal diseases: sepsis, birth asphyxia, necrotizing enter colitis (NEC), and respiratory distress syndrome. These diseases account for 75% of neonatal deaths. The dataset has been obtained from the Asella Comprehensive Hospital. It has been collected between 2018 and 2021. The developed stacking model was compared to three related machine-learning models XGBoost (XGB), Random Forest (RF), and Support Vector Machine (SVM). The proposed stacking model outperformed the other models, with an accuracy of 97.04%. We believe that this will contribute to the early detection and accurate diagnosis of neonatal diseases, especially for resource-limited health facilities. © 2023 Yohanes Gutema Robi and Tilahun Melak Sitote.

关键词： Diseases

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Generation of Dynamic Authorization Using Cryptography For Private-Keyless Data Sharing

SSRN

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SSRN 2023年

作者： Lu, Hai Zhu, Yan Yau, Stephen S. Zhu, Guizhen Lv, Kewei School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85281 United States Data and Communication Science Technology Research Institute Beijing100191 China School of Cyber Security University of Chinese Academy of Sciences Beijing100093 China

Private-keyless access is emerging as an inevitable trend in the evolution of future information systems. It helps simplify key management, enhance security, and increase flexibility of access authorization. Hereby, we introduce a novel security model, Cryptographic Resource Enabled Infrastructure (CREI), to support private-keyless access and policy-based data custody. Firstly, in the data custody phase, data resource and its session key are uploaded in ciphertext form to CREI, and the access authorization complies with multiple policies designated by the provider. Secondly, in the dynamic authorization phase, traditional keys or keycards are replaced with real-time attribute credentials issued by multiple authorities. CREI makes dynamically cryptographic policy decision according to the credentials and the cryptographic policy (cryptopolicy). Technically, we design the Credentials-Driven Cryptosystem (CDC) over ideal lattice to build anti-quantum confidence for CREI. In CDC, preimage Gaussian sampler is adopted to sample short vector as real-time attribute credential instead of user's private key. Small Policy Matrix (SPM) is implemented to convert monotone policies into optimized cryptopolicies in order to reduce accumulated error. The security analysis confirms that the credentials, cryptopolicy and its decision result are existentially unforgeable, ensuring the semantic security of the whole CREI. Experimental results indicate CREI has lower storage and computational costs than existing schemes. Meanwhile, despite continuous improvements to the access policies as system evolves, CREI can simply select an appropriate policy among multiple candidates to make authorization decisions without having to re-encrypt data. © 2023, The Authors. All rights reserved.

关键词： Authorization

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Validating trustworthy service composition through VIPLE and pi-calculus

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International Journal of Simulation and Process Modelling 2020年第1-2期15卷 76-88页

作者： Zhao, Shenghui Li, Yuemin Wang, Yang Chen, Yinong College of Computer Information and Engineering Chuzhou University Chuzhou Anhui China School of Computing Informatics and Decision System Engineering Arizona State University TempeAZ85287 United States

The current formal verification practice focuses on functionality and does not consider verification of the non-functional attributes. In this study, we propose a method in which non-functional attributes are incorporated into the logic rules of inference in terms of composition of the linear logic and pi-calculus. Giving the credibility to non-functional attributes is important, especially in the cloud computing platform and IoT environments, where trust and security are ultra-important. Such studies have not been paid much attention by researchers and practitioners. In our approach, the evolvement of the non-functional attributes is included in the process of formal verification of the service composition scheme. In addition to theoretical analysis, we applied a tool named Visual IoT/robotics Programming Language Environment (VIPLE) to execute and verify the validity of the service composition model's function. We translate the proving process of the linear logic into the corresponding pi-calculus expressions. VIPLE can translate visual work flow into pi-calculus and can verify the correctness of pi-calculus expressions. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Computer circuits

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Non-linear Analysis for Operational Safety Verification of Cyber Physical systems 3

Non-linear Analysis for Operational Safety Verification of C...

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3rd IEEE Conference on Industrial Cyberphysical systems, ICPS 2020

作者： Banerjee, Ayan Lamrani, Imane Gupta, Sandeep K.S. Arizona State University School of Computer Informatics and Decision Systems Engineering United States

ISBN: (纸本)9781728163895

Reach set approximation is an important tool for operational safety analysis of Cyber-Physical systems (CPS). However, industrial CPS typically experience non-linear dynamics. Piece-wise linearization is popularly employed to simplify the continuous dynamics with certain approximation errors, which typically increase non-linearly with respect to size of each piece (simplex). In this paper, we utilize ExReach that employs a novel reach set estimation algorithm for non-linear hybrid systems and show the use on practical medical cyber-physical system examples such as artificial pancreas and ventilators. In addition, we compare the performance of ExReach with existing tools such as Flow? on six non-linear systems with dimensions varying from 2 to 28. ExReach outputs a tighter over-approximation of the reach set of the CPS than Flow* or C2E2. © 2020 IEEE.

关键词： Cyber Physical System

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On designing experiments for a dynamic response modeled by regression splines

On designing experiments for a dynamic response modeled by r...

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作者： Pan, Rong Saleh, Moein School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ United States PayPal San Jose United States

Dynamic response systems are often found in science, engineering, and medical applications, but the discussion on experimental design for such a system is relatively rare in literature. For an experimenter, designing such experiments requires making decisions on (1) when or where to take response measurements along the dynamic variable and (2) how to choose the combination of experimental factors and their levels. The first consideration is unique for such experiments, especially when the measurement cost is high. In this paper, we present a design approach through the mixed-effect linear model, which is based on a hierarchical B-spline function for the dynamic response. We develop several theorems that can assist in finding a statistically efficient sampling plan and propose an algorithm for searching the D-optimal design of a dynamic response system. © 2019 John Wiley & Sons, Ltd.

关键词： Dynamic response

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Coupling Weap and Leap Models Using Interaction Modeling

Coupling Weap and Leap Models Using Interaction Modeling

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2020 Spring Simulation Conference, SpringSim 2020

作者： Fard, Mostafa D. Sarjoughian, Hessam S. Arizona State University Arizona Center for Integrative Modeling Simulation School of Computing Informatics and Decision Systems Engineering TempeAZ United States

ISBN: (纸本)9781565553705

It is useful to model the interactions between the water and energy models separately. A coupled water and energy model using an interaction model lends itself to developing flexible, yet rigorous predictive simulation studies. A WEAP-LEAP interaction model is developed based on the Knowledge Interchange Broker modeling approach. A RESTful simulation framework is developed for coupling the Componentized-WEAP and Componentized-LEAP systems. Every interaction model is defined to have a set of modules where each module has its input and output ports with data transformation schemes. The input and output ports of the Componentized-WEAP and Componentized-LEAP models are coupled with those of the interaction model. A cyclic, synchronous execution protocol is defined for concurrent, bidirectional data transformations. The computational efficiency of this loosely coupled water-energy framework is acceptable compared with the tightly WEAP-LEAP system. This proposed framework shows understanding the water-energy system nexus is advantageous using interaction modeling. © 2020 SCS.

关键词： Computational efficiency

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StyleGAN-∞: Extending StyleGAN to Arbitrary-Ratio Translation with StyleBook

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IEEE Transactions on Visualization and Computer Graphics 2024年

作者： Dai, Yihua Xiang, Tianyi Deng, Bailin Du, Yong Cai, Hongmin Qin, Jing He, Shengfeng South China University Of Technology School Of Computer Science And Engineering Guangzhou China Singapore Management University School Of Computing And Information Systems Singapore Cardiff University School Of Computer Science And Informatics United Kingdom Ocean University Of China Faculty Of Information Science And Engineering Qingdao China Hong Kong Polytechnic University School Of Nursing Hong Kong Hong Kong

Although pre-trained large-scale generative models StyleGAN series have proven to be effective in various editing and translation tasks, they are limited to pre-defined fixed aspect ratio. To overcome this limitation, we propose StyleGAN-∞, a model that enables pre-trained StyleGAN to perform arbitrary-ratio conditional synthesis. Our key insight is to distill the expressive StyleGAN features into a StyleBook, such that an arbitrary-ratio condition can be translated to other forms by properly assembling pre-defined StyleBook vectors. To learn and leverage the StyleBook, we employ a network with three distinct stages, each corresponding to StyleBook extraction, StyleBook correspondence learning, and arbitrary-ratio synthesis. Extensive experiments on various conditional synthesis tasks, like super-resolution, sketch synthesis, and semantic synthesis, demonstrate superior performances over state-of-the-art image-to-image translation methods. Moreover, our model can easily generate megapixel images in diverse modalities by taking advantage of different pre-trained StyleGAN models. © 1995-2012 IEEE.

关键词： Generative adversarial networks

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PPO-Based Energy Efficiency Maximization For RIS-Assisted Multi-User Miso systems

PPO-Based Energy Efficiency Maximization For RIS-Assisted Mu...

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IEEE Conference on Vehicular Technology (VTC)

作者： Amjad Iqbal Ala'a Al-Habashna Gabriel Wainer Gary Boudreau Faouzi Bouali Department of Systems and Computer Engineering Carleton University Ottawa Canada School of Computing and Informatics Al Hussein Technical University Amman Jordan Ericsson Canada Kanata Canada Coventry University Coventry United Kingdom

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

In this paper, we explore the integration of a reconfigurable intelligent surface (RIS) with a multi-antenna base station (BS) for downlink multi-user multiple-input-single-output (MU-MISO) systems. We aim to enhance energy efficiency (EE) by jointly optimizing beamforming and phase shifts at the BS and RIS, respectively, while ensuring each mobile user meets their link budget requirements. The resulting optimization problem is inherently non-convex. To address this challenge, we employ proximal policy optimization (PPO), known for efficiently managing non-convex problems and reducing training overhead in continuous action spaces through a clip factor. Furthermore, by leveraging deep neural networks (DNN), the proposed PPO-based solution provides the optimum values for the beamforming at the BS and the phase shift at the RIS, respectively. Finally, we demonstrate the effectiveness and accuracy of the proposed PPO-based algorithm through an extensive simulation campaign, comparing its performance against baseline methods (i.e., fractional programming (FP) and deep deterministic policy gradient (DDPG)). The results show that our proposed PPO-based algorithm outperforms the considered baseline approaches (i.e., FP and DDPG) in terms of EE by 34.2% and 15.8%, respectively.

关键词： Training Vehicular and wireless technologies Array signal processing Artificial neural networks Reconfigurable intelligent surfaces Programming MISO communication Energy efficiency Multiuser channels Optimization

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