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4th IEEE/ACM International Conference on Mobile software engineering and Systems, MOBILESoft 2017

作者： Mujahid, Suhaib Sierra, Giancarlo Abdalkareem, Rabe Shihab, Emad Shang, Weiyi Lab Dept. Computer Science and Software Engineering Concordia University Montreal Canada

ISBN: (纸本)9781538626696

Wearable apps are becoming increasingly popular in recent years. However, to date, very few studies examined the issues that wearable apps face. Prior studies showed that user reviews contain a plethora of insights that can be used to understand quality issues and help developers build better quality mobile apps. Therefore, in this paper, we mine user reviews in order to understand the user complaints of wearable apps. We manually sample and categorize 589 reviews from 6 Android wearable apps. Our findings indicate that the most frequent complaints are related to functional errors, lack of functionality, and cost. Our results are useful to the wearable developer community since they highlight the issues that users face and care most about. © 2017 IEEE.

关键词： Android (operating system)

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A study on performance evaluation of computer systems using Petri Nets

A study on performance evaluation of computer systems using ...

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International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS)

作者： Tanuja Shailesh Ashalatha Nayak Devi Prasad Dept. Computer Science and Engineering Manipal Institute of Technology Manipal Academy of Higher Education Software Consultant Manipal India

ISBN: (纸本)9781538677100

This paper describes performance evaluation of Real-time system using Petri net. Two types of Petri nets Stochastic Petri net (SPN) and Generalized Stochastic Petri net(GSPN) are discussed and a comparative study the two variants of Petri net has been proposed. This comparison will give an insight on the use of Generalized Stochastic Petri net over Stochastic Petri net. An example of a parallel system modelled using SPN and GSPN is used to analyze the comparison between SPN and GSPN. A case study from manufacturing industry that belongs to the class of pull strategies Just-in-Time is considered to explore the flexibility of GSPN in modeling and analysis of a Real-time system. Open source software PIPE is used to model and analyze SPN and GSPN for performance evaluation of Real-Time system.

关键词： Petri nets Analytical models Stochastic processes Performance evaluation Real-time systems Throughput Computational modeling

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Poster abstract: Recommendation-based smart indoor navigation 2

Poster abstract: Recommendation-based smart indoor navigatio...

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2nd IEEE/ACM International Conference on Internet-of-Things Design and Implementation, IoTDI 2017

作者： Wang, Wenlu Ku, Wei-Shinn Dept. of Computer Science and Software Engineering Auburn University AuburnAL United States

ISBN: (纸本)9781450349666

Localization in indoor spaces has to rely on sensing devices (e.g., Radio Frequency Identification (RFID) readers, WiFi routers, bluetooth beacons) rather than GPS devices. On the other side, we could build a smart indoor environment that facilitates all types of spatial services with various sensing devices. In this paper, we focus on the topic of spatial navigation. Due to the complexity of indoor environments, we believe the indoor navigation strategy should not be limited to the shortest path. Taking shopping centers for example, a navigation path should be not only the shortest path, but also an attractive route to the shopper. We aim to build a smart indoor navigation system, which not only learns the user's behavior through previous sensing data, but also enjoys working with heterogeneous devices. Therefore, we propose a novel recommendation based smart navigation strategy with Recurrent Neural Network (RNN). This strategy provides optimal user experience by: 1) Memorizing the user's historical data;2) Overlapping the navigation with the user's indoor behavior model;3) Making recommendations based on real-time detections from sensor devices. © 2017 ACM.

关键词： Recurrent neural networks

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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-dept. literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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Tour de Tune - Auditory-game-motor synchronisation in exergames 27

Tour de Tune - Auditory-game-motor synchronisation in exerga...

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27th International Conference on Artificial Reality and Telexistence, ICAT 2017 and the 22nd Eurographics Symposium on Virtual Environments, EGVE 2017

作者： Finlayson, J. Peterson, J. Free, J. Lo, M. Shaw, L. Lutteroth, C. Wünsche, B.C. Dept. of Software Engineering University of Auckland New Zealand Dept. of Computer Science University of Auckland New Zealand Dept. of Computer Science University of Bath United Kingdom

ISBN: (纸本)9783038680383

Exergaming has been heralded as a promising approach to increase physical activity in hard-to-reach populations such as sedentary young adults. By combining physical activity with entertainment, researchers and developers hope that the excitement and immersion provided by a computer game will result in increased motivation and dissociation from the discomfort of physical exercise. A different approach to improve physical activity is the use of music. Music, in particular if synchronised with the rhythm of exercise, has been shown to increase performance and decrease the amount of perceived effort for the same performance. So far little research has been done on the combined effect of music and gameplay in exergaming. In this paper we investigate the effect of game-music synchronisation for an immersive exergame. We present a simple yet effective music analysis algorithm, and a novel exergame enabling synchronisation of gameplay with the music's intensity. Our results indicate that our exergame significantly increases enjoyment and motivation compared to music alone. It slightly increases performance, but also increases perceived effort. We did not find any significant differences between gameplay synchronised and not synchronised with the music. Our results confirm the positive effects of music while exercising, but suggest that gameplay might have a bigger effect on exergame effectiveness, and more research on the interaction between gameplay and music needs to be done. © 2017 The Author(s).

关键词： Motivation

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Integrated software Development Methodology for Real-time Precise Control of UAV

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IOP Conference Series: Materials Science and engineering 2019年第1期611卷

作者： Jung Kyu Park Eun Young Park Heung Seok Jeon Dept. of Computer Software Engineering Changshin Univ. Changwon-si Korea Dept. Biomedical Laboratory science Shinhan University Uijeongbu-si South Korea Dept. of Computer Engineering Konkuk University Chungju-si Korea

Recently, drones have been widely used in education and industry. In this paper, we propose a navigation and control algorithm to develop unmanned drones quickly. To limit the proposed framework, we analysed the existing drone solution and simulation framework. We also used Hardware-in-the-Loop (HIL) simulation for rapid development. HIL will simulate physical systems that interface with embedded control equipment on real-time hardware. The code generated in this process can be experimented on a hardware device so that the control performance of the drones can be verified without draining the drones in the outdoor environment. Using the proposed method, you save time and money on drone development while providing stability.

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Toward a self-learned Smart Contracts

arXiv

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arXiv 2018年

作者： Almasoud, Ahmed Eljazzar, Maged M. Hussain, Farookh Faculty of Software University of Technology Sydney UltimoNSW2007 Australia Computer Engineering Dept. Faculty of Engineering Cairo Universit Giza12613 Egypt

In recent years, Blockchain technology has been highly valued and disruptive. Several research has presented a merge between blockchain and current application i.e. medical, supply chain, and e-commerce. Although Blockchain architecture does not have a standard yet, IBM, MS, AWS offer BaaS (Blockchain as a Service). In addition to the current public chains i.e. Ethereum, NEO, and Cardeno. There are some differences between several public ledgers in terms of development and architecture. This paper introduces the main factors that affect integration of Artificial Intelligence with Blockchain. As well as, how it could be integrated for forecasting and automating;building self-regulated chain. Copyright © 2018, The Authors. All rights reserved.

关键词： Smart contract

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Learning a bias correction for lidar-only motion estimation

arXiv

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arXiv 2018年

作者： Tang, Tim Y. Yoon, David J. Pomerleau, François Barfoot, Timothy D. Institute for Aerospace Studies University of Toronto Toronto Canada Dept. Computer Science and Software Engineering Laval University Quebec City Canada

This paper presents a novel technique to correct for bias in a classical estimator using a learning approach. We apply a learned bias correction to a lidar-only motion estimation pipeline. Our technique trains a Gaussian process (GP) regression model using data with ground truth. The inputs to the model are high-level features derived from the geometry of the point-clouds, and the outputs are the predicted biases between poses computed by the estimator and the ground truth. The predicted biases are applied as a correction to the poses computed by the estimator. Our technique is evaluated on over 50 km of lidar data, which includes the KITTI odometry benchmark and lidar datasets collected around the University of Toronto campus. After applying the learned bias correction, we obtained significant improvements to lidar odometry in all datasets tested. We achieved around 10% reduction in errors on all datasets from an already accurate lidar odometry algorithm, at the expense of only less than 1% increase in computational cost at run-time. Copyright © 2018, The Authors. All rights reserved.

关键词： Optical radar

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Coarse-grained mtime update for better fsync() performance 17

Coarse-grained mtime update for better fsync() performance

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32nd Annual ACM Symposium on Applied Computing, SAC 2017

作者： Son, Hankeun Lee, Seongjin Choi, Gyeongyeol Won, Youjip Dept. of Computer Science Hanyang University Korea Republic of Dept. of Aerospace and Software Engineering Gyeongsang National University Korea Republic of

ISBN: (纸本)9781450344869

This work is dedicated to improve the performance of the fsync(), which is one of the most expensive system calls in UNIX operating systems. Due to the recent advancement of the Flash storage based storage device, the storage device can flush the data blocks in order of magnitudes faster than the legacy HDDs. Often, the rate of flushing the data blocks to the storage device prevails the rate of CPU updating the file system time. The amount of the dirty blocks created in the system depends on the timer interrupt interval of the kernel. Read and write operations update the atime and mtime metadata, respectively. These timestamps are useful;however, there is significant performance degradation due to frequent updates of the metadata. Now in the file system, atime has several options to mediate between usefulness and performance efficiency. Most of the Database Management Systems frequently perform fsync() to guarantee the consistency of user data. The synchronous writes involve journaling overhead of updating mtime metadata in EXT4 file system. However, the effect of frequent update of mtime on write intensive workload has been overlooked. We introduce coarse-grained mtime update scheme to increase the mtime/ctime timestamp update interval while maintaining the same level of resolution for kernel time interrupts. As a result, coarse-grained update interval scheme reduces the journaling overhead with the least effort. The experiment results show that the I/O performance of random workload on mobile and PC increased about 7% and 107% against the default mtime update interval, respectively. The result of insert operations on PERSIST mode of SQLite on mobile and PC shows 8.4% and 45.1% of I/O performance increase, respectively. On MySQL OLTP workload, the performance increased by 7.9%. Copyright 2017 ACM.

关键词： Metadata

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Embracing Technical Debt, from a Startup Company Perspective

Embracing Technical Debt, from a Startup Company Perspective

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International Conference on software Maintenance (ICSM)

作者： Terese Besker Antonio Martini Rumesh Edirisooriya Lokuge Kelly Blincoe Jan Bosch Computer Science and Engineering Software Engineering Chalmers University of Technology Göteborg Sweden CA Technologies Strategic Research Team Barcelona Spain Dept. of Electrical and Computer Engineering The University of Auckland Auckland New Zealand

software startups are typically under extreme pressure to get to market quickly with limited resources and high uncertainty. This pressure and uncertainty is likely to cause startups to accumulate technical debt as they make decisions that are more focused on the short-term than the long-term health of the codebase. However, most research on technical debt has been focused on more mature software teams, who may have less pressure and, therefore, reason about technical debt very differently than software startups. In this study, we seek to understand the organizational factors that lead to and the benefits and challenges associated with the intentional accumulation of technical debt in software startups. We interviewed 16 professionals involved in seven different software startups. We find that the startup phase, the experience of the developers, software knowledge of the founders, and level of employee growth are some of the organizational factors that influence the intentional accumulation of technical debt. In addition, we find the software startups are typically driven to achieve a "good enough level," and this guides the amount of technical debt that they intentionally accumulate to balance the benefits of speed to market and reduced resources with the challenges of later addressing technical debt.

关键词： software Companies Interviews Conferences Product development

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