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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Khannouz, Martin Glatard, Tristan Concordia University Department of Computer Science and Software Engineering MontrealQC Canada

ISBN: (纸本)9781665480451

Supervised learning algorithms generally assume the availability of enough memory to store data models during the training and test phases. However, this assumption is unrealistic when data comes in the form of infinite data streams, or when learning algorithms are deployed on devices with reduced amounts of memory. Such memory constraints impact the model behavior and assumptions. In this paper, we show that under memory constraints, increasing the size of a tree-based ensemble classifier can worsen its performance. In particular, we experimentally show the existence of an optimal ensemble size for a memory-bounded Mondrian forest on data streams and we design an algorithm to guide the forest toward that optimal number by using an estimation of overfitting. We tested different variations for this algorithm on a variety of real and simulated datasets, and we conclude that our method can achieve up to 95% of the performance of an optimally-sized Mondrian forest for stable datasets, and can even outperform it for datasets with concept drifts. All our methods are implemented in the OrpailleCC open-source library and are ready to be used on embedded systems and connected objects. © 2022 IEEE.

关键词： Learning algorithms

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Energy Efficiency Issues in Android Application: A Literature Review 24

Energy Efficiency Issues in Android Application: A Literatur...

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24th International Multitopic Conference, INMIC 2022

作者： Ullah, Obaid Hanan, Muhammad Ghafoor, Maryam Abdul National University of Computer and Emerging Sciences Department of Software Engineering Islamabad Pakistan

ISBN: (数字)9798350397109

ISBN: (纸本)9798350397109

In today's digital world, almost every person owns a smartphone device. Due to more emphasis on the functional aspect of an application, programmers often follow such practices that consume a lot of energy. Hence, the purpose of this literature review is to find such issues that can cause more energy consumption in the android applications along with finding their solutions from the literature. The literature review also includes year-wise and venue-wise paper distribution. Out of our initial 145 papers, we discarded 4 papers based on a duplicate study, then 100 papers were discarded on the title and abstract-based screening while 22 papers were discarded based on inclusion/exclusion and quality assurance criteria. A final of 19 studies were considered for this study and were read thoroughly. Our results reveal that bad programming practice was the most discussed issue (26%) while tool-related problems and patterns were the least discussed issues in the literature (15.7%). Tool-based solutions are discussed mostly (36.84%) while refactoring technique and applying other techniques are discussed least (10.5%) in the literature. The work is helpful for the researchers and developers as they can learn from this about the energy consumption reasons and their solutions. © 2022 IEEE.

关键词： Electric power utilization

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Towards Secure Agile software Development Process: A Practice-Based Model 48

Towards Secure Agile Software Development Process: A Practic...

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48th Euromicro Conference on software engineering and Advanced Applications, SEAA 2022

作者： Ardo, Abdulhamid A. Bass, Julian M. Gaber, Tarek University of Salford Department of Computer Science & Software Engineering Manchester United Kingdom

ISBN: (纸本)9781665461528

Agile methods are a well-established paradigm in the software development field. Agile adoption has contributed to improving software quality. However, software products are vulnerable to security challenges and susceptible to cyberattacks. This study aims to improve security of software products when using an agile software development process. A multi-methods qualitative research approach was adopted in this study. First, we conducted semi-structured interviews with 23 agile practitioners having varied years of cybersecurity experiences. An approach informed by grounded theory methodology was adopted for data analysis. Second, we developed a novel practice-based agile software development process model derived from the results of the data analysis conducted. Third, we validated the model through a focus group comprising five senior agile cybersecurity professionals to evaluate its relevancy and novelty. The study has identified 26 security practices, organized into the six - software development life-cycle phases: planning, requirements, design, implementation, testing, and deployment. We have mapped the practices onto four swim lanes each representing an agile role. The self-organizing team is exclusively involved in three security practices, the security specialist in nine, penetration tester in one and the DevOps team collaborates on one with the security specialist. There are also seven practices that are collaboratively performed by the self-organizing team and the security specialist. Each of the practices in the model was examined during the validation phase of the study. There are two contributions in this study. First, the paper proposes a novel practice-based model comprising of 26 security practices mapped to agile roles. Second, we propose a new practice, in response to an observed lack of collaborative ceremonies, to disseminate awareness of and hence compliance with security standards. © 2022 IEEE.

关键词： software testing

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Does Repeatedly Typing the Same Phrase Provide a Good Estimate of Expert Text Entry Performance?

Does Repeatedly Typing the Same Phrase Provide a Good Estima...

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Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023

作者： Mutasim, Aunnoy K. Batmaz, Anil Ufuk Hudhud Mughrabi, Moaaz Stuerzlinger, Wolfgang Simon Fraser University VancouverBC Canada Computer Science & Software Engineering Department Concordia University MontrealQC Canada Mechatronics Engineering Department Kadir Has University Istanbul Turkey

ISBN: (纸本)9781450394222

To identify if novel/unfamiliar keyboard layouts like OPTI can outperform QWERTY, lengthy training through longitudinal studies is typically required. To reduce this logistical bottleneck, a popular approach in the literature requires participants to type the same phrase repeatedly. However, it is still unknown whether this approach provides a good estimate of expert performance. To validate this method, we set up a study where participants were tasked with typing the same phrase 96 times for both OPTI and QWERTY. Results showed that this approach has the potential to estimate expert performance for novel/unfamiliar keyboards faster than the traditional approach with different phrases. Yet, we also found that accurate estimates still require training over several days and, therefore, do not eliminate the need for a longitudinal study. Our findings thus show the need for research on faster, easier, and more reliable empirical approaches to evaluate text entry systems. © 2023 Owner/Author.

关键词： Taps

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Real-time 3D hand-object pose estimation for human-robot interaction

Real-time 3D hand-object pose estimation for human-robot int...

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2022 Australasian Conference on Robotics and Automation, ACRA 2022

作者： Yin, Yue McCarthy, Chris Rezazadegan, Dana Department of Computer Science and Software Engineering Swinburne University of Technology Melbourne Australia

ISBN: (纸本)9781713866480

Fast and accurate real-time 3D hand-object pose estimation is an important capability for many collaborative human-robot interaction applications. However, the application of vision-based hand-object pose estimation remains challenging, with most existing approaches relying on dedicated depth-sensing cameras and/or specialised hardware support to meet high computation and memory storage requirements. This limits the generality of use-cases for which 3D hand-object pose estimation models can be applied. Recent work has considered the use of lightweight models to reduce storage and computational overheads, typically trading off accuracy for realtime performance. While sufficient for some applications, high accuracy remains a key priority, especially in the context of human-robot collaboration. Addressing this issue, we propose a novel lightweight model for 3D handobject pose estimation that maintains realtime performance while also achieving an accuracy exceeding that of current state-of-theart approaches on the First Person Hand Action (FPHA) dataset. Our model thus offers a viable RGB-only solution for human-robot collaboration applications, and for low compute, embedded platforms more generally. © 2022 Australasian Robotics and Automation Association. All rights reserved.

关键词： Human robot interaction

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Critical Thermal Characterization of Next-Generation Solid-State Batteries for Automotive Battery Management Systems 14

Critical Thermal Characterization of Next-Generation Solid-S...

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14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Chetri, Chandan Williamson, Sheldon Group Department of Electrical Computer and Software Engineering Oshawa Canada

ISBN: (纸本)9798331516116

Solid-state batteries (SSBs) are at the forefront of next-generation energy storage technologies, promising enhanced safety, energy density, and longevity compared to traditional lithium-ion batteries. However, managing the thermal behavior of SSBs during charging is critical to ensuring their safe and reliable operation. This paper presents an in-depth analysis of the thermal characteristics of SSBs under various charging conditions, based on laboratory experiments conducted in controlled environments. The study specifically evaluates the thermal performance of SSBs in comparison to traditional lithium nickel cobalt aluminum oxide (NCA) batteries, with an emphasis on their potential application in e-mobility. The insights gained from this research are expected to inform the development of advanced thermal management strategies, contributing to the design of safer and more efficient solid-state battery technologies for e-mobility applications. © 2025 IEEE.

关键词： Solid-State Batteries

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A Machine Learning Based Approach to Detect Fault Injection Attacks in IoT software Systems

A Machine Learning Based Approach to Detect Fault Injection ...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Gangolli, Aakash Mahmoud, Qusay H. Azim, Akramul Ontario Tech University Department of Electrical Computer and Software Engineering OshawaON Canada

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

With the rapid growth of Internet of Things (IoT) applications, the security of these systems has become critical. Fault injection attacks are a type of physical attack on the hardware components of an IoT system. These attacks cause the IoT system software to behave abnormally, which the adversaries exploit. Typically, these attacks have been detected through the use of a separate hardware detection mechanism, which is expensive and itself vulnerable to attack. The purpose of this paper is to propose a machine learning based approach to detect the attacks by monitoring specific run-time software parameters in the live environment of an IoT system. The proposed approach generates a labelled dataset by injecting instruction-level faults into the software executable, which is then used to train a machine learning model that can predict whether the IoT software system is currently being affected by a fault injection attack. Using a software fault injection tool to create a labelled dataset enables the use of supervised machine learning techniques, which produce more accurate prediction results than unsupervised techniques. The machine learning model can be used in the live environment of an IoT software system to monitor specific run-time software properties in order to detect the effects of a fault injection attack on the software. Additionally, the model classifies the type of fault introduced into the software as a result of the attack, which can be used to determine the necessary corrective action. © 2022 IEEE.

关键词： Internet of things

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Bibliometric analysis of artificial intelligence and optical coherence tomography images:research hotspots and frontiers

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International Journal of Ophthalmology(English edition) 2023年第9期16卷 1431-1440页

作者： Hai-Wen Feng Jun-Jie Chen Zhi-Chang Zhang Shao-Chong Zhang Wei-Hua Yang Department of Software Engineering School of SoftwareShenyang University of TechnologyShenyang 110870Liaoning ProvinceChina Department of Computer School of Intelligent MedicineChina Medical UniversityShenyang 110122Liaoning ProvinceChina Shenzhen Eye Hospital Jinan UniversityShenzhen 518040Guangdong ProvinceChina

AIM:To explore the latest application of artificial intelligence(AI)in optical coherence tomography(OCT)images,and to analyze the current research status of AI in OCT,and discuss the future research ***:On June 1,2023,a bibliometric analysis of the Web of Science Core Collection was performed in order to explore the utilization of AI in OCT *** parameters such as papers,countries/regions,citations,databases,organizations,keywords,journal names,and research hotspots were extracted and then visualized employing the VOSviewer and CiteSpace V bibliometric ***:Fifty-five nations reported studies on AI biotechnology and its application in analyzing OCT *** United States was the country with the largest number of published ***,197 institutions worldwide provided published articles,where University of London had more publications than the *** reference clusters from the study could be divided into four categories:thickness and eyes,diabetic retinopathy(DR),images and segmentation,and OCT ***:The latest hot topics and future directions in this field are identified,and the dynamic evolution of AIbased OCT imaging are ***-based OCT imaging holds great potential for revolutionizing clinical care.

关键词： artificial intelligence optical coherence tomography bibliometric deep learning machine learning

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Enabling Trusted Peer-to-Peer Microgrid Energy Transactions during High-Impact Low Probability Weather Events 11

Enabling Trusted Peer-to-Peer Microgrid Energy Transactions ...

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11th International Conference on Innovative Smart Grid Technologies - Asia, ISGT-Asia 2022

作者： Lakshita, Lakshita Nair, Nirmal-Kumar C. The University of Auckland Department of Electrical Computer and Software Engineering Auckland New Zealand

ISBN: (纸本)9798350399660

Existing technology management strategies to address the electricity distribution system resilience, are utilizing distributed energy resources (DERs) and hardening the network assets during High Impact Weather events (HIW). The retail market mechanism platform for multiple DERs during a power outage caused by the HIW events has not been discussed in the existing literature. This paper focuses on peer-to-peer (P2P) transactive energy platform that expects to improve energy utilization rates among several DERs considering the suspension of halting of normal pricing mechanism. Hence, a model for the feasibility of P2P transactive energy platforms across four neighborhoods during a grid disturbance caused by 2018 windstorm in Auckland, New Zealand has been discussed along with the weather data analysis for the affected zone. This paper includes an islanded microgrid, which can be utilized during a disturbance and sustain its local demand through PV generation, battery storage and P2P energy transactions. © 2022 IEEE.

关键词： Energy resources

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Wide-ranging parameter extraction of Lithium-ion Batteries to Estimate State of Health using Electrochemical Impedance Spectroscopy 1

Wide-ranging parameter extraction of Lithium-ion Batteries t...

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1st IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2022

作者： Anekal, Latha Samanta, Akash Williamson, Sheldon Ontario Tech University Department of Electrical Computer and Software Engineering Oshawa Canada

ISBN: (纸本)9798350398069

To ensure effective and safer utilization of Lithium-Ion Batteries (LIB), accurate State Estimation particularly State of Health (SOH) is extremely essential, especially in automotive applications. Accurate information about SOH not only plays a crucial role in health-conscious battery management while at the same time helps to prognose battery fault and replacement. Battery SOH cannot be measured directly. Therefore, typically equivalent models and data-driven estimation techniques are used to obtain SOH through external measurements. Feature vectors required for SOH estimation can be very effectively extracted by Electrochemical Impedance Spectroscopy (EIS). Still, existing EIS-based methods have several limitations, issues, and challenges. Thus, a comprehensive review of state-of-the-art EIS-based SOH estimation techniques is presented in this paper to expedite the research effort toward developing a more advanced and practical EIS method for accurate and real-time SOH estimation. © 2022 IEEE.

关键词： Lithium-ion batteries

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