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Annual Conference of Industrial Electronics Society

作者： Arsalan Liaqat Max Somerville Matthew M. Y. Kuo John Spray Chen-Wei Yang Roopak Sinha Computer Science and Software Engineering Department Auckland University of Technology Auckland New Zealand Software Engineering Consultant Auckland New Zealand Dependable Communication and Computation Systems Lulea University of Technology Sweden School of Information Technology Deakin University Melbourne Australia

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

In smaller components of industrial or energy automation systems, such as device controllers of Protection and Control (PAC) systems in smart grids, controller functionality is tightly coupled with the physical device or sensor capabilities. At this level, software is small and therefore easy to maintain and test. However, when multiple controllers are interconnected and higher-level functionality is added, software applications grow exponentially, and ensuring maintainability becomes proportionally challenging. In this paper, we extend the IEC 61499 reference architecture used to develop industrial automation software with the principles of Abstraction Layered Architecture (ALA) that has shown up to 400% improvements in industrial software maintainability. We show that even a light application of abstraction layering on the top, application-level of IEC 61499 applications makes them significantly more readable and slightly more maintainable. More concrete gains in maintainability are expected when abstraction layering is integrated into lower layers.

关键词： Industrial electronics Automation Buildings computer architecture Control systems software Picture archiving and communication systems Smart grids Protection IEC Standards

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A Multi-functional Fast Electric Vehicle Charging Technique

A Multi-functional Fast Electric Vehicle Charging Technique

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2021 IEEE Southern Power Electronics Conference, SPEC 2021

作者： Song, Bingkun Wang, Lei Madawala, Udaya Baguley, Craig The University of Auckland Department of Electrical Computer and Software Engineering Auckland New Zealand Hunan University College of Electrical and Information Engineering Changsha China

ISBN: (纸本)9781665436236

For many distribution network operators (DNOs), the phases to which single-phase loads are connected is unknown. This can present a problem in terms of unbalanced loading across phases, which will be significantly exacerbated by the future impact of large-scale electric vehicle (EV) charging loads. In addition, the implementation of EV charging systems can give rise to the presence of significant harmonics on power systems, as a result of converter operation. Therefore, this paper proposes a fast EV charging technique that incorporates phase balancing and harmonic suppression features. This allows multiple and important functions that are necessary for the improved operation of a local distribution network to be achieved through the installation of a single unit. Consequently, units based on the proposed technique suit the large-scale and strategic deployment in distribution networks. The paper describes the technique in detail, presenting relevant theory and the control strategy. To demonstrate the applicability of the proposed technique, simulated results of a 50 kW fast EV charger are presented under various unbalanced load conditions. © 2021 IEEE.

关键词： Harmonic analysis

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Inertial Motion Tracking on Mobile and Wearable Devices:Recent Advancements and Challenges

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Tsinghua Science and Technology 2021年第5期26卷 692-705页

作者： Zhipeng Song Zhichao Cao Zhenjiang Li Jiliang Wang Yunhao Liu the School of Software Tsinghua UniversityBeijing 100084China the Department of Computer Science and Engineering Michigan State UniversityMichiganMI 48824USA the Department of Computer Science City University of Hong KongHong Kong 999077China the Department of Automation and the Global Innovation eXchange Institute(GIX) Tsinghua UniversityBeijing 100084China

Motion tracking via Inertial Measurement Units(IMUs)on mobile and wearable devices has attracted significant interest in recent ***-accuracy IMU-tracking can be applied in various applications,such as indoor navigation,gesture recognition,text input,*** efforts have been devoted to improving IMU-based motion tracking in the last two decades,from early calibration techniques on ships or airplanes,to recent arm motion models used on wearable smart *** this paper,we present a comprehensive survey on IMU-tracking techniques on mobile and wearable *** also reveal the key challenges in IMU-based motion tracking on mobile and wearable devices and possible directions to address these challenges.

关键词： Inertial Measurement Units(IMUs) motion tracking accelerometer gyroscope magnetometer sensor fusion

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Practical and Efficient Model Extraction of Sentiment Analysis APIs

Practical and Efficient Model Extraction of Sentiment Analys...

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International Conference on software engineering (ICSE)

作者： Weibin Wu Jianping Zhang Victor Junqiu Wei Xixian Chen Zibin Zheng Irwin King Michael R. Lyu School of Software Engineering Sun Yat-sen University Department of Computer Science and Engineering The Chinese University of Hong Kong Department of Computing The Hong Kong Polytechnic University Tencent

Despite their stunning performance, developing deep learning models from scratch is a formidable task. Therefore, it popularizes Machine-Learning-as-a-Service (MLaaS), where general users can access the trained models of MLaaS providers via Application programming Interfaces (APIs) on a pay-per-query basis. Unfortunately, the success of MLaaS is under threat from model extraction attacks, where attackers intend to extract a local model of equivalent functionality to the target MLaaS model. However, existing studies on model extraction of text analytics APIs frequently assume adversaries have strong knowledge about the victim model, like its architecture and parameters, which hardly holds in practice. Besides, since the attacker's and the victim's training data can be considerably discrepant, it is non-trivial to perform efficient model extraction. In this paper, to advance the understanding of such attacks, we propose a framework, PEEP, for practical and efficient model extraction of sentiment analysis APIs with only query access. Specifically, PEEP features a learning-based scheme, which employs out-of-domain public corpora and a novel query strategy to construct proxy training data for model extraction. Besides, PEEP introduces a greedy search algorithm to settle an appropriate architecture for the extracted model. We conducted extensive experiments with two victim models across three datasets and two real-life commercial sentiment analysis APIs. Experimental results corroborate that PEEP can consistently outperform the state-of-the-art baselines in terms of effectiveness and efficiency.

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Improving Candle Direction Classification in Forex Market Using Support Vector Machine with Hyperparameters Tuning 7

Improving Candle Direction Classification in Forex Market Us...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Oetama, Raymond Sunardi Heryadi, Yaya Lukas Suparta, Wayan Computer Science Bina Nusantara University Jakarta Indonesia Binus Graduate Program Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Institut Teknologi Nasional Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350345711

Foreign Exchange market is the world's largest daily currency turnover. Two of the popular currencies Euro and Pound sterling traded against the US Dollar. Since the Russia and Ukraine war started in February 2022, their exchange rates decrease to the lowest rate ever. Even though the general trend is bearish, several daily candles increase for some days making challenges for forex analysts. To solve this problem, classification is applied. The data is labeled downward and upward. By utilizing Linear Kernel and Radial Basis Function (RBF) Kernel-based Support Vector Machines (SVM), the candle direction can be classified and optimized by tuning the Hyperparameters. The accuracy of candle direction classifications are highly improved. After tuning, in general, classification using Linear Models can outperform RBF Models. The best accuracy found on the Pound sterling against US Dollar by using the Linear model is 98.11% and the accuracy becomes 100% on data testing at a ratio of 70:30. Whilst for the Euro against the US Dollar, the best accuracy found the same for both Linear and RBF models on a ratio of 80:20 at 97.53%. However, on data testing, it decreases to 94.51% for Linear Model and 93.41% using RBF Model. The implication of this study is SVM can successfully classify candle direction on pairs in the Forex Market that are affected by a big event that comes for such a long period as long as the hyperparameter is tuned. © 2022 IEEE.

关键词： Support vector machines

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4D-MultispectralNet: Multispectral Stereoscopic Disparity Estimation using Human Masks

arXiv

引用

arXiv 2022年

作者： Duplessis-Guindon, Philippe Bilodeau, Guillaume-Alexandre LITIV Lab Department of Computer and Software Engineering Polytechnique Montreal Canada

Multispectral stereoscopy is an emerging field. A lot of work has been done in classical stereoscopy, but multispectral stereoscopy is not studied as frequently. This type of stereoscopy can be used in autonomous vehicles to complete the information given by RGB cameras. It helps to identify objects in the surroundings when the conditions are more difficult, such as in night scenes. This paper focuses on the RGB-LWIR spectrum. RGB-LWIR stereoscopy has the same challenges as classical stereoscopy, that is occlusions, textureless surfaces and repetitive patterns, plus specific ones related to the different modalities. Finding matches between two spectrums adds another layer of complexity. Color, texture and shapes are more likely to vary from a spectrum to another. To address this additional challenge, this paper focuses on estimating the disparity of people present in a scene. Given the fact that people's shape is captured in both RGB and LWIR, we propose a novel method that uses segmentation masks of the human in both spectrum and than concatenate them to the original images before the first layer of a Siamese Network. This method helps to improve the accuracy, particularly within the one pixel error range. Copyright © 2022, The Authors. All rights reserved.

关键词： Stereo image processing

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Modular Self-Lock Origami: design, modeling, and simulation to improve the performance of a rotational joint

arXiv

引用

arXiv 2023年

作者： Zare, Samira Spaeth, Alex Suresh, Sandya Teodorescu, Mircea Department of Electrical and Computer Engineering University of California Santa Cruz United States SIP program University of California Santa Cruz United States Department of Computer Science and Engineering United States

Origami structures have been widely explored in robotics due to their many potential advantages. Origami robots can be very compact, as well as cheap and efficient to produce. In particular, they can be constructed in a flat format using modern manufacturing techniques. Rotational motion is essential for robotics, and a variety of origami rotational joints have been proposed in the literature. However, few of these are even approximately flat-foldable. One potential enabler of flat origami rotational joints is the inclusion of lightweight pneumatic pouches which actuate the origami’s folds;however, pouch actuators only enable a relatively small amount of rotational displacement. The previously proposed Four-Vertex Origami is a flat-foldable structure which provides an angular multiplier for a pouch actuator, but suffers from a degenerate state. This paper presents a novel rigid origami, the Self-Lock Origami, which eliminates this degeneracy by slightly relaxing the assumption of flat-foldability. This joint is analysed in terms of a trade-off between the angular multiplier and the mechanical advantage. Furthermore, the Self-Lock Origami is a modular joint which can be connected to similar or different joints to produce complex movements for various applications;three different manipulator designs are introduced as a proof of concept. Copyright © 2023, The Authors. All rights reserved.

关键词： Manipulators

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A Customizable Lightweight STM for Irregular Algorithms on GPU

A Customizable Lightweight STM for Irregular Algorithms on G...

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Shayan Manoochehri Patrick Cristofaro Dhrubajyoti Goswami Department of Computer Science and Software Engineering Concordia University Montreal Canada

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

Irregular algorithms are often encountered in highly data-centric application domains. These algorithms operate on irregular data structures such as sparse graphs with irregular access patterns, which may also modify the underlying topology unpredictably. High computational time and inherent data parallelism present in these algorithms motivate the use of GPUs for speeding things up, however there are challenges for their efficient implementations due to: difficulty in protecting the shared data consistency in the presence of concurrent dynamic transactions; irregular access patterns due to unstructured data structures; and dynamic structural modifications of the underlying topology. One approach to overcome these challenges is to use software Transactional Memory (STM). However, overly complex design and implementations of contemporary STM-based approaches and lack of proper framework to employ them in conjunction with the irregular algorithms stalls their adoption by the programming community. To overcome some of these challenges, this research proposes a lightweight STM with a simple design (Lite GSTM), based on a lock stealing algorithm, and an associated extensible framework to hide the complexity of the STM from a programmer. The framework is extensible by allowing plug-ins of customized STMs designed for different needs of transactions. The use of the framework is elaborated with two use cases which employ completely different irregular algorithms, however, have some common features: the underlying data structure is a graph, and the graph is structurally modified (coarsened) unpredictably in the course of execution. The paper presents the performance comparisons of the STM-based implementations with respect to their sequential and non-STM based counterparts, which show promising results.

关键词： Distributed processing Heuristic algorithms software algorithms Graphics processing units programming Parallel processing Data structures

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HGDRec:Next POI Recommendation Based on Hypergraph Neural Network and Diffusion Model

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IEEE Transactions on Services Computing 2025年第3期18卷 1445-1458页

作者： Yinchen Pan Jun Zeng Ziwei Wang Haoran Tang Junhao Wen Min Gao School of Big Data and software engineering Chongqing University Chongqing China College of Computer Science and Technology Zhejiang University Hangzhou China Department of Computing The Hong Kong Polytechnic University Kowloon Hong Kong

In recent years, next Point-of-Interest (POI) recommendation is essential for many location-based services, aiming to predict the most likely POI a user will visit next. Current research employs graph-based and sequential methods, which have significantly improved performance. However, there are still limitations: numerous methods overlook the fact that user intent is constantly changing and complex. Furthermore, prior studies have seldom addressed spatiotemporal correlations while considering differences in user behavior patterns. Additionally, implicit feedback contains noise. To address these issues, we propose a recommender model named HGDRec for the next POI recommendation. Specifically, we introduce an approach for extracting trajectory intent by integrating multi-dimensional trajectory representations to achieve a multi-level understanding of user trajectories. Then, by analyzing users’ long trajectories, we construct global hypergraph structures across spatiotemporal regions to comprehensively capture user behavior patterns. Additionally, to further optimize trajectory intent representation, we employ a feature optimization method based on the improved diffusion model. Extensive experiments on three real-world datasets validate the superiority of HGDRec over the state-of-the-art methods.

关键词： Trajectory Diffusion models Spatiotemporal phenomena Feature extraction Optimization Transformers Data mining Noise measurement Data models Correlation

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An IoT-Based Air Pollution Monitoring System for Smart City 4

An IoT-Based Air Pollution Monitoring System for Smart City

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4th International Conference on computer Systems, ICCS 2024

作者： Aubakirov, Alibek Makhanov, Kanat Issainova, Aliya Glazyrina, Natalya Razkhova, Bibigul Satybaldina, Dina School of Computer Science Hangzhou Dianzi University Hangzhou China Electronics and Telecommunications L.N Gumilyov Eurasian National University Department of Radio Engineering Astana Kazakhstan L.N. Gumilyov Eurasian National University Information Security Department Astana Kazakhstan L.N Gumilyov Eurasian National University Computer and Software Engineering Department Astana Kazakhstan L.N. Gumilyov Eurasian National University Department of Artificial Astana Kazakhstan Information Security and Cryptology Research Institute L.N. Gumilyov Eurasian National University Astana Kazakhstan

ISBN: (纸本)9798350366341

In this paper, we present the results of research on the design and development of a gas analytical unit, an electronic nose, with an autonomous power supply, as well as the function of wireless data transmission via the Long-Range Wide Area Networks protocol. We built the device on a circuit board featuring eight gas sensors (MQ series), an STM32F103C8T6 microcontroller with 12-bit analog-to-digital conversion, a RAK3172 wireless data transmission module, voltage dividers, and a USB serial adapter. It also has an HDC2080DMBR temperature and humidity sensor. We evaluated the electronic nose performance towards standard mixtures of carbon dioxide, carbon monoxide, nitrogen dioxide, ammonia, and hydrogen sulfide, which are important analytes in outdoor and indoor air quality monitoring. Multidimensional linear regression methods were employed to build calibration curves for electronic nose sensors, which allowed for converting the measured sensor responses into quantitative values of the concentrations of the analyzed substances. The estimated coefficients of determination, R2, approach 1 indicating a strong correlation between the approximating model and the original data. The multivariate chemiresistive responses were successfully clustered using the k-means algorithm, revealing clear distinctions between sensor data associated with different gas concentrations. The k-NN classifier, applied to the clustered data, achieved 100% accuracy in identifying gas concentrations, underscoring the potential of the proposed methodology for gas sensing applications. We proposed and implemented the architecture of a network of mobile gas analyzers as the Internet of Things devices for environmental monitoring using the VK Cloud Platform. © 2024 IEEE.

关键词： Analog to digital conversion

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