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10th International Conference on Condition Monitoring and Diagnosis, CMD 2024

作者： Suwanasri, Thanapong Panmala, Nattapon Suwanasri, Cattareeya Thanasettagone, Thanachat Lacharochana, Sakda The Sirindhorn International Thai-German Graduate School of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Technical Education Department of Teacher Training in Electrical Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand Unipower Engineering Co. Ltd. Bangkok Thailand Global Power Synergy Public Company Limited Bangkok Thailand

ISBN: (纸本)9788986510225

in a 115 kV switchyard substation, there are several major equipment that are gradually deteriorated due to ageing and degradation. Those equipment are one of the important element in a power generating utility to supply the reliable electricity to diverse customers. Therefore, their failures would cause catastrophic consequences and lead to long outage time. Thus, the need for condition and performance assessments of those switchyard equipment for life extension purposes is obligatory to ensure system reliability, to meet customer requirements and to optimize the investment cost. To access the condition of such high voltage equipment, protective relays, building structure and equipment foundations, their technical specification as well as visual inspection and preventive maintenance results of individual equipment must be systematically analyzed to determine the possibility for life extension according to manufacturer guideline as well as international standards and recommendations for condition aging assessment representing in term of conditional aging index. While the other aspects as age, rating adequacy, technology obsolescence, satisfaction in operation, failure rate and defect severity are required to determine the need for renovation/replacement known as replacement index. Then, the proposed methodology has been employed to assess the condition and performance of each equipment such as every major high voltage equipment, control building, protective relays in a switchyard of power station with satisfactory result. © 2024 The Korean Institute of electrical Engineers (KIEE).

关键词： Obsolescence

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Classifying Bicycle Infrastructure Using On-Bike Street-Level Images

arXiv

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arXiv 2024年

作者： Backman, Kal Beck, Ben Kulić, Dana Department of Electrical and Computer Systems Engineering School of Public Health and Preventive Medicine Monash University Australia

While cycling offers an attractive option for sustainable transportation, many potential cyclists are discouraged from taking up cycling due to the lack of suitable and safe infrastructure. Efficiently mapping cycling infrastructure across entire cities is necessary to advance our understanding of how to provide connected networks of high-quality infrastructure. Therefore we propose a system capable of classifying available cycling infrastructure from on-bike smartphone camera data. The system receives an image sequence as input, temporally analyzing the sequence to account for sparsity of signage. The model outputs cycling infrastructure class labels defined by a hierarchical classification system. Data is collected via participant cyclists covering 7,006Km across the Greater Melbourne region that is automatically labeled via a GPS and OpenStreetMap database matching algorithm. The proposed model achieved an accuracy of 95.38%, an increase in performance of 7.55% compared to the non-temporal model. The model demonstrated robustness to extreme absence of image features where the model lost only 6.6% in accuracy after 90% of images being replaced with blank images. This work is the first to classify cycling infrastructure using only street-level imagery collected from bike-mounted mobile phone cameras, while demonstrating robustness to feature sparsity via long temporal sequence analysis. © 2024, CC BY.

关键词： Bicycles

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A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models (May, 10.1093/jamia/ocac065, 2022)

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2022年第9期29卷 1656-1656页

作者： Wang, H. Echo Landers, Matthew Adams, Roy Subbaswamy, Adarsh Kharrazi, Hadi Gaskin, Darrell J. Saria, Suchi Department of Health Policy and Management Johns Hopkins Bloomberg School of Public Health Baltimore Maryland USA Department of Computer Science University of Virginia Charlottesville Virginia USA Department of Psychiatry and Behavioral Sciences Johns Hopkins School of Medicine Baltimore Maryland USA Department of Computer Science and Statistics Whiting School of Engineering Johns Hopkins University Baltimore Maryland USA

Objective Health care providers increasingly rely upon predictive algorithms when making important treatment decisions, however, evidence indicates that these tools can lead to inequitable outcomes across racial and socio-economic groups. In this study, we introduce a bias evaluation checklist that allows model developers and health care providers a means to systematically appraise a model’s potential to introduce bias. Materials and Methods Our methods include developing a bias evaluation checklist, a scoping literature review to identify 30-day hospital readmission prediction models, and assessing the selected models using the checklist. Results We selected 4 models for evaluation: LACE, HOSPITAL, Johns Hopkins ACG, and HATRIX. Our assessment identified critical ways in which these algorithms can perpetuate health care inequalities. We found that LACE and HOSPITAL have the greatest potential for introducing bias, Johns Hopkins ACG has the most areas of uncertainty, and HATRIX has the fewest causes for concern. Discussion Our approach gives model developers and health care providers a practical and systematic method for evaluating bias in predictive models. Traditional bias identification methods do not elucidate sources of bias and are thus insufficient for mitigation efforts. With our checklist, bias can be addressed and eliminated before a model is fully developed or deployed. Conclusion The potential for algorithms to perpetuate biased outcomes is not isolated to readmission prediction models; rather, we believe our results have implications for predictive models across health care. We offer a systematic method for evaluating potential bias with sufficient flexibility to be utilized across models and applications.

关键词： predictive model hospital readmission bias health care disparity clinical decision-making

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Compressed VGGNet for Automatic COVID-19 Disease Detection from CT Scan Images 8th

Compressed VGGNet for Automatic COVID-19 Disease Detection f...

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8th IFIP TC 12 International Conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Vinothini, R. Niranjana, G. Dhamanti, Inge Lailiyah, Syifa’ul Yakub, Fitri Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur 603203 India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur 603203 India Department of Health Policy and Administration Faculty of Public Health Universitas Airlangga Surabaya Indonesia Faculty of Health Medicine and Life Sciences Universitas Airlangga East Java Indonesia Electronic System Engineering Department Malaysia-Japan International Institute of Technology Kuala Lumpur Malaysia

ISBN: (纸本)9783031736162

Millions of people across the globe were affected by this rapidly spreading disease by the year 2020. Contamination of the respiratory system results from contracting COVID-19. Nonetheless, establishing a conclusive diagnosis of COVID-19 may prove difficult due to the subtle differences it shares with conventional pneumonia and the complexities involved in identifying areas of infection. A growing number of approaches based on deep learning (DL) are being proposed for the automated detection of COVID-19 from CT scan images. By employing the data pretreatment methodology, unprocessed image data becomes prepared for further analysis. The proposed framework utilised transfer learning to construct VGGNet, which is capable of discerning the Covid-19 disease. The model was subsequently assessed in comparison to the most sophisticated models, VGG16 and VGG19, using the SARS-COV2 CT scan dataset. This dataset contains 1230 CT scans of non-infected images and 1252 CT scans of Covid-19-infected images. The model has achieved 99% accuracy, 98% precision, 97% recall, and 98% F1-score, among other performance metrics. © IFIP International Federation for Information Processing 2025.

关键词： COVID-19

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The Use of Eye Tracking as a Measure of Situation Awareness in Power System Control Rooms

The Use of Eye Tracking as a Measure of Situation Awareness ...

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2022 IEEE Texas Power and Energy Conference, TPEC 2022

作者： Gooris, Michael Peres, S. Camille Hernandez, Omar Fru, Felix Azenwi Idehen, Ikponmwosa Mao, Zeyu Jang, Wonyeok Overbye, Thomas School of Public Health Texas Am University United States Texas Am University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9781665479028

Power systems control rooms are fast-paced, dynamic environments that require operators to maintain awareness of numerous pieces of information. A construct that has been previously used to examine operator ability to process and retain information is situation awareness. It is the process by which information is perceived, comprehended, and then used to project events that may likely occur. It is often measured using observational or self-report methods. In recent times, however, researchers have started using physiological measures such as eye tracking to measure situation awareness. In this paper, we report a pilot study exploring the use of eye tracking metrics to evaluate situation awareness in the operation of a test power system within the confines of a typical control room. Eye tracking results are compared to the results of a Cognitive Task Analysis (CTA), with elaboration of their implications. © 2022 IEEE.

关键词： Eye tracking

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Eye Tracking Assisted Human Factor Analysis Platform for Power System Situational Awareness

Eye Tracking Assisted Human Factor Analysis Platform for Pow...

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2022 IEEE Power and Energy Conference at Illinois, PECI 2022

作者： Mao, Zeyu Idehen, Ikponmwosa Jang, Wonhyeok Shetye, Komal Davis, Katherine Overbye, Thomas Gooris, Michael Peres, S. Camille Texas A and M University Department of Electrical and Computer Engineering United States Texas A and M University School of Public Health United States

ISBN: (纸本)9781665402293

Data presentation techniques in power grid operations are important in determining situation awareness for control room engineers and operators. While innovative displays can be designed to convey static, dynamic, and other relevant attributes of grid information, an arising concern is their effectiveness in enabling control room operations. This paper presents an integrated architectural platform for performing human factors experimenting and analysis for power systems situation awareness. It leverages eye-tracking and other biosensing devices in simulated power system operations to capture critical human behavior data that can be further analyzed to extract qualitative and quantitative metrics in defining grid situation awareness. The architecture is designed to enable the assessment of presentation techniques and behavior of users (otherwise, known as respondents) either in real-time simulated grid operations, or offline when conveying the current state of the grid through static displays. © 2022 IEEE.

关键词： Eye tracking

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Disturbance Observer-Enhanced Adaptive CBFs for Safety-Critical Motion Control of Autonomous Vehicles 27

Disturbance Observer-Enhanced Adaptive CBFs for Safety-Criti...

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Cheng, Yifan Zhang, Yuxiang Jiang, Yuyao Chu, Hongqing Gao, Bingzhao Chen, Hong College of Electronic and Information Engineering Tongji University Shanghai201804 China National University of Singapore Department of Electrical and Computer Engineering Singapore117583 Singapore School of Customs and Public Administration Shanghai Customs College Shanghai201204 China School of Automotive Studies Tongji University Shanghai201804 China

ISBN: (纸本)9798331505929

The standalone adaptability in the penalty parameters of adaptive control barrier functions (ACBFs), may be insufficient to meet the high requirements for safety and robustness of autonomous vehicles (AVs) motion control, especially under system disturbances. This paper integrates the disturbance observer theory into the ACBFs, in order to improve the robustness and adaptability of the corresponding optimization framework. The enhanced performance is mainly realized in the following aspects: firstly, an auxiliary system for safety-critical control design is defined, and the constraints, related to the penalty parameters, are introduced. Secondly, the disturbance observers are introduced to estimate the unknown parts of high-order safety and stability constraints. Thirdly, the estimated error bounds are introduced into the original framework of ACBF-CLF-QPs to guarantee robustness and adaptive safety. The superior performance compared to the original ACBFs is verified in the AVs motion control under the classical scenario, and the simulation results indicate that, the proposed method has stronger robustness and adaptability to system disturbances while meeting the safety constraints. © 2024 IEEE.

关键词： Autonomous vehicles

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Investigating Ultra-Short-Term Heart Rate Variability as an Indicator of Craving in Recently Treated Patients with Opioid Use Disorder 46

Investigating Ultra-Short-Term Heart Rate Variability as an ...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Abbaraju, Vikram Bashar, Syed Khairul Nawar, Afra Rahman, Farhan N. Choi, Jaiyoun Lambert, Tamara P. Gazi, Asim H. Harrison, Anna B. Robinson, Madeline R. Mesfin, Hewitt Gray, Trinity A. Mermin-Bunnell, Kellen Jacquement, Nora Tomic, Nikolina Welsh, Justine W. Patel, Santosh Vaccarino, Viola Shah, Amit J. Douglas Bremner, J. Inan, Omer T. Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA United States Emory University School of Medicine Department of Psychiatry and Behavioral Sciences AtlantaGA United States Georgia Institute of Technology The Wallace H. Coulter Department of Biomedical Engineering AtlantaGA United States Emory University Department of Epidemiology Rollins School of Public Health AtlantaGA United States

ISBN: (纸本)9798350371499

Induced craving frequently leads to relapse in patients with a history of opioid use disorder (OUD). Quantifying the physiological manifestations of craving can enable caregivers of patients with OUD to continuously monitor craving and thus help inform treatment plans. Heart rate variability (HRV) is a promising candidate to capture the trends in such manifestations due to the ease of measuring changes in heartbeat intervals using the electrocardiogram. However, the relationship between craving and HRV measured over periods shorter than 5 minutes, i.e., ultra-short-term HRV, has not yet been investigated in detail. In this work, we present the first analysis on the relationship between 12 HRV features computed over ~2-minute periods and subjective craving reported on the visual analog scale (VAS-craving). Patients with OUD stable on medication (N = 12) went through an approximately 2-hour protocol involving audio/visual opioid cues to induce craving, alongside active transcutaneous vagus nerve stimulation or sham stimulation. Regardless of stimulation type, changes in VAS-craving scores over the course of the protocol were negatively correlated with changes in two ultra-short-term HRV features: the number of adjacent normal heartbeat intervals differing by more than 50 milliseconds (r = -0.63, p = 0.03) and the total power across all frequency bands (r = -0.69, p = 0.03).Clinical relevance - This preliminary study suggests that certain ultra-short-term HRV features can potentially serve as indicators of craving in patients with a history of OUD. Using such metrics computed over small data intervals can enable efficient clinical decision making and may help prevent opioid relapse. © 2024 IEEE.

关键词： Heart

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Smart Happy Device with IoT : For those who suffer anxiety, stress, and depression 12

Smart Happy Device with IoT : For those who suffer anxiety, ...

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12th IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2024

作者： Yakub, Fitri Azizan, Azizul Dhamanti, Inge Khudzari, Ahmad Zahran Md. Govindan, Niranjana Muljono, Muljono UTM Malaysia-Japan International Institute of Technology Electronic System Engineering Department Kuala Lumpur Malaysia Universiti Teknologi Malaysia Cyberphysical Research Group Embedded AI & ML Science Lab Faculty of Artificial Intelligence Kuala Lumpur Malaysia Universitas Airlangga Faculty of Public Health Department of Health Policy and Administration Surabaya Indonesia UTM Faculty of Engineering Department of Biosciences & Medical Engineering Johor Bahru Malaysia SRMIST Faculty of Engineering & Technology Department of Computing Technologies Chennai India Universitas Dian Nuswantoro Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9798350340204

Due to the rising cases of Covid-19 in the world especially in Malaysia, the impact had been hit hard for many people. Due to this all people must be isolated in their home. It has affected the well-being and working life of millions of people across the world. Due to this disease, the mental health among people has increased significantly for the past 2 years. According to MoH, out of 983 Malaysian students, about 20.4%, 6.6%, and 2.8% are experienced minimal to moderate, marked to severe, and most extreme levels of anxiety, respectively. The main stressors are the remote online teaching, and uncertainty about the future regarding study and career which can affect mental health. Thus, the main objective of this project is to develop a product that may provide different medication methods to its users by helping people who suffer anxiety, stress, and depression. We used aromatherapy, positive quotes, and music therapy in order to release stress. The user can also check his or her pulse rate by only touching the fingerprint through the sensor. The microcontrollers used in this project are Arduino Uno and Arduino Mega to build the project circuit. The experimental results can improve body health, mind and spirit which enhances both physical and emotional health. © 2024 IEEE.

关键词： COVID-19

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Joint Planning of Charging Stations and Power Systems for Heavy-Duty Drayage Trucks

arXiv

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arXiv 2024年

作者： Ye, Zuzhao Yu, Nanpeng Wei, Ran Department of Electrical and Computer Engineering University of California Riverside RiversideCA United States School of Public Policy University of California Riverside RiversideCA United States

As global concerns about climate change intensify, the transition towards zero-emission freight is becoming increasingly vital. Drayage is an important segment of the freight system, typically involving the transport of goods from seaports or intermodal terminals to nearby warehouses. This sector significantly contributes to not only greenhouse gas emissions, but also pollution in densely populated areas. This study presents a holistic optimization model designed for an efficient transition to zero-emission drayage, offering cost-effective strategies for the coordinated investment planning for power systems, charging infrastructure, and electric drayage trucks. The model is validated in the Greater Los Angeles area, where regulatory goals are among the most ambitious. Furthermore, the model’s design allows for easy adaptation to other regions. By focusing on drayage trucks, this study also paves the way for future research into other freight categories, establishing a foundation for a more extensive exploration in this field. Copyright © 2024, The Authors. All rights reserved.

关键词： Investments

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