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59th Annual Conference on Information sciences and systems, CISS 2025

作者： Liang, Zhirui Li, Qi Liu, Anqi Dvorkin, Yury Johns Hopkins University Department of Applied Mathematics and Statistics BaltimoreMD United States Johns Hopkins University Department of Computer Science BaltimoreMD United States Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD United States Johns Hopkins University Department of Civil and System Engineering BaltimoreMD United States

ISBN: (纸本)9798331513269

This paper presents an end-to-end framework for calibrating wind power forecast models to minimize operational costs in two-stage power markets, where the first stage involves a distributionally robust optimal power flow (DR-OPF) model. Unlike traditional methods that adjust forecast parameters and uncertainty quantification (UQ) separately, this framework jointly optimizes both the forecast model parameters and the decision conservativeness, which determines the size of the ambiguity set in the DR-OPF model. The framework aligns UQ with actual uncertainty realizations by directly optimizing downstream operational costs, a process referred to as cost-oriented calibration. The calibration is achieved using a gradient descent approach. To enable efficient differentiation, the DR-OPF problem is reformulated into a convex form, and the Envelope Theorem is leveraged to simplify gradient derivation in the two-stage setting. Additionally, the framework supports distributed implementation, effectively reducing computational overhead and enhancing efficiency. By proactively calibrating forecast parameters and prescribing optimal decision conservativeness, the framework significantly enhances cost efficiency and reliability in power system operations. Numerical experiments on an IEEE 5-bus system demonstrate the effectiveness and efficiency of the proposed approach. © 2025 IEEE.

关键词： Wind forecasting

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Implementation Public Address system Design Based on Audio Over Ethernet (AoE)

Implementation Public Address System Design Based on Audio O...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Supriyono, Ignatius Agus Sediyono, Eko Setyawan, Iwan Managas, Dendy Jonas Prasetya Kristiadi, Dedy Santoso, Nesti Anggraini Nurhaeni, Tuti University of Raharja Computer System Tangerang Indonesia Satya Wacana Christian University Computer Science Salatiga Indonesia Satya Wacana Christian University Electrical Engineering Salatiga Indonesia University of Raharja Computer Science Tangerang Indonesia University of Raharja Information System Tangerang Indonesia

ISBN: (纸本)9781665468763

Disaster management that occurs in high-rise buildings is an urgent need to avoid injury and loss of life. Pelita Harapan International School is an international school that has several building units with hundreds of students. The student evacuation information system in the face of disasters uses a Public Address system such as public announcements, fire alarms, earthquake alarms or other emergency alarms. However, there are constraints such as limited coverage between the PA system and analog amplifiers in the building connected to the central office resulting in signal loss, increased audio sources, and accuracy of zone selection. The purpose of this study is to create a device that can communicate with other IP-based PA system devices such as PA system Network Controllers as servers, remote microphones, or other devices that use IP addresses using the on going system analysis method. The solution presented is the use of an Internet Protocol (IP) network-based PA system amplifier using Audio over Ethernet (AoE) technology, where remote microphones in different buildings have the same function to convey emergency and alarm information to all zones selected to be Novelty. This research. Furthermore, the IP address segment is divided into subnets to represent different buildings. The result of this research is the implementation that has been carried out in the Pelita Harapan International School building with satisfactory results. © 2022 IEEE.

关键词： Ethernet

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Comparative Analysis Of Deep Learning Architectures For The Classification Of Eye-Related Diseases 12

Comparative Analysis Of Deep Learning Architectures For The ...

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12th International Conference on Orange Technology, ICOT 2024

作者： Sultan, Muhammad Ali Kaburuan, Emil R. Rasool, Fezan Suwito, Misni Harjo Informatics Engineering Department Mercu Buana University Jakarta Barat Indonesia Computer Science Department Lahore University of Management Sciences Lahore Pakistan Information System Department Mercu Buana University Jakarta Barat Indonesia

ISBN: (纸本)9798331523602

Eye-related disorders are among the driving causes of vision impedances worldwide. Accurate classification of retinal conditions is crucial for adequate treatment and management. This research explores the potential of three advanced deep-learning models, namely—-VGG16, DenseNet, and Swin Transformers, to classify four eye-related disorders utilizing the Optical Coherence Tomography Image Retinal Database (OCTID) taken from ICPSR. The OCTID dataset contains retinal OCT images representing four distinct pathological conditions: age-related macular degeneration, diabetic retinopathy, central serous retinopathy, macular holes, and normal retinas. Evaluation is done based on metrics such as accuracy, precision, recall, and F1 score. The comparison of these models, paired with interpretability techniques such as GRADCAM and Integrated Gradients, reveals that VGG16 achieves the highest F1-score, demonstrating robust classification performance. At the same time, Swin Transformers develops competitive accuracy with practical interpretability through Integrated Gradients. DenseNet showed slightly lower metrics but performed adequately on the GRADCAM outputs. This study underscores the critical role of advanced deep learning frames, which work to enhance diagnostic accuracy for retinal disorders and provide a foundation for future developments in ophthalmic disease classification. © 2024 IEEE.

关键词： Optical coherence tomography

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An Improved Imitation Learning Algorithm Based on Markov Chain

An Improved Imitation Learning Algorithm Based on Markov Cha...

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2024 IEEE International Conference on Control science and systems engineering, ICCSSE 2024

作者： Yu, Jiyang Huang, Dan He, Xiaobao Han, Yong Wang, Jianyu Sun, Kaiwen Beijing Institute of Spacecraft System Engineering China Academy of Space Technology Beijing China China Research and Development Academy of Machinery Equipment Chongqing University of Technology Beijing Chongqing China College of Computer Science and Engineering Chongqing University of Technology Chongqing China

ISBN: (纸本)9798331517199

An improved imitation learning algorithm based on Markov chain is proposed, aiming to enhance the performance of autonomous driving in complex environments. Imitation learning learns task execution by observing expert behavior, while Markov chains are used to model state transition processes. The existing imitation learning algorithms have limited ability to handle complex tasks, especially in natural environments. The algorithm proposed in this article improves learning efficiency and autonomous control performance by introducing strategy iteration and reward function design for sudden obstacles. The core idea is to introduce Markov decision processes into traditional imitation learning frameworks to improve learning efficiency and performance. By acquiring a refined strategy, the objective is to mimic the agent's actions within the environment to closely resemble those of the expert. To achieve this, first train an initial strategy using expert examples. Then, use this strategy to generate new examples and update the strategy using these examples. This process iterates continuously until the strategy converges. The experimental results show that on the lunar environment autonomous driving datasets, the accuracy of our algorithm reaches 95% with a mean square error of 0.02, while the accuracy of the comparative algorithm is the highest at 90% with a mean square error of 0.05. This indicates that the improved algorithm can more accurately learn and imitate the driving behavior of experts. In addition, the performance of the algorithm is stable at different iteration times, indicating good convergence. © 2024 IEEE.

关键词： Contrastive Learning

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Optimized Design of a Haptic Unit for Vibrotactile Amplitude Modulation

Optimized Design of a Haptic Unit for Vibrotactile Amplitude...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Huang, Jingchen Fang, Yun Guo, Weichao Qiao, Zhijian Sheng, Xinjun School of Mechanical Engineering Meta Robotics Institute Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration Shanghai200240 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong

ISBN: (纸本)9781665481090

Communicating information to users is a crucial aspect of human-machine interaction. Vibrotactile feedback encodes information into spatiotemporal vibrations, enabling users to perceive tactile sensations. It offers advantages such as lightweight, wearability, and high stability, with broad applications in sensory substitution, virtual reality, education, and healthcare. However, existing haptic unit designs lack amplitude modulation capabilities, which limits their applications. This paper proposed an optimized design of the haptic unit from the perspective of vibration amplitude modulation. A modified elastic model was developed to describe the propagation and attenuation mechanisms of vibration in the skin. Based on the model, two types of hierarchical architectural design were proposed. The design incorporated various materials arranged in multiple layers to amplify or attenuate the vibration amplitude as it traveled through the structure. An experimental platform was built to evaluate the performance of the optimized design. © 2024 IEEE.

关键词： Virtual reality

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Covertvasion: Depicting threats through covert channels based novel evasive attacks in android

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International Journal of Intelligent Networks 2023年第1期4卷 337-348页

作者： Gautam, Sunil Pattani, Ketaki Zuhair, Mohd Rashid, Mamoon Ahmad, Nazir Department of Computer Science and Engineering Institute of Technology Nirma University Ahmedabad Gujarat India Department of Computer Sciences and Engineering Institute of Advanced Research Gujarat Gandhinagar India School of Information Communication and Technology Bahrain Polytechnic Isa Town Bahrain Department of Information System College of Applied Sciences King Khalid University P.O. Box 61913 Muhayel63317 Saudi Arabia

Privacy and security issues concerning mobile devices have substantial consequences for individuals, groups, governments, and businesses. The Android operating system bolsters smartphone data protection by imposing restrictions on app behavior. Nevertheless, attackers conduct systematic resource analyses and divert privacy-sensitive information from plain view. They employ evasive mechanisms to evade system monitoring and create an illusion of benign and non-sensitive communication. Furthermore, covert channels amplify the impact of these malicious activities by facilitating information transfer through non-standard methods. The purpose of this research is to shed light on these novel threats targeting Android systems. The study delves into security and privacy attacks that compromise sensitive user information. The methodology leverages evasion concepts and employs sound-specific covert channel communication, particularly ultrasonic channels. This research work introduces novel evasive attacks, namely Prime-Composite Evasive Information Invasion (PCEII) and File-lock-based Evasive Information Invasion (FEII), both relying on covert channel communication. These unique variants of attacks successfully evade user data within a few milliseconds for both noisy as well as non-noisy environments and do not show any signs of detection by antivirus mechanisms like Anti-Virus Guard (AVG), 360 security, etc. and state-of-the-art tools such as TaintDroid, MockDroid and others. The paper not only assesses their impact on the privacy and security of information but also introduces avenues for their detection and mitigation. © 2023 The Authors

关键词： Android (operating system)

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High-Voltage SF6 Circuit Breaker Maintenance 33rd

High-Voltage SF6 Circuit Breaker Maintenance

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33rd International Conference on Organization and Technology of Maintenance, OTO 2024

作者： Soldo, Luka Knežević, Goran Zovko, Mario Croatian Transmission System Operator Transmission Area Osijek Vukovarska Cesta 217 Osijek31000 Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Kneza Trpmira 2b Osijek31000 Croatia

ISBN: (纸本)9783031805967

Nowadays, the need for uninterrupted power supply is greater than ever. One of the most effective ways to ensure an uninterrupted supply of electricity is the correct selection of the method and interval of maintenance of elements in a high-voltage substation. In this way, not only is a high-quality delivery of electricity ensured, but also the possibility of equipment failure that can be dangerous for people in the substation is reduced. A high-voltage circuit breaker is a device that performs several different functions. It is used for network configuration changes, and also provides protection for equipment and personnel. High voltages and thermal (current) stresses cause aging and wear of switch parts, and through various forms of maintenance and testing, damage parts are determined and potential hazards are safely removed. This paper explains the maintenance procedures of the high-voltage SF6 circuit breaker. Using the example of a high-voltage line-bay circuit breaker, the entire 6Y circuit breaker revision procedure (revision that is carried out in six-year cycles) is presented. In addition to visual inspection, checking, cleaning and replacement of worn parts, the switch on and off times were recorded. The quality of SF6 gas was also tested by measuring the concentration of SF6 gas decomposition products and the concentration of mineral oil aerosols in SF6 gas, by measuring the dew point of the gas and controlling the volume percentage of SF6 gas. The voltage drops at the primary connections of the switches were measured, and the operation of the pressure relays was also checked. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Mineral oils

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Evaluation of Meteorological Factors’ Effect on Daily Heart Rate Variability Over Five Years 12

Evaluation of Meteorological Factors’ Effect on Daily Heart...

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12th International Conference on Awareness science and Technology, iCAST 2023

作者： Kokubun, Kota Li, Tianhui Chen, Wenxi Dept. of Computer and Information Systems The University of Aizu Aizu-Wakamatsu Japan Division of Information System The University of Aizu Aizu-Wakamatsu Japan Dept. of Computer Science and Engineering The University of Aizu Aizu-Wakamatsu Japan

ISBN: (纸本)9798350324693

The aim of this study is to investigate the effect of meteorological factors on heart rate variability (HRV) derived from daily electrocardiogram (ECG) data. Daily meteorological data were obtained from the Japan Meteorological Agency’s database. Daily ECG data were measured while bathing for five y ears. T he s ubject w as a h ealthy m ale i n h is fi fties. After collecting ECG data, R-R intervals were calculated to perform HRV analysis in time domain and frequency domain. The evaluation of link between meteorological factors and HRV parameters was realized by utilizing meteorological factors’ importance calculated by Random Forest, and Steel-Dwass significant difference analysis of the values. Additionally, the evaluation was also performed by analyzing the obtained meteorological factors’ importance values using Granger Causality test. In Steel-Dwass test, several significant d ifferences (p © 2023 IEEE.

关键词： Electrocardiograms

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Community Opinion Maximization in Social Networks

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IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： Liu, Yilu Zhang, Qingfu Wang, Zhenkun Department of Computer Science City University of Hong Kong Hong Kong China School of System Design and Intelligent Manufacturing and the Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

Maximizing the influence of opinions is an emerging research topic in social networks. Although the community is a key structure of social networks, little effort has been made to investigate how to maximize the influence of opinions on all communities. This paper proposes a systematic approach to address this issue. First, we construct a multi-faceted opinion evolution (MFOE) model with three critical influence factors, namely, individuals, neighbors, and communities, to describe the opinion evolution process in social networks. The convergence analysis confirms its ability to reveal the influence of opinions. Then, we define the overall community opinion to measure the influence of opinions on all communities and employ it as the objective function to formulate an optimization problem called community opinion maximization (COM). We show that the COM problem is NP-hard. To optimize this problem, a memetic algorithm with three problem-specific schemes is developed and termed MACOM. Extensive experimental studies on real-world social networks demonstrate the plausibility of the MFOE model and the effectiveness of MACOM. IEEE

关键词： Optimization

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Human Activity Recognition in Free Living Using a Wearable Sensor: A Two-Stage Approach 12

Human Activity Recognition in Free Living Using a Wearable S...

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12th International Conference on Awareness science and Technology, iCAST 2023

作者： Li, Tianhui Zhou, Xue Kokubun, Kota Chen, Wenxi Division of Information System The University of Aizu Aizu-Wakamatsu Japan Dept. of Computer and Information Systems The University of Aizu Aizu-Wakamatsu Japan Dept. of Computer Science and Engineering The University of Aizu Aizu-Wakamatsu Japan

ISBN: (纸本)9798350324693

A novel two-stage approach for human activity recognition (HAR) using a wearable sensor is proposed in this study. The goal is to achieve both coarse-level and fine-level recognition of activities. The study focuses on five common activities: desk-working, driving, walking, downstairs, and upstairs. Three-axis acceleration signals were collected using a wrist-worn accelerometer sensor, and the activities were annotated during the participant’s daily routines. The acceleration data were preprocessed through segmentation, feature extraction, and normalization. In the first s tage, a t raditional m achine learning model (decision tree) was used for coarse-level classification, distinguishing between activities with exercise and without exercise. In the second stage, deep learning models were employed for fine-level classification to recognize specific activities within the coarse classes. The performance of the models was evaluated using accuracy, sensitivity, and specificity. T he p roposed approach showed promising results with accuracies of 93.53%, 93.52%, 85.70%, 98.11%, and 85.91% respectively for desk-working, driving, walking, downstairs, and upstairs, demonstrating the effectiveness of the two-stage strategy for HAR. The proposed two-stage approach outperforms the one-stage method (decision tree classifier a nd d eep l earning m odel), p articularly i n imbalanced data, achieving a graceful equilibrium between sensitivity and specificity. T he s tudy h ighlights t he i mportance o f considering the complexity and variability of daily activities for accurate classification a nd r esource optimization. © 2023 IEEE.

关键词： Wearable sensors

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