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11th International Conference on electrical and Electronics engineering, ICEEE 2024

作者： Khan, Esrat Ba'ba, Leen Alshatri, Ruqaia Parvez, Saba Gad, Abdalla Jama, Mohamed College of Engineering Abu Dhabi University Electrical Computer and Biomedical Engineering Department Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350362541

The United Arab Emirates has a large and sophisticated street lighting infrastructure;therefore, the photometric performance of the street lighting systems must be prioritized. Locating the malfunctions in a large street lighting infrastructure can be time-consuming and arduous. In this paper, a low-cost street lighting performance monitoring system is designed, implemented, and tested. The proposed system comprises three main components: an illuminance sensor, a spectrometer, and a GNSS receiver. These components build a light and robust system to mount on vehicles' rooftops. Additionally, a comprehensive data analysis and inference engine is developed to determine the photometric performance of the lighting poles by identifying the number and the position of the defective luminaires, under-performing luminaires, poles obstructed by vegetation, and lighting poles that suffer from a complete power outage due to electrical faults in lighting control cabinets. Lastly, the field survey results are demonstrated in reports and interactive online visualization using Google Maps, in which the obtained information can be converted into performance metrics and indexes overlayed on urban maps. © 2024 IEEE.

关键词： Poles

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Board 262: Enhancing Deep Knowledge Tracing via Diffusion Models for Personalized Adaptive Learning

Board 262: Enhancing Deep Knowledge Tracing via Diffusion Mo...

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2024 ASEE Annual Conference and Exposition

作者： Dong, Xishuang Fu, Yujian Kuo, Ming-Mu Sarker, Shouvon Qian, Lijun Li, Xiangfang Electrical and Computer Engineering Department Roy G. Perry College of Engineering Prairie View A&M University United States Electrical Engineering and Computer Science Department Alabama A&M University United States

In contrast to pedagogies like evidence-based teaching, personalized adaptive learning (PAL) distinguishes itself by closely monitoring the progress of individual students and tailoring the learning path to their unique knowledge and requirements. A crucial technique for effective PAL implementation is knowledge tracing, which models students' evolving knowledge to predict their future performance. Based on these predictions, personalized recommendations for resources and learning paths can be made to meet individual needs. Recent advancements in deep learning have successfully enhanced knowledge tracking through Deep Knowledge Tracing (DKT). This paper introduces generative AI models to further enhance DKT. Generative AI models, rooted in deep learning, are trained to generate synthetic data, addressing data scarcity challenges in various applications across fields such as natural language processing (NLP) and computer vision (CV). This study aims to tackle data shortage issues in student learning records to enhance DKT performance for PAL. Specifically, it employs TabDDPM, a diffusion model, to generate synthetic educational records to augment training data for enhancing DKT. The proposed method's effectiveness is validated through extensive experiments on ASSISTments datasets. The experimental results demonstrate that the AI-generated data by TabDDPM significantly improves DKT performance, particularly in scenarios with small data for training and large data for testing. © American Society for engineering Education, 2024.

关键词： Contrastive Learning

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XDGesture: An xLSTM-based Diffusion Model for Co-speech Gesture Generation

XDGesture: An xLSTM-based Diffusion Model for Co-speech Gest...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zhang, Zixing Li, Jiajun Wang, Bin Liu, Yiming Zhao, Huan Schuller, Björn W. College of Computer Science and Electronic Engineering Hunan University China GLAM Department of Computing Imperial College London United Kingdom

ISBN: (纸本)9798350368741

In multimodal human-computer interaction, generating co-speech gestures is crucial for enhancing interaction naturalness and user experience. However, achieving synchronized and natural gesture sequences remains a significant challenge due to the complexity of modeling temporal dependencies across different modalities. Existing methods often rely on simple concatenation techniques, which are limited in effectively handling multimodal information. To address this issue, we propose XDGesture, a diffusion-based framework that integrates a Cross-Modal Fusion module and xLSTM. The Cross-Modal Fusion module efficiently merges information from different modalities, providing the model with rich contextual conditions. Meanwhile, xLSTM, with its enhanced memory structure and exponential gating mechanism, processes the fused multimodal data, capturing long-range dependencies between speech and gestures. This enables the generation of high-quality gesture sequences that are naturally synchronized with speech. Experimental results demonstrate that XDGesture remarkably outperforms existing baselines on multiple datasets, particularly in terms of gesture quality, naturalness, and synchronization with speech. © 2025 IEEE.

关键词： Co-speech gesture generation Diffusion model Multimodal feature fusion xLSTM

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Non-invasive Determination of Anemia Condition Using Photoplethysmography and Linear Regression 23

Non-invasive Determination of Anemia Condition Using Photopl...

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13th International Conference on Biomedical engineering and Technology, ICBET 2023

作者： Coscolluela, Kristine Y. Jawod, Danielle Nicole O. Villaverde, Jocelyn Flores Juanatas, Roben A. School of Electrical Electronics and Computer Engineering Mapua University Philippines College of Computing in Information Technologies National University Philippines

ISBN: (纸本)9798400707438

Anemia is a disease wherein the number of red blood cells that transport hemoglobin throughout the body drops significantly. Untreated, anemia can cause various medical complications. As such, the proponents have devised a non-invasive anemia diagnosis system that accepts photoplethysmography (PPG) signals from the patient in real-time and derives hemoglobin concentration levels using linear regression. The PPG signals are obtained through a reflective-type optical sensor consisting of Red and IR LEDs integrated with a signal conditioning circuit. Digital signal processing, feature extraction, and linear regression were used to obtain the PPG signal's AC/DC ratio and generate a conversion formula used in deriving hemoglobin concentration values. To verify that there is no significant difference between the actual and predicted hemoglobin concentration values, a paired t-test was used. Since the obtained p-value 0.3 is greater than the 0.05 level of significance, the null hypothesis is accepted, which means the conventional method and the developed system have no significant difference in their results. As such, it can be concluded that the proposed system is a viable alternative for anemia diagnosis. © 2023 ACM.

关键词： Linear regression

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Dissipativity-Based Decentralized Control and Topology Co-Design for Vehicular Platoons With Disturbance String Stability 63

Dissipativity-Based Decentralized Control and Topology Co-De...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Song, Zihao Welikala, Shirantha Antsaklis, Panos J. Lin, Hai University of Notre Dame College of Engineering Department of Electrical Engineering IN46556 United States Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States

ISBN: (纸本)9798350316339

Merging and splitting of vehicles in a platoon is a basic maneuvering that makes the platoons more scalable and flexible. The main challenges lie in simultaneously ensuring the compositionality of the distributed controllers and the string stability of the platoon. To handle this problem, we propose a control and topology co-design method for vehicular platoons, which enables seamless merging and splitting of vehicular platoons. In particular, we first present a centralized linear matrix inequality (LMI)-based control and topology co-design optimization for vehicular platoons with formal (centralized) disturbance string stability (DSS) guarantee. Then, these centralized DSS constraints are made decentralized by developing an alternative set of sufficient conditions. Using these decentralized DSS constraints and Sylvester's criterion-based techniques, the said centralized LMI problem is decomposed into a set of smaller decentralized LMI problems that can be solved at each vehicle in a compositional manner, enabling seamless vehicular merging/splitting. Finally, simulation examples are provided to validate the proposed co-design method through a specifically developed simulator. © 2024 IEEE.

关键词： Decentralized control

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IoT Device Authentication via RAM Trace Analysis: A Representation Learning Framework

IoT Device Authentication via RAM Trace Analysis: A Represen...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Iqbal, Asif Aman, Muhammad Naveed Sikdar, Biplab National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore University of Nebraska-Lincoln School of Computing Nebraska United States

ISBN: (纸本)9798350351255

Recent advances in IoT, machine learning, and edge computing have driven transformative paradigms like smart cities, grids, healthcare, and transportation systems, providing efficient solutions. This has led to a pervasive proliferation of connected devices, ranging from high-power computers to low-power sensors. Yet, the complex IoT architecture poses numerous vulnerabilities, demanding robust security measures. Existing firmware attestation techniques often encounter obstacles due to proprietary constraints, necessitating access to the device's authentic firmware. To address this challenge, this paper proposes a novel software-based attestation framework that utilizes RAM traces from IoT devices for remote verification. By employing deep learning models trained in a representation learning paradigm, our framework empowers the remote verifier to authenticate the internal state of IoT devices. Leveraging data collected from real-world prototype devices, our approach achieves an impressive 100% detection rate for critical attacks on IoT devices with a false positive rate of 10-3. Remarkably, our framework preserves device availability and maintains low authentication latency, highlighting its efficacy and practicality for securing IoT ecosystems. © 2024 IEEE.

关键词： Firmware

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MCU-Based Hot Compression Belt Control System as Menstrual Cramp Reliever 23

MCU-Based Hot Compression Belt Control System as Menstrual C...

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13th International Conference on Biomedical engineering and Technology, ICBET 2023

作者： Borris, Darianne Mae S. De Chavez, Mark Anthony D. De Ocampo, Denise R. Linsangan, Noel B. De Leon, Voltaire B. Villaverde, Jocelyn Flores Juanatas, Roben A. School of Electrical Electronics and Computer Engineering Mapua University Philippines College of Computing in Information Technologies National University Philippines

ISBN: (纸本)9798400707438

Women experience menstrual cycles every month, especially those in their teens and twenties. Some might not have encountered problems with their monthly period but many suffer from pain called Menstrual Cramps or Dysmenorrhea. Medicines, pain relievers, and hot compress are the solutions that women take in order to relieve the pain they experience. But some of these solutions are not enough and some are not safe for those who cannot take medicines easily. The use of the Hot Compression Belt control systems solved the problems of women with menstrual discomfort. It is safer to use and more effective. The device is capable of generating heat and compression for the purpose of aiding abdominal and back pain. Through the tests conducted, the device was proven to be effective and capable of relieving menstrual cramps and decreasing pain. The study has also proven that abdominal temperature increases during menstruation, and pain is correlated to temperature. © 2023 ACM.

关键词： Control systems

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Towards a lightweight security framework using blockchain and machine learning

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Blockchain(Research and Applications) 2024年第1期5卷 107-118页

作者： Shereen Ismail Muhammad Nouman Diana W.Dawoud Hassan Reza School of Electrical Engineering and Computer Science University of North DakotaND 58202USA Department of Computer Science COMSATS University IslamabadIslamabad 44000Pakistan College of Engineering and Information Technology University of DubaiDubaiUnited Arab Emirates

Cyber-attacks pose a significant challenge to the security of Internet of Things(IoT)sensor networks,necessitating the development of robust countermeasures tailored to their unique characteristics and *** prevention and detection techniques have been proposed to mitigate these *** this paper,we propose an integrated security framework using blockchain and Machine Learning(ML)to protect IoT sensor *** framework consists of two modules:a blockchain prevention module and an ML detection *** blockchain prevention module has two lightweight mechanisms:identity management and trust *** management employs a lightweight Smart Contract(SC)to manage node registration and authentication,ensuring that unauthorized entities are prohibited from engaging in any tasks,while trust management uses a lightweight SC that is responsible for maintaining trust and credibility between sensor nodes throughout the network’s lifetime and tracking historical node *** and transaction validation are achieved through a Verifiable Byzantine Fault Tolerance(VBFT)mechanism to ensure network reliability and *** ML detection module utilizes the Light Gradient Boosting Machine(LightGBM)algorithm to classify malicious nodes and notify the blockchain network if it must make decisions to mitigate their *** investigate the performance of several off-the-shelf ML algorithms,including Logistic Regression,Complement Naive Bayes,Nearest Centroid,and Stacking,using the WSN-DS *** is selected following a detailed comparative analysis conducted using accuracy,precision,recall,F1-score,processing time,training time,prediction time,computational complexity,and Matthews Correlation Coefficient(MCC)evaluation metrics.

关键词： Blockchain Machine learning IoT Security Integration Smart contracts

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Glucose-6-Phosphate Dehydrogenase Deficiency Detection using MyRIO Microcontroller and Color Sensor System 23

Glucose-6-Phosphate Dehydrogenase Deficiency Detection using...

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13th International Conference on Biomedical engineering and Technology, ICBET 2023

作者： Linsangan, Noel B. Fradejas, Dayne N. Gaba, Vince Harley D. Manuel, Lester N. Villaverde, Jocelyn Flores Juanatas, Roben A. School of Electrical Electronics and Computer Engineering Mapua University Philippines College of Computing in Information Technologies National University Philippines

ISBN: (纸本)9798400707438

This paper presents a device that can detect the deficiency of Glucose-6-Phosphate Dehydrogenase in blood samples. A color sensor system was used in which the blue value of a sample is observed under ultraviolet light. A deficient blood sample will yield values from 19 and below, while a normal blood sample will yield values from 25 and above. To consider values outside the specified range, values of 20 and below are considered deficient, and values above are considered normal. The system made use of a myRIO microcontroller intended as an improvement to the PIC microcontroller. The system also made use of a light switching mechanism that uses the white color of the base to determine if a sample is inserted and switches between the ultraviolet and white light as a way of minimizing power consumption. © 2023 ACM.

关键词： Microcontrollers

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Development of Force Sensing Nipple for Describing Changes in Suckle Behavior Between Healthy & Sick Dairy Breed Calves

Development of Force Sensing Nipple for Describing Changes i...

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2024 American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2024

作者： Chen, Zoe M. von Konigslow, Taika E. Bhattacharjee, Tapomayukh Department of Electrical and Computer Engineering College of Engineering Cornell University IthacaNY14853 United States Department of Population Medicine and Diagnostic Sciences College of Veterinary Medicine Cornell University IthacaNY14853 United States Department of Computer Science Bowers College of Computing and Information Science Cornell University IthacaNY14853 United States

ISBN: (纸本)9798331302214

Young dairy calves are susceptible to diseases, especially during the first six weeks of life. Calf caregivers use qualitative visual cues during health checks as early disease indicators. Few quantitative measurement devices have been designed and validated to help with the earlier identification of sick calves. Most methods provide no continuous monitoring options, are time-consuming, or require direct animal contact, which may contribute to pathogen spread and expose caregivers to zoonotic pathogens. Previous studies have shown that diarrhetic and sick calves have weaker suckling reflexes, compared to healthy counterparts. However, quantifiable differences in suckle compression forces have yet to be defined. Our goal is to create a device that can measure the suckle compression force differences between healthy and sick calves. The device is modeled after feeding nipples attached to portable calf feeding bottles and measures forces of up to 50N, with an error of ±3.09N. Preliminary field testing found that suckle compressions from one healthy calf (N=160 suckles) had an average force of 14.97N with a standard deviation of 4.30N, while weak suckle compressions from a calf demonstrating less interest in suckling (N=221 suckles) had an average force of 4.55N with a standard deviation of 2.35N. We intend to integrate the device into a commercial automated milk-feeding system to provide a quantified indicator of suckle compression force over time. Future work will test the device’s ability to withstand rugged conditions and determine associations with early disease detection. © 2024 ASABE Annual International Meeting. All rights reserved.

关键词： Pathogens

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