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Electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Akeem. A. Azeez Biniyam Mezgebo Rodrigo França Sherif S. Sherif Biomedical Engineering Graduate Program University of Manitoba Winnipeg Canada Dept. of Electrical andComputer Engineering University of Manitoba Winnipeg Canada Dept. of Restorative Dentistry University of Manitoba Winnipeg Canada Dept. of Electrical and Computer Engineering University of Manitoba Winnipeg Canada

This paper presents an optical coherence tomography (OCT) system in conjunction with a novel image reconstruction technique employed for in vitro imaging of human teeth. The primary goal is to enhance the signal-to-noise ratio (SNR) in the obtained images. The study entails a comparative analysis between the conventional Fast Fourier Transform (FFT) OCT image reconstruction method and a newly introduced scaled nonuniform discrete Fourier transform (NDFT) approach. The findings reveal that the NDFT method consistently delivers superior results in terms of peak signal-to-noise ratio (PSNR) and overall image quality, even when dealing with redundant and nonuniform frequency domain samples. In light of these results, this paper concludes that integrating NDFT into OCT procedures has the potential to significantly enhance the quality of image reconstructions, thereby fostering its broader application in the field of dental imaging.

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Platform for Evanescent Wave Sensor Fabrication Based on 3D-Printed Fiber Optic Holder

Platform for Evanescent Wave Sensor Fabrication Based on 3D-...

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Optical Fiber Sensors (LAWOFS), Latin American Workshop on

作者： Afonso Henrique Henschel Baptista Pedro Bertemes-Filho Aleksander Paterno Raquel Bettega Jose Pedro Mansueto Serbena Nathalia Prediger Ricardo Kamikawachi Department of Electrical Engineering Center for Science and Technology - Santa Catarina State University – CCT-UDESC Joinville Brazil Group of Organic Optoelectronic Devices (GOOD) Federal University of Parana – UFPR Curitiba Brazil Graduate Program in Electrical and Computer Engineering Federal University of Technology - Parana – UTFPR Curitiba Brazil

ISBN: (数字)9786589532026

ISBN: (纸本)9798350362725

This paper describes the low-cost manufacturing process of an evanescent wave fiber sensor platform that allows the etching of the fiber in hydrofluoric acid with the proposed 3D-printed fiber holder in an acid resistant material. The fiber holder is practical for allowing several processing procedures during its use and sensor fabrication, allowing sensor optical and electrical operation. In this work, some aspects of its characterization are presented in the optical domain showing the excitation of surface plasmons in the visible range, and also indication of its electrical operation of the thin-film as electrode.

关键词： Optical fiber polarization Optical fiber sensors Gold Optical polarization Biomedical optical imaging Optical device fabrication Optical films

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Single-Phase Transformerless UPS with Interleaved Boost Converters for Battery Discharging

Single-Phase Transformerless UPS with Interleaved Boost Conv...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Alan R. A. Pinto Filipe A. C. Bahia Reuben P. R. Souza José R. Pinheiro Fabiano F. Costa Post-Graduate Program in Electrical Engineering PPGEE Federal University of Bahia Salvador Brazil Dept. of Electrical and Computer Engineering DEEC Federal University of Bahia Salvador Brazil Dept. of Electrical Engineering DEE Federal University of Campina Grande Campina Grande Brazil

This paper proposes a reconfiguration for a single-phase, double conversion uninterruptible power supply (UPS). With the addition of two static switches to the original circuit, the UPS mitigates the ripple in the current, through battery discharge performed by two legs. Other than these switches, the circuit topology is preserved. The preliminary results show a satisfactory level of ripples for the inductor current and suitable power quality for the output voltage.

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Image color correction, enhancement, and editing

arXiv

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arXiv 2021年

作者： Afifi, Mahmoud Nasser Mohammed Graduate Program in Electrical Engineering and Computer Science York University TorontoON Canada

This thesis presents methods and approaches to image color correction, color enhancement, and color editing. To begin, we study the color correction problem from the standpoint of the camera's image signal processor (ISP). A camera's ISP is hardware that applies a series of in-camera image processing and color manipulation steps, many of which are nonlinear in nature, to render the initial sensor image to its final photo-finished representation saved in the 8-bit standard RGB (sRGB) color space. As white balance (WB) is one of the major procedures applied by the ISP for color correction, this thesis presents two different methods for ISP white balancing. Afterwards, we discuss another scenario of correcting and editing image colors, where we present a set of methods to correct and edit WB settings for images that have been improperly white-balanced by the ISP. Then, we explore another factor that has a significant impact on the quality of camera-rendered colors, in which we outline two different methods to correct exposure errors in camera-rendered images. Lastly, we discuss post-capture auto color editing and manipulation. In particular, we propose auto image recoloring methods to generate different realistic versions of the same camera-rendered image with new colors. Through extensive evaluations, we demonstrate that our methods provide superior solutions compared to existing alternatives targeting color correction, color enhancement, and color editing. © 2021, CC BY.

关键词： Color

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Interpretable Machine Learning for Multi-Class Crop Yield Prediction

Interpretable Machine Learning for Multi-Class Crop Yield Pr...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Aldian Nurcahyo Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Compuer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia Compuer Science Departement Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

Crop Yield Analysis and Prediction is a fast-expanding discipline that is critical for optimizing agricultural methods. A lack of trustworthy data is one of the challenges in estimating crop yields. We develop predictive models for 22 different fruits and vegetables data. The goals of this study are to create accurate and interpretable crop recommendation models. We used multiple machine learning (ML) models for multi-class crop production prediction to fulfill our research goal. We thoroughly examined the influence of climate and nutrient factors on crop yield, considering their complex interactions. To improve the dataset, augmented data techniques were applied. Configuring the parameters and fine-tuning the hyperparameters is our technique to increase the model performance. Furthermore, we employ explainable artificial intelligence (XAI) techniques and interpretability tools like Shapley Additive exPlanations (SHAP) to improve the interpretability of our prediction model. Our findings reveal that the XGBoost model has the best performance model with 99.86% accuracy, followed by SVM Poly Kernel with 99.32% and Random Forest with 98.82%. Feature selection and analysis are emphasized, particularly in regional agricultural contexts. This study contributes to the creation of accurate and interpretable crop recommendation models while also addressing the issue of untrustworthy data, providing useful insights for optimizing agricultural practices.

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Cloud-Native Mobile Application Applied for Law and Regulations Harmonization

Cloud-Native Mobile Application Applied for Law and Regulati...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Muhammad Juan Al Qausar Yaya Heryadi Lukas Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Navigating the complex legal and regulatory landscape requires a sophisticated platform that is not only comprehensive but also user-friendly and enables seamless analysis and document comparison in the legal realm. To address this challenging requirement, this research is dedicated to the user experience (UX) design of state-of the-art cloud-native mobile applications specifically designed for legal and regulatory harmonization. The methodology used is based on design thinking principles and takes advantage of the benefits of cloud computing. These include, but are not limited to, scalability, reliability, and security. The result is a solution that is not only powerful but also cost-effective. The core of this application follows a user-centered design philosophy and involves potential users closely in the design process. A comprehensive evaluation is performed using the System Usability Scale (SUS) methodology to measure the effectiveness and usability of the application. The results of this comprehensive approach are convincing. The application has an impressive 95.5% usage rate, indicating strong user engagement. Furthermore, user satisfaction ratings are particularly high and transformative impact of this application in a complex environment of legal harmonization. Through its innovative design, seamless functionality, and user-centric approach, this application has proven to be not only a technical solution, but also a catalyst for positive change in the legal and regulatory harmonization process.

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Synthetic Batik Pattern Generator Using Wasserstein Generative Adversarial Network with Gradient Penalty

Synthetic Batik Pattern Generator Using Wasserstein Generati...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Kus Andriadi Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Batik is an Indonesian world cultural heritage. Batik consists of many kinds of patterns depending on where the batik comes from, Batik-making techniques continue to develop along with technology development. Among the batik making techniques that are widely used are hand-written, stamping, and printing. Batik motifs have been widely used as research material, especially in the field of artificial intelligence. The diverse appearance of batik motifs has attracted many researchers to carry out research on making synthetic batik patterns, one of which uses a Generative Adversarial Network. This paper presents a synthetic batik pattern model based on the Wasserstein Generative Adversarial Network with Gradient Penalty. This model has been proven to create new synthetic batik patterns quite well and almost identical with images provided in the dataset, with the notes if the dataset provided is large.

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Combining Knee Acoustic Emissions, Patient-Reported Measures, and Machine Learning to Assess Osteoarthritis Severity

Combining Knee Acoustic Emissions, Patient-Reported Measures...

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International Workshop on Wearable and Implantable Body Sensor Networks (BSN)

作者： Christopher Nichols H. Trask Crane Dave Ewart Omer T. Inan Bioengineering Graduate Program Georgia Institute of Technology Atlanta GA USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Minneapolis Veterans Affairs Medical Center Minneapolis MN USA Coulter Dept. of Biomedical Engineering School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

Current methods for quantifying osteoarthritis severity have limited resolution and accessibility. Patient-recorded outcome measures such as the Knee Injury and Osteoarthritis Outcome Score (KOOS) capture symptom severity, but are subjectively reported and have little correlation with quantifiable metrics of disease such as Kellgren-Lawrence x-ray grade or MRI findings. Knee acoustic emissions (KAEs) offer a convenient, noninvasive option for quantifying joint health. Here, we use machine learning and wearable design to create an interpretable two-stage algorithm for combining KAEs and KOOS scores into an objective, more accessible method of quantifying disease severity. Our algorithm successfully discriminated between early and late-stage osteoarthritis (balanced accuracy = 85%, ROC-AUC = 0.88). The addition of KAEs improved classification of osteoarthritis severity over the use of KAEs (balanced accuracy = 53%, ROC-AUC = 0.786) or KOOS scores alone (balanced accuracy = 63%, ROC-AUC = 0.593). The findings suggest that KAEs combined with patient-recorded metrics can be used to make a more objective and accessible metric for digitally monitoring knee joint health.

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Lightweight Pedestrian Detection through Guided Filtering and Deep Learning 10

Lightweight Pedestrian Detection through Guided Filtering an...

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10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Muchtar, Kahlil Saddami, Khairun Bintang, Akhyar Cenggoro, Tjeng Wawan Pardamean, Bens Lin, Chih-Yang Ernita, Tia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Bina Nusantara University School of Computer Science Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Yuan-Ze University Department of Electrical And Engineering Taoyuan Taiwan

ISBN: (纸本)9781665436762

In this paper, we propose a novel approach to locate and detect moving pedestrians in a video. Our proposed method first locates the region of interest (ROI) using a background subtraction algorithm based on guided filtering. This novel background subtraction algorithm allows our method to also filter unexpected noises at the same time, which could benefit the performance of our proposed method. Subsequently, the pedestrians are detected using YOLOv3 within the provided ROI. Our experiments showed that the proposed method has a competitive performance in the CDNET2014 dataset with a fast-processing time. © 2021 IEEE.

关键词： Convolutional neural networks

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Reachability Analysis of Nonlinear Discrete-Time Systems Using Polyhedral Relaxations and Constrained Zonotopes

arXiv

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arXiv 2025年

作者： Rego, Brenner S. Raffo, Guilherme V. Terra, Marco H. Scott, Joseph K. Department of Chemical and Biomolecular Engineering Georgia Institute of Technology 311 Ferst Dr. AtlantaGA30318 United States Department of Electrical and Computer Engineering University of São Paulo SP São Carlos13566-590 Brazil Department of Electronics Engineering the Graduate Program in Electrical Engineering Federal University of Minas Gerais MG Belo Horizonte31270-901 Brazil

This paper presents a novel algorithm for reachability analysis of nonlinear discrete-time systems. The proposed method combines constrained zonotopes (CZs) with polyhedral relaxations of factorable representations of nonlinear functions to propagate CZs through nonlinear functions, which is normally done using conservative linearization techniques. The new propagation method provides better approximations than those resulting from linearization procedures, leading to significant improvements in the computation of reachable sets in comparison to other CZ methods from the literature. Numerical examples highlight the advantages of the proposed algorithm. © 2025, CC BY-NC-ND.

关键词： Numerical methods

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