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18th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2022

作者： Tey, Fu Jie Wu, Tin-Yu Liu, Mei-Yin Chen, Yi-Kai Department of Electrical Engineering National Taiwan University of Science and Technology Taipei City Taiwan Department of Management Information Systems National Pingtung University of Science and Technology Neipu Taiwan Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan City Taiwan

ISBN: (纸本)9789819901043

This study focuses on the brainwave analysis of the correlation between listening to the rain and water sounds and reducing human-perceived temperature. Brainwave changes are monitored when experimental subjects listen to rain and water sounds at various frequencies. The experiment result shows that listening to the sounds of rain and water in an environment of high temperature and high humidity can boost α waves to induce feelings of calm and relaxed mental state. In order to investigate subjects’ psychological and physiological changes induced by brainwave changes while listening to rain and water sounds for different time durations in a high temperature and humidity environment, this study uses the Fourier transform to obtain the spectra of natural rain/water sounds and analyzes the sound frequencies. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fourier analysis

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Methylene Blue Removal on Biodegradable Adsorptive Membranes Fabricated From Sugarcane Bagasse Pulp: Characterization and Performance Study

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Macromolecular Symposia 2024年第2期413卷 2300088-2300088页

作者： Elshabrawy, Salma O. M. Elhussieny, Amal Taha, Mahmoud M. Konsowa, Abdelaziz H. Fahim, Irene S. Smart Engineering Systems Research Center Nile University Juhayna Square Giza El Sheikh Zayed Egypt Chemical Engineering Department Faculty of Engineering Alexandria University Alexandria21544 Egypt Environmental Engineering Program Zewail City of Science and Technology University of Science and Technology October Gardens 6th of October Giza12578 Egypt

Dye-containing waste should be carefully treated using environmentally friendly technology to prevent environmental harm and preserve water resources. Adsorptive membranes are a promising new approach for decreasing, recovering, and reusing waste while also removing contaminants like dyes. In this work, two different techniques are employed to create membranes using sugarcane bagasse pulp and carbon from charcoal. In the first technique, the surface of sugarcane bagasse is coated with charcoal paste as shown in Figure 1, while in the second, the carbon is combined with sugarcane bagasse pulp particles before being formed into sheets. It is discovered that the manufactured membranes has micron-sized pores. It is discovered that the mixed-fabricated membrane has a 99.4% better efficiency than the coated one. The membranes' surfaces are characterized using FTIR and SEM analysis. © 2024 Wiley-VCH GmbH.

关键词： Charcoal

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Product Competitor Analysis for First-Year engineering Students

Product Competitor Analysis for First-Year Engineering Stude...

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IEEE International Conference on Teaching, Assessment and Learning for engineering (TALE)

作者： Kuntinee Maneeratana Peerapat Thongnuek Danupol Hoonsopon Suvanchai Pongsugitwat Charasphat Preuksarattanawut Nattaporn Tonanon Sirikanya Phongtongjalearn Department of Mechanical Engineering Chulalongkorn University Bangkok Thailand Interdisciplinary Program of Biomedical Engineering Chulalongkorn University Thailand Marketing Department Chulalongkorn Business School Chulalongkorn University Thailand Department of Metallurgical Engineering Chulalongkorn University Bangkok Thailand Department of Chemical Engineering Chulalongkorn University Bangkok Thailand Faculty of Engineering Chulalongkorn University Bangkok Thailand

This paper presented a learning model for product competitor analysis to first-year engineering students. Students were assigned to watch a video which contained an example before class. In a 45-minutes allotted class time, students were grouped, on-site or online, and assigned to complete an exercise on the product and direct competitor of their choice. The exercise focused on the 4Ps model for marketing implementation – product, price, place, and promotion – of the product and competitor and concluded with the strength, weakness, and unique value proposition of the product. The works were usually rough but acceptable. Students were generally satisfied and 86% found the exercise at least useful in the subsequent design thinking projects. In the future, the ChatGPT could be used to increase the working speed and, thus, reduced the most common complaint of insufficient time while increasing the work quality.

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Image Processing Pipeline to Compute Homologous Recombination Score 22

Image Processing Pipeline to Compute Homologous Recombinatio...

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12th International Conference on Biomedical engineering and Technology, ICBET 2022

作者： Vundavilli, Haswanth Tumiati, Manuela Hautaniemi, Sampsa Datta, Aniruddha Kauppi, Liisa Texas A&M University United States The University of Texas MD Anderson Cancer Center United States Research Program in Systems Oncology Faculty of Medicine University of Helsinki Finland Department of Electrical and Computer Engineering The Center for Bioinformatics and Genomic Systems Engineering Texas A&M University United States

ISBN: (纸本)9781450395779

DNA double-strand breaks (DSBs) occur frequently in eukaryotic cells, and the homologous recombination pathway (HR) is one of the major pathways required to repair these breaks. However, tumor cells that are able to repair DSBs are unlikely to die due to damage incurred by DNA damaging chemotherapies, such as platinum compounds. While platinum-based therapies have been effective in treating various cancers, they also carry harsh side effects, and thus ideally platinum should be used when the probability of treatment resistance is low. HR scores provide a measure for patients' tumor's HR capacity and have been shown to predict their chemotherapy response and long-term survival. Calculating this score manually from immunofluorescence microscopy images for each patient is error-prone and time-consuming. Herein, we propose an image processing pipeline that takes as input imaging data from three emission channels (representing nuclei, S-phase cells, and HR-mediated repair in a tumor slice) from an epifluorescence microscope and computes the HR score. Our open-source methodology forms a rationale to develop similar approaches in predicting chemotherapeutic responses and facilitating to make treatment decisions. © 2022 ACM.

关键词： Chemotherapy

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Meta-optic accelerators for object classifier

Meta-optic accelerators for object classifier

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Zheng, Hanyu Liu, Quan Zhou, You Kravchenko, Ivan I. Huo, Yuankai Valentine, Jason Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37212 United States Department of Computer Science Vanderbilt University NashvilleTN37212 United States Department of Mechanical Engineering Vanderbilt University NashvilleTN37212 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37212 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States

A meta-optic platform for accelerating object classification is demonstrated. End-to-end design is used to co-optimize the optical and digital systems resulting in a high-speed and robust classifier with 93.1% accurac...

ISBN: (纸本)9781957171258

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Snow Depth Estimation Using Sentinel-1 Through Investigation Of Influential Factors On Snowpack Properties And Backscatter

Snow Depth Estimation Using Sentinel-1 Through Investigation...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Chandra Prabha R Srinivasarao Tanniru Raaj Ramsankaran Department of Civil Engineering Hydro-Remote Sensing Applications(H-RSA) Group Indian Institute of Technology Bombay Interdisciplinary Program in Climate Studies Indian Institute of Technology Bombay

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Advancing the monitoring of seasonal snow, a natural reservoir of fresh water, is crucial for hydrological and climatological research. The utilization of synthetic aperture radar (SAR) systems for this purpose has gained prominence due to its improved capabilities and advantages over alternative methods. The study aims to improve snow depth estimation in the Western Himalayas by taking into account the influence of other variables on the relationship between Sentinel-1 C-band backscatter and snow depth. For this purpose, a preliminary study is done using random forest machine learning algorithm. The model parameters are optimized through grid search and cross-validation on temporally independent folds of data and evaluated on spatially independent data, revealing the model's capability to estimate snow depth with an RMSE of 89.34 cm and MAE of 67.56 cm. The study highlights the potential for improving snow depth estimates, particularly for deeper snowpacks, through the analysis and inclusion of variables that influence snowpack properties in complex topography.

关键词： Machine learning algorithms Snow Estimation Sentinel-1 Surfaces Reservoirs Data models

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An explainable non-invasive hybrid machine learning framework for accurate prediction of thyroid-stimulating hormone levels

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Computers in Biology and Medicine 2025年 189卷 109974-109974页

作者： Mohammed, Areej Alshraideh, Hussam Abu-Helalah, Munir Shamayleh, Abdulrahim Department of Industrial Engineering Engineering Systems Management Program American University of Sharjah SharjahP.O. Box 26666 United Arab Emirates Department of Industrial Engineering American University of Sharjah SharjahP.O. Box 26666 United Arab Emirates Industrial Engineering Department Jordan University of Science and Technology Irbid Jordan Department of Family and Community Medicine School of Medicine University of Jordan Public Health Institute Amman Jordan

Machine learning models, including thyroid biomarkers, are increasingly utilized in healthcare for biomarker prediction. These models offer the potential to enhance disease diagnosis through data-driven approaches relying on non-invasive techniques. However, no studies have explored the application of fully non-invasive methods for predicting thyroid-stimulating hormone (TSH) levels. Consequently, this study introduces a novel, fully non-invasive framework for predicting TSH levels by developing an innovative hybrid machine learning model that balances performance, complexity, and interpretability. Seven ML models were evaluated, and the best-performing models were integrated into a hybrid approach to balance performance, complexity, and interpretability. A dataset of 6190 instances from Jordan was used for model development. Four-dimensional non-invasive factors, including demographics, symptoms, family history, and newly engineered symptom scores, were incorporated into the model. The hybrid model achieved an R2 of 94.2 % and RMSE of 0.015, demonstrating superior predictive performance. Model interpretability was ensured using LIME and SHAP explainers, confirming aggregated symptom scores' critical role in enhancing prediction accuracy. A robust feature selection technique was implemented, reducing model complexity and enhancing performance. Among the top ten features for predicting TSH levels were hypothyroidism and hyperthyroidism symptom scores, family history, cold intolerance, itchy-dry skin, sweating, hand tremors, and palpitations. The model can be employed to develop cost-effective diagnostic tools for thyroid disorders. It also offers a robust framework that can be generalized to predict other biomarkers and applied in diverse contexts. © 2025 Elsevier Ltd

关键词： Prediction models

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Decomposition and Reorganization of Phonetic Information for Speaker Embedding Learning

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IEEE/ACM Transactions on Audio Speech and Language Processing 2023年 31卷 1745-1757页

作者： Hong, Qian-Bei Wu, Chung-Hsien Wang, Hsin-Min National Cheng Kung University and Academia Sinica Graduate Program of Multimedia Systems and Intelligent Computing Tainan701 Taiwan Academia Sinica Taipei115 Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan701401 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan

Speech content is closely related to the stability of speaker embeddings in speaker verification tasks. In this paper, we propose a novel architecture based on self-constraint learning (SCL) and reconstruction task (RT) to remove the influence of phonetic information on speaker embedding generation. First, SCL is used to reduce the divergence of frame-level features, which can avoid ambiguity between the resulting embeddings of the two utterances being compared. Second, RT is used to further remove phonetic information in frame-level layers, focusing on speaker-discriminative feature transformation. In our experiments, the speaker embedding models were trained on the VoxCeleb2 dataset and evaluated on the VoxCeleb1, Librispeech, SITW and VoxMovies datasets. Experimental results on VoxCeleb1 show that the proposed DROP-TDNN system reduced the EER by 7.5%, compared to the state-of-the-art ECAPA-TDNN system. Furthermore, the proposed DROP-TDNN system also outperformed the ECAPA-TDNN system in the experiments on SITW, Librispeech and VoxMovies under cross-dataset conditions. In the experiments on SITW, the proposed system reduced the EER by 3.4% compared to the ECAPA-TDNN system. In the experiments on Librispeech, the proposed system demonstrated the advantage of removing phonetic information under the clean speech condition, with a significant reduction of 25.5% in EER compared to the ECAPA-TDNN system. In the experiments on VoxMovies, the proposed system reduced the EER by up to 7.9% compared to the ECAPA-TDNN system under different pronunciation and background conditions. © 2014 IEEE.

关键词： Speech recognition

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Design and Implementation of Cascaded Ant Colony Optimization Coupled with Sliding Mode Controller for Autonomous Cruise Control System

Design and Implementation of Cascaded Ant Colony Optimizatio...

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Energy Technologies for Future Grids (ETFG), IEEE International Conference on

作者： Muhammad Majid Gulzar Muhammad Mughees Ahmed Adnan Shakoor Muhammad Khalid Department of Control & Instrumentation Engineering Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Department of Electrical Engineering University of Central Punjab Lahore Pakistan Electrical Engineering Department Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

Driving assist systems are being widely used in modern cars nowadays for safety, efficiency and comfort. These systems are used in cruise control, self-driving control and even obstacle avoidance. All these systems include a lot of sensors and radars, which work together and generate fast responses to manipulate the direction or speed of a car. The main objective of using this sort of technology is to reduce accidents by reducing stress on the driver by increasing comfort of travel. The aim of this research is to develop a controller for cruise control in vehicles that can help to reach the desired speed most accurately, quite fast and efficiently. The proposed Ant Colony Optimization coupled with Sliding Mode Controller (ACO & SMC) used in this research is more accurate and robust that can help to tune the parameters in a way that the cruise control system gives a minimum error, stable results with the least possible disturbances. Later on, the results are also compared with already used state-of-the-art technologies implemented for cruise control to show the superiority of the proposed controller.

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Influence of Magnetically-Induced Nonlinear Added Stiffness on the Lift Galloping of Square Cylinders at Low Reynolds Number

SSRN

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SSRN 2023年

作者： Rashed, Mostafa R. Shaaban, Mahmoud Mechanical Engineering Department Faculty of Engineering Modern University for Technology and Information Cairo Egypt Mechanical Engineering Program School of Engineering and Applied Sciences Nile University Cairo Egypt Smart Engineering Systems Center Nile University Cairo Egypt

A square cylinder may gallop if subjected to fluid flow experiencing a self-excited vibration mode that can harvest energy for low-power applications. The harvested power is typically low and depends on the upstream flow velocity and system dynamic parameters. In this study, the influence of nonlinear stiffness induced by two repulsive magnetic poles on the galloping response of a square rod is investigated at a mass ratio of 10 and a Reynolds number of 200. The vibration response of two identical coaxial square rods with magnetic poles attached to their opposite ends is analyzed. Two simplified configurations are selected to model the magnetic forces: a pair of identical monopoles and a pair of identical dipoles. Results show that the magnet configuration and strength significantly affect the vibration amplitude and the onset flow velocity. A weak magnetic force can enhance vibration and reduce onset flow velocity, while a stronger pair of dipoles may push the bistable system to a state of low-amplitude vibration with a mean displacement. The influence of magnets in this configuration has potential as a control technique for energy harvesting applications. © 2023, The Authors. All rights reserved.

关键词： Computational fluid dynamics

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