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Flexible organic solar cells for biomedical devices

Nano Research 2021年第9期14卷 2891-2903页

作者： Bin Kan Faheem Ershad Zhoulyu Rao Cunjiang Yu Department of Mechanical Engineering University of HoustonHoustonTX 77204USA Department of Biomedical Engineering University of HoustonHoustonTX 77204USA Materials Science and Engineering Program University of HoustonHoustonTX 77204USA Department of Electrical and Computer Engineering University of HoustonHoustonTX 77204USA Texas Center for Superconductivity University of HoustonHoustonTX 77204USA

Organic solar cells(OSCs),particularly made based on solution processing methods,have made significant progress over the past decades through the concurrent evolution of organic photovoltaic materials and device ***,high power conversion efficiencies around 18%and over 16%have been demonstrated in both rigid and flexible OSCs,*** most of the OSC research has centered on efficiency and cost,their emerging and potential usages in many critical applications,particularly in biomedical fields have been *** this mini-review,we will briefly discuss the high-performance organic photovoltaic materials and the representative flexible OSCs to give a scope on the recent rapid development of ***,we will review some progress on the applications of OSCs in biomedical devices and integrated *** potential challenges associated with integrating OSCs for biomedical devices will be put forward.

关键词： organic solar cells photovoltaic flexible biomedical bioelectronics

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Distributed control of mobile robots in an environment with static obstacles

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IET Cyber-Systems and Robotics 2021年第2期3卷 128-139页

作者： Konstantinos Giannousakis Anthony Tzes Electrical&Computer Engineering Department University of PatrasRioGreece Electrical&Computer Engineering Program New York University Abu DhabiAbu DhabiUnited Arab Emirates

This study addresses the problem of deploying a group of mobile robots over a nonconvex region with *** that the robots are equipped with omnidirectional range sensors of common radius,disjoint subsets of the sensed area are assigned to the *** proximity-based subsets are calculated using the visibility notion,where the cell of each robot is treated as an opaque obstacle for the other *** on that,optimal spatially distributed coordination algorithms are derived for the area coverage problem and for the homing problem,where the swarm needs to move to specific *** studies demonstrate the results.

关键词： robot mobile visibility

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Eye Tracking System Using Convolutional Neural Network 5

Eye Tracking System Using Convolutional Neural Network

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5th International Conference on computer and Applications, ICCA 2023

作者： Iskandar, Shatha Jaara, Zahraa Ali, Mohamad Abou Sbeity, Fatima Kasem, Abdallah Hamawy, Lara Lebanese International University Department of Biomedical Engineering Lebanon University of the Basque Country Dept.of Computer Science & Artificial Intelligence Spain Lebanese University Dept. of Physics & Electronics Lebanon Notre Dame University Dept. of Electrical & Computer Engineering Lebanon

ISBN: (纸本)9798350303254

Several diseases and disabilities, including cerebral palsy (CP), cause patients to lose their ability to communicate easily with the outside world. In this paper we aim to detect the movement of the iris that can be used to move a wheelchair for CP patients, write sentences by simply looking at an interactive screen, or even by moving an artificial arm. Thus, the two-dimensional CNN model and the coding method, we proposed, tracks the eye movement, specifically the movement of the iris, using VGG image annotator software and a dataset of several people's eyes images A dataset of 500 images from several patients, where only the eyes were cropped and studied, was taken to train the model about eye movement and detection. The proposed model achieved a mean squared error drop of about 49,720 from the original we started with, which was 50,000. © 2023 IEEE.

关键词： Neural network models

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The 32 Analog Channels Readout for the Long-Flight GAPS Balloon Experiment Tracking System 53rd

The 32 Analog Channels Readout for the Long-Flight GAPS Ball...

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53rd Annual Meeting of the Italian Electronics Society, SIE 2022

作者： Riceputi, E. Boezio, M. Fabris, L. Ghislotti, L. Lazzaroni, P. Manghisoni, M. Ratti, L. Re, V. Zampa, G. Department of Engineering and Applied Sciences University of Bergamo Dalmine Italy INFN Trieste Division Trieste Italy Oak Ridge National Laboratory Oak RidgeTN United States Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (纸本)9783031260650

The paper describes the main results of the characterization of the flight ASIC developed for the readout of a lithium-drifted silicon, Si(Li), detector-based tracker. The system aims to detect indirect signatures of dark matter through the identification of low-energy ( © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： CMOS integrated circuits

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Diabetes Classification Problem with CatBoost Method and Optuna Gradient Boosting Optimization 6

Diabetes Classification Problem with CatBoost Method and Opt...

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6th International Conference on Information and Communications Technology, ICOIACT 2023

作者： Kurniawan, Safar Dwi Purwono, Purwono Ma'arif, Alfian Suwarno, Iswanto Politeknik Harapan Bersama Department of Computer Engineering Tegal Indonesia Universitas Harapan Bangsa Department of Informatics Purwokerto Indonesia Universitas Ahmad Dahlan Department of Electrical Engineering Yogyakarta Indonesia Universitas Muhammadiyah Yogyakarta Department of Engineer Professional Program Yogyakarta Indonesia

ISBN: (纸本)9798350315639

Diabetes mellitus is a dangerous global epidemic that can cause kidney failure, heart attack, blindness, and death. The main cause of this disease is too high blood sugar levels due to the irrelevant work of pancreatic beta cells. Rapid computer technology advances and implementations based on artificial intelligence have penetrated various fields, especially the health sector. Data mining and machine learning are technologies that continue to grow, are reliable, and can be used as research support tools in the medical field. This technology is considered capable of helping to automate diabetes prediction. Based on related research, our contribution to this research is to utilize the CatBoost method with Optuna optimization. In the data preprocessing stage, all 768 data sets have gone through removing outliers, normalizing features to reducing dimensions. The dataset is divided into 85\% composition for training data and 15\% for test data. At the feature selection stage with Correlation Pearson's, we found that Glucose correlated with diabetes outcome or disease because it had a value range of 0.47. The results' accuracy is considered less than optimal because it only produces an accuracy value below 80%, even after optimization with Optuna. It can be seen that there was only an increase of 7\% after optimizing with Optuna. © 2023 IEEE.

关键词： Data mining

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Design and Development of a Non-Invasive Glucose Monitoring Device Using Advanced Microcontroller 4

Design and Development of a Non-Invasive Glucose Monitoring ...

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4th International Conference on Expert Clouds and Applications, ICOECA 2024

作者： Divya, S. Karthikeyan, P. Vaigundamoorthi, M. Ramya, D. Soudagar, Manzoore Elahi Rajendiran, M. Dr. N.G.P. Institute of Technology Department of Biomedical Engineering Tamil Nadu Coimbatore641048 India Velammal College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Madurai6641021 India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Tamil Nadu Coimbatore641021 India Sri Eshwar College of Engineering Department of Computer Science and Business Systems Tamil Nadu Coimbatore641202 India Saveetha School of Engineering Saveetha Institute of Medical and Techinical Sciences Department of VLSI Microelectronics Tamil Nadu Chennai602105 India Panimalar Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9798350385793

Millions of individuals all over the world are living with diabetes, a chronic condition that necessitates regular monitoring of Blood Glucose Levels (BGL). The present technique for minimal invasive BGL monitoring involves taking a small blood sample and transferring it to a glucometer. However, this procedure can be uncomfortable for the patient. This research presents a method for non-invasively monitoring BGL with the help of a powerful controller called the ARM Cortex-M4. For non-invasive applications, we use photoplethysmography (PPG) signals. Using a photodiode and an infrared LED light, PPG samples are received from a finger sensor. Signal processing and feature extraction are carried out using the Gray-Level Co-occurrence Matrix (GLCM) method. To predict the BGL, two ML models are developed: one employing a Linear Regression (LR) model and the other an Artificial Neural Network (ANN) model. The experimental findings show that the ANN model is quite effective, with an R2 score of 0.986. After careful consideration, the ARM Cortex-M4 microcontroller's processing capabilities were found to be optimal for running the ANN model. The model must be fine-tuned before deployment so it can communicate with the microcontroller and provide correct inference in real time. The finger sensor simplifies PPG sample collection, and the OLED display makes it simple to view BGL. © 2024 IEEE.

关键词： Photoplethysmography

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Breaking Language Barriers for Real-Time Translation Solutions in Tourism Using Cloud Computing and AI 3

Breaking Language Barriers for Real-Time Translation Solutio...

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3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Jame, S. Lourdu Nageswari, C. Shobana Jayaprakash, S. Punarselvam, E. Meenakshi, R. Muthulekshmi, M. SRM Institute of Science and Technology Kattankulathur Department of Electrical and Electronics Engineering Tamil Nadu Chennai India R.M.D. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Sathyabama Institute of Science and Technology School of Electrical and Electronics Engineering Tamil Nadu Chennai India Department of Information Technology Tamil Nadu Namakkal India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331523893

To improve tourism experiences and enable cultural communication in today's worldwide tourism industry, it is essential to communicate effectively across linguistic boundaries. Cloud computing and artificial intelligence (AI) are the focus of this paper to create tourism-specific real-time translation systems. These solutions use cloud computing and advanced AI algorithms to better connect visitors with local businesses and provide accurate and contextually aware translations. Important technical parts include cloud computing for scalability and accessibility, machine learning models for language comprehension, and natural language processing (NLP). It uses empirical research or case study techniques to assess the solutions' practicability, performance, and user acceptability. Through the efficient and effective removal of language barriers, the results highlight the promise of cloud-based AI translation systems to revolutionize the tourist industry. This research investigates real-time translation innovations, highlighting scalability, context awareness, and multilingual support, with implications for future advances in AI and cloud-based tourist applications. Also covered are potential avenues for further study and application, with the growth of the tourist industry's continuous development and use of AI-driven solutions. The proposed approach enhances real-time translation using cloud computing and AI, enabling scalability and context-aware translations. However, there are other challenges, such as overcoming latency and advanced, idiomatic expressions. © 2025 IEEE.

关键词： Tourism

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Harnessing Vision Transformers for Precise and Explainable Breast Cancer Diagnosis 27th

Harnessing Vision Transformers for Precise and Explainable B...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Balaha, Hossam Magdy Ali, Khadiga M. Gondim, Dibson Ghazal, Mohammed El-Baz, Ayman Bioengineering Department J.B. Speed School of Engineering University of Louisville LouisvilleKY United States Pathology Department Faculty of Medicine Mansoura University Mansoura Egypt Department of Pathology and Laboratory Medicine University of Louisville LouisvilleKY United States Electrical Computer and Biomedical Engineering Department Abu Dhabi University Abu Dhabi United Arab Emirates

ISBN: (纸本)9783031781940

Breast cancer (BC) remains a significant global health challenge, impacting millions of lives annually. Traditional histopathological analysis, while essential, can be subjective and time-consuming, potentially leading to diagnostic inaccuracies. This study proposes a novel computer-Aided Diagnosis (CAD) framework utilizing Vision Transformers (ViTs) for BC diagnosis from histopathology slides. ViTs excel in capturing global dependencies within images, offering enhanced diagnostic accuracy compared to conventional methods. The framework integrates ViTs with advanced decision-making techniques like 2-tier majority fusion and SHapley Additive exPlanations (SHAP) for improved interpretability. Experimental results on a dataset of post-neoadjuvant therapy breast cancer samples demonstrate the efficacy of the proposed approach, achieving high performance metrics and providing insights into model predictions. The proposed approach achieves state-of-the-art performance with an accuracy exceeding 97% surpassing existing methods both on the utilized dataset and an external benchmark, specifically the Breast Cancer Histopathological Database (BreakHis). Time complexity analysis suggests that the proposed framework offers computational efficiency, with the dominant factors influencing overall complexity being the number of patches, sequence length, and number of layers in the ViT model. This study contributes a robust methodology towards enhancing BC diagnostic precision and efficiency through cutting-edge AI technologies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Diseases

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Direct laser speckle contrast imaging with sampling bias correction

Direct laser speckle contrast imaging with sampling bias cor...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Zheng, Shuqi Mertz, Jerome Department of Electrical and Computer Engineering Boston University 8 St. Mary's St. BostonMA02215 United States Department of Biomedical Engineering Boston University 44 Cummington Mall BostonMA02215 United States

Speckle contrast is generally calculated from localized window containing limited statistics, resulting a systematic bias in the estimation. We achieve sampling bias correction and demonstrate accurate quantitative la...

ISBN: (纸本)9781957171258

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Impact of exposure time and power intensity on cell viability in 3D bioprinting 12

Impact of exposure time and power intensity on cell viabilit...

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Laser 3D Manufacturing XII 2025

作者： Tavares-Negrete, Jorge A. Babayigit, Ceren Boyraz, Ozdal Esfandyarpour, Rahim Laboratory for Integrated Nano Bio Electronics Innovation The Henry Samueli School of Engineering University of California IrvineCA92697 United States Department of Biomedical Engineering The University of California IrvineCA92697 United States Department of Electrical Engineering and Computer Science The University of California IrvineCA92697 United States Department of Mechanical and Aerospace Engineering The University of California IrvineCA92697 United States Henry Samueli School of Engineering University of California IrvineCA92697 United States

ISBN: (纸本)9781510684560

In 3D bioprinting, the photopolymerization of bioinks is a critical step in building desired structures with high precision. The chosen parameters, such as exposure time and light intensity during photopolymerization of the bioinks, significantly influence the resolution, cell viability, and proliferation of the bioprinted constructs. This study investigates how varying exposure times (10-30 s) and light intensities (0.04-0.11 mW/mm^2) in a laser-based bioprinter affect the performance of 3T3 fibroblasts embedded in GelMA bioinks. The metabolic activity and cell morphology of the bioprinted constructs were assessed over a week-long culture period. The findings reveal a clear relationship between longer exposure times and reduced cell viability. On day 7, samples exposed for extended periods exhibited the lowest metabolic activity, with differences of around 40% between treatments. In contrast, samples exposed to different light intensities resulted in variations below 15% in metabolic activity. GelMA bioinks exhibited less favorable outcomes under prolonged exposure, with cells displaying more rounded and less proliferative morphologies. In contrast, lower exposure times promoted more elongated cell shapes and network formation. These results highlight the importance of optimizing exposure time and light intensity to preserve cell wellness in 3D bioprinted constructs. © 2025 SPIE.

关键词： Cell culture

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