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CLEO: Applications and Technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Nobile, Nicholas A. Lian, Chuanyu Sun, Hongyi Huang, Yi-Siou Mills, Brian Popescu, Cosmin Constantin Callahan, Dennis Hu, Juejun Ríos Ocampo, Carlos A. Youngblood, Nathan Electrical & Computer Engineering Department University of Pittsburgh PittsburghPA15213 United States Department of Materials Science & Engineering University of Maryland College ParkMD20742 United States Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States Department of Materials Science & Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Draper Scholar Program The Charles Stark Draper Laboratory Inc. CambridgeMA02139 United States The Charles Stark Draper Laboratory Inc. CambridgeMA02139 United States

Sb2Se3 is used to switch between broadband transparency and enhanced index contrast in two device types leveraging Bragg gratings for tunable stop- and pass-band functionalities. Experimental results highlight fabrication challenges and efficacy of the designs. © Optica Publishing Group 2024, © 2024 The Author(s)

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A Platform for Monitoring Student Commuting in the Use of School Transport in Smart Cities - A Facial Recognition Based Approach

A Platform for Monitoring Student Commuting in the Use of Sc...

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2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023

作者： Da Costa Rocha, Jesse De Souza, Marcela Alves Cardoso, Evelin Helena Silva Vijaykumar, Nandamudi De Araujo, Jasmine Priscyla Leite Frances, Renato Lisboa Graduate Program in Electrical Engineering Belém Para Brazil Information and Communication Technology Center Marabá Para Brazil Department of Computer Science Capitão Poço Para Brazil Coordination of Applied Research and Technological Development São Paulo Brazil

ISBN: (纸本)9798350302523

This article proposes an intelligent platform for monitoring students' steps on their way to school until they leave the school to their homes. This platform can identify students and notify those responsible and competent authorities in various situations of school life, such as: entering and leaving the school bus, entering and leaving school, entering the school cafeteria, etc. The first application aims to control access to the school bus through facial recognition. In the tests carried out, the recognition system achieved excellent results in all metrics. © 2023 IEEE.

关键词： Students

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Gaze depth estimation for eye-tracking systems

Gaze depth estimation for eye-tracking systems

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Multimodal Image Exploitation and Learning 2023

作者： Stone, Abigail Rajeev, Srijith Rao, Shishir Paramathma Panetta, Karen Agaian, Sos Gardony, Aaron Nordlund, Jessica Skantar, Rebecca Department of Electrical and Computer Engineering Tufts University MedfordMA02155 United States Department of Computer Science City University of New York New YorkNY10016 United States U.S. Army Combat Capabilities Development Command Soldier Center NatickMA01760 United States Center for Applied Brain and Cognitive Sciences Tufts University MedfordMA02155 United States

ISBN: (数字)9781510661677

ISBN: (纸本)9781510661660

Eye-tracking holds numerous promises for improving the mixed reality experience. While eye-tracking devices are capable of accurate gaze mapping on 2D surfaces, depth estimation of gaze points remains a challenging problem. Most gaze-based interaction applications are supported by estimation techniques that find a mapping between gaze data and corresponding targets on a 2D surface. This approach inevitably leads to a biased outcome, as the nearest objects in the line of sight will tend to be the target of interest more often. One viable solution would be to estimate gaze as a 3D coordinate (x, y, z) rather than the traditional 2D coordinate (x, y). This article first introduces a new comprehensive 3D gaze dataset collected in a realistic scene setting. Data was collected using a head-mounted eye-tracker and a depth estimation camera. Next, we present a novel depth estimation model, trained on the new gaze dataset to accurately predict gaze depth based on calibrated gaze vectors. This method could help develop a mapping between gaze and 3D objects on a 3D plane. The presented model improves the reliability of depth measurement of visual attention in real scenes as well as the accuracy of depth-based scenes in virtual reality environments. Improving situational awareness using 3D gaze data will benefit several domains, particularly human-vehicle interaction, autonomous driving, and augmented reality. © 2023 SPIE.

关键词： Mapping

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White Bread Mold Detection using K-Means Clustering Based on Grey Level Co-Occurrence Matrix and Region of Interest

White Bread Mold Detection using K-Means Clustering Based on...

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International Seminar on Application for Technology of Information and Communication (ISemantic)

作者： Qori Alfatah Putra Christy Atika Sari Eko Hari Rachmawanto Nur Ryan Dwi Cahyo Edy Mulyanto Mohamed Ayad Alkhafaji Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Department of Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Department of Computer Science National University of Science and Technology DhiQar Iraq

This research paper presents a bread mold identification system that utilizes digital image processing techniques, specifically K-means clustering and thresholding, to accurately detect and classify mold-infected areas on bread. The system aims to provide valuable information regarding the safety of consuming mold-contaminated bread, enabling consumers to make informed decisions and reduce the risk of health issues associated with consuming mold-infested bread. the K-means clustering algorithm for mold classification, considering factors such as the number of iterations and the distance metric within the feature space to determine its accuracy. The GLCM feature extraction technique is employed to extract texture information from bread images, encompassing features such as standard deviation (110.62), contrast (1.46), energy, and homogeneity (0.96 and 0.77, respectively). Experimental results demonstrate that the Euclidean Distance yielded the highest result of 72.73, the Cosine Distance obtained the highest result of 8.25, and the City Block Distance obtained the highest result of 92.11. These findings showcase the effectiveness of the system in accurately detecting and classifying mold-infected areas on bread, thereby aiding in ensuring food safety and reducing health risks for consumers.

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Based-on computer Vision Applications for Bus Stop Passenger Detection System

Based-on Computer Vision Applications for Bus Stop Passenger...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Yu-Cheng Chang Hua-Wen Tsai Chao-Yi Huang Zong-Rong Wu Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taiwan Department of Bachelor's Program in Intelligent Robot National Yunlin University of Science and Technology Taiwan Department of Technical and Vocational Program in Artificial Intelligence National Yunlin University of Science and Technology Taiwan

Passenger transport is one of the most common ways of commuting in Taiwan. It plays an important role in the transportation system due to its large number of stations, dense frequency, and cheap transportation. Due to the unfriendly transportation environment and a large number of passengers, a blind spot of passenger transportation exists, which leads to traffic accidents at the station. We research to make the "Bus Stop Passenger Detection System". Taking the object detection of "Wheelchairs" into consideration, it is more convenient to assist the disabled to find the passenger transportation system, which makes Taiwan's transportation system more convenient.

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Mechanism of Threshold Voltage Instability in Double Gate α-IGZO Nanosheet TFT under Bias and Temperature Stress

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IEEE Journal of the Electron Devices Society 2024年 12卷 464-471页

作者： Aslam, Muhammad Chang, Shu-Wei Chen, Yi-Ho Lee, Yao-Jen Li, Yiming Lee, Wen-Hsi Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electrical Engineering National Cheng Kung University Tainan City701401 Taiwan Institute of Pioneer Semiconductor Innovation Industry Academic Innovation School National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

Amorphous indium gallium zinc oxide (a-IGZO)-based thin film transistors (TFTs) are increasingly becoming popular because of their potential in futuristic applications, including CMOS technology. Given the demand for CMOS-compatible, ultra-scaled, reliable, and high-performing devices, we fabricate and analyze scaled-channel a-IGZO-TFTs with an optimal double-gate structure, a thin nanosheet-based channel, and an effective high- κ dielectric namely HfO2. The reliably reported double gate IGZO nanosheet TFTs (DG-IGZO-NS-TFTs) are tested under positive and negative bias stress at variant temperatures, and the resulting modulations are analyzed critically. The reported DG-IGZO-NSTFTs exhibit a negative side threshold voltage shift (Δ Vth) accompanied by an increase in Ion/Ion(0) under negative bias temperature stress (NBTS) at elevated temperatures, which indicates the presence of additional charges. An anomalous negative side shifting of the Vth is observed under positive bias temperature stress (PBTS), where diffused hydrogen atoms are identified as introducing excess n-type carriers into the channel and causing the observed Δ Vth. The spectroscopic analysis is performed to establish evidence for the assumed mechanisms, and the role of individual gates is investigated in the context of performance variance under temperature-bias stress. Moreover, the partial reversibility of the stress-induced degradation is experimentally established and methodically discussed. Overall, the reported results offer a comprehensive understanding of scaled-channel DG-NS-IGZO-TFTs, which help shape performance-enhancement strategies, control degradation mechanisms, and define appropriate application scenarios. © 2013 IEEE.

关键词： Thin film transistors

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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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Social Media Analysis using Sentiment Analysis on COVID-19 from Twitter

Social Media Analysis using Sentiment Analysis on COVID-19 f...

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International Conference on Information Technology, Information Systems and Electrical engineering (ICITISEE)

作者： Fairuz Iqbal Maulana Yaya Heryadi Lukas Wayan Suparta Yulyani Arifin Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

The development of the internet is getting faster, participating in encouraging the emergence of new and innovative information. In filtering the various information that appears, we need a recommended system to perform well for users in today's internet era. A well-performing recommendation system in question is a reliable recommendation algorithm. This algorithm is fundamental to analyzing various information, such as responses on social media based on user behavior data related to the topic of COVID. This data is crawled from tweets on social media Twitter. The data analysis algorithm obtained uses Python, which is then visualized in the form of a diagram. The processed data is user comments on Twitter, and the text data is analyzed using Python, using more than 60000 data sets taken to form visualizations and conclusions. From sentiment analysis, polarity and subjectivity data are obtained to be analyzed, which are negative, neutral, or positive. The result is show positive tweets with 29.2%, negative tweets is 13%, and 57.8% neutral tweets. Lastly, sentiment analysis can help people effectively infer vast and complex data from social media like Twitter.

关键词： COVID-19 Sentiment analysis Analytical models Data analysis Social networking (online) Blogs Data visualization

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Zema Dataset: A Comprehensive Study of Yaredawi Zema with a Focus on Horologium Chants

arXiv

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arXiv 2024年

作者： Muluneh, Mequanent Argaw Peng, Yan-Tsung Degife, Worku Abebe Tadesse, Nigussie Abate Demeku, Aknachew Mebreku Su, Li Institute of Information Science Academia Sinica Taipei Taiwan Department of Information System University of Gondar Gondar Ethiopia Department of Computer Science National Chengchi University Taipei Taiwan Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Taiwan Department of Information Management National Taiwan University of Science and Technology Taipei Taiwan Department of Material Science and Engineering National Taiwan University of Science and Technology Taipei Taiwan

Computational music research plays a critical role in advancing music production, distribution, and understanding across various musical styles in the world. Despite the immense cultural and religious significance, the Ethiopian Orthodox Tewahedo Church (EOTC) chants are relatively underrepresented in computational music research. This paper contributes to this field by introducing a new dataset specifically tailored for the analysis of EOTC chants, also known as Yaredawi Zema. This work provides a comprehensive overview of a 10-hour dataset, 369 instances, creation, and curation process, including rigorous quality assurance measures. Our dataset has a detailed word-level temporal boundary and reading tone annotation along with the corresponding chanting mode label of audios. Moreover, we have also identified the chanting options associated with multiple chanting notations in the manuscript by annotating them accordingly. Our goal in making this dataset available to the public1 is to encourage more research and study of EOTC chants, including lyrics transcription, lyric-to-audio alignment, and music generation tasks. Such research work will advance knowledge and efforts to preserve this distinctive liturgical music, a priceless cultural artifact for the Ethiopian people. © 2024, CC BY.

关键词： Music

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Sum-Rate Maximization for Intelligent Reflecting Surface Assisted MIMO SWIPT Systems 6

Sum-Rate Maximization for Intelligent Reflecting Surface Ass...

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6th IEEE Symposium on Future Telecommunication Technologies, SOFTT 2022

作者： Liong, H.J. Chiong, C.W.R. Gopal, Lenin Juwono, Filbert H. Curtin University Malaysia Department of Electrical and Computer Engineering Miri Sarawak98009 Malaysia University of Southampton Malaysia Eko Galleria Department of Electrical and Electronic Engineering Nusajaya Johor79100 Malaysia University of Southampton Malaysia Eko Galleria Computer Science Program Nusajaya Johor79100 Malaysia

ISBN: (纸本)9781665455978

Intelligent reflecting surface (IRS) has recently stimulated an upsurge of research interest due to its capability of enhancing the spectral and energy efficiencies for future sixth generation (6G) wireless communication systems. This motivates the integration of IRS into simultaneous wireless information and power transfer (SWIPT) systems to improve the performance of energy harvesting and information de-coding. To unleash the full potential of IRS and achieve high sum-rate, the optimal joint transmitter precoding and reflective beamforming design is crucial yet challenging to solve. The issue has not been well investigated and the solution remains elusive. Hence, this research aims to jointly optimize the transmitter precoding and reflective beamforming matrices for IRS-Assisted multi-user multiple-input multiple-output (MIMO) SWIPT systems under quality of service (QoS) constraints. Simulation results demonstrate the effectiveness of IRS in enhancing the system performance. © 2022 IEEE.

关键词： Beamforming

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