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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Lu, Bright Xu, Bo Krueper, Greg Zohrabi, Mo Gopinath, Juliet T. Park, Wounjhang Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States Department of Physics University of Colorado BoulderCO80309 United States Materials Science and Engineering Program University of Colorado BoulderCO80309 United States

ISBN: (纸本)9781957171395

We report Ge23Sb7S70 chalcogenide ring resonators with up to 8 × 104 quality factors operating around 3.6 µm wavelength fabricated through e-beam lithography. Their rib waveguide geometry can be engineered to support close-to-zero dispersion modes needed for mid-infrared microcomb generation. CLEO 2024 © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Ring lasers

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Peak Picking Multiple Onset Detection Functions Using Recurrent Neural Networks 22

Peak Picking Multiple Onset Detection Functions Using Recurr...

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10th International Conference on computer and Communications Management, ICCCM 2022

作者： Xuan, Mobai Mizutani, Tetsuya Master's Program in Computer Science University of Tsukuba Japan Department of Information Engineering University of Tsukuba Japan

ISBN: (纸本)9781450396349

Onset detection is a fundamental task in music information retrieval (MIR). Classical approaches using onset detection functions (ODFs) and hand-crafted peak-picking methods are outperformed by those utilizing neural networks, which are considered state-of-the-art. However, these methods bring much more computational costs and thus can be unfavored when implementing onset detections on low-performance devices. Previous work utilizing both an ODF and a recurrent neural network (RNN) provides another option as a trade-off between accuracy and processing speed. However, it only used one single ODF for the input of the network. In the present study, we propose a novel method utilizing multiple ODFs and an RNN fusing these ODFs, together with several techniques in training the network and peak-picking. Our proposed method outperformed previous work by approximately 1% at the cost of a halved processing speed, serving as another option for trading-off between accuracy and speed. One of our future works is looking for other ODFs that can be both fast-calculating and beneficial to accuracy. © 2022 ACM.

关键词： Recurrent neural networks

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The Implementation of TOGAF for Enterprise System Planning on XYZ Campus

The Implementation of TOGAF for Enterprise System Planning o...

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2023 International Conference on Networking, Electrical engineering, computer Science, and Technology, IConNECT 2023

作者： Sirait, Tamsir Hasudungan Lumban Gaol, Ford Supangkat, Suhono Harso Ranti, Benny Bina Nusantara University Binus Graduate Program Computer Science Jakarta Indonesia Bina Nusantara University Computer Science Department Jakarta Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia Universitas Indonesia Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350331172

Universities can employ information technology as one means of achieving their goals and objectives. Universities can get advantages from information technology, such as effective resource management and information management for decision-making. However, don't forget that the campus must consider what technology is appropriate to assist them achieve their goals, particularly in the current industrial era 4.0 where technology is available with many different choices. The campus requires an enterprise architecture in order to design, manage, and coordinate information technology infrastructure, applications, and processes strategically and thoroughly. The adoption of enterprise information system architecture (EA) is also intended to improve the quality of services provided to internal and external stakeholders. In this case, Enterprise Architecture can help an organization to match its information technology resources with business processes and strategies to achieve their goals. This research was conducted using TOGAF ADM, also known as the Open Group Architecture Framework Architecture Development Method. This method offers best practices for creating enterprise architecture and emphasizes several steps that include creating an architectural vision, information systems, business architecture modeling to help XYZ campus manage all their information technology. © 2023 IEEE.

关键词： Information management

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A Feasibility Study: Magnetic Field Monitoring in Cycled Lead Acid Cells for Stationary Applications

A Feasibility Study: Magnetic Field Monitoring in Cycled Lea...

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IEEE Electrical Energy Storage Application and Technologies Conference (EESAT)

作者： Scarleth Vasconcelos Pritpal Singh Ross Lee Sustainable Engineering Program Villanova University Villanova USA Dept of Electrical and Computer Engineering Villanova University Villanova USA

ISBN: (数字)9798331524852

ISBN: (纸本)9798331536411

This research introduces a novel, real-time, non-invasive, non-destructive, and accurate method for battery mon-itoring using magnetic field mapping. This technique detects stratification in flooded Lead Acid Batteries at different states of charge, providing early notification by monitoring variations in hydrogen ion concentration during cycling. The study tracked pH and magnetic field variations across $H_{2}SO_{4}$ electrolyte specific gravities ranging from 1.07 to 1.33, showing a 17%-20% pH reduction over 12 hours, indicating acid stratification. A proof-of-concept using air-core solenoid coils demonstrated a direct correlation between secondary coil output voltage and $H_{2}SO_{4}$ concentrations, influenced by the induced magnetic field at the primary coil and electrolyte concentration changes. The optimal AC input frequency for maximizing the induced magnetic field mapping response was identified as 30–33 kHz, depending on the physical properties of the magnetic field inductors. An inverse correlation was also observed between the induced magnetic field and the distance between the coils. This approach offers a promising alternative for lead acid battery monitoring, potentially improving battery management and lifespan. The experimental tests also included monitored variations in secondary coil output voltage in a single flooded lead acid cell during cycling. The preliminary results demonstrated a decrease in the magnetic field during charge and an increase during discharge.

关键词： Coils Lead acid batteries Correlation Voltage measurement Electrolytes Discharges (electric) Lead compounds Magnetic fields Solenoids Monitoring

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High-quality Mid-infrared Chalcogenide Ring Resonator

High-quality Mid-infrared Chalcogenide Ring Resonator

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Infrared devices

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Classifying Tweet Sentiment Analysis on Airlines using Random Forest Classifier, Naïve Bayes Classifier and K-Nearest Neighbors Classifier Algorithm

Classifying Tweet Sentiment Analysis on Airlines using Rando...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Alexander, Ivan Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Bina Nusantara University Binus Graduate Program Computer Science Computer Science Departement Jakarta11480 Indonesia Universitas Katolik Indonesia Atma Jaya Cognitive Engineering Research Group Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350327472

Opinion has always affected businesses and individuals especially from the Public. People react through social media and spread it incompletely. The situation was then accepted as public opinion. There are three categories of opinion i.e., positive, negative, and neutral. To investigate public opinion on a particular issue of interest, sentiment analysis might be employed. By offering a solution to the text classification challenge, this experiment focuses on the perception of airline tweets among the American public. We offer a method to classify tweets as positive, negative, or neutral using three machine learning classifiers: Random Forest Classifier, Naive Bayes Classifier, and K-Nearest Neighbors Classifier. We examined the performance of three machine learning classifiers in terms of accuracy, average precision, average recall, and average f-1 score. The results demonstrate that the Random Forest Classifier, which produces 82% accuracy, 80% average precision, 82% average recall, and 80% average f1-score, performs the best among the machine learning classifiers. © 2023 IEEE.

关键词： Tweets

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Prediction of Post-COVID-19 Pandemic Learning Mode Preferences Using Machine Learning 14

Prediction of Post-COVID-19 Pandemic Learning Mode Preferenc...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Pratondo, Agus Novianty, Astri Putro, Budi Laksono Komala Sari, Siska Telkom University School of Applied Sciences Department of Multimedia Engineering Bandung Indonesia Telkom University School of Electrical Engineering Department of Computer Engineering Bandung Indonesia Indonesia University of Education Department of Computer Science Education Bandung Indonesia Telkom University School of Applied System Diploma Program of Information System Bandung Indonesia

ISBN: (纸本)9798350335095

The COVID-19 epidemic has had a huge impact on the educational landscape, prompting the adoption of online and remote learning as viable alternatives to conventional in-person instruction. In order to create effective educational methods as institutions prepare for the post-pandemic period, it is essential to understand students' preferences for various learning modes. With the aid of machine learning techniques, this study seeks to forecast preferences for learning styles in post-pandemic higher education. The study made use of a dataset compiled from a wide range of college students, which included information on the institution type (public or private), program type (bachelor's or diploma), academic discipline (science or humanities), gender, year of study, internet use, communication costs, comorbidity status, vaccination history, gadget and laptop ownership, and preferred learning mode (online, in-person, or both). For the aim of prediction, a Support Vector Machine (SVM) was used. Its kernel functions included linear, polynomial, radial basis function (RBF), and sigmoid. Performance criteria like accuracy, precision, recall, and F1 score were used to assess the models after the dataset was randomly partitioned into training and testing sets. The findings showed that for identifying the preferred mode of learning, SVM with the RBF kernel had the highest prediction accuracy (91.67%). Further proving the RBF kernel's efficacy, the confusion matrix analysis showed that high values in the diagonal represented accurate predictions for each of the three classes (both online and onsite). The results imply that machine learning approaches, in particular SVM with the RBF kernel, may accurately forecast students' preferences for learning modes in the post-pandemic situation. In a post-pandemic society, the findings provide insightful information that may be used to build adaptable and inclusive learning models and put them into practice. © 2023 IEEE.

关键词： Support vector machines

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A Fitness Movement Evaluation System Using Deep Learning 15

A Fitness Movement Evaluation System Using Deep Learning

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15th International Conference on Knowledge and Systems engineering, KSE 2023

作者： Chang, Chin-Chih Wei, Chi-Hung Wu, Hao-Wei Hsiao, Sean Chung Hua University Department of Computer Science and Information Engineering Hsinchu City Taiwan Ph.D. Program in Engineering Science Chung Hua University Hsinchu City Taiwan Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu City Taiwan

ISBN: (纸本)9798350329742

This paper proposes a fitness movement evaluation system using deep learning. The system uses a deep convolutional neural network (CNN) to extract features from pictures of fitness movements. The features are then used to classify the movements into different categories. The system is evaluated on a dataset of pictures of fitness movements. The results show that the system can accurately classify the movements into different categories. The system is designed to provide feedback to users on their fitness movements. The proposed system is a valuable tool for fitness enthusiasts. The main contribution of this paper is to propose a way to give users a score for their fitness movement. It can help users improve their fitness and track their progress over time. The system is also a valuable tool for fitness professionals. It can help professionals develop new fitness programs and provide feedback to their clients. © 2023 IEEE.

关键词： Convolutional neural networks

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Bubble-pen lithography:Fundamentals and applications

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Aggregate 2022年第4期3卷 85-100页

作者： Pavana Siddhartha Kollipara Ritvik Mahendra Jingang Li Yuebing Zheng Walker Department of Mechanical Engineering The University of Texas at AustinAustinTexasUSA Department of Electrical and Computer Engineering The University of Texas at AustinAustinTexasUSA Material Science and Engineering Program Texas Materials InstituteThe University of Texas at AustinAustinTexasUSA

Developing on-chip functional devices requires reliable fabrication methods with high resolution for miniaturization,desired components for enhanced performance,and high throughput for fast prototyping and mass ***,laser-based bubble-pen lithography(BPL)has been developed to enable sub-micron linewidths,in situ synthesis of custom materials,and on-demand patterning for various functional components and *** exploits Marangoni convection induced by a laser-controlled microbubble to attract,accumulate,and immobilize particles,ions,and molecules onto different *** years have witnessed tremendous progress in theory,engineering,and application of BPL,which motivated us to write this ***,an overview of experimental demonstrations and theoretical understandings of BPL is ***,we discuss the advantages of BPL and its diverse applications in quantum dot displays,biological and chemical sensing,clinical diagnosis,nanoalloy synthesis,and *** conclude this review with our perspective on the challenges and future directions of BPL.

关键词： additive manufacturing capillary flow lithography marangoni convection microbubbles sensing

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Applying ant colony optimization algorithm to solve flying probe inspection problem

Applying ant colony optimization algorithm to solve flying p...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Chen, Chih-Yung Chang, Yu-Ming National Pingtung University of Science and Technology Program in Artificial Intelligence and Mechatronics Pingtung Taiwan Shu-Te University Department of Computer Science and Information Engineering Kaohsiung Taiwan

ISBN: (纸本)9798350324174

This paper applies ant colony optimization (ACO) algorithm for the dual-pin flying probe circuit board inspection optimal path searching problem. First, the proposed approach creates a representation for circuit inspection path, which groups and encodes the measurement endpoints into a sequence. Moreover, the ant colony algorithm with the sequence can be used to solve the complex circuit optimal problem. The experimental results show that the best solutions of ACO are performed better than other algorithms. © 2023 IEEE.

关键词： Inspection

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