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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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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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Impact of Multimedia Sensor Placement to Car Licence Number Detection 2022

Impact of Multimedia Sensor Placement to Car Licence Number ...

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11th International Conference on Software and computer Applications, ICSCA 2022

作者： Amelia, Afritha Zarlis, Muhammad Suherman, Suherman Efendi, Syahril Graduate Program of Computer Science Faculty of Computer Science and Information Technology University of Sumatera Utara Indonesia Computer Science Faculty of Computer Science and Information Technology University of Sumatera Utara Indonesia Electrical Engineering Faculty of Engineering University of Sumatera Utara Indonesia

ISBN: (纸本)9781450385770

A vehicle has a license plate and can be identified by the license number attached to the vehicle plate. For detection and recognition, multimedia sensors can be used so that it requires a vehicle tracking application that has a vehicle monitoring function and has implications for various fields. One of them is a multimedia sensor that requires an optimal design and method in the form of the number of multimedia sensors to be used, the placement of the multimedia sensor positions and solutions in the event of a system failure. To achieve multimedia sensor performance, research on multimedia sensors is carried out using a camera type with Phase Detection Auto Focus (PDAF) technology which is similar to a pair of right and left eyes to see an object. The objects detected were 2 cars, where the car passed the camera sensor at a speed of 10-15 km/hour 20 times. Changes in the distance of the vehicle to the camera affect the disparity value and the object's accuracy value, namely and the object's Accuracy value of the minimum disparity value of 6.20×106 of 16.88×109. © 2022 ACM.

关键词： Disparity Vehicle plate Phase Detection Auto Focus (PDAF) Tracking application Object accuracy

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Normality Addition via Normality Detection in Industrial Image Anomaly Detection Models

arXiv

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arXiv 2024年

作者： Yi, Jihun Jung, Dahuin Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of School of Computer Science and Engineering Soongsil University Seoul Korea Republic of Department of Electrical and Computer Engineering and Interdisciplinary Program in AI Seoul National University Seoul Korea Republic of

The task of image anomaly detection (IAD) aims to identify deviations from normality in image data. These anomalies are patterns that deviate significantly from what the IAD model has learned from the data during training. However, in real-world scenarios, the criteria for what constitutes normality often change, necessitating the reclassification of previously anomalous instances as normal. To address this challenge, we propose a new scenario termed "normality addition," involving the post-training adjustment of decision boundaries to incorporate new normalities. To address this challenge, we propose a method called Normality Addition via Normality Detection (NAND), leveraging a vision-language model. NAND performs normality detection which detect patterns related to the intended normality within images based on textual descriptions. We then modify the results of a pre-trained IAD model to implement this normality addition. Using the benchmark dataset in IAD, MVTec AD, we establish an evaluation protocol for the normality addition task and empirically demonstrate the effectiveness of the NAND method. Copyright © 2024, The Authors. All rights reserved.

关键词： Visual languages

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Early Detection of Heart Rate Conditions in Autistic Children Using IoT-Based Systems

Early Detection of Heart Rate Conditions in Autistic Childre...

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International Conference on electrical engineering and computer Science (ICECOS)

作者： Nizam Albar Melinda Melinda Yuwaldi Away dept. Electrical Engineering Master of Electrical Engineering Study Program Universitas Syiah Kuala Banda Aceh Indonesia dept. Electrical Engineering and Computer Engineering Faculty Universitas Syiah Kuala Banda Aceh Indonesia

ISBN: (数字)9798350368253

ISBN: (纸本)9798350368260

Early detection of heart rate conditions in autistic children is crucial for anticipating tantrum reactions and providing prompt medical intervention. Previous research designed a prototype for acquiring Electrocardiogram (ECG) signals using the AD8232 sensor, but it required a long time to identify heart rate conditions. This study aims to develop the previous prototype using Internet of Things (IoT) implementation to acquire and identify the heart rate conditions of autistic children in real time. The ECG signal data is analyzed using Butterworth Filter and Artificial Neural Network (ANN) integrated into Raspberry Pi and results are transmitted to the Blynk App. Testing over 20 minutes showed that in the first 10 minutes, the system identified a normal heart rate at 105.19 BPM with 67% accuracy, while in the second 10 minutes, the heart rate rose to 117.19 BPM with tantrum symptoms and 75% accuracy. This system helps medical personnel provide immediate intervention during tantrums.

关键词： Heart rate Pediatrics Accuracy Prototypes Artificial neural networks Electrocardiography Real-time systems Internet of Things Servers Testing

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Plasmonic BICs as Biosensors with Better Detectivity

Plasmonic BICs as Biosensors with Better Detectivity

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Li, Zhichao Prasad, Ciril S. Wang, Xielin Naik, Gururaj V. Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States

Plasmonic sensors exhibit high sensitivity due to enhanced local fields. But, their detectivity is poor because of their poor Q-factors. Using a plasmonic BIC, we experimentally demonstrate enhanced Q-factors in a pla... 详细信息

ISBN: (纸本)9781957171258

关键词： Q factor measurement

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Spectral DiffuserScope - Computational Snapshot Hyperspectral Imager for Microscopy

Spectral DiffuserScope - Computational Snapshot Hyperspectra...

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2023 Computational Optical Sensing and Imaging, COSI 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： Aggarwal, Neerja Markley, Eric Raniwala, Yashovardhan Houck, William D. Lee, Kyung Chul Bae, Junghyun Baek, Nakkyu Park, Wook Lee, Seung Ah Waller, Laura Department of Electrical Engineering and Computer Sciences University of California Berkeley United States UCB/UCSF Joint Graduate Program in Bioengineering University of California Berkeley United States VIAVI Solutions Inc Santa Rosa United States School of Electrical and Electronic Engineering Yonsei University Seoul Korea Republic of

We introduce a computational snapshot hyperspectral imager for benchtop microscopy. The compact device uses a diffuser and spectral filter array to multiplex spatio-spectral information into a 2D measurement, then rec... 详细信息

ISBN: (纸本)9781957171289

关键词： Blue light emitting diodes Diffusers Fluorescence microscopy Image sensors Spatial resolution Ultraviolet light emitting diodes

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MODELING THE HODGKIN-HUXLEY NEURON TO DETERMINE NEURONAL ENERGY CONSUMPTION EFFICIENCY AND OXYGEN CONSUMPTION VALUES

Biomedical Sciences Instrumentation

引用

Biomedical Sciences Instrumentation 2022年第2期58卷 50-58页

作者： Enochson, Avery Ewert, Daniel Mitar, Dipankar Striker, Ryan Cleveland, Jerika Wolf, Henry Gieser, Anna Braaten, Ben Allen, Jeffery Allen, Monica Department of Integrated Engineering at Iron Range Engineering Program of Minnesota State University Mankato MN United States Department of Computer Science and Computer Engineering University of Wisconsin – La Crosse La CrosseWI United States Department of Electrical and Computer Engineering North Dakota State University FargoND United States Air Force Research Laboratory Munitions Directorate Eglin Air Force Base Eglin AFB FL United States

Understanding neuronal structure and function is essential to studying the human brain. The goal of this project was to create a model of human brain neurons that accurately reflects neuronal function, energy consumption, and oxygen consumption. Extensive work has been performed on the Hodgkin-Huxley model of neurons to accurately model neuronal firing. This study focuses on the creation of a model of the Hodgkin-Huxley neuron in MATLAB with the assistance of the DynaSim toolbox. This model was used to compute values and using another model the energy efficiency of the neuron was calculated and related to oxygen consumption, which then corresponds to Blood Oxygenation Level Dependent (BOLD) imaging in fMRI. The results of this study provide detailed visual and technical information about how the brain neurons function, which is crucial to the further development in brain imaging techniques and to further our understanding of why and how our complex brains function. © 2022 IAE All rights reserved.

关键词： Neurons

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One-Way Quantum Repeater with Rare-Earth-Ions Doped in Solids

arXiv

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arXiv 2024年

作者： Lei, Yisheng Department of Electrical and Computer Engineering and Applied Physics Program Northwestern University EvanstonIL60208 United States

Quantum repeaters are proposed to overcome exponential photon loss over distance in fibers. One-way quantum repeaters eliminate the need for two-way classical communications, which can potentially outperform quantum memory based quantum repeaters. I propose that rare-earth-ions doped in solids and coupled with nano-cavity can be used to generate photonic cluster state efficiently, which serve as good platforms for one-way quantum repeater nodes. In addition, I propose a multiplexed scheme of photonic tree cluster state generation with multiple quantum emitters. With less than 100 quantum emitters, secret key rates can reach the order of MHz over a few thousand kilometers. This proposal is especially useful for generating large scale photonic cluster state, which is essential for correcting operational errors during processing in quantum repeater nodes. © 2024, CC BY.

关键词： Metal ions

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Quality Analytics for Latin American and Brazilian Robotics Symposiums

Quality Analytics for Latin American and Brazilian Robotics ...

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2024 Brazilian Symposium on Robotics (SBR), and 2024 Workshop on Robotics in Education (WRE)

作者： Luiz Marcos Garcia Gonçalves Electrical and Computer Engineering Graduate Program Universidade Federal do Rio Grande do Norte Natal Brazil

ISBN: (数字)9798350391084

ISBN: (纸本)9798350391091

We bring historical findings related to the most important Latin American and Brazilian Robotics Symposiums including their quality analytics regarding all papers published since their creation. For this quality analysis, we first provide a little of history and then we apply a methodology based on a systematic mapping of the literature using Scopus (from Elsevier) and Web of Science. The quality analysis includes variables as citations metrics, and also other historical variables as participation per countries, per states, per universities, and contributed areas among others. We use metadata and tools available in the most commonly used digital libraries, for a fair comparison. To the end, with basis on the results of our methodological approach, we point out that the community has followed the right path for establishing a high quality event, mainly regarding the decision of publication of the proceedings at IEEE Xplore, and recently in the Brazilian computer Society Library (Sol-SBC), all together. Also, our analysis corroborate to verify the modi operandi that have been used in the events execution, including joining in the Workshop of Robotics in Education (WRE) and the competitions (RCB, OBR, MNR, CBR, LARC). Besides happening jointly, each event keeps their original event structure and characteristics.

关键词： Measurement Systematics Conferences Education Metadata Libraries History Robots

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