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Absolute gradient algorithm for adaptive IIR notch filter

Absolute gradient algorithm for adaptive IIR notch filter

2012 9th International Conference on Electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON 2012

作者： Nosan, A. Punchalard, R. Computer Engineering Graduate Program Faculty of Engineering Mahanakorn University of Technology Bangkok Thailand Department of Telecommunication Engineering Mahanakorn University of Technology Bangkok Thailand

ISBN: (纸本)9781467320245

The gradient algorithm used absolute value of error signal as a criterion to adjust the filter coefficient of adaptive IIR notch filter is presented in this paper. The objective is to estimate or track the frequency of a single sinusoidal signal corrupted by additive white Gaussian noise. The proposed algorithm can solve the problem of selecting an initial condition as met in the previous method. Moreover, it also has a high convergence speed. © 2012 IEEE.

关键词： Notch filters

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Real Time Chest X-Ray Interpretation Applying Vision Transformer for Tuberculosis Detection

Real Time Chest X-Ray Interpretation Applying Vision Transfo...

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2024 International Conference on computer engineering, Network and Intelligent Multimedia, CENIM 2024

作者： Irhamsyah, Muhammad Roslidar Yunidar Al Lail Qadrillah, M. Nasaruddin Arnia, Fitri Munadi, Khairul Universitas Syiah Kuala Post Graduate Program in Engineering Banda Aceh2311 Indonesia Faculty of Engineering Department of Electrical and Computer Engineering 2311 Indonesia

ISBN: (纸本)9798350368802

Tuberculosis (TB) is an infectious disease that can attack the lungs and other organs. In the diagnosis of TB, the interpretation of X-ray radiological images requires special skills from medical specialists. However, the lack of experience of medical personnel and focus on X-ray examinations can be a challenge for radiologists because it has the potential to cause diagnostic errors in image interpretation. Therefore, we proposed a web-based application of real-time chest X-ray interpreter by integrating the deep learning model of Vision Transformer (ViT) to interpret chest X-ray images. The inference model was trained and tested on 652 normal and 652 tuberculosis X-ray images. The data preprocessing of Contrast Adaptive Histogram Equalization (CLAHE) was implemented to increase chest X-ray image contrast as well as inference model performance. The proposed real time system can inteprete the tested chest x-ray images with an accuracy of 95% and with simulation duration time of 4.7 seconds. © 2024 IEEE.

关键词： Diagnosis

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LSTM with Adam Optimization-Powered High Accuracy Preeclampsia Classification 21

LSTM with Adam Optimization-Powered High Accuracy Preeclamps...

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21st International Electronics Symposium, IES 2019

作者： Sakinah, Nur Tahir, Muhlis Badriyah, Tessy Syarif, Iwan Politeknik Elektronika Negeri Surabaya Graduate Program of Engineering Technology Surabaya Indonesia Computer Graphic Engineering Technology Study Program Politeknik Negeri Sambas Kalimantan Barat Indonesia

ISBN: (纸本)9781728144498

Preeclampsia is a pregnancy complication characterized by high blood pressure and signs of damage to another organ system, most often the liver and kidneys. Preeclampsia usually begins after 20 weeks of pregnancy in women whose blood pressure had been normal. To anticipate the risk of preeclampsia and prevent the death of pregnant women, a predictive system is needed for preeclampsia. to predict this, the data obtained will be studied to recognize patterns for predicting preeclampsia. Artificial neural network is one method that has the ability to learn patterns from a data. The system built in this study is to use the artificial neural network method by using the architecture of Long Short-Term Memory (LSTM) Neural Networks. But this technique requires the right parameters to get accurate predictions. In this paper analyze several parameters such as number of time series patterns, number of hidden neurons, max epoch, and composition of training and test data on the accuracy of the predictions obtained. The results of the analysis showed that the system built was able to predict Preeclampsia well, with an average accuracy rate of 90.22% for data testing. © 2019 IEEE.

关键词： Long short-term memory

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Electrically Reconfigurable Intelligent Optoelectronics in 2-D van der Waals Materials

arXiv

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arXiv 2025年

作者： Wang, Yu Zhang, Dehui Song, Yihao Lee, Jea Jung Tian, Meng Biswas, Souvik Xia, Fengnian Guo, Qiushi Photonics Initiative Advanced Science Research Center City University of New York 85 St Nicholas Terrace New YorkNY10031 United States Physics Program Graduate Center City University of New York 365 5th Ave New YorkNY10016 United States Department of Electrical Engineering and Computer Sciences University of California Berkeley 566 Cory Hall BerkeleyCA94720 United States Department of Electrical Engineering Yale University 15 Prospect St New HavenCT06511 United States E. L. Ginzton Laboratory Stanford University 348 Via Pueblo Mall StanfordCA94305 United States

In optoelectronics, achieving electrical reconfigurability is crucial as it enables the encoding, decoding, manipulating, and processing of information carried by light. In recent years, two-dimensional van der Waals (2-D vdW) materials have emerged as promising platforms for realizing reconfigurable optoelectronic devices. Compared to materials with bulk crystalline lattice, 2-D vdW materials offer superior electrical reconfigurability due to high surface-to-volume ratio, quantum confinement, reduced dielectric screening effect, and strong dipole resonances. Additionally, their unique band structures and associated topology and quantum geometry provide novel tuning capabilities. This review article seeks to establish a connection between the fundamental physics underlying reconfigurable optoelectronics in 2-D materials and their burgeoning applications in intelligent optoelectronics. We first survey various electrically reconfigurable properties of 2-D vdW materials and the underlying tuning mechanisms. Then we highlight the emerging applications of such devices, including dynamic intensity, phase and polarization control, and intelligent sensing. Finally, we discuss the opportunities for future advancements in this field. Copyright © 2025, The Authors. All rights reserved.

关键词： Van der Waals forces

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Sentiment Analysis in Indonesian Trading using Lexicon-based and Support Vector Machine

Sentiment Analysis in Indonesian Trading using Lexicon-based...

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2023 International Conference on computer Science, Information Technology and engineering, ICCoSITE 2023

作者： Oetama, Raymond Sunardi Yanfi, Yanfi Ikhsan Assiddiq Up, Masagus M. Muhamad Isa, Sani Universitas Multimedia Nusantara Information System DepartmentFaculty of Engineering and Informatics Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350320954

Many individuals now trade online utilizing trading software in the digital world. Binomo is one of Indonesia's most popular trading platforms. This is because some influencers made several promises to Binomo customers. Since many customers were deceived, this case became quite popular. This study was executed to see how Indonesians felt about the Binomo application after the case went viral. The solution taken was in the form of sentiment analysis because there had been no previous research on sentiment analysis that discussed the Binomo case. The data was scanned using Netlytic tools, a cloud-based text and social network analyzer capable of identifying any talks on social media sites such as Twitter. The sentiment analysis of Binomo trading tweets by using the Multi-Perspective Question Answering lexicon utilized the KNIME tool. But unfortunately, the accuracy of sentiment analysis results is low. Furthermore, the Support Vector Machine technique is also being conducted. The Term Frequency-Inverse Document Frequency method is applied to perform feature extraction whilst the chi-square approach is utilized to identify features that are thought to be useful for inclusion in the classification process and to exclude features that are irrelevant to the target class. The obtained accuracy is 86%. The study proposes that words from the algorithm's outputs can be utilized to improve the quality of sentiment analysis using the lexicon. As an outcome of the algorithm, positive and negative terms are added to the lexicon, increasing the accuracy of sentiment analysis using the new vocabulary from 58.984% to 71.146%. © 2023 IEEE.

关键词： Support vector machines

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A kernel method for MicroRNA target prediction using sensible data and position-based features

A kernel method for MicroRNA target prediction using sensibl...

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2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05

作者： Kim, Sung-Kyu Nam, Jin-Wu Lee, Wha-Jin Zhang, Byoung-Tak Graduate Program in Bioinformatics School of Computer Science and Engineering Seoul National University Seoul 151-744 Korea Republic of

ISBN: (纸本)0780393872

MicroRNAs (miRNAs) are small endogenous RNAs of ∼22nt that act as direct post-transcriptional regulators in animals and plants. MicroRNAs generally perform a function by binding to the complementary site on the 3' untranslated region of Its target gene and especially the Smers on the 5' part of miRNA seems important as a seed. Computational methods for miRNA target prediction have been focusing on this seed region, but recent researches revealed that the specificity of the seed region may be sharply decreased even by a point mutation. In this paper, we present a kernel method for miRNA target prediction in animals, which improves the prediction performance with biologically sensible data and position-based features reflecting the way of miRNA:mRNA pairing mechanism. In building a training dataset, we choose experimentally verified data only to improve the quality of dataset by excluding randomly synthesized one and consequently to make the result of learning valid. We use sensitivity, specificity, and area under ROC curve as performance measures of our algorithm and compare the results of various dataset configurations. The overall results were 92.1% in sensitivity, 83.3% in specificity, and 0.931 in area under ROC curve. With position-based features, an increase of 3.3% in sensitivity and 1.6% in specificity were observed. In the feature selection experiment to investigate the role of individual position-based features, the result suggests that pairing at positions 4, 5, 6 of the seed part is of greater importance than the other positions together with the general stability of the seed part. © 2005 IEEE.

关键词： RNA

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Requirements specification and evaluation for transient faults in communication protocols based on RT-FRIDA framework

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IFAC-PapersOnLine 2018年第10期51卷 76-81页

作者： Roque, Alexandre S. Nunes, Gerson L. Freitas, Edison P. Pereira, Carlos E. Graduate Program in Electrical Engineering Federal University of Rio Grande do Sul UFRGS Porto Alegre Brazil Computer Science and Engineering Department Regional Integrated University of High Uruguay and Missions URI Santo Angelo Brazil

This paper presents an evaluation of requirements specification for two critical real-time control systems, which depends of industrial communications protocols. It is proposed the use of aspect-oriented modeling (AOM) to map transient fault behaviors in design phases, with RT-FRIDA framework extended for fault modeling capabilities. Requirements specification for an Active suspension control system and for a fault detection control system applied in agricultural implements was made as case study. Faults are specified as non-functional requirements and evaluated applying a quantitative softgoal weight method. Results presented indicates aspect-oriented fault modeling as an important ally to specify faults that have potential to degrade performance of real-time control systems. © 2016

关键词： Suspensions (components) Active suspension systems Agricultural implements Control systems Fault detection Fault tree analysis Interactive computer systems Network protocols Real time control Real time systems Specifications Active suspension control Aspect oriented Aspect Oriented Modeling Industrial communications Non functional requirements Requirements analysis Requirements specifications Transient faults

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Random Number Generator for Securing Data Exchange in Smart Factory: Recent Trends and Best Practices 3

Random Number Generator for Securing Data Exchange in Smart ...

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3rd International Conference on computer Technologies, ICCTech 2024

作者： Sama, Andi Meyliana Heryadi, Yaya Sahroni, Taufik Roni Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information System Information System Department Jakarta11480 Indonesia BINUS Graduate Program-Doctor of Computer Science Jakarta Computer Science Department Jakarta11530 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Industrial Engineering Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350395419

IT/OT convergence in the form of a Cyber-Physical System (CPS) presents an opportunity to apply recent Information Technology (IT) advancements to Operational Technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption. © 2024 IEEE.

关键词： Data transfer

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Virtual instrumentation interfaces for real-time control and display of electric machine drives

Virtual instrumentation interfaces for real-time control and...

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2008 ASEE Annual Conference and Exposition

作者： Sundaram, Ramakrishnan Mak, Fong Tandle, Sunil Gannon University Department of Electrical and Computer Engineering Gannon University Gannon/GE Transportation Embedded System Graduate Program

No abstract available

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A multiobjective genetic approach with TOPSIS to learn fuzzy rule-based classification systems 8

A multiobjective genetic approach with TOPSIS to learn fuzzy...

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8th Brazilian Conference on Intelligent Systems, BRACIS 2019

作者： De Oliveira Araujo, Antonio Eloy Krohling, Renato Antonio Graduate Program in Computer Science PPGI Federal University of Espirito Santo - UFES Vitoria ES Brazil Production Engineering Department LABCin and Graduate Program in Computer Science PPGI Federal University of Espirito Santo - UFES Vitoria ES Brazil

ISBN: (纸本)9781728142531

The design of a Fuzzy Rule-Based Classification System (FRBCS) taking into account accuracy and interpretability (number of rules) of the FRBCS is an important issue. In this paper, we extend our previous work by considering the average number of fuzzy labels per input variable as a new objective to be treated with TOPSIS. In addition, we employ information entropy to determine the weights of the evaluation criteria. We compare our proposal with a method that deals with the accuracy-interpretability tradeoff by means of a multiobjective evolutionary process based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The obtained results show the effectiveness of the proposed approach. © 2019 IEEE.

关键词： Multiobjective optimization

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