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Fuzzy Support Vector Regression with Grey Wolf Optimization in Stock Market Prediction

Fuzzy Support Vector Regression with Grey Wolf Optimization ...

International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

作者： Titimakan Sonsupap Sansanee Auephanwiriyakul Nipon Theera-Umpon Computer Engineering Department Faculty of Engineering Graduate School Chiang Mai University Chiang Mai Thailand Computer Engineering Department Faculty of Engineering Biomedical Engineering Institute Biomedical Engineering and Innovation Research Center Chiang Mai University Chiang Mai Thailand Electrical Engineering Department Faculty of Engineering Biomedical Engineering Institute Biomedical Engineering and Innovation Research Center Chiang Mai University Chiang Mai Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

The stock market price is influenced by many factors both domestic and international factors. To help stock traders in make buying or selling decision, a stock price prediction model is needed. In this paper, a stock closing price prediction system is introduced. We utilized 17 financial factors, i.e., 8 technical analysis factors (Crude oil price, Gold spot, Thai Baht to US Dollar exchange rate, High price, Low price, Opening price, Closing price, and Volume) and 9 fundamental factors (Exponential moving average, Relative strength index, Current ratio, Return on equity ratio, Return on assets ratio, Net profit margin ratio, Debt to equity ratio, Price to earning ratio, and Price to book value) from 18 previous working days as our inputs. We then computed chaos centroids from each factor. Finally, to predict the Monday closing price, the fuzzy support vector regression with the grey wolf optimization is utilized. There are 29 companies in 6 industry groups, i.e., RESOURCE, SERVICE, INDUS, PROPCON, AGRO, and TECH, considered in this research. We found that the minimum root mean square error of the blind test set is 0.3698 and the maximum of that is 11.66. However, the prediction trend of each company is very similar to the real closing price.

关键词： Support vector machines Industries Gold Oils Companies Market research Indexes

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Inferring the Effects of Protein Variants on Protein-Protein Interactions with Interpretable Transformer Representations

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Research 2024年第2期2023卷 473-489页

作者： Zhe Liu Wei Qian Wenxiang Cai Weichen Song Weidi Wang Dhruba Tara Maharjan Wenhong Cheng Jue Chen Han Wang Dong Xu Guan Ning Lin Shanghai Mental Health Center Shanghai Jiao Tong University School of MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina Shanghai Key Laboratory of Psychotic Disorders ShanghaiChina School of Information Science and Technology Institute of Computational BiologyNortheast Normal UniversityChangchunChina Department of Electrical Engineering and Computer Science University of MissouriColumbiaMO 65211USA Christopher S.Bond Life Sciences Center University of MissouriColumbiaMO 65211USA

Identifying pathogenetic variants and inferring their impact on protein-protein interactions sheds light on their functional consequences on *** by the availability of experimental data on the consequences of protein interaction,most existing methods focus on building models to predict changes in protein binding ***,we introduced MIPPI,an end-to-end,interpretable transformer-based deep learning model that learns features directly from sequences by leveraging the interaction data from *** was specifically trained to determine the types of variant impact(increasing,decreasing,disrupting,and no effect)on protein-protein *** demonstrate the accuracy of MIPPI and provide interpretation through the analysis of learned attention weights,which exhibit correlations with the amino acids interacting with the ***,we showed the practicality of MIPPI in prioritizing de novo mutations associated with complex neurodevelopmental disorders and the potential to determine the pathogenic and driving ***,we experimentally validated the functional impact of several variants identified in patients with such ***,MIPPI emerges as a versatile,robust,and interpretable model,capable of effectively predicting mutation impacts on protein-protein interactions and facilitating the discovery of clinically actionable variants.

关键词： consequences weights versatile

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Dynamically Reconfigurable Broadband SP3T Switch Powered by WPT for Antenna Switching Applications 52

Dynamically Reconfigurable Broadband SP3T Switch Powered by ...

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52nd European Microwave Conference, EuMC 2022

作者： Bilal, Asif Quddious, Abdul Rezaeieh, Sasan Ahdi Iezekiel, Stavros Antoniades, Marco A. Emphasis Research Centre University of Cyprus Cyprus University of Cyprus Department of Electrical and Computer Engineering Cyprus Kios Research Center for Excellence University of Cyprus Cyprus School of Information Technology and Electrical Engineering The University of Queensland Australia Ryerson University Department of Electrical Computer & Biomedical Engineering Canada

ISBN: (数字)9782874870699

ISBN: (纸本)9782874870699

In this work, a broadband single pole triple throw (SP3T) switch that operates between a frequency range of 0.02 - 6 GHz is reconfigured by means of wireless power transfer (WPT) through an energy harvesting (EH) circuit. The WPT is achieved by designing three rectennas working at 2.3 GHz, 2.45 GHz, and 2.6 GHz. Each rectenna consists of a low-power RF rectifier circuit associated with a distinct antenna element and a commercially available e-peas AEM30940 power management unit (PMU) that is able to provide an output of 1.8 V - 4.1 V with cold start-up from 380 mV and 3 μW input power. The PMU also consists of a storage capacitor where the energy from the low power received signal is stored. The three input pins of the SP3T switch require a driving voltage of 1.8 V to actuate its RF port. This voltage is provided by the designed rectennas through the PMU, and we can actuate the switch with a very low power (3 μW) received signal. The rectennas are designed to provide the 380 mV between -12 dBm to -10 dBm received power with a conversion efficiency of approx. 40 %for each rectenna. The proposed method to wirelessly enable the SP3T switch with a low-power RF signal can provide a breakthrough to reconfigure microwave devices and antennas for a broad range of applications, and also paves the way not only for the generation of clean energy, but also for its use as an alternative to batteries. © 2022 European Microwave Association (EuMA).

关键词： Energy harvesting

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Automatic Identification of Abnormal Lung Sounds Using Time-Frequency Analysis and Convolutional Neural Network 15

Automatic Identification of Abnormal Lung Sounds Using Time-...

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15th International Conference on Information Technology and electrical engineering, ICITEE 2023

作者： Phettom, Rattanathon Theera-Umpon, Nipon Auephanwiriyakul, Sansanee Biomedical Engineering Institute Chiang Mai University Chiang Mai Thailand Graduated School Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Chiang Mai University Chiang Mai Thailand Department of Computer Engineering Chiang Mai University Chiang Mai Thailand

ISBN: (纸本)9798350304466

This research focuses on the development of a method utilizing signal processing and machine learning techniques to identify abnormal lung sounds, specifically adventitious lung sounds, for diagnosis and monitoring. The proposed algorithm combines short-time Fourier transform (STFT) with convolutional neural networks (CNN) to automatically analyze breath sounds captured by a stethoscope. By employing a band pass filter, noise is effectively removed, facilitating accurate identification of lung sounds. The algorithm classifies abnormal lung sounds, such as crackles and wheezes, with an impressive accuracy rate of 85.27%. This research not only enhances the efficiency of physical examinations but also enables the recording and analysis of lung sounds, thereby offering valuable insights into the progression of treatments. Furthermore, the development of this medical device has significant implications for advancing human healthcare and information retrieval in the field of respiratory medicine. © 2023 IEEE.

关键词： Convolution

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Design and Simulation of a 3-Transistor Active Pixel Sensor Using MATLAB Simulink 23

Design and Simulation of a 3-Transistor Active Pixel Sensor ...

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23rd International Arab Conference on Information Technology, ACIT 2022

作者： Al Tarabsheh, Anas Alheeh, Huda Abu Dhabi University Department of Electrical Biomedical Computer Engineering Abu Dhabi United Arab Emirates The Hashemite University Faculty of Engineering Electrical Engineering Department Jordan Al Ain University Department of Network and Communication Engineering Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350320244

This paper proposes a Simulink model to simulate the pixel circuit with variable light intensities to investigate the impact of the light intensity on the CMOS image sensor pixels. This article also explores the CMOS image sensor pixel categories and presents the design and the simulation of the 3- Transistor (3T) Active Pixel Sensor (APS) in the MATLAB/Simulink tool. The analysis investigates the conversion of the light into an electrical signal for a single-pixel sensing circuit which consists of a photodiode and three NMOS transistors. The paper also proposes three modes for pixel operation;reset, integration, and readout modes. The simulations of the electrical signals for each of the studied modes of operation show how the output electrical signals are correlated to the input light intensities. The charging/discharging speed for the photodiodes is also investigated. The output voltage for different light intensities, including the dark case, is simulated, and it is shown its inverse proportionality with the light intensity. As a result, the Cpd discharges faster if the amount of light is increased. The more the light intensity, the lower value for the output voltage. © 2022 IEEE.

关键词： Photodiodes

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Quantifying statistics of gene product copy-number fluctuations: A stochastic hybrid systems approach

Quantifying statistics of gene product copy-number fluctuati...

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IEEE Conference on Decision and Control

作者： Zahra Vahdat Abhyudai Singh Department of Electrical and Computer Engineering University of Delaware Newark DE USA Department of Electrical and Computer Engineering Biomedical Engineering Mathematical Sciences Center for Bioinformatics and Computational Biology University of Delaware Newark DE USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Across diverse cell types, genes are often expressed at low levels resulting in significant stochastic fluctuations (noise) in intracellular copy number of mRNAs and proteins over time. Motivated by single-cell experiments, we capture this stochasticity by considering a given gene that toggles between transcriptionally active and inactive states with the time spent in each state being an arbitrary random variable. mRNAs are synthesized from the active state as per a Poisson process and each molecule degrades after a random lifespan (i.e., random time from birth to death). Modeling this process using the Stochastic Hybrid System (SHS) formalism we derive exact analytical results for the statistical moments of molecular counts. Our results show that for fixed mean mRNA numbers, fluctuations in mRNA levels are amplified with decreasing noise in mRNA lifespan. Relaxing the Poisson process assumption, we next consider a scenario where transcription events occur such that the time between successive events is an arbitrarily distributed random variable. In this case, we show that decreasing noise in mRNA lifespan can both increase/decrease mRNA count fluctuations depending on the underlying transcriptional process. Finally, we extend these results to the protein level, where increasing noise in mRNA counts is sometimes associated with decreasing noise in protein copy numbers.

关键词： Proteins Analytical models Fluctuations Exponential distribution Noise Stochastic processes Information processing Random variables Timing Kinetic theory

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Intelligent ADHD Detection Using Explainable Multimodal Fusion Model

Intelligent ADHD Detection Using Explainable Multimodal Fusi...

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Information Technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Ho-Jung Tsai Hsiao-Kuang Wu Chun-Chuan Chen Chen-Hsin Yeh Tzu-Yueh Chu Shih-Ching Yeh Department of Computer Science and Information Engineering National Central University Department of Biomedical Sciences and Engineering National Central University College of Computer Science and Electrical Engineering Hunan University

ISBN: (数字)9798350363609

ISBN: (纸本)9798350363616

Deep learning has been proved to diagnose Attention Deficit/Hyperactivity Disorder (ADHD) accurately, but it has raised concerns about trustworthiness because of the lack of explainability. Fortunately, the development of explainable artificial intelligence (XAI) offers a solution to this problem. In this study, we employed a VR-based GO/NOGO task with distractions, capturing participants' eye movement, head movement, and electroencephalography (EEG) data. We used the collected data to train an explainable multimodal fusion model. Besides classifying between ADHD and normal children, the proposed model also generates explanation heatmaps. The heatmaps provide the importance of specific variables and timestamps in the EEG data to help us analyze the patterns captured by the model. According to our observations, the model identified specific time intervals that related to specific event-related potentials (ERPs) components. The heatmaps also demonstrate that the impacts of distractions vary between not only the GO and NOGO events but also ADHD and normal children.

关键词： Heating systems Deep learning Pediatrics Accuracy Explainable AI Brain modeling Electroencephalography Data models Physiology Information technology

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Control of an Underactuated Quadrotor Using LQR and Visual Markers

Control of an Underactuated Quadrotor Using LQR and Visual M...

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Gabriel Fernandes Andre G. S. Conceicao Humberto X. De Araújo Postgraduate Program in Electrical Engineering Federal University of Bahia Salvador Brazil Department of Electrical and Computer Engineering Federal University of Bahia Salvador Brazil

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

In this study, a robust Linear Quadratic Regulator (LQR) controller was developed and evaluated for the Bebop 2 quadrotor drone. Polytopic uncertainties in the dynamic model were taken into account in the control design, ensuring robustness. The drone's localization was achieved using fiducial markers and a Kalman Filter for state estimation, integrating visual and positional data. The controller design utilized Linear Matrix Inequalities (LMIs) to optimize performance while accounting for system constraints. A circular trajectory in three-dimensional space was employed to assess the controller's effectiveness in simulation. Results demonstrated precise trajectory tracking, stability, and robust performance despite parameter uncertainties. These findings highlight the applicability of the proposed framework for real-world scenarios involving underactuated UAVs.

关键词： Location awareness Visualization Uncertain systems Uncertainty Trajectory tracking Stability analysis Trajectory Vehicle dynamics Quadrotors Drones

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Minimum Energy Speed Planning for Autonomous Electric Vehicles Using Maximum Current Curve

Minimum Energy Speed Planning for Autonomous Electric Vehicl...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Masoud Mohammadi Poria Fajri Reza Sabzehgar Arash Asrari Electrical and Biomedical Engineering Department University of Nevada Reno NV USA Department of Electrical and Computer Engineering San Diego State University San Diego CA USA Department of Electrical and Computer Engineering Purdue University Northwest Hammond IN USA

ISBN: (数字)9798350317664

ISBN: (纸本)9798350317671

One often overlooked aspect of calculating minimum energy path for autonomous electric vehicles (AEVs) is consideration of electric motor's physical limitations. This aspect becomes significantly complex when considering other constraints during the speed planning stage. One such limitation is the electric motor’s ability to extract maximum energy during regenerative braking (RB). This paper incorporates maximum current curve (MCC) and other motor limitations for solving optimum speed planning of AEVs using mixed-integer linear programming (MILP). The proposed approach not only determines the most suitable speed profile for a predefined route but also streamlines the integration of RB in obtaining optimal speed profile. This involves operating the motor based on its MCC and analyzing its impact on selecting different speed trajectories. The proposed method is compared to a base case model that does not incorporate MCC into its MILP formulation. The results are validated through MATLAB/Simulink simulation for a route under study and it is shown that the proposed method consumes 2.3% less energy throughout the route when compared to the base case scenario.

关键词： Energy consumption Decision making Transportation Electric vehicles Linear programming Mathematical models Planning

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High-resolution 3D Blood Flow Tomography in the Sub-diffuse Regime Using Laser Speckle Contrast Imaging

High-resolution 3D Blood Flow Tomography in the Sub-diffuse ...

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Clinical and Translational Biophotonics, Translational 2022

作者： Jafari, Chakameh Z. Mihelic, Samuel A. Engelmann, Shaun Dunn, Andrew K. The University of Texas at Austin Department of Electrical and Computer Engineering AustinTX United States The University of Texas at Austin Department of Biomedical Engineering AustinTX United States

We present a novel high-resolution (down to capillary levels) computational optical imaging technique based on laser speckle contrast imaging (LSCI) principles, for 3D reconstruction of blood flow maps in complex tiss... 详细信息

ISBN: (纸本)9781557528209

关键词： Speckle

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