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Solar Conference (MENA-SC), Middle East and North Africa

作者： Wadhah Alzahmi Alyaa Alyaarbi Tahani Alnaqbi Ayman Alzaatreh Dubai Electricity and Water Authority Dubai United Arab Emirates Department of Industrial Engineering Engineering Systems Management Program American University of Sharjah Sharjah Sharjah United Arab Emirates Department of Mathematics and Statistics College of Arts and Sciences American University of Sharjah Sharjah Sharjah United Arab Emirates

Global energy consumption has increased over the years due to population growth, economic expansion, and the pursuit of a higher quality of life. The building sector is a critical sector for high consumption, contributing to about 36% of the total global energy consumption in 2020. The global interest in reducing energy consumption allows different sectors to adopt renewable resources such as solar photovoltaics (PV). However, utilizing solar PV in buildings has limitations due to rooftop space constraints in newly designed buildings. Due to this limitation and continuous innovation in solar PV technologies, Building Integrated Photovoltaics (BIPV) have been introduced as a potential alternative for solar PV in buildings. As such, BIPV energy performance and panel temperatures are affected by many factors such as orientation setup and technology type. Therefore, this research aims to analyze the impact of technology type (indium gallium selenide (CIGS) and monocrystalline (MONO) & orientation on BIPV energy production & module temperature. The data used for this study is based on a project completed in Dubai for BIPV in building applications. The results indicate that BIPV type and system orientation during each session significantly affect BIPV energy production and BIPV module temperature.

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Emerging Neuroimaging Approach of Hybrid EEG-fNIRS Recordings: Data Collection and Analysis Challenges

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Data Science in Science 2024年第1期3卷

作者： Pinto-Orellana, Marco Antonio Khan, Haroon Ombao, Hernando Mirtaheri, Peyman Biomedical Engineering Department University of California Irvine Irvine CA United States Department of Mechanical Electronics and Chemical Engineering Oslomet–Oslo Metropolitan University Oslo Norway Statistics Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

The hybrid EEG-fNIRS (electroencephalogram - functional near-infrared spectroscopy) modality provides a comprehensive understanding of brain activity by simultaneously capturing electrical and hemodynamic responses. It takes advantage of the temporal resolution in EEG with the good spatial resolution of fNIRS. This hybrid system is non-invasive, portable, and relatively affordable compared to functional magnetic resonance imaging (fMRI). Despite its inherent limitations, EEG-fNIRS systems can be a valuable tool in neuroimaging, suitable for cognitive and clinical research that requires temporal and spatial information about brain function. They are well-suited in naturalistic experimental settings, brain-computer interface applications, and disease diagnosis. This paper also explores electro-metabolic interactions in the motor cortex during left- and right-hand grip tasks. We analyzed cross-frequency coupling (CFC) between delta rhythms (0–4Hz) and oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) concentrations calculated from fNIRS. CFC was estimated as the correlation between HbO, HbR, and the instantaneous amplitude of delta signals. CFC cannot be studied with non-synchronous measurements and is not directly related to activation amplitudes. Based on previous fMRI-EEG studies, some categories of oscillations denote a negligible correlation with fNIRS signals. However, our results showed a contra-lateral coupling between delta-EEG and HbO with significant pattern differences in the left motor cortex. © 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.

关键词： cross-frequency coupling data pre-processing electrical-hemodynamic coupling Hybrid EEG-fNIRS statistical modeling synchronization

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Modeling brain connectivity with graphical models on frequency domain

arXiv

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arXiv 2018年

作者： Gao, Xu Shen, Weining Ting, Chee-Ming Cramer, Steven C. Srinivasan, Ramesh Ombao, Hernando Department of Statistics University of California IrvineCA United States School of Biomedical Engineering and Health Sciences Universiti Teknologi Malaysia Malaysia Department of Anatomy and Neurobiology University of California IrvineCA United States Department of Cognitive Sciences University of California IrvineCA United States Statistics Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

Multichannel electroencephalograms (EEGs) have been widely used to study cortical connectivity during acquisition of motor skills. In this paper, we introduce copula Gaussian graphical models on spectral domain to characterize dependence in oscillatory activity between channels. To obtain a simple and robust representation of brain connectivity that can explain the most variation in the observed signals, we propose a framework based on maximizing penalized likelihood with Lasso regularization to search for the sparse precision matrix. To address the optimization problem, graphical Lasso, Ledoit-Wolf and sparse estimation of a covariance matrix (SPCOV) algorithms were modified and implemented. Simulations show the benefit of using the proposed algorithms in terms of robustness and small estimation errors. Furthermore, analysis of the EEG data in a motor skill task conducted using algorithms of modified graphical LASSO and Ledoit-Wolf, reveal a sparse pattern of brain connectivity among cortices which is consistent with the results from other work in the literature. Copyright © 2018, The Authors. All rights reserved.

关键词： Electroencephalography

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The instructional benefits from faculty participation in industrial outreach

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Journal of engineering Education 2001年第3期90卷 429-435页

作者： McKinnis, David R. McNamara, Kevin T. Kuczek, Thomas Salvendy, Gavriel Technical Assistance Program Purdue University United States Agricultural Economics Department Purdue University United States Department of Statistics Purdue University United States School of Industrial Engineering Purdue University United States Department of Statistics Purdue University 1399 Mathematical Sciences Building West Lafayette IN 47907-1399 United States Purdue University Technical Assistance Program 1284 Civil Engineering Building West Lafayette IN 47907-1284 United States School of Industrial Engineering Purdue University 1287 Grissom Hall West Lafayette IN 47907-1287 United States Agricultural Economics Department Purdue University 1145 Krannert Building West Lafeyette IN 47907-1145 United States

During the past twenty years, universities have significantly expanded their community service and outreach roles, including the addition of industrial outreach programs. This development has caused a need for an increased understanding of the nature and results of faculty participation in industrial outreach. This study of nineteen university-based outreach programs and 107 participating faculty found that participating faculty perceive positive impacts and outcomes for the educational and research missions of the university from their industrial outreach. Although positive perceptions and outcomes were identified, the faculty participating in this study identified barriers that must be addressed to expand die participation of faculty in industrial outreach.

关键词： engineering education

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Modeling functional cell types in spike train data

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PLoS Computational Biology 2023年第10 October期19卷 e1011509-e1011509页

作者： Zdeblick, Daniel N. Shea-Brown, Eric T. Witten, Daniela M. Buice, Michael A. Department of Electrical and Computer Engineering University of Washington SeattleWA United States Department of Applied Math University of Washington SeattleWA United States MindScope Program Allen Institute SeattleWA United States Department of Statistics and Biostatistics University of Washington SeattleWA United States

A major goal of computational neuroscience is to build accurate models of the activity of neurons that can be used to interpret their function in circuits. Here, we explore using functional cell types to refine single-cell models by grouping them into functionally relevant classes. Formally, we define a hierarchical generative model for cell types, single-cell parameters, and neural responses, and then derive an expectation-maximization algorithm with variational inference that maximizes the likelihood of the neural recordings. We apply this "simultaneous" method to estimate cell types and fit single-cell models from simulated data, and find that it accurately recovers the ground truth parameters. We then apply our approach to in vitro neural recordings from neurons in mouse primary visual cortex, and find that it yields improved prediction of single-cell activity. We demonstrate that the discovered cell-type clusters are well separated and generalizable, and thus amenable to interpretation. We then compare discovered cluster memberships with locational, morphological, and transcriptomic data. Our findings reveal the potential to improve models of neural responses by explicitly allowing for shared functional properties across neurons. Copyright: © 2023 Zdeblick et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

关键词： Neurons

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Parallel Approximations of the Tukey g-and-h Likelihoods and Predictions for Non-Gaussian Geostatistics

Parallel Approximations of the Tukey g-and-h Likelihoods and...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Sagnik Mondal Sameh Abdulah Hatem Ltaief Ying Sun Marc G. Genton David E. Keyes Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Kingdom of Saudi Arabia Statistics Program King Abdullah University of Science and Technology Extreme Computing Research Center King Abdullah University of Science and Technology

Maximum likelihood estimation is an essential tool in the procedure to impute missing data in climate/weather applications. By defining a particular statistical model, the maximum likelihood estimation can be used to understand the underlying structure of given geospatial data. The Gaussian random field has been widely used to describe geospatial data, as one of the most popular models under the hood of maximum likelihood estimation. Computation of Gaussian log-likelihood demands operations on a dense symmetric positive definite matrix, often parameterized by the Matérn correlation function. This computation of the log-likelihood requires $\mathcal{O}(n^{2})$ storage and $\mathcal{O}(n^{3})$ operations, which can be a huge task considering that the number of geographical locations, $n$ , now commonly reaches into the millions. However, despite its appealing theoretical properties, the assumptions of Gaussianity may be unrealistic since real data often show signs of skewness or have some extreme values. Herein, we consider the Tukey ${g-}$ and $-h$ (TGH) random field as an example of a non-Gaussian random field that shows more robustness in modeling geospatial data by including two more parameters to incorporate skewness and heavy tail features in the model. This work provides the first HPC implementation of the TGH random field's inference on parallel hardware architectures. Using task-based programming models associated with dynamic runtime systems, our implementation leverages the high concurrency of current parallel systems. This permits to run the exact log-likelihood evaluation of the Tukey g-and-h (TGH) random fields for a decent number of geospatial locations. To tackle large-scale problems, we provide additionally an implementation of the given model using two different low-rank approximations. We compress the aforementioned positive-definite symmetric matrix for computing the log-likelihood and rely on the Tile Low-Rank (TLR) and the Hierarchical Off-Diagon

关键词： Maximum likelihood estimation Symmetric matrices Runtime Computational modeling Linear algebra Tail Predictive models

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New Solitary Wave and Computational Solitons for Kundu Eckhaus Equation

SSRN

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SSRN 2022年

作者： Jaradat, Mohammed M.M. Batool, Amna Raza, Nauman Butt, Asma Rashid Mathematics Program Department of Mathematics Statistics and Physics College of Arts and Sciences Qatar University Doha2713 Qatar Department of Mathematics University of the Punjab Quaid-e-Azam Campus Lahore Pakistan Department of Mathematics University of Engineering and Technology Lahore Pakistan

The goal of this research is to nd novel optical solutions to the Kundu-Eckhaus equation,which possess crucial role in the eld of nonlinear optics. Collective variable (CV) strategyis adopted to solve governing equation including Raman e ect and quintic nonlinearity. Theparameters employed in this approach are chirp, temporal position, phase, amplitude, frequencyand width, namely collective variables. The fourth order Runge-Kutta technique is a renownednumerical scheme that aims towards the solution of the resulting system of ordinary di erentialequations representing the variables involved in the pulse ansatz. This techniques presents theevolution of pulse parameters with regard to propagation variable. The graphical pro les atsuitable values of pulse parameters are also provided. The results developed in this article showthat CV approach can be applied to solve a variety of nonlinear problems in mathematicalsciences. © 2022, The Authors. All rights reserved.

关键词： Solitons

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A Comparative Study of Fishing Activity Detection Approaches in Maritime Surveillance

A Comparative Study of Fishing Activity Detection Approaches...

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Computer Science, Computer engineering, & Applied Computing (CSCE), Congress in

作者： Vinicius D. Do Nascimento Tiago A. O. Alves Diego L. C. Dutra Sandip Kundu Systems Engineering and Computer Science Program (PESC) Federal University of Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Mathematics and Statistics Institute State University of Rio de Janeiro (UERJ) Rio de Janeiro Brazil Electrical and Computer Engineering (ECE) Department University of Massachusetts Amherst USA

Maritime authorities (MA) must track fishing vessels to ensure that fishing activities are limited to permitted areas. If illegal fishing is suspected, resources must be allocated to intercept and inspect the vessels. Thus, a false flag by the MA is costly, so it is important to use accurate detection methods. We compare the accuracy and computational time of the main approaches for detecting fishing activities described in the literature, using the Global Fishing Watch (GFW) dataset. We find that Long Short-Term Memory (LSTM) neural networks achieves an optimal accuracy of 1.00, while the random forest approach comes second with an accuracy of 0.87. Given the high cost of mistakes for MA, we conclude that the LSTM's high computational cost is worthwhile.

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Real-Time 2-D FIR Trapezoidal Digital Filters for 2.4 GHz Aperture Receiver Applications

Real-Time 2-D FIR Trapezoidal Digital Filters for 2.4 GHz Ap...

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Moratuwa engineering Research Conference (MERCon)

作者： Viduneth Ariyarathna Vítor A. Coutinho Sravan Pulipati Arjuna Madanayake Ravi T. Wijesekara Chamira U. S. Edussooriya‡ Len T. Bruton§ Thushara K. Gunaratne Renato J. Cintra Dept. of Electrical and Computer Engineering University of Akron USA Grad. Program in Electrical Engineering and Signal Processing Group Statistics UFPE Brazil Dept. of Electronic and Telecommunication Engineering University of Moratuwa Sri Lanka University of Moratuwa Moratuwa LK University of Calgary Calgary AB CA Herzberg Astronomy and Astrophysics National Research Council Canada

This paper presents the implementation of a two-dimensional (2-D) finite-impulse-response (FIR) trapezoidal filter based beamforming array receiver. A 2.4 GHz 16-element receive-mode IQ array is designed and used for physically measuring the beam patterns corresponding to 2-D FIR trapezoidal filters. The 16-element beamformer is implemented using the reconfigurable open architecture computing hardware version-2 (ROACH-2) field programmable gate array (FPGA) platform to perform analog to digital conversion and digital signal processing. The 2-D FIR trapezoidal filter is designed as a 16-spatial input 32-tap filter and is implemented targeting the ROACH-2's Xilinx Virtex 6 (sx475t) FPGA chip as a filter-and-sum architecture. The receiver array is precisely rotated (keeping the transmitter fixed) to digitally measure the received energy by integrating the instantaneous power of the output of the 2-D FIR trapezoidal filter for each angle of reception. The main lobe of the measured beam pattern is well aligned with the simulated beam pattern, and the highest measured side-lobe level is -17.8 dB.

关键词： Finite impulse response filters Array signal processing Antenna arrays Receivers Extraterrestrial measurements Computer architecture Field programmable gate arrays

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Retracted: Effect of Types and Gap on Spark Plugs on Exhaust Emissions on the 110CC Double Wheel Vehicles and Its Dissemination Using Website

Retracted: Effect of Types and Gap on Spark Plugs on Exhaust...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, Computer Science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Ginting, Tinus Manurung, Hotler Harahap, Astro Julida Ongko, Erianto Hartono, H. Abdullah, Dahlan Erliana, Cut Ita Saddhono, Kundharu Sriadhi, S. Supriyono, S. Iskandar, Akbar Saleh, A.A. Sudarsana, I. Ketut Department of Mechanical Engineering Akademi Teknologi Industri Immanuel Indonesia Department of Informatics Akademi Teknologi Industri Immanuel Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Department of Geography Education Universitas Prof Dr Hazairin SH Bengkulu Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Statistics Financial and Social Sciences Research Group Indonesia Department of Religious Education Institut Hindu Dharma Negeri Denpasar Denpasar Indonesia

Based on the formulation of the problem to be discussed by the writer is to know: the influence of 0.4 mm spark gap variation, and standard spark plug type, to CO and HC, the influence of 0.5 mm spark plug gap variation, and variation of platinum spark plug on CO and HC, influence of spark gap variation 0,6mm, and variation of iridium spark plug type to CO and HC emission Method used to obtain data needed to support the writer that is research method with experiment, literature study method or literature study The result of this research concludes that there is spark gap influence 0.4 mm, with variations of standard plug, platinum and iridium spark plugs against CO and HC emissions, where the lowest CO value is 0.27% and HC 98 ppm, 0.5 mm spark plug with lowest CO 0.15% and HC 46 ppm, 0.6 mm spark plug gap the lowest CO value of 0.19% and HC 24 ppm. The results of this research will be disseminated using the website. © Published under licence by IOP Publishing Ltd.

关键词： Information systems

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