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Synthetic Batik Pattern Generator Using Wasserstein Generative Adversarial Network with Gradient Penalty 6

Synthetic Batik Pattern Generator Using Wasserstein Generati...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Andriadi, Kus Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Binus Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Yogyakarta55281 Indonesia

ISBN: (纸本)9798350358346

Batik is an Indonesian world cultural heritage. Batik consists of many kinds of patterns depending on where the batik comes from, Batik-making techniques continue to develop along with technology development. Among the batik making techniques that are widely used are hand-written, stamping, and printing. Batik motifs have been widely used as research material, especially in the field of artificial intelligence. The diverse appearance of batik motifs has attracted many researchers to carry out research on making synthetic batik patterns, one of which uses a Generative Adversarial Network. This paper presents a synthetic batik pattern model based on the Wasserstein Generative Adversarial Network with Gradient Penalty. This model has been proven to create new synthetic batik patterns quite well and almost identical with images provided in the dataset, with the notes if the dataset provided is large. © 2023 IEEE.

关键词： Generative adversarial networks

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Accelerated DSP functions on the CBE for the X-Midas Toolkit

Accelerated DSP functions on the CBE for the X-Midas Toolkit

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International Waveform Diversity and Design Conference, WDD 2012

作者： Jezak, Joseph A. Berdanier, Charles Levitan, Steven P. Chiarulli, Donald M. Computer Engineering Graduate Program University of Pittsburgh United States USAF AFRL/RYMDA Wright Patterson Air Force Base United States Department of Electrical and Computer Engineering University of Pittsburgh United States Department of Computer Science University of Pittsburgh United States

ISBN: (纸本)9781509005987

We characterize the impact of the Cell Broadband Engine architecture, on commonly used radar DSP algorithms. We use the capabilities of the CBE to accelerate several key computational kernels including Matrix Multiplication, Matrix Inversion, and the Finite Impulse Response (FIR) filter. These algorithms are implemented and benchmarked as library routines within the X-Midas Toolkit. We observe speedups as large as 1200x for complex matrix multiplication, but speedups of 40x to 60x are more typical. We find that system I/O overhead within the X-Midas toolkit severely limited the performance of the applications. © 2012 IEEE.

关键词： FIR filters

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Big Data Governance for Building A Smart Cities 10

Big Data Governance for Building A Smart Cities

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10th International Conference on ICT for Smart Society, ICISS 2019

作者： Zulkarnain, Novan Kosala, Raymond Ranti, Benny Supangkat, Suhono Harso Bina Nusantara University Computer Science Department BINUS Graduate Program Doctor of Computer Science Information Systems Department Jakarta11480 Indonesia Universitas Indonesia Computer Science Department Depok16424 Indonesia Institute of Technology Bandung School of Electrical and Informatics Engineering Bandung40132 Indonesia

ISBN: (纸本)9781728148809

There have been many studies conducted related to Smart City, IT Governance and Big Data. In this study aims to find out how the relationship between the three and how to form a framework to explain it. The methodology used is qualitative by looking for some literature on smart city framework, IT Governance framework, and a Big Data framework. From these results, an overall picture of the relationship between the three is concluded, where Big Data has a role in IT Governance. and also the relationship of IT Governance to the realization of Smart City. And the final results of this study produce a framework to explain the relationship between Smart City, IT Governance and Big Data. © 2019 IEEE.

关键词： Big data

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Fuzzy-neuro predictive control, tuned by genetic algorithms, applied to a fermentation process

Fuzzy-neuro predictive control, tuned by genetic algorithms,...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： J.A. Fabro L.V.R. Arruda Automation and Advanced Control Systems Labratory-LASCA Graduate Program on Electrical Engineering and Applied Computer Science-CPGEI Federal Centre of Technological Education of Paraná Curitiba Parana Brazil

This paper proposes the development of a fuzzy predictive control. Genetic algorithms (GA's) are used to automatically tune the controller. A recurrent neural network is used to identify the process, and then provides predictions about the process behavior, based on control actions applied to the system. These predictions are used by the fuzzy controller, in order to accomplish a better control of an alcoholic fermentation process from chemical industry. This problem has been chosen due to its non-linearity and large accommodation time, that make it hard to control by standard controllers. Comparison of performance is made with non-predictive approaches(PID and Fuzzy-PD), and also with another predictive approach, GPC(Generalized Predictive Control).

关键词： Predictive control Genetic algorithms Control systems Fuzzy control Alcoholism Recurrent neural networks Nonlinear control systems Artificial intelligence Biomass Control system synthesis

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Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using Random Forest, KNN, Decision Tree and Naïve Bayes 7

Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using ...

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7th IEEE International Conference on Information Technology and Digital Applications, ICITDA 2022

作者： Pohan, Husni Iskandar Suparta, Wayan Heryadi, Yaya Wibowo, Antoni Lukas Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

Dengue Hemorrhagic Fever is an acute viral infectious disease caused by the dengue virus. Transmitted through the bite of Aedes Mosquitoes and divided into 4 severity. Severity 1 and 2 are characterized by a decrease in platelet levels below normal and there is a change in hemoconcentration, while Severity 3 and 4 are included in Dengue Shock Syndrome (DSS). The purpose of the study was to classify the severity of dengue, based on age, gender, platelets, body temperature, bleeding, and also doctor's recommendation. The advancement of information technology is the reason for the development of medical science, especially with artificial intelligence. Abundant medical data becomes a source that can be processed in improving the quality of medical information. The method chosen is Random Forest, kNN, Decision Tree and Naïve Bayes. The dataset used is the medical records of all DHF patients for 30 months in the period Jan 2019 to June 2021, at the Nadhifa Al Ghiffari Clinic in Bojongsoang District, Bandung Regency. © 2022 IEEE.

关键词： Decision trees

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A blind deconvolution approach to discontinuity location and characterization in ultrasonic nondestructive testing

A blind deconvolution approach to discontinuity location and...

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European Signal Processing Conference (EUSIPCO)

作者： Giovanni A. Guarneri Daniel R. Pipa Flávio Neves Lúcia V. R. de Arruda Graduate Program in Electrical Engineering (PPGEE) Federal University of Technology - Paraná (UTFPR) Pato Branco Paraná Brazil Graduate Program in Electrical and Computer Engineering (CPGEI) Federal University of Technology - Paraná (UTFPR) Curitiba Paraná Brazil

This paper presents a new algorithm for discontinuity location and characterization using A-scan signals from an ultrasonic inspection system. The algorithm is based on solving an inverse problem in which the observation model is different from that traditionally used. In this model, the input vector represents the location of the geometrical center of the discontinuity and the scattering amplitude of the discontinuity is embedded in the impulse response of the ultrasonic inspection system. First, we jointly estimate the locations and the scattering amplitudes of the discontinuities from the acquired signals. Then, the geometrical parameters of the discontinuities are calculated from the estimated scattering amplitude. The method is tested to characterize side-drilled holes using both synthetic and real data. The results demonstrates the effectiveness of the algorithm.

关键词： Signal processing algorithms Synchronous digital hierarchy Scattering Transducers Acoustics Approximation algorithms Europe

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Notification-Oriented programming Language and Compiler

Notification-Oriented Programming Language and Compiler

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Brazilian Symposium on Computing System engineering (SBESC)

作者： Adriano Francisco Ronszcka Cleverson Avelino Ferreira Paulo Cézar Stadzisz João Alberto Fabro Jean Marcelo Simão Graduate School in Electrical Engineering and Industrial Computer Science (CPGEI) Graduate School of Applied Computing (PPGCA) Federal University of Technology Parana (UTFPR) Curitiba Brazil

The so-called Notification-Oriented Paradigm (NOP) is a new technique to develop software. NOP is a rule-oriented approach where each rule and fact-base element is split in small entities. These entities particularly collaborate by means of precise notifications only when their state changes. This allows carrying out an inference process free of structural and temporal redundancies. Due to its peculiar properties, NOP tends to be an alternative to achieve suitable performance in program execution, easiness in codification level, and appropriate code modularity, structuration and decoupling. In order to validate these supposed features, a framework was implemented in C++. Even though it quite demonstrated the features of the paradigm in terms of execution performance and development process, it still presented a gap therein. In this context, this paper presents a preliminary programming language and compiler to explore NOP features. This new approach simplifies the development in NOP and speedup execution performance.

关键词： Redundancy C++ languages programming Collaboration Engines Couplings

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Spectral Learning of Shared Dynamics Between Generalized-Linear Processes 38

Spectral Learning of Shared Dynamics Between Generalized-Lin...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Oganesian, Lucine L. Sani, Omid G. Shanechi, Maryam M. Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA United States Ming Hsieh Department of Electrical and Computer Engineering Thomas Lord Department of Computer Science Alfred E. Mann Department of Biomedical Engineering Neuroscience Graduate Program University of Southern California Los AngelesCA United States

Generalized-linear dynamical models (GLDMs) remain a widely-used framework within neuroscience for modeling time-series data, such as neural spiking activity or categorical decision outcomes. Whereas the standard usage of GLDMs is to model a single data source, certain applications require jointly modeling two generalized-linear time-series sources while also dissociating their shared and private dynamics. Most existing GLDM variants and their associated learning algorithms do not support this capability. Here we address this challenge by developing a multi-step analytical subspace identification algorithm for learning a GLDM that explicitly models shared vs. private dynamics within two generalized-linear time-series. In simulations, we demonstrate our algorithm's ability to dissociate and model the dynamics within two time-series sources while being agnostic to their respective observation distributions. In neural data, we consider two specific applications of our algorithm for modeling discrete population spiking activity with respect to a secondary time-series. In both synthetic and real data, GLDMs learned with our algorithm more accurately decoded one time-series from the other using lower-dimensional latent states, as compared to models identified using existing GLDM learning algorithms. © 2024 Neural information processing systems foundation. All rights reserved.

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On-chip western blotting: In-situ renaturation of SDS-protein complexes unifies sodium dodecyl sulfate (SDS) sizing & blotting in one microdevice

On-chip western blotting: In-situ renaturation of SDS-protei...

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15th International Conference on Miniaturized Systems for Chemistry and Life sciences 2011, MicroTAS 2011

作者： Hou, Chenlu Herr, Amy E. University of California Electrical Engineering and Computer Science Berkeley United States University of California Bioengineering Berkeley United States University of California UCSF Graduate Program in Bioengineering Berkeley United States

ISBN: (纸本)9781618395955

Western blotting readily identifies specific proteins amidst complex biological backgrounds [1, 2]. Nevertheless, immunob-lotting suffers from tremendous labor-intensive and time-intensive requirements [3]. The slab-gel assays require 1-2 days for completion with multiple hands-on "blotting" steps and yield semi-quantitative information. Recently, our group has introduced new approaches for completing Western blotting. The microfluidic integration strategies introduced and used allow rapid results reporting, full assay automation, and limited sample consumption (1-10 uL). Our integration strategies use spatial, temporal, and spatiotemporal modulation of separation mechanisms in fully electrophoretic systems. The present study reports on recapitulation of immunoaffinity in previously sized proteins, using novel in-transit electrophoretic removal of SDS from SDS-protein complexes. Early results show both the length- and timescales for protein 'renaturation' are compatible with on-chip operation. Further, substantial binding affinity is recapitulated using this streamlined and promising approach.

关键词： Sodium dodecyl sulfate

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AI-driven Maintenance Tool for Synchronous Power Generator Temperature Monitoring Using Fiber Bragg Gratings

AI-driven Maintenance Tool for Synchronous Power Generator T...

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SBMO/IEEE MTT-S International Conference on Microwave and Optoelectronics (IMOC)

作者： Uilian José Dreyer Erlon V. da Silva Wilian Oliveira Paulo H. R. Mazzo Kleiton de M. Sousa André Biffe Di Renzo Cicero Martelli Jean Carlos Cardozo da Silva Graduate Program in Energy Systems (PPGSE) ENGlE Brasil Energia Universidade Tecnologica Federal do Parana-UTFPR Curitiba Parana Brazil Graduate Program in Electrical and Computer Engineering (CPGEI)

The carbon brushes and slip rings of a hydrogen-erator are the main components guiding the excitation current from the bridge to the rotor windings. The brushes' temperature are crucial to infer their operational condition and, the generator status. This work presents the temperature measurement of six Fiber Bragg Gratings (FBG) sensors installed in a 370 MVA electric generator brushes. The results show the sensors' capacity to monitor the brushes' temperature in accordance with the current flowing through them. Together with the sensors, an Artificial Intelligence (AI) technique was applied to the measured temperature to detect anomalous events regarding the current supplied to the rotor windings. The optical sensors combined with the AI could detect five events of abnormal current behaviour. One is presented in detail in this paper. This sensing system can be further applied to online fault detection using the temperature measured by the FBGs as a brush condition indicator and a generator operation and maintenance tool.

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