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Intelligent Cybernetics technology & Applications (ICICyTA), International Conference on

作者： John Raphael G. Cuevas John Kenneth R. Rili Anny Neolicia G. Santillan Vivien A. Agustin Mary Grace N. Gonzales Criselle J. Centeno Richard C. Regala Department of Information Technology College of Information Systems and Technology Management Pamantasan ng Lungsod ng Maynila Manila Philippines Department of Computer Science Associate Dean of College of Information Systems and Technology Management Pamantasan ng Lungsod ng Maynila Manila Philippines Department of Information Technology Faculty of College of Engineering and Technology Pamantasan ng Lungsod ng Maynila Manila Philippines Department of Information Technology Director of Graduate Program of College of Information Systems and Technology Management Pamantasan ng Lungsod ng Maynila Manila Philippines Department of Computer Science Computer Lab Administrator of College of Engineering and Technology Pamantasan ng Lungsod ng Maynila Manila Philippines

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

LayOut Loud is an AI-powered augmented reality (AR) and mobile application designed to revolutionize room interior design by offering tailored, real-time solutions for layout optimization. The primary objective of this tool is to design AI-powered features that analyze user-provided room dimensions, furniture types, and style preferences. By leveraging advanced algorithms, LayOut Loud generates personalized design suggestions that cater to the individual needs and aesthetic tastes of users, ensuring that each interior design experience is customized and unique. A key goal of the application is to enhance user experience and decision-making through a clustering algorithm. This algorithm categorizes furniture pieces based on their suitability and appearance in living spaces, streamlining the selection process for users. By enabling the visualization of these items in a 3D model, users can make informed decisions about their interior design choices, ensuring that each piece contributes to the overall aesthetic and functional harmony of the space. Additionally, LayOut Loud focuses on improving its AR capabilities by allowing users to capture their room layouts and view virtual furniture arrangements in real time. This feature provides practical, interactive design solutions, empowering users to experiment with different configurations and instantly see how potential changes would appear in their actual living environments. Ultimately, LayOut Loud offers a user-friendly, immersive platform that transforms the way individuals approach interior design.

关键词： Solid modeling Three-dimensional displays Layout Decision making Clustering algorithms Real-time systems User experience Mobile applications Augmented reality Optimization

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Brain Function Assessment of EEG in Mild Cognitive Impairment using Timelag Analysis

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, information and systems 2025年第4期145卷 467-473页

作者： Tanabe, Akifumi Harachi, Kento Yamamoto, Yusuke Muramatsu, Ayumi Nagahara, Hajime Takemura, Noriko Shimojo, Shinji Furihata, Daisuke Mizuno-Matsumoto, Yuko Graduate School of Information Science University of Hyogo 7-1-28 Minatojima Minami Chuo-ku Hyogo Kobe650-0047 Japan Department of Medical Engineering Aino University 4-5-4 Higashi-Ohda Ibaraki Osaka567-0012 Japan D3 Center The University of Osaka 2-8 Yamadaoka Osaka Suita565-0871 Japan D3 Center The University of Osaka 5-1 Mihogaoka Ibaraki Osaka567-0047 Japan Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Fukuoka Iizuka820-8502 Japan Faculty of Software and Information Technology Aomori University 2-3-1 Shachihata Aomori-shi Aomori030-0943 Japan

This research aimed to reveal the information process in the brain of the patients who suffered from mild cognitive impairment (MCI) using the power spectra and timelag analysis in electroencephalogram (EEG). The patients with MCI have memory or thinking problems, and are at a great risk of developing Alzheimer's disease or a related dementia. Ten patients with MCI and 13 healthy adults (non-MCI) were examined. The EEGs (122.88 seconds/subject) during a state of relaxation with the eyes closed, were analyzed using the Fourier analysis (power spectrum) and the timelag analysis. The results showed that the mean value of the power spectra in MCI was significantly higher than the mean value in non-MCI in the theta band. The mean value of the absolute timelag values (ATL) in MCI was significantly lower than the mean value in non-MCI in the frontal and left temporal areas. Our findings suggest that the features from EEG of MCI were abstracted in the theta band, and the propagation of information related to memory in brain would becoming fast in MCI. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Electroencephalography

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Arabic Dialect Identification in Social Media:A Comparative Study of Deep Learning and Transformer Approaches

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Intelligent Automation & Soft Computing 2024年第5期39卷 907-928页

作者： Enas Yahya Alqulaity Wael M.S.Yafooz Abdullah Alourani Ayman Jaradat Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMedina42353Saudi Arabia Department of Management Information Systems College of Business and EconomicsQassim UniversityBuraydah51452Saudi Arabia Internet of Things Department Faculty of Science and Information TechnologyJadara UniversityIrbid21110Jordan

Arabic dialect identification is essential in Natural Language Processing(NLP)and forms a critical component of applications such as machine translation,sentiment analysis,and cross-language text *** difficulties in differentiating between Arabic dialects have garnered more attention in the last 10 years,particularly in social *** difficulties result from the overlapping vocabulary of the dialects,the fluidity of online language use,and the difficulties in telling apart dialects that are closely *** dialects with limited resources and adjusting to the ever-changing linguistic trends on social media platforms present additional challenges.A strong dialect recognition technique is essential to improving communication technology and cross-cultural understanding in light of the increase in social media *** distinguish Arabic dialects on social media,this research suggests a hybrid Deep Learning(DL)*** Long Short-Term Memory(LSTM)and Bidirectional Long Short-Term Memory(BiLSTM)architectures make up the model.A new textual dataset that focuses on three main dialects,i.e.,Levantine,Saudi,and Egyptian,is also *** 11,000 user-generated comments from Twitter are included in this dataset,which has been painstakingly annotated to guarantee accuracy in dialect ***,DL models,and basic machine learning classifiers are used to conduct several tests to evaluate the performance of the suggested *** methodologies,including TF-IDF,word embedding,and self-attention mechanisms,are *** suggested model fares better than other models in terms of accuracy,obtaining a remarkable 96.54%,according to the trial *** study advances the discipline by presenting a new dataset and putting forth a practical model for Arabic dialect *** model may prove crucial for future work in sociolinguistic studies and NLP.

关键词： Dialectal Arabic transformers deep learning natural language processing systems

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Oil Spill Identification using Deep Convolutional Neural Networks 14

Oil Spill Identification using Deep Convolutional Neural Net...

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14th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2022

作者： Feinauer, David M. Latif, Ghazanfar Alenazy, Abeer M. Tayem, Nizar Alghazo, Jaafar Alzubaidi, Loay Virginia Military Institute Department of Electrical and Computer Engineering LexingtonVA United States Prince Mohammad Bin Fahd University Computer Science Department Khobar Saudi Arabia Texas A&m University Department of Engineering and Technology Commerce United States Higher Colleges of Technology Faculty of Computer Information Systems United Arab Emirates

ISBN: (纸本)9781665487719

Oil spill detection is an extremely important topic in which Machine Learning (ML) can be utilized because oil spills that go undetected can cause huge environmental negative impacts. The science of how an oil spill can cause devastation to wildlife has been widely viewed with sorrow and the early detection of oil spills can greatly reduce the negative impact oil spills have on the environment. If an optimal solution is found for oil spill detection, continuous monitoring can be achieved either through satellite images or images obtained from unmanned aerial vehicles such as drones. In this paper, we develop a dataset for oil spill detection collected from images from the Internet and other online resources. The dataset consists of 783 images of Oil Spills and 783 normal images. Since these are real-world images, research done on this dataset will produce a more realistic and practical solution. In this paper, we also propose an enhanced CNN model based on GoogleNet and VGG16 combined with transfer learning for the detection and classification of oil spills. The GoogleNet Transfer Learning model achieved better results of training accuracy of 97.5%, training loss of 0.0894, and validation accuracy of 95.6%. Since this is a new dataset, the results cannot be compared to anything in the extant literature. © 2022 IEEE.

关键词： Oil spills

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Harmonic Analysis of SEPIC DC-DC Converter

Harmonic Analysis of SEPIC DC-DC Converter

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Junior Conference on Lighting (Lighting)

作者： Gergana Vacheva Plamen Stanchev Nikolay Hinov Departement of Power Electronics Faculty of Electronic Engineering and Technologies Technical University of Sofia Sofia Bulgaria Departement of Information Technology in Industry Faculty of Computer Systems and Technologies Technical University of Sofia Sofia Bulgaria

ISBN: (数字)9798350352757

ISBN: (纸本)9798350352764

In the presented work, a harmonic analysis has been implemented to determine the resonance occurrence node of the Sepic DC-DC converter. The simulation studies were implemented in MATLAB/Simulink. Two cases of transistor conduction are presented. The differential equations for describing the processes in the converter are presented. State space matrices are used to implement harmonic analysis. Simulation studies are obtained and comments are made on the advantages and disadvantages of the methods used.

关键词： Lighting Differential equations DC-DC power converters Harmonic analysis Resonance Transistors Matrix converters

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Harmonic Analysis of Cûk DC-DC Converter

Harmonic Analysis of Cûk DC-DC Converter

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International Symposium on Electrical Apparatus and Technologies (SIELA)

ISBN: (数字)9798350382365

ISBN: (纸本)9798350382372

In the present paper, a harmonic analysis of a Cuk DC-DC converter is realized. A simulation model was implemented in MATLAB/Simulink. The converter is described using differential equations that are represented in state space. Two scenario of on and off transistor are considered. Simulation results are shown, where it can be observed in which case resonance occurs, which significantly influences the design of the circuit. Main advantages and disadvantages of the selected topology are described.

关键词： Smart cities Simulation RLC circuits DC-DC power converters Harmonic analysis Resonance Power electronics

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LTSpice Based Stability Analysis of DC-DC Converter for LED Drivers

LTSpice Based Stability Analysis of DC-DC Converter for LED ...

引用

Junior Conference on Lighting (Lighting)

ISBN: (数字)9798350352757

ISBN: (纸本)9798350352764

This article presents a stability analysis of a boost DC-DC converter for powering an LED strip. A model of a DC converter is presented and the principle of operation is described. LTSpice software was used to implement the mathematical model. LED strip data provided by the manufacturer is used. Simulation results of the realized studies by Fourier transformation are presented. Investigating the influence of transient in LED drivers is useful in order to ensure the stability of the manufactured device under various external influences.

关键词： Strips Voltage fluctuations Simulation Lighting DC-DC power converters Light emitting diodes Stability analysis

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Modelling of PV Plant for Supplying of Medium Sized Enterprises

Modelling of PV Plant for Supplying of Medium Sized Enterpri...

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International Symposium on Electrical Apparatus and Technologies (SIELA)

作者： Gergana Vacheva Andrei Borisov Nikolay Hinov Plamen Stanchev Departement of Power Electronics Faculty of Electronic Engineering and Technologies Technical University of Sofia Sofia Bulgaria Departement of Information Technology in Industry Faculty of Computer Systems and Technologies Technical University of Sofia Sofia Bulgaria

ISBN: (数字)9798350382365

ISBN: (纸本)9798350382372

In current research a photovoltaic plant for supplying medium sized enterprises is studied. In the presented manuscript the main advantages of the proposed system and disadvantages of connecting photovoltaic systems to the distribution network are discussed. Also, the parameters and external influences on the power plant are presented. Data from smart meters for electricity production for a period of 1 year were used.

关键词： Photovoltaic systems Meters Green energy Electricity Production Distribution networks Supercapacitors

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Classification of Breast Cancer Molecular Subtypes with Grouping-Scoring-Modeling Approach that Incorporates Disease-Disease Association information

Classification of Breast Cancer Molecular Subtypes with Grou...

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IEEE Signal Processing and Communications Applications (SIU)

作者： Emma Qumsiyeh Burcu Bakir-Gungor Malik Yousef Department of Computer Science and Information Technology Al-Quds University Jerusalem Palestine Department of Computer Engineering Faculty of Engineering Abdullah Gul University Kayseri Turkey Department of Information Systems Galilee Digital Health Research Center Zefat Academic College Zefat Israel

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

This study uses modern sequencing technology and large biological databases to investigate the molecular intricacies of complicated diseases like cancer. Using gene expression databases and biomarkers, the research aims to improve breast cancer molecular subtype identification for better patient outcomes. Using BRCA LumAB_Her2Basal dataset, this study compares an integrative machine learning-based strategy (GediNET) to traditional feature selection approaches across machine learning classifiers. GediNET excels at uncovering crucial disease-disease connections and potential biomarkers using the Grouping-Scoring-Modeling (GSM) approach, which favors gene groupings above individual genes. Our comparative analysis highlights GediNET’s exceptional performance, notably in terms of accuracy and Area Under the Curve metrics, underscoring its effectiveness in uncovering the genetic intricacies of breast cancer. GediNET’s promise to improve disease classification and biomarker identification by improving biological mechanism understanding goes beyond exceeding traditional approaches. The work shows that GediNET’s integrative method can promote bioinformatics research by identifying the most informative genes associated with certain diseases, enabling focused and customized medicine.

关键词： Measurement Sequential analysis Databases Machine learning Biomarkers Signal processing Genetics

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Performance Evaluation of Multi-ONU Customers Access Network using Spectrum Slicing and Duplication Techniques 5

Performance Evaluation of Multi-ONU Customers Access Network...

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5th International Conference on Emerging Electrical Energy, Electronics and Computing Technologies, ICE4CT 2024

作者： Rahman, Juwairiyyah Abdul Mugunthan, Sivaguru A.L. Hassan, Hasliza Abu Muslim, Norliana Ab-Rahman, Mohammad Syuhaimi Department of Electrical Engineering Faculty of Engineering and Life Sciences Universiti Selangor Selangor Bestari Jaya45600 Malaysia Department of Computer and Communication Technology Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Perak Kampar31900 Malaysia Department of Electrical Electronics and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Malaysia Electrical and Computer Engineering Program Faculty of Engineering Sohar University PC:311 Sohar Oman

This study aims to increase the number of access users by limiting the sample size to 30 users while ensuring that every Optical Network Unit (ONU) receives data from the Optical Line Terminal (OLT). The proposed solution allows for the determination of power requirements at each ONU based on bus-star topologies, facilitating an increase in user capacity. The power received by each ONU is a critical parameter that system designers must consider when planning the implementation of Fiber to the Home (FTTH), as it impacts the output data in terms of Bit Error Rate (BER) and Signal Quality Factor (QF) for each user. Various parameters were evaluated to ensure that the enhanced network improves scalability while adhering to standard specifications. These parameters included the Q-factor, BER, eye diagram, user count, and received power. The study employed slicing and duplication techniques, utilizing Arrayed Waveguide Grating (AWG) for signal duplication and Wavelength Division Multiplexing for signal slicing. The simulations were conducted using a transmitter operating at a frequency of 1491 nm with a power output of 0 dBm, utilizing the latest version of OptiSystem 20 software. The results highlighted the system's capability to support a total of 73,728 users, meeting stringent performance criteria. Specifically, the system achieved a Q-factor greater than 6, indicating high signal quality, and a bit error rate (BER) lower than 1 × 10-9, ensuring reliable data transmission. For the sampled 30 users, the average Q factor was 8.1527, and the average BER was 5.3648 × 10^-11, with an output power level of -54.278 dBm. Despite an increase in users, the quality of the data supplied to clients remained unchanged. These outcomes underscore the robustness and efficiency of the design in delivering high-capacity, error-resilient optical communication. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Q factor measurement

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