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GLOBAL WELL-POSEDNESS FOR THE FULL COMPRESSIBLE NAVIER-STOKES EQUATIONS

Acta Mathematica Scientia 2022年第5期42卷 2131-2148页

作者： Jinlu LI Zhaoyang YIN Xiaoping ZHAI School of Mathematics and Computer Sciences Gannan Normal UniversityGanzhou 341000China Department of Mathematics Sun Yat-sen UniversityGuangzhou 510275China Faculty of Information Technology Macao University of Science and TechnologyMacaoChina Department of Mathematics Guangdong University of TechnologyGuangzhou 510520China School of Mathematics and Statistics Shenzhen UniversityShenzhen 518060China

We are concerned with the Cauchy problem regarding the full compressible Navier-Stokes equations in R^(d)(d=2,3).By exploiting the intrinsic structure of the equations and using harmonic analysis tools(especially the Littlewood-Paley theory),we prove the global solutions to this system with small initial data restricted in the Sobolev ***,the initial temperature may vanish at infinity.

关键词： compressible Navier-Stokes equations global well-posedness Friedrich's method compactness arguments

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Identification and Analysis of Phishing Website based on Machine Learning Methods 12

Identification and Analysis of Phishing Website based on Mac...

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12th IEEE Symposium on computer Applications and Industrial Electronics, ISCAIE 2022

作者： Alkawaz, Mohammed Hazim Joanne Steven, Stephanie Mohammad, Omar Farook Gapar Md Johar, Md Management and Science University Faculty of Information Sciences & Engineering Selangor Shah Alam Malaysia Management and Science University School of Graduates Studies Selangor Shah Alam Malaysia Al-Hadba University College Computer Technology Engineering Mosul Iraq Management and Science University Information Technology and Innovation Centre Selangor Shah Alam Malaysia

ISBN: (纸本)9781665487030

People are increasingly sharing their details online as internet usage grows. Therefore, fraudsters have access to a massive amount of information and financial activities. The attackers create web pages that seem like reputable sites and transmit the malevolent content to victims to get them to provide subtle information. Prevailing phishing security measures are inadequate for detecting new phishing assaults. To accomplish this aim, objective to meet for this research is to analyses and compare phishing website and legitimate by analyzing the data collected from open-source platforms through a survey. Another objective for this research is to propose a method to detect fake sites using Decision Tree and Random Forest approaches. Microsoft Form has been utilized to carry out the survey with 30 participants. Majority of the participants have poor awareness and phishing attack and does not obverse the features of interface before accessing the search browser. With the data collection, this survey supports the purpose of identifying the best phishing website detection where Decision Tree and Random Forest were trained and tested. In achieving high number of feature importance detection and accuracy rate, the result demonstrates that Random Forest has the best performance in phishing website detection compared to Decision Tree. © 2022 IEEE.

关键词： Decision trees

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Analysis of Shoping Intention Using E-Commerce during Pandemic 8

Analysis of Shoping Intention Using E-Commerce during Pandem...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Oktavia, Tanty Gaol, Ford Lumban Hosoda, Takaaki Wijaya, Alessandro Bryan Tio, Fendy Malaysiani, Liza Azzahra Sanjaya, Sandi Martin, Yessin Rio Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Decision Science Department Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9781665416979

This study aims to investigate people's shopping intentions using e-commerce during the pandemic in Indonesia. The method used in this research is the quantitative method in which the results of the study are used as an assumption and research discussion. Data collection was carried out by questionnaires then measure using t-test. The result can be concluded that the intention to shop using e-commerce during the COVID-19 pandemic is influenced using e-commerce features and e-commerce techniques. These results indicate that the intention to shop using e-commerce can increase if the availability of goods in e-commerce is quite complete, the quality of goods sold is very high, normal prices and technical requirement, such as speed, security, and a good e-commerce design system. © 2021 IEEE.

关键词： COVID-19

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YOLOv5: Case Study of Image Resolution Influence on Fire Detection 65

YOLOv5: Case Study of Image Resolution Influence on Fire Det...

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65th International Symposium ELMAR, ELMAR 2023

作者： Maric, Petar Hrzic, Franko Arlovic, Matej Patel, Mitesh Azeem, Muhammad Moazam Balen, Josip Computer Science and Information Technology Osijek Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Osijek31000 Croatia University of Rijeka Faculty of Engineering Rijeka51000 Croatia NVIDIA Corporation Santa ClaraCA95051 United States Qatar University Doha Qatar

ISBN: (纸本)9798350325126

Fire presents a dangerous occurrence in inhabited places or places occupied by humans. Apart from very high material damage, it can result in human fatalities. In the past, numerous sensor-based methods were developed in order to reduce the reaction time and improve fire detection accuracy. With the advent of modern convolutional neural networks (CNN), object detection models quickly emerged, together with novel fire detection methods utilizing said models. In this paper, we aim to demonstrate the performance of YOLOv5 on our custom dataset, which contains indoor fire occurrences. Furthermore, we are investigating the influence of the input image resolution on the models' performances. This is important due to the hardware limitations of the models that would be used in real-life applications. The research shows that different metrics (F1-Score, inference time, mAP50) can yield different models as the best-performing ones. However, since the models have to be relatively small, quick, and accurate, we have proposed the ranking-based evaluation of the models from the aspect of the input image resolution. The evaluation showed that the models obtained the best overall score when the input image resolution was set to $512 \times 512$ pixels. © 2023 IEEE.

关键词： Image resolution

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A Design and Implementation of Water Heater Model Plant with Temperature Estimation Model for IOT Studies 7

A Design and Implementation of Water Heater Model Plant with...

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7th International Conference on Vocational Education and Electrical Engineering, ICVEE 2024

作者： Pradhana, Anak Agung Surya Funabiki, Nobuo Kotama, I Nyoman Darma Desnanjaya, I Gusti Made Ngurah Radhitya, Made Leo Mahajaya, Nyoman Sarasuartha Okayama University Graduate School of Environmental Life Natural Science and Technology Okayama Japan Okayama University Department of Electrical and Communication Engineering Okayama Japan Institute of Business and Technology Indonesia Department of Computer System Engineering Denpasar Indonesia Institute of Business and Technology Indonesia Department of Informatic Technology Denpasar Indonesia Institut Teknologi Dan Bisnis Stikom Departement of Magister Information Systems Denpasar Indonesia

ISBN: (纸本)9798331505103

This study presents the development of an Internet of Things (IoT) system for a water heater model, focusing on enhancing reliability during sensor malfunctions that could disrupt operations. Using the SEMAR IoT platform, the system efficiently collects and analyzes data, while the integration of the Holt-Winter algorithm ensures accurate temperature estimates, even with unreliable or missing sensor data. The algorithm successfully auto-calibrates sensors, predicts temperature at specific time intervals based on real sensor behavior, and fills in missing data during sensor failures. Tests show strong correlations between estimated and actual temperatures, allowing uninterrupted operation. This solution offers a flexible, cost-effective alternative to traditional redundancy, ensuring system reliability during sensor failures. Future research will explore alternative predictive models and conduct real-world testing to validate the system's resilience under complex conditions. © 2024 IEEE.

关键词： Temperature measurement

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Follicle Detection Model on Ovarian Ultrasound Image 7

Follicle Detection Model on Ovarian Ultrasound Image

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Hartati, Sri Musdholifah, Aina Wulaning Ayu, Putu Desiana Dasuki, Jaswadi Universitas Gadjah Mada Department of Computer Science and Electronics Yogyakarta Indonesia Institut Teknologi Dan Bisnis Stikom Bali Faculty Computer and Informatics Department of Information Technology Bali Indonesia Universitas Gadjah Mada Faculty of Medicine Public Health and Nursing Yogyakarta Indonesia

ISBN: (纸本)9798350345711

every woman has two ovaries. Ovaries have several follicles, which consist of oocytes or eggs which are filled with granulosa cells. Some women can have a difference in the number of follicles in each ovary. There are cases of several follicles that are coincided, making it difficult to calculate the number of follicles. In this study, the separation of adjoining follicles and automatic follicle counting was carried out from the results of ovarian ultrasound image segmentation. The segmentation results obtained feature information in the form of follicular feature extraction as many as eight features. The techniques used in this work for feature selection was carried out using Principal Components Analysis (PCA) to reduce the feature. In this study, the PCA and Support Vector Machine (SVM) classifier produced higher accuracy than the classification without PCA. The experimental results also show that the proposed method produced higher classification accuracy than previous work, which yielded 90.39% accuracy, 90.27 % sensitivity, and 90.43 % specificity. © 2022 IEEE.

关键词： Principal component analysis

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Clustering Analysis of a Spatiotemporal Dataset with a Novel Kernel Density Estimator

Clustering Analysis of a Spatiotemporal Dataset with a Novel...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jen-Chien Yu Chun-Chieh Yang John Reuben Gilbert Rou-Jun Liu Yen-Jen Oyang Meng-Han Yang Department of Computer Science and Information Engineering National Kaohsiung University of Science and Technology Kaohsiung City Taiwan ROC Master Program in Statistics National Taiwan University Taipei Taiwan ROC Department of Computer Science & Information Engineering National Taiwan University Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University

A vast number of spatiotemporal datasets collected from a wide range of sources has motivated scientists to develop effective approaches to identify interesting patterns hidden in these datasets. In this respect, kernel density estimators, which belong to a class of non-parametric estimators in statistics, have been widely exploited in recent years. With this background, we have developed a novel kernel density estimator aiming to provide accurate analysis results. According to the evaluation with a real spatiotemporal dataset, which collected emergency medical service records in a county in the United States, the proposed kernel density estimator can approximate the probability density function significantly more accurately than a conventional kernel density estimator. Furthermore, we have exploited the proposed kernel density estimator to identify interesting patterns hidden in the real spatiotemporal dataset.

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QoE-oriented Soft Caching with Content Recommendation for Edge Computing Networks

QoE-oriented Soft Caching with Content Recommendation for Ed...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Wang, Chenyang Chen, Yan Sun, Chuan Jia, Bosen Wang, Xiaofei Taleb, Tarik Leung, Victor C. M. Shenzhen University College of Computer Science & Software Engineering Shenzhen China Shenzhen518132 China Ruhr University Bochum Faculty of Electrical Engineering and Information Technology Bochum Germany Nanyang Technological University College of Computing and Data Science Singapore China Unicom Digital Technology Co. Ltd Beijing China Tianjin University College of Intelligence and Computing Tianjin China University of British Columbia Vancouver Canada

ISBN: (纸本)9798350351255

Mobile Edge Caching (MEC) can potentially alleviate Internet transmission congestion by delivering content at the network edge. However, current MEC solutions suffer from low resource utilization efficiency and often fail to meet user Quality of Experience (QoE), primarily due to dynamic user requests and obsessive pursuit of direct caching hits. Given the prevalence of recommendation systems, users often lack precise requests when using recommendation-based applications like TikTok and Taobao, insted passively enjoying recommended content. In this paper, we introduce a recommendation-enabled MEC architecture to enhance resource utilization and QoE. We develop a recommendation-enabled soft caching model and formulate the optimization problem as maximizing joint system revenue. To address this, we propose an attention-assisted federated learning deep Q-network algorithm. We conduct the simulations by using the real-world MIND dataset. The results demonstrate that our proposed algorithm outperforms existing baselines, demonstrating its effectiveness in improving resource utilization and QoE. © 2024 IEEE.

关键词： Mobile edge computing

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Comparison of potential energy of solar radiation in rooftop modeling using different building levels of detail

Comparison of potential energy of solar radiation in rooftop...

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2023 Annual Conference, ASPRS 2023

作者： Ihsan, K.T.N. Sakti, A.D. Higuchi, A. Takenaka, H. Suwardhi, D. Wikantika, K. Doctor Program in Program Study of Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung Indonesia Graduate School of Science and Engineering Chiba University Chiba Japan Remote Sensing and Geographic Information Science Research Group Faculty of Earth Sciences and Technology Institut Teknologi Bandung Bandung40132 Indonesia Center for Remote Sensing Institut Teknologi Bandung Bandung40132 Indonesia Center for Environmental Remote Sensing Chiba University Chiba263-8522 Japan

The potential for future energy crises is a problem the world is currently facing. Many countries are switching from fossil to renewable energy to prevent an energy crisis. One of the most developed renewable energy today is solar energy. Easy installation makes solar energy installation not only on a large scale but also on a home scale. Urban areas will be very suitable for building solar photovoltaic (PV) roofs due to minimal open areas. In installing rooftop solar PV, sound planning is needed to predict the energy potential that can be provided by solar energy on the rooftop of a building. Spatial modeling can be done to determine the energy potential and suitable location for rooftop solar PV installation. In building rooftop solar PV modeling, the level of detail of the building will affect the results of the model. The rooftop's shape and the building's height will affect the amount of solar radiation going into the building. However, the higher the level of detail of the building, the higher the cost and processing time will be. This study will review the differences in modeling the potential of rooftop solar PV using different levels of detail. This research will integrate solar radiation data from remote sensing to determine the energy potential of solar radiation and digital surface model data from photogrammetry to create a level of detail for buildings. Integration of solar radiation data and the level of detail of the building will use hillshade analysis. Hillshade analysis can review the shadow effect on the rooftop of a building which will be directly related to the potential of solar energy on the rooftop of the building. This study determines the energy potential on the rooftop of the building with different levels of detail, namely 0, 1, and actual shape, to determine the difference in energy potential in the three scenarios. Hopefully, this research will determine the best level of detail for modeling rooftop solar PV. The best model that can sho

关键词： Remote sensing

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Evolutionary Approach to Security Games with Signaling 31

Evolutionary Approach to Security Games with Signaling

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31st International Joint Conference on Artificial Intelligence, IJCAI 2022

作者： Żychowski, Adam Mańdziuk, Jacek Bondi, Elizabeth Venugopal, Aravind Tambe, Milind Ravindran, Balaraman Faculty of Mathematics and Information Science Warsaw University of Technology Poland Center for Research on Computation and Society Harvard University United States Robert Bosch Centre for Data Science and AI IIT Madras India Department of Computer Science and Engineering IIT Madras India

ISBN: (纸本)9781956792003

Green Security Games have become a popular way to model scenarios involving the protection of natural resources, such as wildlife. Sensors (e.g. drones equipped with cameras) have also begun to play a role in these scenarios by providing real-time information. Incorporating both human and sensor defender resources strategically is the subject of recent work on Security Games with Signaling (SGS). However, current methods to solve SGS do not scale well in terms of time or memory. We therefore propose a novel approach to SGS, which, for the first time in this domain, employs an Evolutionary Computation paradigm: EASGS. EASGS effectively searches the huge SGS solution space via suitable solution encoding in a chromosome and a specially-designed set of operators. The operators include three types of mutations, each focusing on a particular aspect of the SGS solution, optimized crossover and a local coverage improvement scheme (a memetic aspect of EASGS). We also introduce a new set of benchmark games, based on dense or locally-dense graphs that reflect real-world SGS settings. In the majority of 342 test game instances, EASGS outperforms state-of-the-art methods, including a reinforcement learning method, in terms of time scalability, nearly constant memory utilization, and quality of the returned defender's strategies (expected payoffs). © 2022 International Joint Conferences on Artificial Intelligence. All rights reserved.

关键词： Chromosomes

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