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A NUMA-aware Graph Database for Hybrid Memory System 21

A NUMA-aware Graph Database for Hybrid Memory System

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21st IEEE International Symposium on Parallel and Distributed Processing with Applications, 13th IEEE International conference on Big Data and Cloud Computing, 16th IEEE International conference on Social Computing and Networking and 13th International conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Tan, Shaoheng Liu, Chang Li, Dingding Tang, Yong Zeng, Deze South China Normal University School of Computer Science Guangdong Guangzhou510631 China China University of Geosciences School of Computer Science Hubei Wuhan430074 China

ISBN: (纸本)9798350329223

Compared to traditional relational databases (RDBMS), specialized graph databases (GDBs) can efficiently store and process graph data in both time and space. Hence, domains like social networks often use GDBs for data management, such as representing friendships. Optane DC Persistent Memory Module (DCPMM) is a novel memory device combining byte-addressability, non-volatility, high density and superior performance. Intuitively, applying GDB on DCPMM with the Non-Uniform Memory Access (NUMA) architecture may improve I/O performance, yet the real performance may be unstable due to stacked hardware characteristics. Specifically, DCPMM exhibits serious NUMA effects and unexpected read/write asymmetry compared to DRAM. To tackle these issues, we propose a NUMA-aware graph database called NAPGDB. NAPGDB employs delegated thread pools to improve the latency of accessing remote nodes. Additionally, it categorizes read/write requests into short-running and long-running tasks, with the former being served synchronously instead of using delegated threads to improve CPU utilization. We implement NAPGDB and the experimental results show that NAPGDB can improve the remote throughput by 1.3x-1.7x compared with the multithreaded Redis with RedisGraph. © 2023 IEEE.

关键词： Graph databases

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A software Tool for Microwave Tomography 24th

A Software Tool for Microwave Tomography

引用

24th Argentinian Congress of Bioengineering (SABI) / 13th Clinical engineering conference (SABI)

作者： Jose Cervantes, Maria Gomez, Javier Luparello, Diego Morales, Martin Fajardo, Jesus Galvan, Julian Caiafa, Cesar F. Irastorza, Ramiro M. Inst Fis Liquidos & Sistemas Biol IFLySiB CONICET La Plata Argentina Univ Nacl Arturo Jauretche Inst Ingn & Agron Florencio Varela Argentina Univ Michigan Dept Radiol Ann Arbor MI 48109 USA Inst Argentino Radioastron IAR CONICET CCT La Pla Villa Elisa Argentina

ISBN: (纸本)9783031619595;9783031619601

the objective of this work was to show the development of an open-source software tool in Python code for microwave tomography. the forward problem was solved by three numerical approaches: finite element method, method of moments, and finite difference time domain method. It was implemented using modern and efficient numerical libraries (FEniCSx and Meep). the software was focused in the transversal magnetic mode propagation problem in two dimensions. Two classic algorithms were programmed in order to solve the inverse problem (Born and Backpropagation) and other will be added in the future. the aim of this project is to develop a tool for academic and educational purposes, and to promote collaboration between groups working in this field.

关键词： Microwave imaging forward problem inverse problem

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A novel 24- Hour deep neural network based Streamflow Forecasting method in Data-Scarce Regions 13

A novel 24- Hour deep neural network based Streamflow Foreca...

引用

13th Smart Grid conference, SGC 2023

作者： Taheri, Parissa Taheri, Sahra Taheri, Masoume Taheri, Gelare Shomal University Civil Engineering Transportation Major Water Resources Expert of the Regional Water Company of Alborz Province Iran Gorgan University Water Resources Management Engineering Iran Kharazmi University Artificial Intelligence Engineering Financial Expert of the Electricity Distribution Company of Alborz Province Iran Alzahra University Software Engineering Information Technology Expert of Refah Kargaran Bank Tehran Province Iran

ISBN: (纸本)9798350396065

Accurate forecasting of streamflow is vital for effective water resource management and environmental conservation, particularly in regions with limited hydrological data. this paper presents a pioneering 24-hour streamflow forecasting method designed for areas with sparse data. By harnessing deep neural networks, this approach addresses challenges associated with scarce and unreliable data. the model's performance is evaluated using data from diverse hydrological domains, highlighting its adaptability and robustness. the results indicate that the deep neural network-based model surpasses traditional methods, offering more reliable streamflow predictions. this research contributes to disaster preparedness, efficient resource allocation, and environmental sustainability, while also paving the way for broader applications of machine learning in hydrology. © 2023 IEEE.

关键词： Deep neural networks

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NUMERICAL MODELLING OF MASS TIMBER BEAM-COLUMN CONNECTIONS 13

NUMERICAL MODELLING OF MASS TIMBER BEAM-COLUMN CONNECTIONS

引用

13th World conference on Timber engineering: Timber for a Livable Future, WCTE 2023

作者： Jayasekara, Labuwatte Manathum Milindu B. Foster, Robert M. Department of Engineering University of Cambridge United Kingdom

ISBN: (纸本)9781713873297

Multi-storey timber buildings are becoming increasingly popular due to advancements in engineered timber technology. Sophisticated timber connections in such buildings play a critical role in both the performance and safety of the structure, particularly in accidental and earthquake situations. therefore, a thorough understanding of timber connection behaviour is necessary for safe and efficient building design. However, few existing studies capture timber connection behaviours in a sufficiently comprehensive manner to be applied to the complex loading conditions that can occur in accidental situations. this study develops a computational modelling approach that can predict intricate pre- and post-failure behaviours of timber beam-column connections under various loading conditions. First, the commercially available Finite Element software package Abaqus was used to model a timber beam-column connection. then, nonlinear quasi-static analyses were performed under shear and moment conditions. Finally, sensitivity analyses were conducted to ensure that the model produces consistent results. the computational results obtained agree well with experimental results available in the literature. the developed numerical modelling approach is thus shown to have potential for simulating the complicated behaviour of timber connections under loads and, hence, for the design of safe, efficient timber connections. © 13th World conference on Timber engineering, WCTE 2023. All rights reserved.

关键词： Sensitivity analysis

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Bacterial Strain Classification using Convolutional Neural Network for Automatic Bacterial Disease Diagnosis 13

Bacterial Strain Classification using Convolutional Neural N...

引用

13th International conference on Cloud Computing, Data Science and engineering, Confluence 2023

作者： Trivedi, Sandeep Patel, Nikhil Faruqui, Nuruzzaman Deloitte Consulting Llp Houston United States University of Dubuque Iowa United States Daffodil International University Department of Software Engineering Daffodil Smart City Dhaka Bangladesh

ISBN: (纸本)9781665462631

Diseases caused by bacterial contamination are common causes of human illness. Different bacterial strains are responsible for different types of diseases. there are more than 4,900 different strains so far have been discovered. that is why it is impractical to start the treatment of diseases caused by bacterial attacks without diagnosing the particular strain that caused the diseases. the traditional method of bacterial strain classification from the specimens is still widely used in microbiological practice for clinical application. However, it s a time-consuming process and requires well-trained, experienced microbiologists. this paper proposes a computer-aided artificial intelligent-based automatic bacterial strain classification method that is faster than traditional methods and a potentially better alternative. We designed, optimized, and experimented with a Convolutional Neural Network (CNN) to automatically classify bacterial strains from the digital images of the bacterial strains captured using an SC30 camera from an Olympus CX31 Upright Biological Microscope. the proposed network classifies the bacterial strains with 95.12% accuracy, 96.01% precision, 96.70% recall, and 4.88% error rate. this paper uses an innovative image augmentation method to overcome the limitation of the number of training images. the proposed network performs better than similar approaches regarding classification accuracy and network simplicity. © 2023 IEEE.

关键词： Diseases

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Quantifying Object-Oriented System Complexity: Introducing a Powerful Measurement Tool 13

Quantifying Object-Oriented System Complexity: Introducing a...

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13th IEEE International conference on System engineering and Technology, ICSET 2023

作者： Jasser, Muhammed Basheer Zhen, Lee Ming Issa, Bayan Hong, Ling Mee Al-Hadi, Ismail Ahmed Al-Qasem Sunway University Department of Computing and Information Systems Selangor Sunway City Malaysia University of Aleppo Faculty of Informatics Engineering Syria Institute of Computer Science & Digital Innovation UCSI University Kuala Lumpur Malaysia

ISBN: (纸本)9798350340891

A lot of metrics and tools have been devised to measure the complexity of software systems. through measurement, software professionals can have a better understanding and control of a software's complexity. In this paper, we reviewed complexity metrics and tools for object-oriented systems. the existing tools measure either implemented systems which may be source code or compile binaries, or class diagrams. the tools that measure implemented systems already offer a wide variety of features to satisfy different needs. However, the tools that measure class diagrams are not only poor in amount, but all take in class diagram XMI files, with none of them taking in PlantUML class diagram source code. PlantUML is a popular text-based UML diagramming tool that enables users to define UML diagrams with a domain specific language then renders the diagram for them. Hence, we developed a web application that measures class diagram complexity via PlantUML class diagram source code. It measures five class metrics and seven system metrics visualized as tables and bar charts, with the results exportable to PDF and CSV. Our tool's measurements were also evaluated to be correct when it is within our scope of supported syntax. © 2023 IEEE.

关键词： Object oriented programming

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Intelligent Covid-19 Vaccine Supplychain Management System 13

Intelligent Covid-19 Vaccine Supplychain Management System

引用

13th International conference on Information and Communication Systems (ICICS)

作者： Abdelgani, Yazan Makki, Qasem H. Ali, Hussein AlZu'bi, Shadi Al Zaytoonah Univ Jordan Fac Sci & Informat Technol POB 130 Amman 11733 Jordan

ISBN: (纸本)9781665480970

In light of the trend of countries to give vaccines to their people, it was concluded that the best solution to confront the COVID-19 pandemic is to give the vaccine, as it prevents its transmission from person to person, and if the infection is infected, the symptoms are much less than the degree of danger of the person who did not meet the vaccine. In this paper, we presented tables on the types of vaccines, a brief explanation of the Coronavirus, and the idea of our software project. Vaccine handling skills, where gives users the opinions of the people who received the vaccine and the doctors also according to the age group and the disease.

关键词： Covid-19 Vaccine Big Data Artificial Intelligence Deep Learning databases

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A Non-Intrusive Load Monitoring Method Based on Relative Position Matrix and Residual Network 13

A Non-Intrusive Load Monitoring Method Based on Relative Pos...

引用

13th International conference on Intelligent Control and Information Processing, ICICIP 2025

作者： Huang, Jin-Yang Chen, Chun-Hua Jiang, Yi Yan, Junwei Zhang, Jun Zhan, Zhi-Hui School of Software Engineering South China University of Technology Guangzhou China Department of Electrical and Electronic Engineering Hanyang University Ansan Korea Republic of School of Mechanical and Automotive Engineering South China University of Technology Guangzhou China College of Artificial Intelligence Nankai University Tianjin China

ISBN: (纸本)9798331516147

Non-Intrusive Load Monitoring (NILM) technology identifies various appliances’ types and operational status by analyzing electrical data collected from sensors in residential or commercial buildings, offering significant practical value. However, due to the limitations of existing methods for constructing appliance features, the identification performance of NILM models needs improvement. Addressing this, we propose a method for constructing appliance features based on a relative position matrix (RPM), which more accurately captures the temporal characteristics of electrical data compared to other methods. Additionally, a deep learning model based on the improved ResNet18 with multi-scale fusion is proposed for the load identification task. In this paper, comparative experiments were conducted on the PLAID dataset. We compared the RPM with three appliance feature construction methods: voltage-current trajectory (VI), markov transition field (MTF), and gramian angular field (GAF). We also compared our results with advanced methods reported in other literature. the results show that this method outperforms existing methods in terms of precision, recall, and F1 score across various evaluation metrics. © 2025 IEEE.

关键词： Markov processes

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the Fault-Resistant Web Application Infrastructure Using Autoscaling 13

The Fault-Resistant Web Application Infrastructure Using Aut...

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13th International conference on Advanced Computer Information Technologies, ACIT 2023

作者： Korobeinikova, Tetiana Chekhmestruk, Roman Mykhaylov, Pavlo Romanyuk, Olexandr Romanyuk, Oksana Achanyar, Hamza Lviv Polytechnic National University Department of Information Technology Security Lviv Ukraine 3D GENERATION UA LLC Vinnytsia Ukraine 3D GENERATION GmbH Dortmund Germany Vinnytsia National Technical University Faculty of Information Technologies and Computer Engineering Vinnytsia Ukraine

关键词： auto-scaling client server

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Automation of Measurements for Digital Posturography in a Standing Position: software EPPA! 24th

Automation of Measurements for Digital Posturography in a St...

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24th Argentinian Congress of Bioengineering (SABI) / 13th Clinical engineering conference (SABI)

作者： Oleari, Cristina Fusco, Mara Molina, Diego Edwards Miralles, Monica T. Univ Buenos Aires Fac Ciencias Med Catedra Biomecan & Anat Func Buenos Aires DF Argentina Pontificia Univ Catolica Argentina Fac Ingn & Ciencias Agr Lab Biomecan & Ingn Para Salud Buenos Aires DF Argentina Univ Tecnol Nacl Fac Reg Haedo Buenos Aires DF Argentina Univ Buenos Aires Fac Arquitectura Diseno & Urbanismo Ctr Invest Diseno Ind Prod Complejos Buenos Aires DF Argentina

ISBN: (纸本)9783031619595;9783031619601

this paper introduces the development of the EPPA! software, with its Spanish acronym, "Evaluacion Posturografica de Pie Automatizada," created using Matlab R2019a from Mathworks (R). EPPA! serves the following purposes: a) To facilitate the objective evaluation of posture in a standing position through the standardization of 55 (fifty-five) variables (linear (+/- 1 cm) and angular (+/- 2 degrees)), linked to anatomical indicators in digital posturographs in the standing position. b) To provide access to intersegmental postural diagnoses based on regions, planes, and views, with respect to ideal reference lines and normality ranges. c) To enable additional measurements of the evaluator's choice, beyond the standardized ones, tailored to the clinical case and the significance of specific anatomical regions or singularities of interest. To validate the software, a comparisonwith the open-source software Kinovea (c) 0.9.5was conducted using a pilot sample (n= 6) of older adult volunteers of both genders, who were referred for postural treatment due to diagnoses of orthopedic and/or traumatological musculoskeletal conditions. this study excluded individuals with neurological pathologies affecting motor control. the comparison was carried out by healthcare professionals with expertise in posturographic assessment. We found significant differences in the results of this comparison, with the Two One-Side Test (TOST) based on the normality of variable (linear and angular) in paired samples (p < 0.05).

关键词： Human posture Postural Evaluation Posturography software design Physical therapy

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