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检索条件"任意字段=International Conference on Measurement and Modeling of Computer Systems"

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Detecting Semantic Similarity of Diseases based Machine Learning

Detecting Semantic Similarity of Diseases based Machine Lear...

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2023 IEEE international conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Qumsiyeh, Emma Yousef, Malik Salah, Zaidoun Jayousi, Rashid Al-Quds University Department of Computer Science and Information Technology Jerusalem Palestine Zefat Academic College Galilee Digital Health Research Center Department of Information Systems Zefat Israel Arab American University Molecular Genetics and Genetic Toxicology Ramallah Palestine

ISBN: (纸本)9798350337488

Identifying disease-disease associations (DDAs) is critical in medicine and systems biology, providing valuable insights into the complex relationships among different diseases. Recent advances in systems biology and the increasing availability of diverse biological data have provided opportunities for such research. However, the heterogeneity of the data makes it difficult to identify disease associations. To develop effective methods for predicting DDAs, it is necessary to leverage data at the molecular level. In this study, utilizing the Grouping-Scoring-modeling approach, we have developed a statistical technique to compute a semantic similarity metric between the disease under study and other diseases. We have also used Jaccard similarity to compute similarity among disease groups. We have considered GediNETPro, using machine learning techniques, to record, over the Monte Carlo cross-validation, all the ranks based on the scores assigned by the S component to each disease group. The K-means clustering algorithm is applied to these recorded ranks for each disease group to detect patterns of similar diseases by placing them into coherent clusters. A cluster score (named as cluster-score) is assigned for each cluster by averaging the ranks of its members. Notably, the lowest cluster score is the more significant one. The semantic approach is applied to the top-ranked clusters to detect a semantic relationship between the disease under investigation and other diseases (groups). In addition, we have applied diversity metrics based on the Jaccard measurement to each disease cluster to support the semantic findings. A high value of diversity indicates a greater likelihood of detecting distinct groups with semantic relationships. This study enhances our understanding of disease associations and increases our ability to improve treatment strategies. This is especially important in a context where disease associations go beyond the scope of genetic factors. © 2023 IEEE.

关键词： disease-disease associations diversity metrics GediNETPro Grouping-Scoring-modeling approach Jaccard index Jaccard similarity K-means clustering algorithm machine learning Monte Carlo cross-validation semantic similarity

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SIGMETRICS 2013 - Proceedings of the 2013 ACM SIGMETRICS international conference on measurement and modeling of computer systems

SIGMETRICS 2013 - Proceedings of the 2013 ACM SIGMETRICS Int...

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2013 ACM SIGMETRICS international conference on measurement and modeling of computer systems, SIGMETRICS 2013

ISBN: (纸本)9781450319003

The proceedings contain 56 papers. The topics discussed include: a first look at cellular network performance during crowded events;characterizing and modeling the impact of wireless signal strength on smartphone battery drain;a large-scale service system with packing constraints: minimizing the number of occupied servers;online energy generation scheduling for microgrids with intermittent energy sources and co-generation;root cause detection in a service-oriented architecture;the design space of probing algorithms for network-performance measurement;scheduling of users with Markovian time-varying transmission rates;exact analysis of the M/M/k/setup class of Markov chains via recursive renewal reward;stochastic modeling of large-scale solid-state storage systems: analysis, design tradeoffs and optimization;quantifying the benefits of joint content and network routing;and on understanding the energy consumption of arm-based multicore servers.

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Reliability Analysis of DC EV Charging Stations for E-Mobility 50

Reliability Analysis of DC EV Charging Stations for E-Mobili...

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50th Annual conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Masum, Mahmudul Islam Chen, Sipeng Kiran, Dhruva Sankalp Hassan Franco, Kenny Behnamfar, Milad Amaan, Adil Tariq, Mohd Sarwat, Arif School of Computing and Information Sciences Florida International University Miami United States Department of Electrical and Computer Engineering Florida International University Miami United States Harman International Whitefield Bangalore560066 India

ISBN: (纸本)9781665464543

This research paper discusses the reliability analysis of Direct Current (DC) Electric Vehicle (EV) charging stations, focusing on their crucial role in advancing sustainable transportation. Utilizing Continuous Markov Processes, the methodology assesses the dependability of key components in DC charging systems, such as inverters, resonant circuits, transformers, and rectifiers. Real-world operational data and failure rates derived from MIL-HDBK-217 are employed for analysis, and the study utilizes the Markov process to model the system’s dynamic behavior, presenting results that affirm the high reliability (0.9993) of the DC charging infrastructure over a ten-year period. The impact of different Mean Time to Repair (MTTR) on system reliability is considered. The reliability analysis is conducted using dedicated software designed for Markov modeling and system reliability assessment. © 2024 IEEE.

关键词： Markov processes

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The Trustworthiness measurement Model of Component based on Spherical Fuzzy Sets

The Trustworthiness Measurement Model of Component based on ...

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computer, Vision and Intelligent Technology (ICCVIT), international conference on

作者： Songpo Meng Yanfang Ma School of Computer Science and Technology Huaibei Normal University Huaibei China School of Computer Science and Engineering Changzhou Institute of Technology Changzhou China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

With the continuous increase of functions of the software system, a highly trustworthy software system can help users solve problems in daily life better. How to evaluate a software system's trustworthiness has become an important problem in software engineering. Based on subjective and objective weights, this paper proposes a method to calculate the trustworthiness of components. Firstly, based on spherical fuzzy sets, expert weights are determined by expert similarity, and the subjective weights of component attributes are obtained by combining expert weights with the evaluation of component attributes by experts. Secondly, the initial variance of component attributes is improved, and the objective weight of component attributes is calculated by using the improved variance method. Furthermore, combining the subjective and objective weights, the component attribute weight distribution method is proposed, and then the component trustworthiness measurement model is established. Finally, the component’s trustworthiness in the cross-border medical management system project is evaluated to show the rationality of the measurement model.

关键词： Weight measurement Fuzzy sets computer vision Analytical models Computational modeling Software systems Software engineering

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An Extensive Analysis of Data Clumps in UML Class Diagrams 19

An Extensive Analysis of Data Clumps in UML Class Diagrams

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19th international conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2024

作者： Baumgartner, Nils Pulvermüller, Elke Software Engineering Research Group School of Mathematics/Computer Science/Physics Osnabrück University Osnabrück49090 Germany

ISBN: (纸本)9789897586965

This study investigated the characteristics of data clumps in UML class diagrams. Data clumps are group of variables which appear together in multiple locations. In this study we compared the data clumps characteristics in UML class diagrams with them of source code projects. By analyzing the extensive Lindholmen and GenMyModel datasets, known for their real–world applicability, diversity, and containing more than 100,000 class diagrams in total, significant differences in the distribution and nature of data clumps were revealed. Approximately 19 % of the analyzed class diagrams contained data clumps. It was observed that field–field data clumps predominated in UML class diagrams, particularly in the GenMyModel dataset, while parameter–parameter data clumps were less frequent. Moreover, in contrast to the distribution in source code projects, data clumps in UML class diagrams were typically distributed across multiple classes or interfaces, forming larger chains. parameter–parameter data clumps were predominant in source code projects, indicating more detailed implementation of methods in these projects. These findings reflect different modeling approaches and paradigms among the respective user groups. This study has provided important insights regarding the development of UML modeling tools, teaching methods, and design practices in software development. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Design

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Assessment of Urban Drainage Capacity and Flood Risk Based on Computing Simulation

Assessment of Urban Drainage Capacity and Flood Risk Based o...

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2023 international conference on computer Simulation and modeling, Information Security, CSMIS 2023

作者： Tang, Chuanjun Wang, Hanlin Hou, Te Ren, Gaoxiang Liu, Zhipeng Wang, Shoudong Cai, Wei Xiao, Bin Wang, Yanbiao Beijing Capital International Airport Co. Ltd. Beijing China Beijing Capital International Airport Co. Ltd. Beijing Capital International Airport Information Technology Department Beijing China Beijing Capital International Airport Co. Ltd. Beijing Capital International Airport Terminal Area Monitor&Control Center Beijing China ZhengYuan Geomatics Group Co. Ltd. ZhengYuan Geomatics Group HIT ZhengYuan Information Technology Department Beijing China

ISBN: (纸本)9798350343724

Heavy rainfall often triggers urban flood disasters, which are the primary natural calamity encountered by cities. These events not only have a significant impact on urban transportation but also jeopardize the safety of residents and their assets. Using computer and GIS technology, this research developed a hydrodynamic simulation model that combines one-dimensional and two-dimensional approaches to simulate urban areas. The simulations were conducted based on prescribed rainfall patterns for various return periods, including 1-year, 2-years, 3-years, 10-years, and 50-years. The GIS system was utilized to visualize the outcomes of the simulation. The primary findings can be summarized as follows: The integration of computer technology and GIS can equip a theoretical basis and technical backing for urban flood management, drainage systems, and the planning of inundation zones. Moreover, the simulation results can be displayed with accuracy and in an aesthetically engaging fashion. The current drainage system in the study area still has certain risks, such as multiple water accumulation points, deep water accumulation, and a wide range of water accumulation. Hence, there is a need to undertake well-considered planning and modernization of the existing drainage infrastructure in order to enhance its flood resilience. © 2023 IEEE.

关键词： Urban transportation

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Smartphone Based Food Classification: Applications, Challenges, and Future Prospects for Diabetics 20

Smartphone Based Food Classification: Applications, Challeng...

引用

20th IEEE international conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT, HONET 2023

作者： Crystal, Afnan Ahmed Valero, Maria Nino, Valentina Kennesaw State University Department of Computer Science United States Kennesaw State University Department of Information Technology United States Kennesaw State University Department of Industrial and Systems Engineering United States

ISBN: (纸本)9798350331110

Diabetes has become a global health concern, posing risk to millions of individuals. Managing dietary consumption is crucial for the overall health of diabetic patients. Traditional methods of monitoring food intake can be tedious and unreliable. However, computer vision-based solutions, such as image-based food recognition systems (FIRS) using mobile cameras, offer automated and efficient ways to track food intake. This systematic review examines mobile computer vision approaches for food classification, volume estimation, and calorific measurement. Besides, the study discusses the potential integration of Glycemic Index estimation to FIRS to benefit diabetic patients. Future directions and issues related to FIRS are also explored. © 2023 IEEE.

关键词： Health risks

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Design of Charge Point Based on Rectangular Self Convolution Window Algorithm Data measurement 1

引用

13th international conference on Frontier Computing, FC 2023

作者： Li, Wanzhong Shandong Anlan Power Technology Co LTD. Shandong Zibo255000 China

ISBN: (数字)9789819995387

ISBN: (纸本)9789819995370

The charge point design based on the rectangular self convolution window algorithm data measurement is to use the rectangular self convolution window to measure the electric field strength in a certain area. This method can simultaneously measure electric field strength, voltage and current. The main advantage of this method is that it can be applied to any type of charging equipment at any location without changing its form or structure. In addition, the method has no effect on the charging system itself;Therefore, it can be used to test different types of charging systems. In this paper, the main circuit units of electric vehicle charging pile are designed, including rectifier unit, power conversion unit and human-computer interaction unit, and the rectifier unit and power conversion unit are modeled. For the rectifier unit, VIENNA rectifier is used to replace the common power frequency rectifier to provide DC with good power quality. Then DC-DC full bridge power conversion is performed on the output DC current, and the output is adjusted by phase shifting control. Finally, the human-computer interaction unit is designed, and the work flow chart of the human-computer interaction system is given. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Rectifying circuits

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Dual-IMU-WIP: An easy-to-build Walk-in-Place System based on Inertial measurement Units 10

Dual-IMU-WIP: An easy-to-build Walk-in-Place System based on...

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10th IEEE international conference on Computational Intelligence and Virtual Environments for measurement systems and Applications (IEEE CIVEMSA)

作者： Uhlmann, Tom Brunnett, Guido Tech Univ Chemnitz Chemnitz Germany

ISBN: (数字)9781665434454

ISBN: (纸本)9781665434454

Locomotion interfaces for virtual environments remain an active field of research. Walk-in-place (WIP), where the intent to move is communicated to the system by taking steps on the spot, provides a realistic experience to the user without being confined to a limited tracking area. The proposed systems found in the literature have complex setups, require bulky hardware, and use closed source software, which makes reproduction of the results as well as follow-up research difficult or impossible. We propose an easy-to-build wireless WIP system based on consumer grade electronic components which is versatile, affordable, and extensible. We use the rotation and position data of inertial measurement units attached to the user's left and right shin, perform signal processing directly on the device, and show how to use this data for continuous movement in a virtual environment. Our locomotion interface uses a state machine and features low start and stop latencies as well as the detection of foot gestures for rotation and sideward movements. The proposed device is small enough to be mounted on a pair of shin guards. We developed an exercise application to proof that our system works in a practical scenario, where the user moves through a virtual environment by using her/his legs only. We publish building plans of the device and make our software open source in order to make our results replicable and allow for follow-up research.

关键词： Walk-in-Place Locomotion Interface Virtual Environment Input Device Human-computer Interaction

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Enhancing the Efficiency of the Grouping-Scoring-modeling Framework with Statistical Pre-Scoring Component for Transcriptomic Data Analysis

Enhancing the Efficiency of the Grouping-Scoring-Modeling Fr...

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18th international Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2025

作者： Khokhar, Maham Bakir-Gungor, Burcu Yousef, Malik Department of Data Science Social Sciences Institute Abdullah Gul University Kayseri38080 Turkey Department of Computer Engineering Faculty of Engineering Abdullah Gul University Kayseri38080 Turkey Department of Information Systems Galilee Digital Health Research Center Zefat Academic College Zefat13206 Israel

The advent of high-throughput transcriptomic technologies has generated vast transcriptomic datasets, challenging current analytical methodologies with their sheer volume and complexity. The Grouping-Scoring modeling (G-S-M) approach is one of the recent approaches that treat groups of genes (or clusters of genes) by embedding prior biological knowledge with machine learning in order to detect the most significant groups for classification tasks. The G-S-M might need to treat thousand ten thousand of groups (scoring those groups) which might affect the speed and performance of the algorithm. In response, this study introduces the Pre Scoring G-S-M model, an enhancement of the established Grouping-Scoring-modeling (G-S-M) framework. This approach incorporates a Pre-Scoring component that leverages the Limma package for its empirical Bayes methods to optimize initial transcriptomic data evaluation through a percentage-based selection of statistically significant gene groups. Aimed at reducing computational demand and streamlining feature selection, the model also addresses data redundancy by eliminating duplicate gene-disease associations. Application to nine human gene expression datasets from the GEO database showed promising results. It demonstrated improvements in computational efficiency and analytical precision while reducing the number of features selected per dataset compared to the traditional G-S-M approach, without compromising accuracy. These initial findings highlight the Pre-Scoring G-S-M model's potential to enhance transcriptomic data analysis, indicating a promising direction for future bioinformatics research. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Data accuracy

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