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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Hurta, Martin Schwarzerova, Jana Naegele, Thomas Weckwerth, Wolfram Provaznik, Valentine Sekanina, Lukas Brno University of Technology Faculty of Information Technology Department of Computer Systems Brno Czech Republic Brno University of Technology Faculty of Electrical Engineering and Communication Department of Biomedical Engineering Brno Czech Republic Vienna Austria Lmu Munich Plant Evolutionary Cell Biology Faculty of Biology Munich Germany Vienna Austria

ISBN: (纸本)9798350337488

The polygenic risk score has proven to be a valuable tool for assessing an individual's genetic predisposition to phenotype (disease) within biomedicine in recent years. However, traditional regression-based methods for polygenic risk scores calculation have limitations that can impede their accuracy and predictive power. This study introduces an innovative approach to enhance polygenic risk scores calculation through the application of genetic programming. By harnessing the power of genetic programming, we aim to overcome the limitations of traditional regression techniques and improve the accuracy of polygenic risk scores predictions. Specifically, we showed that a polygenic risk score generated through Cartesian genetic programming yielded comparable or even more robust statistical distinctions between groups that we evaluated within three independent case studies. © 2023 IEEE.

关键词： Computational biology Genetic Programming Genetic Variations Polygenic risk score

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Enhancing Medical Support in the Arabic Language Through Personalized ChatGPT Assistance

arXiv

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arXiv 2024年

作者： Issa, Mohamed Abdelwahed, Ahmed Computer and Systems Department Faculty of Engineering Zagazig University Egypt Faculty of Computer Science and Information Technology Egypt-Japan University for Science and Technology Egypt

This Paper discusses the growing popularity of online medical diagnosis as an alternative to traditional doctor visits. It highlights the limitations of existing tools and emphasizes the advantages of using ChatGPT, which provides real-time, personalized medical diagnosis at no cost. The paragraph summarizes a research study that evaluated the performance of ChatGPT in Arabic medical diagnosis. The study involved compiling a dataset of disease information and generating multiple messages for each disease using different prompting techniques. ChatGPT's performance was assessed by measuring the similarity between its responses and the actual diseases. The results showed promising performance, with average scores of around 76% for similarity measures. Various prompting techniques were used, and chain prompting demonstrated a relative advantage. The study also recorded an average response time of 6.12 seconds for the ChatGPT API, which is considered acceptable but has room for improvement. While ChatGPT cannot replace human doctors entirely, the findings suggest its potential in emergency cases and addressing general medical inquiries. Overall, the study highlights ChatGPT's viability as a valuable tool in the medical field. © 2024, CC BY.

关键词： Diagnosis

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Reliability of Multipath Networks with Optimization of the Location of Inter-Path Communication Nodes

Reliability of Multipath Networks with Optimization of the L...

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2023 International Russian Smart Industry Conference, SmartIndustryCon 2023

作者： Bogatyrev, Vladimir A. Tu Le, Anh Abramova, Evgenia A. Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Security Saint Petersburg Russia University ITMO Faculty of Software Engineering and Computer Technology Saint Peterburg Russia

ISBN: (纸本)9781665464291

The article explores the possibility of improving the reliability of a network with multipath routing. A feature of the proposed study is the analysis of the influence of the placement of switching nodes that switch path segments on the probability of network connectivity with servers of the same type and heterogeneous in functionality. The purpose of the article is to increase the reliability of the network, taking into account the influence of the placement of communication nodes that implement the switching of route segments during reconfiguration, on the connectivity of the network with servers that are homogeneous and heterogeneous in functionality. The research involves the construction of a structural reliability model that takes into account the possibility of failures of both communication nodes and the links between them. The reliability model is built taking into account the availability of request sources with full and non-full access connections to the set of network paths. © 2023 IEEE.

关键词： Reliability

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Experimental Study on Motion Controller based on NN-ARX and ARMAX Actuator Identification for 3-DoF Delta Parallel Robot 11

Experimental Study on Motion Controller based on NN-ARX and ...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Jalali, Hasan Damavandi, Hossein Kalhor, Ahmad Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran Sadjad University Faculty of Computer Engineering and Information Technology Mashhad Iran University of Tehran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350308105

Today, system identification plays a pivotal role in control science and offering a myriad of applications. This paper places its focus on the identification of actuator models within real-world delta robots for informing controller design. Two identification methods, namely NN-ARX and ARMAX, have been employed to extract the dynamic characteristics of the robot actuators, resulting in dynamic models of these integral components being derived. These dynamic models have been utilized in simulations for controller design, and due to the disparities in the identification models, distinct controllers have been realized. Subsequently, these controllers have been practically implemented on delta robots, and their performances have been subjected to a comprehensive comparative analysis. The results demonstrate that controllers integrating the identified actuator models outperformed those designed without the incorporation of the identification models. In practice, the implementation of controllers based on NN-ARX yielded the most favorable results among all the tested controllers. This research not only underscores the importance of accurate actuator models in control system design but also highlights the superior performance of neural network-based controllers in real-world robotic applications. In particular, the practical results of NN-ARX-based controllers were able to achieve significantly lower RMSE of 2.3562, 1.9531, and 2.1185 for the three motors, respectively, as opposed to the 4.1369, 3.0125, and 3.0363 achieved by the ARMAX-based controllers. © 2023 IEEE.

关键词： Controllers

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Predicting Breast Cancer Survival: Comparative Analysis of Machine Learning and Deep Learning Models 5

Predicting Breast Cancer Survival: Comparative Analysis of M...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Bathool, Saliha Alashetty, Ashvini Farquad, M.A.H. School of Engineering And Design Alliance University Bengalore India School of CS &IT. JAIN Deemed-To-Be University Bengalore India Higher Colleges of Technology Faculty of Computer Information Systems Ras Al-Khaimah United Arab Emirates

ISBN: (纸本)9798331530013

The forward-looking study is grounded in the comprehensive chronic cancer death data of Surveillance, Epidemiology, and End Results, one of the most remarkable datasets for breast cancer survival rates ever examined. The approach of this study is to divide patients' data under a particular case feature;in this case, we explore patients' survival rate for breast cancer, which is our main goal. This is done by using the T-test, log-rank test, ANOVA test, and chi-square test, as well as linear regression. In the second part, we include everything from the prediction software to building models. Logistic Regression, Decision Tree and Random Forest Support Vector Machines (S.K.), K-Nearest Neighbors, Naive Bayes, Gradient Boosting, Convolutional Neural Networks, and Long Short-Term Memory Networks Models are heavily evaluated based on various key metrics such as accuracy, precision, and recall. Parameter optimization is performed for each model, and robust validation techniques are implemented to ensure the reliability and generalizability of our findings. The clustered approach is chosen to carry out a comprehensive and systematic explanation of the different factors that may influence the lifespan of women who have survived the cancer and the use of ML and DL models as a predictive tool. Survival anticipation for breast cancer is imperative in the context of personalized therapies. ML and DL models have proven to be powerful instruments in predicting the future states of patients based on their data. © 2024 IEEE.

关键词： Convolutional neural networks

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Cluster Availability Model with information Update Following Node Recovery

Cluster Availability Model with Information Update Following...

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2023 Wave Electronics and its Application in information and Telecommunication systems, WECONF 2023

作者： Bogatyrev, V.A. Bogatyrev, S.V. Sivov, V.V. Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Security Saint Petersburg Russia ITMO University Faculty of Software Engineering and Computer Technology Saint-Petersburg Russia

ISBN: (纸本)9798350348293

A model for evaluating the availability of a fault-tolerant cluster with a constraint on the maximum query service time is proposed. Node recovery in the cluster involves replacing the entire computational node with the latest backup results before the failure. information update after the backup is achieved through the replication of this information from the working nodes of the cluster. The purpose of the article is to assess the reliability of the cluster and its readiness to timely service requests critical to the waiting time. Restoring up-to-date data in a cluster node after previously entering the data saved during backup into it requires the use of resources of the node in which the data is being restored and the node containing up-to-date data. The specified pair of nodes is excluded from the request servicing process, which reduces the likelihood of timely maintenance. information recovery in case of failures of all nodes containing replicas of up-to-date data requires more time compared to replication from the memory of a functioning node. © 2023 IEEE.

关键词： Fault tolerance

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A Perceptual Data Cleansing Model (SDCM) for Reducing the Dirty Data

A Perceptual Data Cleansing Model (SDCM) for Reducing the Di...

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2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Al-Madi, Mohammad Azmi Abdel-Wahab, Ahmed Alshanty, Mohammed Bawazeer, Shaikhan Alzahrani, Mohammed Al-Zaytoonah University of Jordan Faculty of Science and Information Technology Department of Computer Sciences Amman Jordan Arab Open University Faculty of Computer Studies Riyadh Saudi Arabia Al-Azhar University Deprtment of Systems and Computers Engineering Cairo Egypt

ISBN: (纸本)9798350347050

Data cleansing approaches aim at revealing and reducing different types of outsourced errors. Such errors introduce a major issue as data cleansing often involves costly computations and time consumption. Data cleansing is complicated as most of the errors within the obtained data emerge in different forms, such as typos, duplicates, noncompliance with business rules, outdated data, and missing values. In this paper, the Supervised Dataset Cleaning Model (SDCM) is proposed in order to detect and reduce different types of outsourced errors that are stored in the data repository according to the supervised cleaning rules that are practiced from the previous cleaning processes. The findings indicates that the cleaning execution time can be reduced with this supervised model and the accuracy of the model is also increased when it covers the entire training rules and classified error types derived from the data warehouse. There are some expected future directions, which include: implementing full scale of SDCM and comparing the results obtained with different current methods. By comparing different data cleaning algorithms with SDCM, a knowledge gap is likely to arise in the search for further future improvements. © 2023 IEEE.

关键词： Errors

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Comparative Analysis of SVM and CNN Classifiers for EEG Signal Classification in Response to Different Auditory Stimuli

Comparative Analysis of SVM and CNN Classifiers for EEG Sign...

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2024 International Conference on Telecommunications and Intelligent systems, ICTIS 2024

作者： Tibermacine, Ahmed Akrour, Djouher Khamar, Rofeida Tibermacine, Imad Eddine Rabehi, Abdelaziz University of Biskra Department of Computer Science Biskra Algeria Sapienza University of Rome Department of Computer Automation and Management Engineering Rome Italy Zian Achour University of Djelfa Laboratory of Telecommunications and Smart Systems Faculty of Sciences and Technology Djelfa17000 Algeria

ISBN: (纸本)9798331527396

This study aims to classify brainwave patterns using electroencephalogram (EEG) signals in response to various auditory stimuli, specifically Quran recitation, participants' favorite music, and Interstellar's main theme. By analyzing the unique EEG responses elicited by these stimuli, the study explores cognitive and emotional processing differences. Two prominent classifiers, Support Vector Machine (SVM) and Convolutional Neural Networks (CNN), were utilized. SVM, combined with Power Spectral Density (PSD) features, achieved the highest accuracy of 95% when distinguishing Quran recitation from rest. CNN, particularly with Kernel Density Estimation (KDE) features, exhibited strong performance in distinguishing between different auditory stimuli, with an average accuracy exceeding 90%. These results highlight the critical role of feature extraction techniques, such as PSD and KDE, in improving classification performance and deepening our understanding of EEG-based emotional and cognitive responses to auditory stimuli. © 2024 IEEE.

关键词： Convolutional neural networks

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Reliability of a Reconfigurable Network with Segment Switching

Reliability of a Reconfigurable Network with Segment Switchi...

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2023 Wave Electronics and its Application in information and Telecommunication systems, WECONF 2023

作者： Tu, Le Anh Bogatyrev, V.A. Abramova, E.A. ITMO University Faculty of Software Engineering and Computer Technology Saint Peterburg Russia Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Security Saint Petersburg Russia

ISBN: (纸本)9798350348293

The article proposes models of the structural reliability of a multipath routing network with the possibility of its reconfiguration when switching path segments. The models are focused on optimizing the placement of segment switching nodes, aimed at achieving maximum network performance with the option of connecting request sources to the available communication paths with servers. The study considers the options for connecting each source of requests with one of the paths or with all paths for connecting to servers. The paper shows the existence of an optimal placement of path switching nodes, in which the maximum reliability of the system is achieved. © 2023 IEEE.

关键词： Redundancy

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Cooperative Air-Ground Instant Delivery by UAVs and Crowdsourced Taxis 40

Cooperative Air-Ground Instant Delivery by UAVs and Crowdsou...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Gao, Junhui Wang, Qianru Zhang, Xin Shi, Juan Zhao, Xiang Han, Qingye Pan, Yan School of Computer Science Northwestern Polytechnical University China School of Computer Science and Technology Xidian University China Air Force Engineering University China National University of Defense Technology Laboratory for Big Data and Decision China School of Management Science and Real Estate Chongqing University China National University of Defense Technology National Key Laboratory of Information Systems Engineering China National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing China

ISBN: (纸本)9798350317152

Instant delivery has become a fundamental service in people's daily lives. Different from the traditional express service, the instant delivery has a strict shipping time constraint after being ordered. However, the labor shortage makes it challenging to realize efficient instant delivery. To tackle the problem, researchers have studied to introduce vehicles (i.e., taxis) or Unmanned Aerial Vehicles (UAVs or drones) into instant delivery tasks. Unfortunately, the delivery detour of taxis and the limited battery of UAVs make it hard to meet the rapidly increasing instant delivery demands. Under this circumstance, this paper proposes an air-ground cooperative instant delivery paradigm to maximize the delivery performance and meanwhile minimize the negative effects on the taxi passengers. Specifically, a data-driven delivery potential-demands-aware cooperative strategy is designed to improve the overall delivery performance of both UAVs and taxis as well as the taxi passengers' experience. The experimental results show that the proposed method improves the delivery number by 30.1% and 114.5% compared to the taxi-based and UAV-based instant delivery respectively, and shortens the delivery time by 35.7% compared to the taxi-based instant delivery. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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