检索结果-内蒙古大学图书馆

Comparison Analysis of Data Sending Performance Using The Cayenne and ThingSpeak IoT Platform 4

学校读者我要写书评

暂无评论

Comparison Analysis of Data Sending Performance Using The Ca...

4th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2022

作者： Pranoto, Kirana Astari Ramadhan, Yogi Reza Caesarendra, Wahyu Triwiyanto Glowacz, Adam Dash, Santanu Kumar Wahyono, Bambang T Faculty of Integrated Technologies Universiti Brunei Darussalam Gadong BE1410 Brunei CV. Rekayasa Desain Manufaktur Semarang Indonesia Department of Electromedical Engineering Politeknik Kesehatan Surabaya Surabaya Indonesia Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Agh University of Science and Technology Poland Vellore Institute of Technology Vellore Tamil Nadu India Faculty of Computer Science Universitas Pembangunan Nasional Veteran Jakarta Jakarta Indonesia

ISBN: (纸本)9781665473279

The speed and accuracy of an IoT platform are crucial in a data transfer process. On a simple data transfer, the speed differential may not have much of an impact on the validity or accuracy. However, significant variations in data reading speed will adversely affect the accuracy of the processed data in data transfer activities that include a large volume of data and are carried out continually. This research was conducted to discover a comparison between the Cayenne IoT platform and the ThingSpeak IoT platform based on the speed of data transmission and the accuracy of data reading, which is then expected to be used to develop further projects. In this study, a simple temperature reading device was made using the DS18B20 temperature sensor as a temperature reading component controlled by the ESP8266 microcontroller. The ESP8266 also operates to process data which will then be sent to the IoT platform using the uPyCraft IDE to program the ESP8266 microcontroller. This research was accomplished by measuring the temperature of three different conditions of water as a reference value. The previous research shows that the Cayenne IoT platform displays data faster than the ThingSpeak IoT platform (about 2 to 5 seconds). However, the accuracy level refers to the result of the difference in the average temperature reading of the IoT ThingSpeak platform digital thermometer, which is more accurate than Cayenne. The difference generated by the Cayenne IoT platform in room temperature water is 2.9%, in hot water is 1.52%, and in cold water is 3.47%. On the other hand, ThingSpeak obtained the difference in room temperature water by 3.04%, hot water by 1.5%, and cold water by 3.06%. Inaccessible mode, the Cayenne IoT platform can display sensor readings according to the program created at intervals of two seconds. © 2022 IEEE.

关键词： Data transfer

Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Daniol, Mateusz Hemmerling, Daria Sikora, Jakub Jemiolo, Pawel Wodzinski, Marek Wojcik-Pedziwiatr, Magdalena The AGH University of Kraków Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Krakow Poland Information Systems Institute Sierre Switzerland The Andrzej Frycz Modrzewski Krakow University Department of Neurology Krakow Poland

Parkinson's disease ranks as the second most prevalent neurodegenerative disorder globally. This research aims to develop a system leveraging Mixed Reality capabilities for tracking and assessing eye movements. In this paper, we present a medical scenario and outline the development of an application designed to capture eye-tracking signals through Mixed Reality technology for the evaluation of neurodegenerative diseases. Additionally, we introduce a pipeline for extracting clinically relevant features from eye-gaze analysis, describing the capabilities of the proposed system from a medical perspective. The study involved a cohort of healthy control individuals and patients suffering from Parkinson's disease, showcasing the feasibility and potential of the proposed technology for non-intrusive monitoring of eye movement patterns for the diagnosis of neurodegenerative diseases. Copyright © 2024, The Authors. All rights reserved.

关键词： Augmented reality

Novel Composite Material with Thermally Conducting and Adsorption Capabilities for Localized Cooling

学校读者我要写书评

暂无评论

Novel Composite Material with Thermally Conducting and Adsor...

International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)

作者： Nitin Satpute Aditya Sudhir Tupe Varad Nitin Yardi Mangesh Choudhary Marek Iwaniec Ramesh Narina Mechanical Engineering Department Vishwakarma University Pune India Department of Art and Design Vishwakarma University Pune India Department of Design Vishwakarma University Pune India Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science & Technology Krakow Poland

ISBN: (数字)9798350378627

ISBN: (纸本)9798350378634

The presented work discloses a new method of heat dissipation, with use of a composite material vessel. The conceived vessel is manufactured from clay and copper powder, which has adsorption and better thermal conductivity characteristics. The composite vessel contains water inside the cavity and has a thermally insulating layer at the bottom. The water has direct contact with the vessel walls and gets adsorbed inside the vessel. The heat from the source is directed to the vessel material and is used to evaporate the water adsorbed inside the vessel, leading to desorption of the water contained inside the vessel. Continuous cycles of adsorption and desorption ensure that the heat from the vessel is utilized to provide latent heat of vaporization to the water. Experiments are conducted with different test cases to demonstrate the effectiveness of the proposed method of heat dissipation over that of the conventional method of free and forced convection.

关键词： Micromechanical devices Powders Cooling Composite materials Adsorption Water heating Conductivity

Improving Quality Control of Whole Slide Images by Explicit Artifact Augmentation

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Jurgas, Artur Wodzinski, Marek D’Amato, Marina van der Laak, Jeroen Atzori, Manfredo Müller, Henning AGH University of Krakow Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Krakow30059 Poland Institute of Informatics Sierre3960 Switzerland Radboud University Medical Center Nijmegen Netherlands Department of Neuroscience University of Padova Padova Italy Medical Faculty University of Geneva Geneva Switzerland

The problem of artifacts in whole slide image acquisition, prevalent in both clinical workflows and research-oriented settings, necessitates human intervention and re-scanning. Overcoming this challenge requires developing quality control algorithms, that are hindered by the limited availability of relevant annotated data in histopathology. The manual annotation of ground-truth for artifact detection methods is expensive and time-consuming. This work addresses the issue by proposing a method dedicated to augmenting whole slide images with artifacts. The tool seamlessly generates and blends artifacts from an external library to a given histopathology dataset. The augmented datasets are then utilized to train artifact classification methods. The evaluation shows their usefulness in classification of the artifacts, where they show an improvement from 0.10 to 0.01 AUROC depending on the artifact type. The framework, model, weights, and ground-truth annotations are freely released to facilitate open science and reproducible research. © 2024, CC BY.

关键词： Quality control

A Systematic Literature Review on Task Allocation and Performance Management Techniques in Cloud Data Center

学校读者我要写书评

暂无评论

computer Systems Science & engineering 2024年第3期48卷 571-608页

作者： Nidhika Chauhan Navneet Kaur Kamaljit Singh Saini Sahil Verma Abdulatif Alabdulatif Ruba Abu Khurma Maribel Garcia-Arenas Pedro A.Castillo University Institute of Computing Chandigarh UniversityPunjab143001India Department of Computer Science and Engineering Chandigarh UniversityPunjab143001India Department of Computer Science and Engineering Uttaranchal UniversityUttarakhand248007India Department of Computer Science College of Computer Qassim UniversityBuraydah52571Saudi Arabia MEU Research Unit Faculty of Information TechnologyMiddle East UniversityAmman11831Jordan Department of Computer Engineering Automatics and RoboticsUniversity of GranadaGranada18071Spain Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

As cloud computing usage grows,cloud data centers play an increasingly important *** maximize resource utilization,ensure service quality,and enhance system performance,it is crucial to allocate tasks and manage performance *** purpose of this study is to provide an extensive analysis of task allocation and performance management techniques employed in cloud data *** aim is to systematically categorize and organize previous research by identifying the cloud computing methodologies,categories,and gaps.A literature review was conducted,which included the analysis of 463 task allocations and 480 performance management *** review revealed three task allocation research topics and seven performance management *** allocation research areas are resource allocation,load-Balancing,and *** management includes monitoring and control,power and energy management,resource utilization optimization,quality of service management,fault management,virtual machine management,and network *** study proposes new techniques to enhance cloud computing work allocation and performance ***-comings in each approach can guide future *** research’s findings on cloud data center task allocation and performance management can assist academics,practitioners,and cloud service providers in optimizing their systems for dependability,cost-effectiveness,and *** methodologies can steer future research to fill gaps in the literature.

关键词： Cloud computing data centre task allocation performance management resource utilization

A novel framework for differentiating vessel-like objects in coronarography images

学校读者我要写书评

暂无评论

A novel framework for differentiating vessel-like objects in...

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Witold Serwatka Katarzyna Heryan Joanna Sorysz Marcin Jarzab Kamil Sterna Faculty of Computer Science Electronics and Telecommunications AGH University of Science and Technology Krakow Poland Autosymed SRL Iasi Romania Department of Measurement and Electronics AGH University of Science and Technology Krakow Poland Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science and Technology Krakow Poland

Coronary Artery Disease is the leading cause of death worldwide. Its prevalence will grow while access to specialized medical care will be further limited due to staff shortages. Therefore, any facilitation of diagnosis or treatment is of paramount importance. The diagnosis based on Coronary Angiography can be automated to perform a quantitative evaluation of lesions. This requires precise segmentation of coronary arteries. At the moment, the state-of-the-art algorithms fail to eliminate vessel-like artifacts that are wrongly included in segmentation results (e.g. catheters, stitches). This is a bottleneck for the automatization of the diagnosis workflow that precedes clinical action. In this paper, we propose a 2-step post-segmentation refinement algorithm. A binary segmentation of the coronary arteries is used to extract image features - inputs for an XGBoost Classifier. Its predictions are improved by a neighborhood filter that leverages contextual information to assign correct labels. The algorithm is primarily concerned with differentiating vessels from other vessel-like objects and does so with a 99% accuracy rate. It takes advantage of an original local description of Tamura features, which proved to be one of the most influential factors in decision-making. As a result, the segmentation of coronary arteries is cleaned from artifacts, enabling AI-supported diagnosis workflows to be automated. After re-training, the proposed method can be used to eliminate post-segmentation artifacts in other medical *** relevance— The algorithm proposed in this paper allows for the development of software that could automatically calculate the Syntax Score in real time. This would shorten diagnostics time and allow for immediate action in critical cases.

关键词：

Multiple-criteria Heuristic Rating Estimation

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Kędzior, Anna Kulakowski, Konrad AGH University of Science and Technology Faculty of Applied Mathematics Krak Poland AGH University of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Krak Poland

One of the most widespread multi-criteria decision-making methods is the Analytic Hierarchy Process (AHP). AHP successfully combines the pairwise comparisons method and the hierarchical approach. It allows the decision-maker to set priorities for all ranked alternatives. But what if, for some of them, their ranking value is known (e.g., it can be determined differently)? The Heuristic Rating Estimation (HRE) method proposed in 2014 tried to bring the answer to this question. However, the considerations were limited to a model that did not consider many criteria. In this work, we go a step further and analyze how HRE can be used as part of the AHP hierarchical framework. The theoretical considerations are accompanied by illustrative examples showing HRE as a multiple-criteria decision-making method. Copyright © 2022, The Authors. All rights reserved.

关键词： Analytic hierarchy process

Heuristic Rating Estimation Method for the incomplete pairwise comparisons matrices

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Kulakowski, Konrad Kędzior, Anna AGH University of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Krak Poland AGH University of Science and Technology Faculty of Applied Mathematics Krak Poland

The Heuristic Rating Estimation Method enables decision-makers to decide based on existing ranking data and expert comparisons. In this approach, the ranking values of selected alternatives are known in advance, while these values have to be calculated for the remaining ones. Their calculation can be performed using either an additive or a multiplicative method. Both methods assumed that the pairwise comparison sets involved in the computation were complete. In this paper, we show how these algorithms can be extended so that the experts do not need to compare all alternatives pairwise. Thanks to the shortening of the work of experts, the presented, improved methods will reduce the costs of the decision-making procedure and facilitate and shorten the stage of collecting decision-making data. Copyright © 2022, The Authors. All rights reserved.

关键词： Decision making

A Bio-Medical Snake Optimizer System Driven by Logarithmic Surviving Global Search for Optimizing Feature Selection and its application for Disorder Recognition

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Khurma, Ruba Abu Alhenawi, Esraa Braik, Malik Hashim, Fatma A. Chhabra, Amit Castillo, Pedro A. MEU Research Unit Faculty of Information Technology Middle East University Amman11831 Jordan Computer Science Department Al- Ahliyya Amman University Amman Jordan Software Engineering Department Al- Ahliyya Amman University Amman Jordan Computer Science Department Prince Abdullah bin Ghazi Faculty of Information and Communication Technology Al-Balqa Applied University Salt Jordan Faculty of Engineering Helwan University Egypt Department of Computer Engineering and Technology Guru Nanak Dev University Amritsar143005 India Department of Computer Engineering Automatics and Robotics University of Granada Granada Spain

It is of paramount importance to enhance medical practices, given how important it is to protect human life. Medical therapy can be accelerated by automating patient prediction using machine learning techniques. To double the efficiency of classifiers, several preprocessing strategies must be adopted for their crucial duty in this field. Feature selection (FS) is one tool that has been used frequently to modify data and enhance classification outcomes by lowering the dimensionality of datasets. Excluded features are those that have a poor correlation coefficient with the label class, that is, they have no meaningful correlation with classification and do not indicate where the instance belongs. Along with the recurring features, which show a strong association with the remainder of the features. Contrarily, the model being produced during training is harmed, and the classifier is misled by their presence. This causes overfitting and increases algorithm complexity and processing time. The pattern is made clearer by FS, which also creates a broader classification model with a lower chance of overfitting in an acceptable amount of time and algorithmic complexity. To optimize the FS process, building wrappers must employ metaheuristic algorithms (MAs) as search algorithms. The best solution, which reflects the best subset of features within a particular medical dataset that aids in patient diagnosis, is sought in this study using the Snake Optimizer (SO). The swarm-based approaches that SO is founded on have left it with several general flaws, like local minimum trapping, early convergence, uneven exploration and exploitation, and early convergence. By employing the cosine function to calculate the separation between the present solution and the ideal solution, the logarithm operator was paired with SO to better the exploitation process and get over these restrictions. In order to get the best overall answer, this forces the solutions to spiral downward. Additionally, S

关键词： Evolutionary algorithms