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arXiv 2023年

作者： Drakopoulos, Georgios Mylonas, Phivos Sioutas, Spyros Department of Informatics Ionian University Greece Computer Engineering and Informatics Department University of Patras Greece

MSC Codes 05C12, 05C20, 05C80, 05C85Mobile health applications are steadily gaining momentum in the modern world given the omnipresence of various mobile or WiFi connections. Given that the bandwidth of these connections increases over time, especially in conjunction with advanced modulation and error-correction codes, whereas the latency drops, the cooperation between mobile applications becomes gradually easier. This translates to reduced computational burden and heat dissipation for each isolated device at the expense of increased privacy risks. This chapter presents a configurable and scalable edge computing architecture for cooperative digital health mobile applications. © 2023, CC BY.

关键词： Mobile computing

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Enhancing IT Risk Management in XYZ Vocational School: Leveraging COBIT 5 Framework with the APO12 Domain

Enhancing IT Risk Management in XYZ Vocational School: Lever...

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2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024

作者： Winanti Fernando, Erick Gate, Jullend Universitas Insan Pembangunan Department of Information Systems Indonesia Universitas Multimedia Nusantara Information System Faculty of Engineering and Informatics Tangerang Indonesia Bina Nusantara University Binus Online Learning Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350372229

This article explores the importance of IT risk management, especially at XYZ Vocational School. The agency is equipped to manage business risks, emphasizing the need to improve decision-making and risk mitigation by identifying potential hazards and evaluating internal and external threats, including hacking risks. The research investigates IT risk management at XYZ Vocational School using a qualitative and quantitative method with a focus on the APO12 COBIT 5 domain: Align, plan, and organize. It assesses subdomains such as data collection, risk analysis, profile maintenance, risk articulation, portfolio management, and response strategies. Conclusively, the research reveals institutional IT capabilities at level 1 (Performed Process) in the APO12 subdomain. Recommendations include developing COBIT-compliant SOPs for processes at this level, highlighting the need for further improvements in IT governance. This study provides valuable insights into IT risk management practices, offering recommendations for improving IT governance in educational settings. © 2024 IEEE.

关键词： APO12 Domain COBIT 5 Information technology Risk Management Vocational School

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A Comparison of Regression Techniques for Prediction of Air Quality in Smart Cities 1

A Comparison of Regression Techniques for Prediction of Air ...

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1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Garg, Kamal Deep Gupta, Manik Sharma, Bhisham Dhaou, Imed Ben Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Dar Al-Hekma University Hekma School of Engineering Computing and Informatics Department of Computer Science Jeddah Saudi Arabia

ISBN: (纸本)9781665472753

The expansion of the internet of things (IoT) and Big Data are two factors that have contributed to the rise in popularity of smart cities. The ability to anticipate the quality of the air in an area with precision and efficiency is one of the fundamental building blocks of a smart city. The amount of polluted air found in smart cities throughout the world has been gradually growing. Because of this, there has been a rise in the concentration of several air pollutants in the environment, including particulate matter (PM 10), sulphur dioxide (SO2), and PM 2.5, amongst others. Because of the possibility of uncontrollable repercussions, such as an increase in the severity of asthma and cardiovascular disease, this situation poses a risk to the country and to the people who live in it. Heavy industry and vehicle exhaust have been major contributors to the growth of air pollution in smart cities such as New Delhi, Bombay, Chandigarh, and Bengaluru in India. The purpose of this investigation is to compare and contrast the efficiency of a variety of machine learning methods in order to assess the precision of the air quality index (AQI) projection of PM 2.5 in Chandigarh, India. Models for predicting AQI are trained and tested using a variety of statistical techniques like Linear regression, Lasso regression, KNN regression, and Random Forest regression This Root Mean Square Error (RMSE) found for Linear regression, Lasso regression, KNN regression, and Random Forest regression are 31.01, 29,45, 37.09 and 28.3. From all four models, random forest regression was more accurate than the other three regression models in estimating PM 2.5 levels in India's smart city. © 2023 IEEE.

关键词： Diseases

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Solution of the Problem of Positioning Moving Objects on Analytical Trajectories With a Minimum Composition of Satellite Measurements

Solution of the Problem of Positioning Moving Objects on Ana...

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International Conference on Industrial engineering, Applications and Manufacturing (ICIEAM)

作者： Sergey V. Sokolov Daniil V. Marshakov Irina V. Reshetnikova Department of Informatics and Computer Engineering Moscow Technical University of Communications and Informatics Rostov-on-Don Russia Research Department Moscow Technical University of Communications and Informatics Rostov-on-Don Russia

ISBN: (数字)9798331512194

ISBN: (纸本)9798331512200

The paper deals with the problem of high-precision positioning for mobile objects moving along program trajectories. An equation describing the dynamics of changing the spatial coordinates of the object based only on satellite measurements and invariant to its physical and technical characteristics is obtained. In addition, an equation of the spatial coordinates observer, also invariant to the design features of the object, is constructed on the basis of primary pseudodistance measurements. The peculiarity of application of this approach in the considered case is its complementation with the idea of approximation of a priori (programmed) trajectory of a mobile object by a set of trajectory intervals described by the given analytical models in the object coordinate space. As such trajectory intervals, the paper considers orthodromic (shortest) and circular intervals, which are the most typical for programme trajectories of transport objects (highways, railways, airlines, etc.). Analytical dependences of spatial coordinates are obtained for circular intervals. Since approximation by the specified trajectory intervals can be easily implemented using electronic maps, in general, the integration of electronic map information and nonlinear filtering algorithms in the processing of primary satellite measurements makes it possible to drastically reduce computational costs when estimating the current coordinates of a mobile object while significantly improving positioning accuracy compared to traditional methods of processing satellite messages. The effectiveness of the proposed approach is illustrated by a numerical example.

关键词： Satellites Coordinate measuring machines Accuracy Filtering Current measurement Position measurement Stability analysis Mathematical models Trajectory Numerical stability

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A fast parallel classification model for the diagnosis of cancer

Recent Advances in Computer Science and Communications

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Recent Advances in computer Science and Communications 2021年第1期14卷 291-301页

作者： Jain, Divya Singh, Vijendra Department of Computer Science and Engineering School of Engineering and Technology The Northcap University Gurugram India Department of Informatics School of Computer Science University of Petroleum and Energy Studies Dehradun India

Background: In this era of voluminous data, there is a need to process data speedily in less time. Moreover, it is also essential to diminish the dimensionality of data as well as to apply parallel computations for classification. SVM is a prominent classification tool and is currently one of the most popular state-of-the-art models for solving various classification problems that makes use of parallel computations to speed up its processing. Objective: To develop a fast, promising classification system using optimized SVM classifier with hybridized dimensionality reduction for the diagnosis of cancer disease. Methods: The proposed approach comprises of two stages – the first stage presents a hybrid approach to reduce the dimensionality of cancer datasets, and the second stage presents an efficient classification method to optimize the SVM parameters and improve its accuracy. To lessen the execution time, the proposed approach uses GPUs to concurrently run different processes on machine workers. Results: The proposed method with the combination of dimensionality reduction & parallel classification using optimized SVM classifier is found to give excellent results based on ‘Classification Accuracy’, ‘Selected Features’ and ‘Execution Time’. Conclusion: The experimental findings with benchmark datasets indicate that the proposed diagnostic model yields significant improvement in terms of execution time when compared to the conventional approach. The proposed model can assist doctors and medical professionals in the quick selection of most significant risk factors for the diagnosis and prognosis of cancer diseases. © 2021 Bentham Science Publishers.

关键词： Classification (of information)

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ReviewRanker: A Semi-supervised Learning-Based Approach for Code Review Quality Estimation 6th

ReviewRanker: A Semi-supervised Learning-Based Approach for ...

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6th International Conference on Recent Innovations in Computing, ICRIC 2023

作者： Mahbub, Saifullah Easin Arafat, Md. Rahman, Chowdhury Rafeed Ferdows, Zannatul Hasan, Masum Department of Computer Science and Engineering United International University United City Madani Avenue Dhaka1212 Bangladesh Data Science and Engineering Department Faculty of Informatics Eötvös Loránd University Pázmány Péter Str. 1/A Budapest1117 Hungary Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka1000 Bangladesh School of Computing National University of Singapore Singapore Singapore Department of Computer Science University of Rochester RochesterNY United States

ISBN: (纸本)9789819734412

Code review is considered a key process in the software industry for minimizing bugs and improving code quality. Inspection of review process effectiveness and continuous improvement can boost development productivity. Such inspection is a time-consuming and human-bias-prone task. We propose a semi-supervised learning-based system ReviewRanker which is aimed at assigning each code review a confidence score which is expected to resonate with the quality of the review. Our proposed method is trained based on simple and well-defined labels provided by developers. The labeling task requires little to no effort from the developers and has an indirect relation to the end goal (assignment of review confidence score). ReviewRanker is expected to improve industry-wide code review quality inspection by reducing human bias and the effort required for such a task. The system has the potential of minimizing the back-and-forth cycle existing in the development and review process. Usable code and dataset for this research can be found at: https://***/saifarnab/code_review. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Self-supervised learning

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Fully integrated Windows framework for source localization with MNE Python and FreeSurfer

Fully integrated Windows framework for source localization w...

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作者： Oppermann, Hannes Wulf, Simon Komosar, Milana Haueisen, Jens Haueisen, Jens Department of Computer Science and Automation Institute of Biomedical Engineering and Informatics Technische Universität Ilmenau Ilmenau Germany Department of Neurology Biomagnetic Center University Hospital Jena Jena Germany

There is a variety of software packages, toolboxes, or libraries for the analysis and processing of neurophysiological data such as EEG and MEG. Many of these solutions provide algorithms for both, sensor-space analysis and sourcespace analysis. Especially with the solutions that run on Windows machines, it is noticeable that the step of the volume model generation is usually not included, since the state-ofthe- art software for this (FreeSurfer) is a Unix-based software and thus not available forWindows machines. Therefore, our goal was to develop a fully-integrated software solution for Windows machines, accessing all processing steps already implemented in an existing toolbox and using FreeSurfer in the same system. Due to its widespread use, we chose MNE Python as the basis for our fully integrated software solution. We used the Windows Subsystem for Linux to create a virtual Linux kernel for the FreeSurfer installation. To demonstrate the workflow, the libeep, and AutoReject libraries have been added. A 64-channel EEG recording during right-hand movement (ME) and imagination (MI) was used to test the implemented workflow. The developed framework consists of several modules within Python, mainly using existing scripts and functions. The library libeep was integrated to read the EEG data with the '.cnt', eeprope format. AutoReject was used to automatically interpolate detected bad channels or to reject complete epochs. FreeSurfer was successfully integrated and customized Python scripts enabled the communication between MNE Python on a Windows machine and FreeSurfer on a virtual Linux kernel. With the above-mentioned EEG dataset, we performed source reconstruction and were able to show ERD/S patterns for both, ME and MI. Our new, fullyintegrated software framework can be used on Windows machines to perform a complete process of source reconstruction. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Python

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Provably Efficient Multi-Cancer Image Segmentation Based on Multi-Class Fuzzy Entropy

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Informatica (Slovenia) 2023年第8期47卷 77-88页

作者： Jasim, Hend Muslim Ghrabat, Mudhafar Jalil Jassim Abdulrahman, Luqman Qader Nyangaresi, Vincent Omollo Ma, Junchao Abduljabbar, Zaid Ameen Abduljaleel, Iman Qays Department of Computer Science College of Education for Pure Sciences University of Basrah Basrah61004 Iraq Iraqi Commission for Computers and Informatics The Informatics Institute for Postgraduate Studies Baghdad Iraq Computer Science Department Al-Turath University College Baghdad10013 Iraq College of Health Science Hawler Medical University Erbil Iraq Jaramogi Oginga Odinga University of Science and Technology Bondo40601 Kenya College of Big Data and Internet Shenzhen Technology University Shenzhen518118 China Technical Computer Engineering Department AL-Kunooze University College Basrah6100 Iraq Huazhong University of Science and Technology Shenzhen Institute Shenzhen518000 China Department of Computer Science College of Computer Science and Information Technology University of Basrah Basrah61004 Iraq

One of the segmentation techniques with the greatest degree of success used in numerous recent applications is multi-level thresholding. The selection of appropriate threshold values presents difficulties for traditional methods, however, and, as a result, techniques have been developed to address these difficulties multidimensionally. Such approaches have been shown to be an efficient way of identifying the areas affected in multi-cancer cases in order to define the treatment area. Multi-cancer methods that facilitate a certain degree of competence are thus required. This study tested storing MRI brain scans in a multidimensional image database, which is a significant departure from past studies, as a way to improve the efficacy, efficiency, and sensitivity of cancer detection. The evaluation findings offered success rates for cancer diagnoses of 99.08%, 99.87%, 94%;97.08%, 98.3%, and 93.38% sensitivity;the success rates of in particular were 99.99%;98.23%, 99.53%, and 99.98%. © 2023 Slovene Society Informatika. All rights reserved.

关键词： Image segmentation

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DiverseNet: Decision Diversified Semi-supervised Semantic Segmentation Networks for Remote Sensing Imagery

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 14258-14271页

作者： Ma, Wanli Karakus, Oktay Rosin, Paul L. Cardiff University School of Computer Science and Informatics Cardiff United Kingdom University of Cambridge Department of Engineering Cambridge United Kingdom

Semi-supervised learning (SSL) aims to help reduce the cost of the manual labelling process by leveraging a substantial pool of unlabelled data alongside a limited set of labelled data during the training phase. Since pixel-level manual labelling in large-scale remote sensing imagery is expensive and time consuming, semi-supervised learning has become a widely used solution to deal with this. However, the majority of existing SSL frameworks, especially various teacher-student frameworks, are too bulky to run efficiently on a GPU with limited memory. There is still a lack of lightweight SSL frameworks and efficient perturbation methods to promote the diversity of training samples and enhance the precision of pseudo labels during training. In order to fill this gap, we proposed a simple, lightweight, and efficient SSL architecture named DiverseHead, which promotes the utilisation of multiple decision heads instead of multiple whole networks. Another limitation of most existing SSL frameworks is the insufficient diversity of pseudo labels, as they rely on the same network architecture and fail to explore different structures for generating pseudo labels. To solve this issue, we propose DiverseModel to explore and analyse different networks in parallel for SSL to increase the diversity of pseudo labels. The two proposed methods, namely DiverseHead and DiverseModel, both achieve competitive semantic segmentation performance in four widely used remote sensing imagery datasets compared to state-of-the-art semi-supervised learning methods. Meanwhile, the proposed lightweight DiverseHead architecture can be easily applied to various state-of-the-art SSL methods while further improving their performance. The code is available at Here. © 2008-2012 IEEE.

关键词： Semantic Segmentation

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Image Filtering Techniques for Beam Prediction in a Real-world 6G UAV Scenario 6

Image Filtering Techniques for Beam Prediction in a Real-wor...

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6th World Symposium on Communication engineering, WSCE 2023

作者： Rekkas, Vasileios P. Sotiroudis, Sotirios P. Sarigiannids, Panagiotis Psannis, Konstantinos E. Karagiannidis, George K. Goudos, Sotirios K. ELEDIA@AUTH School of Physics Aristotle University of Thessaloniki Thessaloniki54124 Greece University of Western Macedonia Department of Informatics and Telecommunications Engineering Kozani Greece University of Macedonia Department of Applied Informatics Thessaloniki54124 Greece School of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54124 Greece

ISBN: (纸本)9798350339505

Millimeter-wave (mm-wave) and terahertz (THz) communication systems can satisfy the high data rate requirements in 5G, 6G, and beyond networks, but still rely on the use of extensive antenna arrays to guarantee sufficient received signal strength. Many antennas incur high beam training overhead;thus, the narrow beams require adjustment to support highly mobile applications. Deep learning (DL) vision-aided solutions can potentially forecast the optimal beams, leveraging raw RGB images captured at the base station. Image filtering techniques have been widely used in computer vision (CV) to modify and enhance the quality of an image, based on specific rules. This work applies different filters to RGB images for accurate mm-wave/THz beam prediction and feature extraction based on pre-trained convolutional neural networks (CNNs). The assessment of the developed framework is conducted on an actual dataset captured by an unmanned aerial vehicle (UAV) operating in the millimeter-wave (mm-wave) frequency range. The dataset comprises RGB images taken at the base station. Ensemble filtering techniques are also studied, enhancing the beam prediction accuracy of two state-of-the-art (SOTA) DL models. © 2023 IEEE.

关键词： Millimeter waves

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