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An Integrated Bipolar Picture Fuzzy Decision Driven System to Scrutinize Food Waste Treatment Technology through Assorted Factor Analysis

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computer Modeling in engineering & Sciences 2024年第9期140卷 2665-2687页

作者： Navaneethakrishnan Suganthi Keerthana Devi Samayan Narayanamoorthy Thirumalai Nallasivan Parthasarathy Chakkarapani Sumathi Thilagasree Dragan Pamucar Vladimir Simic Hasan Dinçer Serhat Yüksel Department of Mathematics Bharathiar UniversityCoimbatore641046India Department of Mathematics Sri Ramakrishna Mission Vidyalaya College of Arts and ScienceCoimbatore641020India Department of Operations Research and Statistics Faculty of Organizational SciencesUniversity of BelgradeBelgrade11000Serbia College of Engineering Department of Industrial Engineering and ManagementYuan Ze UniversityTaoyuan City320315TaiwanChina Faculty of Transport and Traffic Engineering University of BelgradeVojvode Stepe 305Belgrade11000Serbia Department of Computer Science and Engineering College of InformaticsKorea UniversitySeoul02841Republic of Korea School of Business Istanbul Medipol UniversityIstanbul34083Turkey Department of Economics and Management Khazar UniversityBakuAzerbaijan

Food Waste(FW)is a pressing environmental concern that affects every country *** one-third of the food that is produced ends up as waste,contributing to the carbon ***,the FW must be properly treated to reduce environmental *** study evaluates a few available Food Waste Treatment(FWT)technologies,such as anaerobic digestion,composting,landfill,and incineration,which are widely used.A Bipolar Picture Fuzzy Set(BPFS)is proposed to deal with the ambiguity and uncertainty that arise when converting a real-world problem to a mathematical model.A novel Criteria Importance Through Intercriteria Correlation-Stable Preference Ordering Towards Ideal Solution(CRITIC-SPOTIS)approach is developed to objectively analyze FWT selection based on thirteen criteria covering the industry’s technical,environmental,and entrepreneurial *** CRITIC method is used for the objective analysis of the importance of each criterion in FWT *** SPOTIS method is adopted to rank the alternative hassle-free,following the *** proposed model offers a rank reversal-free model,i.e.,the rank of the alternatives remains unaffected even after the addition or removal of an *** addition,comparative and sensitivity analyses are performed to ensure the reliability and robustness of the proposed model and to validate the proposed result.

关键词： Fuzzy food waste treatment selection bipolar picture fuzzy set and decision-making

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IAQ Monitoring System Optimizing Data-Driven Sensor Placement

IAQ Monitoring System Optimizing Data-Driven Sensor Placemen...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Gabriel Filios Sotiris Nikoletseas Ioannis Stivaros Department of Computer Engineering and Informatics University of Patras Greece Computer Technology Institute and Press "Diophantus" Greece

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

Indoor Air Quality (IAQ) significantly impacts people’s health and comfort in buildings. Although IAQ research spans two decades, a comprehensive assessment of factors affecting indoor air pollution remains elusive. Recent efforts focus on real-time monitoring using virtual sensing, a computational technique in engineering and data science. This paper presents a novel IAQ monitoring system emphasizing dynamic sensor placement for enhanced efficiency. The system employs random sensor positions and calculates measurement predictability, allowing identification and removal of less useful sensors, reducing data volume, and saving energy. Multiple reduction strategies are available, depending on the target number of edge devices or the desired maximum prediction error. Importantly, the system operates locally, without relying on internet connectivity. It consists of edge devices using air quality sensors, a gateway for data gathering and algorithm initiation, by training and evaluating multiple different machine learning techniques to determine point combination predictability. Deployed in two indoor settings, one with HVAC and the other naturally ventilated, the system’s effectiveness is assessed, shortcomings identified, and conclusions drawn for future work.

关键词： Training Sensor placement Machine learning algorithms Volume measurement Soft sensors Position measurement Prediction algorithms

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A Fairness-aware Coverage Algorithm for Drone Swarms 7

A Fairness-aware Coverage Algorithm for Drone Swarms

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7th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2022

作者： Bezas, Konstantinos Tsoumanis, Georgios Koritsoglou, Kyriakos Oikonomou, Konstantinos Tzallas, Alexandros T. Giannakeas, Nikolaos Tsipouras, Markos Angelis, Constantinos T. Department of Informatics and Telecommunications University of Ioannina Campus of Arta Greece Department of Informatics Ionian University Corfu Greece Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

Drones have evolved over the past years to a level that they have become more efficient and, at the same time, have miniature sizes and advanced environment sensing capabilities. As a result, drone swarms are being applied in various applications nowadays, as they can sense and process information from the surrounding environment to achieve higher level of functionality. For example, drone swarms are employed in disaster control and large area monitoring to prevent catastrophic events such as wild fires. For drone swarms to operate properly, a critical aspect is their remote command and control capabilities. Since swarms can possibly consist of an increased number of drones, it is important that they hold a certain degree of autonomy. In the current work, a Coverage Path Planning (CPP) algorithm is proposed for unknown area exploration. The proposed algorithm discovers the Wireless Sensor Network (WSN) nodes within the area and, then, it collects their data under a data collection scheme being used. For evaluating the proposed algorithm, a simulated environment is developed to assess its effectiveness in terms of fairness in data collection from the WSN nodes. Fairness, in the current case, measures the percentage of data collected from the WSN nodes and is calculated multiple times during the experiments. Two coverage paths are considered here, the parallel lines and the spiral lines. The results showcase that the coverage path affects the fairness index while the parallel lines seem to provide more consistent data collection than the spiral, the latter increasing the fairness index. © 2022 IEEE.

关键词： Drones

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The Effect of Preprocessing on Skin Lesion Segmentation 8

The Effect of Preprocessing on Skin Lesion Segmentation

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8th International Conference on Information Technology, InCIT 2024

作者： Nugroho, Arief Kelik Afiahayati Wibowo, Moh Edi Soebono, Hardyanto Universitas Gadjah Mada Faculty of Mathematics and Natural Science Department of Computer Science and Electronics Yogyakarta Indonesia Universitas Jenderal Soedirman Faculty of Engineering Department of Informatics Engineering Purwokerto Indonesia Public Health and Nursing Universitas Gadjah Mada Faculty of Medicine Department of Dermatology and Venereology Yogyakarta Indonesia

ISBN: (纸本)9798350366303

Image preprocessing is a crucial step in enhancing the quality of skin lesion images before segmentation, with the primary objective of removing noise and artifacts that could interfere with the segmentation process and reduce accuracy. This process involves various techniques designed to address artifacts such as hair, black frames, skin lines, and vignettes, which may arise due to variables in image acquisition, such as lighting conditions and skin characteristics. Several preprocessing techniques used include artifact removal using Gaussian filter, bottom hat filter, and median filter, as well as hair removal methods like DullRazor and short line detector. Image augmentation techniques, such as rotation and transformation, are also employed to ensure that key features in the image are well preserved and accurately reflected in the data, helping to prevent overfitting during the classification stage. Additionally, contrast enhancement through methods like Contrast-Limited Adaptive Histogram Equalization (CLAHE) and gamma correction is used to improve lesion visibility and enhance the accuracy of lesion boundary detection. Findings from various studies indicate that appropriate preprocessing can significantly improve image quality, leading to more accurate segmentation. Descriptive statistical testing can be employed to analyze the extent to which these preprocessing steps affect segmentation outcomes, focusing on accuracy improvements and the reduction of segmentation errors caused by artifacts and noise in the images. Thus, effective preprocessing not only enhances image quality but also provides a stronger foundation for more accurate segmentation and classification in skin lesion diagnosis. © 2024 IEEE.

关键词： Median filters

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Numerical P Systems: Variants and Applications 24

Numerical P Systems: Variants and Applications

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24th Conference Information Technologies - Applications and Theory, ITAT 2024

作者： Bobe, Radu Traian Gheorghe, Marian Ipate, Florentin Niculescu, Ionuţ Mihai Department of Computer Science Faculty of Mathematics and Computer Science University of Bucharest Str Academiei 14 Bucharest010014 Romania Faculty of Engineering and Informatics University of Bradford Bradford West YorkshireBD7 1DP United Kingdom

Numerical P systems are compuational models which are inspired by cellular processes and use numerical values inside the membrane structure. In this paper we will present the variants of numerical P systems that have been proposed in the literature. In particular, we will discuss the advantages introduced by these extensions in terms of Turing completeness and potential applications. Moreover, using a reference example, we will experiment a mapping between some important numerical P systems variants. © 2024 CEUR-WS. All rights reserved.

关键词： Membrane structures

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An Architecture For Cooperative Mobile Health Applications

arXiv

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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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Divide-and-train: A new approach to improve the predictive tasks of bike-sharing systems

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Mathematical Biosciences and engineering 2024年第7期21卷 6471-6492页

作者： Ali, Ahmed Salah, Ahmad Bekhit, Mahmoud Fathalla, Ahmed Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia Higher Future Institute for Specialized Technological Studies Cairo3044 Egypt College of Computing and Information Sciences University of Technology and Applied Sciences Ad-Dhahirah Ibri Oman Zagazig University Department of Computer Science Faculty of Computers and Informatics Sharkeya Zagazig Egypt Sydney Australia Kaplan Business School Sydney Australia Department of Mathematics Faculty of Science Suez Canal University Ismailia Egypt

Bike-sharing systems (BSSs) have become commonplace in most cities worldwide as an important part of many smart cities. These systems generate a continuous amount of large data volumes. The effectiveness of these BSS systems depends on making decisions at the proper time. Thus, there is a vital need to build predictive models on the BSS data for the sake of improving the process of decision-making. The overwhelming majority of BSS users register before utilizing the service. Thus, several BSSs have prior knowledge of the user’s data, such as age, gender, and other relevant details. Several machine learning and deep learning models, for instance, are used to predict urban flows, trip duration, and other factors. The standard practice for these models is to train on the entire dataset to build a predictive model, whereas the biking patterns of various users are intuitively distinct. For instance, the user’s age influences the duration of a trip. This endeavor was motivated by the existence of distinct user patterns. In this work, we proposed divide-and-train, a new method for training predictive models on station-based BSS datasets by dividing the original datasets on the values of a given dataset attribute. Then, the proposed method was validated on different machine learning and deep learning models. All employed models were trained on both the complete and split datasets. The enhancements made to the evaluation metric were then reported. Results demonstrated that the proposed method outperformed the conventional training approach. Specifically, the root mean squared error (RMSE) and mean absolute error (MAE) metrics have shown improvements in both trip duration and distance prediction, with an average accuracy of 85% across the divided sub-datasets for the best performing model, i.e., random forest. © 2024 the Author(s).

关键词： Forecasting

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Emotion Recognition Techniques 1

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1st international conference on Machine Intelligence and computer Science Applications, ICMICSA 2022

作者： Knouzi, Maryam Ennaji, Fatima Zohra Hafidi, Imad Laboratory of Process Engineering Computer Science and Mathematics Department of Mathematics and Informatics National School of Applied Sciences University Sultan Moulay Slimane Beni-Mellal Morocco

ISBN: (数字)9783031293139

ISBN: (纸本)9783031288456

This article evaluates techniques for obtaining facial images from convolutional neural networks to identify emotion expressions. The primary goal of the paper is to discuss the most often used approaches to analyzing and recognizing emotional expressions on the face. The works that were reviewed might be divided into two major trends: the traditional techniques and those that were especially developed using neural *** analysis revealed that using CNNs improved level of performance. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Emotion Recognition

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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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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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