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26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022

作者： Paradowski, Bartosz Szyjewski, Zdzislaw Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Institute of Management University of Szczecin ul. Cukrowa 8 Szczecin71-004 Poland

The ever-growing interest in multi-criteria decision-making methods requires research that would compare them with each other as the decision-makers would need help choosing the appropriate method. It is important to highlight the differences between them, because using different methods may result in discrepancies in the obtained rankings. Additionally, it is worthwhile for the research to take into account the problems whose solution is extremely valuable. To this end, we present a comparison of five multi-criteria decision-making methods: TOPSIS, VIKOR, COMET, SPOTIS, and MARCOS in the supplier selection problem. The conducted research showed significant differences in the evaluation of the preferences of the alternatives and some discrepancies in the obtained rankings. © 2022 The Authors. Published by Elsevier B.V.

关键词： Decision making

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Rule-based expert system supporting Individual Education-and-Therapeutic Program composition in SYSABA 26

Rule-based expert system supporting Individual Education-and...

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26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022

作者： Kolodziejczyk, Joanna Grzegorczyk-Dluciak, Nela Kuliga, Ewa Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Polish Association of Behavioral Therapy Os. Wysokie 7 Krakow31-819 Poland

System for Applied Behavioral Analysis (SYSABA) is a freeware web-based software developed in Poland that aids therapists who work with developmentally disordered children. A pioneer in Poland application is adapted to Applied Behavior Analysis (ABA) methodology and is compliant with the Polish Regulation of the Ministry of Education. A part of SYSABA is a module that helps compose a compliant with Polish regulations and ABA methodology, the Individual Education-and-Therapeutic Program (pol. IPET). This development process is guided by an expert system, including specialists' knowledge of the subject. The IPET composition is demanding and time-consuming, and the decisions made by the therapist will influence the treatment results. Because there are many paths to the final curriculum, the decision-making module in SYSABA was designed to improve and standardize the process. The paper provides details of the IPETs expert module design in SYSABA. The expert knowledge of long-term supervisors was expressed in a set of regulations and constraints supplying a rule-based expert system. The unstructured expertise was translated into a logical SYSABA two-level framework. Thirty-six rules guiding skill and behavior curricula were created. The effectiveness of the expert system was confirmed by a survey after one year of SYSABA usage. © 2022 The Authors. Published by Elsevier B.V.

关键词： Expert systems

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Practical Study of Selected Multi-Criteria methods Comparison 26

Practical Study of Selected Multi-Criteria Methods Compariso...

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26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022

作者： Wieckowski, Jakub Szyjewski, Zdzislaw Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Institute of Management University of Szczecin ul. Cukrowa 8 Szczecin71-004 Poland

Multi-Criteria Decision Analysis (MCDA) methods enable a comprehensive analysis of decision options to identify the most preferred values. However, the abundance of these techniques, using different transformations in the calculations, can cause a divergence of results. However, the resulting rankings should be as consistent and reliable as possible. In this paper, we used the TOPSIS, COPRAS, SPOTIS, and COMET methods to examine the consistency of their results in the practical problem of laptop evaluation. The rankings were then compared with the reference ranking. The research showed that among the methods listed, the COPRAS method's results differed the most from the others. In turn, this technique ensured a ranking in line with the reference ranking. Based on the results, it can be established that the methods used are characterized by high consistency of results. © 2022 The Authors. Published by Elsevier B.V.

关键词： Preferred numbers

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Autonomous Emergency Triage Support System

Autonomous Emergency Triage Support System

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International Conference on Computational science and Computational Intelligence (CSCI)

作者： Ol'Tunde Ashaolu William Lyons Ioannis Stefanakos Radu Calinescu Ibrahim Habli Victoria Hodge Chiara Picardi Katherine Plant Beverley Townsend York and Scarborough Teaching Hospitals NHS Foundation Trust / Hull-York Medical School York UK Department of Computer Science University of York York UK Faculty of Engineering and Physical Sciences University of Southampton Southampton UK

ISBN: (数字)9798350361513

ISBN: (纸本)9798350372304

Medical staff shortages and growing healthcare demands due to an ageing population mean that many patients face delays in receiving critical care in the emergency departments (EDs) of hospitals worldwide. As such, the use of autonomous, robotics and AI technologies to help streamline the triage of ED patients is of utmost importance. In this paper, we present our ongoing work to develop an autonomous emergency triage support system intended to alleviate the current pressures faced by hospital emergency departments. By employing a combination of robotic and AI techniques, our solution aims to speed up the initial stages of ED triage. Its preliminary evaluation using synthetic patient datasets generated with ED medic input suggests that our solution has the potential to improve the ED triage process, supporting the timely and accurate delivery of patient care in emeraency settings.

关键词： Hospitals Scientific computing Sociology Aging Delays Artificial intelligence Statistics

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Splitting criteria for ordinal decision trees: an experimental study

arXiv

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arXiv 2024年

作者： Ayllón-Gavilán, Rafael Martínez-Estudillo, Francisco José Guijo-Rubio, David Hervás-Martínez, César Gutiérrez, Pedro Antonio Department of Computer Science and Numerical Analysis Universidad de Córdoba Campus de Rabanales Ctra. N-IVa Km. 396 Córdoba14071 Spain Department of Quantitative Methods Universidad Loyola Andalucía C. Escritor Castilla Aguayo 4 Córdoba14004 Spain

Ordinal Classification (OC) is a machine learning field that addresses classification tasks where the labels exhibit a natural order. Unlike nominal classification, which treats all classes as equally distinct, OC takes the ordinal relationship into account, producing more accurate and relevant results. This is particularly critical in applications where the magnitude of classification errors has implications. Despite this, OC problems are often tackled using nominal methods, leading to suboptimal solutions. Although decision trees are one of the most popular classification approaches, ordinal tree-based approaches have received less attention when compared to other classifiers. This work conducts an experimental study of tree-based methodologies specifically designed to capture ordinal relationships. A comprehensive survey of ordinal splitting criteria is provided, standardising the notations used in the literature for clarity. Three ordinal splitting criteria, Ordinal Gini (OGini), Weighted Information Gain (WIG), and Ranking Impurity (RI), are compared to the nominal counterparts of the first two (Gini and information gain), by incorporating them into a decision tree classifier. An extensive repository considering 45 publicly available OC datasets is presented, supporting © 2024, CC BY-NC-ND.

关键词： Adversarial machine learning

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Analysis Pre and Post COVID-19 Pandemic Rorschach Test Data of Using EM Algorithms and GMM Models

Analysis Pre and Post COVID-19 Pandemic Rorschach Test Data ...

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2022 Scholar's Yearly Symposium of Technology, Engineering and Mathematics, SYSTEM 2022

作者： Ponzi, Valerio Russo, Samuele Wajda, Agata Brociek, Rafal Napoli, Christian Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Roma00185 Italy Department of Psychology Sapienza University of Rome Via dei Marsi 78 Roma00185 Italy Institute of Energy and Fuel Processing Technology Zabrze41-803 Poland Department of Mathematics Applications and Methods for Artificial Intelligence Faculty of Applied Mathematics Silesian University of Technology Gliwice44-100 Poland Institute for Systems Analysis and Computer Science Italian National Research Council Via dei Taurini 19 Roma00185 Italy

The global spread of the COVID-19 virus has become one of the greatest challenges that humanity has faced in recent years. The unprecedented circumstances of forced isolation and uncertainty that it has imposed on us continue to impact our mental well-being, whether or not we have been directly affected by the virus. Over a period of nearly three years (2017-2020), data was collected from multiple administrations of the Rorschach test, one of the most renowned and extensively studied psychological tests. This study involved the clustering of data, collected through the RAP3 software, to analyze the distinctive trends in data recorded before and after the pandemic. This was achieved through the implementation of the well-established machine learning algorithm, Expectation-Maximization. The proposed solution effectively identifies the key variables that significantly influence the subject's score and provides a reliable solution. Additionally, the solution offers an intuitive visualization that can assist psychologists in accurately interpreting shifts in trends and response distributions within a large amount of data in the two periods. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

关键词： Principal component analysis

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Design and measurement of a heart rate monitoring system by using the BLE technology 21

Design and measurement of a heart rate monitoring system by ...

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2nd International Symposium on Artificial Intelligence for Medicine sciences, ISAIMS 2021

作者： Zhong, Si Bai, Yanli Lan, Rushi He, Guomin Yuan, Yu Huang, Guanfeng Luo, Xiaonan Teaching and Practice Department Guilin University of Electronic Science and Technology Guangxi Guilin China School of Electronic Engineering and Automation Guilin University of Electronic Science and Technology Guangxi Guilin China Hospital Guilin University of Electronic Science and Technology Guangxi Guilin China School of Computer and Information Security Guilin University of Electronic Science and Technology Guangxi Guilin China

ISBN: (纸本)9781450395588

Since the heart rate is one of the critical indicators of the human body, the heart-rate monitoring process plays an important role in the evaluation of the body function wellness. Along these lines, a portable wireless heart-rate monitoring system is presented in this work based on a Bluetooth Low Energy (BLE) system. Our approach comprises the features of fast transmission rate, high communication efficiency, low cost, and strong anti-interference, while the data analysis process is also carried out within the designed configuration. From our extracted results, it is concluded that the heart-rate monitoring system using the BLE approach has the ability to carry out the functions of real-time acquisition of heart rate, curve comparison analysis, wireless data transmission, and data storage on the mobile APP terminal. In addition, the hardware design of the system is realized by employing the STM32, OLED, and MAX30102 components. As far as the development of the upper computer is concerned, it is implemented by using the JAVA and XML software packages in the environment of Android Studio. Moreover, the development of the lower computer software is realized by STM32 programming with MDK5. In terms of the measurement process accuracy, the measurement error lies within the range of 0∼5.41%, whereas comparing this system with similar equipment and analyzing the sampled data, it is concluded that the performance of the measurement process can address the respective practical application requirements. The final goal of this study is to provide a robust system with sound technical parameter support for the application of the BLE technology in the field of heart- rate monitoring. © 2021 ACM.

关键词： Heart

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6D Pose Estimation Based on Edge-Enhanced Point Pair Features for Surgical Navigation 8

6D Pose Estimation Based on Edge-Enhanced Point Pair Feature...

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8th International Conference on Virtual Reality, ICVR 2022

作者： Liu, Chenyi Chen, Fei Deng, Lu Yi, Renjiao Zheng, Lintao Zhu, Chenyang School of Computer Science National University of Defense Technology Changsha China Second XiangYa Hospital Central South University Department of Spine Surgery Changsha China Clinical Nursing Teaching and Research Section Second Xiang Ya Hospital Changsha China College of Meteorology and Oceanography National University of Defense Technology Changsha China

ISBN: (数字)9781665479110

ISBN: (纸本)9781665479110

This paper proposes an efficient 6D pose estimation method for the automatic spinal surgical navigation system. Visual-based pose estimation is challenging in realistic surgical scenes due to the human spine's geometric complexity and symmetric ambiguity. Instead of considering the whole scene for pose estimation, we introduce a targeted down-sampling strategy that focuses more on edge area for efficient feature extraction of complex geometry. A pose hypothesis validation approach is then presented to resolve the symmetric ambiguity. Note that our method can also work on incomplete scenes since our sampling and validation do not require a whole model. We perform evaluations on two challenging datasets, which demonstrate the superiority of our method on pose estimation of geometrically complex, occluded, symmetrical objects. We also implemented a prototype of a surgical navigation system based on the proposed method, which may provide a viable option for improving the spinal clinical surgery system. © 2022 IEEE.

关键词： Geometry

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SSC- l0 : Sparse Subspace Clustering with the l0 Inequality Constraint 7th

SSC- l0 : Sparse Subspace Clustering with the l0 Inequality...

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7th Asian Conference on Pattern Recognition, ACPR 2023

作者： Wang, Yangbo Zhou, Jie Lin, Qingshui Lu, Jianglin Gao, Can National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518060 China Basic Teaching Department Liaoning Technical University Huludao125105 China College of Engineering Northeastern University BostonMA02115 United States

ISBN: (纸本)9783031476648

Self-expression learning methods often obtain a coefficient matrix to measure the similarity between pairs of samples. However, directly using all points to represent a fixed sample in a class under the self-expression framework may not be ideal, as points from other classes participate in the representing process. To alleviate this issue, this study attempts to achieve representation learning between points only coming from the same class. In practice, it is easier for data points from the same class to represent each other than that from different classes. So, when reconstructing a point, if the number of non-zero elements in the coefficient vector is limited, a model is more likely to select data points from the class where the reconstructed point lies to complete the reconstruction work. Based on this idea, we propose Sparse Subspace Clustering with the l0 inequality constraint (SSC- l0 ). In SSC- l0, the l0 inequality constraint determines the maximum number of non-zero elements in the coefficient vector, which helps SSC- l0 to conduct representation learning among the points in the same class. After introducing the simplex constraint to ensure the translation invariance of the model, an optimization method concerning l0 inequality constraint is formed to solve the proposed SSC- l0, and its convergence is theoretically analyzed. Extensive experiments on well-known datasets demonstrate the superiority of SSC- l0 compared to several state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Learning systems

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Enhanced Labeling Technique for Reddit Text and Fine-Tuned Longformer Models for Classifying Depression Severity in English and Luganda

arXiv

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arXiv 2024年

作者： Kimera, Richard Rim, Daniela N. Kirabira, Joseph Udomah, Ubong Godwin Choi, Heeyoul Department of Advanced Convergence Handong Global University Pohang Korea Republic of School of Computer Science and Electrical Engineering Handong Global University Pohang Korea Republic of Department of Psychiatry Busitema University Faculty of Health Sciences Mbale Uganda Department of Psychiatry University of Uyo Teaching Hospital Uyo Akwa Ibom Nigeria

Depression is a global burden and one of the most challenging mental health conditions to control. Using the BDI questionnaire, experts can detect its severity early, administer appropriate medication to patients, and impede its progression. Owing to the fear of potential stigmatization, many patients turn to social media platforms such as Reddit for advice and assistance at various stages of their journey. This research extracts text from Reddit to facilitate the diagnostic process, employs a proposed labelling approach to categorize the text, and subsequently fine-tunes the Longformer model. The model's performance is compared against the baseline models, including Naive Bayes, Random Forest, Support Vector Machines, and Gradient Boosting. Our findings reveal that the Longformer model outperforms the baseline models in both English (48%) and Luganda (45%) languages on a custom-made dataset. © 2024, CC BY.

关键词： Support vector machines

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