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Financial Performance Evaluation of Leading Retail Companies in BIST Utilizing Decomposed Fuzzy TOPSIS 1

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Barutbas, Kaan Bulut, Bayram Otay, Irem Istanbul Bilgi Univ Dept Ind Engn TR-34060 Istanbul Turkiye

ISBN: (数字)9783031671951

ISBN: (纸本)9783031671944;9783031671951

Evaluation of the financial performance of companies has a wide range of applications and indicators. The evaluation process has become much more complicated and crucial especially during and after the pandemics. Fuzzy sets were first introduced to be able to cope with uncertainty and vagueness in real-world applications. Since its introduction, various extensions of fuzzy sets have developed. In this paper, decomposed fuzzy sets (DFS) which were recently proposed fuzzy set extensions have been utilized. In this study, the Decomposed Fuzzy Technique for Order Preference by Similarities to Ideal Solution (DF TOPSIS) has been applied to assess leading retail companies in Borsa Istanbul (BIST). According to this approach, the criteria set has been determined by literature review and experts' opinions and the leading companies in ISE have been evaluated based on the determined criteria set. Considering the vagueness and imprecise information in the decision-making environment, we believe this study will create a strong roadmap for those such as stakeholders and investors who are interested in analyzing the financial performance of the companies.

关键词： Financial Performance Financial Indicators Fuzzy MCDM Decomposed Fuzzy TOPSIS Decomposed Fuzzy Sets

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Mobile Victim Signs Monitoring Through Non-invasive Robotic System 27th

Mobile Victim Signs Monitoring Through Non-invasive Robotic ...

引用

27th International Conference on Climbing and Walking Robots and Mobile Machine Support Technologies (CLAWAR)

作者： Orbea, David Ullon, Christyan Cruz del Cerro, Jaime Barrientos, Antonio Univ Politecn Madrid Ctr Automat & Robat Consejo Super Invest Cient Madrid 28006 Spain

ISBN: (纸本)9783031707216;9783031707223

Robotic assistance for search and rescue (SAR) tasks in postdisaster environments focuses on offering faster response times for detecting potential victims and acquiring relevant information for prompt medical evaluation. An important potential feature of these robotic systems is the ability to rapidly and efficiently access victims' vital signs, such as heart rate, respiratory rate, or body temperature. Current methods are still based on manual inhalation - exhalation counts in a minute to obtain the breathing rate. From the approach of mobile robotics, this work proposes a robotic system for analyzing the respiratory rate condition of victims in SAR missions. The system is composed of a legged-manipulator robot equipped with a RGB sensor at the end effector, which, through convolutional neural networks (CNN), identifies a victim and defines a close relative position, then deploys the manipulator to a pose near the victim's thoracic region, performs motion data acquisition through optical flow techinque, and process the data to estimate respiratory rate. The system has been tested in indoor and outdoor environments. System evidences robustness on difficult lighting conditions and different patterns on victims' clothes.

关键词： Victim detection Respiratory rate Search and Rescue Vital signs Legged-manipulator robot

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Lung Disease Self-screening Using Deep Learning and Mobile Apps for Telehealth Monitoring 9th

Lung Disease Self-screening Using Deep Learning and Mobile A...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Alhamdi, Muhammad Jurej Al Yafi Nurbadriani, Cut Nanda Mufti, Alfatirta Yunida, Yunida Roslidar, Roslidar Univ Syiah Kuala Dept Elect & Comp Engn Banda Aceh 23111 Indonesia

ISBN: (纸本)9789819735556;9789819735563

Based on data from the World Health Organization (WHO), lung disease is the third largest killer in the world. Therefore, this research aims to design a lung disease screening (LUDESC) system based on deep learning to monitor lung disorders early on using mobile applications for telehealth care. The proposed system comprises a digital stethoscope to hear lung sounds that can be directly connected to a smartphone with an audio jack connector. At the same time, the DL model embedded in the mobile apps allows users to recognize the lung condition of healthy, chronic obstructive pulmonary disease (COPD), bronchiolitis, bronchiectasis, or upper respiratory tract infection (URTI). The proposed application also provides appropriate health recommendations if the lungs experience abnormalities. The prediction model was built using ResNet50 1D trained on datasets downloaded from the International Conference on Biomedical and Health Informatics (ICBHI) 2017. This dataset consists of 5.5 h of total voice recordings from 120 patients and 6898 respiratory circulations. The simulation result shows that the classifier model based on the ResNet50 1D achieved an accuracy rate of 98%, precision of 91.3%, recall of 93.83%, and F1-score of 91%. The LUDESC testing results show very satisfactory values, indicating its ability to perform properly.

关键词： Lung disease Self-screening Deep learning Telehealth care

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A Conceptual Framework for Building Robust Blockchain Technology-Enabled Business Processes in Commodity Markets: A systems Approach 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Lobo, Vivian Brian Rao, Madhuri TSEC Mumbai India

ISBN: (数字)9789819713202

ISBN: (纸本)9789819713196;9789819713202

Blockchain technology is an emerging area in the field of commodity markets and is achieving extensive recognition off lately. Blockchain is a decentralized platform that enables multiple independent parties, even those who lack trust among themselves, to work together, share information, and engage in coordinated activities through a transparent and reliable system. Commodity trading is a multifaceted system that involves multiple parties or actors. In a centralized commodity trading market, factors such as the degree of trust, cooperation, and transaction efficiency of multiple parties or actors are usually found to be low because of various reasons. Moreover, the involvement of third parties in commodity trading markets results in several challenges such as heterogeneity and intricate processes, information leakage risk, and superior costs. Blockchain technology being decentralized, transparent, traceable, and tamperproof helps in improving such factors and challenges. The use of systems approach strengthens them further. Taking into consideration these aspects, this study aims to present a conceptual framework for building robust blockchain technology-enabled business processes in commodity markets using systems approach.

关键词： Blockchain Business processes Commodity trading markets Decentralization Framework Smart contracts systems approach

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Robust Adaptive Finite-Time Motion Control of Underactuated Marine Vehicles 6th

Robust Adaptive Finite-Time Motion Control of Underactuated ...

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6th Iberian Robotics Conference (Robot)

作者： Reza Nazmara, G. Pedro Aguiar, A. Univ Porto ARISE Res Ctr Syst & Technol SYSTEC Fac Engn P-4200465 Porto Portugal Univ Porto Dept Elect & Comp Engn Fac Engn P-4200465 Porto Portugal

ISBN: (纸本)9783031591662;9783031591679

This paper focuses on the development of an adaptive back-stepping control for underactuated marine vehicles. In order to estimate system uncertainty, a fuzzy system with a simple structure is utilized. A novel dynamical formulation has been developed for deriving the control signal. The Lyapunov function has been employed to formally prove the Semi-globally Practically Finite-time Stability of the overall closed loop system. Simulations are conducted on an underactuated marine vehicle to assess the effectiveness of the proposed control approach. These simulations consider various challenging scenarios, including external disturbances, unmodeled dynamics, time-varying water currents, and lateral velocities. Furthermore, a comparison analysis is performed.

关键词： Backstepping Control Fuzzy Estimator Marine Vehicles Finite-time Stability

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Using Artificial Intelligence Image Generators in Product Design Within Industry 4.0 10th

Using Artificial Intelligence Image Generators in Product De...

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Lemes, Samir Kelestura, Muharem Tabak, Edin Buzadija, Nevzudin Univ Zenica Polytech Fac Zenica 72000 Bosnia & Herceg

ISBN: (纸本)9783031662676;9783031662683

We are witnessing a sudden increase in the general public's interest in computer graphics, whose creation is due to AI image generators. These tools are responsible for creating realistic graphics from the entered text description. They are based on deep learning algorithms trained on an extensive graphical data set. Recently, the artificial intelligence system behind OpenAI, DALL-E 2, which can generate digital images based on textual descriptions, has become widely available. In addition, more and more similar tools are appearing on the market, such as Craiyon, Imagen, Midjourney, Stable Diffusion, etc. AI-generated designis an emerging technology whose advantages and disadvantages in engineering applications have yet to be verified. We analysed the advantages and disadvantages of applying this technology in product design within Industry 4.0.

关键词： Artificial Intelligence AI image generator Computer Graphics CAD

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Hydraulic Quadruped Robot JINPOONG II: Toward Qualified Platform for Mobile Manipulation in Field Environment 1

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18th International Conference on Intelligent Autonomous systems (IAS)

作者： Seo, Jaehong Park, Sangshin Kim, Jin Tak Kim, Jinhyeon Cho, Jungsan Korea Inst Ind Technol AI Robot R&D Dept Ansan South Korea

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

We introduce a hydraulic quadruped robot, JINPOONG II, designed to qualify as a base platform for mobile manipulation. The mobile manipulation process in the field environment can be classified into three stages: "Approach," "Stretch-out," and "Manipulation." To qualify as suitable the mobile platform must have "mobility," "dexterity" to perform each stage, and "stability" to ensure stable operation of every process of stages. The quadruped robot is the most suitable candidate for mobile manipulator application because it can satisfy these requirements. We adopted a SLIP-based leg mechanism and a suitable control strategy to configure a quadruped robot that meets the qualifications. We then tested JINPOONG II's performance of body motion and interaction with external forces to verify whether the subject robot has the required qualifications in line with the design intent. The results established that JINPOONG II could perform 6 DoF motions of the body and various other compliance motions and walking on rough terrain. This indicates that JINPOONG II is equipped with qualifications as a base platform for mobile manipulators.

关键词： Robotics Autonomous vehicles

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MAGNAT: Maritime Management Ensemble Learning System 12th

MAGNAT: Maritime Management Ensemble Learning System

引用

12th World Conference on Information systems and Technologies (WorldCIST)

作者： Mesgaribarzi, Niusha Univ South Eastern Norway USN Fac Technol Nat & Maritime Sci Horten Norway

ISBN: (纸本)9783031602177;9783031602184

The classification of ships using remotely sensed data is increasingly vital for maritime security, environmental monitoring, and commercial applications. Advances in satellite imagery and remote sensing technologies have heightened the need for effective ship classification algorithms. A key challenge lies in the variability of ship appearances due to size, shape, orientation, and environmental factors. Ensemble learning, which combines multiple classifiers for improved accuracy, has shown promise in this area. However, this method faces issues like increased memory and time complexity, and the influence of lower-quality models, highlighting the need for model pruning. This study presents a new approach to maritime management through the introduction of an ensemble learning system. The MAGNAT (Maritime mAnaGement eNsemble leArning sysTem) proposal and novel contribution in this paper represent an intelligent ensemble solution that significantly enhances ship classification in the maritime domain through the adoption of ensemble learning techniques. Incorporating various Convolutional Neural Network (CNN) models into the training process, a novel aggregation strategy is devised to eliminate redundant models, retaining only those that actively enhance the learning process. Extensive experiments utilizing a renowned ship dataset were conducted to validate the effectiveness of the framework, ultimately demonstrating its superiority over conventional ensemble solutions.

关键词： Ensemble Learning Maritime Applications Convolution Neural Network

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Calcification Recognition: A Preliminary Result Based on a Computational Conceptual Model 1

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16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Martinez-Perez, Francisco E. Nunez-Varela, Alberto Nava-Munoz, Sandra Nunez-Varela, Jose Ignacio Ramirez-Gamez, Cesar A. Castillo-Barrera, Francisco Edgar Univ Autonoma San Luis Potosi Ave De Manuel Nava 8 Zona Univ San Luis Potosi 078290 Mexico

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

Breast cancer, as a disease with high incidence among women, has motived computer science researchers to create support tools with the aim of helping radiologists its early detection, this is an important factor in the positive outcome of its treatment, which must be based according to the person, the type of cancer and its spread. Current research has based their work on computational methodologies without considering the medical methodologies followed by radiologists, mainly showing results as a binary classification of benign or malign. We present our preliminary results focusing on an activities diagram. This diagram shows a computational model based on a medical methodology, focusing on calcification recognition with the purpose of obtaining a BI-RADS classification. Our aim is to look for other ways to tackle this problem, so that computational systems could serve as an aid to radiologists, capable of showing results similar to those used by them.

关键词： Breast cancer calcifications computational conceptual model

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Information Application in systems: Research, Models, and Problems 5th

Information Application in Systems: Research, Models, and Pr...

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5th International Conference on Communication and Intelligent systems (ICCIS)

作者： Geyda, Alexander S. Russian Acad Sci St Petersburg Fed Res Ctr St Petersburg 198188 Russia

ISBN: (纸本)9789819720521;9789819720538

The article devoted to the "information paradox," which originated in economic theory and formulated back in 1980s by Nobel Prize laureate Robert Solow. Author tries to explain this paradox from a broader perspective of modern systems sciences, cybernetics, and action theory. The aim is to develop a mathematical model of information application, leading to accurate predictions of its impact, based on formal modeling. I propose a graph-theoretic means to represent possible sequences of complex states and transitions which appear due to information application. This model is further used for creation of algebraic and programming code models, enabling the calculation of quantitative success measures for information application during system's functioning and the assessment of entropy change caused by information utilization. The article outlines various research directions related to the creation of mathematical models for information application. New approach presented to resolve the Solow paradox by mathematical modeling of information application results.

关键词： Information quality Information application Efficiency Effectiveness

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