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CI-MM-Dombi operator based on interval type-2 spherical fuzzy set and its applications on sustainable supply chain with risk criteria: using CI-TODIM-MARCOS method

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Soft Computing 2024年第17-18期28卷 10023-10056页

作者： Giri, Binoy Krishna Roy, Sankar Kumar Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University West Bengal Midnapore721102 India

Sustainable supplier selection and optimal quantity transportation (S3OQT) play an important role in supply chain management. This research represents a new four-stage solution approach for S3OQT where the multi-criteria decision making (MCDM) methods are integrated through an optimization model. In first stage, a new uncertainty interval type-2 spherical fuzzy set (IT2SFS) is introduced to help the decision-makers (DMs) for securing and reliable results in hesitancy situations. We develop a new operator on IT2SFS under Dombi t-norm and t-conorm by integrating Muirhead mean (MM) operator based on Choquet integral (CI). The preferences and priorities to the sustainable criteria based on interaction and interrelationship are represented by CI. Thereafter, the weights of the criteria and sub-criteria are determined by CI-indifference threshold-based attribute ratio analysis (ITARA) method by utilizing the proposed operator. In second stage, to evaluate the weights of the suppliers and to rank these, we construct a new MCDM method CI-TODIM (an acronym in Portuguese of interactive multi-criteria decision-making)-measurement alternatives and ranking according to compromise solution (MARCOS) method by utilizing the proposed operator and then finally design a new ranking function. In third stage, a new model on stochastic multi-objective mixed-integer non-linear solid transportation problem (SM2NSTP) is established to identify suitable supplier under sustainable risk criteria, and then, optimal quantity of products are transported from each supplier. Thereafter, we propose TOPSIS-neutrosophic-game theoretic approach (TNGTA) to obtain Pareto-optimal solution. We apply Ε-constraint method to obtain Pareto-optimal solution from SM2NSTP model. In the fourth stage, a comparative study is drawn among the obtained Pareto-optimal solutions that are extracted from TNGTA and Ε-constraint method. Finally, two MCDM models, CRITIC-TOPSIS and CRITIC-MARCOS, are used to help the DMs for s

关键词： Fuzzy sets

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Suspicious transaction alert and blocking system for cryptocurrency exchanges in metaverse’s social media universes: RG-guard

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Neural Computing and Applications 2024年第30期36卷 18825-18840页

作者： Gürfidan, Remzi Computer Programming Department Yalvaç Technical Sciences Vocational School Isparta University of Applied Science Isparta Turkey

In this study, we propose an effective system called RG-Guard that detects potential risks and threats in the use of cryptocurrencies in the metaverse ecosystem. In order for the RG-Guard engine to detect suspicious transactions, Ethereum network transaction information and phishing wallet addresses were collected, and a unique dataset was created after the data preprocessing process. During the data preprocessing process, we manually distinguished the features within the original dataset that contained potential risk indicators. The learning process of the RG-Guard engine in risk classification was achieved by developing a deep learning model based on LSTM + Softmax. In the training process of the model, RG-Guard was optimised for maximum accuracy, and optimum hyperparameters were obtained. The reliability and dataset performance of the preferred LSTM + Softmax model were verified by comparing it with algorithms used in risk classification and detection applications in the literature (Decision tree, XG boost, Random forest and light gradient boosting machine). Accordingly, among the trained models, LSTM + Softmax has the highest accuracy with an F1-score of 0.9950. When a cryptocurrency transaction occurs, RG-Guard extracts the feature vectors of the transaction and assigns a risk level between 1 and 5 to the parameter named βrisk. Since transactions with βrisk > = 3 are labelled as suspicious transactions, RG-Guard blocks this transaction. Thus, thanks to the use of the RG-Guard engine in metaverse applications, it is aimed to easily distinguish potential suspicious transactions from instant transactions. As a result, it is aimed to detect and prevent instant potential suspicious transactions with the RG-Guard engine in money transfers, which have the greatest risk in cryptocurrency transactions and are the target of fraud. The original dataset prepared in the proposed study and the hybrid LSTM + Softmax model developed specifically for the model are expected to c

关键词： Decision trees

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An Experimental Study in Determining Basic Robotic Coding Skills of Pre-School Students with Intellectual Disabilities

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2022年第23期16卷 84-98页

作者： Yildiz, Ezgi Pelin Çengel, Metin Department of Computer Programming Kafkas University Kars Turkey Department of Computer Programming Sakarya University of Applied Sciences Sakarya Turkey

Today, it can be said that coding has become a key competence for students and people working in many different fields in the business world. It is assumed that those who seek and develop new ways to learn-teach coding will be one step ahead. The educational use of coding started with the use of the Logo programming language in the *** concept has started to revive in recent years with visual programming languages such as "Alice, its code, *** and Scratch". These visual programming structures enable young learners to write applications without having to learn the complex code structures of traditional programming languages. In this study to develop an experimental study to determine the basic robotic coding skills of preschool students with intellectual disabilities. The sample of the study consists of a total of 20 students with studying in pre-school education institutions in a city in Türkiye. The ages of the students are between 5 years old. Semi-experimental design, one of the experimental research designs, was used in the research. In this context, 1 experimental and 1 control group was formed with the random assignment method. The materials used in both the experimental and control groups were determined as the preschool robotic coding set U-bot starter package.5 weeks were determined as the teaching process and a total of 12 activities that served the purpose were applied to the students. During the applications, the data of the students were collected with the help of the observation form, coding skill test and after the application, they were collected through focus group interviews. As a result, at the end of the 5-week period, it was observed that there were positive significant changes in the two dependent variables (academic achievement andlearning rate) that were used as a basis for measuring the learning skills of both the experimental group and the control group students. © 2022,International Journal of Interactive Mobile Technologies. All

关键词： Students

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Implementation of Safety-Related Intrusion Detection for an Industrial Robotic Arm

Implementation of Safety-Related Intrusion Detection for an ...

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2025 International Conference on Control, Automation, and Instrumentation, IC2AI 2025

作者： Haydar, Georgio Abou Telawi, Samer Borcsok, Josef Architecture and System Programming University of Kassel Department of Computer Kassel Germany

ISBN: (纸本)9798331529604

Ensuring the safety of human workers collaborating with industrial robots is paramount. This research work presents a novel approach by developing a safety-related intruder detection system for the operational zones of industrial robots, following the IEC 61508 standard and adopting the related redundant architecture. The hardware integrates light curtains and radar sensors in a dual-layer configuration, while the software utilizes a safety system-on-chip to implement real-time diagnostics and fault tolerance. Protecting employees and ensuring a smooth and safe work environment are significant concerns for all companies. As a result, numerous standards and regulations have been established to provide safe collaboration between humans and machines. However, despite these measures, accidents continue to occur, resulting in varying degrees of injuries. The proposed system is depicted through a comprehensive schematic, emphasizing the integration of safety measures within the robotic environment. The detailed prototype demonstrates practical application, show-casing the system's ability to detect intrusions, initiate emergency responses, and transition to fail-safe states during component failures. This research work advances safety protocols in human-robot collaboration within industrial settings, fostering a safe working environment through a well-defined safety framework. © 2025 IEEE.

关键词： Industrial robots

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Effects of Different Optimizations at Detection of Vehicles and Pedestrians with YOLOv8 8

Effects of Different Optimizations at Detection of Vehicles ...

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8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024

作者： Iren, Ecem İzmir Kavram Vocational School Computer Programming Program İzmir Turkey

ISBN: (纸本)9798331531492

Improvements in deep learning has facilitated traffic management by providing analyzing and prediction capabilities on the road. In this study, vehicle and pedestrian detection with YOLOv8 was carried out with different optimizations such as Adam, Stochastic Gradient Descent (SGD) and RMSprop, at the end of the experiments, the model with SGD which produced 87.1 % in mAP was seen as the best optimizer when compared with others at detecting objects. © 2024 IEEE.

关键词： Adam optimization deep learning pedestrian detection RMSprop Optimization SGD optimization vehicle detection YOLOv8

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Healthcare Data Analytics Based on Machine Learning

Healthcare Data Analytics Based on Machine Learning

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2024 IEEE International Conference on Communications, Computing, Cybersecurity and Informatics, CCCI 2024

作者： Gancheva, Veska Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies Sofia1000 Bulgaria

ISBN: (纸本)9798350349832

Technology advancements have transformed medical science and practice, leading to the vast gathering of a wide range of medical data. Medical researchers use artificial intelligence techniques extensively because they enable the identification and creation of models of complicated datasets and the interactions between them. This, in turn, enables the successful prediction of future outcomes associated with a specific sickness type. An artificial intelligence-based approach to healthcare data analytics is presented, which leverages data to build a desired model and solve a particular issue. The suggested approach for healthcare data analytics uses a random forest and feedforward artificial neural network with two hidden layers as its basis to get the best model. © 2024 IEEE.

关键词： Adversarial machine learning

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Multi-attribute decision making for power Dombi operators under Pythagorean fuzzy information with MABAC method

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Journal of Ambient Intelligence and Humanized Computing 2023年第8期14卷 10761-10778页

作者： Jana, Chiranjibe Garg, Harish Pal, Madhumangal Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore721102 India Punjab Patiala147004 India

Pythagorean fuzzy sets have a lot of applications in the field of engineering and scientific problems. Also, besides, the power averaging (PA) operator can reduce the influence of evaluating extreme data from some bias experts. Dombi operator has flexibility in working on parameter evaluation. Here, Dombi operations combined with PA operator are used to construct some Pythagorean fuzzy power Dombi operators, i.e. Pythagorean fuzzy power Dombi weighted averaging (PFPDWA), order weighted averaging and hybrid weighted averaging operators have been introduced. Further, Pythagorean fuzzy power Dombi weighted geometric (PFPDWG), order weighted geometric and hybrid weighted geometric operators have been considered. Meanwhile, some properties of these operators have been established in detail. To solve the Pythagorean fuzzy multiple attribute decision making problem by using PFPDWA and PFPDWG operators to design an algorithm for the proposed approach. At the same time, a novel approach is proposed to design multiple attribute border approximation area comparison approached with Pythagorean fuzzy numbers to justify the feasibility of the proposed approach. Finally, we compare the developed approach with some existing operators to show its efficiency. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Decision making

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Mathematical Model of Crane Scheduling for a Defined Slab Storage Locations Assignment in a Continuous Cast Billet Warehouse

Mathematical Model of Crane Scheduling for a Defined Slab St...

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2024 International Russian Automation Conference, RusAutoCon 2024

作者： Shchegolikhin, Ivan S. Andreev, Sergey M. Nosov Magnitogorsk State Technical University Department of Computer Engineering and Programming Magnitogorsk Russia

An increasing number of steel factories around the world are integrating two processes: continuous casting and hot rolling. The slab warehouse is the link between these two processes. Slabs of certain sizes are cast on the continuous casting machine streams and then transported to the slab warehouse. In the warehouse, overhead cranes move the slabs to storage locations, into stacks. The sequence of slabs arriving at the slab warehouse plays an important role: slabs that arrive earlier should, as a rule, be stacked earlier. If several cranes may be operating in a warehouse in an adjacent space, the scheduling of cranes becomes much more difficult: a safe distance must be maintained between the cranes. This paper proposes a mathematical model of crane scheduling for a defined solution to the storage location assignment problem in a slab warehouse. This mathematical model considers a large number of constraints specific to the mentioned process, such as: orthogonality of crane movement;order of slab processing;minimum distance between cranes;maximum and minimum height of stacks;and many others. The developed mathematical model takes into account the space-time characteristics of the warehouse and crane trajectories, which allows its application to create a digital twin of the slab warehouse, which will allow to check the acceptability of the crane schedule for some solution of the problem of storage location assignment. © 2024 IEEE.

关键词： Continuous casting

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Heterogeneous ensemble classifier in medical decision support systems 5

Heterogeneous ensemble classifier in medical decision suppor...

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Povoroznyuk, Anatol Y. Povoroznyuk, Oksana Filatova, Anna Department of Computer Engineering and Programming National Technical University "Kharkiv Polytechnic Institute Kharkiv Ukraine

ISBN: (纸本)9798350384499

The work is devoted to solving the current scientific and technical problem of constructing a diagnostic decision support system in medicine based on a heterogeneous ensemble classifier model that implements two approaches to formulating a diagnostic conclusion: a probabilistic one based on the analysis of the training sample, and expert information on the structure of symptom complexes. The choice of prototype matching method as a probabilistic component is justified. Formalization of expert information on the structure of symptom complexes was carried out by representing symptom complexes of diseases with numerical intervals of linguistic variables. Options for taking into account expert assessments about the structure of symptom complexes in an ensemble classifier are considered. Test verification of the developed classifier was done on real medical data and confirmed the effectiveness of its work. ©2024 IEEE.

关键词： Expert systems

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Scoring rule and its application in intuitionistic fuzzy parameterized soft set-based decision-making problem

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 14209-14224页

作者： Paik, Biplab Mondal, Shyamal Kumar Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University W.B. Midnapore721 102 India

There is an importance of multi-criteria group decision-making (MCGDM) problems based on soft set theory in decision analysis. This article focuses on MCGDM problems based on intuitionistic fuzzy parameterized soft sets (IFPSS) structure. Our goal in decision-making is to select an object by verifying all the parameters. Fuzzy ranking is one of the essential critical tools used in the MCGDM process. The ranking system plays a vital role in the comparison of Intuitionistic fuzzy numbers (IFN) in MCGDM, like fuzzy numbers. However, most of the ranking methods on IFN mentioned in the literature have some limitations. By addressing the limitations of existing score functions and proposing a new and improved method for ranking IFNs, this article can make a significant contribution to the field of MCDM and decision-making under uncertainty. We have also introduced a new similarity measure of two intuitionistic fuzzy soft sets (IFSS). Using the concept of scoring rule, we have defined the reduced FP-soft set of an IFPSS. Additionally, we have calculated the adequate standard of a decision-maker in MCGDM problems under the IFPSS environment. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Decision theory

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