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Found 6278 publications

A new state reduction approach for fuzzy cognitive map with case studies for waste management systems

Miklós F. Hatwágner Peter Foldesi Adrienn Buruzs László T. Kóczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2015-01-01

Volume: 331

Issue: Unknown

Page Range: 119-127

Description:

The authors have investigated the sustainability of Integrated Waste Management Systems (IWMS). These systems were modeled by Fuzzy Cognitive Maps (FCM), which are known as adequate fuzzy-neural network type models for multi-component systems with a stable state. The FCM model was designed of thirty-three factors to describe the real world processes of IWMS in as much detailed and as much accurately as possible. Although, this detailed model meets the requirements of accuracy, the presentation and explanation of such a complex model is difficult due to its size.While there is a general consensus in the literature about a very much simplified model of IWMSs, detailed investigation lead to the assumption that a much more complex model with considerably more factors (components) would more adequately simulate the rather complex real life behavior of the IWMS.As the starting point we used the thirty-three component model based on the consensus of a workshop of experts coming from all areas of the IWMS (operation, regulation, management, etc.) and the set goal was to find the most accurate real model that could be obtained by analyzing and properly reducing this – very likely too much detailed, or atomized – model.In this paper, a new state reduction approach with three different metrics is presented. The practical aspects of the results gained by these methods are evaluated.

Open Access: Yes

DOI: 10.1007/978-3-319-13153-5_12

Global research trends on cyberbullying: A bibliometric study

Arti Singh Abderahman Rejeb Smriti Pathak Hunnar Nangru

Publication Name: Computers in Human Behavior Reports

Publication Date: 2024-12-01

Volume: 16

Issue: Unknown

Page Range: Unknown

Description:

The rapid growth of the media industry, particularly social media, has enhanced interaction and information sharing but has also led to harmful uses of cyberspace, such as cyberbullying. This phenomenon, primarily affecting adolescents, involves repeated harm through electronic devices in forms like abusive or aggressive text messages, inappropriate videos, and identity theft. The present study utilizes the Scopus database to analyze 5201 publications on cyberbullying from 1999 to 2023. Using various bibliometric network methods for analysis such as networks, citation, co-citation, collaboration, and keyword co-occurrence networks, along with intellectual structure maps, we identified key contributors and publications from this field. The study identifies significant growth in scientific output over the years, with prominent contributors like Michelle F. Wright, Heidi Vandebosch, and Rosario Ortega-Ruiz, and key journals including Computers in Human behavior, International Journal of Environmental Research and Public Health, and Journal of Interpersonal Violence. The United States leads research production, with substantial collaboration among American institutions, followed by Canada and the United Kingdom. This study recognizes social media, gender, and online abuse as key topics well-explored in studies on cyberbullying. However, further investigation is required in fields such as cyber dating violence and harassment, along with the associated challenges faced by sexual minorities. Our results show a growing research interest among academics in understanding the various aspects of cyberbullying in recent years.

Open Access: Yes

DOI: 10.1016/j.chbr.2024.100499

Two-Stage Learning Based Fuzzy Cognitive Maps Reduction Approach

Miklós F. Hatwágner M. Furkan Dodurka Elpiniki I. Papageorgiou Leon Urbas László T. Kóczy Engin Yesil

Publication Name: IEEE Transactions on Fuzzy Systems

Publication Date: 2018-10-01

Volume: 26

Issue: 5

Page Range: 2938-2952

Description:

In this study, a new two-stage learning based reduction approach for fuzzy cognitive maps (FCM) is introduced in order to reduce the number of concepts. FCM is a graphical modeling technique that follows a reasoning approach similar to the human reasoning and the decision-making process. The FCM model incorporates the available knowledge and expertise in the form of concepts and in the direction and strength of the interactions among concepts. One of the modeling problems of FCMs is that oversized FCM models suffer from interpretability problems. An oversized FCM may contain concepts that are semantically similar and affect the other concepts in a similar way. This new study introduces a two-stage model reduction approach, and both static and dynamic analyses are considered without losing essential information. In the first stage, the number of concepts is reduced by merging similar concepts into clusters, whereas in the second stage the transformation function parameters of concepts are optimized. In order to show the benefit of using the proposed reduction approach, two sets of studies are conducted. First, a huge set of synthetic FCMs are generated, and the results of these statistical analyses are presented via various tables and figures. Subsequently, suggestions to the decision makers are given. Second, experimental studies are also presented to show the decision parameters and procedure for the proposed approach. The results show that after using the concept reduction approach presented in this study, the interpretability of FCM increases with an acceptable amount of information loss in the output concepts.

Open Access: Yes

DOI: 10.1109/TFUZZ.2018.2793904

Analysis of RFId application through an automotive supplier's production processes

Petra Döbrössy Dorottya Mánik Lajos Tóth

Publication Name: Isciii 07 3rd International Symposium on Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2007-09-25

Volume: Unknown

Issue: Unknown

Page Range: 177-181

Description:

The Department of Logistics and Forwarding at Széchenyi István University in Gyor, Hungary started a project in an automotive industry supplier company. The purpose of the project is to grow the efficiency of the production process. In order to achieve the target we should reorganized the IT system. During the research we had to take the special production circumstances and the already exist ad hock hformation system into consideration. The article adumbrates the course of the project shortly, the faults of the system, the own-developed new information system and represents how the human failures could be eliminated though RFId application. © 2007 IEEE.

Open Access: Yes

DOI: 10.1109/ISCIII.2007.367385

The structure of the univoque set in the big case

Gabor Kallos

Publication Name: Publicationes Mathematicae Debrecen

Publication Date: 2001-01-01

Volume: 59

Issue: 3-4

Page Range: 471-489

Description:

Let β > 1, Θ = 1/β, D = {0, 1, . . . , [β]}. In this paper we continue the investigation of the numbers which have only one expansion in the form ∑n=1∞ εnΘn with ε ∈ DN. We present a method for the determination of the Hausdorff dimension of the set of these numbers in the so-called big case, illustrated with interesting examples.

Open Access: Yes

DOI: 10.5486/pmd.2001.2581

A taxonomy of CogInfoCom trigger types in practical use cases

None Csapó Peter Varlaki Péter Baranyi

Publication Name: 3rd IEEE International Conference on Cognitive Infocommunications Coginfocom 2012 Proceedings

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 21-25

Description:

An important challenge in CogInfoCom is how to design multi-sensory signals which are capable of communicating high-level information to users. Although there have been investigations on how to design groups of signals for this purpose (referred to as CogInfoCom channels), and how to map high-level concepts onto patterns of sensory signals across different modalities, one general question has still not been addressed: how should a system decide when to provide information to users in interactive CogInfoCom systems? This paper represents an attempt to bridge this gap, and to provide a taxonomy of CogInfoCom trigger types in order to help answer this question. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/CogInfoCom.2012.6421990

Assessing the effectiveness of RS, GIS, and AI data integration in analysing agriculture performance to enable sustainable land management

Nail Beisekenov Marzhan Sadenova Petar Sabev Varbanov

Publication Name: Discover Sustainability

Publication Date: 2024-12-01

Volume: 5

Issue: 1

Page Range: Unknown

Description:

The integration of Earth Remote Sensing (ERS) data with advancements in artificial intelligence has revolutionised sustainable land management. Current research in this field focuses on analysing remotely sensed data. This paper presents the results of effectively using spectral reflectance values of soil samples from several climatic zones in Kazakhstan to classify the content of macronutrients in soil, including nitrogen, phosphorus, potassium, and humus. The analysis of macronutrient content in the soil, combined with spectral data from Sentinel-2 L2A satellite imagery, has been integrated with geoinformation systems and mathematical modelling. The results of the macronutrient classification have been visualised in the form of cartograms. The classification analysis involved mathematical modelling of statistical data arrays on the content of phosphorus, potassium, humus, and nitrogen in the soil using the BN-BPNN neural network model, compared with data obtained from agrochemical soil sampling. The model tests demonstrate high efficiency for two soil types. For chernozem soil, the accuracy of nitrogen determination was 90.55%, phosphorus 98.1%, potassium 57.06%, and humus 90.54%. For chestnut soil, the accuracy was nitrogen 98.19%, phosphorus 42.16%, potassium 89.81%, and humus 98.88%. These results highlight the significant potential of this methodology for adaptation to various soil and climatic conditions. The “smart” technique developed for remote determination of macronutrient content, with automated express construction of cartograms, provides real-time information on soil nutrient levels. This research significantly enhances the integration efficiency of RS (remote sensing), GIS (geographical information systems), and AI (artificial intelligence) data in agriculture, contributing to sustainable land management.

Open Access: Yes

DOI: 10.1007/s43621-024-00625-4

IP Packet Forwarding Performance Comparison of the FD.io VPP and the Linux Kernel

Melinda Kosák Gábor Lencse

Publication Name: Infocommunications Journal

Publication Date: 2025-01-01

Volume: 17

Issue: 2

Page Range: 35-44

Description:

There are numerous free software solutions for IPv4 or IPv6 packet forwarding. The Fast Data Project / Vector Packet Processing (FD.io VPP) is a novel and prominent solution. This paper investigates its performance and scalability compared to that of the Linux kernel. The investigation was conducted in accordance with the requirements outlined in the relevant Request for Comments (RFC) documents (RFC 2544, RFC 4814, and RFC 5180) using the siitperf measurement software. Two different test environments were used to eliminate the potential hardware-specific side effects and to gain insight into the performance and scalability of the IPv4 and IPv6 packet forwarding capability of the two investigated solutions. It was found that FD.io VPP outperformed the Linux kernel by approximately an order of magnitude. The configuration of FD.io VPP, along with the details of the measurements, are provided, and the results are presented and analyzed in the paper.

Open Access: Yes

DOI: 10.36244/ICJ.2025.2.5

Temperature and frequency dependent preisach model

Miklós Kuczmann

Publication Name: Przeglad Elektrotechniczny

Publication Date: 2018-01-01

Volume: 94

Issue: 4

Page Range: 5-8

Description:

The present paper deals with a frequency and temperature dependent modeling approach for hysteresis loops of ferromagnetic materials. The model is based on the Preisach model. The frequency dependency is taken into account by the statistical loss theorem, while thermal effects were incorporated by a generalization of the model equation. The model was validated against measurements made on a soft magnetic material. The results of the proposed model were in good agreement with measured data.

Open Access: Yes

DOI: 10.15199/48.2018.04.02