Search Everything

Tip: Search using "First Name + Last Name", e.g.
János Kiss instead of Kiss János.

Publications - 6278

Pulchellaobovella brunszvikae sp. nov.: the second species of the genus in Africa with the notes on the genus Pulchellaobovella Hirschmann, 1979 (Acari: Uropodina: Urodinychidae)

Sergey G. Ermilov Jenő Kontschán Rita Ábrahám

Publication Name: International Journal of Acarology

Publication Date: 2025-01-01

Volume: 51

Issue: 7-8

Page Range: 525-529

Description:

Herein, a new species, Pulchellaobovella brunszvikaesp. nov. (Mesostigmata: Uropodina: Urodinychidae), is described and illustrated based on two females and two males collected in Kenya. It is the second representative of the genus Pulchellaobovella in Africa. The new species differs from the already described Pulchellaobovella species in the presence of strongly sclerotized grooves on the dorsal shield, which are unique characters in this genus. A generic diagnosis and a new key to the known species are presented. Paper: http://www.zoobank.org/urn:LSIDurn:lsid:zoobank.org:pub:77E084D4-8256-4148-A500-4A336CCF4A8C New species: http://www.zoobank.org/urn:LSIDurn:lsid:zoobank.org:pub:6C6EE41C-F38F-4242-8063-9441FE96A430.

Open Access: Yes

DOI: 10.1080/01647954.2025.2571118

Example for convex hull tightening increasing the feasible parameter region at Linear Matrix Inequality based control design

Peter Varlaki Alexandra Szollosi Péter Baranyi

Publication Name: Ines 2014 IEEE 18th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2014-09-24

Volume: Unknown

Issue: Unknown

Page Range: 175-180

Description:

The paper shows an example when the tightening of the convex hull determined by the vertexes of the polytopic Tensor Product model representation of a given quasi Linear Parameter Varying state-space model leads to feasible Linear Matrix Inequality based control design. In addition the paper unveils that the relaxation of the Tensor Product model complexity interferes also with the Linear Matrix Inequality feasibility results. The example at hand consists of the complex Nonlinear Aeroelastic Test Apparatus model of the three degree of freedom aeroelastic wing section model including Stribeck friction. The relaxation and convex hull tightening is based on the concept of the Tensor Product model transformation.

Open Access: Yes

DOI: 10.1109/INES.2014.6909364

In trust we thrive: What drives the sharing economy?

Gauri Shankar Gupta Kinga Szabó

Publication Name: Corvinus Journal of Sociology and Social Policy

Publication Date: 2020-01-01

Volume: 11

Issue: 2

Page Range: 49-68

Description:

The rapid growth of the sharing economy in the last two decades may signal a paradigm shift in global capitalism and societal values. Digital platforms have brought together strangers with under-utilized capacities and assets with those who need them but who are not looking for ownership. The radius of trust, which was initially confined to family, friends and local communities, now encompasses strangers who speak no common language and who may live oceans apart. Trust, driven by Digital Identity (DI) and Trust and Reputation Information (TRI), has enabled what was considered improbable or even impossible some years ago. The further expansion and deepening of trust, based on new technologies combined with the international legal framework, has the potential to rewrite the apparatus of modern capitalism and societal values. Civil society and governments need to engage on this issue to guide them in a direction that is most beneficial to society. However, the current extraordinary situation due to the Coronavirus pandemic, coupled with the foreseeable tendency to complete digital control, is likely to have far-reaching impact on the future development of the sharing economy.

Open Access: Yes

DOI: 10.14267/CJSSP.2020.2.3

Tensor-based Format for Exchanging Hypergraphs between Cognitive Entities

None Csapó Csaba Hajdu

Publication Name: 2022 IEEE 1st International Conference on Internet of Digital Reality Iod 2022

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 33-38

Description:

Robotic and other intelligent systems have recently gained prominence, integrating a growing number of new functionalities. Since the beginning, the flexible semantic self-recognition of intelligent devices has been a challenge. The traditional solution is to provide a centralized source of semantic descriptions (in parameter servers or external sources). This paper introduces a graph-like binary format for machine-to-machine information exchange to efficiently index and process graph-based data at each endpoint. The exchanged graphs, which are represented as multidimensional tensors, are based on the formal theory of hypergraphs, allowing for the description of associations between not just two, but multiple modalities. We show in addition that hierarchical information is also compatible with this hypergraph-based formalism. Thus, structured information can be shared between intelligent entities, using the proposed format, to share information for reasoning, planning (e.g., motion planning in robotics), as well as environment representation. A further motivation includes the description of vision data by providing semantic information that can be rewritten in interpretable form for the target visualization engine.

Open Access: Yes

DOI: 10.1109/IoD55468.2022.9986845

Searching for a nonlinear ODE model of vehicle crash with genetic optimization

Miklós F. Hatwágner István Harmati András Horváth

Publication Name: Saci 2012 7th IEEE International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2012-01-01

Volume: Unknown

Issue: Unknown

Page Range: 131-136

Description:

Vehicle crash is a very complex process, which can be modelled in details using the finite element method (FEM), but a simple, quasi-heuristic model with a limited number of parameters is often more beneficial. In this paper we propose a relatively simple dynamic model for deformation and force during a frontal collision process, which has very similar behavior to the experimental data. A genetic-type optimization of model parameters is executed on three car crash experimental data sets. ©2012 IEEE.

Open Access: Yes

DOI: 10.1109/saci.2012.6249990

Dr. Steinberger Sarolta (1875–1966) és az ártatlanság vélelme

Bóka Dalma Göndör Éva Zsák Brúnó

Publication Name: Orvosi Hetilap

Publication Date: 2025-01-12

Volume: 166

Issue: 2

Page Range: 77-80

Description:

No description provided

Open Access: Yes

DOI: 10.1556/650.2025.HO2817

Application of Machine Learning to Automatic Gear Shift Schedule Design of Alternative Drive Systems

Adrienn Dineva Szabolcs Kocsis Szurke Adam Zsuga

Publication Name: 2022 22nd International Symposium on Electrical Apparatus and Technologies Siela 2022 Proceedings

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Intelligent automatic transmission shift schedule design has been well established in the last decade. However, due to the paradigm change is currently taking place in mobility sector, which resulted in a rapid progress of Electric Vehicles and Autonomous Vehicles, intelligent automatic gear shift strategies are still in the focus of much research. In addition, the proper transmission shift schedule generation is especially important from the viewpoint of energy efficiency optimizing algorithms, which is affected by the driving style, power losses, etc. Fundamentally, conventional shift schedule design relies on lookup tables obtained from test-bench measurements and real-world driving measurements. During real time test data collection, the measurement of some variables may be impractical and/or patterns of important driving conditions may be unavailable during short-distance routes neglecting the comprehensive effects of the transient operation. Machine Learning methods in combination with model-based data generation is a promising alternative, which allows a significant reduction in development time and a more precise calibration by using rich historical data rich. Such models can be easily fitted to alternative drive systems also, which may raise more specific requirements regarding gear shift scheduling issues coupled with efficiency. In this paper the performances of Machine Learning models are investigated in automatic gear shift schedule generation based on simulated driving cycle test data. Results of simulation investigations validate the applicability and efficiency of the proposed approach.

Open Access: Yes

DOI: 10.1109/SIELA54794.2022.9845718

Equivalence of MCDM Methods and Synthesis of Solution Based on Ratings Obtained in Different Models

Dragan Pamucar Irik Z. Mukhametzyanov

Publication Name: Decision Making Applications in Management and Engineering

Publication Date: 2025-01-01

Volume: 8

Issue: 2

Page Range: 1-20

Description:

Synthesis of solutions based on a set of models is a modern trend in the field of multi-criteria choice. It is assumed that a solution based on many methods increases the reliability of the decisions made. One of the important tasks is to select an independent set of models. Comparison of various multi-criteria methods is performed using two lists: rank and rating. To compare the rating of alternatives obtained using different MCDM models, the article uses the Relative Performance Indicator (RPI). Using RPI, six identical methods for aggregating private attributes of alternatives are established: Weighted Sum Model (WSM), Ratio System approach (RS), Multi-Attributive Border Approximation area Comparison (MABAC), Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) with L1 metric, Multi Atributive Ideal-Real Comparative Analysis (MAIRCA) and Ranking of Alternatives with Weights of Criterion (RAWEC) provided that each aggregation method combines the same method of linear normalization of attributes. This allows avoiding duplication of equivalent methods in the Multi-Method Model (3M) approach combining different MCDM models. When solving MCDM problems, it is recommended to use the simplest and most easily interpreted of them: WSM. The presented methodology is recommended as mandatory for the analysis of new or hybrid MCDM methods to eliminate duplication of existing methods. A synthesis of a solution based on ratings obtained in different MCDM models within the 3M approach is proposed. The method includes coordinating the common goal of several models and bringing the ratings obtained in different MCDM models to a common scale, which allows comparing and aggregating the ratings. The resulting rating is more informative than a rating based on ranks, such as Borda rules or similar, since it reflects the real proportions of the effectiveness of alternatives in different models.

Open Access: Yes

DOI: 10.31181/dmame8220251473

Harnessing artificial intelligence for urban economic resilience

Hyoungsuk Lee Xin Zhao Xiaowei Ma Guoqing Zhai Nicholas Apergis

Publication Name: Applied Economics

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Amid escalating global economic uncertainty, a comprehensive analysis of the effect of artificial intelligence (AI) development on urban economic resilience (UER) is crucial for promoting sustainable global economic development. This study utilizes panel data from 284 Chinese cities from 2010 to 2022 to empirically test the influence of urban AI on UER and its role mechanism by using the fixed-effects, mediating-effects, and moderating-effects models. The study reveals that AI significantly enhances UER, with an improvement of 7.44%. Harnessing AI for UER remains valid even after conducting the robustness and endogeneity tests. Mechanism analysis discovered that AI enhances UER by increasing urban innovation ability. Industrial structure and wage structure positively moderate the effect of AI on UER. Heterogeneity analysis demonstrates that the improvement effect of AI level on UER is more evident in large (7.49% increase), southern (5.11% increase), non-resource-based (10.84% increase), and high-economic cities (11.17% increase). This paper discusses the path selection from an AI perspective to enhance UER, which provides a useful reference for cities seeking to navigate the new wave of technological revolution.

Open Access: Yes

DOI: 10.1080/00036846.2025.2501352