Search Everything

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

Publications - 6289

Artificial neural network for modeling and investigating the effects of forming tool characteristics on the accuracy and formability of thin aluminum alloy blanks when using SPIF

Imre Paniti Sherwan Mohammed Najm

Publication Name: International Journal of Advanced Manufacturing Technology

Publication Date: 2021-06-01

Volume: 114

Issue: 9-10

Page Range: 2591-2615

Description:

Incremental Sheet Forming (ISF) has attracted attention due to its flexibility as far as its forming process and complexity in the deformation mode are concerned. Single Point Incremental Forming (SPIF) is one of the major types of ISF, which also constitutes the simplest type of ISF. If sufficient quality and accuracy without defects are desired, for the production of an ISF component, optimal parameters of the ISF process should be selected. In order to do that, an initial prediction of formability and geometric accuracy helps researchers select proper parameters when forming components using SPIF. In this process, selected parameters are tool materials and shapes. As evidenced by earlier studies, multiple forming tests with different process parameters have been conducted to experimentally explore such parameters when using SPIF. With regard to the range of these parameters, in the scope of this study, the influence of tool material, tool shape, tool-end corner radius, and tool surface roughness (Ra/Rz) were investigated experimentally on SPIF components: the studied factors include the formability and geometric accuracy of formed parts. In order to produce a well-established study, an appropriate modeling tool was needed. To this end, with the help of adopting the data collected from 108 components formed with the help of SPIF, Artificial Neural Network (ANN) was used to explore and determine proper materials and the geometry of forming tools: thus, ANN was applied to predict the formability and geometric accuracy as output. Process parameters were used as input data for the created ANN relying on actual values obtained from experimental components. In addition, an analytical equation was generated for each output based on the extracted weight and bias of the best network prediction. Compared to the experimental approach, analytical equations enable the researcher to estimate parameter values within a relatively short time and in a practicable way. Also, an estimate of Relative Importance (RI) of SPIF parameters (generated with the help of the partitioning weight method) concerning the expected output is also presented in the study. One of the key findings is that tool characteristics play an essential role in all predictions and fundamentally impact the final products.

Open Access: Yes

DOI: 10.1007/s00170-021-06712-4

The event-driven social responsibility in small and medium-sized enterprises

Adrienn Reisinger Roland Zsolt Szabó

Publication Name: Corporate Social Responsibility and Environmental Management

Publication Date: 2024-09-01

Volume: 31

Issue: 5

Page Range: 3927-3939

Description:

Since the survival and growth of small firms depend largely on their ability to acquire legitimacy within the institutional environment, social responsibility plays an important role in their lives. The aim of this study was to investigate how a disruption in the normal course of business can lead to an evolution and change in the social responsibility activities of small and medium-sized enterprises. Such disruptions, called critical incidents, interrupt the normal functioning of the business. The case-based exploratory study found that such critical events can have a positive impact. In particular, they can initiate the integration of socially responsible business practices. This is a journey from philanthropic donations to fully integrated socially responsible practices, often driven by internal triggering events such as organisational growth, unanticipated changes in management, or generational change, which allow new values to be brought on board. When such an internal event is followed by a highly critical but external event, such as the COVID-19 pandemic, the transformation gains momentum. The findings also suggest that social responsibility can be a new source of competitive advantage.

Open Access: Yes

DOI: 10.1002/csr.2775

A virtual environment for testing and evaluation of control algorithms for a line follower robot

Miklós Kuczmann Tamás Budai

Publication Name: Gpmc 2020 2nd IEEE International Conference on Gridding and Polytope Based Modeling and Control Proceedings

Publication Date: 2020-11-19

Volume: Unknown

Issue: Unknown

Page Range: 53-54

Description:

In this paper we introduce a new virtual test environment realized in MaxWhere which can be used to model and compare different control algorithms for a line follower robot.

Open Access: Yes

DOI: 10.1109/GPMC50267.2020.9333822

Application of artificial neural networks for characterisation of formability properties of sheet metals

Dóra Harangozó Imre Czinege

Publication Name: International Journal of Lightweight Materials and Manufacture

Publication Date: 2024-01-01

Volume: 7

Issue: 1

Page Range: 37-44

Description:

Artificial neural network models were developed to estimate forming limit diagrams from tensile test results based on our own experiments and data from the literature for steel and aluminium sheet metals. Experimental data were obtained from tensile tests and Nakazima tests. The input parameters used in the models were yield strength, ultimate tensile strength, uniform elongation, elongation at fracture, anisotropy coefficient and hardening exponent or combinations of these. The forming limit curves were defined by the measured minor and major strains using seven standard test specimens. After training the artificial neural network, the difference between measured and predicted results was evaluated by linear regression parameters and by the absolute errors. For steel sheet data taken from the literature, the estimated outputs of ANN models were compared with the results of empirical formulae developed by different authors. It was found that there was a high correlation coefficient between predicted and measured values for models using neural networks, which gave better approximations than other linear and non-linear models.

Open Access: Yes

DOI: 10.1016/j.ijlmm.2023.08.003

Implant for augmentation of Cerebral blood flow trial-1 (IMPact-1). A single-arm feasibility study evaluating the safety and potential benefit of the Ischemic Stroke System for treatment of acute ischemic stroke

Vinod Puri Hans Christoph Diener Laszlo Csiba Ilona Adam Bernd Griewing Attila Csanyi Nasli R. Ichaporia Attila Valikovics Andreas Hetzel Natan Bornstein Stefan Schwab Dietmar Schneider Subhash Kaul Dheeraj Khurana

Publication Name: Plos One

Publication Date: 2019-07-01

Volume: 14

Issue: 7

Page Range: Unknown

Description:

Background The Ischemic Stroke System is a novel device designed to deliver stimulation to the sphenopalatine ganglion(SPG).The SPG sends parasympathetic innervations to the anterior cerebral circulation. In rat stroke models, SPG stimulation results in increased cerebral blood flow, reduced infarct volume, protects the blood brain barrier, and improved neurological outcome. We present here the results of a prospective, multinational, single-arm, feasibility study designed to assess the safety, tolerability, and potential benefit of SPG stimulation inpatients with acute ischemic stroke(AIS). Methods Patients with anterior AIS, baseline NIHSS 7–20 and ability to initiate treatment within 24h from stroke onset, were implanted and treated with the SPG stimulation. Patients were followed up for 90 days. Effect was assessed by comparing the patient outcome to a matched population from the NINDS rt-PA trial placebo patients. Results Ninety-eight patients were enrolled (mean age 57years, mean baseline NIHSS 12 and mean treatment time from stroke onset 19h). The observed mortality rate(12.2%), serious adverse events (SAE)incidence(23.5%) and nature of SAE were within the expected range for the population. The modified intention to treat cohort consisted of 84 patients who were compared to matched patients from the NINDS placebo arm. Patients treated with SPG stimulation had an average mRS lower by 0.76 than the historical controls(CMH test p = 0.001). Conclusion The implantation procedure and the SPG stimulation, initiated within 24hr from stroke onset, are feasible, safe, and tolerable. The results call for a follow-up randomized trial (funded by BrainsGate; clinicaltrials.gov number, NCT03733236).

Open Access: Yes

DOI: 10.1371/journal.pone.0217472

Chinese and Indian FDI in Hungary and the role of Eastern Opening policy

Eszter Lukács Katalin Völgyi

Publication Name: Asia Europe Journal

Publication Date: 2021-06-01

Volume: 19

Issue: 2

Page Range: 167-187

Description:

The aim of this paper is to assess the main features of Chinese and Indian investments in Hungary and the role of the Hungarian Government’s Eastern Opening policy in the attraction of investments from these two Asian giants. This paper covers the sectoral distribution, modes of market entry, and motivations of Chinese and Indian foreign direct investments. The automotive sector is the most attractive sector for investors from both countries. ICT manufacturing (electronics) and services, and the renewable energy sector are also very attractive for Chinese companies. The same is true for IT/BPO services and the chemical sector in the case of Indian companies. Chinese and Indian companies enter the Hungarian economy mainly through green-field investments or acquisitions. Market-seeking and strategic asset-seeking motives are dominant in the case of investors from both countries. This paper also puts a special emphasis on studying the impacts of Hungary’s Eastern Opening policy (launched in 2012) on Chinese and Indian investments. The findings show that the Eastern Opening policy has had a significant impact on the investment decision (location choice) of new Chinese and Indian investors and further expansion of investments by Chinese and Indian companies located in Hungary due to four factors, namely high-ranking political meetings, strategic cooperation agreements, cash grants from the Hungarian Government and supportive services of HIPA.

Open Access: Yes

DOI: 10.1007/s10308-020-00592-1

Contribution to knowledge of Uropodina mites (Acari: Mesostigmata) of Virginia, USA

Sergey G. Ermilov Jenő Kontschán

Publication Name: Acarologia

Publication Date: 2025-01-01

Volume: 65

Issue: 4

Page Range: 998-1010

Description:

During the investigation of the Uropodina mites of Virginia state (USA) two previously known species (Trachytes balazyi Wiśniewski & Hirschmann, 1994 and Jedediella hoffmani Kontschán, 2017) are discovered in some new localities. Besides the known Uropodina mites, two new species are discovered and described from this state. Trachytes jokaii n. sp. differs from the congener in the shape of the wide and ribbed anterior margin, the shape of the female genital shield and the sculpture of the ventral shield of females. A new key to the North American Trachytes species is also presented. The second species Klebensbergia virginiana n. gen., n. sp. is a unique Uropodina mite in the temperate climate. Only the tropical Penicillaturopoda Hirschmann, 1979 is similar to the new genus.

Open Access: Yes

DOI: 10.24349/tb3j-gb36

EDLRIS: A European Driving License for Robots and Intelligent Systems

Claudiu Radu Pozna Áron Ballagi Imre Szalay Marlene Miglbauer Martin Kandlhofer Ronald Bieber Wilfried Baumann Istvan Alfoldi Manuel Menzinger Sandra Plomer Margit Ehardt-Schmiederer Inge Strobl-Zuchtriegl Gabor Miltenyi Thomas Winkler Julia Lassnig Gerald Steinbauer

Publication Name: Ki Kunstliche Intelligenz

Publication Date: 2021-06-01

Volume: 35

Issue: 2

Page Range: 221-232

Description:

This article presents a novel educational project aiming at the development and implementation of a professional, standardized, internationally accepted system for training and certifying teachers, school students and young people in Artificial Intelligence (AI) and Robotics. In recent years, AI and Robotics have become major topics with a huge impact not only on our everyday life but also on the working environment. Hence, sound knowledge about principles and concepts of AI and Robotics are key skills for this century. Nonetheless, hardly any systematic approaches exist that focus on teaching principles of intelligent systems at K-12 level, addressing students as well as teachers who act as multipliers. In order to meet this challenge, the European Driving License for Robots and Intelligent Systems—EDLRIS was developed. It is based on a number of previously implemented and evaluated projects and comprises teaching curricula and training modules for AI and Robotics, following a competency-based, blended learning approach. Additionally, a certification system proves peoples’ acquired competencies. After developing the training and certification system, the first 32 trainer and trainee courses with a total of 445 participants have been implemented and evaluated. By applying this innovative approach—a standardized and widely recognized training and certification system for AI and Robotics at K-12 level for both high school teachers and students—we envision to foster AI/Robotics literacy on a broad basis.

Open Access: Yes

DOI: 10.1007/s13218-021-00716-8

The implication of business intelligence in risk management: a case study in agricultural insurance

Mohammad J. Tarokh Sayyed M. Haybatollahi Sayyed M. Haybatollahi Mehran Amini Farid Yousefinejad Sara Salimi

Publication Name: Journal of Data Information and Management

Publication Date: 2021-06-01

Volume: 3

Issue: 2

Page Range: 155-166

Description:

The increasing data scales in today’s business sectors coupled with the necessity of risk management raise the importance of business intelligence tools as an integrated solution for the insurance industry. These tools have mostly been used to achieve effective risk management. Although methods of risk management in the insurance industry have been proposed many years ago, the research effort has primarily been focused on predictive analyses. This study aimed to investigate the role of business intelligence as a solution to illustrate its potential in risk management particularly for decision-makers in agricultural insurance. We hypothesized that this would make a preferable decision in uncertain conditions. Sample data from the online transaction process system of Iran agricultural insurance fund were preprocessed in SQL server. Multidimensional online analytical processing architecture was analyzed using Targit business intelligence tool. Our results identified financial risks that lead to a framework of controlling risk based on business intelligence in the agricultural insurance fund.

Open Access: Yes

DOI: 10.1007/s42488-021-00050-6