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Found 6319 publications

SZTAKI @ ImageCLEFmed 2020 Tuberculosis Task

No authors available

Publication Name: CEUR Workshop Proceedings

Publication Date: 2020-01-01

Volume: 2696

Issue:

Page Range: Unknown

Description:

In this paper we describe our submission to the ImageCLEFmed 2020 Tuberculosis task and discuss additional results on the training set with various neural networks. After some centralization and normalization we independently categorized the 2D slices with convolutional neural networks (traditional and residual feed-forward networks) and we aggregated the individual predictions based on the positions of the lung and the slices. Our additional experiments with various aggregation methods indicate that individual slices do not necessary contain enough information about such complex structures.

Open Access: No

DOI: DOI not available

Numerical study on the micro-mechanical behaviour of artificial granular materials

No authors available

Publication Name: Proceedings of the 2020 Session of the 13th fib International PhD Symposium in Civil Engineering

Publication Date: 2020-01-01

Volume:

Issue:

Page Range: 86-93

Description:

Numerical models for the simulation of the micro-mechanical behaviour of granular assemblies have a wide range of applications, for instance in material science, process engineering, environmental engineering, railway engineering and geotechnical engineering (in this study we examined one macro-grain but what important is behaviour of granular assemblies). In this examination, experimental tests and numerical computations using the discrete element method (DEM) are carried out to evaluate the micro-mechanical behviour of the granular materials. For this purpose, artificial materials are taken into consideration for experimental Brazilian laboratory tests, and then according to the experimental results the DEM model is calibrated. Artificial crushable materials are produced by mixing cement and silt according to their mass ratio, in which cement can provide bonding and silt is the main filling material. In the DEM model, a 3D crushable granular material 'macro-grain' is built up from a large number of micro-grains which are associated according to crushable parallel bond properties. The behaviour of the single crushable grains and the fragmentation patterns under different contact configuration and load position are studied. The DEM simulation results show that the contact configuration type and load position affect the fragmentation patterns and loading capacity.

Open Access: No

DOI: DOI not available

Numerical study on the micro-mechanical behaviour of artificial granular materials

No authors available

Publication Name: fib Symposium

Publication Date: 2020-01-01

Volume:

Issue:

Page Range: 86-93

Description:

Numerical models for the simulation of the micro-mechanical behaviour of granular assemblies have a wide range of applications, for instance in material science, process engineering, environmental engineering, railway engineering and geotechnical engineering (in this study we examined one macro-grain but what important is behaviour of granular assemblies). In this examination, experimental tests and numerical computations using the discrete element method (DEM) are carried out to evaluate the micro-mechanical behviour of the granular materials. For this purpose, artificial materials are taken into consideration for experimental Brazilian laboratory tests, and then according to the experimental results the DEM model is calibrated. Artificial crushable materials are produced by mixing cement and silt according to their mass ratio, in which cement can provide bonding and silt is the main filling material. In the DEM model, a 3D crushable granular material ‘macro-grain’ is built up from a large number of micro-grains which are associated according to crushable parallel bond properties. The behaviour of the single crushable grains and the fragmentation patterns under different contact configuration and load position are studied. The DEM simulation results show that the contact configuration type and load position affect the fragmentation patterns and loading capacity.

Open Access: No

DOI: DOI not available

An efficient evolutionary metaheuristic for the traveling repairman (Minimum latency) problem

Peter Foldesi Boldizsar Tuu-Szabo Ĺaszĺo T. Ḱoczy

Publication Name: International Journal of Computational Intelligence Systems

Publication Date: 2020-01-01

Volume: 13

Issue: 1

Page Range: 781-793

Description:

In this paper we revisit the memetic evolutionary family of metaheuristics, called Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA), whose members combine Furuhashi’s Bacterial Evolutionary Algorithm and various discrete local search techniques. These algorithms have proven to be efficient approaches for the solution of NP-hard discrete optimization problems such as the Traveling Salesman Problem (TSP) with Time Windows. This paper presents our results in solving the Traveling Repairman Problem (also called Minimum Latency Problem) with a DBMEA variant. The results are compared with state-of-the-art heuristics found in the literature. The DBMEA in most cases turned out to be faster than all other methods, and for the bigger benchmark instances it was also found to have better solutions than the former best-known results. Based on these test results we claim to have found the best approach and thus we suggest the use of the DBMEA for the Traveling Repairman Problem, especially for large instances.

Open Access: Yes

DOI: 10.2991/ijcis.d.200529.001

The effect of background and outlier subtraction on the structural entropy of two-dimensional measured data

No authors available

Publication Name: International Journal of Reasoning-based Intelligent Systems

Publication Date: 2020-01-01

Volume: 12

Issue: 3

Page Range: 200-209

Description:

For colonoscopy images the main information is in the fine structure of the surface of the bowel or colorectal polyps, similarly to the case of combustion engine cylinder surface scans, where the grooving and wear can be detected from the fine pattern superposed to a cylinder curvature. In both cases appear outliers, colonoscopy images have many reflections, whereas the roughness scanners detect small dust particles as well as the micron scale vibrations from the environment. The method presented in this paper takes care of both the problems using histogram stretching together with a special type of filtering. Also, masks are introduced in order to control the effect of the operators. The effects of the processing steps on the structural entropy of the image is also studied, as structural entropies are used in characterisation of the images. By removing the background makes the structural entropies much smaller, and by suppressing the outliers the structural entropies increase.

Open Access: No

DOI: DOI not available

Recent advances in learning content and infrastructure development for layout and process planning courses at the SZTAKI learning factories

Zsolt Kemény Richárd Beregi Bence Tipary Kristóf Abai János Nacsa

Publication Name: Procedia Manufacturing

Publication Date: 2020-01-01

Volume: 45

Issue: Unknown

Page Range: 319-324

Description:

Two locations maintained by SZTAKI-in Budapest and Gyor, respectively-provide infrastructure for learning factory programs, primarily in layout and process planning, and process execution. In addition to project-oriented work successfully hosted by the facilities for several years, the development of repeatable and evolvable learning content began in 2019. A preceding publication presented a roadmap for the development of re-usable courses based on outcomes of one-shot projects which built up an initial infrastructure. This paper gives an in-progress view at selected dimensions of learning content and course development. In view of recent additions to available infrastructure, an extended portfolio of design and scenario choices is presented with suggested sets of options which can be opened up for elaboration by course participants. Complementing these, typical course types are also summarized, with special emphasis on options likely to be deployed in the current operating context of the facilities.

Open Access: Yes

DOI: 10.1016/j.promfg.2020.04.024

Shelf life of bottled water – field conditions in Hungary

Rajmund Kuti Judit Molnár Bendegúz Papp Rita Molnár Dóra Beke

Publication Name: Journal of Food and Nutrition Research

Publication Date: 2020-01-01

Volume: 59

Issue: 4

Page Range: 361-366

Description:

Professional soldiers and firefighters are deployed to deal with the consequences of various disasters, where their supply is carried out under field conditions. This study investigated whether improperly stored bottled drinking water can change its quality and pose a biological hazard. Microbiological quality of 20 samples of bottled mineral water produced in Hungary, including 10 uncarbonated, 5 carbonated and 5 flavoured mineral water samples, was investigated under field conditions. Culturable microorganisms were enumerated by ISO 6222:1999; coliforms and Escherichia coli by ISO 9308-1:2000; Pseudomonas aeruginosa by ISO 16266:2006; Enterococcus spp. by ISO 7899-2:2000; and Clostridium perfringens by ISO 14189:2013. In six cases among uncarbonated water samples, the aerobic colony counts exceeded the standard value. Furthermore, coliforms and P. aeruginosa were detected in three cases. However, in carbonated and flavoured mineral water, no samples of unacceptable bacteriological quality were observed, as their pH value was significantly lower and that probably did not favour proliferation of bacteria. Due to their acidic condition, carbonated and flavoured mineral water appears to be less vulnerable to microbiological contamination under field conditions. During flood damage remediation, it is advisable to perform the supply of intervention units with carbonated and flavoured mineral water to avoid infection.

Open Access: Yes

DOI: DOI not available

Mathematics self-efficacy, learning approaches, academic performance in the light of the number of failed attempts

No authors available

Publication Name: SEFI 48th Annual Conference Engaging Engineering Education, Proceedings

Publication Date: 2020-01-01

Volume:

Issue:

Page Range: 286-296

Description:

Mathematics is a language for expressing physical, chemical and engineering laws nevertheless engineering students often perform poorly in mathematics. Studying can be influenced by several different social, cognitive and non-cognitive factors which all can have an impact on students' academic performance. Many researches revealed positive effects of mathematics self-efficacy on mathematics achievement. Similar results can be found among learning approaches, students using deep-approach achieve better results. It is legitimate to question whether there is a relationship between self-efficacy and learning approaches. My research focused on the interrelationship between two aspects of mathematics self-efficacy (mastery experience, physiological state), learning approaches (deep strategy, deep motive, surface strategy, surface motive) and achievement. This research also examined the variance of self-efficacy, learning approaches and achievement in relation to the number of failed attempts. 306 undergraduate engineering students at a Hungarian university took part in the study. To examine the above mentioned question the study employed quantitative approach and data were collected using two questionnaires during the semester. The self-efficacy scale was adapted from a variety of sources and was modified to local conditions. To measure learning approaches the Revised Two Factor Study Process Questionnaire was rephrased to the domain of mathematics and to the local conditons. The data were analysed quantitatively using descriptive statistics, bivariate correlation, partial correlation, and regression analysis. The results show that self-efficacy, learning approaches and academic achievement were strongly correlated with each other. Students who have higher level self-efficacy use deep strategy in learning and have deep motives, while students classified as low in self-efficacy adopted surface learning approaches. A new variable was introduced which has not been investigated yet in other researches: the number of failed attempts. A significant correlation between the mentioned variables and the number of attempts was identified. My results demonstrate the importance of such kind of learning environment which fosters self-efficacy and deep learning approach.

Open Access: No

DOI: DOI not available

Territorial Research in Central Europe – Report on the 2019 Conferences of the Hungarian Regional Science Association

Szilárd Rácz Ildikó Egyed

Publication Name: Deturope

Publication Date: 2020-01-01

Volume: 12

Issue: 3

Page Range: 7-12

Description:

No description provided

Open Access: Yes

DOI: 10.32725/det.2020.019