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1
Content available remote

Analysis of Out of Control Signals in Multivariate Processes with Multilayer Neural Network

100%
Boran S., Diren D.
Acta Physica Polonica A
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2017
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vol. 132
|
issue 3
1054-1057
EN
Control charts that are used for monitoring the process and detecting the out-of-control signals are important tools for statistical process control. It is simple to estimate source(s) for out-of-control signals in the univariate process, whereas it is difficult to identify the source(s) in the multivariate processes. The reason is that these kinds of processes require monitoring and controlling of more than one quality characteristics simultaneously. In this study, the proposed model is expected to detect the source(s) for out-of-control signals without help of an expert in the process, by using a multilayer neural network. This model was implemented in furniture fasteners manufacturing. Time gain was obtained while detecting source(s) for out-of-control signals.
2
Content available remote

Performance Evaluation of Small-Medium Enterprises Based on Management and Organization

100%
Cengız Toklu M., Taşkin H.
Acta Physica Polonica A
|
2017
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vol. 132
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issue 3
994-998
EN
Companies need to constantly evaluate their activities in strategic planning process. These activities include all processes in the company, such as management and organization, research and development, production planning, manufacturing, post-sales services, accounting and finance. The aim of this study is to propose an evaluation model that can be used to evaluate management and organization performance for small and medium enterprises. In the proposed model, fuzzy multi-criteria decision-making approaches consisting of fuzzy analytic network process and fuzzy decision making trial and evaluation laboratory methods are used to determine the weights of performance criteria. A case study has been conducted in a small and medium enterprise for empirical evidence. From the outcome of our investigation, it is possible to conclude that "corporate communication" and "process management" are more important criteria. The most important sub-criteria are listed as, "senior management in harmony with each other", "employee requests and demands are collected periodically" and "pocket reference that includes procedures and fixed rules are available".
3
Content available remote

An Artificial Neural Network-Based Estimation of Bremsstarahlung Photon Flux Calculated by MCNPX

100%
Tekin H., Manici T., Altunsoy E., Yilancioglu K., Yilmaz B.
Acta Physica Polonica A
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2017
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vol. 132
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issue 3
967-969
EN
Bremsstrahlung has an important place in the field of experimental physics, especially for description of photon-matter interaction and for characterization and analysis of materials. Bremsstrahlung photon is created by a high-energy electron, deflected in the electric field of atomic nucleus. Bremsstrahlung is also important for experimental studies, not only in the field of nuclear physics and particle physics but also in the fields of solid state physics, applied physics and astrophysics. In recent years, Monte Carlo simulation has become a widely used method for calculations related to bremsstrahlung. On the other hand, predictions by using artificial neural network can be performed with high accuracy. This study aims at observing variation in the photon flux as unction of target thickness and at processing output data by using an artificial neural network. We achieved a high degree of compatibility between two different methods. This study suggests that artificial neural network is a powerful tool for prediction of Bremsstrahlung and for other scientific problems.
4
Content available remote

Determination of Customer Loyalty Levels by Using Fuzzy MCDM Approaches

100%
Cengız Toklu M.
Acta Physica Polonica A
|
2017
|
vol. 132
|
issue 3
650-654
EN
Customer loyalty is an important issue for business enterprises to improve their market performance. It can be defined as the outcome of a customer's belief in a particular company and customer satisfaction with the company's products or/and services. Business enterprises can make strategic marketing decisions by using customer loyalty levels and manage customer relations. This research will mainly focus on determination of loyalty criteria. The second objective of the research is to prioritize the criteria set. In the proposed model, fuzzy multi-criteria decision making approaches consisting of fuzzy analytic network process and fuzzy decision making trial and evaluation laboratory methods were used to determine the customer loyalty level. A case study has been conducted in a small-medium enterprise to improve the understanding of how companies establish a customer selection strategy with customer loyalty degree. The results from this study indicate that "resistance to change", "purchase frequency" and "switching cost" are the most important criteria to determine customer loyalty.
5
Content available remote

Usability of Fuzzy Logic Modeling for Prediction of Fresh Properties of Self-Compacting Concrete

100%
Beycioğlu A., Gültekin A., Aruntaş H.
Acta Physica Polonica A
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2017
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vol. 132
|
issue 3
1140-1141
EN
The aim of this study is to investigate the usability of fuzzy logic modelling for prediction of fresh properties of self-compacting concrete. In the modelling process, the percentage of fly ash and the percentage of granulated blast furnace slag, as replacement of cement, the percentage of micronized calcite, as replacement of total aggregate, were used as inputs. The slump flow diameter and time and also the V-funnel time were used as outputs. Results show that fuzzy logic modelling may be a useful approach to predict fresh properties of self-compacting concrete, containing fly ash, granulated blast furnace slag and micronized calcite.
6
Content available remote

Antioxidant Properties and Stability of Geissospermum Reticulatum Tinctures: Lag Phase ESR and Chemometric Analysis

76%
Sajkowska-Kozielewicz J. J., Gulik K., Makarova K., Paradowska K.
Acta Physica Polonica A
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2017
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vol. 132
|
issue 1
68-73
EN
Geissospermum species are widely used in folk medicine in the Amazon region. This study was conducted to determine total phenolic and flavonoid contents of three tinctures of Geissospermum reticulatum barks from Peruvian Amazon and correlate these contents to the antioxidant activities and stability. Total content of phenolic compounds (from 694.91 to 1430.67 mg GAE/kg) and flavonoids (575.23-815.65 mg CAE/kg) were found by spectrophotometric methods. The obtained values were interpreted by artificial neural networks to describe the most beneficial conditions for tinctures. All tinctures have demonstrated the maximum of total flavonoid between 14 and 20 weeks of maceration, whereas the maximum of total flavonoid was between 25 and 30. The highest antioxidant properties were exhibited by tinctures in 3 different tests (ferric reducing ability of plasma, DPPH-ESR, oxygen radical absorbance capacity) after 35 weeks of maceration. The principal component analysis was employed to relate contents and properties. Results from the lag phase with α -(4-pyridyl-1-oxide)-N-tert-butylnitrone (POBN) spin trap studies at 60°C demonstrated that the stability of tinctures were related to total phenolic content. Thus, samples with 550-800 mg GAE/kg were more stable than those with higher total phenolic contents. The most beneficial conditions for bark tinctures depend on aimed final products, e.g. maximum of polyphenols or flavonoids and long-term stability. Further studies about content and storage conditions are needed.
7
Content available remote

Prediction of Impact Resistance Properties of Concrete Using Radial Basis Function Networks

76%
Yazici S., Inan Sezer G., Sezer A.
Acta Physica Polonica A
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2017
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vol. 132
|
issue 3
1036-1040
EN
This study presents an investigation of the prediction of impact resistance of steel-fiber-reinforced concrete and ordinary concrete specimens. In the experimental part of this study, parameters identifying impact resistance of various concrete mixtures were determined using an impact test machine, in accordance with ACI Committee 544. For this aim, concrete specimens containing three different aggregates (basalt, limestone and natural aggregate) were cured in water at 20°C for 28 days. After curing impact resistance tests were performed on specimens having compressive strength values between 20 and 50 MPa, to determine the blows to initial crack and failure. The specimens were also subjected to splitting tensile strength and ultrasonic pulse velocity tests. Initially, using blows to initial crack and failure, many attempts were made to classify the impact resistance of different types of concrete in terms of the origin of used aggregate, strength properties or ultrasonic pulse velocity, however, this made no sense. The specimens could only be classified in terms of steel fiber presence. Therefore, radial basis function network, which belongs to another kind of unsupervised classifier network, was used to estimate the two above-mentioned impact resistance parameters. In this scope, independent from aggregate origin used in preparation of specimens, compressive strength, splitting tensile strength and ultrasonic pulse velocity of the specimens were used to predict the impact resistance parameters of the concrete specimens. The results revealed that three listed parameters can be used for estimation of blows to formation of initial crack and failure. Scatter plots, root mean square error and absolute value of average residual parameters were used to verify the errors in predictions, which were very low, compared with the uncertainty in test and ambiguity of data in hand.
8
Content available remote

Optimization of Antioxidant Properties of Creams with Berry Extracts by Artificial Neural Networks

52%
Makarova K., Zawada K., Wagner D., Skowyra J.
Acta Physica Polonica A
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2017
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vol. 132
|
issue 1
44-51
EN
Oxidative stress and the excess of free radicals accelerate the ageing process of human skin. The application of skin cream with antioxidant compounds could reduce the damage caused by free radicals. In this work we studied two types of skin creams with extracts from aronia (Aronia melanocarpa), elderberry (Sambucus nigra) and bilberry (Vaccinium myrtillus) because of their high content of anthocyanins, i.e. strong natural antioxidants. The 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging ability of the skin creams with berry extracts were studied with ESR spectroscopy. The artificial neural networks were applied to optimize the berry extract concentration and storage time for oil-in-water and water-in-oil creams. Based on experimental results chokeberry and elderberry extracts in oil-in-water cream base revealed higher DPPH radical scavenging ability than in the corresponding water-in-oil. Artificial neural networks predicts maxima of DPPH radical scavenging for 1-week stored elderberry (2.23 mg DPPH/g) and 1-week stored chokeberry (5.84 mg DPPH/g) and bilberry (5.26 mg DPPH/g) 0.76% extracts in oil-in-water creams. The maxima of DPPH radical scavenging for water-in-oil creams were predicted for 6-week stored 0.8% aronia extract, freshly prepared 0.76% bilberry extract and 1-week stored 0.56% elderberry extract. The artificial neural networks predicted values are in good agreement with the experimental values. DPPH-EPR could be combined with artificial neural networks to optimize the extract concentration, and the type of cream base as well as to predict the effect of storage based on a limited number of experiments and samples.
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