A novel anti-slip control approach for railway vehicles with traction based on adhesion estimation with swarm intelligence

Anti-slip control systems are essential for railway vehicle systems with traction. In order to propose an effective anti-slip control system, adhesion information between wheel and rail can be useful. However, direct measurement or observation of adhesion condition for a railway vehicle in operation is quite demanding. Therefore, a proportional–integral controller, which operates simultaneously with a recently proposed swarm intelligence-based adhesion estimation algorithm, is proposed in this study. This approach provides determination of the adhesion optimum on the adhesion-slip curve so that a reference slip value for the controller can be determined according to the adhesion conditions between wheel and rail. To validate the methodology, a tram wheel test stand with an independently rotating wheel, which is a model of some low floor trams produced in Czechia, is considered. Results reveal that this new approach is more effective than a conventional controller without adhesion condition estimation.

     

Optimising the production of energy from coblended food waste and biosolids using batch reactor studies

Energy production from a coblended mixture of biosolids and food waste was optimised for hydrogen and methane production. Four different blends were prepared by varying the carbohydrate : protein (carb : pro) ratios. The biosolids contained a low carbohydrate fraction and so was not suitable for hydrogen production when used alone. However coblending this waste with a carbohydrate‐enriched food waste produced a greater hydrogen yield, making this option viable. Batch studies showed that the optimised mix had a biosolids concentration of 25.7% (w/w). The largest hydrogen yield of 198.5 mL/gVS_removed was observed when the carb : pro was 2.78, and this was threefold higher than the other carb : pro ratios evaluated in this study. The digestate recovered after hydrogen recovery had a C : N of 17.5, which is in the ideal range for methane production. The biochemical methane potential test showed a methane yield of 239 mL/gVS_removed, and the total volatile solids destruction following two‐phase hydrogen and methane production was 93%.     

Genetic programming based formulation of rotation capacity of wide flange beams

This study is a pioneer work that proposes genetic programming (GP) as a new approach for the explicit formulation of available rotation capacity of wide-flange beams which is an important phenomenon that determines the plastic behaviour of steel structures. The database for the GP formulation is based on extensive experimental results from literature. The results of the GP-based formulation are compared with numerical results obtained by a specialized computer program and existing analytical equations. The results indicate that the proposed GP formulation performs quite well compared to numerical results and existing analytical equations and is quite practical for use.     

Intelligent tutoring system model based on fuzzy logic and constraint-based student model

Neural Computing and Applications - A model for an intelligent tutoring system (ITS) that uses fuzzy logic and a constraint-based student model (CBM) is proposed. The goal of the ITS is to teach...     

Detection of mitotic cells in breast cancer histopathological images using deep versus handcrafted features

One of the most important processes in the diagnosis of breast cancer, which is the leading mortality rate in women, is the detection of the mitosis stage at the cellular level. In literature, many studies have been proposed on the computer-aided diagnosis (CAD) system for detecting mitotic cells in breast cancer histopathological images. In this study, comparative evaluation of conventional and deep learning based feature extraction methods for automatic detection of mitosis in histopathological images are focused. While various handcrafted features are extracted with textural/spatial, statistical and shape-based methods in conventional approach, the convolutional neural network structure proposed on the deep learning approach aims to create an architecture that extracts the features of small cellular structures such as mitotic cells. Mitosis detection/counting is an important process that helps us assess how aggressive or malignant the cancer’s spread is. In the proposed study, approximately 180,000 non-mitotic and 748 mitotic cells are extracted for the evaluations. It is obvious that the classification stage cannot be performed properly due to the imbalanced numbers of mitotic and non-mitotic cells extracted from histopathological images. Hence, the random under-sampling boosting (RUSBoost) method is exploited to overcome this problem. The proposed framework is tested on mitosis detection in breast cancer histopathological images dataset provided from the International Conference on Pattern Recognition (ICPR) 2014 contest. In the results obtained with the deep learning approach, 79.42% recall, 96.78% precision and 86.97% F-measure values are achieved more successfully than handcrafted methods. A client/server-based framework has also been developed as a secondary decision support system for use by pathologists in hospitals. Thus, it is aimed that pathologists will be able to detect mitotic cells in various histopathological images more easily through necessary interfaces.

     

Nutritional value and antioxidant capacity of lunch meals consumed by elderly people of Sharpeville,South Africa

The main objective of this study was to determine the nutritional value and the total dietary antioxidant capacity (TDAC) of lunch meals consumed by elderly people attending a day-care centre in Sharpeville, South Africa. Meals were monitored and collected for a two-week period. The menus were analysed for water, ash, fat, protein, carbohydrates, polyphenols and antioxidant capacity. Eighteen food items, grouped in seven different menus, were identified. Energy provided by the menus covered 32% of the daily reference intakes for females and 25% for males, and the distribution of macronutrients in the menus was 10%, 34% and 56% for protein, fat and carbohydrates, respectively. This is close to the prescribed acceptable macronutrient distribution ranges of 10–35% protein, 20–35% fat and 45–65% carbohydrates. TDAC available from the menus was estimated at 332 μmol Trolox equivalents by DPPH (2,2′-diphenyl-1-picrylhydrazyl) and represented about 9% of the recommended daily allowance. Fruit, which represented only 2.8% of the amount of foods composing the menus, supplied 75.3% of TDAC, whilst contributions from vegetables and legumes were low. With 269 mg gallic acid equivalent in the menus, total phenolics appeared to be quantitatively the main dietary antioxidant, and were significantly correlated (r = 0.443 and p = 0.007) with antioxidant capacity. Fruit portions of the meals served by the day-care centre to the elderly of Sharpeville, need to be increased and diversified in order to reinforce their intake of antioxidants and thus reduce the incidence of non-communicable diseases.     

Fatty acid composition in some selected marine fish species living in Turkish waters

The muscle fatty acid (FA) composition of 12 selected marine fish species living in Turkish waters was determined. FA profiles of muscle were compared in terms of total and individual saturated (SFAs) and unsaturated fatty acids. Total SFA, monounsaturated fatty acid (MUFA), n‐3 polyunsaturated fatty acid (n‐3 PUFA) and n‐6 polyunsaturated fatty acid (n‐6 PUFA) contents as well as n‐3/n‐6 FA and eicosapentaenoic acid (EPA)/docosahexaenoic acid (DHA) ratios differed (P < 0.01) in all fish species. Palmitic acid (16:0) among total SFAs, oleic acid (18:1n‐9) among MUFAs, DHA (22:6n‐3) among n‐3 PUFAs and 18:2n‐6 and 20:4n‐6 among n‐6 PUFAs were the most abundant FAs. The ratio of n‐3/n‐6 PUFA contents, indicating the availability of n‐3 PUFAs that are beneficial for human health, ranged from 2.67 to 12.61. The EPA/DHA ratio was between 0.17 and 0.83 in the marine fish species studied. Copyright © 2005 Society of Chemical Industry     

A Novel Color Image Segmentation Approach Based on Neutrosophic Set and Modified Fuzzy c-Means

Color image segmentation is an important technique in image processing, pattern recognition and computer vision. Many segmentation algorithms have been proposed. However, it is still a complex task especially when there are noises in the images, which have not been studied in much detail. Neutrosophic set (NS) studies the origin, nature, and scope of neutralities. In this paper, we apply NS in the color image and define some new concepts. A directional α-mean operation is proposed to reduce the set indeterminacy. The fuzzy c-means clustering method is improved by integrating with NS and employed for the color image segmentation. The computation of membership and the clustering termination criterion are redefined accordingly. Moreover, a validity criterion is employed to determine the optimal clustering number. Numerical experiments serve to illustrate the effectiveness and reliability of the proposed approach. Experimental results demonstrate that our approach can segment color images automatically and effectively, produce good results as favorably compared to some existing algorithms. The optimal clustering number is determined automatically and no prior knowledge is required. Especially, it can segment both images with the simple and distinct objects and the images with complex and noisy objects, which is the most difficult task for color image segmentation.     

A novel material for lightweight concrete production

This paper presents the results of an experimental study on the effects of using recycled waste expanded polystyrene foam (EPS), as a potential aggregate in lightweight concrete. In this study, thermally modified waste EPS foams have been used as aggregate. Modified waste expanded polystyrene aggregates (MEPS) were obtained by heat treatment method by keeping waste EPS foams in a hot air oven at 130 °C for 15 min. Effects of MEPS aggregate on several properties of concrete were investigated. For this purpose, six series of concrete samples were prepared. MEPS aggregate was used as a replacement of natural aggregate, at the levels of 0%, 25%, 50%, 75%, and 100% by volume. The density of MEPS is much less than that of natural aggregate; MEPS concrete becomes a lightweight concrete with a density of about 900–1700 kg/m³. The 28-d compressive strengths of MEPS concrete range from 12.58 MPa to 23.34 MPa, which satisfies the strength requirement of semi-structural lightweight concrete.