Classification of brain hemorrhage computed tomography images using OzNet hybrid algorithm

Classification of brain hemorrhage computed tomography (CT) images provides a better diagnostic implementation for emergency patients. Attentively, each brain CT image must be examined by doctors. This situation is time-consuming, exhausting, and sometimes leads to making errors. Hence, we aim to find the best algorithm owing to a requirement for automatic classification of CT images to detect brain hemorrhage. In this study, we developed OzNet hybrid algorithm, which is a novel convolution neural networks (CNN) algorithm. Although OzNet achieves high classification performance, we combine it with Neighborhood Component Analysis (NCA) and many classifiers: Artificial neural networks (ANN), Adaboost, Bagging, Decision Tree, K-Nearest Neighbor (K-NN), Linear Discriminant Analysis (LDA), Naïve Bayes and Support Vector Machines (SVM). In addition, Oznet is utilized for feature extraction, where 4096 features are extracted from the fully connected layer. These features are reduced to have significant and informative features with minimum loss by NCA. Eventually, we use these classifiers to classify these significant features. Finally, experimental results display that OzNet-NCA-ANN excellent classifier model and achieves 100% accuracy with created Dataset 2 from Brain Hemorrhage CT images.     

Investigation of Ant System parameter interactions by using design of experiments for job-shop scheduling problems

In recent years, one of the most important and promising research fields has been metaheuristics to find optimal or near-optimal solutions for NP-hard combinatorial optimization problems. Improving the quality of the solution or the solution time is basic research area on metaheuristics. Modifications of the existing ones or creation of hybrid approaches are the focus of these efforts. Another area of improving the solution quality of metaheuristics is finding the optimal combination of algorithm control parameters. This is usually done by design of experiments or one-at-a-time approach in genetic algorithms, simulated annealing and similar metaheuristics. We observe that, in studies which use Ant Colonies Optimization (ACO) as an optimization technique; the levels of control parameters are determined by some non-systematic initial experiments and the interactions of the parameters are not studied yet.In this study, the parameters of Ant System have been investigated on different sized and randomly generated job-shop scheduling problems by using design of experiments. The effects and interactions of the parameters have been interpreted with the outputs of the experiments. Referring to the statistical analysis it is observed that none of the interactions between the Ant System parameters has a significant effect on makespan value. A specific fractional experimental design is suggested instead of the full factorial design. Depending on the findings from the benchmark problems it will be a reliable approach to use the suggested design for saving time and effort in experiments without sacrificing the solution quality.     

Geochemical characteristics of major and trace elements in Sahinali Coals,Aydin, Turkey

In this study, geochemical behavior of elements is investigated in 25 coal samples collected at 10 locations of ?ahinli coaliferous units at southeast of Ayd?n, Turkey. In all the samples, X-ray powder diffraction and inductively coupled plasma mass spectrometry analyses were performed and element and mineral compositions were determined. Total organic carbon (TOC) values of coals are between 14.6 and 37.7 wt% with average of 28.5 wt%. Samples are composed of quartz, calcite, feldspar, dolomite, mica, gypsum, and salt minerals which are accompanied by illite-, kaolinite-, and smectite-type clay minerals. Comparison of average element contents of world coals and studied samples yields that K > Fe > As > U > Cs > Y > Er > Al > Th > Rb > Yb > W > Tb > Dy > Lu > Ce > Sm > La > Ho > Si > Nd > Gd > Tm > Eu > Nb > Pr > Pb > Sn > Ni > Cu > Ga > Ta > Sb > Zr > Cd > V > Zn > Co > Mo > P > Hf > Ba are found to be enriched, while Mn > Be > Ca > Sr > Bi > Mg are found to be depleted. Statistically elements are correlated with TOC.     

A Review of Dehydration of Various Industrial Sludges

Wastewater characteristics and sludge generation potential of point source categories are reviewed critically. Novel industry-specific sludge dewatering/drying solutions necessary to establish a sustainable model are examined through a detailed literature survey. Knowledge of sludge properties is one of the most critical issues needed to design dewatering/drying equipment. This study focuses on industrial wastewater/sludge characterization. In addition, a comprehensive review of current drying models and technologies is also presented. A summary of the results derived from a novel thin-film-based photonic sludge dewatering/drying study is outlined as an alternative approach for industrial sludge control. Sludge was dried in a tubular quartz reactor (TQR), the inner surface of which was coated with a TiO₂ thin film. The TQR was irradiated with UV A, UV B, and UV C lamps. The consumed and generated energy fluxes through endergonic and exergonic reactions driven by photolysis and photocatalysis were investigated. In addition, the variations in sludge dewatering/drying characteristics were also examined and compared with conventional methods to evaluate the energy requirements.     

A review of the day-ahead natural gas consumption in Denmark:starting point towards forecasting accuracy improvement

Natural gas consumption forecasting is crucial for transmission system operators,distribution system operators,traders,and other players in the market.This work...     

The effect of replacing fat with oat bran on fatty acid composition and physicochemical properties of meatballs

Oat bran was used as a fat substitute in the production of meatballs. The effect of oat bran addition on the fatty acid composition, trans fatty acids, total fat, some physicochemical and sensory properties of the samples was studied. Meatballs were produced with four different formulations; the addition of 5, 10, 15 and 20% oat bran. Control samples were formulated with 25% fat addition as in commercial production. The major fatty acids were cis-oleic, palmitic and stearic acid in all the meatball samples, those with oat bran added as well as the control. Meatballs containing oat bran had lower concentrations of total fat and total trans fatty acids than the control samples. Meatballs made with 20% oat bran had the highest protein, salt and ash contents, L value (lightness), b value (yellowness), and the lowest moisture content and a value (redness). There was no significant difference among the meatball samples with respect to sensory properties, and all samples had high acceptability.     

Refinement of some basic features of Zr surface-layered Bi-2223 superconductor with diffusion annealing temperature

This study aims to investigate the influences of diffusion annealing temperatures on structural, morphological, electrical, and superconducting features of Zr surface-layered Bi-2223 ceramics. The present study also covers an in-depth understanding of correlations between disorders and transition temperatures. The Zr diffusion is carried out via an annealing process between 650 and 840 °C. The observed results depict that the Zr ions can easily diffuse into the deeper level of Bi-ceramics and possible Zr/Bi substitution has occurred due to the driving force of high thermal energy. Besides, it is found that the Zr diffusion improves the general crystallinity quantities of Bi-2223 ceramic up to 800 °C annealing temperature. In addition, better intergranular couplings with a smoother plate-like structure are extensively observed in surface morphology for the samples annealed at 800 °C. Significant refinements of both basic electrical resistivity, hole carrier densities, and critical temperatures with narrow transitions are also obtained for the Zr surface-layered Bi-2223 ceramics after the 800 °C annealing process. The obtained improvements in critical fundamental features can be attributed to the optimum pairing mechanism, best crystal structure quality, ideal Cu–O₂ interlayer coupling strengths, and enhanced interaction between adjacent superconductive layers. Besides, the first-order derivative of electrical resistivity versus temperature graphs indicates that the best annealing temperature enables to triggers to stabilize the superconductivity in the homogeneous regions. It can be concluded that the Zr impurity diffusion at 800 °C is promising for the improvement in the basic features of Bi-2223 superconducting systems for future applications in superconductor technology.

     

Investigating the effect of production process of ball mill refiner on some physical quality parameters of compound chocolate: response surface methodology approach

Chocolate compound was produced using ball mill refiner, and the effect of agitator shaft speed and refining time on the physical quality parameters (particle size, colour and steady‐state rheology) of compound chocolate was determined using response surface methodology. The shaft speed and refining time range were selected between 40–60 r.p.m. and 10–30 min, respectively. Determination coefficient of the models established for particle size, Newtonian viscosity and colour parameters (brightness, chroma and hue angle) were found to be very close to unity. Increasing shaft speed and time induced a reduction in particle size and an increase in viscosity of the samples. Temperature sweep test was also performed, and the obtained data were successfully fitted to Arrhenius equation to calculate the corresponding parameters representing temperature dependency of the compounds. The results highlighted that the establishment of such models can provide essential information in terms of optimisation of production processes regarding usage purpose of the compound chocolate.     

The Correlation Between Statistically Downscaled Precipitation Data and Groundwater Level Records in North-Western Turkey

Downscaling of atmospheric climate parameters is a sophisticated tool to develop statistical relationships between large-scale atmospheric variables and local-scale meteorological variables. In this study, the variables selected from the National Centre for Environmental Prediction and National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data set were used as predictors for the downscaling of monthly precipitation in a watershed located in north-western Turkey where station records terminated two decades ago. An Artificial Neural Network (ANN) based approach was used to downscale global climate predictors that are positively correlated to the existing time frame of precipitation data in the basin. The downscaled precipitation information were used to extend the non-existing data from the meteorological station, which were later correlated with groundwater level data obtained from automatic pressure transducers that continuously record depth to groundwater. The results of the study showed that, among a large set of NCEP/NCAR parameters, surface precipitation data recorded at the meteorological station was strongly correlated with precipitation rate, air temperature and relative humidity at surface and air temperature at 850, 500, and 200 hPa pressure levels, and geopotential heights at 850 and 200 hPa pressure levels. The gaps in station data were then filled with the correlations obtained from NCEP/NCAR parameters and a complete precipitation data set was obtained that extended to current time line. This extended precipitation time series was later correlated with the existing groundwater level data from an alluvial plain in order to develop a general relationship that can be used in basin-wide water budget estimations. The proposed methodology is believed to serve the needs of engineers and basin planners who try to create a link between related hydrological variables under data-limited conditions.     

Effect of wastewater composition on archaeal population diversity

Distribution and occurrence of Archaea and methanogenic activity in a laboratory scale, completely mixed anaerobic reactor treating pharmaceutical wastewaters were investigated and associated with reactor performance. The reactor was initially seeded with anaerobic digester sludge from an alcohol distillery wastewater treatment plant and was subjected to a three step feeding strategy. The feeding procedure involved gradual transition from a glucose containing feed to a solvent stripped pharmaceutical wastewater and then raw pharmaceutical wastewater. During the start-up period, over 90% COD removal efficiency at an organic loading rate (OLR) of 6 kg COD m(-3)d(-1) was achieved with glucose feeding, and acetoclastic methanogenic activity was 336 ml CH4 gTVS(-1)d(-1). At the end of the primary loading, when the feed contained solvent stripped pharmaceutical wastewater at full composition, 71% soluble COD removal efficiency was obtained and acetoclastic methanogenic activity decreased to half of the rate under glucose feed (166 ml CH4 gTVS(-1)d(-1)). At the end of secondary loading with 60% (w/v) raw pharmaceutical wastewater, COD removal dropped to zero and acetoclastic methanogenic activity fell to less than 10 ml CH4 gTVS(-1)d(-1). Throughout the course of the experiment, microbial community structure was monitored by DGGE analysis of 16S rRNA gene fragments. Five different archaeal taxa were identified and the predominant archaeal sequences belonged to methanogenic Archaea. Two of these showed greatest sequence identity with Methanobacterium formicicum and Methanosaeta concilii. The types of Archaea present changed little in response to changing feed composition but the relative contribution of different organisms identified in the archaeal DGGE profiles did change.