A novel data preprocessing method to estimate the air pollution (SO2): neighbor-based feature scaling (NBFS)

The forecasting of air pollution is important for living environment and public health. The prediction of SO₂ (sulfur dioxide), which is one of the indicators of air pollution, is a significant part of steps to be done in order to decrease the air pollution. In this study, a novel feature scaling method called neighbor-based feature scaling (NBFS) has been proposed and combined with artificial neural network (ANN) and adaptive network–based fuzzy inference system (ANFIS) prediction algorithms in order to predict the SO₂ concentration value is from air quality metrics belonging to Konya province in Turkey. This work consists of two stages. In the first stage, SO₂ concentration dataset has been scaled using neighbor-based feature scaling. In the second stage, ANN and ANFIS prediction algorithms have been used to forecast the SO₂ value of scaled SO₂ concentration dataset. SO₂ concentration dataset was obtained from Air Quality Statistics database of Turkish Statistical Institute. To constitute dataset, the mean values belonging to seasons of winter period have been used with the aim of watching the air pollution changes between dates of December, 1, 2003 and December, 30, 2005. In order to evaluate the performance of the proposed method, the performance measures including mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and IA (Index of Agreement) values have been used. After NBFS method applied to SO₂ concentration dataset, the obtained RMSE and IA values are 83.87–0.27 (IA) and 93–0.33 (IA) using ANN and ANFIS, respectively. Without NBFS, the obtained RMSE and IA values are 85.31–0.25 (IA) and 117.71–0.29 (IA) using ANN and ANFIS, respectively. The obtained results have demonstrated that the proposed feature scaling method has been obtained very promising results in the prediction of SO₂ concentration values.     

Resource Leveling in Line‐of‐Balance Scheduling

Resource leveling involves minimizing resource fluctuations without changing the completion time of a project. A smooth distribution of resources minimizes logistical problems and results in cost savings. Line‐of‐balance (LOB) is a resource‐based scheduling system that is used in projects that exhibit repetitive characteristics, performs resource allocation as a matter of course, but does not deal with resource leveling. In the past, researchers experienced declines in productivity whenever they leveled resources in different linear scheduling models by adjusting activities’ production rates. The objective of this research is to develop a genetic algorithm‐based resource leveling model for LOB schedules that does not impact productivity negatively. This model is based on the “natural rhythm” principle, according to which a crew of optimum size will be able to complete an activity in the most productive way. The “natural rhythm” principle allows shifting the start time of an activity at different units by adjusting the number of crews without changing the duration of the activity in any one unit and without violating the precedence relationships between activities. An LOB schedule is established for a pipeline project and is used to illustrate the proposed resource leveling model. It was observed that the model provides a smoother resource utilization histogram. Performing resource leveling in LOB scheduling without sacrificing productivity is the major contribution of the proposed model.     

Capability of the rosemary (Rosmarinus officinalis) extract on the oxidative stability of cooked sea bream (Sparus aurata) during frozen storage

The effects of rosemary extract addition on oxidative stability of cooked sea bream during frozen storage period were investigated. Sea bream fillets were fried, oven baked and grilled. Three groups with rosemary extract were also cooked by the same methods and cooked samples (with and without rosemary extract) were stored in ?18?°C for 4?months. After cooking procedures, the FFA formation was quite similar in fresh-raw and fried sea bream fillets, but significantly increased oven baked (0.31?C0.33% oleic acid) and grilled fillets (0.39?C0.40% oleic acid). The highest value of PV was also obtained from grilled fillets (1.18?C1.58?meq/kg). However, TBA values (1.92?mg MA/kg for fresh-raw fillet) did not increase in sea bream fillets after the frying and grilling procedure except oven baking without rosemary extract (2.41?mg MA/kg). A considerable increase in the FFA, PV and TBA was observed in all cooked groups during frozen storage period. The treated samples with rosemary extract generally showed slower PV and TBA formation than those of the untreated samples. However, the additions of rosemary extract have positive effect on sensory quality of baked sea bream.     

Preparation and characterization of new window material CdS thin films at low substrate temperature (<300 K) with vacuum deposition

Low-temperature vacuum deposition instead of the commonly used vacuum deposition at high substrate temperatures has been applied to prepare new window material CdS thin films. The structural, optical and electrical properties of vacuum-evaporated CdS thin films were investigated as a function of substrate temperature (100–300 K) and the post-deposition annealing temperature (at 473, 573 and 673 K). It was determined that films deposited at all substrate temperatures were polycrystalline in nature with hexagonal structure and a strong (0 0 2) texture. The AFM and SEM studies showed that the microstructures of the as-deposited films agreed with the expectations from structure zone model. X-ray diffraction studies showed that the crystallinity of the CdS films was improved on annealing. Optical spectroscopy results of the films indicated that the optical band gap value increased from 2.40 to 2.42 eV with decreased substrate temperature. Increasing the annealing temperature sharpened the band edge. The dark resistivity increased from 4.5×10³ to 7.3×10³ Ω cm and the carrier concentration decreased from 4.7×10¹⁷ to 3.5×10¹⁵ cm⁻³ as the substrate temperature decreased from 300 to 100 K.     

Effect of tempering temperature and microstructure on the corrosion behavior of a tempered steel

In this study, a tempered martensitic matrix was obtained in a low carbon steel, by applying austenization, quenching and tempering heat treatments. After austenization at 1000°C for 30 minutes, steel samples were quenched in water and then tempered at 200, 540 and 600°C for 30 minutes. Hardness measurements were done and then immersion tests were carried out in a 3.5 wt % NaCl solution for periods ranging between 1–7 days. Weight losses of the samples were determined after each immersion period and microstructural studies were performed on the corroded surfaces. Corrosion rates were calculated using weight loss data and verified by potentiodynamic tests. Results revealed that corrosion behavior of the experimental steels was directly affected by tempering temperature, hardness and microstructure.     

The determination of interface state energy distribution of the H-terminated Zn/p-type Si Schottky diodes with high series resistance by the admittance spectroscopy

Analysis of Zn/p-Si Schottky diodes (SDs) with high resistivity has been given by admittance spectroscopy. The importance of the series resistance in the determination of energy distribution of interface states and especially their relaxation time in the SDs with high resistivity has been considered. The effect of the series resistance on capacitance-conductance/frequency characteristics has been given by comparing experimental data with theoretical data. The interface state density N_ss from the admittance spectroscopy ranges from 1.0×10¹² cm⁻² eV⁻¹ in 0.720-E_v eV to 2.03×10¹² cm⁻² eV⁻¹ in 0.420-E_v eV. Furthermore, the relaxation time ranges from 4.20×10⁻⁵ s in (0.420-E_v) eV to 3.20×10⁻⁴ s in (0.720-E_v) eV. It has been seen that the interface state density has a very small distribution range (1.0-2.03×10¹² cm⁻² eV⁻¹) that is ascribed to the predominant termination with hydrogen of the silicon surface after HF treatment.