Self-efficacy expressed as people\'s faith about their ability to achieve a task or complete a level of performance that exercise influences over events that affect their lives. Self-efficacy plays a dynamic role in students\' lives and future. The diminution and development of self-efficacy will contribute towards their achievement in life. Self-efficacy in academics is an essential indicator of higher secondary level study success. Students with high academic self-efficacy will experience a better transition to the university at the end of their secondary education. This research aims to examine which factors relate to secondary school students’ self-efficacy in terms of being successful college students. Using a survey about student method, the questionnaire has been selected as a suitable data tool for research sample consisting of 434 students from 18 different colleges of nine different districts of Punjab province of Pakistan. Concerning male and female the comparison level of general self-efficacy, the results of the current investigation depict that, there is clear and noteworthy line concerning self-efficacy and gender differences of science students at the higher secondary school level, as male science learners feel confident about their final output as compared to female science students.

In this work, simple analytical solution of the diffusion equation is obtained under the boundary conditions which contain the deposition of pollutants on the ground surface. The vertical eddy diffusivity is assumed as power law of �z�, to be limited by an elevated mixing height. Also the decay time dependent is calculated. The resulting analytical formula is obtained by using power law, standard, and Brigg�s methods for estimating dispersion parameters. The proposed model has been compared with observed data from the research reactor at Inshas and Hanford experiment in unstable and stable conditions respectively.

This research aims to know the impact of technology, capacity optimization, the ability to keep the prize down, and the ease of access to raw materials on the competitive advantage of Small, Micro, and Medium Enterprises (SMEs) of milkfish processing in Demak Regency. Research samples are 125 business actors of Small, Micro, and Medium Enterprises (SMEs) of milkfish processing at five districts in Demak Regency. Data analysis uses SPSS program of version 22 which approach is Structural Equation Modelling (SEM). Research finding shows that the five proposed hypotheses are accepted. They are: 1) technology has significant effect on competitive advantage, 2) capacity optimization has significant effect on competitive advantage, 3) the ability to keep the price down has significant effect on competitive advantage, 4) the ease of access to raw materials has significant effect on competitive advantage, and 5) competitive advantage has significant effect on marketing performance. Competitive advantage plays a role as a mediator variable and it strengthens the correlation among technology, capacity optimization, the ability to keep the price down, and the ease of access to raw materials and marketing performance.

The objective of this study is to determine the prevalence and antibiotic resistance of Aeromonas spp. in spring, well and distribution waters in Van city and its province and to evaluate the Aeromonas spp. in terms of public health risks. For this purpose samples (n = 120) were collected from 19 natural springs, 10 wells and 91 public drinking water supply distribution systems. The membrane filter method was used for detection and counting of the bacteria. Several strains of Aeromonas spp. were isolated and identified. The antibiotic resistance of each strain was determined. Contamination was found in about 30% of the total number of samples studied. Three isolates of Aeromonas hydrophila (2.5%), two of Aeromonas sobria (1.6%), and thirty-one from Aeromonas caviae (25.8%) were found in all samples. The A. hydrophila isolates showed resistance to ceftazidime (66.6 %), cefotaxime, ampicilin and amoxicillin clavulanic acid (33.3 %). A. caviae was resistant to ampicilin (58.1 %), amoxicillin clavulanic acid (80.6 %), and ceftazidime (32.2 %) and A. sobria was resistant to amoxicillin clavulanic acid and ceftazidime (100 %), cefotaxime, ofloxacin, piperacillin and tetracycline(50 %). As a result these waters are not fit for consumption in terms of the Aeromonas spp. they contain and may be poses a potential public health hazard in terms of public health

Buses are one of key communication channel between function units and inside memory blocks of processors to deliver data or commands. Advancement, if the jobs are executed by multiprocessor systems, the bus management is very important and it is depended by the arbitration strategy. In this paper, we issued the methodology of bus traffic, fixed priority ambition, that based system-on-chip and to combine to two DLX processors both having 32-bit and to be emulated in ARM SoC (System-on-Chip) Designer simulation tools. For convenience control the traffic scheme among cores, we accomplished a fixed priority arbiter. Through the bus race experiment, we obviously obtained the follows result while the duty times are increasing, but the numbers of bus collusion are not obviously grown. The results are very valid while multi-cores designing.

Abstract\n Objective: The main objective of this study is to develop a robust, scalable, efficient classification algorithm for imbalanced data which is based on the classification of enzymes and lower approximation of subset and can handle large amount of data.It can also be used for preprocessing of imbalanced data.\n Methods and Analysis: Extrinsic or Data level and Intrinsic or algorithmic level solutions exists to tackle the problem of imbalanced training sets. The methodology adopted in this study is Data level solutions, it is those that try to resample and balance the dataset by increasing the artificial-instances in the smaller class by constructing new artificial samples, known as over sampling.This study proposes a new algorithm through construction of new samples using the synthetic minority oversampling technique hybridized with the application of a new algorithm called Enzyme-Computation which is an editing technique based on enzyme-classification and lower approximation of a subset. We show that any data can be classified by Enzyme-Computation algorithm similar to as enzymes are classified into 6 classes.\nFindings: The proposed algorithm called Enzyme-Computation has been experimentally evaluated with other preprocessing algorithms, validated and supported by comparative validation and shows good results. For comparative analysis we have taken 22 datasets from the UCI repository. The other algorithms chosen for comparison are: SMOTE, SMOTE-ENN, SMOTE-TomekLinks, Borderline-SMOTE1, Borderline-SMOTE2. We applied the hypothesis testing technique that provides support to the analysis of the results.We use different types of tests.For multiple comparisons; we use the Iman-Davenport test to detect statistical differences among a group of results.To show how good a method is with respect to its partners we consider the average ranking of the algorithms. The ranking of the Enzyme-Computation algorithms on each data-set selected for this study is also studied.In order to compare the results; we used a multiple comparison test to find the best preprocessing algorithm. We have observed that the best ranking is obtained by our proposal-Enzyme-Computation and the two last positions correspond to Borderline-Smote1 and Borderline-Smote2.\nApplication/Improvements:The novelty of this proposal is that the quality of the new synthetic instances is evaluated using Enzyme-Computation Algorithm .This evaluation allows us to include only those artificial instances that are within the lower approximation of the minority class.Further this algorithm can be enhanced based on new concepts developed for physico-chemical properties of Enzymes and its classification.

The thermodynamic properties of CaGeO3 perovskite alloy are investigated using the quasi-hormonic Debye model and the first principles calculation based on the density-functional-theory. The ranges of the pressure [0-12GPa] and the temperature [100-900K] are well selected to study this alloy in its orthorhombic structure. The temperature and pressure effects on the unit cell volume, Bulk modulus, heat capacities, Debye temperatures, thermal expansion coefficient and entropy are determined from the non-equilibrium Gibbs functions. The calculated results indicate that the CaGeO3 perovskite alloy exhibit a negative thermal expansion. The high Debye temperature and high Bulk modulus obtained allow classifying our compounds as hard material with the specificity to store the heat. Also the minimum entropy value obtained confirms that our material is highly ordered.