Throughput accounting is concerned with a throughput measurement process to determine the efficiency of the company, to know the problems and obstacles it suffers from, to determine their causes and ways to address them.The research problem is represented by the following question: does the application of a throughput accounting lead to maximizing the company's profits? The aim of the research is to demonstrate the importance of throughput accounting, which is one of the tools of management accounting in providing an efficient information system that provides the company’s management with the information it needs to improve its production processes, increase a throughput, and thus maxi

The aim of the research is to identify the effect of instructional design according to Kagan structure among the first intermediate school student’s, and how skills could help in generating information in mathematics. In accordance with the research objectives, the researcher has followed the experimental research method by adopting an experimental design with two equivalent groups of post-test to measure skills in generating information. Accordingly, the researcher raised two main null hypotheses: there were no statistically significant differences at the level of significance (0.05) between the average scores of the experimental group who studied the material according to Kagan structure and th

The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.

This study aims to the little impact of accounting financial performance (AFP) analysis on the money market in the Iraqi economy. Potentially limiting future market activity could be international risks and obstacles, which in turn could cause issues and crises (Shah & Jan, 2014; Bakhtiyarovich, 2020)‏. The study concept was inspired by the recognition that there must be communication between the importance of the AFP analysis of the Iraqi securities market and the country’s financial and economic institutions. The sample of the study included ten Iraqi banks listed in the Iraq Stock Exchange (ISE) for the period 2010–2020. The three mathematical models included in the statistical analysis served as the basis for projectin

A simple setup of random number generator is proposed. The random number generation is based on the shot-noise fluctuations in a p-i-n photodiode. These fluctuations that are defined as shot noise are based on a stationary random process whose statistical properties reflect Poisson statistics associated with photon streams. It has its origin in the quantum nature of light and it is related to vacuum fluctuations. Two photodiodes were used and their shot noise fluctuations were subtracted. The difference was applied to a comparator to obtain the random sequence.

The study presents the performance of flexural strengthening of concrete members exposed to partially unbonded prestressing with a particular emphasis on the amount (0, 14.2, and 28.5%) of cut strands-symmetrical and asymmetrical damage. In addition to examining the influence of cut strands on the remaining capacity of post-tensioned unbonded members and the effectiveness of carbon fiber reinforced polymer laminates restoration, The investigated results on rectangular members subjected to a four-point static bending load based on the composition of the laminate affected the stress of the CFRP, the failure mode, and flexural strength and deflection are covered in this study. The experimental results revealed that the usage of CFRP la

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is