This research amid to measure the impact of organizational flexibility (structural flexibility, operational flexibility, and strategic flexibility) in achieving organizational prosperity and its dimensions (strategic agility, intellectual capital, innovation and sustainable competitive advantage) in a number of Iraqi cellular communications companies. The research adopted descriptive analytical approach. A sample of (85) persons from the research community was selected, which included (Department managers, Directors administrative units, Communication engineers), to answer the questionnaire prepared for this purpose. And to analyze data and derive results. Statist

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.

To create a highly efficient photovoltaic-thermal (PV-T) system and maximise the energy and exergy efficiency, this study aims to propose an innovative configuration of a PV-T system comprising wavy tubes with twisted-tape inserts. Following the validation of a numerical model, a parametric study has been conducted to assess the geometrical effects of twisted tape and wavy tubes, as well as the coolant fluid type and velocity, on the overall performance of a PV-T system, located in Shiraz, Iran. It is found that employing twisted tape improves the energy and exergy efficiency by approx. 6.3%. The best configuration yields 12.4% and 16.8% increase in energy and exergy efficiency compared to conventional PV systems. This is achieved at 15% vo

Stereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi me

The study aimed to investigate the employment of electronic supervision applications in developing the teaching performance of teachers in Oman. Based on the qualitative method and the study population consisted of all the teachers of the first cycle in the Governorate of Muscat. The study sample amounted to 24 female teachers. The interview was used as a tool for data collection. The study reached several results, including: There are difficulties in employing electronic supervision applications, which are weak network, density of curricula, lack of experience in applying technology, and the large number of tasks assigned to the teacher. These difficulties can also be overcome by strengthening the network, training teachers, reducing th

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.

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

Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte