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The purpose of this paper is to describe a framework for enhancing organizational productivity and capacity building at the national, industry-wide level that is based on an active collaboration between elements of the industry that the authors will refer to as the organization and the educational system that trains/educates the human resources that play a vital role in enabling the organization to acquire and then maintain the competitive advantage needed to be successful.

This framework is based on the concept of competencies of the human resource and a competence-based model for recruiting and developing these human resources. This framework has been successfully applied by the Kemt Enterprise Training Partnership (ETP)/Technical and Vocational Education and Training (TVET-Egypt) project in the Egyptian papermaking industry to solidify an understanding of the required competencies in this sector. For the purposes, the term competency will be defined as a set of skills, knowledge and behavior that allows employees to do their jobs effectively and efficiently without interfering with either other tasks or tasks they will encounter in the future.

Organizational productivity will be assumed to be related to having a workforce that is both competent and of the appropriate size, and can be determined using an organizational function map coupled to the development of a set of related occupational standards.

The paper proposed a national framework competence-based model which collaborates all the national efforts to enhance the national competitiveness.

This paper aims to use quick response (QR) code along with online videos to teach one of the college foundation courses in an international institution to enhance the grasp of the students and to boost the students’ learning outcomes.

The study discussed and elaborated the findings that mainly focused on the usage of the online resources to teach Engineering Economy course. Besides, the authors analyzed how the gender may have different feedback for the student.

The study emphasized on the expectations of the students to use videos in the learning experience that preferred to be developed by course educator and to be published on the university platform, like blackboard or faculty website, that conforms university transformation vision undergoing nowadays. It is recommended to have a successful learning experience; it is the educator's responsibility to improve the personal digitization skills that would be used in the e-learning implementations, that will be used for the educational technology, which requires the use of creative media production mobile applications.

The education field has witnessed significant development over the past years in terms of using digital technologies as pedagogical tools to enhance the students’ learning experience especially the internet, where the traditional trends become outdated to be used in the classrooms. One of the main players in this field is videos that are considered as the main influencer to this educational change, where it has been demonstrated to and boost the quality of the learning experience.

In this study, students participated to explore the usefulness of using online learning through using videos blended with QR code to enhance the students’ performance in understanding one of the undergraduate foundation courses in the college of engineering, namely, engineering economy. A survey was distributed to students after the core material of the course was covered. The collected responses were then studied and analyzed.

The purpose of this research is to study the physical and mechanical properties beside the durability of concrete as well as corrosion resistance of reinforced concrete by replacing Ordinary Portland cement (OPC) with different ratios of silica fume and meta-kaolin and applying two paint formulations to enhance corrosion resistance and mechanical properties. In this work, modified concrete mixes containing pozzolanic materials of industrial wastes such as silica fume (SF) with ratios ranging between (0, 10 and 15%) and calcined raw material such as meta-kaolin (MK) with ratios (0, 3, 5 and 10%), were introduced using water binder ratio (w/b) 0.45 to study their effect on the physico-mechanical properties and durability of concrete as well as corrosion protection performance of reinforced concrete. Two paint formulations containing the same ingredients except that one of them is free from talc (G1) and the other contains talc (G2) were applied on the rebars embedded in these modified mixes. Talc is known to offer high pH to the surrounding media.

Modified concrete mixes containing the coated reinforced concrete steel with the different paint formulations in presence and absence of talc were tested, and the corrosion behavior was studied using electrochemical impedance spectroscopy (EIS) in 3.5% NaCl, and the concrete mixes were also tested through their compressive strength, chloride permeability, scanning electron microscope/energy dispersive X-ray analysis and bond strength.

The results revealed that the hardened reinforced concrete mix containing 10% SF with 5% MK with embedded rebars coated with G2 (paint containing talc) was the best concrete system which offers concrete sustainability besides high corrosion protection performance, i.e. presence of talc in the paints combined with the effect of cement blended with SF and MK showed positive effect on the reinforced concrete properties that leads to more durability and workability.

The integrity of using two efficient methods of corrosion protection beside the effect of the different replacements in concrete mixes containing coated reinforced concrete steel with paint formulations free from talc (G1) and others containing talc (G2), which lead to fatal changes in the pH of the surrounding media (i.e. concrete which has high alkaline pH) to achieve good concrete properties aside with convenient paint formulations together.

This study aims to evaluate the effect of pH on the reinforced concrete steel protection for rebars coated with paint formulations containing talc and free from it. As the presence of talc in paints can offer high pH which cordially affects the protection behavior of the coated rebars. Additionally, this study includes evaluating the durability of concrete mixes in presence of some replacements of ordinary cement such as meta-kaolin (MK) and ground granulated blast furnace slag (GGBFS).

Two paint formulations were prepared containing the same ingredients except that (P1) is free from talc and (P2) contains talc. The anticorrosive behavior of painted steel in the blended concrete mixes containing MK and GGBFS was studied by using different electrochemical techniques in chloride solution. The concrete durability was evaluated by the means of compressive and bond strength beside chloride permeability. Different concrete mixes containing mineral groups or pozzolanic materials were prepared by replacing (10, and 30%) GGBFS and (5, 10 and 15%) MK as binary from cement CEM I with (w/b) 0.45 with superplasticizer ratio (SP) 2% of the binder

It was found that the presence of talc, in spite of its ability to offer high pH, has affected positively the corrosion behavior of reinforced concrete steel by forming a complex with concrete even if it is present in paint formulation and not free in the medium.

The results revealed that concrete blended with (30% GGBFS and 10% MK) with coated rebars with P2 containing talc showed the highest corrosion protection performance in addition to modified permeability and compression resistance.

This paper aims to present a critical appraisal of Ghassan Kanafani’s short story “The Child Goes to the Camp” using the Appraisal Theory proposed by Martin and Rose (2007) in an attempt to investigate the predicament of the Palestinians who were forced to flee their country and live in refugee camps as well as the various effects refugee life had on them.

Using the Appraisal Theory, and with a special focus on the categories of Attitude and Graduation, the paper aims to shed light on the plight of refugees through revealing the narrator’s suffering in a refugee camp where the most important virtue becomes remaining alive.

Analysing the story using the Appraisal Theory reveals the impact refugee life has left on the narrator and his family. This story serves as a warning for the world of the suffering refugees have to endure when they are forced to flee their war-torn countries.

Although Kanafani’ resistance literature has been studied extensively, his short stories have not received much scholarly attention. In addition, his works have not been subject to linguistic analysis. This study presents an appraisal analysis of Kanafani’s “The Child Goes to the Camp” in an attempt to investigate how the author’s linguistic choices are key to highlighting the suffering of the Palestinians, especially children, in refugee camps.

The purpose of this paper is to examine the effect of knowledge management capabilities (KMCs) on organizational learning (OL) and supply chain management practices (SCMPs). In addition, to study the effect of OL, KMC and supply chain management on organizational performance (OP).

To study the relationships between KMC, OL, SCMP and OP, different techniques such as factor analysis, correlation analysis and structural equation modeling were used to verify the validity of the proposed conceptual model, and to test the suggested hypotheses, data collected from 165 companies in the Saudi food industry (representing a response rate of 64.9 per cent) were used.

According to the study’s findings, SCMP and OL are positively affected by KMC. Moreover, OP is directly affected by KMC, OL and SCMP.

Owing to the specific nature of the sample, the findings of the current research are applicable only to the food industry.

The current research introduced a conceptual model, which has been tested and verified in the Saudi food industry. The findings recommend that both KMC and OL as well as SCMP will contribute to improving the OP. In addition, KMC will improve the SCMP and OL.

Cracks are prevalent signs of pavement distress found on highways globally. The use of artificial intelligence (AI) and deep learning (DL) for crack detection is increasingly considered as an optimal solution. Consequently, this paper introduces a novel, fully connected, optimised convolutional neural network (CNN) model using feature selection algorithms for the purpose of detecting cracks in highway pavements.

To enhance the accuracy of the CNN model for crack detection, the authors employed a fully connected deep learning layers CNN model along with several optimisation techniques. Specifically, three optimisation algorithms, namely adaptive moment estimation (ADAM), stochastic gradient descent with momentum (SGDM), and RMSProp, were utilised to fine-tune the CNN model and enhance its overall performance. Subsequently, the authors implemented eight feature selection algorithms to further improve the accuracy of the optimised CNN model. These feature selection techniques were thoughtfully selected and systematically applied to identify the most relevant features contributing to crack detection in the given dataset. Finally, the authors subjected the proposed model to testing against seven pre-trained models.

The study's results show that the accuracy of the three optimisers (ADAM, SGDM, and RMSProp) with the five deep learning layers model is 97.4%, 98.2%, and 96.09%, respectively. Following this, eight feature selection algorithms were applied to the five deep learning layers to enhance accuracy, with particle swarm optimisation (PSO) achieving the highest F-score at 98.72. The model was then compared with other pre-trained models and exhibited the highest performance.

With an achieved precision of 98.19% and F-score of 98.72% using PSO, the developed model is highly accurate and effective in detecting and evaluating the condition of cracks in pavements. As a result, the model has the potential to significantly reduce the effort required for crack detection and evaluation.

The proposed method for enhancing CNN model accuracy in crack detection stands out for its unique combination of optimisation algorithms (ADAM, SGDM, and RMSProp) with systematic application of multiple feature selection techniques to identify relevant crack detection features and comparing results with existing pre-trained models.

The purpose of this study is to explore the information-seeking behavior of Egyptian physicians serving in COVID-19 isolation hospitals.

A sample of 91 physicians serving in Egyptian isolation hospitals answered the study questionnaire.

Demographically, more than half of respondents were males. Over one-third of them are holding Doctor of Medicine (M.D), followed by one-third holding Master of Medicine (MMed). Respondents' age ranged from 30 to 60 years. Internal medicine is the most common specialty, accounting for nearly half of all physicians, followed by chest medicine and intensive care medicine. The information-seeking behavior of these three groups in their regular work is believed to be different, but since all of the participants are working in COVID-19 isolation hospitals, they should have the same information resources, Internet access and the same needs relevant to COVID-19 in order to make accurate clinical decisions. The physicians used traditional and electronic information sources to fulfill their information needs, the most important of which were to make a specific research, find an answer to a specific case, and deliver a medical lecture. Colleagues, coworkers, nurses and pharmacists were the most important channels pursued by Egyptian physicians to obtain information.

This study is the first study that focuses on investigating the information-seeking behavior of Egyptian physicians serving in isolation hospitals. Any findings resulted from this study may serve as a noteworthy reference that may be useful to the Egyptian health sector, experts, researchers, as well as policymakers in establishing strategic decisions for making the understating much better.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2020-0350

Studying the shear stress and pressure resulting on the walls of blood vessels, especially during high-pressure cases, which may lead to the explosion or rupture of these vessels, can also lead to the death of many patients. Therefore, it was necessary to try to control the shear and normal stresses on these veins through nanoparticles in the presence of some external forces, such as exposure to some electromagnetic shocks, to reduce the risk of high pressure and stress on those blood vessels. This study aims to examines the shear and normal stresses of electroosmotic-magnetized Sutterby Buongiorno’s nanofluid in a symmetric peristaltic channel with a moderate Reynolds number and curvature. The production of thermal radiation is also considered. Sutterby nanofluids equations of motion, energy equation, nanoparticles concentration, induced magnetic field and electric potential are calculated without approximation using small and long wavelengths with moderate Reynolds numbers.

The Adomian decomposition method solves the nonlinear partial differential equations with related boundary conditions. Graphs and tables show flow features and biophysical factors like shear and normal stresses.

This study found that when curvature and a moderate Reynolds number are present, the non-Newtonian Sutterby fluid raises shear stress across all domains due to velocity decay, resulting in high shear stress. Additionally, modest mobility increases shear stress across all channel domains. The Sutterby parameter causes fluid motion resistance, which results in low energy generation and a decrease in the temperature distribution.

Equations of motion, energy equation, nanoparticle concentration, induced magnetic field and electric potential for Sutterby nano-fluids are obtained without any approximation i.e. the authors take small and long wavelengths and also moderate Reynolds numbers.