Rousing Vocabulary: A Pioneering Approach to Stimulate Learners to Acquire EFL

For English as a Foreign Language students, it might be challenging to acquire vocabulary in particular. To give students a hand overcoming possible vocabulary acquisition difficulties, this study aimed at addressing the term Rousing Vocabulary, identifying its features and specifying its types as well. To quickly and deeply get the essential information to answer the two research questions, a questionnaire was used as a data collection tool. To design the questionnaire, the researcher held two 5-member focus groups of Saudi university students and one 4-member focus group of specialists. The three groups were asked to specify the main potential features and types of Rousing Vocabulary. The items invented were assembled, constructed, and used for the required questionnaire. The survey's validity and reliability were taken into account while evaluating the questionnaire's accuracy and consistency. One main result revealed that all participants agreed with the impression of having such features of Rousing Vocabulary. Among 5 potential features reached, the participants have a stronger experience with “Words that learners enjoy hearing and saying” and “Words that arouse strong feelings and are highly expressive”. Another main result showed that the vast majority agreed with the impression of having potential types of Rousing Vocabulary. Among 5 potential types of Rousing Vocabulary reached, the participants thought that “Words that belong to an area of interest” and “Frequently used words” had a higher potential ability to help students acquire new words easily. Some interpretations were discussed, and based on the study's findings, several recommendations were made

A neural network based human identification framework using ear images

This paper presents a framework that uses ear images for human identification. The framework makes use of Principal Component Analysis (PCA) for ear image feature extraction and Multilayer Feed Forward Neural Network for classification. Framework are proposed to improve recognition accuracy of human identification. The framework was tested on an ear image database to evaluate its reliability and recognition accuracy. The experimental results showed that our framework achieved higher stable recognition accuracy and over-performed other existing methods. The recognition accuracy stability and computation time with respect to different image sizes and factors were investigated thoroughly as well in the experiments.<br /

How corporate governance and ownership affect banks’ risktaking in the MENA countries?.

[Abstract]: Purpose – The purpose of this paper is to explore the relationship between corporate governance and risk-taking behaviour of banks operating in the Middle East and North African (MENA) countries. Design/methodology/approach – In doing so, the authors use a data set covering 165 banks located in 13 MENA countries over the period 2005–2012 and apply dynamic panel data methodology. Findings – The results show that good governance acting in the interests of shareholders could lead to excessive risk taking; in this sense, a conflict of interest between the stakeholders, interested in the solvency of the financial system, and shareholders, trying to maximise their benefit, may occur. The greater risk can be reinforced by the governance of the country and a strong macro governance framework can incentivise a higher risk exposure in banks, showing the influence of bank regulation and law enforcement on the risks taken by banks. Originality/value – To the best of the authors’ knowledge, this is the first paper showing that corporate governance is relevant for explaining risk taking at the country and bank levels in MENA countries

Do Companies Adopt Big Data as Determinants of Sustainability: Evidence from Manufacturing Companies in Jordan

Information and communication technology make it easier for managers to gather customer data quickly and efficiently. However, managing, analysing, and utilizing the vast amount of data for sustainability decision are not easy. Therefore, this study aims to examine the readiness of manufacturing firms in adopting big data analytics in sustainable development. Moreover, this study employed the Partial Least Square Structural Equation Modelling (PLS-SEM) technique and analyses the data collected from 172 respondents working in different organizations in Amman and Jordan. The results reveal that there is a significant relationship between top management support and competitive pressures and intentions to adopt big data analytics. However, the moderating influence of perceived risk on the relationship between intention and actual use of big data has not been proved. The study provides fresh findings on determinants of intention to adopt big data analytics, actual use, and moderating role of perceived risk within the model to develop sustainability. Furthermore, the study has a number of theoretical and practical implications. Our main findings provide a deeper understanding of the enablers of BDA adoption through the development of a framework that includes direct and moderating constructs, as well as recommendations to practitioners on how to enhance BDA adoption based on eight BDA enablers

Factors affecting managers\u27 intention to adopt green supply chain management practices: evidence from manufacturing firms in Jordan

Global sustainability movement encourages companies to adopt and implement green supply chain management (GSCM) practices across the organization. Moreover, the integration of green practices into traditional supply chain is still to be a difficult task in manufacturing sector. However, empirical studies regarding the identification of influential factors affecting GSCM adoption among supply chain managers in manufacturing sector are under researched. This study assesses the factors affecting GSCM adoption in Jordan manufacturing firms. A well-structured questionnaire was administered for data collection. A valid 376 responses were collected from different manufacturing firms in Jordan. The data were analyzed, and the proposed model was validated using the structural equation modeling (SEM) approach. Results reveal that four factors, namely, supplier, environmental, customer, and cost factors significantly influence the intention to adopt GSCM among managers. The firm size had significantly moderated the relationship between market/financial and GSCM adoption, internal factor and GSCM adoption. The study will help the policymakers to understand the drivers of GSCM adoption among managers and assist them in implementing GSCM practices according to the size of the firm. This study is first of its kind to analyze the role of firm size as a moderator on the relationship between market/financial, supplier, governmental, environmental, internal, customers, cost factors, and GSCM in the context of Jordon

Royal Jelly Pretreatment Can Either Protect or Aggravate Brain Damage Induced by Hypoxia-Ischemia in Mice, Depending on its Dose

Royal jelly is a bee-derived product with potent antioxidative and many other biological properties. The present study was designed to examine the effect of Royal jelly (RJ) on brain damage induced by hypoxia-ischemia in mice. Mice were given RJ orally one dose / day (0-300 mg/kg body wt./ day for 13 consecutive days, survival time of mice were recorded following decapitation (Total brain ischemia model; model-1) and i. p. injection of NaNO2 to induce brain hypoxia (model-2)

Gobierno corporativo y desempeño de los bancos en los países de MENA

We analyze the effect of corporate governance on banks’ performance in the MENA countries using an index comprised of seven widely used governance measures, as a measure of firm-level corporate governance. In addition, we have also considered country governance as an important determinant of performance. The data at the firm level has been obtained from the Bankscope Database and we also hand-collect the corporate governance data from the annual reports over the period 2005-2012, covering the period of the financial crisis. At the country level we obtain the data from different sources. Our paper shows that corporate governance is relevant explaining performance in a way consistent with the segmentation of the corporate governance at both country level and bank level. It highlights the need for internal governance mechanisms but also the importance of country governance in emerging markets. The best governance at the country level has a positive effect under favorable conditions but not in crisis situationsAnalizamos el efecto del gobierno corporativo en el desempeño de los bancos en los países MENA utilizando un índice compuesto por siete medidas de gobierno ampliamente utilizadas, como una medida del gobierno corporativo a nivel de empresa. Además, también hemos considerado la gobernanza del país como un determinante importante del desempeño. Los datos a nivel de empresa se han obtenido de la base de datos de Bankscope y también recopilamos manualmente los datos de gobierno corporativo de los informes anuales durante el período 2005-2012, que cubren el período de la crisis financiera. A nivel de país obtenemos los datos de diferentes fuentes. Nuestro documento muestra que el gobierno corporativo es relevante para explicar el desempeño de una manera consistente con la segmentación del gobierno corporativo tanto a nivel nacional como bancario. Destaca la necesidad de mecanismos de gobernanza interna, pero también la importancia de la gobernanza nacional en los mercados emergentes. La mejor gobernanza a nivel de país tiene un efecto positivo en condiciones favorables, pero no en situaciones de crisi