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This research aims to examine the macro determinants that significantly affect financial development in the Middle East and North Africa (MENA) region, which could be used furtherly to play a major role in economic sustainability since one of the major driving forces for economic development is the financial development.

The significant determinants of financial development should be efficiently used by the MENA region countries for creating huge financial sector development and innovation, stimulating economic development in turn and leading to the completion of the cycle of development and sustainability. To achieve this study's objective, the researcher employed a quantitative method to develop an econometric model.

This model consisted of two Panel EGLS Cross-Section Random Effects Models (REMs) in which Domestic credit to the private sector as a percentage of GDP (?PCGDP?_it) and stock market capitalization ratio (?SMC?_it) were taken as the dependent variables. In addition, the independent variables included the corruption perception index, financial freedom (FF), political stability (PS) and trade openness (TO). The researcher extracted the data for the analysis from different databases including the World Bank, the Organization for Economic Cooperation and Development and the International Monetary Fund. Throughout the first – Panel EGLS Cross-Section Random Effects Model, it turned out that, while FF, TO and corruption index had a positive relationship with ?PCGDP?_it, PS had an adverse effect on ?PCGDP?_it. The second – Panel EGLS Cross-Section Random Effects Model showed that, while PS and TO had a positive effect on stock market performance, the corruption index and FF had an adverse effect on stock market performance.

Throughout the first – Panel EGLS Cross-Section Random Effects Model, it turned out that, while FF, TO and corruption index had a positive relationship with ?PCGDP?_it, PS had an adverse effect on ?PCGDP?_it. The second – Panel EGLS Cross-Section Random Effects Model showed that, while PS and TO had a positive effect on stock market performance, the corruption index and FF had an adverse effect on stock market performance.

Adopting the split complementizer phrase (CP) hypothesis, the paper aims at providing an account for object cliticization in Standard Arabic (SA) as an instance of object displacement. Kayne's proposal on cliticization is adopted here to account for the type of displacement in SA that objects clitics in SA, like full determiner phrases (DPs), obligatorily move from their base position as independent complements of the verb to the specifier of Foc first before attaching to the verb under the tense node.

This research adopts a qualitative interpretive research design (Creswell, 2007, 2010). The majority of the samples chosen for the study involve dependent pronominal objects obligatorily attached to the verb. The samples were judged to be grammatical based on the author's judgment as an native speaker of Arabic. Moreover, all the examples were checked for grammaticality by two full professors of Arabic grammar who are native speakers.

The analysis proposed that, like lexical DP's, pronominal objects originate as separate maximal projection (XP) constituents and move from their base position as verbal complements to the focus position [Spec, Foc]. In other words, both are able to move out of VP, targeting the same specifier position of a functional projection. This movement is focus-driven, that is, triggered by the edge feature on Foc. Pronominal objects at a later phase crucially higher than V0 (possibly in phonetic form (PF)) get cliticized to the verb which has adjoined to T.

Unlike displaced lexical DP objects in SA syntax, displaced pronominal objects, however, have received less critical attention especially within Rizzi's (1997, 2004) left periphery theory and, therefore, some areas of these constructions remain poorly understood.

The purpose of this paper is to solve the problem of tuning of EKF parameters (process and measurement noise co-variance matrices) designed for attitude estimation using Global Positioning System (GPS) aided inertial sensors by employing a Human Opinion Dynamics (HOD)-based optimization technique and modifying the technique using maximum likelihood estimators and study its performance as compared to Particle Swarm Optimization (PSO) and manual tuning.

A model for the determination of attitude of flight vehicles using inertial sensors and GPS measurement is designed and experiments are carried out to collect raw sensor and reference data. An HOD-based model is utilized to estimate the optimized process and measurement noise co-variance matrix. Added to it, few modifications are proposed in the HOD model by utilizing maximum likelihood estimator and finally the results obtained by the proposed schemes analysed.

Analysis of the results shows that utilization of evolutionary algorithms for tuning is a significant improvement over manual tuning and both HOD and PSO-based methods are able to achieve the same level of accuracy. However, the HOD methods show better convergence and is easier to implement in terms of tuning parameters. Also, utilization of maximum likelihood estimator shows better search during initial iterations which increases the robustness of the algorithm.

The paper is unique in its sense that it utilizes a HOD-based model to solve tuning problem of EKF for attitude estimation.