Syed Masiur Rahman

Saudization (Localization) – A critical review

Abstract This paper introduces the concept of Saudization and critically reviews its existing and potential impacts and consequences. It identifies that Saudization has positively contributed to reducing the overall percentage of foreign labor. However, there have been some difficulties, such as a decline in competitiveness among regional business companies with respect to a business friendly environment, and reduced direct foreign investment, which influenced the reduction of the tax on foreign investors. Saudization should place importance on skill development among Saudi nationals by strengthening educational and vocational training, and providing time-specific incentives, rather than relying only on a quota system. Saudization should be implemented more through market forces and incentives. Collecting comprehensive information on the nature and magnitude of Saudi unemployment could be a first step in developing appropriate Saudization policies. This paper suggests appropriate coordination and consultation between the government, the private sector and the public at large, so that any policies on Saudization become more easily acceptable and executable in both the public and private sector.

Review of the Fuzzy Logic Based Approach in Traffic Signal Control : Prospects in Saudi Arabia

Abstract The first implementation of fuzzy logic controller in the literature appeared in 1977, which shows better performance compared to vehicle actuated controller for a very simplified intersection having two one-way streets based on a simple green time extension principle. After that, further development is taking place by adopting fuzzy logic based traffic signal control for two-way single intersection without turning vehicles, single intersection with all possible movements, multiple intersections, phase sequence and time determination, congested intersection and network, etc. Research in fuzzy logic based traffic signal control is getting inspired by the results which indicate better performance compared to traditional traffic signal controls, specifically during heavy and uneven traffic volume conditions. It can be expected that the fuzzy logic approach will not only contribute in the advancement of adaptive traffic signal control but will also contribute significantly in the future approach of transportation management system (TMS) by improving the performance of the adaptive controller and the overall decision making process of the TMS. However, there are only a few examples of this kind of traffic signal control or TMS in real life. Researchers in rapidly developing countries like Saudi Arabia should investigate the potential of the fuzzy logic based traffic signal control or TMS under the unique local conditions to curb the loss incurred due to congestion.

A communicative planning approach to combat graduate unemployment in Saudi Arabia

Abstract This paper introduces and critically reviews the Saudi education and unemployment situation. It sets out the specialized nature of issues regarding education and unemployment which are seldom found in other countries. The governmental efforts and subsequent results in the employment sectors are investigated to illustrate the reasons behind prevailing and expected future graduate unemployment. In addition, this paper proposes the application of a combination of a rational planning model and the concept of communicative rationality in solving the problem of graduate unemployment in Saudi Arabia. It asserts the need for comprehensive data on the nature and magnitude of unemployment, and adequate consultation with all the stakeholders including the private sector. A brief survey conducted among the graduates of King Fahd University of Petroleum & Minerals (KFUPM) reveals that, while they are competent and easily absorbed into the market, the scenario is not the same for other educational institutions. Similar studies for other educational institutions will facilitate an understanding of the extent of coordination with the job market. A study is being conducted to enhance the creation of a link between the market demand for educational programs and programs offered by educational institutes.

The role of the private sector towards Saudisation (localisation)

This paper introduces the concept of Saudisation and briefly reviews its existing and potential impacts and consequences. The Saudi Government embarked on the Saudisation of the workforce as a strategic objective to nationalise the workforce and tackle the problem of unemployment among the nationals. The governmental policy seeks to force the private sector to hire more Saudis, to establish a priority for hiring the domestic workforce without relying on market forces and incentives. This paper emphasises on the extent of participation of the private sector and the fundamental reasons which are contributing in the unwillingness to actively participate in the Saudisation programme. It also investigates the measures which might help increasing the participation of the private sector. This paper recommends adopting a participatory approach in policy-making process regarding Saudisation where the private sector can participate actively with other counterparts.

The Rationale for SEA to Overcome the Inadequacy of Environmental Assessment in Bangladesh

The first remarkable environmental initiatives in Bangladesh were taken because of the Stockholm Conference on Human Environment in 1972. The provision that requires Environmental Impact Assessment (EIA) for any new public and private project was first incorporated in the National Environmental Policy, 1992. Still environmental degradation is one of the major concerns in Bangladesh. Like some other developing countries, it initiates and conducts EIA in order to satisfy international donor agencies. Now, EIA is becoming matured through the positive steps of government, non-governmental organizations (NGOs) and international agencies. However, EIA cannot adequately address all the prevailing environmental issues in Bangladesh because of its inherent and contextual limitations. This article explores the evolution of environmental assessment in Bangladesh, mostly at the strategic level. It investigates some of the policy failures, which resulted due to the absence of environmental assessment at the strategic level. Through a questionnaire survey (e-mail) and extensive literature review, this research concludes that Strategic Environmental Assessment (SEA) as a process can effectively address the limitations of EIA and contribute to policy development in order to ensure sustainable development.

Prediction of non-hydrocarbon gas components in separator by using Hybrid Computational Intelligence models

AbstractAccurate prediction of non-hydrocarbon (Non-HC) gas components in the gas-oil separators reduces the cost of gas and oil production in petroleum engineering. However, this task is difficult because there is no known relation among the properties of crude oil and the separators. There are studies that attempt to predict hydrocarbons (HCs) components using either Computational Intelligence (CI) techniques or conventional techniques like Equitation-of-State (EOS) and Empirical Correlation (EC). In this paper, we explore the applicability of CI techniques such as Artificial Neural Network, Support Vector Regressions, and Adaptive Neuro-Fuzzy Inference System to predict the Non-HC gas components in gas-oil separator tank. Further, we incorporate Genetic Algorithms (GA) into the Hybrid Computational Intelligence (HCI) models to enhance the accuracy of prediction. GA is used to determine the most favorable values of the tuning parameters in the CI models. The performances of the CI and HCI models are compared with the performance of the conventional techniques like EOS and EC. The experimental results show that accuracy of prediction by CI and HCI models outperform the conventional methods for N2 and H2S gas components. Furthermore, the HCI models perform better than the non-optimized CI models while predicting the Non-HC gas components.

Dynamics of energy sector and GHG emissions in Saudi Arabia

The energy sector is the main contributor to GHG emissions in Saudi Arabia. The tremendous growth of GHG emissions poses serious challenges for the Kingdom in terms of their reduction targets, and also the mitigation of the associated climate changes. The rising trend of population and urbanization affects the energy demand, which results in a faster rate of increase in GHG emissions. The major energy sector sources that contribute to GHG emissions include the electricity generation, road transport, desalination plants, petroleum refining, petrochemical, cement, iron and steel, and fertilizer industries. In recent years, the energy sector has become the major source, accounting for more than 90% of national CO2 emissions. Although a substantial amount of research has been conducted on renewable energy resources, a sustainable shift from petroleum resources is yet to be achieved. Public awareness, access to energy-efficient technology, and the development and implementation of a legislative framework, energy pricing policies, and renewable and alternative energy policies are not mature enough to ensure a significant reduction in GHG emissions from the energy sector. An innovative and integrated solution that best serves the Kingdoms long-term needs and exploits potential indigenous, renewable, and alternative energy resources while maintaining its sustainable development stride is essential. Policy relevance The main contributor to GHG emissions in Saudi Arabia is the energy sector that accounts for more than 90% of the national CO2 emissions. Tremendous growth of GHG emissions poses serious challenges for the Kingdom in their reduction and mitigating the associated climate changes. This study examines the changing patterns of different activities associated with energy sector, the pertinent challenges, and the opportunities that promise reduction of GHG emissions while providing national energy and economic security. The importance of achieving timely, sustained, and increasing reductions in GHG emissions means that a combination of policies may be needed. This study points to the long-term importance of making near- and medium-term policy choices on a well-informed, strategic basis. This analytical paper is expected to provide useful information to the national policy makers and other decision makers. It may also contribute to the GHG emission inventories and the climate change negotiations.

Application of Support Vector Machine Modeling on Phase Distribution in the Riser of an LSCFB Reactor

Abstract Support vector machine (SVM) modeling approach is applied to predict the solids holdups distribution of a liquid–solid circulating fluidized bed (LSCFB) riser. The SVM model is developed/trained using experimental data collected from a pilot-scale LSCFB reactor. Two different size glass bead particles (500 μm (GB-500) and 1,290 μm (GB-1290)) are used as solid phase, and water is used as liquid phase. The trained model successfully predicted the experimental solids holdups of the LSCFB riser under different operating parameters. It is observed that the model predicted cross-sectional average of solids holdups in the axial directions and radial flow structure are well agreement with the experimental values. The goodness of the model prediction is verified by using different statistical performance indicators. For the both sizes of particles, the mean absolute error is found to be less than 5%. The correlation coefficients (0.998 for GB-500 and 0.994 for GB-1290) also show favorable indications of the suitability of SVM approach in predicting the solids holdup of the LSCFB system.

Apparent kinetics of nonisothermal high temperature oxidative degradation of ethylene homopolymers: effects of residual catalyst surface chemistry and structure

The effects of two supported residual catalysts—one Ziegler-Natta and another metallocene—on the nonisothermal thermooxidative degradation of the resulting ethylene homopolymers were investigated using TGA experiments and kinetic modeling. The rigorous constitutive kinetic model (developed in this study), unlike the analytical Horowitz and Metzger model, fitted very well to the entire TGA curve, without distribution of activation energy Ea, for n (overall degradation order) = 1 for both polymers. Neither n nor Ea varied as a function of fractional weight loss of the polymer. Hence, the proposed unified molecular level concept of surface chemistry and structure of the residual catalysts held all through the degradation process. The above feature of n and Ea also indicates the suitability of the model formulation and the effectiveness of the parameter-estimation algorithm. Random polymer chain scission, with the cleavage of the −C−C− and the −O−O− (hydroperoxide) bonds, prevailed. The types of residual catalyst surface chemistry and structure varied the bond cleavage process. The metallocene Zr residual catalyst caused more thermooxidative degradation in MetCat HomoPE than what the Ti one did in Z-N HomoPE. The rigorous constitutive model-predicted apparent kinetic energy Ea, and frequency factor Z also support this finding. The proposed degradation mechanism suggests that the Zr residual catalyst more (i) decreased the activation energy required to decompose the −C−C− and the −O−O− bonds, and (ii) eliminated β-hydrogen (by the carbonyl functionalities) from the polymer chains. These findings were attributed to the differences in surface chemistry and structure of the residual catalysts. Therefore, the current study presents a rigorous constitutive kinetic model that duly illustrates the influence of the characteristic surface chemistry and structure of the residual catalysts on the high temperature oxidative degradation of polyethylenes.

Ozone levels in the Empty Quarter of Saudi Arabia--application of adaptive neuro-fuzzy model.

In arid regions, primary pollutants may contribute to the increase of ozone levels and cause negative effects on biotic health. This study investigates the use of adaptive neuro-fuzzy inference system (ANFIS) for ozone prediction. The initial fuzzy inference system is developed by using fuzzy C-means (FCM) and subtractive clustering (SC) algorithms, which determines the important rules, increases generalization capability of the fuzzy inference system, reduces computational needs, and ensures speedy model development. The study area is located in the Empty Quarter of Saudi Arabia, which is considered as a source of huge potential for oil and gas field development. The developed clustering algorithm-based ANFIS model used meteorological data and derived meteorological data, along with NO and NO2 concentrations and their transformations, as inputs. The root mean square error and Willmott’s index of agreement of the FCM- and SC-based ANFIS models are 3.5 ppbv and 0.99, and 8.9 ppbv and 0.95, respectively. Based on the analysis of the performance measures and regression error characteristic curves, it is concluded that the FCM-based ANFIS model outperforms the SC-based ANFIS model.