A Comparison between Islamic Banking and Conventional Banking Sector in Pakistan

The Islamic banking system is attaining enormous development. Several modern international conventional banks were also enchanting significant concern and starting Islamic banking branches in their organizations, which work in compliance with the specific Islamic Shariah principles in a number of states of Pakistan. The Islamic banking structure is bizarrely facing gigantic contest by the Islamic banking sector all over the world as well as from the well-known International commercial banks that hold out services and products of IB. It is an attempt for exploration and investigation of the extensive and essential factors, which persuade consumers to choose the Islamic banking or conventional banking and the function of demographic features, which track consumers to the assortment of IB or CB in Pakistan. Sample of 341 respondents has been used in this study mainly focused on non-probability convenience test tool. Pre-institute 5 point likert survey instrument ranging from 5 to 1 was applied to gather data. The conclusion reveals that there are countless factors other than religious perception like employee and customer interactions, convenience, reputation, financial benefits & services, and technology, which are fundamental for the consumers for the assortment of Islamic or conventional banking. The demographic characteristics of the respondents also have a significant impact. The authors expect that the crux of this study will explore new ways for the Islamic banking system to emphasis on specific emerging factors to enhance the efficiency and performance of the Islamic banking system in Pakistan. There will be enormous advantage for executives of IBs & CBs in developing marketing approach

Energy Consumption Rate based Stable Election Protocol (ECRSEP) for WSNs

In recent few yearsWireless Sensor Networks (WSNs) have seen an increased interest in various applications like border field security, disaster management and medical applications. So large number of sensor nodes are deployed for such applications, which can work autonomously. Due to small power batteries in WSNs, efficient utilization of battery power is an important factor. Clustering is an efficient technique to extend life time of sensor networks by reducing the energy consumption. In this paper, we propose a new protocol; Energy Consumption Rate based Stable Election Protocol (ECRSEP). Our CH selection scheme is based on the weighted election probabilities of each node according to the Energy Consumption Rate (ECR) of each node. We compare results of our proposed protocol with Low Energy Adaptive Clustering Hierarchy (LEACH), Distributed Energy Efficient Clustering (DEEC), Stable Election Protocol (SEP), and Enhanced SEP(ESEP). Our simulation results show that our proposed protocol, ECRSEP outperforms all these protocols in terms of network stability and network lifetime

Aspects of Mir Sher Ali Afsos’s Poetry

Mir sher Ali Afsos was a successful ghazal poet of his era. He has tried almost all the popular genres of speech. The poetry of Mir Sher Ali Afsos seems to be impressive in the color of despair apart from love, but this color is traditional. A study of Kuliat-e-Afsos reveals that he has used all the essentials of art to enhance the reader's quest for techniques, similes and metaphors in his words, as well as the craft of poetry. Afsos has also used beautiful arts in his speech, all these accessories create a charming beauty in the poetry which makes the poet beautiful. His poetry is romantic. In this article effort is made to analyse his poetry

Competitiveness and Comparative Advantage of Pakistan in Leather and Leather Products Trade: Analysis and Trends

Livestock sector is considered the second key sector of agriculture through its share of more than half to value added and 11.8% to GDP and main source of raw material for leather industry of the country. This local availability of raw materials and low wage cost gives the country a competitive edge in the world market. This study is an effort to examine Pakistan's competitiveness of leather and leather products with a set of Revealed Comparative Advantage (RCA) and Revealed Competitive Advantage index with respect to international trade. The study has utilized Balassa index, Vollrath index and Revealed Symmetric Comparative Advantage index for empirical analysis in Pakistan during the time span from 2003 to 2014. The findings of the study illustrate that Pakistan has a high degree of comparative advantage in this sector during period under analysis which indicates the potential of leather sector exports for foreign exchange earnings. The results of the study also show that the position of Leather sector lies in the “Competitive position product group” and “Threatened product group”. There is need to strengthen comparative and competitive advantage in Leather sector by policy support and facilitating role by all stakeholders to attain the growth in livestock and agriculture sector and improve the income of related stakeholders

An agent-based simulation framework for complex systems

In this abstract we present a new approach to the simulation of complex systems as biological interaction networks, chemical reactions, ecosystems, etc. It aims at overcoming previously proposed analytical approaches that, because of several computational challenges, could not handle systems of realistic com- plexity. The proposed model is based on a set of agents interacting through a shared environment. Each agent functions independently from the others, and its be- havior is driven only by its current status and the "content" of the surrounding environment. The environment is the only "data repository" and does not store the value of variables, but only their presence and concentration. Each agent performs 3 main functions: 1. it samples the environment at random locations 2. based on the distribution of the sampled data and a proper Transfer Func- tion, it computes the rate at which the output values are generated 3. it writes the output "products" at random locations. The environment is modeled as a Really Random Access Memory (R2AM). Data is written and sampled at random memory locations. Each memory location represent an atomic sample (a molecule, a chemical compound, a protein, an ion, . . . ). Presence and concentration of these samples are what constitutes the environment data set. The environment can be sensitive to external stimuli (e.g., pH, Temperature, ...) and can include topological information to allow its partitioning (e.g. between nucleus and cytoplasm in a cell) and the modeling of sample "movements" within the environment. The proposed approach is easily scalable in both complexity and computa- tional costs. Each module could implement a very simple object as a single chemical reaction or a very complex process as a gene translation into a pro- tein. At the same time, from the hardware point of view, the complexity of the objects implementing a single agent can range from a single software process to a dedicated computer or hardware platfor

Using Boolean Networks to Model Post-transcriptional Regulation in Gene Regulatory Networks

In Gene Regulatory Networks research there is a considerable lack of tech- niques and tools to understand these networks from a System Biology point of view. The typical biological approach is to reconstruct a particular network from expression patterns, then try to validate its dynamics by simulation, use simulation to analyze its reactions to some perturbations, and finally go back "in vitro" to validate the simulation results. Nevertheless, when the goal is to understand the high-level, general mechanisms that allow these networks to work or to be stable under mild perturbations, this type of approach has shown very strong limitations. In this work we want to better understand the role of miRNA as a stabilizing mechanism in gene regulatory networks. Boolean networks have been recently used to better understand the struc- tural and dynamical properties of regulatory networks. Attractors and ergodic sets have been easily correlated with many of the typical biological cell behav- iors (cancer, differentiation, pluripotential, ...). The most widely used model are nevertheless very simple, and work under too strict constraints. We are defining an enhanced model based on Boolean Networks but also able to take into account post-transcriptional regulation and possibly be extended to other regulatory mechanisms (e.g. ceRNA) that have been already proven crucial in vivo. The final goal is to try to understand if the wide number of miRNA targets constitutes a structural network-stability mechanism used to make the network immune to „regulatory" noise. To achieve this result we evolve the modified Boolean networks for high or low sensitivity to perturbations, and then analyze the resulting networks to understand if specific structural patterns containing miRNA-like post-transcriptional regulatory elements can be correlated with the network stabilit

Building Gene Expression Profile Classifiers with a Simple and Efficient Rejection Option in R

Background: The collection of gene expression profiles from DNA microarrays and their analysis with pattern recognition algorithms is a powerful technology applied to several biological problems. Common pattern recognition systems classify samples assigning them to a set of known classes. However, in a clinical diagnostics setup, novel and unknown classes (new pathologies) may appear and one must be able to reject those samples that do not fit the trained model. The problem of implementing a rejection option in a multi-class classifier has not been widely addressed in the statistical literature. Gene expression profiles represent a critical case study since they suffer from the curse of dimensionality problem that negatively reflects on the reliability of both traditional rejection models and also more recent approaches such as one-class classifiers. Results: This paper presents a set of empirical decision rules that can be used to implement a rejection option in a set of multi-class classifiers widely used for the analysis of gene expression profiles. In particular, we focus on the classifiers implemented in the R Language and Environment for Statistical Computing (R for short in the remaining of this paper). The main contribution of the proposed rules is their simplicity, which enables an easy integration with available data analysis environments. Since in the definition of a rejection model tuning of the involved parameters is often a complex and delicate task, in this paper we exploit an evolutionary strategy to automate this process. This allows the final user to maximize the rejection accuracy with minimum manual intervention. Conclusions: This paper shows how the use of simple decision rules can be used to help the use of complex machine learning algorithms in real experimental setups. The proposed approach is almost completely automated and therefore a good candidate for being integrated in data analysis flows in labs where the machine learning expertise required to tune traditional classifiers might not be availabl

Does FDI Regulatory Policies Influence FDI Inflows in Developing Countries? A Non Linear Analysis

Purpose: Foreign Direct Investment (FDI) inflow is regarded as highly important particularly for developing countries as it enhances economic activities and creates job opportunities. The main objective of the present study is to analyze the impact of two regulatory policies i.e. Regulatory Restrictiveness Index (RRI) and Ease of Doing Business (EDB) on FDI inflows in developing countries. Research Gap: Not many studies have discussed the role of more than one regulatory policy to examine their impact on FDI inflows. Therefore, the present study is an attempt to bridge this research gap as it uses two regulatory policies to examine this relationship. Design/Methodology/Approach: The study performs the non-linear analysis using two separate models to determine FDI inflows in 39 developing countries for the period 1997-2020.For this purpose FGLS econometric technique is utilized. The Main Findings: The linearized marginal effects of RRI show that all the countries are located on the left side of U shaped curve while linearized marginal effects of EDB show that some countries lie on the left side and others lie on the right side of U shaped curve. The higher value of the level coefficient than the value of the quadratic coefficient reveals the stronger influence of level coefficients in both models. Theoretical/Practical Implications of the Findings: The study concludes that developing countries need to reduce FDI restrictions to attract maximum FDI inflows. Furthermore, it is recommended that for improving the confidence of foreign investors, appropriate and consistent policies should be designed and implemented

The Effect of Market and Entrepreneurial Orientation on Firm Performance

Market orientation (MO) and Entrepreneurial orientation (EO) have gained the importance in today’s world. Now these two are considered the main sources in the increase of firm performance. A corelation analysis is performed to understand and determine whether the market orientation and entrepreneurial orientation is associated with the firm performance. The Past studies did not analyze the effect of MO and EO on the firm performance. The research design and methodology adopted is given together with the findings leading to the conclusions related to propositions concerning the variables. The data is collected from various reputed universities that are giving the business education. Entrepreneurial orientation and market orientation provides the basic knowledge about the organizational learning that enables the organization to achieve the high performance and to understand the values of customers (Liu et al, 2002). The paper draws on survey data from 100 students including male and female students. The results show that EO and MO are strongly co-related with dependent variable. However, a few recommendations and future research is also given