Islamabad, Pakistan

The International Islamic University , is a public research university located in the urban area of Islamabad, Pakistan. It is regarded as one of the noted institution of Islam, theology, divinity, and the science.Founded and established in 1980, the university was restructured, reorganized, and reconstituted in its current and modern form in 1985. It is one of premium institute of higher learning, and regarded as one of the largest university in the country. With approximated ~30,000 students currently enrolled in IIU, the university is ranked among the top public universities in "general category" by the HEC, as of 2012. The university offers undergraduate, post-graduate, and doctoral studies programmes in science, humanities, arts, religious studies, social and natural science.In addition, the university has nine research faculties and six autonomous academies, institutes and centers. The university is also noted for its engaging efforts to produce educational quality assurance for the purpose of improving academic standards in the country. It is completely distinct from the International Islamic University in Malaysia. Wikipedia.

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Lung cancer is the major cause of mortality worldwide. Major signalling pathways that could play significant role in lung cancer therapy include (1) Growth promoting pathways (Epidermal Growth Factor Receptor/Ras/ PhosphatidylInositol 3-Kinase) (2) Growth inhibitory pathways (p53/Rb/P14ARF, STK11) (3) Apoptotic pathways (Bcl-2/Bax/Fas/FasL). Insilico strategy was implemented to solve the mystery behind selected lung cancer pathway by applying comparative modeling and molecular docking studies. YASARA [v 12.4.1] was utilized to predict structural models of P16-INK4 and RB1 genes using template 4ELJ-A and 1MX6-B respectively. WHAT CHECK evaluation tool demonstrated overall quality of predicted P16-INK4 and RB1 with Z-score of -0.132 and -0.007 respectively which showed a strong indication of reliable structure prediction. Protein-protein interactions were explored by utilizing STRING server, illustrated that CDK4 and E2F1 showed strong interaction with P16-INK4 and RB1 based on confidence score of 0.999 and 0.999 respectively. In order to facilitate a comprehensive understanding of the complex interactions between candidate genes with their functional interactors, GRAMM-X server was used. Protein-protein docking investigation of P16-INK4 revealed four ionic bonds illustrating Arg47, Arg80,Cys72 and Met1 residues as actively participating in interactions with CDK4 while docking results of RB1 showed four hydrogen bonds involving Glu864, Ser567, Asp36 and Arg861 residues which interact strongly with its respective functional interactor E2F1. This research may provide a basis for understanding biological insights of P16-INK4 and RB1 proteins which will be helpful in future to design a suitable drug to inhibit the disease pathogenesis as we have determined the interacting amino acids which can be targeted in order to design a ligand in-vitro to propose a drug for clinical trials. Protein -protein docking of candidate genes and their important interacting residues likely to be provide a gateway for developing computer aided drug designing.

Muhammad F.,International Islamic University, Islamabad
Annals of Nuclear Energy | Year: 2013

The effects of using high density low enriched uranium on the worth of the control rods of a material test research reactor were studied. For this purpose, the low density LEU fuel of an MTR was replaced with high density U-Mo (9 w/o) LEU fuels, having uranium densities of 6.57 g/cm3, 7.74 g/cm 3 and 8.90 g/cm3. Simulations were carried out to calculate the worth of the control rods at beginning of life. Three control rod materials were investigated: Ag-In-Cd alloy, B4C and Hf. Nuclear reactor analysis codes WIMS-D4 and CITATION were employed to carry out these calculations. It was seen that the control rod worth decreased as the uranium density of fuel increased from 6.57 g/cm3 to 8.90 g/cm3. The decrease was 10.58%, 9.39% and 9.74% for Ag-Cd-In alloy, B4C and Hf respectively. Even the increase in control rod thickness could not compensate for the decreased worth. © 2013 Elsevier Ltd. All rights reserved.

Raja M.A.Z.,COMSATS Institute of Information Technology | Raja M.A.Z.,International Islamic University, Islamabad
Information Sciences | Year: 2014

In this article, the numerical techniques are presented for the solution of Troesch's problem based on neural networks optimized with three different methods including particle swarm optimization (PSO), active set (AS) and PSO hybridized with AS (PSO-AS) algorithms. The variable transformation is applied in order to convert the original problem to a transformed problem which is relatively less stiff to solve. Feed-forward artificial neural networks are used to model the transformed problem. Learning of adjustable parameters is made with PSO, AS and PSO-AS algorithms. The proposed methodologies are applied to a number of cases for stiff and non-stiff boundary value problems. The comparative analyses are carried out with other standard numerical solutions, as well as approximate analytical solver. © 2014 Elsevier Inc. All rights reserved.

Azam A.,COMSATS Institute of Information Technology | Arshad M.,International Islamic University, Islamabad
Fuzzy Sets and Systems | Year: 2010

In this paper a result on common fixed point theorem for a pair of contractive type fuzzy mappings in a metric space is established which improves the result of Vijayaraju and Marudai [Fixed point theorems for fuzzy mappings, Fuzzy Sets and Systems 135 (2003) 401-408]. © 2009 Elsevier B.V. All rights reserved.

Anwar J.,International Islamic University, Islamabad
Renewable and Sustainable Energy Reviews | Year: 2016

The influence of reducing energy imports (5%, 10% and 15%) on primary energy supply, diversification of energy resources, cost of imported fuels, energy security and environmental emission during 2005–2050 were analyzed through a long term integrated energy system model of Pakistan using MARKet ALlocation (MARKAL) framework. The study found that primary energy supply would decrease marginally, while cumulative renewable energy would increase by 24%. Energy import dependency would reduce by 3%, diversification of energy resources would increase 1.1 fold and vulnerability would decrease by 9% under energy import reduction scenario as compared to the base case. The cost of imported fuels would reduce by 10% and the greenhouse gas emissions would decrease by 8% in the energy import reduction scenario. The impact on energy security was represented through a set of eleven energy security indicators. The improvements in energy security indicators under energy import reduction targets indicate the enhancement of energy security of Pakistan. © 2016 Elsevier Ltd

Chaudhary N.I.,International Islamic University, Islamabad | Raja M.A.Z.,COMSATS Institute of Information Technology
Nonlinear Dynamics | Year: 2014

In this study, a novel adaptive strategy is designed based on fractional least mean square (LMS) algorithm for parameter estimation of Hammerstein nonlinear autoregressive moving average system with exogenous noise (HN-ARMAX). The design scheme consists of parameterization of HN-ARMAX systems to obtain linear-in-parameter models and to use fractional LMS algorithm for adapting unknown parameter vectors. The performance analysis of the proposed method is carried out based on convergence to the desired values of HN-ARMAX systems, and comparison is made with state-of-the-art kernel LMS and Volterra LMS algorithms. The consistency in terms of accuracy and convergence is established through the results of statistical analysis based on sufficient large number of independent runs rather than single successful run of the algorithm. The performance of proposed scheme is superior due to its strong mathematical foundations, nonlinear weight updating mechanism and more convergence controlling variables but at the cost of bit more computational requirements. © 2014, Springer Science+Business Media Dordrecht.

Shabir M.,Quaid-i-Azam University | Mahmood T.,International Islamic University, Islamabad
Computers and Mathematics with Applications | Year: 2011

In this paper we define (∈,∈∨qk)-fuzzy h-sub hemirings, (∈,∈∨qk)-fuzzy h-bi-ideals,(∈,∈∨qk)-fuzzy h-quasi-ideals. We characterize h-hemiregular and h-intra-hemiregular hemirings by the properties of their (∈,∈∨qk)-fuzzy h-ideals, (∈,∈∨qk)-fuzzy h-bi-idealsand (∈,∈∨qk)-fuzzy h-quasi-ideals. Some of these characterizations are generalizations of the characterizations given in [36] [X. Ma, J. Zhan, Generalized fuzzyh-bi-ideals and h-quasi-ideals of hemirings, Inform. Sci. 179 (2009) 12491268]. © 2010 Elsevier Ltd. All rights reserved.

Daud A.,International Islamic University, Islamabad
Knowledge-Based Systems | Year: 2012

Researchers interests finding has been an active area of investigation for different recommendation tasks. Previous approaches for finding researchers interests exploit writing styles and links connectivity by considering time of documents, while semantics-based intrinsic structure of words is ignored. Consequently, a topic model named Author-Topic model is proposed, which exploits semantics-based intrinsic structure of words present between the authors of research papers. It ignores simultaneous modeling of time factor which results in exchangeability of topics problem, which is, important factor to deal with when finding dynamic research interests. For example, in many real world applications, like finding reviewers for papers and finding taggers in the social tagging systems one needs to consider different time periods. In this paper, we present time topic modeling approach named Temporal-Author-Topic (TAT) which can simultaneously model text, researchers and time of research papers to overcome the exchangeability of topic problem. The mixture distribution over topics is influenced by both co-occurrences of words and timestamps of the research papers. Consequently, topics occurrence and their related researchers change over time, while the meaning of particular topic almost remains unchanged. Proposed approach is used to discover topically related researchers for different time periods. We also show how their interests and relationships change over a time period. Empirical results on large research papers corpus show the effectiveness of our proposed approach and dominance over Author-Topic (AT) model, by handling the exchangeability of topics problem, which enables it to obtain similar meaning of a particular topic overtime. © 2011 Elsevier B.V. All rights reserved.

Amjad T.,International Islamic University, Islamabad | Sher M.,International Islamic University, Islamabad | Daud A.,International Islamic University, Islamabad
Future Generation Computer Systems | Year: 2012

Data grid is a distributed collection of storage and computational resources that are not bounded within a geophysical location. It is a fast growing area of research and providing efficient data access and maximum data availability is a challenging task. To achieve this task, data is replicated to different sites. A number of data replication techniques have been presented for data grids. All replication techniques address some attributes like fault tolerance, scalability, improved bandwidth consumption, performance, storage consumption, data access time etc. In this paper, different issues involved in data replication are identified and different replication techniques are studied to find out which attributes are addressed in a given technique and which are ignored. A tabular representation of all those parameters is presented to facilitate the future comparison of dynamic replication techniques. The paper also includes some discussion about future work in this direction by identifying some open research problems. © 2011 Elsevier B.V. All rights reserved.

Salam A.,International Islamic University, Islamabad | Khayal M.S.H.,Fatima Jinnah Women University
Knowledge and Information Systems | Year: 2012

Finding frequent patterns play an important role in mining association rules, sequences, episodes, Web log mining and many other interesting relationships among data. Frequent pattern mining methods often produce a huge number of frequent itemsets that is not feasible for effective usage. The number of highly correlated patterns is usually very small and may even be one. Most of the existing frequent pattern mining techniques often require the setting of many input parameters and may involve multiple passes over the database. Minimum support is the widely used parameter in frequent pattern mining to discover statistically significant patterns. Specifying appropriate minimum support is a challenging task for a data analyst as the choice of minimum support value is somewhat arbitrary. Generally, it is required to repeatedly execute an algorithm, heuristically tuning the value of minimum support over a wide range, until the desired result is obtained, certainly, a very time-consuming process. Setting up an inappropriate minimum support may also cause an algorithm to fail in finding the true patterns. We present a novel method to efficiently retrieve top few maximal frequent patterns in order of significance without use of the minimum support parameter. Instead, we are only required to specify a more human understandable parameter, namely the desired number itemsets k. Our technique requires only a single pass over the database and generation of length two itemsets. The association ratio graph is proposed as a compact structure containing concise information, which is created in time quadratic to the size of the database. Algorithms are described for using this graph structure to discover top-most and top-k maximal frequent itemsets without minimum support threshold. To effectively achieve this, the method employs construction of an all path source-to-destination tree to discover all maximal cycles in the graph. The results can be ranked in decreasing order of significance. Results are presented demonstrating the performance advantages to be gained from the use of this approach. © 2011 Springer-Verlag London Limited.

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