Search results for: Mustansar Ali Ghazanfar

Authors: Saima Nazir, Mustansar Ali Ghazanfar, Sanay Muhammad Umar Saeed, Muhammad Awais Azam, Saad Ali Alahmari

Abstract:

Terrorism is an important and challenging concern. The entire world is threatened by only few sophisticated terrorist groups and especially in Gulf Region and Pakistan, it has become extremely destructive phenomena in recent years. Predicting the pattern of attack type, attack group and target type is an intricate task. This study offers new insight on terrorist group’s attack type and its chosen target. This research paper proposes a framework for prediction of terrorist attacks using the historical data and making an association between terrorist group, their attack type and target. Analysis shows that the number of attacks per year will keep on increasing, and Al-Harmayan in Saudi Arabia, Al-Qai’da in Gulf Region and Tehreek-e-Taliban in Pakistan will remain responsible for many future terrorist attacks. Top main targets of each group will be private citizen & property, police, government and military sector under constant circumstances.

Keywords: data mining, counter terrorism, machine learning, SVM

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Authors: Hina Iqbal, Mustansar Ali Ghazanfar, Sandor Szedmak

Abstract:

Recommender systems uses artificial intelligence practices for filtering obscure information and can predict if a user likes a specified item. Kernel mapping Recommender systems have been proposed which are accurate and state-of-the-art algorithms and resolve recommender system’s design objectives such as; long tail, cold-start, and sparsity. The aim of research is to propose hybrid framework that can efficiently integrate different versions— namely item-based and user-based KMR— of KMR algorithm. We have proposed various heuristic algorithms that integrate different versions of KMR (into a unified framework) resulting in improved accuracy and elimination of problems associated with conventional recommender system. We have tested our system on publically available movies dataset and benchmark with KMR. The results (in terms of accuracy, precision, recall, F1 measure and ROC metrics) reveal that the proposed algorithm is quite accurate especially under cold-start and sparse scenarios.

Keywords: Kernel Mapping Recommender Systems, hybrid recommender systems, cold start, sparsity, long tail

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Authors: Ghazanfar Bozai, Kanwal Gul

Abstract:

In Pakistan, SMEs are the major source of contribution to the economy, but due to lack of proper HR practices (lack of employee engagement), these fast growing business shut down with in few years of startup. The purpose of this study is to conduct a comprehensive literature survy of the major best practices used for employee engagement globally. This paper could be used as employee engagement best practices guide for SME’s in developing countries. This article is focused on identifying the attributes of employee engagement in different countries/ cultures and organizations. It will provide a summary of employee engagement models used globally and how SMEs could pick suitable attributes of employee engagement as per their structural culture. This article will add valuable literature on employee engagement in developing countries for new startups and small, medium business.

Keywords: attributes, employee engagement, human resources practices, small medium enterprises

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Authors: Ghazanfar Ali, Fahad N Almajhdi

Abstract:

This study provides data on the viral diagnosis and molecular epidemiology of influenza A(H3N2) virus isolated in Riyadh, Saudi Arabia. Nasopharyngeal aspirates from 80 clinically infected patients in the peak of the 2010-2011 winter seasons were processed for viral diagnosis by RT-PCR. Sequencing of entire HA and NA genes of representative isolates and molecular epidemiological analysis were performed. A total of 06 patients were positive for influenza A, B and respiratory syncytial viruses by RT-PCR assays; out of these only one sample was positive for influenza A(H3N2) by RT-PCR. Phylogenetic analysis of the HA and NA gene sequences showed identities higher than 99-98.8 % in both genes. They were also similar to reference isolates in HA sequences (99 % identity) and in NA sequences (99 % identity). Amino acid sequences predicted for the HA gene were highly identical to reference strains. The NA amino acid substitutions identified did not include the oseltamivir-resistant H275Y substitution. Conclusion: Viral isolation and RT-PCR together were useful for diagnosis of the influenza A (H3N2) virus. Variations in HA and NA sequences are similar to those identified in worldwide reference isolates and no drug resistance was found.

Keywords: influenza A (H3N2), genetic characterization, viral isolation, RT-PCR, Saudi Arabia

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Authors: Rida Batool, Faizah Altaf, Saba Nadeem, Afifa Aslam, Faisal Alamgir, Ghazanfar Abbas

Abstract:

Today, the need of the hour is to find out alternative renewable energy resources in order to reduce the burden on fossil fuels and prevent alarming environmental degradation. Solid oxide fuel cell (SOFC) is considered a good alternative energy conversion device because it is environmentally benign and supplies energy on demand. The only drawback associated with SOFC is its high operating temperature. In order to reduce operating temperature, different types of composite material are prepared. In this work, titanium doped lanthanum gallium cerate (LGCT) composite is prepared through the co-precipitation method as electrolyte and examined for low temperature SOFCs (LTSOFCs). The structural properties are analyzed by X-Ray Diffractometry (XRD) and Fourier Transform Infrared (FTIR) Spectrometry. The surface properties are investigated by Scanning Electron Microscopy (SEM). The electrolyte LGCT has the formula LGCTO₃ because it showed two phases La.GaO and Ti.CeO₂. The average particle size is found to be (32 ± 0.9311) nm. The ionic conductivity is achieved to be 0.073S/cm at 650°C. Arrhenius plots are drawn to calculate activation energy and found 2.96 eV. The maximum power density and current density are achieved at 68.25mW/cm² and 357mA/cm², respectively, at 650°C with hydrogen. The prepared material shows excellent ionic conductivity at comparatively low temperature, that makes it a potentially good candidate for LTSOFCs.

Keywords: solid oxide fuel cell, LGCTO₃, cerium composite oxide, ionic conductivity, low temperature electrolyte

Procedia PDF Downloads 108