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Umar Farooq
Department of Computer Science, University of Science and Technology Bannu, Bannu, Khyber Pakhtunkhwa, Pakistan

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Short Biography

Umar Farooq is an Assistant Professor at the Department of CS, University of Science and Technology Bannu, Pakistan.

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Journal article
Published: 19 May 2021 in PeerJ Computer Science
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Evacuation modeling and simulation are usually used to explore different possibilities for evacuation, however, it is a real challenge to integrate different categories of characteristics in unified modeling space. In this paper, we propose an agent-based model of an evacuating crowd so that a comparative analysis of a different sets of parameters categorized as individual, social and technological aspects, is made possible. In particular, we focus on the question of rationality vs. emotionalism of individuals in a localized social context. In addition to that, we propose and model the concept of extended social influence, thereby embedding technological influence within the social influence, and analyze its impact on the efficiency of evacuation. NetLogo is used for simulating different variations in environments, evacuation strategies, and agents demographics. Simulation results revealed that there is no substantial advantage of informational overload on people, as this might work only in those situations, where there are fewer chances of herding. In more serious situations, people should be left alone to decide. They, however, could be trained in drills, to avoid panicking in such situations and concentrate on making their decisions solely based on the dynamics of their surroundings. It was also learned that distant connectivity has no apparent advantage and can be ruled out while designing an evacuation strategy based on these recommendations.

ACS Style

Kashif Zia; Umar Farooq; Muhammad Shafi; Alois Ferscha. On the effectiveness of multi-feature evacuation systems: an agent-based exploratory simulation study. PeerJ Computer Science 2021, 7, e531 .

AMA Style

Kashif Zia, Umar Farooq, Muhammad Shafi, Alois Ferscha. On the effectiveness of multi-feature evacuation systems: an agent-based exploratory simulation study. PeerJ Computer Science. 2021; 7 ():e531.

Chicago/Turabian Style

Kashif Zia; Umar Farooq; Muhammad Shafi; Alois Ferscha. 2021. "On the effectiveness of multi-feature evacuation systems: an agent-based exploratory simulation study." PeerJ Computer Science 7, no. : e531.

Journal article
Published: 23 March 2021 in IoT
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The things in the Internet of Things are becoming more and more socially aware. What social means for these things (more often termed as “social objects”) is predominately determined by how and when objects interact with each other. In this paper, an agent-based model for Social Internet of Things is proposed, which features the realization of various interaction modalities, along with possible network structures and mobility modes, thus providing a novel model to ask interesting “what-if” questions. The scenario used, which is the acquisition of shared resources in a common spatial and temporal world, demands agents to have ad-hoc communication and a willingness to cooperate with others. The model was simulated for all possible combinations of input parameters to study the implications of competitive vs. cooperative social behavior while agents try to acquire shared resources/services in a peer-to-peer fashion. However, the main focus of the paper was to analyze the impact of profile-based mobility, which has an underpinning on parameters of extent and scale of a mobility profile. The simulation results, in addition to others, reveal that there are substantial and systematic differences among different combinations of values for extent and scale.

ACS Style

Kashif Zia; Umar Farooq; Muhammad Shafi; Muhammad Arshad. An Agent-Based Model of Task-Allocation and Resource-Sharing for Social Internet of Things. IoT 2021, 2, 187 -204.

AMA Style

Kashif Zia, Umar Farooq, Muhammad Shafi, Muhammad Arshad. An Agent-Based Model of Task-Allocation and Resource-Sharing for Social Internet of Things. IoT. 2021; 2 (1):187-204.

Chicago/Turabian Style

Kashif Zia; Umar Farooq; Muhammad Shafi; Muhammad Arshad. 2021. "An Agent-Based Model of Task-Allocation and Resource-Sharing for Social Internet of Things." IoT 2, no. 1: 187-204.

Journal article
Published: 16 April 2020 in Future Internet
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The latest manifestation of “all connected world" is the Internet of Things (IoT), and Internet of Vehicles (IoV) is one of the key examples of IoT these days. In Social IoV (SIoV), each vehicle is treated as a social object where it establishes and manages its own Social Network (SN). Incidentally, most of the SIoV research in the literature is related to proximity-based connectivity and interactions. In this paper, we bring people in the loop by incorporating their SNs. While emphasizing a recommendation scenario, in which vehicles may require recommendations from SNs of their owners (in addition to their own SIoV), we proposed an agent-based model of information sharing (for context-based recommendations) on a hypothetical population of smart vehicles. Some important hypotheses were tested using a realistic simulation setting. The simulation results reveal that a recommendation using weak ties is more valuable than a recommendation using strong ties in pure SIoV. The simulation results also demonstrate that recommendations using the most-connected person in the social network are not more valuable than recommendation using a random person in the social network. The model presented in this paper can be used to design a multi-scale recommendation system, which uses SIoV and a typical SN in combination.

ACS Style

Kashif Zia; Muhammad Shafi; Umar Farooq. Improving Recommendation Accuracy Using Social Network of Owners in Social Internet of Vehicles. Future Internet 2020, 12, 69 .

AMA Style

Kashif Zia, Muhammad Shafi, Umar Farooq. Improving Recommendation Accuracy Using Social Network of Owners in Social Internet of Vehicles. Future Internet. 2020; 12 (4):69.

Chicago/Turabian Style

Kashif Zia; Muhammad Shafi; Umar Farooq. 2020. "Improving Recommendation Accuracy Using Social Network of Owners in Social Internet of Vehicles." Future Internet 12, no. 4: 69.

Other
Published: 06 April 2020
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Motivated by the rapid spread of COVID-19 all across the globe, we have performed simulations of a system dynamic epidemic spread model in different possible situations. The simulation, not only captures the model dynamic of the spread of the virus, but also, takes care of population and mobility data. The model is calibrated based on epidemic data and events specifically of Sultanate of Oman, which can easily be generalized. The simulation results are quite disturbing, indicating that, during a process of stringent social distancing and testing strategies, a small perturbation can lead to quite undesirable outcomes. The simulation results, although consistent in expected outcomes across changing parameters’ values, also indicate a substantial mismatch with real numbers. An analysis of what can be the reason of this mismatch is also performed. Within these contradictions, for Oman, regarding the eradication of epidemic, the future is not extremely alarming.

ACS Style

Kashif Zia; Umar Farooq. COVID-19 Outbreak in Oman: Model-Driven Impact Analysis and Challenges. 2020, 1 .

AMA Style

Kashif Zia, Umar Farooq. COVID-19 Outbreak in Oman: Model-Driven Impact Analysis and Challenges. . 2020; ():1.

Chicago/Turabian Style

Kashif Zia; Umar Farooq. 2020. "COVID-19 Outbreak in Oman: Model-Driven Impact Analysis and Challenges." , no. : 1.

Journal article
Published: 12 August 2019 in Safety
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“The wisdom of crowds” is often observed in social discourses and activities around us. The manifestations of it are, however, so intrinsically embedded and behaviorally accepted that an elaboration of a social phenomenon evidencing such wisdom is often considered a discovery; or at least an astonishing fact. One such scenario is explored here, namely, the conceptualization and modeling of a food safety system—a system directly related to social cognition. The first contribution of this paper is the re-evaluation of Knowles’s model towards a more conscious understanding of “the wisdom of crowds” effects on inspection and consumption behaviors. The second contribution is augmenting the model with social networking capabilities, which acts as a medium to spread information about stores and help consumers find uncontaminated stores. Simulation results revealed that stores respecting social cognition improve the effectiveness of the food safety system for consumers as well as for the stores. Simulation findings also revealed that active societies have the capability to self-organize effectively, even if they lack regulatory obligations.

ACS Style

Kashif Zia; Umar Farooq; Arshad Muhammad. Agent-Based Modeling of a Self-Organized Food Safety System. Safety 2019, 5, 52 .

AMA Style

Kashif Zia, Umar Farooq, Arshad Muhammad. Agent-Based Modeling of a Self-Organized Food Safety System. Safety. 2019; 5 (3):52.

Chicago/Turabian Style

Kashif Zia; Umar Farooq; Arshad Muhammad. 2019. "Agent-Based Modeling of a Self-Organized Food Safety System." Safety 5, no. 3: 52.

Original article
Published: 03 February 2017 in Virtual Reality
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OpenSimulator has emerged as one of the leading tools to help researchers, developers, and practitioners working in the field of virtual worlds since it is an open-source alternative to second life, the state of the art in virtual worlds. The grid mode of OpenSimulator is highly scalable, and it places no restriction on the number of cooperating OpenSimulator instances, each of which may simulate activity in an arbitrary number of regions. However, like second life, it suffers from both over-provision and under-provision of resources due to static allocation of regions to instances and the lack of an expansion and contraction model which adjusts resource allocation according to workload. We have used OpenSimulator to implement dynamic scalability which is an integral part of our novel infrastructure presented in earlier work. This paper reports timing analysis of the basic capabilities of OpenSimulator that are used to re-locate regions to additional simulators. The focus has been on a conservative extension to OpenSimulator using existing methods. To overcome serious performance issues during reassignment of a region, we present two extended region removal methods. Comparison of timing information for both existing and extended strategies is provided on both a network of Windows systems and a cluster of Linux nodes.

ACS Style

Umar Farooq; John Glauert. Faster dynamic spatial partitioning in OpenSimulator. Virtual Reality 2017, 21, 193 -202.

AMA Style

Umar Farooq, John Glauert. Faster dynamic spatial partitioning in OpenSimulator. Virtual Reality. 2017; 21 (4):193-202.

Chicago/Turabian Style

Umar Farooq; John Glauert. 2017. "Faster dynamic spatial partitioning in OpenSimulator." Virtual Reality 21, no. 4: 193-202.