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Gama Platform Survey for Agent-Based Modelling
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The agent-based modeling is currently utilized extensively to analyze complex systems. It supported such growth, because it was able to convey distinct levels of interaction in a complex detailed environment. Meanwhile, agent-based models incline to be progressively complex. Thus, powerful modeling and simulation techniques are needed to address this rise in complexity. In recent years, a number of platforms for developing agent-based models have been developed. Actually, in most of the agents, often discrete representation of the environment, and one level of interaction are presented, where two or three are regarded hardly in various agent-based models. The key issue is that modellers work in these areas is not assisted by simulation platforms. Therefore, GAMA modelling and simulation platform is designed to facilitate the development of spatialized, multi-paradigms and multi-scale models to address this challenge.This platform enables modelers to build explicit and multi-level models geographically (spatially). It includes notably effective Data Mining models and Geographic Information Systems (GIS) that make the effort to model and analyze easier. This study examines how this platform deals with these concerns and how modeler's tools are provided from the box. Also, shows its skills relating to the tight combination of 3D visualization, GIS data management, and multi-level modeling. Furthermore, several examples of GAMA-based projects that had been built for complex models.

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Advanced Computer Science And Applications
Achieving Flatness: Honeywords Generation Method for Passwords based on user behaviours
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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Enhanced Chain-Cluster Based Mixed Routing Algorithm for Wireless Sensor Networks
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Energy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Engineering
Self-Repairing Technique Based on Microcapsules for Cementitious Composites- A Review
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Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

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Publication Date
Mon Mar 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Bionics-Based Approach for Object Tracking to Implement in Robot Applications
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In this paper, an approach for object tracking that is inspired from human oculomotor system is proposed and verified experimentally. The developed approach divided into two phases, fast tracking or saccadic phase and smooth pursuit phase. In the first phase, the field of the view is segmented into four regions that are analogue to retinal periphery in the oculomotor system. When the object of interest is entering these regions, the developed vision system responds by changing the values of the pan and tilt angles to allow the object lies in the fovea area and then the second phase will activate. A fuzzy logic method is implemented in the saccadic phase as an intelligent decision maker to select the values of the pan and tilt angle based

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Publication Date
Sun Apr 01 2018
Journal Name
2018 9th International Conference On Information And Communication Systems (icics)
An intersection-based segment aware algorithm for geographic routing in VANETs
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In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Severity Based Light-Weight Encryption Model for Secure Medical Information System
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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks
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The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

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Publication Date
Fri Dec 01 2023
Journal Name
Ieee Antennas And Wireless Propagation Letters
Stabilized and Fast Method for Compressive-Sensing-Based Method of Moments
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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
Smart Routing Management Framework Exploiting Dynamic Data Resources of Cross-Layer Design and Machine Learning Approaches for Mobile Cognitive Radio Networks: A Survey
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