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Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network
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Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destination node via multi-hop routing techniques. An appropriate, efficient, and stable routing algorithm must be developed for various VANET applications to address the issues of dynamic topology and intermittent connectivity. Therefore, this paper proposes a novel routing algorithm called efficient and stable routing algorithm based on user mobility and node density (ESRA-MD). The proposed algorithm can adapt to significant changes that may occur in the urban vehicular environment. This algorithm works by selecting an optimal route on the basis of hop count and link duration for delivering data from source to destination, thereby satisfying various quality of service considerations. The validity of the proposed algorithm is investigated by its comparison with ARP-QD protocol, which works on the mechanism of optimal route finding in VANETs in urban environments. Simulation results reveal that the proposed ESRA-MD algorithm shows remarkable improvement in terms of delivery ratio, delivery delay, and communication overhead.

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Publication Date
Thu Jun 01 2023
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Innovations in t-way test creation based on a hybrid hill climbing-greedy algorithm
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<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm
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Publication Date
Wed May 29 2019
Journal Name
Journal Of Planner And Development
War disasters and their effects on urban structure
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Many urban and rural areas fall under the impact of disasters, whether natural or industrial, and with increasing complexity in urban areas, with diversity of economic, social and political components, and technological and cognitive development, the effects of disasters and wars have increased with the time, where disasters are affecting all aspects of life, causing great waste of property and lives, also displacement of populations and disruption of economic life, these effects are multiplied if they are not dealt with in sound curricula and scientific strategies.

The research aims to identify the experiences of some countries and their strategies and effective programs in reconstruction after exposure to disasters and wars wit

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Planner And Development
Urban wetlands and their impact on city sustainability
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Urban wetlands are one of the complex systems that provide many economic, social and environmental services to the city. In this research, the most important services provided by urban wetlands from the point of view of the urban planner were reviewed, and the types of these lands and their divisions according to the type of services provided by each type were presented. Environmental is represented in its ability to reduce the dangers of floods, mitigate the climate and reduce its negative impacts, purify water and deplete a lot of suspended impurities and pollutants, and social services such as recreational areas and beautiful landscapes that inspire joy and reassurance in the soul, as well as cultural areas and sports activities for m

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
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Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

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Publication Date
Thu May 05 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Classification SINGLE-LEAD ECG by using conventional neural network algorithm
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Topology-Based Modularity and Modularity Density for Detecting Protein Complexes: A Comparative Study
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     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

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Publication Date
Fri Jul 30 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm
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The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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