The purpose of this study is to evaluate the effect of hydrated lime addition methods as filler replacement on fatigue performance of Hot Mix Asphalt (HMA). Three types of addition methods of hydrated lime were introduced namely dry HL on dry aggregate and saturated surface aggregate above 3% and slurry HL on dry aggregate, ordinary Lime stone powder was reduced by three HL percentage (1.0, 2.0 and 3.0 %). The effect of different methods were investigated on the fatigue properties of HMA using, third-point flexural fatigue bending Test. Pneumatic Repeated Load System (PRLS) was carried out to establish the effect of hydrated lime on the fatigue failure criteria and to select the proper hydrated lime application methods on fatigue behavior of HMA mixtures. The fatigue functions for asphalt mixture with hydrated lime are obtained and compared, and it confirm that the fatigue property of asphalt mixture can be improved using all methods and the addition methods were exhibited different optimality for the result due to its effect . The test results were carried out through the performance analysis using Vesys 5W (2003) to study the long term effectiveness of hydrated lime effect.
<p>Vehicular ad-hoc networks (VANET) suffer from dynamic network environment and topological instability that caused by high mobility feature and varying vehicles density. Emerging 5G mobile technologies offer new opportunities to design improved VANET architecture for future intelligent transportation system. However, current software defined networking (SDN) based handover schemes face poor handover performance in VANET environment with notable issues in connection establishment and ongoing communication sessions. These poor connectivity and inflexibility challenges appear at high vehicles speed and high data rate services. Therefore, this paper proposes a flexible handover solution for VANET networks by integrating SDN and
... Show MoreProgression in Computer networks and emerging of new technologies in this field helps to find out new protocols and frameworks that provides new computer network-based services. E-government services, a modernized version of conventional government, are created through the steady evolution of technology in addition to the growing need of societies for numerous services. Government services are deeply related to citizens’ daily lives; therefore, it is important to evolve with technological developments—it is necessary to move from the traditional methods of managing government work to cutting-edge technical approaches that improve the effectiveness of government systems for providing services to citizens. Blockchain technology is amon
... Show MoreKinetic analysis has received great importance in the fields of sports and biomedicine, as it provides accurate data about the motor performance of athletes and helps in improving performance and preventing injuries, and among the technological tools currently available, artificial intelligence applications such as the (on form) application, which works to analyze performance directly and indirectly and has several advantages where direct analysis of performance is possible and reduce time and costs without referring to the video and analyzing it with analysis programs such as the (kenovea) program, which needs more time and greater experience by the person analyzing it, The research aimed at a comparative study to measure some mechanical v
... Show MoreWireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati
... Show MoreThe evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities. Cloud computing can be used to store big data. The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Future generations of wireless communications systems are expected to evolve toward allowing massive ubiquitous connectivity and achieving ultra-reliable and low-latency communications (URLLC) with extremely high data rates. Massive multiple-input multiple-output (m-MIMO) is a crucial transmission technique to fulfill the demands of high data rates in the upcoming wireless systems. However, obtaining a downlink (DL) training sequence (TS) that is feasible for fast channel estimation, i.e., meeting the low-latency communications required by future generations of wireless systems, in m-MIMO with frequency-division-duplex (FDD) when users have different channel correlations is very challenging. Therefore, a low-complexity solution for
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