In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of ho

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

The filler in the asphalt mixture is essential since it plays a significant role in toughening and stiffening the asphalt. Changes in filler type can lead the asphalt mixtures to perform satisfactorily during their design life or degrade rapidly when traffic and environmental effects are considered. This study aims to assess the impact of filler types such as limestone dust (LS) and hydrated lime (HL) on Marshall characteristics and moisture damage in asphalt mixtures. Three different percentages of HL were employed in this study to partially replace the LS mineral filler: 1.5, 2.0, and 2.5% by aggregate weight. Furthermore, a control mixture was created with 7% LS by overall aggregate weight for the wearing course layer. The Marsha

<p>In this paper, a simple color image compression system has been proposed using image signal decomposition. Where, the RGB image color band is converted to the less correlated YUV color model and the pixel value (magnitude) in each band is decomposed into 2-values; most and least significant. According to the importance of the most significant value (MSV) that influenced by any simply modification happened, an adaptive lossless image compression system is proposed using bit plane (BP) slicing, delta pulse code modulation (Delta PCM), adaptive quadtree (QT) partitioning followed by an adaptive shift encoder. On the other hand, a lossy compression system is introduced to handle the least significant value (LSV), it is based on

Experimental and numerical investigations of the centrifugal pump performance at non-cavitating and cavitating flow conditions were carried out in the present study. Experiments were performed by applying a vacuum to a closed-loop system to investigate the effects of the net positive suction head available (NPSHa), flow rate, water temperature and pump speed on the centrifugal pump performance. Accordingly, many of the important parameters concerning cavitation phenomenon were calculated. Also, the noise which is accompanied by cavitation was measured. Numerical analysis was implemented for two phase flow (the water and its vapor) using a 2-D simulation by ANSYS FLUENT software to investigate the internal flow of centrifugal pump under c

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t