This paper addresses the nature of Spatial Data Infrastructure (SDI), considered as one of the most important concepts to ensure effective functioning in a modern society. It comprises a set of continually developing methods and procedures providing the geospatial base supporting a country’s governmental, environmental, economic, and social activities. In general, the SDI framework consists of the integration of various elements including standards, policies, networks, data, and end users and application areas. The transformation of previously paper-based map data into a digital format, the emergence of GIS, and the Internet and a host of online applications (e.g., environmental impact analysis, navigation, applications of VGI data, governmental efficiency drives) have led to huge leaps forward in SDI development. However, SDI progress can be held back by numerous challenges, both technical and non-technical. The paper outlines these challenges from the perspective of the country of Iraq, where there is an absence of a clear direction towards efficient SDI operation and a lack of knowledge for establishing and managing effective SDI. These challenges could be met by considering and resolving generic issues, identified by the experiences of other nations, by researchers, and by organisations. These issues are investigated and assessed by means of a questionnaire survey and interviews, directed towards important participants in the field of SDI development in the country. The results present the SDI issues in order of relevance to assist developers and users in solving potential SDI and data integration problems within Iraq.
This research aims at making a comparative survey between the dry season in (2017-2018) and the wet season (2018-2019) in Iraq concerning the variation of rainfall and pressure systems responsible for such a difference. In this paper, seven climatological stations have been selected: Mosul, Kirkuk, Khanaqin, Baghdad, Rutba, Diwaniyah and Basra. Results have shown that the first category of rainfall of the two seasons has recorded a higher number of rainy days in comparison with the second and third categories with a total of 274 day in a dry season and 403 day of a wet season. Further, the total amount of the annual continuous rain is higher than the total of thunderstorms in a dry season as well as in the
... Show MoreSoil is a crucial component of environment. Total soil analysis may give information about possible enrichment of the soil with heavy metals. Heavy metals, potentially contaminate soils, may have been dumped on the ground. chromium, nickel and cadmium,
Background :The cotton factories have difference steps, spinning and weaving are van important parts of the factories. Cotton industry workers are exposed to various hazards in the different departments of textile factories. The major health problems associated with cotton dust are respiratory problems. Cotton workers display an excess of lung function abnormalities when compared to a community control population.
Aim of Study: This study assessed the effect of exposure to cotton dust in spinning and weaving workers on the lung function in Iraq, by measuring Forced Vital Capacity (FVC),Forced Expiratory Volume in the first second(FEV1), FEV1 ∕ FVC Ratio, and Forced Expiratory Flow 50%(FEF50%),with varying degree of reduction in lung
Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le
... Show MoreThe tourism industry has undergone exponential transformation, reshaped by online travel agencies (OTAs), shifting consumer preferences, and technological advancements. Established OTAs like TripAdvisor and Travelocity face pressures to adapt their strategies to capitalize on these disruptive landscape changes. This research involves a comparative analysis examining the key challenges confronting TripAdvisor and Travelocity, with a focus on opportunities to leverage artificial intelligence (AI) in enhancing personalization and the traveler experience. The study utilizes publicly available data on the companies and academic literature on AI innovation diffusion. Findings reveal that while TripAdvisor has actively developed AI-based trip plan
... Show MoreThis research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg
... Show MoreThe research aims at measuring the impact of visual media on the development of the tourism services sector, which is a field study for the public. It aims at determining the impact of visual media on tourism sector development, clarifying the concept of visual media and its functions and studying the role of media in the development of tourism culture among the public. For a sample of the employees of the University of Baghdad, consisting of (120) male and female. A questionnaire was prepared for this purpose consisting of (21) questions distributed to the sample. The data were analyzed and the hypotheses were tested using the statistical program spss to unload the results and calculate the frequencies, percentages and correlati
... Show MoreHuman 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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