A Geographic Information System (GIS) is a computerized database management system for accumulating, storage, retrieval, analysis, and display spatial data. In general, GIS contains two broad categories of information, geo-referenced spatial data and attribute data. Geo-referenced spatial data define objects that have an orientation and relationship in two or three-dimensional space, while attribute data is qualitative data that can be counted for recording and analysis. The main aim of this research is to reveal the role of GIS technology in the enhancement of bridge maintenance management system components such as the output results, and make it more interpretable through dynamic colour coding and more sophisticated visualization techniques than the conventional tabular data format. To achieve the main objective of this research, two study areas have been chosen: the old constructionbridge (Al-Qadisiyah bridge) and the newly constructed bridge (Barboty bridge). Both of them are in Al-Muthanna city \ Iraq. The data collection process was achieved in two stages: the first stage is providing a georeferenced satellite image for each study area for the purpose of producing a two-dimensional map. The second stage includes the field surveying process by total station and level instruments. GIS have been used to create a comprehensive database (Geodatabase) for both study areas. Geostatistical analysis was carried out in which the settlement areas of both study areas were defined by producing a colour image. The statistical tables for these analyses showed that the highest decline in the elevation reached at Al-Qadisiyah bridge to 19 mm in the middle of the bridge which is coloured as a red areas. On the other hand, it was found that the highest decline in the elevation of the Barboty bridge is 16 mm in the last part of steel space which is also coloured as a red areas.
Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
... Show MoreUnder aerobic and anaerobic conditions, two laboratory-scale reactors were operated. Each reactor
was packed with 8.5 kg of shredded synthetic solid waste (less than 5 cm) that was prepared according to an
average composition of domestic solid waste in the city of Kirkuk. Using an air compressor, aerobic
conditions were created in the aerobic reactor. This study shows that the aerobic reactor was more efficient in
COD and BOD5 removal which were 97.88% and 91.25% while in case of anaerobic reactor, they were
66.53%and 19.11%, respectively.
The aim of this research is to find the impact of the efficiency of Management information systems (MIS) on the effectiveness of governmental organizations performance.
To achieve the objective of the research, the analytical descriptive method was adopted. A questionnaire was designed consisting of (35) paragraphs, and the sample consisted of (200) individual. The research attemped to answer the following question: To achieve the objective of the research, the analytical descriptive method was adopted. A questionnaire was designed consisting of (35) paragraphs, and the sample consisted of (200) individual. The research tried to answer the following question: What is the actual utilization of modern admi
... Show MoreWireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
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