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Enhancing Spatial Accuracy of OpenStreetMap Data: A Geometric Approach
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OpenStreetMap (OSM), recognised for its current and readily accessible spatial database, frequently serves regions lacking precise data at the necessary granularity. Global collaboration among OSM contributors presents challenges to data quality and uniformity, exacerbated by the sheer volume of input and indistinct data annotation protocols. This study presents a methodological improvement in the spatial accuracy of OSM datasets centred over Baghdad, Iraq, utilising data derived from OSM services and satellite imagery. An analytical focus was placed on two geometric correction methods: a two-dimensional polynomial affine transformation and a two-dimensional polynomial conformal transformation. The former involves twelve coefficients for adjustment, while the latter encompasses six. Analysis within the selected region exposed variances in positional accuracy, with distinctions evident between Easting (E) and Northing (N) coordinates. Empirical results indicated that the conformal transformation method reduced the Root Mean Square Error (RMSE) by 4.434 meters in the amended OSM data. Contrastingly, the affine transformation method exhibited a further reduction in total RMSE by 4.053 meters. The deployment of these proposed techniques substantiates a marked enhancement in the geometric fidelity of OSM data. The refined datasets have significant applications, extending to the representation of roadmaps, the analysis of traffic flow, and the facilitation of urban planning initiatives.

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Publication Date
Thu Dec 18 2025
Journal Name
Journal Of Optical Communications
Enhancing of underwater wireless optical communication system based on single photon detector
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Abstract<p>This work investigates a simulation model of an underwater optical wireless communication (UOWC) system. Several water scenarios are considered: Harbor I (HA-I), Harbor II (HA-II), Coastal Ocean (CO), Clear Ocean (CL), and Pure Sea (PU). A laser diode (LD) with modulation schemes (NRZ-OOK) transmits data at various speeds of 2.5 Gbps, 5 Gbps, and 10 Gbps. To identify the optical signal, a single-photon detection (SPD), APD and PIN photodiodes are utilized. The analytical evaluation of the performance is executed using Q-factor, received power and bit error rate (BER). According to the results, the PU achieved an underwater distance of 35.5 m, 35 m, 34.5 m, for data tran</p> ... Show More
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Publication Date
Fri Jun 16 2017
Journal Name
Computers
Enhancing BER Performance Limit of BCH and RS Codes Using Multipath Diversity
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Publication Date
Sun Dec 14 2025
Journal Name
Online Journal Of Art And Design
Intellectual Approach in Corona Pandemic Designs
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The intellectual approach is manifested in communicating information and achieving it in the best ways and methods, and that the philosophy of the approach falls under the sociological dimensions on the one hand and on the other hand is linked to the visual language presented by graphic design through an informative visual discourse that includes behavior and prophecy as two main axes for integration in presenting social, guiding and indicative educational topics to complete the picture of the achievement. In front of the recipient, the goals of the design were achieved in addressing the topic (Corona Pandemic), which took a social and cultural turn, and also included politics and economics, and went beyond the limits

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Publication Date
Thu Oct 01 2015
Journal Name
Engineering And Technology Journal
Genetic Based Optimization Models for Enhancing Multi- Document Text Summarization
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Publication Date
Sun Dec 01 2019
Journal Name
Al-nahrain Journal Of Science
Enhancing Sparse Adjacency Matrix for Community Detection in Large Networks
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Publication Date
Sat Oct 01 2016
Journal Name
2016 6th International Conference On Information Communication And Management (icicm)
Enhancing case-based reasoning retrieval using classification based on associations
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Publication Date
Fri Jan 01 2010
Journal Name
2010 Second International Conference On Computer Research And Development
Per-Priority Flow Control (PPFC) for Enhancing Metro Ethernet QoS
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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Engineering
Practical comparation of the accuracy and speed of YOLO, SSD and Faster RCNN for drone detection
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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Tue Jun 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Land Use/Cover Change Analysis Using Remote Sensing Data: A Case Study, Zhengzhou Area, Henan Province, China
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In the last two decades, arid and semi-arid regions of China suffered rapid changes in the Land Use/Cover Change (LUCC) due to increasing demand on food, resulting from growing population. In the process of this study, we established the land use/cover classification in addition to remote sensing characteristics. This was done by analysis of the dynamics of (LUCC) in Zhengzhou area for the period 1988-2006. Interpretation of a laminar extraction technique was implied in the identification of typical attributes of land use/cover types. A prominent result of the study indicates a gradual development in urbanization giving a gradual reduction in crop field area, due to the progressive economy in Zhengzhou. The results also reflect degradati

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