Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG researchers and specialist with an easy and fast method of handling the EEG big data.
For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers
... Show MoreIntroduction: Elite football performance hinges on rapid tactical decision-making under physical and cognitive strain. While peripheral fatigue’s effects on motor output are well documented, the neurophysiological markers of mental fatigue and their impact on in-game decision making remain underexplored. Objective: To determine how EEG-derived central fatigue indices—frontal theta power and the theta/alpha ratio—relate to tactical decision accuracy and speed in elite football players. Methodology: Twenty male national-level footballers (age 22.4 ± 2.1 years; ≥ 5 years’ experience) completed the Yo-Yo Intermittent Recovery Test Level 1 while wearing an 8-channel dry-electrode frontal EEG headset. Frontal theta
... Show MoreThe textile industries play a prominent role in reviving the national economy, but they are currently suffering from several problems, including the high costs of their activities, the low quality of their production processes, and accordingly, the hexagonal diffraction approach came to help analyze production activities to determine which of them are the most expensive and do not have a benefit or cost greater than Its benefit as a result of waste and losses that accompany its implementation. And by applying to the Iraqi mechanical carpet factory, the research reached several conclusions, the most important of which is the presence of several sources of waste and loss, such as activities and operations that do not add value, whi
... Show MoreThis paper studies the investment project evaluation under the condition of uncertainty. Evaluation of investment project under risk and uncertainty is possible to be carried out through application of various methods and techniques. The best known methods are : Risk-adjusted discount rate , certainty equivalent method , Sensitivity analysis and Simulation method The objective of this study is using the sensitivity analysis in evaluation Glass Bottles project in Anbar province under the condition of risk and uncertainty.
After applying sensitivity analysis we found that the glass bottles project sensitive to the following factors (cash flow, the cost of investment, and the pro
... Show MoreThis research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio
... Show MoreThis study aims to estimate the accuracy of digital elevation models (DEM) which are created with exploitation of open source Google Earth data and comparing with the widely available DEM datasets, Shuttle Radar Topography Mission (SRTM), version 3, and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. The GPS technique is used in this study to produce digital elevation raster with a high level of accuracy, as reference raster, compared to the DEM datasets. Baghdad University, Al Jadriya campus, is selected as a study area. Besides, 151 reference points were created within the study area to evaluate the results based on the values of RMS.Furthermore, th
... Show MoreModeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem
... Show MoreSome problems want to be solved in image compression to make the process workable and more efficient. Much work had been done in the field of lossy image compression based on wavelet and Discrete Cosine Transform (DCT). In this paper, an efficient image compression scheme is proposed, based on a common encoding transform scheme; It consists of the following steps: 1) bi-orthogonal (tab 9/7) wavelet transform to split the image data into sub-bands, 2) DCT to de-correlate the data, 3) the combined transform stage's output is subjected to scalar quantization before being mapped to positive, 4) and LZW encoding to produce the compressed data. The peak signal-to-noise (PSNR), compression ratio (CR), and compression gain (CG) measures were used t
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