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Development prediction algorithm of vehicle travel time based traffic data
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This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera images and later distinguished vehicles are assigned to the looking at route segment so instantaneous and current velocities are calculated. All data were effectively processed and visualized using both MATLAB and Python programming language and its libraries.

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Publication Date
Mon Mar 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Bionics-Based Approach for Object Tracking to Implement in Robot Applications
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In this paper, an approach for object tracking that is inspired from human oculomotor system is proposed and verified experimentally. The developed approach divided into two phases, fast tracking or saccadic phase and smooth pursuit phase. In the first phase, the field of the view is segmented into four regions that are analogue to retinal periphery in the oculomotor system. When the object of interest is entering these regions, the developed vision system responds by changing the values of the pan and tilt angles to allow the object lies in the fovea area and then the second phase will activate. A fuzzy logic method is implemented in the saccadic phase as an intelligent decision maker to select the values of the pan and tilt angle based

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Publication Date
Sun Dec 24 2017
Journal Name
Iraqi Journal Of Laser
All Fiber Chemical Liquids Refractive Index Sensor Based on Multimode Interference
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A simple all optical fiber sensor based on multimode interference (MMI) for chemical liquids sensing was designed and fabricated. A segment of coreless fiber (CF) was spliced between two single mode fibers to buildup single mode-coreless-single mode (SCS) structure. Broadband source and optical signal analyzer were connected to the ends of SCS structure. De-ionized water, acetone, and n-hexane were used to test the performance of the sensor. Two influence factors on the sensitivity namely the length and the diameter of the CF were investigated. The obtained maximum sensitivity was at n-hexane at 340.89 nm/RIU (at a wavelength resolution of the optical spectrum analyzer of 0.02 nm) when the diameter of the CF reduced from 125 μm to 60 μ

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Engineering
Self-Repairing Technique Based on Microcapsules for Cementitious Composites- A Review
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Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Design and Implementation ofICT-Based Recycle-Rewarding System for Green Environment
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This paper proposes a collaborative system called Recycle Rewarding System (RRS), and focuses on the aspect of using information communication technology (ICT) as a tool to promote greening. The idea behind RRS is to encourage recycling collectors by paying them for earning points. In doing so, both the industries and individuals reap the economical benefits of such system. Finally, and more importantly, the system intends to achieve a green environment for the Earth. This paper discusses the design and implementation of the RRS, involves: the architectural design, selection of components, and implementation issues. Five modules are used to construct the system, namely: database, data entry, points collecting and recording, points reward

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Priority Based Transmission Rate Control with Neural Network Controller in WMSNs
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Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia appli

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Publication Date
Tue Apr 11 2023
Journal Name
Sensors
EEG Signal Complexity Measurements to Enhance BCI-Based Stroke Patients’ Rehabilitation
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The second leading cause of death and one of the most common causes of disability in the world is stroke. Researchers have found that brain–computer interface (BCI) techniques can result in better stroke patient rehabilitation. This study used the proposed motor imagery (MI) framework to analyze the electroencephalogram (EEG) dataset from eight subjects in order to enhance the MI-based BCI systems for stroke patients. The preprocessing portion of the framework comprises the use of conventional filters and the independent component analysis (ICA) denoising approach. Fractal dimension (FD) and Hurst exponent (Hur) were then calculated as complexity features, and Tsallis entropy (TsEn) and dispersion entropy (DispEn) were assessed as

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Publication Date
Mon Jul 15 2019
Journal Name
Iet Microwaves, Antennas & Propagation
Hilbert metamaterial printed antenna based on organic substrates for energy harvesting
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Abstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to

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Publication Date
Sun May 01 2016
Journal Name
2016 Al-sadeq International Conference On Multidisciplinary In It And Communication Science And Applications (aic-mitcsa)
Landsat-8 (OLI) classification method based on tasseled cap transformation features
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Sun Oct 25 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
EFFECT OF EXERCISES USING DIFFERENT RESISTORS IN THE DEVELOPMENT OF THE SPECIAL STRENGTH OF THE ARMS AND THE COMPLETION OF JAVELIN FOR THE ATHLETES OF THE SCHOOL SPECIALIZED ATHLETICS
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Athletics are different from other games as a competition between individuals to show their competence and physical ability to achieve new record numbers in the various activities and various between the boards, jumping and throwing and each type of these activities in particular performance so found the researcher to find the method of training resistors in the development of special power and achievement In the effectiveness of javelin, where the researchers chose the sample of the athletes from the specialized school of athletics to effectively throw the spear at the ages of 15-17 years and carried out the tests of the research, which includes the strength of the speed of the arms and explosive power and The various resistance exercise

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