International Journal of Research and Engineering
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New Insights of Background Estimation and Region Localization
Get PDFSubtraction of background in a crowded scene is a crucial and challenging task of monitoring the surveillance systems. Because of the similarity between the foreground object and the background, it is known that the background detection and moving foreground objects is difficult. Most of the previous works emphasize this field but they cannot distinguish the foreground from background due to the challenges of gradual or sudden illumination changes, high-frequencies background objects of motion changes, background geometry changes and noise. After getting the foreground objects, segmentation is need to localize the objects region. Image segmentation is a useful tool in many areas, such as object recognition, image processing, medical image analysis, 3D reconstruction, etc. In order to provide a reliable foreground image, a carefully estimated background model is needed. To tackle the issues of illumination changes and motion changes, this paper establishes an effective new insight of background subtraction and segmentation that accurately detect and segment the foreground people. The scene background is investigates by a new insight, namely Mean Subtraction Background Estimation (MS), which identifies and modifies the pixels extracted from the difference of the background and the current frame. Unlike other works, the first frame is calculated by MS instead of taking the first frame as an initial background. Then, this paper make the foreground segmentation in the noisy scene by foreground detection and then localize these detected areas by analyzing various segmentation methods. Calculation experiments on the challenging public crowd counting dataset achieve the best accuracy than state-of-the-art results. This indicates the effectiveness of the proposed work
Low Enriched Uranium based Nuclear Rocket Propulsion Technology: Mars Exploration Mission
Get PDFMany space agencies like NASA, SPACE-X have promised to send humans into the red planet in future. So, considering their project of mars colonization, nuclear rocket propulsion would be the better option. Replacing chemical rockets by nuclear rockets may reduce the mission duration and also can reduce the mass of the propellant used. In chemical rockets, propellant releases energy through combustion but in case of nuclear rockets, propellant i.e. hydrogen is heated up in controlled fission reaction in nuclear reactor inside the rocket engine. Specific impulse of the nuclear rocket is greater than chemical rocket. This helps in providing gigantic thrust as a result mission duration is decreased. The challenging parameter of increasing specific impulse is solved by maximizing specific impulse which is done by increasing the exhaust core temperature. The fuel is selected in such a way so that the exhaust temperature would be obtained. The (U, Zr) C –graphite fuel is selected because it has high uranium density and melting point is equivalent to exhaust core temperature which is sufficient enough to enhance the reactivity of the fissile material and thus to increase the rocket performance. A mathematical analysis shows that the percentage of mass of propellant used in mars mission will be lesser than the chemical rockets because the specific impulse is expected to be more in nuclear propulsion. The specific impulse obtained from the CFD Analysis of rocket nozzle is 979 sec with exit velocity of 9604m/s
Plant Leaf Disease Detection and Classification using Image Processing
Get PDFMyanmar is an agricultural country and then crop production is one of the major sources of earning. So, more than half of our population depends on agriculture for livelihood. Due to the factors like diseases, pest attacks and sudden change in the weather condition, the productivity of the crop decreases. Automatic detection of plant diseases is essential to automatically detect the symptoms of diseases as early as they appear on the growing stage. This paper proposed a methodology for the analysis and detection of plant leaf diseases using digital image processing techniques. The experimental results demonstrate that the proposed system can successfully detect and classify four major plant leaves diseases: Bacterial Blight and Cercospora Leaf Spot, Powdery Mildew and Rust
Myanmar Warning Board Recognition System
Get PDFIn any country, warning text is described on the signboards or wallpapers to follow by everybody. This paper present Myanmar character recognition from various warning text signboards using block based pixel count and eight-directions chain code. Character recognition is the process of converting a printed or typewritten or handwritten text image file into editable and searchable text file. In this system, the characters on the warning signboard images are recognized using the hybrid eight direction chain code features and 16-blocks based pixel count features. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation, vertically cropping method and bounding box is used for connected component character segmentation. In the classification step, the performance accuracy is measured by two ways such as KNN (K’s Nearest Neivour) classifier and feature based approach of template matching on 150 warning text signboard images
Determining the Impact of TQM Principles on Strategic Performance
Get PDFThis research attempts to determine the impact of the principles of TQM on the strategic performance of the universities. This topic is of relatively important because TQM principles prioritize strategic performance indicators for the current research sample and its contribution to enhancing the University's viability, growth and competitiveness. Based on the above, a research model was developed to determine the nature of the relationship and the impact between TQM principles and strategic performance. The data was collected through a questionnaire distributed to 32 member of Cihan University Faculties. The data was analyzed by SPSS Software V.23
Evaluation of Story Drift under Pushover Analysis in Reinforced Concrete Moment Frames
Get PDFThe accurate prediction of story drift and its distribution along the height of the structure is very critical for seismic performance evaluation since the non-structural damage is directly related to the story drift. Pushover analysis is an accepted method for seismic evaluation of existing structures as well as performance-based design of new structures. Regarding assumptions and limitations in pushover analysis, there is a need to estimate the error that would affect the accuracy of story drift. This paper investigates the validity of pushover analysis to predict story drift under different lateral load patterns. For this purpose, several reinforced concrete moment frames with different heights were analyzed using pushover and nonlinear time history analyses and obtained results were compared to evaluate the error level
Multivariate Analysis of Stream Sediment Geochemical Data for Gold Exploration in Delijan, Iran
Get PDFMuteh is a major Iranian gold mine that is located in Delijan, within in the Sanandaj-Sirjan metallogenic zone. Previously, the gold mineralization in Muteh was interpreted to be formed in Precambrian. However, recent geological models propose younger age, i.e., late Eocene, for the gold mineralization, therefore, the geologic units of age and older than late Eocene can be considered as targets for gold exploration. The objective of this paper is to investigate Muteh type gold mineralization potential in the area with respect to the new geological models. Statistical analysis of 644 stream sediment samples was used to determine anomalous concentrations Au and elemental correlations of Au geochemical pathfinders. Using the factor analysis, an eight-factor model was established for the stream sediment geochemical data explaining 74.76% of the total variance. Factor 4 was found to be representative of Al-Ca-Na-K-P, which defines the lithological variation in the data. Factor 6 represents the variation of Pb-Ag-Sb-Ba-Tl, which is related to the hydrothermal mineralization. The factor 7 includes Au-S-Mo and is representative of regional geochemical patterns of gold. The correlation of Au with S and Mo signifies the inclusions of Au in pyrite minerals of Muteh mine. Factor 7 specifies three exploration targets. Moreover, the fourth prospective area representing significant geochemical signatures for gold mineralization was not detected in factor analysis. The results show that data reduction techniques, such as factor analysis, have great potential for geochemical applications; however, it is essential to perform careful analysis in addition to using these techniques. Factor analysis highlights the regional geochemical patterns and may slight the smaller subsystems
Method and Apparatus for a Differential Localized Microscopy System Based on Position Sensitive Detector
Get PDFA precise measurement of position using a Position Sensitive Detector (PSD) is fundamental in mitigating the geometric error factors that are caused by the pincushion-type distortion of these sensors. These errors can be addressed by implementing a differential localized method to significantly reduce signal to noise ratio (SNR) in PSD and the microscopy system. The differential method based on Time difference of Arrival (TDoA) is proposed and implemented in this research. The simulation and the actual results of the system further confirm the significant improvement in accuracy and precision of the system
Optimal Energy Storage Sizing in Photovoltaic and Wind Hybrid Power System Meeting Demand-Side Management Program in Viet Nam
Get PDFThis paper proposes a new method to determine optimal energy storage sizing in photovoltaic and wind hybrid power generation systems. These generations are placed in a scheme of three blocks to forecast, measure, dispatch/control and distribute power flows in whole system to meet requirements of the demand-side management program in Viet Nam. Data about electric load power, power of solar irradiance, ambient temperature, wind speed and other weather conditions must be forecasted in a high accuracy. An algorithm to determine the optimal sizing is designed basing on forecasting data, constraints, the relation of quantities in whole system and the capability to charge/discharge energy of energy storage. The optimal sizing in this research helps to rearrange load diagrams that compensates deficient energy completely in stages having high and medium price levels. It can be applied at each bus to reduce cost for buying electricity from electric power system. The new proposal is illustrated by simulation results in a case study carried out by MATLAB 2017a
Hybrid Power Systems for Commercial Application in Kenya
Get PDFThe cost, availability and stability of power are parameters that greatly define the quality of energy supplied by a generating system. A hybrid power system with different sources of energy must be properly designed in order to capitalize on the positive features of the deployed resources. Hybrid power system optimization is a process that allows for deliberate attainment of desired output from a power system. In this paper, a learning institution, East African School of Aviation (EASA) was selected as a case study for investigating the outcome of harnessing local energy resources to serve a commercial consumer in Kenya. A cost competitive hybrid power system was obtained through Simulation and optimization processes