Search results for: features comparison

Authors: Supriya Patibanda, Xiaopeng Gong, Krishna N. Jonnalagadda, Ralph Abrahams

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Yttria stabilized zirconia (YSZ) is used as a top coat in thermal barrier coatings in high-temperature turbine/jet engine applications. The mechanical behaviour of YSZ depends on the microstructural features like crack density and porosity, which are a result of coating method. However, experimentally ascertaining their individual effect is difficult due to the inherent challenges involved like material synthesis and handling. The current work deals with the development of a phenomenological model to replicate the tensile behavior of air plasma sprayed YSZ obtained from experiments. Initially, uniaxial tensile experiments were performed on freestanding YSZ coatings of ~300 µm thick for different crack densities and porosities. The coatings exhibited a nonlinear behavior and also a huge variation in strength values. With the obtained experimental tensile curve as a base and crack density and porosity as prime variables, a phenomenological model was developed using ABAQUS interface with new user material defined employing VUMAT sub routine. The relation between the tensile stress and the crack density was empirically established. Further, a parametric study was carried out to investigate the effect of the individual features on the non-linearity in these coatings. This work enables to generate new coating designs by varying the key parameters and predicting the mechanical properties with the help of a simulation, thereby minimizing experiments.

Keywords: crack density, finite element method, plasma sprayed coatings, VUMAT

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Authors: Jianghao Hu, Hongyu Wang

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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Mojtaba Noghabaei, Khashayar Asadi, Kevin Han

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Simultaneous Localization and Mapping (SLAM) technology has recently attracted the attention of construction companies for real-time performance monitoring. To effectively use SLAM for construction performance monitoring, SLAM results should be registered to a Building Information Models (BIM). Registring SLAM and BIM can provide essential insights for construction managers to identify construction deficiencies in real-time and ultimately reduce rework. Also, registering SLAM to BIM in real-time can boost the accuracy of SLAM since SLAM can use features from both images and 3d models. However, registering SLAM with the BIM in real-time is a challenge. In this study, a novel SLAM platform named Model-Based SLAM (MB-SLAM) is proposed, which not only provides automated registration of SLAM and BIM but also improves the localization accuracy of the SLAM system in real-time. This framework improves the accuracy of SLAM by aligning perspective features such as depth, vanishing points, and vanishing lines from the BIM to the SLAM system. This framework extracts depth features from a monocular camera’s image and improves the localization accuracy of the SLAM system through a real-time iterative process. Initially, SLAM can be used to calculate a rough camera pose for each keyframe. In the next step, each SLAM video sequence keyframe is registered to the BIM in real-time by aligning the keyframe’s perspective with the equivalent BIM view. The alignment method is based on perspective detection that estimates vanishing lines and points by detecting straight edges on images. This process will generate the associated BIM views from the keyframes' views. The calculated poses are later improved during a real-time gradient descent-based iteration method. Two case studies were presented to validate MB-SLAM. The validation process demonstrated promising results and accurately registered SLAM to BIM and significantly improved the SLAM’s localization accuracy. Besides, MB-SLAM achieved real-time performance in both indoor and outdoor environments. The proposed method can fully automate past studies and generate as-built models that are aligned with BIM. The main contribution of this study is a SLAM framework for both research and commercial usage, which aims to monitor construction progress and performance in a unified framework. Through this platform, users can improve the accuracy of the SLAM by providing a rough 3D model of the environment. MB-SLAM further boosts the application to practical usage of the SLAM.

Keywords: perspective alignment, progress monitoring, slam, stereo matching.

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Authors: Sergio Alejandro Cuevas, Catherine Etchebest, Fernando Luis Barroso Da Silva

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The flavivirus genus has several organisms responsible for generating various diseases in humans. Special in Brazil, Zika (ZIKV), Dengue (DENV) and Yellow Fever (YFV) viruses have raised great health concerns due to the high number of cases affecting the area during the last years. Diagnostic is still a difficult issue since the clinical symptoms are highly similar. The understanding of their common structural/dynamical and biomolecular interactions features and differences might suggest alternative strategies towards differential serological diagnostics and therapeutic intervention. Due to their immunogenicity, the primary focus of this study was on the ZIKV, DENV and YFV non-structural proteins 1 (NS1) protein. By means of computational studies, we calculated the main physical chemical properties of this protein from different strains that are directly responsible for the biomolecular interactions and, therefore, can be related to the differential infectivity of the strains. We also mapped the electrostatic differences at both the sequence and structural levels for the strains from Uganda to Brazil that could suggest possible molecular mechanisms for the increase of the virulence of ZIKV. It is interesting to note that despite the small changes in the protein sequence due to the high sequence identity among the studied strains, the electrostatic properties are strongly impacted by the pH which also impact on their biomolecular interactions with partners and, consequently, the molecular viral biology. African and Asian strains are distinguishable. Exploring the interfaces used by NS1 to self-associate in different oligomeric states, and to interact with membranes and the antibody, we could map the strategy used by the ZIKV during its evolutionary process. This indicates possible molecular mechanisms that can explain the different immunological response. By the comparison with the known antibody structure available for the West Nile virus, we demonstrated that the antibody would have difficulties to neutralize the NS1 from the Brazilian strain. The present study also opens up perspectives to computationally design high specificity antibodies.

Keywords: zika, biomolecular interactions, electrostatic interactions, molecular mechanisms

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

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Authors: Yongqi Dong, Zuo Zhang, Rui Fu, Li Li

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The records generated by taxicabs which are equipped with GPS devices is of vital importance for studying human mobility behavior, however, here we are focusing on taxi drivers' operation strategies between workdays and weekends temporally and spatially. We identify a group of valuable characteristics through large scale drivers' behavior in a complex metropolis environment. Based on the daily operations of 31,000 taxi drivers in New York City, we classify drivers into top, ordinary and low-income groups according to their monthly working load, daily income, daily ranking and the variance of the daily rank. Then, we apply big data analysis and visualization methods to compare the different characteristics among top, ordinary and low income drivers in selecting of working time, working area as well as strategies between workdays and weekends. The results verify that top drivers do have special operation tactics to help themselves serve more passengers, travel faster thus make more money per unit time. This research provides new possibilities for fully utilizing the information obtained from urban taxicab data for estimating human behavior, which is not only very useful for individual taxicab driver but also to those policy-makers in city authorities.

Keywords: big data, operation strategies, comparison, revenue, temporal, spatial

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Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: Lae-Jeong Park

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The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: pedestrian detection, color segmentation, false positive, feature extraction

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Authors: Keerthilatha Pai, Sakshi Kamra

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Objectives: Determining the position of the mandibular canal prior to implant placement and surgeries of the posterior mandible are important to avoid the nerve injury. The visibility of the mandibular canal varies according to the imaging modality. Although panoramic radiography is the most common, slowly cone beam computed tomography is replacing it. This study was conducted with an aim to determine and compare the visibility of superior and inferior borders of the mandibular canal in digital panoramic radiograph, reformatted panoramic radiograph and cross-sectional images of cone beam computed tomography. Study design: digital panoramic, reformatted panoramic radiograph and cross sectional CBCT images of 25 human mandibles were evaluated for the visibility of the superior and inferior borders of the mandibular canal according to a 5 point scoring criteria. Also, the canal was evaluated as completely visible, partially visible and not visible. The mean scores and visibility percentage of all the imaging modalities were determined and compared. The interobserver and intraobserver agreement in the visualization of the superior and inferior borders of the mandibular canal were determined. Results: The superior and inferior borders of the mandibular canal were completely visible in 47% of the samples in digital panoramic, 63% in reformatted panoramic and 75.6% in CBCT cross-sectional images. The mandibular canal was invisible in 24% of samples in digital panoramic, 19% in reformatted panoramic and 2% in cross-sectional CBCT images. Maximum visibility was seen in Zone 5 and least visibility in Zone 1. On comparison of all the imaging modalities, CBCT cross-sectional images showed better visibility of superior border in Zones 2,3,4,6 and inferior border in Zones 2,3,4,6. The difference was statistically significant. Conclusion: CBCT cross-sectional images were much superior in the visualization of the mandibular canal in comparison to reformatted and digital panoramic radiographs. The inferior border was better visualized in comparison to the superior border in digital panoramic imaging. The mandibular canal was maximumly visible in posterior one-third region of the mandible and the visibility decreased towards the mental foramen.

Keywords: cone beam computed tomography, mandibular canal, reformatted panoramic radiograph, visualization

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Authors: Guadalupe Fuentes-Lombardo, Manuel Carlos Vallejo-Martos, Rubén Fernández-Ortiz, Miriam Cano-Rubio

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The different ways in which companies enter foreign markets, exporting their products and direct investment and using strategic alliances or not, are influenced by a series of peculiarities specific to family businesses. In these companies, different systems, such as the family, property, and business overlap; giving them unique and specific characteristics which on occasions can enhance the development of cooperation agreements and in other situations can hinder them. Previous research has shown that these companies are more likely to enter into strategic alliances with certain specific features, and are more reluctant to take part in others in which some of the advantages of the family business are put at risk, such as control of ownership and decision-making over the company by the family, among others. These arguments show that there is a wide range of interesting aspects and peculiarities in the process of internationalization of the family business, although the research objectives of this paper focus on three in particular. Our first objective will be to discover why family businesses decide to establish or not strategic alliances in their internationalization processes in comparison with other companies that are not family owned. Secondly we will be identifying the idiosyncratic aspects of family businesses that favor or hinder the use of strategic alliances as a means of entering foreign markets. Our third and final objective will be to define the types of strategic alliance most commonly used by family businesses and the reasons why they choose these particular forms of alliance rather than others. We chose these research objectives for three main reasons. Firstly because research on this subject shows that alliances are the best way to begin the international expansion process, among other reasons because they provide the partners with different kinds of resources and capacity, so increasing the probability of successful internationalization. Secondly, because family and non-family businesses are often equipped with different types of resources and strategic alliances, offer them the chance to acquire resources less frequently found in family businesses. Thirdly, because the strengths and weaknesses of these companies could affect their decisions whether or not to use strategic alliances in their international expansion process and the success achieved in these alliances. As a result, these companies prefer to enter into cooperation agreements with conditions that do not put their specific status as family companies at risk.

Keywords: family business, internationalization, strategic alliances, olive-oil and wine industry

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression.

Keywords: image compression, radon transform, linear predictive coding (LPC), run lengthcoding (RLC), meteosat second generation (MSG)

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Authors: Laura Dembovska, Ina Pundiene, Diana Bajare

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Alkali-activated aluminium-silicate composites (AASC) can be used in the production of innovative materials with a wide range of properties and applications. AASC are associated with low CO₂ emissions; in the production process, it is possible to use industrial by-products and waste, thereby minimizing the use of a non-renewable natural resource. This study deals with the preparation of heat-resistant porous AASC based on chamotte for high-temperature applications up to 1200°C. Different fillers, aluminium scrap recycling waste as pores forming agent and alkali activation with 6M sodium hydroxide (NaOH) and potassium hydroxide (KOH) solution were used. Sodium hydroxide (NaOH) is widely used for the synthesis of AASC compared to potassium hydroxide (KOH), but comparison of using different activator for geopolymer synthesis is not well established. Changes in chemical composition of AASC during heating were identified and quantitatively analyzed by using DTA, dimension changes during the heating process were determined by using HTOM, pore microstructure was examined by SEM, and mineralogical composition of AASC was determined by XRD. Lightweight porous AASC activated with NaOH have been obtained with density in range from 600 to 880 kg/m³ and compressive strength from 0.8 to 2.7 MPa, but for AAM activated with KOH density was in range from 750 to 850 kg/m³ and compressive strength from 0.7 to 2.1 MPa.

Keywords: alkali activation, alkali activated materials, elevated temperature application, heat resistance

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Authors: J. A. Ageeva, Z. S. Zavyalova

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The article considers social media as a tool for business promotion. We analyze and compare the SMM experience in the western countries and Russia. A short review of Russian social networks are given including their peculiar features, and the main problems and perspectives of Russian SMM are described.

Keywords: social media, social networks, marketing, SMM

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Authors: H. K. G. K. D. K. Hapuhinna, R. D. Gunaratne, H. M. J. C. Pitawala

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Hydroxyapatite is a bioceramic which can be used for applications in orthopedics and dentistry due to its structural similarity with the mineral phase of mammalian bones and teeth. In this study, it was synthesized, chemically changing natural Eppawala chloroapatite mineral as a value-added product. Sol-gel approach and solid state sintering were used to synthesize products using diluted nitric acid, ethanol and calcium hydroxide under different conditions. Synthesized Eppawala hydroxyapatite powder was characterized using X-ray Fluorescence (XRF), X-ray Powder Diffraction (XRD), Fourier-transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC) in order to find out its composition, crystallinity, presence of functional groups, bonding type, surface morphology, microstructural features, and thermal dependence and stability, respectively. The XRD results reflected the formation of a hexagonal crystal structure of hydroxyapatite. Elementary composition and microstructural features of products were discussed based on the XRF and SEM results of the synthesized hydroxyapatite powder. TGA and DSC results of synthesized products showed high thermal stability and good material stability in nature. Also, FTIR spectroscopy results confirmed the formation of hydroxyapatite from apatite via the presence of hydroxyl groups. Those results coincided with the FTIR results of mammalian bones including human bones. The study concludes that there is a possibility of producing hydroxyapatite using commercially available Eppawala chloroapatite in Sri Lanka.

Keywords: dentistry, Eppawala chlorapatite, hydroxyapatite, orthopedics

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: Asma Rebaya, Kaouther Gasmi, Imen Amari, Salem Hasnaoui

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Over these last years, applications such as telecommunications, signal processing, digital communication with advanced features (Multi-antenna, equalization..) witness a rapid evaluation accompanied with an increase of user exigencies in terms of latency, the power of computation… To satisfy these requirements, the use of hardware/software systems is a common solution; where hardware is composed of multi-cores and software is represented by models of computation, synchronous data flow (SDF) graph for instance. Otherwise, the most of the embedded system designers utilize Simulink for modeling. The issue is how to simplify the c code generation, for a multi-cores platform, of an application modeled by Simulink. To overcome this problem, we propose a workflow allowing an automatic transformation from the Simulink model to the SDF graph and providing an efficient schedule permitting to optimize the number of cores and to minimize latency. This workflow goes from a Simulink application and a hardware architecture described by IP.XACT language. Based on the synchronous and hierarchical behavior of both models, the Simulink block diagram is automatically transformed into an SDF graph. Once this process is successfully achieved, the scheduler calculates the optimal cores’ number needful by minimizing the maximum density of the whole application. Then, a core is chosen to execute a specific graph task in a specific order and, subsequently, a compatible C code is generated. In order to perform this proposal, we extend Preesm, a rapid prototyping tool, to take the Simulink model as entry input and to support the optimal schedule. Afterward, we compared our results to this tool results, using a simple illustrative application. The comparison shows that our results strictly dominate the Preesm results in terms of number of cores and latency. In fact, if Preesm needs m processors and latency L, our workflow need processors and latency L'< L.

Keywords: hardware/software system, latency, modeling, multi-cores platform, scheduler, SDF graph, Simulink model, workflow

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Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: R. F. B. Gonçalves, E. N. Iwama, J. A. F. F. Rocco, K. Iha

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Propellants based on Hydroxyl Terminated Polybutadiene/Ammonium Perchlorate (HTPB/AP) are the most commonly used in most of the rocket engines used by the Brazilian Armed Forces. This work aimed at the possibility of extending its useful life (currently in 10 years) by performing kinetic-chemical analyzes of its energetic material via Differential Scanning Calorimetry (DSC) and also performing computer simulation of aging process using the software Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). Thermal analysis via DSC was performed in triplicates and in three heating ratios (5 ºC, 10 ºC, and 15 ºC) of rocket motor with 11 years shelf-life, using the Arrhenius equation to obtain its activation energy, using Ozawa and Kissinger kinetic methods, allowing comparison with manufacturing period data (standard motor). In addition, the kinetic parameters of internal pressure of the combustion chamber in 08 rocket engines with 11 years of shelf-life were also acquired, for comparison purposes with the engine start-up data.

Keywords: shelf-life, thermal analysis, Ozawa method, Kissinger method, LAMMPS software, thrust

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Authors: Mustaffa Kamal Bashar Mohd Fauzi, Puteri Shireen Jahn Kassim, Nurul Syala Abdul Latip

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It is increasingly realized that sustainability includes both a response to the climatic and cultural context of a place. To assess the cultural context, a morphological analysis of urban patterns from heritage legacies is necessary. While the climatic form is derived from an analysis of meteorological data, cultural patterns and forms must be abstracted from a typological and morphological study. This current study aims to analyzes morphological and formal elements of water-based architectural and urban design of past Islamic vernacular complexes in the hot arid regions and how a vast utilization of water was shaped and sited to act as cooling devices for an entire complex. Apart from its pleasant coolness, water can be used in an aesthetically way such as emphasizing visual axes, vividly enhancing the visual of the surrounding environment and symbolically portraying the act of purity in the design. By comparing 2 case studies based on the analysis of interactions of water features into the form, planning and morphology of 2 Islamic heritage complexes, Fatehpur Sikri (India) and Lahore Fort (Pakistan) with a focus on Shish Mahal of Lahore Fort in terms of their mass, architecture and urban planning, it is agreeable that water plays an integral role in their climatic amelioration via different methods of water conveyance system. Both sites are known for their substantial historical values and prominent for their sustainable vernacular buildings for example; the courtyard of Shish Mahal in Lahore fort are designed to provide continuous coolness by constructing various miniatures water channels that run underneath the paved courtyard. One of the most remarkable features of this system that all water is made dregs-free before it was inducted into these underneath channels. In Fatehpur Sikri, the method of conveyance seems differed from Lahore Fort as the need to supply water to the ridge where Fatehpur Sikri situated is become the major challenges. Thus, the achievement of supplying water to the palatial complexes is solved by placing inhabitable water buildings within the two supply system for raising water. The process of raising the water can be either mechanical or laborious inside the enclosed well and water rising houses. The studies analyzes and abstract the water supply forms, patterns and flows in 3-dimensional shapes through the actions of evaporative cooling and wind-induced ventilation under arid climates. Through the abstraction analytical and descriptive relational morphology of the spatial configurations, the studies can suggest the idealized spatial system that can be used in urban design and complexes which later became a methodological and abstraction tool of sustainability to suit the modern contemporary world.

Keywords: heritage site, Islamic vernacular architecture, water features, morphology, urban design

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Authors: Alireza Barari, Ahmad Abdi

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Regular body trainings cause adaption in various system in body. One of the important effect of body training is its effect on immune system. It seems that cytokines usually release after long period exercises or some exercises which cause skeletal muscular damages. If some of the cytokines which cause responses such as inflammation of cells in skeletal muscles, with manipulating of training program, it can be avoided or limited from those exercises which induct cytokines release. Ginger plant is a kind of medicinal plants which is known as a anti inflammation plant. This plant is as most precedence medicinal plants in medicine science especially in inflammation cure. The aim of the present study was the effect of selected resistance training and consumption of ginger extract on IL-1α and TNFα untrained young women. The population includes young women interested in participating in the study with the average of 30±2 years old from Abbas Abad city among which 32 participants were chosen randomly and divided into 4 four groups, resistance training (R), resistance training and ginger consumption(RG), Ginger consumption(G)and Control group(C). The training groups performed circuit resistance training at the intensity of 65-75% one repeat maximum, 3 days a week for 6 weeks. Besides resistance training, subjects were given either ginseng (5 mg/kg per day) or placebo. Prior to and 48 hours after interventions body composition was measured and blood samples were taken in order to assess serum levels of IL-1α and TNFα. Plasma levels of cytokines were measured with commercially available ELISA Kits.IL-1α kit and TNFα kit were used in this research. To demonstrate the effectiveness of the independent variable and the comparison between groups, t-test and ANOVA were used. To determine differences between the groups, the Scheffe test was used that showed significant changes in any of the variables. we observed that circuit resistance training in R and RG groups can significant decreased in weight and body mass index in untrained females (p<0.05). The results showed a significant decreased in the mean level of IL-1α levels before and after the training period in G group (p=0.046) and RG group (p=0.022). Comparison between groups also showed there was significant difference between groups R-RG and RG-C. Intergroup comparison results showed that the mean levels of TNFα before and after the training in group G (p=0.044) and RG (p=0.037), significantly decreased. Comparison between groups also showed there was significant difference between groups R–RG , R-G ,RG-C and G-C. The research shows that circuit resistance training with reducing overload method results in systemic inflammation had significant effect on IL-1α levels and TNFα. Of course, Ginger can counteract the negative effects of resistance training exercise on immune function and stability of the mast cell membrane. Considerable evidence supported the anti-inflammatory properties of ginger for several constituents, especially gingerols, shogaols, paradols, and zingerones, through decreased cytokine gene TNF α and IL-1Α expression and inhibition of cyclooxygenase 1 and 2. These established biological actions suggest that ingested ginger could block the increase in IL-1α.

Keywords: resistance training, ginger, IL-1α , TNFα

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Authors: Mustafa Hyder, Shamaila Burney, Roohi Mumtaz

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The aim of this study is to determine the consequences of silent or hidden messages and their effectiveness in deteriorating or altering our ethical norms and values. The study also focuses the repercussions of subconscious messages and possibilities of ethical diffusion in our society. The research based on the question that what are the different factors that motivate advertisers to include subliminal messages and how much these unspoken truths affecting our ethical values silently. What are the causes and effects of the subliminal messages in general and the level of ethical diffusion and its acceptance? The concept of advertising is to promote and highlight the salient features of the products and services, a company offers. Advertising is the best option nowadays to convey the related information to the consumers so that they attracted more towards the products or services proposed. The other thing advertisers concentrate, is the psychological characteristics using to persuade consumers choice. Using skills and tactics of advertising to promote a product in such a way that it creates a sensation, controversy or brand consciousness among the consumers or customers. The purpose to have increase purchase or to gain popularity in comparison to their competitors, they sometimes use such tactics and techniques, which is highly unethical and immoral for any society. These kinds of stuff used very smartly within the ads that only the conscious mind subconsciously catches the meaning of those glittery images, posters, phrases, tag lines and non-verbal clues. This study elucidates the subliminal advertising their repercussions and impact on consumer’s behaviour in our society with the help of few ads embedded subliminally and the trends of profitability. The methods used to accomplish our research are based on qualitative research along with the research articles, books and feedback from focused groups regarding the topic. The basic objective of this study was that, there is no significant change in the behaviour and attitude observed. These messages capture very short-term life on the viewer’s subconscious mind but in long run people get used to it and hence not only have the diffusion power but also has the high level of acceptance as well that reflects mostly through their social behaviours and attitudes.

Keywords: ethical diffusion, subconscious, subliminal advertising, unspoken facts

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Authors: Nawal A. Abu-Shady, Ibrahim M. I. Hamoda, Ahmed R. Z. Baghdadi, Mohammed K. Mohamed

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Background: The aim of this work was to investigate the efficacy of Transcranial Magnetic Therapy (TMT) on balance in hemiparetic stroke patients. It was conducted in outpatient clinic and in BIODEX balance system lab in Faculty of Physical Therapy, Cairo University. Subjects and Methods: Thirty hemiparetic stroke patients from both sexes represent the sample of this study. The patients' ages ranged from 45 to 55 years. They were assigned randomly into two equal groups; the study group (GA) and the control group (GB). control group treated by selected therapeutic physical therapy program. GA treated by the same program of treatment as the GB in addition to TMT. The duration of treatment was six weeks, three times weekly.day after day. The different aspects of dynamic balance (overall stability, anteroposterior stability and mediolateral stability indices) were assessed pre and post treatment objectively by Biodex balance system and clinically by Short Form of Berg Balance Scale (SFBBS) in both groups. Results: Comparison of each variable pre and post treatment in each group revealed a significant improvement in all different parameters in both groups ( p < 0.01), however comparison between post results revealed that the GA showed a high significant improvement higher than the GB in all different variables.

Keywords: stroke, TMT, SFBBS, biodex balance system

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Authors: Sujit Kumar Pradhan, Anil Kumar, Vijay Kumar

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The testing process of the software during the software development time is a crucial step as it makes the software more efficient and dependable. To estimate software’s reliability through the mean value function, many software reliability growth models (SRGMs) were developed under the assumption that operating and testing environments are the same. Practically, it is not true because when the software works in a natural field environment, the reliability of the software differs. This article discussed an SRGM comprising change-point and imperfect debugging in a simulated testing environment. Later on, we extended it in a multi-release direction. Initially, the software was released to the market with few features. According to the market’s demand, the software company upgraded the current version by adding new features as time passed. Therefore, we have proposed a generalized multi-release SRGM where change-point and imperfect debugging concepts have been addressed in a simulated testing environment. The failure-increasing rate concept has been adopted to determine the change point for each software release. Based on nine goodness-of-fit criteria, the proposed model is validated on two real datasets. The results demonstrate that the proposed model fits the datasets better. We have also discussed the optimal release time of the software through a cost model by assuming that the testing and debugging costs are time-dependent.

Keywords: software reliability growth models, non-homogeneous Poisson process, multi-release software, mean value function, change-point, environmental factors

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Authors: Rihab Idoudi, Karim Saheb Ettabaa, Basel Solaiman, Kamel Hamrouni

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Medical association rules induction is used to discover useful correlations between pertinent concepts from large medical databases. Nevertheless, ARs algorithms produce huge amount of delivered rules and do not guarantee the usefulness and interestingness of the generated knowledge. To overcome this drawback, we propose an ontology based interestingness measure for ARs ranking. According to domain expert, the goal of the use of ARs is to discover implicit relationships between items of different categories such as ‘clinical features and disorders’, ‘clinical features and radiological observations’, etc. That’s to say, the itemsets which are composed of ‘similar’ items are uninteresting. Therefore, the dissimilarity between the rule’s items can be used to judge the interestingness of association rules; the more different are the items, the more interesting the rule is. In this paper, we design a distinct approach for ranking semantically interesting association rules involving the use of an ontology knowledge mining approach. The basic idea is to organize the ontology’s concepts into a hierarchical structure of conceptual clusters of targeted subjects, where each cluster encapsulates ‘similar’ concepts suggesting a specific category of the domain knowledge. The interestingness of association rules is, then, defined as the dissimilarity between corresponding clusters. That is to say, the further are the clusters of the items in the AR, the more interesting the rule is. We apply the method in our domain of interest – mammographic domain- using an existing mammographic ontology called Mammo with the goal of deriving interesting rules from past experiences, to discover implicit relationships between concepts modeling the domain.

Keywords: association rule, conceptual clusters, interestingness measures, ontology knowledge mining, ranking

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Authors: T. Mokhele, O. Mutanga, F. Ahmed

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South Africa is one of the few countries that have stopped using the same Enumeration Areas (EAs) for census enumeration and dissemination. The advantage of this change is that confidentiality issue could be addressed for census dissemination as the design of geographic unit for collection is mainly to ensure that this unit is covered by one enumerator. The objective of this paper was to evaluate the performance of automated zone design output areas against non-zone design developed geographies using the 2001 census data, and 2011 census to some extent, as the main input. The comparison of the Automated Zone-design Tool (AZTool) census output areas with the Small Area Layers (SALs) and SubPlaces based on confidentiality limit, population distribution, and degree of homogeneity, as well as shape compactness, was undertaken. Further, SPSS was employed for validation of the AZTool output results. The results showed that AZTool developed output areas out-perform the existing official SAL and SubPlaces with regard to minimum population threshold, population distribution and to some extent to homogeneity. Therefore, it was concluded that AZTool program provides a new alternative to the creation of optimised census output areas for dissemination of population census data in South Africa.

Keywords: AZTool, enumeration areas, small areal layers, South Africa

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Authors: Nils Haglund, Svenolof Dahlgren, Maria Rastam, Peik Gustafsson, Karin Kalien

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In Sweden, like in most developed countries, there is a substantial increase of children diagnosed with autism and other conditions within the autism spectrum (ASD). The rapid increase of ASD rates stresses the importance of developing care programs to provide support and comprehensive interventions for affected families. The current observational study was conducted in order to evaluate an ongoing Comprehensive Intensive Early Intervention (CIEI) program for children with autism in southern Sweden. The change in autism symptoms among children participating in CIEI (intervention group, n=67) was compared with children who received traditional habilitation services only (comparison group, n=27). Children of parents who accepted the offered CIEI-program, constituted the intervention group, whereas children, whose parents (for some reason) were not interested in the offered CIEI-program, constituted the comparison group. The CIEI-program was individualized to each child by experienced applied behavior analysis (ABA) specialists with different backgrounds as psychologists, speech pathologists or special education teachers, in cooperation with parents and preschool staff. Due to the individualization, the intervention could vary in intensity and techniques. The intensity was calculated to 15-25 hours each week at home and the preschool altogether. Each child was assigned one 'trainer', who was often employed as a preschool teacher but could have another educational background. An agreement between supervisor- parents and preschool staff was reached to confirm the intensity and content of the CIEI- program over an approximately two-year intervention period. Symptom changes were measured as evaluation-ADOS-2-scores, total- and severity-scores, minus the corresponding baseline-scores, divided by the time between baseline and evaluation. The difference between the study-groups regarding change of ADOS-2-scores was estimated using ANCOVA. In the current study, children in the CIEI-group improved their ADOS-2-total scores between baseline and evaluation (-0.8 scores per year; 95%CI: -1.2 to -0.4), whereas no such improvement was detected in the comparison group (+0.1 scores per year; 95%CI: -0.7 to +0.9). The change difference (change in the CIEI-group vs. change in the comparison group) was statistically significant, both crude and after adjusting for possible confounders (-1.1; 95%CI -1.9 to -0.4). Children in the CIEI-group also significantly improved their ADOS-calibrated severity scores, but not significantly differently so from the comparison group. The results from the current study indicate that the CIEI program significantly improves social and communicative skills among children with autism and that children with developmental delay could benefit to a similar degree as other children. The results support earlier studies reporting on the improvement of autism symptoms after early intensive interventions. The results from observational studies are difficult to interpret, but it is nevertheless of uttermost importance to evaluate costly autism intervention programs. Such results may be of immediate importance to healthcare organizations when allocating the already strained resources to different patient groups. Albeit the obvious limitation of the current naturalistic study, the results support previous positive studies and indicate that children with autism benefit from participating in early comprehensive, intensive programs and that investments in these programs may be highly justifiable.

Keywords: autism symptoms, ADOS-scores, evaluation, intervention program

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Authors: Zill-E-Huma, Humaira Siddiqi

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This paper comprises of synthesis of thermally stable, mechanically strong polyimides. The polyimides were considered as most diverse class of polymers having unlimited applications. They were widely used as optical wave guides, in aerospace, for gas separation, as biomaterials and in electronics. Here the focus was to increase thermal stability and mechanical strength of polyimides. For this purpose two monomers were synthesized and were further polymerized via anhydrides to polyimides. The monomer diamines were synthesized by nucleophilic attack of aniline/2-fluoro aniline on hydroxy benzaldehydes. The two diamines synthesized were 3-(bis(4-aminophenyl) methyl) phenol (3OHDA) and 4-(bis(4-amino-3-fluorophenyl) methyl) phenol (2F4OHDA). These diamines were then reacted with dianhydrides to get polyimides. Two neat polyimides of both diamines with pyromellitic dianhydride (PMDA) and one neat polyimide of 4'-(Hexafluoroisopropylidene) diphthalic dianhydride (6FDA) with 3OHDA were synthesized. To compare the properties of synthesized polyimides like thermal stability, rigidity, flexibility, toughness etc. a commercial diamine oxydianiline (ODA) was used. Polyimides from oxydianiline were basically rigid. Nine different polyimide blends were synthesized from 3OHDA and commercial diamines ODA to have a better comparison of properties. TGA and mechanical testing results showed that with the increase in the percentage of 3OHDA in comparison to ODA the flexibility, toughness, strength of polyimide, thermal stability goes on increasing. So, synthesized diamines were responsible for improvement of properties of polyimides.

Keywords: diamines, dianhydrides, oxydianiline, polyimides

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Authors: Min Jee Lee, Young Sun Park, Shin Ahn, Chang Hwan Sohn, Dong Woo Seo, Jae Ho Lee, Yoon Seon Lee, Kyung Soo Lim, Won Young Kim

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Background: Acute myocardial infarction (AMI) concomitant with acute aortic syndrome (AAS) is rare but prompt recognition of concomitant AAS is crucial, especially in patients with ST-segment elevation myocardial infarction (STEMI) because misdiagnosis with early thrombolytic or anticoagulant treatment may result in catastrophic consequences. Objectives: This study investigated the clinical features of patients of STEMI concomitant with AAS that may lead to the diagnostic clue. Method: Between 1 January 2010 and 31 December 2014, 22 patients who were the initial diagnosis of acute coronary syndrome (AMI and unstable angina) and AAS (aortic dissection, intramural hematoma and ruptured thoracic aneurysm) in our emergency department were reviewed. Among these, we excluded 10 patients who were transferred from other hospital and 4 patients with non-STEMI, leaving a total of 8 patients of STEMI concomitant with AAS for analysis. Result: The mean age of study patients was 57.5±16.31 years and five patients were Standford type A and three patients were type B aortic dissection. Six patients had ST-segment elevation in anterior leads and two patients had in inferior leads. Most of the patients had acute onset, severe chest pain but no patients had dissecting nature chest pain. Serum troponin I was elevated in three patients but all patients had D-dimer elevation. Aortic regurgitation or regional wall motion abnormality was founded in four patients. However, widened mediastinum was seen in all study patients. Conclusion: When patients with STEMI have elevated D-dimer and widened mediastinum, concomitant AAS may have to be suspected.

Keywords: aortic dissection, myocardial infarction, ST-segment, d-dimer

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Authors: Khin Mar Yee, Mu Mu Than, Kyi Lint, Aye Aye Oo, Chan Mya Hmway, Khin Zar Chi Winn

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The dynamic changes of Land Use and Land Cover (LULC) changes in Yangon have generally resulted the improvement of human welfare and economic development since the last twenty years. Making map of LULC is crucially important for the sustainable development of the environment. However, the exactly data on how environmental factors influence the LULC situation at the various scales because the nature of the natural environment is naturally composed of non-homogeneous surface features, so the features in the satellite data also have the mixed pixels. The main objective of this study is to the calculation of accuracy based on change detection of LULC changes by Support Vector Machines (SVMs). For this research work, the main data was satellite images of 1996, 2006 and 2015. Computing change detection statistics use change detection statistics to compile a detailed tabulation of changes between two classification images and Support Vector Machines (SVMs) process was applied with a soft approach at allocation as well as at a testing stage and to higher accuracy. The results of this paper showed that vegetation and cultivated area were decreased (average total 29 % from 1996 to 2015) because of conversion to the replacing over double of the built up area (average total 30 % from 1996 to 2015). The error matrix and confidence limits led to the validation of the result for LULC mapping.

Keywords: land use and land cover change, change detection, image processing, support vector machines

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Authors: Somaye Zare

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The critical beam radius is a significant factor that predicts the behavior of the laser beam in the plasma, so if the laser beam radius is adequately greater in comparison to it, the beam will experience stable focusing on the plasma; otherwise, the beam will diverge after entering into the plasma. In this work, considering the paraxial approximation and moment theories, the localization of a relativistic laser beam in thermal quantum plasma is investigated. Using the dielectric function obtained in the quantum hydrodynamic model, the mathematical equation for the laser beam width parameter is attained and solved numerically by the fourth-order Runge-Kutta method. The results demonstrate that the stouter focusing effect is occurred in the moment theory compared to the paraxial approximation. Besides, similar to the two theories, with increasing Fermi temperature, plasma density, and laser intensity, the oscillation rate of the beam width parameter growths and focusing length reduces which means improving the focusing effect. Furthermore, it is understood that behaviors of the critical laser radius are different in the two theories, in the paraxial approximation, the critical radius after a minimum value is enhanced with increasing laser intensity, but in the moment theory, with increasing laser intensity, the critical radius decreases until it becomes independent of the laser intensity.

Keywords: laser localization, quantum plasma, paraxial approximation, moment theory, quantum hydrodynamic model

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