Search results for: depth images
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5566

Search results for: depth images

4636 Effect of Various Tillage Systems on Soil Compaction

Authors: Sushil Kumar, Mukesh Jain, Vijaya Rani, Vinod Kumar

Abstract:

The prime importance of tillage is that it prepares the land where the seed easily germinate and later the plant can well establish. Using different types of equipments driven manually or by powered, machines make the soil suitable to place the seeds into the desirable depth. Moreover, tillage loosens the compacted layers. Heavy equipment and tillage implements can cause damage to the soil structure. Effect of various tillage methods on soil compaction was studied in Rabi season of 2013-14 at village Ladwa, Hisar, Haryana (India). The experiments studied the effect of six tillage treatments i.e. no tillage or zero tillage (T1), tillage with rotavator (T2), disc harrow (T3), rotavator + sub soiler (T4), disc harrow + sub soiler (T5) and power harrow (T6) on soil compaction. Soil compaction was measured before tillage and after sowing at 0, 30, 60 and 90 days after sowing. No change in soil resistance was recorded before and after no tillage treatment. Maximum soil resistance was found in zero tillage followed by disc harrow up to 150 mm soil depth. Minimum soil resistance was found in rotavator immediately after the tillage treatment. However, the soil resistance approached the same level as it had been before the tillage after the soil strata where the implement cannot reach.

Keywords: tillage, no tillage, rotavator, subsoiler, compaction

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4635 Ensemble of Deep CNN Architecture for Classifying the Source and Quality of Teff Cereal

Authors: Belayneh Matebie, Michael Melese

Abstract:

The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

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4634 From Data Processing to Experimental Design and Back Again: A Parameter Identification Problem Based on FRAP Images

Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

Abstract:

FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

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4633 Architecture Performance-Related Design Based on Graphic Parameterization

Authors: Wenzhe Li, Xiaoyu Ying, Grace Ding

Abstract:

Architecture plane form is an important consideration in the design of green buildings due to its significant impact on energy performance. The most effective method to consider energy performance in the early design stages is parametric modelling. This paper presents a methodology to program plane forms using MATLAB language, generating 16 kinds of plane forms by changing four designed parameters. DesignBuilder (an energy consumption simulation software) was proposed to simulate the energy consumption of the generated planes. A regression mathematical model was established to study the relationship between the plane forms and their energy consumption. The main finding of the study suggested that there was a cubic function relationship between the depth-ratio of U-shaped buildings and energy consumption, and there is also a cubic function relationship between the width-ratio and energy consumption. In the design, the depth-ratio of U-shaped buildings should not be less than 2.5, and the width-ratio should not be less than 2.

Keywords: graphic parameterization, green building design, mathematical model, plane form

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4632 Gynocentrism and Self-Orientalization: A Visual Trend in Chinese Fashion Photography

Authors: Zhen Sun

Abstract:

The study adopts the method of visual social semiotics to analyze a sample of fashion photos that were recently published in Chinese fashion magazines that target towards both male and female readers. It identifies a new visual trend in fashion photography, which is characterized by two features. First, the photos represent young, confident, and stylish female models with lower-class sloppy old men. The visual inharmony between the sexually desirable women and the aged men has suggested an impossibly accomplished sexuality and eroticism. Though the women are still under the male gaze, they are depicted as unreachable objects of voyeurism other than sexual objects subordinated to men. Second, the represented people are usually put in the backdrop of tasteless or vulgar Chinese town life, which is congruent with the images of men but makes the modern city girls out of place. The photographers intentionally contrast the images of women with that of men and with the background, which implies an imaginary binary division of modern Orientalism and the photographers’ self-orientalization strategy. Under the theoretical umbrella of neoliberal postfeminism, this study defines a new kind of gynocentric stereotype in Chinese fashion photography, which challenges the previous observations on gender portrayals in fashion magazines.

Keywords: fashion photography, gynocentrism, neoliberal postfeminism, self-orientalization

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4631 Comparison of an Anthropomorphic PRESAGE® Dosimeter and Radiochromic Film with a Commercial Radiation Treatment Planning System for Breast IMRT: A Feasibility Study

Authors: Khalid Iqbal

Abstract:

This work presents a comparison of an anthropomorphic PRESAGE® dosimeter and radiochromic film measurements with a commercial treatment planning system to determine the feasibility of PRESAGE® for 3D dosimetry in breast IMRT. An anthropomorphic PRESAGE® phantom was created in the shape of a breast phantom. A five-field IMRT plan was generated with a commercially available treatment planning system and delivered to the PRESAGE® phantom. The anthropomorphic PRESAGE® was scanned with the Duke midsized optical CT scanner (DMOS-RPC) and the OD distribution was converted to dose. Comparisons were performed between the dose distribution calculated with the Pinnacle3 treatment planning system, PRESAGE®, and EBT2 film measurements. DVHs, gamma maps, and line profiles were used to evaluate the agreement. Gamma map comparisons showed that Pinnacle3 agreed with PRESAGE® as greater than 95% of comparison points for the PTV passed a ± 3%/± 3 mm criterion when the outer 8 mm of phantom data were discluded. Edge artifacts were observed in the optical CT reconstruction, from the surface to approximately 8 mm depth. These artifacts resulted in dose differences between Pinnacle3 and PRESAGE® of up to 5% between the surface and a depth of 8 mm and decreased with increasing depth in the phantom. Line profile comparisons between all three independent measurements yielded a maximum difference of 2% within the central 80% of the field width. For the breast IMRT plan studied, the Pinnacle3 calculations agreed with PRESAGE® measurements to within the ±3%/± 3 mm gamma criterion. This work demonstrates the feasibility of the PRESAGE® to be fashioned into anthropomorphic shape, and establishes the accuracy of Pinnacle3 for breast IMRT. Furthermore, these data have established the groundwork for future investigations into 3D dosimetry with more complex anthropomorphic phantoms.

Keywords: 3D dosimetry, PRESAGE®, IMRT, QA, EBT2 GAFCHROMIC film

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4630 Analysis of Facial Expressions with Amazon Rekognition

Authors: Kashika P. H.

Abstract:

The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

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4629 Wetting-Drying Cycles Effect on Piles Embedded in a Very High Expansive Soil

Authors: Bushra Suhail, Laith Kadim

Abstract:

The behavior of model piles embedded in a very high expansive soil was investigated, a specially manufactured saturation-drying tank was used to apply three cycles of wetting and drying to the expansive soil surrounding the model straight shaft and under reamed piles, the relative movement of the piles with respect to the soil surface was recorded with time, also the exerted uplift pressure of the piles due to soil swelling was recorded. The behavior of unloaded straight shaft and under reamed piles was investigated. Two design charts were presented for straight shaft and under reamed piles one for the required pile depth for zero upward movement due to soil swelling, the other for the required pile depth to exert zero uplift pressure when the soil swells. Under reamed piles showed a decrease in upward movement of 20% to 40%, and an uplift pressure decrease of 10% to 30%.

Keywords: expansive soil, piles, under reamed, structural and geotechnical engineering

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4628 Role of Television in Constructing Gender for Young Women

Authors: Bhavna Negi

Abstract:

Several studies highlight the significance of media in constructing realities around us. According to Forbes magazine the demand of televisions has increased several times in the developing nations. A recent survey reveals that 112 million Indian households have a television, with 61 percent accessing cable. The space and visibility of television has enormously grown over the last decade in Indian homes. This small box has indeed taken a large place in their daily routines. The multi channel viewing and TRPs puzzle the Indian audience. This medium creates and constructs social images and roles which form internal representation about societal functioing. According to National Council of Applied Economic Research about twenty seven percent Indian literate youth watches TV for recreation. The present study finds about the role of television and its impact on young college going women with reference to family based serials shown on television. It is interesting to see how young women perceive the popular family soaps and define norms, roles and spaces for a woman and a man. The paper further examines the subtle messages given to young women through television serials. It draws insights into the relationship between the contemporary Indian women and the images conceptualized and communicated on television.

Keywords: media, women, gender, social roles

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4627 Automated Ultrasound Carotid Artery Image Segmentation Using Curvelet Threshold Decomposition

Authors: Latha Subbiah, Dhanalakshmi Samiappan

Abstract:

In this paper, we propose denoising Common Carotid Artery (CCA) B mode ultrasound images by a decomposition approach to curvelet thresholding and automatic segmentation of the intima media thickness and adventitia boundary. By decomposition, the local geometry of the image, its direction of gradients are well preserved. The components are combined into a single vector valued function, thus removes noise patches. Double threshold is applied to inherently remove speckle noise in the image. The denoised image is segmented by active contour without specifying seed points. Combined with level set theory, they provide sub regions with continuous boundaries. The deformable contours match to the shapes and motion of objects in the images. A curve or a surface under constraints is developed from the image with the goal that it is pulled into the necessary features of the image. Region based and boundary based information are integrated to achieve the contour. The method treats the multiplicative speckle noise in objective and subjective quality measurements and thus leads to better-segmented results. The proposed denoising method gives better performance metrics compared with other state of art denoising algorithms.

Keywords: curvelet, decomposition, levelset, ultrasound

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4626 Physical Properties Characterization of Shallow Aquifer and Groundwater Quality Using Geophysical Method Based on Electrical Resistivity Tomography in Arid Region, Northeastern Area of Tunisia: A Study Case of Smar Aquifer

Authors: Nesrine Frifita

Abstract:

In recent years, serious interest in underground sources has led to more intensive studies of depth, thickness, geometry and properties of aquifers. Geophysical method is the common technique used in discovering the subsurface. However, determining the exact location of groundwater in subsurface layers is one of problems that needs to be resolved. While the biggest problem is the quality of the groundwater which suffers from pollution risk especially with water shortage in arid regions under a remarkable climate change. The present study was conducted using electrical resistivity tomography at Jeffara coastal area in Southeast Tunisia to image the potential shallow aquifer and studying their physical properties. The purpose of this study is to understand the characteristics and depth of the Smar aquifer. Therefore, it can be used as a reference in groundwater drilling in order to guide the farmers and to improve the living of the inhabitants of nearby cities. The use of the Winner-Schlumberger array for data acquisition is suitable to obtain a deeper profile in areas with homogeneous layers. For that, six electrical resistivity profiles were carried out in Smar watershed using 72 electrodes with 4 and 5 m spacing. The resistivity measurements were carefully interpreted by a least-square inversion technique using the RES2DINV program. Findings show that the Smar aquifer has about 31 m thickness and it extends to 36.5 m depth in the downstream area of Oued Smar. The defined depth and geometry of Smar aquifer indicate that the sedimentary cover thins toward the coast, and the Smar shallow aquifer becomes deeper toward the West. While the resistivity values show a significant contrast even reaching < 1 Ωm in ERT1, this resistivity value can be related to the saline water that foretells a risk of pollution and bad groundwater quality. The ERT1 geoelectrical model defines an unsaturated zone, while under ERT3 site, the geoelectrical model presents a saturated zone, which reflect a low resistivity values indicate the locally surface water coming from the nearby Office of the National Sanitation Utility (ONAS) that can be a source of recharge of the studied shallow aquifer and more deteriorate the groundwater quality in this region.

Keywords: electrical resistivity tomography, groundwater, recharge, smar aquifer, southeastern tunisia

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4625 Using 3D Satellite Imagery to Generate a High Precision Canopy Height Model

Authors: M. Varin, A. M. Dubois, R. Gadbois-Langevin, B. Chalghaf

Abstract:

Good knowledge of the physical environment is essential for an integrated forest planning. This information enables better forecasting of operating costs, determination of cutting volumes, and preservation of ecologically sensitive areas. The use of satellite images in stereoscopic pairs gives the capacity to generate high precision 3D models, which are scale-adapted for harvesting operations. These models could represent an alternative to 3D LiDAR data, thanks to their advantageous cost of acquisition. The objective of the study was to assess the quality of stereo-derived canopy height models (CHM) in comparison to a traditional LiDAR CHM and ground tree-height samples. Two study sites harboring two different forest stand types (broadleaf and conifer) were analyzed using stereo pairs and tri-stereo images from the WorldView-3 satellite to calculate CHM. Acquisition of multispectral images from an Unmanned Aerial Vehicle (UAV) was also realized on a smaller part of the broadleaf study site. Different algorithms using two softwares (PCI Geomatica and Correlator3D) with various spatial resolutions and band selections were tested to select the 3D modeling technique, which offered the best performance when compared with LiDAR. In the conifer study site, the CHM produced with Corelator3D using only the 50-cm resolution panchromatic band was the one with the smallest Root-mean-square deviation (RMSE: 1.31 m). In the broadleaf study site, the tri-stereo model provided slightly better performance, with an RMSE of 1.2 m. The tri-stereo model was also compared to the UAV, which resulted in an RMSE of 1.3 m. At individual tree level, when ground samples were compared to satellite, lidar, and UAV CHM, RMSE were 2.8, 2.0, and 2.0 m, respectively. Advanced analysis was done for all of these cases, and it has been noted that RMSE is reduced when the canopy cover is higher when shadow and slopes are lower and when clouds are distant from the analyzed site.

Keywords: very high spatial resolution, satellite imagery, WorlView-3, canopy height models, CHM, LiDAR, unmanned aerial vehicle, UAV

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4624 Evaluation of SCS-Curve Numbers and Runoff across Varied Tillage Methods

Authors: Umar Javed, Kristen Blann, Philip Adalikwu, Maryam Sahraei, John McMaine

Abstract:

The soil conservation service curve number (SCS-CN) is a widely used method to assess direct runoff depth based on specific rainfall events. “Actual” estimated runoff depth was estimated by subtracting the change in soil moisture from the depth of precipitation for each discrete rain event during the growing seasons from 2021 to 2023. Fields under investigation were situated in a HUC-12 watershed in southeastern South Dakota selected for a common soil series (Nora-Crofton complex and Moody-Nora complex) to minimize the influence of soil texture on soil moisture. Two soil moisture probes were installed from May 2021 to October 2023, with exceptions during planting and harvest periods. For each field, “Textbook” CN estimates were derived from the TR-55 table based on corresponding mapped land use land cover LULC class and hydrologic soil groups from web soil survey maps. The TR-55 method incorporated HSG and crop rotation within the study area fields. These textbook values were then compared to actual CN values to determine the impact of tillage practices on CN and runoff. Most fields were mapped as having a textbook C or D HSG, but the HSG of actual CNs was that of a B or C hydrologic group. Actual CNs were consistently lower than textbook CNs for all management practices, but actual CNs in conventionally tilled fields were the highest (and closest to textbook CNs), while actual CNs in no-till fields were the lowest. Preliminary results suggest that no-till practice reduces runoff compared to conventional till. This research highlights the need to use CNs that incorporate agricultural management to more accurately estimate runoff at the field and watershed scale.

Keywords: curve number hydrology, hydrologic soil groups, runoff, tillage practices

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4623 Effect of Salvadora Persica Gel on Clinical and Microbiological Parameters of Chronic Periodontitis

Authors: Tahira Hyder, Saima Quraeshi, Zohaib Akram

Abstract:

Salvadora Persica (SP) is known to have anti-inflammatory, antioxidant, anti-coagulant and anti-bacterial properties that may provide therapeutic benefits in the treatment of chronic periodontitis (CP). The current clinical trial was designed to investigate the clinical and anti-microbial effects of SP gel as an adjunct to scaling and root planning (SRP) in subjects with generalized CP. Sixty-six subjects with CP were randomized allocated into two groups: SRP + SP gel (test group) and SRP only (control group). Clinical parameters (periodontal pocket depth, gingival recession, clinical attachment level, bleeding score and plaque score) were recorded at baseline before SRP and at 6 weeks. At baseline and 6 weeks subgingival plaque samples were collected and periodontopathogen Porphyromonas Gingivalis (Pg) quantified using Real-time Polymerase Chain Reaction (RT-PCR). Both therapies reduced the mean periodontal pocket depth (PPD), plaque score (PS) and bleeding score (BOP) and improved the mean clinical attachment level (CAL) between baseline and 6 weeks. In subjects receiving adjunctive SP gel a statistically significant improvement was observed in BOP at follow-up compared to control group (15.01±3.47% and 22.81±6.81% respectively, p=0.001), while there was no statistically significant difference in periodontal pocket depth, gingival recession, clinical attachment level and plaque score between both groups. The test group displayed significantly greater Pg reduction compared to the control group after 6 weeks. The current study establishes that local delivery of SP gel into periodontal pocket in CP stimulated a significant reduction in bacteria Pg level and an improvement in gingival health, as evident from a reduced bleeding score, when used as an adjunct to SRP.

Keywords: miswak, scaling and root planing, porphyromonas gingivalis, chronic periodontitis

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4622 Rapid Monitoring of Earthquake Damages Using Optical and SAR Data

Authors: Saeid Gharechelou, Ryutaro Tateishi

Abstract:

Earthquake is an inevitable catastrophic natural disaster. The damages of buildings and man-made structures, where most of the human activities occur are the major cause of casualties from earthquakes. A comparison of optical and SAR data is presented in the case of Kathmandu valley which was hardly shaken by 2015-Nepal Earthquake. Though many existing researchers have conducted optical data based estimated or suggested combined use of optical and SAR data for improved accuracy, however finding cloud-free optical images when urgently needed are not assured. Therefore, this research is specializd in developing SAR based technique with the target of rapid and accurate geospatial reporting. Should considers that limited time available in post-disaster situation offering quick computation exclusively based on two pairs of pre-seismic and co-seismic single look complex (SLC) images. The InSAR coherence pre-seismic, co-seismic and post-seismic was used to detect the change in damaged area. In addition, the ground truth data from field applied to optical data by random forest classification for detection of damaged area. The ground truth data collected in the field were used to assess the accuracy of supervised classification approach. Though a higher accuracy obtained from the optical data then integration by optical-SAR data. Limitation of cloud-free images when urgently needed for earthquak evevent are and is not assured, thus further research on improving the SAR based damage detection is suggested. Availability of very accurate damage information is expected for channelling the rescue and emergency operations. It is expected that the quick reporting of the post-disaster damage situation quantified by the rapid earthquake assessment should assist in channeling the rescue and emergency operations, and in informing the public about the scale of damage.

Keywords: Sentinel-1A data, Landsat-8, earthquake damage, InSAR, rapid damage monitoring, 2015-Nepal earthquake

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4621 Diagnosis of Alzheimer Diseases in Early Step Using Support Vector Machine (SVM)

Authors: Amira Ben Rabeh, Faouzi Benzarti, Hamid Amiri, Mouna Bouaziz

Abstract:

Alzheimer is a disease that affects the brain. It causes degeneration of nerve cells (neurons) and in particular cells involved in memory and intellectual functions. Early diagnosis of Alzheimer Diseases (AD) raises ethical questions, since there is, at present, no cure to offer to patients and medicines from therapeutic trials appear to slow the progression of the disease as moderate, accompanying side effects sometimes severe. In this context, analysis of medical images became, for clinical applications, an essential tool because it provides effective assistance both at diagnosis therapeutic follow-up. Computer Assisted Diagnostic systems (CAD) is one of the possible solutions to efficiently manage these images. In our work; we proposed an application to detect Alzheimer’s diseases. For detecting the disease in early stage we used the three sections: frontal to extract the Hippocampus (H), Sagittal to analysis the Corpus Callosum (CC) and axial to work with the variation features of the Cortex(C). Our method of classification is based on Support Vector Machine (SVM). The proposed system yields a 90.66% accuracy in the early diagnosis of the AD.

Keywords: Alzheimer Diseases (AD), Computer Assisted Diagnostic(CAD), hippocampus, Corpus Callosum (CC), cortex, Support Vector Machine (SVM)

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4620 Least-Square Support Vector Machine for Characterization of Clusters of Microcalcifications

Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

Abstract:

Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: clusters of microcalcifications, ductal carcinoma in situ, least-square support vector machine, particle swarm optimization

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4619 High-Resolution Computed Tomography Imaging Features during Pandemic 'COVID-19'

Authors: Sahar Heidary, Ramin Ghasemi Shayan

Abstract:

By the development of new coronavirus (2019-nCoV) pneumonia, chest high-resolution computed tomography (HRCT) has been one of the main investigative implements. To realize timely and truthful diagnostics, defining the radiological features of the infection is of excessive value. The purpose of this impression was to consider the imaging demonstrations of early-stage coronavirus disease 2019 (COVID-19) and to run an imaging base for a primary finding of supposed cases and stratified interference. The right prophetic rate of HRCT was 85%, sensitivity was 73% for all patients. Total accuracy was 68%. There was no important change in these values for symptomatic and asymptomatic persons. These consequences were besides free of the period of X-ray from the beginning of signs or interaction. Therefore, we suggest that HRCT is a brilliant attachment for early identification of COVID-19 pneumonia in both symptomatic and asymptomatic individuals in adding to the role of predictive gauge for COVID-19 pneumonia. Patients experienced non-contrast HRCT chest checkups and images were restored in a thin 1.25 mm lung window. Images were estimated for the existence of lung scratches & a CT severity notch was allocated separately for each patient based on the number of lung lobes convoluted.

Keywords: COVID-19, radiology, respiratory diseases, HRCT

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4618 Shaft Friction of Bored Pile Socketed in Weathered Limestone in Qatar

Authors: Thanawat Chuleekiat

Abstract:

Socketing of bored piles in rock is always seen as a matter of debate on construction sites between consultants and contractors. The socketing depth normally depends on the type of rock, depth at which the rock is available below the pile cap and load carrying capacity of the pile. In this paper, the review of field load test data of drilled shaft socketed in weathered limestone conducted using conventional static pile load test and dynamic pile load test was made to evaluate a unit shaft friction for the bored piles socketed in weathered limestone (weak rock). The borehole drilling data were also reviewed in conjunction with the pile test result. In addition, the back-calculated unit shaft friction was reviewed against various empirical methods for bored piles socketed in weak rock. The paper concludes with an estimated ultimate unit shaft friction from the case study in Qatar for preliminary design.

Keywords: piled foundation, weathered limestone, shaft friction, rock socket, pile load test

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4617 Flood-Induced River Disruption: Geomorphic Imprints and Topographic Effects in Kelantan River Catchment from Kemubu to Kuala Besar, Kelantan, Malaysia

Authors: Mohamad Muqtada Ali Khan, Nor Ashikin Shaari, Donny Adriansyah bin Nazaruddin, Hafzan Eva Bt Mansoor

Abstract:

Floods play a key role in landform evolution of an area. This process is likely to alter the topography of the earth’s surface. The present study area, Kota Bharu is very prone to floods extends from upstream of Kelantan River near Kemubu to the downstream area near Kuala Besar. These flood events which occur every year in the study area exhibit a strong bearing on river morphological set-up. In the present study, three satellite imageries of different time periods have been used to manifest the post-flood landform changes. The pre-processing of the images such as subset, geometric corrections and atmospheric corrections were carried-out using ENVI 4.5 followed by the analysis processes. Twenty sets of cross sections were plotted using software Erdas 9.2, ERDAS and ArcGis 10 for the all three images. The results show a significant change in the length of the cross section which suggest that the geomorphological processes play a key role in carving and shaping the river banks during the floods.

Keywords: flood induced, geomorphic imprints, Kelantan river, Malaysia

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4616 Tidal Current Behaviors and Remarkable Bathymetric Change in the South-Western Part of Khor Abdullah, Kuwait

Authors: Ahmed M. Al-Hasem

Abstract:

A study of the tidal current behavior and bathymetric changes was undertaken in order to establish an information base for future coastal management. The average velocity for tidal current was 0.46 m/s and the maximum velocity was 1.08 m/s during ebb tide. During spring tides, maximum velocities range from 0.90 m/s to 1.08 m/s, whereas maximum velocities vary from 0.40 m/s to 0.60 m/s during neap tides. Despite greater current velocities during flood tide, the bathymetric features enhance the dominance of the ebb tide. This can be related to the abundance of fine sediments from the ebb current approaching the study area, and the relatively coarser sediment from the approaching flood current. Significant bathymetric changes for the period from 1985 to 1998 were found with dominance of erosion process. Approximately 96.5% of depth changes occurred within the depth change classes of -5 m to 5 m. The high erosion processes within the study area will subsequently result in high accretion processes, particularly in the north, the location of the proposed Boubyan Port and its navigation channel.

Keywords: bathymetric change, Boubyan island, GIS, Khor Abdullah, tidal current behavior

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4615 Groundwater Investigation Using Resistivity Method and Drilling for Irrigation during the Dry Season in Lwantonde District, Uganda

Authors: Tamale Vincent

Abstract:

Groundwater investigation is the investigation of underground formations to understand the hydrologic cycle, known groundwater occurrences, and identify the nature and types of aquifers. There are different groundwater investigation methods and surface geophysical method is one of the groundwater investigation more especially the Geoelectrical resistivity Schlumberger configuration method which provides valuable information regarding the lateral and vertical successions of subsurface geomaterials in terms of their individual thickness and corresponding resistivity values besides using surface geophysical method, hydrogeological and geological investigation methods are also incorporated to aid in preliminary groundwater investigation. Investigation for groundwater in lwantonde district has been implemented. The area project is located cattle corridor and the dry seasonal troubles the communities in lwantonde district of which 99% of people living there are farmers, thus making agriculture difficult and local government to provide social services to its people. The investigation was done using the Geoelectrical resistivity Schlumberger configuration method. The measurement point is located in the three sub-counties, with a total of 17 measurement points. The study location is at 0025S, 3110E, and covers an area of 160 square kilometers. Based on the results of the Geoelectrical information data, it was found two types of aquifers, which are open aquifers in depth ranging from six meters to twenty-two meters and a confined aquifer in depth ranging from forty-five meters to eighty meters. In addition to the Geoelectrical information data, drilling was done at an accessible point by heavy equipment in the Lwakagura village, Kabura sub-county. At the drilling point, artesian wells were obtained at a depth of eighty meters and can rise to two meters above the soil surface. The discovery of artesian well is then used by residents to meet the needs of clean water and for irrigation considering that in this area most wells contain iron content.

Keywords: artesian well, geoelectrical, lwantonde, Schlumberger

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4614 Design Study for the Rehabilitation of a Retaining Structure and Water Intake on Site

Authors: Yu-Lin Shen, Ming-Kuen Chang

Abstract:

In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

Procedia PDF Downloads 350
4613 Evaluation of IMERG Performance at Estimating the Rainfall Properties through Convective and Stratiform Rain Events in a Semi-Arid Region of Mexico

Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

Abstract:

Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

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4612 Content-Based Image Retrieval Using HSV Color Space Features

Authors: Hamed Qazanfari, Hamid Hassanpour, Kazem Qazanfari

Abstract:

In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods.

Keywords: content-based image retrieval, color difference histogram, efficient features selection, entropy, correlation

Procedia PDF Downloads 250
4611 Delineating Subsurface Linear Features and Faults Under Sedimentary Cover in the Bahira Basin Using Integrated Gravity and Magnetic Data

Authors: M. Lghoul, N. El Goumi, M. Guernouche

Abstract:

In order to predict the structural and tectonic framework of the Bahira basin and to have a 3D geological modeling of the basin, an integrated multidisciplinary work has been conducted using gravity, magnetic and geological data. The objective of the current study is delineating the subsurfacefeatures, faults, and geological limits, using airborne magnetic and gravity data analysis of the Bahira basin. To achieve our goal, we have applied different enhanced techniques on magnetic and gravity data: power spectral analysis techniques, reduction to pole (RTP), upward continuation, analytical signal, tilt derivative, total horizontal derivative, 3D Euler deconvolutionand source parameter imagining. The major lineaments/faults trend are: NE–SW, NW-SE, ENE–WSW, and WNW–ESE. The 3D Euler deconvolution analysis highlighted a number of fault trend, mainly in the ENE-WSW, WNW-ESE directions. The depth tothe top of the basement sources in the study area ranges between 200 m, in the southern and northern part of the Bahira basin, to 5000 m located in the Eastern part of the basin.

Keywords: magnetic, gravity, structural trend, depth to basement

Procedia PDF Downloads 133
4610 Integrating Wound Location Data with Deep Learning for Improved Wound Classification

Authors: Mouli Banga, Chaya Ravindra

Abstract:

Wound classification is a crucial step in wound diagnosis. An effective classifier can aid wound specialists in identifying wound types with reduced financial and time investments, facilitating the determination of optimal treatment procedures. This study presents a deep neural network-based classifier that leverages wound images and their corresponding locations to categorize wounds into various classes, such as diabetic, pressure, surgical, and venous ulcers. By incorporating a developed body map, the process of tagging wound locations is significantly enhanced, providing healthcare specialists with a more efficient tool for wound analysis. We conducted a comparative analysis between two prominent convolutional neural network models, ResNet50 and MobileNetV2, utilizing a dataset of 730 images. Our findings reveal that the RestNet50 outperforms MovileNetV2, achieving an accuracy of approximately 90%, compared to MobileNetV2’s 83%. This disparity highlights the superior capability of ResNet50 in the context of this dataset. The results underscore the potential of integrating deep learning with spatial data to improve the precision and efficiency of wound diagnosis, ultimately contributing to better patient outcomes and reducing healthcare costs.

Keywords: wound classification, MobileNetV2, ResNet50, multimodel

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4609 Optimized and Secured Digital Watermarking Using Entropy, Chaotic Grid Map and Its Performance Analysis

Authors: R. Rama Kishore, Sunesh

Abstract:

This paper presents an optimized, robust, and secured watermarking technique. The methodology used in this work is the combination of entropy and chaotic grid map. The proposed methodology incorporates Discrete Cosine Transform (DCT) on the host image. To improve the imperceptibility of the method, the host image DCT blocks, where the watermark is to be embedded, are further optimized by considering the entropy of the blocks. Chaotic grid is used as a key to reorder the DCT blocks so that it will further increase security while selecting the watermark embedding locations and its sequence. Without a key, one cannot reveal the exact watermark from the watermarked image. The proposed method is implemented on four different images. It is concluded that the proposed method is giving better results in terms of imperceptibility measured through PSNR and found to be above 50. In order to prove the effectiveness of the method, the performance analysis is done after implementing different attacks on the watermarked images. It is found that the methodology is very strong against JPEG compression attack even with the quality parameter up to 15. The experimental results are confirming that the combination of entropy and chaotic grid map method is strong and secured to different image processing attacks.

Keywords: digital watermarking, discreate cosine transform, chaotic grid map, entropy

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4608 MITOS-RCNN: Mitotic Figure Detection in Breast Cancer Histopathology Images Using Region Based Convolutional Neural Networks

Authors: Siddhant Rao

Abstract:

Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: breast cancer, mitotic count, machine learning, convolutional neural networks

Procedia PDF Downloads 224
4607 GPU Accelerated Fractal Image Compression for Medical Imaging in Parallel Computing Platform

Authors: Md. Enamul Haque, Abdullah Al Kaisan, Mahmudur R. Saniat, Aminur Rahman

Abstract:

In this paper, we have implemented both sequential and parallel version of fractal image compression algorithms using CUDA (Compute Unified Device Architecture) programming model for parallelizing the program in Graphics Processing Unit for medical images, as they are highly similar within the image itself. There is several improvements in the implementation of the algorithm as well. Fractal image compression is based on the self similarity of an image, meaning an image having similarity in majority of the regions. We take this opportunity to implement the compression algorithm and monitor the effect of it using both parallel and sequential implementation. Fractal compression has the property of high compression rate and the dimensionless scheme. Compression scheme for fractal image is of two kinds, one is encoding and another is decoding. Encoding is very much computational expensive. On the other hand decoding is less computational. The application of fractal compression to medical images would allow obtaining much higher compression ratios. While the fractal magnification an inseparable feature of the fractal compression would be very useful in presenting the reconstructed image in a highly readable form. However, like all irreversible methods, the fractal compression is connected with the problem of information loss, which is especially troublesome in the medical imaging. A very time consuming encoding process, which can last even several hours, is another bothersome drawback of the fractal compression.

Keywords: accelerated GPU, CUDA, parallel computing, fractal image compression

Procedia PDF Downloads 336