Search results for: lung computed tomography (CT) images

Authors: J. Urban, Á. S. Botella, L. E. Robaina, A. Bárta, P. Souček, P. Císař, Š. Papáček, L. M. Domínguez

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Skin coloration in fish is of great physiological, behavioral and ecological importance and can be considered as an index of animal welfare in aquaculture as well as an important quality factor in the retail value. Currently, in order to compare color in animals fed on different diets, biochemical analysis, and colorimetry of fished, mildly anesthetized or dead body, are very accurate and meaningful measurements. The noninvasive method using digital images of the fish body was developed as a standalone application. This application deals with the computation burden and memory consumption of large input files, optimizing piece wise processing and analysis with the memory/computation time ratio. For the comparison of color distributions of various experiments and different color spaces (RGB, CIE L*a*b*) the comparable semi-equidistant binning of multi channels representation is introduced. It is derived from the knowledge of quantization levels and Freedman-Diaconis rule. The color calibrations and camera responsivity function were necessary part of the measurement process.

Keywords: color distribution, fish skin color, piecewise transformation, object to background segmentation

Procedia PDF Downloads 259

Authors: Larry V. Aceres, Jesryl B. Paulite, Emelie M. Pelicano, J. B. Anciano, J. A. Esteban

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Enhancing the population of beneficial arthropods under less diverse agroecosystem is the most sought by many researchers and plant growers. This strategy was done through the establishment of pintoi peanut, Arachis pintoi as live mulch or cover crop in pummelo orchard of the University of Southeastern Philippines (USeP), Mabini, Compostela Valley Province, Philippines. This study was conducted to compare and compute population dynamics and diversity of beneficial arthropods in pummelo in with and without Arachis pintoi cover crop. Data collections were done for the 12-month period (from June 2013 to May 2014) at the pummelo orchard of USeP Mabini Campus, COMVAL Province, Philippines and data were analyzed using the Independent Samples T-Test to compare the effect of the presence and absence of Arachis pintoi on beneficial arthropods incidence in pummelo orchard. Moreover, diversity and family richness analyses were computed using the Margalef’s diversity index for family richness; the Shannon index of general diversity and the evenness index; and the Simpson index of dominance. Results revealed numerically and statistically higher density of important beneficial arthropods such as microhymenopterans, macrohymenopterans, spiders, tachinid flies and ground beetles were recorded in pummelo orchard with Arachis pintoi than from without Arachis pintoi cover crop for the 12-month observation period. Further, the result of the study revealed the high family richness and diversity index with more or less even distribution of individuals within the family and low dominance index were documented in pummelo with Arachis pintoi cover crop than from pummelo without Arachis pintoi cover crop. The study revealed that planting A. pintoi in pummelo orchard could enhance natural enemy populations.

Keywords: Arachis pintoi, cover crop, beneficial arthropods, pummelo

Procedia PDF Downloads 321

Authors: Humaira Mujeeb, Farah Qadir

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The present study aimed to explore the association between interpersonal relationship and postpartum depression with a special focus on gender of the infant among women in Gilgit, Gilgit-Baltistan, Pakistan. The research was quantitative in nature. It was a correlation study with a cross-sectional study design. The target population was women between six weeks to six months after the delivery of a baby. The sample size of 158 women has been computed by using G*Power (3.0.10 version). The sample was taken through quota sampling technique which was used to gather data according to the specifically predefined groups (79 women with female infants and 79 women with male infants). The sample was selected non-randomly according to the fixed quota. A protocol which had demographic and interpersonal relationship variables alongside with the Urdu version Edinburgh postnatal depression scale was used to collect the relevant data. The data was analyzed by using SPSS 16.0 software package. A statistically significant association between the attachment with husband in women who had a female infant and postpartum depression has been found. The association between the husband’s emotional and physical support in women who had a female infant and postpartum depression had also been found significant. In case of women with a male infant, the association between support of in-laws and postpartum depression is statistically significant. An association between the violence/discrimination based on the basis of infant's gender in women who had a female infant and postpartum depression is also found. These findings points out that when studying the correlates of postpartum depression, it is imperative to carry out an analysis in the context of gender by considering gender of the infant especially in societies where strict gender preferences exists.

Keywords: infant, gender, attachment, husband, in-laws, support, violence, discrimination, Edinburgh postnatal depression scale, Gilgit, Pakistan

Procedia PDF Downloads 595

Authors: H. Farokhi, A. Bahadoran

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This paper is focused on the absorbance and magnetic properties of a novel nanocomposite based on conducting polymer, carbon black and barium hexaferrite in epoxy resin on the E-glass fibre substrate. The highly conductive nanocomposite was provided by in-situ polymerization of aniline in the presence of carbon black (C) and barium hexaferrite (BaFe12O19) as electromagnetic absorbance material. The structure, morphology, and magnetic properties of samples were characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM) and vibrating sample magnetometer (VSM). SEM images showed the uniformly coated PAni on the surface of carbon black and barium hexaferrite. XRD peaks also verified the presence of carbon black and barium hexaferrite in the nanocomposite. The microwave characteristics determined from the magnetic and dielectric properties of the elastomeric composites obtained from scattering data by fitting the samples in a waveguide, where measured in the frequency in X-band frequency range, the range of 8 to 12 GHz. The reflection losses were evaluated to be less than −5dB over the whole X-band frequency (8–12 GHz) for the thickness of 1.4mm.

Keywords: conductive polymer, magnetic materials, capacitance, electrochemical cell

Procedia PDF Downloads 247

Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

Procedia PDF Downloads 115

Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

Procedia PDF Downloads 89

Authors: Supaporn Wimonchailerk

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This research aims to study how to design and create the media to promote Thai cuisine. The study used qualitative research methods by using in-depth interview 3 key informants who have experienced in the production of food or cooking shows in television programs with an aspect of acknowledging Thai foods. The results showed that visual presentation is divided into four categories. First, the light meals should be presented in details via the close-up camera with lighting to make the food look more delicious. Then the curry presentation should be arranged a clear and crisp light focus on a colorful curry paste. Besides the vision of hot steam floating from the plate and a view of curry spread on steamed rice can call great attentions. Third, delivering good appearances of the fried or spicy foods, the images must allow the audiences to see the shine of the coat covering the texture of the food and the colorful of the ingredients. Fourth, the presentation of sweets is recommended to focus on details of food design, composition, and layout.

Keywords: media production, television, promote, Thai cuisine

Procedia PDF Downloads 236

Authors: S. Sudhakar, Geetha Manjunath, Siva Teja Kakileti, Himanshu Madhu

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Diagnosis of breast cancer at early stages has seen better clinical and survival outcomes. Survival rates in developing countries like India are very low due to accessibility and affordability issues of screening tests such as Mammography. In addition, Mammography is not much effective in younger women with dense breasts. This leaves a gap in current screening methods. Thermalytix is a new technique for detecting breast abnormality in a non-contact, non-invasive way. It is an AI-enabled computer-aided diagnosis solution that automates interpretation of high resolution thermal images and identifies potential malignant lesions. The solution is low cost, easy to use, portable and is effective in all age groups. This paper presents the results of a retrospective comparative analysis of Thermalytix over Mammography and Clinical Breast Examination for breast cancer screening. Thermalytix was found to have better sensitivity than both the tests, with good specificity as well. In addition, Thermalytix identified all malignant patients without palpable lumps.

Keywords: breast cancer screening, radiology, thermalytix, artificial intelligence, thermography

Procedia PDF Downloads 291

Authors: Okuyade Ighoroje Wilson Ata

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Magneto-hydrodynamic mixed convective chemically reacting fluid flow through two parallel vertical plates channel with Hall, radiation, and chemical reaction effects are examined. The fluid is assumed to be chemically reactive, electrically conducting, magnetically susceptible, viscous, incompressible, and Newtonian; the plates are porous, electrically conductive, and heated to a high-temperature regime to generate thermal rays. The flow system is highly interactive, such that cross/double diffusion is present. The governing equations are partial differential equations transformed into ordinary differential equations using similarity transformation and solved by the method of Homotopy Perturbation. Expressions for the concentration, temperature, velocity, Nusselt number, Sherwood number, and Wall shear stress are obtained, computed, and presented graphically and tabularly. The analysis of results shows, amongst others, that an increase in the Raleigh number increases the main velocity and temperature but decreases the concentration. More so, an increase in chemical reaction rate increases the main velocity, temperature, rate of heat transfer from the terminal plate, the rate of mass transfer from the induced plate, and Wall shear stress on both the induced and terminal plates, decreasing the concentration, and the mass transfer rate from the terminal plate. Some of the obtained results are benchmarked with those of existing literature and are in consonance.

Keywords: chemical reaction, hall effect, magneto-hydrodynamic, radiation, vertical plates channel

Procedia PDF Downloads 76

Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

Procedia PDF Downloads 460

Authors: Imana Shahrin Tania, Mohammad Ali

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The present study reports the synthesis, characterization and application of nano-sized zinc-oxide (ZnO) particles on a cotton fabric surface. The aim of the investigations is to impart the antimicrobial activity on textile cloth. Nanoparticle is synthesized by wet chemical method from zinc sulphate and sodium hydroxide. SEM (scanning electron micrograph) images are taken to demonstrate the surface morphology of nanoparticles. XRD analysis is done to determine the crystal size of the nanoparticle. With the conformation of nanoformation, the cotton woven fabric is treated with ZnO nanoparticle by mechanical thermo-fixation (pad-dry-cure) technique. To increase the wash durability of nano treated fabric, an acrylic binder is used as a fixing agent. The treated fabric shows up to 90% bacterial reduction for S. aureus (Staphylococcus aureus) and 87% for E. coli (Escherichia coli) which is appreciable for bacteria protective clothing.

Keywords: nanoparticle, zinc oxide, cotton fabric, antibacterial activity, binder

Procedia PDF Downloads 131

Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi

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The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.

Keywords: 3D reconstruction, light pattern structure, texture mapping, museum

Procedia PDF Downloads 465

Authors: Celso Afonso Klein Jr., Henrique Cantarelli, Fernando Portella, Keiichi Hosaka, Eduardo Reston, Fabricio Collares, Roberto Zimmer

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TTo evaluate the influence of preheating self-adhesive cement at 39ºC on cell migration, cytotoxicity and degree of conversion. RelyX U200, Set PP and MaxCem Elite were subjected to a degree of conversion analysis (FTIR-ATR). For the cytotoxicity analysis, extracts (24 h and 7 days) were placed in contact with NIH/3T3 cells. For cell migration, images were captured of each sample until the possible closure of the cleft occurred. In the results of the degree of conversion, preheating did not improve the conversion of cement. For the MTT, preheating did not improve the results within 24 hours. However, it generated positive results within 7 days for the Set PP resin cement. For cell migration, high rates of cell death were found in all groups. It is concluded that preheating at 39ºC caused a positive effect only in increasing the cell viability of the Set PP resin cement and that both materials analyzed are highly cytotoxic.

Keywords: dental cements, resin cements, degree of conversion, cytotoxicity, cell migration assays

Procedia PDF Downloads 70

Authors: Mohamad Kassab, Amal El Fallah Seghrouchni, Frederic Barbaresco, Raed Abu Zitar

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Detecting objects such as drones is a challenging task as their relative size and maneuvering capabilities deceive machine learning models and cause them to misclassify drones as birds or other objects. In this work, we investigate applying several deep learning techniques to benchmark real data sets of flying drones. A deep learning paradigm is proposed for the purpose of mitigating the complexity of those systems. The proposed paradigm consists of a hybrid between the AdderNet deep learning paradigm and the Single Shot Detector (SSD) paradigm. The goal was to minimize multiplication operations numbers in the filtering layers within the proposed system and, hence, reduce complexity. Some standard machine learning technique, such as SVM, is also tested and compared to other deep learning systems. The data sets used for training and testing were either complete or filtered in order to remove the images with mall objects. The types of data were RGB or IR data. Comparisons were made between all these types, and conclusions were presented.

Keywords: drones detection, deep learning, birds versus drones, precision of detection, AdderNet

Procedia PDF Downloads 178

Authors: Shannon Rappe, Elizabeth Morse, David Phillippi

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Postpartum women with an opioid use disorder (OUD) are at high risk for treatment disengagement, leaving them vulnerable to overdose and death between seven and twelve months postpartum. Intensive case management programs have been proposed as an effective strategy to reduce barriers and increase treatment engagement among postpartum women. The purpose of this project is to determine the effects of early engagement in an intensive case management program on postpartum engagement and infant health outcomes among postpartum women with opioid use. This retrospective review of secondary data was collected on 225 infants, and 221 postpartum women enrolled in an intensive case management program in Tennessee between May 1, 2019, and May 5, 2020. Chi-squares were computed to examine the timing of engagement during pregnancy, maternal treatment outcomes, and infant health outcomes, including neonatal abstinence syndrome (NAS), birth weight, gestational age, and length of stay. The mean prenatal program engagement was 109 days (SD = 67.6); 16.7% (n = 37) enrolled during the first trimester, 37.6% (n = 83) in the second trimester, and 45.7% (n = 101) in the third trimester. Of the 221 women engaged, 45.2% (n = 100) remained engaged in the case of management at the time of data collection, and 40% (n = 89) remained engaged in MAT at the time of data collection. Twenty- five percent (n = 25) of mothers who graduated sustained engagement in MAT. Of 225 infants 28.9% (n = 65) had a positive NAS status, mean birth weight was 6.5 lbs. (SD = 19.3); mean gestational age was 38.3 weeks (SD = 19.3) and mean length of stay was 8.19 days (SD = 9.8). This study's findings identified that engaging mothers during pregnancy in a program designed to meet their unique challenges positively impacts both the mother and infant outcomes, regardless of their timing.

Keywords: intensive case management, neonatal abstinence syndrome, opioid addiction, opioid crisis, opioid use in pregnant women, postpartum addiction

Procedia PDF Downloads 209

Authors: Nimisha Elsa Koshy, Varun P. Gopi, V. I. Thajudin Ahamed

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The entire visualization of GastroIntestinal (GI) tract is not possible with conventional endoscopic exams. Wireless Capsule Endoscopy (WCE) is a low risk, painless, noninvasive procedure for diagnosing diseases such as bleeding, polyps, ulcers, and Crohns disease within the human digestive tract, especially the small intestine that was unreachable using the traditional endoscopic methods. However, analysis of massive images of WCE detection is tedious and time consuming to physicians. Hence, researchers have developed software methods to detect these diseases automatically. Thus, the effectiveness of WCE can be improved. In this paper, a novel textural feature extraction method is proposed based on Contourlet transform and Log Gabor filter to distinguish ulcer regions from normal regions. The results show that the proposed method performs well with a high accuracy rate of 94.16% using Support Vector Machine (SVM) classifier in HSV colour space.

Keywords: contourlet transform, log gabor filter, ulcer, wireless capsule endoscopy

Procedia PDF Downloads 540

Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

Procedia PDF Downloads 155

Authors: Ahmed Elrewainy

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Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no information about the given data cube. Sparsity is one of the recent approaches used in the source recovery or unmixing techniques. The l₁-norm optimization problem “basis pursuit” could be used as a sparsity-based approach to solve this unmixing problem where the endmembers is assumed to be sparse in an appropriate domain known as dictionary. This optimization problem is solved using proximal method “iterative thresholding”. The l₁-norm basis pursuit optimization problem as a sparsity-based unmixing technique was used to unmix real and synthetic hyperspectral data cubes.

Keywords: basis pursuit, blind source separation, hyperspectral imaging, spectral unmixing, wavelets

Procedia PDF Downloads 194

Authors: Kelemewerk Destalem, Joongjae Cho, Jaeseong Lee, Ju H. Park, Joonhyuk Yoo

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Background subtraction and temporal difference are often used for moving object detection in video. Both approaches are computationally simple and easy to be deployed in real-time image processing. However, while the background subtraction is highly sensitive to dynamic background and illumination changes, the temporal difference approach is poor at extracting relevant pixels of the moving object and at detecting the stopped or slowly moving objects in the scene. In this paper, we propose a moving object detection scheme based on adaptive background subtraction and temporal difference exploiting dynamic background updates. The proposed technique consists of a histogram equalization, a linear combination of background and temporal difference, followed by the novel frame-based and pixel-based background updating techniques. Finally, morphological operations are applied to the output images. Experimental results show that the proposed algorithm can solve the drawbacks of both background subtraction and temporal difference methods and can provide better performance than that of each method.

Keywords: background subtraction, background updating, real time, light weight algorithm, temporal difference

Procedia PDF Downloads 340

Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

Procedia PDF Downloads 449

Authors: Thanakrit Taweesoontorn, Sarucha Yanyong, Poom Konghuayrob

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Robotic arms have gained popularity in various industries due to their accuracy and efficiency. This research proposes a method for bin-picking tasks using the Cobot, combining the YOLOv5 CNNs model for object detection and pose estimation with traditional feature detection (FAST), feature description (BRISK), and matching algorithms. By integrating these algorithms and utilizing a small-scale depth sensor camera for capturing depth and color images, the system achieves real-time object detection and accurate pose estimation, enabling the robotic arm to pick objects correctly in both position and orientation. Furthermore, the proposed method is implemented within the ROS framework to provide a seamless platform for robotic control and integration. This integration of robotics, cameras, and AI technology contributes to the development of industrial robotics, opening up new possibilities for automating challenging tasks and improving overall operational efficiency.

Keywords: robotic vision, image processing, applications of robotics, artificial intelligent

Procedia PDF Downloads 94

Authors: Sang Hun Park, Moung Young Lee, Su Min Yu, Hyun Sang Jo, Ji Hyeon Kim, Chul Gyu Song

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A near-infrared light source used as a light source in the fluorescence imaging system is suitable for use in real-time during the operation since it has no interference in surgical vision. However, fluorescence images do not have depth information. In this paper, we configured the device with the research on molecular imaging systems for monitoring thrombus imaging using fluorescence and photoacoustic. Fluorescence imaging was performed using a phantom experiment in order to search the exact location, and the Photoacoustic image was in order to detect the depth. Fluorescence image obtained when evaluated through current phantom experiments when the concentration of the contrast agent is 25μg / ml, it was confirmed that it looked sharper. The phantom experiment is has shown the possibility with the fluorescence image and photoacoustic image using an indocyanine green contrast agent. For early diagnosis of cardiovascular diseases, more active research with the fusion of different molecular imaging devices is required.

Keywords: fluorescence, photoacoustic, indocyanine green, carotid artery

Procedia PDF Downloads 600

Authors: H. Yousefnia, A. Aghanejad, A. Mirzaei, R. Enayati, A. R. Jalilian, S. Zolghadri

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Bone metastases occur in many cases at an early stage of the tumour disease; however, their symptoms are recognized rather late. The aim of this study was the preparation and quality control of 111In-BPAMD for diagnostic purposes. 111In was produced at the Agricultural, Medical, and Industrial Research School (AMIRS) by means of 30 MeV cyclotron via natCd(p,x)111In reaction. Complexion of In‐111 with BPAMD was carried out by using acidic solution of 111InCl3 and BPAMD in absolute water. The effect of various parameters such as temperature, ligand concentration, pH, and time on the radiolabeled yield was studied. 111In-BPAMD was prepared successfully with the radiochemical purity of 95% at the optimized condition (100 µg of BPAMD, pH=5, and at 90°C for 1 h) which was measured by ITLC method. The final solution was injected to wild-type mice and biodistribution was determined up to 72 h. SPECT images were acquired after 2 and 24 h post injection. Both the biodistribution studies and SPECT imaging indicated high bone uptake while accumulation in other organs was approximately negligible. The results show that 111In-BPAMD can be used as an excellent tracer for diagnosis of bone metastases by SPECT imaging.

Keywords: biodistribution, BPAMD, 111In, SPECT

Procedia PDF Downloads 559

Authors: Muna F. Al-Sammaraie

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The aim of this research is to present a multi spectral image enhancement methods used to achieve highly real digital image populates only a small portion of the available range of digital values. Also, a quantitative measure of image enhancement is presented. This measure is related with concepts of the Webers Low of the human visual system. For decades, several image enhancement techniques have been proposed. Although most techniques require profuse amount of advance and critical steps, the result for the perceive image are not as satisfied. This study involves changing the original values so that more of the available range is used; then increases the contrast between features and their backgrounds. It consists of reading the binary image on the basis of pixels taking them byte-wise and displaying it, calculating the statistics of an image, automatically enhancing the color of the image based on statistics calculation using algorithms and working with RGB color bands. Finally, the enhanced image is displayed along with image histogram. A number of experimental results illustrated the performance of these algorithms. Particularly the quantitative measure has helped to select optimal processing parameters: the best parameters and transform.

Keywords: image enhancement, multi-spectral, RGB, histogram

Procedia PDF Downloads 326

Authors: Abdur Rahim, Lauro Tatsuo Kubota, Yoshitaka Gushikem

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Carbon ceramic mesoporous SiO2/50wt%C (SBET= 170 m2g-1), where C is graphite, was prepared by the sol gel method. Scanning electron microscopy images and the respective element mapping showed that, within the magnification used, no phase segregation was detectable. It presented the electric conductivities of 0.49 S cm-1. This material was used to support cobalt phthalocyanine, prepared in situ, to assure a homogeneous dispersion of the electro active complex in the pores of the matrix. The surface density of cobalt phthalocyanine, on the matrix surfaces was 0.015 mol cm-2. Pressed disk, made with SiO2/50wt%C/CoPc, was used to fabricate an electrode and tested as sensors for nitrite determination by electro chemical technique. A linear response range between 0.039 and 0.42 mmol l−1,and correlation coefficient r=0.9996 was obtained. The electrode was chemically very stable and presented very high sensitivity for this analyte, with a limit of detection, LOD = 1.087 x 10-6 mol L-1.

Keywords: SiO2/C/CoPc, sol-gel method, electrochemical sensor, nitrite oxidation, carbon ceramic material, cobalt phthalocyanine

Procedia PDF Downloads 314

Authors: Essang Anwana Onuntuei, Chinyere Blessing Azunwoke

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The study focused on probing the effectiveness of online consumer privacy and protection laws, electronic transaction laws, privacy and data protection laws, and cybercrime legislation amid frequent cyber-attacks and malware types worldwide. An empirical analysis was engaged to uncover ties and causations between the stringency and implementation of these legal structures and the prevalence of cyber threats. A deliberate sample of seventy-eight countries (thirteen countries each from six continents) was chosen as sample size to study the challenges linked with trending regulations and possible panoramas for improving cybersecurity through refined legal approaches. Findings establish if the frequency of cyber-attacks and malware types vary significantly. Also, the result proved that various cybercrime laws differ statistically, and electronic transactions law does not statistically impact the frequency of cyber-attacks. The result also statistically revealed that the online Consumer Privacy and Protection law does not influence the total number of cyber-attacks. In addition, the results implied that Privacy and Data Protection laws do not statistically impact the total number of cyber-attacks worldwide. The calculated value also proved that cybercrime law does not statistically impact the total number of cyber-attacks. Finally, the computed value concludes that combined multiple cyber laws do not significantly impact the total number of cyber-attacks worldwide. Suggestions were produced based on findings from the study, contributing to the ongoing debate on the validity of legal approaches in battling cybercrime and shielding consumers in the digital age.

Keywords: cybercrime legislation, cyber attacks, consumer privacy and protection law, detection, electronic transaction law, prevention, privacy and data protection law, prohibition, prosecution

Procedia PDF Downloads 39

Authors: D. Densenbal, Ts. Naidansuren, M. Oyunchimeg, Ts. Manaljav, D. Udval, L. Khosbayar, Kh. Solongo, D. Ichinnorov, B. Solongo

Abstract:

Background: The rapid economic growth and to the common use of smoky fuel such as coal in the small traditional houses (Ger) in Mongolia is worsening its air pollution problem. In addition, the smoking rate is considered to be high. Despite these conditions, few prevalence studies of COPD epidemiology and diagnose have been performed in Mongolia. The spirometric test is a widely used diagnose for COPD. Aims: Healthy and over the 40 aged adults were evaluated of Pulmonary function test in Ulaanbaatar. Methods: Healthy, over the 40 aged residences were admitted for this study from II sub-district, in Khan-Uul district of Ulaanbaatar city. In this cross-sectional study. Health information was collected 184 subjects between 01-03 July in 2013; spirometry device was named Hichest–105 Japan that was employed for this study. Studies were using the acceptability standards outlined, and data were compared with personal reference data generated on Asian subjects which were performed abnormally to evaluated by global initiative obstructive lung decreases (GOLD). Data were analyzed using SPSS 20 software. Results: A total of 134 subjects (age 52.9±9.8, man 32.8%) were performed PFT which were interpreted normal 73.9% (sum of man 65.0% and woman 79.4% ), abnormal 26.1% which were typed obstruction 17.2% (23), restriction 6% (8), mixed 3% (4). Airflow obstruction were determined in all man 25% (11), woman 13.3% (12) which were classified mild 43.4% (man 54.5%, woman 33.3%), moderate 52.2% (36.3% vs. 66.7%) and severe 4.3% man 1 GOLD degree. Undetermined a very severe obstruction. Normal PFT subjects were compared a group of gender and age group which man was significantly higher than the women (p<0.05). Age group of PFT decrease was no difference in gender (p>0.05) also no difference in BMI (p>0.05). Normal PFT subjects were compared with predicted values were used to Asian population which was significantly lower than FEV1 (0.15±0.36 l), PEF (1.92±1.31 l) and same deference occurred man (FEV1 0.19±0.42 l, PEF 2.04±1.64), women (0.14±0.33 l vs. 1.86±1.15 l). The decrease of FEV1 was defined in over the 60 age group higher than other age groups. Conclusion: Not only observed an air flow limitation prevalence dominance in all case but also COPD prevalence diagnosed man were higher than women. Normal PFT subjects were compared with predicted values were used to Asian population which was significant air flow limitation started early.

Keywords: PFT, obstruction, FEV1, COPD

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Authors: Gelacio JuáRez-Luna, Daniel Enrique GonzáLez-RamíRez, Enrique Tenorio-Montero

Abstract:

Frame elements coupled with springs elements are used for modelling the development of hinges in segmented tunnels, the spring elements modelled the rotational, transversal and axial failure. These spring elements are equipped with constitutive models to include independently the moment, shear force and axial force, respectively. These constitutive models are formulated based on damage mechanics and experimental test reported in the literature review. The mesh of the segmented tunnels was discretized in the software GID, and the nonlinear analyses were carried out in the finite element software ANSYS. These analyses provide the capacity curve of the primary and secondary lining of a segmented tunnel. Two numerical examples of segmented tunnels show the capability of the spring elements to release energy by the development of hinges. The first example is a segmental concrete lining discretized with frame elements loaded until hinges occurred in the lining. The second example is a tunnel with primary and secondary lining, discretized with a double ring frame model. The outer ring simulates the segmental concrete lining and the inner ring simulates the secondary cast-in-place concrete lining. Spring elements also modelled the joints between the segments in the circumferential direction and the ring joints, which connect parallel adjacent rings. The computed load vs displacement curves are congruent with numerical and experimental results reported in the literature review. It is shown that the modelling of a tunnel with primary and secondary lining with frame elements and springs provides reasonable results and save computational cost, comparing with 2D or 3D models equipped with smeared crack models.

Keywords: damage, hinges, lining, tunnel

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Authors: V. V. Fomin, A. P. Mikhailovich, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

Abstract:

Ground-level landscape photos can be used as a source of objective data on woody vegetation and vegetation dynamics. We proposed a method for processing, analyzing, and presenting ground photographs, which has the following advantages: 1) researcher has to form holistic representation of the study area in form of a set of interlapping ground-level landscape photographs; 2) it is necessary to define or obtain characteristics of the landscape, objects, and phenomena present on the photographs; 3) it is necessary to create new or supplement existing textual descriptions and annotations for the ground-level landscape photographs; 4) single or multiple ground-level landscape photographs can be used to develop specialized geoinformation layers, schematic maps or thematic maps; 5) it is necessary to determine quantitative data that describes both images as a whole, and displayed objects and phenomena, using algorithms for automated image analysis. It is suggested to match each photo with a polygonal geoinformation layer, which is a sector consisting of areas corresponding with parts of the landscape visible in the photos. Calculation of visibility areas is performed in a geoinformation system within a sector using a digital model of a study area relief and visibility analysis functions. Superposition of the visibility sectors corresponding with various camera viewpoints allows matching landscape photos with each other to create a complete and wholesome representation of the space in question. It is suggested to user-defined data or phenomenons on the images with the following superposition over the visibility sector in the form of map symbols. The technology of geoinformation layers’ spatial superposition over the visibility sector creates opportunities for image geotagging using quantitative data obtained from raster or vector layers within the sector with the ability to generate annotations in natural language. The proposed method has proven itself well for relatively open and clearly visible areas with well-defined relief, for example, in mountainous areas in the treeline ecotone. When the polygonal layers of visibility sectors for a large number of different points of photography are topologically superimposed, a layer of visibility of sections of the entire study area is formed, which is displayed in the photographs. Also, as a result of this overlapping of sectors, areas that did not appear in the photo will be assessed as gaps. According to the results of this procedure, it becomes possible to obtain information about the photos that display a specific area and from which points of photography it is visible. This information may be obtained either as a query on the map or as a query for the attribute table of the layer. The method was tested using repeated photos taken from forty camera viewpoints located on Ray-Iz mountain massif (Polar Urals, Russia) from 1960 until 2023. It has been successfully used in combination with other ground-based and remote sensing methods of studying the climate-driven dynamics of woody vegetation in the Polar Urals. Acknowledgment: This research was collaboratively funded by the Russian Ministry for Science and Education project No. FEUG-2023-0002 (image representation) and Russian Science Foundation project No. 24-24-00235 (automated textual description).

Keywords: woody, vegetation, repeated, photographs

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Authors: Ramin Mehdiabadi

Abstract:

Background: Breast cancer remains the most prevalent cancer diagnosis and the leading cause of cancer death among women globally, representing 11.7% of new cases and 6.9% of deaths. While the incidence and mortality of major cancers are declining in developed regions like the United States and Western Europe, underdeveloped and developing countries exhibit an increasing trend, attributed to lifestyle factors such as smoking, physical inactivity, and high-calorie diets. Objective: This study explores the intricate relationship between the mammalian transcription factor forkhead box (FoxM1) and the microRNA miR-216b-5p in various subtypes of breast cancer, aiming to deepen the understanding of their roles in tumorigenesis, metastasis, and drug resistance. Methods: Breast cancer subtypes were categorized based on key biomarkers: estrogen receptors, progesterone receptors, and human epidermal growth factor receptor 2. These include luminal A, luminal B, HER2 enriched, triple-negative, and normal-like subtypes. We focused on analyzing the expression levels of FoxM1 and miR-216b-5p, given the known role of FoxM1 in cell proliferation and its implications in cancer pathologies such as lung, gastric, and breast cancers. Concurrently, miR-216b-5p's function as a tumor suppressor was evaluated to ascertain its regulatory effects on FoxM1. Results: Preliminary data indicate a nuanced interplay between FoxM1 and miR-216b-5p, suggesting a potential inverse relationship that varies across breast cancer subtypes. This relationship underscores the dual role of these biomarkers in modulating cancer progression and response to treatments. Conclusion: The findings advocate for the potential of miR-216b-5p to serve as a prognostic biomarker and a therapeutic target, particularly in subtypes where FoxM1 is prominently expressed. Understanding these molecular interactions provides crucial insights into the personalized treatment strategies and could lead to more effective therapeutic interventions in breast cancer management. Implications: The study highlights the importance of molecular profiling in breast cancer treatment and emphasizes the need for targeted therapeutic approaches in managing diverse cancer subtypes, particularly in varying global contexts where lifestyle factors significantly impact cancer dynamics.

Keywords: breast cancer, gene expression, FoxM1, microRNA

Procedia PDF Downloads 51