Search results for: lung segmentation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 957

Search results for: lung segmentation

447 Overview and Pathophysiology of Radiation-Induced Breast Changes as a Consequence of Radiotherapy Toxicity

Authors: Monika Rezacova

Abstract:

Radiation-induced breast changes are a consequence of radiotherapy toxicity over the breast tissues either related to targeted breast cancer treatment or other thoracic malignancies (eg. lung cancer). This study has created an overview of different changes and their pathophysiology. The main conditions included were skin thickening, interstitial oedema, fat necrosis, dystrophic calcifications, skin retractions, glandular atrophy, breast fibrosis and radiation induced breast cancer. This study has performed focused literature search through multiple databases including pubmed, medline and embase. The study has reviewed English as well as non English publications. As a result of the literature the study provides comprehensive overview of radiation-induced breast changes and their pathophysiology with small focus on new development and prevention.

Keywords: radiotherapy toxicity, breast tissue changes, breast cancer treatment, radiation-induced breast changes

Procedia PDF Downloads 159
446 Temperature Contour Detection of Salt Ice Using Color Thermal Image Segmentation Method

Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

Abstract:

The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

Procedia PDF Downloads 315
445 Tank Barrel Surface Damage Detection Algorithm

Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

Abstract:

The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

Procedia PDF Downloads 139
444 Differentiation of Customer Types by Stereotypical Characteristics for Modular and Conventional Construction Methods

Authors: Peter Schnell, Phillip Haag

Abstract:

In the course of the structural transformation of the construction industry, the integration of industrialization and digitization has led to the development of construction methods with an increased degree of prefabrication, such as system or modular construction. Compared to conventional construction, these innovative construction methods are characterized by modified structural and procedural properties and expand the range of construction services. Faced with the supply side, it is possible to identify construction-specific customer types with different characteristics and certain preferences as far as the choice of construction method is concerned. The basis for this finding was qualitative expert interviews. By evaluating the stereotypical customer needs, a corresponding segmentation of the demand side can be made along with the basic orientation and decision behavior. This demarcation supports the target- and needs-oriented customer approach and contributes to cooperative and successful project management.

Keywords: differentiation of customer types, modular construction methods, conventional construction methods, stereotypical customer types

Procedia PDF Downloads 110
443 Photogrammetry and Topographic Information for Urban Growth and Change in Amman

Authors: Mahmoud M. S. Albattah

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Urbanization results in the expansion of administrative boundaries, mainly at the periphery, ultimately leading to changes in landcover. Agricultural land, naturally vegetated land, and other land types are converted into residential areas with a high density of constructs, such as transportation systems and housing. In urban regions of rapid growth and change, urban planners need regular information on up to date ground change. Amman (the capital of Jordan) is growing at unprecedented rates, creating extensive urban landscapes. Planners interact with these changes without having a global view of their impact. The use of aerial photographs and satellite images data combined with topographic information and field survey could provide effective information to develop urban change and growth inventory which could be explored towards producing a very important signature for the built-up area changes.

Keywords: highway design, satellite technologies, remote sensing, GIS, image segmentation, classification

Procedia PDF Downloads 444
442 Slope Effect in Emission Evaluation to Assess Real Pollutant Factors

Authors: G. Meccariello, L. Della Ragione

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The exposure to outdoor air pollution causes lung cancer and increases the risk of bladder cancer. Because air pollution in urban areas is mainly caused by transportation, it is necessary to evaluate pollutant exhaust emissions from vehicles during their real-world use. Nevertheless their evaluation and reduction is a key problem, especially in the cities, that account for more than 50% of world population. A particular attention was given to the slope variability along the streets during each journey performed by the instrumented vehicle. In this paper we dealt with the problem of describing a quantitatively approach for the reconstruction of GPS coordinates and altitude, in the context of correlation study between driving cycles / emission / geographical location, during an experimental campaign realized with some instrumented cars. Finally the slope analysis can be correlated to the emission and consumption values in a specific road position, and it could be evaluated its influence on their behaviour.

Keywords: air pollution, driving cycles, GPS signal, slope, emission factor, fuel consumption

Procedia PDF Downloads 392
441 Real-Time Measurement Approach for Tracking the ΔV10 Estimate Value of DC EAF

Authors: Jin-Lung Guan, Jyh-Cherng Gu, Chun-Wei Huang, Hsin-Hung Chang

Abstract:

This investigation develops a revisable method for estimating the estimate value of equivalent 10 Hz voltage flicker (DV10) of a DC Electric Arc Furnace (EAF). This study also discusses three 161kV DC EAFs by field measurement, with those results indicating that the estimated DV10 value is significantly smaller than the survey value. The key point is that the conventional means of estimating DV10 is inappropriate. There is a main cause as the assumed Qmax is too small. Although DC EAF is regularly operated in a constant MVA mode, the reactive power variation in the Main Transformer (MT) is more significant than that in the Furnace Transformer (FT). A substantial difference exists between estimated maximum reactive power fluctuation (DQmax) and the survey value from actual DC EAF operations. However, this study proposes a revisable method that can obtain a more accurate DV10 estimate than the conventional method.

Keywords: voltage flicker, dc EAF, estimate value, DV10

Procedia PDF Downloads 450
440 Automatic Number Plate Recognition System Based on Deep Learning

Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

Abstract:

In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: ANPR, CS, CNN, deep learning, NPL

Procedia PDF Downloads 306
439 Cells Detection and Recognition in Bone Marrow Examination with Deep Learning Method

Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

Procedia PDF Downloads 192
438 Scattering Operator and Spectral Clustering for Ultrasound Images: Application on Deep Venous Thrombi

Authors: Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier, Léo Fréchier, Barthélémy Hermenault

Abstract:

Deep Venous Thrombosis (DVT) occurs when a thrombus is formed within a deep vein (most often in the legs). This disease can be deadly if a part or the whole thrombus reaches the lung and causes a Pulmonary Embolism (PE). This disorder, often asymptomatic, has multifactorial causes: immobilization, surgery, pregnancy, age, cancers, and genetic variations. Our project aims to relate the thrombus epidemiology (origins, patient predispositions, PE) to its structure using ultrasound images. Ultrasonography and elastography were collected using Toshiba Aplio 500 at Brest Hospital. This manuscript compares two classification approaches: spectral clustering and scattering operator. The former is based on the graph and matrix theories while the latter cascades wavelet convolutions with nonlinear modulus and averaging operators.

Keywords: deep venous thrombosis, ultrasonography, elastography, scattering operator, wavelet, spectral clustering

Procedia PDF Downloads 479
437 Klippel Feil Syndrome: A Case Report and Review of Literature

Authors: Rim Frikha, Nouha Bouayed Abdelmoula, Afifa Sellami, Salima Daoud, Tarek Rebai

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Klippel-Feil Syndrome (KFS) is characterized by congenital vertebral fusion of the cervical spine resulting from faulty segmentation along the embryo's developing axis. A wide spectrum of associated anomalies may be present. This heterogeneity has complicated elucidation of the genetic etiology and management of the syndrome. We report a case of an isolated Klippel-Feil Syndrome with C5-C6 fusion on the cervical spine. It‘s the rarest form of congenital fused cervical vertebrae which is predisposed to the risk of spinal cord injury and neurologic problems. The aim of this paper was to review clinical heterogeneity; radiographic abnormalities and genetic etiology in Klippel-Feil Syndrome. We insist in comprehensive evaluation and delineation of diagnostic and prognostic classes.

Keywords: Klippel–Feil anomaly, genetic, clinical heterogeneity, radiographic abnormalities

Procedia PDF Downloads 484
436 Positron Emission Tomography Parameters as Predictors of Pathologic Response and Nodal Clearance in Patients with Stage IIIA NSCLC Receiving Trimodality Therapy

Authors: Andrea L. Arnett, Ann T. Packard, Yolanda I. Garces, Kenneth W. Merrell

Abstract:

Objective: Pathologic response following neoadjuvant chemoradiation (CRT) has been associated with improved overall survival (OS). Conflicting results have been reported regarding the pathologic predictive value of positron emission tomography (PET) response in patients with stage III lung cancer. The aim of this study was to evaluate the correlation between post-treatment PET response and pathologic response utilizing novel FDG-PET parameters. Methods: This retrospective study included patients with non-metastatic, stage IIIA (N2) NSCLC cancer treated with CRT followed by resection. All patients underwent PET prior to and after neoadjuvant CRT. Univariate analysis was utilized to assess correlations between PET response, nodal clearance, pCR, and near-complete pathologic response (defined as the microscopic residual disease or less). Maximal standard uptake value (SUV), standard uptake ratio (SUR) [normalized independently to the liver (SUR-L) and blood pool (SUR-BP)], metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured pre- and post-chemoradiation. Results: A total of 44 patients were included for review. Median age was 61.9 years, and median follow-up was 2.6 years. Histologic subtypes included adenocarcinoma (72.2%) and squamous cell carcinoma (22.7%), and the majority of patients had the T2 disease (59.1%). The rate of pCR and near-complete pathologic response within the primary lesion was 28.9% and 44.4%, respectively. The average reduction in SUVmₐₓ was 9.2 units (range -1.9-32.8), and the majority of patients demonstrated some degree of favorable treatment response. SUR-BP and SUR-L showed a mean reduction of 4.7 units (range -0.1-17.3) and 3.5 units (range –1.7-12.6), respectively. Variation in PET response was not significantly associated with histologic subtype, concurrent chemotherapy type, stage, or radiation dose. No significant correlation was found between pathologic response and absolute change in MTV or TLG. Reduction in SUVmₐₓ and SUR were associated with increased rate of pathologic response (p ≤ 0.02). This correlation was not impacted by normalization of SUR to liver versus mediastinal blood pool. A threshold of > 75% decrease in SUR-L correlated with near-complete response, with a sensitivity of 57.9% and specificity of 85.7%, as well as positive and negative predictive values of 78.6% and 69.2%, respectively (diagnostic odds ratio [DOR]: 5.6, p=0.02). A threshold of >50% decrease in SUR was also significantly associated pathologic response (DOR 12.9, p=0.2), but specificity was substantially lower when utilizing this threshold value. No significant association was found between nodal PET parameters and pathologic nodal clearance. Conclusions: Our results suggest that treatment response to neoadjuvant therapy as assessed on PET imaging can be a predictor of pathologic response when evaluated via SUV and SUR. SUR parameters were associated with higher diagnostic odds ratios, suggesting improved predictive utility compared to SUVmₐₓ. MTV and TLG did not prove to be significant predictors of pathologic response but may warrant further investigation in a larger cohort of patients.

Keywords: lung cancer, positron emission tomography (PET), standard uptake ratio (SUR), standard uptake value (SUV)

Procedia PDF Downloads 234
435 A Novel Method for Silence Removal in Sounds Produced by Percussive Instruments

Authors: B. Kishore Kumar, Rakesh Pogula, T. Kishore Kumar

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The steepness of an audio signal which is produced by the musical instruments, specifically percussive instruments is the perception of how high tone or low tone which can be considered as a frequency closely related to the fundamental frequency. This paper presents a novel method for silence removal and segmentation of music signals produced by the percussive instruments and the performance of proposed method is studied with the help of MATLAB simulations. This method is based on two simple features, namely the signal energy and the spectral centroid. As long as the feature sequences are extracted, a simple thresholding criterion is applied in order to remove the silence areas in the sound signal. The simulations were carried on various instruments like drum, flute and guitar and results of the proposed method were analyzed.

Keywords: percussive instruments, spectral energy, spectral centroid, silence removal

Procedia PDF Downloads 412
434 An Improved Circulating Tumor Cells Analysis Method for Identifying Tumorous Blood Cells

Authors: Salvador Garcia Bernal, Chi Zheng, Keqi Zhang, Lei Mao

Abstract:

Circulating Tumor Cells (CTC) is used to detect tumoral cell metastases using blood samples of patients with cancer (lung, breast, etc.). Using an immunofluorescent method a three channel image (Red, Green, and Blue) are obtained. These set of images usually overpass the 11 x 30 M pixels in size. An aided tool is designed for imaging cell analysis to segmented and identify the tumorous cell based on the three markers signals. Our Method, it is cell-based (area and cell shape) considering each channel information and extracting and making decisions if it is a valid CTC. The system also gives information about number and size of tumor cells found in the sample. We present results in real-life samples achieving acceptable performance in identifying CTCs in short time.

Keywords: Circulating Tumor Cells (CTC), cell analysis, immunofluorescent, medical image analysis

Procedia PDF Downloads 214
433 Zero-Knowledge Proof-of-Reserve: A Confidential Approach to Cryptocurrency Asset Verification

Authors: Sam Ng, Lewis Leighton, Sam Atkinson, Carson Yan, Landan Hu, Leslie Cheung, Brian Yap, Kent Lung, Ketat Sarakune

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This paper introduces a method for verifying cryptocurrency reserves that balances the need for both transparency and data confidentiality. Our methodology employs cryptographic techniques, including Merkle Trees, Bulletproof, and zkSnark, to verify that total assets equal or exceed total liabilities, represented by customer funds. Importantly, this verification is achieved without disclosing sensitive information such as the total asset value, customer count, or cold wallet addresses. We delve into the construction and implementation of this methodology. While the system is robust and scalable, we also identify areas for potential enhancements to improve its efficiency and versatility. As the digital asset landscape continues to evolve, our approach provides a solid foundation for ensuring continued trust and security in digital asset platforms.

Keywords: cryptocurrency, crypto-currency, proof-of-reserve, por, zero-knowledge, ZKP

Procedia PDF Downloads 72
432 MTT Assay-Guided Isolation of a Cytotoxic Lead from Hedyotis umbellata and Its Mechanism of Action against Non-Small Cell Lung Cancer A549 Cells

Authors: Kirti Hira, A. Sajeli Begum, S. Mahibalan, Poorna Chandra Rao

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Introduction: Cancer is one of the leading causes of death worldwide. Although existing therapy effectively kills cancer cells, they do affect normal growing cells leading to many undesirable side effects. Hence there is need to develop effective as well as safe drug molecules to combat cancer, which is possible through phyto-research. The currently available plant-derived blockbuster drugs are the example for this. In view of this, an investigation was done to identify cytotoxic lead molecules from Hedyotis umbellata (Family Rubiaceae), a widely distributed weed in India. Materials and Methods: The methanolic extract of the whole plant of H. umbellata (MHU), prepared through Soxhlet extraction method was further fractionated with diethyl ether and n-butanol, successively. MHU, ether fraction (EMHU) and butanol fraction (BMHU) were lyophilized and were tested for the cytotoxic effect using 3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay against non-small cell lung cancer (NSCLC) A549 cell lines. The potentially active EMHU was subjected to chromatographic purification using normal-phase silica columns, in order to isolate the responsible bioactive compounds. The isolated pure compounds were tested for their cytotoxic effect by MTT assay against A549 cells. Compound-3, which was found to be most active, was characterized using IR, 1H- and 13C-NMR and MS analysis. The study was further extended to decipher the mechanism of action of cytotoxicity of compound-3 against A549 cells through various in vitro cellular models. Cell cycle analysis was done using flow cytometry following PI (Propidium Iodide) staining. Protein analysis was done using Western blot technique. Results: Among MHU, EMHU, and BMHU, the non-polar fraction EMHU demonstrated a significant dose-dependent cytotoxic effect with IC50 of 67.7μg/ml. Chromatography of EMHU yielded seven compounds. MTT assay of isolated compounds explored compound-3 as potentially active one, which inhibited the growth of A549 cells with IC50value of 14.2μM. Further, compound-3 was identified as cedrelopsin, a coumarin derivative having molecular weight of 260. Results of in vitro mechanistic studies explained that cedrelopsin induced cell cycle arrest at G2/M phase and down-regulated the expression of G2/M regulatory proteins such as cyclin B1, cdc2, and cdc25C, dose dependently. This is the first report that explores the cytotoxic mechanism of cedrelopsin. Conclusion: Thus a potential small lead molecule, cedrelopsin isolated from H. umbellata, showing antiproliferative effect mediated by G2/M arrest in A549 cells was discovered. The effect of cedrelopsin against other cancer cell lines followed by in vivo studies can be performed in future to develop a new drug candidate.

Keywords: A549, cedrelopsin, G2/M phase, Hedyotis umbellata

Procedia PDF Downloads 175
431 Nanoparticle Exposure Levels in Indoor and Outdoor Demolition Sites

Authors: Aniruddha Mitra, Abbas Rashidi, Shane Lewis, Jefferson Doehling, Alexis Pawlak, Jacob Schwartz, Imaobong Ekpo, Atin Adhikari

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Working or living close to demolition sites can increase risks of dust-related health problems. Demolition of concrete buildings may produce crystalline silica dust, which can be associated with a broad range of respiratory diseases including silicosis and lung cancers. Previous studies demonstrated significant associations between demolition dust exposure and increase in the incidence of mesothelioma or asbestos cancer. Dust is a generic term used for minute solid particles of typically <500 µm in diameter. Dust particles in demolition sites vary in a wide range of sizes. Larger particles tend to settle down from the air. On the other hand, the smaller and lighter solid particles remain dispersed in the air for a long period and pose sustained exposure risks. Submicron ultrafine particles and nanoparticles are respirable deeper into our alveoli beyond our body’s natural respiratory cleaning mechanisms such as cilia and mucous membranes and are likely to be retained in the lower airways. To our knowledge, how various demolition tasks release nanoparticles are largely unknown and previous studies mostly focused on course dust, PM2.5, and PM10. General belief is that the dust generated during demolition tasks are mostly large particles formed through crushing, grinding, or sawing of various concrete and wooden structures. Therefore, little consideration has been given to the generated submicron ultrafine and nanoparticles and their exposure levels. These data are, however, critically important because recent laboratory studies have demonstrated cytotoxicity of nanoparticles on lung epithelial cells. The above-described knowledge gaps were addressed in this study by a novel newly developed nanoparticle monitor, which was used for nanoparticle monitoring at two adjacent indoor and outdoor building demolition sites in southern Georgia. Nanoparticle levels were measured (n = 10) by TSI NanoScan SMPS Model 3910 at four different distances (5, 10, 15, and 30 m) from the work location as well as in control sites. Temperature and relative humidity levels were recorded. Indoor demolition works included acetylene torch, masonry drilling, ceiling panel removal, and other miscellaneous tasks. Whereas, outdoor demolition works included acetylene torch and skid-steer loader use to remove a HVAC system. Concentration ranges of nanoparticles of 13 particle sizes at the indoor demolition site were: 11.5 nm: 63 – 1054/cm³; 15.4 nm: 170 – 1690/cm³; 20.5 nm: 321 – 730/cm³; 27.4 nm: 740 – 3255/cm³; 36.5 nm: 1,220 – 17,828/cm³; 48.7 nm: 1,993 – 40,465/cm³; 64.9 nm: 2,848 – 58,910/cm³; 86.6 nm: 3,722 – 62,040/cm³; 115.5 nm: 3,732 – 46,786/cm³; 154 nm: 3,022 – 21,506/cm³; 205.4 nm: 12 – 15,482/cm³; 273.8 nm: Keywords: demolition dust, industrial hygiene, aerosol, occupational exposure

Procedia PDF Downloads 423
430 Facial Emotion Recognition with Convolutional Neural Network Based Architecture

Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

Procedia PDF Downloads 275
429 Adaptive Few-Shot Deep Metric Learning

Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

Procedia PDF Downloads 171
428 Intelligent Grading System of Apple Using Neural Network Arbitration

Authors: Ebenezer Obaloluwa Olaniyi

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In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

Procedia PDF Downloads 399
427 The Impact of Web Based Education on Cancer Patients’ Clinical Outcomes

Authors: F. Arıkan, Z. Karakus

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Cancer is a widespread disease in the world and is the third reason of deaths among the chronic diseases. Educating patients and caregivers has a vital role for empowering them in managing disease and treatment's symptoms. Informing of the patients about their disease and treatment process decreases patient's distress and decisional conflicts, improves wellbeing of them, increase success of the treatment and survival. In this era, technological education methods are used for patients that have different chronic disease. Many studies indicated that especially web based patient education such as chronic obstructive lung disease; heart failure is more effective than printed materials. Web based education provide easiness to patients while they are reaching health services. It also has more advantages because of it decreases health cost and requirement of staff. It is thought that web based education may be beneficial method for cancer patient's empowerment in coping with the disease's symptoms. The aim of the study is evaluate the effectiveness of web based education for cancer patients' clinical outcomes.

Keywords: cancer patients, e-learning, nursing, web based education

Procedia PDF Downloads 432
426 Steady State and Accelerated Decay Rate Evaluations of Membrane Electrode Assembly of PEM Fuel Cells

Authors: Yingjeng James Li, Lung-Yu Sung, Huan-Jyun Ciou

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Durability of Membrane Electrode Assembly for Proton Exchange Membrane Fuel Cells was evaluated in both steady state and accelerated decay modes. Steady state mode was carried out at constant current of 800mA / cm2 for 2500 hours using air as cathode feed and pure hydrogen as anode feed. The degradation of the cell voltage was 0.015V after such 2500 hrs operation. The degradation rate was therefore calculated to be 6uV / hr. Accelerated mode was carried out by switching the voltage of the single cell between OCV and 0.2V. The durations held at OCV and 0.2V were 20 and 40 seconds, respectively, meaning one minute per cycle. No obvious change in performance of the MEA was observed after 10000 cycles of such operation.

Keywords: durability, lifetime, membrane electrode assembly, proton exchange membrane fuel cells

Procedia PDF Downloads 589
425 The Operation Strategy and Public Relations Trend for Public Relations Strategies Development in Thailand

Authors: Kanyapat U. Tapao

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The purpose of this study is to analyze the operation strategy strategies and public relations trend for public relations strategies development in public television station in Thailand. This study is a qualitative approach by indent interview from the 6 key informants that are managers of Voice TV and Thairath TV Channel. The results showed that both TV stations have to do research before making a release on the operation strategy policy such as a slogan, segmentation, integrated marketing communication and PR activity and also in term of Public Relations trend are including online media, online content and online training before opening the station and start promoting. By the way, we found the PR strategy for both TV station should be including application on mobile, online content, CRM activity, online banner, special event, and brand ambassador in order to bring a very reliable way.

Keywords: online banner, operation strategy, public relations trend, public relations strategies development

Procedia PDF Downloads 319
424 Differentiated Thyroid Cancer Presenting with Solitary Bony Metastases to the Frontal Bone of the Skull

Authors: Christy M. Moen, Richard B. Townsley

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Introduction: Metastasis to the frontal bone in thyroid cancer is extremely rare. A literature review found only six cases of thyroid cancer that metastasised to the frontal bone, with two of those involving further bone sites. Case Report: The patient was originally referred to the Oral and Maxillofacial Surgery team with an isolated mass on her forehead. Biopsies were performed, which showed this was likely a metastatic deposit from thyroid cancer. CT-PET scan showed this was an isolated lesion. The patient had a total thyroidectomy, and the forehead lesion was managed with radiotherapy. On interval scanning, the patient’s bony lesion had increased in size and had new lung nodules, which likely represented further metastasis. Conclusion: Isolated bony metastases to the frontal bone are rare. An important clinical principle to remember is that a bony metastasis from an unknown primary is more likely than primary bone cancer.

Keywords: cancer, thyroid, head and neck, surgery

Procedia PDF Downloads 212
423 The Types of Collaboration Models Driven by Public Art Establishment–Case Study of Taichung City

Authors: Cheng-Lung Yu, Ying-His Liao

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Some evidence show that public art accelerates local economic growth. Even local governments award the collaboration of public-private partnership to sustain the creation of public art for urban economic development. Through the public-private partnership of public art establishment it is obvious that public construction projects have been led by the governmental policy yet the private developers have played crucial roles to drive the innovative business models such as tourism investment, real estate value up and community participation. This study shows that the types of collaboration have been driven by Taichung city governmental policy from the regulation of public art establishment in the past three years. Through some cases empirical analyzes the authors discover the trends concerning the public art development to support local economic growth in Taiwan.

Keywords: public art, public art establishment regulation, construction management, urban governance

Procedia PDF Downloads 34
422 Modeling and Tracking of Deformable Structures in Medical Images

Authors: Said Ettaieb, Kamel Hamrouni, Su Ruan

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This paper presents a new method based both on Active Shape Model and a priori knowledge about the spatio-temporal shape variation for tracking deformable structures in medical imaging. The main idea is to exploit the a priori knowledge of shape that exists in ASM and introduce new knowledge about the shape variation over time. The aim is to define a new more stable method, allowing the reliable detection of structures whose shape changes considerably in time. This method can also be used for the three-dimensional segmentation by replacing the temporal component by the third spatial axis (z). The proposed method is applied for the functional and morphological study of the heart pump. The functional aspect was studied through temporal sequences of scintigraphic images and morphology was studied through MRI volumes. The obtained results are encouraging and show the performance of the proposed method.

Keywords: active shape model, a priori knowledge, spatiotemporal shape variation, deformable structures, medical images

Procedia PDF Downloads 343
421 Parallel Genetic Algorithms Clustering for Handling Recruitment Problem

Authors: Walid Moudani, Ahmad Shahin

Abstract:

This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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420 Rhythmic Prioritisation as a Means of Compositional Organisation: Analysing Meshuggah’s “do Not Look Down”

Authors: Nicholas Freer

Abstract:

Rhythmic complexity in progressive metal is a developing area of analysis, particularly the interpretation of hyper-metric time spans as hierarchically significant rhythmic units of compositional organisation (Pieslak 2007, Charupakorn 2012, Capuzzo 2018, Calder 2018, Lucas 2018, Hannan 2020). This paper adds to this developing area by considering the relationships between the concepts of tactus, metric imposition, polymeter and rhythmic parallax in the Meshuggah composition “Do Not Look Down”. By considering an architectonic rhythmic framework within “Do Not Look Down” as the controlling organisation mechanism, an exploration of the interaction between distinct rhythmic layers and the composition’s formal segmentation and harmony (as riffs), reveals a pervasive structural misalignment between these elements. By exhibiting how Meshuggah’s manipulations of rhythmic complexities deliberately blur structural boundaries, creating misalignments in a flat approach to temporal partitioning (Nieto 2014), rhythmic characteristics of Meshuggah and the genre of Djent are exposed.

Keywords: hypermeter, rhythmic parallax, meshuggah, temporal partitioning

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419 3D Images Representation to Provide Information on the Type of Castella Beams Hole

Authors: Cut Maisyarah Karyati, Aries Muslim, Sulardi

Abstract:

Digital image processing techniques to obtain detailed information from an image have been used in various fields, including in civil engineering, where the use of solid beam profiles in buildings and bridges has often been encountered since the early development of beams. Along with this development, the founded castellated beam profiles began to be more diverse in shape, such as the shape of a hexagon, triangle, pentagon, circle, ellipse and oval that could be a practical solution in optimizing a construction because of its characteristics. The purpose of this research is to create a computer application to edge detect the profile of various shapes of the castella beams hole. The digital image segmentation method has been used to obtain the grayscale images and represented in 2D and 3D formats. This application has been successfully made according to the desired function, which is to provide information on the type of castella beam hole.

Keywords: digital image, image processing, edge detection, grayscale, castella beams

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418 A Data-Driven Platform for Studying the Liquid Plug Splitting Ratio

Authors: Ehsan Atefi, Michael Grigware

Abstract:

Respiratory failure secondary to surfactant deficiency resulting from respiratory distress syndrome is considered one major cause of morbidity in preterm infants. Surfactant replacement treatment (SRT) is considered an effective treatment for this disease. Here, we introduce an AI-mediated approach for estimating the distribution of surfactant in the lung airway of a newborn infant during SRT. Our approach implements machine learning to precisely estimate the splitting ratio of a liquid drop during bifurcation at different injection velocities and patient orientations. This technique can be used to calculate the surfactant residue remaining on the airway wall during the surfactant injection process. Our model works by minimizing the pressure drop difference between the two airway branches at each generation, subject to mass and momentum conservation. Our platform can be used to generate feedback for immediately adjusting the velocity of injection and patient orientation during SRT.

Keywords: respiratory failure, surfactant deficiency, surfactant replacement, machine learning

Procedia PDF Downloads 126