Search results for: angle classification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3482

Search results for: angle classification

2162 Image Segmentation Using 2-D Histogram in RGB Color Space in Digital Libraries

Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

Abstract:

This paper presents an unsupervised color image segmentation method. It is based on a hierarchical analysis of 2-D histogram in RGB color space. This histogram minimizes storage space of images and thus facilitates the operations between them. The improved segmentation approach shows a better identification of objects in a color image and, at the same time, the system is fast.

Keywords: image segmentation, hierarchical analysis, 2-D histogram, classification

Procedia PDF Downloads 370
2161 Movable Airfoil Arm (MAA) and Ducting Effect to Increase the Efficiency of a Helical Turbine

Authors: Abdi Ismail, Zain Amarta, Riza Rifaldy Argaputra

Abstract:

The Helical Turbine has the highest efficiency in comparison with the other hydrokinetic turbines. However, the potential of the Helical Turbine efficiency can be further improved so that the kinetic energy of a water current can be converted into mechanical energy as much as possible. This paper explains the effects by adding a Movable Airfoil Arm (MAA) and ducting on a Helical Turbine. The first research conducted an analysis of the efficiency comparison between a Plate Arm Helical Turbine (PAHT) versus a Movable Arm Helical Turbine Airfoil (MAAHT) at various water current velocities. The first step is manufacturing a PAHT and MAAHT. The PAHT and MAAHT has these specifications (as a fixed variable): 80 cm in diameter, a height of 88 cm, 3 blades, NACA 0018 blade profile, a 10 cm blade chord and a 60o inclination angle. The MAAHT uses a NACA 0012 airfoil arm that can move downward 20o, the PAHT uses a 5 mm plate arm. At the current velocity of 0.8, 0.85 and 0.9 m/s, the PAHT respectively generates a mechanical power of 92, 117 and 91 watts (a consecutive efficiency of 16%, 17% and 11%). At the same current velocity variation, the MAAHT respectively generates 74, 60 and 43 watts (a consecutive efficiency of 13%, 9% and 5%). Therefore, PAHT has a better performance than the MAAHT. Using analysis from CFD (Computational Fluid Dynamics), the drag force of MAA is greater than the one generated by the plate arm. By using CFD analysis, the drag force that occurs on the MAA is more dominant than the lift force, therefore the MAA can be called a drag device, whereas the lift force that occurs on the helical blade is more dominant than the drag force, therefore it can be called a lift device. Thus, the lift device cannot be combined with the drag device, because the drag device will become a hindrance to the lift device rotation. The second research conducted an analysis of the efficiency comparison between a Ducted Helical Turbine (DHT) versus a Helical Turbine (HT) through experimental studies. The first step is manufacturing the DHT and HT. The Helical turbine specifications (as a fixed variable) are: 40 cm in diameter, a height of 88 cm, 3 blades, NACA 0018 blade profile, 10 cm blade chord and a 60o inclination angle. At the current speed of 0.7, 0.8, 0.9 and 1.1 m/s, the HT respectively generates a mechanical power of 72, 85, 93 and 98 watts (a consecutive efficiency of 38%, 30%, 23% and 13%). At the same current speed variation, the DHT generates a mechanical power of 82, 98, 110 and 134 watts (a consecutive efficiency of 43%, 34%, 27% and 18%), respectively. The usage of ducting causes the water current speed around the turbine to increase.

Keywords: hydrokinetic turbine, helical turbine, movable airfoil arm, ducting

Procedia PDF Downloads 366
2160 Synthesis and Characterization of PVDF, FG, PTFE, and PES Membrane Distillation Modified with Silver Nanoparticles

Authors: Lopez J., Mehrvar M., Quinones E., Suarez A., RomeroC.

Abstract:

The Silver Nanoparticles (AgNP) are used as deliver of heat on surface of Membrane Distillation in order to fight against Thermal Polarization and improving the Desalination Process. In this study AgNPwere deposited by dip coating process over PVDF, FG hydrophilic, and PTFE hydrophobic commercial membranes as substrate. Membranes were characterized by SEM, EDS, contact angle, Pore size distributionand using a UV lamp and a thermal camera were measured the performance of heat deliver. The presence of AgNP 50 – 150 nm and the increase in absorption of energy over membrane were verified.

Keywords: silver nanoparticles, membrane distillation, plasmon effect, heat deliver

Procedia PDF Downloads 112
2159 Use of a Business Intelligence Software for Interactive Visualization of Data on the Swiss Elite Sports System

Authors: Corinne Zurmuehle, Andreas Christoph Weber

Abstract:

In 2019, the Swiss Federal Institute of Sport Magglingen (SFISM) conducted a mixed-methods study on the Swiss elite sports system, which yielded a large quantity of research data. In a quantitative online survey, 1151 elite sports athletes, 542 coaches, and 102 Performance Directors of national sports federations (NF) have submitted their perceptions of the national support measures of the Swiss elite sports system. These data provide an essential database for the further development of the Swiss elite sports system. The results were published in a report presenting the results divided into 40 Olympic summer and 14 winter sports (Olympic classification). The authors of this paper assume that, in practice, this division is too unspecific to assess where further measures would be needed. The aim of this paper is to find appropriate parameters for data visualization in order to identify disparities in sports promotion that allow an assessment of where further interventions by Swiss Olympic (NF umbrella organization) are required. Method: First, the variable 'salary earned from sport' was defined as a variable to measure the impact of elite sports promotion. This variable was chosen as a measure as it represents an important indicator for the professionalization of elite athletes and therefore reflects national level sports promotion measures applied by Swiss Olympic. Afterwards, the variable salary was tested with regard to the correlation between Olympic classification [a], calculating the Eta coefficient. To estimate the appropriate parameters for data visualization, the correlation between salary and four further parameters was analyzed by calculating the Eta coefficient: [a] sport; [b] prioritization (from 1 to 5) of the sports by Swiss Olympic; [c] gender; [d] employment level in sports. Results & Discussion: The analyses reveal a very small correlation between salary and Olympic classification (ɳ² = .011, p = .005). Gender demonstrates an even small correlation (ɳ² = .006, p = .014). The parameter prioritization was correlating with small effect (ɳ² = .017, p = .001) as did employment level (ɳ² = .028, p < .001). The highest correlation was identified by the parameter sport with a moderate effect (ɳ² = .075, p = .047). The analyses show that the disparities in sports promotion cannot be determined by a particular parameter but presumably explained by a combination of several parameters. We argue that the possibility of combining parameters for data visualization should be enabled when the analysis is provided to Swiss Olympic for further strategic decision-making. However, the inclusion of multiple parameters massively multiplies the number of graphs and is therefore not suitable for practical use. Therefore, we suggest to apply interactive dashboards for data visualization using Business Intelligence Software. Practical & Theoretical Contribution: This contribution provides the first attempt to use Business Intelligence Software for strategic decision-making in national level sports regarding the prioritization of national resources for sports and athletes. This allows to set specific parameters with a significant effect as filters. By using filters, parameters can be combined and compared against each other and set individually for each strategic decision.

Keywords: data visualization, business intelligence, Swiss elite sports system, strategic decision-making

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2158 The AI Method and System for Analyzing Wound Status in Wound Care Nursing

Authors: Ho-Hsin Lee, Yue-Min Jiang, Shu-Hui Tsai, Jian-Ren Chen, Mei-Yu XU, Wen-Tien Wu

Abstract:

This project presents an AI-based method and system for wound status analysis. The system uses a three-in-one sensor device to analyze wound status, including color, temperature, and a 3D sensor to provide wound information up to 2mm below the surface, such as redness, heat, and blood circulation information. The system has a 90% accuracy rate, requiring only one manual correction in 70% of cases, with a one-second delay. The system also provides an offline application that allows for manual correction of the wound bed range using color-based guidance to estimate wound bed size with 96% accuracy and a maximum of one manual correction in 96% of cases, with a one-second delay. Additionally, AI-assisted wound bed range selection achieves 100% of cases without manual intervention, with an accuracy rate of 76%, while AI-based wound tissue type classification achieves an 85.3% accuracy rate for five categories. The AI system also includes similar case search and expert recommendation capabilities. For AI-assisted wound range selection, the system uses WIFI6 technology, increasing data transmission speeds by 22 times. The project aims to save up to 64% of the time required for human wound record keeping and reduce the estimated time to assess wound status by 96%, with an 80% accuracy rate. Overall, the proposed AI method and system integrate multiple sensors to provide accurate wound information and offer offline and online AI-assisted wound bed size estimation and wound tissue type classification. The system decreases delay time to one second, reduces the number of manual corrections required, saves time on wound record keeping, and increases data transmission speed, all of which have the potential to significantly improve wound care and management efficiency and accuracy.

Keywords: wound status analysis, AI-based system, multi-sensor integration, color-based guidance

Procedia PDF Downloads 100
2157 Improving Chest X-Ray Disease Detection with Enhanced Data Augmentation Using Novel Approach of Diverse Conditional Wasserstein Generative Adversarial Networks

Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

Abstract:

Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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2156 Application of 1-MCP on ‘Centro’ Melon at Different Days after Harvest

Authors: L. P. L. Nguyen, G. Hitka, T. Zsom, Z. Kókai

Abstract:

This study is aimed to investigate the influence of postharvest delays of 1-Methylcyclopropene (1-MCP) treatment on prolonging the storage potential of melon. Melons were treated with 625-650 ppb 1-MCP at 10 °C for 24 hours on the 1st, 3rd and 5th day after harvest. Decreased ethylene production and retarded softening of melon fruits after 7 days of storage at 10 °C plus 3 days of shelflife were obtained by 1-MCP applications. 1-MCP strongly affected the chlorophyll fluorescence characteristics and hue angle values of melon. After shelf-life, the peel color of treated melon was slow in turning to yellow compared to the control. Additionally, firmness of melons treated on the first day after harvest was 38% higher than that of the control fruit. Results showed that fruits treated on the 1st and the 3rd day after harvest could maintain the quality of melon.

Keywords: 1-MCP, muskmelon, storage, treatment.

Procedia PDF Downloads 217
2155 Nanorods Based Dielectrophoresis for Protein Concentration and Immunoassay

Authors: Zhen Cao, Yu Zhu, Junxue Fu

Abstract:

Immunoassay, i.e., antigen-antibody reaction, is crucial for disease diagnostics. To achieve the adequate signal of the antigen protein detection, a large amount of sample and long incubation time is needed. However, the amount of protein is usually small at the early stage, which makes it difficult to detect. Unlike cells and DNAs, no valid chemical method exists for protein amplification. Thus, an alternative way to improve the signal is through particle manipulation techniques to concentrate proteins, among which dielectrophoresis (DEP) is an effective one. DEP is a technique that concentrates particles to the designated region through a force created by the gradient in a non-uniform electric field. Since DEP force is proportional to the cube of particle size and square of electric field gradient, it is relatively easy to capture larger particles such as cells. For smaller ones like proteins, a super high gradient is then required. In this work, three-dimensional Ag/SiO2 nanorods arrays, fabricated by an easy physical vapor deposition technique called as oblique angle deposition, have been integrated with a DEP device and created the field gradient as high as of 2.6×10²⁴ V²/m³. The nanorods based DEP device is able to enrich bovine serum albumin (BSA) protein by 1800-fold and the rate has reached 180-fold/s when only applying 5 V electric potential. Based on the above nanorods integrated DEP platform, an immunoassay of mouse immunoglobulin G (IgG) proteins has been performed. Briefly, specific antibodies are immobilized onto nanorods, then IgG proteins are concentrated and captured, and finally, the signal from fluorescence-labelled antibodies are detected. The limit of detection (LoD) is measured as 275.3 fg/mL (~1.8 fM), which is a 20,000-fold enhancement compared with identical assays performed on blank glass plates. Further, prostate-specific antigen (PSA), which is a cancer biomarker for diagnosis of prostate cancer after radical prostatectomy, is also quantified with a LoD as low as 2.6 pg/mL. The time to signal saturation has been significantly reduced to one minute. In summary, together with an easy nanorod fabrication and integration method, this nanorods based DEP platform has demonstrated highly sensitive immunoassay performance and thus poses great potentials in applications for early point-of-care diagnostics.

Keywords: dielectrophoresis, immunoassay, oblique angle deposition, protein concentration

Procedia PDF Downloads 98
2154 Generating Synthetic Chest X-ray Images for Improved COVID-19 Detection Using Generative Adversarial Networks

Authors: Muneeb Ullah, Daishihan, Xiadong Young

Abstract:

Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

Procedia PDF Downloads 79
2153 Better Defined WHO International Classification of Disease Codes for Relapsing Fever Borreliosis, and Lyme Disease Education Aiding Diagnosis, Treatment Improving Human Right to Health

Authors: Mualla McManus, Jenna Luche Thaye

Abstract:

World Health Organisation International Classification of Disease codes were created to define disease including infections in order to guide and educate diagnosticians. Most infectious diseases such as syphilis are clearly defined by their ICD 10 codes and aid/help to educate the clinicians in syphilis diagnosis and treatment globally. However, current ICD 10 codes for relapsing fever Borreliosis and Lyme disease are less clearly defined and can impede appropriate diagnosis especially if the clinician is not familiar with the symptoms of these infectious diseases. This is despite substantial number of scientific articles published in peer-reviewed journals about relapsing fever and Lyme disease. In the USA there are estimated 380,000 people annually contacting Lyme disease, more cases than breast cancer and 6x HIV/AIDS cases. This represents estimated 0.09% of the USA population. If extrapolated to the global population (7billion), 0.09% equates to 63 million people contracting relapsing fever or Lyme disease. In many regions, the rate of contracting some form of infection from tick bite may be even higher. Without accurate and appropriate diagnostic codes, physicians are impeded in their ability to properly care for their patients, leaving those patients invisible and marginalized within the medical system and to those guiding public policy. This results in great personal hardship, pain, disability, and expense. This unnecessarily burdens health care systems, governments, families, and society as a whole. With accurate diagnostic codes in place, robust data can guide medical and public health research, health policy, track mortality and save health care dollars. Better defined ICD codes are the way forward in educating the diagnosticians about relapsing fever and Lyme diseases.

Keywords: WHO ICD codes, relapsing fever, Lyme diseases, World Health Organisation

Procedia PDF Downloads 184
2152 Models to Estimate Monthly Mean Daily Global Solar Radiation on a Horizontal Surface in Alexandria

Authors: Ahmed R. Abdelaziz, Zaki M. I. Osha

Abstract:

Solar radiation data are of great significance for solar energy system design. This study aims at developing and calibrating new empirical models for estimating monthly mean daily global solar radiation on a horizontal surface in Alexandria, Egypt. Day length hours, sun height, day number, and declination angle calculated data are used for this purpose. A comparison between measured and calculated values of solar radiation is carried out. It is shown that all the proposed correlations are able to predict the global solar radiation with excellent accuracy in Alexandria.

Keywords: solar energy, global solar radiation, model, regression coefficient

Procedia PDF Downloads 394
2151 Landslide and Liquefaction Vulnerability Analysis Using Risk Assessment Analysis and Analytic Hierarchy Process Implication: Suitability of the New Capital of the Republic of Indonesia on Borneo Island

Authors: Rifaldy, Misbahudin, Khalid Rizky, Ricky Aryanto, M. Alfiyan Bagus, Fahri Septianto, Firman Najib Wibisana, Excobar Arman

Abstract:

Indonesia is a country that has a high level of disaster because it is on the ring of fire, and there are several regions with three major plates meeting in the world. So that disaster analysis must always be done to see the potential disasters that might always occur, especially in this research are landslides and liquefaction. This research was conducted to analyze areas that are vulnerable to landslides and liquefaction hazards and their relationship with the assessment of the issue of moving the new capital of the Republic of Indonesia to the island of Kalimantan with a total area of 612,267.22 km². The method in this analysis uses the Analytical Hierarchy Process and consistency ratio testing as a complex and unstructured problem-solving process into several parameters by providing values. The parameters used in this analysis are the slope, land cover, lithology distribution, wetness index, earthquake data, peak ground acceleration. Weighted overlay was carried out from all these parameters using the percentage value obtained from the Analytical Hierarchy Process and confirmed its accuracy with a consistency ratio so that a percentage of the area obtained with different vulnerability classification values was obtained. Based on the analysis results obtained vulnerability classification from very high to low vulnerability. There are (0.15%) 918.40083 km² of highly vulnerable, medium (20.75%) 127,045,44815 km², low (56.54%) 346,175.886188 km², very low (22.56%) 138,127.484832 km². This research is expected to be able to map landslides and liquefaction disasters on the island of Kalimantan and provide consideration of the suitability of regional development of the new capital of the Republic of Indonesia. Also, this research is expected to provide input or can be applied to all regions that are analyzing the vulnerability of landslides and liquefaction or the suitability of the development of certain regions.

Keywords: analytic hierarchy process, Borneo Island, landslide and liquefaction, vulnerability analysis

Procedia PDF Downloads 156
2150 Erosion Wear of Cast Al-Si Alloys

Authors: Pooja Verma, Rajnesh Tyagi, Sunil Mohan

Abstract:

Al-Si alloys are widely used in various components such as liner-less engine blocks, piston, compressor bodies and pumps for automobile sector and aerospace industries due to their excellent combination of properties like low thermal expansion coefficient, low density, excellent wear resistance, high corrosion resistance, excellent cast ability, and high hardness. The low density and high hardness of primary Si phase results in significant reduction in density and improvement in wear resistance of hypereutectic Al-Si alloys. Keeping in view of the industrial importance of the alloys, hypereutectic Al-Si alloys containing 14, 16, 18 and 20 wt. % of Si were prepared in a resistance furnace using adequate amount of deoxidizer and degasser and their erosion behavior was evaluated by conducting tests at impingement angles of 30°, 60°, and 90° with an erodent discharge rate of 7.5 Hz, pressure 1 bar using erosion test rig. Microstructures of the cast alloys were examined using Optical microscopy (OM) and scanning electron microscopy (SEM) and the presence of Si particles was confirmed by x-ray diffractometer (XRD). The mechanical properties and hardness were measured using uniaxial tension tests at a strain rate of 10-3/s and Vickers hardness tester. Microstructures of the alloys and X-ray examination revealed the presence of primary and eutectic Si particles in the shape of cuboids or polyhedral and finer needles. Yield strength (YS), ultimate tensile strength (UTS), and uniform elongation of the hypereutectic Al-Si alloys were observed to increase with increasing content of Si. The optimal strength and ductility was observed for Al-20 wt. % Si alloy which is significantly higher than the Al-14 wt. % Si alloy. The increased hardness and the strength of the alloys with increasing amount of Si has been attributed presence of Si in the solid solution which creates strain, and this strain interacts with dislocations resulting in solid-solution strengthening. The interactions between distributed primary Si particles and dislocations also provide Orowan strengthening leading to increased strength. The steady state erosion rate was found to decrease with increasing angle of impact as well as Si content for all the alloys except at 900 where it was observed to increase with the increase in the Si content. The minimum erosion rate is observed in Al-20 wt. % Si alloy at 300 and 600 impingement angles because of its higher hardness in comparison to other alloys. However, at 90° impingement angle the wear rate for Al-20 wt. % Si alloy is found to be the minimum due to deformation, subsequent cracking and chipping off material.

Keywords: Al-Si alloy, erosion wear, cast alloys, dislocation, strengthening

Procedia PDF Downloads 59
2149 Effects of Injector Nozzle Geometry on Spray Atomization Characteristics

Authors: Arya Pirooz

Abstract:

Air and fuel must be mixed correctly so that there is perfect combustion, which calls for fuel atomization by injection. In this study, the effects of different parameters such as number of orifices, length and diameter of orifices, diameter of nozzle sac and the angle of needle seat in injectors were investigated with the use of rate of injection and sac pressure. The unit pump of the OM-457 diesel engine was modelled on Avl-Hydsim. The results illustrate that the sac pressure decreased by 46% when the number of holes were doubled, although the rate of injection had an immense change. Also, the sac pressure increased up to 60% when the diameter of orifices decreased by 40% in spite of the semi-constant injection rate.

Keywords: injection, OM-457 engine, nozzle geometry, atomization

Procedia PDF Downloads 489
2148 A Convolution Neural Network Approach to Predict Pes-Planus Using Plantar Pressure Mapping Images

Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

Abstract:

Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

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2147 Remote Sensing and Geographic Information Systems for Identifying Water Catchments Areas in the Northwest Coast of Egypt for Sustainable Agricultural Development

Authors: Mohamed Aboelghar, Ayman Abou Hadid, Usama Albehairy, Asmaa Khater

Abstract:

Sustainable agricultural development of the desert areas of Egypt under the pressure of irrigation water scarcity is a significant national challenge. Existing water harvesting techniques on the northwest coast of Egypt do not ensure the optimal use of rainfall for agricultural purposes. Basin-scale hydrology potentialities were studied to investigate how available annual rainfall could be used to increase agricultural production. All data related to agricultural production included in the form of geospatial layers. Thematic classification of Sentinal-2 imagery was carried out to produce the land cover and crop maps following the (FAO) system of land cover classification. Contour lines and spot height points were used to create a digital elevation model (DEM). Then, DEM was used to delineate basins, sub-basins, and water outlet points using the Soil and Water Assessment Tool (Arc SWAT). Main soil units of the study area identified from Land Master Plan maps. Climatic data collected from existing official sources. The amount of precipitation, surface water runoff, potential, and actual evapotranspiration for the years (2004 to 2017) shown as results of (Arc SWAT). The land cover map showed that the two tree crops (olive and fig) cover 195.8 km2 when herbaceous crops (barley and wheat) cover 154 km2. The maximum elevation was 250 meters above sea level when the lowest one was 3 meters below sea level. The study area receives a massive variable amount of precipitation; however, water harvesting methods are inappropriate to store water for purposes.

Keywords: water catchements, remote sensing, GIS, sustainable agricultural development

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2146 Computer Aide Discrimination of Benign and Malignant Thyroid Nodules by Ultrasound Imaging

Authors: Akbar Gharbali, Ali Abbasian Ardekani, Afshin Mohammadi

Abstract:

Introduction: Thyroid nodules have an incidence of 33-68% in the general population. More than 5-15% of these nodules are malignant. Early detection and treatment of thyroid nodules increase the cure rate and provide optimal treatment. Between the medical imaging methods, Ultrasound is the chosen imaging technique for assessment of thyroid nodules. The confirming of the diagnosis usually demands repeated fine-needle aspiration biopsy (FNAB). So, current management has morbidity and non-zero mortality. Objective: To explore diagnostic potential of automatic texture analysis (TA) methods in differentiation benign and malignant thyroid nodules by ultrasound imaging in order to help for reliable diagnosis and monitoring of the thyroid nodules in their early stages with no need biopsy. Material and Methods: The thyroid US image database consists of 70 patients (26 benign and 44 malignant) which were reported by Radiologist and proven by the biopsy. Two slices per patient were loaded in Mazda Software version 4.6 for automatic texture analysis. Regions of interests (ROIs) were defined within the abnormal part of the thyroid nodules ultrasound images. Gray levels within an ROI normalized according to three normalization schemes: N1: default or original gray levels, N2: +/- 3 Sigma or dynamic intensity limited to µ+/- 3σ, and N3: present intensity limited to 1% - 99%. Up to 270 multiscale texture features parameters per ROIs per each normalization schemes were computed from well-known statistical methods employed in Mazda software. From the statistical point of view, all calculated texture features parameters are not useful for texture analysis. So, the features based on maximum Fisher coefficient and the minimum probability of classification error and average correlation coefficients (POE+ACC) eliminated to 10 best and most effective features per normalization schemes. We analyze this feature under two standardization states (standard (S) and non-standard (NS)) with Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA). The 1NN classifier was performed to distinguish between benign and malignant tumors. The confusion matrix and Receiver operating characteristic (ROC) curve analysis were used for the formulation of more reliable criteria of the performance of employed texture analysis methods. Results: The results demonstrated the influence of the normalization schemes and reduction methods on the effectiveness of the obtained features as a descriptor on discrimination power and classification results. The selected subset features under 1%-99% normalization, POE+ACC reduction and NDA texture analysis yielded a high discrimination performance with the area under the ROC curve (Az) of 0.9722, in distinguishing Benign from Malignant Thyroid Nodules which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Conclusions: Our results indicate computer-aided diagnosis is a reliable method, and can provide useful information to help radiologists in the detection and classification of benign and malignant thyroid nodules.

Keywords: ultrasound imaging, thyroid nodules, computer aided diagnosis, texture analysis, PCA, LDA, NDA

Procedia PDF Downloads 270
2145 An Algebraic Geometric Imaging Approach for Automatic Dairy Cow Body Condition Scoring System

Authors: Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, Yoichiro Horii

Abstract:

Today dairy farm experts and farmers have well recognized the importance of dairy cow Body Condition Score (BCS) since these scores can be used to optimize milk production, managing feeding system and as an indicator for abnormality in health even can be utilized to manage for having healthy calving times and process. In tradition, BCS measures are done by animal experts or trained technicians based on visual observations focusing on pin bones, pin, thurl and hook area, tail heads shapes, hook angles and short and long ribs. Since the traditional technique is very manual and subjective, the results can lead to different scores as well as not cost effective. Thus this paper proposes an algebraic geometric imaging approach for an automatic dairy cow BCS system. The proposed system consists of three functional modules. In the first module, significant landmarks or anatomical points from the cow image region are automatically extracted by using image processing techniques. To be specific, there are 23 anatomical points in the regions of ribs, hook bones, pin bone, thurl and tail head. These points are extracted by using block region based vertical and horizontal histogram methods. According to animal experts, the body condition scores depend mainly on the shape structure these regions. Therefore the second module will investigate some algebraic and geometric properties of the extracted anatomical points. Specifically, the second order polynomial regression is employed to a subset of anatomical points to produce the regression coefficients which are to be utilized as a part of feature vector in scoring process. In addition, the angles at thurl, pin, tail head and hook bone area are computed to extend the feature vector. Finally, in the third module, the extracted feature vectors are trained by using Markov Classification process to assign BCS for individual cows. Then the assigned BCS are revised by using multiple regression method to produce the final BCS score for dairy cows. In order to confirm the validity of proposed method, a monitoring video camera is set up at the milk rotary parlor to take top view images of cows. The proposed method extracts the key anatomical points and the corresponding feature vectors for each individual cows. Then the multiple regression calculator and Markov Chain Classification process are utilized to produce the estimated body condition score for each cow. The experimental results tested on 100 dairy cows from self-collected dataset and public bench mark dataset show very promising with accuracy of 98%.

Keywords: algebraic geometric imaging approach, body condition score, Markov classification, polynomial regression

Procedia PDF Downloads 148
2144 Xen45 Gel Implant in Open Angle Glaucoma: Efficacy, Safety and Predictors of Outcome

Authors: Fossarello Maurizio, Mattana Giorgio, Tatti Filippo.

Abstract:

The most widely performed surgical procedure in Open-Angle Glaucoma (OAG) is trabeculectomy. Although this filtering procedure is extremely effective, surgical failure and postoperative complications are reported. Due to the its invasive nature and possible complications, trabeculectomy is usually reserved, in practice, for patients who are refractory to medical and laser therapy. Recently, a number of micro-invasive surgical techniques (MIGS: Micro-Invasive Glaucoma Surgery), have been introduced in clinical practice. They meet the criteria of micro-incisional approach, minimal tissue damage, short surgical time, reliable IOP reduction, extremely high safety profile and rapid post-operative recovery. Xen45 Gel Implant (Allergan, Dublin, Ireland) is one of the MIGS alternatives, and consists in a porcine gelatin tube designed to create an aqueous flow from the anterior chamber to the subconjunctival space, bypassing the resistance of the trabecular meshwork. In this study we report the results of this technique as a favorable option in the treatment of OAG for its benefits in term of efficacy and safety, either alone or in combination with cataract surgery. This is a retrospective, single-center study conducted in consecutive OAG patients, who underwent Xen45 Gel Stent implantation alone or in combination with phacoemulsification, from October 2018 to June 2019. The primary endpoint of the study was to evaluate the reduction of both IOP and number of antiglaucoma medications at 12 months. The secondary endpoint was to correlate filtering bleb morphology evaluated by means of anterior segment OCT with efficacy in IOP lowering and eventual further procedures requirement. Data were recorded on Microsoft Excel and study analysis was performed using Microsoft Excel and SPSS (IBM). Mean values with standard deviations were calculated for IOPs and number of antiglaucoma medications at all points. Kolmogorov-Smirnov test showed that IOP followed a normal distribution at all time, therefore the paired Student’s T test was used to compare baseline and postoperative mean IOP. Correlation between postoperative Day 1 IOP and Month 12 IOP was evaluated using Pearson coefficient. Thirty-six eyes of 36 patients were evaluated. As compared to baseline, mean IOP and the mean number of antiglaucoma medications significantly decreased from 27,33 ± 7,67 mmHg to 16,3 ± 2,89 mmHg (38,8% reduction) and from 2,64 ± 1,39 to 0,42 ± 0,8 (84% reduction), respectively, at 12 months after surgery (both p < 0,001). According to bleb morphology, eyes were divided in uniform group (n=8, 22,2%), subconjunctival separation group (n=5, 13,9%), microcystic multiform group (n=9, 25%) and multiple internal layer group (n=14, 38,9%). Comparing to baseline, there was no significative difference in IOP between the 4 groups at month 12 follow-up visit. Adverse events included bleb function decrease (n=14, 38,9%), hypotony (n=8, 22,2%) and choroidal detachment (n=2, 5,6%). All eyes presenting bleb flattening underwent needling and MMC injection. The higher percentage of patients that required secondary needling was in the uniform group (75%), with a significant difference between the groups (p=0,03). Xen45 gel stent, either alone or in combination with phacoemulsification, provided a significant lowering in both IOP and medical antiglaucoma treatment and an elevated safety profile.

Keywords: anterior segment OCT, bleb morphology, micro-invasive glaucoma surgery, open angle glaucoma, Xen45 gel implant

Procedia PDF Downloads 136
2143 Experimental Activity on the Photovoltaic Effect

Authors: Salomão Manuel Francisco, Manuel António Salgueiro Da Silva, Bento Filipe Barreiras Pinto Cavadas, Teresa Monteiro Seixas

Abstract:

In bachelor's degrees in Physics Education framework in Angola, and to a certain extent, within the community of Portuguese language countries (CPLP), teaching methodologies rely heavily on theoretical memorization and mathematical demonstrations. This approach often discourages students, particularly the female population, as the reliance on theoretical mathematical demonstrations generates the perception of Physics as an arduous, challenging discipline. To address this challenge and recognize the value of practical application as an evaluative criterion of material truth, we propose a practical activity in Environmental Physics that will be shared with Angolan higher education teachers, who will receive full scaffolding and support from the authors. These teachers, adopting and developing similar activities in a classroom setting, will contribute to the environmental education framework as well. Additionally, this work aligns with different goals of UNESCO's 2030 agenda, namely, specifically, goals 4, 5, 7, 11, 13, and 17. The experimental activity developed in this work is centered around the demonstration of the photovoltaic effect and its application for renewable energy production. The first objective of the activity is to study the variation of electrical power supplied by a photovoltaic system (PV) to an electrical circuit as the angle of light incidence changes. Students can observe that the power supplied to the circuit is greater when light rays fall perpendicularly on the PV. However, as the angle of incidence increases, resulting in a larger area covered by the light rays, the power supplied to the circuit decreases due to lower irradiance. The second objective is to demonstrate that the power output can be maximized by adjusting the circuit load resistance at each irradiance value. In these two parts of the activity, students can analyze experimental data taking into account the irradiance law and the equivalent circuit description of a PV cell. Through detailed data analysis, students are also expected to assess the effects of temperature on PV efficiency degradation and the efficiency enhancement provided by light concentration mechanisms. As a third objective, students can explore how the color of incident light affects the PV output power, considering the quantum nature of light and its interaction with the PV system.

Keywords: experiments, irradiation law, physic teaching, photovoltaic effect

Procedia PDF Downloads 73
2142 Effects of Transcutaneous Electrical Pelvic Floor Muscle Stimulation on Peri-Vulva Area on Stress Urinary Incontinence: A Preliminary Study

Authors: Kim Ji-Hyun, Jeon Hye-Seon, Kwon Oh-Yun, Park Eun-Young, Hwang Ui-Jae, Gwak Gyeong-Tae, Yoon Hyeo-Bin

Abstract:

Stress urinary incontinence (SUI), a common women health problem, is an involuntary leakage of urine while sneezing, coughing, or physical exertion caused by insufficient strength of the pelvic floor and sphincter muscles. SUI also leads to decrease in quality of life and limits sexual activities. SUI is related to the increased bladder neck angle, bladder neck movement, funneling index, urethral width, and decreased urethral length. Various pelvic floor muscle electrical stimulation (ES) interventions have been applied to improve the symptoms of the people with SUI. ES activates afferent fibers of pudendal nerve and smoothly induces contractions of the pelvic floor muscles such as striated periurethral muscles and striated pelvic floor muscles. ES via intravaginal electrodes are the most frequently used types of the pelvic floor muscle ES for the female SUI. However, inserted electrode is uncomfortable and it increases the risks of infection. The purpose of this preliminary study was to determine if the 8-week transcutaneous pelvic floor ES would be effective to improve the symptoms and satisfaction of the females with SUI. Easy-K, specially designed ES equipment for the people with SUI, was used in this study. The oval shape stimulator can be placed on a toilet seat, and the surface has invaded electrode fit to contact with the entire vulva area while users are sitting on the stimulator. Five women with SUI were included in this experiment. Prior to the participation, subjects were instructed about procedures and precautions in using the ES. They have used the stimulator once a day for 20 minutes for each session at home. Outcome data was collected 3 times at the baseline, 4 weeks and 8 weeks after the intervention. Intravaginal sonography was used to measure the bladder neck angle, bladder neck movement, funneling index, thickness of an anterior rhabdosphincter and a posterior rhabdosphincter, urethral length, and urethral width. Leavator ani muscle (LAM) contraction strength was assessed by manual palpation according to the oxford scoring system. In addition, incontinence quality of life (IQOL) and female sexual function index (FSFI) questionnaires were used to obtain addition subjective information. Friedman test, a nonparametric statistical test, was used to determine the effectiveness of the ES. The Wilcoxon test was used for the post-hoc analysis and the significance level was set at .05. The bladder neck angle, funneling index and urethral width were significantly decreased after 8-weeks of intervention (p<.05). LAM contraction score, urethral length and anterior and posterior rhabdosphicter thickness were statistically increased by the intervention (p<.05). However, no significant change was found in the bladder neck movement. Although total score of the IQOL did not improve, the score of the ‘avoidance’ subscale of IQOL had significant improved (p<.05). FSFI had statistical difference in FSFI total score and ‘desire’ subscale (p<.05). In conclusion, 8-week use of a transcutaneous ES on peri-vulva area improved dynamic mechanical structures of the pelvic floor musculature as well as IQOL and conjugal relationship.

Keywords: electrical stimulation, Pelvic floor muscle, sonography, stress urinary incontinence, women health

Procedia PDF Downloads 144
2141 Multi-Size Continuous Particle Separation on a Dielectrophoresis-Based Microfluidics Chip

Authors: Arash Dalili, Hamed Tahmouressi, Mina Hoorfar

Abstract:

Advances in lab-on-a-chip (LOC) devices have led to significant advances in the manipulation, separation, and isolation of particles and cells. Among the different active and passive particle manipulation methods, dielectrophoresis (DEP) has been proven to be a versatile mechanism as it is label-free, cost-effective, simple to operate, and has high manipulation efficiency. DEP has been applied for a wide range of biological and environmental applications. A popular form of DEP devices is the continuous manipulation of particles by using co-planar slanted electrodes, which utilizes a sheath flow to focus the particles into one side of the microchannel. When particles enter the DEP manipulation zone, the negative DEP (nDEP) force generated by the slanted electrodes deflects the particles laterally towards the opposite side of the microchannel. The lateral displacement of the particles is dependent on multiple parameters including the geometry of the electrodes, the width, length and height of the microchannel, the size of the particles and the throughput. In this study, COMSOL Multiphysics® modeling along with experimental studies are used to investigate the effect of the aforementioned parameters. The electric field between the electrodes and the induced DEP force on the particles are modelled by COMSOL Multiphysics®. The simulation model is used to show the effect of the DEP force on the particles, and how the geometry of the electrodes (width of the electrodes and the gap between them) plays a role in the manipulation of polystyrene microparticles. The simulation results show that increasing the electrode width to a certain limit, which depends on the height of the channel, increases the induced DEP force. Also, decreasing the gap between the electrodes leads to a stronger DEP force. Based on these results, criteria for the fabrication of the electrodes were found, and soft lithography was used to fabricate interdigitated slanted electrodes and microchannels. Experimental studies were run to find the effect of the flow rate, geometrical parameters of the microchannel such as length, width, and height as well as the electrodes’ angle on the displacement of 5 um, 10 um and 15 um polystyrene particles. An empirical equation is developed to predict the displacement of the particles under different conditions. It is shown that the displacement of the particles is more for longer and lower height channels, lower flow rates, and bigger particles. On the other hand, the effect of the angle of the electrodes on the displacement of the particles was negligible. Based on the results, we have developed an optimum design (in terms of efficiency and throughput) for three size separation of particles.

Keywords: COMSOL Multiphysics, Dielectrophoresis, Microfluidics, Particle separation

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2140 Computational Modelling of pH-Responsive Nanovalves in Controlled-Release System

Authors: Tomilola J. Ajayi

Abstract:

A category of nanovalves system containing the α-cyclodextrin (α-CD) ring on a stalk tethered to the pores of mesoporous silica nanoparticles (MSN) is theoretically and computationally modelled. This functions to control opening and blocking of the MSN pores for efficient targeted drug release system. Modeling of the nanovalves is based on the interaction between α-CD and the stalk (p-anisidine) in relation to pH variation. Conformational analysis was carried out prior to the formation of the inclusion complex, to find the global minimum of both neutral and protonated stalk. B3LYP/6-311G**(d, p) basis set was employed to attain all theoretically possible conformers of the stalk. Six conformers were taken into considerations, and the dihedral angle (θ) around the reference atom (N17) of the p-anisidine stalk was scanned from 0° to 360° at 5° intervals. The most stable conformer was obtained at a dihedral angle of 85.3° and was fully optimized at B3LYP/6-311G**(d, p) level of theory. The most stable conformer obtained from conformational analysis was used as the starting structure to create the inclusion complexes. 9 complexes were formed by moving the neutral guest into the α-CD cavity along the Z-axis in 1 Å stepwise while keeping the distance between dummy atom and OMe oxygen atom on the stalk restricted. The dummy atom and the carbon atoms on α-CD structure were equally restricted for orientation A (see Scheme 1). The generated structures at each step were optimized with B3LYP/6-311G**(d, p) methods to determine their energy minima. Protonation of the nitrogen atom on the stalk occurs at acidic pH, leading to unsatisfactory host-guest interaction in the nanogate; hence there is dethreading. High required interaction energy and conformational change are theoretically established to drive the release of α-CD at a certain pH. The release was found to occur between pH 5-7 which agreed with reported experimental results. In this study, we applied the theoretical model for the prediction of the experimentally observed pH-responsive nanovalves which enables blocking, and opening of mesoporous silica nanoparticles pores for targeted drug release system. Our results show that two major factors are responsible for the cargo release at acidic pH. The higher interaction energy needed for the complex/nanovalve formation to exist after protonation as well as conformational change upon protonation are driving the release due to slight pH change from 5 to 7.

Keywords: nanovalves, nanogate, mesoporous silica nanoparticles, cargo

Procedia PDF Downloads 115
2139 Effect of Oxidation on Wetting Behavior between Silicon and Silicon Carbide

Authors: Zineb Benouahmane, Zhang Lifeng

Abstract:

Experimental oxidation tests at high temperature (1300°C-1500°C) on α-SiC samples have been performed with different holding times and atmosphere (air, argon). Oxidized samples were then analyzed using X-ray photoelectron spectroscopy coupled to SEM and DAKTEK surface profiler verification. The oxidation rate and the mas gain were found to increase with temperature and holding times, corresponding to a passive oxidation regime which lead to the formation of SiO2 layer. The sessile drop method is employed in order to measure the wetting angles between Si/SiC system at high temperature (1430°C-1550°C). Contact angle can be varied between 44 °C to 85°C, by controlling the oxygen content in α-SiC. Increasing the temperature occurred the infiltration of liquid silicon and deoxidation of the coating.

Keywords: oxidation, wettability, silicon, SiC

Procedia PDF Downloads 451
2138 A Simulation-Based Investigation of the Smooth-Wall, Radial Gravity Problem of Granular Flow through a Wedge-Shaped Hopper

Authors: A. F. Momin, D. V. Khakhar

Abstract:

Granular materials consist of particulate particles found in nature and various industries that, due to gravity flow, behave macroscopically like liquids. A fundamental industrial unit operation is a hopper with inclined walls or a converging channel in which material flows downward under gravity and exits the storage bin through the bottom outlet. The simplest form of the flow corresponds to a wedge-shaped, quasi-two-dimensional geometry with smooth walls and radially directed gravitational force toward the apex of the wedge. These flows were examined using the Mohr-Coulomb criterion in the classic work of Savage (1965), while Ravi Prakash and Rao used the critical state theory (1988). The smooth-wall radial gravity (SWRG) wedge-shaped hopper is simulated using the discrete element method (DEM) to test existing theories. DEM simulations involve the solution of Newton's equations, taking particle-particle interactions into account to compute stress and velocity fields for the flow in the SWRG system. Our computational results are consistent with the predictions of Savage (1965) and Ravi Prakash and Rao (1988), except for the region near the exit, where both viscous and frictional effects are present. To further comprehend this behaviour, a parametric analysis is carried out to analyze the rheology of wedge-shaped hoppers by varying the orifice diameter, wedge angle, friction coefficient, and stiffness. The conclusion is that velocity increases as the flow rate increases but decreases as the wedge angle and friction coefficient increase. We observed no substantial changes in velocity due to varying stiffness. It is anticipated that stresses at the exit result from the transfer of momentum during particle collisions; for this reason, relationships between viscosity and shear rate are shown, and all data are collapsed into a single curve. In addition, it is demonstrated that viscosity and volume fraction exhibit power law correlations with the inertial number and that all the data collapse into a single curve. A continuum model for determining granular flows is presented using empirical correlations.

Keywords: discrete element method, gravity flow, smooth-wall, wedge-shaped hoppers

Procedia PDF Downloads 76
2137 Robust Stabilization against Unknown Consensus Network

Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

Abstract:

This paper considers a robust stabilization problem of a single agent in a multi-agent consensus system composed of identical agents, when the network topology of the system is completely unknown. It is shown that the transfer function of an agent in a consensus system can be described as a multiplicative perturbation of the isolated agent transfer function in frequency domain. Applying known robust stabilization results, we present sufficient conditions for a robust stabilization of an agent against unknown network topology.

Keywords: single agent control, multi-agent system, transfer function, graph angle

Procedia PDF Downloads 444
2136 Flexible, Hydrophobic and Mechanical Strong Poly(Vinylidene Fluoride): Carbon Nanotube Composite Films for Strain-Sensing Applications

Authors: Sudheer Kumar Gundati, Umasankar Patro

Abstract:

Carbon nanotube (CNT) – polymer composites have been extensively studied due to their exceptional electrical and mechanical properties. In the present study, poly(vinylidene fluoride) (PVDF) – multi-walled CNT composites were prepared by melt-blending technique using pristine (ufCNT) and a modified dilute nitric acid-treated CNTs (fCNT). Due to this dilute acid-treatment, the fCNTs were found to show significantly improved dispersion and retained their electrical property. The fCNT showed an electrical percolation threshold (PT) of 0.15 wt% in the PVDF matrix as against 0.35 wt% for ufCNT. The composites were made into films of thickness ~0.3 mm by compression-molding and the resulting composite films were subjected to various property evaluations. It was found that the water contact angle (WCA) of the films increased with CNT weight content in composites and the composite film surface became hydrophobic (e.g., WCA ~104° for 4 wt% ufCNT and 111.5° for 0.5 wt% fCNT composites) in nature; while the neat PVDF film showed hydrophilic behavior (WCA ~68°). Significant enhancements in the mechanical properties were observed upon CNT incorporation and there is a progressive increase in the tensile strength and modulus with increase in CNT weight fraction in composites. The composite films were tested for strain-sensing applications. For this, a simple and non-destructive method was developed to demonstrate the strain-sensing properties of the composites films. In this method, the change in electrical resistance was measured using a digital multimeter by applying bending strain by oscillation. It was found that by applying dynamic bending strain, there is a systematic change in resistance and the films showed piezo-resistive behavior. Due to the high flexibility of these composite films, the change in resistance was reversible and found to be marginally affected, when large number of tests were performed using a single specimen. It is interesting to note that the composites with CNT content notwithstanding their type near the percolation threshold (PT) showed better strain-sensing properties as compared to the composites with CNT contents well-above the PT. On account of the excellent combination of the various properties, the composite films offer a great promise as strain-sensors for structural health-monitoring.

Keywords: carbon nanotubes, electrical percolation threshold, mechanical properties, poly(vinylidene fluoride), strain-sensor, water contact angle

Procedia PDF Downloads 234
2135 Classification of ECG Signal Based on Mixture of Linear and Non-Linear Features

Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

Abstract:

In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

Procedia PDF Downloads 253
2134 Residual Compressive Strength of Drilled Glass Fiber Reinforced Composites

Authors: Navid Zarif Karimi, Giangiacomo Minak, Parnian Kianfar

Abstract:

Drilling is one of the most frequently used machining process for glass fiber reinforced polymer composites due to the need for structural joining. In drilling of composite laminates, interlaminar cracking, or delamination, has a detrimental effect on the compressive strength of these materials. The delamination can be controlled by adopting proper drilling condition. In this paper, the effect of feed rate, cutting speed and drill point angle on delamination and residual compressive strength of drilled GFRPs is studied. The objective is to find optimal conditions for maximum residual compressive strength.

Keywords: composite material, delamination, drilling, residual compressive strength

Procedia PDF Downloads 450
2133 A Survey of Baseband Architecture for Software Defined Radio

Authors: M. A. Fodha, H. Benfradj, A. Ghazel

Abstract:

This paper is a survey of recent works that proposes a baseband processor architecture for software defined radio. A classification of different approaches is proposed. The performance of each architecture is also discussed in order to clarify the suitable approaches that meet software-defined radio constraints.

Keywords: multi-core architectures, reconfigurable architectures, software defined radio, baseband processor

Procedia PDF Downloads 468