Search results for: Images in Performances
2093 Quantitative Risk Analysis for Major Subsystems and Project Success of a Highthrouput Satellite
Authors: Ibrahim Isa Ali (Pantami), Abdu Jaafaru Bambale, Abimbola Alale, Danjuma Ibrahim Ndihgihdah, Muhammad Alkali, Adamu Idris Umar, Babadoko Dantala Mohammed, Moshood Kareem Olawole
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This paper dwells on the risk management required for High throughput Satellite (HTS) project, and major subsystems that pertains to the improved performance and reliability of the spacecraft. The paper gives a clear picture of high‐throughput satellites (HTS) and the associated technologies with performances as they align and differ with the traditional geostationary orbit or Geosynchronous Equatorial Orbit (GEO) Communication Satellites. The paper also highlights critical subsystems and processes in project conceptualization and execution. The paper discusses the configuration of the payload. The need for optimization of resources for the HTS project and successful integration of critical subsystems for spacecraft requires implementation of risk analysis and mitigation from the preliminary design stage; Assembly, Integration and Test (AIT); Launch and in-orbit- Management stage.Keywords: AIT, HTS, in-orbit management, optimization
Procedia PDF Downloads 1032092 Content-Aware Image Augmentation for Medical Imaging Applications
Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang
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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving
Procedia PDF Downloads 2222091 Diesel Engine Performance Optimization to Reduce Fuel Consumption and Emissions Issues
Authors: hadi kargar, bahador shabani
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In this article, 16 cylinder motor combustion CFD modeling with a diameter of 165 mm and 195 mm along the way to help the FIRE software to optimize its function to work. A three-dimensional model of the processes that formed inside the cylinder made that involves mixing the fuel and air, ignition and spraying. In this three-dimensional model, all chemical species, density of air fuel spraying and spray with full profile intended to detailed results from mixing the fuel and air, igniting the ignition advance, spray, and mixed media in different times and get fit by moving the piston. Optimal selection of the model for the shape of the piston and spraying fuel specifications (including the management of spraying, the number of azhneh hole, start time of spraying and spraying angle) to achieve the best fuel consumption and minimal pollution. The spray hole 6 and 7 in three different configurations with five spraying and gives the best geometry and various performances in the simulation. 6 hole spray angle, finally spraying 72.5 degrees and two forms of spraying a better performance in comparison with other items of their own.Keywords: spray, FIRE, CFD, optimize, diesel engine
Procedia PDF Downloads 4192090 Integration of Fuzzy Logic in the Representation of Knowledge: Application in the Building Domain
Authors: Hafida Bouarfa, Mohamed Abed
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The main object of our work is the development and the validation of a system indicated Fuzzy Vulnerability. Fuzzy Vulnerability uses a fuzzy representation in order to tolerate the imprecision during the description of construction. At the the second phase, we evaluated the similarity between the vulnerability of a new construction and those of the whole of the historical cases. This similarity is evaluated on two levels: 1) individual similarity: bases on the fuzzy techniques of aggregation; 2) Global similarity: uses the increasing monotonous linguistic quantifiers (RIM) to combine the various individual similarities between two constructions. The third phase of the process of Fuzzy Vulnerability consists in using vulnerabilities of historical constructions narrowly similar to current construction to deduce its estimate vulnerability. We validated our system by using 50 cases. We evaluated the performances of Fuzzy Vulnerability on the basis of two basic criteria, the precision of the estimates and the tolerance of the imprecision along the process of estimation. The comparison was done with estimates made by tiresome and long models. The results are satisfactory.Keywords: case based reasoning, fuzzy logic, fuzzy case based reasoning, seismic vulnerability
Procedia PDF Downloads 2922089 Automatic Censoring in K-Distribution for Multiple Targets Situations
Authors: Naime Boudemagh, Zoheir Hammoudi
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The parameters estimation of the K-distribution is an essential part in radar detection. In fact, presence of interfering targets in reference cells causes a decrease in detection performances. In such situation, the estimate of the shape and the scale parameters are far from the actual values. In the order to avoid interfering targets, we propose an Automatic Censoring (AC) algorithm of radar interfering targets in K-distribution. The censoring technique used in this work offers a good discrimination between homogeneous and non-homogeneous environments. The homogeneous population is then used to estimate the unknown parameters by the classical Method of Moment (MOM). The AC algorithm does not need any prior information about the clutter parameters nor does it require both the number and the position of interfering targets. The accuracy of the estimation parameters obtained by this algorithm are validated and compared to various actual values of the shape parameter, using Monte Carlo simulations, this latter show that the probability of censing in multiple target situations are in good agreement.Keywords: parameters estimation, method of moments, automatic censoring, K distribution
Procedia PDF Downloads 3732088 Using the Timepix Detector at CERN Accelerator Facilities
Authors: Andrii Natochii
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The UA9 collaboration in the last two years has installed two different types of detectors to investigate the channeling effect in the bent silicon crystals with high-energy particles beam on the CERN accelerator facilities: Cherenkov detector CpFM and silicon pixel detector Timepix. In the current work, we describe the main performances of the Timepix detector operation at the SPS and H8 extracted beamline at CERN. We are presenting some detector calibration results and tuning. Our research topics also cover a cluster analysis algorithm for the particle hits reconstruction. We describe the optimal acquisition setup for the Timepix device and the edges of its functionality for the high energy and flux beam monitoring. The measurements of the crystal parameters are very important for the future bent crystal applications and needs a track reconstruction apparatus. Thus, it was decided to construct a short range (1.2 m long) particle telescope based on the Timepix sensors and test it at H8 SPS extraction beamline. The obtained results will be shown as well.Keywords: beam monitoring, channeling, particle tracking, Timepix detector
Procedia PDF Downloads 1802087 Design of Compact Dual-Band Planar Antenna for WLAN Systems
Authors: Anil Kumar Pandey
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A compact planar monopole antenna with dual-band operation suitable for wireless local area network (WLAN) application is presented in this paper. The antenna occupies an overall area of 18 ×12 mm2. The antenna is fed by a coplanar waveguide (CPW) transmission line and it combines two folded strips, which radiates at 2.4 and 5.2 GHz. In the proposed antenna, by optimally selecting the antenna dimensions, dual-band resonant modes with a much wider impedance matching at the higher band can be produced. Prototypes of the obtained optimized design have been simulated using EM solver. The simulated results explore good dual-band operation with -10 dB impedance bandwidths of 50 MHz and 2400 MHz at bands of 2.4 and 5.2 GHz, respectively, which cover the 2.4/5.2/5.8 GHz WLAN operating bands. Good antenna performances such as radiation patterns and antenna gains over the operating bands have also been observed. The antenna with a compact size of 18×12×1.6 mm3 is designed on an FR4 substrate with a dielectric constant of 4.4.Keywords: CPW antenna, dual-band, electromagnetic simulation, wireless local area network (WLAN)
Procedia PDF Downloads 2092086 Short-Term and Working Memory Differences Across Age and Gender in Children
Authors: Farzaneh Badinloo, Niloufar Jalali-Moghadam, Reza Kormi-Nouri
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The aim of this study was to explore the short-term and working memory performances across age and gender in school aged children. Most of the studies have been interested in looking into memory changes in adult subjects. This study was instead focused on exploring both short-term and working memories of children over time. Totally 410 school child participants belonging to four age groups (approximately 8, 10, 12 and 14 years old) among which were 201 girls and 208 boys were employed in the study. digits forward and backward tests of the Wechsler children intelligence scale-revised were conducted respectively as short-term and working memory measures. According to results, there was found a general increment in both short-term and working memory scores across age (p ˂ .05) by which whereas short-term memory performance was shown to increase up to 12 years old, working memory scores showed no significant increase after 10 years old of age. No difference was observed in terms of gender (p ˃ .05). In conclusion, this study suggested that both short-term and working memories improve across age in children where 12 and 10 years of old are likely the crucial age periods in terms of short-term and working memories development.Keywords: age, gender, short-term memory, working memory
Procedia PDF Downloads 4782085 Application of Biomass Ashes as Supplementary Cementitious Materials in the Cement Mortar Production
Authors: S. Šupić, M. Malešev, V. Radonjanin, M. Radeka, M. Laban
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The production of low cost and environmentally friendly products represents an important step for developing countries. Biomass is one of the largest renewable energy sources, and Serbia is among the top European countries in terms of the amount of available and unused biomass. Substituting cement with the ashes obtained by the combustion of biomass would reduce the negative impact of concrete industry on the environment and would provide a waste valorization by the reuse of this type of by-product in mortars and concretes manufacture. The study contains data on physical properties, chemical characteristics and pozzolanic properties of obtained biomass ashes: wheat straw ash and mixture of wheat and soya straw ash in Serbia, which were, later, used as supplementary cementitious materials in preparation of mortars. Experimental research of influence of biomass ashes on physical and mechanical properties of cement mortars was conducted. The results indicate that the biomass ashes can be successfully used in mortars as substitutes of cement without compromising their physical and mechanical performances.Keywords: biomass, ash, cementitious material, mortar
Procedia PDF Downloads 1842084 Normalized Compression Distance Based Scene Alteration Analysis of a Video
Authors: Lakshay Kharbanda, Aabhas Chauhan
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In this paper, an application of Normalized Compression Distance (NCD) to detect notable scene alterations occurring in videos is presented. Several research groups have been developing methods to perform image classification using NCD, a computable approximation to Normalized Information Distance (NID) by studying the degree of similarity in images. The timeframes where significant aberrations between the frames of a video have occurred have been identified by obtaining a threshold NCD value, using two compressors: LZMA and BZIP2 and defining scene alterations using Pixel Difference Percentage metrics.Keywords: image compression, Kolmogorov complexity, normalized compression distance, root mean square error
Procedia PDF Downloads 3402083 A Study on Performance Prediction in Early Design Stage of Apartment Housing Using Machine Learning
Authors: Seongjun Kim, Sanghoon Shim, Jinwooung Kim, Jaehwan Jung, Sung-Ah Kim
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As the development of information and communication technology, the convergence of machine learning of the ICT area and design is attempted. In this way, it is possible to grasp the correlation between various design elements, which was difficult to grasp, and to reflect this in the design result. In architecture, there is an attempt to predict the performance, which is difficult to grasp in the past, by finding the correlation among multiple factors mainly through machine learning. In architectural design area, some attempts to predict the performance affected by various factors have been tried. With machine learning, it is possible to quickly predict performance. The aim of this study is to propose a model that predicts performance according to the block arrangement of apartment housing through machine learning and the design alternative which satisfies the performance such as the daylight hours in the most similar form to the alternative proposed by the designer. Through this study, a designer can proceed with the design considering various design alternatives and accurate performances quickly from the early design stage.Keywords: apartment housing, machine learning, multi-objective optimization, performance prediction
Procedia PDF Downloads 4812082 Comparison of Solar Radiation Models
Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci
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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)
Procedia PDF Downloads 3512081 Distributed Framework for Pothole Detection and Monitoring Using Federated Learning
Authors: Ezil Sam Leni, Shalen S.
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Transport service monitoring and upkeep are essential components of smart city initiatives. The main risks to the relevant departments and authorities are the ever-increasing vehicular traffic and the conditions of the roads. In India, the economy is greatly impacted by the road transport sector. In 2021, the Ministry of Road Transport and Highways Transport, Government of India, produced a report with statistical data on traffic accidents. The data included the number of fatalities, injuries, and other pertinent criteria. This study proposes a distributed infrastructure for the monitoring, detection, and reporting of potholes to the appropriate authorities. In a distributed environment, the nodes are the edge devices, and local edge servers, and global servers. The edge devices receive the initial model to be employed from the global server. The YOLOv8 model for pothole detection is used in the edge devices. The edge devices run the pothole detection model, gather the pothole images on their path, and send the updates to the nearby edge server. The local edge server selects the clients for its aggregation process, aggregates the model updates and sends the updates to the global server. The global server collects the updates from the local edge servers, performs aggregation and derives the updated model. The updated model has the information about the potholes received from the local edge servers and notifies the updates to the local edge servers and concerned authorities for monitoring and maintenance of road conditions. The entire process is implemented in FedCV distributed environment with the implementation using the client-server model and aggregation entities. After choosing the clients for its aggregation process, the local edge server gathers the model updates and transmits them to the global server. After gathering the updates from the regional edge servers, the global server aggregates them and creates the updated model. Performance indicators and the experimentation environment are assessed, discussed, and presented. Accelerometer data may be taken into consideration for improved performance in the future development of this study, in addition to the images captured from the transportation routes.Keywords: federated Learning, pothole detection, distributed framework, federated averaging
Procedia PDF Downloads 1032080 Development of the Logistic Service Providers under the Pandemic Affects during COVID-19 in Turkey
Authors: Süleyman Günes
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The crucial effects of the COVID-19 pandemic have on social and economic systems in Turkey as well as all over the world. It has impacted logistic providers and worldwide supply chains. Unexpected risks played a central role in creating vulnerabilities for logistics service operations during the pandemic terms. This study aims to research and design qualitative and quantitive contributions to logistic services. The COVID-19 pandemic brought unavoidable risks to the logistics industry in Turkey. The Logistic Service Providers (LSPs) have learned how to ensure uncertainties and risks triggered by main and adverse effects. The risks that LSPs encounter during the COVID-19 pandemic have been investigated and unveiled, and identified uncertainties and risks. The cause-effect structures were displayed by the qualitative and quantitive studies. The results suggest that supply chains and demand changes triggered by the COVID-19 pandemic while it influenced financial failure and forecast horizon with operational performances.Keywords: logistic service providers, COVID-19, development, financial failure
Procedia PDF Downloads 732079 The Meaning in Life and the Content of Mental Images of Temporal Mental Simulations in Poles and Americans
Authors: Katarzyna Pasternak
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Experiencing the meaning of life is widely recognised as a vital element of well-being and central human motivation. Studies have shown that a higher meaning of life is associated, among other things, with a higher quality of life, higher levels of happiness and better declared health. The subject of the study is the meaning in life measured with The Meaning in Life Questionnaire and the presence of such emotions as nostalgia, awe and hope, and the content of imaginations measured after temporal mental simulations in Americans and Poles. The respondents had to imagine themselves in future, in 40 years and describe two events that would take place at that time. Next, participants assessed the importance of the events described by them, recognised whether during their journey through time they felt awe, hope and nostalgia, and answered the questionnaire examining the meaning in life. 204 (102 from Poland 102 from the USA ) people aged 21 to 60 participated in the study. The study checked whether there were differences in the content of the imaginations of the respondents from Poland and USA, and whether there were statistically significant difference between the declared sense of meaning in life among participants from both countries. The result of the study hane shown that there were no differences in the overall result obtained by the participants in The Meaning in Life Questionnaire , while there were statistically significant differences among the subscales of the questionnaire. It turned out that Americans have a higher presence of meaning in life than Poles, but they obtained lower results in searching of meaning in life. Studies have also shown that there was a statistically significant difference between Poles and Americans in feeling awe after a mental simulation. Poles felt higher level of awe. Images about the future differed between Poles and Americans. Poles judged that the events they described were very important to them. Interestingly, the content of American participants’ imaginations was dominated by topics related to the future of the world, ecology and world peace. There were also ideas about nice moments spent with friends and family. Among Poles, ideas related to professional career and development as well as family events dominated. Research shows that despite the lack of differences in the general meaning in life, Poles are more focused on searching for meaning in life than Americans. The study shows interesting differences between the two cultures.Keywords: meaning in life, mental simulations, imaginations, temporal mental simulations, future, cultural differences
Procedia PDF Downloads 1052078 Automatic Classification Using Dynamic Fuzzy C Means Algorithm and Mathematical Morphology: Application in 3D MRI Image
Authors: Abdelkhalek Bakkari
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Image segmentation is a critical step in image processing and pattern recognition. In this paper, we proposed a new robust automatic image classification based on a dynamic fuzzy c-means algorithm and mathematical morphology. The proposed segmentation algorithm (DFCM_MM) has been applied to MR perfusion images. The obtained results show the validity and robustness of the proposed approach.Keywords: segmentation, classification, dynamic, fuzzy c-means, MR image
Procedia PDF Downloads 4792077 A Survey on Types of Noises and De-Noising Techniques
Authors: Amandeep Kaur
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Digital Image processing is a fundamental tool to perform various operations on the digital images for pattern recognition, noise removal and feature extraction. In this paper noise removal technique has been described for various types of noises. This paper comprises discussion about various noises available in the image due to different environmental, accidental factors. In this paper, various de-noising approaches have been discussed that utilize different wavelets and filters for de-noising. By analyzing various papers on image de-noising we extract that wavelet based de-noise approaches are much effective as compared to others.Keywords: de-noising techniques, edges, image, image processing
Procedia PDF Downloads 3362076 Hardware-in-the-Loop Test for Automatic Voltage Regulator of Synchronous Condenser
Authors: Ha Thi Nguyen, Guangya Yang, Arne Hejde Nielsen, Peter Højgaard Jensen
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Automatic voltage regulator (AVR) plays an important role in volt/var control of synchronous condenser (SC) in power systems. Test AVR performance in steady-state and dynamic conditions in real grid is expensive, low efficiency, and hard to achieve. To address this issue, we implement hardware-in-the-loop (HiL) test for the AVR of SC to test the steady-state and dynamic performances of AVR in different operating conditions. Startup procedure of the system and voltage set point changes are studied to evaluate the AVR hardware response. Overexcitation, underexcitation, and AVR set point loss are tested to compare the performance of SC with the AVR hardware and that of simulation. The comparative results demonstrate how AVR will work in a real system. The results show HiL test is an effective approach for testing devices before deployment and is able to parameterize the controller with lower cost, higher efficiency, and more flexibility.Keywords: automatic voltage regulator, hardware-in-the-loop, synchronous condenser, real time digital simulator
Procedia PDF Downloads 2512075 Comparison of Various Control Methods for an Industrial Multiproduct Fractionator
Authors: Merve Aygün Esastürk, Deren Ataç Yılmaz, Görkem Oğur, Emre Özgen Kuzu, Sadık Ödemiş
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Hydrocracker plants are one of the most complicated and most profitable units in the refinery process. It takes long chain paraffinic hydrocarbons as feed and turns them into smaller and more valuable products, mainly kerosene and diesel under high pressure with the excess amount of hydrogen. Controlling the product qualities well directly contributes to the unit profit. Control of a plant is mainly based on PID and MPC controllers. Controlling the reaction section is important in terms of reaction severity. However, controlling the fractionation section is more crucial since the end products are separated in fractionation section. In this paper, the importance of well-configured base layer control mechanism, composed of PID controllers, is highlighted. For this purpose, two different base layer control scheme is applied in a hydrocracker fractionator column performances of schemes, which is a direct contribution to better product quality, are compared.Keywords: controller, distillation, configuration selection, hydrocracker, model predictive controller, proportional-integral-derivative controller
Procedia PDF Downloads 4392074 Selection of Intensity Measure in Probabilistic Seismic Risk Assessment of a Turkish Railway Bridge
Authors: M. F. Yilmaz, B. Ö. Çağlayan
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Fragility curve is an effective common used tool to determine the earthquake performance of structural and nonstructural components. Also, it is used to determine the nonlinear behavior of bridges. There are many historical bridges in the Turkish railway network; the earthquake performances of these bridges are needed to be investigated. To derive fragility curve Intensity measures (IMs) and Engineering demand parameters (EDP) are needed to be determined. And the relation between IMs and EDP are needed to be derived. In this study, a typical simply supported steel girder riveted railway bridge is studied. Fragility curves of this bridge are derived by two parameters lognormal distribution. Time history analyses are done for selected 60 real earthquake data to determine the relation between IMs and EDP. Moreover, efficiency, practicality, and sufficiency of three different IMs are discussed. PGA, Sa(0.2s) and Sa(1s), the most common used IMs parameters for fragility curve in the literature, are taken into consideration in terms of efficiency, practicality and sufficiency.Keywords: railway bridges, earthquake performance, fragility analyses, selection of intensity measures
Procedia PDF Downloads 3572073 Electrodeposition of NiO Films from Organic Solvent-Based Electrolytic Solutions for Solar Cell Application
Authors: Thierry Pauporté, Sana Koussi, Fabrice Odobel
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The preparation of semiconductor oxide layers and structures by soft techniques is an important field of research. Higher performances are expected from the optimizing of the oxide films and then use of new methods of preparation for a better control of their chemical, morphological, electrical and optical properties. We present the preparation of NiO by electrodeposition from pure polar aprotic medium and mixtures with water. The effect of the solvent, of the electrochemical deposition parameters and post-deposition annealing treatment on the structural, morphological and optical properties of the films is investigated. We remarkably show that the solvent is inserted in the deposited layer and act as a blowing agent, giving rise to mesoporous films after elimination by thermal annealing. These layers of p-type oxide have been successfully used, after sensitization by a dye, in p-type dye-sensitized solar cells. The effects of the solvent on the layer properties and the application of these layers in p-type dye-sensitized solar cells are described.Keywords: NiO, layer, p-type sensitized solar cells, electrodeposition
Procedia PDF Downloads 2972072 Combining an Optimized Closed Principal Curve-Based Method and Evolutionary Neural Network for Ultrasound Prostate Segmentation
Authors: Tao Peng, Jing Zhao, Yanqing Xu, Jing Cai
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Due to missing/ambiguous boundaries between the prostate and neighboring structures, the presence of shadow artifacts, as well as the large variability in prostate shapes, ultrasound prostate segmentation is challenging. To handle these issues, this paper develops a hybrid method for ultrasound prostate segmentation by combining an optimized closed principal curve-based method and the evolutionary neural network; the former can fit curves with great curvature and generate a contour composed of line segments connected by sorted vertices, and the latter is used to express an appropriate map function (represented by parameters of evolutionary neural network) for generating the smooth prostate contour to match the ground truth contour. Both qualitative and quantitative experimental results showed that our proposed method obtains accurate and robust performances.Keywords: ultrasound prostate segmentation, optimized closed polygonal segment method, evolutionary neural network, smooth mathematical model, principal curve
Procedia PDF Downloads 2022071 Estimation of Fouling in a Cross-Flow Heat Exchanger Using Artificial Neural Network Approach
Authors: Rania Jradi, Christophe Marvillet, Mohamed Razak Jeday
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One of the most frequently encountered problems in industrial heat exchangers is fouling, which degrades the thermal and hydraulic performances of these types of equipment, leading thus to failure if undetected. And it occurs due to the accumulation of undesired material on the heat transfer surface. So, it is necessary to know about the heat exchanger fouling dynamics to plan mitigation strategies, ensuring a sustainable and safe operation. This paper proposes an Artificial Neural Network (ANN) approach to estimate the fouling resistance in a cross-flow heat exchanger by the collection of the operating data of the phosphoric acid concentration loop. The operating data of 361 was used to validate the proposed model. The ANN attains AARD= 0.048%, MSE= 1.811x10⁻¹¹, RMSE= 4.256x 10⁻⁶ and r²=99.5 % of accuracy which confirms that it is a credible and valuable approach for industrialists and technologists who are faced with the drawbacks of fouling in heat exchangers.Keywords: cross-flow heat exchanger, fouling, estimation, phosphoric acid concentration loop, artificial neural network approach
Procedia PDF Downloads 1982070 Investigation of Solar Concentrator Prototypes under Tunisian Conditions
Authors: Moncef Balghouthi, Mahmoud Ben Amara, Abdessalem Ben Hadj Ali, Amenallah Guizani
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Concentrated solar power technology constitutes an interesting option to meet a part of future energy demand, especially when considering the high levels of solar radiation and clearness index that are available particularly in Tunisia. In this work, we present three experimental prototypes of solar concentrators installed in the research center of energy CRTEn in Tunisia. Two are medium temperature parabolic trough solar collector used to drive a cooling installation and for steam generation. The third is a parabolic dish concentrator used for hybrid generation of thermal and electric power. Optical and thermal evaluations were presented. Solutions and possibilities to construct locally the mirrors of the concentrator were discussed. In addition, the enhancement of the performances of the receivers by nano selective absorption coatings was studied. The improvement of heat transfer between the receiver and the heat transfer fluid was discussed for each application.Keywords: solar concentrators, optical and thermal evaluations, cooling and process heat, hybrid thermal and electric generation
Procedia PDF Downloads 2552069 ANAC-id - Facial Recognition to Detect Fraud
Authors: Giovanna Borges Bottino, Luis Felipe Freitas do Nascimento Alves Teixeira
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This article aims to present a case study of the National Civil Aviation Agency (ANAC) in Brazil, ANAC-id. ANAC-id is the artificial intelligence algorithm developed for image analysis that recognizes standard images of unobstructed and uprighted face without sunglasses, allowing to identify potential inconsistencies. It combines YOLO architecture and 3 libraries in python - face recognition, face comparison, and deep face, providing robust analysis with high level of accuracy.Keywords: artificial intelligence, deepface, face compare, face recognition, YOLO, computer vision
Procedia PDF Downloads 1562068 Performing Fat Activism in Australia: An Autoethnographic Exploration
Authors: Jenny Lee
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Fat Studies is emerging as an interdisciplinary area of study, intersecting with Gender Studies, Sociology, Human Development and the Creative Arts. A focus on weight loss, and, therefore, fat hatred, has resulted in a form of discriminatory institutional practice that impacts women in the Western world. This focus is sanctioned by a large dieting industry, medical associations, the media, and at times, government initiatives. This paper will discuss the emergence of the so-called ‘Obesity Epidemic’ in Australia and the Western world and the stereotypes that thin equals healthy and fat equals unhealthy. This paper will argue that, for those with a health focus, ‘Health at every size’ is a more effective principle, which involves striving for healthy living, without a focus on weight loss. This discussion will contextualise an autoethnographic exploration of how fat acceptance and Health at Every Size can be encouraged through fat activism and fat political art. As part of this paper, a selection of the recent performance, writing and art in Australia will be presented, including Aquaporko, the fat femme synchronised swim team and VaVaBoomBah, the Melbourne fat burlesque performances.Keywords: activism, fat, health, obesity, performance
Procedia PDF Downloads 1822067 Brainwave Classification for Brain Balancing Index (BBI) via 3D EEG Model Using k-NN Technique
Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan
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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.Keywords: power spectral density, 3D EEG model, brain balancing, kNN
Procedia PDF Downloads 4872066 Map Matching Performance under Various Similarity Metrics for Heterogeneous Robot Teams
Authors: M. C. Akay, A. Aybakan, H. Temeltas
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Aerial and ground robots have various advantages of usage in different missions. Aerial robots can move quickly and get a different sight of view of the area, but those vehicles cannot carry heavy payloads. On the other hand, unmanned ground vehicles (UGVs) are slow moving vehicles, since those can carry heavier payloads than unmanned aerial vehicles (UAVs). In this context, we investigate the performances of various Similarity Metrics to provide a common map for Heterogeneous Robot Team (HRT) in complex environments. Within the usage of Lidar Odometry and Octree Mapping technique, the local 3D maps of the environment are gathered. In order to obtain a common map for HRT, informative theoretic similarity metrics are exploited. All types of these similarity metrics gave adequate as allowable simulation time and accurate results that can be used in different types of applications. For the heterogeneous multi robot team, those methods can be used to match different types of maps.Keywords: common maps, heterogeneous robot team, map matching, informative theoretic similarity metrics
Procedia PDF Downloads 1682065 Characterization of Poly(Hydroxyethyl Methacrylate-Glycidyl Methacrylate)-Imino Diacetic Acid Membrane to Adsorbing Leather Dye
Authors: Ahmet Aslan, Safiye Meric Acikel, Raziye Hilal Senay, Sinan Akgol
Abstract:
Different chemical substances and too much water are used during leather production. Therefore, the waste water load of the leather industry is harmful to the environment. One of the pollution sources is the production of leather coloring process is a further need to focus on the removal of dye waste waters subject. These water-soluble dyes have a small organic molecular size. Besides the environmental hazards, these dyes cannot be underestimated, they also have harmful effects on human health. In this study, poly(hydroxyethyl methacrylate-glycidyl methacrylate) p(HEMA-GMA) hydrogel membranes were synthesized by UV polymerization method. The hydrogel synthesized is modified with imino diacetic acid (IDA) and then chelated with Cr (III) ions. The chelating capacity of the membranes was determined according to the time, pH and concentration parameters. Dynamic swelling test, elemental analysis, ninhydrin analysis and adsorption, desorption and reusability performances of membranes were also determined.Keywords: adsorption, dye, leather, p(HEMA-GMA)-IDA
Procedia PDF Downloads 1812064 Study and Design of Novel Structure of Circularly Polarized Dual Band Microstrip Antenna Fed by Hybrid Coupler for RFID Applications
Authors: M. Taouzari, A. Sardi, J. El Aoufi, Ahmed Mouhsen
Abstract:
The purpose of this work is to design a reader antenna fed by 90° hybrid coupler that would ensure a tag which is detected regardless of its orientation for the radio frequency identification system covering the UHF and ISM bands frequencies. Based on this idea, the proposed work is dividing in two parts, first part is about study and design hybrid coupler using the resonators planar called T-and Pi networks operating in commercial bands. In the second part, the proposed antenna fed by the hybrid coupler is designed on FR4 substrate with dielectric permittivity 4.4, thickness dielectric 1.6mm and loss tangent 0.025. The T-slot is inserted in patch of the proposed antenna fed by the hybrid coupler is first designed, optimized and simulated using electromagnetic simulator ADS and then simulated in a full wave simulation software CST Microwave Studio. The simulated antenna by the both softwares achieves the expected performances in terms of matching, pattern radiation, phase shifting, gain and size.Keywords: dual band antenna, RFID, hybrid coupler, polarization, radiation pattern
Procedia PDF Downloads 131