Search results for: Evaluation Method
7262 The Measurement of Latvian and Russian Ethnic Attitudes, Using Evaluative Priming Task and Self-Report Methods
Authors: Maria Bambulyaka, Irina Plotka, Nina Blumenau, Dmitry Igonin, Elena Ozola, Laura Shimane
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The purposes of researches - to estimate implicit ethnic attitudes by direct and indirect methods, to determine the accordance of two types measuring, to investigate influence of task type used in an experiment, on the results of measuring, as well as to determine a presence or communication between recent episodic events and chronologic correlations of ethnic attitudes. Method of the implicit measuring - an evaluative priming (EPT) carried out with the use of different SOA intervals, explicit methods of research are G.Soldatova-s types of ethnic identity, G.Soldatova-s index of tolerance, E.Bogardus scale of social distance. During five stages of researches received results open some aspects of implicit measuring, its correlation with the results of self-reports on different SOA intervals, connection of implicit measuring with emotional valence of episodic events of participants and other indexes, presenting a contribution to the decision of implicit measuring application problem for study of different social constructs
Keywords: Ethnic attitudes, explicit method, implicit method, priming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15927261 Well-Being and Helping Technology for Retired Population in Finland
Authors: R. Pääkkönen, L. Korpinen
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This study aimed to evaluate parameters influencing well-being and how to maintain well-being as long as possible after retirement. There is contradictory information on the health changes after retirement in Finland. This work is based on interviews, statistics, and literature evaluation of Finland. Most often, balance, multitasking reaction time, and adaptation of vision in dim and darks areas are worsened. Slowing is one characteristic that is difficult to measure properly. The most important is try to determine ways to manage daily activities and symptoms of disease after retirement. Medicine is advancing, problems are often also on the economic side. Information of technical aids is important. It is worth planning a retirement age.
Keywords: Retirement, working, aging, wellness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11367260 VISMA: A Method for System Analysis in Early Lifecycle Phases
Authors: Walter Sebron, Hans Tschürtz, Peter Krebs
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The choice of applicable analysis methods in safety or systems engineering depends on the depth of knowledge about a system, and on the respective lifecycle phase. However, the analysis method chain still shows gaps as it should support system analysis during the lifecycle of a system from a rough concept in pre-project phase until end-of-life. This paper’s goal is to discuss an analysis method, the VISSE Shell Model Analysis (VISMA) method, which aims at closing the gap in the early system lifecycle phases, like the conceptual or pre-project phase, or the project start phase. It was originally developed to aid in the definition of the system boundary of electronic system parts, like e.g. a control unit for a pump motor. Furthermore, it can be also applied to non-electronic system parts. The VISMA method is a graphical sketch-like method that stratifies a system and its parts in inner and outer shells, like the layers of an onion. It analyses a system in a two-step approach, from the innermost to the outermost components followed by the reverse direction. To ensure a complete view of a system and its environment, the VISMA should be performed by (multifunctional) development teams. To introduce the method, a set of rules and guidelines has been defined in order to enable a proper shell build-up. In the first step, the innermost system, named system under consideration (SUC), is selected, which is the focus of the subsequent analysis. Then, its directly adjacent components, responsible for providing input to and receiving output from the SUC, are identified. These components are the content of the first shell around the SUC. Next, the input and output components to the components in the first shell are identified and form the second shell around the first one. Continuing this way, shell by shell is added with its respective parts until the border of the complete system (external border) is reached. Last, two external shells are added to complete the system view, the environment and the use case shell. This system view is also stored for future use. In the second step, the shells are examined in the reverse direction (outside to inside) in order to remove superfluous components or subsystems. Input chains to the SUC, as well as output chains from the SUC are described graphically via arrows, to highlight functional chains through the system. As a result, this method offers a clear and graphical description and overview of a system, its main parts and environment; however, the focus still remains on a specific SUC. It helps to identify the interfaces and interfacing components of the SUC, as well as important external interfaces of the overall system. It supports the identification of the first internal and external hazard causes and causal chains. Additionally, the method promotes a holistic picture and cross-functional understanding of a system, its contributing parts, internal relationships and possible dangers within a multidisciplinary development team.
Keywords: Analysis methods, functional safety, hazard identification, system and safety engineering, system boundary definition, system safety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11357259 Comparison of Power Generation Status of Photovoltaic Systems under Different Weather Conditions
Authors: Zhaojun Wang, Zongdi Sun, Qinqin Cui, Xingwan Ren
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Based on multivariate statistical analysis theory, this paper uses the principal component analysis method, Mahalanobis distance analysis method and fitting method to establish the photovoltaic health model to evaluate the health of photovoltaic panels. First of all, according to weather conditions, the photovoltaic panel variable data are classified into five categories: sunny, cloudy, rainy, foggy, overcast. The health of photovoltaic panels in these five types of weather is studied. Secondly, a scatterplot of the relationship between the amount of electricity produced by each kind of weather and other variables was plotted. It was found that the amount of electricity generated by photovoltaic panels has a significant nonlinear relationship with time. The fitting method was used to fit the relationship between the amount of weather generated and the time, and the nonlinear equation was obtained. Then, using the principal component analysis method to analyze the independent variables under five kinds of weather conditions, according to the Kaiser-Meyer-Olkin test, it was found that three types of weather such as overcast, foggy, and sunny meet the conditions for factor analysis, while cloudy and rainy weather do not satisfy the conditions for factor analysis. Therefore, through the principal component analysis method, the main components of overcast weather are temperature, AQI, and pm2.5. The main component of foggy weather is temperature, and the main components of sunny weather are temperature, AQI, and pm2.5. Cloudy and rainy weather require analysis of all of their variables, namely temperature, AQI, pm2.5, solar radiation intensity and time. Finally, taking the variable values in sunny weather as observed values, taking the main components of cloudy, foggy, overcast and rainy weather as sample data, the Mahalanobis distances between observed value and these sample values are obtained. A comparative analysis was carried out to compare the degree of deviation of the Mahalanobis distance to determine the health of the photovoltaic panels under different weather conditions. It was found that the weather conditions in which the Mahalanobis distance fluctuations ranged from small to large were: foggy, cloudy, overcast and rainy.
Keywords: Fitting, principal component analysis, Mahalanobis distance, SPSS, MATLAB.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6747258 Oil Recovery Study by Low Temperature Carbon Dioxide Injection in High-Pressure High-Temperature Micromodels
Authors: Zakaria Hamdi, Mariyamni Awang
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For the past decades, CO2 flooding has been used as a successful method for enhanced oil recovery (EOR). However, high mobility ratio and fingering effect are considered as important drawbacka of this process. Low temperature injection of CO2 into high temperature reservoirs may improve the oil recovery, but simulating multiphase flow in the non-isothermal medium is difficult, and commercial simulators are very unstable in these conditions. Furthermore, to best of authors’ knowledge, no experimental work was done to verify the results of the simulations and to understand the pore-scale process. In this paper, we present results of investigations on injection of low temperature CO2 into a high-pressure high-temperature micromodel with injection temperature range from 34 to 75 °F. Effect of temperature and saturation changes of different fluids are measured in each case. The results prove the proposed method. The injection of CO2 at low temperatures increased the oil recovery in high temperature reservoirs significantly. Also, CO2 rich phases available in the high temperature system can affect the oil recovery through the better sweep of the oil which is initially caused by penetration of LCO2 inside the system. Furthermore, no unfavorable effect was detected using this method. Low temperature CO2 is proposed to be used as early as secondary recovery.
Keywords: Enhanced oil recovery, CO2 flooding, micromodel studies, miscible flooding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11467257 Positive Solutions for a Class of Semipositone Discrete Boundary Value Problems with Two Parameters
Authors: Benshi Zhu
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In this paper, the existence, multiplicity and noexistence of positive solutions for a class of semipositone discrete boundary value problems with two parameters is studied by applying nonsmooth critical point theory and sub-super solutions method.Keywords: Discrete boundary value problems, nonsmoothcritical point theory, positive solutions, semipositone, sub-super solutions method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13437256 Facile Synthesis of Vertically Aligned ZnO Nanowires on Carbon Layer by Vapour Deposition
Authors: Kh. A. Abdullin, N. B. Bakranov, S. E. Kudaibergenov, S.E. Kumekov, V. N. Ermolaev, L. V. Podrezova
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A facile vapour deposition method of synthesis of vertically aligned ZnO nanowires on carbon seed layer was developed. The received samples were investigated on electronic microscope JSM-6490 LA JEOL and x-ray diffractometer X, pert MPD PRO. The photoluminescence spectra (PL) of obtained ZnO samples at a room temperature were studied using He-Cd laser (325 nm line) as excitation source.
Keywords: ZnO nanowires, vapor-phase deposition, Nicatalytic layer, facile method of synthesis, carbon catalytic layer, thephotoluminescence spectra, X-ray spectrum.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14547255 A new Configurable Decimation Filter using Pascal-s Triangle Theorem
Authors: A. Chahardah Cherik, E. Farshidi
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This paper presents a new configurable decimation filter for sigma-delta modulators. The filter employs the Pascal-s triangle-s theorem for building the coefficients of non-recursive decimation filters. The filter can be connected to the back-end of various modulators with different output accuracy. In this work two methods are shown and then compared from area occupation viewpoint. First method uses the memory and the second one employs Pascal-s triangle-s method, aiming to reduce required gates. XILINX ISE v10 is used for implementation and confirmation the filter.Keywords: Decimation filter, sigma delta, Pascal's triangle'stheorem, memory
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16847254 Nonlinear Dynamic Analysis of Base-Isolated Structures Using a Mixed Integration Method: Stability Aspects and Computational Efficiency
Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino
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In order to reduce numerical computations in the nonlinear dynamic analysis of seismically base-isolated structures, a Mixed Explicit-Implicit time integration Method (MEIM) has been proposed. Adopting the explicit conditionally stable central difference method to compute the nonlinear response of the base isolation system, and the implicit unconditionally stable Newmark’s constant average acceleration method to determine the superstructure linear response, the proposed MEIM, which is conditionally stable due to the use of the central difference method, allows to avoid the iterative procedure generally required by conventional monolithic solution approaches within each time step of the analysis. The main aim of this paper is to investigate the stability and computational efficiency of the MEIM when employed to perform the nonlinear time history analysis of base-isolated structures with sliding bearings. Indeed, in this case, the critical time step could become smaller than the one used to define accurately the earthquake excitation due to the very high initial stiffness values of such devices. The numerical results obtained from nonlinear dynamic analyses of a base-isolated structure with a friction pendulum bearing system, performed by using the proposed MEIM, are compared to those obtained adopting a conventional monolithic solution approach, i.e. the implicit unconditionally stable Newmark’s constant acceleration method employed in conjunction with the iterative pseudo-force procedure. According to the numerical results, in the presented numerical application, the MEIM does not have stability problems being the critical time step larger than the ground acceleration one despite of the high initial stiffness of the friction pendulum bearings. In addition, compared to the conventional monolithic solution approach, the proposed algorithm preserves its computational efficiency even when it is adopted to perform the nonlinear dynamic analysis using a smaller time step.Keywords: Base isolation, computational efficiency, mixed explicit-implicit method, partitioned solution approach, stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10597253 Wasteless Solid-Phase Method for Conversion of Iron Ores Contaminated with Silicon and Phosphorus Compounds
Authors: А. V. Panko, Е. V. Ablets, I. G. Kovzun, М. А. Ilyashov
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Based upon generalized analysis of modern know-how in the sphere of processing, concentration and purification of iron-ore raw materials (IORM), in particular, the most widespread ferrioxide-silicate materials (FOSM), containing impurities of phosphorus and other elements compounds, noted special role of nanotechnological initiatives in improvement of such processes. Considered ideas of role of nanoparticles in processes of FOSM carbonization with subsequent direct reduction of ferric oxides contained in them to metal phase, as well as in processes of alkali treatment and separation of powered iron from phosphorus compounds. Using the obtained results the wasteless method of solid-phase processing, concentration and purification of IORM and FOSM from compounds of phosphorus, silicon and other impurities was developed and it excels known methods of direct iron reduction from iron ores and metallurgical slimes.
Keywords: Iron ores, solid-phase reduction, nanoparticles in reduction and purification of iron from silicon and phosphorus, wasteless method of ores processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17967252 Continuous Functions Modeling with Artificial Neural Network: An Improvement Technique to Feed the Input-Output Mapping
Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa
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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.
Keywords: Neural network computing, information processing, input-output mapping, training time, computers with high memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13237251 Improving the Design of Blood Pressure and Blood Saturation Monitors
Authors: L. Parisi
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A blood pressure monitor or sphygmomanometer can be either manual or automatic, employing respectively either the auscultatory method or the oscillometric method. The manual version of the sphygmomanometer involves an inflatable cuff with a stethoscope adopted to detect the sounds generated by the arterial walls to measure blood pressure in an artery. An automatic sphygmomanometer can be effectively used to monitor blood pressure through a pressure sensor, which detects vibrations provoked by oscillations of the arterial walls. The pressure sensor implemented in this device improves the accuracy of the measurements taken.
Keywords: Blood pressure, blood saturation, sensors, actuators, design improvement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37387250 Image Analysis for Obturator Foramen Based on Marker-Controlled Watershed Segmentation and Zernike Moments
Authors: Seda Sahin, Emin Akata
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Obturator Foramen is a specific structure in Pelvic bone images and recognition of it is a new concept in medical image processing. Moreover, segmentation of bone structures such as Obturator Foramen plays an essential role for clinical research in orthopedics. In this paper, we present a novel method to analyze the similarity between the substructures of the imaged region and a hand drawn template as a preprocessing step for computation of Pelvic bone rotation on hip radiographs. This method consists of integrated usage of Marker-controlled Watershed segmentation and Zernike moment feature descriptor and it is used to detect Obturator Foramen accurately. Marker-controlled Watershed segmentation is applied to separate Obturator Foramen from the background effectively. Then, Zernike moment feature descriptor is used to provide matching between binary template image and the segmented binary image for final extraction of Obturator Foramens. Finally, Pelvic bone rotation rate calculation for each hip radiograph is performed automatically to select and eliminate hip radiographs for further studies which depend on Pelvic bone angle measurements. The proposed method is tested on randomly selected 100 hip radiographs. The experimental results demonstrated that the proposed method is able to segment Obturator Foramen with 96% accuracy.Keywords: Medical image analysis, marker-controlled watershed segmentation, segmentation of bone structures on hip radiographs, pelvic bone rotation rate, zernike moment feature descriptor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19937249 Multi-Sensor Image Fusion for Visible and Infrared Thermal Images
Authors: Amit Kr. Happy
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This paper is motivated by the importance of multi-sensor image fusion with specific focus on Infrared (IR) and Visible image (VI) fusion for various applications including military reconnaissance. Image fusion can be defined as the process of combining two or more source images into a single composite image with extended information content that improves visual perception or feature extraction. These images can be from different modalities like Visible camera & IR Thermal Imager. While visible images are captured by reflected radiations in the visible spectrum, the thermal images are formed from thermal radiation (IR) that may be reflected or self-emitted. A digital color camera captures the visible source image and a thermal IR camera acquires the thermal source image. In this paper, some image fusion algorithms based upon Multi-Scale Transform (MST) and region-based selection rule with consistency verification have been proposed and presented. This research includes implementation of the proposed image fusion algorithm in MATLAB along with a comparative analysis to decide the optimum number of levels for MST and the coefficient fusion rule. The results are presented, and several commonly used evaluation metrics are used to assess the suggested method's validity. Experiments show that the proposed approach is capable of producing good fusion results. While deploying our image fusion algorithm approaches, we observe several challenges from the popular image fusion methods. While high computational cost and complex processing steps of image fusion algorithms provide accurate fused results, but they also make it hard to become deployed in system and applications that require real-time operation, high flexibility and low computation ability. So, the methods presented in this paper offer good results with minimum time complexity.
Keywords: Image fusion, IR thermal imager, multi-sensor, Multi-Scale Transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4307248 Robust Conversion of Chaos into an Arbitrary Periodic Motion
Authors: Abolhassan Razminia, Mohammad-Ali Sadrnia
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One of the most attractive and important field of chaos theory is control of chaos. In this paper, we try to present a simple framework for chaotic motion control using the feedback linearization method. Using this approach, we derive a strategy, which can be easily applied to the other chaotic systems. This task presents two novel results: the desired periodic orbit need not be a solution of the original dynamics and the other is the robustness of response against parameter variations. The illustrated simulations show the ability of these. In addition, by a comparison between a conventional state feedback and our proposed method it is demonstrated that the introduced technique is more efficient.
Keywords: chaos, feedback linearization, robust control, periodic motion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16977247 Comparing Abused and Normal Male Students in Tehran Guidance Schools: Emphasizing the Co-Dependency of Their Mothers
Authors: Mohamad Saleh Sangin Ostadi, Esmail Safari, Somayeh Akbari, Kaveh Qaderi Bagajan
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The aim of this study is to compare abused and normal male students in Tehran guidance schools with emphasis on the co-dependency of their mothers. The method of this study is based on survey method and comparison (Ex-Post Facto). The method of sampling is also multi-stage cluster. Accordingly, we did sampling from secondary schools of education and training in Tehran, including 12 schools with levels of first, second and third. Each of the schools represents the three – high, medium and low- economic and social conditions. In the following, three classes from every school and 20 students from each class were randomly selected. By (CTQ) abused and normal students were separated that 670 children were recognized as normal and 50 children as abused. Then, 50 children were randomly selected from normal group and compared with abused group. Using Spanned-Fischer Co-dependency Scale, we compared mothers of abused and normal students. The results showed that mothers of the abused children have higher co- dependency average comparing to the mothers of the normal children.
Keywords: Co-dependency, child abuse, abused children, parental psychological health.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17217246 Evaluation of the Role of Advocacy and the Quality of Care in Reducing Health Inequalities for People with Autism, Intellectual and Developmental Disabilities at Sheffield Teaching Hospitals
Authors: Jonathan Sahu, Jill Aylott
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Individuals with Autism, Intellectual and Developmental disabilities (AIDD) are one of the most vulnerable groups in society, hampered not only by their own limitations to understand and interact with the wider society, but also societal limitations in perception and understanding. Communication to express their needs and wishes is fundamental to enable such individuals to live and prosper in society. This research project was designed as an organisational case study, in a large secondary health care hospital within the National Health Service (NHS), to assess the quality of care provided to people with AIDD and to review the role of advocacy to reduce health inequalities in these individuals. Methods: The research methodology adopted was as an “insider researcher”. Data collection included both quantitative and qualitative data i.e. a mixed method approach. A semi-structured interview schedule was designed and used to obtain qualitative and quantitative primary data from a wide range of interdisciplinary frontline health care workers to assess their understanding and awareness of systems, processes and evidence based practice to offer a quality service to people with AIDD. Secondary data were obtained from sources within the organisation, in keeping with “Case Study” as a primary method, and organisational performance data were then compared against national benchmarking standards. Further data sources were accessed to help evaluate the effectiveness of different types of advocacy that were present in the organisation. This was gauged by measures of user and carer experience in the form of retrospective survey analysis, incidents and complaints. Results: Secondary data demonstrate near compliance of the Organisation with the current national benchmarking standard (Monitor Compliance Framework). However, primary data demonstrate poor knowledge of the Mental Capacity Act 2005, poor knowledge of organisational systems, processes and evidence based practice applied for people with AIDD. In addition there was poor knowledge and awareness of frontline health care workers of advocacy and advocacy schemes for this group. Conclusions: A significant amount of work needs to be undertaken to improve the quality of care delivered to individuals with AIDD. An operational strategy promoting the widespread dissemination of information may not be the best approach to deliver quality care and optimal patient experience and patient advocacy. In addition, a more robust set of standards, with appropriate metrics, needs to be developed to assess organisational performance which will stand the test of professional and public scrutiny.Keywords: Autism, intellectual developmental disabilities, advocacy, health inequalities, quality of care.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8927245 Adaptive Kernel Principal Analysis for Online Feature Extraction
Authors: Mingtao Ding, Zheng Tian, Haixia Xu
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The batch nature limits the standard kernel principal component analysis (KPCA) methods in numerous applications, especially for dynamic or large-scale data. In this paper, an efficient adaptive approach is presented for online extraction of the kernel principal components (KPC). The contribution of this paper may be divided into two parts. First, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. Second, KPC are recursively formulated to overcome the batch nature of standard KPCA.This formulation is derived from the recursive eigen-decomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. The proposed method not only alleviates sub-optimality of the KPCA method for non-stationary data, but also maintains constant update speed and memory usage as the data-size increases. Experiments for simulation data and real applications demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy.
Keywords: adaptive method, kernel principal component analysis, online extraction, recursive algorithm
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15527244 Hyperspectral Imaging and Nonlinear Fukunaga-Koontz Transform Based Food Inspection
Authors: Hamidullah Binol, Abdullah Bal
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Nowadays, food safety is a great public concern; therefore, robust and effective techniques are required for detecting the safety situation of goods. Hyperspectral Imaging (HSI) is an attractive material for researchers to inspect food quality and safety estimation such as meat quality assessment, automated poultry carcass inspection, quality evaluation of fish, bruise detection of apples, quality analysis and grading of citrus fruits, bruise detection of strawberry, visualization of sugar distribution of melons, measuring ripening of tomatoes, defect detection of pickling cucumber, and classification of wheat kernels. HSI can be used to concurrently collect large amounts of spatial and spectral data on the objects being observed. This technique yields with exceptional detection skills, which otherwise cannot be achieved with either imaging or spectroscopy alone. This paper presents a nonlinear technique based on kernel Fukunaga-Koontz transform (KFKT) for detection of fat content in ground meat using HSI. The KFKT which is the nonlinear version of FKT is one of the most effective techniques for solving problems involving two-pattern nature. The conventional FKT method has been improved with kernel machines for increasing the nonlinear discrimination ability and capturing higher order of statistics of data. The proposed approach in this paper aims to segment the fat content of the ground meat by regarding the fat as target class which is tried to be separated from the remaining classes (as clutter). We have applied the KFKT on visible and nearinfrared (VNIR) hyperspectral images of ground meat to determine fat percentage. The experimental studies indicate that the proposed technique produces high detection performance for fat ratio in ground meat.Keywords: Food (Ground meat) inspection, Fukunaga-Koontz transform, hyperspectral imaging, kernel methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15007243 Epileptic Seizure Prediction by Exploiting Signal Transitions Phenomena
Authors: Mohammad Zavid Parvez, Manoranjan Paul
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A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/ deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.Keywords: Epilepsy, Seizure, Phase Correlation, Fluctuation, Deviation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24677242 Estimation of Natural Frequency of the Bearing System under Periodic Force Based on Principal of Hydrodynamic Mass of Fluid
Authors: M. H. Pol, A. Bidi, A. V. Hoseini
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Estimation of natural frequency of structures is very important and isn-t usually calculated simply and sometimes complicated. Lack of knowledge about that caused hard damage and hazardous effects. In this paper, with using from two different models in FEM method and based on hydrodynamic mass of fluids, natural frequency of an especial bearing (Fig. 1) in an electric field (or, a periodic force) is calculated in different stiffness and different geometric. In final, the results of two models and analytical solution are compared.Keywords: Natural frequency of the bearing, Hydrodynamic mass of fluid method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26467241 Application of Quality Index Method, Texture Measurements and Electronic Nose to Assess the Freshness of Atlantic Herring (Clupea harengus) Stored in Ice
Authors: Nga T.T. Mai, Emilía Martinsdóttir, Kolbrún Sveinsdóttir, Gudrun Olafsdóttir, Sigurjón Arason
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Atlantic herring (Clupea harengus) is an important commercial fish and shows to be more and more demanded for human consumption. Therefore, it is very important to find good methods for monitoring the freshness of the fish in order to keep it in the best quality for human consumption. In this study, the fish was stored in ice up to 2 weeks. Quality changes during storage were assessed by the Quality Index Method (QIM), quantitative descriptive analysis (QDA) and Torry scheme, by texture measurements: puncture tests and Texture Profile Analysis (TPA) tests on texture analyzer TA.XT2i, and by electronic nose (e-nose) measurements using FreshSense instrument. Storage time of herring in ice could be estimated by QIM with ± 2 days using 5 herring per lot. No correlation between instrumental texture parameters and storage time or between sensory and instrumental texture variables was found. E-nose measurements could be use to detect the onset of spoilage.Keywords: Herring, Quality Index Method (QIM), freshness, storage time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16507240 Analysis and Flight Test for Small Inflatable Wing Design
Authors: Zhang Jun-Tao, Hou Zhong-xi, Guo Zheng, Chen Li-li
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This article discusses stress analysis and the shape characteristics of the inflatable wing, and then introduces the design method of inflatable wing, in order to accurately approximate a standard airfoil. It specifically analyses the aerodynamic characteristics of the inflatable wing with the method of CFD, along with comparing to standard airfoil, afterwards we carries out the manufacture of inflatable wing and the flight test.
Keywords: Inflatable wing, Stress analysis, Aerodynamic characteristics, Flight test
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26967239 Improved Computational Efficiency of Machine Learning Algorithms Based on Evaluation Metrics to Control the Spread of Coronavirus in the UK
Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick
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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.
Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1727238 Solution of Logistics Center Selection Problem Using the Axiomatic Design Method
Authors: Fulya Zaralı, Harun Resit Yazgan
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Logistics centers represent areas that all national and international logistics and activities related to logistics can be implemented by the various businesses. Logistics centers have a key importance in joining the transport stream and the transport system operations. Therefore, it is important where these centers are positioned to be effective and efficient and to show the expected performance of the centers. In this study, the location selection problem to position the logistics center is discussed. Alternative centers are evaluated according certain criteria. The most appropriate center is identified using the axiomatic design method.Keywords: Logistic center, axiomatic design, facility location, information systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17987237 Labview-Based System for Fiber Links Events Detection
Authors: Bo Liu, Qingshan Kong, Weiqing Huang
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With the rapid development of modern communication, diagnosing the fiber-optic quality and faults in real-time is widely focused. In this paper, a Labview-based system is proposed for fiber-optic faults detection. The wavelet threshold denoising method combined with Empirical Mode Decomposition (EMD) is applied to denoise the optical time domain reflectometer (OTDR) signal. Then the method based on Gabor representation is used to detect events. Experimental measurements show that signal to noise ratio (SNR) of the OTDR signal is improved by 1.34dB on average, compared with using the wavelet threshold denosing method. The proposed system has a high score in event detection capability and accuracy. The maximum detectable fiber length of the proposed Labview-based system can be 65km.
Keywords: Empirical mode decomposition (EMD), events detection, Gabor transform, optical time domain reflectometer (OTDR), wavelet threshold denoising.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8037236 The Evaluation and Application of FMEA in Sepahan Oil Co
Authors: Hekmatpanah M., Fadavinia, A.
Abstract:
Failure modes and effects analysis (FMEA) is an effective technique for preventing potential problems and actions needed to error cause removal. On the other hand, the oil producing companies paly a critical role in the oil industry of Iran as a developing country out of which, Sepahan Oil Co. has a considerable contribution. The aim of this research is to show how FMEA could be applied and improve the quality of products at Sepahan Oil Co. For this purpose, the four liter production line of the company has been selected for investigation. The findings imply that the application of FMEA has reduced the scraps from 50000 ppm to 5000 ppm and has resulted in a 0.92 percent decrease of the oil waste.
Keywords: FMEA, Iran, Sepahan Oil Co., Canning, Waste, Scrap
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27797235 Smith Predictor Design by CDM for Temperature Control System
Authors: Roengruen P., Tipsuwanporn V., Puawade P., Numsomran A.
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Smith Predictor control is theoretically a good solution to the problem of controlling the time delay systems. However, it seldom gets use because it is almost impossible to find out a precise mathematical model of the practical system and very sensitive to uncertain system with variable time-delay. In this paper is concerned with a design method of smith predictor for temperature control system by Coefficient Diagram Method (CDM). The simulation results show that the control system with smith predictor design by CDM is stable and robust whilst giving the desired time domain system performance.
Keywords: CDM, Smith Predictor, temperature process
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24337234 Synthesis, Characterization and PL Properties of Cds Nanoparticles Confined within a Functionalized SBA-15 Mesoprous
Authors: Azam Anaraki Firooz, Ali Reza Mahjoub, Reza Donyaei Ziba
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A simple and dexterous in situ method was introduced to load CdS nanocrystals into organofunctionalized mesoporous, which used an ion-exchange method. The products were extensively characterized by combined spectroscopic methods. X- ray diffraction (XRD) and high-resolution transmission electron microscopy (HRTEM) demonstrated both the maintenance of pore symmetry (space group p6mm) of SBA-15 and the presence of CdS nanocrystals with uniform sizes of about 6 - 8 nm inside the functionalized SBA-15 channels. These mesoporous silica-supported CdS composites showed room temperature photoluminescence properties with a blue shift, indicating the quantum size effect of nanocrystalline CdS.
Keywords: Semiconductors, luminescence, mesoporous material, CdS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16367233 Operational Risk – Scenario Analysis
Authors: Milan Rippel, Petr Teply
Abstract:
This paper focuses on operational risk measurement techniques and on economic capital estimation methods. A data sample of operational losses provided by an anonymous Central European bank is analyzed using several approaches. Loss Distribution Approach and scenario analysis method are considered. Custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution is evaluated. Two main questions are assessed – What is the most appropriate statistical method to measure and model operational loss data distribution? and What is the impact of hypothetical plausible events on the financial institution? The g&h distribution was evaluated to be the most suitable one for operational risk modeling. The method based on the combination of historical loss events modeling and scenario analysis provides reasonable capital estimates and allows for the measurement of the impact of extreme events on banking operations.Keywords: operational risk, scenario analysis, economic capital, loss distribution approach, extreme value theory, stress testing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2429