Search results for: Accuracy Assessment
2707 A Family Cars- Life Cycle Cost (LCC)-Oriented Hybrid Modelling Approach Combining ANN and CBR
Authors: Xiaochuan Chen, Jianguo Yang, Beizhi Li
Abstract:
Design for cost (DFC) is a method that reduces life cycle cost (LCC) from the angle of designers. Multiple domain features mapping (MDFM) methodology was given in DFC. Using MDFM, we can use design features to estimate the LCC. From the angle of DFC, the design features of family cars were obtained, such as all dimensions, engine power and emission volume. At the conceptual design stage, cars- LCC were estimated using back propagation (BP) artificial neural networks (ANN) method and case-based reasoning (CBR). Hamming space was used to measure the similarity among cases in CBR method. Levenberg-Marquardt (LM) algorithm and genetic algorithm (GA) were used in ANN. The differences of LCC estimation model between CBR and artificial neural networks (ANN) were provided. ANN and CBR separately each method has its shortcomings. By combining ANN and CBR improved results accuracy was obtained. Firstly, using ANN selected some design features that affect LCC. Then using LCC estimation results of ANN could raise the accuracy of LCC estimation in CBR method. Thirdly, using ANN estimate LCC errors and correct errors in CBR-s estimation results if the accuracy is not enough accurate. Finally, economically family cars and sport utility vehicle (SUV) was given as LCC estimation cases using this hybrid approach combining ANN and CBR.Keywords: case-based reasoning, life cycle cost (LCC), artificialneural networks (ANN), family cars
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19522706 Performance Analysis of Genetic Algorithm with kNN and SVM for Feature Selection in Tumor Classification
Authors: C. Gunavathi, K. Premalatha
Abstract:
Tumor classification is a key area of research in the field of bioinformatics. Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. The main drawback of gene expression data is that it contains thousands of genes and a very few samples. Feature selection methods are used to select the informative genes from the microarray. These methods considerably improve the classification accuracy. In the proposed method, Genetic Algorithm (GA) is used for effective feature selection. Informative genes are identified based on the T-Statistics, Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate solutions of GA are obtained from top-m informative genes. The classification accuracy of k-Nearest Neighbor (kNN) method is used as the fitness function for GA. In this work, kNN and Support Vector Machine (SVM) are used as the classifiers. The experimental results show that the proposed work is suitable for effective feature selection. With the help of the selected genes, GA-kNN method achieves 100% accuracy in 4 datasets and GA-SVM method achieves in 5 out of 10 datasets. The GA with kNN and SVM methods are demonstrated to be an accurate method for microarray based tumor classification.
Keywords: F-Test, Gene Expression, Genetic Algorithm, k- Nearest-Neighbor, Microarray, Signal-to-Noise Ratio, Support Vector Machine, T-statistics, Tumor Classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 45272705 Effective Design Parameters on the End Effect in Single-Sided Linear Induction Motors
Authors: A. Zare Bazghaleh, M. R. Naghashan, H. Mahmoudimanesh, M. R. Meshkatoddini
Abstract:
Linear induction motors are used in various industries but they have some specific phenomena which are the causes for some problems. The most important phenomenon is called end effect. End effect decreases efficiency, power factor and output force and unbalances the phase currents. This phenomenon is more important in medium and high speeds machines. In this paper a factor, EEF , is obtained by an accurate equivalent circuit model, to determine the end effect intensity. In this way, all of effective design parameters on end effect is described. Accuracy of this equivalent circuit model is evaluated by two dimensional finite-element analysis using ANSYS. The results show the accuracy of the equivalent circuit model.Keywords: Linear induction motor, end effect, equivalent circuitmodel, finite-element method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27862704 Taguchi-Based Optimization of Surface Roughness and Dimensional Accuracy in Wire EDM Process with S7 Heat Treated Steel
Authors: Joseph C. Chen, Joshua Cox
Abstract:
This research focuses on the use of the Taguchi method to reduce the surface roughness and improve dimensional accuracy of parts machined by Wire Electrical Discharge Machining (EDM) with S7 heat treated steel material. Due to its high impact toughness, the material is a candidate for a wide variety of tooling applications which require high precision in dimension and desired surface roughness. This paper demonstrates that Taguchi Parameter Design methodology is able to optimize both dimensioning and surface roughness successfully by investigating seven wire-EDM controllable parameters: pulse on time (ON), pulse off time (OFF), servo voltage (SV), voltage (V), servo feed (SF), wire tension (WT), and wire speed (WS). The temperature of the water in the Wire EDM process is investigated as the noise factor in this research. Experimental design and analysis based on L18 Taguchi orthogonal arrays are conducted. This paper demonstrates that the Taguchi-based system enables the wire EDM process to produce (1) high precision parts with an average of 0.6601 inches dimension, while the desired dimension is 0.6600 inches; and (2) surface roughness of 1.7322 microns which is significantly improved from 2.8160 microns.
Keywords: Taguchi parameter design, surface roughness, dimensional accuracy, Wire EDM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10772703 Subjective Versus Objective Assessment for Magnetic Resonance Images
Authors: Heshalini Rajagopal, Li Sze Chow, Raveendran Paramesran
Abstract:
Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modality. Subjective assessment of the image quality is regarded as the gold standard to evaluate MR images. In this study, a database of 210 MR images which contains ten reference images and 200 distorted images is presented. The reference images were distorted with four types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur and DCT compression. The 210 images were assessed by ten subjects. The subjective scores were presented in Difference Mean Opinion Score (DMOS). The DMOS values were compared with four FR-IQA metrics. We have used Pearson Linear Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) to validate the DMOS values. The high correlation values of PLCC and SROCC shows that the DMOS values are close to the objective FR-IQA metrics.Keywords: Medical Resonance (MR) images, Difference Mean Opinion Score (DMOS), Full Reference Image Quality Assessment (FR-IQA).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22052702 Feature Subset Selection approach based on Maximizing Margin of Support Vector Classifier
Authors: Khin May Win, Nan Sai Moon Kham
Abstract:
Identification of cancer genes that might anticipate the clinical behaviors from different types of cancer disease is challenging due to the huge number of genes and small number of patients samples. The new method is being proposed based on supervised learning of classification like support vector machines (SVMs).A new solution is described by the introduction of the Maximized Margin (MM) in the subset criterion, which permits to get near the least generalization error rate. In class prediction problem, gene selection is essential to improve the accuracy and to identify genes for cancer disease. The performance of the new method was evaluated with real-world data experiment. It can give the better accuracy for classification.Keywords: Microarray data, feature selection, recursive featureelimination, support vector machines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15332701 State-Of-The Art Practices in Bridge Inspection
Authors: Salam R. Yaghi, Saleh Abu Dabous
Abstract:
Government reports and published research have flagged and brought to public attention the deteriorating condition of a large percentage of bridges in Canada and the United States. With the increasing number of deteriorated bridges in the US, Canada, and around the globe, condition assessment techniques of concrete bridges are evolving. Investigation for bridges’ defects such as cracks, spalls, and delamination and their level of severity are the main objectives of condition assessment. Inspection and rehabilitation programs are being implemented to monitor and maintain deteriorated bridge infrastructure. This paper highlights the state-of-the art of current practices being performed for concrete bridge inspection. The information is gathered from the literature and through a distributed questionnaire. The current practices in concrete bridge inspection rely on the use of hummer sounding and chain dragging tests. Non-Destructive Testing (NDT) techniques are not being utilized fully in the process. Nonetheless, they are being partially utilized by the recommendation of the bridge inspector after conducting visual inspection. Lanes are usually closed during the performance of visual inspection and bridge inspection in general.Keywords: Bridge Inspection, Condition Assessment, questionnaire, Non-Destructive Testing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19952700 The Selection of the Nearest Anchor Using Received Signal Strength Indication (RSSI)
Authors: Hichem Sassi, Tawfik Najeh, Noureddine Liouane
Abstract:
The localization information is crucial for the operation of WSN. There are principally two types of localization algorithms. The Range-based localization algorithm has strict requirements on hardware, thus is expensive to be implemented in practice. The Range-free localization algorithm reduces the hardware cost. However, it can only achieve high accuracy in ideal scenarios. In this paper, we locate unknown nodes by incorporating the advantages of these two types of methods. The proposed algorithm makes the unknown nodes select the nearest anchor using the Received Signal Strength Indicator (RSSI) and choose two other anchors which are the most accurate to achieve the estimated location. Our algorithm improves the localization accuracy compared with previous algorithms, which has been demonstrated by the simulating results.Keywords: WSN, localization, DV-hop, RSSI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18022699 Risk Assessment of Particulate Matter (PM10) in Makkah, Saudi Arabia
Authors: Turki M. Habeebullah, Atef M. F. Mohammed, Essam A. Morsy
Abstract:
In recent decades, particulate matter (PM10) have received much attention due to its potential adverse health impact and the subsequent need to better control or regulate these pollutants. The aim of this paper is focused on study risk assessment of PM10 in four different districts (Shebikah, Masfalah, Aziziyah, Awali) in Makkah, Saudi Arabia during the period from 1 Ramadan 1434 AH - 27 Safar 1435 AH. Samples were collected by using Low Volume Sampler (LVS Low Volume Sampler) device and filtration method for estimating the total concentration of PM10. The study indicated that the mean PM10 concentrations were 254.6 (186.1 - 343.2) μg/m3 in Shebikah, 184.9 (145.6 - 271.4) μg/m3 in Masfalah, 162.4 (92.4-253.8) μg/m3 in Aziziyah, and 56.0 (44.5 - 119.8) μg/m3 in Awali. These values did not exceed the permissible limits in PME (340 μg/m3 as daily average). Furthermore, health assessment is carried out using AirQ2.2.3 model to estimate the number of hospital admissions due to respiratory diseases. The cumulative number of cases per 100,000 were 1534 (18-3050 case), which lower than that recorded in the United States, Malaysia. The concentration response coefficient was 0.49 (95% CI 0.05 - 0.70) per 10 μg/m3 increase of PM10.Keywords: Air pollution, Respiratory diseases, AirQ2.2.3, Makkah.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25892698 Application of BP Neural Network Model in Sports Aerobics Performance Evaluation
Authors: Shuhe Shao
Abstract:
This article provides partial evaluation index and its standard of sports aerobics, including the following 12 indexes: health vitality, coordination, flexibility, accuracy, pace, endurance, elasticity, self-confidence, form, control, uniformity and musicality. The three-layer BP artificial neural network model including input layer, hidden layer and output layer is established. The result shows that the model can well reflect the non-linear relationship between the performance of 12 indexes and the overall performance. The predicted value of each sample is very close to the true value, with a relative error fluctuating around of 5%, and the network training is successful. It shows that BP network has high prediction accuracy and good generalization capacity if being applied in sports aerobics performance evaluation after effective training.Keywords: BP neural network, sports aerobics, performance, evaluation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16082697 On Developing a Core Guideline for English Language Training Programs in Business Settings
Authors: T. Ito, K. Kawaguchi, R. Ohta
Abstract:
The purpose of this study is to provide a guideline to assist globally-minded companies in developing task-based English- language programs for their employees. After conducting an online self-assessment questionnaire comprised of 45 job-related tasks, we analyzed responses received from 3,000 Japanese company employees and developed a checklist that considered three areas; i) the percentage of those who need to accomplish English-language tasks in their workplace (need for English), ii) a five-point self-assessment score (task performance level), and iii) the impact of previous task experience on perceived performance (experience factor). The 45 tasks were graded according to five proficiency levels. Our results helped us to create a core guideline that may assist companies in two ways: first, in helping determine which tasks employees with a certain English proficiency should be able to satisfactorily carry out, and secondly, to quickly prioritize which business-related English skills they would need in future English language programs.
Keywords: Business settings, Can-do statements, English language training programs, Self-assessment, Task experience.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14392696 Stochastic Learning Algorithms for Modeling Human Category Learning
Authors: Toshihiko Matsuka, James E. Corter
Abstract:
Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.Keywords: category learning, cognitive modeling, radial basis function, stochastic optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16192695 Safety Climate Assessment and Its Impact on the Productivity of Construction Enterprises
Authors: Krzysztof J. Czarnocki, F. Silveira, E. Czarnocka, K. Szaniawska
Abstract:
Research background: Problems related to the occupational health and decreasing level of safety occur commonly in the construction industry. Important factor in the occupational safety in construction industry is scaffold use. All scaffolds used in construction, renovation, and demolition shall be erected, dismantled and maintained in accordance with safety procedure. Increasing demand for new construction projects unfortunately still is linked to high level of occupational accidents. Therefore, it is crucial to implement concrete actions while dealing with scaffolds and risk assessment in construction industry, the way on doing assessment and liability of assessment is critical for both construction workers and regulatory framework. Unfortunately, professionals, who tend to rely heavily on their own experience and knowledge when taking decisions regarding risk assessment, may show lack of reliability in checking the results of decisions taken. Purpose of the article: The aim was to indicate crucial parameters that could be modeling with Risk Assessment Model (RAM) use for improving both building enterprise productivity and/or developing potential and safety climate. The developed RAM could be a benefit for predicting high-risk construction activities and thus preventing accidents occurred based on a set of historical accident data. Methodology/Methods: A RAM has been developed for assessing risk levels as various construction process stages with various work trades impacting different spheres of enterprise activity. This project includes research carried out by teams of researchers on over 60 construction sites in Poland and Portugal, under which over 450 individual research cycles were carried out. The conducted research trials included variable conditions of employee exposure to harmful physical and chemical factors, variable levels of stress of employees and differences in behaviors and habits of staff. Genetic modeling tool has been used for developing the RAM. Findings and value added: Common types of trades, accidents, and accident causes have been explored, in addition to suitable risk assessment methods and criteria. We have found that the initial worker stress level is more direct predictor for developing the unsafe chain leading to the accident rather than the workload, or concentration of harmful factors at the workplace or even training frequency and management involvement.
Keywords: Civil engineering, occupational health, productivity, safety climate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11012694 Face Recognition Using Principal Component Analysis, K-Means Clustering, and Convolutional Neural Network
Authors: Zukisa Nante, Wang Zenghui
Abstract:
Face recognition is the problem of identifying or recognizing individuals in an image. This paper investigates a possible method to bring a solution to this problem. The method proposes an amalgamation of Principal Component Analysis (PCA), K-Means clustering, and Convolutional Neural Network (CNN) for a face recognition system. It is trained and evaluated using the ORL dataset. This dataset consists of 400 different faces with 40 classes of 10 face images per class. Firstly, PCA enabled the usage of a smaller network. This reduces the training time of the CNN. Thus, we get rid of the redundancy and preserve the variance with a smaller number of coefficients. Secondly, the K-Means clustering model is trained using the compressed PCA obtained data which select the K-Means clustering centers with better characteristics. Lastly, the K-Means characteristics or features are an initial value of the CNN and act as input data. The accuracy and the performance of the proposed method were tested in comparison to other Face Recognition (FR) techniques namely PCA, Support Vector Machine (SVM), as well as K-Nearest Neighbour (kNN). During experimentation, the accuracy and the performance of our suggested method after 90 epochs achieved the highest performance: 99% accuracy F1-Score, 99% precision, and 99% recall in 463.934 seconds. It outperformed the PCA that obtained 97% and KNN with 84% during the conducted experiments. Therefore, this method proved to be efficient in identifying faces in the images.
Keywords: Face recognition, Principal Component Analysis, PCA, Convolutional Neural Network, CNN, Rectified Linear Unit, ReLU, feature extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4772693 A Comparative Study on the Impact of Global Warming of Applying Low Carbon Factor Concrete Products
Authors: Su-Hyun Cho, Chang-U Chae
Abstract:
Environmental impact assessment techniques have been developed as a result of the worldwide efforts to reduce the environmental impact of global warming. By using the quantification method in the construction industry, it is now possible to manage the greenhouse gas is to systematically evaluate the impact on the environment over the entire construction process. In particular, the proportion of greenhouse gas emissions at the production stage of construction material occupied is high, and efforts are needed in particular in the construction field. In this research, intended for concrete products for the construction materials, by using the LCA method, we compared the results of environmental impact assessment and carbon emissions of developing products that have been applied low-carbon technologies compared to existing products. As a results, by introducing a raw material of industrial waste, showed carbon reduction. Through a comparison of the carbon emission reduction effect of low carbon technologies, it is intended to provide academic data for the evaluation of greenhouse gases in the construction sector and the development of low carbon technologies of the future.
Keywords: CO2 Emissions, CO2 Reduction, Ready-mixed Concrete, Environmental Impact Assessment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20442692 Acoustic Source Localization Based On the Extended Kalman Filter for an Underwater Vehicle with a Pair of Hydrophones
Authors: ByungHoon Kang, Jeawook Shin, Ju-man Song, Hyun-Taek Choi, PooGyeon Park
Abstract:
In this study, we consider a special situation that only a pair of hydrophone on a moving underwater vehicle is available to localize a fixed acoustic source of far distance. The trigonometry can be used in this situation by using two different DOA of different locations. Notice that the distance between the two locations should be measured. Therefore, we assume that the vehicle is sailing straightly and the moving distance for each unit time is measured continuously. However, the accuracy of the localization using the trigonometry is highly dependent to the accuracy of DOAs and measured moving distances. Therefore, we proposed another method based on the extended Kalman filter that gives more robust and accurate localization result.
Keywords: Localization, acoustic, underwater, extended Kalman filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21832691 ELD79-LGD2006 Transformation Techniques Implementation and Accuracy Comparison in Tripoli Area, Libya
Authors: Jamal A. Gledan, Othman A. Azzeidani
Abstract:
During the last decade, Libya established a new Geodetic Datum called Libyan Geodetic Datum 2006 (LGD 2006) by using GPS, whereas the ground traversing method was used to establish the last Libyan datum which was called the Europe Libyan Datum 79 (ELD79). The current research paper introduces ELD79 to LGD2006 coordinate transformation technique, the accurate comparison of transformation between multiple regression equations and the three – parameters model (Bursa-Wolf). The results had been obtained show that the overall accuracy of stepwise multi regression equations is better than that can be determined by using Bursa-Wolf transformation model.
Keywords: Geodetic datum, horizontal control points, traditional similarity transformation model, unconventional transformation techniques.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27222690 Slice Bispectrogram Analysis-Based Classification of Environmental Sounds Using Convolutional Neural Network
Authors: Katsumi Hirata
Abstract:
Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.
Keywords: Bispectrum, convolutional neural network, environmental sound, slice bispectrogram, spectrogram.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6062689 A Recommender System Fusing Collaborative Filtering and User’s Review Mining
Authors: Seulbi Choi, Hyunchul Ahn
Abstract:
Collaborative filtering (CF) algorithm has been popularly used for recommender systems in both academic and practical applications. It basically generates recommendation results using users’ numeric ratings. However, the additional use of the information other than user ratings may lead to better accuracy of CF. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's review can be regarded as the new informative source for identifying user's preference with accuracy. Under this background, this study presents a hybrid recommender system that fuses CF and user's review mining. Our system adopts conventional memory-based CF, but it is designed to use both user’s numeric ratings and his/her text reviews on the items when calculating similarities between users.Keywords: Recommender system, collaborative filtering, text mining, review mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15792688 Environmental Impact Assessment of Gotv and Hydro-Electric Dam on the Karoon River Using ICOLD Technique
Authors: A. Sayadi, A. Khodadadi D., S. Partani
Abstract:
Today Environmental Impact Assessment (EIA) is known as one of the most important tools for decision makers in the construction of civil and industrial projects towards sustainable development. In the past, projects were evaluated based on cost and benefit analysis regardless of the physical and biological environmental effects and its socio-economical impacts. According to the Department of Environment (DOE) of Iran's regulations, the construction of hydroelectric dams is an activity that requires an EIA report. In this paper the environmental impact assessment of the Gotvand hydro-electrical dam has been evaluated in the three environment elements, biological, Physical-chemical and cultural units. This dam is one of the largest dams in Iran with a volume of 4500 MCM and is going to be the last dam on the Karoon River in the south of Iran. In this paper the ICOLD (International Commission on Large Dams) technique was employed for the environmental impact assessment of the dam. The research includes all socio economical and environmental effects of the dam during the construction and operation of the hydro electric dam and Environmental management, monitoring and mitigation of negative impacts were analyzed. In this project the results led to using some techniques to protect the destructive impacts on biological aspects beside the effective long time period impacts on the biological aspects. The impacts on physical aspects are temporary and negative commonly that could be restored and rehabilitated in natural process in the long time in operation period.
Keywords: "Gotvand Hydro Electric Dam", "EIA", "ICOLD and Leopold matrices"
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33732687 Bi-Lateral Comparison between NIS-Egypt and NMISA-South Africa for the Calibration of an Optical Spectrum Analyzer
Authors: Osama Terra, Hatem Hussein, Adriaan Van Brakel
Abstract:
Dense wavelength division multiplexing (DWDM) technology requires tight specification and therefore measurement of wavelength accuracy and stability of the telecommunication lasers. Thus, calibration of the used Optical Spectrum Analyzers (OSAs) that are used to measure wavelength is of a great importance. Proficiency testing must be performed on such measuring activity to insure the accuracy of the measurement results. In this paper, a new comparison scheme is introduced to test the performance of such calibrations. This comparison scheme is implemented between NIS-Egypt and NMISA-South Africa for the calibration of the wavelength scale of an OSA. Both institutes employ reference gas cell to calibrate OSA according to the standard IEC/ BS EN 62129 (2006). The result of this comparison is compiled in this paper.
Keywords: OSA calibration, HCN gas cell, DWDM technology, wavelength measurement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10312686 Calibration of the Radical Installation Limit Error of the Accelerometer in the Gravity Gradient Instrument
Authors: Danni Cong, Meiping Wu, Xiaofeng He, Junxiang Lian, Juliang Cao, Shaokuncai, Hao Qin
Abstract:
Gravity gradient instrument (GGI) is the core of the gravity gradiometer, so the structural error of the sensor has a great impact on the measurement results. In order not to affect the aimed measurement accuracy, limit error is required in the installation of the accelerometer. In this paper, based on the established measuring principle model, the radial installation limit error is calibrated, which is taken as an example to provide a method to calculate the other limit error of the installation under the premise of ensuring the accuracy of the measurement result. This method provides the idea for deriving the limit error of the geometry structure of the sensor, laying the foundation for the mechanical precision design and physical design.Keywords: Gravity gradient sensor, radial installation limit error, accelerometer, uniaxial rotational modulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9182685 Quality of Concrete of Recent Development Projects in Libya
Authors: Mohamed .S .Alazhari, Milad. M. Al Shebani
Abstract:
Numerous concrete structures projects are currently running in Libya as part of a US$50 billion government funding. The quality of concrete used in 20 different construction projects were assessed based mainly on the concrete compressive strength achieved. The projects are scattered all over the country and are at various levels of completeness. For most of these projects, the concrete compressive strength was obtained from test results of a 150mm standard cube mold. Statistical analysis of collected concrete compressive strengths reveals that the data in general followed a normal distribution pattern. The study covers comparison and assessment of concrete quality aspects such as: quality control, strength range, data standard deviation, data scatter, and ratio of minimum strength to design strength. Site quality control for these projects ranged from very good to poor according to ACI214 criteria [1]. The ranges (Rg) of the strength (max. strength – min. strength) divided by average strength are from (34% to 160%). Data scatter is measured as the range (Rg) divided by standard deviation () and is found to be (1.82 to 11.04), indicating that the range is ±3σ. International construction companies working in Libya follow different assessment criteria for concrete compressive strength in lieu of national unified procedure. The study reveals that assessments of concrete quality conducted by these construction companies usually meet their adopted (internal) standards, but sometimes fail to meet internationally known standard requirements. The assessment of concrete presented in this paper is based on ACI, British standards and proposed Libyan concrete strength assessment criteria.Keywords: Acceptance criteria, Concrete, Compressive strength, quality control
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17532684 A Novel Spectral Index for Automatic Shadow Detection in Urban Mapping Based On WorldView-2 Satellite Imagery
Authors: Kaveh Shahi, Helmi Z. M. Shafri, Ebrahim Taherzadeh
Abstract:
In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of WorldView-2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows with accuracy of 94% effectively and automatically. Furthermore, the new shadow detection index improved road extraction from 82% to 93%.
Keywords: Spectral index, shadow detection, remote sensing images, WorldView-2.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33142683 CMOS Solid-State Nanopore DNA System-Level Sequencing Techniques Enhancement
Authors: Syed Islam, Yiyun Huang, Sebastian Magierowski, Ebrahim Ghafar-Zadeh
Abstract:
This paper presents system level CMOS solid-state nanopore techniques enhancement for speedup next generation molecular recording and high throughput channels. This discussion also considers optimum number of base-pair (bp) measurements through channel as an important role to enhance potential read accuracy. Effective power consumption estimation offered suitable range of multi-channel configuration. Nanopore bp extraction model in statistical method could contribute higher read accuracy with longer read-length (200 < read-length). Nanopore ionic current switching with Time Multiplexing (TM) based multichannel readout system contributed hardware savings.
Keywords: DNA, Nanopore, Amplifier, ADC, Multichannel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29182682 Assessing the Viability of Solar Water Pumps Economically, Socially and Environmentally in Soan Valley, Punjab
Authors: Zenab Naseem, Sadia Imran
Abstract:
One of the key solutions to the climate change crisis is to develop renewable energy resources, such as solar and wind power and biogas. This paper explores the socioeconomic and environmental viability of solar energy, based on a case study of the Soan Valley Development Program. Under this project, local farmers were provided solar water pumps at subsidized rates. These have been functional for the last seven years and have gained popularity among the local communities. The study measures the economic viability of using solar energy in agriculture, based on data from 36 households, of which 12 households each use diesel, electric and solar water pumps. Our findings are based on the net present value of each technology type. We also carry out a qualitative assessment of the social impact of solar water pumps relative to diesel and electric pumps. Finally, we conduct an environmental impact assessment, using the lifecycle assessment approach. All three analyses indicate that solar energy is a viable alternative to diesel and electricity.Keywords: Alternative energy sources, pollution control adoption and costs, solar energy pumps, sustainable development.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26142681 Designing an Optimal Safe Layout for a Fuel Storage Tanks Farm: Case Study of Jaipur Oil Depot
Authors: Moosa Haji Abbasi, Emad Benhelal, Arshad Ahmad
Abstract:
Storage tank farms are essential industrial facilities to accumulate oil, petrochemicals and gaseous products. Since tank farms contain huge mass of fuel and hazardous materials, they are always targets of serious accidents such as fire, explosion, spill and toxic release which may cause severe impacts on human health, environmental and properties.
Although having a safe layout is not able to prevent initiating accidents, however it effectively controls and reduces the adverse impact of such accidents.
The aim of this paper is to determine the optimal layout for a storage tank contains different type of hydrocarbon fuels. A quantitative risk assessment is carried out on a selected tank farm in Jaipur, India, with particular attention given to both the consequence modeling and the overall risk assessment using PHAST Software. Various designs of tank layouts are examined taking into consideration several issues of plant operations and maintenance. In all stages of the work, standard guidelines specified by the industry are considered and recommendations are substantiated with simulation results and risk quantification.
Keywords: Tank farm, safe distance, safe layout, risk assessment, PHAST.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 156222680 Application of KL Divergence for Estimation of Each Metabolic Pathway Genes
Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani
Abstract:
Development of a method to estimate gene functions is an important task in bioinformatics. One of the approaches for the annotation is the identification of the metabolic pathway that genes are involved in. Since gene expression data reflect various intracellular phenomena, those data are considered to be related with genes’ functions. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.
Keywords: Metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23162679 Enhanced Weighted Centroid Localization Algorithm for Indoor Environments
Authors: I. Nižetić Kosović, T. Jagušt
Abstract:
Lately, with the increasing number of location-based applications, demand for highly accurate and reliable indoor localization became urgent. This is a challenging problem, due to the measurement variance which is the consequence of various factors like obstacles, equipment properties and environmental changes in complex nature of indoor environments. In this paper we propose low-cost custom-setup infrastructure solution and localization algorithm based on the Weighted Centroid Localization (WCL) method. Localization accuracy is increased by several enhancements: calibration of RSSI values gained from wireless nodes, repetitive measurements of RSSI to exclude deviating values from the position estimation, and by considering orientation of the device according to the wireless nodes. We conducted several experiments to evaluate the proposed algorithm. High accuracy of ~1m was achieved.
Keywords: Indoor environment, received signal strength indicator, weighted centroid localization, wireless localization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30862678 A Matching Algorithm of Minutiae for Real Time Fingerprint Identification System
Authors: Shahram Mohammadi, Ali Frajzadeh
Abstract:
A lot of matching algorithms with different characteristics have been introduced in recent years. For real time systems these algorithms are usually based on minutiae features. In this paper we introduce a novel approach for feature extraction in which the extracted features are independent of shift and rotation of the fingerprint and at the meantime the matching operation is performed much more easily and with higher speed and accuracy. In this new approach first for any fingerprint a reference point and a reference orientation is determined and then based on this information features are converted into polar coordinates. Due to high speed and accuracy of this approach and small volume of extracted features and easily execution of matching operation this approach is the most appropriate for real time applications.
Keywords: Matching, Minutiae, Reference point, Reference orientation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2404