Search results for: Statistical Pattern Recognition.
1997 3-D Reconstruction of Objects Using Digital Fringe Projection: Survey and Experimental Study
Authors: R. Talebi, A. Abdel-Dayem, J. Johnson
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Three-dimensional reconstruction of small objects has been one of the most challenging problems over the last decade. Computer graphics researchers and photography professionals have been working on improving 3D reconstruction algorithms to fit the high demands of various real life applications. Medical sciences, animation industry, virtual reality, pattern recognition, tourism industry, and reverse engineering are common fields where 3D reconstruction of objects plays a vital role. Both lack of accuracy and high computational cost are the major challenges facing successful 3D reconstruction. Fringe projection has emerged as a promising 3D reconstruction direction that combines low computational cost to both high precision and high resolution. It employs digital projection, structured light systems and phase analysis on fringed pictures. Research studies have shown that the system has acceptable performance, and moreover it is insensitive to ambient light. This paper presents an overview of fringe projection approaches. It also presents an experimental study and implementation of a simple fringe projection system. We tested our system using two objects with different materials and levels of details. Experimental results have shown that, while our system is simple, it produces acceptable results.Keywords: Digital fringe projection, 3D reconstruction, phase unwrapping, phase shifting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 52201996 Release Management with Continuous Delivery: A Case Study
Authors: A. Maruf Aytekin
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We present our approach on using continuous delivery pattern for release management. One of the key practices of agile and lean teams is the continuous delivery of new features to stakeholders. The main benefits of this approach lie in the ability to release new applications rapidly which has real strategic impact on the competitive advantage of an organization. Organizations that successfully implement Continuous Delivery have the ability to evolve rapidly to support innovation, provide stable and reliable software in more efficient ways, decrease the amount of resources need for maintenance, and lower the software delivery time and costs. One of the objectives of this paper is to elaborate a case study where IT division of Central Securities Depository Institution (MKK) of Turkey apply Continuous Delivery pattern to improve release management process.
Keywords: Automation, continuous delivery, deployment, release management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 54661995 Land Use Changes in Two Mediterranean Coastal Regions: Do Urban Areas Matter?
Authors: L. Salvati, D. Smiraglia, S. Bajocco, M. Munafò
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This paper focuses on Land Use and Land Cover Changes (LULCC) occurred in the urban coastal regions of the Mediterranean basin in the last thirty years. LULCC were assessed diachronically (1975-2006) in two urban areas, Rome (Italy) and Athens (Greece), by using CORINE land cover maps. In strictly coastal territories a persistent growth of built-up areas at the expenses of both agricultural and forest land uses was found. On the contrary, a different pattern was observed in the surrounding inland areas, where a high conversion rate of the agricultural land uses to both urban and forest land uses was recorded. The impact of city growth on the complex pattern of coastal LULCC is finally discussed.
Keywords: Land use changes, coastal region, Rome, Attica, southern Europe.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24311994 Navigation Patterns Mining Approach based on Expectation Maximization Algorithm
Authors: Norwati Mustapha, Manijeh Jalali, Abolghasem Bozorgniya, Mehrdad Jalali
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Web usage mining algorithms have been widely utilized for modeling user web navigation behavior. In this study we advance a model for mining of user-s navigation pattern. The model makes user model based on expectation-maximization (EM) algorithm.An EM algorithm is used in statistics for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. The experimental results represent that by decreasing the number of clusters, the log likelihood converges toward lower values and probability of the largest cluster will be decreased while the number of the clusters increases in each treatment.Keywords: Web Usage Mining, Expectation maximization, navigation pattern mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15791993 Development of a Complex Meteorological Support System for UAVs
Authors: Z. Bottyán, F. Wantuch, A. Z. Gyöngyösi, Z. Tuba, K. Hadobács, P. Kardos, R. Kurunczi
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The sensitivity of UAVs to the atmospheric effects are apparent. All the same the meteorological support for the UAVs missions is often non-adequate or partly missing. In our paper we show a new complex meteorological support system for different types of UAVs pilots, specialists and decision makers, too. The mentioned system has two important parts with different forecasts approach such as the statistical and dynamical ones. The statistical prediction approach is based on a large climatological data base and the special analog method which is able to select similar weather situations from the mentioned data base to apply them during the forecasting procedure. The applied dynamic approach uses the specific WRF model runs twice a day and produces 96 hours, high resolution weather forecast for the UAV users over the Hungary. An easy to use web-based system can give important weather information over the Carpathian basin in Central-Europe. The mentioned products can be reached via internet connection.Keywords: Aviation meteorology, statistical weather prediction, unmanned aerial systems, WRF.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27601992 Vision Based Hand Gesture Recognition
Authors: Pragati Garg, Naveen Aggarwal, Sanjeev Sofat
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With the development of ubiquitous computing, current user interaction approaches with keyboard, mouse and pen are not sufficient. Due to the limitation of these devices the useable command set is also limited. Direct use of hands as an input device is an attractive method for providing natural Human Computer Interaction which has evolved from text-based interfaces through 2D graphical-based interfaces, multimedia-supported interfaces, to fully fledged multi-participant Virtual Environment (VE) systems. Imagine the human-computer interaction of the future: A 3Dapplication where you can move and rotate objects simply by moving and rotating your hand - all without touching any input device. In this paper a review of vision based hand gesture recognition is presented. The existing approaches are categorized into 3D model based approaches and appearance based approaches, highlighting their advantages and shortcomings and identifying the open issues.Keywords: Computer Vision, Hand Gesture, Hand Posture, Human Computer Interface.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 63411991 Optimizing of Fuzzy C-Means Clustering Algorithm Using GA
Authors: Mohanad Alata, Mohammad Molhim, Abdullah Ramini
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Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models.Keywords: Fuzzy clustering, Fuzzy C-Means, Genetic Algorithm, Sugeno fuzzy systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32561990 Use of Gaussian-Euclidean Hybrid Function Based Artificial Immune System for Breast Cancer Diagnosis
Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel
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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.
Keywords: Artificial Immune System, Breast Cancer Diagnosis, Euclidean Function, Gaussian Function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21211989 A File Splitting Technique for Reducing the Entropy of Text Files
Authors: Abdel-Rahman M. Jaradat, , Mansour I. Irshid, Talha T. Nassar
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A novel file splitting technique for the reduction of the nth-order entropy of text files is proposed. The technique is based on mapping the original text file into a non-ASCII binary file using a new codeword assignment method and then the resulting binary file is split into several subfiles each contains one or more bits from each codeword of the mapped binary file. The statistical properties of the subfiles are studied and it is found that they reflect the statistical properties of the original text file which is not the case when the ASCII code is used as a mapper. The nth-order entropy of these subfiles are determined and it is found that the sum of their entropies is less than that of the original text file for the same values of extensions. These interesting statistical properties of the resulting subfiles can be used to achieve better compression ratios when conventional compression techniques are applied to these subfiles individually and on a bit-wise basis rather than on character-wise basis.
Keywords: Bit-wise compression, entropy, file splitting, source mapping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14441988 A Neural Network Classifier for Estimation of the Degree of Infestation by Late Blight on Tomato Leaves
Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira
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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.
Keywords: Artificial neural networks, digital image processing, pattern recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25531987 Tracking Objects in Color Image Sequences: Application to Football Images
Authors: Mourad Moussa, Ali Douik, Hassani Messaoud
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In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.
Keywords: Image segmentation, objects tracking, Parzen window, singular value decomposition, target recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19851986 A Thai to English Machine Translation System Using Thai LFG Tree Structure as Interlingua
Authors: Tawee Chimsuk, Surapong Auwatanamongkol
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Machine Translation (MT) between the Thai and English languages has been a challenging research topic in natural language processing. Most research has been done on English to Thai machine translation, but not the other way around. This paper presents a Thai to English Machine Translation System that translates a Thai sentence into interlingua of a Thai LFG tree using LFG grammar and a bottom up parser. The Thai LFG tree is then transformed into the corresponding English LFG tree by pattern matching and node transformation. Finally, an equivalent English sentence is created using structural information prescribed by the English LFG tree. Based on results of experiments designed to evaluate the performance of the proposed system, it can be stated that the system has been proven to be effective in providing a useful translation from Thai to English.
Keywords: Interlingua, LFG grammar, Machine translation, Pattern matching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22951985 Neural Network Based Speech to Text in Malay Language
Authors: H. F. A. Abdul Ghani, R. R. Porle
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Speech to text in Malay language is a system that converts Malay speech into text. The Malay language recognition system is still limited, thus, this paper aims to investigate the performance of ten Malay words obtained from the online Malay news. The methodology consists of three stages, which are preprocessing, feature extraction, and speech classification. In preprocessing stage, the speech samples are filtered using pre emphasis. After that, feature extraction method is applied to the samples using Mel Frequency Cepstrum Coefficient (MFCC). Lastly, speech classification is performed using Feedforward Neural Network (FFNN). The accuracy of the classification is further investigated based on the hidden layer size. From experimentation, the classifier with 40 hidden neurons shows the highest classification rate which is 94%.
Keywords: Feed-Forward Neural Network, FFNN, Malay speech recognition, Mel Frequency Cepstrum Coefficient, MFCC, speech-to-text.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7461984 Development of a Computer Vision System for the Blind and Visually Impaired Person
Authors: Roselyn A. Maaño
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Eyes are an essential and conspicuous organ of the human body. Human eyes are outward and inward portals of the body that allows to see the outside world and provides glimpses into ones inner thoughts and feelings. Inevitable blindness and visual impairments may results from eye-related disease, trauma, or congenital or degenerative conditions that cannot be corrected by conventional means. The study emphasizes innovative tools that will serve as an aid to the blind and visually impaired (VI) individuals. The researchers fabricated a prototype that utilizes the Microsoft Kinect for Windows and Arduino microcontroller board. The prototype facilitates advanced gesture recognition, voice recognition, obstacle detection and indoor environment navigation. Open Computer Vision (OpenCV) performs image analysis, and gesture tracking to transform Kinect data to the desired output. A computer vision technology device provides greater accessibility for those with vision impairments.
Keywords: Algorithms, Blind, Computer Vision, Embedded Systems, Image Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36101983 A Novel Neighborhood Defined Feature Selection on Phase Congruency Images for Recognition of Faces with Extreme Variations
Authors: Satyanadh Gundimada, Vijayan K Asari
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A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.
Keywords: Discriminant analysis, intra-class probability distribution, principal component analysis, phase congruency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18501982 Earthquake Classification in Molluca Collision Zone Using Conventional Statistical Methods
Authors: H. J. Wattimanela, U. S. Passaribu, N. T. Puspito, S. W. Indratno
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Molluca Collision Zone is located at the junction of the Eurasian, Australian, Pacific and the Philippines plates. Between the Sangihe arc, west of the collision zone, and to the east of Halmahera arc is active collision and convex toward the Molluca Sea. This research will analyze the behavior of earthquake occurrence in Molluca Collision Zone related to the distributions of an earthquake in each partition regions, determining the type of distribution of a occurrence earthquake of partition regions, and the mean occurence of earthquakes each partition regions, and the correlation between the partitions region. We calculate number of earthquakes using partition method and its behavioral using conventional statistical methods. In this research, we used data of shallow earthquakes type and its magnitudes ≥4 SR (period 1964-2013). From the results, we can classify partitioned regions based on the correlation into two classes: strong and very strong. This classification can be used for early warning system in disaster management.
Keywords: Molluca Collision Zone, partition regions, conventional statistical methods, Earthquakes, classifications, disaster management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19821981 Annotations of Gene Pathways Images in Biomedical Publications Using Siamese Network
Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu
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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Manually annotating pathway diagrams is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.
Keywords: Biological pathway, gene identification, object detection, Siamese network, ResNet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2471980 A Robust Method for Hand Tracking Using Mean-shift Algorithm and Kalman Filter in Stereo Color Image Sequences
Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Robert Niese, Bernd Michaelis
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Real-time hand tracking is a challenging task in many computer vision applications such as gesture recognition. This paper proposes a robust method for hand tracking in a complex environment using Mean-shift analysis and Kalman filter in conjunction with 3D depth map. The depth information solve the overlapping problem between hands and face, which is obtained by passive stereo measuring based on cross correlation and the known calibration data of the cameras. Mean-shift analysis uses the gradient of Bhattacharyya coefficient as a similarity function to derive the candidate of the hand that is most similar to a given hand target model. And then, Kalman filter is used to estimate the position of the hand target. The results of hand tracking, tested on various video sequences, are robust to changes in shape as well as partial occlusion.Keywords: Computer Vision and Image Analysis, Object Tracking, Gesture Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29191979 Towards a Complete Automation Feature Recognition System for Sheet Metal Manufacturing
Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä
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Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.Keywords: Feature recognition, automation, sheet metal manufacturing, CAM, CAD.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11501978 The Content Based Objective Metrics for Video Quality Evaluation
Authors: Michal Mardiak, Jaroslav Polec
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In this paper we proposed comparison of four content based objective metrics with results of subjective tests from 80 video sequences. We also include two objective metrics VQM and SSIM to our comparison to serve as “reference” objective metrics because their pros and cons have already been published. Each of the video sequence was preprocessed by the region recognition algorithm and then the particular objective video quality metric were calculated i.e. mutual information, angular distance, moment of angle and normalized cross-correlation measure. The Pearson coefficient was calculated to express metrics relationship to accuracy of the model and the Spearman rank order correlation coefficient to represent the metrics relationship to monotonicity. The results show that model with the mutual information as objective metric provides best result and it is suitable for evaluating quality of video sequences.
Keywords: Objective quality metrics, mutual information, region recognition, content based metrics
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15061977 The Diet Adherence in Cardiovascular Disease Risk Factors Patients in the North of Iran Based on the Mediterranean Diet Adherence
Authors: Marjan Mahdavi-Roshan, Arsalan Salari, Mahboobeh Gholipour, Moona Naghshbandi
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Background and objectives: Before any nutritional intervention, it is necessary to have the prospect of eating habits of people with cardiovascular risk factors. In this study, we assessed the adherence of healthy diet based on Mediterranean dietary pattern and related factors in adults in the north of Iran. Methods: This study was conducted on 550 men and women with cardiovascular risk factors that referred to Heshmat hospital in Rasht, northern Iran. Information was collected by interview and reading medical history and measuring anthropometric indexes. The Mediterranean Diet Adherence Screener was used for assessing dietary adherence, this screener was modified according to religious beliefs and culture of Iran. Results: The mean age of participants was 58±0.38 years. The mean of body mass index was 27±0.01 kg/m2, and the mean of waist circumference was 98±0.2 cm. The mean of dietary adherence was 5.76±0.07. 45% of participants had low adherence, and just 4% had suitable adherence. The mean of dietary adherence in men was significantly higher than women (p=0. 07). Participants in rural area and high educational participants insignificantly had an unsuitable dietary Adherence. There was no significant association between some cardiovascular disease risk factors and dietary adherence. Conclusion: Education to different group about dietary intake correction and using a Mediterranean dietary pattern that is similar to dietary intake in the north of Iran, for controlling cardiovascular disease is necessary.
Keywords: Dietary adherence, Mediterranean dietary pattern, cardiovascular disease, north of Iran.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9891976 Preliminary Investigation on Combustion Characteristics of Rice Husk in FBC
Authors: W. Permchart, S. Tanatvanit
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The experimental results on combustion of rice husk in a conical fluidized bed combustor (referred to as the conical FBC) using silica sand as the bed material are presented in this paper. The effects of excess combustion air and combustor loading as well as the sand bed height on the combustion pattern in FBC were investigated. Temperatures and gas concentrations (CO and NO) along over the combustor height as well as in the flue gas downstream from the ash collecting cyclone were measured. The results showed that the axial temperature profiles in FBC were explicitly affected by the combustor loading whereas the excess air and bed height were found to have minor influences on the temperature pattern. Meanwhile, the combustor loading and the excess air significantly affected the axial CO and NO concentration profiles; however, these profiles were almost independent of the bed height. The combustion and thermal efficiencies for this FBC were quantified for different operating conditions.Keywords: Temperature, Combustor loading, Excess air, Bed height.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16311975 Scots Pine Needles as Bioindicators in Determining the Aerial Distribution Pattern of Sulphur Emissions around Industrial Plants
Authors: Risto Pöykiö, Jari Hietala, Hannu Nurmesniemi
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In this study, the Scots pine (Pinus sylvestris L.) C needles (i.e. the current-year-needles) were used as bioindicators in determining the aerial distribution pattern of sulphur emissions around industrial point sources at Kemi, Northern Finland. The average sulphur concentration in the C needles was 897 mg/kg (d.w.), with a standard deviation of 118 mg/kg (d.w.) and range 740 – 1350 mg/kg (d.w.). According to results in this study, Scots pine needles (Pinus sylvestris L.) appear to be an ideal bioindicators for identifying atmospheric sulphur pollution derived from industrial plants and can complement the information provided by plant mapping studies around industrial plants.Keywords: Emission, Sulphur, Scots Pine, Pinus sylvestris
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17461974 Customer Knowledge and Service Development, the Web 2.0 Role in Co-production
Authors: Roberto Boselli, Mirko Cesarini, Mario Mezzanzanica
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The paper is concerned with relationships between SSME and ICTs and focuses on the role of Web 2.0 tools in the service development process. The research presented aims at exploring how collaborative technologies can support and improve service processes, highlighting customer centrality and value coproduction. The core idea of the paper is the centrality of user participation and the collaborative technologies as enabling factors; Wikipedia is analyzed as an example. The result of such analysis is the identification and description of a pattern characterising specific services in which users collaborate by means of web tools with value co-producers during the service process. The pattern of collaborative co-production concerning several categories of services including knowledge based services is then discussed.Keywords: Service Interaction Patterns, Services Science, Web2.0 tools, Service Development Process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17271973 Detecting Circles in Image Using Statistical Image Analysis
Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee
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The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.Keywords: Image processing, median filter, projection, scalespace, segmentation, threshold.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18331972 Composite Kernels for Public Emotion Recognition from Twitter
Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang
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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.
Keywords: Public emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7731971 Monitoring CO2 and H2S Emission in Live Austrian and UK Concrete Sewer Pipes
Authors: Anna Romanova, Morteza A. Alani
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Corrosion of concrete sewer pipes induced by sulfuric acid is an acknowledged problem and a ticking time-bomb to sewer operators. Whilst the chemical reaction of the corrosion process is well-understood, the indirect roles of other parameters in the corrosion process which are found in sewer environment are not highly reflected on. This paper reports on a field studies undertaken in Austria and United Kingdom, where the parameters of temperature, pH, H2S and CO2 were monitored over a period of time. The study establishes that (i) effluent temperature and pH have similar daily pattern and peak times, when examined in minutes scale; (ii) H2S and CO2 have an identical hourly pattern; (iii) H2S instant or shifted relation to effluent temperature is governed by the root mean square value of CO2.
Keywords: Concrete corrosion, carbon dioxide, hydrogen sulphide, sewer pipe, sulfuric acid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21201970 Data Oriented Modeling of Uniform Random Variable: Applied Approach
Authors: Ahmad Habibizad Navin, Mehdi Naghian Fesharaki, Mirkamal Mirnia, Mohamad Teshnelab, Ehsan Shahamatnia
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In this paper we introduce new data oriented modeling of uniform random variable well-matched with computing systems. Due to this conformity with current computers structure, this modeling will be efficiently used in statistical inference.Keywords: Uniform random variable, Data oriented modeling, Statistical inference, Prodigraph, Statistically complete tree, Uniformdigital probability digraph, Uniform n-complete probability tree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16311969 Dispersion Rate of Spilled Oil in Water Column under Non-Breaking Water Waves
Authors: Hanifeh Imanian, Morteza Kolahdoozan
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The purpose of this study is to present a mathematical phrase for calculating the dispersion rate of spilled oil in water column under non-breaking waves. In this regard, a multiphase numerical model is applied for which waves and oil phase were computed concurrently, and accuracy of its hydraulic calculations have been proven. More than 200 various scenarios of oil spilling in wave waters were simulated using the multiphase numerical model and its outcome were collected in a database. The recorded results were investigated to identify the major parameters affected vertical oil dispersion and finally 6 parameters were identified as main independent factors. Furthermore, some statistical tests were conducted to identify any relationship between the dependent variable (dispersed oil mass in the water column) and independent variables (water wave specifications containing height, length and wave period and spilled oil characteristics including density, viscosity and spilled oil mass). Finally, a mathematical-statistical relationship is proposed to predict dispersed oil in marine waters. To verify the proposed relationship, a laboratory example available in the literature was selected. Oil mass rate penetrated in water body computed by statistical regression was in accordance with experimental data was predicted. On this occasion, it was necessary to verify the proposed mathematical phrase. In a selected laboratory case available in the literature, mass oil rate penetrated in water body computed by suggested regression. Results showed good agreement with experimental data. The validated mathematical-statistical phrase is a useful tool for oil dispersion prediction in oil spill events in marine areas.Keywords: Dispersion, marine environment, mathematical-statistical relationship, oil spill.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11461968 Enhancing Human-Computer Interaction and Feedback in Touchscreen Icon
Authors: Hsinfu Huang Li-Hao Chen
Abstract:
In order to enhance the usability of the human computer interface (HCI) on the touchscreen, this study explored the optimal tactile depth and effect of visual cues on the user-s tendency to touch the touchscreen icons. The experimental program was designed on the touchscreen in this study. Results indicated that the ratio of the icon size to the tactile depth was 1:0.106. There were significant effects of experienced users and novices on the tactile feedback depth (p < 0.01). In addition, the results proved that the visual cues provided a feedback that helped to guide the user-s touch icons accurately and increased the capture efficiency for a tactile recognition field. This tactile recognition field was 18.6 mm in length. There was consistency between the experienced users and novices under the visual cue effects. Finally, the study developed an applied design with touch feedback for touchscreen icons.
Keywords: HCI, Touchscreen icon, Touch feedback, Optimaltactile depth, Visual cues.
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