Search results for: Run Length features
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2448

Search results for: Run Length features

2328 Assessment of In-Situ Water Sensitive Urban Design Elements

Authors: Niranjali Jayasuirya, Majell Backhausen

Abstract:

Water Sensitive Urban Design (WSUD) features are increasingly used to treat and manage polluted stormwater runoff in urbanised areas. It is important to monitor and evaluate the effectiveness of the infrastructure in achieving their intended performance targets after constructing and operating these features overtime. The paper presents the various methods of analysis used to assess the effectiveness of the in-situ WSUD features, such as: onsite visual inspections during operational and non operational periods, maintenance audits and periodic water quality testing. The results will contribute to a better understanding of the operational and maintenance needs of in-situ WSUD features and assist in providing recommendations to better manage life cycle performance.

Keywords: Bio-retention swales, Maintenance plan, Operational plan, Water Sensitive Urban Design, Water quality improvement.

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2327 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

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2326 A Remote Sensing Approach to Calculate Population Using Roads Network Data in Lebanon

Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Chehayeb, Nada Badaro Saliba

Abstract:

In developing countries, such as Lebanon, the demographic data are hardly available due to the absence of the mechanization of population system. The aim of this study is to evaluate, using only remote sensing data, the correlations between the number of population and the characteristics of roads network (length of primary roads, length of secondary roads, total length of roads, density and percentage of roads and the number of intersections). In order to find the influence of the different factors on the demographic data, we studied the degree of correlation between each factor and the number of population. The results of this study have shown a strong correlation between the number of population and the density of roads and the number of intersections.

Keywords: Population, road network, statistical correlations, remote sensing.

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2325 Classification of Political Affiliations by Reduced Number of Features

Authors: Vesile Evrim, Aliyu Awwal

Abstract:

By the evolvement in technology, the way of expressing opinions switched direction to the digital world. The domain of politics, as one of the hottest topics of opinion mining research, merged together with the behavior analysis for affiliation determination in texts, which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 were constituted by Linguistic Inquiry and Word Count (LIWC) features were tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that the “Decision Tree”, “Rule Induction” and “M5 Rule” classifiers when used with “SVM” and “IGR” feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “Function”, as an aggregate feature of the linguistic category, was found as the most differentiating feature among the 68 features with the accuracy of 81% in classifying articles either as Republican or Democrat.

Keywords: Politics, machine learning, feature selection, LIWC.

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2324 Indoor Mobile Robot Positioning Based on Wireless Fingerprint Matching

Authors: Xu Huang, Jing Fan, Maonian Wu, Yonggen Gu

Abstract:

This paper discusses the design of an indoor mobile robot positioning system. The problem of indoor positioning is solved through Wi-Fi fingerprint positioning to implement a low cost deployment. A wireless fingerprint matching algorithm based on the similarity of unequal length sequences is presented. Candidate sequences selection is defined as a set of mappings, and detection errors caused by wireless hotspot stability and the change of interior pattern can be corrected by transforming the unequal length sequences into equal length sequences. The presented scheme was verified experimentally to achieve the accuracy requirements for an indoor positioning system with low deployment cost.

Keywords: Fingerprint match, indoor positioning, mobile robot positioning system, Wi-Fi, wireless fingerprint.

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2323 Study on the Effect of Road Infrastructure, Socio-Economic and Demographic Features on Road Crashes in Bangladesh

Authors: Shakil M. Rifaat, Md. H. Rahman, Mohammed, Mosabbir Pasha

Abstract:

Road crashes not only claim lives and inflict injuries but also create economic burden to the society due to loss of productivity. The problem of deaths and injuries as a result of road traffic crashes is now acknowledged to be a global phenomenon with authorities in virtually all countries of the world concerned about the growth in the number of people killed and seriously injured on their roads. However, the road crash scenario of a developing country like Bangladesh is much worse comparing with this of developed countries. For developing proper countermeasures it is necessary to identify the factors affecting crash occurrences. The objectives of the study is to examine the effect of district wise road infrastructure, socioeconomic and demographic features on crash occurrence .The unit of analysis will be taken as individual district which has not been explored much in the past. Reported crash data obtained from Bangladesh Road Transport Authority (BRTA) from the year 2004 to 2010 are utilized to develop negative binomial model. The model result will reveal the effect of road length (both paved and unpaved), road infrastructure and several socio economic characteristics on district level crash frequency in Bangladesh.

Keywords: Demographic, Negative Binomial Model, Road Infrastructure, Socio-economic, Traffic Safety.

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2322 Human Verification in a Video Surveillance System Using Statistical Features

Authors: Sanpachai Huvanandana

Abstract:

A human verification system is presented in this paper. The system consists of several steps: background subtraction, thresholding, line connection, region growing, morphlogy, star skelatonization, feature extraction, feature matching, and decision making. The proposed system combines an advantage of star skeletonization and simple statistic features. A correlation matching and probability voting have been used for verification, followed by a logical operation in a decision making stage. The proposed system uses small number of features and the system reliability is convincing.

Keywords: Human verification, object recognition, videounderstanding, segmentation.

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2321 A New Internal Architecture Based on Feature Selection for Holonic Manufacturing System

Authors: Jihan Abdulazeez Ahmed, Adnan Mohsin Abdulazeez Brifcani

Abstract:

This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine dataset, the statistical result proves that the proposed system is effective and has the ability to choose informative features with high accuracy.

Keywords: Artificial Neural Networks, Holonic Approach, Feature Selection, Bee Algorithm.

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2320 Experimental Investigation and Sensitivity Analysis for the Effects of Fracture Parameters to the Conductance Properties of Laterite

Authors: Bai Wei, Kong Ling-Wei, Guo Ai-Guo

Abstract:

This experiment discusses the effects of fracture parameters such as depth, length, width, angle and the number of the fracture to the conductance properties of laterite using the DUK-2B digital electrical measurement system combined with the method of simulating the fractures. The results of experiment show that the changes of fracture parameters produce effects to the conductance properties of laterite. There is a clear degressive period of the conductivity of laterite during increasing the depth, length, width, or the angle and the quantity of fracture gradually. When the depth of fracture exceeds the half thickness of the soil body, the conductivity of laterite shows evidently non-linear diminishing pattern and the amplitude of decrease tends to increase. The length of fracture has fewer effects than the depth to the conductivity. When the width of fracture reaches some fixed values, the change of the conductivity is less sensitive to the change of the width, and at this time, the conductivity of laterite maintains at a stable level. When the angle of fracture is less than 45°, the decrease of the conductivity is more clearly as the angle increases. But when angle is more than 45°, change of the conductivity is relatively gentle as the angle increases. The increasing quantity of the fracture causes the other fracture parameters having great impact on the change of conductivity. When moisture content and temperature were unchanged, depth and angle of fractures are the major factors affecting the conductivity of laterite soil; quantity, length, and width are minor influencing factors. The sensitivity of fracture parameters affect conductivity of laterite soil is: depth >angles >quantity >length >width.

Keywords: laterite, fracture parameters, conductance properties, conductivity, uniform design, sensitivity analysis

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2319 Multi-algorithmic Iris Authentication System

Authors: Hunny Mehrotra, Banshidhar Majhi, Phalguni Gupta

Abstract:

The paper proposes a novel technique for iris recognition using texture and phase features. Texture features are extracted on the normalized iris strip using Haar Wavelet while phase features are obtained using LOG Gabor Wavelet. The matching scores generated from individual modules are combined using sum of score technique. The system is tested on database obtained from Bath University and Indian Institute of Technology Kanpur and is giving an accuracy of 95.62% and 97.66% respectively. The FAR and FRR of the combined system is also reduced comparatively.

Keywords: Fusion, Haar Wavelet, Iris, LOG Gabor Wavelet, Phase, Texture.

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2318 Dynamic TDMA Slot Reservation Protocol for QoS Provisioning in Cognitive Radio Ad Hoc Networks

Authors: S. M. Kamruzzaman

Abstract:

In this paper, we propose a dynamic TDMA slot reservation (DTSR) protocol for cognitive radio ad hoc networks. Quality of Service (QoS) guarantee plays a critically important role in such networks. We consider the problem of providing QoS guarantee to users as well as to maintain the most efficient use of scarce bandwidth resources. According to one hop neighboring information and the bandwidth requirement, our proposed protocol dynamically changes the frame length and the transmission schedule. A dynamic frame length expansion and shrinking scheme that controls the excessive increase of unassigned slots has been proposed. This method efficiently utilizes the channel bandwidth by assigning unused slots to new neighboring nodes and increasing the frame length when the number of slots in the frame is insufficient to support the neighboring nodes. It also shrinks the frame length when half of the slots in the frame of a node are empty. An efficient slot reservation protocol not only guarantees successful data transmissions without collisions but also enhance channel spatial reuse to maximize the system throughput. Our proposed scheme, which provides both QoS guarantee and efficient resource utilization, be employed to optimize the channel spatial reuse and maximize the system throughput. Extensive simulation results show that the proposed mechanism achieves desirable performance in multichannel multi-rate cognitive radio ad hoc networks.

Keywords: TDMA, cognitive radio, ad hoc networks, QoSguarantee, dynamic frame length.

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2317 Identification of Printed Punjabi Words and English Numerals Using Gabor Features

Authors: Rajneesh Rani, Renu Dhir, G. S. Lehal

Abstract:

Script identification is one of the challenging steps in the development of optical character recognition system for bilingual or multilingual documents. In this paper an attempt is made for identification of English numerals at word level from Punjabi documents by using Gabor features. The support vector machine (SVM) classifier with five fold cross validation is used to classify the word images. The results obtained are quite encouraging. Average accuracy with RBF kernel, Polynomial and Linear Kernel functions comes out to be greater than 99%.

Keywords: Script identification, gabor features, support vector machines.

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2316 Fuzzy Inference System Based Unhealthy Region Classification in Plant Leaf Image

Authors: K. Muthukannan, P. Latha

Abstract:

In addition to environmental parameters like rain, temperature diseases on crop is a major factor which affects production quality & quantity of crop yield. Hence disease management is a key issue in agriculture. For the management of disease, it needs to be detected at early stage. So, treat it properly & control spread of the disease. Now a day, it is possible to use the images of diseased leaf to detect the type of disease by using image processing techniques. This can be achieved by extracting features from the images which can be further used with classification algorithms or content based image retrieval systems. In this paper, color image is used to extract the features such as mean and standard deviation after the process of region cropping. The selected features are taken from the cropped image with different image size samples. Then, the extracted features are taken in to the account for classification using Fuzzy Inference System (FIS).

Keywords: Image Cropping, Classification, Color, Fuzzy Rule, Feature Extraction.

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2315 Quantifying the Sustainable Building Criteria Based on Case Studies from Malaysia

Authors: Fahanim Abdul Rashid, Muhammad Azzam Ismail, Deo Prasad

Abstract:

In order to encourage the construction of green homes (GH) in Malaysia, a simple and attainable framework for designing and building GHs is needed. This can be achieved by aligning GH principles against Cole-s 'Sustainable Building Criteria' (SBC). This set of considerations was used to categorize the GH features of three case studies from Malaysia. Although the categorization of building features is useful at exploring the presence of sustainability inclinations of each house, the overall impact of building features in each of the five SBCs are unknown. Therefore, this paper explored the possibility of quantifying the impact of building features categorized in SBC1 – “Buildings will have to adapt to the new environment and restore damaged ecology while mitigating resource use" based on existing GH assessment tools and methods and other literature. This process as reported in this paper could lead to a new dimension in green home rating and assessment methods.

Keywords: Green homes, Malaysia, Sustainable BuildingCriteria, Sustainable homes

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2314 Fast Facial Feature Extraction and Matching with Artificial Face Models

Authors: Y. H. Tsai, Y. W. Chen

Abstract:

Facial features are frequently used to represent local properties of a human face image in computer vision applications. In this paper, we present a fast algorithm that can extract the facial features online such that they can give a satisfying representation of a face image. It includes one step for a coarse detection of each facial feature by AdaBoost and another one to increase the accuracy of the found points by Active Shape Models (ASM) in the regions of interest. The resulted facial features are evaluated by matching with artificial face models in the applications of physiognomy. The distance measure between the features and those in the fate models from the database is carried out by means of the Hausdorff distance. In the experiment, the proposed method shows the efficient performance in facial feature extractions and online system of physiognomy.

Keywords: Facial feature extraction, AdaBoost, Active shapemodel, Hausdorff distance

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2313 Fused Structure and Texture (FST) Features for Improved Pedestrian Detection

Authors: Hussin K. Ragb, Vijayan K. Asari

Abstract:

In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: Pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor.

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2312 Effect of Different Salt Concentrations and Temperatures on Seed Germination and Seedling Characters in Safflower (Carthamus tinctorius L.) Genotypes

Authors: Rahim Ada, Zamari Temory, Hasan Dalgiç

Abstract:

Germination and seedling responses of seven safflower seed genotypes (Dinçer, Remzibey, Black Sun2 cultivars and A19, F4, I1, J19 lines) to different salinity concentrations (0, 5, 10 and 20g l-1) and temperatures (10 and 20oC) evaluated in Completely Randomized Factorial Designs in Department of Field Crops of Selcuk University, Konya, Turkey. Seeds in the control (distilled water) had at 10 and 20oC the highest germination percentage (93.88 and 94.32%), shoot length (4.60 and 8.72cm) and root length (4.27 and 6.54cm) shoot dry weight (22.37mg and 25.99mg) and root dry weight (2.22 and 2.47mg). As the salt concentration increased, values of all characters were decreased. In this experiment, in 20g l-1 salt concentration found germination percentage (21.28 and 26.66%), shoot (1.32 and 1.35cm) and root length (1.04 and 1.10cm) shoot (8.05mg and 7.49mg) and root dry weight (0.83 and 0.98mg) at 10 and 20oC.

Keywords: NaCl, Safflower, Temperature.

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2311 Fusion of Finger Inner Knuckle Print and Hand Geometry Features to Enhance the Performance of Biometric Verification System

Authors: M. L. Anitha, K. A. Radhakrishna Rao

Abstract:

With the advent of modern computing technology, there is an increased demand for developing recognition systems that have the capability of verifying the identity of individuals. Recognition systems are required by several civilian and commercial applications for providing access to secured resources. Traditional recognition systems which are based on physical identities are not sufficiently reliable to satisfy the security requirements due to the use of several advances of forgery and identity impersonation methods. Recognizing individuals based on his/her unique physiological characteristics known as biometric traits is a reliable technique, since these traits are not transferable and they cannot be stolen or lost. Since the performance of biometric based recognition system depends on the particular trait that is utilized, the present work proposes a fusion approach which combines Inner knuckle print (IKP) trait of the middle, ring and index fingers with the geometrical features of hand. The hand image captured from a digital camera is preprocessed to find finger IKP as region of interest (ROI) and hand geometry features. Geometrical features are represented as the distances between different key points and IKP features are extracted by applying local binary pattern descriptor on the IKP ROI. The decision level AND fusion was adopted, which has shown improvement in performance of the combined scheme. The proposed approach is tested on the database collected at our institute. Proposed approach is of significance since both hand geometry and IKP features can be extracted from the palm region of the hand. The fusion of these features yields a false acceptance rate of 0.75%, false rejection rate of 0.86% for verification tests conducted, which is less when compared to the results obtained using individual traits. The results obtained confirm the usefulness of proposed approach and suitability of the selected features for developing biometric based recognition system based on features from palmar region of hand.

Keywords: Biometrics, hand geometry features, inner knuckle print, recognition.

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2310 Roll of Membership functions in Fuzzy Logic for Prediction of Shoot Length of Mustard Plant Based on Residual Analysis

Authors: Satyendra Nath Mandal, J. Pal Choudhury, Dilip De, S. R. Bhadra Chaudhuri

Abstract:

The selection for plantation of a particular type of mustard plant depending on its productivity (pod yield) at the stage of maturity. The growth of mustard plant dependent on some parameters of that plant, these are shoot length, number of leaves, number of roots and roots length etc. As the plant is growing, some leaves may be fall down and some new leaves may come, so it can not gives the idea to develop the relationship with the seeds weight at mature stage of that plant. It is not possible to find the number of roots and root length of mustard plant at growing stage that will be harmful of this plant as roots goes deeper to deeper inside the land. Only the value of shoot length which increases in course of time can be measured at different time instances. Weather parameters are maximum and minimum humidity, rain fall, maximum and minimum temperature may effect the growth of the plant. The parameters of pollution, water, soil, distance and crop management may be dominant factors of growth of plant and its productivity. Considering all parameters, the growth of the plant is very uncertain, fuzzy environment can be considered for the prediction of shoot length at maturity of the plant. Fuzzification plays a greater role for fuzzification of data, which is based on certain membership functions. Here an effort has been made to fuzzify the original data based on gaussian function, triangular function, s-function, Trapezoidal and L –function. After that all fuzzified data are defuzzified to get normal form. Finally the error analysis (calculation of forecasting error and average error) indicates the membership function appropriate for fuzzification of data and use to predict the shoot length at maturity. The result is also verified using residual (Absolute Residual, Maximum of Absolute Residual, Mean Absolute Residual, Mean of Mean Absolute Residual, Median of Absolute Residual and Standard Deviation) analysis.

Keywords: Fuzzification, defuzzification, gaussian function, triangular function, trapezoidal function, s-function, , membership function, residual analysis.

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2309 Iris Recognition Based On the Low Order Norms of Gradient Components

Authors: Iman A. Saad, Loay E. George

Abstract:

Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: Iris recognition, contrast stretching, gradient features, texture features, Euclidean metric.

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2308 Leveraging Quality Metrics in Voting Model Based Thread Retrieval

Authors: Atefeh Heydari, Mohammadali Tavakoli, Zuriati Ismail, Naomie Salim

Abstract:

Seeking and sharing knowledge on online forums have made them popular in recent years. Although online forums are valuable sources of information, due to variety of sources of messages, retrieving reliable threads with high quality content is an issue. Majority of the existing information retrieval systems ignore the quality of retrieved documents, particularly, in the field of thread retrieval. In this research, we present an approach that employs various quality features in order to investigate the quality of retrieved threads. Different aspects of content quality, including completeness, comprehensiveness, and politeness, are assessed using these features, which lead to finding not only textual, but also conceptual relevant threads for a user query within a forum. To analyse the influence of the features, we used an adopted version of voting model thread search as a retrieval system. We equipped it with each feature solely and also various combinations of features in turn during multiple runs. The results show that incorporating the quality features enhances the effectiveness of the utilised retrieval system significantly.

Keywords: Content quality, Forum search, Thread retrieval, Voting techniques.

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2307 Property Aggregation and Uncertainty with Links to the Management and Determination of Critical Design Features

Authors: Steven Whittle, Ingrida Valiusaityte

Abstract:

Within the domain of Systems Engineering the need to perform property aggregation to understand, analyze and manage complex systems is unequivocal. This can be seen in numerous domains such as capability analysis, Mission Essential Competencies (MEC) and Critical Design Features (CDF). Furthermore, the need to consider uncertainty propagation as well as the sensitivity of related properties within such analysis is equally as important when determining a set of critical properties within such a system. This paper describes this property breakdown in a number of domains within Systems Engineering and, within the area of CDFs, emphasizes the importance of uncertainty analysis. As part of this, a section of the paper describes possible techniques which may be used within uncertainty propagation and in conclusion an example is described utilizing one of the techniques for property and uncertainty aggregation within an aircraft system to aid the determination of Critical Design Features.

Keywords: Complex Systems, Critical Design Features, Property Aggregation, Uncertainty.

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2306 Study of Features for Hand-printed Recognition

Authors: Satish Kumar

Abstract:

The feature extraction method(s) used to recognize hand-printed characters play an important role in ICR applications. In order to achieve high recognition rate for a recognition system, the choice of a feature that suits for the given script is certainly an important task. Even if a new feature required to be designed for a given script, it is essential to know the recognition ability of the existing features for that script. Devanagari script is being used in various Indian languages besides Hindi the mother tongue of majority of Indians. This research examines a variety of feature extraction approaches, which have been used in various ICR/OCR applications, in context to Devanagari hand-printed script. The study is conducted theoretically and experimentally on more that 10 feature extraction methods. The various feature extraction methods have been evaluated on Devanagari hand-printed database comprising more than 25000 characters belonging to 43 alphabets. The recognition ability of the features have been evaluated using three classifiers i.e. k-NN, MLP and SVM.

Keywords: Features, Hand-printed, Devanagari, Classifier, Database

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2305 Automatic Feature Recognition for GPR Image Processing

Authors: Yi-an Cui, Lu Wang, Jian-ping Xiao

Abstract:

This paper presents an automatic feature recognition method based on center-surround difference detecting and fuzzy logic that can be applied in ground-penetrating radar (GPR) image processing. Adopted center-surround difference method, the salient local image regions are extracted from the GPR images as features of detected objects. And fuzzy logic strategy is used to match the detected features and features in template database. This way, the problem of objects detecting, which is the key problem in GPR image processing, can be converted into two steps, feature extracting and matching. The contributions of these skills make the system have the ability to deal with changes in scale, antenna and noises. The results of experiments also prove that the system has higher ratio of features sensing in using GPR to image the subsurface structures.

Keywords: feature recognition, GPR image, matching strategy, salient image

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2304 On Pseudo-Random and Orthogonal Binary Spreading Sequences

Authors: Abhijit Mitra

Abstract:

Different pseudo-random or pseudo-noise (PN) as well as orthogonal sequences that can be used as spreading codes for code division multiple access (CDMA) cellular networks or can be used for encrypting speech signals to reduce the residual intelligence are investigated. We briefly review the theoretical background for direct sequence CDMA systems and describe the main characteristics of the maximal length, Gold, Barker, and Kasami sequences. We also discuss about variable- and fixed-length orthogonal codes like Walsh- Hadamard codes. The equivalence of PN and orthogonal codes are also derived. Finally, a new PN sequence is proposed which is shown to have certain better properties than the existing codes.

Keywords: Code division multiple access, pseudo-noise codes, maximal length, Gold, Barker, Kasami, Walsh-Hadamard, autocorrelation, crosscorrelation, figure of merit.

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2303 Optimization of Partially Filled Column Subjected to Oblique Loading

Authors: M. S. Salwani, B. B. Sahari, Aidy Ali, A. A. Nuraini

Abstract:

In this study, optimization is carried out to find the optimized design of a foam-filled column for the best Specific Energy Absorption (SEA) and Crush Force Efficiency (CFE). In order to maximize SEA, the optimization gives the value of 2.3 for column thickness and 151.7 for foam length. On the other hand to maximize CFE, the optimization gives the value of 1.1 for column thickness and 200 for foam length. Finite Element simulation is run by using this value and the SEA and CFE obtained 1237.76 J/kg and 0.92.

Keywords: Crash, foam, oblique loading.

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2302 Elastic Strain-Concentration Factor of Cylindrical Bars with Circumferential Flat-Bottom Groove under Static Tension

Authors: Hitham M. Tlilan

Abstract:

Using finite element method (FEM), the elastic new strain-concentration factor (SNCF) of cylindrical bars with circumferential flat-bottom groove is studied. This new SNCF has been defined under triaxial stress state. The employed specimens have constant groove depth with net section and gross diameters of 10.0 and 16.7 mm, respectively. The length of flatness ao has been varied form 0.0 ~12.5 mm to study the elastic SNCF of this type of geometrical irregularities. The results that the elastic new SNCF rapidly drops from its elastic value of the groove with ao = 0.0, i.e. circumferential U-notch, and reaches minimum value at ao = 2 mm. After that the elastic new SNCF becomes nearly constant with increasing flatness length (ao). The value of tensile load at yielding at the groove root increases with increasing ao. The current results show that severity of the notch decreases with increasing flatness length ao.

Keywords: Bar, groove, strain, tension

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2301 Robot Vision Application based on Complex 3D Pose Computation

Authors: F. Rotaru, S. Bejinariu, C. D. Niţâ, R. Luca, I. Pâvâloi, C. Lazâr

Abstract:

The paper presents a technique suitable in robot vision applications where it is not possible to establish the object position from one view. Usually, one view pose calculation methods are based on the correspondence of image features established at a training step and exactly the same image features extracted at the execution step, for a different object pose. When such a correspondence is not feasible because of the lack of specific features a new method is proposed. In the first step the method computes from two views the 3D pose of feature points. Subsequently, using a registration algorithm, the set of 3D feature points extracted at the execution phase is aligned with the set of 3D feature points extracted at the training phase. The result is a Euclidean transform which have to be used by robot head for reorientation at execution step.

Keywords: features correspondence, registration algorithm, robot vision, triangulation method.

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2300 Parallel Discrete Fourier Transform for Fast FIR Filtering Based on Overlapped-save Block Structure

Authors: Ying-Wen Bai, Ju-Maw Chen

Abstract:

To successfully provide a fast FIR filter with FTT algorithms, overlapped-save algorithms can be used to lower the computational complexity and achieve the desired real-time processing. As the length of the input block increases in order to improve the efficiency, a larger volume of zero padding will greatly increase the computation length of the FFT. In this paper, we use the overlapped block digital filtering to construct a parallel structure. As long as the down-sampling (or up-sampling) factor is an exact multiple lengths of the impulse response of a FIR filter, we can process the input block by using a parallel structure and thus achieve a low-complex fast FIR filter with overlapped-save algorithms. With a long filter length, the performance and the throughput of the digital filtering system will also be greatly enhanced.

Keywords: FIR Filter, Overlapped-save Algorithm, ParallelStructure

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2299 Harmonic Parameters with HHT and Wavelet Transform for Automatic Sleep Stages Scoring

Authors: Wei-Chih Tang, Shih-Wei Lu, Chih-Mong Tsai, Cheng-Yan Kao, Hsiu-Hui Lee

Abstract:

Previously, harmonic parameters (HPs) have been selected as features extracted from EEG signals for automatic sleep scoring. However, in previous studies, only one HP parameter was used, which were directly extracted from the whole epoch of EEG signal. In this study, two different transformations were applied to extract HPs from EEG signals: Hilbert-Huang transform (HHT) and wavelet transform (WT). EEG signals are decomposed by the two transformations; and features were extracted from different components. Twelve parameters (four sets of HPs) were extracted. Some of the parameters are highly diverse among different stages. Afterward, HPs from two transformations were used to building a rough sleep stages scoring model using the classifier SVM. The performance of this model is about 78% using the features obtained by our proposed extractions. Our results suggest that these features may be useful for automatic sleep stages scoring.

Keywords: EEG, harmonic parameter, Hilbert-Huang transform, sleep stages, wavelet transform.

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