Search results for: 1−skeleton. A. M. S.Classification:[2000] 18D35

Authors: Ahmad Attiq Al-Ogaibi, Ahmad Sharieh, Moh’d Belal Al-Zoubi, R. Bremananth

Abstract:

In pattern clustering, nearest neighborhood point computation is a challenging issue for many applications in the area of research such as Remote Sensing, Computer Vision, Pattern Recognition and Statistical Imaging. Nearest neighborhood computation is an essential computation for providing sufficient classification among the volume of pixels (voxels) in order to localize the active-region-of-interests (AROI). Furthermore, it is needed to compute spatial metric relationships of diverse area of imaging based on the applications of pattern recognition. In this paper, we propose a new methodology for finding the nearest neighbor point, depending on making a virtually grid of a hexagon cells, then locate every point beneath them. An algorithm is suggested for minimizing the computation and increasing the turnaround time of the process. The nearest neighbor query points Φ are fetched by seeking fashion of hexagon holistic. Seeking will be repeated until an AROI Φ is to be expected. If any point Υ is located then searching starts in the nearest hexagons in a circular way. The First hexagon is considered be level 0 (L0) and the surrounded hexagons is level 1 (L1). If Υ is located in L1, then search starts in the next level (L2) to ensure that Υ is the nearest neighbor for Φ. Based on the result and experimental results, we found that the proposed method has an advantage over the traditional methods in terms of minimizing the time complexity required for searching the neighbors, in turn, efficiency of classification will be improved sufficiently.

Keywords: Hexagon cells, k-nearest neighbors, Nearest Neighbor, Pattern recognition, Query pattern, Virtually grid

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Authors: Amina Amirat, Abdelfettah Bouri

Abstract:

If price and quantity are the fundamental building blocks of any theory of market interactions, the importance of trading volume in understanding the behavior of financial markets is clear. However, while many economic models of financial markets have been developed to explain the behavior of prices -predictability, variability, and information content- far less attention has been devoted to explaining the behavior of trading volume. In this article, we hope to expand our understanding of trading volume by developing a new measure of herding behavior based on a cross sectional dispersion of volumes betas. We apply our measure to the Toronto stock exchange using monthly data from January 2000 to December 2002. Our findings show that the herd phenomenon consists of three essential components: stationary herding, intentional herding and the feedback herding.

Keywords: Herding behavior, market return, trading volume.

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Authors: Ah-young Jeon, In-cheol Kim, Jae-hee Jung, Soo-young Ye, Jae-hyung Kim, Ki-gon Nam, Seoung-wan Baik, Jung-hoon Ro, Gye-rok Jeon

Abstract:

The aged are faced with increasing risk for falls. The aged have the easily fragile bones than others. When falls have occurred, it is important to detect this emergency state because such events often lead to more serious illness or even death. A implementation of PDA system, for detection of emergency situation, was developed using 3-axis accelerometer in this paper as follows. The signals were acquired from the 3-axis accelerometer, and then transmitted to the PDA through Bluetooth module. This system can classify the human activity, and also detect the emergency state like falls. When the fall occurs, the system generates the alarm on the PDA. If a subject does not respond to the alarm, the system determines whether the current situation is an emergency state or not, and then sends some information to the emergency center in the case of urgent situation. Three different studies were conducted on 12 experimental subjects, with results indicating a good accuracy. The first study was performed to detect the posture change of human daily activity. The second study was performed to detect the correct direction of fall. The third study was conducted to check the classification of the daily physical activity. Each test was lasted at least 1 min. in third study. The output of acceleration signal was compared and evaluated by changing a various posture after attaching a 3-axis accelerometer module on the chest. The newly developed system has some important features such as portability, convenience and low cost. One of the main advantages of this system is that it is available at home healthcare environment. Another important feature lies in low cost to manufacture device. The implemented system can detect the fall accurately, so will be widely used in emergency situation.

Keywords: Alarm System, Ambulatory monitoring, Emergency detection, Classification of activity, and 3-axis accelerometer.

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Authors: B. Golchin, N. Riahi

Abstract:

One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: T. Balasubramanian, A. Pandiarani

Abstract:

In this paper we introduce some subspaces of fuzzy entire sequence space. Some general properties of these sequence spaces are discussed. Also some inclusion relation involving the spaces are obtained. Mathematics Subject Classification: 40A05, 40D25.

Keywords: Fuzzy Numbers, Entire sequences, completeness, Fuzzy entire sequences

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Authors: Yepeng Cheng, Yasuhiko Morimoto

Abstract:

Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.

Keywords: Customer value, Huff's Gravity Model, POS, retailer.

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Authors: Xun Ge, Jianhua Gong

Abstract:

 

ankings for output of Chinese main agricultural commodity in the world for 1978, 1980, 1990, 2000, 2006, 2007 and 2008 have been released in United Nations FAO Database. Unfortunately, where the ranking of output of Chinese cotton lint in the world for 2008 was missed. This paper uses sequential data mining methods with decision rules filling this gap. This new data mining method will be help to give a further improvement for United Nations FAO Database.

Keywords: Ranking, output of the main agricultural commodity, gross domestic product, decision table, information system, data mining, decision rule

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Authors: Vladimir I. Byshev, Victor G. Neiman, Yuri A. Romanov, Ilya V. Serykh

Abstract:

Since atmosphere pressure field is an actual envoy of climatic signal the atmospheric Highs and Lows should be attributed to the key active focal points within the ocean-atmosphere interplay system. Here we were set a task to determine how the dynamics of those centres of action relates to the climate change both on regional and global scales. For this target the near-surface temperature and atmospheric pressure differences between the Icelandic Low and the Azores High were considered. The secular term of phase states of the system under consideration was found divided into three nonintersecting subsets. Each of that was put in consequence with one of three climatic scenarios related to the periods of 1905-1935 (relatively warm phase), 1940-1970 (cold phase) and 1980-2000 (warm phase).

Keywords: Climate change, climatic scenario, fields of environmental characteristics, North Atlantic region.

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Authors: M. A. Fodha, H. Benfradj, A. Ghazel

Abstract:

This paper is a survey of recent works that proposes a baseband processor architecture for software defined radio. A classification of different approaches is proposed. The performance of each architecture is also discussed in order to clarify the suitable approaches that meet software-defined radio constraints.

Keywords: Multi-core architectures, reconfigurable architecture, software defined radio.

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Authors: Şahin Emrah Amrahov, Fatih Aybar, Serhat Doğan

Abstract:

In this paper we consider the rule reduct generation problem. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms, that are used to solve this problem, are well-known. Alternative to these algorithms, we develop Pruning Rule Generation (PRG) algorithm. We compare the PRG algorithm with RG and MRG.

Keywords: Rough sets, Decision rules, Rule induction, Classification.

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Authors: Alexei M. Mikhailov

Abstract:

The paper discusses the mathematics of pattern indexing and its applications to recognition of visual patterns that are found in video clips. It is shown that (a) pattern indexes can be represented by collections of inverted patterns, (b) solutions to pattern classification problems can be found as intersections and histograms of inverted patterns and, thus, matching of original patterns avoided.

Keywords: Artificial neural cortex, computational biology, data mining, pattern recognition.

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Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian

Abstract:

Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.

Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.

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Authors: Ashkan Ebadi, Andrea Schiffauerova

Abstract:

In spite of the global efforts toward gender equality, female researchers are still underrepresented in professional scientific activities. The gender gap is more seen in engineering and math-intensive technological scientific fields thus calling for a specific attention. This paper focuses on the Canadian funded researchers who are active in natural sciences and engineering, and analyses the gender aspects of researchers’ performance, their scientific collaboration patterns as well as their share of the federal funding within the period of 2000 to 2010. Our results confirm the existence of gender disparity among the examined Canadian researchers. Although it was observed that male researchers have been performing better in terms of number of publications, the impact of the research was almost the same for both genders. In addition, it was observed that research funding is more biased towards male researchers and they have more control over their scientific community as well.

Keywords: Bibliometrics, collaboration, funding, gender differences, research output.

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Authors: Ali Gholami, Ebrahim Panahpour, Amir Hossein Davami

Abstract:

In this research, a part of Aghche basin in Isfahan province with an area about 2000 hectars, was chosen to be obtain curve number coefficient runoff and W indicator in second Cook method By using aerial photos 1968 and 1995, the satellite data of the IRS in 2008. Then the process of land use changes in the period of study and its effect on the changes of curve number (CN), W indicator and surface runoff coefficient (C) of the basin was investigated. These results showed that on the track of these land use changes the weight averages curve number (CN), surface runoff coefficient (C) and W indicator of the basin were increased to 0.92, 0.02 and 0.78 unit in the first period of study and 1.18, 0.03, 0.99 Unit in the second period of study respectively.

Keywords: Aghche Watershed, Curve Numbers (CV), Land UseChanges, Surface Runoff Coefficient(C) Map, W indicator

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

Abstract:

This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining.

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Authors: M.O. Makhmalbaf, M. GhanooniBagha, M.A. Tutunchian, M. Zabihi Samani

Abstract:

In this paper first, Two buildings have been modeled and then analyzed using nonlinear static analysis method under two different conditions in Nonlinear SAP 2000 software. In the first condition the interaction of soil adjacent to the walls of basement are ignored while in the second case this interaction have been modeled using Gap elements of nonlinear SAP2000 software. Finally, comparing the results of two models, the effects of soil-structure on period, target point displacement, internal forces, shape deformations and base shears have been studied. According to the results, this interaction has always increased the base shear of buildings, decreased the period of structure and target point displacement, and often decreased the internal forces and displacements.

Keywords: Seismic Rehabilitation, Soil-Structure Interaction, Short Structure, Nonlinear Static Analysis.

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Authors: F. Lazzali, S. Bedaoui

Abstract:

Structural performance and seismic vulnerability of masonry buildings in Algeria are investigated in this paper. Structural classification of such buildings is carried out regarding their structural elements. Seismicity of Algeria is briefly discussed. Then vulnerability of masonry buildings and their failure mechanisms in the Boumerdes earthquake (May, 2003) are examined.

Keywords: Masonry building, seismic deficiencies, vulnerability classes

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Authors: A. Habibizad Navin, A. Sadighi, M. Naghian Fesharaki, M. Mirnia, M. Teshnelab, R. Keshmiri

Abstract:

This paper presents a new data oriented model of image. Then a representation of it, ADBT, is introduced. The ability of ADBT is clustering, segmentation, measuring similarity of images etc, with desired precision and corresponding speed.

Keywords: Data oriented modelling, image, clustering, segmentation, classification, ADBT and image processing.

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Authors: Ahmed Z. Gabr, Ahmed A. Helal, Hussein E. Said

Abstract:

With the incessant increase of power systems capacity and voltage grade, the safety of grounding grid becomes more and more prominent. In this paper, the designing substation grounding grid is presented by means of genetic algorithm (GA). This approach purposes to control the grounding cost of the power system with the aid of controlling grounding rod number and conductor lengths under the same safety limitations. The proposed technique is used for the design of the substation grounding grid in Khalda Petroleum Company “El-Qasr” power plant and the design was simulated by using CYMGRD software for results verification. The result of the design is highly complying with IEEE 80-2000 standard requirements.

Keywords: Genetic algorithm, optimum grounding grid design, power system analysis, power system protection, single layer model, substation.

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Authors: Sinee Sankrusme

Abstract:

Boon Rawd Brewery is a beer company based in Thailand that has an exemplary image, both as a good employer and a well-managed company with a strong record of social responsibility. The most famous of the company’s products is Singha beer. To study the company’s marketing strategy, a case study analysis was conducted together with qualitative research methods. The study analyzed the marketing strategy of Boon Rawd Brewery before the liberalization of the liquor market in 2000. The company’s marketing strategies consisted of the following: product line strategy, product development strategy, block channel strategy, media strategy, trade strategy, and consumer incentive strategy. Additionally, the company employed marketing mix strategy based on the 4Ps: product, price, promotion and place (of distribution).

Keywords: Beer, Boon Rawd Brewery Company, Marketing Strategy.

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Authors: Fahad Shahbaz Khan, Rao Muhammad Anwer, Olof Torgersson

Abstract:

The vast amount of information hidden in huge databases has created tremendous interests in the field of data mining. This paper examines the possibility of using data clustering techniques in oral medicine to identify functional relationships between different attributes and classification of similar patient examinations. Commonly used data clustering algorithms have been reviewed and as a result several interesting results have been gathered.

Keywords: Oral Medicine, Cluto, Data Clustering, Data Mining.

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Authors: Somayeh Tourani, Alireza Behvandi

Abstract:

The peng-Robinson (PR), a cubic equation of state (EoS), is extended to polymers by using a single set of energy (A1, A2, A3) and co-volume (b) parameters per polymer fitted to experimental volume data. Excellent results for the volumetric behavior of the 11 polymer up to 2000 bar pressure are obtained. The EoS is applied to the correlation and prediction of Henry constants in polymer solutions comprising three polymer and many nonpolar and polar solvents, including supercritical gases. The correlation achieved with two adjustable parameter is satisfactory compared with the experimental data. As a result, the present work provides a simple and useful model for the prediction of Henry's constant for polymer containing systems including those containing polar, nonpolar and supercritical fluids.

Keywords: Equation of state, Henry's constant, Peng-Robinson, polymer solution.

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Authors: Aini Hussain, M A Hannan, Azah Mohamed, Hilmi Sanusi, Burhanuddin Yeop Majlis

Abstract:

Airbag deployment has been known to be responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decisions. Therefore, the authorities and industries have been looking for more innovative and intelligent products to be realized for future enhancements in the vehicle safety systems (VSSs). Although the VSSs technologies have advanced considerably, they still face challenges such as how to avoid unnecessary and untimely airbag deployments that can be hazardous and fatal. Currently, most of the existing airbag systems deploy without regard to occupant size and position. As such, this paper will focus on the occupant and crash sensing performances due to frontal collisions for the new breed of so called smart airbag systems. It intends to provide a thorough discussion relating to the occupancy detection, occupant size classification, occupant off-position detection to determine safe distance zone for airbag deployment, crash-severity analysis and airbag decision algorithms via a computer modeling. The proposed system model consists of three main modules namely, occupant sensing, crash severity analysis and decision fusion. The occupant sensing system module utilizes the weight sensor to determine occupancy, classify the occupant size, and determine occupant off-position condition to compute safe distance for airbag deployment. The crash severity analysis module is used to generate relevant information pertinent to airbag deployment decision. Outputs from these two modules are fused to the decision module for correct and efficient airbag deployment action. Computer modeling work is carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes.

Keywords: Crash severity analysis, occupant size classification, smart airbag, vehicle safety system.

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Authors: Y. C. Mao, G. S. Chen

Abstract:

Bicycle configuration is not as large as those of motorcycles or automobiles, while it indeed composes a complicated dynamic system. People-s requirements on comfortability, controllability and safety grow higher as the research and development technologies improve. The shock absorber affects the vehicle suspension performances enormously. The absorber takes the vibration energy and releases it at a suitable time, keeping the wheel under a proper contact condition with road surface, maintaining the vehicle chassis stability. Suspension design for mountain bicycles is more difficult than that of city bikes since it encounters dynamic variations on road and loading conditions. Riders need a stiff damper as they exert to tread on the pedals when climbing, while a soft damper when they descend downhill. Various switchable shock absorbers are proposed in markets, however riders have to manually switch them among soft, hard and lock positions. This study proposes a novel design of the bicycle shock absorber, which provides automatic smooth tuning of the damping coefficient, from a predetermined lower bound to theoretically unlimited. An automatic quick releasing valve is involved in this design so that it can release the peak pressure when the suspension fork runs into a square-wave type obstacle and prevent the chassis from damage, avoiding the rider skeleton from injury. This design achieves the automatic tuning process by innovative plunger valve and fluidic passage arrangements without any electronic devices. Theoretical modelling of the damper and spring are established in this study. Design parameters of the valves and fluidic passages are determined. Relations between design parameters and shock absorber performances are discussed in this paper. The analytical results give directions to the shock absorber manufacture.

Keywords: Modelling, Simulation, Bicycle, Shock Absorber, Damping, Releasing Valve

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Authors: S. N. Turkmen Koc, A. S. Kipcak, M. B. Piskin, E. Moroydor Derun, N. Tugrul

Abstract:

Active carbon can be obtained from agricultural sources. Due to the high surface area, the production of activated carbon from cheap resources is very important. Since the surface area of 1 g activated carbon is approximately between 300 and 2000 m², it can be used to remove both organic and inorganic impurities. In this study, the adsorption of Zn metal was studied with the product of activated carbon, which is obtained from pomegranate peel by microwave and chemical activation methods. The microwave process of pomegranate peel was carried out under constant microwave power of 800 W and 1 to 4 minutes. After the microwave process, samples were treated with H₂SO₄ for 3 h. Then prepared product was used in synthetic waste water including 40 ppm Zn metal. As a result, removal of waste Zn in waste water ranged from 91% to 93%.

Keywords: Activated carbon, chemical activation, H2SO4, microwave, pomegranate peel.

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Authors: Raimund Leitner, Susanne Rosskopf

Abstract:

Near-infrared (NIR) spectroscopy is a widely used method for material identification for laboratory and industrial applications. While standard spectrometers only allow measurements at one sampling point at a time, NIR Spectral Imaging techniques can measure, in real-time, both the size and shape of an object as well as identify the material the object is made of. The online classification and sorting of recovered paper with NIR Spectral Imaging (SI) is used with success in the paper recycling industry throughout Europe. Recently, the globalisation of the recycling material streams caused that water-based flexographic-printed newspapers mainly from UK and Italy appear also in central Europe. These flexo-printed newspapers are not sufficiently de-inkable with the standard de-inking process originally developed for offset-printed paper. This de-inking process removes the ink from recovered paper and is the fundamental processing step to produce high-quality paper from recovered paper. Thus, the flexo-printed newspapers are a growing problem for the recycling industry as they reduce the quality of the produced paper if their amount exceeds a certain limit within the recovered paper material. This paper presents the results of a research project for the development of an automated entry inspection system for recovered paper that was jointly conducted by CTR AG (Austria) and PTS Papiertechnische Stiftung (Germany). Within the project an NIR SI prototype for the identification of flexo-printed newspaper has been developed. The prototype can identify and sort out flexoprinted newspapers in real-time and achieves a detection accuracy for flexo-printed newspaper of over 95%. NIR SI, the technology the prototype is based on, allows the development of inspection systems for incoming goods in a paper production facility as well as industrial sorting systems for recovered paper in the recycling industry in the near future.

Keywords: spectral imaging, imaging spectroscopy, NIR, waterbasedflexographic, flexo-printed, recovered paper, real-time classification.

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Authors: Zahra Gharineiat, Malik Khalfan

Abstract:

The significance of emissions from the road transport sector (such as air pollution, noise, etc) has grown considerably in recent years. In Australia, 14.3% of national greenhouse gas emissions in 2000 were the transport sector-s share which 12.9% of net national emissions were related to a road transport alone. Considering the growing attention to the green house gas(GHG) emissions, this paper attempts to provide air pollution modeling aspects of environmental consequences of the road transport by using one of the best computer based tools including the Geographic Information System (GIS). In other word, in this study, GIS and its applications is explained, models which are used to model air pollution and GHG emissions from vehicles are described and GIS is applied in real case study that attempts to forecast GHG emission from people who travel to work by car in 2031 in Melbourne for analysing results as thematic maps.

Keywords: Geographic Information System (GIS), Green HouseGas(GHG) emission, sustainable development, transportation

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Authors: James Kuria, John Kihiu

Abstract:

A mathematical model for determining the overall efficiency of a multistage tractor gearbox including all gear, lubricant, surface finish related parameters and operating conditions is presented. Sliding friction, rolling friction and windage losses were considered as the main sources of power loss in the gearing system. A computer code in FORTRAN was developed to simulate the model. Sliding friction contributes about 98% of the total power loss for gear trains operating at relatively low speeds (less than 2000 rpm input speed). Rolling frictional losses decrease with increased load while windage losses are only significant for gears running at very high speeds (greater than 3000 rpm). The results also showed that the overall efficiency varies over the path of contact of the gear meshes ranging between 94% to 99.5%.

Keywords: Efficiency, multistage gear train, rolling friction, slidingfriction, windage losses.

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Authors: Ahmed Al-Ani

Abstract:

The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that utilizes the ACO algorithm to implement a feature subset search procedure. Initial results obtained using the classification of speech segments are very promising.

Keywords: Ant Colony Optimization, ant systems, feature selection, pattern recognition.

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Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

Abstract:

This paper presents an unsupervised color image segmentation method. It is based on a hierarchical analysis of 2-D histogram in RGB color space. This histogram minimizes storage space of images and thus facilitates the operations between them. The improved segmentation approach shows a better identification of objects in a color image and, at the same time, the system is fast.

Keywords: Image segmentation, hierarchical analysis, 2-D histogram, Classification.

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