Search results for: Local features modelling

Authors: Adel Bouchakhchoukha, Hakim Akeb

Abstract:

In this work, we propose a hybrid heuristic in order to solve the Team Orienteering Problem (TOP). Given a set of points (or customers), each with associated score (profit or benefit), and a team that has a fixed number of members, the problem to solve is to visit a subset of points in order to maximize the total collected score. Each member performs a tour starting at the start point, visiting distinct customers and the tour terminates at the arrival point. In addition, each point is visited at most once, and the total time in each tour cannot be greater than a given value. The proposed heuristic combines beam search and a local optimization strategy. The algorithm was tested on several sets of instances and encouraging results were obtained.

Keywords: Team Orienteering Problem, Vehicle Routing, Beam Search, Local Search.

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Authors: Essam A. Al-Bahkali, Mahir H. Es-saheb, Jonny Herwan

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In this study the elastic-plastic stress distribution in weld-bonded joint, fabricated from austenitic stainless steel (AISI 304) sheet of 1.00 mm thickness and Epoxy adhesive Araldite 2011, subjected to axial loading is investigated. This is needed to improve design procedures and welding codes, and saving efforts in the cumbersome experiments and analysis. Therefore, a complete 3-D finite element modelling and analysis of spot welded, bonded and weld-bonded joints under axial loading conditions is carried out. A comprehensive systematic experimental program is conducted to determine many properties and quantities, of the base metals and the adhesive, needed for FE modelling, such like the elastic – plastic properties, modulus of elasticity, fracture limit, the nugget and heat affected zones (HAZ) properties, etc. Consequently, the finite element models developed, for each case, are used to evaluate stresses distributions across the entire joint, in both the elastic and plastic regions. The stress distribution curves are obtained, particularly in the elastic regions and found to be consistent and in excellent agreement with the published data. Furthermore, the stresses distributions are obtained in the weld-bonded joint and display the best results with almost uniform smooth distribution compared to spot and bonded cases. The stress concentration peaks at the edges of the weld-bonded region, are almost eliminated resulting in achieving the strongest joint of all processes.

Keywords: Spot Welded, Weld-Bonded, Load-Displacement curve, Stress distribution

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Authors: M. Iommi, G. Losco

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Current building sector is focused on reduction of energy requirements, on renewable energy generation and on regeneration of existing urban areas. These targets need to be solved with a systemic approach, considering several aspects simultaneously such as climate conditions, lighting conditions, solar radiation, PV potential, etc. The solar access analysis is an already known method to analyze the solar potentials, but in current years, simulation tools have provided more effective opportunities to perform this type of analysis, in particular in the early design stage. Nowadays, the study of the solar access is related to the easiness of the use of simulation tools, in rapid and easy way, during the design process. This study presents a comparison of three simulation tools, from the point of view of the user, with the aim to highlight differences in the easy-to-use of these tools. Using a real urban context as case study, three tools; Ecotect, Townscope and Heliodon, are tested, performing models and simulations and examining the capabilities and output results of solar access analysis. The evaluation of the ease-to-use of these tools is based on some detected parameters and features, such as the types of simulation, requirements of input data, types of results, etc. As a result, a framework is provided in which features and capabilities of each tool are shown. This framework shows the differences among these tools about functions, features and capabilities. The aim of this study is to support users and to improve the integration of simulation tools for solar access with the design process.

Keywords: Solar access analysis, energy building design tools, urban planning, solar potential.

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Authors: Y. A. Adla, R. Soubra, M. Kasab, M. O. Diab, A. Chkeir

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Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals out of which 11 were chosen based on their Intraclass Correlation Coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, five features were introduced to the Linear Discriminant Analysis classifier and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90% respectively.

Keywords: Doppler radar system, stand-to-sit phase, TUG test, machine learning, classification

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Authors: Nasser AlShawaaf, Soo Hee Lee

Abstract:

Arts globalisation represents a different phenomenon than arts commercialisation which was facilitated by local cultural policies. This study examines the causes and effects of globalisation of art museums in France. Building on art literature, we conducted a literature review of cultural policies. Our findings show that the cultural policies of the French government since the 1980s of cultural democratisation, cultural decentralisation, and implementing market principles on the cultural sector are leading to arts globalisation. Although globalisation is producing economic benefits and enhancing cultural reach, however, the damages include artistic values and creativity, cultural heritage and representation, and the museum itself. Art museums and host cities could overcome negative consequences through a hybrid collection display and develop local collections gradually.

Keywords: Cultural policy, cultural decentralisation, cultural globalisation, art museums, contextual analysis, France.

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: Artificial bee colony algorithm, economic dispatch, unit commitment, wind power.

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Authors: P. K. Singhal, R. Naresh, V. Sharma

Abstract:

This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: Artificial bee colony algorithm, economic dispatch, unit commitment, wind power.

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Authors: S. Sendilkumar, B. L. Mathur, Joseph Henry

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A new approach for protection of power transformer is presented using a time-frequency transform known as Wavelet transform. Different operating conditions such as inrush, Normal, load, External fault and internal fault current are sampled and processed to obtain wavelet coefficients. Different Operating conditions provide variation in wavelet coefficients. Features like energy and Standard deviation are calculated using Parsevals theorem. These features are used as inputs to PNN (Probabilistic neural network) for fault classification. The proposed algorithm provides more accurate results even in the presence of noise inputs and accurately identifies inrush and fault currents. Overall classification accuracy of the proposed method is found to be 96.45%. Simulation of the fault (with and without noise) was done using MATLAB AND SIMULINK software taking 2 cycles of data window (40 m sec) containing 800 samples. The algorithm was evaluated by using 10 % Gaussian white noise.

Keywords: Power Transformer, differential Protection, internalfault, inrush current, Wavelet Energy, Db9.

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Authors: U. Datta

Abstract:

The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: Co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection.

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Authors: R. Sridevi, G. Jagajothi

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Artificial Immune Systems (AIS), inspired by the human immune system, are algorithms and mechanisms which are self-adaptive and self-learning classifiers capable of recognizing and classifying by learning, long-term memory and association. Unlike other human system inspired techniques like genetic algorithms and neural networks, AIS includes a range of algorithms modeling on different immune mechanism of the body. In this paper, a mechanism of a human immune system based on apoptosis is adopted to build an Intrusion Detection System (IDS) to protect computer networks. Features are selected from network traffic using Fisher Score. Based on the selected features, the record/connection is classified as either an attack or normal traffic by the proposed methodology. Simulation results demonstrates that the proposed AIS based on apoptosis performs better than existing AIS for intrusion detection.

Keywords: Apoptosis, Artificial Immune System (AIS), Fisher Score, KDD dataset, Network intrusion detection.

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Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic

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Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.

Keywords: Sphere in Cube Grid Approach to Modelling of Shale Gas Production Using Non-Linear Flow Mechanisms

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Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma, Hirendra Das

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Signature represents an individual characteristic of a person which can be used for his / her validation. For such application proper modeling is essential. Here we propose an offline signature recognition and verification scheme which is based on extraction of several features including one hybrid set from the input signature and compare them with the already trained forms. Feature points are classified using statistical parameters like mean and variance. The scanned signature is normalized in slant using a very simple algorithm with an intention to make the system robust which is found to be very helpful. The slant correction is further aided by the use of an Artificial Neural Network (ANN). The suggested scheme discriminates between originals and forged signatures from simple and random forgeries. The primary objective is to reduce the two crucial parameters-False Acceptance Rate (FAR) and False Rejection Rate (FRR) with lesser training time with an intension to make the system dynamic using a cluster of ANNs forming a multiple classifier system.

Keywords: offline, algorithm, FAR, FRR, ANN.

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Authors: M. Guillard, M. Philippe, F. Laurent, J. Martinerie, J. P. Lachaux, G. Florence

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One approach to assess neural networks underlying the cognitive processes is to study Electroencephalography (EEG). It is relevant to detect various mental states and characterize the physiological changes that help to discriminate two situations. That is why an EEG (amplitude, synchrony) classification procedure is described, validated. The two situations are "eyes closed" and "eyes opened" in order to study the "alpha blocking response" phenomenon in the occipital area. The good classification rate between the two situations is 92.1 % (SD = 3.5%) The spatial distribution of a part of amplitude features that helps to discriminate the two situations are located in the occipital regions that permit to validate the localization method. Moreover amplitude features in frontal areas, "short distant" synchrony in frontal areas and "long distant" synchrony between frontal and occipital area also help to discriminate between the two situations. This procedure will be used for mental fatigue detection.

Keywords: Classification, EEG Synchrony, alpha, resting situation.

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Authors: Xinyue Zhao, Yutaka Satoh, Hidenori Takauji, Shun'ichi Kaneko

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A hybrid feature based adaptive particle filter algorithm is presented for object tracking in real scenarios with static camera. The hybrid feature is combined by two effective features: the Grayscale Arranging Pairs (GAP) feature and the color histogram feature. The GAP feature has high discriminative ability even under conditions of severe illumination variation and dynamic background elements, while the color histogram feature has high reliability to identify the detected objects. The combination of two features covers the shortage of single feature. Furthermore, we adopt an updating target model so that some external problems such as visual angles can be overcame well. An automatic initialization algorithm is introduced which provides precise initial positions of objects. The experimental results show the good performance of the proposed method.

Keywords: Hybrid feature, adaptive Particle Filter, robust Object Tracking, Grayscale Arranging Pairs (GAP) feature.

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Authors: Ei Phyo Wai, Nay Min Tun

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Computation of facility location problem for every location in the country is not easy simultaneously. Solving the problem is described by using cluster computing. A technique is to design parallel algorithm by using local search with single swap method in order to solve that problem on clusters. Parallel implementation is done by the use of portable parallel programming, Message Passing Interface (MPI), on Microsoft Windows Compute Cluster. In this paper, it presents the algorithm that used local search with single swap method and implementation of the system of a facility to be opened by using MPI on cluster. If large datasets are considered, the process of calculating a reasonable cost for a facility becomes time consuming. The result shows parallel computation of facility location problem on cluster speedups and scales well as problem size increases.

Keywords: cluster, cost, demand, facility location

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Authors: E. J. Cilliers, Z. Goosen

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The impact that urban green spaces have on sustainability and quality of life is phenomenal. This is also true for the local South African environment. However, in reality green spaces in urban environments are decreasing due to growing populations, increasing urbanization and development pressure. This further impacts on the provision of child-friendly spaces, a concept that is already limited in local context. Child-friendly spaces are described as environments in which people (children) feel intimately connected to, influencing the physical, social, emotional, and ecological health of individuals and communities. The benefits of providing such spaces for the youth are well documented in literature. This research therefore aimed to investigate the concept of child-friendly spaces and its applicability to the South African planning context, in order to guide the planning of such spaces for future communities and use. Child-friendly spaces in the urban environment of the city of Durban, was used as local case study, along with two international case studies namely Mullerpier public playground in Rotterdam, the Netherlands, and Kadidjiny Park in Melville, Australia. The aim was to determine how these spaces were planned and developed and to identify tools that were used to accomplish the goal of providing successful child-friendly green spaces within urban areas. The need and significance of planning for such spaces was portrayed within the international case studies. It is confirmed that minimal provision is made for green space planning within the South African context, when there is reflected on the international examples. As a result international examples and disciples of providing child-friendly green spaces should direct planning guidelines within local context. The research concluded that child-friendly green spaces have a positive impact on the urban environment and assist in a child’s development and interaction with the natural environment. Regrettably, the planning of these child-friendly spaces is not given priority within current spatial plans, despite the proven benefits of such.

Keywords: Built environment, child-friendly spaces, green spaces. public places, urban area.

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Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

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Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: Texture classification, texture descriptor, SIFT, SURF, ORB.

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Authors: M. Si-Ahmed, A. Belakrouf, S. Kenai

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The use of additions in cement in manufacturing, mortar and concrete offers economic and ecological advantages. Cements with additions such as limestone, slag and natural pouzzolana are produced in cement factories in Algeria. Several studies analyzed the effect of these additions on the physical and mechanical properties as well as the durability of concrete. However, few studies were conducted on the effect of local metakaolin on mechanical properties and durability of concrete. The main purpose of this paper is to analyze the performance of mortar and concrete with local metakaolin. The preparation of the metakaolin was carried out by calcination of kaolin at a temperature of 850 °C for a period of 3 hours. The experimental results have shown that the rates of substitutions of 10 and 15% metakaolin increases the compressive strength and flexural strength at both early age and long term. The durability and the permeability were also improved by reducing the coefficient of sorptivity.

Keywords: Metakaolin, calcination, compressive strength, durability.

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Authors: Amado, M. P., Amado, A., Poggi, F., Correia de Freitas, J.

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Today is widely understood that global energy consumption patterns are directly related to the urban expansion and development process. This expansion is based on the natural growth of human activities and has left most urban areas totally dependent on fossil fuel derived external energy inputs. This status-quo of production, transportation, storage and consumption of energy has become inefficient and is set to become even more so when the continuous increases in energy demand are factored in. The territorial management of land use and related activities is a central component in the search for more efficient models of energy use, models that can meet current and future regional, national and European goals.

In this paper a methodology is developed and discussed with the aim of improving energy efficiency at the municipal level. The development of this methodology is based on the monitoring of energy consumption and its use patterns resulting from the natural dynamism of human activities in the territory and can be utilized to assess sustainability at the local scale. A set of parameters and indicators are defined with the objective of constructing a systemic model based on the optimization, adaptation and innovation of the current energy framework and the associated energy consumption patterns. The use of the model will enable local governments to strike the necessary balance between human activities and economic development and the local and global environment while safeguarding fairness in the energy sector.

Keywords: Solar urban planning, solar smart city, urban development, energy efficiency.

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Authors: W. F. Ribeiro, J. L. N. Góes

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The industrial process adds to engineering wood products features absent in solid wood, with homogeneous structure and reduced defects, improved physical and mechanical properties, bio-deterioration, resistance and better dimensional stability, improving quality and increasing the reliability of structures wood. These features combined with using fast-growing trees, make them environmentally ecological products, ensuring a strong consumer market. The wood I-joists are manufactured by the industrial profiles bonding flange and web, an important aspect of the production of wooden I-beams is the adhesive joint that bonds the web to the flange. Adhesives can effectively transfer and distribute stresses, thereby increasing the strength and stiffness of the composite. The objective of this study is to evaluate different resins in a shear strain specimens with the aim of analyzing the most efficient resin and possibility of using national products, reducing the manufacturing cost. First was conducted a literature review, where established the geometry and materials generally used, then established and analyzed 8 national resins and produced six specimens for each.

Keywords: Engineered wood products, structural resin, wood i-joist.

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Authors: O. Hassanein, Sreenatha G. Anavatti, Tapabrata Ray

Abstract:

The dynamics of the Autonomous Underwater Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate accurately because of the variations of these coefficients with different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line adaptive fuzzy model and adaptive neural fuzzy network (ANFN) model techniques to overcome the uncertain external disturbance and the difficulties of modelling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The models- parameters are adapted according to the back propagation algorithm based upon the error between the identified model and the actual output of the plant. The proposed ANFN model adopts a functional link neural network (FLNN) as the consequent part of the fuzzy rules. Thus, the consequent part of the ANFN model is a nonlinear combination of input variables. Fuzzy control system is applied to guide and control the AUV using both adaptive models and mathematical model. Simulation results show the superiority of the proposed adaptive neural fuzzy network (ANFN) model in tracking of the behavior of the AUV accurately even in the presence of noise and disturbance.

Keywords: AUV, AUV dynamic model, fuzzy control, fuzzy modelling, adaptive fuzzy control, back propagation, system identification, neural fuzzy model, FLNN.

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Authors: Khalil Monfaredi, Hassan Faraji Baghtash, Majid Abbasi

Abstract:

In this paper a novel high output impedance, low input impedance, wide bandwidth, very simple current mirror with input and output voltage requirements less than that of a simple current mirror is presented. These features are achieved with very simple structure avoiding extra large node impedances to ensure high bandwidth operation. The circuit's principle of operation is discussed and compared to simple and low voltage cascode (LVC) current mirrors. Such outstanding features of this current mirror as high output impedance ~384K, low input impedance~6.4, wide bandwidth~178MHz, low input voltage ~ 362mV, low output voltage ~ 38mV and low current transfer error ~4% (all at 50μA) makes it an outstanding choice for high performance applications. Simulation results in BSIM 0.35μm CMOS technology with HSPICE are given in comparison with simple, and LVC current mirrors to verify and validate the performance of the proposed current mirror.

Keywords: Analog circuits, Current mirror, high frequency, Low power, Low voltage.

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Authors: Jaroslav Polec, Petra Heribanová, Tomáš Hirner

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In this paper we proposed a method for finding video frames representing one sign in the finger alphabet. The method is based on determining hands location, segmentation and the use of standard video quality evaluation metrics. Metric calculation is performed only in regions of interest. Sliding mechanism for finding local extrema and adaptive threshold based on local averaging is used for key frames selection. The success rate is evaluated by recall, precision and F1 measure. The method effectiveness is compared with metrics applied to all frames. Proposed method is fast, effective and relatively easy to realize by simple input video preprocessing and subsequent use of tools designed for video quality measuring.

Keywords: Key frame, video, quality, metric, MSE, MSAD, SSIM, VQM, sign language, finger alphabet.

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Authors: Aleksandar Tsenov

Abstract:

The main goal of this work is to propose a way for combined use of two nontraditional algorithms by solving topological problems on telecommunications concentrator networks. The algorithms suggested are the Simulated Annealing algorithm and the Genetic Algorithm. The Algorithm of Simulated Annealing unifies the well known local search algorithms. In addition - Simulated Annealing allows acceptation of moves in the search space witch lead to decisions with higher cost in order to attempt to overcome any local minima obtained. The Genetic Algorithm is a heuristic approach witch is being used in wide areas of optimization works. In the last years this approach is also widely implemented in Telecommunications Networks Planning. In order to solve less or more complex planning problem it is important to find the most appropriate parameters for initializing the function of the algorithm.

Keywords: Concentrator network, genetic algorithm, simulated annealing, UCPL.

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Authors: Aree Thongpukdee, Chockpisit Thepsithar, Chuthalak Thammaso

Abstract:

Use of plants grown in local area for edible has a long tradition in different culture. The indigenous knowledge such as usage of plants as vegetables by local people is risk to disappear when no records are done. In order to conserve and transfer this valuable heritage to the new generation, ethnobotanical study should be investigated and documented. The survey of vegetable plants traditionally used was carried out in the year 2012. Information was accumulated via questionnaires and oral interviewing from 100 people living in 36 villages of 9 districts in Amphoe Huai Mek, Kalasin, Thailand. Local plant names, utilized parts and preparation methods of the plants were recorded. Each mentioned plant species were collected and voucher specimens were prepared. A total of 55 vegetable plant species belonging to 34 families and 54 genera were identified. The plant habits were tree, shrub, herb, climber, and shrubby fern at 21.82%, 18.18%, 38.18%, 20.00% and 1.82% respectively. The most encountered vegetable plant families were Leguminosae (20%), Cucurbitaceae (7.27%), Apiaceae (5.45%), whereas families with 3.64% uses were Araceae, Bignoniaceae, Lamiaceae, Passifloraceae, Piperaceae and Solanaceae. The most common consumptions were fresh or brief boiled young shoot or young leaf as side dishes of ‘jaeo, laab, namprik, pon’ or curries. Most locally known vegetables included 45% of the studied plants which grow along road side, backyard garden, hedgerow, open forest and rice field.

Keywords: Ethnobotanical survey, Thailand, vegetable plants.

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Authors: John Mark Lampos, Virgilio Sison

Abstract:

Two constructions of unit-memory binary convolutional codes from linear block codes over the finite semi-local ring F2r +vF2r , where v2 = v, are presented. In both cases, if the linear block code is systematic, then the resulting convolutional encoder is systematic, minimal, basic and non-catastrophic. The Hamming free distance of the convolutional code is bounded below by the minimum Hamming distance of the block code. New examples of binary convolutional codes that meet the Heller upper bound for systematic codes are given.

Keywords: Convolutional codes, semi-local ring, free distance, Heller bound.

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Authors: Areej Almalkawi, Sameer Hamadna, Parviz Soroushian, Nalin Darsana

Abstract:

The work on indigenous binders in this paper focused on the following indigenous raw materials: red clay, red lava and pumice (as primary aluminosilicate precursors), wood ash and gypsum (as supplementary minerals), and sodium sulfate and lime (as alkali activators). The experimental methods used for evaluation of these indigenous raw materials included laser granulometry, x-ray fluorescence (XRF) spectroscopy, and chemical reactivity. Formulations were devised for transforming these raw materials into alkali aluminosilicate-based hydraulic cements. These formulations were processed into hydraulic cements via simple heating and milling actions to render thermal activation, mechanochemical and size reduction effects. The resulting hydraulic cements were subjected to laser granulometry, heat of hydration and reactivity tests. These cements were also used to prepare mortar mixtures, which were evaluated via performance of compressive strength tests. The measured values of strength were correlated with the reactivity, size distribution and microstructural features of raw materials. Some of the indigenous hydraulic cements produced in this reporting period yielded viable levels of compressive strength. The correlation trends established in this work are being evaluated for development of simple and thorough methods of qualifying indigenous raw materials for use in production of indigenous hydraulic cements.

Keywords: One-part geopolymer cement, aluminosilicate precursors, thermal activation, mechanochemical.

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Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

Abstract:

Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: Feature fusion, image retrieval, membership function, normalization.

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Authors: G. H. Majzoob, B. Sharifi Hamadani

Abstract:

Mapping between local and global coordinates is an important issue in finite element method, as all calculations are performed in local coordinates. The concern arises when subparametric are used, in which the shape functions of the field variable and the geometry of the element are not the same. This is particularly the case for C* elements in which the extra degrees of freedoms added to the nodes make the elements sub-parametric. In the present work, transformation matrix for C1* (an 8-noded hexahedron element with 12 degrees of freedom at each node) is obtained using equivalent C0 elements (with the same number of degrees of freedom). The convergence rate of 8-noded C1* element is nearly equal to its equivalent C0 element, while it consumes less CPU time with respect to the C0 element. The existence of derivative degrees of freedom at the nodes of C1* element along with excellent convergence makes it superior compared with it equivalent C0 element.

Keywords: Mapping, Finite element method, C* elements, Convergence, C0 elements.

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Authors: Sri Hartati, 1Agus Harjoko, Brad G. Nickerson

Abstract:

A prototype of an anomaly detection system was developed to automate process of recognizing an anomaly of roentgen image by utilizing fuzzy histogram hyperbolization image enhancement and back propagation artificial neural network. The system consists of image acquisition, pre-processor, feature extractor, response selector and output. Fuzzy Histogram Hyperbolization is chosen to improve the quality of the roentgen image. The fuzzy histogram hyperbolization steps consist of fuzzyfication, modification of values of membership functions and defuzzyfication. Image features are extracted after the the quality of the image is improved. The extracted image features are input to the artificial neural network for detecting anomaly. The number of nodes in the proposed ANN layers was made small. Experimental results indicate that the fuzzy histogram hyperbolization method can be used to improve the quality of the image. The system is capable to detect the anomaly in the roentgen image.

Keywords: Image processing, artificial neural network, anomaly detection.

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