Search results for: Communication channel model; Broadband Powerlinecommunication; Branched network; OFDM; Delay Spread

Authors: Shazia Javed, Noor Atinah Ahmad

Abstract:

In this paper an efficient incomplete factorization preconditioner is proposed for the Least Mean Squares (LMS) adaptive filter. The proposed preconditioner is approximated from a priori knowledge of the factors of input correlation matrix with an incomplete strategy, motivated by the sparsity patter of the upper triangular factor in the QRD-RLS algorithm. The convergence properties of IPLMS algorithm are comparable with those of transform domain LMS(TDLMS) algorithm. Simulation results show efficiency and robustness of the proposed algorithm with reduced computational complexity.

Keywords: Autocorrelation matrix, Cholesky's factor, eigenvalue spread, Markov input.

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Authors: H. Ahmed, A. Schlenkhoff

Abstract:

Recently, permeable breakwaters have been suggested to overcome the disadvantages of fully protection breakwaters. These protection structures have minor impacts on the coastal environment and neighboring beaches where they provide a more economical protection from waves and currents. For regular waves, a numerical model is used (FLOW-3D, VOF) to investigate the hydraulic performance of a permeable breakwater. The model of permeable breakwater consists of a pair of identical vertical slotted walls with an impermeable upper and lower part, where the draft is a decimal multiple of the total depth. The middle part is permeable with a porosity of 50%. The second barrier is located at distant of 0.5 and 1.5 of the water depth from the first one. The numerical model is validated by comparisons with previous laboratory data and semi-analytical results of the same model. A good agreement between the numerical results and both laboratory data and semi-analytical results has been shown and the results indicate the applicability of the numerical model to reproduce most of the important features of the interaction. Through the numerical investigation, the friction factor of the model is carefully discussed.

Keywords: Coastal structures, permeable breakwater, slotted wall, numerical model, energy dissipation coefficient.

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Authors: Aref Ghafouri, Mohammad Javad Mollakazemi, Farhad Asadi

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In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: Frequency response, Order of model reduction, frequency matching condition.

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Authors: F. Barzegar, M. H. Sheikhi

Abstract:

In the present work we model a Multiquantum Well structure Separate Absorption and Charge Multiplication Avalanche Photodiode (MQW-SACM-APD), while the Absorption region coincide with the MQW. We consider the nonuniformity of electric field using split-step method in active region. This model is based on the carrier rate equations in the different regions of the device. Using the model we obtain the photocurrent, and dark current. As an example, InGaAs/InP SACM-APD and MQW-SACM-APD are simulated. There is a good agreement between the simulation and experimental results.

Keywords: Avalanche Photodiode, Physical Model, MultiquantumWell, Split Step Method.

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Authors: Hichem Sassi, Tawfik Najeh, Noureddine Liouane

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Information of nodes’ locations is an important criterion for lots of applications in Wireless Sensor Networks. In the hop-based range-free localization methods, anchors transmit the localization messages counting a hop count value to the whole network. Each node receives this message and calculates its own distance with anchor in hops and then approximates its own position. However the estimative distances can provoke large error, and affect the localization precision. To solve the problem, this paper proposes an algorithm, which makes the unknown nodes fix the nearest anchor as a reference and select two other anchors which are the most accurate to achieve the estimated location. Compared to the DV-Hop algorithm, experiment results illustrate that proposed algorithm has less average localization error and is more effective.

Keywords: Wireless Sensors Networks, Localization problem, localization average error, DV–Hop Algorithm, MATLAB.

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Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

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Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector autoregressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is Neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel model, Neural networks, Svensson model, Vector autoregressive model, Yield curve.

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Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

Abstract:

Cosmic showers, during the transit through space, produce sub - products as a result of interactions with the intergalactic or interstellar medium which after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of High Energy Particle Showers involve a plethora of theoretical and experimental works with a host of constraints resulting in inaccuracies in measurements. Therefore, there exist a necessity to develop a readily available system based on soft-computational approaches which can be used for EAS analysis. This is due to the fact that soft computational tools such as Artificial Neural Network (ANN)s can be trained as classifiers to adapt and learn the surrounding variations. But single classifiers fail to reach optimality of decision making in many situations for which Multiple Classifier System (MCS) are preferred to enhance the ability of the system to make decisions adjusting to finer variations. This work describes the formation of an MCS using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN) with data inputs from correlation mapping Self Organizing Map (SOM) blocks and the output optimized by another SOM. The results show that the setup can be adopted for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

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Authors: Van-Quang Trinh, Gi-Soo Chung, Hee-Cheol Kim

Abstract:

The increasing number of senior population gradually causes to demand the use of information and communication technology for their satisfactory lives. This paper presents the development of an integrated TV based system which offers an opportunity to provide value added services to a large number of elderly citizens, and thus helps improve their quality of life. The design philosophy underlying this paper is to fulfill both technological and human aspects. The balance between these two dimensions has been currently stressed as a crucial element for the design of usable systems in real use, particularly to the elderly who have physical and mental decline. As the first step to achieve it, we have identified human and social factors that affect the elder-s quality of life by a literature review, and based on them, build four fundamental services: information, healthcare, learning and social network services. Secondly, the system architecture, employed technologies and the elderly-friendly system design considerations are presented. This reflects technological and human perspectives in terms of the system design. Finally, we describe some scenarios that illustrate the potentiality of the proposed system to improve elderly people-s quality of life.

Keywords: Elderly people, human computer interaction, quality of life, smart television, user-centered system design

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Authors: Parvinder S. Sandhu, Harpreet Kaur, Amanpreet Singh

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Automatic reusability appraisal is helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable components from existing legacy systems; that can save cost of developing the software from scratch. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. In this research work, structural attributes of software components are explored using software metrics and quality of the software is inferred by different Neural Network based approaches, taking the metric values as input. The calculated reusability value enables to identify a good quality code automatically. It is found that the reusability value determined is close to the manual analysis used to be performed by the programmers or repository managers. So, the developed system can be used to enhance the productivity and quality of software development.

Keywords: Neural Network, Software Reusability, Software Metric, Accuracy, MAE, RMSE.

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Authors: M. Kasumović, A. Hodžić, M. Tešanović

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One way for optimum loading of overdimensioning conveyers is speed (capacity) decrement, with attention for production capabilities and demands. At conveyers which drives with three phase slip-ring induction motor, technically reasonable solution for conveyer (driving motors) speed regulation is using constant torque subsynchronous cascade with static semiconductor converter and transformer for energy reversion to the power network. In the paper is described mathematical model for parameter calculation of two-motors 6 kV subsynchronous cascade. It is also demonstrated that applying of this cascade gave several good properties, foremost in electrical energy saving, also in improving of other energy indexes, and finally that results in cost reduction of complete electrical motor drive.

Keywords: Conveyer with rubber belt, electrical motor drive, sub synchronous cascade

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Authors: Jakub Kraus, Vladimír Plos, Peter Vittek

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This article focuses on the issue of airport emergency plans, which are documents describing reactions to events with impact on aviation safety or aviation security. The article specifically focuses on the use and creation of emergency plans, where could be found a number of disagreements between different stakeholders, for which the airport emergency plan applies. Those are the friction surfaces of interfaces, which is necessary to identify and ensure them smooth process to avoid dangerous situations or delay.

Keywords: Airport emergency plan, aviation safety, aviation security, comprehensive management system, friction surfaces of airport emergency plan, interfaces of processes.

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Authors: Ramanarayana Kandikattu, Lillykutty Jacob

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'Secure routing in Mobile Ad hoc networks' and 'Internet connectivity to Mobile Ad hoc networks' have been dealt separately in the past research. This paper proposes a light weight solution for secure routing in integrated Mobile Ad hoc Network (MANET)-Internet. The proposed framework ensures mutual authentication of Mobile Node (MN), Foreign Agent (FA) and Home Agent (HA) to avoid various attacks on global connectivity and employs light weight hop-by-hop authentication and end-to-end integrity to protect the network from most of the potential security attacks. The framework also uses dynamic security monitoring mechanism to monitor the misbehavior of internal nodes. Security and performance analysis show that our proposed framework achieves good security while keeping the overhead and latency minimal.

Keywords: Internet, Mobile Ad hoc Networks, Secure routing.

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Authors: Sepehr M.H.Jamarani, M.H.Moradi, H.Behnam, G.A.Rezai Rad

Abstract:

This paper presents an approach for early breast cancer diagnostic by employing combination of artificial neural networks (ANN) and multiwaveletpacket based subband image decomposition. The microcalcifications correspond to high-frequency components of the image spectrum, detection of microcalcifications is achieved by decomposing the mammograms into different frequency subbands,, reconstructing the mammograms from the subbands containing only high frequencies. For this approach we employed different types of multiwaveletpacket. We used the result as an input of neural network for classification. The proposed methodology is tested using the Nijmegen and the Mammographic Image Analysis Society (MIAS) mammographic databases and images collected from local hospitals. Results are presented as the receiver operating characteristic (ROC) performance and are quantified by the area under the ROC curve.

Keywords: Breast cancer, neural networks, diagnosis, multiwavelet packet, microcalcification.

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Authors: Zoltan Theisz, Gergely Mezei

Abstract:

Modern industrial automation relies on service oriented concepts of Internet of Things (IoT) device modeling in order to provide a flexible and extendable environment for service meta-repository. However, state-of-the-art meta-modeling techniques prefer design-time modeling, which results in a heavy usage of class sometimes unnecessary static subtyping. Although this approach benefits from clear-cut object-oriented design principles, it also seals the model repository for further dynamic extensions. In this paper, a dynamic multi-level modeling approach is introduced that enables dynamic subtyping through a more relaxed partial instantiation mechanism. The approach is demonstrated on a simple sensor network example.

Keywords: Meta-modeling, dynamic subtyping, DMLA, industrial automation, arrowhead.

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Authors: S. Wongkoon, M. Pollar, M. Jaroensutasinee, K. Jaroensutasinee

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This study aimed at developing a forecasting model on the number of Dengue Haemorrhagic Fever (DHF) incidence in Northern Thailand using time series analysis. We developed Seasonal Autoregressive Integrated Moving Average (SARIMA) models on the data collected between 2003-2006 and then validated the models using the data collected between January-September 2007. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The most suitable model was the SARIMA(2,0,1)(0,2,0)12 model with a Akaike Information Criterion (AIC) of 12.2931 and a Mean Absolute Percent Error (MAPE) of 8.91713. The SARIMA(2,0,1)(0,2,0)12 model fitting was adequate for the data with the Portmanteau statistic Q20 = 8.98644 ( x20,95= 27.5871, P>0.05). This indicated that there was no significant autocorrelation between residuals at different lag times in the SARIMA(2,0,1)(0,2,0)12 model.

Keywords: Dengue, SARIMA, Time Series Analysis, Northern Thailand.

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Authors: Ya-Ling Huang, Ming-Chun Tsai, Fan Hsu, Kai-Ru Hsieh

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This paper mainly discusses the research and practice process of a laboratory curriculum by leading students to perform field investigation into time-honoured shops that have existed for more than 50 years in the downtown area of Tainan, Taiwan, and then search again for design elements and completing the design. The participants are juniors from the Department of Visual Communication Design, Kun Shan University. The duration of research and practice is two months. Operators of these shops are invited to jointly appraise the final achievements. 9 works out of 27 are chosen for final exhibition and commercialization.

Keywords: Culture creative industry, visual communication design, curriculum experimental.

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Authors: Toshihiko Matsuka, James E. Corter

Abstract:

Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.

Keywords: category learning, cognitive modeling, radial basis function, stochastic optimization.

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Authors: Masato Nishi, Tetsushi Kaburagi, Masashi Kurose, Tei Hirashima, Tetsusei Kurasiki

Abstract:

The process of thermoforming a carbon fiber reinforced thermoplastic (CFRTP) has increased its presence in the automotive industry for its wide applicability to the mass production car. A non-isothermal forming for CFRTP can shorten its cycle time to less than 1 minute. In this paper, the textile reinforcement FE model which the authors proposed in a previous work is extended to the CFRTP model for non-isothermal forming simulation. The effect of thermoplastic is given by adding shell elements which consider thermal effect to the textile reinforcement model. By applying Reuss model to the stress calculation of thermoplastic, the proposed model can accurately predict in-plane shear behavior, which is the key deformation mode during forming, in the range of the process temperature. Using the proposed model, thermoforming simulation was conducted and the results are in good agreement with the experimental results.

Keywords: Carbon fiber reinforced thermoplastic (CFRTP), Finite element analysis (FEA), Pre-impregnated textile composite, Non-isothermal forming.

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Authors: H. Z. Ulukan, E. Demircioğlu, M. Erol Genevois

Abstract:

The scope of this paper and the aim of proposed model were to apply monetary Input –Output (I-O) analysis to point out the importance of reusing know-how and other requirements in order to reduce the production costs in a manufacturing process for a laptop computer. I-O approach using the monetary input-output model is employed to demonstrate the impacts of different factors in a manufacturing process. A sensitivity analysis showing the correlation between these different factors is also presented. It is expected that the recommended model would have an advantageous effect in the cost minimization process.

Keywords: Input-Output Analysis, Monetary Input-Output Model, Manufacturing Process, Laptop Computer.

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Authors: Moustafa S. El-Sammany

Abstract:

Flash floods are considered natural disasters that can cause casualties and demolishing of infra structures. The problem is that flash floods, particularly in arid and semi arid zones, take place in very short time. So, it is important to forecast flash floods earlier to its events with a lead time up to 48 hours to give early warning alert to avoid or minimize disasters. The flash flood took place over Wadi Watier - Sinai Peninsula, in October 24th, 2008, has been simulated, investigated and analyzed using the state of the art regional weather model. The Weather Research and Forecast (WRF) model, which is a reliable short term forecasting tool for precipitation events, has been utilized over the study area. The model results have been calibrated with the real data, for the same date and time, of the rainfall measurements recorded at Sorah gauging station. The WRF model forecasted total rainfall of 11.6 mm while the real measured one was 10.8 mm. The calibration shows significant consistency between WRF model and real measurements results.

Keywords: Early warning system, Flash floods forecasting, WadiWatier, WRF model.

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Authors: Hossein Sahoolizadeh, Mahdi Rahimi, Hamid Dehghani

Abstract:

We introduce an algorithm based on the morphological shared-weight neural network. Being nonlinear and translation-invariant, the MSNN can be used to create better generalization during face recognition. Feature extraction is performed on grayscale images using hit-miss transforms that are independent of gray-level shifts. The output is then learned by interacting with the classification process. The feature extraction and classification networks are trained together, allowing the MSNN to simultaneously learn feature extraction and classification for a face. For evaluation, we test for robustness under variations in gray levels and noise while varying the network-s configuration to optimize recognition efficiency and processing time. Results show that the MSNN performs better for grayscale image pattern classification than ordinary neural networks.

Keywords: Face recognition, Neural Networks, Multi-layer Perceptron, masking.

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Authors: Reza Bazargan Lari, Mohammad H. Fattahi

Abstract:

Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.

Keywords: Wavelet, de-noising, predictability, time series fractal analysis, valid length, ANN.

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Authors: Nicolò Vaiana, Giorgio Serino

Abstract:

The nonlinear time history analysis of seismically base-isolated structures can require a significant computational effort when the behavior of each seismic isolator is predicted by adopting the widely used differential equation Bouc-Wen model. In this paper, a nonlinear exponential model, able to simulate the response of seismic isolation bearings within a relatively large displacements range, is described and adopted in order to reduce the numerical computations and speed up the nonlinear dynamic analysis. Compared to the Bouc-Wen model, the proposed one does not require the numerical solution of a nonlinear differential equation for each time step of the analysis. The seismic response of a 3d base-isolated structure with a lead rubber bearing system subjected to harmonic earthquake excitation is simulated by modeling each isolator using the proposed analytical model. The comparison of the numerical results and computational time with those obtained by modeling the lead rubber bearings using the Bouc-Wen model demonstrates the good accuracy of the proposed model and its capability to reduce significantly the computational effort of the analysis.

Keywords: Base isolation, computational efficiency, nonlinear exponential model, nonlinear time history analysis.

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Authors: Manssour A. Abdulsalam Bin Miskeen, Ahmed Mohamed Alhodairi, Riza Atiq Abdullah Bin O. K. Rahmat

Abstract:

In the planning point of view, it is essential to have mode choice, due to the massive amount of incurred in transportation systems. The intercity travellers in Libya have distinct features, as against travellers from other countries, which includes cultural and socioeconomic factors. Consequently, the goal of this study is to recognize the behavior of intercity travel using disaggregate models, for projecting the demand of nation-level intercity travel in Libya. Multinomial Logit Model for all the intercity trips has been formulated to examine the national-level intercity transportation in Libya. The Multinomial logit model was calibrated using nationwide revealed preferences (RP) and stated preferences (SP) survey. The model was developed for deference purpose of intercity trips (work, social and recreational). The variables of the model have been predicted based on maximum likelihood method. The data needed for model development were obtained from all major intercity corridors in Libya. The final sample size consisted of 1300 interviews. About two-thirds of these data were used for model calibration, and the remaining parts were used for model validation. This study, which is the first of its kind in Libya, investigates the intercity traveler’s mode-choice behavior. The intercity travel mode-choice model was successfully calibrated and validated. The outcomes indicate that, the overall model is effective and yields higher precision of estimation. The proposed model is beneficial, due to the fact that, it is receptive to a lot of variables, and can be employed to determine the impact of modifications in the numerous characteristics on the need for various travel modes. Estimations of the model might also be of valuable to planners, who can estimate possibilities for various modes and determine the impact of unique policy modifications on the need for intercity travel.

Keywords: Multinomial logit model, improved intercity transport, intercity mode-choice behavior, disaggregate analysis.

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

Abstract:

Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of big data technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centres or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through VADER and RoBERTa model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and Term Frequency – Inverse Document Frequency (TFIDF) Vectorization and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide if the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: Counter vectorization, Convolutional Neural Network, Crawler, data technology, Long Short-Term Memory, LSTM, Web Scraping, sentiment analysis.

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Authors: Bi-Huei Tsai

Abstract:

Prior research has not effectively investigated how the profitability of Chinese branches affect FDIs in China [1, 2], so this study for the first time incorporates realistic earnings information to systematically investigate effects of innovation, imitation, and profit factors of FDI diffusions from Taiwan to China. Our nonlinear least square (NLS) model, which incorporates earnings factors, forms a nonlinear ordinary differential equation (ODE) in numerical simulation programs. The model parameters are obtained through a genetic algorithms (GA) technique and then optimized with the collected data for the best accuracy. Particularly, Taiwanese regulatory FDI restrictions are also considered in our modified model to meet the realistic conditions. To validate the model-s effectiveness, this investigation compares the prediction accuracy of modified model with the conventional diffusion model, which does not take account of the profitability factors. The results clearly demonstrate the internal influence to be positive, as early FDI adopters- consistent praises of FDI attract potential firms to make the same move. The former erects a behavior model for the latter to imitate their foreign investment decision. Particularly, the results of modified diffusion models show that the earnings from Chinese branches are positively related to the internal influence. In general, the imitating tendency of potential consumers is substantially hindered by the losses in the Chinese branches, and these firms would invest less into China. The FDI inflow extension depends on earnings of Chinese branches, and companies will adjust their FDI strategies based on the returns. Since this research has proved that earning is an influential factor on FDI dynamics, our revised model explicitly performs superior in prediction ability than conventional diffusion model.

Keywords: diffusion model, genetic algorithms, nonlinear leastsquares (NLS) model, prediction error.

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Authors: Qianhong Zhang, Lihui Yang, Daixi Liao

Abstract:

In this paper, by employing a new Lyapunov functional and an elementary inequality analysis technique, some sufficient conditions are derived to ensure the existence and uniqueness of periodic oscillatory solution for fuzzy bi-directional memory (BAM) neural networks with time-varying delays, and all other solutions of the fuzzy BAM neural networks converge the uniqueness periodic solution. These criteria are presented in terms of system parameters and have important leading significance in the design and applications of neural networks. Moreover an example is given to illustrate the effectiveness and feasible of results obtained.

Keywords: Fuzzy BAM neural networks, Periodic solution, Global exponential stability, Time-varying delays

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Authors: Kumiko Inagaki

Abstract:

Japanese society is experiencing an aging population and declining birth rate along with the popularization of higher education, spread of economic globalization, rapid progress in technical innovation, changes in employment conditions, and emergence of a knowledge-based society. Against this background, interest in career education at Japanese universities has increased in recent years. This paper describes how the government has implemented career education policies in Japan, and introduces the cases of two universities that have successfully linked career education to university education in Japan.

Keywords: Career Education, Employability, Higher Education, Japanese University, University Education.

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Authors: XueSong Yu, JiaFeng Liu, XiangLong Tang, JianHua Huang

Abstract:

For improving the efficiency of human 3D tracking, we present an algorithm to track 3D Arm Motion. First, the Hierarchy Limb Model (HLM) is proposed based on the human 3D skeleton model. Second, via graph decomposition, the arm motion state space, modeled by HLM, can be discomposed into two low dimension subspaces: root nodes and leaf nodes. Finally, Rao-Blackwellised Particle Filter is used to estimate the 3D arm motion. The result of experiment shows that our algorithm can advance the computation efficiency.

Keywords: Hierarchy Limb Model; Rao-Blackwellised Particle Filter; 3D tracking

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Authors: J. Tospornsampan, I. Kita, M. Ishii, Y. Kitamura

Abstract:

In this paper a combination approach of two heuristic-based algorithms: genetic algorithm and tabu search is proposed. It has been developed to obtain the least cost based on the split-pipe design of looped water distribution network. The proposed combination algorithm has been applied to solve the three well-known water distribution networks taken from the literature. The development of the combination of these two heuristic-based algorithms for optimization is aimed at enhancing their strengths and compensating their weaknesses. Tabu search is rather systematic and deterministic that uses adaptive memory in search process, while genetic algorithm is probabilistic and stochastic optimization technique in which the solution space is explored by generating candidate solutions. Split-pipe design may not be realistic in practice but in optimization purpose, optimal solutions are always achieved with split-pipe design. The solutions obtained in this study have proved that the least cost solutions obtained from the split-pipe design are always better than those obtained from the single pipe design. The results obtained from the combination approach show its ability and effectiveness to solve combinatorial optimization problems. The solutions obtained are very satisfactory and high quality in which the solutions of two networks are found to be the lowest-cost solutions yet presented in the literature. The concept of combination approach proposed in this study is expected to contribute some useful benefits in diverse problems.

Keywords: GAs, Heuristics, Looped network, Least-cost design, Pipe network, Optimization, TS

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