Search results for: resistance training

Authors: Tai-Hwa Emily Lu

Abstract:

This study was a part of the three-year longitudinal research on setting up an math learning model for the disadvantaged students in Taiwan. A target 2nd grade class with 10 regular students and 6 disadvantaged students at a disadvantaged area in Taipei participated in this study. Two units of a market basal math textbook concerning fractions, three-dimensional figures, weight and capacity were adapted to enhance their math learning motivations, confidences and effects. The findings were (1) curriculum adaptation was effective on enhancing students- learning motivations, confidences and effects; (2) story-type problems and illustrations decreased difficulties on understanding math language for students from new immigrant families and students with special needs; (3) “concrete – semiconcrete – abstract" teaching strategies and hands-on activities were essential to raise students learning interests and effects; and (4) curriculum adaptation knowledge and skills needed to be included in the pre- and in-service teacher training programs.

Keywords: curriculum adaptations, mathematics, disadvantaged students, inclusive classroom

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Authors: Javier A. Dominguez Caballero, Graeme A. Manson, Matthew B. Marshall

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Cutting tools with ceramic inserts are often used in the process of machining many types of superalloy, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. This article explores the relationship between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process and the evolution of sparks created during the same process. These sparks were analysed through pictures of the cutting process recorded using an SLR camera. Features relating to the intensity and area of the cutting sparks were extracted from the individual pictures using image processing techniques. These features were then related to the ceramic insert’s crater wear area.

Keywords: Ceramic cutting tools, high speed machining, image processing, tool condition monitoring, tool wear.

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Authors: Binay K. Dutta, Tayseir M. Abd Ellateif, Saikat Maitra

Abstract:

In the present work homogeneous silica film on silicon was fabricated by colloidal silica sol. The silica sol precursor with uniformly granular particle was derived by the alkaline hydrolysis of tetraethoxyorthosilicate (TEOS) in presence of glycerol template. The film was prepared by dip coating process. The templated hetero-structured silica film was annealed at elevated temperatures to generate nano- and meso porosity in the film. The film was subsequently annealed at different temperatures to make it defect free and abrasion resistant. The sol and the film were characterized by the measurement of particle size distribution, scanning electron microscopy, XRD, FTIR spectroscopy, transmission electron microscopy, atomic force microscopy, measurement of the refractive index, thermal conductivity and abrasion resistance. The porosity of the films decreased whereas refractive index and dielectric constant of it `increased with the increase in the annealing temperature. The thermal conductivity of the films increased with the increase in the film thickness. The developed porous silica film holds strong potential for use in different areas.

Keywords: Silica film, Nanoporous, Sol-gel, Templating, Dip coating.

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Authors: Omid Borazjani, Mahmoud Roosta, Khodakhast Isapour, Ali Reza Rajabi

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This paper presents an application of Artificial Neural Network (ANN) algorithm for improving power system voltage stability. The training data is obtained by solving several normal and abnormal conditions using the Linear Programming technique. The selected objective function gives minimum deviation of the reactive power control variables, which leads to the maximization of minimum Eigen value of load flow Jacobian. The considered reactive power control variables are switchable VAR compensators, OLTC transformers and excitation of generators. The method has been implemented on a modified IEEE 30-bus test system. The results obtain from the test clearly show that the trained neural network is capable of improving the voltage stability in power system with a high level of precision and speed.

Keywords: Artificial Neural Network (ANN), Load Flow, Voltage Stability, Power Systems.

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Authors: J. Chen, N. Hundal

Abstract:

Conventional machining is a form of subtractive manufacturing, in which a collection of material-working processes utilizing power-driven machine tools are used to remove undesired material to achieve a desired geometry. This paper presents an approach for comparison between turning center and vertical machining center by optimization of cutting parameters at cylindrical workpieces leading to minimum surface roughness by using taguchi methodology. Aluminum alloy was taken to conduct experiments due to its unique high strength-weight ratio that is maintained at elevated temperatures and their exceptional corrosion resistance. During testing, the effects of the cutting parameters on the surface roughness were investigated. Additionally, by using taguchi methodology for each of the cutting parameters (spindle speed, depth of cut, insert diameter, and feed rate) minimum surface roughness for the process of turn-milling was determined according to the cutting parameters. A confirmation experiment demonstrates the effectiveness of taguchi method.

Keywords: Surface roughness, taguchi parameter design, turning center, turn-milling operations, vertical machining center.

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Authors: S. Pancucci

Abstract:

Professional development is the focus of this study. It reports on questionnaire data that examined the perceived effectiveness of the Train the Trainer model of technology professional development for elementary teachers. Eighty-three selected teachers called Information Technology Coaches received four half-day and one after-school in-service sessions. Subsequently, coaches shared the information and skills acquired during training with colleagues. Results indicated that participants felt comfortable as Information Technology Coaches and felt well prepared because of their technological professional development. Overall, participants perceived the Train the Trainer model to be effective. The outcomes of this study suggest that the use of the Train the Trainer model, a known professional development model, can be an integral and interdependent component of the newer more comprehensive learning community professional development model.

Keywords: change, education, learning community, professional development, school improvement, technology coach, Train the Trainer.

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Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim

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In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.

Keywords: Artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt.

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Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

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Composite patching is a common way for reinforcing the cracked pipes and cylinders. The effects of composite patch reinforcement on fracture parameters of a cracked pipe depend on a variety of parameters such as number of layers, angle, thickness, and material of each layer. Therefore, stacking sequence optimization of composite patch becomes crucial for the applications of cracked pipes. In this study, in order to obtain the optimal stacking sequence for a composite patch that has minimum weight and maximum resistance in propagation of cracks, a coupled Multi-Objective Genetic Algorithm (MOGA) and Finite Element Method (FEM) process is proposed. This optimization process has done for longitudinal and transverse semi-elliptical cracks and optimal stacking sequences and Pareto’s front for each kind of cracks are presented. The proposed algorithm is validated against collected results from the existing literature.

Keywords: Multi objective optimization, Pareto front, composite patch, cracked pipe.

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Authors: Zohreh Bang Tavakoli, Shuktika Chatterjee

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This study is investigating the impact of ideological structures in terms of conservative and liberal on shaping immigration acceptance attitudes under the contribution of socio-economic status. According to motivated reasoning theory, political ideology is identified as a recurrent impact on the formation of attitude, while conservatives tend to express more hostility toward immigrants in comparison to liberals which are proposed to be more tolerant towards immigrants. Our finding suggests that political ideology will structure individual attitudes when citizens socio-economic vulnerability and level of education are low enough to consider immigrants as a threat. Therefore, economic vulnerability is proposed to weaken the ideological predispositions’ resistance. There has been some threats and factors such as level of education and economic condition proposed by group competition theory and labor market competition theory as fundamental factors which can strengthen or weaken the effects of political ideology on individuals’ attitudes towards immigration; those mechanisms for liberals and conservatives will be operated differently.

Keywords: Conservative, immigration, liberal, political ideology.

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Authors: Ashish Kumar, Sanjeev Kumar Suman

Abstract:

This study investigated the influence of Cloisite-15A nanoclay on the physical, performance, and mechanical properties of bitumen binder. Cloisite-15A was blended in the bitumen in variegated percentages from 1% to 9% with increment of 2%. The blended bitumen was characterized using penetration, softening point, and dynamic viscosity using rotational viscometer, and compared with unmodified bitumen equally penetration grade 60/70. The rheological parameters were investigated using Dynamic Shear Rheometer (DSR), and mechanical properties were investigated by using Marshall Stability test. The results indicated an increase in softening point, dynamic viscosity and decrease in binder penetration. Rheological properties of bitumen increase complex modulus, decrease phase angle and improve rutting resistances as well. There was significant improvement in Marshall Stability, rather marginal improvement in flow value. The best improvement in the modified binder was obtained with 5% Cloisite-15A nanoclay.

Keywords: Cloisite-15A, complex shear modulus, phase angle, rutting resistance.

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Authors: Victor Oluwaseyi Olowonisi

Abstract:

The paper aimed at presenting an overview on the concept of e-learning as it relates to higher education and how it provides opportunities for students, instructors and the government in developing the educational sector. It also touched on the benefits and challenges attached to e-learning as a new medium of reaching more students especially in the Nigerian context. The opportunities attributed to e-learning in the paper includes breaking boundaries barriers, reaching a larger number of students, provision of jobs for ICT experts, etc. In contrary, poor power supply, cost of implementation, poor computer literacy, technophobia (fear of technology), computer crime and system failure were some of the challenges of e-learning discussed in the paper. The paper proffered that the government can help the people gain more from e-learning through its financing. Also, it was stated that instructors/lecturers and students need to undergo training on computer application in order for e-learning to be more effective in developing higher education in Nigeria.

Keywords: E-Learning, education, higher education, increasing literacy.

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Authors: Latha Parthiban, R. Subramanian

Abstract:

Heart disease (HD) is a major cause of morbidity and mortality in the modern society. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. All doctors are unfortunately not equally skilled in every sub specialty and they are in many places a scarce resource. A system for automated medical diagnosis would enhance medical care and reduce costs. In this paper, a new approach based on coactive neuro-fuzzy inference system (CANFIS) was presented for prediction of heart disease. The proposed CANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach which is then integrated with genetic algorithm to diagnose the presence of the disease. The performances of the CANFIS model were evaluated in terms of training performances and classification accuracies and the results showed that the proposed CANFIS model has great potential in predicting the heart disease.

Keywords: CANFIS, genetic algorithms, heart disease, membership function.

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Authors: Juliana V. Pereira, Adriana S. M. Batista, Jefferson P. Nascimento, Clascídia A. Furtado, Luiz O. Faria

Abstract:

The combination of the properties of graphene oxide (OG) and PVDF homopolymer makes their combined composite materials as multifunctional systems with great potential. Knowledge of the molecular structure is essential for better use. In this work, the degradation of PVDF polymer exposed to gamma irradiation in oxygen atmosphere in high dose rate has been studied and compared to degradation of PVDF/OG composites. The samples were irradiated with a Co-60 source at constant dose rate, with doses ranging from 100 kGy to 1,000 kGy. In FTIR data shown that the formation of oxidation products was at the both samples with formation of carbonyl and hydroxyl groups amongst the most prevalent products in the pure PVDF samples. In the other hand, the composites samples exhibit less presence of degradation products with predominant formation of carbonyl groups, these results also seen in the UV-Vis analysis. The results show that the samples of composites may have greater resistance to the irradiation process, since they have less degradation products than pure PVDF samples seen by spectroscopic techniques.

Keywords: Gamma irradiation, PVDF, PVDF/OG composites, spectroscopic techniques.

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Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy

Abstract:

Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.

Keywords: Neural Models, Algorithms, Microstrip Lines, Analysis, Synthesis

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Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Mustafa Mhawesh, Reza Langari

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This paper describes the development of a model of an impaired human arm performing a reaching motion, which will be used to predict hand path trajectories for people with reduced arm joint mobility. Assuming that the arm was in contact with a surface during the entire movement, the contact conditions at the initial and final task locations were determined and used to generate the entire trajectory. The model was validated by comparing it to experimental data, which simulated an arm joint impairment by physically constraining the joint motion with a brace. Future research will include using the model in the development of physical training protocols that avoid early recruitment of “healthy” Degrees-Of-Freedom (DOF) for reaching motions, thus facilitating an Active Range-Of-Motion Recovery (AROM) for a particular impaired joint.

Keywords: Higher order kinematic specifications, human motor coordination, impaired movement, kinematic synthesis.

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Authors: R. Gaceb-Terrak, F. Rahmania

Abstract:

Takerbucht is the only cultivar of date palm known as being resistant to the bayoud disease, caused by Fusarium oxysporum f. sp. albedinis (F.o.a.). In the aim to understand more about the defense mechanisms implied, we realized phytochemical analyses of this cultivar leaflets and roots and this, for the first time, using gas chromatography-mass spectrometry (GC-MS).The examination of our results shows that fifty-four molecules have been detected, fourteen of which are common to leaflets and roots. This study revealed also the organs' richness in derivatives fatty acids: both saturated and unsaturated are represented mainly by methyl esters of Hexadecanoic and 9,12,15-Octadecatrienoic acids. 1-Dodecanethiol, derivative Dodecanoic acid is only present in roots. It’s of great interest to note that the screening revealed the steroidal saponins abundance, among which Yamogenin acetate and Diosgenin, exclusively detected in Takerbucht. They may play an essential role, in the date palm resistance to the bayoud disease.

Keywords: Analysis by GC-MS, leaflets and roots of resistant date palm to F.o.a., derivatives fatty acids, steroidal saponins.

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Authors: Cuong Nguyen Khac, Ju H. Park, Ho-Youl Jung

Abstract:

This paper proposes a new approach to perform the problem of real-time face detection. The proposed method combines primitive Haar-Like feature and variance value to construct a new feature, so-called Variance based Haar-Like feature. Face in image can be represented with a small quantity of features using this new feature. We used SVM instead of AdaBoost for training and classification. We made a database containing 5,000 face samples and 10,000 non-face samples extracted from real images for learning purposed. The 5,000 face samples contain many images which have many differences of light conditions. And experiments showed that face detection system using Variance based Haar-Like feature and SVM can be much more efficient than face detection system using primitive Haar-Like feature and AdaBoost. We tested our method on two Face databases and one Non-Face database. We have obtained 96.17% of correct detection rate on YaleB face database, which is higher 4.21% than that of using primitive Haar-Like feature and AdaBoost.

Keywords: AdaBoost, Haar-Like feature, SVM, variance, Variance based Haar-Like feature.

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Authors: Supriya Pal, Kalyan Adhikari, Somnath Mukherjee, Sudipta Ghosh

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This study presents the application of artificial neural network for modeling the phenolic compound migration through vertical soil column. A three layered feed forward neural network with back propagation training algorithm was developed using forty eight experimental data sets obtained from laboratory fixed bed vertical column tests. The input parameters used in the model were the influent concentration of phenol(mg/L) on the top end of the soil column, depth of the soil column (cm), elapsed time after phenol injection (hr), percentage of clay (%), percentage of silt (%) in soils. The output of the ANN was the effluent phenol concentration (mg/L) from the bottom end of the soil columns. The ANN predicted results were compared with the experimental results of the laboratory tests and the accuracy of the ANN model was evaluated.

Keywords: Modeling, Neural Networks, Phenol, Soil media

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Authors: Bambang Ariantara, Nandy Putra, Rangga Aji Pamungkas

Abstract:

The development of electric vehicle batteries have resulted in very high energy density lithium-ion batteries. However, this progress is accompanied by the risk of thermal runaway, which can result in serious accidents. Heat pipes are heat exchangers that are suitable to be applied in electric vehicle battery thermal management for their lightweight, compact size and do not require external power supply. This paper aims to examine experimentally a Flat Plate Loop Heat Pipe (FPLHP) performance as a heat exchanger in thermal management system of lithium-ion battery for electric vehicle application. The heat generation of the battery was simulated using a cartridge heater. Stainless steel screen mesh was used as the capillary wick. Distilled water, alcohol and acetone were used as working fluids with a filling ratio of 60%. It was found that acetone gives the best performance that produces thermal resistance of 0.22 W/°C with 50°C evaporator temperature at heat flux load of 1.61 W/cm2.

Keywords: Electric vehicle, flat plate loop heat pipe, lithium-ion battery, thermal management system.

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Authors: P. I. Itoua, D. Sun, S. Shen

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This study aimed at investigating the properties of asphalt and mix asphalt based on the effects of waste toner sources (WT1 and WT2) with 8% dosage waste toner powders (WT). The test results included penetration, softening points, ductility, G*sinδ, G*/sinδ, Ideal cracking test (IDEAL-CT), and Ideal shear rutting test (IDEAL-RT). The results showed that the base binder with WT2 had a significantly higher viscosity value compared to the WT1 modified binder, and thus, higher energy for mixing and compaction is needed. Furthermore, the results of penetration, softening points, G*sinδ, and G*/sinδ were all affected by waste toner type. In terms of asphalt mixture, the IDEAL-RT test revealed that the addition of waste toner improved the rutting resistance of the asphalt mixture regardless of toner type. Further, CTindex values for waste toner-modified asphalt mixtures show no significant difference. Above all, WT-modified asphalt mixtures produced by the wet process have better rutting performance.

Keywords: Waste toner, waste toner-modified asphalt, asphalt mixture properties, IDEAL-RT test, IDEAL-CT test.

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Authors: H. Ucar, U. Aridogan

Abstract:

Composite structures become intriguing for the design of aerospace, automotive and marine applications due to weight reduction, corrosion resistance and radar signature reduction demands and requirements. Studies on piezoelectric ceramic transducers (PZT) for diagnostics and health monitoring have gained attention for their sensing capabilities, however PZT structures are prone to fail in case of heavy operational loads. In this paper, we develop a piezo-based Glass Fiber Reinforced Polymer (GFRP) composite finite element (FE) model, validate with experimental setup, and identify the applicability and limitations of PZTs for a marine application. A case study is conducted to assess the piezo-based sensing capabilities in a representative marine composite structure. A FE model of the composite structure combined with PZT patches is developed, afterwards the response and functionality are investigated according to the sea conditions. Results of this study clearly indicate the blockers and critical aspects towards industrialization and wide-range use of PZTs for marine composite applications.

Keywords: FRP, marine composite, piezoelectric transducer, sea state, wave-induced loads.

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Authors: Dong Wook Lee, Seung Hyun Kim, Jeongho Oh

Abstract:

With the strengthened regulation on the mandatory use of recycled aggregate, development of construction materials using recycled aggregate has recently increased. This study aimed to secure the performance of asphalt concrete mixture by developing recycled-modified asphalt using recycled basalt aggregate from the Jeju area. The strength of the basalt aggregate from the Jeju area used in this study was similar to that of general aggregate, while the specific surface area was larger due to the development of pores. Modified asphalt was developed using a general aggregate-recycled aggregate ratio of 7:3, and the results indicated that the Marshall stability increased by 27% compared to that of asphalt concrete mixture using only general aggregate, and the flow values showed similar levels. Also, the indirect tensile strength increased by 79%, and the toughness increased by more than 100%. In addition, the TSR for examining moisture resistance was 0.95 indicating that the reduction in the indirect tensile strength due to moisture was very low (5% level), and the developed recycled-modified asphalt could satisfy all the quality standards of asphalt concrete mixture.

Keywords: Asphalt Concrete Mixture, Performance Grade, Recycled Basalt Aggregate, Recycled-Modified Asphalt.

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Authors: A. Beheshti, S. Salkhordeh, H. Amini

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Based on statistics released by Islamic Republic of Iran Police (IRIP), from among the total 9555 motorcycle accidents that happened in 2007, 857 riders died and 11219 one got injured. If we also consider the death toll and injuries of other vehicles' accidents resulted from traffic violation by motorcycle riders, then paying attention to the motorcycle accidents seems to be very necessary. Therefore, in this study we tried to investigate the traits and issues related to production, application, and training, along with causes of motorcycle accidents from 4 perspectives of road, human, environment and vehicle and also based on statistical and geographical analysis of accident-sheets prepared by Iran Road Patrol Department (IRPD). Unfamiliarity of riders with regulations and techniques of motorcycling, disuse of safety equipments, inefficiency of roads and design of junctions for safe trafficking of motorcycles and finally the lack of sufficient control of responsible organizations are among the major causes which lead to these accidents.

Keywords: Motorcycle, Motorcycle riders, Road accidents, Statistical analysis of accidents.

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Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

Abstract:

The state of the art in instructional design for computer-assisted learning has been strongly influenced by advances in information technology, Internet and Web-based systems. The emphasis of educational systems has shifted from training to learning. The course delivered has also been changed from large inflexible content to sequential small chunks of learning objects. The concepts of learning objects together with the advanced technologies of Web and communications support the reusability, interoperability, and accessibility design criteria currently exploited by most learning systems. These concepts enable just-in-time learning. We propose to extend theses design criteria further to include the learnability concept that will help adapting content to the needs of learners. The learnability concept offers a better personalization leading to the creation and delivery of course content more appropriate to performance and interest of each learner. In this paper we present a new framework of learning environments containing knowledge discovery as a tool to automatically learn patterns of learning behavior from learners' profiles and history.

Keywords: Knowledge mining, Web-based learning, Learning environments.

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Authors: A. Ruimi, S. Goyal, B. M. Nour

Abstract:

Interactive web-based computer simulations are needed by the medical community to replicate the experience of surgical procedures as closely and realistically as possible without the need to practice on corpses, animals and/or plastic models. In this paper, we offer a review on current state of the research on simulations of surgical threads, identify future needs and present our proposed plans to meet them. Our goal is to create a physics-based simulator, which will predict the behavior of surgical thread when subjected to conditions commonly encountered during surgery. To that end, we will i) develop three dimensional finite element models based on the Cosserat theory of elasticity ii) test and feedback results with the medical community and iii) develop a web-based user interface to run/command our simulator and visualize the results. The impacts of our research are that i) it will contribute to the development of a new generation of training for medical school students and ii) the simulator will be useful to expert surgeons in developing new, better and less risky procedures.

Keywords: Cosserat rod-theory, FEM simulations, Modeling, Surgical thread.

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Authors: T. Hacib, M. R. Mekideche, N. Ferkha

Abstract:

This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study consists in the simulation of a large number of parameters in a material under test, using the finite element method (FEM). Both variations in relative magnetic permeability and electrical conductivity of the material under test are considered. Then, the obtained results are used to generate a set of vectors for the training of MLP neural network. Finally, the obtained neural network is used to evaluate a group of new materials, simulated by the FEM, but not belonging to the original dataset. Noisy data, added to the probe measurements is used to enhance the robustness of the method. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Keywords: Inverse problem, MLP neural network, parametersidentification, FEM.

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Authors: S. A. Naeini, A. Khalili

Abstract:

Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: Settlement, subway line, FLAC3D, ANFIS method.

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Authors: Samy Sadek, Ayoub Al-Hamadi, Bernd Michaelis, Usama Sayed

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In this paper, we propose a supervised method for color image classification based on a multilevel sigmoidal neural network (MSNN) model. In this method, images are classified into five categories, i.e., “Car", “Building", “Mountain", “Farm" and “Coast". This classification is performed without any segmentation processes. To verify the learning capabilities of the proposed method, we compare our MSNN model with the traditional Sigmoidal Neural Network (SNN) model. Results of comparison have shown that the MSNN model performs better than the traditional SNN model in the context of training run time and classification rate. Both color moments and multi-level wavelets decomposition technique are used to extract features from images. The proposed method has been tested on a variety of real and synthetic images.

Keywords: Image classification, multi-level neural networks, feature extraction, wavelets decomposition.

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Authors: Yuanyuan Chai, Limin Jia, Zundong Zhang

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Hybrid algorithm is the hot issue in Computational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classification method and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy Inference System (M-ANFIS) and weight updating formula in consideration with qualitative representation of inference consequent parts in fuzzy neural networks. M-ANFIS model adopts Mamdani fuzzy inference system which has advantages in consequent part. Experiment results of applying M-ANFIS to evaluate traffic Level of service show that M-ANFIS, as a new hybrid algorithm in computational intelligence, has great advantages in non-linear modeling, membership functions in consequent parts, scale of training data and amount of adjusted parameters.

Keywords: Fuzzy neural networks, Mamdani fuzzy inference, M-ANFIS

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Authors: Neamat El Gayar

Abstract:

Learning using labeled and unlabelled data has received considerable amount of attention in the machine learning community due its potential in reducing the need for expensive labeled data. In this work we present a new method for combining labeled and unlabeled data based on classifier ensembles. The model we propose assumes each classifier in the ensemble observes the input using different set of features. Classifiers are initially trained using some labeled samples. The trained classifiers learn further through labeling the unknown patterns using a teaching signals that is generated using the decision of the classifier ensemble, i.e. the classifiers self-supervise each other. Experiments on a set of object images are presented. Our experiments investigate different classifier models, different fusing techniques, different training sizes and different input features. Experimental results reveal that the proposed self-supervised ensemble learning approach reduces classification error over the single classifier and the traditional ensemble classifier approachs.

Keywords: Multiple Classifier Systems, classifier ensembles, learning using labeled and unlabelled data, K-nearest neighbor classifier, Bayes classifier.

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