Search results for: Artificial accelerated ageing test

Authors: Lambros V. Skarlas, Grigorios N. Beligiannis, Efstratios F. Georgopoulos, Adam V. Adamopoulos

Abstract:

The aim of this contribution is to present a new approach in modeling the electrical activity of the human heart. A recurrent artificial neural network is being used in order to exhibit a subset of the dynamics of the electrical behavior of the human heart. The proposed model can also be used, when integrated, as a diagnostic tool of the human heart system. What makes this approach unique is the fact that every model is being developed from physiological measurements of an individual. This kind of approach is very difficult to apply successfully in many modeling problems, because of the complexity and entropy of the free variables describing the complex system. Differences between the modeled variables and the variables of an individual, measured at specific moments, can be used for diagnostic purposes. The sensor fusion used in order to optimize the utilization of biomedical sensors is another point that this paper focuses on. Sensor fusion has been known for its advantages in applications such as control and diagnostics of mechanical and chemical processes.

Keywords: Artificial Neural Networks, Diagnostic System, Health Condition Modeling Tool, Heart Diagnostics Model, Heart Electricity Model.

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Authors: A. Goel, S.C. Gupta, S.K.Wasan

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Testable software has two inherent properties – observability and controllability. Observability facilitates observation of internal behavior of software to required degree of detail. Controllability allows creation of difficult-to-achieve states prior to execution of various tests. In this paper, we describe COTT, a Controllability and Observability Testing Tool, to create testable object-oriented software. COTT provides a framework that helps the user to instrument object-oriented software to build the required controllability and observability. During testing, the tool facilitates creation of difficult-to-achieve states required for testing of difficultto- test conditions and observation of internal details of execution at unit, integration and system levels. The execution observations are logged in a test log file, which are used for post analysis and to generate test coverage reports.

Keywords: Controllability, Observability, Test Coverage and Testing Tool.

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Authors: A. Sina, A. Aeenmehr, H. Mohamadian

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Optimization and control of reactive power distribution in the power systems leads to the better operation of the reactive power resources. Reactive power control reduces considerably the power losses and effective loads and improves the power factor of the power systems. Another important reason of the reactive power control is improving the voltage profile of the power system. In this paper, voltage and reactive power control using Neural Network techniques have been applied to the 33 shines- Tehran Electric Company. In this suggested ANN, the voltages of PQ shines have been considered as the input of the ANN. Also, the generators voltages, tap transformers and shunt compensators have been considered as the output of ANN. Results of this techniques have been compared with the Linear Programming. Minimization of the transmission line power losses has been considered as the objective function of the linear programming technique. The comparison of the results of the ANN technique with the LP shows that the ANN technique improves the precision and reduces the computation time. ANN technique also has a simple structure and this causes to use the operator experience.

Keywords: voltage control, linear programming, artificial neural network, power systems

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Authors: Hannachi Med Tahar, H. Djebaili, B. Daheche

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In this approach, we have tried to describe the flattening of welded tubes, and its experimental application. The test is carried out at the (National product processing company dishes and tubes production). Usually, the final products (tubes) undergo a series of non-destructive inspection online and offline welding, and obviously destructive mechanical testing (bending, flattening, flaring, etc.). For this and for the purpose of implementing the flattening test, which applies to the processing of round tubes in other forms, it took four sections of welded tubes draft (before stretching hot) and welded tubes finished (after drawing hot and annealing), it was also noted the report 'health' flattened tubes must not show or crack or tear. The test is considered poor if it reveals a lack of ductility of the metal.

Keywords: Flattening, destructive testing, tube drafts, finished tube, Castem 2001.

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Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: Acute hepatitis, Medical resource cost, Artificial neural network, Support vector regression.

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Authors: Zainudin Arsad, Norul Baine Mat Johor

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Tourism industry is an important sector in Malaysia economy and this motivates the examination of long-run relationships between tourist arrivals from three selected European countries in Malaysia and four possible determinants; relative prices, exchange rates, transportation cost and relative prices of substitute destination. The study utilizes data from January 1999 to September 2008 and employs standard econometric techniques that include unit root test and cointegration test. The estimated demand model indicates that depreciation of local currency and increases in prices at substitute destination have positive impact on tourist arrivals while increase in transportation cost has negative impact on tourist arrivals. In addition, the model suggests that higher rate of increase in local prices relative to prices at tourist country of origin may not deter tourists from coming to Malaysia

Keywords: origin country, unit root test, cointegration test

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Authors: Bao Thach Nguyen, Abbas Mohajerani

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The California Bearing Ratio (CBR) has been acknowledged as an important parameter to characterize the bearing capacity of earth structures, such as earth dams, road embankments, airport runways, bridge abutments and pavements. Technically, the CBR test can be carried out in the laboratory or in the field. The CBR test is time-consuming and is infrequently performed due to the equipment needed and the fact that the field moisture content keeps changing over time. Over the years, many correlations have been developed for the prediction of CBR by various researchers, including the dynamic cone penetrometer, undrained shear strength and Clegg impact hammer. This paper reports and discusses some of the results from a study on the prediction of CBR. In the current study, the CBR test was performed in the laboratory on some finegrained subgrade soils collected from various locations in Victoria. Based on the test results, a satisfactory empirical correlation was found between the CBR and the physical properties of the experimental soils.

Keywords: California bearing ratio, fine-grained soils, pavement, soil physical properties.

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Authors: Mohamed Abdallah, Mostafa Warith, Roberto Narbaitz, Emil Petriu, Kevin Kennedy

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Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.

Keywords: Adaptive neural fuzzy inference system (ANFIS), gas production, landfill

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Authors: Wullapa Wongsinlatam

Abstract:

Back propagation algorithm (BP) is a widely used technique in artificial neural network and has been used as a tool for solving the time series problems, such as decreasing training time, maximizing the ability to fall into local minima, and optimizing sensitivity of the initial weights and bias. This paper proposes an improvement of a BP technique which is called IM-COH algorithm (IM-COH). By combining IM-COH algorithm with cuckoo search algorithm (CS), the result is cuckoo search improved control output hidden layer algorithm (CS-IM-COH). This new algorithm has a better ability in optimizing sensitivity of the initial weights and bias than the original BP algorithm. In this research, the algorithm of CS-IM-COH is compared with the original BP, the IM-COH, and the original BP with CS (CS-BP). Furthermore, the selected benchmarks, four time series samples, are shown in this research for illustration. The research shows that the CS-IM-COH algorithm give the best forecasting results compared with the selected samples.

Keywords: Artificial neural networks, back propagation algorithm, time series, local minima problem, metaheuristic optimization.

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Authors: Khashayar Jafari, Mostafa Jafarian Abyaneh, Vahab Toufigh

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Polymer concrete (PC) is a distinct concrete with superior characteristics in comparison to ordinary cement concrete. It has become well-known for its applications in thin overlays, floors and precast components. In this investigation, the mechanical properties of PC with different epoxy resin contents, ordinary cement concrete (OCC) and lightweight concrete (LC) have been studied under uniaxial compression test. The study involves five types of concrete, with each type being tested four times. Their complete elastic-plastic behavior was compared with each other through the measurement of volumetric strain during the tests. According to the results, PC showed higher strength, ductility and energy absorption with respect to OCC and LC.

Keywords: Polymer concrete, ordinary cement concrete, lightweight concrete, uniaxial compression test, volumetric strain.

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: Anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines.

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Authors: M. O. Hamzah, M. R. M. Hasan

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Binder drainage test is widely used to set an upper limit to the design binder content of porous asphalt. However, the presence of high amount of fine particles in the drained binder may affect the accuracy of the test result. This paper presents a study to characterize the composition and particle size distribution of fine particles accumulated in the drained binder. Fine aggregates and filler in the drained binder were extracted using a suitable solvent. Then, wet and dry sieve analysis was carried out to identify the actual composition of the extracted fine aggregates and filler. From the results, almost half of the drained binder consisted of fine aggregates and this significantly affects the accuracy of the design binder content of porous asphalt mix. This simple finding highlights the importance of taking into account the presence of fine aggregates in the calculation of drained binder.

Keywords: Porous asphalt, Binder drainage test, Drained binder, Fine particle proportion

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Authors: Marcio Leal, Marta Villamil

Abstract:

Computacional recognition of sign languages aims to allow a greater social and digital inclusion of deaf people through interpretation of their language by computer. This article presents a model of recognition of two of global parameters from sign languages; hand configurations and hand movements. Hand motion is captured through an infrared technology and its joints are built into a virtual three-dimensional space. A Multilayer Perceptron Neural Network (MLP) was used to classify hand configurations and Dynamic Time Warping (DWT) recognizes hand motion. Beyond of the method of sign recognition, we provide a dataset of hand configurations and motion capture built with help of fluent professionals in sign languages. Despite this technology can be used to translate any sign from any signs dictionary, Brazilian Sign Language (Libras) was used as case study. Finally, the model presented in this paper achieved a recognition rate of 80.4%.

Keywords: Sign language recognition, computer vision, infrared, artificial neural network, dynamic time warping.

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: Malaria, deep learning, DL, convolution neural network, CNN, thin blood smears.

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Authors: Vahid Salmani, Mahmoud Naghibzadeh, Farid Seifi, Amirhossein Taherinia

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Soccer simulation is an effort to motivate researchers and practitioners to do artificial and robotic intelligence research; and at the same time put into practice and test the results. Many researchers and practitioners throughout the world are continuously working to polish their ideas and improve their implemented systems. At the same time, new groups are forming and they bring bright new thoughts to the field. The research includes designing and executing robotic soccer simulation algorithms. In our research, a soccer simulation player is considered to be an intelligent agent that is capable of receiving information from the environment, analyze it and to choose the best action from a set of possible ones, for its next move. We concentrate on developing a two-phase method for the soccer player agent to choose its best next move. The method is then implemented into our software system called Nexus simulation team of Ferdowsi University. This system is based on TsinghuAeolus[1] team that was the champion of the world RoboCup soccer simulation contest in 2001 and 2002.

Keywords: RoboCup, Soccer simulation, multi-agent environment, intelligent soccer agent, ball controller agent.

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Authors: Simin Sadeghi-Saeb

Abstract:

Metacognitive strategies consistently play important roles in reading comprehension. The metacognitive strategies involve the active monitoring and consequent regulation and orchestration of the cognitive processes in relation to the cognitive objects or data on which they bear. In this paper, the effect of instruction in using metacognitive strategies on reading academic materials, type of metacognitive strategies were mostly used by college university students before and after the instruction and the level they use those strategies before and after the instruction were studied. For these aims, 50 female college students were chosen. Then, they were divided randomly into two groups, experimental and control groups. At first session, students in both groups took the standard TOFEL exam. After the pre-test had been administered, the instruction began. After treatment, a post-test was taken. It is useful to state that after pre-test and post-test the same questionnaire was handed to the students of experimental group. The results of this research show that the instruction of metacognitive strategies has positive effect on the students' scores in reading comprehension tests. Furthermore, it showed that before and after the instruction, the students' usage of metacognitive strategies changed. Also, it demonstrated that the instruction affected the students' level of metacognitive strategies' usage.

Keywords: EFL students, English reading comprehension, instruction, metacognitive strategies.

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Authors: Andreas Theissler, Ian Dear

Abstract:

In the automotive industry test drives are being conducted during the development of new vehicle models or as a part of quality assurance of series-production vehicles. The communication on the in-vehicle network, data from external sensors, or internal data from the electronic control units is recorded by automotive data loggers during the test drives. The recordings are used for fault analysis. Since the resulting data volume is tremendous, manually analysing each recording in great detail is not feasible. This paper proposes to use machine learning to support domainexperts by preventing them from contemplating irrelevant data and rather pointing them to the relevant parts in the recordings. The underlying idea is to learn the normal behaviour from available recordings, i.e. a training set, and then to autonomously detect unexpected deviations and report them as anomalies. The one-class support vector machine “support vector data description” is utilised to calculate distances of feature vectors. SVDDSUBSEQ is proposed as a novel approach, allowing to classify subsequences in multivariate time series data. The approach allows to detect unexpected faults without modelling effort as is shown with experimental results on recordings from test drives.

Keywords: Anomaly detection, fault detection, test drive analysis, machine learning.

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Authors: Mohamed Aymen Slim, Afef Abdelkrim, Mohamed Benrejeb

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The handwriting is a physical demonstration of a complex cognitive process learnt by man since his childhood. People with disabilities or suffering from various neurological diseases are facing so many difficulties resulting from problems located at the muscle stimuli (EMG) or signals from the brain (EEG) and which arise at the stage of writing. The handwriting velocity of the same writer or different writers varies according to different criteria: age, attitude, mood, writing surface, etc. Therefore, it is interesting to reconstruct an experimental basis records taking, as primary reference, the writing speed for different writers which would allow studying the global system during handwriting process. This paper deals with a new approach of the handwriting system modeling based on the velocity criterion through the concepts of artificial neural networks, precisely the Radial Basis Functions (RBF) neural networks. The obtained simulation results show a satisfactory agreement between responses of the developed neural model and the experimental data for various letters and forms then the efficiency of the proposed approaches.

Keywords: ElectroMyoGraphic (EMG) signals, Experimental approach, Handwriting process, Radial Basis Functions (RBF) neural networks, Velocity Modeling.

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Authors: Hui J. Gwon, Youn M. Lim, Jong S. Park, Young C. Nho

Abstract:

In this study, hydrogels consisted of polyvinyl alcohol, propylene glycol and β-glucan were developed by radiation technique for wound dressing. The prepared hydrogels were characterized by examining of physical properties such as gel fraction and absorption ratio. The gel fraction and absorption ratio were dependent on the crosslinking density. On observing the wound healing of rat skin, the resulting hydrogels accelerated the wound healing comparing to cotton gauze. Therefore, the PVA/propylene glycol/β-glucan blended hydrogels can greatly accelerate the healing without causing irritation.

Keywords: β-Glucan, poly(vinyl alcohol), propylene glycol, radiation, wound dressing.

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Authors: Najmeh Bolbolamiri, Maryam Setayesh Sanai, Ahmad Mirabadi

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This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.

Keywords: stator currents monitoring, railway points, point failures, fault detection and diagnosis, Kolmogorov-Smirnov test, time-domain analysis.

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Authors: Thaniya Kaosol, Narumol Sohgrathok

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In this paper, a Biochemical Methane Potential (BMP) test provides a measure of the energy production potential from codigestion between the frozen seafood wastewater and the decanter cake. The experiments were conducted in laboratory-scale. The suitable ratio of the frozen seafood wastewater and the decanter cake was observed in the BMP test. The ratio of the co-digestion between the frozen seafood wastewater and the decanter cake has impacts on the biogas production and energy production potential. The best performance for energy production potential using BMP test observed from the 180 ml of the frozen seafood wastewater and 10 g of the decanter cake ratio. This ratio provided the maximum methane production at 0.351 l CH4/g TCODremoval. The removal efficiencies are 76.18%, 83.55%, 43.16% and 56.76% at TCOD, SCOD, TS and VS, respectively. The result can be concluded that the decanter cake can improve the energy production potential of the frozen seafood wastewater. The energy provides from co-digestion between frozen seafood wastewater and decanter cake approximately 19x109 MJ/year in Thailand.

Keywords: Frozen seafood wastewater, decanter cake, biogas, methane, BMP test.

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Authors: Chang S. Woo, Hyun S. Park, Wan D. Kim

Abstract:

Fatigue life prediction and evaluation are the key technologies to assure the safety and reliability of automotive rubber components. The objective of this study is to develop the fatigue analysis process for vulcanized rubber components, which is applicable to predict fatigue life at initial product design step. Fatigue life prediction methodology of vulcanized natural rubber was proposed by incorporating the finite element analysis and fatigue damage parameter of maximum strain appearing at the critical location determined from fatigue test. In order to develop an appropriate fatigue damage parameter of the rubber material, a series of displacement controlled fatigue test was conducted using threedimensional dumbbell specimen with different levels of mean displacement. It was shown that the maximum strain was a proper damage parameter, taking the mean displacement effects into account. Nonlinear finite element analyses of three-dimensional dumbbell specimens were performed based on a hyper-elastic material model determined from the uni-axial tension, equi-biaxial tension and planar test. Fatigue analysis procedure employed in this study could be used approximately for the fatigue design.

Keywords: Rubber, Material test, Finite element analysis, Strain, Fatigue test, Fatigue life prediction.

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Authors: Ahmad Forouzantabar

Abstract:

this paper presents a novel neural network controller with composite adaptation low to improve the trajectory tracking problems of biped robots comparing with classical controller. The biped model has 5_link and 6 degrees of freedom and actuated by Plated Pneumatic Artificial Muscle, which have a very high power to weight ratio and it has large stoke compared to similar actuators. The proposed controller employ a stable neural network in to approximate unknown nonlinear functions in the robot dynamics, thereby overcoming some limitation of conventional controllers such as PD or adaptive controllers and guarantee good performance. This NN controller significantly improve the accuracy requirements by retraining the basic PD/PID loop, but adding an inner adaptive loop that allows the controller to learn unknown parameters such as friction coefficient, therefore improving tracking accuracy. Simulation results plus graphical simulation in virtual reality show that NN controller tracking performance is considerably better than PD controller tracking performance.

Keywords: Biped robot, Neural network, Plated Pneumatic Artificial Muscle, Composite adaptation

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Authors: Kitti Leangkrua

Abstract:

This paper presents a risk-based maintenance strategy of a power transformer in order to optimize operating and maintenance costs. The methodology involves the study and preparation of a database for the collection the technical data and test data of a power transformer. An evaluation of the overall condition of each transformer is performed by a program developed as a result of the measured results; in addition, the calculation of the main equipment separation to the overall condition of the transformer (% HI) and the criteria for evaluating the importance (% ImI) of each location where the transformer is installed. The condition assessment is performed by analysis test data such as electrical test, insulating oil test and visual inspection. The condition of the power transformer will be classified from very poor to very good condition. The importance is evaluated from load criticality, importance of load and failure consequence. The risk matrix is developed for evaluating the risk of each power transformer. The high risk power transformer will be focused firstly. The computerized program is developed for practical use, and the maintenance strategy of a power transformer can be effectively managed.

Keywords: Asset management, risk-based maintenance, power transformer, health index.

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Authors: I. Parkova, A. Vališevskis, A. Viļumsone

Abstract:

Nocturnal enuresis or bed-wetting is intermittent incontinence during sleep of children after age 5 that may precipitate wide range of behavioral and developmental problems. One of the non-pharmacological treatment methods is the use of a bed-wetting alarm system. In order to improve comfort conditions of nocturnal enuresis alarm system, modular moisture sensor should be replaced by a textile sensor. In this study behavior and moisture detection speed of woven and sewn sensors were compared by analyzing change in electrical resistance after solution (salt water) was dripped on sensor samples. Material of samples has different structure and yarn location, which affects solution detection rate. Sensor system circuit was designed and two sensor tests were performed: system activation test and false alarm test to determine the sensitivity of the system and activation threshold. Sewn sensor had better result in system’s activation test – faster reaction, but woven sensor had better result in system’s false alarm test – it was less sensitive to perspiration simulation. After experiments it was found that the optimum switching threshold is 3V in case of 5V input voltage, which provides protection against false alarms, for example – during intensive sweating.

Keywords: Conductive yarns, moisture textile sensor.

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Authors: Abiodun M. Lawal, Benjamin O. Olley

Abstract:

Long Distance Truck Drivers (LDTDs) have been found to be a high risk group in the spread of HIV/AIDS globally; perhaps, due to their high Sexual Risk Behaviours (SRBs). Interventions for reducing SRBs in trucking population have not been fully exploited. A quasi-experimental control group pretest-posttest design was used to assess the efficacy of psycho-education and behavioural skills training in reducing SRBs among LDTDs. Sixteen drivers rivers were randomly assigned into either experimental or control groups using balloting technique. Questionnaire was used as an instrument for data collection. Repeated measures t-test and independent t-test were used to test hypotheses. Intervention had significant effect on the SRBs among LDTDs at post-test (t{7}= 6.01, p<.01) and at follow up (t{7} = 6.42, p<.01). No significant difference in sexual risk behaviour of LDTDs at post-test and at follow-up stage. Similarly, intervention had significant effects on sexual risk behaviour at post-test (t {14} = - 4.69, p<.05) and at follow-up (t {14} = -9.56, p<.05) respectively. At post-test and follow-up stages, drivers in experimental group reported reduced SRBs than those in control group. Drivers in experimental group reported lower sexual risk behaviour a week after intervention as well as at three months follow-up than those in control group. It is concluded that HIV/AIDS preventive intervention that provides the necessary informational and behavioural skills content can significantly impact long distance truck drivers’ sexual risk behaviours.

Keywords: HIV/AIDS interventions, Long distance truck drivers, Nigeria, Sexual risk behaviours.

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Authors: Daniel L. Clinciu, Ikrom Abdulaev, Brian D. Oscar

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Various personality profile tests are used to identify personality strengths and limits in individuals, helping both individuals and managers to optimize work and team effort in organizations. One such test, the Hartman’s personality profile, emphasizes four driving "core motives" influenced or affected by both strengths and limitations classified into four colors: Red - motivated by power; Blue - discipline and loyalty; White - peace; and Yellow – fun loving. Two shortcomings of Hartman’s personality test are noted; 1) only one selection for every item / situation allowed and 2) selection of an item / option even if not applicable. A test taker may be as much nurturing as he is opinionated but since “opinionated” seems less attractive the individual would likely select nurturing, causing a misidentification in personality strengths and limits. Since few individuals have a “strong” personality, it is difficult to assess their true personality strengths and limits allowing only one choice or requiring unwanted choices, undermining the potential of the test. We modified Hartman’s personality profile allowing test takers to make either multiple choices for any item / situation or leave them blank if applicable. Sixty-eight participants (38 males and 30 females), 17 - 49 years old, from countries in Asia, Europe, N. America, CIS, Africa, Latin America, and Oceania were included. 58 participants (85.3%) reported the modified test, allowing multiple / no choices better identified their personality strengths and limits, while 10 participants (14.7%) expressed the original (one choice version) was sufficient. The overall results show that our modified test enhanced the identification and balance of core personalities’ strengths and limits, aiding test takers, managers and organizations to better assess individual characteristics, particularly useful in making task-related, teamwork, and management decisions.

Keywords: Organizational behavior, personality tests, personality limitations, personality strengths, task management, team work.

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Authors: Fatemeh Mosalman Yazdi

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One of the most important requirements for the operation and planning activities of an electrical utility is the prediction of load for the next hour to several days out, known as short term load forecasting. This paper presents the development of an artificial neural network based short-term load forecasting model. The model can forecast daily load profiles with a load time of one day for next 24 hours. In this method can divide days of year with using average temperature. Groups make according linearity rate of curve. Ultimate forecast for each group obtain with considering weekday and weekend. This paper investigates effects of temperature and humidity on consuming curve. For forecasting load curve of holidays at first forecast pick and valley and then the neural network forecast is re-shaped with the new data. The ANN-based load models are trained using hourly historical. Load data and daily historical max/min temperature and humidity data. The results of testing the system on data from Yazd utility are reported.

Keywords: Artificial neural network, Holiday forecasting, pickand valley load forecasting, Short-term load-forecasting.

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Authors: Wen-Chi Liu

Abstract:

This study applies a simple and powerful nonlinear unit root test to test the validity of long-run purchasing power parity (PPP)  in a sample of 10 East-Asian countries (i.e., China, Hong Kong,  Indonesia, Japan, Korea, Malaysia, Philippines, Singapore, Taiwan  and Thailand) over the period of March 1985 to September 2008. The empirical results indicate that PPP holds true for half of these 10  East-Asian countries under study, and the adjustment toward PPP is found to be nonlinear and in an asymmetric way. 

 

Keywords: Purchasing Power Parity, East-Asian Countries, Nonlinear Unit Root Test, Asymmetry.

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Authors: Chuang-Chun Chiou

Abstract:

Ageing population is a global trend; therefore the need of care service has been increasing dramatically. There are three basic forms of service delivered to the elderly: institution, community, and home. Particularly, the institutional service can be seen as an extension of medical service. The nursing home or so-called care home which is equipped with professional staff and facilities can provide a variety of service including rehabilitation service, short-term care, and long term care. Similar to hospital and other health care service, care home service do need to provide quality and cost-effective service to satisfy the dwellers. The main purpose of this paper is to show how lean thinking and service innovation can be applied to care home operation. The issues and key factors of implementing lean practice are discussed.

Keywords: Lean, Service improvement, SERVQUAL, Care home service.

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