Search results for: Multivariate Adaptive Regression Splines Pulmonary Function Test

Authors: Adnan Al-Smadi

Abstract:

One of the primary uses of higher order statistics in signal processing has been for detecting and estimation of non- Gaussian signals in Gaussian noise of unknown covariance. This is motivated by the ability of higher order statistics to suppress additive Gaussian noise. In this paper, several methods to test for non- Gaussianity of a given process are presented. These methods include histogram plot, kurtosis test, and hypothesis testing using cumulants and bispectrum of the available sequence. The hypothesis testing is performed by constructing a statistic to test whether the bispectrum of the given signal is non-zero. A zero bispectrum is not a proof of Gaussianity. Hence, other tests such as the kurtosis test should be employed. Examples are given to demonstrate the performance of the presented methods.

Keywords: Non-Gaussian, bispectrum, kurtosis, hypothesistesting, histogram.

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Authors: Sufian Ashraf Mazhari, Surendra Kumar

Abstract:

In this paper performance of Puma 560 manipulator is being compared for hybrid gradient descent and least square method learning based ANFIS controller with hybrid Genetic Algorithm and Generalized Pattern Search tuned radial basis function based Neuro-Fuzzy controller. ANFIS which is based on Takagi Sugeno type Fuzzy controller needs prior knowledge of rule base while in radial basis function based Neuro-Fuzzy rule base knowledge is not required. Hybrid Genetic Algorithm with generalized Pattern Search is used for tuning weights of radial basis function based Neuro- fuzzy controller. All the controllers are checked for butterfly trajectory tracking and results in the form of Cartesian and joint space errors are being compared. ANFIS based controller is showing better performance compared to Radial Basis Function based Neuro-Fuzzy Controller but rule base independency of RBF based Neuro-Fuzzy gives it an edge over ANFIS

Keywords: Neuro-Fuzzy, Robotic Control, RBFNF, ANFIS, Hybrid GA.

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Authors: Mustafa Sahin, İlkay Yavrucuk

Abstract:

This paper presents a wind turbine envelope protection control algorithm that protects Variable Speed Variable Pitch (VSVP) wind turbines from damage during operation throughout their below and above rated regions, i.e. from cut-in to cut-out wind speed. The proposed approach uses a neural network that can adapt to turbines and their operating points. An algorithm monitors instantaneous wind and turbine states, predicts a wind speed that would push the turbine to a pre-defined envelope limit and, when necessary, realizes an avoidance action. Simulations are realized using the MS Bladed Wind Turbine Simulation Model for the NREL 5 MW wind turbine equipped with baseline controllers. In all simulations, through the proposed algorithm, it is observed that the turbine operates safely within the allowable limit throughout the below and above rated regions. Two example cases, adaptations to turbine operating points for the below and above rated regions and protections are investigated in simulations to show the capability of the proposed envelope protection system (EPS) algorithm, which reduces excessive wind turbine loads and expectedly increases the turbine service life.

Keywords: Adaptive envelope protection control, limit detection and avoidance, neural networks, ultimate load reduction, wind turbine power control.

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Authors: Rawya Rizk, Rehab Abdel-Kader, Rabab Ramadan

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Unlike the best effort service provided by the internet today, next-generation wireless networks will support real-time applications. This paper proposes an adaptive early packet discard (AEPD) policy to improve the performance of the real time TCP traffic over ATM networks and avoid the fragmentation problem. Three main aspects are incorporated in the proposed policy. First, providing quality-of-service (QoS) guaranteed for real-time applications by implementing a priority scheduling. Second, resolving the partially corrupted packets problem by differentiating the buffered cells of one packet from another. Third, adapting a threshold dynamically using Fuzzy logic based on the traffic behavior to maintain a high throughput under a variety of load conditions. The simulation is run for two priority classes of the input traffic: real time and non-real time classes. Simulation results show that the proposed AEPD policy improves throughput and fairness over that using static threshold under the same traffic conditions.

Keywords: Early packet discard, Fuzzy logic, packet dropping policies, quality-of-service (QoS), TCP over ATM

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Authors: Refaat M Mohamed, Ayman El-Baz, Aly A. Farag

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This paper introduces a novel approach to estimate the clique potentials of Gibbs Markov random field (GMRF) models using the Support Vector Machines (SVM) algorithm and the Mean Field (MF) theory. The proposed approach is based on modeling the potential function associated with each clique shape of the GMRF model as a Gaussian-shaped kernel. In turn, the energy function of the GMRF will be in the form of a weighted sum of Gaussian kernels. This formulation of the GMRF model urges the use of the SVM with the Mean Field theory applied for its learning for estimating the energy function. The approach has been tested on synthetic texture images and is shown to provide satisfactory results in retrieving the synthesizing parameters.

Keywords: Image Modeling, MRF, Parameters Estimation, SVM Learning.

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Authors: Martin Doran, Roy Sterritt, George Wilkie

Abstract:

The majority of today’s mobile robots are very dependent on battery power. Mobile robots can operate untethered for a number of hours but eventually they will need to recharge their batteries in-order to continue to function. While computer processing and sensors have become cheaper and more powerful each year, battery development has progress very little. They are slow to re-charge, inefficient and lagging behind in the general progression of robotic development we see today. However, batteries are relatively cheap and when fully charged, can supply high power output necessary for operating heavy mobile robots. As there are no cheap alternatives to batteries, we need to find efficient ways to manage the power that batteries provide during their operational lifetime. This paper proposes the use of autonomic principles of self-adaption to address the behavioral changes a battery experiences as it gets older. In life, as we get older, we cannot perform tasks in the same way as we did in our youth; these tasks generally take longer to perform and require more of our energy to complete. Batteries also suffer from a form of degradation. As a battery gets older, it loses the ability to retain the same charge capacity it would have when brand new. This paper investigates how we can adapt the current state of a battery charge and cycle count, to the requirements of a mobile robot to perform its tasks.

Keywords: Autonomic, self-adaptive, self-optimizing, degradation.

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Authors: Kyaw Myo Lin

Abstract:

This paper presents small signal stability study carried over the 140-Bus, 31-Machine, 5-Area MEPE system and validated on free and open source software: PSAT. Well-established linearalgebra analysis, eigenvalue analysis, is employed to determine the small signal dynamic behavior of test system. The aspects of local and interarea oscillations which may affect the operation and behavior of power system are analyzed. Eigenvalue analysis is carried out to investigate the small signal behavior of test system and the participation factors have been determined to identify the participation of the states in the variation of different mode shapes. Also, the variations in oscillatory modes are presented to observe the damping performance of the test system.

Keywords: Eigenvalue analysis, Mode shapes, MEPE test system, Participation factors, Power System oscillations.

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Authors: Kazumoto Tanaka, Takayuki Fujino

Abstract:

Sports games conducted as a group are a form of therapeutic exercise for aged people with decreased strength and for people suffering from permanent damage of stroke and other conditions. However, it is difficult for patients with different athletic abilities to play a game on an equal footing. This study specifically examines a computer video game designed for therapeutic exercise, and a game system with support given depending on athletic ability. Thereby, anyone playing the game can participate equally. This video-game, to be specific, is a popular variant of balloon volleyball, in which players hit a balloon by hand before it falls to the floor. In this game system, each player plays the game watching a monitor on which the system displays tailor-made video-game images adjusted to the person’s athletic ability, providing players with player-adaptive assist support. We have developed a multiplayer game system with an image generation technique for the tailor-made video-game and conducted tests to evaluate it.

Keywords: Therapeutic exercise, computer video game, disability-adaptive assist, tailor-made video-game image.

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Authors: H. Ogras, M. Turk

Abstract:

In this study, a system of encryption based on chaotic sequences is described. The system is used for encrypting digital image data for the purpose of secure image transmission. An image secure communication scheme based on Logistic map chaotic sequences with a nonlinear function is proposed in this paper. Encryption and decryption keys are obtained by one-dimensional Logistic map that generates secret key for the input of the nonlinear function. Receiver can recover the information using the received signal and identical key sequences through the inverse system technique. The results of computer simulations indicate that the transmitted source image can be correctly and reliably recovered by using proposed scheme even under the noisy channel. The performance of the system will be discussed through evaluating the quality of recovered image with and without channel noise.

Keywords: Digital image, Image encryption, Secure communication

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Authors: Ammar Elyas babiker, M.Nordin B. Zakaria, Hassan Yosif, Samir B. Ibrahim

Abstract:

Variable channel conditions in underwater networks, and variable distances between sensors due to water current, leads to variable bit error rate (BER). This variability in BER has great effects on energy efficiency of error correction techniques used. In this paper an efficient energy adaptive hybrid error correction technique (AHECT) is proposed. AHECT adaptively changes error technique from pure retransmission (ARQ) in a low BER case to a hybrid technique with variable encoding rates (ARQ & FEC) in a high BER cases. An adaptation algorithm depends on a precalculated packet acceptance rate (PAR) look-up table, current BER, packet size and error correction technique used is proposed. Based on this adaptation algorithm a periodically 3-bit feedback is added to the acknowledgment packet to state which error correction technique is suitable for the current channel conditions and distance. Comparative studies were done between this technique and other techniques, and the results show that AHECT is more energy efficient and has high probability of success than all those techniques.

Keywords: Underwater communication, wireless sensornetworks, error correction technique, energy efficiency

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Authors: Liubov Evstigneeva

Abstract:

In this paper an attempt is made to establish causal nexuses between innovation and international trade in Russia. The topicality of this issue is determined by the necessity of choosing policy instruments for economic modernization and transition to innovative development. The vector auto regression (VAR) model and Granger test are applied for the Russian monthly data from 2005 until the second quartile of 2015. Both lagged import and export at the national level cause innovation, the latter starts to stimulate foreign trade since it is a remote lag. In comparison to aggregate data, the results by patent’s categories are more diverse. Importing technologies from foreign countries stimulates patent activity, while innovations created in Russia are only Granger causality for import to Commonwealth of Independent States.

Keywords: Export, import, innovation, patents.

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Authors: V. Vargas-Alejo, L. E. Montero-Moguel

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Understanding the concept of function has been important in mathematics education for many years. In this study, the models built by a group of five business administration and accounting undergraduate students when carrying out a population growth activity are analyzed. The theoretical framework is the Models and Modeling Perspective. The results show how the students included tables, graphics, and algebraic representations in their models. Using technology was useful to interpret, describe, and predict the situation. The first model, the students built to describe the situation, was linear. After that, they modified and refined their ways of thinking; finally, they created exponential growth. Modeling the activity was useful to deep on mathematical concepts such as covariation, rate of change, and exponential function also to differentiate between linear and exponential growth.

Keywords: Covariation reasoning, exponential function, modeling, representations.

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Authors: Khadiga Kahwa, Aniza Ismail

Abstract:

Depression, anxiety, and stress are associated with decreased role functioning, productivity, and quality of life. International students are more prone to psychological distress as they face many stressors while studying abroad. The objectives of the study were to determine the prevalence and associated factors of depression, anxiety, and stress among international students, their help-seeking behavior, and their awareness of the available on-campus mental support services. A cross-sectional study with a purposive sampling method was performed on 280 international students at Universiti Kebangsaan Malaysia (UKM) between the age of 18 and 35 years. The Depression Anxiety Stress Scale-21 (DASS-21) questionnaire was used anonymously to assess the mental health of students. Socio-demographic, help-seeking behavior, and awareness data were obtained. Independent sample t-test, one-way ANOVA test, and multiple linear regression were used to explore associated factors. The overall prevalence of depression, anxiety, and stress among international students were 58.9%, 71.8%, and 53.9%, respectively. Age was significantly associated with depression and anxiety. Ethnicity showed a significant association with depression and stress. No other factors were found to be significantly associated with psychological distress. Only 9.6% of the international students had sought help from on-campus mental support services. Students who were aware of the presence of such services were only 21.4% of the participants. In conclusion, this study addressed the gap in the literature on the mental health of international students and provided data that could be used in intervention programs to improve the mental health of the increasing number of international students in Malaysia.

Keywords: Anxiety, depression, stress, help-seeking behavior, students.

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Authors: Changho Han, Jaemin Lee, Li Hua, Seokkwon Jeong

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Design of membership function ranges in fuzzy logic control (FLC) is presented for robust control of a variable speed refrigeration system (VSRS). The criterion values of the membership function ranges can be carried out from the static experimental data, and two different values are offered to compare control performance. Some simulations and real experiments for the VSRS were conducted to verify the validity of the designed membership functions. The experimental results showed good agreement with the simulation results, and the error change rate and its sampling time strongly affected the control performance at transient state of the VSRS.

Keywords: Variable speed refrigeration system, Fuzzy logic control, membership function range, control performance.

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Authors: Jiming Yang

Abstract:

A kind of singularly perturbed boundary value problems is under consideration. In order to obtain its approximation, simple upwind difference discretization is applied. We use a moving mesh iterative algorithm based on equi-distributing of the arc-length function of the current computed piecewise linear solution. First, a maximum norm a posteriori error estimate on an arbitrary mesh is derived using a different method from the one carried out by Chen [Advances in Computational Mathematics, 24(1-4) (2006), 197-212.]. Then, basing on the properties of discrete Green-s function and the presented posteriori error estimate, we theoretically prove that the discrete solutions computed by the algorithm are first-order uniformly convergent with respect to the perturbation parameter ε.

Keywords: Convergence analysis, green's function, singularly perturbed, equi-distribution, moving mesh.

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Authors: B. Nassar, W. Hussein, M. Mokhtar

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The critical concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission, but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the problem above coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions, and the results show that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Keywords: Space telemetry monitoring, multivariate analysis, PCA algorithm, space operations.

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Authors: S. Gokul Prassad, S. Aakash, K. Malar Mohan

Abstract:

In the process to cope with the challenges faced by the automobile industry in providing ride comfort, the electronics and control systems play a vital role. The control systems in an automobile monitor various parameters, controls the performances of the systems, thereby providing better handling characteristics. The automobile suspension system is one of the main systems that ensure the safety, stability and comfort of the passengers. The system is solely responsible for the isolation of the entire automobile from harmful road vibrations. Thus, integration of the control systems in the automobile suspension system would enhance its performance. The diverse road conditions of India demand the need of an efficient suspension system which can provide optimum ride comfort in all road conditions. For any passenger vehicle, the design of the suspension system plays a very important role in assuring the ride comfort and handling characteristics. In recent years, the air suspension system is preferred over the conventional suspension systems to ensure ride comfort. In this article, the ride comfort of the adaptive suspension system is compared with that of the passive suspension system. The schema is created in MATLAB/Simulink environment. The system is controlled by a proportional integral differential controller. Tuning of the controller was done with the Particle Swarm Optimization (PSO) algorithm, since it suited the problem best. Ziegler-Nichols and Modified Ziegler-Nichols tuning methods were also tried and compared. Both the static responses and dynamic responses of the systems were calculated. Various random road profiles as per ISO 8608 standard are modelled in the MATLAB environment and their responses plotted. Open-loop and closed loop responses of the random roads, various bumps and pot holes are also plotted. The simulation results of the proposed design are compared with the available passive suspension system. The obtained results show that the proposed adaptive suspension system is efficient in controlling the maximum over shoot and the settling time of the system is reduced enormously.

Keywords: Automobile suspension, MATLAB, control system, PID, PSO.

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Authors: Amarunnishad T.M., Govindan V.K., Abraham T. Mathew

Abstract:

An image compression method has been developed using fuzzy edge image utilizing the basic Block Truncation Coding (BTC) algorithm. The fuzzy edge image has been validated with classical edge detectors on the basis of the results of the well-known Canny edge detector prior to applying to the proposed method. The bit plane generated by the conventional BTC method is replaced with the fuzzy bit plane generated by the logical OR operation between the fuzzy edge image and the corresponding conventional BTC bit plane. The input image is encoded with the block mean and standard deviation and the fuzzy bit plane. The proposed method has been tested with test images of 8 bits/pixel and size 512×512 and found to be superior with better Peak Signal to Noise Ratio (PSNR) when compared to the conventional BTC, and adaptive bit plane selection BTC (ABTC) methods. The raggedness and jagged appearance, and the ringing artifacts at sharp edges are greatly reduced in reconstructed images by the proposed method with the fuzzy bit plane.

Keywords: Image compression, Edge detection, Ground truth image, Peak signal to noise ratio

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Authors: S. Sowmyayani, P. Arockia Jansi Rani

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This paper integrates Octagon and Square Search pattern (OCTSS) motion estimation algorithm into H.264/AVC (Advanced Video Coding) video codec in Adaptive Group of Pictures (AGOP) mode. AGOP structure is computed based on scene change in the video sequence. Octagon and square search pattern block-based motion estimation method is implemented in inter-prediction process of H.264/AVC. Both these methods reduce bit rate and computational complexity while maintaining the quality of the video sequence respectively. Experiments are conducted for different types of video sequence. The results substantially proved that the bit rate, computation time and PSNR gain achieved by the proposed method is better than the existing H.264/AVC with fixed GOP and AGOP. With a marginal gain in quality of 0.28dB and average gain in bitrate of 132.87kbps, the proposed method reduces the average computation time by 27.31 minutes when compared to the existing state-of-art H.264/AVC video codec.

Keywords: Block Distortion Measure, Block Matching Algorithms, H.264/AVC, Motion estimation, Search patterns, Shot cut detection.

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Authors: Meryem Elif Çelebi Yakartepe, Ayşe Betül Gökarslan

Abstract:

Sustainable architecture is an approach which accepts the climatic and tomographic data as a necessary preliminary data package by favoring the relationship between human and nature and which strives to use the sources economically. The reflection of sustainable architecture approach to preservation - restoration discipline is including the architectural inheritance to daily life with its unique or new function by restoring it.

The restoration decisions of Yılan Kırkan Fountain in Isparta province of Turkey is a good example of the works of sustainable architecture and the preservation of architectural inheritance. It is aimed that Yılan Kırkan Fountain, which is desolate nowadays with no function, to be restored by the local authorities and university, included in the daily life and continue its function.

Keywords: Conservation and Restoration, Sustainable Architecture, Movement Technique, Isparta Yılan Kırkan Fountain.

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Authors: S. Areerachakul

Abstract:

Nowadays, several techniques such as; Fuzzy Inference System (FIS) and Neural Network (NN) are employed for developing of the predictive models to estimate parameters of water quality. The main objective of this study is to compare between the predictive ability of the Adaptive Neuro-Fuzzy Inference System (ANFIS) model and Artificial Neural Network (ANN) model to estimate the Biochemical Oxygen Demand (BOD) on data from 11 sampling sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2004-2011. The five parameters of water quality namely Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen (NO3N), and Total Coliform bacteria (T-coliform) are used as the input of the models. These water quality indices affect the biochemical oxygen demand. The experimental results indicate that the ANN model provides a higher correlation coefficient (R=0.73) and a lower root mean square error (RMSE=4.53) than the corresponding ANFIS model.

Keywords: adaptive neuro-fuzzy inference system, artificial neural network, biochemical oxygen demand, surface water.

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Authors: Sarit Rashkovits, Yael Livne

Abstract:

The study investigates the relationship between education level, workplace learning behaviors, psychological empowerment and burnout in a sample of 191 teachers. We hypothesized that education level will positively affect psychological state of increased empowerment and decreased burnout, and we purposed that these effects will be mediated by workplace learning behaviors. We used multiple regression analyses to test the model that included also the 6 following control variables: The teachers' age, gender, and teaching tenure; the schools' religious level, the pupils' needs: regular/ special needs, and the class level: elementary/ high school. The results support the purposed mediating model.

Keywords: Education level, Learning behaviors, Psychological empowerment, Burnout.

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Authors: A. Bakhtiar, B. Purwanggono, N. Metasari

Abstract:

PT XYZ is a bottled drinking water company. To preserve production resources owned by the company so that the resources could be utilized well, it has implemented maintenance management system, which has important role in company's profitability, and is one of the factors influenced overall company's performance. Yet, up to now the company has never measured maintenance activities' contribution to company's performance. Performance evaluation is done according to adapted Balanced Scorecard model fitted to maintenance function context. This model includes six perspectives: innovation and growth, production, maintenance, environment, costumer, and finance. Actual performance measurement is done through Analytic Hierarchy Process and Objective Matrix. From the research done, we can conclude that the company's maintenance function is categorized in moderate performance. But, there are some indicators which has high priority but low performance, which are: costumers' complain rate, work lateness rate, and Return on Investment.

Keywords: Maintenance, performance, balanced scorecard, objective matrix.

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Authors: Melvin A. Ballera

Abstract:

Prior literature in the field of adaptive and personalized learning sequence in e-learning have proposed and implemented various mechanisms to improve the learning process such as individualization and personalization, but complex to implement due to expensive algorithmic programming and need of extensive and prior data. The main objective of personalizing learning sequence is to maximize learning by dynamically selecting the closest teaching operation in order to achieve the learning competency of learner. In this paper, a revolutionary technique has been proposed and tested to perform individualization and personalization using modified reversed roulette wheel selection algorithm that runs at O(n). The technique is simpler to implement and is algorithmically less expensive compared to other revolutionary algorithms since it collects the dynamic real time performance matrix such as examinations, reviews, and study to form the RWSA single numerical fitness value. Results show that the implemented system is capable of recommending new learning sequences that lessens time of study based on student's prior knowledge and real performance matrix.

Keywords: E-learning, fitness value, personalized learning sequence, reversed roulette wheel selection algorithms.

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Authors: S. K. Appiah, E. N. Aidoo, D. Asamoah Owusu, M. W. Nuonabuor

Abstract:

Urbanization remains one of the unique predominant factors which is linked to the destruction of urban environment and its associated cases of soil contamination by heavy metals through the natural and anthropogenic activities. These activities are important sources of toxic heavy metals such as arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), and lead (Pb), nickel (Ni) and zinc (Zn). Often, these heavy metals lead to increased levels in some areas due to the impact of atmospheric deposition caused by their proximity to industrial plants or the indiscriminately burning of substances. Information gathered on potentially hazardous levels of these heavy metals in soils leads to establish serious health and urban agriculture implications. However, characterization of spatial variations of soil contamination by heavy metals in Ghana is limited. Kumasi is a Metropolitan city in Ghana, West Africa and is challenged with the recent spate of deteriorating soil quality due to rapid economic development and other human activities such as “Galamsey”, illegal mining operations within the metropolis. The paper seeks to use both univariate and multivariate geostatistical techniques to assess the spatial distribution of heavy metals in soils and the potential risk associated with ingestion of sources of soil contamination in the Metropolis. Geostatistical tools have the ability to detect changes in correlation structure and how a good knowledge of the study area can help to explain the different scales of variation detected. To achieve this task, point referenced data on heavy metals measured from topsoil samples in a previous study, were collected at various locations. Linear models of regionalisation and coregionalisation were fitted to all experimental semivariograms to describe the spatial dependence between the topsoil heavy metals at different spatial scales, which led to ordinary kriging and cokriging at unsampled locations and production of risk maps of soil contamination by these heavy metals. Results obtained from both the univariate and multivariate semivariogram models showed strong spatial dependence with range of autocorrelations ranging from 100 to 300 meters. The risk maps produced show strong spatial heterogeneity for almost all the soil heavy metals with extremely risk of contamination found close to areas with commercial and industrial activities. Hence, ongoing pollution interventions should be geared towards these highly risk areas for efficient management of soil contamination to avert further pollution in the metropolis.

Keywords: Coregionalization, ordinary cokriging, multivariate geostatistical analysis, soil contamination, soil heavy metals, risk maps, spatial distribution.

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Authors: Youcef Bekakra, Djilani Ben attous

Abstract:

In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.

Keywords: Induction motor drive, field oriented control, model reference adaptive system (MRAS), particle swarm optimization (PSO).

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Authors: Aseem Rajvanshi, Pankaj Kumar Pandey

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Increase in population has increased the demand of energy to fulfill all its needs. This will result in burden on fossil fuels especially crude oil. Waste oil due to its disposal problem creates environmental degradation. In this context, this paper studies utilization of waste cooking oil and waste motor sludge for making lubricating grease. Experimental studies have been performed by variation in time and concentration of mixture of waste cooking oil and waste motor sludge. The samples were analyzed using penetration test (ASTM D-217), dropping point (ASTM D-566), work penetration (ASTM D-217) and copper strip test (ASTM D-408). Among 6 samples, sample 6 gives the best results with a good drop point and a fine penetration value. The dropping point and penetration test values were found to be 205 °C and 315, respectively. The penetration value falls under the category of NLGI (National Lubricating Grease Institute) consistency number 1.

Keywords: Crude oil, copper strip corrosion test, dropping point, penetration test.

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Authors: Guojia Ma, Guoqiang Lin, Shuili Gong, Gang Sun, Dawang Wang

Abstract:

A diamond-like carbon (DLC) based solid-lubricant film was designed and DLC films were successfully prepared using a microwave plasma enhanced magnetron sputtering deposition technology. Post-test characterizations including Raman spectrometry, X-ray diffraction, nano-indentation test, adhesion test, friction coefficient test were performed to study the influence of substrate bias voltage on the mechanical properties of the W- and S-doped DLC films. The results indicated that the W- and S-doped DLC films also had the typical structure of DLC films and a better mechanical performance achieved by the application of a substrate bias of -200V.

Keywords: Adhesive Strength, Coefficient of Friction, Substrate Bias, W- and S-doped DLC film

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Authors: Ali E. Abbas

Abstract:

This paper highlights some of the normative issues that might result by setting independent thresholds in risk analyses and particularly with safety regions. A second objective is to explain how such regions can be specified appropriately in a meaningful way. We start with a review of the importance of setting deterministic trade-offs among target requirements. We then show how to determine safety regions for risk analysis appropriately using utility functions.

Keywords: Decision analysis, thresholds, risk, reliability.

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Authors: Yuzhi Cai

Abstract:

In this paper, we discuss a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. Together with a combining forecasts technique, we then predict USD to GBP currency exchange rates. Combined forecasts contain all the information captured by the fitted QAR models at different quantile levels and are therefore better than those obtained from individual models. Our results show that an unequally weighted combining method performs better than other forecasting methodology. We found that a median AR model can perform well in point forecasting when the predictive density functions are symmetric. However, in practice, using the median AR model alone may involve the loss of information about the data captured by other QAR models. We recommend that combined forecasts should be used whenever possible.

Keywords: Exchange rate, quantile regression, combining forecasts.

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