Search results for: computer aided prediction.

Authors: Jun Wan, Zehua Chen, Yingwu Chen, Zhidong Bai

Abstract:

Classification is an interesting problem in functional data analysis (FDA), because many science and application problems end up with classification problems, such as recognition, prediction, control, decision making, management, etc. As the high dimension and high correlation in functional data (FD), it is a key problem to extract features from FD whereas keeping its global characters, which relates to the classification efficiency and precision to heavens. In this paper, a novel automatic method which combined Genetic Algorithm (GA) and classification algorithm to extract classification features is proposed. In this method, the optimal features and classification model are approached via evolutional study step by step. It is proved by theory analysis and experiment test that this method has advantages in improving classification efficiency, precision and robustness whereas using less features and the dimension of extracted classification features can be controlled.

Keywords: Classification, functional data, feature extraction, genetic algorithm, wavelet.

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Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

Abstract:

Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is easy to get a dataset of interacting proteins as positive examples, there are no experimentally confirmed non-interacting proteins to be considered as negative examples. Therefore, in this paper we solve this problem as a one-class classification problem using one-class support vector machines (SVM). Using only positive examples (interacting protein pairs) in training phase, the one-class SVM achieves accuracy of about 80%. These results imply that protein-protein interaction can be predicted using one-class classifier with comparable accuracy to the binary classifiers that use artificially constructed negative examples.

Keywords: Bioinformatics, Protein-protein interactions, One-Class Support Vector Machines

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Authors: Zerarka Hizia, Akchiche Mustapha, Prunier Florent

Abstract:

The landslide of Ain El Hammam (AEH) is characterized by a complex geology and a high hydrogeology hazard. AEH's perpetual reactivation compels us to look closely at its triggers and to better understand the mechanisms of its evolution in mass and in depth. This study builds a numerical model to simulate the influencing factors such as precipitation, non-saturation, and pore pressure fluctuations, using Plaxis software. For a finer analysis of instabilities, we use Hill's criterion, based on the sign of the second order work, which is the most appropriate material stability criterion for non-associated elastoplastic materials. The results of this type of calculation allow us, in theory, to predict the shape and position of the slip surface(s) which are liable to ground movements of the slope, before reaching the rupture given by the plastic limit of Mohr Coulomb. To validate the numerical model, an analysis of inclinometer measures is performed to confirm the direction of movement and kinematic of the sliding mechanism of AEH’s slope.

Keywords: Landslide, second order work, precipitation, inclinometers.

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Authors: Bo-Wun Huang, Jao-Hwa Kuang, J.-G. Tseng, Yan-De Wu

Abstract:

An investigation of noise in a micro stepping motor is considered to study in this article. Because of the trend towards higher precision and more and more small 3C (including Computer, Communication and Consumer Electronics) products, the micro stepping motor is frequently used to drive the micro system or the other 3C products. Unfortunately, noise in a micro stepped motor is too large to accept by the customs. To depress the noise of a micro stepped motor, the dynamic characteristics in this system must be studied. In this article, a Visual Basic (VB) computer program speed controlled micro stepped motor in a digital camera is investigated. Karman KD2300-2S non-contract eddy current displacement sensor, probe microphone, and HP 35670A analyzer are employed to analyze the dynamic characteristics of vibration and noise in a motor. The vibration and noise measurement of different type of bearings and different treatment of coils are compared. The rotating components, bearings, coil, etc. of the motor play the important roles in producing vibration and noise. It is found that the noise will be depressed about 3~4 dB and 6~7 dB, when substitutes the copper bearing with plastic one and coats the motor coil with paraffin wax, respectively.

Keywords: micro motor, noise, vibration

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Authors: R. J. Chang

Abstract:

A cyclostationary Gaussian linearization method is formulated for investigating the time average response of nonlinear system under sinusoidal signal and white noise excitation. The quantitative measure of cyclostationary mean, variance, spectrum of mean amplitude, and mean power spectral density of noise are analyzed. The qualitative response behavior of stochastic jump and bifurcation are investigated. The validity of the present approach in predicting the quantitative and qualitative statistical responses is supported by utilizing Monte Carlo simulations. The present analysis without imposing restrictive analytical conditions can be directly derived by solving non-linear algebraic equations. The analytical solution gives reliable quantitative and qualitative prediction of mean and noise response for the Duffing system subjected to both sinusoidal signal and white noise excitation.

Keywords: Cyclostationary, Duffing system, Gaussian linearization, sinusoidal signal and white noise.

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Authors: Ε. Giovanis

Abstract:

In this paper we present an autoregressive model with neural networks modeling and standard error backpropagation algorithm training optimization in order to predict the gross domestic product (GDP) growth rate of four countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer after the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model in the out-of-sample period. The idea behind this approach is to propose a parametric regression with weighted variables in order to test for the statistical significance and the magnitude of the estimated autoregressive coefficients and simultaneously to estimate the forecasts.

Keywords: Autoregressive model, Error back-propagation Feed-Forward neural networks, , Gross Domestic Product

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Authors: E. Giovanis

Abstract:

In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.

Keywords: Autoregressive model, Feed-Forward neuralnetworks, Genetic Algorithms, Gross Domestic Product

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Authors: N. N. Mosola, K. F. Moeketsi, R. Sehobai, N. Pule

Abstract:

The Internet brings increasing use of Information and Communications Technology (ICT) services and facilities. Consequently, new computing paradigms emerge to provide services over the Internet. Although there are several benefits stemming from these services, they pose several risks inherited from the Internet. For example, cybercrime, identity theft, malware etc. To thwart these risks, this paper proposes a holistic approach. This approach involves multidisciplinary interactions. The paper proposes a top-down and bottom-up approach to deal with cyber security concerns in developing countries. These concerns range from regulatory and legislative areas, cyber awareness, research and development, technical dimensions etc. The main focus areas are highlighted and a cybersecurity model solution is proposed. The paper concludes by combining all relevant solutions into a proposed cybersecurity model to assist developing countries in enhancing a cyber-safe environment to instill and promote a culture of cybersecurity.

Keywords: Cybercrime, cybersecurity, computer emergency response team, computer security incident response team.

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Authors: Yeqing Guan, Fen Yang

Abstract:

To learn about China-s future energy demand, this paper first proposed GM(1,1) model group based on recursive solutions of parameters estimation, setting up a general solving-algorithm of the model group. This method avoided the problems occurred on the past researches that remodeling, loss of information and large amount of calculation. This paper established respectively all-data-GM(1,1), metabolic GM(1,1) and new information GM (1,1)model according to the historical data of energy consumption in China in the year 2005-2010 and the added data of 2011, then modeling, simulating and comparison of accuracies we got the optimal models and to predict. Results showed that the total energy demand of China will be 37.2221 billion tons of equivalent coal in 2012 and 39.7973 billion tons of equivalent coal in 2013, which are as the same as the overall planning of energy demand in The 12th Five-Year Plan.

Keywords: energy demands, GM(1, 1) model group, least square estimation, prediction

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Authors: Danilo López, Edwin Rivas, Leyla López

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This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.

Keywords: Cognitive radio, MLPNN, base station, prediction, best effort, real time.

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Authors: Belkacem Laimouche

Abstract:

With the field of Artificial Intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: Artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, inter-laboratory comparison, data analysis, data reliability, bias impact assessment, bias measurement.

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Authors: Ranya Elkhayat

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This paper aims at offering a futures study for higher education in the Middle East. Paying special attention to the negative impacts of neoliberalism, the paper will demonstrate how higher education is now commodified, corporatized and how arts and humanities are eschewed in favor of science and technology. This conceptual paper argues against the neoliberal agenda and aims at providing an alternative exemplified in the Capabilities Approach with special reference to Martha Nussbaum’s theory. The paper is divided into four main parts: the current state of higher education under neoliberal values, a prediction of the conditions of higher education in the near future, the future of higher education using the theoretical framework of the Capabilities Approach, and finally, some areas of concern regarding the approach. The implications of the study demonstrate that Nussbaum’s Capabilities Approach will ensure that the values of education are preserved while avoiding the pitfalls of neoliberalism.

Keywords: Capabilities approach, education future, higher education, MENA.

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Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

Abstract:

The protein domain structure has been widely used as the most informative sequence feature to computationally predict protein-protein interactions. However, in a recent study, a research group has reported a very high accuracy of 94% using hydrophobicity feature. Therefore, in this study we compare and verify the usefulness of protein domain structure and hydrophobicity properties as the sequence features. Using the Support Vector Machines (SVM) as the learning system, our results indicate that both features achieved accuracy of nearly 80%. Furthermore, domains structure had receiver operating characteristic (ROC) score of 0.8480 with running time of 34 seconds, while hydrophobicity had ROC score of 0.8159 with running time of 20,571 seconds (5.7 hours). These results indicate that protein-protein interaction can be predicted from domain structure with reliable accuracy and acceptable running time.

Keywords: Bioinformatics, protein-protein interactions, support vector machines, protein features.

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Authors: Sangsuree Vasupongayya

Abstract:

Fair share objective has been included into the goaloriented parallel computer job scheduling policy recently. However, the previous work only presented the overall scheduling performance. Thus, the per-user performance of the policy is still lacking. In this work, the details of per-user fair share performance under the Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair share priority backfill policy namely RelShare(1d) is also studied. The performance of all policies is collected using an event-driven simulator with three real job traces as input. The experimental results show that the high demand users are usually benefited under most policies because their jobs are large or they have a lot of jobs. In the large job case, one job executed may result in over-share during that period. In the other case, the jobs may be backfilled for performances. However, the users with a mixture of jobs may suffer because if the smaller jobs are executing the priority of the remaining jobs from the same user will be lower. Further analysis does not show any significant impact of users with a lot of jobs or users with a large runtime approximation error.

Keywords: deviation, fair share, discrepancy search, priority scheduling.

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Authors: Rose Shayeghi, Pejman Hosseinioun

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The Multiple Intelligences theory characterizes human intelligence as a multifaceted entity that exists in all human beings with varying degrees. The most important contribution of this theory to the field of English Language Teaching (ELT) is its role in identifying individual differences and designing more learnercentered programs. The present study aims at investigating the relationship between different elements of multiple intelligence and grammar scores. To this end, 63 female Iranian EFL learner selected from among intermediate students participated in the study. The instruments employed were a Nelson English language test, Michigan Grammar Test, and Teele Inventory for Multiple Intelligences (TIMI). The results of Pearson Product-Moment Correlation revealed a significant positive correlation between grammatical accuracy and linguistic as well as interpersonal intelligence. The results of Stepwise Multiple Regression indicated that linguistic intelligence contributed to the prediction of grammatical accuracy.

Keywords: Multiple intelligence, grammar, ELT, EFL, TIMI.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour

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In this paper back-propagation artificial neural network (BPANN )with Levenberg–Marquardt algorithm is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The output data are the coefficient of polynomial that fitted on barreling curves. Neural network was trained using barreling curves generated by finite element simulations of the upsetting and the corresponding material parameters. This technique was tested for three different specimens and can be successfully employed to predict the deformation of the upsetting process

Keywords: Back-propagation artificial neural network(BPANN), prediction, upsetting

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Authors: R. Altamimi, G. Skinner, K. Nesbitt

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Encouraging physical activity amongst children and adolescents is becoming an increasingly relevant issue in modern society. Studies have shown that involving children and adolescents in physical activity is essential for their physical, mental and social development. However, with technology playing an increasingly important role in reducing physical work it is becoming more critical to incorporate adequate physical activities into our lives. One way to overcome this problem is to harness technology so that it promotes physical activities, for example, by motivating children and adolescents to exercise more. This paper describes a promising solution to the question of how to increase levels of physical activity in children and adolescents by combining gaming technologies with exercise tracking goals. This research describes a framework called FITTER (Framework for Integrating activity Tracking Technologies for Electronic Recreation) that combines video game play with more traditional, non-computer physical activities.

Keywords: Exergames, Home-based eHealth, Human-computer Interaction, Natural User Interfaces, Wearable Health Informatics.

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Authors: Ali Kezmane, Said Boukais, Mohand Hamizi

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This paper presents an analytical study on the behavior of reinforced concrete walls with rectangular cross section. Several experiments on such walls have been selected to be studied. Database from various experiments were collected and nominal shear wall strengths have been calculated using formulas, such as those of the ACI (American), NZS (New Zealand), Mexican (NTCC), and Wood and Barda equations. Subsequently, nominal shear wall strengths from the formulas were compared with the ultimate shear wall strengths from the database. These formulas vary substantially in functional form and do not account for all variables that affect the response of walls. There is substantial scatter in the predicted values of ultimate shear strength. Two new semi empirical equations are developed using data from tests of 57 walls for transitions walls and 27 for slender walls with the objective of improving the prediction of peak strength of walls with the most possible accurate.

Keywords: Shear strength, reinforced concrete walls, rectangular walls, shear walls, models.

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Authors: Antoaneta Stefanova, Rositsa Gencheva, Pavlin Groudev

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This paper presents the modeling approach in SBO sequence for VVER 1000 reactors and describes the reactor core behavior at late in-vessel phase in case of late reflooding by HPIS and gives preliminary results for the ASTECv2 validation. The work is focused on investigation of plant behavior during total loss of power and the operator actions. The main goal of these analyses is to assess the phenomena arising during the Station blackout (SBO) followed by primary side high pressure injection system (HPIS) reflooding of already damaged reactor core at very late “in-vessel” phase. The purpose of the analyses is to define how the later HPIS switching on can delay the time of vessel failure or possibly avoid vessel failure. The times for HPP injection were chosen based on previously performed investigations.

Keywords: VVER, operator action validation, reflooding of overheated reactor core, ASTEC computer code.

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Authors: Asep Bayu Dani Nandiyanto, Asep Suhendi, Yutaka Kisakibaru, Takashi Ogi, Kikuo Okuyama

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An ordered porous antimony-doped tin oxide (ATO) film was successfully prepared using a simple coating process with colloidal templates. The facile production was effective when a combination of 16-nm ATO (as a model of an inorganic nanoparticle) and polystyrene (PS) spheres (as a model of the template) weresimply coated to produce a composite ATO/PS film. Heat treatment was then used to remove the PS and produce the porous film. The porous film with a spherical pore shape and a highly ordered porous structure could be obtained. A potential way for the control of pore size could be also achieved by changing initial template size. The theoretical explanation and mechanism of porous formation were also added, which would be important for the scaling-up prediction and estimation.

Keywords: Porous structure film; ATO particle; Ultra-low refractive index; vertical drop method; Low-density material;

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

Abstract:

This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: Landslide, limit analysis, ANN, soil properties.

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Authors: Naci Büyükkaracığan

Abstract:

Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.

Keywords: Gediz Basin, goodness-of-fit tests, Minimum flows, probability distribution.

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Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Deivid Pires, Rafael Haag, Elton Gimenez Rossini

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This study evaluated the uncertainties involved in the solar radiation projections generated by the Brazilian Earth System Model (BESM) of the Weather and Climate Prediction Center (CPTEC) belonging to Coupled Model Intercomparison Phase 5 (CMIP5), with the aim of identifying efficiency in the projections for solar radiation of said model and in this way establish the viability of its use. Two different scenarios elaborated by Intergovernmental Panel on Climate Change (IPCC) were evaluated: RCP 4.5 (with more optimistic contour conditions) and 8.5 (with more pessimistic initial conditions). The method used to verify the accuracy of the present model was the Nash coefficient and the Statistical bias, as it better represents these atmospheric patterns. The BESM showed a tendency to overestimate the data ​​of solar radiation projections in most regions of the state of Rio Grande do Sul and through the validation methods adopted by this study, BESM did not present a satisfactory accuracy.

Keywords: Climate changes, projections, solar radiation, uncertainty.

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Authors: A. R. Salimi, M. Esmaeili, B. Salehi

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The development and extension of large cities induced a need for shallow tunnel in soft ground of building areas. Estimation of ground settlement caused by the tunnel excavation is important engineering point. In this paper, prediction of surface subsidence caused by tunneling in one section of seventh line of Tehran subway is considered. On the basis of studied geotechnical conditions of the region, tunnel with the length of 26.9km has been excavated applying a mechanized method using an EPB-TBM with a diameter of 9.14m. In this regard, settlement is estimated utilizing both analytical and numerical finite element method. The numerical method shows that the value of settlement in this section is 5cm. Besides, the analytical consequences (Bobet and Loganathan-Polous) are 5.29 and 12.36cm, respectively. According to results of this study, due tosaturation of this section, there are good agreement between Bobet and numerical methods. Therefore, tunneling processes in this section needs a special consolidation measurement and support system before the passage of tunnel boring machine.

Keywords: TBM, Subsidence, Numerical Method, Analytical Method.

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Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević

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The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Keywords: Data mining, knowledge discovery in databases, prediction models, student success.

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Authors: Ngozi Nwogu, Mohammed Kajama, Edward Gobina

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Atmospheric carbon dioxide emissions are considered as the greatest environmental challenge the world is facing today. The tasks to control the emissions include the recovery of CO2 from flue gas. This concern has been improved due to recent advances in materials process engineering resulting in the development of inorganic gas separation membranes with excellent thermal and mechanical stability required for most gas separations. This paper, therefore, evaluates the performance of a highly selective inorganic membrane for CO2 recovery applications. Analysis of results obtained is in agreement with experimental literature data. Further results show the prediction performance of the membranes for gas separation and the future direction of research. The materials selection and the membrane preparation techniques are discussed. Method of improving the interface defects in the membrane and its effect on the separation performance has also been reviewed and in addition advances to totally exploit the potential usage of this innovative membrane.

Keywords: Carbon dioxide, gas separation, inorganic ceramic membrane & perm selectivity.

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Authors: Ramlan Zailani, Halim Ghafar, Mohamad Sofian So'aib

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Air infiltration in mass scale industrial applications of bio char production is inevitable. The presence of oxygen during the carbonization process is detrimental to the production of biochar yield and properties. The experiment was carried out on several wood species in a fixed-bed pyrolyser under various fractions of oxygen ranging from 0% to 11% by varying nitrogen and oxygen composition in the pyrolysing gas mixtures at desired compositions. The bed temperature and holding time were also varied. Process optimization was carried out by Response Surface Methodology (RSM) by employing Central Composite Design (CCD) using Design Expert 6.0 Software. The effect of oxygen ratio and holding time on biochar yield within the range studied were statistically significant. From the analysis result, optimum condition of 15.2% biochar yield of mangrove wood was predicted at pyrolysis temperature of 403 oC, oxygen percentage of 2.3% and holding time of two hours. This prediction agreed well with the experiment finding of 15.1% biochar yield.

Keywords: Mangrove wood, slow pyrolysis, oxygen infiltration.

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Authors: Toshinori Takabatake, Yoshikazu Komano

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Recently, the improvements in processing performance of a computer and in high speed communication of an optical fiber have been achieved, so that the amount of data which are processed by a computer and flowed on a network has been increasing greatly. However, in a client-server system, since the server receives and processes the amount of data from the clients through the network, a load on the server is increasing. Thus, there are needed to introduce a server with high processing ability and to have a line with high bandwidth. In this paper, concerning to P2P networks to resolve the load on a specific server, a criterion called an Indexed-Priority Metric is proposed and its performance is evaluated. The proposed metric is to allocate some files to each node. As a result, the load on a specific server can distribute them to each node equally well. A P2P file sharing system using the proposed metric is implemented. Simulation results show that the proposed metric can make it distribute files on the specific server.

Keywords: peer-to-peer, file-sharing system, load-balancing, dependability

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Authors: Reneiloe Seodigeng, Malwandla Hanabe, Haleden Chiririwa, Hilary Rutto, Tumisang Seodigeng

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Neutralisation of acid-mine drainage (AMD) using limestone is cost effective, and good results can be obtained. However, this process has its limitations; it cannot be used for highly acidic water which consists of Fe(III). When Fe(III) reacts with CaCO₃, it results in armoring. Armoring slows the reaction, and additional alkalinity can no longer be generated. Limestone is easily accessible, so this problem can be easily dealt with. Experiments were carried out to evaluate the effect of PVC pipe length on ferric and ferrous ions. It was found that the shorter the pipe length the more these dissolved metals precipitate. The effect of the pipe length on the hydrogen ions was also studied, and it was found that these two have an inverse relationship. Experimental data were further compared with the model prediction data to see if they behave in a similar fashion. The model was able to predict the behaviour of 1.5m and 2 m pipes in ferric and ferrous ion precipitation.

Keywords: Acid mine drainage, neutralization, limestone, modeling.

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Authors: Guoliang Fan, Aiping Li, Xuemei Liu, Liyun Xu

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The performance of the tightening equipment will decline with the working process in manufacturing system. The main manifestations are the randomness and discretization degree increasing of the tightening performance. To evaluate the degradation tendency of the tightening performance accurately, a complexity measurement approach based on Kolmogorov entropy is presented. At first, the states of performance index are divided for calibrating the discrete degree. Then the complexity measurement model based on Kolmogorov entropy is built. The model describes the performance degradation tendency of tightening equipment quantitatively. At last, a study case is applied for verifying the efficiency and validity of the approach. The research achievement shows that the presented complexity measurement can effectively evaluate the degradation tendency of the tightening equipment. It can provide theoretical basis for preventive maintenance and life prediction of equipment.

Keywords: Complexity measurement, Kolmogorov entropy, manufacturing system, performance evaluation, tightening equipment.

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