Text Mining Technique for Data Mining Application

Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In decision tree approach is most useful in classification problem. With this technique, tree is constructed to model the classification process. There are two basic steps in the technique: building the tree and applying the tree to the database. This paper describes a proposed C5.0 classifier that performs rulesets, cross validation and boosting for original C5.0 in order to reduce the optimization of error ratio. The feasibility and the benefits of the proposed approach are demonstrated by means of medial data set like hypothyroid. It is shown that, the performance of a classifier on the training cases from which it was constructed gives a poor estimate by sampling or using a separate test file, either way, the classifier is evaluated on cases that were not used to build and evaluate the classifier are both are large. If the cases in hypothyroid.data and hypothyroid.test were to be shuffled and divided into a new 2772 case training set and a 1000 case test set, C5.0 might construct a different classifier with a lower or higher error rate on the test cases. An important feature of see5 is its ability to classifiers called rulesets. The ruleset has an error rate 0.5 % on the test cases. The standard errors of the means provide an estimate of the variability of results. One way to get a more reliable estimate of predictive is by f-fold –cross- validation. The error rate of a classifier produced from all the cases is estimated as the ratio of the total number of errors on the hold-out cases to the total number of cases. The Boost option with x trials instructs See5 to construct up to x classifiers in this manner. Trials over numerous datasets, large and small, show that on average 10-classifier boosting reduces the error rate for test cases by about 25%.

Self-Organization of Radiation Defects: Temporal Dissipative Structures

A theoretical approach to radiation damage evolution is developed. Stable temporal behavior taking place in solids under irradiation are examined as phenomena of self-organization in nonequilibrium systems. Experimental effects of temporal self-organization in solids under irradiation are reviewed. Their essential common properties and features are highlighted and analyzed. Dynamical model to describe development of self-oscillation of density of point defects under stationary irradiation is proposed. The emphasis is the nonlinear couplings between rate of annealing and density of defects that determine the kind and parameters of an arising self-oscillation. The field of parameters (defect generation rate and environment temperature) at which self-oscillations develop is found. Bifurcation curve and self-oscillation period near it is obtained.

Electronic Voting System using Mobile Terminal

Electronic voting (E-voting) using an internet has been recently performed in some nations and regions. There is no spatial restriction which a voter directly has to visit the polling place, but an e-voting using an internet has to go together the computer in which the internet connection is possible. Also, this voting requires an access code for the e-voting through the beforehand report of a voter. To minimize these disadvantages, we propose a method in which a voter, who has the wireless certificate issued in advance, uses its own cellular phone for an e-voting without the special registration for a vote. Our proposal allows a voter to cast his vote in a simple and convenient way without the limit of time and location, thereby increasing the voting rate, and also ensuring confidentiality and anonymity.

Study Interaction between Tin Dioxide Nanowhiskers and Ethanol Molecules in Gas Phase: Monte Carlo(MC) and Langevin Dynamics (LD) Simulation

Three dimensional nanostructure materials have attracted the attention of many researches because the possibility to apply them for near future devices in sensors, catalysis and energy related. Tin dioxide is the most used material for gas sensing because its three-dimensional nanostructures and properties are related to the large surface exposed to gas adsorption. We propose the use of branch SnO2 nanowhiskers in interaction with ethanol. All Sn atoms are symmetric. The total energy, potential energy and Kinetic energy calculated for interaction between SnO2 and ethanol in different distances and temperatures. The calculations achieved by methods of Langevin Dynamic and Mont Carlo simulation. The total energy increased with addition ethanol molecules and temperature so interactions between them are endothermic.

Probabilistic Modelling of Marine Bridge Deterioration

Chloride induced corrosion of steel reinforcement is the main cause of deterioration of reinforced concrete marine structures. This paper investigates the relative performance of alternative repair options with respect to the deterioration of reinforced concrete bridge elements in marine environments. Focus is placed on the initiation phase of reinforcement corrosion. A laboratory study is described which involved exposing concrete samples to accelerated chloride-ion ingress. The study examined the relative efficiencies of two repair methods, namely Ordinary Portland Cement (OPC) concrete and a concrete which utilised Ground Granulated Blastfurnace Cement (GGBS) as a partial cement replacement. The mix designs and materials utilised were identical to those implemented in the repair of a marine bridge on the South East coast of Ireland in 2007. The results of this testing regime serve to inform input variables employed in probabilistic modelling of deterioration for subsequent reliability based analysis to compare the relative performance of the studied repair options.

An Investigation of the Cu-Ni Compound Cathode Materials Affecting on Transient Recovery Voltage

The purpose of this research was to analyze and compare the instability of a contact surface between Copper and Nickel an alloy cathode in vacuum, the different ratio of Copper and Copper were conducted at 1%, 2% and 4% by using the cathode spot model. The transient recovery voltage is predicted. The cathode spot region is recognized as the collisionless space charge sheath connected with singly ionized collisional plasma. It was found that the transient voltage is decreased with increasing the percentage of an amount of Nickel in cathode materials.

Evaluating the Effect of Farmers’ Training on Rice Production in Sierra Leone: A Case Study of Rice Cultivation in Lowland Ecology

This study endeavors to evaluate the effects of farmers’ training program on the adoption of improved farming practices, the output of rice farming, and the income as well as the profit from rice farming by employing an ex-post non-experimental data in Sierra Leone. It was established that participating in farmers’ training program increased the possibility of adoption of the improved farming activities that were implemented in the study area. Through the training program also, the proceeds from rice production was also established to have increased considerably. These results were in line with the assumption that one of the main constraints on the growth in agricultural output particularly rice cultivation in most African states is the lack of efficient extension programs.

Multiwavelet and Biological Signal Processing

In this paper we are to find the optimum multiwavelet for compression of electrocardiogram (ECG) signals and then, selecting it for using with SPIHT codec. At present, it is not well known which multiwavelet is the best choice for optimum compression of ECG. In this work, we examine different multiwavelets on 24 sets of ECG data with entirely different characteristics, selected from MIT-BIH database. For assessing the functionality of the different multiwavelets in compressing ECG signals, in addition to known factors such as Compression Ratio (CR), Percent Root Difference (PRD), Distortion (D), Root Mean Square Error (RMSE) in compression literature, we also employed the Cross Correlation (CC) criterion for studying the morphological relations between the reconstructed and the original ECG signal and Signal to reconstruction Noise Ratio (SNR). The simulation results show that the Cardinal Balanced Multiwavelet (cardbal2) by the means of identity (Id) prefiltering method to be the best effective transformation. After finding the most efficient multiwavelet, we apply SPIHT coding algorithm on the transformed signal by this multiwavelet.

Stress Relaxation of Date at Different Temperature and Moisture Content of Product: A New Approach

Iran is one of the greatest producers of date in the world. However due to lack of information about its viscoelastic properties, much of the production downgraded during harvesting and postharvesting processes. In this study the effect of temperature and moisture content of product were investigated on stress relaxation characteristics. Therefore, the freshly harvested date (kabkab) at tamar stage were put in controlled environment chamber to obtain different temperature levels (25, 35, 45, and 55 0C) and moisture contents (8.5, 8.7, 9.2, 15.3, 20, 32.2 %d.b.). A texture analyzer TAXT2 (Stable Microsystems, UK) was used to apply uniaxial compression tests. A chamber capable to control temperature was designed and fabricated around the plunger of texture analyzer to control the temperature during the experiment. As a new approach a CCD camera (A4tech, 30 fps) was mounted on a cylindrical glass probe to scan and record contact area between date and disk. Afterwards, pictures were analyzed using image processing toolbox of Matlab software. Individual date fruit was uniaxially compressed at speed of 1 mm/s. The constant strain of 30% of thickness of date was applied to the horizontally oriented fruit. To select a suitable model for describing stress relaxation of date, experimental data were fitted with three famous stress relaxation models including the generalized Maxwell, Nussinovitch, and Pelege. The constant in mentioned model were determined and correlated with temperature and moisture content of product using non-linear regression analysis. It was found that Generalized Maxwell and Nussinovitch models appropriately describe viscoelastic characteristics of date fruits as compared to Peleg mode.

Neural Network Based Icing Identification and Fault Tolerant Control of a 340 Aircraft

This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the icing parameters and the reconfigured flight dynamics having the similar performance before the icing. In other words, the destabilizing icing affect is compensated.

Wiener Filter as an Optimal MMSE Interpolator

The ideal sinc filter, ignoring the noise statistics, is often applied for generating an arbitrary sample of a bandlimited signal by using the uniformly sampled data. In this article, an optimal interpolator is proposed; it reaches a minimum mean square error (MMSE) at its output in the presence of noise. The resulting interpolator is thus a Wiener filter, and both the optimal infinite impulse response (IIR) and finite impulse response (FIR) filters are presented. The mean square errors (MSE-s) for the interpolator of different length impulse responses are obtained by computer simulations; it shows that the MSE-s of the proposed interpolators with a reasonable length are improved about 0.4 dB under flat power spectra in noisy environment with signal-to-noise power ratio (SNR) equal 10 dB. As expected, the results also demonstrate the improvements for the MSE-s with various fractional delays of the optimal interpolator against the ideal sinc filter under a fixed length impulse response.

Capacity Enhancement in Wireless Networks using Directional Antennas

One of the biggest drawbacks of the wireless environment is the limited bandwidth. However, the users sharing this limited bandwidth have been increasing considerably. SDMA technique which entails using directional antennas allows to increase the capacity of a wireless network by separating users in the medium. In this paper, it has been presented how the capacity can be enhanced while the mean delay is reduced by using directional antennas in wireless networks employing TDMA/FDD MAC. Computer modeling and simulation of the wireless system studied are realized using OPNET Modeler. Preliminary simulation results are presented and the performance of the model using directional antennas is evaluated and compared consistently with the one using omnidirectional antennas.

Leaf Chlorophyll of Corn, Sweet basil and Borage under Intercropping System in Weed Interference

Intercropping is one of the sustainable agricultural factors. The SPAD meter can be used to predict nitrogen index reliably, it may also be a useful tool for assessing the relative impact of weeds on crops. In order to study the effect of weeds on SPAD in corn (Zea mays L.), sweet basil (Ocimum basilicum L.) and borage (Borago officinalis L.) in intercropping system, a factorial experiment was conducted in three replications in 2011. Experimental factors were included intercropping of corn with sweet basil and borage in different ratios (100:0, 75:25, 50:50, 25:75 and 0:100 corn: borage or sweet basil) and weed infestation (weed control and weed interference). The results showed that intercropping of corn with sweet basil and borage increased the SPAD value of corn compare to monoculture in weed interference condition. Sweet basil SPAD value in weed control treatments (43.66) was more than weed interference treatments (40.17). Corn could increase the borage SPAD value compare to monoculture in weed interference treatments.

Evolutionary Approach for Automated Discovery of Censored Production Rules

In the recent past, there has been an increasing interest in applying evolutionary methods to Knowledge Discovery in Databases (KDD) and a number of successful applications of Genetic Algorithms (GA) and Genetic Programming (GP) to KDD have been demonstrated. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski & Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations, in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the 'If P Then D' part of the CPR expresses important information, while the Unless C part acts only as a switch and changes the polarity of D to ~D. This paper presents a classification algorithm based on evolutionary approach that discovers comprehensible rules with exceptions in the form of CPRs. The proposed approach has flexible chromosome encoding, where each chromosome corresponds to a CPR. Appropriate genetic operators are suggested and a fitness function is proposed that incorporates the basic constraints on CPRs. Experimental results are presented to demonstrate the performance of the proposed algorithm.

Federal Open Agent System Platform

Open Agent System platform based on High Level Architecture is firstly proposed to support the application involving heterogeneous agents. The basic idea is to develop different wrappers for different agent systems, which are wrapped as federates to join a federation. The platform is based on High Level Architecture and the advantages for this open standard are naturally inherited, such as system interoperability and reuse. Especially, the federal architecture allows different federates to be heterogeneous so as to support the integration of different agent systems. Furthermore, both implicit communication and explicit communication between agents can be supported. Then, as the wrapper RTI_JADE an example, the components are discussed. Finally, the performance of RTI_JADE is analyzed. The results show that RTI_JADE works very efficiently.

A Heuristic Algorithm Approach for Scheduling of Multi-criteria Unrelated Parallel Machines

In this paper we address a multi-objective scheduling problem for unrelated parallel machines. In unrelated parallel systems, the processing cost/time of a given job on different machines may vary. The objective of scheduling is to simultaneously determine the job-machine assignment and job sequencing on each machine. In such a way the total cost of the schedule is minimized. The cost function consists of three components, namely; machining cost, earliness/tardiness penalties and makespan related cost. Such scheduling problem is combinatorial in nature. Therefore, a Simulated Annealing approach is employed to provide good solutions within reasonable computational times. Computational results show that the proposed approach can efficiently solve such complicated problems.

Directors- Islamic Code of Ethics

This paper discusses a new model of Islamic code of ethics for directors. Several corporate scandals and local (example Transmile and Megan Media) and overseas corporate (example Parmalat and Enron) collapses show that the current corporate governance and regulatory reform are unable to prevent these events from recurring. Arguably, the code of ethics for directors is under research and the current code of ethics only concentrates on binding the work of the employee of the organization as a whole, without specifically putting direct attention to the directors, the group of people responsible for the performance of the company. This study used a semi-structured interview survey of well-known Islamic scholars such as the Mufti to develop the model. It is expected that the outcome of the research is a comprehensive model of code of ethics based on the Islamic principles that can be applied and used by the company to construct a code of ethics for their directors.

Probabilistic Model Development for Project Performance Forecasting

In this paper, based on the past project cost and time performance, a model for forecasting project cost performance is developed. This study presents a probabilistic project control concept to assure an acceptable forecast of project cost performance. In this concept project activities are classified into sub-groups entitled control accounts. Then obtain the Stochastic S-Curve (SS-Curve), for each sub-group and the project SS-Curve is obtained by summing sub-groups- SS-Curves. In this model, project cost uncertainties are considered through Beta distribution functions of the project activities costs required to complete the project at every selected time sections through project accomplishment, which are extracted from a variety of sources. Based on this model, after a percentage of the project progress, the project performance is measured via Earned Value Management to adjust the primary cost probability distribution functions. Then, accordingly the future project cost performance is predicted by using the Monte-Carlo simulation method.

Non-negative Principal Component Analysis for Face Recognition

Principle component analysis is often combined with the state-of-art classification algorithms to recognize human faces. However, principle component analysis can only capture these features contributing to the global characteristics of data because it is a global feature selection algorithm. It misses those features contributing to the local characteristics of data because each principal component only contains some levels of global characteristics of data. In this study, we present a novel face recognition approach using non-negative principal component analysis which is added with the constraint of non-negative to improve data locality and contribute to elucidating latent data structures. Experiments are performed on the Cambridge ORL face database. We demonstrate the strong performances of the algorithm in recognizing human faces in comparison with PCA and NREMF approaches.

Designing and Implementing an Innovative Course about World Wide Web, Based on the Conceptual Representations of Students

Internet is nowadays included to all National Curriculums of the elementary school. A comparative study of their goals leads to the conclusion that a complete curriculum should aim to student-s acquisition of the abilities to navigate and search for information and additionally to emphasize on the evaluation of the information provided by the World Wide Web. In a constructivistic knowledge framework the design of a course has to take under consideration the conceptual representations of students. The following paper presents the conceptual representation of students of eleven years old, attending the Sixth Grade of Greek Elementary School about World Wide Web and their use in the design and implementation of an innovative course.