pH-Responsiveness Properties of a Biodigradable Hydrogels Based on Carrageenan-g-poly(NaAA-co-NIPAM)

A novel thermo-sensitive superabsorbent hydrogel with salt- and pH-responsiveness properties was obtained by grafting of mixtures of acrylic acid (AA) and N-isopropylacrylamide (NIPAM) monomers onto kappa-carrageenan, kC, using ammonium persulfate (APS) as a free radical initiator in the presence of methylene bisacrylamide (MBA) as a crosslinker. Infrared spectroscopy was carried out to confirm the chemical structure of the hydrogel. Moreover, morphology of the samples was examined by scanning electron microscopy (SEM). The effect of MBA concentration and AA/NIPAM weight ratio on the water absorbency capacity has been investigated. The swelling variations of hydrogels were explained according to swelling theory based on the hydrogel chemical structure. The hydrogels exhibited salt-sensitivity and cation exchange properties. The temperature- and pH-reversibility properties of the hydrogels make the intelligent polymers as good candidates for considering as potential carriers for bioactive agents, e.g. drugs.

A Hybrid Approach for Quantification of Novelty in Rule Discovery

Rule Discovery is an important technique for mining knowledge from large databases. Use of objective measures for discovering interesting rules lead to another data mining problem, although of reduced complexity. Data mining researchers have studied subjective measures of interestingness to reduce the volume of discovered rules to ultimately improve the overall efficiency of KDD process. In this paper we study novelty of the discovered rules as a subjective measure of interestingness. We propose a hybrid approach that uses objective and subjective measures to quantify novelty of the discovered rules in terms of their deviations from the known rules. We analyze the types of deviation that can arise between two rules and categorize the discovered rules according to the user specified threshold. We implement the proposed framework and experiment with some public datasets. The experimental results are quite promising.

A Comparison of Marginal and Joint Generalized Quasi-likelihood Estimating Equations Based On the Com-Poisson GLM: Application to Car Breakdowns Data

In this paper, we apply and compare two generalized estimating equation approaches to the analysis of car breakdowns data in Mauritius. Number of breakdowns experienced by a machinery is a highly under-dispersed count random variable and its value can be attributed to the factors related to the mechanical input and output of that machinery. Analyzing such under-dispersed count observation as a function of the explanatory factors has been a challenging problem. In this paper, we aim at estimating the effects of various factors on the number of breakdowns experienced by a passenger car based on a study performed in Mauritius over a year. We remark that the number of passenger car breakdowns is highly under-dispersed. These data are therefore modelled and analyzed using Com-Poisson regression model. We use the two types of quasi-likelihood estimation approaches to estimate the parameters of the model: marginal and joint generalized quasi-likelihood estimating equation approaches. Under-dispersion parameter is estimated to be around 2.14 justifying the appropriateness of Com-Poisson distribution in modelling underdispersed count responses recorded in this study.

Edit Distance Algorithm to Increase Storage Efficiency of Javanese Corpora

Since the one-to-one word translator does not have the facility to translate pragmatic aspects of Javanese, the parallel text alignment model described uses a phrase pair combination. The algorithm aligns the parallel text automatically from the beginning to the end of each sentence. Even though the results of the phrase pair combination outperform the previous algorithm, it is still inefficient. Recording all possible combinations consume more space in the database and time consuming. The original algorithm is modified by applying the edit distance coefficient to improve the data-storage efficiency. As a result, the data-storage consumption is 90% reduced as well as its learning period (42s).

Reconstitute Information about Discontinued Water Quality Variables in the Nile Delta Monitoring Network Using Two Record Extension Techniques

The world economic crises and budget constraints have caused authorities, especially those in developing countries, to rationalize water quality monitoring activities. Rationalization consists of reducing the number of monitoring sites, the number of samples, and/or the number of water quality variables measured. The reduction in water quality variables is usually based on correlation. If two variables exhibit high correlation, it is an indication that some of the information produced may be redundant. Consequently, one variable can be discontinued, and the other continues to be measured. Later, the ordinary least squares (OLS) regression technique is employed to reconstitute information about discontinued variable by using the continuously measured one as an explanatory variable. In this paper, two record extension techniques are employed to reconstitute information about discontinued water quality variables, the OLS and the Line of Organic Correlation (LOC). An empirical experiment is conducted using water quality records from the Nile Delta water quality monitoring network in Egypt. The record extension techniques are compared for their ability to predict different statistical parameters of the discontinued variables. Results show that the OLS is better at estimating individual water quality records. However, results indicate an underestimation of the variance in the extended records. The LOC technique is superior in preserving characteristics of the entire distribution and avoids underestimation of the variance. It is concluded from this study that the OLS can be used for the substitution of missing values, while LOC is preferable for inferring statements about the probability distribution.

Applying Complex Network Theory to Software Structure Analysis

Complex networks have been intensively studied across many fields, especially in Internet technology, biological engineering, and nonlinear science. Software is built up out of many interacting components at various levels of granularity, such as functions, classes, and packages, representing another important class of complex networks. It can also be studied using complex network theory. Over the last decade, many papers on the interdisciplinary research between software engineering and complex networks have been published. It provides a different dimension to our understanding of software and also is very useful for the design and development of software systems. This paper will explore how to use the complex network theory to analyze software structure, and briefly review the main advances in corresponding aspects.

Treatment of Recycled Concrete Aggregates by Si-Based Polymers

The recycling of concrete, bricks and masonry rubble as concrete aggregates is an important way to contribute to a sustainable material flow. However, there are still various uncertainties limiting the widespread use of Recycled Concrete Aggregates (RCA). The fluctuations in the composition of grade recycled aggregates and their influence on the properties of fresh and hardened concrete are of particular concern regarding the use of RCA. Most of problems occurring while using recycled concrete aggregates as aggregates are due to higher porosity and hence higher water absorption, lower mechanical strengths, residual impurities on the surface of the RCA forming weaker bond between cement paste and aggregate. So, the reuse of RCA is still limited. Efficient polymer based treatment is proposed in order to reuse RCA easier. The silicon-based polymer treatments of RCA were carried out and were compared. This kind of treatment can improve the properties of RCA such as the rate of water absorption on treated RCA is significantly reduced.

A Study on the Differential Diagnostic Model for Newborn Hearing Loss Screening

According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.

Left Ventricular Model Using Second Order Electromechanical Coupling: Effects of Viscoelastic Damping

It is known that the heart interacts with and adapts to its venous and arterial loading conditions. Various experimental studies and modeling approaches have been developed to investigate the underlying mechanisms. This paper presents a model of the left ventricle derived based on nonlinear stress-length myocardial characteristics integrated over truncated ellipsoidal geometry, and second-order dynamic mechanism for the excitation-contraction coupling system. The results of the model presented here describe the effects of the viscoelastic damping element of the electromechanical coupling system on the hemodynamic response. Different heart rates are considered to study the pacing effects on the performance of the left-ventricle against constant preload and afterload conditions under various damping conditions. The results indicate that the pacing process of the left ventricle has to take into account, among other things, the viscoelastic damping conditions of the myofilament excitation-contraction process.

Evaluating Service Quality of Online Auction by Fuzzy MCDM

This paper applies fuzzy set theory to evaluate the service quality of online auction. Service quality is a composition of various criteria. Among them many intangible attributes are difficult to measure. This characteristic introduces the obstacles for respondent in replying to the survey. So as to overcome this problem, we invite fuzzy set theory into the measurement of performance. By using AHP in obtaining criteria and TOPSIS in ranking, we found the most concerned dimension of service quality is Transaction Safety Mechanism and the least is Charge Item. Regarding to the most concerned attributes are information security, accuracy and information.

Diffusion of Mobile Entertainment in Malaysia: Drivers and Barriers

This research aims to examine the key success factors for the diffusion of mobile entertainment services in Malaysia. The drivers and barriers observed in this research include perceived benefit; concerns pertaining to pricing, product and technological standardization, privacy and security; as well as influences from peers and community. An analysis of a Malaysian survey of 384 respondents between 18 to 25 years shows that subscribers placed greater importance on perceived benefit of mobile entertainment services compared to other factors. Results of the survey also show that there are strong positive correlations between all the factors, with pricing issue–perceived benefit showing the strongest relationship. This paper aims to provide an extensive study on the drivers and barriers that could be used to derive architecture for entertainment service provision to serve as a guide for telcos to outline suitable approaches in order to encourage mass market adoption of mobile entertainment services in Malaysia.

Finding Pareto Optimal Front for the Multi-Mode Time, Cost Quality Trade-off in Project Scheduling

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

An Algorithm of Finite Capacity Material Requirement Planning System for Multi-stage Assembly Flow Shop

This paper aims to develop an algorithm of finite capacity material requirement planning (FCMRP) system for a multistage assembly flow shop. The developed FCMRP system has two main stages. The first stage is to allocate operations to the first and second priority work centers and also determine the sequence of the operations on each work center. The second stage is to determine the optimal start time of each operation by using a linear programming model. Real data from a factory is used to analyze and evaluate the effectiveness of the proposed FCMRP system and also to guarantee a practical solution to the user. There are five performance measures, namely, the total tardiness, the number of tardy orders, the total earliness, the number of early orders, and the average flow-time. The proposed FCMRP system offers an adjustable solution which is a compromised solution among the conflicting performance measures. The user can adjust the weight of each performance measure to obtain the desired performance. The result shows that the combination of FCMRP NP3 and EDD outperforms other combinations in term of overall performance index. The calculation time for the proposed FCMRP system is about 10 minutes which is practical for the planners of the factory.

The Development of Positive Emotion Regulation Strategies Scale for Children and Adolescents

The study was designed to develop a measurement of the positive emotion regulation questionnaire (PERQ) that assesses positive emotion regulation strategies through self-report. The 14 items developed for the surveying instrument of the study were based upon literatures regarding elements of positive regulation strategies. 319 elementary students (age ranging from 12 to14) were recruited among three public elementary schools to survey on their use of positive emotion regulation strategies. Of 319 subjects, 20 invalid questionnaire s yielded a response rate of 92%. The data collected wasanalyzed through methods such as item analysis, factor analysis, and structural equation models. In reference to the results from item analysis, the formal survey instrument was reduced to 11 items. A principal axis factor analysis with varimax was performed on responses, resulting in a 2-factor equation (savoring strategy and neutralizing strategy), which accounted for 55.5% of the total variance. Then, the two-factor structure of scale was also identified by structural equation models. Finally, the reliability coefficients of the two factors were Cronbach-s α .92 and .74. Gender difference was only found in savoring strategy. In conclusion, the positive emotion regulation strategies questionnaire offers a brief, internally consistent, and valid self-report measure for understanding the emotional regulation strategies of children that may be useful to researchers and applied professionals.

Organizational Commitment of Anadolu University Open Education Faculty Students

Distance education program is a dimension of contemporary and new education technologies. Concepts and applications in this field are the results of a series of educational demands and developments in various communication and education technologies. Distance education applications have some conceptual bases. These are creating new education opportunities, realizing work-education unity, getting democratic in education, lifelong education, tendency to individual matters, effective use of institutions, integration of technology and education, tendency to individual and social needs, taking three dimensional integration as the main principle (publishing, printed materials and face to face education), reaching maximum mass, individual and mass education integrity and education demand and financial matters balance. Economics, Business Administration and Open Education faculties, which have been giving education within Anadolu University since 1982 in Turkey, are carrying on education with nearly 1.000.000 students. The aim of this study is to determine organizational commitment levels of students who have been studying at Anadolu University Economics, Business Administration and Open Education faculties in the scope of affective, continuance and nominative commitment in Allen&Meyer model. In the study, organizational commitment of the Economics, Business Administration and Open Education faculty students, who are receiving education by means of distance education, to their faculties is dealt after introducing Anadolu University Distance Education system which gives higher education via distance education method in Turkey. In order to increase the success level of faculties it is required for students to have high level of organizational commitment to their faculties. A questionnaire has been applied by using “Organizational Commitment Scale", developed by Meyer&Allen to determine organizational commitments of Economics, Business Administration and Open Education students. Organizational commitment is dealt with as affective, continuance and nominative commitment. The questionnaire was applied face to face to randomly chosen 500 students living in Eskişehir and the data was downloaded to the computer by using SPSS program and the results were analyzed in terms of demographic features (gender, age, marital status, years of study, work and income level) of students by using frequency test, ttest and ANOVA test. As a result of these analyses, when the comments of Open Education Faculty students on levels of affective, continuance and nominative commitment to their faculties were examined, it has been revealed that continuance commitment level has the highest rate. Among the female participants; continuance commitment is high in the age range of 30-40, for normative commitment it is 17-22. However no dominant age range was defined for affective commitment. Regarding the marital status; continuance commitment average is higher among married participants; but nominative affective commitment average is higher among single participants. As to the years of study, affective and continuance commitment is higher among senior students while normative commitment is higher among junior students. Moreover; in terms of continuance, affective and normative commitment, those who do not work and have low income have higher level of all there commitment types than those who work and have relatively high income.

The Number of Rational Points on Elliptic Curves y2 = x3 + a3 on Finite Fields

In this work, we consider the rational points on elliptic curves over finite fields Fp. We give results concerning the number of points Np,a on the elliptic curve y2 ≡ x3 +a3(mod p) according to whether a and x are quadratic residues or non-residues. We use two lemmas to prove the main results first of which gives the list of primes for which -1 is a quadratic residue, and the second is a result from [1]. We get the results in the case where p is a prime congruent to 5 modulo 6, while when p is a prime congruent to 1 modulo 6, there seems to be no regularity for Np,a.

Feature Based Dense Stereo Matching using Dynamic Programming and Color

This paper presents a new feature based dense stereo matching algorithm to obtain the dense disparity map via dynamic programming. After extraction of some proper features, we use some matching constraints such as epipolar line, disparity limit, ordering and limit of directional derivative of disparity as well. Also, a coarseto- fine multiresolution strategy is used to decrease the search space and therefore increase the accuracy and processing speed. The proposed method links the detected feature points into the chains and compares some of the feature points from different chains, to increase the matching speed. We also employ color stereo matching to increase the accuracy of the algorithm. Then after feature matching, we use the dynamic programming to obtain the dense disparity map. It differs from the classical DP methods in the stereo vision, since it employs sparse disparity map obtained from the feature based matching stage. The DP is also performed further on a scan line, between any matched two feature points on that scan line. Thus our algorithm is truly an optimization method. Our algorithm offers a good trade off in terms of accuracy and computational efficiency. Regarding the results of our experiments, the proposed algorithm increases the accuracy from 20 to 70%, and reduces the running time of the algorithm almost 70%.

Evaluation of the Inhibitory Effect of Some Plant Crude Extracts Against Albugo Candida, the Causal Agent of White Rust

White rust, caused by Albugo candida, is the most destructive foliar diseases of persian cress, Lepidium sativum in Iran. Application of fungicide is the most common method for the disease control. However, regarding the problems created by synthetic pesticides application, environmentally safe methods are needed to replace chemical pesticides. In this study, the antifungal activity of plant natural extracts was investigated for their ability to inhibit zoospore release from sporangia of A. candida. The crude extract of 46 plants was obtained using methanol. The inhibitory effect of the extracts was examined by mixing the plant extracts with a zoosporangial suspension of A. candida (1×106 spore/ml) at three concentrations, 250, 100 and 50 ppm. The experiments were conducted in a completely randomized design, with three replicates. The results of the experiment showed that three out of 46 plants species, including, Rhus coriaria, Anagallis arvensis and Mespilus germanica were completely inhibit zoospore release from zoosporangia of Albugo candida at concentration of 50 ppm.

Identification of Aircraft Gas Turbine Engine's Temperature Condition

Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.

On-Line Geometrical Identification of Reconfigurable Machine Tool using Virtual Machining

One of the main research directions in CAD/CAM machining area is the reducing of machining time. The feedrate scheduling is one of the advanced techniques that allows keeping constant the uncut chip area and as sequel to keep constant the main cutting force. They are two main ways for feedrate optimization. The first consists in the cutting force monitoring, which presumes to use complex equipment for the force measurement and after this, to set the feedrate regarding the cutting force variation. The second way is to optimize the feedrate by keeping constant the material removal rate regarding the cutting conditions. In this paper there is proposed a new approach using an extended database that replaces the system model. The feedrate scheduling is determined based on the identification of the reconfigurable machine tool, and the feed value determination regarding the uncut chip section area, the contact length between tool and blank and also regarding the geometrical roughness. The first stage consists in the blank and tool monitoring for the determination of actual profiles. The next stage is the determination of programmed tool path that allows obtaining the piece target profile. The graphic representation environment models the tool and blank regions and, after this, the tool model is positioned regarding the blank model according to the programmed tool path. For each of these positions the geometrical roughness value, the uncut chip area and the contact length between tool and blank are calculated. Each of these parameters are compared with the admissible values and according to the result the feed value is established. We can consider that this approach has the following advantages: in case of complex cutting processes the prediction of cutting force is possible; there is considered the real cutting profile which has deviations from the theoretical profile; the blank-tool contact length limitation is possible; it is possible to correct the programmed tool path so that the target profile can be obtained. Applying this method, there are obtained data sets which allow the feedrate scheduling so that the uncut chip area is constant and, as a result, the cutting force is constant, which allows to use more efficiently the machine tool and to obtain the reduction of machining time.