Estimation of missing values is an important step in the preprocessing. In this paper, at two-step approach is proposed to fill the NUMERIC missing values. In the first step, data is clustered. In the second step, the missing data in each cluster are estimated using a combination of weighted k nearest neighbors and linear regression METHODs. The correlation measure is employed to determine the appropriate METHOD for the filling of missing data in each cluster. The quality of estimated missing values is evaluated using the root mean squared error (RMSE) criterion. Effect of different input parameters on the error of estimated values is investigated. Moreover, the performance of the proposed METHOD for the estimation purpose is evaluated on five datasets. Finally, the efficiency of the proposed METHOD is compared to four different estimation METHODs, namely, Mean estimation, multi-layer perceptron (MLP) based estimation, fuzzy C-means (FCM) based approximation METHOD, and Class-based K-clusters nearest neighbor imputation (CKNNI) METHOD. Experimental results show that the proposed METHOD produces less error in comparison to other compared METHODs, in most of the cases.

Association rule mining process can be visualized as a multi-objective problem rather than as a single objective one. Measures like support, confidence and other interestingness criteria which are used for evaluating a rule, can be thought of as different objectives of association rule mining problem. Support count is the number of records, which satisfies all the conditions that exist in the rule. This objective represents the accuracy of the rules extracted from the database. Confidence represents the proportion of records for which the prediction of the rule (or model in the case of a complete classification) is correct, and it is one of the most widely quoted measures of quality, especially in the context of complete classification. Interestingness measures how much interesting the rule is. Using these three measures as the objectives of rule mining problem, this article uses a Simulated Annealing algorithm to extract some useful and interesting rules from any Market-basket type databases. The experimental results show that the algorithm may be suitable for large and noisy datasets but don't stay in local minimum.

using criteria and quantitive METHODs for levelling residential place in spatial system, of regions not only leads to recognition of unequilibrium rate of residential places but it is also a criteria for attempting to decreas and removing available unequilibrium omang them. this study aims to explain the developing condition of khorasan razavi provinces cities with special look at Quchan by enjoying of descriptive-analytical reseach technique and by using taxonomy technique (in supplementary from of moris and standard credit) and based on 84 indicators in various sections. Achieved results indicates that: it is seen that there is much interval and inequality among the cities of this province in terms of being developed, so that mashhad with the development coefficient of 0/42 was identified as the most enjoying city and mahvelat with the development coefficient of 0/99 as the most deprived city of the province.Quchan among other cities of province is in tenth rank based on moris model and standard credit, seventh rank based on taxonomy model, and in deprived class from development position point of view.Thus, according to research findings, the ruling model on spatial structure of khorasan razavi province is dependent on center- surrounding model.

Background: Metal working fluids (MWFs) sprayed through lathe machine operations in the air, are considered as hazardous chemical constituents of working room air. MWFs are detrimental for respiratory system and skin and are also suggested as probable carcinogens. Materials and METHODs: Occupational exposure of a representative group of lathe machine operators exposed to MWFs and a group of assembly workers without active exposure were monitored. Measurements of lung function parameters such as forced expiratory volume in one second (FEV1), forced volume capacity (FVC) and FEV1/FVC of exposed and control groups were obtained after cross-shift exposure to MWFs. Results: Exposure of the majority of lathe machine operators was in excess of the occupational exposure limit for MWFs in the range of 0.1-19.0 mg/m3 with the mean of 8.51 and standard deviation of 2.80 mg/m3. Exposure of the control group (assembly workers) to MWFs was below the sensitivity of analytical METHOD. Differences of predicted lung function parameters (FEV1, FVC) between the exposed and the control population were significant (p<0.001). Correlation coefficient of lung function parameters of FEV1 and FVC with cross-shift exposure was also significant (p<0.001). Conclusion: Considering occupational monitoring of lathe machine operators exposed to MWFs and depression of their lung function parameters, implementation of standard control measures along with periodic lung function monitoring should be done.      

The present NUMERICal study is the second part of an investigation of unsteady cavitating flows. In the first part, cavity formation, establishment and disappearance were recorded using a high speed camera. Cavitation bubble length and diameter were extracted in accelerating and decelerating phases of model flight. Comparison of the experimental results with those of the steady state flow field solution showed an unacceptable agreement. In the present study a more realistic unsteady cavitating flow field simulation of the first part of the experiments is performed. The actual velocity variation of the experimental test is used in a dynamic mesh, unsteady flow field solution. NUMERICal results including the length and diameter of partial cavitation bubble in the accelerating phase had fairly good agreement with the experimental results. This is in contrast to the steady NUMERICal results presented in the first part, which had a significant difference with the experiments. The maximum error of the length and diameter of the supercavitation bubble of the first part of the experimental and present NUMERICal results is less than 10%, while the usual steady results are totally unacceptable.

Background: The Single Assessment NUMERIC Evaluation (SANE) is a simple, one-question patient-reported outcome measure (PROM). We systematically reviewed correlations between SANE and more extensive PROMs. METHODs: We identified studies with correlation coefficients between SANE and other shoulder, knee, and anklespecific PROMs. We calculated mean, median and range across studies and time points of data collection. Results: Eleven studies provided 14 correlations, six shoulder-specific PROMs in four studies, six knee-specific PROMs in six studies and two ankle specific PROMs in one study. The mean correlation comparing SANE and knee-specific PROMs was 0. 60 (SD 0. 24), median 0. 66, and range 0. 12 to 0. 88. Among studies comparing SANE and shoulderspecific PROMs mean correlation was 0. 59 (SD 0. 20), median 0. 62 and range 0. 20 to 0. 89. The mean correlation between SANE and ankle-specific PROMs was 0. 69 (SD 0. 17), median 0. 69 and range 0. 75 to 0. 81. Conclusion: There seems to be moderate correlation amongst PROMs, even those that are a single question. Future research might address whether patient reported outcome measure a common underlying construct even when they consist of a single question.