Developing an Interactive Spatial Multi-Attribute Decision Support System for Assessing Water Resources Allocation Scenarios

Water Resources Management - In water resource management, assessing water resource allocation scenarios (WRASs) is an important multi-attribute decision making (MADM) problem. It involves...     

Modelling of air damping effect on the performance of encapsulated MEMS resonators

Microsystem Technologies - The dynamic performance of a micro-resonator depends on its energy loss mechanism which is quantified by Q-factor (Quality factor). This paper presents numerical...     

Reference Range Estimation: Accounting for Measurement System Errors

Reference range is a statistic that is used in health related fields to represent the range of the most likely values for a variable of interest. Based on this range, individuals are classified as being healthy or unhealthy. In biostatistics, the reference range is calculated as the (1 ? α)% prediction interval, where this prediction interval is based on the estimated population variance from the data. Such estimation of population variance is not precise, because obtained test results do usually have errors associated with them. These errors are due to the imprecise test procedure or gauge used. In this paper, the total variability in the data is decomposed into two categories. The first is the patient‐to‐patient variability and the other is the variability due to the measurement system used. Estimation of the two kinds is performed through a gauge repeatability and reproducibility study, then the reference range is calculated, taking into account only the patient‐to‐patient variability. The revised reference range procedure is illustrated through a case study of vitamin B12 test results. A closed form formula is given to calculate the probability of a given test result being within the revised reference range. Copyright © 2015 John Wiley & Sons, Ltd.     

Tracking and Analysis of Pedestrian’s Behavior in Public Places

Crowd management becomes a global concern due to increased population in urban areas. Better management of pedestrians leads to improved use of public places. Behavior of pedestrian’s is a major factor of crowd management in public places. There are multiple applications available in this area but the challenge is open due to complexity of crowd and depends on the environment. In this paper, we have proposed a new method for pedestrian’s behavior detection. Kalman filter has been used to detect pedestrian’s using movement based approach. Next, we have performed occlusion detection and removal using region shrinking method to isolate occluded humans. Human verification is performed on each human silhouette and wavelet analysis and particle gradient motion are extracted for each silhouettes. Gray Wolf Optimizer (GWO) has been utilized to optimize feature set and then behavior classification has been performed using the Extreme Gradient (XG) Boost classifier. Performance has been evaluated using pedestrian’s data from avenue and UBI-Fight datasets, where both have different environment. The mean achieved accuracies are 91.3% and 85.14% over the Avenue and UBI-Fight datasets, respectively. These results are more accurate as compared to other existing methods.     

Pan Evaporation Modeling Using Neural Computing Approach for Different Climatic Zones

The purpose of this study was to develop and apply the neural networks models to estimate daily pan evaporation (PE) for different climatic zones such as temperate and arid climatic zones, Republic of Korea and Iran. Three kinds of the neural networks models, namely multilayer perceptron-neural networks model (MLP-NNM), generalized regression neural networks model (GRNNM), and support vector machine-neural networks model (SVM-NNM), were used to estimate daily PE. The available climatic variables, consisted of mean air temperature (T_mean), mean wind speed (U_mean), sunshine duration (SD), mean relative humidity (RH_mean), and extraterrestrial radiation (R_a) were used to estimate daily PE using the various input combinations of climate variables. The measurements for the period of January 1985?CDecember 1990 (Republic of Korea) and January 2002?CDecember 2008 (Iran) were used for training and testing the employed neural networks models. The results obtained by SVM-NNM indicated that it performs better than MLP-NNM and GRNNM for estimating daily PE. A comparison was also made among the employed models, which demonstrated the superiority of MLP-NNM, GRNNM, and SVM-NNM over Linacre model and multiple linear regression model (MLRM).     

Ranking alternatives in a preferential voting system using fuzzy concepts and data envelopment analysis

In this paper, a new method for aggregating the opinions of experts in a preferential voting system is proposed. The method, which uses fuzzy concept in handling crisp data, is computationally efficient and is able to completely rank the alternatives. Through this method, the number of votes for certain rank position that each alternative receives are first grouped together to form fuzzy numbers. The nearest point to a fuzzy number concept is then used to introduce an artificial ideal alternative. Data envelopment analysis is next used to find the efficiency scores of the alternatives in a pair-wise comparison with the artificial ideal alternative. Alternatives are rank based on these efficiency scores. If the alternatives are not completely ranked, a weight restriction method also based on fuzzy concept is used on the un-discriminated alternatives until they are completely ranked. Two examples are given for illustration of the method.     

Aerosol Process for the In Situ Coating of Nanoparticles with a Polymer Shell

This article presents a novel method to encapsulate gas-borne nanoparticles with a polymeric shell. This method implies heterogeneous condensation of monomer vapor around the surface of nanoparticles as nuclei and polymerization is then subsequently started by addition of NH₃ as aerosol initiator. Ag and SiO₂ nanoparticles were generated as inorganic core by spark discharge and nebulization, respectively, and glycidyl methacrylate (GMA) was used as organic monomer. The effect of several parameters, including vapor pressure of monomer and properties of inorganic core such as morphology, material, particle size, and production method on the thickness of polymeric shell and morphology of resulting nanocomposites has been investigated. The particle size distribution and morphology of the resulting core-shell nanoparticles have been studied via scanning mobility particle sizer (SMPS) and transmission electron microscope (TEM). Finally, the coating efficiency was determined by aerosol photoemission (APE) and the results show that monomer and polymer coating efficiency are 99% and 60%, respectively.

Copyright 2014 American Association for Aerosol Research     

Alkaline hydrolysis of the cyclic nitramine explosives RDX,HMX, and CL-20: new insights into degradation pathways obtained by the observation of novel intermediates

Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX, I) and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) hydrolyze at pH > 10 to form end products including NO2-, HCHO, HCOOH, NH3, and N2O, but little information is available on intermediates, apart from the tentatively identified pentahydro-3,5-dinitro-1,3,5-triazacyclohex-1-ene (II). Despite suggestions that RDX and HMX contaminated groundwater could be economically treated via alkaline hydrolysis, the optimization of such a process requires more detailed knowledge of intermediates and degradation pathways. In this study, we hydrolyzed the monocyclic nitramines RDX, MNX (hexahydro-1-nitroso-3,5-dinitro-1,3,5-triazine), and HMX in aqueous solution (pH 10-12.3) and found that nitramine removal was accompanied by formation of 1 molar equiv of nitrite and the accumulation of the key ring cleavage product 4-nitro-2,4-diazabutanal (4-NDAB, O2NNHCH2NHCHO). Most of the remaining C and N content of RDX, MNX, and HMX was found in HCHO, N2O, HCOOH, and NH3. Consequently, we selected RDX as a model compound and hydrolyzed it in aqueous acetonitrile solutions (pH 12.3) in the presence and absence of hydroxypropyl-beta-cyclodextrin (HP-beta-CD) to explore other early intermediates in more detail. We observed a transient LC-MS peak with a [M-H] at 192 Da that was tentatively identified as 4,6-dinitro-2,4,6-triaza-hexanal (O2NNHCH2NNO2CH2NHCHO, III) considered as the hydrolyzed product of II. In addition, we detected another novel intermediate with a [M-H] at 148 Da that was tentatively identified as a hydrolyzed product of III, namely, 5-hydroxy-4-nitro-2,4-diaza-pentanal (HOCH2NNO2CH2NHCHO, IV). Both III and IV can act as precursors to 4-NDAB. In the case of the polycyclic nitramine 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20), denitration (two NO2-) also led to the formation of HCOOH, NH3, and N2O, but neither HCHO nor 4-NDAB were detected. The results provide strong evidence that initial denitration of cyclic nitramines in water is sufficient to cause ring cleavage followed by spontaneous decomposition to form the final products.