Improvement of Crystallinity of KZr2P3O12 by Sol-Gel Synthesis

The X-ray diffraction pattern for potassium-zirconium phosphate is significantly improved when the material is prepared by the sol-gel route rather than the powder method. Peaks at high, low, and intermediate angles are presented and compared for the two methods. It is assumed that the more nearly homogeneous mixing of the elements in the sol-gel process is responsible for the significant improvement in crystallinity.     

Prediction of Experimental Methanol Decomposition Rates on Platinum from First Principles

A microkinetic model for methanol decomposition on platinum is presented. The model incorporates competitive decomposition pathways, beginning with both O–H and C–H bond scission in methanol, and uses results from density functional theory (DFT) calculations [Greeley and Mavrikakis, J. Am. Chem. Soc. 124 (2002) 7193, Greeley and Mavrikakis, J. Am. Chem. Soc. 126 (2004) 3910]. Results from reaction kinetics experiments show that the rate of H₂ production increases with increasing temperature and methanol concentration in the feed and is only nominally affected by the presence of CO or H₂ with methanol. The model, based on the values of binding energies, pre-exponential factors and activation energy barriers derived from first principles calculations, accurately predicts experimental reaction rates and orders. The model also gives insight into the most favorable reaction pathway, the rate-limiting step, the apparent activation energy, coverages, and the effects of pressure. It is found that the pathway beginning with the C–H bond scission (CH₃OH→H₂COH→HCOH→CO) is dominant compared with the path beginning with O–H bond scission. The cleavage of the first C–H bond in methanol is the rate-controlling step. The surface is highly poisoned by CO, whereas COH appears to be a spectator species.     

Melt‐processable rubber: Chlorinated waste tire rubber‐filled polyvinyl chloride

Chlorinated ground rubber tire (Cl‐GRT) particles were used as filler in a plasticized polyvinylchloride (PVC) to develop a melt‐processable rubber composition. Physical properties of the Cl‐GRT‐filled PVC compound showed improvement compared to the nonchlorinated counterpart. Interaction between Cl‐GRT and PVC was examined on the basis of results of stress relaxation, dynamic mechanical thermal analysis, and solvent swelling studies. The Cl‐GRT could be loaded upto 40 parts per hundred parts of PVC, and the composition still retains the elastomeric characteristics. The Cl‐GRT‐filled composite was found to be reprocessable like the unfilled PVC compound. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 84: 622–631, 2002; DOI 10.1002/app.10352     

Multi-objective Optimization Based Recursive Feature Elimination for Process Monitoring

Neural Processing Letters - Process monitoring helps to estimate the quality of the end products, equipment health parameters, and operational reliability of chemical processes. This is an area in...     

Automated bank cheque verification using image processing and deep learning methods

Multimedia Tools and Applications - Automated bank cheque verification using image processing is an attempt to complement the present cheque truncation system, as well as to provide an alternate...     

高速公路施工区车辆强制换道耗时生存模型

为研究高速公路施工区车辆强制换道行为及其影响因素,采用生存分析中的半参数分析方法建立强制换道耗时的乘法风险率模型.通过无人机拍摄采集高速公路施工区的车辆换道耗时及其影响因素数据,最终确立换道耗时Cox比例风险模型,对换道耗时数据进行Cox回归建模分析.结果表明:近77%的换道车辆在10 s内完成换道;小型车和中型车经养护施工区的换道耗时未发现显著性差别;对于相同的换道耗时,平峰期的累积生存率明显低于高峰期和过渡时期,而高峰期的累积生存率最高.建立的强制换道耗时生存模型可有效的定量分析车型和交通时段对高速公路施工区车辆换道行为的影响,可为高速公路施工区交通管理控制及车辆换道行为建模及仿真奠定一定的理论基础.     

Multi-objective reactive power market clearing in competitive electricity market using HFMOEA

This paper presents an application of a hybrid fuzzy multi-objective evolutionary algorithm (HFMOEA) for solving a highly constraint, mixed integer type, complex multi-objective reactive power market clearing (RPMC) problem for the competitive electricity market environment. In HFMOEA based multi-objective optimization approach, based on the output of a fuzzy logic controller crossover and mutation probabilities are varied dynamically. It enhances stochastic search capabilities of HFMOEA. In multi-objective RPMC optimization framework, two objective functions namely the total payment function (TPF) for reactive power support from generators and synchronous condensers and the total real transmission loss (TRTL) are minimized simultaneously for clearing the reactive power market. The proposed HFMOEA based multi-objective RPMC scheme is tested on a standard IEEE 24 bus reliability test system and its performance is compared with five other multi-objective evolutionary techniques such as MOPBIL, NSGA-II, UPS-EMOA and SPEA-2 and a new extended form of NSGA (ENSGA-II). Applying all these six evolutionary techniques, a detailed statistical analysis using T-test and boxplots is carried out on three performance metrics (spacing, spread and hypervolume) data for RPMC problem. The obtained simulation results confirm the overall superiority of HFMOEA to generate better Pareto-optimal solutions with higher convergence rate as compared to above mentioned algorithms. Further, TPF and TRTL values corresponding to the best compromise solutions are obtained using said multi-objective evolutionary techniques. These values are compared with one another to take better market clearing decisions in competitive electricity environment.     

On semantic annotation of decision models

The growth of service sector in recent years has led to renewed research interests in the design and management of service systems. Decision support systems (DSS) play an important role in supporting this endeavor, through management of organizational resources such as models and data, thus forming the “back stage” of service systems. In this article, we identify the requirements for semantically annotating decision models and propose a model representation scheme, termed Semantically Annotated Structure Modeling Markup Language (SA-SMML) that extends Structure Modeling Markup Language (SMML) by incorporating mechanisms for linking semantic models such as ontologies that represent problem domain knowledge concepts. This model representation format is also amenable to a scalable Service-Oriented Architecture (SOA) for managing models in distributed environments. The proposed model representation technique leverages recent advances in the areas of semantic web, and semantic web services. Along with design considerations, we demonstrate the utility of this representation format with an illustrative usage scenarios with a particular emphasis on model discovery and composition in a distributed environment.     

Fault tolerant multiple event detection in a wireless sensor network

With an increasing acceptance of Wireless Sensor Networks (WSNs), the health of individual sensor is becoming critical in identifying important events in the region of interest. One of the key challenges in detecting event in a WSN is how to detect it accurately transmitting minimum information providing sufficient details about the event. At the same time, it is also important to devise a strategy to handle multiple events occurring simultaneously. In this paper, we propose a Polynomial-based scheme that addresses these problems of Event Region Detection (PERD) by having a aggregation tree of sensor nodes. We employ a data aggregation scheme, TREG (proposed in our earlier work) to perform function approximation of the event using a multivariate polynomial regression. Only coefficients of the polynomial (P$P$) are passed instead of aggregated data. PERD includes two components: event recognition and event report with boundary detection. This can be performed for multiple simultaneously occurring events. We also identify faulty sensor(s) using the aggregation tree. Performing further mathematical operations on the calculated P$P$ can identify the maximum (max) and minimum (min) values of the sensed attribute and their locations. Therefore, if any sensor reports a data value outside the [min, max] range, it can be identified as a faulty sensor. Since PERD is implemented over a polynomial tree on a WSN in a distributed manner, it is easily scalable and computation overhead is marginal. Results reveal that event(s) can be detected by PERD with error in detection remaining almost constant achieving a percentage error within a threshold of 10%$10\%$ with increase in communication range. Results also show that a faulty sensor can be detected with an average accuracy of 94%$94\%$ and it increases with increase in node density.