Silver nanocluster formation in silicate glass by single step ion-exchange

We report the formation of silver nanoclusters of average size ∼ 1.1 nm in a single step ion-exchanged silica glass. Silver clusters are formed in a glass during ion-exchange by fine-tuning the ion-exchange parameters such as salt composition, temperature and time. Such nanocluster formation during ion-exchange preserves the waveguiding properties of the ion-exchanged surface of the glass making them suitable for nonlinear waveguide device fabrication.     

An objective comparison of the cost effectiveness of three testing methods

Branch testing is a well established method for exercising software. JJ-path testing, whilst employed by some practitioners, is less popular, and the testing of JJ-pairs finds few adherents. In this paper an objective, practical study of the cost-effectiveness of these three testing methods is reported. The effectiveness of each method is assessed, in the presence of infeasible paths, not only on its ability to cover the specific structural element of code that it targets, but also on its ability to cover the structural elements targeted by the other two methods – the collateral coverage it achieves. The assessment is based on the results derived from experiments in which each of the three methods is applied to 35 units of program code.     

A new method of strength calculation and lifetime prediction of pipe bends operating in the creep range

An easy to use method for an approximate creep life prediction for pipe bends was developed within a recent R & D-project in Germany. The new algorithm is based on a Finite-Element parameter study comprising approximately 200 pipe bends. The creep behaviour of the materials primarily used for main steam and hot reheat piping is described using the Graham–Walles creep law. Since the new algorithm considers the time dependent out-of-roundness and stress redistribution of the pipe bend, it yields a more precise creep life prediction, compared to standard piping codes. It is possible to integrate this new calculation into existing online lifetime-monitoring-systems.     

A new approach for constructing the concept map

In recent years, e-learning system has become more and more popular and many adaptive learning environments have been proposed to offer learners customized courses in accordance with their aptitudes and learning results. For achieving the adaptive learning, a predefined concept map of a course is often used to provide adaptive learning guidance for learners. However, it is difficult and time consuming to create the concept map of a course. Thus, how to automatically create a concept map of a course becomes an interesting issue. In this paper, we propose a Two-Phase Concept Map Construction (TP-CMC) approach to automatically construct the concept map by learners’ historical testing records. Phase 1 is used to preprocess the testing records; i.e., transform the numeric grade data, refine the testing records, and mine the association rules from input data. Phase 2 is used to transform the mined association rules into prerequisite relationships among learning concepts for creating the concept map. Therefore, in Phase 1, we apply Fuzzy Set Theory to transform the numeric testing records of learners into symbolic data, apply Education Theory to further refine it, and apply Data Mining approach to find its grade fuzzy association rules. Then, in Phase 2, based upon our observation in real learning situation, we use multiple rule types to further analyze the mined rules and then propose a heuristic algorithm to automatically construct the concept map. Finally, the Redundancy and Circularity of the concept map constructed are also discussed. Moreover, we also develop a prototype system of TP-CMC and then use the real testing records of students in junior high school to evaluate the results. The experimental results show that our proposed approach is workable.     

Service quality and ERP implementation: A conceptual and empirical study of semiconductor-related industries in Taiwan

This paper examines the effectiveness of the implementation of enterprise resource planning (ERP) in improving service quality in the Taiwanese semiconductor industry by assessing the expectations and the perceptions of service quality from the perspectives of both upstream manufacturers and downstream customers. The study first establishes a modified service quality gap model incorporating: (i) the downstream customers’ expectations and perceptions, and (ii) the upstream manufacturers’ perceptions of the customers’ expectations and perceptions. An empirical study by questionnaire survey is then undertaken to investigate the gaps proposed in the research model. The results show that service quality gaps do exist in the Taiwanese semiconductor industry between upstream manufacturers that are implementing ERP and their downstream customers. The study shows that the proposed model provides valuable guidance to manufacturers with respect to the prevention, detection, and elimination of the demonstrated service quality gaps. The model thus helps manufacturers to evaluate the contribution of various ERP modules to improved customer satisfaction with service quality and also provides guidance on improvement strategies to enhance service quality by eliminating quality gaps.     

A weighted multivariate Fuzzy C-Means method in interval-valued scientific production data

Clustering is the process of organizing objects into groups whose members are similar in some way. Most of the clustering methods involve numeric data only. However, this representation may not be adequate to model complex information which may be: histogram, distributions, intervals. To deal with these types of data, Symbolic Data Analysis (SDA) was developed. In multivariate data analysis, it is common some variables be more or less relevant than others and less relevant variables can mask the cluster structure. This work proposes a clustering method based on fuzzy approach that produces weighted multivariate memberships for interval-valued data. These memberships can change at each iteration of the algorithm and they are different from one variable to another and from one cluster to another. Furthermore, there is a different relevance weight associated to each variable that may also be different from one cluster to another. The advantage of this method is that it is robust to ambiguous cluster membership assignment since weights represent how important the different variables are to the clusters. Experiments are performed with synthetic data sets to compare the performance of the proposed method against other methods already established by the clustering literature. Also, an application with interval-valued scientific production data is presented in this work. Clustering quality results have shown that the proposed method offers higher accuracy when variables have different variabilities.     

Validating an object placement planner for robotic pick-and-place tasks

This paper proposes an object placement planner for a grasped object during pick-and-place tasks. The proposed planner automatically determines the pose of an object that is stably placed near a user-assigned point on the environment surface. In our proposed method, first the polygon models of both the object and the environment are clustered, with each cluster being approximated by a planar region. The position/orientation of an object placed on the environment surface can be determined by selecting a pair of clusters: one from the object and the other from the environment. We furthermore conduct several tests to determine the position/orientation of the object, namely the Convexity Test, the Contact Test and the Stability Test. We demonstrate that, by using the polygon model of the environment that is obtained by means of conversion of the point cloud, we can determine the position/orientation of an object and can thereby realize a pick-and-place task.     

Model checking response times in Networked Automation Systems using jitter bounds

Response time (RT) of Networked Automation Systems (NAS) is affected by timing imperfections induced due to the network, computing and hardware components. Guaranteeing RT in the presence of such timing imperfections is essential for building dependable NAS, and to avoid costly upgrades after deployment in industries.This investigation proposes a methodology and work-flow that combines modelling, simulation, verification, experiments, and software tools to verify the RT of the NAS during the design, rather than after deployment. The RT evaluation work-flow has three phases: model building, modelling and verification. During the model building phase component reaction times are specified and their timing performance is measured by combining experiments with simulation. During the modelling phase, component based mathematical models that capture the network architecture and inter-connection are proposed. Composition of the component models gives the NAS model required for studying the RT performance on system level. Finally, in the verification step, the NAS formal models are abstracted as UPPAAL timed automata with their timing interfaces. To model timing interfaces, the action patterns, and their timing wrapper are proposed. The formal model of high level of abstraction is used to verify the total response time of the NAS where the reactions to be verified are specified using a subset of timed computation tree logic (TCTL) in UPPAAL model checker. The proposed approach is illustrated on an industrial steam boiler deployment.