Large-volume metrology instrument selection and measurability analysis

A wide range of metrology processes are involved in the manufacture of large products. In addition to the traditional tool-setting and product-verification operations, increasingly flexible metrology-enabled automation is also being used. Faced with many possible measurement problems and a very large number of metrology instruments employing diverse technologies, the selection of the appropriate instrument for a given task can be highly complex. Also, as metrology has become a key manufacturing process, it should be considered in the early stages of design, and there is currently very little research to support this. This paper provides an overview of the important selection criteria for typical measurement processes and presents some novel selection strategies. Metrics that can be used to assess measurability are also discussed. A prototype instrument selection and measurability analysis application is also presented, with discussion of how this can be used as the basis for development of a more sophisticated measurement planning tool. © 2010 Authors.

Selection, staging and sequencing in the recent Chinese privatization

Selection in privatization is a decision-making process of choosing state-owned enterprises (SOEs), prioritizing and sequencing privatizing events, and determining the extent of private ownership in partial privatization. We investigate this process in an important but rarely studied case of China. Based on the SOE population over 1998-2008, we track 49,456 wholly SOEs and identify 9,359 privatization cases over time. Our econometric analysis concludes: (i) The privatization selection is a complex decision-making process in which local governments balance between various economic, financial and political objectives. (ii) In the recent Chinese privatization, firm performance relates to the selection, staging and sequencing in privatization in an inverted-U fashion. The worse and the best performing SOEs are more likely to remain state-owned, maintain higher state holding when privatized, and are less likely to be privatized later in time. These patterns suggest the privatization reform slowdown and the underlying changes in the privatization policy.

Visualisation of heterogeneous data with simultaneous feature saliency using Generalised Generative Topographic Mapping

Most machine-learning algorithms are designed for datasets with features of a single type whereas very little attention has been given to datasets with mixed-type features. We recently proposed a model to handle mixed types with a probabilistic latent variable formalism. This proposed model describes the data by type-specific distributions that are conditionally independent given the latent space and is called generalised generative topographic mapping (GGTM). It has often been observed that visualisations of high-dimensional datasets can be poor in the presence of noisy features. In this paper we therefore propose to extend the GGTM to estimate feature saliency values (GGTMFS) as an integrated part of the parameter learning process with an expectation-maximisation (EM) algorithm. The efficacy of the proposed GGTMFS model is demonstrated both for synthetic and real datasets.

Scalability and process transfer of mesenchymal stromal cell production from monolayer to microcarrier culture using human platelet lysate

Background aims: The selection of medium and associated reagents for human mesenchymal stromal cell (hMSC) culture forms an integral part of manufacturing process development and must be suitable for multiple process scales and expansion technologies. Methods: In this work, we have expanded BM-hMSCs in fetal bovine serum (FBS)- and human platelet lysate (HPL)-containing media in both a monolayer and a suspension-based microcarrier process. Results: The introduction of HPL into the monolayer process increased the BM-hMSC growth rate at the first experimental passage by 0.049 day and 0.127/day for the two BM-hMSC donors compared with the FBS-based monolayer process. This increase in growth rate in HPL-containing medium was associated with an increase in the inter-donor consistency, with an inter-donor range of 0.406 cumulative population doublings after 18 days compared with 2.013 in FBS-containing medium. Identity and quality characteristics of the BM-hMSCs are also comparable between conditions in terms of colony-forming potential, osteogenic potential and expression of key genes during monolayer and post-harvest from microcarrier expansion. BM-hMSCs cultured on microcarriers in HPL-containing medium demonstrated a reduction in the initial lag phase for both BM-hMSC donors and an increased BM-hMSC yield after 6 days of culture to 1.20 ± 0.17 × 105 and 1.02 ± 0.005 × 105 cells/mL compared with 0.79 ± 0.05 × 105 and 0.36 ± 0.04 × 105 cells/mL in FBS-containing medium. Conclusions: This study has demonstrated that HPL, compared with FBS-containing medium, delivers increased growth and comparability across two BM-hMSC donors between monolayer and microcarrier culture, which will have key implications for process transfer during scale-up.

Client QoE-oriented segment selection for DASH

A segment selection method controlled by Quality of Experience (QoE) factors for Dynamic Adaptive Streaming over HTTP (DASH) is presented in this paper. Current rate adaption algorithms aim to eliminate buffer underrun events by significantly reducing the code rate when experiencing pauses in replay. In reality, however, viewers may choose to accept a level of buffer underrun in order to achieve an improved level of picture fidelity or to accept the degradation in picture fidelity in order to maintain the service continuity. The proposed rate adaption scheme in our work can maximize the user QoE in terms of both continuity and fidelity (picture quality) in DASH applications. It is shown that using this scheme a high level of quality for streaming services, especially at low packet loss rates, can be achieved. Our scheme can also maintain a best trade-off between continuity-based quality and fidelity-based quality, by determining proper threshold values for the level of quality intended by clients with different quality requirements. In addition, the integration of the rate adaptation mechanism with the scheduling process is investigated in the context of a mobile communication network and related performances are analyzed.

Modelling question selection behaviour in online communities

Value of online Question Answering (QandA) communities is driven by the question-answering behaviour of its members. Finding the questions that members are willing to answer is therefore vital to the effcient operation of such communities. In this paper, we aim to identify the parameters that cor- relate with such behaviours. We train different models and construct effective predictions using various user, question and thread feature sets. We show that answering behaviour can be predicted with a high level of success.

Generalized KPCA by adaptive rules in feature space

Principal component analysis (PCA) is well recognized in dimensionality reduction, and kernel PCA (KPCA) has also been proposed in statistical data analysis. However, KPCA fails to detect the nonlinear structure of data well when outliers exist. To reduce this problem, this paper presents a novel algorithm, named iterative robust KPCA (IRKPCA). IRKPCA works well in dealing with outliers, and can be carried out in an iterative manner, which makes it suitable to process incremental input data. As in the traditional robust PCA (RPCA), a binary field is employed for characterizing the outlier process, and the optimization problem is formulated as maximizing marginal distribution of a Gibbs distribution. In this paper, this optimization problem is solved by stochastic gradient descent techniques. In IRKPCA, the outlier process is in a high-dimensional feature space, and therefore kernel trick is used. IRKPCA can be regarded as a kernelized version of RPCA and a robust form of kernel Hebbian algorithm. Experimental results on synthetic data demonstrate the effectiveness of IRKPCA. © 2010 Taylor & Francis.

Adaptív döntéshozatal a beszállítóválasztásban = Adaptive Decision-making in Supplier Selection

Herbert Simon, a korlátozott racionalitás elméletének megalkotója szerint a döntéshozatalunk hatékonyságát az határozza meg, hogy korlátozott kognitív kapacitásaink birtokában milyen stratégiákkal birkózunk meg a komplex környezet kihívásaival. Az erre az elméletre építő kutatások egyik alapvetése, hogy az egyéni problémamegoldási folyamat helyzetspecifikus és ez az idomulás kulcsfontosságú az eredményességben és hatékonyságban. A döntéshozó rendelkezik egy „adaptív szerszámosládával”, amelyből a megfelelő helyzetekben a megfelelő döntési eljárásokat választja. A tanulmányban a szerző egy kvalitatív kutatás eredményeire építve, a beszállítóválasztás példáján keresztül mutat be lehetséges válaszokat a keveset kutatott kérdésre: hogyan működik az adaptivitás folyamata? A tanulmány a döntési helyzethez való alkalmazkodás kialakulását vizsgálja a döntési folyamatok kognitív szintjén. ______ Herbert Simon, the author of theory of bounded rationality claimed that the results of our decision-making is defined by the approprietness of strategies with which we handle the complexity of the environment with our bounded cognitive capacities. One of the main issues or research programs building on this theory is that problem solving is situation-specific, and the adjustment of strategies to actual situational factors is crucial for the effectiveness and efficiency of decision-making. The decision-maker possesses an „adaptive toolbox”, from which he chooses the right decision tools in the right situations. The author, based on the findnings of a qualitative study, presents possible answers to the not well-elaborated question: how does the process of adaptivity work? Forming of an adaptive mechanism is in the focus.

Adaptív döntéshozatal a beszállítóválasztás példáján (Adaptive decision-making on example of the supplier selection)

Ez a tanulmány a projektvezetési szakirodalomban kialakult ismeretanyagot szem előtt tartva (noha tételesen nem hivatkozva arra) tárja fel azt a sajátos és tipikusnak nevezhető kontextust, amelyben a projektalapú szervezetek projektmarketing tevékenysége megnyilvánul. A tanulmány célja tehát nem magának a projektmarketingnek a kérdéskörére irányul, hanem elsősorban annak projektspecifikus kontextusára. Jellegét illetően a tanulmány spekulatív jellegű, vagyis lényegét tekintve nem empirikus kutatási eredményekből levont következtetésekre épül. _____ The author analyses the cognitive level of individual decisions by placing the adaptive decision-maker in the centre of interest. The main question is how do adaptive processes evolve and what factors determine the adaptive mechanism. The author builds on his own qualitative study conducted with the Grounded Theory Methodology in the SME sector. The supplier selection decision is chosen from the wide range of business decisions. From the research results the two elements of the adaptive mechanism – the metastructure and the attitude set –, the process of their evolution and the factors determining this process are presented. The findings here are a middle-range theory, which can be elaborated further, but they provide some interesting insights already.

The effects of writing process instruction on the writing and reading performance of students with learning disabilities

The purpose of this study was to determine the efficacy of a writing process approach for the instruction of language arts with learning disabled elementary students. A nonequivalent control group design was used. The sample included 24 students with learning disabilities who were in second and third grade. All students were instructed in resource room settings for ninety minutes per day in language arts. The students in the treatment group received instruction using the writing process steps to create complete meaningful compositions on self-chosen topics. A literature-based reading program accompanied instruction in writing to provide examples of good writing and to provide a basis for topic selection. The students in the control group received instruction through the use of the county-adopted textbooks and accompanying worksheets. The teacher followed basic textbook and curriculum guide suggestions which consisted mainly of fill in the blank and matching type exercises. The treatment group consisted of 12 students: five second-graders and seven third-graders. The control group consisted of 12 students: four second-graders and eight third-graders. All students were pretested and posttested using the Woodcock-Johnson Tests of Achievement-Revised (WJ-R ACH) for writing samples and the Woodcock Reading Mastery Test (WRMT) for reading achievement. T-tests were also done to investigate the gain from pre to post for each reading or writing variable for each group separately. The results showed a highly significant difference from pretest to posttest for all writing and reading variables for both groups. Analysis of Covariance showed that the population mean posttest achievement scores for all variables adjusted for the pretest were higher for the treatment group than those for the control group.

Contribution of the vasculature to the Alzheimer's disease process

One of the pathological hallmarks of Alzheimer's disease (AD) brain is extracellular β-amyloid (Aβ) plaques containing 39-42 amino acid Aβ peptides. The deposition of Aβ around blood vessels, known as Cerebral amyloid angiopathy (CAA), is also a common feature in AD brain. Vascular density and cerebral blood flow are reduced in AD brains, and vascular risk factors such as hypertension and diabetes are also risk factors for AD. We have shown previously that Aβ peptides can potently inhibit angiogenesis both in-vitro and in-vivo, but the mechanism of action for this effect is not known. Therefore, my first hypothesis was that particular amino acid sequence(s) within the Aβ peptide are required for inhibition of angiogenesis. From this aim, I found a peptide sequence which was critical for anti-angiogenic activity (HHQKLVFF). This sequence contains a heparan sulfate proteoglycan growth factor binding domain implying that Aβ can interfere with growth factor signaling. Leading on from this, my second hypothesis was that Aβ can inhibit angiogenesis by binding to growth factor receptors. I found that Aβ can bind to Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2), and showed that this is one mechanism by which Aβ can inhibit angiogenesis. Since the vasculature is disrupted in AD brains, I investigated whether a strategy to increase brain vascularization would be beneficial against AD pathology. Therefore, my third hypothesis was that voluntary exercise (which is known to increase brain vascularization in rodents) can ameliorate Aβ pathology, increase brain vascularization, and improve behavioral deficits in a transgenic mouse model of AD. I found that exercise has no effect on Aβ pathology, brain vascularization or behavioral deficits. Therefore, in the transgenic mouse model that I used, exercise is an ineffective therapeutic strategy against AD pathology and symptoms.

Comprehensive process maps for synthesizing high density aluminum oxide-carbon nanotube coatings by plasma spraying for improved mechanical and wear properties

Plasma sprayed aluminum oxide ceramic coating is widely used due to its outstanding wear, corrosion, and thermal shock resistance. But porosity is the integral feature in the plasma sprayed coating which exponentially degrades its properties. In this study, process maps were developed to obtain Al2O3-CNT composite coatings with the highest density (i.e. lowest porosity) and improved mechanical and wear properties. Process map is defined as a set of relationships that correlates large number of plasma processing parameters to the coating properties. Carbon nanotubes (CNTs) were added as reinforcement to Al2O 3 coating to improve the fracture toughness and wear resistance. Two novel powder processing approaches viz spray drying and chemical vapor growth were adopted to disperse CNTs in Al2O3 powder. The degree of CNT dispersion via chemical vapor deposition (CVD) was superior to spray drying but CVD could not synthesize powder in large amount. Hence optimization of plasma processing parameters and process map development was limited to spray dried Al2O3 powder containing 0, 4 and 8 wt. % CNTs. An empirical model using Pareto diagram was developed to link plasma processing parameters with the porosity of coating. Splat morphology as a function of plasma processing parameter was also studied to understand its effect on mechanical properties. Addition of a mere 1.5 wt. % CNTs via CVD technique showed ∼27% and ∼24% increase in the elastic modulus and fracture toughness respectively. Improved toughness was attributed to combined effect of lower porosity and uniform dispersion of CNTs which promoted the toughening by CNT bridging, crack deflection and strong CNT/Al2O3 interface. Al2O 3-8 wt. % CNT coating synthesized using spray dried powder showed 73% improvement in the fracture toughness when porosity reduced from 4.7% to 3.0%. Wear resistance of all coatings at room and elevated temperatures (573 K, 873 K) showed improvement with CNT addition and decreased porosity. Such behavior was due to improved mechanical properties, protective film formation due to tribochemical reaction, and CNT bridging between the splats. Finally, process maps correlating porosity content, CNT content, mechanical properties, and wear properties were developed.

The order selection and lot sizing problem in the make-to-order environment

This research is motivated by the need for considering lot sizing while accepting customer orders in a make-to-order (MTO) environment, in which each customer order must be delivered by its due date. Job shop is the typical operation model used in an MTO operation, where the production planner must make three concurrent decisions; they are order selection, lot size, and job schedule. These decisions are usually treated separately in the literature and are mostly led to heuristic solutions. The first phase of the study is focused on a formal definition of the problem. Mathematical programming techniques are applied to modeling this problem in terms of its objective, decision variables, and constraints. A commercial solver, CPLEX is applied to solve the resulting mixed-integer linear programming model with small instances to validate the mathematical formulation. The computational result shows it is not practical for solving problems of industrial size, using a commercial solver. The second phase of this study is focused on development of an effective solution approach to this problem of large scale. The proposed solution approach is an iterative process involving three sequential decision steps of order selection, lot sizing, and lot scheduling. A range of simple sequencing rules are identified for each of the three subproblems. Using computer simulation as the tool, an experiment is designed to evaluate their performance against a set of system parameters. For order selection, the proposed weighted most profit rule performs the best. The shifting bottleneck and the earliest operation finish time both are the best scheduling rules. For lot sizing, the proposed minimum cost increase heuristic, based on the Dixon-Silver method performs the best, when the demand-to-capacity ratio at the bottleneck machine is high. The proposed minimum cost heuristic, based on the Wagner-Whitin algorithm is the best lot-sizing heuristic for shops of a low demand-to-capacity ratio. The proposed heuristic is applied to an industrial case to further evaluate its performance. The result shows it can improve an average of total profit by 16.62%. This research contributes to the production planning research community with a complete mathematical definition of the problem and an effective solution approach to solving the problem of industry scale.

Measurability characteristics mapping for large volume metrology instruments selection

Measurement and verification of products and processes during the early design is attracting increasing interest from high value manufacturing industries. Measurement planning is deemed as an effective means to facilitate the integration of the metrology activity into a wider range of production processes. However, the literature reveals that there are very few research efforts in this field, especially regarding large volume metrology. This paper presents a novel approach to accomplish instruments selection, the first stage of measurement planning process, by mapping measurability characteristics between specific measurement assignments and instruments.

Large volume metrology instrument selection and measurability analysis

Metrology processes used in the manufacture of large products include tool setting, product verification and flexible metrology enabled automation. The range of applications and instruments available makes the selection of the appropriate instrument for a given task highly complex. Since metrology is a key manufacturing process it should be considered in the early stages of design. This paper provides an overview of the important selection criteria for typical measurement processes and presents some novel selection strategies. Metrics which can be used to assess measurability are also discussed. A prototype instrument selection and measurability analysis application is presented with discussion of how this can be used as the basis for development of a more sophisticated measurement planning tool. © Springer-Verlag Berlin Heidelberg 2010.