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.

The risk of adverse selection and its management in the process of venture capital investment (The experience of Hungarian investors)

Venture capitalists can be regarded as financers of young, high-risk enterprises, seeking investments with a high growth potential and offering professional support above and beyond their capital investment. The aim of this study is to analyse the occurrence of information asymmetry between venture capital investors and entrepreneurs, with special regard to the problem of adverse selection. In the course of my empirical research, I conducted in-depth interviews with 10 venture capital investors. The aim of the research was to elicit their opinions about the situation regarding information asymmetry, how they deal with problems arising from adverse selection, and what measures they take to manage these within the investment process. In the interviews we also touched upon how investors evaluate state intervention, and how much they believe company managers are influenced by state support.

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.

Selection Of Students For Hotel Schools: A Comparative Study

In the discussion - Selection Of Students For Hotel Schools: A Comparative Study - by William Morgan, Professor, School of Hospitality Management at Florida International University, Morgan’s initial observation is: “Standards for the selection of students into schools of hospitality management around the world vary considerably when it comes to measuring attitudes toward the industry. The author discusses current standards and recommends some changes.” In addition to intellectual ability, Professor Morgan wants you to know that an intangible element such as attitude is an equally important consideration to students seeking curriculum and careers in the hospitality field. “…breaches in behavior or problems in the tourist employee encounter are often caused by attitudinal conditions which pre exist the training and which were not able to be totally corrected by the unfreezing, movement, and refreezing processes required in attitudinal change,” says Morgan. “…other than for some requirements for level or grade completed or marks obtained, 26 of the 54 countries sampled (48.1 percent) had no pre-selection process at all. Of those having some form of a selection process (in addition to grades), 14 schools in 12 countries (22.2 percent) had a formal admissions examination,” Professor Morgan empirically provides. “It was impossible, however, to determine the scope of this admissions examination as it might relate to attitude.” The attitude intangible is a difficult one to quantify. With an apparent sameness in hotels, restaurants, and their facilities the significant distinctions are to be found in their employees. This makes the selection process for both schools and employers a high priority. Moreover, can a student, or a prospective employee, overcome stereotypes and prejudices to provide a high degree of service in the hospitality industry? This query is an important element of this article. “If utilized in the hotel, technical, or trade school or in the hiring process at the individual facility, this [hiring] process would provide an opportunity to determine if the prospective student or worker is receptive to the training to be received,” advises Professor Morgan. “Such a student or worker is realistic in his aims and aspirations, ready in his ability to receive training, and responsive to the needs of the guest, often someone very different from himself in language, dress, or degree of creature comforts desired,” your author further counsels. Professor Morgan looks to transactional analysis, role playing, languages, and cross cultural education as playing significant roles in producing well intentioned and knowledgeable employees. He expands upon these concepts in the article. Professor Morgan holds The International Center of Glion, Switzerland in high regard and cites that program’s efforts to maintain relationships and provide graduates with ongoing attitudinal enlightenment programs.

Solving satisfiability, *implication, and equivalence problems in database systems

Satisfiability, implication and equivalence problems are important and widely-encountered database problems that need to be efficiently and effectively solved. We provide a comprehensive and systematic study of these problems. We consider three popular types of arithmetic inequalities, (X op C), (X op Y), and (X op Y + C), where X and Y are attributes, C is a constant of the domain of X, and op $\in\ \{{<},\ {\le},\ {=},\ {\not=},\ {>},\ {\ge}\}.$ These inequalities are most frequently used in a database system, since the first type of inequalities represents $\theta$-join, the second type represents selection, and the third type is popular in deductive databases. We study the problems under the integer domain and the real domain, as well as under two different operator sets.^ Our results show that solutions under different domains and/or different operator sets are quite different. In this dissertation, we either report the first necessary and sufficient conditions as well as their efficient algorithms with complexity analysis, or provide improved algorithms. ^

Biological factors affecting sea survival of Atlantic salmon Salmo salar L., in Western Arm Brook and an analysis of selection by the commercial fishery of nearby St. Barbe Bay, Newfoundland

The problems faced by scientists in charge of managing Atlantic salmon (Salmo salar) stocks are : i) how to maintain spawning runs consisting of repeat spawners and large multi-sea-winter (MSW) adults in the face of selective homewater and distant commercial fisheries and , ii) how to more accurately predict returns of adults. Using data from scales collected from maiden Atlantic salmon grilse from two locations on the Northern Peninsula of Newfoundland, St. Barbe Bay and Western Arm Brook, their length at smolting was back calculated. These data were then used to examine whether the St. Barbe commercial fishery is selective for salmon of particular smolt age and/or size. Analysis indicated that come commercial fishery selected larger, but not necessarily older adults that those escaping to Western Arm Brook over the period of this study, 1978-1987. It was determined that less than average size smolts survived better than above average size smolts. Slection for repeat spawners, large MSW salmon, and larger grilse has meant reductions in the proportions of these adults in the spawning runs on Western Arm Brook. This may impact the Western Arm Brook salmon stock by increasing the population instability. Sea survival was significantly correlated with selection by the commercial fishery. Characteristics of adults in Western Arm Brook during the period of study (1978-1987) did not help in explaining yearly variation in sea survival. The characteristics of smolts, however, when subjected to multiple regression analysis explained 57.2 percent of the yearly variation in sea survival.

Ant Colony Optimization for Requirement selection in Incremental Software development

This proposal shows that ACO systems can be applied to problems of requirements selection in software incremental development, with the idea of obtaining better results of those produced by expert judgment alone. The evaluation of the ACO systems should be done through a compared analysis with greedy and simulated annealing algorithms, performing experiments with some problems instances

A Pyramidal Genetic Algorithm for Multiple-Choice Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence, higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

Tensor Completion for Multidimensional Inverse Problems with Applications to Magnetic Resonance Relaxometry

This thesis deals with tensor completion for the solution of multidimensional inverse problems. We study the problem of reconstructing an approximately low rank tensor from a small number of noisy linear measurements. New recovery guarantees, numerical algorithms, non-uniform sampling strategies, and parameter selection algorithms are developed. We derive a fixed point continuation algorithm for tensor completion and prove its convergence. A restricted isometry property (RIP) based tensor recovery guarantee is proved. Probabilistic recovery guarantees are obtained for sub-Gaussian measurement operators and for measurements obtained by non-uniform sampling from a Parseval tight frame. We show how tensor completion can be used to solve multidimensional inverse problems arising in NMR relaxometry. Algorithms are developed for regularization parameter selection, including accelerated k-fold cross-validation and generalized cross-validation. These methods are validated on experimental and simulated data. We also derive condition number estimates for nonnegative least squares problems. Tensor recovery promises to significantly accelerate N-dimensional NMR relaxometry and related experiments, enabling previously impractical experiments. Our methods could also be applied to other inverse problems arising in machine learning, image processing, signal processing, computer vision, and other fields.

A Pyramidal Evolutionary Algorithm with Different Inter-Agent Partnering Strategies for Scheduling Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

A Pyramidal Evolutionary Algorithm with Different Inter-Agent Partnering Strategies for Scheduling Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

A Pyramidal Genetic Algorithm for Multiple-Choice Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence, higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

Nested Rollout Policy Adaptation for optimizing vehicle selection in complex VRPs

The goal of Vehicle Routing Problems (VRP) and their variations is to transport a set of orders with the minimum number of vehicles at least cost. Most approaches are designed to solve specific problem variations independently, whereas in real world applications, different constraints are handled concurrently. This research extends solutions obtained for the traveling salesman problem with time windows to a much wider class of route planning problems in logistics. The work describes a novel approach that:  supports a heterogeneous fleet of vehicles  dynamically reduces the number of vehicles  respects individual capacity restrictions  satisfies pickup and delivery constraints  takes Hamiltonian paths (rather than cycles) The proposed approach uses Monte-Carlo Tree Search and in particular Nested Rollout Policy Adaptation. For the evaluation of the work, real data from the industry was obtained and tested and the results are reported.

Clinical characteristics and selection of treatment modality for patients with vitreomacular traction:real-world implementation of NICE guidance (TA297)

Aim: To investigate the qualitative aspects in patient selection and the quantitative impact of disease burden in real world treatment of vitreomacular traction (VMT) and implementation of the National Institute for Health and Care Excellence (NICE) guidance (TA297). Methods: A monocentric, retrospective review of consecutive patients undergoing optical coherence tomography (OCT) imaging over a 3 month period. Patients with VMT in at least one eye were identified for further data collection on laterality, visual acuity, symptoms, presence of epiretinal membrane, macular hole and treatment selection. Results: A total of 3472 patients underwent OCT imaging with a total of 6878 eyes scanned. Out of 87 patients, 74 patients had unilateral VMT (38 right, 36 left) and 13 patients had bilateral VMT. Eighteen patients with unilateral VMT satisfied NICE criteria of severe sight problems in the affected eye. Eight were managed for a coexisting pathology, one refused treatment, one patient did not attend, two closed spontaneously, and one received ocriplasmin prior to the study start date. Only two patients with unilateral VMT received ocriplasmin and three underwent vitrectomy. Those failing to meet NICE criteria for unilateral VMT were predominantly asymptomatic (n=49) or had coexisting ERM (n=5) or both (n=2). Conclusion: Ocriplasmin provides an alternative treatment for patients with symptomatic VMT. Our data shows that the majority of patients with VMT do not meet NICE TA297 primarily due to lack of symptoms. Those meeting NICE criteria, but not treated, tended to have coexisting macular pathology. Variation in patient selection due to subjective factors not outlined in NICE guidance suggests that real world outcomes of ocriplasmin therapy should be interpreted with caution.

Investigating key decision problems to optimize the operation and maintenance strategy of offshore wind farms

This paper investigates three decision problems with potential to optimize operation and maintenance and logistics strategies for offshore wind farms: the timing of pre-determined jack-up vessel campaigns; selection of crew transfer vessel fleet; and timing of annual services. These problems are compared both in terms of potential cost reduction and the stochastic variability and associated uncertainty of the outcome. Pre-determined jack-up vessel campaigns appear to have a high cost reduction potential but also a higher stochastic variability than the other decision problems. The paper also demonstrates the benefits and difficulties of considering problems together rather than solving them in isolation.