A heuristic approach for component scheduling on a high-speed PCB assembly machine

The collect-and-place machine is one of the most widely used placement machines for assembling electronic components on the printed circuit boards (PCBs). Nevertheless, the number of researches concerning the optimisation of the machine performance is very few. This motivates us to study the component scheduling problem for this type of machine with the objective of minimising the total assembly time. The component scheduling problem is an integration of the component sequencing problem, that is, the sequencing of component placements; and the feeder arrangement problem, that is, the assignment of component types to feeders. To solve the component scheduling problem efficiently, a hybrid genetic algorithm is developed in this paper. A numerical example is used to compare the performance of the algorithm with different component grouping approaches and different population sizes.

A compartmental CFD-PBM model of high shear wet granulation

The conventional, geometrically lumped description of the physical processes inside a high shear granulator is not reliable for process design and scale-up. In this study, a compartmental Population Balance Model (PBM) with spatial dependence is developed and validated in two lab-scale high shear granulation processes using a 1.9L MiPro granulator and 4L DIOSNA granulator. The compartmental structure is built using a heuristic approach based on computational fluid dynamics (CFD) analysis, which includes the overall flow pattern, velocity and solids concentration. The constant volume Monte Carlo approach is implemented to solve the multi-compartment population balance equations. Different spatial dependent mechanisms are included in the compartmental PBM to describe granule growth. It is concluded that for both cases (low and high liquid content), the adjustment of parameters (e.g. layering, coalescence and breakage rate) can provide a quantitative prediction of the granulation process.

A new VRPPD model and a hybrid heuristic solution approach for e-tailing

We analyze a business model for e-supermarkets to enable multi-product sourcing capacity through co-opetition (collaborative competition). The logistics aspect of our approach is to design and execute a network system where “premium” goods are acquired from vendors at multiple locations in the supply network and delivered to customers. Our specific goals are to: (i) investigate the role of premium product offerings in creating critical mass and profit; (ii) develop a model for the multiple-pickup single-delivery vehicle routing problem in the presence of multiple vendors; and (iii) propose a hybrid solution approach. To solve the problem introduced in this paper, we develop a hybrid metaheuristic approach that uses a Genetic Algorithm for vendor selection and allocation, and a modified savings algorithm for the capacitated VRP with multiple pickup, single delivery and time windows (CVRPMPDTW). The proposed Genetic Algorithm guides the search for optimal vendor pickup location decisions, and for each generated solution in the genetic population, a corresponding CVRPMPDTW is solved using the savings algorithm. We validate our solution approach against published VRPTW solutions and also test our algorithm with Solomon instances modified for CVRPMPDTW.

Component scheduling for chip shooter machines: a hybrid genetic algorithm approach

A chip shooter machine for electronic component assembly has a movable feeder carrier, a movable X–Y table carrying a printed circuit board (PCB), and a rotary turret with multiple assembly heads. This paper presents a hybrid genetic algorithm (HGA) to optimize the sequence of component placements and the arrangement of component types to feeders simultaneously for a chip shooter machine, that is, the component scheduling problem. The objective of the problem is to minimize the total assembly time. The GA developed in the paper hybridizes different search heuristics including the nearest-neighbor heuristic, the 2-opt heuristic, and an iterated swap procedure, which is a new improved heuristic. Compared with the results obtained by other researchers, the performance of the HGA is superior in terms of the assembly time. Scope and purpose When assembling the surface mount components on a PCB, it is necessary to obtain the optimal sequence of component placements and the best arrangement of component types to feeders simultaneously in order to minimize the total assembly time. Since it is very difficult to obtain the optimality, a GA hybridized with several search heuristics is developed. The type of machines being studied is the chip shooter machine. This paper compares the algorithm with a simple GA. It shows that the performance of the algorithm is superior to that of the simple GA in terms of the total assembly time.

Meta-analysis of the population and phenotypic expression of CYP2C9/2C19 polymorphism on drug metabolism in different ethnicities

The term "pharmacogenetics" has been defined as the scientific study of inherited factors that affect the human drug response. Many pharmacogenetie studies have been published since 1995 and have focussed on the principal enzyme family involved in drug metabolism, the cytochrome P450 family, particularly cytochrome P4502C9 and 2C19. In order to investigate the pharmacogenetic aspect of pharmacotherapy, the relevant studies describing the association of pharmacogenetic factor(s) in drug responses must be retrieved from existing literature using a systematic review approach. In addition, the estimation of variant allele prevalence for the gene under study between different ethnic populations is important for pharmacogenetic studies. In this thesis, the prevalence of CYP2C9/2C19 alleles between different ethnicities has been estimated through meta-analysis and the population genetic principle. The clinical outcome of CYP2C9/2C19 allelic variation on the pharmacotherapy of epilepsy has been investigated; although many new antiepileptic drugs have been launched into the market, carbamazepine, phenobarbital and phenytoin are still the major agents in the pharmacotherapy of epilepsy. Therefore, phenytoin was chosen as a model AED and the effect of CYP2C9/2C19 genetic polymorphism on phenytoin metabolism was further examined.An estimation of the allele prevalence was undertaken for three CYP2C9/2C19 alleles respectively using a meta-analysis of studies that fit the Hardy-Weinberg equilibrium. The prevalence of CYP2C9*1 is approximately 81%, 96%, 97% and 94% in Caucasian, Chinese, Japanese, African populations respectively; the pooled prevalence of CYP2C19*1 is about 86%, 57%, 58% and 85% in these ethnic populations respectively. However, the studies of association between CYP2C9/2C19 polymorphism and phenytoin metabolism failed to achieve any qualitative or quantitative conclusion. Therefore, mephenytoin metabolism was examined as a probe drug for association between CYP2C19 polymorphism and mephenytoin metabolic ratio. Similarly, analysis of association between CYP2C9 polymorphism and warfarin dose requirement was undertaken.It was confirmed that subjects carrying two mutated CYP2C19 alleles have higher S/R mephenytoin ratio due to deficient CYP2C19 enzyme activity. The studies of warfarin and CYP2C9 polymorphism did not provide a conclusive result due to poor comparability between studies.The genetic polymorphism of drug metabolism enzymes has been studied extensively, however other genetic factors, such as multiple drug resistance genes (MDR) and genes encoding ion channels, which may contribute to variability in function of drug transporters and targets, require more attention in future pharmacogenetic studies of antiepileptic drugs.

Enhancing delivery of health behaviour change interventions in primary care: a meta-synthesis of views and experiences of primary care nurses

Objective To systematically find and synthesise qualitative studies that elicited views and experiences of nurses involved in the delivery of health behaviour change (HBC) interventions in primary care, with a focus on how this can inform enhanced delivery and adherence to a structured approach for HBC interventions. Methods Systematic search of five electronic databases and additional strategies to maximise identification of studies, appraisal of studies and use of meta-synthesis to develop an inductive and interpretative form of knowledge synthesis. Results Nine studies met the inclusion criteria. Synthesis resulted in the development of four inter-linking themes; (a) actively engaging nurses in the process of delivering HBC interventions, (b) clarifying roles and responsibilities of those involved, (c) engaging practice colleagues, (d) communication of aims and potential outcomes of the intervention. Conclusion The synthesis of qualitative evidence resulted in the development of a conceptual framework that remained true to the findings of primary studies. This framework describes factors that should be actively promoted to enhance delivery of and adherence to HBC interventions by nurses working in primary care. Practice implications The findings can be used to inform strategies for researchers, policymakers and healthcare providers to enhance fidelity and support delivery of HBC interventions.

Meta level component-based framework for distributed computing applications

Adaptability for distributed object-oriented enterprise frameworks is a critical mission for system evolution. Today, building adaptive services is a complex task due to lack of adequate framework support in the distributed computing environment. In this thesis, we propose a Meta Level Component-Based Framework (MELC) which uses distributed computing design patterns as components to develop an adaptable pattern-oriented framework for distributed computing applications. We describe our novel approach of combining a meta architecture with a pattern-oriented framework, resulting in an adaptable framework which provides a mechanism to facilitate system evolution. The critical nature of distributed technologies requires frameworks to be adaptable. Our framework employs a meta architecture. It supports dynamic adaptation of feasible design decisions in the framework design space by specifying and coordinating meta-objects that represent various aspects within the distributed environment. The meta architecture in MELC framework can provide the adaptability for system evolution. This approach resolves the problem of dynamic adaptation in the framework, which is encountered in most distributed applications. The concept of using a meta architecture to produce an adaptable pattern-oriented framework for distributed computing applications is new and has not previously been explored in research. As the framework is adaptable, the proposed architecture of the pattern-oriented framework has the abilities to dynamically adapt new design patterns to address technical system issues in the domain of distributed computing and they can be woven together to shape the framework in future. We show how MELC can be used effectively to enable dynamic component integration and to separate system functionality from business functionality. We demonstrate how MELC provides an adaptable and dynamic run time environment using our system configuration and management utility. We also highlight how MELC will impose significant adaptability in system evolution through a prototype E-Bookshop application to assemble its business functions with distributed computing components at the meta level in MELC architecture. Our performance tests show that MELC does not entail prohibitive performance tradeoffs. The work to develop the MELC framework for distributed computing applications has emerged as a promising way to meet current and future challenges in the distributed environment.

What do we know about the experience of age related macular degeneration? A systematic review and meta-synthesis of qualitative research

Age Related Macular Degeneration (AMD) is the leading cause of registerable blindness with a high medical and societal cost burden. Much of the research examining experiences of living with AMD has been conducted independently with small sample sizes and has failed to impact on practice. Meta-synthesis of qualitative research can improve the understanding of the experience of living with AMD by drawing together findings of qualitative studies. This article presents a systematic review and meta-synthesis of qualitative studies investigating the experience of AMD (literature searched up to April 2012; published studies identified range from 1996 to 2009). The review highlights themes relating to: functional limitations, adaptation and independence; feelings about the future with vision impairment; interaction with the health service; social engagement; disclosure; and the emotional impacts of living with AMD. Attention to the experience of living with AMD can help us to better understand the needs of patients. This meta-synthesis aimed to bring together the findings of qualitative research studies and highlights important areas for consideration when caring for patients with AMD. Our findings suggest that a holistic approach to service provision and support for AMD is needed which takes into account individuals' needs and experiences when coping with and adjusting to living with AMD. This support should aim to reduce stigma, increase social engagement, and develop the psychological resources of patients with AMD.

Knowledge management in knowledge intensive service networks:a strategic management approach

Purpose – The main purpose of this paper is to analyze knowledge management in service networks. It analyzes the knowledge management process and identifies related challenges. The authors take a strategic management approach instead of a more technology-oriented approach, since it is believed that managerial problems still remain after technological problems are solved. Design/methodology/approach – The paper explores the literature on the topic of knowledge management as well as the resource (or knowledge) based view of the firm. It offers conceptual insights and provides possible solutions for knowledge management problems. Findings – The paper discusses several possible solutions for managing knowledge processes in knowledge-intensive service networks. Solutions for knowledge identification/generation, knowledge application, knowledge combination/transfer and supporting the evolution of tacit network knowledge include personal and technological aspects, as well as organizational and cultural elements. Practical implications – In a complex environment, knowledge management and network management become crucial for business success. It is the task of network management to establish routines, and to build and regularly refresh meta-knowledge about the competencies and abilities that exist within the network. It is suggested that each network partner should be rated according to the contribution to the network knowledge base. Based on this rating, a particular network partner is a member of a certain knowledge club, meaning that the partner has access to a particular level of network knowledge. Such an established routine provides strong incentives to add knowledge to the network's knowledge base Originality/value – This paper is a first attempt to outline the problems of knowledge management in knowledge-intensive service networks and, by so doing, to introduce strategic management reasoning to the discussion.

Making hiring decisions:a grounded theory approach to a practise-based study of filtering in selection

This thesis objective is to discover “How are informal decisions reached by screeners when filtering out undesirable job applications?” Grounded theory techniques were employed in the field to observe and analyse informal decisions at the source by screeners in three distinct empirical studies. Whilst grounded theory provided the method for case and cross-case analysis, literature from academic and non-academic sources was evaluated and integrated to strengthen this research and create a foundation for understanding informal decisions. As informal decisions in early hiring processes have been under researched, this thesis contributes to current knowledge in several ways. First, it locates the Cycle of Employment which enhances Robertson and Smith’s (1993) Selection Paradigm through the integration of stages that individuals occupy whilst seeking employment. Secondly, a general depiction of the Workflow of General Hiring Processes provides a template for practitioners to map and further develop their organisational processes. Finally, it highlights the emergence of the Locality Effect, which is a geographically driven heuristic and bias that can significantly impact recruitment and informal decisions. Although screeners make informal decisions using multiple variables, informal decisions are made in stages as evidence in the Cycle of Employment. Moreover, informal decisions can be erroneous as a result of a majority and minority influence, the weighting of information, the injection of inappropriate information and criteria, and the influence of an assessor. This thesis considers these faults and develops a basic framework of understanding informal decisions to which future research can be launched.

Linked knowledge sources for topic classification of microposts:a semantic graph-based approach

Short text messages a.k.a Microposts (e.g. Tweets) have proven to be an effective channel for revealing information about trends and events, ranging from those related to Disaster (e.g. hurricane Sandy) to those related to Violence (e.g. Egyptian revolution). Being informed about such events as they occur could be extremely important to authorities and emergency professionals by allowing such parties to immediately respond. In this work we study the problem of topic classification (TC) of Microposts, which aims to automatically classify short messages based on the subject(s) discussed in them. The accurate TC of Microposts however is a challenging task since the limited number of tokens in a post often implies a lack of sufficient contextual information. In order to provide contextual information to Microposts, we present and evaluate several graph structures surrounding concepts present in linked knowledge sources (KSs). Traditional TC techniques enrich the content of Microposts with features extracted only from the Microposts content. In contrast our approach relies on the generation of different weighted semantic meta-graphs extracted from linked KSs. We introduce a new semantic graph, called category meta-graph. This novel meta-graph provides a more fine grained categorisation of concepts providing a set of novel semantic features. Our findings show that such category meta-graph features effectively improve the performance of a topic classifier of Microposts. Furthermore our goal is also to understand which semantic feature contributes to the performance of a topic classifier. For this reason we propose an approach for automatic estimation of accuracy loss of a topic classifier on new, unseen Microposts. We introduce and evaluate novel topic similarity measures, which capture the similarity between the KS documents and Microposts at a conceptual level, considering the enriched representation of these documents. Extensive evaluation in the context of Emergency Response (ER) and Violence Detection (VD) revealed that our approach outperforms previous approaches using single KS without linked data and Twitter data only up to 31.4% in terms of F1 measure. Our main findings indicate that the new category graph contains useful information for TC and achieves comparable results to previously used semantic graphs. Furthermore our results also indicate that the accuracy of a topic classifier can be accurately predicted using the enhanced text representation, outperforming previous approaches considering content-based similarity measures. © 2014 Elsevier B.V. All rights reserved.

Meta level component-based framework for distributed computing systems

Adaptability for distributed object-oriented enterprise frameworks in multimedia technology is a critical mission for system evolution. Today, building adaptive services is a complex task due to lack of adequate framework support in the distributed computing systems. In this paper, we propose a Metalevel Component-Based Framework which uses distributed computing design patterns as components to develop an adaptable pattern-oriented framework for distributed computing applications. We describe our approach of combining a meta-architecture with a pattern-oriented framework, resulting in an adaptable framework which provides a mechanism to facilitate system evolution. This approach resolves the problem of dynamic adaptation in the framework, which is encountered in most distributed multimedia applications. The proposed architecture of the pattern-oriented framework has the abilities to dynamically adapt new design patterns to address issues in the domain of distributed computing and they can be woven together to shape the framework in future. © 2011 Springer Science+Business Media B.V.

The effectiveness of workplace coaching:A meta-analysis of learning and performance outcomes; scale development; theoretical model of individual differences and longitudinal study

The extant literature on workplace coaching is characterised by a lack of theoretical and empirical understanding regarding the effectiveness of coaching as a learning and development tool; the types of outcomes one can expect from coaching; the tools that can be used to measure coaching outcomes; the underlying processes that explain why and how coaching works and the factors that may impact on coaching effectiveness. This thesis sought to address these substantial gaps in the literature with three linked studies. Firstly, a meta-analysis of workplace coaching effectiveness (k = 17), synthesizing the existing research was presented. A framework of coaching outcomes was developed and utilised to code the studies. Analysis indicated that coaching had positive effects on all outcomes. Next, the framework of outcomes was utilised as the deductive start-point to the development of the scale measuring perceived coaching effectiveness. Utilising a multi-stage approach (n = 201), the analysis indicated that perceived coaching effectiveness may be organised into a six factor structure: career clarity; team performance; work well-being; performance; planning and organizing and personal effectiveness and adaptability. The final study was a longitudinal field experiment to test a theoretical model of individual differences and coaching effectiveness developed in this thesis. An organizational sample of 84 employees each participated in a coaching intervention, completed self-report surveys, and had their job performance rated by peers, direct reports and supervisors (a total of 352 employees provided data on participant performance). The results demonstrate that compared to a control group, the coaching intervention generated a number of positive outcomes. The analysis indicated that coachees’ enthusiasm, intellect and orderliness influenced the impact of coaching on outcomes. Mediation analysis suggested that mastery goal orientation, performance goal orientation and approach motivation in the form of behavioural activation system (BAS) drive, were significant mediators between personality and outcomes. Overall, the findings of this thesis make an original contribution to the understanding of the types of outcomes that can be expected from coaching, and the magnitude of impact coaching has on outcomes. The thesis also provides a tool for reliably measuring coaching effectiveness and a theoretical model to understand the influence of coachee individual differences on coaching outcomes.

Parallel Problem Solving from Nature – PPSN XIV:14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings

This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.