Scale independent surface characterisation: Geography meets precision surface metrology

The recently published standard ISO 25178-2 distinguishes between field parameters and feature parameters for surface texture characterisation, whereby the main difference between these two types is due to the fact that the parameters belonging to the first group are deduced from all points of a scale-limited surface, while the parameters belonging to the second group are deduced from only a subset of predefined topological surface features. As specified in ISO 25178-2, two prerequisites are indispensable for the determination of the feature parameters, viz., an adequate data structure for surface characterisation and a suitable formal method for surface generalisation, i.e. for the successive elimination of the less important surface features. Within ISO 25178-2 change trees are proposed for describing the surface topography, while Wolf pruning is suggested for surface simplification (cf. also ISO 16610-85). Apart from the techniques specified in ISO 25178-2 and ISO 16610-85, the present paper describes a second geometrical–topological approach for the characterisation and generalisation of surfaces that has its origin within the geosciences and is based on weighted surface networks and w-contractions. In addition, it is revealed how the two approaches, both of which have their foundations in graph theory, are interrelated to each other and how, from a historical point of view, the GIScience approach forms the basis of the one applied within surface metrology. Finally, some applications within precision engineering are described.     

Understanding veterinarians’ prescribing decisions on antibiotic dry cow therapy

In the United Kingdom, blanket antibiotic dry cow therapy (BDCT) is commonly prescribed. An alternate strategy is selective dry cow therapy (SDCT) whereby a teat sealant is given instead of an antibiotic to cows with a low probability of infection. Switching from BDCT to SDCT can significantly reduce antibiotic use. The aims of this study were to explore how veterinarians (vets) rationalized their prescribing decisions for mammary treatments at drying off, and the barriers and motivators they perceived to implementing SDCT. Face-to-face interviews were conducted with 20 purposively recruited vets from 6 practices in England, United Kingdom. The data were analyzed qualitatively using an inductive thematic analysis. The majority of participants stated a personal preference for SDCT because it constitutes more responsible antibiotic use. On the majority of farms, the prescribing decision was taken by a senior veterinarian and BDCT was prescribed. Less experienced vets expressed a desire to be more involved in the decision-making process. The first theme, prioritizing responsible antimicrobial prescribing, encapsulated the difficulties vets expressed engaging with farmers, conflicts of interest, and vets’ determination to take action. The second theme, the effect of a vet's experience on their ability to influence farmers, focused on the specific challenges faced by less experienced vets and the importance of vets being both trusted by farmers and being knowledgeable. The third theme, vets’ perceptions about the risk and complexity of implementing SDCT, revealed markedly different levels of concern and fears about adverse outcomes with teat sealants versus antibiotics. The results also showed differences in perceptions about how difficult SDCT is to implement in practice. The last theme, vets’ suggestions for facilitating the introduction of SDCT, was wide ranging and provided useful insight from a veterinary perspective into ways to facilitate SDCT. Initiatives that seek to alter vets’ perceptions of the risks associated with switching to using SDCT are likely to prove useful in facilitating change. Our results also suggest that it is vital for senior vets to take a leading role in facilitating farms to implement SDCT. Less experienced colleagues may benefit from more help from senior vets to gain the trust of farmers and to become involved more quickly in herd-level preventive medicine. Vets must work together and take a united approach to reduce antimicrobial use.     

Waste electronics and electrical equipment disassembly and recycling using Petri net analysis: Considering the economic value and environmental impacts

The Industry Council for Electronic Equipment Recycling (ICER) has published estimates of waste generation based on both assumptions and analysis regarding the relationship between the market sales of Electrical and Electronic Equipment (EEE) in a given year and the expected lifetime of products as well as by employing market saturation factors. Waste EEE (WEEE) has an adverse impact on the environment. Therefore, it is important to reduce the quantity of WEEE through recycling. While attempting to improve the recycling rate of WEEE by enhancing the disassembly processes, two issues must be considered simultaneously—economy and safety. In this paper, a Petri Net (PN) based analysis approach is proposed to deal with the disassembly and recycling problems in End-Of-Life (EOL) WEEE. By using the PN analysis, the optimal tradeoff between the cost and environmental effectiveness of the disassembly processes is determined. A case study is used to illustrate the proposed analysis method.     

Degree-constrained minimum spanning tree problem with uncertain edge weights

Uncertainty theory has shown great advantages in solving many nondeterministic problems, one of which is the degree-constrained minimum spanning tree (DCMST) problem in uncertain networks. Based on different criteria for ranking uncertain variables, three types of DCMST models are proposed here: uncertain expected value DCMST model, uncertain α-DCMST model and uncertain most chance DCMST model. In this paper, we give their uncertainty distributions and fully characterize uncertain expected value DCMST and uncertain α-DCMST in uncertain networks. We also discover an equivalence relation between the uncertain α-DCMST of an uncertain network and the DCMST of the corresponding deterministic network. Finally, a related genetic algorithm is proposed here to solve the three models, and some numerical examples are provided to illustrate its effectiveness.     

Focused SWOT: diagnosing critical strengths and weaknesses

Despite the problems involved in its use, SWOT (strengths-weaknesses-opportunities-threats) analysis remains a major strategic tool for listing the strengths and weaknesses of an organisation, for recording the major strengths and translating them into value. This paper presents a straightforward methodology for making a structured analysis of strengths and weaknesses, based on an analysis of important value-creating events and the strengths and weaknesses that caused these events. The focused SWOT methodology distils the strengths and weaknesses into core competences and core problems, by using the core-competence tree and the current-reality tree. The core competences and core problems are then linked into a plan of action aimed at preserving and leveraging the organisation's core competences, while defending against exposure to core problems. Applications of the methodology are presented and it is demonstrated in a detailed case study.     

Modeling of quantitative relationships between physicochemical properties of active pharmaceutical ingredients and tensile strength of tablets using a boosted tree

Objectives: The aim of this study was to explore the potential of boosted tree (BT) to develop a correlation model between active pharmaceutical ingredient (API) characteristics and a tensile strength (TS) of tablets as critical quality attributes.

Methods: First, we evaluated 81 kinds of API characteristics, such as particle size distribution, bulk density, tapped density, Hausner ratio, moisture content, elastic recovery, molecular weight, and partition coefficient. Next, we prepared tablets containing 50% API, 49% microcrystalline cellulose, and 1% magnesium stearate using direct compression at 6, 8, and 10?kN, and measured TS. Then, we applied BT to our dataset to develop a correlation model. Finally, the constructed BT model was validated using k-fold cross-validation.

Results: Results showed that the BT model achieved high-performance statistics, whereas multiple regression analysis resulted in poor estimations. Sensitivity analysis of the BT model revealed that diameter of powder particles at the 10th percentile of the cumulative percentage size distribution was the most crucial factor for TS. In addition, the influences of moisture content, partition coefficients, and modal diameter were appreciably meaningful factors.

Conclusions: This study demonstrates that BT model could provide comprehensive understanding of the latent structure underlying APIs and TS of tablets.     

基于决策树的羽流追踪机器人自主决策方法研究

针对无法获得可靠羽流流向信息不利于实现羽流追踪的问题，提出了一种基于决策树的羽流追踪移动机器人自主决策方法。该方法通过移动机器人两侧的浓度传感器采集到的浓度信息，利用追踪的行为规则建立决策树模型，获得行为决策信息，使机器人高效地追踪到羽流并精确地定位。由于浓度变化关系蕴含了羽流的流向及流速信息，从而取代了传统方法中流向及流速传感器。在扩散环境下，通过移动机器人羽流追踪实验，实现了良好的源定位效果。     

Structural and operational management of Turkish airports: a bootstrap data envelopment analysis of efficiency

This paper explores the structural and operational dimensions of the efficiencies of airports. The two-stage procedure is suggested to assess the efficiencies of airports in this study. In the first-stage, Classification and Regression Tree, which is one of the machine-learning approaches used to divide the airports into homogeneous and thus comparable sub-groups. In the second stage, the bootstrap data envelopment analysis approach obtains more precise structural and operational efficiency scores. To illustrate the proposed framework use, we applied it to a real case associated with Turkish airports. The results demonstrate that this framework presents a more comprehensive assessment of airport performance rather than conventional data envelopment analysis models. Moreover, it provides to show the deficiencies of the structural and operational management of airports. The findings can help anywhere airport authorities as well as Turkish airport authorities.     

Day‐Ahead Global Solar Radiation Forecasting Using Binary Trees and Factor Analysis

A method is proposed for forecasting global solar radiation. The method is based on weather information using binary trees and factor analysis. The feature of this method is that it is possible to use a simple linear forecasting equation. The method has been tested on meteorological and global solar radiation data obtained at several observation sites, and the results show that it is a promising means of maintaining the balance between demand and supply of electric power in power systems of the near future with a large number of photovoltaic systems installed.