Chemical characterization of honey bees by curie-point pyrolysis-gas chromatography-pattern recognition

Valcarce, R. and Smith, G.G., 1989. Chemical characterization of honey bees by Curie-point pyrolysis-gas chromatography-pattern recognition. Chemometrics and Intelligent Laboratory Systems, 6: 157-166.Curie-point pyrolysis-gas chromatography coupled with the application of three different multivariate pattern recognition programs [SPSS-X (hierarchical cluster analysis), MVSP (principal component analysis) and FCVPC-87 (fuzzy c-varieties pattern recognition)] was used to develop an alternative technique for discriminating European, African, Africanized, and F₁, hybrid honey bees based on non-morphological characteristics. FCVPC-87 was also employed to evaluate the pyrograms for the discriminating chemical features responsible for differentiating these bees. The chemical identities of the discriminating peaks were determined by pyrolysis-gas chromatography-mass spectrometry.     

Evaluation of sustainability using fuzzy association rules mining

Several technologies have been emerging for aiding the management of sustainability. Yet most of them are in development stages. The complex manufacturing systems necessitate the validation of flexible solutions using advanced managerial tools and techniques. This article reports the utilization of fuzzy association rule mining (FARM) approach which enables the decision makers to make flexible decisions for evaluating sustainability in the presence of attributes such as Cost, Market share performance, Profitability, Quality, Toxicity, Legislative factors, Social cohesion, Trade opportunities, and flexibility. The approach has been used for sustainability evaluation in an Indian rotary switches manufacturing organization. The experiences of the conduct of this research indicate that sustainability evaluation can be performed without constraints by the decision makers.     

Interestingness of association rules in data mining: Issues relevant to e-commerce

The ubiquitous low-cost connectivity synonymous with the internet has changed the competitive business environment by dissolving traditional sources of competitive advantage based on size, location and the like. In this level playing field, firms are forced to compete on the basis of knowledge. Data mining tools and techniques provide e-commerce applications with novel and significant knowledge. This knowledge can be leveraged to gain competitive advantage. However, the automated nature of data mining algorithms may result in a glut of patterns — the sheer numbers of which contribute to incomprehensibility. Importance of automated methods that address this immensity problem, particularly with respect to practical application of data mining results, cannot be overstated. We first examine different approaches to address this problem citing their applicability to e-commerce whenever appropriate. We then provide a detailed survey of one important approach, namely interestingness measure, and discuss its relevance in e-commerce applications such as personalization in recommender systems. Study of current literature brings out important issues that reveal many promising avenues for future research. We conclude by reiterating the importance of post-processing methods in data mining for effective and efficient deployment of e-commerce solutions.     

New dispatching rules for shop scheduling: A step forward

This paper provides a set of new dispatching rules for the minimization of various performance measures such as mean, maximum and variance of flow time and tardiness in dynamic shops. A static rule which minimizes the number of tardy jobs is also proposed. To evaluate these proposed rules, their relative performance is analysed in open job shops and reported in comparison with the standard benchmark rules such as the SPT (shortest process time) and EDD (earliest due-date), popular rules like ATC (apparent tardiness cost) and MOD (modified operational due-date), and the best performing rules in current literature such as RR, PT + WINQ, PT + WINQ + SL and AT-RPT. Thereafter, a comparative analysis of the relative performance of these rules is carried out in job shops (with no machine revisitation of jobs) and flow shops (with missing operations on jobs) in dynamic environments. Based on the simulation study and analysis of results in different manufacturing environments viz. job shops and flow shops, observations and conclusions are made, highlighting some interesting aspects about the effect of routeing on the individual performance of rules.     

采用非线性化学指纹图谱技术测定蜂蜜中糖含量的新方法

本文采用非线性化学指纹图谱技术测定蜂蜜中的主要成分葡萄糖和果糖。以葡萄糖-果糖作为有机底物,改变其相对含量,结果发现振荡周期、诱导期、振荡寿命等参数出现规律性变化。利用上述参数随葡萄糖-果糖含量改变而变化的规律建立数学模型,从而可以测定蜂蜜振荡体系中两种糖的含量,为测定蜂蜜中葡萄糖和果糖的含量提供了一种新方法。此外结合相似系统理论对蜂蜜质量进行了评价,为蜂蜜的定性鉴别提供了新的思路。     

Phase-field modeling for facet dendrite growth of silicon

Dendrite growth of silicon from its undercooled melt was investigated by using the phase-field model for a faceted crystal with anisotropic interfacial energy. The phase-field parameters at the thin interface limit were derived and used in the simulation. The accuracy of the model was estimated from the calculated equilibrium interface shape. The errors in anisotropy and Gibbs-Thomson coefficient were within 1% and 10%, respectively. The growth of a silicon crystal from its undercooled melt has been analyzed and it is shown that the shape of growing crystal changes from square-like to dendritic with increase of undercooling. In a facet dendrite growth the tip grows keeping its shape and the shape is the same regardless of undercooling or growth velocity. It is also shown that there exists the scaling law between the characteristic length of the tip and growth velocity similar to that of a non-facet dendrite.     

Real time selection of scheduling rules and knowledge extraction via dynamically controlled data mining

A new scheduling system for selecting dispatching rules in real time is developed by combining the techniques of simulation, data mining, and statistical process control charts. The proposed scheduling system extracts knowledge from data coming from the manufacturing environment by constructing a decision tree, and selects a dispatching rule from the tree for each scheduling period. In addition, the system utilises the process control charts to monitor the performance of the decision tree and dynamically updates this decision tree whenever the manufacturing conditions change. This gives the proposed system the ability to adapt itself to changes in the manufacturing environment and improve the quality of its decisions. We implement the proposed system on a job shop problem, with the objective of minimising average tardiness, to evaluate its performance. Simulation results indicate that the performance of the proposed system is considerably better than other simulation-based single-pass and multi-pass scheduling algorithms available in the literature. We also illustrate knowledge extraction by presenting a sample decision tree from our experiments.     

New insight into the functional dependence rules in turbulence modelling

This paper is intended to revisit the Euclidean invariance of turbulence models, in particular of the algebraic Reynolds stress models (ARSM). The approach is motivated by the existing different interpretations of the Euclidean invariance of an equation. We show that these interpretations are not suitable to rule out functional dependencies in turbulence. We use the concept of Euclidean invariance with respect to a constitutive or flow rule class of a closure relation to analyze the Euclidean invariance properties of the ARSM. It turns out that the existing ARSM are Euclidean invariant with respect to two different classes, that are basically determined by the equilibrium assumption made in an inertial and a non-inertial reference frame, respectively. The first one is more restrictive and does not include the relative environment dependence of the Reynolds stress tensor in the implicit ARSM. The second class endeavors to involve this environment dependence. After this first step, the issue how to formulate a unified rationale for a consistent reduction procedure based on extended thermodynamics to rule out functional dependencies of the ARSM relations for Reynolds-averaged Navier-Stokes equations (RANS) or large eddy simulations (LES) is left for future work.     

Phase-field modeling for facet dendrite growth of silicon

Dendrite growth of silicon from its undercooled melt was investigated by using the phase-field model for a faceted crystal with anisotropic interfacial energy. The phase-field parameters at the thin interface limit were derived and used in the simulation. The accuracy of the model was estimated from the calculated equilibrium interface shape. The errors in anisotropy and Gibbs-Thomson coefficient were within 1% and 10%, respectively. The growth of a silicon crystal from its undercooled melt has been analyzed and it is shown that the shape of growing crystal changes from square-like to dendritic with increase of undercooling. In a facet dendrite growth the tip grows keeping its shape and the shape is the same regardless of undercooling or growth velocity. It is also shown that there exists the scaling law between the characteristic length of the tip and growth velocity similar to that of a non-facet dendrite.     

A basic flat facet finite element for the analysis of general shells

A triangular flat facet finite element for the analysis of general thin shells is presented. It is constructed from simple cubic polynomial displacement fields using a complete set of six degrees of freedom at the element vertices, thereby easily meeting the requirements of standard commercial computer programs. The theoretical development is based on a variational principle which allows a direct formulation of the element stiffness matrix, without inversion, and which permits considerable simplification of the mathematical formulation. The new flat facet element generally produces more accurate numerical results than those obtained in earlier related work. It also offers a possible basis for constructing an improved curved approximation to a shell surface and for further developments in connection with applications involving geometric non-linearity.     

New technique for calculating the volume of the measurement chamber for a charge induction aerosol particle counter

The proposed procedure for determining the counting volume guaranteeing 5% relative error for particle counting takes into account the statistical properties of the aerosol stream and gives a new relationship for the maximum counted aerosol concentration which can be measured without dilution for a specified volume of the measurement chamber. Translated from Izmeritel'naya Tekhnika, No. 9, pp. 52–54, September, 1998.     

A simulation study on the performance of task-determination rules and delivery-dispatching rules for multiple-load AGVs

In this paper, the control problem of multiple-load automated guided vehicles (AGVs) is studied. A control process that identifies four problems faced by multiple-load AGVs is proposed. The first problem is the task-determination problem, in which a multiple-load AGV determines whether its next task is a pickup task or a delivery task. The second problem is the delivery-dispatching problem, in which a multiple-load AGV determines which delivery point it should visit next if its next task is a delivery task. The third problem is the pickup-dispatching problem, in which a multiple-load AGV determines which pickup point it should visit next if its next task is a pickup task. Finally, the fourth problem is the load-selection problem, which requires a multiple-load AGV to determine which load it should pick up from the output queue of a pickup point. This paper focuses on the first and second problems. Different task-determination rules and delivery-dispatching rules are proposed for these two problems. For the problems that are not the main focus of this study, rules found in the literature or real systems are adopted in this study. The objective of this study is twofold. First, we need to understand how well the proposed rules will perform in different performance measures, e.g. the system's throughput and the mean lateness of parts. Second, we need to understand the mutual effects that different types of rules have on each other, so that the best combination of rules can be identified. Computer simulations were conducted to test the performance of the proposed rules. It is hoped the knowledge learned from this study can be beneficial to real multiple-load AGV systems similar to the one studied here.     

Practical finite pivoting rules for the simplex method

Summary A pivoting rule is crucial to the simplex method. This paper suggests two variants of Bland's type of pivoting rule. In contrast with the latter, which are based on indices of variables, the new rules are based on so-called pivoting indices, which are of full geometrical meaning. According to the underlying geometric philosophy of them and test results obtained by the author, these rules are not only finite and simple, but also promising practically.

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Zusammenfassung Pivot-Regeln sind ein wesentliches Element der Simplexmethode. In dieser Arbeit stellen wir zwei Varianten von Pivot-Regeln des Bland'schen Typs vor. Während die Bland-Regel auf einer Indizierung der Variablen beruht, arbeiten die neuen Regeln mit sogenannten Pivoting-Indices, denen eine geometrische Bedeutung zukommt. Aufgrund dieser geometrischen Philosophie und durch Testrechnungen gestützt, erweisen sich diese Regeln nicht nur als einfach und endlich, sondern auch als vielversprechend für den praktischen Einsatz.

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This work was performed in part while the author was visiting the Department of Mathematics, University of Washington, Seattle, USA     

A facet ensemble approach for evaluation of array performance inultrasonic NDE

The use of ultrasonic array systems, in conjunction with a synthetic aperture focusing technique (SAFT) has recognized potential for flaw characterization in nondestructive evaluation (NDE). However, defect type, location, orientation and geometrical constraints imposed by the test specimen can reduce the effectiveness of nonoptimal array systems. To assist with design, a simulation approach for evaluation of array performance for NDE imaging was developed and is described in this paper. In the development of the model, several key factors were identified as being critical in defining the response of a linear ultrasonic transducer array. These include the ultrasonic wavelet generated by each array element, the directivity of the transducers and the interaction of the ultrasonic wave field with the surface which is to be imaged. Following several simplifying assumptions, and employing a linear systems approach, the cumulative response of all these factors was formulated. Thus a low-cost, yet powerful, interactive model for system design evaluation could be implemented. To illustrate the model, a range of simulation results is presented, concerning the imaging of a fatigue crack in a solid medium. The influence of array element spacing and centre frequency is considered, in conjunction with aperture size, defect orientation and surface roughness. In each case, the principal factors governing final image quality are discussed and where possible, recommendations are made concerning array design and imaging strategy