Simulation-based support tool for operator performance in batch manufacturing

In industry, the workload and utilization of shop floor operators is often misunderstood. In this paper, we will present several real case studies, using Discrete Event Simulation (DES) models, which allow us to better understand operators in a batch manufacturing environment. The first study investigates labour in a machining plant consisting of multiple identical CNC machines that batch produce parts. The second study investigates labour in an eight station, gravity die casting rotary table. The results from these studies have shown that there can be potential improvements made by the production planners in the current labour configuration. In the first case study, a matrix is produced that estimates what the operator's utilization levels will be for various configurations. From this, the preferred operator to machine ratio over a range of cycle times is presented. In the second study, the results have shown that by reducing the casting cycle time, the operator would be overloaded. A discrete event simulation of these two cases highlighted areas that were misunderstood by plant management, and provided them with a useful decision support tool for production planning.

Groups, graphs and mutually unbiased bases

A new characteristic free approach to constructing large sets of mutually unbiased bases in Hilbert space is developed. We associate with a seed set of bases a finite subgroup of which defines a strongly regular graph. Large sets of mutually unbiased bases are obtained as the cliques of the graph.

Baseline comorbidities in a population-bases cohort of rheumatoid arthritis patients receiving biological therapy: data from the Australian Rheumatology Association database

Aims: To describe the baseline characteristics of an Australian population-based cohort of rheumatoid arthritis (RA) patients commencing biological therapy.

Methods: Descriptive analysis from the Australian Rheumatology Association Database (ARAD).

Results: Up to October 2006, there were 681 RA patients taking biologics enrolled in ARAD. Baseline data were available for 624 (72% female, mean (SD) age 57.0 (12.5) years). Of these, 59.5% reported at least one comorbid condition, most commonly hypertension (35.7%) and osteoporosis (30.4%); 61 (9.8%) had a history of malignancy (35 nonmelanoma skin, 5 breast, 4 bowel, 5 cervix, 3 melanoma, 3 prostate and 1 each of lip, lung, myeloma, testis, uterus, vagina). Self-reported infections within the previous 6 months were common (71.5%).

Conclusions: History of comorbidities, including recent infections, is common among Australian RA patients commencing biologics, and 10% have a history of malignancy. This may impact future evaluations of health outcomes among this population, including attribution of adverse events of biologic therapy.

Wavelets/multiwavelets bases and correspondence estimation problem : an analytic study

Correspondence estimation in one of the most active research areas in the field of computer vision and number of techniques has been proposed, possessing both advantages and shortcomings. Among the techniques reported, multiresolution analysis based stereo correspondence estimation has gained lot of research focus in recent years. Although, the most widely employed medium for multiresolution analysis is wavelets and multiwavelets bases, however, relatively little work has been reported in this context. In this work we have tried to address some of the issues regarding the work done in this domain and the inherited shortcomings. In the light of these shortcomings, we propose a new technique to overcome some of the flaws that could have significantly impact on the algorithm performance and has not been addressed in the earlier propositions. Proposed algorithm uses multiresolution analysis enforced with wavelets/multiwavelts transform modulus maxima to establish correspondences between the stereo pair of images. Variety of wavelets and multiwavelets bases, possessing distinct properties such as orthogonality, approximation order, short support and shape are employed to analyse their effect on the performance of correspondence estimation. The idea is to provide knowledge base to understand and establish relationships between wavelets and multiwavelets properties and their effect on the quality of stereo correspondence estimation.

Evidence for the direct interaction between methylene blue and guanine bases using DNA-modified carbon paste electrodes

It is explored that methylene blue interacts with the guanine bases specifically, rather than the bases of ss-DNA in general. This interaction can be used as a method of quantifying the amount of oligonucleotide that is immobilized onto an electrode surface.

Implementation and applications of the distortion operator

The distortion operator transforms 2D images in a manner similar to image warping or morphing, allowing source pixels to be mapped to any destination pixel. This operator can be implemented on current hardware, allowing at least one distortion per frame at interactive frame rates. Potential applications are numerous, but those described include re-mapping images for correct projection onto curved screens, correcting camera distortion from multiple sources simultaneously, and allowing constant time dynamic texturing and lighting of a static scene which is independent of geometric complexity.

Virtual haptic cell model for operator training

Microrobotic cell injection is an area of growing research interest. Typically, operators rely on visual feedback to perceive the microscale environment and are subject to lengthy training times and low success rates. Haptic interaction offers the ability to utilise the operator’s haptic modality and to enhance operator performance. Our earlier work presented a haptically enabled system for assisting the operator with certain aspects of the cell injection task. The system aimed to enhance the operator’s controllability of the micropipette through a logical mapping between the haptic device and microrobot, as well as introducing virtual fixtures for haptic guidance. The system was also designed in such a way that given the availability of appropriate force sensors, haptic display of the cell penetration force is straightforward. This work presents our progress towards a virtual replication of the system, aimed at facilitating offline operator training. It is suggested that operators can use the virtual system to train offline and later transfer their skills to the physical system. In order to achieve the necessary representation of the cell within the virtual system, methods based on a particle-based cell model are utilised. In addition to providing the necessary visual representation, the cell model provides the ability to estimate cell penetration forces and haptically display them to the operator. Two different approaches to achieving the virtual system are discussed.

Aggregation for Atanassov's intuitionistic and interval valued fuzzy sets: the median operator

Atanassov's intuitionistic fuzzy sets (AIFS) and interval valued fuzzy sets (IVFS) are two generalizations of a fuzzy set, which are equivalent mathematically although different semantically. We analyze the median aggregation operator for AIFS and IVFS. Different mathematical theories have lead to different definitions of the median operator. We look at the median from various perspectives: as an instance of the intuitionistic ordered weighted averaging operator, as a Fermat point in a plane, as a minimizer of input disagreement, and as an operation on distributive lattices. We underline several connections between these approaches and summarize essential properties of the median in different representations.

An efficient one-pass method for discovering bases of recently frequent episodes over online data streams

The knowledge embedded in an online data stream is likely to change over time due to the dynamic evolution of the stream. Consequently, infrequent episode mining over an online stream, frequent episodes should be adaptively extracted from recently generated stream segments instead of the whole stream. However, almost all existing frequent episode mining approaches find episodes frequently occurring over the whole sequence. This paper proposes and investigates a new problem: online mining of recently frequent episodes over data streams. In order to meet strict requirements of stream mining such as one-scan, adaptive result update and instant result return, we choose a novel frequency metric and define a highly condensed set called the base of recently frequent episodes. We then introduce a one-pass method for mining bases of recently frequent episodes. Experimental results show that the proposed method is capable of finding bases of recently frequent episodes quickly and adaptively. The proposed method outperforms the previous approaches with the advantages of one-pass, instant result update and return, more condensed resulting sets and less space usage.

A penalty-based aggregation operator for non-convex intervals

In the case of real-valued inputs, averaging aggregation functions have been studied extensively with results arising in fields including probability and statistics, fuzzy decision-making, and various sciences. Although much of the behavior of aggregation functions when combining standard fuzzy membership values is well established, extensions to interval-valued fuzzy sets, hesitant fuzzy sets, and other new domains pose a number of difficulties. The aggregation of non-convex or discontinuous intervals is usually approached in line with the extension principle, i.e. by aggregating all real-valued input vectors lying within the interval boundaries and taking the union as the final output. Although this is consistent with the aggregation of convex interval inputs, in the non-convex case such operators are not idempotent and may result in outputs which do not faithfully summarize or represent the set of inputs. After giving an overview of the treatment of non-convex intervals and their associated interpretations, we propose a novel extension of the arithmetic mean based on penalty functions that provides a representative output and satisfies idempotency.