The use of simulated games in an undergraduate course manufacturing processes

Simulation games bring the real engineering situation into class room. They are ideally suited to situations where the size and cost of some systems cannot be replicated in educational institutions, e.g. large-scale production facilities and manufacturing processes. Students undertaking a course in Manufacturing Processes participated in a role-playing game within a simulated manufacturing environment for the production of LEGO widgets. The game has three discrete phases; each with a briefing session, a production “run” and a debriefing session. It encourages observation and discussion of possible improvements required to increase productivity, and also visualizes some of the manufacturing concepts. This paper describes the exceptional learning outcomes achieved, the explicit understanding of manufacturing strategies and an insight into the approaches taken by world class manufacturers to maximise production. Surveys of students, taken before and after the game, revealed that they gained a greater appreciation for the course content by being immersed in this simulated scenario. The game also illustrated the importance of good team interaction, the application of different problem-solving techniques, and proved the odd adage “work smarter not faster”

Computer aided monitoring of breast abnormalities in X-ray mammograms

X­ray mammography is regarded as the most effective tool for the detection and diagnosis of breast cancer, but the interpretation of mammograms is a difficult and error­prone task. Computer­aided detection (CADe) systems address the problem that radiologists often miss signs of cancers that are retrospectively visible in mammograms. Furthermore, computer­aided diagnosis (CADx) systems assist the radiologist in the classification of mammographic lesions as benign or malignant[1]. This paper details a novel alternative system namely computer­aided monitoring (CAM) system. The designed CAM system can be used to objectively measure the properties of a suspected abnormal area in a mammogram. Thus it can be used to assist the clinician to objectively monitor the abnormality. For instance its response to treatment and consequently its prognosis. The designed CAM system is implemented using the Hierarchical Clustering based Segmentation (HCS) [2] [3] [4] process. Brief description of the implementation of this CAM system is as follows : Using the approximate location and size of the abnormality, obtained from the user, the HCS process automatically identifies the more appropriate boundaries of the different regions within a region of interest (ROI), centred at the approximate location. From the set of, HCS process segmented, regions the user identifies the regions which most likely represent the abnormality and the healthy areas. Subsequently the CAM system compares the characteristics of the user identified abnormal region with that of the healthy region; to differentiate malignant from benign abnormality. In processing sixteen mammograms from mini­MIAS [5], the designed CAM system demonstrated a success rate of 100% in differentiating malignant from benign abnormalities

Simplified Algorithm for Dynamic Demand Response in Smart Homes Under Smart Grid Environment

Under Smart Grid environment, the consumers may respond to incentive--based smart energy tariffs for a particular consumption pattern. Demand Response (DR) is a portfolio of signaling schemes from the utility to the consumers for load shifting/shedding with a given deadline. The signaling schemes include Time--of--Use (ToU) pricing, Maximum Demand Limit (MDL) signals etc. This paper proposes a DR algorithm which schedules the operation of home appliances/loads through a minimization problem. The category of loads and their operational timings in a day have been considered as the operational parameters of the system. These operational parameters determine the dynamic priority of a load, which is an intermediate step of this algorithm. The ToU pricing, MDL signals, and the dynamic priority of loads are the constraints in this formulated minimization problem, which yields an optimal schedule of operation for each participating load within the consumer provided duration. The objective is to flatten the daily load curve of a smart home by distributing the operation of its appliances in possible low--price intervals without violating the MDL constraint. This proposed algorithm is simulated in MATLAB environment against various test cases. The obtained results are plotted to depict significant monetary savings and flattened load curves.Comment: This paper was accepted and presented in 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia). Furthermore, the conference proceedings has been published in IEEE Xplor

Improving medical image perception by hierarchical clustering based segmentation

It has been well documented that radiologists' performance is not perfect: they make both false positive and false negative decisions. For example, approximately thirty percent of early lung cancer is missed on chest radiographs when the evidence is clearly visible in retrospect [1]. Currently Computer-Aided Detection (CAD) uses software, designed to reduce errors by drawing radiologists' attention to possible abnormalities by placing prompts on images. Alberdi et al examined the effects of CAD prompts on performance, comparing the negative effect of no prompt on a cancer case with prompts on a normal case. They showed that no prompt on a cancer case can have a detrimental effect on reader sensitivity and that the reader performs worse than if the reader was not using CAD. This became particularly apparent when difficult cases were being read. They suggested that the readers were using CAD as a decision making tool instead of a prompting aid. They conclude that "incorrect CAD can have a detrimental effect on human decisions" [2]. The goal of this paper is to explore the possibility of using Hierarchical Clustering based Segmentation (HCS) [3], as a perceptual aid, to improve the performance of the reader

Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses

In this work, we adapt a method based on multiple hypothesis tracking (MHT) that has been shown to give state-of-the-art vessel segmentation results in interactive settings, for the purpose of extracting trees. Regularly spaced tubular templates are fit to image data forming local hypotheses. These local hypotheses are used to construct the MHT tree, which is then traversed to make segmentation decisions. However, some critical parameters in this method are scale-dependent and have an adverse effect when tracking structures of varying dimensions. We propose to use statistical ranking of local hypotheses in constructing the MHT tree, which yields a probabilistic interpretation of scores across scales and helps alleviate the scale-dependence of MHT parameters. This enables our method to track trees starting from a single seed point. Our method is evaluated on chest CT data to extract airway trees and coronary arteries. In both cases, we show that our method performs significantly better than the original MHT method.Comment: Accepted for publication at the International Journal of Medical Physics and Practic

Scandium Cluster and Metallocene Chemistry

This thesis focuses on the synthesis and characterization of scandium compounds. One goal was to investigate the solution reactivity of {CSc6}I12Sc, which resulted in the isolation of a molecular scandium nitride, [(C5H5)2ScNSc(C5H5)(THF)]2, and a scandium propoxide complex, [(C5H5)2Sc(µ-OPr)]2. Besides this, priority was given to the synthesis and characterization of the first scandium dinitrogen complex, [(C5Me4H)2Sc]2(µ-η2:η2-N2), along with its precursor compounds: (C5Me4H)2ScCl(THF), (C5Me4H)2Sc(η3-C3H5) and [(C5Me4H)2Sc]2[(µ-Ph)BPh3]. The reduction of the latter complex with KC8 under N2 gave the elusive [(C5Me4H)2Sc]2(µ-η2:η2-N2). Structure determination supported by DFT calculations revealed a coplanar arrangement of a bridging side-on bound dinitrogen unit and two scandium atoms. In one reaction, the dinitrogen complex co-crystallized with an oxide impurity as {[(C5Me4H)2Sc]2(µ-η2:η2-N2)[(C5Me4H)2Sc]2(µ-O)}. Additionally, the borohydride complexes (C5Me4R)2M(BH4)(THF)x (M = Sc, Y; R = H, Me; x = 0, 1) were prepared. Yttrium borohydride complexes were investigated with respect to their dinitrogen activation capability, but were found to be inactive. Ligand based reactivity of (C5Me4R)2Sc(η3-C3H5) (R = H, Me) occured with 9-BBN (9-borabicyclo[3.3.1]nonane) to form the corresponding (C5Me4R)2Sc(µ-H)2BC8H14 complexes, from which oxygen exposure (R = H) yielded (C5Me4H)2Sc(µ-O)BC8H14. Subsequent investigations focused on the reaction of [(C5Me4H)2Sc]2[(µ-Ph)BPh3] with KC5Me4H and gave (5-C5Me4H)2Sc(1-C5Me4H), which was structurally characterized and is the first example of an 1-coordination mode for a (C5Me4H)- ligand bound to a rare-earth metal. This complex undergoes Sigma Bond Metathesis (SBM) reactivity towards diphenyldichalcogenides, PhEEPh (E = S, Se, Te), to produce [(C5Me4H)2ScSPh]2 and (C5Me4H)2ScEPh (E = Se, Te) complexes. The analogous products could be isolated and were fully characterized through the ligand based reactivity of (C5Me4H)2Sc(η3-C3H5) and PhEEPh reagents. These reactions also worked in the presence of THF to yield the solvated complexes (C5Me4H)2ScEPh(THF) (E = S, Se, Te). The reaction of (C5Me4H)2Sc(η3-C3H5) with pySSpy produced the analogous (C5Me4H)2ScSpy complex. In addition, the formation of a scandium selenium cluster complex [(C5Me4H)Sc]3[SePh]6 was identified and reactivity studies with PhTeTePh additionally resulted in the isolation of a scandium tellurium cluster compound, {[(C5Me5)Sc]4(μ3-Te)4}. The functionalization of N2O via insertion into the metal carbon bond of allyl compounds, (C5Me4R)2M(η3-C3H5) (M = Sc, Y, La, Sm; R = H, Me) formed [(C5Me4R)2M(µ-1:2-ON=NC3H5)]2 complexes. The insertion of iPrN=C=NiPr into the Sc-C bond of (C5Me4H)2Sc(3-C3H5) gave (C5Me4H)2Sc[(iPr)NC(CH2CH=CH2)N(iPr)-κ2N,N']. Finally, although the desired products were not isolated from an attempted reaction of (C5Me4H)2Sc(3-C3H5) with diphenylhydrazine, a scandium hydroxo cluster complex (C5Me4H)5Sc5(µ5-O)(µ3-OH)4(µ2-OH)4∙[(C6H5)NH]2 was isolated