93 research outputs found
Adopting lean manufacturing techniques in small and medium manufacturing enterprises
No full textSmall and medium sized enterprises (SMEs) form a significant part of national and
regional economic prosperity. They strengthen the capacity to generate employment
and wealth for national and regional benefit. The importance of SMEs to the
prosperity of a society and their contribution to new job creation, coupled with the
recognition that they seem to underperform highlights the need to assist this group of
companies improve their performance.
During the course of this research the author investigated whether SME manufacturing
organisations had opportunities to improve productivity and performance, conducted a
literature review of the application of cellular one piece flow and then tested a model to
implement cellular one piece flow with three SME manufacturing organisations.
This thesis establishes that SME manufacturing organisations do have opportunities to
improve productivity and performance through cellular one piece flow
Una extensión del método de Nelder Mead a problemas de optimización no lineales enteros mixtos
No full textAbstractThis article presents a new algorithm based on the Nelder-Mead simplex algorithmic method for identifying a local optimum, at least on unconstrained nonlinear mixed-integer problems. The algorithmic method, Integer Mixed Simplex Algorithm (IMSA), so called by the author, is based on a double simplex structure, which is composed of a real n-dimensional simplex structure (real simplex) and an integer n-dimensional simplex structure (integer simplex). The original Nelder-Mead operations are applied on the real simplex. Meanwhile, a novel group of operations are applied on the integer simplex. This new set of operations, together with the original Nelder-Mead operations, guarantee a new trail point at each IMSA iteration in the search of the local optimum in the integer real mixed 2n-dimensional numerical field ℝn×ℤn without the need of integer to real conversions
Artificial Bee Colony Algorithm with Nelder–Mead Method to Solve Nurse Scheduling Problem
No full textThe nurse scheduling problem (NSP) is an NP-Hard combinatorial optimization scheduling problem that allocates a set of shifts to the group of nurses concerning the schedule period subject to the constraints. The objective of the NSP is to create a schedule that satisfies both hard and soft constraints suggested by the healthcare management. This work explores the meta-heuristic approach to an artificial bee colony algorithm with the Nelder–Mead method (NM-ABC) to perform efficient nurse scheduling. Nelder–Mead (NM) method is used as a local search in the onlooker bee phase of ABC to enhance the intensification process of ABC. Thus, the author proposed an improvised solution strategy at the onlooker bee phase with the benefits of the NM method. The proposed algorithm NM-ABC is evaluated using the standard dataset NSPLib, and the experiments are performed on various-sized NSP instances. The performance of the NM-ABC is measured using eight performance metrics: best time, standard deviation, least error rate, success percentage, cost reduction, gap, and feasibility analysis. The results of our experiment reveal that the proposed NM-ABC algorithm attains highly significant achievements compared to other existing algorithms. The cost of our algorithm is reduced by 0.66%, and the gap percentage to move towards the optimum value is 94.30%. Instances have been successfully solved to obtain the best deal with the known optimal value recorded in NSPLib
The role of an addictive tendency towards food and patterns of body fat distribution in obesity and metabolic health
No full textFood addiction (FA) is a contributing factor to obesity. Individuals with similar total body fat (BF) %, exhibit a large amount of heterogeneity in how BF is distributed. Certain BF distribution (BFD) patterns produce different outcomes regarding metabolic health. Little is known about how FA influences BFD and metabolic profiles.
The study was designed to evaluate the correlation between FA symptom counts and metabolic characteristics, the correlation between FA symptoms and BFD patterns with emphasis on central obesity and Visceral fat (VF), and the role of android fat (AF) in women’s metabolic health. Data from the CODING study was used for analysis.
FA symptoms are correlated with HOMA-β, triglycerides (TG), inversely correlated with high-density lipoprotein (HDL) in men and are correlated with TG in post-menopausal women. FA symptom counts were also associated with central obesity markers in men and women, including trunk fat (TF) and VF. Women exhibited slightly stronger correlations for all BFD measures except for VF and AF than in men. AF to GF ratio (AGR) affected metabolic characteristics and metabolic syndrome (MetS) risk in women. When separated into AGR tertiles, women in each tertile differed significantly in levels of insulin, glucose, TG, HDL, low-density lipoprotein (LDL), total cholesterol (TC), blood pressure (BP), and waist circumference (WC). Women in the top tertile exhibited higher levels of HOMA-IR and HOMA-β. When women in the top AGR quartile, matched by age and body mass index (BMI) with a control group while controlling for VF, were 2.4x more likely to have MetS.
In conclusion, FA symptoms exhibit correlations with markers of metabolic disturbance in men and to a smaller degree in women. FA symptoms are also correlated with central obesity in men and women. Women with high levels of AF are at increased risk of developing MetS when compared to women of similar age and BMI.Includes bibliographical references
The use of the Nelder-Mead Method in estimating projection parameters for globe photographs
No full textA photo of a terrestrial or celestial globe can be handled as a map. The only hard issue is its projection: the so-called Tilted Perspective Projection, when the optical axis of the photo intersects the globe’s centre, is simplified to the Vertical Near-Side Perspective Projection. Georeferencing such a photo needs the exact parameters of the projections. These parameters depend on the position of the viewpoint of the camera.Several hundreds of globe photos had to be georeferenced during the Virtual Globes Museum project, which made it necessary to automate the calculation of the projection parameters. The author developed a program for this task, which uses the Nelder-Mead Method in order to find the optimum parameters when a set of control points are given as input.The Nelder-Mead method is a numerical algorithm for minimizing a function in a many-dimensional space. The function in the present application is the average error (i.e. the distance between the calculated and real position) of the control points calculated from the actual values of parameters. The parameters are the geographical coordinates of the projection centre, the image coordinates of the same point, the rotation of the projection, the height of the perspective point and the scale of the photo (calculated in pixels/km).The program reads the Global Mapper’s Ground Control Point (.GCP) file format as input and creates projection description files (.PRJ) for the same software. The initial values of the geographical coordinates of the projection centre are calculated as the average of the control points, while the other parameters are set to experimental values, which represent the most common circumstances of taking a globe photograph. The algorithm runs until the change of the parameters sinks below a pre-defined limit. The minimum search can be refined by using the previous result parameter set as new initial values.This paper introduces the calculation mechanism and examples of the usage. Other possible usages of the method are also discussed
YFAS and BFD Data
No full textThis data set contains measures of body fat distribution, physical activity, caloric intake, gender, age and symptoms of food addiction for men and women of a general population from Newfoundland and Labrador. <br
The Association of Upper Body Obesity with Insulin Resistance in the Newfoundland Population
No full textBody-fat distribution is a primary risk factor for insulin resistance and cardiovascular disease. Visceral fat explains only a portion of this risk. The link between upper-body fat and insulin resistance is uncertain. Furthermore, upper-body fat is not clearly defined. Dual-energy X-ray absorptiometry (DXA) can accurately quantify body fat. In this study, we explored the relationship between non-visceral upper-body adiposity and insulin resistance and other markers of metabolic syndrome. Fat proportions in the upper body, leg, and visceral regions were quantified by using DXA in 2547 adult Newfoundlanders aged 19 and older. Adjusting for remaining fat regions, we performed partial correlation analysis for each body region and insulin resistance defined by the Homeostatic Model of Assessment (HOMA). Similarly, partial correlation analysis was also performed between each fat region and other markers of metabolic syndrome, including high-density lipoprotein cholesterol (HDL), triglycerides (TG), body mass index (BMI), and blood pressure. Major confounding factors, including age, caloric intake, and physical activity, were statistically controlled by using partial correlation analysis. Interactions between sex, menopausal status, and medication status were also tested. Arm adiposity was correlated with HOMA-IR (R = 0.132, p < 0.001) and HOMA-β (R = 0.134, p < 0.001). Visceral adiposity was correlated with HOMA-IR (R = 0.230, p < 0.001) and HOMA-β (R = 0.160, p < 0.001). No significant correlation between non-visceral trunk adiposity and insulin resistance was found. Non-visceral trunk adiposity was negatively correlated with HDL in men (R = −0.110, p < 0.001) and women (R = −0.117, p < 0.001). Non-visceral trunk adiposity was correlated with TG (total: R = 0.079, p < 0.001; men: R = 0.105, p = 0.012; women: R = 0.078, p = 0.001). In menopausal women, leg adiposity was negatively correlated with HOMA-IR (R = −0.196, p < 0.001) and HOMA-β (R = −0.101, p = 0.012). Upper-body adiposity in the arms is an independent contributor to insulin resistance. Upper-body adiposity in the non-visceral trunk region is an independent contributor to metabolic syndrome. Leg adiposity is protective against metabolic syndrome in women
The estimation of utility consistent labor supply models by means of simulated scores
No full textLabour Supply
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