964 resultados para multiple objective programming


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The objective of this article is to identify differential traits of successful SMEs in comparison to average SME firms in the textile and clothing sector. The method used is the multiple case-study of 12 firms based on qualitative and quantitative data obtained by means of in-depth interviews. Building on recent academic literature, we use four main dimensions that may explain success: i) knowledge generation (R&D) and acquisition; ii) innovation activity; iii) product and market characteristics and iv) strategic characteristics. Our results indicate that a higher R&D intensity and knowledge acquisition do not explain success. The main differential characteristic is that successful firms have a higher level of innovation activity, since innovation is their strategic priority, being a result of perceiving the key success factors of their markets differently. From the analysis it also follows that the prevalent strategy of successful firms is the niche strategy, with a demand pull focus, and a high proximity to the customer

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Global warming mitigation has recently become a priority worldwide. A large body of literature dealing with energy related problems has focused on reducing greenhouse gases emissions at an engineering scale. In contrast, the minimization of climate change at a wider macroeconomic level has so far received much less attention. We investigate here the issue of how to mitigate global warming by performing changes in an economy. To this end, we make use of a systematic tool that combines three methods: linear programming, environmentally extended input output models, and life cycle assessment principles. The problem of identifying key economic sectors that contribute significantly to global warming is posed in mathematical terms as a bi criteria linear program that seeks to optimize simultaneously the total economic output and the total life cycle CO2 emissions. We have applied this approach to the European Union economy, finding that significant reductions in global warming potential can be attained by regulating specific economic sectors. Our tool is intended to aid policymakers in the design of more effective public policies for achieving the environmental and economic targets sought.

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Most Finnish periodical magazines have a website, often an online service. The objective of this thesis is to understand the magazines’ resources and capabilities and match them with online strategies’ goals and objectives. The thesis’ theoretical part focuses on explaining and classifying resources, capabilities, goals and objectives, and applying everything into Finnish magazine publishing context. In the empirical part, there is a comparative case study of four magazines. The findings indicate that with cooperating, advertising and community hosting capabilities magazines may utilize their human, brand, content and customer base resources. The resources can be further addressed to reach profitability, customer-centricity and brand congruency goals.

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The skill of programming is a key asset for every computer science student. Many studies have shown that this is a hard skill to learn and the outcomes of programming courses have often been substandard. Thus, a range of methods and tools have been developed to assist students’ learning processes. One of the biggest fields in computer science education is the use of visualizations as a learning aid and many visualization based tools have been developed to aid the learning process during last few decades. Studies conducted in this thesis focus on two different visualizationbased tools TRAKLA2 and ViLLE. This thesis includes results from multiple empirical studies about what kind of effects the introduction and usage of these tools have on students’ opinions and performance, and what kind of implications there are from a teacher’s point of view. The results from studies in this thesis show that students preferred to do web-based exercises, and felt that those exercises contributed to their learning. The usage of the tool motivated students to work harder during their course, which was shown in overall course performance and drop-out statistics. We have also shown that visualization-based tools can be used to enhance the learning process, and one of the key factors is the higher and active level of engagement (see. Engagement Taxonomy by Naps et al., 2002). The automatic grading accompanied with immediate feedback helps students to overcome obstacles during the learning process, and to grasp the key element in the learning task. These kinds of tools can help us to cope with the fact that many programming courses are overcrowded with limited teaching resources. These tools allows us to tackle this problem by utilizing automatic assessment in exercises that are most suitable to be done in the web (like tracing and simulation) since its supports students’ independent learning regardless of time and place. In summary, we can use our course’s resources more efficiently to increase the quality of the learning experience of the students and the teaching experience of the teacher, and even increase performance of the students. There are also methodological results from this thesis which contribute to developing insight into the conduct of empirical evaluations of new tools or techniques. When we evaluate a new tool, especially one accompanied with visualization, we need to give a proper introduction to it and to the graphical notation used by tool. The standard procedure should also include capturing the screen with audio to confirm that the participants of the experiment are doing what they are supposed to do. By taken such measures in the study of the learning impact of visualization support for learning, we can avoid drawing false conclusion from our experiments. As computer science educators, we face two important challenges. Firstly, we need to start to deliver the message in our own institution and all over the world about the new – scientifically proven – innovations in teaching like TRAKLA2 and ViLLE. Secondly, we have the relevant experience of conducting teaching related experiment, and thus we can support our colleagues to learn essential know-how of the research based improvement of their teaching. This change can transform academic teaching into publications and by utilizing this approach we can significantly increase the adoption of the new tools and techniques, and overall increase the knowledge of best-practices. In future, we need to combine our forces and tackle these universal and common problems together by creating multi-national and multiinstitutional research projects. We need to create a community and a platform in which we can share these best practices and at the same time conduct multi-national research projects easily.

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The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

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Social media is a rather new phenomenon which has revolutionised the world of online communication. However, academic research on how companies can benefit from social media is lacking. The research objective of this thesis was to examine the use of social media in international brand communication of small Finnish design-intensive companies. Therefore, this research contributes also to the research gap in SME branding. The focus was on communication targeted at consumers. The research was carried out as a mixed methods research employing the questionnaire and multiple case study methods. The questionnaire was used to gather preliminary information on Finnish design-intensive companies and to provide an eligible list of companies for deeper examination. Then, four case companies were studied in more depth. The empirical evidence of the case companies was mainly gathered through theme interviews. The results of the questionnaire shed light on the internationalisation of small Finnish designintensive companies. On average, the companies had internationalised rather quickly after they had been founded. However, the share of exports was rather low in most of the companies. The results revealed also that social media was already used widely in the exporting companies and the use can be expected to grow in future. The findings of the multiple case study suggest that branding activities in small Finnish designintensive companies are constrained by limited resources and skills. In addition, the branding activities are strongly guided by the vision and values of the entrepreneur(s) rather than extensive marketing research. The brand structure was simple in all case companies and they aimed at having a standardised brand image across markets. However, all case companies had faced a need for some adaptation of their international brand communication. Internationally important brand communication channels were international fairs, the internet, word-of-mouth and social media. Social media offered a cost-effective brand communication channel for the case companies. It was used for various purposes, such as creating brand awareness and affecting how the brand is perceived. The entrepreneurs found the use of social media to be rather easy and the case companies had not faced any major challenges. However, the companies had recognised that communication in social media requires consistency and planning. The planning was rather informal and stayed on a general level. Overall, the utilisation of social media in the case companies was limited by a lack of resources. It seemed to affect especially the follow-up of brand communication in social media which stayed rather superficial.

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ABSTRACT The objective of this research was to evaluate the occurance of multiple resistance of Sagittaria montevidensis (SAGMO) biotypes to acetolactate synthase (ALS) and photosystem II (PSII) inhibiting herbicides through dose-response experiments. The experiment was conducted in a greenhouse from October 2012 to March 2013, in Pelotas, RS. The experimental design was completely randomized, with four replications. Treatments were arranged in a triple factorial design: two biotypes of S. montevidensis(SAGMO 35 - susceptible to herbicides and SAGMO 32 - suspected to be multiple resistance to ALS and PSII inhibiting herbicides), four herbicides (penoxsulam, (imazethapyr+imazapic), bentazon and saflufenacil) and 8 rates of these herbicides (1/32x, 1/16x, 1/8x, 1/4x, 1/2x, 0x, 1x, 2x, 4x, 8x, 16x, 32x and 64x). SAGMO 32 biotype presented high levels of resistance to penoxsulam, (imazethapyr+imazapic) and bentazon. For a 50% reduction in dry matter of the resistant biotype rate of 138 and 2.46 times higher than the label required for the susceptible biotype of the herbicides (imazethapyr+imazapic) and bentazon, respectively, are required. Saflufenacil may be used successfully to controlSagittaria montevidensis resistant in irrigated rice.

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It has been proposed that the multiple-platform method (MP) for desynchronized sleep (DS) deprivation eliminates the stress induced by social isolation and by the restriction of locomotion in the single-platform (SP) method. MP, however, induces a higher increase in plasma corticosterone and ACTH levels than SP. Since deprivation is of heuristic value to identify the functional role of this state of sleep, the objective of the present study was to determine the behavioral differences exhibited by rats during sleep deprivation induced by these two methods. All behavioral patterns exhibited by a group of 7 albino male Wistar rats submitted to 4 days of sleep deprivation by the MP method (15 platforms, spaced 150 mm apart) and by 7 other rats submitted to sleep deprivation by the SP method were recorded in order to elaborate an ethogram. The behavioral patterns were quantitated in 10 replications by naive observers using other groups of 7 rats each submitted to the same deprivation schedule. Each quantification session lasted 35 min and the behavioral patterns presented by each rat over a period of 5 min were counted. The results obtained were: a) rats submitted to the MP method changed platforms at a mean rate of 2.62 ± 1.17 platforms h-1 animal-1; b) the number of episodes of noninteractive waking patterns for the MP animals was significantly higher than that for SP animals (1077 vs 768); c) additional episodes of waking patterns (26.9 ± 18.9 episodes/session) were promoted by social interaction in MP animals; d) the cumulative number of sleep episodes observed in the MP test (311) was significantly lower (chi-square test, 1 d.f., P<0.05) than that observed in the SP test (534); e) rats submitted to the MP test did not show the well-known increase in ambulatory activity observed after the end of the SP test; f) comparison of 6 MP and 6 SP rats showed a significantly shorter latency to the onset of DS in MP rats (7.8 ± 4.3 and 29.0 ± 25.0 min, respectively; Student t-test, P<0.05). We conclude that the social interaction occurring in the MP test generates additional stress since it increases the time of forced wakefulness and reduces the time of rest promoted by synchronized sleep.

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It is well established that interleukin-6 (IL-6) is an essential growth factor for multiple myeloma (MM) and patients with increased IL-6 levels have a poor prognosis. In healthy subjects, the presence of the C allele at a polymorphic site (-174 G/C) of the IL-6 gene is related to low IL-6 levels. In view of the potential association of this particular polymorphism with IL-6 concentration, and the relevance of IL-6 in MM pathogenesis, the objective of the present study was to investigate the prevalence of IL-6 (-174 G/C) promoter polymorphism and its association with development of MM in Brazilian individuals. We investigated the prevalence of these alleles in 52 patients and 60 healthy subjects (matched by age, sex, and race) of a Brazilian population. Thirty patients were male (42.4%), 24 (46.2%) were white and the median age at diagnosis was 58.5 years (range: 28 to 84 years). To determine the IL-6 (-174 G/C) polymorphism, molecular analysis was performed by polymerase chain reaction followed by endonuclease restriction digestion. The genotype distributions observed in the group of patients were 4% CC, 42% GC and 54% GG. The C allele frequency was 0.25. These results were similar to the control group, suggesting no impact of this polymorphism on the susceptibility to MM.

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The main objective of this study was to find out the bases for innovation model formulation in an existing organization based on cases. Innovation processes can be analyzed based on their needs and based on their emphasis on the business model development or R&D. The research was conducted in energy sector within one company by utilizing its projects as cases for the study. It is typical for the field of business that development is slow, although the case company has put emphasis on its innovation efforts. Analysis was done by identifying the cases’ needs and comparing them. The results were that because of the variances in the needs of the cases, the applicability of innovation process models varies. It was discovered that by dividing the process into two phases, a uniform model could be composed. This model would fulfill the needs of the cases and potential future projects as well.

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The objective of the present study was to determine if there is a relationship between serum levels of brain-derived neurotrophic factor (BDNF) and the number of T2/fluid-attenuated inversion recovery (T2/FLAIR) lesions in multiple sclerosis (MS). The use of magnetic resonance imaging (MRI) has revolutionized the study of MS. However, MRI has limitations and the use of other biomarkers such as BDNF may be useful for the clinical assessment and the study of the disease. Serum was obtained from 28 MS patients, 18-50 years old (median 38), 21 women, 0.5-10 years (median 5) of disease duration, EDSS 1-4 (median 1.5) and 28 healthy controls, 19-49 years old (median 33), 19 women. BDNF levels were measured by ELISA. T1, T2/FLAIR and gadolinium-enhanced lesions were measured by a trained radiologist. BDNF was reduced in MS patients (median [range] pg/mL; 1160 [352.6-2640]) compared to healthy controls (1640 [632.4-4268]; P = 0.03, Mann-Whitney test) and was negatively correlated (Spearman correlation test, r = -0.41; P = 0.02) with T2/FLAIR (11-81 lesions, median 42). We found that serum BDNF levels were inversely correlated with the number of T2/FLAIR lesions in patients with MS. BDNF may be a promising biomarker of MS.

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The Robocup Rescue Simulation System (RCRSS) is a dynamic system of multi-agent interaction, simulating a large-scale urban disaster scenario. Teams of rescue agents are charged with the tasks of minimizing civilian casualties and infrastructure damage while competing against limitations on time, communication, and awareness. This thesis provides the first known attempt of applying Genetic Programming (GP) to the development of behaviours necessary to perform well in the RCRSS. Specifically, this thesis studies the suitability of GP to evolve the operational behaviours required of each type of rescue agent in the RCRSS. The system developed is evaluated in terms of the consistency with which expected solutions are the target of convergence as well as by comparison to previous competition results. The results indicate that GP is capable of converging to some forms of expected behaviour, but that additional evolution in strategizing behaviours must be performed in order to become competitive. An enhancement to the standard GP algorithm is proposed which is shown to simplify the initial search space allowing evolution to occur much quicker. In addition, two forms of population are employed and compared in terms of their apparent effects on the evolution of control structures for intelligent rescue agents. The first is a single population in which each individual is comprised of three distinct trees for the respective control of three types of agents, the second is a set of three co-evolving subpopulations one for each type of agent. Multiple populations of cooperating individuals appear to achieve higher proficiencies in training, but testing on unseen instances raises the issue of overfitting.

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The CATCH Kids Club (CKC) is an after-school intervention that has attempted to address the growing obesity and physical inactivity concerns publicized in current literature. Using Self-Determination Theory (SDT: Deci & Ryan, 1985) perspective, this study's main research objective was to assess, while controlling for gender and age, i f there were significant differences between the treatment (CKC program participants) and control (non- eKC) groups on their perceptions of need satisfaction, intrinsic motivation and optimal challenge after four months of participation and after eight months of participation. For this study, data were collected from 79 participants with a mean age of9.3, using the Situational Affective State Questionnaire (SASQ: Mandigo et aI., 2008). In order to determine the common factors present in the data, a principal component analysis was conducted. The analysis resulted in an appropriate three-factor solution, with 14 items loading onto the three factors identified as autonomy, competence and intrinsic motivation. Initially, a multiple analysis of co-variance (MANCOY A) was conducted and found no significant differences or effects (p> 0.05). To further assess the differences between groups, six analyses of co-variance (ANeOY As) were conducted, which also found no significant differences (p >0 .025). These findings suggest that the eKC program is able to maintain the se1fdetermined motivational experiences of its participants, and does not thwart need satisfaction or self-determined motivation through its programming. However, the literature suggests that the CKe program and other P A interventions could be further improved by fostering participants' self-determined motivational experiences, which can lead to the persistence of healthy PA behaviours (Kilpatrick, Hebert & Jacobsen, 2002).

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This thesis focuses on developing an evolutionary art system using genetic programming. The main goal is to produce new forms of evolutionary art that filter existing images into new non-photorealistic (NPR) styles, by obtaining images that look like traditional media such as watercolor or pencil, as well as brand new effects. The approach permits GP to generate creative forms of NPR results. The GP language is extended with different techniques and methods inspired from NPR research such as colour mixing expressions, image processing filters and painting algorithm. Colour mixing is a major new contribution, as it enables many familiar and innovative NPR effects to arise. Another major innovation is that many GP functions process the canvas (rendered image), while is dynamically changing. Automatic fitness scoring uses aesthetic evaluation models and statistical analysis, and multi-objective fitness evaluation is used. Results showed a variety of NPR effects, as well as new, creative possibilities.

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Hub Location Problems play vital economic roles in transportation and telecommunication networks where goods or people must be efficiently transferred from an origin to a destination point whilst direct origin-destination links are impractical. This work investigates the single allocation hub location problem, and proposes a genetic algorithm (GA) approach for it. The effectiveness of using a single-objective criterion measure for the problem is first explored. Next, a multi-objective GA employing various fitness evaluation strategies such as Pareto ranking, sum of ranks, and weighted sum strategies is presented. The effectiveness of the multi-objective GA is shown by comparison with an Integer Programming strategy, the only other multi-objective approach found in the literature for this problem. Lastly, two new crossover operators are proposed and an empirical study is done using small to large problem instances of the Civil Aeronautics Board (CAB) and Australian Post (AP) data sets.