Motion analysis deals with determining what and how activities are being performed by a subject, through the use of sensors. The process of answering the what question is commonly known as classification, and answering the how question is here referred to as characterization. Frequently, combinations of inertial sensor such as accelerometers and gyroscopes are used for motion analysis. These sensors are cheap, small, and can easily be incorporated into wearable systems. The overall goal of this thesis was to improve the processing of inertial sensor data for the characterization of movements. This thesis presents a framework for the development of motion analysis systems that targets movement characterization, and describes an implementation of the framework for gait analysis. One substantial aspect of the framework is symbolization, which transforms the sensor data into strings of symbols. Another aspect of the framework is the inclusion of human expert knowledge, which facilitates the connection between data and human concepts, and clarifies the analysis process to a human expert. The proposed implementation was compared to state of practice gait analysis systems, and evaluated in a clinical environment. Results showed that expert knowledge can be successfully used to parse symbolic data and identify the different phases of gait. In addition, the symbolic representation enabled the creation of new gait symmetry and gait normality indices. The proposed symmetry index was superior to many others in detecting movement asymmetry in early-to-mid-stage Parkinson's Disease patients. Furthermore, the normality index showed potential in the assessment of patient recovery after hip-replacement surgery. In conclusion, this implementation of the gait analysis system illustrated that the framework can be used as a road map for the development of movement analysis systems.

Information gathering from sources outside the company plays a critical role in most innovation projects. Particularly, it seems promising to approach external market experts to develop an indepth understanding of current use problems, changing customer needs and trends for new product solutions. When planning expert interviews, firms are confronted with the question whether knowledge is distributed rather homogeneously or heterogeneously ("scattered") among a pool of experts. This issue strongly determines how many experts need to be interviewed in order to develop a comprehensive understanding of a given search field for innovation. In the present paper we analyse expert interviews that were conducted in the context of an innovation project in the field of surgical hygiene products. We find high heterogeneity of expert knowledge: Market experts in our sample vary in terms of market information they provide for the particular product field. We argue that this finding is in alignment with the concept of "bounded rationality" and the theory of "contextual development of knowledge". Our findings have implications for the management of external information gathering and the identification of market experts.(author's abstract)

The World Health Organization, Surgeon General of the United States, and Public Health Agency of Canada have all stated that childhood obesity is one of the most serious health challenges of the 21st century. Thus a purported obesity epidemic among children has generated intense interest in its associated health risks. Increasingly, the medical literature and media blame mothers for failing to provide proper care for their children's health by ignoring the growing weight of their children. While previous literature explores how parenting magazines can be considered public educators about children's health, there is limited literature addressing what parenting magazines specifically say about mothers and childhood obesity. Through a qualitative content analysis of the Canadian parenting magazine Today’s Parent, this paper argues that Today’s Parent stigmatizes mothers by blaming them for the weight issues of children, and suggests future research is needed to investigate to what extent this influences parenting practices.

Since the 1990s, genetically modified (GM) agriculture has become a multi-billion dollar industry. Despite the rapid commercialization of GM crops in the United States, global controversy has slowed the adoption of the technology in developing countries. Yet, few studies have examined regulatory disputes outside of the United States and Europe. Debates in the United States and Europe focus on issues of human health and consumer choice. In other parts of the world, particularly Latin America, disputes center on the threats that GM agriculture poses to unique centers of biodiversity and food security, as well as issues related to bio-fuel expansion and the control over genetic resources and knowledge. My dissertation takes research on biotechnology in a new direction by analyzing the political process through which regulatory knowledge related to GM agriculture is negotiated, contested and reformulated. Guatemala is a key case to examine the politics of biotechnology regulation because despite strong US trade and transnational commercial interests, it is still illegal to grow biotech crops. The question becomes: what explains resistance to agricultural biotechnology? To address this issue, my dissertation focuses on three primary themes. First, I examine historical Mayan rural livelihood strategies within a context of political exclusion and state violence during the country's 36-year civil war. This history, in turn, informs a contemporary context characterized by the continued importance of subsistence-based corn production in the face of mounting rural inequality. Second, I contend that biotechnology regulatory debates in Guatemalan state institutions are integrally tied to a unique national context of corn biodiversity. I focus specifically on disputes between US-sponsored biotechnology regulations based on the principles of free trade and a more cautionary United Nations biosafety program. Third, I argue that resistance to agricultural biotechnology is bringing together diverse Guatemalan Mayan organizations until recently divided by the violence of the civil war. These organizations are deploying sophisticated cultural, economic and environmental knowledges that are effectively challenging efforts to commercialize GM agriculture. On a broader level, this study asserts that resistance to agricultural biotechnology is emblematic of broader struggles over the definition of legitimate knowledge in neoliberal development.

Expert knowledge is an important issue in knowledge management, so how to understand who owned the knowledge that you need and how to touch the experts are important issue. The research is to structure Knowledge Source Map in academic circles by the automatic system and help users to understand the source and the structure of knowledge by querying with this system. Moreover, by this system, user won¡¦t misunderstand experts¡¦ knowledge, and further, they will hold the knowledge and make use of the knowledge. Otherwise, the system also structure communication networks among people by the analysis of social networks to provide a channel for users touching the experts. Therefore, the Knowledge Source Map system is divided into two parts, one is confirmation of the experts, and another is to search for the experts. The former includes analysis in experts, university and domain, and the latter includes family tree analysis, ego-centered networks and shortest path analysis.

Thesis (MScConsEcol)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: Decision-making in conservation should be efficient and effective as time and resources are typically limited. Conservation planning is one process by which stakeholders collaboratively make decisions when attempting to ensure the persistence of biodiversity. Spatial prioritization is the activity of applying quantitative data to spatial analysis to select locations for conservation investment and is a distinct process within conservation planning. The use of experts in spatial prioritization, and more generally in conservation planning, is widely accepted and advocated, but there is no general operational model for how best to involve them. Acceptable standards of practice in selecting experts and in applying specific techniques for eliciting expert knowledge need to be developed and tested in different contexts to ensure robust and defensible results of spatial prioritization processes. Although experts and expert knowledge have limitations, including them in spatial prioritization can produce many benefits, such as increased robustness of decisions and time and cost savings. Timeous, decisive, cost-efficient and robust decision-making is essential when attempting to stem the continued loss of biodiversity across the world. Although widely used, very little research has been conducted into the role of experts in spatial prioritization processes. In this research, the role and use of experts and expert knowledge in spatial prioritization was explored through the following processes: 1) a review of the peer-reviewed literature examining the role, and different types, of experts included in spatial prioritization studies (Chapter 2) to identify the patterns of their involvement; 2) a study examining the process and the differences between individual and group expert outputs and outcomes produced from a typical spatial prioritization workshop to provide a baseline against which experts might be identified for future involvement (Chapter 3); and 3) a study examining the knowledge of local community and land management experts and their ability to predict private landowners self-reported attitudes towards conservation, willingness to partner with organizations and behavior relating to conservation, aimed to test if expert knowledge might replace interviews when mapping conservation opportunity (Chapter 4). The main findings of this research are, firstly, that experts primarily contributed to spatial prioritization through mapping of species, habitats and ecosystems (that can be input into spatial prioritization analyses), and specifically also the selection of areas important for implementing conservation action (e.g., priority conservation areas). Secondly, individual experts contributed different expertise to the spatial prioritization processes in which they were involved, sometimes despite being considered experts in the same field. Individual experts differed to each other in the knowledge they contributed, decisions they made, and in the information content and its spatial representation. Groups of experts collaborating to produce the same information were more effective at capturing expert knowledge than individuals. Thirdly, when seeking to map human and social data to inform the mapping of conservation opportunity, experts were unable to reliably score private landowner's attitudes towards conservation, willingness to partner with organizations and behavior relating to conservation. Experts were able though, to provide accurate knowledge on the general attitudes of landowners, the context of the area in which the research was conducted, and the challenges that landowners in the area face. Collectively, this research can be used to inform the development of standards of best practice to ensure the most effective and cost efficient approach to integrating spatial prioritization software with expert knowledge. / AFRIKAANSE OPSOMMING: Besluitneming in bewaring moet doeltreffend en effektief wees omdat tyd en hulpbronne skaars is. Bewaringsbeplanning is een proses waardeur aandeelhouers gesamentlik besluite kan neem wanneer hul poog om die voortbestaan van biodiversiteit te verseker. Ruimtelike prioritisering verwys na die proses waar kwantitatiewe data toegepas word op ruimtelike analise om areas vir bewaringsbelegging te selekteer. Dit is 'n afsonderlike proses binne bewaringsbeplanning. Die gebruik van deskundiges in die bepaling van ruimtelike prioritisering en meer algemene bewaringsbeplanning word wyd aanvaar en bepleit maar daar is geen algemene operationele model wat bepaal hoe om hul ten beste in te sluit nie. Aanvaarbare standaarde in die praktyk van die seleksie van kundiges en die aanwending van spesifieke tegnieke om kundige kennisstelsels uit te lok moet ontwikkel en getoets word in verskillende kontekste om robuuste en verdedigbare resultate te verseker. Daar is baie voordele verbonde aan die gebruik van deskundiges en kundige kennisstelsels, ten spyte van hul beperkings. Voordele sluit onder andere tyd- en kostebesparings in. Tydige, beslissende, koste-effektiewe en robuuste besluitneming is noodsaaklik wanneer daar gepoog word om die voortdurende wêreldwye verlies aan biodiversiteit te stuit. Al word hul algemeen gebruik is daar nog baie min navorsing gedoen oor die rol van kundiges tydens die proses van ruimtelike prioritisering. Die rol en gebruik van kundiges en kundige kennisstelsels in die bepaling van ruimtelike prioritisering is deur die volgende prosesse ondersoek: 1) 'n Oorsig van portuurbeoordeelde literatuur wat die rol van en verskillende tipes kuniges wat in ruimtelike prioritisering studies ingesluit word, bestudeer (Hoofstuk 2) ten einde die patrone van hul betrokkenheid te identifiseer; 2) 'n studie wat die proses en verskille tussen die insette en uitkomste van individuele en groepe kundiges, soos geproduseer by 'n tipiese ruimtelike prioritisering werkwinkel, bestudeer ten einde 'n grondlyn daar te stel waarteen kundiges vir toekomstige betrokkenheid geïdentifiseer kan word (Hoostuk 3); en 3) 'n bestudering van die kennis van plaaslike gemeenskaps- en grondbestuur kundiges en hul vermoë om privaat grondeienaars se selfgerapporteerde houdings teenoor bewaring, hul bereidwilligheid om met organisasies saam te werk en gedrag wat verband hou met bewaring te voorspel om te toets of kundige kennis onderhoude sal kan vervang tydens die kartering van bewaringsmoontlikhede (Hoofstuk 4). Die vernaamste bevindinge van hierdie navorsing is, ten eerste, dat kundiges se primêre bydrae tot ruimtelike prioritisering plaasvind deur die kartering van spesies, habitats en ekosisteme (wat alles in ruimtelike prioritisering analise vervat kan word), en meer bepaald die seleksie van areas wat belangrik is vir die implementering van bewaringsaksie (bv. prioriteit bewaringsareas). Tweedens, individuele kundiges se bydrae tot die ruimtelike prioritisering prosesse waar hul betrokke was, het verskil, selfs waar hul as kundiges in dieselfde veld beskou word. Individuele kundiges het van mekaar verskil ten opsigte van die kennis wat hul bygedra het, die besluite wat hul geneem het, die inhoud van inligting en die ruimtelike voorstelling daarvan. Groepe kundiges wat saamwerk om dieselfde inligting op te lewer was meer effektief in die vaslegging van kundige kennis as individuele kundiges. Derdens, tydens die soeke na menslike en maatskaplike data om die kartering van bewaringsmoontlikhede in te lig was kundiges nie in staat is om 'n betroubare skatting van privaat grondeienaars se houdings teenoor bewaring, bereidwilligheid om saam met organisasies te werk en gedrag wat verband hou met bewaring te maak nie. Deskundiges kon egter akkurate kennis meedeel ten opsigte van die algemene houdings van grondeienaars, die konteks van die area van navorsing en die uitdagings wat grondeienaars in die spesifieke areas in die gesig staar. Hierdie navorsing kan gesamentlik gebruik word om die ontwikkeling van standaarde van beste praktyk vas te stel om die mees doeltreffende en koste-effektiewe benadering tot die integrasie van ruimtelike prioritisering sagteware met deskundige kennis te verseker.

Authoritative, top-down forms of environmental governance are presently giving way to more collaborative approaches in which decision making is an ongoing negotiation between government and non-government actors. There is growing consensus that critical environmental concerns—such as contamination of drinking water—relate as much to political, economic and social issues, as to technical and scientific issues. As the trend toward collaborative environmental governance continues, and as science-based knowledge increasingly shares a role in decision-making processes with more “local”, non-scientific knowledge, questions arise concerning how diverse knowledge contributions are understood and engaged in these governance processes. This research explored the relationships between knowledge and collaborative environmental governance processes. The purpose of the research was to identify (1) types of knowledge that individual actors bring into collaborative governance pertaining to water resource protection, (2) uses of that knowledge, and (3) features of collaborative processes that affect the engagement of actor knowledge. Collaborative water governance in New Brunswick provided the context for the research. Most actors did not see a definitive distinction between “expert”, scientific and “local”, non-scientific knowledge; they considered both to be important contributions. Nonetheless, science-based knowledge, especially natural science, was found to be a predominant knowledge type among actors involved in collaborative water governance. Science-based, expert knowledge was more readily used than local knowledge types in the various stages of collaborative governance. Leadership and the definition of actor roles were considered paramount for engaging a wide range of knowledge types in collaborative governance processes.

Authoritative, top-down forms of environmental governance are presently giving way to more collaborative approaches in which decision making is an ongoing negotiation between government and non-government actors. There is growing consensus that critical environmental concerns—such as contamination of drinking water—relate as much to political, economic and social issues, as to technical and scientific issues. As the trend toward collaborative environmental governance continues, and as science-based knowledge increasingly shares a role in decision-making processes with more “local”, non-scientific knowledge, questions arise concerning how diverse knowledge contributions are understood and engaged in these governance processes. This research explored the relationships between knowledge and collaborative environmental governance processes. The purpose of the research was to identify (1) types of knowledge that individual actors bring into collaborative governance pertaining to water resource protection, (2) uses of that knowledge, and (3) features of collaborative processes that affect the engagement of actor knowledge. Collaborative water governance in New Brunswick provided the context for the research. Most actors did not see a definitive distinction between “expert”, scientific and “local”, non-scientific knowledge; they considered both to be important contributions. Nonetheless, science-based knowledge, especially natural science, was found to be a predominant knowledge type among actors involved in collaborative water governance. Science-based, expert knowledge was more readily used than local knowledge types in the various stages of collaborative governance. Leadership and the definition of actor roles were considered paramount for engaging a wide range of knowledge types in collaborative governance processes.

Combine harvesters are used to gather plants from the field and separate them into the components of value, the grain and the straw. The optimal utilization of existing combine potential is an inevitable task to maximize harvest efficiency and hence to maximize profit. The only way to optimize the threshing and separation processes during harvest is to adjust the combine settings to existing conditions. Operating permanently at optimal harvest efficiency can only be achieved by an automatic control system. However, for reasons of transparency and due to lack of sensors, the approach in this thesis is a combined development of an interactive and an automatic control system for combine process optimization. The optimization of combine processes is a multi-dimensional and multi-objective optimization problem. The objectives of optimization are the harvest quality parameters. The decision variables, the parameters that can be modified, are the combine settings. Analytical optimization methods require the existence of a model that provides function values in dependence of defined input parameters. A comprehensive quantitative model for the input-output-behavior of the combine does not exist. Alternative optimization methods that handle multi-dimensional and multi-objective optimization problems can be found in the domain of Artificial Intelligence. In this work, knowledge acquisition was performed in order to obtain expert knowledge on combine process optimization. The result is a knowledge base with six adjustment matrices for different crop and combine types. The adjustment matrices contain problem oriented setting adjustment recommendations in order to solve single issues with quality parameters. A control algorithm has been developed that is also capable of solving multiple issues at the same time, utilizing the acquired expert knowledge. The basic principle to solve the given multi-objective optimization problem is a transformation into one-dimensional single-objective optimization problems which are solved iteratively. Several methods have been developed that are applied sequentially. In simulation, the average improvement from initial settings to optimized settings, achieved by the control algorithm, is between 34.5 % and 67.6 %. This demonstrates the good performance of the control algorithm.

About 75% of the total product cost is determined in the early design phase, which means that the possibilities to affect costs are relatively small when the design phase is completed. For companies, it is therefore vital to conduct reliable cost estimates in the early design phase, when selecting between different design choices. When conducting a cost estimate there are many uncertainties. The aim with this study is therefore to explore how uncertainties regarding product cost can be considered when estimating product cost and how expert’s knowledge can be integrated within cost estimation. A case study has been conducted within the aerospace industry at the company GKN Aerospace Sweden (GAS) in Trollhättan, from which a model to estimate product cost has been developed. The model is developed for space turbines, but can with modifications be used for other products. Space turbines are highly advanced products, produced in small batches with complex manufacturing processes and high costs. Because of the heavy capital investment, long lead times and high risks, cost estimates become very important, which made GAS suitable for the case study. The new cost estimation model (NCEM) developed is a combination between intuitive, analogical and analytical cost estimation techniques. Product cost at GAS is built up by the following cost elements; raw material, purchased parts, material surcharge, manufacturing cost, manufacturing surcharge, outsourced operations, method support, delivery cost, warranty and scrap, which are studied more in depth. The material cost is estimated based on historical data and a list of previous purchased alloys is created. The manufacturing cost is determined more in detail where the cost for each operation is estimated, based on operation time, amount of removed material or welding speed. The method support cost is estimated based on a study of an internal prognosis where the amount of time from each discipline needed to support the product is determined. Included in the NCEM is also a risk assessment. The main insights from this study is that transparency is vital when estimating product cost. It is important to state what assumptions that have been made. Breaking down the product cost into smaller units and create awareness about the cost drivers will identify risks and reduce uncertainness. Experts possess a great deal of knowledge about cost drivers and should be integrated when estimating product cost.