Thesis (MBA.) -- University of Limpopo, 2015 / This research report investigated job satisfaction and organisational commitment in a changing environment at Sefako Makgatho Health Sciences University (SMU). The desire to this enquiry was a result of the recent de-merger and name change experienced at the University hence the researcher developed curiosity to determine if employees are still satisfied with their jobs and whether they are still committed to work for the organisation. The research also investigated the perceptions of employees regarding management of change at SMU. Evidence from the obtained data shows that employees are generally satisfied to work for SMU hence it seems to suggest that they are also committed to work for SMU. The research was quantitative in nature utilising convenient sampling method. A convenient sample size of (114) was utilised in the execution of this research. The sample was drawn from both administrative and academic staff of the institution. Sections A, B and C of the questionnaire were analysed using SPSS version 22 and section D of the questionnaire was analysed using thematic analysis.

Walking around in dynamically changing environments require the integration of three of our sensory systems: visual, vestibular, and kinesethic. Vision is the only modality of these three sensory systems that provides information at a distance for proactively controlling locomotion (Gibson, 1958). The visual system provides information about self-motion, about body position and body segments relative to one another and the environment, and environmental information at a distance (Patla, 1998). Gibson (1979) developed the idea that everyday behaviour is controlled by perception-action coupling between an action and some specific information picked up from the optic flow that is generated by that action. Such that visual perception guides the action required to navigate safely through an environment and the action in turn alters perception. The objective of my thesis was to determine how well perception and action are coupled when approaching and walking through moving doors with dynamically changing apertures. My first two studies were grouped together and here I found that as the level of threat increased, the parameters of control changed and not the controlling mechanism. The two dominant action control parameters observed were a change in approach velocity and a change in posture (i. e. shoulder rotation). These findings add to previous work done in this area using a similar set-up in virtual reality, where after much practice participants increased success rate by decreasing velocity prior to crossing the doors. In my third study I found that visual fixation patterns and action parameters were similar when the location of the aperture was predictable and when it was not. Previous work from other researchers has shown that vision and a subsequent action are tightly coupled with a latency of about 1second. I have found that vision only tightly couples action when a specific action is required and the threat of a collision increases. My findings also point in the same direction as previous work that has shown that individuals look where they are going. My last study was designed to determine if we go where we are looking. Here I found that action does follow vision but is only loosely correlated. The most important and common finding from all the studies is that at 2 seconds prior to crossing the moving doors (any type of movement) vision seems to have the most profound effect on action. At this time variability in action is significantly lower than at prior times. I believe that my findings will help to understand how individuals use vision to modify actions in order to avoid colliding with other people or other moving objects within the environment. And this knowledge will help elderly individuals to be better able to cope with walking in cluttered environments and avoid contacting other objects.

Walking around in dynamically changing environments require the integration of three of our sensory systems: visual, vestibular, and kinesethic. Vision is the only modality of these three sensory systems that provides information at a distance for proactively controlling locomotion (Gibson, 1958). The visual system provides information about self-motion, about body position and body segments relative to one another and the environment, and environmental information at a distance (Patla, 1998). Gibson (1979) developed the idea that everyday behaviour is controlled by perception-action coupling between an action and some specific information picked up from the optic flow that is generated by that action. Such that visual perception guides the action required to navigate safely through an environment and the action in turn alters perception. The objective of my thesis was to determine how well perception and action are coupled when approaching and walking through moving doors with dynamically changing apertures. My first two studies were grouped together and here I found that as the level of threat increased, the parameters of control changed and not the controlling mechanism. The two dominant action control parameters observed were a change in approach velocity and a change in posture (i. e. shoulder rotation). These findings add to previous work done in this area using a similar set-up in virtual reality, where after much practice participants increased success rate by decreasing velocity prior to crossing the doors. In my third study I found that visual fixation patterns and action parameters were similar when the location of the aperture was predictable and when it was not. Previous work from other researchers has shown that vision and a subsequent action are tightly coupled with a latency of about 1second. I have found that vision only tightly couples action when a specific action is required and the threat of a collision increases. My findings also point in the same direction as previous work that has shown that individuals look where they are going. My last study was designed to determine if we go where we are looking. Here I found that action does follow vision but is only loosely correlated. The most important and common finding from all the studies is that at 2 seconds prior to crossing the moving doors (any type of movement) vision seems to have the most profound effect on action. At this time variability in action is significantly lower than at prior times. I believe that my findings will help to understand how individuals use vision to modify actions in order to avoid colliding with other people or other moving objects within the environment. And this knowledge will help elderly individuals to be better able to cope with walking in cluttered environments and avoid contacting other objects.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2015-12-02T18:20:09Z No. of bitstreams: 1 karinemunckvieira.pdf: 1540105 bytes, checksum: fa21a938e102b38c05882b697b40e024 (MD5) / Rejected by Adriana Oliveira (adriana.oliveira@ufjf.edu.br), reason: Título: somente primeira letra da primeira palavra em maiúsculo e nomes próprios também. Palavras-chave: acrescentar uma em cada linha (não precisa colocar ponto e nem vírgula no final) on 2015-12-03T11:56:46Z (GMT) / Submitted by Renata Lopes (renatasil82@gmail.com) on 2015-12-03T12:31:46Z No. of bitstreams: 1 karinemunckvieira.pdf: 1540105 bytes, checksum: fa21a938e102b38c05882b697b40e024 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2015-12-03T13:57:23Z (GMT) No. of bitstreams: 1 karinemunckvieira.pdf: 1540105 bytes, checksum: fa21a938e102b38c05882b697b40e024 (MD5) / Made available in DSpace on 2015-12-03T13:57:23Z (GMT). No. of bitstreams: 1 karinemunckvieira.pdf: 1540105 bytes, checksum: fa21a938e102b38c05882b697b40e024 (MD5) Previous issue date: 2015-02-19 / FAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais / As modificações do ambiente pela ação humana podem favorecer determinadas espécies e comprometer a existência de outras. Os efeitos da interferência antrópica podem ser monitorados através de vespas solitárias, nidificantes em cavidades preexistentes e abelhas sem ferrão. Desta forma, objetivou-se comparar a composição dessas comunidades em áreas de maior (A1) e menor (A2) interferência antrópica em um fragmento urbano de Mata Atlântica. Para investigar a composição de vespas, foram instalados e monitorados, durante um ano, ninhos armadilha de bambu e cartolina de diâmetros variados, em um transecto representante de cada uma das áreas. A fim de comparar os mesmos locais quanto às espécies de meliponíneos residentes, foram feitas buscas de ninhos, por meio de deslocamentos ao longo das trilhas existentes nas áreas arborizadas do Jardim Botânico de Juiz de Fora, MG, que representaram a área A1, e no entorno das antigas construções, representando a área A2. Em relação às vespas, três das quatro espécies coletadas são adaptadas a ambientes modificados, e por esse motivo, houve maior riqueza (n=3) e abundância (n= 21) nessa área, sendo uma espécie (Pachodynerus sp.) exclusiva dessa localidade. O gênero Trypoxylon foi o mais representativo, sendo que 74,07% dos seus ninhos pertenceram a área com maior interferência antrópica. Os gomos de bambu foram utilizados com maior frequência (64,28%) e amostraram todas as espécies de vespas desse estudo. A abundância de ninhos em cada mês esteve correlacionada positivamente com temperatura média (rs= 0,44; p= 0,007), mas só houve correlação com a precipitação, nos meses de dezembro e janeiro. A similaridade entre a composição das espécies de vespas e de abelhas nas áreas A1 e A2 foi moderada (Cs= 0,66; Cs= 0,61), respectivamente; porém, a abundância das mesmas foi semelhantes (t= 1,96/ p= 0,097). Em relação às abelhas sem ferrão, a área A1 apresentou não apenas uma maior densidade de ninhos (80%) e riqueza de espécies (n=8) que a área A2 (n=5), como também em relação a outros estudos em áreas modificadas. A alta densidade de ninhos nessa localidade foi devido a 56,66% pertencerem a Nannotrigona testaceicornis e Tetragonisca angustula, espécies muito encontradas em locais urbanizados. Já a baixa riqueza e abundância de ninhos na área A2, foi, em parte, pelo fato de essa área encontra-se em estágio de sucessão inicial. O estabelecimento dos Hymenoptera amostrados nesse estudo em área de maior interferência antrópica, só foi possível porque a oferta de recursos naturais é suficiente à sobrevivência das espécies. / Environmental changes by human action may favor some species and compromising the existence of other. The effects of the anthropogenic impact can be monitored through solitary wasps that made nests in trap nesting and stingless bees. Thus, the objective was to compare the composition of these communities in areas of greater (A1) and lesser (A2) anthropogenic interference, in an urban fragment of the Atlantic Forest. To investigate the composition wasps were installed and monitored during one year, trap nesting made of bamboo and cardboard, with varying diameters in a representative transect in both areas. In order to compare this locations as the resident species of stingless bees, were made searches for nests along existing trails in the wooded areas of the Jardim Botânico de Juiz de Fora, Minas Gerais, representing the A1 area, and surrounding the old buildings, representing the A2 area. In relation to wasps, three of the four species collected are adapted to changing environments, and therefore, a greater richness (n = 3) and abundance (n = 21) in this area, with one species exclusive of this location (Pachidynerus sp). The Trypoxylon gender was the most representative, with 74.07% of their nests belonged to area with greater human interference. The bamboo canes were frequently used (64.28%) and sampled all kinds of wasps in this study. The abundance of nests in each month was positively correlated with mean temperature (rs = 0.44; p = 0.007), but just only have correlation with rainfall in December and January. The similarity between the species composition of wasps and bees in the areas A1 and A2 was moderate (Cs = 0.66; Cs = 0.61), respectively; but plenty of them was similar (t = 1.96 / p = 0.097). Regarding the stingless bees, the area most affected by human activity, had not only a higher density of nests (80%) and richness of species (n = 8) the A2 area (n=5), but also in relation to other studies in areas modified. The high density of nests in this location was due to 56.67% belong to Nannotrigona testaceicornis and Tetragonisca angustula, species broadly found in urbanized areas. The low richness and abundance of nests in the area A2, was, in part, because this area is at an early succession stage. The establishment of Hymenoptera sampled in this study in an area of greater human interference, was only possible because the supply of natural resources is sufficient for the survival of the species.

This thesis provides insight to the dynamics that come with the emergence of IoT in the furniture and kitchen manufacturing industry. The study is empirically grounded in an explorative case study that involves interviews with six manufacturing companies in the different industry sectors. The purpose has been to shed light on how incumbent companies adapt and implement IoT and the study highlight product features, aspects and challenges that companies are investigating and dealing with as they set out to work with IoT and connected products. The results indicate that companies are viewing IoT as an enabler that better can respond to customer needs and provide users with new experiences. By implementing the concept of IoT companies are currently evaluating how internal knowledge and skillsets correspond to the new technical requirements that the emerging digital setting outlines and by directing internal research they are learning more about IoT and connected products as they proceed. One current major problem is that there are no open protocols that can connect all products regardless of supplier. Nevertheless, implementation of IoT does not solely involve technical aspects and companies are also faced with the dilemma on how to design and develop corresponding commercial processes. To this point early product implementations have arrived on the consumer markets and the future vision is to achieve full integration that imbeds connectivity and interaction among all products in the home.

This dissertation thesis is concerned with developing a mesoscopic model for sin- gle crystalline shape-memory alloys including thermo-dynamically consistent thermo- mechanical coupling - here the term "mesoscopic" refers to the ability of the model to capture fine spatial oscillations of the deformation gradient by means of gradient Young measures. Existence of solutions to the devised model is proved in a "phase-field-like approach" by a scale transition from a microscopic model that features a term related to the interfacial energy; this scale transition from a physically relevant model justifies the mesoscopic relaxation. Further, existence of solutions is also proved by backward- Euler time discretization which forms a conceptual numerical algorithm. Based on this conceptual algorithm a computer implementation of the model has been developed and further optimized in the rate-independent isothermal setting; some calculations using this implementation are also presented. Finally, refinements s of the analysis in the convex case as well as a limit of the phase-field-like approach in this case are exposed, too.

Visual place recognition is the task of finding same places in a set of database images for a given set of query images. This becomes particularly challenging for long-term applications when the environmental condition changes between or within the database and query set, e.g., from day to night. Visual place recognition in changing environments can be used if global position data like GPS is not available or very inaccurate, or for redundancy. It is required for tasks like loop closure detection in SLAM, candidate selection for global localization, or multi-robot/multi-session mapping and map merging. In contrast to pure image retrieval, visual place recognition can often build upon additional information and data for improvements in performance, runtime, or memory usage. This includes additional data-inherent knowledge about information that is contained in the image sets themselves because of the way they were recorded. Using data-inherent knowledge avoids the dependency on other sensors, which increases the generality of methods for an integration into many existing place recognition pipelines. This thesis focuses on the usage of additional data-inherent knowledge. After the discussion of basics about visual place recognition, the thesis gives a systematic overview of existing data-inherent knowledge and corresponding methods. Subsequently, the thesis concentrates on a deeper consideration and exploitation of four different types of additional data-inherent knowledge. This includes 1) sequences, i.e., the database and query set are recorded as spatio-temporal sequences so that consecutive images are also adjacent in the world, 2) knowledge of whether the environmental conditions within the database and query set are constant or continuously changing, 3) intra-database similarities between the database images, and 4) intra-query similarities between the query images. Except for sequences, all types have received only little attention in the literature so far. For the exploitation of knowledge about constant conditions within the database and query set (e.g., database: summer, query: winter), the thesis evaluates different descriptor standardization techniques. For the alternative scenario of continuous condition changes (e.g., database: sunny to rainy, query: sunny to cloudy), the thesis first investigates the qualitative and quantitative impact on the performance of image descriptors. It then proposes and evaluates four unsupervised learning methods, including our novel clustering-based descriptor standardization method K-STD and three PCA-based methods from the literature. To address the high computational effort of descriptor comparisons during place recognition, our novel method EPR for efficient place recognition is proposed. Given a query descriptor, EPR uses sequence information and intra-database similarities to identify nearly all matching descriptors in the database. For a structured combination of several sources of additional knowledge in a single graph, the thesis presents our novel graphical framework for place recognition. After the minimization of the graph's error with our proposed ICM-based optimization, the place recognition performance can be significantly improved. For an extensive experimental evaluation of all methods in this thesis and beyond, a benchmark for visual place recognition in changing environments is presented, which is composed of six datasets with thirty sequence combinations.

Superpixels are the results of an image oversegmentation. They are an established intermediate level image representation and used for various applications including object detection, 3d reconstruction and semantic segmentation. While there are various approaches to create such segmentations, there is a lack of knowledge about their properties. In particular, there are contradicting results published in the literature. This thesis identifies segmentation quality, stability, compactness and runtime to be important properties of superpixel segmentation algorithms. While for some of these properties there are established evaluation methodologies available, this is not the case for segmentation stability and compactness. Therefore, this thesis presents two novel metrics for their evaluation based on ground truth optical flow. These two metrics are used together with other novel and existing measures to create a standardized benchmark for superpixel algorithms. This benchmark is used for extensive comparison of available algorithms. The evaluation results motivate two novel segmentation algorithms that better balance trade-offs of existing algorithms: The proposed Preemptive SLIC algorithm incorporates a local preemption criterion in the established SLIC algorithm and saves about 80 % of the runtime. The proposed Compact Watershed algorithm combines Seeded Watershed segmentation with compactness constraints to create regularly shaped, compact superpixels at the even higher speed of the plain watershed transformation. Operating autonomous systems over the course of days, weeks or months, based on visual navigation, requires repeated recognition of places despite severe appearance changes as they are for example induced by illumination changes, day-night cycles, changing weather or seasons - a severe problem for existing methods. Therefore, the second part of this thesis presents two novel approaches that incorporate superpixel segmentations in place recognition in changing environments. The first novel approach is the learning of systematic appearance changes. Instead of matching images between, for example, summer and winter directly, an additional prediction step is proposed. Based on superpixel vocabularies, a predicted image is generated that shows, how the summer scene could look like in winter or vice versa. The presented results show that, if certain assumptions on the appearance changes and the available training data are met, existing holistic place recognition approaches can benefit from this additional prediction step. Holistic approaches to place recognition are known to fail in presence of viewpoint changes. Therefore, this thesis presents a new place recognition system based on local landmarks and Star-Hough. Star-Hough is a novel approach to incorporate the spatial arrangement of local image features in the computation of image similarities. It is based on star graph models and Hough voting and particularly suited for local features with low spatial precision and high outlier rates as they are expected in the presence of appearance changes. The novel landmarks are a combination of local region detectors and descriptors based on convolutional neural networks. This thesis presents and evaluates several new approaches to incorporate superpixel segmentations in local region detection. While the proposed system can be used with different types of local regions, in particular the combination with regions obtained from the novel multiscale superpixel grid shows to perform superior to the state of the art methods - a promising basis for practical applications.

Probabilistic models of decision making under various forms of uncertainty have been applied in recent years to numerous behavioral and model-based fMRI studies. These studies were highly successful in enabling a better understanding of behavior and delineating the functional properties of brain areas involved in decision making under uncertainty. However, as different studies considered different models of decision making under uncertainty, it is unclear which of these computational models provides the best account of the observed behavioral and neuroimaging data. This is an important issue, as not performing model comparison may tempt researchers to over-interpret results based on a single model. Here we describe how in practice one can compare different behavioral models and test the accuracy of model comparison and parameter estimation of Bayesian and maximum-likelihood based methods. We focus our analysis on two well-established hierarchical probabilistic models that aim at capturing the evolution of beliefs in changing environments: Hierarchical Gaussian Filters and Change Point Models. To our knowledge, these two, well-established models have never been compared on the same data. We demonstrate, using simulated behavioral experiments, that one can accurately disambiguate between these two models, and accurately infer free model parameters and hidden belief trajectories (e.g., posterior expectations, posterior uncertainties, and prediction errors) even when using noisy and highly correlated behavioral measurements. Importantly, we found several advantages of Bayesian inference and Bayesian model comparison compared to often-used Maximum-Likelihood schemes combined with the Bayesian Information Criterion. These results stress the relevance of Bayesian data analysis for model-based neuroimaging studies that investigate human decision making under uncertainty.

Probabilistic models of decision making under various forms of uncertainty have been applied in recent years to numerous behavioral and model-based fMRI studies. These studies were highly successful in enabling a better understanding of behavior and delineating the functional properties of brain areas involved in decision making under uncertainty. However, as different studies considered different models of decision making under uncertainty, it is unclear which of these computational models provides the best account of the observed behavioral and neuroimaging data. This is an important issue, as not performing model comparison may tempt researchers to over-interpret results based on a single model. Here we describe how in practice one can compare different behavioral models and test the accuracy of model comparison and parameter estimation of Bayesian and maximum-likelihood based methods. We focus our analysis on two well-established hierarchical probabilistic models that aim at capturing the evolution of beliefs in changing environments: Hierarchical Gaussian Filters and Change Point Models. To our knowledge, these two, well-established models have never been compared on the same data. We demonstrate, using simulated behavioral experiments, that one can accurately disambiguate between these two models, and accurately infer free model parameters and hidden belief trajectories (e.g., posterior expectations, posterior uncertainties, and prediction errors) even when using noisy and highly correlated behavioral measurements. Importantly, we found several advantages of Bayesian inference and Bayesian model comparison compared to often-used Maximum-Likelihood schemes combined with the Bayesian Information Criterion. These results stress the relevance of Bayesian data analysis for model-based neuroimaging studies that investigate human decision making under uncertainty.