Tanto as inovações como o conhecimento desempenham um papel fundamental no atual cenário econômico e organizacional. Por outro lado, incertezas e turbulências, que podem estar associadas a processos e mudanças nestes cenários, emitem sinais, o que, no âmbito organizacional, denota a necessidade de monitoramento do ambiente competitivo. Os sinais, ainda que fracos e uma vez identificados representam estímulos externos que, associados ao conhecimento fomentam a inovação e, desta forma, podem ser considerados como um dos antecedentes da inovação. Segundo Arboniés (2009), os sinais fracos permitem a criação individual a partir da associação de diferentes sinais entre si e ao conhecimento tácito detido por um grupo de indivíduos. Esse processo denominado de rotinas criativas amplia o campo de alternativas e pode antecipar ameaças e oportunidades, a partir da interpretação criativa de sinais fracos e da concepção de rotinas para o seu processamento. Assim, este trabalho se propôs a estudar o conhecimento como um antecedente da inovação e como resultante do monitoramento externo. O foco estava no papel dos sinais fracos, em seu processamento por meio de rotinas criativas e em sua influência no desempenho em inovação. O objetivo foi então o de analisar as práticas de rotinas criativas para o processamento de sinais fracos e o desempenho em inovação. O método de pesquisa utilizado foi o descritivo exploratório, com um estudo de caso realizado nas empresas do Grupo Alfa. Os resultados indicaram que as empresas que possuem rotinas criativas apresentam desempenho superior em inovação. / Submitted by Marcelo Teixeira (mvteixeira@ucs.br) on 2014-04-30T13:20:50Z No. of bitstreams: 1 Dissertacao Jairo Moran C. Ribeiro.pdf: 2844874 bytes, checksum: 6449394bd3c6eb42842ed08f08c62748 (MD5) / Made available in DSpace on 2014-04-30T13:20:50Z (GMT). No. of bitstreams: 1 Dissertacao Jairo Moran C. Ribeiro.pdf: 2844874 bytes, checksum: 6449394bd3c6eb42842ed08f08c62748 (MD5) / As innovations as knowledge show a main role in the organizational economic scenery nowadays. Furthermore uncertainties and turbulence may be associated with changes in these processes and sceneries, emitting signals and within the organizational context indicate the need of monitoring the competitive environment. These signals still so weak and once a time identified represent the external stimuli which associated to the knowhow can feed, and this way are considered like a background of the innovation. According Arboniés (2009), weak signal allow an individual creation from the association in different signals among theirselves and a tacit knowledge held by a group of individuals. This process called creative routines broadens the alternatives and can anticipate threats and opportunities, from the creative interpretation of weak signals and designing routines for processing. Thus, this study aimed to analyze the knowledge as a background of innovation and as a result of external monitoring. The focus was on the role of weak signals in their processing through creative routines and their influence on innovation performance. Then the goal was to analyse the practice of creative routines for a processing of weak signs and performance in innovation. The method used was the descriptive and exploratory with a case study from Alpha Group Companies. The outcomes indicate that the enterprises that have creative routines also show a superior performance in innovation.

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This study investigates Audio over IP. A stress test was used to see what impact asymmetric latency had on the audio signal in a closed network. The study was constructed into two parts. The first part is the stress test where two AoIP solutions were tested. The two solutions where exposed in two forms of asymmetric latency. First a fixed value was used, next, a custom script was used to simulate changing values of asymmetric latency. The second part of this study involved interviews that where conducted with representatives from the audio industry that are working with audio over IP on a dayto-day usage. The goal for these interviews was to figure out what knowledge the audio industry had about asymmetric latency, if the industry had experienced problems related to latency and what general knowledge the industry has about networks. It was found in the interviews that the limitation in AoIP isn’t the technology in itself but rather missing knowledge with the people that are using the systems.

In this bachelor thesis, the possiblity to correct for room acousticsbased on frequency analysis is studied. A software to calculate transferfunctions online was constructed and tested. This was done using a ver-sion of the Maximum Length Sequence method, which is a method thatrequires long sequences for rooms with long reverberation. During theproject, it was noted that zero padding the sequences improved the ac-curacy greatly, it was also noted that the length of the zero pad aectedthe results. The software was tested both in computer simulations andin practice. While testing in practice, it was noted that the system haslimitations on which rooms it would work in. All testsignals were recordedand afterwards, compared to the original recording. The constructed soft-ware showed, that it is possible to correct for unknown transfer functionsusing only frequency analysis, to some extent. Further, it does correct forthe room's transfer function, but it is dicult to say if it this is valid forall rooms and transfer functions.

This dissertation focuses on two specific problems related to the design of parametric signal classifiers: dimensionality reduction to overcome the curse of dimensionality and information fusion to improve classification by exploiting complementary information from multiple sensors or multiple classifiers. Dimensionality reduction is achieved by introducing a strategy to rank and select a subset of principal component transform (PCT) coefficients that carry the most useful discriminatory information. The criteria considered for ranking transform coefficients include magnitude, variance, inter-class separation, and classification accuracies of individual transform coefficients. The ranking strategy not only facilitates overcoming the dimensionality curse for multivariate classifier implementation but also provides a means to further select, out of a rank-ordered set, a smaller set of features that give the best classification accuracies. Because the class-conditional densities of transform feature vectors are often assumed to be multivariate Gaussian, the dimensionality reduction strategy focuses on overcoming the specific problems encountered in the design of practical multivariate Gaussian classifiers using transform feature vectors. Through experiments with event related potentials (ERPs) and ear pressure signals, it is shown that the dimension of the feature space can be decreased quite significantly by means of the feature ranking and selection strategy. Furthermore, the resulting Gaussian classifiers yield higher classification accuracies than those reported in previous classification studies on the same signal sets. Amongst the four feature selection criteria, Gaussian classifiers using the maximum magnitude and maximum variance selection criteria gave the best classification accuracies across the two sets of classification experiments. For the multisensor case, dimensionality reduction is achieved by introducing a spatio-temporal array model to observe the signals across channels and time, simultaneously. A two-step process which uses the Kolmogrov-Smirnov test and the Lilliefors test is formulated to select the array elements which have different Gaussian densities across all signal categories. Selecting spatio-temporal elements that fit the assumed model and also statistically differ across the signal categories not only decreases the dimensionality significantly but also ensures high classification accuracies. The selection is dynamic in the sense that selecting spatio-temporal array elements corresponds to selecting samples of different sensors at different time-instants. Each selected array element is classified using a univariate Gaussian classifier and the resulting decisions are fused into a decision fusion vector which is classified using a discrete Bayes classifier. The application of the resulting dynamic channel selection-based classification strategy is demonstrated by designing and testing classifiers for multi-channel ERPs and it is shown that strategy yields high classification accuracies. Most noteworthy of the two dimensionality reduction strategies is the fact that the multivariate Gaussian signal classifiers developed can be implemented without having to collect a prohibitively large number of training signals simply to satisfy the dimensionality conditions. Consequently, the classification strategies can be beneficial for designing personalized human-machine-interface (HMI) signal classifiers for individuals from whom only a limited number of training signals can reliably be collected due to severe disabilities. The information fusion strategy introduced is aimed at improving the performance of signal classifiers by combining signals from multiple sensors or by combining decisions of multiple classifiers. Fusion classifiers with diverse components (classifiers or data sets) outperform those with less diverse components. Determining component diversity, therefore, is of the utmost importance in the design of fusion classifiers which are often employed in clinical diagnostic and numerous other pattern recognition problems. A new pairwise diversity-based ranking strategy is introduced to select a subset of ensemble components, which when combined, will be more diverse than any other component subset of the same size. The strategy is unified in the sense that the components can be either polychotomous classifiers or polychotomous data sets. Classifier fusion and data fusion systems are formulated based on the diversity selection strategy and the application of the two fusion strategies are demonstrated through the classification of multi-channel ERPs. From the results it is concluded that data fusion outperforms classifier fusion. It is also shown that the diversity-based data fusion system outperforms the system using randomly selected data components. Furthermore, it is demonstrated that the combination of data components that yield the best performance, in a relative sense, can be determined through the diversity selection strategy.

ABSTRACT The thesis called Health and Social Impacts of Human and Dog Co-existence is a paper describing the development of a human and a dog relationship since old times until present. It deals with the origin of a dog and describes the development of understanding between a human and a dog, which lasts up to the present day. The paper offers an integrated survey on the ways the dogs are used at present, especially in health and social areas. It informs the readers on the dog use possibilities, the care for dogs, and also the principles of communication, which enable quality and peaceful life of a human and a dog. The first objective was to find out what is the respondents´ knowledge on the dog use possibilities in the society. This objective was fulfilled and the hypothesis was proved. Respondents do not know even a half of possible dog use in co-existence with people. The second objective was to find out how respondents perceive the presence of dogs in their surroundings in relation to children. The objective was also fulfilled, however, the hypothesis that more than 75 per cent of respondents are careful during the contact of a child with a dog, was disproved. Quite a high percentage of people nderestimate the possible risk during the contact of a child with a dog. The third objective was focused on the awareness of respondents of the dog body signals. The hypothesis was proved in this case and out of the results it is evident that the people lack information on the signals sent by dogs. For finding out the needed data the questionnaire research was used. The questionnaire was composed of 24 questions and handed out to 350 respondents. The result of the research was the proving of three above mentioned hypotheses. One of them was disproved, the rest was proved. The awareness of respondents is not high. 44 per cent of owners are threatened by the risk of wound caused by their own dog. Everything is the result of insufficient education in the area. I see preventive programmes focused on the principles of proper co-existence of a human and a dog, which start in kindergarten, as a possibility to lower the risk of wounds or bites caused by dogs.

xi, 38 p. : ill. (some col.) A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / A critical question for developmental biology is the mechanism by which cells make fate decisions. In the hematopoietic system, stem cells differentiate into several different cell types, but the mechanisms that affect this process are incompletely known. Understanding these mechanisms is important because abnormal regulation of hematopoiesis can result in disease. STAT1 protein plays crucial roles in mediating innate immunity by transducing interferon signals, but recent results have also related STAT1 to hematopoietic cell differentiation. Here we cloned a previously uncharacterized zebrafish co-ortholog of the human STAT1 gene we call stat1b and investigated the functions of two zebrafish Stat1 proteins in hematopoiesis. The advantage of the zebrafish model is that, due to a whole genome duplication (WGD), some human genes have two co-orthologs in zebrafish. During evolution, co-orthologs have retained or acquired similar, complimentary, or new functions. Both stat1a and stat1b encode all four characteristic domains of the human STAT1 protein. Phylogenetic and conserved synteny analyses showed that stat1b and stat1a arose as duplicates in the teleost genome duplication event, and these analyses clarified the historical origin of the entire vertebrate STAT gene family. RT-PCR demonstrated maternal expression of both stat1a and stat1b . Expression of stat1b, but not stat1a, was detected in hematopoietic domains of embryos by in situ hybridization. Morpholino knockdown of stat1b , but not stat1a, mRNA expression resulted in a decrease in expression of the myeloid cell marker genes spi and mpx and an increase in expression of the hematopoietic progenitor marker gene scl and the erythrocyte marker gene gatal. These results show that in zebrafish, Stat1b protein functions in the commitment of hematopoietic cells to a myeloid cell fate. / Committee in charge: William Cresko, Chairperson, Biology; John Postlethwait, Advisor, Biology; Judith Eisen, Member, Biology; Jan Spitsbergen, Member, Not from U of O; J. Andrew Berglund, Outside Member, Chemistry

abstract: Monitoring vital physiological signals, such as heart rate, blood pressure and breathing pattern, are basic requirements in the diagnosis and management of various diseases. Traditionally, these signals are measured only in hospital and clinical settings. An important recent trend is the development of portable devices for tracking these physiological signals non-invasively by using optical methods. These portable devices, when combined with cell phones, tablets or other mobile devices, provide a new opportunity for everyone to monitor one’s vital signs out of clinic. This thesis work develops camera-based systems and algorithms to monitor several physiological waveforms and parameters, without having to bring the sensors in contact with a subject. Based on skin color change, photoplethysmogram (PPG) waveform is recorded, from which heart rate and pulse transit time are obtained. Using a dual-wavelength illumination and triggered camera control system, blood oxygen saturation level is captured. By monitoring shoulder movement using differential imaging processing method, respiratory information is acquired, including breathing rate and breathing volume. Ballistocardiogram (BCG) is obtained based on facial feature detection and motion tracking. Blood pressure is further calculated from simultaneously recorded PPG and BCG, based on the time difference between these two waveforms. The developed methods have been validated by comparisons against reference devices and through pilot studies. All of the aforementioned measurements are conducted without any physical contact between sensors and subjects. The work presented herein provides alternative solutions to track one’s health and wellness under normal living condition. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016

Quality signalling in motion picture markets is hardly a new topic. It has been covered by many researchers over the years. However, most of the previous studies focused on quality signals in interactions between moviemakers and moviegoers. This study employs a more holistic approach as the author attempts to evaluate effects of quality signals throughout different stages of movies’ life cycle. The author has identified three audiences that movies are presented to; and, each group of audience generates a quality signal for the next audience. Based on the feedback from test audiences, moviemakers decide on when to show movies to professional critics and when to allow them to publish their reviews. Interpretation of these timelines become quality signals for the professional critics who interpret shorter time slot for review publication as a signal of the low quality of the movie and vice versa. Professional critics write their reviews which when published on review aggregators become quality signals for the moviegoers. Reviews generated by the initial moviegoers are interpreted by the moviegoers who intend to watch movies at a later stage. All three assumptions are operationalised and evaluated in a series of linear regression tests in this research on a sample containing 130 out of 134 widely released movies in the US and Canada domestic market in 2017. All of the abovementioned quality signals found to be significant as they could explain at least 40 % of the variance of respective response variables.

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