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Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

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Different concentrations of basil essential oil (Ocimum basilicum L.) (0.19; 0.38; 0.75; 1.87; 3.75 and 6.00 mg.g-1) were evaluated in relation to their antioxidant activity using the DPPH● radical methodology. From the IC50 obtained data, the concentrations of 0.19; 0.38; 0.75; 1.87; 3.75; 6.00 and 12.00 mg.mL-1 were applied directly to the product and these were sensorially evaluated by the test of control difference. The concentrations related to the highest acceptability (0.19; 0.38 and 0.75 mg.g-1) were tested for antioxidant activity in the internal part of Italian type salami - during the processing and after 30 days of storage, in terms of lipid and protein oxidation. The oxidation of lipids was determined using the method of TBARS. The method of carbonyl compounds was employed for proteins oxidation. Five different formulations of salami were elaborated: blank (without the use of antioxidant); control (using sodium eritorbate as antioxidant); and adding 0.19; 0.38 and 0.75 mg.g-1 of basil essential oil. The product was kept between 25 ºC and 18 ºC and UR between 95% and 70%, for 28 days. Analyses were carried out on the processing day and after 2, 7, 14, 21 and 28 days, and also following 30 days of storage. The basil essential oil in vitro presented an antioxidant activity of IC50 12 mg.mL-1. In the internal part of the Italian type salami the commercial antioxidant (control) and the formulation containing 0.75 mg.g-1 of basil essential oil presented antioxidant activity in relation to the lipids, but not to the proteins - during processing and storage.

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The aim of the present study was to precool cauliflower using forced-air, vacuum and high and low flow hydro cooling methods. The weight of the precooled cauliflower heads (5000±5 g) was measured before they were placed in standard plastic crates. Cauliflower heads, whose initial temperature was 23.5 ± 0.5 ºC, were cooled until the temperature reached at 1 ºC. During the precooling process, time-dependent temperature and energy consumption were measured, and during vacuum precooling, the decreasing pressure values were recorded, and a curve of time-dependent pressure decrease (vacuum) was built. The most suitable cooling method to precool cauliflower in terms of cooling time and energy consumption was vacuum, followed by the high and low flow hydro and forced-air precooling methods, respectively. The highest weight loss was observed in the vacuum precooling method, followed by the forced-air method. However, there was an increase in the weight of the cauliflower heads in the high and low flow hydro precooling method. The best colour and hardness values were found in the vacuum precooling method. Among all methods tested, the most suitable method to precool cauliflower in terms of cooling and quality parameters was the vacuum precooling method.

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Cauliflower heads, which were precooled using four different methods including vacuum, forced-air, and high and low flow hydro precooling, were stored under controlled atmosphere and room conditions. Controlled atmosphere conditions (CA) were as follows: 1°C temperature, 90 ± 5% relative humidity, and 0:21 [(%CO2:%O2) – (0:21) control] atmosphere composition. Room conditions (RC) were: 22±1°C temperature and 55-60% humidity. Various quality parameters of the cauliflower heads were assessed during storage (days 0, 7, 14, 21, 28, and 35) under controlled atmosphere and room conditions (days 0, 5, and 10). During storage, weight loss, deterioration rate, overall sensory quality score, hardness, and colour (L, a, b, C and α) were evaluated. In the present study, the strength and quality parameters of cauliflower under CA and RC conditions were obtained. Vacuum precooling was found to be most suitable method before cauliflower was submitted to cold storage and sent to market. Furthermore, the storage of cauliflower without precooling resulted in a significant decrease in quality parameters.

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Erip.: Harper's New Monthly Magazine Vol. LXXXII. Februari, 1891. N:o CCCCLXXXIX.

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ABSTRACT Before the mid 1980s the World Bank conceived "nature" as something to be "conquered" and "environment" as a source of resources for "development". By the late 1980s the Bank incorporated norms of environmental sustainability and indigenous peoples' protection into its mandate, and other development-oriented IOs followed. This two-part paper describes how a fight over the Polonoroeste road project in the Brazilian Amazon - inside the Bank, between the Bank and NGOs supported by the US Congress, and between the Bank and the government of Brazil -helped to generate the far-reaching change of policy norms. The first part describes how the project was designed as an innovation in sustainable development in rainforests; and how it provoked a firestorm inside the Bank as it moved towards project approval.

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The aim of this Master’s thesis is to find a method for classifying spare part criticality in the case company. Several approaches exist for criticality classification of spare parts. The practical problem in this thesis is the lack of a generic analysis method for classifying spare parts of proprietary equipment of the case company. In order to find a classification method, a literature review of various analysis methods is required. The requirements of the case company also have to be recognized. This is achieved by consulting professionals in the company. The literature review states that the analytic hierarchy process (AHP) combined with decision tree models is a common method for classifying spare parts in academic literature. Most of the literature discusses spare part criticality in stock holding perspective. This is relevant perspective also for a customer orientated original equipment manufacturer (OEM), as the case company. A decision tree model is developed for classifying spare parts. The decision tree classifies spare parts into five criticality classes according to five criteria. The criteria are: safety risk, availability risk, functional criticality, predictability of failure and probability of failure. The criticality classes describe the level of criticality from non-critical to highly critical. The method is verified for classifying spare parts of a full deposit stripping machine. The classification can be utilized as a generic model for recognizing critical spare parts of other similar equipment, according to which spare part recommendations can be created. Purchase price of an item and equipment criticality were found to have no effect on spare part criticality in this context. Decision tree is recognized as the most suitable method for classifying spare part criticality in the company.

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The objective of this study was to find out how third party influencers can facilitate value-based selling in a network and how suppliers should aim to impact on these third party influencers to facilitate value-based selling. The study considers construction industry, selling the column connection solution and third party influencers. Third party influencers examined in this study were structural designers. The study also aims to find out structural designers’ value drivers and the differences between the market areas that this study related to. The theoretical part of the study focuses on two separate areas. The first part of the theory focuses on a value-based selling concept: what it is, what it requires and what are the main barriers for value-based selling. The second part of the theory examines value creation in networks. The present knowledge over value creation in networks and different network actors are presented. Project marketing is also discussed briefly because this study’s topic, which is highly related to project business. The results reveal structural designers’ value drivers considering the usage of the column connection solution and present ways how suppliers should aim to impact structural designers to facilitate value-based selling. The main result of the study indicates that third party influencers can have a positive impact on facilitating value-based selling. Structural designers are communicating more or less with all the salient actors in different project phases and they can act as sponsors to support the sales of Peikko’s column connection solution and promote solution to other actors involved to the project. This requires that structural designers can understand the actual benefits of how the solution can improve their and their customers’ business.