Lihaan leikattu kauneus

Kirjallisuusarvostelu

Spare part business analysis and development

The purpose of this Thesis was to comprehensively analyze and develop the spare part business in Company Oy’s five biggest product groups by searching development issues related to single spare parts’ supply chains as well as the spare part business process, make implementation plans for them and implement the plans when possible. The items were classified based on special characteristics of spare parts and on their actual sales volumes. The created item classes were examined for finding improvement possibilities. Management strategies for classified items were suggested. Vendors and customers were analyzed for supporting the comprehensive supply network development work. The effectiveness of the current spare part business process was analyzed in co-operation with the spare part teams in three business unit locations. Several items were taken away from inventories as uselessly stocked items. Price list related to core items with one of the main product group’s core item manufacturer was suggested to be expanded in Town A. Refinement equipment seal item supply chain management was seen important to develop in Town B. A new internal business process model was created for minimizing and enhancing the internal business between Company’s business units. SAP inventory reports and several other features were suggested to be changed or developed. Also the SAP data material management was seen very important to be developed continuously. Many other development issues related to spare parts’ supply chains and the work done in the business process were found. The need for investigating the development possibilities deeper became very clear during the project.

Tutkijan toimintatila

Kirjallisuusarvostelu

Näkökulmia Sophie Elkanin elämään

Kirjallisuusarvostelu

"On annettava lampun palaa." : historiaa kirjoittavat naiset

Kirjallisuusarvostelu

"Yhä vieläkin Lotta Svärdistä, puhe syntyy toisinaan..."

Kirjallisuusarvostelu

Ansiokas synteesi Suomesta sodassa

Kirjallisuusarvostelu

Mennyt tulevaisuus

Kirjallisuusarvostelu

Bag-of-Features Approach to Unsupervised Visual Object Categorisation

The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.

Kosmeettisesta kirurgiasta ilman oikoteitä

Kirjallisuusarvostelu