Textilmarknaden blir allt mer utsatt för konkurrens. Företag måste idag vara duktiga på att erbjuda konsumenter något utöver det vanliga för att hålla sig kvar på marknaden. Det finns olika sätt för företag att konkurrera på och denna uppsats har som syfte att undersöka vilka egenskaper en påse skall ha för att ge kunden ett mervärde som därigenom kan bidra till ökad kundlojalitet. Fyra olika påsar från fyra olika företag har använts i uppsatsen och dessa är: Acne, Best of Brands, KappAhl och H&M. Intervjuer med kvinnor i åldrarna 20–30 år ligger till grund för resultatet. Resultatet av vår uppsats visar att påsen har en positiv inverkan på konsumenters attityder. Påsen bidrar till konsumenters helhetsintryck av butiken och respondenterna upplever sig som bättre kunder när de får en fin påse. Påsen ses som en statussymbol men också som ett marknadsföringsverktyg för varumärket. Solomons ABC-modell har använts för att skapa förståelse för hur olika attribut påverkar konsumentens köpbeteende. Vi skapade en illustration med de olika attributen på påsen vi valt att undersöka. Tillslut skapades en egen modell sammansatt av ABC-modellen och påsens attribut för att tydliggöra vad hos en påse som skapar en attityd hos konsumenten som kan leda till ökad kundlojalitet. / The textile market is more exposed to competition than ever. The companies need to communicate a comparative advantage in order to survive. There are several ways a company can compete and the intended purpose of this report is to examine which characteristics a bag should have in order to increase customer value and strengthen the customer loyalty. The report highlights the design of the bag, its attributes and elements making bags from certain companies of greater importance than others in reinforcing the customer loyalty. Four different bags from different companies have been used in our report. The selected companies were, Acne, Best of Brands, Kappahl & H&M. Interviews have been held with women in the ages20-30 years and are part of the result. The result of our report shows the great impact a bag has regarding consumer attitudes. The bag contributes to the customer’s overall impression of the brand and respondents consider themselves as a customer of greater importance when receiving an elegant bag. The bag is considered as a status symbol as well as a markting tool for the brand. The ABC-model of Solomon has been used to create an understanding of how different attributes of the bag affects the purchasing behaviour of the consumer. We created anillustration with the chosen attributes of the bag that were examined. Finally, we created ourown model with guidance of the ABC-model and the attributes of the bag. This were made to clarify what kind of attributes affecting the customer behaviour, which in turn drives thecustomer loyalty.

This study aimed to determine the potential of packaging to strengthen brand equity in female apparel retail stores. A field experiment was conducted in the Tshwane metropolitan - a key political, economic and urban area in South Africa - to investigate the potential of packaging to be acknowledged as an additional element of the marketing mix in terms of its influence on consumers’ perceptions of the service offering of retailers and their brand equity. The study was done in the context of an emerging economy, where international clothing brands have infiltrated the market and become widely accessible in recent years. The data was collected by using convenience sampling methods, and the self-completion of a structured questionnaire after respondents acted as mystery shoppers at a Single Brand Retailer (SBR) and a Department Store (DS) that carry the same footwear brand in a major shopping centre in this metropolitan. The SBR offers consumers a branded high quality canvas tote bag after purchase, whereas the DS offers a generic plastic bag irrespective of the type of purchase or the price paid. Willing females, all final year students at the University of Pretoria (n =103) were divided in two groups. Individuals visited the two retailers according to a schedule compiled by the researcher. One group visited the SBR first, followed by the DS. The other group did the task in the reverse order. Data analysis involved descriptive statistics, exploratory factor analysis, specifically Principle Component analysis using PROMAX and PROCRUSTES rotation for the two scales that investigated the service offering and brand equity respectively, Means, Standard deviations, Cronbach’s Alpha as well as paired and non-paired 2-tailed t-tests. This study confirmed the potential of secondary packaging as an independent element of the marketing mix in the branded clothing retail industry. The packaging construct dissociated it from the construct ‘Product’ as the literature suggests, which confirms that marketing elements adapt over time and that these changes have to be acknowledged in retail. Respondents generally had a less favourable instore experience in the DS compared to the SBR. The packaging format of SBR was also evaluated more favourably, which enhanced perceptions of the overall service offering. This suggests that respondents’ less favourable evaluation of the less prestigious packaging offered in the DS, is partly to blame for the lower overall evaluations of the service offering of the DS. Packaging also contributed/enhanced brand equity as consumers’ perceptions of the packaging formats – irrespective of whether it was a SBR or a DS – positively contributed to consumers’ perceptions of the brand equity of the retailers that they visited. The contribution of packaging towards brand equity was mostly more prominent than the contribution of other marketing elements such Advertising and Promotion. An order effect was noted. Respondents who visited the DS first, were significantly more impressed with the SBR. Those who went to the SBR first, seemed more forgiving and evaluated the service offering and the brand equity lower compared to the SBR but nevertheless evaluated it more favourably than the group that patronized the DS first. Packaging does not seem to relieve post purchase regret. Respondents were more regretful after their SBR experience. Several explanations may be used to explain this and future studies are envisaged to expand the findings. / Dissertation (MSc)--University of Pretoria, 2014. / gm2014 / Consumer Science / unrestricted

This thesis presents a framework for automatic recognition of human actions in uncontrolled, realistic video data such as movies, internet and surveillance videos. In this thesis, the human action recognition problem is solved from the perspective of local spatio-temporal feature and bag-of-features representation. The bag-of-features model only contains statistics of unordered low-level primitives, and any information concerning temporal ordering and spatial structure is lost. To address this issue, we proposed a novel multiscale local part model on the purpose of maintaining both structure information and ordering of local events for action recognition. The method includes both a coarse primitive level root feature covering event-content statistics and higher resolution overlapping part features incorporating local structure and temporal relationships. To extract the local spatio-temporal features, we investigated a random sampling strategy for efficient action recognition. We also introduced the idea of using very high sampling density for efficient and accurate classification. We further explored the potential of the method with the joint optimization of two constraints: the classification accuracy and its efficiency. On the performance side, we proposed a new local descriptor, called GBH, based on spatial and temporal gradients. It significantly improved the performance of the pure spatial gradient-based HOG descriptor on action recognition while preserving high computational efficiency. We have also shown that the performance of the state-of-the-art MBH descriptor can be improved with a discontinuity-preserving optical flow algorithm. In addition, a new method based on histogram intersection kernel was introduced to combine multiple channels of different descriptors. This method has the advantages of improving recognition accuracy with multiple descriptors and speeding up the classification process. On the efficiency side, we applied PCA to reduce the feature dimension which resulted in fast bag-of-features matching. We also evaluated the FLANN method on real-time action recognition. We conducted extensive experiments on real-world videos from challenging public action datasets. We showed that our methods achieved the state-of-the-art with real-time computational potential, thus highlighting the effectiveness and efficiency of the proposed methods.

京都大学 / 0048 / 新制・課程博士 / 博士(地球環境学) / 甲第22022号 / 地環博第186号 / 新制||地||96(附属図書館) / 京都大学大学院地球環境学舎地球環境学専攻 / (主査)准教授 岡田 直紀, 教授 舟川 晋也, 准教授 真常 仁志 / 学位規則第4条第1項該当 / Doctor of Global Environmental Studies / Kyoto University / DGAM

This dissertation focuses on the construction design of a sine pump. It particularly deals with loss minimisation and strives to solve problems relating to excessive wear of the scrapergate which separates suction and the delivery space. The first part of the dissertation describes a new construction variation of a sine pump and the second part deals with a more detailed study including optimisation of one variation.

This thesis deals with the EFB systems, its standards, types and modes of operation. It describes the design and implementation of an Apple iPad application, intended to be used as an EFB by the Czech general aviation pilots. The real utilization of such application allows for simplification of the preflight check and safe execution of flight while removing the usual load of paper documents from the cockpit. This is achieved through a SW im- plementation of operationally attractive functions. It could be for example: searching in regulations and pilot's handbooks, acquisition and viewing of meteorological informations and recent changes in air traffic, interactive calculation of important parameters or flight navigation.

This thesis covers design and practical realization of a tool for quick search in large image databases, containing from tens to hundreds of thousands photos, based on image similarity. The proposed technique uses various methods of descriptor extraction, creation of Bag of Words dictionaries and methods of storing image data in PostgreSQL database. Further, experiments with the implemented software were carried out to evaluate the search time effectivity and scaling possibilities of the design solution.

Purpose of this thesis is to design and implement a tool for automatic categorization of photos. The proposed tool is based on the Bag of Words classification method and it is realized as a plug-in for the XnView image viewer. The plug-in is able to classify a selected group of photos into predefined image categories. Subsequent notation of image categories is written directly into IPTC metadata of the picture as a keyword.

This work is focused on objects and scenes recognition using machine learning and computer vision tools. Before the solution of this problem has been studied basic phases of the machine learning concept and statistical models with accent on their division into discriminative and generative method. Further, the Bag-of-words method and its modification have been investigated and described. In the practical part of this work, the implementation of the Bag-of-words method with the SVM classifier was created in the Matlab environment and the model was tested on various sets of publicly available images.

Authorship identification is the field of classifying a given text by its author based on the assumption that authors exhibit unique writing styles. This thesis investigates the semantic shortcomings of the vector space model by constructing a semantic kernel created from WordNet which is evaluated on the problem of authorship attribution. A multiclass SVM classifier is constructed using the one-versus-all strategy and evaluated in terms of precision, recall, accuracy and F1 scores. Results show that the use of the semantic scores from WordNet degrades the performance compared to using a linear kernel. Experiments are run to identify the best feature engineering configurations, showing that removing stopwords has a positive effect on the financial dataset Reuters while the Kaggle dataset consisting of short extracts of horror stories benefit from keeping the stopwords.