The role of culture in international students' image formation: the emergence of expected and perceived university image

Tämän tutkimuksen tavoitteena oli selvittää, vaikuttaako kansainvälisen opiskelijan kulttuuritausta opiskelijan odotetun ja koetun yliopistoimagon muodostumiseen. Jotta kulttuurin vaikutuksia yliopistoimagoon voitiin tutkia, tutkimuksessa tunnistettiin yliopistoimagon muodostumiseen oleellisesti vaikuttavat tekijät. Kulttuurin roolia organisaation imagon muodostumisessa ei ole tutkittu aiemmissa tieteellisissä julkaisuissa. Näin ollen tämän tutkimuksen voidaan katsoa edistäneen nykyistä imagotutkimusta. Tutkimuksen kohdeyliopistona oli Lappeenrannan teknillinen yliopisto (LTY). Tutkimuksen empiirinen osa toteutettiin kvantitatiivisena Internet - pohjaisena kyselytutkimuksena tilastollisen analyysin menetelmin. Otos (N=179) koostui kaikista Lappeenrannan teknillisessä yliopistossa lukuvuonna 2005-2006 opiskelleista kansainvälisistä opiskelijoista. Kyselyyn vastasi 68,7 % opiskelijoista. Johtopäätöksenä voidaan todeta, että kulttuurilla ei ole merkittävää vaikutusta yliopistoimagon muodostumiseen. Tutkimuksessa saatiin selville, että yliopiston Internet-sivujen laatu vaikuttaa positiivisesti odotetun yliopistoimagon muodostumiseen, kun taas koettuun yliopistoimagoon vaikuttavat positiivisesti odotettu yliopistoimago, pedagoginen laatu sekä opetusympäristö. Markkinoinnin näkökulmasta tulokset voidaan vetää yhteen toteamalla, että yliopistojen ei tarvitsisi räätälöidä tutkimuksessa tunnistettuja imagoon vaikuttavia tekijöitä eri kulttuureistatulevia opiskelijoita varten.

University Image vs. University Identity: Congruence between Expectations and Experience

The aim of this thesis was to examine congruencies between university identity and university images of prospective and current students. Therefore, factors essentially influencing on expected and experienced university images were identified. Providing an understanding on the differences in the formation of both concepts allowed the analysis of potential incongruities between a university’s identity and the perceptions its students hold. The study was conducted in July and August 2013 at Lappeenranta University of Technology by means of a web-based research survey. The sample consisted of 160 international Master’s degree students who were admitted in 2011, 2012 and 2013. Descriptive and multivariate statistical analysis methods were used to process the data. The results of the study indicated statistically significant incongruities between the case university’s identity and its students’ images. Further, the expected and experienced university images showed incongruities to each other. Deviations were additionally detected to be dependent on the students’ home regions. All in all, there is potential for an improvement of the students’ experiences resulting from a low perception of the student’s preparation for future job life.

New Distance Transforms for Gray Level Image Compression

This thesis deals with distance transforms which are a fundamental issue in image processing and computer vision. In this thesis, two new distance transforms for gray level images are presented. As a new application for distance transforms, they are applied to gray level image compression. The new distance transforms are both new extensions of the well known distance transform algorithm developed by Rosenfeld, Pfaltz and Lay. With some modification their algorithm which calculates a distance transform on binary images with a chosen kernel has been made to calculate a chessboard like distance transform with integer numbers (DTOCS) and a real value distance transform (EDTOCS) on gray level images. Both distance transforms, the DTOCS and EDTOCS, require only two passes over the graylevel image and are extremely simple to implement. Only two image buffers are needed: The original gray level image and the binary image which defines the region(s) of calculation. No other image buffers are needed even if more than one iteration round is performed. For large neighborhoods and complicated images the two pass distance algorithm has to be applied to the image more than once, typically 3 10 times. Different types of kernels can be adopted. It is important to notice that no other existing transform calculates the same kind of distance map as the DTOCS. All the other gray weighted distance function, GRAYMAT etc. algorithms find the minimum path joining two points by the smallest sum of gray levels or weighting the distance values directly by the gray levels in some manner. The DTOCS does not weight them that way. The DTOCS gives a weighted version of the chessboard distance map. The weights are not constant, but gray value differences of the original image. The difference between the DTOCS map and other distance transforms for gray level images is shown. The difference between the DTOCS and EDTOCS is that the EDTOCS calculates these gray level differences in a different way. It propagates local Euclidean distances inside a kernel. Analytical derivations of some results concerning the DTOCS and the EDTOCS are presented. Commonly distance transforms are used for feature extraction in pattern recognition and learning. Their use in image compression is very rare. This thesis introduces a new application area for distance transforms. Three new image compression algorithms based on the DTOCS and one based on the EDTOCS are presented. Control points, i.e. points that are considered fundamental for the reconstruction of the image, are selected from the gray level image using the DTOCS and the EDTOCS. The first group of methods select the maximas of the distance image to new control points and the second group of methods compare the DTOCS distance to binary image chessboard distance. The effect of applying threshold masks of different sizes along the threshold boundaries is studied. The time complexity of the compression algorithms is analyzed both analytically and experimentally. It is shown that the time complexity of the algorithms is independent of the number of control points, i.e. the compression ratio. Also a new morphological image decompression scheme is presented, the 8 kernels' method. Several decompressed images are presented. The best results are obtained using the Delaunay triangulation. The obtained image quality equals that of the DCT images with a 4 x 4

Computational Techniques for Spectral Image Analysis

Multispectral images are becoming more common in the field of remote sensing, computer vision, and industrial applications. Due to the high accuracy of the multispectral information, it can be used as an important quality factor in the inspection of industrial products. Recently, the development on multispectral imaging systems and the computational analysis on the multispectral images have been the focus of a growing interest. In this thesis, three areas of multispectral image analysis are considered. First, a method for analyzing multispectral textured images was developed. The method is based on a spectral cooccurrence matrix, which contains information of the joint distribution of spectral classes in a spectral domain. Next, a procedure for estimating the illumination spectrum of the color images was developed. Proposed method can be used, for example, in color constancy, color correction, and in the content based search from color image databases. Finally, color filters for the optical pattern recognition were designed, and a prototype of a spectral vision system was constructed. The spectral vision system can be used to acquire a low dimensional component image set for the two dimensional spectral image reconstruction. The data obtained by the spectral vision system is small and therefore convenient for storing and transmitting a spectral image.

Color ad spectral image assessment using novel quality and fidelity techniques

The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.

Eye Fundus Image Analysis for Automatic Detection of Diabetic Retinopathy

Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.

Utilization of Particle Image velocimetry in PPOOLEX condensation experiments

Particle Image Velocimetry, PIV, is an optical measuring technique to obtain velocity information of a flow in interest. With PIV it is possible to achieve two or three dimensional velocity vector fields from a measurement area instead of a single point in a flow. Measured flow can be either in liquid or in gas form. PIV is nowadays widely applied to flow field studies. The need for PIV is to obtain validation data for Computational Fluid Dynamics calculation programs that has been used to model blow down experiments in PPOOLEX test facility in the Lappeenranta University of Technology. In this thesis PIV and its theoretical background are presented. All the subsystems that can be considered to be part of a PIV system are presented as well with detail. Emphasis is also put to the mathematics behind the image evaluation. The work also included selection and successful testing of a PIV system, as well as the planning of the installation to the PPOOLEX facility. Already in the preliminary testing PIV was found to be good addition to the measuring equipment for Nuclear Safety Research Unit of LUT. The installation to PPOOLEX facility was successful even though there were many restrictions considering it. All parts of the PIV system worked and they were found out to be appropriate for the planned use. Results and observations presented in this thesis are a good background to further PIV use.

Real-time Image-based RGB-D Camera Motion Tracking and Environment Mapping

In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection

The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.

European luxury brands made in China: the effect of low-cost country manufacturing on brand image and purchase decisions

European luxury brands have an image of manufacturing their products in the same country where the brands originate. However, in the past years many luxury brands have shifted their manufacturing to countries outside Europe. China is now a common manufacturing country for European luxury brands despite the country’s poor image as a manufacturer. Chinese manufacturing is often associated with bad quality, bad labour conditions, mass production, and counterfeits. The image of China does not quite match the image luxury brands enjoy including characteristics such as high end quality, craftsmanship, details, design, or premium price. A negatively perceived country-of-manufacture may have an effect on a brand’s image and consumers’ purchase decisions. This thesis is focused on European luxury brands manufacturing in China, and how this effects the brand image and purchase decisions among luxury consumers. The empirical part of this thesis is based on focus group research, which is a popular method in the field of qualitative research. The main focus group is female luxury consumers in Finland. This main group has been divided into three categories: 1) the university students, 2) the young career women, 3) the experienced luxury consumers. This categorization has been done based on their different stages in luxury consumption. All in all, the empirical research consisted of 11 interviews and 29 participants. The main contribution of this thesis was that there is a difference between the opinions of the younger groups (university students and young career women) and the experienced luxury consumers when discussing the effect of country-of-manufacture on brand image and purchase decisions of luxury brands. The younger participants thought that manufacturing luxury products in China might affect the brand image, but their purchase decisions would not be that much affected by the country-of-origin. The experienced luxury consumers had quite a different view on the country-of-origin of luxury brands – they found it an important decisive factor prior making purchases. The majority of experienced luxury consumers would not buy luxury products made in China, and they would always check where these products are made in.

Vision, image, record : a cultivation of the visual field

I den första delen av den här avhandlingen presenteras en bildens genealogi. Den skildrar hur begreppen för bilden, seendet och jaget utvecklades i relation till varandra i en specifik vetenskaplig och filosofisk kontext. Berättelsen sträcker sig från den tidiga renässansen och det perspektivistiska måleriet, till fotografiets födelse och positivismen. Den här utvecklingen medförde en form av reduktionism i vilken jagets roll – betydelsen av den mänskliga psykologin, vårt omdöme, vår uppmärksamhet och vår vilja – blev förbisedd. Inom den här tanketraditionen uppstod en förskjutning, från en förståelse av bilden som en representation av det tredimensionella rummet på en tvådimensionell yta, till en uppfattning om bilden som en genomskinlig ruta, ett fönster ut mot världen. Idén om avbildningen som en neutral ”blick från ingenstans” kom att förstärka en skeptisk hållning till kommunikation, dialog och vittnesmål och därmed även undergräva vår tillit till varandra och följaktligen vår tillit till oss själva. I den andra delen erbjuder författaren ett alternativ till den tanketradition som behandlas i den första delen. Det som blev förbisett i uppfattningen om en blick från ingenstans var att bilden är ett hjälpmedel då vi bearbetar vårt synfält. Bilden hjälper oss att dela vår syn på saker. Genom den här uppgiften av att dela blir bilden riktningsgivande i våra försök att orientera oss i världen. Jag kan stå bredvid en annan människa och se vad hon ser, men jag vet inte nödvändigtvis hur hon uppfattar det vi ser. Bilden lägger till ett led i det här förhållandet eftersom den inte enbart visar vad den andra ser. När bilden fungerar som den skall visar den också hur den andra ser och på det här sättet blir bilden verksam. Den föreliggande avhandlingen kombinerar epistemologi med vetenskapshistoria och visuella kulturstudier, men dess huvudintresse är filosofiskt. Den befattar sig med filosofiska missförstånd angående avbildning som en mimetisk konstform, kunskap som domesticering och varseblivning som mottagning av data. ------------------------------------------------------ Tämän väitöskirjan ensimmäinen osa selvittää kuvakäsitteen genealogiaa. Se havainnollistaa miten kuvan, näkemisen ja minän käsitteet kehittyivät suhteessa toisiinsa. Kertomus ulottuu varhaisesta renessanssista ja perspektivistisestä maalaustaiteesta, positivismin aikakauteen ja valokuvan syntyyn. Tämä kehitys toi mukanaan reduktionismin jossa minän rooli – ihmisen psykologian merkitys, meidän arviointikyky, meidän huomiokyky sekä meidän tahtomme – vaipui unohduksiin. Ajatusmaailmassa tapahtui siirtymä, kuvan merkitys vaihtui käsityksestä jossa se on kolmiulotteisen tilan representaatio kaksiulotteisella pinnalla, käsitykseen jossa kuva on läpinäkyvä ruutu, ikkuna kohti maailmaa. Ajatus kuvasta neutraalin näkökulman kantajana vahvisti skeptistä suhtautumista kommunikaatiota, dialogisuutta ja subjektiivisuutta kohtaan. Tämä skeptisyys ilmentyi myös vahvana epäluottamuksena ihmiskeskeisyyttä ja toiseutta kohtaan. Toisessa osassa tekijä tarjoaa vaihtoehdon tälle skeptiselle ajatusmaailmalle jota tarkastellaan ensimmäisessä osassa. Kuva on myös väline joka auttaa meitä jäsentämään meidän näkökenttäämme. Se auttaa meitä jakamaan meidän käsityksiä toistemme kanssa. Tämä näkemisen jakamisen käytäntö on kuvan keskeinen tehtävä. Voin seistä toisen ihmisen vieressä ja nähdä samat asiat kuin hän, mutta en välttämättä ymmärrä miten hän näkee nämä asiat. Kuva lisää jotain olennaista tähän suhteeseen. Kun kuva toimii niin kun sen kuuluu toimia, se näyttää myös miten toinen näkee, tällä tavalla kuvasta tulee välittäjä. Tämä väitöskirja yhdistää epistemologiaa, tieteen historiaa ja visuaalisen kulttuurin tutkimusta, mutta sen pääasiallinen tavoite on filosofinen. Se käsittelee filosofisia väärinkäsityksiä koskien kuvan eideettisyyttä.

Internal Employer Brand: The factors affecting the formation of internal employer image

The purpose of this study is to identify the factors affecting the formation of employer image and attractiveness in the minds of an organization’s employees. Six employees from different backgrounds and business units within a larger organization are interviewed, and the results are compared in order to better understand the effect divergent variables have on the resulting factors. The theoretical background of the research is based on the study of the concept of employer branding, an organization’s effort in affecting the employer image it projects and attractiveness perceived by the employees and applicants. The results of the study reveal how immaterial factors, primarily related to self-actualization and social relationships, often took precedence over material ones, so long as the material factors, such as salary and work equipment, were at least on a minimum level acceptable to the employee. As such, focusing on these immaterial factors when forming an employer brand strategy is expected to yield larger benefits in form of employer attractiveness.

Spectral retinal image processing and analysis for ophthalmology

Diabetic retinopathy, age-related macular degeneration and glaucoma are the leading causes of blindness worldwide. Automatic methods for diagnosis exist, but their performance is limited by the quality of the data. Spectral retinal images provide a significantly better representation of the colour information than common grayscale or red-green-blue retinal imaging, having the potential to improve the performance of automatic diagnosis methods. This work studies the image processing techniques required for composing spectral retinal images with accurate reflection spectra, including wavelength channel image registration, spectral and spatial calibration, illumination correction, and the estimation of depth information from image disparities. The composition of a spectral retinal image database of patients with diabetic retinopathy is described. The database includes gold standards for a number of pathologies and retinal structures, marked by two expert ophthalmologists. The diagnostic applications of the reflectance spectra are studied using supervised classifiers for lesion detection. In addition, inversion of a model of light transport is used to estimate histological parameters from the reflectance spectra. Experimental results suggest that the methods for composing, calibrating and postprocessing spectral images presented in this work can be used to improve the quality of the spectral data. The experiments on the direct and indirect use of the data show the diagnostic potential of spectral retinal data over standard retinal images. The use of spectral data could improve automatic and semi-automated diagnostics for the screening of retinal diseases, for the quantitative detection of retinal changes for follow-up, clinically relevant end-points for clinical studies and development of new therapeutic modalities.