Image and value of product brand in industrial markets: Case Stora Enso Consumer Packaging Boards

TUTKIMUKSEN TAVOITTEET Tutkielman tavoitteena oli luoda ensin yleiskäsitys tuotemerkkimarkkinoinnin roolista teollisilla markkinoilla, sekä suhdemarkkinoinnin merkityksestä teollisessa merkkituotemarkkinoinnissa. Toisena oleellisena tavoitteena oli kuvata teoreettisesti merkkituoteidentiteetin rakenne teollisessa yrityksessä ja sen vaikutukset myyntihenkilöstöön, ja lisäksi haluttiin tutkia tuotemerkkien lisäarvoa sekä asiakkaalle että myyjälle. Identiteetti ja sen vaikutukset, erityisesti imago haluttiin tutkia myös empiirisesti. LÄHDEAINEISTO JA TUTKIMUSMENETELMÄT Tämän tutkielman teoreettinen osuus perustuu kirjallisuuteen, akateemisiin julkaisuihin ja aikaisempiin tutkimuksiin; keskittyen merkkituotteiden markkinointiin, identiteettiin ja imagoon, sekä suhdemarkkinointiin osana merkkituotemarkkinointia. Tutkimuksen lähestymistapa on kuvaileva eli deskriptiivinen ja sekä kvalitatiivinen että kvantitatiivinen. Tutkimus on tapaustutkimus, jossa caseyritykseksi valittiin kansainvälinen pakkauskartonki-teollisuuden yritys. Empiirisen osuuden toteuttamiseen käytettiin www-pohjaista surveytä, jonka avulla tietoja kerättiin myyntihenkilöstöltä case-yrityksessä. Lisäksi empiiristä osuutta laajennettiin tutkimalla sekundäärilähteitä kuten yrityksen sisäisiä kirjallisia dokumentteja ja tutkimuksia. TULOKSET. Teoreettisen ja empiirisen tutkimuksen tuloksena luotiin malli jota voidaan hyödyntää merkkituotemarkkinoinnin päätöksenteon tukena pakkauskartonki-teollisuudessa. Teollisen brandinhallinnan tulee keskittyä erityisesti asiakas-suhteiden brandaukseen – tätä voisi kutsua teolliseksi suhdebrandaukseksi. Tuote-elementit ja –arvot, differointi ja positiointi, sisäinen yrityskuva ja viestintä ovat teollisen brandi-identiteetin peruskiviä, jotka luovat brandi-imagon. Case-yrityksen myyntihenkilöstön tuote- ja yritysmielikuvat osoittautuivat kokonaisuudessaan hyviksi. Paras imago on CKB tuotteilla, kun taas heikoin on WLC tuotteilla. Teolliset brandit voivat luoda monenlaisia lisäarvoja sekä asiakas- että myyjäyritykselle.

Image quality in CT: From physical measurements to model observers.

Evaluation of image quality (IQ) in Computed Tomography (CT) is important to ensure that diagnostic questions are correctly answered, whilst keeping radiation dose to the patient as low as is reasonably possible. The assessment of individual aspects of IQ is already a key component of routine quality control of medical x-ray devices. These values together with standard dose indicators can be used to give rise to 'figures of merit' (FOM) to characterise the dose efficiency of the CT scanners operating in certain modes. The demand for clinically relevant IQ characterisation has naturally increased with the development of CT technology (detectors efficiency, image reconstruction and processing), resulting in the adaptation and evolution of assessment methods. The purpose of this review is to present the spectrum of various methods that have been used to characterise image quality in CT: from objective measurements of physical parameters to clinically task-based approaches (i.e. model observer (MO) approach) including pure human observer approach. When combined together with a dose indicator, a generalised dose efficiency index can be explored in a framework of system and patient dose optimisation. We will focus on the IQ methodologies that are required for dealing with standard reconstruction, but also for iterative reconstruction algorithms. With this concept the previously used FOM will be presented with a proposal to update them in order to make them relevant and up to date with technological progress. The MO that objectively assesses IQ for clinically relevant tasks represents the most promising method in terms of radiologist sensitivity performance and therefore of most relevance in the clinical environment.

Optimization of Radiation Dose and Image Quality in Musculoskeletal CT: Emphasis on Iterative Reconstruction Techniques (Part 1).

Computed tomography (CT) is a modality of choice for the study of the musculoskeletal system for various indications including the study of bone, calcifications, internal derangements of joints (with CT arthrography), as well as periprosthetic complications. However, CT remains intrinsically limited by the fact that it exposes patients to ionizing radiation. Scanning protocols need to be optimized to achieve diagnostic image quality at the lowest radiation dose possible. In this optimization process, the radiologist needs to be familiar with the parameters used to quantify radiation dose and image quality. CT imaging of the musculoskeletal system has certain specificities including the focus on high-contrast objects (i.e., in CT of bone or CT arthrography). These characteristics need to be taken into account when defining a strategy to optimize dose and when choosing the best combination of scanning parameters. In the first part of this review, we present the parameters used for the evaluation and quantification of radiation dose and image quality. In the second part, we discuss different strategies to optimize radiation dose and image quality at CT, with a focus on the musculoskeletal system and the use of novel iterative reconstruction techniques.

Optimization of Radiation Dose and Image Quality in Musculoskeletal CT: Emphasis on Iterative Reconstruction Techniques (Part 2).

Computed tomography (CT) is a modality of choice for the study of the musculoskeletal system for various indications including the study of bone, calcifications, internal derangements of joints (with CT arthrography), as well as periprosthetic complications. However, CT remains intrinsically limited by the fact that it exposes patients to ionizing radiation. Scanning protocols need to be optimized to achieve diagnostic image quality at the lowest radiation dose possible. In this optimization process, the radiologist needs to be familiar with the parameters used to quantify radiation dose and image quality. CT imaging of the musculoskeletal system has certain specificities including the focus on high-contrast objects (i.e., in CT of bone or CT arthrography). These characteristics need to be taken into account when defining a strategy to optimize dose and when choosing the best combination of scanning parameters. In the first part of this review, we present the parameters used for the evaluation and quantification of radiation dose and image quality. In the second part, we discuss different strategies to optimize radiation dose and image quality of CT, with a focus on the musculoskeletal system and the use of novel iterative reconstruction techniques.

Whole-body MRI: comprehensive evaluation on a 48-channel 3T MRI system in less than 40 minutes. Preliminary results

OBJECTIVE: To evaluate a comprehensive MRI protocol that investigates for cancer, vascular disease, and degenerative/inflammatory disease from the head to the pelvis in less than 40 minutes on a new generation 48-channel 3T system. MATERIALS AND METHODS: All MR studies were performed on a 48-channel 3T MR scanner. A 20-channel head/neck coil, two 18-channel body arrays, and a 32-channel spine array were employed. A total of 4 healthy individuals were studied. The designed protocol included a combination of single-shot T2-weighted sequences, T1-weighted 3D gradient-echo pre- and post-gadolinium. All images were retrospectively evaluated by two radiologists independently for overall image quality. RESULTS: The image quality for cancer was rated as excellent in the liver, pancreas, kidneys, lungs, pelvic organs, and brain, and rated as fair in the colon and breast. For vascular diseases ratings were excellent in the aorta, major branch vessel origins, inferior vena cava, portal and hepatic veins, rated as good in pulmonary arteries, and as poor in the coronary arteries. For degenerative/inflammatory diseases ratings were excellent in the brain, liver and pancreas. The inter-observer agreement was excellent. CONCLUSION: A comprehensive and time efficient screening for important categories of disease processes may be achieved with high quality imaging in a new generation 48-channel 3T system.

Image guided critical screw placement precision in the cervical spine : important or incidental? : results of a series of 91 consecutive cases using OVEM

Study design: A retrospective study of image guided cervical implant placement precision. Objective: To describe a simple and precise classification of cervical critical screw placement. Summary of Background Data: "Critical" screw placement is defined as implant insertion into a bone corridor which is surrounded circumferentially by neurovascular structures. While the use of image guidance has improved accuracy, there is currently no classification which provides sufficient precision to assess the navigation success of critical cervical screw placement. Methods: Based on postoperative clinical evaluation and CT imaging, the orthogonal view evaluation method (OVEM) is used to classify screw accuracy into grade I (no cortical breach), grade la (screw thread cortical breach), grade II (internal diameter cortical breach) and grade III (major cortical breach causing neural or vascular injury). Grades II and III are considered to be navigation failures, after accounting for bone corridor / screw mismatch (minimal diameter of targeted bone corridor being smaller than an outer screw diameter). Results: A total of 276 screws from 91 patients were classified into grade I (64.9%), grade la (18.1%), and grade II (17.0%). No grade III screw was observed. The overall rate of navigation failure was 13%. Multiple logistic regression indicated that navigational failure was significantly associated with the level of instrumentation and the navigation system used. Navigational failure was rare (1.6%) when the margin around the screw in the bone corridor was larger than 1.5 mm. Conclusions: OVEM evaluation appears to be a useful tool to assess the precision of critical screw placement in the cervical spine. The OVEM validity and reliability need to be addressed. Further correlation with clinical outcomes will be addressed in future studies.

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.

Image Segmentation Using Information Bottleneck Method

In image processing, segmentation algorithms constitute one of the main focuses of research. In this paper, new image segmentation algorithms based on a hard version of the information bottleneck method are presented. The objective of this method is to extract a compact representation of a variable, considered the input, with minimal loss of mutual information with respect to another variable, considered the output. First, we introduce a split-and-merge algorithm based on the definition of an information channel between a set of regions (input) of the image and the intensity histogram bins (output). From this channel, the maximization of the mutual information gain is used to optimize the image partitioning. Then, the merging process of the regions obtained in the previous phase is carried out by minimizing the loss of mutual information. From the inversion of the above channel, we also present a new histogram clustering algorithm based on the minimization of the mutual information loss, where now the input variable represents the histogram bins and the output is given by the set of regions obtained from the above split-and-merge algorithm. Finally, we introduce two new clustering algorithms which show how the information bottleneck method can be applied to the registration channel obtained when two multimodal images are correctly aligned. Different experiments on 2-D and 3-D images show the behavior of the proposed algorithms

Image analysis for assessing broiler breeder behavior response to thermal environment

The research proposes a methodology for assessing broiler breeder response to changes in rearing thermal environment. The continuous video recording of a flock analyzed may offer compelling evidences of thermal comfort, as well as other indications of welfare. An algorithm for classifying specific broiler breeder behavior was developed. Videos were recorded over three boxes where 30 breeders were reared. The boxes were mounted inside an environmental chamber were ambient temperature varied from cold to hot. Digital images were processed based on the number of pixels, according to their light intensity variation and binary contrast allowing a sequence of behaviors related to welfare. The system used the default of x, y coordinates, where x represents the horizontal distance from the top left of the work area to the point P, and y is the vertical distance. The video images were observed, and a grid was developed for identifying the area the birds stayed and the time they spent at that place. The sequence was analyzed frame by frame confronting the data with specific adopted thermal neutral rearing standards. The grid mask overlapped the real bird image. The resulting image allows the visualization of clusters, as birds in flock behave in certain patterns. An algorithm indicating the breeder response to thermal environment was developed.

Using an aerial system of remote sensing to detect different nutritional status in Brachiaria decumbens

The aim of this study was to use digital images acquired by cameras attached to a helium balloon to detect variation of the nutritional status in Brachiaria decumbens. The treatments consisted of five doses of nitrogen (0, 50, 100, 150 e 200kg ha-1) with six replications each, evaluated in a completely randomized statistical design. A remote sensing system composed of digital cameras and microcomputers was used for image acquisition, and a helium balloon lifted the cameras to the heights of 15, 20, 25 and 30m. A portable chlorophyll meter and analyses of leaf nitrogen content were used to make comparisons with data obtained by the remote sensing system. Data was acquired in two phases, in different climatic conditions. At the end of each phase, dry matter production was measured. Three vegetation indices were used to evaluate the detection of different nutritional status. The three indices were able to detect the effects of N doses. The indices constructed with the Green spectral band showed to be more efficient.

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.

Evaluation of bursal lymphoid depletion: comparison between the conventional histology method and digital lymphocyte depletion evaluation system

Abstract: Fifty-five bursa of Fabricius (BF) were evaluated by optical microscopy for three different avian histopathologists (H1, H3 and H4) to determine the degree of lymphoid depletion. One histologist evaluated the same slides at two different times (H1 and H2) with four-months interval between the observations. The same BFs were evaluated using the system of Digital Lymphocyte Depletion Evaluation (ADDL), being performed by three differents operators of the system, not histopathologists. The results showed was a significant difference between the histopathologists and between the scores established by the same expert (H1 and H2). However, there were not significant differences between the scores with the ADDL system, obtained using ADDL. The results make clear the fragility of the subjective lymphocyte depletion score classification by the traditional histologic method, while the ADDL system proves to be more appropriated for the assessment of the lymphoid loss in the BF.

Experimental validation of a 3-D vision-based measurement system applied to robot calibration

One of the problems that slows the development of off-line programming is the low static and dynamic positioning accuracy of robots. Robot calibration improves the positioning accuracy and can also be used as a diagnostic tool in robot production and maintenance. A large number of robot measurement systems are now available commercially. Yet, there is a dearth of systems that are portable, accurate and low cost. In this work a measurement system that can fill this gap in local calibration is presented. The measurement system consists of a single CCD camera mounted on the robot tool flange with a wide angle lens, and uses space resection models to measure the end-effector pose relative to a world coordinate system, considering radial distortions. Scale factors and image center are obtained with innovative techniques, making use of a multiview approach. The target plate consists of a grid of white dots impressed on a black photographic paper, and mounted on the sides of a 90-degree angle plate. Results show that the achieved average accuracy varies from 0.2mm to 0.4mm, at distances from the target from 600mm to 1000mm respectively, with different camera orientations.

Weed mapping using a machine vision system

Weed mapping is a useful tool for site-specific herbicide applications. The objectives of this study were (1) to determine the percentage of land area covered by weeds in no-till and conventionally tilled fields of common bean using digital image processing and geostatistics, and (2) to compare two types of cameras. Two digital cameras (color and infrared) and a differential GPS were affixed to a center pivot structure for image acquisition. Sample field images were acquired in a regular grid pattern, and the images were processed to estimate the percentage of weed cover. After calculating the georeferenced weed percentage values, maps were constructed using geostatistical techniques. Based on the results, color images are recommended for mapping the percentage of weed cover in no-till systems, while infrared images are recommended for weed mapping in conventional tillage systems.