Supplier segmentation and development in project business

The purpose of this study was to expand the applicability of supplier segmentation and development approaches to the project-driven construction industry. These practices are less exploited and not well documented in this operational environment compared to the process-centric manufacturing industry. At first, portfolio models to supply base segmentation and various supplier development efforts were investigated in literature review. A step-wise framework was structured for the empirical research. The empirical study employed multiple research methods in three case studies in a large Finnish construction company. The first study categorized the construction item classes into the purchasing portfolio and positioned suppliers to the power matrix by investigating buyer-supplier relations. Using statistical tests, the study also identified factors that affect suppliers’ performance. The final case study identified improvement areas of the interface between a main contractor and one if its largest suppliers. The final results indicate that only by assessing the supply base in a holistic manner and the power circumstances in it, buyers comprehend how to best establish appropriate supplier development strategies in the project environment.

Statistical segmentation methods and color variance analysis of retinal images

In this research, the effectiveness of Naive Bayes and Gaussian Mixture Models classifiers on segmenting exudates in retinal images is studied and the results are evaluated with metrics commonly used in medical imaging. Also, a color variation analysis of retinal images is carried out to find how effectively can retinal images be segmented using only the color information of the pixels.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

Texture analysis of computed tomography images of acute ischemic stroke patients

Computed tomography (CT) images are routinely used to assess ischemic brain stroke in the acute phase. They can provide important clues about whether to treat the patient by thrombolysis with tissue plasminogen activator. However, in the acute phase, the lesions may be difficult to detect in the images using standard visual analysis. The objective of the present study was to determine if texture analysis techniques applied to CT images of stroke patients could differentiate between normal tissue and affected areas that usually go unperceived under visual analysis. We performed a pilot study in which texture analysis, based on the gray level co-occurrence matrix, was applied to the CT brain images of 5 patients and of 5 control subjects and the results were compared by discriminant analysis. Thirteen regions of interest, regarding areas that may be potentially affected by ischemic stroke, were selected for calculation of texture parameters. All regions of interest for all subjects were classified as lesional or non-lesional tissue by an expert neuroradiologist. Visual assessment of the discriminant analysis graphs showed differences in the values of texture parameters between patients and controls, and also between texture parameters for lesional and non-lesional tissue of the patients. This suggests that texture analysis can indeed be a useful tool to help neurologists in the early assessment of ischemic stroke and quantification of the extent of the affected areas.

Brain tissue segmentation using q-entropy in multiple sclerosis magnetic resonance images

The loss of brain volume has been used as a marker of tissue destruction and can be used as an index of the progression of neurodegenerative diseases, such as multiple sclerosis. In the present study, we tested a new method for tissue segmentation based on pixel intensity threshold using generalized Tsallis entropy to determine a statistical segmentation parameter for each single class of brain tissue. We compared the performance of this method using a range of different q parameters and found a different optimal q parameter for white matter, gray matter, and cerebrospinal fluid. Our results support the conclusion that the differences in structural correlations and scale invariant similarities present in each tissue class can be accessed by generalized Tsallis entropy, obtaining the intensity limits for these tissue class separations. In order to test this method, we used it for analysis of brain magnetic resonance images of 43 patients and 10 healthy controls matched for gender and age. The values found for the entropic q index were 0.2 for cerebrospinal fluid, 0.1 for white matter and 1.5 for gray matter. With this algorithm, we could detect an annual loss of 0.98% for the patients, in agreement with literature data. Thus, we can conclude that the entropy of Tsallis adds advantages to the process of automatic target segmentation of tissue classes, which had not been demonstrated previously.

Effect of wheat flour protein variations on sensory attributes, texture and staling of Taftoon bread

The quality of flat breads depends in part on the textural properties of breads during storage. These properties are largely affected by flour protein quality and quantity. The present study aimed to examine differences between sensory properties, textural and staling of Tandoori breads made from flours of different quality and different quantities of protein. This was implemented by using three flours with 9.4, 11.5 and 13.5% protein contents and different protein qualities shown by Zeleney sedimentation volume 16.25, 22.75 and 23.25 mL respectively. Bread strips were submitted to uniaxial compression between two parallel plates on an Instron Universal Testing machine, and firmness of the breads was determined. Results indicated the differences in the sensory attributes of breads produced by flours of different protein content and quality, demonstrating that high protein high quality flours are not able to sheet and expand under the high temperature - short time conditions employed in Taftoon bread production and are therefore not suitable for this kind of bread. Results showed that flour with 11.5% protein content, produced bread with better sensory characteristics and acceptable storage time.

Effect of soaking and cooking on phytate concentration, minerals, and texture of food-type soybeans

The increasing consumption of soybeans due to its bioactive compounds has attracted interest in describing the grain's constituents and variation during processing. Phytate has been the aim of much research since it chelates essential minerals but also has beneficial antioxidant effects. This study evaluated the variation of phytate, calcium, zinc, and iron during soaking and cooking of soybeans. The phytate: Zn and phytate: Fe molar ratios were determined in order to estimate the bioavailability of these minerals. Six food-type varieties were used: BR 36, BRS 213, BRS 216, BRS 232, BRS 155, and Embrapa 48. The samples were soaked in water 3:1 (w/w) for 12 hours at room temperature and cooked. Cooking time was determined by modeling the softening of each variety using fractional conversion. Water content, phytate, and minerals were determined in raw, soaked and cooked samples. The water content of raw grains for all varieties was 9.9 g.100 g-1 increasing to a range of 58.1-63.7 g.100 g-1 after soaking and 63.1-66.0 g.100 g-1 after cooking. Soaking caused a significant reduction in phytate (23-30%), but cooking caused no additional reduction. The phytate: Zn molar ratio was 20 indicating that zinc absorption could be impaired, while the phytate: Fe molar ratio was 8, below the level of compromising absorption

Effect of whey protein concentrate on texture of fat-free desserts: sensory and instrumental measurements

It is important to understand how changes in the product formulation can modify its characteristics. Thus, the objective of this study was to investigate the effect of whey protein concentrate (WPC) on the texture of fat-free dairy desserts. The correlation between instrumental and sensory measurements was also investigated. Four formulations were prepared with different WPC concentrations (0, 1.5, 3.0, and 4.5 wt. (%)) and were evaluated using the texture profile analysis (TPA) and rheology. Thickness was evaluated by nine trained panelists. Formulations containing WPC showed higher firmness, elasticity, chewiness, and gumminess and clearly differed from the control as indicated by principal component analysis (PCA). Flow behavior was characterized as time-dependent and pseudoplastic. Formulation with 4.5% WPC at 10 °C showed the highest thixotropic behavior. Experimental data were fitted to Herschel-Bulkley model. The addition of WPC contributed to the texture of the fat-free dairy dessert. The yield stress, apparent viscosity, and perceived thickness in the dairy desserts increased with WPC concentration. The presence of WPC promotes the formation of a stronger gel structure as a result of protein-protein interactions. The correlation between instrumental parameters and thickness provided practical results for food industries.

Effect of starter culture and inulin addition on microbial viability, texture, and chemical characteristics of whole or skim milk Kefir

The effect of inulin addition and starters (Kefir grains or commercial starter culture) on the microbial viability, texture, and chemical characteristics of Kefir beverages prepared with whole or skim milk was evaluated during refrigerated storage. The type of starter did not influence microbial viability during the storage of the beverages, but the chemical and textural changes (decreases in pH, lactose concentration, and inulin and increased acidity, firmness, and syneresis) were more pronounced in the formulations fermented with grains than those fermented with the starter culture. The addition of inulin did not influence acidity or viability of lactic acid bacteria, but in general, its effect on the survival of acetic acid bacteria, Lactococcus and yeasts, firmness, and syneresis depended on the type of milk and starter culture used. Generally, the yeast, acetic acid bacteria, and Leuconostoc counts increased or remained unchanged, while the total population of lactic acid bacteria and Lactococcus were either reduced by 1 to 2 logs or remained unchanged during storage.

Influence of process parameters on the color and texture of passion fruit albedo preserved in syrup

The industrialization of passion fruit in the form of juice produces considerable amounts of residue that could be used as food. The objective of the present study was to determine the effects of the volume of passion fruit juice added to the syrup and the cooking time on the color and texture of passion fruit albedo preserved in syrup. Multi-linear models were well fit to describe the value for a* (for the albedo) the values for b* (for the albedo and syrup), which exhibited high correlation coefficients of 98%, 84%, and 88%, respectively. The volume of passion fruit juice added and the cooking time of the albedos in the syrup, involved in the processing of passion fruit albedo preserves in syrup, significantly affected color analyses. The texture was not affected by the parameters studied. Therefore, the use of larger volumes of passion fruit juice and longer cooking time is recommended for the production of passion fruit albedo preserves in syrup to achieve the characteristic yellow color of the fruit.

Effect of the addition of wheat fiber and partial pork back fat on the chemical composition, texture and sensory property of low-fat bologna sausage containing inulin and oat fiber

The objective of this work was to study the effect of adding wheat fiber and partial pork back fat on the quality characteristics of bologna sausage. The compound central rotating design was used with treatments containing fixed levels of inulin (5%) and oat fiber (1%) and variable levels of wheat fiber (0-4%) and pork back fat (0-10%). The pH and protein were similar in all the treatments, the fat was lower than the control treatment and the moisture content was higher than the control treatment (CF) without fibers. The wheat fiber increased the hardness and reduced cohesiveness and scores were given for overall impression. We found that it was possible to prepare low-fat bologna sausage with the addition of 6.58% fiber (5% inulin, 1% oat fiber and 0.58% wheat fiber), whilst retaining good sensory acceptability, thus reducing the pork back fat levels by between 25 and 42.75%.