Use of Statistical Methods in Demand Planning

In a very volatile industry of high technology it is of utmost importance to accurately forecast customers’ demand. However, statistical forecasting of sales, especially in heavily competitive electronics product business, has always been a challenging task due to very high variation in demand and very short product life cycles of products. The purpose of this thesis is to validate if statistical methods can be applied to forecasting sales of short life cycle electronics products and provide a feasible framework for implementing statistical forecasting in the environment of the case company. Two different approaches have been developed for forecasting on short and medium term and long term horizons. Both models are based on decomposition models, but differ in interpretation of the model residuals. For long term horizons residuals are assumed to represent white noise, whereas for short and medium term forecasting horizon residuals are modeled using statistical forecasting methods. Implementation of both approaches is performed in Matlab. Modeling results have shown that different markets exhibit different demand patterns and therefore different analytical approaches are appropriate for modeling demand in these markets. Moreover, the outcomes of modeling imply that statistical forecasting can not be handled separately from judgmental forecasting, but should be perceived only as a basis for judgmental forecasting activities. Based on modeling results recommendations for further deployment of statistical methods in sales forecasting of the case company are developed.

Discrete distributions when modeling the disability severity score of motor victims

Many European states apply score systems to evaluate the disability severity of non-fatal motor victims under the law of third-party liability. The score is a non-negative integer with an upper bound at 100 that increases with severity. It may be automatically converted into financial terms and thus also reflects the compensation cost for disability. In this paper, discrete regression models are applied to analyze the factors that influence the disability severity score of victims. Standard and zero-altered regression models are compared from two perspectives: an interpretation of the data generating process and the level of statistical fit. The results have implications for traffic safety policy decisions aimed at reducing accident severity. An application using data from Spain is provided.

Eosinophilic granulomatosis with polyangiitis (Churg-Strauss) (EGPA) Consensus Task Force recommendations for evaluation and management.

OBJECTIVE: To develop disease-specific recommendations for the diagnosis and management of eosinophilic granulomatosis with polyangiitis (Churg-Strauss syndrome) (EGPA). METHODS: The EGPA Consensus Task Force experts comprised 8 pulmonologists, 6 internists, 4 rheumatologists, 3 nephrologists, 1 pathologist and 1 allergist from 5 European countries and the USA. Using a modified Delphi process, a list of 40 questions was elaborated by 2 members and sent to all participants prior to the meeting. Concurrently, an extensive literature search was undertaken with publications assigned with a level of evidence according to accepted criteria. Drafts of the recommendations were circulated for review to all members until final consensus was reached. RESULTS: Twenty-two recommendations concerning the diagnosis, initial evaluation, treatment and monitoring of EGPA patients were established. The relevant published information on EGPA, antineutrophil-cytoplasm antibody-associated vasculitides, hypereosinophilic syndromes and eosinophilic asthma supporting these recommendations was also reviewed. DISCUSSION: These recommendations aim to give physicians tools for effective and individual management of EGPA patients, and to provide guidance for further targeted research.

Epilepsy priorities in Europe: A report of the ILAE-IBE Epilepsy Advocacy Europe Task Force.

The European Forum on Epilepsy Research (ERF2013), which took place in Dublin, Ireland, on May 26-29, 2013, was designed to appraise epilepsy research priorities in Europe through consultation with clinical and basic scientists as well as representatives of lay organizations and health care providers. The ultimate goal was to provide a platform to improve the lives of persons with epilepsy by influencing the political agenda of the EU. The Forum highlighted the epidemiologic, medical, and social importance of epilepsy in Europe, and addressed three separate but closely related concepts. First, possibilities were explored as to how the stigma and social burden associated with epilepsy could be reduced through targeted initiatives at EU national and regional levels. Second, ways to ensure optimal standards of care throughout Europe were specifically discussed. Finally, a need for further funding in epilepsy research within the European Horizon 2020 funding programme was communicated to politicians and policymakers participating to the forum. Research topics discussed specifically included (1) epilepsy in the developing brain; (2) novel targets for innovative diagnostics and treatment of epilepsy; (3) what is required for prevention and cure of epilepsy; and (4) epilepsy and comorbidities, with a special focus on aging and mental health. This report provides a summary of recommendations that emerged at ERF2013 about how to (1) strengthen epilepsy research, (2) reduce the treatment gap, and (3) reduce the burden and stigma associated with epilepsy. Half of the 6 million European citizens with epilepsy feel stigmatized and experience social exclusion, stressing the need for funding trans-European awareness campaigns and monitoring their impact on stigma, in line with the global commitment of the European Commission and with the recommendations made in the 2011 Written Declaration on Epilepsy. Epilepsy care has high rates of misdiagnosis and considerable variability in organization and quality across European countries, translating into huge societal cost (0.2% GDP) and stressing the need for cost-effective programs of harmonization and optimization of epilepsy care throughout Europe. There is currently no cure or prevention for epilepsy, and 30% of affected persons are not controlled by current treatments, stressing the need for pursuing research efforts in the field within Horizon 2020. Priorities should include (1) development of innovative biomarkers and therapeutic targets and strategies, from gene and cell-based therapies to technologically advanced surgical treatment; (2) addressing issues raised by pediatric and aging populations, as well as by specific etiologies and comorbidities such as traumatic brain injury (TBI) and cognitive dysfunction, toward more personalized medicine and prevention; and (3) translational studies and clinical trials built upon well-established European consortia.

Soldiers in a stingless bee: work rate and task repertoire suggest they are an elite force

The differentiation of workers into morphological subcastes (e.g., soldiers) represents an important evolutionary transition and is thought to improve division of labor in social insects. Soldiers occur in many ant and termite species, where they make up a small proportion of the workforce. A common assumption of worker caste evolution is that soldiers are behavioral specialists. Here, we report the first test of the "rare specialist" hypothesis in a eusocial bee. Colonies of the stingless bee Tetragonisca angustula are defended by a small group of morphologically differentiated soldiers. Contrary to the rare specialist hypothesis, we found that soldiers worked more (+34%-41%) and performed a greater variety of tasks (+23%-34%) than other workers, particularly early in life. Our results suggest a "rare elite" function of soldiers in T. angustula, that is, that they perform a disproportionately large amount of the work. Division of labor was based on a combination of temporal and physical castes, but soldiers transitioned faster from one task to the next. We discuss why the rare specialist assumption might not hold in species with a moderate degree of worker differentiation.

Language Learning in Task Management and Task Accomplishment

In this paper we study student interaction in English and Swedish courses at a Finnish university. We focus on language choices made in task-related activities in small group interaction. Our research interests arose from the change in the teaching curriculum, in which content and language courses were integrated at Tampere University of Technology in 2013. Using conversation analysis, we analysed groups of 4-5 students who worked collaboratively on a task via a video conference programme. The results show how language alternation has different functions in 1) situations where students orient to managing the task, e.g., in transitions into task, or where they orient to technical problems, and 2) situations where students accomplish the task. With the results, we aim to show how language alternation can provide interactional opportunities for language learning. The findings will be useful in designing tasks in the future.

Anthropomorphic model observer performance in three-dimensional detection task for low-contrast computed tomography.

X-ray medical imaging is increasingly becoming three-dimensional (3-D). The dose to the population and its management are of special concern in computed tomography (CT). Task-based methods with model observers to assess the dose-image quality trade-off are promising tools, but they still need to be validated for real volumetric images. The purpose of the present work is to evaluate anthropomorphic model observers in 3-D detection tasks for low-contrast CT images. We scanned a low-contrast phantom containing four types of signals at three dose levels and used two reconstruction algorithms. We implemented a multislice model observer based on the channelized Hotelling observer (msCHO) with anthropomorphic channels and investigated different internal noise methods. We found a good correlation for all tested model observers. These results suggest that the msCHO can be used as a relevant task-based method to evaluate low-contrast detection for CT and optimize scan protocols to lower dose in an efficient way.

The internal wave field in Sau reservoir : Observation and modeling of a third vertical mode

Water withdrawal from Mediterranean reservoirs in summer is usually very high. Because of this, stratification is often continuous and far from the typical two-layered structure, favoring the excitation of higher vertical modes. The analysis of wind, temperature, and current data from Sau reservoir (Spain) shows that the third vertical mode of the internal seiche (baroclinic mode) dominated the internal wave field at the beginning of September 2003. We used a continuous stratification two-dimensional model to calculate the period and velocity distribution of the various modes of the internal seiche, and we calculated that the period of the third vertical mode is ;24 h, which coincides with the period of the dominating winds. As a result of the resonance between the third mode and the wind, the other oscillation modes were not excited during this period

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

IEA Bioenergy Task 40 “Sustainable International Bioenergy Trade: Securing supply and demand” Country report of Finland 2008

This study considered the current situation of biofuels markets in Finland. The fact that industry consumes more than half of the total primary energy, widely applied combined heat and power production and a high share of solid biomass fuels in the total energy consumption are specific to the Finnish energy system. Wood is the most important source of bioenergy in Finland, representing 21% of the total energy consumption in 2006. Almost 80% of the wood-based energy is recovered from industrial by-products and residues. Finland has commitment itself to maintaining its greenhouse gas emissions at the 1990 level, at the highest, during the period 2008–2012. The energy and climate policy carried out in recent years has been based on the National Energy and Climate introduced in 2005. The Finnish energy policy aims to achieve the target, and a variety of measures are taken to promote the use of renewable energy sources and especially wood fuels. In 2007, the government started to prepare a new long-term (up to the year 2050) climate and energy strategy that will meet EU’s new targets for the reduction of green house gas emissions and the promotion of renewable energy sources. The new strategy will be introduced during 2008. The international biofuels trade has a substantial importance for the utilisation of bioenergy in Finland. In 2006, the total international trading of solid and liquid biofuels was approximately 64 PJ of which import was 61 PJ. Most of the import is indirect and takes place within the forest industry’s raw wood imports. In 2006, as much as 24% of wood energy was based on foreignorigin wood. Wood pellets and tall oil form the majority of export streams of biofuels. The indirect import of wood fuels increased almost 10% in 2004–2006, while the direct trade of solid and liquid biofuels has been almost constant.

Fischer-Tropsch Slurry Bubble Column Reactor Modeling

The literature part of the work reviews overall Fischer-Tropsch process, Fischer-Tropsch reactors and catalysts. Fundamentals of Fischer-Tropsch modeling are also presented. The emphasis is on the reactor unit. Comparison of the reactors and the catalysts is carried out to choose the suitable reactor setup for the modeling work. The effects of the operation conditions are also investigated. Slurry bubble column reactor model operating with cobalt catalyst is developed by taking into account the mass transfer of the reacting components (CO and H2) and the consumption of the reactants in the liquid phase. The effect of hydrostatic pressure and the change in total mole flow rate in gas phase are taken into account in calculation of the solubilities. The hydrodynamics, reaction kinetics and product composition are determined according to literature. The cooling system and furthermore the required heat transfer area and number of cooling tubes are also determined. The model is implemented in Matlab software. Commercial scale reactor setup is modeled and the behavior of the model is investigated. The possible inaccuraries are evaluated and the suggestions for the future work are presented. The model is also integrated to Aspen Plus process simulation software, which enables the usage of the model in more extensive Fischer-Tropsch process simulations. Commercial scale reactor of diameter of 7 m and height of 30 m was modeled. The capacity of the reactor was calculated to be about 9 800 barrels/day with CO conversion of 75 %. The behavior of the model was realistic and results were in the right range. The highest uncertainty to model was estimated to be caused by the determination of the kinetic rate.

Modeling the transport phenomena within arterial wall: porous media approach

The transport of macromolecules, such as low-density lipoprotein (LDL), and their accumulation in the layers of the arterial wall play a critical role in the creation and development of atherosclerosis. Atherosclerosis is a disease of large arteries e.g., the aorta, coronary, carotid, and other proximal arteries that involves a distinctive accumulation of LDL and other lipid-bearing materials in the arterial wall. Over time, plaque hardens and narrows the arteries. The flow of oxygen-rich blood to organs and other parts of the body is reduced. This can lead to serious problems, including heart attack, stroke, or even death. It has been proven that the accumulation of macromolecules in the arterial wall depends not only on the ease with which materials enter the wall, but also on the hindrance to the passage of materials out of the wall posed by underlying layers. Therefore, attention was drawn to the fact that the wall structure of large arteries is different than other vessels which are disease-resistant. Atherosclerosis tends to be localized in regions of curvature and branching in arteries where fluid shear stress (shear rate) and other fluid mechanical characteristics deviate from their normal spatial and temporal distribution patterns in straight vessels. On the other hand, the smooth muscle cells (SMCs) residing in the media layer of the arterial wall respond to mechanical stimuli, such as shear stress. Shear stress may affect SMC proliferation and migration from the media layer to intima. This occurs in atherosclerosis and intimal hyperplasia. The study of blood flow and other body fluids and of heat transport through the arterial wall is one of the advanced applications of porous media in recent years. The arterial wall may be modeled in both macroscopic (as a continuous porous medium) and microscopic scales (as a heterogeneous porous medium). In the present study, the governing equations of mass, heat and momentum transport have been solved for different species and interstitial fluid within the arterial wall by means of computational fluid dynamics (CFD). Simulation models are based on the finite element (FE) and finite volume (FV) methods. The wall structure has been modeled by assuming the wall layers as porous media with different properties. In order to study the heat transport through human tissues, the simulations have been carried out for a non-homogeneous model of porous media. The tissue is composed of blood vessels, cells, and an interstitium. The interstitium consists of interstitial fluid and extracellular fibers. Numerical simulations are performed in a two-dimensional (2D) model to realize the effect of the shape and configuration of the discrete phase on the convective and conductive features of heat transfer, e.g. the interstitium of biological tissues. On the other hand, the governing equations of momentum and mass transport have been solved in the heterogeneous porous media model of the media layer, which has a major role in the transport and accumulation of solutes across the arterial wall. The transport of Adenosine 5´-triphosphate (ATP) is simulated across the media layer as a benchmark to observe how SMCs affect on the species mass transport. In addition, the transport of interstitial fluid has been simulated while the deformation of the media layer (due to high blood pressure) and its constituents such as SMCs are also involved in the model. In this context, the effect of pressure variation on shear stress is investigated over SMCs induced by the interstitial flow both in 2D and three-dimensional (3D) geometries for the media layer. The influence of hypertension (high pressure) on the transport of lowdensity lipoprotein (LDL) through deformable arterial wall layers is also studied. This is due to the pressure-driven convective flow across the arterial wall. The intima and media layers are assumed as homogeneous porous media. The results of the present study reveal that ATP concentration over the surface of SMCs and within the bulk of the media layer is significantly dependent on the distribution of cells. Moreover, the shear stress magnitude and distribution over the SMC surface are affected by transmural pressure and the deformation of the media layer of the aorta wall. This work reflects the fact that the second or even subsequent layers of SMCs may bear shear stresses of the same order of magnitude as the first layer does if cells are arranged in an arbitrary manner. This study has brought new insights into the simulation of the arterial wall, as the previous simplifications have been ignored. The configurations of SMCs used here with elliptic cross sections of SMCs closely resemble the physiological conditions of cells. Moreover, the deformation of SMCs with high transmural pressure which follows the media layer compaction has been studied for the first time. On the other hand, results demonstrate that LDL concentration through the intima and media layers changes significantly as wall layers compress with transmural pressure. It was also noticed that the fraction of leaky junctions across the endothelial cells and the area fraction of fenestral pores over the internal elastic lamina affect the LDL distribution dramatically through the thoracic aorta wall. The simulation techniques introduced in this work can also trigger new ideas for simulating porous media involved in any biomedical, biomechanical, chemical, and environmental engineering applications.

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal