Differentiation of Metabolically Distinct Areas within Head and Neck Region using Dynamic 18F-FDG Positron Emission Tomography Imaging

Positron Emission Tomography (PET) using ¹⁸F-FDG is playing a vital role in the diagnosis and treatment planning of cancer. However, the most widely used radiotracer, ¹⁸F-FDG, is not specific for tumours and can also accumulate in inflammatory lesions as well as normal physiologically active tissues making diagnosis and treatment planning complicated for the physicians. Malignant, inflammatory and normal tissues are known to have different pathways for glucose metabolism which could possibly be evident from different characteristics of the time activity curves from a dynamic PET acquisition protocol. Therefore, we aimed to develop new image analysis methods, for PET scans of the head and neck region, which could differentiate between inflammation, tumour and normal tissues using this functional information within these radiotracer uptake areas. We developed different dynamic features from the time activity curves of voxels in these areas and compared them with the widely used static parameter, SUV, using Gaussian Mixture Model algorithm as well as K-means algorithm in order to assess their effectiveness in discriminating metabolically different areas. Moreover, we also correlated dynamic features with other clinical metrics obtained independently of PET imaging. The results show that some of the developed features can prove to be useful in differentiating tumour tissues from inflammatory regions and some dynamic features also provide positive correlations with clinical metrics. If these proposed methods are further explored then they can prove to be useful in reducing false positive tumour detections and developing real world applications for tumour diagnosis and contouring.

Forecasting of wind speeds and directions with artificial neural networks

In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.

Building Dynamic Data Centers for Fast Delivery of New Data and Data Updates

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Scheduling dynamic dataflow graphs with model checking

With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.

Modal testing and numerical modeling of the dynamic properties of layered sheet-steel structure

Recently, due to the increasing total construction and transportation cost and difficulties associated with handling massive structural components or assemblies, there has been increasing financial pressure to reduce structural weight. Furthermore, advances in material technology coupled with continuing advances in design tools and techniques have encouraged engineers to vary and combine materials, offering new opportunities to reduce the weight of mechanical structures. These new lower mass systems, however, are more susceptible to inherent imbalances, a weakness that can result in higher shock and harmonic resonances which leads to poor structural dynamic performances. The objective of this thesis is the modeling of layered sheet steel elements, to accurately predict dynamic performance. During the development of the layered sheet steel model, the numerical modeling approach, the Finite Element Analysis and the Experimental Modal Analysis are applied in building a modal model of the layered sheet steel elements. Furthermore, in view of getting a better understanding of the dynamic behavior of layered sheet steel, several binding methods have been studied to understand and demonstrate how a binding method affects the dynamic behavior of layered sheet steel elements when compared to single homogeneous steel plate. Based on the developed layered sheet steel model, the dynamic behavior of a lightweight wheel structure to be used as the structure for the stator of an outer rotor Direct-Drive Permanent Magnet Synchronous Generator designed for high-power wind turbines is studied.

Demand forecasting process design and methods in medium sized enterprise

The purpose of this thesis was to study the design of demand forecasting processes and management of demand. In literature review were different processes found and forecasting methods and techniques interviewed. Also role of bullwhip effect in supply chain was identified and how to manage it with information sharing operations. In the empirical part of study is at first described current situation and challenges in case company. After that will new way to handle demand introduced with target budget creation and how information sharing with 5 products and a few customers would bring benefits to company. Also the new S&OP process created within this study and organization for it.

Dynamic Analysis Model of Spherical Roller Bearings with Defects

Rolling element bearings are essential components of rotating machinery. The spherical roller bearing (SRB) is one variant seeing increasing use, because it is self-aligning and can support high loads. It is becoming increasingly important to understand how the SRB responds dynamically under a variety of conditions. This doctoral dissertation introduces a computationally efficient, three-degree-of-freedom, SRB model that was developed to predict the transient dynamic behaviors of a rotor-SRB system. In the model, bearing forces and deflections were calculated as a function of contact deformation and bearing geometry parameters according to nonlinear Hertzian contact theory. The results reveal how some of the more important parameters; such as diametral clearance, the number of rollers, and osculation number; influence ultimate bearing performance. Distributed defects, such as the waviness of the inner and outer ring, and localized defects, such as inner and outer ring defects, are taken into consideration in the proposed model. Simulation results were verified with results obtained by applying the formula for the spherical roller bearing radial deflection and the commercial bearing analysis software. Following model verification, a numerical simulation was carried out successfully for a full rotor-bearing system to demonstrate the application of this newly developed SRB model in a typical real world analysis. Accuracy of the model was verified by comparing measured to predicted behaviors for equivalent systems.

Cardiorespiratory adaptations induced by aerobic training in middle-aged men: the importance of a decrease in sympathetic stimulation for the contribution of dynamic exercise tachycardia

We investigated the effects of aerobic training on the efferent autonomic control of heart rate (HR) during dynamic exercise in middle-aged men, eight of whom underwent exercise training (T) while the other seven continued their sedentary (S) life style. The training was conducted over 10 months (three 1-h sessions/week on a field track at 70-85% of the peak HR). The contribution of sympathetic and parasympathetic exercise tachycardia was determined in terms of differences in the time constant effects on the HR response obtained using a discontinuous protocol (4-min tests at 25, 50, 100 and 125 watts on a cycle ergometer), and a continuous protocol (25 watts/min until exhaustion) allowed the quantification of the parameters (anaerobic threshold, VO2 AT; peak O2 uptake, VO2 peak; power peak) that reflect oxygen transport. The results obtained for the S and the T groups were: 1) a smaller resting HR in T (66 beats/min) when compared to S (84 beats/min); 2) during exercise, a small increase in the fast tachycardia (D0-10 s) related to vagal withdrawal (P<0.05, only at 25 watts) was observed in T at all powers; at middle and higher powers a significant decrease (P<0.05 at 50, 100 and 125 watts) in the slow tachycardia (D1-4 min) related to a sympathetic-dependent mechanism was observed in T; 3) the VO2 AT (S = 1.06 and T = 1.33 l/min) and VO2 peak (S = 1.97 and T = 2.47 l/min) were higher in T (P<0.05). These results demonstrate that aerobic training can induce significant physiological adaptations in middle-aged men, mainly expressed as a decrease in the sympathetic effects on heart rate associated with an increase in oxygen transport during dynamic exercise.

Endogenous vasopressin and the central control of heart rate during dynamic exercise

The present article contains a brief review on the role of vasopressinergic projections to the nucleus tractus solitarii in the genesis of reflex bradycardia and in the modulation of heart rate control during exercise. The effects of vasopressin on exercise tachycardia are discussed on the basis of both the endogenous peptide content changes and the heart rate response changes observed during running in sedentary and trained rats. Dynamic exercise caused a specific vasopressin content increase in dorsal and ventral brainstem areas. In accordance, rats pretreated with the peptide or the V1 blocker into the nucleus tractus solitarii showed a significant potentiation or a marked blunting of the exercise tachycardia, respectively, without any change in the pressure response to exercise. It is proposed that the long-descending vasopressinergic pathway to the nucleus tractus solitarii serves as one link between the two main neural controllers of circulation, i.e., the central command and feedback control mechanisms driven by the peripheral receptors. Therefore, vasopressinergic input could contribute to the adjustment of heart rate response (and cardiac output) to the circulatory demand during exercise.

Ambulatory blood pressure and Doppler echocardiographic indexes of borderline hypertensive men presenting an exaggerated blood pressure response during dynamic exercise

Borderline hypertension (BH) has been associated with an exaggerated blood pressure (BP) response during laboratory stressors. However, the incidence of target organ damage in this condition and its relation to BP hyperreactivity is an unsettled issue. Thus, we assessed the Doppler echocardiographic profile of a group of BH men (N = 36) according to office BP measurements with exaggerated BP in the cycloergometric test. A group of normotensive men (NT, N = 36) with a normal BP response during the cycloergometric test was used as control. To assess vascular function and reactivity, all subjects were submitted to the cold pressor test. Before Doppler echocardiography, the BP profile of all subjects was evaluated by 24-h ambulatory BP monitoring. All subjects from the NT group presented normal monitored levels of BP. In contrast, 19 subjects from the original BH group presented normal monitored BP levels and 17 presented elevated monitored BP levels. In the NT group all Doppler echocardiographic indexes were normal. All subjects from the original BH group presented normal left ventricular mass and geometrical pattern. However, in the subjects with elevated monitored BP levels, fractional shortening was greater, isovolumetric relaxation time longer, and early to late flow velocity ratio was reduced in relation to subjects from the original BH group with normal monitored BP levels (P<0.05). These subjects also presented an exaggerated BP response during the cold pressor test. These results support the notion of an integrated pattern of cardiac and vascular adaptation during the development of hypertension.

Forecasting financial weather - can we foresee market sentiment? Spectrum of stock price behavior - NYSE case study

The desire to create a statistical or mathematical model, which would allow predicting the future changes in stock prices, was born many years ago. Economists and mathematicians are trying to solve this task by applying statistical analysis and physical laws, but there are still no satisfactory results. The main reason for this is that a stock exchange is a non-stationary, unstable and complex system, which is influenced by many factors. In this thesis the New York Stock Exchange was considered as the system to be explored. A topological analysis, basic statistical tools and singular value decomposition were conducted for understanding the behavior of the market. Two methods for normalization of initial daily closure prices by Dow Jones and S&P500 were introduced and applied for further analysis. As a result, some unexpected features were identified, such as a shape of distribution of correlation matrix, a bulk of which is shifted to the right hand side with respect to zero. Also non-ergodicity of NYSE was confirmed graphically. It was shown, that singular vectors differ from each other by a constant factor. There are for certain results no clear conclusions from this work, but it creates a good basis for the further analysis of market topology.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.

Accuracy improvement of a demand forecasting model

This research concerns different statistical methods that assist to increase the demand forecasting accuracy of company X’s forecasting model. Current forecasting process was analyzed in details. As a result, graphical scheme of logical algorithm was developed. Based on the analysis of the algorithm and forecasting errors, all the potential directions for model future improvements in context of its accuracy were gathered into the complete list. Three improvement directions were chosen for further practical research, on their basis, three test models were created and verified. Novelty of this work lies in the methodological approach of the original analysis of the model, which identified its critical points, as well as the uniqueness of the developed test models. Results of the study formed the basis of the grant of the Government of St. Petersburg.

Spectral analysis of the electromyograph of the erector spinae muscle before and after a dynamic manual load-lifting test

The aim of the present study was to assess the spectral behavior of the erector spinae muscle during isometric contractions performed before and after a dynamic manual load-lifting test carried out by the trunk in order to determine the capacity of muscle to perform this task. Nine healthy female students participated in the experiment. Their average age, height, and body mass (± SD) were 20 ± 1 years, 1.6 ± 0.03 m, and 53 ± 4 kg, respectively. The development of muscle fatigue was assessed by spectral analysis (median frequency) and root mean square with time. The test consisted of repeated bending movements from the trunk, starting from a 45º angle of flexion, with the application of approximately 15, 25 and 50% of maximum individual load, to the stand up position. The protocol used proved to be more reliable with loads exceeding 50% of the maximum for the identification of muscle fatigue by electromyography as a function of time. Most of the volunteers showed an increase in root mean square versus time on both the right (N = 7) and the left (N = 6) side, indicating a tendency to become fatigued. With respect to the changes in median frequency of the electromyographic signal, the loads used in this study had no significant effect on either the right or the left side of the erector spinae muscle at this frequency, suggesting that a higher amount and percentage of loads would produce more substantial results in the study of isotonic contractions.