Non-destructive technologies have been applied on predicting the stiffness and strength properties of timber for decades. However, these technologies have rarely been investigated on predicting the properties of thermally modified timber. This study was performed to investigate the non-destructive technologies on estimating of the strength and stiffness properties of thermally modified timber. The material that was utilized for study is full-size structural Norway spruce. Twenty-five thermally modified boards were investigated by applying both non-destructive technologies and static bending test; 25 unmodified boards were used as a control group. Timber grader MTG and Sylvatest Trio are two non-destructive tools that were used for the determining the modulus of elasticity (MOE): MTG is an application of resonance frequency technology and Sylvatest Trio is an application of time-of-flight technology (TOF). The results show that both non-destructive technologies provide good results (??2=0.70 from MTG and??2=0.58 from Sylvatest Trio) on estimating the stiffness properties while poor resultson predicting the strength properties of thermally modified boards.The result shows anoverestimation of modulus of elasticity (MOE) from time-of-flight test compared withthe MOEs gathered from static bending test and resonance frequency test for both thermally modified boards and unmodified ones. The stiffness properties of boards after thermal modification reduced slightly (6.5%) compared with unmodified timbers; while strength properties of thermally modified boards decreased (37.5%) significantlycompared with control group.This study is a part of a bigger study performed at Linneaus University by Joran vanBlokland.

Credit risk analysis is an important topic in financial risk management. Financial institutions (e.g. commercial banks) that grant consumers credit need reliable models that can accurately detect and predict defaults. This research investigates the ability of artificial neural networks as a decision support system that can automatically detect and predict “bad” credit risks based on customers demographic, biographic and behavioural characteristics. The study focuses specifically on the learning vector quantization neural network algorithm. This thesis contains a short overview of credit scoring models, an introduction to artificial neural networks and their applications and presents the performance evaluation results of a credit risk detection model based on learning vector quantization networks.

The objective of this research is to investigate how mobile cellular network operators can increase the average revenue per user by stimulating the usage of mobile broadband services. There is a general consensus that the revenue from voice calls is slowly reaching saturation; hence, mobile cellular operators, service providers and content providers are looking for other sources of revenue from their new and existing customers. They are therefore beginning to focus more intensively on customer retention and on developing new strategies that will stimulate the usage of high speed mobile data services. The research shows that most people are aware of many of the mobile data services offered by operators, but that they thought that they were unreliable, slow, difficult to use and expensive. By and large, people signed up for mobile data services because they wanted a mobile always-on connection anytime, anywhere, with faster speed when accessing e-mail and other services or when downloading data from the Internet. The majority of people would use mobile broadband internet service if it cost less to use; if the speed were faster and the service were easy to use; if the cellular phone had a larger screen and used less battery power; and if the keyboard were larger. The relationship between Network operators, WASPs and content providers was found to be good, even though at times it is strained by the increased competition between them; this forces them not to cooperate on some issues for fear of compromising their competitive advantage.

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The continuous growth of the gaming industry develops a highly competitive environment, which provides an incubator of innovation. These conditions lead to the emergence of new business models. Free to play as one of those newly and still developing models is currently trending among the game developing and publishing companies. Delivering skyrocketing profits, the full potential of the model is yet to be revealed. At first sight, the model has a simplistic structure on the business side, however, on the user side it is unclear what motivates players to become customers through the purchase of digital items in the games. This research uses an exploratory and qualitative approach to collect data and identify purchasing behaviour stimuli. It also proposes an option of connecting personality theories as a possible explanation to the purchasing behaviour of players. As a focus for this study, the currently most successful free to play game, League of Legends, was selected and twelve interviews with League of Legends players were conducted. The interviews consisted of two parts, one semi-structured and the other one structured. The semi-structured interview aimed at identifying purchasing behaviour and finding reasons for the purchase of digital items in League of Legends. The second was a personality assessment test, Keirsey Temperament Sorter2. A conventional content analysis of the interviews identified the theme “personal satisfaction” as the main motivation for purchasing digital items. The investigation regarding the proposed connection to personality theory, the research’s results fail to show any connection. However, answering research question number one unveils the importance of the personality factor remains valid and a subject of future research. The research discusses possibilities and direction for future research in the face of testing other than the applied Keirsey personality theory.

The stabilising wall element of the Trä8-system is a deep box-type beam/column element which is made of different types of timber composites including framing members of gluedlaminated timber (glulam) and sheathings of laminated veneer lumber (LVL). This element is used as a ―shear wall‖ in multi-storey buildings up to four storeys. To be able to optimise thecomposite stabilising element and use its maximum potential and efficiency, it is necessary to have sufficient fundamental knowledge and information about the structural behaviour and influences of different mechanical properties and geometrical parameters and dimensions of the sub-elements.In this thesis, structural analysis and design principles of the Trä8 stabilising wall element are discussed, including the early stage of erection during assembly to the final usage and residence. A list of required fundamental basic analyses are presented, including accurate deflection analysis for the serviceability limit state, local pre- and post-buckling of the LVL sheathings, global buckling as well as the lateral-torsional buckling of the stabilising element in different design situations. This thesis is then focused on deformations and local instability. For each type of structural problem, accurate, but simple and general methodology is employed to incorporate a large number of effective geometric and property parameters. In this way, a fast evaluation of the influence of different parameters is possible for a wide range of values without needing several time-consuming 3-D finite element (FE) simulations. In several cases, the accuracy and validity of the obtained solutions and formulae are examined and confirmed by comparing their results to those based on the 3-D FE simulations. First, different composite beam theories including shear effects are employed for deflection analysis of the stabilising timber element. Next, an accurate energy-based methodology isdeveloped rendering an explicit formula that gives accurate predictions for the deflection of the stabilising element within a medium range of sheathing or web thicknesses and/or stiffnesses. For weak shear webs, however, this model is not sufficient. Therefore, another new model based on the partial composite interaction theory is developed for accurate deflection predictions of the element having weak shear webs. This model contains simple but accurate formulae for deflection analysis of any similar composite box-type of element with an arbitrary range of geometry and property parameters.Next, shear buckling of the rectangular LVL-panel between the framing members are analysed using differential quadrature (DQ) numerical technique as well as an explicit analytical solution and a formula is established for accurate and fast prediction of the shear pre-buckling of the LVL. This study is extended by considering the effect of each individual lamina of the LVL as well as general orthotropic material properties using a laminated theoryand the DQ solution approach. Further, the post-buckling of the LVL panel is studied based on a simple analytical method with rotating stress fields together with the accurate 3-D FE simulations. A simple formula is then proposed for accurate prediction of the shear post-buckling resistance of the LVL-panel in the stabilising element. As a result of the thesis concerning the two main focus areas, deformations and local instability, explicit analytical formulae are presented for the design of the box-type stabilisingelement with respect to deflections including shear effects in the serviceability limit state and with respect to local shear buckling of the sheathings of the stabilising element including the post-critical area in the ultimate limit state. / <p>Godkänd; 2016; 20160217 (rasata); Nedanstående person kommer att disputera för avläggande av teknologie doktorsexamen. Namn: Seyed Rasoul Atashipour Ämne: Träbyggnad/Timber Structures Avhandling: Structural Analysis of Deep Composite Box-Type Components With Application to a Proprietary Stabilising Timber Wall Element Opponent: Professor Per Johan Gustafsson, Avd för byggnadsmekanik, Lunds tekniska högskola, Lunds universitet, Lund. Ordförande: Professor Ulf Arne Girhammar, Avd för byggkonstruktion- och produktion, Institutionen för samhällsbyggnad och naturresurser, Luleå tekniska universitet, Luleå Tid: Fredag 18 mars, 2016 kl 10.00 Plats: F1031, Luleå tekniska universitet</p>

Truck drivers often have a tight time schedule and therefore need to carry out several in-vehicle tasks while driving, such as making phone calls, writing down information and navigating to new places. Performing these tasks using a visual-manual interface can impose visual distraction which has been shown to lead to safety-critical events on the roads. Instead of using a visual-manual interface, a speech interface could be a safer alternative if designed properly. However, the cognitive load demanded by speech interfaces and the connection between cognitive load and driving behaviour is not fully understood. In this study, a speech interface and its visual-manual counterpart were evaluated and compared in terms of visual distraction, cognitive load and user efficiency and perceived acceptance. Eye tracking was used to measure visual distraction. The measurements used for cognitive load were the Tactile Detection Response task (TDRT) and the Driving Activity Load Index (DALI). Perceived acceptance and efficiency were measured using the System Usability Scale (SUS), the Subjective Assessment of Speech Systems (SASSI) and semi-structured interviews. The conclusions were that (1) the speech interface was less visually distracting than the visual-manual counterpart, (2) the speech interface was less cognitively demanding than the visual-manual interface, especially in the navigation task, (3) the speech interface was safer to use while driving compared to the visual-manual interface and (4) the speech interface had higher user acceptance and perceived efficiency than the visual-manual interface. Further research should investigate the connection between cognitive load and driving behaviour, such as lane keeping and brake response time, by employing a variety of speech tasks with various complexity as well as including speech interfaces entirely free from visual demand. The focus should be on the difference between baseline driving and speech interaction, as opposed to speech interaction and visual-manual interaction.

This thesis records the design and development of an electrically driven, air to water, vapour compression heat pump of nominally 6kW heat output, for residential space heating. The study was carried out on behalf of GEC Research Ltd through the Interdisciplinary Higher Degrees Scheme at Aston University. A computer based mathematical model of the vapour compression cycle was produced as a design aid, to enable the effects of component design changes or variations in operating conditions to be predicted. This model is supported by performance testing of the major components, which revealed that improvements in the compressor isentropic efficiency offer the greatest potential for further increases in cycle COPh. The evaporator was designed from first principles, and is based on wire-wound heat transfer tubing. Two evaporators, of air side area 10.27 and 16.24m2, were tested in a temperature and humidity controlled environment, demonstrating that the benefits of the large coil are greater heat pump heat output and lower noise levels. A systematic study of frost growth rates suggested that this problem is most severe at the conditions of saturated air at 0oC combined with low condenser water temperature. A dynamic simulation model was developed to predict the in-service performance of the heat pump. This study confirmed the importance of an adequate radiator area for heat pump installations. A prototype heat pump was designed and manufactured, consisting of a hermetic reciprocating compressor, a coaxial tube condenser and a helically coiled evaporator, using Refrigerant 22. The prototype was field tested in a domestic environment for one and a half years. The installation included a comprehensive monitoring system. Initial problems were encountered with defrosting and compressor noise, both of which were solved. The unit then operated throughout the 1985/86 heating season without further attention, producing a COPh of 2.34.

Credit risk analysis is an important topic in financial risk management. Financial institutions (e.g. commercial banks) that grant consumers credit need reliable models that can accurately detect and predict defaults. This research investigates the ability of artificial neural networks as a decision support system that can automatically detect and predict “bad” credit risks based on customers demographic, biographic and behavioural characteristics. The study focuses specifically on the learning vector quantization neural network algorithm. This thesis contains a short overview of credit scoring models, an introduction to artificial neural networks and their applications and presents the performance evaluation results of a credit risk detection model based on learning vector quantization networks.

Agile software development has emerged as a response to the rapidly changing software environment and the need to anticipate late change of requirements. An important tool for many agile methods is a projec tmanagement application with a task board to keep track of the progress. However, it can be difficult to find a project management applicationthat is suited for a workplace where development teams use different methods. The aim of this master thesis was to develop a prototype of a project management application adapted to Codemill AB where development teams use different agile methods. To achieve this, the work process of development teams were investigated, as well as existing project management applications, and the most important functionality and features from a user available point of view were identified. Two design concepts were developed based on the users’ needs. Both concepts were tested and compared by end users in order to develop a refined prototype with the best parts from both concepts. The results indicate that the development process in a workplace can vary a lot between different development teams even though their methods are inspired by the same framework. A project management application for agile software development must be flexible enough to handle these differences without becoming too complex and difficult to use. None of the investigated applications achieved this balance. This work aimed to develop a prototype of an application that fills this gap, with the users' needs in focus. The findings in this thesis are based on Codemill’s needs, however, they could also be considered by others with similar needs.