Matrix Mind : on managerial reframing in multidimensional problem solving

Det är inte ovanligt att man i organisationer ställs inför problem som inte kan hanteras inom befintlig organisationsstruktur. Skälen kan vara att frågorna har många – ibland konflikterande – dimensioner och perspektiv som samtidigt måste beaktas. I den här avhandlingen studeras vilka tankemönster och föreställningar som fanns när grupper av chefer försökte lösa komplexa problem, som inte hade en naturlig organisatorisk hemvist och hur de omsatte dessa tankemönster i handling. Vad kännetecknade det ledarskap som utövades under problemlösningsprocessen? Avhandlingens empiri hämtas från ledarutvecklingsprogram i två internationellt verksamma företag i Sverige, och omfattar 14 verkliga affärsproblem i dessa företag och den process varigenom de löstes. De 14 seminarierna utgör exempel på hur mångdimensionella frågeställningar framgångsrikt hanteras utanför den befintliga organisationsstrukturen. Studien ger, genom att adressera frågor kring tankesätt och ledningsprocesser, en djupare förståelse för förutsättningarna för detta, och lyfter särskilt fram betydelsen av ett ledarskap som inbegriper begreppen intervention, förmåga och omtolkning. Som ett samlat begrepp introduceras bilden att utöva ledarskapet utifrån ett matrix mind. Att påverka strukturer (i vid mening) och därigenom de förmågor som utvecklas, är del i detta ledarskap. Det sker genom interventioner (ingrepp som påverkar relationer i t ex en grupp) och baserades i den aktuella empirin på uppfattningar om värdet av problematisering, erfarenhetsutbyte och av ett språk, som både beskriver och anger inriktning för aktiviteter. Interventioner i strukturer (och till dem knutna processer) beskriver dock bara delvis detta ledarskap. Att leda med ett matrix mind innefattar också ett nyfiket och kreativt förhållningssätt, och att utifrån detta leda omtolkning av problem. I empirin finns flera exempel på detta. Avhandlingen avser att ge ett bidrag inom såväl organisations- som ledarskapsteori.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Situationsfaktorer i sexuellt utnyttjande av barn inverkar på psykosexuella problem : en metaanalys

Pro graduavhanlingens svenska sammanfattning

Ethical research as the target of animal extremism: an international problem

Animal extremism has been increasing worldwide; frequently researchers are the targets of actions by groups with extreme animal rights agendas. Sometimes this targeting is violent and may involve assaults on family members or destruction of property. In this article, we summarize recent events and suggest steps that researchers can take to educate the public on the value of animal research both for people and animals

Generalization of temporal order detection skill learning: two experimental studies of children with dyslexia

The objective of this study was to investigate the phenomenon of learning generalization of a specific skill of auditory temporal processing (temporal order detection) in children with dyslexia. The frequency order discrimination task was applied to children with dyslexia and its effect after training was analyzed in the same trained task and in a different task (duration order discrimination) involving the temporal order discrimination too. During study 1, one group of subjects with dyslexia (N = 12; mean age = 10.9 ± 1.4 years) was trained and compared to a group of untrained dyslexic children (N = 28; mean age = 10.4 ± 2.1 years). In study 2, the performance of a trained dyslexic group (N = 18; mean age = 10.1 ± 2.1 years) was compared at three different times: 2 months before training, at the beginning of training, and at the end of training. Training was carried out for 2 months using a computer program responsible for training frequency ordering skill. In study 1, the trained group showed significant improvement after training only for frequency ordering task compared to the untrained group (P < 0.001). In study 2, the children showed improvement in the last interval in both frequency ordering (P < 0.001) and duration ordering (P = 0.01) tasks. These results showed differences regarding the presence of learning generalization of temporal order detection, since there was generalization of learning in only one of the studies. The presence of methodological differences between the studies, as well as the relationship between trained task and evaluated tasks, are discussed.

Scalable Feature Selection Applications for Genome-Wide Association Studies of Complex Diseases

Personalized medicine will revolutionize our capabilities to combat disease. Working toward this goal, a fundamental task is the deciphering of geneticvariants that are predictive of complex diseases. Modern studies, in the formof genome-wide association studies (GWAS) have afforded researchers with the opportunity to reveal new genotype-phenotype relationships through the extensive scanning of genetic variants. These studies typically contain over half a million genetic features for thousands of individuals. Examining this with methods other than univariate statistics is a challenging task requiring advanced algorithms that are scalable to the genome-wide level. In the future, next-generation sequencing studies (NGS) will contain an even larger number of common and rare variants. Machine learning-based feature selection algorithms have been shown to have the ability to effectively create predictive models for various genotype-phenotype relationships. This work explores the problem of selecting genetic variant subsets that are the most predictive of complex disease phenotypes through various feature selection methodologies, including filter, wrapper and embedded algorithms. The examined machine learning algorithms were demonstrated to not only be effective at predicting the disease phenotypes, but also doing so efficiently through the use of computational shortcuts. While much of the work was able to be run on high-end desktops, some work was further extended so that it could be implemented on parallel computers helping to assure that they will also scale to the NGS data sets. Further, these studies analyzed the relationships between various feature selection methods and demonstrated the need for careful testing when selecting an algorithm. It was shown that there is no universally optimal algorithm for variant selection in GWAS, but rather methodologies need to be selected based on the desired outcome, such as the number of features to be included in the prediction model. It was also demonstrated that without proper model validation, for example using nested cross-validation, the models can result in overly-optimistic prediction accuracies and decreased generalization ability. It is through the implementation and application of machine learning methods that one can extract predictive genotype–phenotype relationships and biological insights from genetic data sets.

The nature and role of trust in temporary virtual problem-solving teams

The objective of this study is to increase understanding of the nature and role of trust in temporary virtual problem-solving teams engaged in real-life co-creation activities, while much of previous research has been conducted in student settings. The different forms and bases of trust, possible trust barriers and trust building actions, and perceived role of trust in knowledge sharing and collaboration are analyzed. The study is conducted as a qualitative case study in case company. Data includes interviews from 24 people: 13 from 3 different project teams that were going on during the study, 8 from already finalized project teams, and 3 founders of case company. Additional data consists of communication archives from three current teams. The results indicate that there were both knowledge-based and swift trust present, former being based on work-related personal experiences about leaders or other team members, and latter especially on references, disposition to trust and institution-based factors such as norms and rules, as well as leader and expert action. The findings suggest that possible barriers of trust might be related to lack of adaptation to virtual work, unclear roles and safety issues, and nature of virtual communication. Actions that could be applied to enhance trust are for example active behavior in discussions, work-related introductions communicating competence, managerial actions and face-to-face interaction. Finally, results also suggest that trust has a focal role as an enabler of action and knowledge sharing, and coordinator of effective collaboration and performance in temporary virtual problem-solving teams.

'TINA', Aids, and the underdevelopment problem in Africa

The assumption that 'There Is No Alternative' (TINA) to capitalism as practiced in the United States of America and Western Europe has been the bane of aids effectiveness in assisting to solve the underdevelopment problem in Africa. This paper attempts to show that except there is a fundamental reorientation in the conceptualization of capitalism-free market and democracy-the underdevelopment problem would only be further complicated with aids.

Datenherrschaft – an Ethically Justified Solution to the Problem of Ownership of Patient Information

Patient information systems are crucial components for the modern healthcare and medicine. It is obvious that without them the healthcare cannot function properly – one can try to imagine how brain surgery could be done without using information systems to gather and show information needed for an operation. Thus, it can be stated that digital information is irremovable part of modern healthcare. However, the legal ownership of patient information lacks a coherent and justified basis. The whole issue itself is actually bypassed by controlling pa- tient information with different laws and regulations how patient information can be used and by whom. Nonetheless, the issue itself – who owns the patient in- formation – is commonly missed or bypassed. This dissertation show the problems if the legislation of patient information ownership is not clear. Without clear legislation, the outcome can be unexpected like it seems to be in Finland, Sweden and United Kingdom: the lack of clear regulation has come up with unwanted consequences because of problematic Eu- ropean Union database directive implementation in those countries. The legal ownership is actually granted to the creators of databases which contains the pa- tient information, and this is not a desirable situation. In healthcare and medicine, we are dealing with issues such as life, health and information which are very sensitive and in many cases very personal. Thus, this dissertation leans on four philosophical theories form Locke, Kant, Heidegger and Rawls to have an ethically justified basis for regulating the patient infor- mation in a proper way. Because of the problems of property and ownership in the context of information, a new concept is needed and presented to replace the concept of owning, that concept being Datenherrschaft (eng. mastery over in- formation). Datenherrschaft seems to be suitable for regulating patient infor- mation because its core is the protection of one’s right over information and this aligns with the work of the philosophers whose theories are used in the work. The philosophical argumentation of this study shows that Datenherrschaft granted to the patients is ethically acceptable. It supports the view that patient should be controlling the patient information about themselves unless there are such specific circumstance that justifies the authorities to use patient information to protect other people’s basic rights. Thus, if the patients would be legally grant- ed Datenherrschaft over patient information we would endorse patients as indi- viduals who have their own and personal experience of their own life and have a strong stance against any unjustified paternalism in healthcare. Keywords: patient information, ownership, Datenherrschaft, ethics, Locke, Kant, Heidegger, Rawls

Exploring knowledge worker motivation in autonomous and interdependent problem solving tasks on virtual platforms

The objective of this study is to understand why virtual knowledge workers conduct autonomous tasks and interdependent problem solving tasks on virtual platforms. The study is qualitative case study including three case organizations that tap the knowledge of expert networks, and utilize virtual platforms in the work processes. Research data includes 15 interviews, that is, five experts from each case company. According to the findings there are some specific characteristics in motivation to work on tasks on online platforms. Autonomy, self-improvement, meaningful tasks, knowledge sharing, time management, variety of contacts, and variety of tasks, and projects motivate virtual knowledge workers. Factors that may enhance individuals’ engagement to work on tasks are trust, security of continuous task flow and income, feedback, meaningful tasks and tasks that contribute to self-improvement, flexibility and effectiveness in time management, and virtual tools that support social interaction. The results also indicate that there are some differences in individuals’ motivation based on the tasks’ nature. That is, knowledge sharing and variety of contacts motivated experts who worked on interdependent problem solving tasks. Then again, autonomy and variety of tasks motivated experts who worked on autonomous tasks.

The quality of the mother-child relationship during collaborative problem solving /

The quality of the mother-child relationship was examined in relation to joint planning, maternal teaching strategies, maternal emotional support, mutual positive affect and attachment security. Fifty-five grade five children and their mothers participated in a laboratory session comprised of various activities and completed questionnaires to evaluate attachment security. Joint planning and social problem solving were assessed observationally during an origami task. Problem solving effectiveness was unrelated to maternal teaching strategies, maternal encouragement and mutual positive affect. A marginally significant relationship was found between maternal encouragement and active child participation. Attachment security was found to be significantly related to sharing of responsibility during local planning, but only for child autonomous performance. An examination of conditional probabilities revealed that mutual positive affect did not increase the likelihood of subsequent mother-child dyadic regulation. However, mutual positive affect was found to be significantly related to both active child participation and dyadic regulation. The hypothesis predicting a mediational model was not supported. The implications of these findings in the theoretical and empirical literature were considered and suggestions for future research were made.

Vulnerability to adverse consequences of drinking and problem drinker status as predicted by risky drinking behaviours, drug use, sex differences and affect : a test of multiple models /

Although alcohol problems and alcohol consumption are related, consumption does not fully account for differences in vulnerability to alcohol problems. Therefore, other factors should account for these differences. Based on previous research, it was hypothesized that risky drinking behaviours, illicit and prescription drug use, affect and sex differences would account for differences in vulnerability to alcohol problems while statistically controlling for overall alcohol consumption. Four models were developed that were intended to test the predictive ability of these factors, three of which tested the predictor sets separately and a fourth which tested them in a combined model. In addition, two distinct criterion variables were regressed on the predictors. One was a measure of the frequency that participants experienced negative consequences that they attributed to their drinking and the other was a measure of the extent to which participants perceived themselves to be problem drinkers. Each of the models was tested on four samples from different populations, including fIrst year university students, university students in their graduating year, a clinical sample of people in treatment for addiction, and a community sample of young adults randomly selected from the general population. Overall, support was found for each of the models and each of the predictors in accounting for differences in vulnerability to alcohol problems. In particular, the frequency with which people become intoxicated, frequency of illicit drug use and high levels of negative affect were strong and consistent predictors of vulnerability to alcohol problems across samples and criterion variables. With the exception of the clinical sample, the combined models predicted vulnerability to negative consequences better than vulnerability to problem drinker status. Among the clinical and community samples the combined model predicted problem drinker status better than in the student samples.

Online problem-based learning : perceptions of nursing educators /

A qualitative study was conducted to detennine 5 nursing educators' perceptions about the online application of a problem-based learning strategy in undergraduate nursing education. The question asked in the study was: Can the essential elements of face-to-face problem-based learning be supported in an online format? The data for this study came from 2 individual tape-recorded interviews with each of the 5 participants over a 3-month period and from a researchjournaI. The educators felt that student-centered learning and critical thinking could be supported within an online format. However, they noted that challenges could exist in terms of developing tutor roles, fostering student self-direction, facilitating group process and connections, and incorporating a nursing philosophy of online learning. The importance of tailoring an online problem-based learning course to reflect educators' philosophies and values in nursing emerged as an important theme from the interview responses. Overall, the participants suggested that an ideal environment would blend both face-to-face and online elements and that fewer elements would be offered in the first 2 years of the nursing program. They described a hybrid model of problem-based learning in which the online component could be used to support face-to-face sessions.