| 1. |
- Almberg, Wah-Sui
(author)
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Modelling Epidemic Influenza : A Novel Approach
- 2012
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Licentiate thesis (other academic/artistic)abstract
- Modellering av dynamiska förlopp i socio-biologiska komplexa system är långt ifrån trivialt. Behovet av fördjupad förståelse av sådana förlopp är många gånger stort. Vi har presenterat ett oortodoxt förslag på hur spridning av influensa i mänsklig population kan beskrivas och simuleras. Traditionellt använder man sig i huvudsak av två typer av modeller. Den ena bygger på matematiska strukturer där dynamiken beskrivs av kontinuerliga differentialförlopp mellan ett fåtal grovt uppdelade sektioner av populationen. Den andra bygger på diskreta förlopp inom visualiserade kontaktnätverk där varje enskild individ i populationen är representerad. Båda dessa metoder har styrkor såväl som svagheter. Bland svagheterna kan man framförallt lyfta fram svårigheterna med att förklara de flesta av influensans observerade epidemiologiska karaktärsdrag. Ett flertal idéer har framlagts för att förklara dessa anomalier. Bland dessa finns en hypotes som trots sin enkelhet skulle kunna förklara en majoritet av de epidemiologiska karaktärsdragen. Problemet med denna hypotes är dock att man inte kunnat hitta empiriska belägg för den. Vi tror att man kan nå närmare en lösning genom att omtolka signifikansen hos denna hypotes och den epidemiologiska karaktäristikan inom ramen för en annorlunda naturvetenskaplig ontologi. Denna omtolkning visar på en informationsbaserad såväl som fysiskt baserad verklighet. Vi menar då inte det traditionella informationsbegreppet som Claude Shannons teoretiserande bygger på, utan David Bohms `aktiva information', där informationen utgör en objektiv aktiv del av naturen, något som existerar oberoende av ett vetande medvetande eller en observatör. Bohm har gett den aktiva informationen en formell struktur i hans teori om det han kallar för `the implicate order'. Tillsammans med Basil Hiley visade han även att kvantmekaniken kan tolkas på ett sådant sätt att aktiv information utgör en fundamental aspekt av teorin, och att den därigenom även förenklas. Baserat på observationer som gjorts och våra resonemang har vi pekat på att en förståelse av epidemiologiska förlopp kanske kan nås genom att använda ett teoretiskt ramverk grundat på aktiv information. I en planerad kommande doktorsavhandling avser vi att presentera en matematisk modell som ytterligare kan underbygga vår hypotes.
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| 2. |
- Ghoorchian, Kambiz, 1981-
(author)
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Graph Algorithms for Large-Scale and Dynamic Natural Language Processing
- 2019
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Doctoral thesis (other academic/artistic)abstract
- In Natural Language Processing, researchers design and develop algorithms to enable machines to understand and analyze human language. These algorithms benefit multiple downstream applications including sentiment analysis, automatic translation, automatic question answering, and text summarization. Topic modeling is one such algorithm that solves the problem of categorizing documents into multiple groups with the goal of maximizing the intra-group document similarity. However, the manifestation of short texts like tweets, snippets, comments, and forum posts as the dominant source of text in our daily interactions and communications, as well as being the main medium for news reporting and dissemination, increases the complexity of the problem due to scalability, sparsity, and dynamicity. Scalability refers to the volume of the messages being generated, sparsity is related to the length of the messages, and dynamicity is associated with the ratio of changes in the content and topical structure of the messages (e.g., the emergence of new phrases). We improve the scalability and accuracy of Natural Language Processing algorithms from three perspectives, by leveraging on innovative graph modeling and graph partitioning algorithms, incremental dimensionality reduction techniques, and rich language modeling methods. We begin by presenting a solution for multiple disambiguation on short messages, as opposed to traditional single disambiguation. The solution proposes a simple graph representation model to present topical structures in the form of dense partitions in that graph and applies disambiguation by extracting those topical structures using an innovative distributed graph partitioning algorithm. Next, we develop a scalable topic modeling algorithm using a novel dense graph representation and an efficient graph partitioning algorithm. Then, we analyze the effect of temporal dimension to understand the dynamicity in online social networks and present a solution for geo-localization of users in Twitter using a hierarchical model that combines partitioning of the underlying social network graph with temporal categorization of the tweets. The results show the effect of temporal dynamicity on users’ spatial behavior. This result leads to design and development of a dynamic topic modeling solution, involving an online graph partitioning algorithm and a significantly stronger language modeling approach based on the skip-gram technique. The algorithm shows strong improvement on scalability and accuracy compared to the state-of-the-art models. Finally, we describe a dynamic graph-based representation learning algorithm that modifies the partitioning algorithm to develop a generalization of our previous work. A strong representation learning algorithm is proposed that can be used for extracting high quality distributed and continuous representations out of any sequential data with local and hierarchical structural properties similar to natural language text.
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| 3. |
- Hjelmblom, Magnus, 1973-
(author)
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Norm-Regulation of Agent Systems : Instrumentalizing an algebraic approach to agent system norms
- 2015
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Doctoral thesis (other academic/artistic)abstract
- An architecture for norm-regulated multi-agent systems based on an algebraic approach to normative systems is instrumentalized and further developed. The core of the instrumentalization is a Prolog module, which together with a Java library can be used for creating client/server-based runtime systems. Norms are represented as conditional sentences, whose normative consequences are formulated by applying normative operators to descriptive conditions. From such general normative conditions follow normative sentences regarding specific states of affairs. These in turn result in permission or prohibition of individual actions in specific situations. Furthermore, an approach to turning runtime systems into instruments for problem-solving by using evolutionary mechanisms for evolving normative systems, is presented. The construction of norm-creating operators on conditions, which forms the basis for the representation of normative systems, is approached from two angles. (i) A logical analysis based on the Kanger-Lindahl theory of normative positions is conducted. This results in two extended sets of types of normative positions, and based on an algebraic version of one of these extended systems, a set of operators for creating agent-specific norms is constructed. (ii) An alternative analysis, which takes as its starting point a systematic exploration of types of state transitions, yields a set of norm-creating operators based on prohibition of transition types. It is furthermore argued that in the context of a class of transition systems, in which transitions are deterministic and associated with a single agent performing an act, operators based on (ii) specify a meaningful semantics of operators based on (i). Theoretical results together with shared code and example applications contribute to make possible theoretically sound, transparently described, and efficiently implemented norm-regulated autonomous agent systems.
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| 4. |
- Cakici, Baki, 1984-
(author)
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The Informed Gaze : On the Implications of ICT-Based Surveillance
- 2013
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Doctoral thesis (other academic/artistic)abstract
- Information and communication technologies are not value-neutral. I examine two domains, public health surveillance and sustainability, in five papers covering: (i) the design and development of a software package for computer-assisted outbreak detection; (ii) a workflow for using simulation models to provide policy advice and a list of challenges for its practice; (iii) an analysis of design documents from three smart home projects presenting intersecting visions of sustainability; (iv) an analysis of EU-financed projects dealing with sustainability and ICT; (v) an analysis of the consequences of design choices when creating surveillance technologies. My contributions include three empirical studies of surveillance discourses where I identify the forms of action that are privileged and the values that are embedded into them. In these discourses, the presence of ICT entails increased surveillance, privileging technological expertise, and prioritising centralised forms of knowledge.
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| 5. |
- Corcoran, Diarmuid
(author)
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Systematic Data-Driven Continual Self-Learning
- 2023
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Doctoral thesis (other academic/artistic)abstract
- There is a lot of unexploited potential in using data-driven and self-learning methods to dramatically improve automatic decision-making and control in complex industrial systems. So far, and on a relatively small scale, these methods have demonstrated some potential to achieve performance gains for the automated tuning of complex distributed systems. However, many difficult questions and challenges remain in relation to how to design methods and organise their deployment and operation into large-scale real-world systems. For systematic and scalable integration of state-of-the-art machine learning into such systems, we propose a structured architectural approach.To understand the essential elements of this architecture, we identify a set of foundational challenges and then derive a set of five research questions. These questions drill into the essential and complex interdependency between data streams, self-learning algorithms that never stop learning and the supporting reference and run-time architectural structures. While there is a need for traditional one-shot supervised models, pushing the technical boundaries of automating all classes of machine learning model training will require a continual approach. To support continual learning, real-time data streams are complemented with accurate synthetic data generated for use in model training. By developing and integrating advanced simulations, models can be trained before deployment into a live system, for which system accuracy is then measured quantitatively in realistic scenarios. Reinforcement learning, exploring an action space and qualifying effective dynamic action combinations, is here employed for effective network policy learning. While single-agent and centralised model training may be appropriate in some cases, distributed multi-agent self-learning is essential in industrial scale systems, and thus such a scalable and energy-efficient approach is developed, implemented and analysed in detail. Energy usage minimisation in software and hardware intense communication systems, such as the 5G radio access system, is an important and difficult problem in its own right. Our work has focused on energy-aware approaches to applying self-learning methods both to energy reduction applications and algorithms. Using this approach, we can demonstrate clear energy savings while at the same time improving system performance.Perhaps most importantly, our work attempts to form an understanding of the broader industrial system issues of applying self-learning approaches at scale. Our results take some clear, formative, steps towards large-scale industrialisation of self-learning approaches in communication systems such as 5G.
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| 6. |
- Gogoulou, Evangelia, et al.
(author)
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Predicting treatment outcome from patient texts : The case of internet-based cognitive behavioural therapy
- 2021
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In: EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. - : Association for Computational Linguistics (ACL). - 9781954085022 ; , s. 575-580
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Conference paper (peer-reviewed)abstract
- We investigate the feasibility of applying standard text categorisation methods to patient text in order to predict treatment outcome in Internet-based cognitive behavioural therapy. The data set is unique in its detail and size for regular care for depression, social anxiety, and panic disorder. Our results indicate that there is a signal in the depression data, albeit a weak one. We also perform terminological and sentiment analysis, which confirm those results. © 2021 Association for Computational Linguistics
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| 7. |
- Odelstad, Jan
(author)
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Many-Sorted Implicative Conceptual Systems
- 2008
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Doctoral thesis (other academic/artistic)abstract
- A theory of many-sorted implicative conceptual systems (abbreviated msic-systems) is presented. Examples of msic-systems include legal systems, normative systems, systems of rules and instructions, and systems expressing policies and various kinds of scientific theories. In computer science, msic-systems can be used in, for instance, legal information systems, decision support systems, and multi-agent systems. In the thesis, msic-systems are studied from a logical and algebraic perspective aiming at clarifying their structure and developing effective methods for representing them. Of special interest are the most narrow links or joinings between different strata in a system, that is between subsystems of different sorts of concepts, and the intermediate concepts intervening between such strata. Special emphasis is put on normative systems, and the role that intermediate concepts play in such systems, with an eye on knowledge representation issues. Normative concepts are constructed out of descriptive concepts using operators based on the Kanger-Lindahl theory of normative positions. An abstract architecture for a norm-regulated multi-agent system is suggested, containing a scheme for how normative positions will restrict the set of actions that the agents are permitted to choose from. Technical results inlude a characterization of an msic-system in terms of the most narrow joinings between different strata, characterization of the structure of the most narrow joinings between two strata, conditions for the extendability of intermediate concepts, and finally, a specification of the conditions such that the Boolean operations on intermediate concepts will result in intermediate concepts and characterization of most narrow joinings in terms of weakest grounds and strongest consequences.
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| 8. |
- Stenebrand, Agneta
(author)
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Dental anxiety among 15-year-olds : Psychosocial factors and oral health
- 2015
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Doctoral thesis (other academic/artistic)abstract
- AIM: The overall aim of this thesis was to examine the associations between dental anxiety, experiences of dental care, psychosocial factors and oral health among 15-year-olds, and to analyse changes in the prevalence of dental anxiety over time.MATERIALS AND METHODS: The thesis was based on two cross-sectional epidemiological studies in Jönköping, Sweden. Papers I, II, and III were based on a random sample of 15-year-old individuals. The total sample consisted of 221 individuals. Six questionnaires were used, one included items of background data, while the others were psychometric instruments measuring dental anxiety, temperament, general anxiety and depression, general fearfulness and attitudes to dental care. Paper IV was based on the Jönköping studies, a series of epidemiological studies from 1973, 1983, 1993, and 2003 in which random samples of 15-year-old individuals were included. The total sample consisted of 405 individuals. Questionnaires including background data and dental anxiety were used and clinical data were collected.RESULTS: Of the 15-year-old individuals 6.5% were classified as dentally anxious with girls proportionally more fearful than boys (Papers I-III). Dental anxiety correlated significantly with three of the temperament dimensions; emotionality, activity and impulsivity. Reported pain or unpleasant experiences during dental care treatment were clear predictors concerning dental anxiety (Paper I). Both symptoms of general anxiety and depression were significantly correlated with dental anxiety after controlling for other potential risk factors (Paper II). Dental anxiety was associated with both general fearfulness and with attitudes to dental care, where the strongest predictor of dental anxiety was general fearfulness (Paper III). A trend analysis over the 30-year period showed a gradient of statistically significantly decreasing dental anxiety prevalence, from 38.1% in 1973 to 12.8% in 2003. Over the period the 15-year-old individuals with dental anxiety had significantly higher number of filled tooth-surfaces than those with no dental anxiety, and also more caries in 1973. There were no such differences concerning plaque and gingivitis (Paper IV).CONCLUSIONS: Dental anxiety in 15-year-olds correlated with experiences of dental care, psychosocial factors as well as to oral health. Specifically, pain experiences related to dental care, attitudes to dental care and general fearfulness seem to have the strongest impact on dental anxiety. Dental anxiety showed a clear declining change over time. More girls than boys reported dental anxiety. The thesis shows that dental care providers need paying attention on providing a supportive dental care situation, in which the patients should not experience pain. One part may be adequate local anaesthesia during operative dentistry or similar dental treatments. Another part may be a good oral health to prevent negative experiences of dental care. There is a need for the understanding of psychological factors associated with dental care procedures.
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| 9. |
- Boberg, Julia, et al.
(author)
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Swedish multimodal cohort of patients with anxiety or depression treated with internet-delivered psychotherapy (MULTI-PSYCH)
- 2023
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In: BMJ Open. - : BMJ Publishing Group Ltd. - 2044-6055. ; 13:10
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Journal article (peer-reviewed)abstract
- Purpose Depression and anxiety afflict millions worldwide causing considerable disability. MULTI-PSYCH is a longitudinal cohort of genotyped and phenotyped individuals with depression or anxiety disorders who have undergone highly structured internet-based cognitive-behaviour therapy (ICBT). The overarching purpose of MULTI-PSYCH is to improve risk stratification, outcome prediction and secondary preventive interventions. MULTI-PSYCH is a precision medicine initiative that combines clinical, genetic and nationwide register data.Participants MULTI-PSYCH includes 2668 clinically well-characterised adults with major depressive disorder (MDD) (n=1300), social anxiety disorder (n=640) or panic disorder (n=728) assessed before, during and after 12 weeks of ICBT at the internet psychiatry clinic in Stockholm, Sweden. All patients have been blood sampled and genotyped. Clinical and genetic data have been linked to several Swedish registers containing a wide range of variables from patient birth up to 10 years after the end of ICBT. These variable types include perinatal complications, school grades, psychiatric and somatic comorbidity, dispensed medications, medical interventions and diagnoses, healthcare and social benefits, demographics, income and more. Long-term follow-up data will be collected through 2029.Findings to date Initial uses of MULTI-PSYCH include the discovery of an association between PRS for autism spectrum disorder and response to ICBT, the development of a machine learning model for baseline prediction of remission status after ICBT in MDD and data contributions to genome wide association studies for ICBT outcome. Other projects have been launched or are in the planning phase.Future plans The MULTI-PSYCH cohort provides a unique infrastructure to study not only predictors or short-term treatment outcomes, but also longer term medical and socioeconomic outcomes in patients treated with ICBT for depression or anxiety. MULTI-PSYCH is well positioned for research collaboration.
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| 10. |
- Boman, Anna
(author)
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Ekonomisk tillväxtmotor : Mälardalsrådets konstruktion av regional utveckling
- 2008
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Licentiate thesis (other academic/artistic)abstract
- As current capital accumulates in more flexible ways and is more often than before distinguished from national states, the options and possibilities for governments to control these financial flows change. Establishing regions and regional cooperation are seen as ways for governments to ensure continued economic growth. At these regional levels significant discussions on the development of society in general, and on the idea of sustainable development in particular, take place. However, there are also academic concepts arguing that current economic growth is in fact unsustainable. These concepts suggest an expansion of the current economic order.In this licentiate thesis the reader will meet Mälardalsrådet, the Council of the Mälar Region, a non-profit association for regional cooperation in the region of Mälardalen. In this study the activity of the Council of the Mälar Region will be understood as communication including ideas, statements, views and arguments.Based on a critical social science point of view this study has been inspired by discourse analysis, where language is seen as a major force. The purpose of this study is to highlight how the Council of the Mälar Region communicate development ideas in areas of economy, environment and sustainable development. This is done by identifying and analysing the Council’s communication on regional development.Behind the vision of growth communicated by the Council of the Mälar Region there is a deeper dimension of uncertainty for the changed social and economical conditions, but maybe the insecurity ends right there. While we should not forget that sustainability has been included in the discussion of growth, the ecological dimension of sustainability has become increasingly anonymous and a part of the national and international dominating consensus of growth and the environment.
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