Problem: Vilka faktorer är avgörande för kulturföretagarens förutsättningar att förena det konstnärliga skapandet med överlevnad som företagare? Syfte: Det övergripandet syftet med denna uppsats är att analyser och utvärdera kulturföretagares marknadsstrategier med avseende på deras förutsättningar att förena konstnärligt skapande med överlevnad. Studiens underliggande syfte består i att analysera och utvärdera kulturspecifika starthus och deras inverkan på kulturföretagares marknadsstrategier. Metod: Studien utgår från en hermeneutisk, kvalitativ och deduktiv forskningsansats. Studien använder sig av metodtriangulering och empiri samlas in med hjälp av surveyundersökning med semistrukturerade intervjuer. Intervjuerna har hållits med sex stycken kulturföretagare, där hälften startats upp via kulturspecifika starthus och hälften startats upp på egen hand. Teorier: Studien använder sig av följande teorier; involveringsteorin, Värdekedja/Värdestjärna samt Industriella nätverk. Dessa förenas i en teoretisk syntes där transaktionsmarknadsförings- och relationsmarknadsföringsperspektiven ställs emot varandra. Empiri: Empirin består enbart av primärdata, där majoriteten förvärvats via intervjuer med de sex kulturföretagarna. Resterande data har erhållits under studiens förstudie, och har främst använts som förförståelse. Slutsats: Studiens resultat tyder på att kulturföretagare har bäst förutsättningar att förena det konstnärliga skapandet med långsiktig överlevnad genom att bedriva samarbeten i nätverksform. Anledningen till detta är att kulturföretagare upplever att det konstnärliga skapandet inte kan upprätthållas om de inte till största del får ägna sig åt den konstnärliga processen. Nätverkssamarbeten möjliggör detta då de utgör en, i kulturföretagarens ögon, skyddande vägg mellan de själva och slutkonsumentens åsikter och önskemål. Studiens resultat kan även tolkas som att det finns ett ökat behov av agenter och producenter inom kulturnäringen.

The technique of sensor fusion addresses the issues relating to the optimality of decision-making in the multiple-sensor framework. The advances in sensor fusion enable to perform intrusion detection for both rare and new attacks. This thesis discusses this assertion in detail, and describes the theoretical and experimental work done to show its validity. The attack-detector relationship is initially modeled and validated to understand the detection scenario. The different metrics available for the evaluation of intrusion detection systems are also introduced. The usefulness of the data set used for experimental evaluation has been demonstrated. The issues connected with intrusion detection systems are analyzed and the need for incorporating multiple detectors and their fusion is established in this work. Sensor fusion provides advantages with respect to reliability and completeness, in addition to intuitive and meaningful results. The goal for this work is to investigate how to combine data from diverse intrusion detection systems in order to improve the detection rate and reduce the false-alarm rate. The primary objective of the proposed thesis work is to develop a theoretical and practical basis for enhancing the performance of intrusion detection systems using advances in sensor fusion with easily available intrusion detection systems. This thesis introduces the mathematical basis for sensor fusion in order to provide enough support for the acceptability of sensor fusion in performance enhancement of intrusion detection systems. The thesis also shows the practical feasibility of performance enhancement using advances in sensor fusion and discusses various sensor fusion algorithms, its characteristics and related design and implementation is-sues. We show that it is possible to build performance enhancement to intrusion detection systems by setting proper threshold bounds and also by rule-based fusion. We introduce an architecture called the data-dependent decision fusion as a framework for building intrusion detection systems using sensor fusion based on data-dependency. Furthermore, we provide information about the types of data, the data skewness problems and the most effective algorithm in detecting different types of attacks. This thesis also proposes and incorporates a modified evidence theory for the fusion unit, which performs very well for the intrusion detection application. The future improvements in individual IDSs can also be easily incorporated in this technique in order to obtain better detection capabilities. Experimental evaluation shows that the proposed methods have the capability of detecting a significant percentage of rare and new attacks. The improved performance of the IDS using the algorithms that has been developed in this thesis, if deployed fully would contribute to an enormous reduction of the successful attacks over a period of time. This has been demonstrated in the thesis and is a right step towards making the cyber space safer.

A method describing the expression and purification of PSI-N together with fusion protein, using affinity chromatography and TEV protease. Although the method proved successful, optimization is still needed due to partial degradation of PSI-N.

The aim of the project was to identify biologically relevant novel gene clusters by using combined genomic data instead of using only gene expression data in isolation. The clustering algorithm based on self-organizing maps (Kasturi et al., 2005) was extended and implemented in order to use gene location data together with the gene expression and the motif occurrence data for gene clustering. A distance function was defined to be used with gene location data. The algorithm was also extended in order to use vector angle distance for gene expression data. Arabidopsis thaliana is chosen as a data source to evaluate the developed algorithm. A test data set was created by using 100 Arabidopsis genes that have gene expression data with seven different time points during cold stress condition, motif occurrence data which indicates the occurrence frequency of 614 different motifs and the chromosomal location data of each gene. Gene Ontology (http://www.geneontology.org) and TAIR (http://arabidopsis.org) databases were used to find the molecular function and biological process information of each gene in order to examine the biological accuracy of newly discovered clusters after using combined genomic data. The biological evaluation of the results showed that using combined genomic data to cluster genes resulted in new biologically relevant clusters.

Karolinska universitetssjukhuset bildades i januari 2004 genom en sammanslagning av tidiga-re Huddinge Universitetssjukhus och Karolinska sjukhuset. Medias bevakning av organisa-tionsförändringen har varit omfattande och de politiska beslutsfattarna har jobbat med att förmedla bakgrunden till sammanslagningen. Fusionen genomfördes för att effektivisera sjukvården och därmed förbättra vårdkvaliteten. En viktig del i effektiviseringsprocessen var att koncentrera den högspecialiserade vården och på så sätt även stärka dess konkurrenskraft. Syftet med denna uppsats var att ta reda på om patienterna vid Karolinska Universitetssjukhuset har uppfattat några effekter i form av förbättrad vårdkvalitet samt om det finns skillnader mellan beslutsfattarnas och patienternas uppfattning om avsikterna till sammanslagningen. Detta har undersökts med hjälp av en kvantitativ enkätundersökning bland patienter på sjuk-huset. Undersökningen visar att patienternas uppfattning om den främsta avsikten till fusionen inte överensstämmer med ansvariga beslutsfattares. Patienterna tror att den främsta avsikten till sammanslagningen var ekonomiska fördelar. En orsak till detta kan vara en allmän uppfatt-ning om att förändringar i offentlig verksamhet enbart sker för att spara pengar, en annan för-klaring är troligtvis medias bevakning och fokusering på kostnaderna för sammanslagningen. Få patienter uppfattar någon skillnad i vårdkvaliteten före och efter sammanslagningen, vilket eventuellt kan bero på att den genomfördes så pass nyligen. Detta behöver i sig inte betyda att det inte finns några skillnader utan snarare att eventuella effekter är lättare att mäta på längre sikt. Det fanns heller inte några stora skillnader i jämförelsen av den förväntade och upplevda vårdkvaliteten. Resultatet är intressant då kundundersökningar gällande service och kvalitet ofta visar på motsatsen, dvs. att kunder har relativt höga förväntningar i förhållande till vad de sedan upplever att de får.

Efficient algorithms for time synchronization, including compensation for clock drift, are essential in order to obtain reliable fusion of data samples from multiple wireless sensor nodes. This paper evaluates the performance of algorithms based on three different approaches; one that synchronizes the local clocks on the sensor nodes, and a second that uses a single clock on the receiving node (e.g. a mobile phone), and a third that uses broadcast messages. The performances of the synchronization algorithms are evaluated in wireless personal area networks, especially Bluetooth piconets and ZigBee/IEEE 802.15.4 networks. A new approach for compensation of clock drift and a realtime implementation of single node synchronization from the mobile phone are presented and tested. Finally, applications of data fusion and time synchronization are shown in two different use cases; a kayaking sports case, and monitoring of heart and respiration of prematurely born infants. / <p>QC 20130605</p>

The two main challenges of the twenty-first century are the scarcity of energy sources and global warming; trigged by the emission of greenhouse gases. In this context, solar energy became increasingly relevant. Because it makes optimal use of the resources, minimizes environmental impacts, and is sustainable over time. However, before installing solar panels, it is convenient pre-assessing the amount of energy that a building can harvest. This study proposes a methodology to semi-automatically generate information a building scale; on a large area. This thesis integrates airborne Light Detection and Ranging (LiDAR) and WoldView-2 satellite data for modelling the solar energy potential of building rooftops in San Francisco, California. The methodology involved building detection solar potential analysis, and estimations at building scale. First, the outline of building rooftops is extracted using an object-based approach. Next, the solar modelling is carried out using the solar radiation analysis tool in ArcGIS, Spatial Analyst. Then, energy that could potentially be harvested by each building rooftop is estimated. The energy estimation is defined in economic and environmental terms.

Research on multisensor data fusion aims at providing the enabling technology to combine information from several sources in order to form a unifi ed picture. The literature work on fusion of conventional data provided by non-human (hard) sensors is vast and well-established. In comparison to conventional fusion systems where input data are generated by calibrated electronic sensor systems with well-defi ned characteristics, research on soft data fusion considers combining human-based data expressed preferably in unconstrained natural language form. Fusion of soft and hard data is even more challenging, yet necessary in some applications, and has received little attention in the past. Due to being a rather new area of research, soft/hard data fusion is still in a edging stage with even its challenging problems yet to be adequately de fined and explored. This dissertation develops a framework to enable fusion of both soft and hard data with the Random Set (RS) theory as the underlying mathematical foundation. Random set theory is an emerging theory within the data fusion community that, due to its powerful representational and computational capabilities, is gaining more and more attention among the data fusion researchers. Motivated by the unique characteristics of the random set theory and the main challenge of soft/hard data fusion systems, i.e. the need for a unifying framework capable of processing both unconventional soft data and conventional hard data, this dissertation argues in favor of a random set theoretic approach as the first step towards realizing a soft/hard data fusion framework. Several challenging problems related to soft/hard fusion systems are addressed in the proposed framework. First, an extension of the well-known Kalman lter within random set theory, called Kalman evidential filter (KEF), is adopted as a common data processing framework for both soft and hard data. Second, a novel ontology (syntax+semantics) is developed to allow for modeling soft (human-generated) data assuming target tracking as the application. Third, as soft/hard data fusion is mostly aimed at large networks of information processing, a new approach is proposed to enable distributed estimation of soft, as well as hard data, addressing the scalability requirement of such fusion systems. Fourth, a method for modeling trust in the human agents is developed, which enables the fusion system to protect itself from erroneous/misleading soft data through discounting such data on-the-fly. Fifth, leveraging the recent developments in the RS theoretic data fusion literature a novel soft data association algorithm is developed and deployed to extend the proposed target tracking framework into multi-target tracking case. Finally, the multi-target tracking framework is complemented by introducing a distributed classi fication approach applicable to target classes described with soft human-generated data. In addition, this dissertation presents a novel data-centric taxonomy of data fusion methodologies. In particular, several categories of fusion algorithms have been identifi ed and discussed based on the data-related challenging aspect(s) addressed. It is intended to provide the reader with a generic and comprehensive view of the contemporary data fusion literature, which could also serve as a reference for data fusion practitioners by providing them with conducive design guidelines, in terms of algorithm choice, regarding the specifi c data-related challenges expected in a given application.

Spinal fusion is the process by which two or more vertebral levels are joined into a single, solid bone mass in order to restore stability to a spine that has been compromised by trauma, degeneracy or metastasis. Fusion is accomplished through internal hardware positioned anteriorly, posteriorly, or with combined anterior-posterior instrumentation. Since the 1990s the frequency of spinal fusions has been rising, and this trend is expected to continue. Posterior approaches to fusion are most common, primarily consisting of pedicle screw and rod constructs. Despite the high success rate for bony fusion with pedicle screw fixation, this technique poses risks to delicate neurological and vascular structures and is heavily dependent on surgeon expertise. In this thesis, a novel and less invasive posterior spinal hardware system was designed and evaluated, which solely utilizes the spinous processes and laminae of the vertebrae as the point of the bone-implant interface. Morphological and biomechanical studies of the posterior spine were undertaken in order to define important geometric information to guide the design of the proposed hardware and to determine the strength of the posterior elements throughout the spine to assess their ability to support posterior element plating. Utilizing this information, a modular dual plate fusion system was developed for single or multi-level fusion. The system accounts for the native curvature of the spine and can be extended to additional vertebral levels at the time of insertion, or at any later time. Prototypes were manufactured in titanium. Positive biomechanical results were found when the proposed hardware was used as a supplement to anterior instrumentation. Additionally, work focused on 2D-3D registration of neutral CT data with flexion extension x-ray images, was undertaken and shown to yield improved accuracy of important vertebral metrics utilized for clinical assessment of spine stability. This technique is applicable to the evaluation of pathology and kinematics at any level of the spine, including post-fusion adjacent level degeneration. The culmination of this work has resulted in a novel, patent pending posterior element spinal fusion system.

The trapping behavior of deuterium and helium in polycrystalline tungsten (PCW) under D+-only, He+-only, sequential and simultaneous irradiation was studied as a function of incident ion fluences and irradiation temperature. Deuterium implanted at 300 and 500 K gets trapped at surface adsorption sites, vacancy-related traps, or extended defects. No deuterium was trapped for 700 K implantations. Results were affected by tungsten-carbide impurities in PCW specimens. It is suggested that He trapping occurs via the formation of He clusters, at impurity sites, or as part of He-vacancy complexes. For sequential implantations, D and He were found to de-trap each other, with He impeding the trapping of D when implanted first at 300 K. Under simultaneous irradiation a decrease in D inventories was observed for all cases, and a re-distribution of He to higher energy traps (associated with He-vacancy complex formation) was observed for higher fluences and temperatures.