Optimizing Mobile Java Location-Based Services in Symbian OS

This thesis evaluates methods for obtaining high performance in applications running on the mobile Java platform. Based on the evaluated methods, an optimization was done to a Java extension API running on top the Symbian operating system. The API provides location-based services for mobile Java applications. As a part of this thesis, the JNI implementation in Symbian OS was also benchmarked. A benchmarking tool was implemented in the analysis phase in order to implement extensive performance test set. Based on the benchmark results, it was noted that the landmarks implementation of the API was performing very slowly with large amounts of data. The existing implementation proved to be very inconvenient for optimization because the early implementers did not take performance and design issues into consideration. A completely new architecture was implemented for the API in order to provide scalable landmark initialization and data extraction by using lazy initialization methods. Additionally, runtime memory consumption was also an important part of the optimization. The improvement proved to be very efficient based on the measurements after the optimization. Most of the common API use cases performed extremely well compared to the old implementation. Performance optimization is an important quality attribute of any piece of software especially in embedded mobile devices. Typically, projects get into trouble with performance because there are no clear performance targets and knowledge how to achieve them. Well-known guidelines and performance models help to achieve good overall performance in Java applications and programming interfaces.

Subthalamic (STN) Deep Brain Stimulation (DBS) in Parkinson's Disease (PD): Correlation Between the Location of the Stimulated Contacts and the Clinical Effects in 14 Patients

Objectives: To correlate the chronic stimulated electrode position on postoperative MRI with the clinical response obtained in PD patients. Material and Method: We retrospectively reviewed 14 consecutive parkinsonian patients who were selected for STN-DBS surgery. Coordinates were determined on an IR T2 MRI coronal section per pendicular to AC-PC plane 3 mm posterior to midcommissural point (MCP) and 12 mm lateral to the midline the inferior aspect of subthalamic region. A CRW stereotactic frame was used for the surgical procedure. A 3D IR T2 MRI was performed postoperatively to determine the location of the stimulated contact in each patient. The clinical results were assessed independently by the neurological team. Results: All but 2 patients had monopolar stimulation. The mean coordinates of the stimulated contacts were: AP ^ ÿ4:23G1:4, Lat ^ 1:12G0:15, Vert ^ ÿ4:1 G2:7 to the MCP. With a mean follow-up of 8 months, all stimulated patients had a significant clinical improvement (preop/postop «ON» UPDRS: 25:8G7:0= 23:3 G8:6; preop/postop «OFF» UPDRS: 50:2G11:4=26:0 G7:8), 60% of them without any antiparkinsonian drug. Conclusion: According to the stereotactic atlas of Schaltenbrand and Warren and the 3D shape of the STN, our results show that our targetting is accurate and almost all the stimulated contacts are comprised in the STN volume. This indicates that MRI is a safe, precise and reproducible procedure for targetting the STN. The location of the stimulated contact within the STN volume is a good predictor of the clinical results.

Development of a systematic computer vision-based method to analyse and compare images of false identity documents for forensic intelligence purposes-Part I: acquisition, calibration and validation issues

Following their detection and seizure by police and border guard authorities, false identity and travel documents are usually scanned, producing digital images. This research investigates the potential of these images to classify false identity documents, highlight links between documents produced by a same modus operandi or same source, and thus support forensic intelligence efforts. Inspired by previous research work about digital images of Ecstasy tablets, a systematic and complete method has been developed to acquire, collect, process and compare images of false identity documents. This first part of the article highlights the critical steps of the method and the development of a prototype that processes regions of interest extracted from images. Acquisition conditions have been fine-tuned in order to optimise reproducibility and comparability of images. Different filters and comparison metrics have been evaluated and the performance of the method has been assessed using two calibration and validation sets of documents, made up of 101 Italian driving licenses and 96 Portuguese passports seized in Switzerland, among which some were known to come from common sources. Results indicate that the use of Hue and Edge filters or their combination to extract profiles from images, and then the comparison of profiles with a Canberra distance-based metric provides the most accurate classification of documents. The method appears also to be quick, efficient and inexpensive. It can be easily operated from remote locations and shared amongst different organisations, which makes it very convenient for future operational applications. The method could serve as a first fast triage method that may help target more resource-intensive profiling methods (based on a visual, physical or chemical examination of documents for instance). Its contribution to forensic intelligence and its application to several sets of false identity documents seized by police and border guards will be developed in a forthcoming article (part II).

Image processing of false identity documents for forensic intelligence

Forensic intelligence has recently gathered increasing attention as a potential expansion of forensic science that may contribute in a wider policing and security context. Whilst the new avenue is certainly promising, relatively few attempts to incorporate models, methods and techniques into practical projects are reported. This work reports a practical application of a generalised and transversal framework for developing forensic intelligence processes referred to here as the Transversal model adapted from previous work. Visual features present in the images of four datasets of false identity documents were systematically profiled and compared using image processing for the detection of a series of modus operandi (M.O.) actions. The nature of these series and their relation to the notion of common source was evaluated with respect to alternative known information and inferences drawn regarding respective crime systems. 439 documents seized by police and border guard authorities across 10 jurisdictions in Switzerland with known and unknown source level links formed the datasets for this study. Training sets were developed based on both known source level data, and visually supported relationships. Performance was evaluated through the use of intra-variability and inter-variability scores drawn from over 48,000 comparisons. The optimised method exhibited significant sensitivity combined with strong specificity and demonstrates its ability to support forensic intelligence efforts.

OERopoly : A Game to Generate Collective Intelligence around OER

Collective Intelligence (CI ) is a phenomenon that emerges at the crossroads of three worlds: Open Educational Resources (OER), Web 2.0 technologies and Online Learning Communities. Building CI for the OER movement means capturing the richness of information, experiences, knowledge and resources, that the movement is constantly generating, in a way that they can be shared and reused for the benefit of the movement itself. The organisation of CI starts from collecting the knowledge and experiences of OER's practitioners and scholars in new creative forms, and then situating this knowledge in a collective 'pot' from where it can be leveraged with new 'intelligent' meanings and toward new 'intelligent' goals. This workshop is an attempt to do so by engaging participants in a CI experience, in which they will contribute to, and at the same time take something from, the existing CI around OER, Web 2.0 technologies and Online Learning Communities.

Lamellarin D bioconjugates II: synthesis and cellular internalization of dendrimer and nuclear location signal derivatives

The design and synthesis of Lamellarin D conjugates with a nuclear localization signal peptide and a poly(ethylene glycol)-based dendrimer are described. Conjugates 1-4 were obtained in 8-84% overall yields from the corresponding protected Lamellarin D. Conjugates 1 and 4 are 1.4 to 3.3-fold more cytotoxic than the parent compound against three human tumor cell lines(MDA-MB-231 breast, A-549 lung, and HT-29 colon). Besides, conjugates 3, 4 showed a decrease in activity potency in BJ skin fibroblasts, a normal cell culture. Cellular internalization was analyzed and nuclear distribution pattern was observed for 4, which contains a nuclear localization signalling sequence.

Análisis de datos de accidentes de tráfico mediante soluciones big data y business intelligence

Este proyecto de final de carrera corresponde al área de inteligencia artificial y representa un caso de uso que pretende utilizar datos reales referentes a accidentes de tráfico (datos de accidentes, muertos, heridos, etc.) y analizarlas conjuntamente con datos que puedan tener una posible relación con los accidentes como el parque de vehículos, las temperaturas de la zona de los accidentes, etc. con la finalidad de poder obtener las posibles relaciones causa-efecto.

Development of tender information process by business intelligence in a global company unit

The purpose of this Thesis was to study what is the present situation of Business Intelligence of the company unit. This means how efficiently unit uses possibilities of modern information management systems. The aim was to resolve how operative informa-tion management of unit’s tender process could be improved by modern information technology applications. This makes it possible that tender processes could be faster and more efficiency. At the beginning it was essential to acquaint oneself with written literature of Business Intelligence. Based on Business Intelligence theory is was relatively easy but challenging to search and discern how tender business could be improved by methods of Busi-ness Intelligence. The empirical phase of this study was executed as qualitative research method. This phase includes theme and natural interviews on the company. Problems and challenges of tender process were clarified in a part an empirical phase. Group of challenges were founded when studying information management of company unit. Based on theory and interviews, group of improvements were listed which company could possible do in the future when developing its operative processes.

Applying collective intelligence to idea evaluation at the front end of innovation

The study focuses on the front end of innovation process. Due to changes in innovation policies and paradigms customers, users and shopfloor employees are becoming increasingly important sources of knowledge. New methods are needed for processing information and ideas coming from multiple sources more effectively. The aim of this study is to develop an idea evaluation tool suitable for the front end of innovation process and capable of utilizing collective intelligence. The study is carried out as a case study research using constructive research approach. The chosen approach suits well for the purposes of the study. The constructive approach focuses on designing new constructs and testing them in real life applications. In this study a tool for evaluating ideas emerging from the course of everyday work is developed and tested in a case organization. Development of the tool is based on current scientific literature on knowledge creation, innovation management and collective intelligence and it is tested in LUT Lahti School of Innovation. Results are encouraging. The idea evaluation tool manages to improve performance at the front end of innovation process and it is accepted in use in the case organization. This study provides insights on what kind of a tool is required for facilitating collective intelligence at the front end of innovation process.

Creative Industries: a Preliminary Insight to their Location Determinants

This paper is about location decisions of Creative Industries and the role played by existent spatial distribution and agglomeration economies of these kinds of activities in order to analyse their location determinants. Our main statistical source is the REIC (Catalan Manufacturing Establishments Register), which has plant-level microdata on location of new plants. Using Count Data Models, our main results show that location determinants are quite similar between both industries and also both non-creative and creative firms are positively influenced by the specialisation level in Creative Industries of municipalities. Moreover, our results provide evidence that the unobserved ‘creative milieu’ has a limited impact on attracting firms. Keywords: creative industries, creative milieu, count data models, industrial location, agglomeration economies

Optimizing of intelligence level in welding

The productivity, quality and cost efficiency of welding work are critical for metal industry today. Welding processes must get more effective and this can be done by mechanization and automation. Those systems are always expensive and they have to pay the investment back. In this case it is really important to optimize the needed intelligence and this way needed automation level, so that a company will get the best profit. This intelligence and automation level was earlier classified in several different ways which are not useful for optimizing the process of automation or mechanization of welding. In this study the intelligence of a welding system is defined in a new way to enable the welding system to produce a weld good enough. In this study a new way is developed to classify and select the internal intelligence level of a welding system needed to produce the weld efficiently. This classification contains the possible need of human work and its effect to the weld and its quality but does not exclude any different welding processes or methods. In this study a totally new way is developed to calculate the best optimization for the needed intelligence level in welding. The target of this optimization is the best possible productivity and quality and still an economically optimized solution for several different cases. This new optimizing method is based on grounds of product type, economical productivity, the batch size of products, quality and criteria of usage. Intelligence classification and optimization were never earlier made by grounds of a made product. Now it is possible to find the best type of welding system needed to welddifferent types of products. This calculation process is a universal way for optimizing needed automation or mechanization level when improving productivity of welding. This study helps the industry to improve productivity, quality and cost efficiency of welding workshops.

Aerosol particle size distributions at a traffic exposed site and an urban background location in Oporto, Portugal

Aerosol size distributions from 6 to 700 nm were measured simultaneously at an urban background site and a roadside station in Oporto. The particle number concentration was higher at the traffic exposed site, where up to 90% of the size spectrum was dominated by the nucleation mode. Larger aerosol mode diameters were observed in the urban background site possibly due to the coagulation processes or uptake of gases during transport. Factor analysis has shown that road traffic and the neighbour stationary sources localised upwind affect the urban area thought intra-regional pollutant transport.

Defining the location factors of new manufacturing site in chemical industry

The objective of this thesis is to examine the factors that have an impact on the location decision of new manufacturing site and to create the relative order of importance of these factors by analytic hierarchy process (AHP). The decision making process especially related to the location selection and the measurement of the location factors are also examined. In theoretical part the character of decision making process and the relevant methods are introduced. Based on the previous studies of other researchers, the location factors are examined and the main research method, analytic hierarchy process, is also introduced. The empirical part of the study mainly follows the phases of decision making process and is emphasized on the main stages of analytic hierarchy process; building the hierarchy, defining the priorities and analyzing the results. The hierarchy is constructed from seven main criteria which all have several sub criteria. The evaluation of the hierarchy is implemented at the group decision making –laboratory and there can be seen significant differences between the importance of criteria. The final stage in the study is to create the appropriate measurement scales to the chosen criteria.