Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

Design of a case-based reasoner for information security in military organizations

Information security is concerned with the protection of information, which can be stored, processed or transmitted within critical information systems of the organizations, against loss of confidentiality, integrity or availability. Protection measures to prevent these problems result through the implementation of controls at several dimensions: technical, administrative or physical. A vital objective for military organizations is to ensure superiority in contexts of information warfare and competitive intelligence. Therefore, the problem of information security in military organizations has been a topic of intensive work at both national and transnational levels, and extensive conceptual and standardization work is being produced. A current effort is therefore to develop automated decision support systems to assist military decision makers, at different levels in the command chain, to provide suitable control measures that can effectively deal with potential attacks and, at the same time, prevent, detect and contain vulnerabilities targeted at their information systems. The concept and processes of the Case-Based Reasoning (CBR) methodology outstandingly resembles classical military processes and doctrine, in particular the analysis of “lessons learned” and definition of “modes of action”. Therefore, the present paper addresses the modeling and design of a CBR system with two key objectives: to support an effective response in context of information security for military organizations; to allow for scenario planning and analysis for training and auditing processes.

Version brève du DISCERN, une voie d'amélioration de la recherche d'information médicale sur le net [Brief-DISCERN, a possible way to improve patient's search on the health-related web]

Internet is increasingly used as a source of information on health issues and is probably a major source of patients' empowerment. This process is however limited by the frequently poor quality of web-based health information designed for consumers. A better diffusion of information about criteria defining the quality of the content of websites, and about useful methods designed for searching such needed information, could be particularly useful to patients and their relatives. A brief, six-items DISCERN version, characterized by a high specificity for detecting websites with good or very good content quality was recently developed. This tool could facilitate the identification of high-quality information on the web by patients and may improve the empowerment process initiated by the development of the health-related web.

Web de control de tráfico marítimo

El proyecto Web de Control de Tráfico Marítimo (WCTM) un proyecto Web que va a gestionar información útil para el Control del Tráfico Marítimo de una determinada zona del mundo. Usa el concepto de arquitectura SOA, una arquitectura que se basa en los servicios Web, proporciona en tiempo real información sobre los buques usando los mapas de Google.

Personalized touristic routes implementing semantic web on GIS

Nowadays, when a user is planning a touristic route is very difficult to find out which are the best places to visit. The user has to choose considering his/her preferences due to the great quantity of information it is possible to find in the web and taking into account it is necessary to do a selection, within small time because there is a limited time to do a trip. In Itiner@ project, we aim to implement Semantic Web technology combined with Geographic Information Systems in order to offer personalized touristic routes around a region based on user preferences and time situation. Using ontologies it is possible to link, structure, share data and obtain the result more suitable for user's preferences and actual situation with less time and more precisely than without ontologies. To achieve these objectives we propose a web page combining a GIS server and a touristic ontology. As a step further, we also study how to extend this technology on mobile devices due to the raising interest and technological progress of these devices and location-based services, which allows the user to have all the route information on the hand when he/she does a touristic trip. We design a little application in order to apply the combination of GIS and Semantic Web in a mobile device.

Aplicació web per a la vigilància epidemiològica a Barcelona emprant sistemes d'informació geogràfica de programari lliure

This project is about the development of a web that uses the tools offered by the Geographic Information Systems based in open source in order to monitoring and detect legionella clusters in Barcelona. This web also produces thematic maps for the study of epidemiologic diseases and has been made with the colaboration of the Barcelona public health agency.

Comunicación de riesgo y sistemas de información en la Web: cinco modelos

Las administracionespúblicas de los países avanzadosestán llevando a caboiniciativas para gestionar lainformación y la comunicaciónde riesgo y emergencias mediantesitios web concebidos ydiseñados para ello. Estos sitiosestán pensados para facilitarinformación a los ciudadanosen caso de emergencias, perotambién contienen informaciónútil para los expertos y las autoridades.En este trabajo, y ala luz de la legislación españolasobre emergencias, se comparanlos sitios de la administraciónautonómica catalana y delgobierno de España con lossitios de tres países de referencia:Estados Unidos, Francia yReino Unido. Al mismo tiempose propone una metodologíasimple para llevar a cabo unacomparación que permita extraerconclusiones y plantearrecomendaciones en un aspectode la gestión de la información que puede resultar clave para salvar bienes materiales y vidas humanas.

Personalized touristic routes implementing semantic web on GIS

Nowadays, when a user is planning a touristic route is very difficult to find out which are the best places to visit. The user has to choose considering his/her preferences due to the great quantity of information it is possible to find in the web and taking into account it is necessary to do a selection, within small time because there is a limited time to do a trip. In Itiner@ project, we aim to implement Semantic Web technology combined with Geographic Information Systems in order to offer personalized touristic routes around a region based on user preferences and time situation. Using ontologies it is possible to link, structure, share data and obtain the result more suitable for user's preferences and actual situation with less time and more precisely than without ontologies. To achieve these objectives we propose a web page combining a GIS server and a touristic ontology. As a step further, we also study how to extend this technology on mobile devices due to the raising interest and technological progress of these devices and location-based services, which allows the user to have all the route information on the hand when he/she does a touristic trip. We design a little application in order to apply the combination of GIS and Semantic Web in a mobile device.

Web user interface architecture for advanced planning and scheduling systems Case: Nokia Demand / Supply Planning Applications

In modem hitec industry Advanced Planning and Scheduling (APS) systems provide the basis for e-business solutions towards the suppliers and the customers. One objective of this thesis was to clarify the modem supply chain management with the APS systems and especially concentrate on the area of Collaborative Planning. In order Advanced Planning and Scheduling systems to be complete and usable, user interfaces are needed. Current Visual Basic user interfaces have faced many complaints and arguments from the users as well as from the development team. This thesis is trying to analyze the reasons and causes for the encountered problems and also provide ways to overcome them. The decision has been made to build the new user interfaces to be Web-enabled. Therefore another objective of this thesis was to research and find suitable technologies for building the Web-based user interfaces for Advanced Planning and Scheduling Systems in Nokia Demand/Supply Planning business area. Comparison between the most suitable technologies is made. Usability issues of Web-enabled user interfaces are also covered. The empirical part of the thesis includes design and implementation of a Web-based user interface with the chosen technology for a particular APS module that enables Collaborative Planning with suppliers.

Web Software Engineering - value added approach

Taking the maximum advantage of technological innovations and the investment in them is of key importance for businesses. The IT industry offers a wide range of innovative high-technology solutions to manage information processing and distribution. However for end-user businesses to make informed decisions in this area is challenging. The aim of this research is to identify the key differences in principal solutions, and what the selection criteria should be for those involved. Existing methodologies for software development are classified, and some key criteria are described to help IT system developers and users determine what are the most important factors in system selection, development and deployment. Statistical data is researched and analysed, a theoretical basis is developed and reviewed, key issues from case studies are identified and generalized to be presented along with the conclusions in the current study. The results give a good basis for corporate consideration and provide overall support to the key decisions in developing web-based software. The conclusion is that new web developments should be considered the stakeholders as an evolution of existing business systems, but they should then pay particular attention to the new advantages that web-based software offers in terms of standardised interfaces and procedures, universal deployment opportunities, and a range of other benefits the study highlights.

Centralized Identity Management for Web Applications

Internet-palvelujen määrä kasvaa jatkuvasti. Henkilöllä on yleensä yksi sähköinen identiteetti jokaisessa käyttämässään palvelussa. Autentikointitunnusten turvallinen säilytys käy yhä vaikeammaksi, kun niitä kertyy yhdet jokaisesta uudesta palvelurekisteröitymisestä. Tämä diplomityö tarkastelee ongelmaa ja ratkaisuja sekä palvelulähtöisestä että teknisestä näkökulmasta. Palvelulähtöisen identiteetinhallinnan liiketoimintakonsepti ja toteutustekniikat – kuten single sign-on (SSO) ja Security Assertion Markup Language (SAML) – käydään läpi karkeiden esimerkkien avulla sekä tutustuen Nokia Account -hankkeessa tuotetun ratkaisun konseptiin ja teknisiin yksityiskohtiin. Nokia Account -palvelun ensimmäisen version toteutusta analysoidaan lopuksi identiteetinhallintapalveluiden suunnitteluperiaatteita ja vaatimuksia vasten.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Improving Transportation and Warehousing Efficiency with Simulation-Based Decision Support Systems

Transportation and warehousing are large and growing sectors in the society, and their efficiency is of high importance. Transportation also has a large share of global carbondioxide emissions, which are one the leading causes of anthropogenic climate warming. Various countries have agreed to decrease their carbon emissions according to the Kyoto protocol. Transportation is the only sector where emissions have steadily increased since the 1990s, which highlights the importance of transportation efficiency. The efficiency of transportation and warehousing can be improved with the help of simulations, but models alone are not sufficient. This research concentrates on the use of simulations in decision support systems. Three main simulation approaches are used in logistics: discrete-event simulation, systems dynamics, and agent-based modeling. However, individual simulation approaches have weaknesses of their own. Hybridization (combining two or more approaches) can improve the quality of the models, as it allows using a different method to overcome the weakness of one method. It is important to choose the correct approach (or a combination of approaches) when modeling transportation and warehousing issues. If an inappropriate method is chosen (this can occur if the modeler is proficient in only one approach or the model specification is not conducted thoroughly), the simulation model will have an inaccurate structure, which in turn will lead to misleading results. This issue can further escalate, as the decision-maker may assume that the presented simulation model gives the most useful results available, even though the whole model can be based on a poorly chosen structure. In this research it is argued that simulation- based decision support systems need to take various issues into account to make a functioning decision support system. The actual simulation model can be constructed using any (or multiple) approach, it can be combined with different optimization modules, and there needs to be a proper interface between the model and the user. These issues are presented in a framework, which simulation modelers can use when creating decision support systems. In order for decision-makers to fully benefit from the simulations, the user interface needs to clearly separate the model and the user, but at the same time, the user needs to be able to run the appropriate runs in order to analyze the problems correctly. This study recommends that simulation modelers should start to transfer their tacit knowledge to explicit knowledge. This would greatly benefit the whole simulation community and improve the quality of simulation-based decision support systems as well. More studies should also be conducted by using hybrid models and integrating simulations with Graphical Information Systems.