<p>To incorporate new technical advances into military domain and make those processes more <i>efficient</i> in accuracy, time and cost, a new concept of Network Centric Warfare has been introduced in the US military forces. In Sweden a similar concept has been studied under the name Network Based Defence (NBD). Here we present one of the methodologies, called tactical plan recognition that is aimed to support NBD in future.</p><p>Advances in sensor technology and modelling produce large sets of data for decision makers. To achieve <i>decision superiority</i>, decision makers have to act agile with proper, adequate and relevant information (data aggregates) available. Information fusion is a process aimed to support decision makers’ situation awareness. This involves a process of combining data and information from disparate sources with <i>prior</i> information or knowledge to obtain an improved state estimate about an agent or phenomena. <i>Plan recognition</i> is the term given to the process of inferring an agent’s intentions from a set of actions and is intended to support decision making.</p><p>The aim of this work has been to introduce a methodology where prior (empirical) knowledge (e.g. behaviour, environment and organization) is represented and combined with sensor data to recognize plans/behaviours of an agent or group of agents. We call this methodology <i>multi-agent plan recognition</i>. It includes knowledge representation as well as imprecise and statistical inference issues.</p><p>Successful plan recognition in large scale systems is heavily dependent on the data that is supplied. Therefore we introduce a <i>bridge</i> between the plan recognition and sensor management where results of our plan recognition are reused to the control of, give <i>focus of attention</i> to, the sensors that are supposed to acquire most important/<i>relevant</i> information.</p><p>Here we combine different theoretical methods (Bayesian Networks, Unified Modeling Language and Plan Recognition) and apply them for tactical military situations for ground forces. The results achieved from several proof-ofconcept models show that it is possible to model and recognize behaviour of tank units.</p>

This thesis evaluates and shows an implementation of a video telephony solution for network connected set-top boxes based on the SIP protocol for managing sessions. Unlike other video telephony implementations the set-top box does not handle both audio and video, but only video. A separate phone is used to handle audio. To maintain compatibility with other video telephony implementations, which expect a single SIP device with both audio and video capabilities, a mechanism to merge the audio (SIP-phone) and video (set-top box) into a single entity was developed using a back-to-back user agent. Due to the set-top boxes'limited hardware it could be impossible to have video compression and decompression performed by the set-top boxes. However, numerous performance tests of compression algorithms showed that the computational power available in the set-top boxes is sufficient to have acceptable frame rate and image quality in a video telephony session. A faster CPU or dedicated hardware for video compression and decompression would however be required in order to compete with dedicated video telephony systems available today. The implemented video telephony system is based on open standards such as SIP, RTP and H.261, which means interoperability with other video telephony implementations, such as Microsoft's Windows Messenger 4.7, is good.

The purpose of this Master’s Thesis is to produce a specification for the aircraft conflict alert system STCA, and implement a prototype as a module in the air traffic surveillance system NOVA9000. The specification is constructed based on functional requirements from EUROCONTROL and describes a system using a nominal trajectory method, where the future paths of aircraft are estimated. The trajectory is created using a probabilistic approach, where future positions are described with probability fields. The prototype is implemented using the specification with some simplifications. The prototype is evaluated using recorded traffic from a heavy air traffic region surrounding an airport with parallel runways. 15 alerts were induced in 1,5 hour of morning traffic; this is far too much to be acceptable. Improvements are proposed and explanations to the high rate of alerts are made.

Nowadays, embedded systems are becoming more and more complex. For this reason, designers focus more and more to adopt component-based methods for their designs. Consequently, there is an increasing interest on modeling and verification issues of component-based embedded systems. In this thesis, a tool, which integrates modeling, simulation and verification of component-based embedded systems, is designed and implemented. This tool uses the PRES+, Petri Net based Representation for Embedded Systems, to model component-based embedded systems. Both simulation and verification of systems are based on the PRES+ models. This tool consists of three integrated sub-tools, each of them with a graphical interface, the PRES+ Modeling tool, the PRES+ Simulation tool and the PRES+ Verification tool. The PRES+ Modeling tool is a graphical editor, with which system designers can model component-based embedded systems easily. The PRES+ Simulation tool, which is used to validate systems, visualizes the execution of a model in an intuitive manner. The PRES+ Verification tool provides a convenient access to a model checker, in which models can be formally verified with respect to temporal logic formulas.

This project explores an improved design for a system that tracks drive and rest time data for heavy vehicle drivers. Tracking rest and driving time data for drivers of heavy vehicles is important since it allows for the drivers to ensure that they are following the laws related to how often they must take breaks. The system built in this project is external to the vehicles. It relies on sending smaller status updates then previously, thus decreasing the data required to track the drive and rest times. The system was evaluated in terms of how much data it saves compared to a system that sends full status updates, it was also evaluated on how the cost scales with an increased load on the system.

To incorporate new technical advances into military domain and make those processes more efficient in accuracy, time and cost, a new concept of Network Centric Warfare has been introduced in the US military forces. In Sweden a similar concept has been studied under the name Network Based Defence (NBD). Here we present one of the methodologies, called tactical plan recognition that is aimed to support NBD in future. Advances in sensor technology and modelling produce large sets of data for decision makers. To achieve decision superiority, decision makers have to act agile with proper, adequate and relevant information (data aggregates) available. Information fusion is a process aimed to support decision makers’ situation awareness. This involves a process of combining data and information from disparate sources with prior information or knowledge to obtain an improved state estimate about an agent or phenomena. Plan recognition is the term given to the process of inferring an agent’s intentions from a set of actions and is intended to support decision making. The aim of this work has been to introduce a methodology where prior (empirical) knowledge (e.g. behaviour, environment and organization) is represented and combined with sensor data to recognize plans/behaviours of an agent or group of agents. We call this methodology multi-agent plan recognition. It includes knowledge representation as well as imprecise and statistical inference issues. Successful plan recognition in large scale systems is heavily dependent on the data that is supplied. Therefore we introduce a bridge between the plan recognition and sensor management where results of our plan recognition are reused to the control of, give focus of attention to, the sensors that are supposed to acquire most important/relevant information. Here we combine different theoretical methods (Bayesian Networks, Unified Modeling Language and Plan Recognition) and apply them for tactical military situations for ground forces. The results achieved from several proof-ofconcept models show that it is possible to model and recognize behaviour of tank units. / QC 20101222

OSINT is the collection and analysis of data from open sources such as Twitter, Instagram or Tiktok. Since most people in today's digitised society have access to mobile devices and cameras, anyone can publish sensitive material on for example troop movements. The aim of this work is to contribute on how OSINT methods can potentially be used for intelligence gathering and by increasing knowledge in this area also protect against the problem of people sharing sensitive information by mistake. This is accomplished by conducting an experiment in which three web scraping methods and three manual methods are used for the collection of potential intelligence on three different social media platforms. Due to the state of the world today, the experiment focuses on the Ukraine conflict. All methods tested during the experiment can be used for intelligence gathering. However, the methods differ in their search capabilities and how well they can filter the results of its searches. Overall, the TWINT tool and manual searches of Twitter performed best because they have the most search options and filtering capabilities. / OSINT är insamling och analys av data från öppna källor som Twitter, Instagram eller Tiktok.Eftersom de flesta i dagens digitaliserade samhälle har tillgång till mobila enheter och kamerorkan vem som helst publicera känsligt material på exempelvis truppförflyttningar. Syftet meddetta arbete är att bidra med kunskap om hur OSINT metoder kan potentiellt användas förinsamling av underrättelse och genom en ökad kunskap kring området också skydda motproblemet där personer delar med sig av känslig information av misstag. Detta genomförsgenom att utföra ett experiment där tre web scraping metoder och tre manuella metoderanvänds för insamling av potentiell underrättelse på tre olika sociala medier plattformar. Pågrund av hur läget ser ut i världen idag så fokuserar experimentet på Ukraina konflikten. Allametoder som testades under experimentets gång kan användas för inhämtning av underrättelse.Metoderna skiljer sig i dock sina sökfunktioner och hur väl de kan filtrera resultaten från desssökningar. Överlag så presterade verktyget TWINT och manuella sökningar av Twitter bäst föratt de har flest sökalternativ och filtreringsmöjligheter.

Systems controlled by embedded computers become indispensable in our lives and can be found in avionics, automotive industry, home appliances, medicine, telecommunication industry, mecatronics, space industry, etc. Fast, accurate and flexible performance estimation tools giving feedback to the designer in every design phase are a vital part of a design process capable to produce high quality designs of such embedded systems. In the past decade, the limitations of models considering fixed task execution times have been acknowledged for large application classes within soft real-time systems. A more realistic model considers the tasks having varying execution times with given probability distributions. No restriction has been imposed in this thesis on the particular type of these functions. Considering such a model, with specified task execution time probability distribution functions, an important performance indicator of the system is the expected deadline miss ratio of tasks or task graphs. This thesis proposes two approaches for obtaining this indicator in an analytic way. The first is an exact one while the second approach provides an approximate solution trading accuracy for analysis speed. While the first approach can efficiently be applied to monoprocessor systems, it can handle only very small multi-processor applications because of complexity reasons. The second approach, however, can successfully handle realistic multiprocessor applications. Experiments show the efficiency of the proposed techniques. / <p>Report code: LiU-Tek-Lic-2002:58.</p>

Play’n GO uses a reporting framework where their customers (operators) can access game related and financial information. These reports are very important for the operators since they use them all the time for statistics, marketing and financial settlement. The reporting framework is now getting old and needs to be updated or replaced.This report will handle the analysis of the current framework, an updated framework, new frameworks and the option of creating a framework by themselves.The result was that it would be easier for them to make a framework of their own, rather than to buy and try to adapt an already existing one.

Virtualization is a widely used technology for running multiple operating systems on a single set of hardware. Virtual machines running the same operating system have been shown to have a large amount of identical data, in such cases deduplication have been shown to be very effective in eliminating duplicated data. This study aimed to investigate if the storage savings are as large as shown in previous research, as well as to investigate if there are any negative performance impacts when using deduplication. The selected performance variables are resource utilisation and disk performance. The selected deduplication implementations are SDFS and ZFS deduplication. Each file system is tested with its respective non-deduplicated file systems, ext4 and ZFS. The results show that the storage savings are between 72,5 % and 73,65 % while the resource utilisation is generally higher when using deduplication. The results also show that deduplication using SDFS has an overall large negative disk performance impact, while ZFS deduplication has a general disk performance increase.