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Healing from conflict allows us to bring the best we can be to each relationship and situation, however current healing techniques focus on the involvement of other people. A self-healing road map could be beneficial. The goal of this research was to examine Locate, Describe and Transform (LDT™) and its potential to provide just such a guide. This qualitative case study examined a single, self-applied LDT™ energy session in order to explore what might be revealed about its underlying conflict healing theoretical framework. Using Moustakas’ heuristic methodology, the LDT™ process was formulated and linked to research in embodiment, metaphor, and energy healing. The concept of universal energy was then compared to four conflict theories of connection, including Maslow’s Self-Actualization, Redekop’s Mimetic Structures of Blessing, LeBaron’s Connected Ways of Knowing, and Gopin’s Eight Steps. LDT™ was found to be theoretically grounded and worthy of further exploration.

In this thesis a non-centralized algorithm is proposed to locate nearby servers based on their players’ positions in a massive multiplayer online game server cluster. The purpose of this is to enable that players can visually see each other even though they are connected to different servers. By utilizing peer to peer connection between the servers the algorithm is tolerant against possible hardware failures. The algorithm simplifies the data sent over the network with a new concave polygon creation algorithm which works in linear execution time, enabling fast computations for real-time games. The algorithm works by finding colliding polygons from other servers and the closest polygons based on distance to find nearby servers which information should be shared with. Those two algorithms at this time work in quadratic execution time which is a point of improvement, which could require the concave polygon to be converted into one or several convex polygons. The algorithm is designed to give the user good access on the amount of network traffic sent over the cluster which gives better control and understanding on how much network traffic that will be sent in the cluster. It shows that the algorithm is dependent on how players in the world are distributed over the servers. By having players nearby each other on the same server improves the result of the algorithm. It is shown that compared to having a centralized server, the network traffic on every single node have reduced network traffic than compared to a centralized server. / In den här uppsatsen presenteras en icke-centraliserad algoritm som hittar närliggande servrar baserat på deras spelares positioner i ett massivt multi-spelare online spel med flera servrar. Syftet är att möjliggöra att spelare från olika servrar kan se varandra visuellt även fast de är uppkopplade till olika servrar. Genom att använda sig av ”peer-to-peer” kommunikation i klustret blir algoritmen tolerant mot hårdvarufel. Algoritmen simplifierar data som skickas genom en ny typ av konkav polygon algoritm vilken fungerar i linjär exekveringstid, vilket möjliggör snabba beräkningar för realtidsspel. Algoritmen fungerar genom att hitta kolliderande polygoner från andra servrar och även de mest närliggande baserat på distans för att lokalisera närliggande servrar att dela information med. De här två algoritmerna arbetar i kvadratisk tid vilket skulle kunna förbättras. Detta kan kräva att konkava polygonen konverteras till en eller flera konvexa polygoner. Algoritmen är designad för att ge användaren bra tillgång till hur mycket nätverkstrafik som bör skickas inom klustret vilket ger en bättre kontroll och förståelse över hur mycket data som kommer att skickas totalt. Det visas att algoritmen är beroende av hur spelarna är distribuerade över servrarna. Genom att ha närliggande spelare i världen på samma server förbättras resultatet av algoritmen. Det visas även att jämfört med en centraliserad server så förbättras nätverkstrafiken på varje enskild nod jämfört med trafiken som mottogs av den centraliserade servern.

The goal of this master thesis is creation of an online system serving as a performing application for presentation results of visual geo-localization in nature and mountain environment. The system offers the users to choose one of the pre-defined photographs or~to~upload one's own photography while choosing a file or inserting an URL address. The~system will localizate a camera of a given image based on a visual geo-localization. The~geo-localization uses the mountain horizon as a key characteristic when searching for similar horizons. The~curve line of the horizon is extracted by a fully automatic algorithm based on supervised learning and dynamic programming. Visual geo-localization running on the server which using new inversed index with cache politic. This allows further scaling of the system. The server processing detected horizon curve and respond with set of the best candidates on results. Results are visualised to the user in form of classic map, detailed sattelite view and rendering of found panorama.