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Design of energy efficient protocols-based optimisation algorithms for IoT networksAl-Janabi, Thair January 2018 (has links)
The increased globalisation of information and communication technologies has transformed the world into the internet of things (IoT), which is accomplished within the resources of wireless sensor networks (WSNs). Therefore, the future IoT networks will consist of high density of connected nodes that suffer from resource limitation, especially the energy one, and distribute randomly in a harsh and large-scale areas. Accordingly, the contributions in this thesis are focused on the development of energy efficient design protocols based on optimisation algorithms, with consideration of the resource limitations, adaptability, scalability, node density and random distribution of node density in the geographical area. One MAC protocol and two routing protocols, with both a static and mobile sink, are proposed. The first proposed protocol is an energy efficient hybrid MAC protocol with dynamic sleep/wake-up extension to the IEEE 802.15.4 MAC, namely, HSW-802.15.4. The model automates the network by enabling it to work exibly in low and high-density networks with a lower number of collisions. A frame structure that offers an enhanced exploitation for the TDMA time slots (TDMAslots) is provided. To implement these enhanced slots exploitation, this hybrid protocol rst schedules the TDMAsslots, and then allocates each slot to a group of devices. A three-dimensional Markov chain is developed to display the proposed model in a theoretical manner. Simulation results show an enhancement in the energy conservation by 40% - 60% in comparison to the IEEE 802.15.4 MAC protocol. Secondly, an efficient centralised clustering-based whale optimisation algorithm (CC- WOA) is suggested, which employs the concept of software de ned network (SDN) in its mechanism. The cluster formulation process in this algorithm considers the random di- versi cation of node density in the geographical area and involves both sensor resource restrictions and the node density in the tness function. The results offer an efficient con- servation of energy in comparison to other protocols. Another clustering algorithm, called centralised load balancing clustering algorithm (C-LBCA), is also developed that uses par- ticle swarm optimisation (PSO) and presents robust load-balancing for data gathering in IoT. However, in large scale networks, the nodes, especially the cluster heads (CHs), suffer from a higher energy exhaustion. Hence, in this thesis, a centralised load balanced and scheduling protocol is proposed utilising optimisation algorithms for large scale IoT net- works, named, optimised mobile sink based load balancing (OMS-LB). This model connects the impact of the Optimal Path for the MS (MSOpath) determination and the adjustable set of data aggregation points (SDG) with the cluster formulation process to de ne an op- timised routing protocol suitable for large scale networks. Simulation results display an improvement in the network lifespan of up to 54% over the other approaches.
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Tracking Atlantic Hurricanes Using Statistical MethodsMiller, Elizabeth Caitlin 01 January 2013 (has links)
Creating an accurate hurricane location forecasting model is of the utmost importance because of the safety measures that need to occur in the days and hours leading up to a storm's landfall. Hurricanes can be incredibly deadly and costly, but if people are given adequate warning, many lives can be spared. This thesis seeks to develop an accurate model for predicting storm location based on previous location, previous wind speed, and previous pressure. The models are developed using hurricane data from 1980-2009.
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SPEA2-based safety system multi-objective optimizationRiauke, Jelena January 2009 (has links)
Safety systems are designed to prevent the occurrence of certain conditions and their future development into a hazardous situation. The consequence of the failure of a safety system of a potentially hazardous industrial system or process varies from minor inconvenience and cost to personal injury, significant economic loss and death. To minimise the likelihood of a hazardous situation, safety systems must be designed to maximise their availability. Therefore, the purpose of this thesis is to propose an effective safety system design optimization scheme. A multi-objective genetic algorithm has been adopted, where the criteria catered for includes unavailability, cost, spurious trip and maintenance down time. Analyses of individual system designs are carried out using the latest advantages of the fault tree analysis technique and the binary decision diagram approach (BDD). The improved strength Pareto evolutionary approach (SPEA2) is chosen to perform the system optimization resulting in the final design specifications. The practicality of the developed approach is demonstrated initially through application to a High Integrity Protection System (HIPS) and subsequently to test scalability using the more complex Firewater Deluge System (FDS). Computer code has been developed to carry out the analysis. The results for both systems are compared to those using a single objective optimization approach (GASSOP) and exhaustive search. The overall conclusions show a number of benefits of the SPEA2 based technique application to the safety system design optimization. It is common for safety systems to feature dependency relationships between its components. To enable the use of the fault tree analysis technique and the BDD approach for such systems, the Markov method is incorporated into the optimization process. The main types of dependency which can exist between the safety system component failures are identified. The Markov model generation algorithms are suggested for each type of dependency. The modified optimization tool is tested on the HIPS and FDS. Results comparison shows the benefit of using the modified technique for safety system optimization. Finally the effectiveness and application to general safety systems is discussed.
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Systematic model-based safety assessment via probabilistic model checkingGOMES, Adriano José Oliveira 31 January 2010 (has links)
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Previous issue date: 2010 / Faculdade de Amparo à Ciência e Tecnologia do Estado de Pernambuco / A análise da segurança (Safety Assessment) é um processo bem conhecido que serve para
garantir que as restrições de segurança de um sistema crítico sejam cumpridas. Dentro dele, a
análise de segurança quantitativa lida com essas restrições em um contexto numérico
(probabilístico).
Os métodos de análise de segurança, como a tradicional Fault Tree Analysis (FTA), são
utilizados no processo de avaliação da segurança quantitativo, seguindo as diretrizes de
certificação (por exemplo, a ARP4761 Guia de Práticas Recomendadas da Aviação). No
entanto, este método é geralmente custoso e requer muito tempo e esforço para validar um
sistema como um todo, uma vez que para uma aeronave chegam a ser construídas, em média,
10.000 árvores de falha e também porque dependem fortemente das habilidades humanas para
lidar com suas limitações temporais que restringem o âmbito e o nível de detalhe que a análise e
os resultados podem alcançar. Por outro lado, as autoridades certificadoras também permitem a
utilização da análise de Markov, que, embora seus modelos sejam mais poderosos que as
árvores de falha, a indústria raramente adota esta análise porque seus modelos são mais
complexos e difíceis de lidar. Diante disto, FTA tem sido amplamente utilizada neste processo,
principalmente porque é conceitualmente mais simples e fácil de entender.
À medida que a complexidade e o time-to-market dos sistemas aumentam, o interesse em
abordar as questões de segurança durante as fases iniciais do projeto, ao invés de nas fases
intermediárias/finais, tornou comum a adoção de projetos, ferramentas e técnicas baseados em
modelos. Simulink é o exemplo padrão atualmente utilizado na indústria aeronáutica.
Entretanto, mesmo neste cenário, as soluções atuais seguem o que os engenheiros já utilizavam
anteriormente. Por outro lado, métodos formais que são linguagens, ferramentas e métodos
baseados em lógica e matemática discreta e não seguem as abordagens da engenharia
tradicional, podem proporcionar soluções inovadoras de baixo custo para engenheiros.
Esta dissertação define uma estratégia para a avaliação quantitativa de segurança baseada na
análise de Markov. Porém, em vez de lidar com modelos de Markov diretamente, usamos a
linguagem formal Prism (uma especificação em Prism é semanticamente interpretada como um
modelo de Markov). Além disto, esta especificação em Prism é extraída de forma sistemática a
partir de um modelo de alto nível (diagramas Simulink anotados com lógicas de falha do
sistema), através da aplicação de regras de tradução. A verificação sob o aspecto quantitativo
dos requisitos de segurança do sistema é realizada utilizando o verificador de modelos de Prism,
no qual os requisitos de segurança tornam-se fórmulas probabilísticas em lógica temporal.
O objetivo imediato do nosso trabalho é evitar o esforço de se criar várias árvores de falhas
até ser constatado que um requisito de segurança foi violado. Prism não constrói árvores de
falha para chegar neste resultado. Ele simplesmente verifica de uma só vez se um requisito de
segurança é satisfeito ou não no modelo inteiro.
Finalmente, nossa estratégia é ilustrada com um sistema simples (um projeto-piloto), mas
representativo, projetado pela Embraer
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Hidden Markov models for robust recognition of vehicle licence platesVan Heerden, Renier Pelser 11 November 2005 (has links)
In this dissertation the problem of recognising vehicle licence plates of which the sym¬bols can not be segmented by standard image processing techniques is addressed. Most licence plate recognition systems proposed in the literature do not compensate for dis¬torted, obscured and damaged licence plates. We implemented a novel system which uses a neural network/ hidden Markov model hybrid for licence plate recognition. We implemented a region growing algorithm, which was shown to work well when used to extract the licence plate from a vehicle image. Our vertical edges algorithm was not as successful. We also used the region growing algorithm to separate the symbols in the licence plate. Where the region growing algorithm failed, possible symbol borders were identified by calculating local minima of a vertical projection of the region. A multilayer perceptron neural network was used to estimate symbol probabilities of all the possible symbols in the region. The licence plate symbols were the inputs of the neural network, and were scaled to a constant size. We found that 7 x 12 gave the best character recognition rate. Out of 2117 licence plate symbols we achieved a symbol recognition rate of 99.53%. By using the vertical projection of a licence plate image, we were able to separate the licence plate symbols out of images for which the region growing algorithm failed. Legal licence plate sequences were used to construct a hidden Markov model contain¬ing all allowed symbol orderings. By adapting the Viterbi algorithm with sequencing constraints, the most likely licence plate symbol sequences were calculated, along with a confidence measure. The confidence measure enabled us to use more than one licence plate and symbol segmentation technique. Our recognition rate increased dramatically when we com¬bined the different techniques. The results obtained showed that the system developed worked well, and achieved a licence plate recognition rate of 93.7%. / Dissertation (MEng (Computer Engineering))--University of Pretoria, 2002. / Electrical, Electronic and Computer Engineering / unrestricted
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Analýza rizik v managementu projektů / Risks Analysis in Project ManagementPaulenda, Ján January 2011 (has links)
The main subject of this Master's thesis is risk management with emphasis on risk analysis stage. All important stages, definitions and techniques are introduced in the context of risk management. There are several risk analysis methods discussed in this thesis, especially the Markov analysis and the Petri net analysis. After the thorough analysis of the subject, the system to support the risk management was designed and implemented, while precisely Markov analysis was chosen.
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Improving Dependability of Space-Cloud Payload Processor by Storage SystemSaid, Hassan, Johansson, Stephanie Liza January 2023 (has links)
Due to the usage of complicated platforms and current high-performance space computing technology, onboard processing in small satellites is expanding. Space-cloud payload processors with Commercial Off-The-Shelf (COTS) components, that are required to be radiation-tolerant, are used to perform the onboard processing. In this thesis, the research will aim to increase the dependability of a generic space-cloud payload processor through its Solid State Drive (SSD) storage unit. To achieve this, a more dependable NAND-flash-based SSD Redundant Array of Independent Disc (RAID) storage system is designed and tested. The reliability of NAND-flash-based SSDs can suffer wear-outs due to increased Program/Erase (P/E) cycles, making them more prone to radiation effects. These radiation effects are considered non-destructive events in the form of bit errors (both single bit-flip and multiple bit-flips). Therefore, making the storage system more dependable involves increasing its reliability against non-destructive events and developing analytical models that account for the considered dynamic of the SSD RAID. The challenge that comes with achieving the aim of this thesis is twofold. First, to explore different RAID levels such that a combination of RAID levels can be incorporated into one SSD for better reliability than a RAID-1 setup. Hence, in this thesis, a RAID array of several SSDs is not considered. Furthermore, the combinations of RAID levels need to account for mixed-critical data. Second, to demonstrate, via simulation and analytical models, the impact on the reliability of the storage system. A comparison study is also undertaken due to the support that the Fourth Extended (Ext4) file system or Zettabyte File System (ZFS) may give to enhance the storage system, and since little research exists that compares the file systems in some feature categories. The solution is a RAID-5 + 6 storage system that is Error Detection And Correction (EDAC) protected by Hamming codes and Reed Solomon (RS) codes. Low-critical data is stored using RAID-5 whereas high-critical data is stored using RAID-6. The simulation of the storage system proves that low-critical stripes of data achieve single fault tolerance whereas high-critical stripes of data tolerate a maximum of 5-bit burst errors. In parallel, several Continuous Time Markov Chain (CTMC) models are analysed, which show that the proposed solution is indeed highly reliable. The comparison study is carried out in a systematic way, and the findings are established as substantial,i.e., ZFS provides greater storage system support. In summary, the results of creating the storage system and analysing it suggest that incorporating RAID-5 and RAID-6 offers better SSD RAID reliability than RAID-1. / Användningen av komplicerade plattformar och aktuell högpresterande rymdberäkningsteknik expanderar onboard-processing i små satelliter. Space-Cloud lösningar med kommersiellt tillgängliga komponenter som är toleranta mot strålningar i rymden används för att utföra onboard-processing. I detta examensarbete syftar forskningen till att förbättra tillförlitligheten hos en generisk rymd dator genom dess SSD-lagringsenhet. För att uppnå detta har ett mer tillförlitligt lagringssystem bestående av NAND-flash och RAID designats och testats. Tillförlitligheten hos NAND-flash-baserade SSD:er kan försämras då dessa kan drabbas av slitage på grund av ökade P/E cykler, vilket gör dem mer benägna för strålningseffekter. Dessa strålningseffekter anses vara icke-destruktiva i form av bit-fel (både enskilda bit-flippar och flera bit-flippar). Med denna anledning görs lagringssystemet mer tillförlitligt för att tolerera icke-destruktiva händelser. Utöver detta, utvecklas analytiska modeller som tar hänsyn till den betraktade dynamiken i SSD RAID. Utmaningen som följer med att uppnå syftet med denna avhandling är tvådelad. För det första, för att utforska olika RAID-nivåer så att en kombination av RAID-nivåer kan inkorporeras i en SSD för bättre tillförlitlighet än RAID-1. Således övervägs inte en RAID-array av flera SSD:er i denna avhandling. Dessutom måste kombinationerna av RAID-nivåer ta hänsyn till data av olika kritikalitet. För det andra, för att genom simulering och analytiska modeller indikera påverkan på lagringssystemets tillförlitlighet. En jämförelsestudie genomförs också på grund av stödet som filsystemen Ext4 eller ZFS kan ge för att förbättra lagringssystemet och eftersom det finns lite forskning som jämför filsystemen i några funktionella kategorier. Lösningen baseras på ett RAID-5+6 lagringssystem som är skyddat av Hamming-koder och RS koder för att upptäcka fel och korrigera dem. Lågkritisk data lagras med RAID-5 medan högkritisk data lagras med RAID-6. Simuleringen av lagringssystemet visar att lågkritiska datasektioner uppnår en fel tolerans mot enskilda bit-flippar medan högkritiska datasektioner kan tåla maximalt 5 bit-flippar. Samtidigt analyseras flera CTMC modeller som visar att den föreslagna lösningen verkligen är mycket tillförlitlig. Jämförelsestudien utförs på ett systematiskt sätt och resultaten fastställs som betydande, det vill säga att ZFS ger större stöd för lagringssystemet. Sammanfattningsvis antyder resultaten av att skapa lagringssystemet och analysera det att inkorporering av RAID-5 och RAID-6 erbjuder bättre tillförlitlighet för SSD RAID än RAID-1.
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Spatio-temporal dynamics in land use and habit fragmentation in Sandveld, South AfricaJames Takawira Magidi January 2010 (has links)
<p>This research assessed landuse changes and trends in vegetation cover in the Sandveld, using remote sensing images. Landsat TM satellite images of 1990, 2004 and 2007 were classified using the maximum likelihood classifier into seven landuse classes, namely water, agriculture, fire patches, natural vegetation, wetlands, disturbed veld, and open sands. Change detection using remote sensing algorithms and landscape metrics was performed on these multi-temporal landuse maps using the Land Change Modeller and Patch Analyst respectively. Markov stochastic modelling techniques were used to predict future scenarios in landuse change based on the classified images and their transitional probabilities. MODIS NDVI multi-temporal datasets with a 16day temporal resolution were used to assess seasonal and annual trends in vegetation cover using time series analysis (PCA and time profiling).Results indicated that natural vegetation decreased from 46% to 31% of the total landscape between 1990 and 2007 and these biodiversity losses were attributed to an increasing agriculture footprint. Predicted future scenario based on transitional probabilities revealed a continual loss in natural habitat and increase in the agricultural footprint. Time series analysis results (principal components and temporal profiles) suggested that the landscape has a high degree of overall dynamic change with pronounced inter and intra-annual changes and there was an overall increase in greenness associated with increase in agricultural activity. The study concluded that without future conservation interventions natural habitats would continue to disappear, a condition that will impact heavily on biodiversity and significant waterdependent ecosystems such as wetlands. This has significant implications for the long-term provision of water from ground water reserves and for the overall sustainability of current agricultural practices.</p>
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Spatio-temporal dynamics in land use and habit fragmentation in Sandveld, South AfricaJames Takawira Magidi January 2010 (has links)
<p>This research assessed landuse changes and trends in vegetation cover in the Sandveld, using remote sensing images. Landsat TM satellite images of 1990, 2004 and 2007 were classified using the maximum likelihood classifier into seven landuse classes, namely water, agriculture, fire patches, natural vegetation, wetlands, disturbed veld, and open sands. Change detection using remote sensing algorithms and landscape metrics was performed on these multi-temporal landuse maps using the Land Change Modeller and Patch Analyst respectively. Markov stochastic modelling techniques were used to predict future scenarios in landuse change based on the classified images and their transitional probabilities. MODIS NDVI multi-temporal datasets with a 16day temporal resolution were used to assess seasonal and annual trends in vegetation cover using time series analysis (PCA and time profiling).Results indicated that natural vegetation decreased from 46% to 31% of the total landscape between 1990 and 2007 and these biodiversity losses were attributed to an increasing agriculture footprint. Predicted future scenario based on transitional probabilities revealed a continual loss in natural habitat and increase in the agricultural footprint. Time series analysis results (principal components and temporal profiles) suggested that the landscape has a high degree of overall dynamic change with pronounced inter and intra-annual changes and there was an overall increase in greenness associated with increase in agricultural activity. The study concluded that without future conservation interventions natural habitats would continue to disappear, a condition that will impact heavily on biodiversity and significant waterdependent ecosystems such as wetlands. This has significant implications for the long-term provision of water from ground water reserves and for the overall sustainability of current agricultural practices.</p>
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Spatio-temporal dynamics in land use and habit fragmentation in Sandveld, South AfricaMagidi, James Takawira January 2010 (has links)
Magister Scientiae (Biodiversity and Conservation Biology) - MSc (Biodiv and Cons Biol) / This research assessed landuse changes and trends in vegetation cover in the Sandveld, using remote sensing images. Landsat TM satellite images of 1990, 2004 and 2007 were classified using the maximum likelihood classifier into seven landuse classes, namely water, agriculture, fire patches, natural vegetation, wetlands, disturbed veld, and open sands. Change detection using remote sensing algorithms and landscape metrics was performed on these multi-temporal landuse maps using the Land Change Modeller and Patch Analyst respectively. Markov stochastic modelling techniques were used to predict future scenarios in landuse change based on the classified images and their transitional probabilities. MODIS NDVI multi-temporal datasets with a 16day temporal resolution were used to assess seasonal and annual trends in vegetation cover using time series analysis (PCA and time profiling).Results indicated that natural vegetation decreased from 46% to 31% of the total landscape between 1990 and 2007 and these biodiversity losses were attributed to an increasing agriculture footprint. Predicted future scenario based on transitional probabilities revealed a continual loss in natural habitat and increase in the agricultural footprint. Time series analysis results (principal components and temporal profiles) suggested that the landscape has a high degree of overall dynamic change with pronounced inter and intra-annual changes and there was an overall increase in greenness associated with increase in agricultural activity. The study concluded that without future conservation interventions natural habitats would continue to disappear, a condition that will impact heavily on biodiversity and significant waterdependent ecosystems such as wetlands. This has significant implications for the long-term provision of water from ground water reserves and for the overall sustainability of current agricultural practices. / South Africa
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