In this article we analyse the structure of Markov processes and reciprocal processes to underline their time symmetrical properties, and to compare them. Our originality consists in adopting a unifying approach of reciprocal processes, independently of special frameworks in which the theory was developped till now (diffusions, or pure jump processes). This leads to some new results, too.

El sector porquí Espanyol ha sofert recentment profuns canvis degut bàsicament al'augment de la competència i al procés de globalització econòmica. Ademes, elsavenços tecnológicos i el grau creixent d'especialització en el sector afavoreixen eldesenvolupament i l'adopció de eienes avançades per a la pressa de decisions. Enaquest context, l'objectiu d'aquesta Tesi ha estat formular i implementar un modeldinàmic estocàstic del comportament productiu d'un remat de truges, basat enprocessos de decisió Markovians i capaç d'ésser utilitzat en condicions reals. Lafinalitat del model és representar alternatives de maneig reproductiu i de reposició enexplotacins porcines per assistir als grangers, tècnics i gerents en la pressa dedecisions en granja.El model de decisió semi-Markovià i el Markovià que s'en deriva del primer handemostrat ser models útils per la representació de les estratègies productives demaneig reproductiu i de la reposició. La disponibilitat de dades de camp de grangesindividuals ha permès la validació del model en situacions reals. La validació ha servittambé per mostrar com el model no pot ser aplicat indiscriminadament a qualsevolgranja, prèviament s'ha d'assegurar l'ajust del model a les condicions concretes decada explotació. També s'ha ficat de manifest que quan el model s'utilitza per acalcular l'estructura de la població a l'equilibri no és necessari que la matriu detransició representi el pas de temps constant, la qual cosa ha permès treballar ambtransicions associades als estats biològics que són més fàcils d'estimar (embeddedMarkov process), ademes, proporcionen estalvis computacionals que permeten unaavaluado més ràpida d'alternatives de maneig reproductiu i la implementaciód'algorismes d'optimització pel problema de la reposició més eficientes.La implementació del model de decisió semi-Markovià dins d'un sistema d'ajut a lapressa de decisions (DSS: Decision Support Systems) ha mostrat l'ús potencial delmodel en granja. El desenvolupament del DSS ha facilitat la disponibilitat d'un modelcomplex com el presentat a potencials usuaris menys especialitzats. El DSS permet algranger avaluar a peu de granja diferentes alternatives productives, analitzar lasensibilitat dels paràmetres que consideri crítics i optimitzar la política de reposició.Ademes, la integració del DSS en un sistema de gestió informatitzat (BDporc®2)facilita la difusió del DSS en empreses de producció porcina i també l'obtenció denoves variables com el número de serveis por monta, la detecció de zels, la deteccióde la gestació, instalacions, etc, que poden ajudar a incrementar la precisió delsresultats. El disseny sofisticat del interface del DSS ha millorat la interpretació delsresultats del model que no sempre és inmediata. La incorporació de l'anàlisi desensibilitat permet estudiar i profunditzar en els components crítics del model quesovint resulta més important que l'obtenció d'un resultat precis. Finalment, el model deremat formulat de forma flexible, és capaç d'adaptar-se a diferents propòsits ambcanvis mínims, la qual cosa contribueix a una millor comprensió dels efectes dediferentes alternatives de maneig reproductiu sobre la millora de la eficiènciaeconòmica de tot el sistema productiu. / El sector porcino en España ha sufrido recientemente profundos cambios debidobásicamente al aumento de la competencia y al proceso de globalización económica.Además, los avances tecnológicos y el creciente grado de especialización en el sectorfavorecen el desarrollo y la adopción de herramientas avanzadas para la toma dedecisiones. En este contexto, el objetivo de esta Tesis es presentar la formulación e¡mplementadón de un modelo dinámico estocástico del comportamiento productivo deun rebaño de cerdas, basado en procesos de decisión Markovianos y capaz de serusado en condiciones reales. La finalidad del modelo es representar alternativas demanejo reproductivo y de reposición en explotacines porcinas para asistir a granjeros,técnicos y gerentes en la toma de decisiones en granja.El modelo de decisión semi-Markovianos y el Markoviano que deriva del primero handemostrado ser modelos útiles en la representación de las estrategias productivas demanejo reproductivo y de la reposición. La disponibilidad de datos de campo degranjas individuales ha permitido la validación del modelo en situaciones reales. Lavalidación ha servido también para mostrar como el modelo no puede ser aplicadoindiscriminadamente en cualquier granja, previamente se asegurar el ajuste delmodelo a las condiciones concretas de cada explotación. También se ha puesto demanifiesto que cuando el modelo se utiliza para calcular la estructura de la poblaciónen equilibrio no es necesario que la matriz de transición represente de paso de tiempoconstante, con lo cual ha sido posible trabajar con transiciones asociadas a losestados biológicas que son más fáciles estimar (embedded Markov process), además,proporcionan ahorros computacionales que permiten una evaluación más rápida dealternativas de manejo reproductivo y la implementación de algoritmos de optimizaciónpara el problema de la reposición más eficientes.La implementación del modelo de decisión semi-Markoviano dentro de un sistema deayuda a la toma de decisiones (DSS: Decision Support Systems) ha mostrado el usopotencial del modelo en granja. El desarrollo del DSS ha facilitado la disponibilidad deun modelo complejo como el presentado a potenciales usuarios menos especializados.El DSS permite al granjero evaluar a pie de granja diferntes alternativas productivas,analizar la sensibilidad de los parámetros que considere críticos y optimiza la políticade reposición. Además, la integración del DSS en un sistema de gestión informatizado(BDporc®3) facilita la difusión del DSS en empresas de producción porcina y tambiénla obtención de nuevas variables como el número de servicios por monta, la detecciónde celos, la detección de la gestación, instalaciones, etc, que pueden ayudar aincrementar la precisión de los resultados. El diseño sofisticados del interface del DSSha mejorado la interpretación de los resultados que no siempre es inmediata. Elanálisis de sensibilidad incorporado permite estudiar y profundizar en los componentescríticos del modelo que a menudo resulta más importante que el disponer de unresultado preciso. Finalmente, el modelo de rebaño formulado de forma flexible, escapaz de adaptarse a distintos propósitos con cambios mínimos, lo que redunda enuna mejor compresión de los efectos de diferentes alternativas de manejo reproductivoa fin de mejorar la eficiencia económica de todo el sistema productivo. / Spanish pig sector has gone through a deep change during recent times, that is duebasically to the increase in competitiveness and the globalisation process of theeconomics. Furthermore, technological advances and the increasing degree ofspecialisation have maden possible the development and adoption of advanced toolsfor decision support. In this context, the objective of this Thesis has been to formulateand implement a dynamic estochastic model representing the productive behaviour ofa sow herd, based on Markov decision processes. The model was aimed to be used infield condicions to analyse different management alternatives on reproduction andreplacement, supporting farm managers in the decision-making process.The semi-Markovià decision model and the derived Markov decision model (embeddedMarkov process) have demonstrated to be useful in the representation of managementalternatives on reproduction and replacement. The availability of data from individualfarms has allowed the validation of the model in real situations. The validation also hasserved to show how the model can not be applied indiscriminately on any farm.Previously, it has been required to assess the fit of the model in specific farmconditions. Also, it is shown that when the model has been used to calculate thepopulation structure at equilibrium was not necessary a transition matrix being timestep constant. Instead have been possible to consider transitions associated tobiological states that are easier to estimate, more precise and provided computationaltime savings. Hence the model, as it was formulated, allowed a faster evaluation ofmanagement alternatives on reproduction and an efficient impleemntation of algorithmsto optimise replacement policies.The implementation of the semi-Markov model into a DSS (DSS: Decision SupportSystems) has shown the potential on-farm use of the model. The development of theDSS makes easier the availability of complex models to less specialised users. TheDSS allows the farm manager to evaluate on-farm different management alternativeson reproduction and optimise replacement decisions. Moreover, the integration of theDSS in a management information system (BDporc®1) makes easier the spreading of itover swine enterprises, as well the obtention of new variables like the number ofservices by mating, heat detections, pregnancy detection, facilities, etc, can help toincrement model precision. The sophisticated dessign of the DSS interface hasimproved the interpretation of the model results, that not always is right direct. Theaddition of sensitivity análisis capability provided insight about the impact of changes incritical components of the model, that quite often result in a more interest than a singleprecise result. Finally, the sow herd model formulated in a flexible way, was able to beadapted to différents goals with minimum changes, thus it contribute to improve theknowledge about the effect of different management alternatives on overall economicefficiency of the system.

Denna uppsats redogör för olika begrepp, metoder och beräkningar som är nödvändiga för att optimera sin spelstrategi i tärningsspelet Yatzy. De begrepp som tas upp i denna uppsats är bl.a. vad Markov-kedjor, sållprincipen och framför allt vad väntevärden är för något, och hur vi kan tillämpa dessa begrepp i spelet Yatzy. Metoderna som har använts när vi beräknat väntevärden kommer i många fall vara relativt likvärdiga, men vi kommer även att påvisa skiljaktigheter. Tanken med uppsatsen är att i varje situation som kan uppstå under spelets gång, kunna välja den spelstrategi som leder till så optimala förhållanden som möjligt.

Over the last fifty years financial markets have seen an enormous expansion and development both in size and variety. An industry that was once small and secluded has transformed into an essential part of today’s economy. Such changes should in part be attributed to substantial advances in computer technology. The latest allowed for a transition from face-to-face trading on organized exchanges to a distributed system of electronic markets with new mechanisms serving the purposes of efficiency, transparency and liquidity. In majority of cases this new trading system is driven by a double auction market mechanism, in which market participants submit buy and sell orders, aiming to strike a balance between certainty of execution and attractiveness of trade price. Generally, information about outstanding buy and sell orders is made available to market participants in the form of a limit order book. It has been suggested by multiple prior research that limit order books contain information that could be used to derive market sentiment and predict future price movement. In the current study we have presented ideas behind double auction market mechanism and have attempted to model run and reversal market regimes using a simple and intuitive Hierarchical Hidden Markov Model. We have proposed a statistical measure of the limit order book imbalance and have used it to build observation (feature) vector for our model. We have built Limit Order Book analyzer – the software tool that has become essential for data cleaning and validation, as well as extraction of feature vector components from the data. We have used the model on high frequency tick-by-tick trade and limit order book data from the Toronto Stock Exchange. We have performed the analysis of computational results; for this purpose we have used a sample of annualized returns of stocks which comprised the TSX60 index at the time of data collection; we have performed the comparative analysis of our results with a simple daily buy & hold trading strategy as well as results of the trade price and volume model presented in the prior research.

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Cloud computing provides business new working paradigm with the benefit of cost reduce and resource sharing. Tasks from different users may be performed on the same machine. Therefore, one primary security concern is whether user data is secure in cloud. On the other hand, hacker may facilitate cloud computing to launch larger range of attack, such as a request of port scan in cloud with virtual machines executing such malicious action. In addition, hacker may perform a sequence of attacks in order to compromise his target system in cloud, for example, evading an easy-to-exploit machine in a cloud and then using the previous compromised to attack the target. Such attack plan may be stealthy or inside the computing environment, so intrusion detection system or firewall has difficulty to identify it. The proposed detection system analyzes logs from cloud to extract the intensions of the actions recorded in logs. Stealthy reconnaissance actions are often neglected by administrator for the insignificant number of violations. Hidden Markov model is adopted to model the sequence of attack performed by hacker and such stealthy events in a long time frame will become significant in the state-aware model. The preliminary results show that the proposed system can identify such attack plans in the real network.

We present a new detection model include monitoring network perimeter and hosts logs to counter the new method of attacking involve different hosts source during an attacking sequence. The new attacking sequence we called ¡§Scout and Intruder¡¨ involve two separate hosts. The scout will scan and evaluate the target area to find the possible victims and their vulnerability, and the intruder launch the precision strike with login activities looked as same as authorized users. By launching the scout and assassin attack, the attacker could access the system without being detected by the network and system intrusion detection system. In order to detect the Scout and intruder attack, we correlate the netflow connection records, the system logs and network data dump, by finding the states of the attack and the corresponding features we create the detection model using the Hidden Markov Chain. With the model we created, we could find the potential Scout and the Intruder attack in the initial state, which gives the network/system administrator more response time to stop the attack from the attackers.

Two models are proposed to describe interactions among genes, transcription factors, and signaling cascades involved in regulating a cellular sub-system. These models fall within the class of Markovian regulatory networks, and can accommodate for different biological time scales. These regulatory networks are used to study pathological cellular dynamics and discover treatments that beneficially alter those dynamics. The salient translational goal is to design effective therapeutic actions that desirably modify a pathological cellular behavior via external treatments that vary the expressions of targeted genes. The objective of therapeutic actions is to reduce the likelihood of the pathological phenotypes related to a disease. The task of finding effective treatments is formulated as sequential decision making processes that discriminate the gene-expression profiles with high pathological competence versus those with low pathological competence. Thereby, the proposed computational frameworks provide tools that facilitate the discovery of effective drug targets and the design of potent therapeutic actions on them. Each of the proposed system-based therapeutic methods in this dissertation is motivated by practical and analytical considerations. First, it is determined how asynchronous regulatory models can be used as a tool to search for effective therapeutic interventions. Then, a constrained intervention method is introduced to incorporate the side-effects of treatments while searching for a sequence of potent therapeutic actions. Lastly, to bypass the impediment of model inference and to mitigate the numerical challenges of exhaustive search algorithms, a heuristic method is proposed for designing system-based therapies. The presentation of the key ideas in method is facilitated with the help of several case studies.

Wireless network analysis and simulations rely on accurate physical layer models. The increased interest in wireless network design and cross-layer design require an accurate and efficient physical layer model especially when a large number of nodes are to be studied and building the real network is not possible. For analysis of upper layer characteristics, a simplified physical layer model has to be chosen to model the physical layer. In this dissertation, the widely used two-state Markov model is examined and shown to be deficient for low to moderate signal-to-noise ratios. The physical layer statistics are investigated, and the run length distributions of the good and bad frames are demonstrated to be the key statistics for accurate physical layer modeling. A four-state Markov model is proposed for the flat Rayleigh fading channel by approximating the run length distributions with a mixture of exponential distributions. The transition probabilities in the four-state Markov model can be established analytically without having to run extensive physical layer simulations, which are required for the two-state Markov model. Physical layer good and bad run length distributions are compared and it is shown that the four-state Markov model reasonably approximates the run length distributions. Ns2 simulations are performed and the four-state Markov model provides a much more realistic approximation compared to the popular two-state Markov model. Achieving good results with the flat Rayleigh fading channel, the proposed four-state Markov model is applied to a few diversity channels. A coded orthogonal fre- quency division multiplexing (OFDM) system with a frequency selective channel and the Alamouti multiple-input multiple-output system are chosen to verify the accuracy of the four-state Markov model. The network simulation results show that the four-state Markov model approximates the physical layer with diversity channel well whereas the traditional two-state Markov model estimates the network throughput poorly. The success of adapting the four-state Markov model to the diversity channel also shows the flexibility of adapting the four-state Markov model to various channel conditions.

The objective of this thesis is to enhance the reliability analysis of Relaying systems and build-up model by Markov theory for taipower transmission lines. The set of combinatory multi-elements can be expressed a transition matrix for any pilot protection analysis. The protective reliability system need for transmission protection is introduced and the block modeling consists of protective relays, communication set and circuit breaker. The block modeling is applied for the analysis of the reliability and availability of protection systems by Markov theory, which can be need to derive the adapative maintance cycle by Markov reliability modeling. The system reliability is analysis related to the interruption of supply power. There many methods to be used for the analysis of system reliability such as state space, network. etc. The Markov modeling is more complicated and difficult, however better time-vary probability functions can be defined, for stochastic modeling, the system reliability at any time axis can be obtained by Markov transition matrix, with the time-vary Markov transition matrix. The customers served by each substation can be affected according to the states of transmission lines healthy. Althouth 80% of system faults occurs in the distribution system, transmission line faults will cause more serious service outage. According to the Kauo-Ping transmission line model in taipower, the optimal protection relay planning is solved by minimizing the overall outage cost of customer service interruption and investment protection relay equipments for transmission power systems with immune algorithm. The objective function and constraints are expressed as antigen, and all feasible solutions are expressed as antibody. The diversity of antibody is then enhanced by proximity of antigen so that the global optimization during the solution process can be obtained. It is found that the power service can be restored effectively with the optimal planning of protection relay by the proposed immune algorithm. Based on the computer simulation of protection relay planning, different protection relaying strategies optimal relay planning and customer loss, can be considered for different to enhance the reliability of protection relay system for loss interruption of customer power outage.