This work has been aimed at developing a mechanistic, transient, 3-D numerical model to predict the behavior of an evaporating thin liquid film on a non-uniformly heated cylindrical rod with simultaneous parallel and cross flow of vapor. Interest in this problem has been motivated by the fact that the liquid film on a full-length boiling water reactor fuel rod may experience significant axial and azimuthal heat flux gradients and cross flow due to variations in the thermal-hydraulic conditions in surrounding subchannels caused by proximity to inserted control blade tip and/or the top of part-length fuel rods. Such heat flux gradients coupled with localized cross flow may cause the liquid film on the fuel rod surface to rupture, thereby forming a dry hot spot. These localized dryout phenomena can not be accurately predicted by traditional subchannel analysis methods in conjunction with empirical dryout correlations. To this end, a numerical model based on the Level Contour Reconstruction Method was developed. The Standard k- turbulence model is included. A cylindrical coordinate system has been used to enhance the resolution of the Level Contour Reconstruction Model. Satisfactory agreement has been achieved between the model predictions and experimental data. A model of this type is necessary to supplement current state-of-the-art BWR core thermal-hydraulic design methods based on subchannel analysis techniques coupled with empirical dry out correlations. In essence, such a model would provide the core designer with a "magnifying glass" by which the behavior of the liquid film at specific locations within the core (specific axial node on specific location within a specific bundle in the subchannel analysis model) can be closely examined. A tool of this type would allow the designer to examine the effectiveness of possible design changes and/or modified control strategies to prevent conditions leading to localized film instability and possible fuel failure.

Family conversation between homes is difficult to initiate at mutually agreeable times as neither participant has exact knowledge of the other's activities or intentions. Whether calling to plan an important family gathering or simply to connect with family members, the question is: Is now a good time to call? People expect friends and family to learn their activity patterns and to minimize interruptions when calling. Can technology provide awareness cues to the caller, even prior to the initiation of the call? This research focuses on sampling the everyday activities of home life to determine environmental factors, which may serve as an indicator for availability. These external factors may be effective for identifying household routines of availability and useful in determining when to initiate conversation across homes. Several workplace studies have shown a person's interruptibility can be reliably assessed and modeled from specific environmental cues; this work looks for similar predictive power in the home. Copresence, location, and activity in the home were investigated as correlates to availability and for their effectiveness within the social protocol of family conversation. These studies indicate there are activities that can be sensed, either in real-time or over some time span, that correlate to self-reported availability. However, the type and amount of information shared is dependent upon individual preferences, social accessibility, and patterns of activities. This research shows friends and family can improve their predictions of when to call if provided additional context, and suggests that abstract representations of either routines or explicit availability status is sufficient and may be preferred by providers. Availability prediction is feasible in the home and useful to those outside the home, but the level of detail to provide in particular situations needs further study. This work has implications for the development of groupware systems, the automatic sensing of activity to deal with interruption, and activity recognition in the home.

Diffuse optical tomography uses near infrared (NIR) light as the probing media to recover the distributions of tissue optical properties. It has a potential to become an adjunct imaging modality for breast and brain imaging, that is capable of providing functional information of the tissue under investigation. As NIR light propagation in the tissue is dominated by scattering, the image reconstruction problem (inverse problem) tends to be non-linear and ill-posed, requiring usage of advanced computational methods to compensate this. Traditional image reconstruction methods in diffuse optical tomography employ l2 –norm based regularization, which is known to remove high frequency noises in the re-constructed images and make them appear smooth. The recovered contrast in the reconstructed image in these type of methods are typically dependent on the iterative nature of the method employed, in which the non-linear iterative technique is known to perform better in comparison to linear techniques. The usage of non-linear iterative techniques in the real-time, especially in dynamical imaging, becomes prohibitive due to the computational complexity associated with them. In the rapid dynamic diffuse optical imaging, assumption of a linear dependency in the solutions between successive frames results in a linear inverse problem. This new frame work along with the l1–norm based regularization can provide better robustness to noise and results in a better contrast recovery compared to conventional l2 –based techniques. Moreover, it is shown that the proposed l1-based technique is computationally efficient compared to its counterpart(l2 –based one). The proposed framework requires a reasonably close estimate of the actual solution for the initial frame and any suboptimal estimate leads to erroneous reconstruction results for the subsequent frames. Modern diffuse optical imaging systems are multi-modal in nature, where diffuse optical imaging is combined with traditional imaging modalities such as MRI, CT, and Ultrasound. A novel approach that can more effectively use the structural information provided by the traditional imaging modalities in these scenarios is introduced, which is based on prior image constrained- l1 minimization scheme. This method has been motivated by the recent progress in the sparse image reconstruction techniques. It is shown that the- l1 based frame work is more effective in terms of localizing the tumor region and recovering the optical property values both in numerical and gelatin phantom cases compared to the traditional methods that use structural information.

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The Master's thesis is engaged in analyse of methods of pricing and comparison of each other. This work is compiled from historical evolution of prising immovables, over adjustment prising in international prising standards, over defination elementary conceptions to analysis selected ways of prising of houses. The Master's thesis analyses process of prising methods and analyses sources which we need to compile a ways of prising. These are most important things to know, when we want to compare ways of prising. There are ten houses in this work from Kroměříž and surroundings. The main target of master's thesis is to ratify and to explain that location of houses and their surroundings are the most importatnt. These two points of view influenced price and salableing of houses. There is a comparison of ways of prising houses at the end of work