One of the legal issues, which brought by the development of information and communication technologies, is also the issue of domain names. With the development of the Internet, many human activities moved into the electronic world, including business activities. Presentation of the business through a website has become an indispensable means of competition. Domain names became a significant asset with regard to its secondary function. Therefore it was necessary to provide legal protection for domain names.Legal system of the Czech Republic does not contain specific legal act of domain names. This thesis deals with the issue of domain names. The object of this thesis is the definition of a domain name from a legal terms, the rights to domain names and registration of domain names. This thesis is limited to domain names, which are registrated in ccTLD .cz. The second part discusses the relationship between domain names and trademarks. In relation to the trademark rights the domain name has dual status. Registration of a sign as a domain name can occur the rights of trademarks. The trademark is one of the most effective means of protection for domain names. It is possible providing protection of domain names with registration in the register of trademarks.The owner of the domain name then has the same rights...

Abstract   Many researchers in social work believe that in today's society require the interaction between organisations takes place on social problems. This study examined the interaction between the police, social services and schools. The purpose of this study are as follows; the aim is to investigate the interaction between social services, the police and schools about young people aged 12-18 years who are at risk for abuse and crime. My questions are: How do the different professions interact regarding young people at risk for abuse and crime? How do they meet young people in their daily work? What obstacles can the different professions see in interaction? What effects do the different professions see in interaction? The study is a qualitative study conducted with semi-structured interviews. Respondents have been two from each organisation. The theory used in the analysis of empirical data is new-institutionalismen. New-institutionalism is a theory developed from organizational theories. Research emanating from organizations influence from the outside world has been designated a new - institutionalism. The new institutionalism is based on individuals, and environmental impact on the organization, as well as their interaction The results of the study mean that different privacy laws are an obstacle in the interaction and also lack of resources is a barrier. This study also shows a positive attitude towards interaction between the different organizations.   Keywords: Interaction, Police, Social service, School, Obstacle, Domain consensus, Domain conflict

The finite-difference time-domain (FDTD) method is one of the most popular numerical electromagnetic analysis tools. This method has been applied to a wide variety of problems such as antennas, electronic packaging, waveguides, etc. However, it is not suitable for large scale structures. The enormous memory requirement prohibits the use of FDTD to a large electrical size. Recently, the pseudospectral time-domain (PSTD) method has been introduced for solution of Maxwell¡¦s equation. This method adopts the Fourier transform algorithm to perform the spatial derivatives. According to Nyquist sampling theorem, it requires only 2 cells per wavelength, so that it is possible to efficiently model larger scale problems. This thesis describes a combination of PSTD and FDTD method applied in different directions. The FDTD be applied to directions along fine structures and the PSTD be applied in direction along large structures.

In order to maintain a continuous power suppply, nowadays relays in transmission systems are required to be able to deal with complicated faults involving non-conventional connections, which poses a challenge to the short circuit analysis performed for the data settings of the relay. The traditional sequence domain method has congenital defects to treat such cases, which leads to a trend of using the actual phase domain method in fault calculation. Although the calculation speed of the phase domain method is not so fast and is memory consumable, it perfomrs well when handling complicated faults. Today more and more commercial software involves phase domain calculation in their short circuit analysis to treat complicated cases. With the advanced development of computers, there is a possibility to totally get rid of the sequence method. In this thesis, a short circuit analysis method based on phase domain is developed. After the three sequence admittance matrices of the system are built, all the data are transformed into phase domain to get the phase domain admittance matrix. The following fault calculations are performed purely in phase domain. The test results of different types of faults in 3 bus, 14 bus, and 30 bus transmission systems are presented and compared with the results of a commercial fault analysis software. The validation of this program is also presented.

Thesis (M.S.) -- Central Connecticut State University, 2009. / Thesis advisor: John E. Harmon. "... in partial fulfillment of the requirements for the degree of Master of Science in Geography." Includes bibliographical references (leaves 75-79). Also available via the World Wide Web.

Calpains are intracellular enzymes that merge cysteine protease and calcium sensing activities together in one molecule. They respond to Ca2+ signals and modify the activity of their targets by selective proteolysis. Calpains are involved in normal cellular process like cell migration and apoptosis. The over-activation of calpain due to disturbances in Ca2+ homeostasis or inactivation due to mutations, contribute to diseases like ischemic injury and muscular dystrophy. The classical calpains 1 and 2 are heterodimeric enzymes containing a large (80 kDa) subunit and a small subunit (28 kDa). Dimerization occurs through the 5th EF-hand of penta-EF-hand (PEF) domains present in both large and small subunits. In this study, I have used structural genomics approaches to explore the PEF and C2-like regulatory domains of some of the other 12 human calpain isoforms. I have shown that recombinant PEF domain of skeletal muscle-specific calpain 3 exists as a stable homodimer when produced alone. Modelling studies suggest that there would be no barriers for dimerization of the full-length enzyme through the PEF domains which would place the protease cores at opposite ends of the dimer. Co-expression studies using small subunit were performed with PEF domains of calpains 1, 3, 8, 9, 11, 12 and 13. A differential tagging system was devised to differentiate heterodimers from homodimers. The PEF domains of calpains 1, 3, 9 and 13 co-expressed with the small subunit, while the others failed to express. The PEF domains of calpains 1 and 9 formed heterodimers. Conversely, the PEF domain of calpain 3 formed a homodimer and that of calpain 13 predominantly formed a homodimer with a small amount of heterodimer. Homodimerization of calpains implies they are less-likely to be inhibited by the endogenous calpain inhibitor, calpastatin. C2-like regulatory domains of calpains 5-13 were also studied. The structure of the distal C2-like domain of calpain 7 was solved. It is markedly different from canonical C2 domains and may not bind Ca2+. / Thesis (Ph.D, Biochemistry) -- Queen's University, 2009-02-11 12:30:29.18

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In the field of machine learning (ML) a very commonly encountered problem is the lack of generalizability of learnt classification functions when subjected to new samples that are not representative of the training distribution. The discrepancy between the training (a.k.a. source) and test (a.k.a.target) distributions are caused by several latent factors such as change in appearance, illumination, viewpoints and so on, which is also popularly known as domain-shift. In order to make a classifier cope with such domain-shifts, a sub-field in machine learning called domain adaptation (DA) has emerged that jointly uses the annotated data from the source domain together with the unlabelled data from the target domain of interest. For a classifier to be adapted to an unlabelled target data set is of tremendous practical significance because it has no associated labelling cost and allows for more accurate predictions in the environment of interest. A majority of the DA methods which address the single source and single target domain scenario are not easily extendable to many practical DA scenarios. As there has been as increasing focus to make ML models deployable, it calls for devising improved methods that can handle inherently complex practical DA scenarios in the real world. In this work we build towards this goal of addressing more practical DA settings and help realize novel methods for more real world applications: (i) We begin our work with analyzing and addressing the single source and single target setting by proposing whitening-based embedded normalization layers to align the marginal feature distributions between two domains. To better utilize the unlabelled target data we propose an unsupervised regularization loss that encourages both confident and consistent predictions. (ii) Next, we build on top of the proposed normalization layers and use them in a generative framework to address multi-source DA by posing it as an image translation problem. This proposed framework TriGAN allows a single generator to be learned by using all the source domain data into a single network, leading to better generation of target-like source data. (iii) We address multi-target DA by learning a single classifier for all of the target domains. Our proposed framework exploits feature aggregation with a graph convolutional network to align feature representations of similar samples across domains. Moreover, to counteract the noisy pseudo-labels we propose to use a co-teaching strategy with a dual classifier head. To enable smoother adaptation, we propose a domain curriculum learning ,when the domain labels are available, that adapts to one target domain at a time, with increasing domain gap. (iv) Finally, we address the challenging source-free DA where the only source of supervision is a source-trained model. We propose to use Laplace Approximation to build a probabilistic source model that can quantify the uncertainty in the source model predictions on the target data. The uncertainty is then used as importance weights during the target adaptation process, down-weighting target data that do not lie in the source manifold.

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