A Novel Model-Free Data Analysis Technique Based on Clustering in a Mutual Information Space: Application to Resting-State fMRI

Non-parametric data-driven analysis techniques can be used to study datasets with few assumptions about the data and underlying experiment. Variations of independent component analysis (ICA) have been the methods mostly used on fMRI data, e.g., in finding resting-state networks thought to reflect the connectivity of the brain. Here we present a novel data analysis technique and demonstrate it on resting-state fMRI data. It is a generic method with few underlying assumptions about the data. The results are built from the statistical relations between all input voxels, resulting in a whole-brain analysis on a voxel level. It has good scalability properties and the parallel implementation is capable of handling large datasets and databases. From the mutual information between the activities of the voxels over time, a distance matrix is created for all voxels in the input space. Multidimensional scaling is used to put the voxels in a lower-dimensional space reflecting the dependency relations based on the distance matrix. By performing clustering in this space we can find the strong statistical regularities in the data, which for the resting-state data turns out to be the resting-state networks. The decomposition is performed in the last step of the algorithm and is computationally simple. This opens up for rapid analysis and visualization of the data on different spatial levels, as well as automatically finding a suitable number of decomposition components

Extreme scaling of brain simulation on JUGENE

QC 2011122

Personnel management strategy of the Nordea Bank

Bakalaura darba tēma ir „Personāla vadīšanas stratēģija Nordea Bankā”. Darbs sastāv no 3 daļām, secinājumiem un priekšlikumiem. Bakalaura darba pirmajā daļā ir personāla vadīšanas virzienu teorētiskais apraksts, otrajā daļā autore raksturo Nordea Banku un tās personāla politiku, kā arī izpētīja uzņēmuma stratēģiju, misiju, struktūru, darbības veidus un Nordea Bankas darbinieku priekšrocības programmu, savukārt trešā daļa ir veltīta personāla vadības stratēģijas nozīmei Nordea bankā. Bakalaura darba uzdevums ir teorētiski izpētīt un aprakstīt personāla vadīšanas būtību: personāla plānošanu, atlasi, novērtēšanu, motivāciju un lojalitāti, sniegt ieskatu par Nordea Banku, tās personāla politiku un darbinieku priekšrocībām un, veicot anketešanu, izpētīt un izanalizēt Nordea Bankas darbinieku motivācijas, lojalitātes un darba apstākļu apmierinātības līmeni. Izteikt priekšlikumus Nordea bankas personāla vadīšanas uzlabošanā. Bakalaura darba apjoms ir 62 lapas. Tajā ir iekļauti 18 attēli, 1 tabula un 3 pielikumi, kā arī tika izmantoti 23 literatūras avoti.The theme of the bachelor work is „Personnel management strategy of the Nordea Bank”. The bachelor work consists of three chapters, conclusions and suggestions. The first chapter of the bachelor work gives a theoretical description of the personnel management direction. The second chapter defines the Nordea Bank and its personnel policy, as well provides an examination of the organization strategy, mission, structure, work environment and benefit programme for the Nordea Bank personnel. The third chapter is devoted to the significance of the personnel management strategy in the Nordea Bank. The aim of the bachelor work is to examine theoretically and to describe the essence of the personnel management: personnel planning, selection, assessment, motivation and loyalty; to give a view of Nordea Bank, its personnel policy and benefits for its personnel, as well to carry out a survey-based examination and analysis of the personnel motivation, loyalty and satisfaction with working conditions. The aim of the work is also to make suggestions about improvement of the Nordea Bank personnel management. The volume of the bachelor work is 62 pages. The work is supplemented by 18 figures, 1 table and 3 appendices; 23 references were used in the work