2 research outputs found
Project: Establishment of the health centre "Sahasra" LTD
No full textMaģistra darba ietvaros tiek izstrādāts autores izdomāts projekts „Veselības centra SIA „Sahasra” izveide”. Projekta idejas pamatā ir nepieciešamība risināt cilvēku psihoemocionālās veselības problēmas, savlaicīgi ārstēt tādas psihiska rakstura problēmas kā depresija, paaugstināts stresa līmenis, izdegšanas sindroms un līdzvērtīgas problēmas. Darba ietvaros ir aprakstīta un analizēta jaunas, specializētas veselības iestādes dibināšana, kuras darbības pamatā ir tradicionālās un netradicionālās medicīnas ārstēšanas metožu komplekss pielietojums. Projekta izstrādes ietvaros autore apskatīja būtiskākos ar projekta īstenošanu saistītos aspektus, veicot padziļinātu nozares izpēti, potenciālo klientu apzināšanu, kā arī izstrādājot projekta finanšu un īstenošanas plānus. Autore norāda, ka projekta realizēšanas gadījumā, tam būs izteikti pozitīva sociālā un ekonomiskā ietekme.Within the framework of the master's thesis the author developed the project “Establishment of the health centre "Sahasra" LTD which is hereby examined. The idea of the project is based on the need to improve the human’s psycho-emotional health issue and ensure timely treatment of such health problems as depression, heightened stress level, burnout syndrome and such alike. In scope of this master’s thesis the establishment of a new medical institution is examined and described, where the complex of traditional and alternative medical treatment will be used. While developing the project the author managed it’s most essential aspects. Within the project, the in-depth industry research, the profile of potential customers and the development of financial and project implementation projections had been done. The author stresses, that if fulfilled the project will bring notably positive social and economic impact
An Innovative Hybrid Approach to Forecasting Soluble Oxygen for Optimal Water Purification in Highly Concentrated Aquaculture
No full textAn important measure of the water\u27s quality in an aquaculture setting is the concentration of dissolved oxygen. Disintegrating oxygen content prediction using conventional techniques is slow and inaccurate due to the complexity, nonlinearity, and dynamics of the process. This research develops a hybrid model that addresses these problems by combining the radiation gradient enhancement machine (LightGBM) with this simple rechargeable unit (Biru). The first step was to find the important parameters by using linear interpolation and smoothing. After removing superfluous variables, the LightGBM algorithm predicts dissolved oxygen in highly intensive aquaculture and establishes its relevance. Lastly, the attention approach was used to map the learning parameter matrices and weighting matrices, allowing various weights to be applied to the Biru\u27s hidden states. The results show that the given prediction model can capture the upward trend of oxygen dissolution fluctuations over a 10-day period with a rate of accuracy reaching 96.28% in only 122 seconds. It takes the least amount of time to compare the model impacts of Biru-AAttention, LightGBM-GGRU, LightGBM-LSTM, as well as LightGBM-BBiru. The improved accuracy of its predictions makes it a valuable tool for controlling the water quality in intensive aquaculture
