Essays about: "Data integration"

Showing result 1 - 5 of 1720 essays containing the words Data integration.

  1. 1. Does industry survey data improve GDP forecasting?

    University essay from Göteborgs universitet/Företagsekonomiska institutionen

    Author : Oscar Andersson; Ludvig Fornstedt; [2024-03-06]
    Keywords : Bayesian; BVAR; Forecasting; GDP; survey data;

    Abstract : This study assesses the integration of industry survey data into Bayesian Vector Auto Regressive (BVAR) models for GDP forecasting in Sweden. Analyzing a combination of macro economic indicators, CPI and unemployment rates, with survey data from NIER, it explores the effects of different variable combinations on the forecasting ability of different models. READ MORE

  2. 2. Exploring the Integration of Artificial Intelligence Tools in English as a Foreign Language (EFL) Pedagogy. A Literature Review

    University essay from Göteborgs universitet / Lärarutbildningsnämnden

    Author : Rasmus Andersson; Axel Ringhagen; Albin Tapper; [2024-01-18]
    Keywords : Teachers; implementing AI; EFL classroom;

    Abstract : The introduction of artificial intelligence (AI) tools in schools has sparked a polarised debate about its negative impact on critical thinking, plagiarism, and problem-solving skills. Future educators will be affected by the tools, prompting this thesis to explore their potential benefits and challenges through a literature review. READ MORE

  3. 3. OPTIMIZATION OF CLONE SELECTION PLATFORM FOR PRODUCTION OF RECOMBINANT PROTEINS

    University essay from Uppsala universitet/Institutionen för medicinsk biokemi och mikrobiologi

    Author : Basel Yousef; [2024]
    Keywords : ;

    Abstract : Background  Biologics are type of proteins that can be produced by expression in a foreign host for medical healthcare applications in humans. Monoclonal antibodies (mAbs) are type of biologics that are designed to specifically bind to one target, with a purpose to inhibit a certain molecule that could be associated with a disease process. READ MORE

  4. 4. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Nikolaos Staikos; [2024]
    Keywords : Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

    Abstract : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. READ MORE

  5. 5. Data analysis for predictive maintenance and potential challenges associated with the technology integration of steel industry machines.

    University essay from Högskolan i Gävle/Elektronik

    Author : Pradip Nath; [2024]
    Keywords : Data Science; Data processing; Industrial Manufacturing; System Identification; Predictive maintenance; Conditional monitoring; Statistical Analysis; Signal processing; Hydraulic System; IoT; Sustainable Maintenance; Data vetenskap; Databehandling; Industriell tillverkning; System identifiering; Prediktivt underhåll; Tillståndsövervakning; Statistisk analys; Signal behandling;

    Abstract : The recharge is the focus of data analysis of the different situations with the integration of the system and development of the two-stage 2/2 proportional cartridge valve for the steel industry machine. Using the statistical analysis technique to visualize the valve signal data behavior identify the accuracy of the machine data and apply the statistical feature extracting model using classification and clustering algorithms of real-time data analysis for the manufacturing. READ MORE