Essays about: "Kostnadsjämförelse"

Showing result 1 - 5 of 14 essays containing the word Kostnadsjämförelse.

1. 1. Cloud Computing Pricing and Deployment Efforts : Navigating Cloud Computing Pricing and Deployment Efforts: Exploring the Public-Private Landscape

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Casper Kristiansson; Fredrik Lundström; [2023]
   Keywords : Cloud computing; Private cloud; Public cloud; Cloud computing services; Cost-effectiveness; Implementation effort; Google GCP; Microsoft Azure; Amazon AWS; Pricing models; Cloud adoption; Cloud cost management; Cloud migration; Instance computing; Serverless computing; Data storage; Molntjänster; Privat moln; Offentligt moln; Kostnadsjämförelse; Kostnadseffektivitet; Google GCP; Microsoft Azure; Amazon AWS; Molninförande; Molnkostnadshantering; Molnmigration; Instance computing; Serverless computing; Dataförvaring;

   Abstract : The expanding adoption of cloud computing services by businesses has transformed IT infrastructure and data management in the computing space. Cloud computing offers advantages such as availability, scalability, and cost-effectiveness, making it a favored choice for businesses of all sizes. READ MORE

3. 2. Comparing the Cost-effectiveness of Image Recognition for Elastic Cloud Computing : A cost comparison between Amazon Web Services EC2 instances

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Christopher Gauffin; Erik Rehn; [2021]
   Keywords : Cloud; On-premise; Infrastructure; Image Recognition; Machine Learning; Deep Learning; Amazon Web Services; EC2; Moln; On-premise; Infrastruktur; Bildigenkänning; Maskinlärning; Djupinlärning; Amazon Web Services; EC2;

   Abstract : With the rise of the usage of AI, the need for computing power has grown exponentially. This has made cloud computing a popular option with its cost- effective and highly scalable capabilities. However, due to its popularity there exists thousands of possible services to choose from, making it hard to find the right tool for the job. READ MORE

4. 3. ManagementPractical Aspects of Aqua Ammonia as Secondary Refrigerant in Ice Rinks

   University essay from KTH/Skolan för industriell teknik och management (ITM)

   Author : Jacqueline Pierri; [2021]
   Keywords : Ice rink; secondary refrigerant; refrigeration; refrigerant management; secondary fluid; natural refrigerant; aqua ammonia;

   Abstract : The transition from fluorinated gases to natural refrigerants could be key to reducing the impacts of climate change. Ice rinks are energy-intensive buildings, with large heating and cooling demands. The pumping power required to move the secondary refrigerant typically accounts for a sizable amount of the energy use of the refrigeration system. READ MORE

5. 4. Cost-efficient method forlifetime extension ofinterconnectedcomputer-based systems

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Wilhelm Holmberg; [2021]
   Keywords : COTS Cost-efficiency Emulator FPGA Lifetime extension Train identification; COTS Emulering FPGA Kostnadseffektivitet Livstidsförlängning Tågidentifiering;

   Abstract : Lifetime and obsolescence of components for computer-based systems poses issues for continued usage and maintenance of the systems. This thesis investigates possible alternatives for lifetime extension of a train identification system used in Stockholm Metro. READ MORE

6. 5. Automatic vs. Manual Data Labeling : A System Dynamics Modeling Approach

   University essay from KTH/Skolan för industriell teknik och management (ITM)

   Author : Clas Blank; [2020]
   Keywords : System Dynamics; Modeling; Data Annotation; Data Labeling; Cost Comparison; Systemdynamik; Modellering; Dataannotation; Kostnadsjämförelse;

   Abstract : Labeled data, which is a collection of data samples that have been tagged with one or more labels, play an important role many software organizations in today's market. It can help in solving automation problems, training and validating machine learning models, or analysing data. READ MORE