Essays about: "instruction time"

Showing result 1 - 5 of 123 essays containing the words instruction time.

  1. 1. Adoption and use of instructional technology in Nigerian Universities. Exploring Faculty Members’ and Students’ Perspectives

    University essay from Göteborgs universitet/Institutionen för pedagogik och specialpedagogik

    Author : Abisola Aminat Adegunju; [2023-06-19]
    Keywords : instructional technology; faculty members; students; perceptions; instruction delivery;

    Abstract : Aim: This study aims to explore faculty members' and students' perspectives on the adoption and use of instructional technology in Nigerian universities. Considering that, instructional technology can assist educators to deliver engaging, personalized, and interactive learning experiences in higher education. READ MORE

  3. 2. A phenomenological study on Chinese parents's primary choice in Gothenburg, Sweden

    University essay from Göteborgs universitet/Institutionen för pedagogik och specialpedagogik

    Author : Haijiao Chen; [2023-06-19]
    Keywords : school choice; parental reason; cross-culture; rational choice theory; theory of acculturation;

    Abstract : Aim: As big differences exist in the culture and school system in China and Sweden, it is hard for Chinese parents to choose primary schools for their children in Sweden. No research has investigated Chinese parents’ school choice in Sweden. READ MORE

  4. 3. Optimizing the instruction scheduler of high-level synthesis tool

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

    Author : Zihao Xu; [2023]
    Keywords : Instruction scheduling; Scheduling algorithm; CGRA; High-level Sythnesis; SiLago; Algorithm-level Synthesis; Constraint programming; Instruktion schemaläggning; schemaläggning algoritm; CGRA; High-level Sythnesis; SiLago; Algoritm-nivå Synthesis; Constraint programmering;

    Abstract : With the increasing complexity of the chip architecture design for meeting different application requirements, the corresponding instruction scheduler of high-level synthesis tool needs to solve complex scheduling problems. Dynamically Reconfigurable Resource Array (DRRA) is a novel architecture based on Coarse-Grained Reconfigurable Architecture (CGRA) on SiLago platform, the instruction scheduler of Vesyla-II, the dedicated High-Level Synthesis (HLS) tool targets for DRRA needs to schedule the specific instruction sets designed for Distributed Two-level Control System (D2LC). READ MORE

  5. 4. High-Performing Cloud Native SW Using Key-Value Storage or Database for Externalized States

    University essay from Linköpings universitet/Institutionen för datavetenskap

    Author : Ahmed Sikh; Joel Axén; [2023]
    Keywords : cloud-native; externalized states; latency; simulator; Redis; PostgreSQL; moln-nativ; externaliserade tillstånd; latens; simulator; Redis; PostgreSQL;

    Abstract : To meet the demands of 5G and what comes after, telecommunications companies will need to replace their old embedded systems with new technology. One such solution could be to develop cloud-native applications that offer many benefits but are less reliable than embedded systems. READ MORE

  6. 5. Low-power Implementation of Neural Network Extension for RISC-V CPU

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

    Author : Dario Lo Presti Costantino; [2023]
    Keywords : Artificial intelligence; Deep learning; Neural networks; Edge computing; Convolutional neural networks; Low-power electronics; RISC-V; AI accelerators; Parallel processing; Artificiell intelligens; Deep learning; Neurala nätverk; Edge computing; konvolutionella neurala nätverk; Lågeffektelektronik; RISC-V; AI-acceleratorer; Parallell bearbetning;

    Abstract : Deep Learning and Neural Networks have been studied and developed for many years as of today, but there is still a great need of research on this field, because the industry needs are rapidly changing. The new challenge in this field is called edge inference and it is the deployment of Deep Learning on small, simple and cheap devices, such as low-power microcontrollers. READ MORE