Sökning: "processing techniques"

Visar resultat 21 - 25 av 781 uppsatser innehållade orden processing techniques.

  1. 21. Life cycle assessment of metal laser powder bed fusion : A deep dive into the significance of system boundary expansion and improvement potential

    Master-uppsats, Linköpings universitet/Industriell miljöteknik

    Författare :Christian Rotter; Erik Fagerberg; [2023]
    Nyckelord :additive manufacturing; life cycle assessment; powder bed fusion; system boundaries; metal laser powder bed fusion; environmental impact; global warming potential;

    Sammanfattning : Metal additive manufacturing (MAM) is a manufacturing technology experiencing a rapid expansion rate. Metal laser powder bed fusion (ML-PBF) is among the most popular techniques in this field. The environmental implications of it are often discussed in literature and compared to conventional manufacturing. LÄS MER

  3. 22. Digital Front End Algorithms for Sub-Band Full Duplex

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Midhat Rizvi; Khaled Al-Khateeb; [2023]
    Nyckelord :Adjacent Channel Leakage Ratio; Bit Error Rate; Clipping and Filtering; Crest Factor Reduction; Digital front end; Digital Pre-Distortion Error Vector Magnitude; Frequency Division Duplex; Power Amplifier; Peak to Average Power Ratio; Peak Cancellation Crest Factor Reduction; Sub Band Full Duplex; Self-Interference Cancellation; Signal-to-Interference Noise Ratio; Signal-to-Noise Ratio; Turbo Clipping; Time Division Duplex; Technology and Engineering;

    Sammanfattning : Sub-band full duplex is a new communication scheme technology, where a single frequency band is partitioned into sub-bands for downlink (DL) and up-link(UL) transmissions, and both can take place simultaneously. The idea behind the sub-band full duplex development is to improve the throughput, and coverage and reduce the latency of the UL communication by allowing the UL reception during the DL transmission. LÄS MER

  4. 23. Bullying Detection through Graph Machine Learning : Applying Neo4j’s Unsupervised Graph Learning Techniques to the Friends Dataset

    Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Författare :Olof Enström; Christoffer Eid; [2023]
    Nyckelord :Bullying; Graph Machine Learning; Community Detection; Neo4j; Data Preprocessing; Similarity Algorithms; Friends; Neo4j; Unsupervised Learning; Anti-bullying;

    Sammanfattning : In recent years, the pervasive issue of bullying, particularly in academic institutions, has witnessed a surge in attention. This report centers around the utilization of the Friends Dataset and Graph Machine Learning to detect possible instances of bullying in an educational setting. LÄS MER

  5. 24. Improved U-Net architecture for Crack Detection in Sand Moulds

    Kandidat-uppsats, Högskolan i Gävle/Datavetenskap

    Författare :Husain Ahmed; Hozan Bajo; [2023]
    Nyckelord :U-Net Architecture; Semantic Segmentation; Convolutional Neural Networks; Crack Detection;

    Sammanfattning : The detection of cracks in sand moulds has long been a challenge for both safety and maintenance purposes. Traditional image processing techniques have been employed to identify and quantify these defects but have often proven to be inefficient, labour-intensive, and time-consuming. LÄS MER

  7. 25. Understanding Sales Performance Using Natural Language Processing - An experimental study evaluating rule-based algorithms in a B2B setting

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Angelica Smedberg; [2023]
    Nyckelord :NLP; Sentiment Analysis; Ruled-based algorithms; TextBlob; VADER; Naïve Bayes; Machine Learning;

    Sammanfattning : Natural Language Processing (NLP) is a branch in data science that marries artificial intelligence with linguistics. Essentially, it tries to program computers to understand human language, both spoken and written. Over the past decade, researchers have applied novel algorithms to gain a better understanding of human sentiment. LÄS MER