Titlebook: Information and Communication Technology for Development for Africa; First International Fisseha Mekuria,Ethiopia Enideg Nigussie,Tesfa Te

poliosis

A Finite-State Morphological Analyzer for Wolayttae Helsinki Finite-State Transducer toolkit (HFST). Developing a full-fledged morphological analysis tool for an under-resourced language like Wolaytta is an important step towards developing further NLP (Natural Language Processing) applications. Morphological analyzers for highly inflectional langu

Compass

Malaria Detection and Classification Using Machine Learning Algorithmsis of Malaria needs careful examination to distinguish infected and healthy .ed .lood .ells (RBCs). However, it is time consuming, needs experience, and may face inaccurate lab results due to human errors. As a result, doctors and specialists are likely to provide improper prescriptions. With the cu

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Survey on Indoor Positioning Techniques and Systemsy of outdoor positioning has become excellent due to the development of GPS. However lots of mass market applications require very excellent positioning capabilities in almost every environments. As a result, indoor positioning has attracted the researchers attention and has been a focus of research

parsimony

Comparative Study of the Performances of Peak-to-Average Power Ratio (PAPR) Reduction Techniques forR reduction capability and computational complexity for equal number of candidate OFDM symbols. Using MATLAB simulation, it is shown that SLM outperforms PTS in PAPR reduction capability. For small values of the number of subblock partitions, the overall computational complexity of PTS is less than

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A Distributed Multi-hop Clustering Algorithm for Infrastructure-Less Vehicular Ad-Hoc Networkshicles and infrastructure. Clustering is proposed as a promising technique to efficiently manage and deal with highly dynamic and dense features of vehicular topology. However, clustering generates a high number of control messages to manage and maintain the clustering structure. In this paper, we p

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Classification of Mammograms Using Convolutional Neural Network Based Feature Extractionbreast cancer detection and classification might possibly enhance the survival rate of the patients through starting early treatment. In this paper, the convolutional Neural Networks (CNN) based feature extraction method is proposed. The features dimensionality was reduced using Principal Component

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