Implementation of Weighted Centroid Neural Network for Edge Preserving Image Compression

Image compression is a type of data compression applied to images. The objective of image compression is to reduce the cost for storage or transmission. Image compression is associated with removing redundant information of image data. Image storage is required for several purposes like document, medical images, etc. In this paper, an edge preserving image compression algorithm based on an unsupervised competitive neural network called weighted centroid neural network (WCNN), is implemented and compared to the other algorithms. The WCNN algorithm allots more representative vectors from the edges of the image than the interior of the image thus helping in better edge preservation of the reconstructed image. After experimenting with the cluster count it is evident that with the increase in the number of cluster the quality of the picture is improved, which is the expected behavior as more clusters leads to more representational vectors

Citation sentence reuse behavior of scientists: A case study on massive bibliographic text dataset of computer science

Our current knowledge of scholarly plagiarism is largely based on the similarity between full text research articles. In this paper, we propose an innovative and novel conceptualization of scholarly plagiarism in the form of reuse of explicit citation sentences in scientific research articles. Note that while full-text plagiarism is an indicator of a gross-level behavior, copying of citation sentences is a more nuanced micro-scale phenomenon observed even for well-known researchers. The current work poses several interesting questions and attempts to answer them by empirically investigating a large bibliographic text dataset from computer science containing millions of lines of citation sentences. In particular, we report evidences of massive copying behavior. We also present several striking real examples throughout the paper to showcase widespread adoption of this undesirable practice. In contrast to the popular perception, we find that copying tendency increases as an author matures. The copying behavior is reported to exist in all fields of computer science; however, the theoretical fields indicate more copying than the applied fields