An Empirical Evaluation of k-Means Coresets

Coresets are among the most popular paradigms for summarizing data. In particular, there exist many high performance coresets for clustering problems such as k-means in both theory and practice. Curiously, there exists no work on comparing the quality of available k-means coresets. In this paper we perform such an evaluation. There currently is no algorithm known to measure the distortion of a candidate coreset. We provide some evidence as to why this might be computationally difficult. To complement this, we propose a benchmark for which we argue that computing coresets is challenging and which also allows us an easy (heuristic) evaluation of coresets. Using this benchmark and real-world data sets, we conduct an exhaustive evaluation of the most commonly used coreset algorithms from theory and practice

Actinobacillosis of the omentum in A Cow

Satu kes actinobacillosis luar biasa menglibatkan omentum lembu dihuraikan. Walaupun pendapatan histologi lesi adalah menyerupai penyakit ini dengan tepat, bakteria penyebabnya Actinobacillus lignieresi tidak diperolehi dalam kajian kultura. Perimustahaknya penyakit ini dalam segi pemeriksaan daging praktik dibincangkan

Producing and Applying Runtime Adjustments to Semantic Textures

Semantic textures are labels associated with objects or regions in a scene, map, or video, and they enable the accurate interpretation of geospatial content. Auto-generated semantic textures frequently include mislabeled regions, e.g., water labeled as ground (and vice-versa). This disclosure describes techniques to enable the touching-up (correcting of semantic labels) of two- or three-dimensional maps, scenes, or videos such that the touch-ups precisely correspond to real-world locations. Touch-up edits can be executed by painting over existing semantic textures using lat-long-centered, touch-up texture tiles as paint brushes within a photo-editing software. The parameters of the touch-up tile, e.g., its resolution, its semantic label (e.g., water, ground, etc.), etc., can be set such that the user has a granular control over the refinement of semantic textures. The mislabeling of ground as water (and vice-versa), an error often found in auto-generated semantic textures, can be corrected or eliminated

Construction and Interpretation Of Corpus-Based English Poetry Vocabulary Profile

Vocabulary Profilers (VPrs) are deeply rooted in pedagogical purposes. The current investigation, however, uses the Classic and Compleat VPrs to: 1) determine the distribution and content of vocabulary in an English poetry corpus 2) explain differences in the constituents of the vocabulary profile (VP), 3) explore the role of language users in constructing the VP. The corpus includes Extended Corpus (EC: 1.363.225 words), Micro Corpus (MC: 43.200 words) from thirty-six poets, and two poems translated into Arabic. The main results show that Types, Offlist words, Academic and Anglo-Saxon words outline the VP, and that the number of Types and the size of the Individual Mental Lexicon constitute the main features of the translator’s VP. The paper concludes that the poet’s construction of the poetry VP undergoes multilayer interpretation by the reader/analyst and the translator, who utilize their socio-environmental context to pin down the semantic potential of the VP anew