This paper gives an experimentally supported review and comparison of several indices based on the conventional K-means inertia criterion for determining number clusters, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> , in datasets, using popular Silhouette width index as a benchmark. Our experiments involve novel version Elbow index, defined values two or three steps apart. We also discuss alternative ways computing summarizing its...

The Santa Barbara post-wildfire debris flows and the Brumadinho tailing-dam failure were two of most catastrophic flood events late 2010s. Both these carried so much solid-phase material, that classic, clear-water, risk approaches cannot replicate them, or forecast other like them. This case study applied new non-Newtonian features in HEC-RAS 6.1 to events, testing widely used model on common mud flow hazards (post-wildfire floods mine tailing dam failures). reproduced inundation boundaries...

DBSCAN is arguably the most popular density-based clustering algorithm, and it capable of recovering non-spherical clusters. One its main weaknesses that treats all features equally. In this paper, we propose a algorithm calculating feature weights representing degree relevance each feature, which takes density structure data into account. First, improve introduce new called DBSCANR. DBSCANR reduces number parameters to one. Then, step introduced process iteratively update based on current...

Nowadays, k-means remains arguably the most popular clustering algorithm [1], [2]. Two of its main properties are simplicity and speed in practice. Here, our claim is that average number iterations takes to converge (τ¯) fact very informative. We find this be particularly interesting because τ¯ always known when applying but has never been, knowledge, used data analysis process. By experimenting with Gaussian clusters, we show related structure a set under study. Data sets containing...

In this paper we introduce the Constrained Minkowski Weighted K-Means. This algorithm calculates cluster specific feature weights that can be interpreted as rescaling factors thanks to use of distance. Here, an small amount labelled data select a exponent and generate clustering constrains based on pair-wise must-link cannot-link rules. We validate our new with total 12 datasets, most which containing features uniformly distributed noise. have run numerous times in each dataset. These...

This work presents a set of experiments conducted to predict the gender Twitter users based on language-independent features extracted from text users' tweets. The were performed version TwiSty dataset including tweets written by six different languages: Portuguese, French, Dutch, English, German, and Italian. Logistic regression (LR), feed-forward neural networks (FFNN) with back-propagation used build models in two settings: Inter-Lingual (IL) Cross-Lingual (CL). In IL setting, training...

The definition of neglected clubfoot (NC) includes a variable range complex deformities the foot that are refractory to conventional treatments or treated inappropriately. Several etiologies may be related this. Ilizarov method has become established as tool for treating these deformities. It minimizes soft-tissue damage through gradual correction deformity, with high success rate in relation achieving plantigrade foot, low incidence recurrence. indications treatment include severe rigid...

Intent classification (IC) and Named Entity Recognition (NER) are arguably the two main components needed to build a Natural Language Understanding (NLU) engine, which is component of conversational agents. The IC NER closely intertwined entities often connected underlying intent. Current research has primarily focused model as separate units, results in error propagation, thus, sub-optimal performance. In this paper, we propose simple yet effective novel framework for NLU where parameters...

Bone defects may be managed with bone transport or acute shortening and lengthening using circular external fixation devices. We performed a multicenter retrospective cohort study to compare the outcomes between Ilizarov frames hexapod for management of defects.Patients treated either were included analysis in two specialist institutions. Primary time consolidation, healing index (BHI), fixator (EFI). Radiographic parameters medial proximal tibial angle, lateral distal posterior anterior...

O pé torto inveterado (PTI) inclui em sua definição uma gama variável de deformidades complexas do refratário a tratamentos convencionais ou tratados forma inadequada. Diversas etiologias podem estar relacionadas. método Ilizarov é consagrado como ferramenta tratamento dessas deformidades, minimiza danos partes moles, através correção gradual da deformidade, com alto índice sucesso relação à obtenção um plantígrado incidência baixa recidiva. As indicações incluem graves e rígidas (Dimeglio...

It is here presented a new method for clustering that uses very limited amount of labeled data, employees two pairwise rules, namely must link and cannot single wise one, cluster. demonstrated the incorporation these rules in intelligent k-means algorithm may increase accuracy results, this proven with experiments where real number clusters data unknown to method.

The k-means clustering algorithm, whilst widely popular, is not without its drawbacks. In this paper, we focus on the sensitivity of to initial set centroids. Since cluster recovery performance can be improved by better initialisation, numerous algorithms have been proposed aiming at producing good However, it still unclear which algorithm should used in any particular scenario. With mind, compare 17 such 6,000 synthetic and 28 real-world data sets. sets were produced under different...