Tactile information is important for gripping, stable grasp, and in-hand manipulation, yet the complexity of tactile data prevents widespread use of such sensors. We make use of an unsupervised learning algorithm that transforms the complex tactile data into a compact, latent representation without the need to record ground truth reference data. These compact representations can either be used ...

Many factors affect the success of Machine Learning (ML) on a given task. The representation and quality of the instance data is first and foremost. If there is much irrelevant and redundant information present or noisy and unreliable data, then knowledge discovery during the training phase is more difficult. It is well known that data preparation and filtering steps take considerable amount of...

This study is emphasized on different types of normalization. Each of which was tested against the ID3 methodology using the HSV data set. Number of leaf nodes, accuracy and tree growing time are three factors that were taken into account. Comparisons between different learning methods were accomplished as they were applied to each normalization method. A new matrix was designed to check for th...

Contraction Hierarchies is a successful speedup-technique to Dijkstra’s seminal shortest path algorithm that has a convenient trade-off between preprocessing and query times. We investigate a shared-memory parallel implementation that uses O(n + m) space for storing the graph and O(1) space for each core during preprocessing. The presented data structures and algorithms consequently exploits ca...

Long-time-series climate prediction is of great significance for mitigating disasters; promoting ecological civilization; identifying change patterns and preventing floods, drought typhoons. However, the general public often struggles with complexity extensive temporal range meteorological data when attempting to accurately forecast extremes. Sequence disorder, weak robustness, low characterist...

expert systems can help to build banks customers' credit scoring models. here, selection of key features of the credit scoring is important. also, it is possible to express the features values as fuzzy. the problem is how to improve features selection by genetic algorithm, in way that these features can be employed as input in fuzzy expert system. this paper presents a hybrid credit scorin...