Abstract This paper describes a new approach to knowledge creation that is instrumental for the emerging paradigm of data-intensive science. The proposed enables acquisition insights from data by exploiting existing relationships between diverse types datasets acquired through various modalities. value consistently improves when it can be linked other because linking multiple allows creating no...

Data-driven conceptual design methods and tools aim to inspire human ideation for new concepts by providing external inspirational stimuli. In prior studies, the stimuli have been limited in terms of coverage, granularity, retrieval guidance. Here, we present a knowledge-based expert system that provides across semantic, document field levels simultaneously from all fields engineering technolog...

Vehicle trajectory prediction tasks have been commonly tackled from two distinct perspectives: either with knowledge-driven methods or more recently data-driven ones. On the one hand, we can explicitly implement domain-knowledge physical priors such as anticipating that vehicles will follow middle of roads. While this perspective leads to feasible outputs, it has limited performance due difficu...

Some people claim “knowledge leads to power”. Even if that claim is true companies only win when knowledge is shared among employees and other stakeholders. Today sharing knowledge when making decisions is more important than most people recognize. One way to share knowledge is to build computerized systems that can store and retrieve knowledge codified as probabilities, rules and relationships...

In this paper, we present a data-driven method for crowd simulation with holonification model. With this extra module, the accuracy of simulation will increase and it generates more realistic behaviors of agents. First, we show how to use the concept of holon in crowd simulation and how effective it is. For this reason, we use simple rules for holonification. Using real-world data, we model the...

in spite of the highly beneficial applications of corpus linguistics in language pedagogy, it has not found its way into mainstream efl. the major reasons seem to be the teachers’ lack of training and the unavailability of resources, especially computers in language classes. phrasal verbs have been shown to be a problematic area of learning english as a foreign language due to their semantic op...

This paper introduces an adaptive neuro-fuzzy inference system (ANFIS) for financial trading, which learns to predict price movements from training data consisting of intraday tick data sampled at high frequency. The empirical data used in our investigation are five-minute mid-price time series from FX markets. The ANFIS optimisation involves back-testing as well as varying the number of epochs...

Introduction 1 Randomness manifests itself in many aspects of real-world problems, such as initial/boundary conditions, model parameters, measurements, to name a few. 2 Its effect may span many scales and grow with time through nonlinear interactions, which results in dramatic difference compared with that of the deterministic model. 3 A typical scenario occurring frequently in practice is that...