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This paper considers ship route extraction and clustering problem based on Automatic Identification System (AIS) data. For the ships with known Maritime Mobile Service Identify (MMSI), we propose a ship route extraction method by using AIS data. For ship route clustering, hierarchical clustering method is selected. We firstly define a distance between ship routes to measure the dissimilarity of them...
Future of food innovation lies in the art and science of designing an interactive connected intelligent device that can detect how we feel and display the content suitable for individual consumers. We designed a smart dining table and chairs that can detect, sense, and analyze consumer's satisfaction, and interact with consumers. A team of furniture designer, software engineers, mechanical engineer,...
The aim of this paper is to introduce a semantic methodology using ontology in order to improve results of data mining in judicial decisions database. An intelligent and automatic method to search for sentences in lawsuits related to the one in trial is presented. A judicial ontology is built with and without rules from experts. The method can provide judiciary celerity, seeking to solve the yearning...
Block-based programming environments make learning to program easier by allowing learners to focus on concepts rather than syntax. However, these environments offer little support when learners encounter difficulty with programming concepts themselves, especially in the absence of instructors. Textual programming environments increasingly use AI and data mining to provide intelligent, adaptive support...
This paper aims at construction of a system which assumes food textures. The system consists of equipment for obtaining the load and the sound signals while the probe is stabbing the food, and the neural network model infers the degree of the food texture. In the experiment, the validity of our proposed system is discussed.
The article is devoted to the study of the method of self-learning of an artificial intelligence, based on the use of software tools for collecting information from various Internet resources. There is developed a web crawler that analyzes Internet resources for the presence of false articles by data mining methods based on an artificial intelligence and by self-learning through the mechanism of neural...
Prediction markets have substantially grown during the last years. In particular, sports forecasting is an important field of application. In this paper we present a new forecasting system oriented to sports. This proposal is a multi-agent system conformed by several intelligent and independent agents. The agents perform different complementary tasks. This heterogeneous approach provides a powerful...
In many real life situations end results and basic starting data are known. To deduce conclusive evidence or to build holistic picture one needs to find out hidden information and missing text. This research paper delivers a novel algorithm (Probabilistic Intent-Action Ontology and Tone Matching Algorithm) to map multiple events on time line by determining their interdependency to predict the most...
Some specific features of modern Artificial Intelligence (AI) technologies are discussed. Intelligent Data Analysis (IDA), defined as data analysis by means of computer intelligent systems (more formal — reasoning systems), is in focus of our discussion. We compare effectiveness of classical Machine Learning (ML) and IDA in extraction of empirical laws (i.e. stable empirical regularities — dependencies)...
Artificial intelligence is a new subject which has been applied in many fields. In recent years, many countries have been promoting quality education, and promotion of the culture of all the students and the overall quality of research and solve problems of practical ability, and multifaceted Intelligent students also advocated the development of a variety of intelligence, and that the goal of quality...
A stroke occurs when the blood supply to a person's brain is interrupted or reduced. The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of predictive data mining technologies. In this work, we compare different methods with our approach for stroke prediction...
Machine Learning or Artificial Intelligence basically involves tasks of modifying and supervising problems taken as vectors in multi-dimensional space. The Primitive algorithms which are used take Polynomial Time for computing such vector problems which are not fruitful for us, on the other hand, Quantum algorithms have the capability to solve such vector problems in a considerable amount of time...
It is of great significance for the competent authorities to study the method of multi-ship encounter situational awareness and to improve vessel traffic service, finally to reduce the number of accidents. This paper describes the concept of AIS-based multi-ship encounter, proposes the method of AIS data time-slicing and the algorithm of AIS-based multi-ship encounter recognition from the idea of...
The use of the big data analytics (BDA) platform is increasingly becoming prevalent in the data sciences. However, BDA processes consume resources and time excessively. Automating BDA processes is a cognitive approach to the BDA domain, which is most impaired by its heavy consumption of time and resources. However, the BDA workflow is highly dependent on diversified constraints because of the high...
This paper explores the potential of Machine Learning (ML) and Artificial Intelligence (AI) to lever Internet of Things (IoT) and Big Data in the development of personalised services in Smart Cities. We do this by studying the performance of four well-known ML classification algorithms (Bayes Network (BN), Naïve Bayesian (NB), J48, and Nearest Neighbour (NN)) in correlating the effects of weather...
Currently, the methods used to analyse and evaluate the properties of food typically involve human sensory panels. These methods have the advantage of producing realistic, in-vivo results however, due to the subjective nature of sensory evaluation, results obtained from different panel members can be inconsistent. This inherent variability in experimental outcomes can lead to difficulties when interpreting...
Knowledge Discovery in Databases (KDD) is a major innovation in knowledge extraction. This knowledge can be extracted to recognize patterns or behaviors. Board games playing patterns are a concise experiment on testing data mining methods in order to find such patterns and behaviors. In this work a Connect-4 game is simulated with several distinct players with different characteristics. Most of these...
In this paper, an overview on existing data mining techniques for time series modeling and analysis will be provided. Classification of available literature on time series data mining shows that the main research orientations can be divided into three subfields: Dimensionality Reduction (Time Series Representation), Similarity Measures and Data Mining Tasks.
Navigation systems for drivers tend to vocalize what they want, when they want. Drivers who need to clarify instructions are often required to read directions in text form, which is a safety risk during real-time control. Instead, we investigate how a two-way-audio command interface might work. Data is easily extracted from text directions so that questions can be answered without knowledge of the...
The accuracy of conventional DGA interpretation methods can be different when each of these methods are used in different places or different circumstances. Rogers Ratio Method (RRM), IEC Ratio Method (IRM) (Basic Gas Ratios Method), GB/T 7252 (National Standard of the People's Republic of China) are popular conventional methods for interpreting the possible faults indicator of transformer in Indonesia...
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