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In this paper, we discuss a novel approach to incrementally construct a rule ensemble. The approach constructs an ensemble from a dynamically generated set of rule classifiers. Each classifier in this set is trained by using a different class ordering. We investigate criteria including accuracy, ensemble size, and the role of starting point in the search. Fusion is done by averaging. Using 22 data...
Online reviews are becoming one of the vital components of e-commerce in recent years as so many people consider having different opinions prior to buying online products or apprehending any online service. Nowadays, in the era of web 2.0, it is completely understandable that people rely on online reviews more than ever while taking a decision. However, guaranteeing the authenticity of these sensitive...
This paper presents a user authentication system based on mouse movement data. An available logging tool named Recording User Input (RUI) is used to collect three types of mouse actions — Mouse Move, Point-and-Click on Left or Right mouse button and Drag-and-Drop. Collected data are divided into N-number of blocks consisting of specific number of actions. From each block seventy four features are...
In this paper we study the problem of content-based image retrieval. In this problem, the most popular performance measure is the top precision measure, and the most important component of a retrieval system is the similarity function used to compare a query image against a database image. However, up to now, there is no existing similarity learning method proposed to optimize the top precision measure...
Dimensionality reduction methods have been shown to be effective for handwritten Chinese character recognition. In this paper, we propose discriminative projection based on locality-sensitive sparse representation (DPLSR) for in-air handwritten Chinese character recognition. DPLSR based on the locality-sensitive sparse representation based classifier (LSRC), which can provide closed-form solutions...
Teachers' role in 21st century is undergoing a transition from the orthodox ‘chalk and talk’ method to a student-centered, activity-based approach that maximizes students' active-learning opportunities and engages them to solve various problems. Teachers play an important role in today's technology-rich classrooms that significantly affect students' learning. For this reason it is time for the students,...
Microblog, especially Twitter, have become an integral part of our daily life, where millions of users sharing their thoughts daily because of its short length characteristics and simple manner of expression. Monitoring and analyzing sentiments from such massive Twitter posts provide enormous opportunities for companies and other organizations to estimate the user acceptance of their products and...
Recent work has shown that computational substrates made from carbon nanotube/polymer mixtures can form trainable Reservoir Computers. This new reservoir computing platform uses computer based evolutionary algorithms to optimise a set of electrical control signals to induce reservoir properties within the substrate. In the training process, evolution decides the value of analogue control signals (voltages)...
Described herein is a general-purpose software engineering architecture for autonomous, computer controlled opponent implementation in modern maneuver warfare simulation and training. The implementation has been developed, refined, and tested in the user crucible for several years. The approach represents a hybrid application of various well-known AI techniques, including domain modeling, agent modeling,...
Light detection and ranging (LIDAR) is a technology of remote imaging technologies. Currently, it is the most important technology for accruing elevation points with a high density in the form of digital elevation model (DEM) construction. However, the high-density data leads to time and memory consumption problems during data processing. In this paper, we depend on radial basis function (RBF) with...
The aim of this study is to establish the effect of task-oriented video gaming on using a myoelectric prosthesis in a basic activity of daily life (ADL). Forty-one able-bodied right-handed participants were randomly assigned to one of four groups. In three of these groups the participants trained to control a video game using the myosignals of the flexors and extensors of the wrist: in the Adaptive...
In this paper a method to develop artificial intuition is suggested. In an attempt to emulate the trial and error, searching is combined with a random choice. It is used in initial steps of the search, which provides reaching the goal in fewer steps, when compared to the case without the random choice. An example game is derived to illustrate the proposed searching technique.
The Gomoku board game is a longstanding challenge for artificial intelligence research. With the development of deep learning, move prediction can help to promote the intelligence of board game agents as proven in AlphaGo. Following this idea, we train deep convolutional neural networks by supervised learning to predict the moves made by expert Gomoku players from RenjuNet dataset. We put forward...
The concept of embedded systems is considered. The advantages of developed embedded systems compared to general purpose are emphasized. The possible ways to develop microcontroller-based embedded systems design tools are analyzed. The features provided by MCU manufacturers are touched upon. The authors investigate the case of development of equipment for education, research and design of embedded...
We have investigated the effect of normalizing Japanese orthographical variants into a uniform orthography on statistical machine translation (SMT) between Japanese and English. In Japanese, 10% of words have reportedly more than one orthographical variants, which is a promising fact for improving translation quality when we normalize these orthographical variants. However, the results show that SMT...
Chinese text categorization, which is a key technology of massive Chinese text data processing, has been applied to information retrieval, document management, text filtering, etc. However, the categorization accuracy has been the major difficulties faced by the application upgrade. To improve the performance of the Chinese text categorization, feature selection, as an important and indispensable...
Deep Neural Networks have become a state of the art approach in perception processing like speech recognition, image processing and natural language processing. Many state of the art benchmarks for these algorithms are using deep learning techniques. The deep neural networks in today's applications need to process very large amount of data. Different approaches have been proposed to solve scaling...
For pathology routine examination microscopic biopsy slides are considered as a most viable choice to analyze and identity ovarian reproductive tissues. Experts require substantial amount of time to process the biopsy slides under the microscope. Electronic modalities are not suitable to analyze smaller tissues especially ovarian reproductive tissues. To reduce the time and effort it would be a better...
Intrusion Detection System (IDS) is an essential method to protect network security from incoming on-line threats. Machine learning enable automates the classification of network patterns. This paper review the learning and detection methods in IDS, discuss the problems with existing intrusion detection systems and review data reduction techniques used in IDS in order to deal with huge volumes of...
It would be difficult and stressful for a single operator to operate an underwater manipulator using his/her both hands in deep sea environments while the operator has to monitor or manipulate additional equipment. In order to reduce the operating pressure and make full use of the operator potentials, in this paper we propose a control strategy for operating the underwater manipulator via P300 brainwaves,...
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