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Hausa sign language (HSL) is the main communication medium among deaf-mute Hausas in northern Nigeria. HSL is so unique that a deaf-mute individual from other part of the country can rarely understand it. HSL includes static and dynamic hand gesture recognitions. In this paper we present an intelligent recognition of static, manual and nonmanual HSL using an enhanced Fourier descriptor. A Red Green...
Lithium-ion batteries are currently the most widely used form of energy storage in electric vehicles. They have a high vitality thickness with a potential for higher limits, they don't need prolonged priming when they're new. However, they're subject to aging rapidly even when they aren't being used. Being able to predict the life expectancy of these batteries can prove to be beneficial in order to...
The use of dual arm robots for human like operations such as the peg-in-hole tasks can be facilitated by learning contact states during manipulation. In this paper, we propose a control scheme that includes the learning of contact states during operations. The approach includes the use of a Motoman SDA-20 dual-arm robot equipped with two three-fingered gripper and a force/torque sensing capability...
A new large signal model construction technique is proposed in this paper. High order current- and charge-sources are used to describe the dispersive behavior of FETs, which are assembled from small signal measurement data. Instead of storing the model data into look-up tables, empirical functions and artificial neural network (ANN) are adopted to implement the model into simulators, which can reduce...
Demand peaks in electrical power system cause serious challenges for energy providers as these events are typically difficult to foresee and require the grid to support extraordinary consumption levels. Accurate peak forecasting enables utility providers to plan the resources and also to take control actions to balance electricity supply and demand. However, this is difficult in practice as it requires...
This paper summarizes the AAIA'17 Data Mining Challenge: Helping AI to Play Hearthstone which was held between March 23, and May 15, 2017 at the Knowledge Pit platform. We briefly describe the scope and background of this competition in the context of a more general project related to the development of an AI engine for video games, called Grail. We also discuss the outcomes of this challenge and...
This paper presents a deep analysis of literature on the problems of optimization of parameters and structure of the neural networks and the basic disadvantages that are present in the observed algorithms and methods. As a result, there is suggested a new algorithm for neural network structure optimization, which is free of the major shortcomings of other algorithms. The paper describes a detailed...
This project explored fundamental methods to find the factors that can be used in classifying and detecting the type of wood. Whereas, the literatures have been reviewed to determine the algorithms developed. Some experiments have been conducted to analyze the model and system. The experiments are based on artificial neural network (ANN) algorithm that used back propagation and conjugate gradient...
Roller element bearing fault diagnosis is crucial in industry to maintain that the machine is in good condition so that there is no delay of work due to machine breakdown. This paper discusses the use of Extreme Learning Machine (ELM) algorithm to classify bearing faults. The performance of ELM is compared with Back Propagation (BP) algorithm. It was found that the results show that the ELM has smaller...
In the previous study, we have investigated that the Extended Kalman Filter (EKF) has the excellennt performance and very fast learning as the training of Feedforward Neural Network (FNN). In the expansion of Kalman filter algorithm for nonlinear estimation, the Unscented Kalman Filter (UKF) was proposed. Enlightened the UKF is superior to EKF, in this study, we investigate the UKF algorithm as the...
To successfully move a robot into the building, the elevator button and elevator floor number detection and recognition can play an important role. It can help a robot move in the building, just as it also can help a visually impaired person who wants to move another floor in the building. Due to vision-based approach, the difference in lighting condition and the complex background are the main obstacles...
In a computer vision system, handwritten digits recognition is a complex task that is central to a variety of emerging applications. It has been widely used by machine learning and computer vision researchers for implementing practical applications like computerized bank check numbers reading. In this study, we implemented a multi-layer fully connected neural network with one hidden layer for handwritten...
Many areas include public transportation, hospitals and shopping mall use the computer technologies for security reasons. The need for integrating the technology with human needs is increased dramatically. Car license plate recognition is one of those technologies that help people to secure themselves from different attacks either attacks that affect their lives or their properties. There is an increasing...
A self-sensing method for switched reluctance motors (SRM) for low speed and stand-still is introduced in this paper. The approach utilizes current slopes excited by voltage pulses that are injected into idle phases. To obtain an undisturbed signal for rotor position estimation, a simple integration of the bit-stream output of the delta-sigma modulators in the current measurement path is applied....
We present detection of various fdters using neural networks usable for our Long wave infrared (LWIR) hyperspectral detection system (HDES). Some reduction techniques are shown, for our aim of the small neural network with small computing requirements. In addition, the filter measurement is usable for calibration and verification of the HDES properties.
Effective generation of hash function is very important for an achievement of a security of today networks. A cryptographic hash function is a transformation that takes an input and returns a fixed-size value, which is called the hash value. A recurrent neural network, as a possible approach, could be used for the hash function generation. The performance of the recurrent neural network (RNN) was...
The False Data Injection (FDI) attack on Load Frequency Control (LFC) caused by the adversary can destabilize the power system. This could cause potential economic and life damages. Therefore, the real-time detection of FDI attacks is necessary and essential to compensate negative effects of such attacks. This paper presents a neural network-based detection (NND) approach to estimate and detect the...
This paper presents a controller tuning method for nonlinear systems by using the so-called virtual reference feedback tuning method and nonlinear compensation based on multilayer neural networks. To demonstrate the effectiveness of the presented method, simulation is carried out for systems with nonlinearities such as hysteresis, cubic functions, and dead zones. Moreover, architectures and computational...
The paper is devoted to consider problems of project management in conditions of internal and external uncertainty in project state assessment. It is shown, that uncertainty of project state assessments influences negatively on the project and on the organized system, in which projects realize. The mechanisms of formalized project state assessment with means of artificial neural networks are proposed...
As it is well-known, orange peel is used for making jam and oil. For this purpose, orange samples with high peel thickness are best. In order to predict peel thickness in orange fruit, we present a system based in image features, comprising: area, eccentricity, perimeter, length/area, blue value, green value, red value, wide, contrast, texture, wide/area, wide/length, roughness, and length. A novel...
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