Feature extraction and ML techniques for static gesture recognition

The main objective of this study is to explore the utility of a neural network-based approach in hand gesture recognition. The proposed system presents two recognition algorithms to recognize a set of six specific static hand gestures, namely open, close, cut, paste, maximize, and minimize. The hand gesture image is passed through three stages: preprocessing, feature extraction, and classification. In the first method, the hand contour is used as a feature that treats scaling and translation of problems (in some cases). However, the complex moment algorithm is used to describe the hand gesture and to treat the rotation problem in addition to scaling and translation. The back-propagation learning algorithm is employed in the multilayer neural network classifier. The second method proposed in this article achieves better recognition rate than the first method.     

The design of multiple feedback topology Chebyshev low-pass active filter with average differential evolution algorithm

Neural Computing and Applications - This study presents the design of a tenth-order multiple feedback Chebyshev low-pass filter (MF-C-LPF). Component selection and gain calculation of filters are...     

The performance of multiwavelets based OFDM system under different channel conditions

In wireless communication reception, the reliability of orthogonal frequency division multiplexing (OFDM) is limited because of the time-varying nature of the channel. This causes inter-carrier interference (ICI) and increases inaccuracies in channel tracking. This can effectively be avoided at the cost of power loss and bandwidth expansion by inserting a cyclic prefix guard interval before each block of parallel data symbols. However, this guard interval decreases the spectral efficiency of the OFDM system as the corresponding amount. Recently, it was found that based on Haar-orthonormal wavelets, discrete wavelet-based OFDM (DWT-OFDM) is capable of reducing the inter symbol interference (ISI) and ICI, which are caused by the loss in orthogonality between the carriers. DWT-OFDM can also support much higher spectrum efficiency than discrete Fourier-based OFDM (DFT-OFDM). In this paper the DFT-OFDM is replaced by Multiwavelets OFDM (DMWT-OFDM) in order to further reduce the level of interference and increase spectral efficiency. It is found that proposed Multiwavelet design achieves much lower bit error rates, increases signal to noise power ratio (SNR), and can be used as an alternative to the conventional OFDM. The proposed OFDM system was modeled tested, and its performance was found under different channel conditions.     

Voiced/non-voiced speech classification using adaptive thresholding with bivariate EMD

This paper introduces a robust voiced/non-voiced (VnV) speech classification method using bivariate empirical mode decomposition (bEMD). Fractional Gaussian noise (fGn) is employed as the reference signal to derive a data adaptive threshold for VnV discrimination. The analyzing speech signal and fGn are combined to generate a complex signal which is decomposed into a finite number of complex-valued intrinsic mode functions (IMFs) by using bEMD. The real and imaginary parts of the IMFs represent the IMFs of observed speech and fGn, respectively. The log-energies of both types of IMFs are calculated. There exist similarities between the IMF log-energy representation of fGn and unvoiced speech signals. Hence, the upper confidence limit from IMF log-energies of fGn is used as data adaptive threshold for VnV classification. If the subband log-energy of speech segment exceeds the threshold, the segment is classified as voiced and unvoiced otherwise. The experimental results show that the proposed algorithm performs better than the recently reported methods without requiring any training data for a wide range of SNRs.     

Intelligently tuned wavelet parameters for GPS/INS error estimation

This paper presents a new algorithm for de-noising global positioning system (GPS) and inertial navigation system (INS) data and estimates the INS error using wavelet multi-resolution analysis algorithm (WMRA)-based genetic algorithm (GA) with a well-designed structure appropriate for practical and real time implementations because of its very short training time and elevated accuracy. Different techniques have been implemented to de-noise and estimate the INS and GPS errors. Wavelet de-noising is one of th...     

A New Mobile Robot Toolbox for Matlab

In this study, a wheeled mobile robot navigation toolbox for Matlab is presented. The toolbox includes algorithms for 3D map design, static and dynamic path planning, point stabilization, localization, gap detection and collision avoidance. One can use the toolbox as a test platform for developing custom mobile robot navigation algorithms. The toolbox allows users to insert/remove obstacles to/from the robot’s workspace, upload/save a customized map and configure simulation parameters such as robot size, virtual sensor position, Kalman filter parameters for localization, speed controller and collision avoidance settings. It is possible to simulate data from a virtual laser imaging detection and ranging (LIDAR) sensor providing a map of the mobile robot’s immediate surroundings. Differential drive forward kinematic equations and extended Kalman filter (EKF) based localization scheme is used to determine where the robot will be located at each simulation step. The LIDAR data and the navigation process are visualized on the developed virtual reality interface. During the navigation of the robot, gap detection, dynamic path planning, collision avoidance and point stabilization procedures are implemented. Simulation results prove the efficacy of the algorithms implemented in the toolbox.     

An improvement of quantitative strategic planning matrix using multiple criteria decision making and fuzzy numbers

The Quantitative Strategic Planning Matrix (QSPM) is a useful tool to prioritize strategies at any level including corporate, business and functional. The ratings and attractive scores used in QSPM, however, require judgmental decisions and should be based on expert's opinion to ensure the applicability of chosen strategies. Application of a fuzzy multi-criteria decision making method is proposed in this paper with the goal of improving the output of conventional QSPM by allowing the experts to employ linguistic terms (qualitative data) in their judgments. Namely, a multi-criteria decision making index via the technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is adapted to the fuzzy QSPM in finding the sum total attractive scores of strategies. As a case study, the proposed method has been applied for strategy prioritization in a Tile Company. The results have been verified with expert knowledge and showed an improvement compared to the non-fuzzy QSPM.     

Evaluation of an adaptive and intelligent educational hypermedia for enhanced individual learning of mathematics: A qualitative study

The purpose of this study is to design a personalized adaptive and intelligent web based tutoring system based on learning style and expert system named UZWEBMAT and to evaluate its effects on 10th grade students’ learning of the unit of probability. In the study, initially, learning objects were prepared in three different ways in relation to three sub-learning areas of Visual–Auditory–Kinesthetic (VAK) learning style for each subject of the probability unit. These were appropriate for secondary school mathematics curricula. Then, they were transferred into the digital environment. Each student’s dominant learning style determines the content to which s/he will be directed since s/he is directed to the content that is appropriate for his/her learning style. The course to be followed by the students within UZWEBMAT and their browsing around the pages are decided by expert system integrated into the system. This expert system sets the situations in which s/he will get solution supports and the course s/he will follow in accordance with the performance of the student. Hereby, each student may follow a different course, and the solution supports s/he will get may also differ highlighting the individual learning. The sample of the study consists of 81 10th grade students and 3 mathematics teachers from two high schools in Trabzon, Turkey. Qualitative data were obtained both from the teachers and students participating in the study in order to answer the research questions about the implementation and evaluation of UZWEBMAT for mathematics teaching in a high school classroom. Obtained data were analyzed using qualitative data analysis methods. According to the results of the present study, positive opinions of students and teachers such as taking into account the individual learning differences and deriving mathematical relations and formulas through exploration became prominent. In addition, there were also other positive opinions of students and teachers such as providing permanent learning and introducing learning responsibility to the students. In this sense, it was concluded that UZWEBMAT is a beneficial instrument for both students and teachers.     

Structure and reversibility of 2D hexagonal cellular automata

Cellular automata are used to model dynamical phenomena by focusing on their local behavior which depends on the neighboring cells in order to express their global behavior. The geometrical structure of the models suggests the algebraic structure of cellular automata. After modeling the dynamical phenomena, it is sometimes an important problem to be able to move backwards in order to understand it better. This is only possible if cellular automata is reversible. In this paper, 2D finite cellular automata defined by local rules based on hexagonal cell structure are studied. Rule matrix of the hexagonal finite cellular automaton is obtained. The rank of rule matrices representing the 2D hexagonal finite cellular automata via an algorithm is computed. It is a well known fact that determining the reversibility of a 2D cellular automata is a very difficult problem in general. Here, the reversibility problem of this family of 2D hexagonal cellular automata is also resolved completely.