Volume 14, Issue 1

In this work, a new flux controlled memristor circuit is presented. It provides a tool to emulate the pinched hysteresis loop.When driven the memristor by a bipolar periodic signal, the memristor exhibits a “pinched hysteresis loop” in the voltage-current plane and starting from some critical frequency, the hysteresis lobe area decreases monotonically as the excitation frequency increases, the pinched hysteresis loop shrinks to a single-valued function when the frequency tends to infinity. The design model numerically simulated and the physical implementation is achieved by using a field programmable analog array (FPAA). The circuit can be modeled and implemented with a changeable nonlinear function blocks and fixed main system blocks. The simplicity of the specific design method makes this proposed model be a very engaging option for the design of the memristor.

A new algorithm for multi-object recognition and localization is introduced in this paper. This algorithm deals with objects which have different reflectivity factors and distinguish color with respect to the other objects. Two beacons scan multi-color objects using long distance IR sensors to estimate their absolute locations. These two beacon nodes are placed at two corners of the environment. The recognition of these objects is estimated by matching the locations of each object with respect to the two beacons. A look-up table contains the distances information about different color objects is used to convert the reading of the long distance IR sensor from voltage to distance units. The locations of invisible objects are computed by using absolute locations of invisible objects method. The performance of introduced algorithm is tested with several experimental scenarios that implemented on color objects.

Gait as a biometric can be used to identify subjects at a distance and thus it receives great attention from the research community for security and surveillance applications. One of the challenges that affects gait recognition performance is view variation. Much work has been done to tackle this challenge. However, the majority of the work assumes that gait silhouettes are captured by affine cameras where only the height of silhouettes changes and the difference in viewing angle of silhouettes in one gait cycle is relatively small. In this paper, we analyze the variation in gait recognition performance when using silhouettes from projective cameras and from affine cameras with different distance from the center of a walking path. This is done by using 3D models of walking people in the gallery set and 2D gait silhouettes from independent (single) cameras in the probe set. Different factors that affect matching 3D human models with 2D gait silhouettes from single cameras for view-independent gait recognition are analyzed. In all experiments, we use 258 multi-view sequences belong to 46 subjects from Multi-View Soton gait dataset. We evaluate the matching performance for 12 different views using Gait Energy Image (GEI) as gait features. Then, we analyze the effect of using different camera configurations for 3D model reconstruction, the GEI from cameras with different settings, the upper and lower body parts for recognition and different GEI resolutions. The results illustrate that low recognition performance is achieved when using gait silhouettes from affine cameras while lower recognition performance is obtained when using gait silhouettes from projective cameras.

In the current scenario, power factor has become an important concern in all industries. Poor power factor gives rise to many problems which result in financial loss of industries and also for the commercial users. The main concern of this work is to improve the usage of real power with respect to reactive power hence improving the power factor. Here we have used the technique of relay switching method with a capacitor so that any drop in power factor can be sensed by the controller and switch the capacitor as required. This will not only help to improve power factor but also demand of electricity supply on utility side will be reduced. The Significance of this work is to build an APFC (Automatic Power Factor Correction) Unit. The APFC appliance calculates the reactive power (KVAR) expended by a system’s load and compensates the lagging PF (power factor) utilizing capacitances from capacitor banks.

The evolution of wireless communication technology increases human machine interaction capabilities especially in controlling robotic systems. This paper introduces an effective wireless system in controlling the directions of a wheeled robot based on online hand gestures. The hand gesture images are captured and processed to be recognized and classified using neural network (NN). The NN is trained using extracted features to distinguish five different gestures; accordingly it produces five different signals. These signals are transmitted to control the directions of the cited robot. The main contribution of this paper is, the technique used to recognize hand gestures is required only two features, these features can be extracted in very short time using quite easy methodology, and this makes the proposed technique so suitable for online interaction. In this methodology, the preprocessed image is partitioned column-wise into two half segments; from each half one feature is extracted. This feature represents the ratio of white to black pixels of the segment histogram. The NN showed very high accuracy in recognizing all of the proposed gesture classes. The NN output signals are transmitted to the robot microcontroller wirelessly using Bluetooth. Accordingly the microcontroller guides the robot to the desired direction. The overall system showed high performance in controlling the robot movement directions.

Non-ideal channel conditions degrade the performance of wireless networks due to the occurrence of frame errors. Most of the well-known works compute the saturation throughput and packet delay for the IEEE 802.11 Distributed Coordination Function (DCF) protocol with the assumption that transmission is carried out via an ideal channel (i.e., no channel bit errors or hidden stations), and/or the errors exist only in data packets. Besides, there are no considerations for transmission errors in the control frames (i.e., Request to Send (RTS), Clear to Send (CTS), and Acknowledgement (ACK)). Considering the transmission errors in the control frames adds complexity to the existing analysis for the wireless networks. In this paper, an analytical model to evaluate the Medium Access Control (MAC) layer saturation throughput and packet delay of the IEEE 802.11g and IEEE 802.11n protocols in the presence of both collisions and transmission errors in a non-ideal wireless channel is provided. The derived analytical expressions reveal that the saturation throughput and packet delay are affected by the network size (n), packet size, minimum backoff window size (Wmin), maximum backoff stage (m), and bit error rate (BER). These results are important for protocol optimization and network planning in wireless networks.

In this paper a radial distribution feeder protection scheme against short circuit faults is introduced. It is based on utilizing the substation measured current signals in detecting faults and obtaining useful information about their types and locations. In order to facilitate important measurement signals features extraction such that better diagnosis of faults can be achieved, the discrete wavelet transform is exploited. The captured features are then utilized in detecting, identifying the faulted phases (fault type), and fault location. In case of a fault occurrence, the detection scheme will make a decision to trip out a circuit breaker residing at the feeder mains. This decision is made based on a criteria that is set to distinguish between the various system states in a reliable and accurate manner. After that, the fault type and location are predicted making use of the cascade forward neural networks learning and generalization capabilities. Useful information about the fault location can be obtained provided that the fault distance from source, as well as whether it resides on the main feeder or on one of the laterals can be predicted. By testing the functionality of the proposed scheme, it is found that the detection of faults is done fastly and reliably from the view point of power system protection relaying requirements. It also proves to overcome the complexities provided by the feeder structure to the accuracy of the identification process of fault types and locations. All the simulations and analysis are performed utilizing MATLAB R2016b version software package.

In nowadays world of rapid evolution of exchanging digital data, data protection is required to protect data from the unauthorized parities. With the widely use of digital images of diverse fields, it is important to conserve the confidentiality of image’s data form any without authorization access. In this paper the problem of secret key exchanging with the communicated parities had been solved by using a random number generator which based on Linear Feedback Shift Register (LFSR). The encryption/decryption is based on Advance Encryption Standard (AES) with the random key generator. Also, in this paper, both grayscale and colored RGB images have been encrypted/decrypted. The functionality of proposed system of this paper, is concerned with three features: First feature, is dealing with the obstetrics of truly random and secure encryption key while the second one deals with encrypting the plain or secret image using AES algorithm and the third concern is the extraction the original image by decrypting the encrypted or cipher one. “Mean Square Error (MSE)”, “Peak Signal to Noise Ratio (PSNR)”, “Normalized Correlation (NK)”, and “Normalized Absolute Error (NAE)” are measured for both (original-encrypted) images and (original-decrypted) image in order to study and analyze the performance of the proposed system according to image quality features.