Volume 2 Issue 1
Authors: D. S. Khmel; A. V. Voytishek
Abstract: Kohonen self-organizing maps (SOM) have a lot of fruitful applications. In the classical monograph Kohonen T., Self-Organizing Maps (Third edition), New York: Springer-Verlag, 2001 the following fields of SOM applications are presented: signal processing, control theory, models of the biological brain function, experimental physics, chemistry and medicine, financial analysis, etc. One of the main applications of SOM is “automated” stochastic iterative numerical algorithm for constructing adaptive grids. Moreover, this algorithm can be treated as the most natural mathematical model of SOM. The algorithm starts with introducing arbitrary initial positions of points (nodes) inside some domain. On every iterative step a sample value of the stochastic variable, which is distributed with respect to given probability distribution density (this density defines the demanded arrangement of nodes in the domain), is realized numerically. The closest (“winner”) point to this sample value defines the learning coefficient (or neighborhood function) which influences on shift of every node. The special choice of the learning coefficient allows getting satisfactory arrangement of points after several iterations. There are difficulties in analytical description of the Kohonen scheme. This description is rather useful for theoretical investigation of the self-organizing algorithm (convergence, estimating of errors, etc.). In monograph the mentioned above, T.Kohonen suggested the following “continuous” approach. Under some principal simplifications (1D case, simplified form of the learning coefficient, assumption about ordering of the initial distribution of nodes, uniform distribution for “attraction nodes”) the recurrent formulas for node’s shifts are replaced by the system of differential equations for “most probable” positions of nodes. This system has no general analytical solution, and only numerical experiments can be used for investigation of asymptotic positions of nodes. In this paper we have proposed direct use of the formulas for node’s shift to get analytical recurrent expressions for the most probable positions of nodes under the Kohonen’s simplifications. We also showed that our approach helps to investigate some special effects of the self-organizing algorithm, in particular, the “boundary effect” which defines undesirable noticeable distances between the boundary nodes and the boundary of the domain. In addition we considered the possibilities for weakening of Kohonen’s restrictions: in particular, we have constructed recurrent formulas for special practical learning coefficient.
Keywords: Kohonen Self-Organizing Maps; Recurrent Formulas; Boundary Effect; Learning Radius
Authors: Siam Charoenseang; Tarinee Tonggoed
Abstract: This research presents an implementation of human-robot cooperation system using augmented reality technique. In this research, human operator and robot arm share the common workspace in virtual object assembly task. The technique of augmented reality is used for creating virtual objects and providing necessary information to the human operator. The virtual objects are in the form of 3D computer graphics superimposed on the real video images. The ARToolKit software library is used in the vision manager to process captured video image and obtain the positions and orientations of targeted objects. The task manager is responsible for generating action plans using STRIPS planning algorithm in assembly task and control system states. The robot manager takes care of computing forward/inverse kinematics of the developed robot arm, reading robot’s joint angles, and sending commands to control the robot. Graphics manager is used to generate 2D and 3D computer graphics rendered on the real video images. The graphics present all guidance information and virtual objects to the operator. The system can generate assembly plans for human and robot step by step. The robot arm is responsible for assisting the human operator by transferring virtual objects to the loading area. Furthermore, a task planner controls all robots’ operations accordingly to human actions. Human operator can accept or decline robot’s assistance. Human operator also receives robot’s task plan in the form of computer graphics during the operation. The computer-generated information will support human operator’s decision for a suitable next step action. Therefore, the augmented reality can enhance the cooperation between human operator and the robot effectively.
Keywords: Human-Robot Cooperation; Augmented Reality; Task Planning
Authors: Hussain Mohammed Dipu Kabir; Saeed Anwar; Md. Liakot Ali; Abu Shahadat Md. Ibrahim; Md. Abdul Matin
Abstract: This paper presents a Field-Programmable Gate Array (FPGA) based secured speech communication system. Data-size is one of the major concerns of cryptographic systems. To maintain same data-rate compression is performed at first. Compression reduced data-size. Watermark and random key is embedded at the vacant places. There are many encryption techniques, but for realtime encryption, fast encryption is needed. FPGA is an efficient device for these operations on realtime signals. Conventional processors contain small number of registers and perform large operations in multiple cycles. FPGA can perform a large number of operations concurrently. Change has brought at the generation of random numbers. To generate more secured random number, nibble bit of noise signal is Xored with hardware-generated random number. In proposed method voice signal is compressed, watermarked, encrypted and sent through a transmission medium from the transmitting end. Receiver receives that signal and decrypts both signal and watermark.
Keywords: FPGA; Watermarking; Compression; AES; DES; Eavesdropping