Intelligent Control of Robotized Workcell by Augmented Reality Application

The computer aided for design, analysis, control, visualization and simulation of robotized workcells is very interesting in this time. Computer Aided Robot Control (CARC) is a subsystem of the system CIM including the computer aided systems of all activities connected with visualization and working of robotized workcells. There are three basic ideas: current CAD/CAM/CAE systems for design and 3D visualization, special PC based control and simulation systems and Augmented Reality Aided Manufacturing (ARAM) systems. This paper describes example of Open Source software application that can to be utilized at planning of the robotized workcells, visualization and off-line programming the automated processes realized by authors.

A Real Time Set Up for Retrieval of Emotional States from Human Neural Responses

Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotiv EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Distributed Motion Control Real-Time Contouring Algorithm Implementation and Performance Test

This paper presents an implementation and performance test of a distributed motion control system based on a master-slave configuration used to move a plasma-cutting torch over a predefined trajectory. The master is a general-purpose computer running on an open source operating system platform and software developer. Software running in the master computer generates commands on real time and we measure performance based on a selected set of differences between expected and observed distances. We are testing the null hypothesis that the outcome trajectory is identical to the input against the alternative hypothesis that there is a shift to the right or left of the input one. We used the Wilcoxon signed ranks test method for the hypothesis test.

FITTER - A Framework for Integrating Activity Tracking Technologies into Electric Recreation for Children and Adolescents

Encouraging physical activity amongst children and adolescents is becoming an increasingly relevant issue in modern society. Studies have shown that involving children and adolescents in physical activity is essential for their physical, mental and social development. However, with technology playing an increasingly important role in reducing physical work it is becoming more critical to incorporate adequate physical activities into our lives. One way to overcome this problem is to harness technology so that it promotes physical activities, for example, by motivating children and adolescents to exercise more. This paper describes a promising solution to the question of how to increase levels of physical activity in children and adolescents by combining gaming technologies with exercise tracking goals. This research describes a framework called FITTER (Framework for Integrating activity Tracking Technologies for Electronic Recreation) that combines video game play with more traditional, non-computer physical activities.

Factors Affecting the Citizen’s Intention to Adopt E-government in Saudi Arabia

This paper discusses E-government, in particular the challenges that face its development and widespread adoption in Saudi Arabia. E-government can be defined based on an existing set of requirements. E-government has been implemented for a considerable time in developed countries. However, E-government services still face many challenges in their implementation and general adoption in Saudi Arabia. In addition, the literature review and the discussion identify the influential factors, such as quality of service, diffusion of innovation, computer and information literacy, culture, lack of awareness, technical infrastructure, website design, and security, that affect the citizens’ intention to adopt E-government services in Saudi Arabia. Consequently, these factors have been integrated in a new model that would influence citizen to adopt E- government services. Therefore, this research presents an integrated model for ascertaining the intention to adopt E-government services and thereby aiding governments in accessing what is required to increase adoption.

Human Interactive E-learning Systems using Head Posture Images

This paper explains a novel approach to human interactive e-learning systems using head posture images. Students- face and hair information are used to identify a human presence and estimate the gaze direction. We then define the human-computer interaction level and test the definition using ten students and seventy different posture images. The experimental results show that head posture images provide adequate information for increasing human-computer interaction in e-learning systems.

A Rigid Point Set Registration of Remote Sensing Images Based on Genetic Algorithms and Hausdorff Distance

Image registration is the process of establishing point by point correspondence between images obtained from a same scene. This process is very useful in remote sensing, medicine, cartography, computer vision, etc. Then, the task of registration is to place the data into a common reference frame by estimating the transformations between the data sets. In this work, we develop a rigid point registration method based on the application of genetic algorithms and Hausdorff distance. First, we extract the feature points from both images based on the algorithm of global and local curvature corner. After refining the feature points, we use Hausdorff distance as similarity measure between the two data sets and for optimizing the search space we use genetic algorithms to achieve high computation speed for its inertial parallel. The results show the efficiency of this method for registration of satellite images.

Computer Study of Cluster Mechanism of Anti-greenhouse Effect

Absorption spectra of infra-red (IR) radiation of the disperse water medium absorbing the most important greenhouse gases: CO2 , N2O , CH4 , C2H2 , C2H6 have been calculated by the molecular dynamics method. Loss of the absorbing ability at the formation of clusters due to a reduction of the number of centers interacting with IR radiation, results in an anti-greenhouse effect. Absorption of O3 molecules by the (H2O)50 cluster is investigated at its interaction with Cl- ions. The splitting of ozone molecule on atoms near to cluster surface was observed. Interaction of water cluster with Cl- ions causes the increase of integrated intensity of emission spectra of IR radiation, and also essential reduction of the similar characteristic of Raman spectrum. Relative integrated intensity of absorption of IR radiation for small water clusters was designed. Dependences of the quantity of weight on altitude for vapor of monomers, clusters, droplets, crystals and mass of all moisture were determined. The anti-greenhouse effect of clusters was defined as the difference of increases of average global temperature of the Earth, caused by absorption of IR radiation by free water molecules forming clusters, and absorption of clusters themselves. The greenhouse effect caused by clusters makes 0.53 K, and the antigreenhouse one is equal to 1.14 K. The increase of concentration of CO2 in the atmosphere does not always correlate with the amplification of greenhouse effect.

Interdisciplinary Principles of Field-Like Coordination in the Case of Self-Organized Social Systems1

This interdisciplinary research aims to distinguish universal scale-free and field-like fundamental principles of selforganization observable across many disciplines like computer science, neuroscience, microbiology, social science, etc. Based on these universal principles we provide basic premises and postulates for designing holistic social simulation models. We also introduce pervasive information field (PIF) concept, which serves as a simulation media for contextual information storage, dynamic distribution and organization in social complex networks. PIF concept specifically is targeted for field-like uncoupled and indirect interactions among social agents capable of affecting and perceiving broadcasted contextual information. Proposed approach is expressive enough to represent contextual broadcasted information in a form locally accessible and immediately usable by network agents. This paper gives some prospective vision how system-s resources (tangible and intangible) could be simulated as oscillating processes immersed in the all pervasive information field.

Faster FPGA Routing Solution using DNA Computing

There are many classical algorithms for finding routing in FPGA. But Using DNA computing we can solve the routes efficiently and fast. The run time complexity of DNA algorithms is much less than other classical algorithms which are used for solving routing in FPGA. The research in DNA computing is in a primary level. High information density of DNA molecules and massive parallelism involved in the DNA reactions make DNA computing a powerful tool. It has been proved by many research accomplishments that any procedure that can be programmed in a silicon computer can be realized as a DNA computing procedure. In this paper we have proposed two tier approaches for the FPGA routing solution. First, geometric FPGA detailed routing task is solved by transforming it into a Boolean satisfiability equation with the property that any assignment of input variables that satisfies the equation specifies a valid routing. Satisfying assignment for particular route will result in a valid routing and absence of a satisfying assignment implies that the layout is un-routable. In second step, DNA search algorithm is applied on this Boolean equation for solving routing alternatives utilizing the properties of DNA computation. The simulated results are satisfactory and give the indication of applicability of DNA computing for solving the FPGA Routing problem.

Pattern Recognition of Biological Signals

This paper presents an evolutionary method for designing electronic circuits and numerical methods associated with monitoring systems. The instruments described here have been used in studies of weather and climate changes due to global warming, and also in medical patient supervision. Genetic Programming systems have been used both for designing circuits and sensors, and also for determining sensor parameters. The authors advance the thesis that the software side of such a system should be written in computer languages with a strong mathematical and logic background in order to prevent software obsolescence, and achieve program correctness.

Action Potential Propagation in Inhomogeneous 2D Mouse Ventricular Tissue Model

Heterogeneous repolarization causes dispersion of the T-wave and has been linked to arrhythmogenesis. Such heterogeneities appear due to differential expression of ionic currents in different regions of the heart, both in healthy and diseased animals and humans. Mice are important animals for the study of heart diseases because of the ability to create transgenic animals. We used our previously reported model of mouse ventricular myocytes to develop 2D mouse ventricular tissue model consisting of 14,000 cells (apical or septal ventricular myocytes) and to study the stability of action potential propagation and Ca2+ dynamics. The 2D tissue model was implemented as a FORTRAN program code for highperformance multiprocessor computers that runs on 36 processors. Our tissue model is able to simulate heterogeneities not only in action potential repolarization, but also heterogeneities in intracellular Ca2+ transients. The multicellular model reproduced experimentally observed velocities of action potential propagation and demonstrated the importance of incorporation of realistic Ca2+ dynamics for action potential propagation. The simulations show that relatively sharp gradients of repolarization are predicted to exist in 2D mouse tissue models, and they are primarily determined by the cellular properties of ventricular myocytes. Abrupt local gradients of channel expression can cause alternans at longer pacing basic cycle lengths than gradual changes, and development of alternans depends on the site of stimulation.

A Fully Parallel Reverse Converter

The residue number system (RNS) is popular in high performance computation applications because of its carry-free nature. The challenges of RNS systems design lie in the moduli set selection and in the reverse conversion from residue representation to weighted representation. In this paper, we proposed a fully parallel reverse conversion algorithm for the moduli set {rn - 2, rn - 1, rn}, based on simple mathematical relationships. Also an efficient hardware realization of this algorithm is presented. Our proposed converter is very faster and results to hardware savings, compared to the other reverse converters.

Sperm Identification Using Elliptic Model and Tail Detection

The conventional assessment of human semen is a highly subjective assessment, with considerable intra- and interlaboratory variability. Computer-Assisted Sperm Analysis (CASA) systems provide a rapid and automated assessment of the sperm characteristics, together with improved standardization and quality control. However, the outcome of CASA systems is sensitive to the method of experimentation. While conventional CASA systems use digital microscopes with phase-contrast accessories, producing higher contrast images, we have used raw semen samples (no staining materials) and a regular light microscope, with a digital camera directly attached to its eyepiece, to insure cost benefits and simple assembling of the system. However, since the accurate finding of sperms in the semen image is the first step in the examination and analysis of the semen, any error in this step can affect the outcome of the analysis. This article introduces and explains an algorithm for finding sperms in low contrast images: First, an image enhancement algorithm is applied to remove extra particles from the image. Then, the foreground particles (including sperms and round cells) are segmented form the background. Finally, based on certain features and criteria, sperms are separated from other cells.

Offline Handwritten Signature Recognition

Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capability to reliably distinguish between an authorized person and an imposter. Signature verification systems can be categorized as offline (static) and online (dynamic). This paper presents a neural network based recognition of offline handwritten signatures system that is trained with low-resolution scanned signature images.

Applications of Prediction and Identification Using Adaptive DCMAC Neural Networks

An adaptive dynamic cerebellar model articulation controller (DCMAC) neural network used for solving the prediction and identification problem is proposed in this paper. The proposed DCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) neural network in efficient learning mechanism, guaranteed system stability and dynamic response. The recurrent network is embedded in the DCMAC by adding feedback connections in the association memory space so that the DCMAC captures the dynamic response, where the feedback units act as memory elements. The dynamic gradient descent method is adopted to adjust DCMAC parameters on-line. Moreover, the analytical method based on a Lyapunov function is proposed to determine the learning-rates of DCMAC so that the variable optimal learning-rates are derived to achieve most rapid convergence of identifying error. Finally, the adaptive DCMAC is applied in two computer simulations. Simulation results show that accurate identifying response and superior dynamic performance can be obtained because of the powerful on-line learning capability of the proposed DCMAC.

Testing Loaded Programs Using Fault Injection Technique

Fault tolerance is critical in many of today's large computer systems. This paper focuses on improving fault tolerance through testing. Moreover, it concentrates on the memory faults: how to access the editable part of a process memory space and how this part is affected. A special Software Fault Injection Technique (SFIT) is proposed for this purpose. This is done by sequentially scanning the memory of the target process, and trying to edit maximum number of bytes inside that memory. The technique was implemented and tested on a group of programs in software packages such as jet-audio, Notepad, Microsoft Word, Microsoft Excel, and Microsoft Outlook. The results from the test sample process indicate that the size of the scanned area depends on several factors. These factors are: process size, process type, and virtual memory size of the machine under test. The results show that increasing the process size will increase the scanned memory space. They also show that input-output processes have more scanned area size than other processes. Increasing the virtual memory size will also affect the size of the scanned area but to a certain limit.

The Shaping of a Triangle Steel Plate into an Equilateral Vertical Steel by Finite-Element Modeling

The orthogonal processes to shape the triangle steel plate into a equilateral vertical steel are examined by an incremental elasto-plastic finite-element method based on an updated Lagrangian formulation. The highly non-linear problems due to the geometric changes, the inelastic constitutive behavior and the boundary conditions varied with deformation are taken into account in an incremental manner. On the contact boundary, a modified Coulomb friction mode is specially considered. A weighting factor r-minimum is employed to limit the step size of loading increment to linear relation. In particular, selective reduced integration was adopted to formulate the stiffness matrix. The simulated geometries of verticality could clearly demonstrate the vertical processes until unloading. A series of experiments and simulations were performed to validate the formulation in the theory, leading to the development of the computer codes. The whole deformation history and the distribution of stress, strain and thickness during the forming process were obtained by carefully considering the moving boundary condition in the finite-element method. Therefore, this modeling can be used for judging whether a equilateral vertical steel can be shaped successfully. The present work may be expected to improve the understanding of the formation of the equilateral vertical steel.

IVE: Virtual Humans AI Prototyping Toolkit

IVE toolkit has been created for facilitating research,education and development in the ?eld of virtual storytelling andcomputer games. Primarily, the toolkit is intended for modellingaction selection mechanisms of virtual humans, investigating level-of-detail AI techniques for large virtual environments, and for exploringjoint behaviour and role-passing technique (Sec. V). Additionally, thetoolkit can be used as an AI middleware without any changes. Themain facility of IVE is that it serves for prototyping both the AI andvirtual worlds themselves. The purpose of this paper is to describeIVE?s features in general and to present our current work - includingan educational game - on this platform.Keywords? AI middleware, simulation, virtual world.

Implementation of an Improved Secure System Detection for E-passport by using EPC RFID Tags

Current proposals for E-passport or ID-Card is similar to a regular passport with the addition of tiny contactless integrated circuit (computer chip) inserted in the back cover, which will act as a secure storage device of the same data visually displayed on the photo page of the passport. In addition, it will include a digital photograph that will enable biometric comparison, through the use of facial recognition technology at international borders. Moreover, the e-passport will have a new interface, incorporating additional antifraud and security features. However, its problems are reliability, security and privacy. Privacy is a serious issue since there is no encryption between the readers and the E-passport. However, security issues such as authentication, data protection and control techniques cannot be embedded in one process. In this paper, design and prototype implementation of an improved E-passport reader is presented. The passport holder is authenticated online by using GSM network. The GSM network is the main interface between identification center and the e-passport reader. The communication data is protected between server and e-passport reader by using AES to encrypt data for protection will transferring through GSM network. Performance measurements indicate a 19% improvement in encryption cycles versus previously reported results.