Implementing a Visual Servoing System for Robot Controlling

Nowadays, with the emerging of the new applications like robot control in image processing, artificial vision for visual servoing is a rapidly growing discipline and Human-machine interaction plays a significant role for controlling the robot. This paper presents a new algorithm based on spatio-temporal volumes for visual servoing aims to control robots. In this algorithm, after applying necessary pre-processing on video frames, a spatio-temporal volume is constructed for each gesture and feature vector is extracted. These volumes are then analyzed for matching in two consecutive stages. For hand gesture recognition and classification we tested different classifiers including k-Nearest neighbor, learning vector quantization and back propagation neural networks. We tested the proposed algorithm with the collected data set and results showed the correct gesture recognition rate of 99.58 percent. We also tested the algorithm with noisy images and algorithm showed the correct recognition rate of 97.92 percent in noisy images.

Analyzing and Comparing the Architectural Specifications and the Urban Role of Scientific– Technological Parks in Iran and the World

The issue of scientific – technological parks has been proposed in several countries of the world especially in western countries since a few decades ago and its efficiency is under examination. In our county Iran, some scientific – technological parks have been established or are being established. This design would evaluate the urban role and method of architecture of these parks in order to criticize its efficiency and offer some suggestions, as much as possible to improve its building methods in Iran. The main problem of this design is that how much these parks in Iran do meet the international measurements. So for this reason, one scientific park in Iran and one from western countries would be studied and compared with each other.

Constitutive Equations for Human Saphenous Vein Coronary Artery Bypass Graft

Coronary artery bypass grafts (CABG) are widely studied with respect to hemodynamic conditions which play important role in presence of a restenosis. However, papers which concern with constitutive modeling of CABG are lacking in the literature. The purpose of this study is to find a constitutive model for CABG tissue. A sample of the CABG obtained within an autopsy underwent an inflation–extension test. Displacements were recoredered by CCD cameras and subsequently evaluated by digital image correlation. Pressure – radius and axial force – elongation data were used to fit material model. The tissue was modeled as onelayered composite reinforced by two families of helical fibers. The material is assumed to be locally orthotropic, nonlinear, incompressible and hyperelastic. Material parameters are estimated for two strain energy functions (SEF). The first is classical exponential. The second SEF is logarithmic which allows interpretation by means of limiting (finite) strain extensibility. Presented material parameters are estimated by optimization based on radial and axial equilibrium equation in a thick-walled tube. Both material models fit experimental data successfully. The exponential model fits significantly better relationship between axial force and axial strain than logarithmic one.

Biokinetics of Coping Mechanism of Freshwater tilapia following Exposure to Waterborne and Dietary Copper

The purpose of this study was to understand the main sources of copper (Cu) accumulation in target organs of tilapia (Oreochromis mossambicus) and to investigate how the organism mediate the process of Cu accumulation under prolonged conditions. By measuring both dietary and waterborne Cu accumulation and total concentrations in tilapia with biokinetic modeling approach, we were able to clarify the biokinetic coping mechanisms for the long term Cu accumulation. This study showed that water and food are both the major source of Cu for the muscle and liver of tilapia. This implied that control the Cu concentration in these two routes will be correlated to the Cu bioavailability for tilapia. We found that exposure duration and level of waterborne Cu drove the Cu accumulation in tilapia. The ability for Cu biouptake and depuration in organs of tilapia were actively mediated under prolonged exposure conditions. Generally, the uptake rate, depuration rate and net bioaccumulation ability in all selected organs decreased with the increasing level of waterborne Cu and extension of exposure duration.Muscle tissues accounted for over 50%of the total accumulated Cu and played a key role in buffering the Cu burden in the initial period of exposure, alternatively, the liver acted a more important role in the storage of Cu with the extension of exposures. We concluded that assumption of the constant biokinetic rates could lead to incorrect predictions with overestimating the long-term Cu accumulation in ecotoxicological risk assessments.

Parametric Analysis in the Electronic Sensor Frequency Adjustment Process

The use of electronic sensors in the electronics industry has become increasingly popular over the past few years, and it has become a high competition product. The frequency adjustment process is regarded as one of the most important process in the electronic sensor manufacturing process. Due to inaccuracies in the frequency adjustment process, up to 80% waste can be caused due to rework processes; therefore, this study aims to provide a preliminary understanding of the role of parameters used in the frequency adjustment process, and also make suggestions in order to further improve performance. Four parameters are considered in this study: air pressure, dispensing time, vacuum force, and the distance between the needle tip and the product. A full factorial design for experiment 2k was considered to determine those parameters that significantly affect the accuracy of the frequency adjustment process, where a deviation in the frequency after adjustment and the target frequency is expected to be 0 kHz. The experiment was conducted on two levels, using two replications and with five center-points added. In total, 37 experiments were carried out. The results reveal that air pressure and dispensing time significantly affect the frequency adjustment process. The mathematical relationship between these two parameters was formulated, and the optimal parameters for air pressure and dispensing time were found to be 0.45 MPa and 458 ms, respectively. The optimal parameters were examined by carrying out a confirmation experiment in which an average deviation of 0.082 kHz was achieved.

Hybrid Intelligent Intrusion Detection System

Intrusion Detection Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for intrusion detection. The techniques that are being investigated includes neural networks and fuzzy logic with network profiling, that uses simple data mining techniques to process the network data. The proposed system is a hybrid system that combines anomaly, misuse and host based detection. Simple Fuzzy rules allow us to construct if-then rules that reflect common ways of describing security attacks. For host based intrusion detection we use neural-networks along with self organizing maps. Suspicious intrusions can be traced back to its original source path and any traffic from that particular source will be redirected back to them in future. Both network traffic and system audit data are used as inputs for both.

Endeavoring Innovation via Research and Development Management: A Case of Iranian Industrial Sector

This study aims at investigating factors in research and development (R&D) growth and exploring the role of R&D management in enhancing social innovation and productivity improvement in Iran-s industrial sector. It basically explores the common types of R&D activities and the industries which benefited the most from active R&D units in Iran. The researchers generated qualitative analyses obtained from primary and secondary data. The primary data have been retrieved through interviews with five key players (Managing Director, Internal Manager, General Manager, Executive Manager, and Project Manager) in the industrial sector. The secondary data acquired from an investigation on Mazandaran, a province of northern Iran. The findings highlight Iran-s focuses of R & D on cost reduction and upgrading productivity. Industries that have benefited the most from active R&D units are metallic, machinery and equipment design, and automotive. We rank order the primary effects of R&D on productivity improvement as follows, industry improvement, economic growth, using professional human resources, generating productivity and creativity culture, creating a competitive and innovative environment, and increasing people-s knowledge. Generally, low budget dedication and insufficient supply of highly skilled scientists and engineers are two important obstacles for R&D in Iran. Whereas, R&D has resulted in improvement in Iranian society, transfer of contemporary knowledge into the international market is still lacking.

What Do Young People Seeking Professional Help Want and Expect From Therapy?

Client expectations and preferences about therapy represent an important area of investigation as research shows they are linked to engagement in therapy and therapy outcomes. Studies examining young people-s expectations and preferences of therapy remain a neglected area of research. The present study explored what expectations and preferences young people seeking professional help held regarding: their role as a client, their therapist-s role, their therapeutic outcomes, and the processes of therapy. Gender and age differences were also examined. Participants included 188 young people aged 12-25 who completed a survey while attending their initial session at a youth mental health service. Data were analysed using quantitative methods. Results found the young people held significantly more pessimistic expectations around therapy when compared to what they had wanted therapy to be like. Few age and gender differences were found. Results highlight the importance of a collaborative therapy approach when working with young people.

Optimization and GIS-Based Intelligent Decision Support System for Urban Transportation Systems Analysis

Optimization plays an important role in most real world applications that support decision makers to take the right decision regarding the strategic directions and operations of the system they manage. Solutions for traffic management and traffic congestion problems are considered major problems that most decision making authorities for cities around the world are looking for. This review paper gives a full description of the traffic problem as part of the transportation planning process and present a view as a framework of urban transportation system analysis where the core of the system is a transportation network equilibrium model that is based on optimization techniques and that can also be used for evaluating an alternative solution or a combination of alternative solutions for the traffic congestion. Different transportation network equilibrium models are reviewed from the sequential approach to the multiclass combining trip generation, trip distribution, modal split, trip assignment and departure time model. A GIS-Based intelligent decision support system framework for urban transportation system analysis is suggested for implementation where the selection of optimized alternative solutions, single or packages, will be based on an intelligent agent rather than human being which would lead to reduction in time, cost and the elimination of the difficulty, by human being, for finding the best solution to the traffic congestion problem.

Design of the Propelling Nozzles for the Launchers and Satellites

The aim of this work is to determine the supersonic nozzle profiles used in propulsion, for the launchers or embarked with the satellites. This design has as a role firstly, to give a important propulsion, i.e. with uniform and parallel flow at exit, secondly to find a short length profiles without modification of the flow in the nozzle. The first elaborate program is used to determine the profile of divergent by using the characteristics method for an axisymmetric flow. The second program is conceived by using the finite volume method to determine and test the profile found connected to a convergent.

3-D Reconstruction of Objects Using Digital Fringe Projection: Survey and Experimental Study

Three-dimensional reconstruction of small objects has been one of the most challenging problems over the last decade. Computer graphics researchers and photography professionals have been working on improving 3D reconstruction algorithms to fit the high demands of various real life applications. Medical sciences, animation industry, virtual reality, pattern recognition, tourism industry, and reverse engineering are common fields where 3D reconstruction of objects plays a vital role. Both lack of accuracy and high computational cost are the major challenges facing successful 3D reconstruction. Fringe projection has emerged as a promising 3D reconstruction direction that combines low computational cost to both high precision and high resolution. It employs digital projection, structured light systems and phase analysis on fringed pictures. Research studies have shown that the system has acceptable performance, and moreover it is insensitive to ambient light. This paper presents an overview of fringe projection approaches. It also presents an experimental study and implementation of a simple fringe projection system. We tested our system using two objects with different materials and levels of details. Experimental results have shown that, while our system is simple, it produces acceptable results.

Productive Design and Calculation of Intermittent Mechanisms with Radial Parallel Cams

The paper deals with the kinematics and automated calculation of intermittent mechanisms with radial cams. Currently, electronic cams are increasingly applied in the drives of working link mechanisms. Despite a huge advantage of electronic cams in their reprogrammability or instantaneous change of displacement diagrams, conventional cam mechanisms have an irreplaceable role in production and handling machines. With high frequency of working cycle periods, the dynamic load of the proper servomotor rotor increases and efficiency of electronic cams strongly decreases. Though conventional intermittent mechanisms with radial cams are representatives of fixed automation, they have distinct advantages in their high speed (high dynamics), positional accuracy and relatively easy manufacture. We try to remove the disadvantage of firm displacement diagram by reducing costs for simple design and automated calculation that leads reliably to high-quality and inexpensive manufacture.

The Role of Human Resource System on Crisis Resolve

Within the new world order, the term “crisis" is nowadays familiar to companies. Organizations are experiencing conditions which are surprising, uncertain, often adverse and usually unstable. The companies, who grasp the importance of transformation within the information age, have felt the need to develop modern methods to achieve the ability to thrive despite severe shocks. Through strategically managing human resource and developing appropriate elements of human resource system, companies can be assured for resolving the crisis. In this paper the role of HR system on resolving crisis has been evaluated. To help accomplish this, an insight on previous strategic HRM literature and an introduction to the elements and relationship within HR systems has been presented. It also reviews different attitude around resilience in literature. It continues by reviewing three elements central to developing an organization-s capacity for crisis resolving and it will demonstrate how designing proper elements of HR system can lead the organizations to possess the ability for passing through crisis. Finally it will evaluate an Iranian Insurance organization in case of one of the three central elements (specific cognitive ability) and observe how successful they were on developing an effective HR system to be ready for facing crisis.

Communication Behaviors as Predictors of Long-Term Dyadic Adjustment: Personality as a Moderator

In this longitudinal study, we examined the moderating role of personality in the relationship between communication behaviors and long-term dyadic adjustment. A sample of 82 couples completed the NEO Five-Factor Inventory and the Dyadic Adjustment Scale. These couples were also videotaped during a 15-minute problem-solving discussion. Approximately 2.5 years later, these couples completed again the Dyadic Adjustment Scale. Results show that personality of both men and women moderates the relationship between communication behaviors of the partner and long-term dyadic adjustment of the individual. Women-s openness and men-s extraversion moderate the relationship between some communication behaviors and long-term dyadic adjustment

The removal of Ni, Cu and Fe from a Mixed Metal System using Sodium Hypophosphite as a Reducing Agent

The main objective of this study was to remove and recover Ni, Cu and Fe from a mixed metal system using sodium hypophosphite as a reducing agent and nickel powder as seeding material. The metal systems studied consisted of Ni-Cu, Ni-Fe and Ni-Cu-Fe solutions. A 5 L batch reactor was used to conduct experiments where 100 mg/l of each respective metal was used. It was found that the metals were reduced to their elemental form with removal efficiencies of over 80%. The removal efficiency decreased in the order Fe>Ni>Cu. The metal powder obtained contained between 97-99% Ni and was almost spherical and porous. Size enlargement by aggregation was the dominant particulate process.

Tool Wear and Surface Roughness Prediction using an Artificial Neural Network (ANN) in Turning Steel under Minimum Quantity Lubrication (MQL)

Tool wear and surface roughness prediction plays a significant role in machining industry for proper planning and control of machining parameters and optimization of cutting conditions. This paper deals with developing an artificial neural network (ANN) model as a function of cutting parameters in turning steel under minimum quantity lubrication (MQL). A feed-forward backpropagation network with twenty five hidden neurons has been selected as the optimum network. The co-efficient of determination (R2) between model predictions and experimental values are 0.9915, 0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra respectively. The results imply that the model can be used easily to forecast tool wear and surface roughness in response to cutting parameters.

Growth, Population, Exports and Wagner's Law: A Case Study of Pakistan (1972-2007)

The objective of this study is to examine the validity of Wagner-s law and relationship between economic growth, population and export for Pakistan. The ARDL Bounds cointegration and ECM are utilized for long and short run equilibrium for the period of 1972-2007. Population has considerable role in an economy and exports are the main source to raise the GDP. With the increase in GDP, the government expenditures may or may not increase. The empirical results indicate that the Wagner-s Law does hold, as economic growth is significantly and positively correlated with government expenditures. However, population and exports have also significant and positive impact on government expenditures both in short and long run. The significant and negative coefficient of error correction term in ECM indicates that after a shock, the long rum equilibrium will again converge towards equilibrium about 70.82 percent within a year.

Aggressive Driving in Young Motorists

Road rage is an increasingly prevalent expression of aggression in our society. Its dangers are apparent and understanding its causes may shed light on preventative measures. This study involved a fifteen-minute survey administered to 147 undergraduate students at a North Eastern suburban university. The survey consisted of a demographics section, questions regarding financial investment in respondents- vehicles, experience driving, habits of driving, experiences witnessing role models driving, and an evaluation of road rage behavior using the Driving Vengeance Questionnaire. The study found no significant differences in driving aggression between respondents who were financially invested in their vehicle compared to those who were not, or between respondents who drove in heavy traffic hours compared to those who did not, suggesting internal factors correlate with aggressive driving habits. The study also found significant differences in driving aggression between males versus females, those with more points on their license versus fewer points, and those who witnessed parents driving aggressively very often versus rarely or never. Additional studies can investigate how witnessing parents driving aggressively is related to future driving behaviors.

Energy Supply, Demand and Environmental Analysis – A Case Study of Indian Energy Scenario

Increasing concerns over climate change have limited the liberal usage of available energy technology options. India faces a formidable challenge to meet its energy needs and provide adequate energy of desired quality in various forms to users in sustainable manner at reasonable costs. In this paper, work carried out with an objective to study the role of various energy technology options under different scenarios namely base line scenario, high nuclear scenario, high renewable scenario, low growth and high growth rate scenario. The study has been carried out using Model for Energy Supply Strategy Alternatives and their General Environmental Impacts (MESSAGE) model which evaluates the alternative energy supply strategies with user defined constraints on fuel availability, environmental regulations etc. The projected electricity demand, at the end of study period i.e. 2035 is 500490 MWYr. The model predicted the share of the demand by Thermal: 428170 MWYr, Hydro: 40320 MWYr, Nuclear: 14000 MWYr, Wind: 18000 MWYr in the base line scenario. Coal remains the dominant fuel for production of electricity during the study period. However, the import dependency of coal increased during the study period. In baseline scenario the cumulative carbon dioxide emissions upto 2035 are about 11,000 million tones of CO2. In the scenario of high nuclear capacity the carbon dioxide emissions reduced by 10 % when nuclear energy share increased to 9 % compared to 3 % in baseline scenario. Similarly aggressive use of renewables reduces 4 % of carbon dioxide emissions.

Developing Pedotransfer Functions for Estimating Some Soil Properties using Artificial Neural Network and Multivariate Regression Approaches

Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.