The influence of Local Export Externalities and Firm International Experience on Export Performance

This research tries to analyze the role that knowledge about foreign markets has in increasing firms- exports in clustered spaces. We consider two interrelated sources of knowledge: firms- direct experience and indirect experience from other clustered firms – export externalities. In particular, it is proposed that firms would improve their export performance by accessing to export externalities if they have some previous direct experience that allows them to identify, understand and exploit them. Also, we propose that this positive influence of previous direct experience on export externalities keeps only up to a point, where it becomes negative, creating an inverted “U" shape. Empirical evidence gathered among wine producers located in La Rioja tends to confirm that firms enjoy of export externalities if they have export experience along several years and countries increase their export performance. While this relationship becomes less relevant as they develop a higher experience, we could not confirm the existence of a curvilinear relationship in their influence on export externalities and export performance.

Involving Action Potential Morphology on a New Cellular Automata Model of Cardiac Action Potential Propagation

Computer modeling has played a unique role in understanding electrocardiography. Modeling and simulating cardiac action potential propagation is suitable for studying normal and pathological cardiac activation. This paper presents a 2-D Cellular Automata model for simulating action potential propagation in cardiac tissue. We demonstrate a novel algorithm in order to use minimum neighbors. This algorithm uses the summation of the excitability attributes of excited neighboring cells. We try to eliminate flat edges in the result patterns by inserting probability to the model. We also preserve the real shape of action potential by using linear curve fitting of one well known electrophysiological model.

Integrating Decision Tree and Spatial Cluster Analysis for Landslide Susceptibility Zonation

Landslide susceptibility map delineates the potential zones for landslide occurrence. Previous works have applied multivariate methods and neural networks for mapping landslide susceptibility. This study proposed a new approach to integrate decision tree model and spatial cluster statistic for assessing landslide susceptibility spatially. A total of 2057 landslide cells were digitized for developing the landslide decision tree model. The relationships of landslides and instability factors were explicitly represented by using tree graphs in the model. The local Getis-Ord statistics were used to cluster cells with high landslide probability. The analytic result from the local Getis-Ord statistics was classed to create a map of landslide susceptibility zones. The map was validated using new landslide data with 482 cells. Results of validation show an accuracy rate of 86.1% in predicting new landslide occurrence. This indicates that the proposed approach is useful for improving landslide susceptibility mapping.

Architecture Based on Dynamic Graphs for the Dynamic Reconfiguration of Farms of Computers

In the last years, the computers have increased their capacity of calculus and networks, for the interconnection of these machines. The networks have been improved until obtaining the actual high rates of data transferring. The programs that nowadays try to take advantage of these new technologies cannot be written using the traditional techniques of programming, since most of the algorithms were designed for being executed in an only processor,in a nonconcurrent form instead of being executed concurrently ina set of processors working and communicating through a network.This paper aims to present the ongoing development of a new system for the reconfiguration of grouping of computers, taking into account these new technologies.

An Experimental Study of the Effect of Coil Step on Heat Transfer Coefficient in Shell- Side of Shell-and-Coil Heat Exchanger

In this study the mixed convection heat transfer in a coil-in-shell heat exchanger for various Reynolds numbers and various dimensionless coil pitch was experimentally investigated. The experiments were conducted for both laminar and turbulent flow inside coil and the effects of coil pitch on shell-side heat transfer coefficient of the heat exchanger were studied. The particular difference in this study in comparison with the other similar studies was the boundary conditions for the helical coils. The results indicate that with the increase of coil pitch, shell-side heat transfer coefficient is increased.

Optimizing Turning Parameters for Cylindrical Parts Using Simulated Annealing Method

In this paper, a simulated annealing algorithm has been developed to optimize machining parameters in turning operation on cylindrical workpieces. The turning operation usually includes several passes of rough machining and a final pass of finishing. Seven different constraints are considered in a non-linear model where the goal is to achieve minimum total cost. The weighted total cost consists of machining cost, tool cost and tool replacement cost. The computational results clearly show that the proposed optimization procedure has considerably improved total operation cost by optimally determining machining parameters.

Multihop Cooperative Transmissions for Asymmetric Traffic Accommodation in CDMA/FDD Cellular Networks

The asymmetric trafc between uplink and downlink over recent mobile communication systems has been conspicuous because of providing new communication services. This paper proposes an asymmetric trafc accommodation scheme adopting a multihop cooperative transmission technique for CDMA/FDD cellular networks. The proposed scheme employs the cooperative transmission technique in the already proposed downlink multihop transmissions for the accommodation of the asymmetric trafc, which utilizes the vacant uplink band for the downlink relay transmissions. The proposed scheme reduces the transmission power at the downlink relay transmissions and then suppresses the interference to the uplink communications, and thus, improves the uplink performance. The proposed scheme is evaluated by computer simulation and the results show that it can achieve better throughput performance.

Optimal Design of Airfoil with High Aspect Ratio in Unmanned Aerial Vehicles

Shape optimization of the airfoil with high aspect ratio of long endurance unmanned aerial vehicle (UAV) is performed by the multi-objective optimization technology coupled with computational fluid dynamics (CFD). For predicting the aerodynamic characteristics around the airfoil the high-fidelity Navier-Stokes solver is employed and SMOGA (Simple Multi-Objective Genetic Algorithm), which is developed by authors, is used for solving the multi-objective optimization problem. To obtain the optimal solutions of the design variable (i.e., sectional airfoil profile, wing taper ratio and sweep) for high performance of UAVs, both the lift and lift-to-drag ratio are maximized whereas the pitching moment should be minimized, simultaneously. It is found that the lift force and lift-to-drag ratio are linearly dependent and a unique and dominant solution are existed. However, a trade-off phenomenon is observed between the lift-to-drag ratio and pitching moment. As the result of optimization, sixty-five (65) non-dominated Pareto individuals at the cutting edge of design spaces that is decided by airfoil shapes can be obtained.

Effect of Nano-Silver on Growth of Saffron in Flooding Stress

Saffron (Crocus sativus) is cultivated as spices, medicinal and aromatic plant species. At autumn season, heavy rainfall can cause flooding stress and inhibits growth of saffron. Thus this research was conducted to study the effect of silver ion (as an ethylene inhibitor) on growth of saffron under flooding conditions. The corms of saffron were soaked with one concentration of nano silver (0, 40, 80 or 120 ppm) and then planting under flooding stress or non flooding stress conditions. Results showed that number of roots, root length, root fresh and dry weight, leaves fresh and dry weight were reduced by 10 day flooding stress. Soaking saffron corms with 40 or 80 ppm concentration of nano silver rewarded the effect of flooding stress on the root number, by increasing it. Furthermore, 40 ppm of nano silver increased root length in stress. Nano silver 80 ppm in flooding stress, increased leaves dry weight.

Selecting Negative Examples for Protein-Protein Interaction

Proteomics is one of the largest areas of research for bioinformatics and medical science. An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. Predicting Protein-Protein Interaction (PPI) is one of the crucial and decisive problems in current research. Genomic data offer a great opportunity and at the same time a lot of challenges for the identification of these interactions. Many methods have already been proposed in this regard. In case of in-silico identification, most of the methods require both positive and negative examples of protein interaction and the perfection of these examples are very much crucial for the final prediction accuracy. Positive examples are relatively easy to obtain from well known databases. But the generation of negative examples is not a trivial task. Current PPI identification methods generate negative examples based on some assumptions, which are likely to affect their prediction accuracy. Hence, if more reliable negative examples are used, the PPI prediction methods may achieve even more accuracy. Focusing on this issue, a graph based negative example generation method is proposed, which is simple and more accurate than the existing approaches. An interaction graph of the protein sequences is created. The basic assumption is that the longer the shortest path between two protein-sequences in the interaction graph, the less is the possibility of their interaction. A well established PPI detection algorithm is employed with our negative examples and in most cases it increases the accuracy more than 10% in comparison with the negative pair selection method in that paper.

Balance of Rural and Urban Structures

Urbanization and regionalization are two different approaches when it comes to economical structures and development, infrastructure and mobility, quality of life and living, education, social cohesion and many other topics. At first glance, the structures associated with urbanization and regionalization seems to be contradicting. This paper discusses possibilities of transfer and cooperation between rural and urban structures. An empirical investigation contributed to reveal scenarios of supposable forms of exchange and cooperation of remote rural areas and big cities.

Sliding Mode Control Based on Backstepping Approach for an UAV Type-Quadrotor

In this paper; we are interested principally in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints in order to develop a new control scheme as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation. After, the use of Backstepping approach for the synthesis of tracking errors and Lyapunov functions, a sliding mode controller is developed in order to ensure Lyapunov stability, the handling of all system nonlinearities and desired tracking trajectories. Finally simulation results are also provided in order to illustrate the performances of the proposed controller.

Impact of Fair Share and its Configurations on Parallel Job Scheduling Algorithms

To provide a better understanding of fair share policies supported by current production schedulers and their impact on scheduling performance, A relative fair share policy supported in four well-known production job schedulers is evaluated in this study. The experimental results show that fair share indeed reduces heavy-demand users from dominating the system resources. However, the detailed per-user performance analysis show that some types of users may suffer unfairness under fair share, possibly due to priority mechanisms used by the current production schedulers. These users typically are not heavy-demands users but they have mixture of jobs that do not spread out.

Grid-based Supervised Clustering - GBSC

This paper presents a supervised clustering algorithm, namely Grid-Based Supervised Clustering (GBSC), which is able to identify clusters of any shapes and sizes without presuming any canonical form for data distribution. The GBSC needs no prespecified number of clusters, is insensitive to the order of the input data objects, and is capable of handling outliers. Built on the combination of grid-based clustering and density-based clustering, under the assistance of the downward closure property of density used in bottom-up subspace clustering, the GBSC can notably reduce its search space to avoid the memory confinement situation during its execution. On two-dimension synthetic datasets, the GBSC can identify clusters with different shapes and sizes correctly. The GBSC also outperforms other five supervised clustering algorithms when the experiments are performed on some UCI datasets.

Reduced Order Modeling of Natural Gas Transient Flow in Pipelines

A reduced order modeling approach for natural gas transient flow in pipelines is presented. The Euler equations are considered as the governing equations and solved numerically using the implicit Steger-Warming flux vector splitting method. Next, the linearized form of the equations is derived and the corresponding eigensystem is obtained. Then, a few dominant flow eigenmodes are used to construct an efficient reduced-order model. A well-known test case is presented to demonstrate the accuracy and the computational efficiency of the proposed method. The results obtained are in good agreement with those of the direct numerical method and field data. Moreover, it is shown that the present reduced-order model is more efficient than the conventional numerical techniques for transient flow analysis of natural gas in pipelines.

An Assessment of the Small Hydropower Potential of Sisakht Region of Yasuj

Energy generated by the force of water in hydropower can provide a more sustainable, non-polluting alternative to fossil fuels, along with other renewable sources of energy, such as wind, solar and tidal power, bio energy and geothermal energy. Small scale hydroelectricity in Iran is well suited for “off-grid" rural electricity applications, while other renewable energy sources, such as wind, solar and biomass, can be beneficially used as fuel for pumping groundwater for drinking and small scale irrigation in remote rural areas or small villages. Small Hydro Power plants in Iran have very low operating and maintenance costs because they consume no fossil or nuclear fuel and do not involve high temperature processes. The equipment is relatively simple to operate and maintain. Hydropower equipment can adjust rapidly to load changes. The extended equipment life provides significant economic advantages. Some hydroelectric plants installed 100 years ago still operate reliably. The Polkolo river is located on Karun basin at southwest of Iran. Situation and conditions of Polkolo river are evaluated for construction of small hydropower in this article. The topographical conditions and the existence of permanent water from springs provide the suitability to install hydroelectric power plants on the river Polkolo. The cascade plant consists of 9 power plants connected with each other and is having the total head as 1100m and discharge about 2.5cubic meter per second. The annual production of energy is 105.5 million kwh.

Modular Hybrid Robots for Safe Human-Robot Interaction

The paper considers a novel modular and intrinsically safe redundant robotic system with biologically inspired actuators (pneumatic artificial muscles and rubber bellows actuators). Similarly to the biological systems, the stiffness of the internal parallel modules, representing 2 DOF joints in the serial robotic chains, is controlled by co-activation of opposing redundant actuator groups in the null-space of the module Jacobian, without influencing the actual robot position. The decoupled position/stiffness control allows the realization of variable joint stiffness according to different force-displacement relationships. The variable joint stiffness, as well as limited pneumatic muscle/bellows force ability, ensures internal system safety that is crucial for development of human-friendly robots intended for human-robot collaboration. The initial experiments with the system prototype demonstrate the capabilities of independently, simultaneously controlling both joint (Cartesian) motion and joint stiffness. The paper also presents the possible industrial applications of snake-like robots built using the new modules.

WiMAX RoF Design for Cost Effective Access Points

An optimized design of E/O and O/E for access points of WiMAX RoF was carried out by evaluating RCE. The use of the DFB-LD, a low input-impedance driving, a low distortion PIN-PD, and a high gain EPHEMT amplifier is promising the cost-effective design. For the uplink RoF design, the use of EDFA and EP-HEMT amplifiers is necessity.

Research of Linear Camera Calibration Based on Planar Pattern

An important step in three-dimensional reconstruction and computer vision is camera calibration, whose objective is to estimate the intrinsic and extrinsic parameters of each camera. In this paper, two linear methods based on the different planes are given. In both methods, the general plane is used to replace the calibration object with very good precision. In the first method, after controlling the camera to undergo five times- translation movements and taking pictures of the orthogonal planes, a set of linear constraints of the camera intrinsic parameters is then derived by means of homography matrix. The second method is to get all camera parameters by taking only one picture of a given radius circle. experiments on simulated data and real images,indicate that our method is reasonable and is a good supplement to camera calibration.

Analysis of Reflectance Photoplethysmograph Sensors

Photoplethysmography is a simple measurement of the variation in blood volume in tissue. It detects the pulse signal of heart beat as well as the low frequency signal of vasoconstriction and vasodilation. The transmission type measurement is limited to only a few specific positions for example the index finger that have a short path length for light. The reflectance type measurement can be conveniently applied on most parts of the body surface. This study analyzed the factors that determine the quality of reflectance photoplethysmograph signal including the emitter-detector distance, wavelength, light intensity, and optical properties of skin tissue. Light emitting diodes (LEDs) with four different visible wavelengths were used as the light emitters. A phototransistor was used as the light detector. A micro translation stage adjusts the emitter-detector distance from 2 mm to 15 mm. The reflective photoplethysmograph signals were measured on different sites. The optimal emitter-detector distance was chosen to have a large dynamic range for low frequency drifting without signal saturation and a high perfusion index. Among these four wavelengths, a yellowish green (571nm) light with a proper emitter-detection distance of 2mm is the most suitable for obtaining a steady and reliable reflectance photoplethysmograph signal