Evolutionary Dynamics on Small-World Networks

We study how the outcome of evolutionary dynamics on graphs depends on a randomness on the graph structure. We gradually change the underlying graph from completely regular (e.g. a square lattice) to completely random. We find that the fixation probability increases as the randomness increases; nevertheless, the increase is not significant and thus the fixation probability could be estimated by the known formulas for underlying regular graphs.

Seismic Alert System based on Artificial Neural Networks

We board the problem of creating a seismic alert system, based upon artificial neural networks, trained by using the well-known back-propagation and genetic algorithms, in order to emit the alarm for the population located into a specific city, about an eminent earthquake greater than 4.5 Richter degrees, and avoiding disasters and human loses. In lieu of using the propagation wave, we employed the magnitude of the earthquake, to establish a correlation between the recorded magnitudes from a controlled area and the city, where we want to emit the alarm. To measure the accuracy of the posed method, we use a database provided by CIRES, which contains the records of 2500 quakes incoming from the State of Guerrero and Mexico City. Particularly, we performed the proposed method to generate an issue warning in Mexico City, employing the magnitudes recorded in the State of Guerrero.

Cross-Industry Innovations – Systematic Identification and Adaption

Due to today-s fierce competition, companies have to be proactive creators of the future by effectively developing innovations. Especially radical innovations allow high profit margins – but they also entail high risks. One possibility to realize radical innovations and reduce the risk of failure is cross-industry innovation (CII). CII brings together problems and solution ideas from different industries. However, there is a lack of systematic ways towards CII. Bridging this gap, the present paper provides a systematic approach towards planned CII. Starting with the analysis of potentials, the definition of promising search strategies is crucial. Subsequently, identified solution ideas need to be assessed. For the most promising ones, the adaption process has to be systematically planned – regarding the risk affinity of a company. The introduced method is explained on a project from the furniture industry.

A PSO-based End-Member Selection Method for Spectral Unmixing of Multispectral Satellite Images

An end-member selection method for spectral unmixing that is based on Particle Swarm Optimization (PSO) is developed in this paper. The algorithm uses the K-means clustering algorithm and a method of dynamic selection of end-members subsets to find the appropriate set of end-members for a given set of multispectral images. The proposed algorithm has been successfully applied to test image sets from various platforms such as LANDSAT 5 MSS and NOAA's AVHRR. The experimental results of the proposed algorithm are encouraging. The influence of different values of the algorithm control parameters on performance is studied. Furthermore, the performance of different versions of PSO is also investigated.

Vehicle Gearbox Fault Diagnosis Based On Cepstrum Analysis

Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs.This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves asthe internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order Cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of Cepstrum analysis in detection and diagnosis of the gear condition.

Development of Coronal Field and Solar Wind Components for MHD Interplanetary Simulations

The connection between solar activity and adverse phenomena in the Earth’s environment that can affect space and ground based technologies has spurred interest in Space Weather (SW) research. A great effort has been put on the development of suitable models that can provide advanced forecast of SW events. With the progress in computational technology, it is becoming possible to develop operational large scale physics based models which can incorporate the most important physical processes and domains of the Sun-Earth system. In order to enhance our SW prediction capabilities we are developing advanced numerical tools. With operational requirements in mind, our goal is to develop a modular simulation framework of propagation of the disturbances from the Sun through interplanetary space to the Earth. Here, we report and discuss on the development of coronal field and solar wind components for a large scale MHD code. The model for these components is based on a potential field source surface model and an empirical Wang-Sheeley-Arge solar wind relation. 

Investigation of Self-Similarity Solution for Wake Flow of a Cylinder

The data measurement of mean velocity has been taken for the wake of single circular cylinder with three different diameters for two different velocities. The effects of change in diameter and in velocity are studied in self-similar coordinate system. The spatial variations of velocity defect and that of the half-width have been investigated. The results are compared with those published by H.Schlichting. In the normalized coordinates, it is also observed that all cases except for the first station are self-similar. By attention to self-similarity profiles of mean velocity, it is observed for all the cases at the each station curves tend to zero at a same point.

Parametric Modeling Approach for Call Holding Times for IP based Public Safety Networks via EM Algorithm

This paper presents parametric probability density models for call holding times (CHTs) into emergency call center based on the actual data collected for over a week in the public Emergency Information Network (EIN) in Mongolia. When the set of chosen candidates of Gamma distribution family is fitted to the call holding time data, it is observed that the whole area in the CHT empirical histogram is underestimated due to spikes of higher probability and long tails of lower probability in the histogram. Therefore, we provide the Gaussian parametric model of a mixture of lognormal distributions with explicit analytical expressions for the modeling of CHTs of PSNs. Finally, we show that the CHTs for PSNs are fitted reasonably by a mixture of lognormal distributions via the simulation of expectation maximization algorithm. This result is significant as it expresses a useful mathematical tool in an explicit manner of a mixture of lognormal distributions.

Estimation of Production Function in Fishery on the Coasts of Caspian Sea

This research was conducted for the first time at the southeastern coasts of the Caspian Sea in order to evaluate the performance of osteichthyes cooperatives through production (catch) function. Using one of the indirect valuation methods in this research, contributory factors in catch were identified and were inserted into the function as independent variables. In order to carry out this research, the performance of 25 Osteichthyes catching cooperatives in the utilization year of 2009 which were involved in fishing in Miankale wildlife refuge region. The contributory factors in catch were divided into groups of economic, ecological and biological factors. In the mentioned function, catch rate of the cooperative were inserted into as the dependant variable and fourteen partial variables in terms of nine general variables as independent variables. Finally, after function estimation, seven variables were rendered significant at 99 percent reliably level. The results of the function estimation indicated that human resource (fisherman quantity) had the greatest positive effect on catch rate with an influence coefficient of 1.7 while weather conditions had the greatest negative effect on the catch rate of cooperatives with an influence coefficient of -2.07. Moreover, factors like member's share, experience and fisherman training and fishing effort played the main roles in the catch rate of cooperative with influence coefficients of 0.81, 0.5 and 0.21, respectively.

Elliptical Features Extraction Using Eigen Values of Covariance Matrices, Hough Transform and Raster Scan Algorithms

In this paper, we introduce a new method for elliptical object identification. The proposed method adopts a hybrid scheme which consists of Eigen values of covariance matrices, Circular Hough transform and Bresenham-s raster scan algorithms. In this approach we use the fact that the large Eigen values and small Eigen values of covariance matrices are associated with the major and minor axial lengths of the ellipse. The centre location of the ellipse can be identified using circular Hough transform (CHT). Sparse matrix technique is used to perform CHT. Since sparse matrices squeeze zero elements and contain a small number of nonzero elements they provide an advantage of matrix storage space and computational time. Neighborhood suppression scheme is used to find the valid Hough peaks. The accurate position of circumference pixels is identified using raster scan algorithm which uses the geometrical symmetry property. This method does not require the evaluation of tangents or curvature of edge contours, which are generally very sensitive to noise working conditions. The proposed method has the advantages of small storage, high speed and accuracy in identifying the feature. The new method has been tested on both synthetic and real images. Several experiments have been conducted on various images with considerable background noise to reveal the efficacy and robustness. Experimental results about the accuracy of the proposed method, comparisons with Hough transform and its variants and other tangential based methods are reported.

A Novel Approach for Coin Identification using Eigenvalues of Covariance Matrix, Hough Transform and Raster Scan Algorithms

In this paper we present a new method for coin identification. The proposed method adopts a hybrid scheme using Eigenvalues of covariance matrix, Circular Hough Transform (CHT) and Bresenham-s circle algorithm. The statistical and geometrical properties of the small and large Eigenvalues of the covariance matrix of a set of edge pixels over a connected region of support are explored for the purpose of circular object detection. Sparse matrix technique is used to perform CHT. Since sparse matrices squeeze zero elements and contain only a small number of non-zero elements, they provide an advantage of matrix storage space and computational time. Neighborhood suppression scheme is used to find the valid Hough peaks. The accurate position of the circumference pixels is identified using Raster scan algorithm which uses geometrical symmetry property. After finding circular objects, the proposed method uses the texture on the surface of the coins called texton, which are unique properties of coins, refers to the fundamental micro structure in generic natural images. This method has been tested on several real world images including coin and non-coin images. The performance is also evaluated based on the noise withstanding capability.

Performance Evaluation of Neural Network Prediction for Data Prefetching in Embedded Applications

Embedded systems need to respect stringent real time constraints. Various hardware components included in such systems such as cache memories exhibit variability and therefore affect execution time. Indeed, a cache memory access from an embedded microprocessor might result in a cache hit where the data is available or a cache miss and the data need to be fetched with an additional delay from an external memory. It is therefore highly desirable to predict future memory accesses during execution in order to appropriately prefetch data without incurring delays. In this paper, we evaluate the potential of several artificial neural networks for the prediction of instruction memory addresses. Neural network have the potential to tackle the nonlinear behavior observed in memory accesses during program execution and their demonstrated numerous hardware implementation emphasize this choice over traditional forecasting techniques for their inclusion in embedded systems. However, embedded applications execute millions of instructions and therefore millions of addresses to be predicted. This very challenging problem of neural network based prediction of large time series is approached in this paper by evaluating various neural network architectures based on the recurrent neural network paradigm with pre-processing based on the Self Organizing Map (SOM) classification technique.

Control of Thermal Flow in Machine Tools Using Shape Memory Alloys

In this paper the authors propose and verify an approach to control heat flow in machine tool components. Thermal deformations are a main aspect that affects the accuracy of machining. Due to goals of energy efficiency, thermal basic loads should be reduced. This leads to inhomogeneous and time variant temperature profiles. To counteract these negative consequences, material with high melting enthalpy is used as a method for thermal stabilization. The increased thermal capacity slows down the transient thermal behavior. To account for the delayed thermal equilibrium, a control mechanism for thermal flow is introduced. By varying a gap in a heat flow path the thermal resistance of an assembly can be controlled. This mechanism is evaluated in two experimental setups. First to validate the ability to control the thermal resistance and second to prove the possibility of a self-sufficient option based on the selfsensing abilities of thermal shape memory alloys.

Particular Qualities of Education in Kazakh Society

Most of the academics connect a theory of multiculturalism with globalization and limit it by last decades of 20th century. However, Kazakh society encountered with this problem when the Soviet-s rule emerged. As a result of repression, the Second World War, development of virgin lands representatives of more than 100 nationalities lives in Kazakhstan. Communist ideology propagandized internationalism, which would defined principles of multicultural community but a common ideology demands a single culture. As a result multicultural society in the USSR developed under control of Russian culture. Education in the USSR was conducted in two departments: autochthonous and Russian. Autochthonous education narrowed student capabilities. Also because of soviet ideology science was conducted in Russian Universities provided education in Russian and all science literature were in Russian. Exceptions were humanitarian fields where Kazakh departments were admitted. Naturally non-Kazakhs studied in Russian departments, moreover Kazakhs preferred to study in Russian as most do nowadays preferring English. As a result Kazakh society consisted of Kazakhs, Kazakhs who recognized Russian as a mother tongue and other nationalities who were also Russian speakers. This aspect continues to distinguish particular qualities of multicultural community in Kazakhstan.

A Novel Method for Areal Surface Roughness Measurement

An area-integrating method that uses the technique of total integrated light scatter for evaluating the root mean square height of the surface Sq has been presented in the paper. It is based on the measurement of the scatter power using a flat photodiode integrator rather than an optical sphere or a hemisphere. By this means, one can obtain much less expensive and smaller instruments than traditional ones. Thanks to this, they could find their application for surface control purposes, particularly in small and medium size enterprises. A description of the functioning of the measuring unit as well as the impact caused by different factors on its properties is presented first. Next, results of measurements of the Sq values performed for optical, silicon and metal samples have been shown. It has been also proven that they are in a good agreement with the results obtained using the Ulbricht sphere instrument.

Designing a Rescue System for Earthquake-Stricken Area with the Aim of Facilitation and Accelerating Accessibilities (Case Study: City of Tehran)

Natural disasters, including earthquake, kill many people around the world every year. Society rescue actions, which start after the earthquake and are called LAST in abbreviation, include locating, access, stabilization and transportation. In the present article, we have studied the process of local accessibility to the injured and transporting them to health care centers. With regard the heavy traffic load due to earthquake, the destruction of connecting roads and bridges and the heavy debris in alleys and street, which put the lives of the injured and the people buried under the debris in danger, accelerating the rescue actions and facilitating the accessibilities are of great importance, obviously. Tehran, the capital of Iran, is among the crowded cities in the world and is the center of extensive economic, political, cultural and social activities. Tehran has a population of about 9.5 millions and because of the immigration of people from the surrounding cities. Furthermore, considering the fact that Tehran is located on two important and large faults, a 6 Richter magnitude earthquake in this city could lead to the greatest catastrophe during the entire human history. The present study is a kind of review and a major part of the required information for it, has been obtained from libraries all of the rescue vehicles around the world, including rescue helicopters, ambulances, fire fighting vehicles and rescue boats, and their applied technology, and also the robots specifically designed for the rescue system and the advantages and disadvantages of them, have been investigated. The studies show that there is a significant relationship between the rescue team-s arrival time at the incident zone and the number of saved people; so that, if the duration of burial under debris 30 minutes, the probability of survival is %99.3, after a day is %81, after 2days is %19 and after 5days is %7.4. The exiting transport systems all have some defects. If these defects are removed, more people could be saved each hour and the preparedness against natural disasters is increased. In this study, transport system has been designed for the rescue team and the injured; which could carry the rescue team to the incident zone and the injured to the health care centers. In addition, this system is able to fly in the air and move on the earth as well; so that the destruction of roads and the heavy traffic load could not prevent the rescue team from arriving early at the incident zone. The system also has the equipment required firebird for debris removing, optimum transport of the injured and first aid.

Technical Trading Rules in Emerging Stock Markets

Literature reveals that many investors rely on technical trading rules when making investment decisions. If stock markets are efficient, one cannot achieve superior results by using these trading rules. However, if market inefficiencies are present, profitable opportunities may arise. The aim of this study is to investigate the effectiveness of technical trading rules in 34 emerging stock markets. The performance of the rules is evaluated by utilizing White-s Reality Check and the Superior Predictive Ability test of Hansen, along with an adjustment for transaction costs. These tests are able to evaluate whether the best model performs better than a buy-and-hold benchmark. Further, they provide an answer to data snooping problems, which is essential to obtain unbiased outcomes. Based on our results we conclude that technical trading rules are not able to outperform a naïve buy-and-hold benchmark on a consistent basis. However, we do find significant trading rule profits in 4 of the 34 investigated markets. We also present evidence that technical analysis is more profitable in crisis situations. Nevertheless, this result is relatively weak.

Sweetpotato Organic Cultivation with Wood Vinegar, Entomopathogenic Nematode and Fermented Organic Substance from Plants

The effect of wood vinegar, entomopathogenic nematodes ((Steinernema thailandensis n. sp.) and fermented organic substances from four plants such as: Derris elliptica Roxb, Stemona tuberosa Lour, Tinospora crispa Mier and Azadirachta indica J. were tested on the five varieties of sweetpotato with potential for bioethanol production ie. Taiwan, China, PROC No.65-16, Phichit 166-5, and Phichit 129-6. The experimental plots were located at Faculty of Agriculture, Natural Resources and Environment, Naresuan University, Phitsanulok, Thailand. The aim of this study was to compare the efficiency of the five treatments for growth, yield and insect infestation on the five varieties of sweetpotato. Treatment with entomopathogenic nematodes gave the highest average weight of sweetpotato tubers (1.3 kg/tuber), followed by wood vinegar, fermented organic substances and mixed treatment with yields of 0.88, 0.46 and 0.43 kg/tuber, respectively. Also the entomopathogenic nematode treatment gave significantly higher average width and length of sweet potato (9.82 cm and 9.45 cm, respectively). Additionally, the entomopathogenic nematode provided the best control of insect infestation on sweetpotato leaves and tubers. Comparison among the varieties of sweetpotato, PROC NO.65-16 showed the highest weight and length. However, Phichit 129-6 gave significantly higher weight of 0.94 kg/tuber. Lastly, the lowest sweet potato weevil infestation on leaves and tubers occurred on Taiwan and Phichit 129-6.

Modern Vibration Signal Processing Techniques for Vehicle Gearbox Fault Diagnosis

This paper presents modern vibration signalprocessing techniques for vehicle gearbox fault diagnosis, via the wavelet analysis and the Squared Envelope (SE) technique. The wavelet analysis is regarded as a powerful tool for the detection of sudden changes in non-stationary signals. The Squared Envelope (SE) technique has been extensively used for rolling bearing diagnostics. In the present work a scheme of using the Squared Envelope technique for early detection of gear tooth pit. The pitting defect is manufactured on the tooth side of a fifth speed gear on the intermediate shaft of a vehicle gearbox. The objective is to supplement the current techniques of gearbox fault diagnosis based on using the raw vibration and ordered signals. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers introduce the load on the flanges of output joint shafts. The gearbox used for experimental measurements is the type most commonly used in modern small to mid-sized passenger cars with transversely mounted powertrain and front wheel drive; a five-speed gearbox with final drive gear and front wheel differential. The results show that the approaches methods are effective for detecting and diagnosing localized gear faults in early stage under different operation conditions, and are more sensitive and robust than current gear diagnostic techniques.

Baseline Performance of Notebook Computer under Various Environmental and Usage Conditions for Prognostics

A study was conducted to formally characterize notebook computer performance under various environmental and usage conditions. Software was developed to collect data from the operating system of the computer. An experiment was conducted to evaluate the performance parameters- variations, trends, and correlations, as well as the extreme value they can attain in various usage and environmental conditions. An automated software script was written to simulate user activity. The variability of each performance parameter was addressed by establishing the empirical relationship between performance parameters. These equations were presented as baseline estimates for performance parameters, which can be used to detect system deviations from normal operation and for prognostic assessment. The effect of environmental factors, including different power sources, ambient temperatures, humidity, and usage, on performance parameters of notebooks was studied.