Object Localization in Medical Images Using Genetic Algorithms

We present a genetic algorithm application to the problem of object registration (i.e., object detection, localization and recognition) in a class of medical images containing various types of blood cells. The genetic algorithm approach taken here is seen to be most appropriate for this type of image, due to the characteristics of the objects. Successful cell registration results on real life microscope images of blood cells show the potential of the proposed approach.

Design and Development of Ferroelectric Material for Microstrip Patch Array Antenna

This paper presents the utilizing of ferroelectric material on antenna application. There are two different ferroelectric had been used on the proposed antennas which include of Barium Strontium Titanate (BST) and Bismuth Titanate (BiT), suitable for Access Points operating in the WLAN IEEE 802.11 b/g and WiMAX IEEE 802.16 within the range of 2.3 GHz to 2.5 GHz application. BST, which had been tested to own a dielectric constant of εr = 15 while BiT has a dielectric constant that higher than BST which is εr = 21 and both materials are in rectangular shaped. The influence of various parameters on antenna characteristics were investigated extensively using commercial electromagnetic simulations software by Communication Simulation Technology (CST). From theoretical analysis and simulation results, it was demonstrated that ferroelectric material used have not only improved the directive emission but also enhanced the radiation efficiency.

Effect of Genotype, Explant Type and Growth Regulators on The Accumulation of Flavonoides of (Silybum marianum L.) in In vitro Culture

The extract of milk thistle contains a mix of flavonolignans termed silymarine.. In order to analysis influence of growth regulators, genotype, explant and subculture on the accumulation of flavonolignans, a study was carried out by using two genotype (Budakalszi and Noor abad moghan cultivars), cotyledon and hypocotyle explants, solid media of MS supplemented by different combinations of two growth regulators; Kinetin (0.1, 1 mg/l) and 2,4-D (1, 2 mg/l). Seeds of the plant were germinated in MS media whitout growth regulators in growth chamber at 26°C and darkness condition. In order to callus induction, the culture media was supplemented whit different concentrations of 2,4-D and kinetin. Calli obtained from explants were sub-cultured four times into the fresh media of the first experiment. flavonoides was extracted from calli in four subcultures. The flavonoid components were determined by high- performance liquid choromatography (HPLC) and separated into Taxifolin, Silydianin+Silychristin, Silybin A+B and Isosilybin A+B. Results showed that with increasing callus age, increased accumulation of silybin A+B, but reduced Isosilybin A+B content. Highest accumulation of Taxifolin was observed at first calli. Calli produced from cotyledon explant of Budakalszi cultivar were superior for Silybin A+B, where calli from hypocotyl explant produced higher amount of Taxifolin and Silydianin+Silychristin. The best cultivar for Silymarin production in this study was Budakalszi cultivar. High amount of SBN A+B and TXF were obtained from hypocotil explant.

A Fuzzy Approach for Delay Proportion Differentiated Service

There are two paradigms proposed to provide QoS for Internet applications: Integrated service (IntServ) and Differentiated service (DiffServ).Intserv is not appropriate for large network like Internet. Because is very complex. Therefore, to reduce the complexity of QoS management, DiffServ was introduced to provide QoS within a domain using aggregation of flow and per- class service. In theses networks QoS between classes is constant and it allows low priority traffic to be effected from high priority traffic, which is not suitable. In this paper, we proposed a fuzzy controller, which reduced the effect of low priority class on higher priority ones. Our simulations shows that, our approach reduces the latency dependency of low priority class on higher priority ones, in an effective manner.

Client Server System for e-Services Access Using Mobile Communications Networks

The client server systems using mobile communications networks for data transmission became very attractive for many economic agents, in the purpose of promoting and offering electronic services to their clients. E-services are suitable for business developing and financial benefits increasing. The products or services can be efficiently delivered to a large number of clients, using mobile Internet access technologies. The clients can have access to e-services, anywhere and anytime, with the support of 3G, GPRS, WLAN, etc., channels bandwidth, data services and protocols. Based on the mobile communications networks evolution and development, a convergence of technological and financial interests of mobile operators, software developers, mobile terminals producers and e-content providers is established. These will lead to a high level of integration of IT&C resources and will facilitate the value added services delivery through the mobile communications networks. In this paper it is presented a client server system, for e-services access, with Smartphones and PDA-s mobile software applications, installed on Symbian and Windows Mobile operating systems.

Leisure and Perceived Wellness of Nursing Students: A Canonical Correlation Analysis

The purpose of this study was to explore the correlation between leisure participation and perceived wellness, with the students of a nursing college in southern Taiwan as the subjects. One thousand six hundred and ninety-six (1,696) surveys were sent, and 1,408 surveys were received for an 83.02% valid response rate. Using canonical correlation analysis to analyze the data, the results showed that the linear combination of the two sets of variable produces five significant canonical variates. Out of the five canonical variates, only the first has sufficient explanatory power. The canonical correlation coefficient of first canonical variate is 0.660. This indicated that leisure participation and perceived wellness are significantly correlated.

Impulse Noise Reduction in Brain Magnetic Resonance Imaging Using Fuzzy Filters

Noise contamination in a magnetic resonance (MR) image could occur during acquisition, storage, and transmission in which effective filtering is required to avoid repeating the MR procedure. In this paper, an iterative asymmetrical triangle fuzzy filter with moving average center (ATMAVi filter) is used to reduce different levels of salt and pepper noise in a brain MR image. Besides visual inspection on filtered images, the mean squared error (MSE) is used as an objective measurement. When compared with the median filter, simulation results indicate that the ATMAVi filter is effective especially for filtering a higher level noise (such as noise density = 0.45) using a smaller window size (such as 3x3) when operated iteratively or using a larger window size (such as 5x5) when operated non-iteratively.

Power-Efficient AND-EXOR-INV Based Realization of Achilles' heel Logic Functions

This paper deals with a power-conscious ANDEXOR- Inverter type logic implementation for a complex class of Boolean functions, namely Achilles- heel functions. Different variants of the above function class have been considered viz. positive, negative and pure horn for analysis and simulation purposes. The proposed realization is compared with the decomposed implementation corresponding to an existing standard AND-EXOR logic minimizer; both result in Boolean networks with good testability attribute. It could be noted that an AND-OR-EXOR type logic network does not exist for the positive phase of this unique class of logic function. Experimental results report significant savings in all the power consumption components for designs based on standard cells pertaining to a 130nm UMC CMOS process The simulations have been extended to validate the savings across all three library corners (typical, best and worst case specifications).

Frame and Burst Acquisition in TDMA Satellite Communication Networks with Transponder Hopping

The paper presents frame and burst acquisition in a satellite communication network based on time division multiple access (TDMA) in which the transmissions may be carried on different transponders. A unique word pattern is used for the acquisition process. The search for the frame is aided by soft-decision of QPSK modulated signals in an additive white Gaussian channel. Results show that when the false alarm rate is low the probability of detection is also low, and the acquisition time is long. Conversely when the false alarm rate is high, the probability of detection is also high and the acquisition time is short. Thus the system operators can trade high false alarm rates for high detection probabilities and shorter acquisition times.

The Effects of Detector Spacing on Travel Time Prediction on Freeways

Loop detectors report traffic characteristics in real time. They are at the core of traffic control process. Intuitively, one would expect that as density of detection increases, so would the quality of estimates derived from detector data. However, as detector deployment increases, the associated operating and maintenance cost increases. Thus, traffic agencies often need to decide where to add new detectors and which detectors should continue receiving maintenance, given their resource constraints. This paper evaluates the effect of detector spacing on freeway travel time estimation. A freeway section (Interstate-15) in Salt Lake City metropolitan region is examined. The research reveals that travel time accuracy does not necessarily deteriorate with increased detector spacing. Rather, the actual location of detectors has far greater influence on the quality of travel time estimates. The study presents an innovative computational approach that delivers optimal detector locations through a process that relies on Genetic Algorithm formulation.

Queen-bee Algorithm for Energy Efficient Clusters in Wireless Sensor Networks

Wireless sensor networks include small nodes which have sensing ability; calculation and connection extend themselves everywhere soon. Such networks have source limitation on connection, calculation and energy consumption. So, since the nodes have limited energy in sensor networks, the optimized energy consumption in these networks is of more importance and has created many challenges. The previous works have shown that by organizing the network nodes in a number of clusters, the energy consumption could be reduced considerably. So the lifetime of the network would be increased. In this paper, we used the Queen-bee algorithm to create energy efficient clusters in wireless sensor networks. The Queen-bee (QB) is similar to nature in that the queen-bee plays a major role in reproduction process. The QB is simulated with J-sim simulator. The results of the simulation showed that the clustering by the QB algorithm decreases the energy consumption with regard to the other existing algorithms and increases the lifetime of the network.

Ready or Not? Markers of Starting Romantic Intimacy at Emerging Adulthood: The Turkish Experience

Emerging adulthood, the new period which is especially prevalent in the developed or industrialized countries during ages 18 to 29, is a new conceptualization proposed by Arnett. Intimacy is a superordinate concept which includes intimate interaction and intimate relationship. This study includes two proceses which are scale development and conduction of gender differences about markers of starting romantic intimacy among Turkish emerging adults. In first process, Markers of Starting Romantic Intimacy Scale, with 17 items and 5 factors, was developed using by 220 participants. In the second step, the scale was administered to 318 Turkish male and female emerging adults between ages 22 and 25. Results show that there is no significant difference between gender and total score of the scale. With respect to gender, there are significant differences between gender and in four subscales which are self perception, affective and cognitive intimacy, self knowledge and romantic verbalizations. Moreover, there is no significant relationship between gender and behavioral intimacy subscale.

The Role of Online Social Networks in Social Movements: Social Polarization and Violations against Social Unity and Privacy of Individuals in Turkey

As a matter of the fact that online social networks like Twitter, Facebook and MySpace have experienced an extensive growth in recent years. Social media offers individuals with a tool for communicating and interacting with one another. These social networks enable people to stay in touch with other people and express themselves. This process makes the users of online social networks active creators of content rather than being only consumers of traditional media. That’s why millions of people show strong desire to learn the methods and tools of digital content production and necessary communication skills. However, the booming interest in communication and interaction through online social networks and high level of eagerness to invent and implement the ways to participate in content production raise some privacy and security concerns. This presentation aims to open the assumed revolutionary, democratic and liberating nature of the online social media up for discussion by reviewing some recent political developments in Turkey. Firstly, the role of Internet and online social networks in mobilizing collective movements through social interactions and communications will be questioned. Secondly, some cases from Gezi and Okmeydanı Protests and also December 17-25 period will be presented in order to illustrate misinformation and manipulation in social media and violation of individual privacy through online social networks in order to damage social unity and stability contradictory to democratic nature of online social networking.

Modeling and Optimization of Process Parameters in PMEDM by Genetic Algorithm

This paper addresses modeling and optimization of process parameters in powder mixed electrical discharge machining (PMEDM). The process output characteristics include metal removal rate (MRR) and electrode wear rate (EWR). Grain size of Aluminum powder (S), concentration of the powder (C), discharge current (I) pulse on time (T) are chosen as control variables to study the process performance. The experimental results are used to develop the regression models based on second order polynomial equations for the different process characteristics. Then, a genetic algorithm (GA) has been employed to determine optimal process parameters for any desired output values of machining characteristics.

Accurate Control of a Pneumatic System using an Innovative Fuzzy Gain-Scheduling Pattern

Due to their high power-to-weight ratio and low cost, pneumatic actuators are attractive for robotics and automation applications; however, achieving fast and accurate control of their position have been known as a complex control problem. A methodology for obtaining high position accuracy with a linear pneumatic actuator is presented. During experimentation with a number of PID classical control approaches over many operations of the pneumatic system, the need for frequent manual re-tuning of the controller could not be eliminated. The reason for this problem is thermal and energy losses inside the cylinder body due to the complex friction forces developed by the piston displacements. Although PD controllers performed very well over short periods, it was necessary in our research project to introduce some form of automatic gain-scheduling to achieve good long-term performance. We chose a fuzzy logic system to do this, which proved to be an easily designed and robust approach. Since the PD approach showed very good behaviour in terms of position accuracy and settling time, it was incorporated into a modified form of the 1st order Tagaki- Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler uses an input variable which automatically changes the PD gain values of the controller according to the frequency of repeated system operations. Performance of the new controller was significantly improved and the need for manual re-tuning was eliminated without a decrease in performance. The performance of the controller operating with the above method is going to be tested through a high-speed web network (GRID) for research purposes.

Potential cIBR-Conjugated PLGA Nanoparticles for Selective Targeting to Leukemic Cells

The expression of LFA-1 diverges from the physiological condition, thus active targeting carrier can provide the benefits from difference into LFA-1 expression in various conditions. Here, the selectivity of cIBR-conjugated nanoparticles (cIBR-NPs), in terms of uptake, was investigated using PBMCs, Mixed PBMCMolt- 3 cells and Molt-3 cells. The expressions of LFA-1 on Molt-3 cells, from flow cytometry and Western blot, possessed the highest level whereas PBMCs showed the lowest level. The kinetic uptake profiles of cIBR-NPs were obtained by flow cytometry, which the degree of cellular uptake presented a similar trend with the level of LFA-1 indicating the influence of LFA-1 expression on the cellular uptake of cIBR-NPs. The conformation of LFA-1 had a slight effect on the cellular uptake of cIBR-NPs. Overall we demonstrated that cIBR-NPs enhanced cellular uptake and improved the selectivity of drug carriers to LFA-1 on the leukemia cells, which related with the order of LFA-1 expression.

Embedding a Large Amount of Information Using High Secure Neural Based Steganography Algorithm

In this paper, we construct and implement a new Steganography algorithm based on learning system to hide a large amount of information into color BMP image. We have used adaptive image filtering and adaptive non-uniform image segmentation with bits replacement on the appropriate pixels. These pixels are selected randomly rather than sequentially by using new concept defined by main cases with sub cases for each byte in one pixel. According to the steps of design, we have been concluded 16 main cases with their sub cases that covere all aspects of the input information into color bitmap image. High security layers have been proposed through four layers of security to make it difficult to break the encryption of the input information and confuse steganalysis too. Learning system has been introduces at the fourth layer of security through neural network. This layer is used to increase the difficulties of the statistical attacks. Our results against statistical and visual attacks are discussed before and after using the learning system and we make comparison with the previous Steganography algorithm. We show that our algorithm can embed efficiently a large amount of information that has been reached to 75% of the image size (replace 18 bits for each pixel as a maximum) with high quality of the output.

Using Ferry Access Points to Improve the Performance of Message Ferrying in Delay-Tolerant Networks

Delay-Tolerant Networks (DTNs) are sparse, wireless networks where disconnections are common due to host mobility and low node density. The Message Ferrying (MF) scheme is a mobilityassisted paradigm to improve connectivity in DTN-like networks. A ferry or message ferry is a special node in the network which has a per-determined route in the deployed area and relays messages between mobile hosts (MHs) which are intermittently connected. Increased contact opportunities among mobile hosts and the ferry improve the performance of the network, both in terms of message delivery ratio and average end-end delay. However, due to the inherent mobility of mobile hosts and pre-determined periodicity of the message ferry, mobile hosts may often -miss- contact opportunities with a ferry. In this paper, we propose the combination of stationary ferry access points (FAPs) with MF routing to increase contact opportunities between mobile hosts and the MF and consequently improve the performance of the DTN. We also propose several placement models for deploying FAPs on MF routes. We evaluate the performance of the FAP placement models through comprehensive simulation. Our findings show that FAPs do improve the performance of MF-assisted DTNs and symmetric placement of FAPs outperforms other placement strategies.

Biometric Technology in Securing the Internet Using Large Neural Network Technology

The article examines the methods of protection of citizens' personal data on the Internet using biometric identity authentication technology. It`s celebrated their potential danger due to the threat of loss of base biometric templates. To eliminate the threat of compromised biometric templates is proposed to use neural networks large and extra-large sizes, which will on the one hand securely (Highly reliable) to authenticate a person by his biometrics, and on the other hand make biometrics a person is not available for observation and understanding. This article also describes in detail the transformation of personal biometric data access code. It`s formed the requirements for biometrics converter code for his work with the images of "Insider," "Stranger", all the "Strangers". It`s analyzed the effect of the dimension of neural networks on the quality of converters mystery of biometrics in access code.

Computational Analysis of the MembraneTargeting Domains of Plant-specific PRAF Proteins

The PRAF family of proteins is a plant specific family of proteins with distinct domain architecture and various unique sequence/structure traits. We have carried out an extensive search of the Arabidopsis genome using an automated pipeline and manual methods to verify previously known and identify unknown instances of PRAF proteins, characterize their sequence and build 3D structures of their individual domains. Integrating the sequence, structure and whatever little known experimental details for each of these proteins and their domains, we present a comprehensive characterization of the different domains in these proteins and their variant properties.