Patterned Growth of ZnO Nanowire Arrays on Zinc Foil by Thermal Oxidation

A simple approach is demonstrated for growing large scale, nearly vertically aligned ZnO nanowire arrays by thermal oxidation method. To reveal effect of temperature on growth and physical properties of the ZnO nanowires, gold coated zinc substrates were annealed at 300 °C and 400 °C for 4 hours duration in air. Xray diffraction patterns of annealed samples indicated a set of well defined diffraction peaks, indexed to the wurtzite hexagonal phase of ZnO. The scanning electron microscopy studies show formation of ZnO nanowires having length of several microns and average of diameter less than 500 nm. It is found that the areal density of wires is relatively higher, when the annealing is carried out at higher temperature i.e. at 400°C. From the field emission studies, the values of the turn-on and threshold field, required to draw emission current density of 10 μA/cm2 and 100 μA/cm2 are observed to be 1.2 V/μm and 1.7 V/μm for the samples annealed at 300 °C and 2.9 V/μm and 3.7 V/μm for that annealed at 400 °C, respectively. The field emission current stability, investigated over duration of more than 2 hours at the preset value of 1 μA, is found to be fairly good in both cases. The simplicity of the synthesis route coupled with the promising field emission properties offer unprecedented advantage for the use of ZnO field emitters for high current density applications.

A Numerical Strategy to Design Maneuverable Micro-Biomedical Swimming Robots Based on Biomimetic Flagellar Propulsion

Medical applications are among the most impactful areas of microrobotics. The ultimate goal of medical microrobots is to reach currently inaccessible areas of the human body and carry out a host of complex operations such as minimally invasive surgery (MIS), highly localized drug delivery, and screening for diseases at their very early stages. Miniature, safe and efficient propulsion systems hold the key to maturing this technology but they pose significant challenges. A new type of propulsion developed recently, uses multi-flagella architecture inspired by the motility mechanism of prokaryotic microorganisms. There is a lack of efficient methods for designing this type of propulsion system. The goal of this paper is to overcome the lack and this way, a numerical strategy is proposed to design multi-flagella propulsion systems. The strategy is based on the implementation of the regularized stokeslet and rotlet theory, RFT theory and new approach of “local corrected velocity". The effects of shape parameters and angular velocities of each flagellum on overall flow field and on the robot net forces and moments are considered. Then a multi-layer perceptron artificial neural network is designed and employed to adjust the angular velocities of the motors for propulsion control. The proposed method applied successfully on a sample configuration and useful demonstrative results is obtained.

SURF Based Image Matching from Different Angle of Viewpoints using Rectification and Simplified Orientation Correction

Speeded-Up Robust Feature (SURF) is commonly used for feature matching in stereovision because of their robustness towards scale changes and rotational changes. However, SURF feature cannot cope with large viewpoint changes or skew distortion. This paper introduces a method which can help to improve the wide baseline-s matching performance in term of accuracy by rectifying the image using two vanishing points. Simplified orientation correction was used to remove the false matching..

On Identity Disclosure Risk Measurement for Shared Microdata

Probability-based identity disclosure risk measurement may give the same overall risk for different anonymization strategy of the same dataset. Some entities in the anonymous dataset may have higher identification risks than the others. Individuals are more concerned about higher risks than the average and are more interested to know if they have a possibility of being under higher risk. A notation of overall risk in the above measurement method doesn-t indicate whether some of the involved entities have higher identity disclosure risk than the others. In this paper, we have introduced an identity disclosure risk measurement method that not only implies overall risk, but also indicates whether some of the members have higher risk than the others. The proposed method quantifies the overall risk based on the individual risk values, the percentage of the records that have a risk value higher than the average and how larger the higher risk values are compared to the average. We have analyzed the disclosure risks for different disclosure control techniques applied to original microdata and present the results.

A new Heuristic Algorithm for the Dynamic Facility Layout Problem with Budget Constraint

In this research, we have developed a new efficient heuristic algorithm for the dynamic facility layout problem with budget constraint (DFLPB). This heuristic algorithm combines two mathematical programming methods such as discrete event simulation and linear integer programming (IP) to obtain a near optimum solution. In the proposed algorithm, the non-linear model of the DFLP has been changed to a pure integer programming (PIP) model. Then, the optimal solution of the PIP model has been used in a simulation model that has been designed in a similar manner as the DFLP for determining the probability of assigning a facility to a location. After a sufficient number of runs, the simulation model obtains near optimum solutions. Finally, to verify the performance of the algorithm, several test problems have been solved. The results show that the proposed algorithm is more efficient in terms of speed and accuracy than other heuristic algorithms presented in previous works found in the literature.

Program Camouflage: A Systematic Instruction Hiding Method for Protecting Secrets

This paper proposes an easy-to-use instruction hiding method to protect software from malicious reverse engineering attacks. Given a source program (original) to be protected, the proposed method (1) takes its modified version (fake) as an input, (2) differences in assembly code instructions between original and fake are analyzed, and, (3) self-modification routines are introduced so that fake instructions become correct (i.e., original instructions) before they are executed and that they go back to fake ones after they are executed. The proposed method can add a certain amount of security to a program since the fake instructions in the resultant program confuse attackers and it requires significant effort to discover and remove all the fake instructions and self-modification routines. Also, this method is easy to use (with little effort) because all a user (who uses the proposed method) has to do is to prepare a fake source code by modifying the original source code.

A Two-Channel Secure Communication Using Fractional Chaotic Systems

In this paper, a two-channel secure communication using fractional chaotic systems is presented. Conditions for chaos synchronization have been investigated theoretically by using Laplace transform. To illustrate the effectiveness of the proposed scheme, a numerical example is presented. The keys, key space, key selection rules and sensitivity to keys are discussed in detail. Results show that the original plaintexts have been well masked in the ciphertexts yet recovered faithfully and efficiently by the present schemes.

A 16Kb 10T-SRAM with 4x Read-Power Reduction

This work aims to reduce the read power consumption as well as to enhance the stability of the SRAM cell during the read operation. A new 10-transisor cell is proposed with a new read scheme to minimize the power consumption within the memory core. It has separate read and write ports, thus cell read stability is significantly improved. A 16Kb SRAM macro operating at 1V supply voltage is demonstrated in 65 nm CMOS process. Its read power consumption is reduced to 24% of the conventional design. The new cell also has lower leakage current due to its special bit-line pre-charge scheme. As a result, it is suitable for low-power mobile applications where power supply is restricted by the battery.

Simulation of Organic Matter Variability on a Sugarbeet Field Using the Computer Based Geostatistical Methods

Computer based geostatistical methods can offer effective data analysis possibilities for agricultural areas by using vectorial data and their objective informations. These methods will help to detect the spatial changes on different locations of the large agricultural lands, which will lead to effective fertilization for optimal yield with reduced environmental pollution. In this study, topsoil (0-20 cm) and subsoil (20-40 cm) samples were taken from a sugar beet field by 20 x 20 m grids. Plant samples were also collected from the same plots. Some physical and chemical analyses for these samples were made by routine methods. According to derived variation coefficients, topsoil organic matter (OM) distribution was more than subsoil OM distribution. The highest C.V. value of 17.79% was found for topsoil OM. The data were analyzed comparatively according to kriging methods which are also used widely in geostatistic. Several interpolation methods (Ordinary,Simple and Universal) and semivariogram models (Spherical, Exponential and Gaussian) were tested in order to choose the suitable methods. Average standard deviations of values estimated by simple kriging interpolation method were less than average standard deviations (topsoil OM ± 0.48, N ± 0.37, subsoil OM ± 0.18) of measured values. The most suitable interpolation method was simple kriging method and exponantial semivariogram model for topsoil, whereas the best optimal interpolation method was simple kriging method and spherical semivariogram model for subsoil. The results also showed that these computer based geostatistical methods should be tested and calibrated for different experimental conditions and semivariogram models.

A Medical Images Based Retrieval System using Soft Computing Techniques

Content-Based Image Retrieval (CBIR) has been one on the most vivid research areas in the field of computer vision over the last 10 years. Many programs and tools have been developed to formulate and execute queries based on the visual or audio content and to help browsing large multimedia repositories. Still, no general breakthrough has been achieved with respect to large varied databases with documents of difering sorts and with varying characteristics. Answers to many questions with respect to speed, semantic descriptors or objective image interpretations are still unanswered. In the medical field, images, and especially digital images, are produced in ever increasing quantities and used for diagnostics and therapy. In several articles, content based access to medical images for supporting clinical decision making has been proposed that would ease the management of clinical data and scenarios for the integration of content-based access methods into Picture Archiving and Communication Systems (PACS) have been created. This paper gives an overview of soft computing techniques. New research directions are being defined that can prove to be useful. Still, there are very few systems that seem to be used in clinical practice. It needs to be stated as well that the goal is not, in general, to replace text based retrieval methods as they exist at the moment.

A Collusion-Resistant Distributed Signature Delegation Based on Anonymous Mobile Agent

This paper presents a novel method that allows an agent host to delegate its signing power to an anonymous mobile agent in such away that the mobile agent does not reveal any information about its host-s identity and, at the same time, can be authenticated by the service host, hence, ensuring fairness of service provision. The solution introduces a verification server to verify the signature generated by the mobile agent in such a way that even if colluding with the service host, both parties will not get more information than what they already have. The solution incorporates three methods: Agent Signature Key Generation method, Agent Signature Generation method, Agent Signature Verification method. The most notable feature of the solution is that, in addition to allowing secure and anonymous signature delegation, it enables tracking of malicious mobile agents when a service host is attacked. The security properties of the proposed solution are analyzed, and the solution is compared with the most related work.

Exploring Customer Trust in B2C Mobile Payments – A Qualitative Study

Mobile payments have been deployed by businesses for more than a decade. Customers use mobile payments if they trust in this relatively new payment method, have a belief and confidence in, as well as reliance on its services and applications. Despite its potential, the current literature shows that there is lack of customer trust in B2C mobile payments, and a lack of studies that determine the factors that influence their trust in these payments; which make these factors yet to be understood, especially in the Middle East region. Thus, this study aims to explore the factors that influence customer trust in mobile payments. The empirical data for this explorative study was collected by establishing four focus group sessions in the UAE. The results indicate that the explored significant factors can be classified into five main groups: customer characteristics, environmental (social and cultural) influences, provider characteristics, mobile-device characteristics, and perceived risks.

Wireless Sensor Networks:Delay Guarentee and Energy Efficient MAC Protocols

Wireless sensor networks is an emerging technology that serves as environment monitors in many applications. Yet these miniatures suffer from constrained resources in terms of computation capabilities and energy resources. Limited energy resource in these nodes demands an efficient consumption of that resource either by developing the modules itself or by providing an efficient communication protocols. This paper presents a comprehensive summarization and a comparative study of the available MAC protocols proposed for Wireless Sensor Networks showing their capabilities and efficiency in terms of energy consumption and delay guarantee.

Chewing behavior and Bolus Properties as Affected by Different Rice Types

The study aimed to investigate the effect of rice types on chewing behaviours (chewing time, number of chews, and portion size) and bolus properties (bolus moisture content, solid loss, and particle size distribution (PSD)) in human subjects. Five cooked rice types including brown rice (BR), white rice (WR), parboiled white rice (PR), high amylose white rice (HR) and waxy white rice (WXR) were chewed by six subjects. The chewing behaviours were recorded and the food boluses were collected during mastication. Rice typeswere found to significantly influence all chewing parameters evaluated. The WXR and BR showed the most pronounced differences compared with other rice types. The initial moisture content of un-chewed WXR was lowest (43.39%) whereas those of other rice types were ranged from 66.86 to 70.33%. The bolus obtained from chewing the WXR contained lowest moisture content (56.43%) whilst its solid loss (22.03%) was not significant different from those of all rice types. In PSD evaluation using Mastersizer S, the diameter of particles measured was ranged between 4 to 3500 μm. The particle size of food bolus from BR, HR, and WXR contained much finer particles than those of WR and PR.

Classification of Initial Stripe Height Patterns using Radial Basis Function Neural Network for Proportional Gain Prediction

This paper aims to improve a fine lapping process of hard disk drive (HDD) lapping machines by removing materials from each slider together with controlling the strip height (SH) variation to minimum value. The standard deviation is the key parameter to evaluate the strip height variation, hence it is minimized. In this paper, a design of experiment (DOE) with factorial analysis by twoway analysis of variance (ANOVA) is adopted to obtain a statistically information. The statistics results reveal that initial stripe height patterns affect the final SH variation. Therefore, initial SH classification using a radial basis function neural network is implemented to achieve the proportional gain prediction.

A Tool for Audio Quality Evaluation Under Hostile Environment

In this paper is to evaluate audio and speech quality with the help of Digital Audio Watermarking Technique under the different types of attacks (signal impairments) like Gaussian Noise, Compression Error and Jittering Effect. Further attacks are considered as Hostile Environment. Audio and Speech Quality Evaluation is an important research topic. The traditional way for speech quality evaluation is using subjective tests. They are reliable, but very expensive, time consuming, and cannot be used in certain applications such as online monitoring. Objective models, based on human perception, were developed to predict the results of subjective tests. The existing objective methods require either the original speech or complicated computation model, which makes some applications of quality evaluation impossible.

Enhanced Conference Organization Based On Correlation of Web Information and Ontology Based Expertise Search

From the importance of the conference and its constructive role in the studies discussion, there must be a strong organization that allows the exploitation of the discussions in opening new horizons. The vast amount of information scattered across the web, make it difficult to find experts, who can play a prominent role in organizing conferences. In this paper we proposed a new approach of extracting researchers- information from various Web resources and correlating them in order to confirm their correctness. As a validator of this approach, we propose a service that will be useful to set up a conference. Its main objective is to find appropriate experts, as well as the social events for a conference. For this application we us Semantic Web technologies like RDF and ontology to represent the confirmed information, which are linked to another ontology (skills ontology) that are used to present and compute the expertise.

Design of a Fuzzy Feed-forward Controller for Monitor HAGC System of Cold Rolling Mill

In this study we propose a novel monitor hydraulic automatic gauge control (HAGC) system based on fuzzy feedforward controller. This is used in the development of cold rolling mill automation system to improve the quality of cold strip. According to features/ properties of entry steel strip like its average yield stress, width of strip, and desired exit thickness, this controller realizes the compensation for the exit thickness error. The traditional methods of adjusting the roller position, can-t tolerate the variance in the entry steel strip. The proposed method uses a mathematical model of the system together with the expert knowledge to perform this adjustment while minimizing the effect of the stated problem. In order to improve the speed of the controller in rejecting disturbances introduced by entry strip thickness variations, expert knowledge is added as a feed-forward term to the HAGC system. Simulation results for the application of the proposed controller to a real cold mill show that the exit strip quality is highly improved.

Influence of Drought on Yield and Yield Components in White Bean

In order to study seed yield and seed yield components in bean under reduced irrigation condition and assessment drought tolerance of genotypes, 15 lines of White beans were evaluated in two separate RCB design with 3 replications under stress and non stress conditions. Analysis of variance showed that there were significant differences among varieties in terms of traits under study, indicating the existence of genetic variation among varieties. The results indicate that drought stress reduced seed yield, number of seed per plant, biological yield and number of pod in White been. In non stress condition, yield was highly correlated with the biological yield, whereas in stress condition it was highly correlated with harvest index. Results of stepwise regression showed that, selection can we done based on, biological yield, harvest index, number of seed per pod, seed length, 100 seed weight. Result of path analysis showed that the highest direct effect, being positive, was related to biological yield in non stress and to harvest index in stress conditions. Factor analysis were accomplished in stress and nonstress condition a, there were 4 factors that explained more than 76 percent of total variations. We used several selection indices such as Stress Susceptibility Index ( SSI ), Geometric Mean Productivity ( GMP ), Mean Productivity ( MP ), Stress Tolerance Index ( STI ) and Tolerance Index ( TOL ) to study drought tolerance of genotypes, we found that the best Stress Index for selection tolerance genotypes were STI, GMP and MP were the greatest correlations between these Indices and seed yield under stress and non stress conditions. In classification of genotypes base on phenotypic characteristics, using cluster analysis ( UPGMA ), all allels classified in 5 separate groups in stress and non stress conditions.

The Identification of Selected Dysfunctions and Paradoxes in Corporate Social Responsibility Management in Small Enterprise

The study presents a brief and synthetic discussion of selected conclusions resulting from multidimensional and in-depth empirical studies. Its theoretical part presents the assumptions referring to social responsibility management from the perspective of the specific nature of small enterprise functioning, while the empirical part presents the selected dysfunctions and paradoxes in social responsibility management referring to this group of enterprises. The paper is summarized by a short list of the resulting recommendations.