The Study of Chain Initiation Effect on the Direct Initiation of Detonation

In this research, effect of combustion reaction mechanism on direct initiation of detonation has been studied numerically. For this purpose, reaction mechanism has been simulated by using a three-step chemical kinetics model. The reaction scheme consists sequentially of a chain-initiation and chainbranching step, followed by a temperature -independent chaintermination. In a previous research, the effect of chain-branching on the direct initiation of detonation is studied. In this research effect of chain-initiation on direct initiation of detonation is investigated. For the investigation, first a characteristic time (τ) for each step of mechanism, which includes effect of different kinetics parameters, is defined. Then the effect of characteristic time of chain-initiation (τI) on critical initiation energy is studied. It is seen that increasing τI, causes critical initiation energy to be increased. Drawing detonation's shock pressure diagrams for different cases, shows that in small value of τI , kinetics has more important effect on the behavior of the wave.

Abrupt Scene Change Detection

A number of automated shot-change detection methods for indexing a video sequence to facilitate browsing and retrieval have been proposed in recent years. This paper emphasizes on the simulation of video shot boundary detection using one of the methods of the color histogram wherein scaling of the histogram metrics is an added feature. The difference between the histograms of two consecutive frames is evaluated resulting in the metrics. Further scaling of the metrics is performed to avoid ambiguity and to enable the choice of apt threshold for any type of videos which involves minor error due to flashlight, camera motion, etc. Two sample videos are used here with resolution of 352 X 240 pixels using color histogram approach in the uncompressed media. An attempt is made for the retrieval of color video. The simulation is performed for the abrupt change in video which yields 90% recall and precision value.

Swarmed Discriminant Analysis for Multifunction Prosthesis Control

One of the approaches enabling people with amputated limbs to establish some sort of interface with the real world includes the utilization of the myoelectric signal (MES) from the remaining muscles of those limbs. The MES can be used as a control input to a multifunction prosthetic device. In this control scheme, known as the myoelectric control, a pattern recognition approach is usually utilized to discriminate between the MES signals that belong to different classes of the forearm movements. Since the MES is recorded using multiple channels, the feature vector size can become very large. In order to reduce the computational cost and enhance the generalization capability of the classifier, a dimensionality reduction method is needed to identify an informative yet moderate size feature set. This paper proposes a new fuzzy version of the well known Fisher-s Linear Discriminant Analysis (LDA) feature projection technique. Furthermore, based on the fact that certain muscles might contribute more to the discrimination process, a novel feature weighting scheme is also presented by employing Particle Swarm Optimization (PSO) for estimating the weight of each feature. The new method, called PSOFLDA, is tested on real MES datasets and compared with other techniques to prove its superiority.

A Similarity Measure for Clustering and its Applications

This paper introduces a measure of similarity between two clusterings of the same dataset produced by two different algorithms, or even the same algorithm (K-means, for instance, with different initializations usually produce different results in clustering the same dataset). We then apply the measure to calculate the similarity between pairs of clusterings, with special interest directed at comparing the similarity between various machine clusterings and human clustering of datasets. The similarity measure thus can be used to identify the best (in terms of most similar to human) clustering algorithm for a specific problem at hand. Experimental results pertaining to the text categorization problem of a Portuguese corpus (wherein a translation-into-English approach is used) are presented, as well as results on the well-known benchmark IRIS dataset. The significance and other potential applications of the proposed measure are discussed.

New Curriculum and New Challenges: What do School Administrators Really Do?

The aim of this qualitative case study is to examine how school principals perform their new roles and responsibilities defined in accordance with the new curriculum. Of ten primary schools that the new curriculum was piloted in Istanbul in school year of 2004-2005, one school was randomly selected as the sample of the study. The participants of the study were comprised of randomly-selected 26 teachers working in the case school. To collect data, an interview schedule was developed based on the new role definitions for school principals by the National Ministry of Education. Participants were interviewed on one-to-one basis in February and March 2007. Overall results showed that the school principal was perceived to be successful in terms of the application of the new curriculum in school. According to the majority of teachers, the principal has done his best to establish the infrastructure that is necessary for successful application of the new program. In addition to these, the principal was reported to adopt a collegial and participatory leadership style by creating a positive school atmosphere that enables the school community (teachers, parents and students) to involve school more than before. Keywordscase study, curriculum implementation, school principals and curriculum

Applications of Support Vector Machines on Smart Phone Systems for Emotional Speech Recognition

An emotional speech recognition system for the applications on smart phones was proposed in this study to combine with 3G mobile communications and social networks to provide users and their groups with more interaction and care. This study developed a mechanism using the support vector machines (SVM) to recognize the emotions of speech such as happiness, anger, sadness and normal. The mechanism uses a hierarchical classifier to adjust the weights of acoustic features and divides various parameters into the categories of energy and frequency for training. In this study, 28 commonly used acoustic features including pitch and volume were proposed for training. In addition, a time-frequency parameter obtained by continuous wavelet transforms was also used to identify the accent and intonation in a sentence during the recognition process. The Berlin Database of Emotional Speech was used by dividing the speech into male and female data sets for training. According to the experimental results, the accuracies of male and female test sets were increased by 4.6% and 5.2% respectively after using the time-frequency parameter for classifying happy and angry emotions. For the classification of all emotions, the average accuracy, including male and female data, was 63.5% for the test set and 90.9% for the whole data set.

Robust Position Control of an Electromechanical Actuator for Automotive Applications

In this paper, the position control of an electronic throttle actuator is outlined. The dynamic behavior of the actuator is described with the help of an uncertain plant model. This motivates the controller design based on the ideas of higher-order slidingmodes. As a consequence anti-chattering techniques can be omitted. It is shown that the same concept is applicable to estimate unmeasureable signals. The control law and the observer are implemented on an electronic control unit. Results achieved by numerical simulations and real world experiments are presented and discussed.

Is Cognitive Dissonance an Intrinsic Property of the Human Mind? An Experimental Solution to a Half-Century Debate

Cognitive Dissonance can be conceived both as a concept related to the tendency to avoid internal contradictions in certain situations, and as a higher order theory about information processing in the human mind. In the last decades, this last sense has been strongly surpassed by the former, as nearly all experiment on the matter discuss cognitive dissonance as an output of motivational contradictions. In that sense, the question remains: is cognitive dissonance a process intrinsically associated with the way that the mind processes information, or is it caused by such specific contradictions? Objective: To evaluate the effects of cognitive dissonance in the absence of rewards or any mechanisms to manipulate motivation. Method: To solve this question, we introduce a new task, the hypothetical social arrays paradigm, which was applied to 50 undergraduate students. Results: Our findings support the perspective that the human mind shows a tendency to avoid internal dissonance even when there are no rewards or punishment involved. Moreover, our findings also suggest that this principle works outside the conscious level.

CO2 Abatement by Methanol Production from Flue-Gas in Methanol Plant

This study investigates CO2 mitigation by methanol synthesis from flue gas CO2 and H2 generation through water electrolysis. Electrolytic hydrogen generation is viable provided that the required electrical power is supplied from renewable energy resources; whereby power generation from renewable resources is yet commercial challenging. This approach contribute to zero-emission, moreover it produce oxygen which could be used as feedstock for chemical process. At ZPC, however, oxygen would be utilized through partial oxidation of methane in autothermal reactor (ATR); this makes ease the difficulties of O2 delivery and marketing. On the other hand, onboard hydrogen storage and consumption; in methanol plant; make the project economically more competitive.

Algorithm for Reconstructing 3D-Binary Matrix with Periodicity Constraints from Two Projections

We study the problem of reconstructing a three dimensional binary matrices whose interiors are only accessible through few projections. Such question is prominently motivated by the demand in material science for developing tool for reconstruction of crystalline structures from their images obtained by high-resolution transmission electron microscopy. Various approaches have been suggested to reconstruct 3D-object (crystalline structure) by reconstructing slice of the 3D-object. To handle the ill-posedness of the problem, a priori information such as convexity, connectivity and periodicity are used to limit the number of possible solutions. Formally, 3Dobject (crystalline structure) having a priory information is modeled by a class of 3D-binary matrices satisfying a priori information. We consider 3D-binary matrices with periodicity constraints, and we propose a polynomial time algorithm to reconstruct 3D-binary matrices with periodicity constraints from two orthogonal projections.

Linear Stability of Convection in a Viscoelastic Nanofluid Layer

This paper presents a linear stability analysis of natural convection in a horizontal layer of a viscoelastic nanofluid. The Oldroyd B model was utilized to describe the rheological behavior of a viscoelastic nanofluid. The model used for the nanofluid incorporated the effects of Brownian motion and thermophoresis. The onset criterion for stationary and oscillatory convection was derived analytically. The effects of the Deborah number, retardation parameters, concentration Rayleigh number, Prandtl number, and Lewis number on the stability of the system were investigated. Results indicated that there was competition among the processes of thermophoresis, Brownian diffusion, and viscoelasticity which caused oscillatory rather than stationary convection to occur. Oscillatory instability is possible with both bottom- and top-heavy nanoparticle distributions. Regimes of stationary and oscillatory convection for various parameters were derived and are discussed in detail.

Secure Internet Connectivity for Dynamic Source Routing (DSR) based Mobile Ad hoc Networks

'Secure routing in Mobile Ad hoc networks' and 'Internet connectivity to Mobile Ad hoc networks' have been dealt separately in the past research. This paper proposes a light weight solution for secure routing in integrated Mobile Ad hoc Network (MANET)-Internet. The proposed framework ensures mutual authentication of Mobile Node (MN), Foreign Agent (FA) and Home Agent (HA) to avoid various attacks on global connectivity and employs light weight hop-by-hop authentication and end-to-end integrity to protect the network from most of the potential security attacks. The framework also uses dynamic security monitoring mechanism to monitor the misbehavior of internal nodes. Security and performance analysis show that our proposed framework achieves good security while keeping the overhead and latency minimal.

The Relationship between Sheep Management and Lamb Mortality

This study was carried out to investigate lamb mortalities relating to ewes' breed and some managemental factors on 250 pregnant ewes (190-Rahmani, 30-Ossimi and 30-Romanov) at Mehallet Mousa, Animal Production Research Station, Kafr El- Sheikh Province, Egypt. These animals divided into five groups according to the managemental factors used. The results revealed that the lamb mortality was higher in Ossimi breed and lower in Romanov one. In addition, the highest lamb mortality occurred among lambs for unsupplemented ewes, for those had body condition score two and for lambs which born outdoor. Moreover, the lamb survivability was increased by the parity of ewes. From this study it can be concluded that the lamb mortality depends on ewes' body condition score, parity, lambing system (indoor or outdoor), nutrition during pregnancy period and selected breed. In addition, the most important period for lamb survival is the first week of age.

On the outlier Detection in Nonlinear Regression

The detection of outliers is very essential because of their responsibility for producing huge interpretative problem in linear as well as in nonlinear regression analysis. Much work has been accomplished on the identification of outlier in linear regression, but not in nonlinear regression. In this article we propose several outlier detection techniques for nonlinear regression. The main idea is to use the linear approximation of a nonlinear model and consider the gradient as the design matrix. Subsequently, the detection techniques are formulated. Six detection measures are developed that combined with three estimation techniques such as the Least-Squares, M and MM-estimators. The study shows that among the six measures, only the studentized residual and Cook Distance which combined with the MM estimator, consistently capable of identifying the correct outliers.

Optimizing the Number of Bits/Stage in 10-Bit, 50Ms/Sec Pipelined A/D Converter Considering Area, Speed, Power and Linearity

Pipeline ADCs are becoming popular at high speeds and with high resolution. This paper discusses the options of number of bits/stage conversion techniques in pipelined ADCs and their effect on Area, Speed, Power Dissipation and Linearity. The basic building blocks like op-amp, Sample and Hold Circuit, sub converter, DAC, Residue Amplifier used in every stage is assumed to be identical. The sub converters use flash architectures. The design is implemented using 0.18

Preliminary Chaos Analyses of Explosion Earthquakes Followed by Harmonic Tremors at Semeru Volcano, East Java, Indonesia

Successive event of explosion earthquake and harmonic tremor recorded at Semeru volcano were analyzed to investigate the dynamical system regarding to their eruptive mechanism. The eruptive activity at Semeru volcano East Java, Indonesia is intermittent emission of ash and bombs with Strombolian style which occurred at interval of 15 to 45 minutes. The explosive eruptions accompanied by explosion earthquakes and followed by volcanic tremor which generated by continuous emission of volcanic ash. The spectral and Lyapunov exponent of successive event of explosion and harmonic tremor were analyzed. Peak frequencies of explosion earthquakes range 1.2 to 1.9 Hz and those of the harmonic tremor have peak frequency range 1.5 — 2.2 Hz. The phase space is reconstructed and evaluated based on the Lyapunov exponents. Harmonic tremors have smaller Lyapunov exponent than explosion earthquakes. It can be considerably as correlated complexity of the mechanism from the variance of spectral and fractal dimension and can be concluded that the successive event of harmonic tremor and explosions are chaotic.

Innovation Development of Food Market of Kazakhstan

Currently, one of the main directions is developing of development based on the clustering of economic operations of Kazakhstan, providing for the organization and concentration of production capacity in one region or the most optimal system. In the modern economic literature clustering is regarded as one of the most effective tools to ensure competitive businesses, and improve their business itself.

Delay Preserving Substructures in Wireless Networks Using Edge Difference between a Graph and its Square Graph

In practice, wireless networks has the property that the signal strength attenuates with respect to the distance from the base station, it could be better if the nodes at two hop away are considered for better quality of service. In this paper, we propose a procedure to identify delay preserving substructures for a given wireless ad-hoc network using a new graph operation G 2 – E (G) = G* (Edge difference of square graph of a given graph and the original graph). This operation helps to analyze some induced substructures, which preserve delay in communication among them. This operation G* on a given graph will induce a graph, in which 1- hop neighbors of any node are at 2-hop distance in the original network. In this paper, we also identify some delay preserving substructures in G*, which are (i) set of all nodes, which are mutually at 2-hop distance in G that will form a clique in G*, (ii) set of nodes which forms an odd cycle C2k+1 in G, will form an odd cycle in G* and the set of nodes which form a even cycle C2k in G that will form two disjoint companion cycles ( of same parity odd/even) of length k in G*, (iii) every path of length 2k+1 or 2k in G will induce two disjoint paths of length k in G*, and (iv) set of nodes in G*, which induces a maximal connected sub graph with radius 1 (which identifies a substructure with radius equal 2 and diameter at most 4 in G). The above delay preserving sub structures will behave as good clusters in the original network.

An Example of Post-Harvest Thermotherapy as a Non-Chemical Method of Pathogen Control on Apples of Topaz Cultivar in Storage

Huge losses in apple production are caused by pathogens that cannot be seen shortly after harvest. After-harvest thermotherapy treatments can considerably improve control of storage diseases on apples and become an alternative to chemical pesticides. In the years 2010-2012 carried out research in this area. Apples of 'Topaz' cultivar were harvested at optimal maturity time for long storage and subject to water bath treatment at 45, 50, 52, 55°C for 60, 120, 180 and 240 seconds. The control was untreated fruits. After 12 and 24 weeks and during so called simulated trade turnover the fruits were checked for their condition and the originators of diseases were determined by using the standard phytopathological methods. The most common originator of 'Topaz' apple infection during storage were the fungi of genus Gloeosporium. In this paper it was proven that for effective protection of 'Topaz' apples against diseases, thermotherapy by using water treatments at temperature range of 50-52°C is quite sufficient.

Constrained Particle Swarm Optimization of Supply Chains

Since supply chains highly impact the financial performance of companies, it is important to optimize and analyze their Key Performance Indicators (KPI). The synergistic combination of Particle Swarm Optimization (PSO) and Monte Carlo simulation is applied to determine the optimal reorder point of warehouses in supply chains. The goal of the optimization is the minimization of the objective function calculated as the linear combination of holding and order costs. The required values of service levels of the warehouses represent non-linear constraints in the PSO. The results illustrate that the developed stochastic simulator and optimization tool is flexible enough to handle complex situations.