Simulations of Routing Protocols of Wireless Sensor Networks

Wireless Sensor Network is widely used in electronics. Wireless sensor networks are now used in many applications including military, environmental, healthcare applications, home automation and traffic control. We will study one area of wireless sensor networks, which is the routing protocol. Routing protocols are needed to send data between sensor nodes and the base station. In this paper, we will discuss two routing protocols, such as datacentric and hierarchical routing protocol. We will show the output of the protocols using the NS-2 simulator. This paper will compare the simulation output of the two routing protocol using Nam. We will simulate using Xgraph to find the throughput and delay of the protocol.

Extended Well-Founded Semantics in Bilattices

One of the most used assumptions in logic programming and deductive databases is the so-called Closed World Assumption (CWA), according to which the atoms that cannot be inferred from the programs are considered to be false (i.e. a pessimistic assumption). One of the most successful semantics of conventional logic programs based on the CWA is the well-founded semantics. However, the CWA is not applicable in all circumstances when information is handled. That is, the well-founded semantics, if conventionally defined, would behave inadequately in different cases. The solution we adopt in this paper is to extend the well-founded semantics in order for it to be based also on other assumptions. The basis of (default) negative information in the well-founded semantics is given by the so-called unfounded sets. We extend this concept by considering optimistic, pessimistic, skeptical and paraconsistent assumptions, used to complete missing information from a program. Our semantics, called extended well-founded semantics, expresses also imperfect information considered to be missing/incomplete, uncertain and/or inconsistent, by using bilattices as multivalued logics. We provide a method of computing the extended well-founded semantics and show that Kripke-Kleene semantics is captured by considering a skeptical assumption. We show also that the complexity of the computation of our semantics is polynomial time.

Investigation of Shear Thickening Liquid Protection Fibrous Material

The stab resistance performance of newly developed fabric composites composed of hexagonal paper honeycombs, filled with shear thickening fluid (STF), and woven Kevlar® fabric or UHMPE was investigated in this study. The STF was prepared by dispersing submicron SiO2 particles into polyethylene glycol (PEG). Our results indicate that the STF-Kevlar composite possessed lower penetration depth than that of neat Kevlar. In other words, the STF-Kevlar composite can attain the same energy level in stab-resistance test with fewer layers of Kevlar fabrics than that of the neat Kevlar fabrics. It also indicates that STF can be used for the fabrication of flexible body armors and can provide improved protection against stab threats. We found that the stab resistance of the STF-Kevlar composite increases with the increase of SiO2 concentration in STF. Moreover, the silica particles functionalized with silane coupling agent can further improve the stab resistance.

Optimum Radio Capacity Estimation of a Single-Cell Spread Spectrum MIMO System under Rayleigh Fading Conditions

In this paper, the problem of estimating the optimal radio capacity of a single-cell spread spectrum (SS) multiple-inputmultiple- output (MIMO) system operating in a Rayleigh fading environment is examined. The optimisation between the radio capacity and the theoretically achievable average channel capacity (in the sense of information theory) per user of a MIMO single-cell SS system operating in a Rayleigh fading environment is presented. Then, the spectral efficiency is estimated in terms of the achievable average channel capacity per user, during the operation over a broadcast time-varying link, and leads to a simple novel-closed form expression for the optimal radio capacity value based on the maximization of the achieved spectral efficiency. Numerical results are presented to illustrate the proposed analysis.

Inverse Problem Methodology for the Measurement of the Electromagnetic Parameters Using MLP Neural Network

This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study consists in the simulation of a large number of parameters in a material under test, using the finite element method (FEM). Both variations in relative magnetic permeability and electrical conductivity of the material under test are considered. Then, the obtained results are used to generate a set of vectors for the training of MLP neural network. Finally, the obtained neural network is used to evaluate a group of new materials, simulated by the FEM, but not belonging to the original dataset. Noisy data, added to the probe measurements is used to enhance the robustness of the method. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Digital Narrative as a Change Agent to Teach Reading to Media-Centric Students

Because today-s media centric students have adopted digital as their native form of communication, teachers are having increasingly difficult time motivating reluctant readers to read and write. Our research has shown these text-averse individuals can learn to understand the importance of reading and writing if the instruction is based on digital narratives. While these students are naturally attracted to story, they are better at consuming them than creating them. Therefore, any intervention that utilizes story as its basis needs to include instruction on the elements of story making. This paper presents a series of digitally-based tools to identify potential weaknesses of visually impaired visual learners and to help motivate these and other media-centric students to select and complete books that are assigned to them

Recycling Poultry Feathers for Pb Removal from Wastewater: Kinetic and Equilibrium Studies

Chicken feathers were used as biosorbent for Pb removal from aqueous solution. In this paper, the kinetics and equilibrium studies at several pH, temperature, and metal concentration values are reported. For tested conditions, the Pb sorption capacity of this poultry waste ranged from 0.8 to 8.3 mg/g. Optimal conditions for Pb removal by chicken feathers have been identified. Pseudo-first order and pseudo-second order equations were used to analyze the experimental data. In addition, the sorption isotherms were fitted to classical Langmuir and Freundlich models. Finally, thermodynamic parameters for the sorption process have been determined. In summary, the results showed that chicken feathers are an alternative and promising sorbent for the treatment of effluents polluted by Pb ions.

Enhancement of m-FISH Images using Spectral Unmixing

Breast carcinoma is the most common form of cancer in women. Multicolour fluorescent in-situ hybridisation (m-FISH) is a common method for staging breast carcinoma. The interpretation of m-FISH images is complicated due to two effects: (i) Spectral overlap in the emission spectra of fluorochrome marked DNA probes and (ii) tissue autofluorescence. In this paper hyper-spectral images of m-FISH samples are used and spectral unmixing is applied to produce false colour images with higher contrast and better information content than standard RGB images. The spectral unmixing is realised by combinations of: Orthogonal Projection Analysis (OPA), Alterating Least Squares (ALS), Simple-to-use Interactive Self-Modeling Mixture Analysis (SIMPLISMA) and VARIMAX. These are applied on the data to reduce tissue autofluorescence and resolve the spectral overlap in the emission spectra. The results show that spectral unmixing methods reduce the intensity caused by tissue autofluorescence by up to 78% and enhance image contrast by algorithmically reducing the overlap of the emission spectra.

Featured based Segmentation of Color Textured Images using GLCM and Markov Random Field Model

In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.

Measuring the Development Level of Chinese Regional Service Industry: An Empirical Analysis based on Entropy Weight and TOPSIS

Using entropy weight and TOPSIS method, a comprehensive evaluation is done on the development level of Chinese regional service industry in this paper. Firstly, based on existing research results, an evaluation index system is constructed from the scale of development, the industrial structure and the economic benefits. An evaluation model is then built up based on entropy weight and TOPSIS, and an empirical analysis is conducted on the development level of service industries in 31 Chinese provinces during 2006 and 2009 from the two dimensions or time series and cross section, which provides new idea for assessing regional service industry. Furthermore, the 31 provinces are classified into four categories based on the evaluation results, and deep analysis is carried out on the evaluation results.

New Product-Type Estimators for the Population Mean Using Quartiles of the Auxiliary Variable

In this paper, we suggest new product-type estimators for the population mean of the variable of interest exploiting the first or the third quartile of the auxiliary variable. We obtain mean square error equations and the bias for the estimators. We study the properties of these estimators using simple random sampling (SRS) and ranked set sampling (RSS) methods. It is found that, SRS and RSS produce approximately unbiased estimators of the population mean. However, the RSS estimators are more efficient than those obtained using SRS based on the same number of measured units for all values of the correlation coefficient.

Weight-Based Query Optimization System Using Buffer

Fast retrieval of data has been a need of user in any database application. This paper introduces a buffer based query optimization technique in which queries are assigned weights according to their number of execution in a query bank. These queries and their optimized executed plans are loaded into the buffer at the start of the database application. For every query the system searches for a match in the buffer and executes the plan without creating new plans.

Experimental Investigation of a Mixture of Methane, Carbon Dioxide and Nitrogen Gas Hydrate Formation in Water-Based Drilling Mud in the Presence or Absence of Thermodynamic Inhibitors

Gas hydrates form when a number of factors co-exist: free water, hydrocarbon gas, cold temperatures and high pressures are typical of the near mud-line conditions in a deepwater drilling operation. Subsequently, when drilling with water based muds, particularly on exploration wells, the risk of hydrate formation associated with a gas influx is high. The consequences of gas hydrate formation while drilling are severe, and as such, every effort should be made to ensure the risk of hydrate formation is either eliminated or significantly reduced. Thermodynamic inhibitors are used to reduce the free water content of a drilling mud, and thus suppress the hydrate formation temperature. Very little experimental work has been performed by oil and gas research companies on the evaluation of gas hydrate formation in a water-based drilling mud. The main objective of this paper is to investigate the experimental gas hydrate formation for a mixture of methane, carbon dioxide & nitrogen in a water-based drilling mud with or without presence of different concentrations of thermodynamic inhibitors including pure salt and a combination of salt with methanol or ethylene glycol at different concentrations in a static loop apparatus. The experiments were performed using a static loop apparatus consisting of a 2.4307 cm inside diameter and 800 cm long pipe. All experiments were conducted at 2200 psia. The temperature in the loop was decreased at a rate of 3.33 °F/h from initial temperature of 80 °F.

Active Disturbance Rejection Control for Wind System Based On a DFIG

This paper proposes the study of a robust control of the doubly fed induction generator (DFIG) used in a wind energy production. The proposed control is based on the linear active disturbance rejection control (ADRC) and it is applied to the control currents rotor of the DFIG, the DC bus voltage and active and reactive power exchanged between the DFIG and the network. The system under study and the proposed control are simulated using MATLAB/SIMULINK.

Improving Injection Moulding Processes Using Experimental Design

Moulded parts contribute to more than 70% of components in products. However, common defects particularly in plastic injection moulding exist such as: warpage, shrinkage, sink marks, and weld lines. In this paper Taguchi experimental design methods are applied to reduce the warpage defect of thin plate Acrylonitrile Butadiene Styrene (ABS) and are demonstrated in two levels; namely, orthogonal arrays of Taguchi and the Analysis of Variance (ANOVA). Eight trials have been run in which the optimal parameters that can minimize the warpage defect in factorial experiment are obtained. The results obtained from ANOVA approach analysis with respect to those derived from MINITAB illustrate the most significant factors which may cause warpage in injection moulding process. Moreover, ANOVA approach in comparison with other approaches like S/N ratio is more accurate and with the interaction of factors it is possible to achieve higher and the better outcomes.

Enhanced Clustering Analysis and Visualization Using Kohonen's Self-Organizing Feature Map Networks

Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.

Multicast Optimization Techniques using Best Effort Genetic Algorithms

Multicast Network Technology has pervaded our lives-a few examples of the Networking Techniques and also for the improvement of various routing devices we use. As we know the Multicast Data is a technology offers many applications to the user such as high speed voice, high speed data services, which is presently dominated by the Normal networking and the cable system and digital subscriber line (DSL) technologies. Advantages of Multi cast Broadcast such as over other routing techniques. Usually QoS (Quality of Service) Guarantees are required in most of Multicast applications. The bandwidth-delay constrained optimization and we use a multi objective model and routing approach based on genetic algorithm that optimizes multiple QoS parameters simultaneously. The proposed approach is non-dominated routes and the performance with high efficiency of GA. Its betterment and high optimization has been verified. We have also introduced and correlate the result of multicast GA with the Broadband wireless to minimize the delay in the path.

Developing the Color Temperature Histogram Method for Improving the Content-Based Image Retrieval

This paper proposes a new method for image searches and image indexing in databases with a color temperature histogram. The color temperature histogram can be used for performance improvement of content–based image retrieval by using a combination of color temperature and histogram. The color temperature histogram can be represented by a range of 46 colors. That is more than the color histogram and the dominant color temperature. Moreover, with our method the colors that have the same color temperature can be separated while the dominant color temperature can not. The results showed that the color temperature histogram retrieved an accurate image more often than the dominant color temperature method or color histogram method. This also took less time so the color temperature can be used for indexing and searching for images.

Effect of Soil Tillage System upon the Soil Properties, Weed Control, Quality and Quantity Yield in Some Arable Crops

The paper presents the influence of the conventional ploughing tillage technology in comparison with the minimum tillage, upon the soil properties, weed control and yield in the case of maize (Zea mays L.), soya-bean (Glycine hispida L.) and winter wheat (Triticum aestivum L.) in a three years crop rotation. A research has been conducted at the University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Romania. The use of minimum soil tillage systems within a three years rotation: maize, soya-bean, wheat favorites the rise of the aggregates hydro stability with 5.6-7.5% on a 0-20 cm depth and 5-11% on 20-30 cm depth. The minimum soil tillage systems – paraplow, chisel or rotary grape – are polyvalent alternatives for basic preparation, germination bed preparation and sowing, for fields and crops with moderate loose requirements being optimized technologies for: soil natural fertility activation and rationalization, reduction of erosion, increasing the accumulation capacity for water and realization of sowing in the optimal period. The soil tillage system influences the productivity elements of cultivated species and finally the productions thus obtained. Thus, related to conventional working system, the productions registered in minimum tillage working represented 89- 97% in maize, 103-112% in soya-bean, 93-99% in winter-wheat. The results of investigations showed that the yield is a conclusion soil tillage systems influence on soil properties, plant density assurance and on weed control. Under minimum tillage systems in the case of winter weat as an option for replacing classic ploughing, the best results in terms of quality indices were obtained from version worked with paraplow, followed by rotary harrow and chisel. At variants worked with paraplow were obtained quality indices close to those of the variant worked with plow, and protein and gluten content was even higher. At Ariesan variety, highest protein content, 12.50% and gluten, 28.6% was obtained for the variant paraplow.

Information Seeking through Assimilation Process in Thai Organization

The purpose of this study is to examine employee assessments of the usefulness/value of different types of information available to those employees during the process of organizational assimilation. Participants in the study were 247 “new" employees at Bangkok Bank. Bangkok Bank considers employees whose length of stay with the bank has been less than 18 months as new employees. Questionnaires were administered to all of the Bank-s new employees to obtain the data for this study. Repeated measures analysis was used to analyze the data. The data were summed and coded by using Statistical Package for Social Science. Newcomers indicate that social information is the most useful information, followed by job (technical, referent, and appraisal information), political, normative, and organizational information. Essentially, social, job, and political information are evaluated by newcomers as highly useful, while normative and organizational information are rated as moderately useful.