Context Modeling and Reasoning Approach in Context-Aware Middleware for URC System

To realize the vision of ubiquitous computing, it is important to develop a context-aware infrastructure which can help ubiquitous agents, services, and devices become aware of their contexts because such computational entities need to adapt themselves to changing situations. A context-aware infrastructure manages the context model representing contextual information and provides appropriate information. In this paper, we introduce Context-Aware Middleware for URC System (hereafter CAMUS) as a context-aware infrastructure for a network-based intelligent robot system and discuss the ontology-based context modeling and reasoning approach which is used in that infrastructure.

A Business Intelligence System Design Based on ASP Platform

The Informational Infrastructures of small and medium-sized manufacturing enterprises are relatively poor, there are serious shortages of capitals which can be invested in informatization construction, computer hardware and software resources, and human resources. To address the informatization issue in small and medium-sized manufacturing enterprises, and enable them to the application of advanced management thinking and enhance their competitiveness, the paper establish a manufacturing-oriented small and medium-sized enterprises informatization platform based on the ASP business intelligence technology, which effectively improves the scientificity of enterprises decision and management informatization.

Self-Assembling Hypernetworks for Cognitive Learning of Linguistic Memory

Hypernetworks are a generalized graph structure representing higher-order interactions between variables. We present a method for self-organizing hypernetworks to learn an associative memory of sentences and to recall the sentences from this memory. This learning method is inspired by the “mental chemistry" model of cognition and the “molecular self-assembly" technology in biochemistry. Simulation experiments are performed on a corpus of natural-language dialogues of approximately 300K sentences collected from TV drama captions. We report on the sentence completion performance as a function of the order of word-interaction and the size of the learning corpus, and discuss the plausibility of this architecture as a cognitive model of language learning and memory.

Space-Time Variation in Rainfall and Runoff: Upper Betwa Catchment

Among all geo-hydrological relationships, rainfallrunoff relationship is of utmost importance in any hydrological investigation and water resource planning. Spatial variation, lag time involved in obtaining areal estimates for the basin as a whole can affect the parameterization in design stage as well as in planning stage. In conventional hydrological processing of data, spatial aspect is either ignored or interpolated at sub-basin level. Temporal variation when analysed for different stages can provide clues for its spatial effectiveness. The interplay of space-time variation at pixel level can provide better understanding of basin parameters. Sustenance of design structures for different return periods and their spatial auto-correlations should be studied at different geographical scales for better management and planning of water resources. In order to understand the relative effect of spatio-temporal variation in hydrological data network, a detailed geo-hydrological analysis of Betwa river catchment falling in Lower Yamuna Basin is presented in this paper. Moreover, the exact estimates about the availability of water in the Betwa river catchment, especially in the wake of recent Betwa-Ken linkage project, need thorough scientific investigation for better planning. Therefore, an attempt in this direction is made here to analyse the existing hydrological and meteorological data with the help of SPSS, GIS and MS-EXCEL software. A comparison of spatial and temporal correlations at subcatchment level in case of upper Betwa reaches has been made to demonstrate the representativeness of rain gauges. First, flows at different locations are used to derive correlation and regression coefficients. Then, long-term normal water yield estimates based on pixel-wise regression coefficients of rainfall-runoff relationship have been mapped. The areal values obtained from these maps can definitely improve upon estimates based on point-based extrapolations or areal interpolations.

Operational Modal Analysis Implementation on a Hybrid Composite Plate

In aerospace applications, interactions of airflow with aircraft structures can result in undesirable structural deformations. This structural deformation in turn, can be predicted if the natural modes of the structure are known. This can be achieved through conventional modal testing that requires a known excitation force in order to extract these dynamic properties. This technique can be experimentally complex because of the need for artificial excitation and it is also does not represent actual operational condition. The current work presents part of research work that address the practical implementation of operational modal analysis (OMA) applied to a cantilevered hybrid composite plate employing single contactless sensing system via laser vibrometer. OMA technique extracts the modal parameters based only on the measurements of the dynamic response. The OMA results were verified with impact hammer modal testing and good agreement was obtained.

Development of Face Surrogate for Impact Protection Design for Cyclist

Bicycle usage for exercise, recreation, and commuting to work in Australia shows that pedal cycling is the fourth most popular activity with 10.6% increase in participants between 2001 and 2007. As with other means of transport, accident and injury becomes common although mandatory bicycle helmet wearing has been introduced. The research aims to develop a face surrogate made of sandwich of rigid foam and rubber sheets to represent human facial bone under blunt impact. The facial surrogate will serve as an important test device for further development of facial-impact protection for cyclist. A test procedure was developed to simulate the energy of impact and record data to evaluate the effect of impact on facial bones. Drop tests were performed to establish a suitable combination of materials. It was found that the sandwich structure of rigid extruded-polystyrene foam (density of 40 kg/m3 with a pattern of 6-mm-holes), Neoprene rubber sponge, and Abrasaflex rubber backing, had impact characteristics comparable to that of human facial bone. In particular, the foam thickness of 30 mm and 25 mm was found suitable to represent human zygoma (cheekbone) and maxilla (upper-jaw bone), respectively.

Grid Computing for the Bi-CGSTAB Applied to the Solution of the Modified Helmholtz Equation

The problem addressed herein is the efficient management of the Grid/Cluster intense computation involved, when the preconditioned Bi-CGSTAB Krylov method is employed for the iterative solution of the large and sparse linear system arising from the discretization of the Modified Helmholtz-Dirichlet problem by the Hermite Collocation method. Taking advantage of the Collocation ma-trix's red-black ordered structure we organize efficiently the whole computation and map it on a pipeline architecture with master-slave communication. Implementation, through MPI programming tools, is realized on a SUN V240 cluster, inter-connected through a 100Mbps and 1Gbps ethernet network,and its performance is presented by speedup measurements included.

Influence of Taguchi Selected Parameters on Properties of CuO-ZrO2 Nanoparticles Produced via Sol-gel Method

The present paper discusses the selection of process parameters for obtaining optimal nanocrystallites size in the CuOZrO2 catalyst. There are some parameters changing the inorganic structure which have an influence on the role of hydrolysis and condensation reaction. A statistical design test method is implemented in order to optimize the experimental conditions of CuO-ZrO2 nanoparticles preparation. This method is applied for the experiments and L16 orthogonal array standard. The crystallites size is considered as an index. This index will be used for the analysis in the condition where the parameters vary. The effect of pH, H2O/ precursor molar ratio (R), time and temperature of calcination, chelating agent and alcohol volume are particularity investigated among all other parameters. In accordance with the results of Taguchi, it is found that temperature has the greatest impact on the particle size. The pH and H2O/ precursor molar ratio have low influences as compared with temperature. The alcohol volume as well as the time has almost no effect as compared with all other parameters. Temperature also has an influence on the morphology and amorphous structure of zirconia. The optimal conditions are determined by using Taguchi method. The nanocatalyst is studied by DTA-TG, XRD, EDS, SEM and TEM. The results of this research indicate that it is possible to vary the structure, morphology and properties of the sol-gel by controlling the above-mentioned parameters.

Performance Comparison of Particle Swarm Optimization with Traditional Clustering Algorithms used in Self-Organizing Map

Self-organizing map (SOM) is a well known data reduction technique used in data mining. It can reveal structure in data sets through data visualization that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOM, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of an adaptive heuristic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOM. The application of our method to several standard data sets demonstrates its feasibility. PSO algorithm utilizes a so-called U-matrix of SOM to determine cluster boundaries; the results of this novel automatic method compare very favorably to boundary detection through traditional algorithms namely k-means and hierarchical based approach which are normally used to interpret the output of SOM.

Effect of Laser Power and Powder Flow Rate on Properties of Laser Metal Deposited Ti6Al4V

Laser Metal Deposition (LMD) is an additive manufacturing process with capabilities that include: producing new part directly from 3 Dimensional Computer Aided Design (3D CAD) model, building new part on the existing old component and repairing an existing high valued component parts that would have been discarded in the past. With all these capabilities and its advantages over other additive manufacturing techniques, the underlying physics of the LMD process is yet to be fully understood probably because of high interaction between the processing parameters and studying many parameters at the same time makes it further complex to understand. In this study, the effect of laser power and powder flow rate on physical properties (deposition height and deposition width), metallurgical property (microstructure) and mechanical (microhardness) properties on laser deposited most widely used aerospace alloy are studied. Also, because the Ti6Al4V is very expensive, and LMD is capable of reducing buy-to-fly ratio of aerospace parts, the material utilization efficiency is also studied. Four sets of experiments were performed and repeated to establish repeatability using laser power of 1.8 kW and 3.0 kW, powder flow rate of 2.88 g/min and 5.67 g/min, and keeping the gas flow rate and scanning speed constant at 2 l/min and 0.005 m/s respectively. The deposition height / width are found to increase with increase in laser power and increase in powder flow rate. The material utilization is favoured by higher power while higher powder flow rate reduces material utilization. The results are presented and fully discussed.

Classifier Based Text Mining for Neural Network

Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.

A Comparative Analysis of the Perceived Bureaucracy in a Turkish State University

Organizational structure of the Turkish state universities is a form of bureaucracy, a high efficient system in rational and formal control. According to the dimensional approach bureaucracy can occur in an organization in a degree, as some bureaucracy characteristics can be stronger than others. In addition, the units of an organization due to their different specific characteristic properties can perceive the bureaucracy differently. In the study, Hall-s Organizational Inventory, which was developed for evaluating the degree of bureaucratization from the dimensional perspective, is used to find out if there is a difference in the perception of the bureaucracy between the academicians working in three different departments and two faculties in the same university.

Geometric and Material Nonlinear Analysis of Reinforced Concrete Structure Considering Soil-Structure Interaction

In the present research, a finite element model is presented to study the geometrical and material nonlinear behavior of reinforced concrete plane frames considering soil-structure interaction. The nonlinear behaviors of concrete and reinforcing steel are considered both in compression and tension up to failure. The model takes account also for the number, diameter, and distribution of rebar along every cross section. Soil behavior is taken into consideration using four different models; namely: linear-, nonlinear Winkler's model, and linear-, nonlinear continuum model. A computer program (NARC) is specially developed in order to perform the analysis. The results achieved by the present model show good agreement with both theoretical and experimental published literature. The nonlinear behavior of a rectangular frame resting on soft soil up to failure using the proposed model is introduced for demonstration.

More Realistic Model for Simulating Min Protein Dynamics: Lattice Boltzmann Method Incorporating the Role of Nucleoids

The dynamics of Min proteins plays a center role in accurate cell division. Although the nucleoids may presumably play an important role in prokaryotic cell division, there is a lack of models to account for its participation. In this work, we apply the lattice Boltzmann method to investigate protein oscillation based on a mesoscopic model that takes into account the nucleoid-s role. We found that our numerical results are in reasonably good agreement with the previous experimental results On comparing with the other computational models without the presence of nucleoids, the highlight of our finding is that the local densities of MinD and MinE on the cytoplasmic membrane increases, especially along the cell width, when the size of the obstacle increases, leading to a more distinct cap-like structure at the poles. This feature indicated the realistic pattern and reflected the combination of Min protein dynamics and nucleoid-s role.

Effect of Fine-Ground Ceramic Admixture on Early Age Properties of Cement Paste

Properties of cement pastes with fine-ground ceramics used as an alternative binder replacing Portland cement up to 20% of its mass are investigated. At first, the particle size distribution of cement and fine-ground ceramics is measured using laser analyser. Then, the material properties are studied in the early hardening period up to 28 days. The hydration process of studied materials is monitored by electrical conductivity measurement using TDR sensors. The changes of materials- structures within the hardening are observed using pore size distribution measurement. The compressive strength measurements are done as well. Experimental results show that the replacement of Portland cement by fine-ground ceramics in the amount of up to 20% by mass is acceptable solution from the mechanical point of view. One can also assume similar physical properties of designed materials to the reference material with only Portland cement as binder.

Challenges of Irrigation Water Supply in Croplands of Arid Regions and their Environmental Consequences – A Case Study in the Dez and Moghan Command Areas of Iran

Renewable water resources are crucial production variables in arid and semi-arid regions where intensive agriculture is practiced to meet ever-increasing demand for food and fiber. This is crucial for the Dez and Moghan command areas where water delivery problems and adverse environmental issues are widespread. This paper aims to identify major problems areas using on-farm surveys of 200 farmers, agricultural extensionists and water suppliers which was complemented by secondary data and field observations during 2010- 2011 cultivating season. The SPSS package was used to analyze and synthesis data. Results indicated inappropriate canal operations in both schemes, though there was no unanimity about the underlying causes. Inequitable and inflexible distribution was found to be rooted in deficient hydraulic structures particularly in the main and secondary canals. The inadequacy and inflexibility of water scheduling regime was the underlying causes of recurring pest and disease spread which often led to the decline of crop yield and quality, although these were not disputed, the water suppliers were not prepared to link with the deficiencies in the operation of the main and secondary canals. They rather attributed these to the prevailing salinity; alkalinity, water table fluctuations and leaching of the valuable agro-chemical inputs from the plants- route zone with farreaching consequences. Examples of these include the pollution of ground and surface resources due to over-irrigation at the farm level which falls under the growers- own responsibility. Poor irrigation efficiency and adverse environmental problems were attributed to deficient and outdated farming practices that were in turn rooted in poor extension programs and irrational water charges.

Development a New Model of EEVC/WG17 Lower Legform for Pedestrian Safety

Development, calibration and validation of a threedimensional model of the Legform impactor for pedestrian crash with bumper are presented. Lower limb injury is becoming an increasingly important concern in vehicle safety for both occupants and pedestrians. In order to prevent lower extremity injuries to a pedestrian when struck by a car, it is important to elucidate the loadings from car front structures on the lower extremities and the injury mechanism caused by these loadings. An impact test procedure with a legform addressing lower limb injuries in car pedestrian accidents has been proposed by EEVC/WG17. In this study a modified legform impactor is introduced and validated against EEVC/WG17 criteria. The finite element model of this legform is developed using LS-DYNA software. Total mass of legform impactor is 13.4 kg.Technical specifications including the mass and location of the center of gravity and moment of inertia about a horizontal axis through the respective centre of gravity in femur and tibia are determined. The obtained results of legform impactor static and dynamic tests are as specified in the EEVC/WG17.

Nonlinear Analysis of Shear Wall Using Finite Element Model

In the analysis of structures, the nonlinear effects due to large displacement, large rotation and materially-nonlinear are very important and must be considered for the reliable analysis. The non-linear fmite element analysis has potential as usable and reliable means for analyzing of civil structures with the availability of computer technology. In this research the large displacements and materially nonlinear behavior of shear wall is presented with developing of fmite element code using the standard Galerkin weighted residual formulation. Two-dimensional plane stress model was carried out to present the shear wall response. Total Lagangian formulation, which is computationally more effective, is used in the formulation of stiffness matrices and the Newton-Raphson method is applied for the solution of nonlinear transient equations. The details of the program formulation are highlighted and the results of the analyses are presented, along with a comparison of the response of the structure with Ansys software results. The presented model in this paper can be developed for nonlinear analysis of civil engineering structures with different material behavior and complicated geometry.

Rheological Characterisation of Collagen Gels from Marine Resources of Black Sea and Chlohexidine Salt for using in Dental Medicine

In the paper we presented the possibility of application collagen gels with active principle-s from marine algae extract and chlorhexidine salt in dental medicine. The hydro-alcoholic extracts from marine algae have been used as they have been obtained. The extracts from marine algae and chlorhexidine salt (digluconate) are incorporated in type I non-denatured fibrillar collagen matrixes. In order to obtain therapeutic effects at nanostructure level, it is important to know the rheological characteristics of the relevant mixtures of collagen gels and extracts from marine algae selected for use. In this survey we have studied mixtures made of non-denatured fibrillar collagen hydro-gels where different concentrations of marine algae have been incorporated. Based on the data obtained for the shearing tensions, we have traced the rheograms – the diagrams for shearing tensions depending on the shearing speed values – from which we have calculated the apparent viscosities as ratios between shearing tension and speed values, which have been figured in relation to the shearing speed values, with a view to levelling dependency.

Gain Tuning Fuzzy Controller for an Optical Disk Drive

Since the driving speed and control accuracy of commercial optical disk are increasing significantly, it needs an efficient controller to monitor the track seeking and following operations of the servo system for achieving the desired data extracting response. The nonlinear behaviors of the actuator and servo system of the optical disk drive will influence the laser spot positioning. Here, the model-free fuzzy control scheme is employed to design the track seeking servo controller for a d.c. motor driving optical disk drive system. In addition, the sliding model control strategy is introduced into the fuzzy control structure to construct a 1-D adaptive fuzzy rule intelligent controller for simplifying the implementation problem and improving the control performance. The experimental results show that the steady state error of the track seeking by using this fuzzy controller can maintain within the track width (1.6 μm ). It can be used in the track seeking and track following servo control operations.