An Efficient and Generic Hybrid Framework for High Dimensional Data Clustering

Clustering in high dimensional space is a difficult problem which is recurrent in many fields of science and engineering, e.g., bioinformatics, image processing, pattern reorganization and data mining. In high dimensional space some of the dimensions are likely to be irrelevant, thus hiding the possible clustering. In very high dimensions it is common for all the objects in a dataset to be nearly equidistant from each other, completely masking the clusters. Hence, performance of the clustering algorithm decreases. In this paper, we propose an algorithmic framework which combines the (reduct) concept of rough set theory with the k-means algorithm to remove the irrelevant dimensions in a high dimensional space and obtain appropriate clusters. Our experiment on test data shows that this framework increases efficiency of the clustering process and accuracy of the results.

Indoor Mapping by using Smartphone Device

This paper presented the potential of smart phone to provide support on mapping the indoor asset. The advantage of using the smart phone to generate the indoor map is that it has the ability to capture, store and reproduces still or video images; indeed most of us do have this powerful gadget. The captured images usually used by maintenance team to save a record for future reference. Here, these images are used to generate 3D models of an object precisely and accurately for efficient and effective solution in data gathering. Thus, it could be a resource for an informative database in asset management.

Dynamic Modeling of Intelligent Air-Cushion Tracked Vehicle for Swamp Peat

Modeling of the dynamic behavior and motion are renewed interest in the improved tractive performance of an intelligent air-cushion tracked vehicle (IACTV). This paper presents a new dynamical model for the forces on the developed small scale intelligent air-cushion tracked vehicle moving over swamp peat. The air cushion system partially supports the 25 % of vehicle total weight in order to make the vehicle ground contact pressure 7 kN/m2. As the air-cushion support system can adjust automatically on the terrain, so the vehicle can move over the terrain without any risks. The springdamper system is used with the vehicle body to control the aircushion support system on any undulating terrain by making the system sinusoidal form. Experiments have been carried out to investigate the relationships among tractive efficiency, slippage, traction coefficient, load distribution ratio, tractive effort, motion resistance and power consumption in given terrain conditions. Experiment and simulation results show that air-cushion system improves the vehicle performance by keeping traction coefficient of 71% and tractive efficiency of 62% and the developed model can meet the demand of transport efficiency with the optimal power consumption.

Comparative Analysis of Concentration in Insurance Markets in New EU Member States

The purpose of this article is to analyze the market structure as well as the degree of concentration in insurance markets in new EU member states. The analysis was conducted using several most commonly used concentration indicators such as concentration ratio, Herfindahl-Hirschman index and entropy index. These indicators were calculated for the 2000-2010 period on the basis of total gross written premium as the most relevant indicator of market power in insurance markets. The results of the analysis showed that in all observed countries the level of concentration decreased, though with significantly different intensity. Yet, in some countries, the level of concentration remains very high.

Investigation of Regenerative and Recuperative Burners for Different Sizes of Reheating Furnaces

This research aims to analyze the regenerative burner and the recuperative burner for the different reheating furnaces in the steel industry. The warm air temperatures of the burners are determined to suit with the sizes of the reheating furnaces by considering the air temperature, the fuel cost and the investment cost. The calculations of the payback period and the net present value are studied to compare the burners for the different reheating furnaces. The energy balance is utilized to calculate and compare the energy used in the different sizes of reheating furnaces for each burner. It is found that the warm air temperature is different if the sizes of reheating furnaces are varied. Based on the considerations of the net present value and the payback period, the regenerative burner is suitable for all plants at the same life of the burner. Finally, the sensitivity analysis of all factors has been discussed in this research.

Effect of Organic Matter and Biofertilizers on Chickpea Quality and Biological Nitrogen Fixation

In order to evaluation the effects of soil organic matter and biofertilizer on chickpea quality and biological nitrogen fixation, field experiments were carried out in 2007 and 2008 growing seasons. In this research the effects of different strategies for soil fertilization were investigated on grain yield and yield component, minerals, organic compounds and cooking time of chickpea. Experimental units were arranged in split-split plots based on randomized complete blocks with three replications. Main plots consisted of (G1): establishing a mixed vegetation of Vicia panunica and Hordeum vulgare and (G2): control, as green manure levels. Also, five strategies for obtaining the base fertilizer requirement including (N1): 20 t.ha-1 farmyard manure; (N2): 10 t.ha-1 compost; (N3): 75 kg.ha-1 triple super phosphate; (N4): 10 t.ha-1 farmyard manure + 5 t.ha-1 compost and (N5): 10 t.ha-1 farmyard manure + 5 t.ha-1 compost + 50 kg.ha-1 triple super phosphate were considered in sub plots. Furthermoree four levels of biofertilizers consisted of (B1): Bacillus lentus + Pseudomonas putida; (B2): Trichoderma harzianum; (B3): Bacillus lentus + Pseudomonas putida + Trichoderma harzianum; and (B4): control (without biofertilizers) were arranged in sub-sub plots. Results showed that integrating biofertilizers (B3) and green manure (G1) produced the highest grain yield. The highest amounts of yield were obtained in G1×N5 interaction. Comparison of all 2-way and 3-way interactions showed that G1N5B3 was determined as the superior treatment. Significant increasing of N, P2O5, K2O, Fe and Mg content in leaves and grains emphasized on superiority of mentioned treatment because each one of these nutrients has an approved role in chlorophyll synthesis and photosynthesis abilities of the crops. The combined application of compost, farmyard manure and chemical phosphorus (N5) in addition to having the highest yield, had the best grain quality due to high protein, starch and total sugar contents, low crude fiber and reduced cooking time.

Investigation of Inter Feeder Power Flow Regulator: Load Sharing Mode

The Inter feeder Power Flow Regulator (IFPFR) proposed in this paper consists of several voltage source inverters with common dc bus; each inverter is connected in series with one of different independent distribution feeders in the power system. This paper is concerned with how to transfer power between the feeders for load sharing purpose. The power controller of each inverter injects the power (for sending feeder) or absorbs the power (for receiving feeder) via injecting suitable voltage; this voltage injection is simulated by voltage drop across series virtual impedance, the impedance value is selected to achieve the concept of power exchange between the feeders without perturbing the load voltage magnitude of each feeder. In this paper a new control scheme for load sharing using IFPFR is proposed.

Library Aware Power Conscious Realization of Complementary Boolean Functions

In this paper, we consider the problem of logic simplification for a special class of logic functions, namely complementary Boolean functions (CBF), targeting low power implementation using static CMOS logic style. The functions are uniquely characterized by the presence of terms, where for a canonical binary 2-tuple, D(mj) ∪ D(mk) = { } and therefore, we have | D(mj) ∪ D(mk) | = 0 [19]. Similarly, D(Mj) ∪ D(Mk) = { } and hence | D(Mj) ∪ D(Mk) | = 0. Here, 'mk' and 'Mk' represent a minterm and maxterm respectively. We compare the circuits minimized with our proposed method with those corresponding to factored Reed-Muller (f-RM) form, factored Pseudo Kronecker Reed-Muller (f-PKRM) form, and factored Generalized Reed-Muller (f-GRM) form. We have opted for algebraic factorization of the Reed-Muller (RM) form and its different variants, using the factorization rules of [1], as it is simple and requires much less CPU execution time compared to Boolean factorization operations. This technique has enabled us to greatly reduce the literal count as well as the gate count needed for such RM realizations, which are generally prone to consuming more cells and subsequently more power consumption. However, this leads to a drawback in terms of the design-for-test attribute associated with the various RM forms. Though we still preserve the definition of those forms viz. realizing such functionality with only select types of logic gates (AND gate and XOR gate), the structural integrity of the logic levels is not preserved. This would consequently alter the testability properties of such circuits i.e. it may increase/decrease/maintain the same number of test input vectors needed for their exhaustive testability, subsequently affecting their generalized test vector computation. We do not consider the issue of design-for-testability here, but, instead focus on the power consumption of the final logic implementation, after realization with a conventional CMOS process technology (0.35 micron TSMC process). The quality of the resulting circuits evaluated on the basis of an established cost metric viz., power consumption, demonstrate average savings by 26.79% for the samples considered in this work, besides reduction in number of gates and input literals by 39.66% and 12.98% respectively, in comparison with other factored RM forms.

A Context-Aware Supplier Selection Model

Selection of the best possible set of suppliers has a significant impact on the overall profitability and success of any business. For this reason, it is usually necessary to optimize all business processes and to make use of cost-effective alternatives for additional savings. This paper proposes a new efficient context-aware supplier selection model that takes into account possible changes of the environment while significantly reducing selection costs. The proposed model is based on data clustering techniques while inspiring certain principles of online algorithms for an optimally selection of suppliers. Unlike common selection models which re-run the selection algorithm from the scratch-line for any decision-making sub-period on the whole environment, our model considers the changes only and superimposes it to the previously defined best set of suppliers to obtain a new best set of suppliers. Therefore, any recomputation of unchanged elements of the environment is avoided and selection costs are consequently reduced significantly. A numerical evaluation confirms applicability of this model and proves that it is a more optimal solution compared with common static selection models in this field.

Neural Networks for Short Term Wind Speed Prediction

Predicting short term wind speed is essential in order to prevent systems in-action from the effects of strong winds. It also helps in using wind energy as an alternative source of energy, mainly for Electrical power generation. Wind speed prediction has applications in Military and civilian fields for air traffic control, rocket launch, ship navigation etc. The wind speed in near future depends on the values of other meteorological variables, such as atmospheric pressure, moisture content, humidity, rainfall etc. The values of these parameters are obtained from a nearest weather station and are used to train various forms of neural networks. The trained model of neural networks is validated using a similar set of data. The model is then used to predict the wind speed, using the same meteorological information. This paper reports an Artificial Neural Network model for short term wind speed prediction, which uses back propagation algorithm.

Supply Chain Management: After Business Process Re-Engineering

This paper is prepared to provide a review of how an automotive manufacturer, ISUZU HICOM Malaysia Co. Ltd. sustained the supply chain management after business process reengineering in 2007. One of the authors is currently undergoing industrial attachment and has spent almost 6 months researching in the production and operation management system of the company. This study was carried out as part of the tasks in the attachment program. The result shows that delivery lateness and outsourcing are the main barriers that affected productivity. From the gap analysis, the authors found that new business process operation had improved suppliers delivery performance.

Evaluation of Curriculum Quality of Postgraduate Studies of Actuarial Science Field at Public Universities of Iran

Evaluation and survey of curriculum quality as one of the most important components of universities system is necessary for different levels in higher education. The main purpose of this study was to survey of the curriculum quality of Actuarial science field. Case: University of SHahid Beheshti and Higher education institute of Eco insurance (according to viewpoint of students, alumni, employers and faculty members). Descriptive statistics (mean, tables, percentage, and frequency distribution) and inferential statistics (CHI SQUARE) were used to analyze the data. Six criteria considered for the Quality of curriculum: objectives, content, teaching and learning methods, space and facilities, Time, assessment of learning. Content, teaching and learning methods, space and facilities, assessment of learning criteria were relatively desirable level, objectives and time criterions were desirable level. The quality of curriculum of Actuarial Science field was relatively desirable level.

Use of NMMO Pretreatment for Biogas Production from Oil Palm Empty Fruit Bunch

Pretreatment of oil palm empty fruit bunch (OPEFB) with N-Methylmorpholine-N-oxide (NMMO) to enhance biogas production was investigated. The pretreatments were performed at 90 and 120ºC for 1, 3, and 5 h using three different concentrations of NMMO of 73%, 79%, and 85%. The pretreated OPEFB was subsequently anaerobically digested to produce biogas. After pretreatment, there were no significant changes of the main composition of OPEFB and the maximum total solid recovery was 92%. The amorphous phase was increased up to 78% at pretreatment condition using 85% NMMO solution for 3 h at 120oC. In general, higher concentration of NMMO and higher temperature resulted in increased amorphous form and higher biogas production. The best results of biogas production reached enhancement of methane yield of 148% compared to the untreated OPEFB and increased in digestion of 94% compared to starch as reference.

Anticancer Effect of Doxorubicin Loaded Heparin based Super-paramagnetic Iron oxide Nanoparticles against the Human Ovarian Cancer Cells

This study determines the effect of naked and heparinbased super-paramagnetic iron oxide nanoparticles on the human cancer cell lines of A2780. Doxorubicin was used as the anticancer drug, entrapped in the SPIO-NPs. This study aimed to decorate nanoparticles with heparin, a molecular ligand for 'active' targeting of cancerous cells and the application of modified-nanoparticles in cancer treatment. The nanoparticles containing the anticancer drug DOX were prepared by a solvent evaporation and emulsification cross-linking method. The physicochemical properties of the nanoparticles were characterized by various techniques, and uniform nanoparticles with an average particle size of 110±15 nm with high encapsulation efficiencies (EE) were obtained. Additionally, a sustained release of DOX from the SPIO-NPs was successful. Cytotoxicity tests showed that the SPIO-DOX-HP had higher cell toxicity than the individual HP and confocal microscopy analysis confirmed excellent cellular uptake efficiency. These results indicate that HP based SPIO-NPs have potential uses as anticancer drug carriers and also have an enhanced anticancer effect.

Energy Efficient Clustering and Data Aggregation in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are wireless networks consisting of number of tiny, low cost and low power sensor nodes to monitor various physical phenomena like temperature, pressure, vibration, landslide detection, presence of any object, etc. The major limitation in these networks is the use of nonrechargeable battery having limited power supply. The main cause of energy consumption WSN is communication subsystem. This paper presents an efficient grid formation/clustering strategy known as Grid based level Clustering and Aggregation of Data (GCAD). The proposed clustering strategy is simple and scalable that uses low duty cycle approach to keep non-CH nodes into sleep mode thus reducing energy consumption. Simulation results demonstrate that our proposed GCAD protocol performs better in various performance metrics.

Turkish Adolescents' Subjective Well-Being with Respect to Age, Gender and SES of Parents

In this research it is aimed that the effect of some demographic factors on Turkish Adolescents' subjective well being is investigated. 432 adolescents who are 247 girls and 185 boys are participated in this study. They are ages 15-17, and also are high school students. The Positive and Negative Affect Scale and Life Satisfaction Scale are used for measuring adolescents' subjective well being. The ANOVA method is used in order to examine the effect of ages. For gender differences, independent t-test method is used, and finally the Pearson Correlation method is used so as to examine the effect of socio economic statues of adolescents' parents. According to results, there is no gender difference on adolescents' subjective well being. On the other hand, SES and age are effect significantly lover level on adolescents' subjective well being.

Structural Analysis of Stiffened FGM Thick Walled Cylinders by Application of a New Cylindrical Super Element

Structural behavior of ring stiffened thick walled cylinders made of functionally graded materials (FGMs) is investigated in this paper. Functionally graded materials are inhomogeneous composites which are usually made from a mixture of metal and ceramic. The gradient compositional variation of the constituents from one surface to the other provides an elegant solution to the problem of high transverse shear stresses that are induced when two dissimilar materials with large differences in material properties are bonded. FGM formation of the cylinder is modeled by power-law exponent and the variation of characteristics is supposed to be in radial direction. A finite element formulation is derived for the analysis. According to the property variation of the constituent materials in the radial direction of the wall, it is not convenient to use conventional elements to model and analyze the structure of the stiffened FGM cylinders. In this paper a new cylindrical super-element is used to model the finite element formulation and analyze the static and modal behavior of stiffened FGM thick walled cylinders. By using this super-element the number of elements, which are needed for modeling, will reduce significantly and the process time is less in comparison with conventional finite element formulations. Results for static and modal analysis are evaluated and verified by comparison to finite element formulation with conventional elements. Comparison indicates a good conformity between results.

Generator Capability Curve Constraint for PSO Based Optimal Power Flow

An optimal power flow (OPF) based on particle swarm optimization (PSO) was developed with more realistic generator security constraint using the capability curve instead of only Pmin/Pmax and Qmin/Qmax. Neural network (NN) was used in designing digital capability curve and the security check algorithm. The algorithm is very simple and flexible especially for representing non linear generation operation limit near steady state stability limit and under excitation operation area. In effort to avoid local optimal power flow solution, the particle swarm optimization was implemented with enough widespread initial population. The objective function used in the optimization process is electric production cost which is dominated by fuel cost. The proposed method was implemented at Java Bali 500 kV power systems contain of 7 generators and 20 buses. The simulation result shows that the combination of generator power output resulted from the proposed method was more economic compared with the result using conventional constraint but operated at more marginal operating point.

Control of Vibrations in Flexible Smart Structures using Fast Output Sampling Feedback Technique

This paper features the modeling and design of a Fast Output Sampling (FOS) Feedback control technique for the Active Vibration Control (AVC) of a smart flexible aluminium cantilever beam for a Single Input Single Output (SISO) case. Controllers are designed for the beam by bonding patches of piezoelectric layer as sensor / actuator to the master structure at different locations along the length of the beam by retaining the first 2 dominant vibratory modes. The entire structure is modeled in state space form using the concept of piezoelectric theory, Euler-Bernoulli beam theory, Finite Element Method (FEM) and the state space techniques by dividing the structure into 3, 4, 5 finite elements, thus giving rise to three types of systems, viz., system 1 (beam divided into 3 finite elements), system 2 (4 finite elements), system 3 (5 finite elements). The effect of placing the sensor / actuator at various locations along the length of the beam for all the 3 types of systems considered is observed and the conclusions are drawn for the best performance and for the smallest magnitude of the control input required to control the vibrations of the beam. Simulations are performed in MATLAB. The open loop responses, closed loop responses and the tip displacements with and without the controller are obtained and the performance of the proposed smart system is evaluated for vibration control.

Adaptive Impedance Control for Unknown Time-Varying Environment Position and Stiffness

This study is concerned with a new adaptive impedance control strategy to compensate for unknown time-varying environment stiffness and position. The uncertainties are expressed by Function Approximation Technique (FAT), which allows the update laws to be derived easily using Lyapunov stability theory. Computer simulation results are presented to validate the effectiveness of the proposed strategy.