Complexity Analysis of Some Known Graph Coloring Instances

Graph coloring is an important problem in computer science and many algorithms are known for obtaining reasonably good solutions in polynomial time. One method of comparing different algorithms is to test them on a set of standard graphs where the optimal solution is already known. This investigation analyzes a set of 50 well known graph coloring instances according to a set of complexity measures. These instances come from a variety of sources some representing actual applications of graph coloring (register allocation) and others (mycieleski and leighton graphs) that are theoretically designed to be difficult to solve. The size of the graphs ranged from ranged from a low of 11 variables to a high of 864 variables. The method used to solve the coloring problem was the square of the adjacency (i.e., correlation) matrix. The results show that the most difficult graphs to solve were the leighton and the queen graphs. Complexity measures such as density, mobility, deviation from uniform color class size and number of block diagonal zeros are calculated for each graph. The results showed that the most difficult problems have low mobility (in the range of .2-.5) and relatively little deviation from uniform color class size.

Physical and Mechanical Properties of Particleboard from Bamboo Waste

This research was to evaluate a technical feasibility of making single-layer experimental particleboard panels from bamboo waste (Dendrocalamus asper Backer) by converting bamboo into strips, which are used to make laminated bamboo furniture. Variable factors were density (600, 700 and 800 kg/m3) and temperature of condition (25, 40 and 55 °C). The experimental panels were tested for their physical and mechanical properties including modulus of elasticity (MOE), modulus of rupture (MOR), internal bonding strength (IB), screw holding strength (SH) and thickness swelling values according to the procedures defined by Japanese Industrial Standard (JIS). The test result of mechanical properties showed that the MOR, MOE and IB values were not in the set criteria, except the MOR values at the density of 700 kg/m3 at 25 °C and at the density of 800 kg/m3 at 25 and 40 °C, the IB values at the density of 600 kg/m3, at 40 °C, and at the density of 800 kg/m3 at 55 °C. The SH values had the test result according to the set standard, except with the density of 600 kg/m3, at 40 and 55 °C. Conclusively, a valuable renewable biomass, bamboo waste could be used to manufacture boards.

Finite Element Analysis of Thin Steel Plate Shear Walls

Steel plate shear walls (SPSWs) in buildings are known to be an effective means for resisting lateral forces. By using un-stiffened walls and allowing them to buckle, their energy absorption capacity will increase significantly due to the postbuckling capacity. The post-buckling tension field action of SPSWs can provide substantial strength, stiffness and ductility. This paper presents the Finite Element Analysis of low yield point (LYP) steel shear walls. In this shear wall system, the LYP steel plate is used for the steel panel and conventional structural steel is used for boundary frames. A series of nonlinear cyclic analyses were carried out to obtain the stiffness, strength, deformation capacity, and energy dissipation capacity of the LYP steel shear wall. The effect of widthto- thickness ratio of steel plate on buckling behavior, and energy dissipation capacities were studied. Good energy dissipation and deformation capacities were obtained for all models.

Exploring the Potential of Phase Change Memories as an Alternative to DRAM Technology

Scalability poses a severe threat to the existing DRAM technology. The capacitors that are used for storing and sensing charge in DRAM are generally not scaled beyond 42nm. This is because; the capacitors must be sufficiently large for reliable sensing and charge storage mechanism. This leaves DRAM memory scaling in jeopardy, as charge sensing and storage mechanisms become extremely difficult. In this paper we provide an overview of the potential and the possibilities of using Phase Change Memory (PCM) as an alternative for the existing DRAM technology. The main challenges that we encounter in using PCM are, the limited endurance, high access latencies, and higher dynamic energy consumption than that of the conventional DRAM. We then provide an overview of various methods, which can be employed to overcome these drawbacks. Hybrid memories involving both PCM and DRAM can be used, to achieve good tradeoffs in access latency and storage density. We conclude by presenting, the results of these methods that makes PCM a potential replacement for the current DRAM technology.

Electronic Government in the GCC Countries

The study investigated the practices of organisations in Gulf Cooperation Council (GCC) countries with regards to G2C egovernment maturity. It reveals that e-government G2C initiatives in the surveyed countries in particular, and arguably around the world in general, are progressing slowly because of the lack of a trusted and secure medium to authenticate the identities of online users. The authors conclude that national ID schemes will play a major role in helping governments reap the benefits of e-government if the three advanced technologies of smart card, biometrics and public key infrastructure (PKI) are utilised to provide a reliable and trusted authentication medium for e-government services.

Computational Networks for Knowledge Representation

In the artificial intelligence field, knowledge representation and reasoning are important areas for intelligent systems, especially knowledge base systems and expert systems. Knowledge representation Methods has an important role in designing the systems. There have been many models for knowledge such as semantic networks, conceptual graphs, and neural networks. These models are useful tools to design intelligent systems. However, they are not suitable to represent knowledge in the domains of reality applications. In this paper, new models for knowledge representation called computational networks will be presented. They have been used in designing some knowledge base systems in education for solving problems such as the system that supports studying knowledge and solving analytic geometry problems, the program for studying and solving problems in Plane Geometry, the program for solving problems about alternating current in physics.

An Approach for Transient Response Calculation of large Nonproportionally Damped Structures using Component Mode Synthesis

A minimal complexity version of component mode synthesis is presented that requires simplified computer programming, but still provides adequate accuracy for modeling lower eigenproperties of large structures and their transient responses. The novelty is that a structural separation into components is done along a plane/surface that exhibits rigid-like behavior, thus only normal modes of each component is sufficient to use, without computing any constraint, attachment, or residual-attachment modes. The approach requires only such input information as a few (lower) natural frequencies and corresponding undamped normal modes of each component. A novel technique is shown for formulation of equations of motion, where a double transformation to generalized coordinates is employed and formulation of nonproportional damping matrix in generalized coordinates is shown.

3D Numerical Simulation of Scouring around Bridge Piers (Case Study: Bridge 524 Crosses the Tanana River)

Due to the three- dimensional flow pattern interacting with bed material, the process of local scour around bridge piers is complex. Modeling 3D flow field and scour hole evolution around a bridge pier is more feasible nowadays because the computational cost and computational time have significantly decreased. In order to evaluate local flow and scouring around a bridge pier, a completely three-dimensional numerical model, SSIIM program, was used. The model solves 3-D Navier-Stokes equations and a bed load conservation equation. The model was applied to simulate local flow and scouring around a bridge pier in a large natural river with four piers. Computation for 1 day of flood condition was carried out to predict the maximum local scour depth. The results show that the SSIIM program can be used efficiently for simulating the scouring in natural rivers. The results also showed that among the various turbulence models, the k-ω model gives more reasonable results.

A Renovated Cook's Distance Based On The Buckley-James Estimate In Censored Regression

There have been various methods created based on the regression ideas to resolve the problem of data set containing censored observations, i.e. the Buckley-James method, Miller-s method, Cox method, and Koul-Susarla-Van Ryzin estimators. Even though comparison studies show the Buckley-James method performs better than some other methods, it is still rarely used by researchers mainly because of the limited diagnostics analysis developed for the Buckley-James method thus far. Therefore, a diagnostic tool for the Buckley-James method is proposed in this paper. It is called the renovated Cook-s Distance, (RD* i ) and has been developed based on the Cook-s idea. The renovated Cook-s Distance (RD* i ) has advantages (depending on the analyst demand) over (i) the change in the fitted value for a single case, DFIT* i as it measures the influence of case i on all n fitted values Yˆ∗ (not just the fitted value for case i as DFIT* i) (ii) the change in the estimate of the coefficient when the ith case is deleted, DBETA* i since DBETA* i corresponds to the number of variables p so it is usually easier to look at a diagnostic measure such as RD* i since information from p variables can be considered simultaneously. Finally, an example using Stanford Heart Transplant data is provided to illustrate the proposed diagnostic tool.

All Proteins Have a Basic Molecular Formula

This study proposes a basic molecular formula for all proteins. A total of 10,739 proteins belonging to 9 different protein groups classified on the basis of their functions were selected randomly. They included enzymes, storage proteins, hormones, signalling proteins, structural proteins, transport proteins, immunoglobulins or antibodies, motor proteins and receptor proteins. After obtaining the protein molecular formula using the ProtParam tool, the H/C, N/C, O/C, and S/C ratios were determined for each randomly selected sample. In this case, H, N, O, and S coefficients were specified per carbon atom. Surprisingly, the results demonstrated that H, N, O, and S coefficients for all 10,739 proteins are similar and highly correlated. This study demonstrates that despite differences in the structure and function, all known proteins have a similar basic molecular formula CnH1.58 ± 0.015nN0.28 ± 0.005nO0.30 ± 0.007nS0.01 ± 0.002n. The total correlation between all coefficients was found to be 0.9999.

Adaptation Learning Speed Control for a High- Performance Induction Motor using Neural Networks

This paper proposes an effective adaptation learning algorithm based on artificial neural networks for speed control of an induction motor assumed to operate in a high-performance drives environment. The structure scheme consists of a neural network controller and an algorithm for changing the NN weights in order that the motor speed can accurately track of the reference command. This paper also makes uses a very realistic and practical scheme to estimate and adaptively learn the noise content in the speed load torque characteristic of the motor. The availability of the proposed controller is verified by through a laboratory implementation and under computation simulations with Matlab-software. The process is also tested for the tracking property using different types of reference signals. The performance and robustness of the proposed control scheme have evaluated under a variety of operating conditions of the induction motor drives. The obtained results demonstrate the effectiveness of the proposed control scheme system performances, both in steady state error in speed and dynamic conditions, was found to be excellent and those is not overshoot.

Synthesis and Analysis of Swelling and Controlled Release Behaviour of Anionic sIPN Acrylamide based Hydrogels

In modern agriculture, polymeric hydrogels are known as a component able to hold an amount of water due to their 3-dimensional network structure and their tendency to absorb water in humid environments. In addition, these hydrogels are able to controllably release the fertilisers and pesticides loaded in them. Therefore, they deliver these materials to the plants' roots and help them with growing. These hydrogels also reduce the pollution of underground water sources by preventing the active components from leaching. In this study, sIPN acrylamide based hydrogels are synthesised by using acrylamide free radical, potassium acrylate, and linear polyvinyl alcohol. Ammonium nitrate is loaded in the hydrogel as the fertiliser. The effect of various amounts of monomers and linear polymer, measured in molar ratio, on the swelling rate, equilibrium swelling, and release of ammonium nitrate is studied.

Increasing Profitability Supported by Innovative Methods and Designing Monitoring Software in Condition-Based Maintenance: A Case Study

In the present article, a new method has been developed to enhance the application of equipment monitoring, which in turn results in improving condition-based maintenance economic impact in an automobile parts manufacturing factory. This study also describes how an effective software with a simple database can be utilized to achieve cost-effective improvements in maintenance performance. The most important results of this project are indicated here: 1. 63% reduction in direct and indirect maintenance costs. 2. Creating a proper database to analyse failures. 3. Creating a method to control system performance and develop it to similar systems. 4. Designing a software to analyse database and consequently create technical knowledge to face unusual condition of the system. Moreover, the results of this study have shown that the concept and philosophy of maintenance has not been understood in most Iranian industries. Thus, more investment is strongly required to improve maintenance conditions.

Self-Adaptive Differential Evolution Based Power Economic Dispatch of Generators with Valve-Point Effects and Multiple Fuel Options

This paper presents the solution of power economic dispatch (PED) problem of generating units with valve point effects and multiple fuel options using Self-Adaptive Differential Evolution (SDE) algorithm. The global optimal solution by mathematical approaches becomes difficult for the realistic PED problem in power systems. The Differential Evolution (DE) algorithm is found to be a powerful evolutionary algorithm for global optimization in many real problems. In this paper the key parameters of control in DE algorithm such as the crossover constant CR and weight applied to random differential F are self-adapted. The PED problem formulation takes into consideration of nonsmooth fuel cost function due to valve point effects and multi fuel options of generator. The proposed approach has been examined and tested with the numerical results of PED problems with thirteen-generation units including valve-point effects, ten-generation units with multiple fuel options neglecting valve-point effects and ten-generation units including valve-point effects and multiple fuel options. The test results are promising and show the effectiveness of proposed approach for solving PED problems.

Intelligent Agent Approach to the Control of Critical Infrastructure Networks

In this paper we propose an intelligent agent approach to control the electric power grid at a smaller granularity in order to give it self-healing capabilities. We develop a method using the influence model to transform transmission substations into information processing, analyzing and decision making (intelligent behavior) units. We also develop a wireless communication method to deliver real-time uncorrupted information to an intelligent controller in a power system environment. A combined networking and information theoretic approach is adopted in meeting both the delay and error probability requirements. We use a mobile agent approach in optimizing the achievable information rate vector and in the distribution of rates to users (sensors). We developed the concept and the quantitative tools require in the creation of cooperating semiautonomous subsystems which puts the electric grid on the path towards intelligent and self-healing system.

Surfactant Stabilized Nanoemulsion: Characterization and Application in Enhanced Oil Recovery

Nanoemulsions are a class of emulsions with a droplet size in the range of 50–500 nm and have attracted a great deal of attention in recent years because it is unique characteristics. The physicochemical properties of nanoemulsion suggests that it can be successfully used to recover the residual oil which is trapped in the fine pore of reservoir rock by capillary forces after primary and secondary recovery. Oil-in-water nanoemulsion which can be formed by high-energy emulsification techniques using specific surfactants can reduce oil-water interfacial tension (IFT) by 3-4 orders of magnitude. The present work is aimed on characterization of oil-inwater nanoemulsion in terms of its phase behavior, morphological studies; interfacial energy; ability to reduce the interfacial tension and understanding the mechanisms of mobilization and displacement of entrapped oil blobs by lowering interfacial tension both at the macroscopic and microscopic level. In order to investigate the efficiency of oil-water nanoemulsion in enhanced oil recovery (EOR), experiments were performed to characterize the emulsion in terms of their physicochemical properties and size distribution of the dispersed oil droplet in water phase. Synthetic mineral oil and a series of surfactants were used to prepare oil-in-water emulsions. Characterization of emulsion shows that it follows pseudo-plastic behaviour and drop size of dispersed oil phase follows lognormal distribution. Flooding experiments were also carried out in a sandpack system to evaluate the effectiveness of the nanoemulsion as displacing fluid for enhanced oil recovery. Substantial additional recoveries (more than 25% of original oil in place) over conventional water flooding were obtained in the present investigation.

Social Interventation from Social Maternage to Peer Advocacy

The aim of this paper is to study in depth some methodological aspects of social interventation, focusing on desirable passage from social maternage method to peer advocacy method. For this purpose, we intend analyze social and organizative components, that affect operator-s professional action and that are part of his psychological environment, besides the physical and social one. In fact, operator-s interventation should not be limited to a pure supply of techniques, nor to take shape as improvised action, but “full of good purposes".

Remarks on Some Properties of Decision Rules

This paper shows that some properties of the decision rules in the literature do not hold by presenting a counterexample. We give sufficient and necessary conditions under which these properties are valid. These results will be helpful when one tries to choose the right decision rules in the research of rough set theory.

Geochemistry of Tektites from Maoming of Guandong Province, China

We measured the major and trace element contents and Rb-Sr isotopic compositions of 12 tektites from the Maoming area, Guandong province (south China). All the samples studied are splash-form tektites which show pitted or grooved surfaces with schlieren structures on some surfaces. The trace element ratios Ba/Rb (avg. 4.33), Th/Sm (avg. 2.31), Sm/Sc (avg. 0.44), Th/Sc (avg. 1.01) , La/Sc (avg. 2.86), Th/U (avg. 7.47), Zr/Hf (avg. 46.01) and the rare earth elements (REE) contents of tektites of this study are similar to the average upper continental crust. From the chemical composition, it is suggested that tektites in this study are derived from similar parental terrestrial sedimentary deposit which may be related to post-Archean upper crustal rocks. The tektites from the Maoming area have high positive εSr(0) values-ranging from 176.9~190.5 which indicate that the parental material for these tektites have similar Sr isotopic compositions to old terrestrial sedimentary rocks and they were not dominantly derived from recent young sediments (such as soil or loess). The Sr isotopic data obtained by the present study support the conclusion proposed by Blum et al. (1992)[1] that the depositional age of sedimentary target materials is close to 170Ma (Jurassic). Mixing calculations based on the model proposed by Ho and Chen (1996)[2] for various amounts and combinations of target rocks indicate that the best fit for tektites from the Maoming area is a mixture of 40% shale, 30% greywacke, 30% quartzite.

Puff Noise Detection and Cancellation for Robust Speech Recognition

In this paper, an algorithm for detecting and attenuating puff noises frequently generated under the mobile environment is proposed. As a baseline system, puff detection system is designed based on Gaussian Mixture Model (GMM), and 39th Mel Frequency Cepstral Coefficient (MFCC) is extracted as feature parameters. To improve the detection performance, effective acoustic features for puff detection are proposed. In addition, detected puff intervals are attenuated by high-pass filtering. The speech recognition rate was measured for evaluation and confusion matrix and ROC curve are used to confirm the validity of the proposed system.