CO2 Sequestration Potential of Construction and Demolition Alkaline Waste Material in Indian Perspective

In order to avoid the potentially devastating consequences of global warming and climate change, the carbon dioxide “CO2" emissions caused due to anthropogenic activities must be reduced considerably. This paper presents the first study examining the feasibility of carbon sequestration in construction and demolition “C&D" waste. Experiments were carried out in a self fabricated Batch Reactor at 40ºC, relative humidity of 50-70%, and flow rate of CO2 at 10L/min for 1 hour for water-to-solids ratio of 0.2 to 1.2. The effect of surface area was found by comparing the theoretical extent of carbonation of two different sieve sizes (0.3mm and 2.36mm) of C&D waste. A 38.44% of the theoretical extent of carbonation equating to 4% CO2 sequestration extent was obtained for C&D waste sample for 0.3mm sieve size. Qualitative, quantitative and morphological analyses were done to validate carbonate formation using X-ray diffraction “X.R.D.," thermal gravimetric analysis “T.G.A., “X-Ray Fluorescence Spectroscopy “X.R.F.," and scanning electron microscopy “S.E.M".

The Study of the Discrete Risk Model with Random Income

In this paper, we extend the compound binomial model to the case where the premium income process, based on a binomial process, is no longer a linear function. First, a mathematically recursive formula is derived for non ruin probability, and then, we examine the expected discounted penalty function, satisfy a defect renewal equation. Third, the asymptotic estimate for the expected discounted penalty function is then given. Finally, we give two examples of ruin quantities to illustrate applications of the recursive formula and the asymptotic estimate for penalty function.

Improved Robust Stability Criteria for Discrete-time Neural Networks

In this paper, the robust exponential stability problem of uncertain discrete-time recurrent neural networks with timevarying delay is investigated. By constructing a new augmented Lyapunov-Krasovskii function, some new improved stability criteria are obtained in forms of linear matrix inequality (LMI). Compared with some recent results in literature, the conservatism of the new criteria is reduced notably. Two numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results.

The Approximate Solution of Linear Fuzzy Fredholm Integral Equations of the Second Kind by Using Iterative Interpolation

in this paper, we propose a numerical method for the approximate solution of fuzzy Fredholm functional integral equations of the second kind by using an iterative interpolation. For this purpose, we convert the linear fuzzy Fredholm integral equations to a crisp linear system of integral equations. The proposed method is illustrated by some fuzzy integral equations in numerical examples.

A Study of Various Numerical Turbulence Modeling Methods in Boundary Layer Excitation of a Square Ribbed Channel

Among the various cooling processes in industrial applications such as: electronic devices, heat exchangers, gas turbines, etc. Gas turbine blades cooling is the most challenging one. One of the most common practices is using ribbed wall because of the boundary layer excitation and therefore making the ultimate cooling. Vortex formation between rib and channel wall will result in a complicated behavior of flow regime. At the other hand, selecting the most efficient method for capturing the best results comparing to experimental works would be a fascinating issue. In this paper 4 common methods in turbulence modeling: standard k-e, rationalized k-e with enhanced wall boundary layer treatment, k-w and RSM (Reynolds stress model) are employed to a square ribbed channel to investigate the separation and thermal behavior of the flow in the channel. Finally all results from different methods which are used in this paper will be compared with experimental data available in literature to ensure the numerical method accuracy.

Research Topic Map Construction

While the explosive increase in information published on the Web, researchers have to filter information when searching for conference related information. To make it easier for users to search related information, this paper uses Topic Maps and social information to implement ontology since ontology can provide the formalisms and knowledge structuring for comprehensive and transportable machine understanding that digital information requires. Besides enhancing information in Topic Maps, this paper proposes a method of constructing research Topic Maps considering social information. First, extract conference data from the web. Then extract conference topics and the relationships between them through the proposed method. Finally visualize it for users to search and browse. This paper uses ontology, containing abundant of knowledge hierarchy structure, to facilitate researchers getting useful search results. However, most previous ontology construction methods didn-t take “people" into account. So this paper also analyzes the social information which helps researchers find the possibilities of cooperation/combination as well as associations between research topics, and tries to offer better results.

Newton-Raphson State Estimation Solution Employing Systematically Constructed Jacobian Matrix

Newton-Raphson State Estimation method using bus admittance matrix remains as an efficient and most popular method to estimate the state variables. Elements of Jacobian matrix are computed from standard expressions which lack physical significance. In this paper, elements of the state estimation Jacobian matrix are obtained considering the power flow measurements in the network elements. These elements are processed one-by-one and the Jacobian matrix H is updated suitably in a simple manner. The constructed Jacobian matrix H is integrated with Weight Least Square method to estimate the state variables. The suggested procedure is successfully tested on IEEE standard systems.

Improvements in Material Handling: A Case Study of Cement Manufacturing Plant

The globalization of the Indian economy has thrown a great challenge to the Indian industries in respect of productivity, quality, cost, delivery etc. Achieving success• the global market has required fundamental shift in the way business is conducted and has dramatically affected virtually every aspect of process industry. The internal manufacturing process and supporting infrastructure should be such that it can compete successfully in global markets with better flexibility and delivery. The paper deals with a case study of a reputed process industry, some changes in the process has been suggested, which leads to reduction in labor cost and production cost.

Novel Adaptive Channel Equalization Algorithms by Statistical Sampling

In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.

Application of Genetic Engineering for Chromium Removal from Industrial Wastewater

The treatment of the industrial wastewater can be particularly difficult in the presence of toxic compounds. Excessive concentration of Chromium in soluble form is toxic to a wide variety of living organisms. Biological removal of heavy metals using natural and genetically engineered microorganisms has aroused great interest because of its lower impact on the environment. Ralston metallidurans, formerly known as Alcaligenes eutrophus is a LProteobacterium colonizing industrial wastewater with a high content of heavy metals. Tris-buffered mineral salt medium was used for growing Alcaligenes eutrophus AE104 (pEBZ141). The cells were cultivated for 18 h at 30 oC in Tris-buffered mineral salt medium containing 3 mM disodium sulphate and 46 mM sodium gluconate as the carbon source. The cells were harvested by centrifugation, washed, and suspended in 10 mM Tris HCl, pH 7.0, containing 46 mM sodium gluconate, and 5 mM Chromium. Interaction among induction of chr resistance determinant, and chromate reduction have been demonstrated. Results of this study show that the above bacteria can be very useful for bioremediation of chromium from industrial wastewater.

Prediction of Protein Subchloroplast Locations using Random Forests

Protein subchloroplast locations are correlated with its functions. In contrast to the large amount of available protein sequences, the information of their locations and functions is less known. The experiment works for identification of protein locations and functions are costly and time consuming. The accurate prediction of protein subchloroplast locations can accelerate the study of functions of proteins in chloroplast. This study proposes a Random Forest based method, ChloroRF, to predict protein subchloroplast locations using interpretable physicochemical properties. In addition to high prediction accuracy, the ChloroRF is able to select important physicochemical properties. The important physicochemical properties are also analyzed to provide insights into the underlying mechanism.

Switching Rule for the Exponential Stability and Stabilization of Switched Linear Systems with Interval Time-varying Delays

This paper is concerned with exponential stability and stabilization of switched linear systems with interval time-varying delays. The time delay is any continuous function belonging to a given interval, in which the lower bound of delay is not restricted to zero. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton-s formula, a switching rule for the exponential stability and stabilization of switched linear systems with interval time-varying delays and new delay-dependent sufficient conditions for the exponential stability and stabilization of the systems are first established in terms of LMIs. Numerical examples are included to illustrate the effectiveness of the results.

On Adaptive Optimization of Filter Performance Based on Markov Representation for Output Prediction Error

This paper addresses the problem of how one can improve the performance of a non-optimal filter. First the theoretical question on dynamical representation for a given time correlated random process is studied. It will be demonstrated that for a wide class of random processes, having a canonical form, there exists a dynamical system equivalent in the sense that its output has the same covariance function. It is shown that the dynamical approach is more effective for simulating and estimating a Markov and non- Markovian random processes, computationally is less demanding, especially with increasing of the dimension of simulated processes. Numerical examples and estimation problems in low dimensional systems are given to illustrate the advantages of the approach. A very useful application of the proposed approach is shown for the problem of state estimation in very high dimensional systems. Here a modified filter for data assimilation in an oceanic numerical model is presented which is proved to be very efficient due to introducing a simple Markovian structure for the output prediction error process and adaptive tuning some parameters of the Markov equation.

A Transform-Free HOC Scheme for Incompressible Viscous Flow past a Rotationally Oscillating Circular Cylinder

A numerical study is made of laminar, unsteady flow behind a rotationally oscillating circular cylinder using a recently developed higher order compact (HOC) scheme. The stream function vorticity formulation of Navier-Stokes (N-S) equations in cylindrical polar coordinates are considered as the governing equations. The temporal behaviour of vortex formation and relevant streamline patterns of the flow are scrutinized over broad ranges of two externally specified parameters namely dimensionless forced oscillating frequency Sf and dimensionless peak rotation rate αm for the Reynolds-s number Re = 200. Excellent agreements are found both qualitatively and quantitatively with the existing experimental and standard numerical results.

Questions in the School

Paper deals with the topic of questions as important components of information behavior in the school. By analyzing the Corpus Schola2010, the state of contemporary education in terms of questioning is proven unsatisfactory: 80% of the questions are asked by teachers; most of teacher-s questions are asked at the beginning of the first grade, than their number decreases and is settling down on 80±10 questions per lesson. The average number of questions within one lesson per one pupil is generally less than one whole question. The highest values are achieved in the first, sixth, eighth and tenth grade,, i.e. in the transition years in which pupils are moving into higher levels of education and every following year it declines. We can state Czech school do not support questioning and question skill of their pupils, thereby typical Czech schools are neglecting the development of thinking, reasoning and cooperation of their pupils.

Evaluation of Optimal Residence Time in a Hot Rolled Reheating Furnace

To calculate the temperature distribution of the slab in a hot rolled reheating furnace a mathematical model has been developed by considering the thermal radiation in the furnace and transient conduction in the slab. The furnace is modeled as radiating medium with spatially varying temperature. Radiative heat flux within the furnace including the effect of furnace walls, combustion gases, skid beams and buttons is calculated using the FVM and is applied as the boundary condition of the transient conduction equation of the slab. After determining the slab emissivity by comparison between simulation and experimental work, variation of heating characteristics in the slab is investigated in the case of changing furnace temperature with various time and the slab residence time is optimized with this evaluation.

Uncertainty Propagation and Sensitivity Analysis During Calibration of an Integrated Land Use and Transport Model

In this work, propagation of uncertainty during calibration process of TRANUS, an integrated land use and transport model (ILUTM), has been investigated. It has also been examined, through a sensitivity analysis, which input parameters affect the variation of the outputs the most. Moreover, a probabilistic verification methodology of calibration process, which equates the observed and calculated production, has been proposed. The model chosen as an application is the model of the city of Grenoble, France. For sensitivity analysis and uncertainty propagation, Monte Carlo method was employed, and a statistical hypothesis test was used for verification. The parameters of the induced demand function in TRANUS, were assumed as uncertain in the present case. It was found that, if during calibration, TRANUS converges, then with a high probability the calibration process is verified. Moreover, a weak correlation was found between the inputs and the outputs of the calibration process. The total effect of the inputs on outputs was investigated, and the output variation was found to be dictated by only a few input parameters.

A Novel Reversible Watermarking Method based on Adaptive Thresholding and Companding Technique

Embedding and extraction of a secret information as well as the restoration of the original un-watermarked image is highly desirable in sensitive applications like military, medical, and law enforcement imaging. This paper presents a novel reversible data-hiding method for digital images using integer to integer wavelet transform and companding technique which can embed and recover the secret information as well as can restore the image to its pristine state. The novel method takes advantage of block based watermarking and iterative optimization of threshold for companding which avoids histogram pre and post-processing. Consequently, it reduces the associated overhead usually required in most of the reversible watermarking techniques. As a result, it keeps the distortion small between the marked and the original images. Experimental results show that the proposed method outperforms the existing reversible data hiding schemes reported in the literature.

A Vehicular Visual Tracking System Incorporating Global Positioning System

Surveillance system is widely used in the traffic monitoring. The deployment of cameras is moving toward a ubiquitous camera (UbiCam) environment. In our previous study, a novel service, called GPS-VT, was firstly proposed by incorporating global positioning system (GPS) and visual tracking techniques for the UbiCam environment. The first prototype is called GODTA (GPS-based Moving Object Detection and Tracking Approach). For a moving person carried GPS-enabled mobile device, he can be tracking when he enters the field-of-view (FOV) of a camera according to his real-time GPS coordinate. In this paper, GPS-VT service is applied to the tracking of vehicles. The moving speed of a vehicle is much faster than a person. It means that the time passing through the FOV is much shorter than that of a person. Besides, the update interval of GPS coordinate is once per second, it is asynchronous with the frame rate of the real-time image. The above asynchronous is worsen by the network transmission delay. These factors are the main challenging to fulfill GPS-VT service on a vehicle.In order to overcome the influence of the above factors, a back-propagation neural network (BPNN) is used to predict the possible lane before the vehicle enters the FOV of a camera. Then, a template matching technique is used for the visual tracking of a target vehicle. The experimental result shows that the target vehicle can be located and tracking successfully. The success location rate of the implemented prototype is higher than that of the previous GODTA.

A Search Algorithm for Solving the Economic Lot Scheduling Problem with Reworks under the Basic Period Approach

In this study, we are interested in the economic lot scheduling problem (ELSP) that considers manufacturing of the serviceable products and remanufacturing of the reworked products. In this paper, we formulate a mathematical model for the ELSP with reworks using the basic period approach. In order to solve this problem, we propose a search algorithm to find the cyclic multiplier ki of each product that can be cyclically produced for every ki basic periods. This research also uses two heuristics to search for the optimal production sequence of all lots and the optimal time length of the basic period so as to minimize the average total cost. This research uses a numerical example to show the effectiveness of our approach.