Generalized ACE Constrained Progressive Edge-Growth LDPC Code Design

In this letter, we propose a generalization of the progressive edge-growth (PEG) algorithm with the aim of designing LDPC code graphs with substantially improved approximated cycle extrinsic message degree (ACE) properties. The proposed realization of generalized PEG algorithm outperforms original PEG algorithm and its subsequent modification proposed by Xiao and Banihashemi.     

Modified Transition Matrix Simulations of Communication Systems

We apply appropriately enhanced transition matrix and multicanonical methods to communication systems. Our procedure not only predicts time-independent quantities such as the bit-error-probability but can also be applied to dynamic effects such as the distribution of fading times.     

A robust algorithm for text region detection in natural scene images

In this paper, a new method for detecting text regions in natural scene images is presented. The proposed algorithm is based on the segmentation of objects in a scene, followed by the identification of text objects by a support vector machine (SVM). First, to segment objects in the scene, the input image is separated into chromatic and achromatic regions according to the distribution of red, green and blue (RGB) elements, and different clustering algorithms are applied. Second, each object is transformed into the wavelet domain for multi-resolution analysis, and moment features of the wavelet coefficients are used in the SVM for the classification of text objects. The proposed approach provides robustness to non-uniform illumination by using different clustering algorithms according to the characteristics of the colour components in the segmentation. Also, moment features, used for classification, are invariant to the size, direction, shape and other properties of texts. Experimental results demonstrate the effectiveness of this approach.     

Implementation of adaptive critic-based neurocontrollers for turbogenerators in a multimachine power system

This paper presents the design and practical hardware implementation of optimal neurocontrollers that replace the conventional automatic voltage regulator (AVR) and the turbine governor of turbogenerators on multimachine power systems. The neurocontroller design uses a powerful technique of the adaptive critic design (ACD) family called dual heuristic programming (DHP). The DHP neurocontrollers' training and testing are implemented on the Innovative Integration M67 card consisting of the TMS320C6701 processor. The measured results show that the DHP neurocontrollers are robust and their performance does not degrade unlike the conventional controllers even when a power system stabilizer (PSS) is included, for changes in system operating conditions and configurations. This paper also shows that it is possible to design and implement optimal neurocontrollers for multiple turbogenerators in real time, without having to do continually online training of the neural networks, thus avoiding risks of instability.     

Distributed Transmit Antenna Selection (DTAS) Under Performance or Energy Consumption Constraints

Motivated by the transmit antenna selection (TAS) concept, used in Multiple-Input-Multiple-Output systems, we argue for distributed transmit antenna selection (DTAS), which corresponds to a method of selecting a subset of available relays in cooperative diversity systems. Assuming amplify and forward relays, the proposed selection method represents a low-complexity tool for determining the optimum relaying set. Two optimization problems are studied: the error probability minimization subject to total energy consumption constraints, and the dual one, the total energy consumption minimization under error performance constraints. Numerical examples verify the advantage of the proposed method in adapting the number of relaying terminals to the desired performance-consumption tradeoff.     

Prediction and quality control of the melt index during production of high-density polyethylene

In polyolefin processes the melt index (MI) is the most important control variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the 1 ^st -order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. The virtual sensor model developed based on the estimation scheme was combined with the virtual on-line analyzer (VOA) to give a quality control system to be implemented in the actual HDPE plant. From the application of the present control system, significant reduction of transition time and the amount of off-spec during grade changes was achieved     

Simultaneous degradation of nitroaromatic compounds TNT,RDX, atrazine,and simazine by Pseudomonas putida HK‐6 in bench‐scale bioreactors

BACKGROUND: Environmental contamination by nitroaromatic compounds such as 2,4,6‐trinitrotoluene (TNT), hexahydro‐1,3,5‐trinitro‐1,3,5‐s‐triazine (RDX), atrazine, and/or simazine (TRAS) generated as waste from military and agricultural activities is a serious worldwide problem. Microbiological treatment of these compounds is an attractive method because many explosives and herbicides are biodegradable and the process can be made cost‐effective. We explored the feasibility of using cultures of Pseudomonas putida HK‐6 for simultaneous degradation of TRAS with the aim of microbial application in wastewater treatment in bench‐scale bioreactors. RESULTS: Experiments were conducted to study the effects of supplemental carbons, nitrogens, and Tween‐80 on the degradation of Ps. putida HK‐6 in media containing TRAS as target substrate(s). The most effective TRAS degradation was shown in the presence of molasses. Addition of nitrogen sources produced a delayed effect for the target substrate(s). Tween‐80 enhanced the degradation of target substrate(s). Simultaneous degradation of these compounds proceeded to completion within the given period. CONCLUSIONS: Ps. putida HK‐6 was capable of growth with TRAS, and the effects of supplements on TRAS degradation and simultaneous TRAS degradation were evaluated in bench‐scale bioreactors. The results of this study have practical applications in the processes of industrial waste stream treatment where the disposal of TRAS may be problematic. Copyright © 2008 Society of Chemical Industry     

Interval based MINLP superstructure synthesis of mass exchange networks

A new simultaneous synthesis approach for mass exchange networks (MENs) is presented. The technique is adapted from the interval based mixed integer non-linear program (MINLP) superstructure (IBMS) synthesis of heat exchanger networks (HENs). The superstructure interval boundary compositions are defined by the supply and target compositions of either the rich or lean set of streams. Each rich and lean stream in the superstructure has the potential of exchanging mass with streams of opposite kind in each interval based on mass transfer feasibility. The model harnesses the strengths of the stagewise superstructure and the pinch technology methods for mass exchange network synthesis (MENS). The IBMS approach simultaneously trades-off the capital and operating costs for MENs. The superstructure composition interval defining approach introduced in this paper enforces the mixing of split streams at equal compositions, hence there is no need to include mixing equations in the model. Fixing the interval boundaries helps to eliminate the complexities involved in initialisations, thus the region of search for the optimum solution is reduced. The IBMS model is applied to MENS problems involving continuous contact and staged columns. It is also extended to problems involving multiple mass separating agents (MSAs) and regeneration. The results obtained compare well with those in the literature.