On-line multi-variable predictive control of molar mass and particle size distributions in free-radical emulsion copolymerization

A multi-variable model predictive control (MPC) was formulated to solve control problems associated with a combination of regulation and targeting desired set-points. We investigated the simultaneous control of key polymer properties: the particle size (PSD) and molecular weight distribution (MWD) by manipulating the flow rates of the monomers (styrene, MMA), surfactant, initiator and the temperature of the reactor. A multi-input-multi-output (MIMO) formulation was constructed for the constrained optimal control problem to maximize the width of the PSD (with M_n at a constant set-point), and to maximize the average molar mass. The strategy developed within a gPROMS-API-DCS environment allowed real-time implementation of model-based control of the process. The optimal control problem was implemented via an interface to a dynamic optimization code. Major improvements in process operation and polymer property control resulted on the implementation of our multi-variable MPC algorithm. The manipulation of the four flow rates and the temperature increased the degree of freedom in the system and achieved tighter PSD and MWD control. The on-line performance of MPC for MWD and PSD control was found to be satisfactory.     

The effectiveness of software metrics in identifying error-prone classes in post-release software evolution process

Many empirical studies have found that software metrics can predict class error proneness and the prediction can be used to accurately group error-prone classes. Recent empirical studies have used open source systems. These studies, however, focused on the relationship between software metrics and class error proneness during the development phase of software projects. Whether software metrics can still predict class error proneness in a system’s post-release evolution is still a question to be answered. This study examined three releases of the Eclipse project and found that although some metrics can still predict class error proneness in three error-severity categories, the accuracy of the prediction decreased from release to release. Furthermore, we found that the prediction cannot be used to build a metrics model to identify error-prone classes with acceptable accuracy. These findings suggest that as a system evolves, the use of some commonly used metrics to identify which classes are more prone to errors becomes increasingly difficult and we should seek alternative methods (to the metric-prediction models) to locate error-prone classes if we want high accuracy.     

Designing genetic regulatory networks using fuzzy Petri nets approach

In this paper, we have successfully presented a fuzzy Petri net (FPN) model to design the genetic regulatory network. Based on the FPN model, an efficient algorithm is proposed to automatically reason about imprecise and fuzzy information. By using the reasoning algorithm for the FPN, we present an alternative approach that is more promising than the fuzzy logic. The proposed FPN approach offers more flexible reasoning capability because it is able to obtain results with fuzzy intervals rather than point values. In this paper, a novel model with a new concept of hidden fuzzy transition (HFT) to design the genetic regulatory network is developed. We have built the FPN model and classified the input data in terms of time point and obtained the output data, so the system can be viewed as the two-input and one output system. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. The experimental results show the proposed approach is feasible and acceptable to design the genetic regulatory network and investigate the dynamical behaviors of gene network.     

Extraction,optimisation and characterisation of phenolics from Thymus vulgaris L.: phenolic content and profiles in relation to antioxidant,antidiabetic and antihypertensive properties

The objectives of this study were to examine varying extraction conditions of Thymus vulgaris L. as related to phenolic content and profiles of the extracts and their antioxidant, antihypertensive and antidiabetic properties. Phenolics were extracted under various conditions pertaining to free and bound phenolics, solvent type and combination of extraction time and temperature, and these extracts were evaluated in terms of their antioxidant activities and inhibitory activities of angiotensin‐converting enzyme (ACE), α‐glucosidase and α‐amylase. The acetone–water solvent mixture (1:1; v/v) produced the extract with the greatest phenolic content, antioxidant activity and inhibitory activities of ACE and α‐glucosidase. The optimal extraction temperature for maximum phenolic content and antioxidant activity associated with methanol extraction was 60 °C, whereas a lower temperature at 40 °C was required to maximise inhibitory activities for ACE, α‐glucosidase and α‐amylase. An inverse relationship was seen between antioxidant and glucosidase inhibitory activities vs. the ACE and α‐amylase inhibitory activities, which suggests the need for extractions to be directed to specific bioactivities of thyme extracts. Generally, the results indicate major differences in phenolic profiles among the tested extraction conditions with thymol as the predominant phenolic seen in most extractions, while gallic acid, rosmarinic acid or diosmin also predominated in other extracts. Extracts with the same predominant phenolic compound and similar phenolic content showed major disparities in their ACE, glucosidase and α‐amylase inhibitory activities, indicating that the major phenolic profiles of thyme extracts may not be necessarily related to the degree of inhibition of ACE, glucosidase and α‐amylase enzymes.     

Simplified gateway selection scheme for multihop relay in vehicular ad hoc network

Integrating vehicular ad hoc network (VANET) and universal mobile telecommunication system (UMTS) could be a promising architecture for future machine‐to‐machine applications. This integration can help vehicles have steady Internet connection through the UMTS network and in communicating with other vehicles. However, dead spot areas and unsuccessful handoff processes caused by the high speed of vehicles can disrupt the implementation of this kind of architecture. In this paper, a new simplified gateway selection (SGS) scheme for multihop relay in a VANET‐UMTS integration network is proposed. The proposed scheme extends the coverage or/and calming of the frequent handoff process and allows vehicles to continue to be connected to the UMTS infrastructure network. An integrated simulation environment that combines VanetMobiSim and NS2 is used to simulate and evaluate the proposed scheme. The simulation results show that the SGS scheme performed better when it was implemented with ad hoc on a demand distance vector routing and destination‐sequenced distance vector routing protocols. Furthermore, the SGS scheme is compared with other cluster‐based gateway selections used in the previous works. The results show that our SGS scheme outperforms other cluster‐based gateway selections scheme in terms of selection delay, control packet overhead, packet delivery ratio, and overall throughput. Copyright © 2013 John Wiley & Sons, Ltd.     

Speech compression exploiting linear prediction coefficients codebook and hamming correction code algorithm

In this paper, a replacement algorithm for Linear Prediction Coefficients (LPC) along with Hamming Correction Code based Compressor (HCDC) algorithms are investigated for speech compression. We started with an CELP system with order 12 and with Discrete Cosine Transform (DCT) based residual excitation. Forty coefficients with transmission rate of 5.14 kbps were first used. For each frame of the testing signals we applied a multistage HCDC, we tested the compression performance for parities from 2 to 7, we were able to achieve compression only at parity 4. This rate reduction was made with no compromise in the original CELP signal quality since compression is lossless. The compression approach is based on constructing dynamic reflection coefficients codebook, this codebook is constructed and used simultaneously using a certain store/retrieve threshold. The initial linear prediction codec we used is excited by a discrete cosine transform (DCT) residual, the results were tested using the MOS and SSNR, we had acceptable ranges for the MOS (average 3.6), and small variations of the SSNR (±5 db).     

Occurrence,types, properties and interactions of phenolic compounds with other food constituents in oil-bearing plants

ABSTRACT

Phenolic phytochemicals have become of interest due to their therapeutic potential, particularly with regards to their anti-cancer, anti-inflammatory, hypolipidemic, and hypoglycemic properties. An evolving area of research involving phenolics in foods and their products pertains to the functional, biological, and nutritional consequences resulting from the binding between certain phenolic compounds and the macronutrient and micronutrient constituents of foods. The goal of this review is to provide a summary of studies investigating endogenous phenolic interactions with major components in food systems, including carbohydrates, proteins, lipids, minerals and vitamins, with a focus on the phenolic compounds and nutrients in oil-bearing plants. Another major objective is to provide a comprehensive overview of the chemical nature of phenolic interactions with food constituents that could affect the quality, nutritional and functional properties of foods. Such information can assist in the discovery and optimization of specific phenolic complexes in plant-based foods that could be utilized towards various applications in the food, nutraceutical and pharmaceutical industries.     

Correction to: Enhanced TOA Estimation Using OFDM over Wide-Band Transmission Based on a Simulated Model

Wireless Personal Communications -