A new investigation with the salting‐out effect on emulsifier‐free emulsion polymerization of methyl methacrylate

The effects of the various salts onto the emulsifier‐free emulsion polymerization of methyl methacrylate (MMA) were investigated. It was found that the kind and amount of the salts were very effective on the polymerization even onto the polymeric products. It is known that the ionic strength of the electrolyte is effective for the polymerization. However, our investigation with the same ionic strength of different electrolyte produced the different effect on the polymerization. It was found that the Stokes radiuses of ions are very important for the reaction kinetics and type of the product. At the same electrolyte concentration, as increased Stokes radii of cation of salts that not react (the fragments of initiator, ions, etc.) in polymerization, polymerization rate and average molecular weight of polymer decreased, polymer particle diameter increased. In the case of Br^? and SO₄⁼ the anions of the salt are also demonstrated some unexpected reactions. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 2494–2500, 2007     

Propylene glycol mono and di stearates as water in oil emulsifiers for oil-well drilling fluids

The objective of drilling operation is to drill, evaluate and complete a well that will produce oil and/or gas efficiently. The responsibility for performing these functions is held by using drilling mud.The research will focus on the oil base mud system due to the importance of that kind of drilling fluid which helped to address several drilling problems such as formation clays that react, swell or slough after expose to WBFs, increasing down hole temperatures, contaminants, stuck pipe, torque and drag.The research will rely on an economical-low cost prepared emulsifiers that used as W/O emulsifiers for oil base mud instead of the imported emulsifier. The new prepared emulsifiers provide an excellent options with emulsification power for oil-based mud that formulated from diesel oil and water.The nonionic emulsifiers were prepared through the esterification reaction of propylene glycol (1?mol) and stearic acid (1?mol) and/or (2?mol), the products were two oil soluble nonionic emulsifiers with hydrophilic/lipophilic balance (HLB) of 3.4 and 2.8 respectively. The chemical structure was confirmed using elemental analysis, FTIR and ¹H NMR.The new prepared emulsifiers were evaluated as primary emulsifiers for oil – base mud and the results were compared with the currently used primary emulsifier. The obtained results exhibited interesting rheology properties and shear-thinning behavior, yield value, thixotropy, gel strength and filter loss.     

Mechanical,vulcametric, and thermal properties of the different 5‐ethylidene 2‐norbornene content of ethylene‐propylene‐diene‐monomer vulcanized with different types and compositions of peroxides

Ethylene‐propylene‐diene‐monomer (EPDM) rubber is an important commercial polymer. The vulcanization process significantly changes its thermal, mechanical, and vulcametric properties. This study was carried out to find optimum formulation of EPDM composite for a better application in automotive industry. Sixteen EPDM polymer samples having different 5‐ethylidene 2‐norbornene (ENB) and ethylene contents were vulcanized with different types and compositions of peroxide and coagents. The mechanical and vulcametric properties of these samples were measured and compared. The type of peroxide, coagent, and EPDM grade affected the mechanical, thermal, and vulcametric properties of the EPDM rubber to some extend. Use of aromatic peroxide and coagent increased the thermal stability slightly. Mechanical properties were changed very slightly with the change of peroxide type for the same content of peroxide and coagent. Scorch time and cure time decreased with initial increase of the peroxide content. EPDM compound vulcanized with BBPIB peroxide and TAC/S coagent has higher cure time than EPDM compound vulcanized with DMBPHa peroxide and TMPTMA coagent. Coran method was used for the modeling of experimental data. Velocity constant for the formation of peroxide radical and polymer radical were found for each case. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Effects of gelatinisation level, gum and transglutaminase on the quality characteristics of rice noodle

The aim of the present study was to investigate the effects of gelatinisation level, gum (locust bean gum, xanthan gum, 3%) and/or transglutaminase (TG, 0.5%) on quality characteristics of rice noodle. In order to improve the dough forming ability, rice flour was gelatinised at levels of 15%, 20%, 25% and 30%. Noodle samples were evaluated in terms of cooking loss, total organic matter (TOM), water absorption, swelling volume, maximum force, colour, sensory properties, pasting properties. Noodle sample with a gelatinisation level of 25% had better cooking and sensory properties. Gum and/or TG were added to this noodle formula. The noodle samples including xanthan gum had better cooking and sensory properties. TG caused a significant decrease in TOM. The samples including locust bean gum had significantly higher maximum force values. Xanthan gum caused decreases in some Rapid ViscoAnalyzer viscosity values of the noodle samples, while locust bean gum caused increases.     

Neural network applications for automatic new topic identification of FAST and Excite search engine transaction logs

Abstract: Content analysis of search engine user queries is an important task, since successful exploitation of the content of queries can result in the design of efficient information retrieval algorithms for more efficient search engines. Identification of topic changes within a user search session is a key issue in content analysis of search engine user queries. This study proposes an artificial neural network application in the area of search engine research to automatically identify topic changes in a user session by using statistical characteristics of queries, such as time intervals and query reformulation patterns. Sample data logs from the FAST and Excite search engines are selected to train the neural network and then the neural network is used to identify topic changes in the data log. As a result, almost all the performance measures yielded favourable results.     

A comparison of security requirements engineering methods

This paper presents a conceptual framework for security engineering, with a strong focus on security requirements elicitation and analysis. This conceptual framework establishes a clear-cut vocabulary and makes explicit the interrelations between the different concepts and notions used in security engineering. Further, we apply our conceptual framework to compare and evaluate current security requirements engineering approaches, such as the Common Criteria, Secure Tropos, SREP, MSRA, as well as methods based on UML and problem frames. We review these methods and assess them according to different criteria, such as the general approach and scope of the method, its validation, and quality assurance capabilities. Finally, we discuss how these methods are related to the conceptual framework and to one another.     

Soft computing and signal processing based active fault tolerant control for benchmark process

Ideally, when faults happen, the closed-loop system should be capable of maintaining its present operation. This leads to the recently studied area of fault-tolerant control (FTC). This paper addresses soft computing and signal processing based active FTC for benchmark process. Design of FTC has three levels: Level 1 comprises a traditional control loop with sensor and actuator interface and the controller. Level 2 comprises the functions of online fault detection and identification. Level 3 comprises the supervisor functionality. Online fault detection and identification has signal processing module, feature extraction module, feature cluster module and fault decision module. Wavelet analysis has been used for signal processing module. In the feature extraction module, feature vector of the sensor faults has been constructed using wavelet analysis, sliding window, absolute maximum value changing ratio and variance changing ratio as a statistical analysis. For the feature cluster module, the self-organizing map (SOM), which is a subtype of artificial neural network has been applied as a classifier of the feature vector. As a benchmark process three-tank system has been used. Control of the three-tank system is provided by fuzzy logic controller. Faults are applied to three level sensors. Sensor faults represent incorrect reading from the sensors that the system is equipped with. When a particular fault occurs in the system, a suitable control scheme has been selected on-line by supervisor functionality to maintain the closed-loop performance of the system. Active FTC has been achieved by switch mode control using fuzzy logic controller. Simulation results show that benchmark process has maintained acceptable performance with FTC for the sensor faults. As a result, when the system has sensor faults soft computing and signal processing based FTC helps for the best performance of the system.