Measurement of Inlet Drop Size Distribution of Secondary Dispersions by Laser Particle Size Analyzer

Knowledge of the Oil drop size distribution, in addition to the mean drop size, is necessary in order to characterize secondary dispersions. Furthermore, the capture efficiency for any drop flowing through a packed bed depends upon its Oil inlet drop diameter. The Oil/Water secondary dispersions produced by the centrifugal pump were analyzed at regular intervals during an experiment to ascertain the drop size distribution and to check that the feed to the coalescence bed was consistent. New techniques that were developed for measurement of drop size distribution of secondary dispersions using Laser Particle Size Analyzer, which consisted of (He/Ne) laser emitter and laser receiver and lenses. The Laser Particle Size Analyzer was fixed directly to the experimental equipment by using the special designed circular cell. The measurement of drop size distribution was done by computer system with application software package. The new mean drop diameter (i.e., d₂₁) equation has been derived theoretically and the results that predicted from this equation exhibited a maximum error of ±15% from the experimental data.     

Multi-vane expander performance: Breathing characteristics

The throttling of the working fluid flow at the inlet and exhaust port openings of multi-vane expanders leads to power losses. Therefore, a mathematical model has been developed to analyse their breathing characteristics. In particular two existing designs of multi-vane expanders, using refrigerant 113 as the working fluid, were considered. The results obtained indicate that multi-vane expanders exhibit easy-breathing behaviours. Improved breathing characteristics can be achieved by the wise selection of operating conditions for any existing design or by optimising the design parameters for a specific application.     

A scheduling decision aid in glass fiber manufacturing

A decision aid for scheduling production in glass fiber manufacturing industry is described. The methodology combines a linear programming (LP) optimization model with a heuristic model. The LP model determines production goals; the heuristic model then uses the LP output to incorporate system-specific constraints in developing processing sequences.     

Feature extraction and ML techniques for static gesture recognition

The main objective of this study is to explore the utility of a neural network-based approach in hand gesture recognition. The proposed system presents two recognition algorithms to recognize a set of six specific static hand gestures, namely open, close, cut, paste, maximize, and minimize. The hand gesture image is passed through three stages: preprocessing, feature extraction, and classification. In the first method, the hand contour is used as a feature that treats scaling and translation of problems (in some cases). However, the complex moment algorithm is used to describe the hand gesture and to treat the rotation problem in addition to scaling and translation. The back-propagation learning algorithm is employed in the multilayer neural network classifier. The second method proposed in this article achieves better recognition rate than the first method.     

Synthesis and characterization of saturated and unsaturated copolyesters based on bis-1,4-(dicarboxymethoxy) benzene

Saturated copolyester were prepared by copolyesterification of bis-1,4-(dicarboxymethoxy) benzene and phthalic anhydride with diethylene glycol, triethylene glycol, tetraethylene glycol, 1,4-butane diol, 1,2-propane diol, and 1,6-hexamethylene glycol. Also, unsaturated copolyesters were prepared by copolyesterification of bis-1,4-(dicarboxymethoxy) benzene and maleic anhydride with the same glycols. All the copolyester resins obtained have been characterized and unsaturated copolyesters in the form of films were determined. IR and ¹H-NMR spectroscopy were used for both qualitative and quantitative analysis of the copolyesters resins and their hydrolyzate products, after curing with styrene. © 1992 John Wiley & Sons, Inc.     

A new expert system for learning management systems evaluation based on neutrosophic sets

There has been a sudden increase in the usage of Learning Management Systems applications to support learner's learning process in higher education. Many studies in learning management system evaluation are implemented under complete information, while the real environment has uncertainty aspects. As these systems were described by development organizations with uncertainty terms such as vague, imprecise, ambiguity and inconsistent, that is why traditional evaluation methods may not be effective. This paper suggests neutrosophic logic as a better option to simulate human thinking than fuzzy logic because unlike fuzzy logic, it is able to handle indeterminacy of information which expresses the percentage of unknown parameters. As previous studies suggested neutrosophic decision maker and neutrosophic expert systems as future work in ecommerce and e‐learning applications, this paper presents neutrosphic expert system for learning management systems evaluation. Information for building and validating the neutrosophic expert system is collected from five experts using surveys, and then analysis is done by using Fuzzytech 5.54d software. Finally, the comparison between fuzzy expert system and neutrosophic expert system results show that the neutrosophic logic is capable of representing uncertainty in human thinking for evaluating Learning Management Systems.     

A novel look-ahead optimization strategy for trie-based approximate string matching

This paper deals with the problem of estimating a transmitted string X ^* by processing the corresponding string Y, which is a noisy version of X ^*. We assume that Y contains substitution, insertion, and deletion errors, and that X ^* is an element of a finite (but possibly, large) dictionary, H. The best estimate X ⁺ of X ^*, is defined as that element of H which minimizes the generalized Levenshtein distance D(X, Y) between X and Y such that the total number of errors is not more than K, for all X ∈H. The trie is a data structure that offers search costs that are independent of the document size. Tries also combine prefixes together, and so by using tries in approximate string matching we can utilize the information obtained in the process of evaluating any one D(X _i , Y), to compute any other D(X _j , Y), where X _i and X _j share a common prefix. In the artificial intelligence (AI) domain, branch and bound (BB) schemes are used when we want to prune paths that have costs above a certain threshold. These techniques have been applied to prune, for example, game trees. In this paper, we present a new BB pruning strategy that can be applied to dictionary-based approximate string matching when the dictionary is stored as a trie. The new strategy attempts to look ahead at each node, c, before moving further, by merely evaluating a certain local criterion at c. The search algorithm according to this pruning strategy will not traverse inside the subtrie(c) unless there is a “hope” of determining a suitable string in it. In other words, as opposed to the reported trie-based methods (Kashyap and Oommen in Inf Sci 23(2):123–142, 1981; Shang and Merrettal in IEEE Trans Knowledge Data Eng 8(4):540–547, 1996), the pruning is done a priori before even embarking on the edit distance computations. The new strategy depends highly on the variance of the lengths of the strings in H. It combines the advantages of partitioning the dictionary according to the string lengths, and the advantages gleaned by representing H using the trie data structure. The results demonstrate a marked improvement (up to 30% when costs are of a 0/1 form, and up to 47% when costs are general) with respect to the number of operations needed on three benchmark dictionaries.     

Optimization Algorithm for Selection and on Site Location of Mobile Cranes

Mobile crane manufacturers provide operators and practitioners with tabulated lift-capacity charts. These charts are structured based on predetermined crane configurations, which consist of boom/jib length, lifting radius, lifting height, main boom angles to ground, and jib angle to ground or its offset to its main boom centerline. Practitioners, however, are often required to lift on a partially extended hydraulic section and/or lifting radius other than those listed in the manufacturers’ lift-capacity charts. This paper presents a newly developed optimization algorithm (referred to in this paper as Algorithm-2) for selecting and locating mobile cranes on construction sites based on their minimum boom length and/or minimum radius, accordingly higher lifting capacities. Algorithm-2 includes an optimization procedure that avoids lifting capacity violations. In addition to the practical use of Algorithm 2, the mathematical representations of the crane’s geometry are also useful for research in the automation and robotic field of operations involving cranes. The algorithm is incorporated into a computer system that integrates a selection module and a database. Data pertinent to crane lift configurations are retrieved from the database and are then processed to determine the optimum, geometrical selection of the crane configuration. A case example is described in order to demonstrate the use of the developed algorithm and to illustrate its essential features.     

Biometric authentication based on PCG and ECG signals: present status and future directions

Due to the great advances in biomedical digital signal processing, new biometric traits have showed noticeable improvements in authentication systems. Recently, the ElectroCardioGram (ECG) and the PhonoCardioGraph (PCG) have been proposed as novel biometrics. This paper aims to review the previous studies related to the usage of the ECG and PCG signals in human recognition. In addition, we discuss briefly the most important techniques and methodologies used by researchers in the preprocessing, feature extraction and classification of the ECG and PCG signals. At the end, we introduce some future considerations that can be applied in this topic such as: the fusion between different techniques previously used, use both ECG and PCG signals in a multimodal biometric authentication system and building a prototype system for real-time authentication.     

Oxy‐fuel combustion technology: current status,applications, and trends

The increased level of emissions of carbon dioxide into the atmosphere due to burning of fossil fuels represents one of the main barriers toward the reduction of greenhouse gases and the control of global warming. In the last decades, the use of renewable and clean sources of energies such as solar and wind energies has been increased extensively. However, due to the tremendously increasing world energy demand, fossil fuels would continue in use for decades which necessitates the integration of carbon capture technologies (CCTs) in power plants. These technologies include oxycombustion, pre‐combustion, and post‐combustion carbon capture. Oxycombustion technology is one of the most promising carbon capture technologies as it can be applied with slight modifications to existing power plants or to new power plants. In this technology, fuel is burned using an oxidizer mixture of pure oxygen plus recycled exhaust gases (consists mainly of CO₂). The oxycombustion process results in highly CO₂‐concentrated exhaust gases, which facilitates the capture process of CO₂ after H₂O condensation. The captured CO₂ can be used for industrial applications or can be sequestrated. The current work reviews the current status of oxycombustion technology and its applications in existing conventional combustion systems (including gas turbines and boilers) and novel oxygen transport reactors (OTRs). The review starts with an introduction to the available CCTs with emphasis on their different applications and limitations of use, followed by a review on oxycombustion applications in different combustion systems utilizing gaseous, liquid, and coal fuels. The current status and technology readiness level of oxycombustion technology is discussed. The novel application of oxycombustion technology in OTRs is analyzed in some details. The analyses of OTRs include oxygen permeation technique, fabrication of oxygen transport membranes (OTMs), calculation of oxygen permeation flux, and coupling between oxygen separation and oxycombustion of fuel within the same unit called OTR. The oxycombustion process inside OTR is analyzed considering coal and gaseous fuels. The future trends of oxycombustion technology are itemized and discussed in details in the present study including: (i) ITMs for syngas production; (ii) combustion utilizing liquid fuels in OTRs; (iii) oxy‐combustion integrated power plants and (iv) third generation technologies for CO₂ capture. Techno‐economic analysis of oxycombustion integrated systems is also discussed trying to assess the future prospects of this technology. Copyright © 2017 John Wiley & Sons, Ltd.