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.     

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.     

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.     

Construction delay analysis techniques

Construction projects continue to suffer delays. Things go wrong and the project's completion date gets pushed back, with someone to be blamed for it. In practice, attempts are made to identify the causes of delays and schedules are modified to incorporate revised duration and new project time. The analysis itself is usually complex and can be aided by a computerized approach. This paper discusses different delay analysis techniques that are currently used by practitioners in the construction industry. It also discusses a proposed new delay analysis technique called the Isolated Delay Type (IDT). These techniques were tested against a case example and their strengths and weaknesses highlighted. The new technique can be used as a standalone module for delay analysis or could be incorporated within a computer system for construction delay analysis and claims preparation called Computerized Delay Claims Analysis (CDCA) that integrates different software including an expert system and management software such as scheduling and a database or spreadsheet.     

Acid–Base Equilibrium of Dodecyldimethyl-Amine-<Emphasis Type="Italic">N</Emphasis>-Oxide Micelles in Water–Butanol Binary at 298 K

Dodecyldimethyl-amine-N-oxide (DDAO) is a zwitterionic surfactant that can be protonated in water to form DDAOH⁺ if the pH of the medium is appropriate. We proposed, in a previous study, an experimental approach to determine directly the ratio of ionization of the surfactant in the micelle and in the bulk, at a given acidity level, without the need of a presupposed model of protonic exchange. We also showed that the relations of Thermodynamics impose a relationship between the critical micelle concentration (cmc) and the level of protonation of DDAO in the micelle and in the bulk. In order to appreciate the general nature of our approach, we have now modified the protonic exchange equilibrium between DDAO and DDAOH⁺ by introducing butanol into the solution. We studied three mixed media (2, 4 and 6% alcohol by volume). For all these mixtures, we validated our experimental and theoretical approaches. Moreover, for all the hydroalcoholic mixtures considered and all pH values, the presence of butanol stabilizes the micelle leading to a decrease of the cmc. Similar to pure water (Lair et al. in Langmuir, 20:8490–8495, 2004), we showed that, in these media, the protonic exchange equilibrium between DDAOH⁺ and DDAO in their micellized forms cannot be characterized by an unique equilibrium constant independent of the pH. However, as the butanol content of the medium increases, the variations in apparent pK with pH decrease, indicating that the behaviour of the acid–base pair in the micelle is classical and corresponds to a stoichiometric proton exchange.     

Computer-Integrated System for Estimating the Costs of Building Projects

The cost estimate is considered one of the most important and critical phases of a construction project. Preparing reliable and accurate estimates to help decision makers is the most challenging assignment that cost engineers and estimators face. For decades, practitioners in the construction industry focused only on estimating the initial cost of a facility, neglecting costs associated with operating and maintaining it. Today, more interest lies in investigating the economics of facility management, which include the cost of owning and operating a building over its useful life. This paper presents a methodology that can be used for an integrated conceptual cost estimating and life-cycle cost analysis for construction projects during their initial phase. The methodology describes the development and implementation of a system that automates the preparation of parametric cost estimates and forecasts future running costs of building projects. The system integrates relational databases, a parametric cost estimate module, an AutoCAD module, a global module, a cost estimate forecasting and decision support system module, and a life cycle costing and sensitivity analysis module. The system will automatically generate a new parametric estimate upon any modification in building design. Once the capital costs are identified, the system forecasts the cost of running and maintaining the new building throughout its expected service life. After assigning the range of deviation, a sensitivity analysis is conducted, which identifies the most sensitive parameters for further consideration and analysis. Designing the system in a user-friendly environment allows owners and decision makers to envision the feasibility of new building projects within their anticipated life cycles. Moreover, it assists architects and cost engineers in generating parametric cost estimates in a dynamic environment. A numerical case example is presented to illustrate the usefulness and capabilities of the developed system.