Quality-Driven Business Process Refactoring

Appropriate description of business processes through standard notations has become one of the most important assets for organizations. Organizations must therefore deal with quality faults in business process models such as the lack of understandability and modifiability. These quality faults may be exacerbated if business process models are mined by reverse engineering, e.g., from existing information systems that support those business processes. Hence, business process refactoring is often used, which change the internal structure of business processes whilst its external behavior is preserved. This paper aims to choose the most appropriate set of refactoring operators through the quality assessment concerning understandability and modifiability. These quality features are assessed through well-proven measures proposed in the literature. Additionally, a set of measure thresholds are heuristically established for applying the most promising refactoring operators, i.e., those that achieve the highest quality improvement according to the selected measures in each case.

Developing a Simple and an Accurate Formula for the Conduction Angle of a Single Phase Rectifier with RL Load

The paper presents a simple and an accurate formula that has been developed for the conduction angle (δ) of a single phase half-wave or full-wave controlled rectifier with RL load. This formula can be also used for calculating the conduction angle (δ) in case of A.C. voltage regulator with inductive load under discontinuous current mode. The simulation results shows that the conduction angle calculated from the developed formula agree very well with that obtained from the exact solution arrived from the iterative method. Applying the developed formula can reduce the computational time and reduce the time for manual classroom calculation. In addition, the proposed formula is attractive for real time implementations.

Improved Back Propagation Algorithm to Avoid Local Minima in Multiplicative Neuron Model

The back propagation algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a training algorithm consisting of a learning rate and a momentum factor. The major drawbacks of above learning algorithm are the problems of local minima and slow convergence speeds. The addition of an extra term, called a proportional factor reduces the convergence of the back propagation algorithm. We have applied the three term back propagation to multiplicative neural network learning. The algorithm is tested on XOR and parity problem and compared with the standard back propagation training algorithm.

Low-Cost Pre-Treatment of Pharmaceutical Wastewater

Pharmaceutical industries and effluents of sewage treatment plants are the main sources of residual pharmaceuticals in water resources. These emergent pollutants may adversely impact the biophysical environment. Pharmaceutical industries often generate wastewater that changes in characteristics and quantity depending on the used manufacturing processes. Carbamazepine (CBZ), {5Hdibenzo [b,f]azepine-5-carboxamide, (C15H12N2O)}, is a significant non-biodegradable pharmaceutical contaminant in the Jordanian pharmaceutical wastewater, which is not removed by the activated sludge processes in treatment plants. Activated carbon may potentially remove that pollutant from effluents, but the high cost involved suggests that more attention should be given to the potential use of low-cost materials in order to reduce cost and environmental contamination. Powders of Jordanian non-metallic raw materials namely, Azraq Bentonite (AB), Kaolinite (K), and Zeolite (Zeo) were activated (acid and thermal treatment) and evaluated by removing CBZ. The results of batch and column techniques experiments showed around 46% and 67% removal of CBZ respectively.

Correlation of Viscosity in Nanofluids using Genetic Algorithm-neural Network (GA-NN)

An accurate and proficient artificial neural network (ANN) based genetic algorithm (GA) is developed for predicting of nanofluids viscosity. A genetic algorithm (GA) is used to optimize the neural network parameters for minimizing the error between the predictive viscosity and the experimental one. The experimental viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15 to 343.15 K and volume fraction up to 15% were used from literature. The result of this study reveals that GA-NN model is outperform to the conventional neural nets in predicting the viscosity of nanofluids with mean absolute relative error of 1.22% and 1.77% for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results of this work have also been compared with others models. The findings of this work demonstrate that the GA-NN model is an effective method for prediction viscosity of nanofluids and have better accuracy and simplicity compared with the others models.

Visualising Energy Efficiency Landscape

This paper discusses the landscape design that could increase energy efficiency in a house. By planting trees in a house compound, the tree shades prevent direct sunlight from heating up the building, and it enables cooling off the surrounding air. The requirement for air-conditioning could be minimized and the air quality could be improved. During the life time of a tree, the saving cost from the mentioned benefits could be up to US $ 200 for each tree. The project intends to visually describe the landscape design in a house compound that could enhance energy efficiency and consequently lead to energy saving. The house compound model was developed in three dimensions by using AutoCAD 2005, the animation was programmed by using LightWave 3D softwares i.e. Modeler and Layout to display the tree shadings in the wall. The visualization was executed on a VRML Pad platform and implemented on a web environment.

Seasonal Prevalence of Aedes aegypti and Ae.albopictus in Three Topographical Areas of Southern Thailand

This study investigated the seasonal prevalence of Aedes aegypti and Ae. albopictus larvae in three topographical areas (i.e. mangrove, rice paddy and mountainous areas). Samples were collected from 300 households in both wet and dry seasons in nine districts in Nakhon Si Thammarat province. Ae. aegypti and Ae. albopictus were found in 21 out of 29 types of water containers in mangrove, rice paddy and mountainous areas. Ae. aegypti and Ae. albopictus laid eggs in different container types depending on season and topographical areas. Ae. aegypti larvae were found most in metal box in mangrove and mountainous areas in wet season. Ae. albopictus larvae were also found most in metal box in mangrove and mountainous areas in both wet and dry seasons. All Ae. albopictus larval indices were higher than Ae. aegypti larval indices in all three topographical areas and both seasons. HI and BI did not differ in three topographical areas but differed between Aedes sp. HI for both Ae. aegypti and Ae. albopictus in all three topographical areas in both seasons were greater than 10 %, except Aedes aegypti in rice paddy area in wet season. This indicated high risks of DHF transmission in these areas.

Ensembling Adaptively Constructed Polynomial Regression Models

The approach of subset selection in polynomial regression model building assumes that the chosen fixed full set of predefined basis functions contains a subset that is sufficient to describe the target relation sufficiently well. However, in most cases the necessary set of basis functions is not known and needs to be guessed – a potentially non-trivial (and long) trial and error process. In our research we consider a potentially more efficient approach – Adaptive Basis Function Construction (ABFC). It lets the model building method itself construct the basis functions necessary for creating a model of arbitrary complexity with adequate predictive performance. However, there are two issues that to some extent plague the methods of both the subset selection and the ABFC, especially when working with relatively small data samples: the selection bias and the selection instability. We try to correct these issues by model post-evaluation using Cross-Validation and model ensembling. To evaluate the proposed method, we empirically compare it to ABFC methods without ensembling, to a widely used method of subset selection, as well as to some other well-known regression modeling methods, using publicly available data sets.

Three Dimensional Modeling of Mixture Formation and Combustion in a Direct Injection Heavy-Duty Diesel Engine

Due to the stringent legislation for emission of diesel engines and also increasing demand on fuel consumption, the importance of detailed 3D simulation of fuel injection, mixing and combustion have been increased in the recent years. In the present work, FIRE code has been used to study the detailed modeling of spray and mixture formation in a Caterpillar heavy-duty diesel engine. The paper provides an overview of the submodels implemented, which account for liquid spray atomization, droplet secondary break-up, droplet collision, impingement, turbulent dispersion and evaporation. The simulation was performed from intake valve closing (IVC) to exhaust valve opening (EVO). The predicted in-cylinder pressure is validated by comparing with existing experimental data. A good agreement between the predicted and experimental values ensures the accuracy of the numerical predictions collected with the present work. Predictions of engine emissions were also performed and a good quantitative agreement between measured and predicted NOx and soot emission data were obtained with the use of the present Zeldowich mechanism and Hiroyasu model. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the internal combustion engine design, optimization and performance analysis.

A Practical Approach for Electricity Load Forecasting

This paper is a continuation of our daily energy peak load forecasting approach using our modified network which is part of the recurrent networks family and is called feed forward and feed back multi context artificial neural network (FFFB-MCANN). The inputs to the network were exogenous variables such as the previous and current change in the weather components, the previous and current status of the day and endogenous variables such as the past change in the loads. Endogenous variable such as the current change in the loads were used on the network output. Experiment shows that using endogenous and exogenous variables as inputs to the FFFBMCANN rather than either exogenous or endogenous variables as inputs to the same network produces better results. Experiments show that using the change in variables such as weather components and the change in the past load as inputs to the FFFB-MCANN rather than the absolute values for the weather components and past load as inputs to the same network has a dramatic impact and produce better accuracy.

Secure Protocol for Short Message Service

Short Message Service (SMS) has grown in popularity over the years and it has become a common way of communication, it is a service provided through General System for Mobile Communications (GSM) that allows users to send text messages to others. SMS is usually used to transport unclassified information, but with the rise of mobile commerce it has become a popular tool for transmitting sensitive information between the business and its clients. By default SMS does not guarantee confidentiality and integrity to the message content. In the mobile communication systems, security (encryption) offered by the network operator only applies on the wireless link. Data delivered through the mobile core network may not be protected. Existing end-to-end security mechanisms are provided at application level and typically based on public key cryptosystem. The main concern in a public-key setting is the authenticity of the public key; this issue can be resolved by identity-based (IDbased) cryptography where the public key of a user can be derived from public information that uniquely identifies the user. This paper presents an encryption mechanism based on the IDbased scheme using Elliptic curves to provide end-to-end security for SMS. This mechanism has been implemented over the standard SMS network architecture and the encryption overhead has been estimated and compared with RSA scheme. This study indicates that the ID-based mechanism has advantages over the RSA mechanism in key distribution and scalability of increasing security level for mobile service.

Quantum Computation using Two Component Bose-Einstein Condensates

Quantum computation using qubits made of two component Bose-Einstein condensates (BECs) is analyzed. We construct a general framework for quantum algorithms to be executed using the collective states of the BECs. The use of BECs allows for an increase of energy scales via bosonic enhancement, resulting in two qubit gate operations that can be performed at a time reduced by a factor of N, where N is the number of bosons per qubit. We illustrate the scheme by an application to Deutsch-s and Grover-s algorithms, and discuss possible experimental implementations. Decoherence effects are analyzed under both general conditions and for the experimental implementation proposed.

Indoor Mapping by using Smartphone Device

This paper presented the potential of smart phone to provide support on mapping the indoor asset. The advantage of using the smart phone to generate the indoor map is that it has the ability to capture, store and reproduces still or video images; indeed most of us do have this powerful gadget. The captured images usually used by maintenance team to save a record for future reference. Here, these images are used to generate 3D models of an object precisely and accurately for efficient and effective solution in data gathering. Thus, it could be a resource for an informative database in asset management.

Treatment of Petroleum Refinery Wastewater by using UASB Reactors

Petroleum refineries discharged large amount of wastewater -during the refining process- that contains hazardous constituents that is hard to degrade. Anaerobic treatment process is well known as an efficient method to degrade high strength wastewaters. Up-flow Anaerobic Sludge Blanker (UASB) is a common process used for various wastewater treatments. Two UASB reactors were set up and operated in parallel to evaluate the treatment efficiency of petroleum refinery wastewater. In this study four organic volumetric loading rates were applied (i.e. 0.58, 0.89, 1.21 and 2.34 kg/m3·d), two loads to each reactor. Each load was applied for a period of 60 days for the reactor to acclimatize and reach steady state, and then the second load applied. The chemical oxygen demand (COD) removals were satisfactory with the removal efficiencies at the loadings applied were 78, 82, 83 and 81 % respectively.

Dynamic Modeling of Intelligent Air-Cushion Tracked Vehicle for Swamp Peat

Modeling of the dynamic behavior and motion are renewed interest in the improved tractive performance of an intelligent air-cushion tracked vehicle (IACTV). This paper presents a new dynamical model for the forces on the developed small scale intelligent air-cushion tracked vehicle moving over swamp peat. The air cushion system partially supports the 25 % of vehicle total weight in order to make the vehicle ground contact pressure 7 kN/m2. As the air-cushion support system can adjust automatically on the terrain, so the vehicle can move over the terrain without any risks. The springdamper system is used with the vehicle body to control the aircushion support system on any undulating terrain by making the system sinusoidal form. Experiments have been carried out to investigate the relationships among tractive efficiency, slippage, traction coefficient, load distribution ratio, tractive effort, motion resistance and power consumption in given terrain conditions. Experiment and simulation results show that air-cushion system improves the vehicle performance by keeping traction coefficient of 71% and tractive efficiency of 62% and the developed model can meet the demand of transport efficiency with the optimal power consumption.

Comparative Analysis of Concentration in Insurance Markets in New EU Member States

The purpose of this article is to analyze the market structure as well as the degree of concentration in insurance markets in new EU member states. The analysis was conducted using several most commonly used concentration indicators such as concentration ratio, Herfindahl-Hirschman index and entropy index. These indicators were calculated for the 2000-2010 period on the basis of total gross written premium as the most relevant indicator of market power in insurance markets. The results of the analysis showed that in all observed countries the level of concentration decreased, though with significantly different intensity. Yet, in some countries, the level of concentration remains very high.

Indoor Moisture Control of Auckland Houses with Different Ventilation Systems

Auckland has a temperate climate with comfortable warm, dry summers and mild, wet winters. Auckland house design not only focus on winter thermal performance and indoor thermal condition, but also indoor moisture control, which is closely related to indirect health effects such as dust mites, fungi, etc. Most Auckland houses are designed to use temporary heating for winter indoor thermal comfort. Based on field study data of indoor microclimate conditions of two Auckland townhouses with a whole home mechanical ventilation system or a passive wind directional skylight vent, this study is to evaluate and compare indoor moisture conditions of two insulated townhouses only using temporary heating with different ventilation systems.

Mathematical Modeling of Asphaltene Precipitation: A Review

In the Enhanced Oil Recovery (EOR) method, use of Carbon dioxide flooding whereby CO2 is injected into an oil reservoir to increase output when extracting oil resulted significant recovery worldwide. The carbon dioxide function as a pressurizing agent when mixed into the underground crude oil will reduce its viscosity and will enable a rapid oil flow. Despite the CO2’s advantage in the oil recovery, it may result to asphaltene precipitation a problem that will cause the reduction of oil produced from oil wells. In severe cases, asphaltene precipitation can cause costly blockages in oil pipes and machinery. This paper presents reviews of several studies done on mathematical modeling of asphaltene precipitation. The synthesized result from several researches done on this topic can be used as guide in order to better understand asphaltene precipitation. Likewise, this can be used as initial reference for students, and new researchers doing study on asphaltene precipitation.

Investigation of Regenerative and Recuperative Burners for Different Sizes of Reheating Furnaces

This research aims to analyze the regenerative burner and the recuperative burner for the different reheating furnaces in the steel industry. The warm air temperatures of the burners are determined to suit with the sizes of the reheating furnaces by considering the air temperature, the fuel cost and the investment cost. The calculations of the payback period and the net present value are studied to compare the burners for the different reheating furnaces. The energy balance is utilized to calculate and compare the energy used in the different sizes of reheating furnaces for each burner. It is found that the warm air temperature is different if the sizes of reheating furnaces are varied. Based on the considerations of the net present value and the payback period, the regenerative burner is suitable for all plants at the same life of the burner. Finally, the sensitivity analysis of all factors has been discussed in this research.