Investigation of Optimal Parameter Settings in Super Duplex Welding

Super steel materials play a vital role in the construction and fabrication of structural, piping and pipeline components. In assuring the integrity of onshore and offshore operating systems, they enable life cycle costs to be minimized. In this context, Duplex stainless steel (DSS) material related welding on constructions and fabrications plays a significant role in maintaining and assuring integrity at an optimal expenditure over the life cycle of production and process systems as well as associated structures. In DSS welding, factors such as gap geometry, shielding gas supply rate, welding current, and type of the welding process are vital to the final joint performance. Hence, an experimental investigation has been performed using an engineering robust design approach (ERDA) to investigate the optimal settings that generate optimal super DSS (i.e. UNS S32750) joint performance. This manuscript illustrates the mathematical approach and experimental design, optimal parameter settings and results of the verification experiment.

Effect of Evaporator Temperature on the Performance of Water Desalination/Refrigeration Adsorption System Using AQSOA-ZO2

Many water desalination technologies have been developed but in general they are energy intensive and have high cost and adverse environmental impact. Recently, adsorption technology for water desalination has been investigated showing the potential of using low temperature waste heat (50-85oC) thus reducing energy consumption and CO2 emissions. This work mathematically compares the performance of an adsorption cycle that produces two useful effects namely, fresh water and cooling using two different adsorbents, silica-gel and an advanced zeolite material AQSOA-ZO2, produced by Mitsubishi plastics. It was found that at low chilled water temperatures, typically below 20oC, the AQSOA-Z02 is more efficient than silica-gel as the cycle can produce 5.8 m3 of fresh water per day and 50.1 Rton of cooling per tonne of AQSOA-ZO2. Above 20oC silica-gel is still better as the cycle production reaches 8.4 m3 per day and 62.4 Rton per tonne of silica-gel. These results show the potential of using the AQSOA-Z02 at low chilled water temperature for water desalination and cooling applications.

Demographics Are Not Enough: Targeting and Segmentation of Anti-Obesity Campaigns in Mexico

Mass media campaigns against obesity are often designed to impact large audiences. This usually means that their audience is defined based on general demographic characteristics like age, gender, occupation etc., not taking into account psychographics like behavior, motivations, wants, etc. Using psychographics, as the base for the audience segmentation, is a common practice in case of successful campaigns, as it allows developing more relevant messages. It also serves a purpose of identifying key segments, those that generate the best return on investment. For a health campaign, that would be segments that have the best chance of being converted into healthy lifestyle at the lowest cost. This paper presents the limitations of the demographic targeting, based on the findings from the reception study of IMSS (Mexican Social Security Institute) antiobesity TV commercials and proposes mothers as the first level of segmentation, in the process of identifying the key segment for these campaigns.

Material Flow Modeling in Friction Stir Welding of AA6061-T6 Alloy and Study of the Effect of Process Parameters

To understand the friction stir welding process, it is very important to know the nature of the material flow in and around the tool. The process is a combination of both thermal as well as mechanical work i.e. it is a coupled thermo-mechanical process. Numerical simulations are very much essential in order to obtain a complete knowledge of the process as well as the physics underlying it. In the present work a model based approach is adopted in order to study material flow. A thermo-mechanical based CFD model is developed using a Finite Element package, Comsol Multiphysics. The fluid flow analysis is done. The model simultaneously predicts shear strain fields, shear strain rates and shear stress over the entire workpiece for the given conditions. The flow fields generated by the streamline plot give an idea of the material flow. The variation of dynamic viscosity, velocity field and shear strain fields with various welding parameters is studied. Finally the result obtained from the above mentioned conditions is discussed elaborately and concluded.

Value Index, a Novel Decision Making Approach for Waste Load Allocation

Waste load allocation (WLA) policies may use multiobjective optimization methods to find the most appropriate and sustainable solutions. These usually intend to simultaneously minimize two criteria, total abatement costs (TC) and environmental violations (EV). If other criteria, such as inequity, need for minimization as well, it requires introducing more binary optimizations through different scenarios. In order to reduce the calculation steps, this study presents value index as an innovative decision making approach. Since the value index contains both the environmental violation and treatment costs, it can be maximized simultaneously with the equity index. It implies that the definition of different scenarios for environmental violations is no longer required. Furthermore, the solution is not necessarily the point with minimized total costs or environmental violations. This idea is testified for Haraz River, in north of Iran. Here, the dissolved oxygen (DO) level of river is simulated by Streeter-Phelps equation in MATLAB software. The WLA is determined for fish farms using multi-objective particle swarm optimization (MOPSO) in two scenarios. At first, the trade-off curves of TC-EV and TC-Inequity are plotted separately as the conventional approach. In the second, the Value-Equity curve is derived. The comparative results show that the solutions are in a similar range of inequity with lower total costs. This is due to the freedom of environmental violation attained in value index. As a result, the conventional approach can well be replaced by the value index particularly for problems optimizing these objectives. This reduces the process to achieve the best solutions and may find better classification for scenario definition. It is also concluded that decision makers are better to focus on value index and weighting its contents to find the most sustainable alternatives based on their requirements.

Potential of Safflower (Carthamus tinctorius L.) for Phytoremedation of Soils Contaminated with Heavy Metals

A field study was conducted to evaluate the efficacy of safflower plant for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. Field experiments with randomized complete block design with five treatments (control, compost amendments added at 20 and 40 t/daa, and vermicompost amendments added at 20 and 40 t/daa) were carried out. The quality of safflower seeds and oil (heavy metals and fatty acid composition) were determined. Tested organic amendments significantly influenced the chemical composition of safflower seeds and oil. The compost and vermicompost treatments significantly reduced heavy metals concentration in safflower seeds and oils, but the effect differed among them. Addition of vermicompost and compost leads to an increase in the content of palmitic acid and linoleic acid, and a decrease in the stearic and oleic acids compared with the control. A significant increase in the quantity of saturated acids was observed in the variants with 20 t/daa of compost and 20 t/daa of vermicompost (9.1 and 8.9% relative to the control). Safflower is a plant which is tolerant to heavy metals and can be successfully used in the phytoremediation of heavy metal contaminated soils. The processing of seeds to oil and using the obtained oil for nutritional purposes will greatly reduce the cost of phytoremediation.

A Metallography Study of Secondary A226 Aluminium Alloy Used in Automotive Industries

The secondary alloy A226 is used for many automotive casting produced by mould casting and high pressure die casting. This alloy has excellent castability, good mechanical properties and cost-effectiveness. Production of primary aluminium alloys belong to heavy source fouling of life environs. The European Union calls for the emission reduction and reduction in energy consumption therefore increase production of recycled (secondary) aluminium cast alloys. The contribution is deal with influence of recycling on the quality of the casting made from A226 in automotive industry. The properties of the casting made from secondary aluminium alloys were compared with the required properties of primary aluminium alloys. The effect of recycling on microstructure was observed using combination different analytical techniques (light microscopy upon black-white etching, scanning electron microscopy - SEM upon deep etching and energy dispersive X-ray analysis - EDX). These techniques were used for the identification of the various structure parameters, which was used to compare secondary alloy microstructure with primary alloy microstructure.

Modelling of Powered Roof Supports Work

Due to the increasing efforts on saving our natural environment a change in the structure of energy resources can be observed - an increasing fraction of a renewable energy sources. In many countries traditional underground coal mining loses its significance but there are still countries, like Poland or Germany, in which the coal based technologies have the greatest fraction in a total energy production. This necessitates to make an effort to limit the costs and negative effects of underground coal mining. The longwall complex is as essential part of the underground coal mining. The safety and the effectiveness of the work is strongly dependent of the diagnostic state of powered roof supports. The building of a useful and reliable diagnostic system requires a lot of data. As the acquisition of a data of any possible operating conditions it is important to have a possibility to generate a demanded artificial working characteristics. In this paper a new approach of modelling a leg pressure in the single unit of powered roof support. The model is a result of the analysis of a typical working cycles.

The Classification Performance in Parametric and Nonparametric Discriminant Analysis for a Class- Unbalanced Data of Diabetes Risk Groups

The problems arising from unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many researchers have found that the performance of existing classifiers tends to be biased towards the majority class. The k-nearest neighbors’ nonparametric discriminant analysis is a method that was proposed for classifying unbalanced classes with good performance. In this study, the methods of discriminant analysis are of interest in investigating misclassification error rates for classimbalanced data of three diabetes risk groups. The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification of class-imbalanced data of diabetes risk groups. Data from a project maintaining healthy conditions for 599 employees of a government hospital in Bangkok were obtained for the classification problem. The employees were divided into three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data including the variables of diabetes risk group, age, gender, blood glucose, and BMI were analyzed and bootstrapped for 50 and 100 samples, 599 observations per sample, for additional estimation of the misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples showed nonnormality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. Searching the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10) and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k=3 or k=4 and the defined prior probabilities of non-risk: risk: diabetic as 0.90: 0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of misclassification. The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Monetary Evaluation of Dispatching Decisions in Consideration of Mode Choice Models

Microscopic simulation tool kits allow for consideration of the two processes of railway operations and the previous timetable production. Block occupation conflicts on both process levels are often solved by using defined train priorities. These conflict resolutions (dispatching decisions) generate reactionary delays to the involved trains. The sum of reactionary delays is commonly used to evaluate the quality of railway operations, which describes the timetable robustness. It is either compared to an acceptable train performance or the delays are appraised economically by linear monetary functions. It is impossible to adequately evaluate dispatching decisions without a well-founded objective function. This paper presents a new approach for the evaluation of dispatching decisions. The approach uses mode choice models and considers the behaviour of the end-customers. These models evaluate the reactionary delays in more detail and consider other competing modes of transport. The new approach pursues the coupling of a microscopic model of railway operations with the macroscopic choice mode model. At first, it will be implemented for railway operations process but it can also be used for timetable production. The evaluation considers the possibility for the customer to interchange to other transport modes. The new approach starts to look at rail and road, but it can also be extended to air travel. The result of mode choice models is the modal split. The reactions by the end-customers have an impact on the revenue of the train operating companies. Different purposes of travel have different payment reserves and tolerances towards late running. Aside from changes to revenues, longer journey times can also generate additional costs. The costs are either time- or track-specific and arise from required changes to rolling stock or train crew cycles. Only the variable values are summarised in the contribution margin, which is the base for the monetary evaluation of delays. The contribution margin is calculated for different possible solutions to the same conflict. The conflict resolution is optimised until the monetary loss becomes minimal. The iterative process therefore determines an optimum conflict resolution by monitoring the change to the contribution margin. Furthermore, a monetary value of each dispatching decision can also be derived.

Dynamic Construction Site Layout Using Ant Colony Optimization

Evolutionary optimization methods such as genetic algorithms have been used extensively for the construction site layout problem. More recently, ant colony optimization algorithms, which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to benchmark combinatorial optimization problems. This paper proposes a formulation of the site layout problem in terms of a sequencing problem that is suitable for solution using an ant colony optimization algorithm. In the construction industry, site layout is a very important planning problem. The objective of site layout is to position temporary facilities both geographically and at the correct time such that the construction work can be performed satisfactorily with minimal costs and improved safety and working environment. During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the construction site layout problem. This paper proposes an ant colony optimization model for construction site layout. A simple case study for a highway project is utilized to illustrate the application of the model.

Fermentation of Xylose and Glucose Mixture in Intensified Reactors by Scheffersomyces stipitis to Produce Ethanol

In this work, two fermentations at different temperatures (25 and 30ºC), with cell recycling, were accomplished to produce ethanol, using a mix of commercial substrates, xylose (70%) and glucose (30%), as organic source for Scheffersomyces stipitis. Five consecutive fermentations of 80 g L-1 (1º, 2º and 3º recycles), 96 g L-1 (4º recycle) and 120 g L-1 (5º recycle)reduced sugars led to a final maximum ethanol concentration of 17.2 and 34.5 g L-1, at 25 and 30ºC, respectively. Glucose was the preferred substrate; moreover xylose startup degradation was initiated after a remaining glucose presence in the medium. Results showed that yeast acid treatment, performed before each cycle, provided improvements on cell viability, accompanied by ethanol productivity of 2.16 g L-1 h- 1 at 30ºC. A maximum 36% of xylose was retained in the fermentation medium and after five-cycle fermentation an ethanol yield of 0.43 g ethanol/g sugars was observed. S. stipitis fermentation capacity and tolerance showed better results at 30ºC with 83.4% of theoretical yield referenced on initial biomass.

Development of Algorithms for the Study of the Image in Digital Form for Satellite Applications: Extraction of a Road Network and Its Nodes

In this paper we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We therefore have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.

Low-Cost Inertial Sensors Modeling Using Allan Variance

Micro-electromechanical system (MEMS) accelerometers and gyroscopes are suitable for the inertial navigation system (INS) of many applications due to low price, small dimensions and light weight. The main disadvantage in a comparison with classic sensors is a worse long term stability. The estimation accuracy is mostly affected by the time-dependent growth of inertial sensor errors, especially the stochastic errors. In order to eliminate negative effects of these random errors, they must be accurately modeled. In this paper, the Allan variance technique will be used in modeling the stochastic errors of the inertial sensors. By performing a simple operation on the entire length of data, a characteristic curve is obtained whose inspection provides a systematic characterization of various random errors contained in the inertial-sensor output data.

Earthquake Vulnerability and Repair Cost Estimation of Masonry Buildings in the Old City Center of Annaba, Algeria

The seismic risk mitigation from the perspective of the old buildings stock is truly essential in Algerian urban areas, particularly those located in seismic prone regions, such as Annaba city, and which the old buildings present high levels of degradation associated with no seismic strengthening and/or rehabilitation concerns. In this sense, the present paper approaches the issue of the seismic vulnerability assessment of old masonry building stocks through the adaptation of a simplified methodology developed for a European context area similar to that of Annaba city, Algeria. Therefore, this method is used for the first level of seismic vulnerability assessment of the masonry buildings stock of the old city center of Annaba. This methodology is based on a vulnerability index that is suitable for the evaluation of damage and for the creation of large-scale loss scenarios. Over 380 buildings were evaluated in accordance with the referred methodology and the results obtained were then integrated into a Geographical Information System (GIS) tool. Such results can be used by the Annaba city council for supporting management decisions, based on a global view of the site under analysis, which led to more accurate and faster decisions for the risk mitigation strategies and rehabilitation plans.

Developing a Web-Based Workflow Management System in Cloud Computing Platforms

Cloud computing is the innovative and leading information technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. In this paper, we aim at the development of workflow management system for cloud computing platforms based on our previous research on the dynamic allocation of the cloud computing resources and its workflow process. We took advantage of the HTML5 technology and developed web-based workflow interface. In order to enable the combination of many tasks running on the cloud platform in sequence, we designed a mechanism and developed an execution engine for workflow management on clouds. We also established a prediction model which was integrated with job queuing system to estimate the waiting time and cost of the individual tasks on different computing nodes, therefore helping users achieve maximum performance at lowest payment. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for cloud computing platform. This development also helps boost user productivity by promoting a flexible workflow interface that lets users design and control their tasks' flow from anywhere.

Preliminary Roadway Alignment Design: A Spatial-Data Optimization Approach

Roadway planning and design is a very complex process involving five key phases before a project is completed; planning, project development, final design, right-of-way, and construction. The planning phase for a new roadway transportation project is a very critical phase as it greatly affects all latter phases of the project. A location study is usually performed during the preliminary planning phase in a new roadway project. The objective of the location study is to develop alignment alternatives that are cost efficient considering land acquisition and construction costs. This paper describes a methodology to develop optimal preliminary roadway alignments utilizing spatial-data. Four optimization criteria are taken into consideration; roadway length, land cost, land slope, and environmental impacts. The basic concept of the methodology is to convert the proposed project area into a grid, which represents the search space for an optimal alignment. The aforementioned optimization criteria are represented in each of the grid’s cells. A spatial-data optimization technique is utilized to find the optimal alignment in the search space based on the four optimization criteria. Two case studies for new roadway projects in Duval County in the State of Florida are presented to illustrate the methodology. The optimization output alignments are compared to the proposed Florida Department of Transportation (FDOT) alignments. The comparison is based on right-of-way costs for the alignments. For both case studies, the right-of-way costs for the developed optimal alignments were found to be significantly lower than the FDOT alignments.

A Cost Effective Approach to Develop Mid-size Enterprise Software Adopted the Waterfall Model

Organizational tendencies towards computer-based information processing have been observed noticeably in the third-world countries. Many enterprises are taking major initiatives towards computerized working environment because of massive benefits of computer-based information processing. However, designing and developing information resource management software for small and mid-size enterprises under budget costs and strict deadline is always challenging for software engineers. Therefore, we introduced an approach to design mid-size enterprise software by using the Waterfall model, which is one of the SDLC (Software Development Life Cycles), in a cost effective way. To fulfill research objectives, in this study, we developed mid-sized enterprise software named “BSK Management System” that assists enterprise software clients with information resource management and perform complex organizational tasks. Waterfall model phases have been applied to ensure that all functions, user requirements, strategic goals, and objectives are met. In addition, Rich Picture, Structured English, and Data Dictionary have been implemented and investigated properly in engineering manner. Furthermore, an assessment survey with 20 participants has been conducted to investigate the usability and performance of the proposed software. The survey results indicated that our system featured simple interfaces, easy operation and maintenance, quick processing, and reliable and accurate transactions.

A Comparative Study of Malware Detection Techniques Using Machine Learning Methods

In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through (semi)-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Factor Resistance Comparison of a Long Shaft in 955 and 1055 John Deere Grain Combine

Transmission shafts are affected by various forces, for example, during acceleration or sudden breaks, bending during transportation, vertical forces that lead to cuts. One of the main failures in combines is breaking shaft which repairmen refer it. Structural resistance of canal against torque is very important in the beginning of the movement. For analyzing stress, a typical sample from a type of combine was selected, called JD955 combine. Long shaft in this combine was analyzed with finite element method by Ansys13 generic package under static load. Conducted analysis showed that there is a maximum stress in contact surfaces of indentations and also in place of changing diameter. Safety factor value is low in parts of the shaft and this increases the probability of failure at these points. To improve the conditions with the least cost and an approach of product improvement, using alternative alloy is important.