Search results for: Event Process Chains

Authors: Erica T. R. Mendonça, Caroline M. B. de Araujo, Filho, Osvaldo Chiavone, Sobrinho, Maurício A. da Motta

Abstract:

Oil and gas exploration is an essential activity for modern society, although the supply of its global demand has caused enough damage to the environment, mainly due to produced water generation, which is an effluent associated with the oil and gas produced during oil extraction. It is the aim of this study to evaluate the treatment of produced water, in order to reduce its oils and greases content (OG), by using flotation as a pre-treatment, combined with oxidation for the remaining organic load degradation. Thus, there has been tested Advanced Oxidation Process (AOP) using both Fenton and photo-Fenton reactions, as well as a chemical oxidation treatment using sodium ferrate(VI), Na₂[FeO₄], as a strong oxidant. All the studies were carried out using real samples of produced water from petroleum industry. The oxidation process using ferrate(VI) ion was studied based on factorial experimental designs. The factorial design was used in order to study how the variables pH, temperature and concentration of Na₂[FeO₄] influences the O&G levels. For the treatment using ferrate(VI) ion, the results showed that the best operating point is obtained when the temperature is 28 °C, pH 3, and a 2000 mg.L^-1 solution of Na₂[FeO₄] is used. This experiment has achieved a final O&G level of 4.7 mg.L^-1, which means 94% percentage removal efficiency of oils and greases. Comparing Fenton and photo-Fenton processes, it was observed that the Fenton reaction did not provide good reduction of O&G (around 20% only). On the other hand, a degradation of approximately 80.5% of oil and grease was obtained after a period of seven hours of treatment using photo-Fenton process, which indicates that the best process combination has occurred between the flotation and the photo-Fenton reaction using solar radiation, with an overall removal efficiency of O&G of approximately 89%.

Keywords: Advanced oxidation process, ferrate(VI) ion, oils and greases removal, produced water treatment.

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Authors: Om Prakash Verma, Rajesh Singla, Rajesh Kumar

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Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired temperature within a specified period of time to avoid the overshoot and absolute error, with better temperature tracking capability, else the process is disturbed.

To overcome above difficulties intelligent controllers, Fuzzy Logic (FL) and Adaptive Neuro-Fuzzy Inference System (ANFIS), are proposed in this paper. The Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. To design ANFIS, Fuzzy-Inference-System is combined with learning capability of Neural-Network.

It is analyzed that ANFIS is best suitable for adaptive temperature control of above system. As compared to PID and FLC, ANFIS produces a stable control signal. It has much better temperature tracking capability with almost zero overshoot and minimum absolute error.

Keywords: PID Controller, FLC, ANFIS, Non-Linear Control System, Water-Bath System, MATLAB-7.

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Authors: Tales H. J. Moreira, Thiago M. R. Dias, Gray F. Moita

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The adviser-advised relationship, in addition to the evident propagation of knowledge, can provide an increase in the scientific production of the advisors. Specifically, in post-graduate programs, in which the advised submit diverse papers in different means of publication, these end up boosting the production of their advisor, since in general the advisors appear as co-authors, responsible for instructing and assisting in the development of the work. Therefore, to visualize the orientation process and the scientific production resulting from this relation is another important way of analyzing the scientific collaboration in the different areas of knowledge. In this work, are used the data of orientations and postgraduate supervisions from the Lattes curricula, from the main advisors who work in the Engineering area, to obtain an overview of the process of orientation of this group, and even, to produce Academic genealogical trees, where it is possible to verify how knowledge has spread in the diverse areas of engineering.

Keywords: Academic genealogy, advice, engineering, lattes platform.

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Authors: Sahil Sharma, Mukesh Gupta, Raj Kumar, N. S Bindra

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This paper presents an experimental investigation on the optimization and the effect of the cutting parameters on Material Removal Rate (MRR) in Plasma Arc Cutting (PAC) of EN-45A Material using Taguchi L ₁₆ orthogonal array method. Four process variables viz. cutting speed, current, stand-off-distance and plasma gas pressure have been considered for this experimental work. Analysis of variance (ANOVA) has been performed to get the percentage contribution of each process parameter for the response variable i.e. MRR. Based on ANOVA, it has been observed that the cutting speed, current and the plasma gas pressure are the major influencing factors that affect the response variable. Confirmation test based on optimal setting shows the better agreement with the predicted values.

Keywords: Analysis of variance, Material removal rate, plasma arc cutting, Taguchi method.

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Authors: Hamza M. A. Muftah

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The study investigates the possible connections between acculturation and the acquisition of a second language on Libyan teenage students in Australia. Specifically, the study examined how various socio-psychological variables influenced English oral proficiency (oral communicative competence and native-like pronunciation) of the participants. In addition, it looked at whether or not SLA affects acculturation towards the target language group. This is achieved by analysing data obtained from semi-structured interviews and oral proficiency interviews. The present study found a definite link between the students’ acculturation process and their oral communicative competence but not native-like pronunciation. The results also provided evidence that SLL process has an impact on integration into the host society as well as the acquisition of a second language culture. Yet, it did not draw a clear conclusion with respect to how such a process affects these aspects.

Keywords: Acculturation, Native-like pronunciation, Oral communicative competence, Second language acquisition, Second language learners.

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Authors: Guranda Tevdoradze

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By the end of XX century in the structure of humanity some changes have been provoked: a new ethnos - Ethnos of Intellect is formed and is still being formed, beside the historical types of ethnoses: open ethnos, closed ethnos, wandering ethnos, dead ethnos, - and this event was caused by the technical progress, development of informational and transport communications, especially - by creation of Internet. The Ethnos of Intellect is something very close to the ÔÇ×Information Society“ described by J. Ellule and Y. Masuda that was regarded as the culture of XXI century, being an antithesis for technical and technicistical civilizations, but it-s necessary to indicate also the essential difference between these concepts: the Ethnos of Intellect is the antithesis of Socium. The existence of such an ethnos within human society that has already become an Information Society itself is extremely important in observing legally and informatically a new kind of reins in the hands of the political power, revealing every attempt to violate the human rights of simple citizens. A concrete example of some conjunction points of legal informatics and informatical law in a certain kind of ambiental studies of the project ''State Registre of Population'' in Russia is very eloquent.

Keywords: Culturology, Legal Informatics, Sociology of Groups.

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Authors: Dorota Rucińska

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This theoretical paper combines the academic discourse regarding a specific part of dark tourism. Based on the literature analysis, distinction of natural disasters in thanatourism was investigated, which is connected with dynamic geographical conditions. Natural disasters used to play an important role in social life by their appearance in myths and religions. Nowadays, tourists pursuing natural hazards can be divided into three groups: Those interested in natural hazards themselves; those interested in landscape deformation and experiencing emotions shortly after extreme events - natural disasters - occur; and finally those interested in historic places log after an extreme event takes place. An important element of the natural disaster tourism is quick access to information on the location of a disaster and the destination of a potential excursion. Natural disaster tourism suits alternative tourism, yet it is opposed culture tourism, and sustainable tourism. The paper compares types and groups of tourists. It also considers the contradictions that describe dualism, which exists in dark tourism.

Keywords: Dark tourism, dualism, natural disasters, natural hazards, thanatoursim.

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Authors: Ayman A. AbuBaker, Rami S.Qahwaji, Musbah J. Aqel, Mohmmad H. Saleh

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Two algorithms are proposed to reduce the storage requirements for mammogram images. The input image goes through a shrinking process that converts the 16-bit images to 8-bits by using pixel-depth conversion algorithm followed by enhancement process. The performance of the algorithms is evaluated objectively and subjectively. A 50% reduction in size is obtained with no loss of significant data at the breast region.

Keywords: Breast cancer, Image processing, Image reduction, Mammograms, Image enhancement

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Authors: Eylem Koç, Hasan Arda Burhan

Abstract:

Location selection presents a crucial decision problem in today’s business world where strategic decision making processes have critical importance. Thus, location selection has strategic importance for companies in boosting their strength regarding competition, increasing corporate performances and efficiency in addition to lowering production and transportation costs. A right choice in location selection has a direct impact on companies’ commercial success. In this study, a store location selection problem of Carglass Turkey which operates in vehicle glass branch is handled. As this problem includes both tangible and intangible criteria, Analytic Network Process (ANP) was accepted as the main methodology. The model consists of control hierarchy and BOCR subnetworks which include clusters of actors, alternatives and criteria. In accordance with the management’s choices, five different locations were selected. In addition to the literature review, a strict cooperation with the actor group was ensured and maintained while determining the criteria and during whole process. Obtained results were presented to the management as a report and its feasibility was confirmed accordingly.

Keywords: Analytic Network Process, BOCR, location selection, multi-actor decision making, multi-criteria decision making, real life problem.

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Authors: Hafizullah A. Hashim, Aniza. A

Abstract:

The Spiral development model has been used successfully in many commercial systems and in a good number of defense systems. This is due to the fact that cost-effective incremental commitment of funds, via an analogy of the spiral model to stud poker and also can be used to develop hardware or integrate software, hardware, and systems. To support adaptive, semantic collaboration between domain experts and knowledge engineers, a new knowledge engineering process, called Spiral_OWL is proposed. This model is based on the idea of iterative refinement, annotation and structuring of knowledge base. The Spiral_OWL model is generated base on spiral model and knowledge engineering methodology. A central paradigm for Spiral_OWL model is the concentration on risk-driven determination of knowledge engineering process. The collaboration aspect comes into play during knowledge acquisition and knowledge validation phase. Design rationales for the Spiral_OWL model are to be easy-to-implement, well-organized, and iterative development cycle as an expanding spiral.

Keywords: Domain Expert, Knowledge Base, Ontology, Software Process.

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Authors: M. Rossini, A. Portioli Studacher

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The market competition is moving from the single firm to the whole supply chain because of increasing competition and growing need for operational efficiencies and customer orientation. Supply chain management allows companies to look beyond their organizational boundaries to develop and leverage resources and capabilities of their supply chain partners. This creates competitive advantages in the marketplace and because of this SCM has acquired strategic importance. Lean Approach is a management strategy that focuses on reducing every type of waste present in an organization. This approach is becoming more and more popular among supply chain managers. The supply chain application of lean approach is not frequent. In particular, it is not well studied which are the impacts of lean approach principles in a supply chain context. In literature there are only few studies aimed at understanding the qualitative impact of the lean approach in supply chains. Therefore, the goal of this research work is to study the impacts of lean principles implementation along a supply chain. To achieve this, a simulation model of a threeechelon multi-product supply chain has been built. Kanban system (and several priority policies) and setup time reduction degrees are implemented in the lean-configured supply chain to apply pull and lot-sizing decrease principles respectively. To evaluate the benefits of lean approach, lean supply chain is compared with an EOQ-configured supply chain. The simulation results show that Kanban system and setup-time reduction improve inventory stock level. They also show that logistics efforts are affected to lean implementation degree. The paper concludes describing performances of lean supply chain in different contexts.

Keywords: Inventory policy, Kanban, lean supply chain, simulation study, supply chain management, planning.

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Authors: Rosmina Bustami, Charles Bong, Darrien Mah, Afnie Hamzah, Marina Patrick

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The distressing flood scenarios that occur in recent years at the surrounding areas of Sarawak River have left damages of properties and indirectly caused disruptions of productive activities. This study is meant to reconstruct a 100-year flood event that took place in this river basin. Sarawak River Subbasin was chosen and modeled using the one-dimensional hydrodynamic modeling approach using InfoWorks River Simulation (RS), in combination with Geographical Information System (GIS). This produces the hydraulic response of the river and its floodplains in extreme flooding conditions. With different parameters introduced to the model, correlations of observed and simulated data are between 79% – 87%. Using the best calibrated model, flood mitigation structures are imposed along the sub-basin. Analysis is done based on the model simulation results. Result shows that the proposed retention ponds constructed along the sub-basin provide the most efficient reduction of flood by 34.18%.

Keywords: Flood, Flood mitigation structure, InfoWorks RS, Retention pond, Sarawak River sub-basin.

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Authors: A. M. Qahtani, G. B. Wills, A. M. Gravell

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Communicating and managing customers’ requirements in software development projects play a vital role in the software development process. While it is difficult to do so locally, it is even more difficult to communicate these requirements over distributed boundaries and to convey them to multiple distribution customers. This paper discusses the communication of multiple distribution customers’ requirements in the context of customised software products. The main purpose is to understand the challenges of communicating and managing customisation requirements across distributed boundaries. We propose a model for Communicating Customisation Requirements of Multi-Clients in a Distributed Domain (CCRD). Thereafter, we evaluate that model by presenting the findings of a case study conducted with a company with customisation projects for 18 distributed customers. Then, we compare the outputs of the real case process and the outputs of the CCRD model using simulation methods. Our conjecture is that the CCRD model can reduce the challenge of communication requirements over distributed organisational boundaries, and the delay in decision making and in the entire customisation process time.

Keywords: Customisation Software Products, Global Software Engineering, Local Decision Making, Requirement Engineering, Simulation Model.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour , Foad Saadi

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In this paper back-propagation artificial neural network (BPANN) is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The output data are the coefficient of polynomial that fitted on barreling curves. Neural network was trained using barreling curves generated by finite element simulations of the upsetting and the corresponding material parameters. This technique was tested for three different specimens and can be successfully employed to predict the deformation of the upsetting process

Keywords: Back-propagation artificial neural network(BPANN), prediction, upsetting

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Authors: S. Pullteap, M. Pathomsuriyaporn

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In this article, a study of employee’s opinion to the factors that affect to the flood preventive and the corrective action plan in an electronic industry at the Sharp Manufacturing (Thailand) Co., Ltd. has been investigated. The surveys data of 175 workers and supervisors have, however, been selected for data analysis. The results is shown that the employees emphasize about the needs in a subsidy at the time of disaster at high levels of 77.8%, as the plan focusing on flood prevention of the rehabilitation equipment is valued at the intermediate level, which is 79.8%. Demonstration of the hypothesis has found that the different education levels has thus been affected to the needs factor at the flood disaster time. Moreover, most respondents give priority to flood disaster risk management factor. Consequently, we found that the flood prevention plan is valued at high level, especially on information monitoring, which is 93.4% for the supervisor item. The respondents largely assume that the flood will have impacts on the industry, up to 80%, thus to focus on flood management plans is enormous.

Keywords: Flood prevention plan, flood event, electronic industrial plant, disaster, risk management.

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Authors: P. Zamov, H. Spangenberg

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Presents a concept for a multidisciplinary process supporting effective task transitions between different technical domains during the architectural design stage. A system configuration challenge is the multifunctional driven increased solution space. As a consequence, more iteration is needed to find a global optimum, i.e. a compromise between involved disciplines without negative impact on development time. Since state of the art standards like ISO 15288 and VDI 2206 do not provide a detailed methodology on multidisciplinary design process, higher uncertainties regarding final specifications arise. This leads to the need of more detailed and standardized concepts or processes which could mitigate risks. The performed work is based on analysis of multidisciplinary interaction, of modeling and simulation techniques. To demonstrate and prove the applicability of the presented concept, it is applied to the design of aircraft high lift systems, in the context of the engineering disciplines kinematics, actuation, monitoring, installation and structure design.

Keywords: Systems engineering, multidisciplinary, architectural design, high lift system.

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Authors: Mercy M. Ramakokovhu, Henry Kasaini, Richard K.K. Mbaya

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The copper flotation tailings from Konkola Copper mine in Nchanga, Zambia were used in the study. The purpose of this study was to determine the leaching characteristics of the tailings material prior and after the physical beneficiation process is employed. The Knelson gravity concentrator (KC-MD3) was used for the beneficiation process. The copper leaching efficiencies and impurity co-extraction percentages in both the upgraded and the raw feed material were determined at different pH levels and temperature. It was observed that the copper extraction increased with an increase in temperature and a decrease in pH levels. In comparison to the raw feed sample, the upgraded sample reported a maximum copper extraction of 69% which was 9%, higher than raw feed % extractions. The impurity carry over was reduced from 18% to 4 % on the upgraded sample. The reduction in impurity co-extraction was as a result of the removal of the reactive gangue elements during the upgrading process, this minimized the number of side reaction occurring during leaching.

Keywords: Atmospheric leaching, Copper, Iron, Knelson concentrator

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Authors: Hamideh Mahdavifar, Ramin Nassiri, Alireza Bagheri

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Enterprise Architecture (EA) is a framework for description, coordination and alignment of all activities across the organization in order to achieve strategic goals using ICT enablers. A number of EA-compatible frameworks have been developed. We, in this paper, mainly focus on Federal Enterprise Architecture Framework (FEAF) since its reference models are plentiful. Among these models we are interested here in its business reference model (BRM). The test process is one important subject of an EA project which is to somewhat overlooked. This lack of attention may cause drawbacks or even failure of an enterprise architecture project. To address this issue we intend to use International Software Testing Qualification Board (ISTQB) framework and standard test suites to present a method to improve EA testing process. The main challenge is how to communicate between the concepts of EA and ISTQB. In this paper, we propose a method for integrating these concepts.

Keywords: Business Reference Model (BRM), Federal Enterprise Architecture (FEA), ISTQB, Test Techniques.

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Authors: R. Sahraian, A. Karampour Haghighi, E. Ghasemi

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Process planning and production scheduling play important roles in manufacturing systems. In this paper a multiobjective mixed integer linear programming model is presented for the integrated planning and scheduling of multi-product. The aim is to find a set of high-quality trade-off solutions. This is a combinatorial optimization problem with substantially large solution space, suggesting that it is highly difficult to find the best solutions with the exact search method. To account for it, a PSO-based algorithm is proposed by fully utilizing the capability of the exploration search and fast convergence. To fit the continuous PSO in the discrete modeled problem, a solution representation is used in the algorithm. The numerical experiments have been performed to demonstrate the effectiveness of the proposed algorithm.

Keywords: Integrated process planning and scheduling, multi objective, MILP, Particle swarm optimization

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Authors: Kuvshinov, D., Siswanto, A., Zimmerman, W. B.

Abstract:

A phorbol-12-myristate-13-acetate (TPA) is a synthetic analogue of phorbol ester (PE), a natural toxic compound of Euphorbiaceae plant. The oil extracted from plants of this family is useful source for primarily biofuel. However this oil might also be used as a foodstuff due to its significant nutrition content. The limitations for utilizing the oil as a foodstuff are mainly due to a toxicity of PE. Currently, a majority of PE detoxification processes are expensive as include multi steps alcohol extraction sequence.

Ozone is considered as a strong oxidative agent. It reacts with PE by attacking the carbon-carbon double bond of PE. This modification of PE molecular structure yields a non toxic ester with high lipid content.

This report presents data on development of simple and cheap PE detoxification process with water application as a buffer and ozone as reactive component. The core of this new technique is an application for a new microscale plasma unit to ozone production and the technology permits ozone injection to the water-TPA mixture in form of microbubbles.

The efficacy of a heterogeneous process depends on the diffusion coefficient which can be controlled by contact time and interfacial area. The low velocity of rising microbubbles and high surface to volume ratio allow efficient mass transfer to be achieved during the process. Direct injection of ozone is the most efficient way to process with such highly reactive and short lived chemical.

Data on the plasma unit behavior are presented and the influence of gas oscillation technology on the microbubble production mechanism has been discussed. Data on overall process efficacy for TPA degradation is shown.

Keywords: Microbubble, ozonolysis, synthetic phorbol ester.

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Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

Abstract:

Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the point specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: Milling process, rotational speed, Artificial Neural Networks, temperature.

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Authors: Fuyan Sun, Guang Wang, Xueyuan Nie

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In this study, a plasma electrolytic oxidation (PEO) process was used to form titanium-aluminum oxide coating on aluminized steel. The present work was mainly to study the effects of treatment time of PEO process on properties of the titanium coating. A potentiodynamic polarization corrosion test was employed to investigate the corrosion resistance of the coating. The friction coefficient and wear resistance of the coating were studied by using pin-on-disc test. The thermal transfer behaviors of uncoated and PEO-coated aluminized steels were also studied. It could be seen that treatment time of PEO process significantly influenced the properties of the titanium oxide coating. Samples with a longer treatment time had a better performance for corrosion and wear protection. This paper demonstrated different treatment time could alter the surface behavior of the coating material.

Keywords: Corrosion, plasma electrolytic oxidation, thermal property, titanium-aluminum oxide.

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Authors: Masoud Mohammadpour, Blair Carlson, Radovan Kovacevic

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The quality of laser welded-brazed (LWB) joints were strongly dependent on the main process parameters, therefore the effect of laser power (3.2–4 kW), welding speed (60–80 mm/s) and wire feed rate (70–90 mm/s) on mechanical strength and surface roughness were investigated in this study. The comprehensive optimization process by means of response surface methodology (RSM) and desirability function was used for multi-criteria optimization. The experiments were planned based on Box– Behnken design implementing linear and quadratic polynomial equations for predicting the desired output properties. Finally, validation experiments were conducted on an optimized process condition which exhibited good agreement between the predicted and experimental results. AlSi3Mn1 was selected as the filler material for joining aluminum alloy 6022 and hot-dip galvanized steel in coach peel configuration. The high scanning speed could control the thickness of IMC as thin as 5 µm. The thermal simulations of joining process were conducted by the Finite Element Method (FEM), and results were validated through experimental data. The Fe/Al interfacial thermal history evidenced that the duration of critical temperature range (700–900 °C) in this high scanning speed process was less than 1 s. This short interaction time leads to the formation of reaction-control IMC layer instead of diffusion-control mechanisms.

Keywords: Laser welding-brazing, finite element, response surface methodology, multi-response optimization, cross-beam laser.

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Authors: C. Ramsauer, J. Karandikar, D. Leitner, T. Schmitz, F. Bleicher

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Machining instability, or chatter, can impose an important limitation to discrete part machining. In this work, a networked implementation of milling stability optimization with Bayesian learning is presented. The milling process was monitored with a wireless sensory tool holder instrumented with an accelerometer at the TU Wien, Vienna, Austria. The recorded data from a milling test cut were used to classify the cut as stable or unstable based on a frequency analysis. The test cut result was used in a Bayesian stability learning algorithm at the University of Tennessee, Knoxville, Tennessee, USA. The algorithm calculated the probability of stability as a function of axial depth of cut and spindle speed based on the test result and recommended parameters for the next test cut. The iterative process between two transatlantic locations was repeated until convergence to a stable optimal process parameter set was achieved.

Keywords: Bayesian learning, instrumented tool holder, machining stability, optimization strategy.

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Authors: Asar Khan, Peter D. Widdop, Andrew J. Day, Aliaster S. Wood, Steve, R. Mounce, John Machell

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This paper describes an automated event detection and location system for water distribution pipelines which is based upon low-cost sensor technology and signature analysis by an Artificial Neural Network (ANN). The development of a low cost failure sensor which measures the opacity or cloudiness of the local water flow has been designed, developed and validated, and an ANN based system is then described which uses time series data produced by sensors to construct an empirical model for time series prediction and classification of events. These two components have been installed, tested and verified in an experimental site in a UK water distribution system. Verification of the system has been achieved from a series of simulated burst trials which have provided real data sets. It is concluded that the system has potential in water distribution network management.

Keywords: Detection, leakage, neural networks, sensors, water distribution networks

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Authors: Emad Ali, Inas Alnashef, Abdelhamid Ajbar, Mohamed HadjKali, Sarwono Mulyono

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In this work, ionic liquids (ILs) for CO2 capturing in typical absorption/stripper process are considered. The use of ionic liquids is considered to be cost-effective because it requires less energy for solvent recovery compared to other conventional processes. A mathematical model is developed for the process based on Peng-Robinson (PR) equation of state (EoS) which is validated with experimental data for various solutions involving CO2. The model is utilized to study the sorbent and energy demand for three types of ILs at specific CO2 capturing rates. The energy demand is manifested by the vapor-liquid equilibrium temperature necessary to remove the captured CO2 from the used solvent in the regeneration step. It is found that higher recovery temperature is required for solvents with higher solubility coefficient. For all ILs, the temperature requirement is less than that required by the typical monoethanolamine (MEA) solvent. The effect of the CO2 loading in the sorbent stream on the process performance is also examined.

Keywords: Ionic liquid, CO2 capturing, CO2 solubility, Vaporliquid equilibrium.

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Authors: Ichihan Tai, Bill Olson, Paul Blessner

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Traditional early warning systems that alarm against crisis are generally based on structured or numerical data; therefore, a system that can make predictions based on unstructured textual data, an uncorrelated data source, is a great complement to the traditional early warning systems. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX), commonly referred to as the fear index, measures the cost of insurance against market crash, and spikes in the event of crisis. In this study, news data is consumed for prediction of whether there will be a market-wide crisis by predicting the movement of the fear index, and the historical references to similar events are presented in an unsupervised manner. Topic modeling-based prediction and representation are made based on daily news data between 1990 and 2015 from The Wall Street Journal against VIX index data from CBOE.

Keywords: Early Warning System, Knowledge Management, Topic Modeling, Market Prediction.

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Authors: Shahin Mirshekari, Mohammadreza Moradi, Hossein Jafari, Mehdi Jafari, Mohammad Ensaf

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This research employs Gaussian Process Regression (GPR) with an ensemble kernel, integrating Exponential Squared, Revised Matérn, and Rational Quadratic kernels to analyze pharmaceutical sales data. Bayesian optimization was used to identify optimal kernel weights: 0.76 for Exponential Squared, 0.21 for Revised Matérn, and 0.13 for Rational Quadratic. The ensemble kernel demonstrated superior performance in predictive accuracy, achieving an R² score near 1.0, and significantly lower values in MSE, MAE, and RMSE. These findings highlight the efficacy of ensemble kernels in GPR for predictive analytics in complex pharmaceutical sales datasets.

Keywords: Gaussian Process Regression, Ensemble Kernels, Bayesian Optimization, Pharmaceutical Sales Analysis, Time Series Forecasting, Data Analysis.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour

Abstract:

In this paper back-propagation artificial neural network (BPANN )with Levenberg–Marquardt algorithm is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The output data are the coefficient of polynomial that fitted on barreling curves. Neural network was trained using barreling curves generated by finite element simulations of the upsetting and the corresponding material parameters. This technique was tested for three different specimens and can be successfully employed to predict the deformation of the upsetting process

Keywords: Back-propagation artificial neural network(BPANN), prediction, upsetting

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Authors: Julio Molleda, Daniel F. García, Juan C. Granda, Francisco J. Suárez

Abstract:

One of the main trouble in a steel strip manufacturing line is the breakage of whatever weld carried out between steel coils, that are used to produce the continuous strip to be processed. A weld breakage results in a several hours stop of the manufacturing line. In this process the damages caused by the breakage must be repaired. After the reparation and in order to go on with the production it will be necessary a restarting process of the line. For minimizing this problem, a human operator must inspect visually and manually each weld in order to avoid its breakage during the manufacturing process. The work presented in this paper is based on the Bayesian decision theory and it presents an approach to detect, on real-time, steel strip defective welds. This approach is based on quantifying the tradeoffs between various classification decisions using probability and the costs that accompany such decisions.

Keywords: Classification, Pattern Recognition, ProbabilisticReasoning, Statistical Data Analysis.

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