Search results for: process modelling

Authors: Yuan Yang, Mickey Lam

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Oral dissolvable films have been considered as a unique alternative approach to conventional oral dosage forms. The films could be administrated via the gastrointestinal tract as conventional dosages or through sublingual/buccal mucosa membranes, which could enhance drug bioavailability by avoiding the first-pass effect and improving permeability due to high blood flow and lymphatic circulation. This work has described a state-of-art technic using nano-emulsion/nano-suspension as a precursor for the film to enhance the bioavailability of BCS class II drugs. The drug molecules are consequentially processed through the emulsification, gelation, and film-casting processes. The gelation process is critical to stabilizing the nano-emulsion for the film-casting as well as controlling the drug release process. Furthermore, the size of the nanoparticle on the film has a strong correlation with the size of the micelles in the precursor and the condition of the gelation process. It has been discovered that nanoparticle from 200 nm to 300 nm has shown the highest permeability for sublingual administration. In one example shown in work, the bioavailability of a low solubilize drug has been increased from 10% to 24% via sublingual administration of the film. The increasing of the bioavailability was thought to be associated with the enhancement of the diffusion process of the drug in the saliva layer above the mucosa membrane and the fact that the presents of the emulsifier help lose the rigid junction of the mucosa cells.

Keywords: oral dissolvable film, nano-suspension, nano-emulsion, bioavailability

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Authors: Benjamin Castillo, Luis Pastenes, Fernando Cordova

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The pathogen growth in animal source foods is a common problem in the food industry, causing monetary losses due to the spoiling of products or food intoxication outbreaks in the community. In this sense, the quality of the product is reflected by the population of deteriorating agents present in it, which are mainly bacteria. The factors which are likely associated with freshness in animal source foods are temperature and processing, storage, and transport times. However, the level of deterioration of products depends, in turn, on the characteristics of the bacterial population, causing the decomposition or spoiling, such as pH level and toxins. Knowing the growth dynamics of the agents that are involved in product contamination allows the monitoring for more efficient processing. This means better quality and reasonable costs, along with a better estimation of necessary time and temperature intervals for transport and storage in order to preserve product quality. The objective of this project is to design a secondary model that allows measuring the impact on temperature bacterial growth and the competition for pH adequacy and release of bacteriocins in order to describe such phenomenon and, thus, estimate food product half-life with the least possible risk of deterioration or spoiling. In order to achieve this objective, the authors propose an analysis of a three-dimensional ordinary differential which includes; logistic bacterial growth extended by the inhibitory action of bacteriocins including the effect of the medium pH; change in the medium pH levels through an adaptation of the Luedeking-Piret kinetic model; Bacteriocin concentration modeled similarly to pH levels. These three dimensions are being influenced by the temperature at all times. Then, this differential system is expanded, taking into consideration the variable temperature and the concentration of pulsed bacteriocins, which represent characteristics inherent of the modeling, such as transport and storage, as well as the incorporation of substances that inhibit bacterial growth. The main results lead to the fact that temperature changes in an early stage of transport increased the bacterial population significantly more than if it had increased during the final stage. On the other hand, the incorporation of bacteriocins, as in other investigations, proved to be efficient in the short and medium-term since, although the population of bacteria decreased, once the bacteriocins were depleted or degraded over time, the bacteria eventually returned to their regular growth rate. The efficacy of the bacteriocins at low temperatures decreased slightly, which equates with the fact that their natural degradation rate also decreased. In summary, the implementation of the mathematical model allowed the simulation of a set of possible bacteria present in animal based products, along with their properties, in various transport and storage situations, which led us to state that for inhibiting bacterial growth, the optimum is complementary low constant temperatures and the initial use of bacteriocins.

Keywords: bacterial growth, bacteriocins, mathematical modelling, temperature

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Authors: Rahul R. Gurpude, Pallvita Yadav, Amrut Mulay

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In recent years, there has been a growing focus on advanced manufacturing processes, and one such emerging process is wire electric discharge machining (WEDM). WEDM is a precision machining process specifically designed for cutting electrically conductive materials with exceptional accuracy. It achieves material removal from the workpiece metal through spark erosion facilitated by electricity. Initially developed as a method for precision machining of hard materials, WEDM has witnessed significant advancements in recent times, with numerous studies and techniques based on electrical discharge phenomena being proposed. These research efforts and methods in the field of ED encompass a wide range of applications, including mirror-like finish machining, surface modification of mold dies, machining of insulating materials, and manufacturing of micro products. WEDM has particularly found extensive usage in the high-precision machining of complex workpieces that possess varying hardness and intricate shapes. During the cutting process, a wire with a diameter ranging from 0.18mm is employed. The evaluation of EDM performance typically revolves around two critical factors: material removal rate (MRR) and surface roughness (SR). To comprehensively assess the impact of machining parameters on the quality characteristics of EDM, an Analysis of Variance (ANOVA) was conducted. This statistical analysis aimed to determine the significance of various machining parameters and their relative contributions in controlling the response of the EDM process. By undertaking this analysis, optimal levels of machining parameters were identified to achieve desirable material removal rates and surface roughness.

Keywords: WEDM, MRR, optimization, surface roughness

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Authors: Tomasz Borowski, Dawid Sołoducha, Rafał Rakoczy, Marian Kordas

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The growing interest in magnetic fields applications is visible due to the increased number of articles on this topic published in the last few years. In this study, the influence of various magnetic fields (MF) on the mass transfer process was examined. To carry out the prototype set-up equipped with an MF generator that is able to generate a pulsed magnetic field (PMF), oscillating magnetic field (OMF), rotating magnetic field (RMF) and static magnetic field (SMF) was used. To demonstrate the effect of MF’s on mass transfer, the calcium carbonate precipitation process was selected. To the vessel with attached conductometric probes and placed inside the generator, specific doses of calcium chloride and sodium carbonate were added. Electrical conductivity changes of the mixture inside the vessel were measured over time until equilibrium was established. Measurements were conducted for various MF strengths and concentrations of added chemical compounds. Obtained results were analyzed, which allowed to creation of mathematical correlation models showing the influence of MF’s on the studied process.

Keywords: mass transfer, oscillating magnetic field, rotating magnetic field, static magnetic field

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Authors: Expedito Pinto De Paula Junior

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Current systems such as artificial satellites, airplanes, automobiles, turbines, power systems and air traffic controls are becoming increasingly more complex and/or highly integrated as defined in SAE-ARP-4754A (Society Automotive Engineering - Certification considerations for highly-integrated or complex aircraft systems standard). Among other processes, the development of such systems requires careful Change and Configuration Management (CCM) to establish and maintain product integrity. Understand the maturity of CCM process based in historical approach is crucial for better implementation in hardware and software lifecycle. The sense of work organization, in all fields of development is directly related to the order and interrelation of the parties, changes in time, and record of these changes. Generally, is observed that engineers, administrators and managers invest more time in technical activities than in organization of work. More these professionals are focused in solving complex problems with a purely technical bias. CCM process is fundamental for development, production and operation of new products specially in the safety critical systems. The objective of this paper is open a discussion about the historical revision based in standards focus of CCM around the world in order to understand and reflect the importance across the years, the contribution of this process for technology evolution, to understand the mature of organizations in the system lifecycle project and the benefits of CCM to avoid errors and mistakes during the Lifecycle Product.

Keywords: changes, configuration management, historical, revision

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Authors: Mohamed Yousef, Magdy Samuel, Maha El-Meligy, Taher El-Bitar

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The present work is dealing with 2% Si-steel alloy. The alloy contains 0.05% C as well as 0.85% Al. The alloy under investigation would be used for electrical transformation purposes. A heating (expansion) - cooling (contraction) dilation investigation was executed to detect the a, a+g, and g transformation temperatures at the inflection points of the dilation curve. On heating, primary a  was detected at a temperature range between room temperature and 687 ^oC. The domain of a+g was detected in the range between 687 ^oC and 746 ^oC. g phase exists in the closed g region at the range between 746 ^oC and 1043 ^oC. The domain of a phase appears again at a temperature range between 1043 and 1105 ^oC, and followed by secondary a at temperature higher than 1105 ^oC. A physical simulation of thermo-mechanical processing on the as-cast alloy was carried out. The simulation process took into consideration the hot flat rolling pilot plant parameters. The process was executed on the thermo-mechanical simulator (Gleeble 3500). The process was designed to include seven consecutive passes. The 1^st pass represents the roughing stage, while the remaining six passes represent finish rolling stage. The whole process was executed at the temperature range from 1100 ^oC to 900 ^oC. The amount of strain starts with 23.5% at the roughing pass and decreases continuously to reach 7.5 % at the last finishing pass. The flow curve of the alloy can be abstracted from the stress-strain curves representing simulated passes. It shows alloy hardening from a pass to the other up to pass no. 6, as a result of decreasing the deformation temperature and increasing of cumulative strain. After pass no. 6, the deformation process enhances the dynamic recrystallization phenomena to appear, where the z-parameter would be high.

Keywords: si- steel, hot deformability, critical transformation temperature, physical simulation, thermo-mechanical processing, flow curve, dynamic softening.

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Authors: James Moir

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The mainstay of Big Data is prediction in that it allows practitioners, researchers, and policy analysts to predict trends based upon the analysis of large and varied sources of data. These can range from changing social and political opinions, patterns in crimes, and consumer behaviour. Big Data has therefore shifted the criterion of success in science from causal explanations to predictive modelling and simulation. The 19th-century science sought to capture phenomena and seek to show the appearance of it through causal mechanisms while 20th-century science attempted to save the appearance and relinquish causal explanations. Now 21st-century science in the form of Big Data is concerned with the prediction of appearances and nothing more. However, this pulls social science back in the direction of a more rule- or law-governed reality model of science and away from a consideration of the internal nature of rules in relation to various practices. In effect Big Data offers us no more than a world of surface appearance and in doing so it makes disappear any context-specific conceptual sensitivity.

Keywords: big data, appearance, disappearance, surface, epistemology

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Authors: A. Nusrath Unissa, Sameer Hassan, Luke Elizabeth Hanna

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Altered drug binding may be an important factor in isoniazid (INH) resistance, rather than major changes in the enzyme’s activity as a catalase or peroxidase (KatG). The identification of structural or functional defects in the mutant KatGs responsible for INH resistance remains as an area to be explored. In this connection, the differences in the binding affinity between wild-type (WT) and mutants of KatG were investigated, through the generation of three mutants of KatG, Ser315Thr [S315T], Ser315Asn [S315N], Ser315Arg [S315R] and a WT [S315]) with the help of software-MODELLER. The mutants were docked with INH using the software-GOLD. The affinity is lower for WT than mutant, suggesting the tight binding of INH with the mutant protein compared to WT type. These models provide the in silico evidence for the binding interaction of KatG with INH and implicate the basis for rationalization of INH resistance in naturally occurring KatG mutant strains of Mycobacterium tuberculosis.

Keywords: Mycobacterium tuberculosis, KatG, INH resistance, mutants, modelling, docking

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Authors: Vytautas Galvanauskas, Vykantas Grincas, Rimvydas Simutis

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This paper investigates a possible practical solution for reasonable oxygen supply during the pluripotent stem cells expansion processes, where the stem cells propagate as aggregates in stirred-suspension bioreactors. Low glucose and low oxygen concentrations are preferred for efficient proliferation of pluripotent stem cells. However, strong oxygen limitation, especially inside of cell aggregates, can lead to cell starvation and death. In this research, the oxygen concentration profile inside of stem cell aggregates in a stem cell expansion process was predicted using a modified oxygen diffusion model. This profile can be realized during the stem cells cultivation process by manipulating the oxygen concentration in inlet gas or inlet gas flow. The proposed approach is relatively simple and may be attractive for installation in a real pluripotent stem cell expansion processes.

Keywords: aggregated stem cells, dissolved oxygen profiles, modeling, stirred-tank, 3D expansion

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Authors: Chassel T. Paras, Tryxzy Q. Dela Cruz, Ma. Carmela Lousie V. Goingco, Pauline L. Tolentino, Carmela S. Dizon

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In implementing inclusive education, parental involvement is measured to be an irreplaceable contributing factor. Parental involvement is described as an indispensable aspect of the teaching-learning process and has a remarkable effect on the student's academic performance. However, there are still differences in the viewpoints, expectations, and needs of both parents and teachers that are not yet fully conveyed in their relationship; hence, the perceptions of SNED teachers are essential in their collaboration with parents. This qualitative study explored how SNED teachers perceive the roles of parental involvement in the teaching-learning process of students with special needs. To answer this question, one-on-one face-to-face semi-structured interviews with three SNED teachers in a selected public school in Angeles City, Philippines, that offer special needs education services were conducted. The gathered data are then analyzed using Interpretative Phenomenological Analysis (IPA). The results revealed four superordinate themes, which include: (1) roles of parental involvement, (2) parental involvement opportunities, (3) barriers to parental involvement, and (4) parent-teacher collaboration practices. These results indicate that SNED teachers are aware of the roles and importance of parental involvement; however, despite parent-teacher collaboration, there are still barriers that impede parental involvement. Also, SNED teachers acknowledge the big roles of parents as they serve as main figures in the teaching-learning process of their children with special needs. Lastly, these results can be used as input in developing a school-facilitated parenting involvement framework that encompasses the contribution of SNED teachers in planning, developing, and evaluating parental involvement programs, which future researchers can also use in their studies

Keywords: parental involvement, special needs education, teaching-learning process, teachers’ perceptions, special needs education teachers, interpretative phenomenological analysis

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Authors: Usarat Thawornchaisit, Kamalasiri Juthaisong, Kasama Parsongjeen, Phonsiri Phoengchan

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In this study, sludge samples that were collected from the wastewater treatment plant of a printed circuit board manufacturing industry in Thailand were subjected to acid extraction using sulfuric acid as the chemical extracting agent. The effects of sulfuric acid concentration (A), the ratio of a volume of acid to a quantity of sludge (B) and extraction time (C) on the efficiency of copper extraction were investigated with the aim of finding the optimal conditions for maximum removal of copper from the wastewater treatment sludge. Factorial experimental design was employed to model the copper extraction process. The results were analyzed statistically using analysis of variance to identify the process variables that were significantly affected the copper extraction efficiency. Results showed that all linear terms and an interaction term between volume of acid to quantity of sludge ratio and extraction time (BC), had statistically significant influence on the efficiency of copper extraction under tested conditions in which the most significant effect was ascribed to volume of acid to quantity of sludge ratio (B), followed by sulfuric acid concentration (A), extraction time (C) and interaction term of BC, respectively. The remaining two-way interaction terms, (AB, AC) and the three-way interaction term (ABC) is not statistically significant at the significance level of 0.05. The model equation was derived for the copper extraction process and the optimization of the process was performed using a multiple response method called desirability (D) function to optimize the extraction parameters by targeting maximum removal. The optimum extraction conditions of 99% of copper were found to be sulfuric acid concentration: 0.9 M, ratio of the volume of acid (mL) to the quantity of sludge (g) at 100:1 with an extraction time of 80 min. Experiments under the optimized conditions have been carried out to validate the accuracy of the Model.

Keywords: acid treatment, chemical extraction, sludge, waste management

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Authors: A. Benhadji, R. Maachi

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Environmental protection has become a major economic development issues. Indeed, the environment has become both market growth factor and element of competition. It is now an integral part of all industrial strategies. Ecosystem protection is based on the reduction of the pollution load in the treatment of liquid waste. The physicochemical techniques are commonly used which a transfer of pollution is generally found. Alternative to physicochemical methods is the use of microorganisms for cleaning up the waste waters. The objective of this research is the evaluation of the effects of exogenous added Pseudomonas strains on pollutants biodegradation. The influence of the critical parameters such as inoculums concentration and duration treatment are studied. The results show that Pseudomonas putida is found to give a maximum reduction in chemical organic demand (COD) in 4 days of incubation. However, toward to protect biological pollution of environment, the treatment is achieved by electro coagulation process using aluminium electrodes. The results indicate that this process allows disinfecting the water and improving the electro coagulated sludge quality.

Keywords: tannery, pseudomonas, biological treatment, electrocoagulation process, sludge quality

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Authors: Saeid Seddegh, Xiaolin Wang, Alan D. Henderson, Dong Chen, Oliver Oims

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The main objective of this research is to study the heat transfer processes and phase change behaviour of a phase change material (PCM) in shell and tube latent heat thermal energy storage (LHTES) systems. The thermal behaviour in a vertical and horizontal shell-and-tube heat energy storage system using a pure thermal conduction model and a combined conduction-convection heat transfer model is compared in this paper. The model is first validated using published experimental data available in literature and then used to study the temperature variation, solid-liquid interface, phase distribution, total melting and solidification time during melting and solidification processes of PCMs. The simulated results show that the combined convection and conduction model can better describe the energy transfer in PCMs during melting process. In contrast, heat transfer by conduction is more significant during the solidification process since the two models show little difference. Also, it was concluded that during the charging process for the horizontal orientation, convective heat transfer has a strong effect on melting of the upper part of the solid PCM and is less significant during melting of the lower half of the solid PCM. However, in the vertical orientation, convective heat transfer is the same active during the entire charging process. In the solidification process, the thermal behavior does not show any difference between horizontal and vertical systems.

Keywords: latent heat thermal energy storage, phase change material, natural convection, melting, shell and tube heat exchanger, melting, solidification

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Authors: Elvira Mustikawati P.H., Iis Dewi Ratih, Dita Amelia

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Bojonegoro has proclaimed a policy of zero malnutrition. Therefore, as an effort to solve the cases of malnutrition children in Bojonegoro, this study used the approach geographically Mixed Weighted Regression (MGWR) to determine the factors that influence the percentage of malnourished children under five in which factors can be divided into locally influential factor in each district and global factors that influence throughout the district. Based on the test of goodness of fit models, R2 and AIC values in GWR models are better than MGWR models. R2 and AIC values in MGWR models are 84.37% and 14.28, while the GWR models respectively are 91.04% and -62.04. Based on the analysis with GWR models, District Sekar, Bubulan, Gondang, and Dander is a district with three predictor variables (percentage of vitamin A, the percentage of births assisted health personnel, and the percentage of clean water) that significantly influence the percentage of malnourished children under five.

Keywords: GWR, MGWR, R2, AIC

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Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: Samir Zeghlache, Abderrahmen Bouguerra, Kamel Kara, Djamel Saigaa

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The control of the trirotor helicopter includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. This paper presents a control strategy for an underactuated six degrees of freedom (6 DOF) trirotor helicopter, based on the coupling of the fuzzy logic control and sliding mode control (SMC). The main purpose of this work is to eliminate the chattering phenomenon. To achieve our purpose we have used a fuzzy logic control to generate the hitting control signal, also the non linear observer is then synthesized in order to estimate the unmeasured states. Finally simulation results are included to indicate the trirotor UAV with the proposed controller can greatly alleviate the chattering effect and remain robust to the external disturbances.

Keywords: fuzzy sliding mode control, trirotor helicopter, dynamic modelling, underactuated systems

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Authors: Rajkumar Ghosh

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Earthquakes pose significant risks to human life and infrastructure, highlighting the importance of effective earthquake mitigation strategies. Traditional earthquake modelling and mitigation efforts have largely focused on the primary fault segments and their slip behaviour. However, earthquakes can exhibit complex rupture dynamics, including out-of-sequence thrust (OOST) events, which occur on secondary or subsidiary faults. This abstract examines the impact of OOST dynamics on earthquake mitigation strategies and their implications for hazard assessment and disaster planning. OOST events challenge conventional seismic hazard assessments by introducing additional fault segments and potential rupture scenarios that were previously unrecognized or underestimated. Consequently, these events may increase the overall seismic hazard in affected regions. The study reviews recent case studies and research findings that illustrate the occurrence and characteristics of OOST events. It explores the factors contributing to OOST dynamics, such as stress interactions between fault segments, fault geometry, and mechanical properties of fault materials. Moreover, it investigates the potential triggers and precursory signals associated with OOST events to enhance early warning systems and emergency response preparedness. The abstract also highlights the significance of incorporating OOST dynamics into seismic hazard assessment methodologies. It discusses the challenges associated with accurately modelling OOST events, including the need for improved understanding of fault interactions, stress transfer mechanisms, and rupture propagation patterns. Additionally, the abstract explores the potential for advanced geophysical techniques, such as high-resolution imaging and seismic monitoring networks, to detect and characterize OOST events. Furthermore, the abstract emphasizes the practical implications of OOST dynamics for earthquake mitigation strategies and urban planning. It addresses the need for revising building codes, land-use regulations, and infrastructure designs to account for the increased seismic hazard associated with OOST events. It also underscores the importance of public awareness campaigns to educate communities about the potential risks and safety measures specific to OOST-induced earthquakes. This sheds light on the impact of out-of-sequence thrust dynamics in earthquake mitigation. By recognizing and understanding OOST events, researchers, engineers, and policymakers can improve hazard assessment methodologies, enhance early warning systems, and implement effective mitigation measures. By integrating knowledge of OOST dynamics into urban planning and infrastructure development, societies can strive for greater resilience in the face of earthquakes, ultimately minimizing the potential for loss of life and infrastructure damage.

Keywords: earthquake mitigation, out-of-sequence thrust, seismic, satellite imagery

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Authors: Pavel H. Llamocca, Victoria Lopez

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The main objective of our work is the comparative analysis of environmental data from Open Data bases, belonging to different governments. This means that you have to integrate data from various different sources. Nowadays, many governments have the intention of publishing thousands of data sets for people and organizations to use them. In this way, the quantity of applications based on Open Data is increasing. However each government has its own procedures to publish its data, and it causes a variety of formats of data sets because there are no international standards to specify the formats of the data sets from Open Data bases. Due to this variety of formats, we must build a data integration process that is able to put together all kind of formats. There are some software tools developed in order to give support to the integration process, e.g. Data Tamer, Data Wrangler. The problem with these tools is that they need data scientist interaction to take part in the integration process as a final step. In our case we don’t want to depend on a data scientist, because environmental data are usually similar and these processes can be automated by programming. The main idea of our tool is to build Hadoop procedures adapted to data sources per each government in order to achieve an automated integration. Our work focus in environment data like temperature, energy consumption, air quality, solar radiation, speeds of wind, etc. Since 2 years, the government of Madrid is publishing its Open Data bases relative to environment indicators in real time. In the same way, other governments have published Open Data sets relative to the environment (like Andalucia or Bilbao). But all of those data sets have different formats and our solution is able to integrate all of them, furthermore it allows the user to make and visualize some analysis over the real-time data. Once the integration task is done, all the data from any government has the same format and the analysis process can be initiated in a computational better way. So the tool presented in this work has two goals: 1. Integration process; and 2. Graphic and analytic interface. As a first approach, the integration process was developed using Java and Oracle and the graphic and analytic interface with Java (jsp). However, in order to open our software tool, as second approach, we also developed an implementation with R language as mature open source technology. R is a really powerful open source programming language that allows us to process and analyze a huge amount of data with high performance. There are also some R libraries for the building of a graphic interface like shiny. A performance comparison between both implementations was made and no significant differences were found. In addition, our work provides with an Official Real-Time Integrated Data Set about Environment Data in Spain to any developer in order that they can build their own applications.

Keywords: open data, R language, data integration, environmental data

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Authors: Pitsanu Tongkhow, Pichet Jiraprasertwong

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This research investigates risk factors for defective products in autoparts factories. Under a Bayesian framework, a generalized linear mixed model (GLMM) in which the dependent variable, the number of defective products, has a Poisson distribution is adopted. Its performance is compared with the Poisson GLM under a Bayesian framework. The factors considered are production process, machines, and workers. The products coded RT50 are observed. The study found that the Poisson GLMM is more appropriate than the Poisson GLM. For the production Process factor, the highest risk of producing defective products is Process 1, for the Machine factor, the highest risk is Machine 5, and for the Worker factor, the highest risk is Worker 6.

Keywords: defective autoparts products, Bayesian framework, generalized linear mixed model (GLMM), risk factors

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Authors: A. Boateng, La Gil-Alana, M. Lesaoana; Hj. Siweya, A. Belete

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This study examines long memory or long-range dependence in the CPI inflation rates of Ghana and South Africa using Whittle methods and autoregressive fractionally integrated moving average (ARFIMA) models. Standard I(0)/I(1) methods such as Augmented Dickey-Fuller (ADF), Philips-Perron (PP) and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests were also employed. Our findings indicate that long memory exists in the CPI inflation rates of both countries. After processing fractional differencing and determining the short memory components, the models were specified as ARFIMA (4,0.35,2) and ARFIMA (3,0.49,3) respectively for Ghana and South Africa. Consequently, the CPI inflation rates of both countries are fractionally integrated and mean reverting. The implication of this result will assist in policy formulation and identification of inflationary pressures in an economy.

Keywords: Consumer Price Index (CPI) inflation rates, Whittle method, long memory, ARFIMA model

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Authors: Saidur R. Chowdhury, Mamme K. Addai, Ernest K. Yanful

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The research was performed to assess the potential of nickel smelter slag, an industrial waste, as an adsorbent in the removal of metals from aqueous solution. An investigation was carried out for Arsenic (As), Copper (Cu), lead (Pb) and Cadmium (Cd) adsorption from aqueous solution. Smelter slag was obtain from Ni ore at the Vale Inco Ni smelter in Sudbury, Ontario, Canada. The batch experimental studies were conducted to evaluate the removal efficiencies of smelter slag. The slag was characterized by surface analytical techniques. The slag contained different iron oxides and iron silicate bearing compounds. In this study, the effect of pH, contact time, particle size, competition by other ions, slag dose and distribution coefficient were evaluated to measure the optimum adsorption conditions of the slag as an adsorbent for As, Cu, Pb and Cd. The results showed 95-99% removal of As, Cu, Pb, and almost 50-60% removal of Cd, while batch experimental studies were conducted at 5-10 mg/L of initial concentration of metals, 10 g/L of slag doses, 10 hours of contact time and 170 rpm of shaking speed and 25oC condition. The maximum removal of Arsenic (As), Copper (Cu), lead (Pb) was achieved at pH 5 while the maximum removal of Cd was found after pH 7. The column experiment was also conducted to evaluate adsorption depth and service time for metal removal. This study also determined adsorption capacity, adsorption rate and mass transfer rate. The maximum adsorption capacity was found to be 3.84 mg/g for As, 4 mg/g for Pb, and 3.86 mg/g for Cu. The adsorption capacity of nickel slag for the four test metals were in decreasing order of Pb > Cu > As > Cd. Modelling of experimental data with Visual MINTEQ revealed that saturation indices of < 0 were recorded in all cases suggesting that the metals at this pH were under- saturated and thus in their aqueous forms. This confirms the absence of precipitation in the removal of these metals at the pHs. The experimental results also showed that Fe and Ni leaching from the slag during the adsorption process was found to be very minimal, ranging from 0.01 to 0.022 mg/L indicating the potential adsorbent in the treatment industry. The study also revealed that waste product (Ni smelter slag) can be used about five times more before disposal in a landfill or as a stabilization material. It also highlighted the recycled slags as a potential reactive adsorbent in the field of remediation engineering. It also explored the benefits of using renewable waste products for the water treatment industry.

Keywords: adsorption, industrial waste, recycling, slag, treatment

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Authors: Xinyi Gao, Xiaoyun Feng, Ruijie Liu, Yumin Xia, Min Shao, Xinqing Wang

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This paper outlines the travel challenges, the absence of society, and studies around disabled women and chooses the Chongqing area as a case study to explore how terrain characteristics and city construction influence our subject's travel choice. It also highlights future transport options and the necessity of addressing the difficult travel position of women with disabilities. This study focuses on the travel demands of women with disabilities, illustrating what their ideal method of travel would be. An analysis of related smart cities like Hong Kong illustrates the aspects to consider in the reconstruction of Chongqing. Finally, relying on current smart city modelling approaches, several design ideas for assistive tools are suggested for the safety of women with disabilities during travel.

Keywords: future smart city, disabled women, Chongqing, inclusive design, human-computer interaction

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Authors: Nasser Mohamed Ramli, Mohamad Syafiq Mohamad

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Many types of controllers were applied on the continuous stirred tank reactor (CSTR) unit to control the temperature. In this research paper, Proportional-Integral-Derivative (PID) controller are compared with Fuzzy Logic controller for temperature control of CSTR. The control system for temperature non-isothermal of a CSTR will produce a stable response curve to its set point temperature. A mathematical model of a CSTR using the most general operating condition was developed through a set of differential equations into S-function using MATLAB. The reactor model and S-function are developed using m.file. After developing the S-function of CSTR model, User-Defined functions are used to link to SIMULINK file. Results that are obtained from simulation and temperature control were better when using Fuzzy logic control compared to PID control.

Keywords: CSTR, temperature, PID, fuzzy logic

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Authors: Barkha Ramteke, Sonali Ridhorkar

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An election is an important event in all countries. Traditional voting has several drawbacks, including the expense of time and effort required for tallying and counting results, the cost of papers, arrangements, and everything else required to complete a voting process. Many countries are now considering online e-voting systems, but the traditional e-voting systems suffer a lack of trust. It is not known if a vote is counted correctly, tampered or not. A lack of transparency means that the voter has no assurance that his or her vote will be counted as they voted in elections. Electronic voting systems are increasingly using blockchain technology as an underlying storage mechanism to make the voting process more transparent and assure data immutability as blockchain technology grows in popularity. The transparent feature, on the other hand, may reveal critical information about applicants because all system users have the same entitlement to their data. Furthermore, because of blockchain's pseudo-anonymity, voters' privacy will be revealed, and third parties involved in the voting process, such as registration institutions, will be able to tamper with data. To overcome these difficulties, we apply Ethereum smart contracts into blockchain-based voting systems.

Keywords: blockchain, AMV chain, electronic voting, decentralized

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Authors: Gennady M. Kulikov, Svetlana V. Plotnikova

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This paper focuses on implementation of the sampling surfaces (SaS) method for the three-dimensional (3D) stress analysis of functionally graded (FG) laminated elastic and piezoelectric shells. The SaS formulation is based on choosing inside the nth layer In not equally spaced SaS parallel to the middle surface of the shell in order to introduce the electric potentials and displacements of these surfaces as basic shell variables. Such choice of unknowns permits the presentation of the proposed FG piezoelectric shell formulation in a very compact form. The SaS are located inside each layer at Chebyshev polynomial nodes that improves the convergence of the SaS method significantly. As a result, the SaS formulation can be applied efficiently to 3D solutions for FG piezoelectric laminated shells, which asymptotically approach the exact solutions of piezoelectricity as the number of SaS In goes to infinity.

Keywords: electroelasticity, functionally graded material, laminated piezoelectric shell, sampling surfaces method

Procedia PDF Downloads 691

Authors: Pedro Augusto Da Silva E Souza Miranda, Niloofar Jalali, Shweta Mistry

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BACKGROUND: Software developers utilize automated solutions to scrape users’ reviews to extract meaningful knowledge to identify problems (e.g., bugs, compatibility issues) and possible enhancements (e.g., users’ requests) to their solutions. However, most of these solutions do not consider the health risk aspects to users. Recent works have shed light on the importance of including health risk considerations in the development cycle of mHealth apps to prevent harm to its users. PROBLEM: The COVID-19 Pandemic in Canada (and World) is currently forcing physical distancing upon the general population. This new lifestyle made the usage of mHealth applications more essential than ever, with a projected market forecast of 332 billion dollars by 2025. However, this new insurgency in mHealth usage comes with possible risks to users’ health due to mHealth apps problems (e.g., wrong insulin dosage indication due to a UI error). OBJECTIVE: These works aim to raise awareness amongst mHealth developers of the importance of considering risks to users’ health within their development lifecycle. Moreover, this work also aims to help mHealth developers with a Proof-of-Concept (POC) solution to understand, process, and identify possible health risks to users of mHealth apps based on users’ reviews. METHODS: We conducted a mixed-method study design. We developed a crawler to mine the negative reviews from two samples of mHealth apps (my fitness, medisafe) from the Google Play store users. For each mHealth app, we performed the following steps: • The reviews are divided into two groups, before starting the COVID-19 (reviews’ submission date before 15 Feb 2019) and during the COVID-19 (reviews’ submission date starts from 16 Feb 2019 till Dec 2020). For each period, the Latent Dirichlet Allocation (LDA) topic model was used to identify the different clusters of reviews based on similar topics of review The topics before and during COVID-19 are compared, and the significant difference in frequency and severity of similar topics are identified. RESULTS: We successfully scraped, filtered, processed, and identified health-related topics in both qualitative and quantitative approaches. The results demonstrated the similarity between topics before and during the COVID-19.

Keywords: natural language processing (NLP), topic modeling, mHealth, COVID-19, software engineering, telemedicine, health risks

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Authors: Tim Giesen, Raphael Adamietz, Pablo Mayer, Philipp Stiefel, Patrick Alle, Dirk Schlenker

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The competitiveness and success of new electrical energy storages such as battery cells are significantly dependent on a short time-to-market. Producers who decide to supply new battery cells to the market need to be easily adaptable in manufacturing with respect to the early customers’ needs in terms of cell size, materials, delivery time and quantity. In the initial state, the required output rates do not yet allow the producers to have a fully automated manufacturing line nor to supply handmade battery cells. Yet there was no solution for manufacturing battery cells in low to medium volumes in a reproducible way. Thus, in terms of cell format and output quantity, a concept for the flexible assembly of battery cells was developed by the Fraunhofer-Institute for Manufacturing Engineering and Automation. Based on clustered processes, the modular system platform can be modified, enlarged or retrofitted in a short time frame according to the ordered product. The paper shows the analysis of the production steps from a conventional battery cell assembly line. Process solutions were found by using I/O-analysis, functional structures, and morphological boxes. The identified elementary functions were subsequently clustered by functional coherences for automation solutions and thus the single process cluster was generated. The result presented in this paper enables to manufacture different cell products on the same production system using seven process clusters. The paper shows the solution for a batch-wise flexible battery cell production using advanced process control. Further, the performed tests and benefits by using the process clusters as cyber-physical systems for an integrated production and value chain are discussed. The solution lowers the hurdles for SMEs to launch innovative cell products on the global market.

Keywords: automation, battery production, carrier, advanced process control, cyber-physical system

Procedia PDF Downloads 338

Authors: Chris Fersterer, Col Fay, Tobias Danielmeier, Kat Achterberg, Scott Willis

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New Zealand, an island nation, has an extensive coastline peppered with small communities of iconic buildings known as Bachs. Post WWII, these modest buildings were constructed by their owners as retreats and generally were small, low cost, often using recycled material and often they fell below current acceptable building standards. In the latter part of the 20^th century, real estate prices in many of these communities remained low and these areas became permanent residences for people attracted to this affordable lifestyle choice. The Blueskin Resilient Communities Trust (BRCT) is an organisation that recognises the vulnerability of communities in low lying settlements as now being prone to increased flood threat brought about by climate change and sea level rise. Some of the inhabitants of Blueskin Bay, Otago, NZ have already found their properties to be un-insurable because of increased frequency of flood events and property values have slumped accordingly. Territorial authorities also acknowledge this increased risk and have created additional compliance measures for new buildings that are less than 2 m above tidal peaks. Community resilience becomes an additional concern where inhabitants are attracted to a lifestyle associated with a specific location and its people when this lifestyle is unable to be met in a suburban or city context. Traditional models of social housing fail to provide the sense of community connectedness and identity enjoyed by the current residents of Blueskin Bay. BRCT have partnered with the Otago Polytechnic Design School to design a new form of community housing that can react to this environmental change. It is a longitudinal project incorporating participatory approaches as a means of getting people ‘on board’, to understand complex systems and co-develop solutions. In the first period, they are seeking industry support and funding to develop a transportable and fully self-contained housing model that exploits current technologies. BRCT also hope that the building will become an educational tool to highlight climate change issues facing us today. This paper uses the Climate Safe House (CSH) as a case study for education in architectural sustainability through experiential learning offered as part of the Otago Polytechnics Bachelor of Design. Students engage with the project with research methodologies, including site surveys, resident interviews, data sourced from government agencies and physical modelling. The process involves collaboration across design disciplines including product and interior design but also includes connections with industry, both within the education institution and stakeholder industries introduced through BRCT. This project offers a rich learning environment where students become engaged through project based learning within a community of practice, including architecture, construction, energy and other related fields. The design outcomes are expressed in a series of public exhibitions and forums where community input is sought in a truly participatory process.

Keywords: community resilience, problem based learning, project based learning, case study

Procedia PDF Downloads 288

Authors: I.-A. Ciobotaru, I.-E. Ciobotaru, D.-I. Vaireanu

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Currently, an ascending trend of battery use may be observed, together with an increase of the generated amount of waste. Efforts have been focused on the recycling of batteries; however, extending their lifetime may be a more adequate alternative, and the development of such methods may prove to be more cost efficient as compared to recycling. In this context, this paper presents the analysis of a proposed process for the reconditioning of some lithium-ions batteries. The analysis is performed based on two criteria, the first one referring to the technical aspect of the reconditioning process and the second to the economic aspects. The main technical parameters taken into consideration are the values of capacitance and internal resistance of the lithium-ion batteries. The economic criterion refers to the evaluation of the efficiency of the reconditioning procedure reported to its total cost for the investigated lithium-ion batteries. Based on the cost analysis, one introduced a novel coefficient that correlates the efficiency of the aforementioned process and its corresponding costs. The reconditioning procedure for the lithium-ion batteries proposed in this paper proved to be valid, efficient, and with reasonable costs.

Keywords: cost assessment, lithium-ion battery, reconditioning coefficient, reconditioning procedure

Procedia PDF Downloads 138

Authors: Jamilatuzzahro, Rezzy Eko Caraka

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The yield curve is the plot of the yield to maturity of zero-coupon bonds against maturity. In practice, the yield curve is not observed but must be extracted from observed bond prices for a set of (usually) incomplete maturities. There exist many methodologies and theory to analyze of yield curve. We use two methods (the Nelson-Siegel Method, the Svensson Method, and the SVR method) in order to construct and compare our zero-coupon yield curves. The objectives of this research were: (i) to study the adequacy of NSS model and SVR to Indonesian government bonds data, (ii) to choose the best optimization or estimation method for NSS model and SVR. To obtain that objective, this research was done by the following steps: data preparation, cleaning or filtering data, modeling, and model evaluation.

Keywords: support vector regression, Nelson-Siegel-Svensson, yield curve, Indonesian government

Procedia PDF Downloads 245