Search results for: laser sintering process

Authors: Afrouz Yousefi, Mohtada Sadrzadeh

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The widespread presence of poly- and perfluoroalkyl substances (PFAS) poses a significant concern due to their ability to accumulate in living organisms and their persistence in the environment, thanks to their robust carbon-fluorine (C-F) bonds, which require substantial energy to break (485 kJ/mol). The prevalence of toxic PFAS compounds can be highly detrimental to ecosystems, wildlife, and human health. Ongoing efforts are dedicated to investigating methods for fully breaking down and eliminating PFAS from the environment. Among the various techniques employed, advanced oxidation processes have shown promise in completely breaking down emerging contaminants in wastewater. However, the drawback lies in the relatively slow reaction rates of these processes and the substantial energy input required, which currently impedes their widespread commercial adoption. We developed a hybrid process, comprising electro-Fenton as an advanced oxidation process and membrane distillation, to simultaneously degrade organic PFAS pollutants and extract pure water from the mixture. In this study, environmentally persistent perfluorooctanoic acid (PFOA), as an emerging contaminant, was used to study the effectiveness of the electro-Fenton/membrane distillation hybrid system. The PFOA degradation studies were conducted in two modes: electro-Fenton and electro-Fenton coupled with membrane distillation. High-performance liquid chromatography with ultraviolet detection (HPLC-UV), ion-chromatography (measuring fluoride ion concentration), total organic carbon (TOC) decay, mineralization current efficiency (MCE), and specific energy consumption (SEC) were evaluated for a single EF and hybrid EF-MD processes. In contrast to a single EF reaction, TOC decay improved significantly in the EF-MD process. Overall, the MCE of hybrid processes surpassed 100% while it remained under 50% for a single EF reaction. Calculations of specific energy consumption (SEC) demonstrated a substantial decrease of nearly one-third in energy usage when integrating the EF reaction with the MD process.

Keywords: water treatment, PFAS, membrane distillation, electro-Fenton, advanced oxidation

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Authors: Cristiane Hengler Corrêa Bernardo

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The communication is an essential part of the process that characterizes scientific research. It should be present in every stage of research in a systemic way. However, this process is not always efficient and effective. Reports of researchers focused on agribusiness point to difficulties in communicating with farmers that negatively impact on research results and may cause distortions and even quite significant inconsistencies. This research aims at identifying the main noise and barriers in communication between agribusiness researchers and farmers. It discusses the possibility of creating a specific strategy to correct or minimize such failures. The main research question: what features of the communication process will be decisive for the communication between agribusiness researcher and farmer occur with greater efficiency? It is expected that the research will result in processes that may correct or minimize such problems, promoting dialogues more efficient knowledge. The research will adopt a qualitative approach, using action research as a form of investigative action for social and educational nature, aiming at promoting understanding and interaction between researchers and members of the investigated situations. To collect and analyze data to document analysis will be used; questionnaires and interviews and content analysis.

Keywords: agribusiness farmers, researchers, science communication, analysis

Procedia PDF Downloads 276

Authors: Fernanda A. P. Peres, Thiago N. Peres, Flavio S. Fogliatto, Michel J. Anzanello

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Batch processes are widely used in food industry and have an important role in the production of high added value products, such as chocolate. Process performance is usually described by variables that are monitored as the batch progresses. Data arising from these processes are likely to display a strong correlation-autocorrelation structure, and are usually monitored using control charts based on multiway principal components analysis (MPCA). Process control of a new batch is carried out comparing the trajectories of its relevant process variables with those in a reference set of batches that yielded products within specifications; it is clear that proper determination of the reference set is key for the success of a correct signalization of non-conforming batches in such quality control schemes. In chocolate manufacturing, misclassifications of non-conforming batches in the conching phase may lead to significant financial losses. In such context, the accuracy of process control grows in relevance. In addition to that, the main assumption in MPCA-based monitoring strategies is that all batches are synchronized in duration, both the new batch being monitored and those in the reference set. Such assumption is often not satisfied in chocolate manufacturing process. As a consequence, traditional techniques as MPCA-based charts are not suitable for process control and monitoring. To address that issue, the objective of this work is to compare the performance of three dynamic time warping (DTW) methods in the alignment and synchronization of chocolate conching process variables’ trajectories, aimed at properly determining the reference distribution for multivariate statistical process control. The power of classification of batches in two categories (conforming and non-conforming) was evaluated using the k-nearest neighbor (KNN) algorithm. Real data from a milk chocolate conching process was collected and the following variables were monitored over time: frequency of soybean lecithin dosage, rotation speed of the shovels, current of the main motor of the conche, and chocolate temperature. A set of 62 batches with durations between 495 and 1,170 minutes was considered; 53% of the batches were known to be conforming based on lab test results and experts’ evaluations. Results showed that all three DTW methods tested were able to align and synchronize the conching dataset. However, synchronized datasets obtained from these methods performed differently when inputted in the KNN classification algorithm. Kassidas, MacGregor and Taylor’s (named KMT) method was deemed the best DTW method for aligning and synchronizing a milk chocolate conching dataset, presenting 93.7% accuracy, 97.2% sensitivity and 90.3% specificity in batch classification, being considered the best option to determine the reference set for the milk chocolate dataset. Such method was recommended due to the lowest number of iterations required to achieve convergence and highest average accuracy in the testing portion using the KNN classification technique.

Keywords: batch process monitoring, chocolate conching, dynamic time warping, reference set distribution, variable duration

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Authors: Mozhgan Sabzehparvar, Mohammad Montazeri, Mahdie Jafarnejad Shahri, Neda Boroumandi, Shakib Alipour, Hamide Torabi, Zahra Dehghani

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In this article, the aesthetic criteria, which are regarded as the key factors in the product development, and design process are carefully taken into account and an attempt has been made to extract the influential concepts in successful product design. This review article was conducted from 22.05.2021 to 22.06.2021, recent published paper in English (2017-2021) in three search engines of JSTOR, IEEE, and EMERALD were selected. The selected main keywords in our search were "Customer, Behavior, Aesthetics, Marketing and Product". During the screenings, 21 articles were analyzed. The aesthetic criteria play a role in increasing the power of choice, loyalty, satisfaction and purchase intention of the customers. Also, product design has a positive effect on the customers’ perception of aesthetics and acts effectively on customer behavior. Aesthetics has a significant relationship with the customer's intention to buy products and can make the product popular and satisfy people.

Keywords: product design, design process, customer behaviour, aesthetic, marketing

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Authors: Arun Raja, Kevin Thomas, Sreyas Tribhu, S. P. Anbuudayasankar

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This paper deals with the application of six sigma methodology in supply chain (SC) and logistics. A detailed cram about how the SC can be improved and its impact on the organization are dealt with and also how the quality plays a vital role in improving SC and logistics are identified. A simulation has been performed using the ARENA software to determine the process efficiency of a bottle manufacturing unit. Further, a Value Stream Mapping (VSM) analysis has been executed on the manufacturing process flow model and the manner by which Value Engineering (VE) holds a significant importance for quality assertion on the products is also studied.

Keywords: supply chain, six sigma, value engineering, logistics, quality

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Authors: Muhammad Akbar Hussain, Muhammad Mehdi Hussain, Waqar Haider

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There are tens of thousands of undetected and uncatalogued pieces of space debris in the Low Earth Orbit (LEO). They are not only difficult to be detected and tracked, their sheer number puts active satellites and humans in orbit around Earth into danger. With the entry of more governments and private companies into harnessing the Earth’s orbit for communication, research and military purposes, there is an ever-increasing need for not only the detection and cataloguing of these pieces of space debris, it is time to take measures to take them out and clean up the space around Earth. Current optical and radar-based Space Situational Awareness initiatives are useful mostly in detecting and cataloguing larger pieces of debris mainly for avoidance measures. Smaller than 10 cm pieces are in a relatively dark zone, yet these are deadly and capable of destroying satellites and human missions. A network of mobile observatories, connected to each other in real time and working in unison as a single instrument, may be able to detect small pieces of debris and achieve effective triangulation to help create a comprehensive database of their trajectories and parameters to the highest level of precision. This data may enable ground-based laser systems to help deorbit individual debris. Such a network of observatories can join current efforts in detection and removal of space debris in Earth’s orbit.

Keywords: space debris, low earth orbit, mobile observatories, triangulation, seamless operability

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Authors: Sadegh Abedi, Ali Yaghoubi, Hamidreza Mashatzadegan

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This paper proposes an approach to identify key processes required by an organization in the field of knowledge management and aligning them with organizational objectives. For this purpose, first, organization’s most important non-financial objectives which are impacted by knowledge management processes are identified and then, using a quality house, are linked with knowledge management processes which are regarded as technical elements. Using this method, processes that are in need of improvement and more attention are prioritized based on their significance. This means that if a process has more influence on organization’s objectives and is in a dire situation comparing to others, is prioritized for choice and improvement. In this research process dominance is considered to be an influential element in process ranking (in addition to communication matrix). This is the reason for utilizing DEA techniques for prioritizing processes in quality house. Results of implementing the method in Khuzestan steel company represents this method’s capability of identifying key processes that require improvements in organization’s knowledge management system.

Keywords: knowledge management, organizational performance, fuzzy data, envelopment analysis

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Authors: Muhammad Luqman, Yusuf Kurniawan

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S-Boxes is one of the linear parts of the cryptographic algorithm. The existence of S-Box in the cryptographic algorithm is needed to maintain non-linearity of the algorithm. Nowadays, modern cryptographic algorithms use an S-Box as a part of algorithm process. Despite the fact that several cryptographic algorithms today reuse theoretically secure and carefully constructed S-Boxes, there is an evaluation characteristic that can measure security properties of S-Boxes and hence the corresponding primitives. Analysis of an S-Box usually is done using manual mathematics calculation. Several S-Boxes are presented as a Truth Table without any mathematical background algorithm. Then, it’s rather difficult to determine the strength of Truth Table S-Box without a mathematical algorithm. A comprehensive analysis should be applied to the Truth Table S-Box to determine the characteristic. Several important characteristics should be owned by the S-Boxes, they are Nonlinearity, Balancedness, Algebraic degree, LAT, DAT, differential delta uniformity, correlation immunity and global avalanche criterion. Then, a comprehensive tool will be present to automatically calculate the characteristics of S-Boxes and determine the strength of S-Box. Comprehensive analysis is done on a deterministic process to produce a sequence of S-Boxes characteristic and give advice for a better S-Box construction.

Keywords: cryptographic properties, Truth Table S-Boxes, S-Boxes characteristic, deterministic process

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Authors: Jantakan Jullawateelert, Korakod Haonoo, Sutipong Sananseang, Sarun Torpaiboon, Thanunthon Bowornsakulwong, Lalintip Hocharoen

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Process scale-up is essential for the biological process to increase production capacity from bench-scale bioreactors to either pilot or commercial production. Scale-up based on constant volumetric oxygen mass transfer coefficient (KLa) is mostly used as a scale-up factor since oxygen supply is one of the key limiting factors for cell growth. However, to estimate KLa of culture vessels operated with different conditions are time-consuming since it is considerably influenced by a lot of factors. To overcome the issue, this study aimed to establish correlation equations of KLa and operating parameters in 0.5 L and 5 L bioreactor employed with pitched-blade impeller and gas sparger. Temperature, gas flow rate, agitation speed, and impeller position were selected as process parameters and equations were created using response surface methodology (RSM) based on central composite design (CCD). In addition, the effects of these parameters on KLa were also investigated. Based on RSM, second-order polynomial models for 0.5 L and 5 L bioreactor were obtained with an acceptable determination coefficient (R²) as 0.9736 and 0.9190, respectively. These models were validated, and experimental values showed differences less than 10% from the predicted values. Moreover, RSM revealed that gas flow rate is the most significant parameter while temperature and agitation speed were also found to greatly affect the KLa in both bioreactors. Nevertheless, impeller position was shown to influence KLa in only 5L system. To sum up, these modeled correlations can be used to accurately predict KLa within the specified range of process parameters of two different sizes of bioreactors for further scale-up application.

Keywords: response surface methodology, scale-up, stirred-tank bioreactor, volumetric oxygen mass transfer coefficient

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Authors: A. Babou, Y. Kerboua Ziari, Y. Kerkoub

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The risks of depletion of fossil fuel reserves and environmental problems caused by their consumption cause to consider alternative energy solutions. Hydrogen appears as a serious solution because its combustion produces only water. The objective of this study is to digitally analyze the effect of operating conditions on the process of absorption of hydrogen in a tank of metal hydride alloy Lanthanum - Nickel (LaNi 5). For this modeling of heat transfer and mass in the tank was carried .The results of numerical weather prediction are in good agreement with the experimental results.

Keywords: hydrogen, storage, energy, fuel, simulation

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Authors: Omur Sercan Oral

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In this paper, the individual and social conflicts are examined with a sociological perspective during the social process of Macondo described in the post-modern book of Gabriel Garcia Marquez, One Hundred Years of Solitude. More specifically, the theme of the solitude of individuals who choose to be isolated and who are isolated is studied within the context of the suicide of Emile Durkheim. As a self-reflective product of individuals in the result-based process, both economically and socially founded in the text, solitude reflects the ultimate process of separation from society. In this sense, the various and multiplying layers of the collective codes of Macondo as microcosm and their interactions with the individuals are examined in this paper under the roof of suicide in the sociological concept. The attempts to explain the reasons, shift, and its reflections on individuals are carried out to cross the lines of one discipline. In doing that, the ideas of Durkheim, Foucault, Weber, and Clausewitz, to some extent, are planted explicitly and implicitly throughout the paper.

Keywords: Durkheim’s concept of suicide, solitude theme in Marquez, collective consciousness, isolation from society, subjectivity

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Authors: Maurice Bilioniere, Katie Lanneau

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Suddenly appeared in 2011, invasions of sargasso seaweeds Fluitans and Natans are a climatic hazard which causes many problems in the Caribbean. Faced with the growth and frequency of the phenomenon of massive sargasso stranding on their coasts, the French West Indies are moving towards the path of industrial recovery. In this context of innovative projects, we will analyze the necessary requirements for the management and performance of the supply chain, taking into account the observed volatility of the sargasso input. Our prospective approach will consist in studying the theoretical framework of modeling a hybrid supply chain by coupling the discreet event simulation (DES) with a valuation of the process costs according to the "activity-based costing" method (ABC). The PREVA approach (PRocess EVAluation) chosen for our modeling has the advantage of evaluating the financial flows of the logistic process using an analytical model chained with an action model for the evaluation or optimization of physical flows.

Keywords: sargasso, PREVA modeling, supply chain, ABC method, discreet event simulation (DES)

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Authors: Gloria James, S. K. Nema, T. S. Anantha Singh, P. Vadivel Murugan

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The usage of tyre has increased enormously in day to day life. The used tyre and rubber products pose major threat to the environment. Conventional thermal techniques such as low temperature pyrolysis and incineration produce high molecular organic compounds (condensed and collected as aromatic oil) and carbon soot particles. Plasma gasification technique can dispose tyre waste and generate combustible gases and avoid the formation of high molecular aromatic compounds. These gases generated in plasma gasification process can be used to generate electricity or as fuel wherever required. Although many experiments have been done on plasma pyrolysis of tyres, very little work has been done on plasma gasification of tyres. In this work plasma gasification of waste tyres have been conducted in a fixed bed reactor having graphite electrodes and direct current (DC) arc plasma system. The output of this work has been compared with the previous work done on plasma pyrolysis of tyres by different authors. The aim of this work is to compare different process based on gas generation, efficiency of the process and explore the most effective option for energy recovery from waste tyres.

Keywords: plasma, gasification, syngas, tyre waste

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Authors: Marianna Maiaru, Gregory M. Odegard, Josh Kemppainen, Ivan Gallegos, Michael Olaya

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Ceramic matrix composites (CMCs) are typically used in applications that require long-term mechanical integrity at elevated temperatures. CMCs are usually fabricated using a polymer precursor that is initially polymerized in situ with fiber reinforcement, followed by a series of cycles of pyrolysis to transform the polymer matrix into a rigid glass or ceramic. The pyrolysis step typically generates volatile gasses, which creates porosity within the polymer matrix phase of the composite. Subsequent cycles of monomer infusion, polymerization, and pyrolysis are often used to reduce the porosity and thus increase the durability of the composite. Because of the significant expense of such iterative processing cycles, new generations of CMCs with improved durability and manufacturability are difficult and expensive to develop using standard Edisonian approaches. The goal of this research is to develop a computational process-modeling-based approach that can be used to design the next generation of CMC materials with optimized material and processing parameters for maximum strength and efficient manufacturing. The process modeling incorporates computational modeling tools, including molecular dynamics (MD), to simulate the material at multiple length scales. Results from MD simulation are used to inform the continuum-level models to link molecular-level characteristics (material structure, temperature) to bulk-level performance (strength, residual stresses). Processing parameters are optimized such that process-induced residual stresses are minimized and laminate strength is maximized. The multiscale process modeling method developed with this research can play a key role in the development of future CMCs for high-temperature and high-strength applications. By combining multiscale computational tools and process modeling, new manufacturing parameters can be established for optimal fabrication and performance of CMCs for a wide range of applications.

Keywords: digital engineering, finite elements, manufacturing, molecular dynamics

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Authors: Chitaranjan Sharma

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The present paper deals with the analysis of a fuel supply system in an automobile engine of a four wheeler which is having both the option of fuel i.e. PETROL and CNG. Since CNG is cheaper than petrol so the priority is given to consume CNG as compared to petrol. An automatic switch is used to start petrol supply at the time of failure of CNG supply. Using regenerative point technique with Markov renewal process, the reliability characteristics which are useful to system designers are obtained.

Keywords: reliability, redundancy, repair time, transition, probability, regenerative points, markov renewal, process

Procedia PDF Downloads 551

Authors: Jayashree Das, V. V. Srinivasu , D. K. Mishra, A. Maity

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Owing to the important potential applications over decades, transition metal (TM: Mn, Fe, Ni, Cu, Cr, V etc.) doped ZnO-based diluted magnetic semiconductors (DMS) always attract research attention for more and newer investigations. One of the interesting aspects of these materials is to study and understand the magnetic property at room temperature properly, which is very crucial to select a material for any related application. In this regard, Electron spin resonance (ESR) study has been proven to be a powerful technique to investigate the spin dynamics of electrons inside the system, which are responsible for the magnetic behaviour of any system. ESR as well as the Raman and Photoluminescence spectroscopy studies are also helpful to study the defects present or created inside the system in the form of oxygen vacancy or cluster instrumental in determining the room temperature ferromagnetic property of transition metal doped ZnO system, which can be controlled through varying dopant concentration, appropriate synthesis technique and sintering of the samples. For our investigation, we synthesised Cu-doped ZnO nanocrystalline samples with composition Zn1-xCux ( 0.005< x < 0.05) by pyrophoric method and sintered at a low temperature of 650 0C. The microwave absorption is studied by the Electron Spin Resonance (ESR) of X-band (9.46 GHz) at room temperature. Systematic analysis of the obtained ESR spectra reveals that all the compositions of Cu-doped ZnO samples exhibit resonance signals of appreciable line widths and g value ~ 2.2, typical characteristic of ferromagnetism in the sample. Raman scattering and the photoluminescence study performed on the samples clearly indicated the presence of pronounced defect related peaks in the respective spectra. Cu doping in ZnO with varying concentration also observed to affect the optical band gap and the respective absorption edges in the UV-Vis spectra. FTIR spectroscopy reveals the Cu doping effect on the stretching bonds of ZnO. To probe into the structural and morphological changes incurred by Cu doping, we have performed XRD, SEM and EDX study, which confirms adequate Cu substitution without any significant impurity phase formation or lattice disorder. With proper explanation, we attempt to correlate the results observed for the structural optical and magnetic behaviour of the Cu-doped ZnO samples. We also claim that our result can be instrumental for appropriate applications of transition metal doped ZnO based DMS in the field of optoelectronics and Spintronics.

Keywords: diluted magnetic semiconductors, electron spin resonance, raman scattering, spintronics.

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Authors: Wiwat Onnakklum

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Clarification is the turbidity removal process of water treatment plant. This paper was to study the factors affecting on energy consumption in order to control energy saving strategy. The factors studied were raw water turbidity in the range of 26-40 NTU and production rate in the range of 3.76-5.20 m³/sec. Clarifiers were sludge blanket and sludge recirculation clarifier. Experimental results found that the raw water turbidity was not affected significantly by energy consumption, while the production rate was affected significantly by energy consumption. Sludge blanket clarifier provided lower energy consumption than sludge recirculation clarifier about 32-37%. Subsequently, the operating pattern in production rate can be arranged to decreased energy consumption. The results showed that it can be reduced about 5.09 % of energy saving of clarification process about 754,655 Baht per year.

Keywords: sludge blanket clarifier, sludge recirculation clarifier, water treatment plant, energy

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Authors: Jia Zhang, Fengmei Yao, Yanjing Tan

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The accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C4 crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS-P-YEC (Remote-Sensing-Photosynthesis-Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS-P-YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002-2011. The statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (P < 0.01) between the simulated yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002-2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.

Keywords: process-based model, C4 crop, maize yield, remote sensing, Northeast China Plain

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Authors: Mei Hong, Wei Liu, Xuemin Dai, Yanxiong Pan, Xiangling Ji

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Polyamic acid (PAA) is the precursor of polyimide (PI) prepared by a two-step method, its molecular weight and molecular weight distribution not only play an important role during the preparation and processing, but also influence the final performance of PI. However, precise characterization on molecular weight of PAA is still a challenge because of the existence of very complicated interactions in the solution system, including the electrostatic interaction, hydrogen bond interaction, dipole-dipole interaction, etc. Thus, it is necessary to establisha suitable strategy which can completely suppress these complex effects and get reasonable data on molecular weight. Herein, the gel permeation chromatography (GPC) coupled with differential refractive index (RI) and multi-angle laser light scattering (MALLS) detectors were applied to measure the molecular weight of (6FDA-DMB) PAA using different mobile phases, LiBr/DMF, LiBr/H3PO4/THF/DMF, LiBr/HAc/THF/DMF, and LiBr/HAc/DMF, respectively. It was found that combination of LiBr with HAc can shield the above-mentioned complex interactions and is more conducive to the separation of PAA than only addition of LiBr in DMF. LiBr/HAc/DMF was employed for the first time as a mild mobile phase to effectively separate PAA and determine its molecular weight. After a series of conditional experiments, 0.02M LiBr/0.2M HAc/DMF was fixed as an optimized mobile phase to measure the relative and absolute molecular weights of (6FDA-DMB) PAA prepared, and the obtained Mw from GPC-MALLS and GPC-RI were 35,300 g/mol and 125,000 g/mol, respectively. Particularly, such a mobile phase is also applicable to other PAA samples with different structures, and the final results on molecular weight are also reproducible.

Keywords: Polyamic acids, Polyelectrolyte effects, Gel permeation chromatography, Mobile phase, Molecular weight

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Authors: Mona Misfer Alshardan, Djamal Ziani

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Enterprise resource planning (ERP) systems are the organizations tickets to the global market. With the implementation of ERP, organizations can manage and coordinate all functions, processes, resources and data from different departments by a single software. However, many organizations consider the cost of traditional ERP to be expensive and look for alternative affordable solutions within their budget. One of these alternative solutions is providing ERP over a software as a service (SaaS) model. This alternative could be considered as a cost effective solution compared to the traditional ERP system. A key feature of any SaaS system is the multi-tenancy architecture where multiple customers (tenants) share the system software. However, different organizations have different requirements. Thus, the SaaS developers accommodate each tenant’s unique requirements by allowing tenant-level customization or configuration. While customization requires source code changes and in most cases a programming experience, the configuration process allows users to change many features within a predefined scope in an easy and controlled manner. The literature provides many techniques to accomplish the configuration process in different SaaS systems. However, the nature and complexity of SaaS ERP needs more attention to the details regarding the configuration process which is merely described in previous researches. Thus, this research is built on strong knowledge regarding the configuration in SaaS to define specifically the configuration borders in SaaS ERP and to design a configuration service with the consideration of the different configuration aspects. The proposed architecture will ensure the easiness of the configuration process by using wizard technology. Also, the privacy and performance are guaranteed by adopting the databases isolation technique.

Keywords: configuration, software as a service, multi-tenancy, ERP

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Authors: Abdulmutallib U. Baraya, Aishatu M. Chadi, Zainab A. Aliyu, Agatha Samson

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Learning Resources is the field of study that investigates the process of analyzing, designing, developing, implementing, and evaluating learning materials, learners, and the learning process in order to improve teaching and learning in university-level education essential for empowering students and various sectors of Nigeria’s economy to succeed in a fast-changing global economy. Innovation in the information age of the 21st century is the use of educational technologies in the classroom for instructional delivery, it involves the use of appropriate educational technologies like smart boards, computers, projectors and other projected materials to facilitate learning and improve performance. The study examined learning resources as determinants for improving the teaching and learning process in Abubakar Tafawa Balewa University (ATBU), Bauchi, Bauchi state of Nigeria. Three objectives, three research questions and three null hypotheses guided the study. The study adopted a Survey research design. The population of the study was 880 lecturers. A sample of 260 was obtained using the research advisor table for determining sampling, and 250 from the sample was proportionately selected from the seven faculties. The instrument used for data collection was a structured questionnaire. The instrument was subjected to validation by two experts. The reliability of the instrument stood at 0.81, which is reliable. The researchers, assisted by six research assistants, distributed and collected the questionnaire with a 75% return rate. Data were analyzed using mean and standard deviation to answer the research questions, whereas simple linear regression was used to test the null hypotheses at a 0.05 level of significance. The findings revealed that physical facilities and digital technology tools significantly improved the teaching and learning process. Also, consumables, supplies and equipment do not significantly improve the teaching and learning process in the faculties. It was recommended that lecturers in the various faculties should strengthen and sustain the use of digital technology tools, and there is a need to strive and continue to properly maintain the available physical facilities. Also, the university management should, as a matter of priority, continue to adequately fund and upgrade equipment, consumables and supplies frequently to enhance the effectiveness of the teaching and learning process.

Keywords: education, facilities, learning-resources, technology-tools

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Authors: Jae-Ho Jang, Jung-Soo Kim, Byung-Jun Kim, Dae-Geun Nam, Uoo-Chang Jung, Yoon-Suk Choi

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Low alloy steels are widely used for pressure vessels, spent fuel storage, and steam generators required to withstand the internal pressure and prevent unexpected failure in nuclear power plants, which these may suffer embrittlement by high levels of radiation and heat for a long period. Therefore, it is important to improve mechanical properties of low alloy steels for the integrity of structure materials at an early stage of fabrication. Recently, it showed that a double austenitizing and tempering (DTA) process resulted in a significant improvement of strength and toughness by refinement of prior austenite grains. In this study, it was investigated that the mechanism of improving mechanical properties according to the change of microstructure by the second fully austenitizing temperature of the DAT process for low alloy steel required the structural integrity. Compared to conventional single austenitizing and tempering (SAT) process, the tensile elongation properties have improved about 5%, DBTTs have obtained result in reduction of about -65℃, and grain size has decreased by about 50% in the DAT process conditions. Grain refinement has crack propagation interference effect due to an increase of the grain boundaries and amount of energy absorption at low temperatures. The higher first austenitizing temperature in the DAT process, the more increase the spheroidized carbides and strengthening the effect of fine precipitates in the ferrite grain. The area ratio of the dimple in the transition area has increased by proportion to the effect of spheroidized carbides. This may the primary mechanisms that can improve low-temperature toughness and elongation while maintaining a similar hardness and strength.

Keywords: double austenitizing, Ductile Brittle transition temperature, grain refinement, heat treatment, low alloy steel, low-temperature toughness

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Authors: Seulki Lee, Seoung Bum Kim

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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

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Authors: Achim Washington, Reece Clothier, Jose Silva

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System Safety Regulations (SSR) are a central component to the airworthiness certification of Unmanned Aircraft Systems (UAS). There is significant debate on the setting of appropriate SSR for UAS. Putting this debate aside, the challenge lies in how to apply the system safety process to UAS, which lacks the data and operational heritage of conventionally piloted aircraft. The limited knowledge and lack of operational data result in uncertainty in the system safety assessment of UAS. This uncertainty can lead to incorrect compliance findings and the potential certification and operation of UAS that do not meet minimum safety performance requirements. The existing system safety assessment and compliance processes, as used for conventional piloted aviation, do not adequately account for the uncertainty, limiting the suitability of its application to UAS. This paper discusses the challenges of undertaking system safety assessments for UAS and presents current and envisaged research towards addressing these challenges. It aims to highlight the main advantages associated with adopting a risk based framework to the System Safety Performance Requirement (SSPR) compliance process that is capable of taking the uncertainty associated with each of the outputs of the system safety assessment process into consideration. Based on this study, it is made clear that developing a framework tailored to UAS, would allow for a more rational, transparent and systematic approach to decision making. This would reduce the need for conservative assumptions and take the risk posed by each UAS into consideration while determining its state of compliance to the SSR.

Keywords: Part 1309 regulations, risk models, uncertainty, unmanned aircraft systems

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Authors: Satya Srii, V., Nethra, N.

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An image analyzer system is described to study the process of imbibition in Melia dubia seeds. The experimental system consisted of control C (seeds with intact pericarp) with two treatments, namely T1 (seeds with pericarp punctured) and T2 (naked seeds without pericarp). The measurement software in the image analyzer can determine the area and perimeter as descriptors of changes in seed size during swelling resulting from imbibition. Using the area and perimeter parameter, the imbibition process in C, T1, and T2 was described by a series of curves similar to the triphasic pattern of water uptake, with the extent and rate depending upon the treatment. Naked seeds without pericarp (T2) took lesser time to reach phase III during imbition followed by seeds with pericarp punctured (T1) while the seeds with intact pericarp (C) were the slowest to attain phase III. This shows the effect of pericarp in acting as a potential inhibitor to imbibition inducing a large delay in germination. The sensitivity and feasibility of the method to investigate individual seeds within a population imply that the image analyzer has high potential in seed biology studies.

Keywords: germination, imbibition, image analyzer, Melia dubia, pericarp

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Authors: Abdellatif Amouri, Sami Boudabbous

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The current study provides insights on the importance of entrepreneurial coaching as a source of developing entrepreneurial intentions among entrepreneurs and a determinant factor of business creation process and growth. Coaching, which implies exchange of adequate information and a mutual understanding between entrepreneurs and their partners, requires a better mutual knowledge of the representations and the perceptions of ideas which are widely present in their dealings and transactions. Therefore, to analyze entrepreneurs’ perceptions of business creation, we addressed a survey questionnaire to a group of Tunisian entrepreneurs and experts in business creation to indicate their level of approval concerning the prominence of coaching. The factor analysis indicates that more than 60% of the respondents believe that each statement reflects an aspect of coaching, with no bias to its position in the entrepreneurial process. Therefore, the image drawn from our respondents’ perceptions is that an entrepreneur is rather "constructed" and "shaped" by multiple apprenticeships both before and during the entrepreneurial act, through an accompaniment process and within interactions with trainers, consultants or professionals in starting a business. Similarly, the results indicate that the poor support structures and lack of accompaniment procedures stand as an obstacle impeding the development of entrepreneurial intention among business creators.

Keywords: Entrepreneurial Behavior, Entrepreneurial Coaching, Entrepreneurial Intention, Perceptions, Venture Creation

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Authors: Jin Zhi

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This study focuses on a green screen keying method developed especially for film visual effects. There are a series of ways of using existing tools for creating mattes from green or blue screen plates. However, it is still a time-consuming process, and the results vary especially when it comes to retaining tiny details, such as hair and fur. This paper introduces an alternative concept and method for retaining edge details of characters on a green screen plate, also, a number of connected mathematical equations are explored. At the end of this study, a simplified process of applying this method in real productions is also introduced.

Keywords: green screen, visual effects, compositing, matte

Procedia PDF Downloads 404

Authors: Aprajeeta Jha, Punyadarshini P. Tripathy

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Drying is one of the most critical unit operations for prolonging the shelf-life of food grains in order to ensure global food security. Photovoltaic integrated solar dryers can be a sustainable solution for replacing energy intensive thermal dryers as it is capable of drying in off-sunshine hours and provide better control over drying conditions. But, performance and reliability of PV based solar dryers depend hugely on climatic conditions thereby, drastically affecting process parameters. Therefore, to ensure quality and prolonged shelf-life of paddy, optimization of process parameters for solar dryers is critical. Proper moisture distribution within the grains is most detrimental factor to enhance the shelf-life of paddy therefore; modeling of mass transport can help in providing a better insight of moisture migration. Hence, present work aims at optimizing the process parameters and to develop a 3D finite element model (FEM) for predicting moisture profile in paddy during solar drying. Optimization of process parameters (power level, air velocity and moisture content) was done using box Behnken model in Design expert software. Furthermore, COMSOL Multiphysics was employed to develop a 3D finite element model for predicting moisture profile. Optimized model for drying paddy was found to be 700W, 2.75 m/s and 13% wb with optimum temperature, milling yield and drying time of 42˚C, 62%, 86 min respectively, having desirability of 0.905. Furthermore, 3D finite element model (FEM) for predicting moisture migration in single kernel for every time step has been developed. The mean absolute error (MAE), mean relative error (MRE) and standard error (SE) were found to be 0.003, 0.0531 and 0.0007, respectively, indicating close agreement of model with experimental results. Above optimized conditions can be successfully used to dry paddy in PV integrated solar dryer in order to attain maximum uniformity, quality and yield of product to achieve global food and energy security

Keywords: finite element modeling, hybrid solar drying, mass transport, paddy, process optimization

Procedia PDF Downloads 139

Authors: Marina Borgert Moraes, Wesley Francisco, Filipe Vargas, Gilmar Patrocínio Thim

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In recent years, carbon nanotubes (CNT) and graphene oxide (GO), especially the functionalized ones, have been added to epoxy resin in order to increase the mechanical, electrical and thermal properties of nanocomposites. However, it's still unknown how the presence of these nanoparticles influences the curing process and the final mechanical properties as well. In this work, kinetic and mechanical properties of the nanocomposites were analyzed, where the kinetic process was followed by DSC and the mechanical properties by DMA. Initially, CNT was annealed at high temperature (1800 °C) under vacuum atmosphere, followed by a chemical treatment using acids and ethylenediamine. GO was synthesized through chemical route, washed clean, dried and ground to #200. The presence of functional groups on CNT and GO surface was confirmed by XPS spectra and FT-IR. Then, epoxy resin, nanoparticles and acetone were mixed by sonication in order to obtain the composites. DSC analyses were performed on samples with different curing cycles (1h 80°C + 2h 120°C; 3h 80°C + 2h 120°C; 5h 80°C) and samples with different times at constant temperature (120°C). Results showed that the kinetic process and the mechanical strength are very dependent on the presence of graphene and functionalized-CNT in the nanocomposites.

Keywords: carbon nanotube, epoxy resin, Graphene oxide, nanocomposite

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

Procedia PDF Downloads 305