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Journal articles on the topic 'Computer process variables'

Author: Grafiati

Published: 19 February 2023

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1

Turng, L.-S., and M. Peić. "Computer aided process and design optimization for injection moulding." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 216, no. 12 (December 1, 2002): 1523–32. http://dx.doi.org/10.1243/095440502321016288.

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Sophisticated computer aided engineering (CAE) simulation tools for injection moulding have been available and are now widely used in industrial practices. As a result, the design and manufacturing of injection-moulded parts have been literally transformed from a ‘black art’ to an engineering discipline based on scientific principles. It is well recognized that computer simulation tools help engineers to gain process insight and to pinpoint blind spots and problems that are overlooked. Nevertheless, there remains a missing link in CAE, which lies in the ability to identify effectively the optimal design and process variables, as it is hampered by the sheer amount of computer-generated data and complex non-linear interactions among those input variables. This paper presents the system implementation and experimental verifications of an integrated CAE optimization tool that couples a process simulation program with optimization algorithms to determine intelligently and automatically the optimal design and process variables for injection moulding. In addition, this study enables evaluation and comparison of various local and global optimization algorithms in terms of computational efficiency and effectiveness for injection moulding, as presented in this paper.

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2

Shamasundar, S., A. G. Marathe, and S. K. Biswas. "Effect of Process Variables on Die-Billet Temperature History in a Slow Speed Hot Coining Type Process." Journal of Engineering for Industry 113, no. 4 (November 1, 1991): 362–72. http://dx.doi.org/10.1115/1.2899709.

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A computer code is developed as a part of an ongoing project on computer aided process modelling of forging operation, to simulate heat transfer in a die-billet system. The code developed on a stage-by-stage technique is based on an Alternating Direction Implicit scheme. The experimentally validated code is used to study the effect of process specifics such as preheat die temperature, machine ascent time, rate of deformation, and dwell time on the thermal characteristics in a batch coining operation where deformation is restricted to surface level only.

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3

Offermans, Tim, Ewa Szymańska, Lutgarde M. C. Buydens, and Jeroen J. Jansen. "Synchronizing process variables in time for industrial process monitoring and control." Computers & Chemical Engineering 140 (September 2020): 106938. http://dx.doi.org/10.1016/j.compchemeng.2020.106938.

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Williams-Green, Joyce, Glen Holmes, and Thomas M. Sherman. "Culture as a Decision Variable for Designing Computer Software." Journal of Educational Technology Systems 26, no. 1 (September 1997): 3–18. http://dx.doi.org/10.2190/ljuq-19h1-ulkc-dt1h.

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Computer software design generally follows a systematic process that addresses decisions on variables known to influence learning success. We propose that culture should be included as part of this decision process. Culture represents the complex of social, emotional, intellectual, physical, and personal factors that individuals use to create meaning. When these cognitive anchors are missing from instructional materials, achievement may be imperiled. Examples of how cultural variables can be incorporated into instructional decisions are presented to illustrate the potential for enhancing software.

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Slišković, Dražen, Ratko Grbić, and Željko Hocenski. "Adaptive Estimation of Difficult-to-Measure Process Variables." Automatika 54, no. 2 (January 2013): 166–77. http://dx.doi.org/10.7305/automatika.54-2.147.

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6

Watson, J. Allen, Michelle I. Eichhorn, and John Scanzoni. "A Home/University Computer Network: Test of a System to Study Families." Journal of Educational Technology Systems 17, no. 4 (June 1989): 319–35. http://dx.doi.org/10.2190/j7uk-5bax-ccb0-p9yf.

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The primary purpose of this study was to produce a new computer-based research paradigm designed to test family process variables. Twenty-nine males representing twenty-nine homes each with a microcomputer and modem served as subjects across a two-month period. A microcomputer/mainframe system was developed and integrated with a conceptual model used to test family decision-making variables. Nine subtests used in the conceptual model served as process variables in this study. Attitude questions concerning gender role preferences, religious commitment, empathy toward spouse, marital commitment, perception of spousal conflicts, degree of individualism, and self-esteem were presented and recorded via university mainframe from home computers. Data were analyzed across two test battery replication (two months). Data showed that the integration of an existing family process conceputal model and the microcomputer/mainframe system could be used as a new research paradigm, that the two months testing provided strong support for paradigm efficiency, and that the paradigm proved to be highly reliable and valid.

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Fonseca, Ijar M., and Peter M. Bainum. "Integrated Structural and Control Optimization." Journal of Vibration and Control 10, no. 10 (October 2004): 1377–91. http://dx.doi.org/10.1177/1077546304042043.

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This paper focuses on the integrated structural/control optimization of a large space structure with a robot arm subject to the gravity-gradient torque through a semi-analytical approach. It is well known that the computer effort to compute numerically derivatives of the constraints with respect to design variables makes the process expensive and time-consuming. In this sense, a semi-analytical approach may represent a good alternative when optimizing systems that require sensitivity calculations with respect to design parameters. In this study, constraints from the structure and control disciplines are imposed on the optimization process with the aim of obtaining the structure’s minimum weight and the optimum control performance. In the process optimization, the sensitivity of the constraints is computed by a semi-analytical approach. This approach combines the use of analytical derivatives of the mass and stiffness matrices with the numerical solution of the eigenvalue problem to obtain the eigenvalue derivative with respect to the design variables. The analytical derivatives are easy to obtain since our space structure is a long one-dimensional beam-like spacecraft.

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Hofmann, N., S. Olive, G. Laschet, F. Hediger, J. Wolf, and P. R. Sahm. "Numerical optimization of process control variables for the Bridgman casting process." Modelling and Simulation in Materials Science and Engineering 5, no. 1 (January 1, 1997): 23–34. http://dx.doi.org/10.1088/0965-0393/5/1/002.

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9

Thoreson, Curtis, Keith Webster, Matthew Darr, and Emily Kapler. "Investigation of Process Variables in the Densification of Corn Stover Briquettes." Energies 7, no. 6 (June 24, 2014): 4019–32. http://dx.doi.org/10.3390/en7064019.

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10

Boschetti, F., F. M. Montevecchi, and R. Fumero. "Virtual Extracorporeal Circulation Process." International Journal of Artificial Organs 20, no. 6 (June 1997): 341–51. http://dx.doi.org/10.1177/039139889702000608.

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Virtual instruments for an extracorporeal circulation (ECC) process were developed to simulate the reactions of a patient to different artificial perfusion conditions. The computer simulation of the patient takes into account the hydraulic, volume, thermal and biochemical phenomena and their interaction with the devices involved in ECC (cannulae dimensions, oxygenator and filter types, pulsatile or continuous pump and thermal exchangers). On the basis of the patient's initialisation data (height, weight, Ht) and perfusion variables (pump flow rate, water temperature, gas flow rate and composition) imposed by the operator, the virtual ECC monitors simulated arterial and venous pressure tracings in real time, along with arterial and venous flow rate tracings, urine production tracing and temperature levels. Oxyhemoglobin arterial and venous blood saturation together with other related variables (pO2, pCO2, pH, HCO3) are also monitored. A drug model which allows the simulation of the effect of vasodilator and diuretic drugs is also implemented. Alarms are provided in order to check which variables (pressure, saturation, pH, urine flow) are out of the expected ranges during the ECC simulation. Consequently the possibility of modifying the control parameters of the virtual devices of the ECC in run-time mode offers an interaction mode between the operator and the virtual environment.

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Alrazeq Saeed, Farah Jamal Abed. "Attitudes of Jordanian Undergraduate Students towards Using Computer Assisted Language Learning (CALL)." International Journal of Education and Literacy Studies 6, no. 1 (January 31, 2018): 12. http://dx.doi.org/10.7575/aiac.ijels.v.6n.1p.12.

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The study aimed at investigating the attitudes of Jordanian undergraduate students towards using computer assisted -language learning (CALL) and its effectiveness in the process of learning the English language. In order to fulfill the study’s objective, the researchers used a questionnaire to collect data, followed-up with semi-structured interviews to investigate the students’ beliefs towards CALL. Twenty- one of Jordanian BA students majoring in English language and literature were selected according to simple random sampling. The results revealed positive attitudes towards CALL in facilitating the process of writing assignments, gaining information; making learning enjoyable; improving their creativity, productivity, academic achievement, critical thinking skills, and enhancing their knowledge about vocabulary grammar, and culture. Furthermore, they believed that computers can motivate them to learn English language and help them to communicate and interact with their teachers and colleagues. The researchers recommended conducting a research on the same topic, taking into consideration the variables of age, gender, experience in using computers, and computer skills.

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Hasan, Raza, Sellappan Palaniappan, Salman Mahmood, Kamal Uddin Sarker, Mian Usman Sattar, Ali Abbas, Vikas Rao Naidu, and Puttaswamy Malali Rajegowda. "eDify: Enhancing Teaching and Learning Process by Using Video Streaming Server." International Journal of Interactive Mobile Technologies (iJIM) 15, no. 11 (June 4, 2021): 49. http://dx.doi.org/10.3991/ijim.v15i11.20245.

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The study investigates the nature and degree of influence of the range of application usability variables on the learning experience of the students at a specific institution of higher education institution in Oman. The study was carried out via eDify implementation encompassing the usability variables and learning experience of the students. Literature does little to suggest the aforementioned relationship in the context of the Omani higher education. The current study would reveal the variables that are critical to effective technology-based learning of the students. The implications generated through the study would allow the institution involved in the study to effectively implement the variables required for enhanced teaching and learning. The methodology used in the study is divided into an exploratory and the main research. Principal component analysis and a range of regression analyses are conducted to test the relationships between the independent and the dependent variable, “learning experience”. Results suggest that the usability variables have both positive and significant effects on the dependent variable of the learning experience. One usability variable that stands out more than others is the usage of mobile media.

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Mendonça, Yuri V. S., Paola G. Vinueza Naranjo, and Diego Costa Pinto. "The Role of Technology in the Learning Process: A Decision Tree-Based Model Using Machine Learning." Emerging Science Journal 6 (January 5, 2023): 280–95. http://dx.doi.org/10.28991/esj-2023-sied-020.

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Machine learning approaches may establish a complex and non-linear relationship among input and response variables for the assessment of the Basic Education Development Index (IDEB) database and show indicators that may contribute to monitoring the quality of education. This paper uses extensive experimental databases from public schools, consisting of a case study in Brazil, to analyze data such as the physical and technological structure of schools and teacher profiles. The research proposes decision tree-based machine learning models for predictions of the best attributes to positively contribute to IDEB. It employs a newly developed SHapley Additive exPlanations (SHAP) approach to classify input variables, so to identify variables that impact the most the final model; a non-probabilistic sample was used, composed from three official databases of 450 schools, and 617 teachers. Results show that the number of computers per student, teachers’ service time, broadband internet access, investments in technology training for teachers, and computer labs in schools are the variables that have the greatest effect on IDEB. The model applied shows high prediction accuracy for test data (MSE = 0.2094 and R² = 0.8991). This article contributes to improving efficiency when monitoring parameters used to measure the quality of a teaching-learning process. Doi: 10.28991/ESJ-2022-SIED-020 Full Text: PDF

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Mendonça, Yuri V. S., Paola G. Vinueza Naranjo, and Diego Costa Pinto. "The Role of Technology in the Learning Process: A Decision Tree-Based Model Using Machine Learning." Emerging Science Journal 6 (January 5, 2023): 280–95. http://dx.doi.org/10.28991/esj-2022-sied-020.

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Machine learning approaches may establish a complex and non-linear relationship among input and response variables for the assessment of the Basic Education Development Index (IDEB) database and show indicators that may contribute to monitoring the quality of education. This paper uses extensive experimental databases from public schools, consisting of a case study in Brazil, to analyze data such as the physical and technological structure of schools and teacher profiles. The research proposes decision tree-based machine learning models for predictions of the best attributes to positively contribute to IDEB. It employs a newly developed SHapley Additive exPlanations (SHAP) approach to classify input variables, so to identify variables that impact the most the final model; a non-probabilistic sample was used, composed from three official databases of 450 schools, and 617 teachers. Results show that the number of computers per student, teachers’ service time, broadband internet access, investments in technology training for teachers, and computer labs in schools are the variables that have the greatest effect on IDEB. The model applied shows high prediction accuracy for test data (MSE = 0.2094 and R² = 0.8991). This article contributes to improving efficiency when monitoring parameters used to measure the quality of a teaching-learning process. Doi: 10.28991/ESJ-2022-SIED-020 Full Text: PDF

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15

Hosseini, Amir Hossein, Sajid Hussain, and Hossam A. Gabbar. "Detecting nonlinear interrelation patterns among process variables using genetic programming." Soft Computing 18, no. 7 (October 30, 2013): 1283–92. http://dx.doi.org/10.1007/s00500-013-1142-3.

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16

Duineveld, C. A. A., A. K. Smilde, and D. A. Doornbos. "Comparison of experimental designs combining process and mixture variables." Chemometrics and Intelligent Laboratory Systems 19, no. 3 (January 1993): 295–308. http://dx.doi.org/10.1016/0169-7439(93)80029-h.

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Duineveld, C. A. A., A. K. Smilde, and D. A. Doornbos. "Comparison of experimental designs combining process and mixture variables." Chemometrics and Intelligent Laboratory Systems 19, no. 3 (January 1993): 309–18. http://dx.doi.org/10.1016/0169-7439(93)80030-l.

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18

Knight, James F. "Acceptability of Video Games Technology for Medical Emergency Training." International Journal of Gaming and Computer-Mediated Simulations 5, no. 4 (October 2013): 86–99. http://dx.doi.org/10.4018/ijgcms.2013100105.

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Using the technology acceptance model (TAM), this study aimed to investigate the acceptability of video game technologies (serious games) for medical emergency procedure and decision making training. Using the Triage Trainer, a prototype serious game for the triage sieve process, differences between gamers and non-gamers, males and females, and the effects of ratings of computer self efficacy (i.e. computer skill and gaming skill) and attitudes towards computers (i.e. enthusiasm and anxiety) on the acceptance model were also investigated. The results show significant correlations for computer self-efficacy and attitude variables with the perceived ease of use (PEOU), perceived usefulness (PU) and attitudes towards use (ATU) of the game. Multiple regression showed that 52% of the variance in ATU was explained by the PU and PEOU. However, none of the secondary variables (self efficacy or emotions) had a significant effect on the ATU, PU and PEOU over and above each other.

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19

Lv, Heng, Xue Ke Sun, Xi Yang, and Cen Feng. "Computer Accounting and Analysis System of Silk’s Weaving Process and Equipment." Applied Mechanics and Materials 251 (December 2012): 56–60. http://dx.doi.org/10.4028/www.scientific.net/amm.251.56.

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On the basis of silk fabric product specifications, making use of programming software to deal with product information, complete the complicated process calculation, realize the connection and running of products information database with the front desk inquiry calculation software. The system can achieve the number of all kinds of machines by automatic accounting according to the requirements of the design, and realize variables to be automatically selected such as the spindle number, efficiency, working hours and linear velocity. Automatically plot and analyze the variation trend of mechanical number in different fabric situation when the number of loom or annual output equality variation. The system contribute to production manager configure the process equipment rapidly and estimate the production ability.

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20

Abdalla, Musa, and Tamir Shagarin. "Industrial Process Control Using LPV." Modern Applied Science 11, no. 9 (August 11, 2017): 39. http://dx.doi.org/10.5539/mas.v11n9p39.

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An industrial process control application of level and temperature is considered. The nonlinear mathematical model of the system is cast as a linear parameter varying (LPV) system. A linear matrix inequality (LMI) type of controller is successfully designed using the LMI unified approach to regulating both controlled variables, namely; temperature and level. The closed loop system is then implemented through computer simulation to show the effectiveness of the controller in performing the combined level-temperature regulation. Basically, this combined level and temperature industrial control application is used to demonstrate the effectiveness of post-modern controllers; in this case LMI based controllers.

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21

Thete, M. M. "Runner-upSimulation of Gas Carburising: Development of Computer Program with Systematic Analyses of Process Variables Involved." Surface Engineering 19, no. 3 (June 2003): 217–28. http://dx.doi.org/10.1179/026708403225006131.

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22

Minari, Roque J., Georgina S. Stegmayer, Luis M. Gugliotta, Omar A. Chiotti, and Jorge R. Vega. "Industrial SBR Process: Computer Simulation Study for Online Estimation of Steady-State Variables Using Neural Networks." Macromolecular Reaction Engineering 1, no. 3 (May 8, 2007): 405–12. http://dx.doi.org/10.1002/mren.200600042.

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23

Pittenger, David J. "Perception Laboratory: A Computer Program to Demonstrate Perceptual Phenomena." Teaching of Psychology 23, no. 1 (February 1996): 46–48. http://dx.doi.org/10.1207/s15328023top2301_12.

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I developed an interactive computer program that allows one to demonstrate and experiment with various phenomena in visual perception using IBM-compatible computers. The program contains modules for demonstrating the color afterimage, the cafe illusion, additive color mixing and the opponent-process theory of color vision, the glowing axes illusion, the Hermann grid, the McCollough effect, the motion aftereffect, the neon illusion, and simultaneous contrast. The user has considerable control over the stimuli making up the image and can manipulate the variables that contribute to the perception of the effect. The program can be used far classroom demonstrations and student laboratory projects.

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24

Hallgrímsson, Ásgeir Daniel, Hans Henrik Niemann, and Morten Lind. "Unsupervised isolation of abnormal process variables using sparse autoencoders." Journal of Process Control 99 (March 2021): 107–19. http://dx.doi.org/10.1016/j.jprocont.2021.01.005.

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25

Sundaram, Sampath, Lalitha Singhan Madhavachari, and Ramya Balu. "Chance Single Sampling Plan for Variables." International Journal of Fuzzy System Applications 4, no. 1 (January 2015): 43–59. http://dx.doi.org/10.4018/ijfsa.2015010103.

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This paper considers the design of single sampling plan for variables when the experimental values are treated as observations on independently and identically distributed normal random variables with fuzzy mean value. The design makes use of Liu's (2008) model IV of Chance Theory. Sampling Plans determined by the sample sizes and acceptance numbers are constructed for situations involving imprecise parameter on using chance theory. The process of determining sample sizes and acceptance threshold values has been carried out on assuming the observed values have hybrid normal distribution. Optimal chance sampling plans for variables are also determined by using minimum angle criterion for different choices of fuzzy risks.

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Zhao, Yuexuan, and Jing Huang. "Dirichlet Process Prior for Student’s t Graph Variational Autoencoders." Future Internet 13, no. 3 (March 16, 2021): 75. http://dx.doi.org/10.3390/fi13030075.

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Graph variational auto-encoder (GVAE) is a model that combines neural networks and Bayes methods, capable of deeper exploring the influential latent features of graph reconstruction. However, several pieces of research based on GVAE employ a plain prior distribution for latent variables, for instance, standard normal distribution (N(0,1)). Although this kind of simple distribution has the advantage of convenient calculation, it will also make latent variables contain relatively little helpful information. The lack of adequate expression of nodes will inevitably affect the process of generating graphs, which will eventually lead to the discovery of only external relations and the neglect of some complex internal correlations. In this paper, we present a novel prior distribution for GVAE, called Dirichlet process (DP) construction for Student’s t (St) distribution. The DP allows the latent variables to adapt their complexity during learning and then cooperates with heavy-tailed St distribution to approach sufficient node representation. Experimental results show that this method can achieve a relatively better performance against the baselines.

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Kusmaeni, Emi, Ratna Nugraheni, Nenny Syahrenny, and Endah Sulistyowati. "Pengaruh Computer Anxiety, Computer Self Efficacy, Pemahaman Akuntansi Terhadap Minat Mahasiswa Menggunakan Software Akuntansi." E-Jurnal Akuntansi 32, no. 9 (September 25, 2022): 2748. http://dx.doi.org/10.24843/eja.2022.v32.i09.p09.

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The purpose of this research is to assess the factors that influence learning interest in using software and to find out the shortcomings that occur in the learning process so that it can improve the learning process strategy. The research population is the 2018-2019 class of students with a total of 338 students being the research sample. Statistics used multiple linear regression analysis. The results showed that computer anxiety and computer self-efficacy had a significant effect on students' interest in using accounting software. While the understanding of accounting has no effect on student interest. So it can be concluded that the variables of computer anxiety, computer self-efficacy, and understanding of accounting have a significant effect on students' interest in using accounting software. Keywords: Computer Anxiety; Computer Self Efficacy; Students’ Interest; Accounting Software

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Yamada, Nobuhito, and Hiromasa Kaneko. "Adaptive soft sensor ensemble for selecting both process variables and dynamics for multiple process states." Chemometrics and Intelligent Laboratory Systems 219 (December 2021): 104443. http://dx.doi.org/10.1016/j.chemolab.2021.104443.

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Savard, Isabelle, Jacqueline Bourdeau, and Gilbert Paquette. "Considering cultural variables in the instructional design process: A knowledge-based advisor system." Computers & Education 145 (February 2020): 103722. http://dx.doi.org/10.1016/j.compedu.2019.103722.

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Offermans, Tim, Ewa Szymańska, Geert H. van Kolllenburg, Lutgarde M. C. Buydens, and Jeroen J. Jansen. "Automatically optimizing dynamic synchronization of individual industrial process variables for statistical modelling." Computers & Chemical Engineering 152 (September 2021): 107402. http://dx.doi.org/10.1016/j.compchemeng.2021.107402.

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Kumar Sunori, Sandeep, Pradeep Kumar Juneja, and Anamika Bhatia Jain. "Model Predictive Control System Design for Boiler Turbine Process." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 5 (October 1, 2015): 1054. http://dx.doi.org/10.11591/ijece.v5i5.pp1054-1061.

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<p>MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In the present work the control of boiler turbine process with three manipulated variables namely fuel flow valve position, steam control valve position and feed water flow valve position and three controlled variables namely drum pressure, output power and drum water level deviation [8] has been attempted using MPC technique. Boiler turbine process is very complex and nonlinear multivariable process. A linearized model obtained using Taylor series expansion around operating point has been used.</p>

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Sajaniemi, Jorma, and Marja Kuittinen. "Visualizing Roles of Variables in Program Animation." Information Visualization 3, no. 3 (June 3, 2004): 137–53. http://dx.doi.org/10.1057/palgrave.ivs.9500075.

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Visualizations may be used to assist in learning elementary computer programming - a skill that is hard to acquire by many students. This article presents a program animation system, PlanAni, that is based on the concept of the roles of variables. Roles represent schematic uses of variables that occur in programs over and over again, and a set of nine roles covers practically all variables in novice-level programs. PlanAni has been evaluated in a classroom experiment comparing traditional teaching with role-based teaching and animation. The results suggest that the introduction of roles provides students with a new conceptual framework that enables them to mentally process program information in a way similar to that of good code comprehenders. The use of role-based animation seems to assist in the adoption of role knowledge and expert-like programming strategies. A semi-structured interview with the teacher indicates that students like to work with the animator and that the system clarifies many concepts in programming.

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DE ALMEIDA, GUSTAVO M., MARCELO CARDOSO, DANILO C. RENA, and SONG W. PARK. "GRAPHICAL REPRESENTATION OF CAUSE-EFFECT RELATIONSHIPS AMONG CHEMICAL PROCESS VARIABLES USING A NEURAL NETWORK APPROACH." International Journal of Computational Intelligence and Applications 09, no. 01 (March 2010): 69–86. http://dx.doi.org/10.1142/s146902681000277x.

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The extraction of information from tabular data is not a natural task for human beings, which is worse when dealing with high dimensional systems. On the other hand, graphical representations make the understanding easier by exploring the human capacity of processing visual information. Such representations can be used for many purposes, e.g., complex systems structuring which contributes to a better understanding of it. This paper constructs a cause-effect map relating the influence of each input process variable on the steam generated by a boiler. The real case study is based on the operations of a chemical recovery boiler of a Kraft pulp mill in Brazil. The map is obtained by two steps, namely the identification of a neural predictive model for the steam and a study of sensitivity analysis. The numerical results are then depicted in a graphical format using a cause-effect map. This representation highlights the relative importance of the predictor variables to the steam generation. The results, in agreement with the literature, show the higher contribution of the heat released during the fuel burning, and the lower influence of both the fuel temperature and the operating variables associated with the primary level of injection of the combustion air.

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Raman, Shivakumar, and Ravi Lakkaraju. "The effect of tool life and other process variables in NC path planning." Computers & Industrial Engineering 24, no. 2 (April 1993): 315–28. http://dx.doi.org/10.1016/0360-8352(93)90017-r.

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Houshmand, Mahmoud, and Bizhan Jamshidnezhad. "An extended model of design process of lean production systems by means of process variables." Robotics and Computer-Integrated Manufacturing 22, no. 1 (February 2006): 1–16. http://dx.doi.org/10.1016/j.rcim.2005.01.004.

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36

Riddell, W. Craig, and Xueda Song. "The Role of Education in Technology Use and Adoption: Evidence from the Canadian Workplace and Employee Survey." ILR Review 70, no. 5 (January 13, 2017): 1219–53. http://dx.doi.org/10.1177/0019793916687719.

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Technology use and adoption by firms and workers is a critical component of the process of technological change. Relying on data from the Canadian Workplace and Employee Survey, this study assesses the causal effects of education on technology use and adoption by using instrumental variables for schooling derived from Canadian compulsory school attendance laws. The authors find that education increases the probability of using computers on the job, and that employees with more education spend more time using computers and have longer work experiences with computers than those with less education. Education does not, however, influence the use of computer-controlled and computer-assisted devices or other technological devices such as cash registers and sales terminals. These findings are consistent with the view that formal education increases the use of technologies that require or enable workers to carry out higher-order tasks, but not those involving routine workplace tasks.

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Yang, Fan, Sirish Shah, and Deyun Xiao. "Signed directed graph based modeling and its validation from process knowledge and process data." International Journal of Applied Mathematics and Computer Science 22, no. 1 (March 1, 2012): 41–53. http://dx.doi.org/10.2478/v10006-012-0003-z.

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Signed directed graph based modeling and its validation from process knowledge and process data This paper is concerned with the fusion of information from process data and process connectivity and its subsequent use in fault diagnosis and process hazard assessment. The Signed Directed Graph (SDG), as a graphical model for capturing process topology and connectivity to show the causal relationships between process variables by material and information paths, has been widely used in root cause and hazard propagation analysis. An SDG is usually built based on process knowledge as described by piping and instrumentation diagrams. This is a complex and experience-dependent task, and therefore the resulting SDG should be validated by process data before being used for analysis. This paper introduces two validation methods. One is based on cross-correlation analysis of process data with assumed time delays, while the other is based on transfer entropy, where the correlation coefficient between two variables or the information transfer from one variable to another can be computed to validate the corresponding paths in SDGs. In addition to this, the relationship captured by data-based methods should also be validated by process knowledge to confirm its causality. This knowledge can be realized by checking the reachability or the influence of one variable on another based on the corresponding SDG which is the basis of causality. A case study of an industrial process is presented to illustrate the application of the proposed methods.

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Gao, Ling, Yu Tian Lin, Hui Bin Lin, Xiao Yi Jia, Jian Qun Lin, and Jian Qiang Lin. "Construction of Computer Controlled Bioreactor." Applied Mechanics and Materials 472 (January 2014): 171–75. http://dx.doi.org/10.4028/www.scientific.net/amm.472.171.

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Bioprocess automation is developing fast for the reasons of quality control, production cost reduction et. al.. Bioreactor is the central equipment of bioprocess. Construction of computer controlled bioreactor is need for bioprocess automation. In this research, a two level hierarchical structure computer control bioreactor system is designed and constructed. The lower level plays the major role of set-point feedback control of process variables and the higher level plays the major role of graphical human interface and biological mathematical model solution. This control system has advantages of high reliability and flexibility than the single level digital control system, and has plenty of functions and high practicality compared with a normal commercial one.

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Xu, Chen, and Fei Liu. "Process monitoring based on distributed principal component analysis with angle-relevant variable selection." International Journal of Distributed Sensor Networks 15, no. 6 (June 2019): 155014771985758. http://dx.doi.org/10.1177/1550147719857583.

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Multivariate statistics process monitoring can achieve dimensionality reduction and latent feature extraction on process variables. However, process variables without beneficial information may affect the monitoring performance. This article proposes a distributed principal component analysis method based on the angle-relevant variable selection for plant-wide process monitoring. The directions of principal components are utilized to construct the sub-blocks, where the variables in each sub-block are determined by angle. After establishing the principal component analysis model in each sub-block, the monitoring results are fused by Bayesian inference. The simulation results show that the proposed method can select the responsible variables effectively and enhance the monitoring performance.

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Gedzevicius, I., and A. V. Valiulis. "Analysis of wire arc spraying process variables on coatings properties." Journal of Materials Processing Technology 175, no. 1-3 (June 2006): 206–11. http://dx.doi.org/10.1016/j.jmatprotec.2005.04.019.

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Epprecht, Eugenio K., Francisco Aparisi, and Sandra García-Bustos. "Optimal linear combination of Poisson variables for multivariate statistical process control." Computers & Operations Research 40, no. 12 (December 2013): 3021–32. http://dx.doi.org/10.1016/j.cor.2013.07.007.

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Eang, Rashid, Nakorn Tippayawong, and Yuegang Yuegang Tan. "Optimization of process variables for drying of cashew nuts by superheated steam." Cogent Engineering 5, no. 1 (January 1, 2018): 1531457. http://dx.doi.org/10.1080/23311916.2018.1531457.

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Forina, M., P. Oliveri, and M. Casale. "Complete validation for classification and class modeling procedures with selection of variables and/or with additional computed variables." Chemometrics and Intelligent Laboratory Systems 102, no. 2 (July 2010): 110–22. http://dx.doi.org/10.1016/j.chemolab.2010.04.011.

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Fachri, Syahyulita, Eka Irawan, and Ilham Syahputra Saragih. "Pengambilan Keputusan Dalam Menentukan Media Pembelajaran Online Pada Masa Pandemi Menggunakan Metode AHP dan TOPSIS." BEES: Bulletin of Electrical and Electronics Engineering 2, no. 2 (November 30, 2021): 47–52. http://dx.doi.org/10.47065/bees.v2i2.952.

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STIKOM Tunas Bangsa is one of the computer science colleges located in Pematangsiantar City. Due to the Covid-19 Pandemic Period, the teaching and learning process is carried out online at their respective homes by students and lecturers. Sources of data obtained by interview and direct observation to students. The author's goal in this study is to determine the best learning media in the Information Systems Study Program at STIKOM Tunas Bangsa by using a combination of TOPSIS and AHP methods. With the given material variables, What'sApp variables, Classroom variables, and E-Learning variables, Google Meet variables and Zoom variables. The result of this study is the increase in the learning process and understanding of students during the Covid 19 Pandemic

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Apley, Daniel W., Jun Liu, and Wei Chen. "Understanding the Effects of Model Uncertainty in Robust Design With Computer Experiments." Journal of Mechanical Design 128, no. 4 (December 19, 2005): 945–58. http://dx.doi.org/10.1115/1.2204974.

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The use of computer experiments and surrogate approximations (metamodels) introduces a source of uncertainty in simulation-based design that we term model interpolation uncertainty. Most existing approaches for treating interpolation uncertainty in computer experiments have been developed for deterministic optimization and are not applicable to design under uncertainty in which randomness is present in noise and/or design variables. Because the random noise and/or design variables are also inputs to the metamodel, the effects of metamodel interpolation uncertainty are not nearly as transparent as in deterministic optimization. In this work, a methodology is developed within a Bayesian framework for quantifying the impact of interpolation uncertainty on the robust design objective, under consideration of uncertain noise variables. By viewing the true response surface as a realization of a random process, as is common in kriging and other Bayesian analyses of computer experiments, we derive a closed-form analytical expression for a Bayesian prediction interval on the robust design objective function. This provides a simple, intuitively appealing tool for distinguishing the best design alternative and conducting more efficient computer experiments. We illustrate the proposed methodology with two robust design examples—a simple container design and an automotive engine piston design with more nonlinear response behavior and mixed continuous-discrete design variables.

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Aher, Vijaya N., Ganesh S. Sable, and Minakshi R. Rajput. "Optimization and Estimation of Transfer Function Model of Milk Evaporation Process." International Journal of Engineering and Advanced Technology 10, no. 5 (June 30, 2021): 308–14. http://dx.doi.org/10.35940/ijeat.e2800.0610521.

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Development of Mathematical model has significant role in many applications such as estimation of relations between input and output variables. The relations can be deterministic or behavioral. From the point of view of control actions to be estimated for a particular application, behavioral model is considered to be of utmost importance. This also amounts the prediction of process behavior in time, frequency and complex domains. Here in this paper, attempts have been made to develop behavioral model of milk evaporation used in dairy industry which is of prominent importance in India because of its agriculture based economy. Besides India, there are also many milk producing countries in the world and their economy is dependent on milk producing animals. It is also imperative that excess milk production to be converted in its preservable form and evaporated milk has special significance in this context. The Milk evaporation is a complex process and its output control variables depend on many of its input manipulation variables. Because of its complex nature and many variables involved in it poses a challenge real life MIMO problem. In this paper, MIMO model of Milk evaporation model is estimated and described.

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Chang, Peter, and Leonhard Bernold. "Multi-objective process optimization for construction." Canadian Journal of Civil Engineering 19, no. 1 (February 1, 1992): 129–36. http://dx.doi.org/10.1139/l92-013.

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Much of the existing work in construction analysis focuses on determining the construction cost based on an allowable project duration. In this type of construction analysis, two important questions are not considered. First, is the construction cost minimized for the allowable process duration? Second, would a small change in the process duration result in a significant change in the cost of the project? An optimization method is proposed to answer these questions. The approach consists of an integration of computer simulation with goal programming. The optimization method proposed allows one to assign priorities to the various design objectives such as cost and duration, which avoids the need to use subjective weights. Furthermore, since the approach simulates the construction process by computer, it can be applied to any repetitive construction process. In addition to the capability of the model to provide a single optimal solution to a construction optimization problem, it can be used to determine the trade-off between conflicting objectives. Examples are presented to illustrate the formulation process and the capabilities as a decision-making tool for construction. It is shown that the trade-off curves produced by the proposed model can provide useful information on the cost implications of various design variables, as well as on the trade-offs that exist among them. Key words: construction optimization, multi-objective optimization, goal programming, trade-off analysis, simulation.

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Young, David A., and Robert L. Bettinger. "The Numic Spread: A Computer Simulation." American Antiquity 57, no. 1 (January 1992): 85–99. http://dx.doi.org/10.2307/2694836.

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We develop a mathematical model for the spread of Numic-speaking peoples across the Great Basin in the second millennium A.D., in accord with the ideas of Bettinger and Baumhoff (1982), who suggested a competitive interaction between the Numic and Prenumic peoples of the region. We construct differential equations representing two competing populations that spread by a diffusion process across an area representing the Great Basin. The demographic variables are fixed to agree with ethnographic data, while the migration rates are fitted to the estimated time for the completion of the spread. The model predicts a spatial distribution of the Numic languages in satisfactory agreement with observations and suggests new avenues of investigation.

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Williams, Sue W., and Shirley M. Rosenwasser. "Computer Interest Differences in Preschool Children According to Sex and Psychological Sex-Typing." Psychology and Human Development: an international journal 2, no. 2 (March 1, 1989): 55–60. http://dx.doi.org/10.2224/sbp.6425.

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The computer interest of 3- and 4-year-old children attending a university-affiliated day care center was assessed via their participation in self-selected computer activities. Computer participation involved a 3-step process culminating in terminal interaction: proximity, observation, and working. Results of 2-way analyses of variance unexpectedly indicated higher computer interest scores for females than males; however, no effects were found for age. Pearson correlations indicated a pattern of negative relationships between boys' preference for the adult male role and the computer interest variables.

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Mackevičius, Vigirdas, and Gabrielė Mongirdaitė. "Weak Approximations of the Wright–Fisher Process." Mathematics 10, no. 1 (January 1, 2022): 125. http://dx.doi.org/10.3390/math10010125.

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In this paper, we construct first- and second-order weak split-step approximations for the solutions of the Wright–Fisher equation. The discretization schemes use the generation of, respectively, two- and three-valued random variables at each discretization step. The accuracy of constructed approximations is illustrated by several simulation examples.

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