Process Modeling - Science topic

If lack of fit is not showing whether the model is significant or non-significant, it typically means that the model does not adequately capture the relationship in the data. In other words, the model's predictions are not significantly different from the actual data points. It may be necessary to reconsider the model choice, check for potential outliers.

Are you now selecting a model that best 'proves your hypothesis'? I understand that this what you are taught to do. I am however worried that you are now data-dredging and this is acceptable practice (https://en.wikipedia.org/wiki/Forking_paths_problem or The Garden of Forking Paths: Why Multiple Comparisons Can Be a Problem, Even When There Is No ‘Fishing Expedition’ or ‘p-Hacking’ and the Research Hypothesis Was Posited Ahead of Time). Using such methods all hypothesis will be 'proven', but no argument that is placed will be internally valid. As such all 'scientific' articles 'proof' their hypothesis. However, nothing of what is written in the before sentence is semantically correct. Proofs are something for the deductive sciences and frequentsist methods cannot support hypothesis (https://en.m.wikipedia.org/wiki/Misuse_of_p-values). This might come over as harsh, and it is, but somehow these issues are written about in the tons, but nobody really dares to say something. If you say something it might harm my your career or you seem to be nitpicking or overly critical. But now, none of our results are practically meaningful, because we only select what we want to see. Then to stay in 'science' you have to perform the same because thats how you get 'positive' results.

How are you offsetting meeting emissions for travel, power, etc.?

We need more time to learn about this issue and then provide opinions. Daniel Malok

Hello Bette Jingyi Wu. How exactly did you assess the "normality" assumption? Thanks for clarifying.

Hi,

IV stands for independent variable, DV for dependent variable, MV for mediating variable, SE for standard error, LLCI and ULCI for lower and upper limits of the 95% confidence interval, respectively.

In the text, you might say something like: The independent variable (IV) significantly influenced both the mediating variable (MV; b = 0.50, p < .001) and the dependent variable (DV; b = 0.35, p < .001). The MV also significantly affected the DV (b = 0.25, p = .002).

Hope this helps.

Some of my thought:

In physics, theories about phase transition could give various non-integer exponents (see e.g. https://en.wikipedia.org/wiki/Ising_critical_exponents).

Sometimes, exponents could arise from specific type of ODE (e.g. https://en.wikipedia.org/wiki/Cauchy%E2%80%93Euler_equation). For example, I am working on one simple physics model and got a second-order ODE. One coefficient is an definite integral of some special function (I can only calculate it numerically). Because of this coefficient, the solution of ODE has non-integer exponents.

Hi Andreas Bittner !

Thank you for taking your time to answer my question!

I'm gonna try my best to make it work. Thanks again!

Another main argument against the learning value of memorization or its suitability as a basis or important element in a theory of learning is that it only concerns a late stage of learning, that is recall. This is a stage in the end of the sequence of sub stages such as assimilation, awareness of problem etc. But one of the arguments above questions this, although literature has not given attention to these objections that seek to upgrade memory phenomena in learning

Also, constructivist theories have seen to eliminate memory phenomena since they are at the other "ideological end" of the spectrum: pre-set knowledge vs constructively, actively constructed by students which is presumed to the sole path to involving higher mental states such as critical thinking, evaluaction, creativity which are basic aims in the realm of education

Dear friend Abdul Wahab

To calculate Parameters of the extended Antoine equation for pure compounds using ASPEN PLUS, you can use the following steps (How can I obtain Antoine coefficients (A, B and C) from Aspen Plus ....):

1. Open Aspen Plus and select a new simulation.

2. Select a property method and component list.

3. Add a component to the simulation by clicking on "Components" in the Data Browser and then clicking on "Add Component".

4. Enter the name of the component and its molecular weight.

5. Click on "Properties" in the Data Browser and then click on "Antoine Parameters".

6. Enter the Antoine parameters for your component in the appropriate fields.

7. Click on "OK" to save your changes.

You can also find Parameters Ci for the Extended Antoine Equations as PLXANT-1. You can transform to the Basic Antoine Equation by using the following formulae:

C1 = A Ln (10)

C2 = -B Ln (10)

C3 = C

I hope this helps!

Source:

(1) How can I obtain Antoine coefficients (A, B and C) from Aspen Plus .... https://www.researchgate.net/post/How_can_I_obtain_Antoine_coefficients_A_B_and_C_from_Aspen_Plus.

(2) Where do I get extended constants of PLXANT for water and carbon .... https://www.researchgate.net/post/Where_do_I_get_extended_constants_of_PLXANT_for_water_and_carbon_dioxide_for_an_ASPEN_program_I_am_running.

(3) Where does ASPEN Plus calculate the vapor pressure of compounds from .... https://www.researchgate.net/post/Where-does-ASPEN-Plus-calculate-the-vapor-pressure-of-compounds-from.

(4) Extended Antoine equation | ResearchGate. https://www.researchgate.net/post/Extended_Antoine_equation.

(5) Antoine Equation | SpringerLink. https://link.springer.com/referenceworkentry/10.1007/978-3-642-40872-4_26-1.

Sigfried Vanaverbeke You might look for libraries or code snippets with decent documentation and examples and determine whether they fit your requirements. Check to see if the code has been tested and confirmed by the community as well.

I believe the issue may be a model misfit . Model 59 in the PROCESS version 4 ,has an independant (X) ,dependant ( Y) and one mediating variable(M) . There is a moderating variable ( W) that is added to impact all three pathways . Your model with three mediators may not be Model 59.

Lian Smits Hello, this article may be helpful for your research. Best wishes. 😄

Qin, X., Yam, K. C., Chen, C., Li, W., & Dong, X. (2021). Talking about COVID-19 is positively associated with team cultural tightness: Implications for team deviance and creativity. Journal of Applied Psychology, 106(4), 530.

You can check out our YouTube Video on the topic https://youtu.be/zlHP6ovkbKw

Also, I like Sleep Junkies article on it :-) https://sleepjunkies.com/two-process-model/#:~:text=For%20the%20past%20few%20decades,the%20daily%20rhythm%20of%20sleep.

I recommended

Moldex3d

Hello Luis,

To the extent that adding a moderator to help explain more of the variance in variable B (by adding M and A*M as predictors of B), it is possible that you'd get different answers as to the mediation amounts for the C and D variables (e.g., coefficient products for b->c * c=>e and b->d * d->e) may well differ from what you found in the first study. For this reason, I'd include the full model (moderation and mediation portions).

Good luck with your work.

A moderator analysis is used to determine whether the relationship between two variables depends on (is moderated by) the value of a third variable. This relationship is commonly between:

1. A continuous dependent variable and continuous independent variable, which is modified by a dichotomous moderator variable;

2. A continuous dependent variable and continuous independent variable, which is modified by a polychromous moderator variable; or

3. A continuous dependent variable and continuous independent variable, which is modified by a continuous moderator variable. In this guide,

https://statistics.laerd.com/statistical-guides/types-of-variable.php#:~:text=Dichotomous%20variables%20are%20nominal%20variables,and%20also%20a%20nominal%20variable).

Stefan Poier Yes, a single-step test of the indirect effect with bootstrap CIs is what I would also recommend. MacKinnon et al. showed that this provides for the most powerful test. That's why I think path analysis with simultaneous estimation of all effects in a single model is the way to go. Nonetheless, I find the logic of the Baron and Kenny approach to still be worthwhile for beginners to think about in order to better understand what mediation actually is.

MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test mediation and other intervening variable effects. Psychological Methods, 7(1), 83-104.

MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39(1), 99-128.

Hello Yanchen,

after looking at Kenny's website, I assume his term "inconsistent mediation" is rather descriptively meant in that regard that you may have a positive indirect effect plus a negative (true) direct effect. If the direct and indirect effect are of equal but opposite sign, then both eliminate each other with the result that the overall relationship or total effect is zero (although an indirect effect exists). A comparable situation is when you have two mediators with opposite design.

Imagine the scenario in which you have a dummy predictor (broken leg, 0 [no] or 1 [yes]) and a single outcome "overall mood". Then imagine one mediator being "pain" and another being "getting attention". A broken leg has a positive effect on pain and pain has a negative effect on mood (=negative indirect effect). Likewise, a broken leg has a positive effect on "getting attention" which then positively affects mood (thus, a positive indirect effect). If both effects are equally strong, then the overall relationship between a broken leg and mood is zero. Beware however that this is no bias but still shows that things often have negative AND positive consequences which may counterbalance each other.

Now back to Kenny mentioning that this is like suppression. IF he simply sticks to the empirical phenomenon (without any causal explanation) of suppression--namely a zero overall effect but a negative direct effect, he is correct and this looks like inconsistent mediation. However, it is more important to consider (and THIS is the fundamental difference to inconsistent mediation) that the suppression scenerio incoporates wrong and biased effects (remember the term "true direct effect" above whereas in the incostent mediation, all effects are correct (ok we assume that for the sake of the argument). Suppression results from a causal structure in which NONE of the variables has any effect on the outcome but this strange behavior results from a sort of bias called "collider bias" in the causal inference literature. Recently, this paper solved the riddle and at least proposed two forms of causal structure that leads to the suppression scenerio (whereas all of psychology including Kenny) has failed for decades to really explain it.

Kim, Y. (2019). The causal structure of suppressor variables. Journal of Educational and Behavioral Statistics, 1076998619825679. doi:10.3102/1076998619825679

For most people this will be rather shocking, as for decades (as so often), people focused on the enhanced prediction results for the target predictor following the inclusion of the suppressor. In this regard, suppression was deemed a good thing. Enhanced prediction, yes, but no effect at all.

HTH

Holger

I could find a solution to this Problem: In the stoichiometric input tick CH4 but assign 0 as stoichiometric coefficient. CH4 will appear as "(N: CH4)" in the reaction equation. When using the option "Advanced" for kinetic input one can use N1 as variable name for the CH4 partial pressure.

ARIS

@ Murad Ali sir, Please do share your suggestions.

Haroon R Abbu Jack Cincotta Hey! I am doing the same thing now for my thesis, and I was wondering if you know what test family (z test, F test...) and what statistical test you used in GPower? Thanks!

Hi,

You can learn Aspen Plus dynamics from the following list:

1- Plantwide Dynamic Simulators in Chemical Processing and Control (2002) - Luyben

2- Distillation Design and Control Using Aspen Simulation (2013) - Luyben

3- Design and Control of Distillation Systems for Separating Azeotropes - Chapter 4 - Luyben

4- ASPEN PLUS - Chemical Engineering Applications - Chapter 15 - KAMAL I.M. AL-MALAH

5- Process Analysis and Simulation in Chemical Engineering - Chapter 8 - Ivan Dario Gil Chaves

Nice answer Mr. David Morse, Thanks. Your link is very good. Mr. Muhammad, follow this instruction.

Dear Johannes,

This reference is for a comparison and evaluation strategy, which includes a process model. Probably, it is not what you are looking for...

Tebes, G., Peppino, D., Becker, P., Papa, F., Rivera, M.B., Olsina, L. (2018). Family of Evaluation Strategies: A Practical Case for Comparing and Adopting Strengths. Journal of Computer Science & Technology, vol. 18, no. 1, pp. 48–60, https://doi.org/10.24215/16666038.18.e06

You can access it also at RG

these articles can be useful:

When selecting a perspective process model, there are some facts to be

Considered they are Scope of validity, the impact of the process, Degree of confidence

And tailorability of the process.

When considering a flash flood prediction system,

If the Scope is well defined so its Helps to define clear goals in order to reduce cycle time also improving code quality. So according to this system the goal would be give accurate prediction reports on time.

The impact of process- This reflects the weight that should be given to each context of the project. In here If the impact is not known then the prescriptive process will lead to unpredictable results. So this is very important part.

Degree of confidence- Effectiveness of this application to be deployed in different areas where floods can be occur.

The ability to modify when changes in requirements can is referred to Tailorable. It must be able to adapt the process described by the prescriptive model to specific goals of the project. In this system adding new databases ,data sets or new functions can be taken as examples.

Six Sigma can be characterized as a quality control technique that centers on dispensing with as numerous surrenders as conceivable. Six Sigma centers on the whole software process in guaranteeing quality. The essential thought behind this methodology is to move forward the quality by recognizing numerous abandons as conceivable. Six Sigma employments Define, Measure, Analyze, Progress, and Control (DMAIC) as an integral part of it. since Six sigma is applied to the whole prepare and is an approach that's based on minimizing the surrenders as much as conceivable, it may make inflexibility that in turn comes about in delays. Additionally , complicated strategies will result from this approach. Assist, since client fulfillment is concerned amazingly where anything not satisfactory by the client is considered as a deformity, the inner quality control measures that an organization utilize will be ruined.

Thank you Justin Nicholes Justin Nicholes , I already got an answer from Suzzane Rivard, former senior editor at MISQ theory and review. She was open to the idea of "narratives", and i used a combination of propositions and narratives (which is different from narrative style of the prose) to reflect all aspects of the theoretical contributions that I wish to present.

And interestingly I don't have any idea of your classification of theory purposes (tell a story, argue for position, combination). If you please share the article for this taxonomy/ typology I would be thankful.

The Unified Modeling Language (UML) is a general-purpose, developmental, modeling language in the field of software engineering that is intended to provide a standard way to visualize the design of a system.

The approach has the advantage of giving high level understanding of the system and the 'actors' who have investment in the system before writing a line of code. It slows development down! This can save development money and result in better end user satisfaction and less maintenance.

The basic characteristics required to select the process model are project type and associated risks, requirements of the project, and the users. One of the key features of selecting a process model is to understand the project in terms of size, complexity, funds available, and so on.

Dear Mr. Krajsic!

I searched for YOU resources that you may find valuable:

1) van Zelst, S.J., Buijs, J.C.A.M., Vázquez-Barreiros, B. et al. Repairing Alignments of Process Models. Bus Inf Syst Eng 62, 289–304 (2020). https://doi.org/10.1007/s12599-019-00601-7 Free access:

2) A case-study: M Adela Grando et al. (2021).Study of EHR-mediated workflows using ethnography and process mining methods Health Informatics Journal 1–14, Free access:

Yours sincerely, Bulcsu Szekely

How large are the groups you are comparing with each dummy variable?

Its quite important to get the BMP test done and after particular days we can also start testing the effluent or the slurry on daily basis to get the actual data too

Much chemical process modelling and/or simulation work can be done with the widely-used Microsoft’s Excel.

Application example ― Simulations carried in Excel 5.0 with Visual Basic for Applications (VBA) macros ― The recursive least squares algorithm (RLS) allows for (real-time) dynamical application of least squares regression to time series. Years ago, while investigating adaptive control and energetic optimization of aerobic fermenters, I have applied the RLS algorithm with forgetting factor (RLS-FF) to estimate the parameters from the KLa correlation, used to predict the O2 gas-liquid mass-transfer, while giving increased weight to most recent data. Estimates were improved by imposing sinusoidal disturbance to air flow and agitation speed (manipulated variables). The power dissipated by agitation was accessed by a torque meter. The proposed (adaptive) control algorithm compared favourably with PID. This investigation was reported at (MSc Thesis):

Your data seems totally ok, but your interpretation is flawed. The significant interaction only tells you that the slopes of your X variable change with changes in your moderator W. Since your exploratory effect of the interaction is very small (2%) I would not expect strong changes.

Additionally, the test of the conditional effects at different levels of the moderator does not compare the slopes with each other, but if each slope is different from zero. Therefore, the slopes may differ from each other but all not from zero. And again additionally, the values for the moderator to test the slopes are artificial (unless you specified it by yourself), in PROCESS 16th, 50th and 84th percentile, others use +/- 1 SD and in case of not symmetrical distributions, this will again change the results. As you can see, with increasing values of W the conditional effect switched from negative to positive values (therefore crossing zero, why they are close to zero and not significant) and has the largest value at W = 1,073. Imagine you would test W = 2.0 the slope would surely be significant.

Taken together, it is not a problem of the data, but the interpretation.

It is always possible to combine two models. I have no idea what "model 7" or "model 15" refers to.

We need the solar scheffler dish (CST) stand formula according to longitude and latitude from 8m² to 32m².

This example may be helpful:

Model Summary

R R-sq MSE F df1 df2 p

.4267 .1821 79.9939 32.0530 3.0000 432.0000 .0000

F(3,432) = 32.05, p <.001, R2 = .18 (all predictors to y)

Apparently better to run model 4 to test first for the mediation, and then run model 7 to test for the moderated mediation.

Hi Juyong Shin

Yes, I agree with the point of Rick Manner's response to the general concept of the multitubular reactor design. And for the modeling of such in Aspen HYSYS, you can PFR model, it has provision for the number of tubes present in the reactor.

So, PFR should be suitably model the MTReactor for you.

Kind regards

see:

there you find a diagram of the process.

also you can make a search on the process:

and patents:

No change helping you without seeing the WHOLE output(s). With a multicategorical X (5 groups?) you should have 12 indirect effects in model 58.

You can check and try to change the nonlinear solver or its parameter.

It is ok to distribute/publish your results even if you did not have the resources to replicate them. As long as you clearly explain that is what you are doing an use word like may and could to indicate the results have not been validated

You should consider only the total scores of the general variables considering the number of your sample, this can be done also in JAMOVI, you can also do it through AMOS that allows to estimate adjustment indexes of the SEM model to evaluate the general hypothesis of the theoretical model raised.

Different models serve not only as a frame for communication, they can help to rise problems as well as discuss them. Communication is not only transportation of messages, nowadays communication is more of sharing ideas and feelings and willingness to participate.

1. Aristotle Model of Communication

2. Shannon and Weaver’s Model of Communication

3. Berlo’s Model of Communication

4. Schramm’s Interactive Model of Communication

Shannon & Weaver’s and Scramm’s models as the key to succeed in intercultural communication by adding to the model the element of interpretation and confirmation of the feedback. Circulation from Schramm’s model gives us feedback, the interpreted decoding, which is the representation of the meaning received. However, confirmation of the feedback seems necessary to keep the communication ongoing and make sure that the message is understood as it was aimed.

Arjun Sankar S Defined Spec. for tower is incorrect so check these paramete in order to make the converging of the tower.

re-Check the parameters again and tell me what happened??

I agree with Prof Amara

This article explains everything

Ihope it helps

polymers or plasticity (Plastic Behaviour of Material)?

When your conceptual framework / research model developed is uniderpinning on previous theoretical framework means you should modify others' theoretical framework by adopting / adapting / add new constructs / variables to form your own / new conceptual framework / research model. When you do that, ensure you complete the following:

BPMN is the effective process modelling standard. There are some BPMN modelling tools that are open source or that have open source editions, such as:

ADONIS:Community Edition

ARIS Express

BeePMN

Bizagi Modeler

Camunda

Flowable

Imixs-Workflow

MID Innovator for Business Analysts

The full BPMN language can be unnecessarily complex. So you may want to use a subset, at least initially, to document processes.

There are other business process modelling approaches such as:

Flow Charting

Swim Lanes

Event Process Chain (EPC)

Value Chain

Unified Modelling Language (UML)

IDEF-0

LOVEM-E

SIPOC

Systems Dynamics

Value Stream Mapping

These might be worth exploring.

There are some notes I have written on the topic of BPM:

https://www.researchgate.net/publication/333486082_Introduction_to_Business_Process_Management https://www.researchgate.net/publication/333486171_Process_Oriented_Architecture https://www.researchgate.net/publication/333486169_RPA_Robotic_Process_Automation_POA_Process_Oriented_Architecture_And_BPM_Business_Process_Management https://www.researchgate.net/publication/333486176_BPM_Business_Process_Management_CRM_and_Cross-Functional_Enterprise-Level_Customer-Focussed_Business_Processes https://www.researchgate.net/publication/333486382_Business_Process_Analysis_and_Design_-_Importance_of_Having_a_Common_Language_Between_Business_and_IT

Dear Mr. Tiwari! This question is very interesting and relevant - so I looked up resources to support you in your work:

1) BRF (2019)."Industry 4.0: how will the new industrial revolution affect the Food Industry" Monday June 24th, 2019.Available at: https://blog.brfingredients.com/en/industry-4-0-food-industry/

2)John de Yonge (2019)."Why your next big bet should be in food innovation" Ernst & Young Global Limited . Available at: https://www.ey.com/en_us/innovation/how-innovation-can-change-the-future-of-food

3) Noor Zafira Noor Hasnan & Yuzainee Md Yusoff (2018). "Short review: Application Areas of Industry 4.0 Technologies in Food Processing Sector", Conference: 2018 IEEE Student Conference on Research and Development (SCOReD) , Available at:

Please see also the document enclosed. Yours sincerely, Bulcsu Szekely

Check if our papers help you:

If I am employing moderation in secondary time series analysis can I need to proceed with the methodology of time series?

I need some liturature regarding its methodology

Actually my all variables (quantitative) are of mixed order can I still procedd with ARDL approach irrespective of moderation analysis?

If someone guide me / suggest some relavent stuff I shall be very grateful for this favor.

This can be calculated using expert choice

Use mean scores when you are conducting a quantitative research using parametric statistics with metric data (Interval / ratio). Use sum of scores when you are using non-parametric statistics with non-metric data like ordinal etc.

I understand projectification as the process of developing a company from traditional to project-based organizational forms. How this process is structured depends on what the starting point for the process is. In his older, but widely quoted paper,

Christophe Midler described four phases of project identification:

- Functional organization and informal project coordination

- Centralized project coordination

- Empowerment and autonomy of the project management structure

- Transforming the permanent processes of the firm

In addition, Midler describes the need for change (e.g. changes in the relationship, changes in tools, changes in career management). In my opinion, these points can be a starting point for your design of the main components of a Projectification process model.

You can download the article from www.sciencedirect.com/science/

yes that's correct

Yes, it is a very large market in any region of the world, initially in the food area and currently already being seen also in the cosmetic. Developed initially for the Islamic community, but is spreading rapidly due to good production and marketing practices.

You are hypothesizing three interactions effects, one for each combination of an IV and the moderator. That should be straightforward with PROCESS.

Why would anyone want to turn ethanol - a valuable trasportation fuel in syngas - CO + H2 waiting t be turned into something more valueable - like ethanol.

FileMaker produces data flow diagrams directly.

Eliseu Gonçalves Sergio Dias Silva