I am conducting a usability study of medical content delivery systems and I was planning to use some heuristics present in a CHI paper for my Heuristic evaluation.However since the area of focus is slightly different from the paper,I am not sure if all the heuristics are applicable and whether I should use them as a guideline.
How would you handle such a situation,would you create your own heuristics or use an existing one and adapt it to suit your process ?
Thanks
You would be wise to use some sort of existing heuristics, such as the paper you are planning to use, then append your own specific rules/guidelines to it.
You'll notice I did not say 'modify'.
A good heuristic evaluation is always tailored for a specific project needs. Use the paper as a start point. Learn the heuristics from it. Adapt the heuristics as much as needed to your domain/project. You also should take into account other classic heuristic evaluation templates, such as http://en.wikipedia.org/wiki/Heuristic_evaluation#Nielsen.27s_heuristics.
Related
I'm looking for a library to help me solve a constraint based logic problem where I need to schedule a number of different events of varying duration. The events have different attributes associated with them and my main issue is that I need to encode "preferences" based on these attributes. These preferences aren't hard constraints, but I would like to maximise how well they are satisfied in the solution. There are also different preferences of competing priorities.
I've taken a look at a few constraint solvers (Sat4j, clasp, Glucose, GlueMiniSat, etc.) but from what I've seen they all seem to only deal with fixed constraints, and setting up preferences would be non-trivial.
I don't care too much about what technology/language it's in - I'm happy to write a wrapper around it.
Absolutely, Choco Solver is a powerful Java constraint solver that is often used for scheduling and planning.
Let's take the following example:
"it would be nice if x = 10"
You can encode preferences in different ways.
1) through variables and constraints.
1.1) reify the constraint with a binary variables
ICF.arithm(x,"=",10).reifyWith(b);
it basically means b = 1 <=> x = 10 (so the constraint may or may not be satisfied), then you can maximise b (possibly with a weight)
1.2) through gap variables
solver.post(ICF.arithm(x,'-',gap,"=",10);
then you can minimise the absolute value of gap (possibly with a weight)
to the constraint.
2) through search : when solving the problem ask the search strategy to try x=10 before trying another value. There is not optimality proof but it works quite well in practice.
Hope this help. Please feel free to contact us for more support on Choco Solver www.cosling.com
best,
I think OptaPlanner is a tool that can help you to solve this problem, check this:
OptaPlanner is a constraint satisfaction solver. It optimizes business
resource planning. Every organization faces scheduling puzzles: assign
a limited set of constrained resources (employees, assets, time and
money) to provide products or services to customers. OptaPlanner
optimizes such planning problems to do more business with less
resources. Use cases include Vehicle Routing, Employee Rostering, Job
Scheduling, Bin Packing and many more.
OptaPlanner is a lightweight, embeddable planning engine. It enables
normal Java™ programmers to solve optimization problems efficiently.
Constraints apply on plain domain objects and can reuse existing code.
There’s no need to input difficult mathematical equations. Under the
hood, OptaPlanner combines sophisticated optimization heuristics and
metaheuristics (such as Tabu Search, Simulated Annealing and Late
Acceptance) with very efficient score calculation.
OptaPlanner is open source software, released under the Apache
Software License. It is written in 100% pure Java™, runs on any JVM
and is available in the Maven Central repository too.
Source:
http://www.optaplanner.org/
It's part of Drools, which has another interesting tools:
http://www.drools.org/
Another actively-maintained library is "choco-solver".
website
github
Another alternative is the Gecode Toolkit. It is an open-source and modern Constraint Programming Solver.
Is it possible for a generalisation in UML to be implemented in Simatic SCL code (or Structured text code)?
The definition of a Generalisation in UML:
A generalisation is a relationship between a morew general classifier and a
more specific classifier. Each Instance of the specific classifier is also an
indirect instance of the general clasifier. Thus, the specific classifier
inherits the features of the more general classifier.
Features specified for instances of the general classifier are implicitly
specified for instances of the specific classifier. Any constraint applying
to instances of the general classifier also applies to instances of the
specific classifier.
In general the answer to this is no, not really. All means of programming PLCs (ladder, ST, FBD, etc) are generally only very lightly abstracted from the actual machine code. They are closer to assembly wrappers than to anything we would think of as a modern development language. Structured Text is closer to very primitive Pascal - it lacks most any sort of object oriented features.
The notion is that PLCs and PLC programmers have long since been used to an approach of extreme micromanagement when it comes to developing programs for them. The reasons for this are many - some more valid than others. Scott Whitlock wrote a good bit here outlining some of those reasons. A big one is that maintenance guys on the factory floor are often the ones trying to troubleshoot the machines and having clear, non-abstract, state-machine information available to them is much more valuable than the need for an elegant, minimal formulation to stroke the ego of the system developer.
PLC programming is a ruthlessly practical industry. If you have the choice between something 10% more practical and something 90% more elegant, the practical solution will always win.
With that said - there are some who are playing in this area. I suggest a quick read of this article for some examples of trying to make ST work a bit like you are suggesting. Still, I would be cautious before putting anything like this to work in a real factory with real machines that need to be both safe and reliably making money.
Is there a package or methodology in existence for the detection of flawed logical arguments in text?
I was hoping for something that would work for text that is not written in an academic setting (such as a logic class). It might be a stretch but I would like something that can identify where logic is trying to be used and identify the logical error. A possible use for this would be marking errors in editorial articles.
I don't need anything that is polished. I wouldn't mind working to develop something either so I'm really looking for what's out there in the wild now.
That's a difficult problem, because you'll have to map natural language to some logical representation, and deal with ambiguity in the process.
Attempto Project may be interesting for you. It has several tools that you can try online. In particular, RACE may be doing something you wanted to do. It checks for consistency on the given assertions. But the bigger issue here is in transforming them to logical forms.
For an onology of logical axioms, OpenCyc and the commercial full Cyc ontologies might be worth investigating as well. CycML is used as a language to model the logical assertions, and the Cyc engine is capable of logical inference. The source for OpenCyc can be found in the OpenCyc SourceForge project. The Cyc Wikipedia page also has great information.
Yes, this is a very nasty problem. I would suggest you try to focus in on a narrow domain. For example, if you are looking for logic errors in cancer determination, you have to focus on which type of cancer as well as what are you trying to resolve eg: correct treatment plans, correct observations, correct procedures, correct stage determination, etc. Then you have to find the taxonomy or ontology for that specific cancer, eg: Medline. So for example, you will likely have to focus in on ONLY lung cancer and then only a subset of lung cancer types and only observations indicating lung cancer. Then you will have identify your corpus, knowledge trees, entity relationships and then worry about negation detection, hypotheticals and subject detection. If Healthcare doesn float your boat, I hear another challenging domain for logic errors is the legal/law industry.
I am looking for insight on modeling. I had a intro course on Design Patterns and basic class diagrams, sequence diagrams, and use cases.
The class diagrams I have found invaluable as a tool of organization in my programming. The use cases are moderately useful so far.
This semester I am in a class going into UML in much more depth i.e. Domain Analysis, Requirements Analysis, Software Design vs. Software Engineering etc.
There is a certain feeling that this is starting to be more voodoo-sciencey or non-concrete when we start trying to be precise with the ambiguities in scenarios, and changing requirements. Is UML past basic class diagrams and use-case diagrams practically useful in productivity in most applications?
It started out voodoo. Diagramming software designs has always been that way. It is a way of showing in pictures what you want to say about the design in a human language. If it was precise enough to generate code from, we'd go ahead and do that and dispense with the coding step altogether.
The only thing UML brings new to the older ways is that it is a standard. Even then, there are so many different kinds of "standard" diagrams that I have to snicker a little when calling it a standard.
However, the activity of design itself is extremely important for all but the most trivial of tasks. The question is whether you are going to spend some time up-front designing your system, or if you are going to do it on-the-fly, after having written a great deal of wrong or unnesscary code. If you want things done quickly and/or well, you do some design up front.
This doesn't just apply to writing software BTW. It is an inherent part of any complex creative activity. My father-in-law, a retired English teacher who writes his children longish postcards when he goes on vacation, actually writes outlines for his postcard messages. Most master painters and sculptors make test drawings first.
No.
All sorts and forms of documentation, are only useful as a means of communication. Documentation for documentations sake is a complete waste of time.
Writing UML is useful and productive only when it comes with a document that explains (in words) what is it you want, why, and how. only then UML can help to illustrate what you are trying to say in the document.
Software teams that produce endless amounts of UML just for the sake of drawing squares, are just wasting time.
You started out with modeling, which is a great thing to do, especially in computer science - you model all the time. Keep in mind UML is a standard for a modeling notation for software systems, nothing more (e.g. it is not an analysis or design methodology) and nothing less (e.g. it is not a way for developers to look productive by drawing nonsense).
You are on the right track, always keep in mind what is actually useful and gives you some value. This is not exactly relevant to your question, but sue cases are not use case diagrams, there are much more, have written form and might help you with much of what you described would be in your next course.
As to your concern, modeling is about abstracting from unimportant details, so some ambiguities might occour. The point is they should be unimportant for the purpose of modeling. For example it does not really matter if you include all the properties of your classes if you want to show the structure of design, e.g. use of some pattern. You can also use public properties without concerning yourself if they are private fields with getters and setters (Java), properties (C#) or generated object methods using metaprogramming (Ruby). The same holds for scenarios captured using use cases - of course you cannot (and should not try to) capture alternative branches using UML, but you can describe the conditions in use case descriptions just enough to avoid ambiguity without having to develop the system first and finding it is wrong afterwards.
As to the voodoo stuff - the problem is that UML is large and so many developers don't know how to use it right and often create more mess than value. Don't be confused by general disrespect for UML, the problem is in tool vendors, commitees and lazy developers... Behind many concepts in UML are well known formal models backed by academic science work, e.g. the state diagrams come from Harel statecharts (http://linkinghub.elsevier.com/retrieve/pii/0167642387900359). So my opinion it is not as much voodoo in principle, it is just oversold with tools not supporting the standard and also the standard tries to be and combine everything (it is an unified language...), however this slowly improves.
My advice for you would be try to learn what is important - those formalisms, analysis and design methods, try them practically and decide for yourself what is useful. If for no other reason, learn UML because it is the language for analysis and design, although large, it is still better than its ~50 predecessors combined:).
From my experience: Not really.
I never came across a really useful sequence diagram. Sequence diagrams stop being useful when the documented process becomes too complex, as you have a hard time following all the lines. But to understand a trivial process, I don't need a sequence diagram. When used as a design tool you will waste a ridiculous amount of time adjusting the diagrams, cussing MS Visio or whatever you use.
The notation however can be useful for a small snapshot when discussing something on a whiteboard. But this is valid for any notation style; UML is just well established, increasing the chances you are understood correctly.
Class diagrams are useful, both in design and in a posteriori documentation. But IMHO you shouldn't be too pedantic about them.
Not in MHO. It's completely superfluous as far as I am concerned.
I'm trying to find best free expert system, with the highest functionality.
I know about CLIPS, but is there another system, for example being able to accept percent of confidence for each rule (fuzzy logic). I need it to know will I be able to do fast a short project using expert system, with highest functionality.
But anyways, it's interesting is there an open source program that aims to gather different AI methods (whitch there are plenty of), and use them together.
So I would be extremely thankeful for any info about more robust CLIPS, or similar programs.
Thanks!
When you say "highest functionality", it isn't exactly clear what you are looking for. CLIPS is a very good and very stable forward chaining inference engine. If you are looking for a rule based system with a different feature set, you would need to specify the features that you are looking for.
If you are looking for hybrids that do both rule-based and fuzzy, you might want to look at FuzzyCLIPS or FuzzyJ.
Another interesting (commercial) hybrid is MindBox's ARTEnterprise which does both rules based and CBR.