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Ubiquitous Computing - Science topic

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I was wondering if someone could clearly define these two terms.
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The National Institute of Standards and Technology (NIST) in (The National Institute of Standards and Technology (NIST), 2011) gives a basic and direct definition for cloud computing (CC) as:
a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction”.
Additionally, some researchers address this technology with the Internet of Everything (IoE) to give more emphasize on the Internet-enabled smart objects and their ubiquitous existence.
Furthermore, you can also refer to my modern paper which contains complete and detailed information:
Nidhal Kamel Taha El-Omari , “Cloud IoT as a Crucial Enabler: a Survey and Taxonomy”, Modern Applied Science, The Canadian Center of Science and Education, published by Canadian Center of Science and Education, Canada, p-ISSN: 1913-1844, e-ISSN: 1913-1852, DOI:10.5539/mas.v13n8p86, 13(8):86-149, 2019.
Or simply you can click here:
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Affective technologies are the interfaces concerning the emotional artificial intelligence branch known as affective computing (Picard, 1997). Applications such as facial emotion recognition technologies, wearables that can measure your emotional and internal states, social robots interacting with the user by extracting and perhaps generating emotions, voice assistants that can detect your emotional states through modalities such as voice pitch and frequency and so on...
Since these technologies are relatively invasive to our private sphere (feelings), I am trying to find influencing factors that might enhance user acceptance of these types of technologies in everyday life (I am measuring the effects with the TAM). Factors such as trust and privacy might be very obvious, but moderating factors such as gender and age are also very interesting. Furthermore, I need relevant literature which I can ground my work on since I am writing a literature review on this topic.
I am thankful for any kind of help!
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Affective technologies like social robots must answer appropriately according to context. For example, if the goal is build empathy (towards human acceptance), social robot must imitate the affect state of humans. In any way, affective technologies need recognize humans emotions first. In this context, we development this paper:
I hope it will be useful
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Hello,
Any one can help with explanation about the difference between Ambient learning and context-aware ubiquitous learning?
Best Regards,
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All my greeting for your response and for the document. I do understand. Ines.
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Interested on collaborative research in the field of Trust and Security in emerging and ubiquitous Computing
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Seeking association for Trust Management and Security Projects. Consider Workshop as a part of projects
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The Fourth Industrial Revolution is the next generation of industry based cyber-physical systems, such as artificial intelligence, robotics, augmented reality, IoT, 3-D printing, nanotechnology, biotechnology, etc. 
How could you image the classroom of the future?
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Good question. Remember, 4IR is about digitised dynamical systems. That is, things and people interconnected, digitised and fast-moving. So, the education system must emphasize analytics and appreciate sociology. Call it interdisciplinarity.
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Some researchers confuse IoT and ubiquitous computing, Is there a clear difference between these terms? What's the role and impact of context-awareness in both fields?
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Ubiquitous computing is all about having computational capability in many different (perhaps all) objects in our environment. Things like stoves Fridges, TV, Cars etc all having some computational power. . The Internet of Things (IoT) is about having these objects in our environment all connected to an internet.
Where these objects are connected to the internet it becomes IoT .
These terms can be used interchangeably when the everyday objects in our environment have the computational power resulting in that being called Ubiquitous Computing and these objects with the computational power being connected to the internet resulting in that equally being called The Internet of things.
I hope you find this helpful.
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I am currently diving into the sea of open-source project for SPH flow simulation. The two candidates I have come across are DualSPHysics and LAMMPS. Both are open-source and have a certain degree of user-modifiable codes. However, I wonder as I go along with my project (I have only spent a couple of hours playing with each of them), which one will be easier for me to handle? In terms of robustness and code sharing (for reproducibility in the future.) 
People who have experience with both packages, may I ask for some insight views? 
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Hi Quang,
Do you have any insight now? Please let me know if you have since I am trying to dive in it too.
Thanks,
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I've developed some new metrics that attempt to gauge the effectiveness of different analytic methods (especially in their ability to discover new findings) and now want to do a more complete literature search. Does anyone have some recommendations for good articles on the development of new metrics for evaluating the effectiveness or power of different analytic/mathematical methods to discover new patterns or relationships?
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Hi Thomas and Chris, First, thank you both for your responses.  Thomas is on the right track when he says that I am looking for more than comparing the performance of learning algorithms per se. Rather I am looking at the ability of an algorithm to discover relationships/patterns of interest. Of course, the most work on such discovery or 'finding ability' is on the comparison of  learning algorithms or pattern recognition algorithms.  Thomas, I found your comment on the gini-index intriguing and I'll follow that path. I am excited about some of this new work - the purpose of the question as I stated was to see if I could add to the current literature review in an upcoming publication.  When that is done, I will gladly send you a copy and we can discuss in depth the approach I have taken.
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IoT simulation in networked manufacturing for ubiquitous approch
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Hello,
Thinskpseak (https://thingspeak.com/) of MATLAB is a very suitable tool for IoT experimentation. Devices such as Arduino, XBee etc. can be easily connected. You can run Thinkspeak in localhost (https://github.com/iobridge/thingspeak) and can be integrated with MATLAB for analytics.
Some blogs-
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I am working in IoT with Hierarchical Cloud (Edge Computing). I have designed some framework intuitively. For results, should I go for "Simulation" or "Practical Implementation"? Also answer WHY and HOW?
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Even I have also started working on edge computing related project. I feel simulation is better initiative rather than real implmentation for such complex system. I have read about the suitability of iFogSim (https://arxiv.org/abs/1606.02007) and need to be explored more. You can try this.
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 I am trying to find the IoT term definition for my research. It seems that it is good opportunity to ask this question once more. In most cases I know the term IoT/IIoT can be replaced by SCADA (Supervisory Control an Data Acquisition) , ICT (Information and Communication Technology) and the text still will be perfectly OK.
Do you think the box (or even pack) of cigarettes could be the “thing”. It has a barcode, so it is the source of data. Is it the sensor - no because in this case the barcode reader (industrial scanner) is the “sensor”. Can we recognize the bar code reader as the “thing” – the answer is not if the goal is to provide GLOBAL cigarettes tracking system. The same applies to drags for example. Is it IoT/IIoT solution - my answer is YES no doubts - it is vital for selected industries.
Is the "thing" smart - I don't think we can call the bar code something smart. The most interesting observation is that we can recognize this case as the IoT solution, but we have not mentioned Internet, wireless, etc.  at all, but only that we have important mobile data and the solution is globally scoped.
Let’s now replace the word GLOBAL by LOCAL (for example cash desks farm in the shop) and the same application is no longer IoT deployment , isn’t it? It is true even if the cash desks are interconnected using IP protocol !
My point is that a good term definition is important to work together on: common rules, architecture, solutions, requirements, capabilities, limitations, etc. The keyword in the previous sentence is COMMON.  Importance of the sensor and data  robustness requirement could be applicable to many applications, e.g. controlling an airplane engine during flight. The same engine could be monitored and tracked after landing in any airport using local WIFI by uploading archival data to a central advanced analytics system. Is it IIoT?  During the flight it isn't, but the solution is life sensitive. After landing it is IIoT, but the reliability of the data and data transfer is not so important, isn't it.
My concern is that your definition  provides pretty good description of the Universe, but working on engineering standards is like carving on the stone - it is one way ticket. To buy one way ticket you must be sure where you are going. 
To be constructive my proposal for the definition is as follows:
Try it against the above example.
In the above proposal the open question is: what is the "mobile data", but I believe that the definition is much closer to the final expectation.  To answer this question I propose this approach:  Data is Data It Doesn’t Matter Where It Comes From!
For implementation of this concept we can use Object Oriented Internet paradigms coved by the:
The only missing thing is how to use these building blocks to make the consistent IoT puzzle (deployment domain). In this case a sponsor is needed to scope globally  the outcome. 
I believe that finally this way we will get good starting point for the further standardization.
Let me know how this scenario works for you.
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I have a definition according to ITU-T in
IoT –  Internet of Things (Page 4)
Best regards
Anatol Badach
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Dan Chalmers has an excellent paper about Pervasive Computing courses, but I'm interested in listen from other professors what they think is harder to teach.
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I took a look at Aware; it will fit very well in my course. Thanks. Regarding the tool of my student (Joelma Peixoto), it will be a free tool for educational purposes, and this time with a good description/version in English ;).
When she has done the work, I will send you a link to evaluate the tool. Regards!
Ps: Could you please answer a short questionnaire for us? Joelma has elaborated it for her requirement elicitation process.
Ps2: I have attached to English papers about LoCCAM
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SensorML is a markup language developed for open geographical information systems. There are java libraries, XSchema definitions for validation, OWL support for semantic reasoning. WHen I did a quick browse through it, then it seems as if it is possible to
  • define self-describing sensors
  • define processing (from source to recipient)
  • and much more
To me, this standard seems to be a real contender for interoperability issues in ubiquitous computing, ambient computing and internet of things. So, have you applied it? What is you experience? What are the advantages and disadvantes? Concerning interoperability, are there any real competitors? 
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I am diving into the implications of ubiquitous computing on the future of learning.
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I am curious: are we assuming that ubiquitous computing is inherently beneficial to the learning process? To all learning processes, regardless of subject?
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Could ubiquitous learning improve learner performance ?
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Yes, I think that the ubiquitous learning is a good form to support and motivate student learning.
Complementing the indications of Fabricio and Duam, there are many works with positive results, e.g.:
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I am working on a project where a statistical estimator (ACE, abundance-based coverage estimation) is used. This estimator is like a function, which maps a set of samples to a single real value. I need to evaluate the performace of this estimator without groundtruth。
I want to evaluate it by LOOCV. If the variance of results from LOOCV is small,  which implies that one less sample won't affect the estimation, then I think the perforamce of the estimatior is good.
I have been trying to search relevant papers but still fail to know how other people handle the evaluation problem without groud truth and wheter LOOCV can be used in this way.
Any suggestions? :)
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Depending on what level of description that you want, I think http://www-bcf.usc.edu/~gareth/ISL/ provides an excellent introduction to LOOCV (and other CV) for non-statisticians. And it is freely available to download from that url.
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Knowing that in real-world ubiquitous learning, learning strategies are different from the e-learning ones, did learner's needs, preferences and their descriptions evolve with u-environments?
Many thanks
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Salem/Hi
ubiquity -> omnipresence: anywhere and anytime. Detect needs of a learner based on its characteristics: learning model, types of intelligence, navigation traces, emotion, intention, fatigue, perseverance, ... but also from the traces of others.
If only one student did not understand, simply bring the concept to him by another example. But if most learners do not understand, we must change the pedagogical approach ... Similarly, if the majority were tired, those who prefer to continue are also tired, but they try to resist fatique
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I am finding the core security issues in Openmoko open source Operating System for Ubiquitous Computing...
Would you please help me to find out some security management issues in Openmoko regarding Ubiquitous Computing.
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Thanks Herrb. 
I am talking about Openmoko Linux. What are the other core issues in respect of Ubiquitous Computer. Would you please help me to find theses issues?
Regards
Imran 
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I am reviewing this area and would like some feedback from researchers working in related projects.
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From my perspective, working in a related field, the most important question is why you need emotion sensing systems? If the answer is because you want to improve health, then that is the challenge, not the sensing systems as systems, but the success of the health improving interventions. And then the challenge become, how one create good health interventions, how do one stop the destructive behavior and motivate the health improving behavior. Here I think social and cultural aspects, long time behavior and learning/mastery curves is important.
What cultural and social values do the system promote and reproduce?
How do one maintain the health improving behavior over time?
How do one create good and challenging learning and mastery experiences (curves) over time?
In our project RHYME we create multi-sensory Internet of Things (interactive MSE) to motivate social and aesthetic co-creation for children with severe disabilities and their families. Here we use musical improvisation (advanced musical algorithms) and sensory stimulation to motivate social co-creation (positive and equal creative behavior that promote both aesthetical experiences and musical mastery). 
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Components are units of composition and reuse, and as such they are carriers of a piece of functionality that can be utilized in fulfilling operational demands for systems. In the literature, various types of analogue and digital hardware components, system, application and utility software components, as well as cyberware (information and knowledge structure) components are discussed. However, it is very difficult to find publications in which comprehensive taxonomies or classifications of these are proposed or applied. Are you aware of any general taxonomy or classification schemes of hardware, software and/or cyberware components, no matter if they are off-the-shelf or custom-developed components? Are there any standards or specifications in these fields?
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Doug Bowman has done a lot of work over the years in defining taxonomies - especially for 3DUI. See: http://people.cs.vt.edu/~bowman/3dui.org/course_notes/siggraph2001/evaluation.pdf . At the moment I can't quite point you to a taxonomy of hardware or software.
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What are the main differences between both context and situation awareness ?
What can Activity theory offer to model situation/context ?
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You can also have a look at Alcaraz and Lopez, who discuss the differentiation between situation awareness and context awareness:
Alcaraz, C., Lopez, J. (2013) Wide-area situation awareness for critical infrastruture protection. Computer 46(4). pp 30-37
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Ubiquitous computing emerged at the beginning of the 1980s. Its main assumption is that computing can be available anywhere, anytime and any context and in anything due to technological developments, new affordances, and societal demand. This idea has been introduced and exploited successfully in many application fields over the years. However, my impression is that ubiquitous computing has so far had only a rather limited impact on computer aided design. Though many researchers studied the affordances and the possible applications of ubiquitous technologies, it would be contra-factual to claim that ubiquitous computing has managed to revolutionize either the methodologies, or the tools and systems of computer-aided design. As the related literature exemplifies it, certain new functionalities and novel tools have been developed by researchers at the academia, but they have not been integrated into commercial systems and industrial best practices. What is your opinion? How has ubiquitous computing influenced the development of CAD systems, tools, and methods? What new functionalities can still be expected?
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Per se is "Ubiquitous computing" a collection of properties which say,e.g., that Ubiquitous Computing means that the computer disappears form view but is available 7/24.
In contrast, the application areas mentioned in the question are at a first glance independent of a Ubiquitous Computing implementation, which could be done, e.g., by Wearable/Mobile Computing.
I doubt that Smartphone screens would be appropriate to present CAD Designs.
In the best case some functions of the application areas in question could also be executed on Wearable Computers/Smartphones. Therefore, I do not see a revolution of, e.g., CAD methodologies by Ubiqutous Computing.
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Is there some recent study of forms and tools of context-aware information retrieval? In ubiquitous systems, ontologies are widely used to represent context information, and information retrieval is a highly complex task, because the heterogeneity of sources and devices.
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Hi,
I don’t know if this is interesting for you: the “Lexicon of Arguments” is a platform where scholarly controversies are displayed and searchable. In particular you can search “VsName” or “NameVs” to find counter arguments from the literature.
Here is a short demo
Spanish demo:
The dimension of “Scientific Camps” helps understand why a certain concept is not mentioned at all – and which other concept might be used instead.
Here is the SRU-interface:
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SensorML is a standard for specifying sensor data processing, e.g., information fusion, sensor fusion, data fusion. In http://www.opengeospatial.org/, they are working on SensorML (as well as TransducerML).
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Hello Jonas Mellin,
here i have added some information based WSN's, Please go through these point it may helps you,
Monitoring health care system
The main features of a monitoring system that integrates the HCCAC (Health Care Context-Aware Computing) architecture and wireless sensor networks and is aimed at improving healthcare of dependent people. The HCCAC system is based on a multi-agent architecture that is comprised of various types of intelligent agents. The primary agent in HCCAC is the Interpreter Agent, which is integrated into the system. The purpose of this agent is to provide solutions for the well being of the user through the use of action plans based on the information provided by the WSN sensors.
The most important characteristics of the system are:
(i) the Interpreter Agent has reasoning capability; it can analyze and reason the context data gathered by the system and provide proactive solutions,
(ii) the Interpreter Agent can easily adapt to the context within which it acts,
(iii) gather sensor data and messages from other agents in order to provide efficient solutions and
(iv) the Interpreter Agent performs a data fusion with the information received.
The system uses several WSNs in order to automatically gather context information. Based on the data received by the WSNs, the Interpreter agent fuses, evaluates and reasons the data in order to develop action plans and initiate events that affect the sensors that are also connected in the WSNs.
and please go through herewith the attached file.
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The research and growth in mobile, ubiquitous and pervasive computing is occurring at an unprecedented rate. With the emergence of commodity wearable computers such as Google Glass, Recon Jet, etc., and with VLSI and SSD memory apparently exceeding Moore's predictions, where does this leave us by 2020? What will contextually-aware apps do? Will the synergy between ubiquitous computing, machine learning, adaptive systems and HCI reach a singularity where apps that actually pass the Turing Test will be commonplace? What do you think?
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The IOT, big data, and ubiquitous computing will I predict introduce untold complexity, as humans respond to immersion in situations of actual or possible ubiquitous monitoring with real time data analysis across real and cyber worlds. One vision is that humans may attempt to adapt and learn responses and controls, perhaps even focusing on engineering bio and profiling outputs readable by sensors. There may be an increased movement to switch off or seek invisibility as privacy becomes a more desirable and less accessible attribute. Data destruction or disruption may be an optional feature. Generic 'types' of identities based on similar groups of people may be preferred by users rather than personalization. Technologies that could allow humans to negotiate and have visibility to control and monitor their own attention, interactions, preferences and predictive patterns in the sea of technologies and networks will be in demand I think. Context aware apps may be device independent, with users flipping identities for different aspects of interactions in different situations. New challenges will be for trustworthy reliable technologies adapt at negotiating control and autonomy between individuals, communities and environments. Energy harvesting will be huge.
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Mobile learning technology strategies across educational institutions are not unilateral. A review of the strategies shows diverse information and requirements. Please take 5 minutes to complete this survey in support of mobile strategy research.
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Interesting question! I've found at my institution that mobile learning happens in spite of institutional policy and lack of support.
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In classroom environments, teachers or lecturers may decide to conduct tests or examinations for students. What are some of the challenges that can be encountered while applying ubiquitous computing devices to classroom environments?
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In my view, the most challenging issue that arises when applying ubiquitous computing devices to classroom environments is the design of the interaction. More specifically, the design of feedback on the students' work. Hattie (2009) identifies feedback as the most effective single variable in the design of learning environments. My PhD thesis (The potential of a classroom network to support teacher feedback : a study in statistics education; http://irs.ub.rug.nl/ppn/343084066 ) was on this issue.
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As an advanced computing paradigm, pervasive computing has numerous benefits. How can pervasive computing be applied to classroom environments, especially in enhancing learning and promoting well-being of students?
Good answers will be really appreciated.
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Take a look at recent works about u-learning. The mais objective of this area is to bring technologies provided by ubiquitous computing to actual learning scenarios. I made some works in this area, and in my opinion there is a "gap" between the technologies and learning techniques.
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I'm looking for a journal to submit my paper which is about modeling context-aware systems
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Depending on the approach of the paper could be: International Journal of Advanced Studies in Computers, Science and Engineering or International Journal of Pervasive Computing and Communications or the Journal of Universal Computer Science.
If the approach is more of a interaction model it could be the International Journal of Human-Computer Interaction.
I know most of these journals are too broad themed but i've seen many papers on ubiquitous computing published there.
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I am just at starting phase in this field, so any kind of guidance will be welcomed.
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You might want to take a look at DiaSim. It is a smart home/office simulator.
DiaSim is, in turn, based on context simulator Siafu. Siafu looks abandoned, but still might be of use to you.
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I will be excited actually to collect and read the most controversial papers about the ubiquitous and pervasive computing fields. I am sure that there are a lot of interesting material to read but of course collecting a refined reading list (more or less) is not that easy for one researcher, this should be driven by the community for richer content. Such material could be also used I think by others and more importantly for a hot discussion at the ubiquitous seminars.
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Here is another nice online article 5 under the title "Things About Ubiquitous Computing That Make Me Nervous" by Anne Galloway,
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What I have seen until now is that these two concepts have mixed with some recent concepts such as Ambient Intelligence and have converged into something fuzzy. People use both concepts synonymously now.
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Hi Ali,
Those terms are interchangeable in many sides in the way the community deals with them. Recently, the most popular conferences in those two areas, Pervasive and Ubicomp, are joined with each other starting from 2013 and the joined conference "UbiComp" will be held in Zurich.
They both refer to the growing trend towards embedding technology in everyday objects so they can communicate information.  The words pervasive and ubiquitous mean "existing everywhere." Pervasive computing devices are completely connected and constantly available. 
I should also point that in his work (Lyytinen, 2003) made a major distinguish between those two concepts by comparing both in terms on mobility and embeddedness. In his work, both pervasive and ubiquitous computing are of high embeddedness but ubiquitous has a higher mobility.