Enabling Programmable Ubiquitous Computing Environments

2009 ◽  
pp. 2708-2734
Author(s):  
Christine Julien ◽  
Sanem Kabadayi
Keyword(s):  
Pervasive Computing ◽  
Local Environment ◽  
Physical World ◽  
Application Development ◽  
Local Data ◽  
Domain Experts ◽  
Domain Specific ◽  
Programming Abstractions ◽  
Rapid Deployment ◽  
Programming Interface

Emerging pervasive computing scenarios involve client applications that dynamically collect information directly from the local environment. The sophisticated distribution and dynamics involved in these applications place an increased burden on developers that create applications for these environments. The heightened desire for rapid deployment of a wide variety of pervasive computing applications demands a new approach to application development in which domain experts with minimal programming expertise are empowered to rapidly construct and deploy domain-specific applications. This chapter introduces the DAIS (Declarative Applications in Immersive Sensor networks) middleware that abstracts a heterogeneous and dynamic pervasive computing environment into intuitive and accessible programming constructs. At the programming interface level, this requires exposing some aspects of the physical world to the developer, and DAIS accomplishes this through a suite of novel programming abstractions that enable on-demand access to dynamic local data sources. A fundamental component of the model is a hierarchical view of pervasive computing middleware that allows devices with differing capabilities to support differing amounts of functionality. This chapter reports on our design of the DAIS middleware and highlights the abstractions, the programming interface, and the reification of the middleware on a heterogeneous combination of client devices and resource-constrained sensors.

Enabling Programmable Ubiquitous Computing Environments

2011 ◽  
pp. 117-149
Author(s):  
Christine Julien ◽  
Sanem Kabadayi
Keyword(s):  
Pervasive Computing ◽  
Local Environment ◽  
Physical World ◽  
Application Development ◽  
Local Data ◽  
Domain Experts ◽  
Programming Abstractions ◽  
Rapid Deployment ◽  
Ubiquitous Computing Environments ◽  
Programming Interface

Emerging pervasive computing scenarios involve client applications that dynamically collect information directly from the local environment. The sophisticated distribution and dynamics involved in these applications place an increased burden on developers that create applications for these environments. The heightened desire for rapid deployment of a wide variety of pervasive computing applications demands a new approach to application development in which domain experts with minimal programming expertise are empowered to rapidly construct and deploy domainspecific applications. This chapter introduces the DAIS (Declarative Applications in Immersive Sensor networks) middleware that abstracts a heterogeneous and dynamic pervasive computing environment into intuitive and accessible programming constructs. At the programming interface level, this requires exposing some aspects of the physical world to the developer, and DAIS accomplishes this through a suite of novel programming abstractions that enable on-demand access to dynamic local data sources. A fundamental component of the model is a hierarchical view of pervasive computing middleware that allows devices with differing capabilities to support differing amounts of functionality. This chapter reports on our design of the DAIS middleware and highlights the abstractions, the programming interface, and the reification of the middleware on a heterogeneous combination of client devices and resource-constrained sensors.

scholarly journals Towards a Domain-Specific Modeling Language for Extracting Event Logs from ERP Systems

2021 ◽  
Vol 11 (12) ◽  
pp. 5476
Author(s):  
Ana Pajić Simović ◽  
Slađan Babarogić ◽  
Ognjen Pantelić ◽  
Stefan Krstović
Keyword(s):  
Process Mining ◽  
Modeling Language ◽  
Sufficient Information ◽  
Event Data ◽  
Erp Systems ◽  
Domain Experts ◽  
Domain Specific ◽  
Event Logs ◽  
Domain Specific Modeling ◽  
Specific Modeling

Enterprise resource planning (ERP) systems are often seen as viable sources of data for process mining analysis. To perform most of the existing process mining techniques, it is necessary to obtain a valid event log that is fully compliant with the eXtensible Event Stream (XES) standard. In ERP systems, such event logs are not available as the concept of business activity is missing. Extracting event data from an ERP database is not a trivial task and requires in-depth knowledge of the business processes and underlying data structure. Therefore, domain experts require proper techniques and tools for extracting event data from ERP databases. In this paper, we present the full specification of a domain-specific modeling language for facilitating the extraction of appropriate event data from transactional databases by domain experts. The modeling language has been developed to support complex ambiguous cases when using ERP systems. We demonstrate its applicability using a case study with real data and show that the language includes constructs that enable a domain expert to easily model data of interest in the log extraction step. The language provides sufficient information to extract and transform data from transactional ERP databases to the XES format.

scholarly journals A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2514
Author(s):  
Tharindu Kaluarachchi ◽  
Andrew Reis ◽  
Suranga Nanayakkara
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Review Paper ◽  
Learning Systems ◽  
Learning Approaches ◽  
Application Development ◽  
Research Gaps ◽  
Domain Experts ◽  
Working Definition ◽  
Real World Application

After Deep Learning (DL) regained popularity recently, the Artificial Intelligence (AI) or Machine Learning (ML) field is undergoing rapid growth concerning research and real-world application development. Deep Learning has generated complexities in algorithms, and researchers and users have raised concerns regarding the usability and adoptability of Deep Learning systems. These concerns, coupled with the increasing human-AI interactions, have created the emerging field that is Human-Centered Machine Learning (HCML). We present this review paper as an overview and analysis of existing work in HCML related to DL. Firstly, we collaborated with field domain experts to develop a working definition for HCML. Secondly, through a systematic literature review, we analyze and classify 162 publications that fall within HCML. Our classification is based on aspects including contribution type, application area, and focused human categories. Finally, we analyze the topology of the HCML landscape by identifying research gaps, highlighting conflicting interpretations, addressing current challenges, and presenting future HCML research opportunities.

Who Am I?

2021 ◽  
Vol 5 (3) ◽  
pp. 1-32
Author(s):  
Natã M. Barbosa ◽  
Gang Wang ◽  
Blase Ur ◽  
Yang Wang
Keyword(s):  
Pervasive Computing ◽  
Physical World ◽  
Web Browsing ◽  
Privacy Concerns ◽  
Internet Users ◽  
Profiling Techniques ◽  
Positive Experiences ◽  
Field Deployment ◽  
Incremental Construction ◽  
And Control

To enable targeted ads, companies profile Internet users, automatically inferring potential interests and demographics. While current profiling centers on users' web browsing data, smartphones and other devices with rich sensing capabilities portend profiling techniques that draw on methods from ubiquitous computing. Unfortunately, even existing profiling and ad-targeting practices remain opaque to users, engendering distrust, resignation, and privacy concerns. We hypothesized that making profiling visible at the time and place it occurs might help users better understand and engage with automatically constructed profiles. To this end, we built a technology probe that surfaces the incremental construction of user profiles from both web browsing and activities in the physical world. The probe explores transparency and control of profile construction in real time. We conducted a two-week field deployment of this probe with 25 participants. We found that increasing the visibility of profiling helped participants anticipate how certain actions can trigger specific ads. Participants' desired engagement with their profile differed in part based on their overall attitudes toward ads. Furthermore, participants expected algorithms would automatically determine when an inference was inaccurate, no longer relevant, or off-limits. Current techniques typically do not do this. Overall, our findings suggest that leveraging opportunistic moments within pervasive computing to engage users with their own inferred profiles can create more trustworthy and positive experiences with targeted ads.

AN OBJECT-BASED APPROACH TO MANAGING DOMAIN SPECIFIC THESAURI: SEMIAUTOMATIC THESAURUS CONSTRUCTION AND QUERY-BASED BROWSING

2002 ◽  
Vol 12 (04) ◽  
pp. 363-389 ◽  
Author(s):  
JAE HUN CHOI ◽  
JAE DONG YANG ◽  
DONG GILL LEE
Keyword(s):  
Object Oriented ◽  
Domain Expert ◽  
Considerable Part ◽  
New Approach ◽  
Domain Experts ◽  
Domain Specific ◽  
Object Based ◽  
Boolean Queries

In this paper, we propose a new approach for managing domain specific thesauri, where object-oriented paradigm is applied to thesaurus construction and query-based browsing. The approach provides an object-oriented mechanism to assist domain experts in constructing thesauri; it determines a considerable part of relationship degrees between terms by inheritance and supplies the domain expert with information available from other parts of the thesaurus being constructed or already constructed. In addition to that, it enables domain experts to incrementally construct the thesaurus, since the automatically determined relationship degrees can be refined whenever a more sophisticated thesaurus is needed. It may minimize domain experts' burden caused by the exhaustive specification of individual relationship. This approach also provides a query-based browsing facility, which enables users to find desired thesaurus terms without tedious browsing in the thesaurus. A browsing query can be formulated with terms rather ambiguous, yet capable of deriving the desired terms. This browsing query is useful especially when users want precise results. In other words, it is useful when they want to use only thesaurus terms carefully selected in reformulating Boolean queries. To demonstrate the feasibility of our approach, we fully implemented an object-based thesaurus system, which supports the semiautomatic thesaurus construction and the query-based browsing facility.

A Domain Specific Modeling Language for Enterprise Application Development

2018 ◽  
Vol 11 (2) ◽  
pp. 51-70
Author(s):  
Bahman Zamani ◽  
Shiva Rasoulzadeh
Keyword(s):  
Tool Support ◽  
Modeling Language ◽  
Application Development ◽  
Web Based ◽  
Domain Specific ◽  
Enterprise Application ◽  
Extension Mechanism ◽  
Enterprise Applications ◽  
Domain Specific Modeling ◽  
Specific Modeling

This article describes how experience in domain specific modeling can be captured and abstracted in a domain specific modeling language (DSML). Modeling with a DSML results in quality models. Patterns of enterprise application architecture (PofEAA) is a rich set of patterns that can be used by designers when designing (modeling) web-based enterprise applications. This article aims at defining a DSML based on PofEAA patterns, as well as providing tool support for designing web-based enterprise applications that use these patterns. The authors have built a DSML using the profile extension mechanism of UML, by defining stereotypes. In addition to the proposed profile, this article has implemented the structure and behavior of PofEAA patterns in Rational Software Architecture (RSA) which is resulted in a tool that facilitates the design of software for designers. To show the usefulness of the tool, it is used for modeling two small systems based on the PofEAA patterns. The results show that many of the design is automated and the modeling speed is increased.

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