Detection of Social Interaction in Smart Spaces

The pervasive sensing technologies found in smart environments offer unprecedented opportunities for monitoring and assisting the individuals who live and work in these spaces. An aspect of daily life that is important for one's emotional and physical health is social interaction. In this paper we investigate the use of smart environment technologies to detect and analyze interactions in smart spaces. We introduce techniques for collect and analyzing sensor information in smart environments to help in interpreting resident behavior patterns and determining when multiple residents are interacting. The effectiveness of our techniques is evaluated using two physical smart environment testbeds.     

Integrated Development of Context-Aware Applications in Smart Spaces

When designing context-aware applications for smart spaces, developers must provide interface specifications for perceptual components, which often come from multiple vendors. The authors outline a set of structuring principles that leverage such specifications. IBM has introduced two tools that facilitate the development of smart space applications. Chilix is a middleware library for bridging disaggregated systems, and SitCom is an integrated development environment enabling context modeling, and simulation and lifecycle management of perceptual components. Chilix provides an attractive lightweight alternative to legacy middleware for distributed computing. SitCom supports perceptual component developers, service developers and context-modeling experts across the development life cycle.     

Information management in context trees

Summary Information management in context trees involves three principal problems: retrieval, updating and garbage collection. These problems are discussed in the paper, and solutions are proposed and motivated. A list organization and relative algorithms to implement context trees are presented. Finally, experimental results are reported about the behaviour of a system which exploits context trees.     

Sensor Networks Motes, Smart Spaces, and Beyond

Sensor networks have come a long way since their humble beginnings in DARPA-funded academic research projects in the 1990s and have morphed into a significant research area in their own right. Over the last decade or so, networked sensing devices have become embedded all around us. In this article we look at how sensor network research and applications have evolved and how emerging trends could determine where they're headed.     

Smart radiation sensor management

We developed two radiation mapping algorithms that can handle different situations based on prior information of the search area. The algorithms were developed in the framework of model-driven measurement, where a world model was used to drive measurement collection, and measurements were used to update the world model.We developed and experimentally tested a robotic implementation of two Bayesian-based radiation mapping strategies in two dimensions, using a commercially available desktop mobile robot fitted with a CsI radiation sensor. Our approach for implementing the Bayesian radiation mapping algorithms was to drive the robot over each segment of the search area, in real time, according to the radiation counts collected by the sensor. Future research directions include extensions to three-dimensional mapping; exploring and characterizing the tradeoffs between time efficiency, map confidence level, and utilization of prior knowledge information; as well as the implementation of Bayesian statistics for the online update of the world model.     

Managing context in business process management systems

Businesses need to continuously focus on change and innovation in order to survive in dynamic environments. The ability of an organization to deploy appropriate business processes requires that the fit between business processes and systems that support the management of these processes is continuously maintained and evolved. Acquisition and use of the knowledge about the context in which business processes are defined, modified, and implemented can help maintain this fit. We identify requirements for a business process management system (BPMS) capable of managing contextual knowledge. Based on these requirements, we have enhanced KOPeR, a knowledge-based system for business process improvement, with an explanation facility that can acquire and maintain knowledge about the context behind process definitions and design choices. A case study that illustrates the functionalities of this system which is designed to improve the fit between business processes and BPMS is presented.

Delivering public value through open government data initiatives in a Smart City context

By using ICT in an innovative way, governments can improve the delivery of services and interaction with stakeholders. Open data is a way to help public organizations became more open and improve interaction with stakeholders. This paper aims to identify what are the public values enhancements acquired on smart city environment that discloses open data. We propose a conceptual model to analyze the smart city initiative. We contextualized the model taking a smart city domain by analyzing three related-initiatives that comprises open data in a smart city case carried at Rio de Janeiro Operations Center (COR) in Brazil by seven deep-interviewees directly involved - from inside and outside – in this case. The findings reveal evidences that open data initiatives contribute to enhance the delivery of public value in smart city contexts.     

Uncertain context data management in dynamic mobile environments

Building systems that acquire, process and reason with context data is a major challenge. Model updates and modifications are required for the mobile context-aware systems. Additionally, the nature of the sensor-based systems implies that the data required for the reasoning is not always available nor it is certain. Finally, the amount of context data can be significant and can grow fast, constantly being processed and interpreted under soft real-time constraints. Such characteristics make it a case for a challenging big data application. In this paper we argue, that mobile context-aware systems require specific methods to process big data related to context, at the same time being able to handle uncertainty and dynamics of this data. We identify and define main requirements and challenges for developing such systems. Then we discuss how these challenges were effectively addressed in the KnowMe project. In our solution, the acquisition of context data is made with the use of the AWARE platform. We extended it with techniques that can minimise the power consumption as well as conserve storage on a mobile device. The data can then be used to build rule models that can express user preferences and habits. We handle the missing or ambiguous data with number of uncertainty management techniques. Reasoning with rule models is provided by a rule engine developed for mobile platforms. Finally, we demonstrate how our tools can be used to visualise the stored data and simulate the operation of the system in a testing environment.     

Smart Sankey picturization for energy management systems in India

AI & SOCIETY - India’s energy demand is predicted to rise by 135% within a span of 20 years. Coping up with surging energy demands requires several reforms in both renewable and...     

智能化通信网络综合管理系统浅析

首先对智能化网络管理技术相关的现状和趋势进行了分析;接着介绍结合了基于策略的网络管理技术、基于规则的告警关联分析技术、基于工作流的过程控制技术实现的智能化综合网络管理系统原型系统。     

Concurrent Cooperating Solvers over Reals

Systems combining an interval narrowing solver and a linear programming solver can tackle constraints over the reals that none of these solvers can handle on their own. In this paper we introduce a cooperating scheme where an interval narrowing solver and a linear programming solver work concurrently. Information exchanged by the solvers is therefore handled as soon as it becomes available. Moreover, to improve the pruning, the linear programming solver computes the actual range of values of each variable with respect to the subset of linear constraints. To validate the proposed architecture a prototype system-named CCC-has been developed. Several examples are given to illustrate the gain in speed and precision we can expect with CCC.     

User Profile Modeling in the context of web-based learning management systems

Over the past two decades, great research efforts have been made towards the personalization of e-learning platforms. This feature increases remarkably the quality of the provided learning services, since the users’ special needs and capabilities are respected. The idea of predicting the users’ preferences and adapting the e-learning platform accordingly is the focal point of this paper. In particular, this paper starts with the main requirements of an advanced e-learning system, explains the way a user navigates in such a system, presents the architecture of a corresponding e-learning system and describes its main components. Research is focused on the User Model component, its role in the e-learning system and the parameters that comprise it. In this context, Bayesian Networks are used as a tool for the encoding, learning and reasoning of probabilistic relationships, with the aim to effectively predict user preferences. In support of this vision, four different scenarios are presented, in order to test the way Bayesian Networks apply in the e-learning field.     

An approach to domain-based scalable context management architecture in pervasive environments

In pervasive environments, context management systems are expected to administrate large volume of contextual information that is captured from spatial to nonspatial elements. Research in context-aware computing produced a number of middleware systems for context management to intermediate the communications between applications and context providers. In particular, in pervasive environments, the design of distributed storage, retrieval and propagation mechanisms of context information across domains is vital. In this paper, we propose a domain-based approach to address the requirements of scalable distributed context management, cross-domain efficient context information dissemination and domain-based privacy policy enforcement. We propose infinitum, a middleware architecture that incorporates the management and communication benefits of the Google Wave Federation Protocol, while also taking advantage of the semantic and inference benefits of ontology-based context models. This architecture establishes a robust cross-domain scalable context management and collaboration framework, which has been implemented and evaluated in a real-life application of “SMART University” to support virtual team collaboration.     

End user dialogue context management of office automation systems

Office work is situated social action, a notion that includes both the social actions of computer systems in their interactions with office workers and other computer systems. This notion can be operationalized by dialogue context, which can then be used as a design parameter in office information systems. Observational data were collected by video recording a secretary's activities over an 8 hour duration. The data were analysed and discussed with the secretary to identify her action units. These action units were then related using an action graph. An interpretation of the action graph and observational data suggest certain features that a dialogue context management mechanism should have. They are: (1) a good match between applications and activities, (2) automated tools to support routine activities, and (3) informative and manageable metaphor to model the real world.     

协同虚拟实验室关键技术的研究

随着计算机网络的发展，远程教学正在成为一种重要的教育模式。网上协同虚拟实验室的出现，使远程教育更趋完善，它的建立大大提高了实验教学的伸缩性和适应性。该文设计了协同虚拟实验室的一种基本框架，论述了协同虚拟实验室应具有的基本功能，提出了协同实验中的并发控制策略，最后指出了协同虚拟实验室设计中用到的其它关键技术：人机交互技术、群体感知技术、组播技术等。     

Information management model for competencies and learning outcomes in an educational context

The Bologna Process opened the door to the globalization of higher education, by creating a unified architecture that enhances the potential of higher education and encourages increasing and continuous interconnection among different higher education strategies in the world, and particularly in Europe. This paper introduces and describes an innovative model for a thorough, organized and systematic analysis of the educational context ? MICRA (model for identifying and classifying Competencies and Learning Outcomes), based on the official documents of the Course Units (syllabus and assessment components). The MICRA model was validated by means of a case study. Competencies and Learning Outcomes were identified in the Computer Science Course Units of the Accounting and Business Administration degree at the Institute of Accounting and Administration of Porto (ISCAP/IPP). We are aware that the adoption of this model by different institutions will contribute to the interoperability of learning outcomes, thus enhancing the mobility of teachers and students in the EHEA (European Higher Education Area) and third countries.     

Perceived risks and risk management of social media in an organizational context

The use of new electronic media for marketing communication is gaining in popularity with organizations, and the adoption of social media (SOME) is enjoying particularly rapid growth. However, organizations are uncertain about using SOME and perceived risks are limiting their use. This study explores the key types of risks that business organizations associate with using SOME in their marketing communication. We also explore the effectiveness of procedural control and proactive focusing processes in managing these risks. The results show that organizations perceive three types of risks that deterred companies from increasing the use of SOME. Companies applied procedural control mechanisms to manage time-loss risks. An organization’s familiarity with SOME was found to have a strong effect on time-loss as well as on other types of risks. Research revealed that the role that proactive focus and procedural control played in managing SOME-related risks was less than had been anticipated.     

Cooperating rewrite processes for natural-language analysis

General methods for understanding a natural language based on the intensive use of rewrite rules and on the existence of several cooperating processes are put forward. The choice of Horn-clause logic as the underlying formalism for semantic representations, together with the employment of unification as pattern-matching procedure and depth-first search with backtracking were derived from logic-programming ideas, in particular from the use of PROLOG. Several examples are presented to illustrate how these methods work.     

Cooperating systems of four-dimensional finite automata

M. Blum and C. Hewitt first proposed two-dimensional automata as a computational model of two-dimensional pattern processing in 1967, and investigated their pattern recognition abilities. Since then, many researchers in this field have investigated many properties of automata on a two- or three-dimensional tape. However, the question of whether processing four-dimensional digital patterns is much more difficult than processing two- or three-dimensional ones is of great interest from both theoretical and practical standpoints. Thus, the study of four-dimensional automata as a computational model of four-dimensional pattern processing has been meaningful. This article introduces a cooperating system of four-dimensional finite automata as one model of four-dimensional automata. A cooperating system of four-dimensional finite automata consists of a finite number of four-dimensional finite automata and a four-dimensional input tape, where these finite automata work independently (in parallel). The finite automata whose input heads scan the same cell of the input tape can communicate with each other, i.e., every finite automaton is allowed to know the internal states of other finite automata on the cell it is scanning at the moment. In this article we mainly investigate the accepting powers of a cooperating system of seven-way four-dimensional finite automata. The seven-way four-dimensional finite automaton is a four-dimensional finite automaton whose input head can move east, west, south, north, up, down, or in the future, but not in the past, on a four-dimensional input tape.