Information-based adaptive fast-forward for visual surveillance

Automated video analysis lacks reliability when searching for unknown events in video data. The practical approach is to watch all the recorded video data, if applicable in fast-forward mode. In this paper we present a method to adapt the playback velocity of the video to the temporal information density, so that the users can explore the video under controlled cognitive load. The proposed approach can cope with static changes and is robust to video noise. First, we formulate temporal information as symmetrized Rényi divergence, deriving this measure from signal coding theory. Further, we discuss the animated visualization of accelerated video sequences and propose a physiologically motivated blending approach to cope with arbitrary playback velocities. Finally, we compare the proposed method with the current approaches in this field by experiments and a qualitative user study, and show its advantages over motion-based measures.     

Non-standard bone simulation: interactive numerical analysis by computational steering

Numerous numerical methods have been developed in an effort to accurately predict stresses in bones. The largest group are variants of the h-version of the finite element method (h-FEM), where low order Ansatz functions are used. By contrast, we3 investigate a combination of high order FEM and a fictitious domain approach, the finite cell method (FCM). While the FCM has been verified and validated in previous publications, this article proposes methods on how the FCM can be made computationally efficient to the extent that it can be used for patient specific, interactive bone simulations. This approach is called computational steering and allows to change input parameters like the position of an implant, material or loads and leads to an almost instantaneous change in the output (stress lines, deformations). This direct feedback gives the user an immediate impression of the impact of his actions to an extent which, otherwise, is hard to obtain by the use of classical non interactive computations. Specifically, we investigate an application to pre-surgical planning of a total hip replacement where it is desirable to select an optimal implant for a specific patient. Herein, optimal is meant in the sense that the expected post-operative stress distribution in the bone closely resembles that before the operation.     

Iterant recombination with one-norm minimization for multilevel Markov chain algorithms via the ellipsoid method

Recently, it was shown how the convergence of a class of multigrid methods for computing the stationary distribution of sparse, irreducible Markov chains can be accelerated by the addition of an outer iteration based on iterant recombination. The acceleration was performed by selecting a linear combination of previous fine-level iterates with probability constraints to minimize the two-norm of the residual using a quadratic programming method. In this paper we investigate the alternative of minimizing the one-norm of the residual. This gives rise to a nonlinear convex program which must be solved at each acceleration step. To solve this minimization problem we propose to use a deep-cuts ellipsoid method for nonlinear convex programs. The main purpose of this paper is to investigate whether an iterant recombination approach can be obtained in this way that is competitive in terms of execution time and robustness. We derive formulas for subgradients of the one-norm objective function and the constraint functions, and show how an initial ellipsoid can be constructed that is guaranteed to contain the exact solution and give conditions for its existence. We also investigate using the ellipsoid method to minimize the two-norm. Numerical tests show that the one-norm and two-norm acceleration procedures yield a similar reduction in the number of multigrid cycles. The tests also indicate that one-norm ellipsoid acceleration is competitive with two-norm quadratic programming acceleration in terms of running time with improved robustness.     

Taxonomy,technology and applications of smart objects

Deployment of embedded technologies is increasingly being examined in industrial supply chains as a means for improving efficiency through greater control over purchase orders, inventory and product related information. Central to this development has been the advent of technologies such as bar codes, Radio Frequency Identification (RFID) systems, and wireless sensors which when attached to a product, form part of the product’s embedded systems infrastructure. The increasing integration of these technologies dramatically contributes to the evolving notion of a “smart product”, a product which is capable of incorporating itself into both physical and information environments. The future of this revolution in objects equipped with smart embedded technologies is one in which objects can not only identify themselves, but can also sense and store their condition, communicate with other objects and distributed infrastructures, and take decisions related to managing their life cycle. The object can essentially “plug” itself into a compatible systems infrastructure owned by different partners in a supply chain. However, as in any development process that will involve more than one end user, the establishment of a common foundation and understanding is essential for interoperability, efficient communication among involved parties and for developing novel applications. In this paper, we contribute to creating that common ground by providing a characterization to aid the specification and construction of “smart objects” and their underlying technologies. Furthermore, our work provides an extensive set of examples and potential applications of different categories of smart objects.     

Derivation of trust federation for collaborative business processes

Service Oriented Architecture (SOA) is considered to be an important enabler of Internet of Services. By adopting SOA in development, business services can be offered, mediated, and traded as web services, so as to support agile and dynamic business collaborations on the Internet. Business collaboration is often implemented as cross-enterprise processes and involves more than one business entity which agrees to join the collaboration. To enable trustworthy and secure provision of services and service composition across enterprise boundaries, trust between business participants must be established, that is, user identities and access rights must be federated, to support business functions defined in the business processes. This paper proposes an approach which derives trust federation from formally described business process models, such as BPMN and WS-CDL processes, to automate security configuration of business collaborations. The result of the derivation is trust policies which identify trust relationships between business participants and can be enforced in enterprises’ service runtimes with support of a policy deployment infrastructure.     

TMS-RFID: Temporal management of large-scale RFID applications

In coming years, there will be billions of RFID tags living in the world tagging almost everything for tracking and identification purposes. This phenomenon will impose a new challenge not only to the network capacity but also to the scalability of event processing of RFID applications. Since most RFID applications are time sensitive, we propose a notion of Time To Live (TTL), representing the period of time that an RFID event can legally live in an RFID data management system, to manage various temporal event patterns. TTL is critical in the “Internet of Things” for handling a tremendous amount of partial event-tracking results. Also, TTL can be used to provide prompt responses to time-critical events so that the RFID data streams can be handled timely. We divide TTL into four categories according to the general event-handling patterns. Moreover, to extract event sequence from an unordered event stream correctly and handle TTL constrained event sequence effectively, we design a new data structure, namely Double Level Sequence Instance List (DLSIList), to record intermediate stages of event sequences. On the basis of this, an RFID data management system, namely Temporal Management System over RFID data streams (TMS-RFID), has been developed. This system can be constructed as a stand-alone middleware component to manage temporal event patterns. We demonstrate the effectiveness of TMS-RFID on extracting complex temporal event patterns through a detailed performance study using a range of high-speed data streams and various queries. The results show that TMS-RFID has a very high throughput, namely 170,000–870,000 events per second for different highly complex continuous queries. Moreover, the experiments also show that the main structure to record the intermediate stages in TMS-RFID does not increase exponentially with the number of events. These results demonstrate that TMS-RFID not only supports high processing speeds, but is also highly scalable.     

SimKnowledge—Analyzing impact of knowledge management measures on team organizations with multi agent-based simulation

Even though there is abundant literature on successful cases of organizations applying knowledge management (KM) measures, many KM initiatives have failed to achieve their knowledge and business goals. In order to foster decisions about the design of such initiatives, information is required on success factors and barriers when selecting KM measures. Multi agent-based simulation (MABS) is suggested as instrument to investigate potential effects of KM measures on dependent variables such as sharing of knowledge in organizations or business performance. For such a simulation, the concept of knowledge sharing, influencing factors and their impact on business and knowledge goals are modeled based on an extensive multi-disciplinary literature survey. An extensive domain model is operationalized in a simulation model which is then further simplified and implemented in a MABS tool used for a series of experiments contrasting results with/without KM measures, specifically skill and experience management. Skill management is found highly sensitive with respect to conditions of application and has no significant impact on knowledge or business goals. Experience management positively impacts knowledge and business goals. Personal documentation leads to specialist, project debriefings to generalist knowledge workers. Finally, the paper discusses the simulation’s limitations and further areas of application.     

On the logic of preference and judgment aggregation

Agents that must reach agreements with other agents need to reason about how their preferences, judgments, and beliefs might be aggregated with those of others by the social choice mechanisms that govern their interactions. The emerging field of judgment aggregation studies aggregation from a logical perspective, and considers how multiple sets of logical formulae can be aggregated to a single consistent set. As a special case, judgment aggregation can be seen to subsume classical preference aggregation. We present a modal logic that is intended to support reasoning about judgment aggregation scenarios (and hence, as a special case, about preference aggregation): the logical language is interpreted directly in judgment aggregation rules. We present a sound and complete axiomatisation. We show that the logic can express aggregation rules such as majority voting; rule properties such as independence; and results such as the discursive paradox, Arrow’s theorem and Condorcet’s paradox—which are derivable as formal theorems of the logic. The logic is parameterised in such a way that it can be used as a general framework for comparing the logical properties of different types of aggregation—including classical preference aggregation. As a case study we present a logical study of, including a formal proof of, the neutrality lemma, the main ingredient in a well-known proof of Arrow’s theorem.     

Next generation session management for 3D teleimmersive interactive environments

In the recent past we have seen a boom of distributed interactive multimedia environments which use multiple correlated media sensors, multi-view displays, and advanced haptic-audio-visual user interfaces for teleimmersive gaming, business meetings and other collaborative activities. However, when we investigate the emerging teleimmersive environments closer, we realize that their overall session management, including end-to-end session setup, establishment and run-time management are not appropriate for the new demands that these environments present. These environments are cyber-physical rooms that demand (a) large scale of multi-sensory devices across geographically-distributed locations and (b) interaction with each other in synchronous and real-time manner. To deal with the new teleimmersive demands, we present a new session management design with (a) session initiation protocol(s) that understand media correlations, (b) view-based multi-stream topology establishment among multiple parties, (c) efficient, light-weight and distributed session monitoring with querying and debugging capabilities, (d) flexible view-based session adaptation with efficient topology adjustments, and (e) light-weighted and consistent session tear-down protocols. The presented design of the next generation session management protocols, services, algorithms and data structures is based on our extensive experiences with building 3D teleimmersive interactive systems, experimenting with high impact teleimmersive applications and deploying such environments at various venues.