This paper presents an algorithmic approach to acquiring the influencing relationships among users by discovering implicit influencing group structure from smartphone usage. The method assumes that a time series of users' application downloads and activations can be represented by individual inter-personal influence factors. To achieve better predictive performance and also to avoid over-fitting, a latent feature model is employed. The method tries to extract the latent structures by monitoring cross validating predictive performances on approximated influence matrices with reduced ranks, which are generated based on an initial influence matrix obtained from a training set. The method adopts Nonnegative Matrix Factorization (NMF) to reduce the influence matrix dimension and thus to extract the latent features. To validate and demonstrate its ability, about 160 university students voluntarily participated in a mobile application usage monitoring experiment. An empirical study on real collected data reveals that the influencing structure consisted of six influencing groups with two types of mutual influence, i.e. intra-group influence and inter-group influence. The results also highlight the importance of sparseness control on NMF for discovering latent influencing groups. The obtained influencing structure provides better predictive performance than state-of-the-art collaborative filtering methods as well as conventional methods such as user-based collaborative filtering techniques and simple popularity.

This paper proposes a verification-aware design methodology that provides developers with a systematic and reliable approach to performing thread-pipelining parallelization on sequential programs. In contrast to traditional design flow, a behavior-model program is constructed before parallelizing as a bridge to help developers gradually leverage the technique of thread-pipelining parallelization. The proposed methodology integrates verification mechanisms into the design flow. To demonstrate the practicality of the proposed methodology, we applied it to the parallelization of a 3D depth map generator with thread pipelining. The parallel 3D depth map generator was further integrated into a 3D video playing system for evaluation of the verification overheads of the proposed methodology and the system performance. The results show the parallel system can achieve 33.72 fps in D1 resolution and 12.22 fps in HD720 resolution through a five-stage pipeline. When verifying the parallel program, the proposed verification approach keeps the performance degradation within 23% and 21.1% in D1 and HD720 resolutions, respectively.

To realize the harmonious cooperation with the operator, the man-machine cooperative system must be designed so as to accommodate with the characteristics of the operator's skill. One of the important considerations in the skill analysis is to investigate the switching mechanism underlying the skill dynamics. On the other hand, the combination of the feedforward and feedback schemes has been proved to work successfully in the modeling of human skill. In this paper, a new stochastic switched skill model for the sliding task, wherein a minimum jerk motion and feedback schemes are embedded in the different discrete states, is proposed. Then, the parameter estimation algorithm for the proposed switched skill model is derived. Finally, some advantages and applications of the proposed model are discussed.

In databases based on a multi-aspects object data model whcih enables multiple aspects of a real-world entity to be represented and to be acquired/lost dynamically, Object Migration (OM) updating membership relationships between an object and classes occurs, as the properties of the object evolve in its lifetime. We have proposed an OM behavior modeling framework using Colored Petri Nets (CPN) to analyze OM behavior. Based on the proposed framework, this paper presents a technique for constructing OM behavior models from OM constraint descriptions and class schemas as its input. The presented technique makes it easy to construct consistent and complete OM behavior models, since OM constraints are described in a simple, modular, and declarative form.

A new approach for generating a system model from its input-output data is presented. The model is approximated as a linear combination of simple basis functions. The number of basis functions is kept as small as possible to prevent over-fitting and to make the model efficiently computable. Based on these conditions, genetic programming is employed for the generation and selection of the appropriate basis. Since the obtained model can be expressed in simple mathematical expressions, it is suitable for using the model as a macro or behavior model in system level simulation. Experimental results are shown.

Mixed Quasi Newton simulation algorithm that is capable of calculating analog circuits containing mixed level of element models is presented. Conventional circuit simulators usually apply Newton method to solve nonlinear system equations resulted from circuit equations. At each Newton iteration step, it is necessary to reevaluate the Jacobian stamp of circuit elements. However, obtaining the Jacobian stamp of elements described by complex behavior models is a computationally expensive process. To reduce the number of Jacobian evaluations, we combine Newton method and Quasi-Newton method as a new updating scheme. The simulation results show that our algorithm can reduce the number of Jacobian evaluations and improve the simulation time, particularly when simulating circuits containing many behavior model elements.

Using object-oriented techniques, one can build software that models the real world more closely. In objectoriented analysis and design, two types of closely interrelated models have been built which specify the static structure and the dynamic behavior of objects. Much work based on those models deals with how to use inheritance to support reuse and easy extension more precisely. In this paper, we are concerned with the dynamic aspects of objects, and define a behavior inheritance relationship between a class and its subclass. We present a set of derivation operations based on the incremental design of the behavior model. The operations preserve the behavior inheritance relationship between classes. The result makes a theoretical base for making new classes by reusing the existing classes in objectoriented system development.

We develop a new class of stochastic Petri net: non-regenerative stochastic Petri net (NRSPN), which allows the firing time of its transitions with arbitrary distributions, and can automatically generate a bounded reachability graph that is equivalent to a generalization of the Markov renewal process in which some of the states may not constitute regeneration points. Thus, it can model and analyze behavior of a system whose states include some non-regeneration points. We show how to model a system by the NRSPN, and how to obtain numerical solutions for the NRSPN model. The probabilistic behavior of the modeled system can be clarified with the reliability measures such as the steady-state probability, the expected numbers of visits to each state per unit time, availability, unavailability and mean time between system failure. Finally, to demonstrate the modeling ability and analysis power of the NRSPN model, we present an example for a fault-tolerant system using the NRSPN and give numerical results for specific distributions.

Behavior modeling of objects is critical in object-oriented design. In particular, it is essential to preserve integrity constraints on object behavior in application environments where objects of various classes dynamically interact with each other. In order to provide a stable design technique, a behavior model using the notion of the life cycle schema of a class is proposed. To model the aspect of behavioral abstraction of objects, the notion of schema refinement together with a diagrammatic representation technique is also defined. In this framework, a formalization of behavior constraints on objects which interact with each other is proposed together with its graphical representation. Verification rules of consistency of behavior constraints are also discussed. In order to perform certain functions, several partner objects of the same or different classes should collaborate establishing client-server relationships. The contract of a class is defined as a collection of responsibilities of a server class to a client class where each responsibility is specified in the form of the script. To achieve a high degree of systems integrity, a procedure to derive scripts from behavior constraints on collaborating partners is developed. It is also critical to evenly distribute responsibilities to partner objects. A delegation is placing a whole or a part of responsibilities of an object in charge of other objects. Based on the design principle delegation along the aggregation hierarchy,' a unified design approach to delegation that enables to reorganize scripts in constraints preserving way is proposed.