A Novel Load Control Strategy For TD-SCDMA Enhanced Uplink
In this paper, we propose a novel load control strategy for TD-SCDMA Enhanced Uplink, called as system-based load control strategy. We compare its performance with the cell-based load control strategy, which was widely accepted in TD-SCDMA release 4/5. It is concluded that system-based load control outperforms cell-based load control in the rise over thermal (RoT) control and the system throughput.

title: A Composition-Oriented Approach for Business Process Formal Design
abstract: Traditional approaches to designing business processes are often inadequate for complicated, distributed, and collaborated settings. However since network technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore a new approach is needed. To this end, we describe the motivation, conceptualization, and analysis of a composition-oriented business process design method. The key advance of our method is that it uses process algebra pi-calculus as its formal basis and builds a complex process by composing simple structured process control modules to reduce the complexity of business process design as well as let several designers collaborate the design of a complex process. To make business process more clear, we also provide way of separating exception processing logic from normal process control logic and provide scooping mechanisms to minimize the detrimental effects of unplanned contingencies by ways of composition

title: Automating change evolution in model-driven engineering
abstract: The escalating complexity of software and system models is making it difficult to rapidly explore the effects of a design decision. Automating such exploration with model transformation and aspect-oriented techniques can improve both productivity and model quality. The combination of model transformation and aspect weaving provides a powerful technology for rapidly transforming legacy systems from the high-level properties that models describe. Further, by applying aspect-oriented techniques and program transformation, small changes at the modeling level can trigger very large transformations at the source code level. Thus, model engineers can explore alternative configurations using an aspect weaver targeted for modeling tools and then use the models to generate program transformation rules for adapting legacy source code on a wide scale.

title: Aspect mining from a modelling perspective
abstract: Aspect mining aims at identifying, analysing, and refactoring crosscutting concerns throughout a legacy system for the purpose of improving software modularisation. This paper presents our investigation into raising the benefits of aspect mining to high level domain-specific models. A key contribution is the capability to identify crosscutting concerns early in development, which will assist in the modularisation of a design through aspects, before proceeding to the implementation level. Furthermore, our experience has led us to believe that aspects are easier to identify at the modelling level, because much of the accidental complexities of implementation concerns are not present in the corresponding modelling abstractions.

title: Model replication: transformations to address model scalability
abstract: 2 SUMMARY In Model-Driven Engineering, it is often desirable to evaluate different design alternatives as they relate to scalability issues of the modeled system. A typical approach to address scalability is model replication, which starts by creating base models that capture the key entities as model elements and their relationships as model connections. A collection of base models can be adorned with necessary information to characterize a specific scalability concern as it relates to how the base modeling elements are replicated and connected together. In current modeling practice, such model replication is usually accomplished by scaling the base model manually. This is a time-consuming process that represents a source of error, especially when there are deep interactions between model components. As an alternative to the manual process, this paper presents the idea of automated model replication through a model transformation process that expands the number of elements from the base model and makes the correct connections among the generated modeling elements. The paper motivates the need for model replication through case studies taken from models supporting different domains.

title: Business Process-Oriented Software Architecture for Supporting Business Process Change
abstract: As a business process is essential in running an enterprise, this paper aims toward improving software architecture by extracting business-relevant semantics from business logic and transforming them as important elements that need to be molded and represented in software architecture. This allows for the development of a business process-oriented software architecture (BPOSA) that can support smoother business process change. The paper introduces the structure of BPOSA and its work mode. Then it describes the steps involved in designing a process-oriented software system, and provides analysis and design methods of extending process-relevant attributes for application in business operations.

title: The Application of Cultural Algorithm in Load Balancing of Hybrid P2P Network
abstract: This paper analyses the defect of the designing model of load balancing in hybrid P2P network, and proposes a new strategy of scheduling for load balancing, which based on culture algorithm of multilayer belief spaces. According to the current load status of each super-node in the system, it can calculate its load weight of the next time section by using the cultural algorithm, and assign the current requests of login with weighted round-robin. The extracted knowledge which is got by selecting the best belief space from the multilayer belief space is used to optimize the constrains of the evolutionary, in order to accelerate the optimization process of the calculation of load weight. Simulation experiments show that the allocation of login request to each node is to be balance much faster through using of cultural algorithm based on multilayer belief spaces.

title: Simplifying the Reconstruction of 3D Models using Parameter Elimination
abstract: Reconstructing large models from images is a significant challenge for computer vision, computer graphics, and related fields. In this paper, we present an approach for simplifying the reconstruction process by mathematically eliminating external camera parameters. This results in less parameters to estimate and in an overall significantly more robust and accurate reconstruction. We reformulate the problem in such a manner as to be able to identify invariants, eliminate superfluous parameters, and measure the performance of our formulation under various conditions. We compare a two-step camera orientation-free method, where the majority of the points are reconstructed using a linear equation set, and a camera position-and- orientation free method, using a degree-two equation set. Both approaches use a full perspective camera and are applied to synthetic and real-world datasets.

title: Learning-Based Driver Workload Estimation
abstract: A popular definition of workload is given by O’Donnell and Eggmeir, which states that “The term workload refers to that portion of the operator’s limited capacity actually required to perform a particular task” . In the vehicle environment, the “particular task” refers to both the vehicle control, which is the primary task, and other secondary activities such as listening to the radio. Three major types of driver workload are usually studied, namely, visual, manual, and cognitive. Auditory workload is not treated as a major type of workload in the driving context because the auditory perception is not considered as a major requirement to perform a driving task. Even when there is an activity that involves audition, the driver is mostly affected cognitively. Lately, the advanced computer and telecommunication technology is introducing many new in-vehicle information systems (IVISs), which give drivers more convenient and pleasant driving experiences. Active research is being conducted to provide IVISs with both high functionality and high usability. On the usability side, driver’s workload is a heated topic advancing in at least two major directions. One is the offline assessment of the workload imposed by IVISs, which can be used to improve the design of IVISs. The other effort is the online workload estimation, based on which IVISs can provide appropriate service at appropriate time, which is usually termed as Workload Management . For example, the incoming phone call may be delayed if the driver is engaged in a demanding maneuver. Among the three major types of driver workload, cognitive workload is the most difficult to measure. For example, withdrawing hands from the steering wheel to reach for a coffee cup requires extra manual workload. It also may require extra visual workload in that the position of the cup may need to be located. Both types of workload are directly measurable through such observations as hands-off-wheel and eyes-offroad time. On the other hand, engaging in thinking (the so-called minds-off-road phenomenon) is difficult to detect. Since the cognitive workload level is internal to the driver, it can only be inferred based on the information that is observable. In this chapter, we report some of our research results on driver’s cognitive workload estimation. After the discussion of the existing practices, we propose a new methodology to design driver workload estimation systems, that is, using machine-learning techniques to derive optimized models to index workload. The advantage of this methodology will be discussed, followed by the presentation of some experimental results. This chapter concludes with discussion of future work.

title: Adaptive motion selection for online hand-eye calibration
abstract: While a robot moves, online hand–eye calibration to determine the relative pose between the robot gripper/end-effector and the sensors mounted on it is very important in a vision-guided robot system. During online hand–eye calibration, it is impossible to perform motion planning to avoid degenerate motions and small rotations, which may lead to unreliable calibration results. This paper proposes an adaptive motion selection algorithm for online hand–eye calibration, featured by dynamic threshold determination for motion selection and getting reliable hand–eye calibration results. Simulation and real experiments demonstrate the effectiveness of our method.

title: Federate Job Mapping Strategy in Grid-Based Virtual Wargame Collaborative Environment
abstract: A crucial issue for grid-based virtual wargame collaborative environment is that of mapping federate jobs to grid nodes efficiently. Because there exits large amount of interactions among federates, it is a challenging work to design an efficient federate mapping strategy. In this paper, we established an objective function for federate job mapping which takes into consideration not only the load of grid nodes, but also network utilization. Experimental results show that the proposed federate job mapping strategy can contribute to load balancing of the virtual wargame collaborative environment.