8252393
Queueing Network-Model Human Processor (QN-MHP): A computational architecture for multitask performance in human-machine systems
Queueing Network-Model Human Processor (QN-MHP) is a computational architecture that integrates two complementary approaches to cognitive modeling: the queueing network approach and the symbolic approach (exemplified by the MHP/GOMS family of models, ACT-R, EPIC, and SOAR). Queueing networks are particularly suited for modeling parallel activities and complex structures. Symbolic models have particular strength in generating a person's actions in specific task situations. By integrating the two approaches, QN-MHP offers an architecture for mathematical modeling and real-time generation of concurrent activities in a truly concurrent manner. QN-MHP expands the three discrete serial stages of MHP, of perceptual, cognitive, and motor processing, into three continuous-transmission subnetworks of servers, each performing distinct psychological functions specified with a GOMS-style language. Multitask performance emerges as the behavior of multiple streams of information flowing through a network, with no need to devise complex, task-specific procedures to either interleave production rules into a serial program (ACT-R), or for an executive process to interactively control task processes (EPIC). Using QN-MHP, a driver performance model was created and interfaced with a driving simulator to perform a vehicle steering, and a map reading task concurrently and in real time. The performance data of the model are similar to human subjects performing the same tasks.
9965299
Computational modeling and experimental investigation of effects of compositional elements on interface and design aesthetics
This article describes computational modeling and two corresponding experimental investigations of the effects of symmetry, balance and quantity of construction elements on interface aesthetic judgments. In the first experiment, 30 black and white geometric images were developed by systematically varying these three attributes in order to validate computational aesthetic quantification algorithms with subject ratings. The second experiment employed the same image layout as Experiment 1 but with realistic looking web pages as stimuli. The images were rated by 16 subjects in each experiment using the ratio-scale magnitude estimation method against a benchmark image with average balance and symmetry values and a standard number of elements. Subjects also established an ordered list of the images according to their aesthetic appeal using the Balanced-Incomplete-Block (BIB) ranking method. Results from both experiments show that subjects are adept at judging symmetry and balance in both the horizontal and vertical directions and thus the quantification of those attributes is justified. The first experiment establishes a relationship between a higher symmetry value and aesthetic appeal for the basic imagery showing that subjects preferred symmetric over non-symmetric images. The second experiment illustrates that increasing the number of groups in a web page causes a decrease in the aesthetic appeal rating.
5965790
On scalable and locality-aware web document sharing
We propose a scalable Web document sharing infrastructure model called Browsers-Aware Proxy Server. In this design, a proxy server connecting to a group of networked clients maintains an index file of data objects of all clients' browser caches. If a user request misses in its local browser cache and the proxy cache, the browsers-aware proxy server will search the index file attempting to find it in another client's browser cache before sending the request to an upper level proxy or the Web server. If such a request does hit in a remote client, this client will directly forward the data object to the requesting client; or the proxy server fetches the data object from this client and then forwards it to the requesting client. The contributions of this caching model are twofold. First, we show that the amount of sharable data in browser caches is significant and can be utilized for document sharing among clients to improve Web caching performance and scalability. Second, the browsers-aware model can effectively and further improve Web prefetching performance. The browsers-aware model and its supported prefetching technique build a strong locality-aware Internet environment to make Web accesses fast with low communication costs. Conducting trace-driven simulations, we show the effectiveness of the browsers-aware model, and its unique advantages to facilitate prefetching.
11844078
Customized Benchmark Generation Using MDA
This paper describes an approach for generating customized benchmark applications from a software architecture description using a Model Driven Architecture (MDA) approach. The benchmark generation and performance data capture tool implementation is based on widely used open source MDA frameworks. The business logic of the benchmark application is modeled in UML and generated by taking advantage of the existing generation "cartridges" so that the current component technology can be exploited in the benchmark. This greatly reduces the effort and expertise needed for benchmarking with complex component technology. We have also extended the MDA framework to model and generate a load testing suite and automatic performance measurement infrastructure. The approach complements current model-based performance prediction and analysis methods by generating the benchmark application from the same application architecture that the performance models are derived from. This provides the potential for tightly integrating runtime performance measurement with model-based prediction either for model validation or improving model prediction accuracy. We illustrate the approach using a case study based on EJB component technology.
2030931
Improved Algorithm Complexities for Linear Temporal Logic Model Checking of Pushdown Systems
This paper presents a novel implementation strategy for linear temporal logic (LTL) model checking of pushdown systems (PDS). The model checking problem is formulated intuitively in terms of evaluation of Datalog rules. We use a systematic and fully automated method to generate a specialized algorithm and data structures directly from the rules. The generated implementation employs an incremental approach that considers one fact at a time and uses a combination of linked and indexed data structures for facts. We provide precise time complexity for the model checking problem; it is computed automatically and directly from the rules. We obtain a more precise and simplified complexity analysis, as well as improved algorithm understanding.
5655838
Automated software engineering using concurrent class machines
Concurrent Class Machines are a novel state-machine model that directly captures a variety of object-oriented concepts, including classes and inheritance, objects and object creation, methods, method invocation and exceptions, multithreading and abstract collection types. The model can be understood as a precise definition of UML activity diagrams which, at the same time, offers an executable, object-oriented alternative to event-based statecharts. It can also be understood as a visual, combined control and data flow model for multithreaded object-oriented programs. We first introduce a visual notation and tool for Concurrent Class Machines and discuss their benefits in enhancing system design. We then equip this notation with a precise semantics that allows us to define refinement and modular refinement rules. Finally, we summarize our work on generation of optimized code, implementation and experiments, and compare with related work.
8093965
A feature-based approach for individualized human head modeling
The human head is a significant part of the human body, with which we can recognize individuals from a vast universe of populations. Since the early 1970s, considerable effort has been devoted to computeraided modeling of human head for applications varied from realistic effect in computer graphics to custom model generation in modern manufacturing industries. However, realistic head modeling is still a challenge and continues to fascinate computer graphics researchers. The greatest difficulties in human head modeling result from the extremely complex geometric form of the human head. To generate realistic individualized models, most proposed head modeling techniques use the common approach of deforming a generic model into an individualized one, based on individual head information. There are various sources to obtain individual information, e.g., anthropometric data, range data and 2D pictures. Given the individual information, the quality of the resulting individualized model depends on the quality of the generic model and the deformation technique used. In our study, we observe that the mathematical form in which the generic model is represented strongly determines the deformation effect and, thus, determines the quality of the resulting individualized models. During the past few years, the multiresolution modeling technique has been demonstrated to be a powerful tool for highly detailed sculptured object modeling. In our work, we adopt the multiresolution technique for generic head modeling and propose a feature-based deformation technique. We show that using our technique we can generate highly realistic individualized head models with speed and efficiency. We also demonstrate that our proposed technique can result in great efficiency for a wide range of downstream applications.