12595607
Sketch Recognition Based on Topological Spatial Relationship
In recognition of composite graphic objects, topological spatial relationships of their components play an important role. Although most researchers focus on binary topological relationships, they cannot carry all information of the internal structure of the compound objects. Therefore, we introduce the ternary relationship, which is a complement to the binary relationship, to describe composite graphic objects. Moreover, we provide a constrained partial permutation algorithm based on both the binary and ternary topological spatial relationships to recognize the sketchy objects input by users in an online manner. Experimental results show that this approach is both efficient and effective for online composite graphics recognition in our sketch-based graphics input system–SmartSketchpad.
11837218
Using Web Based Answer Hunting System to Promote Collaborative Learning
In this paper, we share our pedagogical experience to motivate and facilitate an interactive and collaborative learning atmosphere by using an answer hunting system. In the software engineering practice course we are teaching, a problem that may deteriorate the learning quality is that, the students lack the opportunities of communication and discussion with the instructor both in class and out of class since they do not have many common time slots. Therefore, a web based answer hunting system is carefully designed and built to facilitate the communications between the students and instructor, and among the students. This system is designed based on the Q&A competition metaphor. The students are encouraged to participate in the competition to learn more knowledge, share more knowledge, and earn more participation marks.
30505871
User Interest Detection on Web Pages for Building Personalized Information Agent
In this paper we propose a vision-based approach to detecting user’s interests on web pages. This approach first splits a web page into several blocks of topics according to visual cues and then analyzes the layout structure of the page based on these blocks. The user’s interests are detected according to his browsing behaviors on the blocks and the layout structure of the web page. A personalized information agent is also developed to automatically extract new content from those web pages according to the user’s interests. Our experiments show that our proposed approach to detecting user’s interests on web pages achieves satisfactory accuracy and the personalized information agent significantly saves user’s browsing time and improves user’s browsing experience.
1503292
A Potential IRI Based Phishing Strategy
We anticipate a potential phishing strategy by obfuscation of Web links using Internationalized Resource Identifier (IRI). In the IRI scheme, the glyphs of many characters look very similar while their Unicodes are different. Hence, certain different IRIs may show high similarity. The potential phishing attacks based on this strategy are very likely to happen in the near future with the boosting utilization of IRI. We report this potential phishing strategy to provoke much further dissections of related counter measures.
24959035
A Novel Constraint-Based Approach to Online Graphics Recognition
Online graphics recognition has become the key problem for pen-based user interface on small screen devices, such as PDA and Tablet PC. In this paper, a novel constraint-based approach to online graphics recognition is proposed. The key idea of our approach is that when the user is drawing a graphic object, the system can extract the constraints between primitives and basic shapes from the object and use these constraints to retrieve similar graphic objects from the database at run time. The user can then choose the standard object from the ranked list of results to replace his sketches before he finishes drawing all strokes of the object. For this purpose, we summarize three types of primitives and several types of basic shapes as the basic components of a graphic object. We also define a set of constraints between primitives and basic shapes to represent their structural relations. The algorithms for online constraint extraction and graphics recognition are also presented. Experimental results show that our approach is efficient for online graphics recognition and effective for improving the user’s productivity.
7021428
An online composite graphics recognition approach based on matching of spatial relation graphs
A spatial relation graph (SRG) and its partial matching method are proposed for online composite graphics representation and recognition. The SRG-based approach emphasizes three characteristics of online graphics recognition: partial, structural, and independent of stroke order and stroke number. A constrained partial permutation strategy is also proposed to reduce the computational cost of matching two SRGs, which is originally an NP-complete problem as is graph isomorphism. Experimental results show that our proposed SRG-based approach is both efficient and effective for online composite graphics recognition in our sketch-based graphics input system - SmartSketchpad.
893220
PathExpander: Architectural Support for Increasing the Path Coverage of Dynamic Bug Detection
Dynamic software bug detection tools are commonly used because they leverage run-time information. However, they suffer from a fundamental limitation, the path coverage problem: they detect bugs only in taken paths but not in non-taken paths. In other words, they require bugs to be exposed in the monitored execution. This paper makes one of the first attempts to address this fundamental problem with a simple hardware extension. First, we propose PathExpander, a novel design that dynamically increases the code path coverage of dynamic bug detection tools with no programmer involvement. As a program executes, PathExpander selectively executes non-taken paths in a sandbox without side effects. This enables dynamic bug detection tools to find bugs that are present in these non-taken paths and would otherwise not be detected. Second, we propose a simple hardware extension to control the huge overhead in its pure software implementation to a moderate level. To further minimize overhead, PathExpander provides an optimization option to execute non-taken paths on idle cores in chip multi-processor architectures that support speculative execution. To evaluate PathExpander, we use three dynamic bug detection methods: dynamic software-only checker (CCured), dynamic hardware-assisted checker (iWatcher) and assertions; and conduct side-by-side comparison with PathExpander's counterpart software implementation. Our experiments with seven buggy programs using general inputs that do not expose the tested bugs show that PathExpander is able to help these tools detect 21 (out of 38) tested bugs that are otherwise missed. This is because PathExpander increases the code coverage of each test case from 40% to 65% on average, based on the branch coverage metric. When applications are tested with multiple inputs, the cumulative coverage also significantly improves by 19%. We also show that PathExpander introduces modest false positives (4 on average) and overhead (less than 9.9%). The 3-4 orders of magnitude lower overhead compared with pure-software implementation further justifies the hardware design in PathExpander
6743275
An Infrastructure for Agent Collaboration in Open Environments
In this paper, we present a service composition tool which enables specification of composite services for users with limited programming skills. We view composite services as a loose form of teamwork of service provider agents coordinated by a personal user agent. Such view enables us to use an existing hierarchical model of teamwork as the basis for service composition. An extension to the current model of teamwork is also proposed to achieve flexible and robust execution of composite services in an open environment.
14227266
Thread-Level Speculation on a CMP can be energy efficient
Chip Multiprocessors (CMP) with Thread-Level Speculation (TLS) have become the subject of intense research. However, TLS is suspected of being too energy inefficient to compete against conventional processors. In this paper, we refute this claim. To do so, we first identify the main sources of dynamic energy consumption in TLS. Then, we present simple energy-saving optimizations that cut the energy cost of TLS by over 60% on average with minimal performance impact. The resulting TLS CMP, populated with four 3-issue cores, speeds-up full SPECint 2000 codes by 1.27 on average, while keeping the fraction of the chip's energy consumption due to TLS to only 20%. Compared to a 6-issue superscalar at the same frequency, the TLS CMP is on average faster, while consuming only 85% of its total on-chip power.
11440085
A Mapping Methodology for Designing Software Task Pipelines for Embedded Signal Processing
In this paper, we present a methodology for mapping an Embedded Signal Processing (ESP) application onto HPC platforms such that the throughput performance is maximized. Previous approaches used a linear pipelined execution model which restrict the mapping choices. We show that the “optimal” solution obtained under that model can be improved, using the proposed execution model. Based on the new model, a three-step task mapping methodology is developed. The methodology is demonstrated by designing Software Task Pipelines for modern radar and sonar signal processing applications. Experimental results show improved performance using our approach over those obtained by previous approaches.
11385703
Hardware Enhanced Mining for Association Rules
In this paper, we propose a hardware-enhanced mining framework to cope with many challenging data mining tasks in a data stream environment. In this framework, hardware enhancements are implemented in commercial Field Programmable Gate Array (FPGA) devices, which have been growing rapidly in terms of density and speed. By exploiting the parallelism in hardware, many data mining primitive subtasks can be executed with high throughput, thus increasing the performance of the overall data mining tasks. Simple operations like counting, which take a major portion of conventional mining execution time, can in fact be executed on the hardware enhancements very efficiently. Subtask modules that are used repetitively can also be replaced with the equivalent hardware enhancements. Specifically, we realize an Apriori-like algorithm with our proposed hardware-enhanced mining framework to mine frequent temporal patterns from data streams. The frequent counts of 1-itemsets and 2-itemsets are obtained after one pass of scanning the datasets with our hardware implementation. It is empirically shown that the hardware enhancements provide the scalability by mapping the high complexity operations such as subset itemsets counting to the hardware. Our approach achieve considerably higher throughput than traditional database architectures with pure software implementation. With fast increase in applications of mobile devices where power consumption is a concern and complicated software executions are prohibited, it is envisioned that hardware enhanced mining is an important direction to explore.