2192459
Curriculum Knowledge Representation and Manipulation in Knowledge-Based Tutoring Systems
A knowledge-based tutoring system (KBTS) is a computer-based instructional system that uses artificial intelligence techniques to help people learn some subjects. We found that the knowledge communication process involving a KBTS and a human student can be decomposed into a series of communication cycles, where each cycle concentrates on one topic and contains four major phases: planning, discussing, evaluating and remedying. The major contributions of this work are the development of a generic architecture for supporting the knowledge communication between a KBTS and a student, and a graphical notation and schema for supporting the curriculum knowledge representation and manipulation during the planning phase of a tutoring process. The curriculum knowledge about a course can help a tutoring system determine the sequences in which the topics will be discussed with the students effectively and diagnose the students' mistakes. The curriculum knowledge base contains the goal structure of the course, prerequisite relations, and multiple ways of organizing topics, among others. As an example, we focus on developing SQL-TUTOR, a KBTS for the domain of SQL programming. This system has features such as an efficient control mechanism, explicit curriculum knowledge representation, and individualized private tutoring. For allowing the students relative freedom to decide how to study the domain knowledge about a subject, the system provides the students with a group of operators to hand-tailor the learning schedules according to their special backgrounds, requests, and interests.
14900181
Unordered tree mining with applications to phylogeny
Frequent structure mining (FSM) aims to discover and extract patterns frequently occurring in structural data, such as trees and graphs. FSM finds many applications in bioinformatics, XML processing, Web log analysis, and so on. We present a new FSM technique for finding patterns in rooted unordered labeled trees. The patterns of interest are cousin pairs in these trees. A cousin pair is a pair of nodes sharing the same parent, the same grandparent, or the same great-grandparent, etc. Given a tree T, our algorithm finds all interesting cousin pairs of T in O(|T|/sup 2/) time where |T| is the number of nodes in T. Experimental results on synthetic data and phylogenies show the scalability and effectiveness of the proposed technique. To demonstrate the usefulness of our approach, we discuss its applications to locating co-occurring patterns in multiple evolutionary trees, evaluating the consensus of equally parsimonious trees, and finding kernel trees of groups of phylogenies. We also describe extensions of our algorithms for undirected acyclic graphs (or free trees).
236203
New Techniques for DNA Sequence Classification
DNA sequence classification is the activity of determining whether or not an unlabeled sequence S belongs to an existing class C. This paper proposes two new techniques for DNA sequence classification. The first technique works by comparing the unlabeled sequence S with a group of active motifs discovered from the elements of C and by distinction with elements outside of C. The second technique generates and matches gapped fingerprints of S with elements of C. Experimental results obtained by running these algorithms on long and well conserved Alu sequences demonstrate the good performance of the presented methods compared with FASTA. When applied to less conserved and relatively short functional sites such as splice-junctions, a variation of the second technique combining fingerprinting with consensus sequence analysis gives better results than the current classifiers employing text compression and machine learning algorithms.
12680145
Finding Patterns in Three-Dimensional Graphs: Algorithms and Applications to Scientific Data Mining
Presents a method for finding patterns in 3D graphs. Each node in a graph is an undecomposable or atomic unit and has a label. Edges are links between the atomic units. Patterns are rigid substructures that may occur in a graph after allowing for an arbitrary number of whole-structure rotations and translations as well as a small number (specified by the user) of edit operations in the patterns or in the graph. (When a pattern appears in a graph only after the graph has been modified, we call that appearance "approximate occurrence.") The edit operations include relabeling a node, deleting a node and inserting a node. The proposed method is based on the geometric hashing technique, which hashes node-triplets of the graphs into a 3D table and compresses the label-triplets in the table. To demonstrate the utility of our algorithms, we discuss two applications of them in scientific data mining. First, we apply the method to locating frequently occurring motifs in two families of proteins pertaining to RNA-directed DNA polymerase and thymidylate synthase and use the motifs to classify the proteins. Then, we apply the method to clustering chemical compounds pertaining to aromatic compounds, bicyclicalkanes and photosynthesis. Experimental results indicate the good performance of our algorithms and high recall and precision rates for both classification and clustering.
2286283
Query result ranking over e-commerce web databases
To deal with the problem of too many results returned from an E-commerce Web database in response to a user query, this paper proposes a novel approach to rank the query results. Based on the user query, we speculate how much the user cares about each attribute and assign a corresponding weight to it. Then, for each tuple in the query result, each attribute value is assigned a score according to its "desirableness" to the user. These attribute value scores are combined according to the attribute weights to get a final ranking score for each tuple. Tuples with the top ranking scores are presented to the user first. Our ranking method is domain independent and requires no user feedback. Experimental results demonstrate that this ranking method can effectively capture a user's preferences.
11616193
Automatic Hierarchical Classification of Structured Deep Web Databases
We present a method that automatically classifies structured deep Web databases according to a pre-defined topic hierarchy. We assume that there are some manually classified databases, i.e., training databases, in every node of the topic hierarchy. Each training database is probed using queries constructed from the node titles of the topic hierarchy and the query result counts reported by the database are used to represent the content of the database. Hence, when adding a new database it can be probed by the same set of queries and classified to a node whose training databases are most similar to the new one. Specifically, a support vector machine classifier is trained on each internal node of the topic hierarchy with these training databases and the new database can be classified into the hierarchy top-down level by level. A feature extension method is proposed to create discriminant features. Experiments run on real structured Web databases collected from the Internet show that this classification method is quite accurate.
52854920
Integrated architectural modeling and analysis for high-assurance command and control system design
A Real-Time Architectural Specification (RAS) approach and its application to command and control (C2) systems are presented. Our objective is to establish a formal foundation that will enable us to integrate existing rich but fragmented formal techniques for system specification and verification into a practical and scaleable formal engineering method to support the design and development of highly reliable real-time distributed systems. The contribution of RAS is twofold: First, it provides a formal system that integrates system's timing requirements and requirements propagation into the process of architectural modeling and design in such a way that allows us to systematically enforce that the requirements are met in every step of the design process. Second, it offers an incremental and more scaleable approach for design modeling. These two features together make RAS a suitable model for the design of C2 systems. We further present an incremental method for verifying timing properties of an RAS model that helps to reduce the complexity of analysis both at a given design level and across different design levels.
44717149
Peer-to-Peer Support for File Transfer and Caching Mechanism
In existing Internet file transfer mechanism, proxy servers play a major role in load balancing and reducing duplicate file access requests for services like FTP and WWW. However, proxy servers are usually unaware of the availability of cached contents on other peer proxy servers. This is a waste of time since duplicate requests are needed. Unnecessary traffic can be reduced if cooperation and coordination among peer proxies can be utilized. In this paper, peer-to-peer support was incorporated in ordinary file transfer and caching mechanism to reduce unnecessary processing time and storage. Through the location service, hosts requesting file services can dynamically determine if a copy is available and its current location. Work load for file servers will be greatly reduced, and personalization of file transfer configuration can be fully supported.
8517678
Camera phone based motion sensing: interaction techniques, applications and performance study
This paper presents TinyMotion, a pure software approach for detecting a mobile phone user's hand movement in real time by analyzing image sequences captured by the built-in camera. We present the design and implementation of TinyMotion and several interactive applications based on TinyMotion. Through both an informal evaluation and a formal 17-participant user study, we found that 1. TinyMotion can detect camera movement reliably under most background and illumination conditions. 2. Target acquisition tasks based on TinyMotion follow Fitts' law and Fitts law parameters can be used for TinyMotion based pointing performance measurement. 3. The users can use Vision TiltText, a TinyMotion enabled input method, to enter sentences faster than MultiTap with a few minutes of practicing. 4. Using camera phone as a handwriting capture device and performing large vocabulary, multilingual real time handwriting recognition on the cell phone are feasible. 5. TinyMotion based gaming is enjoyable and immediately available for the current generation camera phones. We also report user experiences and problems with TinyMotion based interaction as resources for future design and development of mobile interfaces.
207156320
Livenotes: a system for cooperative and augmented note-taking in lectures
We describe Livenotes, a shared whiteboard system and educational practice that uses wireless communication and tablet computing to support real-time conversations within small groups of students during lectures, independent of class size. We present an interface design that enables group members to interact with one another by taking lecture notes cooperatively, as well as to augment student note-taking by providing instructor slides in the background to annotate over. Livenotes was designed to facilitate more efficient, stimulating modes of learning that other collaborative approaches do not. We report how the system impacts cooperative learning in an undergraduate class and how students interacted with background slides in the workspace. We conclude with directions for improving the system and learning practice.
12186597
A Power-Saving Multi-Radio Multi-Channel MAC Protocol for Wireless Local Area Networks
Opportunistic spectrum access and adaptive power management are effective techniques to improve throughput, delay performance, and energy efficiency for wireless networks. In this paper, we consider the joint design of opportunistic spectrum access and adaptive power management under the setting of multi-radio nodes and multi-channel wireless local area networks (WLANs) under the distributed coordination function (DCF) mode. This design problem is particularly challenging due to the conflicting nature of the multi-radio capability of a node, i.e., multiple radios improve throughput and delay performance at the cost of increased energy consumption. To address this problem, we propose a power-saving multi-channel MAC protocol (PSM-MMAC), which is capable of reducing the collision probability and the waiting time in the ‘awake’ state of a node, resulting in improved throughput, delay performance, and energy efficiency. The key ideas of PSM-MMAC are the following: we first estimate the number of active links; given this estimation as well as queue lengths and channel conditions, we appropriately select channels, radios, and power states (i.e., awake or doze state); then we optimize the medium access probability in p-persistent CSMA used in the data exchange. Another contribution of this paper is an analytical model that characterizes the throughput performance. Simulation results validate the accuracy of our analytical model and show that our proposed protocol is able to significantly improve both throughput and energy efficiency.