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Articles 361 - 379 of 379
Full-Text Articles in Databases and Information Systems
Modeling Multiple Granularities Of Spatial Objects, Chitra Ramalingam
Modeling Multiple Granularities Of Spatial Objects, Chitra Ramalingam
Electronic Theses and Dissertations
People conceptualize objects in an information space over different levels of details or granularities and shift among these granularities as necessary for the task at hand. Shifting among granularities is fundamental for understanding and reasoning about an information space. In general, shifting to a coarser granularity can improve one's understanding of a complex information space, whereas shifting to a more detailed granularity reveals information that is otherwise unknown. To arrive at a coarser granularity. objects must be generalized. There are multiple ways to perform generalization. Several generalization methods have been adopted from the abstraction processes that are intuitively carried out …
Mining Of Correlated Rules In Genome Sequences, L. Lin, L. Wong, Tze-Yun Leong, P. S. Lai
Mining Of Correlated Rules In Genome Sequences, L. Lin, L. Wong, Tze-Yun Leong, P. S. Lai
Research Collection School Of Computing and Information Systems
With the huge amount of data collected by scientists in the molecular genetics community in recent years, there exists a need to develop some novel algorithms based on existing data mining techniques to discover useful information from genome databases. We propose an algorithm that integrates the statistical method, association rule mining, and classification rule mining in the discovery of allelic combinations of genes that are peculiar to certain phenotypes of diseased patients.
Modeling Intersections Of Geospatial Lifelines, Ramaswam Hariharan
Modeling Intersections Of Geospatial Lifelines, Ramaswam Hariharan
Electronic Theses and Dissertations
Modeling moving objects involves spatio-temporal reasoning. The continuous movements of objects in space-time captured as discrete samples form geospatial lifelines. Existing lifeline models can represent the movement of objects between samples from most likely location to all possible locations. This thesis builds on a model called lifeline bead and necklace that captures all the possible locations of moving objects. Beads are 3-dimensional representations of an object's movements and a series of beads form a necklace. The extent of finding the possible locations is constrained by the speed of movement of the objects. Intersections of lifelines occur when two or more …
The Partial Evaluation Approach To Information Personalization, Naren Ramakrishnan, Saverio Perugini
The Partial Evaluation Approach To Information Personalization, Naren Ramakrishnan, Saverio Perugini
Computer Science Faculty Publications
Information personalization refers to the automatic adjustment of information content, structure, and presentation tailored to an individual user. By reducing information overload and customizing information access, personalization systems have emerged as an important segment of the Internet economy. This paper presents a systematic modeling methodology— PIPE (‘Personalization is Partial Evaluation’) — for personalization. Personalization systems are designed and implemented in PIPE by modeling an information-seeking interaction in a programmatic representation. The representation supports the description of information-seeking activities as partial information and their subsequent realization by partial evaluation, a technique for specializing programs. We describe the modeling methodology at a …
Using Raster Sketches For Digital Image Retrieval, James Carswell
Using Raster Sketches For Digital Image Retrieval, James Carswell
Electronic Theses and Dissertations
This research addresses the problem of content-based image retrieval using queries on image-object shape, completely in the raster domain. It focuses on the particularities of image databases encountered in typical topographic applications and presents the development of an environment for visual information management that enables such queries. The query consists of a user-provided raster sketch of the shape of an imaged object. The objective of the search is to retrieve images that contain an object sufficiently similar to the one specified in the query. The new contribution of this work combines the design of a comprehensive digital image database on-line …
Predictive Adaptive Resonance Theory And Knowledge Discovery In Databases, Ah-Hwee Tan, Hui-Shin Vivien Soon
Predictive Adaptive Resonance Theory And Knowledge Discovery In Databases, Ah-Hwee Tan, Hui-Shin Vivien Soon
Research Collection School Of Computing and Information Systems
This paper investigates the scalability of predictive Adaptive Resonance Theory (ART) networks for knowledge discovery in very large databases. Although predictive ART performs fast and incremental learning, the number of recognition categories or rules that it creates during learning may become substantially large and cause the learning speed to slow down. To tackle this problem, we introduce an on-line algorithm for evaluating and pruning categories during learning. Benchmark experiments on a large scale data set show that on-line pruning has been effective in reducing the number of the recognition categories and the time for convergence. Interestingly, the pruned networks also …
Personalizing The Gams Cross-Index, Saverio Perugini, Priya Lakshminarayanan, Naren Ramakrishnan
Personalizing The Gams Cross-Index, Saverio Perugini, Priya Lakshminarayanan, Naren Ramakrishnan
Computer Science Faculty Publications
The NIST Guide to Available Mathematical Software (GAMS) system at http://gams.nist .gov serves as the gateway to thousands of scientific codes and modules for numerical computation. We describe the PIPE personalization facility for GAMS, whereby content from the cross-index is specialized for a user desiring software recommendations for a specific problem instance. The key idea is to (i) mine structure, and (ii) exploit it in a programmatic manner to generate personalized web pages. Our approach supports both content-based and collaborative personalization and enables information integration from multiple (and complementary) web resources. We present case studies for the domain of linear, …
Investigating The Use Of Kalman Filtering Approaches For Dynamic Origin-Destination Trip Table Estimation, Pushkin Kachroo, Kaan Ozbay, Arvind Narayanan
Investigating The Use Of Kalman Filtering Approaches For Dynamic Origin-Destination Trip Table Estimation, Pushkin Kachroo, Kaan Ozbay, Arvind Narayanan
Electrical & Computer Engineering Faculty Research
This paper studies the applicability of Kalman filtering approaches for network wide traveler origin-destination estimation from link traffic volumes. The paper evaluates the modeling assumptions of the Kalman filters and examines the implications of such assumptions.
Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay
Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay
Electrical & Computer Engineering Faculty Research
A new method for performing dynamic traffic assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems which is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting.
Cascade Artmap: Integrating Neural Computation And Symbolic Knowledge Processing, Ah-Hwee Tan
Cascade Artmap: Integrating Neural Computation And Symbolic Knowledge Processing, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper introduces a hybrid system termed cascade adaptive resonance theory mapping (ARTMAP) that incorporates symbolic knowledge into neural-network learning and recognition. Cascade ARTMAP, a generalization of fuzzy ARTMAP, represents intermediate attributes and rule cascades of rule-based knowledge explicitly and performs multistep inferencing. A rule insertion algorithm translates if-then symbolic rules into cascade ARTMAP architecture. Besides that initializing networks with prior knowledge can improve predictive accuracy and learning efficiency, the inserted symbolic knowledge can be refined and enhanced by the cascade ARTMAP learning algorithm. By preserving symbolic rule form during learning, the rules extracted from cascade ARTMAP can be compared …
Inductive Neural Logic Network And The Scm Algorithm, Ah-Hwee Tan, Loo-Nin Teow
Inductive Neural Logic Network And The Scm Algorithm, Ah-Hwee Tan, Loo-Nin Teow
Research Collection School Of Computing and Information Systems
Neural Logic Network (NLN) is a class of neural network models that performs both pattern processing and logical inferencing. This article presents a procedure for NLN to learn multi-dimensional mapping of both binary and analog data. The procedure, known as the Supervised Clustering and Matching (SCM) algorithm, provides a means of inferring inductive knowledge from databases. In contrast to gradient descent error correction methods, pattern mapping is learned by an inductive NLN using fast and incremental clustering of input and output patterns. In addition, learning/encoding only takes place when both the input and output match criteria are satisfied in a …
The Quest For The Gnarl, Rudy Rucker
The Quest For The Gnarl, Rudy Rucker
SWITCH
The article describes some of the author’s own image-generating computer programs that he describes as “gnarly”. He began writing a simple spirograph program based off simple sine wave function called Spiro. Later transitioned into writing with C and better programs using more nonlinear feedback. Where Spiro is based on a simple sine wave function, Vine uses a nested sine function: the sine of the sine. The need for a more complicated computational approach lead to iteration and parallelism. Julgnarl uses Iteration and Calife uses parallelism. Calife shows one-dimensional cellular automata: spaces in which virtual computers are lined up like beads …
Gnarly Rantings About The Hacker And The Ants, Rudy Rucker
Gnarly Rantings About The Hacker And The Ants, Rudy Rucker
SWITCH
The article is an excerpt from Rucker’s book “The Happy Mutant”. It begins with his reflection of his career with GoMotion. He discusses the relation that he saw between design and cyberspace. Later he discusses his experience with a game a colleague found on the net: a virtual world where player is an ant. He talks about the struggles he goes through in this virtual world because of game difficulty and poor visuals. He ties it all in with how the Silicon Valley works in a similar way, and is filled with hackers and programers all needing each other to …
Book Review: Reasoning Agents In A Dynamic World: The Frame Problem. Kenneth M. Ford And Patrick J. Hayes, Eds.,, Jozsef A. Toth
Book Review: Reasoning Agents In A Dynamic World: The Frame Problem. Kenneth M. Ford And Patrick J. Hayes, Eds.,, Jozsef A. Toth
Jozsef A Toth Ph.D.
No abstract provided.
Rule Extraction: From Neural Architecture To Symbolic Representation, Gail A. Carpenter, Ah-Hwee Tan
Rule Extraction: From Neural Architecture To Symbolic Representation, Gail A. Carpenter, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper shows how knowledge, in the form of fuzzy rules, can be derived from a supervised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning, which simplifies the network structure by removing excessive recognition categories and weights; and quantization of continuous learned weights, which allows the final system state to be translated into a usable set of descriptive rules. Three benchmark studies illustrate the rule extraction methods: (1) Pima Indian diabetes diagnosis, (2) mushroom classification and (3) DNA promoter recognition. Fuzzy ARTMAP and ART-EMAP are compared with the ADAP algorithm, the k nearest neighbor system, …
A Greedy Hypercube-Labeling Algorithm, D. Bhagavathi, C. E. Grosch, S. Olariu
A Greedy Hypercube-Labeling Algorithm, D. Bhagavathi, C. E. Grosch, S. Olariu
Computer Science Faculty Publications
Due to its attractive topological properties, the hypercube multiprocessor has emerged as one of the architectures of choice when it comes to implementing a large number of computational problems. In many such applications, Gray-code labelings of the hypercube are a crucial prerequisite for obtaining efficient algorithms. We propose a greedy algorithm that, given an n-dimensional hypercube H with N=22 nodes, returns a Gray-code labeling of H, that is, a labeling of the nodes with binary strings of length n such that two nodes are neighbors in the hypercube if, and only if, their labels differ in exactly …
A Mergeable Double-Ended Priority Queue, S. Olariu, Z. Wen
A Mergeable Double-Ended Priority Queue, S. Olariu, Z. Wen
Computer Science Faculty Publications
An implementation of a double-ended priority queue is discussed. This data structure referred to as min–max–pair heap can be built in linear time; the operations Delete-min, Delete-max and Insert take O(log n) time, while Find-min and Find-max run in O(1) time. In contrast to the min-max heaps, it is shown that two min–max–pair heaps can be merged in sublinear time. More precisely, two min–max–pair heaps of sizes n and k can be merged in time O(log (n/k) * log k).
Pipelining Data Compression Algorithms, R. L. Bailey, R. Mukkamala
Pipelining Data Compression Algorithms, R. L. Bailey, R. Mukkamala
Computer Science Faculty Publications
Many different data compression techniques currently exist. Each has its own advantages and disadvantages. Combining (pipelining) multiple data compression techniques could achieve better compression rates than is possible with either technique individually. This paper proposes a pipelining technique and investigates the characteristics of two example pipelining algorithms. Their performance is compared with other well-known compression techniques.
Efficient Schemes To Evaluate Transaction Performance In Distributed Database Systems, R. Mukkamala, S. C. Bruell
Efficient Schemes To Evaluate Transaction Performance In Distributed Database Systems, R. Mukkamala, S. C. Bruell
Computer Science Faculty Publications
Database designers and researchers often need efficient schemes to evaluate transaction performance. In this paper, we chose two important performance measures: the average number of nodes accessed and the average number of data items accessed per node by a transaction in a distributed database system. We derive analytical expressions to evaluate these metrics. For general applicability, we consider partially replicated distributed database systems. Our first set of analytic results are closed-form expressions for these two measures. These are based on some fairly restrictive simplifying assumptions. When these assumptions are relaxed, no closed-form expressions exist for these averages. Hence, we develop …