Showing papers on "Field (computer science) published in 2006"

3D distance fields: a survey of techniques and applications

Abstract: A distance field is a representation where, at each point within the field, we know the distance from that point to the closest point on any object within the domain. In addition to distance, other properties may be derived from the distance field, such as the direction to the surface, and when the distance field is signed, we may also determine if the point is internal or external to objects within the domain. The distance field has been found to be a useful construction within the areas of computer vision, physics, and computer graphics. This paper serves as an exposition of methods for the production of distance fields, and a review of alternative representations and applications of distance fields. In the course of this paper, we present various methods from all three of the above areas, and we answer pertinent questions such as How accurate are these methods compared to each other? How simple are they to implement?, and What is the complexity and runtime of such methods?.

Specifying a subset of dynamic inter-related data

Abstract: A natural language tool is provided for specifying a subset of data. The data may be dynamic and have elements which are inter-related. The inter-related data is specified using a natural language expression. The natural language tool enables a user to construct a natural language expression using embedded fields. A user may configure, add and remove fields within the expression. A natural language expression contains at least two configurable fields. The fields of an expression have a tiered relationship. When a higher tiered field is changed, one or more lower tiered fields may be changed in response to the higher field change.

VizRank: Data Visualization Guided by Machine Learning

Abstract: Data visualization plays a crucial role in identifying interesting patterns in exploratory data analysis. Its use is, however, made difficult by the large number of possible data projections showing different attribute subsets that must be evaluated by the data analyst. In this paper, we introduce a method called VizRank, which is applied on classified data to automatically select the most useful data projections. VizRank can be used with any visualization method that maps attribute values to points in a two-dimensional visualization space. It assesses possible data projections and ranks them by their ability to visually discriminate between classes. The quality of class separation is estimated by computing the predictive accuracy of k-nearest neighbor classifier on the data set consisting of x and y positions of the projected data points and their class information. The paper introduces the method and presents experimental results which show that VizRank's ranking of projections highly agrees with subjective rankings by data analysts. The practical use of VizRank is also demonstrated by an application in the field of functional genomics.

Comparison of computational intelligence based classification techniques for remotely sensed optical image classification

Abstract: Several computational intelligence components, namely neural networks (NNs), fuzzy sets, and genetic algorithms (GAs), have been applied separately or in combination to the process of remotely sensed data classification. By applying computational intelligence, we expect increased accuracy through the use of NNs, optimal NN structure and parameter determination via GAs, and transparency using fuzzy sets is expected. This paper systematically reviews and compares several configurations in the particular context of remote sensing for land cover. In addition, some of the configurations used here, such as NEFCASS and CANFIS, have few previous applications in the field. A comparison of the configurations is achieved by testing the different methods with exactly the same case-study data. A thorough assessment of results is performed by constructing an accuracy matrix for each training and testing data set. The evaluation of different methods is not only based on accuracy but also on compactness, completeness, and consistency. The architecture, produced rule set, and training parameters for the specific classification task are presented. Some comments and directions for future work are given

Object Categorization

Abstract: This article presents foundations, original research and trends in the field of object categorization by computer vision methods. The research goals in object categorization are to detect objects in images and to determine the object's categories. Categorization aims for the recognition of generic classes of objects, and thus has also been termed 'generic object recognition'. This is in contrast to the recognition of specific, individual objects. While humans are usually better in generic than in specific recognition, categorization is much harder to achieve for today's computer architectures and algorithms. Major problems are related to the concept of a 'visual category', where a successful recognition algorithm has to manage large intra-class variabilities versus sometimes marginal inter-class differences. It turns out that several techniques which are useful for specific recognition can also be adapted to categorization, but there are also a number of recent developments in learning, representation and detection that are especially tailored to categorization. Recent results have established various categorization methods that are based on local salient structures in the images. Some of these methods use just a 'bag of keypoints' model. Others include a certain amount of geometric modeling of 2D spatial relations between parts, or 'constellations' of parts. There is now a certain maturity in these approaches and they achieve excellent recognition results on rather complex image databases. Further work focused on the description of shape and object contour for categorization is only just emerging. However, there remain a number of important open questions, which also define current and future research directions. These issues include localization abilities, required supervision, the handling of many categories, online and incremental learning, and the use of a 'visual alphabet', to name a few. These aspects are illustrated by the discussion of several current approaches, including our own patch-based system and our boundary fragment-model. The article closes with a summary and a discussion of promising future research directions.

Visualizing the Computational Intelligence Field

Abstract: In this paper, we visualize the structure and the evolution of the computational intelligence (CI) field. Based on our visualizations, we analyze the way in which the CI field is divided into several subfields. The visualizations provide insight into the characteristics of each subfield and into the relations between the subfields. By comparing two visualizations, one based on data from 2002 and one based on data from 2006, we examine how the CI field has evolved over the last years. A quantitative analysis of the data further identifies a number of emerging areas within the CI field.

Intelligent Databases: Technologies and Applications

Abstract: With advances and in-depth applications of computer technologies, and the extensive applications of Web technology in various areas, databases have become the repositories of large volumes of data. It is very critical to manage data resources for effective problem solving and decision making. Collecting and presenting the latest research and development results from the leading researchers in the field of intelligent databases, ""Intelligent Databases: Technologies and Applications"" provides a single record of current research and practical applications in this field. ""Intelligent Databases: Technologies and Applications"" integrates data management in databases with intelligent data processing and analysis in artificial intelligence. This book challenges today's database technology and promotes its evolution.

Table For Storing Parameterized Product/Services Information Using Variable Field Columns

Abstract: Computer implemented systems store descriptions of multiple different types of marketplace items as a collection of parameter-value pairs, using a table having a plurality of rows and columns, wherein values for at least two of the items are stored in cells of first and second ones of the rows, respectively; keys that provide information that can be used to decipher differential mappings of a plurality of the columns to a plurality of parameters in different ones of the rows; and one or more interfaces that collectively display previously stored parameters and values to a human end-user.

A curriculum model for transferable skills development

Abstract: This paper presents a model of curriculum development which can be adapted to fit a teaching framework for developing skills at undergraduate level. The model presented is based upon research conducted in the field of engineering and is promoted here as a theoretical model of best practice for developing skills by providing a holistic view of skills development throughout the curricula. It shows how a progression of implemented strategies is required to complement undergraduate progression from dependent to autonomous learning. The model is jargon-free, which should augment its appeal within engineering and in other disciplines.

Towards automated record linkage

Abstract: The field of Record Linkage is concerned with identifying records from one or more datasets which refer to the same underlying entities. Where entity-unique identifiers are not available and errors occur, the process is non-trivial. Many techniques developed in this field require human intervention to set parameters, manually classify possibly matched records, or provide examples of matched and non-matched records. Whilst of great use and providing high quality results, the requirement of human input, besides being costly, means that if the parameters or examples are not produced or maintained properly, linkage quality will be compromised. The contributions of this paper are a critical discussion on the record linkage process, arguing for a more restrictive use of blocking in research, and evaluating and modifying the farthest-first clustering technique to produce results close to a supervised technique.

Admissible Heuristics for Automated Planning

Abstract: The problem of domain-independent automated planning has been a topic of research in Artificial Intelligence since the very beginnings of the field Due to the desire not to rely on vast quantities

Using a data mining algorithm to discover data rules

Abstract: Provided are a method, system, and article of manufacture for using a data mining algorithm to discover data rules. A data set including multiple records is processed to generate data rules for the data set. Each record has a record format including a plurality of fields and each rule provides a predicted condition for one field based on at least one predictor condition in at least one other field. The generated data rules are provided to a user interface to enable a user to edit the generated data rules. The data rules are stored in a rule repository to be available to use to validate data sets having the record format.

System for planning transfer of traffic of data on basis of packets along ascending communication line in radio communication system

Abstract: FIELD: system for distributing resources of frequencies band between various mobile stations, which realize radio communications with base station. ^ SUBSTANCE: in accordance to method, length of data queue is determined at each mobile station and information, connected to this length, is positioned in field, present in outbound data packet. On receipt of data packet in base station this field input deposited, and information about length of queue is used for distributing resources of frequencies band between connections to mobiles stations. ^ EFFECT: provision of fast dispensing of answers, connected to lengths of data queues. ^ 8 cl, 5 dwg

Natural language tool for specifying a subset of dynamic inter-related data

Abstract: A natural language tool is provided for specifying a subset of data. The data may be dynamic and have elements which are inter-related. The natural language tool enables a user to construct a natural language expression having embedded fields to specify the subset of data. A user may configure, add and remove fields within the expression. The natural language expression contains at least two configurable fields having a tiered relationship. The fields may be associated with type-ahead functionality and menu culling, field manipulation indicators to configure the number of fields in an expression, and matching data count information for a field or the entire expression.

Field-link autofill

Abstract: The invention provides a method for electronic form filling that enables users to enter data into one source form and have that data transferred into any number of electronic target forms. As the fields are linked through the invention, complete accuracy is provided for any single-entry multiple-target form interactions. The invention works regardless of data standards adoption; does not require target forms to ‘opt-in’; does not store any sensitive, private user information; and is not limited by the state-of-the-art in artificial-intelligence research.

Mining fuzzy sequential patterns from quantitative transactions

Abstract: Many researchers in database and machine learning fields are primarily interested in data mining because it offers opportunities to discover useful information and important relevant patterns in large databases. Most previous studies have shown how binary valued transaction data may be handled. Transaction data in real-world applications usually consist of quantitative values, so designing a sophisticated data-mining algorithm able to deal with various types of data presents a challenge to workers in this research field. In the past, we proposed a fuzzy data-mining algorithm to find association rules. Since sequential patterns are also very important for real-world applications, this paper thus focuses on finding fuzzy sequential patterns from quantitative data. A new mining algorithm is proposed, which integrates the fuzzy-set concepts and the AprioriAll algorithm. It first transforms quantitative values in transactions into linguistic terms, then filters them to find sequential patterns by modifying the AprioriAll mining algorithm. Each quantitative item uses only the linguistic term with the maximum cardinality in later mining processes, thus making the number of fuzzy regions to be processed the same as the number of the original items. The patterns mined out thus exhibit the sequential quantitative regularity in databases and can be used to provide some suggestions to appropriate supervisors.

Standard target sets for field sensor performance measurements

Abstract: The US Army Night Vision and Electronic Sensors Directorate (NVESD) Modeling and Simulation Division develops sensors models (FLIR 92, NV Therm, NV Therm IP) that predict the comparative performance of electro-optical sensors. The NVESD modeling branch developed a 12-vehicle, 12-aspect target signature set in 1998 with a known cycle criteria. It will be referred to as the 12-target set. This 12-target set has and will continue to be the modeling "gold standard" for laboratory human perception experiments supporting sensor performance modeling, and has been employed in dozens of published experiments. The 12-target set is, however, too costly for most acquisition field tests and evaluations. The authors developed an 8-vehicle 3-aspect target set, referred to as the 8- target set, and measured its discrimination task difficulty, (N50 and V50). Target identification (ID) range performance predictions for several sensors were made based on those V50/N50 values. A field collection of the 8-target set using those sensors provided imagery for a human perception study. The human perception study found excellent agreement between predicted and measured range performance. The goal of this development is to create a "silver standard" target set that is as dependable in measuring sensor performance as the "gold standard", and is affordable for Milestone A and other field trials.

Mapping of a transactional data model to a reporting data model

Abstract: Systems and techniques for mapping of a transactional data model to a reporting data model are described. In one aspect, an article includes one or more machine-readable media storing instructions operable to cause one or more machines to perform operations. The operations include receiving a transactional data model and a view that includes a collection of view fields, each view field referencing an object in the transactional data model, mapping one or more of a plurality of view fields in the collection to one or more of a plurality of data warehouse objects, and grouping the mapped data warehouse objects into a reporting data model.

Method and system for autocompletion of multiple fields in electronic forms

Abstract: A method and system for autocompletion of multiple fields in electronic forms that generates “inference networks” (Bayesian networks), and evaluates them to suggest likely options for user selection while filling out fields in corresponding electronic forms. The disclosed Bayesian networks are generated and evaluated based on a broad set of information. The information used by the disclosed system for generating an inference network includes form previously selected field values. The information used in the disclosed system to evaluate an inference networks while a current instance of a given form is being filled out includes values previously entered by a current user into preceding form fields, and values of ambient variables that are external to the forms, such as current day of the week, current time of day, etc. When the inference network is evaluated in this way, posterior probabilities are determined for values of fields not yet filled out in the current form instance. These posterior probabilities are used to present value options for the unfilled fields in a way that makes selection of the most-probable options convenient to the user.

Exploratory Mining in Cube Space

Abstract: Data Mining has evolved as a new discipline at the intersection of several existing areas, including Database Systems, Machine Learning, Optimization, and Statistics. An important question is whether the field has matured to the point where it has originated substantial new problems and techniques that distinguish it from its parent disciplines. In this paper, we discuss a class of new problems and techniques that show great promise for exploratory mining, while synthesizing and generalizing ideas from the parent disciplines. While the class of problems we discuss is broad, there is a common underlying objective-to look beyond a single data mining step (e.g., data summarization or model construction) and address the combined process of data selection and transformation, parameter and algorithm selection, and model construction. The fundamental difficulty lies in the large space of alternative choices at each step, and good solutions must provide a natural framework for managing this complexity. We regard this as a grand challenge for Data Mining, and see the ideas in this paper as promising initial steps towards a rigorous exploratory framework that supports the entire process. This is joint work with several people, in particular, Beechung Chen.

System and method for data sensitive filtering of patient demographic record queries

Abstract: A method for data sensitive filtering in patient database searches includes providing (71) a search criteria comprising one or more search locator fields, determining a retrieval formula from said search criteria that maximizes error tolerance in said search criteria while satisfying a predefined response time requirement, retrieving (72) said candidate records from said database, wherein if no retrieval formula can be found to satisfies said response time requirements, requesting additional search criteria, scoring (73) each said candidate record by comparing a search criteria locator field with a corresponding retrieved record field, determining (75) whether said score of said candidate record exceeds a predefined threshold, and if said candidate score does exceed said threshold, adding said candidate record to a list of records to be returned in response to said search criteria.

An Apparatus And Method For Processing Information From A Telephone Network

Abstract: In a telecommunications network having a radio access network (RAN) portion and a core network (CN) portion, data records are built (32) from messages monitored in the RAN portion, each data record including at least two different predetermined types of field values, such as time, location area, cause indicative of a cause of termination of a transaction within a call for which the data record is built, subscriber identity and at least one type of service. The data records are then enriched (38) by providing further information into the data records including at least an identifier for each predetermined type of field value in the data records. An OnLine Analytical Processing (OLAP) cube (46) is generated to allow a selected subset of the enriched data records to be accessed based on a desired combination of dimensions of types of field values and/or field value identifiers and the selected subset is then accessed to enable an aggregation function for at least one predetermined measure, such as volume of service usage, to be performed on the accessed enriched data records. A user interface (50) displays the results of the aggregation function for the selected subset and allows a user to access the enriched data records and the original data records to permit further detailed analysis of a problem.

Data Integration using Semantic Technology: A use case

Abstract: For the integration of data that resides in autonomous data sources Software AG uses ontologies. Data source ontologies describe the data sources themselves. Business ontologies provide an integrated view of the data. F-Logic rules are used to describe mappings between data objects in data source or business ontologies. Furthermore, F-Logic is used as the query language. F-Logic rules are perfectly suited to describe the mappings between objects and their properties. Some of these mapping rules can be generated automatically from the data sources meta data. Some patterns do frequently reoccur in user-defined mapping rules, for instance rules which establish inverse object relations or rules which create new object relations based on the objects' property values. Within our first project access to information is still typical data retrieval and not so much knowledge inference. Therefore, a lot of effort in this project concentrated on query functionality and even more on performance. But these are only first steps. To strengthen this development and to get more experience in this field Software AG recently joined several EU research projects which all have a focus on exploitation of semantic technology with concrete business cases

Animated picker for slider bars and two-dimensional pickers

Abstract: A computer program product for facilitating an expression of emotion in an application, is provided and calls for: providing a field for expressing a range of emotions; providing a location indicator for setting a location within the field; associating a unique expression of emotion with each location for the location indicator; and accepting a user input for changing a location of the location indicator to change the unique expression according to the emotion of the user.

April: an inductive logic programming system

Abstract: Inductive Logic Programming (ILP) is a Machine Learning research field that has been quite successful in knowledge discovery in relational domains. ILP systems use a set of pre-classified examples (positive and negative) and prior knowledge to learn a theory in which positive examples succeed and the negative examples fail. In this paper we present a novel ILP system called April, capable of exploring several parallel strategies in distributed and shared memory machines.

Generation of XML search profiles

Abstract: A system for generating a nested field record related to a corresponding data record is described. The system comprises a structured database for storing a plurality of the corresponding data records and a nested field record generator to query the structured database and generate the nested field record according to data selected from the corresponding data record. The nested field record generator also further derives and includes derived data from the corresponding data record in the nested field record.

Combining fields in known-item email search

Abstract: Emails are examples of structured documents with various fields. These fields can be exploited to enhance the retrieval effectiveness of an Information Retrieval (IR) system that mailing list archives. In recent experiments of the TREC2005 Enterprise track, various fields were applied to varying degrees of success by the participants. In his work, using a field-based weighting model, we investigate the retrieval performance attainable by each field, and examine when fields evidence should be combined or not.

Generation of quadratic potential force fields from flow fields for distributed manipulation

Abstract: Distributed manipulation systems induce motions on objects through the application of many external forces. Many of these systems are abstracted as planar programmable force fields. Quadratic potential fields form a class of such fields that lend themselves to analytical study and exhibit useful stability properties. This paper introduces a new methodology to build quadratic potential fields with simple devices using the naturally existing phenomena of airflow, which is an improvement to the traditional use of the complicated programmable actuator arrays. It also provides a basis for the exploitation, in distributed manipulation, of natural phenomena like airflow, which require rigorous analysis and display stability difficulties. A demonstration and verification of the theoretical results for the special case of the elliptic field with airflows is also presented.