ppxscal/embedding_network huggingface dataset:
Tools and algorithms for mobile robot navigation with uncertain localization
Authors: Joel Burdick
Venue:  (2006)

The ability for a mobile robot to localize itself is a basic requirement for reliable long range autonomous navigation. This thesis introduces new tools and algorithms to aid in robot localization and navigation. I introduce a new range scan matching method that incorporates realistic sensor noise models. This method can be thought of as an improved form of odometry. Results show an order of magnitude of improvement over typical mobile robot odometry. In addition, I have created a new sensor-based planning algorithm where the robot follows the locally optimal path to the goal without exception, regardless of whether or not the path moves towards or temporarily away from the goal. The cost of a path is defined as the path length. This new algorithm, which I call "Optim-Bug", is complete and correct. Finally, I developed a new on-line motion planning procedure that determines a path to a goal that optimally allows the robot to localize itself at the goal. This algorithm is called "Uncertain Bug". In particular, the covariance of the robot's pose estimate at the goal is minimized. This characteristic increases the likelihood that the robot will actually be able to reach the desired goal, even when uncertainty corrupts its localization during movement along path. The robot's path is chosen so that it can use known features in the environment to improve its localization. This thesis is a first step towards bringing the tools of mobile robot localization and mapping together with ideas from sensor-based motion planning.
The Generation of G1 Cubic Bézier Curve Fitting for Thai Consonant Contour
Authors: Natasha Dejdumrong, Seksit Tongtar
Venue: Proceedings of the Geometric Modelling and Imaging (2007)

Conventionally, Thai consonants are composed of head and end of the consonant, closed loop, twists, curves and straight lines. Several well-known Thai fonts follow these traditional writing rules. However, these consonant features make it more difficult to obtain a set of G1-continuity cubic Bézier curves that fit to the contour of Thai consonants. In this study, JasmineUPC font has been chosen for the investigation because it provides some simplified features of Thai consonants such as head, closed loop and twist specification.
A New Approach to Decoding of BCH and Reed-Solomon Codes Using Syzygy
Authors: Il Ho Kim, Hyoung June Ko
Venue: Proceedings of the 2007 Data Compression Conference (2007)

We introduce a new approach to decoding of BCH and Reed-Solomon codes by using syzygy modules of matricies.
Periodical payment model using restricted proxy certificates
Authors: Grigori Goldman
Venue: Proceedings of the thirtieth Australasian conference on Computer science - Volume 62 (2007)

In this paper we shall introduce a new electronic payment concept based on the popular direct debit payment model, entitled periodical payments. The direct debit model currently in use online is neither secure nor flexible, and requires a leap of faith by the customer who must trust the merchant to behave honestly. Electronic direct debit request (DDR) forms are not signed by both parties in a binding manner, which means that merchants can change the terms of DDR agreements post-fact. Unsigned DDR agreements give the merchant unprecedented power over customer accounts with little recourse for dispute. In this paper we shall demonstrate how the use of restricted proxy certificates with cryptographic signatures can be adopted to support a new periodical payment model. A payment policy language is presented that is tailored towards specifying rules that govern precisely how and when merchants can access and transfer funds from customer accounts into their own. Using this model will ensure that mutually signed policies are instantly enforceable on every transaction within a payment period. There is a fundamental difference between this proposal and other electronic payment schemes. Most such schemes attempt to replicate the features of physical cash such as anonymity, and therefore focus on single payment transactions that simulate cash changing hands. Since direct debit is a popular payment choice, our proposal provides significant improvement to this essentially paper-based payment model that currently does not integrate well in a purely electronic world.
Proceedings of the 2007 workshop on Programming languages and analysis for security
Venue: Programming languages and analysis for security (2007)

It is my pleasure to present this proceedings of the 2nd ACM SIGPLAN Workshop on Programming Languages and Analysis for Security (PLAS 2007), which took place on June 14, 2007 in San Diego, California, USA. The workshop was held as part of ACM's Federated Computing Research Conference (FCRC), as a satellite event of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2007). The call for papers solicited submissions of three kinds: full-length technical papers for relatively mature work; short papers for less detailed or more preliminary work; and proposals for informal presentations to be given at the workshop but not to appear in the proceedings. The last category was designed to support the discussion of important and promising ideas at the workshop, even if the ideas were not yet ready for formal publication. Papers submitted to one category could be accepted in a different category at the program committee's discretion We received 28 submissions from researchers at locations around the world. The submissions were comprised of 19 full-length papers, 6 short papers, and 3 informal presentations. One full paper was withdrawn prior to being reviewed. The committee ultimately accepted 10 full-length papers, 3 short papers, and 1 informal presentation. The submitted papers encompassed a variety of topics, including: inferring and enforcing information flow properties in programming languages, statically analyzing software for security vulnerabilities, specifying and enforcing security policies in software, intrusion detection, and models of declassification. Many committee members commented to me on the high quality of the papers we received. I am confident you will be impressed with the strength of the final program contained within these pages
Update Conscious Bitmap Indices
Authors: Guadalupe Canahuate, Michael Gibas, Hakan Ferhatosmanoglu
Venue: Proceedings of the 19th International Conference on Scientific and Statistical Database Management (2007)

Bitmap indices have been widely used in several domains such as data warehousing and scientific applications due to their efficiency in answering certain query types over large data sets. However, their utilization has been largely limited to read-only data sets or to static snapshots of data due to the cost associated with the update and append of new data. Typically, several bitmaps are associated with each indexed attribute in a table, i.e. one for each attribute value, bin, or range. Each one of these bitmaps needs to be updated to reflect a new, appended row. Since a given table could be represented by hundreds or even thousands of bitmaps, the insertion of a single record can be prohibitively costly. In order to transfer the fast query response times offered by bitmap indices to dynamic database domains, we propose an update conscious bitmap index that provides a mechanism to quickly update bitmaps to reflect dynamic database changes. For an insert operation only the bitmaps that represent the values being inserted need to be updated. We formalize the insert and delete operations of the proposed technique and provide a cost model for bitmap updates. We compare the update conscious bitmaps to traditional bitmaps in terms of storage space, update performance, and query execution time.
Secured Information Flow for Asynchronous Sequential Processes
Authors: Isabelle Attali, Denis Caromel, Ludovic Henrio, Felipe Luna Del Aguila
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

We present in this article a precise security model for data confidentiality in the framework of ASP (Asynchronous Sequential Processes). ASP is based on active objects, asynchronous communications, and data-flow synchronizations. We extend it with security levels attached to activities (active objects) and transmitted data. We design a security model that guarantees data confidentiality within an application; this security model takes advantages of both mandatory and discretionary access models. We extend the semantics of ASP with predicate conditions that provide a formal security framework, dynamically checking for unauthorized information flows. As a final result, all authorized communication paths are secure: no disclosure of information can happen. This theoretically-founded contribution may have a strong impact on distributed object-based applications, that are more and more present and confidentiality-demanding on the Internet, it also arises a new issue in data confidentiality: authorization of secured information flow transiting (by the mean of futures) through an unsecured component.
A Greedy Correlation-Incorporated SVM-Based Algorithm for Gene Selection
Authors: Mingjun Song, Sanguthevar Rajasekaran
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 01 (2007)

Microarrays serve scientists as a powerful and efficient tool to observe thousands of genes and analyze their activeness in normal or cancerous tissues. In general microarrays are used to measure the expression levels of thounsands of genes in a cell mixture. Gene expression data obtained from microarrys can be used for various applications. One such application is that of gene selection. Gene selection is very similar to the feature selection problem addressed in the machine learning area. In a nutshell gene selection is the problem of identifying a minimum set of genes that are responsible for certain events (for example the presence of cancer). Informative gene selection is an important problem arising in the analysis of microarray data. In this paper, we present a novel algorithm for gene selection that combines support vector machines with gene correlations. Experiments show that the new algorithm, called GCI-SVM, obtains a higher classification accuracy using a smaller number of selected genes than the well-known algorithms in the literature.
The partitioned dynamic-priority scheduling of sporadic task systems
Authors: Sanjoy K. Baruah, Nathan Wayne Fisher
Venue: Real-Time Systems (2007)

A polynomial-time algorithm is presented for partitioning a collection of sporadic tasks among the processors of an identical multiprocessor platform. Since the partitioning problem is NP-hard in the strong sense, this algorithm is unlikely to be optimal. A quantitative characterization of its worst-case performance is provided in terms of resource augmentation.
Goal-Driven Software Development
Authors: Ingo Schnabel, Markus Pizka
Venue: Proceedings of the 30th Annual IEEE/NASA Software Engineering Workshop (2006)

Established software development processes focus on delivering software within time and budget according to a set of requirements. However, practical experiences show that neither business processes nor requirements can be fully understood in an early stage of a realistic software project. This is not primarily due to inadequate requirements elicitation but the fact that the technical implementation constitutes a formalization of a more or less fuzzy business domain revealing gaps and inconsistencies. Furthermore, the technology used adds constraints and enables new processes. Hence, trying to set the requirements in advance causes change requests, cost and time overruns, or even project cancellation. This paper continues the line of thought of iterative process models by regarding software development as a process iteratively converging business goals and technology from both sides. This "goal-driven process" is successfully applied in real-life commercial software projects and has repeatedly contributed to low cost but high quality software.
Spontaneous speech understanding for robust multi-modal human-robot communication
Authors: Sonja Hüwel, Britta Wrede
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

This paper presents a speech understanding component for enabling robust situated human-robot communication. The aim is to gain semantic interpretations of utterances that serve as a basis for multi-modal dialog management also in cases where the recognized word-stream is not grammatically correct. For the understanding process, we designed semantic processable units, which are adapted to the domain of situated communication. Our framework supports the specific characteristics of spontaneous speech used in combination with gestures in a real world scenario. It also provides information about the dialog acts. Finally, we present a processing mechanism using these concept structures to generate the most likely semantic interpretation of the utterances and to evaluate the interpretation with respect to semantic coherence.
Ontology-Based Service Representation and Selection
Authors: Murat Şensoy, Pınar Yolum
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

Selecting the right parties to interact with is a fundamental problem in open and dynamic environments. The problem is amplified when the number of interacting parties is high, and the parties' reasons for selecting others vary. We examine the problem of service selection in an e-commerce setting where consumer agents cooperate to identify service providers that would satisfy their service needs the most. Previous approaches to service selection are usually based on capturing and exchanging the ratings of consumers to providers. Rating-based approaches have two major weaknesses. 1) ratings are given in a particular context. Even though the context is crucial for interpreting the ratings correctly, the rating-based approaches do not provide the means to represent the context explicitly. 2) The satisfaction criteria of the rater is unknown. Without knowing the expectation of the rater, it is almost impossible to make sense of a rating. We deal with these two weaknesses in two steps. First, we extend a classical rating-based approach by adding a representation of context. This addition improves the accuracy of selected service providers only when two consumers with the same service request are assumed to be satisfied with the same service. Next, we replace ratings with detailed experiences of consumers. The experiences are represented with an ontology that can capture the requested service and the received service in detail. When a service consumer decides to share her experiences with a second service consumer, the receiving consumer evaluates the experience by using her own context and satisfaction criteria. By sharing experiences rather than ratings, the service consumers can model service providers more accurately and, thus, can select service providers that are better suited for their needs.
P Systems and Finite Automata
Authors: Xian Xu
Venue: Proceedings of the First International Conference on Complex, Intelligent and Software Intensive Systems (2007)

In this paper, we integrate the traditional finitestate automata (words, or string based) into the membrane computing paradigm, as previous work prevalently concentrated on multiset based automata. We apply P systems with string objects (worms) to implement finite automata, that is, simulating their running, showing that P systems with string objects can properly hold the computability of finite automata. We give the concept of P system with string objects and finite automata, describe the implementation details, and finally make some future work expectation.
Robust voice activity detection using perceptual wavelet-packet transform and Teager energy operator
Authors: Shi-Huang Chen, Hsin-Te Wu, Yukon Chang, T. K. Truong
Venue: Pattern Recognition Letters (2007)

In this letter, a robust voice activity detection (VAD) algorithm is presented. This proposed VAD algorithm makes use of the perceptual wavelet-packet transform and the Teager energy operator to compute a robust parameter called voice activity shape for VAD. The main advantage of this algorithm is that the preset threshold values or a priori knowledge of the SNR usually needed in conventional VAD methods can be completely avoided. Various experimental results show that the proposed VAD algorithm is capable of outperforming the VAD of Adaptive Multi Rate (AMR) speech codec in both additive noisy and real noisy environments.
Cost-based Optimization of Complex Scientific Queries
Authors: Ruslan Fomkin, Tore Risch
Venue: Proceedings of the 19th International Conference on Scientific and Statistical Database Management (2007)

High energy physics scientists analyze large amounts of data looking for interesting events when particles collide. These analyses are easily expressed using complex queries that filter events. We developed a cost model for aggregation operators and other functions used in such queries and show that it substantially improves performance. However, the query optimizer still produces suboptimal plans because of estimate errors. Furthermore, the optimization is very slow because of the large query size. We improved the optimization by a profiled grouping strategy where the scientific query is first automatically fragmented into subqueries based on application knowledge. Each fragment is then independently profiled on a sample of events to measure real execution cost and cardinality. An optimized fragmented query is shown to execute faster than a query optimized with the cost model alone. Furthermore, the total optimization time, including fragmentation and profiling, is substantially improved.
The use of scalable source routing for networked sensors
Authors: T. Fuhrmann
Venue: Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors (2005)

In this paper, we briefly present a novel routing algorithm, scalable source routing (SSR), which is capable of memory and message efficient routing in networks with 'random topology'. This algorithm enables sensor networks to use recent peer to-peer mechanisms from the field of overlay networks, like e.g. distributed hash tables and indirection infrastructures. Unlike other proposals along that direction, SSR integrates all necessary routing tasks into one simple, highly efficient routing protocol. Simulations demonstrate that in a small-world network with more than 100 000 nodes, SSR requires each node to only store routing data for 255 other nodes to establish routes between arbitrary pairs of nodes. These routes are on average only about 20-30% longer than the globally optimal path between these nodes.
The Application of 3D range images in the interior design practice
Authors: Naai-Jung Shih, Je-Zen Hu
Venue: Proceedings of the 11th International Conference Information Visualization (2007)

The study applies 3D range technology to improve efficiency in interior design and construction with better accuracy and quality. The feasibility of as-built range data was used for visual inspection and drawing production. The technology improved measurement accuracy, retrieved unreachable coordinates, controlled working schedule, compared construction with design, and facilitated follow-up interior maintenance and management over Internet. This study also showed that only accurate design specifications can meet design requirements and prevent construction error. Accurate as-built data solve design problems and control construction quality without increasing budget.
AFDM Approach for Experience Inclusion in Learning Controllers
Authors: S. Gopinath, I. N. Kar, R. K. P. Bhatt
Venue: Proceedings of the International Conference on Computing: Theory and Applications (2007)

In this paper a new method of experience inclusion in iterative learning controllers (ILC) is proposed. Approximate Fuzzy Data Model (AFDM) technique has been adopted for the process of initial input selection. Instead of zero initial input assumption as in most of the ILC algorithms, in this paper the idea of using past trajectory tracking experiences in the selection of initial input for tracking a new trajectory tracking task has been highlighted. Performance of the proposed AFDM based ILC approach, on initial error reduction and error convergence issues are proved. Comparison with existing local learning technique on the selection of initial input for ILC algorithm proves the efficacy of the proposed AFDM based method.
To each his own: The caregiver's role in a computational model of gaze following
Authors: Christof Teuscher, Jochen Triesch
Venue: Neurocomputing (2007)

We investigate a computational model of the emergence of gaze following that is based on a generic basic set of mechanisms. Whereas much attention has been focused so far on the study of the infant's behavior, we systematically analyze the caregiver and show that he plays a crucial role in the development of gaze following in our model, especially for infant models with simulated developmental disorders such as autism and Williams syndrome. We first create two reference infant parameter sets and test their behavior with a simple standard caregiver. Based on these findings we then propose new caregiver models and evaluate them on normally developing infants and on infants with simulated developmental disorders. Further, we investigate if and how a pair of infants (with and without simulated developmental disorders) might learn gaze following from scratch, without a mature caregiver. The findings of this paper suggest the pivotal role the caregiver plays for the infant in developing gaze following, that his predictability is the most important criterion, and that different infant models require particular caregivers for gaze following to emerge optimally. Our simulations are consistent with Leekam's finding, that autistics can learn to follow gaze through a contingent presentation of rewarding visual stimuli, but that a lack of motivation may impede learning.
Development of data analysis algorithms for interpretation of ground-penetrating radar data
Authors: Imad L. Al-Qadi, Gary S. Brown
Venue:  (2003)

According to a 1999 Federal Highway Administration statistic, the U.S. has around 8.2 million lane-miles of roadways that need to be maintained and rehabilitated periodically. Therefore, in order to reduce rehabilitation costs, pavement engineers need to optimize the rehabilitation procedure, which is achieved by accurately knowing the existing pavement layer thicknesses and localization of subsurface defects. Currently, the majority of departments of transportation (DOTs) rely on coring as a means to estimate pavement thicknesses, instead of using other nondestructive techniques, such as Ground Penetrating Radar (GPR). The use of GPR as a nondestructive pavement assessment tool is limited mainly due to the difficulty of GPR data interpretation, which requires experienced operators. Therefore, GPR results are usually subjective and inaccurate. Moreover, GPR data interpretation is very time-consuming because of the huge amount of data collected during a survey and the lack of reliable GPR data-interpretation software. This research effort attempts to overcome these problems by developing new GPR data analysis techniques that allow thickness estimation and subsurface defect detection from GPR data without operator intervention. The data analysis techniques are based on an accurate modeling of the propagation of the GPR electromagnetic waves through the pavement dielectric materials while traveling from the GPR transmitter to the receiver. Image-processing techniques are also applied to detect layer boundaries and subsurface defects. The developed data analysis techniques were validated utilizing data collected from an experimental pavement system: the Virginia Smart Road. The layer thickness error achieved by the developed system was around 3%. The conditions needed to achieve reliable and accurate results from GPR testing were also established.