ppxscal/embedding_network huggingface dataset:
Understanding Dubious Future Problems
Authors: Oğuz Mülâyim, Josep Lluís Arcos
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

Being able to predict the performance of a Case-Based Reasoning system against a set of future problems would provide invaluable information for design and maintenance of the system. Thus, we could carry out the needed design changes and maintenance tasks to improve future performance in a proactive fashion. This paper proposes a novel method for identifying regions in a case base where the system gives low confidence solutions to possible future problems. Experimentation is provided for RoboSoccer domain and we argue how encountered regions of dubiosity help us to analyse the case base and the reasoning mechanisms of the given Case-Based Reasoning system.
A PSO-Based Method for Min-ε Approximation of Closed Contour Curves
Authors: Bin Wang, Chaojian Shi, Jing Li
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

Finding a polygon to approximate the contour curve with the minimal approximation error &epsilon; under the pre-specified number of vertices, is termed min-&epsilon; problem. It is an important issue in image analysis and pattern recognition. A discrete version of particle swarm optimization (PSO) algorithm is proposed to solve this problem. In this method, the position of each particle is represented as a binary string which corresponds to an approximating polygon. Many particles form a swarm to fly through the solution space to seek the best one. For those particles which fly out of the feasible region, the traditional split and merge techniques are applied to adjust their position which can not only move the particles from the infeasible solution space to the feasible region, but also relocate it in a better site. The experimental results show that the proposed PSO-based method has the higher performance over the GA-based methods.
Mining Large-Scale Knowledge Sources for Case Adaptation Knowledge
Authors: David Leake, Jay Powell
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

Making case adaptation practical is a longstanding challenge for case-based reasoning. One of the impediments to widespread use of automated case adaptation is the adaptation knowledge bottleneck: the adaptation process may require extensive domain knowledge, which may be difficult or expensive for system developers to provide. This paper advances a new approach to addressing this problem, proposing that systems mine their adaptation knowledge as needed from pre-existing large-scale knowledge sources available on the World Wide Web. The paper begins by discussing the case adaptation problem, opportunities for adaptation knowledge mining, and issues for applying the approach. It then presents an initial illustration of the method in a case study of the testbed system WebAdapt. WebAdapt applies the approach in the travel planning domain, using OpenCyc, Wikipedia, and the Geonames GIS database as knowledge sources for generating substitutions. Experimental results suggest the promise of the approach, especially when information from multiple sources is combined.
Representing Service-Oriented Architectural Models Using Π-ADL
Authors: Marcos López-Sanz, Zawar Qayyum, Carlos E. Cuesta, Esperanza Marcos, Flavio Oquendo
Venue: Proceedings of the 2nd European conference on Software Architecture (2008)

Despite the well-known advantages of applying the MDA proposal to SOA developments, there are still some gaps that need to be filled. At PIM-level, for example, there is no possibility of having an executable version of the system as it solely comprises technologically independent models. In order to solve this we propose to formalize the architectural model at this level with &Pi; -ADL, an ADL supporting the description of dynamic and evolvable architectures like SOA itself is. Since &Pi; -ADL allows the definition of executable versions of the architecture, the specification written embodies a prototype of the system at the PIM-level. We illustrate this by describing a real case study based on the SMPP standard for sending SMS messages.
A General Algorithm to Recover External Camera Parameters from Pairwise Camera Calibrations
Authors: Jaume Vergés-Llahí, Toshikazu Wada
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

This paper presents a general constructive algorithm to recover external camera parameters from a set of pairwise partial camera calibrations embedded in the structure named Camera Dependency Graph (CDG) [1] that encompasses both the feasibility and the reliability of each calibration. An edge in CDG and its weight account for the existence and for the quality of the essential matrix between the two views connected by it, respectively. Any triplet of cameras sharing visible points forms a triangle in a CDG, which permits to compute the relative scale between any two of its edges. The algorithm first selects from CDG the set of feasible paths being the shortest ones in terms of reliability that also are connected by a sequence of triangles. The global external parameters of the arrangement of cameras are computed in a process in two steps that aggregates partial calibrations, represented by triangles, along the paths connecting pairs of views taking into account the relative scales between triangles until recovering the parameters between the extremes of each path. Finally, the scales of the whole set of paths are referred to one canonical value corresponding to the edge in the CDG working as the global scale. Initial experimental results on simulated data demonstrate the usefulness and accuracy of such scheme that can be applied either alone or as the initial approximation for other calibration methods.
Computational Methods for Determining Individuality
Authors: Sargur N. Srihari, Chang Su
Venue: Proceedings of the 2nd international workshop on Computational Forensics (2008)

Individuality is the state or quality of being an individual. We establish a computational methodology to determine whether a particular modality of data is sufficient to establish the individuality of every individual or even a demographic group. To test the individuality, generative models are given or learned to represent the distribution of certain characteristics such as birthday, human heights and fingerprints. Given the individuality assessments of different characteristic, the models based on multiple characteristics are proven to get strengthen individuality.
Search Query Generation with MCRDR Document Classification Knowledge
Authors: Yang Sok Kim, Byeong Ho Kang
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

The MCRDR (Multiple Classification Ripple-Down Rules) Classifier was developed to classify documents incrementally. A knowledge base of MCRDR-Classifier consists of two types of rules (refining and stopping rules), categories into which documents are classified, and cornerstone cases used for creating new rules. As document classification knowledge reflects user's preference for documents, it can be used to generate search queries to retrieve relevant web pages from public search engines. This research aims to propose various query generation methods using MCRDR knowledge base and evaluates them to choose the best one. For this purpose, search queries were generated from ten users' knowledge bases using the proposed query generation methods and then they were submitted to MSN web search service to retrieve search results. Search results were evaluated with discriminative power (how search results are distinctive?) and domain similarity (how search results are similar to the user's interest?) criteria to select the best query generation methods.
Approximate Reasoning for Efficient Anytime Induction from Relational Knowledge Bases
Authors: Nicola Mauro, Teresa M. Basile, Stefano Ferilli, Floriana Esposito
Venue: Proceedings of the 2nd international conference on Scalable Uncertainty Management (2008)

In most real-world applications the choice of the right representation language represents a fundamental issue, since it may give opportunities for generalization and make inductive reasoning computationally easier or harder. While the setting of First Order Logic (FOL) is the most suitable one to model the multi-relational data of real and complex domains, on the other hand it puts the question of the computational complexity of the knowledge induction that represents a challenge for multi-relational data mining algorithms. Indeed, the complexity of most real domains, in which a lot of relationships are required to model the objects involved, calls for both an efficient and effective search method for exploring the space of candidate solutions and a deduction procedure assessing the validity of the discovered knowledge. A way of tackling the complexity of such domains is to use a method that reformulates a multi-relational learning task into an attribute-value one. In this paper we propose an approximate reasoning technique that decreases the complexity of a relational problem changing both the language and the inference operation used for the deduction. The complexity of the FOL language is decreased by means of a stochastic propositionalization method, while the NP-completeness of the deduction is tackled using an approximate query evaluation. The induction is performed with an anytime algorithm, implemented by a population based method, able to efficiently extract knowledge from structured data in form of complete FOL definitions. The validity of the proposed technique has been proved making an empirical evaluation on a real-world dataset.
Improving Placeholders in Digital Documents
Authors: George Buchanan, Jennifer Pearson
Venue: Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries (2008)

Placeholders in physical documents provide critical support for the human reader in relocating material and their place in the text. However, the equivalent tools in digital documents have long been identified as suffering from unintuitive interactions and low rates of use. This paper evaluates the current bookmarking technologies found in digital document readers, and identifies a number of specific and significant shortcomings in their support for user activity. We introduce some simple interactions that close the gap between user requirements and the placeholder support in a simple document reader program. Through this, we demonstrate that improved interactions can be created that reduce the barriers that inhibit placeholder use in digital documents.
Group Decision Making: From Consistency to Consensus
Authors: F. Chiclana, F. Mata, S. Alonso, E. Herrera-Viedma, L. Martínez
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

In group decision making (GDM) processes, prior to the selection of the best alternative(s), it would be desirable that experts achieve a high degree of consensus or agreement between them. Due to the complexity of most decision making problems, individuals' preferences may not satisfy formal properties. Consistency is one of such properties, and it is associated with the transitivity property. Obviously, when carrying out a rational decision making, consistent information, i.e. information which does not imply any kind of contradiction, is more appropriate than information containing some contradictions. Therefore, in a GDM process, consistency should also be sought after.In this paper we present a consensus model for GDM problems that proceeds from consistency to consensus. This model includes a novel consistency reaching module based on consistency measures. In particular, the model generates advice on how experts should change their preferences in order to reach a solution with high consistency and consensus degrees.
CCTB: Context Correlation for Trust Bootstrapping in Pervasive Environment
Authors: Sheikh I. Ahamed, Mehrab Monjur, Mohammad Saiful Islam
Venue: Proceedings of the 2008 Sixth Annual Conference on Privacy, Security and Trust (2008)

Handheld devices in a pervasive computing environment are prone to security as well as privacy violations, while discovering, sharing and accessing services and contents. Trust models are devised to fight against such violations and breaches. Although initial trust assignment is an important issue in evolving overall trust, a little amount of work has been done in this field so far. In pervasive smart space, similar type of contexts exhibits significant correlations to each other. However, this fact is not taken into consideration while computing the initial trust values. In this paper, we describe a new mechanism to assign initial trust: CCTB (Context Correlation for Trust Bootstrapping), which takes advantage of the presence of correlations among different contexts in a context-ontology. We evaluate the effectiveness of CCTB by simulating in two different scenarios. We show that CCTB offers better initial trust values than the other models considered here. We also implement a prototype for performance measurement using .NET Compact Framework.
Estimation of Time and Cost Oriented Assembly Line Balancing Problem
Authors: Waldemar Grzechca
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

This paper deals with the time and cost oriented balancing of a singlel assembly line where a vast quantity of one single product has to be assembled. The cost-oriented assembly line balancing problem is a generalization of the time-oriented assembly line balancing problem. The objective in cost-oriented assembly line balancing consists in minimizing the total costs per unit. Author of this paper proposes to solve the problem in two ways. First, for a time-oriented problem it will be used some of heuristic methods (RPW, IUFF, Kilbridge&Wester, Moodie&Young) and next for cost-oriented problem it will be used some other heuristic methods given in literature. We should very often consider different measurements of balance ( time of line, smoothness index, line efficiency) to find the best given solution for the calculated problem. As a conclusion author proposes a new measurement method which connects results for time and cost-oriented balance methods.
A Real-Time Genetic Algorithm in Human-Robot Musical Improvisation
Authors: Gil Weinberg, Mark Godfrey, Alex Rae, John Rhoads
Venue: Computer Music Modeling and Retrieval. Sense of Sounds: 4th International Symposium, CMMR 2007, Copenhagen, Denmark, August 27-31, 2007. Revised Papers (2008)

The paper describes an interactive musical system that utilizes a genetic algorithm in an effort to create inspiring collaborations between human musicians and an improvisatory robotic xylophone player. The robot is designed to respond to human input in an acoustic and visual manner, evolving a human-generated phrase population based on a similarity driven fitness function in real time. The robot listens to MIDI and audio input from human players and generates melodic responses that are informed by the analyzed input as well as by internalized knowledge of contextually relevant material. The paper describes the motivation for the project, the hardware and software design, two performances that were conducted with the system, and a number of directions for future work.
Equalization of 8PSK Signals with a Recurrent Neural Network
Authors: Dong-Chul Park, Young-Soo Song, Dong-Min Woo
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

A novel equalization scheme for a wireless ATM communication channel using a recurrent neural network is proposed in this paper. The recurrent neural network used in this scheme is the Complex Bilinear Recurrent Neural Network (CBLRNN). A reduced version of the CBLRNN for faster and stable convergence is first proposed in this paper. The R-CBLRNN is then applied to equalization of a wireless ATM channel for 8PSK, which has severe nonlinearity and intersymbol interference due to multiple propagation paths. The experiments and results show that the proposed R-CBLRNN gives very favorable results in the Mean Square Error (MSE) criterion over conventional equalizers.
An Automated Refereeing and Analysis Tool for the Four-Legged League
Authors: Javier Ruiz-Del-Solar, Patricio Loncomilla, Paul Vallejos
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

The aim of this paper is to propose an automated refereeing and analysis tool for robot soccer. This computer vision based tool can be applied for diverse tasks such as: (i) automated game refereeing, (ii) computer-based analysis of the game, and derivation of game statistics, (iii) automated annotations and semantic descriptions of the game, which could be used for the automatic generation of training data for learning complex high-level behaviors, and (iv) automatic acquisition of real game data to be used in robot soccer simulators. The most attractive application of the tool is automated refereeing. In this case, the refereeing system is built using a processing unit (standard PC) and some static and/or moving video cameras. The system can interact with the robot players and with the game controller using wireless data communication, and with the human spectators and human second referees by speech synthesis mechanisms or using visual displays. We present a refereeing and analysis system for the RoboCup Four-Legged League. This system is composed by three modules: object perception, tracking, and action analysis. The camera placement issue is solved by human controlled camera's placement and movement. Some preliminary experimental results of this system are presented.
Efficient Predictive Control Integrated with Economic Optimisation Based on Neural Models
Authors: Maciej Ławryńczuk, Piotr Tatjewski
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

This paper presents a predictive control scheme integrated with economic optimisation. Two neural models are used: a dynamic one (for the control subproblem) and a steady-state one (for the economic optimisation subproblem). The algorithm is computationally efficient because it needs solving on-line only one quadratic programming problem. Unlike the classical control system structure, the necessity of repeating two nonlinear optimisation problems at each sampling instant is avoided.
Evaluation of the engineering aspects of Whirlwind I
Authors: Norman H. Taylor
Venue: Papers and discussions presented at the Dec. 10-12, 1951, joint AIEE-IRE computer conference: Review of electronic digital computers (1951)

The Whirlwind system is an expanding one now adding terminal equipment such as magnetic tapes, drums, and scopes. The core of the system including control, memory, and arithmetic element now has been running long enough to make an engineering evaluation of its performance, so the following comments will apply mainly to these three sections.
Requirements analysis: A practical object oriented approach
Authors: Ahmed M. Salem, Michael Olsen Darter
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

Most software projects fail due to incomplete, ambiguous and inconsistent requirements. The aim of the paper is to develop a practical approach for performing object oriented requirements analysis. The specific goal is to increase the accuracy, consistency, and completeness of software requirements by using a methodical step-by-step process that has a definite end point. Our proposed approach is followed by a case study to prove the applicability and the effectiveness of the proposed approach.
Reaction-diffusion cellular neural network models
Authors: Angela Slavova
Venue: Proceedings of the 9th WSEAS International Conference on Neural Networks (2008)

In this paper reaction-diffusion Cellular Neural Network models are considered. Dynamics and stability of such models are studied by applying describing function technique. Comparison of the obtained results with the classical ones is made as well.
DPA-Resistance Without Routing Constraints?
Authors: Benedikt Gierlichs
Venue: Proceedings of the 9th international workshop on Cryptographic Hardware and Embedded Systems (2007)

MDPL is a logic style claiming to provide resistance against Differential Side Channel Analysis on power consumption measurements. In this paper we show that the power consumption of a non-linear MDPL gate can be reliably exploited to determine signal values and hence secret data, if the random masks have a slight bias. We present an attack methodology and a case study on how to infer secret key bits of an MDPL secured AES-ASIC in practice by attacking a single MDPL AND gate in a VLSI circuit. Our attack is not based on frequently made assumptions on circuit "anomalies", but on the per definition unbalanced routing, realistic PRNG biases, and knowledge of the circuit layout.
Enhancing Case-Based, Collaborative Web Search
Authors: Oisín Boydell, Barry Smyth
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

This paper describes and evaluates a case-based approach to personalizing Web search by post-processing the results returned by a Web search engine to reflect the interests of a community of like-minded searchers. The search experiences of a community of users are captured as a case base of textual cases, which serves as a way to bias future search results in line with community interests.
The effects of speech recognition technology on the writing skills and attitudes of adolescents with learning disabilities
Authors: Steven Rinehart
Venue:  (2007)

This mixed methods study introduced speech recognition software to three adolescents with learning disabilities. The participants were taught to use Dragon Naturally Speaking (DNS), one of several commercially available speech recognition programs. This software has the capability to recognize a user&rsquo;s voice, transcribe his or her words into text, and make the text available in a word processing format where editing is possible through keyboard or voice commands. This process may help students with learning disabilities, especially in the area of written expression, circumvent the frustration of paper-pencil writing and empower them to express their ideas in written form. Data were collected from several sources: survey data, observations, interviews, written composition analysis, and a standardized test. The results of the data were used to examine the software&rsquo;s effects on the quality of participants&rsquo; written work as well as their attitudes and self-perceptions as writers. Accuracy of use was also calculated to determine whether these adolescents were able to acquire a level acceptable for efficient use of the software. The quality of written compositions improved when using DNS; the effect of on attitude and self-perception were tentative; and the accuracy rate attained for all participants was adequate for the effective use of the software and the accuracy rate for all participants was similar. These results offer hope for those students who face problems with written expression on a daily basis in public school classrooms across the nation.