ppxscal/embedding_network huggingface dataset:
A UML Profile for Knowledge-Based Systems Modelling
Authors: Mohd Syazwan Abdullah, Richard Paige, Chris Kimble, Ian Benest
Venue: Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications (2007)

The Knowledge engineering (KE) techniques are essentially based on the knowledge transfer approach, from domain experts directly to systems. However, this has been replaced by the modelling approach which emphasises using conceptual models to model the problem-solving skill of the domain expert. This paper discusses extending the Unified Modelling Language by means of a profile for modelling knowledge-based system in the context of Model Driven Architecture (MDA) framework. The profile is implemented using the eXecutable Modelling Framework (XMF) Mosaic tool. A case study from the health care domain demonstrates the practical use of this profile; with the prototype implemented in Java Expert System Shell (Jess). The paper also discusses the possible mapping of the profile elements to the platform specific model (PSM) of Jess and provides some discussion on the Production Rule Representation (PRR) standardisation work.
Linear quadratic Gaussian control of 2-dimensional systems
Authors: Ran Yang, Cishen Zhang, Lihua Xie
Venue: Multidimensional Systems and Signal Processing (2007)

The linear quadratic Gaussian (LQG) control for one-dimensional (1D) systems has been known to be one of the fundamental and significant methods in linear system theory. However, the LQG control problem for two-dimensional (2D) systems has not been satisfactorily solved due to their structural and dynamical complexity. In this paper, sufficient conditions for evaluation of the quadratic performance indices of 2D systems in terms of the system state and control variables are proposed. Using these conditions, systematic design methods for finite horizon and infinite horizon LQG controls of 2D systems are developed using a convex optimization method.
A monadic framework for delimited continuations
Authors: R. Kent Dyvbig, Simon Peyton Jones, Amr Sabry
Venue: Journal of Functional Programming (2007)

Delimited continuations are more expressive than traditional abortive continuations and they apparently require a framework beyond traditional continuation-passing style (CPS). We show that this is not the case: standard CPS is sufficient to explain the common control operators for delimited continuations. We demonstrate this fact and present an implementation as a Scheme library. We then investigate a typed account of delimited continuations that makes explicit where control effects can occur. This results in a monadic framework for typed and encapsulated delimited continuations, which we design and implement as a Haskell library.
A Multiple Models Approach for Adaptive Predictive Control of Networked Control Systems
Authors: Chunmao Li, Jian Xiao, Lili Chu, Junhua Liu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

A real-time, self-learning, multiple models adaptive predictive control algorithm is proposed for Networked Control Systems(NCS), which can deal with different distributions of time delay introduced by a communication network or a field bus. The algorithm keeps updating the dynamic models in a model bank, and uses an adaptive model to track the parameter changes of NCS. In the mean time, it uses another adaptive model to ensure the stability of the overall NCS. The convergence analysis shows that the algorithm will finally switch to and stop at a stable, adaptive model.
Errors Estimation Models for Embedded Software Development Projects
Authors: Kazunori Iwata, Toyoshiro Nakashima, Yoshiyuki Anan, Naohiro Ishii
Venue: Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications (2007)

In this study, we analyze and evaluate development data obtained in the course of "OMRON software Co.", that develops equipments used in financial markets, as well as data obtained during the development of software. Because of this, it is becoming very important for the softwaredevelopment corporations to find how to develop software efficiently while guaranteeing delivery time and quality, and holding down developing costs. Especially, estimating man-power of new projects and guaranteeing quality of software are important, because the estimation relates to costs and the quality relates to the reliability of corporations. In the field of embedded software, development techniques, management techniques, tools, testing techniques, reusing techniques, real time operating systems and so on have already been studied. However, there is few studies about the relationship between the development scales and the total errors using the data accumulated by past projects. Hence, we establish a model for the first trial to estimate the errors of a new project by using regression analysis.
Adaptive Execution of Stream Window Joins in a Limited Memory Environment
Authors: Fatima Farag, Moustafa A. Hammad
Venue: Proceedings of the 11th International Database Engineering and Applications Symposium (2007)

A sliding window join (SWJoin) is becoming an integral operation in every stream data management system. In some streaming applications the increasing volume of streamed data as well as the multiplicity of concurrent queries requires an adaptive SWJoin algorithm for the limited memory resources. Previous algorithms of SWJoin address the memory limitation by exploiting external-memory resources while imposing timely ordered arrival of input data streams. In this paper we propose an external-memory sliding-window join algorithm (EM-SWJoin) that addresses general arrival patterns of input streams and exploits disk-based data structures. The algorithm runs in two phases. The first phase partially joins the arriving data of one stream with the memory-resident data of the other streams. The second phase completes the processing of the partially joined data by considering the disk-resident data from the corresponding streams. Swapping from one phase to the other improves the response time of the input data. A comparative study between EM-SWJoin and other related algorithms illustrates the superiority of the proposed algorithm.
An Approach for Web Services Composition Based on QoS and Discrete Particle Swarm Optimization
Authors: Ming Chen, Zhen-wu Wang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

The discrete particle swarm optimization (DPSO) has many merits, for example simple, rapid convergence speed. This paper proposes an approach for web services composition based on Quality of Service (QoS) and DPSO. In the case of lots of web services, this approach has an obvious effect. The simulation results comparing with genetic algorithms (GAs) show that it can produce better results.
GKS The First Graphics Standard
Authors: P. R. Bono
Venue: IEEE Computer Graphics and Applications (1982)

For the first time, an international graphics standard is possible. After years of research and redesign, the GKS emerges as the most likely candidate.
Query-by-Pictorial-Example
Authors: Ning-San Chang
Venue: IEEE Transactions on Software Engineering (1980)

Query-by-Pictorial-Example is a relational query language introduced for manipulating queries regarding pictorial relations as well as conventional relations. In addition to the manipulating capabilities of the conventional query languages, queries can also be expressed in terms of pictorial examples through a display tenninal. Example queries are used to illustrate the language facilities.
Layerless Design of A Power-efficient Clustering Algorithm for Wireless Ad Hoc Networks under Fading
Authors: Chih-Cheng Tseng, Kwang-Cheng Chen
Venue: Wireless Personal Communications: An International Journal (2008)

Traditional wireless ad hoc network power-efficient design proceeds separately on access and clustering algorithms by assuming perfect distance (that is, no fading and channel impairments) at most. In this paper, we discard the traditional layer-concept to tackle this important power-efficient wireless ad hoc networks under shadow fading, by identifying distance between a node pair as a sort of random distance to accommodate fading effect, which of course can be considered as a cross-layer design from traditional concept. By deriving the probability distribution of the distance between two nodes and the probability distribution of the distances between nodes and a randomly selected common reference node, the impacts of shadow fading on the link connectivity and node degree of the randomly constructed network topology are studied. Next, we propose a critical node first (CNF) based clustering algorithm to organize such a shadow faded random network topology into a power-efficient network architecture. By taking the shadow fading effects into considerations, our results show that the cluster-based network architecture generated by the proposed CNF-based clustering algorithm is power-efficient since the required number of exchanges of the cluster maintenance overheads is reduced.
Quantization Complexity and Independent Measurements
Authors: B. Chandrasekaran
Venue: IEEE Transactions on Computers (1974)

It is known that, in general, the number of measurements in a pattern classification problem cannot be increased arbitrarily, when the class-conditional densities are not completely known and only a finite number of learning samples are available. Above a certain number of measurements, the performance starts deteriorating instead of improving steadily. It was earlier shown by one of the authors that an exception to this "curse of finite sample size" is constituted by the case of binary independent measurements if a Bayesian approach is taken and uniform a priori on the unknown parameters are assumed. In this paper, the following generalizations are considered: arbitrary quantization and the use of maximum likelihood estimates. Further, the existence of an optimal quantization complexity is demonstrated, and its relationship to both the dimensionality of the measurement vector and the sample size are discussed. It is shown that the optimum number of quantization levels decreases with increasing dimensionality for a fixed sample size, and increases with the sample size for fixed dimensionality.
SOSRA: Sewice-Oriented Semantic Representation Architecture
Authors: Lin Zhang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

Constructing an effective translation between dSfferent representations is the key point to overcome semantic heterogeneity in information integration systems. This paper puts forward an ontology based information representation architecture-SOSRA. It introduces a GA V (global as view) approach to solve the mapping between heterogeneous semi-structured data in the form of service, discusses the semantic representation algorithm and semantic mapping strategy emphatically. The implementation of SOSRA and its application to semantic integration system is given at the end of this paper to enhance information process accuracy and eficiency.
An Overview of the Tesseract OCR Engine
Authors: R. Smith
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

The Tesseract OCR engine, as was the HP Research Prototype in the UNLV Fourth Annual Test of OCR Accuracy[1], is described in a comprehensive overview. Emphasis is placed on aspects that are novel or at least unusual in an OCR engine, including in particular the line finding, features/classification methods, and the adaptive classifier.
Handling of inconsistent rules with an extended model of fuzzy reasoning
Authors: Nikhil R. Pal, Kuhu Pal (nee Dutta)
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (1999)

It may not always be possible for an expert to provide a set of completely consistent rules. Even if the rules are consistent, all rules may not have equal importance to control the system. Moreover, for a fuzzy controller, the rule-base is usually tuned through modification of membership functions. Effect of changing a membership function is global in the sense that it influences all rules that involve the membership function. Here we propose a very effective extension of the conventional fuzzy reasoning system with incorporation of an importance factor for each rule. This factor allows tuning of the system at the rule level. Of course, one can still tune the membership functions. It enables the system to cope with incorrect and/or incompatible rules and thereby enhances the robustness, flexibility and system modeling capability. The proposed model is quite general and can be used in different applications including control. In the present investigation, we demonstrate with extensive simulation how for a control application inconsistent rules can be dealt with.
Dynamic Optimization of Subquery Processing in Grid Database
Authors: Naijing Hu, Yingying Wang, Liang Zhao
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

Grid database is a new research area combined with the database techniques and Grid techniques, while traditional database query and optimization techniques couldn't fully satisfy the need of Grid database because of the dynamic properties of Grid Nodes. The paper brings forward a query plan model --NSN based on Petri net so as to describe the data relation between subquery and nodes. Based on NSN model paper further puts forward a three phases algorithm --TPs which can make dynamic optimization for subquery processing to fit for fluctuation of environment in grid , Finally the paper tests the algorithms through experiment.
Natural language processing for information retrieval: the time is ripe (again)
Authors: Matthew Lease
Venue: Proceedings of the ACM first Ph.D. workshop in CIKM (2007)

Paraphrasing van Rijsbergen [37], the time is ripe for another attempt at using natural language processing (NLP) for information retrieval (IR). This paper introduces my dissertation study, which will explore methods for integrating modern NLP with state-of-the-art IR techniques. In addition to text, I will also apply retrieval to conversational speech data, which poses a unique set of considerations in comparison to text. Greater use of NLP has potential to improve both text and speech retrieval.
On maximum mutual information speaker-adapted training
Authors: John McDonough, Matthias Wölfel, Emilian Stoimenov
Venue: Computer Speech and Language (2008)

In this work, we combine maximum mutual information parameter estimation with speaker-adapted training (SAT). As will be shown, this can be achieved by performing unsupervised estimation of speaker adaptation parameters on the test data, a distinct advantage for many recognition tasks involving conversational speech. We derive re-estimation formulae for the basic speaker-independent means and variances, the optimal regression class for each Gaussian component when multiple speaker-dependent linear transforms are used for adaptation, as well as the optimal feature-space transformation matrix for use with semi-tied covariance matrices. We also propose an approximation to the maximum likelihood and maximum mutual information SAT re-estimation formulae that greatly reduces the amount of disk space required to conduct training on corpora which contain speech from hundreds or thousands of speakers. We also present empirical evidence of the importance of combination speaker adaptation with discriminative training. In particular, on a subset of the data used for the NIST RT05 evaluation, we show that including maximum likelihood linear regression transformations in the MMI re-estimation formulae provides a WER of 35.2% compared with 39.1% obtained when speaker adaptation is ignored during discriminative training.
Robust H∞ fuzzy control of nonlinear systems with multiple time delays
Authors: Feng-Hsiag Hsiao
Venue: International Journal of Systems Science (2007)

A robustness design of fuzzy control via model-based approach is proposed in this article to overcome the effect of approximation error between multiple time-delay nonlinear systems and Takagi-Sugeno (T-S) fuzzy models. A stability criterion is derived based on Lyapunov's direct method to ensure the stability of nonlinear multiple time-delay systems especially for the resonant and chaotic systems. Positive definite matrices P and Rk of the criterion are obtained by using linear matrix inequality (LMI) optimization algorithms to solve the robust fuzzy control problem. In terms of the control scheme and this criterion, a fuzzy controller is then designed via the technique of parallel distributed compensation (PDC) to stabilize the nonlinear multiple time-delay system and the H∞ control performance is achieved at the same time. Finally, two numerical examples of the chaotic and resonant systems are demonstrated to show the concepts of the proposed approach.
Automatic Extraction and Matching of Control Points for Distortion Correction in Star-Background Image
Authors: Zun-yan Liu, Dan-pei Zhao, Zhi-guo Jiang, Jun-li Yang
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

Usually a typical geometry distortion will occur when images are captured because of inaccuracy of axis distance of lens in the optical camera lens. The problem is also obvious in star-background images, which necessitate distortion correction for subsequent analysis. In this paper, a new method based on starpoint matching is proposed to extract and match automatically control points in star-background images. We acquire automatically control point pairs using point matching between points in pre-corrected image and points in ideal image which relies on the catalog. This work extends applied domain of Hausdorff Distance (HD) which is one of commonly used measures for object matching. In our experiments, Least Trimmed Square HD (LTS-HD) was used in point matching, and the result is effective.
Off-line Signature Verification Using Enhanced Modified Direction Features in Conjunction with Neural Classifiers and Support Vector Machines
Authors: Vu Nguyen, Michael Blumenstein, Vallipuram Muthukkumarasamy, Graham Leedham
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

As a biometric, signatures have been widely used to identify people. In the context of static image processing, the lack of dynamic information such as velocity, pressure and the direction and sequence of strokes has made the realization of accurate off-line signature verification systems more challenging as compared to their on-line counterparts. In this paper, we propose an effective method to perform off-line signature verification based on intelligent techniques. Structural features are extracted from the signature's contour using the Modified Direction Feature (MDF) and its extended version: the Enhanced MDF (EMDF). Two neural network-based techniques and Support Vector Machines (SVMs) were investigated and compared for the process of signature verification. The classifiers were trained using genuine specimens and other randomly selected signatures taken from a publicly available database of 3840 genuine signatures from 160 volunteers and 4800 targeted forged signatures. A distinguishing error rate (DER) of 17.78% was obtained with the SVM whilst keeping the false acceptance rate for random forgeries (FARR) below 0.16%.
A Post Wavelet Iterative Filtering Map Super-resolution Algorithm
Authors: Li Pu, Weiqi Jin, Yushu Liu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

For some imaging system the number of detector array and pixel dimension of sensor are limit, super-resolution algorithm is regarded as a good choice to acquire image with higher resolution without changing hardware. These algorithms are especially used to get higher resolution image from low resolution original image, but at present the representative super-resolution algorithms must apply iterative operation and the calculation speed is quite low. To improve the image quality of restoration and calculation speed, this article first introduces Poisson maximum posteriori probability (MAP) algorithm, MARKOV Poisson maximum posteriori probability (MPMAP) algorithm and wavelet filtering theory. According to the study of MAP algorithm this article proposed a new algorithm combined MAP algorithm with wavelet filtering and it is called post-wavelet MAP algorithm (PWMAP). Test result proved that super-resolution restoration capability of this algorithm is better than MAP algorithm and calculation speed is much faster than MPMAP algorithm.
Evolution of SOA Concepts in Telecommunications
Authors: Thomas Magedanz, Niklas Blum, Simon Dutkowski
Venue: Computer (2007)

The telecommunications industry has always been service-oriented. However, the convergence-driven need to deliver seamless services across different access networks has forced operators to embrace new approaches, including the Intelligent Network, Web-services-based APIs, and most recently, the IP Multimedia Subsystem.
Architecture of an Experimental Office System: the Soft Display Word Processor
Authors: J. E. Shemer
Venue: Computer (1978)

This experimental microprocessor-based office system incorporates architectural features-such as memory paging and distributed processing-normally associated with large computer systems.
Managing Uncertain Expressions in Databases
Authors: Nauman A. Chaudhry, Moginraj Mohandas
Venue: Proceedings of the 11th International Database Engineering and Applications Symposium (2007)

Expressions are used in a range of applications like publish/subscribe, website personalization, etc. Integrating support for expressions in a database management system (DBMS) provides an efficient and scalable platform for applications that use expressions. Additionally, in many cases these applications can benefit from support for uncertain data and expressions. Current DBMS lack such support. In this paper, we investigate how expressions with uncertainty can be integrated in a DBMS and processed like other data stored in the DBMS. We describe the underlying theory and implementation of UNXS (UNcertain eXpression System), a system that we have developed to handle uncertainty in expressions and data. We first develop a theoretical model to compare previous efforts in supporting uncertainty in DBMS and publish/subscribe systems. We propose new techniques for matching uncertain expressions to uncertain data. We then describe an implementation that integrates this support in the PostgreSQL DBMS.