ppxscal/embedding_network huggingface dataset:
PDF document restoration and optimization during image enhancement
Authors: Hui Chao, Carl Staelin, Sagi Schein, Marie Vans, John Lumley
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

We present a document processing method that addresses some of the practical challenges in image enhancement for digital photo album in PDF documents. With the advent of digital offset presses, consumer photo books are becoming increasingly popular, and most such workflows convert the consumer's photos and layout into PDF documents. In order to produce appealing photo albums from consumer photographs, some form of automatic enhancement is usually required, and this enhancement is often done late in the workflow just before printing, and therefore it is done on the PDF file. If each and every PDF generation tool simply inserted a single complete image each time an image appeared in the document, then the process of opening a PDF document, iterating through the document, extracting, enhancing, and replacing images, and then saving the enhanced document would be relatively easy. Unfortunately, PDF generation tools often violate that assumption in two ways. Firstly, large images are often written as a set of small images in strips or tiles, which visually appear to be a single image. Secondly, an image in a PDF document may be reused in the document on different position and pages; directly enhancing images without the consideration of the reuse model could result in great increase in the document size and poor system performance. Therefore, image reconstruction and document optimization were performed in our PDF photo album enhancement solution.
Phase Transitions Caused by Threshold in Random Neural Network and Its Medical Applications
Authors: Guangcheng Xi, Jianxin Chen
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

In this paper, we detect threshold-driven phase transitions in the homogeneous random neural network. When the neurons are arranged as one dimension, the critical threshold is two, while in two dimensions counterpart, the critical threshold is four. We declare that random neural network is a specific case of Abstract neural automata. So we conclude that phase transitions in the random neural network can produce thought in human brain. We successfully apply the network to interpret the relation between diseases and syndrome in Traditional Chinese Medicine.
Detection of pre-defined boundaries between hydrothermal alteration zones using rotation-variant template matching
Authors: Frank J. A. van Ruitenbeek, Harald M. A. van der Werff, Kim A. A. Hein, Freek D. van der Meer
Venue: Computers Geosciences (2008)

A new method for the detection of pre-defined boundaries in single-band image data that uses a rotation-variant template matching (RTM) algorithm is presented. This algorithm matches a miniature image of a pre-defined boundary to image data at various orientations. The image pixels that match boundary criteria are reported in output imagery together with the rotation angle of the template. The method is applied to identify boundaries between hydrothermal alteration zones in processed airborne hyperspectral imagery, based on the presence of white mica minerals. Results show that boundaries identified with RTM are relatively free of noise and more coherent than those identified with, for instance, image slicing techniques. Identified boundaries can be used for image segmentation. The output of the RTM algorithm also provides information on the type of boundary, whether it is crisp or gradual. This information can be used to better characterize mineral variation in the alteration halo associated with fossil hydrothermal systems.
1: -3 resonant centers on C2 with homogeneous cubic nonlinearities
Authors: Zhaoping Hu, Valery G. Romanovski, Douglas S. Shafer
Venue: Computers Mathematics with Applications (2008)

We characterize the collection of systems of differential equations on C^2 of the form x@?=x+p(x,y), y@?=-3y+q(x,y), where p and q are homogeneous polynomials of degree three (either of which may be zero), that possess a first integral in a neighborhood of (0,0) of the form x^3y+..., where omitted terms are of order at least five. Such systems are called 1:-3 resonant centers.
Visualizing and Evaluating Complexity of Textual Case Bases
Authors: Sutanu Chakraborti, Ulises Cerviño Beresi, Nirmalie Wiratunga, Stewart Massie, Robert Lothian, Deepak Khemani
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

This paper deals with two relatively less well studied problems in Textual CBR, namely visualizing and evaluating complexity of textual case bases. The first is useful in case base maintenance, the second in making informed choices regarding case base representation and tuning of parameters for the TCBR system, and also for explaining the behaviour of different retrieval/classification techniques over diverse case bases. We present an approach to visualize textual case bases by "stacking" similar cases and features close to each other in an image derived from the case-feature matrix. We propose a complexity measure called GAME that exploits regularities in stacked images to evaluate the alignment between problem and solution components of cases. GAME class , a counterpart of GAME in classification domains, shows a strong correspondence with accuracies reported by standard classifiers over classification tasks of varying complexity.
Designing Neural Networks Using PSO-Based Memetic Algorithm
Authors: Bo Liu, Ling Wang, Yihui Jin, Dexian Huang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

This paper proposes an effective particle swarm optimization (PSO) based memetic algorithm (MA) for designing artificial neural network. In the proposed PSO-based MA (PSOMA), not only the evolutionary searching mechanism of PSO characterized by individual improvement plus population cooperation and competition is applied to perform the global search, but also several adaptive high-performance faster training algorithms are employed to enhance the local search, so that the exploration and exploitation abilities of PSOMA can be well balanced. Moreover, an effective adaptive Meta-Lamarckian learning strategy is employed to decide which local search method to be used so as to prevent the premature convergence and concentrate computing effort on promising neighbor solutions. Simulation results and comparisons demonstrate the effectiveness and efficiency of the proposed PSOMA.
Classifier based text mining for radial basis function
Authors: M. Govindarajan, R. M. Chandrasekaran
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed radial basis function neural net classifier that performs cross validation for original RBF Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of two data sets like mushroom, weather symbolic. It is shown that, for mushroom (large dataset) the accuracy with Proposed RBF Neural Network was in average around 1.4 % less than with the original RBF Neural Network and the larger the improvement in speed. For weather symbolic (smaller dataset) the accuracy with Proposed RBF Neural Network was in average around 35.7 % less than with the original RBF Neural Network and the smaller the improvement in speed. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.
Cost-Performance Tradeoff for Embedded Systems
Authors: Julie S. Fant, Robert G. Pettit
Venue: Proceedings of the 6th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems (2008)

Software engineering requires creativity, thorough design and analysis, and sound design decisions. Design decisions often have tradeoffs and implications associated with them. Therefore, it is important that design decisions are based on sound analysis. With respect to embedded systems, key drivers are often performance and cost. Thus the purpose of this paper is to describe an approach to aid in the design decision process on cost and performance tradeoffs for embedded systems. Specifically, it presents a model-driven approach to understand and communicate the performance-cost tradeoff.
The development of an intelligent agent prototype for mutual fund investment
Authors: Suresh Subramoniam, Mohamed Tounsi, K. V. Krishnankutty
Venue: International Journal of Electronic Finance (2008)

This paper introduces the development aspects of an intelligent agent for mutual fund investment decisions. The success of next-generation Enterprise Resource Planning (ERP) systems mainly depends on making intelligent systems more useful for automated planning and strategic-level decisions, rather than using them merely for transaction processing at the operational level. The required knowledge for the development of the rule base has been adapted from the literature and the working of the intelligent agent prototype has been demonstrated using suitable examples. The developed system, based on fuzzy logic, takes a wide range of values as input and comes out with a unique decision, whereas an ordinary expert system would have given multiple decisions as output. Vagueness handling is possible on the internet and this helps the evolution of ERP, for which internet enabled strategic decision-making is of paramount importance.
Flow Analysis of Code Customizations
Authors: Anders Hessellund, Peter Sestoft
Venue: Proceedings of the 22nd European conference on Object-Oriented Programming (2008)

Inconsistency between metadata and code customizations is a major concern in modern, configurable enterprise systems. The increasing reliance on metadata, in the form of XML files, and code customizations, in the form of Java files, has led to a hybrid development platform. The expected consistency requirements between metadata and code should be checked but often are not, so current tools offer surprisingly poor development support. In this paper, we adapt classical data flow analyses to detect inconsistencies and provide better static guarantees. We provide a formalization of the consistency requirements and a set of adapted analyses for a concrete case study. Our work is implemented in a fast and efficient prototype in the form of an Eclipse plugin. We validate our work by testing this prototype on actual production code; preliminary results show that this approach is worthwhile. We found a significant number of previously undetected consistency errors and have received very positive feedback from the developer community in the case study.
Optimal companding vector quantization for circularly symmetric sources
Authors: Zoran H. Perić, Olivera D. Milanović, Aleksandra . Jovanović
Venue: Information Sciences: an International Journal (2008)

In this paper, it is shown that optimal Z_2 lattice vector quantization can be implemented using radial companding technique. We derive the optimal vector compressor function for radial compander of memoryless Gaussian source. This result is obtained by taking into consideration the source geometry and by establishing the relation between the volumes and the point densities at the compressor input and compressor output. We also derive the linearized model - the piecewise linear compander. Its performance closely approaches that of optimal vector quantization. For example, for R=8bits/dimension and L=16 regions, the difference between corresponding distortions is about 0.037dB, while the asymptotic performances are identical.
Symmetry and Search --- A Survey
Authors: Steve Linton
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

Searches of one form or another are a central unifying theme in Artificial Intelligence and effective management of symmetry is a key practical consideration in the practical application of a huge range of search techniques. It is almost never desirable to search, but frequently hard to avoid searching, very large numbers of equivalent sections of the search tree. Likewise many searches, if symmetry is not accounted for, will return very large numbers of unwanted equivalent solutions.
An Evolutionary Approach for Learning Motion Class Patterns
Authors: Meinard Müller, Bastian Demuth, Bodo Rosenhahn
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

This article presents a genetic learning algorithm to derive discrete patterns that can be used for classification and retrieval of 3D motion capture data. Based on boolean motion features, the idea is to learn motion class patterns in an evolutionary process with the objective to discriminate a given set of positive from a given set of negative training motions. Here, the fitness of a pattern is measured with respect to precision and recall in a retrieval scenario, where the pattern is used as a motion query. Our experiments show that motion class patterns can automate query specification without loss of retrieval quality.
Privacy Protection Against Malicious Adversaries in Distributed Information Sharing Systems
Authors: Nan Zhang, Wei Zhao
Venue: IEEE Transactions on Knowledge and Data Engineering (2008)

We address issues related to sharing information in a distributed system consisting of autonomous entities, each of which holds a private database. We consider threats from malicious adversaries that can deviate from the designated protocol and change their input databases. We classify malicious adversaries into two widely existing subclasses, namely weakly and strongly malicious adversaries, and propose protocols that can effectively and efficiently protect privacy against malicious adversaries.
Brief paper: Design of H∞ filter for Markov jumping linear systems with non-accessible mode information
Authors: Huaping Liu, Daniel W. C. Ho, Fuchun Sun
Venue: Automatica (Journal of IFAC) (2008)

For Markov jumping linear systems (MJLS), it is often encountered that the jumping mode cannot be accessible for filtering. Therefore it is strongly desirable to design a filter which is independent of the jumping model. In this paper, a new deterministic filter design procedure is proposed, which shows less conservatism than existing results. The whole design procedure can be accomplished by solving a set of linear matrix inequalities (LMIs). Finally, numerical examples are given to illustrate the effectiveness of the proposed approach.
Adam A Testbed for Distributed Virtual Environments
Authors: Jan Sablatnig, Jiehua Chen, Ruedi Seiler, Sven Grottke, Andreas Kopke, Adam Wolisz
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

In Distributed Virtual Environments (DVEs) the data on which the hosts operate is not consistent at all times. To restore data consistency, the DVE has to employ a consistency algorithm. Unfortunately, all existing DVEs have been built for specific application scenarios, which makes it impossible to compare the consistency algorithms and to choose a suitable candidate for a new scenario. To overcome this, we have created a modular simulator-based DVE testbed named Adam with the ability to plug in different application scenarios as well as different consistency algorithms and network constraints. The testbed also contains a large set of measurement tools. Our testbed currently supports two application scenarios and several of the most common consistency algorithms found in the literature. We can compare the solutions on an objective scale and confirm that optimistic consistency typically outperforms loose consistency.
Formal Modeling and Scheduling of Datapaths of Digital Document Printers
Authors: Georgeta Igna, Venkatesh Kannan, Yang Yang, Twan Basten, Marc Geilen, Frits Vaandrager, Marc Voorhoeve, Sebastian Smet, Lou Somers
Venue: Proceedings of the 6th international conference on Formal Modeling and Analysis of Timed Systems (2008)

We apply three different modeling frameworks -- timed automata (Uppaal), colored Petri nets and synchronous data flow -- to model a challenging industrial case study that involves an existing state-of-the-art image processing pipeline. Each of the resulting models is used to derive schedules for multiple concurrent jobs in the presence of limited resources (processing units, memory, USB bandwidth,..). The three models and corresponding analysis results are compared.
Efficient BP Algorithms for General Feedforward Neural Networks
Authors: S. España-Boquera, F. Zamora-Martínez, M. J. Castro-Bleda, J. Gorbe-Moya
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

The goal of this work is to present an efficient implementation of the Backpropagation (BP) algorithm to train Artificial Neural Networks with general feedforward topology. This will lead us to the "consecutive retrieval problem" that studies how to arrange efficiently sets into a sequence so that every set appears contiguously in the sequence. The BP implementation is analyzed, comparing efficiency results with another similar tool. Together with the BP implementation, the data description and manipulation features of our toolkit facilitates the development of experiments in numerous fields.
The INGENIAS Methodology for Advanced Surveillance Systems Modelling
Authors: José M. Gascueña, Antonio Fernández-Caballero
Venue: Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II (2007)

The use of surveillance systems has grown exponentially during the last decade. Moreover, the agency paradigm has shown to be suitable for the design and development of complex systems such as surveillance systems. They provide autonomy, reactivity, social ability and pro-activeness to carry out surveillance tasks in a semi-automatic way, collaborating with users in a more effective manner. Agents provide coordination mechanisms, solve conflicts, and determine through negotiation processes the more appropriate distribution of the surveillance tasks. Existent agent-based surveillance systems do not really use agent-based methodologies to develop them. In this paper, our experience for modelling advanced surveillance systems using the INGENIAS methodology is described.
Euler Diagram Decomposition
Authors: Andrew Fish, Jean Flower
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

Euler diagrams are a common visual representation of set-theoretic statements, and they have been used for visualising the results of database search queries or as the basis of diagrammatic logical constraint languages for use in software specification. Such applications rely upon the ability to automatically generate diagrams from an abstract description. However, this problem is difficult and is known to be NP-complete under certain wellformedness conditions. Therefore methods to identify when and how one can decompose abstract Euler diagrams into simpler components provide a vital step in improving the efficiency of tools which implement a generation process. One such decomposition, called diagram nesting, has previously been identified and exploited. In this paper, we make substantial progress, defining the notion of a disconnecting contour and identifying the conditions on an abstract Euler diagram that allow us to identify disconnecting contours. If a diagram has a disconnecting contour, we can draw it more easily, by combining the results of drawing smaller diagrams. The drawing problem is just one context which benefits from such diagram decomposition - we can also use the disconnecting contour to provide a more natural semantic interpretation of the Euler diagram.
Autocontrol of Electronic Expansion Valve Based on Optimal Fuzzy PD Controller
Authors: Tingrui Liu, Guangqing Chen, Jidai Wang
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

The paper mainly expatiates on control theories, parameters, and transfer functions for electronic expansion valve system. It realizes optimal fuzzy PD controller with more conspicuous effect, and can be put to use in flux process control with high precision. The paper, in the meantime, illustrates the hardware connection, control theory, driving flow chart of stepper motor, and flow chart of the optimal fuzzy control process.
Flowshop scheduling problem with a batching machine and task compatibilities
Authors: A. Oulamara, G. Finke, A. Kamgaing Kuiteing
Venue: Computers and Operations Research (2009)

This paper deals with the problem of task scheduling in a flowshop with two (discrete and batching) machines. Each task has to be processed by both machines. All tasks visit the machines in the same order. The first machine is a discrete machine that can process no more than one task at a time, and the second machine is a batching machine that can process several tasks per batch with the additional feature that the tasks of the same batch have to be compatible. A compatibility relation is defined between each pair of tasks, so that an undirected compatibility graph is obtained which turns out to be an interval graph. The batch processing time is equal to the maximal processing time of the tasks in this batch and all tasks of the same batch start and finish together. The aim is to make batching and sequencing decisions and minimize the makespan.
Transformations Have to be Developed ReST Assured
Authors: Mika Siikarla, Markku Laitkorpi, Petri Selonen, Tarja Systä
Venue: Proceedings of the 1st international conference on Theory and Practice of Model Transformations (2008)

Model transformations do not simply appear. They have to be not-so-simply developed. In early phases of development, there may exist only an intuition or an educated guess on some of the characteristics of the transformation. Instead of assuming a pre-existing complete transformation specification, we embrace change and develop transformations incrementally, gradually refining them into more complete ones as the body of knowledge of the domain grows. We present an iterative process encompassing requirements capture, design and implementation of model transformations. We describe partial transformations as so called transformational patterns and iteratively refine them. We apply the approach to developing a transformation that is used in building APIs that comply with the ReST architectural style.