ppxscal/embedding_network huggingface dataset:
Networks and systems for BT in the 21st century
Authors: M. H. Reeve, C. Bilton, P. E. Holmes, M. Bross
Venue: BT Technology Journal (2007)

This paper provides an overview of BT's 21st century network architecture. Analysis shows that this will deliver an improved customer experience, faster service provision and a significant overall cost reduction on today's base. These aims can only be achieved by a ground-breaking approach which moves from multiple networks each providing one service to a true multiservice network where the services are delivered by combining reusable capabilities. The architecture is therefore based on network, intelligence and operational support systems built from reusable components and an application layer that can expose these capabilities through open interfaces.
Muir Hardware Synthesis for Multimedia Applications
Authors: S. Fischaber, J. McAllister, R. Woods, E. Malins
Venue: Proceedings of the 2006 IEEE/ACM/IFIP Workshop on Embedded Systems for Real Time Multimedia (2006)

Muir hardware synthesis process used in the Abhainn design flow for optimisation and implementation of applications on FPGA-centric platforms and specifically its use for multimedia applications. Demonstrated are transformations available at the algorithmic level for an MPEG-2 encoder to reduce the memory usage and increase the throughput of the system. Also examined is the effect manipulations of the algorithm have on the final hardware architecture. Implementation of the encoder shows that results derived from a system level design approach are comparable with those derived from hand-coded implementations
A web ontologies framework for digital rights management
Authors: Roberto García, Rosa Gil, Jaime Delgado
Venue: Artificial Intelligence and Law (2007)

In order to improve the management of copyright in the Internet, known as Digital Rights Management, there is the need for a shared language for copyright representation. Current approaches are based on purely syntactic solutions, i.e. a grammar that defines a rights expression language. These languages are difficult to put into practise due to the lack of explicit semantics that facilitate its implementation. Moreover, they are simple from the legal point of view because they are intended just to model the usage licenses granted by content providers to end-users. Thus, they ignore the copyright framework that lies behind and the whole value chain from creators to end-users. Our proposal is to use a semantic approach based on semantic web ontologies. We detail the development of a copyright ontology in order to put this approach into practice. It models the copyright core concepts for creation, rights and the basic kinds of actions that operate on content. Altogether, it allows building a copyright framework for the complete value chain. The set of actions operating on content are our smaller building blocks in order to cope with the complexity of copyright value chains and statements and, at the same time, guarantee a high level of interoperability and evolvability. The resulting copyright modelling framework is flexible and complete enough to model many copyright scenarios, not just those related to the economic exploitation of content. The ontology also includes moral rights, so it is possible to model this kind of situations as it is shown in the included example model for a withdrawal scenario. Finally, the ontology design and the selection of tools result in a straightforward implementation. Description Logic reasoners are used for license checking and retrieval. Rights are modelled as classes of actions, action patterns are modelled also as classes and the same is done for concrete actions. Then, to check if some right or license grants an action is reduced to check for class subsumption, which is a direct functionality of these reasoners.
Existence Algorithms for Synchronizing/Distinguishing Sequences
Authors: Sung Je Hong
Venue: IEEE Transactions on Computers (1981)

This correspondence describes two efficient algorithms for determining whether or not a given finite-state machine has a synchronizing sequence and a distinguishing sequence, respectively, and compares them with the well-known tree method. Compared with the tree method, these new algorithms are easier to implement and require less memory size. Since they do not require keeping and searching a look-back directory, they allow significant speed improvements.
Optimal control and optimization algorithm of nonlinear impulsive delay system producing 1,3-propanediol
Authors: Kezan Li, Enmin Feng, Zhilong Xiu
Venue: Journal of Applied Mathematics and Computing (2007)

According to the controllability of pulse times and the amount of jumps in the states at these times in the process of fed-batch culture producing 1,3-propanediol, this paper proposes a terminal optimal control model, whose constraint condition is the nonlinear impulsive delay system. The existence of optimal control is discussed and an optimization algorithm which is applied to each subinternal over one cycle for this optimal control problem is constructed. Finally, the numerical simulations show that the terminal intensity of producing 1,3-propanediol has been increased obviously.
Action- and Workflow-Driven Augmented Reality for Computer-Aided Medical Procedures
Authors: Nassir Navab, Joerg Traub, Tobias Sielhorst, Marco Feuerstein, Christoph Bichlmeier
Venue: IEEE Computer Graphics and Applications (2007)

One key to the success of a user interface that includes AR visualization is its ability to automatically recognize different phases of a workflow, which each require various levels of augmentation. It is also important for the AR system to be transparent to the user during the rest of the procedure. These issues have greater importance when dealing with computer-aided surgery applications. In most of these applications, a surgeon needs augmentation for only quite brief periods, such as choosing the ports for a laparoscopic intervention or localizing the major arteries before starting a liver resection. These augmentations, however, can play an important role in the overall procedure's success. During the past three years, the authors have tried to develop such integrated AR solutions in the context of minimally invasive surgery. In this article, they discuss their activities and recent results.
A New Evaluation Method Based on Variable Range of Triangular Fuzzy Number
Authors: Liang Wei, Feng Dai, Yan Liu, Songtao Wu, Chenggang Cai
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

There is a certain extent of the fuzzy measure with the value of samples and standards in evaluation. Based on the theories of the triangular fuzzy number(TFN) and the variable range fuzzy set, the model for fuzzy approaching degree of triangular fuzzy numbers is established. Then a new evaluation method based on variable range of triangular fuzzy number is proposed in this paper. After analysis of examples, it is shown that this method can further enhance the credibility of the evaluation.
B74-19 Pattern Recognition Techniques
Authors: R. C. Gillespie
Venue: IEEE Transactions on Computers (1974)

Pattern Recognition Techniques does just what the doctor ordered; it serves as a broad informal introduction for engineers, computer scientists, and biologists to the field of pattern recognition. All necessary background is developed within the text, which is illustrated in terms of character recognition. It would be difficult to find a more extensive bibliography. This greatly contributes to the usefulness of this book.
SVT: schema validation tool for microsoft SQL-server
Authors: Ernest Teniente, Carles Farré, Toni Urpí, Carlos Beltrán, David Gañán
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

We present SVT, a tool for validating database schemas in SQL Server. This is done by means of testing desirable properties that a database schema should satisfy. To our knowledge, no commercial relational DBMS provides yet a tool able to perform such kind of validation.
Investigating emotional interaction with a robotic dog
Authors: Christian Martyn Jones, Andrew Deeming
Venue: Proceedings of the 19th Australasian conference on Computer-Human Interaction: Entertaining User Interfaces (2007)

Next generation of consumer-level entertainment robots should offer more natural engaging interaction. This paper reports on the development and evaluation of a consumer-level robotic dog with acoustic emotion recognition capabilities. The dog can recognise the emotional state of its owner from affective cues in the owner's speech and respond with appropriate actions. The evaluation study shows that users can recognise the new robotic dog to be emotionally intelligent and report that this makes the dog appear more 'alive'.
Creating a panoramic field image using multi-spectral stereovision system
Authors: M. Kise, Q. Zhang
Venue: Computers and Electronics in Agriculture (2008)

Satellite-based remote sensing presents a broad view of field scenes while ground-based remote sensing offers detailed observation of the crop to support precision farming decision-making. If it is possible to combine the advantages of both satellite-based and ground-based sensing, the resulting imagery could present both the broad view of a field scene and detailed observation of crop growth, which offers a very informative means for delivering crop production information. This paper describes a fundamental investigation on creating multi-spectral 3D panoramic field imagery by seamlessly integrating ground-based multi-spectral images of the field. A vehicle-mounted stereovision sensor composed of two multi-spectral cameras collects six-spectral channel images to form the multi-spectral 3D field imagery. The collected stereo image stream is then synthesized progressively to create a single seamless field image. The resulting panoramic imagery forms a 3D virtual field scene capable of providing more informative interpretation of crop/field status than a 2D plane image. Field test results proved that the assembled multi-spectral imagery was capable of providing a seamless 3D panoramic view of a soybean field with a broad view for assessing crop growth status with sufficient detail of individual crop plants.
An SVM-Based High-accurate Recognition Approach for Handwritten Numerals by Using Difference Features
Authors: Kaizhu Huang, Jun Sun, Yoshinobu Hotta, Katsuhito Fujimoto, Satoshi Naoi
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

Handwritten numeral recognition is an important pattern recognition task. It can be widely used in various domains, e.g., bank money recognition, which requires a very high recognition rate. As a state-of-the-art classifier, Support Vector Machine (SVM), has been extensively used in this area. Typically, SVM is trained in a batch model, i.e., all data points are simultaneously input for training the classification boundary. However, some slightly exceptional data, only accounting for a small proportion, are critical for the recognition rates. Training a classifier among all the data may possibly treat such legal but slightly exceptional samples as "noise". In this paper, we propose a novel approach to attack this problem. This approach exploits a two-stage framework by using difference features. In the first stage, a regular SVM is trained on all the training data; in the second stage, only the samples misclassified in the first stage are specially considered. Therefore, the performance can be lifted. The number of misclassifications is often small because of the good performance of SVM. This will present difficulties in training an accurate SVM engine only for these misclassified samples. We then further propose a multi-way to binary approach using difference features. This approach successfully transforms multi-category classification to binary classification and expands the training samples greatly. In order to evaluate the proposed method, experiments are performed on 10; 000 handwritten numeral samples extracted from real banks forms. This new algorithm achieves 99:0% accuracy. In comparison, the traditional SVM only gets 98:4%.
Finding hierarchical heavy hitters in streaming data
Authors: Graham Cormode, Flip Korn, S. Muthukrishnan, Divesh Srivastava
Venue: ACM Transactions on Knowledge Discovery from Data (TKDD) (2008)

Data items that arrive online as streams typically have attributes which take values from one or more hierarchies (time and geographic location, source and destination IP addresses, etc.). Providing an aggregate view of such data is important for summarization, visualization, and analysis. We develop an aggregate view based on certain organized sets of large-valued regions (&ldquo;heavy hitters&rdquo;) corresponding to hierarchically discounted frequency counts. We formally define the notion of hierarchical heavy hitters (HHHs). We first consider computing (approximate) HHHs over a data stream drawn from a single hierarchical attribute. We formalize the problem and give deterministic algorithms to find them in a single pass over the input. In order to analyze a wider range of realistic data streams (e.g., from IP traffic-monitoring applications), we generalize this problem to multiple dimensions. Here, the semantics of HHHs are more complex, since a &ldquo;child&rdquo; node can have multiple &ldquo;parent&rdquo; nodes. We present online algorithms that find approximate HHHs in one pass, with provable accuracy guarantees. The product of hierarchical dimensions forms a mathematical lattice structure. Our algorithms exploit this structure, and so are able to track approximate HHHs using only a small, fixed number of statistics per stored item, regardless of the number of dimensions. We show experimentally, using real data, that our proposed algorithms yields outputs which are very similar (virtually identical, in many cases) to offline computations of the exact solutions, whereas straightforward heavy-hitters-based approaches give significantly inferior answer quality. Furthermore, the proposed algorithms result in an order of magnitude savings in data structure size while performing competitively.
A trust based approach for protecting user data in social networks
Authors: Bader Ali, Wilfred Villegas, Muthucumaru Maheswaran
Venue: Proceedings of the 2007 conference of the center for advanced studies on Collaborative research (2007)

Social networks are graphs that represent relations among people, institutions, and their activities. We introduce a novel social access control (SAC) strategy inspired by multi-level security (MLS) [1] for protecting data on social networks. In MLS, the data objects and subjects are classified in hierarchical levels based on security clearance and access controlled accordingly. Instead of clearance levels, we use trust levels to annotate objects and subjects. The trust level of an object is specified by the creator. The trust level of a subject is obtained from a trust modeling process [2, 3]. Reading a data object is controlled using the relative trust values of subjects and objects. We describe one aspect of the SAC model that supports the confidentiality of read-only data objects. We performed simulation studies using traces from the flickr.com social network to evaluate the performance of some key primitives used in the SAC design.
A histogram based data-reducing algorithm for the fixed-point independent component analysis
Authors: Shih-Hsuan Chiu, Chuan-Pin Lu, Dien-Chi Wu, Che-Yen Wen
Venue: Pattern Recognition Letters (2008)

This paper proposes a histogram based data-reducing algorithm for improving the performance of the fixed-point independent component analysis (FastICA). This data-reducing independent component analysis (DR-FastICA) is based upon two statistical criteria to keep the histogram contour of processed data. This algorithm uses two steps (a coarse step for data sampling and a fine one for data tuning) to improve the performance of FastICA. Experimental results show that the proposed algorithm can reduce the computation time and implementation memory needed for executing FastICA, especially for large amounts of data (e.g. 1024x1024 images).
News Briefs
Authors: Linda Dailey Paulson
Venue: Computer (2007)

Topics covered include a spherical optical system that captures images from all directions, evasive cyberattacks that affect unsuspecting visitors to infected Web sites, a high-tech mirror that helps shoppers reflect on their purchases, and a technique that creates high-performance storage technology.
Ontology Based User Profiling in Personalized Information Service Agent
Authors: Jianguo Pan, Bofeng Zhang, Shufeng Wang, Gengfeng Wu, Daming Wei
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

Personalized information service agents have emerged in the recent years to help users to cope with the increasing amount of information available on the Internet. The effectiveness of agents depends mainly on profile completeness and accuracy. In the existing agents, although the performance of these systems improves after learning a user profile, it is difficult to share user profile and adapt user profile to user inter- ests. In order to solve these problems in agents, we present ontology based user profiling methods. The approaches in user profiling, such as representation, acquisition, learning, adaptation and re-ranking, are discussed. Moreover, a personalized information ser- vice agent is designed based on these approaches, and the performance of agent is evaluated.
Toward a PeopleWeb
Authors: Raghu Ramakrishnan, Andrew Tomkins
Venue: Computer (2007)

Important properties of users and objects will move from being tied to individual Web sites to being globally available. The conjunction of a global object model with portable user context will lead to a richer content structure and introduce significant shifts in online communities and information discovery.
A Novel Parallel Binary Counter Design with Parity Prediction and Error Detection Scheme
Authors: W. N. Toy
Venue: IEEE Transactions on Computers (1971)

In binary counters, the parity bit is not preserved when the data undergo the counting operation. It is necessary to predict the parity bit that should be used with the correct result. A special design has been devised to share as much hardware as possible between the counter and the parity prediction circuit. This reduces the number of logic gates and gives a more efficient design. The scheme involves the use of the first 0 detection for both the counting operation and the parity prediction.
Improving neural networks generalization with new constructive and pruning methods
Authors: Marcelo Azevedo Costa, Antônio Pádua Braga, Benjamin Rodrigues de Menezes
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2002)

This paper presents a new constructive method and pruning approaches to control the design of Multi-Layer Perceptron (MLP) without loss in performance. The proposed methods use a multi-objective approach to guarantee generalization. The constructive approach searches for an optimal solution according to the pareto set shape with increasing number of hidden nodes. The pruning methods are able to simplify the network topology and to identify linear connections between the inputs and outputs of the neural model. Topology information and validation sets are used.
PDE-Based Enhancement of Low Quality Documents
Authors: I. Nwogu, Z. Shi, V. Govindaraju
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

Partial Differential Equations are becoming one of the core tools for low-level image processing. They are espe- cially functional in diffusion processes and variational mod- els. In this paper, we exploit the regional smoothing that occurs in a nonlinear diffusion process and use this to en- hance text in a degraded document image. The proposed smoothing method is robust when applied to either a highly corrupted text document or one with little degradation. The technique was tested on historical docu- ments, carbon copies with highly varying grayscale back- grounds and on synthetic noisy documents. The PDE-based method far outperformed other industry-standard binariza- tion techniques when compared quantitatively and qualita- tively.
A multi-ranker model for adaptive XML searching
Authors: Ho Lam Lau, Wilfred Ng
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2008)

The evolution of computing technology suggests that it has become more feasible to offer access to Web information in a ubiquitous way, through various kinds of interaction devices such as PCs, laptops, palmtops, and so on. As XML has become a de-facto standard for exchanging Web data, an interesting and practical research problem is the development of models and techniques to satisfy various needs and preferences in searching XML data. In this paper, we employ a list of simple XML tagged keywords as a vehicle for searching XML fragments in a collection of XML documents. In order to deal with the diversified nature of XML documents as well as user preferences, we propose a novel multi-ranker model (MRM), which is able to abstract a spectrum of important XML properties and adapt the features to different XML search needs. The MRM is composed of three ranking levels. The lowest level consists of two categories of similarity and granularity features. At the intermediate level, we define four tailored XML rankers (XRs), which consist of different lower level features and have different strengths in searching XML fragments. The XRs are trained via a learning mechanism called the Ranking Support Vector Machine in a voting Spy Naïve Bayes framework (RSSF). The RSSF takes as input a set of labeled fragments and feature vectors and generates as output Adaptive Rankers (ARs) in the learning process. The ARs are defined over the XRs and generated at the top level of the MRM. We show empirically that the RSSF is able to improve the MRM significantly in the learning process that needs only a small set of training XML fragments. We demonstrate that the trained MRM is able to bring out the strengths of the XRs in order to adapt different preferences and queries.
Design of Hash-Tree Anti-collision Algorithm
Authors: Hong Zhang, Lei Han, Yu-Lu Li
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

In RFID system, the problem of the collision between tags is a focus topic. The Hash-tree anti-collision algorithm was proposed in the paper, which adopted hash operation to allocate slots for tags and used tree searching method to identify collision tags in the queue of collision slots. The proposed algorithm doesn't require readers to test the precise location of collision bits, and its performance beyond 36.8% is better than ALOHA- based algorithms.
Page Segmentation Competition
Authors: A. Antonacopoulos, B. Gatos, D. Bridson
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

This paper continues the authors' attempt to address the need for objective comparative evaluation of layout analysis methods in realistic circumstances. It describes the Page Segmentation Competition (modus operandi, dataset and evaluation criteria) held in the context of ICDAR2007 and presents the results of the evaluation of three candidate methods. The main objective of the competition was to compare the performance of such methods using scanned documents from commonly- occurring publications. The results indicate that although methods continue to mature, there is still a considerable need to develop robust methods that deal with everyday documents.