ppxscal/embedding_network huggingface dataset:
Supervised Isomap with Dissimilarity Measures in Embedding Learning
Authors: Bernardete Ribeiro, Armando Vieira, João Carvalho Das Neves
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

In this paper we propose a supervised version of the Isomap algorithm by incorporating class label information into a dissimilarity matrix in a financial analysis setting. On the credible assumption that corporates financial status lie on a low dimensional manifold, nonlinear dimensionality reduction based on manifold learning techniques has strong potential for bankruptcy analysis in financial applications. We apply the method to a real data set of distressed and healthy companies for proper geometric tunning of similarity cases. We show that the accuracy of the proposed approach is comparable to the state-of-the-art Support Vector Machines (SVM) and Relevance Vector Machines (RVM) despite the fewer dimensions used resulting from embedding learning.
Access Control and Authorization for Security of RFID Multi-domain Using SAML and XACML
Authors: Dong Seong Kim, Taek-Hyun Shin, Byunggil Lee, Jong Sou Park
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

The necessity of collaboration between different RFID applications domains is becoming significant. The previous works on security and privacy in RFID system, it's commonly assumed that all RFID tags belong to a single RFID system. In this paper, we propose an access control and authorization for security of RFID multi-domain. We employ Security Assertion Markup Language (SAML) and eXtensible Access Control Markup Language (XACML). SAML and XACML are well defined and applied to web security and grid security. We show the possibility of our approach through a case study.
Boundary Shape Recognition Using Accumulated Length and Angle Information
Authors: Marçal Rusiñol, Philippe Dosch, Josep Lladós
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

In this paper we present a method to recognize shapes by analyzing a polygonal approximation of their boundaries. The method is independent of the used approximation method since its recognition strategy does not rely on the number of segments composing the shape. Length and turning angle information are extracted from the chain of segments. The comparison method is invariant to scale, translation and some occlusions of the extracted contour. A simple pre-processing method, also based on arc-length features, is presented to be used as a coarse fitting method to determine angle rotation and as a first filter to eliminate non pertinent candidates.
Modular Neural Networks for Model-Free Behavioral Learning
Authors: Johane Takeuchi, Osamu Shouno, Hiroshi Tsujino
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

Future robots/agents will need to perform situation specific behaviors for each user. To cope with diverse and unexpected situations, model-free behavioral learning is required. We have constructed a modular neural network model based on reinforcement learning and demonstrated that the model can learn multiple kinds of state transitions with the same architectures and parameter values, and without pre-designed models of environments. We recently developed a modular neural network model equipped with a modified on-line modular learning algorithm, which is more suitable for neural networks and more efficient in learning. This paper describes the performances of constructed models using the probabilistically fluctuated Markov decision process including partially observable conditions. In the test transitions, the observed states probabilistically fluctuated. The new learning model is able to function in those complex transitions without specific adjustments for each transition.
Engineering Comparators for Graph Clusterings
Authors: Daniel Delling, Marco Gaertler, Robert Görke, Dorothea Wagner
Venue: Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management (2008)

A promising approach to compare two graph clusterings is based on using measurements for calculating the distance between them. Existing measures either use the structure of clusterings or quality-based aspects with respect to some index evaluating both clusterings. Each approach suffers from conceptional drawbacks. We introduce a new approach combining both aspects and leading to better results for comparing graph clusterings. An experimental evaluation of existing and new measures shows that the significant drawbacks of existing techniques are not only theoretical in nature but manifest frequently on different types of graphs. The evaluation also proves that the results of our new measures are highly coherent with intuition, while avoiding the former weaknesses.
Method of Face Recognition Based on Red-Black Wavelet Transform and PCA
Authors: Yuqing He, Huan He, Hongying Yang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

With the development of the man-machine interface and the recognition technology, face recognition has became one of the most important research aspects in the biological features recognition domain. Nowadays, PCA(Principal Components Analysis) has applied in recognition based on many face database and achieved good results. However, PCA has its limitations: the large volume of computing and the low distinction ability. In view of these limitations, this paper puts forward a face recognition method based on red-black wavelet transform and PCA. The improved histogram equalization is used to realize image preprocessing in order to compensate the illumination. Then, appling the red-black wavelet sub-band which contains the information of the original image to extract the feature and do matching. Comparing with the traditional methods, this one has better recognition rate and can reduce the computational complexity.
Third-order nonlinear optical responses of molecules in the intermediate and strong correlation regime: Variation of second hyperpolarizability in the bond dissociation
Authors: Masayoshi Nakano, Satoru Yamada, Kizashi Yamaguchi
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

The variations in the longitudinal second hyperpolarizabilities (&gamma;) in the bond-dissociation processes of molecules (H$_{2}$ and LiH) are investigated by the finite-field (FF) approach using several ab initio molecular orbital (MO) methods, i.e., spin-restricted methods (RHF, RMPn (n = 2,4), RHF coupled cluster (RCC)) and spin-unrestricted methods (UHF, UMPn (n = 2,4), UHF coupled cluster (UCC)) as well as approximate spin-projected methods (APUHF and APUMPn). The variation of &gamma; in the bond dissociation process is expected to elucidate the feature of third-order nonlinear optical (NLO) properties of molecules, e.g., open-shell organic and transition metal compounds, which belong to the intermediate and strong correlation regime. The calculation methods except for CC exhibit a cusp in the variation of &gamma; at the triplet instability threshold, and remarkable electron-correlation dependency of the variation in &gamma; is observed in the intermediate and large bond-distance region, corresponding to intermediate and strong correlation regime, respectively. From the results of the most accurate methods (UCCSD(T) or RCCSD(T)) employed in this study, not only significant increase and decrease behavior of the magnitude of &gamma; value is observed in the intermediate dissociation region of these molecules but also even the change in the sign of &gamma; value appears in the dissociation process of LiH.
Summarizing and referring: towards cohesive extracts
Authors: Patricia Nunes Gonçalves, Lucia Rino, Renata Vieira
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

In this paper we propose and evaluate a system for summary post-edition, which aims at replacing referential expressions, trying to avoid referencial cohesion problems. To propose expressions that best represent the evoked entity, the system uses knowledge about coreference chains. We evaluate the system both with knowledge provided by manual and automatic annotation of coreference chains.
Amharic-English Information Retrieval
Authors: Atelach Alemu Argaw, Lars Asker
Venue: Evaluation of Multilingual and Multi-modal Information Retrieval: 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain, September 20-22, 2006, Revised Selected Papers (2007)

We describe Amharic-English cross lingual information retrieval experiments in the ad hoc bilingual tracks of the CLEF 2006. The query analysis is supported by morphological analysis and part of speech tagging while we used two machine readable dictionaries supplemented by online dictionaries for term lookup in the translation process. Out of dictionary terms were handled using fuzzy matching and Lucene[4] was used for indexing and searching. Four experiments that differed in terms of utilized fields in the topic set, fuzzy matching, and term weighting, were conducted. The results obtained are reported and discussed.
Development of fast, distributed computational schemes for full body bio-models and their application to novel action potential block in nerves using ultra-short, high intensity electric pulses
Authors: Ravindra P. Joshi
Venue:  (2007)

An extremely robust and novel scheme for computing three-dimensional, time-dependent potential distributions in full body bio-models is proposed, which, to the best of our knowledge, is the first of its kind. This simulation scheme has been developed to employ distributed computation resources, to achieve a parallelized numerical implementation for enhanced speed and memory capability. The other features of the numerical bio-model included in this dissertation research, are the ability to incorporate multiple electrodes of varying shapes and arbitrary locations. The parallel numerical tool also allows for user defined, current or potential stimuli as the excitation input. Using the available computation resources at the university, a strong capability for extremely large bio-models was developed. So far a maximum simulation comprised of 6.7 million nodes has been achieved for a "full rat bio-model" with a 1 mm spatial resolution at an average of 30 seconds per iteration. The ability to compute the resulting potential distribution in a full animal body allows for realistic and accurate studies of bio-responses to electrical stimuli. For example, the voltages computed from the full-body models at various sites and tissue locations could be used to examine the potential for using nanosecond, high-intensity, pulsed electric fields for blocking neural action or action potential (AP) propagation. This would be a novel, localized, and reversible method of controlling neural function without tissue damage. It could potentially be used in "electrically managed pain relief," non-lethal incapacitation, and neural/muscular therapy. The above concept has quantitatively been evaluated in this dissertation. Specifically, the effects of high-intensity (kilo-Volt), ultra-short (&sim;100 nanosecond) electrical pulses have been evaluated, and compared with available experimental data. Good agreement with available data is demonstrated. It is also shown that nerve membrane electroporation, brought about by the high-intensity, external pulsing, could indeed be instrumental in halting AP propagation. Simulations based on a modified distributed cable model to represent nerve segments have been used to demonstrate a numerical "proof-of-concept."
3D Ultrasound-Guided Motion Compensation System for Beating Heart Mitral Valve Repair
Authors: Shelten G. Yuen, Samuel B. Kesner, Nikolay V. Vasilyev, Pedro J. Nido, Robert D. Howe
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Beating heart intracardiac procedures promise significant benefits for patients, however, the fast motion of the heart poses serious challenges to surgeons. We present a new 3D ultrasound-guided motion (3DUS) compensation system that synchronizes instrument motion with the heart. The system utilizes the fact that the motion of some intracardiac structures, including the mitral valve annulus, is largely constrained to translation along one axis. This allows the development of a real-time 3DUS tissue tracker which we integrate with a 1 degree-of-freedom actuated surgical instrument, real-time 3DUS instrument tracker, and predictive filter to devise a system with synchronization accuracy of 1.8 mm RMSE. User studies involving the deployment of surgical anchors in a simulated mitral annuloplasty procedure demonstrate that the system increases success rates by over 100%. Furthermore, it enables more careful anchor deployment by reducing forces to the tissue by 50% while allowing instruments to remain in contact with the tissue for longer periods.
Approximating rank-width and clique-width quickly
Authors: Sang-Il Oum
Venue: ACM Transactions on Algorithms (TALG) (2008)

Rank-width was defined by Oum and Seymour [2006] to investigate clique-width. They constructed an algorithm that either outputs a rank-decomposition of width at most f(k) for some function f or confirms that rank-width is larger than k in time O(&verbar;V&verbar;9log &verbar;V&verbar;) for an input graph G &equals; (V,E) and a fixed k. We develop three separate algorithms of this kind with faster running time. We construct an O(&verbar;V&verbar;4)-time algorithm with f(k) &equals; 3k + 1 by constructing a subroutine for the previous algorithm; we avoid generic algorithms minimizing submodular functions used by Oum and Seymour. Another one is an O(&verbar;V&verbar;3)-time algorithm with f(k) &equals; 24k, achieved by giving a reduction from graphs to binary matroids; then we use an approximation algorithm for matroid branch-width by Hlin&ecaron;n&yacute; [2005]. Finally we construct an O(&verbar;V&verbar;3)-time algorithm with f(k) &equals; 3k &minus; 1 by combining the ideas of the two previously cited papers.
Algebraic Model of an Arithmetic Unit for TTE-Computable Normalized Rational Numbers
Authors: Gregorio Miguel Casado, Juan Manuel García Chamizo, María Teresa Signes Pont
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

A formal specification of an arithmetic unit for computable normalized rational numbers is proposed. This specification, developed under the scope of the paradigm known as algebraic models of processors, exploits the connection between the signed digit representation for rational numbers in Type-2 Theory of Effectivity and online arithmetic in Computer Arithmetic. The proposal aims for specification formalization and calculation reliability together with implementation feasibility.
An Anonymity Model Achievable Via Microaggregation
Authors: Josep Domingo-Ferrer, Francesc Sebé, Agusti Solanas
Venue: Proceedings of the 5th VLDB workshop on Secure Data Management (2008)

k-Anonymity is a privacy model requiring that all combinations of key attributes in a database be repeated at least for k records. It has been shown that k-anonymity alone does not always ensure privacy. A number of sophistications of k-anonymity have been proposed, like p-sensitive k-anonymity, l-diversity and t-closeness. We identify some shortcomings of those models and propose a new model called (k,p,q,r)-anonymity. Also, we propose a computational procedure to achieve this new model that relies on microaggregation.
A new method for distributing power usage across a sensor network
Authors: Patrick Vincent, Murali Tummala, John McEachen
Venue: Ad Hoc Networks (2008)

We present a method for more uniformly distributing the energy burden across a wireless ground-based sensor network communicating with an overhead unmanned aerial vehicle (UAV). A subset of sensor nodes, termed a transmit cluster, receives and aggregates data gathered by the entire network, and forms a distributed antenna array, concentrating the radiated transmission into a narrow beam aimed towards the UAV. Because these duties are power-intensive, the role of transmit cluster must be shifted to different nodes as time progresses. We present an algorithm to reassign the transmit cluster, specifying the time that should elapse between reassignments and the number of hops that should be placed between successive transmit clusters in order to achieve three competing goals: first, we wish to better and more broadly spread the energy load across the sensor network while, second, minimizing the energy expended in moving the transmit cluster, all the while, third, reducing to the extent practicable the time to bring the UAV and the sensor network's beam into alignment. Additionally, we present a method for reconfiguring the communication burden between the ground-based sensor network and the UAV. We describe and analyze two alternative strategies to bring the UAV and the sensor network's beam into alignment, while minimizing the energy expended by the sensor network. The performance of the two strategies is compared in terms of probability of beam-UAV alignment as a function of time, and the expected time to alignment. We examine the performance tradeoff between the choice of strategy and parameters of the sensor network that affect power conservation.
Support Vector Machines for Visualization and Dimensionality Reduction
Authors: Tomasz Maszczyk, Włodzisław Duch
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

Discriminant functions calculated by Support Vector Machines (SVMs) define in a computationally efficient way projections of high-dimensional data on a direction perpendicular to the discriminating hyperplane. These projections may be used to estimate and display posterior probability densities . Additional directions for visualization and dimensionality reduction are created by repeating the linear discrimination process in a space orthogonal to already defined projections. This process allows for an efficient reduction of dimensionality and visualization of data, at the same time improving classification accuracy of a single discriminant function. Visualization of real and artificial data shows that transformed data may not be separable and thus linear discrimination will completely fail, but the nearest neighbor or rule-based methods in the reduced space may still provide simple and accurate solutions.
Study of Image Mosaic Based on the Method of Finite Difference
Authors: Guosheng Yang, Huanlong Zhang, YuLin Yang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

With respect to the problem that it is very difficult for the existing image mosaic algorithms to be adaptive for the big gray difference between the to-be-mosaic images, a novel image mosaic algorithm based on the method of finite difference is proposed, in order to make the boundary area near the seam smooth and to keep the coincidence of globe intensity in a resultant mosaic image. Firstly, an oriented vector field is set up for the to-be-mosaic object according to the method of finite difference. Secondly, an image mosaic problem is transformed into solving the Poission equation given the condition of Dirichlet boundary. Thirdly, under the guidance of the oriented vector field, the resultant mosaic object gradually approximates to the to-be-mosaic object by difference interpolating and iterating, to obtain a final mosaic image with the effect of high definition, harmony in globe, and local smooth transition. At last, the experimental results demonstrate the effectiveness and adaptability of the presented algorithm in this paper.
Separation of Responsibilities between Application Servers and Media Servers in NGNs: A Practical Approach
Authors: Alessandro Amirante, Tobia Castaldi, Lorenzo Miniero, Simon Pietro Romano
Venue: Proceedings of the 8th international conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART on Next Generation Teletraffic and Wired/Wireless Advanced Networking (2008)

In this paper we deal with the separation of concerns among the entities involved in multimedia sessions in Next Generation Networks (NGNs). In particular, the focus is on the explicit separation of responsibilities between Application Servers, which are in charge of the services application logic, and Media Servers, whose task is instead the low-level manipulation and delivery of media streams. The paper describes the standardization proposals coming from both the 3GPP and the IETF from a very practical point of view, and presents the reader with the currently only available implementation of the MEDIACTRL architecture. Furthermore, the paper is also devoted to describing some typical multimedia scenarios from the presented perspective, by providing an in-depth analysis of the related sequence diagrams and protocol messages.
Segmented software cost estimation models based on fuzzy clustering
Authors: Javier Aroba, Juan J. Cuadrado-Gallego, Miguel-Ángel Sicilia, Isabel Ramos, Elena García-Barriocanal
Venue: Journal of Systems and Software (2008)

Parametric software cost estimation models are based on mathematical relations, obtained from the study of historical software projects databases, that intend to be useful to estimate the effort and time required to develop a software product. Those databases often integrate data coming from projects of a heterogeneous nature. This entails that it is difficult to obtain a reasonably reliable single parametric model for the range of diverging project sizes and characteristics. A solution proposed elsewhere for that problem was the use of segmented models in which several models combined into a single one contribute to the estimates depending on the concrete characteristic of the inputs. However, a second problem arises with the use of segmented models, since the belonging of concrete projects to segments or clusters is subject to a degree of fuzziness, i.e. a given project can be considered to belong to several segments with different degrees. This paper reports the first exploration of a possible solution for both problems together, using a segmented model based on fuzzy clusters of the project space. The use of fuzzy clustering allows obtaining different mathematical models for each cluster and also allows the items of a project database to contribute to more than one cluster, while preserving constant time execution of the estimation process. The results of an evaluation of a concrete model using the ISBSG 8 project database are reported, yielding better figures of adjustment than its crisp counterpart.
Optimal Surface Flattening
Authors: Danny Z. Chen, Ewa Misiołek
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

The problem of optimal surface flattening in 3-D finds many applications in engineering and manufacturing. However, previous algorithms for this problem are all heuristics without any quality guarantee and the computational complexity of the problem was not well understood. In this paper, we prove that the optimal surface flattening problem is NP-hard. Further, we show that the problem admits a PTAS and can be solved by a (1 + ¿)-approximation algorithm in O(n logn) time for any constant ¿> 0, where n is the input size of the problem.