ppxscal/embedding_network huggingface dataset:
Reconstruction of Interval Graphs
Authors: Masashi Kiyomi, Toshiki Saitoh, Ryuhei Uehara
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

The graph reconstruction conjecture is a long-standing open problem in graph theory. There are many algorithmic studies related it besides mathematical studies, such as DECK CHECKING, LEGITIMATE DECK, PREIMAGE CONSTRUCTION, and PREIMAGE COUNTING. We study these algorithmic problems limiting the graph class to interval graphs. Since we can solve GRAPH ISOMORPHISM for interval graphs in polynomial time, DECK CHECKING for interval graphs is easily done in polynomial time. Since the number of interval graphs that can be obtained from an interval graph by adding a vertex and edges incident to it can be exponentially large, developing polynomial time algorithms for LEGITIMATE DECK, PREIMAGE CONSTRUCTION, and PREIMAGE COUNTING on interval graphs is not trivial. We present that these three problems are solvable in polynomial time on interval graphs.
Animating Idle Gaze in Public Places
Authors: Angelo Cafaro, Raffaele Gaito, Hannes Högni Vilhjálmsson
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

In realistic looking game environments it is important that virtual characters behave naturally. Our goal is to produce naturally looking gaze behavior for animated agents and avatars that are simply idling. We studied people standing and waiting, as well as people walking down a shopping street. From our observations we built a demo with the CADIA Populus multi-agent social simulation platform.
A New Multiple-attribute Negotiation Model of Mobile E-Commerce
Authors: Pucong Li, Yuansheng Zhong
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

In this paper, we analyze the negotiation protocol, negotiation strategy, negotiation flow and negotiation evaluation deeply, and proposes a new negotiation model of mobile E-commerce by designing new negotiation algorithms and new negotiation evaluation methods. Lastly, we analyze the system architecture of the mobile E-Commerce platform, which adopts the negotiation model, and simulate the negotiation flow through the transaction negotiation of three goods. The results show that the negotiation model, which reflects the user’s intents well, can guarantee the fair of the transaction, and converges rapidly, and is of good adaptability and expansibility.
Algorithmic Program Synthesis with Partial Programs and Decision Procedures
Authors: Rastislav Bodik
Venue: Proceedings of the 16th International Symposium on Static Analysis (2009)

Program synthesizer can derive programs that are efficient, even surprising, but it must be first "programmed" with human insights about the domain and its implementation tricks. In deductive synthesis, the insights are captured by domain theories, often elusive and always requiring formal expertise. To bring synthesis to everyday programmers, we have been exploring algorithmic synthesis, which is to deductive synthesis what model checking is to deductive verification: Rather than deducing a program with a theorem prover, algorithmic synthesis systematically finds the program in a space of candidate implementations. If we help programmers turn their insights into descriptions of candidates, we have a chance for a practical synthesizer.I will show how sketches-partial programs that syntactically define the candidate space-allow programmers to express their insight while eliding tedious code fragments. These fragments are filled in by CEGIS, our counterexample-guided inductive synthesis algorithm that exploits recent advances in automated decision procedures. I will also show how these decision procedures allow us to implement an oracle that helps the programmer refine and formalize his insight about a problem. Finally, I will describe the linguistic support for synthesis in our SKETCH language and show how we synthesized complex implementations of ciphers, scientific codes, and concurrent lock-free data-structures.
Support Vector Machine for Assistant Clinical Diagnosis of Cardiac Disease
Authors: Wei Gong, Shoubin Wang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

Support Vector Machine (SVM) is a novel powerful machine learning method based on statistical learning theory, which is powerful for the characterization of small sample (nonlinearity, high dimension and local minima). Cardiac Diseases are very harmful to the human health. The application of electrocardiogram (ECG) is essential for the clinical diagnosis of cardiac diseases. The use of computers for accurately and quickly cardiac disease diagnosis has been a subject fervently pursued by both internal and external researchers. Therefore, it is great significant to explore even more accurate and higher-speed automatic ECG analysis method. In this paper, Clinical diagnosis of cardiac disease based on SVM is proposed. There are two input patterns of samples: 8-lead ECG in series and in parallel. All experiments are implemented on Pentium 350 MHz with 512 MB RAM. Matlab 6.5 is employ to solve the quadratic programming. Comparison in two input patterns based on SVM, the result shows that SVM method in parallel is highly reliable and accurate. It will have great potential application in clinical diagnosis.
Adaptive Parallel Householder Bidiagonalization
Authors: Fangbin Liu, Frank J. Seinstra
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

With the increasing use of large image and video archives and high-resolution multimedia data streams in many of today's research and application areas, there is a growing need for multimedia-oriented high-performance computing. As a consequence, a need for algorithms, methodologies, and tools that can serve as support in the (automatic) parallelization of multimedia applications is rapidly emerging.This paper discusses the parallelization of Householder bidiagonalization, a matrix factorization method which is an integral part of full Singular Value Decomposition (SVD) -- an important algorithm for many multimedia problems. Householder bidiagonalization is hard to parallelize efficiently because the total number of matrix elements taking part in the calculations reduces during runtime. To overcome the growing negative performance impact of load imbalances and overprovisioning of compute resources, we apply adaptive runtime techniques of periodic matrix remapping and process reduction for improved performance. Results show that our adaptive parallel execution approach provides a significant improvement in efficiency, even when applying a set of compute resources which is (initially) very large.
Towards agile and test-driven development in NLP applications
Authors: Jana Z. Sukkarieh, Jyoti Kamal
Venue: Proceedings of the Workshop on Software Engineering, Testing, and Quality Assurance for Natural Language Processing (2009)

c-rater&reg; is the Educational Testing Service technology for automatic content scoring for short free-text responses. In this paper, we contend that an Agile and test-driven development environment optimizes the development of an NLP-based technology.
Generating Test Case from Functional Requirement of Web Applications
Authors: Bin Zhu, Huaikou Miao, Hongwei Zeng, Shengbo Chen
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

E-commerce has been developing rapidly around the world. We run Web application to support e-commerce. Quality of Web applications influences the functionalities and security of e-commerce. Modeling and testing are important to Quality of Web applications. Many researchers are still to find effective ways to model and test Web applications. Formal methods can improve the quality of Web applications. This paper suggests utilizing a formal language (object-z to) describe functional requirement of Web applications. An approach to generating test sequence is introduced in this paper. We analyze formal specification to find out atomic operations and then identify the environment precondition of the operation (EPRE) for each atomic operation. We use EPREs to build an environment Transition Graph (ETG). The steps of transforming an ETG into environment transition sequences are also addressed. Two test adequacy criteria are defined as a guideline for the selection of the test sequences.
Securing Structured Overlays against Identity Attacks
Authors: Krishna P. N. Puttaswamy, Heather Zheng, Ben Y. Zhao
Venue: IEEE Transactions on Parallel and Distributed Systems (2009)

Structured overlay networks can greatly simplify data storage and management for a variety of distributed applications. Despite their attractive features, these overlays remain vulnerable to the Identity attack, where malicious nodes assume control of application components by intercepting and hijacking key-based routing requests. Attackers can assume arbitrary application roles such as storage node for a given file, or return falsified contents of an online shopper's shopping cart. In this paper, we define a generalized form of the Identity attack, and propose a lightweight detection and tracking system that protects applications by redirecting traffic away from attackers. We describe how this attack can be amplified by a Sybil or Eclipse attack, and analyze the costs of performing such an attack. Finally, we present measurements of a deployed overlay that show our techniques to be significantly more lightweight than prior techniques, and highly effective at detecting and avoiding both single node and colluding attacks under a variety of conditions.
Graph-based learning for statistical machine translation
Authors: Andrei Alexandrescu, Katrin Kirchhoff
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

Current phrase-based statistical machine translation systems process each test sentence in isolation and do not enforce global consistency constraints, even though the test data is often internally consistent with respect to topic or style. We propose a new consistency model for machine translation in the form of a graph-based semi-supervised learning algorithm that exploits similarities between training and test data and also similarities between different test sentences. The algorithm learns a regression function jointly over training and test data and uses the resulting scores to rerank translation hypotheses. Evaluation on two travel expression translation tasks demonstrates improvements of up to 2.6 BLEU points absolute and 2.8% in PER.
A Variational Image-Based Approach to the Correction of Susceptibility Artifacts in the Alignment of Diffusion Weighted and Structural MRI
Authors: Ran Tao, P. Thomas Fletcher, Samuel Gerber, Ross T. Whitaker
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

This paper presents a method for correcting the geometric and greyscale distortions in diffusion-weighted MRI that result from inhomogeneities in the static magnetic field. These inhomogeneities may due to imperfections in the magnet or to spatial variations in the magnetic susceptibility of the object being imaged--so called susceptibility artifacts. Echo-planar imaging (EPI), used in virtually all diffusion weighted acquisition protocols, assumes a homogeneous static field, which generally does not hold for head MRI. The resulting distortions are significant, sometimes more than ten millimeters. These artifacts impede accurate alignment of diffusion images with structural MRI, and are generally considered an obstacle to the joint analysis of connectivity and structure in head MRI. In principle, susceptibility artifacts can be corrected by acquiring (and applying) a field map. However, as shown in the literature and demonstrated in this paper, field map corrections of susceptibility artifacts are not entirely accurate and reliable, and thus field maps do not produce reliable alignment of EPIs with corresponding structural images. This paper presents a new, image-based method for correcting susceptibility artifacts. The method relies on a variational formulation of the match between an EPI baseline image and a corresponding T2-weighted structural image but also specifically accounts for the physics of susceptibility artifacts. We derive a set of partial differential equations associated with the optimization, describe the numerical methods for solving these equations, and present results that demonstrate the effectiveness of the proposed method compared with field-map correction.
Remote Reminiscence Talking and Scheduling Prompter for Individuals with Dementia Using Video Phone
Authors: Kiyoshi Yasuda, Noriaki Kuwahara, Kazunari Morimoto
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Addressing Diversity. Part I: Held as Part of HCI International 2009 (2009)

Caring for individuals with dementia is very difficult and frustrating task, especially for home caregivers. We have created two remote assisting systems, the remote reminiscence talking and scheduling prompter using video phone, and used them with four individuals with dementia living in their homes. For two out of four individuals, reminiscence talking and scheduling prompter are effective respectably, compared to TV watching and care giver's instructions. The psychological stability of one individual has continued for three hours even after the remote reminiscence talking finished. We suggest that remote reminiscence talking and scheduling prompter are very promising for caring individuals with dementia, although further revisions are required.
A New Method for Extracting Multi-line Parameters Based on RHT and Block Operation
Authors: Jie-xian Zeng, Si-xin Li, Xiang Fu
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

Straight line is an important descriptor in image analysis. The drawbacks of traditional straight line parameters extracting methods are anal sized, and a novel multi-line parameters extracting method is proposed. Firstly, the image is divided into blocks, and RHT (random Hough transform) is used to detect straight line parameters in each sub-image. Then, global parameters are extracted based on the relationship of parameters between the sub-images and the global image. Comparisons with traditional scheme are presented and the results demonstrating the performance of the proposed method.
Towards Computational Developmental Model based on Synthetic Approaches
Authors: Minoru Asada, Koh Hosoda, Hiroshi Ishiguro, Yasuo Kuniyoshi, Toshio Inui
Venue: Proceedings of the 2009 IEEE 8th International Conference on Development and Learning (2009)

Cognitive developmental robotics (CDR) [1] has been tackling the issue of how human cognitive functions develop by means of a synthetic approach that developmentally constructs cognitive functions. “Physical embodiment” is the core idea of CDR, and is revisited to make its role clearer, that is, to enable information structuring through interactions with the environment, including other agents. This paper attempts to reveal the developmental process of human cognitive function from a viewpoint of synthetic approach towards building a computational developmental model for the process with brief introductions of existing CDR approaches.
Plant leaf identification using Gabor wavelets
Authors: Dalcimar Casanova, Jarbas Joaci de Mesquita Sá Junior, Odemir Martinez Bruno
Venue: International Journal of Imaging Systems and Technology (2009)

This article presents a novel method of plant classification using Gabor wavelet filters to extract texture filters in a foliar surface. The aim of this promising method is to add to the results obtained by other leaf attributes (such as shape, contour, color, among others), increasing, therefore, the percentage of classification of plant species. To corroborate the efficiency of the technique, an experiment using 20 species from Brazilian flora was done and discussed. The results are also compared with texture Fourier descriptors and cooccurrence matrices. &copy; 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 236&ndash;243, 2009
Detecting Temporal Trends of Technical Phrases by Using Importance Indices and Linear Regression
Authors: Hidenao Abe, Shusaku Tsumoto
Venue: Proceedings of the 18th International Symposium on Foundations of Intelligent Systems (2009)

In this paper, we propose a method for detecting temporal trends of technical terms based on importance indices and linear regression methods. In text mining, importance indices of terms such as simple frequency, document frequency including the terms, and tf-idf of the terms, play a key role for finding valuable patterns in documents. As for the documents, they are often published daily, monthly, annually, and irregularly for each purpose. Although the purposes of each set of documents are not changed, roles of terms and the relationship among them in the documents change temporally. In order to detect such temporal changes, we combined a method to extract terms, importance indices of terms, and trend identification based on linear regression analysis. Empirical results show that our method detected emergent and subsiding trends of extracted terms in a corpus of a research domain. By comparing this method with the existing burst detection method, we investigated the trend of phrases consisting of several burst words in the titles of AAAI and IJCAI.
Existence of Periodic Solution for Hopfield Cellular Neural Networks
Authors: Yanling Li, Anping Liu, Linli Zhang, Zutao Hao
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

As an important tool to study practical problems of biology, engineering and image processing, the cellular neural networks (CNNs) has caused more and more attention. Some interesting results about the existence for cellular neural networks have been obtained. In this paper, by means of iterative analysis, the existence of periodic solution for Hopfield cellular neural networks are considered. Some new results are obtained.
Caching Scheme Could Boost Developing World's Internet Access
Authors: Linda Dailey Paulson
Venue: Computer (2009)

Topics include a caching scheme that could improve Internet access in the developing world, a software tool that eliminates computer freezes, and gender-recognition software that promises to make advertising more effective.
CSBIterKmeans: A New Clustering Algorithm Based on Quantitative Assessment of the Clustering Quality
Authors: Tarek Smaoui, Sascha Müller, Christian Müller-Schloer
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

In this paper we introduce a clustering algorithm CSBIterKmeans based on the well-known k-means algorithm. Our approach is based on the validation of the clustering result by combining two "antipodal" validation metrics, cluster separation and cluster compactness, to determine autonomously the "best" number of clusters and hence dispense with the number of clusters as input parameter. We report about our first results with a collection of audio features extracted from songs and discuss the performance of the algorithm with different numbers of features and objects.
A High-Performance Hardware Architecture for Spectral Hash Algorithm
Authors: Ray C. C. Cheung, Çetin K. Koc, John D. Villasenor
Venue: Proceedings of the 2009 20th IEEE International Conference on Application-specific Systems, Architectures and Processors (2009)

The Spectral Hash algorithm is one of the Round 1 candidates for the SHA-3 family, and is based on spectral arithmetic over a finite field, involving multidimensional discrete Fourier transformations over a finite field, data dependent permutations, Rubic-type rotations, and affine and nonlinear functions. The underlying mathematical structures and operations pose interesting and challenging tasks for computer architects and hardware designers to create fast, efficient, and compact ASIC and FPGA realizations. In this paper, we present an efficient hardware architecture for the full 512-bit hash computation using the spectral hash algorithm. We have created a pipelined implementation on a Xilinx Virtex-4 XC4VLX200-11 FPGA which yields 100 MHz and occupies 38,328 slices, generating a throughput of 51.2 Gbps. Our fully parallel synthesized implementation shows that the spectral hash algorithm is about 100 times faster than the fastest SHA-1 implementation, while requiring only about 13 times as many logic slices.
The Second Answer Set Programming Competition
Authors: Marc Denecker, Joost Vennekens, Stephen Bond, Martin Gebser, Mirosław Truszczyński
Venue: Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning (2009)

This paper reports on the Second Answer Set Programming Competition. The competitions in areas of Satisfiability checking, Pseudo-Boolean constraint solving and Quantified Boolean Formula evaluation have proven to be a strong driving force for a community to develop better performing systems. Following this experience, the Answer Set Programming competition series was set up in 2007, and ran as part of the International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR). This second competition, held in conjunction with LPNMR 2009, differed from the first one in two important ways. First, while the original competition was restricted to systems designed for the answer set programming language, the sequel was open to systems designed for other modeling languages, as well. Consequently, among the contestants of the second competition were a CLP(FD) team and three model generation systems for (extensions of) classical logic. Second, this latest competition covered not only satisfiability problems but also optimization ones. We present and discuss the set-up and the results of the competition.
On AIRS and Clonal Selection for Machine Learning
Authors: Chris Mcewan, Emma Hart
Venue: Proceedings of the 8th International Conference on Artificial Immune Systems (2009)

AIRS is an immune-inspired supervised learning algorithm that has been shown to perform competitively on some common datasets. Previous analysis of the algorithm consists almost exclusively of empirical benchmarks and the reason for its success remains somewhat speculative. In this paper, we decouple the statistical and immunological aspects of AIRS and consider their merits individually. This perspective allows us to clarifying why AIRS performs as it does and identify deficiencies that leave AIRS lacking. A comparison with Radial Basis Functions suggests that each may have something to offer the other.
A Framework for Real-time Local Free-Form Deformation
Authors: Jiacheng Li, Gengliang Wang, Yue Chen
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

A new method for free-form deformation on large-scale models is proposed.The original mesh is deformed by using a control mesh which is the simplification of the original one.All the points on the original one would be parameterized by the blending local coordinate system based on the triangle it corresponds and the neighbors of the triangle.The control mesh could be edited directly and also could be edited by other algorithms.And then the modified mesh is rebuilt from the control mesh and the restored parameters.The new positions of the points are calculated very fast as the calculation of any point only involves in a definite number of faces.In this paper, we proposed a predictable large-scale model deformation method which gives a designer a real-time environment of editing models with millions of points by editing a model at a thousand’s scale.