ppxscal/embedding_network huggingface dataset:
Actively Transfer Domain Knowledge
Authors: Xiaoxiao Shi, Wei Fan, Jiangtao Ren
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

When labeled examples are not readily available, active learning and transfer learning are separate efforts to obtain labeled examples for inductive learning. Active learning asks domain experts to label a small set of examples, but there is a cost incurred for each answer. While transfer learning could borrow labeled examples from a different domain without incurring any labeling cost, there is no guarantee that the transferred examples will actually help improve the learning accuracy. To solve both problems, we propose a framework to actively transfer the knowledge across domains, and the key intuition is to use the knowledge transferred from other domain as often as possible to help learn the current domain, and query experts only when necessary. To do so, labeled examples from the other domain (out-of-domain) are examined on the basis of their likelihood to correctly label the examples of the current domain (in-domain). When this likelihood is low, these out-of-domain examples will not be used to label the in-domain example, but domain experts are consulted to provide class label. We derive a sampling error bound and a querying bound to demonstrate that the proposed method can effectively mitigate risk of domain difference by transferring domain knowledge only when they are useful, and query domain experts only when necessary. Experimental studies have employed synthetic datasets and two types of real world datasets, including remote sensing and text classification problems. The proposed method is compared with previously proposed transfer learning and active learning methods. Across all comparisons, the proposed approach can evidently outperform the transfer learning model in classification accuracy given different out-of-domain datasets. For example, upon the remote sensing dataset, the proposed approach achieves an accuracy around 94.5%, while the comparable transfer learning model drops to less than 89% in most cases. The software and datasets are available from the authors.
Emulating human perception of motion similarity
Authors: Jeff K. T. Tang Howard Leung
Venue: Computer Animation and Virtual Worlds (2008)

Evaluating the similarity of motions is useful for motion retrieval, motion blending, and performance analysis of dancers and athletes. Euclidean distance between corresponding joints has been widely adopted in measuring similarity of postures and hence motions. However, such a measure does not necessarily conform to the human perception of motion similarity. In this paper, we propose a new similarity measure based on machine learning techniques. We make use of the results of questionnaires from subjects answering whether arbitrary pairs of motions appear similar or not. Using the relative distance between the joints as the basic features, we train the system to compute the similarity of arbitrary pair of motions. Experimental results show that our method outperforms methods based on Euclidean distance between corresponding joints. Our method is applicable to content-based motion retrieval of human motion for large-scale database systems. It is also applicable to e-Learning systems which automatically evaluates the performance of dancers and athletes by comparing the subjects' motions with those by experts. Copyright &copy; 2008 John Wiley & Sons, Ltd.
A Time-Varying FARIMA Model for Internet Traffic
Authors: Li Song, Pascal Bondon, Yang Cao, Qi Cheng
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

We present a time-varying fractional autoregressive integrated moving average model and the methodology to fit this model to a non-stationary time series with local stationarity. Our experiments illustrate that the proposed model is able to capture the non-stationarity of traffic with time-varying parameters. An application to Internet traffic data is presented.
Experimental program analysis
Authors: Gregg Rothermel, Sebastian Elbaum
Venue:  (2008)

Program analysis techniques are used by software engineers to deduce and infer characteristics of programs for software-engineering-related tasks. Recently, some program analysis techniques have been designed to leverage characteristics of traditional experimentation. An examination of these techniques suggests that a new form of program analysis technique can be created by incorporating characteristics of experimentation. To date, however, there has been little formal recognition by the software engineering community of this form of program analysis, or the implications of using it. This dissertation presents experimental program analysis as a unique paradigm for conducting program analysis. We define this paradigm by building on principles and methodologies underlying the use of experimentation in other fields. This work offers four primary contributions. First, we provide definitions of experimental program analysis, illustrate them by example, and describe several intriguing differences between experimental program analysis and the use of experimentation in other research fields. Second, we survey the research literature for experimental program analysis techniques to offer insights into their existence and diversity&mdash;both in terms of the techniques themselves and the problem domains in which they operate. Third, we explore the applicability of experimental program analysis in three software engineering problem domains to provide a formative assessment of the capabilities of these techniques, and how they compare&mdash;in terms of cost-effectiveness, utility, and capabilities&mdash;to non-experimental baseline techniques. Fourth, we explore the use of experimental program analysis in a large software development setting, and present a case study to investigate the use of experimental program analysis in that setting. The contributions from the foregoing work support the conjecture that the applicability of experimental program analysis could be substantial. In particular, we expect that this work will expose the research community to use of experimental program analysis techniques, identify domains in which experimental program analysis might be useful, suggest many opportunities for improvements to existing techniques, and promote the use of experimentation in program analysis in order to confront program analysis programs in new and innovative ways. Accordingly, we believe that the experimental program analysis paradigm offers a promising new direction for program analysis research.
Incremental Benchmarks for Software Verification Tools and Techniques
Authors: Bruce W. Weide, Murali Sitaraman, Heather K. Harton, Bruce Adcock, Paolo Bucci, Derek Bronish, Wayne D. Heym, Jason Kirschenbaum, David Frazier
Venue: Proceedings of the 2nd international conference on Verified Software: Theories, Tools, Experiments (2008)

This paper proposes an initial catalog of easy-to-state, relatively simple, and incrementally more and more challenging benchmark problems for the Verified Software Initiative. These benchmarks support assessment of verification tools and techniques to prove total correctness of functionality of sequential object-based and object-oriented software. The problems are designed to help evaluate the state-of-the-art and the pace of progress toward verified software in the near term, and in this sense, they are just the beginning. They will allow researchers to illustrate and explain how proposed tools and techniques deal with known pitfalls and well-understood issues, as well as how they can be used to discover and attack new ones. Unlike currently available benchmarks based on "real-world" software systems, the proposed challenge problems are expected to be amenable to "push-button" verification that leverages current technology.
Fuzzy C-Means Based DNA Motif Discovery
Authors: Mustafa Karabulut, Turgay Ibrikci
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

In this paper, we examined the problem of identifying motifs in DNA sequences. Transcription-binding sites, which are functionally significant subsequences, are considered as motifs. In order to reveal such DNA motifs, our method makes use of Fuzzy clustering of Position Weight Matrix. The Fuzzy C-Means (FCM) algorithm clearly predicted known motifs that existed in intergenic regions of GAL4, CBF1 and GCN4 DNA sequences. This paper also provides a comparison of FCM with some clustering methods such as Self-Organizing Map and K-Means. The results of the FCM algorithm is compared to the results of popular motif discovery tool Multiple Expectation Maximization for Motif Elicitation (MEME) as well. We conclude that soft-clustering-based machine learning methods such as FCM are useful to finding patterns in biological sequences.
Integration of streaming and elastic traffic: a fixed point approach
Authors: H. Hassan, O. Brun, J. M. Garcia, D. Gauchard
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

We present a fixed point approach to evaluate the quality of service of streaming traffic multiplexed with elastic traffic in multi-service networks. First, we handle elastic traffic and streaming traffic separately, and then we derive a general fixed point formulation integrating both types of traffic in best effort networks. Then, we extend the application of this formulation to multi-service networks where priorities and bandwidth sharing schemes can be applied to different flows. Our approach is mainly oriented towards very large scale networks where traditional simulation techniques are not scalable, and where a large number of flows have to be evaluated in reasonable time. We assess the accuracy of our approach by means of event-driven simulations.
Intelligent Agents and Evolvable Systems
Authors: Krzysztof Cetnarowicz, Robert Schaefer, Bojin Zheng, Maciej Paszyński, Bartlomiej Śnieżyński
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

The workshop Intelligent Agents and Evolvable Systems has originated as the fusion of two former workshops: Intelligent Agents and Evolvable Systems and Algorithms and Evolvable Systems. It has been organized since 2004 within the frame of the International Conference on Computational Science. Mathematical considerations, algorithmic aspects and designing computer applications supporting the development and management of systems for the large scale computation have been emphasized.Two contributions are related to the formal description of multi agent systems. The first one delivered by Smołka, concerns agents that carry tasks of distributed, parallel computation. The results ensure existence of time-optimal scheduling and locate the optimal scheduling rules among static ones. The second paper written by Capković, is devoted to the modeling inter-agents relations by Petri Nets. Main results have been obtained by using the discrete event systems control theory and illustrated on several examples.
What Can I Watch on TV Tonight?
Authors: David Bueno, Ricardo Conejo, David Martín, Jorge León, Javier G. Recuenco
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

This paper presents the methods used in a TV Recommender System that helps users in the difficult task of finding an interesting TV program from among the hundreds of channels that we can find nowadays on TV. Our aim is to cover not only user preferences but also user restrictions while watching TV. The recommendations use a hybrid method, combining content based and folksonomy (collaborative and social recommendations). We also present interesting initial results of some experiments that try to show the accuracy of the users recommendations.
Emotional Experience and Interaction Design
Authors: Youn-Kyung Lim, Justin Donaldson, Heekyoung Jung, Breanne Kunz, David Royer, Shruti Ramalingam, Sindhia Thirumaran, Erik Stolterman
Venue: Affect and Emotion in Human-Computer Interaction: From Theory to Applications (2008)

The emotional experience of an interactive system has been the subject of a great deal of recent interest and study in the HCI community. However, many of researchers have pointed out the extreme difficulty in predicting or controlling these emotional experiences through intentional design choices. However, the user study we conducted proposes a different point-of-view than these claims. Although these emotional responses were not always tied directly to the device itself and influenced by contextual factors, we discovered that certain controllable aspects of interactive products showed clear patterns of emotion in the responses of our participants. We discuss our findings and provide implications for the design of emotional experiences in interactive devices.
On Switching to H-Free Graphs
Authors: Eva Jelínková, Jan Kratochvíl
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

In this paper we study the problem of deciding if, for a fixed graph H, a given graph is switching-equivalent to an H-free graph. Polynomial-time algorithms are known for H having at most three vertices or isomorphic to P 4. We show that for H isomorphic to a claw, the problem is polynomial, too. Further, we give a characterization of graphs switching-equivalent to a K 1,2-free graph by ten forbidden induced subgraphs, each having five vertices. We also give the forbidden induced subgraphs for graphs switching-equivalent to a forest of bounded vertex degrees.
Parallel algorithm for codebook generation with multi-step approach and hierarchical clustering
Authors: Akiyoshi Wakatani
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

Parallel system with distributed memory is a promising platform to achieve a high performance computing with less construction cost. Applications with less communications, such as a kind of parameter sweep applications (PSA), can be efficiently carried out on such a parallel system, but some applications are not suitable for the parallel system due to a large communication cost. We focus on PNN (Pairwise Nearest Neighbor) codebook generation algorithm for VQ (Vector Quantization) compression algorithm and propose a parallel version of the PNN algorithm suitable for the parallel system with distributed memory, called "multi-step parallel PNN". The multi-step parallel PNN is a modified version of the PNN algorithm that creates a different codebook than the original PNN does, thus the quality of a codebook created by using the multi-step parallel PNN may be worse than that of a codebook by the original PNN. However, our experimental results show that the quality of the codebook is almost same as that of the original one. We also confirm the effectiveness of the multi-step parallel PNN by the evaluation of the computational complexity of the algorithm and the preliminary experiment executed on a PC cluster system.
Predicting hypotensive episodes during spinal anesthesia with the application of artificial neural networks
Authors: Chao-Shun Lin, Jainn-Shiun Chiu, Ming-Hui Hsieh, Martin S. Mok, Yu-Chuan Li, Hung-Wen Chiu
Venue: Computer Methods and Programs in Biomedicine (2008)

Hypotension is one of the most frequent adverse effects of spinal anesthesia. Several factors might be related to the occurrence of hypotension. Predictions of the hypotensive event, however, had been addressed by only a few authors using logistic regression (LR) models. Artificial neural networks (ANN) are pattern-recognition tools that can be used to detect complex patterns within data sets. The purpose of this study was to develop the ANN-based predictive model to identify patients with high risk of hypotension during spinal anesthesia. From September 2004 to December 2006, the anesthesia records of 1501 patients receiving surgery under spinal anesthesia were used to develop the ANN and LR models. By random selection 75% of data were used for training and the remaining 25% of data were used as test set for validating the predictive performance. Five senior anesthesiologists were asked to review the data of test set and to make predictions of hypotensive event during spinal anesthesia by clinical experience. The ANN model had a sensitivity of 75.9% and specificity of 76.0%. The LR model had a sensitivity of 68.1% and specificity of 73.5%. The area under receiver operating characteristic curves were 0.796 and 0.748. The ANN model performed significantly better than the LR model. The prediction of clinicians had the lowest sensitivity of 28.7%, 22.2%, 21.3%, 16.1%, and 36.1%, and specificity of 76.8%, 84.3%, 83.1%, 87.0%, and 64.0%. The computer-based predictive model should be useful in increasing vigilance in those patients most at risk for hypotension during spinal anesthesia, in allowing for patient-specific therapeutic intervention, or even in suggesting the use of alternative methods of anesthesia.
Rulebase Technology and Legal Knowledge Representation
Authors: Giuseppe Contissa
Venue: Computable Models of the Law: Languages, Dialogues, Games, Ontologies (2008)

This paper reflects the results of a study conducted as a side work connected with the development of ALIS (Automated Legal Intelligent System), modeling a representation of legal knowledge in the area of intellectual property rights using the RuleBurst rule-based system technology. In this first stage, our work has been focused on Italian Copyright law, with the aim to develop a method that could be extended and applied, in a subsequent stage, to other IP legislations in Europe. The integration in the ALIS decision support system of the Ruleburst inferencing system with an advanced legal text retrieval engine and a game-theory strategy engine is facilitated by using a (quasi) natural language-knowledge representation, enhancing the benefits of isomorphism.
Bellman's optimality principle in the weakly structurable dynamic systems
Authors: Gia Sirbiladze, Anna Sikharulidze
Venue: Proceedings of the 9th WSEAS International Conference on Fuzzy Systems (2008)

We pose problems of the Weakly Structurable Continuous Dynamic System (WSCDS) optimal control and briefly discuss the results developed by G. Sirbiladze [11]. Sufficient and necessary conditions are presented for the existence of an extremal fuzzy optimal control processes, for which we use R. Bellman's optimality principle and take into consideration the gain-loss fuzzy process. An example of constructing of the continuous extremal fuzzy dynamic systems optimal control is presented.
Analysis of a BDF&#x2013;DGFE scheme for nonlinear convection&#x2013;diffusion problems
Authors: V&#x00ed;t Dolej&#x0161;&#x00ed;, Miloslav Vlas&#x00e1;k
Venue: Numerische Mathematik (2008)

We deal with the numerical solution of a scalar nonstationary nonlinear convection&#x2013;diffusion equation. We employ a combination of the discontinuous Galerkin finite element method for the space semi-discretization and the k-step backward difference formula for the time discretization. The diffusive and stabilization terms are treated implicitly whereas the nonlinear convective term is treated by a higher order explicit extrapolation method, which leads to the necessity to solve only a linear algebraic problem at each time step. We analyse this scheme and derive a priori asymptotic error estimates in the discrete L &#x221e;(L 2)-norm and the L 2(H 1)-seminorm with respect to the mesh size h and time step &#x03c4; for k&#x00a0;=&#x00a0;2,3. Numerical examples verifying the theoretical results are presented.
Highly Space Efficient Counters for Perl Compatible Regular Expressions in FPGAs
Authors: Chia-Tien Dan Lo, Yi-Gang Tai
Venue: Proceedings of the 4th international workshop on Reconfigurable Computing: Architectures, Tools and Applications (2008)

Signature based network intrusion detection systems (NIDS) rely on an underlying string matching engine that inspects each network packet against a known malicious pattern database. Traditional static pattern descriptions may not efficiently represent sophisticated attack signatures. Recently, most NIDSs have adopted regular expressions such as Perl compatible regular expressions (PCREs) to describe an attack signature, especially for polymorphic worms. PCRE is a superset of traditional regular expression, in which no counters are involved. However, this overloads the performance of software-based NIDSs, causing a big portion of their execution time to be dedicated to pattern matching. Over the past decade, hardware acceleration for the pattern matching has been studied extensively and a marginal performance has been achieved. Among hardware approaches, FPGA-based acceleration engines provide great flexibility because new signatures can be compiled and programmed into their reconfigurable architecture. As more and more malicious signatures are discovered, it becomes harder to map a complete set of malicious signatures specified in PCREs to an FPGA chip. Even worse is that the counters used in PCREs typically take a great deal of hardware resources. Therefore, we propose a space efficient SelectRAM counter for PCREs that involve counting. The design takes advantage of components that consist of a configurable logic block, and thus optimizes space usage. A set of PCRE blocks has been built in hardware to implement PCREs used in Snort/Bro. Experimental results show that the proposed sheme outperforms existing designs by at least 5-fold. Performance results are reported in this paper.
ImageCLEF 2006 Experiments at the Chemnitz Technical University
Authors: Thomas Wilhelm, Maximilian Eibl
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 present a report about our participation in the ImageCLEF photo task 2006 and a short description of our new framework for future use in further CLEF participations. We described and analysed our participation in the monolingual English task. A special Lucene-aligned query expansion and histogram comparison are helping to improve the baseline results.
Error containment
Authors: Robert S. Hanmer
Venue: Proceedings of the 2006 conference on Pattern languages of programs (2006)

High availability is required in many computer systems today. These include web servers, e-commerce applications, network and telephony devices such as routers and switches, and many others. No software is defect free, and neither is the environment in which the software operates. As a result errors happen. To prevent errors from causing failures they must be kept from spreading. The goal is to limit the parts of the system that the error infects with its incorrectness. These patterns discuss two ways of containing errors.