ppxscal/embedding_network huggingface dataset:
Temporal decision trees: model-based diagnosis of dynamic systems on-board
Authors: Luca Console, Claudia Picardi, Daniele Theseider Dupré
Venue: Journal of Artificial Intelligence Research (2003)

The automatic generation of decision trees based on off-line reasoning on models of a domain is a reasonable compromise between the advantages of using a model-based approach in technical domains and the constraints imposed by embedded applications. In this paper we extend the approach to deal with temporal information. We introduce a notion of temporal decision tree, which is designed to make use of relevant information as long as it is acquired, and we present an algorithm for compiling such trees from a model-based reasoning system.
Towards Model-Based Automatic Testing of Attack Scenarios
Authors: M. Zulkernine, M. F. Raihan, M. G. Uddin
Venue: Proceedings of the 28th International Conference on Computer Safety, Reliability, and Security (2009)

Model-based testing techniques play a vital role in producing quality software. However, compared to the testing of functional requirements, these techniques are not prevalent that much in testing software security. This paper presents a model-based approach to automatic testing of attack scenarios. An attack testing framework is proposed to model attack scenarios and test the system with respect to the modeled attack scenarios. The techniques adopted in the framework are applicable in general to the systems, where the potential attack scenarios can be modeled in a formalism based on extended abstract state machines. The attack events, i.e., attack test vectors chosen from the attacks happening in real-world are converted to the test driver specific events ready to be tested against the attack signatures. The proposed framework is implemented and evaluated using the most common attack scenarios. The framework is useful to test software with respect to potential attacks which can significantly reduce the risk of security vulnerabilities.
A fast data collection and augmentation procedure for object recognition
Authors: Benjamin Sapp, Ashutosh Saxena, Andrew Y. Ng
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

When building an application that requires object class recognition, having enough data to learn from is critical for good performance, and can easily determine the success or failure of the system. However, it is typically extremely labor-intensive to collect data, as the process usually involves acquiring the image, then manual cropping and hand-labeling. Preparing large training sets for object recognition has already become one of the main bottlenecks for such emerging applications as mobile robotics and object recognition on the web. This paper focuses on a novel and practical solution to the dataset collection problem. Our method is based on using a green screen to rapidly collect example images; we then use a probabilistic model to rapidly synthesize a much larger training set that attempts to capture desired invariants in the object's foreground and background. We demonstrate this procedure on our own mobile robotics platform, where we achieve 135x savings in the time/effort needed to obtain a training set. Our data collection method is agnostic to the learning algorithm being used, and applies to any of a large class of standard object recognition methods. Given these results, we suggest that this method become a standard protocol for developing scalable object recognition systems. Further, we used our data to build reliable classifiers that enabled our robot to visually recognize an object in an office environment, and thereby fetch an object from an office in response to a verbal request.
Global Optimization for Semi-supervised K-means
Authors: Xue Sun, Kunlun Li, Rui Zhao, Xikun Hu
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

So far most of the K-means algorithms use the number of the labeled data as the K value, but sometimes it doesn’t work well. In this paper, we propose a semi-supervised K-means algorithm based on the global optimization. It can select an appropriate number of clusters as the K value directly and plan a great amount of supervision data by using only a small amount of the labeled data. Combining the distribution characteristics of data sets and monitoring information in each cluster after clustering, we use the voting rule to guide the cluster labeling in the data sets. The experiments indicated that the global optimization algorithm for semi-supervised K-means is quite helpful to improve the K-means algorithm, it can effectively find the best data sets for K values and clustering center and enhancing the performance of clustering.
Weighted Sum Coloring in Batch Scheduling of Conflicting Jobs
Authors: Leah Epstein, Magn&#x00fa;s M. Halld&#x00f3;rsson, Asaf Levin, Hadas Shachnai
Venue: Algorithmica (2009)

Motivated by applications in batch scheduling of jobs in manufacturing systems and distributed computing, we study two related problems. Given is a set of jobs {J 1,&#x2026;,J n }, where J j has a processing time p j , and an undirected intersection graph G=({1,&#x2026;,n},E), with an edge (i,j) whenever the pair of jobs J i and J j cannot be processed in the same batch. We are to schedule the jobs in batches, where each batch completes its processing when the last job in the batch completes execution. The goal is to minimize the sum of job completion times. Our two problems differ in the definition of completion time of a job within a given batch. In the first variant, a job completes its execution when its batch is completed, whereas in the second variant, a job completes execution when its own processing is completed. For the first variant, we show that an adaptation of the greedy set cover algorithm gives a 4-approximation for perfect graphs. For the second variant, we give new or improved approximations for a number of different classes of graphs. The algorithms are of widely different genres (LP, greedy, subgraph covering), yet they curiously share a common feature in their use of randomized geometric partitioning.
Frame rule for mutually recursive procedures manipulating pointers
Authors: Viorel Preoteasa
Venue: Theoretical Computer Science (2009)

Using a predicate transformer semantics of programs, we introduce statements for heap operations and separation logic operators for specifying programs that manipulate pointers. We prove a powerful Hoare total correctness rule for mutually recursive procedures manipulating pointers. The rule combines earlier proof rules for (mutually) recursive procedures with the frame rule for pointer programs. The theory, including the proofs, is implemented in the theorem prover PVS. In this implementation program variables and addresses can store values of almost any type of the theorem prover.
Solving Global Unconstrained Optimization Problems by Symmetry-Breaking
Authors: Xiaohui Ji, Feifei Ma, Jian Zhang
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Global optimization has many real-world applications. Most methods for solving it are based on search,so decreasing its search space can increase the efficiency for their solving. Symmetry-breaking is an important technique for decreasing search space and it has been widely used in SAT,CSP and so on. In this paper, we try to decrease the search space of an unconstrained optimization problem by symmetry breaking.We present a method for extracting symmetries of an unconstrained optimization problem, and a method for constructing constraints to break those symmetries. The experimental results show that our methods are effective and efficient and symmetry-breaking can indeed increase the efficiency of global optimization problems solving.
Exact and Approximate Sizes of Convex Datacubes
Authors: Sébastien Nedjar
Venue: Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery (2009)

In various approaches, data cubes are pre-computed in order to efficiently answer Olap queries. The notion of data cube has been explored in various ways: iceberg cubes, range cubes, differential cubes or emerging cubes. Previously, we have introduced the concept of convex cube which generalizes all the quoted variants of cubes. More precisely, the convex cube captures all the tuples satisfying a monotone and/or antimonotone constraint combination. This paper is dedicated to a study of the convex cube size. Actually, knowing the size of such a cube even before computing it has various advantages. First of all, free space can be saved for its storage and the data warehouse administration can be improved. However the main interest of this size knowledge is to choose at best the constraints to apply in order to get a workable result. For an aided calibrating of constraints, we propose a sound characterization, based on inclusion-exclusion principle, of the exact size of convex cube as long as an upper bound which can be very quickly yielded. Moreover we adapt the nearly optimal algorithm HyperLogLog in order to provide a very good approximation of the exact size of convex cubes. Our analytical results are confirmed by experiments: the approximated size of convex cubes is really close to their exact size and can be computed quasi immediately.
Modifying SO-PMI for Japanese Weblog Opinion Mining by using a balancing factor and detecting neutral expressions
Authors: Guangwei Wang, Kenji Araki
Venue: Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers on XX (2007)

We propose a variation of the SO-PMI algorithm for Japanese, for use in Weblog Opinion Mining. SO-PMI is an unsupervised approach proposed by Turney that has been shown to work well for English. We first used the SO-PMI algorithm on Japanese in a way very similar to Turney's original idea. The result of this trial leaned heavily toward positive opinions. We then expanded the reference words to be sets of words, tried to introduce a balancing factor and to detect neutral expressions. After these modifications, we achieved a well-balanced result: both positive and negative accuracy exceeded 70%. This shows that our proposed approach not only adapted the SO-PMI for Japanese, but also modified it to analyze Japanese opinions more effectively.
Why Locally-Fair Maximal Flows in Client-Server Networks Perform Well
Authors: Kenneth A. Berman, Chad Yoshikawa
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

Maximal flows reach at least a 1/2 approximation of the maximum flow in client-server networks. By adding only 1 additional time round to any distributed maximal flow algorithm we show how this 1/2-approximation can be improved on bounded-degree networks. We call these modified maximal flows `locally fair' since there is a measure of fairness prescribed to each client and server in the network. Let N = (U,V,E,b) represent a client-server network with clients U, servers V, network links E, and node capacities b, where we assume that each capacity is at least one unit. Let d(u) denote the b-weighted degree of any node u ¿ U ¿ V, Δ = max {d(u) | u ¿ U } and ¿ = min { d(v) | v ¿ V }. We show that a locally-fair maximal flow f achieves an approximation to the maximum flow of $\min \{ 1, \frac{\Delta^2 - \delta} {2\Delta^2 - \delta\Delta - \Delta}$ }, and this result is sharp for any given integers ¿ and Δ. This results are of practical importance since local-fairness loosely models the steady-state behavior of TCP/IP and these types of degree-bounds often occur naturally (or are easy to enforce) in real client-server systems.
Image Watermarking Based on Wavelet-Based Contourlet Packet Transform with Best Tree
Authors: Zhenghua Shu, Guodong Liu, Lixin Gan, Lin Zhan, Wenming Fang
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

This paper proposes a watermarking embedding and extracting methods in the frequency domain based on a selection of a high frequency range containing large amount of information. The selected high-frequency range contributes to the imperceptibility of the watermark while the robustness against compression is achieved because the selected frequency range contains large amount of information. The entropy-based algorithm is adopted to find the best tree of the wavelet-based contourlet packet transform (WCPT.)Such best tree represents the best basis of the WCPT whose corresponding frequency subband contains high information energy. In addition, for security aspect of the watermarking process, the bits of the watermark image is randomly permuted before embedding them to the selected subband. The key of the pseudo-random generator provides the security for the watermark. Each bit of the permuted watermark image are embedded to the original image by adjusting the WCPT coefficients of the selected subband, which also allows us to vary the level of watermarking. The proposed methods are tested with various benchmark images of various sizes and with various watermarking levels. The JPEG compression, Gaussian noise and filtering were applied as the attacks. Image Watermarking Based On Wavelet-based Contourlet Packet Transform With Best Tree has a higher imperceptibility than Image Watermarking Based On Wavelet Packet Transform With Best Tree measured in term of peak signal to noise ratio (PSNR) and higher readability measured in term of normalized correlation (NC).
Image Segmentation Using Possibilistic C Means Based on Particle Swarm Optimization
Authors: Zang Jing
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

Fuzzy C-Means has been used in image segmentation widely. However, it isn’t better for the image with noise. Possibilistic C means (PCM) clustering algorithm exhibits the robustness to noise, butPCM is very sensitive to initialization and parameter. In this study, in order to avoid the weakness, a novel PCM was presented. It utilizes the strong ability of the global optimizing of the PSO Algorithm, and avoids the sensitivity to local optimization of the FCM algorithm. Furthermore, the PSO defines the centers and numbers of clustering automatically. Two algorithm combined to find a global optimizing clustering. Finally, Applies the crops diseases image, cuts apart the focus from the original image, the experimental result reveals the advantage of the new algorithm lies in the fact that it can not only avoid the coincident cluster problem but also has less noise sensitivity and higher segmentation accuracy.
Global indoor self-localization based on the ambient magnetic field
Authors: Janne Haverinen, Anssi Kemppainen
Venue: Robotics and Autonomous Systems (2009)

There is evidence that animals utilize local anomalities of Earth's magnetic field not just for orientation detection but also for true navigation, i.e., some animals are not only able to detect the direction of Earth's magnetic field (compass heading), they are able to derive positional information from local cues arising from the local anomalities of Earth's magnetic field. Similarly to Earth's non-constant magnetic field, the magnetic field inside buildings can be highly non-uniform. The magnetic field fluctuations inside buildings arise from both natural and man-made sources, such as steel and reinforced concrete structures, electric power systems, electric and electronic appliances, and industrial devices. Assuming that the anomalities of the magnetic field inside a building are nearly static and they have sufficient local variability, the anomalies provide a unique magnetic fingerprint that can be utilized in global self-localization. Based on the evidence presented in this article it can be argued that this hypothesis is valid. In this article, a Monte Carlo Localization (MCL) technique based on the above hypothesis is proposed. The feasibility of the technique is demonstrated by presenting a series of global self-localization experiments conducted in four arbitrarily selected buildings, including a hospital. The experiment setup consists of a mobile robot instrumented with a 3-axis magnetometer and a computer. In addition to global robot self-localization experiments, successful person self-localization experiments were also conducted by using a wireless, wearable magnetometer. The reported experiments suggest that the ambient magnetic field may remain sufficiently stable for longer periods of time giving support for self-localization techniques utilizing the local deviations of the magnetic field.
Analysis on the Multi-system Collaborative Model of the Enterprise Circular Economy - A Case Study of Hangzhou Iron & Steel Group in China
Authors: Ning Cai, Qi Taisong Shen
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

The pattern of circular economy has been praised by the government, academics and business. But the previous research on the Chinese circular economy only focused on the discuss of the economic paradigm or the role of the technological innovation which is just one dimension of the circular economy strategy. Based on system theory, the authors propose the multi-system cooperative model of the enterprise circular economy by portraying the five systems of the circular economy development strategy (which includes the institutional support system, pollution control system, technological innovation system, waste use system, environmental governance system) of Hangzhou Iron and Steel Group Company and describing the relationship between the five systems. Comparing to the single-dimension model, the multi-system cooperative model is more helpful to the improvement of the environmental performance. Besides, this model not only meet the requirements of the Government's environmental regulatory policy but also improve the firm’s economic performance.
Achieving Security Despite Compromise Using Zero-knowledge
Authors: Michael Backes, Martin P. Grochulla, Catalin Hritcu, Matteo Maffei
Venue: Proceedings of the 2009 22nd IEEE Computer Security Foundations Symposium (2009)

One of the important challenges when designing and analyzing cryptographic protocols is the enforcement of security properties in the presence of compromised participants. This paper presents a general technique for strengthening cryptographic protocols in order to satisfy authorization policies despite participant compromise. The central idea is to automatically transform the original cryptographic protocols by adding non-interactive zero-knowledge proofs.Each participant proves that the messages sent to the other participants are generated in accordance to the protocol.The zero-knowledge proofs are forwarded to ensure the correct behavior of all participants involved inthe protocol, without revealing any secret data.We use an enhanced type system for zero-knowledge to verify that the transformed protocols conform to their authorization policy even if some participants are compromised.Finally, we developed a tool that automatically generates ML implementations of protocols based on zero-knowledge proofs.The protocol transformation, the verification, and the generation of protocol implementations are fully automated.
Object-level document analysis of PDF files
Authors: Tamir Hassan
Venue: Proceedings of the 9th ACM symposium on Document engineering (2009)

The PDF format is commonly used for the exchange of documents on the Web and there is a growing need to understand and extract or repurpose data held in PDF documents. Many systems for processing PDF files use algorithms designed for scanned documents, which analyse a page based on its bitmap representation. We believe this approach to be inefficient. Not only does the rasterization step cost processing time, but information is also lost and errors can be introduced. Inspired primarily by the need to facilitate machine extraction of data from PDF documents, we have developed methods to extract textual and graphic content directly from the PDF content stream and represent it as a list of "objects" at a level of granularity suitable for structural understanding of the document. These objects are then grouped into lines, paragraphs and higher-level logical structures using a novel bottom-up segmentation algorithm based on visual perception principles. Experimental results demonstrate the viability of our approach, which is currently used as a basis for HTML conversion and data extraction methods.
Privacy Risk Diagnosis: Mining l-Diversity
Authors: Mohammad-Reza Zare-Mirakabad, Aman Jantan, Stéphane Bressan
Venue: Database Systems for Advanced Applications: DASFAA 2009 International Workshops: BenchmarX, MCIS, WDPP, PPDA, MBC, PhD, Brisbane, Australia, April 20 - 23, 2009 (2009)

Most of the recent efforts addressing the issue of data privacy have focused on devising algorithms for anonymization and diversification. Our objective is upstream of these works: we are concerned with the diagnosis of privacy risk and more specifically in this paper with l-diversity. We show that diagnosing l-diversity for various definitions of the concept is a knowledge discovery problem that can be mapped to the framework proposed by Mannila and Toivonen. The problem can therefore be solved with level-wise algorithms such as the apriori algorithm. We introduce and prove the necessary monotonicity property with respect to subset operator on attributes set for several instantiations of the l-diversity principle. We present and evaluate an algorithm based on the apriori algorithm. This algorithm computes, for instance, "maximum sets of attributes that can safely be published without jeopardizing sensitive attributes", even if they were quasi-identifiers available from external sources, and "minimum subsets of attributes which jeopardize anonymity".
Adapting Digital Watermark Algorithm Based on Chaos and Image Fusion
Authors: Zhang Fan, Shang Dongfang, Wang Yujing
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

An adapting digital watermark algorithm based on the image fusion and chaos is put forward. The steps of the algorithm are: Firstly, the watermark image is pretreated in disorder using the chaos mapping. Then the NVF function of the carrier image is calculated. The strength of the watermark information is accommodated adaptively, and the watermark information is hidden in the carrier image by the way of the combination with the NVF function and the image fusion. Finally, the experimental results are evaluated using the Mutual Information (MI) and the Cross Entropy (CE). The proposed algorithm shown in this paper promotes the hidden visual effect, ensures the security of watermark, and at the same time promotes the robustness of watermark.
Learning and inference for hierarchically split PCFGs
Authors: Slav Petrov, Dan Klein
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

Treebank parsing can be seen as the search for an optimally refined grammar consistent with a coarse training treebank. We describe a method in which a minimal grammar is hierarchically refined using EM to give accurate, compact grammars. The resulting grammars are extremely compact compared to other high-performance parsers, yet the parser gives the best published accuracies on several languages, as well as the best generative parsing numbers in English. In addition, we give an associated coarse-to-fine inference scheme which vastly improves inference time with no loss in test set accuracy.