ppxscal/embedding_network huggingface dataset:
Extent, Extremum, and Curvature: Qualitative Numeric Features for Efficient Shape Retrieval
Authors: B. Gottfried, A. Schuldt, O. Herzog
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

In content-based image retrieval we are faced with continuously growing image databases that require efficient and effective search strategies. In this context, shapes play a particularly important role, especially as soon as not only the overall appearance of images is of interest, but if actually their content is to be analysed, or even to be recognised. In this paper we argue in favour of numeric features which characterise shapes by single numeric values. Therewith, they allow compact representations and efficient comparison algorithms. That is, pairs of shapes can be compared with constant time complexity. We introduce three numeric features which are based on a qualitative relational system. The evaluation with an established benchmark data set shows that the new features keep up with other features pertaining to the same complexity class. Furthermore, the new features are well-suited in order to supplement existent methods.
A Benchmark for OCL Engine Accuracy, Determinateness, and Efficiency
Authors: Martin Gogolla, Mirco Kuhlmann, Fabian Büttner
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

The Object Constraint Language (OCL) is a central element in modeling and transformation languages like UML, MOF, and QVT. Consequently approaches for MDE (Model-Driven Engineering) depend on OCL. However, OCL is present not only in these areas influenced by the OMG but also in the Eclipse Modeling Framework (EMF). Thus the quality of OCL and its realization in tools seems to be crucial for the success of model-driven development. Surprisingly, up to now a benchmark for OCL to measure quality properties has not been proposed. This paper puts forward in the first part the concepts of a comprehensive OCL benchmark. Our benchmark covers (A) OCL engine accuracy (e.g., for the undefined value and the use of variables), (B) OCL engine determinateness properties (e.g., for the collection operations any and flatten), and (C) OCL engine efficiency (for data type and user-defined operations). In the second part, this paper empirically evaluates the proposed benchmark concepts by examining a number of OCL tools. The paper discusses several differences in handling particular OCL language features and underspecifications in the OCL standard.
Towards bidirectional distributed matchmaking
Authors: Victor Shafran, Gal Kaminka, Sarit Kraus, Claudia V. Goldman
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

Matchmaking is the process of introducing two or more agents to each other. Current matchmaking techniques are unidirectional and fail to address large-scale and highly dynamic systems with time constraints. We propose a new distributed technique which scales well, and still maintains relatively low matchmaking time and communication overhead. Our technique introduces very low storage and computational overhead to the agents. We suggest using a matching cache which can take advantage of the multidirectional nature of the matchmaking problem. We empirically evaluate the proposed technique on bilateral matchmaking and show that it out-performs the existing techniques.
Toward Modeling Sensor Node Security Using Task-Role Based Access Control with TinySec
Authors: Misun Moon, Dong Seong Kim, Jong Sou Park
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

There is a TinySec in TinyOS to provide integrity and confidentiality of message for Wireless Sensor Network (WSN). However, TinySec employs a simple group key management, so if a sensor node is compromised by an adversary, overall sensor nodes in the network are likely to be compromised. Therefore, we propose a new access control methodology for WSN, based on Task-Role Based Access Control (T-RBAC). T-RBAC has been successfully applied to many different kinds of security applications. T-RBAC has also capability to provide flexible authentication and authorization to the system. We present the design and implementation results on our approach, and we show security analysis and comparison results show the feasibility of our approach.
A QoS Provisioning MAC Protocol for IEEE 802.11 WLANs
Authors: Hu Zhengbing, Han Xiaomin
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

In this paper we present extended age dependent backoff protocol (EADB), an extension of the age dependent backoff (ADB) proposed to alleviate the delay and jitter of real-time packets. The proposed retransmission scheme considers not only the persistence factors but also the contention window (CW) to reduce collision rate. The persistence factor (PF) is based on the ages of the real-time packets in the transmission queue and the lifetimes of real-time packets. Moreover, we also consider the collision rate that stations experience to adjust the CW. The proposed scheme is able to prevent the degradation the performance of the network caused by setting the CW as the minimum value after successful transmission. Simulation results indicate that the EADB provides the delay, jitter, and drop rate better than ADB.
Web Application Attack Prevention for Tiered Internet Services
Authors: Susanta Nanda, Lap-Chung Lam, Tzi-Cker Chiueh
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

Because most web application attacks exploit vulnerabilities that result from lack of input validation, a promising approach to thwarting these attacks is to apply validation checks on tainted portions of the operands used in security-sensitive operations, where a byte is tainted if it is data/control dependent on some network packet(s). This paper presents the design, implementation and evaluation of a dynamic checking compiler called WASC, which automatically adds checks into web applications used in three-tier internet services to protect them from the most common two types of web application attacks: SQL- and script-injection attack. In addition to including a taint analysis infrastructure for multi-process and multi-language applications, WASC features the use of SQL and HTML parsers to defeat evasion techniques that exploit interpretation differences between attack detection engines and target applications. Experiments with a fully operational WASC prototype show that it can indeed stop all SQL/script injection attacks that we have tested. Moreover, the end-to-end latency penalty associated with the checks inserted by WASC is less than 30% for the test web applications used in our performance study.
Dialogue-Based Processing of Graphics and Graphical Ontologies
Authors: Ivan Kopeček, Radek Ošlejšek
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

Dialogue-based processing of graphics forms a framework for enabling visually impaired people to access computer graphics. The presented approach integrates current technologies of dialogue systems, computer graphics and ontologies for the purpose of overcoming the obstacles and problems that the development of the system used for the dialogue processing of graphics entails. In this paper we focus on problems related to creating graphical ontologies and exploiting them in the annotation of graphical objects as well as in the development of dialogue strategies. We also present an illustrative example.
Object Recognition with Task Relevant Combined Local Features
Authors: Wenjun Zhu, Liqing Zhang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

A number of cortex-like hierarchical models of object recognition have been proposed these years. In this paper, we improve them by introducing supervision during forming combined local features. The traditional cortex-like hierarchical models always contain three layers which imitate the functions of neurons in ventral visual stream of primates. The bottom layer detects orientation information in a local area. Then the middle layer combines these information to form combined features. Finally, the top layer integrates combined features to form global features which are input into a classifier. In these models, three stages to form global features are all unsupervised. The supervision procedure only occurs after global features are generated, which is implemented by the classifier. But we think the supervision should occurs earlier. For a particular object recognition task, the second stage of generating global features is also supervised because only task relevant combinations are useful. In our paper, we analyze why introducing supervision in this stage is necessary. And we explain task relevant combined local features can be extracted by some feature selection algorithms. We also apply this improved system to a series of object classification problems and compare it with traditional models. The simulation results show that our improvement really boosts object recognition performance.
Integrating Social Commitment-Based Communication in Cognitive Agent Modeling
Authors: Philippe Pasquier, Brahim Chaib-Draa
Venue: Agent Communication II: International Workshops on Agent Communication, AC 2005 and AC 2006, Utrecht, Netherlands, July 25, 2005, and Hakodate, Japan, May 9, 2006, Selected and Revised Papers (2006)

In this paper, we extend the classical BDI architecture for the treatment of social commitments based communication by: (1) linking social commitments and individual intentions, (2) providing a model of the cognitive aspect of communication pragmatics in order to automatize social commitment based communication. In particular, we introduce a general decision-making process leading to attitude change in the appropriate cases.
Exposing the Programming Process
Authors: Jens Bennedsen, Michael E. Caspersen
Venue: Reflections on the Teaching of Programming: Methods and Implementations (2008)

One of the most important goals of an introductory programming course is that the students learn a systematic approach to the development of computer programs. Revealing the programming process is an important part of this. However, textbooks do not address the issue --probably because the textbook medium is static and, therefore, ill-suited to expose the process of programming. We have found that process recordings in the form of captured, narrated programming sessions are a simple, cheap, and efficient way of providing the revelation. We identify seven different elements of the programming process for which process recordings are a valuable communication media in order to enhance the learning process. Student feedback indicates both high learning outcome and superior learning potential compared to traditional classroom teaching.
On Initial Rectifying Learning for Linear Time-Invariant Systems with Rank-Defective Markov Parameters
Authors: Mingxuan Sun
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

This paper presents an initial rectifying learning method for trajectory tracking of linear time-invariant systems with rank-defective Markov parameters. The initial shift problem is addressed through introduction of the initial rectifying action. The role of the rectifying action is examined in case of systems with row and column rank-defective Markov parameters, respectively. Sufficient conditions for convergence of the proposed learning algorithms are derived, by which the learning gains can be chosen. It is shown that the output trajectory converges to the desired one with a smooth transition. The merging of the transition to the desired trajectory occurs at a pre-specified time instant.
Data preparation for clinical data mining in developing a problem list proposing system
Authors: Jau-Huei Lin
Venue:  (2008)

This dissertation was focused on the process of preparing clinical data from its raw format in an electronic health record system to a format appropriate for data mining. The purpose of this data mining effort was to extract logic for a decision support system able to propose medical problems to clinicians. In order to develop a process that could be applied to a large-scaled development, i.e., a decision support system capable of detecting hundreds of medical problems from thousands of variables available in the database, the data preparation process should be systematic and automatic. In this study, a model called "data preparation framework" was developed for the process of data preparation. In the proposed model, data are first retrieved from the data source and transformed into a flattened table format. Then three preprocessing treatments&mdash;missingness representation, general statistical heuristics, and semantic filtering&mdash;are applied to rectify certain data quality problems inherited from the data source. Automatic variable selection algorithms are then used to reduce the number of variables according to their relevance for detecting medical problems. Clinical expertise is used to judge the clinical relevance of each variable in the reduced variable subset, which has been chosen automatically. After expert verification, a data set suitable for further machine learning can be created. To validate the proposed model, a number of experiments were conducted. Two types of measurements were assessed as indicators of performance: clinical relevance of selected variables, judged by clinicians; machine learning performance, evaluated using the area under the receiver operating characteristic curve. The results show that each of the three introduced preprocessing treatments significantly improved the performance, indicated by both types of measurements. In addition, the data sets prepared using the proposed process achieved high clinical relevance and relatively good machine learning performance, compared with various data preparatory pathways tested in the experiment. The proposed data preparation framework incorporates automatic methods with heuristic preprocessing treatments for the potential challenges within a large-scaled development. The automatic methods and heuristic rules can help reduce the demand on manual work in preparing appropriate data and thus make the development feasible.
Beyond quasi-linear utility: strategy/false-name-proof multi-unit auction protocols
Authors: Yuko Sakurai, Yasumasa Saito, Atsushi lwasaki, Makoto Yokoo
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

We develop strategy/false-name-proof multi-unit auction protocols that can handle non-quasi-linear utilities. One almost universal assumption in auction theory literature is that each bidder has quasi-linear utility, except for some works on budget-constrained bidders. In particular, the celebrated VCG protocol is strongly believed to critically depend on the quasi-linear assumption and will break down if this assumption does not hold. We show that with a simple modification, the VCG can handle non-quasi-linear utilities by sacrificing efficiency to a certain extent. The basic idea of this modification is that tentative allocation and payments are determined assuming quasi-linear utilities, but each bidder can choose the actual number of units to obtain based on his non-quasi-linear utility. The modified VCG only uses the gross utility of each bidder. Requiring gross utilities only is an advantage since collecting the entire utility function can be costly. However, determining tentative allocation and payments without considering actual non-quasi-linear utilities can cause significant efficiency loss. Furthermore, the VCG is not robust against false-name-proof. Thus, we propose a new false-name-proof open ascending auction protocol in which each bidder declares his demand for a series of prices. This protocol can improve efficiency without collecting entire utility functions.
A treatment planning code for inverse planning and 3D optimization in hadrontherapy
Authors: F. Bourhaleb, F. Marchetto, A. Attili, G. Pittí, R. Cirio, M. Donetti, S. Giordanengo, N. Givehchi, S. Iliescu, M. Krengli, A. La Rosa, D. Massai, A. Pecka, J. Pardo, C. Peroni
Venue: Computers in Biology and Medicine (2008)

The therapeutic use of protons and ions, especially carbon ions, is a new technique and a challenge to conform the dose to the target due to the energy deposition characteristics of hadron beams. An appropriate treatment planning system (TPS) is strictly necessary to take full advantage. We developed a TPS software, ANCOD++, for the evaluation of the optimal conformal dose. ANCOD++ is an analytical code using the voxel-scan technique as an active method to deliver the dose to the patient, and provides treatment plans with both proton and carbon ion beams. The iterative algorithm, coded in C++ and running on Unix/Linux platform, allows the determination of the best fluences of the individual beams to obtain an optimal physical dose distribution, delivering a maximum dose to the target volume and a minimum dose to critical structures. The TPS is supported by Monte Carlo simulations with the package GEANT3 to provide the necessary physical lookup tables and verify the optimized treatment plans. Dose verifications done by means of full Monte Carlo simulations show an overall good agreement with the treatment planning calculations. We stress the fact that the purpose of this work is the verification of the physical dose and a next work will be dedicated to the radiobiological evaluation of the equivalent biological dose.
A Distributed Privacy-Preserving Association Rules Mining Scheme Using Frequent-Pattern Tree
Authors: Chunhua Su, Kouichi Sakurai
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Association rules mining is a frequently used technique which finds interesting association and correlation relationships among large set of data items which occur frequently together. Nowadays, data collection is ubiquitous in social and business areas. Many companies and organizations want to do the collaborative association rules mining to get the joint benefits. However, the sensitive information leakage is a problem we have to solve and privacy-preserving techniques are strongly needed. In this paper, we focus on the privacy issue of the association rules mining and propose a secure frequent-pattern tree (FP-tree) based scheme to preserve private information while doing the collaborative association rules mining. We show that our scheme is secure and collusion-resistant for n parties, which means that even if n ¿ 1 dishonest parties collude with a dishonest data miner in an attempt to learn the associations rules between honest respondents and their responses, they will be unable to success.
Similarity Search Algorithm for Efficient Sub-trajectory Matching in Moving Databases
Authors: Eun-Cheon Lim, Choon-Bo Shim
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Similarity measure scheme on moving objects has become a topic of increasing in the area of moving databases. In this paper, we propose a new similarity search algorithm for efficient sub-trajectory matching. For measuring similarity between two sub-trajectories, we propose a new v(variable)-warping distance algorithm which enhances the existing time warping distance algorithm by permitting up to v replications for an arbitrary motion of a query trajectory. Our v-warping distance algorithm provides an approximate matching between two trajectories as well as an exact matching between them. Based on our v-warping distance algorithm, we also present a similarity measure scheme for the single trajectory in moving databases. Finally, we show that our scheme based on the v-warping distance achieves much better performance than other conventional schemes, such as Li's one (no-warping) and Shan's one (infinite-warping) in terms of precision and recall measures.
A RST-Resilient Watermarking Scheme Based on Invariant Features
Authors: Yu-xin Zhao, Guang-jie Liu, Yue-wei Dai, Zhi-quan Wang
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

A RST-resilient watermarking scheme based on invariant features are proposed in this paper. The scale-invariant points of wavelet low-frequency sub-image are used to realize resynchronization after RST (Rotation Scale Translation) attacks. An improved HVS model is adopted to embed multiplicative spread spectrum watermark in DWT (Discrete Wavelet Transform) domain, and optimal water- marking detection algorithm is employed to enhance robustness of watermarking. Experiments demonstrate that the proposed scheme can resist both RST and general image processing attacks.
Approximating Generalized Multicut on Trees
Authors: Peng Zhang
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

Given a tree T with costs on edges and a collection of terminal sets X = {S 1, S 2, ..., S l}, the generalized Multicut problem asks to find a set of edges on T whose removal cuts every terminal set in X, such that the total cost of the edges is minimized. The standard version of the problem can be approximately solved by reducing it to the classical Multicut on trees problem. For the prize-collecting version of the problem, we give a primal-dual 3-approximation algorithm and a randomized 2.55-approximation algorithm (the latter can be derandomized). For the k-version of the problem, we show an interesting relation between the problem and the Densest k-Subgraph problem, implying that approximating the k-version of the problem within O(n 1/6 - &epsilon;) for some small &epsilon;> 0 is hard. We also give a min { 2(l - k + 1), k }-approximation algorithm for the k-version of the problem via a nonuniform approach.
Model-Based Segmentation Using Graph Representations
Authors: Dieter Seghers, Jeroen Hermans, Dirk Loeckx, Frederik Maes, Dirk Vandermeulen, Paul Suetens
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

A generic supervised segmentation approach is presented. The object is described as a graph where the vertices correspond to landmarks points and the edges define the landmark relations. Instead of building one single global shape model, a priori shape information is represented as a concatenation of local shape models that consider only local dependencies between connected landmarks. The objective function is obtained from a maximum a posteriori criterion and is build up of localized energies of both shape and landmark intensity information. The optimization problem is discretized by searching candidates for each landmark using individual landmark intensity descriptors. The discrete optimization problem is then solved using mean field annealing or dynamic programming techniques. The algorithm is validated for hand bone segmentation from RX datasets and for 3D liver segmentation from contrast enhanced CT images.
A Framework for the Development of Distributed, Context-Aware Adaptive Hypermedia Applications
Authors: Liliana Ardissono, Anna Goy, Giovanna Petrone
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

The CAWE framework supports the development of context-aware, Service Oriented applications which integrate heterogeneous services and customize the cooperation among multiple users. We present the techniques adopted in the framework to manage a context-sensitive interaction with the users.