ppxscal/embedding_network huggingface dataset:
Proceedings of the 2007 Workshop on New Security Paradigms
Venue: New Security Paradigms Workshop (2008)

NSPW is a unique workshop devoted to the examination of new paradigms in security and the critical study of existing paradigms. Each year since 1992, we examine proposals for new principles upon which information security can be rebuilt from the ground up. We conduct extensive, highly interactive discussions of these proposals, from which we hope both the audience and the authors emerge with a better understanding of the strengths and weaknesses of what has been discussed. It is both the focus on new paradigms and the nature of the interaction during the workshop that makes NSPW a very stimulating event. This year, we were fortunate to have a great program committee and outstanding submissions. In terms of geographical distribution, of the 24 members of the program committee, four were from Europe and the UK, four from Canada, and the rest from the USA. Each program committee member received 4-5 submissions. Each submission was reviewed under a double-bind system. The workshop received 27 submissions (four of which were from industry). Out of these, the program committee accepted 11. The breakdown of the submissions (and acceptances) by geographical region was as follows: 16 submissions had authors from North America (10 accepted), 9 from Europe and the UK (2 accepted), and 3 submissions had authors from other countries 3. Our program committee particularly looked for new paradigms, innovative approaches to older problems, early thinking on new topics, and controversial issues that might not make it into other conferences but deserved to have their try at shaking and breaking the mold. Following the review phase, the program committee held an extensive online discussion, which we believe improved the quality of the feedback to the authors and the program committee chairs. Participation in the workshop was limited to the authors of accepted papers, conference organizers, and a small number of other invitees. Each accepted paper was the focus of one hour of highly interactive discussion with frequent questions and brainstorming. Key points of the comments made during the discussions were scribed and handed to the authors at the end of each session. This feedback made it into the papers you will find in this volume: NSPW is one of the few venues that uses a post-workshop paper revision cycle to allow authors to refine their ideas (and the presentation of their ideas) based on the conversations and interactions at the workshop itself. We hope you will find the end result of this process informative, provocative, and inspiring.
Constraint projections for ensemble learning
Authors: Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou, Qiang Yang
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

It is well-known that diversity among base classifiers is crucial for constructing a strong ensemble. Most existing ensemble methods obtain diverse individual learners through resampling the instances or features. In this paper, we propose an alternative way for ensemble construction by resampling pairwise constraints that specify whether a pair of instances belongs to the same class or not. Using pairwise constraints for ensemble construction is challenging because it remains unknown how to influence the base classifiers with the sampled pairwise constraints. We solve this problem with a two-step process. First, we transform the original instances into a new data representation using projections learnt from pairwise constraints. Then, we build the base classifiers with the new data representation. We propose two methods for resampling pairwise constraints following the standard Bagging and Boosting algorithms, respectively. Extensive experiments validate the effectiveness of our method.
Fatigue Damage Evaluation on Ferromagnetic Materials Using Magnetic Memory Method
Authors: Jiancheng Leng, Minqiang Xu, Shuai Zhao, Jiazhong Zhang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Measuring magnetic parameters nondestructively is important for understanding fatigue phenomena of ferromagnetic materials. In this study, metal magnetic memory method is used as a new diagnostic tool to evaluate fatigue process. Both normal and tangential components of residual magnetic field have been studied on medium carbon steel specimens subjected to rotary bending fatigue. The results indicate that the normal component is related to different stress states while the variation trend of the tangential component with number of cycles shows a good agreement with the fatigue stages. This approach seems to be able to predicate fatigue lifetime.
On Synchronism Control Strategy of Large-Scale Water Press Based on Structure Invariance Principle
Authors: Yucai Zhou, ShaoJun Liu, Minghui Huang, Min Chen, Lihua Zhan
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

The moving beam oflarge –scale water press’s position holdingprecisely plays a great important role in works piece quality. Firstly a precisely synchronism control system is studied ,then the factors which result in the decline of the synchronism control precision are analyzed, finally a new control strategy based on structure invariance is afforded .
Cost-sensitive, Scalable and Adaptive Learning Using Ensemble Methods: Theory and Application
Authors: Wei Fan
Venue:  (2009)

Prior work in inductive learning focused on generic algorithms that sought to reduce complexity. Thus, simplifying assumptions were made. 1. All data resides on a single processor, and resides entirely in main memory; Clearly in modern organizations today, most data resides in a distributed architecture with only small portions being resident in main memory at each moment. 2. Each datum is considered equally important and uniform costs are assumed. In real world contexts, different exemplars frequently have varying costs. 3. All features are freely acquired with no computational or monetary costs. This is unrealistic for many applications, such as medical diagnosis. Usually, the test for each feature consumes different costs and cannot be ignored, i.e., accurate models that only take advantage of the most expensive features are not acceptable. 4. Model is computed on the basis of complete knowledge. A learned hypothesis will be applied to scenarios that are completely represented in the training set. This assumption is more often violated than satisfied. There are usually new and unknown patterns that traditional hypotheses will either ignore or misclassify. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Holonic Rationale and Self-organization on Design of Complex Evolvable Systems
Authors: Paulo Leitão
Venue: Proceedings of the 4th International Conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2009)

Old-fashioned centralized and rigid control structures are becoming inflexible to address the current requirements of reconfigurability, responsiveness and robustness. The Holonic Manufacturing Systems (HMS) paradigm, which was pointed out to face these requirements, translates the concepts inherited from social organizations and biology to the manufacturing world. It offers an alternative way of designing adaptive systems where the traditional centralized control is replaced by decentralization over distributed entities. In spite of its potential, methods regarding the self-adaptation and self-organization of complex systems are still missing. This paper discusses how the insights from biology in connection with new fields of computer science can be useful to enhance the holonic design aiming to achieve more self-adaptive and evolvable systems.
Video Sequence Deinterlacing Using Intensity Gradient Filter and Median Filter with Texture Detection
Authors: Kunhwa Kang, Joohyeok Kim, Jechang Jeong
Venue: Proceedings of the 2009 First International Conference on Advances in Multimedia (2009)

In this paper, we propose a new de-interlacing algorithm for video data using intensity gradient filter and median filter with texture detection in the image block. We first introduce the texture detection. According to texture detection, the current region is determined into smooth region or texture region. In case that the smooth region interpolated by median filter. In addition, in case of the texture region, we calculate missing pixel value using intensity gradient filter. Therefore, we analyze the local region feature using the texture detection and classify each missing pixel into two categories. And then, based on the classification result, a different deinterlacing algorithm is activated in order to obtain the best performance. Experimental results show that the proposed algorithm performs well with a variety of moving sequences compared with traditional intra-field method in the literature.
Probabilistic planning via determinization in hindsight
Authors: Sungwook Yoon, Alan Fern, Robert Givan, Subbarao Kambhampati
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

This paper investigates hindsight optimization as an approach for leveraging the significant advances in deterministic planning for action selection in probabilistic domains. Hindsight optimization is an online technique that evaluates the one-step-reachable states by sampling future outcomes to generate multiple non-stationary deterministic planning problems which can then be solved using search. Hindsight optimization has been successfully used in a number of online scheduling applications; however, it has not yet been considered in the substantially different context of goal-based probabilistic planning. We describe an implementation of hindsight optimization for probabilistic planning based on deterministic forward heuristic search and evaluate its performance on planning-competition benchmarks and other probabilistically interesting problems. The planner is able to outperform a number of probabilistic planners including FF-Replan on many problems. Finally, we investigate conditions under which hindsight optimization is guaranteed to be effective with respect to goal achievement, and also illustrate examples where the approach can go wrong.
Simulation and Experimental Study of a Model Offshore Platform
Authors: Yantao An, Rujian Ma, Meihua Dong, Haiting Zhang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

The simulation and experimental study of a model offshore platform are performed in this paper. A similar model of an offshore platform is designed and constructed. The modal experiments have been done on the model with the method of multi-point excitation and single-point response measurement. The dynamic parameters of the modal are identified including natural frequencies, structural modes and shapes. The comparison of the results between the experiment and the simulation indicates the consistency of design and construction of the similar model and reliability of the experimental data.
New Distinguishing Attack on MAC Using Secret-Prefix Method
Authors: Xiaoyun Wang, Wei Wang, Keting Jia, Meiqin Wang
Venue: Fast Software Encryption: 16th International Workshop, FSE 2009 Leuven, Belgium, February 22-25, 2009 Revised Selected Papers (2009)

This paper presents a new distinguisher which can be applied to secret-prefix MACs with the message length prepended to the message before hashing. The new distinguisher makes use of a special truncated differential path with high probability to distinguish an inner near-collision in the first round. Once the inner near-collision is detected, we can recognize an instantiated MAC from a MAC with a random function. The complexity for distinguishing the MAC with 43-step reduced SHA-1 is 2124.5 queries. For the MAC with 61-step SHA-1, the complexity is 2154.5 queries. The success probability is 0.70 for both.
Research on Virtual NC Technique in High Precision Grinding Process
Authors: Zhigang Jia, Yinbiao Guo, Chen Jiang, Zhenzhong Wang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

A virtual machining system based on virtual manufacturing technique and NC machining technique for high precision grinding machine is developed in this paper, which can realize all processes from the establishment of NC procedure to grinding machining simulation. The virtual machining environment is built with OpenGL technique on the platform of Visual C++, and the geometric simulation and impact interference checking are realized by C++ language. The structure of machining simulation system and its function are proposed. According to grinding machine tool characteristic, appropriate machining path planning is designed. The research shows that the simulations are reliable to complete the virtual grinding machining of the product by checking machining ability, rationality of design, prediction manufacture circle, and promptly modifying design. The method provides the theoretical foundation and reference value of practical application for structure design of grinding machine.
A Novel Fast Motion Estimation Algorithm Based on Starting Search Point Prediction
Authors: Zhaohua Lin, Yanbiao Zou
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

Motion estimation is the most time consuming part of the video coding because of its complexity. A novel fast block matching motion estimation algorithm named Long-Rood fast motion estimation algorithm based on starting search point prediction is proposed for real-time video coding. A number of standard test sequences are adopted for performance comparison of the proposed algorithm and Full Search (FS), Three-Step Search (TSS), Diamond Search (DS) and Adaptive Rood Pattern Search (ARPS) algorithms.The experimental results show that the proposed algorithm is about 3.29~17.24 times faster than that of TSS, 1.71~9.05 times faster than that of DS, and 1.24~4.45 times faster than ARPS, while the Peak Signal-to-Noise Ratio (PSNR) is almost the same or a little higher than the other algorithms.
Towards More Human-Like Episodic Memory for More Human-Like Agents
Authors: Cyril Brom, Jiří Lukavský
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

Episodic memory (EM) is an umbrella term for memory systems that operate with representations of personal history of an entity. The content of EM is related to particular places and moments, and connected to subjective feelings and current goals.Recently, it has been argued that EM is one of the key components contributing to believability of intelligent virtual agents (IVAs), at least when agents interact with humans for more than a couple of minutes, because it allows the user to understand better the agent's history, personality, and internal state: both actual state and past state [e.g. 2, 5]. Technically, the EM is merely a data structure for loss compression of the flow of external events. The EM cannot be implemented as a pure log/video, because these are bad data structures (including human level). Why are they bad? First, they produce too large data. Second, they are not well organised with respect to future possible queries: neither a log nor a video have appropriate indexes in terms of database systems. A better approach is needed.
Implementation of a User Interface Model for Systems Control in Buildings
Authors: Szu-Cheng Chien, Ardeshir Mahdavi
Venue: Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments (2009)

Occupant control actions in a building (i.e. user interactions with environmental systems for heating, cooling, ventilation, lighting, etc.) can significantly affect both indoor climate in and the environmental performance of buildings. Nonetheless, relatively few systematic (long-term and high-resolution) efforts have been made to observe and analyze the means and patterns of such user-system interactions with building systems. Specifically, the necessary requirements for the design and testing of hardware and software systems for user-system interfaces have not been formulated in a rigorous and reliable manner. This paper includes the prototyping of a new generation of user interface model for building systems in sentient buildings. The outcome of these efforts, when realized as a web-based user interface, would allow the occupants to achieve desirable indoor climate conditions with higher levels of connectivity between occupants and sentient environments.
Hierarchical Bayesian domain adaptation
Authors: Jenny Rose Finkel, Christopher D. Manning
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

Multi-task learning is the problem of maximizing the performance of a system across a number of related tasks. When applied to multiple domains for the same task, it is similar to domain adaptation, but symmetric, rather than limited to improving performance on a target domain. We present a more principled, better performing model for this problem, based on the use of a hierarchical Bayesian prior. Each domain has its own domain-specific parameter for each feature but, rather than a constant prior over these parameters, the model instead links them via a hierarchical Bayesian global prior. This prior encourages the features to have similar weights across domains, unless there is good evidence to the contrary. We show that the method of (Daum&eacute; III, 2007), which was presented as a simple "preprocessing step," is actually equivalent, except our representation explicitly separates hyperparameters which were tied in his work. We demonstrate that allowing different values for these hyperparameters significantly improves performance over both a strong baseline and (Daum&eacute; III, 2007) within both a conditional random field sequence model for named entity recognition and a discriminatively trained dependency parser.
Dealing with Objectives in a Constraint-Based Extension to AgentSpeak(L)
Authors: Aniruddha Dasgupta, Aditya K. Ghose
Venue: Multi-Agent Systems for Society: 8th Pacific Rim International Workshop on Multi-Agents, PRIMA 2005, Kuala Lumpur, Malaysia, September 26-28, 2005, Revised Selected Papers (2009)

Incorporating constraints into a reactive BDI agent programming language can lead to better expressive capabilities as well as more efficient computation (in some instances). More interestingly, the use of constraint-based representations can make it possible to deal with explicit agent objectives (as distinct from agent goals) that express the things that an agent may seek to optimize at any given point in time. In this paper we extend the preliminary work of Ooi et.al [1] in augmenting the popular BDI language AgentSpeak(L)[4] with constraint-handling capabilities. We present a slightly modified version of their proposal, in the form of the language CAS (Constraint AgentSpeak). We then extend CAS to form the language CASO (Constraint AgentSpeak with Objectives) to incorporate explicit objectives (represented as objective functions) and present techniques for performing option selection (selecting the best plan to use to deal with the current event) as well as intention selection. In both cases, we present parametric look-ahead techniques, i.e., techniques where the extent of look-ahead style deliberation can be adjusted.
Fuzzy Rule Based Traffic Signal Control System for Oversaturated Intersections
Authors: Syed Muhammad Sheraz, Syed Ali Abbas, Humera Noor
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

A Fuzzy Rule Based Control System is presented in this paper. This control system controls Traffic Signals for regulating traffic on oversaturated intersections with the integration of left and right turns. Based on the Fuzzy Rules, the system decides, whether to extend the current green signal or terminate it. The control system also controls the continuous and safe flow of emergency vehicles.
Bootstrapping least distance estimator in the multivariate regression model
Authors: Myoungshic Jhun, Inkyung Choi
Venue: Computational Statistics Data Analysis (2009)

The most popular estimation methods in multivariate linear regression are the multivariate least squares estimation and the multivariate least absolute estimation. Each method repeats its univariate estimation method p, the number of response variables, times. Although they are relatively easy to apply, they do not employ the relationship between response variables. This study considers the multivariate least distance estimator of Bai et al. (1990) that accounts for this relationship. We confirm its relative efficiency with respect to the multivariate least absolute estimator under the multivariate normal distribution and contaminated distribution. However, the asymptotic inference of the multivariate least distance estimator is shown to perform poorly in certain circumstances. We suggest the bootstrap method to infer the regression parameters and confirm its viability using Monte Carlo studies.
Classification of Fundus Images for Diagnosing Glaucoma by Self-Organizing Map and Learning Vector Quantization
Authors: Nobuo Matsuda, Jorma Laaksonen, Fumiaki Tajima, Hideaki Sato
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

This paper presents a two stage diagnosis system that consists of Self-Organizing Map (SOM) and Learning Vector Quantization (LVQ) subsystems for diagnosis of fundus images. The first stage performs clustering and pseudo-classification of the input feature data by a SOM. The use of the pseudo-classes is able to improve the performance of the second stage consisting of a LVQ codebook. The proposed system has been tested on real medical treatment image data. In the experiments we have achieved a maximum accuracy rate of 71.2%, which is comparable to other results in literature.