ppxscal/embedding_network huggingface dataset:
Cluster-grouping: from subgroup discovery to clustering
Authors: Albrecht Zimmermann, Luc Raedt
Venue: Machine Learning (2009)

We introduce the problem of cluster-grouping and show that it can be considered a subtask in several important data mining tasks, such as subgroup discovery, mining correlated patterns, clustering and classification. The algorithm CG for solving cluster-grouping problems is then introduced, and it is incorporated as a component in several existing and novel algorithms for tackling subgroup discovery, clustering and classification. The resulting systems are empirically compared to state-of-the-art systems such as CN2, CBA, Ripper, Autoclass and CobWeb. The results indicate that the CG algorithm can be useful as a generic local pattern mining component in a wide variety of data mining and machine learning algorithms.
An Improved SPECK Algorithm with Bit Plane Lifting and the Optimal Single Value Prediction
Authors: Xubing Zhang, Yong Zhu, Jianhong Fu
Venue: Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 02 (2009)

SPECK has been found to be competitive in compression of images, while the visual importance of DWT LL sub-band has not been utilized in the SPECK. To improve the compression capability of the SPECK further, this paper presents the LFP-SPECK (Low Frequency Prior SPECK) algorithm. By lifting the bit planes of low frequency sub-band coefficients LFP-SPECK algorithm encodes low frequency sub-band firstly. The double LSP (List of Significant Pixels) lists are adopted here to avoid increasing bits when lifting bit planes. In addition, the algorithm reduces redundancy of the LL sub-band with the optimal single-value linear prediction. The experimental results show that LFP-SPECK algorithm is effective.
A2M: Access-Assured Mobile Desktop Computing
Authors: Angelos Stavrou, Ricardo A. Barrato, Angelos D. Keromytis, Jason Nieh
Venue: Proceedings of the 12th International Conference on Information Security (2009)

Continued improvements in network bandwidth, cost, and ubiquitous access are enabling service providers to host desktop computing environments to address the complexity, cost, and mobility limitations of today's personal computing infrastructure. However, distributed denial of service attacks can deny use of such services to users. We present A2M, a secure and attack-resilient desktop computing hosting infrastructure. A2M combines a stateless and secure communication protocol, a single-hop Indirection-based network (IBN) and a remote display architecture to provide mobile users with continuous access to their desktop computing sessions. Our architecture protects both the hosting infrastructure and the client's connections against a wide range of service disruption attacks. Unlike any other DoS protection system, A2M takes advantage of its low-latency remote display mechanisms and asymmetric traffic characteristics by using multi-path routing to send a small number of replicas of each packet transmitted from client to server. This packet replication through different paths, diversifies the client-server communication, boosting system resiliency and reducing end-to-end latency. Our analysis and experimental results on PlanetLab demonstrate that A2M significantly increases the hosting infrastructure's attack resilience even for wireless scenarios. Using conservative ISP bandwidth data, we show that we can protect against attacks involving thousands (150,000) attackers, while providing good performance for multimedia and web applications and basic GUI interactions even when up to 30% and 50%, respectively, of indirection nodes become unresponsive.
Impact of item density on magic lens interactions
Authors: Michael Rohs, Georg Essl, Johannes Schöning, Anja Naumann, Robert Schleicher, Antonio Krüger
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

We conducted a user study to investigate the effect of visual context in handheld augmented reality interfaces. A dynamic peephole interface (without visual context beyond the device display) was compared to a magic lens interface (with video see-through augmentation of external visual context). The task was to explore objects on a map and look for a specific attribute shown on the display. We tested different sizes of visual context as well as different numbers of items per area, i.e. different item densities. We found that visual context is most effective for sparse item distributions and the performance benefit decreases with increasing density. User performance in the magic lens case approaches the performance of the dynamic peephole case the more densely spaced the items are. In all conditions, subjective feedback indicates that participants generally prefer visual context over the lack thereof. The insights gained from this study are relevant for designers of mobile AR and dynamic peephole interfaces by suggesting when external visual context is most beneficial.
Efficient Range Indexing in DHT-Based Peer-to-Peer Networks
Authors: Tan Yunsong, Wu Yuntao
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

A fundamental problem of peer-to-peer (P2P) systems is efficiently locating a node that stores a desired data item. Distributed hash table (DHT) mechanisms have been proposed to address this problem and manage data in very large, structured P2P systems. DHT algorithms provide efficient exact match object search capabilities without requiring global indexing and are hence extremely scalable. However, supporting range queries efficiently remains a difficult problem. In this paper, we describe an extension to a currently available DHT implementation, in order to support range queries and at the same time preserve the important attributes of P2P systems.
A Study on the Icon Feedback Types of Small Touch Screen for the Elderly
Authors: Wang-Chin Tsai, Chang-Franw Lee
Venue: Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments (2009)

Small touch screens are widely used in applications such as bank ATMs, point-of-sale terminals, ticket vending machines, facsimiles, and home automation in the daily life. It is intuition-oriented and easy to operate. There are a lot of elements that affect the small screen touch performance. One of the essential parts is icon feedback. However, to merely achieve beautiful icon feedback appearance and create interesting interaction experience, many interface designers ignore the real user needs. It is critical for them to trade off the icon feedback type associated with the different users needs in the touch interaction. This is especially important when the user capability is very limited. This paper described a pilot study for identifying factors that determine the icon feedback usability on small touch screen in four older adult Cognitrone groups since current research aimed mostly at general icon guidelines and recommendations and failed to consider and define the specific needs of small touch screen interfaces for the elderly. In this paper, we presented a concept from the focus on human necessity and use a cognitive assessment tool, which is, Cognitrone test, to measure older adult's attention and concentration capability and learn more about how to evaluate and design suitable small screen icon feedback types. Forty-five elder participants were participated. Each subject was asked to complete a battery of Cognitrone tests and divided into 4 groups. Each subject was also requested to perform a set of `continuous touch' usability tasks on small touch screen and comment on open-ended questions. Results are discussed with respect to the perceptual and cognitive factors that influence older adults in the use of icon feedback on small touch screen. It showed significant associations between icon feedback performance and factors of attention and concentration. However, this interrelation was much stronger for the Group 2 and Group 4, especially for Type B, Type C and Type G. Moreover, consistent with previous research, older participants were less sensitive and required longer time to adapt to the high-detailed icon feedback. These results are discussed in terms of icon feedback design strategies for interface designers.
Trajectory Planning and Simulation of a New Symmetric Parallel Mechanism with Three Translational DOF
Authors: Xiuqing Hao, Lei Sun
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Lower mobility parallel robot mechanisms have become analysis hotspot in the field of parallel robot mechanisms because of the characteristics of simple structure, lower price and easy control, they have good prospect in industrial application. In this paper, a new symmetric 3-PCR parallel robot mechanism was designed according to screw theory and single opened chain type synthesis method. On the basis of the structure analysis to 3-PCR parallel robot mechanism, the inverse position equation was built up and the planning method of non-parametric models motion trajectory was studied using inverse analysis theory of kinematics. The course of the trajectory planning was illustrated through a practical example. At last, the method of trajectory planning was proved to be feasible through simulation in ADAMS software.
Privacy-Preserving Classifier Learning
Authors: Justin Brickell, Vitaly Shmatikov
Venue: Financial Cryptography and Data Security: 13th International Conference, FC 2009, Accra Beach, Barbados, February 23-26, 2009. Revised Selected Papers (2009)

We present an efficient protocol for the privacy-preserving, distributed learning of decision-tree classifiers. Our protocol allows a user to construct a classifier on a database held by a remote server without learning any additional information about the records held in the database. The server does not learn anything about the constructed classifier, not even the user's choice of feature and class attributes.Our protocol uses several novel techniques to enable oblivious classifier construction. We evaluate a prototype implementation, and demonstrate that its performance is efficient for practical scenarios.
Application of Support Vector Machine in TCM Diagnosis
Authors: Jun-Feng Yan, Yan Zhan, Wen-Feng Zhu
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

The paper expounds the thinking, methodologies and characteristics about the technology of support vector machine which is applied in Traditional Chinese Medicine (TCM ) Diagnosis. The research shows that it is feasible to search syndrome factors decision-making model by using support vector machine. Nevertheless, to improve the accuracy level of search, further studies on such closely relevant subjects as specification of TCM glossary and on further convergence between computer science and TCM are crucial.
A new clause learning scheme for efficient unsatisfiability proofs
Authors: Knot Pipatsrisawat, Adnan Darwiche
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

We formalize in this paper a key property of asserting clauses (the most common type of clauses learned by SAT solvers). We show that the formalized property, which is called empowerment, is not exclusive to asserting clauses, and introduce a new class of learned clauses which can also be empowering. We show empirically that (1) the new class of clauses tends to be much shorter and induce further backtracks than asserting clauses and (2) an empowering subset of this new class of clauses significantly improves the performance of the Rsat solver on unsatisfiable problems.
Understanding Activity Documentation Work in Remote Mobility Environments
Authors: Alberto L. Morán, Raul Casillas
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

Activity documentation is a critical part of the work of many professionals. Documents are used as a means to store personal information, remind things to do, convey and generate new meaning, and mediate contact among people. In this paper, and based on the results of an observational study, we propose a model of how activity documentation work in remote mobility environments is performed. Further, based on this model and on some identified issues that remote mobility workers face while performing activity documentation work, we propose a set of design insights that designers and developers of support systems could use to inform their designs and developments. These results allow designers and developers not only to support a single activity documentation work phase if so desired, but also to envision the creation of comprehensive services for activity documentation work throughout its complete lifecycle in a seamless, effortless and secure manner.
A Structured Approach to Incident Response Management in the Oil and Gas Industry
Authors: Maria B. Line, Eirik Albrechtsen, Martin Gilje Jaatun, Inger Anne Tøndel, Stig Ole Johnsen, Odd Helge Longva, Irene Wærø
Venue: Critical Information Infrastructure Security: Third International Workshop, CRITIS 2008, Rome, Italy, October13-15, 2008. Revised Papers (2009)

Incident Response is the process of responding to and handling ICT security related incidents involving infrastructure and data. This has traditionally been a reactive approach, focusing mainly on technical issues. In this paper we present the Incident Response Management (IRMA) method, which combines traditional incident response with pro-active learning and socio-technical perspectives. The IRMA method is targeted at integrated operations within the oil and gas industry.
Query Answering in Belief Logic Programming
Authors: Hui Wan, Michael Kifer
Venue: Proceedings of the 3rd International Conference on Scalable Uncertainty Management (2009)

In this paper we introduce a fixpoint semantics for quantitative logic programming, which is able to both combine and correlate evidence from different sources of information. Based on this semantics, we develop efficient algorithms that can answer queries for non-ground programs with the help of an SLD-like procedure. We also analyze the computational complexity of the algorithms and illustrate their uses.
Wearable Modular Device for Facilitation of Napping and Optimization of Post-nap Performance
Authors: Djordje Popovic, Giby Raphael, Robin Johnson, Gene Davis, Chris Berka
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

Sleep deprivation-induced deficiencies in performance can be associated with high financial and human costs. Napping is an effective countermeasure, but the effects depend on previously accumulated sleep debt and timing, duration and sleep architecture of the naps. Long-term assessment of sleep architecture of nap/sleep episodes could yield an estimate of the accumulated sleep debt and help optimize the napping schedule. Moreover, sensory stimulation coupled with real-time assessment of sleep states could optimize sleep architecture and duration of each nap. With these goals in mind we designed a wearable device, dubbed Nap Cap, which integrates real-time EEG analysis with audio, visual and thermal stimulation. The prototype was evaluated on seven subjects (fully rested vs. sleep-deprived). While the prototype provided high quality EEG and comfort, sensory stimulation did not significantly influence sleep architecture. Evaluation of more paradigms of sensory stimulation on larger samples is warranted before final conclusions can be made.
Screen-space perceptual rendering of human skin
Authors: Jorge Jimenez, Veronica Sundstedt, Diego Gutierrez
Venue: ACM Transactions on Applied Perception (TAP) (2009)

We propose a novel skin shader which translates the simulation of subsurface scattering from texture space to a screen-space diffusion approximation. It naturally scales well while maintaining a perceptually plausible result. This technique allows us to ensure real-time performance even when several characters may appear on screen at the same time. The visual realism of the resulting images is validated using a subjective psychophysical preference experiment. Our results show that, independent of distance and light position, the images rendered using our novel shader have as high visual realism as a previously developed physically-based shader.
Acquiring domain-specific dialog information from task-oriented human-human interaction through an unsupervised learning
Authors: Ananlada Chotimongkol, Alexander I. Rudnicky
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

We describe an approach for acquiring the domain-specific dialog knowledge required to configure a task-oriented dialog system that uses human-human interaction data. The key aspects of this problem are the design of a dialog information representation and a learning approach that supports capture of domain information from in-domain dialogs. To represent a dialog for a learning purpose, we based our representation, the form-based dialog structure representation, on an observable structure. We show that this representation is sufficient for modeling phenomena that occur regularly in several dissimilar task-oriented domains, including information-access and problem-solving. With the goal of ultimately reducing human annotation effort, we examine the use of unsupervised learning techniques in acquiring the components of the form-based representation (i.e. task, subtask, and concept). These techniques include statistical word clustering based on mutual information and Kullback-Liebler distance, TextTiling, HMM-based segmentation, and bisecting K-mean document clustering. With some modifications to make these algorithms more suitable for inferring the structure of a spoken dialog, the unsupervised learning algorithms show promise.
Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines
Authors: Sangkyun Lee, Stephen J. Wright
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

We describe a method for solving large-scale semiparametric support vector machines (SVMs) for regression problems. Most of the approaches proposed to date for large-scale SVMs cannot accommodate the multiple equality constraints that appear in semiparametric problems. Our approach uses a decomposition framework, with a primal-dual algorithm to find an approximate saddle point for the min-max formulation of each subproblem. We compare our method with algorithms previously proposed for semiparametric SVMs, and show that it scales well as the number of training examples grows.
Design of ACC Controller Based on Double Level Mamdani Reasoning
Authors: Li Jing-liang, Liu Zhao-du
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

The influence of the tire-road friction to the ACC controller has been analyzed. A double level Mamdani reasoning based ACC fuzzy controller has been established. The membership functions and the reasoning rules have been founded. The simulation results indicates that the ACC controller has very good character of road adaptive, and it performance very well in distance keeping and speed following.
Robust Joint Entropy Regularization of Limited View Transmission Tomography Using Gaussian Approximations to the Joint Histogram
Authors: Dominique Sompel, Sir Michael Brady
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

Information theoretic measures to incorporate anatomical priors have been explored in the field of emission tomography, but not in transmission tomography. In this work, we apply the joint entropy prior to the case of limited angle transmission tomography. Due to the data insufficiency problem, the joint entropy prior is found to be very sensitive to local optima. Two methods for robust joint entropy minimization are proposed. The first approximates the joint probability density function by a single 2D Gaussian, and is found to be appropriate for reconstructions where the ground truth joint histogram is dominated by two clusters, or multiple clusters that are roughly aligned. The second method is an extension to the case of multiple Gaussians. The intended application for the single Gaussian approximation is digital breast tomosynthesis, where reconstructed volumes are approximately bimodal, consisting mainly of fatty and fibroglandular tissues.
Illuminant Change Estimation via Minimization of Color Histogram Divergence
Authors: Michela Lecca, Stefano Messelodi
Venue: Computational Color Imaging: Second International Workshop, CCIW 2009, Saint-Etienne, France, March 26-27, 2009. Revised Selected Papers (2009)

We present a new method for computing the change of light possibly occurring between two pictures of the same scene. We approximate the illuminant variation with the von Kries diagonal transform and estimate it by minimizing a functional that measures the divergence between the image color histograms. Our approach shows good performances in terms of accuracy of the illuminant change estimation and of robustness to pixel saturation and Gaussian noise. Moreover we illustrate how the method can be applied to solve the problem of illuminant invariant image recognition.
Achieving Business Agility by Integrating SOA and BPM Technology
Authors: Chen Ling, Lu Xin
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

The application system of business must be fast enough to response the change from customer's request in current complex business environment. Business agility can ensure the enterprise survives in the explosive competition. In this paper, the author will analyze the limitation and deficiency of the business agility in the traditional enterprise application integration, and propose a novel enterprise application integration and business agility scheme centered as Business Process Management (BPM), based on Service-Oriented Architecture (SOA). On the further discussion of SOA and BPM’s combining principle, the author will propose a new method that BPM agent acts as the connection of SOA and BPM. Through the Coordination of undergoing process and service based on BPM agent, it will reduce the influence causing by separating change of SOA and BPM in maximum, and finally achieve the business agility
Automatic bounding of programmable shaders for efficient global illumination
Authors: Edgar Velázquez-Armendáriz, Shuang Zhao, Miloš Hašan, Bruce Walter, Kavita Bala
Venue: ACM Transactions on Graphics (TOG) (2009)

This paper describes a technique to automatically adapt programmable shaders for use in physically-based rendering algorithms. Programmable shading provides great flexibility and power for creating rich local material detail, but only allows the material to be queried in one limited way: point sampling. Physically-based rendering algorithms simulate the complex global flow of light through an environment but rely on higher level information about the material properties, such as importance sampling and bounding, to intelligently solve high dimensional rendering integrals. We propose using a compiler to automatically generate interval versions of programmable shaders that can be used to provide the higher level query functions needed by physically-based rendering without the need for user intervention or expertise. We demonstrate the use of programmable shaders in two such algorithms, multidimensional lightcuts and photon mapping, for a wide range of scenes including complex geometry, materials and lighting.