ppxscal/embedding_network huggingface dataset:
On the Approximability of Geometric and Geographic Generalization and the Min-Max Bin Covering Problem
Authors: Wenliang Du, David Eppstein, Michael T. Goodrich, George S. Lueker
Venue: Proceedings of the 11th International Symposium on Algorithms and Data Structures (2009)

We study the problem of abstracting a table of data about individuals so that no selection query can identify fewer than k individuals. We show that it is impossible to achieve arbitrarily good polynomial-time approximations for a number of natural variations of the generalization technique, unless P = NP, even when the table has only a single quasi-identifying attribute that represents a geographic or unordered attribute: - Zip-codes: nodes of a planar graph generalized into connected subgraphs - GPS coordinates: points in R2 generalized into non-overlapping rectangles - Unordered data: text labels that can be grouped arbitrarily. These hard single-attribute instances of generalization problems contrast with the previously known NP-hard instances, which require the number of attributes to be proportional to the number of individual records (the rows of the table). In addition to impossibility results, we provide approximation algorithms for these difficult single-attribute generalization problems, which, of course, apply to multiple-attribute instances with one that is quasi-identifying. Incidentally, the generalization problem for unordered data can be viewed as a novel type of bin packing problem---min-max bin covering---which may be of independent interest.
Lexical encoding of MWEs
Authors: Aline Villavicencio, Ann Copestake, Benjamin Waldron, Fabre Lambeau
Venue: Proceedings of the Workshop on Multiword Expressions: Integrating Processing (2004)

Multiword Expressions present a challenge for language technology, given their flexible nature. Each type of multiword expression has its own characteristics, and providing a uniform lexical encoding for them is a difficult task to undertake. Nonetheless, in this paper we present an architecture for the lexical encoding of these expressions in a database, that takes into account their flexibility. This encoding extends in a straightforward manner the one required for simplex (single) words, and maximises the information contained for them in the description of multiwords.
Problems and Landscape Approach for Ecological Rehabilitation in the Dry Valleys of Southwest China
Authors: Yuhong Dong, Shiliang Liu
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

The degradation and rehabilitation of dry valley are increasingly a focus of scientific and applied interest. This paper reviews the general conditions of eco-environmental degradation and puts forward a landscape approach for rehabilitation. Primarily, soil and vegetation degradation is the main cause of the degradation. Systematic analysis and insights into the soil and vegetation degradation phenomena and essences are needed for recovery. Bottom-up approach rehabilitation of dry valleys with farmer’s participation is needed and the relationship of ecological, social, economical factors should be considered and different measures should be taken. Finally, landscape approach for rehabilitation in relation to the policy “return farmland into forest” vegetation recovery, and afforestation are discussed.
Wireless spectrum prediction model based on time series analysis method
Authors: Jinzhao Su, Wei Wu
Venue: Proceedings of the 2009 ACM workshop on Cognitive radio networks (2009)

Cognitive Radio (CR) is considered to be a solution for mitigating the conflict between limited spectrum resources and increasing demand of various applications. For the purpose of guaranteeing primary users, we propose a spectrum prediction model using the spectrum historic utilization information with time series analysis. We conduct experiment on wide TV bands of China from 603.25 MHz to 843.25 MHz, the results show that this model can accurately predict status of channels and find vacant spectrum for cognitive users. We take channel 2 whose center frequency locates in 615.25 MHz for example, average forecasting error ratio is 1.01% with a minimum of 0.79%.
Toward affective cognitive robots for human-robot interaction
Authors: M. Scheutz, J. Kramer, C. Middendorff, P. Schermerhorn, M. Heilman, D. Anderson, P. Bui
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 4 (2005)

We present a brief overview of an architecture for a complex affective robot for human-robot interaction.
BlenX4Bio --- BlenX for Biologists
Authors: Corrado Priami, Paolo Ballarini, Paola Quaglia
Venue: Proceedings of the 7th International Conference on Computational Methods in Systems Biology (2009)

We introduce BlenX4Bio, a high-level interface for the programming language BlenX. BlenX4Bio allows biologists to write BlenX programs without having any programming skills. The main elements of a biological model are specified by filling in a number of tables. Such tables include descriptions of both static and dynamic aspects of the biological system at hand and can then be automatically mapped to BlenX programs for simulation and analysis by means of the CoSBi Lab software platform. In this paper we illustrate the main characteristics of BlenX4Bio through examples taken from biology textbooks.
Automatic text summarization of newswire: lessons learned from the document understanding conference
Authors: Ani Nenkova
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

Since 2001, the Document Understanding Conferences have been the forum for researchers in automatic text summarization to compare methods and results on common test sets. Over the years, several types of summarization tasks have been addressed--single document summarization, multi-document summarization, summarization focused by question, and headline generation. This paper is an overview of the achieved results in the different types of summarization tasks. We compare both the broader classes of baselines, systems and humans, as well as individual pairs of summarizers (both human and automatic). An analysis of variance model is fitted, with summarizer and input set as independent variables, and the coverage score as the dependent variable, and simulation-based multiple comparisons were performed. The results document the progress in the field as a whole, rather then focusing on a single system, and thus can serve as a future reference on the work done up to date, as well as a starting point in the formulation of future tasks. Results also indicate that most progress in the field has been achieved in generic multi-document summarization and that the most challenging task is that of producing a focused summary in answer to a question/topic.
A robot that uses existing vocabulary to infer non-visual word meanings from observation
Authors: Kevin Gold, Brian Scassellati
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

The authors present TWIG, a visually grounded word-learning system that uses its existing knowledge of vocabulary, grammar, and action schemas to help it learn the meanings of new words from its environment. Most systems built to learn word meanings from sensory data focus on the "base case" of learning words when the robot knows nothing, and do not incorporate grammatical knowledge to aid the process of inferring meaning. The present study shows how using existing language knowledge can aid the word-learning process in three ways. First, partial parses of sentences can focus the robot's attention on the correct item or relation in the environment. Second, grammatical inference can suggest whether a new word refers to a unary or binary relation. Third, the robot's existing predicate schemas can suggest possibilities for a new predicate. The authors demonstrate that TWIG can use its understanding of the phrase '"got the ball" while watching a game of catch to learn that "I" refers to the speaker, "you" refers to the addressee, and the names refer to particular people. The robot then uses these new words to learn that "am" and "are" refer to the identity relation.
Face Recognition Based on Grey Relation Metric
Authors: Liu Zunxiong, Cao Yuhong, Xu Zheng
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

There are many distance metrics used in nearest neighbor classifiers. In this paper a grey relation metric, the balance incident degree (BID) is proposed as distance metric based on exploring the theory about grey relational analysis. The presented approach with the method of eigenface is applied in face recognition and compared with the common distance metrics. Through the experiments with ORL dataset, the recognition rates for BID are better than other metrics in the same condition. BID method can also cope with the high dimension problem. The results demonstrate BID can be a good distance metric and deduce into more applications.
Research on Supply-Chain-Based Logistics Service Capability by Combination Weighting Method and Fuzzy VIKOR Algorithm
Authors: Yuansheng Huang, Ying Yan, ZhiWen Qiu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

To realize and effectively manage the customer-oriented logistics capability in supply chain enterprises, a constituent system was established for supply chain logistics service capability. In this study, fuzzy VIKOR algorithm was employed to evaluate the customer-oriented supply-chain-based logistics service capability for supply chain enterprises as solving a multi-criteria decision-making problem. A combination weighting method formed by compared respectively fuzzy weight method and fuzzy entropy weight method is put forward in this paper, it can combine subjectivity and objectivity effectively and can reflect the policymaker's will rationally. At last the effectiveness of our approach was verified by testing the method with an example.
The more the merrier: multi-party negotiation with virtual humans
Authors: Patrick Kenny, Arno Hartholt, Jonathan Gratch, David Traum, Stacy Marsella, Bill Swartout
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

The goal of the Virtual Humans Project at the University of Southern California's Institute for Creative Technologies is to enrich virtual training environments with virtual humans - autonomous agents that support face-to-face interaction with trainees in a variety of roles - through bringing together many different areas of research including speech recognition, natural language understanding, dialogue management, cognitive modeling, emotion modeling, nonverbal behavior and speech and knowledge management. The demo at AAAI will focus on our work using virtual humans to train negotiation skills. Conference attendees will negotiate with a virtual human doctor and elder to try to move a clinic out of harm's way in single and multiparty negotiation scenarios using the latest iteration of our Virtual Humans framework. The user will use natural speech to talk to the embodied agents, who will respond in accordance with their internal task model and state. The characters will carry out a multi-party dialogue with verbal and nonverbal behavior. A video of a single-party version of the scenario was shown at AAAI-06. This new interactive demo introduces several new features, including multiparty negotiation, dynamically generated non-verbal behavior and a central ontology.
Participatory Ergonomics as a Method of Quality Improvement in Maintenance
Authors: Małgorzata Jasiulewicz-Kaczmarek
Venue: Proceedings of the International Conference on Ergonomics and Health Aspects of Work with Computers: Held as Part of HCI International 2009 (2009)

Modern enterprises are forced to constantly improve ways of management and to introduce changes. One of the changes is a alteration of organizational culture and acceptance of participation of employees in designing and implementing new solutions. Striving for general improvement of system efficiency involves joint design of technical and social systems to achieve the best fitness to goals and requirements of system and its parts possible. Not only technical objects, but also workers and workplaces (work environment) require keeping in good condition. Such approach to maintenance stresses human importance and workers place in systems they work in. It also stresses necessity for not engineers, but also quality and ergonomics experts as well as technical objects users to involve into maintenance actions and processes. The paper presents potential of participatory ergonomics to maintenance quality improvement use.
The Uniformization and the Feature Selection about the Inconsistent Classification Data Set
Authors: Xin-ling Wu, Dong-feng He, Guo-qiang Zhou
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

The inconsistency and redundant attributes of a sample data set will drop the classification quality and efficiency. In this paper, the method that can make the classification data set consistent and select a smallest feature variable set is proposed. This method groups together the inconsistent datum of the most likely category to make the data set uniform, based on Bayesian formula. Then with the uniform data set, a category distinction matrix is built and the smallest feature variable subset that can distinguish the category accurately is obtained through the category distinction matrix. A heuristic search strategy is given to select the feature variables. The experiment results using some UCI standard datasets show the proposed method can eliminate the inconsistency of the sample dataset, select the optimal feature variables and drop the dimension of the data effectively.
Simulation on Improving Imaging Resolution of SAFT
Authors: Qiufeng Li, Xinhong Jin, Min Zhao, Lihua Shi, Zhixue Shao
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Concrete is one of the main construction materials in civil engineering. Among the existing Nondestructive Testing (NDT) methods, the imaging techniques that can give a graphic display of the inner structure of the concrete elements have received great attention. Because of several kinds of disturbing signals in the concrete structures imaging by low frequency ultrasound, low signal-noise ratio and poor resolution are engendered. Synthetic Aperture Focusing Technique (SAFT) is one of effect methods in the ultrasonic NDT area, and can focus effectively to reflected waves, and improve the reconstructed image’s resolution through rough B-scan method. For low-frequency excitation signal, however, wavepacket distortion is produced during the focusing process, which decreases test resolution. Therefore, Wavepacket Decomposition Technique (WDT), which can put the whole reflected wavepacket into focusing calculation, is introduced here to improve the reconstructed resolution. This technique solves the problem of wavepacket distortion, and better focusing effect and resolution are obtained. Furthermore, calculating velocity is increased because the points joined into SAFT calculation are cut down greatly. The presented technique has been verified by the simulation experiment. From the results, the method can improve more the ability of localizing object and give better imaging effect.
DEMScale: Large Scale MDS Accounting for a Ridge Operator and Demographic Variables
Authors: Stephen L. France, J. Douglas Carroll
Venue: Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII (2009)

In this paper, a method called DEMScale is introduced for large scale MDS. DEMScale can be used to reduce MDS problems into manageable sub-problems, which are then scaled separately. The MDS items can be split into sub-problems using demographic variables in order to choose the sections of the data with optimal and sub-optimal mappings. The lower dimensional solutions from the scaled sub-problems are recombined by taking sample points from each sub-problem, scaling the sample points, and using an affine mapping with a ridge operator to map the non-sample points. DEMScale builds upon the methods of distributional scaling and FastMDS, which are used to split and recombine MDS mappings. The use of a ridge regression parameter enables DEMScale to achieve stronger solution stability than the basic distributional scaling and FastMDS techniques. The DEMScale method is general, and is independent of the MDS technique and optimization method used.
True Positive Cost Curve: A Cost-Based Evaluation Method for High-Interaction Client Honeypots
Authors: Christian Seifert, Peter Komisarczuk, Ian Welch
Venue: Proceedings of the 2009 Third International Conference on Emerging Security Information, Systems and Technologies (2009)

Client honeypots are security devices designed to find servers that attack clients. High-interaction client honeypots (HICHPs) classify potentially malicious web pages by driving a dedicated vulnerable web browser to retrieve and classify these pages. Considering the size of the Internet, the ability to identify many malicious web pages is a crucial task. HICHPs, however, present challenges: They are slow and tend to miss attacks. For researchers to address these shortcomings, they need methods for evaluating HICHPs. This paper (1) presents an evaluation method called the True Positive Cost Curve (TPCC), which makes it possible to evaluate and compare HICHPs in an operating environment, but also allows an operator to tune HICHPs within a specific operating environment; (2) presents improvements on the way HICHPs visit web pages and evaluates them with the TPCC method; and (3) discusses the impact of time bombs on the performance of HICHPs in an operating environment and the ability to tune an HICHP for optimal performance with the help of the TPCC.
Development of Applications Based on Security Patterns
Authors: Daniel Serrano, José F. Ruiz, Antonio Munoz, Antonio Mana, Alvaro Armenteros, Beatriz Gallego-Nicaso Crespo
Venue: Proceedings of the 2009 Second International Conference on Dependability (2009)

Current approaches for software development fail in the integration of security aspects. Usually, this is because of the software complexity and the speciﬁc expertise needed for the integration of modern security solutions. In this paper we present the SERENITY Project which proposes a framework addressing this issue. SERENITY is based on the separation of the development of security solutions from the development of secure software supported by these security solutions. Both developments, security solutions and secure applications, are centered on the use of libraries of precise descriptions of reusable security solutions stored in the form of security patterns. This approach ﬁts very well with new emerging scenarios such as ambient intelligence, ubiquitous computing, grids, etc. In this paper we present the development of a secure application based on these ideas, in order to do that, we introduce an Application Programming Interface (API) specially designed for use SERENITY advantages.
Optimization Models for Determining Performance Benchmarks in Wireless Sensor Networks
Authors: Valeria Loscri, Enrico Natalizio, Carmelo Costanzo, Francesca Guerriero, Antonio Violi
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

In this paper we propose some innovative optimization models for Wireless Sensor Networks. The models are chosen depending on the task the network is called to execute and they focus on the optimization of some specific performance objectives. Indeed, starting from a generic configuration, the optimal solution defines a specific sensors displacement, which allows the network to achieve high performance, in terms of energy consumption and travelled distance. Controlled mobility of the nodes is used for reaching the wanted displacement. The behavior of the proposed models has been evaluated in comparison with a distributed algorithm on the basis of an extensive computational study and by considering different scenarios.
Designing Reliable and Efficient Networks on Chips, 1st edition
Authors: Srinivasan Murali
Venue:  (2009)

Developing NoC based interconnect tailored to a particular application domain, satisfying the application performance constraints with minimum power-area overhead is a major challenge. With technology scaling, as the geometries of on-chip devices reach the physical limits of operation, another important design challenge for NoCs will be to provide dynamic (run-time) support against permanent and intermittent faults that can occur in the system. The purpose of Designing Reliable and Efficient Networks on Chips is to provide state-of-the-art methods to solve some of the most important and time-intensive problems encountered during NoC design.
All-frequency rendering of dynamic, spatially-varying reflectance
Authors: Jiaping Wang, Peiran Ren, Minmin Gong, John Snyder, Baining Guo
Venue: ACM Transactions on Graphics (TOG) (2009)

We describe a technique for real-time rendering of dynamic, spatially-varying BRDFs in static scenes with all-frequency shadows from environmental and point lights. The 6D SVBRDF is represented with a general microfacet model and spherical lobes fit to its 4D spatially-varying normal distribution function (SVNDF). A sum of spherical Gaussians (SGs) provides an accurate approximation with a small number of lobes. Parametric BRDFs are fit on-the-fly using simple analytic expressions; measured BRDFs are fit as a preprocess using nonlinear optimization. Our BRDF representation is compact, allows detailed textures, is closed under products and rotations, and supports reflectance of arbitrarily high specularity. At run-time, SGs representing the NDF are warped to align the half-angle vector to the lighting direction and multiplied by the microfacet shadowing and Fresnel factors. This yields the relevant 2D view slice on-the-fly at each pixel, still represented in the SG basis. We account for macro-scale shadowing using a new, nonlinear visibility representation based on spherical signed distance functions (SSDFs). SSDFs allow per-pixel interpolation of high-frequency visibility without ghosting and can be multiplied by the BRDF and lighting efficiently on the GPU.
mæve --- An Interactive Tabletop Installation for Exploring Background Information in Exhibitions
Authors: Till Nagel, Larissa Pschetz, Moritz Stefaner, Matina Halkia, Boris Müller
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

This paper introduces the installation mæve: a novel approach to present background information in exhibitions in a highly interactive, tangible and sociable manner. Visitors can collect paper cards representing the exhibits and put them on an interactive surface to display associated concepts and relations to other works. As a result, users can explore both the unifying themes of the exhibition as well as individual characteristics of exhibits. On basis of metadata schemata developed in the MACE (Metadata for Architectural Contents in Europe) project, the system has been put to use the Architecture Biennale to display the entries to the Everyville student competition.