ppxscal/embedding_network huggingface dataset:
A New Spatial Hue Angle Metric for Perceptual Image Difference
Authors: Marius Pedersen, Jon Yngve Hardeberg
Venue: Computational Color Imaging: Second International Workshop, CCIW 2009, Saint-Etienne, France, March 26-27, 2009. Revised Selected Papers (2009)

Color image difference metrics have been proposed to find differences between an original image and a modified version of it. One of these metrics is the hue angle algorithm proposed by Hong and Luo in 2002. This metric does not take into account the spatial properties of the human visual system, and could therefore miscalculate the difference between an original image and a modified version of it. Because of this we propose a new color image difference metrics based on the hue angle algorithm that takes into account the spatial properties of the human visual system. The proposed metric, which we have named SHAME (Spatial Hue Angle MEtric), have been subjected to extensive testing. The results show improvement in performance compared to the original metric proposed by Hong and Luo.
Design and characterization of a 0.35 micron CMOS voltage-to-current converter
Authors: Genival Mariano de Araujo, Heider Marconi G. Madureira, José Camargo da Costa
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

This work presents the design and characterization of a CMOS voltage-to-current (V-I) converter with a current range from -100 &mu;A to 100 &mu;A. The V-I converter has a power consumption of approximately 0.6 mW and its final area was 0.022 mm2 in 0.35 &mu;m CMOS technology.
A statistical framework for protein quantitation in bottom-up MS-based proteomics
Authors: Yuliya Karpievitch, Jeff Stanley, Thomas Taverner, Jianhua Huang, Joshua N. Adkins, Charles Ansong, Fred Heffron, Thomas O. Metz, Wei-Jun Qian, Hyunjin Yoon, Richard D. Smith, Alan R. Dabney
Venue: Bioinformatics (2009)

Motivation: Quantitative mass spectrometry-based proteomics requires protein-level estimates and associated confidence measures. Challenges include the presence of low quality or incorrectly identified peptides and informative missingness. Furthermore, models are required for rolling peptide-level information up to the protein level. Results: We present a statistical model that carefully accounts for informative missingness in peak intensities and allows unbiased, model-based, protein-level estimation and inference. The model is applicable to both label-based and label-free quantitation experiments. We also provide automated, model-based, algorithms for filtering of proteins and peptides as well as imputation of missing values. Two LC/MS datasets are used to illustrate the methods. In simulation studies, our methods are shown to achieve substantially more discoveries than standard alternatives. Availability: The software has been made available in the open-source proteomics platform DAnTE ( http://omics.pnl.gov/software/). Contact: adabney@stat.tamu.edu Supplementary information:Supplementary data are available at Bioinformatics online.
Retrieval of District Evapotranspiration Using Remotely Sensed Biomass Products
Authors: Tao Su, Peng-Xin Wang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

An approach of retrieving district evapotranspiration was studied by using remotely sensed biomass products in the Junchuan Farm of the Northeast of China. Based on the crop management practices of the Junchuan Farm, key soil and crop canopy parameters were applied to develop a biomass model for retrieving district evapotranspiration. Using the mass of dry matter on ground, apportionment coefficient and the corresponding experience expressions deduce the computing model of daily evapotranspiration. The surface energy balance algorithm for land (SEBAL) model is a near real time evapotranspiration monitoring approach. This article uses SEBAL as a referenced model to explain the possibility of using the model of biomass to monitor district evapotranspiration. The results show that the spatial distributions of the retrieved results for these two models are similar. These results indicate the model of biomass is a feasible approach for monitoring district evapotranspiration.
Hardcore Classification: Identifying Play Styles in Social Games Using Network Analysis
Authors: Ben Kirman, Shaun Lawson
Venue: Proceedings of the 8th International Conference on Entertainment Computing (2009)

In the social network of a web-based online game, all players are not equal. Through network analysis, we show that the community of players in a online social game is an example of a scale free small world network and that the growth of the player-base obeys a power law.The community is centred around a minority group of "hardcore" players who define the social environment for the game, and without whom the social network would collapse. Methods are discussed for identifying this critically important subset of players automatically through analysing social behaviours within the game.
Research and Application of XML Documents Query Based on Weight Cost
Authors: Wei Qiu
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

In order to meet the Web-based XML data similar to the information search, data mining, information classification and data exchange needs, analysis of the XML document similarity measure Ways - set metric methods, measurement methods and the cost of linear measure. Based on weights cost for machine learning of XML document similarity measure algorithm. The methods for query expansion to find the most represent the user's query intention to expand the weight of the query words. Experiments show that the algorithm extends the XML query document the scope of the document to improve full-search ratio and accurate search ratio.
Watermarking Scheme Based on DCT and DHT
Authors: Jianqin Zhou, Lingyun He, Cheng Shangguan
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

A new watermarking scheme based on DCT and DHT is presented. First,the host image is transformed as a whole by DCT. Second, the low and middle frequency region of the coefficient matrix is transformed by DHT. At last the watermarking image is embedded into the region of the DHT coefficient block. The experimental results show that the scheme is easy to be realized and the embedded watermark is effectively robust against various image processing operations such as JPEG lossy compression, noise, cropping, scaling, filtering etc.
Variability in Automation System Models
Authors: Gerd Dauenhauer, Thomas Aschauer, Wolfgang Pree
Venue: Proceedings of the 11th International Conference on Software Reuse: Formal Foundations of Reuse and Domain Engineering (2009)

Model driven engineering as well as software product line engineering are two approaches that increase the productivity of creating software. Despite the rather mature support of the individual approaches, tools and techniques for their combination, promising product specific customization of models, are still inadequate. We identify core problems of current approaches when applied to automation system models and propose a solution based on an explicit notion of variability embedded in the core of the modeling language itself.
Data Warehouse Based Approach to the Integration of Semi-structured Data
Authors: Houda Ahmad, Shokoh Kermanshahani, Ana Simonet, Michel Simonet
Venue: Advances in Web and Network Technologies, and Information Management: APWeb/WAIM 2009 International Workshops: WCMT 2009, RTBI 2009, DBIR-ENQOIR 2009, PAIS 2009, Suzhou, China, April 2-4, 2009, Revised Selected Papers (2009)

Semi-structured data play an increasing role in the development of the web through the use of XML. However, the management of semi-structured data poses specific problems because semi-structured data, contrary to classical database, do not rely on a predefined schema. The schema of a document is contained in the document itself and similar documents may be represented by different schemas. Consequently, the techniques and algorithms used for querying or integrating this data are more complex than those used for structured data. In this article we propose the architecture of a Data Warehouse designed for the integration of semi-structured data, so as to make possible searches in data repositories of various origins and structures. This architecture relies on the Osiris system, a DL-based model designed for the representation and management of databases and knowledge bases. In particular, we are interested in the Osiris data model, which gives several points of views on a family of objects. On the other hand, the indexing system of Osiris supports semantic query optimization. We show that the problem of query processing on a XML source is optimized by the objects indexing approach proposed by Osiris.
Location Privacy in RFID Applications
Authors: Ahmad-Reza Sadeghi, Ivan Visconti, Christian Wachsmann
Venue: Privacy in Location-Based Applications: Research Issues and Emerging Trends (2009)

RFID-enabled systems allow fully automatic wireless identification of objects and are rapidly becoming a pervasive technology with various applications. However, despite their benefits, RFID-based systems also pose challenging risks, in particular concerning user privacy. Indeed, improvident use of RFID can disclose sensitive information about users and their locations allowing detailed user profiles. Hence, it is crucial to identify and to enforce appropriate security and privacy requirements of RFID applications (that are also compliant to legislation). This chapter first discusses security and privacy requirements for RFID-enabled systems, focusing in particular on location privacy issues. Then it explores the advances in RFID applications, stressing the security and privacy shortcomings of existing proposals. Finally, it presents new promising directions for privacy-preserving RFID systems, where as a case study we focus electronic tickets (e-tickets) for public transportation.
Estimating and exploiting the entropy of sense distributions
Authors: Peng Jin, Diana McCarthy, Rob Koeling, John Carroll
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

Word sense distributions are usually skewed. Predicting the extent of the skew can help a word sense disambiguation (WSD) system determine whether to consider evidence from the local context or apply the simple yet effective heuristic of using the first (most frequent) sense. In this paper, we propose a method to estimate the entropy of a sense distribution to boost the precision of a first sense heuristic by restricting its application to words with lower entropy. We show on two standard datasets that automatic prediction of entropy can increase the performance of an automatic first sense heuristic.
The Multimode Estimation Modeling for Flight Delay of a Busy Hub-Airport in Flight Chain
Authors: Yujie Liu, Song Ma
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

Flight delay is the root of Delay Propagation, while delay propagated within a Flight Chain. Busy hubairport plays an important role in a Flight Chain, since the Initial Delay often happens there. To research more possible impacting factors in the Flight Chain, a busy hub-airport is chosen as the object in this research. After analyzing the complex and uncertain relationship between flight delays and all possible impacting factors, Bayesian network (BN) adapt to model and estimate about flight delay in a busy hub-airport. We proposed two learning methods with three different models. ModelⅠ is an estimation model for Arrival Delay based on parameter learning of BN with the Expectation-Maximization (EM) algorithm. Model II is estimation model for Arrival Delay based on structure learning of BN with K2 algorithm. The model learned by K2 is proved more suitable for modeling the estimation of flight delay, with a higher estimating correct rate than Model II. Then ModelⅢ is estimation model for Departure Delay with the same algorithm of Model II.
A Stereo-Based System with Inertial Navigation for Outdoor 3D Scanning
Authors: Tomasz Byczkowski, Jochen Lang
Venue: Proceedings of the 2009 Canadian Conference on Computer and Robot Vision (2009)

In this paper, we introduce a 3D scanning system consisting of a stereo camera combined with an inertial navigation system. We employ this system to explore the suitability of the standard 3D scanning pipeline when working with stereo range data of objects and architecture in an outdoor setting. Our range scanning system is very mobile without any mechanical actuators. We rely solely on the inertial navigation system for coarse registration with out any cumbersome manual procedure or scene dependent visual feature tracking. Our detail registration is a variant of the Iterative Closest Point algorithm. We introduce a set of heuristics that aims to produce reliable and repeatable convergence despite the diversity of the objects, and types of motions that may be executed by the operator during the scanning process. We also show that in an outdoor setting, range data based on classical binocular stereo can be effective for 3D modeling. Our system produces results of only slightly lower quality than an indoor triangulation scanner at a much lower system cost.
A Dynamic Task Representation Method for a Virtual Reality Application
Authors: Maria Chiara Leva, Alison Mragaret Kay, Fabio Mattei, Tom Kontogiannis, Massimiliano Ambroggi, Sam Cromie
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

The paper introduces an approach and a tool for representing tasks in the workplace as it emerged from a research finalized in reproducing safety critical tasks in Virtual Reality (VR) simulations. In the context of an EU research project called Virthualis. The tool, developed to address the needs of three different user groups, supports data collection and provides a structure for the interviews and for the simultaneous graphical representation of the task. It can be used as a common means of communication between the technical personnel involved in the interviews, the human factors expert and the VR expert. This aids the common understanding of a task, its main objective, challenges and criticalities whilst performing the actual analysis.
Severity Evaluation Support for Burns Unit Patients Based on Temporal Episodic Knowledge Retrieval
Authors: Jose M. Juarez, Manuel Campos, Jose Palma, F. Palacios, Roque Marin
Venue: Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine (2009)

Severity scores are a sort of medical algorithm commonly used in medicine. In practise, physicians only use a few of them, usually internationally accepted ones involving very simple calculations. However, their daily use in critical care services gives rise to two potential problems. First, they do not always cover the particularities of the local population or a specific pathology may not be considered in the score. Second, these services (e.g. intensive care units or Burns Units) are strongly dependent on the evolution of the patients and, so the temporal component plays an essential role that should always be in mind. On the other hand, the knowledge required is at least partially present in the physician team of the medical unit due to the experience gained in treating individual patients, that is, in the form of episodic knowledge. Therefore, the use of techniques based on analogy reasoning, such as Case-Based Reasoning, would seem a suitable approach for dealing with part of this problem.In this work, we present an episodic knowledge retrieval system to support the physician in evaluating the severity patients from the temporal evolution point of view. To this end, we present different techniques for temporal retrieval based on previous works on temporal similarity. We also demonstrate the suitability of this system by applying it to a specific medical problem arising in a Burns Unit.
Study of a New Cotton Assorting Algorithm
Authors: Fan Xiu-juan, Li Cheng-guo
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

This paper analyzes the cotton assorting by computer, and studies the theory of strategies such as group sorting, elitist preservation, local optimal and self-adaptive mutation which are based upon the basic inheritance algorithm, and designs the hybrid genetic algorithm based computer automatic cotton assorting mathematical model. The computer automatic cotton-blending issue is experimented respectively using the basic genetic algorithms and the improved hybrid genetic algorithm, the results show that the cotton assorting scheme obtained by the improved hybrid genetic algorithm is more reasonable and the accuracy of mixed cotton quality is high. Effectiveness of this model has been verified through example analysis.
Modeling reciprocal behavior in human bilateral negotiation
Authors: Ya'akov Gal, Avi Pfeffer
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

Reciprocity is a key determinant of human behavior and has been well documented in the psychological and behavioral economics literature. This paper shows that reciprocity has significant implications for computer agents that interact with people over time. It proposes a model for predicting people's actions in multiple bilateral rounds of interactions. The model represents reciprocity as a tradeoff between two social factors: the extent to which players reward and retaliate others' past actions (retrospective reasoning), and their estimate about the future ramifications of their actions (prospective reasoning). The model is trained and evaluated over a series of negotiation rounds that vary players' possible strategies as well as their benefit from potential strategies at each round. Results show that reasoning about reciprocal behavior significantly improves the predictive power of the model, enabling it to outperform alternative models that do not reason about reciprocity, or that play various game theoretic equilibria. These results indicate that computers that interact with people need to represent and to learn the social factors that affect people's play when they interact over time.
A Proposal for "Work-Effective Guidelines" for the Growth of HCD
Authors: Haruhiko Urokohara, Tsunehisa Yamaguchi, Hiroaki Nobuta, Shuichi Kanda
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

These are practical guidelines for promoting HCD in the field of design development. We review the role of guidelines that are more effective than previous methods, and which are based on the principles of HCD.
Towards Location-Based Real-Time Monitoring Systems in u-LBS
Authors: Moonbae Song, Hyunseung Choo
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part II (2009)

Recently, ubiquitous location-based services (u-LBS) has been utilized in a variety of practical and mission-critical applications such as security services, personalization services, location-based entertainment, and location-based commerce. The essence of u-LBS is actually the concept of location-awareness where location-aware devices perform more intelligent services for users by utilizing their locations. In order to realize/achieve this concept, a mobile device should continuously monitor the real-time contextual changes of a user; this is what we call location-based monitoring. In this paper, we discuss the research and technical issues on designing location-based real-time monitoring systems in u-LBS along with three major subjects: (1) high-performance spatial index, (2) monitoring query processing engine, and (3) distributed monitoring system with dynamic load balancing capability and energy-efficient management.
A Novel Approach for Creating Activity-Aware Applications in a Hospital Environment
Authors: Jakob E. Bardram
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

Context-aware and activity-aware computing has been proposed as a way to adapt the computer to the user's ongoing activity. However, deductively moving from physical context - like location - to establishing human activity has proved difficult. This paper proposes a novel approach to activity-aware computing. Instead of inferring activities, this approach enables the user to explicitly model their activity, and then use sensor-based events to create, manage, and use these computational activities adjusted to a specific context. This approach was crafted through a user-centered design process in collaboration with a hospital department. We propose three strategies for activity-awareness: context-based activity matching, context-based activity creation, and context-based activity adaptation. We present the implementation of these strategies and present an experimental evaluation of them. The experiments demonstrate that rather than considering context as information, context can be a relational property that links 'real-world activities' with their 'computational activities'.
Abstractions in Process Mining: A Taxonomy of Patterns
Authors: R. P. Jagadeesh Chandra Bose, Wil M. Aalst
Venue: Proceedings of the 7th International Conference on Business Process Management (2009)

Process mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms have problems dealing with such unstructured processes and generate spaghetti-like process models that are hard to comprehend. One reason for such a result can be attributed to constructing process models from raw traces without due pre-processing. In an event log, there can be instances where the system is subjected to similar execution patterns/behavior. Discovery of common patterns of invocation of activities in traces (beyond the immediate succession relation) can help in improving the discovery of process models and can assist in defining the conceptual relationship between the tasks/activities.In this paper, we characterize and explore the manifestation of commonly used process model constructs in the event log and adopt pattern definitions that capture these manifestations, and propose a means to form abstractions over these patterns. We also propose an iterative method of transformation of traces which can be applied as a pre-processing step for most of today's process mining techniques. The proposed approaches are shown to identify promising patterns and conceptually-valid abstractions on a real-life log. The patterns discussed in this paper have multiple applications such as trace clustering, fault diagnosis/anomaly detection besides being an enabler for hierarchical process discovery.
Quantifying the Uncertainty in Measurements for MBAC
Authors: Anne Nevin, Peder J. Emstad, Yuming Jiang, Guoqiang Hu
Venue: Proceedings of the 15th Open European Summer School and IFIP TC6.6 Workshop on The Internet of the Future (2009)

In Measurement Based Admission Control (MBAC), the decision of accepting or rejecting a new flow is based on measurements of the current traffic situation. An in-depth understanding of the measurement error and its uncertainty is vital for the design of a robust MBAC. In this work, we study the measured parameters used by the MBAC and characterize their error. Our work differs significantly from previous work in that we find how the uncertainty in the measurements varies with the length of the observation window.