ppxscal/embedding_network huggingface dataset:
Smart infrastructure matches supply and demand
Authors: Aaron Weiss
Venue: netWorker (2009)

How networks decentralize the power of human intelligence.
Learning to improve earth observation flight planning
Authors: Robert A. Morris, Nikunj Oza, Leslie Keely, Elif Kürklü, Anthony Strawa
Venue: Proceedings of the 20th national conference on Innovative applications of artificial intelligence - Volume 3 (2008)

This paper describes a method and system for integrating machine learning with planning and data visualization for the management of mobile sensors for Earth science investigations. Data mining identifies discrepancies between previous observations and predictions made by Earth science models. Locations of these discrepancies become interesting targets for future observations. Such targets become goals used by a flight planner to generate the observation activities. The cycle of observation, data analysis and planning is repeated continuously throughout a multi-week Earth science investigation.
A Robust Watermarking for MPEG-2
Authors: Huang Li, Jian Li, Hongmei Liu
Venue: Proceedings of the 8th International Workshop on Digital Watermarking (2009)

Motion information is special to video. It provides enough space for watermark embedding. However, the watermark embedded in motion information is usually not robust. In this paper, a robust watermarking algorithm which embeds watermark in motion vectors of P frames is proposed. The reason why the watermark embedded in motion vector is not robust to recompression is that the watermarked motion vector will be changed when the video is recompressed. In order to improve the watermark robustness to recompression, we present to modify the pixel of the current block while embedding watermark bit in its motion vector. In order to minimize the perceptual degradation of video quality, we adopt our previously proposed geometrical method. The experimental results demonstrate the strong robustness of the scheme against common signal processing operations.
The Hardware Interface Design In SoC with Verilog Language
Authors: Zhang Zhen, Zhang Hui
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

With the geometry of the IC(Integrated Circuits) becoming smaller and smaller, more and more high-density integration, function integrated getting stronger and stronger and development cycle becoming shorter and shorter, the SoC (System-on-a-Chip) design methodology based on IP-Reuse has become the main method to design IC. In order to automate IP-Reuse, tools must be created to combine parts of different communication protocol system in this design method, that is, to the interface synthesis. This paper gives us a kind of hardware interface synthesis method based on automatic FSM (Finite State Machine) generation, gives out such interface design based on Verilog language, and carries out simulation.
A Case-Based Perspective on Social Web Search
Authors: Barry Smyth, Peter Briggs, Maurice Coyle, Michael P. O'Mahony
Venue: Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2009)

Web search is the main way for millions of users to access information every day, but we continue to struggle when it comes to finding the right information at the right time. In this paper we build on recent work to describe and evaluate a new application of case-based Web search, one that focuses on how experience reuse can support collaboration among searchers. Special emphasis is placed on the development of a case-based system that is compatible with existing search engines. We also describe the results of a live-user deployment.
Hierarchical Regression for Data Acquisition in Wireless Sensor Networks
Authors: Qiuyue Wang, Chaojun Hou, Xuemei Guo, Guoli Wang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

In this paper, the regression framework is proposed to hierarchically organize the three regression procedures, that is, local data modelling, cluster data modelling and global data modelling, for the energy-efficient data acquisition in wireless sensor networks (WSNs). There are two advantages arising from our method. First, there is no need for any transmissions of the measured data in the modelling procedures, which leads to significant energy savings, even for inhomogeneous networks. Second, there is no error peaking phenomenon occurred at cluster boundaries, which contributes to considerable performance improvement.
Construction of Safe Patent Trading Platform Based on Zero-Knowledge Proof
Authors: Ming Qi, Bing Chen
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

As its own security risks of existing patent trading platform, on-line patent transaction can not be realized. The security problems are mainly embodied in the confidentiality of transaction information, and security of patent delivery areas. One of the important characteristics of Zero-knowledge proof is zero-knowledge, which can enable the verifier to believe that the conclusion is correct without knowing the contents of it. This characteristic can solve the problems of current patent transaction security mentioned above. Based on zero-knowledge proof, through the framework and flow design, this paper builds a secure patent trading platform, which shows a new way of patent trading. What is more, the security and convenience of this trading platform are better than ever before.
Single-Path Restarting Tree Automata
Authors: Friedrich Otto, Heiko Stamer
Venue: Proceedings of the 3rd International Conference on Algebraic Informatics (2009)

Restarting tree automata are an extension of top-down tree automata that incorporate transformations of trees through the execution of certain size-reducing rewrite operations. An input tree is repeatedly rewritten until a simple tree is obtained that is then accepted without further rewrites. Accordingly, these automata can be seen as term-rewriting systems with an incorporated regular control realizing parallel rewrites on independent branches. Here we introduce and study two restricted types of restarting tree automata by restricting the options for the regular control. The first variant we consider is the single-path restarting tree automaton, which is obtained from the general model by restricting it to the ability to pass down information along a single path only. In this way it is enforced that rewrites are executed in a strictly sequential way. Interestingly, single-path restarting tree automata reduce the tree languages they recognize to a proper subclass of the class of regular tree languages. Nevertheless, many of the results on the general model of restarting automata carry over to this variant. The second variant we study is the ground-rewrite restarting tree automaton. It is required to perform its size-reducing rewrite steps only on ground terms of bounded height. Accordingly, these automata can be interpreted as ground term-rewriting systems with additional regular control. Although they are much less expressive than the general model, it turns out that due to an inherent synchronization mechanism they can still accept certain non-regular tree languages. Finally, we consider the combination of both restrictions.
A Simulation Environment for Subject-Specific Radio Channel Modeling in Wireless Body Sensor Networks
Authors: Yan Zhao, Andrea Sani, Yang Hao, Su-Lin Lee, Guang-Zhong Yang
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

This paper presents a simulation environment, based on the parallel finite-difference time-domain (FDTD) method, for subject-specific radio channel modeling in wireless body sensor networks (WBSNs). The simulation environment takes into account realistic antenna radiation patterns in channel modeling to analyze their effects on WBSNs. The proposed simulation tool is applied to a study of body communication channels in a hospital environment and the results are validated by site measurement. It is found from our study that radio channel characteristics in WBSNs are subject specific and associated with human genders and body mass indices (BMIs).
Automatic Plaque Boundary Extraction in Intravascular Ultrasound Image by Fuzzy Inference with Adaptively Allocated Membership Functions
Authors: Eiji Uchino, Noriaki Suetake, Takanori Koga, Shohei Ichiyama, Genta Hashimoto, Takafumi Hiro, Masunori Matsuzaki
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 describes an automatic plaque boundary extraction in the intravascular ultrasound image by a fuzzy inference. In the proposed method, the membership functions in the antecedent parts of the fuzzy rules are adaptively allocated by using the information of the seed points given by a medical doctor. The present method not only improved the accuracy of plaque boundary extraction but also reduced the workload of medical doctors.
UCD-PN: classification of semantic relations between nominals using WordNet and web counts
Authors: Paul Nulty
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

For our system we use the SMO implementation of a support vector machine provided with the WEKA machine learning toolkit. As with all machine learning approaches, the most important step is to choose a set of features which reliably help to predict the label of the example. We used 76 features drawn from two very different knowledge sources. The first 48 features are boolean values indicating whether or not each of the nominals in the sentence are linked to certain other words in the WordNet hypernym and meronym networks. The remaining 28 features are web frequency counts for the two nominals joined by certain common prepositions and verbs. Our system performed well on all but two of the relations; theme-tool and origin entity.
An Outlier Detection Algorithm Based on Arbitrary Shape Clustering
Authors: Xiaoke Su, Yang Lan, Renxia Wan, Yuming Qin
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

Outlier detection is an important branch in data mining field. It provides new methods for analyzing all kinds of massive, complex data with noise. In this paper, an outlier detection algorithm is presented by introducing the arbitrary shape clustering approach and discussing the concept of abnormal cluster. The algorithm firstly partitions the dataset into several clusters by proposed clustering approach. Outliers are then detected from the cluster set according to the abnormal cluster concept. Moreover, by introducing inter-cluster dissimilarity measure, the proposed algorithm gains a good performance on the mixed data. The experimental results on the real-life datasets show our approach outperform the existing methods on identifying meaningful and interesting outliers.
Using Wearable Sensors to Monitor Physical Activities of Patients with COPD: A Comparison of Classifier Performance
Authors: Shyamal Patel, Chiara Mancinelli, Jennifer Healey, Marilyn Moy, Paolo Bonato
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

Chronic obstructive pulmonary disease (COPD) is a major public health problem. Early detection and treatment of an exacerbation in the outpatient setting are important to prevent worsening of clinical status and need for emergency room care or hospital admission. In this study we use accelerometers to capture motion data; and heart rate and respiration rate to capture physiological responses from patients with COPD as they perform a range of Activities of Daily Living (ADL) and physical exercises. We present a comparative analysis of classification performance of a set of different classification techniques and factors that affect classification performance for activity recognition based on accelerometer data. This is the first step towards building a wearable sensor monitoring system for tracking changes in physiological responses of patients with COPD with respect to their physical activity level.
Positive solutions of sublinear Sturm-Liouville problems with changing sign nonlinearity
Authors: Hongyu Li, Jingxian Sun
Venue: Computers Mathematics with Applications (2009)

In this paper, the following nonlinear Sturm-Liouville problem {-(p(x)u^'(x))^'+q(x)u(x)=@lf(x,u(x)),0@?x@?1,@a"0u(0)+@b"0u^'(0)=0,@a"1u(1)+@b"1u^'(1)=0 is discussed by topological methods. In the case that the nonlinear term is non-singular or singular, a global structure of the positive solution set of the above problem is obtained, and the existence of positive solutions is proved under the condition that the nonlinear term is allowed to change sign.
What Is an Activity? Appropriating an Activity-Centric System
Authors: Svetlana Yarosh, Tara Matthews, Thomas P. Moran, Barton Smith
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

Activity-Centric Computing (ACC) systems seek to address the fragmentation of office work across tools and documents by allowing users to organize work around the computational construct of an Activity. Defining and structuring appropriate Activities within a system poses a challenge for users that must be overcome in order to benefit from ACC support. We know little about how knowledge workers appropriate the Activity construct. To address this, we studied users' appropriation of a production-quality ACC system, Lotus Activities, for everyday work by employees in a large corporation. We contribute to a better understanding of how users articulate their individual and collaborative work in the system by providing empirical evidence of their patterns of appropriation. We conclude by discussing how our findings can inform the design of other ACC systems for the workplace.
Soil-Web: An online soil survey for California, Arizona, and Nevada
Authors: D. E. Beaudette, A. T. O'Geen
Venue: Computers Geosciences (2009)

Digital soil survey products represent one of the largest and most comprehensive inventories of soils information currently available. The complex structure of these databases, intensive use of codes and scientific jargon make it difficult for non-specialists to utilize digital soil survey resources. A project was initiated to construct a web-based interface to digital soil survey products (STATSGO and SSURGO) for California, Arizona, and Nevada that would be accessible to the general public. A collection of mature, open source applications (including Mapserver, PostGIS and Apache Web Server) were used as a framework to support data storage, querying, map composition, data presentation, and contextual links to related materials. Application logic was written in the PHP language to ''glue'' together the many components of an online soil survey. A comprehensive website (http://casoilresource.lawr.ucdavis.edu/map) was created to facilitate access to digital soil survey databases through several interfaces including: interactive map, Google Earth and HTTP-based application programming interface (API). Each soil polygon is linked to a map unit summary page, which includes links to soil component summary pages. The most commonly used soil properties, land interpretations and ratings are presented. Graphical and tabular summaries of soil profile information are dynamically created, and aid with rapid assessment of key soil properties. Quick links to official series descriptions (OSD) and other such information are presented. All terminology is linked back to the USDA-NRCS Soil Survey Handbook which contains extended definitions. The Google Earth interface to Soil-Web can be used to explore soils information in three dimensions. A flexible web API was implemented to allow advanced users of soils information to access our website via simple web page requests. Soil-Web has been successfully used in soil science curriculum, outreach activities, and current research projects. Although not the only online soil survey application, Soil-Web remains the simplest and most rapid means of accessing soils information for California, Arizona, and Nevada.
Partial revelation automated mechanism design
Authors: Nathanaël Hyafil, Craig Boutilier
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

In most mechanism design settings, optimal general-purpose mechanisms are not known. Thus the automated design of mechanisms tailored to specific instances of a decision scenario is an important problem. Existing techniques for automated mechanism design (AMD) require the revelation of full utility information from agents, which can be very difficult in practice. In this work, we study the automated design of mechanisms that only require partial revelation of utilities. Each agent's type space is partitioned into a finite set of partial types, and agents (should) report the partial type within which their full type lies. We provide a set of optimization routines that can be combined to address the trade-offs between the amount of communication, approximation of incentive properties, and objective value achieved by a mechanism. This allows for the automated design of partial revelation mechanisms with worst-case guarantees on incentive properties for any objective function (revenue, social welfare, etc.).
AESNB: Active Example Selection with Naïve Bayes Classifier for Learning from Imbalanced Biomedical Data
Authors: Min Su Lee, Je-Keun Rhee, Byoung-Hee Kim, Byoung-Tak Zhang
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

Various real-world biomedical classification tasks suffer from the imbalanced data problem which tends to make the prediction performance of some classes significantly decrease. In this paper, we present an active example selection method with naïve Bayes classifier (AESNB) as a solution for the imbalanced data problem. The proposed method starts with a small balanced subset of training examples. A naïve Bayes classifier is trained incrementally by actively selecting and adding informative examples regardless of the original class distribution. Informative examples are defined as examples that produce high error scores by the current classifier. We examined the performance of AESNB algorithm by using five imbalanced biomedical datasets. Our experimental results show that the naïve Bayes classifier with our active example selection method achieves a competitive classification performance compared to the classifier with sampling or cost-sensitive methods.
The Network Access Control Research Based on Distributed Router
Authors: Juan Yuan, Zongshui Xiao, Qiang Guo, Jibin Su
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

This paper based on a distributed router studies Access Control and Traffic Statistics, and gives the specific implementation method. Based on primary platform expand an Access Control Module (ACM), and implement access control and flow statistics, using rule-based matching filtering table and “Data Cube” store and optimize rules. Using its network number, host number and time-range determine whether the data packets can be transmitted through the route forwarding. It takes NetFlow technology for traffic statistics and collects the data packet of same network number to the data stream. Each data stream can be individually tracked and accurately measured, recorded the transmission attributes such as direction, destination and so on.
Demo abstract: IEEE 802.15.4a-based anchor-free mobile node localization system
Authors: Chanmin Yoon, Haksoo Choi, Seungwoo Lee, Hojung Cha, Byunghun Song, Hyungsu Lee
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

We demonstrate an anchor-free mobile node localization system using Ymote, which is equipped with the IEEE 802.15.4a RF module based on Chirp Spread Spectrum (CSS) technology. In contrast to conventional centralized systems, our system is fully distributed, hence scalable, and enables self-positioning in anchor-free environment. The localization system is implemented on the RETOS operating system.
GraspZoom: zooming and scrolling control model for single-handed mobile interaction
Authors: Takashi Miyaki, Jun Rekimoto
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

A pressure sensing based single-handed interaction model is presented in this paper. Unlike traditional desktop GUI model, mobile UI model has not been established yet. For example, Apple iPhone proposed "Pinch" operation, which use two fingers to zoom-in and zoom-out objects. However, in a today's hand-held situation, manipulation methods using two fingers are not always good solution because they require two hands in order to hold the device itself in most cases. We propose a single-handed UI scheme "GraspZoom": multi-state input model using pressure sensing. Force Sensitive Resistor (FSR) attached on backside of a mobile phone was employed in order to evaluate effectiveness of pressure based control model. We also describe example applications which enable intuitive and continuous zooming and scrolling. By using tiny thumb gesture input along with this pressure sensing method, bi-directional operations (e.g., zoom-in and -out) are also achieved.
Enhancements to Online Help: Adaptivity and Embodied Conversational Agents
Authors: Jérôme Simonin, Noëlle Carbonell
Venue: Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments (2009)

We present and discuss the results of two empirical studies that aim at assessing the contributions, to the effectiveness and efficiency of online help of: adaptive-proactive user support (APH), multimodal (speech and graphics) messages (MH), and embodied conversational agents (ECAs). These three enhancements to online help were implemented using the Wizard of Oz technique. The first study (E1) compares MH with APH, while the second study (E2) compares MH with embodied help (EH). Half of the participants in E1 (8) used MH, and the other half used APH. Most participants who used MH, resp. APH, preferred MH, resp. APH, to standard help systems which implement text and graphics messages (like APH). In particular, proactive assistance was much appreciated. However, higher performances were achieved with MH. A majority of the 22 participants in E2 preferred EH to MH, and were of the opinion that the presence of an ECA, a talking head in this particular case, has the potential to improve help effectiveness and efficiency by increasing novice users' self confidence. However, performances with the two systems were similar, save for help consultation rate which was higher with EH. Longitudinal (usage) studies are needed to confirm the effects of these three enhancements on novice users' judgments and performances.
Automatic Estimation of the Inlier Threshold in Robust Multiple Structures Fitting
Authors: Roberto Toldo, Andrea Fusiello
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

This paper tackles the problem of estimating the inlier threshold in RANSAC-like approaches to multiple models fitting. An iterative approach finds the maximum of a score function which resembles the Silhouette index used in clustering validation. Although several methods have been proposed to solve this problem for the single model case, this is the first attempt to address multiple models. Experimental results demonstrate the performances of the algorithm.