ppxscal/embedding_network huggingface dataset:
Human Interface and the Management of Information. Information and Interaction: Symposium on Human Interface 2009, Held as Part of HCI International 2009, ... Applications, incl. Internet/Web, and HCI), 1st edition
Authors: Gavriel Salvendy, Michael J. Smith
Venue:  (2009)

This two-volume set LNCS 5617 and 5618 constitutes the refereed proceedings of the Symposium on Human Interface 2009, held in San Diego, CA, USA in July 2009 in the framework of the 13th International Conference on Human-Computer Interaction, HCII 2009 with 16 other thematically similar conferences. The 175 revised papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers accepted for presentation thoroughly cover the thematic area of human interface and the management of information. The 93 papers of this second volume address the following major topics: interacting with the world wide web; intelligent techniques for access to information and personalization; visual interfaces, visualization and images; mobile devices and services; ehealth applications and services; education, learning and entertainment; information systems in safety-critical domains.
Spatio-temporal Variability of Soil Nitrogen in North China Plain Using Geostatistical Analysis
Authors: Dong Yuhong, Ouyang Zhu, Liu Shiliang
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

Large changes in land use and land management, which have had a tremendous impact on soil nutrients, have occurred in north China in recent years. Soil nitrogen is more influenced by human activities as the fertilizer application. We compared soil nitrogen in Yucheng County of Shandong province in 2003 to 1980 results from the Second National Soil Survey. The average contents of total nitrogen in 2003 were significantly higher than in 1980. Soil nitrogen increased from 0.68 to 0.84 mg/kg. Spatial variability of soil nitrogen was medium and characterized by coefficients of variation (CV) 22% and 28% in 1980 and 2003, respectively. Then geostatistical analysis was used to find the spatio-temporal variability of soil nitrogen. The results showed that the spatial distribution of soil nitrogen changed greatly between 1980 and 2003. Soil nitrogen showed increasing trends in Yucheng. And Zhangzhuang, Fangsi and Shiliwang towns showed the highest increase in soil nitrogen. The increase in soil nitrogen was contributed to increased application of chemical fertilizer. Among these towns in Yucheng, these with most obviously increase of soil nitrogen had the higher application of chemical fertilizers.
Design and Implementation of Distributed Memory Management System Based on Local Area Network
Authors: Yujian Wang, Lili Fan, Chen Liu, Xing Tian
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

According to the characteristics of data processing in the middle-small enterprises, a distributed memory management system (DMMS) based on LAN is proposed. The manner of data organizing, the design principle and the concrete implementation of every function entity in the system are introduced in detail. The system uses the memory resource of the computers in the LAN to store user application data, solves the problem about I/O capability bottleneck. The data is divided into the packages, and the package management entity (PME) is used for the management of network memory resources. Main package is kept synchronized with backup package by synchronization protocol mechanism to realize the protection of package data. The whole system design adopts flexible framework, each function entity is relatively independent of each other and the protocols and algorithms used in the system are encapsulated to realize agility and expansibility. The results of test show that the efficiency of processing application data by using the system is 5 to 7 times as high as that by using the local fixed disk for user, it is really feasible and effective to apply the distributed technology in the memory management of LAN.
The Pluses and Minuses of Obtaining Measurements from Digital Scans
Authors: Ravindra S. Goonetilleke, Channa P. Witana, Jianhui Zhao, Shuping Xiong
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

Digital scanners are commonplace and are used in many different applications to obtain three-dimensional shapes and linear and circumferential measurements. Even though scanners can be highly accurate, measurements obtained from scanners can vary depending on how an object is scanned, aligned and processed. In this study, we examined the effect of three different alignment methods of foot scans and their effects on ten different measurements. Variations among methods in capturing foot length are relatively small relative to arch length. The foot girths can be quite sensitive to the registration process depending on the complexity of the algorithms used. As expected, linear and girth measurements based on anatomical landmarks will always be independent of any registration process and are thus good ways to obtain repeatable measurements.
Enterprise Supply Chain Management Based on Integration Cooperative Internet Information
Authors: Zhang Yanhong
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

In this paper, supply chain solutions was told for the sharing of information and set up a "information-sharing systems" model. In order to establish such a system, supply chain enterprises have to integrate network nodes, such as a unified coding. In addition, an important task is to transform the traditional "linear" supply chain model, the establishment of a new Internet-based e-supply chain functions. In this supply chain, a core business at the center of the supply chain, information-sharing platform take on the task, each node can be the core business enterprises to exchange information, to shorten the lead time and improve efficiency. In addition, the article also on the traditional supply chain management and new information-sharing model compared to that information-sharing in the supply chain management.
Homogeneity tests for several Poisson populations
Authors: Sung Nok Chiu, Ling Wang
Venue: Computational Statistics Data Analysis (2009)

In this paper we compare the size distortions and powers for Pearson's @g^2-statistic, likelihood ratio statistic LR, score statistic SC and two statistics, which we call UT and VT here, proposed by [Potthoff, R.F., Whittinghill, M., 1966. Testing for homogeneity: II. The Poisson distribution. Biometrika 53, 183-190] for testing the equality of the rates of K Poisson processes. Asymptotic tests and parametric bootstrap tests are considered. It is found that the asymptotic UT test is too conservative to be recommended, while the other four asymptotic tests perform similarly and their powers are close to those of their parametric bootstrap counterparts when the observed counts are large enough. When the observed counts are not large, Monte Carlo simulation suggested that the asymptotic test using SC, LR and UT statistics are discouraged; none of the parametric bootstrap tests with the five statistics considered here is uniformly best or worst, and the asymptotic tests using Pearson's @g^2 and VT always have similar powers to their bootstrap counterparts. Thus, the asymptotic Pearson's @g^2 and VT tests have an advantage over all five parametric bootstrap tests in terms of their computational simplicity and convenience, and over the other four asymptotic tests in terms of their powers and size distortions.
Integrated introspective case-based reasoning for intelligent tutoring systems
Authors: Leen-Kiat Soh
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

Many intelligent tutoring systems (ITSs) have been developed, deployed, assessed, and proven to facilitate learning. However, most of these systems do not generally adapt to new circumstances, do not self-evaluate and self-configure their own strategies, and do not monitor the usage history of the learning content being delivered or presented to the students. These shortcomings force ITS developers to often spend much development time in manual revision and fine-tuning of the learning and instructional contents of an ITS. In this paper, we describe an intelligent agent that delivers learning material adaptively to different students, factoring in the usage history of the learning materials and student profiles as observed by the agent. Student-tutor interaction includes the activities of going through learning material, such as a topical tutorial, a set of examples, and a set of problems. Our assumption is that our agent will be able to capture and utilize these student activities as the primer to select the appropriate examples or problems to administer to the student. Using an integrated introspective case-based reasoning approach, our agent further learns from its experience and refines its reasoning process-including the instructional strategies-to adapt to student needs. Moreover, our agent monitors the usage history of the learning materials to improve its performance. We have built an end-to-end ITS using an agent powered by this integrated introspective case-based reasoning engine. We have deployed the ITS in a CS course. Results indicate that the ITS was able to learn to deliver more appropriate examples and problems to the students.
A new yardstick and tool for personalized vocabulary building
Authors: Thomas K Landauer, Kirill Kireyev, Charles Panaccione
Venue: Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications (2009)

The goal of this research is to increase the value of each individual student's vocabulary by finding words that the student doesn't know, needs to, and is ready to learn. To help identify such words, a better model of how well any given word is expected to be known was created. This is accomplished by using a semantic language model, LSA, to track how every word changes with the addition of more and more text from an appropriate corpus. We define the "maturity" of a word as the degree to which it has become similar to that after training on the entire corpus. An individual student's average vocabulary level can then be placed on the word-maturity scale by an adaptive test. Finally, the words that the student did or did not know on the test can be used to predict what other words the same student knows by using multiple maturity models trained on random samples of typical educational readings. This detailed information can be used to generate highly customized vocabulary teaching and testing exercises, such as Cloze tests.
Color Constancy Algorithm Selection Using CART
Authors: Simone Bianco, Gianluigi Ciocca, Claudio Cusano
Venue: Computational Color Imaging: Second International Workshop, CCIW 2009, Saint-Etienne, France, March 26-27, 2009. Revised Selected Papers (2009)

In this work, we investigate how illuminant estimation techniques can be improved taking into account intrinsic, low level properties of the images. We show how these properties can be used to drive, given a set of illuminant estimation algorithms, the selection of the best algorithm for a given image. The selection is made by a decision forest composed by several trees that vote for one of the illuminant estimation algorithm. The most voted algorithm is then applied to the input image. Experimental results on the widely used Ciurea and Funt dataset demonstrate the accuracy of our approach in comparison to other algorithms in the state of the art.
Ada for the control of degradation of service
Authors: Gertrude Levine
Venue: ACM SIGAda Ada Letters (2009)

This paper examines degradations of service in terms of constructs of the Ada programming language that are effective for their control and deployment. Several studies of the software lifecycle have focused on taxonomies of defects or errors. Categories of service degradations, however, have only recently been identified. A classification scheme for service degradations clarifies their relationship to defects and errors and their role in the prevention of failure. With the growth of hard real-time systems, wireless networks, and multimedia applications, a comprehensive understanding of service degradations and their usage has become ever more important.
Orthogonal Centroid Locally Linear Embedding for Classification
Authors: Yong Wang, Yonggang Hu, Yi Wu
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

The locally linear embedding (LLE) algorithm is an unsupervised technique for nonlinear dimensionality reduction which can represent the underlying manifold as well as possible. While in classification, data label information is available and our main purpose changes to represent class separability as well as possible. To the end of classification, we propose a new supervised variant of LLE, called orthogonal centroid locally linear embedding (OCLLE) algorithm in this paper. It uses class membership information to map overlapping high-dimensional data into disjoint clusters in the embedded space. Experiments show that very promising results are yielded by this variant.
Classification by discriminative regularization
Authors: Bin Zhang, Fei Wang, Ta-Hsin Li, Wen Jun Yin, Jin Dong
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a good classification function is to minimize its empirical prediction loss or structural loss. In this paper, we point out that we can also enhance the discriminality of those classifiers by further incorporating the discriminative information contained in the data set as a prior into the classifier construction process. In such a way, we will show that the constructed classifiers will be more powerful, and this will also be validated by the final empirical study on several benchmark data sets.
Transformation of Online Representation through Time
Authors: Roya Feizy, Ian Wakeman, Dan Chalmers
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

In order to understand the evolution of online identities, we measured the correlation between past and the current representations of self on MySpace social network. We applied several techniques and proposed a personality classifier to calculate the level of honesty and accountability for over 2 million users. We formulized a transformation algorithm to measure both static and dynamic features of identity traits over time. This experiment provides evidence of the dynamic nature of profiles’ information, the social network structure and the group similarities. In this paper, we will discuss how online identities progress during one year time frame and what impact it may have to determine user's characteristics. This analysis can be used to develop a technology to predict the taxonomy of identities and the direction of online social representation.
Agent-organized networks for multi-agent production and exchange
Authors: Matthew E. Gaston, Marie DesJardins
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

As multi-agent systems grow in size and complexity, social networks that govern the interactions among the agents will directly impact system behavior at the individual and collective levels. Examples of such large-scale, networked multi-agent systems include peer-to-peer networks, distributed information retrieval, and agent-based supply chains. One way of dealing with the uncertain and dynamic nature of such environments is to endow agents with the ability to modify the agent social network by autonomously adapting their local connectivity structure. In this paper, we present a framework for agent-organized networks (AONs) in the context of multi-agent production and exchange, and experimentally evaluate the feasibility and efficiency of specific AON strategies. We find that decentralized network adaptation can significantly improve organizational performance. Additionally, we analyze several properties of the resulting network structures and consider their relationship to the observed increase in organizational performance.
A Path Planning System based on 3D Occlusion Detection for Lunar Exploration Rovers
Authors: Andres Mora, Keiji Nagatani, Kazuya Yoshida, Marco Chacin
Venue: Proceedings of the Third IEEE International Conference on Space Mission Challenges for Information Technology (2009)

In this paper, the authors present a path planing system for autonomous navigation of lunar/planetary rover. In the path planner, candidate paths are generated and evaluated by multiple criteria including occlusion index, terrain roughness/inclination indices. The proposed system considers the occlusion effect produced by obstacles present in the inspected environment and the features of the environment itself. An algorithm that computes the next sensing position within the map is introduced as part of the system presented. The different components of the system and their interactions are explained thoroughly. Simulation and experimental results where the proposed system is implemented are presented.
The Effects of Quest Types and Gaming Motivations on Players' Knowledge Acquisitions in an Online Role-Playing Game Environment
Authors: Jiunde Lee, Chih-Yi Chao
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part IV: Interacting in Various Application Domains (2009)

The study explores how the design of quest types and different players' gaming motivations might affect knowledge acquisitions in an online role-playing game environment. An experiment was conducted to collect data. The results showed that "immersion motivation" had the most significant influence on knowledge acquisitions. The bounty-collection quest significantly affected the procedure knowledge of subjects with high immersion motivation, whereas the fed express quest affected declarative knowledge of subjects with high immersion motivation.
A graphical editor for complex event pattern generation
Authors: Sinan Sen, Nenad Stojanovic, Ruofeng Lin
Venue: Proceedings of the Third ACM International Conference on Distributed Event-Based Systems (2009)

There exist several Complex Event Processing (CEP) engines with their own event pattern languages and event pattern generation tools. The development of complex event patterns is a challenging task since one has to handle with the underlying pattern language's syntax. In this demo we present a web based graphical editor for developing complex event patterns in order to provide a more intuitive way for the development of complex event patterns. In our application scenario ActOnTweets we will briefly present how our editor can be used in order to create complex event patterns on top of Twitter. The ActOnTweets application is composed of Twitter, the Open Calais and the Esper event engine.
A High-Speed Optical Multidrop Bus for Computer Interconnections
Authors: Michael R. T. Tan, Paul Rosenberg, Jong-Souk Yeo, Moray McLaren, Sagi Mathai, Terry Morris, Huei Pei Kuo, Joseph Straznicky, Norman P. Jouppi, Shih-Yuan Wang
Venue: IEEE Micro (2009)

Signal integrity constraints of high-speed electronics have made multidrop electrical buses infeasible. This high-speed alternative uses hollow metal waveguides and pellicle beam splitters that interconnect modules attached to the bus. With 1 mW of laser power, the bus can interconnect eight modules at 10 Gbps per channel and achieves an aggregate bandwidth of more than 25 Gbytes per second with 10-bit-wide signaling paths.
Mineralization Information Mining from GIS Map & Attribution Database and Multi-sources Data Intergration
Authors: Liu Xing
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

Much weak information are hidden in Geological map and its attribution database. In mineralization predication application, an imaged map can be combined with raster data. In this paper, some information is extracted from a geological map, such as polygon features of strata formation and lithizones, and line features of fault influence index and its type, etc. These data can be integrated to produce a 24-bit image by data fusion technique. The test result shows that a converted image geological map can hold more geological information than the original vector map, an imaged geological map represents deep mineralization information while which can not express in a vector map.
A Generalization of Forward-Backward Algorithm
Authors: Ai Azuma, Yuji Matsumoto
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Structured prediction has become very important in recent years. A simple but notable class of structured prediction is one for sequences, so-called sequential labeling. For sequential labeling, it is often required to take a summation over all the possible output sequences, when estimating the parameters of a probabilistic model for instance. We cannot make the direct calculation of such a summation from its definition in practice. Although the ordinary forward-backward algorithm provides an efficient way to do it, it is applicable to limited types of summations. In this paper, we propose a generalization of the forward-backward algorithm, by which we can calculate much broader types of summations than the existing forward-backward algorithms. We show that this generalization subsumes some existing calculations required in past studies, and we also discuss further possibilities of this generalization.
Maximum entropy modeling in sparse semantic tagging
Authors: Jia Cui, David Guthrie
Venue: Proceedings of the Student Research Workshop at HLT-NAACL 2004 on XX (2004)

In this work, we are concerned with a coarse grained semantic analysis over sparse data, which labels all nouns with a set of semantic categories. To get the benefit of unlabeled data, we propose a bootstrapping framework with Maximum Entropy modeling (MaxEnt) as the statistical learning component. During the iterative tagging process, unlabeled data is used not only for better statistical estimation, but also as a medium to integrate non-statistical knowledge into the model training. Two main issues are discussed in this paper. First, Association Rule principles are suggested to guide MaxEnt feature selections. Second, to guarantee the convergence of the boot-strapping process, three adjusting strategies are proposed to soft tag unlabeled data.
Identification of Growth Seeds in the Neonate Brain through Surfacic Helmholtz Decomposition
Authors: Julien Lefèvre, François Leroy, Sheraz Khan, Jessica Dubois, Petra S. Huppi, Sylvain Baillet, Jean-François Mangin
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

We report on a new framework to investigate the rapid brain development of newborns. It is based on the analysis of depth maps of the cortical surface through the study of a displacement field estimated by surfacic optical flow methods. This displacement field shows local evolution of sulci directly on the cortical surface. Detection of its critical points is performed with the Helmholtz decomposition which allows us to identify sources of the developmental process. They can be viewed as growth seeds or in other terms points around which the sulcal growth organizes itself. We show the reproducibility of such growth seeds across 4 neonates and make a link of this new concept to the "sulcal roots" one proposed to explain the variability of human brain anatomy.