ppxscal/embedding_network huggingface dataset:
Dynamic Analysis of Tip Set Extra Hard Load of Vertical Shaft Impact Crusher
Authors: Jun-ming Zhang, Fang Zhao, Wei Wang, Xiang-bo Ze, Dong-ning Su
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

Rotor is the major work components of Vertical Shaft Impact Crusher and tip set extra hard is the most wearing part of it. Based on the analysis of the structure and the working principles of the Vertical Shaft Impact Crusher, we set up the three-dimensional model of the rotor in Solid Works. Through the importation of the 3-D model into ADAMS for the dynamic simulation, we simulate the throwing process of the materials when the crusher is in operation, then gain the variation of the biggest and average impact force suffered by the tip set extra hard of rotor at different spindle speed. Simulation analysis shows that the speed of the rotor is an important factor that impacts the crushing quality and efficiency of the vertical shaft impact crusher, but the crushing effect is not always rising with the speed increasing and high speed would aggravate the wear and tear of tip set extra hard .The speed range of the rotor is from 1400 to 1500 rpm or from 1600 to 1750 rpm, between which the tip set extra hard suffers balanced force and can operate stably. In addition, in order to fully take into account the crusher broken quality, efficiency and service life, reducing the value and frequency of the greatest impact is of vital important, for one thing, the rotor structure and the optimization of the relevant parameters need to be taken into consideration, for another thing, the impact of the of uniformity of the feed particle size should also be analyzed.
Gender and Cultural Differences in Perceiving Game Characters of Digital Educational Games
Authors: Effie Lai-Chong Law, Tim Gamble, Daniel Schwarz
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

A survey on the initial design of a digital educational game was developed and administered to the target group in Germany and England. Some significant gender and cultural differences in game play habit, game type preferences and game character perceptions were observed.
Transformations between Cryptographic Protocols
Authors: Joshua D. Guttman
Venue: Foundations and Applications of Security Analysis: Joint Workshop on Automated Reasoning for Security Protocol Analysis and Issues in the Theory of Security, ARSPA-WITS 2009, York, UK, March 28-29, 2009, Revised Selected Papers (2009)

A transformation F between protocols associates the messages sent and received by participants in a protocol ${\it\Pi}_1$ with messages sent and received in some ${\it\Pi}_2$. Transformations are useful for modeling protocol design, protocol composition, and the services that protocols provide.A protocol transformation determines a map from partial behaviors ${\mathbb A}_1$ of ${\it\Pi}_1$--which we call "skeletons"--to skeletons $F({\mathbb A}_1)$ of ${\it\Pi}_2$. Good transformations should act as functors, preserving homomorphisms (information-preserving maps) from one ${\it\Pi}_1$-skeleton to another. Thus, if $H:{\mathbb A}_1\mapsto{\mathbb A}_2$ is a homomorphism between ${\it\Pi}_1$-skeletons, then there should be a homomorphism $F(H): F({\mathbb A}_1)\mapsto F({\mathbb A}_2)$ between their images in ${\it\Pi}_2$.We illustrate protocol transformation by examples, and show that our definition ensures that transformations act as functors.
Simulation Research on Influence of Velocity Discreteness on Venture Degree of Vehicle Rear-End Accidents
Authors: Yihu Wu, Dan Yu, Jixiang Xie
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

The relationship between the velocity discreteness σ and the venture degree of vehicle Rear-end accidents on freeway and urban road is researched by NS model. We could get the followings as the results of simulation: Firstly, the value of global standard deviation of velocity on freeway is bigger than the one on urban road. Secondly, the value of venture degree of Rear-end accidents is added as the increase of the value of global standard deviation of velocityσ, and the venture degree of Rear-end accidents on urban road is more sensitive than the one on freeway. Thirdly, if we could set the values of average velocity as constants and only change the value of initial velocity discretenessσ0, we could conclude that the bigger the value ofσ0 , the bigger the value of m and the less safety to vehicles on the road.
Solving CSPs with Naming Games
Authors: Stefano Bistarelli, Giorgio Gosti
Venue: Recent Advances in Constraints: 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Rome, Italy, June 18-20, 2008, Revised Selected Papers (2009)

Constraint solving problems (CSPs) represent a formalization of an important class of problems in computer science. We propose here a solving methodology based on the naming games. The naming game was introduced to represent N agents that have to bootstrap an agreement on a name to give to an object. The agents do not have a hierarchy and use a minimal protocol. Still they converge to a consistent state by using a distributed strategy. For this reason the naming game can be used to untangle distributed constraint solving problems (DCSPs). Moreover it represents a good starting point for a systematic study of DCSP methods, which can be seen as further improvement of this approach.
Overview of the INEX 2008 XML Mining Track
Authors: Ludovic Denoyer, Patrick Gallinari
Venue: Advances in Focused Retrieval: 7th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2008, Dagstuhl Castle, Germany, December 15-18, 2008. Revised and Selected Papers (2009)

We describe here the XML Mining Track at INEX 2008. This track was launched for exploring two main ideas: first identifying key problems for mining semi-structured documents and new challenges of this emerging field and second studying and assessing the potential of machine learning techniques for dealing with generic Machine Learning (ML) tasks in the structured domain i.e. classification and clustering of semi structured documents. This year, the track focuses on the supervised classification and the unsupervised clustering of XML documents using link information. We consider a corpus of about 100,000 Wikipedia pages with the associated hyperlinks. The participants have developed models using the content information, the internal structure information of the XML documents and also the link information between documents.
Process Analysis of Service Modularization Based on Cluster Arithmetic
Authors: Ling Yang, Miyuan Shan
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

The concept of modularity works not only with physical product but also be used to create flexible service. Modular service architecture reduces the complexities of operation while at the same time speeding in bringing new products to market. In this paper, we create a novel methodology for identifying modules in service. Through service process analysis, a function relation matrix is examined to define the relationships between the service elements. The reintegration process by using ward's method and K-means clustering is also analyzed. Finally we test such approach on the specific case of an express mail delivery service.
An effective and robust method for short text classification
Authors: Victoria Bobicev, Marina Sokolova
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Classification of texts potentially containing a complex and specific terminology requires the use of learning methods that do not rely on extensive feature engineering. In this work we use prediction by partial matching (PPM), a method that compresses texts to capture text features and creates a language model adapted to a particular text. We show that the method achieves a high accuracy of text classification and can be used as an alternative to state-of-art learning algorithms.
Spatial representation and reasoning for human-robot collaboration
Authors: William G. Kennedy, Magdalena D. Bugajska, Matthew Marge, William Adams, Benjamin R. Fransen, Dennis Perzanowski, Alan C. Schultz, J. Gregory Trafton
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

How should a robot represent and reason about spatial information when it needs to collaborate effectively with a human? The form of spatial representation that is useful for robot navigation may not be useful in higher-level reasoning or working with humans as a team member. To explore this question, we have extended previous work on how children and robots learn to play hide and seek to a human-robot team covertly approaching a moving target. We used the cognitive modeling system, ACT-R, with an added spatial module to support the robot's spatial reasoning. The robot interacted with a team member through voice, gestures, and movement during the team's covert approach of a moving target. This paper describes the new robotic system and its integration of metric, symbolic, and cognitive layers of spatial representation and reasoning for its individual and team behavior.
Text comparison using machine-generated nuggets
Authors: Liang Zhou
Venue: Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations on XX (2007)

This paper describes a novel text comparison environment that facilities text comparison administered through assessing and aggregating information nuggets automatically created and extracted from the texts in question. Our goal in designing such a tool is to enable and improve automatic nugget creation and present its application for evaluations of various natural language processing tasks. During our demonstration at HLT, new users will able to experience first hand text analysis can be fun, enjoyable, and interesting using system-created nuggets.
Semantic-Based Segmentation and Annotation of 3D Models
Authors: Laura Papaleo, Leila Floriani
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

3D objects have become widely available and used in different application domains. Thus, it is becoming fundamental to use, integrate and develop techniques for extracting and maintaining their embedded knowledge. These techniques should be encapsulated in portable and intelligent systems able to semantically annotate the 3D object models in order to improve their usability and indexing, especially in innovative web cooperative environments. Lately, we are moving in this direction, with the definition and development of data structures, methods and interfaces for structuring and semantically annotating 3D complex models (and scenes) - even changing in time - according to ontology-driven metadata and following ontology-driven processes. Here, we concentrate on the tools for segmenting manifold 3D models and on the underline structural representation that we build and manipulate. We also describe the first prototype of an annotation tool which allows a hierarchical semantic-driven tagging of the segmented model and provides an interface from which the user can inspect and browse the entire segmentation graph.
The Prismoid of Resources
Authors: Delia Kesner, Fabien Renaud
Venue: Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009 (2009)

We define a framework called the prismoid of resources where each vertex refines the ¿-calculus by using a different choice to make explicit or implicit (meta-level) the definition of the contraction, weakening, and substitution operations. For all the calculi in the prismoid we show simulation of β-reduction, confluence, preservation of β-strong normalisation and strong normalisation for typed terms. Full composition also holds for all the calculi of the prismoid handling explicit substitutions. The whole development of the prismoid is done by making the set of resources a parameter, so that the properties for each vertex are obtained as a particular case of the general abstract proofs.
Frequent Itemset Mining for Clustering Near Duplicate Web Documents
Authors: Dmitry I. Ignatov, Sergei O. Kuznetsov
Venue: Proceedings of the 17th International Conference on Conceptual Structures: Conceptual Structures: Leveraging Semantic Technologies (2009)

A vast amount of documents in the Web have duplicates, which is a challenge for developing efficient methods that would compute clusters of similar documents. In this paper we use an approach based on computing (closed) sets of attributes having large support (large extent) as clusters of similar documents. The method is tested in a series of computer experiments on large public collections of web documents and compared to other established methods and software, such as biclustering, on same datasets. Practical efficiency of different algorithms for computing frequent closed sets of attributes is compared.
Design for Test
Authors: Rebecca J. Wirfs-Brock
Venue: IEEE Software (2009)

The design of tests and of the code that satisfies them should be complementary parts of software development.
Two-Stage Fuzzy Logic Controller Based on Adjustable Phase Sequence for Urban Traffic Intersection
Authors: Xiaohong Peng, Laisheng Xiao, Zhi Mo, Guodong Liu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

On the basis of research on fuzzy traffic control algorithm for a single intersection, we present a new adjustable multi-phase sequence fuzzy control algorithm. By this method, not only the traffic flow of every phase is considered, but also the green time and red time. Base on this algorithm, a two-stage fuzzy control system which consist of the green time delay module and phase selection module is designed .The first stage chooses a candidate of the green light phase which has the highest emergency degree among all red light phases. the second stage judges to continue to delay or convert green light phase according to the length of the vehicle queue at the current green light phase and the candidate. Computer simulation shows that the new type of fuzzy control algorithm possesses flexible phase combi-nation with little delay, it can solve the imbalance of traffic flow very well at the intersection.
A Method of Emotion Recognition Based on ECG Signal
Authors: Ya Xu, Guang-Yuan Liu
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

Emotion recognition from Electrocardiography (ECG) signal has become an important research topic in the field of affective computing. In the current work, ECG signals from multiple subjects were collected when film clips shown to them, and then feature sets were extracted from precise location of P-QRS-T wave by continuous wavelet transform (CWT). Hybrid Particle Swarm Optimization (HPSO) was utilized for feature selection, whose discrimination criteria was the correct rate of fisher classifier and the number of features selected. For recognizing two emotions of joy and sadness, effective features and better recognition rate were obviously obtained. Experimental results indicate that the features that acquired from experimental simulation can represent the changes of emotions, HPSO and fisher classifier are effective ways for emotion recognition.
Iterative Algorithm for Road Simulator Using Smooth Filter
Authors: Bin Wang, Xue-xun Guo, Bo Yang, Gang-feng Tan, Zhan Xu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

Remote parameter control (RPC) is presently the major technique for road simulator. However, the iterative parameters settlement in traditional RPC method much relies on test-personnel's experience. To aim at it, this article presents an improved road simulation iterative method, with which stochastic pavement unevenness has been reproduced on a road simulation test rig. After figuring out input errors by tradition RPC, a smooth filter was devised and then next step input signal was computed by taking filtered error signal directly as the correction of input signal in the iterative formula. For the sake of iterative process stabilization, filter parameter was determined according to the value of iterative relative error. Test results indicate that the iterative process is steady and waveform reproducing precision is high by applying filtered error signal.
Pathfinding Strategy for Multiple Non-Playing Characters in 2.5 D Game Worlds
Authors: Jason Macgregor, Steve Leung
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

This paper investigates and determines the optimal pathfinding strategy for non-playing characters (NPCs) in 2.5D game worlds. Three algorithms, Dijkstra's, Best-first Search (BFS) and the A* algorithm using Manhattan distance, Euclidean distance and Diagonal distance heuristics, are tested under different interaction schemes and test environments consisting of different levels of obstacles. The result shows that the A* algorithm is the optimal algorithm under the Manhattan distance Heuristic. Our tests did not reveal significant difference among the cooperative, non-cooperative or competitive interaction schemes.
Understanding IBM SOA Foundation Suite: Learning Visually with Examples, 1st edition
Authors: Tinny Ng, Jane Fung, Laura Chan, Vivian Mak
Venue:  (2009)

Understanding IBM SOA Foundation Suite Learning Visually with Examples Master the IBM SOA Foundation Through 26 Hands-On, Start-to-Finish Tutorials The IBM SOA Foundation Suite is an integrated, open-standards-based set of software, best practices, and patterns that help you systematically maximize the business value of SOA. Understanding IBM SOA Foundation Suite brings together 26 hands-on tutorials that will help you master IBM SOA Foundation and apply it successfully in your organization. Four of IBMs SOA practitioners identify core IBM SOA Foundation components and usage scenarios, and walk you step-by-step through implementing them in real-world environments. This books self-contained tutorials are presented both in print and through video on the accompanying CD-ROM, showing you the results of every action immediately, whether youre running the software or not. Using these tutorials, technical professionals can quickly move up the learning curve, discovering how each product works, and how they fit together. Youll gain the big picture overview you need to make intelligent up-front decisions, and all the hands-on practice you need to prototype working solutions. Coverage includes Designing services with UML, sharing designs via HTML files, and transforming designs to and from Java with IBM Rational Software Architect Creating services with IBM Rational Application Developer, and deploying them with IBM WebSphere Application Server Implementing effective service governance with IBM WebSphere Service Registry and Repository Integrating existing services into new business processes with IBM WebSphere Integration Developer and IBM WebSphere Process Server Connecting services with IBM WebSphere Message Broker Developing, testing, deploying, and managing portlets with IBM WebSphere Portlet Factory and IBM WebSphere Portal Systematically securing services with IBM Tivoli Federated Identity Manager
Exploring the neural correlates of social stereotyping
Authors: Susanne Quadflieg, David J. Turk, Gordon D. Waiter, Jason P. Mitchell, Adrianna C. Jenkins, C. Neil Macrae
Venue: Journal of Cognitive Neuroscience (2009)

Judging people on the basis of cultural stereotypes is a ubiquitous facet of daily life, yet little is known about how this fundamental inferential strategy is implemented in the brain. Using fMRI, we measured neural activity while participants made judgments about the likely actor (i.e., person-focus) and location (i.e., place-focus) of a series of activities, some of which were associated with prevailing gender stereotypes. Results revealed that stereotyping was underpinned by activity in areas associated with evaluative processing (e.g., ventral medial prefrontal cortex, amygdala) and the representation of action knowledge (e.g., supramarginal gyrus, middle temporal gyrus). In addition, activity accompanying stereotypic judgments was correlated with the strength of participants' explicit and implicit gender stereotypes. These findings elucidate how stereotyping fits within the neuroscience of person understanding.
A Visual Data Mining Approach to Find Overlapping Communities in Networks
Authors: Jiyang Chen, Osmar Zaïane, Randy Goebel
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Communities in social networks may overlap, with some hub nodes belonging to multiple communities. They may also have outliers, which are nodes that belong to no community. The criterion to locate hubs or outliers is network dependent. Previous methods usually require this information as input parameters, e.g., an expected number of communities, with no intuition or assistance. Here we present a visual data mining approach, which first helps the user to make appropriate parameter selections by observing initial data visualizations, and then finds and extracts overlapping community structures from the network. Experimental results verify the scalability and accuracy of our approach on real network data and show its advantages over previous methods.
A Data Mining Method for Finding Hidden Relationship in Blood and Urine Examination Items for Health Check
Authors: Kazuhiko Shinozawa, Norihiro Hagita, Michiko Furutani, Rumiko Matsuoka
Venue: Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects (2009)

Our periodic health examination often describes whether each examination item in blood and urine takes in the reference range of each examination item and a simple summary report on checks in everyday life and the possibility of suspicious diseases. However, it uses n variable items such as AST(GOT), ALT(GPT) which are less correlated, and often includes expensive tumor markers. Therefore, this paper proposes a data mining method for finding hidden relationships between these items in order to reduce the examination fee and giving a report depending on individuals. Since low correlation coefficients are shown in most pairs of items over all clients, a set of item's values in consecutive health examinations of each client is investigated for data mining. Four groups are formed according to the frequency taking outside the reference range in an item for three consecutive examinations, and average values of the other items included in each group are calculated in all pairs of items. The experiment results for three consecutive health examinations show that a lot of item pairs have positive or negative correlations between different frequencies with an item and the averages with the other item despite the fact that their correlation coefficients are small. The result shows both possible reducting of reducing the examination fee as inexpensive as possible and the possibility of a health-care report reflecting individuals.