ppxscal/embedding_network huggingface dataset:
3-D Numerical Simulation of Smoke Flow during Tunnel Fire
Authors: Zhiming Qu, Xiaoli Wang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

Using the conservation law, the theories of high temperature gas dynamics, fluid mechanics, the physical and mathematical turbulence flow field model is set up to simulate the tunnel fire and its smoke flow. An experimental fire in a tunnel is studied in light of the turbulent flow model. The results indicate that the turbulent flow field model is better than before and has prettily good consistency with the experimental data. Through the numerical simulation analysis, it is concluded that the fully developed smoke flow downstream can clearly present the distribution of layered temperature, concentration of CO2 downwind and smoke flow velocity.
Improving learning in networked data by combining explicit and mined links
Authors: Sofus A. Macskassy
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

This paper is about using multiple types of information for classification of networked data in a semi-supervised setting: given a fully described network (nodes and edges) with known labels for some of the nodes, predict the labels of the remaining nodes. One method recently developed for doing such inference is a guilt-by-association model. This method has been independently developed in two different settings-relational learning and semi-supervised learning. In relational learning, the setting assumes that the networked data has explicit links such as hyperlinks between webpages or citations between research papers. The semi-supervised setting assumes a corpus of non-relational data and creates links based on similarity measures between the instances. Both use only the known labels in the network to predict the remaining labels but use very different information sources. The thesis of this paper is that if we combine these two types of links, the resulting network will carry more information than either type of link by itself. We test this thesis on six benchmark data sets, using a within-network learning algorithm, where we show that we gain significant improvements in predictive performance by combining the links. We describe a principled way of combining mUltiple types of edges with different edge-weights and semantics using an objective graph measure called node-based assortativity. We investigate the use of this measure to combine text-mined links with explicit links and show that using our approach significantly improves performance of our classifier over naively combining these two types of links.
A user-oriented webpage ranking algorithm based on user attention time
Authors: Songhua Xu, Yi Zhu, Hao Jiang, Francis C. M. Lau
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

We propose a new webpage ranking algorithm which is personalized. Our idea is to rely on the attention time spent on a document by the user as the essential clue for producing the user-oriented webpage ranking. The prediction of the attention time of a new webpage is based on the attention time of other previously browsed pages by this user. To acquire the attention time of the latter webpages, we developed a browser plugin which is able to record the time a user spends reading a certain webpage and then automatically send that data to a server. Once the user attention time is acquired, we calibrate it to account for potential repetitive occurrences of the webpage before using it in the prediction process. After the user's attention times of a collection of documents are known, our algorithm can predict the user's attention time of a new document through document content similarity analysis, which is applied to both texts and images. We evaluate the webpage ranking results from our algorithm by comparing them with the ones produced by Google's Pagerank algorithm.
Class-based ordering of prenominal modifiers
Authors: Margaret Mitchell
Venue: Proceedings of the 12th European Workshop on Natural Language Generation (2009)

This paper introduces a class-based approach to ordering prenominal modifiers. Modifiers are grouped into broad classes based on where they tend to occur prenominally, and a framework is developed to order sets of modifiers based on their classes. This system is developed to generate several orderings for modifiers with more flexible positional constraints, and lends itself to bootstrapping for the classification of previously unseen modifiers.
Conceptual Workflow Verification and Optimization for Artifact-Centric Business Process
Authors: Dong Li
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

The conceptual workflow can be taken as a middle level between the logical specification level and the physical execution level in business workflow system. The conceptual workflow is very important in providing the independency from both the business operational model and the specified implementation platform, so it supports flexible modifications both in the top level and in the bottom level. In this paper, first, a set of graphic components is proposed here to describe an artifact-centric business process and a conceptual workflow is derived from the business operational model. Then, some syntax rules are proposed for verifying the syntactical correctness of the conceptual workflow. After that several optimization rules are proposed for optimizing the conceptual workflow and the example used shows that the optimization rules can simplify the conceptual workflow thus will improve the performance of the execution of the workflow future.
Performance Analysis of Generalized Well-formed Workflow
Authors: Zuoxian Nie, Xin-hua Jiang, Jian-cheng Liu, Hai-yan Yang
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Performance of workflow schema including overlapping patterns can not be computed by regular reducing approaches, and that excluding overlapping patterns from workflow schema will lose flexibility in schema design, introduce redundant nodes, and make it difficult to describe complex business process. To solve this problem, the concept of generalized well-formed workflow was proposed, in which overlapping patterns can appear in a workflow schema but not in any of its instance subgraphs. Further more, to meet the need of frequently re-computing of process performance after business process reengineering, methods for automatically computing routing probability and time performance of each instance subgraph are proposed, which are basis for our automatic performance analysis algorithm of whole workflow schema. Finally, an example was given to demonstrate the process of performance analysis of a generalized well-formed workflow.
Proposal for "Kansei Library Search System Based on Behavior Analysis
Authors: Nam-Gyu Kang, Reina Nakaya
Venue: Proceedings of the 2009 International Conference on Biometrics and Kansei Engineering (2009)

Library search systems that use "keywords" are very useful for people who know what they are looking for; however, this system is not helpful for those who do not have specific knowledge of what they are looking for. The purpose of this research is to propose a Kansei-library search system. Based on observing how children search, select and find books, we proposed a new system named 'MeguLook' which children can use intuitively (without knowing how to operate the system) and easily without special knowledge about the book. From an evaluation analysis, we confirmed that many people, including children can feel 'pleasure searching for and selecting their favorite books' using 'MeguLook'.
Multicast Extensions to the Location-Prediction Based Routing Protocol for Mobile Ad Hoc Networks
Authors: Natarajan Meghanathan
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

We propose multicast extensions to the location prediction-based routing protocol (NR-MLPBR and R-MLPBR) for mobile ad hoc networks to simultaneously reduce the number of tree discoveries, number of links and the hop count per path from the source to the multicast group. The multicast extensions work as follows: Upon failure of a path to the source, a receiver node attempts to locally construct a global topology using the location and mobility information collected during the latest global broadcast tree discovery. NR-MLPBR predicts a path that has the minimum number of hops to the source and R-MLPBR predicts a path to the source that has the minimum number of non-receiver nodes. If the predicted path exists in reality, the source accommodates the path as part of the multicast tree and continues to send the multicast packets in the modified tree. Otherwise, the source initiates another global broadcast tree discovery.
On-Line Rescheduling to Minimize Makespan under a Limit on the Maximum Sequence Disruption
Authors: Yundong Mu, Xiao Guo
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

In the on-line rescheduling on a single machine, a setof original jobs has already been scheduled to minimize some cost objective, when a new set of jobs arrives overtime. The decision maker needs to insert the new jobs into the existing schedule without excessively disrupting it. In this paper, we consider the online rescheduling problem to minimize makespan under a limit on the maximum sequence disruption constraints and give an online algorithm of competitive ratio 3/2 .
Automatic SAT-compilation of planning problems
Authors: Michael D. Ernst, Todd D. Millstein, Daniel S. Weld
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

Recent work by Kautz et al., provides tantalizing evidence that large, classical planning problems may be efficiently solved by translating them into propositional satisfiability problems, using stochastic search techniques, and translating the resulting truth assignments back into plans for the original problems. We explore the space of such transformations, providing a simple framework that generates eight major encodings (generated by selecting one of four action representations and one of two frame axioms) and a number of subsidiary ones. We describe a fully-implemented compiler that can generate each of these encodings, and we test the compiler on a suite of STRIPS planning problems in order to determine which encodings have the best properties.
On the Brightness of the Thomson Lamp: A Prolegomenon to Quantum Recursion Theory
Authors: Karl Svozil
Venue: Proceedings of the 8th International Conference on Unconventional Computation (2009)

Some physical aspects related to the limit operations of the Thomson lamp are discussed. Regardless of the formally unbounded and even infinite number of "steps" involved, the physical limit has an operational meaning in agreement with the Abel sums of infinite series. The formal analogies to accelerated (hyper-) computers and the recursion theoretic diagonal methods are discussed. As quantum information is not bound by the mutually exclusive states of classical bits, it allows a consistent representation of fixed point states of the diagonal operator. In an effort to reconstruct the self-contradictory feature of diagonalization, a generalized diagonal method allowing no quantum fixed points is proposed.
Analysis and Design of an Improved R-learning
Authors: Wei Chen, Zhenkun Zhai, Xiong Li, Jing Guo
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

This paper presents a modified R-learning according to the traditional average reward reinforcement learning algorithm. Reinforcement learning problems constitute an important class of learning and control problems faced by artificial intelligence systems. The general framework of reinforcement learning can be divided into two forms, discounted reward reinforcement learning and average reward reinforcement learning. R-learning is a model-free average reward reinforcement learning algorithm. Comparing with the conventional R-learning algorithm, this paper undertakes a detailed examination of the improvement of the R-learning, by adding the directing reward function with punitive mechanism and the exploration strategy based on the roulette technique. As the result of this design, agent can gain more information in every learning step. Through applying the improved R-learning to Robocup Simulation League (2D) and making comparison with the Q-learning, empirical results show that the learning efficiency has been increased.
Color Information Processing in Higher Brain Areas
Authors: Hidehiko Komatsu, Naokazu Goda
Venue: Computational Color Imaging: Second International Workshop, CCIW 2009, Saint-Etienne, France, March 26-27, 2009. Revised Selected Papers (2009)

Significant color signal transformation occurs in the primary visual cortex and neurons tuned to various direction in the color space are generated. The resulting multi-axes color representation appears to be the basic principle of color representation throughout the visual cortex. Color signal is conveyed through the ventral stream of cortical visual pathway and finally reaches to the inferior temporal (IT) cortex. Lesion studies have shown that IT cortex plays critical role in color vision. Color discrimination is accomplished by using the activities of a large number of color selective IT neurons with various properties. Both discrimination and categorization are important aspects of our color vision, and we can switch between these two modes depending on the task demand. IT cortex receives top-down signal coding the task and this signal adaptively modulates the color selective responses in IT cortex such that neural signals useful for the ongoing task is efficiently selected.
A B/S Structure-Based T-MPLS Network Management System
Authors: Zhang Yong-jun, Cao Chang, Jia Wu, Chen Rui, Huang Shan-guo, Zhang Jie, Gu Wan-yi
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

The technology of T-MPLS will be widely used in the next generation packet transport network, and some advanced network management methods should be employed in it. To meet this requirement, we introduce a novel network management model based on B/S structure. This implement method integrates Servlet/JSP technologies on the basis of SNMPv3 protocol, fully demonstrating the method's distribution and cross-platform performance. Finally, a simulation result is given to evaluate this system’s performance.
Extending cognitive architecture with episodic memory
Authors: Andrew M. Nuxoll, John E. Laird
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

In this paper, we explore the hypothesis that episodic memory is a critical component for cognitive architectures that support general intelligence. Episodic memory overlaps with case-based reasoning (CBR) and can be seen as a task-independent, architectural approach to CBR. We define the design space for episodic memory systems and the criteria any implementation must meet to be useful in a cognitive architecture. We present an implementation and demonstrate how episodic memory, combined with other components of a cognitive architecture, supports a wealth of cognitive capabilities that are difficult to attain without it.
A new and efficient approach for estimating the accurate time-domain response of single and capacitive coupled distributed RC interconnects
Authors: Massoud Masoumi, Nasser Masoumi, Amir Javanpak
Venue: Microelectronics Journal (2009)

This paper describes a novel yet highly efficient approach for estimating the time-domain response of capacitive coupled distributed RC interconnects. By using this method, the voltage signal at any particular point in such wires can be accurately and quickly obtained with very low computational cost. The proposed model exhibits a very good agreement with HSPICE simulations with worst-case error less than 3% and can be readily implemented in CAD analysis tools. This paper also presents an efficient model to estimate the capacitive crosstalk in high-speed very large scale integration (VLSI) circuits. Experimental results show that the maximum error of our peak noise predictions is less than 2.5%. In addition, this work presents an efficient artificial neural network (ANN)-based technique for modeling the time-domain response of interconnects and crosstalk noise. While existing fast noise estimation metrics may overestimate or underestimate the coupling noise, the simulation results demonstrate the ability of this approach to successfully predict coupling noise with a very good accuracy as compared to HSPICE in modest CPU times. Thereby, the proposed models and techniques can be used to predict the signal integrity for designing high-speed and high-density VLSI circuits.
Quantum complementarity and logical indeterminacy
Authors: Časlav Brukner
Venue: Natural Computing: an international journal (2009)

Whenever a mathematical proposition to be proved requires more information than it is contained in an axiomatic system, it can neither be proved nor disproved, i.e. it is undecidable, or logically undetermined, within this axiomatic system. I will show that certain mathematical propositions on a d-valent function of a binary argument can be encoded in d-dimensional quantum states of mutually unbiased basis (MUB) sets, and truth values of the propositions can be tested in MUB measurements. I will then show that a proposition is undecidable within the system of axioms encoded in the state, if and only if the measurement associated with the proposition gives completely random outcomes.
An Elderly Health Care System Using Wireless Sensor Networks at Home
Authors: Hongwei Huo, Youzhi Xu, Hairong Yan, Saad Mubeen, Hongke Zhang
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

The purpose of this project is to integrate the technologies of wireless sensor networks and public communication networks to construct a healthcare system for senior citizens at home without interfering their daily activities. This system provides 4 main functionalities, including indoor monitoring, outdoor monitoring, activity and health state decision, emergency decision and alarm. JTH has developed a prototype of wireless sensor networks, an interconnection platform and a service management platform to support large scale data interconnections and real-time activity and health state reports to related persons (e.g. doctors or nurses, elder-self, elders’ relatives) via all popular communication approaches, such asautomatic voice telephone call, SMS or Email etc. In this paper, the system functions and implementation approaches are introduced. A series of experiments results shows that the system performs high validity and reliability.
Finding N-Most Prevalent Colocated Event Sets
Authors: Jin Soung Yoo, Mark Bow
Venue: Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery (2009)

Recently, there has been considerable interest in mining spatial colocation patterns from large spatial datasets. Spatial colocations represent the subsets of spatial events whose instances are frequently located together in nearby geographic area. Most studies of spatial colocation mining require the specification of a minimum prevalent threshold to find the interesting patterns. However, it is difficult for users to provide appropriate thresholds without prior knowledge about the task-specific spatial data. We propose a different framework for spatial colocation pattern mining: finding N-most prevalent colocated event sets, where N is the desired number of event sets with the highest interest measure values per each pattern size. We developed an algorithm for mining N-most prevalent colocation patterns. Experimental results with real data show that our algorithmic design is computationally effective.
A Fast Method for Solving System of Nonlinear Equations in Fundamental Matrix Estimation
Authors: Wang Yuanbin, Zhang Bin, Yao Tianshun
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

The computation of the fundamental matrix given a set of point correspondences between two images has been the critical point of research for decades. The fundamental matrix should be of rank two for all the epipolar lines to intersect in a unique epipole. Traditional methods of enforcing the rank two property of the matrix are to parameterize the fundamental matrix during the estimation. This usually results in a system of nonlinear multivariable equations of higher degree and it is hard to solve. This paper presents an effective method to solve the typical nonlinear multivariable equations encountered in the fundamental matrix estimation with rank constraint. The method is based on the classical Lagrange multipliers method. After careful transformations of the problem, we reduce the solution of multivariable nonlinear equations to the solution of some single variable equations.
A Cost Sensitive Ensemble Method for Medical Prediction
Authors: Liangyuan Li, Mei Chen, Hanhu Wang, Wei Chen, Zhiyong Guo
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

In this paper we present an analysis of the importance of cost sensitive methodology in medical disease prediction. And a C5.0 based cost sensitive ensemble approach is presented to support improving the effectiveness and decreasing the misdiagnosis cost in the same time. The verification is conducted on the real cases from Changhai Hospital Renal Registered (CHRR) data which consists of 483 records, and 25 fields are used through variable selection. The real case experiments show that, our approach works effectively and could be used as an assistant approach for peritonitis analysis in some circumstances.
Identifying user values for an activating game for children
Authors: Sari Kujala, Piia Nurkka
Venue: Proceedings of the 13th International MindTrek Conference: Everyday Life in the Ubiquitous Era (2009)

Psychological values describe what is important to a person in life and values are also essential in persuading users. In this paper, we provide a sentence completion tool for identifying user values and demonstrate its use in a case study. The goal of the case study was to identify parents' values related to children's exercise to get first ideas for a game for children. Raising children is particularly value loaded from parents' point of view. Thus, in order to design a persuasive game that activates children to exercise, it is necessary to understand both what is important to children themselves and what is desirable from parents' point of view. The results show that the sentence completion tool helps users to describe their hidden values in their own words and provides important insights for concept design.