ppxscal/embedding_network huggingface dataset:
An Investigation of the Relationship between Land Cover Ratio and Urban Heat Island
Authors: Xingping Wen, Guangdao Hu, Xiaofeng Yang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

This paper investigates the relationship between land cover ratio and UHI in Guangzhou of China. Firstly, the hourly mean temperature was computed from the hourly automatic weather station (AWS) data in October, 2004. Secondly, the CBERS remote sensing image acquired in October 10, 2004 was classified using support vector machine (SVM). Thirdly, the classification outcome was overlapped with a round buffer with 1.5KM radius centered on the AWS, then the land cover ratio, Edge Density (ED) and Mean Fractal Dimension (MFRACT) of the buffer were computed out. Finally, correlation coefficient between hourly mean temperature and land cover ratio, ED and MFRACT was calculated. It concludes that heat island intensity is heavier during the night-time than daytime. Stations which have higher vegetation ratio and higher ED have lower heat island effect. On the contrary, stations which have the higher impervious ratio and lower ED have more serious heat island effect.
Toward Meta-cognitive Tutoring: A Model of Help Seeking with a Cognitive Tutor
Authors: Vincent Aleven, Bruce Mclaren, Ido Roll, Kenneth Koedinger
Venue: International Journal of Artificial Intelligence in Education (2006)

The research reported in this paper focuses on the hypothesis that an intelligent tutoring system that provides guidance with respect to students' meta-cognitive abilities can help them to become better learners. Our strategy is to extend a Cognitive Tutor (Anderson, Corbett, Koedinger, & Pelletier, 1995) so that it not only helps students acquire domain-specific skills, but also develop better general help-seeking strategies. In developing the Help Tutor, we used the same Cognitive Tutor technology at the meta-cognitive level that has been proven to be very effective at the cognitive level. A key challenge is to develop a model of how students should use a Cognitive Tutor's help facilities. We created a preliminary model, implemented by 57 production rules that capture both effective and ineffective help-seeking behavior. As a first test of the model's efficacy, we used it off-line to evaluate students' help-seeking behavior in an existing data set of student-tutor interactions. We then refined the model based on the results of this analysis. Finally, we conducted a pilot study with the Help Tutor involving four students. During one session, we saw a statistically significant reduction in students' meta-cognitive error rate, as determined by the Help Tutor's model. These preliminary results inspire confidence as we gear up for a larger-scale controlled experiment to evaluate whether tutoring on help seeking has a positive effect on students' learning outcomes.
Engineering Label-Constrained Shortest-Path Algorithms
Authors: Chris Barrett, Keith Bisset, Martin Holzer, Goran Konjevod, Madhav Marathe, Dorothea Wagner
Venue: Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management (2008)

We consider a generalization of the shortest-path problem: given an alphabet Σ, a graph G whose edges are weighted and Σ-labeled, and a regular language L ¿ Σ *, the L-constrained shortest-path problem consists of finding a shortest path p in G such that the concatenated labels along p form a word of L. This definition allows to model, e. g., many traffic-planning problems. We present extensions of well-known speed-up techniques for the standard shortest-path problem, and conduct an extensive experimental study of their performance with various networks and language constraints. Our results show that depending on the network type, both goal-directed and bidirectional search speed up the search considerably, while combinations of these do not.
Improving skim reading for document triage
Authors: George Buchanan, Tom Owen
Venue: Proceedings of the second international symposium on Information interaction in context (2008)

When users seek for information, they repeatedly make relevance judgements on individual documents: the act of document triage. Recent research demonstrates that document triage decisions are prone to significant error rates. Document triage also affects the future course of information seeking: users form beliefs about the availability of information, determine new information goals and conclude others. Developing effective interactions to support document triage is therefore critical. This paper investigates how improve support for the quick review of a document, exploiting the principle of semantic zooming. We discover that applying semantic zooming improves the legibility of heading text during the rapid scrolling and overview reading that is associated with the earliest phases of document triage.
Clustering in Ad Hoc Personal Network Formation
Authors: Yanying Gu, Weidong Lu, R. V. Prasad, Ignas Niemegeers
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Personal Network (PN) is a user-centric concept to realize the interconnection of the users' various devices and networks, such as home networks, corporate networks and vehicle area networks, at any time and any place. These networks may be geographically separated from each other and are usually organized in an ad hoc fashion, where the devices in one network can share content, data, applications and resources with each other, and communicate with the outside world. Clustering for personal networks intends to organize these ad-hoc networked heterogeneous devices into hierarchical clusters. A new clustering scheme, Personal Network Clustering Protocol (PNCP), is proposed for PNs and compared with clustering algorithms in the literature in terms of various performance metrics. PNCP performs the cluster formation based on heterogeneity of PNs in a distributed way, forms clusters with a moderate number of nodes, limits the cluster radius to k-hops, decreases the change in the cluster composition, extends the average membership time in the clusters providing stability and generates less overhead traffic. Though it was aimed for PNs, this protocol can also be used for any other heterogeneous ad hoc network for clustering.
Mimicking Go Experts with Convolutional Neural Networks
Authors: Ilya Sutskever, Vinod Nair
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Building a strong computer Go player is a longstanding open problem. In this paper we consider the related problem of predicting the moves made by Go experts in professional games. The ability to predict experts' moves is useful, because it can, in principle, be used to narrow the search done by a computer Go player. We applied an ensemble of convolutional neural networks to this problem. Our main result is that the ensemble learns to predict 36.9% of the moves made in test expert Go games, improving upon the state of the art, and that the best single convolutional neural network of the ensemble achieves 34% accuracy. This network has less than 104 parameters.
Separating Precision and Mean in Dirichlet-Enhanced High-Order Markov Models
Authors: Rikiya Takahashi
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

Robustly estimating the state-transition probabilities of high-order Markov processes is an essential task in many applications such as natural language modeling or protein sequence modeling. We propose a novel estimation algorithm called Hierarchical Separated Dirichlet Smoothing (HSDS), where Dirichlet distributions are hierarchically assumed to be the prior distributions of the state-transition probabilities. The key idea in HSDS is to separate the parameters of a Dirichlet distribution into the precision and mean, so that the precision depends on the context while the mean is given by the lower-order distribution. HSDS is designed to outperform Kneser-Ney smoothing especially when the number of states is small, where Kneser-Ney smoothing is currently known as the state-of-the-art technique for N-gram natural language models. Our experiments in protein sequence modeling showed the superiority of HSDS both in perplexity evaluation and classification tasks. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Efficient Content Creation on the Semantic Web Using Metadata Schemas with Domain Ontology Services (System Description)
Authors: Onni Valkeapää, Olli Alm, Eero Hyvönen
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

Metadata creation is one of the major challenges in developing the Semantic Web. This paper discusses how to make provision of metadata easier and cost-effective by an annotation editor combined with shared ontology services. We have developed an annotation system supporting distributed collaboration in creating annotations, and hiding the complexity of the annotation schema and the domain ontologies from the annotators. Our system adapts flexibly to different metadata schemas, which makes it suitable for different applications. Support for using ontologies is based on ontology services, such as concept searching and browsing, concept URI fetching, semantic autocompletion and linguistic concept extraction. The system is being tested in various practical semantic portal projects.
A Novel Multiple Improved PID Neural Network Ensemble Model for pH Value in Wet FGD
Authors: Shen Yongjun, Gu Xingsheng, Bao Qiong
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

In the limestone/gypsum wet flue gas desulphurization (FGD) technology, the change of slurry pH value in absorber is a nonlinear and time-variation process with a large number of uncertainties, so it's difficult to acquire satisfying mathematical model. In this paper, a novel multiple improved PIDNN ensemble model is proposed to establish the model of slurry pH value. In this model, the concepts of variable integral and partial differential are introduced in the design of hidden-layer of PIDNN, and the concept of output feedback is utilized to improve the ability of PIDNN for dynamic modeling, then multiple improved PIDNN are dynamic combined to get the system output. The results of simulation with field data of wet FGD indicate the validity of this modeling approach.
Statistical Models of Shape: Optimisation and Evaluation, 1 edition
Authors: Rhodri Davies, Carole Twining, Chris Taylor
Venue:  (2008)

Deformable shape models have wide application in computer vision and biomedical image analysis. This book addresses a key issue in shape modelling: establishment of a meaningful correspondence between a set of shapes. Correspondence has traditionally been established by manual annotation of the data, however this is a time-consuming and error-prone process that does not extend easily to 3D. Thus, almost all applications of statistical shape models have been restricted to 2D objects. This book explores a particular approach to establishing correspondence that casts model-building as an optimisation problem. A general framework is established to find the correspondence that optimises an objective function of model quality. Efficient methods, including implementation details, are presented for manipulating correspondences and for optimising the objective function. Practical example applications are presented for 2D as well as for 3D sets of shapes.
Concavely-Priced Timed Automata
Authors: Marcin Jurdziński, Ashutosh Trivedi
Venue: Proceedings of the 6th international conference on Formal Modeling and Analysis of Timed Systems (2008)

Concavely-priced timed automata, a generalization of linearly-priced timed automata, are introduced. Computing the minimum value of a number of cost functions--including reachability price, discounted price, average time, average price, price-per-time average, and price-per-reward average--is considered in a uniform fashion for concavely-priced timed automata. All the corresponding decision problems are shown to be PSPACE-complete. This paper generalises the recent work of Bouyer et al. on deciding the minimum reachability price and the minimum ratio-price for linearly-priced timed automata.A new type of a region graph--the boundary region graph--is defined, which generalizes the corner-point abstraction of Bouyer et al. A broad class of cost functions--concave-regular cost functions--is introduced, and the boundary region graph is shown to be a correct abstraction for deciding the minimum value of concave-regular cost functions for concavely-priced timed automata.
Modelling Short Range Alternating Transitions by Alternating Practical Test Functions
Authors: Stefan Pusca
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

As it is known, practical test-functions [1] are very useful for modeling suddenly emerging phenomena. By this study we are trying to use some specific features of these functions for modeling aspects connected with transitions from a certain steady-state to another, with emphasis on he use of short range alternating functions. The use of such short range alternating functions is required by the fact that in modern physics (quantum physics) all transitions imply the use of certain quantum particles (field quantization) described using associated frequencies for their energy. Due to this reason, a connection between a wave interpretation of transitions (based on continuous functions0 and corpuscle interpretation of transitions (involving creation and annihilation of certain quantum particles) should be performed using certain oscillations defined on a limited time interval corresponding to the transition from one steady-state to another.
Integrating Communication Cost into the Utility Accrual Model for the Resource Allocation in Distributed Real-Time Systems
Authors: Xinfa Hu, Joseph Y. -T. Leung
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

In distributed real-time systems, both computation and communication are critical factors. The timeliness of activities relies on both the computation and the communication involved in them. Moreover, the timeliness of computation relies on that of communication, and vice versa. This property requires that both computation and communication be integrated into the resource allocation model and that the model be able to capture the interplay between them. Unfortunately, the utility/benefit/value accrual models employed in current distributed real-time systems are constructed solely on computation. They are inadequate for capturing the interplay between computation and communication. This paper extends previous research on utility-based model by proposing a new utility accrual model, which integrates both computation and communication. Most importantly, the interplay between computation and communication is fully characterized in the model. Under the new model, resource managers are guided towards maximizing system-wide utility by exploring the interplay between computation and communication instead of traditional meeting the timing constraint on computation and the deadline of communication separately. To validate the effectiveness of this model, a resource allocation algorithm called CAUASA is developed under it. The performance of CAUASA is compared to that of another resource allocation algorithm that is developed according to existing utility accrual models. Simulation results reveal that CAUASA is far superior to its counterpart. Therefore, the new utility accrual model provides a more effective framework for the resource allocation in distributed real-time systems.
Detection for Pickup Errors by Artificial Neural Networks
Authors: Hirotake Esaki, Taizo Umezaki, Tetsumi Horikoshi
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

Taping machines, chip mounters and surface mount device (SMD) inspection systems use image processing techniques for the positioning of SMDs. The improvement of the production quality as well as the productivity is strongly requested in these systems. The image processing system in these systems have inspection functions to improve production quality. Generally, images of the part being picked up by the nozzle are acquired in a horizontal direction, and pickup errors are detected by processing these images. The aim of this paper is to develop a system for detecting pickup errors by processing images of parts acquired from the bottom. By using our proposed method, the detection rate of pickup errors is 99.3%.
Towards the Dynamic Semantic Web
Authors: Ian Oliver
Venue: Proceedings of the 8th international conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART on Next Generation Teletraffic and Wired/Wireless Advanced Networking (2008)

The Semantic Web is emerging as the future platform for computation. The ability to represent information, its structure and some of its semantics in a canonical form that is readable and understandable by machine forms the key infrastructure for truly ubiquitous computing. On top of this structure we are seeing the development of more sophisticated services, reasoning and applications and a re-emergence of machine intelligence in the mainstream environment.
Style subspaces for character animation
Authors: Gengdai Liu
Venue: Computer Animation and Virtual Worlds (2008)

In this paper, we present a novel method for editing stylistic human motions. We represent styles as differences between stylistic and introduced neutral motions, including timing differences and spatial differences. Timing differences are defined as time alignment curves, while spatial differences are found by a machine learning technique: independent feature subspaces analysis, which is the combination of multidimensional independent component analysis and invariant feature subspaces. This technique is used to decompose two motions into several subspaces. One of these subspaces can be defined as style subspace that describes the style aspects of the stylistic motion. In order to find the style subspace, we compare norms of the projections of two motions on each subspace. Once the time alignment curves and style subspaces of several motion clips are obtained, animators can tune, transfer, and merge the style subspaces to synthesize new motion clips with various styles. Our method is easy to use since manual manipulations and large training data sets are not necessary. Copyright &copy; 2008 John Wiley & Sons, Ltd.
RFID Stamp with RFID Passive Reader
Authors: Junki Kang, Namje Park, Yousung Kang, Dooho Choi
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

The RFID system is very much used until it reaches the various services including the physical distribution, circulation, military affairs, health care. The RFID system to a now came to the passive tag itself along the normal distribution route, we could not know. The RFID STAMP SYSTE to be proposed is designed so that it overcomes these disadvantages and we can trace the distribution route with each passive type reader.
Introduction to System Level Design for Heterogeneous Systems
Authors: John Mcallister
Venue: Proceedings of the 8th international workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2008)

For the current generation of heterogeneous multi-core embedded processor, Systemon-Chip and FPGA platforms, implementation and optimisation of Digital Signal and Image Processing applications is an exceptionally challenging task, with the widely accepted viewpoint being that moving towards high abstraction (system) level design principles is the only feasible option to increasing the productivity of application synthesis on such complex platforms. However, this movement, which has been widely touted for many years, has been slow to materialise due to the vast array of processing components, architectures and design methodologies at the disposal of any such system designer.
Identification of fuzzy models using a successive tuning method with a variant identification ratio
Authors: Jeoung-Nae Choi, Sung-Kwun Oh, Witold Pedrycz
Venue: Fuzzy Sets and Systems (2008)

The paper is concerned with the identification of fuzzy inference systems (fuzzy models) realized with the aid of the successive tuning method using a variant identification ratio that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFC-PGA) and information granulation. The HFC-PGA is a certain multi-population version of Parallel Genetic Algorithms (PGA), which is suitable for a simultaneous optimization of both the structure of the fuzzy model as well as its parameters. The granulation of information is realized with the aid of the C-Means clustering algorithm. Information granules formed in this way become essential at further stages of the construction of the fuzzy models by forming the centers (modal values) of the fuzzy sets constituting individual rules of the inference schemes. Further optimization of the fuzzy model deals with an adjustment of a suite of parameters (such as the number of input variables to be used in the model, a collection of specific subsets of the input variables, and the number of membership functions) being used by these variables, and the order and parameters of the polynomial occurring in the conclusions of the corresponding rules. An iterative development of the fuzzy model deals with its structural as well as parametric optimization via HFC-PGA, the C-Means algorithm, and a standard least square estimation method. To evaluate the performance of the proposed model, we exploit well known and commonly used data sets such as gas furnace, Mackey-Glass time series as well as medical imaging system. A comparative analysis demonstrates that the proposed model leads to the superior performance when compared with other fuzzy models reported in the literature.
Smart Caching Algorithm for Software Agents Based on Re-execution Probability
Authors: Jarogniew Rykowski
Venue: Proceedings of the 3rd international conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2007)

In this paper we propose a new, smart strategy for efficient caching of user-defined software agents. The strategy is based on setting up minimum and maximum caching time for individual agents. These timings are formed on the basis of a way of calling an agent (type of input/output gateway serving a call, previous calls to the same agent, etc.), on the one hand, and past/current/ predicted system load, including waiting calls to be served in the near future for the same and other agents, on the other hand. As proven by the tests in real applications, the strategy is efficient, especially in the case of a mass-scale system with thousands and even millions of agents owned (and possibly programmed) by different users.
Taking Steps to Secure Web Services
Authors: David Geer
Venue: Computer (2003)

Organizations are investing considerable resources in Web services, an approach that comprises a set of platform-neutral technologies designed to ease the delivery of services over intranets and the Internet. Web services enable interoperability via a set of open standards, including XML to provide information about the data in a document to users on various platforms; the simple object access protocol (SOAP) for cross-platform interapplication communication; the Web Services Description Language to describe online services; and the universal description, discovery, and integration protocol to find available Web services on the Internet or corporate networks.