ppxscal/embedding_network huggingface dataset:
Probabilistic Logic Learning - A Tutorial Abstract
Authors: Luc Raedt
Venue: Proceedings of the 25th International Conference on Logic Programming (2009)

Probabilistic logic learning (PLL), sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integration of probabilistic reasoning with first order logic representations and machine learning. It has received a lot of attention recently and a rich variety of different formalisms and learning techniques have been developed, which are now being applied to applications in network analysis, robotics, bio-informatics, intelligent agents, etc.This tutorial starts with an introduction to probabilistic representations and machine learning, and then continues with an overview of the state-of-the-art in probabilistic logic learning. We start from classical settings for logic learning (or inductive logic programming) namely learning from entailment, learning from interpretations, and learning from proofs, and show how they can be extended with probabilistic methods. While doing so, we review state-of-the-art probabilistic logic learning approaches and formalisms, such as PRISM, ICL, stochastic logic programs, Bayesian logic programs, CP-Logic and Markov logic.More detailed introductory overviews on probabilistic logic learning can be found in [1,2,3,4,5].
A Framework for Trustworthy Web Service Management
Authors: Shenghui Zhao, Guoxin Wu, Yuemin Li, Kun Yu
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

Web Services have widely employed in many application fields. The loosely coupled and distributed characters of Web Services also incur trustworthiness problem. Quality of service, reputation and security all can be taken into account for trustworthy Web Services. The three aspects affect each other. In this paper, we propose concept of trustworthy Web Services, and design an extend Web Service model that involve service rating, service discovery, service selection and service composition. The proposed framework can not only rate service whether is worthy of trustiness, but also help requestors search for trustworthy services. Moreover, from providers’ perspective, the framework will also provide requestor’s reputation and security to implement double-selection.
User identification by means of sketched stroke features
Authors: Brian David Eoff, Tracy Hammond
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

We present preliminary results of using physical features of a user's sketching style, such as pen tilt and pressure, to identify a user from their sketched strokes.
Comprehensive Bionic Neuron Unified Model
Authors: Jin Lv, Xiao-jun Yang, Chen Guo
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

Synthesize the 12 basic characteristics of the biologic neuron universally approbated by current biomedical and the engineering science field, and based on it put forward a novel unified framework model of artificial neuron -- Comprehensive Bionic Neuron which reflect more complete characteristics of the biologic neuron. Using this unified model to represent the various familiar neuron models and various learning algorithms, its validity is proved.
Flexural Mechanism Design Analysis for a New Piezoelectric Inchworm Actuator
Authors: Zhaocheng Zhang, Hong Hu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

This paper presents a new proof-of-concept design of inchworm-type piezoelectric actuator for precision positioner which avoids the tight tolerance and could be easily assembled. The proposed design uses two parallel linear guiding rods as a guide different from the previousconfigurations which adopted a guide channel or a movingshaft and the clamping clearance is adjustable. For theoptimum design analysis of the clamp and extension flexures, their design equations were developed. They facilitate quick iteration and convergence to an acceptable design based on the requirements. The accuracy of the equations was assessed by comparing them to finite element analysis (FEA) results. Future research will include prototype tests to validate both the analytical and finite element models.
An Improvement of Similarity Measurement Based on Semantic Units
Authors: Gang Wang, Zhong Shenghai, Ying Fengxia
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Because of some flaws of previous similarity measurement models, we extend the concept attributes and propose a method to measure the similarity based on the semantic unit. We use semantic units to express the concept meanings, and use the supporting degree to show the different contributions of different semantic units. By introducing the psychological knowledge of the relevance, the resemblance, and the non-symmetry of similarity, we measure the similarity of concepts successfully. We treat relation as particular concept, and we find a new method to measure the ontology similarity successfully based on semantic units. Finally, our experiments prove that our results are more reasonable, and it is better than other methods.
Aggregate Skyline: Analysis for Online Users
Authors: Shyam Antony, Ping Wu, Divyakant Agrawal, Amr El Abbadi
Venue: Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet (2009)

Aggregation is among the core functionalities of OLAP systems. Frequently, such queries are issued in decision support systems to identify interesting groups of data. In conventional settings, the queries take a long time to compute (hours!) and produce massive result-sets at varying degrees of aggregation. Providing real time analysis results to web users can enhance the utility of sites dealing with large amounts of data. However, to do so, needs succinct ways of capturing interesting analysis results rather than complex offline analysis. The result set should be presentable in a few web pages. Furthermore, such results should be computed quickly and updated in the background whenever possible. We propose skyline queries over aggregated data as a means of providing succinct but interesting analysis results. We support aggregation functions from a large class of monotonous functions that can be specified at runtime, thereby allowing user customization of the analysis. We explore a family of algorithms which try to consume only as many data records as are necessary to compute the skyline and identify an optimal algorithm within the family. We further refine the algorithm by taking into account system issues such as disk behavior which are often ignored but have strong impact on real system performance. Experimental results provide strong validation for the performance and progressive nature of the algorithm.
CGT Code-Based XML Data Compression Method
Authors: Sheng Zhang, Sha Chen, Yuping Liang
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

XML is a de-facto standard for exchanging and presenting information on the Web. However, XML data is also recognized as verbose since it heavily inflates the size of the data due to the repeated tags and structures. The data verbosity problem gives rise to many challenges of conventional query processing and data exchange. Compression techniques are the important way to overcome the verbosity problem. According to the features of XML document, we put forward a new XML data compression method called CGTXDC which uses XML Schema to construct XML document tree about the structure information of XML document and adopts CGT code to encode each tree node for maintaining the structure of the original XML document. CGTXDC requires only a single pass over the input XML document during the compression process and don't need to build the document tree in the memory. The experimental results show much better compression ratio than that of representative XML compression methods, such as Xpress and Xgrind.
Predicting User Behaviour to Facilitate Efficient Provision of Health Applications
Authors: Mohamad El-Hajj, Robert S. Hayward
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Practical analysis of user behavior patterns in social network and community software is one of the many application of data mining tools.Using data mining techniques, over 100 users of the Vividesk private online network ('desktop') for Canadian healthcare professionals was examined over a four year period for user behavior trends using decision trees (DTs) mining.Vividesk provides users with an online community of research and of practice, enabling clients to use web 2.0 and social networking principles to enhance their medical research and practice.Our interest rests primarily in usage patterns related to usergroups and classes of applications on these desktops. Some applications link to licensed information resources which can cost thousands of dollars per year to license. As a result, examining application usage data can help generate information on the relative cost effectiveness of the resources for which clients pay. This study presents an initial analysis of data by grouped resource applications as a means of determining whether deeper analysis is warranted.Data was warehoused and mined using a Microsoft Business intelligence tool (cube), using predetermined dimensions. By warehousing and mining desktop application usage through DTs,previously hidden usage patterns were uncovered. The DT experiments revealed various application usage patterns both within and between the desktops. Usergroups within each environment also demonstrated different access patterns at different times. Based on this analysis, further drilling down is warranted to uncover patterns of particular resource use.Exercises such as these will help predict future user behavior and facilitate the planning of desktop resource provision.
Single document summarization with document expansion
Authors: Xiaojun Wan, Jianwu Yang
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

Existing methods for single document summarization usually make use of only the information contained in the specified document. This paper proposes the technique of document expansion to provide more knowledge to help single document summarization. A specified document is expanded to a small document set by adding a few neighbor documents close to the document, and then the graph-ranking based algorithm is applied on the expanded document set for extracting sentences from the single document, by making use of both the within-document relationships between sentences of the specified document and the cross-document relationships between sentences of all documents in the document set. The experimental results on the DUC2002 dataset demonstrate the effectiveness of the proposed approach based on document expansion. The cross-document relationships between sentences in the expanded document set are validated to be very important for single document summarization.
On Computational Creativity, `Inventing' Theorem Proofs
Authors: Marta Fraňová, Yves Kodratoff
Venue: Proceedings of the 18th International Symposium on Foundations of Intelligent Systems (2009)

We provide a precise illustration of what can be the idea of "computational creativity", that is, the whole set of the methods by which a computer may simulate creativity. This paper is centered on the relationship between computational creativity and theorem proving. The basic tool for this kind of computational creativity is what we call an `asset generator' a specification of which is given in section 5, followed by a short description of our methodology for the generation of assets in theorem proving. In a sense, our `asset generation methodology' relies essentially on making explicit the logician's good sense while performing a recursion constructive proof. Our contribution is making explicit this good sense and making a systematic methodology of it.
Removal of Phosphate from Aqueous Solution Using Iron-Oxide-Coated Sand Filter Media: Batch Studies
Authors: Lu Jianbo, Sun Liping, Zhao Xinhua, Lu Bin, Li Yinlei, Zhang Lei
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Iron-oxide-coated sand (IOCS) filter media was investigated to remove phosphate from aqueous solutions in batch experiments. Adsorbability of phosphate by IOCS-1 and IOCS-2 (prepared by different coating process) was compared in order to gain an available coating process to prepare modified sand filter media for effective removal of phosphate. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis were used to investigate the surface properties of the coated layer. An energy dispersive X-ray (EDAX) analysis was also used for characterizing phosphate adsorption on IOCS surface. Effects of initial pH, contact time and dose of IOCS on the removal of phosphate were studied. The results showed that the removal efficiency of phosphate by IOCS-1 was greater than IOCS-2, thus, further experiments was carried out using IOCS-1. The adsorption of phosphate by IOCS-1 can be well described by Langmuir, Freundlich and Temkin isotherm at various temperatures. For IOCS-1, the adsorption followed the pseudo-second-order reaction kinetics model. Moreover, the phosphate adsorbed IOCS-1 could be regenerated by alkali solution. Results of this study can provide an effective technology based on adsorption/filtration using IOCS filter media for phosphate removal from water and wastewater.
CommunityCommands: command recommendations for software applications
Authors: Justin Matejka, Wei Li, Tovi Grossman, George Fitzmaurice
Venue: Proceedings of the 22nd annual ACM symposium on User interface software and technology (2009)

We explore the use of modern recommender system technology to address the problem of learning software applications. Before describing our new command recommender system, we first define relevant design considerations. We then discuss a 3 month user study we conducted with professional users to evaluate our algorithms which generated customized recommendations for each user. Analysis shows that our item-based collaborative filtering algorithm generates 2.1 times as many good suggestions as existing techniques. In addition we present a prototype user interface to ambiently present command recommendations to users, which has received promising initial user feedback.
Modern Approach for Building of Multi-Agent Systems
Authors: Lukasz Chomatek, Aneta Poniszewska-Marańda
Venue: Proceedings of the 18th International Symposium on Foundations of Intelligent Systems (2009)

Different approaches for distributed programming in modern hardware architectures allows the developers to build the efficient solutions of complicated technical and information problems. The technologies such as Web Services allow the applications to create a cross-platform for data exchange. The multi-agent systems, where a communication between the agents is essential for proper work of such applications can be developed using the technology of Service Oriented Architecture (SOA). The presented article presents how to apply the modern programming technologies, design patterns and software architectures to building standards of multi-agent systems.
Particle Tracking Velocimetry Using the Genetic Algorithm
Authors: K. Ohmi, S. P. Panday
Venue: Journal of Visualization (2009)

A new concept genetic algorithm (GA) has been implemented and tested for the use in the 2-D and 3-D Particle Tracking Velocimetry (PTV). The algorithm is applicable to particle images with larger (greater than 2000) number of particles without losing the excellent accuracy in the particle matching results. This is mainly due to a new fitness function as well as unique genetic operations devised especially for the purpose of particle matching problem. The new fitness function is based on the relaxation of movement of a group of particles and is particularly suited for an increased density of particle images. The unique genetic operations give rise to the concentration of more fit genes in the forward part of the gene strings where the crossover and mutation processes are suppressed. The new algorithm also profits from the new genetic encoding scheme which can deal with the loss-of-pair particles (i.e., those particles which exist in one frame but do not have their matching pair in the other frame), a typical problem in the real image particle tracking velocimetry. In the present study, the new method is tested with 2-D and 3-D synthetic as well as real particle images with a large number of particles.
Adaptive Color Quantization Based on Self-Growing Network
Authors: Li Yurong, Fu Hongguang, Shuai Qinghong
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Color quantization is an important technology in visual information processing. A new algorithm for color quantization is proposed which automatically estimates number of the representative colors to efficiently represent an arbitrary image. It is based on the growing mechanism of Growing When Required neural network and a novel method to visit uniformly pixels in an image. A number of criteria are introduced that have an effect on controlling of the number and topology of neurons in the output layer. The experiments demonstrate that the developed method can automatically define the number of representative colors while keeping distortion to an acceptable level. It is also shown that the algorithm outperforms the popular ones in terms of color distortion.
DAUTI: automated universal traffic introspector
Authors: Jonathan Wellons, John Wisneski
Venue: Proceedings of the 2007 International Lisp Conference (2007)

This paper introduces DAUTI, a network traffic simulator, applies it to a simulation research problem, and demonstrates the ease-of-use and applicability of functional languages to network simulation. DAUTI is an Open-Source, fully configurable, rapidly advancing, and efficient Scheme program that can be used to simulate Cluster load and job delay on any size of network, and provide basic statistics and analysis. In this paper, we use DAUTI to compute the relative performance of load distribution algorithms on a two-stage pipeline with heterogeneous cluster sizes. Specific applications include web servers, and industrial, research and financial batch processing. The choice of the Scheme language (a relative of Lisp) presented numerous opportunities to quickly produce compact and efficient code. This language selection incurred no obstacles.
An Improved Immune Clone Selection Algorithm for Multi Robot Task Scheduling
Authors: WenJie Tian, JiCheng Liu
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

The main aim of this study is managing robot tasks to minimize the deviation between the resource requirements and stated desirable levels. An improved adaptive immune clone selection algorithm (ICSA) is proposed. In this study resource leveling methods are used to solve task scheduling problems in autonomous multi robot group. Robots are considered as resources. The experimental results show that proposed methods have better performances such as good and fast global convergence, strong robustness, insensitive to initial values, simplicity of implementation.
SimpleNLG: a realisation engine for practical applications
Authors: Albert Gatt, Ehud Reiter
Venue: Proceedings of the 12th European Workshop on Natural Language Generation (2009)

This paper describes SimpleNLG, a realisation engine for English which aims to provide simple and robust interfaces to generate syntactic structures and linearise them. The library is also flexible in allowing the use of mixed (canned and non-canned) representations.
A Max-plus Network Calculus
Authors: Baohua Fan, Heying Zhang, Wenhua Dou
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Network calculus is a theory of deterministic queuing systems, which is based on min-plus algebra. This paper shows a novel network calculus that based on other dioids, that is max-plus algebra. Performance bounds can be obtained by max-plus network calculus. We also do a theoretical research on max-plus network calculus by using residuation theory. Finally, we analyze Guaranteed Rate server as an example to illustrate the efficiency of max-plus based network calculus in performance analysis of network calculus.
Computational Performance of a Parallelized Three-Dimensional High-Order Spectral Element Toolbox
Authors: Christoph Bosshard, Roland Bouffanais, Christian Clémençon, Michel O. Deville, Nicolas Fiétier, Ralf Gruber, Sohrab Kehtari, Vincent Keller, Jonas Latt
Venue: Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies (2009)

In this paper, a comprehensive performance review of an MPI-based high-order three-dimensional spectral element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the parallel efficiency. The performance evaluation is analyzed with help of a time prediction model based on a parameterization of the application and the hardware resources. A tailor-made CFD computation benchmark case is introduced and used to carry out this review, stressing the particular interest for clusters with up to 8192 cores. Some problems in the parallel implementation have been detected and corrected. The theoretical complexities with respect to the number of elements, to the polynomial degree, and to communication needs are correctly reproduced. It is concluded that this type of code has a nearly perfect speed up on machines with thousands of cores, and is ready to make the step to next-generation petaflop machines.
Research on Wavelet Chaotic Neural Network with Disturbance of Wavelet Function
Authors: Yao-qun Xu, Xin Zheng, Hai-tao Xin
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

This paper is concerned with the improvement of its internal state for wavelet chaotic neural network by introducing the disturbance of wavelet function. A new type of wavelet chaotic neural network model with disturbance of wavelet function is presented. Then it is applied in the function and combinatorial optimization problems. The simulation results show that the chaotic neural network with disturbance of wavelet function can solve function and combinatorial optimization problems effectively, if the disturbance coefficient is controlled properly. Therefore the very strong robustness and anti-interference ability are embodied in wavelet chaotic neural network.
Storage Performance Optimization Based on ARIMA
Authors: Leijie Zeng, Yanyuan Zhang, Xiaonan Zhao
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

This paper analyzes the potential causes of the performance bottleneck in I/O access paths of storage architecture and proposes a predictive approach based on feedforward to optimize the I/O performance of storage subsystems effectively, which uses a time series analysis method based on ARIMA to build the predictive and monitor model of the performance. This approach can improve the availability of the storage subsystem effectively and decrease TCO by decreasing the possibility of I/O bottlenecks.