ppxscal/embedding_network huggingface dataset:
Biomass Production, Chlorophll A and Carotenoid Contents of Spirulina Maxima in Mixed Culture of Lactose
Authors: Jiang Zheng
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Pollution of the wastewater is a problem for the sustainable development of aquaculture and food industry. Although many treatments have been used in the field, the expensive cost limited their wide application. Microalgae such as Spirulina can utilize the organic substrates of the wastewater as its C or N sources, so it is feasible to purify the wastewater by the microalgae. On another hand, microalgae are a good biomass energy that can be used to produce biofuels. Therefore, culturing microalgae in wastewater and producing microalgae biomass are probable a good method to deal with the problem. The present paper studied and discussed the effects of lactose on its biomass nenergy, chlorophyll a and carenoid contents. The results showed that the biomass of S.maxima could increase significantly after addition of lactose. The optimal lactose concentration was 15g/L and at that concentration S.maxima can grow best, but chlorophyll a and carotenoid contents decrease remarkably. Compared with glucose and acetate, S.maxima had higher tolerance, which would be used for the relief of inhibitory effects caused by over carbon sources.
IEEE 802.16 Wireless Mesh Networks Capacity Estimation Using Collision Domains
Authors: Rafal Krenz
Venue: Proceedings of the 2009 Second International Conference on Advances in Mesh Networks (2009)

Wireless Mesh Networks (WMN) are considered an attractive alternative to the traditional wired backbone networks for broadband Internet access. However, their capacity is limited due to the nature of the radio channel, which must be shared by the nodes forwarding the traffic from and to the gateway. Therefore, estimating the capacity of WMNs is an important question. The capacity analysis proposed for ad hoc networks can not be directly applied to WMN due to some fundamental differences, e.g. a different traffic pattern and node density. The main contribution of this work is the application of collision domains concept to the 802.16 based WMNs. We consider a simple chain topology but the method can be extended to any arbitrary topology and the real world impairments (interference, fading, etc.) can be easily incorporated in the analysis. The presented results may have important implications for 802.16 mesh networks planning.
Using the GEMS system for cancer diagnosis and biomarker discovery from microarray gene expression data
Authors: Alexander Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 4 (2005)

We will demonstrate the GEMS system for automated development and evaluation of high-quality cancer diagnostic models and biomarker discovery from microarray gene expression data. The development of GEMS was informed by the results of an extensive algorithmic evaluation using 11 microarray datasets. The system was further evaluated in two cross-dataset applications and using 5 microarray datasets. The performance of models produced by GEMS is comparable or better than the results obtained by human analysts, and these models generalize well to independent samples in cross-dataset applications. The system is freely available for download from http://www.gems-system.org for noncommercial use.
A Low-Storage-Consumption XML Labeling Method for Efficient Structural Information Extraction
Authors: Wenxin Liang, Akihiro Takahashi, Haruo Yokota
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

Recently, labeling methods to extract and reconstruct the structural information of XML data, which are important for many applications such as XPath query and keyword search, are becoming more attractive. To achieve efficient structural information extraction, in this paper we propose C-DO-VLEI code, a novel update-friendly bit-vector encoding scheme, based on register-length bit operations combining with the properties of Dewey Order numbers, which cannot be implemented in other relevant existing schemes such as ORDPATH. Meanwhile, the proposed method also achieves lower storage consumption because it does not require either prefix schema or any reserved codes for node insertion. We performed experiments to evaluate and compare the performance and storage consumption of the proposed method with those of the ORDPATH method. Experimental results show that the execution times for extracting depth information and parent node labels using the C-DO-VLEI code are about 25% and 15% less, respectively, and the average label size using the C-DO-VLEI code is about 24% smaller, comparing with ORDPATH.
Class model adaptation for speech summarisation
Authors: Pierre Chatain, Edward W. D. Whittaker, Joanna Mrozinski, Sadaoki Furui
Venue: Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX (2006)

The performance of automatic speech summarisation has been improved in previous experiments by using linguistic model adaptation. We extend such adaptation to the use of class models, whose robustness further improves summarisation performance on a wider variety of objective evaluation metrics such as ROUGE-2 and ROUGE-SU4 used in the text summarisation literature. Summaries made from automatic speech recogniser transcriptions benefit from relative improvements ranging from 6.0% to 22.2% on all investigated metrics.
Design and Implementation of Wireless Sensor Network Gateway Based on Environmental Monitoring
Authors: Dun-fan Ye, Liang-liang Min, Wei Wang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

In this paper, we propose a gateway system for wireless sensor network based on environmental monitoring. Resource sharing and long-distance accessing are important issues for application of wireless sensor network and environmental monitoring. It’s necessary to connect wireless sensor network to external network which makes the administrator could access data duly and expediently from long-distance. Especially users can avoid the awful situation when the environment is terrible. A gateway which is high performance, high reliability, low-power and expandable is designed to connect WSN with external network. Gateway accepts data collected by wireless sensor network and then stores the data in an embedded database SQLite3. And users can manage the data via a website from long-distance or applications in console terminal.
A hybrid technique for the periodicity characterization of genomic sequence data
Authors: Julien Epps
Venue: EURASIP Journal on Bioinformatics and Systems Biology (2009)

Many studies of biological sequence data have examined sequence structure in terms of periodicity, and various methods for measuring periodicity have been suggested for this purpose. This paper compares two such methods, autocorrelation and the Fourier transform, using synthetic periodic sequences, and explains the differences in periodicity estimates produced by each. A hybrid autocorrelation--integer period discrete Fourier transform is proposed that combines the advantages of both techniques. Collectively, this representation and a recently proposed variant on the discrete Fourier transform offer alternatives to the widely used autocorrelation for the periodicity characterization of sequence data. Finally, these methods are compared for various tetramers of interest in C. elegans chromosome I.
Effective Communication and the Prevention of Psychological Contract Breach
Authors: Shao Jing, Cao Yake
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

The psychological contract exists at all times in organizational management, the effect of which plays a vital role. Psychological contract breach not only has a deleterious impact on the employees who experience them, but may also have negative consequences for organizational effectiveness. This article will divide the psychological contract into the stage of establishment, adjustment and discrepancy according to the dynamic characteristic of the psychological contract. In order to prevent the breach of psychological contract which would bring the loss to the company, the effective communication with employees and dynamic management at different stages are much needed. Organization should use effective communication skills to strengthen the communication, interaction with employees and dynamic implement of management according to the characteristics of psychological contract in different stages. Therefore, put the occurrence of breach of psychological contract to a minimum extent and make psychological contract between organization and employees positive interaction comes true.
HMF: High-available Message-passing Framework for Cluster File System
Authors: Dong Yang, Zhuan Chen, Rongfeng Tang, Jin Xiong, Dan Meng
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

In large-scale cluster systems, the failure rate of network connection is non-negligibly high. A cluster file system must have the ability to handle network failures in order to provide high-available data accesses service. Traditionally, network failure handling is only guaranteed by network protocol, or implemented within the file system semantic layer. We present the high-available message-passing framework which is called HMF. Based on the operation hierarchy in cluster file system, HMF guarantees the availability of each pair of network transmissions and their interaction with the file system sub-operations. It separates the network fault-tolerance design from the file system and keeps a simple interface between them. HMF could handle a lot of network failures internally, which greatly simplifies the implementation of file system semantic layer. Performance results show that HMF can increase the availability of message passing and reduce the cost of recovery from network failures. When there are two network channels, HMF also improves aggregate I/O bandwidth by 80% in normal condition while the performance degradation due to recovery is below 10%.
Effect of Sensor Resolution on the Accuracy of Positioning Stage
Authors: Teng Li, Yanjie Liu, Lining Sun
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

Sensor as one of the key parts in positioning stage plays an important role in influencing performance of the system. In this paper, for the typical positioning stage, effects of sensor resolution on the positioning accuracy are discussed. The describing function method which is more formula analysis and phase plane method which is more intuitive graphic description are used separately to analyze the problem. We conclude that with the increase of sensor resolution the accuracy of positioning stage is improved, but when the resolution is up to an extent, the effects of it on accuracy are unobvious. This would guide the selection of sensor in order to harmonize the performance of the whole system.
A Data Acquisition and 2-D Flow Measuring Technology in Agricultural Spray Field Based on High Speed Image Processing
Authors: Jun Lu, Pingping Li
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

In order to solve the faults in usual measurements of droplet distribution and motion in agricultural spraying field, a new method is given for the analysis of droplets characteristics and motion with PDIA (Particle / Droplet Image Analysis) and digital image processing technique. During the analysis of the size of droplet and the velocity, images of droplets in spray field has been captured by using high-speed imager. The parameter of droplet such as size, perimeter, equivalent diameter, Shape factor and position etc, have been calculated with digital image processing technology. The trace of droplet in different frames has been tracked with the method, which is based on flag tracking and droplet neighborhood matching probability technique. The results showed this measurement can both realize the motion trace of droplet in different image frames and analyses the velocity of droplet. This measuring technique can detect the droplet parameters quickly and accurately for agricultural sprays, and provide the basic way for research on 2-D flow visualisation image analysis in pesticide application.
Dialogue management in the Mercury flight reservation system
Authors: Stephanie Seneff, Joseph Polifroni
Venue: Proceedings of the ANLP-NAACL 2000 Workshop on Conversational Systems (2000)

This paper describes the dialogue module of the Mercury system which has been under development over the past year or two. Mercury provides telephone access to an on-line flight database, and allows users to plan and price itineraries between major airports worldwide. The main focus of this paper is the dialogue control strategy, which is based on a set of ordered rules as a mechanism to manage complex dialogue interactions. The paper also describes the interactions between the dialogue component and the other servers of the system, mediated via a central hub. We evaluated the system on 49 dialogues from users booking real flights, and report on a number of quantitative measures of the dialogue interaction.
Supporting the adaptation of texts for poor literacy readers: a text simplification editor for Brazilian Portuguese
Authors: Arnaldo Candido,  Jr., Erick Maziero, Caroline Gasperin, Thiago A. S. Pardo, Lucia Specia, Sandra M. Aluisio
Venue: Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications (2009)

In this paper we investigate the task of text simplification for Brazilian Portuguese. Our purpose is three-fold: to introduce a simplification tool for such language and its underlying development methodology, to present an on-line authoring system of simplified text based on the previous tool, and finally to discuss the potentialities of such technology for education. The resources and tools we present are new for Portuguese and innovative in many aspects with respect to previous initiatives for other languages.
Hessian orders and multinormal distributions
Authors: Alessandro Arlotto, Marco Scarsini
Venue: Journal of Multivariate Analysis (2009)

Several well known integral stochastic orders (like the convex order, the supermodular order, etc.) can be defined in terms of the Hessian matrix of a class of functions. Here we consider a generic Hessian order, i.e., an integral stochastic order defined through a convex cone H of Hessian matrices, and we prove that if two random vectors are ordered by the Hessian order, then their means are equal and the difference of their covariance matrices belongs to the dual of H. Then we show that the same conditions are also sufficient for multinormal random vectors. We study several particular cases of this general result.
An Empirical Approach for the Assessment of Scheduling Risk in a Large Globally Distributed Industrial Software Project
Authors: Alberto Avritzer, Adailton Lima
Venue: Proceedings of the 2009 Fourth IEEE International Conference on Global Software Engineering (2009)

We describe an empirical approach for the assessment of the scheduling risk in a large globally distributed industrial software project.We analyzed two and half years of project data and we identified some factors that are likely to impact team productivity and that could affect the team’s ability to meet its schedule objective. We built an analytical model to capture team’s productivity variability, which can be used to approximate the total time required to complete the project.Our approach is designed to be used by project management groups to perform risk assessment early in the software development process.
Causality Discovery with Additive Disturbances: An Information-Theoretical Perspective
Authors: Kun Zhang, Aapo Hyvärinen
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

We consider causally sufficient acyclic causal models in which the relationship among the variables is nonlinear while disturbances have linear effects, and show that three principles, namely, the causal Markov condition (together with the independence between each disturbance and the corresponding parents), minimum disturbance entropy, and mutual independence of the disturbances, are equivalent. This motivates new and more efficient methods for some causal discovery problems. In particular, we propose to use multichannel blind deconvolution, an extension of independent component analysis, to do Granger causality analysis with instantaneous effects. This approach gives more accurate estimates of the parameters and can easily incorporate sparsity constraints. For additive disturbance-based nonlinear causal discovery, we first make use of the conditional independence relationships to obtain the equivalence class; undetermined causal directions are then found by nonlinear regression and pairwise independence tests. This avoids the brute-force search and greatly reduces the computational load.
Trading Strategy in Foreign Exchange Market Using Reinforcement Learning Hierarchical Neuro-Fuzzy Systems
Authors: Marcelo F. Corrêa, Marley Vellasco, Karla Figueiredo, Pedro Vellasco
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

This paper evaluates the performance of the new hybrid neuro-fuzzy model, Reinforcement Learning Hierarchical Neuro-Fuzzy System (RL-HNFP), in a trade decision application. The proposed model was tested with the Euro/Yen negotiated in Foreign Exchange Market. The main objective of the trading system is to optimize the resource allocation, in order to determine the best investment strategy. The performance of the RL-HNFP was compared with different benchmark models. The results showed that the system was able to detect long term strategies, obtaining more profitability with smaller number of trades.
Change (Detection) You Can Believe in: Finding Distributional Shifts in Data Streams
Authors: Tamraparni Dasu, Shankar Krishnan, Dongyu Lin, Suresh Venkatasubramanian, Kevin Yi
Venue: Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII (2009)

Data streams are dynamic, with frequent distributional changes. In this paper, we propose a statistical approach to detecting distributional shifts in multi-dimensional data streams. We use relative entropy, also known as the Kullback-Leibler distance, to measure the statistical distance between two distributions. In the context of a multi-dimensional data stream, the distributions are generated by data from two sliding windows. We maintain a sample of the data from the stream inside the windows to build the distributions.Our algorithm is streaming, nonparametric, and requires no distributional or model assumptions. It employs the statistical theory of hypothesis testing and bootstrapping to determine whether the distributions are statistically different. We provide a full suite of experiments on synthetic data to validate the method and demonstrate its effectiveness on data from real-life applications.
Getting Online but Still Living Offline: The Complex Relationship of Technology Adoption and In-person Social Networks
Authors: Cynthia Putnam, Beth Kolko
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Previous research in Kyrgyzstan has demonstrated the importance of close social networks as avenues for gathering and sharing information, assistance and goods in the country. However, the relationship between technology use and social network use has not been investigated; understanding this relationship is important when considering the design of technology applications that support existing social networks. Contrary to Robert Putnam’s hypothesis that technologies have an "individualizing" force on populations, we have found that social network patterns do not appear to be negatively associated with higher technology use. In fact, the higher the level of technology use, the more face-to-face social networks were used for multiple types of information seeking.
A Novel Semantic Discovery Method Using Transaction Requirements in Database Reverse Engineering
Authors: Fanwei Zhu, Minghui Wu, Jia Lv, Jing Ying
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Existing database reverse engineering approaches mainly analyze the database schema, especially the key constraints, to discover the relationships between relations and attributes. However these methods are only effective for direct semantics discovery, while large part of inferred semantics is still missing. This paper proposes a transaction-oriented semantic discovery method which analyzes the transaction requirements supported by a database to explore hidden semantics. Our method relaxes the constraints on normalization of database design to suit for wide range applications, and is effective for discovering transitive relationships, general-specific relationships and master-detail relationships.
Extending continuous time Bayesian networks
Authors: Karthik Gopalratnam, Henry Kautz, Daniel S. Weld
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

Continuous-time Bayesian networks (CTBNs) (Nodelman, Shelton, & Koller 2002; 2003), are an elegant modeling language for structured stochastic processes that evolve over continuous time. The CTBN framework is based on homogeneous Markov processes, and defines two distributions with respect to each local variable in the system, given its parents: an exponential distribution over when the variable transitions, and a multinomial over what is the next value. In this paper, we present two extensions to the framework that make it more useful in modeling practical applications. The first extension models arbitrary transition time distributions using Erlang-Coxian approximations, while maintaining tractable learning. We show how the censored data problem arises in learning the distribution, and present a solution based on expectation-maximization initialized by the Kaplan-Meier estimate. The second extension is a general method for reasoning about negative evidence, by introducing updates that assert no observable events occur over an interval of time. Such updates were not defined in the original CTBN framework, and we show that their inclusion can significantly improve the accuracy of filtering and prediction. We illustrate and evaluate these extensions in two real-world domains, email use and GPS traces of a person traveling about a city.
An Adaptive Active Vibration and Noise Control System with Online Secondary Path Modeling
Authors: Guo Y. Jin, Hongtian Zhang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

A new active vibration and noise control system with on-line secondary path modeling is proposed in this paper. The present system is able to greatly reduce the mutual disturbances between the control process and the modeling process, leading to an improvement in the overall performance of the active control system. Computer simulation and experiments for active vibration control are conducted. The results demonstrate the superior online modeling ability of secondary path and control performance.