ppxscal/embedding_network huggingface dataset:
Foma: a finite-state compiler and library
Authors: Mans Hulden
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Demonstrations Session (2009)

Foma is a compiler, programming language, and C library for constructing finite-state automata and transducers for various uses. It has specific support for many natural language processing applications such as producing morphological and phonological analyzers. Foma is largely compatible with the Xerox/PARC finite-state toolkit. It also embraces Unicode fully and supports various different formats for specifying regular expressions: the Xerox/PARC format, a Perl-like format, and a mathematical format that takes advantage of the 'Mathematical Operators' Unicode block.
Production Protection to Copy(right) Protection: From the 10NES to DVDs
Authors: Casey O'Donnell
Venue: IEEE Annals of the History of Computing (2009)

Much of what modern digital rights management (DRM) systems attempt to accomplish was actually forcefully implemented on videogame consoles beginning with the Nintendo Entertainment System (NES) and SEGA Genesis system in the early 1980s. Examining the links between modern DRM mechanisms and these early production and copy protection systems can help contextualize the future of media production and access.
Prototype details of the smartphone-based researcher's companion software (RCS)
Authors: Muhanna Muhanna, Brian Tackitt, Sergiu Dascalu
Venue: Journal of Computational Methods in Sciences and Engineering (2009)

Smartphones are handheld devices that include most or all the functionality of traditional personal digital assistants (PDAs) with the additional capability of serving as cell phones. One of the main issues with smartphones is a lack of software programs that meet the needs of certain tasks or application domains. The primary objective of the work presented in this paper has been to create a Researcher's Companion Software that uses the new smartphone technology and incorporates functions and features that meet the specific needs of researchers in various domains. The second objective of our work has been to place a strong emphasis on the software's ease of use and user interaction capabilities, such that researchers from various fields (e.g., engineering, environment studies, social sciences, medicine, arts, education, etc.) can use it almost immediately, without having to go through a lengthy learning process. The Researcher's Companion Software presented in this paper operates on Google's new smartphone platform Android. The RCS enables users to manage references, collaborators, notes, appointments, and checklists, and also provides some advanced capabilities. The key benefit of the RCS is its mobility, which allows researchers to keep track of their research-related information regardless of location, thus significantly improving their overall work productivity.
Salivary Cortisol as a New Biomarker for a Mild Mental Workload
Authors: Shusaku Nomura, Tota Mizuno, Akio Nozawa, Hirotoshi Asano, Hideto Ide
Venue: Proceedings of the 2009 International Conference on Biometrics and Kansei Engineering (2009)

Recent psycho-physiological studies have revealed close relationships between human mental stresses and secretion of hormonal and immunological substances. However, a precise elaboration of fluctuations in the secretion of these biomarkers in the time series against stress; especially against a rather mild stressful task is not yet clearly illuminated. In this study, we used the cortisol, a major glucocorticoid, as a biomarker of mental stress for 1) illustrating the precise stress-response in the time series, and 2) investigating a congruity of cortisol as the biomarker for a mild mental workload. Ten male university students were inscribed to conduct a simple, easy, and monotonous mental arithmetic task for about an hour with intermissions, so as to emulate a mild mental workload. As a result, salivary cortisol depicted an accumulative increase during mild mental workloads, while no marked difference was obtained in the heart rate and its variability. It suggests the slow and long-lasting properties in the stress-response of the cortisol unlike as in autonomous nervous system indices, and therefore plausibly demonstrates the possible candidacy of cortisol as a biomarker for a mild mental load.
Analysis of the projected coupled cluster method in electronic structure calculation
Authors: Reinhold Schneider
Venue: Numerische Mathematik (2009)

The electronic Schr&#x00f6;dinger equation plays a fundamental role in molcular physics. It describes the stationary nonrelativistic behaviour of an quantum mechanical N electron system in the electric field generated by the nuclei. The (Projected) Coupled Cluster Method has been developed for the numerical computation of the ground state energy and wave function. It provides a powerful tool for high accuracy electronic structure calculations. The present paper aims to provide a rigorous analytical treatment and convergence analysis of this method. If the discrete Hartree Fock solution is sufficiently good, the quasi-optimal convergence of the projected coupled cluster solution to the full CI solution is shown. Under reasonable assumptions also the convergence to the exact wave function can be shown in the Sobolev H 1-norm. The error of the ground state energy computation is estimated by an Aubin Nitsche type approach. Although the Projected Coupled Cluster method is nonvariational it shares advantages with the Galerkin or CI method. In addition it provides size consistency, which is considered as a fundamental property in many particle quantum mechanics.
A DNA-Based Algorithm for the Solution of One-in-Three 3-SAT Problem
Authors: Nung-Yue Shi, Chih-Ping Chu
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Abstract-Satisfiability problem is given a Boolean formula, and decide if a satisfying truth assignment exists.K-SAT means that each clause has exactly k literals. One-In-Three (1IN3) 3-SAT problem is defined by Garey and Johnson in 1979 as follows: There is a set V of variables and a collection C of clauses over V such that each clause has 3 literals. And the question is : Is there a truth assignment for V such that each clause in C has exactly one true literal?In this paper, we will use molecular solution to find all true assignment (3 SAT problem) and find One-In-Three (1IN3) solutions on DNA-based Supercomputing. The complexity of the presented DNA-based solution is discussed in section three. And the simulated experiment is applied to verify correction of the proposed DNA-based algorithm for solving the One-In-Three 3-SAT problem in section four.
The role of lexical resources in CJK natural language processing
Authors: Jack Halpern
Venue: Proceedings of the Workshop on Multilingual Language Resources and Interoperability (2006)

The role of lexical resources is often understated in NLP research. The complexity of Chinese, Japanese and Korean (CJK) poses special challenges to developers of NLP tools, especially in the area of word segmentation (WS), information retrieval (IR), named entity extraction (NER), and machine translation (MT). These difficulties are exacerbated by the lack of comprehensive lexical resources, especially for proper nouns, and the lack of a standardized orthography, especially in Japanese. This paper summarizes some of the major linguistic issues in the development NLP applications that are dependent on lexical resources, and discusses the central role such resources should play in enhancing the accuracy of NLP tools.
I2R: three systems for word sense discrimination, Chinese word sense disambiguation, and English word sense disambiguation
Authors: Zheng-Yu Niu, Dong-Hong Ji, Chew-Lim Tan
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

This paper describes the implementation of our three systems at SemEval-2007, for task 2 (word sense discrimination), task 5 (Chinese word sense disambiguation), and the first subtask in task 17 (English word sense disambiguation). For task 2, we applied a cluster validation method to estimate the number of senses of a target word in untagged data, and then grouped the instances of this target word into the estimated number of clusters. For both task 5 and task 17, We used the label propagation algorithm as the classifier for sense disambiguation. Our system at task 2 achieved 63.9% F-score under unsupervised evaluation, and 71.9% supervised recall with supervised evaluation. For task 5, our system obtained 71.2% micro-average precision and 74.7% macro-average precision. For the lexical sample subtask for task 17, our system achieved 86.4% coarse-grained precision and recall.
Conquest: an open-source dialog system for conferences
Authors: Dan Bohus, Sergio Grau Puerto, David Huggins-Daines, Venkatesh Keri, Gopala Krishna, Rohit Kumar, Antoine Raux, Stefanie Tomko
Venue: Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers on XX (2007)

We describe ConQuest, an open-source, reusable spoken dialog system that provides technical program information during conferences. The system uses a transparent, modular and open infrastructure, and aims to enable applied research in spoken language interfaces. The conference domain is a good platform for applied research since it permits periodical redeployments and evaluations with a real user-base. In this paper, we describe the system's functionality, overall architecture, and we discuss two initial deployments.
Virtual Door-Based Coverage Path Planning for Mobile Robot
Authors: Hyun Myung, Hae-Min Jeon, Woo-Yeon Jeong, Seok-Won Bang
Venue: Proceedings of the FIRA RoboWorld Congress 2009 on Advances in Robotics (2009)

This paper presents a novel coverage path planning method in indoor environment for a mobile robot such as cleaning robot. Overall region is divided into several sub-regions based on the virtually extracted doors. The algorithm is inspired from the usual way of dividing an indoor environment into sub-regions, i.e., rooms based on the identification of doors. The virtual door algorithm extracts the virtual doors by combining a Generalized Voronoi Diagram (GVD) and a configuration space eroded by the half of the door size. The region to region cleaning algorithm is also proposed based on the closing and opening operations of virtual doors. The performance of the proposed algorithm has been tested on various real indoor environments using a commercially available cleaning robot.
The Process of Engineering of Security of Information Systems (ESIS): The Formalism of Business Processes
Authors: Wilson Goudalo, Dominique Seret
Venue: Proceedings of the 2009 Third International Conference on Emerging Security Information, Systems and Technologies (2009)

Companies and organizations are faced with quite a tough competition and increasing regulatory and legal constraints. Therefore, the use of security risk management is evolving and becoming more and more important in companies and organizations. We define Engineering of security of information systems as a process whose aim is to guarantee the global security of information systems, in their eco-system in order to meet the stakes of companies. After our article focused on the encapsulation of Security know-how into UML profiles, we focus this work on the presentation of the Process of Engineering of Security into the formalism of Business Processes. The main idea is to succeed the adherence, of all stakeholders of the enterprise, into the security problem. To meet these pragmatic and actual needs of companies and organizations, we would suggest an approach to engineering of security, firstly, based on the standards and good practices of security and, secondly, inspired from the best practices and feedback of advances in the engineering of information systems. This paper shows the feasibility of mapping the process of engineering of Security of Information Systems into the formalism of business process, and presents the concepts of engineering of Security of Information Systems using the foundations and models of Information Systems Engineering.
Improved Fractional Fourier Transform Based Receiver for Spatial Multiplexed MIMO Antenna Systems
Authors: Rajesh Khanna, Rajiv Saxena
Venue: Wireless Personal Communications: An International Journal (2009)

In this work the performance of a Fractional Fourier transform (FrFT) based Minimum Mean Squared Error receiver for MIMO systems with space time processing over Rayleigh faded channels is presented. The proposed receiver called Optimum FrFT based MIMO receiver (OFMR) shows improved performance outperforming the simple MMSE receiver in Rayleigh faded channel.
Semi-supervised learning for blog classification
Authors: Daisuke Ikeda, Hiroya Takamura, Manabu Okumura
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

Blog classification (e.g., identifying bloggers' gender or age) is one of the most interesting current problems in blog analysis. Although this problem is usually solved by applying supervised learning techniques, the large labeled dataset required for training is not always available. In contrast, unlabeled blogs can easily be collected from the web. Therefore, a semi-supervised learning method for blog classification, effectively using unlabeled data, is proposed. In this method, entries from the same blog are assumed to have the same characteristics. With this assumption, the proposed method captures the characteristics of each blog, such as writing style and topic, and uses these characteristics to improve the classification accuracy.
Point process models for event-based speech recognition
Authors: Aren Jansen, Partha Niyogi
Venue: Speech Communication (2009)

Several strands of research in the fields of linguistics, speech perception, and neuroethology suggest that modelling the temporal dynamics of an acoustic event landmark-based representation is a scientifically plausible approach to the automatic speech recognition (ASR) problem. Adopting a point process representation of the speech signal opens up ASR to a large class of statistical models that have seen wide application in the neuroscience community. In this paper, we formulate several point process models for application to speech recognition, designed to operate on sparse detector-based representations of the speech signal. We find that even with a noisy and extremely sparse phone-based point process representation, obstruent phones can be decoded at accuracy levels comparable to a basic hidden Markov model baseline and with improved robustness. We conclude by outlining various avenues for future development of our methodology.
OFFD: Optimal Flexible Frequency Discretization for Naïve Bayes Classification
Authors: Song Wang, Fan Min, Zhihai Wang, Tianyu Cao
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

Incremental Flexible Frequency Discretization (IFFD) is a recently proposed discretization approach for Naïve Bayes (NB). IFFD performs satisfactory by setting the minimal interval frequency for discretized intervals as a fixed number. In this paper, we first argue that this setting cannot guarantee optimal classification performance in terms of classification error. We observed empirically that an optimal minimal interval frequency existed for each dataset. We thus proposed a sequential search and wrapper based incremental discretization method for NB: named Optimal Flexible Frequency Discretization (OFFD). Experiments were conducted on 17 datasets from UCI machine learning repository and performance was compared between NB trained on the data discretized by OFFD, IFFD, PKID, and FFD respectively. Results show that OFFD works better than these alternatives for NB. Experiments between NB discretized on the data with OFFD and C4.5 showed that our new method outperforms C4.5 on most of the datasets we have tested.
Poster abstract: Enabling reliable and high-fidelity data center sensing
Authors: Chieh-Jan Mike Liang, Jie Liu, Liqian Luo, Andreas Terzis
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

RACNet is a sensor network that monitors a data center's environmental conditions at high temporal and spatial resolutions. The data RACNet collects can improve the energy efficiency of data centers, currently one of the fastest growing energy consumers in the U.S. RACNet overcomes the challenge of reliable and low-latency data gathering from dense networks deployed in harsh RF environments through rDCP, a novel network protocol that decouples data collection from topology control. Furthermore, rDCP automatically partitions the network to multiple routing trees, each operating at a different frequency channel. The combination of these features enables rDCP to scale up while maintaining high data yields. Preliminary results from a production deployment of 694 sensors (including 174 wireless nodes) show that rDCP achieves a data yield of 99%, while delivering 90% of the measurements in less than 30 seconds.
Initial study on automatic identification of speaker role in broadcast news speech
Authors: Yang Liu
Venue: Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX (2006)

Identifying a speaker's role (anchor, reporter, or guest speaker) is important for finding the structural information in broadcast news speech. We present an HMM-based approach and a maximum entropy model for speaker role labeling using Mandarin broadcast news speech. The algorithms achieve classification accuracy of about 80% (compared to the baseline of around 50%) using the human transcriptions and manually labeled speaker turns. We found that the maximum entropy model performs slightly better than the HMM, and that the combination of them outperforms any model alone. The impact of the contextual role information is also examined in this study.
Data Sharing and Exchanging Method for Urban Traffic Control System Based on XML
Authors: Jiuchun Gu, Yanguo Qu, Zhenhua Zhang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

In order to achieve the urban traffic control system easy to data sharing, this paper discusses the traffic data sharing demand of the traffic control system and summarizes advantages of XML data model from the point of data exchanging standardization, the paper puts forward the design flow of traffic control markup language and then the traffic control markup language (TCML) is brought forward based on XML. The paper also gives the definition, data architecture and XML schema of TCML. At last, the paper developed a data sharing verification prototype applying the TCML language. The practical simulation result indicated that TCML as a data describing method has shielded difference between traffic controllers; the testing result shows that the measure is feasibility, and TCML is best model for data-sharing and exchanging.
An Empirical Study on the Factors of Chinese Services Economy Growth
Authors: Renfa Yang, Qiong Huang
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

With the rapid development of economy in China, the role of services economy in the social life and national economy growth becomes more and more important. In this paper, we formulate a services economy growth factors model base on the related data of services economy growth in China in 2007. Chinese services economy growth factors have been empirically analyzed using the per capita GDP, the level of urbanization, population density, and population scale. The results show:(1) the role of per capita GDP is not obvious;(2) the scale of the population has the greatest impact on the portion of services added value in GDP;(3) population density has the greatest impact on the portion of services industry employed persons; (4) the level of urbanization to impact services industry is an important factor of the portion of services industry added value. Based on these results, the policy recommendation to improve services economy development is described.
A Case of Using Formal Concept Analysis in Combination with Emergent Self Organizing Maps for Detecting Domestic Violence
Authors: Jonas Poelmans, Paul Elzinga, Stijn Viaene, Guido Dedene
Venue: Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects (2009)

In this paper, we propose a framework for iterative knowledge discovery from unstructured text using Formal Concept Analysis and Emergent Self Organizing Maps. We apply the framework to a real life case study using data from the Amsterdam-Amstelland police. The case zooms in on the problem of distilling concepts for domestic violence from the unstructured text in police reports. Our human-centered framework facilitates the exploration of the data and allows for an efficient incorporation of prior expert knowledge to steer the discovery process. This exploration resulted in the discovery of faulty case labellings, common classification errors made by police officers, confusing situations, missing values in police reports, etc. The framework was also used for iteratively expanding a domain-specific thesaurus. Furthermore, we showed how the presented method was used to develop a highly accurate and comprehensible classification model that automatically assigns a domestic or non-domestic violence label to police reports.
On Discriminative Parameter Learning of Bayesian Network Classifiers
Authors: Franz Pernkopf, Michael Wohlmayr
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

We introduce three discriminative parameter learning algorithms for Bayesian network classifiers based on optimizing either the conditional likelihood (CL) or a lower-bound surrogate of the CL. One training procedure is based on the extended Baum-Welch (EBW) algorithm. Similarly, the remaining two approaches iteratively optimize the parameters (initialized to ML) with a 2-step algorithm. In the first step, either the class posterior probabilities or class assignments are determined based on current parameter estimates. Based on these posteriors (class assignment, respectively), the parameters are updated in the second step. We show that one of these algorithms is strongly related to EBW. Additionally, we compare all algorithms to conjugate gradient conditional likelihood (CGCL) parameter optimization [1].We present classification results for frame- and segment-based phonetic classification and handwritten digit recognition. Discriminative parameter learning shows a significant improvement over generative ML estimation for naive Bayes (NB) and tree augmented naive Bayes (TAN) structures on all data sets. In general, the performance improvement of discriminative parameter learning is large for simple Bayesian network structures which are not optimized for classification.
The direct nano-patterning of ZnO using nanoimprint lithography with ZnO-sol and thermal annealing
Authors: Ki-Yeon Yang, Kyung-Min Yoon, Kyung-Woo Choi, Heon Lee
Venue: Microelectronic Engineering (2009)

Nano-patterned ZnO layer was fabricated by ZnO-sol imprinting with a polymeric mold, followed by annealing. Instead of polymer based imprint resin, ZnO-sol was used as an imprint resin. During the imprinting process, the organic solvent in the ZnO-sol was absorbed into a polymeric mold and thus, ZnO-sol was converted to ZnO-gel. These patterns were subsequently annealed at 650^oC for 1h in atmospheric ambient to form ZnO patterns. X-ray diffraction (XRD) and photoluminescence (PL) confirmed that ZnO-gel was completely converted into ZnO by annealing. Using this ZnO-sol imprinting method, ZnO nano-patterns, as small as 50nm, were fabricated on Si and oxidized Si wafer substrates. The ZnO nano-patterns were characterized using scanning electron microscopy (SEM) and Transmission electron microscopy (TEM).