ppxscal/embedding_network huggingface dataset:
Improving scalability of support vector machines for biomedical named entity recognition
Authors: Jugal K. Kalita
Venue:  (2008)

This research work aims to explore the scalability problems associated with solving the named entity recognition problem using high-dimensional input space and Support Vector Machines (SVM), and to provide solutions that lower the computational time and memory requirements. The named entity recognition approach used is one that fosters language and domain independence by eliminating the use of prior language and/or domain knowledge. The biomedical domain is chosen as the focus of this work due to its importance and inherent challenges. To investigate the scalability of the SVM machine learning approach, we conduct a series of baseline experiments using biomedical abstracts. Single class and multi-class classification performance and results are examined. The initial performance results&mdash;measured in terms of precision, recall, and F-score&mdash;are comparable to those obtained using more complex approaches. These results demonstrate that the simplified architecture used is capable of providing a reasonable solution to the language and domain-independent named entity recognition problem. To improve the scalability of named entity recognition using SVM, two main factors are tackled: computation time and memory requirements. We develop a new cutting plane algorithm for multi-class classification&mdash; SVM-PerfMulti&mdash;based on a new structural formulation for support vector optimization. The solution is several orders of magnitude faster than the traditional SVM-Multiclass machine and provides good out-of-the-box performance, yet it requires a considerable amount of memory that is linear w.r.t. the training data size. We introduce a new database-supported solution embedded in a relational database server. The database framework supports both the binary and multi-class classification problems. We explore the trade-off between computation time and online memory requirement when input feature vectors and trained support vectors are stored and fetched from the database. Database caching of input vectors has minimal to no impact on the computation time. On the other hand, constantly fetching support vectors from permanent storage negatively impacts computation time and can be improved by caching kernel computations in active memory. The database framework promotes the usability of the machine learning solution and provides a way to build a growing dictionary of previously identified named entities.
An adaptive controller for bilateral teleoperation under time delay
Authors: Ali Shahdi, Shahin Sirouspour
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

Previous efforts in bilateral time-delay teleoperation have mainly yielded control algorithms that sacrifice performance in order to guarantee robust stability. This paper proposes a provably stable adaptive predictive controller for teleoperation systems with communication delay. The method uses the model and delay information and can adapt to uncertainties in user and environment dynamics in order to achieve delay-free transparency objectives. These include position tracking and tool impedance shaping. Delay reduction is accomplished using a state observer and estimates of the system parameters. Teleoperation transparency objectives are attained within an output regulation control framework based on the predicted system dynamics. A Lyapunov analysis has been used to prove the stability of the system and to obtain the parameter adaptation law. Simulation results with a single-axis teleoperation setup demonstrate the effectiveness of the proposed approach.
Extended Cooperative Balanced Space-Time Block Coding for Increased Efficiency in Wireless Sensor Networks
Authors: Ali Ekşim, Mehmet Ertuğrul Çelebi
Venue: Proceedings of the 8th International IFIP-TC 6 Networking Conference (2009)

Diversity techniques for communications among sensors are very effective tool to increase reception quality and battery lifetimes. A well-known method to increase diversity in cooperative communications is sensor (relay) selection. However, sensor selection method may lead to the selection of the same (near) sensor for transmission over a long period. One of the alternative techniques to sensor selection is cooperative balanced space-time block coding which utilizes every sensor in sight, thus, distributes the energy consumption among many sensors. Furthermore, it guarantees full diversity for any number of relay sensors. In this work, we consider dual-hop amplify-and-forward wireless sensor network and extend the cooperative balanced space-time block code family to improve its performance. In the proposed scheme, a larger number of codes can be generated for improved coding gain, and better signal-to-noise ratio improvement can be obtained compared to sensor selection schemes.
Specification and Collaboration Driven Software Component Selection- Building a Framework for Component Selection
Authors: Lei Wang
Venue:  (2007)

Building software systems from previously existing components can save time and effort while increasing productivity. The key to a successful Component- Based Development (CBD) is to get the required components. However, components obtained from other developers often show different behaviours than what are required. Thus adapting the components into the system being developed becomes an extra development and maintenance cost. This cost often offsets the benefits of CBD. Imprecise component specifications and user requirements are the main reasons that cause the difficulty of finding the required components. Furthermore, there is little support for component users and developers to collaborate and clear the misunderstanding when selecting components, as CBD has two separate development processes for them. This book aims at building a framework in which component users and developers can collaborate to select components with tools support, by exchanging component and requirement specifications. These specifications should be precise enough so that behavioural mismatches can be detected. This book would interest software developers and component vendors. It is also a reference for researchers in component-based software engineering. 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
A reverse technique for lumping high dimensional model representation method
Authors: M. Alper Tunga, Metin Demiralp
Venue: Proceedings of the 2nd WSEAS international conference on Multivariate analysis and its application in science and engineering (2009)

An orthogonal hyperprismatic grid whose all nodes are accompanied by the given function values can not be generally constructed due to the random nature of the given function data. This prevents the reduction of the single multivariate interpolation to more than one univariate or bivariate interpolations even approximately. It is generally quite difficult to determine an analytical structure for the target function in these problems. Lumping HDMR method is an indexing based High Dimensional Model Representation (HDMR) algorithm used to reconstruct these types of multivariate data by imposing an indexing scheme to obtain an orthogonal geometry for the given problem. By this way, the training of the given data can be accomplished. The next problem is to determine a reverse algorithm for the testing data. This work is about a new algorithm to find the correct coordinate of the given testing data in the orthogonal geometry obtained through Lumping HDMR.
Pupils' Attitudes towards Using Cellular Phones for Learning Activities
Authors: Tadashi Inagaki, Yuki Kobayashi, Hitoshi Nakagawa
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

Cellular phones have become very popular recently. In “Educational Use of Cellular Phones,” our research project, the main theme is how teachers and children use the W-CDMA cellular phone in elementary schools. The pupils were surveyed regarding their attitudes towards the use of cell phones for learning. There are four major findings: Video phone and Bulletin Board System(BBS) access were often used, the pupils treat the cell phone as an immediate and interactive communication tool and overcome their function specific hurdles.
Learn FileMaker Pro 9, 1st edition
Authors: Jonathan Stars
Venue:  (2007)

Learn FileMaker Pro 9 provides a logical, hands-on approach to understanding the features of FileMaker Pro, both for beginners and those who have experience with previous versions of the software. From defining database terms and converting files created in previous FileMaker Pro versions to producing reports and using files on the web, this book covers the fundamentals as well as the newest features that considerably enhance FileMaker Pro s database management capabilities. Learn how to: Format layout objects with Autoresize and conditional formatting. Harness the power of the new External SQL Data Source tools. Adapt one script to many purposes to cut development time and expense. Work with the enhanced Web Viewer to harvest data for your applications. Share data as PDF and Excel files and export data as e-mail attachments. Organize your relationships with the anchor-buoy method. Use the alignment tools to quickly align objects on your layout. 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
An unsupervised vector approach to biomedical term disambiguation: integrating UMLS and Medline
Authors: Bridget T. McInnes
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Student Research Workshop (2008)

This paper introduces an unsupervised vector approach to disambiguate words in biomedical text that can be applied to all-word disambiguation. We explore using contextual information from the Unified Medical Language System (UMLS) to describe the possible senses of a word. We experiment with automatically creating individualized stoplists to help reduce the noise in our dataset. We compare our results to SenseClusters and Humphrey et al. (2006) using the NLM-WSD dataset and with SenseClusters using conflated data from the 2005 Medline Baseline.
Using Support Vector Machines for feature-oriented profile-based recommendations
Authors: Angel Garcia-Crespo, Juan Miguel Gomez-Berbis, Ricardo Colomo-Palacios, Francisco Garcia-Sanchez
Venue: International Journal of Advanced Intelligence Paradigms (2009)

Recommendations have reached a new dimension in a ubiquitous computing environment. A vast amount of information is coming from pervasive services and devices, providing a potential source of value-added knowledge. However, this knowledge must be exposed through a classification technique such as Support Vector Machines (SVMs), which would allow categorising, classifying and evaluating this information based on features and profiles to foster the efficiency of recommendations of informational items. This paper presents an algorithm based on SVMs and an underlying architecture to extract and build a number of recommendations based on features and profile preferences from the user.
A novel fuzzy neural approach to data reconstruction and failure prediction
Authors: C. Quek, R. W. Zhou, C. H. Lee
Venue: International Journal of Intelligent Systems in Accounting and Finance Management (2009)

Bank failure prediction is of great importance to a bank's clients, policy-makers and regulators. Various traditional models have been employed to study bank failures. Unfortunately, their performances are unsatisfactory. In this paper, the pseudo-outer product fuzzy neural network using the compositional rule of inference and singleton fuzzifier (POPFNN-CRI(S))-based bank failure prediction model is proposed. It employs computational bank failure analysis techniques coupled with reconstruction of missing financial data in financial covariates that are available from publicly available financial statements as inputs. The performance of the proposed model is assessed through the classification rate of 3636 US banks observed over a 21-year period. The effects of missing data reconstruction are investigated. Copyright &copy; 2009 John Wiley & Sons, Ltd.
Softspeak: making VoIP play well in existing 802.11 deployments
Authors: Patrick Verkaik, Yuvraj Agarwal, Rajesh Gupta, Alex C. Snoeren
Venue: Proceedings of the 6th USENIX symposium on Networked systems design and implementation (2009)

Voice over IP (VoIP) in 802.11 wireless networks (WiFi) is an attractive alternative to cellular wireless telephony. Unfortunately, VoIP traffic is well known to make inefficient use of such networks. Indeed, we demonstrate that increasing handset deployment has the potential to cripple existing hotspot and enterprise WiFi networks. Our experiments show that VoIP halves the available TCP capacity of an 802.11b hotspot when six to eight VoIP stations share the medium, and effectively extinguishes TCP connectivity when ten VoIP stations are present. Further, we show that neither the higher data rates of 802.11a/g nor the 802.11 standard for quality of service, 802.11e, fully ameliorate the problem. Instead, the problem is rooted in WiFi's contention-based medium-access control mechanism and considerable framing overhead. To remedy this problem, we propose Softspeak, a pair of backwards-compatible software extensions that enables VoIP traffic to share the channel in a more efficient, TDMA-like manner. Softspeak does not require any modifications to the WiFi protocols and significantly reduces the impact of VoIP on TCP capacity while simultaneously improving key VoIP call-quality metrics. Results show improvements in TCP download capacity of 380% for 802.11b and 25-200% for 802.11g.
Determinants of Service Reusability
Authors: George Feuerlicht, Amalka Wijayaweera
Venue: Proceeding of the 2007 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the sixth SoMeT_07 (2007)

Software reuse is regarded is as a key software development objective leading to reduction of costs associated with software development and maintenance. However, there is mounting evidence that software reuse is difficult to achieve in practice, and that software development approaches such as component-based development, and more recently service-oriented computing have failed to achieve anticipated levels of reuse. In this paper we identify the determinants of service reusability and argue that the design of services plays an important role in achieving high levels of reuse. We examine the relationship between service granularity and reuse and note that extensive use of coarse grained, document-centric services by SOA practitioners makes achieving reuse particularly challenging.
WiMAX opportunities for emerging markets
Authors: Hani Eigebali
Venue: Proceedings of the 2009 conference on Information Science, Technology and Applications (2009)

WiMAX is a novel wireless broadband technology with lots of promises for Urban and rural areas. It has the potential of bringing true wireless broadband to the masses at a fraction of the cost of existing solutions. The technology comes with many benefits and a few challenges. This tutorial discusses the technology benefits and applications. It also addresses some of the hurdles towards deployment and what the industry is doing to overcome those hurdles. A special focus will be given to the Middle East and an overview of the opportunities that exist will be presented.
Semi-supervised Segmentation Based on Non-local Continuous Min-Cut
Authors: Nawal Houhou, Xavier Bresson, Arthur Szlam, Tony F. Chan, Jean-Philippe Thiran
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

We propose a semi-supervised image segmentation method that relies on a non-local continuous version of the min-cut algorithm and labels or seeds provided by a user. The segmentation process is performed via energy minimization. The proposed energy is composed of three terms. The first term defines labels or seed points assigned to objects that the user wants to identify and the background. The second term carries out the diffusion of object and background labels and stops the diffusion when the interface between the object and the background is reached. The diffusion process is performed on a graph defined from image intensity patches. The graph of intensity patches is known to better deal with textures because this graph uses semi-local and non-local image information. The last term is the standard TV term that regularizes the geometry of the interface. We introduce an iterative scheme that provides a unique minimizer. Promising results are presented on synthetic textures a nd real-world images.
Knowledge management in Romanian software development organizations
Authors: Scorta Iuliana, Florea Alexandra
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

The software development process is knowledge-intensive. Knowledge is dynamic and evolves with technology, organizational culture and the changing needs of organization's software development practices. Although, knowledge management in software engineering is a topic that received a lot of attention from international academicians and practitioners this subject was not so appealing to the Romanian counterparts. In this paper we conduct an investigation for evaluating aspects of knowledge management practice in Romanian software engineering industry and discuss the concepts studied and the major findings.
Sample size computing for factorial designs: an extension of the Athenian representative method
Authors: Constantinos N. Tsiantis
Venue: Proceedings of the 15th american conference on Applied mathematics (2009)

The paper considers sample size computing as a problem of representation. It clarifies the notion of representation and concentrates on the simultaneous representation of: i) a finite population divided into r × c cells provided by the crossing of levels of two factors, and ii) the respective set of values that a variable of interest takes upon the population subjects. Through a probabilistic approach, the sample size formula for the full factorial design, with non-zero mean differences among cells and interaction among factors, was derived. The formula verifies, that the statistical sample size nst is the product of population representation np and variance (SD) representation ns multiplied by the factor R (sum of cell percentages). This law is an extension of the Athenian law of representation. It applies both for balanced and unbalanced factorial designs and operates as the representation standard in sample size computing for a multi-way (n-way) ANOVA.
Lane marker parameters for vehicle's steering signal prediction
Authors: Andriejus Demčenko, Minija Tamošiunaite, Aušra Vidugiriene, Leonas Jakevičius
Venue: WSEAS TRANSACTIONS on SYSTEMS (2009)

The work considers road lane parameters that correlate with steering angle of a car and which are suitable for accurate prediction of steering signal using neural network technique. Four different parameters, which can be used in driver's assistance system and are based on position, angles and curvature of the lane marker, are proposed and their correspondence to steering signal is analyzed. The steering signal is predicted with the precision of 95% to 97%, depending on a combination of the visually-based parameters provided for the neural network. The work is performed using signals from real road driving.
Low temperature formation of SiO2 thin films by nitric acid oxidation of Si (NAOS) and application to thin film transistor (TFT)
Authors: T. Matsumoto, Asuha, W. -B. Kim, M. Yamada, S. Imai, S. Terakawa, H. Kobayashi
Venue: Microelectronic Engineering (2009)

Nitric acid oxidation of Si (NAOS) can form 1.3-20nm SiO"2 films on Si(100) and poly-crystalline silicon (poly-Si) surfaces at low temperatures below 120^oC. The 1.3nm SiO"2 layer formed by immersion in 68wt% HNO"3 possesses a low leakage current density and it can be made lower by post-metallization annealing (PMA) in hydrogen than that for thermal oxide with the same thickness. A thicker SiO"2 layer can be formed by immersion in 40wt% HNO"3 followed by 68wt% HNO"3, and its leakage current density becomes nearly the same after PMA as that of thermal oxide. The low leakage current density results from elimination of the interface states by hydrogen and the high atomic density of the NAOS-SiO"2 layer as estimated from the vibrational frequencies of transverse and longitudinal optical phonons of the Si-O-Si asymmetric stretching mode. The thickness of the NAOS-SiO"2 layer is uniform even on the rough poly-Si surfaces. The dispersion of the thickness of the NAOS-SiO"2 layer is also found to be less than +/-5% on the 32cmx40cm poly-Si substrates.
Privacy for real-time location-based services
Authors: Lars Kulik
Venue: SIGSPATIAL Special (2009)

Location-Based Services (LBSs) are developing at an amazing pace. Whereas the first generation of LBSs required manual user input of location information via simple web-based interfaces, current GPS-enabled devices such as smartphones or in-car navigation systems can automatically initiate and negotiate LBSs based on their current position. The latest generation of LBSs combines high position accuracy with real-time position updates, which enables numerous applications including asset tracking, location-based advertising, location-sensitive billing, and street-level routing and positioning.
The Agreement Problem in Unreliable Scale-Free Networks
Authors: Kuo-Qin Yan, Shun-Sheng Wang, Shu-Ching Wang
Venue: The Computer Journal (2009)

Generally, tasks in a distributed system must reach agreement. This requires a set of processors to agree on a common value even though some components may be corrupt. There have been several significant studies on this agreement problem in regularized network environments such as the fully connected, broadcast and multicast networks. Recently, many large complex networks have emerged displaying a scale-free feature that influences the system to reach a common value in a novel way. This unanimity problem is called Byzantine agreement (BA). The BA problem is one of the most significant problems in designing a fault-tolerant distributed system. Unfortunately, existing BA protocols cannot cope with the new network environment, and the BA problem thus must be revisited. In this paper, a new BA protocol is proposed that adapts to the scale-free network (SFN) environment and derives its limit of allowable faulty components while maintaining the minimum number of message exchanges. The correctness and complexity of this protocol have been proved. It is observed that an SFN in conjunction with the proposed agreement protocol can tolerate the maximum number of faulty components.