ppxscal/embedding_network huggingface dataset:
Development of CSCW Interfaces from a User-Centered Viewpoint: Extending the TOUCHE Process Model through Defeasible Argumentation
Authors: María Paula González, Victor M. Penichet, Guillermo R. Simari, Ricardo Tesoriero
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

The Task-Oriented and User-CenteredProcess Model for Developing Interfaces for Human-Computer-Human Environments (TOUCHE) is aimed to build up user interfaces for groupware applications under a Human-Computer Interaction perspective. It includes a large set of well known formal models like Class Diagrams, Organizational Structure Diagrams, Task Diagrams, Collaboration Diagrams and Abstract Interaction Objects among others. Most of such models, however, suffer from a number of limitations when formalizing users' commonsense. Over the last few years, Argumentation Systems have been gaining importance in several areas of Artificial Intelligence, mainly as a vehicle for facilitating rationally justifiable decision making when handling incomplete and potentially inconsistent information. This paper sketches a Proof of Concept to show how defeasible argumentation techniques can be embedded within the TOUCHE. The final goal is to enhance the capability of development process models for CSCW systems by including a rule-based approach for efficient reasoning with incomplete and inconsistent information.
Segmentation of Highly Lignified Zones in Wood Fiber Cross-Sections
Authors: Bettina Selig, Cris L. Hendriks, Stig Bardage, Gunilla Borgefors
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

Lignification of wood fibers has important consequences to the paper production, but its exact effects are not well understood. To correlate exact levels of lignin in wood fibers to their mechanical properties, lignin autofluorescence is imaged in wood fiber cross-sections. Highly lignified areas can be detected and related to the area of the whole cell wall. Presently these measurements are performed manually, which is tedious and expensive. In this paper a method is proposed to estimate the degree of lignification automatically. A multi-stage snake-based segmentation is applied on each cell separately. To make a preliminary evaluation we used an image which contained 17 complete cell cross-sections. This image was segmented both automatically and manually by an expert. There was a highly significant correlation between the two methods, although a systematic difference indicates a disagreement in the definition of the edges between the expert and the algorithm.
ATRIPPI: An Atom-residue Preference Scoring Function for Protein-protein Interactions
Authors: Kang-Ping Liu, Lu-Shian Chang, Jinn-Moon Yang
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

We present an ATRIPPI model for analyzing protein-protein interactions. This model is a 167-atom-type and residue-specific interaction preferences with distance bins derived from 641 co-crystallized protein-protein interfaces. The ATRIPPI model is able to yield physical meanings of hydrogen bonding, disulfide bonding, electrostatic interactions, van der Waals and aromatic-aromatic interactions. We applied this model to identify the native states and near-native complex structures on 17 bound and 17 unbound complexes from thousands of decoy structures. On average, 77.5% structures (155 structures) of top rank 200 structures are closed to the native structure. These results suggest that the ATRIPPI model is able to keep the advantages of both atom-atom and residue-residue interactions and is a potential knowledge-based scoring function for protein-protein docking methods. We believe that our model is robust and provides biological meanings to support protein-protein interactions.
Combining Model for Regional GPS Height Conversion Based on Least Squares Support Vector Machines
Authors: Wang Jigang, Hu Yonghui, Zhou Jiangcun
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

In geographical information engineering, height anomalies must be known in order to convert GPS ellipsoid heights into geodetic heights. There are many conversion models, such as polynomial, BP neural network and multi-quadrics fitting. Because the quasi-geoid is an irregular geometric object, every method has both advantages and disadvantages, and is appropriate to different conversion patterns. It is difficult to identify which conversion model is most suitable for a particular area. In order to obtain a more precise and reliable analytical result, the combined model based on least squares support vector machines (LSSVM) has been approached. Derived from statistical learning theory, LSSVM are learning systems that use a hypothesis space of linear function in a high dimensional feature space, trained with a learning algorithm from optimizations theory. As a result, the fitting ability of single models is significantly improved. The combined model still possesses the same important features as the single models. Examples are presented and the results are analyzed in detail to demonstrate the efficiency of the proposed methodology.
Relevance vector machines based modelling and optimisation for collaborative control parameter design: a case study
Authors: Jin Yuan, Cheng-liang Liu, Xuan F. Zha
Venue: International Journal of Computer Applications in Technology (2009)

A new collaborative control parameter design strategy is proposed for economic plant control process. The relevance vector machines (RVMs) and genetic algorithms (GAs) are combined to generate the optimal control index table for controllers. More specifically, the probabilistic model based on RVMs is utilised to describe the non-linear behaviours according to the experimental dataset. The evolution-based optimisation model based on GAs is used for collaborative design of the optimum control parameter combinations. A variable-rate fertilising system is presented as an application case for collaborative generation of control index table with the combined accuracy, energy saving and fertilising-consistency optimisation objectives. The experimental results show the effectiveness of the proposed hybrid approach.
PASS: Peer-ASSessment Approach for Modern Learning Settings
Authors: Mohammad Al-Smadi, Christian Guetl, Frank Kappe
Venue: Proceedings of the 8th International Conference on Advances in Web Based Learning (2009)

Students nowadays play major roles in the new culture of assessment where new forms of assessment have been adapted. Several labels have been used for assessment such as collaborative assessment, self- and peer-assessment. In this paper, we will present a computer-assisted peer assessment system that can be used to improve the learning process. An overall architecture for this system will be presented and an experiment has been conducted. First findings will be discussed and future work will be mentioned.
TACTUS: A Hardware and Software Testbed for Research in Multi-Touch Interaction
Authors: Paul Varcholik, Joseph J. Laviola,  Jr, Denise Nicholson
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques (2009)

This paper presents the TACTUS Multi-Touch Research Testbed, a hardware and software system for enabling research in multi-touch interaction. A detailed discussion is provided on hardware construction, pitfalls, design options, and software architecture to bridge the gaps in the existing literature and inform the researcher on the practical requirements of a multi-touch research testbed. This includes a comprehensive description of the vision-based image processing pipeline, developed for the TACTUS software library, which makes surface interactions available to multi-touch applications. Furthermore, the paper explores the higher-level functionality and utility of the TACTUS software library and how researchers can leverage the system to investigate multi-touch interaction techniques.
Distributed event stream processing with non-deterministic finite automata
Authors: Lars Brenna, Johannes Gehrke, Mingsheng Hong, Dag Johansen
Venue: Proceedings of the Third ACM International Conference on Distributed Event-Based Systems (2009)

Efficient matching of incoming events to persistent queries is fundamental to event pattern matching, complex event processing, and publish/subscribe systems. Recent processing engines based on non-deterministic finite automata (NFAs) have demonstrated scalability in the number of queries that can be efficiently executed on a single machine. However, existing NFA based systems are limited to processing events on a single machine. Consequently, their event processing capacity cannot be increased by adding more machines. In this paper, we present an experimental evaluation of different methods for distributing an event processing system that is based on NFAs across multiple machines in a cluster. Our results show that careful input stream partitioning gives close to linear performance scaleup for CPU bound workloads.
Nucleus-level clustering for word-independent syllable stress classification
Authors: Om D. Deshmukh, Ashish Verma
Venue: Speech Communication (2009)

This paper presents a word-independent technique for classifying the syllable stress of spoken English words. The proposed technique improves upon the existing word-independent techniques by utilizing the acoustic differences of various syllable nuclei. Syllables with acoustically similar nuclei are grouped together and a separate stress classifier is trained for each such group. The performance of the proposed group-specific classifiers is analyzed as the number of groups is increased and is also compared with an alternative data-driven clustering based approach. The proposed technique improves the syllable-level accuracy by 5.2% and the word-level accuracy by 1.1%. The corresponding improvements using the data-driven clustering based approach are 0.12% and 0.02%, respectively.
Acyclic rationality indicators of fuzzy choice functions
Authors: Irina Georgescu
Venue: Fuzzy Sets and Systems (2009)

We introduce the degree of acyclicity of a fuzzy preference relation and two acyclic rationality indicators of a fuzzy choice function C. These two indicators measure the degree to which the choice function C is acyclic G-rational, respectively, acyclic M-rational. We study the fuzzy Condorcet property of a fuzzy choice function and the corresponding indicators. We express the indicator of G-rationality in terms of the Condorcet property and the indicator of @a-consistency.
A Dual-Core Real-Time Embedded System for Vision-Based Automated Guided Vehicle
Authors: Jun Yu, Peihuang Lou, Xing Wu
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

As a cell of Flexible Manufacturing System (FMS), Automated Guided Vehicle (AGV) is widely used in factory. In this paper, we presented a novel technology used for vision-guided AGV. An embedded dual-core processor system with Real-Time Operating System (RTOS) DSP/BIOS is designed for system manager and image processor. We adopt DSP TMS320DM642 as image processor and ARM LPC2210 as controller. The embedded RTOS DSP/BIOS is transplanted on DSP to construct a software development platform for tasks management, which enhance reliability and real-time response of system. Two CCD cameras are fixed on vehicle to capture the scene of lane. One, on the front of vehicle, is used for prediction, the other, at the center of vehicle, is used for accurate positioning. Radio Frequency Identification (RFID) reader is loaded on vehicle to collect the information stored in RFID tag which placed by the side of lane. The experimental results demonstrate the advantages of real-time and robust.
Determining noisy attractors of delayed stochastic gene regulatory networks from multiple data sources
Authors: Xiaofeng Dai, Olli Yli-Harja, Andre S. Ribeiro
Venue: Bioinformatics (2009)

Motivation: Gene regulatory networks (GRNs) are stochastic, thus, do not have attractors, but can remain in confined regions of the state space, i.e. the ‘noisy attractors’, which define the cell type and phenotype. Results: We propose a gamma-Bernoulli mixture model clustering algorithm (ΓBMM), tailored for quantizing states from gamma and Bernoulli distributed data, to determine the noisy attractors of stochastic GRN. ΓBMM uses multiple data sources, naturally selects the number of states and can be extended to other parametric distributions according to the number and type of data sources available. We apply it to protein and RNA levels, and promoter occupancy state of a toggle switch and show that it can be bistable, tristable or monostable depending on its internal noise level. We show that these results are in agreement with the patterns of differentiation of model cells whose pathway choice is driven by the switch. We further apply ΓBMM to a model of the MeKS module of Bacillus subtilis, and the results match experimental data, demonstrating the usability of ΓBMM. Availability: Implementation software is available upon request. Contact:andre.sanchesribeiro@tut.fi; xiaofeng.dai@tut.fi Supplementary information: Supplementary data are available at Bioinformatics online.
Automated grading of student programming assignments
Authors: Stefan Brandle
Venue: Journal of Computing Sciences in Colleges (2009)

Grading student programs is one of those things that can be a headache for both faculty and students. For faculty --- especially if teaching with frequent assignments or larger class sizes --- grading takes a lot of time. In addition, it is hard to stay on top of the grading of weekly programs. Students often do not receive feedback quickly enough for it to be helpful for the next assignment and it is frequently not very detailed.
Can Physicians Structure Clinical Guidelines? Experiments with a Mark-Up-Process Methodology
Authors: Erez Shalom, Yuval Shahar, Meirav Taieb-Maimon, Guy Bar, Susana B. Martins, Ohad Young, Laszlo Vaszar, Yair Liel, Avi Yarkoni, Mary K. Goldstein, Akiva Leibowitz, Tal Marom, Eitan Lunenfeld
Venue: Knowledge Management for Health Care Procedures: ECAI 2008 Workshop, K4HelP 2008, Patras, Greece, July 21, 2008, Revised Selected Papers (2009)

We have previously developed an architecture and a set of tools called the Digital electronic Guideline Library (DeGeL), which includes a web-based tool for structuring (marking-up) free-text clinical guidelines (GLs), namely, the URUZ Mark-up tool. In this study, we developed and evaluated a methodology and a tool for a mark-up-based specification and assessment of the quality of that specification, of procedural and declarative knowledge in clinical GLs. The methodology includes all necessary activities before, during and after the mark-up process, and supports specification and conversion of the GL's free-text representation through semi-structured and semi-formal representations into a machine comprehensible representation. For the evaluation of this methodology, three GLs from different medical disciplines were selected. For each GL, as an indispensable step, an ontology-specific consensus was created, determined by a group of expert physicians and knowledge engineers, based on GL source. For each GL, two mark-ups in a chosen GL ontology (Asbru) were created by a distinct clinical editor; each of the clinical editors created a semi-formal mark-up of the GL using the URUZ tool. To evaluate each mark-up, a gold standard mark-up was created by collaboration of physician and knowledge engineer, and a specialized mark-up-evaluation tool was developed, which enables assessment of completeness, as well as of syntactic and semantic correctness of the mark-up. Subjective and objective measures were defined for qualitative and quantitative evaluation of the correctness (soundness) and completeness of the marked-up knowledge, with encouraging results.
Suffix tree characterization of maximal motifs in biological sequences
Authors: Maria Federico, Nadia Pisanti
Venue: Theoretical Computer Science (2009)

Finding motifs in biological sequences is one of the most intriguing problems for string algorithm designers due to, on the one hand, the numerous applications of this problem in molecular biology and, on the other hand, the challenging aspects of the computational problem. Indeed, when dealing with biological sequences it is necessary to work with approximations (that is, to identify fragments that are not necessarily identical, but just similar, according to a given similarity notion), and this complicates the problem. Existing algorithms run in time linear with respect to the input size. Nevertheless, the output size can be very large due to the approximation (namely exponential in the approximation degree). This often makes the output unreadable, as well as slowing down the inference itself. A high degree of redundancy has been detected in the set of motifs that satisfy traditional requirements, even for exact motifs. Moreover, it has been observed many times that only a subset of these motifs, namely the maximal motifs, could be enough to provide the information of all of them. In this paper, we aim at removing such redundancy. We extend some notions of maximality already defined for exact motifs to the case of approximate motifs with Hamming distance, and we give a characterization of maximal motifs on the suffix tree. Given that this data structure is used by a whole class of motif extraction tools, we show how these tools can be modified to include the maximality requirement without changing the asymptotical complexity.
A theoretical framework for transfer of knowledge across modalities in artificial and biological systems
Authors: Francesco Orabona, Barbara Caputo, Antje Fillbrandt, Frank W. Ohl
Venue: Proceedings of the 2009 IEEE 8th International Conference on Development and Learning (2009)

Learning from sensory patterns associated with different kinds of sensors is paramount for biological systems, as it permits them to cope with complex environments where events rarely appear twice in the same way. In this paper we want to investigate how perceptual categories formed in one modality can be transferred to another modality in biological and artificial systems. We first present a study on Mongolian gerbils that show clear evidence of transfer of knowledge for a perceptual category from the auditory modality to the visual modality. We then introduce an algorithm that mimics the behavior of the rodents within the online learning framework. Experiments on simulated data produced promising results, showing the pertinence of our approach.
A Frame Synchronization and Symbol Timing Synchronization Algorithm in Burst OFDM Communication Based on IEEE802.11a
Authors: Sun Wensheng, Zhang Yuanyuan
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

This paper studies an algorithm on frame and symbol timing synchronization in burst OFDM communication based on IEEE802.11a, and analyzes the effect of symbol timing synchronization error. It’s not perfect in many algorithms on timing synchronization at present, such as high complexity, floated threshold along with the signal energy. Therefore, it's necessary to propose an algorithm on symbol timing synchronization using the specialty of Short Training Sequence in this paper. The analysis and the simulation results show that the algorithm proposed in this paper can improve the bit-error-rate performance of the system effectively. Moreover, it also has an adaptive threshold and low implementation complexity. Therefore, the proposed algorithm is suitable for fast symbol timing synchronization in burst OFDM system.
Dealing with Telephone Fraud Using CAPTCHA
Authors: Hua Zhang, Xiangming Wen, Peizhou He, Wei Zheng
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Nowadays mobile communication permeates daily life everywhere. So as the troubles made by spam SMS (Short Message Service), telephone frauds are also obsessing the users. In this paper a new method is proposed for avoiding telephone frauds using CAPTCHA (Completely Automatic Public Turing Test to Tell Computer and Human Apart) systems. In this method, an authorize code is structured and decomposed into several parts. After dealing with the parts separately an animation authorize code is generated with these parts as its frames. The animation authorize code is sent as a SMS multimedia message to the one who is calling in. The caller should type the authorize code correctly and send the code back as a short message in reply. If the caller can pass the CAPTCHA test, it will be identified that the call is not a fraud.
POIROT: integrated learning of web service procedures
Authors: Mark Burstein, Robert Laddaga, David McDonald, Michael Cox, Brett Benyo, Paul Robertson, Talib Hussain, Marshall Brinn, Drew McDermott
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

POIROT is an integration framework for combining machine learning mechanisms to learn hierarchical models of web services procedures from a single or very small set of demonstration examples. The system is organized around a shared representation language for communications with a central hypothesis blackboard. Component learning systems share semantic representations of their hypotheses (generalizations) and inferences about demonstration traces. To further the process, components may generate learning goals for other learning components. POIROT's learners or hypothesis formers develop workflows that include order dependencies, subgoals, and decision criteria for selecting or prioritizing subtasks and service parameters. Hypothesis evaluators, guided by POIROT's meta-control component, plan experiments to confirm or disconfirm hypotheses extracted from these learning products. Collectively, they create methods that POIROT can use to reproduce the demonstration and solve similar problems. After its first phase of development, POIROT has demonstrated it can learn some moderately complex hierarchical task models from semantic traces of user-generated service transaction sequences at a level that is approaching human performance on the same learning task.
Service Interruptions in Large-Scale Service Systems
Authors: Guodong Pang, Ward Whitt
Venue: Management Science (2009)

Large-scale service systems, where many servers respond to high demand, are appealing because they can provide great economy of scale, producing a high quality of service with high efficiency. Customer waiting times can be short, with a majority of customers served immediately upon arrival, while server utilizations remain close to 100%. However, we show that this confluence of quality and efficiency is not achieved without risk, because there can be severe congestion if the system does not operate as planned. In particular, we show that the large scale makes the system more vulnerable to service interruptions when (i) most customers remain waiting until they can be served, and (ii) when many servers are unable to function during the interruption, as may occur with a system-wide computer failure. Increasing scale leads to higher server utilizations, which in turn leads to longer recovery times from service interruptions and worse performance during such events. We quantify the impact of service interruptions with increasing scale by introducing and analyzing approximating deterministic fluid models. We also show that these fluid models can be obtained from many-server heavy-traffic limits.