ppxscal/embedding_network huggingface dataset:
The Study of a Capacitance Sensor and its System Used in Measuring Ice Thickness, Sedimentation and Water Level of a Reservoir
Authors: Yinke Dou, Jianmin Qin, XiaoMin Chang
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

This paper presents a multi-electrode capacitance sensor and its system used in measuring sedimentation volume, water level, ice thickness of a river or reservoir. Based on the different characteristics of the capacitor in the different mediums such as in ice, water, sediment, a multi-functional, multi-electrode and non-closed capacitance sensor is designed. That is, a multi- electrode capacitance sensor is set up around a long hollow circular, which can be vertically placed in a river or reservoir. The capacitance value of each group is measured respectively. Using a simple algorithm, the two-dimensional cross-section data can be transformed into three-dimensional volume. Based on the experiment, a capacitance sensor and its system used in measuring ice thickness, sedimentation and water level of a reservoir is introduced. Experiments show that the sensor and its measurement system is advanced.
Fabric Defect Detection Method Based on Gabor Filter Mask
Authors: Runping Han, Lingmin Zhang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

In this paper, a fabric defect detection method based on Gabor filter masks is proposed. In this method, one even symmetric Gabor filter mask and one odd symmetric Gabor filter mask derived from the impulse response of the optimal Gabor filter are used. The optimal Gabor filter is designed to match with the texture features of defect-free fabric image, whose parameters are obtained by using the genetic algorithm. The performance of the proposed method is evaluated off-line by using a group of fabric sample images containing many kinds of fabric defects. The experimental results exhibit its accurate defect detection with low false alarms. And the effectiveness and robustness of the proposed method are confirmed.
pieTouch: a direct touch gesture interface for interacting with in-vehicle information systems
Authors: Ronald Ecker, Verena Broy, Andreas Butz, Alexander De Luca
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

Touch-sensitive displays seem like a natural and promising option for dealing with the increasing complexity of current in-vehicle information systems (IVIS), but since they can hardly be used without visual attention conventional point touch systems are rarely considered in cars. To ensure road safety, the drivers' visual attention needs to be focused almost entirely to the road. In order to integrate touch screens successfully into cars, new concepts are needed to reduce visual demand. The adaptation of pie menus serving as a visualisation of gestures reduces the user's cognitive load, and we were able to achieve an almost blind interaction with the IVIS. We compared our design to a generic touch system using a dual task evaluation method (Lane Change Task [18][20]), and the results regarding total task completion time, lane deviation and subjective preferences confirm a higher usability and efficiency, as well as an added hedonic quality of pieTouch.
Ensemble SWLDA Classifiers for the P300 Speller
Authors: Garett D. Johnson, Dean J. Krusienski
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques (2009)

The P300 Speller has proven to be an effective paradigm for brain-computer interface (BCI) communication. Using this paradigm, studies have shown that a simple linear classifier can perform as well as more complex nonlinear classifiers. Several studies have examined methods such as Fisher's Linear Discriminant (FLD), Stepwise Linear Discriminant Analysis (SWLDA), and Support Vector Machines (SVM) for training a linear classifier in this context. Overall, the results indicate marginal performance differences between classifiers trained using these methods. It has been shown that, by using an ensemble of linear classifiers trained on independent data, performance can be further improved because this scheme can better compensate for response variability. The present study evaluates several offline implementations of ensemble SWLDA classifiers for the P300 speller and compares the results to a single SWLDA classifier for seven able-bodied subjects.
Let us read together: Development and evaluation of a computer-assisted reciprocal early English reading system
Authors: Yu-Ju Lan, Yao-Ting Sung, Kuo-En Chang
Venue: Computers Education (2009)

This study attempts to implement a cooperative reading environment for EFL early reading using a mobile-device-supported computer-assisted reciprocal early English reading (CAREER) system, and to evaluate its effect on the early reading skills and learning behaviors of elementary EFL learners. The design rationale of CAREER is based on the three essential components of effective reading instructions: balanced reading structure, immediate and specific feedback, and reciprocal learning scenario. Analytical results indicate that the CAREER system reduces the problems experienced by students in a conventional cooperative learning environment and effectively helps elementary EFL learners orchestrate their learning while completing individual reading tasks and pursuing group goals. The results also demonstrate that CAREER appears to be able to benefit elementary EFL learners in developing reading skills. In sum, with the support of CAREER, the early reading skills of elementary students are benefited by cooperating with each other.
Cryptography with Constant Input Locality
Authors: Benny Applebaum, Yuval Ishai, Eyal Kushilevitz
Venue: Journal of Cryptology (2009)

We study the following natural question: Which cryptographic primitives (if any) can be realized by functions with constant input locality, namely functions in which every bit of the input influences only a constant number of bits of the output? This continues the study of cryptography in low complexity classes. It was recently shown by Applebaum et al. (FOCS 2004) that, under standard cryptographic assumptions, most cryptographic primitives can be realized by functions with constant output locality, namely ones in which every bit of the output is influenced by a constant number of bits from the input. We (almost) characterize what cryptographic tasks can be performed with constant input locality. On the negative side, we show that primitives which require some form of non-malleability (such as digital signatures, message authentication, or non-malleable encryption) cannot be realized with constant input locality. On the positive side, assuming the intractability of certain problems from the domain of error correcting codes (namely, hardness of decoding a random binary linear code or the security of the McEliece cryptosystem), we obtain new constructions of one-way functions, pseudorandom generators, commitments, and semantically-secure public-key encryption schemes whose input locality is constant. Moreover, these constructions also enjoy constant output locality and thus they give rise to cryptographic hardware that has constant-depth, constant fan-in and constant fan-out. As a byproduct, we obtain a pseudorandom generator whose output and input locality are both optimal (namely,&#x00a0;3).
Implementing Fast Packet Filters by Software Pipelining on x86 Processors
Authors: Yoshiyuki Yamashita, Masato Tsuru
Venue: Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies (2009)

Packet filters are essential for network traffic/security management on the Internet. Filters implemented by software on general-purpose CPUs are very flexible but occasionally suffer from poor performance. In order to address this problem, we have investigated software pipelining techniques for loops with a number of conditional branches for use in software-based fast packet filters. Based on our previous researches, we herein apply the software pipelining approach in an attempt to increase the filter performance for large filter rules. We validate the effectiveness of the proposed approach on Intel x86-32/64 series, as well as Intel Itanium 2 processors, which speaks to the generality and practicality of the proposed approach. The software pipelined program codes on x86-64 processors are 2.2 times faster than C-compiler-based codes and 1.8 times faster than carefully optimized hand-compiled codes. In addition, the performance of the pipelined codes we obtained on x86-64 processors is comparable to that on Itanium 2 processors with predicate registers.
Tuning complex event processing rules using the prediction-correction paradigm
Authors: Yulia Turchin, Avigdor Gal, Segev Wasserkrug
Venue: Proceedings of the Third ACM International Conference on Distributed Event-Based Systems (2009)

There is a growing need for the use of active systems, systems that act automatically based on events. In many cases, providing such active functionality requires materializing (inferring) the occurrence of relevant events. A widespread paradigm for enabling such materialization is Complex Event Processing (CEP), a rule based paradigm, which currently relies on domain experts to fully define the relevant rules. These experts need to provide the set of basic events which serves as input to the rule, their inter-relationships, and the parameters of the events for determining a new event materialization. While it is reasonable to expect that domain experts will be able to provide a partial rules specification, providing all the required details is a hard task, even for domain experts. Moreover, in many active systems, rules may change over time, due to the dynamic nature of the domain. Such changes complicate even further the specification task, as the expert must constantly update the rules. As a result, we seek additional support to the definition of rules, beyond expert opinion. This work presents a mechanism for automating both the initial definition of rules and the update of rules over time. This mechanism combines partial information provided by the domain expert with machine learning techniques, and is aimed at improving the accuracy of event specification and materialization. The proposed mechanism consists of two main repetitive stages, namely rule parameter prediction and rule parameter correction. The former is performed by updating the parameters using an available expert knowledge regarding the future changes of parameters. The latter stage utilizes expert feedback regarding the actual past occurrence of events and the events materialized by the CEP framework to tune rule parameters. We also include possible implementations for both stages, based on a statistical estimator and evaluate our outcome using a case study from the intrusion detection domain.
EM algorithm-based adaptive custom thresholding for image denoising in wavelet domain
Authors: S. Selvakumar Raja, Mala John
Venue: International Journal of Imaging Systems and Technology (2009)

In this article, a novel denoising technique based on custom thresholding operating in the wavelet transform domain is proposed. The denoising process is spatially adaptive and also sub-band adaptive. To render the denoising algorithm space adaptive, a Vector Quantization (VQ)-based algorithm is used. The design of the VQ is based on Expectation Maximization (EM) algorithm. The results of the algorithm is demonstrated on SAR images corrupted by speckle noise. Experimental results show that Custom thresholding function outperforms the traditional soft, hard, and Bayes threshoding functions, improving the denoised results significantly in terms of Peak Signal to Noise Ratio (PSNR). &copy; 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 175&ndash;178, 2009
Mining Graph Evolution Rules
Authors: Michele Berlingerio, Francesco Bonchi, Björn Bringmann, Aristides Gionis
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequence of snapshots of an evolving graph, we aim at discovering rules describing the local changes occurring in it. Adopting a definition of support based on minimum image we study the problem of extracting patterns whose frequency is larger than a minimum support threshold. Then, similar to the classical association rules framework, we derive graph-evolution rules from frequent patterns that satisfy a given minimum confidence constraint. We discuss merits and limits of alternative definitions of support and confidence, justifying the chosen framework. To evaluate our approach we devise GERM (Graph Evolution Rule Miner), an algorithm to mine all graph-evolution rules whose support and confidence are greater than given thresholds. The algorithm is applied to analyze four large real-world networks (i.e., two social networks, and two co-authorship networks from bibliographic data), using different time granularities. Our extensive experimentation confirms the feasibility and utility of the presented approach. It further shows that different kinds of networks exhibit different evolution rules, suggesting the usage of these local patterns to globally discriminate different kind of networks.
Mining Multiple Level Non-redundant Association Rules through Two-Fold Pruning of Redundancies
Authors: Corrado Loglisci, Donato Malerba
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

Association rules (AR) are a class of patterns which describe regularities in a set of transactions. When items of transactions are organized in a taxonomy, AR can be associated with a level of the taxonomy since they contain only items at that level. A drawback of multiple level AR mining is represented by the generation of redundant rules which do not add further information to that expressed by other rules. In this paper, a method for the discovery of non-redundant multiple level AR is proposed. It follows the usual two-stepped procedure for AR mining and it prunes redundancies in each step. In the first step, redundancies are removed by resorting to the notion of multiple level closed frequent itemsets, while in the second step, pruning is based on an extension of the notion of minimal rules. The proposed technique has been applied to a real case of analysis of textual data. An empirical comparison with the Apriori algorithm proves the advantages of the proposed method in terms of both time-performance and redundancy reduction.
Ergonomic Analysis of Different Computer Tools to Support the German Air Traffic Controllers
Authors: Muriel Didier, Margeritta Wilamowitz-Moellendorff, Ralph Bruder
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

The Institute of Ergonomics of the Darmstadt University of Technology supported the German Air Traffic Control in analyzing how the implementation of new tools influences the work procedures of the air traffic controllers and if a modification of the work structures is necessary. New tools, such as "Data link" (contact with the pilot via an electronic connection), the Problem Display Window and the Main Data Window that replaces the former flight strips, were tested in simulations. The goals of the study were to select the most appropriate investigation method to be used, taking into account the specific features of the controllers' work, to test different tools in a simulated environment and to analyze the impact of the new tools on the air traffic controllers.
A computer vision approach to Micro-Nucleus automatic detection and surface measurements
Authors: Michele Ceccarelli, Domenico Grimaldi, Francesco Lamonaca, Antonio Speranza
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

This paper reports a novel method for Nucleus and Micro Nucleuses segmentation. These biological structures are very handy to biologists for relieving structural chromosome aberration. The adopted method consists into a pipeline of advanced computer vision algorithms some of them specifically tailored for the current segmentation problem. Starting from weak hypotheses on size, shape and colour of Micro Nucleuses it is possible to efficiently segment all the image features by computer vision approach. Experimental results on real images are reported
On the accuracy of nodal stress computation in plane elasticity using finite volumes and finite elements
Authors: M. Vaz,  Jr., P. A. Muñoz-Rojas, G. Filippini
Venue: Computers and Structures (2009)

This paper addresses accuracy issues of nodal stresses in both finite elements and finite volumes. Strategies to evaluate nodal stresses for finite elements are also briefly discussed. Emphasis is placed on the application of finite volumes to solid mechanics and an overview of recent advancements is presented. Numerical simulation of test problems shows that accuracy of nodal stresses evaluated using finite elements is strongly dependent on the recovery strategy. In all cases, stress recovery at boundary nodal points renders large errors for all non-patch schemes. Contrastingly, finite volumes provide an accurate computation of nodal stresses, including at domain boundaries.
Hybrid Noor iteration method for nonexpansive mappings in Hilbert spaces
Authors: Jianhua Huang, Jinliang Shen
Venue: Computers Mathematics with Applications (2009)

In this paper, hybrid Noor iteration method was introduced for nonexpansive mappings in Hilbert spaces. The sufficient and necessary conditions that the iteration sequences converge strongly to a fixed point of a nonexpansive mapping are obtained in Hilbert spaces.
Structural Characteristic Analysis of Large Scale Object-Oriented Software and Its Evolution Based on Complex Network Theory
Authors: Yi Yao, Song Huang, Yu Hong, Zheng-ping Ren
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Many real-world networks are discovered to be complex networks in the last few years. Because software systems become more and more complicated, we attempt to apply complex network theory to study the large object-oriented software program with two versions in this paper. It is shown that large object-oriented software network is a scale-free network by computing its characteristic parameters. Especially, with increase of software’s scale, scale-free property is more evident. The statistical characteristic of software development network in which people are engaged is simply investigated and it also has properties of small world, and scale free. Some significant advices for software design and development are proposed.
Federated Identity Management
Authors: David W. Chadwick
Venue: Foundations of Security Analysis and Design V: FOSAD 2007/2008/2009 Tutorial Lectures (2009)

This paper addresses the topic of federated identity management. It discusses in detail the following topics: what is digital identity, what is identity management, what is federated identity management, Kim Cameron's 7 Laws of Identity, how can we protect the user's privacy in a federated environment, levels of assurance, some past and present federated identity management systems, and some current research in FIM.
c-GAMMA: Comparative Genome Analysis of Molecular Markers
Authors: Pierre Peterlongo, Jacques Nicolas, Dominique Lavenier, Raoul Vorc'H, Joël Querellou
Venue: Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (2009)

Discovery of molecular markers for efficient identification of living organisms remains a challenge of high interest. The diversity of species can now be observed in details with low cost genomic sequences produced by new generation of sequencers. A method, called c-GAMMA, is proposed. It formalizes the design of new markers for such data. It is based on a series of filters on forbidden pairs of words, followed by an optimization step on the discriminative power of candidate markers.First results are presented on a set of microbial genomes. The importance of further developments are stressed to face the huge amounts of data that will soon become available in all kingdoms of life.
The Frenet frame beyond classical differential geometry: Application to cartographic generalization of roads
Authors: J. F. Reinoso, M. Moncayo, M. Pasadas, F. J. Ariza, J. L. García
Venue: Mathematics and Computers in Simulation (2009)

The reconstruction of curves from their curvature is a problem not very well-solved in cartographic generalization of roads. Frenet's formulas theoretically solve this problem. The result shows that there exists a curve (up to rigid motion) with prefixed curvature function and torsion. By the use of the curvature and torsion functions, in closed forms, it is possible to obtain many beautiful examples in connection with this classical construction. In the case of plane curves, the torsion is equal to zero and the curve is characterized by the curvature. Nevertheless, if our starting point is a discrete set of arc length curvature experimental measures, the application of the Frenet frame is not straightforward. This study aims to describe how to adapt the classical Frenet frame to more realistic contexts derived from practical requirements. Our approach is applied to numerical measures derived from roads defined by Spanish Cartography, more precisely, by the Mapa Topografico Nacional 1:25.000 (MTN25). The method described will be used to obtain generalizations of the original road by performing a standard wavelet decomposition on the curvature before the application of the Frenet frame for plane curves.
Speech graffiti vs. natural language: assessing the user experience
Authors: Stefanie Tomko, Roni Rosenfeld
Venue: Proceedings of HLT-NAACL 2004: Short Papers on XX (2004)

Speech-based interfaces have great potential but are hampered by problems related to spoken language such as variability, noise and ambiguity. Speech Graffiti was designed to address these issues via a structured, universal interface protocol for interacting with simple machines. Since Speech Graffiti requires that users speak to the system in a certain way, we were interested in how users might respond to such a system when compared with a natural language system. We conducted a user study and found that 74% of users preferred the Speech Graffiti system to a natural language interface in the same domain. User satisfaction scores were higher for Speech Graffiti and task completion rates were roughly equal.
Investigating the Run Time Behavior of Distributed Applications by Using Tiny Java Virtual Machines with Wireless Communications
Authors: Tsuyoshi Miyazaki, Takayuki Suzuki, Fujio Yamamoto
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

From the viewpoint of programming education, distributed application programs carried out in a small JAVA machine group were considered. These computers are equipped with radio communication facility, multi-thread function, LEDs and various sensors. Parallel genetic algorithms and distributed search problems were targeted for the study here. About the latter, a detailed implementation method and the result of the experiment are shown. In such a computing environment, it was understood that the internal behavior and the data communication in the distributed application were easy to be grasped by an effect of visualizing them by the physical interface.