ppxscal/embedding_network huggingface dataset:
Solving a Problem in Grid Applications: Using Aspect Oriented Programming
Authors: Hyuck Han, Shingyu Kim, Hyungsoo Jung, Heon Y. Yeom
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Aspect Oriented Programming (AOP) was introduced 10 years ago and many research projects have focused on broadening AOP and its target areas. However, few applications in the Grid computing world adopt AOP in comparison with very vigorous research of AOP. Therefore, we present a case study that covers a general networking problem in the Grid computing. AOP provides a novel solution of the problem without modifying existing source code. Aspects that we define are simple, intuitive and reusable. We believe that our implementation is very useful in developing other Grid computing software platforms, and AOP can be a powerful method in modularizing source codes and solving problems of software architectures.
Complexity and Limiting Ratio of Boolean Functions over Implication
Authors: Hervé Fournier, Danièle Gardy, Antoine Genitrini, Bernhard Gittenberger
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

We consider the logical system of boolean expressions built on the single connector of implication and on positive literals. Assuming all expressions of a given size to be equally likely, we prove that we can define a probability distribution on the set of boolean functions expressible in this system. We then show how to approximate the probability of a function f when the number of variables grows to infinity, and that this asymptotic probability has a simple expression in terms of the complexity of f. We also prove that most expressions computing any given function in this system are "simple", in a sense that we make precise.
Grasp synthesis from low-dimensional probabilistic grasp models
Authors: Heni Ben Amor
Venue: Computer Animation and Virtual Worlds (2008)

We propose a novel data-driven animation method for the synthesis of natural looking human grasping. Motion data captured from human grasp actions is used to train a probabilistic model of the human grasp space. This model greatly reduces the high number of degrees of freedom of the human hand to a few dimensions in a continuous grasp space. The low dimensionality of the grasp space in turn allows for efficient optimization when synthesizing grasps for arbitrary objects. The method requires only a short training phase with no need for preprocessing of graphical objects for which grasps are to be synthesized. Copyright &copy; 2008 John Wiley & Sons, Ltd.
SAWSDL, mediation and XQUERY for web services discovery
Authors: Amel Benna, Nacer Boudjlida, Hassina Talantikite
Venue: Proceedings of the 8th international conference on New technologies in distributed systems (2008)

Web services have been adopted by large industrial and commercial organizations to achieve interoperability between distributed systems. The interaction between web services components is done through publication, research, discovery and then invocation based on the service's description. However, their publication in an UDDI registry doesn't offer enough description of the service offering. The main idea described in this paper is about having a semantic description of web services (using SAWSDL) and then storing their functionality, during the publication phase, in a register named 'semantic links base'. This base represents the mediator between the service requestor and the service provider and would minimize the search time during the discovery step, because the mapping between the request concepts and the Web services are known in advance. The Web services discovery process is about finding these mappings between the user query, which is defined in a unified manner by referring to an ontology, and the web services functionality. The user request is translated into a query on the 'semantic links base' as well as the UDDI registry. The result returned can then be used as entry point for another query.
An Experiment on Human Face Recognition Performance for Access Control
Authors: Marcus Butavicius, Chloë Mount, Veneta Macleod, Robyn Vast, Ian Graves, Jadranka Sunde
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

An experiment was conducted on human face recognition performance in an access control scenario. Ten judges compared fifty individuals to security ID style photos where 20% of the photos were of different people, assessed to look similar to the individual presenting the photo. Performance was better than that observed in the only other comparable live-to-photo experiment [1] with a false match rate of 9% [CI95%: 2%, 16%] in this study compared to 66% [CI95%: 50%, 82%] and a false reject rate of 5% [CI95%: 0%, 11%] compared to 14% [CI95%: 0.3%, 28%]. These differences were attributed to divergences in experimental methodology, especially with regards to the distractor tasks used. It is concluded that the figures provided in the current study are more appropriate estimates of performance in access control scenarios. Substantial individual variation in face matching abilities, response time and confidence ratings was observed.
Laser pointers and a touch screen: intuitive interfaces for autonomous mobile manipulation for the motor impaired
Authors: Young Sang Choi, Cressel D. Anderson, Jonathan D. Glass, Charles C. Kemp
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

El-E ("Ellie") is a prototype assistive robot designed to help people with severe motor impairments manipulate everyday objects. When given a 3D location, El-E can autonomously approach the location and pick up a nearby object. Based on interviews of patients with amyotrophic lateral sclerosis (ALS), we have developed and tested three distinct interfaces that enable a user to provide a 3D location to El-E and thereby select an object to be manipulated: an ear-mounted laser pointer, a hand-held laser pointer, and a touch screen interface. Within this paper, we present the results from a user study comparing these three user interfaces with a total of 134 trials involving eight patients with varying levels of impairment recruited from the Emory ALS Clinic. During this study, participants used the three interfaces to select everyday objects to be approached, grasped, and lifted off of the ground. The three interfaces enabled motor impaired users to command a robot to pick up an object with a 94.8% success rate overall after less than 10 minutes of learning to use each interface. On average, users selected objects 69% more quickly with the laser pointer interfaces than with the touch screen interface. We also found substantial variation in user preference. With respect to the Revised ALS Functional Rating Scale (ALSFRS-R), users with greater upper-limb mobility tended to prefer the hand-held laser pointer, while those with less upper-limb mobility tended to prefer the ear-mounted laser pointer. Despite the extra efficiency of the laser pointer interfaces, three patients preferred the touch screen interface, which has unique potential for manipulating remote objects out of the user's line of sight. In summary, these results indicate that robots can enhance accessibility by supporting multiple interfaces. Furthermore, this work demonstrates that the communication of 3D locations during human-robot interaction can serve as a powerful abstraction barrier that supports distinct interfaces to assistive robots while using identical, underlying robotic functionality.
Minimum Leaf Out-Branching Problems
Authors: Gregory Gutin, Igor Razgon, Eun Jung Kim
Venue: Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management (2008)

Given a digraph D, the Minimum Leaf Out-Branching problem (MinLOB) is the problem of finding in D an out-branching with the minimum possible number of leaves, i.e., vertices of out-degree 0. We prove that MinLOB is polynomial-time solvable for acyclic digraphs. In general, MinLOB is NP-hard and we consider three parameterizations of MinLOB. We prove that two of them are NP-complete for every value of the parameter, but the third one is fixed-parameter tractable (FPT). The FPT parametrization is as follows: given a digraph D of order n and a positive integral parameter k, check whether D contains an out-branching with at most n ¿ k leaves (and find such an out-branching if it exists). We find a problem kernel of order O(k·2 k ) and construct an algorithm of running time O(2 O(klogk) + n 3), which is an `additive' FPT algorithm.
Traffic Data Preparation for a Hybrid Network IDS
Authors: Álvaro Herrero, Emilio Corchado
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

An increasing effort has being devoted to researching on the field of Intrusion Detection Systems (IDS's). A wide variety of artificial intelligence techniques and paradigms have been applied to this challenging task in order to identify anomalous situations taking place within a computer network. Among these techniques is the neural network approach whose models (or most of them) have some difficulties in processing traffic data "on the fly". The present work addresses this weakness, emphasizing the importance of an appropriate segmentation of raw traffic data for a successful network intrusion detection relying on unsupervised neural models. In this paper, the presented neural model is embedded in a hybrid artificial intelligence IDS which integrates the case based reasoning and multiagent paradigms.
Design procedure for nonlinear multivariable processes control
Authors: Lupu Ciprian, Popescu Dumitru, Udrea Andreea, Dimon Catalin
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

This study presents comparative results of real time implementing of three methods for control a multivariable process with nonlinear static characteristics. The first two methods are classic and are based on decentralized control and respectively, on static decoupling procedures. The third proposed method is developed using a combined feedforward and feedback control scheme with nonlinear compensators. The use of this last structure imposes solving some specific problems, like process's static characteristic determination, construction of a nonlinear compensator or robust control law design. The applicability of the proposed method and of the two classic methods is proved using a real-time structure based on RST control algorithms. In the end, its software implementation and the obtained results are also shown.
It's Not Easy Being Green: Supporting Collaborative "Green Design" Learning
Authors: Sourish Chaudhuri, Rohit Kumar, Mahesh Joshi, Elon Terrell, Fred Higgs, Vincent Aleven, Carolyn Penstein Rosé
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

We present the results of a study in which we contrast alternative forms of collaborative learning support in the midst of a collaborative design task in which students negotiate between increasing power and increasing environmental friendliness. In this context, we evaluated the instructional effectiveness of four alternative support conditions as well as a goal manipulation. Both manipulations yield surprising findings, which we are continuing to investigate.
Modeling Phone Duration of Lithuanian by Classification and Regression Trees, using Very Large Speech Corpus
Authors: Giedrius Norkevičius, Gailius Raškinis
Venue: Informatica (2008)

Classification and regression tree approach was used in this research to model phone duration of Lithuanian. 300 thousand samples of vowels and 400 thousand samples of consonants extracted from VDU-AB20 corpus were used in experimental part of research. Set of 15 parameters characterizing phone and its context were selected for duration prediction. The most significant of them were: identifier (ID) of phone being predicted, adjacent phones IDs and number of phones in syllable. Models were built using two different data sets: one speaker and 20 speakers. The influence of cost complexity pruning and different values of pre pruning were investigated. Prediction by average leaf duration vs. prediction by median leaf duration was also compared. Investigation of most vivid errors was performed, speech rate normalization and trivial noise reduction were applied and influence on models evaluation parameters discussed. The achieved results, correlation 0.8 and 0.75 respectively for vowels and consonants, and RMSE of ~18 ms are comparable with those reported for Check, Hindi and Telugu, Korean.
Simultaneous change point analysis and variable selection in a regression problem
Authors: Y. Wu
Venue: Journal of Multivariate Analysis (2008)

In this paper, an information-based criterion is proposed for carrying out change point analysis and variable selection simultaneously in linear models with a possible change point. Under some weak conditions, this criterion is shown to be strongly consistent in the sense that with probability one, it chooses the smallest true model for large n. Its byproducts include strongly consistent estimates of the regression coefficients regardless if there is a change point. In case that there is a change point, its byproducts also include a strongly consistent estimate of the change point parameter. In addition, an algorithm is given which has significantly reduced the computation time needed by the proposed criterion for the same precision. Results from a simulation study are also presented.
Bio-terror Preparedness Exercise in a Mixed Reality Environment
Authors: Alok Chaturvedi, Chih-Hui Hsieh, Tejas Bhatt, Adam Santone
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

The paper presents a dynamic data-driven mixed reality environment to complement a full-scale bio-terror preparedness exercise. The environment consists of a simulation of the virtual geographic locations involved in the exercise scenario, along with an artificially intelligent agent-based population. The crisis scenario, like the epidemiology of a disease or the plume of a chemical spill or radiological explosion, is then simulated in the virtual environment. The public health impact, the economic impact and the public approval rating impact is then calculated based on the sequence of events defined in the scenario, and the actions and decisions made during the full-scale exercise. The decisions made in the live exercise influence the outcome of the simulation, and the outcomes of the simulation influence the decisions being made during the exercise. The mixed reality environment provides the long-term and large-scale impact of the decisions made during the full-scale exercise.
FPGA Implementation of Parallel Alpha-Beta Associative Memories
Authors: Mario Aldape-Pérez, Cornelio Yáñez-Márquez, Amadeo José Argüelles-Cruz
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

Associative memories have a number of properties, including a rapid, compute efficient best-match and intrinsic noise tolerance that make them ideal for many applications. However, a significant bottleneck to the use of associative memories in real-time systems is the amount of data that requires processing. Notwithstanding, Alpha-Beta Associative Memories have been widely used for color matching in industrial processes [1], text translation [2] and image retrieval applications [3]. The aim of this paper is to present the work that produced a dedicated hardware design, implemented on a field programmable gate array (FPGA) that applies the Alpha-Beta Associative Memories model for fingerprint verification tasks. Along the experimental phase, performance of the proposed associative memory architecture is measured by learning large sequences of symbols and recalling them successfully. As a result, a simple but efficient embedded processing architecture that overcomes various challenges involved in pattern recognition tasks is implemented on a Xilinx Spartan3 FPGA.
Constructing and Visualizing Transformation Chains
Authors: Jens Pilgrim, Bert Vanhooff, Immo Schulz-Gerlach, Yolande Berbers
Venue: Proceedings of the 4th European conference on Model Driven Architecture: Foundations and Applications (2008)

Model transformations can be defined by a chain or network of sub-transformations, each fulfilling a specific task. Many intermediate models, possibly accompanied by traceability models, are thus generated before reaching the final target(s). There is a need for tools that assist the developer in managing and interpreting this growing amount of MDD artifacts. In this paper we first discuss how a transformation chain can be modeled and executed in a transformation language independent way. We then explore how the available traceability information can be used to generate suitable diagrams for all intermediate and final models. We also propose a technique to visualize all the diagrams along with their traceability information in a single view by using a 3D diagram editor. Finally, we present an example transformation chain that has been modeled, executed and visualized using our tools.
Improved spectral relaxation methods for binary quadratic optimization problems
Authors: Carl Olsson, Anders P. Eriksson, Fredrik Kahl
Venue: Computer Vision and Image Understanding (2008)

In this paper, we introduce two new methods for solving binary quadratic problems. While spectral relaxation methods have been the workhorse subroutine for a wide variety of computer vision problems-segmentation, clustering, subgraph matching to name a few-it has recently been challenged by semidefinite programming (SDP) relaxations. In fact, it can be shown that SDP relaxations produce better lower bounds than spectral relaxations on binary problems with a quadratic objective function. On the other hand, the computational complexity for SDP increases rapidly as the number of decision variables grows making them inapplicable to large scale problems. Our methods combine the merits of both spectral and SDP relaxations-better (lower) bounds than traditional spectral methods and considerably faster execution times than SDP. The first method is based on spectral subgradients and can be applied to large scale SDPs with binary decision variables and the second one is based on the trust region problem. Both algorithms have been applied to several large scale vision problems with good performance.
Biologically-Inspired Digital Architecture for a Cortical Model of Orientation Selectivity
Authors: Cesar Torres-Huitzil, Bernard Girau, Miguel Arias-Estrada
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

This paper presents a biologically inspired modular hardware implementation of a cortical model of orientation selectivity of the visual stimuli in the primary visual cortex targeted to a Field Programmable Gate Array (FPGA) device. The architecture mimics the functionality and organization of neurons through spatial Gabor-like filtering and the so-called cortical hypercolumnar organization. A systolic array and a suitable image addressing scheme are used to partially overcome the von Neumann bottleneck of monolithic memory organization in conventional microprocessor-based system by processing small and local amounts of sensory information (image tiles) in an incremental way. A real-time FPGA implementation is presented for 8 different orientations and aspects such as flexibility, scalability, performance and precision are discussed to show the plausibility of implementing biologically-inspired processing for early visual perception in digital devices.
Dynamic Language Modeling for the European Portuguese
Authors: Ciro Martins, António Teixeira, João Neto
Venue: Proceedings of the 8th international conference on Computational Processing of the Portuguese Language (2008)

Up-to-date language modeling is recognized to be a critical aspect of maintaining the level of performance for a speech recognizer over time for most applications. In particular for applications such as transcription of broadcast news and conversations where the occurrence of new words is very frequent, especially for highly inflected languages like the European Portuguese. An unsupervised adaptation approach, which dynamically adapts the active vocabulary and language model during a multi-pass speech recognition process, is presented. Experimental results confirmed the adequacy of the proposed approaches. Experiments were carried out for a European Portuguese Broadcast News transcription system with the best preliminary results yielding a relative reduction of 65.2% in OOV word rate and 6.6% in WER.
The Complexity of Translating BLPs to RMMs
Authors: Stephen Muggleton, Niels Pahlavi
Venue: Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers (2007)

Probabilistic Logic Learning (PLL) aims at learning probabilistic logical frameworks on the basis of data. Such frameworks combine expressive knowledge representation formalisms with reasoning mechanisms grounded in probability theory. Numerous frameworks have already addressed this issue. Therefore, there is a real need to compare these frameworks in order to be able to unify them. This paper provides a comparison of Relational Markov Models (RMMs) and Bayesian Logic Programs (BLPs). We demonstrate relations between BLPs' and RMMs' semantics, arguing that RMMs encode the same knowledge as a sub-class of BLPs. We fully describe a translation from a sub-class of BLPs into RMMs and provide complexity results which demonstrate an exponential expansion in formula size, showing that RMMs are less compact than their equivalent BLPs with respect to this translation. The authors are unaware of any more compact translation between BLPs and RMMs. A full implementation has already been realized, consisting of meta-interpreters for both BLPs and RMMs and a translation engine. The equality of BLPs' and corresponding RMMs' probability distributions has been proven on practical examples.
Productive Parallel Programming: The PCN Approach
Authors: Ian Foster, Robert Olson, Steven Tuecke
Venue: Scientific Programming (1992)

We describe the PCN programming system, focusing on those features designed to improve the productivity of scientists and engineers using parallel supercomputers. These features include a simple notation for the concise specification of concurrent algorithms, the ability to incorporate existing Fortran and C code into parallel applications, facilities for reusing parallel program components, a portable toolkit that allows applications to be developed on a workstation or small parallel computer and run unchanged on supercomputers, and integrated debugging and performance analysis tools. We survey representative scientific applications and identify problem classes for which PCN has proved particularly useful.
HMF: simple type inference for first-class polymorphism
Authors: Daan Leijen
Venue: ACM SIGPLAN Notices (2008)

HMF is a conservative extension of Hindley-Milner type inference with first-class polymorphism. In contrast to other proposals, HML uses regular System F types and has a simple type inference algorithm that is just a small extension of the usual Damas-Milner algorithm W. Given the relative simplicity and expressive power, we feel that HMF can be an attractive type system in practice. There is a reference implementation of the type system available online together with a technical report containing proofs (Leijen 2007a,b).