ppxscal/embedding_network huggingface dataset:
Using Reo for Service Coordination
Authors: Alexander Lazovik, Farhad Arbab
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

In this paper we address coordination of services in complex business processes. As the main coordination mechanism we rely on a channel-based exogenous coordination language, called Reo, and investigate its application to service-oriented architectures. Reo supports a specific notion of composition that enables coordination of individual services, as well as complex composite business processes. Accordingly, a coordinated business process consists of a set of web services whose collective behavior is coordinated by Reo.
CAD on Brain, Fundus, and Breast Images
Authors: Hiroshi Fujita, Yoshikazu Uchiyama, Toshiaki Nakagawa, Daisuke Fukuoka, Yuji Hatanaka, Takeshi Hara, Yoshinori Hayashi, Yuji Ikedo, Gobert N. Lee, Xin Gao, Xiangrong Zhou
Venue: Medical Imaging and Informatics: 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers (2008)

Three computer-aided detection (CAD) projects are hosted at the Gifu University, Japan as part of the "Knowledge Cluster Initiative" of the Japanese Government. These projects are regarding the development of CAD systems for the early detection of (1) cerebrovascular diseases using brain MRI and MRA images by detecting lacunar infarcts, unruptured aneurysms, and arterial occlusions; (2) ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy using retinal fundus images; and (3) breast cancers using ultrasound 3-D volumetric whole breast data by detecting the breast masses. The brain CAD system achieves a sensitivity of 96.8% at 0.71 false positive (FP) per image for the lacunar-infarct detection, and 93.8% at 1.2 FPs per patient for the small unruptured aneurysm detection. The sensitivity and specificity for the detection of abnormal cases with arterial occlusions in MRA images are 80.0% and 95.3%, respectively. For the glaucoma detection using the retinal fundus CAD system, a sensitivity and specificity of 77.8% and 74.5% are obtained in the analysis of the optic nerve head and a sensitivity of 61.5% at 1.3 FPs per image is achieved in the detection of the retinal nerve fiber layer defects. Hemorrhages and exudates in diabetic retinopathy diagnosis are detected at a sensitivity and specificity of 84.6% and 20.6%, respectively, for the former and 76.9% and 83.3%, respectively, for the latter. For hypertensive retinopathy, the arteriolar-narrowing scheme can identify 76.2% of true positives at 1.4 FPs per image. For the breast CAD system, the image viewer that constructs the breast volume image data is developed, which also includes the CAD function with a sensitivity of 80.5% at 3.8 FPs per breast. The CAD schemes are still being improved for all the systems along with an increase in the number of image databases. Clinical examinations will be started soon, and commercialized CAD systems for the above subjects will appear by the completion of this project.
Fluctuationlessness approximation towards orthogonal hyperprismatic grid construction
Authors: Burcu Tunga, Metin Demiralp
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

The main purpose of this work is to construct transformations which map the nodes created by the individual matrix representations N independent variables to the hypegrid nodes where the values of an N variate functions are given. Recent works of the Demiralp's group show that the matrix representation of a multivariate function can be approximated by the image of its independent variable matrix representations under that function at the fluctuationlessness limit. This brings the possibility of using only N dimensional cartesian space points which are characterized by N-tuples whose elements are the eigenvalues of the matrix representations of those independent variable. However, these points may not match the points where the values of the function under consideration are given. Hence, N-dimensional shifts of the eigenvalue based points to data given points is requiered. This can be done by using certain polynomial interpolations. This work aims at the evaluation of those polynomials.
A Hypothesis on How the Neocortex Extracts Information for Prediction in Sequence Learning
Authors: Weiyu Wang
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

From the biological view, each component of a temporal sequence is represented by neural code in cortical areas of different orders. In whatever order areas, minicolumns divide a component into sub-components and parallel process them. Thus a minicolumn is a functional unit. Its layer IV neurons form a network where cell assemblies for sub-components form. Then layer III neurons are triggered and feed back to layer IV. Considering the delay, through Hebbian learning the connections from layer III to layer IV can associate a sub-component to the next. One sub-component may link multiple following sub-components plus itself, but the prediction is deterministic by a mechanism involving competition and threshold dynamic. So instead of learning the whole sequence, minicolumns selectively extract information. Information for complex concepts are distributed in multiple minicolumns, and long time thinking are in the form of integrated dynamics in the whole cortex, including recurrent activity.
Computer aided designed innovative device for measuring manufacturing forces
Authors: Mihaiela Iliescu, Marian Gheorghe
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

Manufacturing forces must be known because of their key role in determining geometrical precision of the manufactured parts, in influencing technological system's rigidity and in reducing energy consumption. The innovation of the designed device for measuring these forces consists in the elastic element, whose shape and behaviour were simulated by Finite Element Method, ANSYS Program. The device's prototype was tested so that, its rigidity characteristics and calibration equations have been determined. Used while manufacturing, both in machining and metal forming process, and aided by a LabVIEW data acquisition system, the device enabled the exact determination of manufacturing forces.
Cooperative intelligent system for manufacturing scheduling
Authors: Ana Madureira, Joaquim Santos, Ivo Pereira
Venue: Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering (2008)

Hybridization of intelligent systems is a promising research field of computational intelligence focusing on combinations of multiple approaches to develop the next generation of intelligent systems. In this paper we will model a Manufacturing System by means of Multi-Agent Systems and Meta-Heuristics technologies, where each agent may represent a processing entity (machine). The objective of the system is to deal with the complex problem of Dynamic Scheduling in Manufacturing Systems.
An Hybrid, QoS-Aware Discovery of Semantic Web Services Using Constraint Programming
Authors: José María García, David Ruiz, Antonio Ruiz-Cortés, Octavio Martín-Díaz, Manuel Resinas
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

Most Semantic Web Services discovery approaches are not well suited when using complex relational, arithmetic and logical expressions, because they are usually based on Description Logics. Moreover, these kind of expressions usually appear when discovery is performed including Quality-of-Service conditions. In this work, we present an hybrid discovery process for Semantic Web Services that takes care of QoS conditions. Our approach splits discovery into stages, using different engines in each one, depending on its search nature. This architecture is extensible and loosely coupled, allowing the addition of discovery engines at will. In order to perform QoS-aware discovery, we propose a stage that uses Constraint Programming, that allows to use complex QoS conditions within discovery queries. Furthermore, it is possible to obtain the optimal offer that fulfills a given demand using this approach.
General Solution for Supervised Graph Embedding
Authors: Qubo You, Nanning Zheng, Shaoyi Du, Yang Wu
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

Recently, Graph Embedding Framework has been proposed for feature extraction. However, it is an open issue that how to compute the robust discriminant transformation. In this paper, we first show that supervised graph embedding algorithms share a general criterion (Generalized Rayleigh Quotient). Through novel perspective to Generalized Rayleigh Quotient, we propose a general solution, called General Solution for Supervised Graph Embedding (GSSGE), for extracting the robust discriminant transformation of Supervised Graph Embedding. Finally, extensive experiments on real-world data are performed to demonstrate the effectiveness and robustness of our proposed GSSGE.
A Simulated Student Can Improve Collaborative Learning
Authors: Aurora Vizcaíno
Venue: International Journal of Artificial Intelligence in Education (2005)

This paper describes a Simulated Student architecture designed to detect and avoid three situations that decrease the benefits of learning in collaboration. These are off-topic conversations, students with passive behaviour and problems related to students' learning. In order to check the efficiency of the model in a real case a Simulated Student, which has the features described in the model, was added to a collaborative, synchronous system for learning programming. This paper describes the experiment undertaken to test the efficiency of the Simulated Student at correcting the three negative situations. The experiment showed that in the majority of the situations the Simulated Student worked correctly, thus proving that the model proposed is adequate in the avoidance of negative situations.
Support of Interviewing Techniques in Physical Access Control Systems
Authors: Svetlana N. Yanushkevich, Oleg Boulanov, Adrian Stoica, Vlad P. Shmerko
Venue: Proceedings of the 2nd international workshop on Computational Forensics (2008)

This paper investigates the enhancing of the decision-making support in the physical access control systems through deployment of the interviewing techniques widely used in forensics. While most of the physiological and behavioral information contents of the interviewee's responses can only be detected by the well-trained interviewer and supported by special devices such as lie detector, this approach is not feasible in the application such as physical access control. An alternative is the surveillance devices and biometric sensors for non-invasive registration of biometric data. In this paper, we focus on extracting the physiological and behavioral information from the video and infrared facial images. Our experiments show that the interviewing and interrogation techniques armored using the biometric assistant devices, can be employed to support the user's decision-making.
Asymmetry of Left Versus Right Lateral Face in Face Recognition
Authors: Wenfeng Chen, Chang Hong Liu, Xiaolan Fu
Venue: Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction (2007)

Prior research has found that the left side of the face is emotionally more expressive than the right side [1]. This was demonstrated in a study where the right and the left halves of a face image were combined with their mirror-reversed duplicates to make composite images. When observers were asked which composite face appeared more emotional, they selected the left-left over the right-right composite more often.
Symbolic Hybrid Programming Tool for Software Understanding
Authors: Erkki Laitila
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

Research on source code understanding has attracted computer scientists for decades. It is known [12] that the code is the functional standard for each computer system. One can assume that most functional errors can automatically be captured from code. In this paper we describe a metatheory for software understanding, with pieces of domino as a metaphor. With the help of the tiles of the game, each of the stages of the data flow in software reverse engineering can be modeled. The last element in this hybrid construction is the maintainer, who plans modifications by using symbolic code information based on previous game movements. This process was evaluated for Java.
Experiences with Mobile Games Product Line Development at Meantime
Authors: Vander Alves, Tarcísio Câmara, Carina Alves
Venue: Proceedings of the 2008 12th International Software Product Line Conference (2008)

Small and Medium Enterprises (SME) represent a significant percentage of software companies. Although there are some experience reports on using Software Product Line (SPL) techniques in SMEs, there is a lack of such reports on the Mobile Games domain. This domain is attractive both economically and technically, with a significant amount of variability, thus suggesting the use of a SPL approach. Accordingly, we conduct an exploratory study in a company in this domain, eliciting the main challenges, determining if and how SPL approaches help to address them, and raising hypotheses to guide future studies.
On-Line Probability, Complexity and Randomness
Authors: Alexey Chernov, Alexander Shen, Nikolai Vereshchagin, Vladimir Vovk
Venue: Proceedings of the 19th international conference on Algorithmic Learning Theory (2008)

Classical probability theory considers probability distributions that assign probabilities to all events (at least in the finite case). However, there are natural situations where only part of the process is controlled by some probability distribution while for the other part we know only the set of possibilities without any probabilities assigned.We adapt the notions of algorithmic information theory (complexity, algorithmic randomness, martingales, a priori probability) to this framework and show that many classical results are still valid.
Forecasting models for interval-valued time series
Authors: André Luis S. Maia, Francisco de A. T. de Carvalho, Teresa B. Ludermir
Venue: Neurocomputing (2008)

This paper presents approaches to interval-valued time series forecasting. The first and second approaches are based on the autoregressive (AR) and autoregressive integrated moving average (ARIMA) models, respectively. The third approach is based on an artificial neural network (ANN) model and the last is based on a hybrid methodology that combines both ARIMA and ANN models. Each approach fits, respectively, two models on the mid-point and range of the interval values assumed by the interval-valued time series in the learning set. The forecasting of the lower and upper bounds of the interval value of the time series is accomplished through a combination of forecasts from the mid-point and range of the interval values. The evaluation of the models presented is based on the estimation of the average behavior of the mean absolute error and mean squared error in the framework of a Monte Carlo experiment. The results demonstrate that the approaches are useful in forecasting alternatives for interval-valued time series and indicate that the hybrid model is an effective way to improve the forecasting accuracy achieved by any one of the models separately.
Computing an approximation of the 1-center problem on weighted terrain surfaces
Authors: Mark A. Lanthier, Doron Nussbaum, Tsuo-Jung Wang
Venue: Journal of Experimental Algorithmics (JEA) (2009)

In this article, we discuss the problem of determining a meeting point of a set of scattered robots R &equls; {r1, r2,&hellip;,rs} in a weighted terrain P, which has n > s triangular faces. Our algorithmic approach is to produce a discretization of P by producing a graph G &equls; {VG, EG}, which lies on the surface of P. For a chosen vertex &pprime; &isin; VG, we define &Verbar;&Pi;(ri, &pprime;)&Verbar; as the minimum weight cost of traveling from ri to &pprime;. We show that min&pprime; &isin; VG{max1&le;i&le;s {&Verbar;&Pi;(ri,&pprime;)&Verbar;}} &le; minp&ast;&isin;P{max1&le;i&le;s{&Verbar;&Pi;(ri,p&ast;)&Verbar;}} + 2W&verbar;L&verbar;, where L is the longest edge of P, W is the maximum cost weight of a face of P, and p&ast; is the optimal solution. Our algorithm requires O(snm log(snm) + snm2) time to run, where m &equals; n in the Euclidean metric and m &equals; n2 in the weighted metric. However, we show, through experimentation, that only a constant value of m is required (e.g., m &equals; 8) in order to produce very accurate solutions (< 1&percnt; error). Hence, for typical terrain data, the expected running time of our algorithm is O(sn log(sn)). Also, as part of our experiments, we show that by using geometrical subsets (i.e., 2D/3D convex hulls, 2D/3D bounding boxes, and random selection) of the robots we can improve the running time for finding &pprime;, with minimal or no additional accuracy error when comparing &pprime; to p&ast;.
Modeling software artifact count attribute withs-curves
Authors: Dick B. Simmons, William M. Lively
Venue:  (2007)

The estimation of software project attributes, such as size, is important for software project resource planning and process control. However, research regarding software attribute modeling, such as size, effort, and cost, are high-level and static in nature. This research defines a new operation-level software project attribute that describes the operational characteristic of a software project. The result is a measurement based on the s-curve parameter that can be used as a control variable for software project management. This result is derived from modeling the count of artifact instances created by the software engineering process, which are stored by software tools. Because of the orthogonal origin of this attribute in regard to traditional static estimators, this s-curve based software attribute can function as an additional indicator of software project activities and also as a quantitative metric for assessing development team capability.
Holistic approach for classifying and retrieving personal Arabic handwritten documents
Authors: Salama Brook, Zaher Al Aghbari
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

This paper presents a novel holistic technique for classifying and retrieving Arabic handwritten text documents. The retrieval of Arabic handwritten documents is performed in several steps. First, the Arabic handwritten document images are segmented into words, and then each word is segmented into its connected parts. Second, several features are extracted from these connected parts and then combined to represent a word with one consolidated feature vector. Finally, a generalized feedforward neural network is used to learn and classify the different styles/fonts into word classes, which are used to retrieve Arabic handwritten text documents.
SOPHIE: Use case and evaluation
Authors: Sinuhe Arroyo, Miguel-Angel Sicilia
Venue: Information and Software Technology (2008)

Services communicate with each other by exchanging self-contained messages. Depending on the specific requirements of the business model they serve and the application domain for which services were deployed, a number of mismatches (i.e. sequence and cardinality of messages exchanges, structure and format of messages and content semantics), can occur which prevent interoperation among a priori compatible services. This paper presents the evaluation of SOPHIE, a conceptual framework for supporting the conceptualization of ontology-based services choreographies. In doing so a three fold approach is taken that considers formal, epistemological and technical aspects. The formal evaluation tries to prove the consistency, completeness and conciseness of ontological model used. The epistemological evaluation enumerates the improvements and differentiating aspect of SOPHIE with respect to existing related work and reviews a number of application areas where the work was successfully applied. Finally, the technical feasibility evaluation tries to demonstrate the viability of the approach from the point of view of the engineering process required to allow the interaction of heterogeneous Semantic Services.
Parametric higher-order abstract syntax for mechanized semantics
Authors: Adam Chlipala
Venue: Proceeding of the 13th ACM SIGPLAN international conference on Functional programming (2008)

We present parametric higher-order abstract syntax (PHOAS), a new approach to formalizing the syntax of programming languages in computer proof assistants based on type theory. Like higher-order abstract syntax (HOAS), PHOAS uses the meta language's binding constructs to represent the object language's binding constructs. Unlike HOAS, PHOAS types are definable in general-purpose type theories that support traditional functional programming, like Coq's Calculus of Inductive Constructions. We walk through how Coq can be used to develop certified, executable program transformations over several statically-typed functional programming languages formalized with PHOAS; that is, each transformation has a machine-checked proof of type preservation and semantic preservation. Our examples include CPS translation and closure conversion for simply-typed lambda calculus, CPS translation for System F, and translation from a language with ML-style pattern matching to a simpler language with no variable-arity binding constructs. By avoiding the syntactic hassle associated with first-order representation techniques, we achieve a very high degree of proof automation.
Verification of delay insensitivity in bit-level pipelined dual-rail threshold logic adders
Authors: A. Neslin Ismailoglu, Murat Askar
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

A delay-insensitivity verification method is proposed for bit-level pipelined systolic dual-rail threshold logic adders, which achieve speed-up through early and input-incomplete carry output generation and which employ bit-wise completion at pipeline registers. The proposed method simplifies the verification task significantly, regardless of the operand length of the adder, such that analysis of three adjacent systoles for the eight possible early/late carry output generation scenarios is sufficient for detecting the input combinations which violate delay insensitivity. Using this method, structural modifications for re-establishing delay-insensitivity could be devised without sacrificing the speed-up advantages due to early carry generation. The method could also be applied to other pipelined data processing applications in dual-rail threshold logic.
Letters: Generalization of finite size Boolean perceptrons with genetic algorithms
Authors: D. M. L. Barbato, J. J. De Groote
Venue: Neurocomputing (2008)

We present an investigation of the generalization ability of finite size perceptrons with binary couplings. The results for the expected generalization error provide a guide for practical applications by establishing limits for the learning capacity of finite systems. The method applied to find solutions was the genetic algorithm, which showed to be efficient, even for values of @a larger then the Gardner-Derrida storage capacity @a"G"D=1.245, for which the number of solutions is largely reduced. We show that the generalization error of finite size networks for @a up to @a"G"D coincides with the value calculated through the statistical mechanical analysis in the thermodynamic limit.