ppxscal/embedding_network huggingface dataset:
Fuzzy Classification with Multi-objective Evolutionary Algorithms
Authors: Fernando Jiménez, Gracia Sánchez, José F. Sánchez, José M. Alcaraz
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

In this work we propose, on the one hand, a multi-objective constrained optimization model to obtain fuzzy models for classification considering criteria of accuracy and interpretability. On the other hand, we propose an evolutionary multi-objective approach for fuzzy classification from data with real and discrete attributes. The multi-objective evolutionary approach has been evaluated by means of three different evolutionary schemes: Preselection with niches, NSGA-II and ENORA. The results have been compared in terms of effectiveness by means of statistical techniques using the well-known standard Iris data set.
Space-Time Multi-Resolution Banded Graph-Cut for Fast Segmentation
Authors: Tobi Vaudrey, Daniel Gruber, Andreas Wedel, Jens Klappstein
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

Applying real-time segmentation is a major issue when processing every frame of image sequences. In this paper, we propose a modification of the well known graph-cut algorithm to improve speed for discrete segmentation. Our algorithm yields real-time segmentation, using graph-cut, by performing a single cut on an image with regions of different resolutions, combining space-time pyramids and narrow bands. This is especially suitable for image sequences, as segment borders in one image are refined in the next image. The fast computation time allows one to use information contained in every image frame of an input image stream at 20 Hz, on a standard PC. The algorithm is applied to traffic scenes, using a monocular camera installed in a moving vehicle. Our results show the segmentation of moving objects with similar results to standard graph-cut, but with improved speed.
Diagrammatic Interrelationships between Global and Local Algebraic Visual Objects: Communicating the Visual Abstraction
Authors: Julie Tolmie
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

This poster considers mathematical diagrams composed of algebraic visual objects where the role of words and symbols has been explicitly removed with the intention of (re)assigning that role to visual object. Interrelationships between global and local algebraic visual objects become the working abstraction in the space, but challenge text. This transposition is juxtaposed against the historical parallel of early western musical notation, the music as language vs. music as space conflict targeted in the Papal Bull of 1324-25.
In the Moodie: Using `Affective Widgets' to Help Contact Centre Advisors Fight Stress
Authors: Nicola Millard, Linda Hole
Venue: Affect and Emotion in Human-Computer Interaction: From Theory to Applications (2008)

This paper describes an user experience study of a particular `affective widget' - called a `moodie'. This onscreen device helps to paint an emotional picture of the day of a contact centre employee. These users undertake work that can be classified as `emotional labour' [10] - in other words they may have to express emotions whilst on a customer telephone call that they may not necessarily feel, both about the customer and the technology that they are using to mediate the conversation. This often leads to user stress, a poor customer experience and high staff churn. Moodies were designed as part of a prototype interface called a Motivational User Interface (MUI). They were created as a way of expressing and self reporting the emotional responses that users feel throughout the day. These prototype affective widgets were then evaluated by contact centre employees and their managers.
Auto Exposure Control for Multiple-Slope Cameras
Authors: André Gooßen, Marcus Rosenstiel, Simon Schulz, Rolf-Rainer Grigat
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

The dynamic range of natural scenes usually exceeds the dynamic range of imaging sensors by several orders of magnitude. To overcome information loss multiple-slope cameras allow acquisition of images at extended dynamic ranges. However the response curve still has to be adapted to the scene. We present a new auto exposure control for multiple-slope cameras. The proposed method derives an optimum response curve in terms of recorded information. It considers dynamic range expansion as well as the resulting coarsening of quantization. We evaluated our method by simulation and implementation for an actual multiple-slope camera.
Composable modeling and distributed simulation framework for discrete supply-chain systems with predictive control
Authors: Dongping Huang
Venue:  (2008)

Supply-chain networks such as semiconductor manufacturing systems exhibit a high degree of structural and behavioral complexity. Simulation modeling concepts, approaches, and tools are the primary means for analysis and design of intricate behavior and relationships found in many of today's supply-chain networks. A fundamental barrier in developing rigorous simulation models of supply-chain systems is the necessity of using inherently different kinds of models and simulators. This is because no single modeling and simulation framework has been shown to adequately represent, at a realistic level of detail, a supply-chain system with tactical (short-term) control and strategic (long-term) planning policies. Composition of disparate model types affords rigorous synthesis of complementary classes of simulation, control, and optimization models. A novel framework using an approach called Knowledge Interchange Broker (KIB) was developed for composing the distinct classes of Discrete Event System Specification (DEVS), Model Predictive Control (MPC), and Linear Optimization (LP) models. First, the KIB model composability approach was employed to compose DEVS and MPC modeling formalisms. A KIBDEVS/MPC was developed and used to create a hybrid DEVSJAVA/MATLAB prototype environment. The benefits of simulating combined discrete-event and control-theoretic models was demonstrated against a scaled prototypical semiconductor supply-chain system. Then, the KIBDEVS/LP/MPC was developed to support composing models that can be described in DEVS, MPC, and LP modeling formalism. This novel KIB provides a set of suitable message mappings and transformations. A causal parallel execution protocol with logical time synchronization was devised and used to develop a prototype distributed simulation framework for DEVSJAVA, MATLAB, and OPLStudio, a linear optimization tool. The resulting simulation framework offers a basis for modeling complex discrete-part systems and, in particular, semiconductor manufacturing supply-chain systems.
Interactive Clothes Design Support System
Authors: Yuki Ogata, Takehisa Onisawa
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

This paper proposes a clothes design support system. Interactive Genetic Algorithms are applied to the support system in order to reflect users's Kansei to clothes design. The system presents several designed clothes candidates to a user and a user evaluates them. According to user's evaluation, the system gives genetic algorithms (GA) operations, selection, crossover and mutations, to clothes candidates. Repeating the procedures, presentation, evaluation and GA operations, satisfying clothes are obtained. Subjects experiments are performed to verify usefulness of the presented system.
Computational complexity simplified
Authors: Ahmed Tarek
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

There exists a variety of techniques for the computational complexity analysis of algorithms and functions. This analysis is imperative to the algorithmic and the functional performance. Besides the big-oh complexity, there are other complexity notations, such as Ω, Θ, small o and small ω notational complexities. Complexity analysis is used to select an appropriate algorithm for solving a given problem using computer. Unfortunately, most of the prevailing approaches lack in simplicity and consistency. Existing techniques are complex, and rather difficult to practice in applications. There is a trend to exploit the notational complexities in the existing literature by treating those as functions instead of sets. In this paper, different notational complexities and their paradigms are studied from the new perspectives. Simplified and consistent approaches are introduced that will make the analysis even simpler and easier to follow. Abused notational complexities are analyzed through the appropriate approach.
Utility-Based Regression
Authors: Luis Torgo, Rita Ribeiro
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

Cost-sensitive learning is a key technique for addressing many real world data mining applications. Most existing research has been focused on classification problems. In this paper we propose a framework for evaluating regression models in applications with non-uniform costs and benefits across the domain of the continuous target variable. Namely, we describe two metrics for asserting the costs and benefits of the predictions of any model given a set of test cases. We illustrate the use of our metrics in the context of a specific type of applications where non-uniform costs are required: the prediction of rare extreme values of a continuous target variable. Our experiments provide clear evidence of the utility of the proposed framework for evaluating the merits of any model in this class of regression domains.
A model of the digital tool promoting the teacher's instructional innovation
Authors: Rong-Jyue Fang, Hung Jen Yang, Hua Lin Tsai, Chi Jen Lee, Dai-Hua Li
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

This study intends to investigate Digital Assistant (PDA) is net devices and its application in education. The study went through literature review and staged interview. The interview process targeted on students and parents from an experimental primary class located in Kaohsiung County, southern Taiwan, They all joined the digital experimental project in that specific primary school. In the experimental period each parents in that class were distributed a PHS phone. Through message transmission and mobile net communication, parents discussed and shared feelings with teacher and other parents through using mobile devices (pros & cons). Finally, as reference material, it concludes by making suggestions for educational government authorities, primary school administration departments and teachers who utilize PDAs to achieve teaching innovation.
Production improving in gas lift wells using nodal analysis
Authors: Edgar Camargo, José Aguilar, Addison Ríos, Francklin Rivas, Joseph Aguilar-Martin
Venue: Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation (2008)

In this work, a gas lift-based oil production wells improvement technique is presented. This technique is based on Nodal Analysis, which is applied to well head level, where the production data are available. Thus, a production model is obtained, representing the production curve. This model allows calculating the production flow and pressure drop relation that can be found in all the components of the completion system. So, it will be possible to determine the oil or gas flow that can be produced by the well, considering the perforation and completion geometry. With this information, we can build a production optimization system in order to increase the production flow rate.
Challenges in the Design and Development of Context-Aware Applications
Authors: Jadwiga Indulska
Venue: Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing (2008)

Context-awareness plays an important role in pervasive computing as adaptations of applications to context changes (changes in computing environment and in user activities/tasks) help to achieve the goal of computing services available everywhere and at any time. There is a growing body of research on context-aware applications that are adaptable and capable of acting autonomously on behalf of users. However, there are still many open research issues that challenge the pervasive computing community. In this talk I discuss several of these research challenges. First, I outline the state of the art in context information modelling, management and reasoning as well as possible future research directions in this area. This is followed by a discussion of context information management that allows development of fault-tolerant and autonomic context-aware applications. As one of the challenges inhibiting the development of context-aware applications is their complexity, I discuss software engineering approaches that ease the task of developing such applications. Context-aware applications adapt to context changes using context information. However this context information may be imprecise or erroneous and therefore can lead to incorrect adaptation decisions creating usability problems and affecting acceptance of context-aware applications. This creates a need for some balance between autonomy of context-aware applications and the user control of the applications. I describe some early approaches my team is working on to tackle this problem. Finally, I discuss research issues related to privacy of context information and how context can be used to enhance security mechanisms within pervasive computing environments.
Reheat Steam Temperature Composite Control System Based on CMAC Neural Network and Immune PID Controller
Authors: Daogang Peng, Hao Zhang, Ping Yang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Reheat steam circle system is usually used in modern super-high parameters unit of power plant, which has the characteristics of long process channel, large inertia and long time lag, etc. Thus conventional PID control strategy cannot achieve good control performance. Prompted by the feedback regulation mechanism of biology immune response and the virtues of CMAC neural network, a composite control strategy based on CMAC neural network and immune PID controller is presented in this paper, which has the effect of feed-forward control for load changes as the unit load channel signal of reheat steam temperature is transmitted to the CMAC neural network to take charge of load change effects. The input signal of the controlled system are weighted and integrated by the output signals of CMAC neural network and immune PID controller, and then a variable parameter robust controller is constituted to act on the controlled system. Thus, good regulating performance is guaranteed in the initial control stage and also in case of characteristic deviations of the controlled system. Simulation results show that this control strategy is effective, practicable and superior to conventional PID control.
Perfect DCJ Rearrangement
Authors: Sèverine Bérard, Annie Chateau, Cedric Chauve, Christophe Paul, Eric Tannier
Venue: Proceedings of the international workshop on Comparative Genomics (2008)

We study the problem of transforming a multichromosomal genome into another using Double-Cut-and-Join (DCJ) operations. We introduce the notion of DCJ scenario that does not break families of common intervals (groups of genes co-localized in both genomes). Such scenarios are called perfect, and generalize the notion of perfect reversal scenarios. While perfect sorting by reversals is NP-hard if the family of common intervals is nested, we show that finding a shortest perfect DCJ scenario can be answered in polynomial time in this case. Moreover, while perfect sorting by reversals is easy when the family of common intervals is weakly separable, we show that the corresponding problem is NP-hard in the DCJ case. These contrast with previous comparisons between the reversal and DCJ models, that showed that most problems have similar complexity in both models.
Dialogue Modes in Expert Tutoring
Authors: Whitney L. Cade, Jessica L. Copeland, Natalie K. Person, Sidney K. D'Mello
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Previous studies have examined human-to-human dialogue in expert tutoring on the speech act level, but these analyses fail to provide the context necessary for understanding how a series of speech acts relate to each other. This research examined tutorial dialogue in terms of sustained, pedagogically distinct phases, referred to as tutoring "modes", which gives context to the finer-grained analysis of "moves". Our accomplishments were twofold: we developed a new annotation scheme for tutorial dialogue that takes into account clusters of multiple dialogue moves, and we determined the extent to which these modes occurred in the tutoring sessions. We also examined likely sequences of modes, all of which are important factors when building an ITS that reproduces the efforts of expert human tutors.
A Simple Linear Time Algorithm for the Isomorphism Problem on Proper Circular-Arc Graphs
Authors: Min Chih Lin, Francisco J. Soulignac, Jayme L. Szwarcfiter
Venue: Proceedings of the 11th Scandinavian workshop on Algorithm Theory (2008)

A circular-arc model $ {\mathcal {M}} =(C,\mathcal{A})$ is a circle C together with a collection $\mathcal{A}$ of arcs of C. If no arc is contained in any other then $\mathcal{M}$ is a proper circular-arc model, and if some point of C is not covered by any arc then ${\mathcal{M}}$ is an interval model. A (proper) (interval) circular-arc graph is the intersection graph of a (proper) (interval) circular-arc model. Circular-arc graphs and their subclasses have been the object of a great deal of attention in the literature. Linear time recognition algorithms have been described both for the general class and for some of its subclasses. For the isomorphism problem, there exists a polynomial time algorithm for the general case, and a linear time algorithm for interval graphs. In this work we develop a linear time algorithm for the isomorphism problem in proper circular-arc graphs, based on uniquely encoding a proper circular-arc model. Our method relies on results about uniqueness of certain PCA models, developed by Deng, Hell and Huang in [6]. The algorithm is easy to code and uses only basic tools available in almost every programming language.
Comparison of Numerical Models of Impact Force for Simulation of Earthquake-Induced Structural Pounding
Authors: Robert Jankowski
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Structural pounding during earthquakes is a complex phenomenon involving plastic deformations, local cracking, etc. The aim of the present paper is to check the accuracy of three pounding force numerical models, such as: the linear viscoelastic model, the non-linear elastic model following the Hertz law of contact and the non-linear viscoelastic model. In the analysis, the results of numerical simulations have been compared with the results of an impact experiment conducted by dropping balls of different building materials. The results of the study indicate that the non-linear viscoelastic model is the most precise one in simulating the pounding force time history during impact.
A Compact Arabic Lexical Semantics Language Resource Based on the Theory of Semantic Fields
Authors: Mohamed Attia, Mohsen Rashwan, Ahmed Ragheb, Mohamed Al-Badrashiny, Husein Al-Basoumy, Sherif Abdou
Venue: Proceedings of the 6th international conference on Advances in Natural Language Processing (2008)

Applications of statistical Arabic NLP in general, and text mining in specific, along with the tools underneath perform much better as the statistical processing operates on deeper language factorizations than on raw text. Lexical semantic factorization is very important in this regard due to its feasibility, high level of abstraction, and the language independence of its output.In the core of such a factorization lies an Arabic lexical semantic DB. While building this LR, we had to go beyond the conventional exclusive collection of words from dictionaries and thesauri that cannot alone produce a satisfactory coverage of this highly inflective and derivative language.This paper is hence devoted to the design and implementation of an Arabic lexical semantics LR that enables the retrieval of the possible senses of any given Arabic word at a high coverage.Instead of tying full Arabic words to their possible senses, our LR flexibly relates morphologically and PoS-tags constrained Arabic lexical compounds to a predefined limited set of semantic fields across which the standard semantic relations are defined. With the aid of the same large-scale Arabic morphological analyzer and PoS tagger in the runtime, the possible senses of virtually any given Arabic word are retrievable.
Browsing Assistance Service for Intranet Information Systems
Authors: Peter Géczy, Noriaki Izumi, Shotaro Akaho, Kôiti Hasida
Venue: Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects (2008)

Improved usability and efficiency of organizational information systems brings economical benefits to the organization and time benefits to the users. We present a browsing assistance service suitable for the organizational intranet environments. It helps users to shorten their browsing interactions and achieve their goals faster. These benefits are accomplished by providing relevant suggestions on the potential navigation targets of interest to the users. The system design employs the analytics of user browsing behavior and its appropriate segmentation. It efficiently utilizes the initial and the terminal navigation points for providing recommendations. The performance of the system has been evaluated on the real world data of a large scale intranet portal.
Distributed Self-Pruning(DSP) Algorithm for Bridges in Clustered Ad Hoc Networks
Authors: Seok Yeol Yun, Hoon Oh
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

In clustered ad hoc networks, it is often required that a clusterhead, a leader of cluster, send a message to all its neighbor clusterheads. One simple approach is to use a flooding scheme in which every bridge node receiving a message simply relays it only if it receives the message for the first time. However, the flooding tends to degrade network efficiency severely because many bridges relay the message unnecessarily, causing neighbor clusterheads to receive multiple copies of the same message along different paths. A distributed self-pruning algorithm proposed in this paper attacks this problem.
Refining Existing Theories of Program Comprehension During Maintenance for Concurrent Software
Authors: Scott D. Fleming, Eileen Kraemer, R. E. K. Stirewalt, Laura K. Dillon, Shaohua Xie
Venue: Proceedings of the 2008 The 16th IEEE International Conference on Program Comprehension (2008)

While the sources of complexity in the initial design and verification of multi-threaded software systems are well-documented, less is known of the issues specific to the maintenance of these systems. The literature contains a number of observational studies of programmers performing maintenance, conducted in the context of sequential software and designed to investigate the factors and behaviors that lead to success. To help fill the gap in knowledge in the area of concurrent software maintenance, we conducted a study that refines the findings of two prior studies, those of Littman et al. and of Vessey, to address issues and obstacles that arise in the understanding of concurrent software. We validated these refinements by observing programmers performing corrective maintenance on a small but complex multi-threaded server program.