ppxscal/embedding_network huggingface dataset:
Outsourcer selection and order tracking in a supply chain by mobile agents
Authors: Chi-Bin Cheng, Che Wang
Venue: Computers and Industrial Engineering (2008)

This study presents an automated outsourcer selection and order tracking system for alliance members within a particular supply chain named Center-Satellite Factory System, where the center factory outsources its manufacturing operations to satellite factories. The objective of the proposed system is to assist the center factory to find suitable outsourcers for a particular customer order. The system employs mobile agents to convey order and capacity information between the center factory and the potential outsourcers. The final outsourcer selection decision is based upon the capacity availability of the satellite factories and their historical track record in achieving on-time deliveries. The system provides customers with an order tracking capability such that they can monitor the status of their orders as they are executed. A prototype version of the proposed system is implemented on a web platform. To enable data exchange between different organizations, the system employs an XML (eXtensible Markup Language) data format. The capabilities of the proposed system are demonstrated using a case study involving a machining tool company in Taiwan.
Evaluation Methods for Multimodal Systems: A Comparison of Standardized Usability Questionnaires
Authors: Ina Wechsung, Anja B. Naumann
Venue: Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems (2008)

Different questionnaires assessing the usability of two multimodal systems and one unimodal system were compared. Each participant (N=21) performed several tasks with each device and was afterwards asked to rate the system by filling out different questionnaires. The results show that standardized questionnaires are applicable only to a limited extent. Despite some concordance, the results differ considerably and thus indicate the need for the development of a valid and reliable questionnaire covering the usability and quality of multimodal systems.
A Complete Axiomatic System for a Process-Based Spatial Logic
Authors: Radu Mardare, Alberto Policriti
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

The process-based Spatial Logics are multi-modal logics developed for semantics on Process Algebras and designed to specify concurrent properties of dynamic systems. On the syntactic level, they combine modal operators similar to operators of Hennessy-Milner logic, dynamic logic, arrow logic, relevant logic, or linear logic. This combination generates expressive logics, sometimes undecidable, for which a wide range of applications have been proposed.In the literature, there exist some sound proof systems for spatial logics, but the problem of completeness against process-algebraic semantics is still open. The main goal of this paper is to identify a sound-complete axiomatization for such a logic. We focus on a particular spatial logic that combines the basic spatial operators with dynamic and classical operators. The semantics is based on a fragment of CCS calculus that embodies the core features of concurrent behaviors. We prove the logic decidable both for satisfiability/validity and mode-checking, and we propose a sound-complete Hilbert-style axiomatic system for it.
Usability Engineering
Authors: C. Foltz, N. Schneider, B. Kausch, M. Wolf, C. Schlick, H. Luczak
Venue: Collaborative and Distributed Chemical Engineering. From Understanding to Substantial Design Process Support: Results of the IMPROVE Project (2008)

The number of employees working exclusively with computers increased almost 20 percent within the last four years. In technical offices and in the field of research and development the largest amount, 94 percent, can be found. Hence the focal point of the research project was composed of the development and prototypical implementation of software tools for the support of the work of process development engineers. This field of application provides a large range of innovative computer support because of its high amount of creative work processes hardly to support by strictly structured software tools. Additionally the exploration of many design alternatives and weakly structured constraints between different activities with unexpected or planned iterations can scarcely supported in a conventional way. For this research objective several specialized applications were developed and the ergonomics of their user interfaces were evaluated. These application specific evaluation methods form the groundwork for the redesign based on the design recommendations.The following section describes the foundations of software ergonomics with corresponding international norms. It will also be shown, that software ergonomics knowledge alone, however, is not sufficient in order to be able to assess the quality of the software support. So the well known ergonomic requirements were supplemented by methods for work analysis. In general, the support of creative and communicative work processes requires a detailed analysis of necessary activities, organizational structure, and information flow including the identification of organizational bottlenecks. The basis for the conducted evaluation of work thus constitute three different models of work analysis which are introduced and discussed.A suitable procedure was presented, not only for the development of evaluation criteria, but also for application scenarios for the following evaluation of subjects. The scenarios will be briefly described, and the results of the various evaluations of subjects will be introduced. These findings show the quality of the developed prototypes in terms of their area of application and give recommendations for possible improvements.
Concurrency Analysis for Shared Memory Programs with Textually Unaligned Barriers
Authors: Yuan Zhang, Evelyn Duesterwald, Guang R. Gao
Venue: Languages and Compilers for Parallel Computing: 20th International Workshop, LCPC 2007, Urbana, IL, USA, October 11-13, 2007, Revised Selected Papers (2007)

Concurrency analysis is a static analysis technique that determines whether two statements or operations in a shared memory program may be executed by different threads concurrently. Concurrency relationships can be derived from the partial ordering among statements imposed by synchronization constructs. Thus, analyzing barrier synchronization is at the core of concurrency analyses for many parallel programming models. Previous concurrency analyses for programs with barriers commonly assumed that barriers are named or textually aligned. This assumption may not hold for popular parallel programming models, such as OpenMP, where barriers are unnamed and can be placed anywhere in a parallel region, i.e., they may be textually unaligned. We present in this paper the first interprocedural concurrency analysis that can handle OpenMP, and, in general, programs with unnamed and textually unaligned barriers.We have implemented our analysis for OpenMP programs written in C and have evaluated the analysis on programs from the NPB and SpecOMP2001 benchmark suites.
Ensembling Extreme Learning Machines
Authors: Huawei Chen, Huahong Chen, Xiaoling Nian, Peipei Liu
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Extreme learning machine (ELM) is a novel learning algorithm much faster than the traditional gradient-based learning algorithms for single-hidden-layer feedforward neural networks (SLFNs). Neural network ensemble is a learning paradigm where several neural networks are jointly used to solve a problem. In our work, we investigated the performance of ELMs ensemble on regression problems. A simple ensembling approach Product Index based Excluding ensemble(PIEx) was proposed to ensemble accurate and diverse member networks. The experimental results show that the ensemble can effectively improve the performance compared with the generalization ability of single ELM and PIEx outperforms Bagging and Simple Averaging. The results also show ELM training can generate diverse neural networks even though using the same training set.
The Travelling Salesman Problem in Bounded Degree Graphs
Authors: Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

We show that the travelling salesman problem in bounded-degree graphs can be solved in time $O\bigl((2-\epsilon)^n\bigr)$, where &epsilon;> 0 depends only on the degree bound but not on the number of cities, n. The algorithm is a variant of the classical dynamic programming solution due to Bellman, and, independently, Held and Karp. In the case of bounded integer weights on the edges, we also present a polynomial-space algorithm with running time $O\bigl((2-\epsilon)^n\bigr)$ on bounded-degree graphs.
A Format for a Graphical Communications Protocol
Authors: Lorenzo Aguilar
Venue: IEEE Computer Graphics and Applications (1986)

This article describes the requirements for a graphical format on which a graphical on-line communications protocol can be based. It is argued that on-line graphical communications is similar to graphical session capture, and thus we propose an Interactive Graphical Communications Format using the GKSM session metafile. The discussion includes items that complement the GKSM metafile as a format for on-line interactive exchanges. One key application area of such a format is multimedia on-line conferencing. Therefore, we present a conferencing software architecture for processing the proposed format. This format specification is made available to those planning multimedia conferencing systems, as a contribution toward the development of a graphical communication protocol that will permit the interoperation of these systems.
A Field Evaluation of Natural Language for Data Retrieval
Authors: M. Jarke
Venue: IEEE Transactions on Software Engineering (1985)

Although a large number of natural language database interfaces have been developed, there have been few empirical studies of their practical usefulness. This paper presents the design and results of a field evaluation of a natural language system-NLS-used for data retrieval.
Scenario Argument Structure vs Individual Claim Defeasibility: What Is More Important for Validity Assessment?
Authors: Boris A. Galitsky, Sergei O. Kuznetsov
Venue: Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning (2008)

We conduct comparative analysis of two sources of argumentation-related information to assess validity of scenarios of interaction between agents. The first source is an overall structure of a scenario, which included communicative actions in addition to attack relations and is learned from previous experience of multi-agent interactions. In our earlier studies we proposed a concept-based learning technique for this source. Scenarios are represented by directed graphs with labeled vertices (for communicative actions) and arcs (for temporal and attack relations). The second source is a traditional machinery to handle argumentative structure of a dialogue, assessing the validity of individual claims. We build a system where data for both sources are visually specified, to assess a validity of customer complaints. Evaluation of contribution of each source shows that both sources of argumentation-related information are essential for assessment of multi-agent scenarios. We conclude that concept learning of scenario structure should be augmented by defeasibility analysis of individual claims to successfully reason about scenario truthfulness.
Fast Divide-and-Conquer Algorithms for Preemptive Scheduling Problems with Controllable Processing Times --- A Polymatroid Optimization Approach
Authors: Natalia V. Shakhlevich, Akiyoshi Shioura, Vitaly A. Strusevich
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

We consider a variety of preemptive scheduling problems with controllable processing times on a single machine and on identical/uniform parallel machines, where the objective is to minimize the total compression cost. In this paper, we propose fast divide-and-conquer algorithms for these scheduling problems. Our approach is based on the observation that each scheduling problem we discuss can be formulated as a polymatroid optimization problem. We develop a novel divide-and-conquer technique for the polymatroid optimization problem and then apply it to each scheduling problem. We show that each scheduling problem can be solved in $ \O({\rm T}_{\rm feas}(n) \times\log n)$ time by using our divide-and-conquer technique, where n is the number of jobs and Tfeas(n) denotes the time complexity of the corresponding feasible scheduling problem with n jobs. This approach yields faster algorithms for most of the scheduling problems discussed in this paper.
Feature selection strategies for poorly correlated data: correlation coefficient considered harmful
Authors: Silang Luo, David Corne
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Feature selection is often found to be an essential pre-processing step when data mining is applied to many-attribute datasets (e.g. several hundred or thousands of attributes). Feature selection aims to pre-select a relatively small number of attributes, thus speeding up further processing and (hopefully) eliminating data that have minimal or no discriminatory power. Often, feature selection is done on the basis of the straightforward statistical correlation, discarding features that have the lowest correlation with the target class(es). However, when these correlation values tend to be rather low for all features (common in many datasets of importance), the basis for pre-selection of any specific set of features is undermined, and straightforward feature selection may do more harm than good. We confirm this by investigating the performance of five feature selection strategies on several datasets with varying overall correlation values, finding that statistical correlation is never the best choice for poorly correlated data. The most reliable methods among those tested are either no feature selection, or Evolutionary Algorithm feature selection.
Design of high performance mimo receiver: algorithms and vlsi architectures
Authors: Poras T. Balsara
Venue:  (2008)

Multi-carrier modulation (OFDM), iterative error-correction-coding (Turbo and LDPC codes) have potential for enabling high capacity data-centric reliable wireless network. However, multiple-input multiple-output (MIMO), the most significant technical breakthroughs in modern communications, has shown the most profound effect on the capacity and reliability of wireless networks. The performance improvements resulting from MIMO come at the cost of increased computational complexity and power consumption in the wireless receiver. Owing to the requirements of the portable mobile devices, the design of high throughput system with lower complexity and power is one of the key challenges in MIMO receiver design. Currently available DSP processors lack the capability to achieve such conflicting and stringent requirements. The largest potential for complexity and power reduction of highest-performance VLSI circuits for MIMO receiver lies in the joint optimization of algorithms and the architectures with circuit level trade-offs in mind. This dissertation proposes a high performance MIMO receiver design by joint optimization between architectures and algorithms. Firstly, we propose minimum wordlength and precision requirements to ensure negligible performance degradation of several MIMO architectures that include diversity through space-time block codes (STBCs) and detection of spatial multiplexing (SM) using sub-optimal and near-optimal detection algorithms under finite word-length based on results from extensive simulations. We also propose a procedure to quantify the decision-point SNR for MIMO receiver. Secondly, we propose a low latency, low complexity scalable VLSI architecture for QR decomposition, an essential pre-computation for many receiver algorithms, based on modified Gram-Schmidt algorithm. Lastly, we propose pruned K-Best algorithm for near maximum likelihood (ML) detection of SM scheme. The pruned K-Best algorithm enables a high throughput and low complexity VLSI architectures for SM detection. The proposed architectures for four transmit and four receive SM architectures with 16-QAM requires 13 clock cycles to detect 16 bits and achieves a throughput of 246.15 Mbps and power consumption of 200mW at 75K gates when implemented in 0.18um CMOS process. The proposed architecture is scalable for any QAM constellation and number of transmit antennas. The scalability is shown by extending the architectures to 64-QAM constellation. We conclude this dissertation by describing a comprehensive MIMO receiver design by covering most commonly adopted MIMO architectures.
A Simple Scaling Algorithm Based on Areas Pixels
Authors: Alain Horé, François Deschênes, Djemel Ziou
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

In this paper, we propose a new scaling algorithm which performs the scaling up/down transform using an area pixel model rather than a point pixel model. The proposed algorithm uses a variable number of pixels of an original image to calculate a pixel of the scaled image. Our algorithm has good characteristics such as fine-edge and good smoothness. Different quality parameters (standard deviation, root mean square error, aliasing, edge map) are used to compare our algorithm with four image scaling algorithms: nearest neighbour, bilinear, bicubic and winscale algorithms. The results show that our algorithm generally produces images of better quality with few aliasing, few blur and high contrast.
Parallel Imaging Problem
Authors: Thành Nguyen, Éva Tardos
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

Metric Labeling problems have been introduced as a model for understanding noisy data with pair-wise relations between the data points. One application of labeling problems with pair-wise relations is image understanding, where the underlying assumption is that physically close pixels are likely to belong to the same object.In this paper we consider a variant of this problem, we will call Parallel Imaging, where instead of directly observing the noisy data, the data undergoes a simple linear transformation first, such as adding different images. This class of problems arises in a wide range of imaging problems. Our study has been motivated by the Parallel Imaging problem in Magnetic Resonance Image (MRI) reconstruction. We give a constant factor approximation algorithm for the case of speedup of two with the truncated linear metric, motivated by the MRI reconstruction problem. Our method uses local search and graph cut techniques.
A Novel Filtering and Fusion Algorithm for Sequence Image Matching Navigation
Authors: Fei Meng, Xiaogang Yang, Peng Sun, Shicheng Wang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

In order to improve the reliability and matching precision of image matching navigation system, a novel filtering and fusion algorithm for sequence image matching is proposed. The essence of the matching results filtering and fusion problems for aircraft matching navigation system is firstly analyzed. Then, a new Windows Median Filter (WMF) is designed to filtering the longitudinal matching position sequence. Furthermore, based on Least Squares Estimate (LSE) method, the filtering and fusion algorithm is presented, the principle and flowchart of the algorithm is given. Simulation experiments and practical examples show the feasibility and availability of the proposed algorithm in eliminating the mismatching points and random matching disturbance for sequence image matching navigation system.
Resource Management in a Multi-agent System by Means of Reinforcement Learning and Supervised Rule Learning
Authors: Bartłomiej Śnieżyński
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

In this paper two learning methods are presented: reinforcement learning and supervised rule learning. The former is a classical approach to a learning problem in multi-agent systems. The latter is a novel approach, according to the author's knowledge, which has several advantages. Both methods are used for resource management in a multi-agent system. The environment is a Fish Bank game, where agents manage fishing companies. Both learning methods are applied to generate ship allocation strategy. In this article the system architecture and learning processes are described and experimental results comparing the performance of implemented types of agents are presented.
The F-R Model of Teaching in Chinese Universities
Authors: Hui Zhao, Yanbo Huang, Jing Zhang
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

In view of the teaching characteristics of the full-time universities in China, the paper probes into the application of web-based teaching platform and the new model of teaching---the F-R model of teaching that integrates the rigid teaching management with the flexible curricula teaching to make full use of the teaching resources and enhance the teaching efficiency. The new model of teaching not only assures the integrity of the students' knowledge system but also emphasizes the individual difference. It provides a way to cultivate students' personality and develop the students' ability to analyze and solve the actual problems that are necessary for the full-development and innovative person in modern society.
VICUR: A human-vision-based algorithm for curve reconstruction
Authors: Thanh An Nguyen, Yong Zeng
Venue: Robotics and Computer-Integrated Manufacturing (2008)

In this paper, a new algorithm, named VICUR, is presented for curve reconstruction problem. From a set of unorganized points, the proposed algorithm can construct curves that look natural to human vision. The VICUR algorithm is based on two connectivity criteria: proximity and good continuation from the prominent Gestalt principles of perception. Experimental results are presented to show the effectiveness of VICUR.
Laparoscopic Tool Tracking Method for Augmented Reality Surgical Applications
Authors: Alicia M. Cano, Francisco Gayá, Pablo Lamata, Patricia Sánchez-González, Enrique J. Gómez
Venue: Proceedings of the 4th international symposium on Biomedical Simulation (2008)

Vision-based tracking of laparoscopic tools offers new possibilities for improving surgical training and for developing new augmented reality surgical applications. We present an original method to determine not only the tip position, but also the orientation of a laparoscopic tool respect to the camera coordinate frame. A simple mathematical formulation shows how segmented tool edges and camera field of view define the tool 3D orientation. Then, 3D position of the tool tip is determined by image 2D coordinates of any known point of the tool and by tool's diameter. Accuracy is evaluated in real image sequences with known ground truth. Results show a positioning error of 9,28 mmRMS, what is explained by inaccuracies in the estimation of tool edges. The main advantage of proposed method is its robustness to occlusions of the tool tip.