ppxscal/embedding_network huggingface dataset:
Realization of Multi-Delay Filter Using Fermat Number Transforms
Authors: Hamzé Haidar Alaeddine, El Houssaïn Baghious, Guillaume Madre, Gilles Burel
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

This paper is about an efficient implementation of adaptive filtering for echo cancelers. The first objective of this paper is to propose a simplified method of the flexible block Multi-Delay Filter (MDF) algorithm in the time-domain. Then, we will derive a new method for the step-size adaptation coefficient. The second objective is about the realization of a Block Proportionate Normalized Least Mean Squares (BPNLMS++) with the simplified MDF (SMDF) implementation. Using the new step-size method and the smaller block dimension proposed by SMDF, we achieve a faster convergence of the adaptive process with a limited computational cost. Then, an efficient implementation of the new procedure (SMDF-BPNLMS++) block filtering is proposed using Fermat Number Transform, which can significantly reduce the computation complexity of filter implantation on Digital Signal Processor.
Max-min optimality of service rates in queueing systems with customer-average performance criterion
Authors: Li Xia, Ming Xie, Wenjun Yin, Jin Dong
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

In this paper, we consider the optimization of service rates in queueing systems, especially in closed Jackson networks. The optimization criterion is the customer-average performance, which is another important performance metric compared with the traditional time-average performance. Based on the methodology of perturbation analysis, we can derive a performance difference equation when the service rates are changed. With this difference equation, we find the optimal service rates have a Max-Min property, i.e., the optimal service rates can be chosen from its maximal or minimal value. This property can reduce the complexity of this type of optimization problems. Moreover, we also prove the max-min optimality is valid for both state-dependent service rates and load-dependent service rates in queueing systems.
Humanitarian Information Management and Systems
Authors: Bartel Walle, Gerd Eede, Willem Muhren
Venue: Mobile Response: Second International Workshop on Mobile Information Technology for Emergency Response, MobileResponse 2008. Bonn, Germany, May 29-30, 2008, Revised Selected Papers (2009)

In times of major disasters such as hurricane Katrina or the Sichuan earthquake, the need for accurate and timely information is as crucial as is rapid and coherent coordination among the responding humanitarian community. Effective humanitarian information systems that provide timely access to comprehensive, relevant, and reliable information are critical to humanitarian operations. The faster the humanitarian community is able to collect, analyze, disseminate and act on key information, the more effective the response will be, the better needs will be met, and the greater the benefit to the affected populations. This paper presents fundamental principles of humanitarian information management as endorsed by the international humanitarian community, introduces generic systems design premises and presents two recent collaborative efforts in humanitarian information systems development.
Brief paper: Optimal solutions to a class of power management problems in mobile robots
Authors: Wei Zhang, Yung-Hsing Lu, Jianghai Hu
Venue: Automatica (Journal of IFAC) (2009)

This paper studies an approach to minimize the power consumption of a mobile robot by controlling its traveling speed and the frequency of its on-board processor simultaneously. The problem is formulated as a discrete-time optimal control problem with a random terminal time and probabilistic state constraints. A general solution procedure suitable for arbitrary power functions of the motor and the processor is proposed. Furthermore, for a class of realistic power functions, the optimal solution is derived analytically. Interpretations of the optimal solution in the practical context are also discussed. Simulation results show that the proposed method can save a significant amount of energy compared with some heuristic schemes.
Embedding human scheduling in a steel plant simulation
Authors: David Briggs
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

A simulation was commissioned to understand the interactions that constrain the capacity of a steel plant. The aim was for this to become a reusable tool that could evaluate the effect of future changes to market requirements and operational practices. This paper describes how a simulation model incorporating human decision-making was conceived and constructed. The use of simulation as a tool for knowledge capture in scheduling is considered. The resulting tool has been in use for four years and has acted as a driver to reconsider where the real processing bottlenecks are and what part scheduling can play in managing them.
A delay-optimized universal FPGA routing architecture
Authors: Wu Fang, Zhang Huowen, Duan Lei, Lai Jinmei, Wang Yuan, Tong Jiarong
Venue: Proceedings of the 2009 Asia and South Pacific Design Automation Conference (2009)

A universal FPGA routing Architecture is presented, which ensures that every module in the FPGA including CLBs and IOBs have a uniform interconnect architecture, and the load of interconnect lines is equally distributed. So, this architecture is highly repeatable and the signal delay is predictable and regular. Furthermore, the realization of the Programmable Interconnect Point (PIP) and the BUFFER driver is also optimized to benefit the signal delay up to 5%. The test results of the example chip show the reasonableness of these ideas.
Models of Interaction as a Grounding for Peer to Peer Knowledge Sharing
Authors: David Robertson, Adam Barker, Paolo Besana, Alan Bundy, Yun Heh Chen-Burger, David Dupplaw, Fausto Giunchiglia, Frank Harmelen, Fadzil Hassan, Spyros Kotoulas, David Lambert, Guo Li, Jarred Mcginnis, Fiona Mcneill, Nardine Osman, Adrian Perreau Pinninck, Ronny Siebes, Carles Sierra, Chris Walton
Venue: Advances in Web Semantics I: Ontologies, Web Services and Applied Semantic Web (2008)

Most current attempts to achieve reliable knowledge sharing on a large scale have relied on pre-engineering of content and supply services. This, like traditional knowledge engineering, does not by itself scale to large, open, peer to peer systems because the cost of being precise about the absolute semantics of services and their knowledge rises rapidly as more services participate. We describe how to break out of this deadlock by focusing on semantics related to interaction and using this to avoid dependency on a priori semantic agreement; instead making semantic commitments incrementally at run time. Our method is based on interaction models that are mobile in the sense that they may be transferred to other components, this being a mechanism for service composition and for coalition formation. By shifting the emphasis to interaction (the details of which may be hidden from users) we can obtain knowledge sharing of sufficient quality for sustainable communities of practice without the barrier of complex meta-data provision prior to community formation.
Upper bound for variational free energy of Bayesian networks
Authors: Kazuho Watanabe, Motoki Shiga, Sumio Watanabe
Venue: Machine Learning (2009)

In recent years, variational Bayesian learning has been used as an approximation of Bayesian learning. In spite of the computational tractability and good generalization in many applications, its statistical properties have yet to be clarified. In this paper, we focus on variational Bayesian learning of Bayesian networks which are widely used in information processing and uncertain artificial intelligence. We derive upper bounds for asymptotic variational free energy or stochastic complexities of bipartite Bayesian networks with discrete hidden variables. Our result theoretically supports the effectiveness of variational Bayesian learning as an approximation of Bayesian learning.
Demystifying magic: high-level low-level programming
Authors: Daniel Frampton, Stephen M. Blackburn, Perry Cheng, Robin J. Garner, David Grove, J. Eliot B. Moss, Sergey I. Salishev
Venue: Proceedings of the 2009 ACM SIGPLAN/SIGOPS international conference on Virtual execution environments (2009)

The power of high-level languages lies in their abstraction over hardware and software complexity, leading to greater security, better reliability, and lower development costs. However, opaque abstractions are often show-stoppers for systems programmers, forcing them to either break the abstraction, or more often, simply give up and use a different language. This paper addresses the challenge of opening up a high-level language to allow practical low-level programming without forsaking integrity or performance. The contribution of this paper is three-fold: 1) we draw together common threads in a diverse literature, 2) we identify a framework for extending high-level languages for low-level programming, and 3) we show the power of this approach through concrete case studies. Our framework leverages just three core ideas: extending semantics via intrinsic methods, extending types via unboxing and architectural-width primitives, and controlling semantics via scoped semantic regimes. We develop these ideas through the context of a rich literature and substantial practical experience. We show that they provide the power necessary to implement substantial artifacts such as a high-performance virtual machine, while preserving the software engineering benefits of the host language. The time has come for high-level low-level programming to be taken more seriously: 1) more projects now use high-level languages for systems programming, 2) increasing architectural heterogeneity and parallelism heighten the need for abstraction, and 3) a new generation of high-level languages are under development and ripe to be influenced.
An algorithm for studying mental tasks' power spectra along the time
Authors: Plamen Manoilov, Adriana Borodzhieva
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

In pattern recognition based Brain Computer Interfaces (BCIs) the classificator is searching the electroencephalograms' (EEG) signal for known patterns. Patterns are issued by the subject, performing tasks, evoking brain activity with different spatial and frequency distribution. As a result of weariness or inadvertence, patterns' quality decreases. This results in a lower probability of recognition of the pattern. In this paper an analysis of the power spectrum of EEG signals during the performance of some mental tasks is described with a connection of using the EEG for brain-computer interfaces, working with &alpha;- and &mu;-rhythms brain potentials. The goal of the study is to determine the effective duration of every task's performance.
Dual Phase Evolution and Self-organisation in Networks
Authors: Greg Paperin, David G. Green, Tania G. Leishman
Venue: Proceedings of the 7th International Conference on Simulated Evolution and Learning (2008)

Dual Phase Evolution (DPE) is a widespread natural process in which complex systems adapt and self-organise by switching alternately between two phases: a phase of global interactions and a phase of local interactions. We show that in evolving networks of agents, DPE can give rise to a wide variety of topologies. In particular, it can lead to the spontaneous emergence of stabilising modular structure.
Patterns of Information Retrieval in CommunicationNetworks: A Study of Transactive Memory in Organizational WorkTeams
Authors: Edward T. Palazzolo
Venue:  (2008)

As the amount of information accessible continues togrow, information retrieval becomes an increasinglycomplex process that organizational employees mustnavigate many times each day. Transactive memory (TM)theory explains how a team works as a system to gain,organize, and utilize information by sharing two ormore individuals' memories through variouscommunication processes. This book explorescommunication to retrieve information inorganizational work teams from the combinedprospective of TM theory and social networks. Here,the processes of TM theory are explicitly defined innetworks terms, thereby allowing the use of advancedsocial network analysis techniques (that is, p* orExponential Random Graph Models) for hypothesistesting and theoretical development. This research isbased on observed information retrieval patterns fromseven intact organizational work teams acrossmultiple industries.This book addresses managers, employees, andacademics who are interested in better understandingthe intertwined relationship between communicationnetworks and knowledge networks in work teams.
Qualitative Weight Assignment for Multimodal Biometric Fusion
Authors: Raghavendra R., Hemantha Kumar G, Ashok Rao
Venue: Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition (2009)

Multimodal biometrics has drawn lot of attention in recent days as it provides more reliable scheme for person verification. Multimodal biometrics includes the fusion of information from different modalities. This paper presents a novel method for assigning weights before performing fusion at match score level. The proposed method is based on False Acceptance Rate (FAR) and Genuine Acceptance Rate (GAR) obtained for each modality and weights are assigned on match scores of individual modality before performing match score level fusion. Extensive experiments carried out on three different build multimodal biometric databases shows the efficacy of the proposed method
A tearing-based hybrid parallel banded linear system solver
Authors: Maxim Naumov, Ahmed H. Sameh
Venue: Journal of Computational and Applied Mathematics (2009)

A new parallel algorithm for the solution of banded linear systems is proposed. The scheme tears the coefficient matrix into several overlapped independent blocks in which the size of the overlap is equal to the system's bandwidth. A corresponding splitting of the right-hand side is also provided. The resulting independent, and smaller size, linear systems are solved under the constraint that the solutions corresponding to the overlap regions are identical. This results in a linear system whose size is proportional to the sum of the overlap regions which we refer to as the ''balance'' system. We propose a solution strategy that does not require obtaining this ''balance'' system explicitly. Once the balance system is solved, retrieving the rest of the solution can be realized with almost perfect parallelism. Our proposed algorithm is a hybrid scheme that combines direct and iterative methods for solving a single banded system of linear equations on parallel architectures. It has broad applications in finite-element analysis, particularly as a parallel solver of banded preconditioners that can be used in conjunction with outer Krylov iterative schemes.
Learning in virtual environments: Some discrepancies between laboratory- and Internet-based research on associative learning
Authors: Miguel A. Vadillo, Helena Matute
Venue: Computers in Human Behavior (2009)

Some published reports have emphasized the similarities between Internet and laboratory research on associative learning processes. However, few of them, if any, studied systematic divergences between both types of research methodologies. In the present experiment, we investigated these divergences using an experimental preparation for the study of associative learning. The results show that discrimination and discrimination-reversal can be obtained both in laboratory and Internet experiments. However, the learning rate was clearly better in the laboratory than in the Internet condition. This result suggests that associative learning experiments performed over the Internet should provide participants with extensive training to assure that asymptotic performance is achieved.
Motorcycle and License Plate Detection Using Fixed-Size Vertical Projection and Multi-Part Mean Analysis
Authors: Wiwat Phatanasrirat, Suebskul Phiphobmongkol
Venue: Proceedings of the 2009 International Conference on Computer Engineering and Technology - Volume 02 (2009)

This paper proposed methods for motorcycle and license plate detection using fixed-size vertical projection and multi-part mean analysis. The method consisted of two parts: a motorcycle detection and a license plate detection. Fixed-size vertical projection and neural network were used in the motorcycle detection process. Vertical and horizontal scanning was used to extract features for the neural network. Later, a rough filter and a thorough filter were used to approximately locate and finally confirm a license plate, respectively. These methods were tested on both motorcycles with license plates and motorcycles without license plates. The experimental results gave accuracy of 93.20 % for motorcycle detection, 93.33 % for motorcycles with license plates, and 87.23 % for motorcycles without license plates.
Parallel Annotation and Population: A Cross-Language Experience
Authors: Bahareh Sarrafzadeh, Mehrnoush Shamsfard
Venue: Proceedings of the 2009 International Conference on Computer Engineering and Technology - Volume 02 (2009)

In recent years automatic Ontology Population (OP) from texts has emerged as a new field of application for knowledge acquisition techniques. In OP, the instances of an ontology classes will be extracted from text and added under the ontology concepts. On the other hand, semantic annotation which is a key task in moving toward semantic web tries to tag instance data in a text by their corresponding ontology classes; so the ontology population activity accompanies generating semantic annotations usually. In this paper we introduce a cross-lingual population/ annotation system called POPTA which annotates Persian texts according to an English lexicalized ontology and populates the English ontology according to the input Persian texts. It exploits a hybrid approach, a combination of statistical and pattern-based methods as well as techniques founded on the web and search engines and a novel method of resolving translation ambiguities. POPTA also uses Wikipedia as a vast natural language encyclopedia to extract new instances to populate the input ontology
Situation reactive approach to Vendor Managed Inventory problem
Authors: Choonjong Kwak, Jin Sung Choi, Chang Ouk Kim, Ick-Hyun Kwon
Venue: Expert Systems with Applications: An International Journal (2009)

In this research, we deal with VMI (Vendor Managed Inventory) problem where one supplier is responsible for managing a retailer's inventory under unstable customer demand situation. To cope with the nonstationary demand situation, we develop a retrospective action-reward learning model, a kind of reinforcement learning techniques, which is faster in learning than conventional action-reward learning and more suitable to apply to the control domain where rewards for actions vary over time. The learning model enables the inventory control to become situation reactive in the sense that replenishment quantity for the retailer is automatically adjusted at each period by adapting to the change in customer demand. The replenishment quantity is a function of compensation factor that has an effect of increasing or decreasing the replenishment amount. At each replenishment period, a cost-minimizing compensation factor value is chosen in the candidate set. A simulation based experiment gave us encouraging results for the new approach.
Parallel Eigensolvers for a Discretized Radiative Transfer Problem
Authors: Paulo B. Vasconcelos, Osni Marques, Jose E. Roman
Venue: High Performance Computing for Computational Science - VECPAR 2008: 8th International Conference, Toulouse, France, June 24-27, 2008. Revised Selected Papers (2008)

In this work we consider the numerical computation of eigenpairs of a matrix derived from integral operators. The matrix is associated to a radiative transfer problem in stellar atmospheres that is formulated by means of a weakly singular Fredholm integral equation defined on a Banach space. We examine direct and iterative parallel strategies for the eigensolution phase, using state-of-the-art numerical methods implemented in publicly available software packages.
Document identification using shape trees
Authors: Uwe Henker, Uwe Petersohn
Venue: International Journal of Hybrid Intelligent Systems (2009)

We present a technique to identify documents using an abstraction of a scanned image. The types of documents to identify must be known to the system a priori. To this end, the necessary features are saved in a case base [8] as shape trees. This file also contains rules for possible further processing. In an extremely reduced image, it is possible to filter out the significant, distinguishing information from the image and recognize it using case-based reasoning (CBR) [8]. This method has been demonstrated and proven by an example of experiments using medical order forms. An average of 97% of the forms were correctly identified; none were identified incorrectly.
Data hiding in grayscale images by dynamic programming based on a human visual model
Authors: I-Shi Lee, Wen-Hsiang Tsai
Venue: Pattern Recognition (2009)

A new method for data hiding in grayscale images based on a human vision model with distortion-minimizing capabilities is proposed. Each of the eight bit planes of an input grayscale image is viewed as a binary image, into which message data are embedded horizontally. Two optimization techniques, namely, block pattern coding and dynamic programming, are proposed for image distortion minimization. Experimental results show good performs of the proposed method.
An experiment on using the Pioneer3-DX robot in a multichannel measurement system
Authors: G. Vasiliu, A. Filipescu, Al. Stancu, S. Filipescu
Venue: Proceedings of the 8th conference on Systems theory and scientific computation (2008)

Increasing the precision of multichannel measurement systems requires a minimum execution time to select and analyze many probes, accessible from a deposit located inside the measurement system. Mobile robot Pioneer3 handles all the movements of selected probes between the deposit and measurement stand. Sliding-mode control of the robotic manipulator, and fuzzy techniques for trajectory tracking, are used for a minimum manipulation time and higher security in selection and placement of probes. The dynamical model of the mobile robot with one pair of active wheels, time-varying mass and moment of inertia have been used in sliding-mode control. Two closed-loop, on-line parameter estimators have been designed to achieve robustness against parameter uncertainties. Two sliding-mode adaptive controllers corresponding to angular and translation motion have been designed.