ppxscal/embedding_network huggingface dataset:
A Delay Fractioning Approach to Global Synchronization of Complex Networks with Distributed Delays and Stochastic Disturbances
Authors: Quanxin Cheng, Haibo Bao, Jinde Cao
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

In this paper, the global synchronization problem is studied for a class of complex networks. This is the first time that both the distributed delays and the stochastic disturbances are considered at the same time. Based on the idea of `delay fractioning', a sufficient condition which ensures the complex system to be globally synchronized is derived by referring to the Lyapunov functional method and the properties of Kronecker product. The condition, which is expressed in terms of linear matrix inequalities (LMIs), can be solved efficiently by the LMI toolbox in Matlab. The result obtained in this paper is proved to be much less conservative due to the fact that the delay upper bound is greatly enlarged.
Rigel: an architecture and scalable programming interface for a 1000-core accelerator
Authors: John H. Kelm, Daniel R. Johnson, Matthew R. Johnson, Neal C. Crago, William Tuohy, Aqeel Mahesri, Steven S. Lumetta, Matthew I. Frank, Sanjay J. Patel
Venue: Proceedings of the 36th annual international symposium on Computer architecture (2009)

This paper considers Rigel, a programmable accelerator architecture for a broad class of data- and task-parallel computation. Rigel comprises 1000+ hierarchically-organized cores that use a fine-grained, dynamically scheduled single-program, multiple-data (SPMD) execution model. Rigel's low-level programming interface adopts a single global address space model where parallel work is expressed in a task-centric, bulk-synchronized manner using minimal hardware support. Compared to existing accelerators, which contain domain-specific hardware, specialized memories, and/or restrictive programming models, Rigel is more flexible and provides a straightforward target for a broader set of applications. We perform a design analysis of Rigel to quantify the compute density and power efficiency of our initial design. We find that Rigel can achieve a density of over 8 single-precision GFLOPS/mm2 in 45nm, which is comparable to high-end GPUs scaled to 45nm. We perform experimental analysis on several applications ported to the Rigel low-level programming interface. We examine scalability issues related to work distribution, synchronization, and load-balancing for 1000-core accelerators using software techniques and minimal specialized hardware support. We find that while it is important to support fast task distribution and barrier operations, these operations can be implemented without specialized hardware using flexible hardware primitives.
Optimal and MPC control of the Quanser flexible link experiment
Authors: Florin Stinga, Monica Roman, Andreea Soimu, Eugen Bobasu
Venue: Proceedings of the 4th WSEAS/IASME international conference on Dynamical systems and control (2008)

In this paper we developed a control scheme starting from Bond Graph representation of the Quanser Flexible link experiment. The objective of the experiment is to design a control system that positions the flexible arm as well as regulating vibration. The structure of the control scheme uses two types of control methods. In order to achieve a faster or robust response together with optimal control, we computed two model predictive controllers. LQR control and MPC control are based on the optimization of the cost function, except that MPC control handles constraints in the optimization.
Impulsive Exponential Synchronization of Coupled Fuzzy Neural Networks with Time-Varying Delays
Authors: Jianting Zhou, Qiankun Song, Jianxi Yang
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

In this paper, the problem on impulsive exponential synchronization is investigated for coupled fuzzy neural networks with time-varying delays. Based on M-matrix theory and analytic methods, a sufficient condition of impulsive exponential synchronization of two coupled fuzzy neural networks is established. To illustrate the effectiveness of the new scheme, a numerical example with simulation is given.
The Fifth Richard Tapia Celebration of Diversity in Computing Conference: Intellect, Initiatives, Insight, and Innovations
Venue: Richard Tapia Celebration Of Diversity In Computing (2009)

We're honored to welcome you to the fifth Richard Tapia Celebration of Diversity in Computing Conference, and our first event in the Pacific Northwest. Your involvement is critical to the success of the conference, and we encourage you to attend the technical program, visit the exhibit tables, network with your colleagues, and enjoy the social activities. This year's technical program, including papers, panels, workshops, posters, Birds-of-a-Feather sessions, a Doctoral Consortium, and a Robotics Competition, is the strongest in the conference series history. To add to the program, we are honored to have the following plenary speakers: Hector Garcia-Molina, Stanford University; Ann Gates, University of Texas at El Paso; Charles Isbell, Georgia Institute of Technology; Jane Margolis, UCLA; and Mario Pipkin, Microsoft Corporation. In addition to its technical content, the conference includes presentations on initiatives to increase the number of individuals from underrepresented groups succeeding in computing-based careers.
Electric and adsorption characteristics of nanocrystalline V-(N, He) coatings
Authors: Alexey G. Guglya, Viktor G. Kolobrodov, Ruslan L. Vasilenko
Venue: Journal of Nanomaterials (2009)

This paper studies the structure, temperature dependences of electric resistance, and adsorption properties of nanoporous three-component V-(N, He) coatings. The coatings were produced using the technique of ion beam assisted deposition, in particular, deposition of vanadium onto a titanium substrate simultaneously bombarding it with N2 + He ions of 30keV. It is shown, in contrast to V-N composites that have negative TCR (temperature coefficient of resistance), that the V-(N, He) coatings have negative TCR only in the temperature range of 250 to 350°C. A specific surface of pores and adsorption characteristics of V-(N, He) composites depend on preliminary treatment of a titanium surface. A coating deposited onto an untreated substrate has specific surface of 25.5m2/g. The preliminary irradiation of titanium with N2+He beam up to a dose of 6 × 1017 ion/cm2 provides the increase in surface area up to 57.6m2/g. The preliminary ion bombardment provides a considerable increase in hydrogen adsorption capacity of coatings. Especially, such impact is noticeable at the room temperature, when the amount of hydrogen absorbed by a coating that was applied onto a treated surface is more than three times of that absorbed by a coating that was deposited onto nonexposed titanium.
Neuroevolutionary reinforcement learning for generalized helicopter control
Authors: Rogier Koppejan, Shimon Whiteson
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

Helicopter hovering is an important challenge problem in the field of reinforcement learning. This paper considers several neuroevolutionary approaches to discovering robust controllers for a generalized version of the problem used in the 2008 Reinforcement Learning Competition, in which wind in the helicopter's environment varies from run to run. We present the simple model-free strategy that won first place in the competition and also describe several more complex model-based approaches. Our empirical results demonstrate that neuroevolution is effective at optimizing the weights of multi-layer perceptrons, that linear regression is faster and more effective than evolution for learning models, and that model-based approaches can outperform the simple model-free strategy, especially if prior knowledge is used to aid model learning.
Bounded rationality via recursion
Authors: Maciej Łatek, Robert Axtell, Bogumil Kaminski
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

Current trends in model construction in the field of agent-based computational economics base behavior of agents on either game theoretic procedures (e.g. belief learning, fictitious play, Bayesian learning) or are inspired by artificial intelligence (e.g. reinforcement learning). Evidence from experiments with human subjects puts the first approach in doubt, whereas the second one imposes significant computational and memory requirements on agents. In this paper, we introduce an efficient computational implementation of n-th order rationality using recursive simulation. An agent is n-th order rational if it determines its best response assuming that other agents are (n-1)-th order rational and zero-order agents behave according to a specified, non-strategic, rule. In recursive simulations, the simulated decision makers use simulation to inform their own decision making (search for best responses). Our goal is to provide agent modelers with an off-the-shelf implementation of n-th order rationality that leads to model-consistent behaviors of agents, without requiring a learning phase. We extend two classic games (Shapley's fictitious play and Colonel Blotto) to illustrate aspects of the n-th order rationality concept as implemented in our framework.
Solving reactive power control problems in a stressed power system network using evolutionary computation technique
Authors: N. R. H. Abdullah, I. Musirin, M. M. Othman, T. K. A. Rahman
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

Lack in reactive power support in a power system network has led to low voltage level at a load bus. This can also occur in a stressed power system network despite no contingency is subjected to the system. Therefore, reactive power support must be properly established in the system in order to secure the system from possible voltage collapse occurrence. This paper presents Evolutionary Computing technique for solving reactive power control (RPC) problem in the attempt to enhance voltage stability, while minimizing transmission loss and maintaining voltage level at an acceptable level. In this study, evolutionary programming (EP) was chosen as the Evolutionary Computing (EC) technique for solving the RPC; taking into consideration two separate objective functions. Static voltage stability enhancement and minimization of real power loss are implemented separately on a reliability test system. Comparative studies performed with respect to Artificial Immune System (AIS) have highlighted that EP outperformed AIS for both objective functions.
Folksonomy Enrichment and Search
Authors: Sofia Angeletou, Marta Sabou, Enrico Motta
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

The Semantic Web community has expressed its interest on how the Semantic Web technology can be applied more efficiently in a manner that supports real world applications. Additionally, the popularity of social tagging systems has demonstrated a clear need for organisation and more flexible ways of querying the user contributed content. This work presents FLOR, a folksonomy enrichment algorithm, which exploits a variety of knowledge sources to apply structure on the user tagspaces. In addition, a query mechanism is presented demonstrating how the enriched folksonomies structures can be interrogated by transforming the user keyword queries on folksonomies to formal queries on semantic structures. The first prototype of the FLOR enrichment algorithm and a first instance of the query mechanism have been implemented and a demonstration is available online.
Evaluation of a Multiobjective Alternative Routing Method in Carrier IP/MPLS Networks
Authors: Lúcia Martins, Catarina Francisco, João Redol, José Craveirinha, João Clímaco, Paulo Monteiro
Venue: Proceedings of the 8th International IFIP-TC 6 Networking Conference (2009)

We present a first simplified version of the MultiObjective Dynamic Routing (MODR) method, more suitable for a realistic network environment as the computational effort is very much reduced while good results can still be reached. The simplified version presented herein is based on the results obtained from a discrete event simulation study which shows that, in case of overload, more important than the alternative routing algorithm itself is to control the excess of alternative routing traffic. Moreover, in a multiservice network in the case of lightly loaded traffic conditions, when alternative routing starts to be effective, network performance can still be improved if we can avoid alternative routing for specific traffic flows. Classical dynamic alternative routing methods for traditional ISDN networks have a trunk reservation mechanism with a similar purpose but apparently without the same performance. Our method applies to MPLS strongly meshed networks which are typical of core networks.
Collaborative Building of Japanese Kanji Pronunciation Database for Learning Japanese by Chinese
Authors: Fei Yuan, Jing Yuan, Rong Wang, Hiroyuki Mitsuhara, Kazuhide Kanenishi, Yoneo Yano
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

For Chinese learners who learn Japanese, it is difficult to enhance speaking ability through reading Japanese teaching materials and articles. Because many Kanji have the same or approx meaning in Japanese and Chinese, therefore during reading the Japanese educational materials Chinese learners are not necessary to master the pronunciation of Kanji in Japanese to understand. Currently few systems deal with learning the pronunciation of Japanese Kanji in reading and furthermore enhancing speaking ability. In this paper, we present a self-directed reading environment for Chinese learners to learn the pronunciation of Japanese Kanji in daily reading and describe developing a collaborative-building database to realize it.
Nonlinear Dimensionality Reduction, 1st edition
Authors: John A. Lee, Michel Verleysen
Venue:  (2007)

Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets. Traditional methods like principal component analysis and classical metric multidimensional scaling suffer from being based on linear models. Until recently, very few methods were able to reduce the data dimensionality in a nonlinear way. However, since the late nineties, many new methods have been developed and nonlinear dimensionality reduction, also called manifold learning, has become a hot topic. New advances that account for this rapid growth are, e.g. the use of graphs to represent the manifold topology, and the use of new metrics like the geodesic distance. In addition, new optimization schemes, based on kernel techniques and spectral decomposition, have lead to spectral embedding, which encompasses many of the recently developed methods. This book describes existing and advanced methods to reduce the dimensionality of numerical databases. For each method, the description starts from intuitive ideas, develops the necessary mathematical details, and ends by outlining the algorithmic implementation. Methods are compared with each other with the help of different illustrative examples. The purpose of the book is to summarize clear facts and ideas about well-known methods as well as recent developments in the topic of nonlinear dimensionality reduction. With this goal in mind, methods are all described from a unifying point of view, in order to highlight their respective strengths and shortcomings. The book is primarily intended for statisticians, computer scientists and data analysts. It is also accessible to other practitioners having a basic background in statistics and/or computational learning, like psychologists (in psychometry) and economists.
Inferring intra-organizational collaboration from cosine similarity distributions in text documents
Authors: Maria Esteva, Hai Bi
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

We present a method that uses text mining methods and statistical distributions to infer degrees of collaboration between staff members in an organization, based on the similarity of the documents that that they wrote and exchanged over time.
A Concept Map Based Intelligent System for Adaptive Knowledge Assessment
Authors: Alla Anohina, Janis Grundspenkis
Venue: Proceeding of the 2007 conference on Databases and Information Systems IV: Selected Papers from the Seventh International Baltic Conference DB&IS'2006 (2007)

The paper describes a concept map based multiagent system that has been developed for learners' knowledge assessment and self-assessment in process oriented learning. The architecture of the system in terms of modules, their functions and interaction is presented. The special attention is given to the intelligent assessment agent, which at the moment is composed of communication, knowledge evaluation, interaction registering, and expert agents. The paper also discusses a novel approach to adaptive knowledge assessment using concept maps.
Evaluating Between-Pathway Models with Expression Data
Authors: Benjamin J. Hescott, Mark D. Leiserson, Lenore J. Cowen, Donna K. Slonim
Venue: Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology (2009)

Between-Pathway Models (BPMs) are network motifs consisting of pairs of putative redundant pathways. In this paper, we show how adding another source of high-throughput data, microarray gene expression data from knockout experiments, allows us to identify a compensatory functional relationship between genes from the two BPM pathways. We evaluate the quality of the BPMs from four different studies, and we describe how our methods might be extended to refine pathways.
Toward a gold standard for promoter prediction evaluation
Authors: Thomas Abeel, Yves Van de Peer, Yvan Saeys
Venue: Bioinformatics (2009)

Motivation: Promoter prediction is an important task in genome annotation projects, and during the past years many new promoter prediction programs (PPPs) have emerged. However, many of these programs are compared inadequately to other programs. In most cases, only a small portion of the genome is used to evaluate the program, which is not a realistic setting for whole genome annotation projects. In addition, a common evaluation design to properly compare PPPs is still lacking. Results: We present a large-scale benchmarking study of 17 state-of-the-art PPPs. A multi-faceted evaluation strategy is proposed that can be used as a gold standard for promoter prediction evaluation, allowing authors of promoter prediction software to compare their method to existing methods in a proper way. This evaluation strategy is subsequently used to compare the chosen promoter predictors, and an in-depth analysis on predictive performance, promoter class specificity, overlap between predictors and positional bias of the predictions is conducted. Availability: We provide the implementations of the four protocols, as well as the datasets required to perform the benchmarks to the academic community free of charge on request. Contact: yves.vandepeer@psb.ugent.be Supplementary information: Supplementary data are available at Bioinformatics online.
Project to Deliver Online Distance Learning for “Introduction to Database Systems” Between Two Campuses
Authors: Nami Imanishi, Kuniharu Yokomura, Tsuyoshi Sano
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

In recent years, some online courses have been delivered with equipment such as video studios and smartboards (digital whiteboards) [1,2]. Our project started by considering the minimum system requirements for distance learning in our computer rooms. We offered “Introduction to Database Systems”, a purely theory-based course that had not provided a component approach for students who lacked a prior working knowledge of databases. In previous research, we developed the interactive web-based tutorial for the course. The initial findings indicate that students' overall understanding of the course material has improved by using the web-based tutorials. The online teaching materials are described, and we report responses to a questionnaire given to students in both distance and traditional classes.
Maximum-Rate Node Selection for Power-Limited Multiantenna Relay Backbones
Authors: Enzo Baccarelli, Mauro Biagi, Cristian Pelizzoni, Nicola Cordeschi
Venue: IEEE Transactions on Mobile Computing (2009)

Wireless Mesh Networks (WMNs) are envisioned for extending the coverage of WLANs by interconnecting the underlying Access Points (APs) via high-capacity wireless backbones. Since the ultimate goal of a WMN is to provide Internet connectivity to residential clients, WMN traffic is mainly routed over the backbone either toward the Internet Gateways (IGWs) or from the IGWs to the APs. In principle, the transport capacity of a WMN can further be upgraded by equipping the underlying backbone routers with Multiantenna (MA) radio modules. Motivated by the above consideration, in this paper, we focus on the optimized node selection (e.g., path-routing) over MA mesh backbones when the target is to maximize the end-to-end routed information rate subject to a constraint on the total power available for the relays. Under the assumption of Rayleigh-distributed block fading, we assume that point-to-point capacity-achieving Space-Time Codes (STCs) are used for the single-hop link. At first, we tackle the routing problem when neither Interference Mitigation (IM) nor Transmit Beamforming (TB) is performed at the relay nodes, and then, we extend the analysis to the cases when IM and/or TB are also carried out. The effects of Channel-State-Information (CSI) possibly available at the relay nodes are also investigated. So doing, we are able to gain insight about the combined effect of spatial multiplexing and IM capabilities of the overall MA architecture on both end-to-end capacity and access medium performance of the considered WMN.
Automated meter reading system for heat costs allocation
Authors: Ioan Lie, Virgil Tiponut, Ivan Bogdanov, Sabin Ionel, Catalin Daniel Caleanu
Venue: WSEAS Transactions on Circuits and Systems (2009)

The paper presents the design and the implementation of an automated meter reading system for heat costs allocation. The system was developed on three levels: the data acquisition level - where data are recorded from field with costs allocators installed on the radiators; a data concentration level - were data registered by allocators are read at a predetermined time interval with data concentration units and a data processing level - for uploading information in a PC hosted data base for various works afterwards. For each level was defined the hardware requirements and the software specifications including the communications modules, the meter and the user interfaces. A PWM data encoding was proposed as an alternative encoding for wireless communication through RF between data acquisition and concentration levels. The system uses RF for data transmission but also includes a pair of RFID modules facilitating remote programming and diagnostic procedures. In order to fulfill the low power requirements the dedicated modules costs allocator and data collection unit were implemented around MSP430 low power microcontrollers.