ppxscal/embedding_network huggingface dataset:
Watermark Image Restoration Method Based on Block Hopfield Network
Authors: Xiaohong Ma, Xin Li, Hualou Liang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

In this paper, Hopfield network is introduced for the restoration of extracted watermark image which may be blurred due to the signal transfer or various signal processing operations. A novel codebook method is designed to reduce the storage space of the network and to increase the security. First, each watermark image is divided into adjacent and non-overlapped sub-block images and mapped into a codebook. Second, this codebook is encrypted by a chaotic sequence. During the process of watermark restoration, the codebook can be obtained via a secret key which is then used to construct block weight matrix of the neural network for the restoration of the blurred watermark images. Simulation results demonstrate the excellent performance of the proposed method.
Hybrid cache architecture with disparate memory technologies
Authors: Xiaoxia Wu, Jian Li, Lixin Zhang, Evan Speight, Ram Rajamony, Yuan Xie
Venue: Proceedings of the 36th annual international symposium on Computer architecture (2009)

Caching techniques have been an efficient mechanism for mitigating the effects of the processor-memory speed gap. Traditional multi-level SRAM-based cache hierarchies, especially in the context of chip multiprocessors (CMPs), present many challenges in area requirements, core-to-cache balance, power consumption, and design complexity. New advancements in technology enable caches to be built from other technologies, such as Embedded DRAM (EDRAM), Magnetic RAM (MRAM), and Phase-change RAM (PRAM), in both 2D chips or 3D stacked chips. Caches fabricated in these technologies offer dramatically different power and performance characteristics when compared with SRAM-based caches, particularly in the areas of access latency, cell density, and overall power consumption. In this paper, we propose to take advantage of the best characteristics that each technology offers, through the use of Hybrid Cache Architecture (HCA) designs. We discuss and evaluate two types of hybrid cache architectures: inter cache Level HCA (LHCA), in which the levels in a cache hierarchy can be made of disparate memory technologies; and intra cache level or cache Region based HCA (RHCA), where a single level of cache can be partitioned into multiple regions, each of a different memory technology. We have studied a number of different HCA architectures and explored the potential of hardware support for intra-cache data movement and power consumption management within HCA caches. Utilizing a full-system simulator that has been validated against real hardware, we demonstrate that an LHCA design can provide a geometric mean 7% IPC improvement over a baseline 3-level SRAM cache design under the same area constraint across a collection of 25 workloads. A more aggressive RHCA-based design provides 12% IPC improvement over the baseline. Finally, a 2-layer 3D cache stack (3DHCA) of high density memory technology within the same chip footprint gives 18% IPC improvement over the baseline. Furthermore, up to 70% reduction in power consumption over a baseline SRAM-only design is achieved.
Development of a PLIC-VOF method for the dynamic simulation of entry region flow in a laminar falling film
Authors: R. S. Maurya, T. Sundararajan, S. K. Das
Venue: International Journal of Computational Fluid Dynamics (2009)

The present work describes a numerical procedure to simulate the development of hydrodynamic entry region in a gravity-driven laminar liquid film flow over an inclined plane. It provides a better insight into the physics of developing film in entry region. A novel numerical approach is proposed which has the potential to provide solutions for the complex physics of liquid film spreading on solid walls. The method employs an incompressible flow algorithm to solve the governing equations, a PLIC-VOF method to capture the free surface evolution and a continuum surface force (CSF) model to include the effect of surface tension. To account for the moving contact line on the solid substrate, a precursor film model based wall treatment is implemented. Liquid film flow has been simulated for the Reynolds number range of 5 ≤ Re ≤ 37.5, and the predicted results are found to agree well with the available analytical and experimental data.
On Acceptability in Abstract Argumentation Frameworks with an Extended Defeat Relation
Authors: Diego C. Martínez, Alejandro J. García, Guillermo R. Simari
Venue: Proceeding of the 2006 conference on Computational Models of Argument: Proceedings of COMMA 2006 (2006)

Defeat between arguments is established by a combination of two basic elements: a conflict or defeat relation, and a preference relation on the arguments involved in this conflict. We present a new abstract framework for argumentation where two kinds of defeat are present, depending on the outcome of the preference relation: an argument may be a proper defeater or a blocking defeater of another argument. An operator is used to characterize the set of accepted arguments. This operator also provides a method for identifying controversial situations.
Segmentation for English-to-Arabic statistical machine translation
Authors: Ibrahim Badr, Rabih Zbib, James Glass
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

In this paper, we report on a set of initial results for English-to-Arabic Statistical Machine Translation (SMT). We show that morphological decomposition of the Arabic source is beneficial, especially for smaller-size corpora, and investigate different recombination techniques. We also report on the use of Factored Translation Models for English-to-Arabic translation.
Migration motif: a spatial - temporal pattern mining approach for financial markets
Authors: Xiaoxi Du, Ruoming Jin, Liang Ding, Victor E. Lee, John H. Thornton,  Jr.
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

A recent study by two prominent finance researchers, Fama and French, introduces a new framework for studying risk vs. return: the migration of stocks across size-value portfolio space. Given the financial events of 2008, this first attempt to disentangle the relationships between migration behavior and stock returns is especially timely. Their work, however, derives results only for market segments, not individual companies, and only for one-year moves. Thus, we see a new challenge for financial data mining: how to capture and categorize the migration of individual companies, and how such behavior affects their returns. We propose a novel data mining approach to study the multi-year movement of individual companies. Specifically, we address the question: "How does one discover frequent migration patterns in the stock market?" We present a new trajectory mining algorithm to discover migration motifs in financial markets. Novel features of this algorithm are its handling of approximate pattern matching through a graph theoretical method, maximal clique identification, and incorporation of temporal and spatial constraints. We have performed a detailed study of the NASDAQ, NYSE, and AMEX stock markets, over a 43-year span. We successfully find migration motifs that confirm existing finance theories and other motifs that may lead to new financial models.
Towards an electronic dictionary of Tamajaq language in Niger
Authors: Chantal Enguehard, Issouf Modi
Venue: Proceedings of the First Workshop on Language Technologies for African Languages (2009)

We present the Tamajaq language and the dictionary we used as main linguistic resource in the two first parts. The third part details the complex morphology of this language. In the part 4 we describe the conversion of the dictionary into electronic form, the inflectional rules we wrote and their implementation in the Nooj software. Finally we present a plan for our future work.
Pre-processing Techniques for the QSAR Problem
Authors: L. Dumitriu, M. -V. Craciun, A. Cocu, C. Segal
Venue: Proceeding of the 2008 conference on New Trends in Multimedia and Network Information Systems (2008)

Predictive Toxicology (PT) attempts to describe the relationships between the chemical structure of chemical compounds and biological and toxicological processes. The most important issue related to real-world PT problems is the huge number of the chemical descriptors. A secondary issue is the quality of the data since irrelevant, redundant, noisy, and unreliable data have a negative impact on the prediction results. The pre-processing step of Data Mining deals with complexity reduction as well as data quality improvement through feature selection, data cleaning, and noise reduction. In this paper, we present some of the issues that can be taken into account for preparing data before the actual knowledge discovery is performed.
Retrospective analysis of communication events: understanding the dynamics of collaborative multi-party discourse
Authors: Andrew J. Cowell, Jereme Haack, Adrienne Andrew
Venue: Proceedings of the HLT-NAACL 2006 Workshop on Analyzing Conversations in Text and Speech (2006)

This research is aimed at understanding the dynamics of collaborative multi-party discourse across multiple communication modalities. Before we can truly make significant strides in devising collaborative communication systems, there is a need to understand how typical users utilize computationally supported communications mechanisms such as email, instant messaging, video conferencing, chat rooms, etc., both singularly and in conjunction with traditional means of communication such as face-to-face meetings, telephone calls and postal mail. Attempting to understand an individual's communications profile with access to only a single modality is challenging at best and often futile. Here, we discuss the development of RACE -- Retrospective Analysis of Communications Events -- a test-bed prototype to investigate issues relating to multi-modal multi-party discourse. We also examine future avenues of research for further enhancing our prototype and investigating this area.
Teachable characters: semantic neural networks in game AI
Authors: Harri Ketamo
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

The aim of the study was to apply machine learning into educational game and evaluate the outcome in context of cognitive psychology of learning. The study was done in two phases: design phase and evaluation phase (N=59). The design of the game was done in order to support relatively free teaching of a virtual pet in an easy-to-use environment. The main finding of the study was a clear causality between quality of teaching in game world and players' knowledge in real life.
Supervised learning classifier systems for grid data mining
Authors: M. F. Santos, W. Mathew, T. Kovacs, H. Santos
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

This paper explores parallel and distributed implementation of the Learning Classifier System (LCS) technology. Specifically, the adaptation of supervised LCS to the grid data mining requisites, using the agent paradigm, is studied. The paper also examines the competitive data mining model induction possibility with homogeneous and heterogeneous data. A distributed framework is proposed using the grid computing architecture to make Supervised Classifier Systems (UCS) a more efficient distributed environment. This framework allows each local site (or agent) to employ a completely independent UCS. Local models (or UCS's populations) are transmitted occasionally to the global model for combination. The global model then represents a complete knowledge base of the overall classification problem.
Anytime learning and classification for online applications
Authors: Geoffrey I. Webb
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

Many online applications of machine learning require fast classification and hence utilize efficient classifiers such as naïve Bayes. However, outside periods of peak computational load, additional computational resources will often be available. Anytime classification can use whatever computational resources may be available at classification time to improve the accuracy of the classifications made.
Context-aware multi-stage routing
Authors: Adriaan ter Mors, Jeroen van Belle, Cees Witteveen
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

In context-aware route planning, a set of agents has to plan routes on a common infrastructure and each agent has to plan a conflict-free route from a source to a destination without invalidating plans made by other agents. The existence of such a conflict-free set of plans can be ensured if each agent is allowed to reserve time slots on the infrastructure resources it intends to use. In the multi-stage variant of the context-aware routing problem, each agent has a sequence of destination locations it must visit. A naive approach to solve the multi-stage variant is to make context-aware route plans between every two subsequent locations in the sequence, and then to concatenate these plans together. It can easily be shown, however, that this concatenation approach cannot guarantee that a multi-stage plan (if it exists) can always be found, and even if it is found, then it need not be optimal. Therefore, we present a new polynomial-time algorithm for the multi-stage routing problem that always returns the optimal (shortest-time) route for a single agent, given a set of reservations made by previous agents, thus providing a set of Pareto-optimal route plans. Obviously, the need for such a dedicated multi-stage routing algorithm depends on the frequency with which the concatenation approach fails to find a plan, or finds a rather inefficient one. Our experiments show that, given a set of reservations from 200 agents, the concatenation approach fails to find a solution in more than 50% of the cases, for random visiting sequences of six locations or more. However, if the concatenation approach does find a solution, its plan quality is often close to that of an optimal solution.
Multi-information Fusion and Identification System for Laser Welding
Authors: Ming Zhou, Wenzhong Liu, Lei Wan
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

In this paper, we proposed a laser welding quality monitoring system based on vector machine, which uses the light and sound sensors access to the various signals of the welding and Gabor transform features to extract the vector. The basic features of Laser welding is the formation of small holes, pool and photo-induced plasma, and the result is quality of the welding of light, sound and the potential of poor signal. On this basis, making use of the advantage and objectivity of machine leaning, SVM classification and more comprehensive information to determine the parameters of laser welding quality of the welding seam.
MCSE Guide to Planning a Microsoft Windows Server 2003 Network, Enhanced, 1st edition
Authors: Byron Wright, Brian T. McCann
Venue:  (2007)

This full-color hands-on guide book has been enhanced to make learning even easier by offering more detailed lab setup instructions, expanded chapter summaries, and new practice exams that will reinforce the skills learned.
Research on Multi-Agent Parallel Computing Model of Hydrothermal Economic Dispatch in Power System
Authors: Bu-Han Zhang, Junfang Li, Yan Li, Chengxiong Mao, Xin-Bo Ruan, Jianhua Yang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

This paper presents a Multi-Agent Parallel Computing Model (MAPCM) for solving hydrothermal scheduling in the power system. The proposed model is hierarchical with two levels--decomposition level considering real time dispatch with optimal power flow and a coordination level considering the selection method of hydro-coal transfer coefficient under different situation about water head, and active power coordination with generation ramping constraints. The model is applied to a simple case study exploring the effect of multi-agent parallel computing about hydrothermal system. The efficiency analysis shows that the model has much potential for the real-time dispatching.
Constraints, Graphs, Algebra, Logic, and Complexity
Authors: Moshe Y. Vardi
Venue: Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation (2009)

A large class of problems in AI and other areas of computer science can be viewed as constraint-satisfaction problems. This includes problems in database query optimization, machine vision, belief maintenance, scheduling, temporal reasoning, type reconstruction, graph theory, and satisfiability. All of these problems can be recast as questions regarding the existence of homomorphisms between two directed graphs. It is well-known that the constraint-satisfaction problem is NP-complete. This motivated an extensive research program into identify tractable cases of constraint satisfaction.This research proceeds along two major lines. The first line of research focuses on non-uniform constraint satisfaction, where the target graph is fixed. The goal is to identify those target graphs that give rise to a tractable constraint-satisfaction problem. The second line of research focuses on identifying large classes of source graphs for which constraint-satisfaction is tractable. We show in how tools from graph theory, universal algebra, logic, and complexity theory, shed light on the tractability of constraint satisfaction.
Decoupled store completion/silent deterministic replay: enabling scalable data memory for CPR/CFP processors
Authors: Andrew Hilton, Amir Roth
Venue: ACM SIGARCH Computer Architecture News (2009)

CPR/CFP (Checkpoint Processing and Recovery/Continual Flow Pipeline) support an adaptive instruction window that scales to tolerate last-level cache misses. CPR/CFP scale the register file by aggressively reclaiming the destination registers of many in-flight instructions. However, an analogous mechanism does not exist for stores and loads. As the window expands, CPR/CFP processors must track all in-flight stores and loads to support forwarding and detect memory ordering violations. The previously-described SVW (Store Vulnerability Window) and SQIP (Store Queue Index Prediction) schemes provide scalable, non-associative load and store queues, respectively. However, they don't work smoothly in a CPR/CFP context. SVW/SQIP rely on the ability to dynamically stall some loads until a specific older store writes to the cache. Enforcing this serialization in CPR/CFP is expensive if the load and store are in the same checkpoint. We introduce two complementary procedures that implement this serialization efficiently. Decoupled Store Completion (DSC) allows stores to write to the cache before the enclosing checkpoint completes execution. Silent Deterministic Replay (SDR) supports mis-speculation recovery in the presence of DSC by replaying loads older than completed stores using values from the load queue. The combination of DSC and SDR enables an SVW/SQIP based CPR/CFP memory system that outperforms previous designs while occupying less area.
Unsupervised methods of topical text segmentation for Polish
Authors: Dominik Flejter, Karol Wieloch, Witold Abramowicz
Venue: Proceedings of the Workshop on Balto-Slavonic Natural Language Processing: Information Extraction and Enabling Technologies (2007)

This paper describes a study on performance of existing unsupervised algorithms of text documents topical segmentation when applied to Polish plain text documents. For performance measurement five existing topical segmentation algorithms were selected, three different Polish test collections were created and seven approaches to text pre-processing were implemented. Based on quantitative results (Pk and WindowDiff metrics) use of specific algorithm was recommended and impact of pre-processing strategies was assessed. Thanks to use of standardized metrics and application of previously described methodology for test collection development, comparative results for Polish and English were also obtained.
Homotopy perturbation method for the Jumbo-Miwa equation
Authors: Emanullah Hizel
Venue: Proceedings of the 10th WSEAS international conference on evolutionary computing (2009)

In this paper, an iterative numerical solution of the higher dimensional (3+1) physically important nonlinear evolutionary equation is studied by using the Homotopy Perturbation Method (HPM). For this purpose, the Jumbo-Miwa (JM) equation is analyzed with HPM and the available exact solution obtained by Homogenous Balance Method will be compared to show the accuracy of the proposed numerical algorithm. The result approves the effectiveness and accuracy of the HPM.
Domain-oriented edge-based alignment of protein interaction networks
Authors: Xin Guo, Alexander J. Hartemink
Venue: Bioinformatics (2009)

Motivation: Recent advances in high-throughput experimental techniques have yielded a large amount of data on protein–protein interactions (PPIs). Since these interactions can be organized into networks, and since separate PPI networks can be constructed for different species, a natural research direction is the comparative analysis of such networks across species in order to detect conserved functional modules. This is the task of network alignment. Results: Most conventional network alignment algorithms adopt a node-then-edge-alignment paradigm: they first identify homologous proteins across networks and then consider interactions among them to construct network alignments. In this study, we propose an alternative direct-edge-alignment paradigm. Specifically, instead of explicit identification of homologous proteins, we directly infer plausibly alignable PPIs across species by comparing conservation of their constituent domain interactions. We apply our approach to detect conserved protein complexes in yeast–fly and yeast–worm PPI networks, and show that our approach outperforms two recent approaches in most alignment performance metrics. Availability: Supplementary material and source code can be found at http://www.cs.duke.edu/~amink/. Contact: xinguo@cs.duke.edu