ppxscal/embedding_network huggingface dataset:
Input-sensitive scalable continuous join query processing
Authors: Pankaj K. Agarwal, Junyi Xie, Jun Yang, Hai Yu
Venue: ACM Transactions on Database Systems (TODS) (2009)

This article considers the problem of scalably processing a large number of continuous queries. Our approach, consisting of novel data structures and algorithms and a flexible processing framework, advances the state-of-the-art in several ways. First, our approach is query sensitive in the sense that it exploits potential overlaps in query predicates for efficient group processing. We partition the collection of continuous queries into groups based on the clustering patterns of the query predicates, and apply specialized processing strategies to heavily clustered groups (or hotspots). We show how to maintain the hotspots efficiently, and use them to scalably process continuous select-join, band-join, and window-join queries. Second, our approach is also data sensitive, in the sense that it makes cost-based decisions on how to process each incoming tuple based on its characteristics. Experiments demonstrate that our approach can improve the processing throughput by orders of magnitude.
Optimal strong parity edge-coloring of complete graphs
Authors: David P. Bunde, Kevin Milans, Douglas B. West, Hehui Wu
Venue: Combinatorica (2008)

A parity walk in an edge-coloring of a graph is a walk along which each color is used an even number of times. Let p(G) be the least number of colors in an edge-coloring of G having no parity path (a parity edge-coloring). Let $$ \hat p $$(G) be the least number of colors in an edge-coloring of G having no open parity walk (a strong parity edge-coloring). Always $$ \hat p $$(G) &#x2265; p(G) &#x2265; &#x03c7;&#x2032;(G). We prove that $$ \hat p $$(K n ) = 2&#x2308;lgn&#x2309; &#x2212; 1 for all n. The optimal strong parity edge-coloring of K n is unique when n is a power of 2, and the optimal colorings are completely described for all n.
The Importance of Model Parameters and Boundary Conditions in Whole Organ Models of Cardiac Contraction
Authors: Steven Niederer, Kawal Rhode, Reza Razavi, Nic Smith
Venue: Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart (2009)

We have developed a model of active contraction in the whole heart, using an anatomical geometry of a failing human heart, fitted to MRI data. Deformation in this model was driven by a model of active tension generation in human ventricular myocytes. By perturbing model parameters and boundary conditions we have predicted which metrics of cardiac function are sensitive to different parameters or boundary conditions. This allows us to begin to identify parameters that can be determined from different diagnostic modalities.
A study on the influence of measurement location and regularization on the evaluation of boundary tractions by inverse finite element method
Authors: Hyun-Gyu Kim, Kyung Woo Lee
Venue: Finite Elements in Analysis and Design (2009)

This work is concerned with an inverse approach to determine boundary tractions from displacements measured on a remote surface. The influence of measurement location and regularization on the evaluation of unknown tractions is mainly investigated through numerical experiments. The finite element method is employed in the inversion process, and the Tikhonov and the truncated singular value decomposition techniques are used to regularize an ill-conditioned system. The analytical relation between measurement location and the conditioning of a spring inverse problem is presented in this paper. Numerical results show that the solutions of inverse problems using the finite element method are very sensitive to measurement location. In addition, the effects of regularization and noise added to measured displacements are discussed through numerical examples.
Model-based velocity control of electrohydraulic servo systems
Authors: Olimpiu Hancu, Vistrian Maties, Radu Balan, Ciprian Lapusan
Venue: Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation (2009)

It is proposed a strategy which eliminates some nonlinearities of electrohydraulic systems. Using some properties of these systems more simple models are provided with good approximations on the whole operational area. Considering the velocity control problem of nonlinear hydraulic servo systems a model-based controller is designed subjected to known and time-varying parameters. Numerical results were provided to show the effectiveness of proposed approach.
Single point iterative weighted fuzzy C-means clustering algorithm for remote sensing image segmentation
Authors: Jianchao Fan, Min Han, Jun Wang
Venue: Pattern Recognition (2009)

In this paper, a remote sensing image segmentation procedure that utilizes a single point iterative weighted fuzzy C-means clustering algorithm is proposed based upon the prior information. This method can solve the fuzzy C-means algorithm's problem that the clustering quality is greatly affected by the data distributing and the stochastic initializing the centrals of clustering. After the probability statistics of original data, the weights of data attribute are designed to adjust original samples to the uniform distribution, and added in the process of cyclic iteration, which could be suitable for the character of fuzzy C-means algorithm so as to improve the precision. Furthermore, appropriate initial clustering centers adjacent to the actual final clustering centers can be found by the proposed single point adjustment method, which could promote the convergence speed of the overall iterative process and drastically reduce the calculation time. Otherwise, the modified algorithm is updated from multidimensional data analysis to color images clustering. Moreover, with the comparison experiments of the UCI data sets, public Berkeley segmentation dataset and the actual remote sensing data, the real validity of proposed algorithm is proved.
Hash Functions Based on Large Quasigroups
Authors: Václav Snášel, Ajith Abraham, Jiří Dvorský, Pavel Krömer, Jan Platoš
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

In this article we discuss a simple hash function based upon properties of a well-known combinatorial design called quasigroups. The quasigroups are equivalent to the more familiar Latin squares and one of their most important properties is that all possible element of certain quasigroup occurs with equal probability. Actual implementations are based on look-up table implementation of the quasigroup, which is unusable for large quasigroups. In contrast, presneted hash function can be easily implemented. It allows us to compute hash function without storing large amount of data (look-up table). The hash function computation is illustrated by experiments summarized in the last section of this paper. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Topic Initiative in a Simulated Peer Dialogue Agent
Authors: Pamela W. Jordan
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

One goal of our project is to create a dialogue agent that can behave as a student peer and collaborate with a human student to explain or diagnose data structures programs. A human peer must be able to initiate something the agent may not be expecting and the agent must be able to respond to it as a peer would. This paper describes the work we have completed to extend an existing natural language tutorial dialogue system to provide such a capability and the work that remains.
Analysis and comparison of optimized multipump distributed Raman amplifiers in different fiber medias
Authors: M. Katebi Jahromi, F. Emami
Venue: Proceedings of the 8th WSEAS international conference on Electronics, hardware, wireless and optical communication (2009)

In this paper we studied the operation of a five pumped backward distributed Raman amplifier with two different types of fiber mediums; dispersion shifted fiber and z-fiber. We computed the optimized configuration, the signal power and the equivalent noise figure for two types of transferring fiber mediums. We found that, the dispersion shifted fibers have better noise factor and have more uniform signal power respect to z-fibers; so the fiber parameters have strong effects on the operation of Raman amplifiers.
SNMP monitoring with Nagios
Authors: Jason Ellison
Venue: Linux Journal (2009)

Monitor Dell servers with SNMP and Nagios. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A Dual Formulation of the TV-Stokes Algorithm for Image Denoising
Authors: Christoffer A. Elo, Alexander Malyshev, Talal Rahman
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

We propose a fast algorithm for image denoising, which is based on a dual formulation of a recent denoising model involving the total variation minimization of the tangential vector field under the incompressibility condition stating that the tangential vector field should be divergence free. The model turns noisy images into smooth and visually pleasant ones and preserves the edges quite well. While the original TV-Stokes algorithm, based on the primal formulation, is extremely slow, our new dual algorithm drastically improves the computational speed and possesses the same quality of denoising. Numerical experiments are provided to demonstrate practical efficiency of our algorithm.
A Hybrid LS/CP Approach to Solve the Weekly Log-Truck Scheduling Problem
Authors: Nizar Hachemi, Michel Gendreau, Louis-Martin Rousseau
Venue: Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2009)

We present a hybrid approach to solve the log-truck scheduling problem (LTSP), which combines routing and scheduling of forest vehicles and includes aspects such as multiple products and inventory management. The LTSP is closely related to some routing problems encountered in other industries, in particular, so called "pick-up and delivery problems". In general, the LTSP are more complex than classical PDP, since in the LTSP we must synchronise trucks and log-loaders to avoid as much as possible waiting times.
Exploiting hardware/software interactions for analyzing embedded systems
Authors: Frank Mueller
Venue:  (2008)

Embedded systems are often subject to real-time timing constraints. Such systems require determinism to ensure that task deadlines are met. The knowledge of the bounds on worst-case execution times (WCET) of tasks is a critical piece of information required to achieve this objective. One limiting factor in designing real-time systems is the class of processors that may be used. Contemporary processors with their advanced architectural features, such as out-of-order execution, branch prediction, speculation, and prefetching, cannot be statically analyzed to obtain WCETs for tasks as they introduce non-determinism into task execution, which can only be resolved at run-time. Such micro-processors are tuned to reduce average-case execution times at the expense of predictability. Hence, they do not find use in hard real-time systems. On the other hand, static timing analysis derives bounds on WCETs but requires that bounds on loop iterations be known statically, i.e., at compile time. This limits the class of applications that may be analyzed by static timing analysis and, hence, used in a real-time system. Finally, many embedded systems have communication and/or synchronization constructs and need to function on a wide spectrum of hardware devices ranging from small microcontrollers to modern multi-core architectures. Hence, any single analysis technique (be it static or dynamic) will not suffice in gauging the true nature of such systems. This thesis contributes novel techniques that use combinations of analysis methods and constant interactions between them to tackle complexities in modern embedded systems. To be more specific, this thesis (I) introduces of a new paradigm that proposes minor enhancements to modern processor architectures, which, on interaction with software modules, is able to obtain tight, accurate timing analysis results for modern processors; (II) it shows how the constraint concerning statically bound loops may be relaxed and applied to make dynamic decisions at run-time to achieve power savings; (III) it represents the temporal behavior of distributed real-time applications as colored graphs coupled with graph reductions/transformations that attempt to capture inherent &ldquo;meaning&rdquo; in the application. To the best of my knowledge, these methods that utilize interactions between different sources of information to analyze modern embedded systems are a first of their kind.
The Semantic Web and e-Learning
Authors: Chris Daly
Venue: eLearn (2009)

The goal of the Semantic Web is to provide the capacity for computers to understand Web content that exists on systems and servers across the Internet, ultimately adding value to the content and opening rich new data, information, and knowledge frontiers. Billions of Web pages are downloaded daily and are easily understood by humans. The knowledge gap exists for computers as these pages are only structured in the hypertext markup language (HTML) formatting language. When applied to the realm of e-learning, be it content interactions or learner management, the potential to add value is almost limitless.
EMU: the emory user behavior data management system for automatic library search evaluation
Authors: Qi Guo, Ryan P. Kelly, Selden Deemer, Arthur Murphy, Joan A. Smith, Eugene Agichtein
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

We describe EMU, a system for collecting, managing, and mining the behavior data collected in the Emory libraries search system. We describe the data capture system based on the LibX browser plugin, the database management system for successfully storing, searching and exploring millions of resulting user interactions, and preliminary results of interesting queries and statistics that we are using to evaluate the effectiveness of library search tools.
School Innovative Management Model and Strategies: The Perspective of Organizational Learning
Authors: Jingyuan Zhao, Patricia Ordonez de Pablos
Venue: Information Systems Management (2009)

Along with knowledge-based economy coming, knowledge and innovation have been the core elements of national competitive power. Education plays an important role to improve individual or organizational creativity and innovational power. School innovational management is conducive to promoting creativity education. Additionally, it helps schools to acquire competitive power so as to develop constantly. This study discusses the related concepts and content of learning school and school innovative management; analyzes the impact factors of school organizational learning; and establishes the model of school innovative management based organizational learning. From the perspective of organizational learning, the study presents the strategies of school innovative management using for reference for China's schools.
Energy Smart Management of Scientific Data
Authors: Ekow Otoo, Doron Rotem, Shih-Chiang Tsao
Venue: Proceedings of the 21st International Conference on Scientific and Statistical Database Management (2009)

Scientific data centers comprised of high-powered computing equipment and large capacity disk storage systems consume considerable amount of energy. Dynamic power management techniques (DPM) are commonly used for saving energy in disk systems. These involve powering down disks that exhibit long idle periods and placing them in standby mode. A file request from a disk in standby mode will incur both energy and performance penalties as it takes energy (and time) to spin up the disk before it can serve a file. For this reason, DPM has to make decisions as to when to transition the disk into standby mode such that the energy saved is greater than the energy needed to spin it up again and the performance penalty is tolerable. The length of the idle period until the DPM decides to power down a disk is called idleness threshold.In this paper, we study both analytically and experimentally dynamic power management techniques that save energy subject to performance constraints on file access costs. Based on observed workloads of scientific applications and disk characteristics, we provide a methodology for determining file assignment to disks and computing idleness thresholds that result in significant improvements to the energy saved by existing DPM solutions while meeting response time constraints. We validate our methods with simulations that use traces taken from scientific applications.
A new motion management method for lung tumor tracking radiation therapy
Authors: Noriyasu Homma, Masao Sakai, Haruna Endo, Masatoshi Mitsuya, Yoshihiro Takai, Makoto Yoshizawa
Venue: WSEAS TRANSACTIONS on SYSTEMS (2009)

We propose a new motion management method for lung tumor tracking radiotherapy by using a novel time series prediction technique. In radiotherapy, the target motion often affects the conformability of the therapeutic dose distribution delivered to thoracic and abdominal tumors, and thus tumor motion monitoring systems have been developed. Even we can observe tumor motion accurately, however, radiotherapy systems may inherently have mechanical and computational delays to be compensated for synchronizing dose delivery with the motion. For solving the delay problem, we develop a novel system to predict complex time series of the lung tumor motion. An essential core of the system is an adaptive prediction modeling with a phase locking technique by which time-varying cyclic dynamics is transferred into a time invariant one. Simulation studies demonstrate that the proposed system can achieve a clinically useful high accuracy and long-term prediction of the average error 1.05 ± 0.99 [mm] at 1 [sec] ahead prediction.
Swarming to rank for information retrieval
Authors: Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-Thieme
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, Swarm-Rank, which is well-founded in a Particle Swarm Optimization framework. SwarmRank learns a ranking function by optimizing the combination of various types of evidences such content and hyperlink features, while directly maximizing Mean Average Precision, a widely used evaluation measure in Information Retrieval. Experimental results on well-established Learning To Rank benchmark datasets show that our approach significantly outperformed standard approaches (i.e., BM25) that only use basic statistical information derived from documents collections, and is found to be competitive with Ranking SVM and RankBoost in the task of ranking relevant documents at the very top positions.
Scheduling aware network flow models for multi-hop wireless networks
Authors: Vinay Kolar, Nael B. Abu-Ghazaleh
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

Network flow models have proven to be an effective tool in the analysis, optimization and design of network protocols. Critical to the success of these models in general multi-hop wireless networks (MHWNs) is an accurate estimation of the effect of CSMA scheduling. While the existing models capture coarse grained estimates of interference, they do not account for the substantial impact of MAC scheduling. On the other hand, accurate models of throughput in CSMA networks exist. However, they are unsuitable for use as a part of a network flow formulation because of their complexity and some of their underlying assumptions. This paper contributes an efficient and constructive model to estimate the effect of scheduling on interfering links in general MHWN settings. We integrate this approach with a network flow routing model which works with aggregate estimates of capacity to improve the quality of the solution. Simulation results show that accounting for scheduling effects leads to large improvements in the quality of the solution.
Concurrent use in an image management system
Authors: Előd Egyed-Zsigmond, Sonia Lajmi, Zoltán Iszlai
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

Manual image annotation and keyword based image search is a difficult and hardly formalizable problem. Image processing tools extract and assign keywords to the obtained images, but a manual annotation is almost always essential. In this paper we present a model and a system which addresses this issue. It is an online image annotation and management system, which traces the actions of the users and uses the capitalized experience to help them according to the case based reasoning paradigm. The system provides basic online image gallery features: uploading single or zipped images, describing images with keywords, importing xml based image descriptors, managing galleries … In addition the system helps image annotation tracing the actions of the user in order to propose additional keywords and images as well in the description as in the search phase. This help is provided by the capitalization and the reuse of user's experience based on the case based reasoning paradigm. After a short introduction, we describe our use trace model, the assistance strategies and present the developed prototype.
Fuzzy adaptive agent for supply chain management
Authors: Yain-Whar Si, Sio-Fan Lou
Venue: Web Intelligence and Agent Systems (2009)

Recent technological advances in electronic commerce have fuelled the need for designing effective strategies for supply chain management. These strategies are essential in guiding various activities within a supply chain such as component acquisition, inventory management, customer orders bidding, scheduling for production, and delivery. Among these activities, planning of raw material acquisition for inventory and bidding for customer orders can be extremely complex since such activities are required to deal with external entities such as suppliers and customers. Specifically, in the context of the manufacturing industry, acquiring raw materials for maintaining a flexible yet adequate inventory level is a complex issue due to the potential fluctuation in suppliers' production capacity and market demand. Designing an effective strategy for bidding customer orders is also an intricate problem due to the intense competition in fast changing market environments. In this paper, we describe the strategies of a supply chain management agent which adaptively adjusts its target inventory level and customer order bidding price based on fuzzy logic reasoning. The agent has competed in the 2006 Trading Agent Competition for Supply Chain Management and has achieved good results.