ppxscal/embedding_network huggingface dataset:
Hierarchical fuzzy controllers for an astronomical telescope tracking
Authors: Abdel-Fattah Attia
Venue: Applied Soft Computing (2009)

The paper presents an application of fuzzy logic controller (FLC) with hierarchically structured rule base for a two-link direct drive Celestron telescope. The hierarchical fuzzy logic controller (HFLC) is implemented, as nonlinear blocks used in a control system, for supervision of PID controller for position tracking of the telescope driven by electric motors. The HFLC is composed of two FLC stages connected in cascade. The input variables, for the first stage, of the HFLC are the position error and the rate of change in the position error. Then the output from the first stage and the position error integral are used as input variables for the second stage of the HFLC PID. The simulation results of the proposed HFLC PID, when the telescope is subjected to a unit step in reference position, are compared with the PID controller. The dynamic responses of the HFLC PID improve the rise time, damping factor and settling time compared with the PID controller. Also, the proposed techniques, hierarchical fuzzy PID controller, reduce the computation time due to reduction of rule base. The simulation results show the effectiveness of the proposed HFLC PID controller scheme as a promising technique.
Identifying robust plans through plan diagram reduction
Authors: Harish D., Pooja N. Darera, Jayant R. Haritsa
Venue: Proceedings of the VLDB Endowment (2008)

Estimates of predicate selectivities by database query optimizers often differ significantly from those actually encountered during query execution, leading to poor plan choices and inflated response times. In this paper, we investigate mitigating this problem by replacing selectivity error-sensitive plan choices with alternative plans that provide robust performance. Our approach is based on the recent observation that even the complex and dense "plan diagrams" associated with industrial-strength optimizers can be efficiently reduced to "anorexic" equivalents featuring only a few plans, without materially impacting query processing quality. Extensive experimentation with a rich set of TPC-H and TPC-DS-based query templates in a variety of database environments indicate that plan diagram reduction typically retains plans that are substantially resistant to selectivity errors on the base relations. However, it can sometimes also be severely counter-productive, with the replacements performing much worse. We address this problem through a generalized mathematical characterization of plan cost behavior over the parameter space, which lends itself to efficient criteria of when it is safe to reduce. Our strategies are fully non-invasive and have been implemented in the Picasso optimizer visualization tool.
A Wiki that knows where it is being used: insights from potential users
Authors: Maria Plummer, Linda Plotnick, Starr Roxanne Hiltz, Quentin Jones
Venue: ACM SIGMIS Database (2008)

With the advent of extensive wireless networks that blanket physically compact urban enclaves such as office complexes, shopping centers, or university campuses, it is possible to create software applications that provide location-based mobile/online services. One such application is CampusWiki, which integrates location information into a wiki structure. In the design science research reported in this paper, we employed a form of "action research" in which we engaged users as participants in an iterative process of designing and evaluating CampusWiki. Two qualitative studies were undertaken early in the design process in which semi-structured interviews were used to assess potential users' reactions to CampusWiki. Through this research, the designers were able to assess whether their intentions matched the mental models of potential users of the application. The results showed that although many of the perceived benefits were as designed by the developers, a misunderstanding of the location-aware feature led users to unanticipated concerns and expectations. These findings are important in guiding designers and implementers on the desirable and possibly undesirable features of such systems.
Using a file working set model to speed up the recovery of Peer-to-Peer backup systems
Authors: Eduardo M. Colaço, Marcelo Iury S. Oliveira, Alexandro S. Soares, Francisco Brasileiro, Dalton S. Guerrero
Venue: ACM SIGOPS Operating Systems Review (2008)

The high churn and low bandwidth characteristics of peer-to-peer (P2P) backup systems make recovery a time-consuming activity that increases the system's outage. This is especially disturbing from the user's perspective, because during outage the user is prevented from carrying out useful work. Nevertheless, at any given time, a user typically requires only a small number of her files to continue working. If the backup system is able to quickly recover these files, then the system's outage can be greatly reduced, even if a large portion of the data lost is still being recovered. In this paper, we evaluate the use of a file system working set model to support efficient recovery of a P2P backup system. By exploiting a simple LRU-like working set model, we have designed a recovery mechanism that substantially reduces outage and allows the user to return to work more quickly. The simulations we have performed show that even this simple model is able to reduce the outage by as much as 80%, when compared to the state-of-practice in P2P backup recovery.
A hierarchical design of case-based reasoning in the balanced scorecard application
Authors: Fong-Ching Yuan, Chaochang Chiu
Venue: Expert Systems with Applications: An International Journal (2009)

A balanced scorecard (BSC) is a management decision tool intended to be the corporate performance measurement. It also can play an important role in transforming an organization's mission and strategy into a balanced set of integrated performance measures. Assigning suitable weight to each level of balanced scorecard is crucial to conduct performance evaluation effectively. In this research a case-based reasoning (CBR) system has been developed to assist in assigning the suitable weights. Based on the balanced scorecard design, this study proposed a three-level feature weights design to enhance CBR's inference performance. For effective case retrieval, a genetic algorithm (GA) mechanism is employed to facilitate weighting all of levels in balanced scorecard and to determine the most appropriate three-level feature weights. The proposed approach is compared with the equal weights approach and the analytical hierarchy process (AHP) approach. The results indicate that the GA-CBR approach is able to produce more effective performance measurement.
A fuzzy statistics based method for mining fuzzy correlation rules
Authors: Nancy P. Lin, Hung-Jen Chen, Hao-En Chueh, Wei-Hua Hao, Chung-I Chang
Venue: WSEAS Transactions on Mathematics (2007)

Mining fuzzy association rules is the task of finding the fuzzy itemsets which frequently occur together in large fuzzy dataset, but most proposed methods may identify a fuzzy rule with two fuzzy itemsets as interesting when, in fact, the presence of one fuzzy itemsets in a record does not imply the presence of the other one in the same record. To prevent generating this kind of misleading fuzzy rule, in this paper, we construct a new method for finding relationships between fuzzy itemsets based on fuzzy statistics, and the generated rules are called fuzzy correlation rules. In our method, a fuzzy correlation analysis which can show us the strength and the type of the linear relationship between two fuzzy itemsets is used. By using thus fuzzy statistics analysis, the fuzzy correlation rules with the information about that two fuzzy not only frequently occur together in same records but also are related to each other can be generated.
Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis
Authors: Majid Masso, Iosif I. Vaisman
Venue: Bioinformatics (2008)

Motivation: Accurate predictive models for the impact of single amino acid substitutions on protein stability provide insight into protein structure and function. Such models are also valuable for the design and engineering of new proteins. Previously described methods have utilized properties of protein sequence or structure to predict the free energy change of mutants due to thermal (ΔΔG) and denaturant (ΔΔGH2O) denaturations, as well as mutant thermal stability (ΔTm), through the application of either computational energy-based approaches or machine learning techniques. However, accuracy associated with applying these methods separately is frequently far from optimal. Results: We detail a computational mutagenesis technique based on a four-body, knowledge-based, statistical contact potential. For any mutation due to a single amino acid replacement in a protein, the method provides an empirical normalized measure of the ensuing environmental perturbation occurring at every residue position. A feature vector is generated for the mutant by considering perturbations at the mutated position and it's ordered six nearest neighbors in the 3-dimensional (3D) protein structure. These predictors of stability change are evaluated by applying machine learning tools to large training sets of mutants derived from diverse proteins that have been experimentally studied and described. Predictive models based on our combined approach are either comparable to, or in many cases significantly outperform, previously published results. Availability: A web server with supporting documentation is available at http://proteins.gmu.edu/automute Contact: ivaisman@gmu.edu
The resource pooling principle
Authors: Damon Wischik, Mark Handley, Marcelo Bagnulo Braun
Venue: ACM SIGCOMM Computer Communication Review (2008)

Since the ARPAnet, network designers have built localized mechanisms for statistical multiplexing, load balancing, and failure resilience, often without understanding the broader implications. These mechanisms are all types of resource pooling whichmeans making a collection of resources behave like a single pooled resource. We believe that the natural evolution of the Internet is that it should achieve resource pooling by harnessing the responsiveness of multipath-capable end systems. We argue that this approach will solve the problems and limitations of the current piecemeal approaches.
Parallel Processing of Remotely Sensed Hyperspectral Images On Heterogeneous Networks of Workstations Using HeteroMPI
Authors: David Valencia, Alexey Lastovetsky, Maureen O'Flynn, Antonio Plaza, Javier Plaza
Venue: International Journal of High Performance Computing Applications (2008)

The development of efficient techniques for transforming massive volumes of remotely sensed hyperspectral data into scientific understanding is critical for space-based Earth science and planetary exploration. Although most available parallel processing strategies for information extraction and mining from hyperspectral imagery assume homogeneity in the underlying computing platform, heterogeneous networks of computers (HNOCs) have become a promising cost-effective solution, expected to play a major role in many on-going and planned remote sensing missions. In this paper, we develop a new morphological parallel algorithm for hyperspectral image classification using HeteroMPI, an extension of MPI for programming high-performance computations on HNOCs. The main idea of HeteroMPI is to automate and optimize the selection of a group of processes that executes a heterogeneous algorithm faster than any other possible group in a heterogeneous environment. In order to analyze the impact of many-to-one (gather) communication operations introduced by our proposed algorithm, we resort to a recently proposed collective communication model. The parallel algorithm is validated using two heterogeneous clusters at University College Dublin and a massively parallel Beowulf cluster at NASA's Goddard Space Flight Center.
Pangaea: a tightly-coupled IA32 heterogeneous chip multiprocessor
Authors: Henry Wong, Anne Bracy, Ethan Schuchman, Tor M. Aamodt, Jamison D. Collins, Perry H. Wang, Gautham Chinya, Ankur Khandelwal Groen, Hong Jiang, Hong Wang
Venue: Proceedings of the 17th international conference on Parallel architectures and compilation techniques (2008)

Moore's Law and the drive towards performance efficiency have led to the on-chip integration of general-purpose cores with special-purpose accelerators. Pangaea is a heterogeneous CMP design for non-rendering workloads that integrates IA32 CPU cores with non-IA32 GPU-class multi-cores, extending the current state-of-the-art CPU-GPU integration that physically "fuses" existing CPU and GPU designs. Pangaea introduces (1) a resource repartitioning of the GPU, where the hardware budget dedicated for 3D-specific graphics processing is used to build more general-purpose GPU cores, and (2) a 3-instruction extension to the IA32 ISA that supports tighter architectural integration and fine-grain shared memory collaborative multithreading between the IA32 CPU cores and the non-IA32 GPU cores. We implement Pangaea and the current CPU-GPU designs in fully-functional synthesizable RTL based on the production quality RTL of an IA32 CPU and an Intel GMA X4500 GPU. On a 65 nm ASIC process technology, the legacy graphics-specific fixed-function hardware has the area of 9 GPU cores and total power consumption of 5 GPU cores. With the ISA extensions, the latency from the time an IA32 core spawns a GPU thread to the time the thread begins execution is reduced from thousands of cycles to fewer than 30 cycles. Pangaea is synthesized on a FPGA-based prototype and runs off-the-shelf IA32 OSes. A set of general-purpose non-graphics workloads demonstrate speedups of up to 8.8x.
An Ambient Intelligent Agent Model Using Controlled Model-Based Reasoning to Determine Causes and Remedies for Monitored Problems
Authors: Rob Duell, Mark Hoogendoorn, Michel Klein, Jan Treur
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03 (2008)

This paper addresses the design of an ambient agent model that incorporates model-based reasoning methods for the analysis of internal causes of observed undesired behaviours of a human, and for determination of actions that remedy such causes. The models used are based on causal and dynamical relations and integrate numerical aspects. By the model-based reasoning methods hypotheses, observations and actions are generated. Control parameters within these processes are described that allow the ambient agent to focus the reasoning. These control parameters are related to each other and to specific domain and situation characteristics, such as time pressure, or criticality of a situation.
Address Generation Optimization for Embedded High-Performance Processors: A Survey
Authors: Guillermo Talavera, Murali Jayapala, Jordi Carrabina, Francky Catthoor
Venue: Journal of Signal Processing Systems (2008)

Nowadays embedded systems are growing at an impressive rate and provide more and more sophisticated applications characterized by having a complex array index manipulation and a large number of data accesses. Those applications require high performance specific computation that general purpose processors can not deliver at a reasonable energy consumption. Very long instruction word architectures seem a good solution providing enough computational performance at low power with the required programmability to speed up the time to market. Those architectures rely on compiler effort to exploit the available instruction and data parallelism to keep the data path busy all the time. With the density of transistors doubling each 18 months, more and more sophisticated architectures with a high number of computational resources running in parallel are emerging. With this increasing parallel computation, the access to data is becoming the main bottleneck that limits the available parallelism. To alleviate this problem, in current embedded architectures, a special unit works in parallel with the main computing elements to ensure efficient feed and storage of the data: the address generator unit, which comes in many flavors. Future architectures will have to deal with enormous memory bandwidth in distributed memories and the development of address generators units will be crucial for effective next generation of embedded processors where global trade-offs between reaction-time, bandwidth, energy and area must be achieved. This paper provides a survey of methods and techniques that optimize the address generation process for embedded systems, explaining current research trends and needs for future.
Simulation of microphysical structure associated with tropical cloud clusters using mesoscale model and comparison with TRMM observations
Authors: S. Abhilash, K. Mohankumar, S. Das
Venue: International Journal of Remote Sensing (2008)

An attempt has been made in the present study to examine the microphysical structure of a non-squall Tropical Cloud Cluster (TCC). Three-dimensional model simulations of cloud microphysical structure associated with a non-squall TCC occurred on 26 October 2005 over the South Bay of Bengal have been carried out. The initial conditions for the model simulations were improved by incorporating upper air radiosonde observations and Indian Mesosphere Stratosphere Troposphere (MST) radar wind observations through analysis nudging. The horizontal and vertical distribution of the cloud hydrometeor fields observed from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are compared to those simulated by a mesoscale model using a sophisticated microphysical scheme. Substantial differences are noticed in the amounts of cloud microphysical parameters, with simulated values of hydrometeors being higher than TMI retrievals. Spatial distribution of Cloud Liquid Water (CLW) and Rain Water (RNW) from TMI and model simulations correspond well with each other. The cloud microphysical structure during the initial and mature phases of the storm is also investigated. Comparisons of horizontal and vertical reflectivity structure from the TRMM-Precipitation Radar (PR) and those simulated by the model show reflectivity cores of values greater than 30 dBZ. The TRMM-PR echo tops are 3-4 km higher than the simulated echo tops. The 24 hr accumulated precipitation from model simulations are then verified with the combined rainfall product from the TRMM observations.
Modeling the efficiency of top Arab banks: A DEA-neural network approach
Authors: Mohamed M. Mostafa
Venue: Expert Systems with Applications: An International Journal (2009)

This study investigates the efficiency of top Arab banks using two quantitative methodologies: data envelopment analysis and neural networks. The study uses a probabilistic neural network (PNN) and a traditional statistical classification method to model and classify the relative efficiency of top Arab banks. Accuracy indices are used to assess the classification accuracy of the models. Results indicate that the predictive accuracy of NN models is quite similar to that of traditional statistical methods. The study shows that the NN models have a great potential for the classification of banks' relative efficiency due to their robustness and flexibility of modeling algorithms. From a policy perspective, this study highlights the economic importance of encouraging increased efficiency throughout the banking industry in the Arab world.
Personalized online document, image and video recommendation via commodity eye-tracking
Authors: Songhua Xu, Hao Jiang, Francis C.M. Lau
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

We propose a new recommendation algorithm for online documents, images and videos, which is personalized. Our idea is to rely on the attention time of individual users captured through commodity eye-tracking as the essential clue. The prediction of user interest over a certain online item (a document, image or video) is based on the user's attention time acquired using vision-based commodity eye-tracking during his previous reading, browsing or video watching sessions over the same type of online materials. After acquiring a user's attention times over a collection of online materials, our algorithm can predict the user's probable attention time over a new online item through data mining. Based on our proposed algorithm, we have developed a new online content recommender system for documents, images and videos. The recommendation results produced by our algorithm are evaluated by comparing with those manually labeled by users as well as by commercial search engines including Google (Web) Search, Google Image Search and YouTube.
On the frequency of copy number variants
Authors: Iuliana Ionita-Laza, Nan M. Laird, Benjamin A. Raby, Scott T. Weiss, Christoph Lange
Venue: Bioinformatics (2008)

Motivation: Estimating the frequency distribution of copy number variants (CNVs) is an important aspect of the effort to characterize this new type of genetic variation. Currently, most studies report a strong skew toward low-frequency CNVs. In this article, our goal is to investigate the frequencies of CNVs. We employ a two-step procedure for the CNV frequency estimation process. We use family information a posteriori to select only the most reliable CNV regions, i.e. those showing high rates of Mendelian transmission. Results: Our results suggest that the current skew toward low-frequency CNVs may not be representative of the true frequency distribution, but may be due, among other reasons, to the non-negligible false negative rates that characterize CNV detection methods. Moreover, false positives are also likely, as low-frequency CNVs are hard to detect with small sample sizes and technologies that are not ideally suited for their detection. Without appropriate validation methods, such as incorporation of biologically relevant information (for example, in our case, the transmission of heritable CNVs from parents to offspring), it is difficult to assess the validity of specific CNVs, and even harder to obtain reliable frequency estimates. Availability: Software implementing the methods described in this article is available for download at the following address: http://www.isites.harvard.edu/icb/icb.do?keyword=k36162 Contact: iionita@hsph.harvard.edu Supplementary informantion:Supplementary data are available at Bioinformatics online.
TheHotMap.com: Enabling Flexible Interaction in Next-Generation Web Search Interfaces
Authors: Orland Hoeber, Michael Brooks, Daniel Schroeder, Xue Dong Yang
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 (2008)

TheHotMap.com is an example of a next-generation Web search interface, wherein users are able to take an active role in the Web search process. Information that can assist searchers in their Web search tasks is presented in a visual manner. The system supports user interaction both during the query refinement process, as well as the search results exploration process. This paper describes the features of TheHotMap.com; usage log analysis illustrates the benefits of supporting flexible interaction within a single unified Web search interface.