ppxscal/embedding_network huggingface dataset:
Study on fault diagnostic strategy of intelligent magnetic detection microsystems
Authors: Yongqiang Wang, Wenzhong Lou, Ningjun Fan, Jianwei Hao, Dayin Zhang
Venue: Microsystem Technologies (2008)

Intelligent Magnetic Detection Microsystems (IMDM) are complex microsystems, which are used to obtain the information of motor flux and speed in single-driveway traffic system; the microsystems have to fulfill the task in a harsh environment of field, which would infect the reliability of system. An effective method to ensure maintenance cost and reliability is to integrate efficient built-in-test and monitoring function into IMDM, so testability analysis is introduced in the design of Microsystems. The Microsystems testing-points and diagnostic strategy are reasonably identified, which are beneficial to implement the rapid detection and fault isolation. This paper presents an approach to construct a fault message matrix based on the functional block diagram and signal flow chart of the microsystems. By analyzing the contribution of the testing-points to fault detection and fault isolation, the matrix is resolved step by step, the most necessary testing-points are identified and optimal diagnostic strategy is determined. Thus, the purpose of fault detection and fault isolation is achieved by the use of the fewest testing-points and short time.
Detection of stoichiometric inconsistencies in biomolecular models
Authors: Albert Gevorgyan, Mark G. Poolman, David A. Fell
Venue: Bioinformatics (2008)

Motivation: Metabolic modelling provides a mathematically rigorous basis for system-level analysis of biochemical networks. However, the growing sizes of metabolic models can lead to serious problems in their construction and validation. In this work, we describe a relatively poorly investigated type of modelling error, called stoichiometric inconsistencies. These errors are caused by incorrect definitions of reaction stoichiometries and result in conflicts between two fundamental physical constraints to be satisfied by any valid metabolic model: positivity of molecular masses of all metabolites and mass conservation in all interconversions. Results: We introduce formal definitions of stoichiometric inconsistencies, inconsistent net stoichiometries, elementary leakage modes and other important fundamental properties of incorrectly defined biomolecular networks. Algorithms are described for the verification of stoichiometric consistency of a model, detection of unconserved metabolites and inconsistent minimal net stoichiometries. The usefulness of these algorithms for effective resolving of inconsistencies and for detection of input errors is demonstrated on a published genome-scale metabolic model of Saccharomyces cerevisiae and one of Streptococcus agalactiae constructed using the KEGG database. Availability: http://mudshark.brookes.ac.uk/index.php/Albert_Gevorgyan Contact: dfell@brookes.ac.uk
Core cannibalization architecture: improving lifetime chip performance for multicore processors in the presence of hard faults
Authors: Bogdan F. Romanescu, Daniel J. Sorin
Venue: Proceedings of the 17th international conference on Parallel architectures and compilation techniques (2008)

To improve the lifetime performance of a multicore chip with simple cores, we propose the Core Cannibalization Architecture (CCA). A chip with CCA provisions a fraction of the cores as cannibalizable cores (CCs). In the absence of hard faults, the CCs function just like normal cores. In the presence of hard faults, the CCs can be cannibalized for spare parts at the granularity of pipeline stages. We have designed and laid out CCA chips composed of multiple OpenRISC 1200 cores. Our results show that CCA improves the chips' lifetime performances, compared to chips without CCA.
A GA-based movie-on-demand platform using multiple distributed servers
Authors: Gerassimos Barlas, Khaled El-Fakih
Venue: Multimedia Tools and Applications (2008)

In this paper we present the design and explore the performance of a unicast-based distributed system for Movie-on-Demand applications. The operation of multiple servers is coordinated with the assistance of an analytical framework that provides closed-form solutions to the content partitioning and scheduling problem, even under the presence of packet losses. The problem of mapping clients to servers is solved with a genetic algorithm, that manages to provide adequate, near-optimum solutions with a minimum of overhead. While previous studies focused on the static behavior of such a system, i.e. fixed a-priori known number of N servers and K clients commencing operation at the same time instance, this paper focuses on the dynamic behavior of such a system over a period of time with clients coming and going at random intervals. The paper includes a rigorous simulation study that shows how the system behaves in terms of a variety of metrics, including the average access time over all the requested media, in response to differences in the client arrival rate or the consumed server bandwidth. As it is shown, the proposed platform exhibits excellent performance characteristics that surpass traditional approaches that treat clients individually. This has been verified to be true up to extreme system loads, proving the scalability of the proposed content delivery scheme. The significance of our findings also stems from the assumption of unreliable communications, a first for the study of complete systems in this domain.
Opinion analysis for business intelligence applications
Authors: Adam Funk, Yaoyong Li, Horacio Saggion, Kalina Bontcheva, Christian Leibold
Venue: Proceedings of the first international workshop on Ontology-supported business intelligence (2008)

More than ever before, business analysts have access to public forums in which opinions and sentiments about companies, products, and policies are expressed in unstructured form. Mining information from public sources is of great importance to many business intelligence applications such as credit rating or company reputation. We have implemented a supervised machine-learning system which uses linguistic information to classify text by rating (good or bad, for example, or 1 to 5 stars). In an evaluation we have obtained good results in comparison with the state-of-the-art in opinion mining. We are further developing the system to classify each text according to a "qualitative variable" category from an ontology specially developed for Business Intelligence (BI). This work will allow us to generate RDF statements to populate a knowledge base for BI.
A methodology for computing end-to-end delay bounds in FIFO-multiplexing tandems
Authors: Luciano Lenzini, Enzo Mingozzi, Giovanni Stea
Venue: Performance Evaluation (2008)

In this paper we address the problem of finding end-to-end delay bounds for single leaky-bucket shaped flows subject to FIFO multiplexing in tandems of rate-latency nodes. More specifically, we focus on a methodology, called the Least Upper Delay Bound (LUDB) method, which is based on Network Calculus. The latter has already been used for computing delay bounds in tandems in which the paths of the flows are subject to particular restrictions. In this paper we generalize and extend it to tandems traversed by flows following arbitrary paths. We show that such methodology yields better bounds than those obtained through both per-node analysis and comparable methods proposed in the literature.
Exploiting contextual information in recommender systems
Authors: Linas Baltrunas
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

Recommender Systems help an on-line user to tame information overload and are being used now in complex domains where it could be beneficial to exploit context-awareness, e.g., in travel recommendation. Technically, in Recommender Systems we can interpret context as a set of constraints or preferences over the usage of items determined by the contextual conditions (e.g., today it is raining or the user is in a particular location). In fact, there is a lack of approaches to deal effectively with contextual data. This thesis investigates some approaches to exploit context in Recommender Systems. It provides a general architecture of context-aware Recommender Systems and analyzes separate components of this model. The main focus is to investigate new approaches that can bring a real added value to users. In this paper I also describe my initial results on item selection and item weighting for context-dependent Collaborative Filtering (CF). Moreover, I shall present my ongoing research on CF hybridization using context.
Systems with human monitors: a signal detection analysis
Authors: Robert D. Sorkin, David D. Woods
Venue: Human-computer interaction (1985)

Automated factories, the flightdecks of commercial aircraft, and the control rooms of power plants are examples of decision-making environments in which a human operator performs an alerted-monitor role. These human-machine systems include automated monitor or alerting subsystems operating in support of a human monitor. The automated monitor subsystem makes preprogrammed decisions about the state of the underlying process based on current inputs and expectations about normal/abnormal operating conditions. When alerted by the automated monitor subsystem, the human monitor may analyze input data, confirm or disconfirm the decision made by the automated monitor, and take appropriate further action. In this paper, the combined automated monitor-human monitor system is modeled as a signal detection system in which the human operator and the automated component monitor partially correlated noisy channels. The signal detection analysis shows that overall system performance is highly sensitive to the interaction between the human's monitoring strategy and the decision parameter, Ca, of the automated monitor subsystem. Usual design practice is to set Ca to a value that optimizes the automated monitor's detection and false alarm rates. Our analysis shows that this setting will not yield optimal performance for the overall human-machine system. Furthermore, overall system performance may be limited to a narrow range of realizable detection and error rates. As a result, large gains in system performance can be achieved by manipulating the parameters of the automated monitor subsystem in light of the workload characteristics of the human operator.
Visualization of Scientific Arts and Some Examples of Applications
Authors: N. Fujisawa, K. Brown, Y. Nakayama, J. Hyatt, T. Corby
Venue: Journal of Visualization (2008)

In this paper, implementation and visualization of scientific arts are described using some examples of application in subject research areas, such as sculpture, archeology, fine arts and information aesthetics, which have been discussed through the Scientific Art Session at FLUCOME9, Tallahassee, Florida, 2007-9. In the application to sculpture, stereo visualization techniques, such as anaglyph stereo visualization and integral imaging technique, are introduced to realize the three-dimensional geometry of sculpture to enhance visual impact on the art. The second application is the flow visualization technique for archeology, where the vortices behind the river stones are studied to understand the origin of patterns on Jomon pottery. Interestingly, such vortex patterns also appear in the paintings of fine arts. The third example is the visualization of information aesthetics, where the Web information, such as public media and stock market, are visualized through scientific techniques. These examples of visualization of scientific arts provide the present state of the art in interdisciplinary visualization.
Don't care words with an application to the automata-based approach for real addition
Authors: Jochen Eisinger, Felix Klaedtke
Venue: Formal Methods in System Design (2008)

Automata have proved to be a useful tool in infinite-state model checking, since they can represent infinite sets of integers and reals. However, analogous to the use of binary decision diagrams (bdds) to represent finite sets, the sizes of the automata are an obstacle in the automata-based set representation. In this article, we generalize the notion of "don't cares" for bdds to word languages as a means to reduce the automata sizes. We show that the minimal weak deterministic Büchi automaton (wdba) with respect to a given don't care set, under certain restrictions, is uniquely determined and can be efficiently constructed. We apply don't cares to improve the efficiency of a decision procedure for the first-order logic over the mixed linear arithmetic over the integers and the reals based on wdbas.
Architecture and Evaluation of an Asynchronous Array of Simple Processors
Authors: Zhiyi Yu, Michael J. Meeuwsen, Ryan W. Apperson, Omar Sattari, Michael A. Lai, Jeremy W. Webb, Eric W. Work, Tinoosh Mohsenin, Bevan M. Baas
Venue: Journal of Signal Processing Systems (2008)

This paper presents the architecture of an asynchronous array of simple processors (AsAP), and evaluates its key architectural features as well as its performance and energy efficiency. The AsAP processor calculates DSP applications with high energy-efficiency, is capable of high-performance, is easily scalable, and is well-suited to future fabrication technologies. It is composed of a two-dimensional array of simple single-issue programmable processors interconnected by a reconfigurable mesh network. Processors are designed to capture the kernels of many DSP algorithms with very little additional overhead. Each processor contains its own tunable and haltable clock oscillator, and processors operate completely asynchronously with respect to each other in a globally asynchronous locally synchronous (GALS) fashion. A 6×6 AsAP array has been designed and fabricated in a 0.18 μm CMOS technology. Each processor occupies 0.66 mm2, is fully functional at a clock rate of 520---540 MHz at 1.8 V, and dissipates an average of 35 mW per processor at 520 MHz under typical conditions while executing applications such as a JPEG encoder core and a complete IEEE 802.11a/g wireless LAN baseband transmitter. Most processors operate at over 600 MHz at 2.0 V. Processors dissipate 2.4 mW at 116 MHz and 0.9 V. A single AsAP processor occupies 4% or less area than a single processing element in other multi-processor chips. Compared to several RISC processors (single issue MIPS and ARM), AsAP achieves performance 27---275 times greater, energy efficiency 96---215 times greater, while using far less area. Compared to the TI C62x high-end DSP processor, AsAP achieves performance 0.8---9.6 times greater, energy efficiency 10---75 times greater, with an area 7---19 times smaller. Compared to ASIC implementations, AsAP achieves performance within a factor of 2---5, energy efficiency within a factor of 3---50, with area within a factor of 2.5---3. These data are for varying numbers of AsAP processors per benchmark.
RNA structure alignment by a unit-vector approach
Authors: Emidio Capriotti, Marc A. Marti-Renom
Venue: Bioinformatics (2008)

Motivation: The recent discovery of tiny RNA molecules such as µRNAs and small interfering RNA are transforming the view of RNA as a simple information transfer molecule. Similar to proteins, the native three-dimensional structure of RNA determines its biological activity. Therefore, classifying the current structural space is paramount for functionally annotating RNA molecules. The increasing numbers of RNA structures deposited in the PDB requires more accurate, automatic and benchmarked methods for RNA structure comparison. In this article, we introduce a new algorithm for RNA structure alignment based on a unit-vector approach. The algorithm has been implemented in the SARA program, which results in RNA structure pairwise alignments and their statistical signi.cance. Results: The SARA program has been implemented to be of general applicability even when no secondary structure can be calculated from the RNA structures. A benchmark against the ARTS program using a set of 1275 non-redundant pairwise structure alignments results in ¡«6% extra alignments with at least 50% structurally superposed nucleotides and base pairs. A.rst attempt to perform RNA automatic functional annotation based on structure alignments indicates that SARA can correctly assign the deepest SCOR classi.cation to >60% of the query structures. Availability: The SARA program is freely available through a World Wide Web server http://sgu.bioinfo.cipf.es/services/SARA/ Contact: mmarti@cipf.es Supplementary information:Supplementary data are available at Bioinformatics online.
Considering Data-Mining Techniques in User Preference Learning
Authors: Peter Vojtá, Alan Eckhardt
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03 (2008)

In this paper we deal with the problem of learning user preferences from user’s scoring of a small sample of objects with labels from a very small linearly ordered set. The main task of this process is to use these preferences for a top-k query, which delivers the user with an ordered list of k highest ranked objects. We deal with a problem of many ties in the highest score. Two algorithms for learning objective and utility functions are presented. We experiment and compare them to some classical data-mining methods. We use several measures (RMSE and rank correlations …) to evaluate efficiency of these methods.
A multi-objective scatter search for a dynamic cell formation problem
Authors: M. Aramoon Bajestani, M. Rabbani, A. R. Rahimi-Vahed, G. Baharian Khoshkhou
Venue: Computers and Operations Research (2009)

Cellular manufacturing system-an important application of group technology (GT)-has been recognized as an effective way to enhance the productivity in a factory. Consequently, a multi-objective dynamic cell formation problem is presented in this paper, where the total cell load variation and sum of the miscellaneous costs (machine cost, inter-cell material handling cost, and machine relocation cost) are to be minimized simultaneously. Since this type of problem is NP-hard, a new multi-objective scatter search (MOSS) is designed for finding locally Pareto-optimal frontier. To demonstrate the efficiency of the proposed algorithm, MOSS is compared with two salient multi-objective genetic algorithms, i.e. SPEA-II and NSGA-II based on some comparison metrics and statistical approach. The computational results indicate the superiority of the proposed MOSS compared to these two genetic algorithms.
On pseudoknot-bordered words and their properties
Authors: Lila Kari, Shinnosuke Seki
Venue: Journal of Computer and System Sciences (2009)

We study a generalization of the classical notions of bordered and unbordered words, motivated by biomolecular computing. DNA strands can be viewed as finite strings over the alphabet {A, G, C, T}, and are used in biomolecular computing to encode information. Due to the fact that A is Watson-Crick complementary to T and G to C, DNA single strands that are Watson-Crick complementary can bind to each other or to themselves forming so-called secondary structures. Most of these secondary structures are undesirable for biomolecular computational purposes since the strands they involve cannot further interact with other strands. This paper studies pseudoknot-bordered words, a mathematical formalization of pseudoknot-like inter- and intra-molecular structures. In this context, pseudoknot-unbordered words model DNA or RNA strands that will be free of such secondary structures. We obtain several properties of pseudoknot-bordered and -unbordered words. We also address following problem: Given a pseudoknot-unbordered word u, does {u}^+ consist of pseudoknot-unbordered words only? We show that this is not generally true. We find that a sufficient condition for {u}^+ to consist of pseudoknot-unbordered words only is that u be not primitive. All of our results hold for arbitrary antimorphic involutions, of which the DNA Watson-Crick complementarity function is a particular case.
Field Programmable Gate Arrays (FPGA) for Pixel Purity Index Using Blocks of Skewers for Endmember Extraction in Hyperspectral Imagery
Authors: Mingkai Hsueh, Chein-I Chang
Venue: International Journal of High Performance Computing Applications (2008)

Pixel purity index (PPI) is a popular endmember extraction algorithm because of its availability in the ENVI software. Recently, its hardware implementation has been explored by the so-called block of skewers (BOS) that can be used to generate desired skewers required by the PPI with significantly reduced computational complexity. This paper investigates the feasibility of field programmable gate arrays (FPGAs) design for the BOS of a modified PPI (called automatic PPI), referred to as BOS-APPI in high speed computation. Several block designs based on cube, pyramid, square and tetrahedron are also developed for the BOS-APPI along with their FPGA implementations as new reconfigurable systems to perform fast and onboard processing of hyperspectral imagery. Finally, the proposed FPGA designs are realized and substantiated by simulations.
GPU for Parallel On-Board Hyperspectral Image Processing
Authors: Javier Setoain, Manuel Prieto, Christian Tenllado, Francisco Tirado
Venue: International Journal of High Performance Computing Applications (2008)

Hyperspectral analysis algorithms exhibit inherent parallelism at multiple levels, and map nicely on high performance systems such as massively parallel clusters and networks of computers. Unfortunately, these systems are generally expensive and difficult to adapt to onboard data processing scenarios, in which low-weight and low-power integrated components are desirable to reduce mission pay-load. An exciting new development in this field is the emergence of programmable graphics hardware. Driven by the ever-growing demands of game industry, graphics processing units (GPUs) have evolved from expensive, application-specific units into highly parallel and programmable systems which can satisfy extremely high computational requirements at low cost. In this paper, we investigate GPU-based implementations of a morphological endmember extraction algorithm, which is used as a representative case study of joint spatial/spectral techniques for hyperspectral analysis. The proposed implementations are quantitatively compared and assessed in terms of both endmember extraction accuracy and parallel efficiency. Combined, these parts offer a thoughtful perspective on the potential and emerging challenges of implementing hyperspectral imaging algorithms on commodity graphics hardware.
Mapping mineralogical alteration using principal-component analysis and matched filter processing in the Takab area, north-west Iran, from ASTER data
Authors: F. Moore, F. Rastmanesh, H. Asadi, S. Modabberi
Venue: International Journal of Remote Sensing (2008)

The Takab area, located in north-west Iran, is an important gold mineralized region with a long history of gold mining. The gold is associated with toxic metals/metalloids. In this study, Advanced Space Borne Thermal Emission and Reflection Radiometer data are evaluated for mapping gold and base-metal mineralization through alteration mapping. Two different methods are used for argillic and silicic alteration mapping: selective principal-component analysis and matched filter processing (MF). Running a selective principal-component analysis using the main spectral characteristics of key alteration minerals enhanced the altered areas in PC2. MF using spectral library and laboratory spectra of the study area samples gave similar results. However, MF, using the image reference spectra from principal component (PC) images, produced the best results and indicated the advantage of using image spectra rather than library spectra in spectral mapping techniques. It seems that argillic alteration is more effective than silicic alteration for exploration purposes. It is suggested that alteration mapping can also be used to delineate areas contaminated by potentially toxic metals.