ppxscal/embedding_network huggingface dataset:
Shift Invert Coding (SINV) for Low Power VLSI
Authors: Jayapreetha Natesan, Damu Radhakrishnan
Venue: Proceedings of the Digital System Design, EUROMICRO Systems (2004)

Low power VLSI circuit design is one of the most important issues in present day technology. One of the ways of reducing power in a CMOS circuit is to reduce the number of transitions on the bus and Bus Invert Coding is a widely popular technique for that. In this paper we introduce a new way of coding called the ShiftInv Coding that is superior to the bus invert coding technique. Our simulation results show a considerable reduction on the number of transitions over and above that obtained with bus invert coding. Further, the proposed technique requires only 2 extra bits for the low power coding, regardless of the bit-width of the bus and does not assume anything about the nature of the data.
Discovering Similar Patterns for Characterizing Time Series in a Medical Domain
Authors: Fernando Alonso, P. Cara&#x00e7;a-Valente, Lo&#x00ef;c Mart&#x00ed;nez, C&#x00e9;sar Montes
Venue: Knowledge and Information Systems (2003)

In this article, we describe the process of discovering similar patterns in time series and creating reference models for population groups in a medical domain, and particularly in the field of physiotherapy, using data mining techniques on a set of isokinetic data. The discovered knowledge was evaluated against the expertise of a physician specialized in isokinetic techniques, and applied in the I4 (Intelligent Interpretation of Isokinetic Information) project developed in conjunction with the Spanish National Center for Sports Research and Sciences for muscular diagnosis and rehabilitation, injury prevention, training evaluation and planning, etc., of elite athletes and ordinary people.
Real-Time Tasks with Data Output
Venue: Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium (2004)

A real-time task usually generates data. The studyon real-time tasks either ignores this fact like most ofthe research do, or models data as execution time likewhen handling multimedia data. On the other hand,the network research community usually pays littleattention to the data source other than assumingcertain characteristics. There are many real worldapplications where data is not generated at a constantrate during task execution, and the average data rateis not the same among tasks. In this paper we study anew task model with data output as an explicitparameter. We analyze the data output of such task set.We shall derive the data source parameters assumedby network studies. Different scheduling policy resultsin different data output curve, we look at this in detailwith simulations. Our work extends the real-timeresearch to cover a new set of real world applications;it also complements the network study on datatransmission.
Structuring Exception Handling for Dependable Component-Based Software Systems
Authors: Paulo Asterio de C. Guerra, Fernando Castor Filho, Vinicius Asta Pagano, Cecilia Mary F. Rubira
Venue: Proceedings of the 30th EUROMICRO Conference (2004)

Component-based development (CBD) is recognized today as the standard paradigm for structuring large software systems. However, the most popular component models, such as Enterprise Javabeans and DCOM, provide almost no guidance about how to incorporate exception handling into component-based systems. The problem of how to employ language-level exception handling mechanisms to incorporate fault-tolerance in component-based systems is recognized by CBD practitioners as very difficult and often not adequately solved, with negative impact on reliability and maintainability. We believe that the construction of dependable component-based systems requires both (i) a global exception handling strategy for inter-component composition and (ii) a local exception handling strategy for dealing with errors within the reusable components. In this paper we describe a general strategy for the development of fault-tolerant software components and their integration into dependable component-based software systems.
The design of robust multi-loop-cascaded hydro governors
Authors: Ilyas Eker
Venue: Engineering with Computers (2004)

In the present paper, a new multi-loop-cascaded governor is proposed for hydro turbine controls. A turbine model is obtained that covers the effects of the water hammer, travelling waves, inelastic water penstocks and head loss due to the friction. Plant parameter uncertainties are taken into account to investigate stability robustness. The polynomial H&#x221e; robust control design method is used to design the multi-loop-cascaded governor. Water and load disturbance, and permanent oscillations in the power systems such as inter-area modes are included in the robust design procedure. Robust performance is achieved by using parameterised dynamic weighting functions of the design theory. The designed governor ensures that the overall system remains asymptotically stable for all norm-bounded uncertainties. Simulation results show that the system performance specifications and stability margins are improved significantly even in the presence of parameter uncertainties.
Self-efficacy and mental models in learning to program
Authors: Vennila Ramalingam, Deborah LaBelle, Susan Wiedenbeck
Venue: ACM SIGCSE Bulletin (2004)

Learning to program is a unique experience for each student, and it is not fully understood why one person in an introductory programming course learns to program better and more quickly than the next. Self-efficacy is an individual's judgment of his or her ability to perform a task within a specific domain [1]. A mental model is a person's internal (mental) representation of real world objects and systems [9]. Research has shown that high self-efficacy and a good mental model are important to knowledge acquisition and transfer. This research investigates the effects of students' self-efficacy and mental models of programming on learning to program. The results show that self-efficacy for programming is influenced by previous programming experience and increases as a student progresses through an introductory programming course. The results also show that the student's mental model of programming influences self-efficacy and that both the mental model and self-efficacy affect course performance.
Maintaining Constant Frame Rates in 3D Texture-Based Volume Rendering
Authors: Daniel Weiskopf, Manfred Weiler, Thomas Ertl
Venue: Proceedings of the Computer Graphics International (2004)

3D texture-based volume rendering is a popular way of realizingdirect volume visualization on graphics hardware.However, the slice-oriented texture memory layout of manycurrent GPUs may lead to a strongly view-dependent performance,which reduces the fields of application of volumerendering. In this short technical note, we propose aslight modification of texture-based volume rendering thatmaintains roughly constant frame rates on any GPU architecture.The idea is to split the volume into smaller subvolumes.These bricks can be oriented in different directions;thus the varying performance for different viewingdirections is averaged out.
Uncooperative congestion control
Authors: Kartikeya Chandrayana, Shivkumar Kalyanaraman
Venue: Proceedings of the joint international conference on Measurement and modeling of computer systems (2004)

Traditionally uncooperative rate control schemes have implied open loop protocols such as UDP, CBR, etc. In this paper we show that closed loop uncooperative rate control schemes also exist and that the current AQM proposals cannot efficiently control their mis-behavior. Moreover, these proposals require that AQM be installed at all routers in the Internet which is not only expensive but requires significant network upgrade.In this paper we show that management of uncooperative flows need not be coupled with AQM design but can be viewed as edge based policing question. In this paper we propose an analytical model for managing uncooperative flows in the Internet by re-mapping their utility function to a target range of utility functions. This mapping can be achieved by transparently manipulating congestion penalties conveyed to the uncooperative users.The most interesting aspect of this research is that this task can be performed at the edge of the network with little state information about uncooperative flows. The proposed solution is independent of the buffer management algorithm deployed on the network. As such it works with Drop-Tail queues as well as any AQM scheme. We have analyzed the framework and evaluated it on various single and multi-bottleneck topologies with both Drop-Tail and RED. Our results show that the framework is robust and works well even in presence of background traffic and reverse path congestion.
Mapping of Microbial Pathways through Constrained Mapping of Orthologous Genes
Authors: Victor Olman, Hanchuan Peng, Zhengchang Su, Ying Xu
Venue: Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference (2004)

We present a novel computer algorithm for mapping biological pathways from one prokaryotic genome to another. The algorithm maps genes in a known pathway to their homologous genes (if any) in a target genome that is most consistent with (a) predicted orthologous gene relationship, (b) predicted operon structures, and (c) predicted co-regulation relationship of operons. Mathematically, we have formulated this problem as a constrained minimum spanning tree problem (called a Steiner network problem), and demonstrated that this formulation has the desired property through applications. We have solved this mapping problem using a combinatorial optimization algorithm, with guaranteed global optimality. We have implemented this algorithm as a computer program, called PMAP. Our test results on pathway mapping are highly encouraging -- we have mapped a number of pathways of H. influenzae, B. subtilis, H. pylori, and M. tuberculosis to E. coli using P-MAP, whose homologous pathways in E coli. are known and hence the mapping accuracy could be checked. We have then mapped known E. coli pathways in the EcoCyc database to the newly sequenced organism Synechococcus sp WH8102, and predicted 158 Synechococcus pathways. Detailed analyses on the predicted pathways indicate that P-MAPýs mapping results are consistent with our general knowledge about (local) pathways. We believe that P-MAP will be a useful tool for microbial genome annotation projects and inference of individual microbial pathways.
ATPG for Noise-Induced Switch Failures in Domino Logic
Authors: Rahul Kundu, R. D. (Shawn) Blanton
Venue: Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design (2003)

Domino circuits have been used in most modern high-performance microprocessordesigns because of their high speed, low transistor-count andhazard-free operation. However, with technology scaling, domino circuitsare increasingly susceptible to switch failures due to various noise sourcesthat include crosstalk, charge sharing and leakage. To test for such failuresin a manufactured chip, we describe a test pattern generation methodologythat generates specific test patterns to target such failures. These testpatterns activate noise from multiple sources such that their combined effectcauses a switch failure at a domino gate output. In addition, the testpatterns propagate the resulting error to an observable output within theduration of the circuit's clock cycle. The methodology has been implementedand validated using a domino multiplier circuit.
Greenhouse temperature modeling: a comparison between sigmoid neural networks and hybrid models
Authors: Raphael Linker, Ido Seginer
Venue: Mathematics and Computers in Simulation (2004)

Greenhouse operation and inside climate strongly depend on the outside weather. This implies that at least a year of data collection is required to cover the whole operational domain. Greenhouse-climate models calibrated with data limited to only a small region of the operating domain (weather and control), may therefore, produce erroneous predictions when applied to unfamiliar conditions.A comparison is made between the performance of three types of models trained with several seasonal subsets of data: (1) black-box (BB) sigmoid neural network (NN) trained only with in situ data, (2) hybrid physical-RBF (radial basis function) model, and (3) sigmoid neural network trained with a combination of in situ data and synthetic data generated with a physical model (termed 'prior-K sigmoid model').The BB sigmoid model gives the best predictions within the training domain, but performs very badly outside it. On the other hand, the hybrid and prior-K sigmoid models produce useful predictions over the whole operating domain, although they are slightly less accurate within the training domain.
On The Persistence of Computer Dreams - An Application Framework for Robust Adaptive Deployment
Authors: Alun R. Butler, Mohamed Ibrahim, Keith Rennolls, Liz Bacon
Venue: Proceedings of the Database and Expert Systems Applications, 15th International Workshop (2004)

The anticipated rewards of adaptive approaches will only be fully realised when autonomic algorithms can take configuration and deployment decisions that match and exceed those of human engineers. Such decisions are typically characterised as being based on a foundation of experience and knowledge. In humans, these underpinnings are themselves founded on the ashes of failure, the exuberance of courage and (sometimes) the outrageousness of fortune. In this paper we describe an application framework that will allow the incorporation of similarly risky, error prone and downright dangerous software artefacts into live systems - without undermining the certainty of correctness at application level. We achieve this by introducing the notion of application dreaming.
Text classification and named entities for new event detection
Authors: Giridhar Kumaran, James Allan
Venue: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval (2004)

New Event Detection is a challenging task that still offers scope for great improvement after years of effort. In this paper we show how performance on New Event Detection (NED) can be improved by the use of text classification techniques as well as by using named entities in a new way. We explore modifications to the document representation in a vector space-based NED system. We also show that addressing named entities preferentially is useful only in certain situations. A combination of all the above results in a multi-stage NED system that performs much better than baseline single-stage NED systems.
A Parallel Distributed Application of the Wireless Sensor Network
Authors: A. I. Khan, M. Isreb, R. S. Spindler
Venue: Proceedings of the High Performance Computing and Grid in Asia Pacific Region, Seventh International Conference (2004)

The paper describes the use of a wireless sensor network (WSN) for performing parallel pattern recognition computations.A complexity analysis indicates that the proposed algorithm is independent of the number of nodes and hence may scale up indefinitely with the network.It's shown that any material object once overlaid with a WSN, develops a latent associative memory, which enables the object to memorise some of its critical internal states for a real time comparison with those induced by the transient external conditions.
Predicting Real-Time Properties of Component Assemblies: A Scenario-Simulation Approach
Authors: Egor Bondarev, Johan Muskens, Peter de With, Michel Chaudron, Johan Lukkien
Venue: Proceedings of the 30th EUROMICRO Conference (2004)

This paper addresses the problem of predicting timing properties of multi-tasking component assemblies during the design phase. For real-time applications, it is of vital importance to guarantee that the timing requirements of an assembly will be met. We propose a simulation-based approach for predicting the real-time behaviour of an assembly based on models of its constituent components. Our approach extends the scenario-based method in [Prediction of Run-time Consumption in Multi-task Component-Based Systems] by offering a system model that is tailored to the domain of real-time applications. Contributions of this paper include the possibility to handle the following features: mutual exclusion, combinations of aperiodic and periodic tasks and synchronization constraints. The analytical approach we used in previous work cannot handle these features. Therefore, we introduce the simulation-based approach. Our simulator provides data about dynamic resource consumption and real-time properties like response time, blocking time and number of missed deadlines per task. We have validated our approach using a video-decoder application.
Extracting Contour Lines from Scanned Topographic Maps
Authors: Loh Mun San, Safie Mat Yatim, Noor Azam Md Sheriff, Nik Isrozaidi bin Nik Ismail
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualization (2004)

Contour lines are the main graphical element to characterize three-dimensional terrain on two-dimensional map sheets. The conversion of raster contour data to the corresponding vectors is still an interesting problem in the stage of research. In this paper, we suggest a contour extraction or simplification method, subsequently perform a fully automated, derivation of topographic map sheets containing simplified contour lines and inscriptions. The generated contour map is used to produce DEMs. The results concern the computation cost and the accuracy of the underlying contour lines information extracted.
Automated Protein Classification Using Consensus Decision
Authors: Tolga Can, Orhan Camoglu, Ambuj K. Singh, Yuan-Fang Wang
Venue: Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference (2004)

We propose a novel technique for automatically generating the SCOP classification of a protein structure with high accuracy. High accuracy is achieved by combining the decisions of multiple methods using the consensus of a committee (or an ensemble) classifier. Our technique is rooted in machine learning which shows that by judicially employing component classifiers, an ensemble classifier can be constructed to outperform its components. We use two sequence- and three structure-comparison tools as component classifiers. Given a protein structure, using the joint hypothesis, we first determine if the protein belongs to an existing category (family, superfamily, fold) in the SCOP hierarchy. For the proteins that are predicted as members of the existing categories, we compute their family-, superfamily-, and fold-level classifications using the consensus classifier. We show that we can significantly improve the classification accuracy compared to the individual component classifiers. In particular, we achieve error rates that are 3-12 times less than the individual classifiersý error rates at the family level, 1.5-4.5 times less at the superfamily level, and 1.1-2.4 times less at the fold level.
Inter-reference gap distribution replacement: an improved replacement algorithm for set-associative caches
Authors: Masamichi Takagi, Kei Hiraki
Venue: Proceedings of the 18th annual international conference on Supercomputing (2004)

We propose a novel replacement algorithm, called Inter-Reference Gap Distribution Replacement (IGDR), for set-associative secondary caches of processors. IGDR attaches a weight to each memory-block, and on a replacement request it selects the memory-block with the smallest weight for eviction. The time difference between successive references of a memory-block is called its Inter-Reference Gap (IRG). IGDR estimates the ideal weight of a memory-block by using the reciprocal of its IRG.To estimate this reciprocal, it is assumed that each memory-block has its own probability distribution of IRGs; from which IGDR calculates the expected value of the reciprocal of the IRG to use as the weight of the memory-block. For implementation, IGDR does not have the probability distribution; instead it records the IRG distribution statistics at run-time. IGDR classifies memory-blocks and records statistics for each class. It is shown that the IRG distributions of memory-blocks correlate their reference counts, this enables classifying memory-blocks by their reference counts. IGDR is evaluated through an execution-driven simulation. For ten of the SPEC CPU2000 programs, IGDR achieves up to 46.1% (on average 19.8%) miss reduction and up to 48.9% (on average 12.9%) speedup, over the LRU algorithm.
On achieving optimized capacity utilization in application overlay networks with multiple competing sessions
Authors: Yi Cui, Baochun Li, Klara Nahrstedt
Venue: Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures (2004)

In this paper, we examine the problem of large-volume data dissemination via overlay networks. A natural way to maximize the throughput of an overlay multicast session is to split the traffic and feed them into multiple trees. While in single-tree solutions, bandwidth of leaf nodes may remain largely under-utilized, multi-tree solutions increase the chances for a node to contribute its bandwidth by being a relaying node in at least one of the trees. We study the following problems: (1) What is the maximum capacity multi-tree solutions can exploit from overlay networks? (2) When multiple sessions compete within the same network, what is the relationship of two contradictory goals: achieving fairness and maximizing overall throughput? (3) What is the impact of IP routing in achieving at constraining the optimal performance of overlay multicast.We extend the multicommodity flow model to the case of overlay data dissemination, where each commodity is associated with an overlay session, rather than the traditional source-destination pair. We first prove that the problem is solvable in polynomial time, then propose an ε-approximation algorithm, assuming that each commodity can be split in arbitrary ways. The solution to this problem establishes the theoretical upper bound of overall throughput that any multi-tree solution could reach. We then study the same problem with the restriction that each commodity can only be split and fed into a limited number of trees. A randomized rounding algorithm and an online tree-construction algorithm are presented. All these algorithms are evaluated by extensive simulations.
uCLinux for Linux programmers
Authors: David McCullough
Venue: Linux Journal (2004)

Do you want the development ease of Linux or the low price of an MMU-less processor? How about both?
Semi-Balanced Colorings of Graphs: Generalized 2-Colorings Based on a Relaxed Discrepancy Condition
Authors: Jesper Jansson, Takeshi Tokuyama
Venue: Graphs and Combinatorics (2004)

We generalize the concept of a 2-coloring of a graph to what we call a semi-balanced coloring by relaxing a certain discrepancy condition on the shortest-paths hypergraph of the graph. Let G be an undirected, unweighted, connected graph with n vertices and m edges. We prove that the number of different semi-balanced colorings of G is: (1) at most n+1 if G is bipartite; (2) at most m if G is non-bipartite and triangle-free; and (3) at most m+1 if G is non-bipartite. Based on the above combinatorial investigation, we design an algorithm to enumerate all semi-balanced colorings of G in O(nm2) time.