ppxscal/embedding_network huggingface dataset:
Reliability validation of group membership services for x-by-wire protocols
Authors: Philip Koopman
Venue:  (2005)

Distributed fault tolerance algorithms are used for many ultra-reliable systems. For example, aviation fly-by-wire and automotive drive-by-wire network protocols need to reliably deliver data despite the presence of faults. Careful design is required, since ultra-reliable systems permit a failure rate on the order of just 10&minus;9 failures per hour. Unfortunately, investing more effort at the design stage does not assure a more reliable product if no objective measurement technique is used at this stage. The key idea of this dissertation is to estimate the reliability of a service by measuring the probability that the algorithm's maximum fault assumption will be violated. An algorithm's maximum fault assumption states the number of active faults that can be tolerated. The service (and the system) may fail if this assumption is violated. The maximum fault assumption can be tested at design time, before costly design commitments have been made. This dissertation defines a methodology to measure the reliability of a service's maximum fault assumption. The methodology is applied to clock synchronization and group membership services from three safety-critical protocols&mdash;the FlexRay Consortium's FlexRay protocol, TTTech's Time Triggered Protocol Class C (TTP/C), and NASA Langley's Scalable Processor Independent Design for Electromagnetic Resilience (SPIDER). First, I compose an extensive, reusable physical fault model for the aviation and automotive domains. Next, I show how to map this physical fault model to the hybrid fault models in the specifications. For each protocol, I define a Markov model template consisting of an extensible set of states and transitions. Over twenty thousand models are then generated and solved using the NASA Langley Semi-markov Unreliability Range Estimator tool suite. The methodology identifies the type of fault expected to cause the most failures, and locates trade-off points in the design space where a different fault type becomes dominant. Armed with this information, a designer can target improvements to create and validate a more reliable service. For FlexRay clock synchronization, the Welch and Lynch and the Strictly Omissive formally proven services are compared. For TTP/C and SPIDER membership, customizing the fault diagnosis algorithms to handle transient faults improves the overall estimated reliability.
Enhancing Performance and Saving Energy in CMOS DCVSL Gates by Using a New Transistor Sizing Algorithm
Authors: N. Masoumi, M. Ahmadian, F. Raissi, M. Masoumi, J. Ghasemi
Venue: Proceedings of the Fifth International Workshop on System-on-Chip for Real-Time Applications (2005)

In this paper we describe a new algorithm for transistor sizing in CMOS DCVSL (Differential Cascode Voltage Switch Logic) digital circuits. Our proposed method has two different approaches with low computational burden, mathematical based and genetic algorithm based. Using our transistor sizing algorithm, we minimized the propagation delay of a DCVSL full-adder and a DCVSL XOR in 0.5 um CMOS technology. At first, the optimum sizes of these circuits were calculated to obtain the minimum propagation delay. Then the final transistor sizes were obtained by trading off speed, energy and area to meet a set of performance requirements.
A MATLAB Toolbox for Robotic Manipulators
Authors: D. N. Vila-Rosado, J. A. Dominguez-Lopez
Venue: Proceedings of the Sixth Mexican International Conference on Computer Science (2005)

MATLAB toolboxes have been very useful to teach and train without the need for the physical system. Especially in the robotics field, using simulations avoids the considerable cost of building a full robot manipulator. For robotics, there was only one MATLAB toolbox, which has several limitations. These limitations have been cured in the toolbox reported in this paper. Also, there have been some additions to make the toolbox robust and more complete. Some of these improvements are using a closed-form solution for the inverse kinematics, a tough path and trajectory generation. In addition, an end effector (i.e., a two-fingered gripper) has been added, hence the user can simulate a robot which manipulates objects. The full toolbox and its documentation can be freely downloaded from internet.
Comparative Exon Prediction based on Heuristic Coding Region Alignment
Authors: Shu Ju Hsieh, Yun Sheng Chung, Chuan Yi Tang, Chun Yuan Lin
Venue: Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks (2005)

Identifying protein coding genes is one of most challenging problems in computational molecular biology. With increasing numbers of sequenced eukaryotic genomes and syntenic maps across species, it is possible to apply genomic comparison for gene recognition. Here, we propose a program, EXONALIGN, which simultaneously aligns and predicts exons between homologous genomic sequences. The program applies CORAL (COding Region ALignment), a heuristic linear time alignment tool, to determine whether the regions following the conserved splice signals pairs are significant or not. The approach which combines the intrinsic splice site strength with the conservation of protein coding regions and exon-intron structures reduces the computation time and increases the prediction accuracy. EXONALIGN was tested on ROSETTA data set of 117 human-mouse homologous sequence pairs. At the exon level the sensitivity and specificity of EXONALIGN are respectively 89% and 88%, and both are 98% at the nucleotide level. The rates of missing exons and wrong exons are as low as 2%.
A Power-Aware Run-Time System for High-Performance Computing
Authors: Chung-hsing Hsu, Wu-chun Feng
Venue: Proceedings of the 2005 ACM/IEEE conference on Supercomputing (2005)

For decades, the high-performance computing (HPC) community has focused on performance, where performance is defined as speed. To achieve better performance per compute node, microprocessor vendors have not only doubled the number of transistors (and speed) every 18-24 months, but they have also doubled the power densities. Consequently, keeping a large-scale HPC system functioning properly requires continual cooling in a largemachine room, thus resulting in substantial operational costs. Furthermore, the increase in power densities has led (in part) to a decrease in system reliability, thus leading to lost productivity. To address these problems, we propose a power-aware algorithm that automatically and transparently adapts its voltage and frequency settings to achieve significant power reduction and energy savings with minimal impact on performance. Specifically, we leverage a commodity technology called "dynamic voltage and frequency scaling" to implement our power-aware algorithm in the run-time system of commodity HPC systems.
Analog Macromodeling for Combined Resistive Vias, Resistive Bridges, and Capacitive Crosstalk Delay Faults
Authors: Shweta Chary, Michael L. Bushnell
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

The single stuck-at fault model is ineffective in detecting non-traditional resistive via, resistive bridge, and capacitive crosstalk coupling faults that cause timing failures in high-frequency digital circuits. We propose a new combined resistive via, resistive bridging, and capacitive coupling fault model. We use an analog macromodel of the fault to generate tests with a multiple delay, simulation-based, sequential path-delay fault digital fault simulator for automatic test-pattern generation (ATPG). The focus of this paper is the analog macromodels, whereas a companion paper [1] gives the ATPG method. We characterize the delay due to the via resistance and R and C couplings at the fault site, with many variations, using analog simulation and store this in the precomputed macromodel. The macromodel supplies the extra line delay resulting from the fault during ATPG, which eliminates analog simulation during fault simulation. Unlike Breuer [2], we use simulation-based sequential ATPG, rather than PODEM, with this macromodel to obtain more latitude and accuracy for complex fault models for deep submicron (DSM) circuits. We present the various validated analog macromodels for a 0.25 µm TSMC MOSIS process.
Runtime-Coordinated Scalable Incremental Checksum Testing of Combinational Circuits
Authors: Stefan Andrei, Wei-Ngan Chin, Albert M. K. Cheng, Yongxin Zhu
Venue: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2005)

Circuit testing is the most significant cost in modern chip design and production. Due to the complexity in terms of millions of gates, manufacturers often have to truncate test patterns to make the testing feasible on ATEs with limited capacities. In this paper, we present a novel approach to this challenge by run-time coordinating the algorithm and ATE. A unique combination of a #SAT solver, checksum computation and frame testing enables the efficient incremental testing. Unlike checksums from the communication domain which can only detect the existence of stuck-at faults, our approach differentiates by also locating them. In our experimental results, our method further demonstrates a shorter testing time.
Media processing workflow design and execution with ARIA
Authors: Lina Peng, Gisik Kwon, K. Selçuk Candan, Kyung Ryu, Karam Chatha, Hari Sundaram, Yinpeng Chen
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

Recently, we introduced a novel ARchitecture for Interactive Arts (ARIA) middleware that processes, filters, and fuses sensory inputs and actuates responses in real-time while providing various Quality of Service (QoS) guarantees. The objective of ARIA is to incorporate realtime, sensed, and archived media and audience responses into live performances, on demand. An ARIA media workflow graph describes how the data sensed through media capture devices will be processed and what audio-visual responses will be actuated. Thus, each data object streamed between ARIA processing components is subject to transformations, as described by a media workflow graph. The media capture and processing components, such as media filters and fusion operators, are programmable and adaptable; i.e, the delay, size, frequency, and quality/precision characteristics of individual operators can be controlled via a number of parameters. In [1, 4, 5], we developed static and dynamic optimization algorithms which maximize the quality of the actuated responses, minimize the corresponding delay and the resource usage. In this demonstration, we present the ARIA GUI and the underlying kernel. More specifically, we describe how to design a media processing workflow, with adaptive operators, using the ARIA GUI and how to use the various optimization and adaptation alternatives provided by the ARIA kernel to execute media processing workflows.
Evolutionary Robotics: A New Scientific Tool for Studying Cognition
Authors: Inman Harvey, Ezequiel Di Paolo, Rachel Wood, Matt Quinn, Elio Tuci, Elio Tuci Iridia
Venue: Artificial Life (2005)

We survey developments in artificial neural networks, in behavior-based robotics, and in evolutionary algorithms that set the stage for evolutionary robotics ( ER) in the 1990s. We examine the motivations for using ER as a scientific tool for studying minimal models of cognition, with the advantage of being capable of generating integrated sensorimotor systems with minimal (or controllable) prejudices. These systems must act as a whole in close coupling with their environments, which is an essential aspect of real cognition that is often either bypassed or modeled poorly in other disciplines. We demonstrate with three example studies: homeostasis under visual inversion, the origins of learning, and the ontogenetic acquisition of entrainment.
Research note: Modeling distributed data representation and its effect on parallel data accesses
Authors: Dejiang Jin, Sotirios G. Ziavras
Venue: Journal of Parallel and Distributed Computing (2005)

PC clusters have emerged as viable alternatives for high-performance, low-cost computing. In such an environment, sharing data among processes is essential. Accessing the shared data, however, may often stall parallel executing threads. We propose a novel data representation scheme where an application data entity can be incarnated into a set of objects that are distributed in the cluster. The runtime support system manages the incarnated objects and data access is possible only via an appropriate interface. This distributed data representation facilitates parallel accesses for updates. Thus, tasks are subject to few limitations and application programs can harness high degrees of parallelism. Our PC cluster experiments prove the effectiveness of our approach.
Handwritten Document Offline Text Line Segmentation
Authors: C. Weliwitage, A. L. Harvey, A. B. Jennings
Venue: Proceedings of the Digital Image Computing on Techniques and Applications (2005)

In this paper, a method of text segmentation into lines of text known as cut text minimization (CTM) is described. Results applying the CTM method to the NIST data base examples of fifty two word handwritten paragraphs of the American Constitutions are given. The method uses a modified projection method to obtain starting points. Then an optimisation technique is applied which varies the cutting angle and start location to minimize the text pixels cut while tracking between the text lines. Also the method attempts to track around projecting ascenders or descenders by a line following technique. A comparison with the projections method is given. From the results, it is evident that the method is successful on quite distorted documents, and can correctly cut the text block into text lines with minimal incorrect partitioning of data into adjacent lines even when text lines have varying slope and there are penetrations into the space of adjacent lines. The CTM method does not assume text lines have a constant slope.
Evidence Combination for Traffic Adaptive Routing
Authors: M. Balasubramanian, Louise A. Perkins, S. S. Iyengar, Sumeet Dua, Donald H. Kraft
Venue: Proceedings of the 18th International Conference on Systems Engineering (2005)

We propose a novel traffic adaptive routing algorithm to achieve equal path utilization in dynamic networks. We choose traffic measured at each router and the trip-time measured between networks as the indicators of the network condition. We derive the states of the equal-cost paths by combining the evidences pointed by the traffic and trip-time measures using Dempster-Shafer (DS) theory of evidence. The DS theory computes a belief measure and takes into account any ignorance present in the information sources acquiring the evidences and the inherent uncertainty in the network paths due to their dynamic nature. Based on the states of the equal-cost paths determined using DS theory, the routers route data packets among the equal-cost paths proportional to their load conditions. For example, if equal-cost paths P₁ and P₂ as seen from router R are in low and high load condition respectively, the router R will route ⅔ of the data packets through P₁ and ⅓ through P₂. We modified the LINUX IP stack for adaptive routing and traffic measurements. The routing tables are updated every 30 seconds based on the states of the equal-cost paths determined using the DS theory. We demonstrate the algorithm in an interconnected network with LINUX machines configured as routers and show that the proposed evidence combination framework will result in improved path utilization and compare the performance with the per-packet mode of traffic distribution.
Probabilistic web image gathering
Authors: Keiji Yanai, Kobus Barnard
Venue: Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval (2005)

We propose a new method for automated large scale gathering of Web images relevant to specified concepts. Our main goal is to build a knowledge base associated with as many concepts as possible for large scale object recognition studies. A second goal is supporting the building of more accurate text-based indexes for Web images. In our method, good quality candidate sets of images for each keyword are gathered as a function of analysis of the surrounding HTML text. The gathered images are then segmented into regions, and a model for the probability distribution of regions for the concept is computed using an iterative algorithm based on the previous work on statistical image annotation. The learned model is then applied to identify which images are visually relevant to the concept implied by the keyword. Implicitly, which regions or the images are relevant is also determined. Our experiments reveal that the new method performs much better than Google Image Search and a simple method based on more standard content based image retrieval methods.
Weather Data Industry on Brink of "Explosion"
Authors: Greg Goth
Venue: IEEE Distributed Systems Online (2005)

Experts say the weather data industry is ripe for meteoric growth, whether developing better models for forecasting cataclysmic events or building a modern weather sensor network to feed raw data into large databases enabling those models to work.
Does dynamic cursor control gain improve the performance of selection task in wearable computing?
Authors: Ji-Young Hong, Haeng-Suk Chae, Sang Yoo, Moon-Ju Kim, Kwang-Hee Han
Venue: Proceedings of the Ninth IEEE International Symposium on Wearable Computers (2005)

Recent research investigating the use of a trackball mouse in a wearable computing context showed that users have difficulty moving the cursor to the correct location [1]. Dynamic gain control may make cursor not to slip out of the target [2]. In this study, we test the use of dynamic gain with a portable trackball mouse in improving users' performance in a pointing task Experimental results reveal that dynamic gain control improves the pointing task performance in terms of speed and index of performance [4] of hitting the targets.
Multi-Granularity Resource Reservations
Authors: Saowanee Saewong, Ragunathan (Raj) Rajkumar
Venue: Proceedings of the 26th IEEE International Real-Time Systems Symposium (2005)

Resource reservation has been recently supported by many real-time operating systems to provide applications with guaranteed and timely access to system resources. Typically, reservations are based on the worstcase requirements, and therefore can inflate resource demands unnecessarily. Many multimedia applications such as MPEG video streams (1) have high worst-case to average-case demand ratio and (2) can tolerate some deadline misses. To support such applications, we propose a "multi-granularity" reservation model. Instead of the classical {C, T, D} model of resource reservation, the multi-granular reserve specification is given by {{C, T, D}, . . . , {C^x, ε^xT_i}, . . . , {C^y, ε^yT_i}} which represents a guarantee of the highest-granularity reserve for C units of resource during every successive periodic interval of T only as long as the resource usage by each of its low-granularity reserves (e.g., C^x units of resource in every recurring time of ε^xT_i, ε^x ∈ Z^+) is maintained. This multi-granular reservation approach delivers higher system utilization than the pessimistic strategy of worst-case reservation and better temporal isolation than other stochastic and heuristic guarantees in the literature. We perform a detailed schedulability analysis of this model using deadline-monotonic scheduling and derive an appropriate admission control test. We also present detailed analyses and simulation results comparing our reservation scheme for MPEG-4streams with average-case resource reservation, constant bandwidth server (CBS), and (m, k)-firm guarantee.
Hybrid generative/discriminative classifier for unconstrained character recognition
Authors: Lionel Prevost, Loïc Oudot, Alvaro Moises, Christian Michel-Sendis, Maurice Milgram
Venue: Pattern Recognition Letters (2005)

Handwriting recognition for hand-held devices like PDAs requires very accurate and adaptive classifiers. It is such a complex classification problem that it is quite usual now to make co-operate several classification methods. In this paper, we present an original two stages recognizer. The first stage is a model-based classifier which store an exhaustive set of character models. The second stage is a pairwise classifier which separate the most ambiguous pairs of classes. This hybrid architecture is based on the idea that the correct class almost systematically belongs to the two more relevant classes found by the first classifier. Experiments on a 80,000 examples database show a 30% improvement on a 62 classes recognition problem. Moreover, we show experimentally that such an architecture suits perfectly for incremental classification.
Bio Molecular Engine: a bio-inspired environment for models of growing and evolvable computation
Authors: A. Gallini, C. Ferretti, G. Mauri
Venue: Proceedings of the 2005 workshops on Genetic and evolutionary computation (2005)

Evolutionary computation has been often used by computer scientists to evolve the morphologies and control systems of artificial life. Artificial 'brains', behaviour strategies, methods of communication, distributed problem solving and many other topics are commonly explored by using genetic algorithms and other evolutionary search techniques. We think that this approach may provide the general guidelines to efficiently manage and "design" computation on large and homogeneous lattices of simple, asynchronously interacting processing elements. Because of their structural simplicity, this kind of substrates will be suitable architectural models for computational machines based on molecular scale devices. In this paper we present an environment named Bio-molecular Engine (BME), in which different substrates can be simulated and used as "artificial worlds" where computational entities can rise, grow and evolve. In particular we discuss how to use a grid to evolutionary find a good solution to a well defined design issue: how much parallelism is good for a given problem computed in our environment.
Multi-Modal Human Verification Using Face and Speech
Authors: Changhan Park, Joonki Paik, Taewoong Choi, Soonhyob Kim, Youngouk Kim, Jaechan Namkung
Venue: Proceedings of the Fourth IEEE International Conference on Computer Vision Systems (2006)

In this paper, we propose a personal verification method using both face and speech to improve the rate of single biometric verification. False acceptance rate (FAR) and false rejection rate (FRR) have been a fundamental bottleneck of real-time personal verification. The proposed multimodal biometric method is to improve both verification rate and reliability in real-time by overcoming technical limitations of single biometric verification methods. The proposed method uses principal component analysis (PCA) for face recognition and hidden markov model (HMM) for speech recognition. It also uses fuzzy logic for the final decision of personal verification. Based on experimental results, the proposed system can reduce FAR down to 0.0001%, which provides that the proposed method overcomes the limitation of single biometric system and provides stable personal verification in real-time.
Implementing Mobile Environments using Learning Objects: The Athabasca University Digital Reading Room
Authors: Rory McGreal, Billy Cheung, Tony Tin, Steve Schafer
Venue: Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education (2005)

This investigation determined some of the better strategies for delivering educational resources to mobile devices from the Digital Reading Room (DRR) and the Athabasca University(AU) library catalogue using AirPac, making recommendations on the implementation of Mlearning as part of the AU elearning strategy. The primary research question addressed in this short paper is: What are the limitations and difficulties in delivering course materials to mobile devices?