ppxscal/embedding_network huggingface dataset:
A semi-Lagrangian discontinuous Galerkin method for scalar advection by incompressible flows
Authors: M. Restelli, L. Bonaventura, R. Sacco
Venue: Journal of Computational Physics (2006)

A new, conservative semi-Lagrangian formulation is proposed for the discretization of the scalar advection equation in flux form. The approach combines the accuracy and conservation properties of the Discontinuous Galerkin (DG) method with the computational efficiency and robustness of Semi-Lagrangian (SL) techniques. Unconditional stability in the von Neumann sense is proved for the proposed discretization in the one-dimensional case. A monotonization technique is then introduced, based on the Flux Corrected Transport approach. This yields a multi-dimensional monotonic scheme for the piecewise constant component of the computed solution that is characterized by a smaller amount of numerical diffusion than standard DG methods. The accuracy and stability of the method are further demonstrated by two-dimensional tracer advection tests in the case of incompressible flows. The comparison with results obtained by standard SL and DG methods highlights several advantages of the new technique.
A Joint Transformation and Residual Image Descriptor for Morphometric Image Analysis using an Equivalence Class Formulation
Authors: Sokratis Makrogiannis, Ragini Verma, Bilge Karacali, Christos Davatzikos
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

Existing computational anatomy methodologies for morphometric analysis of medical images are often based solely on the shape transformation, typically being a diffeomorphism, that warps these images to a common template or vice versa. However, anatomical differences as well as changes induced by pathology, prevent the warping transformation from producing an exact correspondence. The residual image captures information that is not reflected by the diffeomorphism, and therefore allows us to maintain the entire morphological profile for analysis. In this paper we present a morphological descriptor which combines the warping transformation with the residual image in an equivalence class formulation, to characterize morphology of anatomical structures. Equivalence classes are formed by pairs of transformation and residual, for different levels of smoothness of the warping transformation. These pairs belong to the same equivalence class, since they jointly reconstruct the exact same morphology. Moreover, pattern classification methods are trained on the entire equivalence class, instead of a single pair, in order to become more robust to a variety of factors that affect the warping transformation, including the anatomy being measured. This joint descriptor is evaluated by statistical testing and estimation of class separation by classification, initially for 2-D synthetic images with simulated atrophy and subsequently for a volumetric dataset consisting of schizophrenia patients and healthy controls. Results of class separation indicate that this joint descriptor produces generally better and more robust class separation than using each of the components separately.
A Mobility-Aware Zone-Based Routing Protocol for Mobile Grid Computing
Authors: Rui Li, Renfa Li, Fei Yu, Jigang Wen
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

Mobile grid computing is a new computing paradigm which joins classic grid computing and mobile computing paradigm to provide dependable, seamless, pervasive access to mobile resources and services. It can use the underlying connectivity and routing protocols defined by MANET in order to perform resource discovery and access. This paper proposes a mobility-aware zoned routing protocol for MANET-MAFZP, which create zones in terms of the distance between each node to the Minimum ID node. Resort to the information provided by neighborhood nodes, our proposed protocol's request delay and control overhead is descend to O(2R). In addition, this protocol classifies the mobility pattern with neighbor node and reduces routing control overhead. Simulation results show that the protocol greatly decreased routing time and control overhead.
Bookshelf
Authors: Anthony Akins, Ajit Appari
Venue: IEEE Software (2006)

Two book reviews of The Best Software Writing I by Joel Spolsky and Return on Software: Maximizing the Return on Your Software Investment by Steve Tockey.
Comparative Analysis of Exon Skipping Patterns in Human and Mouse
Authors: Yu-Wei Chiu, Fang-Rong Hsu, Man-Kwan Shan
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

Alternative splicing of pre-mRNAs is a major mechanism of generating protein diversity in higher eukaryotes. It is well known that one of the major forms of alternative splicing is exon skipping, which alternatively skips specific exon during splicing. Previous research, by Miriami and his colleagues, was conducted by using a statistical method to identify two motifs both in upstream and downstream introns that were associated with exon skipping events. In this study, we employed pattern branching motif finding algorithm and approximate mining of consensus sequences algorithm. The data mining approach developed in the study showed its strength of being able to completely discover all possible motifs and made itself a more ideal approach compared to Miriami's.. statistical one. Furthermore, because of the similarities in genes between human and mouse, we compared the two species' motifs in our study. We also discovered the patterns are very likely associated with exon skipping event between human and mouse.
Trajectory Similarity Search in Spatial Networks
Authors: Eleftherios Tiakas, Apostolos N. Papadopoulos, Alexandros Nanopoulos, Yannis Manolopoulos, Dragan Stojanovic, Slobodanka Djordjevic-Kajan
Venue: Proceedings of the 10th International Database Engineering and Applications Symposium (2006)

In several applications, data objects are assumed to move on predefined spatial networks such as road segments, railways, invisible air routes. Moving objects may exhibit similarity with respect to their traversed paths, and therefore two objects can be correlated based on their path similarity. In this paper, we study similarity search for moving object trajectories for spatial networks. The problem poses some important challenges, since it is quite different from the case where objects are allowed to move without any motion restrictions. Experimental results performed on real-life spatial networks show that trajectory similarity can be supported in an effective and efficient manner, by using metric-based access methods.
Program verification as probabilistic inference
Authors: Sumit Gulwani, Nebojsa Jojic
Venue: ACM SIGPLAN Notices (2007)

In this paper, we propose a new algorithm for proving the validity or invalidity of a pre/postcondition pair for a program. The algorithm is motivated by the success of the algorithms for probabilistic inference developed in the machine learning community for reasoning in graphical models. The validity or invalidity proof consists of providing an invariant at each program point that can be locally verified. The algorithm works by iteratively randomly selecting a program point and updating the current abstract state representation to make it more locally consistent (with respect to the abstractions at the neighboring points). We show that this simple algorithm has some interesting aspects: (a) It brings together the complementary powers of forward and backward analyses; (b) The algorithm has the ability to recover itself from excessive under-approximation or over-approximation that it may make. (Because the algorithm does not distinguish between the forward and backward information, the information could get both under-approximated and over-approximated at any step.) (c) The randomness in the algorithm ensures that the correct choice of updates is eventually made as there is no single deterministic strategy that would provably work for any interesting class of programs. In our experiments we use this algorithm to produce the proof of correctness of a small (but non-trivial) example. In addition, we empirically illustrate several important properties of the algorithm.
Evolution of a Remote Access Facility for a PLL Measurement Course
Authors: M. J. Burbidge, I. Grout
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

This paper describes motivations for the further development of an existing remote access facility for use in teaching and learning of microelectronic circuit design and test principles. Initial development was based upon adaptation of 'at presence' material for use with an existing remote access laboratory based upon a standard internet link. The selected course material for adaptation was a PLL (phase-locked loop) circuit. Initially, the remote lab interface was developed with minimal modifications to the existing hardware and the process produced satisfactory results in terms of enhancement of the learning / teaching experience. However, it was evident that some aspects of the course material could be enhanced via appropriate modifications to the existing hardware and software framework. The goal is to work towards a blended learning infrastructure. The paper thus provides observations on the initial course development and then provides details of suggested and ongoing modifications to the material.
Modelling Bacterial Growth Patterns in the presence of Antibiotic
Authors: Ray Walshe
Venue: Proceedings of the 11th IEEE International Conference on Engineering of Complex Computer Systems (2006)

With recent growth in Systems Biology research there has been a significant increase in complex systems modeling research relating to biological systems. Multi-drug resistant (MDR) organisms are a threat not only as hospital-acquired infections, but also now as community-acquired infections. Multilocus sequence typing (MLST) can genetically characterize clones of several bacterial pathogens, allowing the tracking of hypervirulent/ antibiotic resistant lineages and the extent of acquisition and horizontal movement of the resistance genes [23][24][25]. This paper describes the initial research using an agent based cellular automata approach to model the complex subcellular processes in bacteria growth. Rules derived from a biological background simulate the growth of bacteria under a number of conditions including the presence of antibiotic. Altering the level of antibiotic in the bacteria environment and effects on the growth curves was explored and verified. Bacterial survival under a number of conditions (pH, temperature, nutrient concentration) emergent growth patterns and collective behaviour were also studied. A case study using the parameters reflecting the bacterium Escherichia coli was simulated and the results were validated. The software provides an in silico laboratory where bacteria can be grown under a variety of rules and conditions thereby learning the underlying mechanisms of behaviour at a local level, which collectively generate the global behaviour of interest.
Towards Partially Synchronous Overlays: Issues and Challenges
Authors: Jawwad Shamsi, Chunbo Chu, Monica Brockmeyer
Venue: Proceedings of the First International Workshop on Advanced Architectures and Algorithms for Internet Delivery and Applications (2005)

The main advantage of synchronous systems over asynchronous systems is that timing and reliability guarantees can be established ensuring a strong programming model for many applications. These strong guarantees are not provided by the current model of the Internet. However the Internet possesses some synchronous properties which can be exploited to observe partial synchrony, leading to a stronger programming model. In this paper, we argue the importance of synchrony and describe mechanisms which can be used for the construction of partially synchronous overlays on the Internet.
Using the Multi-Start and Island Models for Parallel Multi-Objective Optimization on the Computational Grid
Authors: M. Mezmaz, N. Melab, E-G. Talbi
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

The focus of this paper is on the parallel multi-start and island models of meta-heuristics within the context of multiobjective optimization on the computational grid. The combination of these two models often provides very effective parallel algorithms. However, experiments on large-size problem instances are often stopped before the convergence of these algorithms is achieved. The full exploitation of the cooperation needs a large amount of computational resources and the management of the fault tolerance issue. In this paper, we propose a grid-based fault-tolerant approach for these models and their implementation on the XtremWeb grid middleware. The approach has been experimented on the bi-objective Flow-Shop problem on a computational grid which is a multi-domain education network composed of 321 heterogeneous Linux PCs. The preliminary results, obtained after an execution time of several days, demonstrate that the use of grid computing allows to fully exploit effectively and efficiently the two parallel models and their combination for solving challenging optimization problems. An improvement of the effectiveness by over 60% compared to a serial meta-heuristic is obtained with a computational grid.
A novel interface to sensor networks using handheld augmented reality
Authors: Malinda Rauhala, Ann-Sofie Gunnarsson, Anders Henrysson
Venue: Proceedings of the 8th conference on Human-computer interaction with mobile devices and services (2006)

Augmented Reality technology enables a mobile phone to be used as an x-ray tool, visualizing structures and states not visible to the naked eye. In this paper we evaluate a set of techniques used augmenting the world with a visualization of data from a sensor network. Combining virtual and real information introduces challenges as information from the two domains might interfere. We have applied our system to humidity data and present a user study together with feedback from domain experts. The prototype system can be seen as the first step towards a novel tool for inspection of building elements.
Active Appearance Models for Automatic Fitting of 3D Morphable Models
Authors: Nathan Faggian, Andrew P. Paplinski, Jamie Sherrah
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

This paper presents a fast fitting method for 3D Morphable Models (3DMMs). In most cases fitting a Morphable Model to an image is done using slow non-linear optimization processes. We avoid this by introducing a relationship to Active Appearance Models (AAMs) that can be used to linearize the non-linear optimization problem of 3DMM fitting. Using the combination of a constrained AAM and closed form 2D-3D fitting method for 3DMMs we show that a perceptually close 3D shape can be extracted from the AAM fittings. We show preliminary results of the method and a simplified exterior orientation solution. Finally we conclude with a tracking algorithm that is based on the combination of the AAM and 3DMM, presenting the tracking and reconstruction errors.
Weaves: a framework for reconfigurable programming
Authors: Joy Mukherjee, Srinidhi Varadarajan
Venue: International Journal of Parallel Programming (2005)

This paper presents a language independent runtime framework--called Weaves--for object based composition of unmodified code modules that enables selective sharing of state between multiple control flows through a process. Furthermore, the framework allows dynamic instantiation of code modules and control flows through them. In effect, weaves create intra-process modules (similar to objects in OOP) from code written in any language. Applications can be built by instantiating Weaves to form Tapestries of dynamically interacting code. The framework enables objects to be arbitrarily shared--it is a true superset of both processes as well as threads, with code sharing and fast context switching time similar to threads. Weaves does not require any special support from either the language or application code--practically any code can be weaved. Weaves also include support run-time loading and linking of object modules enabling the next generation of highly dynamic applications. This paper presents the elements of the Weaves framework and its implementation on the Linux platform over source-code independent ELF object files. The current implementation has been validated over Sweep3D, a benchmark for 3D discrete ordinates neutron transport (Koch et al. Trans. Am. Nucl. Soc. 65 (198) [1992]), and a user-level port of the Linux 2.4 family kernel TCP/IP protocol stack.
Interplay of energy and performance for disk arrays running transaction processing workloads
Authors: S. Gurumurthi, Jianyong Zhang, A. Sivasubramaniam, M. Kandemir
Venue: Proceedings of the 2003 IEEE International Symposium on Performance Analysis of Systems and Software (2003)

The growth of business enterprises and the emergence of the Internet as a medium for data processing has led to a proliferation of applications that are server-centric. The power dissipation of such servers has a major consequence not only on the costs and environmental concerns of power generation and delivery, but also on their reliability and on the design of cooling and packaging mechanisms for these systems. This paper examines the energy and performance ramifications in the design of disk arrays which consume a major portion of the power in transaction processing environments. Using traces of TPC-C and TPC-H running on commercial servers, we conduct in-depth simulations of energy and performance behavior of disk arrays with different RAID configurations. Our results demonstrate that conventional disk power optimizations that have been previously proposed and evaluated for single disk systems' (laptops/workstations) are not very effective in server environments, even if we can design disks than have extremely fast spinup/spindown latencies and predict the idle periods accurately. On the other hand, tuning RAID parameters (RAID type, number of disks, stripe size etc.) has more impact on the power and performance behavior of these systems, sometimes having opposite effects on these two criteria.
Perceptual History Influences Neural Responses to Face and Body Postures
Authors: Tjeerd Jellema, David I. Perrett
Venue: Journal of Cognitive Neuroscience (2003)

We show that under natural viewing, the responses of cells the temporal lobe of the macaque to the sight of static head body postures is controlled by the sight of immediately actions. Cells in the anterior part of the superior sulcus responded vigorously to the sight of a face or posture that followed a particular body action, but not when it followed other actions. The effective action or posture presented in isolation or in different sequences failed to produce a response. Our results demonstrate that cells in the temporal cortex could support the formation of expectations about impending behavior of others.
An efficient fuzzy based neuro: genetic algorithm for stock market prediction
Authors: K. G. Srinivasa, K. R. Venugopal, L. M. Patnaik
Venue: International Journal of Hybrid Intelligent Systems (2006)

Stock market prediction is a complex and tedious task that involves the processing of large amounts of data, that are stored in ever growing databases. The vacillating nature of the stock market requires the use of data mining techniques like clustering for stock market analysis and prediction. Genetic algorithms and neural networks have the ability to handle complex data. In this paper, we propose a fuzzy based neuro-genetic algorithm - Fuzzy based Evolutionary Approach to Self Organizing Map(FEASOM) to cluster stock market data. Genetic algorithms are used to train the Kohonen network for better and effective prediction. The algorithm was tested on real stock market data of companies like Intel, General Motors, Infosys, Wipro, Microsoft, IBM, etc. The algorithm consistently outperformed regression model, backpropagation algorithm and Kohonen network in predicting the stock market values.
Performance Analysis of a Time-Threshold Based Bandwidth Allocation Scheme for Data Calls in Cellular Networks
Authors: Idil Candan, Muhammed Salamah
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

In this paper, we developed an analytical model of a time-threshold based bandwidth allocation scheme for data calls in cellular networks. The scheme is based on monitoring the elapsed real time of handoff calls and according to a time threshold parameter, handoff calls are either prioritized or treated as new calls. The scheme is modeled using a onedimensional markov chain and numerical analysis is presented to estimate blocking probabilities of new calls, dropping probabilities of handoff calls and system utilization. The scheme is simulated under different network conditions. It is observed that analytical results closely match the simulation results. The results show that the proposed scheme yields a considerable enhancement in terms of performance/cost ratio when compared with the conventional schemes.
Robust decentralized fast-output sampling technique based power system stabilizer for a multi-machine power system
Authors: Rajeev Gupta, B. Bandyopadhyay, A. M. Kulkarni
Venue: International Journal of Systems Science (2005)

Power-system stabilizers (PSSs) are added to excitation systems to enhance the damping during low-frequency oscillations, In this paper, the design of robust decentralized PSS for four machines with a 10-bus system using fast-output sampling feedback is proposed. The nonlinear model of a multimachine system is linearized at different operating points, and 16 linear state space models are obtained. For all of these plants, a common stabilizing state feedback gain, F, is obtained. A robust decentralized fast-output sampling feedback gain which realizes this state feedback gain is obtained using LMI approach. This method does not require all the states of the system for feedback and is easily implementable. This robust decentralized fast-output sampling control is applied to a nonlinear plant model of several machines at different operating (equilibrium) points. This method yields encouraging results for the design of power-system stabilizers.
Tracking of the Articulated Upper Body on Multi-View Stereo Image Sequences
Authors: Julius Ziegler, Kai Nickel, Rainer Stiefelhagen
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

We propose a novel method for tracking an articulated model in a 3D-point cloud. The tracking problem is formulated as the registration of two point sets, one of them parameterised by the model's state vector and the other acquired from a 3D-sensor system. Finding the correct parameter vector is posed as a linear estimation problem, which is solved by means of a scaled unscented Kalman filter. Our method draws on concepts from the widely used iterative closest point registration algorithm (ICP), basing the measurement model on point correspondences established between the synthesised model point cloud and the measured 3D-data. We apply the algorithm to kinematically track a model of the human upper body on a point cloud obtained through stereo image processing from one or more stereo cameras. We determine torso position and orientation as well as joint angles of shoulders and elbows. The algorithm has been successfully tested on thousands of frames of real image data. Challenging sequences of several minutes length where tracked correctly. Complete processing time remains below one second per frame.