A template-based approach to automatic face enhancement

This paper presents Visual ENhancement of USers (VENUS), a system able to automatically enhance male and female frontal facial images exploiting a database of celebrities as reference patterns for attractiveness. Each face is represented by a set of landmark points that can be manually selected or automatically localized using active shape models. The faces can be compared remapping the landmarks by means of Catmull–Rom splines, a class of interpolating splines particularly useful to extract shape-based representations. Given the input image, its landmarks are compared against the known beauty templates and moved towards the K-nearest ones by 2D image warping. The VENUS performances have been evaluated by 20 volunteers on a set of images collected during the Festival of Creativity, held in Florence, Italy, on October 2007. The experiments show that the 73.9% of the beautified faces are more attractive than the original pictures.     

A template-based approach for the generation of abstractable and reducible models of featured networks

We investigate the relationship between symmetry reduction and inductive reasoning when applied to model checking networks of featured components. Popular reduction techniques for combatting state space explosion in model checking, like abstraction and symmetry reduction, can only be applied effectively when the natural symmetry of a system is not destroyed during specification. We introduce a property which ensures this is preserved, open symmetry. We describe a template-based approach for the construction of open symmetric Promela specifications of featured systems. For certain systems (safely featured parameterised systems) our generated specifications are suitable for conversion to abstract specifications representing any size of network. This enables feature interaction analysis to be carried out, via model checking and induction, for systems of any number of featured components. In addition, we show how, for any balanced network of components, by using a graphical representation of the features and the process communication structure, a group of permutations of the underlying state space of the generated specification can be determined easily. Due to the open symmetry of our Promela specifications, this group of permutations can be used directly for symmetry reduced model checking.The main contributions of this paper are an automatic method for developing open symmetric specifications which can be used for generic feature interaction analysis, and the novel application of symmetry detection and reduction in the context of model checking featured networks.We apply our techniques to a well known example of a featured network – an email system.     

A fuzzy inference approach to template-based visual tracking

The tracking of visual features using appearance models is a well studied but still open area of computer vision. In the absence of knowledge about the structural constraints of the tracked object, the validity of the model can be compromised if only appearance information is used. We propose a fuzzy inference scheme that can be used to selectively update a given template-based model in tracking tasks. This allows us to track moving objects under translation, rotation, and scale changes with minimal feature drift. Moreover, no rigidity constraint needs to be enforced on the moving target. Some experiments have been performed using several targets, and the results are very close to the ground truth paths. The computational cost of our approach is low enough to allow its application in real-time tracking using modest hardware requirements.     

A template-based approach for parallel hexahedral two-refinement

We provide a template-based approach for generating locally refined all-hex meshes. We focus specifically on refinement of initially structured grids utilizing a 2-refinement approach where uniformly refined hexes are subdivided into eight child elements. The refinement algorithm consists of identifying marked nodes that are used as the basis for a set of four simple refinement templates. The target application for 2-refinement is a parallel grid-based all-hex meshing tool for high performance computing in a distributed environment. The result is a parallel consistent locally refined mesh requiring minimal communication and where minimum mesh quality is greater than scaled Jacobian 0.3 prior to smoothing.     

Computing the correlation dimension on a network of workstations

We present a parallel algorithm for computing the correlation dimension (D₂) from a time series generated by a dynamic system, using the method of correlation integrals, which essentially requires the computation of distances among a set of points in the state space. The parallelization is suitable for coarse-grained multiprocessor systems with distributed memory and is carried out using a virtually shared memory model. The algorithm simultaneously gives all the correlation integrals at various state space dimensions needed to estimate the D₂. Two versions are discussed: the first computes all distances between points; the second computes only distances less than a fixed ϵ, and employs a box-assisted approach and linked lists for an efficient search of neighbouring points. The algorithms, coded in Fortran 77, are tested on a heterogeneous network of workstations consisting of various DEC Alphas of different powers, interconnected by Ethernet; the Network Linda parallel environment is used. A detailed analysis of performance is carried out using the generalization of speed-up and efficiency for heterogeneous systems. The algorithms are fully asynchronous and so intrinsically balanced. In almost all the situations they provide a unitary efficiency. The second version greatly reduces the computational work, thus making it possible to tackle D₂ estimation even for medium and high-dimensional systems, where an extremely large number of points is involved. The algorithms can also be employed in other applicative contexts requiring the efficient computation of distances among a large set of points. The method proposed for the analysis of performance can be applied to similar problems. © 1998 John Wiley & Sons, Ltd.     

Parallel volume rendering on a network of workstations

An algorithm for parallel volume rendering on general-purpose workstations connected to a local area network (LAN) is presented. The algorithm is based on an efficient scan-line algorithm for volume rendering of irregular meshes. This algorithm computes images by intersecting the mesh with successive planes defined through each scan line and perpendicular to the screen. These planes are called scan planes. Image coherency from one scan plane to the next, and within each scan plane, speeds up image computation. The proposed algorithm is a modified version of the scan-line algorithm, suitable for parallelization and for handling large data sets efficiently. Based on an efficiency analysis of this version, it is concluded that minimal additional computing and communication are required if each processor is given the task of computing sequences of successive lines in the image. Ways of achieving good load balancing on a group of heterogeneous workstations that have arbitrary loads by other users are suggested     

Automatic mesh generation for mobile network dimensioning using evolutionary approach

We focus on the dimensioning process of cellular networks that addresses the evaluation of equipment global costs to cover a city. To deal with frequency assignment, that constitutes the most critical resource in mobile systems, the network is usually modeled as a pattern of regular hexagonal cells. Each cell represents the area covered by the signal of a transmitter or base station (BS). Our work emphasizes on the design of irregular hexagonal cells in an adaptive way. Hexagons transform themselves and adapt their shapes according to a traffic density map and to geometrical constraints. This process, called adaptive meshing (AM), may be seen as a solution to minimize the required number of BS to cover a region and to propose a basis for transmitter positioning. The solution we present to the mesh generation problem for mobile network dimensioning is based on the use of an evolutionary algorithm. This algorithm, called hybrid island evolutionary strategy (HIES), performs distributed computation. It allows the user to tackle problem instances with large traffic density map requiring several hundreds of cells. HIES combines local search fast computation on individuals, incorporated into a global island-like strategy. Experiments are done on one real case representing the mobile traffic load of the second French city of Lyon and on several other traffic maps from urban fictive data sets.     

Data-parallel programming on a network of heterogeneous workstations

We describe a compiler and run-time system that allow data-parallel programs to execute on a network of heterogeneous UNIX workstations. The programming language supported is Dataparallel C, a SIMD language with virtual processors and a global name space. This parallel programming environment allows the user to take advantage of the power of multiple workstations without adding any message-passing calls to the source program. Because the performance of Individual workstations in a multi-user environment may change during the execution of a Dataparallel C program, the run-time system automatically performs dynamic load balancing. We present experimental results that demonstrate the usefulness of dynamic load-balancing In a multi-user environment These results suggest that initially allocating the same amount of work to each processor and letting the dynamic load balancing algorithm adjust the load during program execution yields very good performance. Hence neither the compiler nor the run-time system need a priori knowledge of the speeds of the machines that will participate in a program execution.     

Molecular dynamics simulation on a network of workstations using a machine-independent parallel programming language.

Molecular dynamics simulations investigate local and global motion in molecules. Several parallel computing approaches have been taken to attack the most computationally expensive phase of molecular simulations, the evaluation of long range interactions. This paper reviews these approaches and develops a straightforward but effective algorithm using the machine-independent parallel programming language, Linda. The algorithm was run both on a shared memory parallel computer and on a network of high performance Unix workstations. Performance benchmarks were performed on both systems using two proteins. This algorithm offers a portable cost-effective alternative for molecular dynamics simulations. In view of the increasing numbers of networked workstations, this approach could help make molecular dynamics simulations more easily accessible to the research community.     

Radio-wave propagation prediction using ray-tracing techniques on a network of workstations (NOW)

Ray-tracing based radio wave propagation prediction models play an important role in the design of contemporary wireless networks as they may now take into account diverse physical phenomena including reflections, diffractions, and diffuse scattering. However, such models are computationally expensive even for moderately complex geographic environments. In this paper, we propose a computational framework that functions on a network of workstations (NOW) and helps speed up the lengthy prediction process. In ray-tracing based radio propagation prediction models, orders of diffractions are usually processed in a stage-by-stage fashion. In addition, various source points (transmitters, diffraction corners, or diffuse scattering points) and different ray-paths require different processing times. To address these widely varying needs, we propose a combination of the phase-parallel and manager/workers paradigms as the underpinning framework. The phase-parallel component is used to coordinate different computation stages, while the manager/workers paradigm is used to balance workloads among nodes within each stage. The original computation is partitioned into multiple small tasks based on either raypath-level or source-point-level granularity. Dynamic load-balancing scheduling schemes are employed to allocate the resulting tasks to the workers.We also address issues regarding main memory consumption, intermediate data assembly, and final prediction generation. We implement our proposed computational model on a NOW configuration by using the message passing interface (MPI) standard. Our experiments with real and synthetic building and terrain databases show that, when no constraint is imposed on the main memory consumption, the proposed prediction model performs very well and achieves nearly linear speedups under various workload. When main memory consumption is a concern, our model still delivers very promising performance rates provided that the complexity of the involved computation is high, so that the extra computation and communication overhead introduced by the proposed model do not dominate the original computation. The accuracy of prediction results and the achievable speedup rates can be significantly improved when 3D building and terrain databases are used and/or diffuse scattering effect is taken into account.     

Systematic design space exploration using a template-based ontological method

The realization of complex engineered systems using models that are typically incomplete, inaccurate and not of equal fidelity requires the understanding and prediction of process behavior in design. This necessitates the need for extending designer’s abilities in making design decisions that are robust, flexible and modifiable particularly in the early stages of design. To address this requirement, we propose in this paper, an ontology for design space exploration and a template-based ontological method that supports systematic design space exploration ensuring the determination of the right combination of design information that meets the different goals and requirements set for a process chain. Using the proposed method, a designer is able to (1) systematically adjust the design space in due time to manage the risks of errors accumulating and propagating during the design of different stages of the process chain, (2) improve the ability to communicate and understand the interactions between design information in the process chain. We achieve the said through (1) procedure for design space exploration is identified to determine the sequence of activities needed for the systematic exploration of design space under uncertainty; (2) the decision-based design information flow is archived using the design space exploration process template and represented by utilizing frame-based ontology to facilitate the management of re-usable information. We demonstrate the efficacy of this template-based ontological method for design space exploration by carrying out the design of a multi-stage hot rod rolling system in steel manufacturing process chain.     

A local approach to concept generation

Generating concepts defined by a binary relation between a set of properties and a set of objects is one of the important current problems encountered in Data Mining and Knowledge Discovery in Databases. We present a new algorithmic process which computes all the concepts, without requiring an exponential-size data structure, and with a good worst-time complexity analysis, which makes it competitive with the best existing algorithms for this problem. Our algorithm can be used to compute the edges of the lattice as well at no extra cost.      

A multiscale approach to network event identification using geolocated twitter data

The large volume of data associated with social networks hinders the unaided user from interpreting network content in real time. This problem is compounded by the fact that there are limited tools available for enabling robust visual social network exploration. We present a network activity visualization using a novel aggregation glyph called the clyph. The clyph intuitively combines spatial, temporal, and quantity data about multiple network events. We also present several case studies where major network events were easily identified using clyphs, establishing them as a powerful aid for network users and owners.     

A non-blocking locking method and performance evaluation on network of workstations

A network of workstation(NOW) can act as a single and scalable powerful computer by building a paralle and distributed computing platform on top of it.WAKASHI is such a platform system that supports persitent object management and makes full use of resources of NOW for high perforance transaction processing,One of the main difficulties to overcome is the bottleneck caused by concurrency control mechanism.Therefore,a non-bloking locking method is designed,by adopting several novel techniques to make it outperform the other typical locking methods such as 2PL:1) an SDG (Semantic Dependency Graph)based non-blocking locking protocol for fast transaction scheduling;2) a nmassively virtual memory based backup-page undo algorithm for fast restart;and 3) a multi-processor and multi-thread based transaction manager for fast execution.The new mechanisms have been implemented in WAKASHI and the performance comparison experiments have been implemented in WAKASHI and the performance comparison experiments with 2PL and DWDL have been done.The results show that the new method can outperform 2PL and DWDL under certain conditons.This is meaningful for choosing effective concurrency control mechanisms for improving transaction-rpocessing performance in NOW environments.     

Automated generation of test oracles using a model-driven approach

ContextSoftware development time has been reduced with new development tools and paradigms, testing must accompany these changes. In order to release software products in a timely manner as well as to minimise the impact of possible errors introduced during maintenance interventions, testing automation has become a central goal. Whilst research has produced significant results in test case generation and tools for test case (re)-execution, one of the most important open problems in testing is the automation of oracle generation. The oracle decides whether the program under test has or has not behaved correctly and then issues a pass/fail verdict. In most cases, writing the oracle is a time-consuming activity that, moreover, is manual in most cases.ObjectiveThis article automates two important steps in the test oracle: obtention of expected output and its comparison with the actual output, using a model-driven approach.MethodThe oracle automation problem is resolved using a model-driven framework, based on OMG standards: UML is used as metamodel and QVT and MOF2Text as transformation languages. The automated testing framework takes the models that describe the system as input, using UML notation and derives from them the test model and then the test code, following a model-driven approach. Test oracle procedures are obtained from a UML state machine.ResultsA complete executable test case at functional test level is obtained, composed of a test procedure with parametrized input test data and expected result automation.ConclusionThe oracle automation is obtained using a model-driven approach, test cases are obtained automatically from UML models. The model-driven testing framework was applied to an industrial application and has been useful to testing automation for the main functionalities in the system.     

A template-based baseball video scene classification using efficient playfield segmentation

In this paper, we present an effective and efficient framework for baseball video scene classification. The results of scene classification can be able to provide the ground for baseball video abstraction and high-level event extraction. In general, most conventional approaches are shot-based, which shot change detection and key-frame extraction are necessary prerequisite procedures. On the contrary, we propose a frame-based approach. In our scene classification framework, an efficient playfield segmentation technique is proposed, and then the reduced field maps are utilized as scene templates. Because the shot change detection and the key-frame extraction are not required in proposed method, the new framework is very simple and efficient. The experimental results have demonstrated that the effectiveness of our proposed framework for baseball videos scene classification, and it can be easily extended the template-based approach to other kinds of sports videos.     

Protocol converter generation using the STS approach

During the past four years, the authors have developed the Synchronizing Transition Set (STS) approach to solve protocol conversion problems for interconnecting heterogeneous computer networks. The STS approach is a 5-step formal algorithm: given service specifications of target protocols as its input, it derives a protocol converter specification as output. Several variations of the STS algorithm have been studied, and it was formally proven that all of these variations support the same correctness properties [1–4], such as conformity, liveness and transparency properties. Recently, the STS algorithm has been fully implemented in an STS protocol converter generation package. The package is written in the C language under a standard UNIX operating system. It needs less than 1000 lines of C statements to fully implement the STS algorithm. Moreover, to generate a converter between some classical example protocols, such as ABP (alternating bit protocol) and go-back-n protocols, it only takes a few seconds to derive a correct protocol converter specification using a desktop workstation. In this paper, the STS algorithm and its implementation are presented.     

A distributed processing algorithm for solving integer programs using a cluster of workstations

The sequential branch and bound algorithm is the most established method for solving mixed integer and discrete programming problems. It is based on the tree search of the possible subproblems of the original problem. There are two goals in carrying out a tree search, namely, (i) finding a good and ultimately the best integer solution, and (ii) to prove that the best solution has been found or no integer feasible solution exists. We call these the stage 1 and stage 2 of tree search. In general it is extremely difficult to choose the ideal search strategy in stage 1 or stage 2 for a given integer programming (IP) problem. On the other hand by investigating a number of different strategies (and hence different search trees) a good solution can be reached quickly in respect of many practical IP problems. Starting from this observation a parallel branch and bound algorithm has been designed which exploits this two stage approach. In the first stage we investigate a number of alternative search trees (forest search) in the hope of finding a good solution quickly. This we call the multiple heuristic search (MHS). In this approach the best integer solution is broadcast to other processors involved in MHS tree development. In the second stage we reorganise the search to investigate branches of a chosen tree in parallel. This two stage algorithm has been implemented on a cluster of SUN workstations using the Parallel Virtual Machine (PVM) harness [12]. The results of our investigation for a range of well known test problems taken from the MIPLIB set and others from the literature are reported here.