A template-based approach to the generation of distributedapplications using a network of workstations

A computational model and system for the generation of distributed applications in a workstation environment are presented. The well-known RPC model is modified by a novel concept known as template attachment. A computation consists of a network of sequential procedures which have been encapsulated in templates. A small selection of templates is available from which a distributed application with the desired communication behavior can be rapidly built. The system generates all the required low-level code for correct synchronization, communication, and scheduling. This results in a system that is easy to use and flexible and can provide a programmer with the desired amount of control in using idle processing power over a network of workstations. The practical feasibility of the model has been demonstrated by implementing it for Unix-based workstation environments     

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.     

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 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 reconstruction of plane-symmetric 3D models from freehand sketches

This paper presents a method for reconstructing a 3D model from a freehand sketch. There are two methods used in sketch-based modeling research: gestural modeling and reconstructional modeling. This research involves the reconstructional modeling method of Mitani, which was originally designed for a box-shaped model using a predefined template. Here, this method is improved by leveraging a relational template and a template matching method that extend the range of categories of the reconstructed objects. Sketch preprocessing details are provided and the template-based reconstructional method then uses the sketch preprocessing results to reconstruct a 3D model from a freehand sketch.     

Rank order-based recommendation approach for multiple featured products

Recommendation methods, which suggest a set of products likely to be of interest to a customer, require a great deal of information about both the user and the products. Recommendation methods take different forms depending on the types of preferences required from the customer. In this paper, we propose a new recommendation method that attempts to suggest products by utilizing simple information, such as ordinal specification weights and specification values, from the customer. These considerations lead to an ordinal weight-based multi-attribute value model. This model is well suited to situations in which there exist insufficient data regarding the demographics and transactional information on the target customers, because it enables us to recommend personalized products with a minimal input of customer preferences. The proposed recommendation method is different from previously reported recommendation methods in that it explicitly takes into account multidimensional features of each product by employing an ordered weight-based multi-attribute value model. To evaluate the proposed method, we conduct comparative experiments with two other methods rooted in distance-based similarity measures.     

A fast approach for automatic generation of fuzzy rules bygeneralized dynamic fuzzy neural networks

A fast approach for automatically generating fuzzy rules from sample patterns using generalized dynamic fuzzy neural networks (GD-FNNs) is presented. The GD-FNN is built based on ellipsoidal basis functions and functionally is equivalent to a Takagi-Sugeno-Kang fuzzy system. The salient characteristics of the GD-FNN are: (1) structure identification and parameters estimation are performed automatically and simultaneously without partitioning input space and selecting initial parameters a priori; (2) fuzzy rules can be recruited or deleted dynamically; (3) fuzzy rules can be generated quickly without resorting to the backpropagation (BP) iteration learning, a common approach adopted by many existing methods. The GD-FNN is employed in a wide range of applications ranging from static function approximation and nonlinear system identification to time-varying drug delivery system and multilink robot control. Simulation results demonstrate that a compact and high-performance fuzzy rule-base can be constructed. Comprehensive comparisons with other latest approaches show that the proposed approach is superior in terms of learning efficiency and performance     

A user-centric approach to service creation and delivery over next generation networks

Next Generation Networks (NGN) provide Telecommunications operators with the possibility to share their resources and infrastructure, facilitate the interoperability with other networks, and simplify and unify the management, operation and maintenance of service offerings, thus enabling the fast and cost-effective creation of new personal, broadband ubiquitous services. Unfortunately, service creation over NGN is far from the success of service creation in the Web, especially when it comes to Web 2.0. This paper presents a novel approach to service creation and delivery, with a platform that opens to non-technically skilled users the possibility to create, manage and share their own convergent (NGN-based and Web-based) services. To this end, the business approach to user-generated services is analyzed and the technological bases supporting the proposal are explained.     

A predictive approach for the generation of rhetorical devices

Human discourse is fraught with rhetorical devices such as contradictions, illustrations, and analogies. These rhetorical devices carry important information which a listener uses to speed up the comprehension process. In this paper, we present a taxonomy of rhetorical devices commonly used in tutoring environment, and model the meaning of a class of rhetorical devices in terms of their anticipated effect on a listener's knowledge. These predictions are then used in planning computer-generated discourse. As a testbed for our ideas, a system called WISHFUL is being implemented to generate commentaries in the domain of high-school algebra within the framework of an intelligent tutoring system.     

A new forwarding address for next generation networks

The forwarding address plays an important role in constructing a communication network.In this paper,a new forwarding address suitable for next generation networks named the vector address(VA) is proposed which is different from the forwarding address coding methods of current networks.The characteristics of the VA are analyzed.Complex network theory and a theoretical analysis method are introduced to study the average address length of the VA when used to construct a global network.Simulation experiments in a practical network topology model are carried out to validate the results.The results show that not only can the VA construct a simpler,more secure,and more scalable network,but it also can accommodate many more users than an Internet Protocol(IP) network with the same address length.     

A generic accounting scheme for next generation networks

Accounting is generally considered as one of the most challenging issues in modern and future mobile networks. As multi-domain complex heterogeneous environments are becoming a common terrain, accounting procedures performed by network and service providers have turned into a key aspect. However, in order for these networks to reliably deliver modern real-time services, they should, among other things, provide accurate accounting services, particularly billing. This work elaborates on the accounting process, proposing a novel and robust accounting system. The requirements of the proposed mechanism are defined and all the accounting scenarios that the system should cope with are examined. All the proposed accounting extensions are implemented by means of Diameter AVPs and commands. Our mechanism is generic and capitalizes on the existing AAA infrastructure, thus providing secure means to transfer and store sensitive billing data. More importantly, it can be easily incorporated into the providers’ existing mechanisms regardless of the underlying network technology. At the same time, its generic nature allows for interoperability between different network operators and service providers. Through extensive experimentation, we can also infer that our scheme is lightweight, scalable, and easy to implement requiring only minor modifications to the core Diameter protocol.     

Validation and automatic test generation on UML models: the AGATHA approach

UML-based methodologies take more and more space in the software development domain. In addition, the need to validate applications as early as possible in the development cycle is now mandatory to satisfy cost and time-to-market constraints. In this context, this paper describes, first, how to bridge the gap between semiformal UML models and a formal technology ensuring test case generation. Second, the formal tool used to automatically generate test sequences, named AGATHA, is described in minute detail. Finally, this approach is illustrated throughout by a toy example of an elevator system.     

Validation and automatic test generation on UML models: the AGATHA approach

The related economic goals of test generation are quite important for software industry. Manufacturers ever seeking to increase their productivity need to avoid malfunctions at the time of system specification: the later the defaults are detected, the greater the cost is. Consequently, the development of techniques and tools able to efficiently support engineers who are in charge of elaborating the specification constitutes a major challenge whose fallout concerns not only sectors of critical applications but also all those where poor conception could be extremely harmful to the brand image of a product.This article describes the design and implementation of a set of tools allowing software developers to validate UML (the Unified Modeling Language) specifications. This toolset belongs to the AGATHA environment, which is an automated test generator, developed at CEA/LIST.The AGATHA toolset is designed to validate specifications of communicating concurrent units described using an EIOLTS formalism (Extended Input Output Labeled Transition System). The goal of the work described in this paper is to provide an interface between UML and an EIOLTS formalism giving the possibility to use AGATHA on UML specifications.In this paper we describe first the translation of UML models into the EIOLTS formalism, and the translation of the results of the behavior analysis, provided by AGATHA, back into UML. Then we present the AGATHA toolset; we particularly focus on how AGATHA overcomes several problems of combinatorial explosion. We expose the concept of symbolic calculus and detection of redundant paths, which are the main principles of AGATHA's kernel. This kernel properly computes all the symbolic behaviors of a system specified in EIOLTS and automatically generates tests by way of constraint solving. Eventually we apply our method to an example and explain the different results that are computed.     

Architectures for the future networks and the next generation Internet: A survey

Networking research funding agencies in USA, Europe, Japan, and other countries are encouraging research on revolutionary networking architectures that may or may not be bound by the restrictions of the current TCP/IP based Internet. We present a comprehensive survey of such research projects and activities. The topics covered include various testbeds for experimentations for new architectures, new security mechanisms, content delivery mechanisms, management and control frameworks, service architectures, and routing mechanisms. Delay/disruption tolerant networks which allow communications even when complete end-to-end path is not available are also discussed.     

A level-set approach for the metamorphosis of solid models

We present a new approach to 3D shape metamorphosis. We express the interpolation of two shapes as a process where one shape deforms to maximize its similarity with another shape. The process incrementally optimizes an objective function while deforming an implicit surface model. We represent the deformable surface as a level set (iso-surface) of a densely sampled scalar function of three dimensions. Such level-set models have been shown to mimic conventional parametric deformable surface models by encoding surface movements as changes in the grayscale values of a volume data set. Thus, a well-founded mathematical structure leads to a set of procedures that describes how voxel values can be manipulated to create deformations that are represented as a sequence of volumes. The result is a 3D morphing method that offers several advantages over previous methods, including minimal need for user input, no model parameterization, flexible topology, and subvoxel accuracy     

Neural networks as material models within a multiscale approach

This paper shows the application of neural networks in a multiscale analysis of a reinforced concrete beam. A mesoscale model is presented, which simulates the pullout test of a reinforcement bar in concrete. By applying a homogenization procedure, a macroscopic stress vs. crack opening response is obtained from the mesoscale simulations. The neural network is used to approximate this relation in a macroscale simulation and replaces the material formulation of the interface layer between concrete and reinforcement, thus avoiding the computationally expensive parallel simulation on different scales.     

一种无线传感器网络可靠拓扑的生成算法

在无线传感器网络（ WSNs）的应用中,网络中的节点需要将采集到的数据信息传送到汇聚节点,其信息传输的可靠性是十分重要的。然而,由于无线通信信道容易受到干扰和噪音的影响,极限情况时甚至可能造成数据传输失败,这对无线传感器网络的正常工作提出了极大挑战。针对上述问题,提出一种可靠拓扑的生成算法,通过该算法设计了一组可靠的路由拓扑,并通过仿真验证了其可靠性。     

A template-based Tabu Search algorithm for the Consistent Vehicle Routing Problem

This paper presents a generic template-based solution framework and its application to the so-called Consistent Vehicle Routing Problem (ConVRP). The ConVRP is an NP-hard combinatorial optimization problem and involves the design of a set of minimum cost vehicle routes to service a set of customers with known demands over multiple days. Customers may receive service either once or with a predefined frequency; however frequent customers must receive consistent service, i.e., must be visited by the same driver over approximately the same time throughout the planning period. The proposed solution framework adopts a two-level master-slave decomposition scheme. Initially, a master template route schedule is constructed in an effort to determine the service sequence and assignment of frequent customers to vehicles. On return, the master template is used as the basis to design the actual vehicle routes and service schedules for both frequent and non-frequent customers over multiple days. To this end, a Tabu Search improvement method is employed that operates on a dual mode basis and modifies both the template routes and the actual daily schedules in a sequential fashion. Computational experiments on benchmark data sets illustrate the competitiveness of the proposed approach compared to existing results.     

Attentional networks for music generation

Realistic music generation has always remained as a challenging problem as it may lack structure or rationality. In this work, we propose a deep learning based music generation method in order to produce old style music particularly JAZZ with rehashed melodic structures utilizing a Bi-directional Long Short Term Memory (Bi-LSTM) Neural Network with attention. Owing to the success in modelling long-term temporal dependencies in sequential data and its success in case of videos, Bi-LSTMs with attention serves as a natural choice and early utilization in music generation. We validate in our experiments that Bi-LSTMs with attention are able to preserve the richness and technical nuances of the music performed.

     

A unified approach to analyzing models of cellular communication networks with data call buffering

A unified approach to the analysis of models of cellular communication networks with queues of data calls was developed. Consideration was given to the models with two types of strategies for admission to the cell channels and the buffer. In one strategy, admission to the voice call channels is based on reservation of channels for handover of calls of the given type, and in the other strategy, on the scheme of truncating the calls of the given type. In both models, the strategy of buffer admission by the data calls relies on the scheme of place reservation for handover of the calls of the given type. The models with finite and infinite data call queues were studied. For different admission strategies, algorithms to calculate the servicing performance indices were given, and the results of their comparative analysis were presented.