Computational Science and Its Applications – ICCSA 2013

The main goal of this research is the rationalization of the structure and the energetics of K

 + 

-(C

6

H

6

)

n

-(H

2

O)

m

(n=1-4; m=1-6) aggregates for which the full intermolecular potential,

V

, is given as a combination of few leading effective interaction components. Despite the fact that the K

 + 

-(C

6

H

6

)

n

-(H

2

O)

m

systems are better considered as aggregates rather than solvated species, we find that the dynamics of the molecules surrounding the ion can be rationalized in terms of ”a first and a second solvation shell” centered on K

 + 

. The substitution of one C

6

H

6

by two or more molecules of H

2

O in the first solvation shell, has also been investigated in order to understand the role played by them in stabilizing certain structures. The interplay between molecules of the first and the second solvation shell has also been analyzed.

In time-dependent quantum reactive scattering calculations, it is important to quickly and accurately apply the Hamiltonian, as this must be performed at every time-step. We present a method of separating the Hamiltonian for adiabatically-adjusting principal axes hyperspherical (APH) coordinates into its constituent parts, vectorizing these to reduce computational steps required in matrix multiplications, and finally parallelizing the application to reduce the time required to perform the calculation. This reduction in time is achieved with no modification of results for triatomic systems of either lithium or hydrogen.

By making use of a Grid enabled

ab initio

molecular simulator we have tackled the

a priori

study of the N

2

(

${}^1{\Sigma}_g^+$

) + N

2

(

${}^1{\Sigma}_g^+$

) process. A detailed analysis of the results obtained from high level

ab initio

(Coupled Cluster) calculation of the electronic structure of N

4

for a large number of nuclear geometries has singled out the fact that Coupled Cluster calculations are insufficiently accurate when the internuclear distances of the approaching N

2

diatoms are stretched, because in such cases the wavefunction of the N

4

system cannot be properly described by a single determinant. For this reason we have carried out Multi Reference calculations (using the same basis set) for a large number of the nuclear geometries considered for the Coupled Cluster study. Then, a 4-atoms global potential energy surface has been worked out for use in dynamics calculations.

Methanimine is a molecule of interest in astrobiology, as it is considered an abiotic precursor of the simplest amino acid glycine. Methanimine has been observed in the interstellar medium and in the upper atmosphere of Titan. In particular, it has been speculated that its polymerization can contribute to the formation of the haze aerosols that surround the massive moon of Saturn. Unfortunately, such a suggestion has not been proved by laboratory experiments. Methanimine is difficult to investigate in laboratory experiments because it is a transient species that must be produced

in situ

. To assess its potential role in the formation of Titan’s aerosol, we have performed a theoretical investigation of possible formation routes and dimerization. The aim of this study is to understand whether formation and dimerization of methanimine and, eventually, its polymerization, are possible under the conditions of the atmosphere of Titan. Results of high-level electronic structure calculations are reported.

Density functional (DFT) calculations for different size cluster models of the hydrogen-terminated HF

aq

-etched (100) Si surface have been performed to verify that the quantities of interest (namely, atomic net charges and interatomic distances) in assigning the lines observed by X-ray photoelectron spectroscopy (XPS) vary weakly with cluster size. Net charge analysis based on Voronoi Deformation Density (VDD) method and accurate DFT geometry optimization calculations involving the smallest clusters as local models of various surface silicon atoms are used to assign chemical species to the features observed in the XPS spectra through evaluation of the chemical shifts, which are controlled by both the net charge and the Madelung potential truncated to nearest neighbours of the considered atoms.

The autoionization dynamics of triatomic molecules induced by He

*

(2

3,1

S

1,0

) and Ne

*

(

3

P

2,0

) collisions has been discussed. The systems are analyzed by using an optical potential model within a semiclassical approach. The real part of the potential is formulated applying a semiempirical method, while the imaginary part has been used in the fitting procedure of the data adjusting its pre-exponential factor. The good agreement between calculations and experiment confirms the attractive nature of the potential energy surface driving the He

*

and Ne

*

-H

2

O dynamics.

This paper describes and discusses the implementation, in a high-throughput computing environment, of the ANSYS® commercial suite. ANSYS® implements the calculations in a way which can be ported onto parallel architectures efficiently and for this reason the User Support Unit of the Italian Grid Initiative (IGI) and the INFN-Legnaro National Laboratories (INFN-LNL) worked together to implement a Grid enabled version of the ANSYS® code using the IGI Portal, a powerful and easy to use gateway to distributed computing and storage resources. The collaboration focused on the porting of the code onto the EGI Grid environment for the benefit of the involved community and for those communities interested in exploiting production Grid infrastructures in the same way.

The paper describes the design and the implementation of a built-in assistant software module aimed at managing the metadata of a federation of collaborative repositories of learning objects. The paper focuses mainly on the standardization of the classification criteria and their application to Molecular sciences.

This paper evaluates the waiting time for a visiting schedule created by a tour-and-charging scheduler for electric vehicles in Jeju city area. As a promising vehicle network application, this service alleviates the range anxiety of electric vehicles by finding an energy-efficient tour schedule, alternately considering tour and charging. For the field test on the real-life tour spot distribution and charger availability, 3 model tour courses are selected first, each of which has the tour length of 155, 166, and 148

km

, respectively, and different number of chargers on the path. The evaluation process measures and compares the tour time and thus the waiting time on 3 courses for tour schedules generated by our scheduler and legacy traveling salesman problem solver. The experiment discovers that our scheme reduces the waiting time by up to 21.1 % and eliminates the waiting time if the stay time intervals are 90, 80, and 40 minutes for each course on the current distribution of spots and chargers.

As device-to-device (D2D) communications enables direct communication between user equipments, it can alleviate traffic overload on base stations. Qualcomm has introduced a new OFDM-based synchronous frame architecture for MAC/PHY, which is called FlashLinQ. In FlashLinQ, D2D user equipments perform signal-to-interference ratio based connection scheduling in order to distributively access wireless medium. The connection scheduling scheme enables D2D user equipments to simultaneously transmit data through same wireless medium. However, in this scheme since D2D user equipments simultaneously perform the medium access, they unnecessarily may yield data communication. In this paper, we propose a scheme that D2D user equipments adaptively perform connection scheduling by ignoring the interference from D2D links which are expected to yield data transmission. We verify that the proposed scheme can improve the system performance through simulations.

In existing wireless communication systems such as cellular network, base station can become bottleneck since terminals have to exchange data traffic each other only through a base station. In order to solve this problem, device-to-device (D2D) communication has been considered. Recently, Qualcomm Inc. has introduced FlashLinQ (FLQ) for D2D communication, which has a radio frame based on orthogonal frequency division multiplex (OFDM). In FLQ, terminals distributively access to medium based on their D2D link qualities and interference from other terminals. However, terminal with low link quality can cause that other terminals excessively give up their medium access. In order to solve this problem, we propose a probabilistic medium access scheme for D2D terminals in FLQ. In the proposed scheme, terminal stochastically tries accessing to medium based on its link quality, and the excessive yieldings of other terminals are reduced. Through simulation, we evaluate performance of the proposed scheme by comparing that of FLQ. We show that the proposed scheme can improve performance of FLQ by simulation results.

An increasing demand for efficient and safe electricity management has motivated the development of smart grid and accelerated the technical research for smart grid. On one side, a smart microgrid has been recently given an interest as a relatively small-scale, self-contained, medium/low voltage electric power system (EPS); it houses various distributed energy resources (DERs) with renewable energy and controllable loads in a physically close location. In this paper, we overview the research trend for the network design and security issues of smart microgrid, different from smart grid, and survey the effort of standardization for them. Through the survey, we derive the novel research issues to address for the successful realization of smart microgrid.

In this paper, a dynamic Sub-channel Assignment Algorithm (DSA) based on orthogonal frequency division multiple access (OFDMA) technology operating in the time division duplexing (TDD) and a new routing protocol are proposed. The proposed of dynamic Sub-channel Assignment Algorithm solves several drawbacks of existing radio resource allocation techniques in OFDM system used in ad-hoc and multi-hop networks, such as the hidden and exposed node problem, mobility, co-channels interference in frequency (CCI). An interference avoidance mechanism allows the system to reduce CCI and to operate with full frequency re-use. The proposed routing protocol is jointed with the MAC protocol based the algorithm to ensure the mobility and multi-hop, thus the quality of service in ad-hoc and multi-hop networks is significantly improved.

The rapid growth of data size causes several problems such as storage limitation and increment of data management cost. In order to store and manage massive data, Distributed File System (DFS) is widely used. Furthermore, in order to reduce the volume of storage, data deduplication schemes are being extensively studied. The data deduplication increases the available storage capacity by eliminating duplicated data. However, deduplication process causes performance overhead such as disk I/O. In this paper, we propose a content-based chunk placement scheme to increase deduplication rate on the DFS. To avoid performance overhead caused by deduplication process, we use

lessfs

in each chunk server. With our design, our system performs decentralized deduplication process in each chunk server. Moreover, we use consistent hashing for chunk allocation and failure recovery. Our experimental results show that the proposed system reduces the storage space by 60% than the system without consistent hashing.

One of the critical issue of wireless sensor networks is a poor sensor battery. It leads to sensor vulnerability for battery exhausting attacks. Quick depletion of battery power is not only explained by intrusions but also by a malfunction of networks protocols. In this paper, a special type of denial-of-service attack is investigated. The intrusion effect is the depletion of sensor battery power. In contrast to general denial-of-service attack, quality of service under the considered attack is not necessarily degraded. Therefore, the application of traditional defense mechanism against this intrusion is not always possible. Taking into account proprieties of wireless sensor networks, a model for evaluation of energy consumption under the attack is described. Using this model, the attack detection method is offered.

The objective of the CEREALAB database is to help the breeders in choosing molecular markers associated to the most important traits. Phenotypic and genotypic data obtained from the integration of open source databases with the data obtained by the CEREALAB project are made available to the users. The CEREALAB database has been and is currently extensively used within the frame of the CEREALAB project.

This paper presents the main achievements and the ongoing research to annotate the CEREALAB database and to publish it in the Linking Open Data network, in order to facilitate breeders and geneticists in searching and exploiting linked agricultural resources. One of the main focus of this paper is to discuss the use of the AGROVOC Linked Dataset both to annotate the CEREALAB schema and to discover schema-level mappings among the CEREALAB Dataset and other resources of the Linking Open Data network, such as NALT, the National Agricultural Library Thesaurus, and DBpedia.

The work presented in this paper is a part of Observox, a community environmental information system for the monitoring of agricultural practices and their pressure on water resources in the Vesle basin, Champagne-Ardenne, France. The construction of Observox is the result of several research projects, and it is based on a methodology involving the actors concerned by the issue of water quality. Furthermore such a system requires the use of information provided by multiple sources which are usually imperfect. To provide the most honest indicators to the system’s users, we integrate the notion of information quality by a degree of confidence. Thus we present the use of two main frameworks for imperfect knowledge management in the environmental information system, the fuzzy logic for propagating imprecision and belief functions for merging classifications.

We construct predictions of fire boundary growth using level set methods. We generate a correction for predictions at the subsequent time step based on current error. The current error is captured by a thin-plate spline deformation from the initial predicted boundary to the observed boundary, which is then applied to the initial prediction at the subsequent time step. We apply these methods to data from the 1996 Bee Fire and 2002 Troy Fire. We also compare our results to earlier predictions for the Bee Fire using the FARSITE method. Error is measured using the Hausdorff distance. We determine conditions under which error correction improves prediction performance.

Farmers in Sri Lanka are badly affected by not being able to get vital information required to support their farming activities in a timely manner. Some of the required information can be found in government websites, agriculture department leaflets, and through radio and television programs on agriculture. Due to its unstructured and varied format, and lack of targeted delivery methods, this knowledge is not reaching the farmers. Therefore, this knowledge needs to be provided not only in a structured way, but also in a context-specific manner. To address this shortcoming an international collaborative research project was launched to develop a Social Life Network to provide necessary information to farmers using mobile devices. Agricultural information has strong local characteristics in relation to climate, culture, history, languages, and local plant varieties. These local characteristics as well as the need to provide information in a context-specific manner made us to develop an ontology for agriculture. In this paper we present the approach we used to derive contextual information related to the farmers and the ontological approach that we developed to meet information needs of the farmers at various stages of the farming life cycle.

The need to perform complex analysis and decision making tasks has motivated growing interest in Geographic Information Systems (GIS) as a means to compare different scenarios and simulate the evolution of phenomena. However, data and function complexity may critically affect human interaction and system performances during planning and prevention activities. This is especially true when the scenarios of interest involve space or time in imprecise contexts.

In this paper we propose a visual language which drives users to perform queries involving discrete objects by considering their temporal component. Moreover, in order to allow queries closer to the user mental model we add a specific hint for relaxing constraints and allowing fuzzy conditions. The visual language will be tested on two specific contexts concerning with the fire risk and the air pollution.

This work was initiated to tackle issues met by the ITK Company in developing and designing new crop models for decision support systems. At the crossroads of two disciplines, Computer Science and Agronomy, we propose the use of Model-Driven Engineering which has the potential to be the future of software engineering. This paper presents the model-driven approach retained to achieve a full-fledge crop modeling and simulation environment. The metamodel and graphical concrete syntax designed are overcoming the lack of formal tool for conceptual modeling. The presented prototype permits to improve ITK production process through the use of code generation techniques.

Timely and relevant agriculture information is essential for farmers to make effective decisions. Finding the right approach to provide this information to empower farmers is vital due to the high failure rate in current agricultural information systems. As most farmers now have mobile phones we developed a mobile based information system. We used participatory action research methodology to enable high farmer participation to ensure sustainability of the solution. The initial version of the application based on the preliminary studies focused on the crop choosing stage of the farming life cycle. This initial prototype was evaluated with a sample of farmers to check their willingness in adapting such technology, usefulness of provided information and usability of the application in order to support their day to day decision making process. The sample group strongly endorsed the various aspects of the prototype application and provided valuable insights for improvement.

Pattern search methods are widely used for the minimization of non-convex functions without the use of derivatives. One of the main features of pattern search methods is the flexibility to incorporate different search strategies taking advantage of the imported global optimization techniques without jeopardizing their convergence properties. Pattern search methods can also be adapted to problem contexts where the user can provide points incorporating a priori knowledge of the problem that can lead to an objective function improvement. Here, an automated incorporation of a priori knowledge in pattern search methods is implemented instead of an algorithm that requires the user’s contribution. Moreover, a priori knowledge can also play a role on the choice of the initial point(s), an important aspect in the success of a global optimization process. Our pattern search approach is tailored for addressing the beam angle optimization (BAO) problem in intensity-modulated radiation therapy (IMRT) treatment planning that consists of selecting appropriate radiation incidence directions and may influence the quality of the IMRT plans, both to enhance better organs sparing and to improve tumor coverage. Beam’s-eye-view dose ray tracing metrics are used as a priori knowledge of the problem both to decide the initial point(s) and to be incorporated within a pattern search methods framework. A couple of retrospective treated cases of head-and-neck tumors at the Portuguese Institute of Oncology of Coimbra is used to discuss the benefits of incorporating a priori dosimetric knowledge in pattern search methods for the optimization of the BAO problem.

The aim of our contribution is to call attention to the relationship between totally regular variables, introduced by R. Delanghe in 1970, and Appell sequences with respect to the hypercomplex derivative. Under some natural normalization condition the set of all paravector valued totally regular variables defined in the three dimensional Euclidean space will be completely characterized. Together with their integer powers they constitute automatically Appell sequences, since they are isomorphic to the complex variables.

This paper presents a genetic algorithm for the Team Orienteering Problem with double Time Windows (TOPdTW). The aim is to study TOPdTW to model a real problem that arises within the operating rooms in a hospital. The Genetic Algorithm uses a peculiar way to construct solutions that only generates valid solutions, which improves the global performance. This constructive algorithm reads the chromosome and decides which operation is scheduled next in the route. The algorithm was tested using some public instances of the TOPTW and instances generated for TOPdTW. The computational results are presented.

The most common approach for solving constrained optimization problems is based on penalty functions, where the constrained problem is transformed into an unconstrained problem by penalizing the objective function when constraints are violated. In this paper, we analyze the implementation of penalty functions, within the DIRECT algorithm. In order to assess the applicability and performance of the proposed approaches, some benchmark problems from engineering design optimization are considered.

Multilocal programming aims to locate all the local solutions of an optimization problem. A stochastic method based on a multistart strategy and a derivative-free filter local search for solving general constrained optimization problems is presented. The filter methodology is integrated into a coordinate search paradigm in order to generate a set of trial approximations that might be acceptable if they improve the constraint violation or the objective function value relative to the current one. Preliminary numerical experiments with a benchmark set of problems show the effectiveness of the proposed method.

The 1-Hop Information flooding (1HI) and 2-Hop Backward Information flooding (2HBI) schemes for choosing the retransmission nodes have been studied to solve the broadcast storm Problem for data flooding in wireless sensor networks (WSNs). These schemes do not consider duty cycles to save the energy of sensor node. Recently duty cycle approach is very commonly used as it performs well to save the energy of sensor nodes We analyze the performance of Conventional flooding, 1HI and 2BHI with duty cycles.In the well-known test environment, the result with 30% duty cycle shows that 2HBI scheme can reduce energy consumption up to 65%, increase the number of floodings up to 2 times, and increase the flooding duration up to 6 times. The comparison shows that 2HBI scheme takes the longest flooding time with duty cycle approach, where as it takes the shortest flooding time in non-duty cycled networks. Through various experiments, this paper suggests that proper schemes for various deployment conditions.

The formal verification of cyber-physical systems is a challenging task mainly because of the involvement of various factors of continuous nature, such as the analog components or the surrounding environment. Traditional verification methods, such as model checking or automated theorem proving, usually deal with these continuous aspects by using abstracted discrete models. This fact makes cyber-physical system designs error prone, which may lead to disastrous consequences given the safety and financial critical nature of their applications. Leveraging upon the high expressiveness of higher-order logic, we propose to use higher-order-logic theorem proving to analyze continuous models of cyber-physical systems. To facilitate this process, this paper presents the formalization of the solutions of second-order homogeneous linear differential equations. To illustrate the usefulness of our foundational cyber-physical system analysis formalization, we present the formal analysis of a damped harmonic oscillator and a second-order op-amp circuit using the HOL4 theorem prover.

Cloud computing is the top issue of IT industry. In addition, the mobile platform has become a major keyword of IT technologies. Thus, we introduce the mobile cloud computing that consist of the union of two concepts. This conflated model can provide a high performance computing in mobile platform. To provide the mobile cloud computing service, it needs various IT technologies. Among these technologies, remote access protocol is one of major issues because it is directly related in a performance of mobile cloud computing. There are two major standard protocols to provide remote access. They are Remote Frame Buffer protocol(RFB protocol) and Remote Desktop Protocol(RDP protocol). RFB protocol relays the view image from a server to a client. It has a simple architecture, but it makes many network traffics structurally. On the other hand, RDP protocol sends the message of a server event to client and the client creates and shows the view image to users. It has smaller traffic than the RFB protocol, but it is only used in Windows platform due to the license problem. The other protocol called SPICE can solve problems from two standard protocols. This protocol has similar architecture to RDP protocol and it is an open-source program. However, SPICE protocol cannot support Android platform now. In this paper, we introduce the way to convert SPICE protocol to support Android platform. However, the modified protocol has some additional delay. Therefore, we also propose the way to enhance the performance of this protocol. It can provide a high performance and be suitable for the mobile cloud.

Nowadays, the smartphone has become the critical issue of users information security. The smartphone services not only principal functions of a cellular phone but also personalized functions such as mobile banking and GPS location tracking. It means that an attacker will be able to obtain a variety of personal information when an attacker compromises the smartphone. For this reason, malwares target environments have been changed to the smartphone platforms from computers. The android OS has the permission mechanism that was designed to prevent malicious behaviors of installed applications. However most of the users are not concerned about permissions of application to install. Thus, the android OS needs an advanced security mechanism that will be able to warn malicious behaviors of installed applications to the user. In this paper, we proposed permission-based application monitoring model, which is performed at the Android OS-level.

A number of similar structured wireless sensors, constituting a Wireless Sensor Network (WSN) are used for activity recognition— particularly for coaching of a bowler to practice correct bowling action in the game of cricket. Several experiments are conducted for training certain algorithms, like K-means and Hidden Markov Model, etc., and the real-time data acquired by a subject under study, or a cricket bowler, is tested for statistical characteristics’ comparison. This paper explains the whole implemented system and the prime application in which it can assist in the field of cricket.

Back-propagation Neural Network (BPNN) algorithm is one of the most widely used and a popular technique to optimize the feed forward neural network training. Traditional BP algorithm has some drawbacks, such as getting stuck easily in local minima and slow speed of convergence. Nature inspired meta-heuristic algorithms provide derivative-free solution to optimize complex problems. This paper proposed a new meta-heuristic search algorithm, called cuckoo search (CS), based on cuckoo bird’s behavior to train BP in achieving fast convergence rate and to avoid local minima problem. The performance of the proposed Cuckoo Search Back-Propagation (CSBP) is compared with artificial bee colony using BP algorithm, and other hybrid variants. Specifically OR and XOR datasets are used. The simulation results show that the computational efficiency of BP training process is highly enhanced when coupled with the proposed hybrid method.

Higher Order Neural Networks (HONNs) have emerged as an important tool for time series prediction and have been successfully applied in many engineering and scientific problems. One of the models in HONNs is a Functional Link Neural Network (FLNN) known to be conveniently used for function approximation and can be extended for pattern recognition with faster convergence rate and lesser computational load compared to ordinary feedforward network like the Multilayer Perceptron (MLP). In training the FLNN, the mostly used algorithm is the Backpropagation (BP) learning algorithm. However, one of the crucial problems with BP learning algorithm is that it can be easily gets trapped on local minima. This paper proposed an alternative learning scheme for the FLNN to be applied on temperature forecasting by using Artificial Bee Colony (ABC) optimization algorithm. The ABC adopted in this work is known to have good exploration and exploitation capabilities in searching optimal weight especially in numerical optimization problems. The result of the prediction made by FLNN-ABC is compared with the original FLNN architecture and toward the end we found that FLNN-ABC gives better result in predicting the next-day ahead prediction.

Back propagation neural network (BPNN) algorithm is a widely used technique in training artificial neural networks. It is also a very popular optimization procedure applied to find optimal weights in a training process. However, traditional back propagation optimized with Levenberg marquardt training algorithm has some drawbacks such as getting stuck in local minima, and network stagnancy. This paper proposed an improved Levenberg-Marquardt back propagation (LMBP) algorithm integrated and trained with Cuckoo Search (CS) algorithm to avoided local minima problem and achieves fast convergence. The performance of the proposed Cuckoo Search Levenberg-Marquardt (CSLM) algorithm is compared with Artificial Bee Colony (ABC) and similar hybrid variants. The simulation results show that the proposed CSLM algorithm performs better than other algorithm used in this study in term of convergence rate and accuracy.

From an Information Retrieval perspective there are many works which have been proposed to deal with the problem of retrieving and searching relevant documents. One of the main drawbacks of traditional approaches is related with their static context similarity evaluation, this issue has been addressed by manually refining the query . In this paper we describe a context-based method to dynamically improve the query during document search. A set of experiments were conducted to evaluate the precision and recall of the proposed method, evaluation of results show the benefits of this novel method.

The bottom-up saliency, an early stage of humans’ visual attention, can be considered as a binary classification problem between center and surround classes. Discriminant power of features for the classification is measured as mutual information between features and two classes distribution. The estimated discrepancy of two feature classes very much depends on considered scale levels; then, multi-scale structure and discriminant power are integrated by employing discrete wavelet features and Hidden markov tree (HMT). With wavelet coefficients and Hidden Markov Tree parameters, quad-tree like label structures are constructed and utilized in maximum a posterior probability (MAP) of hidden class variables at corresponding dyadic sub-squares. Then, saliency value for each dyadic square at each scale level is computed with discriminant power principle and the MAP. Finally, across multiple scales is integrated the final saliency map by an information maximization rule. Both standard quantitative tools such as NSS, LCC, AUC and qualitative assessments are used for evaluating the proposed multiscale discriminant saliency method (MDIS) against the well-know information-based saliency method AIM on its Bruce Database wity eye-tracking data. Simulation results are presented and analyzed to verify the validity of MDIS as well as point out its disadvantages for further research direction.

We address an application of vehicle routing problem (VRP) in the real life, namely waste collection problem. Constraints are considered including conflicts between waste properties, time windows of the waste, and multiple landfills. A combination of flow and set partitioning formulation is suggested to model the problem in case of multi-objective optimization. To minimize the total traveling time and number of vehicles of solution, we propose using a memetic algorithm (MA) with

λ

-interchange mechanism. The

λ

-interchange operator is modified to be compatible with new sub-routes construction for the multiple landfills.

In experiments, we compare the result of proposed MA method with some good results published as well as other meta-heuristic algorithms. The density of conflict matrix is also considered to understand its influence on the quality of the solution. Experimental results show that our approach can be competitive to other results in the VRP with time windows. Furthermore, the algorithm outperforms others in the VRP with time windows and conflict.

This paper proposes a distributed control algorithm to im- plement dynamic task allocation in a swarm robotics environment. In this context, each robot that integrates the swarm must run the algorithm periodically in order to control the underlying actions and decisions. The algorithm was implemented and extensively tested. The corresponding performance and effectiveness are promising.

Multi-Processor System on Chip (MPSoC) offers a set of processors, embedded in one single chip. A parallel application can, then, be scheduled to each processor, in order to accelerate its execution. One problem in MPSoCs is the communication between processors, necessary to run the application. The shared memory provides the means to exchange data. In order to allow for non-blocking parallelism, we based the interconnection network in the crossbar topology. In this kind of interconnection, processors have full access to their own memory module simultaneously. On the other hand, processors can address the whole memory. One processor accesses the memory module of another processor only when it needs to retrieve data generated by the latter. This paper presents the specification and modeling of an interconnection network based on crossbar topology. The aim of this work is to investigate the performance characteristics of a parallel application running on this platform.

Real-world phenomena have traditionally been modelled in 2D/3D GIS. However, powerful insights can be gained by integrating additional non-spatial dimensions, such as time and scale. While this integration to form higher-dimensional objects is theoretically sound, its implementation is problematic since the data models used in GIS are not appropriate. In this paper, we present our research on one possible data model/structure to represent higher-dimensional GIS datasets: generalised maps. It is formally defined, but is not directly applicable for the specific needs of GIS data, e.g. support for geometry, overlapping and disconnected regions, holes, complex handling of attributes, etc. We review the properties of generalised maps, discuss needs to be modified for higher-dimensional GIS, and describe the modifications and extensions that we have made to generalised maps. We conclude with where this research fits within our long term goal of a higher dimensional GIS, and present an outlook on future research.

Geometrically, parcel boundaries are represented by polygons. Unfortunately, they are induced by a set of lines in some drawings (for example, CAD). In this article, we present an algorithm that polygonizes quickly and precisely a set of lines and stores the resulting polygons as well as adjacency relationships in a topological model. These pre-calculated topological relationships are efficient for basic functions, such as parcel division and parcel merge, in land parcel exploitation and management systems. Our algorithm is simple and easy to implement.

W3DS clients should be able to request 3D scenes, either using the

getscene

or

gettile

operations, and directly display them without any additional manipulation or geographic positional correction.

In this paper we will discuss how tiles should be served to W3DS clients, since 3D tiles are more difficult to manage than 2D tiles. While 2D tiles just need to be placed side by side, 3D tiles also have to fit along the z axis.

The volume and complexity of 3D information requires more complicated logic on the client side. Clients can decide that geographic features far away from the viewer can have less detail than those near the observer. For that reason, 3D clients may want to join together tiles of different resolutions.

We will show an algorithm to perfectly slice 3D terrain models using the GDAL and CGAL libraries. It can be used in existing W3DS services to improve the quality of visualisations.

Data mining is a task of extracting useful patterns/episodes from large databases. Sequence data can be modeled using episodes. An episode is serial if the underlying temporal order is total. An episode rule of associating two episodes suggests a temporal implication of the antecedent episode to the consequent episode. We present two mining algorithms for finding frequent and confident serial-episode rules with their ideal occurrence/window widths, if exist, in event sequences based on the notion of minimal occurrences constrained by constant and mean maximum gap, respectively. A preliminary empirical study that illustrates the applicability of the episode-rule mining algorithms is performed with a set of earthquake data.

The kernel is a non-parametric estimation method of the probability density function of a random variable based on a finite sample of data. The estimated function is smooth and level of smoothness is defined by a parameter represented by

h

, called bandwidth or window. In this simulation work we compare, by the use of mean square error and bias, the performance of the normal kernel in smoothing the empirical ROC curve, using various amounts of bandwidth. In this sense, we intend to compare the performance of the normal kernel, for various values of bandwidth, in the smoothing of ROC curves generated from Normal distributions and evaluate the variation of the mean square error for these samples. Two methodologies were followed: replacing the distribution functions of positive cases (abnormal) and negative (normal), on the definition of the ROC curve, smoothed by nonparametric estimators obtained via the kernel estimator and the smoothing applied directly to the ROC curve. We conclude that the empirical ROC curve has higher standard error when compared with the smoothed curves, a small value for the bandwidth favors a higher standard error and a higher value of the bandwidth increasing bias estimation.

The main objective of this study is evaluate the influence of several covariates in the occurrence of two types of vertical jaw dysplasia (open bite and deepbite) in orthodontics field.

The study of vertical jaw dysplasia is of great interest to the community of orthodontists, to ensure long-term stability of treatment, as this envolves complex etiological factors.

In this work we propose to build a multinomial logistic regression model that could assess the probability of an individual have open bite or deepbite taking into account some cephalometric measures of hyoid bone (HB) and some individual characteristics.

The study was conducted in a retrospective evaluation and consisted of 191 individuals random selected from a clinic in the Northern region of Portugal. We evaluated multiple factors in the construction of multinomial logistic regression model with 2 logit functions. The technique used to select variables to be included in the model, was the stepwise technique by choosing the smallest

p

value for the variable entering in the model.

Of the modeling process through multinomial logistic regression have resulted five position of the hyoid bone that have statistical significance and that can contribute as an auxiliary for the diagnosis of vertical jaw dysplasia.

Curve framing has numerous applications in computer graphics modeling, e.g., in the construction of extruded surfaces. Commonly used curve framing techniques such as the Frenet frame, parallel transport frame and ‘up-vector’ frame cannot handle all types of curves. Mismatch between the technique used and the curve being modeled may result in the extruded surfaces being twisted. We propose a simple end-to-end vector-projection approach to curve framing. Our results show that the technique yields less twists compared to those based on the Frenet frame.

Retrofitting existing buildings is a key aspect for reaching the proposed energy consumption reduction targets in all countries. The availability of as-built building model is of primary importance for both thermal lack diagnosis and planning retrofitting works. In particular, integration between Building Information Models (BIMs) and Infrared Thermography (IRT) can be a powerful tool for evaluating building thermal efficiency. Indeed, thermography can be efficiently used to detect thermal bridges and heat losses. However, thermographic images does not allow geometrical measurements whereas precise localization of thermal defects is a main aspect for retrofitting intervention planning. For this reason building models can be efficiently integrated with thermal images and provide metric information to thermographic analysis. In this paper a methodology for combining thermographies, acquired by different platforms, and building models automatically derived from laser scanning technology is presented.

Serious games usually refer to games that are used for training, advertising, simulation, or education and that provide a high fidelity simulation of particular environments and situations. Serious games are starting to be also employed in surgery-based training applications. This paper presents a serious game for training on suturing in laparoscopic surgery. In particular, it is focused on the physical modeling of the virtual environment and on the definition of a set of parameters used to assess the level of skills developed by the trainees. A pair of haptic devices has been utilized in order to simulate the manipulation of the surgical instruments.

Edutainment refers to any form of entertainment aimed at an educational role; it enhances the learning environment and makes it much more engaging and fun-filled. The videogame is one of the most exciting and immediate tools of the edutainment applications since the game enables a type of multisensory and immersive relationship of the user through its interactive interface; Virtual Reality technology makes possible to create applications for edutainment purposes and to integrate different learning approaches. One of the important applications of edutainment is the reconstruction of 3D environments aimed at the study of cultural heritage. This paper presents some results of the MediaEvo Project that has led the researchers to use the reconstruction of a town in the Middle Ages in order to develop a multi-channel and multi-sensory platform for the edutainment in Cultural Heritage. MediaEvo project has permitted a didactic experimentation whereby simulation is considered as a precious teaching support tool. The educational MediaEvo game has prompted students to participate in and experience in a simulated and immersive environment of a town in the Middle Ages in order to connect the recreational actions, and to critically discover roles, functions and actions referring to Medieval life.

This work presents a method to model a spherical mesh by modifying its heightmap in an augmented reality environment. Our contribution is the use of the hierarchical structure of semiregular A4-8 meshes to represent a dynamic deformable mesh suitable for modeling. It defines only a fraction of the overall terrain that is subjected to local deformations. The modeling of spherical terrains is achieved with proper subdivision constraints at the singularities of the parametric space. An error metric dependent on the observer and on the geometry of the topography was used to provide fast visualization and editing. The results demonstrate that the use of the A4-8 mesh combined with the tangible augmented reality system is flexible to shape spherical terrains and can be easily modified to deal with other topologies, such as the torus and the cylinder.

Agent-based modeling is used to study many kind of complex systems in different fields such as biology, ecology, or sociology. Visualization of the execution of a such complex systems is crucial in the capacity to apprehend its dynamics. The ever increasing complexification of requirements asked by the modeller has highlighted the need for more powerful tools than the existing ones to represent, visualize and interact with a simulation and extract data online to discover imperceptible dynamics at different spatio-temporal scales. In this article we present our research in advanced visualization and online data analysis developed in GAMA an agent-based, spatially explicit, modeling and simulation platform.

We present a real-time fall detection and activity recognition system (FDAR) that can be easily deployed using Wii Remotes worn on human body. Features extracted from continuous accelerometer data streams are used for training pattern recognition models, then the models are used for detecting falls and recognizing 14 fine grained activities including unknown activities in realtime. An experiment on 12 subjects was conducted to rigorously evaluate the system performance. With the recognition rates as high as 91% precision and recall for 10-fold cross validation and as high as 82% precision and recall for leave one subject out evaluations, the results demonstrated that the development of real-time fall detection and activity recognition systems using low-cost sensors is feasible.

In this paper, we present the description of an animation solver that allows the automatic moving of the different parts of a signing avatar body. The objective is to obtain a realistic animation of the virtual character that enables deaf person to visualize realistic gestures. Our approach is based on a thorough study of sign language and gestures classification. We identified the main constraints required for automatic generation of postures in sign language, and we developed a graphical interface in order to facilitate editing. This interface allows, in particular, the selection of the sign components and the rendering of the choice made on the avatar postures. The challenge of this project is to find a good compromise between computational time and realistic representation that should be closer to real-time generation signs.

In our research, we propose and implement a virtual reality system with the common and widely used devices such as 3D screen and digital webcam. Our approach involves the combination of 3D stereoscopic rendering and face tracking technique in order to render a stereo scene based on the position of the viewer. Our approach is to calculate the offset values of face position to assign to the virtual camera position relatively. We employ a technique to change the typical symmetric frustum into asymmetric to achieve the head-coupled perspective. With our system, the rendered scene observed by human eyes remains realistic and the viewport can be seen as the physical window in the real environment. Therefore, the right perspective can be maintained regardless of viewer position.

The optimization of the process of implementing virtual exhibitions on the Web represents an interesting research area devoted to simplify the design and the production of virtual exhibitions, particularly for people with a scarce technical skill and strong competencies in the area to which the exhibition is related to.

In the present paper we propose a web environment facilitating the production of virtual exhibition through a series of operations: from the virtual representation of the physical structure, starting from the image of a 2D map that is processed to optimize the walls identification, to the management of the artworks shown in the exhibition, including the selection of the artworks and their positioning in the physical structure. Finally the virtual exhibition may be released to the visitors, making the virtual world available for the download on the client side.

Several technologies have been adopted in order to reach a user friendly backoffice environment, suitable for being used by naive (from the technology point of view) users, concentrated on the subject related to the virtual exhibition: the OpenCV library which make possible to produce the physical scenario in which the exhibition will take place evaluating the measures from 2D maps, the SVG graphic format per representing the map after having detected the boundaries of the provided 2D map, Ajax, X3D and X3DOM which enable the virtual environment representation.

As a testbed we present the virtual museum of Villa Fidelia in Spello, PG, Italy.

The paper starting on page 683 of this publication has been retracted because a significant amount of material was taken verbatim and without permission from the publication “FABRIK: A fast, iterative solver for the Inverse Kinematics problem” by Andreas Aristidou and Joan Lasenby, © 2011 Elsevier Inc.