Volume 6, Issue 1

The paper proposes a new efficient approach to computation of interpolating spline surfaces. The generalization of an unexpected property, noticed while approximating polynomials of degree four by cubic ones, confirmed that a similar interrelation property exists between biquartic and bicubic polynomial surfaces as well. We prove that a 2×2-component C1 -class bicubic Hermite spline will be of class C2 if an equispaced grid is used and the coefficients of the spline components are computed from a corresponding biquartic polynomial. It implies that a 2×2 uniform clamped spline surface can be constructed without solving any equation. The applicability of this biquartic polynomials based approach to reducing dimensionalitywhile computing spline surfaces is demonstrated on an example.

Identifying the interesting places through GPS trajectory mining has been well studied based on the visitor’s frequency. However, the places popularity estimation based on the trajectory analysis has not been explored yet. The limitation in the majority of the traditional popularity estimation and place user-rating based methods is that all the participants are given the same importance. In reality, it heavily depends on the visitor’s category, for example, international visitors make distinct impact on popularity. The proposed method maintains a registry to keep the information about the visited users, their stay time and the travel distance from their home location. Depending on the travel nature the visitors are labeled as native, regional and tourist for each place in question. It considers the fact that the higher stay in a place is an implicit measure of the greater likings. Theweighted frequency is eventually fuzzified and applied rule based fuzzy inference system (FIS) to compute popularity of the places in terms of the ratings ∈ [0, 5]. We have evaluated the proposed method using a large real road GPS trajectory of 182 users for identifying the ratings for the collected 26807 point of interests (POI) in Beijing (China).

Games are a well-suited testbed for the development and evaluation of concepts and tools in artificial intelligence (AI). In our paper we outline the architecture of a web-based game server that was developed to support the teaching of artificial intelligence at the university level as well as research in the domain of AI and rule-based language development. The server combines a Prolog-based declarative approach with Java-based server technologies. The architecture consists of multiple, strictly separated components. Declarative components comprise the gameindependent core engine as well as game-dependent logic and visualization descriptions. General operations (e.g. user management, load balancing, match maintenance etc.) and rendering of the visualization descriptions with actual GUI techniques are implemented imperatively. External interfaces are provided to integrate remote developers and learners to facilitate usage beyond the borders of a single university.

Radial basis function networks (RBFNs) have gained widespread appeal amongst researchers and have shown good performance in a variety of application domains. They have potential for hybridization and demonstrate some interesting emergent behaviors. This paper aims to offer a compendious and sensible survey on RBF networks. The advantages they offer, such as fast training and global approximation capability with local responses, are attracting many researchers to use them in diversified fields. The overall algorithmic development of RBF networks by giving special focus on their learning methods, novel kernels, and fine tuning of kernel parameters have been discussed. In addition, we have considered the recent research work on optimization of multi-criterions in RBF networks and a range of indicative application areas along with some open source RBFN tools.

Internet-of-Things (IoT) is the latest buzzword, havings its origins in the erstwhile Sensor Networks. Sensor Networks produce a large amount of data. According to the needs this data requires to be processed, delivered and accessed. This processed data when made available with the physical device location, user preferences, time constraints; generically called as context-awareness; is widely referred to as the core function for ubiquitous systems. To our best knowledge there is lack of analysis of context information fusion for ubiquitous sensor networks. Adopting appropriate information fusion techniques can help in screening noisy measurements, control data in the network and take necessary inferences that can help in contextual computing. In this paper we try and explore different context information fusion techniques by comparing a large number of solutions, their methods, architectures and models. All the surveyed techniques can be adapted to the IoT framework.

The ready to use set of functions to facilitate solving a generalized eigenvalue problem for symmetric matrices in order to efficiently calculate eigenvalues and eigenvectors, using Compute Unified Device Architecture (CUDA) technology from NVIDIA, is provided. An integral part of the CUDA is the high level programming environment enabling tracking both code executed on Central Processing Unit and on Graphics Processing Unit. The presented matrix structures allow for the analysis of the advantages of using graphics processors in such calculations.

Streamlines are commonly used in scientific visualization. They are the most used geometric items in primitive-based visualization algorithms. In this paper, a modified version of the farthest point seeding strategy streamline placement is presented. The main advantage compared to the original method is the use of a simple easy to implement underlying data structure. The Delaunay triangulation used in the original algorithm is heavy and susceptible to the calculation robustness errors. The distances between lines and the localization of the biggest void in the domain are approximated using the Delaunay triangulation. This paper presents an adaptive distance grid to model the visualization domain and incorporate anywhere the local distance to all the other streamlines and the boundaries exactly without any approximation. The streamlines are started at the farthest point from all the existing ones and the domain boundaries. The localization of the seed point position is directly accessible via the distance adaptive grid. The grid update is direct too, and is done by a greedy algorithm avoiding any additional cost. The obtained results are sufficient, and the extension to multi-resolution is straight and simple.

This paper deals with particular issues in detection of human body’s movement using contactless sensor and consecutive application of recorded data on avatars model.We aimed at applying transformations to the skeleton model and skin of the avatar. Initial stages include choice of proper sensor and appropriate methods for transformation description. A semi-immersive virtual reality training system in the form of a fitting room has been chosen as a particular implementation of the body movement detection and application. The fitting room was selected because of its entertaining nature and a potential to be used as a training system for handicapped people with movement impairments.

We describe the notion of abstraction and conceptualization of information obtained by symbolization of letters. We are able to recognize already observed information with those abstracted concepts. Further more, we are also able to recognize similar meaningful objects. Similarities identification is based on a repetition in the structure of information symbolized as a regular language string. We discuss approaches of repetition identification, i.e., longest repeating non-overlapping subsequence and longest common subsequence. Then we apply those approaches to the symbolized letters, thus obtaining abstracted information in the form of concepts.

Existing 3D MEMS-based optical switches offer good optical properties (low insertion loss, low crosstalk), high reliability and low power consumption. These switches utilize highly reflective micro-mirrors to manipulate an optical signal inside the switch directly without any conversions. They are used to build dynamically reconfigurable, highly-scalable physical optical network layer. As indicated by the simulation results of this paper, many of existing micro-mirror designs do not have their dynamic characteristics well optimized and this limits the switching speed of the optical switch. In a 3DMEMS switch, the coupling between the mechanical structure (micro-mirror) and electrostatic field (electrodes) results in dynamic coupled rotation of the micro-mirror about its axes, known as the cross-axis coupling effect. The coupling nature of micro-mirror rotation makes its control difficult. In this paper,we present the simulation case studies and a simple optimization technique leading to decoupled rotation of the micro-mirror about two perpendicular axes. This helps to reduce the switching time of the switch while keeping the same manufacturing process and only minimal design changes.

Context in the form of meta-data has been accredited as an important component in cross-domain collaborative filtering (CDCF). In this research paper CDCF concept is used to exploit event information (context) from two UI matrices to allow the recommendation performance of one domain (Facebook- User-Event Matrix) to benefit from the information from another domain (Bookmyshow- Event-Tag Matrix). The model based collaborative filtering approach Tensor Factorization(TF) has been used to integrate Facebook provided User-Event context information with Bookmyshow Event-Tag context information to recommend events. In contrast to the standard collaborative tag recommendation, our CDCF approach uses one User-Event matrix of Facebook that takes another Bookmyshow Event-Tag matrix as additional informant. The proposed cross-domain based Event Recommendation approach is divided into three modules- i) data collection which extracts the unstructured dataset from the two domains Bookmyshow and social networking site Facebook using API’s; ii) data mapping module which is basically used to integrate the common knowledge/ data that can be shared between considered different domains (Facebook & Bookmyshow). This module integrates and reduces the data into structured events’ instances. As the dataset was collected from two different sites, an intersection of both was taken out. Therefore this module is carefully designed according to reliability of information that is common between two domains; iii) 3 order tensor factorization and Latent Dirichlet Allocation (LDA) used for most preferable recommendation by less pertinent result reduction. The proposed 3 order tensor factorization is designed for maximizing the mutual benefit from both the considered domains (organizer and user). Therefore providing three recommendations: For organizers: 1) system recommends places to conduct specific event according to maximum of attendees of a particular type of event at a specific location; 2) recommending target audience to organizer: those who are interested to attend event on the basis of past data for promotion purposes. For users: 3) recommending events to users of their interest on the basis of past record. Our result shows significant improvement in reduction of less relevant data and result effectiveness is measured through recall and precision. Reduction of less relevant recommendation is 64%, 72% and 63% for place recommendation to organizer, target audience recommendation to organizer and event recommendation to user respectively. The proposed tensor factorization approach achieved 68% precision, 15.5% recall in recommending attendees to organizer and 62% precision, 13.4% recall for event recommendation to user.

In this paper, we try to present the problems of the modern approach to treating various phobias. Virtual environments created by virtual reality (VR) tools can help to make the treatment of certain types of phobias more efficient. Attention to this form of phobia treatment with the help of VR is on the rise in the world, so we are also monitoring its development, as well. Our paper introduces the necessary hardware and software that has been piloted in our department, but also methods of creating virtual environments, models and application designed for medical therapies of patients. In ourworkwe have searched for and tested the following methods for creating virtual environments: A) modelling using computer graphics, B) modelling animation using animation programs, C) taking pictures of static objects and scenes, D) filming moving objects and scenes using classic video or special scanning techniques to create 360∘ panoramas or E) any combination of these methods.

This article presents a comprehensive study of 30 color transforms to accurately segment images of halftone prints and thus calculating the parameters of a color prediction model. The transforms are evaluated combining three metrics: the model accuracy,Otsu’s discriminant, and correlation coefficients of histograms. Hierarchical cluster analysis is applied to determine the thresholds to segment the image histogram into paper, ink and mixed area. Among the 30 different transforms discussed in this article, 21 channels are of 7 color space models (RGB, CMYK, CIELAB, HSV, YIQ, YCbCr, and XYZ) and the other 9 channels are specially designed. Notable increase in model accuracy validates the segmentation accuracy and the necessity of choosing the appropriate transform. A set of 180 halftone images of different print properties (such as paper, halftone, ink and printing technology) has been used for the evaluation. It is found that, the most appropriate transform depends on the type of primary ink, but the corresponding transforms in CMYK color space model have shown consistent performance. CMYK-C, XYZ-Y and LAB-B are the best transforms for Cyan, Magenta and Yellow ink color respectively. YIQ-I and HSV-S are good candidates if a single transform is to be chosen for all primary ink colors.

Texts (books, novels, papers, short messages) are sequences of sentences, words or symbols. Each author has an unique writing style. It can be characterized by some collection of attributes obtained from texts. The text verification is the case of an authorship verification where we have some text and we analyze if all parts of this textwere written by the same (unknown or known) author. In this paper, there are analyzed and compared results of two developed methods for a text verification based on ngrams of symbols and on local histograms of words. The results of a symbol n-gram method and a method of word histograms for a dissimilarities searching in text parts of each text are analyzed and evaluated. The searched dissimilarities call for an attention to the text (or not) if the text parts were written by the same author or not. The attention depends on selected parameters prepared in experiments. Results illustrate usability of the methods to dissimilarities searching in text parts.

This paper develops the nonlinear model predictive control (NMPC) algorithm to control autonomous robots tracking feasible paths generated directly from the nonlinear dynamic equations.NMPC algorithm can secure the stability of this dynamic system by imposing additional conditions on the open loop NMPC regulator. The NMPC algorithm maintains a terminal constrained region to the origin and thus, guarantees the stability of the nonlinear system. Simulations show that the NMPC algorithm can minimize the path tracking errors and control the autonomous robots tracking exactly on the feasible paths subject to the system’s physical constraints.

Good object-oriented design is crucial for a successful software product. Metric-based approaches and the identification of design smells are established concepts for identifying design flaws and deriving design improvements thereof. Nevertheless, metrics are difficult to use for improvements as they provide only weak guidance and are difficult to interpret. Thus, this paper proposes a novel design quality model (DQM) based on fundamental object-oriented design principles and best practices. In course of discussing DQM, the paper provides a contribution in three directions: (1) it shows how to measure design principles automatically, (2) then the measuring result is used to assess the degree of fulfilling object-oriented design principles, (3) and finally design improvements of identified design flaws in object-oriented software are derived. Additionally, the paper provides an overview of the research area by explaining terms used to describe designrelated aspects and by depicting the result of a survey on the importance of object-oriented design principles. The underlying concepts of the DQM are explained before it is applied on two open-source projects in the format of a case study. The qualitative discussion of its application shows the advantages of the automated design assessment that can be used for guiding design improvements.

An upgraded version of Ford-Fulkerson algorithm is proposed, which allows to determine the maximum flow and the distribution flow in branches of the network. Results of simulation using this algorithm are given. They show its effectiveness in comparison with the other variants of flow distribution in the network at change of the capacity of branches randomly in time.

The initial boundary value problem of the dynamics of fluid saturated porous media, described by three elastic parameters in the reversible hydrodynamic approximation, is numerically solved. A linear two-dimensional problem as dynamic equations of porous media for components of velocities, stresses and pore pressure is considered. The equations of motion are based on conservation laws and are consistent with thermodynamic conditions. In this case, a medium is considered to be ideally isotropic (in the absence of energy dissipation) and twodimensional heterogeneous with respect to space. For a numerical solution of the dynamic problem of poroelasticity we use the Laguerre transform with respect to time and the finite difference technique with respect to spatial coordinates on the staggered grids with fourth order of accuracy. The description of numerical implementation of the algorithm offered is presented, and its characteristics are analyzed. Numerical results of the simulation of seismic wave fields for the test layered models have been obtained on the multiprocessor computer.

Grapheme to phoneme conversion is one of the main subsystems of Text-to-Speech (TTS) systems. Converting sequence of written words to their corresponding phoneme sequences for the Persian language is more challenging than other languages; because in the standard orthography of this language the short vowels are omitted and the pronunciation ofwords depends on their positions in a sentence. Common approaches used in the Persian commercial TTS systems have several modules and complicated models for natural language processing and homograph disambiguation that make the implementation harder as well as reducing the overall precision of system. In this paper we define the grapheme-to-phoneme conversion as a sequential labeling problem; and use the modified Recurrent Neural Networks (RNN) to create a smart and integrated model for this purpose. The recurrent networks are modified to be bidirectional and equipped with Long-Short Term Memory (LSTM) blocks to acquire most of the past and future contextual information for decision making. The experiments conducted in this paper show that in addition to having a unified structure the bidirectional RNN-LSTM has a good performance in recognizing the pronunciation of the Persian sentences with the precision more than 98 percent.

A workflow is an automation of a process, in which participants (people or programs) are involved in activities for solving a set of tasks according to certain rules and constraints in order to attain a common goal. The concept of workflow appeared in business informatics. Currently the workflow techniques are used in many other fields such as medical informatics, bioinformatics, automation of scientific research, computer-aided design and manufacturing, etc. An ontology is a formal description (in terms of concepts, entities, their properties and relationships) of knowledge for solving a given class of problems. In particular, ontologies can be used in problems related to workflows. In this paper, we introduce a formalism that extends the language of the interval Allen’s logic, and show how this formalism can be applied to specify temporal knowledge in ontologies for workflows. For the extended Allen’s logic, we construct a deduction system based on the analytic tableaux method. We also show (by examples) how to apply the deduction method to query answering over ontologies written in the extended Allen’s logic.