3HA: Hybrid Hole Healing Algorithm in a Wireless Sensor Networks

In wireless sensor networks (WSNs), the appearance of coverage holes over a large target field is mostly possible. Those holes reduce network performance and may affect the network efficiency. Several approaches were proposed to heal coverage holes in WSNs, but they still suffer from some weaknesses. In this paper we suggest a distributed algorithm, named hybrid hole healing algorithm (3HA), to find the minimum effective patching positions to deploy additional nodes to cover the holes. A hole manager node of each hole is responsible for operating the 3HA algorithm which requires two phases. The first phase finds all candidate patching positions using a Voronoi diagram. It takes all Voronoi vertices within the hole as the initial patching positions list. The second phase reduces as much as possible this list based on integer linear programming and on a probabilistic sensor model. The 3HA algorithm repeats the above phases in rounds, until all Voronoi vertices are covered. Simulation results show that our solution offers a high coverage ratio for various forms and sizes of holes and reduces the number of additional sensors when compared to some algorithms like the Perimeter-based, the Delaunay triangulation-based, the Voronoi-based, and the Trees-based coverage hole healing methods.

     

HiSQL: A Front-end Query System for Historical Relational Databases

The paper describes a prototype system called HiSQL (Historical SQL) which extends the functionality of SQL in manipulating historical data, by providing functions for spatial and temporal processing. Conceptually the paper is divided into three parts: the first part deals with the design and architecture of the system; the second part introduces a case study (the defters); and the third part describes specific functions for spatial and temporal processing of serial documents. The paper concludes with a comparison between HiSQL and SQL and suggestions for further work. This revised version was published online in August 2006 with corrections to the Cover Date.     

Analysis of thin walled structures using the boundary element method

In this article the direct boundary element formulations of stretching and bending plate problems are combined together to solve thin walled structures and other similar frames. The final system is obtained by assuming each individual plane structural element as a subregion. After the necessary transforms of these equations they can be combined together taking into account the displacement compatibility and equilibrium conditions.     

Determination of water activities and osmotic and activity coefficients of the system NaCl–BaCl2–H2O at 298.15 K

The water activities of the mixed aqueous electrolyte NaCl–BaCl₂(aq) are measured at total molalities from 0.25 mol kg⁻¹ to about saturation for different ionic strength fractions (y) of NaCl with y=0.33,0.50,0.67. The results allow the deduction of osmotic coefficients. The experimental results are compared with the predictions of the Zdanovskii, Stokes, and Robinson (ZSR), Kusik and Meissner (KM), Robinson and Stokes (RS), Lietzke and Stoughton (LSII), Reilly, Wood, and Robinson (RWR), and Pitzer models. From these measurements, the Pitzer mixing ionic parameters are determined and used to predict the solute activity coefficients in the mixture. The excess Gibbs energy is also determined.     

Simple Robust PID Tuning for Magnetic Levitation Systems Using Model-free Control and $${{\cal H}_\infty}$$ ℋ ∞ Control Strategies

International Journal of Control, Automation and Systems - This paper proposes two control techniques to provide robust tracking for magnetic levitation systems (MLS): model-free control (MFC) and...     

SOA$$^\mathrm{}$$: a new way to design the decision in SOA—based on the new standard Decision Model and Notation (DMN)

In recent years, Service Oriented Architecture (SOA) technologies are emerging as a powerful vehicle for organizations that need to integrate their applications within and across organizational boundaries. In addition, organizations need to make better decisions more quickly. Moreover, they need to change those decisions immediately to adapt to this increasingly dynamic business environment. It is primarily a question in ensuring the decisional aspect by adopting the SOA as a support architecture. In this paper, we describe a new approach called SOA\(^\mathrm{+d}\) based on a certain number of standards. It is going to be studied on three dimensions: The first is related to the definition of the information system implied in the SOA based on the use case model. The second develops the business dimension which is based on the BPMN (Business Process Modeling Notation). The last dimension addresses the need of decision; we use the new standard decision model and notation (DMN) which is recently approved by Object Management Group (OMG) and considered as a simple notation to specify the decision. Finally, Service Oriented Architecture Modeling Language (SoaML) will be used for design of several services. We also present our meta-model Decisional Model of Service (DMS) to define a new set of concepts necessary for modeling the three levels. Some of them are already known, whereas others are new and are proposed as an element of this work. we illustrate our proposal with a real case study in the Pharmacy Inventory Management.     

A learning framework for the optimization and automation of document binarization methods

Almost all binarization methods have a few parameters that require setting. However, they do not usually achieve their upper-bound performance unless the parameters are individually set and optimized for each input document image. In this work, a learning framework for the optimization of the binarization methods is introduced, which is designed to determine the optimal parameter values for a document image. The framework, which works with any binarization method, has a standard structure, and performs three main steps: (i) extracts features, (ii) estimates optimal parameters, and (iii) learns the relationship between features and optimal parameters. First, an approach is proposed to generate numerical feature vectors from 2D data. The statistics of various maps are extracted and then combined into a final feature vector, in a nonlinear way. The optimal behavior is learned using support vector regression (SVR). Although the framework works with any binarization method, two methods are considered as typical examples in this work: the grid-based Sauvola method, and Lu’s method, which placed first in the DIBCO’09 contest. The experiments are performed on the DIBCO’09 and H-DIBCO’10 datasets, and combinations of these datasets with promising results.