Use of distributed data sources in facility location

Facility location decisions are usually determined by cost and coverage related factors although empirical studies show that such factors as infrastructure, labor conditions and competition also play an important role in practice. The objective of this paper is to develop a multi-objective facility location model accounting for a wide range of factors affecting decision-making. The proposed model selects potential facilities from a set of pre-defined alternative locations according to the number of customers, the number of competitors and real-estate cost criteria. However, that requires large amount of both spatial and non-spatial input data, which could be acquired from distributed data sources over the Internet. Therefore, a computational approach for processing input data and representation of modeling results is elaborated. It is capable of accessing and processing data from heterogeneous spatial and non-spatial data sources. Application of the elaborated data gathering approach and facility location model is demonstrated using an example of fast food restaurants location problem.     

Soft computing-based approaches to predict energy consumption and stability margin of six-legged robots moving on gradient terrains

Soft computing-based approaches have been developed to predict specific energy consumption and stability margin of a six-legged robot ascending and descending some gradient terrains. Three different neuro-fuzzy and one neural network-based approaches have been developed. The performances of these approaches are compared among themselves, through computer simulations. Genetic algorithm-tuned multiple adaptive neuro-fuzzy inference system is found to perform better than other three approaches for predicting both the outputs. This could be due to a more exhaustive search carried out by the genetic algorithm in comparison with back-propagation algorithm and the use of two separate adaptive neuro-fuzzy inference systems for two different outputs. A designer may use the developed soft computing-based approaches in order to predict specific energy consumption and stability margin of the robot for a set of input parameters, beforehand.     

Effects of turning gait parameters on energy consumption and stability of a six-legged walking robot

Minimization of energy consumption plays a key role in the locomotion of a multi-legged robot used for various purposes. Turning gaits are the most general and important factors for omni-directional walking of a six-legged robot. This paper presents an analysis on energy consumption of a six-legged robot during its turning motion over a flat terrain. An energy consumption model is developed for statically stable wave gaits in order to minimize dissipating energy for optimal feet forces distributions. The effects of gait parameters, namely angular velocity, angular stroke and duty factors are studied on energy consumption, as the six-legged robot walks along a circular path of constant radius with wave gait. The variations of average power consumption and energy consumption per unit weight per unit traveled length with the angular velocity and angular stroke are compared for the turning gaits of a robot with four different duty factors. Computer simulations show that wave gait with a low duty factor is more energy-efficient compared to that with a high duty factor at the highest possible angular velocity. A stability analysis based on normalized energy stability margin is performed for turning motion of the robot with four duty factors for different angular strokes.     

Process diagnostics using trace alignment: Opportunities, issues, and challenges

Business processes leave trails in a variety of data sources (e.g., audit trails, databases, and transaction logs). Hence, every process instance can be described by a trace, i.e., a sequence of events. Process mining techniques are able to extract knowledge from such traces and provide a welcome extension to the repertoire of business process analysis techniques. Recently, process mining techniques have been adopted in various commercial BPM systems (e.g., BPM|one, Futura Reflect, ARIS PPM, Fujitsu Interstage, Businesscape, Iontas PDF, and QPR PA). Unfortunately, traditional process discovery algorithms have problems dealing with less structured processes. The resulting models are difficult to comprehend or even misleading. Therefore, we propose a new approach based on trace alignment. The goal is to align traces in such a way that event logs can be explored easily. Trace alignment can be used to explore the process in the early stages of analysis and to answer specific questions in later stages of analysis. Hence, it complements existing process mining techniques focusing on discovery and conformance checking. The proposed techniques have been implemented as plugins in the ProM framework. We report the results of trace alignment on one synthetic and two real-life event logs, and show that trace alignment has significant promise in process diagnostic efforts.     

Choroidal neovascular membrane in Best's vitelliform macular dystrophy

The right eye of a 9-year-old white boy with Best's vitelliform macular dystrophy had an intact egg-yolk lesion and a retinal pigment epithelial defect superiorly, suggesting an early pseudohypopyon stage. The disruptive phase of the left eye showed subretinal hemorrhages, a "signet ring," and a subretinal neovascular membrane.     

Searching for points-to analysis

The points-to analysis problem is to find the pointer relationships that could arise during program execution. Many points-to analysis algorithms exist, each making a particular trade off between cost of the analysis and precision of the results. In this paper, we show how points-to analysis algorithms can be defined as transformed versions of an exact algorithm. We present a set of program transformations over a general program model and use them to define some existing points-to analysis algorithms. Doing so makes explicit the approximations involved in these algorithms. We also show how the transformations can be used to define new points-to analysis algorithms. Our transformations are generic and may be useful in the design of other program analysis algorithms.     

Influence of Liquid Phase Additives on Structural and Sintering Behaviour of Samarium Modified Lead Titanate Ceramics

The combination of metal oxides Bi₂O₃:Li₂O in a ratio 89:11 gives a eutectic with a melting point of ～680°C. Such a low melting point oxide combination creates a working liquid phase at a highly favorable temperature for use as a densification aid. A liquid—phase sintering aid incorporating Bi₂O₃ and Li₂O is presented which demonstrates not only a reduction in the required sintering temperature but also shows relatively higher ‘c/a’ ratio (tetragonality) of PbTiO₃ ceramics with no fragility of the samples. Detailed dilatometric investigations have been performed in order to study the dominant shrinkage mechanism in the present system. Besides acting as a liquid phase fluxing agent, Bi₂O₃/Li₂O also behave as Curie shifter, which decreases Curie temperature in lead titanate system. The Curie temperature has also been verified from the thermal expansion behavior of sintered specimens. The value of dielectric constant increases after poling which may be due to the dominance of 180° domain wall over 90°.     

Modeling Compression Behavior of Structured Geomaterials

The influence of the natural (or artificially induced) structure of a geomaterial on its compression behavior is investigated. An approach for modeling this influence for various structured geomaterials is proposed by using the disturbed state concept. An isotropic compression model is formulated on three basic assumptions. A special version of the proposed model is also described for situations where the compression is one-dimensional. The proposed compression model is used to simulate the behavior of a variety of structured geomaterials such as clays, sands, calcareous soils, clay-shale, soft rock, unsaturated soils, and soils artificially treated by adding chemical agents or mechanical reinforcement, and the model is evaluated on the basis of these simulations. A general discussion on the influence of the structure of geomaterials on their mechanical properties is also presented.