A case study on the object-oriented framework for modeling product families with the dominant variation of the topology in the one-of-a-kind production

Traditional configuration-based product family modeling techniques do not yield favorable solutions for modeling the product families with the dominant product topology variations. This paper presents the case study for the modeling of variations of the product configuration, parameters, and topologies in mass production of custom windows and doors in a one-of-a-kind production (OKP) company. The case study is based on the object-oriented product family modeling framework we developed for OKP which is characterized by the dominant product variation by topology. The problem of variation in topology in our framework is solved by the manual model transformation in the computer-aided design module which creates a new metamodel of products with the desired topology and which is the basis for a further, automatic model transformation. Usage of our framework has a positive effect on the level of the product customizations and shortening of the leading time which helps OKP companies in obtaining a better position at the market. Our software solution for the designing and manufacturing of custom windows and doors based on our framework is implemented in more than 300 mostly small- and medium-sized enterprises. It proves our concept which can be used for the realization of the information systems for computer-aided one-of-a-kind production in the companies with a different production plan.     

Aerodynamic design and analysis of a small-scale vertical axis wind turbine

Small-scale vertical axis wind turbines are regarded today as an attractive source of green energy, still insufficiently implemented and tested. This paper presents a fast design methodology of such a VAWT, in terms of choosing its main parameters: airfoil, rotor diameter and solidity. For obtaining generated power of each considered geometrical model at different undisturbed wind velocities and rotor angular velocities two models were used — momentum and vortex-wake model, combined with experimentally measured airfoil data (airfoil lift and drag coefficients). Even though the former model is simpler, it is the most utilized model, known to provide good results in stationary working regimes. Both models still present fairly accurate and fast tools for computation and optimization, particularly useful in the phase of conceptual design. In this research, the use of the momentum model resulted in determination of the maximal power coefficient, optimal- and minimal freestream velocity for every considered VAWT model. From these output parameters, a selection of the optimal geometric model was done, and a more detailed transient analysis and flow representation around the selected solution was obtained by the vortex-wake model. The results obtained by the two used computational models coincide satisfactorily.     

Implicit Meshes for Effective Silhouette Handling

Using silhouettes in uncontrolled environments typically requires handling occlusions as well as changing or cluttered backgrounds, which limits the applicability of most silhouette based methods. For the purpose of 3-D shape modeling, we show that representing generic 3-D surfaces as implicit surfaces lets us effectively address these issues. This desirable behavior is completely independent from the way the surface deformations are parame-trized. To show this, we demonstrate our technique in three very different cases: Modeling the deformations of a piece of paper represented by an ordinary triangulated mesh; reconstruction and tracking a person’s shoulders whose deformations are expressed in terms of Dirichlet Free Form Deformations; reconstructing the shape of a human face parametrized in terms of a Principal Component Analysis model. Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users. This work was supported in part by the Swiss National Science Foundation     

A multimodal hand-based verification system with an aliveness-detection module

This paper presents a multimodal biometrie verification system based on the following hand features: palmprint, four digitprints and four fingerprints. The features are obtained using the Karhunen-Loève transform based approach, and information fusion at the matching-score level was applied. We experimented with different resolutions of the regions of interest, different numbers of features and several normalization and fusion techniques at the matching-score level. To increase the reliability of the system to spoof attacks we included an aliveness-detection module based on thermal images of the hand dor sa. The verification performance when using a system configuration with optimum parameters, i.e., resolution, number of features, normalization and fusion technique, showed an equal error rate (EER) of 0.0020%, which makes the system appropriate for the implementation of high-security biometric systems.     

Application of fuzzy logic for evaluation of the level of social acceptance of waste treatment

The social aspect is very important in sustainability assessment of waste treatment technique, as well as making decision on their application and planning. In recent years, it is becoming evident that a waste treatment technique, which ignores social aspects, is doomed to failure. The most commonly used social indicators are: number of jobs created, level of social acceptance, public knowledge, public health etc. The most of them are qualitative and measuring the sustainability and quantifying the social dimension of sustainability are difficult tasks. This paper presents the application of fuzzy logic for evaluating the social indicator—level of social acceptance. The fuzzy set theory and fuzzy logic were used to develop a model for the evaluation of level of social acceptance, due to the lack of data, uncertainties, and qualitative character of indicators and also to provide effective way to include knowledge and gained experience on the process. A questionnaire was applied as instrument for data collection. The fuzzy model was verified using the city of Ni? as a case study. The results obtained using the developed fuzzy model, shows that the highest level of social acceptance in the city of Ni? is for recycling (57.47 %) and the lowest level of social acceptance is for incineration (17.74 %). The presented study suggests an innovative methodology for evaluation of level of social acceptance of certain waste treatment based on fuzzy logic approach and can be used for ranking of waste management scenarios in the sustainability assessment.     

Supervised clustering of label ranking data using label preference information

This paper studies supervised clustering in the context of label ranking data. The goal is to partition the feature space into K clusters, such that they are compact in both the feature and label ranking space. This type of clustering has many potential applications. For example, in target marketing we might want to come up with K different offers or marketing strategies for our target audience. Thus, we aim at clustering the customers’ feature space into K clusters by leveraging the revealed or stated, potentially incomplete customer preferences over products, such that the preferences of customers within one cluster are more similar to each other than to those of customers in other clusters. We establish several baseline algorithms and propose two principled algorithms for supervised clustering. In the first baseline, the clusters are created in an unsupervised manner, followed by assigning a representative label ranking to each cluster. In the second baseline, the label ranking space is clustered first, followed by partitioning the feature space based on the central rankings. In the third baseline, clustering is applied on a new feature space consisting of both features and label rankings, followed by mapping back to the original feature and ranking space. The RankTree principled approach is based on a Ranking Tree algorithm previously proposed for label ranking prediction. Our modification starts with K random label rankings and iteratively splits the feature space to minimize the ranking loss, followed by re-calculation of the K rankings based on cluster assignments. The MM-PL approach is a multi-prototype supervised clustering algorithm based on the Plackett-Luce (PL) probabilistic ranking model. It represents each cluster with a union of Voronoi cells that are defined by a set of prototypes, and assign each cluster with a set of PL label scores that determine the cluster central ranking. Cluster membership and ranking prediction for a new instance are determined by cluster membership of its nearest prototype. The unknown cluster PL parameters and prototype positions are learned by minimizing the ranking loss, based on two variants of the expectation-maximization algorithm. Evaluation of the proposed algorithms was conducted on synthetic and real-life label ranking data by considering several measures of cluster goodness: (1) cluster compactness in feature space, (2) cluster compactness in label ranking space and (3) label ranking prediction loss. Experimental results demonstrate that the proposed MM-PL and RankTree models are superior to the baseline models. Further, MM-PL is has shown to be much better than other algorithms at handling situations with significant fraction of missing label preferences.     

INFERENCE PROCEDURES FOR FUZZY KNOWLEDGE REPRESENTATION SCHEME

This article presents a formal model of the knowledge representation scheme based on the fuzzy Petri net (FPN) theory. The model is represented as a 13-tuple consisting of the components of the FPN, two functions that give semantic meanings to the scheme and a set of contradictions. For the scheme, called the knowledge representation scheme based on the fuzzy Petri nets theory (KRFPN) the fuzzy inheritance and fuzzy recognition-inference procedures based on the dynamical properties of the FPN, are described in detail. The upper-time complexity of both the proposed inference algorithms is O(nm), where n is the number of places (concepts) and m is the number of transitions (relations) in the scheme. Illustrative examples of the fuzzy inheritance and the fuzzy recognition algorithms for the knowledge base, designed by the KRFPN, are given.     

The Use of Object-Oriented Modeling for Water Resources Planning in Egypt

Water problems are omnipresent and are already becoming a limiting factor in the development of many countries. Currently the balance between the available and required water in Egypt is fragile. Any movement away from the balancing point means either less ambitious economic development or depletion of the resources and degradation of the environment. The continuing revolution in computer hardware and software is expected to provide more insight into the water problems and to alleviate some of the future water crises. In this paper we have investigated potential benefits which can be accrued from the application of object-oriented modeling in water resources.     

Improvement of the stoichiometric network analysis for determination of instability conditions of complex nonlinear reaction systems

Stoichiometric network analysis (SNA), a known method for analyzing complex reaction systems including biochemical ones, is improved and applied to a nonlinear process studied far from equilibrium in a continuously fed, well stirred tank reactor (CSTR). A particular attention is focused on the determination of the narrow range of the control parameter values where the main steady state is unstable and where different dynamic states can be simulated numerically. The instability region, the most important feature of nonlinear reaction systems, is calculated as a function of the SNA parameters (current rates and reciprocal concentrations of intermediate species in the steady state) and simplified by retaining only the dominant terms. Since the number of the current rates is usually larger than the number of linearly independent equations to be used for their calculation, it is shown here that the current rates can be replaced with a smaller number of reaction rates at the steady state. These rates are related to the experimental data in a simple manner. The instability condition is also written as a function of dimensionless parameters derived from the SNA. This general approach is applied to a model of the Bray–Liebhafsky (BL) reaction having seven reactions without direct autocatalysis or autoinhibition, studied under CSTR conditions. Since the model has six intermediate species, it would be very difficult to analyze its instability condition by the conventional procedure, where a sixth order characteristic equation would have to be solved. On the other hand, the instability condition, obtained easily by the improved SNA, locates correctly the oscillatory region using numerical integration. Other dynamic states found earlier with a larger model of the BL reaction, such as mixed-mode oscillations, period doubling and chaos, are also obtained within the theoretically predicted oscillatory region. Thus, besides the general advantages of the improved stoichiometric network analysis as a method appropriate for the examination of complex nonlinear reactions, we show that the various mentioned dynamic states can be obtained by a very simple variant of the model of the BL reaction realized under CSTR conditions.