Process network solution of a clothing manufacturer’s problem

The current work focuses on a Hungarian clothing manufacturer’s problem. First the industrial problem is presented; its corresponding critical pass method graph is depicted. To answer all emerging questions with respect to alternative possibilities, a large number of critical pass method problems have to be solved cumbersomely. Instead, first this graph is transformed into a process network. Alternatives specified by mainly financial necessities as well as human resource constraints can now be easily managed, namely where specific activities can be performed in different ways by various employee having different qualifications, requiring different durations and obviously respective costs can be considered within this model. These separate cases can commonly be handled within the resultant sole process network and the corresponding mathematical programming model

Histogram based segmentation of shadowed leaf images

This paper corresponds to the solution of some problems realized during ragweed identification experiments, namely the samples collected on the field by botanical experts did not match the initial conditions expected. Reflections and shadows appeared on the image, which made the segmentation more difficult, therefore also the classification was not efficient in previous study. In this work, unlike those solutions, which try to remove the shadow by restoring the illumination of image parts, the focus is on separating leaf and background points based on chromatic information, basically by examining the histograms of the full image and the border. This proposed solution filters these noises in the subspaces of hue, saturation and value space and their combination. It also describes a qualitative technique to select the appropriate values from the filtered outputs. With this method, the results of segmentation improved a lot

Identification of Shadowed Areas to Improve Ragweed Leaf Segmentation

As part of a project targeting geometrical structure analysis and identification of ragweed leaves, sample images were created. Even though images were taken under near optimal conditions, the samples still contain noise of cast shadow. The proposed method improves chromaticity based primary shape segmentation efficiency by identification and re-classification of the shadowed areas. The primary classification of each point is done generally based on thresholding the Hue channel of Hue/Saturation/Value color space. In this work, the primary classification is enhanced by thresholding an intra-class normalized weight computed from the class specific Value channel. The corrective step is the removal of areas marked as shadow from the object class. The idea is based on the assumption that the image contains a single, flat leaf in front of a homogeneous background, but there are no color and illumination restrictions. Thus, parameters of the imaging system and the light sources have influence on homogeneity of image parts; however vague shadows differ only in intensity, and hard shadows can only be dropped on the background

Ragweed detection based on SURF features

U radu se opisuje analiza parametara koji odgovaraju automatskom otkrivanju ambrozije na temelju SURF značajki. Osnovna ideja je sastaviti bazu podataka značajki iz vrlo jednostavnih uzoraka s karakterističnim obilježjima listova biljke i usporediti bazu podataka tih značajki sa značajkama dobivenim iz običnih slika sa ili bez ambrozije. Rezultati istraživanja jasno pokazuju da takav pristup ima svrhu te vrijednost kao posebna metoda ili kao moguća baza za učenje ekspertnog sustava klasifikacije.The paper describes a parameter study corresponding to automatic detection of ragweed based on SURF features. The basic idea behind the method is to build a feature database from very simple ragweed samples containing characteristic features of the leaves of the plant, and compare the feature database to features extracted from natural images which contain or lack ragweed. The results of the study clearly show that the approach is promising and has value as a standalone method, or as a potential training basis for a classification expert system

Algorithmic Generation of Building Typology for Office Building Design

Numerous office building design optimizations are in international research to reduce energy consumption, optimize costs and provide optimal comfort. However, there is a lack of knowledge on the effects of geometry and space organization. This study deals with space organization problems and searches for all possible optimal building space structure configurations in terms of energy and comfort parameters using a mathematical algorithmic method. The methodology is based on the formulation of feasible architectural rules and their translation into an algorithm that can generate 2D floor plans satisfying all boundary conditions. In the framework of an exemplary modeling procedure, a 4-story office building geometry generation was carried out, resulting in 17-floor plan versions and 7 different building geometries. The resulting building shapes were classified by energy-related geometry parameters (envelope surface/useful area) for the future step of the research, where the cases will be compared with the help of building simulations. With the help of the method, it was possible to significantly narrow the search space, but future improvements are needed for faster work for wider applicability

Building Geometry as a Variable in Energy, Comfort, and Environmental Design Optimization—A Review from the Perspective of Architects

Due to negative environmental impacts caused by the building industry, sustainable buildings have recently become one of the most investigated fields in research. As the design technique itself is mainly responsible for building performance, building energy design optimization is of particular interest. Several studies concentrate on systems, operation, and control optimization, complemented by passive strategies, specifically related to the envelope. In building physics, different architectural considerations, in particular, the building’s shape, are essential variables, as they greatly influence the performance of a building. Most scientific work that takes into consideration building geometry explores spaces without any energy optimization or calculates optimization processes of a few basic variables of simplified space geometries. Review studies mainly discuss the historic development of optimization algorithms, building domains, and the algorithm-system and software framework performance with coupling issues. By providing a systemized clustering of different levels of shape integration intensities, space creation principals, and algorithms, this review explores the current status of sustainability related shape optimization. The review proves that geometry design variable modifications and, specifically, shape generation techniques offer promising optimization potential; however, the findings also indicate that building shape optimization is still in its infancy

A Novel Measure Inspired by Lyapunov Exponents for the Characterization of Dynamics in State-Transition Networks

The combination of network sciences, nonlinear dynamics and time series analysis provides novel insights and analogies between the different approaches to complex systems. By combining the considerations behind the Lyapunov exponent of dynamical systems and the average entropy of transition probabilities for Markov chains, we introduce a network measure for characterizing the dynamics on state-transition networks with special focus on differentiating between chaotic and cyclic modes. One important property of this Lyapunov measure consists of its non-monotonous dependence on the cylicity of the dynamics. Motivated by providing proper use cases for studying the new measure, we also lay out a method for mapping time series to state transition networks by phase space coarse graining. Using both discrete time and continuous time dynamical systems the Lyapunov measure extracted from the corresponding state-transition networks exhibits similar behavior to that of the Lyapunov exponent. In addition, it demonstrates a strong sensitivity to boundary crisis suggesting applicability in predicting the collapse of chaos