A model of diatom shape and texture for analysis, synthesis and identification

We describe tools for automatic identification and classification of diatoms that compare photographs with other photographs and drawings, via a model. Identification of diatoms, i.e. assigning a new specimen to one of the known species, has applications in many disciplines, including ecology, palaeoecology and forensic science. The model we build represents life cycle and natural variation of both shape and texture over multiple diatom species, derived automatically from photographs and/or drawings. The model can be used to automatically produce drawings of diatoms at any stage of their life cycle development. Similar drawings are traditionally used for diatom identification, and encapsulate visually salient diatom features. In this article, we describe the methods used for analysis of photographs and drawings, present our model of diatom shape and texture variation, and finish with results of identification experiments using photographs and drawings as well as a detailed evaluation.     

A shape optimization study for tool design in resistance welding

The purpose of this study is to apply shape optimization tools for design of resistance welding electrodes. The numerical simulation of the welding process has been performed by a simplified FEM model implemented in COMSOL. The design process is formulated as an optimization problem where the objective is to prolong the life-time of the electrodes. Welding parameters like current, time and electrode shape parameters are selected to be the design variables while constraints are chosen to ensure a high quality of the welding. Surrogate models based on a Kriging approximation has been used in order to simplify the calculation of shape sensitivities and to generate a generic tool that can be interfaced with other simulation tools. An example numerical study shows the potential of applying optimal design techniques in this area. Part of this work was presented at WCSMO7 in Seoul Korea, May 21–25, 2007, in the paper titled ‘Some optimization aspects of resistance welding’ (CD-ROM, pp 2687–2695).     

A shape analysis framework for neuromorphometry

This paper addresses in an integrated and systematic fashion the relatively overlooked but increasingly important issue of measuring and characterizing the geometrical properties of nerve cells and structures, an area often called neuromorphology. After discussing the main motivation for such an endeavour, a comprehensive mathematical framework for characterizing neural shapes, capable of expressing variations over time, is presented and used to underline the main issues in neuromorphology. Three particularly powerful and versatile families of neuromorphological approaches, including differential measures, symmetry axes/skeletons, and complexity, are presented and their respective potentials for applications in neuroscience are identified. Examples of applications of such measures are provided based on experimental investigations related to automated dendrogram extraction, mental retardation characterization, and axon growth analysis.     

Principal component analysis: A tool for assembly management

The dimensional variations of components or detail parts in a complex assembly could be within the acceptable specifications, but when put together, the proper fit of the final assembly can not be obtained. It becomes difficult to locate the root cause of the assembly misfit. The principal component analysis, a multi-variant statistical method, can define the position of the principal variables or the major parameters which signify the misfit condition. Depending on the correlation strength of the original variables, it is possible to present the variation characteristics of 20 or 30 variables by only two or three principal components. The method is simple to use, and could save time and money by accelerating the identification of the assembly problems.     

A user-friendly tool for image analysis

A new graphical tool (Multimedia University’s RSIMANA—Remote-Sensing Image Analyzer) developed for image analysis is described in this paper. MATLAB and ENVI are some of the commercially available tools in the market that aid in image processing and analysis. But their current versions are of limited assistance in image analysis; for example, MATLAB can extract the area of irregular objects and patterns in images, but not their length. ENVI is more focused on image processing than on image analysis functions. Other commercially available tools are also prohibitively expensive. This indicates the need to develop a userfriendly graphical tool that meets research objectives in the educational environment. The text was submitted by the author in English. Hema Nair. Born 1965. Educational qualifications: B.Tech. (Electrical Engineering) from Government Engineering College affiliated to University of Calicut, Kerala State, India, 1986; MSc (Electrical Engineering) from National University of Singapore, 1993; MSc (Computer Science) from Clark Atlanta University, USA, 1996. Previous employment: Researcher and Project Leader in AT & T, New Jersey, USA, for about 5 years. Also worked in Bangalore, India, before that in Apple Information Technology Ltd. as Teaching Faculty. Current employment: lecturer, Faculty of Engineering and Technology, Multimedia University, Malaysia. Current research: the final stages of her PhD in Computer Science at Multimedia University. Scientific interests are image analysis, pattern recognition, databases, AI, data mining. Member of IEEE (USA) since 1997, Professional Member of ACM (USA) since 1997, Member of Institution of Engineers (India) since 1986. Reviewer for IASTED International Conference 2004. Current PhD project entitled “Pattern Extraction and Concept Clustering in Linguistic Terms from Mined Images” is funded by an Intensive Research in Priority Area (IRPA) grant from Government of Malaysia. Research for MSc in Computer Science from USA was funded by a research grant from the US Army. Author of three International Conference papers accepted in Portugal, Belgium, and India.     

A tool for graphical network modeling and analysis

GMA, a generic graphical modeling and analysis package that satisfies both commercial users and performance evaluation researchers is described. Using a graphical interface, both novices and experts can analyze the performance of diverse networks simply by loading a configuration file and traffic data. GMA accommodates a variety of networks and modeling techniques. Its structure and use are described, and a simple four-node network is analyzed as an example     

A Web-based tool for data analysis and presentation

In a distributed development environment, the display and analysis of project data are complicated by heterogeneous environments. The authors discuss WebME visualization tool that gathers disparate development data collected from distributed environments and displays them using Web technology     

A robust tangent PCA via shape restoration for shape variability analysis

Pattern Analysis and Applications - This paper presents a novel method for handling the effects of shape outliers in statistical shape analysis. Usually performed by a variant of classical...     

A mutation analysis tool for Java programs

Program mutation is a fault-based technique for measuring the effectiveness of test cases that, although powerful, is computationally expensive. The principal expense of mutation is that many faulty versions of the program under test, called mutants, must be created and repeatedly executed. This paper describes a tool, called JavaMut, that implements 26 traditional and object-oriented mutation operators for supporting mutation analysis of Java programs. The current version of that tool is based on syntactic analysis and reflection for implementing mutation operators. JavaMut is interactive; it provides a graphical user interface to make mutation analysis faster and less painful. Thanks to such automated tools, mutation analysis should be achieved within reasonable costs.     

Evaluating shape correspondence for statistical shape analysis: a benchmark study

This paper introduces a new benchmark study to evaluate the performance of landmark-based shape correspondence used for statistical shape analysis. Different from previous shape-correspondence evaluation methods, the proposed benchmark first generates a large set of synthetic shape instances by randomly sampling a given statistical shape model that defines a ground-truth shape space. We then run a test shape-correspondence algorithm on these synthetic shape instances to identify a set of corresponded landmarks. According to the identified corresponded landmarks, we construct a new statistical shape model, which defines a new shape space. We finally compare this new shape space against the ground-truth shape space to determine the performance of the test shape-correspondence algorithm. In this paper, we introduce three new performance measures that are landmark independent to quantify the difference between the ground-truth and the newly derived shape spaces. By introducing a ground-truth shape space that is defined by a statistical shape model and three new landmark-independent performance measures, we believe the proposed benchmark allows for a more objective evaluation of shape correspondence than previous methods. In this paper, we focus on developing the proposed benchmark for $2$D shape correspondence. However it can be easily extended to $3$D cases.     

ShapeSynth: Parameterizing model collections for coupled shape exploration and synthesis

Recent advances in modeling tools enable non‐expert users to synthesize novel shapes by assembling parts extracted from model databases. A major challenge for these tools is to provide users with relevant parts, which is especially difficult for large repositories with significant geometric variations. In this paper we analyze unorganized collections of 3D models to facilitate explorative shape synthesis by providing high‐level feedback of possible synthesizable shapes. By jointly analyzing arrangements and shapes of parts across models, we hierarchically embed the models into low‐dimensional spaces. The user can then use the parameterization to explore the existing models by clicking in different areas or by selecting groups to zoom on specific shape clusters. More importantly, any point in the embedded space can be lifted to an arrangement of parts to provide an abstracted view of possible shape variations. The abstraction can further be realized by appropriately deforming parts from neighboring models to produce synthesized geometry. Our experiments show that users can rapidly generate plausible and diverse shapes using our system, which also performs favorably with respect to previous modeling tools.     

A new software tool for synthesis of linear PID controllers

A new versatile software utility for synthesis of linear PID controllers is described, and the software listing is presented. The software is in the MATLAB environment. Closed-form PID controller gain design equations are developed. The design approach is systematic, and it is based on frequency matching technique with a model matching criteria. The objective is to design a closed-loop feedback system with a PID controller whose dynamic and static behavior would mimic a user-defined reference linear model. The design procedure is automated via a new MATLAB command. The software also has applications in synthesis of nonlinear PID controllers. Because the design equations are of a closed form, the speed of calculations is high; therefore, design software may be used in designing self-tuning adaptive PID controllers.     

IRA-WDS: A GIS-based risk analysis tool for water distribution systems

This paper presents the development of a new software tool IRA-WDS. This GIS-based software predicts the risks associated with contaminated water entering water distribution systems from surrounding foul water bodies such as sewers, drains and ditches. Intermittent water distribution systems are common in developing countries and these systems are prone to contamination when empty. During the non-supply hours contaminants from pollution sources such as sewers, open drains and surface water bodies enter into the water distribution pipes through leaks and cracks. Currently there are no tools available to help engineers identify the risks associated with contaminant intrusion into intermittent water distribution systems. Hence it is anticipated that IRA-WDS will find wide application in developing countries. The paper summarises the details of the mathematical models that form the basis of IRA-WDS. It also describes the software architecture, the main modules, and the integration with GIS using a tight coupling approach. A powerful GUI has been developed that enables data for the models to be retrieved from the spatial databases and the outputs to be converted into tables and thematic maps. This is achieved seamlessly through DLL calling functions within the GIS. This paper demonstrates the application of the software to a real case study in India. The outputs from IRA-WDS are risk maps showing the risk of contaminant intrusion into various parts of the water distribution system. The outputs also give an understanding of the main factors that contribute to the risk.     

A rainfall analysis and forecasting tool

MENSEI-L is a stand-alone software tool for the automatic analysis of pluviometric networks, that also provides three-day rainfall forecasts based on weather types. The software tool, implemented in Python and R, is able to fill missing values in original daily data series and to generate synthetic pluviometers in ungauged locations, by means of kriging techniques. MENSEI-L also characterizes punctual and spatial, average and extreme distributions of precipitation for the complete pluviometric network. Tenerife (Canary Islands, Spain) is used as study site to evaluate the capabilities of MENSEI-L and the implicit rainfall analysis methodology that it implements. MENSEI-L proves to be a useful tool to extract information from dense observation networks where manual analysis is not practical.     

A methodology and tool environment for process analysis and reengineering

Most private and public organizations have recently turned their attention to the process by which they operate, to improve service and product quality and customer satisfaction. To support business process reengineering, methods and tools for process modeling and analysis are required. The paper presents the ARTEMIS methodology and associated tool environment for business process analysis for reengineering. In the ARTEMIS methodological framework, business processes are modeled as workflows and are analyzed according to an organizational structure perspective and an operational structure perspective. With these two perspectives, the analyst can plan reengineering interventions based on the degree of autonomy/dependency of organization units in terms of coupling, and the inter-process semantic correspondences, in terms of data and operation similarity, respectively. The ARTEMIS methodology and associated tool environment have been conceived and applied in the framework of the PROGRESS research project. In the paper, we report on a reengineering case study of this project involving the Italian Ministry of Justice.