An entropy-based approach to automatic image segmentation of satellite images

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.

Automatic contour extraction from 2D neuron images

This work describes a novel methodology for automatic contour extraction from 2D images of 3D neurons (e.g. camera lucida images and other types of 2D microscopy). Most contour-based shape analysis methods cannot be used to characterize such cells because of overlaps between neuronal processes. The proposed framework is specifically aimed at the problem of contour following even in presence of multiple overlaps. First, the input image is preprocessed in order to obtain an 8-connected skeleton with one-pixel-wide branches, as well as a set of critical regions (i.e., bifurcations and crossings). Next, for each subtree, the tracking stage iteratively labels all valid pixel of branches, tip to a critical region, where it determines the suitable direction to proceed. Finally, the labeled skeleton segments are followed in order to yield the parametric contour of the neuronal shape under analysis. The reported system was successfully tested with respect to several images and the results from a set of three neuron images are presented here, each pertaining to a different class, i.e. alpha, delta and epsilon ganglion cells, containing a total of 34 crossings. The algorithms successfully got across all these overlaps. The method has also been found to exhibit robustness even for images with close parallel segments. The proposed method is robust and may be implemented in an efficient manner. The introduction of this approach should pave the way for more systematic application of contour-based shape analysis methods in neuronal morphology. (C) 2008 Elsevier B.V. All rights reserved.

An algorithm for automatic checking of exercises in a dynamic geometry system: iGeom

One of the key issues in e-learning environments is the possibility of creating and evaluating exercises. However, the lack of tools supporting the authoring and automatic checking of exercises for specifics topics (e.g., geometry) drastically reduces advantages in the use of e-learning environments on a larger scale, as usually happens in Brazil. This paper describes an algorithm, and a tool based on it, designed for the authoring and automatic checking of geometry exercises. The algorithm dynamically compares the distances between the geometric objects of the student`s solution and the template`s solution, provided by the author of the exercise. Each solution is a geometric construction which is considered a function receiving geometric objects (input) and returning other geometric objects (output). Thus, for a given problem, if we know one function (construction) that solves the problem, we can compare it to any other function to check whether they are equivalent or not. Two functions are equivalent if, and only if, they have the same output when the same input is applied. If the student`s solution is equivalent to the template`s solution, then we consider the student`s solution as a correct solution. Our software utility provides both authoring and checking tools to work directly on the Internet, together with learning management systems. These tools are implemented using the dynamic geometry software, iGeom, which has been used in a geometry course since 2004 and has a successful track record in the classroom. Empowered with these new features, iGeom simplifies teachers` tasks, solves non-trivial problems in student solutions and helps to increase student motivation by providing feedback in real time. (c) 2008 Elsevier Ltd. All rights reserved.

Automatic camera control in virtual environments augmented using multiple sparse videos

Automated virtual camera control has been widely used in animation and interactive virtual environments. We have developed a multiple sparse camera based free view video system prototype that allows users to control the position and orientation of a virtual camera, enabling the observation of a real scene in three dimensions (3D) from any desired viewpoint. Automatic camera control can be activated to follow selected objects by the user. Our method combines a simple geometric model of the scene composed of planes (virtual environment), augmented with visual information from the cameras and pre-computed tracking information of moving targets to generate novel perspective corrected 3D views of the virtual camera and moving objects. To achieve real-time rendering performance, view-dependent textured mapped billboards are used to render the moving objects at their correct locations and foreground masks are used to remove the moving objects from the projected video streams. The current prototype runs on a PC with a common graphics card and can generate virtual 2D views from three cameras of resolution 768 x 576 with several moving objects at about 11 fps. (C)2011 Elsevier Ltd. All rights reserved.

New Improvements in Automatic Structure Elucidation Using the LSD (Logic for Structure Determination) and the SISTEMAT Expert Systems

This article describes the integration of the LSD (Logic for Structure Determination) and SISTEMAT expert systems that were both designed for the computer-assisted structure elucidation of small organic molecules. A first step has been achieved towards the linking of the SISTEMAT database with the LSD structure generator. The skeletal descriptions found by the SISTEMAT programs are now easily transferred to LSD as substructural constraints. Examples of the synergy between these expert systems are given for recently reported natural products.

Application of solid sampling device for direct determination of chromium and nickel in lubricating oils by graphite furnace atomic absorption spectrometry

One method using a solid sampling device for the direct determination of Cr and Ni in fresh and used lubricating oils by graphite furnace atomic absorption spectrometry are proposed. The high organic content in the samples was minimized using a digestion step at 400 degrees C in combination with an oxidant mixture 1.0% (v v(-1)) HNO3+15% (v v(-1)) H2O2+0.1% (m v(-1)) Triton X-100 for the in situ digestion. The 3-field mode Zeeman-effect allowed the spectrometer calibration up to 5 ng of Cr and Ni. The quantification limits were 0.86 mu g g(-1) for Cr and 0.82 mg g(-1) for Ni, respectively. The analysis of reference materials showed no statistically significant difference between the recommended values and those obtained by the proposed methods.

Analytical Assessment of a Home Made Capillary Electrophoresis Equipment with Linear Charge Coupled Device for Visible Light Absorption Detection in the Determination of Food Dyes

The performance of modular home made capillary electrophoresis equipment with spectrophotometric detection, at a visible region by means of a miniaturized linear charge coupled device, was evaluated for the determination of four food dyes. This system presents a simple but efficient home made cell detection scheme. A computer program that converts the spectral data after each run into the electropherograms was developed to evaluate the analytical parameters. The dyes selected for analytical evaluation of the system were Brilliant Blue FCF, Fast Green FCF, Sunset Yellow FCF, and Amaranth. Separation was carried out in a 29cm length and 75 mu m I.D fused silica capillary, using 10mmolL-1 borate buffer at pH 9, with separation voltage of 7.5kV. The detection limits for the dyes were between 0.3 and 1.5mgL-1 and the method presented adequate linearity over the ranges studied, with correlation coefficients greater than 0.99. The method was applied for determination and quantification of these dyes in fruit juices and candies.

Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

Nonstationary feature extraction techniques for automatic classification of impact acoustic signals

Condition monitoring of wooden railway sleepers applications are generallycarried out by visual inspection and if necessary some impact acoustic examination iscarried out intuitively by skilled personnel. In this work, a pattern recognition solutionhas been proposed to automate the process for the achievement of robust results. Thestudy presents a comparison of several pattern recognition techniques together withvarious nonstationary feature extraction techniques for classification of impactacoustic emissions. Pattern classifiers such as multilayer perceptron, learning cectorquantization and gaussian mixture models, are combined with nonstationary featureextraction techniques such as Short Time Fourier Transform, Continuous WaveletTransform, Discrete Wavelet Transform and Wigner-Ville Distribution. Due to thepresence of several different feature extraction and classification technqies, datafusion has been investigated. Data fusion in the current case has mainly beeninvestigated on two levels, feature level and classifier level respectively. Fusion at thefeature level demonstrated best results with an overall accuracy of 82% whencompared to the human operator.

Implementation and role of device management Solutions to the end users

This research is based on consumer complaints with respect to recently purchased consumer electronics. This research document will investigate the instances of development and device management as a tool used to aid consumer and manage consumer’s mobile products in order to resolve issues in or before the consumers is aware one exists. The problem at the present time is that mobile devices are becoming very advanced pieces of technology, and not all manufacturers and network providers have kept up the support element of End users. As such, the subject of the research is to investigate how device management could possibly be used as a method to promote research and development of mobile devices, and provide a better experience for the consumer. The wireless world is becoming increasingly complex as revenue opportunities are driven by new and innovative data services. We can no longer expect the customer to have the knowledge or ability to configure their own device. Device Management platforms can address the challenges of device configuration and support through new enabling technologies. Leveraging these technologies will allow a network operator to reduce the cost of subscriber ownership, drive increased ARPU (Average Revenue per User) by removing barriers to adoption, reduce churn by improving the customer experience and increase customer loyalty. DM technologies provide a flexible and powerful management method but are managing the same device features that have historically been configured manually through call centers or by the end user making changes directly on the device. For this reason DM technologies must be treated as part of a wider support solution. The traditional requirement for discovery, fault finding, troubleshooting and diagnosis are still as relevant with DM as they are in the current human support environment yet the current generation of solutions do little to address this problem. In the deployment of an effective Device Management solution the network operator must consider the integration of the DM platform, interfacing with many areas of the business, supported by knowledge of the relationship between devices, applications, solutions and services maintained on an ongoing basis. Complementing the DM solution with published device information, setup guides, training material and web based tools will ensure the quality of the customer experience, ensuring that problems are completely resolved, driving data usage by focusing customer education on the use of the wireless service In this way device management becomes a tool used both internally within the network or device vendor and by the customer themselves, with each user empowered to effectively manage the device without any prior knowledge or experience, confident that changes they apply will be relevant, accurate, stable and compatible. The value offered by an effective DM solution with an expert knowledge service will become a significant differentiator for the network operator in an ever competitive wireless market. This research document is intended to highlight some of the issues the industry faces as device management technologies become more prevalent, and offers some potential solutions to simplify the increasingly complex task of managing devices on the network, where device management can be used as a tool to aid customer relations and manage customer’s mobile products in order to resolve issues before the user is aware one exists. The research is broken down into the following, Customer Relationship Management, Device management, the role of knowledge with the DM, Companies that have successfully implemented device management, and the future of device management and CRM. And it also consists of questionnaires aimed at technical support agents and mobile device users. Interview was carried out with CRM managers within support centre to further the evidence gathered. To conclude, the document is to consider the advantages and disadvantages of device management and attempt to determine the influence it will have over customer support centre, and what methods could be used to implement it.

Determination of Thermal and Blue Light Photochemical Hazard Protection needed by Automatic Welding filters

Recent developments in biological research, has shown that the initial maximum permissible exposure (MPE) limits for protection of workers from risks associated with artificial optical radiations were more stringent than needed. Using the most recent MPE limits for artificial optical radiation this piece of work was focused on the investigation of the level of visible light attenuation needed by automatic welding filters in case of switching failure. Results from the comparison of different exposure standards were employed in investigating the need of Vis/IR and blue light transmittance requirement for automatic welding filters. Real and arbitrary spectra were taken into consideration for the worst and best case scenarios of artificial optical radiations. An excel worksheet developed during the execution of this project took into consideration the exposure from different light sources and the precision of the spectrometer used in measuring the transmittances of a welding filter. The worksheet was developed and tested with known product properties to investigate the validity of its formulation. The conclusion drawn from this project was that attenuation in the light state will be needed for products with the darkest state shade 11 or higher. Also shown is that current welding filter protects the eye well enough even in the case of switching failure.

A web application for follow-up of results from a mobile device test battery for parkinson’s disease patients

Background: A test battery consisting of self-assessments and motor tests (tapping and spiral drawing) was developed for a hand computer with touch screen in a telemedicine setting. Objectives: To develop and evaluate a web-based system that delivers decision support information to the treating clinical staff for assessing PD symptoms in their patients based on the test battery data. Methods: The test battery is currently being used in a clinical trial (DAPHNE, EudraCT No. 2005-002654-21) by sixty five patients with advanced Parkinson’s disease (PD) on 9991 test occasions (four tests per day during in all 362 week-long test periods) at nine clinics around Sweden. Test results are sent continuously from the hand unit over a mobile net to a central computer and processed with statistical methods. They are summarized into scores for different dimensions of the symptom state and an ‘overall test score’ reflecting the overall condition of the patient during a test period. The information in the web application is organized and presented graphically in a way that the general overview of the patient performance per test period is emphasized. Focus is on the overall test score, symptom dimensions and daily summaries. In a recent preliminary user evaluation, the web application was demonstrated to the fifteen study nurses who had used the test battery in the clinical trial. At least one patient per clinic was shown. Results: In general, the responses from nurses were positive. They claimed that the test results shown in the system were consistent with their own clinical observations. They could follow complications, changes and trends within their patients. Discussion: In conclusion, the system is able to summarise the various time series of motor test results and self-assessments during test periods and present them in a useful manner. Its main contribution is a novel and reliable way to capture and easily access symptom information from patients’ home environment. The convenient access to current symptom profile as well as symptom history provides a basis for individualized evaluation and adjustment of treatments.

Mobile systems for monitoring Parkinson's disease

A challenge for the clinical management of Parkinson's disease (PD) is the large within- and between-patient variability in symptom profiles as well as the emergence of motor complications which represent a significant source of disability in patients. This thesis deals with the development and evaluation of methods and systems for supporting the management of PD by using repeated measures, consisting of subjective assessments of symptoms and objective assessments of motor function through fine motor tests (spirography and tapping), collected by means of a telemetry touch screen device. One aim of the thesis was to develop methods for objective quantification and analysis of the severity of motor impairments being represented in spiral drawings and tapping results. This was accomplished by first quantifying the digitized movement data with time series analysis and then using them in data-driven modelling for automating the process of assessment of symptom severity. The objective measures were then analysed with respect to subjective assessments of motor conditions. Another aim was to develop a method for providing comparable information content as clinical rating scales by combining subjective and objective measures into composite scores, using time series analysis and data-driven methods. The scores represent six symptom dimensions and an overall test score for reflecting the global health condition of the patient. In addition, the thesis presents the development of a web-based system for providing a visual representation of symptoms over time allowing clinicians to remotely monitor the symptom profiles of their patients. The quality of the methods was assessed by reporting different metrics of validity, reliability and sensitivity to treatment interventions and natural PD progression over time. Results from two studies demonstrated that the methods developed for the fine motor tests had good metrics indicating that they are appropriate to quantitatively and objectively assess the severity of motor impairments of PD patients. The fine motor tests captured different symptoms; spiral drawing impairment and tapping accuracy related to dyskinesias (involuntary movements) whereas tapping speed related to bradykinesia (slowness of movements). A longitudinal data analysis indicated that the six symptom dimensions and the overall test score contained important elements of information of the clinical scales and can be used to measure effects of PD treatment interventions and disease progression. A usability evaluation of the web-based system showed that the information presented in the system was comparable to qualitative clinical observations and the system was recognized as a tool that will assist in the management of patients.

Automatic and objective assessment of alternating tapping performance in Parkinson’s disease

This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions (‘speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’) and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson’s Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping.