Capacity Building for Hazmat Transport Emergency Preparedness: 'Hotspot Impact Zone' Mapping from Flammable and Toxic Releases

Hazardous Material transportation by road is coupled with inherent risk of accidents causing loss of lives, grievous injuries, property losses and environmental damages. The most common type of hazmat road accident happens to be the releases (78%) of hazardous substances, followed by fires (28%), explosions (14%) and vapour/ gas clouds (6 %.). The paper is discussing initially the probable 'Impact Zones' likely to be caused by one flammable (LPG) and one toxic (ethylene oxide) chemicals being transported through a sizable segment of a State Highway connecting three notified Industrial zones in Surat district in Western India housing 26 MAH industrial units. Three 'hotspots' were identified along the highway segment depending on the particular chemical traffic and the population distribution within 500 meters on either sides. The thermal radiation and explosion overpressure have been calculated for LPG / Ethylene Oxide BLEVE scenarios along with toxic release scenario for ethylene oxide. Besides, the dispersion calculations for ethylene oxide toxic release have been made for each 'hotspot' location and the impact zones have been mapped for the LOC concentrations. Subsequently, the maximum Initial Isolation and the protective zones were calculated based on ERPG-3 and ERPG-2 values of ethylene oxide respectively which are estimated taking the worst case scenario under worst weather conditions. The data analysis will be helpful to the local administration in capacity building with respect to rescue / evacuation and medical preparedness and quantitative inputs to augment the District Offsite Emergency Plan document.

Automated Thickness Measurement of Retinal Blood Vessels for Implementation of Clinical Decision Support Systems in Diagnostic Diabetic Retinopathy

The structure of retinal vessels is a prominent feature, that reveals information on the state of disease that are reflected in the form of measurable abnormalities in thickness and colour. Vascular structures of retina, for implementation of clinical diabetic retinopathy decision making system is presented in this paper. Retinal Vascular structure is with thin blood vessel, whose accuracy is highly dependent upon the vessel segmentation. In this paper the blood vessel thickness is automatically detected using preprocessing techniques and vessel segmentation algorithm. First the capture image is binarized to get the blood vessel structure clearly, then it is skeletonised to get the overall structure of all the terminal and branching nodes of the blood vessels. By identifying the terminal node and the branching points automatically, the main and branching blood vessel thickness is estimated. Results are presented and compared with those provided by clinical classification on 50 vessels collected from Bejan Singh Eye hospital..

A New Ridge Orientation based Method of Computation for Feature Extraction from Fingerprint Images

An important step in studying the statistics of fingerprint minutia features is to reliably extract minutia features from the fingerprint images. A new reliable method of computation for minutiae feature extraction from fingerprint images is presented. A fingerprint image is treated as a textured image. An orientation flow field of the ridges is computed for the fingerprint image. To accurately locate ridges, a new ridge orientation based computation method is proposed. After ridge segmentation a new method of computation is proposed for smoothing the ridges. The ridge skeleton image is obtained and then smoothed using morphological operators to detect the features. A post processing stage eliminates a large number of false features from the detected set of minutiae features. The detected features are observed to be reliable and accurate.

Entrepreneurship Game: Digital 'Catur Bistari'

The role of entrepreneurs in generating the economy is very important. Thus, nurturing entrepreneurship skills among society is very crucial and should start from the early age. One of the methods is to teach through game such as board game. Game provides a fun and interactive platform for players to learn and play. Besides that as today-s world is moving towards Islamic approach in terms of finance, banking and entertainment but Islamic based game is still hard to find in the market especially games on entrepreneurship. Therefore, there is a gap in this segment that can be filled by learning entrepreneurship through game. The objective of this paper is to develop an entrepreneurship digital-based game entitled “Catur Bistari" that is based on Islamic business approach. Knowledge and skill of entrepreneurship and Islamic business approach will be learned through the tasks that are incorporated inside the game.

Automatic Segmentation of Dermoscopy Images Using Histogram Thresholding on Optimal Color Channels

Automatic segmentation of skin lesions is the first step towards development of a computer-aided diagnosis of melanoma. Although numerous segmentation methods have been developed, few studies have focused on determining the most discriminative and effective color space for melanoma application. This paper proposes a novel automatic segmentation algorithm using color space analysis and clustering-based histogram thresholding, which is able to determine the optimal color channel for segmentation of skin lesions. To demonstrate the validity of the algorithm, it is tested on a set of 30 high resolution dermoscopy images and a comprehensive evaluation of the results is provided, where borders manually drawn by four dermatologists, are compared to automated borders detected by the proposed algorithm. The evaluation is carried out by applying three previously used metrics of accuracy, sensitivity, and specificity and a new metric of similarity. Through ROC analysis and ranking the metrics, it is shown that the best results are obtained with the X and XoYoR color channels which results in an accuracy of approximately 97%. The proposed method is also compared with two state-ofthe- art skin lesion segmentation methods, which demonstrates the effectiveness and superiority of the proposed segmentation method.

Human Verification in a Video Surveillance System Using Statistical Features

A human verification system is presented in this paper. The system consists of several steps: background subtraction, thresholding, line connection, region growing, morphlogy, star skelatonization, feature extraction, feature matching, and decision making. The proposed system combines an advantage of star skeletonization and simple statistic features. A correlation matching and probability voting have been used for verification, followed by a logical operation in a decision making stage. The proposed system uses small number of features and the system reliability is convincing.

A Sub-Pixel Image Registration Technique with Applications to Defect Detection

This paper presents a useful sub-pixel image registration method using line segments and a sub-pixel edge detector. In this approach, straight line segments are first extracted from gray images at the pixel level before applying the sub-pixel edge detector. Next, all sub-pixel line edges are mapped onto the orientation-distance parameter space to solve for line correspondence between images. Finally, the registration parameters with sub-pixel accuracy are analytically solved via two linear least-square problems. The present approach can be applied to various fields where fast registration with sub-pixel accuracy is required. To illustrate, the present approach is applied to the inspection of printed circuits on a flat panel. Numerical example shows that the present approach is effective and accurate when target images contain a sufficient number of line segments, which is true in many industrial problems.

A Nonoblivious Image Watermarking System Based on Singular Value Decomposition and Texture Segmentation

In this paper, a robust digital image watermarking scheme for copyright protection applications using the singular value decomposition (SVD) is proposed. In this scheme, an entropy masking model has been applied on the host image for the texture segmentation. Moreover, the local luminance and textures of the host image are considered for watermark embedding procedure to increase the robustness of the watermarking scheme. In contrast to all existing SVD-based watermarking systems that have been designed to embed visual watermarks, our system uses a pseudo-random sequence as a watermark. We have tested the performance of our method using a wide variety of image processing attacks on different test images. A comparison is made between the results of our proposed algorithm with those of a wavelet-based method to demonstrate the superior performance of our algorithm.

Key Frames Extraction for Sign Language Video Analysis and Recognition

In this paper we proposed a method for finding video frames representing one sign in the finger alphabet. The method is based on determining hands location, segmentation and the use of standard video quality evaluation metrics. Metric calculation is performed only in regions of interest. Sliding mechanism for finding local extrema and adaptive threshold based on local averaging is used for key frames selection. The success rate is evaluated by recall, precision and F1 measure. The method effectiveness is compared with metrics applied to all frames. Proposed method is fast, effective and relatively easy to realize by simple input video preprocessing and subsequent use of tools designed for video quality measuring.

Hot-Spot Blob Merging for Real-Time Image Segmentation

One of the major, difficult tasks in automated video surveillance is the segmentation of relevant objects in the scene. Current implementations often yield inconsistent results on average from frame to frame when trying to differentiate partly occluding objects. This paper presents an efficient block-based segmentation algorithm which is capable of separating partly occluding objects and detecting shadows. It has been proven to perform in real time with a maximum duration of 47.48 ms per frame (for 8x8 blocks on a 720x576 image) with a true positive rate of 89.2%. The flexible structure of the algorithm enables adaptations and improvements with little effort. Most of the parameters correspond to relative differences between quantities extracted from the image and should therefore not depend on scene and lighting conditions. Thus presenting a performance oriented segmentation algorithm which is applicable in all critical real time scenarios.

Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) Parameters for Propane, Ethylene, and Hydrogen under Supercritical Conditions

Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EOS) is a modified SAFT EOS with three pure component specific parameters: segment number (m), diameter (σ) and energy (ε). These PC-SAFT parameters need to be determined for each component under the conditions of interest by fitting experimental data, such as vapor pressure, density or heat capacity. PC-SAFT parameters for propane, ethylene and hydrogen in supercritical region were successfully estimated by fitting experimental density data available in literature. The regressed PCSAFT parameters were compared with the literature values by means of estimating pure component density and calculating average absolute deviation between the estimated and experimental density values. PC-SAFT parameters available in literature especially for ethylene and hydrogen estimated density in supercritical region reasonably well. However, the regressed PC-SAFT parameters performed better in supercritical region than the PC-SAFT parameters from literature.

En-Face Optical Coherence Tomography and Fluorescence in Evaluation of Orthodontic Interfaces

Bonding has become a routine procedure in several dental specialties – from prosthodontics to conservative dentistry and even orthodontics. In many of these fields it is important to be able to investigate the bonded interfaces to assess their quality. All currently employed investigative methods are invasive, meaning that samples are destroyed in the testing procedure and cannot be used again. We have investigated the interface between human enamel and bonded ceramic brackets non-invasively, introducing a combination of new investigative methods – optical coherence tomography (OCT), fluorescence OCT and confocal microscopy (CM). Brackets were conventionally bonded on conditioned buccal surfaces of teeth. The bonding was assessed using these methods. Three dimensional reconstructions of the detected material defects were developed using manual and semi-automatic segmentation. The results clearly prove that OCT, fluorescence OCT and CM are useful in orthodontic bonding investigations.

Accurate Dimensional Measurement of 3D Round Holes Based on Stereo Vision

This paper present an effective method to accurately reconstruct and measure the 3D curve edges of small industrial parts based on stereo vision. To effectively fit the curve of the measured parts using a series of line segments in the images, a strategy from coarse to fine is employed based on multi-scale curve fitting. After reconstructing the 3D curve of a hole through a curved surface, its axis is adjusted so that it is parallel to the Z axis with least squares error and the dimensions of the hole can be calculated on the XY plane easily. Experimental results show that the presented method can accurately measure the dimensions of round holes through a curved surface.

A Study on the Attractiveness of Heavy Duty Motorcycle

The culture of riding heavy motorcycles originates from advanced countries and mainly comes from Europe, North America, and Japan. Heavy duty motorcycle riders are different from people who view motorcycles as a convenient mean of transportation. They regard riding them as a kind of enjoyment and high-level taste. The activities of riding heavy duty motorcycles have formes a distinctive landscape in domestic land in Taiwan. Previous studies which explored motorcycle culture in Taiwan still focused on the objects of motorcycle engine displacement under 50 cc.. The study aims to study the heavy duty motorcycles of engine displacement over 550 cc. and explores where their attractiveness is. For finding the attractiveness of heavy duty motorcycle, the study chooses Miryoku Engineering (Preference-Based Design) approach. Two steps are adopted to proceed the research. First, through arranging the letters obtained from interviewing experts, EGM (The Evaluation Grid Method) was applied to find out the structure of attractiveness. The attractive styles are eye-dazzling, leisure, classic, and racing competitive styles. Secondarily, Quantification Theory Type I analysis was adopted as a tool for analyzing the importance of attractiveness. The relationship between style and attractive parts was also discussed. The results could contribute to the design and research development of heavy duty motorcycle industry in Taiwan.

A 3D Approach for Extraction of the Coronaryartery and Quantification of the Stenosis

Segmentation and quantification of stenosis is an important task in assessing coronary artery disease. One of the main challenges is measuring the real diameter of curved vessels. Moreover, uncertainty in segmentation of different tissues in the narrow vessel is an important issue that affects accuracy. This paper proposes an algorithm to extract coronary arteries and measure the degree of stenosis. Markovian fuzzy clustering method is applied to model uncertainty arises from partial volume effect problem. The algorithm employs: segmentation, centreline extraction, estimation of orthogonal plane to centreline, measurement of the degree of stenosis. To evaluate the accuracy and reproducibility, the approach has been applied to a vascular phantom and the results are compared with real diameter. The results of 10 patient datasets have been visually judged by a qualified radiologist. The results reveal the superiority of the proposed method compared to the Conventional thresholding Method (CTM) on both datasets.

Real-time Performance Study of EPA Periodic Data Transmission

EPA (Ethernet for Plant Automation) resolves the nondeterministic problem of standard Ethernet and accomplishes real-time communication by means of micro-segment topology and deterministic scheduling mechanism. This paper studies the real-time performance of EPA periodic data transmission from theoretical and experimental perspective. By analyzing information transmission characteristics and EPA deterministic scheduling mechanism, 5 indicators including delivery time, time synchronization accuracy, data-sending time offset accuracy, utilization percentage of configured timeslice and non-RTE bandwidth that can be used to specify the real-time performance of EPA periodic data transmission are presented and investigated. On this basis, the test principles and test methods of the indicators are respectively studied and some formulas for real-time performance of EPA system are derived. Furthermore, an experiment platform is developed to test the indicators of EPA periodic data transmission in a micro-segment. According to the analysis and the experiment, the methods to improve the real-time performance of EPA periodic data transmission including optimizing network structure, studying self-adaptive adjustment method of timeslice and providing data-sending time offset accuracy for configuration are proposed.

A New Method for Detection of Artificial Objects and Materials from Long Distance Environmental Images

The article presents a new method for detection of artificial objects and materials from images of the environmental (non-urban) terrain. Our approach uses the hue and saturation (or Cb and Cr) components of the image as the input to the segmentation module that uses the mean shift method. The clusters obtained as the output of this stage have been processed by the decision-making module in order to find the regions of the image with the significant possibility of representing human. Although this method will detect various non-natural objects, it is primarily intended and optimized for detection of humans; i.e. for search and rescue purposes in non-urban terrain where, in normal circumstances, non-natural objects shouldn-t be present. Real world images are used for the evaluation of the method.

Modeling and Simulating Human Arm Movement Using a 2 Dimensional 3 Segments Coupled Pendulum System

A two dimensional three segments coupled pendulum system that mathematically models human arm configuration was developed along with constructing and solving the equations of motions for this model using the energy (work) based approach of Lagrange. The equations of motion of the model were solved iteratively both as an initial value problem and as a two point boundary value problem. In the initial value problem solutions, both the initial system configuration (segment angles) and initial system velocity (segment angular velocities) were used as inputs, whereas, in the two point boundary value problem solutions initial and final configurations and time were used as inputs to solve for the trajectory of motion. The results suggest that the model solutions are sensitive to small changes in the dynamic forces applied to the system as well as to the initial and boundary conditions used. To overcome the system sensitivity a new approach is suggested.

Delay-Dependent Stability Analysis for Neutral Type Neural Networks with Uncertain Parameters and Time-Varying Delay

In this paper, delay-dependent stability analysis for neutral type neural networks with uncertain paramters and time-varying delay is studied. By constructing new Lyapunov-Krasovskii functional and dividing the delay interval into multiple segments, a novel sufficient condition is established to guarantee the globally asymptotically stability of the considered system. Finally, a numerical example is provided to illustrate the usefulness of the proposed main results.

A Real-Time Tracking System Developed for an Interactive Stage Performance

A real-time tracking system was built to track performers on an interactive stage. Using an ordinary, up to date, desktop workstation, the performers- silhouette was segmented from the background and parameterized by calculating the normalized central image moments. In the stage system, the silhouette moments were then sent to a parallel workstation, which used them to generate corresponding 3D virtual geometry and projected the generated graphic back onto the stage.