Fractal Dimension Analysis to Detect the Progress of Cancer Using Transmission Optical Microscopy

Fractal dimension, a measure of self-similarity in a structure, is a powerful physical parameter for the characterization of structural property of many partially filled disordered materials. Biological tissues are fractal in nature and reports show a change in self-similarity associated with the progress of cancer, resulting in changes in their fractal dimensions. Here, we report that fractal dimension measurement is a potential technique for the detection of different stages of cancer using transmission optical microscopy. Transmission optical microscopy of a thin tissue sample produces intensity distribution patterns proportional to its refractive index pattern, representing its mass density distribution. We measure fractal dimension detection of different cancer stages and find its universal feature. Many deadly cancers are difficult to detect in their early to different stages due to the hard-to-reach location of the organ and/or lack of symptoms until very late stages. To study these deadly cancers, tissue microarray (TMA) samples containing different stages of cancers are analyzed for pancreatic, breast, colon, and prostate cancers. The fractal dimension method correctly differentiates cancer stages in progressive cancer, raising possibilities for a physics-based accurate diagnosis method for cancer detection.

Construction Method of Enterprise-level Database Operational Measurement Platform Based on Bidirectional Coupling Algorithm

When identifying the enterprise database data information, the enterprise database operational dimension measurement platform based on the bilinear method will produce ringing or overshoot effect, the database data monitoring effect is poor as well as the accuracy of operation measurement. To solve this problem, this paper proposes a method to build an enterprise level database operation and maintenance measurement platform based on bidirectional coupling algorithm. Build enterprise database operation measurement platform. The enterprise database monitoring platform is connected with the monitoring database by remote database chain. The Oracle database job scheduling method is used to obtain the monitoring index information in the monitored database, and the database memory performance is comprehensively evaluated by MPI (Memory Perform Index). The platform uses semantic capture layer and related analysis layer to distinguish user behavior, analyze user experience satisfaction, and realize the operation measurement of enterprise level database. The experimental results show that the operational measurement platform built by this method has high throughput, low memory occupancy rate, high measurement accuracy and good user experience.

The analysis of F-actin structure of mesenchymal stem cells by quantification of fractal dimension

The actin cytoskeleton is indispensable for the motility and migration of all types of cells; therefore, it plays a crucial role in the ability of the tissues to repair. Mesenchymal stem cells are intensively used in regenerative medicine, but usually relatively low percent of transplanted cells reaches the injury. To overcome this evident limitation, researchers try to enhance the motility and migration rate of the cells. As one of the approaches, co-cultivation and preconditioning of stem cells with biologically active compounds, which can cause actin cytoskeleton rearrangements followed by an increase of migratory properties of the cells, could be applied. The observed changes in F-actin structure induced by the compounds require quantitative estimation, and measurement of fluorescence intensity of the F-actin image captured by various microscopic techniques is commonly used nowadays. However, this approach could not always accurately detect the observed changes in the shape and structure of actin cytoskeleton. At this time, the image of F-actin has an irregular geometric pattern, and thus could be considered and characterized as a fractal object. To quantify the re-organization of cellular F-actin in terms of fractal geometry Minkovsky’s box-counting method is suitable, but it is not widely used nowadays. We modified and improved the previously described method for fractal dimension measurement, and successfully applied it for the quantification of the F-actin structures of human mesenchymal stem cells.

A Tensor voting Based Surface Anomaly Classification Approach by Using 3D Point Cloud Data

Advanced 3D scanning technology has been widely used in many industries to collect the massive point cloud data of artifacts for part dimension measurement and shape analysis. Though point cloud data also has product surface quality information, it is challenging to conduct effective surface anomaly classification due to the complex data representation, high-dimensionality, and inconsistent size of the 3D point cloud data within each sample. To deal with these challenges, this paper proposes a tensor voting based approach for anomaly classification of artifact surfaces. A case study based on 3D scanned data obtained from a manufacturing plant shows the effectiveness of the proposed method.

The Evaluation of Physical Dimension on the Design of Campus Buildings towards Resilience Initiative at the University of Malaya

Over the last few decades, the concept of resilience has received a great deal of attention in urban contexts. Universities are a hub of learning in the urban system, with diverse stakeholders facing various risks. As a result, to mitigate the adverse effects of any calamity, it is in the university's best interest to embed resilience components. There are still few studies on campus that address the concept of resilience. As a result, the purpose of this descriptive-analytical study is to create a practical framework for examining factors that specifically impact the physical characteristics of campus resilience, with the University of Malaya as a case study. The physical dimension measurement tools are developed through a systematic review of the literature and validated through expert interviews. The AHP method is used to weight 12 indicators to assess U.M. resiliency through four different buildings. According to the findings, each building has a different level of resilience index ranging from 0.30 to 0.80, and building characteristics play a critical role in U.M. resiliency. As a result, the final index reveals that U.M. has a moderate level of resilience.

Automated Dimension Measurement System

In this fast-paced world, it is inevitable that the manual labor employed in industries will be replaced by their automated counterparts. There are a number of existing solutions which deal with object dimensions estimation but only a few of them are suitable for deployment in the industry. The reason being the trade-off between the cost, time for processing, accuracy and system complexity. The proposed system aims to automate the mentioned tasks with the help of a single camera and a line laser module for each conveyor belt setup using laser triangulation method to measure the height and edge detection algorithm for measuring the length and breadth of the object. The minimal use of equipment makes the system simple, power and time efficient. The proposed system has an average error of around 3% in the dimension estimation.

Research on O-ring Dimension Measurement Algorithm Based on Cubic Spline Interpolation

Current O-ring dimension measurement algorithms based on machine vision are mainly whole-pixel level algorithms, which have the disadvantage of a low measurement accuracy. In order to improve the stability and accuracy of O-ring dimension measurement, a sub-pixel edge detection algorithm based on cubic spline interpolation is proposed for O-ring dimension measurement. After image pre-processing of the O-ring graphics, the whole-pixel-level O-ring edges are obtained by using a noise-resistant mathematical morphology method, and then the sub-pixel edge contours are obtained using a sub-pixel edge detection algorithm based on cubic spline interpolation. Finally, the edge curve is fitted with the least squares method to obtain its inner and outer diameter as well as the size of the wire diameter. The experimental data show that the algorithm has a mean square error of 4.8 μm for the outer diameter and 0.18 μm for the wire diameter. The outer diameter error is kept within ± 100 μm and the wire diameter error can be kept within ±15 μm. Compared with the whole pixel algorithm, the measurement accuracy has been greatly improved.