• Particle and aerosol research
• /
• v.11 no.4
• /
• pp.99-105
• /
• 2015

The possible existence forms of particle aggregates in liquid medium are classified into four different types according to their morphological characteristics, including the single particles that are separated from each other, the linear aggregates in which all component particles are located in a line, the planar aggregates where all particles are arranged on a plane, and the volumetric aggregates where all particles forms a three-dimensional space. These particle aggregates with different space morphologies have different fractal dimensions and different influence on the rheological phenomena of the solid-liquid system. The effects of various aggregates on the suspension viscosity are analyzed and related with the particle concentration, and then a mathematical model is presented to determine the fractal dimensions of various aggregates by measuring the apparent viscosity of the solid-liquid system. In the model, the viscous fractal dimension is developed as a new concept, the fractal dimensions of different aggregates can be obtained separately and then the relative components of various aggregates experimentally analyzed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.372-375
• /
• 2003

The incidence of blindness resulting from diabetic retinopathy has significantly increased despite the intervention of insulin to control diabetes mellitus. Early signs are microaneurysms, exudates, intraretinal hemorrhages, cotton wool patches, microvascular abnormalities, and venous beading. Advanced stages include neovascularization, fibrous formations, preretinal and vitreous microhemorrhages, and retinal detachment. Microaneurysm count is important because it is an indicator of retinopathy progression. The purpose of this paper is to apply data mining to detect diabetic retinopathy patterns in routine fundus fluorescein angiography. Early symptoms are of principal interest and therefore the emphasis is on detecting microaneurysms rather than vessel tortuosity. The analysis does not involve image-recognition algorithms. Instead, mathematical filtering isolates microaneurysms, microhemorrhages, and exudates as objects of disconnected sets. A neural network is trained on their distribution to return fractal dimension. Hausdorff and box counting dimensions grade progression of the disease. The field is acquired on fluorescein angiography with resolution superior to color ophthalmoscopy, or on patterns produced by physical or mathematical simulations that model viscous fingering of water with additives percolated through porous media. A mathematical filter and neural network perform the screening process thereby eliminating the time consuming operation of determining fractal set dimension in every case.