USING TOTAL DOUBLE-BOND VALUE OF AN EDIBLE OIL TO PREDICT ITS EFFECT ON PLASMA LIPIDS

The objective of this study was to investigate the accuracy of using the total double-bond value (TDV) of edible oil to predict its effect on the plasma lipid level of rats. The test oils used included fish oil, squid visceral oil (high long chain n-3 PUFA, corn oil, soybean oil (high n-6 PUFA), olive oil, lard (high MUFA) and hydrogenated beef tallow (high SFA, S). Test diets contained 15% of each test oil with the cholesterol level made up to 1%. The results demonstrated that the sum of the percents of each MUFA and PUFA in an oil, multiplied by the number of double bonds in each compound (TDV), may be a better indicator to predict the effects of the oils on plasma lipid metabolism. There was a negative correlation between TDV and plasma total lipids and cholesterol levels, but the lard group was slightly lower than expected. Using TDV as an indicator for plasma lipid metabolism may not be perfect, but is much better than the P/S or P+M/S ratio.     

A KNOWLEDGE-BASED NAVIGATION SCHEME FOR AUTONOMOUS LAND VEHICLES

A knowledge-based navigation system for autonomous land vehicles (ALVs) has been developed which can successfully negotiate an obstacle and threat-laden terrain, even if nothing is known beforehand about the terrain. The ALV stores new information in its memory as it travels, has the ability to backtrack out of unexpected dead ends, and performs spontaneous decision making in the field based on local sensor readings. The optimal global route of the ALV journey is obtained using dynamic programming, and decision making is accomplished via a production rule-based system. Execution examples demonstrate the power of the prototype system to solve navigation problems. This establishes the feasibility of constructing a valid ALV by combining search techniques with artificial intelligence tools such as production rule-based systems.     

Alignment with sub‐pixel accuracy for images of multi‐modality microscopes using automatic calibration

A biological specimen is often imaged with various imaging modalities, and it is crucial that such images are well aligned to best reveal physiological structures and functions of the specimen for in‐depth analyses. In this paper, we present a methodology for automatic calibration of multiple optical imaging modalities within the x–y detector plane using a custom chrome‐on‐glass target and an automatic and accurate registration algorithm. The target contains lines crossing at random angles, and our method of registration is based on the alignment of salient features extracted from the lines within the individual images. Once spatial relationships are found between the various detectors and applied to the resultant images, no further registration is required for all static samples, and the registered images serve as the starting point for registration of dynamic samples, where the remaining misalignment is caused by sample movement. We have validated our algorithm with 40 inter‐modal and 30 intra‐modal image pairs, and the success rates are 95 and 100%, respectively, with sub‐pixel accuracy. This methodology is widely applicable to any multi‐modal microscope that combines a number of imaging modalities on a common platform assuming images of the target can be obtained.     

Improvement of extraction efficiency for GaN-based light emitting diodes

A simple, low cost method for mass production to enhance the light extraction efficiency of GaN-related LEDs was proposed. With appropriate process parameters, the nature lithography of nanosphere can be used to fabricate two-dimensional nanostructures, including the nanomesh ZnO layer, photonic crystal (PhC) patterned p-GaN, and patterned sapphire substrates. Based on preliminary results, the extraction efficiencies of LEDs with these nanostructures can thus be improved and the nature lithography is demons...     

Detecting and locating burrs of industrial parts

Burrs (excess material) are usually squeezed out around the periphery of the mould, and are irregular and vary considerably between parts. This paper aims at the development of a machine vision system for automatic detection of burrs and peripheral defects of casting parts. This non-contact detection result can be applied to automatic deburring systems and used for automatic inspection of peripheral breakdown.

This research concentrates on flat casting parts comprising piecewise smooth curves on the boundaries. The detection procedure is based on the fact that the irregular burrs show high curvature changes in a small segment of the boundary, whereas a smooth segment without burrs presents a succession of low curvature points. Given a casting part with burrs, we arbitrarily select a few boundary points from the smooth segments and connect these points to form a polygon. The matching process then finds a corresponding polygon from the model part. The transformation parameters of rotational angle and translation between the part in the image and the model part are evaluated from these two equivalent polygons. The proposed matching algorithm is computationally fast and the time complexity is bounded by O(m), where m is the number of points on the digital boundary of the model part.     

EFFECTS OF LIQUID VISCOSITY ON RHEOLOGY OF CONCENTRATED SUSPENSIONS

ABSTRACT

This paper presents the experimental results on the effects of liquid viscosity on the rheology of concentrated suspensions of solid particles in Newtonian liquids. Specifically, the relative viscosity of a pseudoplastic suspension decreases as the viscosity of the suspending liquid increases, indicating excess energy dissipation in a less viscous liquid. In contrast, the relative viscosity of a Newtonian suspension is only slightly affected by the liquid viscosity. It is in excellent agreement with the value predicted from the rigid sphere model which neglects nonhydrodynamic interactions, and assumes zero particle-to-liquid relative velocity. The flow behavior indices of both concentrated suspensions are independent of the liquid viscosity.     

Rapid Service-Oriented Business Process Generation Method Based on Ontology

Service-oriented business process generation is a key activity in the Service- Oriented Architecture （SOA） business lifecy- cle, and most of the other activities such as application execution depend on the business process being developed, After the business requirements are acquired, a developer has to use specific programming technologies to or- chestrate web services to generate a deploy- able business process. It is time-consuming to specify all the business processes from low- level web services, especially for an enterprise that focuses on a series of similar businesses. This paper proposes a rapid service-oriented business process generation method with do- main-specific assets specified in ontology sy- stems. Assets with different levels ,of granu- larity are reused to refine the high level bus- iness process framework for executable busin- ess processes using the Business Process Exe- cutional Language （BPEL）. The new method- ology significantly simplifies service-oriented business process generation by reusing assets to construct business processes. A business pro- cess generation tool is also implemented to support the efficient visual design of SOA pro- cesses with the proposed method. This paper verifies the proposed method using a shipment tracking case. The studies show that the num- ber of reusable assets increases significantly as these projects progress, and the business pro- cess generation speed also increases at the same time.     

以不同大气环流模型评估气候变迁对高屏溪流域河川流量

由于气候变迁对于世界各地所造成之影响不一，且不同大气模型模拟所得结果不尽相同，故此类研究存在一定的不确定性。本研究将台湾大学全球变迁中心针对国际政府间气候变迁观察小组(IPCC)公告之大气环流模型(GCM)模拟结果的统计降尺资料，经水文模拟，分析气候变迁对此区域水资源可能造成的冲击及不同模型所得结果之变异。比较不同大气环流模型(包括CGCM2、CCCSR/NIES、ECHAM4、GFDL-R30、HadCM3等模型)所得的情景模拟降雨径流结果，虽然以不同大气环流模型资料模拟后，所得到之流量变化不尽相同，但仍可明显看出在气候变迁影响下，高屏溪流域流量变化趋势大致为，未来丰水期流量上升，而枯水期流量呈现小幅减少趋势。且各模型之变异范围随未来时间愈长其可能变异愈大。枯水期各模型之变异约在-26%~+15%，而丰水期之变异约在-10%~+82%。其中A2情景下枯水期各模型之变异约在-26%~+13%，而丰水期之变异约在-10%~+66%。而B2情景下枯水期各模型之变异约在-18%~+15%，而丰水期之变异约在-3%~+82%。此结果可供相关研究或决策单位参考，以期使气候变迁对水资源之冲击的评估能更佳周详。