Cylindrical Lenses Based Spectral Domain Low-Coherence Interferometry for On-line Surface Inspection

This paper presents a spectral domain low-coherence interferometry (SD-LCI) method that is effective for applications in on-line surface inspection because it can obtain a surface profile in a single shot. It has an advantage over existing spectral interferometry techniques because it uses cylindrical lenses as the objective lens in a Michelson interferometric configuration to enable the measurement of long profiles. The adjustable profile length in our experimental setup, determined by the NA of the illuminating system and the aperture of cylindrical lenses, is up to 10 mm. To simulate real-time surface inspection, large-scale 3D surface measurement was carried out by translating the tested sample during the measurement procedure. Two step height surfaces were measured and the captured interferograms were analysed using a fast Fourier transform algorithm. Both 2D profile results and 3D surface maps closely align with the calibrated specifications given by the manufacturer

Landscape as framework : downtown revival through rebuilding spatial identity

In developing revitalization strategies for depopulating, shrinking districts, the economic and psychological disciplines remain the key focus. In contrast, landscape architecture has long been underestimated as a guiding framework in city revitalization. This thesis book presents how landscape architecture could function as a framework to revive a city through spatial comfort and spatial identity. Using downtown Fall River as an example, this book speculates how landscape transforms a city physically and mentally. By rebuilding Fall River’s spatial comfort and spatial identity, landscape architecture could drive social engagement, revitalize local economy, recall lost history, and ultimately, allow the city to revive and flourish

White Light Channeled Spectrum Interferometry for the On-line Surface Inspection

In the industries making high volume as well as large area foil products and flexible electronics, the deposition and patterning of multi-layer thin films on large area substrates is often involved in the manufacturing processes. For these types of product, the films must be uniform and largely perfect across most of the area of the foil. To achieve a high product yield, the key challenge is to inspect the foil surface at production speed as well as have the sufficient resolution to detect the defects resulting from the coating and patterning processes. After the effective inspection, further process like local repair technique can be applied to remove the defects. We present a white light channeled spectrum interferometry (WLCSI) method that is effective for applications in on-line surface inspection because it can obtain a surface profile in a single shot. It has an advantage over existing spectral interferometry techniques by using cylindrical lenses as the objective lens in a Michelson interferometric configuration to enable the measurement of long profiles. The adjustable profile length in our experimental setup, determined by the NA of the illuminating system and the aperture of cylindrical lenses, is up to 10 mm. By translating the tested sample during the measurement procedure, fast and large-scale on-line surface inspection can be achieved. The performance of the WLCSI was evaluated experimentally by measuring step heights. The measuring results closely align with the calibrated specifications given by the manufacturer as well as the measurement results by the other commercial instrument, which demonstrate that the proposed WLCSI could be applied to production line like the R2R surface inspection, where only defects on the film surface are concerned in terms of the quality control

In-Situ Surface Inspection Using White Light Channelled Spectrum Interferometer

We introduce a new environmentally robust optical interferometry system for fast surface profile measurement. The proposed white light channelled spectrum Interferometer (WLCSI) is effective for applications in on-line surface inspection because it can obtain a surface profile in a single shot. Compared to the traditional spectral interferometry techniques, cylindrical lens is used in the Michelson interferometric objective of our system to achieve the measurement of long profiles. Combined with a modern high speed CCD camera, general-purpose graphics processing unit (GPGPU) and multi-core processors computing technology, large dynamic measurement with a high signal-to-noise ratio is realized. The designed prototype of WLCSI is presented and its performance was evaluated experimentally by measuring two surface samples. The measuring results closely align with the calibrated specifications given by the manufacturer as well as the measurement results by the other commercial instrument, which shows that the proposed WLCSI could be applied to production line like the roll-to-toll (R2R) surface inspection where only defects on the film surface are concerned in terms of the quality contro

Whole-Chain Recommendations

With the recent prevalence of Reinforcement Learning (RL), there have been tremendous interests in developing RL-based recommender systems. In practical recommendation sessions, users will sequentially access multiple scenarios, such as the entrance pages and the item detail pages, and each scenario has its specific characteristics. However, the majority of existing RL-based recommender systems focus on optimizing one strategy for all scenarios or separately optimizing each strategy, which could lead to sub-optimal overall performance. In this paper, we study the recommendation problem with multiple (consecutive) scenarios, i.e., whole-chain recommendations. We propose a multi-agent RL-based approach (DeepChain), which can capture the sequential correlation among different scenarios and jointly optimize multiple recommendation strategies. To be specific, all recommender agents (RAs) share the same memory of users' historical behaviors, and they work collaboratively to maximize the overall reward of a session. Note that optimizing multiple recommendation strategies jointly faces two challenges in the existing model-free RL model - (i) it requires huge amounts of user behavior data, and (ii) the distribution of reward (users' feedback) are extremely unbalanced. In this paper, we introduce model-based RL techniques to reduce the training data requirement and execute more accurate strategy updates. The experimental results based on a real e-commerce platform demonstrate the effectiveness of the proposed framework.Comment: 29th ACM International Conference on Information and Knowledge Managemen