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Utilizing the photopolymer based volume-holography phase grating, a cubic-phase optical element is fabricated for the generation of 1D and 2D Airy beams. The characteristic properties of the generated Airy beams are experimentally verified and discussed.

This paper proposes a new kind of non-contact optical measurement system, which combines with a polygon mirror and a conical lens to achieve the purpose of simultaneously measuring six-degree-of-freedom (6 DOF) geometric errors for a rotary axis of a machine tool. At the beginning, we used the Zemax software to construct the proposed optical structure and observe the change of light spots on the detectors. Then, we built the proposed optical structure on the Matlab software by using the skew-ray tracing method, which used to present the actual condition of light spot change and compare with the simulation results. Then, we designed the appropriate fixtures to place the system structure on a rotary axis in a laboratory environment. After completing the laboratory-built prototype, we analyzed the effects of different geometric errors on the detectors at different angular positions of a rotary axis of a machine tool. The proposed measurement system simultaneously measured 6 DOF geometric errors of the rotary axis, and the experimental results were compared with those of two dial gauges by using the measurement method of ISO 230–7. The experimental results show that the maximum deviation ranges of the radial motion error in X axis, the radial motion error in Y axis, the tilt motion error around X, and the tilt motion error around Y are ±4.7 µm, ±6.0 µm, ±3.6 arcsec, and ±8.1 arcsec, respectively.

In ophthalmology, aligning images in indocyanine green and fluorescein angiograph sequences is important for the treatment of subretinal lesions. This paper introduces an algorithm that is tailored to align jointly in a common reference space all the images in an angiogram sequence containing both modalities. To overcome the issues of low image contrast and low signal-to-noise ratio for late-phase images, the structural similarity between two images is enhanced using Gabor wavelet transform. Image pairs are pairwise registered and the transformations are simultaneously and globally adjusted for a mutually consistent joint alignment. The joint registration process is incremental and the success depends on the correctness of matches from the pairwise registration. To safeguard the joint process, our system performs the consistency test to exclude incorrect pairwise results automatically to ensure correct matches as more images are jointly aligned. Our dataset consists of 60 sequences of polypoidal choroidal vasculopathy collected by the EVEREST Study Group. On average, each sequence contains 20 images. Our algorithm successfully pairwise registered $95.04\%$ of all image pairs, and joint registered $98.7\%$ of all images, with an average alignment error of 1.58 pixels.

This study compares the effects of three backbone polymers, LDPE, HDPE and LDPE/HDPE, on the dimensions and mechanical properties of 316L stainless steel MIM compact. MIM parts of optimal quality can be produced using properly formulated binders. A spiral flow test is performed firstly to elucidate the flow behaviors of MIM feedstocks. Secondly, the injection molding of tensile bars is tested to examine the dimensional stability and the mechanical strength of sintered parts against variation in the binder formula. Among the three backbone polymers considered herein, HDPE performs best in terms of both the stability of flow and the MIM compact quality; LDPE performs the worst. HDPE has significantly better length, width, density, and hardness by up to 24%, 27%, 30%, and 64%, respectively. In summary, this work has demonstrated that a backbone polymer strongly affects the dimensions and the mechanical properties of the sintered part. The proper selection of a backbone polymer, such as HDPE, is required to increase the dimensional accuracy and quality of 316L sintered parts.

Data mining is traditionally adopted to retrieve and analyze knowledge from large amounts of data. Private or confidential data may be sanitized or suppressed before it is shared or published in public. Privacy preserving data mining (PPDM) has thus become an important issue in recent years. The most general way of PPDM is to sanitize the database to hide the sensitive information. In this paper, a novel hiding-missing-artificial utility (HMAU) algorithm is proposed to hide sensitive itemsets through transaction deletion. The transaction with the maximal ratio of sensitive to nonsensitive one is thus selected to be entirely deleted. Three side effects of hiding failures, missing itemsets, and artificial itemsets are considered to evaluate whether the transactions are required to be deleted for hiding sensitive itemsets. Three weights are also assigned as the importance to three factors, which can be set according to the requirement of users. Experiments are then conducted to show the performance of the proposed algorithm in execution time, number of deleted transactions, and number of side effects.

In this paper, a novel hiding-missing-artificial utility (HMAU) algorithm is proposed to hide sensitive itemsets through transaction deletion. It considers three side effects of hiding failure, missing itemsets, and artificial itemsets for evaluating whether the processed transactions are required to be deleted or not, in sanitization process. Experiments show that the proposed HMAU algorithm has better performance whether in the execution times, the number of deleted transactions, and the number of side effects.

Privacy-preserving data mining (PPDM) has become an important issue to hide the confidential or private data before it is shared or published in recent years. In this paper, a novel algorithm is proposed to hide sensitive itemsets through item deletion. Three side effects of hiding failures, missing itemsets, and artificial itemsets are considered to evaluate whether the transactions or the itemsets are required to be deleted for hiding sensitive itemsets. Experiments are then conducted to show the performance of the proposed algorithm in execution time, number of deleted transactions, and number of side effects.