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Chia-Ning Yang

Publications and source records attributed to Chia-Ning Yang.

3 recordsLinked to original sources

Solving satisfiability problems using a novel microarray-based DNA computer.

An algorithm based on a modified sticker model accompanied with an advanced MEMS-based microarray technology is demonstrated to solve SAT problem, which has long served as a benchmark in DNA computing. Unlike conventional DNA computing algorithms needing an initial data pool to cover correct and incorrect answers and further executing a series of separation procedures to destroy the unwanted ones, we built solutions in parts to satisfy one clause in one step, and eventually solve the entire Boolean formula through steps. No time-consuming sample preparation procedures and delicate sample applying equipment were required for the computing process. Moreover, experimental results show the bound DNA sequences can sustain the chemical solutions during computing processes such that the proposed method shall be useful in dealing with large-scale problems.

Algorithms↗

A DNA solution of SAT problem by a modified sticker model.

Among various DNA computing algorithms, it is very common to create an initial data pool that covers correct and incorrect answers at first place followed by a series of selection process to destroy the incorrect ones. The surviving DNA sequences are read as the solutions to the problem. However, algorithms based on such a brute force search will be limited to the problem size. That is, as the number of parameters in the studied problem grows, eventually the algorithm becomes impossible owing to the tremendous initial data pool size. In this theoretical work, we modify a well-known sticker model to design an algorithm that does not require an initial data pool for SAT problem. We propose to build solution sequences in parts to satisfy one clause in a step, and eventually solve the whole Boolean formula after a number of steps. Accordingly, the size of data pool grows from one sort of molecule to the number of solution assignments. The proposed algorithm is expected to provide a solution to SAT problem and become practical as the problem size scales up.

Algorithms↗

Corneal astigmatic change after photorefractive keratectomy and photoastigmatic refractive keratectomy.

PURPOSE: To evaluate and compare the efficacy, safety, predictability, and surgically induced astigmatism (SIA) of photorefractive keratectomy (PRK) and photoastigmatic refractive keratectomy (PARK). SETTING: Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan. METHODS: In this retrospective study, 70 eyes were treated for myopia and 70 eyes were treated for myopic astigmatism. Refraction, corneal topography, slitlamp findings, and visual acuity in the 2 groups at 1, 3, and 6 months were evaluated and compared. Vector analysis was performed to determine the SIA in both groups. RESULTS: The mean preoperative spherical equivalent at the glasses plane in the PRK and PARK groups was -6.06 diopters (D) and -7.18 D, respectively. At 6 months, the mean reduction in astigmatism in the PARK group was 61.0%. Predictability was within +/-1.0 D in 85.2% of eyes in the PRK group and 62.5% in the PARK group. An uncorrected visual acuity of 20/40 or better was achieved in 91.8% and 83.9% of eyes, respectively. The mean SIA was 0.64 D in the PRK group, with a general with-the-rule axis shift. The results of vector analysis were more favorable when calculated from refractive values than from Sim-K corneal topography values. The mean astigmatism correction index and index of success calculated from refractive data were 0.75 and 0.38 in the PARK group. The mean magnitude and angle of error were 0.22 +/- 0.52 D and -2.13 +/- 24.41 degrees, respectively. CONCLUSIONS: Photorefractive keratectomy and PARK were effective and safe procedures for the correction of myopia and myopic astigmatism. However, SIA occurred with spherical myopic treatments. This small SIA may be a confounding factor in low astigmatic treatments.

Adult↗