Multimode Waveguides on an SOI Platform for Arbitrary Power Splitting Ratio Couplers

Optical power couplers with arbitrary power splitting ratios are important components for many applications such as Mach-Zehnder interferometer-based structures, filters, switches, dispersion compensations, optical interconnects, and microring resonators. In this chapter, we present a new approach to achieve a very high compact coupler with arbitrary power splitting ratios on silicon on insulator (SOI) waveguides. The proposed device requires only one 4×4 multimode interference (MMI) coupler. We use a passive wide SOI waveguide to achieve the phase shifter. The footprint of the whole device is only about 6×150 μm2. A large fabrication tolerance of ±50 nm can be achieved. The modified effective index method, beam propagation method, finite difference method, and finite difference-time difference method are used to optimally design the whole device

High FSR and Critical Coupling Control of Microring Resonator Based on Graphene-Silicon Multimode Waveguides

We present a new approach for designing a compact microring resonator structure based on only one multimode waveguide, which can provide a very high free spectral range (FSR) and capability of controlling the critical coupling. The silicon on insulator (SOI) waveguide and graphene-silicon waveguide (GSW) are used for the proposed structure. By changing the applied voltage on the graphene sheet, we can achieve a full control of the critical coupling. Some important properties of the proposed microring resonator such as free spectral range and quality factor are analyzed. We show that our structure can provide all characteristics of a single microring resonator with universal applications such as optical switching, modulating, filtering and signal processing, etc

CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference

We propose a novel statistical method for testing the results of anomaly detection (AD) under domain adaptation (DA), which we call CAD-DA -- controllable AD under DA. The distinct advantage of the CAD-DA lies in its ability to control the probability of misidentifying anomalies under a pre-specified level $\alpha$ (e.g., 0.05). The challenge within this DA setting is the necessity to account for the influence of DA to ensure the validity of the inference results. Our solution to this challenge leverages the concept of conditional Selective Inference to handle the impact of DA. To our knowledge, this is the first work capable of conducting a valid statistical inference within the context of DA. We evaluate the performance of the CAD-DA method on both synthetic and real-world datasets

An efficient approach to measure the difficulty degree of practical programming exercises based on student performances

oai:ojs.www.rev-jec.org:article/282This study examines the generality of easy to hard practice questions in programming subjects. One of the most important contributions is to propose four new formulas for determining the difficulty degree of questions. These formulas aim to describe different aspects of difficulty degree from the learner's perspective instead of the instructor's subjective opinions. Then, we used clustering technique to group the questions into three easy, medium and difficult degrees. The results will be the baseline to consider the generality of the exercise sets according to each topic. The proposed solution is then tested on the data set that includes the results of the two subjects: Programming Fundamentals, Data Structures and Algorithms from Ho Chi Minh City University of Technology. The most important result is to suggest the instructors complete various degrees according to each topic for better evaluating student's performance