arXiv subjects

Bin Shen

Publications and source records attributed to Bin Shen.

58 records · Page 4Linked to original sources

arXiv2013

Edge Couplers with relaxed Alignment Tolerance for Pick-and-Place Hybrid Integration of III-V Lasers with SOI Waveguides

We report on two edge-coupling and power splitting devices for hybrid integration of III-V lasers with sub-micrometric silicon-on-insulator (SOI) waveguides. The proposed devices relax the horizontal alignment tolerances required to achieve high coupling efficiencies and are suitable for passively aligned assembly with pick-and-place tools. Light is coupled to two on-chip single mode SOI waveguides with almost identical power coupling efficiency, but with a varying relative phase accommodating the lateral misalignment between the laser diode and the coupling devices, and is suitable for the implementation of parallel optics transmitters. Experimental characterization with both a lensed fiber and a Fabry-Pérot semiconductor laser diode has been performed. Excess insertion losses (in addition to the 3 dB splitting) taken as the worst case over both waveguides of respectively 2 dB and 3.1 dB, as well as excellent 1 dB horizontal loss misalignment ranges of respectively 2.8 um and 3.8 um (worst case over both in-plane axes) have been measured for the two devices. Back-reflections to the laser are below -20 dB for both devices within the 1 dB misalignment range. Devices were fabricated with 193 nm DUV optical lithography and are compatible with mass-manufacturing with mainstream CMOS technology.

physics.optics↗

arXiv2012

Robust Nonnegative Matrix Factorization via $L_1$ Norm Regularization

Nonnegative Matrix Factorization (NMF) is a widely used technique in many applications such as face recognition, motion segmentation, etc. It approximates the nonnegative data in an original high dimensional space with a linear representation in a low dimensional space by using the product of two nonnegative matrices. In many applications data are often partially corrupted with large additive noise. When the positions of noise are known, some existing variants of NMF can be applied by treating these corrupted entries as missing values. However, the positions are often unknown in many real world applications, which prevents the usage of traditional NMF or other existing variants of NMF. This paper proposes a Robust Nonnegative Matrix Factorization (RobustNMF) algorithm that explicitly models the partial corruption as large additive noise without requiring the information of positions of noise. In practice, large additive noise can be used to model outliers. In particular, the proposed method jointly approximates the clean data matrix with the product of two nonnegative matrices and estimates the positions and values of outliers/noise. An efficient iterative optimization algorithm with a solid theoretical justification has been proposed to learn the desired matrix factorization. Experimental results demonstrate the advantages of the proposed algorithm.

cs.LG↗

arXiv2012

Resource Availability-Aware Advance Reservation for Parallel Jobs with Deadlines

Advance reservation is important to guarantee the quality of services of jobs by allowing exclusive access to resources over a defined time interval on resources. It is a challenge for the scheduler to organize available resources efficiently and to allocate them for parallel AR jobs with deadline constraint appropriately. This paper provides a slot-based data structure to organize available resources of multiprocessor systems in a way that enables efficient search and update operations, and formulates a suite of scheduling policies to allocate resources for dynamically arriving AR requests. The performance of the scheduling algorithms were investigated by simulations with different job sizes and durations, system loads and scheduling flexibilities. Simulation results show that job sizes and durations, system load and the flexibility of scheduling will impact the performance metrics of all the scheduling algorithms, and the PE-Worst-Fit algorithm becomes the best algorithm for the scheduler with the highest acceptance rate of AR requests, and the jobs with the First-Fit algorithm experience the lowest average slowdown. The data structure and scheduling policies can be used to organize and allocate resources for parallel AR jobs with deadline constraint in large-scale computing systems.

cs.DC↗

arXiv2010

A Study of Medium Access Control Protocols for Wireless Body Area Networks

The seamless integration of low-power, miniaturised, invasive/non-invasive lightweight sensor nodes have contributed to the development of a proactive and unobtrusive Wireless Body Area Network (WBAN). A WBAN provides long-term health monitoring of a patient without any constraint on his/her normal dailylife activities. This monitoring requires low-power operation of invasive/non-invasive sensor nodes. In other words, a power-efficient Medium Access Control (MAC) protocol is required to satisfy the stringent WBAN requirements including low-power consumption. In this paper, we first outline the WBAN requirements that are important for the design of a low-power MAC protocol. Then we study low-power MAC protocols proposed/investigated for WBAN with emphasis on their strengths and weaknesses. We also review different power-efficient mechanisms for WBAN. In addition, useful suggestions are given to help the MAC designers to develop a low-power MAC protocol that will satisfy the stringent WBAN requirements.

cs.NI↗