Although massively parallel sequencing approaches have been widely used to study genomic variation, simple alignment of short reads to a reference genome cannot be used to investigate the full range of structural variation and phased diploid architecture, which are important for precision medicine. By contrast, the single-molecule real-time (SMRT) sequencing platform produces long reads that can resolve repetitive structures effectively. We integrated this technology with several other sequencing approaches to construct a high-quality

Flexible and skin-attachable vibration sensors have been studied for use as wearable voice-recognition electronics. However, the development of vibration sensors to recognize the human voice accurately with a flat frequency response, a high sensitivity, and a flexible/conformable form factor has proved a major challenge. Here, we present an ultrathin, conformable, and vibration-responsive electronic skin that detects skin acceleration, which is highly and linearly correlated with voice pressure. This device consists of a crosslinked ultrathin polymer film and a hole-patterned diaphragm structure, and senses voices quantitatively with an outstanding sensitivity of 5.5 V Pa −1 over the voice frequency range. Moreover, this ultrathin device (<5 μm) exhibits superior skin conformity, which enables exact voice recognition because it eliminates vibrational distortion on rough and curved skin surfaces. Our device is suitable for several promising voice-recognition applications, such as security authentication, remote control systems and vocal healthcare.

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Part I of this paper proposed a development process and system platform for the development of autonomous cars based on distributed system architecture. The proposed development methodology enabled the design and development of an autonomous car with benefits such as a reduction of computational complexity, fault-tolerant characteristics, and system modularity. In present paper (Part II), a case study of the proposed development methodology are addressed by showing the implementation process of an autonomous driving system. In order to describe the implementation process intuitively, core autonomous driving algorithms (localization, perception, planning, vehicle control, and system management) are briefly introduced and applied to the implementation of an autonomous driving system. We are able to examine the advantages of a distributed system architecture and the proposed development process by conducting a case study on the autonomous system implementation. The validity of the proposed methodology is proved through the autonomous car, A1 that won the 2012 Autonomous Vehicle Competition in Korea with all missions completed.