Even under controlled, in vitro conditions, individual cells of the same type in the same environment are highly heterogeneous in their molecular responses. While the genome is nearly constant across an organism, the proteome and interactome vary from cell to cell and time to time. The aggregation of signals from multiple cells, which current assays require, washes out this heterogeneity and masks
Smartphone indoor positioning technology is a boost to the rapidly growing mobile location-based services (LBS) industry. As the latest initiative, the In-Location Alliance, formed by 22 member companies, including Nokia, Qualcomm, Broadcom, etc.[1], was recently launched to drive innovation and market adoption of high-accuracy indoor positioning and related services.
The continued development of accurate and reliable LBS will not only improve the experience of smartphone users, but will also create new marketing opportunities. Emerging indoor LBS include social networking, people finders, marketing campaigns, asset tracking, etc. Because most indoor LBS are used by pedestrians, in this work we focus the development of our proposed indoor positioning solution on a pedestrian scenario.Multiple sensors and signals of opportunity have been used for indoor positioning and navigation [2,3]. Examples of such sensors include accelerometers, gyroscopes, compasses, cameras, proximity sensors, and electromyography sensors [4].
In this work, signals of opportunity are defined as signals that were not originally intended for positioning and navigation, and they include radio frequency (RF) signals, e.
g., cellular networks, wireless local area networks (WLAN) and Bluetooth [5], and naturally occurring signals, such as Earth��s magnetic field and polarized light from the sun [6]. Each method has its own respective drawback. For example, cellular positioning systems offer limited accuracy. Inertial sensors only provide a relative location estimate with accuracy degrading over time, and they must be used together with other technologies, e.g., Global Positioning System (GPS), to estimate absolute Anacetrapib location [7,8].Due to the cost effectiveness and extensive availability of the existing network infrastructure, WLAN signals Cilengitide have been widely used for indoor positioning [9�C11].
Traditional solutions usually have utilized a special-purpose hardware unit to observe the WLAN received signal strength indication (RSSI) signals for indoor positioning. RSSI observables are location dependent, and they are commonly used to estimate indoor locations through a fingerprinting approach.This study develops a smartphone indoor positioning solution using the built-in hardware and computational resources of smartphones.