Another example are the optical fiber sensors that exploit the optical fiber transmission characteristics to achieve sensing objectives, such as evanescent wave and surface plasmon resonance technologies [3].Of the various biosensor types, optical fiber biosensors offer the unique characteristic of no electromagnetic interference. Small, lightweight, and with the potential for miniaturization, optic fibers can be used not only to transmit light signals, but also as the primary sensing element. Optical fibers are widely employed for engineering and environmental control and in mechanical and biological developments [4].Optical fibers have a three-layer structure that comprises a silica-based fiber core, a polymer cladding, and a coating of harder polymer as the outermost layer that protects the fiber.

Various methods and structures to provide optical fibers with sensing capabilities have been developed, including fiber Bragg grating [5], fiber-optic interferometers [6], and window-type optical fiber sensors [7]. Among them, window-type optical fiber sensors, as shown in Figure 1, have the simplest structure; only partial removal of the coating material is required to expose the fiber core beneath. Once exposed, the window-type optical fiber structure allows sensors in a test environment to conduct ambient refractive index sensing using the attenuated total reflection (ATR).Figure 1.Schematic of the fiber sensor: (a) crude fiber; and (b) fiber sensors (window type).The current methods for stripping part of the optical fiber material can be broadly divided into mechanical and chemical methods.

The most common of the many mechanical fiber optic stripping methods involve polishing the stripper or fiber [8]. However, the fact that the fiber optic stripper can potentially damage the fiber core presents a significant disadvantage. The fiber polishing method typically requires more expensive equipment, although it does offer high machining accuracy. The chemical method involves the use of various solutions such as sulfuric acid, which was employed by Matthewson [9]. The optical fiber was soaked in sulfuric acid before heating it to between 180 and 200 ��C to soften and strip the outer coating material. Nonetheless, etching quality is also difficult to control because a slight error can generate unexpected processing phenomena that affect the sensing quality.

Researchers have also employed the flame vaporization technique by exploiting the melting point characteristics of various layers of the optical fiber cable. This technique is used to vaporize the outer cladding material, exposing the glass Cilengitide fiber core. Although easy to process, the processing scope and duration of this method is difficult to control, rendering it unsuitable for extended research [10].

Three measurement approaches have been reported in TLS field measurements: single-scan, multi-scan and multi-single-scan. In the single-scan approach, the laser scanner is placed at the center of the plot and one full field-of-view (e.g., 360�� in horizontal direction and 310�� in vertical direction) scan is made. This approach has the simplest measurement setting and fastest measurement speed in the three approaches because only one scan is applied to a plot. The major problem of this approach, however, is the low detection rate. In the sample plot, 10%�C32% of all trees are not scanned from the plot center because of occlusion effects [17,18,20,25].Several scanning positions are necessary to measure all trees in a plot. In the multi-scan approach, several scans are made inside and outside of the plot.

Individual data sets are merged, typically using artificial targets, to form a single point cloud. This approach provides the best data set as the merged point cloud records trees from different directions; however, the approach is not always practical due to the cost of the manual or semi-automated processing required for the registration of several scans. In the multi-single-scan approach, several point clouds are processed individually and data sets are merged at the feature and decision levels. In this approach, the work load is clearly lower than with the multi-scan approach because reference targets are not required and the merging of several scans is fully automated. The detection rate is also clearly higher than that of the single-scan approach because the plot is scanned from several stations.

In practice, convenient measurement methods and rapid data acquisition are always preferred. New possibilities are currently being studied to improve the efficiency Drug_discovery of field data collection. Laser scanning has recently been put on moving platforms to build MLS systems and is being studied for forest mapping applications. The main advantage of applying MLS for forest measurements lies in its rapid data collection. Within an equal time frame, the area that can be investigated by utilizing MLS is significantly larger than the area investigated with TLS.The MLS system consists of one or several laser scanner(s) and multi-sensor positioning and orientation sensors. The first commercial MLS system for surveying applications was StreetMapper, which appeared in the market in 2006.

Similar sensor configurations are also used in robotics. MLS systems utilized in surveying and robotics have different emphases and perspectives. Surveying MLS emphasizes an absolute coordinate system and high measurement accuracy. In robotics, relative positions and accuracy are important. Because of the different applications, real-time processing is necessary for robotics but is only an advantage for surveying MLS.

ZnO has been extensively used for chemical and biological sensing due to its thermal stability under usual operating conditions, as well as excellent biomimetic properties combined with high electron communication features which makes it an attractive actuator for the so-called third generation biosensors [27�C33]. On the other hand, ZNRs have unique advantages in immobilizing enzymes that retain their bioactivity due to the desirable microenvironment and the direct electron transfer between the enzyme’s active sites and the electrode [34�C37], in addition to the relatively larger surface-to-volume ratios compared to their thin film and bulk material counterparts. It is known that the sensing mechanism of ZnO is of the surface controlled type, in which the grain sizes, surface states, and oxygen adsorption quantities all play important roles in its sensitivity [6,31,38�C42].

2.?Experimental2.1. The Fabrication of ZnO NRs on the Gold Coated Glass SubstrateWe have fabricated the sensor electrodes utilizing glass substrates coated with gold then followed by the growth of ZNRs. All processing steps for the preparation of the present sensor electrodes are as follows: the first step was cleaning of the substrate, where the glass substrates were sonicated in an ultrasonic bath for about 10 min in isopropanol and acetone, respectively. Then these substrates were cleaned with deionized water and lastly they were dried with an air gun. Then these glass substrates were affixed into the vacuum chamber of an evaporator instrument (Satis CR 725, Zurich, Switzerland).

After this an adhesive layer of 20 nm of titanium was evaporated on the substrates and then a 100 nm thickness layer of gold thin film was evaporated.Well-aligned ZNRs have been grown by the low temperature ACG method. This could be described as a two-step process: spin-coating a ZnO seed layer on the substrate followed by the growth of the nanorods. In the first step, the ZnO seed precursor was prepared from zinc acetate dihydrate in methanol under basic conditions as described in [43]. The solution was then spin-coated on the substrate in the first step at 1,500 rpm for 10 s and the second step at 3,000 rpm for 20 s. The second step, growth of the ZNRs, involved a hydrothermal process [44] where the substrates coated with ZnO seeds were introduced horizontally and upside-down into a 0.

025 M equimolar solution Brefeldin_A of hexamethylenetetramine and zinc nitrate hexahydrate and then kept in a preheated electric oven at 90 ��C for 4�C6 h. Before the substrates were placed into the solution, a small part of the gold coated glass was covered in order to be used as a contact pad for the electrochemical measurements. Finally, the samples were rinsed several times in deionized water to remove any residual salt on the surface of nanostructures and then they were dried with an air gun.

Sensing, processing and communication capabilities are enabled on each sensor node. WSNs are attractive because they can be deployed in nearly any kind of environment without wired connections. More recently, the availability of inexpensive hardware (such as microphones) that are able to ubiquitously capture multimedia content from the environment has fostered the development of wireless multimedia sensor networks (WMSNs) [1,2]. WMSN is equipped by wirelessly interconnected devices that allow retrieving multimedia data, such as video and audio streams. As sensor nodes usually work in unsupervised area, the battery can not be recharged or replaced. To prolong the lifetime of WMSN, energy efficiency becomes a crucial issue.The target tracking application of WMSN is investigated, where acoustic sensors are adopted to localize the target.

Each sensor node can acquire acoustic signals from the target. In centralized networks, there are usually sink nodes for global processing and control. To enhance the resilience of WMSN against sensor node failures or congestion conditions around the sink node, self-organizing and distributed decision of sensor nodes are useful approaches [3]. Considering the target tracking performance, a distributed architecture of WMSN should be exploited to avoid large communication overheads in the centralized approach. For the sensor nodes, it is assumed that the low-power sleep mode is supported by their operation system, i.e., sensor node can switch between active mode and sleep mode.

As described in [4], the power consumption of sleep mode is usually several orders of magnitude less than that of active mode. Energy saving can be achieved by sending sensor node to sleep as much as possible when there is no sensing, processing or communication task. To enhance the energy efficiency and the detection accuracy of WMSN, the sleep coordination and collaborative localization of sensor nodes can be performed with the prior target motion information derived from target tracking procedure. Carfilzomib Therefore, target position forecasting is necessary during target tracking.As the state model of target motion is nonlinear, so target tracking is usually treated as nonlinear estimation problems [5]. The classical method is extending the standard Kalman filter to nonlinear system by local linearizing all nonlinear models around certain points, which is so called Extended Kalman filter (EKF) [6]. In practical, the target may have high maneuvers. Some algorithms have been proposed for maneuvering target tracking, such as unscented Kalman filter (UKF) [7] and unscented particle filter (UPF) [8]. However, these algorithms are computation-expensive under the constraints of limited processing capability.

The direct observation of very low pressure systems by radar altimeters has not been investigated yet.Altimeters (ERS-2, ENVISAT, TOPEX/Poseidon, Jason-1, GFO) provide global sea surface height (SSH) measurements of the ocean under nearly all weather conditions, with the exception of periods of extremely heavy rain, which sometimes occur in hurricanes. The global SSH error for Jason-1 (J1) is estimated to 3.9 cm in normal meteorological conditions [5]. Radar altimeters thus have some potential for determining storm surge heights when flying over the storms. Now, three satellites (J1, ENVISAT, ERS-2) fly together, thus deeply improving the global temporal and spatial altimeter coverage.

The Inverse Barometer (IB) response has been extensively studied for normal meteorological conditions [6�C10]; but it remains uncertain that there exists a significant Sea Level Pressure/Sea Level Anomaly (SLP/SLA) correlation during storms and hurricanes, which are generally characterized by heavy rains, high sea states and strong winds.Indeed, the ocean response to tropical cyclone surface forcing is a complex interaction between Dacomitinib baroclinic and barotropic motions that re-distribute energy in the ocean during and after these strong forcing events. This response has been characterized as a predominately baroclinic phenomenon associated with the isopycnal displacements in the thermocline and the excitation of near-inertial three dimensional oscillations. A secondary component is the barotropic response associated with the sea surface depression of several tenths of a cm in geostrophic balance with a cyclonically rotating current field [11,12].

The inverse barometer effect is balanced by the surface Ekman divergence in the eye of the storm (pressure+wind induced surge on Figure 1). Most (> 85 %) of the storm surge is caused by winds pushing the ocean surface ahead of the storm on the right side of the track in the Northern hemisphere and left side in the Southern hemisphere [11,12].Figure 1.Localization of the storm surge (http://www.aoml.noaa.gov/phod/cyclone).In general, the strongest winds in a hurricane are found on the right side of the storm (Northern hemisphere) because the motion of the hurricane adds to its swirling winds. Since the surface pressure gradient (from the tropical cyclone centre to the environmental conditions) determines the wind strength, the central pressure indirectly does indicate the height of the storm surges, but not directly.The aim of this paper is to improve the observation of extreme low pressure events with altimetry and to investigate the relationship between atmospheric SLP and the SLA measurements during such extreme conditions.