Scanning Near-shore Intertidal Terrain Using Ground LiDAR

Intertidal zone refers to the area under and above the water during high and low tides. Traditionally, this zone is not within the scope of land management authorities. Moreover, in accordance with principals set out by existing plans, intertidal zones are excluded from management zones. Boundaries should therefore be set at the land and sea border. Traditionally, methods in determining this have included the traditional theodolite (total station) method, mapping and aerial photography (photogrammetry). However, existing operational restrictions lower efficiency, in addition to increasing time and operational costs. Therefore this paper explores the practicality of a user- friendly, ground-based high resolution laser scanning technology. This method offers easy operation and high-density characteristics with an instrument platform that can be installed on elevated rooftops. High accuracy and resolution is achieved using a stop-and-go method producing Digital Terrain Model (DTM) data. The range of the completed data is 61km in length, 2.5km in width, and -0.5m depth, with a sampling error of approximately ±2cm. Through the implementation discussed in this research, accurate information about the changes of topography in intertidal areas can be obtained

Anticipating Daily Intention using On-Wrist Motion Triggered Sensing

Anticipating human intention by observing one's actions has many applications. For instance, picking up a cellphone, then a charger (actions) implies that one wants to charge the cellphone (intention). By anticipating the intention, an intelligent system can guide the user to the closest power outlet. We propose an on-wrist motion triggered sensing system for anticipating daily intentions, where the on-wrist sensors help us to persistently observe one's actions. The core of the system is a novel Recurrent Neural Network (RNN) and Policy Network (PN), where the RNN encodes visual and motion observation to anticipate intention, and the PN parsimoniously triggers the process of visual observation to reduce computation requirement. We jointly trained the whole network using policy gradient and cross-entropy loss. To evaluate, we collect the first daily "intention" dataset consisting of 2379 videos with 34 intentions and 164 unique action sequences. Our method achieves 92.68%, 90.85%, 97.56% accuracy on three users while processing only 29% of the visual observation on average

Improvement of LiDAR Data Accuracy Using 12 Parameter Affine Transformation

LiDAR data in a local coordinate system may need to be georeferenced and converted into a geographic or projected system. In coordinate transformation, the 7-parameter Helmet transformation method is usually used in measurements to eliminate the systematic errors made by a laser scanner. However, 7-parameter coordinate transformation assumes that there is only one scale error in all of the systematic errors. This study used 12 parameter affine transformation for coordinate transformation of airborne LiDAR data and terrestrial LiDAR data. The LiDAR data accuracy results upon 6-parameter similarity transformation, 7-parameter similarity transformation, and 12-parameter affine transformation were compared. The results showed that using 12-parameter affine transformation the airborne LiDAR and terrestrial LiDAR data have 2-3 times greater accuracy than do 7-parameter or 6-parameter transformations

Paper-based tuberculosis diagnostic devices with colorimetric gold nanoparticles

A colorimetric sensing strategy employing gold nanoparticles and a paper assay platform has been developed for tuberculosis diagnosis. Unmodified gold nanoparticles and single-stranded detection oligonucleotides are used to achieve rapid diagnosis without complicated and time-consuming thiolated or other surface-modified probe preparation processes. To eliminate the use of sophisticated equipment for data analysis, the color variance for multiple detection results was simultaneously collected and concentrated on cellulose paper with the data readout transmitted for cloud computing via a smartphone. The results show that the 2.6 nM tuberculosis mycobacterium target sequences extracted from patients can easily be detected, and the turnaround time after the human DNA is extracted from clinical samples was approximately 1 h

Osteomyelitis of Multiple Lumbar Vertebrae Associated with Infected Aortic Aneurysm: A Case Report

A 73-year-old male patient presented with a pulsating abdominal mass and intractable low back pain for several days. Magnetic resonance imaging revealed an infected abdominal aortic aneurysm invading the second, third, and fourth lumbar vertebrae. He underwent radical debridement of the infected aneurysm with reconstruction using vascular bypass, partial corpectomy of the L2 to L4 vertebrae, anterior reconstruction with autogenous fibular shaft, and posterior instrumentation with posterolateral fusion. Culture of the necrotic tissues grew oxacillin-resistant Staphylococcus aureus. He received intravenous vancomycin infusion for 4 weeks and oral ciprofloxacin for 6 months postoperatively. After a 15-month follow-up, no apparent signs of further infection were noted. C-reactive protein and erythrocyte sedimentation rate returned to normal during follow-up. No neurologic symptoms other than mild low back soreness were noted. The stability of the lumbar spine was maintained using long segment reconstruction with autogenous fibula shaft and posterior instrumentation along with posterolateral fusion. Infected aortic aneurysm with vertebral osteomyelitis is a rare clinical entity. Prompt diagnosis and adequate treatment are essential