Drone Controller Localization Based on RSSI Ratio.

We proposed two methods for the localization of drone controllers based on received signal strength indicator (RSSI) ratios: the RSSI ratio fingerprint method and the model-based RSSI ratio algorithm. To evaluate the performance of our proposed algorithms, we conducted both simulations and field trials. The simulation results show that our two proposed RSSI-ratio-based localization methods outperformed the distance mapping algorithm proposed in literature when tested in a WLAN channel. Moreover, increasing the number of sensors improved the localization performance. Averaging a number of RSSI ratio samples also improved the performance in propagation channels that did not exhibit location-dependent fading effects. However, in channels with location-dependent fading effects, averaging a number of RSSI ratio samples did not significantly improve the localization performance. Additionally, reducing the grid size improved the performance in channels with small shadowing factor values, but this only resulted in marginal gains in channels with larger shadowing factors. Our field trial results align with the simulation results in a two-ray ground reflection (TRGR) channel. Our methods provide a robust and effective solution for the localization of drone controllers using RSSI ratios.

A land untouched by dentistry - singapore brings dental care to afghanistan.

In 2007, the Singapore Armed Forces deployed a Dental Project Team (DPT) to the capital city of the Bamiyan Province in Afghanistan. The team set up the province's first modern dental facility. Besides providing primary dental care to the 60,000 population there, the Singaporeans also trained and prepared a team of Afghan dentist and dental assistants. The Afghan dental team took over the dental clinic and continued to provide care when it was time for the DPT to depart for home. Braving challenging security and austere living conditions, the DPT completed its mission successfully.

Remembering the Musi - SilkAir Flight MI 185 crash victim identification.

On 19 December 1997, SilkAir Flight MI 185, a Boeing B737-300 airliner crashed into the Musi River near Palembang, Southern Sumatra, enroute from Jakarta, Indonesia to Singapore. All 104 passengers and crew onboard were killed. Of the human remains recovered, 6 positive identifications were made, including that of one Singaporean. Two of the identifications were by dental records, 2 by fingerprints, 1 by age estimation and 1 by personal effects. This paper describes the crash victim identification of Flight MI 185. The authors were part of an Indonesia- Singapore forensic team deployed for 3 weeks in Palembang to assist the Indonesian authorities in human remains identification.

The killing field of Khao Lak: forensic odontology in Thailand tsunami victim identification.

Forensic odontology is the science of dental identification. This paper describes the contribution of forensic odontology to tsunami victim identification in Thailand, with particular reference to the Singaporean victims. Thirteen Singaporeans were reported missing in Phuket following the Indian ocean tsunami on 26 December 2004. To date, 10 victims have been found and identified, eight of whom were identified by dental records. The author travelled twice to southern Thailand and spent 5 weeks there. First, in December 2004 as part of a Singapore Police Force Disaster Victim Identification team deployed in Khao Lak, and later in July 2005 at the Thai Tsunami Victim Identification Information Management Centre in Phuket.