An Analysis of Background Interference on Fire Debris

AbstractIn this study, the controlled burn experiments of carpets with and without gasoline in this study and commonly encountered substrates produced complex chromatograms producing peaks that were identified by mass spectrometry and comparison with reference standards and each other. The result shown that many of the compounds frequently encountered as a result of either combustion products or pyrolysis products of carpets detected in fresh gasoline as well. These compounds as background interferences that detect weather the gasoline exist in carpet combustion products or not

The Analysis of UV on No Traces Combustion-supporting in Fire Residue

AbstractIn this paper, the ethyl nitrite which ethanol and sodium nitrite's reaction product has the UV absorption peaks in 300nm∼ 400nm to qualitative identification for ethanol. The methanol has the similar absorption peaks in the same range, but these peaks have blue shift or red shift as the steric effects. Quantitative analysis of residual ethanol by the establishment of standard curves and recovery tests and other data analysis. Thus complete the qualitative and quantitative identification of ethanol

Mean Shift-Based Mobile Localization Method in Mixed LOS/NLOS Environments for Wireless Sensor Network

Mobile localization estimation is a significant research topic in the fields of wireless sensor network (WSN), which is of concern greatly in the past decades. Non-line-of-sight (NLOS) propagation seriously decreases the positioning accuracy if it is not considered when the mobile localization algorithm is designed. NLOS propagation has been a serious challenge. This paper presents a novel mobile localization method in order to overcome the effects of NLOS errors by utilizing the mean shift-based Kalman filter. The binary hypothesis is firstly carried out to detect the measurements which contain the NLOS errors. For NLOS propagation condition, mean shift algorithm is utilized to evaluate the means of the NLOS measurements and the data association method is proposed to mitigate the NLOS errors. Simulation results show that the proposed method can provide higher location accuracy in comparison with some traditional methods

Bridging Role Of Absorptive Capacity For Knowledge Management Systems Success

This paper aims to gain a better understanding of KMS success. Based on the absorptive capacity theory, we develop a research model to explain how the use of KMS increases organizational performance by increasing the organizational absorptive capacity and the higher order capabilities. The absorptive capacity plays an important role in transforming KMS usage into agility and innovativeness and the sequent organizational performance. The model is empirically tested with a survey. The results support the mediation effect of absorptive capacity on the use of KMS and the two higher order organizational capabilities, the mediation effects of the two superior organizational capabilities on the relationship between KMS usage and organizational performance and the mediation effect on the link between absorptive capacity and performance