ON BOUNDARY VALUE PROBLEMS FOR A CLASS OF SINGULAR INTEGRAL EQUATIONS

Joint Research on Environmental Science and Technology for the Eart

AN EFFECTIVE REVERSIBLE DATA HIDING METHOD BASED ON PIXEL-VALUE-ORDERING

This paper presents a new effective reversible data hiding method based on pixel-value-ordering (iGePVO-K) which is improvement of a recent GePVO-K method that recently is considered as a PVO-used method having highest embedding capacity. In comparison with GePVO-K method, iGePVO-K has the following advantages. First, the embedding capacity of the new method is higher than that of GePVO-K method by using data embedding formulas reasonably and reducing the location map size. Second, for embedding data, in the new method, each pixel value is modified at most by one, while in GePVO-K method, each pixel value may be modified by two. In fact, in the GePVO-K method, the largest pixels are modified by two for embedding bits 1 and by one for bits 0. This is also true for the smallest pixels. Meanwhile, in the proposed method, the largest pixels are modified by one for embedding bits 1 and are unchanged if embedding bits 0. Therefore, the stego-image quality in proposed method is better than that in GePVO-K method. Theoretical analysis and experiment results show that the proposed method has higher embedding capacity and better stego image quality than GePVO-K method

Methods for Online UAV Path Planning for Tracking Multiple Objects

Unmanned aerial vehicles (UAVs) or drones have rapidly evolved to enable carrying various sensors such as thermal sensors for vision or antennas for radio waves. Therefore, drones can be transformative for applications such as surveillance and monitoring because they have the capability to greatly reduce the time and cost associated with traditional tasking methods. Realising this potential necessitates equipping UAVs with the ability to perform missions autonomously. This dissertation considers the problems of online path planning for UAVs for the fundamental task of surveillance comprising of tracking and discovering multiple mobile objects in a scene. Tracking and discovering an unknown and time-varying number of objects is a challenging problem in itself. Objects such as people or wildlife tend to switch between various modes of movements. Measurements received by the UAV’s on-board sensors are often very noisy. In practice, the on-board sensors have a limited field of view (FoV), hence, the UAV needs to move within range of the mobile objects that are scattered throughout a scene. This is extremely challenging because neither the exact number nor locations of the objects of interest are available to the UAV. Planning the path for UAVs to effectively detect and track multi-objects in such environments poses additional challenges. Path planning techniques for tracking a single object are not applicable. Since there are multiple moving objects appearing and disappearing in the region, following only certain objects to localise them accurately implies that a UAV is likely to miss many other objects. Furthermore, online path planning for multi-UAVs remains challenging due to the exponential complexity of multi-agent coordination problems. In this dissertation, we consider the problem of online path planning for UAV-based localisation and tracking of multi-objects. First, we realised a low cost on-board radio receiver system on aUAV and demonstrated the capability of the drone-based platform for autonomously tracking and locating multiple mobile radio-tagged objects in field trials. Second, we devised a track-before-detect filter coupled with an online path planning algorithm for joint detection and tracking of radio-tagged objects to achieve better performance in noisy environments. Third, we developed a multi-objective planning algorithm for multi-agents to track and search multi-objects under the practical constraint of detection range limited on-board sensors (or FoV limited sensors). Our formulation leads to a multi-objective value function that is a monotone submodular set function. Consequently, it allows us to employ a greedy algorithm for effectively controlling multi-agents with a performance guarantee for tracking discovered objects while searching for undiscovered mobile objects under practical constraints of limited FoV sensors. Fourth, we devised a fast distributed tracking algorithm that can effectively track multi-objects for a network of stationary agents with different FoVs. This is the first such solution to this problem. The proposed method can significantly improve capabilities of a network of agents to track a large number of objects moving in and out of the limited FoV of the agents’ sensors compared to existing methods that do not consider the problem of unknown and limited FoV of sensors.Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 202

Vibrational Study of the Hydrogen Adsorption on the Missing Row Platinum (110) Surface

The hydrogen vibration was investigated to analyze its affect on the hydrogen adsorption on the missing row platinum surface (H/Pt(110)-(1$\times$2) model) in the ultrahigh vacuum (UHV). The density functional theory (DFT) combined with the approximation oscillation of the hydrogen atom on the surface was used. When the hydrogen coverage ΘH on the surface is 100% ($\Theta$ = 1 ML), and taking into account the vibrational effect, the bond formed at the edge of the first layer (short bridge) is the most stable site. The vibrational effect on the adsorption model H/Pt(110)-(1$\times$2) is significant

Nucleotide variation at the methionine synthase locus in an endangered tree species, Fokienia hodginsii (Cupressaceae) in Vietnam

Nucleotide variation at the methionine synthase (MetE) locus within and among populations of an endangered forest tree Fokienia hodginsii in Vietnam was investigated in the present study. A total of 12 populations were sampled across Vietnam. The length of the sequenced locus varied from 1567 to 1559 bp. A total of 42 polymorphic sites were detected among samples. Overall, nucleotide diversity was estimated to be 0.00499 and 0.00692 at the total (ðtot) and silent sites (ðsilent) in the pool, respectively. Nucleotide diversity within populations varied from 0.00300 to 0.00521 at the total and 0.00357 to 0.00666 at silent sites. The estimates of nucleotide diversity were lower in the 4 populations located in central and southern Vietnam (0.00300 to 0.00380) in comparison with the northern populations (ranging from 0.00399 to 0.00543). Overall estimates of genetic differentiation among 12 populations were low (FST = 0.093 and KST* = 0.078), even though both values were highly significant (P < 0.001). Pairwise analysis among 12 populations showed significant genetic differentiation as evaluated by FST and Snn but not significant as evaluated by KST*. Analysis of genetic clustering using BAPS provided the best support for all 144 sequences belonging to the same genetic cluster. The implication of the results revealed in this study in the genetic conservation of F. hodginsii was discussed.Key words: Population genetics, conservation, forest, methionine synthase (MetE), structure