The coverage probability of both the cellular users and the Device-to-Device(D2D) users are analyzed. We assume that the cellular users are able to communication with the Base Station(BS) either by relying on the assistance of Full-Duplex(FD) mode relays or via direct user-to-BS links with high-enough Signal-to-Interference-plus-Noise-Ratio(SINR). Note that the FD-mode devices are capable of simultaneously operating in two modes,i.e. the D2D mode and the cooperative relay mode,with the sum power consumption at these devices kept constant. The closedform expressions for coverage probability of both tier users are derived. After that,numerical analyses are provided,showing that the coverage probability of the both the cellular and the D2D users can be substantially influenced by a variety of parameters,including the power allocation factor of the relays,the density of users,and the self-interference imposed on the FD mode relays,etc. Furthermore,in the D2D enabled networks,it is shown that the FD relay aided transmission is beneficial to enhancing the coverage probability of the cellular users if the target SINR is lower than 5 d B.
Biocompatible NaREF_4(RE=0.4Y+0.4La+0.2(Yb,Er,Tm)(molar ratio)) upconversion nanoparticles(UCNPs) with strong visible fluorescence were synthesized by a solvothermal method and subsequent surface modification. Modulated upconversion luminescence emission spectra were obtained via changing the doping. In vitro and in vivo bioimagings were carried out with shrimps. The upconversion nanoprobes with an acidic/PEG hybrid ligand could quickly capture the basic Rhodamine-B(RB) in shrimp cells and formed a close UCNPs@RB system. The residual organic dye RB in shrimps could be detected on the basis of luminescent resonance energy transfer(LRET). It could be rapidly addressed based on LRET detection that RB residue existed in the shrimps after incubating in the aqueous solution of RB higher than 3 μg/m L for 12 h.
Image enhancement technology plays a very important role to improve image quality in image processing. By enhancing some information and restraining other information selectively, it can improve image visual effect. The objective of this work is to implement the image enhancement to gray scale images using different techniques. After the fundamental methods of image enhancement processing are demonstrated, image enhancement algorithms based on space and frequency domains are systematically investigated and compared. The advantage and defect of the above-mentioned algorithms are analyzed. The algorithms of wavelet based image enhancement are also deduced and generalized. Wavelet transform modulus maxima(WTMM) is a method for detecting the fractal dimension of a signal, it is well used for image enhancement. The image techniques are compared by using the mean(μ),standard deviation(?), mean square error(MSE) and PSNR(peak signal to noise ratio). A group of experimental results demonstrate that the image enhancement algorithm based on wavelet transform is effective for image de-noising and enhancement. Wavelet transform modulus maxima method is one of the best methods for image enhancement.
