Description: For the requirement of quality-based image coding, an approach to predict the quality of image coding based on differential information entropy is proposed. First of all, some typical prediction approaches are introduced, and then the differential information entropy is reviewed. Taking JPEG2000 as an example, the relationship between differential information entropy and the objective assessment indicator PSNR at a fixed compression ratio is established via data fitting, and the constraint for fitting is to minimize the average error. Next, the relationship among differential information entropy, compression ratio and PSNR at various compression ratios is constructed and this relationship is used as an indicator to predict the image coding quality. Finally, the proposed approach is compared with some traditional approaches. From the experiments, it can be seen that the differential information entropy has a better linear relationship with image coding quality than that with the image activity. Therefore, the conclusion can be reached that the proposed approach is capable of predicting image coding quality at low compression ratios with small errors, and can be widely applied in a variety of real-time space image coding systems for its simplicity.

Description: Sensors, Vol. 18, Pages 1572: Optimal Resource Allocation for NOMA-TDMA Scheme with α-Fairness in Industrial Internet of Things Sensors doi: 10.3390/s18051572 Authors: Yanjing Sun Yiyu Guo Song Li Dapeng Wu Bin Wang In this paper, a joint non-orthogonal multiple access and time division multiple access (NOMA-TDMA) scheme is proposed in Industrial Internet of Things (IIoT), which allowed multiple sensors to transmit in the same time-frequency resource block using NOMA. The user scheduling, time slot allocation, and power control are jointly optimized in order to maximize the system α -fair utility under transmit power constraint and minimum rate constraint. The optimization problem is nonconvex because of the fractional objective function and the nonconvex constraints. To deal with the original problem, we firstly convert the objective function in the optimization problem into a difference of two convex functions (D.C.) form, and then propose a NOMA-TDMA-DC algorithm to exploit the global optimum. Numerical results show that the NOMA-TDMA scheme significantly outperforms the traditional orthogonal multiple access scheme in terms of both spectral efficiency and user fairness.

Description: A novel biosensing platform was developed by integrating an aptamer-based DNA biosensor with graphene oxide (GO) for rapid and facile detection of adenosine triphosphate (ATP, as a model target). The DNA biosensor, which is locked by GO, is designed to contain two sensing modules that include recognition site for ATP and self-replication track that yields the nicking domain for Nt.BbvCI. By taking advantage of the different binding affinity of single-stranded DNA, double-stranded DNA and aptamer-target complex toward GO, the DNA biosensor could be efficiently released from GO in the presence of target with the help of a complementary DNA strand (CPDNA) that partially hybridizes to the DNA biosensor. Then, the polymerization/nicking enzyme synergetic isothermal amplification could be triggered, leading to the synthesis of massive DNA amplicons, thus achieving an enhanced sensitivity with a wide linear dynamic response range of four orders of magnitude and good selectivity. This biosensing strategy expands the applications of GO-DNA nanobiointerfaces in biological sensing, showing great potential in fundamental research and biomedical diagnosis.

Description: FengYun-3B (FY-3B) soil moisture product, retrieved from passive microwave brightness temperature data based on the Qp model, has rarely been applied at the catchment and region scale. One of the reasons for this is its coarse spatial resolution (25-km). The study in this paper presented a new method to obtain a high spatial resolution soil moisture product by downscaling FY-3B soil moisture product from 25-km to 1-km spatial resolution  using the theory of Apparent Thermal Inertia (ATI) under bare surface or sparse vegetation covered land surface. The relationship between soil moisture and ATI was first constructed, and the coefficients were obtained directly from 25-km FY-3B soil moisture product and ATI derived from MODIS data, which is different from previous studies often assuming the same set of coefficients applicable at different spatial resolutions. The method was applied to Naqu area on the Tibetan Plateau to obtain the downscaled 1-km resolution soil moisture product, the latter was validated using ground measurements collected from Soil Moisture/Temperature Monitoring Network on the central Tibetan Plateau (TP-STMNS) in 2012. The downscaled soil moisture showed promising results with a coefficient of determination R2 higher than 0.45 and a root mean-square error (RMSE) less than 0.11 m3/m3 when comparing with the ground measurements at 5 sites out of the 9 selected sites. It was found that the accuracy of downscaled soil moisture was largely influenced by the accuracy of the FY-3B soil moisture product. The proposed method could be applied for both bare soil surface and sparsely vegetated surface.

Description: Wireless Body Sensor Networks (WBSNs) are gaining importance in the era of the Internet of Things (IoT). The modern medical system is a particular area where the WBSN techniques are being increasingly adopted for various fundamental operations. Despite such increasing deployments of WBSNs, issues such as the infancy in the size, capabilities and limited data processing capacities of the sensor devices restrain their adoption in resource-demanding applications. Though providing computing and storage supplements from cloud servers can potentially enrich the capabilities of the WBSNs devices, data security is one of the prevailing issues that affects the reliability of cloud-assisted services. Sensitive applications such as modern medical systems demand assurance of the privacy of the users’ medical records stored in distant cloud servers. Since it is economically impossible to set up private cloud servers for every client, auditing data security managed in the remote servers has necessarily become an integral requirement of WBSNs’ applications relying on public cloud servers. To this end, this paper proposes a novel certificateless public auditing scheme with integrated privacy protection. The multi-user model in our scheme supports groups of users to store and share data, thus exhibiting the potential for WBSNs’ deployments within community environments. Furthermore, our scheme enriches user experiences by offering public verifiability, forward security mechanisms and revocation of illegal group members. Experimental evaluations demonstrate the security effectiveness of our proposed scheme under the Random Oracle Model (ROM) by outperforming existing cloud-assisted WBSN models.