Generalization Error in Deep Learning

Deep learning models have lately shown great performance in various fields such as computer vision, speech recognition, speech translation, and natural language processing. However, alongside their state-of-the-art performance, it is still generally unclear what is the source of their generalization ability. Thus, an important question is what makes deep neural networks able to generalize well from the training set to new data. In this article, we provide an overview of the existing theory and bounds for the characterization of the generalization error of deep neural networks, combining both classical and more recent theoretical and empirical results

Graphene electrode modified with electrochemically reduced graphene oxide for label-free DNA detection.

A novel printed graphene electrode modified with electrochemically reduced graphene oxide was developed for the detection of a specific oligonucleotide sequence. The graphene oxide was immobilized onto the surface of a graphene electrode via π-π bonds and electrochemical reduction of graphene oxide was achieved by cyclic voltammetry. A much higher redox current was observed from the reduced graphene oxide-graphene double-layer electrode, a 42% and 36.7% increase, respectively, in comparison with that of a bare printed graphene or reduced graphene oxide electrode. The good electron transfer activity is attributed to a combination of the large number of electroactive sites in reduced graphene oxide and the high conductivity nature of graphene. The probe ssDNA was further immobilized onto the surface of the reduced graphene oxide-graphene double-layer electrode via π-π bonds and then hybridized with its target cDNA. The change of peak current due to the hybridized dsDNA could be used for quantitative sensing of DNA concentration. It has been demonstrated that a linear range from 10(-7)M to 10(-12)M is achievable for the detection of human immunodeficiency virus 1 gene with a detection limit of 1.58 × 10(-13)M as determined by three times standard deviation of zero DNA concentration

Sampling curves with finite rate of innovation

In this paper, we extend the theory of sampling signals with finite rate of innovation (FRI) to a specific class of two-dimensional curves, which are defined implicitly as the zeros of a mask function. Here the mask function has a parametric representation as a weighted summation of a finite number of complex exponentials, and therefore, has finite rate of innovation . An associated edge image, which is discontinuous on the predefined parametric curve, is proved to satisfy a set of linear annihilation equations. We show that it is possible to reconstruct the parameters of the curve (i.e., to detect the exact edge positions in the continuous domain) based on the annihilation equations. Robust reconstruction algorithms are also developed to cope with scenarios with model mismatch. Moreover, the annihilation equations that characterize the curve are linear constraints that can be easily exploited in optimization problems for further image processing (e.g., image up-sampling). We demonstrate one potential application of the annihilation algorithm with examples in edge-preserving interpolation. Experimental results with both synthetic curves as well as edges of natural images clearly show the effectiveness of the annihilation constraint in preserving sharp edges, and improving SNRs

Phytoestrogens

Collectively, plants contain several different families of natural products among which are compounds with weak estrogenic or antiestrogenic activity toward mammals. These compounds, termed phytoestrogens, include certain isoflavonoids, flavonoids, stilbenes, and lignans. The best-studied dietary phytoestrogens are the soy isoflavones and the flaxseed lignans. Their perceived health beneficial properties extend beyond hormone-dependent breast and prostate cancers and osteoporosis to include cognitive function, cardiovascular disease, immunity and inflammation, and reproduction and fertility. In the future, metabolic engineering of plants could generate novel and exquisitely controlled dietary sources with which to better assess the potential health beneficial effects of phytoestrogens

Caching and UAV Friendly Jamming for Secure Communications With Active Eavesdropping Attacks

Natural Science Foundation of Sichuan under Grant 2022NSFSC0887; Fundamental Research Funds for the Central Universities under Grant 2682021ZTPY117 and 2682022CX020; ARC under Grant DP190100770; ARC Laureate Fellowship under Grant FL160100032; ARC under Grant DP190101988 and DP210103410

Joint Optimization for Cooperative Computing Framework in Double-IRS-Aided MEC Systems

Natural Science Foundation of Sichuan Province under Grant 2022NSFSC0887; Fundamental Research Funds for the Central Universities under Grant 2682021ZTPY117 and 2682022CX020; National Natural Science Foundation of China under Grant 62201137; National Natural Science Foundation of China under Grant 62271419; Australian Research Council Laureate Fellowship grant number FL160100032; Australian Research Council Grant DP190101988 and DP210103410