Background Electrochemical sensors are devices that use electrical signals to detect the presence or concentration of a target analyte. These sensors are widely used in a range of applications including glucose sensors, environmental monitoring, food safety testing, medical diagnostics, and industrial process control. However, the manufacturing process...

In normal differentiated cells, most of the genome is densely methylated, except CpG islands near promoters of actively transcribed genes. Maintaining this boundary between unmethylated promoter-associated and adjacent methylated regions is crucial as loss of segregation can lead to disease. Unfortunately, it is not clear where these boundaries are,...

Background Solid oxide fuel cells (SOFCs) have drawn attention in recent years as an alternative power generation technology, due to their high efficiency and low emissions. The lanthanum strontium manganite (LSM)-yttria-stabilized zirconia (YSZ) cathode is widely utilized in SOFCs because of its high performance and stability. The microstructure of...

The success of conventional supervised learning relies on large-scale labeled datasets to achieve high accuracy. However, annotating millions of data samples is labor-intensive and time-consuming. This promotes self-supervised learning as an attractive solution with artificial labels being used instead of human-annotated ones for training. Contrastive...

Deep neural networks (DNNs) have shown extraordinary performance in recent years for various applications, including image classification, object detection, speech recognition, etc. Accuracy-driven DNN architectures tend to increase model sizes and computations in a very fast pace, demanding a massive amount of hardware resources. Frequent communication...

­Advanced vehicle control systems (e.g., an electronic stability control system) can greatly reduce accident rates and fatality in accidents. Vehicle control systems in automated vehicles (AVs) are able to ensure vehicle safety in many driving scenarios by cooperating with other advanced perception and path planning systems of the AVs. A typical...

Background Industrial and agricultural unmanned aerial vehicles (UAVs) have been widely used for long-distance flight applications such as aerial photography, mapping, package transportation, inspection, and pesticide spraying. Typically, coplanar multirotor UAVs, such as quadcopters and hexacopters are applied to perform these tasks because of their...

Nowadays, one practical limitation of deep neural networks (DNNs) is their high degree of specialization to a single task. This motivates researchers to develop algorithms that can adapt the DNN model to multiple tasks sequentially, while still performing well on past tasks. This process of gradually adapting the DNN model to learn from different...

­One practical limitation of deep neural network (DNN) is its high degree of specialization to a single task or domain (e.g., one visual domain). This motivates the development of algorithms that can adapt DNN model to multiple domains sequentially while still performing well on past domains. This is known as multi-domain learning. Conventional...

­Recently, Deep Neural Networks (DNNs) have been deployed in many safety-critical applications. The security of DNN models can be compromised by adversarial input examples, where the adversary maliciously crafts and adds input noise to fool a DNN model. The perturbation of model parameters (e.g., weight) is another security concern, one that relates...