Data-Driven Clustering Analysis for Representative Electric Vehicle Charging Profile in South Korea.

As the penetration of electric vehicles (EVs) increases, an understanding of EV operation characteristics becomes crucial in various aspects, e.g., grid stability and battery degradation.

Calibrating Low-Cost Smart Insole Sensors with Recurrent Neural Networks for Accurate Prediction of Center of Pressure.

This paper proposes a scheme for predicting ground reaction force (GRF) and center of pressure (CoP) using low-cost FSR sensors. GRF and CoP data are commonly collected from smart insoles to analyze the wearer's gait and diagnose balance issues. This approach can be utilized to improve a user's rehabilitation process and enable customized treatment plans for patients with specific diseases, making it a useful technology in many fields.

Two-Stage Model-Based Predicting PV Generation with the Conjugation of IoT Sensor Data.

This paper proposes a novel short-term photovoltaic voltage (PV) prediction scheme using IoT sensor data with the two-stage neural network model. It is efficient to use environmental data provided by the meteorological agency to predict future PV generation. However, such environmental data represent the average value of the wide area, and there is a limitation in detecting environmental changes in the specific area where the solar panel is installed.

EggBlock: Design and Implementation of Solar Energy Generation and Trading Platform in Edge-Based IoT Systems with Blockchain.

In this paper, to balance power supplement from the solar energy's intermittent and unpredictable generation, we design a solar energy generation and trading platform (EggBlock) using Internet of Things (IoT) systems and blockchain technique. Without a centralized broker, the proposed EggBlock platform can promote energy trading between users equipped with solar panels, and balance demand and generation. By applying the second price sealed-bid auction, which is one of the suitable pricing mechanisms in the blockchain technique, it is possible to derive truthful bidding of market participants according to their utility function and induce the proceed transaction.

Reflective-emissive photoluminescent cholesteric liquid crystal display.

We fabricated a photoluminescent cholesteric liquid crystal (PL-CLC) cell for a display application that can be used to display high-quality moving pictures under all ambient conditions including dark and sunlit conditions. The PL-CLC cell is switchable between the reflective mode under bright conditions and the emissive mode in the dark. The effective reflectance of the PL-CLC is higher than that of a conventional CLC device by more than 30%, and the contrast ratios were approximately 10 and 7 in the reflective and emissive modes, respectively.

Complementarity between fluorescence and reflection in photoluminescent cholesteric liquid crystal devices.

The combination of photoluminescence (PL) and cholesteric liquid crystal (CLC) provides interesting complementary features for an optimized display application. Distortion of the Bragg lattice of CLCs decreases selective reflection but increases fluorescence intensity; recovery of a uniform lattice in turn results in increased reflection and decreased fluorescence. This complementary relationship between the fluorescence and the Bragg reflection gives rise to self-compensations for color shifts due to either dynamic slow response of CLC helix or mismatch of oblique incidence of light with respect to the helical axis.