Ministry of Science and ICT

R&D subsidy design and innovation additionality: disentangling the mechanisms in South Korea’s innovation system

Sang-Min Park, Ilwon Seo, Taehyuk Kwon, NICHOLAS SPYRIDON VONORTAS

kr, us (code pays fourni par la source)

DeepTDM: Deep Learning-Based Prediction of Sequential Therapeutic Drug Monitoring Levels of Vancomycin

Jinkyeong Park, Dohyun Kim, Minkyu Kim, Yoon Jun Kim et autres

OBJECTIVE: Therapeutic drug monitoring (TDM) is essential for managing medication dosages in critically ill patients, particularly for antibiotics such as vancomycin. The dynamic physiological conditions of critically ill patients require frequent monitoring of vancomycin levels to ensure therapeutic therapeutic efficacy while minimizing …

kr (code pays fourni par la source)

All‐Ferroelectric Spiking Neural Networks via Morphotropic Phase Boundary Neurons

Jangsaeng Kim, Eun Chan Park, Wonjun Shin, Ryun‐Han Koo et autres

Artificial neurons and synapses are crucial for efficiently implementing spiking neural networks (SNNs) in hardware. The distinct functional requirements of artificial neurons and synapses present significant challenges in the implementation of area- and energy-efficient SNNs. This study reports an all-ferroelectric SNN system …

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Polarization Pruning: Reliability Enhancement of Hafnia‐Based Ferroelectric Devices for Memory and Neuromorphic Computing

Ryun‐Han Koo, Wonjun Shin, Jangsaeng Kim, Jiyong Yim et autres

Ferroelectric (FE) materials are key to advancing electronic devices owing to their non-volatile properties, rapid state-switching abilities, and low-energy consumption. FE-based devices are used in logic circuits, memory-storage devices, sensors, and in-memory computing. However, the primary challenge in advancing the practical applications …

kr, us (code pays fourni par la source)

Chemisorption Manipulation by Adjusting the Carrier Concentration of the Adsorbent and Its Application to Adsorbate Identification

Gyuweon Jung, Kangwook Choi, Suyeon Ju, Jaehyeon Kim et autres

Progress in techniques for manipulating chemisorption has substantially advanced various applications. Herein, we present a widely applicable method to manipulate chemisorption by adjusting the carrier concentration of the adsorbent. We demonstrate that in both n - and p -type adsorbents, an increase …

kr (code pays fourni par la source)

Strengthening the Korean Network of Microbial Culture Collections in the Microbiome Era

Yiseul Kim, Hyang Min Cheong, Grace Choi, Kyung-Min Choi et autres

Microbes are critical contributors in main areas of biotechnology, including green, red, and white biotechnology. This is why the importance of the preservation of microbial resources cannot be emphasized enough. Culture collections are repositories not only for the preservation and maintenance of …

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Toward Ideal Low‐Frequency Noise in Monolayer CVD MoS 2 FETs: Influence of van der Waals Junctions and Sulfur Vacancy Management

Wonjun Shin, Junsung Byeon, Ryun‐Han Koo, Jungmoon Lim et autres

Abstract The pursuit of sub‐1‐nm field‐effect transistor (FET) channels within 3D semiconducting crystals faces challenges due to diminished gate electrostatics and increased charge carrier scattering. 2D semiconductors, exemplified by transition metal dichalcogenides, provide a promising alternative. However, the non‐idealities, such as excess …

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Demonstration of In‐Memory Biosignal Analysis: Novel High‐Density and Low‐Power 3D Flash Memory Array for Arrhythmia Detection

Jangsaeng Kim, Jiseong Im, Wonjun Shin, Soochang Lee et autres

Smart healthcare systems integrated with advanced deep neural networks enable real-time health monitoring, early disease detection, and personalized treatment. In this work, a novel 3D AND-type flash memory array with a rounded double channel for computing-in-memory (CIM) architecture to overcome the limitations …

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Toward Optimized In‐Memory Reinforcement Learning: Leveraging 1/f Noise of Synaptic Ferroelectric Field‐Effect‐Transistors for Efficient Exploration

Jangsaeng Kim, Wonjun Shin, Jiyong Yim, Dongseok Kwon et autres

Reinforcement learning (RL), exhibiting outstanding performance in various fields, requires large amounts of data for high performance. While exploration techniques address this requirement, conventional exploration methods have limitations: complexity of hardware implementation and significant hardware burden. Herein, in‐memory RL systems leveraging intrinsic …

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Innovative strategy for enhancing nature-based solutions during climate technology transfer process

Woo-Jin Lee, Jaeryoung Song

Recently, Nature-based Solutions (NbS) have increasingly been regarded as a new opportunity to maximize the synergies between nature, society, and the economy. In addition, especially for policymakers and practitioners engaged in climate technology transfer activities from developed to developing countries, this concept …

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New Gas Identification Method Using Gas Sensor-Amplifier Merged Array and In-Memory Computing-Based Preprocessing

Gyuweon Jung, Jaehyeon Kim, Yujeong Jeong, Jinwoo Park et autres

We present a novel gas identification method using a sensor-amplifier merged array and in-memory computing-based preprocessing. An amplifier array that effectively integrates pFET-type and resistive sensors senses gases and selectively amplifies the sensing signals. The amplified array signals are preprocessed in the …

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Proposition of Adaptive Read Bias: A Solution to Overcome Power and Scaling Limitations in Ferroelectric‐Based Neuromorphic System

Ryun‐Han Koo, Wonjun Shin, Seung Whan Kim, Jiseong Im et autres

Abstract Hardware neuromorphic systems are crucial for the energy‐efficient processing of massive amounts of data. Among various candidates, hafnium oxide ferroelectric tunnel junctions (FTJs) are highly promising for artificial synaptic devices. However, FTJs exhibit non‐ideal characteristics that introduce variations in synaptic weights, …

kr (code pays fourni par la source)