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Activation evaluation of substances around the target in 70-MeV proton beam irradiation facilities
Baek Beomyeol,Kim Sangrok,Yang Hyungjin 한국물리학회 2023 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.82 No.11
Various substances in the target room of 70-MeV proton beam irradiation facility must be managed as radioactive waste owing to their activation during operations. In radioactive waste management, it is important to calculate the storage period. Consequently, radionuclides of activated substances and radioactivity concentration must be investigated. This study investigated the radionuclides and radioactivity values of activated aluminum, concrete, stainless steel, and each concrete by depth using computational simulations (Monte Carlo N-Particle, FISPACT-II) and measurements. Most of the radionuclides and radioactivity values of the substances obtained by the two methods exceeded the clearance level. For nuclides exceeding the clearance level, the ratio of the FISPACT-II to measurement results yielded an average of 1.21. With increase in the depth of the concrete, the diference between the two results increased. For all substances, the period of satisfying the clearance criterion was more than 10 years. This long period is attributed to the efects of long half-life nuclides 22Na and 54Mn. Thus, when calculating the storage period for radioactive waste disposal, the method resulting in higher activity values for 22Na and 54Mn should be applied.
Comparison of writing methods of single memory cell with volatile and nonvolatile memory functions
Kim, Hyungjin,Baek, Myung-Hyun,Hwang, Sungmin,Lee, Jong-Ho,Park, Byung-Gook JAPAN SOCIETY OF APPLIED PHYSICS 2017 Applied physics express Vol.10 No.6
<P>A single memory cell having both volatile memory (VM) and nonvolatile memory (NVM) functions with an independent asymmetric dual-gate structure is reported, as well as its programming methods. In the case of operating the device as a VM cell, a higher sensing margin is obtained, and an undesirable soft-programming issue is suppressed when a gate-induced drain leakage programming method is used. Additionally, the sensing margin and hold retention time of the VM operation are improved in a programmed state of the NVM function. These results indicate that the proposed device has potential for high-density embedded-memory applications. (C) 2017 The Japan Society of Applied Physics</P>
Implementation of Neuromorphic System with Si-based Floating-body Synaptic Transistors
Jungjin Park,Hyungjin Kim,Min-Woo Kwon,Sungmin Hwang,Myung-Hyun Baek,Jeong-Jun Lee,Taejin Jang,Byung-Gook Park 대한전자공학회 2017 Journal of semiconductor technology and science Vol.17 No.2
We have developed the neuromorphic system that can work with the four-terminal Si-based synaptic devices and verified the operation of the system using simulation tool and printed-circuit-board (PCB). The symmetrical current mirrors connected to the n-channel and p-channel synaptic devices constitute the synaptic integration part to express the excitation and the inhibition mechanism of neurons, respectively. The number and the weight of the synaptic devices affect the amount of the current reproduced from the current mirror. The double-stage inverters controlling delay time and the NMOS with large threshold voltage (VT) constitute the action-potential generation part. The generated action-potential is transmitted to next neuron and simultaneously returned to the back gate of the synaptic device for changing its weight based on spike-timing-dependent-plasticity (STDP).
CMOS Analog Integrate-and-fire Neuron Circuit for Driving Memristor based on RRAM
Kwon, Min-Woo,Baek, Myung-Hyun,Park, Jungjin,Kim, Hyungjin,Hwang, Sungmin,Park, Byung-Gook The Institute of Electronics and Information Engin 2017 Journal of semiconductor technology and science Vol.17 No.2
We designed the CMOS analog integrate and fire (I&F) neuron circuit for driving memristor based on resistive-switching random access memory (RRAM). And we fabricated the RRAM device that have $HfO_2$ switching layer using atomic layer deposition (ALD). The RRAM device has gradual set and reset characteristics. By spice modeling of the synaptic device, we performed circuit simulation of synaptic device and CMOS neuron circuit. The neuron circuit consists of a current mirror for spatial integration, a capacitor for temporal integration, two inverters for pulse generation, a refractory part, and finally a feedback part for learning of the RRAM. We emulated the spike-timing-dependent-plasticity (STDP) characteristic that is performed automatically by pre-synaptic pulse and feedback signal of the neuron circuit. By STDP characteristics, the synaptic weight, conductance of the RRAM, is changed without additional control circuit.
Eun-Jung Park,Hyungjin Kim,Seung Min Jung,Yoon-Kyoung Sung,Han Joo Baek,Jisoo Lee 대한내과학회 2020 The Korean Journal of Internal Medicine Vol.35 No.1
Biological disease-modifying antirheumatic drugs (bDMARDs) are highly effective agents for the treatment of inf lammatory arthritis; however, they also possess a potential risk for serious infection. Recently, with the rapid expansion of the bDMARDs market in Korea, reports of serious adverse events related to the agents have also increased, necessitating guidance for the use of bDMARDs. Current work entitled, “Expert consensus for the use of bDMARDs drugs for inflammatory arthritis in Korea,” is the first to describe the appropriate use of bDMARDs in the management of inflammatory arthritis in Korea, with an aim to provide guidance for the local medical community to improve the quality of clinical care. Twelve consensus statements regarding the use of bDMARDs for the management of rheumatoid arthritis and ankylosing spondylitis were generated. In this review, we provide detailed guidance on bDMARDs use based on expert consensus, including who should prescribe, the role of education, indications for use, and monitoring strategies for safety.
Hwang, Sungmin,Kim, Hyungjin,Park, Jungjin,Kwon, Min-Woo,Baek, Myung-Hyun,Lee, Jeong-Jun,Park, Byung-Gook IEEE 2018 IEEE electron device letters Vol.39 No.9
<P>We perform a system-level simulation of hardware spiking neural network (SNN) consisting of silicon-based synaptic transistors and integrate-and-fire (I&F) neuron circuits. Using electrical models of the synaptic device and I&F neuron circuit, a three-layer fully connected SNN in hardware is presented for MNIST pattern recognition by means of <I>ex situ</I> training. Right-justified rate coding is employed as an information encoding method, and negative weight values are implemented by a pair of the synaptic transistors (specifically, excitatory and inhibitory synapses). Furthermore, the variability effect occurring in the devices and circuits is demonstrated. This result indicates that the system has tolerance to the variations and how precisely the variations need to be controlled for hardware SNN applications.</P>
( Eun-jung Park ),( Hyungjin Kim ),( Seung Min Jung ),( Yoon-kyoung Sung ),( Han Joo Baek ),( Jisoo Lee ) 대한류마티스학회 2020 대한류마티스학회지 Vol.27 No.1
Biological disease-modifying antirheumatic drugs (bDMARDs) are highly effective agents for the treatment of inflammatory arthritis; however, they also possess a potential risk for serious infection. Recently, with the rapid expansion of the bDMARDs market in Korea, reports of serious adverse events related to the agents have also increased, necessitating guidance for the use of bDMARDs. Current work entitled, “Expert Consensus for the Use of bDMARDs Drugs for Inflammatory Arthritis in Korea,” is the first to describe the appropriate use of bDMARDs in the management of inflammatory arthritis in Korea, with an aim to provide guidance for the local medical community to improve the quality of clinical care. Twelve consensus statements regarding the use of bDMARDs for the management of rheumatoid arthritis and ankylosing spondylitis were generated. In this review, we provide detailed guidance on bDMARDs use based on expert consensus, including who should prescribe, the role of education, indications for use, and monitoring strategies for safety. (J Rheum Dis 2020;27:4-21)
Implementation of Neuromorphic System with Si-based Floating-body Synaptic Transistors
Park, Jungjin,Kim, Hyungjin,Kwon, Min-Woo,Hwang, Sungmin,Baek, Myung-Hyun,Lee, Jeong-Jun,Jang, Taejin,Park, Byung-Gook The Institute of Electronics and Information Engin 2017 Journal of semiconductor technology and science Vol.17 No.2
We have developed the neuromorphic system that can work with the four-terminal Si-based synaptic devices and verified the operation of the system using simulation tool and printed-circuit-board (PCB). The symmetrical current mirrors connected to the n-channel and p-channel synaptic devices constitute the synaptic integration part to express the excitation and the inhibition mechanism of neurons, respectively. The number and the weight of the synaptic devices affect the amount of the current reproduced from the current mirror. The double-stage inverters controlling delay time and the NMOS with large threshold voltage ($V_T$) constitute the action-potential generation part. The generated action-potential is transmitted to next neuron and simultaneously returned to the back gate of the synaptic device for changing its weight based on spike-timing-dependent-plasticity (STDP).
CMOS Analog Integrate-and-fire Neuron Circuit for Driving Memristor based on RRAM
Min-Woo Kwon,Myung-Hyun Baek,Jungjin Park,Hyungjin Kim,Sungmin Hwang,Byung-Gook Park 대한전자공학회 2017 Journal of semiconductor technology and science Vol.17 No.2
We designed the CMOS analog integrate and fire (I&F) neuron circuit for driving memristor based on resistive-switching random access memory (RRAM). And we fabricated the RRAM device that have HfO2 switching layer using atomic layer deposition (ALD). The RRAM device has gradual set and reset characteristics. By spice modeling of the synaptic device, we performed circuit simulation of synaptic device and CMOS neuron circuit. The neuron circuit consists of a current mirror for spatial integration, a capacitor for temporal integration, two inverters for pulse generation, a refractory part, and finally a feedback part for learning of the RRAM. We emulated the spike-timing-dependent-plasticity (STDP) characteristic that is performed automatically by presynaptic pulse and feedback signal of the neuron circuit. By STDP characteristics, the synaptic weight, conductance of the RRAM, is changed without additional control circuit.