전동석 교수

In this paper, we present a neuromorphic processor that could learn to classify images through spiking information between neurons. Data is only computed locally, and there is no need for energy-hungry data transmissions that is required for any other machine learning algorithms. Careful algorithmic adaptations, along with novel hardware implementation of softmax functions are introduced to deliver maximum performance on image classification tasks while minimizing energy consumption. The design

Interleukin (IL)-12 activates T helper (Th) 1 cells to produce interferon (IFN)-gamma which inhibits atopic inflammation. IL-12 acts through interaction with its receptor, especially beta(2) subunit. In several studies, the low production of IFN-gamma in peripheral mononuclear cells of atopic patients on response to IL-12 stimulation has been reported. Therefore we investigated the IL-12 receptor beta(2) (IL-12R beta(2)) mRNA expression and RNA editing, nucleotide 2451 C-to-U conversion, to find

We experienced a case in which yeasts in blood\nsample from a patient with cervical cancer with hepatic\nmetastasis and multiple intraperitoneal cysts interfered\nwith platelet morphology flag in automated\nblood analyzer. The peripheral blood smear was performed\nto confirm the flag and revealed intracellular\nand extracellular yeasts, which were subsequently\nidentified as Candida parapsilosis by blood culture.

Abstract Abstract 1455 Background: Since the acquired somatic mutation, JAK2 V617F, was discovered as a first molecular marker of myeloproliferative neoplasms (MPN), and it has been detected variably in each MPN subtypes. However, JAK2 V617F does not found in all of MPN cases and not necessarily specific to a particular clinicpathologic entity. Recently, mutation of the putative tumor suppressor gene, Ten-Eleven-Translocation-2(TET2), has been identified in MPN patients. However, the frequency o

In this paper, we present a neuromorphic processor that could learn to classify images through spiking information between neurons. Data is only computed locally, and there is no need for energy-hungry data transmissions that is required for any other machine learning algorithms. Careful algorithmic adaptations, along with novel hardware implementation of softmax functions are introduced to deliver maximum performance on image classification tasks while minimizing energy consumption. The design

Children with Down syndrome (DS) have a higher risk of developing leukemia than do healthy children, and they especially have a higher risk for developing transient myeloproliferative disorder (TMD) or acute megakaryocytic leukemia (AMKL). In recent studies, it has been reported that most of these patients have acquired mutation of the GATA1 gene, which encodes the erythroid/megakaryocytic transcription factor GATA1. GATA1 mutations have not been found in AMKL patients who did not have DS and ot