• Management & Information Systems Review
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• v.31 no.1
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• pp.89-116
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• 2012

This paper is an empirical study for the listed manufacturing companies in the Korea Stock Exchange during the sample period(2001-2010). The research is based on the target adjustment model(Shyam-Sunder and Myers(1999)) and the pecking order model(Frank and Goyal(2003)), and is aimed at reflecting the critical viewpoint of Chirinko and Singha(2000). An analysis in the model of Shyam-Sunder and Myers(1999) shows the value is too low to support the pecking order model in view of the following results. A target adjustment coefficient value is between 0 and 1, and is significant variable and explanatory power is very high, while deficit-in-funds coefficients close to 0. In addition, the result of an empirical test following the methodology used by Frank and Goyal(2003) does not support the pecking order theory.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.840-845
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• 2001

Development of a small gas-turbine combustor for 100kW class APU(Auxiliary Power Unit) has been performed. This combustor is a reverse-annular type and has a tangential swirler in the liner head to improve the fuel/air mixing and flame stability. Three main and three pilot fuel injectors of the simplex pressure-swirl type are used. The performance target at the design condition includes a turbine inlet temperature of 1170K, a combustion efficiency of 99%, a pattern factor of 30%, and an engine durability of 3000 hours. Under developing the combustor, we conducted performance test of our first prototype(TS1) with some variants. As a result of the test, the performance targets of the combustor are satisfied except that the pattern factor is about 4% higher than target value. So, we redesigned the second prototype(TS2) and conduct performance test with the critical focus on pattern factor and exit mean temperature. We adopted TS2 four variant to check the improvement of pattern factor. As the result, the pattern factors of several variants were satisfied with the performance target. Finally, We chose the TS2A variant as a final combustor for our APU model.

• Food Science and Biotechnology
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• v.16 no.3
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• pp.457-462
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• 2007

Histone acetyltransferase (HAT) is a family of enzymes that regulate histone acetylation. Dysfunction of HAT plays a critical role in the development of cancer. Here we have screened the various plant extracts to find out the potent HAT inhibitors. The bellflower (Platycodon grandiflorum) root have exhibited approximately 30% of the inhibitory effects on HAT activity, especially p300 and CBP (CREB-binding protein) at the concentration of $100\;{\mu}g/mL$. The cell viability was decreased approximately 52% in LNCaP cell for 48 hr incubation. Furthermore, mRNA level of 3 androgen receptor target genes, PSA, NKX3.1, and TSC22 were decreased with bellflower root extract treatment ($100\;{\mu}g/mL$) in the presence of androgen. In ChIP assay, the acetylation of histone H3 and H4 in PSA promoter region was dramatically repressed by bellflower root treatment, but not TR target gene, Dl. Therefore, the potent HAT inhibitory effect of bellflower root led to the decreased transcription of AR target genes and prostate cancer cell growth with the repression of histone hyperacetylation.

• Biomolecules & Therapeutics
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• v.23 no.6
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• pp.493-509
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• 2015

Antibody-drug conjugates utilize the antibody as a delivery vehicle for highly potent cytotoxic molecules with specificity for tumor-associated antigens for cancer therapy. Critical parameters that govern successful antibody-drug conjugate development for clinical use include the selection of the tumor target antigen, the antibody against the target, the cytotoxic molecule, the linker bridging the cytotoxic molecule and the antibody, and the conjugation chemistry used for the attachment of the cytotoxic molecule to the antibody. Advancements in these core antibody-drug conjugate technology are reflected by recent approval of Adectris$^{(R)}$(anti-CD30-drug conjugate) and Kadcyla$^{(R)}$(anti-HER2 drug conjugate). The potential approval of an anti-CD22 conjugate and promising new clinical data for anti-CD19 and anti-CD33 conjugates are additional advancements. Enrichment of antibody-drug conjugates with newly developed potent cytotoxic molecules and linkers are also in the pipeline for various tumor targets. However, the complexity of antibody-drug conjugate components, conjugation methods, and off-target toxicities still pose challenges for the strategic design of antibody-drug conjugates to achieve their fullest therapeutic potential. This review will discuss the emergence of clinical antibody-drug conjugates, current trends in optimization strategies, and recent study results for antibody-drug conjugates that have incorporated the latest optimization strategies. Future challenges and perspectives toward making antibody-drug conjugates more amendable for broader disease indications are also discussed.

• Journal of Sensor Science and Technology
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• v.28 no.6
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• pp.414-419
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• 2019

An ultrasonic based magnetostrictive position sensor (MPS) provides an indication of real target position. It determines the real target position by multiplying the propagation speed of ultrasonic wave and the time-of-flight between the receiving signals; one is the initial signal by an excitation current and the other is the reflection signal by the ultrasonic wave. The propagation speed of the ultrasonic wave depends on the temperature of the waveguide. Hence, the change of the propagation speed in various environments is a critical factor in terms of the positioning accuracy in the MPS. This means that the influence of the changes in the waveguide temperature needs to be compensated. In this paper, we presents a novel way to improve the positioning accuracy of MPSs using temperature compensation for waveguide. The proposed method used the inherent measurement blind area for the structure of the MPS, which can simultaneously measure the position of the moving target and the temperature of the waveguide without any additional devices. The average positional error was approximately -23.9 mm and -1.9 mm before and after compensation, respectively. It was confirmed that the positioning accuracy was improved by approximately 93%.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.207-218
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• 2018

Recently, it becomes a big trend in the banking industry to apply a big data analytics technique to extract essential knowledge from their customer database. Such a trend is based on the capability to analyze the big data with powerful analytics software and recognize the value of big data analysis results. However, there exits still a need for more systematic theory and mechanism about how to adopt a big data analytics approach in the banking industry. Especially, there is no study proposing a practical case study in which big data analytics is successfully accomplished from the marketing perspective. Therefore, this study aims to analyze a target marketing case in the banking industry from the view of big data analytics. Target database is a big data in which about 3.5 million customers and their transaction records have been stored for 3 years. Practical implications are derived from the marketing perspective. We address detailed processes and related field test results. It proved critical for the big data analysts to consider a sense of Veracity and Value, in addition to traditional Big Data's 3V (Volume, Velocity, and Variety), so that more significant business meanings may be extracted from the big data results.

• Parasites, Hosts and Diseases
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• v.46 no.1
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• pp.1-15
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• 2008

Introduction of double-stranded RNA (dsRNA) into some cells or organisms results in degradation of its homologous mRNA, a process called RNA interference (RNAi). The dsRNAs are processed into short interfering RNAs (siRNAs) that subsequently bind to the RNA-induced silencing complex (RISC), causing degradation of target mRNAs. Because of this sequence-specific ability to silence target genes, RNAi has been extensively used to study gene functions and has the potential to control disease pathogens or vectors. With this promise of RNAi to control pathogens and vectors, this paper reviews the current status of RNAi in protozoans, animal parasitic helminths and disease-transmitting vectors, such as insects. Many pathogens and vectors cause severe parasitic diseases in tropical regions and it is difficult to control once the host has been invaded. Intracellularly, RNAi can be highly effective in impeding parasitic development and proliferation within the host. To fully realize its potential as a means to control tropical diseases, appropriate delivery methods for RNAi should be developed, and possible off-target effects should be minimized for specific gene suppression. RNAi can also be utilized to reduce vector competence to interfere with disease transmission, as genes critical for pathogenesis of tropical diseases are knockdowned via RNAi.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.703-722
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• 2016

Passive wireless devices have increasing civilian and military applications, especially in the scenario with wearable devices and Internet of Things. In this paper, we study indoor localization of a target equipped with radio-frequency identification (RFID) device in ultra-wideband (UWB) wireless networks. With known room layout, deterministic multipath components, including the line-of-sight (LOS) signal and the reflected signals via multipath propagation, are employed to locate the target with one transmitter and a single inaccurate receiver. A factor graph corresponding to the joint posterior position distribution of target and receiver is constructed. However, due to the mixed distribution in the factor node of likelihood function, the expressions of messages are intractable by directly applying belief propagation on factor graph. To this end, we approximate the messages by Gaussian distribution via minimizing the Kullback-Leibler divergence (KLD) between them. Accordingly, a parametric message passing algorithm for indoor passive localization is derived, in which only the means and variances of Gaussian distributions have to be updated. Performance of the proposed algorithm and the impact of critical parameters are evaluated by Monte Carlo simulations, which demonstrate the superior performance in localization accuracy and the robustness to the statistics of multipath channels.

• Nuclear Engineering and Technology
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• v.40 no.7
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• pp.551-560
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• 2008

Radiation has stochastic aspects in its generation, its choice of interaction mode during traveling in media, and its impact on living bodies. In certain circumstances, like in high dose environments resulting from low-LET radiation, the variance in its impact on a target volume is negligible. On the contrary, in low dose environments, especially when they are attributed to high-LET radiation, the impact on the target carries with it a large variance. This variation is more significant for smaller target volumes. Microdosimetric techniques, which have been developed to estimate the distribution of radiation energy deposited to cellular and subcellular-sized targets, contrast with macrodosimetric techniques which count only the average value. Since cells and DNA compounds are the critical targets in human bodies, microdosimetry, or dose estimation by microscopic approach, helps one better analyze the biological effects of radiation on the human body. By utilizing microbeam systems designed for individual cell irradiation, scientists have discovered that human cells exhibit radiosensitive reactions without being hit themselves (bystander effect). During the past 10 or more years, a new therapeutic protocol using discontinuous multiple micro-slit beams has been investigated for its clinical application. It has been suggested that the beneficial bystander effect is the essence of this protocol.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.337-345
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• 2020

The Weapon-Target Assignment(WTA) problem can be formulated as an optimization problem that minimize the threat of targets. Existing methods consider the trade-off between optimality and execution time to meet the various mission objectives. We propose a multi-agent reinforcement learning algorithm for WTA based on mean field game to solve the problem in real-time with nearly optimal accuracy. Mean field game is a recent method introduced to relieve the curse of dimensionality in multi-agent learning algorithm. In addition, previous reinforcement learning models for WTA generally do not consider weapon interference, which may be critical in real world operations. Therefore, we modify the reward function to discourage the crossing of weapon trajectories. The feasibility of the proposed method was verified through simulation of a WTA problem with multiple targets in realtime and the proposed algorithm can assign the weapons to all targets without crossing trajectories of weapons.