• Journal of Microbiology and Biotechnology
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• v.23 no.3
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• pp.329-334
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• 2013

Uridinediphospho-N-acetylglucosamine enolpyruvyl transferase (MurA, E.C. 2.5.1.7) is an essential bacterial enzyme that catalyzes the first step of the cell wall biosynthetic pathway, which involves the transfer of an enolpyruvyl group from phosphoenolpyruvate to uridinediphospho-Nacetylglucosamine. In this study, novel inhibitors of Haemophilus influenzae MurA (Hi MurA) were identified using high-throughput screening of a chemical library from the Korea Chemical Bank. The identified compounds contain a quinoline moiety and have much lower effective inhibitory concentrations ($IC_{50}$) than fosfomycin, a wellknown inhibitor of MurA. These inhibitors appear to covalently modify the sulfhydryl group of the active site cysteine (C117), since the C117D mutant Hi MurA was not inhibited by these compounds and excess dithiothreitol abolished their inhibitory activities. The increased mass value of Hi MurA after treatment with the identified inhibitor further confirmed that the active-site cysteine residue of Hi MurA is covalently modified by the inhibitor.

• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.377-382
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• 2010

With the advent of flash memory based new storage device (SSD), there is considerable interest within the computer industry in using flash memory based storage devices for many different types of application. The dynamic index structure of large text collections has been a primary issue in the Information Retrieval Applications among them. Previous studies have proven the three approaches to be effective: In- Place, merge-based index structure and a combination of both. The above-mentioned strategies have been researched with the traditional storage device (HDD) which has a constraint on how keep the contiguity of dynamic data. However, in case of the new storage device, we don' have any constraint contiguity problems due to its low access latency time. But, although the new storage device has superiority such as low access latency and improved I/O throughput speeds, it is still not well suited for traditional dynamic index structures because of the poor random write throughput in practical systems. Therefore, using the experimental performance evaluation of various index maintenance schemes on the new storage device, we propose an efficient index structure for new storage device that improves significantly the index maintenance speed without degradation of query performance.

• The Transactions of the Korea Information Processing Society
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• v.1 no.4
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• pp.502-510
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• 1994

CDMA technique has been largely focused for Wireless Data Communication and Personal Communication Network. ALOHA protocol also has been proven to be effective for Packet Radio Radio Network regardless of low throughput due to channel collisions. In this paper, we evaluate the performance of MS-CDMA-ALOHA (Mini-Slotted-CDMA-ALOHA) system, by analytic and simulation method. The superiority of the MS-CDMA-ALOHA system over conventional Slotted ALOHA and Slotted-CDMA-ALOHA systems are clearly demonstrated for throughput, delay and stability performances.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.2A
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• pp.130-138
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• 2008

In this paper, we propose a user selection method to maximize the sum-rate of downlink over opportunistic beamforming. The throughput of an opportunistic beamforming with non-uniformly distributed or a small number of users can decrease. In order to improve the throughput, we propose a scheduling method that does not use SINR or SNR but uses the effective channel gain of each user obtained from the SINR or SNR feedback. The proposed method makes it possible to select users flexibly according to the distribution of users. In numerical results, we show that the proposed methods improve the average sum-rate about 60% when users are distributed non uniformly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.7C
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• pp.641-652
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• 2002

We introduce a new ultra-large capacity time- and wavelength-division hybrid optical switching system, called ESCIMONET(Easily SCalable Interconnected Multiwavelength Optical NETwork). We describe its architecture, principle of operation, and performance characteristics. ESCIMONET is very effective system in terms of its handling capacity versus number of wavelength needed. It can handle n$^3$number of channels using only n number of different wavelengths. The insertion loss of the whole system is less than conventional optical switching system so that the number of optical amplifiers in the system can be minimized. We analyzed the performance of the system by investigation the characteristics of the buffer used in the system such as throughput and average waiting time of the signal in a buffer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.559-567
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• 2015

This paper focuses on evaluating the performance of a cellular network using power control based frequency reuse partitioning (FRP) in downlink (DL). In our work, in order to have the realistic environment, the spectral efficiency of the system is evaluated through traffic analysis, which most of the previous works did not consider. To further decrease the cell edge user's outage, the concept of power ratio is introduced and applied to the DL FRP based cellular network. In considering network topology, we first divide the cell coverage area into two regions, the inner and outer regions. We then allocate different sub-bands in the inner and outer regions of each cell. In the analysis, for each zone ratio, the performance of FRP system is evaluated for the given number of power ratios. We consider performance metrics such as call blocking probability, channel utilization, outage probability and effective throughput. The simulation results show that there is a significant improvement in the outage experienced by outer UEs with power control scheme compared to that with no power control scheme and an increase in overall system throughput.

• Molecules and Cells
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• v.44 no.3
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• pp.127-135
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• 2021

Since the introduction of RNA sequencing (RNA-seq) as a high-throughput mRNA expression analysis tool, this procedure has been increasingly implemented to identify cell-level transcriptome changes in a myriad of model systems. However, early methods processed cell samples in bulk, and therefore the unique transcriptomic patterns of individual cells would be lost due to data averaging. Nonetheless, the recent and continuous development of new single-cell RNA sequencing (scRNA-seq) toolkits has enabled researchers to compare transcriptomes at a single-cell resolution, thus facilitating the analysis of individual cellular features and a deeper understanding of cellular functions. Nonetheless, the rapid evolution of high throughput single-cell "omics" tools has created the need for effective hypothesis verification strategies. Particularly, this issue could be addressed by coupling cell engineering techniques with single-cell sequencing. This approach has been successfully employed to gain further insights into disease pathogenesis and the dynamics of differentiation trajectories. Therefore, this review will discuss the current status of cell engineering toolkits and their contributions to single-cell and genome-wide data collection and analyses.

• ETRI Journal
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• v.44 no.5
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• pp.733-745
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• 2022

In software-defined wireless networking (SDWN), the optimal routing technique is one of the effective solutions to improve its performance. This routing technique is done by many different methods, with the most common using integer linear programming problem (ILP), building optimal routing metrics. These methods often only focus on one routing objective, such as minimizing the packet blocking probability, minimizing end-to-end delay (EED), and maximizing network throughput. It is difficult to consider multiple objectives concurrently in a routing algorithm. In this paper, we investigate the application of machine learning to control routing in the SDWN. An intelligent routing algorithm is then proposed based on the machine learning to improve the network performance. The proposed algorithm can optimize multiple routing objectives. Our idea is to combine supervised learning (SL) and reinforcement learning (RL) methods to discover new routes. The SL is used to predict the performance metrics of the links, including EED quality of transmission (QoT), and packet blocking probability (PBP). The routing is done by the RL method. We use the Q-value in the fundamental equation of the RL to store the PBP, which is used for the aim of route selection. Concurrently, the learning rate coefficient is flexibly changed to determine the constraints of routing during learning. These constraints include QoT and EED. Our performance evaluations based on OMNeT++ have shown that the proposed algorithm has significantly improved the network performance in terms of the QoT, EED, packet delivery ratio, and network throughput compared with other well-known routing algorithms.

• ETRI Journal
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• v.45 no.1
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• pp.45-59
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• 2023

In this paper, to optimize the average delay and power allocation (PA) for system users, we propose a resource scheduling scheme for wireless networks based on Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM) according to the first fifth-generation standards. For delay minimization, we solve a throughput maximization problem that considers CPOFDM systems with carrier aggregation (CA). Regarding PA, we consider an approach that involves maximizing goodput using an effective signal-to-noise ratio. An algorithm for jointly solving delay minimization through computation of required user rates and optimizing the power allocated to users is proposed to compose the resource allocation approach. In wireless network simulations, we consider a scenario with the following capabilities: CA, 256-Quadrature Amplitude Modulation, millimeter waves above 6 GHz, and a radio frame structure with 120 KHz spacing between the subcarriers. The performance of the proposed resource allocation algorithm is evaluated and compared with those of other algorithms from the literature using computational simulations in terms of various Quality of Service parameters, such as the throughput, delay, fairness index, and loss rate.

• The Plant Pathology Journal
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• v.40 no.2
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• pp.115-124
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• 2024

Citrus cultivation plays a pivotal role, making a significant contribution to global fruit production and dietary consumption. Accurate identification of viral pathogens is imperative for the effective management of plant viral disease in citrus crops. High-throughput sequencing serves as an alternative approach, enabling comprehensive pathogen identification on a large scale without requiring pre-existing information. In this study, we employed HTS to investigate viral pathogens infecting citrus in three different regions of South Korea: Jejudo (Jeju), Wando-gun (Wando), and Dangjin-si (Dangjin). The results unveiled diverse viruses and viroids that exhibited regional variations. Notably, alongside the identification of well-known citrus viruses such as satsuma dwarf virus, citrus tatter leaf virus, and citrus leaf blotch virus (CLBV), this study also uncovered several viruses and viroids previously unreported in Korean citrus. Phylogenetic analysis revealed that majority of identified viruses exhibited the closest affilations with isolates from China or Japan. However, CLBV and citrus viroid-I-LSS displayed diverse phylogenetic positions, reflecting their regional origins. This study advances our understanding of citrus virome diversity and regional dynamics through HTS, emphasizing its potential in unraveling intricate viral pathogens in agriculture. Consequently, it significantly contributes to disease management strategies, ensuring the resilience of the citrus industry.