• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.989-997
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• 2018

Massive event stream brings us great challenges in its volume, velocity, variety, value and veracity. Picking up some valuable information from it often faces with long detection time, high memory consumption and low detection efficiency. Aiming to solve the problems above, an efficient complex event detection method based on NFA_HTS (Nondeterministic Finite Automaton_Hash Table Structure) is proposed in this paper. The achievement of this paper lies that we successfully use NFA_HTS to realize the detection of complex event from massive RFID event stream. Specially, in our scheme, after using NFA to capture the related RFID primitive events, we use HTS to store and process the large matched results, as a result, our scheme can effectively solve the problems above existed in current methods by reducing lots of search, storage and computation operations on the basis of taking advantage of the quick classification and storage technologies of hash table structure. The simulation results show that our proposed NFA_HTS scheme in this paper outperforms some general processing methods in reducing detection time, lowering memory consumption and improving event throughput.

• Genomics & Informatics
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• 제6권3호
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• pp.126-129
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• 2008

The robust identification and comprehensive profiling of copy number alterations (CNAs) is highly challenging. The amount of data obtained from high-throughput technologies such as array-based comparative genomic hybridization is often too large and it is required to develop a comprehensive and versatile tool for the detection and visualization of CNAs in a genome-wide scale. With this respective, we introduce a software framework, CGHscape that was originally developed to explore the CNAs for the study of copy number variation (CNV) or tumor biology. As a standalone program, CGHscape can be easily installed and run in Microsoft Windows platform. With a user-friendly interface, CGHscape provides a method for data smoothing to cope with the intrinsic noise of array data and CNA detection based on SW-ARRAY algorithm. The analysis results can be demonstrated as log2 plots for individual chromosomes or genomic distribution of identified CNAs. With extended applicability, CGHscape can be used for the initial screening and visualization of CNAs facilitating the cataloguing and characterizing chromosomal alterations of a cohort of samples.

• Journal of Information Processing Systems
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• 제8권3호
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• pp.459-470
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• 2012

Recently, high-throughput technologies such as the two-hybrid system, protein chip, Mass Spectrometry, and the phage display have furnished a lot of data on protein-protein interactions (PPIs), but the data has not been accurate so far and the quantity has also been limited. In this respect, computational techniques for the prediction and validation of PPIs have been developed. However, existing computational methods do not take into account the fact that a PPI is actually originated from the interactions of domains that each protein contains. So, in this work, the information on domain modules of individual proteins has been employed in order to find out the protein interaction relationship. The system developed here, WASPI (Web-based Assistant System for Protein-protein interaction Inference), has been implemented to provide many functional insights into the protein interactions and their domains. To achieve those objectives, several preprocessing steps have been taken. First, the domain module information of interacting proteins was extracted by taking advantage of the InterPro database, which includes protein families, domains, and functional sites. The InterProScan program was used in this preprocess. Second, the homology comparison with the GO (Gene Ontology) and COG (Clusters of Orthologous Groups) with an E-value of $10^{-5}$, $10^{-3}$ respectively, was employed to obtain the information on the function and annotation of each interacting protein of a secondary PPI database in the WASPI. The BLAST program was utilized for the homology comparison.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2013년도 제45회 하계 정기학술대회 초록집
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• pp.76.1-76.1
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• 2013

Atomic Layer Deposition (ALD) has remarkably developed in semiconductor and nano-structure applications since early 1990. Now, the advantages of ALD process are well-known as controlling atomic-level-thickness, manipulating atomic-level-composition control, and depositing impurity-free films uniformly. These unique properties may accelerate ALD related industries and applications in various functional thin film markets. On the other hand, one of big markets, Display industry, just starts to look at the potential to adopt ALD functional films in emerging display applications, such as transparent and flexible displays. Unlike conventional ALD process strategies (good quality films and stable precursors at high deposition processes), recently major display industries have suggested the following requirements: large area equipment, reasonable throughput, low temperature process, and cost-effective functional precursors. In this talk, it will be mentioned some demands of display industries for applying ALD processes and/or functional films, in terms of emerging display technologies. In fact, the AMOLED (active matrix organic light emitting diode) Television markets are just starting at early 2013. There are a few possibilities and needs to be developing for AMOLED, Flexible and transparent Display markets. Moreover, some basic results will be shown to specify ALD display applications, including transparent conduction oxide, oxide semiconductor, passivation and barrier films.

• Mass Spectrometry Letters
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• 제12권3호
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• pp.93-105
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• 2021

Exosomes have gained the attention of the scientific community because of their role in facilitating intercellular communication, which is critical in disease monitoring and drug delivery research. Exosome research has grown significantly in recent decades, with a focus on the development of various technologies for isolating and characterizing exosomes. Among these efforts is the use of matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS), which offers high-throughput direct analysis while also being cost and time effective. MALDI is used less frequently in exosome research than electrospray ionization due to the diverse population of extracellular vesicles and the impurity of isolated products, both of which necessitate chromatographic separation prior to MS analysis. However, MALDI-MS is a more appropriate instrument for the analytical approach to patient therapy, given it allows for fast and label-free analysis. There is a huge drive to explore MALDI-MS in exosome research because the technology holds great potential, most notably in biomarker discovery. With methods such as fingerprint analysis, OMICs profiling, and statistical analysis, the search for biomarkers could be much more efficient. In this review, we highlight the potential of MALDI-MS as a tool for investigating exosomes and some of the possible strategies that can be implemented based on prior research.

• Genomics & Informatics
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• 제19권3호
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• pp.27.1-27.4
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• 2021

Due to the rapid evolution of high-throughput technologies, a tremendous amount of data is being produced in the biological domain, which poses a challenging task for information extraction and natural language understanding. Biological named entity recognition (NER) and named entity normalisation (NEN) are two common tasks aiming at identifying and linking biologically important entities such as genes or gene products mentioned in the literature to biological databases. In this paper, we present an updated version of OryzaGP, a gene and protein dataset for rice species created to help natural language processing (NLP) tools in processing NER and NEN tasks. To create the dataset, we selected more than 15,000 abstracts associated with articles previously curated for rice genes. We developed four dictionaries of gene and protein names associated with database identifiers. We used these dictionaries to annotate the dataset. We also annotated the dataset using pretrained NLP models. Finally, we analysed the annotation results and discussed how to improve OryzaGP.

• Korean Chemical Engineering Research
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• 제61권4호
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• pp.487-495
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• 2023

암모니아는 인류의 식량문제를 해결할 수 있는 비료 생산의 주요 원료임과 동시에 무탄소 연료이면서 친환경적인 수소 운반자로서 중요한 에너지원으로 알려져 있다. 그래서 지금까지도 암모니아를 합성하거나 분해하는 기술들이 각광을 받고 있다. 암모니아 합성 및 분해 반응을 촉진시키기 위해서는 반드시 촉매 재료가 필요하다. 고성능 및 값싼 암모니아 합성 및 분해용 신촉매를 설계하기 위해서는 무수히 많은 합성 가능한 촉매 후보군들을 다루어야만 하는데 전통적인 접근법만으로 탐색 및 분석을 하기엔 시간적, 경제적인 비용이 많이 들 수밖에 없다. 최근에 4차 산업혁명의 핵심기술에 속하는 머신러닝을 이용하여 이용하여 고성능 촉매를 빠르고 정확하게 찾을 수 있는 탐색 모델이 개발되어 왔다. 본 연구에서는 암모니아 합성 및 분해용 반응 메커니즘에 대해서 알아보고, 고성능 및 경제적인 암모니아 합성 및 분해 촉매를 효율적으로 탐색할 수 있는 머신러닝 기반 방법에 대한 최신 연구 및 전망을 기술하였다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.1-1
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• 2003

It is clear that computers will play a key role in the biology of the future. Even now, it is virtually impossible to keep track of the key proteins, their names and associated gene names, physical constants(e.g. binding constants, reaction constants, etc.), and hewn physical and genetic interactions without computational assistance. In this sense, computers act as an auxiliary brain, allowing one to keep track of thousands of complex molecules and their interactions. With the advent of gene expression array technology, many experiments are simply impossible without this computer assistance. In the future, as we seek to integrate the reductionist description of life provided by genomic sequencing into complex and sophisticated models of living systems, computers will play an increasingly important role in both analyzing data and generating experimentally testable hypotheses. The future of bioinformatics is thus being driven by potent technological and scientific forces. On the technological side, new experimental technologies such as microarrays, protein arrays, high-throughput expression and three-dimensional structure determination prove rapidly increasing amounts of detailed experimental information on a genomic scale. On the computational side, faster computers, ubiquitous computing systems, high-speed networks provide a powerful but rapidly changing environment of potentially immense power. The challenges we face are enormous: How do we create stable data resources when both the science and computational technology change rapidly? How do integrate and synthesize information from many disparate subdisciplines, each with their own vocabulary and viewpoint? How do we 'liberate' the scientific literature so that it can be incorporated into electronic resources? How do we take advantage of advances in computing and networking to build the international infrastructure needed to support a complete understanding of biological systems. The seeds to the solutions of these problems exist, at least partially, today. These solutions emphasize ubiquitous high-speed computation, database interoperation, federation, and integration, and the development of research networks that capture scientific knowledge rather than just the ABCs of genomic sequence. 1 will discuss a number of these solutions, with examples from existing resources, as well as area where solutions do not currently exist with a view to defining what bioinformatics and biology will look like in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제2권2호
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• pp.63-81
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• 2008

WiMAX has been introduced as a competitive alternative for metropolitan broadband wireless access technologies. It is connection oriented and it can provide very high data rates, large service coverage, and flexible quality of services (QoS). Due to the large number of connections and flexible QoS supported by WiMAX, the uplink access in WiMAX networks is very challenging since the medium access control (MAC) protocol must efficiently manage the bandwidth and related channel allocations. In this paper, we propose and investigate a cost-effective WiMAX bandwidth management scheme, named the WiMAX partial sharing scheme (WPSS), in order to provide good QoS while achieving better bandwidth utilization and network throughput. The proposed bandwidth management scheme is compared with a simple but inefficient scheme, named the WiMAX complete sharing scheme (WCPS). A maximum entropy (ME) based analytical model (MEAM) is proposed for the performance evaluation of the two bandwidth management schemes. The reason for using MEAM for the performance evaluation is that MEAM can efficiently model a large-scale system in which the number of stations or connections is generally very high, while the traditional simulation and analytical (e.g., Markov models) approaches cannot perform well due to the high computation complexity. We model the bandwidth management scheme as a queuing network model (QNM) that consists of interacting multiclass queues for different service classes. Closed form expressions for the state and blocking probability distributions are derived for those schemes. Simulation results verify the MEAM numerical results and show that WPSS can significantly improve the network’s performance compared to WCPS.

• 응용통계연구
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• 제35권5호
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• pp.667-684
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• 2022

유전자 발현 데이터는 각 유전자에 대해 mRNA 양의 정도를 나타내고, 그러한 유전자 발현량에 대한 분석은 질병 발생에 대한 메커니즘을 이해하고 새로운 치료제와 치료 방법을 개발하는데 중요한 아이디어를 제공해오고 있다. 오늘날 DNA 마이크로어레이와 RNA-시퀀싱과 같은 고출력 기술은 수천 개의 유전자 발현량을 동시에 측정하는 것을 가능하게 하여 고차원성이라는 유전자 발현 데이터의 특징을 발생시켰다. 이러한 고차원성으로 인해 유전자 발현 데이터를 분석하기 위한 학습 모형들은 과적합 문제에 부딪히기 쉽고, 이를 해결하기 위해 차원 축소 또는 변수 선택 기술들이 사전 분석 단계로써 보통 사용된다. 특히, 사전 분석 단계에서 우리는 유전자 선택법을 이용하여 부적절하거나 중복된 유전자를 제거할 수 있고 중요한 유전자를 찾아낼 수도 있다. 현재까지 다양한 유전자 선택 방법들이 기계학습의 맥락에서 개발되어왔다. 본 논문에서는 기계학습 접근법을 사용하는 최근의 유전자 선택 방법들을 집중적으로 살펴보고자 한다. 또한, 현재까지 개발된 유전자 선택 방법들의 근본적인 문제점과 앞으로의 연구 방향에 대해 논의하고자 한다.