• Title, Summary, Keyword: Intelligent Vaccine

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Development of a Novel Subunit Vaccine Targeting Fusobacterium nucleatum FomA Porin Based on In Silico Analysis

  • Jeong, Kwangjoon;Sao, Puth;Park, Mi-Jin;Lee, Hansol;Kim, Shi Ho;Rhee, Joon Haeng;Lee, Shee Eun
    • International Journal of Oral Biology
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    • v.42 no.2
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    • pp.63-70
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    • 2017
  • Selecting an appropriate antigen with optimal immunogenicity and physicochemical properties is a pivotal factor to develop a protein based subunit vaccine. Despite rapid progress in modern molecular cloning and recombinant protein technology, there remains a huge challenge for purifying and using protein antigens rich in hydrophobic domains, such as membrane associated proteins. To overcome current limitations using hydrophobic proteins as vaccine antigens, we adopted in silico analyses which included bioinformatic prediction and sequence-based protein 3D structure modeling, to develop a novel periodontitis subunit vaccine against the outer membrane protein FomA of Fusobacterium nucleatum. To generate an optimal antigen candidate, we predicted hydrophilicity and B cell epitope parameter by querying to web-based databases, and designed a truncated FomA (tFomA) candidate with better solubility and preserved B cell epitopes. The truncated recombinant protein was engineered to expose epitopes on the surface through simulating amino acid sequence-based 3D folding in aqueous environment. The recombinant tFomA was further expressed and purified, and its immunological properties were evaluated. In the mice intranasal vaccination study, tFomA significantly induced antigen-specific IgG and sIgA responses in both systemic and oral-mucosal compartments, respectively. Our results testify that intelligent in silico designing of antigens provide amenable vaccine epitopes from hard-to-manufacture hydrophobic domain rich microbial antigens.

Development of Vaccine with Artificial Intelligence: By Analyzing OP Code Features Based on Text and Image Dataset (OP Code 특징 기반의 텍스트와 이미지 데이터셋 연구를 통한 인공지능 백신 개발)

  • Choi, Hyo-Kyung;Lee, Se-Eun;Lee, Ju-Hyun;Hong, Rae-Young;Choi, Won-Hyok;Kim, Hyung-Jong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.5
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    • pp.1019-1026
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    • 2019
  • Due to limitations of existing methods for detecting newly introduced malware, the importance of the development of artificial intelligence vaccines arises. Existing artificial intelligence vaccines have a disadvantage that the accuracy of the detection rate is low because those vaccines do not scan all parts of the file. In this paper, we suggest an enhanced method for detecting malware which is composed of unique OP Code features in the malware files. Specifically, we tested the method with text datasets trained on Random Forest algorithm and with image datasets trained on the Inception V3 model. As a result, the highest accuracy of the detection rate was about 80%.

A Study of Telematics Platform Realizatipn Strategy & Business Modelusing Tablet PC System (Tablet PC를 이용한 차세대 텔레메틱스 플랫폼 전략과 이를 응용한 비즈니스 모델에 관한 연구)

  • Kim Se-Joong;Kim Tae-Gyu
    • Management & Information Systems Review
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    • v.15
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    • pp.187-222
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    • 2004
  • The existing fixed telematics facilities for car were restricting of efficiency, utilization, communication, possibility, so it become disconnected with reality in the domestic and foreign market within thy near future, like as the case of 'car-phone'. It is too difficult to make a various business model on the restrict basis. To solve these problems, We suggested Tablet PC system as a new mobile telematics platform. The telematics platform based on the Tablet PC realize the perfect office, because it shows an excellent portability, high power and extension, various input equipment, and environment of communication in the car. To realize this concreteness, it needs a proper marketing strategy for a new business model. For this purpose, We analyzed the structure of industry, selected a proper target market, and established the strategy of marketing. Additionally, We proposed new business models ; particularly Portal site, Car-Home network, Car Software Tuning, and T-Vaccine(Intelligent Car Inspection System). These are made possible by the only Tablet PC platform.

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Adaptive Intrusion Detection Algorithm based on Artificial Immune System (인공 면역계를 기반으로 하는 적응형 침입탐지 알고리즘)

  • Sim, Kwee-Bo;Yang, Jae-Won
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.2
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    • pp.169-174
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    • 2003
  • The trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online, or an offline internet, so it is expected to make a problem more and more. The goal of intrusion detection is to identify unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators in real time. In fact, the general security system based on Internet couldn't cope with the attack properly, if ever. other regular systems have depended on common vaccine softwares to cope with the attack. But in this paper, we will use the positive selection and negative selection mechanism of T-cell, which is the biologically distributed autonomous system, to develop the self/nonself recognition algorithm and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. For making it come true, we will apply AIS to the network environment, which is a computer security system.

The Development of Clinical Decision Support System for Diagnosing Neurogenic Bladder

  • Batmunh, Nyambat;Chae, Young M.
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • pp.478-485
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    • 2001
  • In this study, we have developed a prototype of clinical decision support systems (CDSS) for diagnosing neurogenic bladder and compared its predicted diagnoses with the actual diagnoses using 92 patient\`s Urodynamic study cases. The CDSS was developed using a Visual Basic based on the evidence-based rules extracted from guidelines and other references regarding a diagnosis of neurogenic bladder. To compare with the 92 final diagnoses made by doctors at the Yonsei Rehabilitation Center, we classified all diagnoses into 5 groups. The predictive rates of the CDSS were: 48.0% for areflexic neurogenic bladder; 60.0% for hyperreflexic neurogenic bladder in a spinal shock recovery stage; 72.9% for hyperreflexic neurogenic bladder, and 80.0% for areflexic neurogenic bladder in a spinal shock stage, which was the highest predicted rate. There were only 2 cases for hyperreflexic neurogenic bladder in a well controlled detrusor activity, and its predictive rate was 0%. The study results showed that CDSS for diagnosing neurogenic bladder could provide a helpful advice on decision-making for doctors. The findings also suggest that physicians should be involved in all development stages to ensure that systems are developed in a fashion that maximizes their beneficial effect on patient care, and that systems are acceptable to both professionals and patients. The future studies will concentrate on including more validating the system.

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Design and Implementation of a Cloud-Based Recovery System against Ransomware Attacks (클라우드 기반 랜섬웨어 복구 시스템 설계 및 구현)

  • Ha, Sagnmin;Kim, Taehoon;Jung, Souhwan
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.27 no.3
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    • pp.521-530
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    • 2017
  • In this paper, we propose a protection solution against intelligent Ransomware attacks by encrypting not only source files but also backup files of external storage. The system is designed to automatically back up to the cloud server at the time of file creation to perform monitoring and blocking in case a specific process affects the original file. When client creates or saves a file, both process identifiers, parent process identifiers, and executable file hash values are compared and protected by the whitelist. The file format that is changed by another process is monitored and blocked to prevent from suspicious behavior. By applying the system proposed in this paper, it is possible to protect against damage caused by the modification or deletion of files by Ransomware.

Naming Scheme for Standardization of Detection Rule on Security Monitoring Threat Event (보안관제 위협 이벤트 탐지규칙 표준 명명법 연구)

  • Park, Wonhyung;Kim, Yanghoon;Lim, YoungWhan;Ahn, Sungjin
    • Convergence Security Journal
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    • v.15 no.4
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    • pp.83-90
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    • 2015
  • Recent, Cyber attacks such as hacking and malicious code techniques are evolving very rapidly changing cyber a ttacks are increasing, the number of malicious code techniques vary accordingly become intelligent. In the case of m alware because of the ambiguity in the number of malware have increased rapidly by name or classified as maliciou s code may have difficulty coping with. This paper investigated the naming convention of the vaccine manufacturer s in Korea to solve this problem, the analysis and offers a naming convention for security control event detection r ule analysis to compare the pattern of the detection rule out based on this current.

The Classification System and Information Service for Establishing a National Collaborative R&D Strategy in Infectious Diseases: Focusing on the Classification Model for Overseas Coronavirus R&D Projects (국가 감염병 공동R&D전략 수립을 위한 분류체계 및 정보서비스에 대한 연구: 해외 코로나바이러스 R&D과제의 분류모델을 중심으로)

  • Lee, Doyeon;Lee, Jae-Seong;Jun, Seung-pyo;Kim, Keun-Hwan
    • Journal of Intelligence and Information Systems
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    • v.26 no.3
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    • pp.127-147
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    • 2020
  • The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.