• Journal of Korea Multimedia Society
• /
• v.8 no.8
• /
• pp.1119-1133
• /
• 2005

As a very important part in development of the protocol, verification and conformance test for protocol specification are complementary techniques that are used to increase the level of confidence in the system functions as prescribed by their specifications. In this paper, we verify the safety and liveness properties of rail signal control protocol type 1 specified in LTS with model checking method, and experimentally prove that it is possible to check for the deadlock, livelock and rechability of the states and actions on LTS. The implemented formal checker is able to verify whether properties expressed in modal logic are true in specifications using modal mu-calculus. We also propose a formal method on generation of conformance test cases using the concept of UIO sequences from verified protocol specification. The suggested tools are implemented by C++ language under Windows NT.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2008.11a
• /
• pp.694-697
• /
• 2008

A retaining wall system suitable for a construction project is selected on the basis of subsoil conditions. If the decision-maker selects an improper system, it has a negative effect on the cost and schedule of the construction project. There have been many studies related to the models and processes for selecting optimal retaining wall systems. However, engineers who are not familiar with formal analysis methods could not easily utilize the formal methods proposed by previous studies. In order to overcome this problem, we developed a web-based decision support system called Dr. Underground, which is both physically and technically easily accessible by engineers. Dr. Underground was developed based on a selection method developed from a precedent research project. It was developed using a server-side web language ASP.NET and MS Access as a database. Decision-makers can input data about the building's condition, construction site conditions and adjacent site conditions in this system. Based on the input data, Dr. Underground recommends an optimal retaining wall system for the inputted conditions and provides detail information on the system.

• Proceedings of the Korea Society for Simulation Conference
• /
• 1994.10a
• /
• pp.7-8
• /
• 1994

최근 들어 원자재, 재공품 또는 완제품을 신속하고 정확하게 공급/배분하기 위해 저장과 인출을 담당하는 Material Handling System을 이용하여 작업자의 개입요소를 줄이며, 제고관리 Computer를 이용하여 입고/출고 명령을 유효적절하게 처리하는 ASRS(Atomated Storage and Retreival System : 자동창고 시스템)가 널리 공급되고 있다. 중앙은행의 현금창고, 병원의 약품창고, 식품/화장품 회사의 배송창고, 군수물자의 군납창고에 이르기까지 물품의 저장 또는 공급의 필용성을 갖는 곳에서는 어디든지 찾아볼 수 있는 ASRS는 가깝게는 관공소나 대형빌딩의 주차장에도 이의 개념이 도입되어 사용됨을 볼 수 있다. 최근의 인금인상, 구인난등의 이유로 ASRS설치는 계속 증가할 추세에 있으나 자동 창고 시스템을 설치하기 위해서는 막대한 초기 투자가 필요하며 시스템의 설계 및 설치후 운영에 대한 연구가 반드시 필요하다. ASRS의 운영 Rule 검증, 수행능력 분석등의 목적을 갖는 연구에는 여러 접근방법이 있을 수 있으나 구성 설비와 운영 Rule의 복잡한 관계로 컴퓨터 시뮬레이션의 거의 유일한 문제해결 방법이다. ASRS의 Modeling에 관한 기존의 연구로는 수리모델 수립. 이산사건 시스템의 관점에서 event-graphy, petri-net을 이용한 modeling이 있으며 ASRS에 대한 전용 Simulator 개발등이 진행되었다. 본 연구의 대상 시스템은 2개의 Rack과 하나의 Stacker Crane 으로 구성된 Aisle과 입출고의 물류를 처리하는 순환 RGVS(Rail Guided Vehicle System), 입/출고장을 구성하는 Conveyor Net등으로 이루어진 제조-물류시스템의 일반적인 ASRS이다. 또 이 ASRS의 입/출고 방식은 전수 입/출고만을 포함하며 Blocking 방지를 위한 Capaicty 예약, 다중설비 선택등의 문제등을 고려하고 있다. 본 연구의 접근방법으로는 ASRS의 개념적인 Reference Model을 수립하고 이 Reference Model에 대한 Formal Model로 DEVS(Discrete Event System Specification)을 이용하여 시스템을 Modeling하였다. 이의 Computer Simulation을 위하여 DEVS형식론 환경에서의 Simulation Language인 DEVSim ++ⓒ를 이용하여 시스템을 구현하였다.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.4
• /
• pp.739-751
• /
• 2019

Security in embedded devices has become a significant issue. Threats on the sup-ply chain, like using counterfeit components or inserting backdoors intentionally are one of the most significant issues in embedded devices security. To mitigate these threats, high-level security evaluation and certification more than EAL (Evaluation Assurance Level) 5 on CC (Common Criteria) are necessary on hardware components, especially on the cryptographic module such as AES. High-level security evaluation and certification require detecting covert channel such as backdoors on the cryptographic module. However, previous studies have a limitation that they cannot detect some kinds of backdoors which leak the in-formation recovering a secret key on the cryptographic module. In this paper, we present an expanded definition of backdoor on hardware AES module and show how to detect the backdoor which is never detected in Verilog HDL using model checker NuSMV.

• Journal of Internet Computing and Services
• /
• v.21 no.1
• /
• pp.127-135
• /
• 2020

As the importance of the use and analysis of big data is emerging, there is a growing interest in natural language processing techniques for unstructured data such as news articles and comments. Particularly, as the collection of big data becomes possible, data mining techniques capable of pre-processing and analyzing data are emerging. In this case study with a telecom company, we propose a methodology how to formalize unstructured data using text mining. The domain is determined as equipment failure and the data is about 2.2 million equipment check ledger data. Data on equipment failures by 800,000 per year is accumulated in the equipment check ledger. The equipment check ledger coexist with both formal and unstructured data. Although formal data can be easily used for analysis, unstructured data is difficult to be used immediately for analysis. However, in unstructured data, there is a high possibility that important information. Because it can be contained that is not written in a formal. Therefore, in this study, we study to develop digital transformation method for unstructured data in equipment check ledger.

• Journal of KIISE:Databases
• /
• v.32 no.2
• /
• pp.111-119
• /
• 2005

Electronic catalog contains ich semantics associated with products, and serves as a challenging practical domain for ontology application. Ontology is concerned with the nature and relations of being. It can play a crucial role in e-commerce as a formalization of e-Catalogs. Description Logics provide a theoretical core for most of the current ontology languages. In this paper, we present an ontological model of e-Catalogs in DL. We take an Extended Entity Relationship approach for conceptual modeling method, and present the fundamental set of modeling constructs and corresponding description language representation for each construct. Additional semantic knowledge can be represented directly in DL. Our modeling language stands within SHIQ(d) which is known reasonably practical with regard to its expressiveness and complexity. We illustrate sample scenarios to show how our approach may be utilized in modeling e-Catalogs, and also implement the scenarios through a DL inference tool to see the practical feasibility.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.6
• /
• pp.721-729
• /
• 2006

Numbers of research on ontology construction and its application are being done for knowledge and information processing using computers. But, the current ontology development methods and ontology construction tools are using in restricted field on propose. Therefore, proper ontology development processes and ontology construction tools on ontology characteristic are needed. In this paper, we propose ontology construction process(OntoProcess) that non-experts in specific field are able to construct ontology through conceptualization of knowledge and formalization of concepts from language resource. Beside, some problems may be occurred while numbers of people are working together to construct ontology: i)duplicated concept definition in conceptualization process of knowledge and ii)decreasing efficiency of ontology construction by short understanding about formal language and tool operation in formalization process. To solve the problems, we propose an ontology construction process for multiple developers (OntoProcess) using meta ontology. We develop an ontology construction system(OntoCS) based on proposed processes, and we show the efficiency of proposed processes and system from ontology construction experiment.

• Korean Journal of Audiology
• /
• v.25 no.3
• /
• pp.119-123
• /
• 2021

Background and Objectives: The influence of music training on different areas of the brain has been extensively researched, but the underlying neurobehavioral mechanisms remain unknown. In the present study, the effects of training for more than three years in Carnatic music (an Indian form of music) on the discrimination ability of different areas of the brain were tested using P300 analysis at three electrode placement sites. Subjects and Methods: A total of 27 individuals, including 13 singers aged 16-30 years (mean±standard deviation, 23±3.2 years) and 14 non-singers aged 16-30 years (mean age, 24±2.9 years), participated in this study. The singers had 3-5 years of formal training experience in Carnatic music. Cortical activities in areas corresponding to attention, discrimination, and memory were tested using P300 analysis, and the tests were performed using the Intelligent Hearing System. Results: The mean P300 amplitude of the singers at the Fz electrode placement site (5.64±1.81) was significantly higher than that of the non-singers (3.85±1.60; t(25)=3.3, p<0.05). The amplitude at the Cz electrode placement site in singers (5.90±2.18) was significantly higher than that in non-singers (3.46±1.40; t(25)=3.3, p<0.05). The amplitude at the Pz electrode placement site in singers (4.94±1.89) was significantly higher than that in non-singers (3.57±1.50; t(25)=3.3, p<0.05). Among singers, the mean P300 amplitude was significantly higher in the Cz site than the other placement sites, and among non-singers, the mean P300 amplitude was significantly higher in the Fz site than the other placement sites, i.e., music training facilitated enhancement of the P300 amplitude at the Cz site. Conclusions: The findings of this study suggest that more than three years of training in Carnatic singing can enhance neural coding to discriminate subtle differences, leading to enhanced discrimination abilities of the brain, mainly in the generation site corresponding to Cz electrode placement.

• Journal of Audiology & Otology
• /
• v.25 no.3
• /
• pp.119-123
• /
• 2021

Background and Objectives: The influence of music training on different areas of the brain has been extensively researched, but the underlying neurobehavioral mechanisms remain unknown. In the present study, the effects of training for more than three years in Carnatic music (an Indian form of music) on the discrimination ability of different areas of the brain were tested using P300 analysis at three electrode placement sites. Subjects and Methods: A total of 27 individuals, including 13 singers aged 16-30 years (mean±standard deviation, 23±3.2 years) and 14 non-singers aged 16-30 years (mean age, 24±2.9 years), participated in this study. The singers had 3-5 years of formal training experience in Carnatic music. Cortical activities in areas corresponding to attention, discrimination, and memory were tested using P300 analysis, and the tests were performed using the Intelligent Hearing System. Results: The mean P300 amplitude of the singers at the Fz electrode placement site (5.64±1.81) was significantly higher than that of the non-singers (3.85±1.60; t(25)=3.3, p<0.05). The amplitude at the Cz electrode placement site in singers (5.90±2.18) was significantly higher than that in non-singers (3.46±1.40; t(25)=3.3, p<0.05). The amplitude at the Pz electrode placement site in singers (4.94±1.89) was significantly higher than that in non-singers (3.57±1.50; t(25)=3.3, p<0.05). Among singers, the mean P300 amplitude was significantly higher in the Cz site than the other placement sites, and among non-singers, the mean P300 amplitude was significantly higher in the Fz site than the other placement sites, i.e., music training facilitated enhancement of the P300 amplitude at the Cz site. Conclusions: The findings of this study suggest that more than three years of training in Carnatic singing can enhance neural coding to discriminate subtle differences, leading to enhanced discrimination abilities of the brain, mainly in the generation site corresponding to Cz electrode placement.

• ETRI Journal
• /
• v.44 no.4
• /
• pp.573-587
• /
• 2022

The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO₂ fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.