• Journal of the Korean Society of Safety
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• v.11 no.3
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• pp.143-153
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• 1996

Shutdown of boiler plants is a dynamic, complicated, and hazardous operation. Operational error is a major contributor to danserous situations during boiler plant shutdowns. It is important to develop an automatic system which synthesizes operating procedures to safely go from normal operation to complete shutdown. Knowledge representation for automatic shutdown of boiler plants makes use of the hierarchical, rule-based framework for heuristic knowledge, the semantic network, frame for process topology, and AI techniques such as rule matching, forward chaining, backward chaining, and searching. This knowledge representation and modeling account for the operational states, primitive operation devices, effects of their application, and planning methodology. Also, this is designed to automatically formulate subgoals, search for positive operation devices, formulate constraints, and synthesize shutdown procedures in boiler plants.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1647-1652
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• 2008

The PEGASIS protocol is more effective about energy consumption more than LEACH in USN environment. However, PEGASIS is weakness enemy in change of sensor network net composition because It changes BS node frequently. Therefore, we propose new routing protocol that use Sub-Cluster Chaining to solve this problem in this paper. It can reduce overhead that happen in election of middle node doing so and reduce energy consumption. Also, It can supplement limitation that PEGASIS has. This is treatise shows that new protocol that propose than existent PEGASIS through simulation is superior.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.2
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• pp.39-48
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• 2022

The application of digital technology to instrumentation and control systems in nuclear power plants has overcome many shortcomings of analog technology, but the threat of cybersecurity has increased. Along with other systems, the reactor protection system also uses digital-based equipment, so responding to cybersecurity threats is essential. We generally determine cybersecurity threats according to the role and function of the system. However, since the instrumentation and control system has various systems linked to each other, it is essential to analyze cybersecurity threats together between the connected systems. In this paper, we analyze the cybersecurity threat of the reactor protection system with the associated facilities. To this end, we quantitatively identified the risk of the reactor protection system by considering safety functions, a communication type, the use of analog or digital-based equipment of the associated systems, and the software vulnerability of the configuration module of the reactor protection system.

• Journal of Information Processing Systems
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• v.20 no.1
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• pp.24-37
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• 2024

To address the requirement for high-speed encryption of large amounts of data, this study improves the widely adopted cipher block chaining (CBC) mode and proposes a controllable parallel cipher block chaining (CPCBC) block cipher mode of operation. The mode consists of two phases: extension and parallel encryption. In the extension phase, the degree of parallelism n is determined as needed. In the parallel encryption phase, n cipher blocks generated in the expansion phase are used as the initialization vectors to open n parallel encryption chains for parallel encryption. The security analysis demonstrates that CPCBC mode can enhance the resistance to byte-flipping attacks and padding oracle attacks if parallelism n is kept secret. Security has been improved when compared to the traditional CBC mode. Performance analysis reveals that this scheme has an almost linear acceleration ratio in the case of encrypting a large amount of data. Compared with the conventional CBC mode, the encryption speed is significantly faster.

• Proceedings of the KOR-KST Conference
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• 2007.05a
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• pp.581-589
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• 2007

• Journal of KIISE
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• v.44 no.5
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• pp.496-502
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• 2017

Pointer Networks is a deep-learning model for the attention-mechanism outputting of a list of elements that corresponds to the input sequence and is based on a recurrent neural network (RNN). The coreference resolution for pronouns is the natural language processing (NLP) task that defines a single entity to find the antecedents that correspond to the pronouns in a document. In this paper, a pronoun coreference-resolution method that finds the relation between the antecedents and the pronouns using the Pointer Networks is proposed; furthermore, the input methods of the Pointer Networks-that is, the chaining order between the words in an entity-are proposed. From among the methods that are proposed in this paper, the chaining order Coref2 showed the best performance with an F1 of MUC 81.40 %. The method showed performances that are 31.00 % and 19.28 % better than the rule-based (50.40 %) and statistics-based (62.12 %) coreference resolution systems, respectively, for the Korean pronouns.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3010-3022
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• 1997

Expert system is one of AI area which was came out at the end of 19705s. It simulates the human's way of thinking to give solutions of Problem in many applications. Most expert system consists of many components such as inference engine, knowledge base, and so on. Especially the performance of expert system depends on the control of enfficiency of inference engine. Inference engine has to get features; tirst, if possible to minimize restrictions when the knowledge base is constructed second, it has to serve various kinds of inferencing methods. In this paper, we design and implement the inference engine which is able to support the general functions to knowledge domain and inferencing method. For the purpose, forward chaining, backward chaining, and direct chaining was employed as an inferencing method in order to be able to be used by user request selectively. Also we not on1y selected production system which makes one ease staradization and modulation to obtain knowledges in target domain, but also constructed knowledge base by means of Extended Clause Bit Metrics (ECBM). Finally, the performance evaluation of inference engine between Rete pattern matching and ECBM has been done.

• Korean Journal of Optics and Photonics
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• v.24 no.5
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• pp.262-270
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• 2013

In this paper, we propose a modified optical CBC(Cipher Block Chaining) encryption method using optical XOR logic operations. The proposed method is optically implemented by using dual encoding and a free-space interconnected optical logic gate technique in order to process XOR operations in parallel. Also, we suggest a CBC encryption/decryption optical module which can be fabricated with simple optical architecture. The proposed method makes it possible to encrypt and decrypt vast two-dimensional data very quickly due to the fast optical parallel processing property, and provides more security strength than the conventional electronic CBC algorithm because of the longer security key with the two-dimensional array. Computer simulations show that the proposed method is very effective in CBC encryption processing and can be applied to even ECB(Electronic Code Book) mode and CFB(Cipher Feedback Block) mode.

• Journal of KIISE:Databases
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• v.33 no.2
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• pp.151-162
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• 2006

RDF Semantics, one of W3C Recommendations, provides the RDFS entailment rules, which are used for the RDFS inference. Sesame, which is well known RDF repository, supports the RDBMS-based RDFS inference using the forward-chaining strategy. Since inferencing in the forward-chaining strategy is performed in the data loading time, the data loading time in Sesame is slow down be inferencing. In this paper, we propose the order scheme for applying the RDFS entailment rules to improve inference performance. The proposed application order makes the inference process terminate without repetition of the process for most cases and guarantees the completeness of inference result. Also the application order helps to reduce redundant results during the inference by predicting the results which were made already by previously applied rules. In this paper, we show that our approaches can improve the inference performance with comparisons to the original Sesame using several real-life RDF datasets.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.87-97
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• 2008

The traditional trip-based modeling approach has assumed that a trip is generated for a purpose. However, the approach has not considered trips as a set of connected trips nor has it considered trip chaining. The purpose of this study is to identify general characteristics of trip chaining, and to explore relationships between trip purposes and trip chains using multivariate regression models. The data for this study come from the 2006 Seoul household travel diary survey. It is found that simple trip chains are dominant phenomena, and socio-economic characteristics such as occupation, income, age, and gender are closely related to types of trip chains. People aged less than 20, females, or high-income people are more likely to have a higher number of home-based trip chains. In addition, commute and school trips for workers and students respectively tend to be strongly associated with simple trip chains, while shopping and leisure trips for housewives tend to be related to simple trip chains.