• Journal of KIISE
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• v.43 no.10
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• pp.1115-1123
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• 2016

Assumption-based truth maintenance system (ATMS) is a tool that maintains the reasoning process of inference engine. It also supports non-monotonic reasoning based on dependency-directed backtracking. Bookkeeping all the reasoning processes allows it to quickly check and retract beliefs and efficiently provide solutions for problems with large search space. However, the amount of data has been exponentially grown recently, making it impossible to use a single machine for solving large-scale problems. The maintaining process for solving such problems can lead to high computation cost due to large memory overhead. To overcome this drawback, this paper presents an approach towards incrementally maintaining the reasoning process of inference engine on cluster using Spark. It maintains data dependencies such as assumption, label, environment and justification on a cluster of machines in parallel and efficiently updates changes in a large amount of inferred datasets. We deployed the proposed ATMS on a cluster with 5 machines, conducted OWL/RDFS reasoning over University benchmark data (LUBM) and evaluated our system in terms of its performance and functionalities such as assertion, explanation and retraction. In our experiments, the proposed system performed the operations in a reasonably short period of time for over 80GB inferred LUBM2000 dataset.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.181-197
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• 2001

A heuristic method TABU-CSP using Tabu Search (TS) is described for solving Constraint Satisfaction Problems (CSPs). The method is started with a complete but inconsistent solution of a binary CSP and obtained in prespecified number of iterations either a consistent solution or a near optimal solution with an acceptable number of conflicts. The repair in the solution at each iterative step is done by using two heuristics alternatively. The first heuristic is a min-conflicts heuristic that chooses a variable with the maximum number of conflicts and reassigns it the value which leads to the minimum number of conflicts. If the acceptable solution is not reached after the search continued for a certain number of iterations, the min-conflict heuristic is changed and the variable selected least number of times is chosen for repair. If an acceptable solution is not reached, the method switches back to the min-conflict heuristic and proceeds further. This allowed the method to explore a different region of search space space for the solution as well as to prevent cycling. The demonstration of the method is shown on a toy problem [9]which has no solution. The method is then tested on various randomly generated CSPs with different starting solutions. The performance of the proposed method in terms of the average number of consistency is checked and the average number of conflicts is conflicts is compared with that of the Branch and Bound(BB) method used to obtain the same solution. In almost all cases, the proposed method moves faster to the acceptable solution than BB.

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1773-1780
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• 1996

KBANN (knowledge-based artificial neural network) combining the symbolic approach and the numerical approach has been shown to be more effective than other machine learning models. However KBANN doesn't have the theory refinement ability because the topology of network can't be altered dynamically. Although TopGen was proposed to extend the ability of KABNN in this respect, it also had some defects due to the link-ing of hidden nodes to input nodes and the use of beam search. The algorithm which could solve this TopGen's defects, by adding the hidden nodes linked to next layer nodes and using hill-climbing search with backtracking, is designed.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2435-2446
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• 1998

In this paper. We describe a dataflow model for efficient execution of a functional logic language and a method of translation a functional logic language into a dataflow graph. To explore parallelism and intelligent backtracking, we us model in which clause and function are represented as independent dataflow graph. The node denotes basic actions to be performed when the clause and function are executed. The dataflow mechanism allows an operation to be executed as soon as all its operands are available. Since the operations can never be executed earlier, a dataflow model is an excellent base for increasing execution speed. We did decrease a delay time with concurrent execution of dependency analysis and subgoal.

• Journal of the Korea Computer Industry Society
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• v.9 no.4
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• pp.171-176
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• 2008

Most booking techniques make a reservation without customer's preference on internet. These techniques have booking problems not to improve customer's preference in the service industry. We have tried to apply object-based scheduling technique to performing art reservation. For customer's satisfaction, we have considered customer's preferences in the reservation scheduling. The scheduling technique for performing art reservation proposed in this thesis is based on object-oriented concepts. To consider the over all satisfaction, the events of every object are alloted to the sitting plan board along its priority. To minimize backtracking or not to fail the allotment of events, we have scheduled to rise customer's preference in the scheduling.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.241-245
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• 1989

A knowledge based expert system is a computer program that emulates the reasoning process of a human expert in a specific problem domain. This paper presents an expert system to diagnose the various faults in power system. The developed expert system is represented considering two points; the possibility of solution and the fast processing speed. As uncertainties exist in the facts and rules which comprise the knowledge base of the expert system, Certainty Factor, which is based on the confirmation theory is used for the inexact reasoning. Also, as the diagnosis problem requires the inductive reasoning process in nature, the solution is imperfect and not unique in general. So the expert system is designed to generate all the possible hypothesis in order of the possibility and also it can explain the propagation procedure of the faults for each solution using the built in backtracking mechanism. In realization of the expert system, the processing speed is greatly dependent upon the problem representation, reasoning scheme and search strategy. So, in this paper the fault diagnosis problem itself is analysed from the view point of Artificial Intelligence and as a result, the expert system has the following basic features. 1) The certainty factor is adopted in the inference engine for inexact reasoning. 2) Problem apace is represented using the problem reduction technique. 3) Bidirectional reasoning scheme is used. 4) Best first search strategy is adopted for rapid processing. The expert system was developed us ing PROLOG language.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.130-137
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• 1990

The multipath multistage interconnection network is proposed which has the capability of dynamic rerouting. Construction of the network gets simpler, and the number of stages is reduced to $LOG_{2}$(N), so hardware complexity is reduced. This proposed algorithm makes it possible that destination adresses are used as routing tags, and it is easy to set up the path. Because this proposed network has a dynamic rerouting, backtracking is not necessary to set up another path when conflicts of switch faults are occurred. To estimate a performance, analytic methods are used and it is proved that probability of acceptance is improved in this Multipath MIN.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.131-136
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• 1990

In this paper, new methods are proposed which speed up the logical redundancy identification for the gate-level logic optimization. Redundancy indentification, as well as deterministic test pattern generation, can be viewed as a finite space search problem, of which execution time depends on the size of the search space. For the purpose of efficient search, we propose dynamic head line and mandatory assignment. Dynamic head lines are changed dynamically in the process of the redundancy identification. Mandatory assignement can avoid unnecessary assignment. They can reduce the search size efficiently. Especially they can be used even though the circuit is modified in the optimization procedure, that is different from the test pattern generation methods. Some experimental results are presented indicating that the proposed methods are faster than existing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.165-168
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• 2013

The USA has declared the cyber space as the 5th battlefield following land, sea, air, and space. In contrast to physical wars, in national cyberwarfare differentiation between friend and foe is impossible, and the boundaries between the lines of attack and defense are obscure. Therefore, to perform national cyberwarfare, credibility of all command delivery information performed in the cyber space should be confirmed. In this paper, the authors have determined the commands performed in national cyberwarfare, granted authorized IPv6 in space including the earth, moon and Mars for information credibility, and used LINK joints loaded with stealth functions to secure the credibility of command information.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.1
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• pp.1-8
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• 2015

In many image processing tasks, connected component labeling (CCL) is performed to extract regions of interest. CCL was usually done in a sequential fashion when image resolution was relatively low and there are small number of input channels. As image resolution gets higher up to HD or Full HD and as the number of input channels increases, sequential CCL is too time-consuming to be used in real time applications. To cope with this situation, parallel CCL framework was introduced where multiple cores are utilized simultaneously. Several parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method[1], modified 8 directional label selection (M8DLS) method[2], and HYBRID1 method[3]. Soh [3] showed that HYBRID1 outperforms NSZ-LE and M8DLS, and argued that HYBRID1 is by far the best. In this paper we propose an improved hybrid parallel CCL algorithm termed as HYBRID2 that hybridizes M8DLS with label backtracking (LB) and show that it runs around 20% faster than HYBRID1 for various kinds of images.