• Journal of applied mathematics & informatics
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• v.37 no.5_6
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• pp.459-467
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• 2019

In this work, via Orlicz functions, we have obtained a generalization of rough statistical convergence of asymptotically equivalent triple sequences a new non-matrix convergence method, which is intermediate between the ordinary convergence and the rough statistical convergence. We also have examined some inclusion relations related to this concept. We obtain the results are non negative real numbers with respect to the partial order on the set of real numbers.

• Journal of the Korean Mathematical Society
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• v.58 no.1
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• pp.69-90
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• 2021

In this paper, we prove weighted norm inequalities for rough singular integrals along surfaces with radial kernels h and sphere kernels Ω by assuming h ∈ △γ(ℝ+) and Ω ∈ ����β(Sn-1) for some γ > 1 and β > 1. Here Ω ∈ ����β(Sn-1) denotes the variant of Grafakos-Stefanov type size conditions on the unit sphere. Our results essentially improve and extend the previous weighted results for the rough singular integrals and the corresponding maximal truncated operators.

• Journal of the Korean Mathematical Society
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• v.48 no.4
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• pp.703-725
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• 2011

In this paper, we establish the vector-valued inequalities for the commutators of singular integrals with rough kernels. In particular, our results can essentially improve some well-known results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.337-339
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• 1996

In this paper, we construct rough relational database model using approximation concepts of rough set. Also, we analyze the relation between objects, attributes and attribute values and, propose the method that can generate flexible retrieval results.

• Applied Microscopy
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• v.18 no.2
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• pp.141-152
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• 1988

The developmental processes of the protein body are studied on endosperm cells of Panax ginseng during seed maturation periods. The spherosome, mitochondria, rough endoplasmic reticulum, and ribosome are observed and then are gradually increased in early endosperm cells. Protein body developed from vesicles produced by the rough endoplasmic reticulum and was formed at the enlarged ends of rough endoplasmic reticulum. Also, vacuole-like protein body was observed in associated with rough endoplasmic reticulum. Golgi complex is observed in associated with vacuole and its vesicles containing proteinaceous granules moved and accumulated to the vacuole. Proteinaceous granules are deposited in the spherical or oval shaped vacuole and gradually, vacuole is surrounded by the multi-membranous structure. Rough endoplasmic reticulum, ribosome, Golgi complex, and vacuole are observed in associated with protein body formation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.296-301
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• 1998

The Rough Set theory suggested by Pawlak in 1982 has been useful in AI, machine learning, knowledge acquisition, knowledge discovery from databases, expert system, inductive reasoning. etc. The main advantages of rough set are that it does not need any preliminary or additional information about data and reduce the superfluous informations. but it is a significant disadvantage in the real application that the inference result form is not the real control value but the divided disjoint interval attribute. In order to overcome this difficulty, we will propose approach in which Rough set theory and Neuro-fuzzy fusion are combined to obtain the optimal rule base from lots of input/output datum. These results are applied to the rule construction for infering the temperatures of refrigerator's specified points.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.1
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• pp.13-19
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• 2017

In modern industry, the machining process is very important for manufacturing various products. More than 80% of machining processes apply rough cutting. The target of this study is to establish the optimal condition of rough cutting using trochoidal motion for improving productivity. For research, the range of cutting conditions is defined by trochoidal motion. The cutting time and tolerance are measured and evaluated according to the cutting conditions of machining. Experimental data are utilized for comparing trochoidal motion and contouring. It is found that the cutting time of trochoidal motion is two times less than that of contouring with optimal cutting conditions. To conclude, trochoidal motion for rough cutting under appropriate cutting conditions improves productivity and shortens processing time significantly.

• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.19-27
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• 1997

This paper presents rough cut tool path planning for the fewer-axis machine consisting of a three-axis CNC machine and a rotary indexing table. In the problem dealt with in this paper, the tool orientation is "intermediately" changed, distinguished from the conventional problem where the tool orientation is assumed to be fixed. The developed rough cut path planning algorithm tries to minimize the number of tool orientation (setup) changes together with tool changes and the machining time for the rough cut by the four procedures: a) decomposition of the machining area based on the possibility of tool interference (via convex hull operation), b) determination of the optimal tool size and orientation (via network graph theory and branch-and bound algorithm), c) generation of tool path for the tool and orientation (based on zig-zag pattern), and d) feedrate adjustment to maintain the cutting force at an operation level (based on average cutting force). The developed algorithms are validated via computer simulations, and can be also used in pure fiveaxis machining environment without modification.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.331-337
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• 1997

In this paper we will discuss a type of inductive learning called learning from examples, whose task is to induce general descriptions of concepts from specific instances of these concepts. In many real life situations however new instances can be added to the set of instances. It is first proposed within the framework of rough set theory, for such cases, an algorithm to find minimal set of rules for decision tables without recalculation for overall set of instances. The method of learning presented here is based on a rough set concept proposed by Pawlak[2]. It is shown an algorithm to fund minimal set of rules using reduct change theorems giving criteria for minimum recalculation and an illustrative example.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.441-447
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• 2001

In general, Rough Set theory is used for classification, inference, and decision analysis of incomplete data by using approximation space concepts in information system. Information system can include quantitative attribute values which have interval characteristics, or incomplete data such as multiple or unknown(missing) data. These incomplete data cause tole inconsistency in information system and decrease the classification ability in system using Rough Sets. In this paper, we present various types of incomplete data which may occur in information system and propose INcomplete information Processing System(INiPS) which converts incomplete information system into complete information system in using Rough Sets.