• Bulletin of the Korean Mathematical Society
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• v.53 no.1
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• pp.263-272
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• 2016

By using the finite projective geometry method, the separating properties of linear constant-weight codes are presented. An algorithm is given for computing the cardinality of separating coordinate positions of certain disjoint codeword sets of linear constant-weight codes.

• Honam Mathematical Journal
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• v.28 no.1
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• pp.1-22
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• 2006

First, we obtain some results of intuitionistic fuzzy congruences on a regular semigroups contained in ($XH,\;XH^c$). Secondly, we introduce the concept of intuitionistic fuzzy idempotent separating congruences on a semigroup and investigate some of it's properties.

• The Pure and Applied Mathematics
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• v.12 no.4 s.30
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• pp.253-274
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• 2005

An additive regular Semiring S is left inversive if the Set E+ (S) of all additive idempotents is left regular. The set LC(S) of all left inversive semiring congruences on an additive regular semiring S is a lattice. The relations $\theta$ and k (resp.), induced by tr. and ker (resp.), are congruences on LC(S) and each $\theta$-class p$\theta$ (resp. each k-class pk) is a complete modular sublattice with $p_{min}$ and $p_{max}$ (resp. With $p^{min}$ and $p^{max}$), as the least and greatest elements. $p_{min},\;p_{max},\;p^{min}$ and $p^{max}$, in particular ${\epsilon}_{max}$, the maximum additive idempotent separating congruence has been characterized explicitly. A semiring is quasi-inversive if and only if it is a subdirect product of a left inversive and a right inversive semiring.

• Journal of Biosystems Engineering
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• v.42 no.4
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• pp.242-250
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• 2017

Purpose: This study was conducted to determine the appropriate operating conditions through a factorial experiment for the secondary separating part of the self-propelled pepper harvester. Methods: An experimental setup that simulates the secondary separating part of the self-propelled pepper harvester was organized. Test samples were classified into three types according to the number of peppers on a stem, and 12 sets were prepared for each type. Among the operating conditions of the secondary separating part, the rotational speed of drum B (four levels), radial clearance between drums and cylindrical teeth (three levels), and speed ratio between the three drums (two levels) were set as the test factors, and tests were repeated three times for different levels of each factor. The appropriate operating conditions were determined by analyzing the separation ratio and damage ratio of the peppers collected through the secondary separating part. Results: The test factors changed the overall separation ratio and overall damage ratio in similar trends. In other words, the conditions that caused high overall separation ratios also exhibited high overall damage ratios. Owing to the high overall damage ratio in the condition with the highest overall separation ratio, the operating conditions should be selected considering both ratios. Conclusions: When the condition with more than 60% of overall separation ratio and less than 15% of overall damage ratio was considered as the appropriate operating condition, 70 rpm of the rotational speed of drum B, 5 mm of the radial clearance between drums and cylindrical teeth, and 7:3:5 for the speed ratio of the three drums A, B, and C should be applied for the secondary separating part used in this study. Supplementary studies will be required in the future to find optimal operating conditions through the actual field test under further divided test factors.

• Bulletin of the Korean Mathematical Society
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• v.31 no.2
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• pp.173-180
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• 1994

Let H be a separable, infinite dimensional, compled Hilbert space and let L(H) be the algebra of all bounded linear operators on H. A dual algebra is a subalgebra of L(H) that contains the identity operator $I_{H}$ and is closed in the ultraweak topology on L(H). Note that the ultraweak operator topology coincides with the wea $k^{*}$ topology on L(H)(see [3]). Bercovici-Foias-Pearcy [3] studied the problem of solving systems of simultaneous equations in the predual of a dual algebra. The theory of dual algebras has been applied to the topics of invariant subspaces, dilation theory and reflexibity (see [1],[2],[3],[5],[6]), and is deeply related with properties ( $A_{m,n}$). Jung-Lee-Lee [7] introduced n-separating sets for subalgebras and proved the relationship between n-separating sets and properties ( $A_{m,n}$). In this paper we will study the relationship between direct sum and properties ( $A_{m,n}$). In particular, using some results of [7] we obtain relationship between n-separating sets and direct sum of von Neumann algebras.ras.s.ras.

• Honam Mathematical Journal
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• v.29 no.1
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• pp.101-118
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• 2007

The notions of digital k-homotopy equivalence and digital ($k_0,k_1$)-homotopy equivalence were developed in [13, 16]. By the use of the digital k-homotopy equivalence, we can investigate digital k-homotopy equivalent properties of Cartesian products constructed by the minimal simple closed 4- and 8-curves in $\mathbf{Z}^2$.

• International Journal of Contents
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• v.12 no.2
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• pp.42-48
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• 2016

We present efficient algorithms for computing centroid directions for each of the three types of monotonicity in a polyhedron: strong, weak, and directional monotonicity, which can be used for optimizing directions in many 3D manufacturing processes. Strongly- and directionally-monotone directions are the poles of great circles separating a set of spherical polygons on the unit sphere, the centroids of which are shown to be obtained by applying the previous result for determining the maximum intersection of the set of their dual spherical polygons. Especially in this paper, we focus on developing an efficient method for approximating the weakly-monotone centroid, which is the pole of one of the great circles intersecting a set of spherical polygons on the unit sphere. The original problem is approximately reduced into computing the intersection of great bands for avoiding complicated computational complexity of non-convex objects on the unit sphere, which can be realized with practical linear-time operations.

• Biomolecules & Therapeutics
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• v.15 no.2
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• pp.123-126
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• 2007

A sensitive, simple and highly selective liquid chromatography method of determination for extraction of pseudoephedrine hydrochloride from Allegra D tablet was developed. The chief benefit of the present method is the minimal sample preparation, as the procedure is only filtering through pore syringe filter. Two drugs (pseudoephedrine hydrochloride, fexofenadine) were separated on a C$_{18}$ column and analyzed by high performance liquid chromatography (HPLC). The method had a chromatographic run time of 8.0 min. 1 ml of pseudoephedrine hydrochloride solution (1 mg/ml) was filtered through 0.22 um pore syringe filter. 50 ul of filtering solution was injected to HPLC pump and we knew the retention time (1.85 min) of separating of pseudoephedrine hydrochloride using UV detector at 280 nm. We used C$_{18}$ column (4.6 mm${\times}$250 mm), mobile phase solution (<0.05 mol/L NaH$_2$PO$_4$, 2 ml/L H$_3$PO$_4$>/CH$_3$CN / sodium dodesyl sulfate = 60 ml / 40 ml / 1 g). We separated psedoephedrine hydrochloride at run time of 1.85 min from Allegra D tablet solution (1 mg/ml) filtered through 0.22 um pore syringe filter using UV detector at 280 nm. Flow rate was set at 1.0 ml/min and the column temperature was set at 40$^{\circ}C$. Psedoephedrine hydrochloride solution (1 mg/ml) separated from Allegra D tablet was filtered through 0.22 um pore syringe filter and injected 50 ul. We confirmed the peak of psedoephedrine hydrochloride at same retention time and the separating solution was freeze-dried. In conclusion, A simple isocratic reverse-phase HPLC method has been developed that provides excellent separation of pseudoephedrine from Allegra D tablet.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3378-3393
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• 2014

We have witnessed the rapid development of information technology in recent years. One of the key phenomena is the fast, near-exponential increase of data. Consequently, most of the traditional data classification methods fail to meet the dynamic and real-time demands of today's data processing and analyzing needs--especially for continuous data streams. This paper proposes an improved incremental learning algorithm for a large-scale data stream, which is based on SVM (Support Vector Machine) and is named DS-IILS. The DS-IILS takes the load condition of the entire system and the node performance into consideration to improve efficiency. The threshold of the distance to the optimal separating hyperplane is given in the DS-IILS algorithm. The samples of the history sample set and the incremental sample set that are within the scope of the threshold are all reserved. These reserved samples are treated as the training sample set. To design a more accurate classifier, the effects of the data volumes of the history sample set and the incremental sample set are handled by weighted processing. Finally, the algorithm is implemented in a cloud computing system and is applied to study user behaviors. The results of the experiment are provided and compared with other incremental learning algorithms. The results show that the DS-IILS can improve training efficiency and guarantee relatively high classification accuracy at the same time, which is consistent with the theoretical analysis.

• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.365-370
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• 2017

This study analyze correlation between weekdays data and special days data of different power demand patterns, and builds a separate data set, and suggests ways to reduce power demand prediction error by using deep learning network suitable for each data set. In addition, we propose a method to improve the prediction rate by adding the environmental elements and the separating element to the meteorological element, which is a basic power demand prediction elements. The entire data predicted power demand using LSTM which is suitable for learning time series data, and the special day data predicted power demand using DNN. The experiment result show that the prediction rate is improved by adding prediction elements other than meteorological elements. The average RMSE of the entire dataset was 0.2597 for LSTM and 0.5474 for DNN, indicating that the LSTM showed a good prediction rate. The average RMSE of the special day data set was 0.2201 for DNN, indicating that the DNN had better prediction than LSTM. The MAPE of the LSTM of the whole data set was 2.74% and the MAPE of the special day was 3.07 %.