• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.178-182
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• 2002

For action selection as well as teaming, simple associations between stimulus and response have been employed in most of literatures. But, for successful task accomplishment, it is required that artificial life system can team and express behavioral sequences. In this paper, we propose a novel action-selection-mechanism to deal with behavioral sequences. For this, we define behavioral motivation as a primitive node for action selection, and then hierarchically construct a tree with behavioral motivations. The vertical path of the tree represents behavioral sequences. Here, such a tree for our proposed ASM can be newly generated and/or updated, whenever a new behavioral sequence is learned. To show the validity of our proposed ASM, three 2-D grid world simulations will be illustrated.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.22-24
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• 2001

This paper presents a fault phase selection algorithm for transmission line protection by means of the symmetrical components. Accurate fault phase selection is necessary for collect functioning of transmission line relaying, particularly in Extra High Voltage (EHV) networks. The conventional phase selection algorithm used the phase difference between positive and negative sequence current excluding load current. But, it is difficult to abstract only fault current since we can not know the time which a fault occurs. The proposed algorithm can select the accurately fault phase using fault current contained pre-fault current.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.25-30
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• 1989

This study is concerned with a job sequencing method using the concept of sampling technique. This sampling technique has never been applied to develop the scheduling algorithms. The most job sequencing algorithms have been developed to determine the best or good solution under the special conditions. Thus, it is not only very difficult, but also taken too much time to develop the appropriate job schedules that satisfy the complex work conditions. The application areas of these algorithms are also very narrow. Under these circumstances it is very desirable to develop a simple job sequencing method which can produce the good solution with the short tine period under any complex work conditions. It is called a sampling job sequencing method in this study. This study is to examine the selection of the good job sequence of 1%-5% upper group by the sampling method. The result shows that there is the set of 0.5%-5% job sequence group which has to same amount of performance measure with the optimal job sequence in the case of experiment of 2/n/F/F max. This indicates that the sampling job sequencing method is a useful job sequencing method to find the optimal or good job sequence with a little effort and time consuming. The results of ANOVA show that the two factors, number of jobs and the range of processing time are the significant factors for determining the job sequence at $\alpha$=0.01. This study is extended to 3 machines to machines job shop problems further.

• Journal of Korean Society for Quality Management
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• v.17 no.1
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• pp.69-81
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• 1989

This study is concerned with a job sequencing method using the concept of sampling technique in the case of Job Shop. This is the follow study of Kang and Ro (1988) which examined the possibility of application of sampling technique to determine the Job Sequence in the case of Flow Shop. Not only it is very difficult, but also it takes too much time to develop the appropriate job schedules that satisfy the complex work conditions. The most job sequencing algorithms have been developed to determine the best or good solution under the special conditions or assumptions. The application areas of these algorithms are also very narrow, so it is very hard to find the appropriate algorithm which satisfy the complex work conditions. In this case it is very desirable to develop a simple job sequencing method which can select the optimal job sequence or near optimal job sequence with a little effort. This study is to examine the effect of sampling job sequencing which can select the good job of 0.01%~5% upper good group. The result shows that there is the sets of 0.05%~23% job sequence group which has the same amount of performance measure with the optimal job sequence in the case of experiment of N/M/G/$F_{max}$. This indicates that the sampling job sequencing method is a useful job sequencing method to find the optimal or good job sequence with consuming a small amount of time. The results of ANOVA show that the only one factor, number of machines is the significant factor for determining the job sequence at ${\alpha}=0.01$. It takes about 10 minutes to compare the number of 10,000 samples of job sequence by personal computer and it is proved that the selection rate of the same job sequence with optimal job sequence is 23.0%, 3.9% and 0.065% in the case of 2 machines, 3 machines and 4 machines, respectively. The area of application can readily be extended to the other work condition.

• Journal of IKEEE
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• v.22 no.3
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• pp.658-663
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• 2018

In this paper, we consider node deployment algorithms for the sequence-based localization (SBL) which is recently employed for in-door positioning systems, Whereas previous node selection or deployment algorithms seek to place nodes at centrold of the region where more targets are likely to be found, we observe that the boundaries dividing such regions can be good locations for the nodes in SBL systems. Motivated by this observation, we propose an efficient node deployment algorithm that determines the boundaries by using the well-known K-means algorithm and find the potential node locations based on the bi-section method for low-complexity design. We demonstrate through experiments that the proposed algorithm achieves significant localization performance over random node allocation with a substantially reduced complexity as compared with a full search.

• Molecules and Cells
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• v.25 no.4
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• pp.467-478
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• 2008

Simple sequence repeats (SSRs) and interSSR (ISSR) marker systems were used in this study to reveal genetic changes induced by artificial selection for short/long larval duration in the tropical strain Nistari of the silkworm Bombyx mori. Artificial selection separated longer larval duration (LLD) ($29.428{\pm}0.723days$) and shorter larval duration (SLD) ($22.573{\pm}0.839days$) lines from a base, inbred population of Nistari (larval span of $23.143{\pm}0.35days$). SSR polymorphism was observed between the LLD and SLD lines at one microsatellite locus, Bmsat106 ($CA_7$) and at two loci of 1074 bp and 823 bp generated with the ISSR primer UBC873. Each of these loci was present only in the LLD line. The loci segregated in the third generation of selection and were fixed in opposite directions. In the $F_2$ generation of the $LLD{\times}SLD$ lines, the alleles of Bmsat106 and $UBC873_{1074bp}$ segregated in a 1:1 ratio and the loci were present only in the LLD individuals. $UBC873_{823bp}$ was homozygous. Single factor ANOVA showed a significant association between the segregating loci and longer larval duration. Together, the two alleles contributed to an 18% increase in larval duration. The nucleotide sequences of the $UBC873_{1074bp}$ and $UBC873_{823bp}$ loci had 67% A/T content and consisted of direct, reverse, complementary and palindromic repeats. The repeats appeared to be "nested" (59%) in larger repeats or as clustered elements adjacent to other repeats. Of 203 microsatellites identified, dinucleotides (67.8%) predominated and were rich in A/T and T/A motifs. The sequences of the $UBC873_{1074bp}$ and $UBC873_{823bp}$ loci showed similarity (E = 0.0) to contigs located in Scaffold 010774 and Scaffold 000139, respectively, of the B. mori genome. BLASTN analysis of the $UBC873_{1074bp}$ sequence showed significant homology of (nt.) 45-122 with upstream region of three exons from Bombyx. The complete sequence of this locus showed ~49% nucleotide conservation with transposon 412 of Drosophila melanogaster and the Ikirara insertions of Anopheles gambiae. The A + T richness and lack of coding potential of these small loci, and their absence in the SLD line, reflect the active process of genetic change associated with the switch to short larval duration as an adaptation to the tropics.

• The Plant Pathology Journal
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• v.30 no.2
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• pp.195-199
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• 2014

Apple stem pitting virus (ASPV), of the Foveavirus genus in the family Betaflexiviridae, is one of the most common viruses of apple and pear trees. To examine variability of the coat protein (CP) gene from ASPV, eight isolates originating from 251 apple trees, which were collected from 22 apple orchards located in intensive apple growing areas of the North Gyeongsang and North Jeolla Provinces in Korea, were sequenced and compared. The nucleotide sequence identity of the CP gene of eight ASPV isolates ranged from 77.0 to 97.0%, while the amino acid sequence identity ranged from 87.7 to 98.5%. The N-terminal region of the viral CP gene was highly variable, whereas the C-terminal region was conserved. Genetic algorithm recombination detection (GARD) and single breakpoint recombination (SBP) analyses identified base substitutions between eight ASPV isolates at positions 54 and 57 and position 771, respectively. GABranch analysis was used to determine whether the eight isolates evolved due to positive selection. All values in the GABranch analysis showed a ratio of substitution rates at non-synonymous and synonymous sites (dNS/dS) below 1, suggestive of strong negative selection forces during ASPV CP history. Although negative selection dominated CP evolution in the eight ASPV isolates, SLAC and FEL tests identified four possible positive selection sites at codons 10, 22, 102, and 158. This is the first study of the ASPV genome in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.941-955
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• 2015

In dual-channel networks (DCNs), all frequency hopping (FH) sequences used for data channels are chosen from the original FH sequence used for the control channel by shifting different initial phases. As the number of data channels increases, the hitting frequency point problem becomes considerably serious because DCNs is non-orthogonal synchronization network and FH sequences are non-orthogonal. The increasing severity of the hitting frequency point problem consequently reduces the resource utilization efficiency. To solve this problem, we propose a novel hitting frequency point collision avoidance method, which consists of a sequence-selection strategy called sliding correlation (SC) and a collision avoidance strategy called keeping silent on hitting frequency point (KSHF). SC is used to find the optimal phase-shifted FH sequence with the minimum number of hitting frequency points for a new data channel. The hitting frequency points and their locations in this optimal sequence are also derived for KSHF according to SC strategy. In KSHF, the transceivers transmit or receive symbol information not on the hitting frequency point, but on the next frequency point during the next FH period. Analytical and simulation results demonstrate that unlike the traditional method, the proposed method can effectively reduce the number of hitting frequency points and improve the efficiency of the code resource utilization.

• Food Science and Biotechnology
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• v.17 no.5
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• pp.1052-1059
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• 2008

Sequential Sensitivity Analysis (SSA) and conditional stimulus model have been developed to describe sequence effects in difference tests and proposed to generate prediction of differences in sensitivity between various test protocols and to assist the appropriate selection of difference test. Yet, such models did not furnish a complete explanation of the relative sensitivity in 4 different versions of 3-alternative forced choice (AFC) tests where various interstimulus rinses were introduced. In the present study, the vector of the contrasts between various conditional stimuli were measured using same-different and 2-AFC and a new 16-distribution conditional stimulus model was developed by refining Lee and O'Mahony's contrast model. This new model gave superior predictions than previous models.

• Journal of Life Science
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• v.11 no.1
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• pp.34-38
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• 2001

The cDNA encoding ribosomal protein S4(RPS 4) from an ovary cDNA library of the Japanese monkey (Macaca fuscata) was cloned and sequenced. The RPS4X gene from monkey X chromosome encodes a deduced protein of 263 amino acids and share 99.1% cDNA sequence similarity and 100% amino acid sequence identify with the human RPS4X. Rate of synonymous substitution was higher in RPS4Y than in RPS4X in comparison to the monkey and human. The ratio of synonymous and nonsynonymous substitutions per site indicated that directional selection has nor occurred in RPS4 genes. Phylogenetic analysis using the neighbor-joining method revealed that X and Y-linked RPS4 genes have evolved independently.