• Title/Summary/Keyword: Random selection

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Designing Hypothesis of 2-Substituted-N-[4-(1-methyl-4,5-diphenyl-1H-imidazole-2-yl)phenyl] Acetamide Analogs as Anticancer Agents: QSAR Approach

  • Bedadurge, Ajay B.;Shaikh, Anwar R.
    • Journal of the Korean Chemical Society
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    • v.57 no.6
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    • pp.744-754
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    • 2013
  • Quantitative structure-activity relationship (QSAR) analysis for recently synthesized imidazole-(benz)azole and imidazole - piperazine derivatives was studied for their anticancer activities against breast (MCF-7) cell lines. The statistically significant 2D-QSAR models ($r^2=0.8901$; $q^2=0.8130$; F test = 36.4635; $r^2$ se = 0.1696; $q^2$ se = 0.12212; pred_$r^2=0.4229$; pred_$r^2$ se = 0.4606 and $r^2=0.8763$; $q^2=0.7617$; F test = 31.8737; $r^2$ se = 0.1951; $q^2$ se = 0.2708; pred_$r^2=0.4386$; pred_$r^2$ se = 0.3950) were developed using molecular design suite (VLifeMDS 4.2). The study was performed with 18 compounds (data set) using random selection and manual selection methods used for the division of the data set into training and test set. Multiple linear regression (MLR) methodology with stepwise (SW) forward-backward variable selection method was used for building the QSAR models. The results of the 2D-QSAR models were further compared with 3D-QSAR models generated by kNN-MFA, (k-Nearest Neighbor Molecular Field Analysis) investigating the substitutional requirements for the favorable anticancer activity. The results derived may be useful in further designing novel imidazole-(benz)azole and imidazole-piperazine derivatives against breast (MCF-7) cell lines prior to synthesis.

A Study on the Impact of Multi-Skilled Agents on the Service Quality of Call Centers (멀티스킬 상담 인력이 콜센터 서비스 품질에 미치는 영향에 관한 연구)

  • Chen, Taoyuan;Park, Chan-Kyoo
    • Journal of Information Technology Services
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    • v.18 no.3
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    • pp.17-35
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    • 2019
  • Call centers do not simply play a role of responding to customers' calls, but they have developed into a core unit for maintaining competitiveness through services, marketing, or sales. Since the service quality of call centers heavily affects customer satisfaction, organizations have focused on enhancing it by reducing waiting time and increasing service level. One of the techniques, which improve the service quality of call centers, is to employ multi-skilled agents that can handle more than one type of calls. This study deals with three issues relevant to multi-skilled agents. First, we analyze how the way of allocating a specific group of agents to a set of skills affects the performance of call centers. Secondly, we investigate the relationship between the number of multi-skilled agents and the performance of call centers. Finally, we examine the impact of agent selection rules on the performance of call centers. Two selection rules are compared : the first rule is to assign a call to any available agent at random while the other rule is to assign a call preferably to single-skilled agents over multi-skilled agents when applicable. Based on simulation experiments, we suggest three implications. First, as the length of cycles in the agent-skill configuration network becomes longer, call centers achieve higher service level and shorter waiting time. Secondly, simulation results show that as the portion of multi-skilled agents increases, the performance of call centers improves. However, most of the improvement is attained when the portion of multi-skilled agents is relatively low. Finally, the agent selection rules do not significantly affect the call centers' performance, but the rule of preferring single-skilled agents tends to distribute the workload among agents more equally.

Whole-Genome Characterization of Alfalfa Mosaic Virus Obtained from Metagenomic Analysis of Vinca minor and Wisteria sinensis in Iran: with Implications for the Genetic Structure of the Virus

  • Moradi, Zohreh;Mehrvar, Mohsen
    • The Plant Pathology Journal
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    • v.37 no.6
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    • pp.619-631
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    • 2021
  • Alfalfa mosaic virus (AMV), an economically important pathogen, is present worldwide with a very wide host range. This work reports for the first time the infection of Vinca minor and Wisteria sinensis with AMV using RNA sequencing and reverse transcription polymerase chain reaction confirmation. De novo assembly and annotating of contigs revealed that RNA1, RNA2, and RNA3 genomic fragments consist of 3,690, 2,636, and 2,057 nucleotides (nt) for IR-VM and 3,690, 2,594, and 2,057 nt for IR-WS. RNA1 and RNA3 segments of IR-VM and IR-WS closely resembled those of the Chinese isolate HZ, with 99.23-99.26% and 98.04-98.09% nt identity, respectively. Their RNA2 resembled that of Canadian isolate CaM and American isolate OH-2-2017, with 97.96-98.07% nt identity. The P2 gene revealed more nucleotide diversity compared with other genes. Genes in the AMV genome were under dominant negative selection during evolution, and the P1 and coat protein (CP) proteins were subject to the strongest and weakest purifying selection, respectively. In the population genetic analysis based on the CP gene sequences, all 107 AMV isolates fell into two main clades (A, B) and isolates of clade A were further divided into three groups with significant subpopulation differentiation. The results indicated moderate genetic variation within and no clear geographic or genetic structure between the studied populations, implying moderate gene flow can play an important role in differentiation and distribution of genetic diversity among populations. Several factors have shaped the genetic structure and diversity of AMV: selection, recombination/reassortment, gene flow, and random processes such as founder effects.

Shared Tree-based Multicast RP Re-Selection Scheme in High-Speed Internet Wide Area Network (고속 인터넷 환경에서 공유 트리 기반 멀티캐스트 RP 재선정 기법)

  • 이동림;윤찬현
    • The KIPS Transactions:PartC
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    • v.8C no.1
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    • pp.60-67
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    • 2001
  • Multicast Protocol for multimedia service on the Internet can be classified into two types, e.g., source based tree and shared tree according to difference of tree construction method. Shared tree based multicast is known to show outstanding results in the aspect of scalability than source based tree. Generally, There have been lots of researches on the method to satisfy QoS constraints through proper Rendezvous Point (RP) in the shared tree. In addition, as the multicast group members join and leave dynamically in the service time, RP of the shared tree should b be reselected for guranteeing Qos to new member, But, RP reselection method has not been considered generally as the solution to satisfy QoS C constraints. In this paper, new initial RP selection and RP reselection method are proposed, which utilize RTCP (Real Time Control Protocol) report packet fields. Proposed initial RP selection and RP reselection method use RTCP protocol which underlying multimedia application service So, the proposed method does not need any special process for collecting network information to calculate RP. New initial RP selection method s shows better performance than random and topology based one by 40-50% in simulation. Also, RP reselection method improves delay p performance by 50% after initial RP selection according to the member’s dynamicity.

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Variable Selection of Feature Pattern using SVM-based Criterion with Q-Learning in Reinforcement Learning (SVM-기반 제약 조건과 강화학습의 Q-learning을 이용한 변별력이 확실한 특징 패턴 선택)

  • Kim, Chayoung
    • Journal of Internet Computing and Services
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    • v.20 no.4
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    • pp.21-27
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    • 2019
  • Selection of feature pattern gathered from the observation of the RNA sequencing data (RNA-seq) are not all equally informative for identification of differential expressions: some of them may be noisy, correlated or irrelevant because of redundancy in Big-Data sets. Variable selection of feature pattern aims at differential expressed gene set that is significantly relevant for a special task. This issues are complex and important in many domains, for example. In terms of a computational research field of machine learning, selection of feature pattern has been studied such as Random Forest, K-Nearest and Support Vector Machine (SVM). One of most the well-known machine learning algorithms is SVM, which is classical as well as original. The one of a member of SVM-criterion is Support Vector Machine-Recursive Feature Elimination (SVM-RFE), which have been utilized in our research work. We propose a novel algorithm of the SVM-RFE with Q-learning in reinforcement learning for better variable selection of feature pattern. By comparing our proposed algorithm with the well-known SVM-RFE combining Welch' T in published data, our result can show that the criterion from weight vector of SVM-RFE enhanced by Q-learning has been improved by an off-policy by a more exploratory scheme of Q-learning.

Studies on the selection in soybean breeding. -II. Additional data on heritability, genotypic correlation and selection index- (대두육종에 있어서의 선발에 관한 실험적연구 -속보 : 유전력ㆍ유전상관, 그리고 선발지수의 재검토-)

  • Kwon-Yawl Chang
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.3
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    • pp.89-98
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    • 1965
  • The experimental studies were intended to clarify the effects of selection, and also aimed at estimating the heritabilities, the genotypic correlations among some agronomic characters, and at calculating the selection index on some selective characters for the selection of desirable lines, under different climatic conditions. Finally practical implications of these studies, especially on the selection index, were discussed. Twenty-two varieties, determinate growing habit type, were selected at random from the 138 soybean varieties cultivated the year before, were grown in a randomized block design with three replicates at Chinju, Korea, under May and June sowing conditions. The method of estimating heritabilities for the eleven agronomic characters-flowering date, maturity date, stem length, branch numbers per plant, stem diameter, plant weight, pod numbers per plant, grain numbers per plant and 100 grain weight, shown in Table 3, was the variance components procedures in a replicated trial for the varieties. The analysis of covariance was used to obtain the genotypic correlations and phenotypic correlations among the eight characters, and the selection indexes for some agronomic characters were calculated by Robinson's method. The results are summarized as follows: Heritabilities : The experiment on the genotype-environment interaction revealed that in almost all of the characters investigated the interaction was too large to be neglected and materially affected the estimates of various genotypic parameters. The variation in heritability due to the change of environments was larger in the characters of low heritability than in those of high heritability. Heritability values of flowering date, fruiting period (days from flowering to maturity), stem length and 100 grain weight were the highest in both environments, those of yield(grain weight) and other characters were showed the lower values(Table 3). These heritability values showed a decreasing trend with the delayed sowing in the experiments. Further, all calculated heritability values were higher than anticipated. This was expected since these values, which were the broad sense heritability, contain the variance due to dominance and epistasisf in addition to the additive genetic variance. Genotypic correlations : Genotypic correlations were slightly higher than the corresponding phenotypic correlations in both environments, but the variation in values due to the change of environment appeared between grain weight and some other characters, especially an increase between grain weight and flowering date, and the total growing period(Table 6). Genotypic correlations between grain weight and other characters indicated that high seed yield was genetically correlated with late flowering, late maturity, and the other five characters namely branch numbers per plant, stem diameter, plant weight, pod numbers per plant and grain numbers per plant, but not with 100 grain weight of soybeans. Pod numbers and grain numbers per plant were more closely correlated with seed yields than with other characters. Selection index : For the comparison and the use of selection indexes in the selection, two kinds of selection indexes were calculated, the former was called selection index A and the later selection index B as shown in Table 7. Selection index A was calculated by the values of grain weight per plant as the character of yield(character Y), but the other, selection index B, was calculated by the values of pod numbers per plant, instead of grain weight per plant, as the character of yield'(character Y'). These results suggest that selection index technique is useful in soybean breeding. In reality, however, as the selection index varies with population and environment, it must be calculated in each population to which selection is applied and in each environment in which the population is located. In spite of the expected usefulness of selection index technique in soybean breeding, unsolved problems such as the expense, time and labor involved in calculating the selection index remain. For these reasons and from these experimental studies, it was recognized that in the breeding of self-fertilized soybean plants the selection for yield should be based on a more simple selection index such as selection index B of these experiments rather than on the complex selection index such as selection index A. Furthermore, it was realized that the selection index for the selection should be calculated on the basis of the data of some 3-4 agronomic characters-maturity date(X$_1$), branch numbers per plant(X$_2$), stem diameter(X$_3$) and pod numbers per plant etc. It must be noted that it should be successful in selection to select for maturity date(X$_1$) which has high heritability, and the selection index should be calculated easily on the basis of the data of branch numbers per plant(X$_2$), stem diameter(X$_3$) and pod numbers per plant, directly after the harvest before drying and threshing. These characters should be very useful agronomic characters in the selection of Korean soybeans, determinate growing habit type, as they could be measured or counted easily thus saving time and expense in the duration from harvest to drying and threshing, and are affected more in soybean yields than the other agronomic characters.

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Frame Selection Algorithm for the RFID system (RFID 시스템을 위한 프레임 선택 기법)

  • Lee Ju-No;Joe In-Whee
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06d
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    • pp.55-57
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    • 2006
  • 최근 국내 표준의 확정과 함께 새로운 수익모델로써 다양한 분야에서 활용이 기대가 되는 RFID 무선인식 시스템은 국내의 많은 업체와 기관들이 현재 다양한 솔루션을 개발함으로써 다가오는 유비쿼터스 환경에 적극 대응하고 있다. RFID 시스템의 중요한 기술요소 중 하나는 다중 태그로 인한 충돌을 처리하는 Anti-collision 알고리즘이다. 본 논문에서는 먼저 충돌방지기법의 종류와 최근에 900MHz대역의 RFID 표준으로 확정된 ISO/IEC 18000-6 Type C 표준문서에서 소개한 Slotted random 충돌방지 알고리즘을 분석하고, 충돌 정도에 따라 적응적으로 다음 프레임의 크기를 조정하는 기법을 제안한다. 모든 태그를 완전히 읽어내는데 걸리는 시간을 계산하기 위해서 Type C 표준을 적용한 모의실험을 통해 성능평가를 하였다.

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TOA Estimation Technique for IR-UWB Based on Homogeneity Test

  • Djeddou, Mustapha;Zeher, Hichem;Nekachtali, Younes;Drouiche, Karim
    • ETRI Journal
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    • v.35 no.5
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    • pp.757-766
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    • 2013
  • This paper deals with the estimation of the time of arrival (TOA) of ultra-wideband signals under IEEE 802.15.4a channel models. The proposed approach is based on a randomness test and consists of determining whether an autoregressive (AR) process modeling an energy frame is random or not by using a distance to measure the randomness. The proposed method uses a threshold that is derived analytically according to a preset false alarm probability. To highlight the effectiveness of the developed approach, simulation setups as well as real data experiments are conducted to assess the performance of the new TOA estimation algorithm. Thereby, the proposed method is compared with the cell averaging constant false alarm rate technique, the threshold comparison algorithm, and the technique based on maximum energy selection with search back. The obtained results are promising, considering both simulations and collected real-life data.

Finding Top-k Answers in Node Proximity Search Using Distribution State Transition Graph

  • Park, Jaehui;Lee, Sang-Goo
    • ETRI Journal
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    • v.38 no.4
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    • pp.714-723
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    • 2016
  • Considerable attention has been given to processing graph data in recent years. An efficient method for computing the node proximity is one of the most challenging problems for many applications such as recommendation systems and social networks. Regarding large-scale, mutable datasets and user queries, top-k query processing has gained significant interest. This paper presents a novel method to find top-k answers in a node proximity search based on the well-known measure, Personalized PageRank (PPR). First, we introduce a distribution state transition graph (DSTG) to depict iterative steps for solving the PPR equation. Second, we propose a weight distribution model of a DSTG to capture the states of intermediate PPR scores and their distribution. Using a DSTG, we can selectively follow and compare multiple random paths with different lengths to find the most promising nodes. Moreover, we prove that the results of our method are equivalent to the PPR results. Comparative performance studies using two real datasets clearly show that our method is practical and accurate.

Merging of Two Artificial Neural Networks

  • Kim, Mun-Hyuk;Park, Jin-Young
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.258-261
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    • 2002
  • This paper addresses the problem of merging two feedforward neural networks into one network. Merging is accomplished at the level of hidden layer. A new network selects its hidden layer's units from the two networks to be merged We uses information theoretic criterion (quadratic mutual information) in the selection process. The hidden unit's output and the target patterns are considers as random variables and the mutual information between them is calculated. The mutual information between hidden units are also considered to prevent the statistically dependent units from being selected. Because mutual information is invariant under linear transformation of the variables, it shows the property of the robust estimation.

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