• Title/Summary/Keyword: Genetic potential

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Knowledge-based learning for modeling concrete compressive strength using genetic programming

  • Tsai, Hsing-Chih;Liao, Min-Chih
    • Computers and Concrete
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    • v.23 no.4
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    • pp.255-265
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    • 2019
  • The potential of using genetic programming to predict engineering data has caught the attention of researchers in recent years. The present paper utilized weighted genetic programming (WGP), a derivative model of genetic programming (GP), to model the compressive strength of concrete. The calculation results of Abrams' laws, which are used as the design codes for calculating the compressive strength of concrete, were treated as the inputs for the genetic programming model. Therefore, knowledge of the Abrams' laws, which is not a factor of influence on common data-based learning approaches, was considered to be a potential factor affecting genetic programming models. Significant outcomes of this work include: 1) the employed design codes positively affected the prediction accuracy of modeling the compressive strength of concrete; 2) a new equation was suggested to replace the design code for predicting concrete strength; and 3) common data-based learning approaches were evolved into knowledge-based learning approaches using historical data and design codes.

Exploring Ways to Improve the Predictability of Flowering Time and Potential Yield of Soybean in the Crop Model Simulation (작물모형의 생물계절 및 잠재수량 예측력 개선 방법 탐색: I. 유전 모수 정보 향상으로 콩의 개화시기 및 잠재수량 예측력 향상이 가능한가?)

  • Chung, Uran;Shin, Pyeong;Seo, Myung-Chul
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.19 no.4
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    • pp.203-214
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    • 2017
  • There are two references of genetic information in Korean soybean cultivar. This study suggested that the new seven genetic information to supplement the uncertainty on prediction of potential yield of two references in soybean, and assessed the availability of two references and seven genetic information for future research. We carried out evaluate the prediction on flowering time and potential yield of the two references of genetic parameters and the new seven genetic parameters (New1~New7); the new seven genetic parameters were calibrated in Jinju, Suwon, Chuncheon during 2003-2006. As a result, in the individual and regional combination genetic parameters, the statistical indicators of the genetic parameters of the each site or the genetic parameters of the participating stations showed improved results, but did not significant. In Daegu, Miryang, and Jeonju, the predictability on flowering time of genetic parameters of New7 was not improved than that of two references. However, the genetic parameters of New7 showed improvement of predictability on potential yield. No predictability on flowering time of genetic parameters of two references as having the coefficient of determination ($R^2$) on flowering time respectively, at 0.00 and 0.01, but the predictability of genetic parameter of New7 was improved as $R^2$ on flowering time of New7 was 0.31 in Miryang. On the other hand, $R^2$ on potential yield of genetic parameters of two references were respectively 0.66 and 0.41, but no predictability on potential yield of genetic parameter of New7 as $R^2$ of New7 showed 0.00 in Jeonju. However, it is expected that the regional combination genetic parameters with the good evaluation can be utilized to predict the flowering timing and potential yields of other regions. Although it is necessary to analyze further whether or not the input data is uncertain.

High Utility Itemset Mining over Uncertain Datasets Based on a Quantum Genetic Algorithm

  • Wang, Ju;Liu, Fuxian;Jin, Chunjie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.8
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    • pp.3606-3629
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    • 2018
  • The discovered high potential utility itemsets (HPUIs) have significant influence on a variety of areas, such as retail marketing, web click analysis, and biological gene analysis. Thus, in this paper, we propose an algorithm called HPUIM-QGA (Mining high potential utility itemsets based on a quantum genetic algorithm) to mine HPUIs over uncertain datasets based on a quantum genetic algorithm (QGA). The proposed algorithm not only can handle the problem of the non-downward closure property by developing an upper bound of the potential utility (UBPU) (which prunes the unpromising itemsets in the early stage) but can also handle the problem of combinatorial explosion by introducing a QGA, which finds optimal solutions quickly and needs to set only very few parameters. Furthermore, a pruning strategy has been designed to avoid the meaningless and redundant itemsets that are generated in the evolution process of the QGA. As proof of the HPUIM-QGA, a substantial number of experiments are performed on the runtime, memory usage, analysis of the discovered itemsets and the convergence on real-life and synthetic datasets. The results show that our proposed algorithm is reasonable and acceptable for mining meaningful HPUIs from uncertain datasets.

Growth Simulation of Ilpumbyeo under Korean Environment Using ORYZA2000: I. Estimation of Genetic Coefficients

  • Lee Chung-Kuen;Shin Jae-Hoon;Shin Jin-Chul;Kim Duk-Su;Choi Kyung-Jin
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2004.04a
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    • pp.100-101
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    • 2004
  • [ $\bigcirc$ ] In the growth simulation using genetic coefficients calculated with fooled data under various condition, WAGT was not higher and LAI, WLVG, WSO were higher, but WST was similar before grain-filling stage after the became lower because of higher translocation of carbohydrates than in the growth simulation using genetic coefficients calculated with data under high nitrogen applicated condition. $\bigcirc$ Genetic coefficients should be calculated with data showing potential in ORYZA2000, but under 180 kg and 240 kg N condition in 2003, plants were infected by panicle blast and also yield was not higher than under 120 kg N condition showing not potential condition and therefore not appropriate for genetic coefficients estimation compared with pooled data from various condition.

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Identification of High Affinity Non-Peptidic Small Molecule Inhibitors of MDM2-p53 Interactions through Structure-Based Virtual Screening Strategies

  • Bandaru, Srinivas;Ponnala, Deepika;Lakkaraju, Chandana;Bhukya, Chaitanya Kumar;Shaheen, Uzma;Nayarisseri, Anuraj
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.9
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    • pp.3759-3765
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    • 2015
  • Background: Approaches in disruption of MDM2-p53 interactions have now emerged as an important therapeutic strategy in resurrecting wild type p53 functional status. The present study highlights virtual screening strategies in identification of high affinity small molecule non-peptidic inhibitors. Nutlin3A and RG7112 belonging to compound class of Cis-imidazoline, MI219 of Spiro-oxindole class and Benzodiazepine derived TDP 665759 served as query small molecules for similarity search with a threshold of 95%. The query molecules and the similar molecules corresponding to each query were docked at the transactivation binding cleft of MDM2 protein. Aided by MolDock algorithm, high affinity compound against MDM2 was retrieved. Patch Dock supervised Protein-Protein interactions were established between MDM2 and ligand (query and similar) bound and free states of p53. Compounds with PubCid 68870345, 77819398, 71132874, and 11952782 respectively structurally similar to Nutlin3A, RG7112, Mi219 and TDP 665759 demonstrated higher affinity to MDM2 in comparison to their parent compounds. Evident from the protein-protein interaction studies, all the similar compounds except for 77819398 (similar to RG 7112) showed appreciable inhibitory potential. Of particular relevance, compound 68870345 akin to Nutlin 3A had highest inhibitory potential that respectively showed 1.3, 1.2, 1.16 and 1.26 folds higher inhibitory potential than Nutilin 3A, MI 219, RG 7112 and TDP 1665759. Compound 68870345 was further mapped for structure based pharamacophoric features. In the study, we report Cis-imidazoline derivative compound; Pubcid: 68870345 to have highest inhibitory potential in blocking MDM2-p53 interactions hitherto discovered.

Assessing the Performance of Pongamia pinnata (l.) Pierre under Ex-situ Condition in Karnataka

  • Divakara, Baragur Neelappa;Nikhitha, Chitradurga Umesh
    • Journal of Forest and Environmental Science
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    • v.38 no.1
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    • pp.12-20
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    • 2022
  • Pongamia (Pongamia pinnata L.) as a source of non-edible oil, is potential tree species for biodiesel production. For several reasons, both technical and economical, the potential of P. pinnata is far from being realized. The exploitation of genetic diversity for crop improvement has been the major driving force for the exploration and ex situ/in situ conservation of plant genetic resources. However, P. pinnata improvement for high oil and seed production is not achieved because of unsystematic way of tree improvement. Performance of P. pinnata planted by Karnataka Forest Department was assessed based on yield potential by collecting 157 clones out of 264 clones established by Karnataka Forest Department research wing under different research circles/ranges. It was evident that the all the seed and pod traits were significantly different. Further, selection of superior germplasm based on oil and pod/seed parameters was achieved by application of Mahalanobis statistics and Tocher's technique. On the basis of D2 values for all possible 253 pairs of populations the 157 genotypes were grouped into 28 clusters. The clustering pattern showed that geographical diversity is not necessarily related to genetic diversity. Cluster means indicated a wide range of variation for all the pod and seed traits. The best cluster having total oil content of more than 34.9% with 100 seed weight of above 125 g viz. Cluster I, II, III, IX, XV, XIX, XXI, XXIII, XXVI and XXVII were selected for clonal propagation.

Copying and Manipulating Nature: Innovation for Textile Materials

  • Rossbach, Volker;Patanathabutr, Pajaera;Wichitwechkarn, Jesdawan
    • Fibers and Polymers
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    • v.4 no.1
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    • pp.8-14
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    • 2003
  • This paper considers the potential impact of biological approaches such as bio-copying (biomimetics) and biomanipulating (e.g. genetic engineering) on future developments in the field of textiles and, in particular, fibres. If analytical tools for studying biological systems combined with those of materials science are further developed, and higher efficiency and reproducibility of genetic engineering technology can be achieved, the potential for the copying and manipulation of nature for textile innovations will be immense. The present state for both fields is described with examples such as touch and close fastener, structurally coloured fibres, the Lotus of lect (for bio-copying), as well as herbicide tolerant cotton, insecticide resistant cotton (Bt cotton), cotton polyester bicomponent fibres, genetically engineered silkworm and silk protein, and spider fibres. (for genetic engineering).

Utilization of Primordial Germ Cell(PGC) as Transferor of Avian Genetic Materials (가금의 유전물질전달체로서의 원시생식세포의 이용)

  • 여정수
    • Korean Journal of Animal Reproduction
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    • v.12 no.1
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    • pp.11-14
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    • 1988
  • Utilizatin of primordial germ cell(PGC) as transferor of genetic materials is great potential in manipulating genes to promote genetic performances in chicken. This study explored that PGCs from early embryos as vehicle for molecular breeding strategles were isolated, these chromosomally marked donor PGCs were transplanted to germinal crescent of host embryos, and genetic materials of donor PGC were identified at the proliferative stage in host gonads.

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Tuning Rules of the PID Controller Based on Genetic Algorithms (유전알고리즘에 기초한 PID 제어기의 동조규칙)

  • Kim, Do-Eung;Jin, Gang-Gyoo
    • Proceedings of the KIEE Conference
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    • 2002.07d
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    • pp.2167-2170
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    • 2002
  • In this paper, model-based tuning rules of the PID controller are proposed incorporating with genetic algorithms. Three sets of optimal PID parameters for set-point tracking are obtained based on the first-order time delay model and a genetic algorithm as a optimization tool which minimizes performance indices(IAE, ISE and ITAE). Then tuning rules are derived using the tuned parameter sets, potential rule models and a genetic algorithm. Simulation is carried out to verify the effectiveness of the proposed rules.

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Genetic Diversity of Orobanche cumana Populations in Serbia

  • Ivanovic, Zarko;Marisavljevic, Dragana;Marinkovic, Radovan;Mitrovic, Petar;Blagojevic, Jovana;Nikolic, Ivan;Pavlovic, Danijela
    • The Plant Pathology Journal
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    • v.37 no.6
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    • pp.512-520
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    • 2021
  • In this study, we report genetic characterization of Orobanche cumana, the causal agent of sunflower wilting in Serbia. The genetic diversity of this parasitic plant in Serbia was not studied before. Random amplified polymorphic DNA (RAPD) markers and partial rbcL gene sequences analysis were used to characterize the O. cumana populations at the molecular level. While phylogenetic analyses of RAPD-PCR amplicons were performed using unweighted pair-group Method analyses, rbcL gene sequences were analyzed using neigbor joining method and minimum spanning tree. Molecular analyses of RAPD-PCR analysis revealed high genetic diversity of O. cumana populations which indicated high adaptive potential of this parasitic weed in Serbia. Further analyses of rbcL gene using minimum spanning tree revealed clear differences among diverse sections of Orobanche genus. Although this molecular marker lacked the resolution to display intrapopulation diversity it could be a useful tool for understanding the evolution of this parasitic plant. Our results suggested that O. cumana has great genetic potential which can lead to differentiation of more virulent races which is important for determining crop breeding strategies for their control.