Metode Pembobotan Kata Berbasis Cluster Untuk Perangkingan Dokumen Berbahasa Arab

Perangkingan dokumen telah menjadi topik yang banyak dibahas pada sistem temu kembali informasi untuk memberikan urutan dokumen paling relevan berdasarkan kueri yang diberikan oleh pengguna. Namun, penelitian tentang perangkingan dokumen dalam bahasa Arab masih belum banyak dilakukan karena memiliki morfologi yang unik dan literatur dalam bahasa Arab yang masih sedikit. Selain itu, didalam proses perangkingan juga diperlukan perhitungan pembobotan kata yang optimal supaya dapat memberikan hasil yang sesuai. Pembobotan kata yang paling umum digunakan adalah term frequency-inverse document frequency (TF.IDF) yang hanya menghitung pembobotan setiap kata berdasarkan pengelompokan dokumen saja sehingga dapat menyebabkan relevansi antar dokumen menjadi rendah karena memiliki tingkat kemiripan antar dokumen yang berbeda. Oleh karena itu, diperlukan suatu pembobotan kata berdasarkan pengelompokan dokumen dalam suatu cluster untuk meningkatkan relevansi antar dokumen. Tujuan penelitian ini membuat metode perangkingan dokumen berbahasa Arab dengan menggunakan pembobotan berbasis cluster yang menggabungkan TF.IDF dan inverse cluster frequency (ICF) sehingga diperoleh TF.IDF.ICF. Evaluasi dilakukan menggunakan dokumen e-book berbahasa Arab yang telah dikelompokkan menjadi tiga cluster. Hasil penelitian membuktikan pembobotan TF.IDF.ICF mampu menemukan dokumen paling relevan terhadap kueri yang dimasukan oleh pengguna serta memperoleh nilai rata-rata precision dan F1-Measure yang lebih tinggi daripada hanya menggunakan pembobotan TF.IDF yaitu sebesar 68% dan 78%.

Genomic selection for non-key traits in radiata pine when the documented pedigree is corrected using DNA marker information

Background Non-key traits (NKTs) in radiata pine (Pinus radiata D. Don) refer to traits other than growth, wood density and stiffness, but still of interest to breeders. Branch-cluster frequency, stem straightness, external resin bleeding and internal checking are examples of such traits and are targeted for improvement in radiata pine research programmes. Genomic selection can be conducted before the performance of selection candidates is available so that generation intervals can be reduced. Radiata pine is a species with a long generation interval, which if reduced could significantly increase genetic gain per unit of time. The aim of this study was to evaluate the accuracy and predictive ability of genomic selection and its efficiency over traditional forward selection in radiata pine for the following NKTs: branch-cluster frequency, stem straightness, internal checking, and external resin bleeding. Results Nine hundred and eighty-eight individuals were genotyped using exome capture genotyping by sequencing (GBS) and 67,168 single nucleotide polymorphisms (SNPs) used to develop genomic estimated breeding values (GEBVs) with genomic best linear unbiased prediction (GBLUP). The documented pedigree was corrected using a subset of 704 SNPs. The percentage of trio parentage confirmed was about 49% and about 50% of parents were re-assigned. The accuracy of GEBVs was 0.55–0.75 when using the documented pedigree and 0.61–0.80 when using the SNP-corrected pedigree. A higher percentage of additive genetic variance was explained and a higher predictive ability was observed when using the SNP-corrected pedigree than using the documented pedigree. With the documented pedigree, genomic selection was similar to traditional forward selection when assuming a generation interval of 17 years, but worse than traditional forward selection when assuming a generation interval of 14 years. After the pedigree was corrected, genomic selection led to 37–115% and 13–77% additional genetic gain over traditional forward selection when generation intervals of 17 years and 14 years were assumed, respectively. Conclusion It was concluded that genomic selection with a pedigree corrected by SNP information was an efficient way of improving non-key traits in radiata pine breeding.

DISTRIBUIÇÃO ESPACIAL DA BROCA-DO-ESTIPE-DO-COQUEIRO

O objetivo desta pesquisa foi estudar a distribuição espacial de Rhinostomus barbirostris (Coleoptera: Curculionidae) (Fabricius, 1775) em coqueiro (Cocos nucifera L.). Foram realizadas 10 amostragens quinzenalmente do número de machos, fêmeas e total (macho + fêmea), de R. barbirostris em armadilhas demarcada com uma tela de náilon envoltas as palmeiras com sintoma característico do ataque dessa praga, totalizando 24 armadilhas. Para o estudo da distribuição espacial de R. barbirostris, foram calculados os índices de dispersão: razão variância/média (I), índice de Morisita (), coeficiente de Green (Cx), expoente k da distribuição binomial negativa (k), índice de grupo por tamanho (IGT), Índice de frequência de agrupamento (IFA) e Índice de Patchiness (IP) para cada amostragem. Foi testado o ajuste dos dados as distribuições Poisson e binomial negativa. Os resultados obtidos nos índices de agregação calculados indicam que a maioria das amostragens apresentou distribuição agregada de R. barbirostris, para todas as variáveis estudadas. A distribuição binomial negativa foi o modelo mais adequado para representar a distribuição de frequência da coleobroca no coqueiro, já que a variância foi superior à média na maioria das amostragens.Palavras-chave: Rhinostomus barbirostris; cocoicultura; índices de dispersão. SPATIAL DISTRIBUTION OF COCONUT BORER ABSTRACT: The objective of this research was to study the spatial distribution of Rhinostomus barbirostris (Coleoptera: Curculionidae) (Fabricius, 1775) in coconut (Cocos nucifera L.). They were made ten samples every two weeks,of males, females and the total (Male + female), R. barbirostris in marked traps with a nylon screen surrounded with palm trees characteristic symptom of the attack of this pest, totaling 24 traps. To study the spatial distribution of R. barbirostris, dispersion indexes were calculated: variance / mean ratio, Morisita index , Green coefficient (Cx), k exponent of negative binomial distribution, index of de Cluster Size (ICS), index of de Cluster Frequency (ICF) e index of de Patchiness (IP) for each sample. It tested the data fitting the Poisson distribution and binomial negative. The results calculated in aggregation indexes indicate that Most samplings presented aggregated distribution of R. barbirostris for all the variables studied. The negative binomial distribution was the best model to represent the frequency distribution of the coconut borer, since the variance was higher than the average for the majority of the samples.Keywords: Rhinostomus barbirostris; coconut farmin; dispersion indexes.