Judul: Analisis glukosa, zat besi dan hemoglobin dalam darah kerbau di rumah potong hewan Kotamadya Bogor
Abstrak: Hasil analisis kadar glukosa dalam darah kerbau didapat data berkisar antara 53,87 mg/100 ml darah sampai 76,80 mg/100 ml darah. Hasil yang didapat ini masih dalam batas - batas normal diabandingkan data pustaka yang ada (berkisar antara 43,9 mg/100 ml darah sampai 73,3 mg/100 ml darah), bahkan beberapa ekor memperliahatkan kadar glukosa yang tinggi. Tingginya kadar glukosa darah ini mungkin oleh faktor stress (sesuai dengan cara pengambilan sampel), mungkin oleh faktor makanan, mungkin oleh umur, dan beberapa kemungkinan faktor lain.
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Judul: Kadar glukosa, hemoglobin ( Hb ) dan besi ( Fe ) darah domba di rumah potonh hewan Bogor
Abstrak: Kadar glukosa, hemoglobin dan besi mempunyai arti yang penting dalam darah pada khususnya dan tubuh pada umumnya. Secara normal berkaitan dengan metabolisma tubuh, yang berarti bahwa proses-proses kimia yang memungkinkan bagi sel untuk melangsungkan kehidupan. Tujuan penelitian ini adalah untuk mengumpulkan data data normal dari kadar glukosa, hemoglobin dan besi. Selain itu juga untuk mengetahui kesehatan hewan.. Penelitian dilakukan di Laboratorium Biokimia, Fakultas Kedokteran Hewan, Institut Pertanian Bogor dimulai da- ri tanggal 29 April hingga 4 Mei 1985. Metoda penelitian adalah dengan pemeriksaan darah domba yang diambil dari Rumah Potong Hewan Bogor. Pemeriksaan dilakukan dengan menggunakan zat-zat kimia yang telah ditentukan. Kemudian pembacaan hasil dilakukan dengan spektro- fotometer. Berdasarkan hasil pemeriksaan ternyata kadar glukosa, hemoglobin dan besi darah domba rata-rata tidak mengalami penyimpangan atau kelainan. Walaupun dilihat secara individu ada yang menunjukkan peningkatan dan penurunan dari toleransi normal….
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Judul: The Construction of Greedy SVP LLL Algorithm
Abstrak: A lattice is a set of all integer linear combination of a set of linearly independent vectors in ℝ𝑛���. The independent vectors are called bases of lattice. Any lattice can be generated from many bases, and these bases have the same cardinality. In the lattice, the most fundamental and renowned problem is the Shortest Vector Problem (SVP). SVP is a tracking problem of the shortest nonzero vector in a lattice with equivalent bases. In two dimensions, SVP problem has resolved exactly by Gauss’ algorithm. When the lattice dimension is higher than two, A.K. Lenstra, H.W. Lenstra and L. Lovasz gave a LLL algorithm to compute approximation of nonzero shortest vector in the lattice. Reduced bases solution obtained from LLL algorithm still be an approximation and has polynomial running time of arbitrary dimension which large enough. In 1994, Schnoor and Euchner modified this LLL algorithm as a new variant which later was named deep insertion LLL algorithm. This algorithm is a modified version of the LLL algorithm to the terms of the exchange step to improve the accuracy of output of LLL reduced bases and applying it to the subset sum problem. The purpose of this research are: (1) Reconstruct the LLL algorithm and deep insertion LLL algorithm using a geometric approach. (2) Construct a greedy SVP LLL algorithm. (3) Implement the three algorithms in a symbolic programming language, and evaluate them experimentally. A bases ℬ=[𝐛���1,𝐛���2,…,𝐛���𝑛���] in ℝ𝑚��� is called reduced LLL with parameter 𝛿��� if satisfies: (a) |𝜇���𝑗���𝑖���|≤12, for every integer 𝑖���,𝑗��� with 1≤𝑖���<𝑗���<𝑛���. (b)𝛿���‖𝜋���𝑗���(𝐛���𝑗���)‖2≤‖𝜋���𝑗���(𝐛���𝑗���+1)‖2, for 𝑗���=1,2,…,𝑛���−1,where 𝛿��� is a reduced parameter of real numbers with 14<𝛿���<1. The first requirement is the reduced basis 𝛿��� must “nearly orthogonal” and in its computation case, this requirement can be reached out by using the Gram-Schmidt’s orthogonalization. While the second requirement is called exchange step, or used to called as Lovasz condition. By using both of these requirements, then they establish the LLL algorithm. Then, Schnoor and Euchner modify the LLL algorithm based on the requirements of the exchange step called the deep insertion LLL algorithm, where the exchange step is based on the comparison of the projected vector in orthogonal complement [𝐛���1,𝐛���2,…,𝐛���𝑘���−1]⊥ after j-th reduction. To construct greedy SVP LLL algorithm, the requirements of the exchange step is based on purely by comparing norm of lattice 𝐛���𝑗��� with norm lattice 𝐛���𝑖��� for 𝑖���=1,2,3…,𝑗���−1. The process of insertion reduced vector after the exchange step also has done greedily. Then, we calculate the number of arithmetic operation in greedy SVP LLL algorithm for further analysis. The result of our exprimentation for three algorithms on the certain matrix size shows that the running time of the three algorithms increases propotional to the size of the matrix. The result also shows that by using 𝛿���=34 for the LLL algorithm and the deep insertion LLL algorithm, and the greedy SVP LLL algorithm which is a new variant made by using no parameter of 𝛿���, outperform of the other of two previous algorithm in terms of speed with the same output.
Keyword: LLL algorithm, LLL deep insertion algorithm, greedy SVP LLL algorithm