Judul: Pengaruh tingkat penambahan tepung kunyit (Curcuma domestica val.) dan tepung daun pepaya (Carica papaya L.) dalam ransum terhadap gambaran darah ayam broiler yang mengalami cekaman panas
Abstrak: The experiment was conducted to study the hematological profile of broiler under heat stress and fed with Carica papaya L leaf meal and curcuma domestica val. meal at different level as a feed additive. Heat stress happened ao the third weeks with temperature 34 °C and take care of it for six weeks. The diet contain metabolizable energy (ME) 2900 kkal/kg and crude protein (CP) 21%. Threatments were R1 : control diet, R2 : 99.98% control feed and 0.02% Bambermycin, R3 : 98% control feed and 1% Carica papaya L leaf meal and 1% Curcuma domestica val. meal R4 : 97% control feed and 1.5% Carica papaya L leaf meal and 1.5% Curcuma domestica val. meal, R5 : 96% control feed Carica papaya L leaf meal and 2% Curcuma domestica val.
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Judul: Pengaruh pemberian campuran tepung kunyit dan tepung daun pepaya dalam ransum terhadap gambaran metabolisme lemak ayam broiler yang mengalami cekaman panas
Abstrak: The experiment was conducted to determine the effect of utilization Curcuma domestica meal and Carica papaya leaf meal on total cholesterol, triglycerides, HDL, and LDL serum concentrations in broilers which were maintained under heat streaa condition. Two hundred Day Old Chicken (DOC) broilers were divided into five treatments. The experimental design was Completely Randomized Design with five treatments. The experimental design was Completely Randomized Design with five treatments and four replications, that were control diet (R1), control diet antibiotics (R2), control diet +1% curcuma meal +1% papaya leaf meal (R3),control diet +1.5% curcuma meal +1.5% papaya leaf meal (R4) and control diet +2% curcuma meal +2% papaya leaf meal (R5).
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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