Judul: Characteristic analysis of freeze drying and determining transport properties frozen dried ginger (Zingiber officinale. Rosc.) paste, with the advisory committee
Abstrak: Ginger comodity is one of raw matter used to make traditional medicine (jamu) in Indonesia. Beside that, ginger also is used as cooking spice and food industry. As traditional medicine, it should be containing active components that are useful to heal human diseases and keep stability of the human health. To elongagte he duration of that commodity, it should be stored in dried condition so that it should be dried. One method to make the moisture content of the matter in very low condition is by drying it at vacuum condition or freeze method.
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Judul: Uji Performansi Alat Pengering Tipe Rak dan Pengaruh Perlakuan Awal terhadap Mutu Jahe Kering (Zingiber officinale Rosc.)
Abstrak: Ginger (Zingiber officinale Rosc.) is one of spices and medicinal plant which has high economic value and have been widely recognized by the Indonesian people. Fresh ginger has moisture content between 85-91% wet basis causes reduction quality of ginger if it is not eventually to be processed or dried. Generally, farmers and traders dried the ginger by using sun drying which require a lot of time, so that the artificial drying is needed to produce dried ginger with better quality and can shorten the drying time. The objectives of the research are to conduct the performance assessment of Sunbeam Food Dehydrator, which is rack-type dryer that using electrical energy as heat source; to assess the effect of immersion in lime solution (Ca(OH)2) at concentration of 2%, 4% and 6% to the quality of dried ginger; as well as studying the temperature distribution and air flow patterns in the dryer using Computational Fluid Dynamics (CFD). The results of the research showed that the dryer has capacity about 1kg of ginger slice and drying efficiency of 25.09%. It also shown that the immersion in lime solution gave a significant effect on increasing ash content and lightness of dried ginger, but it gave no significant effect on essential oil content of dried ginger. The treatment of immersion in 6% concentration of lime solution produce dry ginger with ash content that beyond of quality standard limit. The simulation of temperature and air flow patterns inside the dryer showed the accuracy of 97.09% and resulting linear regression of the relationship between measurement temperature and simulation temperature of 0.943. This shows that the CFD simulation gives good results in predicting the distribution of air temperature and air flow patterns inside the dryer.
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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