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Articles by Z. Jin
Total Records ( 2 ) for Z. Jin
  Y. X. Yang , Z. Jin , S. Y. Yoon , J. Y. Choi , P. L. Shinde , X. S. Piao , B. W. Kim , S. J. Ohh and B. J. Chae
  The effects of lysine restriction during grower phase and realimentation during finisher phase on growth performance, nutrient digestibility, blood metabolites, carcass traits and pork quality were studied. Sixty-four pigs (two castrated males and two females per pen) weighing 34.34±5.22 kg were assigned to four dietary treatments. During grower (35-55 kg), pigs were fed isoenergetic lysine-restricted diets. The different lysine content of diets were 0.950 (NRC recommendation), 0.760, 0.665 and 0.570%, corresponding to lysine restriction of 20, 30 and 40%. Then all pigs were fed with common finisher 1 (55-85 kg) and 2 (85-115 kg) diets. Lysine restriction during the grower phase resulted in poor performance and lower concentration of blood metabolites but improved the nutrient digestibility and efficiency of lysine utilization. Compensatory growth response in terms of improved weight gain and feed efficiency was observed in pigs previously fed lysine-restricted diets during finisher 1, but the concentration of blood urea nitrogen and total protein were lower. No differences in growth performance, digestibility of nutrients and blood metabolites were noted during finisher 2. Lysine restriction of grower diets decreased the dressing percentage (quadratic, P=0.024), and protein content of longissimus muscle (linear P=0.034, and quadratic P=0.009). Thus, it could be concluded that pigs subjected to lysine restriction during grower phase exhibited compensatory growth responses in weight gain and improved efficiency of feed and lysine utilization for weight gain and lean accretion during finisher phase.
  Z. Huajun and Z. Jin
  This study proposes a new direct exponential function computer based on CORDIC algorithm to solve the neuron realization problem on the Evolvable Hardware (EHW). The direct exponential function computer combines the essential character of exponential function with CORDIC algorithm and turns aside the conventional approach which computes the exponential function by adding sinh (x) and cosh (x) indirectly. Because the direct computer executes shift-add operation in allusion to exponential function directly and get rid of the computation of sinh (x) and cosh (x), it not only calculates much faster than the indirect computer, but also saves much more logic gates. In addition, through strict and integrated analysis, the direct computer is proved to own perfect convergence. It converges to the real value with arbitrary precision and operates shift-add operation without any unnecessary rotation. Since of the direct efficient shift-add operation, the direct computer is useful for the application of neural network based on the EHW.
 
 
 
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