An Alternative Algorithm for Soft Set Parameter Selection using Special Order

The outcome of the reduction of soft data is dependent on the quality and discount evidence that increases with optimization analysis. There is a set of techniques that can be used to reduce the data, but the different techniques showed different results as each technique is focused on solving a particular problem. This paper proposed a parameter reduction algorithm, known as 3C algorithm, to circumvent the false frequent object in reduction. Results indicated that the proposed algorithm is easy to implement and perform better than the state-of-the-art parameter reduction algorithm. Also, the proposed algorithm can be used as an effective alternative method for reducing parameters in order to enhance the decision making process. Comparative analysis were performed between the proposed algorithm and the state-of-the-art parameter reduction algorithm using several soft set in terms of parameter reductio

Hybrid Filter for Attributes Reduction in Soft Set

The purpose of this research is to overcome hybrid parameterization reduction limitation that focuses only on individual parameter reduction, whereas in some cases the individual parameter reduction is not sufficient even implies reduction. It was found that the reduction sometimes is not able to reduce the number of data; hence, for this reason it became necessary to look for an alternative technique that can significantly reduce the parameters. This paper proposed an alternative method based on hybrid filter to select attributes in soft set. For significant candidates the method used R supp checking to confirm the correctness of the reduction. Comparison of the reduction methods shows that the proposed method provides better result than the parameterization reduction in enhancing reduction. The false candidates were filtered in the huge candidate reduction by the Min supp. The proposed method can be used to maintain object before attribute reduction as well as to reduce parameter size drastically while maintaining consistency in decision making

Analysis of Parameterization Value Reduction of Soft Sets and its Algorithm

In this paper, the parameterization value reduction of soft sets and its algorithm in decision making are studied and described. It is based on parameterization reduction of soft sets. The purpose of this study is to investigate the inherited disadvantages of parameterization reduction of soft sets and its algorithm. The algorithms presented in this study attempt to reduce the value of least parameters from soft set. Through the analysis, two techniques have been described. Through this study, it is found that parameterization reduction of soft sets and its algorithm has yielded a different and inconsistency in suboptimal result

Hybrid Framework Parameterization Reduction Combination in Soft Set

Voluminous data are available in soft sets,which makes itdifficult to recognize the soft set decisions of the data.The large increase in the volume of these soft set has made it necessary to enlarge the size of the storage media to store the data. Consequently,several researches have proposeds oft set reduction of the data. This paper proposes uncertain soft set by hybridizing two soft set reduction techniques producing a significant result without affecting the decisive characteristics of the data. This proposed method utilizes advanced techniques to govern knowledge with proper reduction of related resources that can assist the decision making process

Effect of Moringa oleifera feed supplementation on the serum biochemical profile of broilers challenged with very virulent infectious bursal disease virus

Objective: This study was conducted to assess the effect of dietary Moringa oleifera leaf (MOL) feed supplementation on serum biochemical parameters of broilers challenged with very virulent infectious bursal disease virus (vvIBDV). Materials and methods: Two hundred and forty day-old Ross 308 hybrid broiler chicks were randomly assigned into four groups (A, B, C and D) of 60 chicks each and raised in deep litter housing. Broiler starter (BS) and broiler finisher (BF) mash were formulated each with 5% MOL included as part of the feed ingredient for broilers in groups A and B while BS and BF for broilers in groups C and D were formulated without MOL. Broilers in groups A, B and C were challenged intraocularly at 35 days of age with with 0.05 mL of a live vvIBDV, while those in group D served as control. Blood was collected from 10 broilers in each group via the wing vein at 35, 38 and 42 days of age to determine their serum biochemical profile. Results: The level of melondialdehyde (MDA) was observed to significantly decrease in groups A and C. There was a significant decrease in the level of AST in group A, B, C and D. The values of ALT significantly decreased in group A, B, C and D. Conclusion: Supplementing broilers feed with MOL neither protect the liver from damage nor prevent lipid peroxidation. [J Adv Vet Anim Res 2018; 5(2.000): 155-165

Aloe vera Gel Ameliorates Fat-Rich and High Fructose (FRHF) Diet-Induced Pancreatic and Splenic Damage in Mice

High-fat diet alone or in combination with high fructose has been known to induce diabetes, obesity, hypertension, and immune dysfunction. The study evaluates the role of Aloe vera in fat-rich and high fructose diet-induced (FRHFD) hyperglycemias in addition to testicular and splenic morphology in mice. Twenty BALB/c Mice were randomly distributed into four groups (n=5). The groups were fed on a normal diet, FRHFD, FRHFD + 10 g Aloe vera, and FRHFD + 20 g Aloe vera for 10 weeks. All the mice were sacrificed a day after the 10 weeks of treatment. The result showed that mice fed on FRHFD plus Aloe vera had a significantly lower (p<0.05) blood glucose level relative to the FRHFD-fed mice. The mice fed on FRHFD plus Aloe vera had a significantly lower (p<0.05) blood glucose level relative to the FRHFD-fed mice. Aloe vera was found to ameliorate FRHFD-induced pancreatic islet and acini damage. It also prevented distorted lymphoid cells and testicular damage induced by FRHFD. Aloe vera prevents hyperglycemia and protects pancreatic islets in FRHFD-fed mice. It further prevents immune dysfunction and protects against testicular damage. Hence, Aloe vera supplementation could be an alternative and/or complementary therapy for hyperglycemia-related disorders