Effect of processing steps on the physico-chemical properties of dried-seasoned squid

The effects of processing steps on the physico-chemical properties of dried-seasoned squid were studied using two kinds of squids. Browning was observed as indicated by an increase in yellowness (b^∗ value) during the semi-drying and roasting step. The temperature and time of heating and type of roasting, as well as the material itself were the key factors influencing the browning. A high level of trimethylamine oxide (TMAO), and low contents of trimethylamine (TMA) and dimethylamine (DMA) were detected in the raw material. TMAO gradually decreased during the processing, while TMA, DMA and formaldehyde (FA) increased significantly especially in boiled meat. The temperature of boiling was the most crucial factor impacting the production of FA. FA could be greatly decreased during the cooling process by washing with water or changing the roasting techniques. Therefore, to improve the quality of dried-seasoned squid, more attention should be paid to the temperature and roasting techniques during the processing.     

FA272并条机的电气改造

纺织厂使用的并条机FA272,原电气控制为继电器接触控制,经过多年的使用,设备老化,另外,原设计的一些缺陷已明显暴露出来,现采用PLC和变频器进行技术改造,可简化外围控制电路,降低控制线路的故障率,提高运行可靠性,控制性能明显提高,大大地提高了生产效益,受到了厂家的欢迎.     

基于EEMD和萤火虫算法优化SVM的溶解氧预测

养殖池塘中的溶解氧(DO)对水产品的生长和品质有着至关重要的作用.为了提高溶解氧预测的准确性和有效性,提出了一种基于集合经验模态分解(EEMD)和萤火虫算法(FA)优化支持向量机(SVM)的组合预测模型.首先,将DO 时间序列通过集合经验模态分解为一组去除噪声的并相对稳定的子序列.接着,利用相空间重构(PSR)重建分解...     

9FA燃气轮机的供气降压运行技术

9FA燃气轮机正常的天然气供气压力在4.0MPa及以上,那么在供气压力为2.0MPa时机组能否实现降压运行呢?通过对某厂9FA燃气轮机的供气降压运行实践证明,这种技术是可行的。9FA燃机的供气降压运行技术,拓宽了机组运行的供气范围,对某些天然气压力不足的地区有着现实的意义。     

基于拓扑改进与交叉策略的萤火虫算法

针对萤火虫算法（FA）复杂度大，对高维函数优化困难，容易陷入局部极小值等问题，提出了基于拓扑改进与交叉策略的萤火虫算法。该算法用冯诺依曼拓扑结构来模拟萤火虫之间的邻域结构，提高了全局搜索能力，并且减小了计算复杂度。同时，引入自适应交叉策略，根据萤火虫的多样性动态的调整交叉概率，增强了萤火虫跳出局部最优的能力。对8个标准测试函数的仿真实验表明，改进后的萤火虫算法与标准萤火虫算法相比，有更高的收敛精度和稳定性。     

Effect of increasing amounts of a linoleic-rich dietary fat on the fat composition of four pig breeds. Part I: Backfat fatty acid evolution

Four diets prepared, respectively, with 0%, 2%, 4% and 8% of a high-linoleic added fat were administered (76 days of treatment) to a sample of 112 pigs of four breeds (Landrace, Large White, Duroc and a crossbreed Landrace × Duroc). The effects of diet and breed on the evolution of the fatty acid composition of backfat were examined by taking biopsies. Over time, a continuous increase in stearic, palmitic and oleic acids throughout the pig’s life was observed. Oleic acid showed the smallest differences among the four diets at the end of the experiment, while stearic and palmitic acid showed higher differences according to the increase in the percentage of dietary fat. Stearic acid showed the highest rate of increase over time, according to the increasing intake of linoleic acid (diets 1–4). These increases were compensated by a decrease in linoleic acid, although this decrease tended to stabilize according to a higher percentage of added fat and also, for diet 4 (8% fat), an increase in linoleic acid was observed at the end of the experiment. Among the minor fatty acids, arachidonic acid showed a clear decrease over time, although higher levels at the end of the experiment were observed for diets including 4% and 8% of added fat, compared to the other two diets including lower amounts of linoleic acid. Moreover, a significant effect was observed for the factor breed. So, Duroc pigs showed the highest rate of deposit of linoleic acid and the lowest of stearic acid, while the other three breeds showed similar rates.     

基于改进萤火虫算法求解旅行商问题

鉴于TSP问题是古老的组合优化难题,而萤火虫算法在求解函数优化问题中表现出优良的性能,因此,本文利用改进的萤火虫算法求解TSP问题.首先,在分析了旅行商问题的特点后,采用整数编码的方式来表示萤火虫的位置.然后,在标准萤火虫算法的位置更新过程中引入了对数递减的惯性权重来影响萤火虫的迭代过程,同时结合了遗传算法中的选择,交叉,变异以及进化逆转操作来提高每一次迭代中种群的多样性及种群的搜索能力,并将改进的算法解决TSP问题.最后,通过Matlab仿真实验表明改进的算法在求解TSP问题时具有更好收敛速度和优化效果.     

基于萤火虫算法的无线传感器网络的分簇路由协议

在无线传感器网络(WSNs)中,合适的分簇方法对于网络的能量损耗和能量均衡至关重要,通过采用自组织映射神经网络和萤火虫算法,以寻求最优解,从而获取合适的分簇,并且在数据传输阶段采用新的路由协议.实验表明:通过这些方法可以延长网络存活时间和均衡网络结构.     

Wind turbine micrositing by using the firefly algorithm

Traditionally energy has been a burning issue of mankind, however, this trend has changed with the advent of clean technologies such as wind power. It is common knowledge that wind turbines need to be installed in an open, unobstructed area to obtain the maximal power output. This document attempts to solve the problem of optimization of the layout of large wind farms by the use of nature inspired algorithms. Particular reference is made to the use of the firefly algorithm. A good comparison is made with the past approaches of the use of spread sheets and GA's for optimization.     

A real time experimental setup for classification of epilepsy risk levels

The objective of this paper is to analyze the performance of singular value decomposition, expectation maximization, and Elman Neural Networks in optimization of code converter outputs in the classification of epilepsy risk levels from EEG (electroencephalogram) signals. The signal parameters such as the total number of positive and negative peaks, spikes and sharp waves, their duration etc., were extracted using morphological operators and wavelet transforms. Code converters were considered as a level one classifier. Code converters were found to have a performance index and quality value of 33.26 and 12.74, respectively, which is low. Consequently, for the EEG signals of 20 patients, the post classifiers were applied across 3 epochs of 16 channels. After having made a comparative study of different architectures, SVD was found to be the best post classifier as it marked a performance index of 89.48 and a quality value of 20.62. Elman neural network also exhibits good performance metrics than SVD in the morphological operator based feature extraction method.