关于职业院校PLC课程的教学质量提升策略分析

职业院校毕业的学生其在未来工作中的表现如何在很大程度上取决于职业院校的教学质量如何.本文所提出的一些办法可以调动学生学习的积极性和主动性,实现自主学习,在提升PLC课程教学质量的同时也保障学生良好的学习效果,希望能为今后职业院校PLC课程教学的深入发展奠定良好的基础.     

Assessment model of classroom acoustics criteria for enhancing speech intelligibility and learning quality

In this paper, a new classroom acoustics assessment model (CAAM) based on analytic hierarchy process (AHP) for enhancing speech intelligibility and learning quality is proposed. The model is based on five main criteria that affect the learning process and related to classrooms acoustical properties. These include classroom specifications, noise sources inside and outside the classroom, teaching style, and vocal effort. The priority and weights of these major criteria along with their alternatives are identified using the views of students, staff, education consultants, and expertise by using a developed questionnaire, and the AHP methodology. This model can be considered as a helpful framework enabling universities decision makers to take effective decisions on classroom acoustics treatment issues. It also provides colleges’ higher authorities the suitable guidelines that help for determining necessary requirements that help to raise the quality and efficiency of the educational environment; in order to reach an excellent learning environment; and hence increasing students learning outcomes.     

SUMONA: A supervised method for optimizing network alignment

This study focuses on improving the multi-objective memetic algorithm for protein–protein interaction (PPI) network alignment, Optimizing Network Aligner – OptNetAlign, via integration with other existing network alignment methods such as SPINAL, NETAL and HubAlign. The output of this algorithm is an elite set of aligned networks all of which are optimal with respect to multiple user-defined criteria. However, OptNetAlign is an unsupervised genetic algorithm that initiates its search with completely random solutions and it requires substantial running times to generate an elite set of solutions that have high scores with respect to the given criteria. In order to improve running time, the search space of the algorithm can be narrowed down by focusing on remarkably qualified alignments and trying to optimize the most desired criteria on a more limited set of solutions. The method presented in this study improves OptNetAlign in a supervised fashion by utilizing the alignment results of different network alignment algorithms with varying parameters that depend upon user preferences. Therefore, the user can prioritize certain objectives upon others and achieve better running time performance while optimizing the secondary objectives.     

Ultrafiltration‐LC–MS combined with semi‐preparative HPLC for the simultaneous screening and isolation of lactate dehydrogenase inhibitors from Belamcanda chinensis

Stroke represents the fourth leading cause of death in the USA and the second leading cause of death worldwide. Lactate dehydrogenase inhibitors are widely used in the treatment of ischemic stroke and natural products are considered a promising source of novel lactate dehydrogenase inhibitors. In this study, we used PC12 cells to determine the protective effect of extracts from the herb Belamcanda chinensis following toxic challenge. Using ultrafiltration high‐performance liquid chromatography coupled with photo‐diode array detection and electrospray ionization mass spectrometry, we screened and identified isoflavonoids from Belamcanda chinensis extracts. Semi‐preparative high‐performance liquid chromatography was then applied to separate and isolate the active constituents. Using these methods, we identified six major compounds in Belamcanda chinensis as lactate dehydrogenase inhibitors: tectoridin, iristectorin A, iridin, tectorigenin, irigenin, and irisflorentin, which were then isolated to >92% purity. This is the first report that Belamcanda chinensis extracts contain potent lactate dehydrogenase inhibitors. Our results demonstrate that the systematic isolation of bioactive components from Belamcanda chinensis guided by ultrafiltration high‐performance liquid chromatography coupled with photo‐diode array detection and electrospray ionization mass spectrometry represents a feasible and efficient technique that could be extended for the identification and isolation of other enzyme inhibitors.     

改进人工蜂群算法优化ELM分类模型

针对极限学习机(Extreme Learning Machine,ELM)参数优化问题,提出改进人工蜂群算法(Improvement Artificial bee colony, IABC)优化ELM分类模型。算法采用解更新策略池代替固定不变的更新策略,将邻域搜索自适应化;优化侦察蜂搜索方式,利用Kent映射产生均匀性更优的初始随机数序列。在分类数据集中,将IABC-ELM分类模型同ELM、PSO-ELM分类模型进行对比实验。实验中,IABC-ELM模型取得了最佳的分类结果,得到了最低的输出权重范数。结果表明,IABC-ELM模型分类效果显著优于对比模型,证实了IABC算法优化ELM分类模型的有效性和优越性。     

集成电路生产中成品率的有效管理

本文分析了在集成电路制造过程中,使用的基础材料、设备、工艺技术所产生的污染粒子,随机缺陷对IC产品成品率的影响。并主要介绍了从经典学习曲线概念中推导出来的成品率提高模型已被用于追踪产品成品率的提高,该模型建立在能优先迅速解决影响成品率诸多问题的基础上。实际成品率与模型化成品率的比较充分证明了成品率提高模型的实际意义。     

Controllability of Linear Systems in Non Reflexive Banch Spaces

§ 1.Introduction　 Let Xand Ube Banch spaces,S(t) a C0 semi-group in X,A the infinitesimal gen-erator of S(t) ,and B∈L(U,X) .Consider the systemΣP:x(t) =Ax(t) + Bu(t) ,　 t≥ 0 ,(1 .1 )where u∈ Lploc([0 ,∞ ) ,U) ,1≤p<∞ .　 The problem of controllability of linear systems in Banch spaces has been studied bymany authors.In [1 ] ,the weak and strong reachability and controllability of infinite di-mensional linear systems were investigated.In[2 ,3 ,4 ] ,the controllability of infi…     

Learning effect and deteriorating jobs in the single machine scheduling problems

This paper studies the single machine scheduling problems with learning effect and deteriorating jobs simultaneously. In this model, the processing times of jobs are defined as functions of their starting times and positions in a sequence. It is shown that even with the introduction of learning effect and deteriorating jobs to job processing times, the makespan, the total completion time and the sum of the k$k$th power of completion times minimization problems remain polynomially solvable, respectively. But for the following objective functions: the total weighted completion time and the maximum lateness, this paper proves that the shortest weighted processing time first (WSPT) rule and the earliest due-date first (EDD) rule can construct the optimal sequence under some special cases, respectively.     

Representation in the (Artificial) Immune System

Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or, modelling biologically plausible dynamical systems, with little overlap between. We propose that this dichotomy is somewhat to blame for the lack of significant advancement of the field in either direction and demonstrate how a simplistic interpretation of Perelson’s shape-space formalism may have largely contributed to this dichotomy. In this paper, we motivate and derive an alternative representational abstraction. To do so we consider the validity of shape-space from both the biological and machine learning perspectives. We then take steps towards formally integrating these perspectives into a coherent computational model of notions such as life-long learning, degeneracy, constructive representations and contextual recognition—rhetoric that has long inspired work in AIS, while remaining largely devoid of operational definition.     

薏仁种类的近红外光谱技术快速鉴别

薏仁是一种药食两用资源,对其品质快速鉴别的需求也越来越多,近红外光谱技术(near infrared spectroscopy,NIRS)作为一种快速、 无损且环保的方法正适合这一需求。 以不同产地和品种薏仁的近红外光谱为基础,结合化学计量学方法对薏仁种类进行鉴别。 对原光谱用无监督学习算法主成分分析(principal component analysis,PCA)和有监督学习算法学习向量量化(learning vector quantization,LVQ)神经网络、 支持向量机(support vector machine,SVM)进行定性判别分析。 由于不同地区和不同品种的薏仁营养物质组成复杂且含量相近,所选两类薏仁的特征变量很相似,因而PCA得分图重叠严重,很难区分;而LVQ神经网络和SVM都能得到满意结果,LVQ神经网络的预测正确率为90.91%,SVM在经过惩罚参数和核函数参数优选后,分类准确率能达到100%。 结果表明：近红外光谱技术结合化学计量学方法可作为一种快速、 无损、 可靠的方法用于薏仁种类的鉴别,并为市场规范提供技术参考。