New exact solutions of the Tzitzéica-type equations in non-linear optics using the expa function method

One specific class of non-linear evolution equations, known as the Tzitzéica-type equations, has received great attention from a group of researchers involved in non-linear science. In this article, new exact solutions of the Tzitzéica-type equations arising in non-linear optics, including the Tzitzéica, Dodd–Bullough–Mikhailov and Tzitzéica–Dodd–Bullough equations, are obtained using the exp_a function method. The integration technique actually suggests a useful and reliable method to extract new exact solutions of a wide range of non-linear evolution equations.     

A PV installation framework concerning electricity variable rates

This paper assesses building integrated photovoltaic (BIPV) installation parameters based on the profit generated by a photovoltaic system. It takes into consideration a home building case study and it investigates its monthly energy demand based on a specific location and a typical occupancy. The capability of a photovoltaic (PV) system to generate more profit occurs when solar intensity is maximum while the electric energy price is at its highest rate. The paper traces a framework that encompasses different aspects such as energy demand, energy price, and solar intensity. This framework identifies profit alternatives according to different installation parameters. A tool that predicts a PV installation hourly electric energy production is developed. The profit generated is simulated for home buildings located in Beirut (Lebanon) and Xihua (China), both at 33.8° latitude north. The paper highlights a new approach for BIPV installations, taking into account weather conditions, energy demand, and electric energy utility rates.     

Predicting Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae) populations and associated grain damage in smallholder farmers’ maize stores: A machine learning approach

Prostephanus truncatus is a notorious pest of stored-maize grain and its spread throughout sub-Saharan Africa has led to increased levels of grain storage losses. The current study developed models to predict the level of P. truncatus infestation and associated damage of maize grain in smallholder farmer stores. Data were gathered from grain storage trials conducted in Hwedza and Mbire districts of Zimbabwe and correlated with weather data for each site. Insect counts of P. truncatus and other common stored grain insect pests had a strong correlation with time of year with highest recorded numbers from January to May. Correlation analysis showed insect-generated grain dust from boring and feeding activity to be the best indicator of P. truncatus presence in stores (r = 0.70), while a moderate correlation (r = 0.48) was found between P. truncatus numbers and storage insect parasitic wasps, and grain damage levels significantly correlated with the presence of Tribolium castaneum (r = 0.60). Models were developed for predicting P. truncatus infestation and grain damage using parameter selection algorithms and decision-tree machine learning algorithms with 10-fold cross-validation. The P. truncatus population size prediction model performance was weak (r = 0.43) due to the complicated sampling and detection of the pest and eight-week long period between sampling events. The grain damage prediction model had a stronger correlation coefficient (r = 0.93) and is a good estimator for in situ stored grain insect damage. The models were developed for use under southern African climatic conditions and can be improved with more input data to create more precise models for building decision-support tools for smallholder maize-based production systems.     

河南渑池地区铝土矿工艺矿物学及锂的赋存状态研究

通过河南省渑池地区含锂铝土矿(岩)层工艺矿物学分析,查明铝土矿的物质组成、嵌布特征、伴生锂分布特征和赋存状态,为矿产综合利用提供理论依据。结果显示:该铝土矿Al2O3含量为54.8%,铝硅比值(A/S)为2.6,铝土矿层和粘土岩层中Li2O含量均高于伴生锂边界品位,粘土岩中锂更为富集；矿物组成除一水硬铝石之外,主要是以集合体形态产出的粘土矿物。采用稀酸解析、选矿测试和电子探针分析锂的赋存状态,查明矿石中锂主要是以类质同象置换形式赋存在伊利石和高岭石等粘土矿物中；选矿富锂尾矿中Li2O可富集到0.57%左右,是锂综合回收利用的重点研究对象。      

斗轮取料机液压控制系统的故障分析及改进

针对臂式斗轮取料机运行中抖动现象,进行了故障分析和排除,并对其液压原理和元件选型进行了优化及改进,为相关液压系统的故障分析和设计选型提供参考。     

紫金山东南矿段成矿期次、阶段浅析

通过对紫金山东南矿段铜钼(金)矿床地质矿化特征分析,指出铜钼矿化带主要赋存于花岗闪长斑岩的内外接触带,处于似斑状花岗闪长斑岩的上部,金矿化带赋存在表生氧化带的英安玢岩、隐爆角砾岩中。经过对矿石的组构特征、矿物生成顺序等特征分析,将矿床的成矿演化过程分为斑岩热液期、高硫化浅成低温热液期、表生氧化期三个主要矿化期次,进一步将斑岩热液期分为黑云母-钾长石化阶段、石英-绢云母化阶段、碳酸盐化阶段三个阶段;高硫化浅成低温热液期分为地开石化阶段、明矾石化阶段、硅化阶段三个阶段。研究结果为进一步研究矿床成因提供了依据。     

改进Elman神经网络在短期热负荷预测中的应用

热电厂的短期热负荷预测在城市集中供暖中起着至关重要的作用,直接影响热电厂的经济效益和热能利用率。电厂的短期热负荷一般采用神经网络预测模型进行预测,而BP神经网络应用最为广泛。Elman神经网络算法在BP神经网络基础上加入了承接层,作为一步延时算子,实现记忆能力,使系统具备适应时变能力,增强系统全局稳定性。但Elman神经网络算法模型的构造依然需要大量样本的支撑,而且输入层的变量多,导致预测时间依然很长,收敛速度慢。该文在Elman神经网络预测前,进行了相关系数预处理和对样本中异常值的平均化预处理,通过数据归一化运算,使Elman神经网络输入层变量大幅减少。仿真实验表明,改进的Elman神经网络算法使预测模型快速寻优,减少预测时间的同时明显提高预测精度。     

Etching characteristics of thin SiON films using a liquefied perfluorocarbon precursor of C6F12O with a low global warming potential

Perfluorocarbon gas is widely used in the semiconductor industry. However, perfluorocarbon has a negative effect on the global environment owing to its high global warming potential (GWP) value. An alternative solution is essential. Therefore, we evaluated the possibility of replacing conventional perfluorocarbon etching gases such as CHF₃ with C₆F₁₂O, which has a low GWP and is in a liquid state at room temperature. In this study, silicon oxynitride (SiON) films were plasma-etched using inductively coupled CF₄ +C₆F₁₂O+O₂ mixed plasmas. Subsequently, the etching characteristics of the film, such as etching rate, etching profile, selectivity over Si, and photoresist, were investigated. A double Langmuir probe was used and optical emission spectroscopy was performed for plasma diagnostics. In addition, a contact angle goniometer and x-ray photoelectron spectroscope were used to confirm the change in the surface properties of the etched SiON film surface. Consequently, the etching characteristics of the C₆F₁₂O mixed plasma exhibited a lower etching rate, higher SiON/Si selectivity, lower plasma damage, and more vertical etched profiles than the conventional CHF₃ mixed plasma. In addition, the C₆F₁₂O gas can be recovered in the liquid state, thereby decreasing global warming. These results confirmed that the C₆F₁₂O precursor can sufficiently replace the conventional etching gas.     

基于启发式BP算法的软件缺陷预测模型

针对软件缺陷预测时缺陷数据集中存在的类别分布不平衡问题，结合上采样算法SMOTE与Edited Nearest Neighbor (ENN) 数据清洗策略，提出了一种基于启发式BP神经网络算法的软件缺陷预测模型。模型中采用上采样算法SMOTE增加少数类样本以改善项目中的数据不平衡状况，并针对采样后数据噪声问题进行ENN数据清洗，结合基于启发式学习的模拟退火算法改进四层BP神经网络后建立分类预测模型，在AEEEM数据库上使用交叉验证对提出的方案进行性能评估，结果表明所提出的算法能够有效提高模型在预测类不平衡数据时的分类准确度。