Sentiment Analysis of Code-Mixed Bambara-French Social Media Text Using Deep Learning Techniques

The global growth of the Internet and the rapid expansion of social networks such as Facebook make multilingual sentiment analysis of social media content very necessary. This paper performs the first sentiment analysis on code-mixed Bambara-French Facebook comments. We develop four Long Short-term Memory (LSTM)-based models and two Convolutional Neural Network (CNN)-based models, and use these six models, Naïve Bayes, and Support Vector Machines (SVM) to conduct experiments on a constituted dataset. Social media text written in Bambara is scarce. To mitigate this weakness, this paper uses dictionaries of character and word indexes to produce character and word embedding in place of pre-trained word vectors. We investigate the effect of comment length on the models and perform a comparison among them. The best performing model is a one-layer CNN deep learning model with an accuracy of 83.23 %.     

Systemic Thinking and Practice Toward Facilitating Inclusive Education: Reflections on a Case of Co-Generated Knowledge and Action in South Africa

This article offers our reflections around a case of facilitating systemic thinking and practice in which the first author of the article (Tlale) interacted with research participants/participant researchers with the intention of strengthening systemic thought and action toward fostering inclusive education in the setting (a rural school in the Eastern Cape in South Africa). We reflect upon the process and also how our engagement was perceived by participants, as expressed in feedback received from them. We point to how Tlale introduced the idea of systemic thinking (to teachers, school management team, school governing body, and a district officer for the district) as tied to the possibility of acting to generate transformation toward a more inclusive educational context for the benefit of the learners at the school in question, thus acting as a systemic mediator on their behalf.     

The Ordering and Replacement Policy for the System with Two Types of Failures

In this paper, the optimal maintenance policy is investigated for a system with stochastic lead time and two types of failures. The system has two types of failures, one type is repairable, when the repairable failure occurs, the system will be repaired by repairman, and the system after repair is not "as good as new". The other type of failure is unrepairable, and when the unrepairable failure occurs the system must be replaced by a new and identical one. The spare system for replacement is available only by order, and the lead time for delivering the spare system is stochastic. The successive survival times of the system form a stochastically decreasing geometric process, the consecutive repair times after failures of the system form a renewal process. By using the renewal process theory and geometric process theory, the explicit expression of the long-run average cost per unit time under ordering policy(N-1) is derived, and the corresponding optimal can be found analytically. Finally,the numerical analyses are given.     

Effect of MWCNT reinforcement on the precipitation-hardening behavior of AA2219

Aluminum alloy matrix composites have found a predominant place in research, and their applications are explored in almost all industries. The aerospace industry has been using precipitation-hardenable alloys in structural applications. However, insufficient literature is available on the influence of multiwalled carbon nanotubes (MWCNTs) on precipitation-hardenable alloy composite materials; thus, this work was designed to elucidate the effect on MWCNT reinforcement on AA2219 with and without precipitation hardening. Reinforcement with MWCNTs has been reported to accelerate precipitation and to achieve greater hardness within a much shorter time. The addition of 0.75wt% MWCNTs resulted in maximal hardness at 90 min, which is approximately 27% of improvement over the maximum hardness achieved by the corresponding monolithic alloy after 10 h of aging. The sample reinforced with 0.75wt% MWCNTs showed an improvement of 82% in hardness by solutionizing and aging compared to that achieved by sintering.     

近空间雷达网角度定位算法

研究了一种基于角度信息的近空间雷达网定位算法.首先根据几何关系将目标与各站的关系方程转换成线性方程,并求出带噪声的最小二乘解,然后通过最大似然估计将定位问题转化成无约束极值问题,以最小二乘解为初值,利用DFP算法进行迭代求得更精确的定位解,并给出了求解的详细步骤,最后推导了几何精度因子的表达式,并对算法性能和定位精度进行了仿真分析,证明了算法的有效性.     

处理旋转运动图象模糊问题的一种算法

提出了处理旋转体图象运动模糊现象的一种算法。该算法取决于图象退化过程的先验知识。在先求出匀速直线运动模糊处理算法的基础上,推导出匀速旋转体的运动模糊处理算法。实验结果表明,该算法较好地解决了图象运动模糊问题。     

变形压力钢管的压力脉动

给出了变形压力钢管压力脉动的偏微分方程,并针对压力钢管一端有压力脉动的情形进行了线性化求解,这对于输液管道的稳定性,特别是对水力机组压力钢管内水体共振现象的分析具有一定的实用性．     

全站仪中间法三角高程测量精度分析

通过对全站仪中间法三角高程测量原理进行分析,推导了中间法三角高程的误差传播公式,研究了测距误差、测角误差和大气折光系数误差对高差的精度影响.采用中间法三角高程测量方法在一个较小范围内进行了三角高程测量,779 m的水准路线测量闭合差为0.5 mm,并和精密二等水准成果进行了对比分析,试验结果验证了该方法可以替代高精度水准测量的可行性.     

一种无需操作系统的硬件级可信度量方法

针对云计算等新型计算环境下的可信度量问题,提出了一种无需操作系统的硬件级全盘任意文件可信度量方法.通过在U-key中放置可信度量代理(TMA),利用TMA自主解析文件系统获取磁盘中任意文件的扇区存储地址,从而能够在不存在Grub、未启动操作系统以及不需要其他任何硬软件支持的情况下,实现对全盘任意文件的可信度量.考虑到TMA的安全性,利用B方法实现了对TMA的形式化开发.与已有的工作相比,所提方法不仅能够应用在云计算等新型计算环境中,而且能够应用于不存在可信平台模块(TPM)等安全增强芯片的普通计算机上.实验证明了本方法是有效的.