An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.     

基于四水听器的充水弹性管声速测量方法*

实验室中水声材料声学参数的测量主要在水声声管中进行。管内平面波声速是正确测量这些参数的基础。该文提出一种基于四水听器结合不同边界的测量充水弹性管中声速的新方法。该方法利用4个固定位置处的水听器,采用最小二乘的方法,使得两组水听器分别得到的声管末端入射波声压差值的平方最小的声速即为管内平面波声速。该方法利用单频信号,在每一频率点均可测得声速,可以在任一种声管末端边界下进行测量,同时无需知道各水听器到边界的精确距离,在文中的3种边界下声速测量结果具有很好的一致性,实验操作简单、误差很小。该方法的仿真结果与管内声速的理论值吻合得很好,同时实验测量结果与仿真值之间的误差很小,证明了方法的准确性以及鲁棒性,为声管声速测量提供一个很好的思路。     

KEADA: Identifying Key Classes in Software Systems Using Dynamic Analysis and Entropy-Based Metrics

Software maintenance is indispensable in the software development process. Developers need to spend a lot of time and energy to understand the software when maintaining the software, which increases the difficulty of software maintenance. It is a feasible method to understand the software through the key classes of the software. Identifying the key classes of the software can help developers understand the software more quickly. Existing techniques on key class identification mainly use static analysis techniques to extract software structure information. Such structure information may contain redundant relationships that may not exist when the software runs and ignores the actual interaction times between classes. In this paper, we propose an approach based on dynamic analysis and entropy-based metrics to identify key classes in the Java GUI software system, called KEADA (identifying KEy clAsses based on Dynamic Analysis and entropy-based metrics). First, KEADA extracts software structure information by recording the calling relationship between classes during the software running process; such structure information takes into account the actual interaction of classes. Second, KEADA represents the structure information as a weighted directed network and further calculates the importance of each node using an entropy-based metric OSE (One-order Structural Entropy). Third, KEADA ranks classes in descending order according to their OSE values and selects a small number of classes as the key class candidates. In order to verify the effectiveness of our approach, we conducted experiments on three Java GUI software systems and compared them with seven state-of-the-art approaches. We used the Friedman test to evaluate all approaches, and the results demonstrate that our approach performs best in all software systems.     

一种针对FPGA位流的自动化故障注入分析方法

理论上通过篡改FPGA位流,利用其实现的密码算法的错误输出可以分析出密钥,但这种攻击通常需要非常了解目标FPGA的内部结构与位流的对应关系。而位流逆向的难度很大,导致此类攻击的实用性不高。文章提出一种针对FPGA位流的自动化故障注入分析方法,不需要逆向位流,结合张帆等人提出的持久性故障分析理论,把因篡改算法常量导致的出错结果作为可利用的故障。并首次在Xilinx-7系列FPGA开发板上利用Spider进行电压故障注入实验,480条错误密文就可以得到AES-128的密钥,且在10 min内可以完成数据的采集和分析。对于加密位流的情况,可以先利用电磁侧信道分析方法得到明文位流,再结合该文的分析方法来进行密钥破解。     

基于VR技术的智能变电站混合巡检培训系统设计

为提升变电站混合巡检培训系统对学员的培训效率、增加学员的体验感和学习兴趣,设计了一种基于VR技术的智能变电站混合巡检培训系统,通过SolidWorks和3D Max结合设备电气特点、动作特点以及物理特点共同构建变电站设备场景,采用3D Max软件创建三维虚拟变电站场景,便于学员在三维场景中漫游巡检.在实验中,通过变压器...     

晶格畸变检测仪研究碳化硅晶片中位错缺陷分布

利用晶格畸变检测仪研究了SiC晶片位错分布情况,通过对熔融KOH腐蚀后的SiC晶片进行全片或局部扫描,从而得到完整SiC晶片或局部区域的位错分布.与LEXT OLS40003D激光共聚焦显微镜扫描腐蚀图进行比较,晶格畸变检测仪扫描腐蚀图可以将晶片上位错腐蚀坑信息完全呈现出来,且根据腐蚀坑呈现的颜色及尺寸大小,可以分辨出...     

Dempster-Shafer证据理论在目标意图预测中的应用

为了准确对目标意图进行预测,以便我方及时合理地作出战术决策,采用D-S证据理论对目标意图进行预测。首先提取出影响目标意图预测的各个态势因素,然后分析每个因素的影响效果。在此基础上建立目标意图预测的数学模型,利用D-S合成法则将所有因素的影响进行综合,并计算出各个可能命题的概率赋值并给出相应决策。最后,通过仿真实例验证了该方法在目标意图预测中的可行性和实用性。     

一种新的全姿态指示画面填充算法

现代飞机座舱主飞行仪显示系统中,全姿态指示天地区域的填充是件非常费时的工作。提出了一种新的区域填充算法。该算法第一步引入分块查找的思想以及基于填充区域的特点确定采用水平线或者竖直线扫描方式,并且对区域轮廓中满足关键码字段的像素点建立坐标数组;第二步根据已确定的扫描方式进行区域填充。此外,求取新旧地平线交点并没有采用通过大量数值计算直接求取的方法,而是采用了比较法。实验结果表明该算法显著提高了填充速度和显示效果,降低了数据存储空间量。     

对数比放大电路在精密光功率计中的应用

光功率测量是光纤通信系统最基本的测量参数之一.在实际测量中,光功率计要求有很大的动态测量范围.采用传统线性放大电路设计的光功率计,存在着换档误差,动态测量范围也受到限制.由于结果显示要进行对数运算,软件处理也相对比较复杂.为改善上述不足,使用对数比放大电路代替传统的线性放大电路.这样可以避免换档误差和繁琐的对数运算,提高精度.经过实际设计验证,改进设计可获得80 dB动态范围,0.1 dLBm的测量精度,而且电路简洁、易于校准.此设计方法已在实际产品得以应用.     

一种改进的单载波频域迭代均衡算法

改进了传统频域迭代均衡算法中相关系数的计算.仿真发现,在数字电视地面广播信道,提出的算法以更低的复杂度获得了比已有算法更好的性能.