A KNN Undersampling Approach for Data Balancing

In supervised learning, the imbalanced number of instances among the classes in a dataset can make the algorithms to classify one instance from the minority class as one from the majority class. With the aim to solve this problem, the KNN algorithm provides a basis to other balancing methods. These balancing methods are revisited in this work, and a new and simple approach of KNN undersampling is proposed. The experiments demonstrated that the KNN undersampling method outperformed other sampling methods. The proposed method also outperformed the results of other studies, and indicates that the simplicity of KNN can be used as a base for efficient algorithms in machine learning and knowledge discovery.

Relationship of Uncertainty Between Polygon Segment and Line Segment for Spatial Data in GIS

The mathematic theory for uncertainty model of line segment are summed up to achieve a general conception, and the line error hand model of εσ is a basic uncertainty model that can depict the line accuracy and quality efficiently while the model of εm and error entropy can be regarded as the supplement of it. The error band model will reflect and describe the influence of line uncertainty on polygon uncertainty. Therefore, the statistical characteristic of the line error is studied deeply by analyzing the probability that the line error falls into a certain range. Moreover, the theory accordance is achieved in the selecting the error buffer for line feature and the error indicator. The relationship of the accuracy of area for a polygon with the error loop for a polygon boundary is deduced and computed.

Intelligent tools and techniques for modern management

In order to make decisions all companies need information. As a rule, all the informatics systems of a company contain a multitude of data and turn these data into information that has to be analyzed in order to make decisions. It is a slow process. The solution of this drawback is given by Business Intelligence （BI） applications that can help companies increase income or diminish costs by offering the executive management appropriate information on the basis of which quick and efficient decisions can be taken.The main purpose of the paper is to prove the necessity that BI tools should be used by the modem manager. Managers are aware of that by putting into practice the BI solutions, opportunities of getting control over the business process and methods are improved and better, timely analysis functions of the performance parameters can be obtained.

Identification of Best Model for Equilibrium Data of Ethanol-Water Mixture

Four empirical models are tested for fitting the T-y-x equilibrium data of ethanol-water mixture by minimizing the Root Mean Square （RMS） between equilibrium data and theoretical points. The total pressure of the correspondent data is 101.3 kPa. All models parameters are also identified. The study suggests that NRTL model fits the equilibrium data best with RMS = 0.4 %.

Benchmarking visual SLAM methods in mirror environments

Visual simultaneous localisation and mapping(vSLAM)finds applications for indoor and outdoor navigation that routinely subjects it to visual complexities,particularly mirror reflections.The effect of mirror presence(time visible and its average size in the frame)was hypothesised to impact localisation and mapping performance,with systems using direct techniques expected to perform worse.Thus,a dataset,MirrEnv,of image sequences recorded in mirror environments,was collected,and used to evaluate the performance of existing representative methods.RGBD ORB-SLAM3 and BundleFusion appear to show moderate degradation of absolute trajectory error with increasing mirror duration,whilst the remaining results did not show significantly degraded localisation performance.The mesh maps generated proved to be very inaccurate,with real and virtual reflections colliding in the reconstructions.A discussion is given of the likely sources of error and robustness in mirror environments,outlining future directions for validating and improving vSLAM performance in the presence of planar mirrors.The MirrEnv dataset is available at https://doi.org/10.17035/d.2023.0292477898.

二芳基三嗪类化合物抗HIV-1活性的理论研究

应用分子力学方法、从头算法优化了28个二芳基三嗪(DATA)类抗野生型HIV-1化合物分子结构,从分子构象模型中提取了多类参数,结合电子类参数、几何类参数、分子物化参数与活性之间建立了QSAR多元线性回归模型.模型显示:分子中连接三嗪环与B环的X位置上净电荷量的增加以及分子中吸电子基团的引入有利于其抗HIV-1活性的增强,同时,前线轨道能级差ΔE的增大和分子体积适当的增大亦有利于其抗HIV-1活性的提高,并且后两者是影响该类化合物抗HIV-1活性的主要因素.

Development of non-nucleoside reverse transcriptase inhibitors(NNRTIs):our past twenty years

Human immunodeficiency virus(HIV)is the primary infectious agent of acquired immunodeficiency syndrome(AIDS),and non-nucleoside reverse transcriptase inhibitors(NNRTIs)are the cornerstone of HIV treatment.In the last 20 years,our medicinal chemistry group has made great strides in developing several distinct novel NNRTIs,including 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine(HEPT),thio-dihydro-alkoxy-benzyl-oxopyrimidine(S-DABO),diaryltriazine(DATA),diarylpyrimidine(DAPY)analogues,and their hybrid derivatives.Application of integrated modern medicinal strategies,including structure-based drug design,fragment-based optimization,scaffold/fragment hopping,molecular/fragment hybridization,and bioisosterism,led to the development of several highly potent analogues for further evaluations.In this paper,we review the development of NNRTIs in the last two decades using the above optimization strategies,including their structure-activity relationships,molecular modeling,and their binding modes with HIV-1 reverse transcriptase(RT).Future directions and perspectives on the design and associated challenges are also discussed.