Schedule-an expert-like system for machine scheduling

The construction of an expert-like system for machine scheduling called SCHEDULE is presented. Essential parts of SCHEDULE were developed by students in a laboratory course Operations Research on Microcomputers at the University of Karlsruhe, Germany. SCHEDULE consists of the components data base, knowledge base, inference engine, explanation facility, dialog component, and knowledge acquisition component. The knowledge base contains an algorithm base for solving different types of scheduling problems. To establish the rules of the knowledge base the well-known three-field classification of deterministic machine scheduling problems and the concept of the reduction digraph are exploited. Experiences gained during building and demonstrating SCHEDULE are reported.     

提高西德MNPJ型毛圈圆纬机压针三角与舌针使用寿命的研究

本文通过西德MNPJ型毛圈圆纬机编织过程的受力分析和机械润滑试验,提出了提高三角和舌针使用寿命的途径;同时又对该机三角系统的材料进行了研究,提出了自制三角系统的看法。     

predForm-Site: Formylation site prediction by incorporating multiple features and resolving data imbalance

Formylation is one of the newly discovered post-translational modifications in lysine residue which is responsible for different kinds of diseases. In this work, a novel predictor, named predForm-Site, has been developed to predict formylation sites with higher accuracy. We have integrated multiple sequence features for developing a more informative representation of formylation sites. Moreover, decision function of the underlying classifier have been optimized on skewed formylation dataset during prediction model training for prediction quality improvement. On the dataset used by LFPred and Formator predictor, predForm-Site achieved 99.5% sensitivity, 99.8% specificity and 99.8% overall accuracy with AUC of 0.999 in the jackknife test. In the independent test, it has also achieved more than 97% sensitivity and 99% specificity. Similarly, in benchmarking with recent method CKSAAP_FormSite, the proposed predictor significantly outperformed in all the measures, particularly sensitivity by around 20%, specificity by nearly 30% and overall accuracy by more than 22%. These experimental results show that the proposed predForm-Site can be used as a complementary tool for the fast exploration of formylation sites. For convenience of the scientific community, predForm-Site has been deployed as an online tool, accessible at http://103.99.176.239:8080/predForm-Site.     

A combination of modified particle swarm optimization algorithm and support vector machine for gene selection and tumor classification

In the analysis of gene expression profiles, the number of tissue samples with genes expression levels available is usually small compared with the number of genes. This can lead either to possible overfitting or even to a complete failure in analysis of microarray data. The selection of genes that are really indicative of the tissue classification concerned is becoming one of the key steps in microarray studies. In the present paper, we have combined the modified discrete particle swarm optimization (PSO) and support vector machines (SVM) for tumor classification. The modified discrete PSO is applied to select genes, while SVM is used as the classifier or the evaluator. The proposed approach is used to the microarray data of 22 normal and 40 colon tumor tissues and showed good prediction performance. It has been demonstrated that the modified PSO is a useful tool for gene selection and mining high dimension data.     

从电子工业“脊梁”到全面开花的镓元素

镓是第一个根据化学元素周期律预言并在自然界中证实的元素，是室温下电导率和热导率均为最大的液态物质，镓在电子工业中得到了广泛应用，被誉为电子工业“脊梁”。近十几年来，镓的更多应用潜力被发掘出来，在电子工业、散热、增材制造、柔性机器、生物医学等领域均有重要的应用前景。     

基于机器视觉的车辆时空参数识别

车辆荷载信息是分析桥梁受力和性能评估的重要依据,其中车辆时空信息是准确识别车辆荷载的关键参数。考虑到传统在桥面埋设传感器的方法影响交通、破坏路面,提出了一种基于机器视觉技术的车辆荷载时空参数识别方法,包括车辆的横向定位、车速、车轴数、轴距的识别。基于正面拍摄视频,采用背景差分法来实现车辆检测,进一步通过车牌识别确定车辆在图像中的位置,然后根据车牌与车道线距离来实现车辆横向定位。基于侧面拍摄视频,采用图像标定方法,结合已知长度的辅助检测线来获取车辆的轴距、轴数、车速等车辆参数。通过试验室模型试验和现场试验验证了提出的方法。结果表明,现场试验中车辆横向定位和车速的最大误差分别为2.42%和2.67%,轴距的平均误差为1.63%,识别结果可以为更多其他车辆参数如轴重和总重的识别提供重要的技术支撑。     

基于卡诺机的大规模MIMO通信容量建模及性能分析

信息本质上以能量和熵的形式在通信系统中流动,类似于传统热机中的能量流动过程。结合热力学卡诺机模型和经典香农信息论理论,建立了一个广义的热力学(multiple input multiple output, MIMO)通信系统模型,对大规模天线通信场景下使用前向纠错码的信道容量进行分析。利用通信系统中存在的自由度和熵的概念,推导了热力学模型下的广义信道容量,并对信道容量与噪声自由度及编码开销的关系进行验证仿真。仿真结果表明,所提出的热力学信道容量与香农信道容量是一致的。     

Tractability frontiers in probabilistic team semantics and existential second-order logic over the reals

Probabilistic team semantics is a framework for logical analysis of probabilistic dependencies. Our focus is on the axiomatizability, complexity, and expressivity of probabilistic inclusion logic and its extensions. We identify a natural fragment of existential second-order logic with additive real arithmetic that captures exactly the expressivity of probabilistic inclusion logic. We furthermore relate these formalisms to linear programming, and doing so obtain PTIME data complexity for the logics. Moreover, on finite structures, we show that the full existential second-order logic with additive real arithmetic can only express NP properties. Lastly, we present a sound and complete axiomatization for probabilistic inclusion logic at the atomic level.