The influence of mining factors on seismic activity during longwall mining of a coal seam

In this article an attempt to determine the influence of mining factors on the seismic activity during the longwall mining of the upper layer of coal seam no. 405/2 in one of the Polish hard coal mines in the Upper Silesian Coal Basin was conducted. Two longwall panels were mined in analogous geological conditions and based on the same mining system and technology. However, there was significant difference with regards to the mining factors, which was reflected in the observed seismic activity. Some tools used in mining seismology were applied to illustrate the aforementioned influence of mining factors, e.g. the frequency-energy distribution, the frequency-magnitude distribution, the 2 D distribution of released seismic energy, the relationship between released seismic energy and the volume of mined coal, the Benioff strain release, and the Gutenberg-Richter(GR) b coefficient distribution(b is the proportion between high and low energy tremors). Concerning the Benioff strain release, a new solution, based on the slope of a fitted line in a moving time window, is proposed.     

煤炭资源型城市转型模式研究：以徐州贾汪区为例

煤炭资源型城市为我国经济发展提供了重要的资源和能源支持,研究资源型城市转型的经验模式对调整区域经济结构、确保社会稳定和改善生态环境具有重要的实践意义。本文采用文献综述法和实证分析法,研究我国东部煤炭资源枯竭型城市转型所面临的共性难题,并以徐州贾汪区转型探索经历为例,总结城市转型的"徐州贾汪区模式",主要包括放大正向外部效应、长期坚持矿地融合、大力建设矿区社会生态系统恢复力三条路径。研究结果表明,煤炭城市转型发展的共性问题相互联系、相互影响,是一个系统性难题,必须引入系统性思维。我国东部矿区普遍人口密集,农业发达、沉陷积水是最主要的共性特征,煤炭开采产生的社会问题、经济问题、生态问题、环境问题基本相同,转型发展模式值得互鉴。     

乌兰矿采矿现状及技术应对方案

本文分析了乌兰矿投产前期采矿现状及存在的主要问题,针对该矿所处蒙古国经济落后、投资风险大的现实状况,为避免生产中断、规避投资风险,早日回收前期投资考虑,采取了双斜坡道开拓、全尾胶结充填、高端壁空场嗣后充填采矿、多中段组合式连续开采等系列技术应对方案。大大降低了一次性投资规模及投资风险,前期投资得以快速回笼的同时,矿山产能也充分释放,确保了矿山的持续稳定,取得了较好的经济和社会效益。为海外地下近地表矿体开采矿山规避投资风险提供了很好的技术方案借鉴。     

Picosecond laser trimming of ceramic cores with porous multi-scale particle microstructure

The ceramic core, produced by hot injection molding, is one of the critical components for manufacturing high-performance aircraft engine turbine blades. However, the injection molding process will cause defects such as burrs and flashes in the fine structure of the formed ceramic core. Manual trimming is necessary, but the trimming quality is poor, and the yield is low. In this paper, the online trimming method of ceramic cores is studied. Based on the orthogonal experiment method, the optimal laser parameters for processing the ceramic core's porous multi-scale particle structure material were obtained. Further, the problems of the match head and tail phenomenon and dimensional accuracy improvement in trimming ceramic cores have been studied. A path optimisation method is proposed to improve the quality and accuracy of the trimming profile effectively. Finally, the overall process flow of ceramic core trimming is elaborated, and experimental verification is given. The results show that the ceramic core online trimming method proposed in this paper has advantages of high precision and high yield compared with the manual method, which will have substantial potential application value in the aviation field.     

陕北沙漠区浅埋厚煤层开采潜水位及生态响应

煤炭开采造成上覆岩层破裂、移动，破坏了矿区含（隔）水层结构，改变了地表水及地下水循环演化状态，对浅表层生态环境造成严重影响，引发一系列环境地质问题。为深入研究沙漠地区厚煤层开采给潜水位及生态环境造成的影响，以毛乌素沙漠金鸡滩矿为例，对水文地质条件进行了研究，采用数值模拟的方法，模拟了沙漠区厚煤层开采潜水位的变化，并通过采动潜水位监测数据验证了预测结果。调查分析了研究区及周边地表生态环境现状，预测采后潜水位基本满足植物生长需求，对生态环境影响不大。     

Flexible Distribution-Based Regression Models for Count Data: Application to Medical Diagnosis

Abstract

Data mining techniques have been successfully utilized in different applications of significant fields, including medical research. With the wealth of data available within the health-care systems, there is a lack of practical analysis tools to discover hidden relationships and trends in data. The complexity of medical data that is unfavorable for most models is a considerable challenge in prediction. The ability of a model to perform accurately and efficiently in disease diagnosis is extremely significant. Thus, the model must be selected to fit the data better, such that the learning from previous data is most efficient, and the diagnosis of the disease is highly accurate. This work is motivated by the limited number of regression analysis tools for multivariate counts in the literature. We propose two regression models for count data based on flexible distributions, namely, the multinomial Beta-Liouville and multinomial scaled Dirichlet, and evaluated the proposed models in the problem of disease diagnosis. The performance is evaluated based on the accuracy of the prediction which depends on the nature and complexity of the dataset. Our results show the efficiency of the two proposed regression models where the prediction performance of both models is competitive to other previously used regression models for count data and to the best results in the literature.     

Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs’ platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs’ platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.     

云岗矿极近距离煤层安全开采采掘技术研究

为防止311盘区11-2^#层工作面掘进及采煤过程中造成近距离煤层的漏顶事故发生,通过优化工作面布置方式、掘进期间支护形式及参数,制定工作面开采期间的回采工艺及顶板管理措施,在生产实践过程中总结了一套安全可靠的极近距离煤层采掘技术,对近距离煤层开采有一定的指导意义。     

Fault handling in large water networks with online dictionary learning

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.     

宏阳煤矿薄煤层沿空留巷实践应用

为了缓解矿井采掘接替紧张局面,宏阳煤矿采用沿空留巷技术,对12102运输顺槽采取顶板超前采面打设锚索梁、顶板超前预裂爆破,留巷段采用“钢梁+单体液压支柱”的方式进行巷道支护。该技术现场应用后,减少了巷道掘进工程量,减少了煤炭损失,增加了经济效益,降低了职工劳动强度,有利于采掘接替。