Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Prediction of risk factors of cyberbullying-related words in Korea: Application of data mining using social big data

The study examined a decision tree analysis using social big data to conduct the prediction model on types of risk factors related to cyberbullying in Korea. The study conducted an analysis of 103,212 buzzes that had noted causes of cyberbullying and data were collected from 227 online channels, such as news websites, blogs, online groups, social network services, and online bulletin boards. Using opinion-mining method and decision tree analysis, the types of cyberbullying were sorted using SPSS 25.0. The results indicated that the total rate of types of cyberbullying in Korea was 44%, which consisted of 32.3% victims, 6.4% perpetrators, and 5.3% bystanders. According to the results, the impulse factor was also the greatest influence on the prediction of the risk factors and the propensity for dominance factor was the second greatest factor predicting the types of risk factors. In particular, the impulse factor had the most significant effect on bystanders, and the propensity for dominance factor was also significant in influencing online perpetrators. It is necessary to develop a program to diminish the impulses that were initiated by bystanders as well as victims and perpetrators because many of those bystanders have tended to aggravate impulsive cyberbullying behaviors.     

Data sharing mechanism of various mineral resources based on blockchain

Basins with various mineral resources coexisting and enriching often occupy an important strategic position. The exploration of various mineral resources is repetitive at present due to unshared data and imperfect management mechanism. This situation greatly increases the cost of energy exploitation in the country. Traditional data-sharing mode has several disadvantages, such as high cost, difficulty in confirming the right of data, and lack of incentive mechanism, which make achieving real data sharing difficult. In this paper, we propose a data-sharing mechanism based on blockchain and provide implementation suggestions and technical key points. Compared with traditional data-sharing methods, the proposed data-sharing mechanism can realize data sharing, ensure data quality, and protect intellectual property. Moreover, key points in the construction are stated in the case study section to verify the feasibility of the data-sharing system based on blockchain proposed in this paper.     

Smart firefighting construction in China: Status,problems, and reflections

“Smart firefighting” construction as a part of the “smart city” has been a concern of the public security and fire agencies at all levels. In this study, the status, problems, and reflections of “smart firefighting” construction in China are discussed. A recent survey indicates that China has launched its smart firefighting construction and initially created a new perspective on its regional smart firefighting work based on three main aspects: intelligent disaster perception by Internet of Things (IoT) construction, intelligent disaster prevention by big data construction, and intelligent disaster disposal by emergency rescue platform construction. However, the current smart firefighting construction in China still has some prominent problems such as the data interconnectivity and normalized management of various platforms, the extensibility of smart firefighting platforms, and the intelligent level of smart firefighting researches, which need to be solved urgently. Therefore, we argue that smart firefighting construction in China should establish data interconnectivity, industrial normalized management, 2D/3D geographic information interaction and extension, high-integration fire protection theory, and many other aspects in the near future and truly realize firefighting visualization and efficient data applications for 4D time space. This study could provide valuable reference for smart firefighting and smart city construction.     

辅助消声器在轿车排气消声器性能研究中的应用

引入辅助消声器（BAM）原理，对T15汽车加速行驶产生的“噗噗”声进行试验分析，发现了原消声器系统存在的问题，并对原消声器结构做了优化，解决了“噗噗”声问题。     

大孔距小排距的孔网参数在中深孔爆破中的应用

天铁集团的石矿厂多年来爆破效果不理想，粉矿率高，通过对爆破孔网参数的优化，采用大孔距、小排距的孔网参数在中深孔爆破中取得了较好的效果。     

大型钢制立式储罐的导链式倒装法施工

介绍了导链式倒装法安装大型钢制立式储罐的原理及制作工艺流程。     

辽宁省节水工作存在问题及对策

辽宁省是水资源严重短缺的省份之一，水资源不足已成为制约全省经济社会可持续发展的瓶颈。通过对全省大型取用水户的调查分析，找出了辽宁省节水工作中存在的问题，提出了节约用水工作的对策和建议。     

英台地区天然水驱油藏的开发特点及稳产技术

掌握边底水运动规律，控制并利用活跃的边底水能量，是成功开发天然水驱油藏的关键。英台地区的英台、四方坨子和一棵树等三个油田均为天然水驱油藏，天然能量充足。油藏投入开发后初期含水较高，含水上升极快，造成产油量大幅度递减。针对其开发特点，适时采用大泵、电潜泵提液强采，通过大量补孔层间接替以及加密调整和扩边等稳产技术措施，确保了油藏以3％-5％的采油速度长期稳产，水驱采收率高达50％以上。