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Cryptocurrencies have emerged as important financial software systems. They rely on a secure distributed ledger data structure; mining is an integral part of such systems. Mining adds records of past transactions to the distributed ledger known as Blockchain, allowing users to reach secure, robust consensus for each transaction. Mining also introduces wealth in the form of new units of currency. Cryptocurrencies...
This paper introduces a new methodology for digital design properties extraction from simulation traces. The innovated methodology is based on a new data mining technique guided with static analysis of the intended design. The mining engine of the proposed methodology is based on innovated Breadth-First Decision Tree (BF-DT) search algorithm. The data structure of each node in the decision tree is...
Sequence correlation method has limits in unknown attacks identification and requires pre-defining the causal relationship between attack behavior. To solve this problem, an alert correlation algorithm, denoted as TPrefixSpan, based on the sequence pattern mining is proposed in this paper, based on PrefixSpan algorithm, TPrefixSpan algorithm introduces time interval that can thoroughly narrow, the...
With the advent of internet, online social network is seen as playing a very important role in connecting people and a platform to share ideas. In the current scenario, given restriction on resources available for advertisement, the best place to sell one's product would definitely be these online social networks. The popularity of social network has influenced the computer researchers to ponder on...
Social Network Analysis (SNA) is a technique for modeling the communication patterns between individuals in a way that illuminates the structure of the network and the importance of individuals within the network. SNA has gained a recent importance due to the appearance of various web 2.0 platforms like blogs, wikis, content and media sharing sites which consists of a huge collection of data. These...
Semi-structured processes are data-driven, human-centric, flexible processes whose execution between instances can vary dramatically. Due to their unpredictability and data-driven nature, it's becoming increasingly important to mine traces of events collected from these processes. This enables the extraction of mined process models that could help users handle new process instances. Process-mining...
In the paper we first propose a user preference model with the minimum support intelligent set method. Secondly, we propose a new data mining problem, the structure of the database to find frequent patterns associated pair. To effectively address these problems, we developed a series of cutting ability with a strong algorithm. The new algorithm is also discussed in the one-dimensional and multi-dimensional...
Our previous work has preliminarily investigated the batch processing model and its implementation. To solve the problem of setting batch processing areas for the applications of batch processing in workflow, this paper proposes a method of discovering batch processing area from workflow logs. Its mining process includes phrases of mining initial workflow model, identifying batch processing feature...
Based on the air distribution request of the mine ventilation network, carries on the optimized computation to the mine ventilation system network's nonlinear programming mathematical model using harmony search, uses penalty functions method carries on transformation to the constraint equation, fuses the dynamic perturbation and the simulated annealing to improve the harmony search algorithm, the...
Ant-based techniques are designed to take biological inspirations on the behavior of these social insects. Data clustering techniques are classification algorithms that have a wide range of applications, from Biology to Image processing and Data presentation. Since real life ants do perform clustering and sorting of objects among their many activities, we expect that a study of ant colonies can provide...
A great amount of fault wave has been recorded by the devices for detecting phase-to-ground faults in ineffectively grounded systems. However, a better method hasn't found for effectively taking advantage of these data to improve the result of fault line selection. Data mining techniques can be used for fault line selection in ineffectively grounded system to gain knowledge from the existing data...
Ultra-wideband (UWB) technology has the characteristics which other wireless communication technology can not match to. It combines with wireless sensor network (WSN) technology, using in the environment of coal mine underground, to achieve safety monitoring by WSN node location. Using appropriate location algorithm can not only improve the location accuracy of the calculation can also reduce system...
Compares with the traditional forward neural network, the cover algorithm has the running rate to be quick, precision high characteristic, but the cover algorithm's initial domain center is the stochastic selection. The experiment indicated that the network performance and the study order have the close relationship. Proposed one kind of new improvement overlapping cover algorithm in the forward neural...
Based on analyzing the contents of safety early-warning system for the working face in mine and according to the production characteristic of coal mine in China, combining the analytical hierarchy process and neural network BP algorithm. The safety early-warning system for the working face in mine was also designed based on the combinatorial algorithm. The system was applied to estimate support capacity...
The safety analysis methods of the current management of traditional safety system that are the method of the fault tree analysis (FTA) and the information system of safety management (monitoring) are integrated and optimized by applying the data mining association algorithm. The new theoretical model of the management of the mining safety system is established to avoid the shortcomings that are omissions,...
A new way which can reduce environment noise underground in mine tunnel is produced. By analysis of the noise in central water pump house, point out that noise underground is mainly consist of base frequency and harmonic frequency coming from electric motor and transformer, with its frequency coverage below 650Hz. Acoustic spread environment in mine tunnel is similar to that in duct. Therefore, it...
Algorithms from several interesting application domains exhibit the property of inherent resilience to “errors” from extrinsic or intrinsic sources, offering entirely new avenues for performance and power optimization by relaxing the conventional requirement of exact (numerical or Boolean) equivalence between the specification and hardware implementation. We propose scalable effort hardware design...
Prevention and control of the disastrous accident is the top priority of coal mine production safety. RBF and the combined grey neural network (CGNN) model are established. Combined with cascade-correlation (CC) and RBF-DDA algorithms, gas explosion impacting on coal mine production safety largely is analyzed. The analysis results show that gas explosion accident is caused by many reasons. The relationship...
Association rules mining is an important research topic in data mining and knowledge discovery. Traditional algorithms for mining association rules are built on the binary attributes databases, which has three limitations. Firstly, it cannot concern quantitative attributes; secondly, only the positive association rules are discovered; thirdly, it treat each item with the same significance although...
In order to enhance the security of poor working underground environment, it's important to study on the problem of location and tracking for keeping mining personnel and down hole equipments safe. We put forward wireless sensor network underground location algorithm which is based on the superposition of RSSI and DV-Hop. This algorithm makes up for the shortage of RSSI algorithm and DV-Hop algorithm...
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