Developing an expertise system is vital for many applications especially in doctor's community. Previous work uses ranking based on experience and location. In the proposed model, we introduce an Expertise search ...
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ISBN:
(纸本)9781479980826
Developing an expertise system is vital for many applications especially in doctor's community. Previous work uses ranking based on experience and location. In the proposed model, we introduce an Expertise search system. The first step of the ESS to extract the profile from web. The ESS first lookup the doctor's profile and then list the profile based on ranking. In this paper we use the real case information of doctor's and integrate the profile information using EM framework. The propose system use clustering algorithm for name disambiguation. Also we describe the architecture diagram for the proposed ESS system.
In this paper we present a novel algorithm for video anomaly detection. It is based on multiple local cells, which are acquired by splitting entire monitor scene. At each local cell, we group all feature vectors with ...
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In this paper we present a novel algorithm for video anomaly detection. It is based on multiple local cells, which are acquired by splitting entire monitor scene. At each local cell, we group all feature vectors with clustering algorithm based on minimum spanning tree, and further model all groups using improved one-class SVM to build ensemble classifiers. For any new features at each local node in incoming video clips, we use the corresponding learned ensemble classifiers to estimate maximum abnormality degree. The proposed approach has been tested on publicly available datasets with frame-level and pixel-level criteria, and outperforms other state-of-the-art approaches.
Bitcoin is the world's first decentralized cryptocurrency whose transactions are recorded on a distributed, openly accessible ledger. On the Bitcoin Blockchain, an entity's real-world identity is hidden behind...
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Bitcoin is the world's first decentralized cryptocurrency whose transactions are recorded on a distributed, openly accessible ledger. On the Bitcoin Blockchain, an entity's real-world identity is hidden behind a pseudonym, a socalled ***, Bitcoin is widely assumed to provide a high degree of anonymity, which is a driver for its frequent use for illicit *** criminal activities that use Bitcoin as an intermediary are becoming more rampant, and it is difficult for law enforcement agencies to identify and track them. In order to identify the identity behind the Bitcoin address and realize the supervision of the blockchain, this paper propose to give a review of the most used Bitcoin clustering algorithms. The research is divided into two categories: One is the Transaction-based heuristic method for static address information;The other is classic clustering algorithms for dynamic behavior patterns, so as to achieve the purpose of de-anonymization of Bitcoin.
Identifying and analyzing components of complexes is essential to understand the activities and organization of the cell. Moreover, it provides additional information on the possible function of proteins involved in t...
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Identifying and analyzing components of complexes is essential to understand the activities and organization of the cell. Moreover, it provides additional information on the possible function of proteins involved in these complexes. Two bioinformatics approaches are usually used for this purpose. The first is based on the identification, by clustering algorithms, of full or densely connected sub-graphs in protein—protein interaction networks derived from experimental sources that might represent complexes. The second approach consists of the integration of genomic and proteomic data by using Bayesian networks or decision trees. This approach is based on the hypothesis that proteins involved in a complex usually share common properties. less
In this paper, a large number of higher vocational college teaching data norm extraction with the appropriate model design and improvement. So as to improve the effectiveness of data analysis, it provides powerful cla...
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In this paper, a large number of higher vocational college teaching data norm extraction with the appropriate model design and improvement. So as to improve the effectiveness of data analysis, it provides powerful classroom analysis support for classroom teaching evaluation in higher vocational *** concept of overall distribution is used to describe the overall data state by presenting the distribution diagram. The big data simulation analysis results can provide reference or basis for the construction of normal model resources of classroom teaching quality of teachers in vocational colleges as a whole.
Progress in wireless communication has made possible the development of low cost wireless sensor networks. In recent years, as the development of wireless sensor networks, people have done some research on cluster-bas...
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Progress in wireless communication has made possible the development of low cost wireless sensor networks. In recent years, as the development of wireless sensor networks, people have done some research on cluster-based protocol, about the proongation of the lifetime of WSN and decrease of energy consumed by the sensors. clustering sensor nodes is an effective topology control approach, but these algorithms are not optimized for the characteristics of heterogeneous wireless sensor networks. This paper introduces the new energy adaptive protocol to reduce overall power consumption, maximize the network lifetime in a heterogeneous wireless sensor network. In our protocol, NEAP (the Novel Energy Adaptive Protocol for heterogeneous wireless sensor networks) the cluster-head is elected by a probability, based on threshold per round and cluster formation based on nodes current battery power and numbers of members currently under a cluster-head are taken, distance between cluster-heads and nods. At last, the simulation results show that NEAP achieves longer lifespan and reduce energy consumption in wireless sensor networks.
Glass is the precious material evidence of the early trade of the ancient Silk Road, but the ancient glass is easily weathered by the influence of burial, and its composition ratio changes, which affects the correct j...
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Glass is the precious material evidence of the early trade of the ancient Silk Road, but the ancient glass is easily weathered by the influence of burial, and its composition ratio changes, which affects the correct judgment of its category. The study of the composition analysis and identification of ancient glass products is of great help to understand the social culture and foreign trade civilization at that time. This paper mainly studies the composition analysis and identification of ancient glassware, to evaluate, predict and classify the ancient glassware, this paper establishes a comprehensive evaluation model, using the chi-square test, K-means clustering model, decision tree model, Lasso regression and grey correlation degree test. It helps archaeologists to analyze and predict the correlation between the weathering degree of cultural relics and their attributes and chemical composition content, and according to the existing classification standards of cultural relics.A labelled subclassification scheme is formulated to identify the types of unknown cultural relics. At the same time, the correlation between the chemical components of different types of cultural relics was analyzed.
The key factor to increase enterprise profits and reduce the logistic costs is scientific and reasonable logistics demand forecasting, the accuracy of which can directly influence the effect of decision-making for an ...
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The key factor to increase enterprise profits and reduce the logistic costs is scientific and reasonable logistics demand forecasting, the accuracy of which can directly influence the effect of decision-making for an enterprise. In some instance, a single customer's demand is irregular, while the demand in a region is comparatively more stable, so it can be better forecasted. In this paper, we have proposed a method to form regions in order that the demand in these regions can be more efficient forecasted while the error of transportation cost caused by replacement of customers by regions can be controlled. Each formed region consists of adjacent customers with similar unit transportation cost to all distributors. Numerical test with data form Northeast Subsidiary Company of China National Petroleum Corporation shows that the method can improve forecast accuracy efficiently.
Academic procrastination is a common phenomenon in China's higher vocational education. Due to the weakening of the role of teacher supervisors and the lack of students' self-control, the academic procrastinat...
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ISBN:
(纸本)9781450398091
Academic procrastination is a common phenomenon in China's higher vocational education. Due to the weakening of the role of teacher supervisors and the lack of students' self-control, the academic procrastination of students in online learning is more likely to occur. At present, it has become a trend to use educational data mining and artificial intelligence technology to evaluate, predict and intervene in online learning, so as to solve the problem of practical teaching lag and improve the teaching effect of vocational education. In this paper, the data of "Computer Application Foundation" course of higher vocational students on Chaoxing platform is used to process the data by using K-means and DBSCAN clustering algorithms, and the performance of the two algorithms is evaluated by using the contour coefficient. The results show that the K-means algorithm has better performance. The students were divided into active learners, mild procrastinators and severe procrastinators by K-means clustering algorithm. Then, combined with decision tree (DT), neural network (NN) and Naive Bayes (NB) algorithm to verify the accuracy of K-means clustering algorithm in identifying the classification of students' procrastination tendency, this paper hopes to provide some advises for online learning procrastinators and encourage students to keep learning initiative and enthusiasm.
clustering is the unsupervised, semisupervised, and supervised classification of patterns into groups. The clustering problem has been addressed in many contexts and disciplines. Cluster analysis encompasses different...
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clustering is the unsupervised, semisupervised, and supervised classification of patterns into groups. The clustering problem has been addressed in many contexts and disciplines. Cluster analysis encompasses different methods and algorithms for grouping objects of similar kinds into respective categories. In this chapter, we describe a number of methods and algorithms for cluster analysis in a stepwise framework. The steps of a typical clustering analysis process include sequentially pattern representation, the choice of the similarity measure, the choice of the clustering algorithm, the assessment of the output, and the representation of the clusters. less
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