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Sun C.,National School in Computer Science | Li Q.,National School in Computer Science | Cui L.,National School in Computer Science | Yan Z.,National School in Computer Science | And 2 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2015

The rapid growth of data makes it possible for us to study human behavior patterns. Knowing the patterns of human behavior is of great use to help us detect the unusual fraud human behavior. Existing fraud detection methods can be divided into two categories: pattern based and outlier detection based methods. However, because of the sparsity and complex granularity of big data, these methods have high false positive in fraud detection. In this paper, we propose an effective hybrid fraud detection method. We propose SSIsomap which improves isomap to cluster behaviors into behavior classes and propose SimLOF which improves LOF to conduct outlier detection, then we use Dempster-Shafer evidence Theory for combining behavior pattern evidence and outlier evidence, which yields a degree of belief of fraud to the new coming claim. The experiment result shows our method has significantly higher accuracy than exsiting methods in medical insurance fraud detection. © Springer International Publishing Switzerland 2015.


Lin W.,Huazhong University of Science and Technology | Yu D.Y.,Huazhong University of Science and Technology | Zhang C.,Huazhong University of Science and Technology | Liu X.,University of Michigan | And 4 more authors.
Journal of Cleaner Production | Year: 2015

Industry is responsible for nearly half of the global energy consumption. Recent studies on sustainable manufacturing focused on energy saving to reduce the unit production cost and environmental impacts. Besides energy consumption, certain manufacturing activities in machine shops, such as the use of cutting fluids, disposal of worn tools, and material consumption, also cause other environmental impacts. Since all these activities lead to carbon footprint directly or indirectly, carbon footprint can be employed as a new and overall environment criterion in manufacturing. In this study, an integrated model for processing parameter optimization and flow-shop scheduling was developed. Objectives to minimize both makespan and carbon footprint were considered simultaneously, which was solved by a multi-objective teaching. -learning-based optimization algorithm. Furthermore, three carbon-footprint-reduction strategies were employed to optimize the scheduling results: (i) postponing strategy, (ii) setup strategy, and (iii) processing parameter preliminary optimization strategy. In the theoretical aspect, the strategies greatly improved the performance of the optimization results through reducing machine idle time and cutting down the search space. From the perspective of practical applications, these strategies greatly help elevate production efficiency and reduce environmental impacts. © 2015 Elsevier Ltd.


Junru Y.,Shandong University of Science and Technology | Chuanjuan S.,Shandong University of Science and Technology | Nannan Z.,Shandong Hoteam Software Co. | Daozhong Z.,Shandong Hoteam Software Co. | Ning X.,Shandong Hoteam Software Co.
Open Petroleum Engineering Journal | Year: 2015

In the paper, to the patchwork problem of large chemical storage tank bottom, theoretical researches on arranging special-shaped parts are carried out. The heuristic layout algorithm with dynamic decision layout order and based on graphics position strategy is proposed. According to the algorithm, basing on Sinovation platform, using the object-oriented programming language C++ and Visual Studio tools, the arranging and patchwork system is designed and developed. And the application researches are made with the system. The results show that, comparing with the rectangular envelopment algorithm, the plate utilization ratio is increased with the patchwork algorithm proposed in the paper. © 2015 Junru et al.; Licensee Bentham Open.


Zhang H.,Shandong University of Science and Technology | Yan Z.,Shandong University of Science and Technology | Sun C.,Shandong University of Science and Technology | Wei S.,Shandong Hoteam Software Co.
Proceedings - 2015 12th Web Information System and Application Conference, WISA 2015 | Year: 2015

As the sources of data become more and more diversified, the importance of data conflict detection is emerging. We are committed to research a new method, through the use of behavior pattern detection of heterogeneous data semantic conflict. We find that the structured data which can represents the behavior of an entity contradict from the reality behavior of the entity which can be got from unstructured text, which is often referred to as pattern conflict. So in this paper, we convert the structured data with semantic into data-converted event. Combine them with the text event extracted from unstructured text, according to the relation between entities, get a large event graph G. Find the common conflict pattern through frequent sub-graph discovery on graph G. Then use the common conflict patterns to detect conflict data. The experiment shows that our method can detect the conflict data effectively with a high recall. © 2015 IEEE.


Guan H.,Shandong University of Science and Technology | Li Q.,Shandong University of Science and Technology | Yan Z.,Shandong University of Science and Technology | Wei W.,Shandong Hoteam Software Co.
Proceedings - 2015 12th Web Information System and Application Conference, WISA 2015 | Year: 2015

With the rapid progress in data mining and outlier detection, outlier detection methods have been widely used in various domains. The density based LOF method is the commonly used outlier detection method. In big data, the size and dimensions of data is very large, and the data is sparse. Those features make the LOF not suitable for big data. According to the features of big data, we propose a novel SLOF method. We use vectors to denote the complex high dimensional objects in dataset. We compute the distances between objects based on the concept of vector similarity. We introduce the idea of feature bagging approach, to make the SLOF method robust and accurate. We compare the performance of SLOF, LOF and the PINN methods. The experimental results show that SLOF scores' distribution is more stable, the recall rate and precision of SLOF is much better than LOF and PINN methods. © 2015 IEEE.


Zhu C.,Shandong University of Science and Technology | Li Q.,Shandong University of Science and Technology | Kong L.,Shandong University of Science and Technology | Wei S.,Shandong Hoteam Software Co.
Proceedings - 2015 12th Web Information System and Application Conference, WISA 2015 | Year: 2015

In big data epoch, one of the major challenges is the large volume of mixed structured and unstructured data, which comes in heterogeneous sources. Because of different form, structured and unstructured data are often considered apart from each other. However, they may speak about the same entities of the world. If a query involve both structured data and its unstructured counterpart, it is inefficient to execute it separately. The paper presents a novel index structure tailored towards the combinations of structured and unstructured data. The combined index is a joint index over structured database and unstructured document, based on entity co-occurrences. It is also a semantic index which describes the semantic relationships between entities and their multiple resources. We store the index as RDF graphs and queries are SPARQL-like. Experiments show that the associated index can not only provide apposite information but also execute queries efficiently. © 2015 IEEE.


Zhao J.,Shandong University of Science and Technology | Wang X.,Shandong University of Science and Technology | Yan Z.,Shandong University of Science and Technology | Wei S.,Shandong Hoteam Software Co.
Proceedings - 2015 12th Web Information System and Application Conference, WISA 2015 | Year: 2015

Event is a widely used concept these years. Many areas such as Natural Language Process, Information Retrieval have used event as the basic information unit in their research. So, the mining of event association is very necessary for our research. And it plays an important role business intelligence and researches of relations between events. Usually events are associated with others when they often occur in the vicinity of others or co-occur in the same context. However, there are some implicit associations we cannot mine only from sequence or context. In this paper, we aim to find associations of events under the background of Data Integration Systems. By using the structured information of data integration system, the background information of entities can be extracted to classify events. So we classify the events into different categories which makes it possible to mine the statistical information from event sequence. Furthermore, we generalize the association between event entities to predict the implicit association in our algorithm. We validate our method with experiments and results show the useful information in the area of business intelligence. © 2015 IEEE.


Sun J.,Shandong Jianzhu University | Wang Y.,Shandong Jianzhu University | Yin F.,Shandong Jianzhu University | Qiu H.,Shandong Hoteam Software Co.
MATEC Web of Conferences | Year: 2016

Process planning is the key link that connects the product design and manufacture. In order to continually improve the effectiveness and efficiency of process planning an auto enterprise in consistent with the process management requirements of TS16949, the requirements for assembly process planning is analysed and the main problems affecting the design and production efficiency are discussed. The infrastructure of the structured process planning and management platform is constructed combing the management technology and TS16949 quality system, then the structured PPPR (product, process, plant and resource)model is reintegrated to analyze the relationships among the objects with the object-oriented method. In the end, with the principles of maintaining conveniently and operating practically, the assembly process planning and management system is implemented according to the characteristics of the process in the enterprise, and the main function modules of the system are described. © 2016 Owned by the authors, published by EDP Sciences.


Yang J.,Shandong University of Science and Technology | Huan X.,Shandong University of Science and Technology | Zhang L.,Shandong University of Science and Technology | Zhang D.,Shandong Hoteam Software Co. | Zhang Y.,Shandong University of Science and Technology
Proceedings of the 2nd International Conference on Electronic and Mechanical Engineering and Information Technology, EMEIT 2012 | Year: 2012

According to the material composition and structure characteristics, a hierarchical modeling method for the cladding part is proposed. The clad, interface and substrate are firstly modeled respectively, then they are glued together, meanwhile the bonding strength is considered. The cladding part modeling system prototype is designed based on the software SINOVATION. © the authors.


Sun J.K.,Shandong Jianzhu University | Yang C.Y.,Shandong Hoteam Software Co. | Qiu H.H.,Shandong Hoteam Software Co.
Applied Mechanics and Materials | Year: 2014

As the precision and quality requirements for assembly process is very high, with the features of security or irreversibility, assembly has become an key link of restricting the improvement of product quality and productivity for some industries such as automotive, aerospace and other industries. In this paper, based on the construction of the tri-dimensional visual platform, assembly process design process is studied, on the basis of tri-dimensional process model, the assembly process is simulated and analyzed in real-time, the assembly path and assembly interference check is implemented, thus shorten the planning and assembly debugging cycle greatly, improve the quality and efficiency of the process design. © (2014) Trans Tech Publications, Switzerland.

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