Toward Activity Mapping for Artifact-Centric Business Process

Yuyu Yin,Zhengshuang Zhu,Min Gao,Aihua Song 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.6

The existing method of task mapping between process models is mostly based on the similarity of labels to get the similarity between tasks, which is affected by a single factor and easy to cause errors. This paper proposes a task mapping method for Artifact-Centric business process analyzes the data operation in business process execution. At first we add the description of data operation to EZ-Flow model. Secondly select the similar artifact attributes of the two business artifact by whole artifacts similarity calculation and based them to calculate two tasks’ similarity by label similarity, artifact operation similarity and context similarity calculations. Finally, the task mapping comes from the optimal selection of tasks’ similarities. Experimental results verify the effectiveness of the method, and show that the method reflects the data operation characteristics of business process model, as artifact task mapping of the process model provides a feasible method.

Cross-domain Recommendation by Combining Feature Tags with Transfer Learning

Yuyu Yin,Xin Wang,Jilin zhang,Jian Wan 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.10

Most recommender systems based on collaborative filtering aim to provide recommendations for a user in one domain. But data sparsity is a major problem for collaborative filtering techniques. Recently, many scholars have proposed recommendation models to alleviate the sparsity problem by transferring rating matrix in other domains. But different domains have different rating scales (e.g., rating scale may be 1-5 or 1-10). Simple process for the rating scale does not reflect the real situation. The diversity of rating scales may cause the opposite effect, making the recommendation results more imprecise. In this paper, we propose a transfer model which learning the common feature tags from other domain. This model ignores the difference of rating scales between two domains, and focus on studying the feature tags. Using its own rating values to fill the missing value. We first get the different types of users (items) based on non-negative matrix tri-factorization from auxiliary domain. The process we call the user (item) clustering. Than we can get a BP neural network which can judge the type of user according to user's feature tags by studying the features of different types of users (items). And we classify the user (items) which from target domain by exploiting the trained neural network and the users’ feature tags of target domain. Use the average rating values of the same type of users (items) to fill the missing value of target domain. We perform extensive experiments to show that our proposed model outperforms the state-of-the-art CF methods for the cross-domain recommendation task.

Biodegradable polyhydroxybutyrate/poly-ε-caprolactone fibrous membranes modified by silica composite hydrol for super hydrophobic and outstanding antibacterial application

Xinghuan Lin,Maoli Yin,Ying Liu,Lin Li,Xuehong Ren,Yuyu Sun,Tung-Shi Huang 한국공업화학회 2018 Journal of Industrial and Engineering Chemistry Vol.63 No.-

Fibrous membranes based on polyhydroxybutyrate/poly-ε-caprolactone (PHB/PCL) blends were obtained by electrospinning. Composite nanoparticles produced from N-halamine precursors and silane precursors were used to modify silica hydrosol which were obtained by the condensation of tetraethylorthosilicate followed the Stöber method. The produced composite nanoparticles were characterized by TEM and FT-IR. The dip-pad process was used to coat the synthesized silica composite nanoparticles onto the fibrous membrane. The coated PHB/PCL fibrous membranes were characterized by SEM, FT-IR and TGA. After chlorination, the chlorinated fibrous membranes showed excellent hydrophobicity with water contact angle of 151° ± 1° and exhibited effective antimicrobial activity against Escherichia coli O157:H7 and Staphylococcus aureus with 99.95% and 99.91% bacterial reduction within 60 min of contact time, respectively. The coated membranes showed good stability and durability toward UVA light exposure and storage. The cell biocompatibility test indicated that the membranes have no cytotoxicity. Therefore, the designed antibacterial fibrous membranes with super hydrophobicity may have great potential for use in food packaging and biomedical materials.

Analyzing the Impact of the Internet on Higher Education

Renjie Zhou,Dongchen Xia,Yuyu Yin,Jilin Zhang,Wei Zhang,Jin Feng 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.6

The Internet has gone deeply into nowadays college students’ life, and has become an important platform for students to study, entertainment, and build social relationships. In this paper, we study the patterns of how college students use the Internet, and analyze the potential impacts of Internet on the living and education of college students. We find that 95% of college students spend more than two hours online per day. Academic and career development is the top motivation for college students to use the Internet. However, high percentage of the college students is not able to control their usage of the Internet well, which leading to recognition that the Internet is a negative factor that affects their course performance. The findings are helpful for educators to guide students to use Internet in a reasonable way and to find ways to make the Internet to be conducive to high quality of higher education.

Optimizing Web Service Composition for Data-intensive Applications

Dongjin Yu,Chang Li,Yuyu Yin 보안공학연구지원센터 2014 International Journal of Database Theory and Appli Vol.7 No.2

The View Growth Pattern of User Generated Videos on YouTube

Renjie Zhou,Dongchen Xia,Yuyu Yin,Jilin Zhang,Wei Zhang 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.6

With the rapid development of social media, video sharing sites like YouTube are getting more and more attention. Discovering the view growth pattern have become interesting topics for researchers as well as advertisers, media companies. In this paper, we analyze two aspects about video view growth pattern of YouTube videos. Firstly, the pattern of aggregated view is studied. It is found that the aggregated view rate peaks in the first few days, and falls quickly in the following days, and then decrease slowly during the consecutive weeks. Finally, the view rate tends to be a constant on the long run. The aggregated view count after a period of two months can be fitted with a linear line. Secondly, the view growth pattern of individual video is explored. The results indicate that the majority of videos peak at the very beginning of videos’ lifetime, and the category of view sources causes the peak is different. The view count of individual video and the view count from each source item also stabilize after a period of two months, and we finally show the referring time and active period of each source item.

DH-LRU: Dynamic Hybrid LRU Caching Scheme for PRAM/DRAM Hybrid Main Memory

Yongjian Ren,Hongtianchen Xie,Gangyong Jia,Jilin Zhang,Yuyu Yin,Jian Wan 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.11

Both performance and capacity of the main memory are the key to the computer systems in current architecture. DRAM, which is the most used main memory, can’t extend in capacity for its high energy consumption and repeatedly refresh. Fortunately, some new memory mediums, such as phase-change memory (PRAM), are used to replace traditional DRAM memory. These new memories have many advantages, like low energy consumption, without repeatedly refresh, high density storage, and so on. Therefore, these memories are promising. However, their low read/write performance and limited life are restricted the replacement process. In current time, hybrid memory, which consists of both PRAM and DRAM, is a good choice. In this way, the memory capacity can be extended. So, the most challenge for the hybrid memory is the performance. In this paper, we propose a dynamic hybrid LRU caching scheme (DH-LRU) for the last level cache in PRAM/DRAM hybrid main memory to improve the main memory performance. Compared with traditional cache policies, like LRU, FIFO, RANDOM, CFLRU, our DH-LRU improves performance by 4.6%. Moreover, energy consumption of write and read operation can be reduced up to 88.2%.

Predicting Web Service QoS via Combining Matrix Factorization with Network Location

Li Zhou,Zhibo Song,Suichu Zhai,Tan Xiao,Yuyu Yin 보안공학연구지원센터(IJUNESST) 2014 International Journal of u- and e- Service, Scienc Vol.7 No.3

Analyzing Spatiotemporal Characteristics of Education Network Traffic with Flexible Multiscale Entropy

Chen Yang,Renjie Zhou,Jian Wan,Jilin Zhang,Yuyu Yin 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.5

In this paper, we propose an analysis method of spatial and temporal characteristics of education network traffic based on flexible multiscale entropy (FMSE). As an improved method, flexible multiscale entropy has a significant improvement in stability and accuracy over multiscale entropy (MSE). We analyze network traffic in different time scales, space scales and traffic levels by building network traffic time-space analysis model and using flexible multiscale entropy as a method to quantify complexity of different network traffic subsequences. The results show that there are distinct characteristics in the complexity of different levels of network traffic. We also find that the existence of a large number of small network traffic flows has a significant influence on the complexity of network traffic.