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| 1 | Extracting elite pairwise constraints for clustering 显示文摘 | Jiang He Ren Zhilei Xuan Jifeng | 2013 | Neurocomput- ing2013，99，1： | 1 |
| 2 | New Insights Into Diversification ofHyper-Heuristics 显示文摘 | Zhilei Ren He Jiang Jifeng Xuan etal | 2014 | IEEE Transactions on Cybernetics2014，44，10： | 1 |
| 3 | Controlled adsorption of cellulase onto pretreated corncob by pH adjustment显示文摘 | Ruoyu Du Rongxin Su Xuan Li Xiaowei Tantai Zhaohui Liu Jifeng Yang Wei Qi Zhimin He | 2012 | Cellulose2012，，2： | 1 |
| 4 | Developer recommendation on bug commenting:a ranking approach for the developer crowd显示文摘A bug tracking system provides a collaborative platform for the developer crowd. After a bug report is submitted, developers can make comments to supplement the details of the bug report. Due to the large number of developers and bug reports, it is hard to determine which developer(also called commenter) is able to comment on a particular bug report. We refer to the problem of recommending developers for commenting on bug reports as commenter recommendation. In this paper, we perform an empirical analysis on commenter recommendation based on five-year bug reports of four open source projects. First, we preliminarily analyze bug comments and commenters in three categories, the relationship between commenters and fixers, the data scale of comments, and the collaboration on bug commenting. Second, we design a recommendation approach via ranking developers in the crowd to reduce the manual effort of identifying commenters. In this approach,we formulize the commenter recommendation problem as a multi-label recommendation task and leverage both developer collaboration and bug content to find out appropriate commenters. Experimental results show that our approach can effectively recommend commenters; 41% to 75% of the recall value is achieved for top-10 recommendation. Our empirical analysis on bug commenting can help developers understand and improve the process of fixing bugs. | Jifeng XUAN He JIANG Hongyu ZHANG Zhilei REN | 2017 | Science China(Information Sciences)2017，60，7： | 1 |
| 5 | Messages from CEISEE 2023 Committee显示文摘The China-Europe International Symposium on Software Engineering Education(CEISEE)is an international educational conference jointly initiated by Harbin Institute of Technology and Technological University Dublin in 2005.The CEISEE is held alternately in China and Europe every year.The host cities include Harbin,Dublin in Ireland,Guangzhou,Bordeaux in France,Xi’an,Northampton in the United Kingdom,Shanghai,Milan in Italy,Chengdu,Zwikau in Germany,Shenyang,Athens in Greece,Shenzhen,Lisbon in Portugal,Beijing,and Wuhan in 2023.The conference has been gaining increasing international influence. | Xiaofei Xu Bing Wu Bing Li Luciano Baresi Wei Lu Rong Peng Yves Ducq Jifeng Xuan Cindy Liu Weiwei Xing Xiaoyuan Xie Peng Liang | 2023 | 计算机教育2023，，12： | 0 |
| 6 | Feature based problem hardness understanding for requirements engineering显示文摘Heuristics and metaheuristics have achieved great accomplishments in various fields, and the investigation of the relationship between these algorithms and the problem hardness has been a hot topic in the research field. Related research work has contributed much to the understanding of the underlying mechanisms of the algorithms for problem solving. However, most existing studies consider traditional combinatorial problems as their case studies. In this study, taking the Next Release Problem(NRP) from the requirements engineering as a case study, we investigate the relationship between software engineering problem instances and heuristics. We employ an evolutionary algorithm to evolve NRP instances, which are uniquely hard or easy for the target heuristic(Greedy Randomized Adaptive Search Procedure and Randomized Hill Climbing in this paper). Then, we use a feature-based method to estimate the hardness of the evolved instances, with respect to the target heuristic. Experimental results demonstrate that, evolutionary algorithm can be used to evolve NRP instances that are uniquely hard or easy to solve. Moreover, the features enable the estimation of the target heuristics' performance. | Zhilei REN He JIANG Jifeng XUAN Shuwei ZHANG Zhongxuan LUO | 2017 | Science China(Information Sciences)2017，60，3： | 0 |
| 7 | Dynamic numerical simulation on grinding medium flow field for vibration mill under various vibrating amplitude–frequency combination conditions显示文摘People gained limited progress on refinement of super-hard powder using the vibration mill for many years.According to various amplitude–frequency combination working conditions of vibration mill prototype,simulation research on dynamic characteristic of grinding medium flow field based on PFC is proposed in the paper,and a dynamics model of grinding medium flow field in barrel is established.Furthermore,trajectory image of medium flow,kinetic energy and strain energy and collision frequency can be obtained.The simulation analysis shows that collision between media as well as between media and the barrel can cause the changes of kinetic energy and strain energy of grinding medium flow under various amplitude–frequency combination conditions,and an energy-lacking region exists in the barrel.Contrast experiments under various working conditions show that kinetic energy and strain energy of grinding medium flow have large increment and energy-lacking regions become smaller,and then energy consumption decreases on working condition of high-amplitude and middle-frequency.The conclusion has practical value to refine powder by high-intensity vibration mill with certain frequency. | Xiaolan Yang Jifeng Liu Xuan Zhang Shangwei Cheng | 2015 | International Journal of Modeling, Simulation, and Scientific Computing2015，6，1： | 0 |
| 8 | Functional characterization of novel NPRL3 mutations identified in three families with focal epilepsy显示文摘Focal epilepsy accounts for 60% of all forms of epilepsy, but the pathogenic mechanism is not well understood. In this study,three novel mutations in NPRL3(nitrogen permease regulator-like 3), c.937_945del, c.1514dup C and 6,706-bp genomic DNA(g DNA) deletion, were identified in three families with focal epilepsy by linkage analysis, whole exome sequencing(WES) and Sanger sequencing. NPRL3 protein is a component of the GATOR1 complex, a major inhibitor of m TOR signaling. These mutations led to truncation of the NPRL3 protein and hampered the binding between NPRL3 and DEPDC5, which is another component of the GATOR1 complex. Consequently, the mutant proteins enhanced m TOR signaling in cultured cells, possibly due to impaired inhibition of m TORC1 by GATOR1. Knockdown of nprl3 in Drosophila resulted in epilepsy-like behavior and abnormal synaptic development. Taken together, these findings expand the genotypic spectrum of NPRL3-associated focal epilepsy and provide further insight into how NPRL3 mutations lead to epilepsy. | Shiyue Du Sheng Zeng Li Song Hongying Ma Rui Chen Junyu Luo Xu Wang Tingbin Ma Xuan Xu Hao Sun Ping Yi Jifeng Guo Yaling Huang Mugen Liu Tao Wang Wei-Ping Liao Luoying Zhang Jing Yu Liu Beisha Tang | 2023 | Science China(Life Sciences)2023，66，9： | 0 |
| 9 | Misleading classification显示文摘In this paper,we investigate a new problem–misleading classification in which each test instance is associated with an original class and a misleading class.Its goal for the data owner is to form the training set out of candidate instances such that the data miner will be misled to classify those test instances to their misleading classes rather than original classes.We discuss two cases of misleading classification.For the case where the classification algorithm is unknown to the data owner,a KNN based Ranking Algorithm(KRA)is proposed to rank all candidate instances based on the similarities between candidate instances and test instances.For the case where the classification algorithm is known,we propose a Greedy Ranking Algorithm(GRA)which evaluates each candidate instance by building up a classifier to predict the test set.In addition,we also show how to accelerate GRA in an incremental way when naive Bayes is employed as the classification algorithm.Experiments on 16 UCI data sets indicated that the ranked candidate instances by KRA can achieve promising leaking and misleading rates.When the classification algorithm is known,GRA can dramatically outperform KRA in terms of leaking and misleading rates though more running time is required. | JIANG He XUAN JiFeng REN ZhiLei WU YouXi WU XinDong | 2014 | Science China(Information Sciences)2014，57，5： | 0 |
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