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PFIN : A Parallel Frequent Itemset Mining Algorithm Using Nodesets
Chen Lin,Junzhong Gu 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.6
Frequent Itemset Mining (FIM) is one of most fundamental techniques in data mining with extensive applications to a variety of data mining problems such as association rule mining, correlations, clustering and classification. Since the first proposal of frequent itemset mining, numerous serial algorithms have been proposed in order to improve mining performance, yet most of them cannot scale to massive datasets which are very common nowadays. In this paper, we propose a new parallel FIM algorithm named PFIN based on Nodeset which is a more efficient data structure for mining frequent itemsets. PFIN can intelligently decompose a large-scale FIM problem into a set of tasks, where each task can be executed in parallel without unnecessary communication overheads. Moreover, a hash-based load balancing strategy has been adopted to optimize resource use and maximize throughput. For evaluating the performance of PFIN, we have conduct extensive experiments on Spark which is an emerging distributed in-memory processing framework to compare it against PFP which is one of state-of-the-art parallel FIM algorithms on a range of real datasets. The experimental results demonstrate that our proposed PFIN are highly competitive with PFP in scalability performance, outperforming PFP in speed performance.
Lanlan Chen,Junzhong Zou,Takenao Sugi,Masatoshi Nakamura,Shuichiro Shirakawa 제어·로봇·시스템학회 2010 International Journal of Control, Automation, and Vol.8 No.4
Rest breaks are very important to prevent the accumulation of mental fatigue in sustained mental work environments. In this research, an integrated design and evaluation system for fatigue and relaxation is proposed, which consists of subjective scale, performance assessment and neurological signals. A work-rest schedule containing mental calculation and rest break is designed to reflect effect of prolonged cognitive work and rest time in mental work environments. Inter-individual difference has been taken into account to extract common features. The results indicate that rest breaks in sus-tained mental work are effective to counteract mental fatigue and improve work efficiency. Rest breaks are widely recommended in practical mental work circumstance. Integrated analysis from multi-estimators is helpful to improve the validity and explore the underlying mechanisms central to mental fatigue. Electroencephalogram (EEG) signals at occipital region show high correlation with performance. Thus EEG signals can contribute to the efficient design of work-rest schedule.
Lingbo Kong1,Ziliang Zhang,Yang Song,Junzhong Chen 한국펄프·종이공학회 2023 펄프.종이기술 Vol.55 No.4
With the purpose of improving molded pulp product (MPP) drying process, the present work investigated the microwave drying performance of MPP under the power level of 500 W and compared that with the convective drying method. The drying kinetics, the effective moisture diffusivity, and the energy consumption of the two drying methods were evaluated respectively. It was found that the drying time was shortened from 22.0 min for convective drying to 16.0 min for microwave drying due to 27% of drying rate enhancement, and the effective moisture diffusivity was increased from 3.01×10-10 to 4.49×10-10 m2/s. Additionally, 88% of energy consumption could be saved in the microwave drying process. An artificial neural network (ANN) was employed to predict the moisture removing kinetics of MPP. The results revealed that the ANN modeling could be used to predict the drying kinetics of MPP effectively and then determine the moisture content in the drying process.