Weifang, China

Weifang University

www.wfu.edu.cn/
Weifang, China

Weifang University is a university based in Weifang City, Shandong Province, China. Wikipedia.


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News Article | May 5, 2017
Site: en.prnasia.com

WUXI, China, May 6, 2017 /PRNewswire/ -- The final round of the 2017 ASC Student Supercomputer Challenge (ASC17) ended in Wuxi. Tsinghua University stood out from 20 teams from around the world after a fierce one-week competition, becoming grand champion and winning the prize. As the world's largest supercomputing competition, ASC17 received applications from 230 universities around the world, 20 of which got through to the final round held this week at the National Supercomputing Center in Wuxi after the qualifying rounds. During the final round, the university student teams were required to independently design a supercomputing system under the precondition of a limited 3000W power consumption. They also had to operate and optimize standard international benchmark tests and a variety of cutting-edge scientific and engineering applications including AI-based transport prediction, genetic assembly, and material science. Moreover, they were required to complete high-resolution maritime simulation on the world's fastest supercomputer, "Sunway TaihuLight". The grand champion, team Tsinghua University, completed deep parallel optimization of the high-resolution maritime data simulation mode MASNUM on TaihuLight, expanding the original program up to 10,000 cores and speeding up the program by 392 times. This helped the Tsinghua University team win the e Prize award. MASNUM was nominated in 2016 for the Gordon Bell Prize, the top international prize in the supercomputing applications field. The runner-up, Beihang University, gave an outstanding performance in the popular AI field. After constructing a supercomputing system which received massive training based on past big data of transportation provided by Baidu, their self-developed excellent deep neural network model yielded the most accurate prediction of road conditions during the morning peak. The first-time finalist, Weifang University team, constructed a highly optimized advanced heterogeneous supercomputing system with Inspur's supercomputing server, and ran the international HPL benchmark test, setting a new world record of 31.7 TFLOPS for float-point computing speed. The team turned out to be the biggest surprise of the event and won the award for best computing performance. Moreover, Ural Federal University, National Tsing Hua University, Northwestern Polytechnical University and Shanghai Jiao Tong University won the application innovation award. The popular choice award was shared by Saint-Petersburg State University and Zhengzhou University. "It is great to see the presence of global teams in this event," Jack Dongarra, the Chairman of the ASC Expert Committee, founder of the TOP500 list that ranks the 500 most powerful supercomputer systems in the world, and professor at the Oak Ridge National Laboratory of the United States and the University of Tennessee, said in an interview. "This event inspired students to gain advanced scientific knowledge. TaihuLight is an amazing platform for this event. Just imagine the interconnected computation of everyone's computer in a gymnasium housing 100,000 persons, and TaihuLight's capacity is 100 times of such a gym. This is something none of the teams will ever be able to experience again." According to Wang Endong, initiator of the ASC competition, academician of the Chinese Academy of Engineering, and the chief scientist of Inspur Group, the rapid development of AI at the moment is significantly changing human society. At the core of such development are computing, data and algorithms. With this trend, supercomputers will become an important infrastructure for intelligent society in the future, and their speed of development and standards will be closely related to social development, improvement in livelihood, and progress of civilization. ASC competition is always committed to cultivating future-oriented, inter-disciplinary supercomputing talents to extend the benefits to the greater population. ASC17 is jointly organized by the Asian Supercomputing Community, Inspur Group, the National Supercomputing Center in Wuxi, and Zhengzhou University. Initiated by China, the ASC supercomputing challenge aims to be the platform to promote exchanges among young supercomputing talent from different countries and regions, as well as to groom young talent. It also aims to be the key driving force in promoting technological and industrial innovations by improving the standards in supercomputing applications and research. To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/tsinghua-university-won-asc17-championship-big-time-300452166.html


News Article | May 5, 2017
Site: www.prnewswire.com

The grand champion, team Tsinghua University, completed deep parallel optimization of the high-resolution maritime data simulation mode MASNUM on TaihuLight, expanding the original program up to 10,000 cores and speeding up the program by 392 times. This helped the Tsinghua University team win the e Prize award. MASNUM was nominated in 2016 for the Gordon Bell Prize, the top international prize in the supercomputing applications field. The runner-up, Beihang University, gave an outstanding performance in the popular AI field. After constructing a supercomputing system which received massive training based on past big data of transportation provided by Baidu, their self-developed excellent deep neural network model yielded the most accurate prediction of road conditions during the morning peak. The first-time finalist, Weifang University team, constructed a highly optimized advanced heterogeneous supercomputing system with Inspur's supercomputing server, and ran the international HPL benchmark test, setting a new world record of 31.7 TFLOPS for float-point computing speed. The team turned out to be the biggest surprise of the event and won the award for best computing performance. Moreover, Ural Federal University, National Tsing Hua University, Northwestern Polytechnical University and Shanghai Jiao Tong University won the application innovation award. The popular choice award was shared by Saint-Petersburg State University and Zhengzhou University. "It is great to see the presence of global teams in this event," Jack Dongarra, the Chairman of the ASC Expert Committee, founder of the TOP500 list that ranks the 500 most powerful supercomputer systems in the world, and professor at the Oak Ridge National Laboratory of the United States and the University of Tennessee, said in an interview. "This event inspired students to gain advanced scientific knowledge. TaihuLight is an amazing platform for this event. Just imagine the interconnected computation of everyone's computer in a gymnasium housing 100,000 persons, and TaihuLight's capacity is 100 times of such a gym. This is something none of the teams will ever be able to experience again." According to Wang Endong, initiator of the ASC competition, academician of the Chinese Academy of Engineering, and the chief scientist of Inspur Group, the rapid development of AI at the moment is significantly changing human society. At the core of such development are computing, data and algorithms. With this trend, supercomputers will become an important infrastructure for intelligent society in the future, and their speed of development and standards will be closely related to social development, improvement in livelihood, and progress of civilization. ASC competition is always committed to cultivating future-oriented, inter-disciplinary supercomputing talents to extend the benefits to the greater population. ASC17 is jointly organized by the Asian Supercomputing Community, Inspur Group, the National Supercomputing Center in Wuxi, and Zhengzhou University. Initiated by China, the ASC supercomputing challenge aims to be the platform to promote exchanges among young supercomputing talent from different countries and regions, as well as to groom young talent. It also aims to be the key driving force in promoting technological and industrial innovations by improving the standards in supercomputing applications and research. To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/tsinghua-university-won-asc17-championship-big-time-300452166.html


Li J.,Weifang University
Acta Crystallographica Section E: Structure Reports Online | Year: 2011

In the crystal structure of the title compound, C2H 8N+·-C9H3Br4O 4 -·CH4O, intermolecular N - H⋯O and O - H⋯O hydrogen bonds link the components into chains along [001]. Additional stabilization is supplied by weak C - H⋯O and C - H⋯Br interactions.


Li J.,Weifang University
Acta Crystallographica Section E: Structure Reports Online | Year: 2011

In the anion of the title compound, C7H10N +·C9H3Br4O4-·CH3O, the dihedral angles formed by the benzene ring and the mean planes of the carboxyl-ate and meth-oxy-carbonyl groups are 74.8 (5) and 75.0 (5)°, respectively. In the crystal, intermolecular N - H⋯O and O - H⋯O hydrogen bonds link the components into chains along [100]. Additional stabilization is provided by weak intermolecular C - H⋯O hydrogen bonds.


Zinc finger genes comprise a large and diverse gene family. Based on their individual finger structures and spacing, zinc finger proteins are further divided into different families according to their specific molecular functions. Genes in the CCCH family encode zinc finger proteins containing a motif with three cysteines and one histidine. They play important roles in plant growth and development, and in response to biotic and abiotic stresses. However, the limited analysis of the genome sequence has meant that there is no detailed information concerning the CCCH zinc finger family in tomato (Solanum lycopersicum). Here, we identified 80 CCCH zinc finger protein genes in the tomato genome. A complete overview of this gene family in tomato was presented, including the chromosome locations, gene duplications, phylogeny, gene structures and protein motifs. Promoter sequences and expression profiles of putative stress-responsive members were also investigated. These results revealed that, with the exception of four genes, the 80 CCCH genes are distributed over all 12 chromosomes with different densities, and include six segmental duplication events. The CCCH family in tomato could be divided into 12 groups based on their different CCCH motifs and into eight subfamilies by phylogenetic analysis. Analysis showed that almost all CCCH genes contain putative stress-responsive cis-elements in their promoter regions. Nine CCCH genes chosen for further quantitative real-time PCR analysis showed differential expression patterns in three representative tomato tissues. In addition, their expression levels indicated that these genes are mostly involved in the response to mannitol, heat, salicylic acid, ethylene or methyl jasmonate treatments. To the best of our knowledge, this is the first report of a genome-wide analysis of the tomato CCCH zinc finger family. Our data provided valuable information on tomato CCCH proteins and form a foundation for future studies of these proteins, especially for those members that may play important roles in stress responses. © 2014, Springer-Verlag Berlin Heidelberg.


Liu L.,Weifang University
Communications in Computer and Information Science | Year: 2011

In this paper, the existence of analytic solutions of an iterative functional differential equation is studied. We reduce this problem to finding analytic solutions of a functional differential equation without iteration of the unknown function. For technical reasons, in previous work the constant α given in Schröder transformation is required to fulfill that α is off the unit circle or lies on the circle with the Diophantine condition. In this paper, we break the restraint of the Diophantine condition and obtain results of analytic solutions in the case of α at resonance, i.e., at a root of the unity and the case of α near resonance under the Brjuno condition. © 2011 Springer-Verlag Berlin Heidelberg.


Xing M.,Weifang University
Journal of Convergence Information Technology | Year: 2012

Open source software has become an increasingly threatening competitor to traditional proprietary software. Through a modified vertical differentiation model, this paper investigates how open source software affects the quality of proprietary software and software differentiation. Assume that proprietary software producer pursues profit maximization and open source software is freely available for users. Moreover, users need to bear higher opportunity costs in learning and maintaining open source software in comparison with proprietary software. The results show that the quality of proprietary software may not increase in the quality of open source software. This conclusion subverts the traditional understanding of people. Moreover, software differentiation between open source and proprietary software decreases with an increase in the usability or features level of open source software.


A new method using electromagnetic voltage transformers to transfer transient travelling waves is proposed to locating the line faults and identifies the faults type in neutral non-effective grounding system. Analysis model of electromagnetic voltage transformers for analyzing transform characteristics of traveling waves is built, and the transform characteristics is studied using parameters of practical voltage transformers. The results show that electromagnetic voltage transformers can transfer traveling waves surge effectively and meeting the needs of fault location. The transform characteristics and rules of travelling waves for three-phase electromagnetic voltage transformers are analyzed. The results show that there are certain rules for the transient traveling waves of single-phase earth fault and various short-circuit faults transferring to the secondary side of electromagnetic voltage transformers. On this basis, the principle and method that using the signals measured in the secondary side of electromagnetic voltage transformers to locate line faults point and judge the type of fault is proposed. Experimental tests verify the feasibility and correctness of the proposed method.


Chang A.,Weifang University
Iranian Polymer Journal (English Edition) | Year: 2015

The pH-sensitive starch-g-poly(acrylic acid)/sodium alginate (St-g-PAA/SA) hydrogel beads for the controlled release of diclofenac sodium(DS) were prepared simply by crosslinking SA using calcium ions under the existence of the St-g-PAA superabsorbent. The St-g-PAA/SA-DS hydrogel beads were characterized by IR and scanning electron microscopy. The effects of weight ratio of St-g-PAA to SA and pH on the swelling behaviors of the hydrogel beads in pH 7.4 phosphate buffer solution were investigated. In addition, the effects of weight ratio of St-g-PAA to SA and the concentration of SA solution on the entrapment efficiency (EE) for DS and the cumulative release of DS were studied in detail. The St-g-PAA/SA-DS hydrogel beads are pH-sensitive with an interpenetrated polymer network. The introduced St-g-PAA superabsorbent has great influence on the swelling behavior and the cumulative release of DS. The pristine SA-DS hydrogel beads disintegrated in pH 7.4 phosphate buffer solution in 3 h, whereas the disintegration of SA-DS beads was delayed or avoided by introducing a proper amount of the St-g-PAA superabsorbent. Also, the burst release of DS was successfully overcome by the introduced St-g-PAA superabsorbent. A weight ratio of St-g-PAA to SA of 1:9 and an SA concentration of 4 wt % are very helpful for the sustained release of DS. © 2015, Iran Polymer and Petrochemical Institute.


Song J.,Weifang University
International Journal of Digital Content Technology and its Applications | Year: 2012

In order to confirm the spatiallocation of the fruit target, a target location method by inosculating ultrasonic ranging and vision was developed for eggplant picking robot. The two dimension image information was achieved by means of color camera. The distance of fruit target was measured by using ultrasonic distance measurer. A three layers BP(Back Propagation) neural network was structured to locate the eggplant. The input variables of the neural network were image center coordinates and distance obtained by ultrasonic distance measurer. The output were space coordinates of picking point. The improved BP algorithm was used to train the parameter of the neural network. The effective parameter was achieved after 100 times of training. Experiments showed that the average rms error of the space coordinates of eggplant was 15.6mm when the measure distance ranges from 150 mm to 600 mm and the average time consumed was 0.27s. The target location method by inosculating ultrasonic ranging and vision information for eggplant picking robot owns good intelligence and wide adaptability and it can meet the demands of the eggplant picking robot.

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