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Data-Driven Student Support for Academic Success by Developing Student Skill Profiles 2

Data-Driven Student Support for Academic Success by Developi...

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2nd International Multidisciplinary Information Technology and Engineering conference, IMITEC 2020

作者： Ajoodha, Ritesh Dukhan, Shalini Jadhav, Ashwini School of Computer Science and Applied Mathematics The University of the Witwatersrand Johannesburg South Africa School of Animal Plant and Environmental Sciences The University of the Witwatersrand Johannesburg South Africa The University of the Witwatersrand Faculty of Science Johannesburg South Africa

ISBN: (纸本)9781728195209

In this paper, we attempt to provide a data-driven solution to the data-congested environment of attributes related to student success and contribute towards preventing the increased dropout rates at South African higher education institutions. One of the most significant discussions in higher education is student attrition in their first year of study. Student career guidance is an area that requires investigation in light of high attrition rates at university. Recent developments in data analytics, and the analysis of large data sets have enabled the production of powerful predictive models. This paper highlights how a predictive model can assist students, with an interest in Science to develop a skill profile required to be successful in their undergraduate Science programme. This is achieved by identifying the difference between the necessary skills required to be successful in a science programme (derived using data driven approaches) from the current learner's skill profile (derived from the learners' performance in assessments). The learners' skill profile is used to predict success in four Science streamlines. Based on the prediction results, we gauge the improvement in skills required to succeed in that programme. We provide the following contributions: (a) a trained classifier able to calculate the distribution over learners' success in Science streamlines focused around the notion of skill profiles;(b) a ranking of these skill profiles according to their information gain (entropy);and (c) an interactive program to calculate the posterior probability over these skill profiles given learner's pre-university observations. We argue that it is crucial that students gauge the focus areas of skill improvement prior to enrolling for their degree so that they can consider streams in Science degrees that are suited to their academic strengths. © 2020 IEEE.

关键词： Probability distributions

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Redesign NAMD molecular dynamics non-bonded force-field on sunway manycore processor 21

Redesign NAMD molecular dynamics non-bonded force-field on s...

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21st IEEE International conference on high performance Computing and Communications, 17th IEEE International conference on Smart City and 5th IEEE International conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Chen, Junshi An, Hong Yan, Binghui Liang, Weihao Liu, Xin Department of Computer Science and Technology University of Science and Technology of China China National Research Center of Parallel Computer Engineering and Technology Beijing China

ISBN: (纸本)9781728120584

NAnoscale Molecular Dynamics (NAMD) is a parallel molecular dynamics application used to study the structure and dynamics of large biomolecular complexes, such as various types of viruses. In a biomolecular system, billions of time steps are required to understand the biological phenomena of interest. It requires enormous computing power to have a long-timescale observation of the molecule behavior of a large simulation system. NAMD meets this demand with thousands of state-of-the-art manycore processors. The Sunway Taihulight supercomputer is the number one computing system in the top 500 list of supercomputers in November 2017, with a peak performance of 125 PFlops and equipped with 40,960 SW26010 manycore processors. In this paper, we present various optimization techniques that enable the non-bonded force calculation, which is the most computation intensive and time-consuming part of NAMD, to achieve high performance on the SW26010 manycore processor. The optimizations include software cache design on local data memory, separated computing and storage cores, fine-grained inter-core data communication for fast force updating, and vectorization. © 2019 IEEE.

关键词： Molecular dynamics

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Design and Implementation of a Low-Latency and high-Reliability System Based on Software-Defined Radio (SDR) 5

Design and Implementation of a Low-Latency and High-Reliabil...

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5th IEEE International conference on computer and Communications, ICCC 2019

作者： Wu, Zhiwen Yang, Tianpeng Liu, Haitao Shi, Geng Zheng, Kan Beijing University of Posts and Telecommunications Intelligent Computing and Communication Lab Beijing China China Telecom Research Institute Technology Innovation Center Beijing China

ISBN: (纸本)9781728147437

Ultra-reliable and low-latency communication (URLLC) is one of the three major service classes supported by the fifth generation (5G) New Radio (NR) technical specifications. In this paper, we introduce a physical layer architecture that can meet the low-latency and high-reliability requirements. The downlink system is designed according to the Third Generation Partner Project (3GPP) specifications based on software defined radio (SDR) system. The URLLC system physical layer downlink is implemented on the open source OpenAirInterface (OAI) platform to evaluate the latency and reliability performance of the scheme. Not only the URLLC system reliability performance is tested based on the simulation platform, but also the delay performance is evaluated by the realization of the over-the-air system. The experimental results show that the designed scheme can approximately meet the reliability and delay performance requirements of the 3GPP specifications. © 2019 IEEE.

关键词： Software radio

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Synthesizing Smart Solving Strategy for Symbolic Execution

Synthesizing Smart Solving Strategy for Symbolic Execution

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IEEE International conference on Automated Software Engineering (ASE)

作者： Zehua Chen Zhenbang Chen Ziqi Shuai Yufeng Zhang Weiyu Pan College of Computer National University of Defense Technology Changsha China State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

ISBN: (数字)9781450367684

ISBN: (纸本)9781728172811

Constraint solving is one of the challenges for symbolic execution. Modern SMT solvers allow users to customize the internal solving procedure by solving strategies. In this extended abstract, we report our recent progress in synthesizing a program-specific solving strategy for the symbolic execution of a program. We propose a two-stage procedure for symbolic execution. At the first stage, we synthesize a solving strategy by utilizing deep learning techniques. Then, the strategy will be used in the second stage to improve the performance of constraint solving. The preliminary experimental results indicate the promising of our method.

关键词： Deep learning Software engineering

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Learning Pyramid-Context Encoder Network for high-Quality Image Inpainting 32

Learning Pyramid-Context Encoder Network for High-Quality Im...

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IEEE/CVF conference on computer Vision and Pattern Recognition (CVPR)

作者： Zeng, Yanhong Fu, Jianlong Chao, Hongyang Guo, Baining Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou Peoples R China Sun Yat Sen Univ Key Lab Machine Intelligence & Adv Comp Minist Educ Guangzhou Peoples R China Microsoft Res Beijing Peoples R China

ISBN: (纸本)9781728132938

high-quality image inpainting requires filling missing regions in a damaged image with plausible content. Existing works eitherfill the regions by copying image patches or generating semantically-coherent patches from region context, while neglect the fact that both visual and semantic plausibility are highly-demanded. In this paper, we propose a Pyramid-context ENcoder Network (PEN-Net) for image inpainting by deep generative models. The PEN-Net is built upon a U-Net structure, which can restore an image by encoding contextual semantics from full resolution input, and decoding the learned semantic features back into images. Specifically, we propose a pyramid-context encoder, which progressively learns region affinity by attention from a high-level semantic feature map and transfers the learned attention to the previous low-level feature map. As the missing content can be filled by attention transfer from deep to shallow in a pyramid fashion, both visual and semantic coherence for image inpainting can be ensured. We further propose a multi-scale decoder with deeply-supervised pyramid losses and an adversarial loss. Such a design not only results in fast convergence in training, but more realistic results in testing. Extensive experiments on various datasets show the superior performance of the proposed network.

关键词： Computational Photography Image and Video Synthesis

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The performance test and optimization of crystal-MD program on Tianhe-2 2nd

The performance test and optimization of crystal-MD program ...

引用

2nd International Workshop on high performance Computing for Advanced Modeling and Simulation in Nuclear Energy and Environmental Science, HPCMS 2018, and 1st International Workshop on HPC Supported Data Analytics for Edge Computing, HiDEC 2018 held at the 32nd ACM International conference on Supercomputing, ACM ICS 2018

作者： Li, Jianjiang Zhang, Kai Wei, Peng Wang, Jie Hu, Changjun Department of Computer Science and Technology University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9789813299863

In the research field of virtual reactor, the study of materials is one of the most significant issues, and in the research of materials irradiation effect, Molecular Dynamics (MD) is the widely used method. In this paper, the existing Crystal-MD simulation program has been tested in a homogeneous way on the platform of Tianhe-2 supercomputer, and the program has also been rewritten according to the heterogeneous multi-core architecture of Tianhe-2, and finally tested on the Tianhe-2 platform. Our experimentation results show that homogeneous Crystal-MD simulation program has a good expansion on Tianhe-2 and with the same number of nodes, the heterogeneous program is more efficient than the homogeneous one. © Springer Nature Singapore Pte Ltd 2019.

关键词： Supercomputers

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A holistic stream partitioning algorithm for distributed stream processing systems 20

A holistic stream partitioning algorithm for distributed str...

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20th International conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2019

作者： Li, Kejian Liu, Gang Lu, Minhua Guangdong Province Key Laboratory of Popular High Performance Computers Guangdong Province Engineering Center of China-made High Performance Data Computing System College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China School of Biomedical Engineering Shenzhen University Shenzhen518060 China

ISBN: (纸本)9781728126166

The performances of modern distributed stream processing systems are critically affected by the distribution of the load across workers. Skewed data streams in real world are very common and pose a great challenge to these systems, especially for stateful applications. Key splitting, which allows a single key to be routed to multiple workers, is a great idea to achieve good balance of load in the cluster. However, it comes with the cost of increased memory consumption and computation overhead as well as network communication. In this paper, we present a new definition of metric to model the cost of key splitting for intra-operator parallelism in stream processing systems and provide a novel perspective to reduce replication factor while keeping both overall load imbalance and processing latency low. Similar to previous work, our approach treats the head and the tail of the distribution differently in order to reduce memory requirements. For the head, it uses our proposed notion of regional load imbalance to decide dynamically whether to make one more worker responsible for the heavy hitter or not. For the tail, it simply uses hash partitioning to keep the size of the routing table for the head as small as possible. Extensive experimental evaluation demonstrates that our approach provides superior performance compared to the state-of-the-art partitioning algorithms in terms of load imbalance, replication factor and latency over different levels of skewed stream distributions. © 2019 IEEE.

关键词： Distributed parameter control systems

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Anisotropy search in the Ultra high Energy Cosmic Ray Spectrum in the Northern Hemisphere using latest data obtained with Telescope Array surface detector 37

Anisotropy search in the Ultra High Energy Cosmic Ray Spectr...

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37th International Cosmic Ray conference, ICRC 2021

作者： Nonaka, Toshiyuki Abbasi, R.U. Abu-Zayyad, T. Allen, M. Arai, Y. Arimura, R. Barcikowski, E. Belz, J.W. Bergman, D.R. Blake, S.A. Buckland, I. Cady, R. Cheon, B.G. Chiba, J. Chikawa, M. Fujii, T. Fujisue, K. Fujita, K. Fujiwara, R. Fukushima, M. Fukushima, R. Furlich, G. Gonzalez, R. Hanlon, W. Hayashi, M. Hayashida, N. Hibino, K. Higuchi, R. Honda, K. Ikeda, D. Inadomi, T. Inoue, N. Ishii, T. Ito, H. Ivanov, D. Iwakura, H. Iwasaki, A. Jeong, H.M. Jeong, S. Jui, C.C.H. Kadota, K. Kakimoto, F. Kalashev, O. Kasahara, K. Kasami, S. Kawai, H. Kawakami, S. Kawana, S. Kawata, K. Kharuk, I. Kido, E. Kim, H.B. Kim, J.H. Kim, J.H. Kim, M.H. Kim, S.W. Kimura, Y. Kishigami, S. Kubota, Y. Kurisu, S. Kuzmin, V. Kuznetsov, M. Kwon, Y.J. Lee, K.H. Lubsandorzhiev, B. Lundquist, J.P. Machida, K. Matsumiya, H. Matsuyama, T. Matthews, J.N. Mayta, R. Minamino, M. Mukai, K. Myers, I. Nagataki, S. Nakai, K. Nakamura, R. Nakamura, T. Nakamura, T. Nakamura, Y. Nakazawa, A. Nishio, E. Nonaka, T. Oda, H. Ogio, S. Ohnishi, M. Ohoka, H. Oku, Y. Okuda, T. Omura, Y. Ono, M. Onogi, R. Oshima, A. Ozawa, S. Park, I.H. Potts, M. Pshirkov, M.S. Remington, J. Rodriguez, D.C. Rubtsov, G.I. Ryu, D. Sagawa, H. Sahara, R. Saito, Y. Sakaki, N. Sako, T. Sakurai, N. Sano, K. Sato, K. Seki, T. Sekino, K. Shah, P.D. Shibasaki, Y. Shibata, F. Shibata, N. Shibata, T. Shimodaira, H. Shin, B.K. Shin, H.S. Shinto, D. Smith, J.D. Sokolsky, P. Sone, N. Stokes, B.T. Stroman, T.A. Takagi, Y. Takahashi, Y. Takamura, M. Takeda, M. Takeishi, R. Taketa, A. Takita, M. Tameda, Y. Tanaka, H. Tanaka, K. Tanaka, M. Tanoue, Y. Thomas, S.B. Thomson, G.B. Tinyakov, P. Tkachev, I. Tokuno, H. Tomida, T. Troitsky, S. Tsuda, R. Tsunesada, Y. Uchihori, Y. Udo, S. Uehama, T. Urban, F. Wong, T. Yada, K. Yamamoto, M. Yamazaki, K. Yang, J. Yashiro, K. Yoshida, F. Yoshioka, Y. Zhezher, Y. Zundel, Z. Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwanoha Kashiwa Chiba277-8582 Japan Department of Physics Loyola University Chicago ChicagoIL United States High Energy Astrophysics Institute Department of Physics and Astronomy University of Utah Salt Lake CityUT United States Graduate School of Science Osaka City University Osaka Osaka Japan Department of Physics The Research Institute of Natural Science Hanyang University Seongdong-gu Seoul Korea Republic of Department of Physics Tokyo University of Science Chiba Noda Japan Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa Japan The Hakubi Center for Advanced Research Graduate School of Science Kyoto University Kitashirakawa-Oiwakecho Sakyo-ku Kyoto Japan Information Engineering Graduate School of Science and Technology Shinshu University Nagano Nagano Japan Faculty of Engineering Kanagawa University Kanagawa Yokohama Japan Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Yamanashi Kofu Japan Academic Assembly School of Science and Technology Institute of Engineering Shinshu University Nagano Nagano Japan The Graduate School of Science and Engineering Saitama University Saitama Saitama Japan Astrophysical Big Bang Laboratory RIKEN Saitama Wako Japan Department of Physics SungKyunKwan University Jang-an-gu Suwon Korea Republic of Department of Physics Tokyo City University Setagaya-ku Tokyo Japan Institute for Nuclear Research The Russian Academy of Sciences Moscow Russia Faculty of Systems Engineering and Science Shibaura Institute of Technology Minato-ku Tokyo Japan Department of Engineering Science Faculty of Engineering Osaka Electro-Communication University Neyagawa-shi Osaka Japan Department of Physics Chiba University Chiba Chiba Japan Service de Physique Theorique University Libre de Bruxelles Brussels Belgium Department of Physics Yonsei University Seodaemun-gu Seoul Korea Republic of Cente

The Telescope Array (TA) experiment is located in the western desert of Utah, USA and observes ultra-high energy cosmic rays in the northern hemisphere. At the energies, the shape of the cosmic ray energy spectrum carries information of the source distribution. We present the search for differences in spectrum shape in different parts of the sky using latest data of TA surface detector (SD) data. From this study, we observe an apparent enhancement in the region of the northern sky that contain nearby objects, such as the super-galactic plane. Details of this analysis will be presented. © Copyright owned by the author(s).

关键词： Cosmology

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LHCnn: A novel efficient multivariate time series prediction framework utilizing convolutional neural networks 21

LHCnn: A novel efficient multivariate time series prediction...

引用

作者： Liu, Chengxi Li, Kenli Liu, Jing Chen, Cen College of Computer Science and Electronic Engineering Hunan University Changsha China College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China

ISBN: (纸本)9781728120584

The Multivariate time series prediction problem has always been an important and hot issue in the human society. This problem has attracting a large number of researchers to conduct related research. However, the time series data in the real world is highly complex and the data size is large, which brings great inconvenience and challenge to the research work. The RNN-based model made some great progress on the traditional Sequence to Sequence problem such as NLP nowadays. But using the RNN-based model to predict the multivariate time series data still have some problems. For example, the time series data in the real world usually has a certain periodicity, the RNN-based model is hard to capture the global information. In this paper, we propose a CNN-based model called LHCnn(Low-high Cnn). LHCnn combines the CNN with the Attention mechanisms. The model uses multi-layer CNNs to extract the surface and the deep features of the data. Then we combine these two kinds of features with the Attention mechanisms to produce the final prediction. We also train the model in parallel on multiple GPUs to accelerate the training process. In the final part of this paper, we discuss the effort of real-time series data in the experiment, and then proved that this model not only can ensure reliability and stability, but also can achieve higher accuracy. Analyzing working principle of many time series sequencing models and comparing them each other, this one is better than others right now. © 2019 IEEE.

关键词： Forecasting

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Reconstruction of Air Shower Events Measured by the Surface Detectors of the TAx4 Experiment 37

Reconstruction of Air Shower Events Measured by the Surface ...

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37th International Cosmic Ray conference, ICRC 2021

作者： Jeong, Hyomin Abbasi, R.U. Abu-Zayyad, T. Allen, M. Arai, Y. Arimura, R. Barcikowski, E. Belz, J.W. Bergman, D.R. Blake, S.A. Buckland, I. Cady, R. Cheon, B.G. Chiba, J. Chikawa, M. Fujii, T. Fujisue, K. Fujita, K. Fujiwara, R. Fukushima, M. Fukushima, R. Furlich, G. Gonzalez, R. Hanlon, W. Hayashi, M. Hayashida, N. Hibino, K. Higuchi, R. Honda, K. Ikeda, D. Inadomi, T. Inoue, N. Ishii, T. Ito, H. Ivanov, D. Iwakura, H. Iwasaki, A. Jeong, H.M. Jeong, S. Jui, C.C.H. Kadota, K. Kakimoto, F. Kalashev, O. Kasahara, K. Kasami, S. Kawai, H. Kawakami, S. Kawana, S. Kawata, K. Kharuk, I. Kido, E. Kim, H.B. Kim, J.H. Kim, J.H. Kim, M.H. Kim, S.W. Kimura, Y. Kishigami, S. Kubota, Y. Kurisu, S. Kuzmin, V. Kuznetsov, M. Kwon, Y.J. Lee, K.H. Lubsandorzhiev, B. Lundquist, J.P. Machida, K. Matsumiya, H. Matsuyama, T. Matthews, J.N. Mayta, R. Minamino, M. Mukai, K. Myers, I. Nagataki, S. Nakai, K. Nakamura, R. Nakamura, T. Nakamura, T. Nakamura, Y. Nakazawa, A. Nishio, E. Nonaka, T. Oda, H. Ogio, S. Ohnishi, M. Ohoka, H. Oku, Y. Okuda, T. Omura, Y. Ono, M. Onogi, R. Oshima, A. Ozawa, S. Park, I.H. Potts, M. Pshirkov, M.S. Remington, J. Rodriguez, D.C. Rubtsov, G.I. Ryu, D. Sagawa, H. Sahara, R. Saito, Y. Sakaki, N. Sako, T. Sakurai, N. Sano, K. Sato, K. Seki, T. Sekino, K. Shah, P.D. Shibasaki, Y. Shibata, F. Shibata, N. Shibata, T. Shimodaira, H. Shin, B.K. Shin, H.S. Shinto, D. Smith, J.D. Sokolsky, P. Sone, N. Stokes, B.T. Stroman, T.A. Takagi, Y. Takahashi, Y. Takamura, M. Takeda, M. Takeishi, R. Taketa, A. Takita, M. Tameda, Y. Tanaka, H. Tanaka, K. Tanaka, M. Tanoue, Y. Thomas, S.B. Thomson, G.B. Tinyakov, P. Tkachev, I. Tokuno, H. Tomida, T. Troitsky, S. Tsuda, R. Tsunesada, Y. Uchihori, Y. Udo, S. Uehama, T. Urban, F. Wong, T. Yada, K. Yamamoto, M. Yamazaki, K. Yang, J. Yashiro, K. Yoshida, F. Yoshioka, Y. Zhezher, Y. Zundel, Z. Sungkyunkwan University Physics Department Seobu-ro Suwon-si2066 Korea Republic of Cooperation Center for Cosmic Ray Research Seobu-ro Suwon-si2066 Korea Republic of Department of Physics Loyola University Chicago ChicagoIL United States High Energy Astrophysics Institute Department of Physics and Astronomy University of Utah Salt Lake CityUT United States Graduate School of Science Osaka City University Osaka Osaka Japan Department of Physics The Research Institute of Natural Science Hanyang University Seongdong-gu Seoul Korea Republic of Department of Physics Tokyo University of Science Chiba Noda Japan Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa Japan The Hakubi Center for Advanced Research Graduate School of Science Kyoto University Kitashirakawa-Oiwakecho Sakyo-ku Kyoto Japan Information Engineering Graduate School of Science and Technology Shinshu University Nagano Nagano Japan Faculty of Engineering Kanagawa University Kanagawa Yokohama Japan Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Yamanashi Kofu Japan Academic Assembly School of Science and Technology Institute of Engineering Shinshu University Nagano Nagano Japan The Graduate School of Science and Engineering Saitama University Saitama Saitama Japan Astrophysical Big Bang Laboratory RIKEN Saitama Wako Japan Department of Physics SungKyunKwan University Jang-an-gu Suwon Korea Republic of Department of Physics Tokyo City University Setagaya-ku Tokyo Japan Institute for Nuclear Research The Russian Academy of Sciences Moscow Russia Faculty of Systems Engineering and Science Shibaura Institute of Technology Minato-ku Tokyo Japan Department of Engineering Science Faculty of Engineering Osaka Electro-Communication University Neyagawa-shi Osaka Japan Department of Physics Chiba University Chiba Chiba Japan Service de Physique Théorique Université Libre de Bruxelles Brussels Belgium Department of P

The source, propagation and acceleration mechanism of ultra-high-energy cosmic rays (UHECR) have been investigated since the first discovery of the UHECRs to solve the mystery of the extremely high-energy universe. The Telescope Array times 4 (TAx4) experiment, which currently consists of 257 Surface Detectors (SDs) and 2 Fluorescence Detector (FD) stations, had been built in Utah, USA in 2019. The TAx4 SDs observe secondary particles in an extensive air shower induced by the UHECR, and we reconstruct arrival direction and energy of the UHECR using the signal intensities and timings measured by the SDs. We present the reconstruction procedure of the UHECR and the preliminary energy spectrum above 10 EeV measured by the TAx4 SDs. © Copyright owned by the author(s).

关键词： Fluorescence

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