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International Conference on Informatics and Computing (ICIC)

作者： Aulia Akhrian Syahidi Ahmad Afif Supianto Tsukasa Hirashima Yutaka Watanobe Smart City Information System Applied Undergraduate Program Politeknik Negeri Banjarmasin Banjarmasin City Indonesia Research Center for Data and Information Sciences National Research and Innovation Agency (BRIN) Bandung City Indonesia Learning Engineering Laboratory Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama Higashihiroshima Japan Department of Computer Science and Engineering Division of Information Systems University of Aizu Aizu-Wakamatsu City Fukushima Japan

ISBN: (纸本)9798350345728

Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process, it is necessary to collect a lot of data through analysis of the learning process. The purpose of this study is to recommend and report the performance of an activity tracking system equipped with visual artifacts as an educational data mining approach to analyze action patterns when learners complete the arrangement of program code lines in each programming problem. In this study, data were taken from activity recordings when learners used interactive learning media for a basic programming subject called TOLSYASUPI-EduMed which had problem-solving learning models embedded in their interactions. Learning Analytics is used as a method of this research and data relationships from learner actions during the learning process using the “if-then” rule. Log data is used for recording and detecting activities carried out by learners. We confirm that the results of the study are based on the findings of the data relationship that if the lines of program code are too long (more than five lines) then almost all learners experience a bottleneck condition. The completion time of each question and the number of iterations in completing the program code lines for each question have also been recorded and have a pattern of connection between the data. The information that has been obtained is then forwarded to teachers or stakeholders as key information to make appropriate feedback to learners based on the results as a means of analyzing and evaluating the programming learning process.

关键词： Visualization Codes Media Data models Recording Data mining Problem-solving

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Tunable and adjustable broadband RF photonic fractional Hilbert transformer based on a Kerr soliton crystal optical microcomb

Research Square

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Research Square 2021年

作者： Tan, Mengxi Xu, Xingyuan Moss, David J. The Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia The Electro-Photonics Laboratory Department of Electrical and Computer System Engineering Monash University ClaytonVIC3800 Australia

We demonstrate an RF photonic fractional Hilbert transformer based on an integrated Kerr microcomb source featuring a record low free spectral range of 49 GHz. By programming and shaping the comb lines according to calculated tap weights for up to 39 wavelengths across the C-band, we achieve tunable bandwidths ranging from 1.2 to 15.3 GHz as well as variable center frequencies from baseband to 9.5 GHz, for both standard integral and arbitrary fractional orders. We experimentally characterize the RF amplitude and phase response of the tunable bandpass and lowpass Hilbert transformers with 90 and 45-degree phase shifts. The experimental results show good agreement with theory, confirming the effectiveness of our approach as a powerful way to implement standard and fractional order Hilbert transformers with broad and variable bandwidths and center frequencies, with high reconfigurability and greatly reduced size and complexity. © 2021, CC BY.

关键词： Optical signal processing

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Interfacial spintronic THz emission

arXiv

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arXiv 2023年

作者： Agarwal, Piyush Medwal, Rohit Dongol, Keynesh Mohan, John Rex Yang, Yingshu Asada, Hironori Fukuma, Yasuhiro Singh, Ranjan Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore637371 Singapore Center for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University Singapore639798 Singapore Department of Physics Indian Institute of Technology Uttar Pradesh Kanpur208016 India Department of Electronic Devices and Engineering Graduate School of Science and Engineering Yamaguchi University Ube755-8611 Japan Department of Physics and Information Technology Faculty of Computer Science and System Engineering Kyushu Institute of Technology Iizuka820-8502 Japan

The broken inversion symmetry at the ferromagnet (FM)/heavy-metal (HM) interface leads to spin-dependent degeneracy of the energy band, forming spin-polarized surface states. As a result, the interface serves as an effective medium for converting spin accumulation into two-dimensional charge current through the inverse Rashba-Edelstein effect. Exploring and assessing this spin-to-charge conversion (SCC) phenomenon at the FM/HM interface could offer a promising avenue to surpass the presumed limits of SCC in bulk HM layers. We utilize spintronic heterostructures as a platform to measure the spin-to-charge conversion (SCC) experienced by photoexcited spin currents. These heterostructures emit terahertz electric field when illuminated by femtosecond laser pulses, enabling us to quantitatively assess the ultrafast SCC process. Our results demonstrate a robust interfacial spin-to-charge conversion (iSCC) within a synthetic antiferromagnetic heterostructure, specifically for the NiFe/Ru/NiFe configuration, by isolating the SCC contribution originating from the interface itself, separate from the bulk heavy-metal (HM) region. Moreover, the iSCC at the NiFe/Ru interface is discovered to be approximately 27% of the strength observed in the highest spin-Hall conducting heavy-metal, Pt. Our results thus highlight the significance of interfacial engineering as a promising pathway for achieving efficient ultrafast spintronic devices. Copyright © 2023, The Authors. All rights reserved.

关键词： Electric fields

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Learning interpretable deep state space model for probabilistic time series forecasting

arXiv

引用

arXiv 2021年

作者： Li, Longyuan Yan, Junchi Yang, Xiaokang Jin, Yaohui State Key Lab of Advanced Optical Communication System and Network MoE Key Lab of Artificial Intelligence AI Institute Department of Computer Science and Engineering Shanghai Jiao Tong University China

Probabilistic time series forecasting involves estimating the distribution of future based on its history, which is essential for risk management in downstream decision-making. We propose a deep state space model for probabilistic time series forecasting whereby the non-linear emission model and transition model are parameterized by networks and the dependency is modeled by recurrent neural nets. We take the automatic relevance determination (ARD) view and devise a network to exploit the exogenous variables in addition to time series. In particular, our ARD network can incorporate the uncertainty of the exogenous variables and eventually helps identify useful exogenous variables and suppress those irrelevant for forecasting. The distribution of multi-step ahead forecasts are approximated by Monte Carlo simulation. We show in experiments that our model produces accurate and sharp probabilistic forecasts. The estimated uncertainty of our forecasting also realistically increases over time, in a spontaneous manner. © 2021, CC BY.

关键词： State space methods

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The Effect of Device Redundancy in Timeliness of Information

The Effect of Device Redundancy in Timeliness of Information

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IEEE International Conference on Communications (ICC)

作者： Kang Lang Zhengchuan Chen Nikolaos Pappas Howard H. Yang Yunjian Jia Tony Q. S. Quek School of Microelectronics and Communication Engineering Chongqing University Chongqing China State Key Laboratory of Integrated Services Networks Xidian University Xi'an China Department of Computer and Information Science Linköping University Linköping Sweden Zhejiang University/University of Illinois at Urbana-Champaign Institute Zhejiang University Haining China Information System Technology and Design Pillar Singapore University of Technology and Design Singapore

Emerging interaction-based Internet of Things (IoT) applications have stringent demand for timeliness, imposing critical challenges to the design of status update system. Using redundant devices to update the status of the same process is a promising way to improve timeliness, but this approach can result in out of order update arrivals, making it difficult to analyze timeliness. To that end, the present paper conducts a theoretical study toward the Age of Information (AoI) of a multi-queue status update system where multiple sensors observe one physical process and update a common monitor. Based on the stochastic hybrid systems method, the average AoI of the considered system is derived in closed form. The theoretical results are consistent with the simulation results, verifying the correctness of the theoretical analysis. It is shown that the logarithm of the average AoI is linearly decreasing with the logarithm of the number of sensors.

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Engineered Modular Neuronal Networks-on-Chip Represent Structure-Function Relationship

SSRN

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SSRN 2024年

作者： Habibey, Rouhollah Striebel, Johannes Latiftikhereshki, Roshanak Schmieder, Felix Nasiri, Rohollah Latifi, Shahrzad Universitäts-Augenklinik Bonn University of Bonn Dep. of Ophthalmology Ernst-Abbe-Straße 2 BonnD-53127 Germany CRTD - Center for Regenerative Therapies TU Dresden Dresden01307 Germany Dept. Neuroscience Italian Institute of Technology Genova Italy Department of Computer Engineering Faculty of Engineering Kermanshah Branch Azad University Kermanshah Iran Laboratory of Measurement and Sensor System Technique Faculty of Electrical and Computer Engineering TU Dresden Helmholtzstraße 18 Dresden01069 Germany Division of Nanobiotechnology Department of Protein Science Science for Life Laboratory KTH Royal Institute of Technology Solna Sweden AIMES Center for the Advancement of Integrated Medical and Engineering Sciences Department of Neuroscience Karolinska Institute Solna Sweden Department of Neurology David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Neuroscience Rockefeller Neuroscience Institute West Virginia University MorgantownWV26506 United States

Brain function is substantially linked to the highly organized structure of neuronal networks. The structures of in vitro assembled neuronal circuits often vary between samples and change over time, making it challenging to reliably record network functional output and link it to network structure. Therefore, engineering neuronal structures with predefined geometry and reproducible functional features is essential to robustly model in vivo neuronal circuits. Here, we engineered thin microchannel devices to assemble 2D and 3D modular networks. The microchannel devices were coupled with a multi-electrode array (MEA) electrophysiology system to enable long-term electrophysiology recordings from microengineered circuits. Each network consisted of 64 modules connected to their adjacent modules by micron-sized channels. The microstructures physically confined neurons to the recording electrodes, which significantly improved the efficiency of electrophysiology readout. In addition, the microstructures maintained the modular network structure for weeks. Modular circuits within microfluidic devices showed consistent spatial patterns of activity over weeks, which was lacking in the randomly formed circuits. The number of physical connections per module was shown to influence the measured activity and functional connectivity parameters, which represents the impact of network structure on its functional output. We show that microengineered 3D modular networks with profound activity and higher number of functional connections recapitulate key functional features of developing cortex. Structurally and functionally stable 2D and 3D networks mimic the modular architecture of brain circuits and provide a robust and reproducible in vitro microphysiological system for basic and translational neuroscience research. © 2024, The Authors. All rights reserved.

关键词： Microfluidics

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Static Bound Analysis of Dynamically Allocated Resources for C Programs

Static Bound Analysis of Dynamically Allocated Resources for...

引用

International Symposium on Software Reliability engineering (ISSRE)

作者： Guangsheng Fan Taoqing Chen Banghu Yin Liqian Chen Tengbin Wang Ji Wang College of Computer National University of Defense Technology Changsha China HPCL National University of Defense Technology Changsha China College of System Engineering National University of Defense Technology Changsha China

ISBN: (纸本)9781665425889

It is widely desired to precisely predict bounds of resource usages statically in a program, particularly when the program runs in resource-limited contexts. The resource bound problem becomes more challenging for C programs due to the allowed flexible manipulations on dynamically allocated resources in C. In this paper, we present a static analysis approach to deriving the bounds of dynamically allocated resources for C programs. The key idea is to combine numerical value analysis with pointer analysis under the unified framework of abstract interpretation. First, to track resource usage, we intro-duce auxiliary numerical variables to model the resource usage due to resource-manipulating functions such as allocation and deallocation. Second, to handle resource-manipulating functions involving pointers as parameters or return values, we propose a pointer analysis approach designed specifically for resource bound analysis, and combine it with numerical value analysis, to handle pointer arithmetics, dynamic allocation and deallocation, etc. Then, we infer the value bound of auxiliary resource-usage modeling variables to predict resource bounds at each program location. We have implemented our approach in a tool called DARB and conducted experiments on a set of benchmarks extracted from real-world programs. The results show that DARB can deal with C programs with complex resource manipulations.

关键词： Analytical models Static analysis Predictive models Benchmark testing Dynamic scheduling Numerical models Software reliability

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Unmanned Aerial Vehicle Swarm-Enabled Edge Computing: Potentials, Promising Technologies, and Challenges

arXiv

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arXiv 2022年

作者： Wu, Wei Zhou, Fuhui Wang, Baoyun Wu, Qihui Dong, Chao Hu, Rose Qingyang The College of Communication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China The Department of Electrical and Computer Engineering Utah State University LoganUT84322 United States

Unmanned aerial vehicle (UAV) swarm enabled edge computing is envisioned to be promising in the sixth generation wireless communication networks due to their wide application sensories and flexible deployment. However, most of the existing works focus on edge computing enabled by a single or a small scale UAVs, which are very different from UAV swarm-enabled edge computing. In order to facilitate the practical applications of UAV swarm-enabled edge computing, the state of the art research is presented in this article. The potential applications, architectures and implementation considerations are illustrated. Moreover, the promising enabling technologies for UAV swarm-enabled edge computing are discussed. Furthermore, we outline challenges and open issues in order to shed light on the future research directions. © 2022, CC BY-NC-SA.

关键词： Unmanned aerial vehicles (UAV)

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Improving Heart Transplant Rejection Classification Training using Progressive Generative Adversarial Networks

Improving Heart Transplant Rejection Classification Training...

引用

2021 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2021

作者： Mirzazadeh, Ali Mohseni, Arshawn Ibrahim, Sahar Giuste, Felipe O. Zhu, Yuanda Shehata, Bahig M. Deshpande, Shriprasad R. Wang, May D. The College of Computing Georgia Institute of Technology AtlantaGA30322 United States The Coulter Department of Biomedical Engineering Georgia Institute of Technology AtlantaGA30322 United States The School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30322 United States The Department of Pathology Wayne State University School of Medicine DetroitMI48201 United States The Pediatric Cardiology Children's National Health System WashingtonDC20010 United States

ISBN: (纸本)9781665403580

Cardiac allograft rejection is a life-threatening complication that can occur in patients following heart transplantation. Endomyocardial biopsies, the current gold-standard for monitoring rejection, require manual identification of samples by experts;however, this can be subjective, costly and time-consuming. computer-aided diagnosis models can potentially provide an automated analysis that offers accurate and consistent detection of biopsy samples. Unfortunately, the lack of a large dataset of rejection pathology signs, due to time consuming clinical annotations, limits the classification performance of such conventional AI-based models. In this paper, we developed a generative adversarial network (GAN) that creates synthetic tissue tiles from heart transplant whole slide images (WSIs) to serve as data for training rejection classifier models. To generate synthetic rejection histology regions, we used inspirational image generation (IIG) with a single rejection reference image. Additionally, to demonstrate objective improvement in image classification using synthetic rejection regions, we use a pretrained VGG-19 classifier to differentiate between rejection versus nonrejection tiles. We greatly improved classification performance, achieving an increase in the Matthews correlation coefficient (MCC) from 0.411 to 0.790 when the training set was augmented with our synthetic rejection tiles. Our model was able to create visibly realistic rejection tissue tiles which was used to augment the rejection tile database and enhanced automated rejection detection. © 2021 IEEE

关键词： Generative adversarial networks

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Automatic projector defocus measurement method with large depth of field for fringe projection system

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Measurement Science and Technology 2025年第6期36卷 065018-065018页

作者： Wence Chen Shourui Yang Yang Yu Yangyang Jia Miao Liu Shengyong Chen Engineering Research Center of Learning-Based Intelligent System (Ministry of Education) and the School of Computer Science and Engineering Tianjin University of Technology Tianjin 300384 People’s Republic of China Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin 300072 People’s Republic of China

The optimal defocus method is proved to be helpful to improve the accuracy of fringe projection measurement system. Using this characteristic, this paper proposes an automatic projector defocus method by using a self-designed control module to adjust the projector lens precisely. By applying automatic defocus to large depth of field measurements, the optimal defocus level at any position within the measurement range is determined. First, the gray histogram wave peak detection method is used to divide the object's point cloud into multiple parts, and the optimal defocus measurement is performed to obtain multiple groups of point clouds. Then the linear interpolation method is used to solve the error of each point in the point cloud. Finally, the corresponding points are fused to get a set of point clouds with higher precision. The feasibility and effectiveness of the method are validated by experiments, which demonstrate an improved measurement accuracy of about 16% to the traditional method without defocusing.

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