Jie Ding

Beijing Institute of Technology

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Xuge Fan

Beijing Institute of Technology

Fengyi Jiang

Nanchang University

Vahid Tarokh

Duke University

Asen Asenov

University of Glasgow

Jianli Zhang

Nanchang University

Chunlan Mo

Southeast University

Longquan Xu

Nanchang University

Xiaolan Wang

University of Science and Technology of China

Junlin Liu

Jiangsu University

Wendong Zhang

North University of China

Cooperative Institutions

Chinese Academy of Sciences

University of Glasgow

Nanchang University

Beijing Institute of Technology

Huazhong University of Science and Technology

Taiyuan University of Technology

University of Chinese Academy of Sciences

Tianjin University

University of Science and Technology of China

Tsinghua University

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Research on Virtual Music Teaching Guidance System

Atlantis Highlights in Computer Sciences/Atlantis highlights in computer sciences (2023)

Jie Ding

With the rapid development of scientific and technological information, information technology has been widely used in the teaching of various disciplines.The rapid development and popularization of Internet technology has brought great convenience to people's work, life and study, and also brought great impact on traditional industries.Under this benign influence, people gradually adapt to the existence of the Internet, thus making the birth of the Internet thinking.The development of the Internet has also had a great impact on music teaching.The Internet platform can meet the learning requirements of students in the new era, and then improve the efficiency of students in music learning, so that students can complete the learning of music skills through the Internet.This paper mainly tells about the research of virtual music teaching and guidance system based on the Internet environment, according to the current situation to put forward their own opinions, and put forward some solutions for the current problems, the purpose is to speed up the research progress of virtual music teaching assistance system, improve the learning efficiency of students.

10.2991/978-94-6463-040-4_8

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Machine Learning Enabled Preamble Collision Resolution in Distributed Massive MIMO

Jie Ding Daiming Qu Pei Liu Jinho Choi

Preamble collision is a bottleneck that impairs the performance of random access (RA) user equipment (UE) in grant-free RA (GFRA). In this paper, by leveraging distributed massive multiple input multiple output (mMIMO) together with machine learning, a novel machine learning based framework solution is proposed to address the preamble collision problem in GFRA. The key idea is to identify and employ the neighboring access points (APs) of a collided RA UE for its data decoding rather than all the APs, so that the mutual interference among collided RA UEs can be effectively mitigated. To this end, we first design a tailored deep neural network (DNN) to enable the preamble multiplicity estimation in GFRA, where an energy detection (ED) method is also proposed for performance comparison. With the estimated preamble multiplicity, we then propose a K-means AP clustering algorithm to cluster the neighboring APs of collided RA UEs and organize each AP cluster to decode the received data individually. Simulation results show that a decent performance of preamble multiplicity estimation in terms of accuracy and reliability can be achieved by the proposed DNN, and confirm that the proposed schemes are effective in preamble collision resolution in GFRA, which are able to achieve a near-optimal performance in terms of uplink achievable rate per collided RA UE, and offer significant performance improvement over traditional schemes.<br>

Preamble

Random access

10.36227/techrxiv.13498338.v2

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The analysis of static random access memory stability under the influence of statistical variability and bias temperature instability-induced ageing

Semiconductor Science and Technology (2020)

Jie Ding Asen Asenov

Statistical Analysis

10.1088/1361-6641/abcbd6

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CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning

arXiv (Cornell University) (2024)

Erum Mushtaq Duygu Nur Yaldiz Yavuz Faruk Bakman Jie Ding Chenyang Tao

Continual self-supervised learning (CSSL) learns a series of tasks sequentially on the unlabeled data. Two main challenges of continual learning are catastrophic forgetting and task confusion. While CSSL problem has been studied to address the catastrophic forgetting challenge, little work has been done to address the task confusion aspect. In this work, we show through extensive experiments that self-supervised learning (SSL) can make CSSL more susceptible to the task confusion problem, particularly in less diverse settings of class incremental learning because different classes belonging to different tasks are not trained concurrently. Motivated by this challenge, we present a novel cross-model feature Mixup (CroMo-Mixup) framework that addresses this issue through two key components: 1) Cross-Task data Mixup, which mixes samples across tasks to enhance negative sample diversity; and 2) Cross-Model feature Mixup, which learns similarities between embeddings obtained from current and old models of the mixed sample and the original images, facilitating cross-task class contrast learning and old knowledge retrieval. We evaluate the effectiveness of CroMo-Mixup to improve both Task-ID prediction and average linear accuracy across all tasks on three datasets, CIFAR10, CIFAR100, and tinyImageNet under different class-incremental learning settings. We validate the compatibility of CroMo-Mixup on four state-of-the-art SSL objectives. Code is available at \url{https://github.com/ErumMushtaq/CroMo-Mixup}.

10.48550/arxiv.2407.12188

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Deciphering the energy storage mechanism of CoS2 nanowire arrays for High-Energy aqueous copper-ion batteries

Journal of Colloid and Interface Science (2024)

Rong Niu Jie Ding Jiajun Chen Zhenxin Zhao Xiaomin Wang

Electrochemical energy storage

10.1016/j.jcis.2024.09.073

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The study of electron mobility on ultra-scaled silicon nanosheet FET

Physica Scripta (2024)

Tongfei Liu Ali Rezaei Kaige Yang Xuge Fan Pranav Acharya

Abstract The nanosheet FET (NSFET) is the successor to FinFET, and its mobility significantly affects device performance. In this paper, we investigate the impact of phonon (ph) and surface roughness (SR) scattering on the electron mobility of n-type silicon NSFETs. The effects of channel width, thickness, and doping concentrations on NSFETs' mobility are also analyzed. Non-Equilibrium Green’s Function (NEGF) solver which incorporates scattering mechanisms using the self-energy formulation is employed. The mobility behavior in NSFETs is strongly affected by ph scattering and SR scattering. As for ultrathin nanosheets, severe mobility degradation is dominated by SR scattering. The mobility is slightly affected by the doping concentrations. Simulation results provide guidance to researchers and industry in understanding and predicting the variation of mobility under the trend of continuous scaling.

Nanosheet

Electron Mobility

10.1088/1402-4896/ad56d9

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Jie Ding Chunrong Zuo

Recent years, the frequent occurrence of public health emergency incident in China has caused great loss to economy and severe impact to peoples' lives. The public health emergency decision is an unstructured and non-programmed decision under high pressure, and this has brought great difficulties to public health department. In this paper the case-based reasoning (CBR), a artificial intelligence technology will be introduced to public health emergency decision field and a new similarity measure method for public health case is presented. This method can calculate the similarity of two cases composed of different types of feature values easily which can hardly be achieved by conventional K-NN (k nearest neighbor) method.

Similarity (geometry)

Feature (linguistics)

Similarity measure

10.1109/iccsnt.2011.6182516

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TGF-β/Smads信号通路对胃肠间质瘤细胞增殖和侵袭能力的影响

肿瘤 (2018)

丁杰 Jie Ding 张忠民 Zhongmin Zhang 徐开盛

目的探讨转化生长因子β（transforming growth factor-β，TGF-β）/Smads信号通路对胃肠间质瘤（gastrointestinal stromal tumor，GIST）细胞增殖、侵袭能力的影响及可能的作用机制。方法分别采用外源性TGF-β1单独或联合不同浓度的SB-431542处理GIST882细胞，激活和阻断GIST882细胞的TGF-β/Smads信号转导通路；采用MTT法检测激活和阻断TGF-β/Smads信号通路对GIST882细胞增殖能力的影响，Transwell小室侵袭实验检测对GIST882细胞侵袭能力的影响；实时荧光定量PCR和蛋白质印迹法检测激活和阻断TGF-β/Smads信号通路后对GIST882细胞中Slug mRNA和蛋白表达的影响。采用siRNA干扰的方法沉默Smad3基因的表达，并采用实时荧光定量PCR和蛋白质印迹法检测Smad3基因的沉默效率，及对GIST882细胞中Slug mRNA及蛋白表达的影响。结果TGF-β1激活TGF-β/Smads信号通路后，GIST882细胞的增殖活性和侵袭能力均明显增高（P值均结论TGF-β/Smads信号通路能介导GIST882细胞的增殖和侵袭能力，调控Slug的表达，且该调控是Smad3依赖性的。Slug可能在TGF-β/Smads信号通路介导的GIST转移过程中发挥重要的作用。

10.3781/j.issn.1000-7431.2018.11.672

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The Efficiency Droop of InGaN-Based Green LEDs with Different Superlattice Growth Temperatures on Si Substrates via Temperature-Dependent Electroluminescence

Chinese Physics Letters (2017)

Weijing Qi Longquan Xu Chunlan Mo Xiaolan Wang Jie Ding

InGaN-based green light-emitting diodes (LEDs) with different growth temperatures of superlattice grown on Si (111) substrates are investigated by temperature-dependent electroluminescence between 100 K and 350 K. It is observed that with the decrease of the growth temperature of the superlattice from 895°C to 855°C, the forward voltage decreases, especially at low temperature. We presume that this is due to the existence of the larger average size of V-shaped pits, which is determined by secondary ion mass spectrometer measurements. Meanwhile, the sample with higher growth temperature of superlattice shows a severer efficiency droop at cryogenic temperatures (about 100 K–150 K). Electron overflow into p-GaN is considered to be the cause of such phenomena, which is relevant to the poorer hole injection into multiple quantum wells and the more reduced effective active volume in the active region.

10.1088/0256-307x/34/7/077301

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Simulation research on coupling of metal cavity near the lightning channel based on rocket-triggered Lightning Experiment

2022 Asia-Pacific International Symposium on Electromagnetic Compatibility (APEMC) (2016)

Kun Liu Jie Ding Shun Zhang

Since the thin metal layers results in limited shielding effectiveness against the dominant magnetic field generated by a lightning pulse, research on the shielding effectiveness of metal cavity with slot placed near a lightning channel is of great significance. In this paper, the magnetic fields measured at 78m distance from the classical rocket-triggered lightning flash during the SHandong Artificially Triggering Lightning Experiment (SHATLE) were compared with simulated magnetic fields, acquiring good agreement. The coupling effects of metal cavity with a slot placed at a distance of 78m from the lightning channel are then simulated and analyzed based on the simulation model. According to the simulation results, the location of lightning channel relative to the cavity has a great impact on the magnetic flux density inside the cavity. For the electromagnetic shielding and cooling, the slot located at the top side of the cavity has better performance.

Lightning

Rocket (weapon)

Electromagnetic pulse

10.1109/apemc.2016.7522977

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