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International Conference on Computer Engineering and Applications (ICCEA)

作者： Chuang Feng Chao Che Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

The review of standard declaration of import and export commodities refers to the evaluation of whether the declaration information of the commodities filled in by enterprises conforms to the customs filling standards according to the standardized declaration catalogue The manual review method cannot meet the actual work needs. Therefore, using text classification algorithm to conduct this task is necessary. The classification method based on the pre-training model would rely on the keywords. However, for the review of standard declaration task, excessive reliance on keywords will reduce the classification effect because of ignoring the overall information of the text. Keyword mask pre-training model is proposed. In the fine-tuning stage, the model designs a keyword masking strategy and a keyword blinding strategy. The keyword masking strategy regularizes the BERT model with a mask mechanism, that is, the keywords are reconstructed with other text information except keywords, so that the model focuses on non-keywords information; Keyword blinding strategy makes the model unable to distinguish the categories of text information without contextual text information, which can eliminate the influence of keywords on model decision-making. The experimental results on the real customs declaration data set showing that the method in this thesis exceeds the baseline method in terms of precision and true negative rate.

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Speech Emotion Recognition using Channel Attention Mechanism

Speech Emotion Recognition using Channel Attention Mechanism

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International Conference on Computer Engineering and Applications (ICCEA)

作者： Ruifeng Zhu Caixia Sun Xiaopeng Wei Lasheng Zhao Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education (Dalian University) Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

In order to improve the accuracy of speech emotion recognition, this paper proposes a speech emotion recognition method based on the channel attention mechanism. Firstly, Mel Frequency Ceptral Coefficient(MFCC), speech spectrograms and spectral envelopes are selected as the initial input features; then, multiple depth network models are used to extract feature maps from different angles in parallel; then, weights are assigned and fused to the feature maps output from each sub-depth network model by the channel attention mechanism; finally, the fused feature maps are used to predict emotion categories. The experimental results on CASIA, Emo-DB, and SAVEE emotion datasets show that the method achieves 88.3 % , 85.1%, and 64.5% recognition accuracy, respectively, with better recognition performance compared to recent comparative literature models.

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Performance Verification of State Feedback H∞ State Molecular Controller Via Chemical Reaction Networks 5

Performance Verification of State Feedback H∞ State Molecul...

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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Yao, Jingwang Wang, Xing'An Lv, Hui Li, Yang Zhang, Wujie Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China Dalian University College of Environmental and Chemical Engineering Dalian116622 China Dalian Chivy Biotechnology Co. Ltd Dalian116023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China

ISBN: (纸本)9798350325294

An important goal in synthetic biology is in the design and implementation of control strategies embedded in biochemical reaction systems to enable control of the process at the molecular level. The problem of set-point tracking and perturbation disturbances in the biochemical reaction process can be solved by a state feedback control strategy and a more stable and better dynamic performance of synthetic controllers. First, it is shown how a set of CRNs can provide state feedback to the biomolecular implementation of the H∞ controller. Then, to facilitate the modularity of biochemical process design, CRNs of trigonometric functions and repetitive sequence step signals are defined for the first time as input signals to the controller. Finally, numerical simulation experiments are designed to verify the effectiveness of the whole scheme from several perspectives, such as setpoint tracking and external perturbations. The results show that the state feedback H∞ molecular controller outperforms the conventional linear controller because it has a faster tracking response and better perturbation rejection performance. © 2023 IEEE.

关键词： Controllers

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Family of Mutually Uncorrelated Codes for DNA Storage Address design

IEEE Transactions on Nanobioscience

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IEEE Transactions on Nanobioscience 2025年第3期PP卷 PP页

作者： Liu, Zhenlu Cao, Ben Shao, Qi Zheng, Yanfen Wang, Bin Zhou, Shihua Zheng, Pan Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China University of Canterbury Upper Riccarton Department of Accounting and Information Systems Christchurch8140 New Zealand

Deoxyribonucleic acid (DNA) has become an ideal medium for long-term storage and retrieval due to its extremely high storage density and long-term stability. But access efficiency is an existing bottleneck in DNA storage, especially the lack of high-quality random access address sequences. Therefore, in this paper, we report a series of approaches based on k-weakly mutually uncorrelated (k-WMU) codes to design the address sequence to improve the access efficiency of DNA storage. To address the problem of DNA sequences that are poorly scalable at the base level, we propose a 0-m-ruling coding scheme combined with k-WMU codes that can make address sequences avoid generating secondary structure with stem lengths ranging from 3 to 9. Based on the decoupled structure, We further extend the k-WMU codes with error correction function while satisfying combinatorial biological constraints. In order to investigate the performance of the designed address sequences for real-world applications, we perform simulation experiments based on thermodynamic properties and error correction capability as well as compared the minimum free energy (MFE), melting temperature (TM), and average decoding success rate (ADSR) with previous work. The results show that designed address sequences have a high MFE value and ADSR and a substantial reduction in TM-variance while satisfying the combinatorial biological constraints. As the quality of address sequences improves, this will help to achieve accurate random access as well as enhance the robustness of the DNA storage system. © 2002-2011 IEEE.

关键词： DNA sequences

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A Doctor Recommendation Framework for Online Medical Platforms Using Multi-Source Heterogeneous Data 2021

A Doctor Recommendation Framework for Online Medical Platfor...

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7th International Conference on computing and Artificial Intelligence, ICCAI 2021

作者： Che, Mingxuan Zhao, Lasheng Jin, Bo Dalian University Department of Information Engineering China Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University China School of Innovation and Entrepreneurship Dalian University of Technology China

ISBN: (纸本)9781450389501

The emergence of the online medical platform provides convenience for patients, but at the same time, how to choose the right doctor among thousands of doctors on the platform has become a problem for patients. Nowadays, most doctor recommendation methods meet computation inefficiency issues as the data amount is extreme huge. In addition, the data on different medical platforms cannot be utilized due to inconsistent structures. To address the above two problems, this paper proposes a framework for doctor recommendation using multi-source heterogeneous data with two models: knowledge fusion model and doctor recommendation model. In the knowledge fusion model, two systems are established for co-evolution to integrate multi-source heterogeneity data. One system maps various types of health data to coding strings for evolutionary calculation;the other uses co-evolution to generate a unified coding string. In the doctor recommendation model, the ranking of doctors under different attributes is used as input to obtain the comprehensive ranking of doctors, the method performs effective to fuse knowledge from all kinds of data. The experimental results on 1157 orthopedic surgeons show that our framework greatly improves the computational efficiency while maintaining the accuracy. © 2021 ACM.

关键词： Computational efficiency

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Towards Diverse and Natural Stochastic Human Motion Prediction with a Novel Multiobjective Optimization Framework

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Gui, Xu Yu, Hua Hou, Yaqing Zhang, Qiang Zhou, Dongsheng Dalian University Key lab the Key Laboratory of Advanced Design and Intelligent Computing (Ministry of Education) School of Software Engineering Dalian 116622 China Dalian University of Technology School of Computer Science and Technology Dalian 116024 China

Stochastic human motion prediction has garnered significant attention in the realm of human-robot interactions. However, existing generative models for this task often struggle with mode collapse. Even the widely used denoising diffusion models face a trade-off between the diversity and accuracy of the generated future human motion sequences. Additionally, these methods overlook the motion diversity difference present within the same pattern of human motions. To alleviate this issue, we propose a novel method called Multiobjective Optimization Framework for stochastic Human Motion Prediction (MOFHMP), to enhance the diversity and accuracy of the predicted human motions simultaneously. This proposed MOFHMP reformulates the whole task as a multiobjective optimization problem, and designs a multiobjective optimization network to enhance the diversity and accuracy of predicted human motions. To optimize the designed multiobjective problem, we propose a novel multiobjective optimization algorithm that integrates a Conditional Variational AutoEncoder (CVAE) generative model, which aims to meet the multiple objective requirements in the designed multiobjective function. It is important to note that the Multiobjective Optimization Process (MOP) works in the sampling process of the proposed MOFHMP method, therefore, MOFHMP can enhance the performance of the stochastic human motion prediction without introducing additional training parameters, which means that the proposed method can be easily incorporated to other generative models. In addition, we demonstrate that the proposed MOFHMP also works for controllable human motion prediction, making it a versatile and efficient approach. Through qualitative and quantitative experiments, MOFHMP achieves state-of-the-art results surpassing the baseline methods, validating its superiority in stochastic human motion prediction. © 2016 IEEE.

关键词： controllable human motion prediction generative model multiobjective optimization network Stochastic human motion prediction

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Performance Verification of Smith Predictor Control Using IMC Scheme via Chemical Reaction Networks and DNA Strand Displacement Reaction

Performance Verification of Smith Predictor Control Using IM...

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Smart World Congress (SWC), IEEE

作者： Jingwang Yao Hui Lv Yijun Xiao Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

Biochemical process control is often achieved through feedback control strategies for theoretical analysis and optimization of biochemical reaction processes. Here, the design improves the robustness of the biochemical process by taking advantage of the Smith prediction structure and internal mode control within the chemical reaction network theory framework to intervene against the time delays and perturbations present in the biochemical process. First, an IMC representation of Smith prediction is constructed using the presence of parameter rectification of the control method, and then an IMC-MSP control scheme is proposed. A first-order time-lag controlled object is established in the construction of the IMC-MSP control scheme. Besides, CRNs and kinetic representations are established based on the control structure to facilitate the evaluation of the control system performance. In this paper, CRNs representations of parabolic functions as signal inputs are defined for the first time and optimized for stepping signals to facilitate the design and study of biomolecular circuits. Notably, for the CRNs-based IMC-MSP control scheme, on the one hand, numerical simulation experiments are designed to verify the effectiveness of the whole scheme from multiple perspectives of time delays, external perturbations, and filter tuning parameters; on the other hand, using DNA strand displacement is reflected to verify the feasibility of the whole scheme.

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Static Virus Spread Algorithm for DNA Sequence design

arXiv

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arXiv 2023年

作者： Yao, Yao Zhang, Xun Liu, Xin Liu, Yuan Zhang, Xiaokang Zhang, Qiang The School of Computer Science and Technology Dalian University of Technology Liaoning Dalian116024 China The Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian116622 China

DNA is not only the genetic material of life, but also a favorable material for a new computing model. Various research works based on DNA computing have been carried out in recent years. DNA sequence design is the foundation of such research. The sequence quality directly affects the universality, robustness, and stability of DNA computing. How to design DNA sequences depends on the biological properties and target requirements, which is a typical combinatorial optimization problem. In this paper, in order to design DNA sequences with high-quality, we propose a novel meta-heuristic evolutionary algorithm, termed the static virus spread algorithm (SVS). Through this algorithm, we focus on the constraints of universal DNA sequence design and produce a large number of DNA sequences with non-complementarity and small difference in melting temperature as the objectives, and fully considering the balanced proportion of the four bases. The computer simulation and polyacrylamide gel electrophoresis experiments show that the high-quality DNA sequences designed by this algorithm are effective, which is expected to provide a convenient tool for sequence preparation before DNA biochemical operations. Copyright © 2023, The Authors. All rights reserved.

关键词： DNA sequences

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Research on Speech Synthesis Technology Based on Rhythm Embedding 3

Research on Speech Synthesis Technology Based on Rhythm Embe...

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2020 3rd International Conference on Computer Information Science and Artificial Intelligence, CISAI 2020

作者： Wu, Tianxin Zhao, Lasheng Zhang, Qiang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian116622 China

In recent years, Text-To-Speech (TTS) technology has developed rapidly. People have also been paying more attention to how to narrow the gap between synthetic speech and real speech, hoping that synthesized speech can be integrated with real rhythm. A rhythmic feature embedding method for Text-To-Speech was proposed in this thesis based on Tacotron2 model, which has arisen in the field of TTS in recent years. Firstly, rhythmic feature extraction through World vocoder can reduce redundant information in rhythmic features. Then, rhythmic feature fusion based on Variational Auto-Encoder (VAE) network can enhance rhythmic information. Experiments are carried out on the data set LJSpeech-1.0, and then subjective evaluation and objective evaluation are carried out on the synthesized speech respectively. Compared with the comparative literature, the subjective blind hearing test (ABX) score increased by 25%. At that same time, the objective Mel Cepstral Distortion value (MCD) declined to 12.77. © Published under licence by IOP Publishing Ltd.

关键词： Speech synthesis

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A Novel Cross-FOV Gaze-Driven Human-Robot Interaction Framework for Service Robots

A Novel Cross-FOV Gaze-Driven Human-Robot Interaction Framew...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted computing, UIC-ATC

作者： Zheng Zhao Pengfei Yi Jing Dong Rui Liu Mingkai Cheng Dongsheng Zhou Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing (Ministry of Education) School of Software Engineering Dalian University Dalian China Dalian University of Technology Dalian China

Gaze-based methods have been widely applied in human-robot interactions (HRI). However, most methods were often limited to scenarios where the human face and the gazed object should be in the same field of view (FOV), which is difficult to adapt to the complex and changeable typical daily life scene where the service robot is located. To improve the limitation, this paper proposes a framework capable of completing tasks even if the person and the gazed object are not in the same FOV, requiring only a single RGB camera. First, a cross-FOV gaze estimation algorithm is designed to get the gaze point from images containing a human face captured by an RGB camera. Then a multi-view fusion decision model is employed to drive the robot to turn to the gaze point and identify the object according to the gaze point. Finally, a robot can complete tasks using this information. Experiments under conditions of different lighting, different scenes and different users on the NAO robot show the effectiveness of our method.

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