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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Hiep X. Dinh Armandas Balcytis Tomoki Ozawa Yasutomo Ota Toshihiko Baba Satoshi Iwamoto Arnan Mitchell Thach G. Nguyen Integrated Photonics and Applications Centre RMIT University Melbourne VIC Australia Advanced Institute for Materials Research Tohoku University Sendai Japan Department of Applied Physics and Physico-Informatics Keio University Yokohama Japan Department of Electrical and Computer Engineering Yokohama National University Yokohama Japan Research Center for Advanced Science and Technology The University of Tokyo Tokyo Japan

We report synthetic frequency dimension Su-Schrieffer-Heeger model and its band structure observation using coupled ring cavities on an integrated photonic chip. Intra-cell and inter-cell couplings between hybridized ... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Structural rings Band structures Couplings Frequency modulation Scalability Electro-optic modulators Ring lasers

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A gelatin-based artificial SEI for lithium deposition regulation and polysulfide shuttle suppression in lithium-sulfur batteries

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Journal of Energy Chemistry 2021年第1期30卷 310-317,I0010页

作者： Naseem Akhtar Xiaogang Sun Muhammad Yasir Akram Fakhar Zaman Weikun Wang Anbang Wang Long Chen Hao Zhang Yuepeng Guan Yaqin Huang Beijing Key Laboratory of Electrochemical Process and Technology for Materials Key Laboratory of Biomedical Materials of Natural MacromoleculesMinistry of EducationBeijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijing 100029China Research Institute of Chemical Defense Beijing 100191China

Lithium-sulfur(Li-S) battery is one of the best candidates for the next-generation energy storage system due to its high theoretical capacity(1675 mA h-1),low cost and environment ***,lithium(Li) dendrites formation and polysulfide shuttle effect are two major challenges that limit the commercialization of Li-S *** we design a facile bifunctional interlayer of gelatin-based fibers(GFs),aiming to protect the Li anode surface from the dendrites growth and also hinder the polysulfide shuttle *** reveal that the 3D structural network of GFs layer with abundant polar sites helps to homogenize Li-ion flux,leading to uniform Li-ion ***,the polar moieties also immobilize the lithium polysulfides and protect the Li metal from the *** a result,the anodeprotected batteries have shown significantly enhanced performance.A high coulombic efficiency of 96% after 160 cycles has been achieved in the Li-Cu half *** Li-Li symmetric cells exhibit a prolonged lifespan for 800 h with voltage hysteresis(10 mV).With the as-prepared GFs layer,the Li-S battery shows approximately 14% higher capacity retention than the pristine battery at 0.5 C after 100 *** work presents that this gelatin-based bi-functional interlayer provides a viable strategy for the manufacturing of advanced Li-S batteries.

关键词： Bifunctional layer Gelatin-based fibers Shuttle effect Artificial SEI Lithium-sulfur battery

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Medical Image Super-Resolution via Diagnosis-Guided Attention

Medical Image Super-Resolution via Diagnosis-Guided Attentio...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Jingwei Wang Peng Zhou Xianjun Han Yanming Chen Anhui Provincial International Joint Research Center for Advanced Technology in Medical Imaging School of Computer Science and Technology Anhui University Hefei China School of Computer Science and Technology Anhui University Hefei China

Medical image super-resolution (SR) is an important medical image processing task and is often helpful for downstream medical analysis tasks. Most of the conventional SR methods tried to generate visually more convincing images whereas ignoring the following downstream tasks. In this paper, we take the Alzheimer’s disease diagnosis as the downstream task and propose a novel diagnosis-guided medical image SR network, which can make the SR and diagnosis be boosted by each other. The method contains two sub-networks, i.e., the SR network and the diagnosis network. To achieve better diagnosis performance, in the SR network, we apply the deformable convolution to capture the regions of interest (ROIs) with different and irregular sizes and shapes, which are important for diagnosis. Moreover, to integrate the two tasks, i.e., SR and diagnosis, more profoundly, we design a novel diagnosis-guided attention module, which makes the key regions for diagnosis can be reconstructed more clearly by the SR network. The extensive experiments on medical image data sets show that the proposed method often outperforms other state-of-the-art SR methods, which demonstrates its effectiveness. The codes of this paper are released in https://***/WJingwei/SRDA.

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CAFI: News Recommendation with Candidate Perception of Fine-Grained Interaction Information

CAFI: News Recommendation with Candidate Perception of Fine-...

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International Conference on Computer Supported Cooperative Work in Design

作者： Yiwen Li Zhenyu Yang Xiaoyang Li Zhijun Li Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

The most critical task in personalized news recommendation is to perform exact matching between candidate news and users’ interests. Existing news recommendation methods usually model users’ interests from historical clicked news items without considering candidate news, which makes it difficult to precisely match candidate news with users’ interests. Moreover, it is challenging to distinguish similar news when forming a vector representation. Simply adding candidate news to the user interest modeling process without considering word-level information does not provide sufficient discrimination for recommending appropriate news. In this paper, we propose a news recommendation model with candidate-aware fine-grained interaction information (CAFI). In our approach, we propose a fine-grained interaction module that matches candidate news items and text fragments of each historical news item at each semantic granularity to achieve interaction between the two at the word level and help similar historical news form more specific and accurate representations. In addition, our proposed gated self-attention mechanism utilizes the candidate news features as channel moderation gates to implement the process of filtering out information that is irrelevant to the candidate news for learning user interest representations, thereby better matching the candidate news to specific user interests. Experiments conducted on the large real-world Microsoft News Dataset (MIND) show that our model significantly outperforms the previously developed models in terms of all metrics. Our code is published at the following URL: https://***/liyiweneven/CAFI.

关键词： Uniform resource locators Measurement Codes Filtering Federated learning Semantics Focusing

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A monolithically sculpted van der Waals nano-opto-electro-mechanical coupler

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Light(science & Applications) 2022年第3期11卷 76-85页

作者： Tongyao Zhang Hanwen Wang Xiuxin Xia Ning Yan Xuanzhe Sha Jinqiang Huang Kenji Watanabe Takashi Taniguchi Mengjian Zhu Lei Wang Jiantou Gao Xilong Liang Chengbing Qin Liantuan Xiao Dongming Sun Jing Zhang Zheng Han Xiaoxi Li State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Opto-ElectronicsShanxi UniversityTaiyuan 030006China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China School of Material Science and Engineering University of Science and Technology of ChinaAnhui 230026China Research Center for Functional Materials National Institute for Materials Science1-1 NamikiTsukuba 305-0044Japan International Center for Materials Nanoarchitectonics National Institute for Materials Science1-1 NamikiTsukuba 305-0044Japan College of Advanced Interdisciplinary Studies National University of Defense TechnologyChangsha 410073China The Key Laboratory of Science and Technology on Silicon Devices Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China The University of Chinese Academy of Sciences Beijing 100029China State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Laser SpectroscopyShanxi UniversityTaiyuan 030006China

The nano-opto-electro-mechanical systems(NOEMS)are a class of hybrid solid devices that hold promises in both classical and quantum manipulations of the interplay between one or more degrees of freedom in optical,electrical and mechanical *** date,studies of NOEMS using van der Waals(vdW)heterostructures are very limited,although vdW materials are known for emerging phenomena such as spin,valley,and topological ***,we devise a universal method to easily and robustly fabricate vdW heterostructures into an architecture that hosts opto-electro-mechanical couplings in one single *** demonstrated several functionalities,including nano-mechanical resonator,vacuum channel diodes,and ultrafast thermo-radiator,using monolithically sculpted graphene NOEMS as a *** readout of electric and magnetic field tuning of mechanical resonance in a CrOCl/graphene vdW NOEMS is further *** results suggest that the introduction of the vdW heterostructure into the NOEMS family will be of particular potential for the development of novel lab-on-a-chip systems.

关键词： monolithic tuning resonator

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HGTA: News Recommendation Based on Hierarchical Granular Semantic Embeddings and Threshold Attention

HGTA: News Recommendation Based on Hierarchical Granular Sem...

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International Conference on Computer Supported Cooperative Work in Design

作者： Yiwen Li Zhenyu Yang Zhijun Li Xiaoyang Li Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

Personalized news recommendation helps users find interesting content among much news information. Most existing news recommendation techniques densely interact a user’s historical clicked news with candidate news to capture their reading interest. However, during this process, even if certain historical clicked news is weakly correlated with the candidate news, the model still interacts with it, generating more noise information when constructing user interests. Simultaneously, the news representation learning process using neural networks is a fine-grained to coarse-grained learning process; i.e., as the network deepens, the fine-grained original news information is easily lost. Therefore, to solve the above problems, this paper proposes a news recommendation model based on hierarchical granular semantic embeddings and threshold attention (HGTA). In HGTA, we propose a threshold attention module to filter unimportant historical clicked news by setting an attention score threshold, i.e., interacting only with historical clicked news that is strongly correlated with the candidate news when capturing user interests. Thus, the model attention is focused, and the noisy interaction information is reduced. Furthermore, when training the neural network, to prevent the loss of fine-grained information, we design a hierarchical granular information extraction module to capture both coarse- and fine-grained news features to better enrich the news semantics. Experiments conducted on the large real-world Microsoft News Dataset (MIND) show that our model achieves highly competitive results in terms of popular metrics. Our code is published at the following URL: https://***/liyiweneven/HGTA.

关键词： Uniform resource locators Training Representation learning Federated learning Semantics Neural networks Noise

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Particle packing theory guided multiscale alumina filled epoxy resin with excellent thermal and dielectric performances

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Journal of Materiomics 2022年第5期8卷 1058-1066页

作者： Qi-Kun Feng Chang Liu Dong-Li Zhang Yan-Hui Song Kai Sun Hai-Ping Xu Zhi-Min Dang State Key Laboratory of Power System Department of Electrical EngineeringTsinghua UniversityBeijing100084China School of Chemistry and Chemical Engineering Xi'an University of Science and TechnologyXi'an710054China Shanghai Engineering Research Center of Advanced Thermal Functional Materials Shanghai Polytechnic UniversityShanghai201209China

Polymers and composites with high thermal conductivity are promising yet challenging for the growing demand of thermal management in electrical and electronic *** by the closest packing model,a multiscale filling Al_(2)O_(3) strategy was designed and incorporated with epoxy resin(EP)to form high thermal conductive composites in this *** composites with single filler loading were also *** microstructures,thermal,rheological,and dielectric characteristics of the multiscale filling Al_(2)O_(3)/EP composites have been *** with single-scale Al_(2)O_(3) filled epoxy based composites,it is found that the multiscale filling Al_(2)O_(3)/EP composites exhibit higher thermal conductivity under the same filler loading of 50 vol%,which is attributed to the efficient heat conduction paths formed by appropriate multiscale ***,a remarkably improved thermal conductivity of 2.707 W m^(-1) K^(-1) was acquired in Al_(2)O_(3)/EP composites at filler loading of 50 vol%(5 mm Al_(2)O_(3)(26.67 vol%),30 mm Al_(2)O_(3)(27.41 vol%)and 70 mm Al_(2)O_(3)(45.92 vol%)),which is about 1300%higher than that of the pure epoxy *** addition,the dielectric constant of the Al_(2)O_(3)/EP composites were significantly improved while keeping the dielectric loss almost *** finite element simulation further verified the effectiveness of improving the thermal conductivity of materials in the heat dissipation of electrical ***,this research provides a simple strategy for manufacturing high thermal conductive composite materials with a wide range of potential applications as packaging materials.

关键词： Closest packing model Epoxy composites Alumina Thermal conductivity Dielectric property

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Imbalanced data In Energy Disaggregation 3

Imbalanced data In Energy Disaggregation

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2022 3rd International Conference on Computer Information and Big Data Applications, CIBDA 2022

作者： Shang, Yong Gao, Xiaoyu Zhao, Xiaoyong North China Electric Power Scientific Research Institute Co. Beijing China School of Information and Manage Beijing Information Science & Technology University Beijing China Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Information Science & Technology University Beijing100129 China

ISBN: (纸本)9783800758760

Energy disaggregation forecasts the consumption of individual appliance from a single meter that records a household's overall electricity requirement. Although the appliance's consumption of each usage fits a specific pattern, its load contains however different repetitive patterns in a period with personal habits of householder. Thus, it has no significant distribution and many numeric power levels as usual classification problem. Imbalanced data contains a skewed class as minority comparing to its majority, which is widely regarded as a significant drawback of the performance obtained by most standard classifier algorithms. Regarding the class biases a lot from the majority, the definition of skewed class and minority in regression shall be redefined in energy disaggregation. Upon the scenario, this paper aims to locate the rare class and provide an empirical assumption to help the relevant models to achieve higher performance. Accordingly, this paper locates the imbalanced data in Non-Intrusive Load Monitoring (NILM) in detail and verify the effect of skewed data to the modeling process. It supplies for reasoning performance difference between NILM dataset and appliances and provides a factor of promoting relevant algorithms' performance. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Electric load management

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Opinion-Tree-guided Contrastive Learning for Aspect Sentiment Quadruple Prediction

Opinion-Tree-guided Contrastive Learning for Aspect Sentimen...

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International Conference on Computer Supported Cooperative Work in Design

作者： Zhijun Li Zhenyu Yang Yiwen Li Xiaoyang Li Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

In recent years, aspect sentiment quadruple prediction (ASQP) has become a popular task in the field of aspect-based sentiment analysis. When modeling comment statements, it is often necessary to consider structural information between sentiment labels. Existing approaches categorize these labels by encoding text and dependency tree structures separately and then incorporating their representations, but this approach fails to effectively capture the structural information between sentiment labels. To address this problem, we propose a method for ASQP called Opinion-Tree-guided Contrastive Learning (OTCL), which embeds structural information directly into the text instead of modeling it separately. Specifically, OTCL utilizes the opinion tree structure to guide the construction of positive samples of the input text during training. By associating the input text with its positive samples, the text encoder can learn to generate textual representations associated with the opinion tree structure. We validate the effectiveness of our method on two commonly used datasets.

关键词： Training Sentiment analysis Federated learning Contrastive learning Predictive models Encoding Task analysis

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Lensless efficient snapshot hyperspectral imaging using dynamic phase modulation

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Photonics research 2025年第2期13卷 511-526页

作者： CHONG ZHANG XIANGLEI LIU LIZHI WANG SHINING MA YUANJIN ZHENG YUE LIU HUA HUANG YONGTIAN WANG WEITAO SONG Beijing Engineering Research Center of Mixed Reality and Advanced Display School of Optics and PhotonicsBeijing Institute of TechnologyBeijing 100081China Zhengzhou Research Institute Beijing Institute of TechnologyZhengzhou 450000China State Key Laboratory of Radio Frequency Heterogeneous Integration College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China School of Computer Science and Technology Beijing Institute of TechnologyBeijing 100081China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore School of Artificial Intelligence Beijing Normal UniversityBeijing 100875China

Snapshot hyperspectral imaging based on a diffractive optical element(DOE)is increasingly featured in recent progress in deep *** remarkable advances in spatial and spectral resolutions,the limitations of current photolithography technology have prevented the fabricated DOE from being designed at ideal heights and with high diffraction efficiency,diminishing the effectiveness of coded imaging and reconstruction accuracy in some ***,we propose,to our knowledge,a new lensless efficient snapshot hyperspectral imaging(LESHI)system that utilizes a liquid-crystal-on-silicon spatial light modulator(LCoS-SLM)to replace the traditionally fabricated DOE,resulting in high modulation levels and reconstruction *** the single-lens imaging model,the system can leverage the switch ability of LCoS-SLM to implement distributed diffractive optics(DDO)imaging and enhance diffraction efficiency across the full visible *** the proposed method,we develop a proof-of-concept prototype with an image resolution of 1920×1080 pixels,an effective spatial resolution of 41.74μm,and a spectral resolution of 10 nm,while improving the average diffraction efficiency from 0.75 to0.91 over the visible wavelength range(400-700 nm).Additionally,LESHI allows the focal length to be adjusted from 50 mm to 100 mm without the need for additional optical components,providing a cost-effective and timesaving solution for real-time on-site *** is the first imaging modality,to the best of our knowledge,to use dynamic diffractive optics and snapshot hyperspectral imaging,offering a completely new approach to computational spectral imaging and deep optics.

关键词： photolithography technology fabricated doe Efficient coded imaging diffractive optical element doe Snapshot Lensless deep opticsdespite

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