共查询到20条相似文献，搜索用时 15 毫秒
1.
提出一种应用于FPGA中的新型宽调整范围的数字占空比矫正电路.该电路在0.13μm CMOS标准工艺下实现,具有固定上升延时的特性.通过采用连续逼近寄存器,实现了占空比的快速调整.测试结果表明,其调整范围为10%～85%,在80～250 MHz输入范围内输出占空比变化为50%±2%,所需调整时间为6个时钟周期. 相似文献
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3.
《Information processing & management》2023,60(2):103227
Recently, the Transformer model architecture and the pre-trained Transformer-based language models have shown impressive performance when used in solving both natural language understanding and text generation tasks. Nevertheless, there is little research done on using these models for text generation in Arabic. This research aims at leveraging and comparing the performance of different model architectures, including RNN-based and Transformer-based ones, and different pre-trained language models, including mBERT, AraBERT, AraGPT2, and AraT5 for Arabic abstractive summarization. We first built an Arabic summarization dataset of 84,764 high-quality text-summary pairs. To use mBERT and AraBERT in the context of text summarization, we employed a BERT2BERT-based encoder-decoder model where we initialized both the encoder and decoder with the respective model weights. The proposed models have been tested using ROUGE metrics and manual human evaluation. We also compared their performance on out-of-domain data. Our pre-trained Transformer-based models give a large improvement in performance with ～79% less data. We found that AraT5 scores ～3 ROUGE higher than a BERT2BERT-based model that is initialized with AraBERT, indicating that an encoder-decoder pre-trained Transformer is more suitable for summarizing Arabic text. Also, both of these two models perform better than AraGPT2 by a clear margin, which we found to produce summaries with high readability but with relatively lesser quality. On the other hand, we found that both AraT5 and AraGPT2 are better at summarizing out-of-domain text. We released our models and dataset publicly1,.2 相似文献
4.
《Information processing & management》2019,56(6):102093
Knowledge graphs are widely used in retrieval systems, question answering systems (QA), hypothesis generation systems, etc. Representation learning provides a way to mine knowledge graphs to detect missing relations; and translation-based embedding models are a popular form of representation model. Shortcomings of translation-based models however, limits their practicability as knowledge completion algorithms. The proposed model helps to address some of these shortcomings.The similarity between graph structural features of two entities was found to be correlated to the relations of those entities. This correlation can help to solve the problem caused by unbalanced relations and reciprocal relations. We used Node2vec, a graph embedding algorithm, to represent information related to an entity's graph structure, and we introduce a cascade model to incorporate graph embedding with knowledge embedding into a unified framework. The cascade model first refines feature representation in the first two stages (Local Optimization Stage), and then uses backward propagation to optimize parameters of all the stages (Global Optimization Stage). This helps to enhance the knowledge representation of existing translation-based algorithms by taking into account both semantic features and graph features and fusing them to extract more useful information. Besides, different cascade structures are designed to find the optimal solution to the problem of knowledge inference and retrieval.The proposed model was verified using three mainstream knowledge graphs: WIN18, FB15K and BioChem. Experimental results were validated using the hit@10 rate entity prediction task. The proposed model performed better than TransE, giving an average improvement of 2.7% on WN18, 2.3% on FB15k and 28% on BioChem. Improvements were particularly marked where there were problems with unbalanced relations and reciprocal relations. Furthermore, the stepwise-cascade structure is proved to be more effective and significantly outperforms other baselines. 相似文献
5.
Curvature-induced dielectrophoresis for continuous separation of particles by charge in spiral microchannels 总被引：1，自引：0，他引：1
The separation of particles from a heterogeneous mixture is critical in chemical and biological analyses. Many methods have been developed to separate particles in microfluidic devices. However, the majority of these separations have been limited to be size based and binary. We demonstrate herein a continuous dc electric field driven separation of carboxyl-coated and noncoated 10 μm polystyrene beads by charge in a double-spiral microchannel. This method exploits the inherent electric field gradients formed within the channel turns to manipulate particles by dielectrophoresis and is thus termed curvature-induced dielectrophoresis. The spiral microchannel is also demonstrated to continuously sort noncoated 5 μm beads, noncoated 10 μm beads, and carboxyl-coated 10 μm beads into different collecting wells by charge and size simultaneously. The observed particle separation processes in different situations are all predicted with reasonable agreements by a numerical model. This curvature-induced dielectrophoresis technique eliminates the in-channel microelectrodes and obstacles that are required in traditional electrode- and insulator-based dielectrophoresis devices. It may potentially be used to separate multiple particle targets by intrinsic properties for lab-on-a-chip applications. 相似文献
6.
Jang K Xu Y Tanaka Y Sato K Mawatari K Konno T Ishihara K Kitamori T 《Biomicrofluidics》2010,4(3):32208
Recently, interest in single cell analysis has increased because of its potential for improving our understanding of cellular processes. Single cell operation and attachment is indispensable to realize this task. In this paper, we employed a simple and direct method for single-cell attachment and culture in a closed microchannel. The microchannel surface was modified by applying a nonbiofouling polymer, 2-methacryloyloxyethyl phosphorylcholine (MPC) polymer, and a nitrobenzyl photocleavable linker. Using ultraviolet (UV) light irradiation, the MPC polymer was selectively removed by a photochemical reaction that adjusted the cell adherence inside the microchannel. To obtain the desired single endothelial cell patterning in the microchannel, cell-adhesive regions were controlled by use of round photomasks with diameters of 10, 20, 30, or 50 μm. Single-cell adherence patterns were formed after 12 h of incubation, only when 20 and 30 μm photomasks were used, and the proportions of adherent and nonadherent cells among the entire UV-illuminated areas were 21.3%±0.3% and 7.9%±0.3%, respectively. The frequency of single-cell adherence in the case of the 20 μm photomask was 2.7 times greater than that in the case of the 30 μm photomask. We found that the 20 μm photomask was optimal for the formation of single-cell adherence patterns in the microchannel. This technique can be a powerful tool for analyzing environmental factors like cell-surface and cell-extracellular matrix contact. 相似文献
7.
Using femtosecond laser to fabricate highly precise interior three-dimensional microstructures in polymeric flow chip 总被引：1，自引：0，他引：1
This paper reports using femtosecond laser marker to fabricate the three-dimensional interior microstructures in one closed flow channel of plastic substrate. Strip-like slots in the dimensions of 800 μm×400 μm×65 μm were ablated with pulse Ti:sapphire laser at 800 nm (pulse duration of ～120 fs with 1 kHz repetition rate) on acrylic slide. After ablation, defocused beams were used to finish the surface of microstructures. Having finally polished with sonication, the laser fabricated structures are highly precise with the arithmetic roughness of 1.5 and 4.5 nm. Fabricating such highly precise microstructures cannot be accomplished with nanosecond laser marking or other mechanical drilling methods. In addition, since laser ablation can directly engrave interior microstructures in one closed chip, glue smearing problems to damage molded microstructures possibly to occur during the chip sealing procedures can be avoided too. 相似文献
8.
This study presents packaged microscale liquid lenses actuated with liquid droplets of 300-700 μm in diameter using the dielectric force manipulation. The liquid microlens demonstrated function focal length tunability in a plastic package. The focal length of the liquid lens with a lens droplet of 500 μm in diameter is shortened from 4.4 to 2.2 mm when voltages applied change from 0 to 79 V(rms). Dynamic responses that are analyzed using 2000 frames∕s high speed motion cameras show that the advancing and receding times are measured to be 90 and 60 ms, respectively. The size effect of dielectric liquid microlens is characterized for a lens droplet of 300-700 μm in diameter in an aspect of focal length. 相似文献
9.
《Information processing & management》2022,59(6):103112
Existing approaches in online health question answering (HQA) communities to identify the quality of answers either address it subjectively by human assessment or mainly using textual features. This process may be time-consuming and lose the semantic information of answers. We present an automatic approach for predicting answer quality that combines sentence-level semantics with textual and non-textual features in the context of online healthcare. First, we extend the knowledge adoption model (KAM) theory to obtain the six dimensions of quality measures for textual and non-textual features. Then we apply the Bidirectional Encoder Representations from Transformers (BERT) model for extracting semantic features. Next, the multi-dimensional features are processed for dimensionality reduction using linear discriminant analysis (LDA). Finally, we incorporate the preprocessed features into the proposed BK-XGBoost method to automatically predict the answer quality. The proposed method is validated on a real-world dataset with 48121 question-answer pairs crawled from the most popular online HQA communities in China. The experimental results indicate that our method competes against the baseline models on various evaluation metrics. We found up to 2.9% and 5.7% improvement in AUC value in comparison with BERT and XGBoost models respectively. 相似文献
10.
A novel microflow cytometer is proposed in which the particles are focused in the horizontal and vertical directions by means of the Saffman shear lift force generated within a micro-weir microchannel. The proposed device is fabricated on stress-relieved glass substrates and is characterized both numerically and experimentally using fluorescent particles with diameters of 5 μm and 10 μm, respectively. The numerical results show that the micro-weir structures confine the particle stream to the center of the microchannel without the need for a shear flow. Moreover, the experimental results show that the particles emerging from the micro-weir microchannel pass through the detection region in a one-by-one fashion. The focusing effect of the micro-weir microchannel is quantified by computing the normalized variance of the optical detection signal intensity. It is shown that the focusing performance of the micro-weir structure is equal to 99.76% and 99.57% for the 5-μm and 10-μm beads, respectively. Overall, the results presented in this study confirm that the proposed microcytometer enables the reliable sorting and counting of particles with different diameters. 相似文献
11.
《Information processing & management》2022,59(6):103076
Knowledge graph representation learning (KGRL) aims to infer the missing links between target entities based on existing triples. Graph neural networks (GNNs) have been introduced recently as one of the latest trendy architectures serves KGRL task using aggregations of neighborhood information. However, current GNN-based methods have fundamental limitations in both modelling the multi-hop distant neighbors and selecting relation-specific neighborhood information from vast neighbors. In this study, we propose a new relation-specific graph transformation network (RGTN) for the KGRL task. Specifically, the proposed RGTN is the first pioneer model that transforms a relation-based graph into a new path-based graph by generating useful paths that connect heterogeneous relations and multi-hop neighbors. Unlike the existing GNN-based methods, our approach is able to adaptively select the most useful paths for each specific relation and to effectively build path-based connections between unconnected distant entities. The transformed new graph structure opens a new way to model the arbitrary lengths of multi-hop neighbors which leads to more effective embedding learning. In order to verify the effectiveness of our proposed model, we conduct extensive experiments on three standard benchmark datasets, e.g., WN18RR, FB15k-237 and YAGO-10-DR. Experimental results show that the proposed RGTN achieves the promising results and even outperforms other state-of-the-art models on the KGRL task (e.g., compared to other state-of-the-art GNN-based methods, our model achieves 2.5% improvement using H@10 on WN18RR, 1.2% improvement using H@10 on FB15k-237 and 6% improvement using H@10 on YAGO3-10-DR). 相似文献
12.
《Information processing & management》2023,60(3):103298
Effective learning schemes such as fine-tuning, zero-shot, and few-shot learning, have been widely used to obtain considerable performance with only a handful of annotated training data. In this paper, we presented a unified benchmark to facilitate the problem of zero-shot text classification in Turkish. For this purpose, we evaluated three methods, namely, Natural Language Inference, Next Sentence Prediction and our proposed model that is based on Masked Language Modeling and pre-trained word embeddings on nine Turkish datasets for three main categories: topic, sentiment, and emotion. We used pre-trained Turkish monolingual and multilingual transformer models which can be listed as BERT, ConvBERT, DistilBERT and mBERT. The results showed that ConvBERT with the NLI method yields the best results with 79% and outperforms previously used multilingual XLM-RoBERTa model by 19.6%. The study contributes to the literature using different and unattempted transformer models for Turkish and showing improvement of zero-shot text classification performance for monolingual models over multilingual models. 相似文献
13.
《Information processing & management》2022,59(4):102962
Listwise learning to rank models, which optimize the ranking of a document list, are among the most widely adopted algorithms for finding and ranking relevant documents to user information needs. In this paper, we propose ListMAP, a new listwise learning to rank model with prior distribution that encodes the informativeness of training data and assigns different weights to training instances. The main intuition behind ListMAP is that documents in the training dataset do not have the same impact on training a ranking function. ListMAP formalizes the listwise loss function as a maximum a posteriori estimation problem in which the scoring function must be estimated such that the log probability of the predicted ranked list is maximized given a prior distribution on the labeled data. We provide a model for approximating the prior distribution parameters from a set of observation data. We implement the proposed learning to rank model using neural networks. We theoretically discuss and analyze the characteristics of the introduced model and empirically illustrate its performance on a number of benchmark datasets; namely MQ2007 and MQ2008 of the Letor 4.0 benchmark, Set 1 and Set 2 of the Yahoo! learning to rank challenge data set, and Microsoft 30k and Microsoft 10K datasets. We show that the proposed models are effective across different datasets in terms of information retrieval evaluation metrics NDCG and MRR at positions 1, 3, 5, 10, and 20. 相似文献
14.
利用高空场、地面场、物理量场、卫星云图和多普勒雷达资料分析了2006年6月10日强对流天气的发生、发展机制.结果表明:此次过程为一次典型的飑线天气过程,500 hPa的阶梯槽及冷平流、925 hPa暖湿舌的存在是形成该天气的大尺度环流背景;底层辐合场为大气运动提供抬升作用:露点锋是触发强对流天气的重要原因;IC、K指数分布说明此次过程的大尺度典型的不稳定层结. 相似文献
15.
以塔克拉玛干沙漠为主的中国西北沙漠区是东亚地区主要沙尘释放源区之一。本文利用美国大气研究中心（NCAR）的公用气候模式（CCM3）与一个沙尘释放和沉降模式（DEAD）相嵌套、能够反映沙尘扬起及输送和沉降动态过程的耦合模式系统（CCM3-DEAD），通过改变中国西北沙漠-半沙漠区下垫面类型的数值模拟试验，对比分析了西北沙尘源区地表类型的改善对东亚地区沙尘释放及大气粉尘含量变化的可能影响。研究结果表明，地表覆盖状况与沙尘释放关系密切，沙尘源区地表类型的改善可明显抑制沙尘的释放。中国西北沙漠-半沙漠区地表的改善，可引起整个中国北方至蒙古国的大气粉尘含量减少，使大气环境明显改善。假设以塔克拉玛干为主的沙漠-半沙漠区不存在（当地地表类型若以温带草原植被为主），则整个中国北方沙尘释放和沉降通量仅为目前的50%左右。模式中分4个粒级描述沙尘释放及沉降通量，其中1.0~2.5μm和2.5~5.0μm两个粒级的贡献约占总通量的76%，对比试验显示在没有塔克拉玛干等沙漠存在的情况下这两个粒径释放通量大大降低。由西北沙漠-半沙漠区释放的沙尘，经大气环流传输可直接影响到我国东北、华北等东部地区的大气粉尘状况，并对日本、韩国及其周边地区也有一定影响。 相似文献
16.
《Information processing & management》2023,60(3):103327
The high-value patent identification (HVPI) and the standard-essential patent identification (SEPI) are two important issues in the fields of intellectual property and the standardization, respectively. Almost all the HVPI and the SEPI are based on the single-task learning. In this paper, we unify the HVPI and the SEPI in a multi-task learning framework in consideration of the mutual reinforcement of the two tasks. In our model, we extract the patent structured features and embed the patent textual features using the pre-training model. Given these features, we explore a multi-task learning based identification model to identify the high-value patents and the standard-essential patents. We evaluate our model by comparing with two state-of-the-art models on the 5 balanced datasets and 2 imbalanced datasets. The results show our multi-task learning based model outperforms significantly these single-tasking learning based models in the measurements: precision, recall, F1 and accuracy. On the balanced datasets, the average increments of measurements are 1.3%, 1.29%, 1.28% and 1.28% respectively. On the imbalanced datasets, the average increments of measurements are 2.24%, 1.62%, 1.75% and 0.66% respectively. 相似文献
17.
《Information processing & management》2022,59(3):102927
Due to the harmful impact of fabricated information on social media, many rumor verification techniques have been introduced in recent years. Advanced techniques like multi-task learning (MTL), shared-private models suffer from many strategic limitations that restrict their capability of veracity identification on social media. These models are often reliant on multiple tasks for the primary targeted objective. Even the most recent deep neural network (DNN) models like VRoC, Hierarchical-PSV, StA-HiTPLAN etc. based on VAE, GCN, Transformer respectively with improved modification are able to perform good on veracity identification task but with the help of additional auxiliary information, mostly. However, their rise is still not substantial with respect to the proposed model even though the proposed model is not using any additional information. To come up with an improved DNN model architecture, we introduce globally Discrete Attention Representations from Transformers (gDART). Discrete-Attention mechanism in gDART is capable of capturing multifarious correlations veiled among the sequence of words which existing DNN models including Transformer often overlook. Our proposed framework uses a Branch-CoRR Attention Network to extract highly informative features in branches, and employs Feature Fusion Network Component to identify deep embedded features and use them to make enhanced identification of veracity of an unverified claim. Moreover, to achieve its goal, gDART is not dependent on any costly auxiliary resource but on an unsupervised learning process. Extensive experiments reveal that gDART marks a considerable performance gain in veracity identification task over state-of-the-art models on two real world rumor datasets. gDART reports a gain of 36.76%, 40.85% on standard benchmark metrics. 相似文献
18.
基于MODIS/NDVI时序数据的土地覆盖分类 总被引：6，自引：0，他引：6
以250m分辨率的MODIS/NDVI时间序列数据为主要数据源,通过Sacizkky-Golay滤波重建高质量NDVI时间序列数据;同时融合500m分辨率的MODIS多光谱反射率数据和90m分辨率的DEM数据.将非监督分类法和决策树法相结合,进行黑龙江流域土地覆盖分类研究.对分类结果采用已有的土地覆盖数据和高分辨率遥感影像进行精度评价,评价结果表明,利用MODIS/NDVI时间序列数据获得较高精度的土地覆盖分类结果是可行的. 相似文献
19.
城市轨道交通对住房价格影响的计量分析——以南京市地铁1、2号线为例 总被引：4，自引：0，他引：4
本文从理论和实证角度,分析验证了城市轨道交通对沿线站点住房价格的影响。首先通过理论分析提出假说,然后基于特征价格方法构建计量分析模型,利用南京市地铁1、2号线站点附近2km范围内二手楼盘数据,实证分析了城市轨道交通地铁对沿线站点住房价格的影响。结果表明:1城市轨道交通对沿线站点住房价格产生了显著的增值效应,不同距离范围影响程度不同,距地铁站点500m以内住房价格比500m以外高出14.3%,1 000m以内住房价格比1 000m以外高出8.9%,1 500m以内住房价格比1 500m以外高出3.9%,当距离范围超过1 500m后,增值效应在统计上不显著;2轨道交通对住房价格的影响程度与距地铁站点直线距离存在着显著的倒"U"形关系,影响程度随距离先增大后减小,在距地铁站点大约320m时影响程度最大;3轨道交通对沿线站点住房价格的影响程度具有显著的分市场效应,对郊区市场的影响程度要远大于主城区市场。 相似文献
20.
黄土高原低山丘陵区农村居民点分布与地形因子关系研究——以兰州市七里河区为例 总被引：12，自引：1，他引：11
选取黄土高原低山丘陵区的兰州市七里河区农村居民点为研究对象,以ArcGIS9.3软件为技术平台,基于研究区DEM提取研究区高程、坡度、坡向、地形起伏度、地表粗糙度、坡度变率、坡向变率、地表切割深度和地形高程变异系数9个地形因子,在对9个地形因子进行分级分析后,应用分布指数以及信息熵计算分析了地形因子与农村居民点分布格局的关系.结果表明,研究区农村居民点在各地形位上分布的优势地形位分别为:高程1 500～1 750m和1 750～2 000m的地区,坡度0～5°、5～10°和10～15°的地区,坡向W、S、SW的地区,地形起伏度0～50m和50～100m的地区,地表粗糙度1～1.1的地区,坡度变率0～5°的地区,坡向变率10～15°和15～20°的地区,地表切割深度0～10m的地区,地形高程变异系数0～0.003的地区.同时,在各优势地形位上农村居民点的分布呈现出相对较高的有序性,这体现了农村居民点分布格局与地形因子关系的高度关联性. 相似文献