scholarly journals Modal Sense Classification At Large

2016 ◽  
Vol 14 ◽  
Author(s):  
Ana Marasović ◽  
Mengfei Zhou ◽  
Alexis Palmer ◽  
Anette Frank
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Classification Task ◽  
High Quality ◽  
Modal Verbs ◽  
Empirical Basis ◽  
Syntactic Features ◽  
Projection Approach ◽  
Annotated Corpora

Modal verbs have different interpretations depending on their context. Their sense categories – epistemic, deontic and dynamic – provide important dimensions of meaning for the interpretation of discourse. Previous work on modal sense classification achieved relatively high performance using shallow lexical and syntactic features drawn from small-size annotated corpora. Due to the restricted empirical basis, it is difficult to assess the particular difficulties of modal sense classification and the generalization capacity of the proposed models. In this work we create large-scale, high-quality annotated corpora for modal sense classification using an automatic paraphrase-driven projection approach. Using the acquired corpora, we investigate the modal sense classification task from different perspectives.

The Benders Dual Decomposition Method

2020 ◽  
Vol 68 (3) ◽  
pp. 878-895
Author(s):  
Ragheb Rahmaniani ◽  
Shabbir Ahmed ◽  
Teodor Gabriel Crainic ◽  
Michel Gendreau ◽  
Walter Rei
Keyword(s):  
Decomposition Method ◽  
High Performance ◽  
Large Scale ◽  
Benders Decomposition ◽  
Master Problem ◽  
Computational Results ◽  
Dual Decomposition ◽  
High Quality ◽  
Lagrangian Dual ◽  
Decomposition Strategies

Many methods that have been proposed to solve large-scale MILP problems rely on the use of decomposition strategies. These methods exploit either the primal or dual structures of the problems by applying the Benders decomposition or Lagrangian dual decomposition strategy, respectively. In “The Benders Dual Decomposition Method,” Rahmaniani, Ahmed, Crainic, Gendreau, and Rei propose a new and high-performance approach that combines the complementary advantages of both strategies. The authors show that this method (i) generates stronger feasibility and optimality cuts compared with the classical Benders method, (ii) can converge to the optimal integer solution at the root node of the Benders master problem, and (iii) is capable of generating high-quality incumbent solutions at the early iterations of the algorithm. The developed algorithm obtains encouraging computational results when used to solve various benchmark MILP problems.

Anbar: Collection and analysis of a large scale Urdu language Twitter corpus

2021 ◽  
pp. 1-12
Author(s):  
Bilal Tahir ◽  
Muhammad Amir Mehmood
Keyword(s):  
Computational Linguistics ◽  
High Performance ◽  
Large Scale ◽  
Temporal Frequency ◽  
Quality Data ◽  
User Characteristics ◽  
Vocabulary Size ◽  
High Quality ◽  
Social Analytics ◽  
One Year

 The confluence of high performance computing algorithms and large scale high-quality data has led to the availability of cutting edge tools in computational linguistics. However, these state-of-the-art tools are available only for the major languages of the world. The preparation of large scale high-quality corpora for low resource language such as Urdu is a challenging task as it requires huge computational and human resources. In this paper, we build and analyze a large scale Urdu language Twitter corpus Anbar. For this purpose, we collect 106.9 million Urdu tweets posted by 1.69 million users during one year (September 2018-August 2019). Our corpus consists of tweets with a rich vocabulary of 3.8 million unique tokens along with 58K hashtags and 62K URLs. Moreover, it contains 75.9 million (71.0%) retweets and 847K geotagged tweets. Furthermore, we examine Anbar using a variety of metrics like temporal frequency of tweets, vocabulary size, geo-location, user characteristics, and entities distribution. To the best of our knowledge, this is the largest repository of Urdu language tweets for the NLP research community which can be used for Natural Language Understanding (NLU), social analytics, and fake news detection.

III-V CMOS technologies on Si platform

2011 ◽  
Vol 1336 ◽  
Author(s):  
M. Takenaka ◽  
S. Takagi
Keyword(s):  
Integrated Circuits ◽  
High Performance ◽  
Large Scale ◽  
Film Formation ◽  
High Electron ◽  
High Quality ◽  
Electron Effective Mass ◽  
Monolithically Integrated ◽  
Si Substrates ◽  
Future Technology

ABSTRACTThe heterogeneous integration of III-V semiconductors with the Si platform is expected to provide high performance CMOS logic for future technology nodes because of high electron mobility and low electron effective mass in III-V semiconductors. However, there are many technology issues to be addressed for integrating III-V MOSFETs on the Si platform as follow; high-quality MOS interface formation, low resistivity source/drain formation, and high-quality III-V film formation on Si substrates. In this paper, we present several possible solutions for the above critical issues of III-V MOSFETs on the Si platform. In addition, we present the III-V CMOS photonics platform on which III-V MOSFETs and III-V photonics can be monolithically integrated for ultra-large scale electric-optic integrated circuits.

scholarly journals SMA-Assisted Exfoliation of Graphite by Microfluidization for Efficient and Large-Scale Production of High-Quality Graphene

Nanomaterials ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 1653 ◽  
Author(s):  
Yuzhou Wang ◽  
Xianye Zhang ◽  
Haihui Liu ◽  
Xingxiang Zhang
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Cost Effective ◽  
Scale Production ◽  
Polyamide 66 ◽  
High Quality ◽  
Uniform Size ◽  
Large Scale Production ◽  
Maleic Anhydride Copolymer ◽  
Few Layer Graphene

In this paper, the sodium salt of styrene-maleic anhydride copolymer (SMA) was used as a stabilizer in the process of graphite exfoliation to few-layer graphene using the technique of microfluidization in water. This method is simple, scalable, and cost-effective, and it produces graphene at concentrations as high as 0.522 mg mL−1. The generated high-quality graphene consists of few-layer sheets with a uniform size of less than 1 μm. The obtained graphene was uniformly dispersed and tightly integrated into a polyamide 66 (PA66) matrix to create high-performance multifunctional polymer nanocomposites. The tensile strength and thermal conductivity of 0.3 and 0.5 wt% EG/PA66 composites were found to be ~32.6% and ~28.8% greater than the corresponding values calculated for pure PA66, respectively. This confirms that the new protocol of liquid phase exfoliation of graphite has excellent potential for use in the industrial-scale production of high-quality graphene for numerous applications.

scholarly journals Domain based Chunking

2021 ◽  
Vol 10 (04) ◽  
pp. 1-14
Author(s):  
Nilamadhaba Mohapatra ◽  
Namrata Sarraf ◽  
Swapna sarit Sahu
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Named Entity Recognition ◽  
Entity Recognition ◽  
High Quality ◽  
Specific Domain ◽  
Cold Starting ◽  
Named Entity ◽  
Machine Learning Model ◽  
Grammar Rules

Chunking means splitting the sentences into tokens and then grouping them in a meaningful way. When it comes to high-performance chunking systems, transformer models have proved to be the state of the art benchmarks. To perform chunking as a task it requires a large-scale high quality annotated corpus where each token is attached with a particular tag similar as that of Named Entity Recognition Tasks. Later these tags are used in conjunction with pointer frameworks to find the final chunk. To solve this for a specific domain problem, it becomes a highly costly affair in terms of time and resources to manually annotate and produce a large-high-quality training set. When the domain is specific and diverse, then cold starting becomes even more difficult because of the expected large number of manually annotated queries to cover all aspects. To overcome the problem, we applied a grammar-based text generation mechanism where instead of annotating a sentence we annotate using grammar templates. We defined various templates corresponding to different grammar rules. To create a sentence we used these templates along with the rules where symbol or terminal values were chosen from the domain data catalog. It helped us to create a large number of annotated queries. These annotated queries were used for training the machine learning model using an ensemble transformer-based deep neural network model [24.] We found that grammar-based annotation was useful to solve domain-based chunks in input query sentences without any manual annotation where it was found to achieve a classification F1 score of 96.97% in classifying the tokens for the out of template queries.

scholarly journals Sentiment Classification in Customer Service Dialogue with Topic-Aware Multi-Task Learning

2020 ◽  
Vol 34 (05) ◽  
pp. 9177-9184
Author(s):  
Jiancheng Wang ◽  
Jingjing Wang ◽  
Changlong Sun ◽  
Shoushan Li ◽  
Xiaozhong Liu ◽  
...  
Keyword(s):  
Customer Service ◽  
Large Scale ◽  
Empirical Studies ◽  
Critical Role ◽  
Classification Performance ◽  
Sentiment Classification ◽  
Classification Task ◽  
High Quality ◽  
Task Learning ◽  
Novel Approach

Sentiment analysis in dialogues plays a critical role in dialogue data analysis. However, previous studies on sentiment classification in dialogues largely ignore topic information, which is important for capturing overall information in some types of dialogues. In this study, we focus on the sentiment classification task in an important type of dialogue, namely customer service dialogue, and propose a novel approach which captures overall information to enhance the classification performance. Specifically, we propose a topic-aware multi-task learning (TML) approach which learns topic-enriched utterance representations in customer service dialogue by capturing various kinds of topic information. In the experiment, we propose a large-scale and high-quality annotated corpus for the sentiment classification task in customer service dialogue and empirical studies on the proposed corpus show that our approach significantly outperforms several strong baselines.

High Performance Thermal Conductive Sheets Made of Carbon Fibers

2011 ◽  
Author(s):  
Keisuke Aramaki ◽  
Hiroyuki Ryoson ◽  
Yuichi Ishida
Keyword(s):  
Thermal Conductivity ◽  
Carbon Fibers ◽  
High Performance ◽  
Large Scale ◽  
Cooling System ◽  
Thermal Contact ◽  
Thickness Direction ◽  
High Quality ◽  
Process Step

Today, the quality of LCD (Liquid Crystal Display) TVs has improved along with the quality of the installed LSI (Large Scale Integration) Thus, the cooling system needs to have high performance. However, LCD TV requires a large area but thin cooling system, so the TIM in which used in LCD TV requires highly softness. Thus we have developed high-quality yet soft thermal conductive sheets in which carbon fibers are directed in the thickness direction. The thermal conductivity of the 2-mm-thick sheets is more than 23 W/mK, and the compressibility is more than 10%. In this case the thermal conductivity was measured in accordance with ASTM D5470. The compressibility means the ratio of the difference between the initial thickness and the thickness when the sheets were loaded. The carbon fibers are more than 100 μm long and about 10 μm in diameter. This sheet contains alumina and aluminum nitride particles. The manufacturing process for the sheet is as follows. Step 1: The mixing process. Step 2: The resin including the carbon fibers and the particles is pressed into a long rectangular cast. Step 3: The resin is heated to harden it. Step 4: The resin is sliced into sheets. In step 1, because the carbon fibers are long, the fibers are likely affected by shear stress. Thus, the fibers are aligned in a lengthwise direction. In Step 4, we used a supersonic wave cutter to achieve ideal slicing, thereby reducing the thermal contact resistance. These processes produced high-quality yet soft thermal conductive sheets. In these processes, the carbon fibers aligned in the thickness direction, which was determined in an SEM observation. Moreover, we found that, by slicing in the orientation direction at inclining angles, only the softness improved, without any deterioration in the thermal conductivity.

Potential of hyphenated ultra-high performance liquid chromatography-scheduled multiple reaction monitoring algorithm for large-scale quantitative analysis of traditional Chinese medicines

RSC Advances ◽  
2015 ◽  
Vol 5 (71) ◽  
pp. 57372-57382 ◽  
Author(s):  
Qingqing Song ◽  
Yuelin Song ◽  
Na Zhang ◽  
Jun Li ◽  
Yong Jiang ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
High Performance ◽  
Large Scale ◽  
Multiple Reaction Monitoring ◽  
Core Shell ◽  
Traditional Chinese Medicines ◽  
Reaction Monitoring ◽  
High Quality ◽  
Chinese Medicines ◽  
Monitoring Algorithm

The combination of a core–shell ADME column with a sMRM algorithm offers the potential for large-scale quantitative analysis of the components in TCMs by providing not only high quality quantitative signals but also reliable MS2 spectra.

The Structure and Properties of MoSi2 Thin Film in Mos Process

1980 ◽  
Vol 38 ◽  
pp. 326-327
Author(s):  
C.K. Wu ◽  
P. Chang ◽  
N. Godinho
Keyword(s):  
Thin Film ◽  
Integrated Circuits ◽  
High Performance ◽  
Large Scale ◽  
Process Development ◽  
Structure And Properties ◽  
Metal Silicides ◽  
High Oxidation ◽  
Important Approach ◽  
High Oxidation Resistance

Recently, the use of refractory metal silicides as low resistivity, high temperature and high oxidation resistance gate materials in large scale integrated circuits (LSI) has become an important approach in advanced MOS process development (1). This research is a systematic study on the structure and properties of molybdenum silicide thin film and its applicability to high performance LSI fabrication.

RECOMMENDATIONS FOR THE CHOICE OF MILKING INSTALLATIONS IN LOOSE HOUSING SYSTEMS OF COWS

2020 ◽  
Author(s):  
В.В. ГОРДЕЕВ ◽  
В.Е. ХАЗАНОВ
Keyword(s):  
Dairy Cows ◽  
High Performance ◽  
Large Scale ◽  
Dairy Farms ◽  
Economic Indicators ◽  
Technical Level ◽  
Housing Systems ◽  
Working Shift ◽  
Technical And Economic Indicators

При выборе типа доильной установки и ее размера необходимо учитывать максимальное планируемое поголовье дойных коров и размер технологической группы, кратность и время одного доения, продолжительность рабочей смены дояров. Анализ технико-экономических показателей наиболее распространенных на сегодняшний день типов доильных установок одинакового технического уровня свидетельствует, что наилучшие удельные показатели имеет установка типа «Карусель» (1), а установка типа «Елочка» (2) требует более высоких затрат труда и средств. Установка «Параллель» (3) занимает промежуточное положение. Из анализа пропускной способности и количества необходимых операторов: установка 2 рекомендована для ферм с поголовьем дойного стада до 600 голов, 3 — не более 1200 дойных коров, 1 — более 1200 дойных коров. «Карусель» — наиболее рациональный, высокопроизводительный, легко автоматизируемый и, следовательно, перспективный способ доения в залах, особенно для крупных молочных ферм. The choice of the proper type and size of milking installations needs to take into account the maximum planned number of dairy cows, the size of a technological group, the number of milkings per day, and the duration of one milking and the operator's working shift. The analysis of technical and economic indicators of currently most common types of milking machines of the same technical level revealed that the Carousel installation had the best specific indicators while the Herringbone installation featured higher labour inputs and cash costs. The Parallel installation was found somewhere in between. In terms of the throughput and the required number of operators Herringbone is recommended for farms with up to 600 dairy cows, Parallel — below 1200 dairy cows, Carousel — above 1200 dairy cows. Carousel was found the most practical, high-performance, easily automated and, therefore, promising milking system for milking parlours, especially on the large-scale dairy farms.

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