Search | Engineering

Subscribe Submit

Home Journals Focus Achievement Fronts About Us 中文版

Resource Type

Journal Article 8

Year

2022 1

2020 2

2018 1

2017 1

2016 1

2002 1

Keywords

sentiment analysis 2

Association rules 1

Cross-domain 1

Destination image 1

Information visualization 1

Kansei Engineering 1

Sentiment classification 1

Sentiment visualization 1

Sequence visualization 1

Tourism user-generated content 1

active defense 1

active immunity 1

boosting algorithm 1

cloudnetwork integration 1

deterministic network 1

emotion 1

life-time 1

multi-level protection 1

novel network architecture 1

open ︾

Search scope:

排序： Display mode:

Qian Xuesen—An Example for Scientific and Technological Circles to Learn From

Tu Yuanji

Strategic Study of CAE 2002, Volume 4, Issue 2, Pages 1-7

Abstract:

Qian Xuesen´s life-time is reviewed in this article and his excellent character and behaviour that are benefited from good family breeding and school education are highly praised. His brilliant talent and plentiful attainments after receiving his training under Theodore von Kármán in the United States are introduced. The article describes, with host of facts that are rarely known, Qian´s unrelenting struggle for returning homeland and the contributions he made with all his heart to China´s space undertaking after he returned to China. Finally, the article reveals Qian´s lofty ideological level and virtuous character towards money, honour and position.

Keywords： seek knowledge tackle key problems in science and technology work style thinking and moral character revolutionarysentiment

HTML PDF Collect

Review of sentiment analysis: An emotional product development view

Frontiers of Engineering Management Pages 592-609 doi: 10.1007/s42524-022-0227-z

Abstract: Given that sentiment analysis (SA) can extract and analyze people’s opinions, sentiments, attitudes,

Keywords： sentiment analysis emotion product development Kansei Engineering

HTML PDF Collect

NLWSNet: a weakly supervised network for visual sentiment analysis in mislabeled web images

Luo-yang Xue, Qi-rong Mao, Xiao-hua Huang, Jie Chen,mao_qr@ujs.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 9, Pages 1267-1412 doi: 10.1631/FITEE.1900618

Abstract: Large-scale datasets are driving the rapid developments of deep convolutional neural networks for . However, the annotation of large-scale datasets is expensive and time consuming. Instead, it is easy to obtain weakly labeled web images from the Internet. However, noisy labels still lead to seriously degraded performance when we use images directly from the web for training networks. To address this drawback, we propose an end-to-end network, which is robust to mislabeled web images. Specifically, the proposed attention module automatically eliminates the distraction of those samples with incorrect labels by reducing their attention scores in the training process. On the other hand, the special-class activation map module is designed to stimulate the network by focusing on the significant regions from the samples with correct labels in a approach. Besides the process of feature learning, applying regularization to the classifier is considered to minimize the distance of those samples within the same class and maximize the distance between different class centroids. Quantitative and qualitative evaluations on well- and mislabeled web image datasets demonstrate that the proposed algorithm outperforms the related methods.

HTML PDF Collect

Words alignment based on association rules for cross-domain sentiment classification None

Xi-bin JIA, Ya JIN, Ning LI, Xing SU, Barry CARDIFF, Bir BHANU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 2, Pages 260-272 doi: 10.1631/FITEE.1601679

Abstract: Automatic classification of sentiment data (e.g., reviews, blogs) has many applications in enterpriseHowever, it is difficult to train an accurate sentiment classifier for different domains.One of the major reasons is that people often use different words to express the same sentiment in differentSo, the accuracy of the sentiment classifier will decline sharply when we apply a classifier trainedpropose a novel approach called words alignment based on association rules (WAAR) for cross-domain sentiment

Keywords： Sentiment classification Cross-domain Association rules

HTML PDF Collect

The influence of social media on stock volatility

Xianjiao WU, Xiaolin WANG, Shudong MA, Qiang YE

Frontiers of Engineering Management 2017, Volume 4, Issue 2, Pages 201-211 doi: 10.15302/J-FEM-2017018

Abstract: social factors, such as increased attention to a stock’s volatility, is more significant than public sentimentA prediction model is introduced based on social factors and public sentiment to predict stock volatility

Keywords： stock volatility social data sentiment analysis boosting algorithm

HTML PDF Collect

Development of Novel Network Architectures

Ouyang Man, Liu Jiang, Liao Xinyue, Huang Tao

Strategic Study of CAE 2022, Volume 24, Issue 4, Pages 12-21 doi: 10.15302/J-SSCAE-2022.04.002

Abstract: Existing technological solutions are categorized into evolutionary and revolutionary solutions.As revolutionary solutions, researchers advocate strategies for redesigning the network, seeking a novel

It is noteworthy that revolutionary solutions can better meet futureterms of existing novel network architectures, the ICN and eXpressible Internet Architecture (XIA) are revolutionary

Keywords： novel network architecture revolutionary and evolutionary networks deterministic network segment routing

HTML PDF Collect

The Strategy of TC 3.0: A Revolutionary Evolution in Trusted Computing

Shen Changxiang,Zhang Dawei and Liu Jiqiang,Ye Heng, Qiu Shuo

Strategic Study of CAE 2016, Volume 18, Issue 6, Pages 53-57 doi: 10.15302/J-SSCAE-2016.06.011

Abstract:

This paper introduces the status, problems, and future strategies of the traditional defense system and analyzes issues in the current protection structure. We then propose the trusted computing (TC) 3.0 strategy, which is an active defense architecture based on active immunity. Furthermore, we give an example of TC 3.0 in cloud computing and provide some suggestions on enforcing active defense.

Keywords： trusted computing (TC) 3.0 active defense active immunity multi-level protection protection structure