scholarly journals Linear Context Transform Block

2020 ◽  
Vol 34 (04) ◽  
pp. 5553-5560
Author(s):  
Dongsheng Ruan ◽  
Jun Wen ◽  
Nenggan Zheng ◽  
Min Zheng
Keyword(s):  
Empirical Study ◽  
State Of The Art ◽  
Future Research ◽  
Computational Burden ◽  
Global Context ◽  
Linear Transform ◽  
Consistent Performance ◽  
Performance Gains ◽  
Context Features ◽  
The Relationship

Squeeze-and-Excitation (SE) block presents a channel attention mechanism for modeling global context via explicitly capturing dependencies across channels. However, we are still far from understanding how the SE block works. In this work, we first revisit the SE block, and then present a detailed empirical study of the relationship between global context and attention distribution, based on which we propose a simple yet effective module, called Linear Context Transform (LCT) block. We divide all channels into different groups and normalize the globally aggregated context features within each channel group, reducing the disturbance from irrelevant channels. Through linear transform of the normalized context features, we model global context for each channel independently. The LCT block is extremely lightweight and easy to be plugged into different backbone models while with negligible parameters and computational burden increase. Extensive experiments show that the LCT block outperforms the SE block in image classification task on the ImageNet and object detection/segmentation on the COCO dataset with different backbone models. Moreover, LCT yields consistent performance gains over existing state-of-the-art detection architectures, e.g., 1.5∼1.7% APbbox and 1.0%∼1.2% APmask improvements on the COCO benchmark, irrespective of different baseline models of varied capacities. We hope our simple yet effective approach will shed some light on future research of attention-based models.

The Effect Of Humble Leader Behavior, Leader Expertise, And Organizational Identification On Employee Turnover Intention

2016 ◽  
Vol 32 (4) ◽  
pp. 1145-1156 ◽  
Author(s):  
Jie Li ◽  
Qiao Zhuan Liang ◽  
Zhen Zhen Zhang
Keyword(s):  
Boundary Condition ◽  
Empirical Study ◽  
Leadership Style ◽  
Organizational Identification ◽  
Turnover Intention ◽  
Employee Turnover ◽  
Leader Behavior ◽  
Future Research ◽  
Employee Turnover Intention ◽  
The Relationship

As a bottom-up leadership style, humble leadership has attracted increasing attention from scholars in recent years. But its effectiveness and mechanism still lack rigorous empirical study. In this study, we investigate the mechanism and boundary condition by which humble leader behavior exerts influence on followers’ turnover intention. Two-wave data collected from 249 scientific and technological personnel in China supported our hypothesized model. We found that humble leader behavior is significantly negatively related to follower turnover intention. The relationship is further partially mediated by organizational identification, and moderated by leader expertise. Implications for theory, practice and future research are discussed. 

scholarly journals IMPACT OF MICROFINANCE LOANS ON THE PERFORMANCE OF SMES: THE CASE OF LEBANON

2020 ◽  
Vol 21 (2) ◽  
pp. 769-779
Author(s):  
Fida Moussa
Keyword(s):  
Empirical Study ◽  
Financial Performance ◽  
Empirical Evidence ◽  
Low Income ◽  
Secondary Data ◽  
Future Research ◽  
The North ◽  
Dependent Variables ◽  
The Relationship ◽  
The Needy

Microfinance is the arrangement of budgetary administrations to low-income individuals and to SMEs. An empirical study was undertaken to identify the relationship between micro credits from MFIs and the SMEs’ financial performance. Secondary data were collected from 17 SMEs in North Lebanon. Another secondary data were collected from four MFIs in Lebanon concerning the characteristics of their beneficiaries. Data were analyzed using SPSS Ver. 23. The results showed notable relationships between amount of micro loan and the dependent variables, the number of women recipients of credits remains little in Lebanon, the categories of businesses mostly profiting from the MFIs in Lebanon are commerce, service, and trade sectors and the beneficiaries are primarily situated at Mount Lebanon, South, Bekaa, and at the north. The research contributes to the enduring deliberation on the effect of micro loans on the SMEs’ financial performance. It is vital to see how MFIs could add to the monetary advancement of the country, by improving the welfare levels of all the needy individuals. This study can be utilized to provide useful empirical evidence for future research and to raise awareness on this significant matter for SMEs’ managers, MFIs’ managers and clients, and for the analysts.

scholarly journals LCF: A Local Context Focus Mechanism for Aspect-Based Sentiment Classification

2019 ◽  
Vol 9 (16) ◽  
pp. 3389 ◽  
Author(s):  
Biqing Zeng ◽  
Heng Yang ◽  
Ruyang Xu ◽  
Wu Zhou ◽  
Xuli Han
Keyword(s):  
State Of The Art ◽  
Sentiment Classification ◽  
Experimental Results ◽  
Local Context ◽  
Baseline Model ◽  
Global Context ◽  
Benchmark Datasets ◽  
Art Performance ◽  
Context Features

Aspect-based sentiment classification (ABSC) aims to predict sentiment polarities of different aspects within sentences or documents. Many previous studies have been conducted to solve this problem, but previous works fail to notice the correlation between the aspect’s sentiment polarity and the local context. In this paper, a Local Context Focus (LCF) mechanism is proposed for aspect-based sentiment classification based on Multi-head Self-Attention (MHSA). This mechanism is called LCF design, and utilizes the Context features Dynamic Mask (CDM) and Context Features Dynamic Weighted (CDW) layers to pay more attention to the local context words. Moreover, a BERT-shared layer is adopted to LCF design to capture internal long-term dependencies of local context and global context. Experiments are conducted on three common ABSC datasets: the laptop and restaurant datasets of SemEval-2014 and the ACL twitter dataset. Experimental results demonstrate that the LCF baseline model achieves considerable performance. In addition, we conduct ablation experiments to prove the significance and effectiveness of LCF design. Especially, by incorporating with BERT-shared layer, the LCF-BERT model refreshes state-of-the-art performance on all three benchmark datasets.

scholarly journals The relationship between return on investment and the market share of certain listed companies in selected market sectors: 1975 - 1985

1988 ◽  
Vol 19 (3) ◽  
pp. 85-89
Author(s):  
P. W.C. De Wit ◽  
N. J.R. Steyn
Keyword(s):  
Empirical Study ◽  
South African ◽  
Market Share ◽  
Return On Investment ◽  
Positive Relationship ◽  
Theoretical Study ◽  
Future Research ◽  
Meaningful Relationship ◽  
The Relationship ◽  
A Company

During a theoretical study of company objectives it was found that it is generally assumed that a positive relationship exists between return on investment and the market share of a company. Examination of the formula for calculating return on investment shows, however, that this may not necessarily be the case. As existing studies regarding this relationship could not give any clarity, the need arose for a South African based study. An empirical study was accordingly executed on listed retail stores and companies involved in the manufacturing and distribution of furniture. The period involved was 1975-1985. No meaningful relationship between return on investment and market share could be found. Various recommendations that may lead to more conclusive results during future research were made. The need for accurate findings exists to establish whether the marketing objective is in line with the company objective.

The state of the art in semantic relatedness: a framework for comparison

2017 ◽  
Vol 32 ◽  
Author(s):  
Yue Feng ◽  
Ebrahim Bagheri ◽  
Faezeh Ensan ◽  
Jelena Jovanovic
Keyword(s):  
State Of The Art ◽  
Semantic Relatedness ◽  
Knowledge Bases ◽  
The State ◽  
Future Research ◽  
Research Directions ◽  
Knowledge Resources ◽  
Future Research Directions ◽  
The Relationship ◽  
Sr Method

AbstractSemantic relatedness (SR) is a form of measurement that quantitatively identifies the relationship between two words or concepts based on the similarity or closeness of their meaning. In the recent years, there have been noteworthy efforts to compute SR between pairs of words or concepts by exploiting various knowledge resources such as linguistically structured (e.g. WordNet) and collaboratively developed knowledge bases (e.g. Wikipedia), among others. The existing approaches rely on different methods for utilizing these knowledge resources, for instance, methods that depend on the path between two words, or a vector representation of the word descriptions. The purpose of this paper is to review and present the state of the art in SR research through a hierarchical framework. The dimensions of the proposed framework cover three main aspects of SR approaches including the resources they rely on, the computational methods applied on the resources for developing a relatedness metric, and the evaluation models that are used for measuring their effectiveness. We have selected 14 representative SR approaches to be analyzed using our framework. We compare and critically review each of them through the dimensions of our framework, thus, identifying strengths and weaknesses of each approach. In addition, we provide guidelines for researchers and practitioners on how to select the most relevant SR method for their purpose. Finally, based on the comparative analysis of the reviewed relatedness measures, we identify existing challenges and potentially valuable future research directions in this domain.

scholarly journals A Novel Residual Dense Pyramid Network for Image Dehazing

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1123 ◽  
Author(s):  
Yin ◽  
Wang ◽  
Yang
Keyword(s):  
Information Fusion ◽  
State Of The Art ◽  
Structural Information ◽  
Training Process ◽  
Image Dehazing ◽  
Edge Information ◽  
Global Context ◽  
Learning Module ◽  
Intermediate Layers ◽  
Context Features

Recently, convolutional neural network (CNN) based on the encoder-decoder structurehave been successfully applied to image dehazing. However, these CNN based dehazing methodshave two limitations: First, these dehazing models are large in size with enormous parameters, whichnot only consumes much GPU memory, but also is hard to train from scratch. Second, these models,which ignore the structural information at different resolutions of intermediate layers, cannot captureinformative texture and edge information for dehazing by stacking more layers. In this paper, wepropose a light-weight end-to-end network named the residual dense pyramid network (RDPN)to address the above problems. To exploit the structural information at different resolutions ofintermediate layers fully, a new residual dense pyramid (RDP) is proposed as a building block.By introducing a dense information fusion layer and the residual learning module, the RDP canmaximize the information flow and extract local features. Furthermore, the RDP further learnsthe structural information from intermediate layers via a multiscale pyramid fusion mechanism.To reduce the number of network parameters and to ease the training process, we use one RDPin the encoder and two RDPs in the decoder, following a multilevel pyramid pooling layer forincorporating global context features before estimating the final result. The extensive experimentalresults on a synthetic dataset and real-world images demonstrate that the new RDPN achievesfavourable performance compared with some state-of-the-art methods, e.g., the recent denselyconnected pyramid dehazing network, the all-in-one dehazing network, the enhanced pix2pixdehazing network, pixel-based alpha blending, artificial multi-exposure image fusions and thegenetic programming estimator, in terms of accuracy, run time and number of parameters. To bespecific, RDPN outperforms all of the above methods in terms of PSNR by at least 4.25 dB. The runtime of the proposed method is 0.021 s, and the number of parameters is 1,534,799, only 6% of thatused by the densely connected pyramid dehazing network.

Structural Reforms, Growth, and Inequality

2018 ◽  
Author(s):  
Nauro F. Campos ◽  
Paul De Grauwe ◽  
Yuemei Ji
Keyword(s):  
Economic Growth ◽  
Income Inequality ◽  
State Of The Art ◽  
Negative Impact ◽  
Future Research ◽  
Structural Reforms ◽  
Econometric Evidence ◽  
The Relationship ◽  
Critical Overview ◽  
Theoretical Developments

This chapter provides a critical overview of the state of the art in the economics literature on structural reforms. It takes stock of theoretical developments, measurement efforts, and of the econometric evidence. We start with a simple theoretical framework for the relationship between structural reforms, economic growth, and income inequality. We argue that whether structural reforms have a positive or negative impact depends on various factors. The type of reform, timing, sequence, and political constraints play crucial roles in determining the effectiveness of reforms on economic growth and income inequality. We conclude by proposing a 7-point agenda for future research.

Gender, Gender Equality, and Corruption

2021 ◽  
pp. 558-579
Author(s):  
Amy C. Alexander
Keyword(s):  
Gender Equality ◽  
State Of The Art ◽  
Critical Assessment ◽  
Self Determination ◽  
Future Research ◽  
Gender Role Socialization ◽  
Role Socialization ◽  
Theoretical Assumptions ◽  
Societal Level ◽  
The Relationship

This chapter covers the state of the art in theory and evidence on the relationship between gender, gender equality, and corruption. Starting with the theoretical assumptions that link individuals’ gender to the likelihood to engage in corruption, the chapter covers the four mechanisms proposed throughout the literature for expecting women to engage less: gender role socialization, power marginalization, the greater importance of an effective state for women’s self-determination, and the tendency to hold women to higher standards. From here, the chapter reviews additional societal-level theories on gender equality and corruption: 1) theory assuming that gender equality lowers corruption by empowering women, promoting women’s interests and generating norms of impartiality; and, 2) theory assuming that lower corruption increases gender equality. The chapter then reviews the evidence in support of the various theories and concludes with a critical assessment that identifies gaps and suggests future research.

Symptoms of Alcohol Dependence Predict Suicide Ideation Among Alaskan Undergraduates

Crisis ◽  
2016 ◽  
Vol 37 (3) ◽  
pp. 232-235 ◽  
Author(s):  
Christopher R. DeCou ◽  
Monica C. Skewes
Keyword(s):  
Depressive Symptoms ◽  
Alcohol Consumption ◽  
Alcohol Dependence ◽  
Suicide Ideation ◽  
Alcohol Problems ◽  
Future Research ◽  
Causal Mechanism ◽  
Students At Risk ◽  
The Relationship ◽  
Alcohol Related Problems

Abstract. Background: Previous research has demonstrated an association between alcohol-related problems and suicidal ideation (SI). Aims: The present study evaluated, simultaneously, alcohol consequences and symptoms of alcohol dependence as predictors of SI after adjusting for depressive symptoms and alcohol consumption. Method: A sample of 298 Alaskan undergraduates completed survey measures, including the Young Adult Alcohol Consequences Questionnaire, the Short Alcohol Dependence Data Questionnaire, and the Beck Depression Inventory – II. The association between alcohol problems and SI status was evaluated using sequential logistic regression. Results: Symptoms of alcohol dependence (OR = 1.88, p < .05), but not alcohol-related consequences (OR = 1.01, p = .95), emerged as an independent predictor of SI status above and beyond depressive symptoms (OR = 2.39, p < .001) and alcohol consumption (OR = 1.08, p = .39). Conclusion: Alcohol dependence symptoms represented a unique risk for SI relative to alcohol-related consequences and alcohol consumption. Future research should examine the causal mechanism behind the relationship between alcohol dependence and suicidality among university students. Assessing the presence of dependence symptoms may improve the accuracy of identifying students at risk of SI.

The Relationship Between Interoception and Metacognition

2016 ◽  
Vol 30 (2) ◽  
pp. 76-86 ◽  
Author(s):  
Judith Meessen ◽  
Verena Mainz ◽  
Siegfried Gauggel ◽  
Eftychia Volz-Sidiropoulou ◽  
Stefan Sütterlin ◽  
...  
Keyword(s):  
Memory Performance ◽  
Memory Task ◽  
Demographic Characteristics ◽  
Metacognitive Awareness ◽  
Interoceptive Awareness ◽  
Future Research ◽  
Heartbeat Perception ◽  
Interoceptive Accuracy ◽  
The Relationship

Abstract. Recently, Garfinkel and Critchley (2013) proposed to distinguish between three facets of interoception: interoceptive sensibility, interoceptive accuracy, and interoceptive awareness. This pilot study investigated how these facets interrelate to each other and whether interoceptive awareness is related to the metacognitive awareness of memory performance. A sample of 24 healthy students completed a heartbeat perception task (HPT) and a memory task. Judgments of confidence were requested for each task. Participants filled in questionnaires assessing interoceptive sensibility, depression, anxiety, and socio-demographic characteristics. The three facets of interoception were found to be uncorrelated and interoceptive awareness was not related to metacognitive awareness of memory performance. Whereas memory performance was significantly related to metamemory awareness, interoceptive accuracy (HPT) and interoceptive awareness were not correlated. Results suggest that future research on interoception should assess all facets of interoception in order to capture the multifaceted quality of the construct.

Sign in / Sign up

Export Citation Format

Share Document