KSII Transactions on Internet and Information Systems (TIIS)
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v.16
no.11
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pp.3507-3522
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2022
Model pruning methods have attracted huge attention owing to the increasing demand of deploying models on low-resource devices recently. Most existing methods use the weight norm of filters to represent their importance, and discard the ones with small value directly to achieve the pruning target, which ignores the contribution of the small norm filters. This is not only results in filter contribution waste, but also gives comparable performance to training with the random initialized weights [1]. In this paper, we point out that the small norm filters can harm the performance of the pruned model greatly, if they are discarded directly. Therefore, we propose a novel filter contribution recycle (FCR) method for structured model pruning to resolve the fore-mentioned problem. FCR collects and reassembles contribution from the small norm filters to obtain a mixed contribution collector, and then assigns the reassembled contribution to other filters with higher probability to be preserved. To achieve the target FLOPs, FCR also adopts a weight decay strategy for the small norm filters. To explore the effectiveness of our approach, extensive experiments are conducted on ImageNet2012 and CIFAR-10 datasets, and superior results are reported when comparing with other methods under the same or even more FLOPs reduction. In addition, our method is flexible to be combined with other different pruning criterions.
This paper presents a new loss allocation scheme using power contribution method Power contribution is to find how much power at each generating/1oad bus is contributed to individual load/generating bus. In this paper power contribution is calculated using fundamental circuit theory. In numerical simulation, an illustrative example applying the proposed scheme to 6-bus test system is shown.
Journal of Korean Academy of Nursing Administration
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v.17
no.2
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pp.168-179
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2011
Purpose: The purpose of this study was to identify level of recognition of the importance, satisfaction and contribution of APNs' role by physicians, nurses, and advanced practice nurses. Method: Perceived importance and satisfaction were measured with a 23-item questionnaire on APN role with 5 subcategories. APNs' contribution was investigated using a 13-item outcome questionnaire developed by the researchers. Between August 15 and October 31, 2009, the researchers collected data from 68 physicians, 265 nurses, and 23 APNs all working in a single tertiary hospital. Data were analyzed using descriptive statistics, Kruskal-Wallis Test with Bonferroni's Correction and scatter plot. Result: The importance (3.24~3.39, 4 point scale), satisfaction (3.02~3.13, 4 point scale), and contribution of APNs' role (3.39~4.12, 5 point scale) were well recognized by the health care professionals. All the three health care professional groups rated APNs' contribution high in medical service management, continuity of care, patient accessibility, improvement in patient satisfaction, and patient and family education. 'Importance-Satisfaction Analysis' showed that patient data management by APNs needed greater effort. Conclusions: The findings show that the importance, satisfaction, contribution of APNs' role are recognized, and indicate a need for further development of APNs' role through efforts to overcome the gaps identified through this research.
Kim, Solhee;Han, Seunghyun;Kang, Seong-Soo;Suh, Kyo
Journal of The Korean Society of Agricultural Engineers
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v.64
no.5
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pp.41-51
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2022
Carbon neutrality is emerging as a new paradigm for the international society by transiting from climate change to climate risk. This study proposes evaluation methods for the carbon reduction contribution of climate-related national R&D projects in order to introduce a green budget system in the agricultural sector. We considered the domestic and foreign green budget systems and classified national R&D projects into positive, negative, and neutral from the perspective of carbon reduction. The results of this study propose three methods to estimate the monetary costs and carbon benefits by adopting the framework for the economic evaluation of national R&D projects conducted by the Rural Development Administration. These methods support to evaluate the potential contribution to carbon reduction of national R&D projects in the agricultural sector. Finally, the proposed methods were tested and verified for the efficiency and validity of evaluating carbon reduction contribution. These evaluation methods of the carbon reduction contribution can be used as a basic methodology for the pre-budget calculations of national R&D projects and the contribution for the greenhouse gas reduction budget.
KSII Transactions on Internet and Information Systems (TIIS)
/
v.15
no.7
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pp.2339-2355
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2021
In this paper, a joint probabilistic data association algorithm based on loss function (LJPDA) is proposed so that the computation load and accuracy of the multi-target tracking algorithm can be guaranteed simultaneously. Firstly, data association is divided in to three cases based on the relationship among validation gates and the number of measurements in the overlapping area for validation gates. Also the contribution coefficient is employed for evaluating the contribution of a measurement to a target, and the loss function, which reflects the cost of the new proposed data association algorithm, is defined. Moreover, the equation set of optimal contribution coefficient is given by minimizing the loss function, and the optimal contribution coefficient can be attained by using the Newton-Raphson method. In this way, the weighted value of each target can be achieved, and the data association among measurements and tracks can be realized. Finally, we compare performances of LJPDA proposed and joint probabilistic data association (JPDA) algorithm via numerical simulations, and much attention is paid on real-time performance and estimation error. Theoretical analysis and experimental results reveal that the LJPDA algorithm proposed exhibits small estimation error and low computation complexity.
Objectives : We analyzed the changes from 1996 to 2002 in distributive equity of the contribution burden in the Korean National Health Insurance. Methods : The study subjects were a total of 8,923 employee households and a total of 7,296 self-employed households over the period from 1996 to 2002. Those were the households meeting the two criteria as completing each annual survey and having no change in the job of head of the household during that period from the raw data of the Household Income and Expenditure Survey annually conducted by the Korean National Statistical Office. The unit of analysis was a household, and this was the standard for assessing the contribution that is now applied on a monthly basis. Deciles Distribution Ratio, Contribution Concentration Curve and Contribution Concentration Index were estimated as the index of inequality. Multiple regression analysis was conducted to compare the annual ability-to-pay elasticity of the contribution to the reference year of 1996 for three groups (all households, the employee households, and the self-employed households). Results : For the index of inequality, the distributive equity of contribution was improved in all three groups. In particular, the employee group experienced a substantial improvement. Using multiple regression analysis, the ability-to-pay elasticity of the contribution in the employee group significantly increased ($\beta$=0.232, p<0.0001) in the year 2002 as compared to the reference year of 1996. The elasticity in the self-employed group also significantly increased ($\beta$=0.186, p<0.05), although its change was smaller than that in the employee group. Conclusions : The employee group had a greater improvement for the distributive equity of the contribution burden than the self-employed group. Within the observation period, there were two important integration reforms: one was the integration of 227 self-employed societies in 1998 and the other was the integration of 139 employee societies in 2000. We expected that the equity of the contribution burden would be improved for the self-employed group since the integration reform of 1998. However, it was not improved for the self-employed group until the year 2000. This result suggests that capturing exactly the beneficiaries' ability-to-pay such as income is the precedent for distributive equity of the contribution burden, although a more sophisticated imposition standard of contribution is needed.
A challenge in fostering virtual communities is the continuous supply of knowledge, namely members' willingness to contribute knowledge to their communities. Previous research argues that giving away knowledge eventually causes the possessors of that knowledge to lose their unique value to others, benefiting all except the contributor. Furthermore, communication within virtual communities involves a large number of participants with different social backgrounds and perspectives. The establishment of mutual understanding to comprehend conversations and foster knowledge contribution in virtual communities is inevitably more difficult than face-to-face communication in a small group. In spite of these arguments, evidence suggests that individuals in virtual communities do engage in social behaviors such as knowledge contribution. It is important to understand why individuals provide their valuable knowledge to other community members without a guarantee of returns. In virtual communities, knowledge is inherently rooted in individual members' experiences and expertise. This personal nature of knowledge requires social interactions between virtual community members for knowledge transfer. This study employs the social capital theory in order to account for interpersonal relationship factors and identity theory for individual and group factors that may affect knowledge contribution. First, social capital is the relationship capital which is embedded within the relationships among the participants in a network and available for use when it is needed. Social capital is a productive resource, facilitating individuals' actions for attainment. Nahapiet and Ghoshal (1997) identify three dimensions of social capital and explain theoretically how these dimensions affect the exchange of knowledge. Thus, social capital would be relevant to knowledge contribution in virtual communities. Second, existing research has addressed the importance of identity in facilitating knowledge contribution in a virtual context. Identity in virtual communities has been described as playing a vital role in the establishment of personal reputations and in the recognition of others. For instance, reputation systems that rate participants in terms of the quality of their contributions provide a readily available inventory of experts to knowledge seekers. Despite the growing interest in identities, however, there is little empirical research about how identities in the communities influence knowledge contribution. Therefore, the goal of this study is to better understand knowledge contribution by examining the roles of social capital and identity in virtual communities. Based on a theoretical framework of social capital and identity theory, we develop and test a theoretical model and evaluate our hypotheses. Specifically, we propose three variables such as cohesiveness, reciprocity, and commitment, referring to the social capital theory, as antecedents of knowledge contribution in virtual communities. We further posit that members with a strong identity (self-presentation and group identification) contribute more knowledge to virtual communities. We conducted a field study in order to validate our research model. We collected data from 192 members of virtual communities and used the PLS method to analyse the data. The tests of the measurement model confirm that our data set has appropriate discriminant and convergent validity. The results of testing the structural model show that cohesion, reciprocity, and self-presentation significantly influence knowledge contribution, while commitment and group identification do not significantly influence knowledge contribution. Our findings on cohesion and reciprocity are consistent with the previous literature. Contrary to our expectations, commitment did not significantly affect knowledge contribution in virtual communities. This result may be due to the fact that knowledge contribution was voluntary in the virtual communities in our sample. Another plausible explanation for this result may be the self-selection bias for the survey respondents, who are more likely to contribute their knowledge to virtual communities. The relationship between self-presentation and knowledge contribution was found to be significant in virtual communities, supporting the results of prior literature. Group identification did not significantly affect knowledge contribution in this study, inconsistent with the wealth of research that identifies group identification as an important factor for knowledge sharing. This conflicting result calls for future research that examines the role of group identification in knowledge contribution in virtual communities. This study makes a contribution to theory development in the area of knowledge management in general and virtual communities in particular. For practice, the results of this study identify the circumstances under which individual factors would be effective for motivating knowledge contribution to virtual communities.
Journal of Information Technology Applications and Management
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v.28
no.6
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pp.117-132
/
2021
Based on the core value of the Q&A community, the contribution of knowledge and information has a great impact on users' community evaluation. As a small social group, the relationships and interactions among community members are quickly formed through information technology. As such, the cognitive evaluation of the relationship between community members will have an impact on the intention of information contribution. This research builds on the previous research based on the social exchange theory and establishes a dual model of swift guanxi in examining the relationship between guanxi and continuous knowledge contribution. In the current study, 305 survey questionnaires were used and 249 valid questionnaires were used for analysis. The analysis results are as follows: First, information support has a positive impact on dedication-based swift guanxi. While hypothesis between information support and constraint-based swift guanxi was not be supported. Second, emotional support has a positive impact on the formation of swift guanxi from a dual perspective. Third, the swift guanxi from the dual perspective has a positive impact on the intention of continuous knowledge contribution. Finally, although personal involvement has an adjustment effect, it is a downward adjustment effect, hypotheses are not supported. The current study offers theoretical and practical implications in field of knowledge management, specifically knowledge contribution in the virtual community.
Jie Ma;Xu-Yun Hua;Mou-Xiong Zheng;Jia-Jia Wu;Bei-Bei Huo;Xiang-Xin Xing;Xin Gao;Han Zhang;Jian-Guang Xu
Korean Journal of Radiology
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v.23
no.10
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pp.986-997
/
2022
Objective: Whether metabolic redistribution occurs in patients with white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) is unknown. This study aimed 1) to propose a measure of the brain metabolic network for an individual patient and preliminarily apply it to identify impaired metabolic networks in patients with WMHs, and 2) to explore the clinical and imaging features of metabolic redistribution in patients with WMHs. Materials and Methods: This study included 50 patients with WMHs and 70 healthy controls (HCs) who underwent 18F-fluorodeoxyglucose-positron emission tomography/MRI. Various global property parameters according to graph theory and an individual parameter of brain metabolic network called "individual contribution index" were obtained. Parameter values were compared between the WMH and HC groups. The performance of the parameters in discriminating between the two groups was assessed using the area under the receiver operating characteristic curve (AUC). The correlation between the individual contribution index and Fazekas score was assessed, and the interaction between age and individual contribution index was determined. A generalized linear model was fitted with the individual contribution index as the dependent variable and the mean standardized uptake value (SUVmean) of nodes in the whole-brain network or seven classic functional networks as independent variables to determine their association. Results: The means ± standard deviations of the individual contribution index were (0.697 ± 10.9) × 10-3 and (0.0967 ± 0.0545) × 10-3 in the WMH and HC groups, respectively (p < 0.001). The AUC of the individual contribution index was 0.864 (95% confidence interval, 0.785-0.943). A positive correlation was identified between the individual contribution index and the Fazekas scores in patients with WMHs (r = 0.57, p < 0.001). Age and individual contribution index demonstrated a significant interaction effect on the Fazekas score. A significant direct association was observed between the individual contribution index and the SUVmean of the limbic network (p < 0.001). Conclusion: The individual contribution index may demonstrate the redistribution of the brain metabolic network in patients with WMHs.
This study conducted analyses on biogenic volatile organic compounds (BVOC) emission sources contributing to urban ozone ($O_3$) concentration in Osaka Prefecture, Japan in summer 2010 by using the Weather Research and Forecasting model (WRF) version 3.5.1 and the Community Multiscale Air Quality model (CMAQ) version 5.0.1. This prefecture is characterized by highly urbanized area with small forest area. The contributions of source regions surrounding Osaka were estimated by comparing the baseline case and zero-out cases for BVOC emissions from each source region. The zero-out emission runs showed that the BVOC emissions substantially contributed to urban $O_3$ concentration in Osaka (10.3 ppb: 15.9% of mean daily maximum 1-h $O_3$ concentration) with day-by-day variations of contributing source regions, which were qualitatively explained by backward trajectory analyses. Although $O_3$ concentrations were especially high on 23 July and 2 August 2010, the contribution of BVOC on 23 July (35.4 ppb: 25.6% of daily maximum $O_3$) was much larger than that on 2 August (20.9 ppb: 14.2% of daily maximum $O_3$). To investigate this difference, additional zero-out cases for anthropogenic VOC (AVOC) emissions from Osaka and for VOC emissions on the target days were performed. On 23 July, the urban $O_3$ concentration in Osaka was dominantly increased by the transport from the northwestern region outside Osaka with large contribution of $O_3$ that was produced through BVOC reactions by the day before and was retained over the nocturnal boundary layer. On 2 August, the concentration was dominantly increased by the local photochemical production inside Osaka under weak wind condition with the particularly large contribution of AVOC emitted from Osaka on the day.
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