• Korean Journal of Social Welfare Studies
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• v.49 no.2
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• pp.257-295
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• 2018

This study delineates how recipients access, understand, and make use of social welfare information in their life-worlds. Through this vivid illustration about recipients' information behaviors, this research aims to suggest that government-centred welfare informatization policy should be readjusted. South Korean government has made enormous efforts to deliver and share social welfare information and knowledge with recipients, by organizing IT eduction programmes, offering free computers, and opening welfare portals. However, despite of such endeavors, not a few recipients find difficulty in gaining, grasping, and using welfare information. In fact, welfare informatization programmes have so far been initiated by the governmental bureaucratic system, and the voice of recipients have hardly been reflected on the informatization policy. Starting from this problem, this study examines how low-income recipients perceive and accept social welfare information in their daily lives and reflects on social welfare information at their point. For this purpose, this research conducted in-depth interviews with 14 recipients and analyzed the data using a framework analysis method. Based on the results, it raises the need for the remodelling of current welfare informatization measures from the perspective of recipients rather than following the custom of the bureaucratic system.

• The Journal of the Acoustical Society of Korea
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• v.39 no.2
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• pp.120-130
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• 2020

This paper solves the problem in underdetermined convolutive mixture by improving the disadvantages of the multichannel nonnegative matrix factorization technique widely used in blind source separation. In conventional researches based on Spatial Covariance Matrix (SCM), each element composed of values such as power gain of single channel and correlation tends to degrade the quality of the separated sources due to high variance. In this paper, level and frequency normalization is performed to effectively cluster the estimated sources. Therefore, we propose a novel SCM and an effective distance function for cluster pairs. In this paper, the proposed SCM is used for the initialization of the spatial model and used for hierarchical agglomerative clustering in the bottom-up approach. The proposed algorithm was experimented using the 'Signal Separation Evaluation Campaign 2008 development dataset'. As a result, the improvement in most of the performance indicators was confirmed by utilizing the 'Blind Source Separation Eval toolbox', an objective source separation quality verification tool, and especially the performance superiority of the typical SDR of 1 dB to 3.5 dB was verified.