• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3790-3803
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• 2018

Content-based image retrieval is an approach used to query images based on their semantics. Semantic based retrieval has its application in all fields including medicine, space, computing etc. Semantically generated binary hash codes can improve content-based image retrieval. These semantic labels / binary hash codes can be generated from unlabeled data using convolutional autoencoders. Proposed approach uses semi-supervised deep hashing with semantic learning and binary code generation by minimizing the objective function. Convolutional autoencoders are basis to extract semantic features due to its property of image generation from low level semantic representations. These representations of images are more effective than simple feature extraction and can preserve better semantic information. Proposed activation and loss functions helped to minimize classification error and produce better hash codes. Most widely used datasets have been used for verification of this approach that outperforms the existing methods.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.19-24
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• 2018

Recently, people can create small content by themselves and it improved into a form that can be promoted. Also, as active small business owners increase, they produce the content for promotion by themselves without external professional help and they utilize it. This paper studies the method to make Mobile Apps, Mobile Web and homepage services available by automatically generating the mobile based mini content. The automated content creation system suggests the method that small business owners and groups can easily communicate with new people by bringing Single Page Application, hybrid mobile web app, N-Screen based content building, private cloud-based PaaS building technology, P2P network based file sharing and multimedia thread technologies together and creating the content.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.19-24
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• 2010

The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users have a tendency to build playlist for manage songs. However the manual selection of songs for creating playlist is a troublesome work. This paper proposes an auto playlist generation system considering user context of use and preferences. This system has two separated systems; 1) the mood and emotion classification system and 2) the music recommendation system. Firstly, users need to choose just one seed song for reflecting their context of use. Then system recommends candidate song list before the current song ends in order to fill up user playlist. User also can remove unsatisfied songs from the recommended song list to adapt the user preference model on the system for the next song list. The generated playlists show well defined mood and emotion of music and provide songs that the preference of the current user is reflected.

• Asian Journal of Atmospheric Environment
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• v.11 no.2
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• pp.122-130
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• 2017

The main purpose of the study was to clarify the properties of individual particles collected at each behavior space of a factory worker. The samplings of size-segregated ($PM_{2.1-1.1}$ and $PM_{4.7-3.3}$) indoor particles were conducted at three different behavior spaces of a factory worker who is engaged in an auto parts manufacturing plant (i.e., his home, his work place in factory, and his favorite restaurant). Elemental specification (i.e., relative elemental content and distribution in and/or on individual particles) was performed by a micro-PIXE system. Every element detected from the coarse particulate matters of home was classified into three groups, i.e., a group of high net-counts (Na, Al, and Si), a group of intermediate net-counts (Mg, S, Cl, K, and Ca), and a group of minor trace elements (P, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, and Pb). The results of EF for $PM_{4.7-3.3}$ in home indicated that several heavy metals were generated from the sources within the house itself. An exceptional feature shown in the individual particles in workplace is that Cr, Mn, and Co were clearly detected in both fine and coarse particles. Cluster analysis suggested that the individual coarse particles ($PM_{4.7-3.3}$) collected at the indoor of factory were chemically heterogeneous and they modified with sea-salt, mineral, and artificially derived elements. The principal components in individual coarse particles collected at restaurant were sea-salt and mineral without mixing with harmful trace elements like chromium and manganese. Compared to the indoor fine particles of home and restaurant, many elements, especially, Cl, Na, Cr, Mn, Pb, and Zn showed overwhelmingly high net-counts in those of factory.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.337-342
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• 2010

The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users are tend to build play-list for manage songs. However the manual selection of songs for creating play-list is bothersome task. This paper proposes an auto play-list recommendation system considering user's context of use and preference. This system has two separate systems: mood and emotion classification system and music recommendation system. Users need to choose just one seed song for reflection their context of use and preference. The system recommends songs before the current song ends in order to fill up user play-list. User also can remove unsatisfied songs from recommended song list to adapt user preferences of the system for the next recommendation precess. The generated play-lists show well defined mood and emotion of music and provide songs that user preferences are reflected.

• Journal of the Korea Organic Resources Recycling Association
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• v.8 no.4
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• pp.129-137
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• 2000

In this study, biological treatment process of MWWT(Municipal wet-waste Treatment) has been developed through a moduling of the containerized closed ATAD(Auto thermal aerobic digestion) system & closed vertical dynamic acerator, which were used for food waste and cattle manure, respectively. Though biological process has several advantages such as low concentrations of heavy metals and salts, proper and stable C/N ratio and constant reaction rate against the process treating two wastes separately, it has a obstacles of salt concentration and much usage of bulking agent such as wood chip. After rapid oxidation in the boxed tower reactor for 5 days, the content of sewage sludge would be reduced 65% on around, might be mixed with the food waste that had been treated in the static closed reactor during 6 days and put in the secondary static reactor for curing. During composting process, the odor contained in the gas generated from the reactor was removed by passing it through a biofilter as well as the leachate was treated in the wastewater treatment facility. Consequently, it seemed to be possible to compost sewage sludge at mild and stable operating condition and at low cost through the biological ATAD process resulting in the production of organic compost satisfying the specifications regulated by itself.