• Proceedings of the Korean Radioactive Waste Society Conference
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• 2017.05a
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• pp.309-310
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• 2017

• Advances in environmental research
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• v.5 no.4
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• pp.237-249
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• 2016

The management of municipal solid waste (MSW) is essential for every community; and, it is currently a major challenge in Nigeria. This paper provides an overview of the current MSW management trends in Nigeria and proposes new sustainable MSW management systems. Across Nigerian cities, MSW management is characterized by inefficient collection and transportation to disposal sites. Collection services do not reach some unplanned areas and slums due to poor street network. Even some planned areas are not reached by collection services. The informal sector contributes to waste collection, resource recovery and recycling; however, their activities are not recognized by the governments. Markets exist for recovered materials but more efforts need to be geared towards intensive recovery of materials and expansion of these markets. Despite the high proportion of putrescible matter in MSW, the only form of treatment commonly used currently is open burning for volume reduction. The high organic fraction presents a great opportunity for composting and anaerobic digestion. Ultimate disposal is currently done in open dumpsites. This needs to be upgraded to engineered landfills that are properly sited and adequately operated by well trained personnel. There is an emerging waste stream of concern, electronic-waste (e-waste), that requires urgent sustainable management as e-waste are currently co-disposed with other waste streams or burnt in the open posing detrimental health impacts.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.11a
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• pp.89-90
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• 2018

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.112-114
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• 2022

This paper proposes an E-Commerce service that supports large quantities of food waste sales generated by collective residences, including apartments, to consumers in urban areas, such as livestock farmers, through online transactions. Unlike general E-Commerce, the proposed service uses a smart food waste bin equipped with an IoT-based sensor and communication module to automatically collect the location information of each apartment and the amount of food waste to be displayed in a specialized E-Commerce platform. The key of this system is to provide information and sell it to consumers. The smart food waste bin periodically delivers its current capacity and location using a weight sensor, GPS sensor and LoRa communication module to a cloud-based database to be used in web or mobile applications. The proposed E-Commerce service is expected to help resolve the food waste disposal problem and revitalize the local economy by linking with a service that delivers food waste from each apartment to a nearby location where the buyer is located.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2010.10a
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• pp.277-278
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• 2010

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.11a
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• pp.119-120
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• 2018

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.11a
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• pp.444-445
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• 2018

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.11a
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• pp.91-92
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• 2018

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.11a
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• pp.93-94
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• 2018

• Biotechnology and Bioprocess Engineering:BBE
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• v.7 no.5
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• pp.268-274
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• 2002

Enzymatic hydrolysis of waste office paper was evaluated using three commercial cellulases, Acremonium cellulase, Meicelase, and Cellulosin T2. Varying the enzyme loading from 1 to 10% (w/w) conversion of waste office paper to reducing sugar was investigated. The conversion increased with the increase in the enzyme loading: in the case of enzyme loading of 10% (w/w), Acremonium cellulase yielded 79%conversion of waste office paper, which was 17% higher compared to Meicelase, 13% higher than that of Cellulosin T2. Empirical model for the conversion (%) of waste office paper to re-ducing sugar (x) was derived from experimental results as follow, x = $kE^{m}t^{(aE+b)}$ where k, m, a, and b de-note empirical constants. E indicates initial enzyme concentration.