著者
三宅 正男 石井 俊匡 山上 慶 平藤 哲司
出版者
一般社団法人 資源・素材学会
雑誌
Journal of MMIJ (ISSN:18816118)
巻号頁・発行日
vol.135, no.12, pp.109-115, 2019-12-31 (Released:2019-12-26)
参考文献数
20

Leaching of copper anode slime using hydrochloric acid (HCl) and hydrogen peroxide (H2O2) is performed to recover Au. It is imperative to reduce the amount of the costly oxidizing agent, H2O2, used in this leaching. In conventional conditions, the Se contained in the slime is oxidized and dissolved by the leachant as well as Au. If Au alone can be selectively leached, it should reduce the use of H2O2. The calculation of equilibrium potentials showed that when the concentration of HCl is high, it is possible for Au to be selectively leached, while the dissolution of Se is suppressed. The selective leaching of Au was demonstrated by experiments using 8 mol L-1 and 12 mol L-1 HCl solutions with various amounts of added H2O2. In the selective leaching, the increase in the leaching rate of Au with increasing amounts of H2O2 diminished after the leaching rate reached 80%. This may be because Au remained inside the Se particles, and the contact between Au and the leachant was physically inhibited by the Se layer encompassing the Au atoms. However, a leaching rate of Au of greater than 95% was achieved, even when the leaching rate of Se was less than 30%. From these results, it was confirmed that the use of H2O2 can be reduced by the selective leaching of Au compared to the cases in which all Se in the slime is dissolved.
著者
斉藤 裕樹 高山 翼 山上 慶 戸辺 義人 鉄谷 信二
雑誌
情報処理学会論文誌 (ISSN:18827764)
巻号頁・発行日
vol.55, no.2, pp.773-781, 2014-02-15

GPS機能を備えた携帯端末などによる位置情報取得技術の普及により,人々の訪れた場所どうしを結ぶ行動履歴を解析する研究が活発に行われている.経路情報の蓄積によって得られる行動履歴は,人々の興味と移動との関係を解析する手段として注目されている.一方,TwitterをはじめとするマイクロブログはテキストとともにGPSセンサによる位置情報を付与し,公開することが可能なサービスとして世界的に利用されている.本論文では,マイクロブログ上に蓄積された人々の行動履歴を基に利用者の行動とコンテキストを解析し確率過程モデルに適用させることで,将来の利用者の行動を予測する手法の提案を行う.また,マイクロブログの実データを用いた行動予測精度の評価実験から,単純統計を用いた従来手法より高い予測精度が得られることを確認した.The advance of GPS-enabled portable devices such as PDAs and smart phones facilitates people to record their location histories. Location trajectories imply human behaviors and preferences related for their interests. On the other hand, microblog services such as Twitter enable us to publish text messages (e.g., Tweets) and location-tags (e.g., Geo-tags) to subscribers. This paper proposes a schema for predicting user behavior by analyzing location trajectories and contexts by applying a stochastic model. And, we confirm the effectiveness of our schema through experiment using the actual data obtained from microblog service.