音楽を評論する文書に書かれている内容やその書き方に対する詳細な分析は、その産業的あるいは学術的な発展の可能性にもかかわらず、まだ十分になされているとは言えない。本研究では、音楽評論文書の各文をその内容に従って計算機で自動的に分類するタスクに取り組んだ。また、このために用いる分類スキームの策定、およびそれに基づいてアノテーションを行ったコーパスの構築も行った。評論文書の各文は、楽曲の背景を述べる部分や、奏者の来歴を記す部分、演奏の特徴を描写する部分、あるいは筆者が演奏から受けた印象を表現する部分、などから構成されている。このような区分を自動的に施せる分類器を作成するために、まず人手によって明確な区分を行えるようなアノテーションスキームの設計を行った。このスキームに基づいて、音楽評論雑誌やウェブサイトから収集した評論文書データに対し人手でアノテーションを付与し、機械学習分類器の訓練および評価に用いるデータセットを構築した。これらの結果について、アノテータ間のアノテーション一致度および分類器の精度（F値）による評価を行った。

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The social network model has been regarded as a promising mechanism to defend against Sybil attack. This model assumes that honest peers and Sybil peers are connected by only a small number of attack edges. Detection of the attack edges plays a key role in restraining the power of Sybil peers. In this paper, an attack-resisting, distributed algorithm, named Random walk and Social network model-based clustering (RSC), is proposed to detect the attack edges. In RSC, peers disseminate random walk packets to each other. For each edge, the number of times that the packets pass this edge reflects the betweenness of this edge. RSC observes that the betweennesses of attack edges are higher than those of the non-attack edges. In this way, the attack edges can be identified. To show the effectiveness of RSC, RSC is integrated into an existing social network model-based algorithm called SOHL. The results of simulations with real world social network datasets show that RSC remarkably improves the performance of SOHL.

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A framework is established for evaluating the adaptability of rural households to tourism disturbance in the suburbs of a metropolis, based on the theory of the social-ecological system with tourism as the system disturbance. Two traditional villages in Beijing suburbs are selected as study cases and compared in terms of the development stage of tourism and the phases and approaches of adaption by rural households to tourism disturbance. Stepwise regression and grey relational analysis are applied to investigate the factors influencing the functionality and stability of the rural social-ecological system.

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Most travelers take photographs when they encounter impressive scenes. One of the tourism areas that has recently been receiving a great amount of attention is “photogenic tourism.” Photogenic travelers find interesting travel photographs on Social Networking Services (SNS) and then decide to go traveling. They also take many photographs while traveling and post them on SNS. Photogenic travelers seem to have a desire to express themselves, confirm their identity, and become aware of new aspects of themselves through a series of photogenic behaviors. The purpose of this study was to assess to what extent university students engage in photogenic tourism. Additionally, this study aimed to verify the following hypotheses: [Hypothesis 1] Looking back at photographs taken during travel elicits a sense of identity and helps discover new aspects of oneself and [Hypothesis 2] Those who frequently look at travel photographs before traveling, take photographs during travel, and post them on SNS confirm their identity and become more aware of new aspects of themselves. The survey was conducted among 189 university students in May 2018. The results demonstrate that for about half the participants, interesting travel photographs on SNS helped them decide to travel. Photogenic tourism seems to be popular among younger generations. Hypothesis 1 and Hypothesis 2 were supported by the results of this study.

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In Japan, many local governments are currently investing more effort into promoting inbound tourism. Many studies have been conducted to examine destination image in Japan. However, few studies investigate the differences in point of view between Japanese tourists and foreign tourists toward particular tourist attractions. Depending upon the tourist’s country of origin, there are variances in preferences or impressions of such locations. In addition, tourism promoters have their own ideas about which tourist attractions they want to recommend in their cities or towns. This study investigates the differences in destination image of a particular tourist attraction held by Japanese tourists and foreign tourists using a data mining approach toward analyzing the text data from reviews posted on TripAdvisor. Moreover, the information in the official sightseeing websites was analyzed using text mining with respect to Japanese and English text data in order to compare the results of Japanese and foreign tourists’ destination images of a particular tourist attraction. It was found that different destination images arose from one tourist attraction between Japanese and English texts. In addition, there were some sightseeing events that were not in the destination images of tourists , which can consider to be a recommendation by local promoters.

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本研究は、旅行口コミサイトに投稿された白川郷に関する日本人および外国人のeWOM（電子口コミ）をテキストマイニングにより比較解析し、観光行動分析におけるテキストマイニングの有用性を検討した。潜在的ディリクレ配分法によってクラスタリングした日本語と英語のeWOMを比較したところ、食事、散策や見学、写真撮影など、集落内の観光行動に関する複数のトピックで双方の内容に一定の共通性がみられた一方、世界遺産に関する双方のトピックには、大きな違いがみられた。日本語版に外国人観光客の急増に対するネガティブな反応が現れたのに対し、英語版の特徴語からは、対象地がユニークな民俗文化を愉しむ場所として消費されている様子が読み取れた。また、双方が利用可能な白川郷までの移動手段の多寡を反映して、交通手段に関するトピックでも、双方に違いが現れた。出発地で層化した共起ネットワーク分析でも、既存のインタビュー調査の結果を裏づける知見が得られ、定性的な調査で得られた知見を補強する手段としての有効性も示された。

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Urban freight movement is the lifeline for any city around the world. Freight trips in the city are basically for two purposes, primary trips catering to the needs of local population which remains more of less constant for a given population and secondary trips produced by the industrial activities carried out in the city, which are dependent of the nature and size of the industry. Decentralized nature of industry is bound to generate more freight trips as compared to an integrated industry with its components under a single roof. In the present study the impact of decentralized small scale industry induced freight trips on the overall traffic flows is studied. Surat city with predominant presence of textile industry is taken as a case study. The study brings to notice the extent of impact the regular traffic, useful for transport and urban planners to device curbing strategies.

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We propose a method of collective sentiment classification that assumes dependencies among labels of an input set of reviews. The key observation behind our method is that the distribution of polarity labels over reviews written by each user or written on each product is often skewed in the real world; intolerant users tend to report complaints while popular products are likely to receive praise. We encode these characteristics of users and products (referred to as user leniency and product popularity) by introducing global features in supervised learning. To resolve dependencies among labels of a given set of reviews, we explore two approximated decoding algorithms, “easiest-first decoding” and “two-stage decoding.” Experimental results on real-world datasets with user and/or product information confirm that our method contributed greatly to classification accuracy.

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第39回　日本エネルギー学会関西支部セミナー

第60回石炭科学会議 開催案内

第17回　微粒化セミナー

東北支部　2023年度講演会・見学会

新エネルギー・水素部会 第６回 新エネルギー・水素部会　シンポジウム 洋上での再生可能エネルギー発電の最前線

第11回アジアバイオマス科学会議（開催地：秋田）開催案内

第19回バイオマス科学会議開催案内

関西支部 「第68回研究発表会」発表募集

学生のための国際会議発表支援募集（2023年10月）

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日本エネルギー学会誌論文特集「重質油」論文募集のご案内

日本エネルギー学会誌論文特集「生活のエネルギー」論文募集のご案内

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創立100周年記念式典/第31回日本エネルギー学会大会　開催案内/第31回日本エネルギー学会大会　プログラム/北海道支部 学会100周年記念講演会及び施設見学会/令和4年度「バイオマス夏の学校」開催のお知らせ/第5回 新エネルギー・水素部会　シンポジウム/第59回石炭科学会議/天然ガス部会講演会開催案内/第10回アジアバイオマス科学会議（開催地：タイ）開催案内/第18 回バイオマス科学会議/関西支部「第67回研究発表会」発表募集/ほか

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