The Irony of Choice

We are having the inevitable late night conversation. You talk about your eventual wedding, your marriage to the person you love, the timeline you’ve created for yourself, and your plans for what our future children will do together. I clarify that I don’t want to have children, but you can’t seem to understand that decision. You question how happy, satisfied, or fulfilled my life will be without children, the maternal instincts I’m supposed to be feeling, and my desire to have something to care for and love. You’re convinced that I will recognize how empty my life will be sans kids and that I will change my mind about motherhood. I’m confused: why do you trust my judgment about everything else, but my decision to (or not to) give birth and raise children is questionable? [excerpt

Vietnamese EFL learners’ perspectives on online extensive reading during emergency remote L2 teaching

Previous research has shown a range of benefits of extensive reading for second or foreign language (L2) learning, as well as learners’ positive attitudes towards extensive reading. However, during emergency remote teaching around the globe as a consequence of the Covid-19 pandemic, where all L2 classes have been moved online, little research has investigated online extensive reading as well as learners’ perspectives on this activity. Therefore, the present study was conducted to investigate Vietnamese EFL learners’ perspectives on online extensive reading during emergency remote L2 teaching amidst the Covid-19 pandemic. Eighty-seven Vietnamese EFL learners at a local university participated in the study. They were involved in one online extensive reading over 12 weeks. Data were collected through semi-structured interviews with the participants. The results showed that all the learners had positive attitudes towards online extensive reading during emergency remote L2 teaching. Learners reported enjoying the variety of topics and genres found in online extensive reading, the suitability of the texts for their L2 proficiency, the usefulness of the program for enhancing their L2 competence as well as general knowledge, along with the convenience that the program offers. Learners also suggested several improvements in the website interface and the addition of more topics, genres, and quizzes

情報検索における意味的ギャップの解消 : トピックモデルを用いた先進的画像探索

Tohoku University徳山豪課

Mobile Tour Assistant for Malaysia

Malaysia's tourism industry has seen a rapid growth rate for the past years, and played a significant role in the development of the country's economy. 2007 is a special year for Malaysian tourism since it is called the "Visit Malaysia" year in celebration of 50 years of Independence. Information Technology has made remarkable contributions to the growth of tourism industry in Malaysia. Its efforts to promote tourism range from websites providing information to systems to service tourists. However, while countries with well-developed tourism industry like France and Hong Kong have developed comprehensive tour assistant packages for tourists, Malaysia is yet to do so. Thus, a comprehensive mobile tour package is needed for Malaysia. The objective of the project is to develop a well-designed tour assistant running on PDAs which makes use of current trends in mobile applications such as the adoption of AI technique in scheduling. Due to time and resource constraints, the project focuses on areas within and around Kuala Lumpur and targets on short-stay and transit tourists. Going through a thorough literature review and following the waterfall methodology, the project has successfully developed a full package of mobile tour assistant including the back end and front end. The project also makes contribution to creatively applying Genetic Algorithm, an AI technique in plan auto-scheduling. The author hopes that the package will be of high commercial value and contribute significantly to boosting Malaysia's tourism

Neural Computing for Event Log Quality Improvement

Department of Management EngineeringAn event log is a vital part used for process mining such as process discovery, conformance checking or enhancement. Like any other data, the initial event logs can be too coarse resulting in severe data mining mistakes. Traditional statistical reconstruction methods work poorly with event logs, because of the complex interrelations among attributes, events and cases. As such, machine learning approaches appear more suitable for reconstructing or repairing event logs. However, there is very limited work on exploiting neural networks to do this task. This thesis focuses on two issues that may arise in the coarse event logs, incorrect attribute values and missing attribute values. We are interested in exploring the application of different kinds of autoencoders on the task of reconstructing event logs since this architecture suits the problem of unsupervised learning, such as the ones we are considering. When repairing an event log, in fact, one cannot assume that a training set with true labels is available for model training. We also propose the techniques for preprocessing and training the event logs data. In order to provide an insight on how feasible and applicable our work is, we have carried out experiments using real-life datasets. Regarding the first issue, we train autoencoders under purely unsupervised manner to deal with the problem of anomaly detection without using any prior knowledge of the domain. We focus on developing algorithms that can capture the general pattern and sequence aspect of the data. In order to solve the second issue, we develop models that should not only learn the representation and underlying true distribution of the data but also be able to generate the realistic and reliable output that has the characteristic of the logs.ope