微細電子デバイス用高品質Ni/Ru薄膜形成を目指したホットワイヤーALDプロセスの開発

学位の種別: 課程博士審査委員会委員 : (主査)東京大学教授 霜垣 幸浩, 東京大学教授 寺嶋 和夫, 東京大学教授 光田 好孝, 東京大学准教授 長汐 晃輔, 東京大学准教授 杉山 正和University of Tokyo(東京大学

User behavior prediction via heterogeneous information preserving network embedding

© 2018 Elsevier B.V. User behavior prediction with low-dimensional vectors generated by user network embedding models has been verified to be efficient and reliable in real applications. However, most user network embedding models utilize homogeneous properties to represent users, such as attributes or user network structure. Though some works try to combine two kinds of properties, the existing works are still not enough to leverage the rich semantics of users. In this paper, we propose a novel heterogeneous information preserving user network embedding model, which is named HINE, for user behavior classification in user network. HINE applies attributes, user network connection, user network structure, and user behavior label information for user representation in user network embedding. The embedded vectors considering these multi-type properties of users contribute to better user behavior classification performances. Experiments verified the superior performances of the proposed approach on real-world complex user network dataset

Socialized healthcare service recommendation using deep learning

© 2018, The Natural Computing Applications Forum. Socialized recommender system recommends reliable healthcare services for users. Ratings are predicted on the healthcare services by merging recommendations given by users who has social relations with the active users. However, existing works did not consider the influence of distrust between users. They recommend items only based on the trust relations between users. We therefore propose a novel deep learning-based socialized healthcare service recommender model, which recommends healthcare services with recommendations given by recommenders with both trust relations and distrust relations with the active users. The influences of recommenders, considering both the node information and the structure information, are merged via the deep learning model. Experimental results show that the proposed model outperforms the existing works on prediction accuracy and prediction coverage simultaneously, even for cold start users or users with very sparse trust relations. It is also computational less expensive

Preparation of graphene/aligned carbon nanotube array composite films for thermal packaging applications

Vertically aligned carbon nanotube arrays (VACNTs) have been successfully achieved by CVD. The carbon nanotubes were almost triple-walled. Furthermore, the graphene/VACNT composite films have been prepared as thermal interface materials, using photolithographic and densification processes. Compared with pure epoxy resin, the longitudinal thermal conductivity of the composite films was obviously improved, which confirmed that VACNTs provided additional longitudinal heat transfer channels in the films. Furthermore, their longitudinal thermal conductivity was largely dependent on the distribution of VACNTs. The transversal thermal conductivity of the composite film with a pattern size of 300 mu m was about seven times higher than that of pure epoxy resin. This indicated that graphene provided additional horizontal heat transfer channels to achieve the enhancement of transversal thermal conductivity in composite films. (C) 2019 The Japan Society of Applied Physic

Maximum likelihood estimation-assisted ASVSF through state covariance-based 2D SLAM algorithm

The smooth variable structure filter (ASVSF) has been relatively considered as a new robust predictor-corrector method for estimating the state. In order to effectively utilize it, an SVSF requires the accurate system model, and exact prior knowledge includes both the process and measurement noise statistic. Unfortunately, the system model is always inaccurate because of some considerations avoided at the beginning. Moreover, the small addictive noises are partially known or even unknown. Of course, this limitation can degrade the performance of SVSF or also lead to divergence condition. For this reason, it is proposed through this paper an adaptive smooth variable structure filter (ASVSF) by conditioning the probability density function of a measurementto the unknown parameters at one iteration. This proposed method is assumed to accomplish the localization and direct point-based observation task of a wheeled mobile robot, TurtleBot2. Finally, by realistically simulating it and comparing to a conventional method, the proposed method has been showing a better accuracy and stability in term of root mean square error (RMSE) of the estimated map coordinate (EMC) and estimated path coordinate (EPC)

Human impacts on the cladoceran community of Jili Lake, arid NW China, over the past century

Deterioration of aquatic ecosystems, as a consequence of human-induced disturbances, is a critical global concern. To fully understand the responses of aquatic systems to anthropogenic impacts, it is crucial to assess long-term changes in lakes. The water quality of Jili Lake, a large water body in northwest China, has deteriorated recently, owing to the growing impacts of regional warming and human activities. Thus, Jili Lake was a prime candidate for evaluation of historical multi-stressor impacts. Meteorological data, historical documents, and assemblages of cladoceran microfossils in the sediments of Jili Lake were employed to investigate changes in the cladoceran community over the past century, and to evaluate the response of that aquatic community to human activities. From the 1920s to the 1950s, species richness of the cladoceran community was high, which reflected conditions of relatively low human impact. From the 1960s to 1970s, a sharp decrease in Bosmina longirostris, a planktonic cladoceran species, suggested a decrease in water level as a result of dam construction and intensified water exploitation. Since the 1980s, the water level in the lake has been restored, but increased fish farming and construction of a water storage facility caused salinisation and eutrophication of Jili Lake. Accordingly, the cladoceran community displayed distinct signs of a regime shift, with a gradual transition to dominance of B. longirostris and a sharp decrease in littoral species (e.g. Leydigia leydigi, L. acanthocercoides, Alona quadrangularis, Alona affinis). Our results suggest that human-induced disturbances were the main factor that drove changes in the cladoceran community since about the mid-20th century.Peer reviewe

Investigating Verticillium wilt occurrence in cotton and its risk management by the direct return of cotton plants infected with Verticillium dahliae to the field

Verticillium wilt is one of the most crucial diseases caused by Verticillium dahliae that threatens the cotton industry. Statistical results showed that the return of cotton plants infected with V. dahliae to the field might be an essential cause of the continuous aggravation of cotton Verticillium wilt. The correlation among the cotton plants infected with V. dahliae returning to the field, the occurrence of Verticillium wilt, and the number of microsclerotia in rhizosphere soil need further investigation. A potted experiment was carried out to explore the effects of the direct return of cotton plants infected with Verticillium dahliae to the field on the subsequent growth and Verticillium wilt occurrence in cotton. As a risk response plan, we investigated the feasibility of returning dung-sand (i.e., insect excreta) to the field, the dung-sand was from the larvae of Protaetia brevitarsis (Coleoptera: Cetoniidea) that were fed with the V. dahliae–infected cotton plants. The results demonstrated that the return of the entire cotton plants to the field presented a promotional effect on the growth and development of cotton, whereas the return of a single root stubble or cotton stalks had an inhibitive effect. The return of cotton stalks and root stubble infected with V. dahliae increased the risk and degree of Verticillium wilt occurrence. The disease index of Verticillium wilt occurrence in cotton was positively correlated with the number of microsclerotia in the rhizosphere soil. The disease index increased by 20.00%, and the number of soil microsclerotia increased by 8.37 fold in the treatment of returning root stubble infected with V. dahliae to the field. No Verticillium wilt microsclerotia were detected in the feed prepared from cotton stalks and root stubble fermented for more than 5 days or in the transformed dung-sand. There was no risk of inoculation with Verticillium wilt microsclerotia when the dung-sand was returned to the field. The indirect return of cotton plants infected with V. dahliae to the field by microorganism–insect systems is worthy of further exploration plan of the green prevention and control for Verticillium wilt and the sustainable development of the cotton industry

Effects of Musical Tempo on Musicians’ and Non-musicians’ Emotional Experience When Listening to Music

Tempo is an important musical element that affects human’s emotional processes when listening to music. However, it remains unclear how tempo and training affect individuals’ emotional experience of music. To explore the neural underpinnings of the effects of tempo on music-evoked emotion, music with fast, medium, and slow tempi were collected to compare differences in emotional responses using functional magnetic resonance imaging (fMRI) of neural activity between musicians and non-musicians. Behaviorally, musicians perceived higher valence in fast music than did non-musicians. The main effects of musicians and non-musicians and tempo were significant, and a near significant interaction between group and tempo was found. In the arousal dimension, the mean score of medium-tempo music was the highest among the three kinds; in the valence dimension, the mean scores decreased in order from fast music, medium music, to slow music. Functional analyses revealed that the neural activation of musicians was stronger than those of non-musicians in the left inferior parietal lobe (IPL). A comparison of tempi showed a stronger activation from fast music than slow music in the bilateral superior temporal gyrus (STG), which provided corresponding neural evidence for the highest valence reported by participants for fast music. Medium music showed stronger activation than slow music in the right Heschl’s gyrus (HG), right middle temporal gyrus (MTG), right posterior cingulate cortex (PCC), right precuneus, right IPL, and left STG. Importantly, this study confirmed and explained the connection between music tempo and emotional experiences, and their interaction with individuals’ musical training

Single-Trial EEG-fMRI Reveals the Generation Process of the Mismatch Negativity

Although research on the mismatch negativity (MMN) has been ongoing for 40 years, the generation process of the MMN remains largely unknown. In this study, we used a single-trial electro-encephalography (EEG)-functional magnetic resonance imaging (fMRI) coupling method which can analyze neural activity with both high temporal and high spatial resolution and thus assess the generation process of the MMN. We elicited the MMN with an auditory oddball paradigm while recording simultaneous EEG and fMRI. We divided the MMN into five equal-durational phases. Utilizing the single-trial variability of the MMN, we analyzed the neural generators of the five phases, thereby determining the spatiotemporal generation process of the MMN. We found two distinct bottom-up prediction error propagations: first from the auditory cortex to the motor areas and then from the auditory cortex to the inferior frontal gyrus (IFG). Our results support the regularity-violation hypothesis of MMN generation