Hosei University
  • Tokyo, Japan
Recent publications
In football, players express their objections to referees’ decisions in the form of “protests” when they are not convinced that the referee’s judgment is correct. Previous studies have shown that protests have several disadvantages. Furthermore, since switching between offense and defense is important in football, moving quickly to the next play without protesting is important. Therefore, this study sought to identify factors associated with protests by football players. Specifically, interviews were conducted with university football players regarding the reasons that they would or would not protest against referees during football matches. Based on the interview results, items were created to measure protests against referees in football games and to measure factors expected to be related to such protests, and a questionnaire survey was conducted using these items. The results showed that players who felt that protests were costly, felt that they could cope well with unsatisfactory judgments made by referees, or who respected referees did not protest very often in various situations in football games.
Participatory organizational interventions offer an effective way to promote occupational safety and health. Despite an increasing number of studies, a common definition of participatory organizational interventions has yet to be established. Therefore, we aimed to form a definition using the following process. First, we developed a tentative draft definition of organizational interventions and participatory elements, based on the relevant literature. The tentative definition was revised in several rounds of an extensive discussion by the authors. This resulted in the draft definition. We asked 15 selected international experts in occupational safety and health to review and comment on the draft definition. We carefully reviewed their comments, and formulated our final proposed definition. To summarize the key points of the final version of the definition, organizational interventions are planned actions that primarily directly target working conditions with the aim of promoting and maintaining of the highest degree of physical, mental, and social well‐being of workers in all occupations. In addition, as participatory elements of organizational interventions in the final definition, ideally, all workers participate in every step of the intervention, while participating in part of the steps of the intervention in some cases. Furthermore, in principle, all workers participate in each step of intervention, while it is also acceptable that only elected representatives among workers participate in the intervention.
Escherichia coli K-12 possesses two versions of Trk/Ktr/HKT-type K⁺ transporters, TrkG and TrkH. The current paradigm is that TrkG and TrkH have largely identical characteristics, and little information is available regarding their functional differences. Here we show using cation uptake experiments with K⁺ transporter knockout mutants that TrkG and TrkH have distinct ion transport activities and physiological roles. K⁺-transport by TrkG required Na⁺, while TrkH-mediated K⁺ uptake was not affected by Na⁺. An aspartic acid located five residues away from a critical glycine in the third pore-forming region might be involved in regulation of Na⁺-dependent activation of TrkG. In addition, we found that TrkG but not TrkH had Na⁺ uptake activity. Our analysis of K⁺ transport mutants revealed that TrkH supported cell growth more than TrkG, however, TrkG was able to complement loss of TrkH-mediated K⁺ uptake in E. coli. Furthermore, we determined that transcription of trkG in E. coli was downregulated but not completely silenced by the xenogeneic silencing factor H-NS. Taken together, the transport function of TrkG is clearly distinct from that of TrkH, and TrkG seems to have been accepted by E. coli during evolution as a K⁺ uptake system that coexists with TrkH.
This study examined whether six dispositional psychological measures; Frequency of Flow Experience, Resilience, Self-Esteem, Self-Efficacy, Will for Meaningful Life, and Trait-Anxiety are associated with heart rate diurnal rhythm parameters. The associations of four physiological parameters—24-hour and 12-hour periodic component amplitudes, diurnal heart rate range amplitude, and autonomic switching rate—with the six dispositional psychological measures were analyzed. The physiological parameters were extracted using two different methods from heart rate data continuously recorded at one-minute intervals by a wrist device. Conventional cosinor and spline-based methods were used. The study was conducted on 20 healthy individuals aged 25–57 years. Single regression analysis showed a significant correlation of Frequency of Flow Experience, Resilience, and Will for Meaningful Life with heart rate rhythm parameters (p < 0.05), and a trend of significant correlation of Self-Esteem with heart rate rhythm parameters (p < 0.1). On the other hand, Self-Efficacy consistently showed a positive correlation, while the only negative psychological measure; Trait-Anxiety, showed a negative correlation with heart rate rhythm parameters, although statistical significance was not reached (p > 0.1). Principal component analysis extracted two orthogonal components with which multiple principal component regression yielded better R² (coefficient of determination) values than single regression for Frequency of Flow Experience (R² = 0.451, p < 0.05), Resilience (R² = 0.587, p < 0.05), Self-Esteem (R² = 0.494, p < 0.05), Will for Meaningful Life (R² = 0.364, p < 0.05), Self-Efficacy (R² = 0.322, p < 0.1), and Trait-Anxiety (R² = 0.241, p > 0.1). Based on these results, positive dispositional psychological measures were associated with physiological parameters representing long-term characteristics of autonomic nervous activity. The research outcome may be applied to develop a ubiquitous healthcare monitoring system that integrates both physiological bio-signals and psychological measures.
The increase of combination number according to the increase of variables is a serious problem in using section optimization for steel structures. Response Surface Method (RSM) which uses approximate functions made by sampling data was proofed as one of effective optimization methods. This paper shows features of the proposed method that combined with genetic algorithm by applying it to allowable stress design of a middle rise steel structure and changing the setting of RSM which are a response surface algorithm and a space filler algorithm. In addition, the feature of the optimized structures is analyzed by nonlinear dynamic response analysis.
Cyber-physical systems (CPS) offer integrated resolutions for various applications by combining computer and physical components and enabling individual machines to work together for much more excellent benefits. The ad hoc based CPS provides a promising architecture due to its decentralized nature and destructive-resistance. A growing number of information leakage events in CPSs and the following serious consequences have aroused ubiquitous concern about information security. In this paper, we combine physical layer security solutions and millimeter-wave (mmWave) techniques to safeguard the ad hoc network and investigate the reliability-security tradeoff by taking user demands for the network into account, where eavesdroppers attempt to intercept messages. For the secrecy enhancements, we adopt an artificial noise (AN) assisted transmission scheme, in which AN is employed to create non-cancellable interference to eavesdroppers. The reliability and security are correspondingly characterized by the connection outage probability and secrecy outage probability, and their analytical expressions of them are attained through theoretical analysis for the purpose of the tradeoff issue discussion. Our results reveal that secrecy performance in mmWave ad hoc networks gains significant improvement through the use of AN. It also shows that given total transmit power, there exists a tradeoff between reliability and security to achieve optimal outage performance.
The quality of the healthcare environment has become an essential factor for healthcare users to access quality services. Smart healthcare systems use the Internet of Medical Things (IoMT) devices to capture patients’ health data for treatment or diagnostic purposes. This sensitive collected patient data is shared between the different stakeholders across the network to provide quality services. Due to this, healthcare systems are vulnerable to confidentiality, integrity and privacy threats. In the COVID-19 scenario, when collaborative medical consultation is required, the quality assessment of the framework is essential to protect the privacy of doctors and patients. In this paper, a ring signature-based anonymous authentication and quality assessment scheme is designed for collaborative medical consultation environments for quality assessment and protection of the privacy of doctors and patients. This scheme also uses a new KMOV Cryptosystem to ensure the quality of the network and protect the system from different attacks that hamper data confidentiality.
This study aims to strengthen carbon nanotube (CNT)/Al composites, which were fabricated by a combination of spark plasma sintering (SPS) and repeated hot rolling techniques. Dry ball milling was conducted to uniformly disperse CNT in Al powders. The microstructures of the CNT/Al composites including dispersibility of CNT were observed using a scanning electron microscope (SEM) and transmission electron microscope (TEM). Ball milling treatments promoted to reduce the number of CNT aggregations and increase C concentrations in the CNT aggregations in the composites. Anisotropic tensile behavior was also investigated, which demonstrated that the post-SPS repeated hot rolling can highly enhance the tensile strength as well as deformability of the composites.
Although previous studies have examined the impact of long working hours on mental health in China, they have not addressed the initial value and reverse causality issues. To bridge this gap in the literature, I conducted a dynamic longitudinal analysis to investigate the association between long working hours and the risk of mental illness nationwide. Using three-wave longitudinal data from the China Family Panel Studies conducted in 2014, 2016, and 2018, I adopted dynamic regression models with lagged long working hours variables to examine their association with the risk of mental illness. The results indicate that long working hours have positive and significant (p < 0.01 or p < 0.05) associations with the risk of mental illness (OR: 1.12~1.22). The effect is more significant for women, white-collar workers, and employees in micro-firms, compared with their counterparts (i.e., men, pink-and blue-collar workers, employees of large firms, and self-employed individuals). The results provide empirical evidence of the effects of long working hours on mental health in China, confirming the need to enforce the regulations regarding standard working hours and monitor regulatory compliance by companies, as these factors are expected to improve mental health.
The taxonomic status of millipedes of the genus Spirobolus Brandt, 1833, referred to as "Yaeyama-maruyasude" from the Yaeyama Islands, Ryukyu Islands, Japan, was unresolved. We assess the taxonomic status of these Yaeyama Spirobolus sp. using an integrated morphological and molecular approach, and describe them as a new species, S. akamma sp. nov., for which partial sequences of the nuclear 28S ribosomal RNA, mitochondrial cytochrome c oxidase subunit I, and 16S ribosomal RNA markers are provided. This new species differs from continental China and Taiwan endemic congeners in anterior gonopod morphology (in having an elongate and subtriangular coxa, and a pentagonal mesal sternal process), posterior gonopod morphology (in having a coronoid prefemoral endite with rounded distal end, and an elongate telopodite), and in having four serrations on the cyphopod lateral flange.
In the midst of digitalization, a polarization has developed between autonomous and proactive consumers and those who prefer altruistic and accidental consumption. Consumers who prefer accidental consumption seek context-dependent, instantaneous consumption, and unpredictable, impulsive satisfaction. Inspiration associated with consumption behavior can satisfy this impulse satisfaction and motivate subsequent purchase-related behavior. In this paper, we review existing research on “consumer inspiration,” which is important when considering marketing in response to accidental consumption. Consumer inspiration is examined from the three perspectives of “mechanism,” “antecedents,” and “effects”. There are three issues for future research. (1) Since inspiration is diffuse, it is necessary to establish a marketing perspective to deal with it. (2) It is necessary to examine individual differences and situational factors in the digital environment. (3) It is necessary to study the cognitive Consequences of consumer inspiration.
Ethnographic fieldwork has become a common method in CSCW research for understanding places and people. Recent technological developments have expanded opportunities for ethnographic fieldwork by teams by enhancing recording and management of field data and facilitating collaboration among researchers. In this research, we examine the implications of conducting ethnographic fieldwork and managing data appropriately according to its characteristics in teams. In particular, this paper focuses on images, which are major media comprising ethnographic data. This paper explores how multi-layered interpretations of the field emerge by sharing external and internal information of images in stages within teams. The results of a study in which three tentative research teams conducted fieldwork suggest that the scope for imagination and interpretation can be expanded by sharing external and internal information of images with team members in stages. This paper aims to discuss methodological design space of fieldwork in teams.
Vocabulary is a key variable to successful listening comprehension. Research has explored the relationship between aural and orthographic vocabularies and listening comprehension. This current study examined the relationships among aural vocabulary, orthographic vocabulary, and listening comprehension within the same Japanese cohort in an integrated manner. The test data of 155 Japanese EFL students, who took identical aural and orthographic vocabulary tests (the listening vocabulary levels test [LVLT] and new vocabulary levels test [NVLT], respectively) and a high-stakes listening test (Test of English for International Communication (TOEIC) for Parts I and II), were analyzed. The results indicated that aural and orthographic vocabulary are closely related but not identical. Moreover, orthographic vocabulary is more connected to the word- and propositional-level understanding of extended texts than to aural vocabulary for the Japanese group. More specifically, the 2,000-word and 4,000-word level and the academic vocabulary of the orthographic vocabulary predicted 27% of the variance of the listening comprehension test performance, whereas only the academic words of the aural vocabulary predicted 8%.
Fat‐tree topologies are widely used in interconnect network designs for parallel supercomputers. In the classic fat‐tree, compute nodes are connected to leaf stage switches by links. Given a large number of compute nodes, many switches and links are required, resulting in high hardware costs. To solve this problem, this paper proposes two hybrid topologies, k$$ k $$‐Cube k$$ k $$‐Ary n$$ n $$‐Tree (CAT) and Mirrored k$$ k $$‐Cube k$$ k $$‐Ary n$$ n $$‐Tree (MiCAT), based on fat‐tree and hypercube. Instead of connecting k$$ k $$ compute nodes directly to a leaf switch, we connect a k$$ k $$‐cube to the switch, and each switch in the k$$ k $$‐cube part connects k$$ k $$ compute nodes. That is, this k$$ k $$‐cube consists of 2k−1$$ {2}^k-1 $$ switches and k(2k−1)$$ k\left({2}^k-1\right) $$ compute nodes. We give the shortest path routing algorithms and evaluate the path diversity, cost, performance, and average packet latency of CAT and MiCAT. The results show that CAT and MiCAT can save up to 87%$$ 87\% $$ switches and 80%$$ 80\% $$ links in a large‐scale parallel system, k=n=8$$ k=n=8 $$ for example, compared to fat‐trees, and meanwhile, both CAT and MiCAT have higher path diversities than fat‐trees.
This study examined the effects of bottom-up instruction (BI) on a high-stakes listening test for second language (L2) listeners and compared these effects with those of strategy instruction (SI) in relation to their proficiency levels. Two intact classes (48 L2 listeners) of different L2 listening proficiency levels received five weeks of BI and two weeks of SI. BI offered explicit knowledge of spoken English combined with reproduction practice, whereas SI helped learners deploy metacognitive knowledge and test-taking strategies. The data were collected three times: before the intervention (pre-test) and after each instruction (mid- and post-test). A common-item design that permits Rasch analysis was used. The results showed that BI improved L2 ­listeners’ test performances regardless of their proficiency levels, ­highlighting the usefulness of BI in boosting listening proficiency. Conversely, SI benefited only high proficiency L2 listeners, which supports the threshold hypothesis claiming that L2 listeners require a certain level of L2 proficiency to deploy metacognitive knowledge and test-taking strategies successfully.
This paper investigates households’ consumption smoothing behavior by estimating the intertemporal elasticity of substitution of consumption (IES) while allowing labor/leisure to vary. To this end, we adopt a utility specification that allows non-separability between consumption and leisure. Using this specification, we define a leisure margin as the gap between the IES that allows leisure to vary and the IES that keeps leisure constant. We find a positive and statistically significant leisure margin throughout the paper. In addition, the leisure margin becomes larger when the spouse’s leisure is taken into consideration. This result indicates that family labor supply plays an important role in households’ consumption decisions. We further explore the heterogeneous nature of nonmarket time, and show that consumption-leisure substitutability could be explained largely by home production. Our findings demonstrate the importance of time allocation when individuals make decisions on consumption and saving.
The arrangement of buildings and their forms in houses, such as roofs, eaves, and walls, in the Important Preservation Districts for Groups of Traditional Buildings were analyzed to determine the composition of historic Japanese streetscapes. Then, based on the form data and publicly provided map data, simplified three-dimensional models of the streetscapes, depicting their images, were represented using the automatic form generation method. The characteristics of the historic Japanese streetscapes were explored using the simplified models.
The impact of Internet of Things (IoT) has become increasingly significant in smart manufacturing, while deep generative model (DGM) is viewed as a promising learning technique to work with large amount of continuously generated industrial Big Data in facilitating modern industrial applications. However, it is still challenging to handle the imbalanced data when using conventional Generative Adversarial Network (GAN) based learning strategies. In this article, we propose a distribution bias aware collaborative GAN (DB-CGAN) model for imbalanced deep learning in industrial IoT, especially to solve limitations caused by distribution bias issue between the generated data and original data, via a more robust data augmentation. An integrated data augmentation framework is constructed by introducing a complementary classifier into the basic GAN model. Specifically, a conditional generator with random labels is designed and trained adversarially with the classifier to effectively enhance augmentation of the number of data samples in minority classes, while a weight sharing scheme is newly designed between two separated feature extractors, enabling the collaborative adversarial training among generator, discriminator, and classifier. An augmentation algorithm is then developed for intelligent anomaly detection in imbalanced learning, which can significantly improve the classification accuracy based on the correction of distribution bias using the rebalanced data. Compared with five baseline methods, experiment evaluations based on two real-world imbalanced datasets demonstrate the outstanding performance of our proposed model in tackling the distribution bias issue for multiclass classification in imbalanced learning for industrial IoT applications.
Edge caching has emerged as a promising approach to meet explosive mobile data on 6G networks. One critical issue in edge caching is file popularity prediction. The federated learning (FL) based distributed algorithm is used to predict file popularity, which solves user privacy issues in centralized algorithms. However, due to the heterogeneity of user devices, the feedback time (i.e., the update and upload time of model parameters) is various for each user, which causes the feedback delay in the framework of FL-based edge caching. In this letter, we devise a feedback delay-tolerant proactive caching scheme (FLASH) based on FL in which each user utilizes hybrid filtering on stacked autoencoders to train the prediction model locally. Experimental results indicate that FLASH can effectively handle feedback delay and outperform counterpart algorithms in cache efficiency.
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1,849 members
Hideo Nishiumi
  • Department of Chemical Science and Technology
Takanobu Sawagaki
  • Department of Social Sciences
Makoto Takizawa
  • Research Center for Computing and Multimedia Studies
Hiroshi Ueda
  • Research Center for Computing and Multimedia Studies
Yoshifuru Saito
  • Faculty of Science and Engineering
2-17-1 Fujimi, Chiyoda-ku, 102-8160, Tokyo, Japan
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