ため池堤体の異なる貯水状態を考慮した地震時応答

京都大学新制・課程博士博士(工学)甲第23476号工博第4888号新制||工||1764(附属図書館)京都大学大学院工学研究科社会基盤工学専攻(主査)教授 渦岡 良介, 教授 三村 衛, 教授 肥後 陽介学位規則第4条第1項該当Doctor of Philosophy (Engineering)Kyoto UniversityDGA

Factors influencing the adoption of smart wearable devices

This study aims to examine the factors and issues in adoption of smart wearable devices. Wearable devices have many functions to offer which make them very useful in our daily lives. However, factors influencing the adoption of these devices are not well understood. This research explores the inhibiting and contributing factors influencing the adoption of wearable devices by employing the laddering approach. Qualitative data were collected through in-depth interviews using the laddering technique in order to understand these factors. Wearable devices that were examined include the Smart Glass (Google Glass) and the Smart Watch (Sony Smart Watch 3). After the participants had the opportunity to try out these two devices, the factors that are most important to them in deciding whether to adopt or not to adopt these devices were laddered. The use of the laddering technique with the Means-End Chain approach not only offers a greater understanding of the factors influencing the adoption of wearable devices, but also reveal the relationships among these factors and any meaningful associations with self (i.e., the user). This research has advanced our understanding on the adoption of wearable devices and provide some insights into the key design criteria to better fit users\u27 needs --Abstract, page iii

FACTORS HINDERING THE HERITAGE DESTINATION PROMOTION IN MALAYSIAN CONTEXT

The present research empirically investigates the preferences of the respondents currently residing in Malaysia towards the promotion of heritage destinations in Kuala Lumpur. The present study makes an attempt to identify the key determinant factors that are actually hindering the heritage destination promotion in Malaysian context. For the purpose of the research, the attractions in Kuala Lumpur are segmented as Heritage, Architectural, Natural and Amusement landmarks. Data has been collected from a self-administered questionnaire, returned by 100 survey participants. In accordance with thedestination competitiveness analysis and based on the preferences and attitudes expressed by the respondents towards these attractions, they are grouped as heritage and tourist destination travelers.Visitor profiles are developed depending upon their demographics such as age, income, education, occupation and marital status. Different heritage destination activities including visit to art galleries and museums, historical organizations and towns, cultural festivals etc., are studied in association with the heritage traveler site assessment. The awareness, visitation, interest, importance and satisfaction levels of the travelers to heritage sites are assessed in detail.Furthermore, motivations and barriers to visit heritage sites in conjunction with other prevailing attractions are examined. Apart from the above mentioned, respondents satisfaction, awareness and spending levels are measured with reference to the heritage travel attributes and amenities usage. Respondent's intention and preference to visit as well as revisit heritage sites in comparison with other architectural, natural and amusement landmarks are explored. The importance of information sources in promotion of heritage destinations to the travelers is presented and managerial implications are discussed. Moreover, SWOT analysis thoroughly analyzes the current market situation for heritage destination promotion in Kuala Lumpur. Avenues for further research are presented

CLASSIFICATION OF LARGE SCALE FISH DATASET BY DEEP NEURAL NETWORKS

The development of robust and efficient fish classification systems has become essential to preventing the rapid depletion of aquatic resources and building conservation strategies. A deep learning approach is proposed here for the automated classification of fish species from underwater images. The proposed methodology leverages state-of-the-art deep neural networks by applying the compact convolutional transformer (CCT) architecture, which is famous for faster training and lower computational cost. In CCT, data augmentation techniques are employed to enhance the variability of the training data, reducing overfitting and improving generalization. The preliminary outcomes of our proposed method demonstrate a promising accuracy level of 100% over the Large-scale fish dataset, with the potential for real-time deployment in aquatic monitoring systems. Furthermore, this work proposes avenues for future research in the domain of fish classification

Circumstances Probing Internet Banking Users to Use Alternative Channels: Thematic Matrix Display Analysis

This study highlights the circumstances that actually probe internet banking users to switch to the use of alternative channels in performing their banking transactions within Australian context. Data obtained from 372 internet banking users was analysed by employing thematic matrix analysis technique to identify various macro and micro thematic categories in that hierarchical order of importance. Results revealed factors such as ‘unable to perform over the internet’, ‘lack of internet access’, ‘not sure of something’, ‘problem rectification’, ‘proximity to auxiliary facilities’ and ‘type of internet connectivity’ were relevant in identifying the circumstances under which they preferred to use other banking channels. The study provides important implications for the formulation of effective service delivery channel management strategies by way of implementing effective mechanisms. Moreover, the study also outlines important guidelines for practical solutions in order to reduce the impact of situational barriers thus focusing on effective customer retention strategies. With the information provided by this research, bank executives, consultants and academics will have enhanced knowledge of the service areas they need to focus on to improve customer satisfaction, retention and profitability in the financial services businesses

Cognitive Power of Women

For ages together, men and women were considered to be different in biological and social terms due to which men enjoyed superiority over women. In the current scenario, this idea is fading due to the sense of equality. However, it is a controversial issue regarding whether differing or equal that made people research about the innate aspects of both the genders. It is ironical that though men and women are the same species they differ in their perceptions and deeds. This paper restricts to the discussion of mere cognition processes of both the genders. It compares and contrasts the thought processes of woman to that of men and the gender brain myths. In this paper, woman’s brain power is identified and the impact of physiological and sociological factors on woman is highlighte

Densification of selected agricultural crop residues as feedstock for the biofuel industry

The two main sources of biomass for energy generation are purpose-grown energy crops and waste materials. Energy crops, such as Miscanthus and short rotation woody crops (coppice), are cultivated mainly for energy purposes and are associated with the food vs. fuels debate, which is concerned with whether land should be used for fuel rather than food production. The use of residues from agriculture, such as barley, canola, oat and wheat straw, for energy generation circumvents the food vs. fuel dilemma and adds value to existing crops. In fact, these residues represent an abundant, inexpensive and readily available source of renewable lignocellulosic biomass. In order to reduce industry’s operational cost as well as to meet the requirement of raw material for biofuel production, biomass must be processed and handled in an efficient manner. Due to its high moisture content, irregular shape and size, and low bulk density, biomass is very difficult to handle, transport, store, and utilize in its original form. Densification of biomass into durable compacts is an effective solution to these problems and it can reduce material waste. Upon densification, many agricultural biomass materials, especially those from straw and stover, result in a poorly formed pellets or compacts that are more often dusty, difficult to handle and costly to manufacture. This is caused by lack of complete understanding on the natural binding characteristics of the components that make up biomass. An integrated approach to postharvest processing (chopping, grinding and steam explosion), and feasibility study on lab-scale and pilot scale densification of non-treated and steam exploded barley, canola, oat and wheat straw was successfully established to develop baseline data and correlations, that assisted in performing overall specific energy analysis. A new procedure was developed to rapidly characterize the lignocellulosic composition of agricultural biomass using the Fourier Transform Infrared (FTIR) spectroscopy. In addition, baseline knowledge was created to determine the physical and frictional properties of non-treated and steam exploded agricultural biomass grinds. Particle size reduction of agricultural biomass was performed to increase the total surface area, pore size of the material and the number of contact points for inter-particle bonding in the compaction process. Predictive regression equations having higher R2 values were developed that could be used by biorefineries to perform economic feasibility of establishing a processing plant. Specific energy required by a hammer mill to grind non-treated and steam exploded barley, canola, oat and wheat straw showed a negative power correlation with hammer mill screen sizes. Rapid and cost effective quantification of lignocellulosic components (cellulose, hemicelluloses and lignin) of agricultural biomass (barley, canola, oat and wheat) is essential to determine the effect of various pre-treatments (such as steam explosion) on biomass used as feedstock for the biofuel industry. A novel procedure to quantitatively predict lignocellulosic components of non-treated and steam exploded barley, canola, oat and wheat straw was developed using Fourier Transformed Infrared (FTIR) spectroscopy. Regression equations having R2 values of 0.89, 0.99 and 0.98 were developed to predict the cellulose, hemicelluloses and lignin compounds of biomass, respectively. The average absolute difference in predicted and measured cellulose, hemicellulose and lignin in agricultural biomass was 7.5%, 2.5%, and 3.8%, respectively. Application of steam explosion pre-treatment on agricultural straw significantly altered the physical and frictional properties, which has direct significance on designing new and modifying existing bins, hoppers and feeders for handling and storage of straw for biofuel industry. As a result, regression equations were developed to enhance process efficiency by eliminating the need for experimental procedure while designing and manufacturing of new handling equipment. Compaction of low bulk density agricultural biomass is a critical and desirable operation for sustainable and economic availability of feedstock for the biofuel industry. A comprehensive study of the compression characteristics (density of pellet and total specific energy required for compression) of ground non-treated and steam exploded barley, canola, oat and wheat straw obtained from three hammer mill screen sizes of 6.4, 3.2 and 1.6 mm at 10% moisture content (wb) was conducted. Four preset pressures of 31.6, 63.2, 94.7 and 138.9 MPa, were applied using an Instron testing machine to compress samples in a cylindrical die. It was determined that the applied pressure (60.4%) was the most significant factor affecting pellet density followed by the application of steam explosion pre-treatment (39.4%). Similarly, the type of biomass (47.1%) is the most significant factor affecting durability followed by the application of pre-treatment (38.2%) and grind size (14.6%). Also, the applied pressure (58.3%) was the most significant factor affecting specific energy required to manufacture pellets followed by the biomass (15.3%), pre-treatment (13.3%) and grind size (13.2%), which had lower but similar effect affect on specific energy. In addition, correlations for pellet density and specific energy with applied pressure and hammer mill screen sizes having highest R2 values were developed. Higher grind sizes and lower applied pressures resulted in higher relaxations (lower pellet densities) during storage of pellets. Three compression models, namely: Jones model, Cooper-Eaton model, and Kawakita-Ludde model were considered to determine the pressure-volume and pressure-density relationship of non-treated and steam exploded straws. Kawakita-Ludde model provided the best fit to the experimental data having R2 values of 0.99 for non-treated straw and 1.00 for steam exploded biomass samples. The steam exploded straw had higher porosity than non-treated straw. In addition, the steam exploded straw was easier to compress since it had lower yield strength or failure stress values compared to non-treated straw. Pilot scale pelleting experiments were performed on non-treated, steam exploded and customized (adding steam exploded straw grinds in increments of 25% to non-treated straw) barley, canola, oat and wheat straw grinds obtained from 6.4, 3.2, 1.6 and 0.8 mm hammer mill screen sizes at 10% moisture content (wb). The pilot scale pellet mill produced pellets from ground non-treated straw at hammer mill screen sizes of 0.8 and 1.6 mm and customized samples having 25% steam exploded straw at 0.8 mm. It was observed that the pellet bulk density and particle density are positively correlated. The density and durability of agricultural straw pellets significantly increased with a decrease in hammer mill screen size from 1.6 mm to 0.8 mm. Interestingly, customization of agricultural straw by adding 25% of steam exploded straw by weight resulted in higher durability (> 80%) pellets but did not improve durability compared to non-treated straw pellets. In addition, durability of pellets was negatively correlated to pellet mill throughput and was positively correlated to specific energy consumption. Total specific energy required to form pellets increased with a decrease in hammer mill screen size from 1.6 to 0.8 mm and also the total specific energy significantly increased with customization of straw at 0.8 mm screen size. It has been determined that the net specific energy available for production of biofuel is a significant portion of original agricultural biomass energy (89-94%) for all agricultural biomass

Time, action and psychosis: using subjective time to investigate the effects of ketamine on sense of agency

Sense of agency refers to the experience of initiating and controlling actions in order to influence events in the outside world. A disturbed sense of agency is found in certain psychiatric and neurological disorders, most notably schizophrenia. Sense of agency is associated with a subjective compression of time: actions and their outcomes are perceived as bound together in time. This is known as ‘intentional binding’ and, in healthy adults, depends partly on advance prediction of action outcomes. Notably, this predictive contribution is disrupted in patients with schizophrenia. In the present study we aimed to characterise the psychotomimetic effect of ketamine, a drug model for psychosis, on the predictive contribution to intentional binding. It was shown that ketamine produced a disruption that closely resembled previous data from patients in the early, prodromal, stage of schizophrenic illness. These results are discussed in terms of established models of delusion formation in schizophrenia. The link between time and agency, more generally, is also considered