Search results for: Goro Fujita

Authors: Nur Aisyah Jalalludin, Arwindra Rizqiawan, Goro Fujita

Abstract:

In this study, we aim to demonstrate a microgrid system experimental simulation for an easy understanding of a large-scale microgrid system. This model is required for industrial training and learning environments. However, in order to create an exact representation of a microgrid system, the laboratory-scale system must fulfill the requirements of a grid-connected inverter, in which power values are assigned to the system to cope with the intermittent output from renewable energy sources. Aside from that, during changes in load capacity, the grid-connected system must be able to supply power from the utility grid side and microgrid side in a balanced manner. Therefore, droop control is installed in the inverter’s control board to maintain equal power sharing in both sides. This power control in a stand-alone condition and droop control in a grid-connected condition must be implemented in order to maintain a stabilized system. Based on the experimental results, power control and droop control can both be applied in the system by comparing the experimental and reference values.

Keywords: droop control, droop characteristic, grid-connected inverter, microgrid, power control

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Authors: Hiroshi Yamaguchi, Phillip C. Y. Sheu, Ryo Fujita, Shigeo Tsujii

Abstract:

In this paper, the secure BioSemantic Scheme is presented to bridge biological/biomedical research problems and computational solutions via semantic computing. Due to the diversity of problems in various research fields, the semantic capability description language (SCDL) plays and important role as a common language and generic form for problem formalization. SCDL is expected the essential for future semantic and logical computing in Biosemantic field. We show several example to Biomedical problems in this paper. Moreover, in the coming age of cloud computing, the security problem is considered to be crucial issue and we presented a practical scheme to cope with this problem.

Keywords: biomedical applications, private information retrieval (PIR), semantic capability description language (SCDL), semantic computing

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Authors: I-Huan Chiu, Kazuhiko Ninomiya, Shin’ichiro Takeda, Meito Kajino, Miho Katsuragawa, Shunsaku Nagasawa, Atsushi Shinohara, Tadayuki Takahashi, Ryota Tomaru, Shin Watanabe, Goro Yabu

Abstract:

In recent years, a nondestructive elemental analysis method based on muonic X-ray measurements has been developed and applied for various samples. Muonic X-rays are emitted after the formation of a muonic atom, which occurs when a negatively charged muon is captured in a muon atomic orbit around the nucleus. Because muonic X-rays have higher energy than electronic X-rays due to the muon mass, they can be measured without being absorbed by a material. Thus, estimating the two-dimensional (2D) elemental distribution of a sample became possible using an X-ray imaging detector. In this work, we report a non-destructive imaging experiment using muonic X-rays at Japan Proton Accelerator Research Complex. The irradiated target consisted of polypropylene material, and a double-sided silicon strip detector, which was developed as an imaging detector for astronomical observation, was employed. A peak corresponding to muonic X-rays from the carbon atoms in the target was clearly observed in the energy spectrum at an energy of 14 keV, and 2D visualizations were successfully reconstructed to reveal the projection image from the target. This result demonstrates the potential of the non-destructive elemental imaging method that is based on muonic X-ray measurement. To obtain a higher position resolution for imaging a smaller target, a new detector system will be developed to improve the statistical analysis in further research.

Keywords: DSSD, muon, muonic X-ray, imaging, non-destructive analysis

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Authors: Benoît Bucher, Hika Kuroshima, Kazuo Fujita

Abstract:

Although altruism is commonly observed in humans and is considered one of the most important factors in the survival of our species, its cognitive mechanisms and evolutionary roots are yet to be explained. This study is based on the previous findings that bonobos (Pan Paniscus) preferred to share a limited amount of food with others regardless of their relationships with the others. Findings such as this suggest that humans’ propensity for altruistic food-sharing may be shared among apes and may have evolved much longer ago than previously considered. We thus adapted the previous experimental design using tufted capuchins (Cebus apella), New World monkeys separating from humans about 40 million years ago. In order to achieve this, 12 pairs of capuchins (consisting of a benefactors and a partner) were tested in a row of two adjacent cages separated by a swinging door locked by a key (Fig.1). We observed whether the monkeys in possession of food (the benefactors) would allow their partner to enter their cage by unlocking the door between them. Results showed that the monkeys clearly preferred to monopolize the food for themselves, even though they in a few cases unlocked the door after eating the preferred food. This suggests that this species, which has been shown to be sensitive to the others’ welfare, would not actively share food at a cost of their own. Although further studies are needed, our results suggest the existence of significant differences in the evolutionary development of the pro social tendencies between bonobos and capuchin monkeys.

Keywords: altruism, capuchin monkeys, food sharing, pro social behaviors

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Authors: Mohammad Mirwais Arghandiwal, Fujita Motohiro, Wisinee Wisetjindawat

Abstract:

Since 2001, the new government of Afghanistan addressed the improvement of transportation in rural areas as one of the key issues for the country development. This paper thus, aims to show the impotency of transportation in the rural area of Kabul province. A field survey in Kabul Province capital of Afghanistan has been conducted during March, 2015, and 201 questionnaires were collected from four districts named Shakar Dara, Paghman, Char Asyab, and Khak Jabar to investigate the impacts of road transportation on the people’s daily life. The districts had their road projects constructed during the last 3-5 years. The interviewees are chosen randomly from a different category of districts residences. As transportation is one of the most important factors for the development of the communities, during the survey it was very easily to observe a positive effect on the life of people. The improvement on the accessibility has had a positive impact on the land and land price. In this paper, a model is created to show the relationship between different factors and the land price improvement. In the end, a recommendation is presented on the establishment of the community council for a better use and maintenance of road projects. We emphasize on a public and private partnership at a community level in the districts during the construction period too. In addition, the communities should be encouraged on their positive role in the improvement of transportation through their participation and collaboration with the local government.

Keywords: accessibility, Afghanistan, poverty, rural area, transportation development

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Authors: Ezedin Geta Seid

Abstract:

Slope failures are among the common geo-environmental natural hazards in the hilly and mountainous terrain of the world causing damages to human life and destruction of infrastructures. In Ethiopia, the demand for the construction of infrastructures, especially highways and railways, has increased to connect the developmental centers. However, the failure of roadside slopes formed due to the difficulty of geographical locations is the major difficulty for this development. As a result, a comprehensive site-specific investigation of destabilizing agents and a suitable selection of slope profiles are needed during design. Hence, this study emphasized the stability analysis and performance evaluation of slope profiles (single slope, multi-slope, and benched slope). The analysis was conducted for static and dynamic loading conditions using limit equilibrium (slide software) and finite element method (Praxis software). The analysis results in selected critical sections show that the slope is marginally stable, with FS varying from 1.2 to 1.5 in static conditions, and unstable with FS below 1 in dynamic conditions. From the comparison of analysis methods, the finite element method provides more valuable information about the failure surface of a slope than limit equilibrium analysis. Performance evaluation of geometric profiles shows that geometric modification provides better and more economical slope stability. Benching provides significant stability for cut slopes (i.e., the use of 2m and 3m bench improves the factor of safety by 7.5% and 12% from a single slope profile). The method is more effective on steep slopes. Similarly, the use of a multi-slope profile improves the stability of the slope in stratified soil with varied strength. The performance is more significant when it is used in combination with benches. The study also recommends drainage control and slope reinforcement as a remedial measure for cut slopes.

Keywords: slope failure, slope profile, bench slope, multi slope

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

Abstract:

In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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