13197 research outputs found
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Quantization and Attention-based Hierarchical Deep Learning Models for Beam Training in mmWave Massive MIMO Systems
Get PDF奈良先端科学技術大学院大学博士（工学）doctoral thesi
A Soft Robotic Skin with Integrated Optical Sensing and Jamming Mechanism
Get PDF奈良先端科学技術大学院大学博士（工学）doctoral thesi
Anti-inflammatory Activity Prediction of Plant Secondary Metabolites Based on Machine Learning Models
Get PDF奈良先端科学技術大学院大学修士(工学)master thesi
Advancing Rare Disease Research by Unifying Both Supervised and Unsupervised Methods
Get PDF奈良先端科学技術大学院大学博士(工学)doctoral thesi
Garbage Content Estimation Using Internet of Things and Machine Learning
No full textMuch garbage is produced daily in homes due to living activities, including cooking and eating. The garbage must be adequately managed for human well-being and environmental protection. Although the existing IoT-based smart garbage systems have gained high garbage classification accuracy, they still have a problem that they provide a small number of garbage categories, not enough for reasonable practices of household garbage separation. This study presents a new smart garbage bin system, SGBS, embedded with multiple sensors to solve the problem. We deployed temperature, humidity, and gas sensors to know the condition and identify the garbage content disposed of. Then, we introduce a new garbage content estimation method by training a machine learning model using daily collected fuse sensor readings combined with detailed household garbage contents annotations to perform garbage classification tasks. For evaluation, we deployed the designed SGBS in five households over one month. As a result, we confirmed that the leave-one-house cross-validation results showed an accuracy of 91% in 5 kitchen waste contents, also, 89% in 5 paper/softbox contents, and 85% in the 8 garbage categories for the classification tasks.journal articl
Patterned proliferation orients tissue-wide stress to control root vascular symmetry in Arabidopsis
No full textSymmetric tissue alignment is pivotal to the functions of plant vascular tissue, such as long-distance molecular transport and lateral organ formation. During the vascular development of the Arabidopsis roots, cytokinins initially determine cell-type boundaries among vascular stem cells and subsequently promote cell proliferation to establish vascular tissue symmetry. Although it is unknown whether and how the symmetry of initially defined boundaries is progressively refined under tissue growth in plants, such boundary shapes in animal tissues are regulated by cell fluidity, e.g., cell migration and intercalation, lacking in plant tissues. Here, we uncover that cell proliferation during vascular development produces anisotropic compressive stress, smoothing, and symmetrizing cell arrangement of the vascular-cell-type boundary. Mechanistically, the GATA transcription factor HANABA-TARANU cooperates with the type-B Arabidopsis response regulators to form an incoherent feedforward loop in cytokinin signaling. The incoherent feedforward loop fine-tunes the position and frequency of vascular cell proliferation, which in turn restricts the source of mechanical stress to the position distal and symmetric to the boundary. By combinatorial analyses of mechanical simulations and laser cell ablation, we show that the spatially constrained environment of vascular tissue efficiently entrains the stress orientation among the cells to produce a tissue-wide stress field. Together, our data indicate that the localized proliferation regulated by the cytokinin signaling circuit is decoded into a globally oriented mechanical stress to shape the vascular tissue symmetry, representing a reasonable mechanism controlling the boundary alignment and symmetry in tissue lacking cell fluidity.journal articl
An Algorithm to Correct the Sensitivity Distribution of a Retarding Field Analyzer for Photoelectron Holography
No full textRecently, we developed a retarding field analyzer (RFA) with high energy resolution and wide acceptance angles, which was installed at BL25SU in SPring-8, Japan. This apparatus enables us to measure photoelectron angular distributions (photoelectron holograms) with a solid angle of ±49° in a few minutes, and this approach is now being applied to measure the atomic arrangements of dopants and interfaces. However, correcting the sensitivity distribution of the measured images by the RFA is important in processing this data. The sensitivity distribution of the RFA is difficult to measure directly because it depends on the geometry of a sample, the kinetic energy of the photoelectrons, and so forth. Therefore, we developed an image processing algorithm to estimate the sensitivity distribution using spherical harmonics. This approach is more accurate than a Fourier transform and can efficiently correct the sensitivity distribution. Moreover, the algorithm can also be adopted in a wide variety of other applications in addition to RFA measurements.journal articl
Analysis of interaction between miner decision making and user action for incentive mechanism of bitcoin blockchain
No full textIn Bitcoin blockchain, miner nodes are likely to choose transactions with high fee to be included in a block. This makes transactions with high fee being processed fast, affecting the amount of transaction fee that users want to pay. The reward for a winning miner consists of transaction fee and newly issued coins, and hence the amount of newly issued coins also affects the miner decision to participate in the mining competition. In addition, mining reward also affects the total hash computing power, which plays an important role of Bitcoin security for reducing the success probability of security attack by a malicious miner. In this paper, we develop a mathematical model for analyzing the interaction between miner decision making and user actions in terms of transaction fees, transaction-confirmation time, and security. We analyze the transaction-inclusion process with queueing theory, while decision making processes of miners and users are analyzed in the context of Nash equilibrium. The numerical examples show how the mining costs and newly issued coins affect miner decision making.journal articl
Theoretical model of membrane protrusions driven by curved active proteins
No full textEukaryotic cells intrinsically change their shape, by changing the composition of their membrane and by restructuring their underlying cytoskeleton. We present here further studies and extensions of a minimal physical model, describing a closed vesicle with mobile curved membrane protein complexes. The cytoskeletal forces describe the protrusive force due to actin polymerization which is recruited to the membrane by the curved protein complexes. We characterize the phase diagrams of this model, as function of the magnitude of the active forces, nearest-neighbor protein interactions and the proteins’ spontaneous curvature. It was previously shown that this model can explain the formation of lamellipodia-like flat protrusions, and here we explore the regimes where the model can also give rise to filopodia-like tubular protrusions. We extend the simulation with curved components of both convex and concave species, where we find the formation of complex ruffled clusters, as well as internalized invaginations that resemble the process of endocytosis and macropinocytosis. We alter the force model representing the cytoskeleton to simulate the effects of bundled instead of branched structure, resulting in shapes which resemble filopodia.journal articl
