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Computational Fluid-Structure Interaction Design Approach for Polymer Micromachined Insect-mimetic Flapping Wings of Air Vehicles
No full textThis paper proposes 2.5-dimensional polymer micromachined insect-mimetic wings based on a fluid-structure interaction (FSI) design concept that enables natural deformations like cambering and pitching under fluid forces. Instead of directly employing an analysis for the FSI, an iterative structural Design Window (DW) search is used to reduce the computational cost significantly. A DW search using the iterative method refines the initial design by addressing fabrication challenges and tuning it to meet manufacturability constraints. The successful fabrication and demonstration of the final design solution for a wing demonstrates the effectiveness of the iterative DW search based on the FSI design concept. Furthermore, a pixel model is introduced to convert an unstructured to a structured mesh for the FSI analysis to further reduce the computational cost. The camber and pitching error between the unstructured and structured meshes is minimized to achieve insect-like aerodynamic performance by adjusting the elastic moduli of center and root veins. Finally, an analysis for the FSI is conducted, based on the parameters obtained from the pixel model to evaluate the flight performance on the basis of the lift, camber, and pitching required by an actual insect to maneuver and hover.journal articl
Evolution and extraction of decision-making mechanisms in collective perception of a robotic swarm
Get PDFThis paper demonstrates the evolution and extraction approach for the controller of the robotic swarm. The collective perception task has received a lot of attention in the field of swarm robotics. In addition, recent studies showed that the evolutionary robotics (ER) approach successfully designed decision-making strategies for the task. This study focused on a detailed analysis of the evolved decision-making strategies. As in related work, the artificial neural network (ANN) was employed to approximate a decision-making mechanism. At first, we examined how the available information for ANN affects the performance of the collective perception task. Secondly, a visualization approach was proposed to extract evolved decision-making mechanisms from ANNs. The computer simulations showed that our visualization approach successfully extracted the evolved decision-making mechanisms as reusable or analyzable by any others.journal articl
Research on the Application of Deep Learning in Smart Agriculture
Get PDF九州工業大学博士（工学）1 Introduction| 2 The Deep Learning Application in Corn Cultivation| 3 Extraction Phenotypic Parameters of Corn Plant| 4 Multiple Object Tracking of Corns| 5 Pose Estimation of Corns| 6 ConclusionSmart agriculture is an inevitable stage of agricultural technology development and a current research hotspot. As an emerging field, smart agriculture integrates advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), and computer vision to improve production efficiency, reduce labor intensity, and optimize crop management. With the growing demand for global food security and sustainable agriculture, smart agriculture is transforming traditional farming, making it more data-driven, precise, and automated. Corn is the most important staple food and is irreplaceable in agriculture. Deep learning is an important part of AI. The application of deep learning in corn planting is a critical topic. The main research of this paper is the application of deep learning technology in corn growth detection, focusing on solving key challenges such as extraction of phenotypic parameters, multi-object tracking in complex environments, and pose estimation. These tasks are at the core of promoting the development of precise management of smart agriculture in corn cultivation, contributing to the related research in the field of smart agriculture. Firstly, in terms of extraction of phenotypic parameters, the stereo corn phenotype extraction algorithm (SCPE) based on key point detection was proposed. SCPE algorithm is based on the YOLOv7-Pose algorithm. A deep learning algorithm was used to extract different keypoints of corn plants, depth information was obtained by combining binocular photo data, and then the characterization of corn plants was extracted, including plant height, ear position, leaf length, and leaf angle. The innovation of this work lies in deep learning model structure optimization and fewer parameters. This method improves the traditional manual operation mode, avoids the problem of large errors and low efficiency, and realizes more efficient contactless corn plant growth monitoring. Secondly, in the multi-object tracking task, this study is based on YOLOv8 + DeepSort algorithm, mainly aiming at the accuracy and stability of the tracking algorithm in complex environments such as dense objects, severe occlusion, and view changes. This work optimizes the traditional YOLOv8 model through an attention mechanism and feature fusion network. The tracking algorithm’s performance is verified by a dataset of simulated corn to test its performance in a complex environment. Finally, in the corn pose estimation task, this paper proposes the stereo corn pose detection algorithm (SCPD) based on 3D object detection with stereo images to detect corn pose and dimension. The algorithm consists of FCOS-Stereo and Cross-Stereo-Efficientformer. FCOSStereo is used to accurately detect objects from binocular images with union bounding boxes. Cross-Stereo-Efficientformer is based on a transformer structure with good regression capabilities. The Cross-Stereo-Efficientformer uses union bounding boxes to regress 3D bounding boxes. SCPD is superior to the traditional algorithm in the constructed corn 3D object detection dataset. Detecting the pose of corn is particularly important for automating tasks such as precise harvesting and directional spraying, which require an accurate understanding of each corn’s spatial pose and position. The future research plan proposed in this paper includes combining the 3D position and attitude information of binocular cameras with the SLAM (real-time positioning and map Construction) algorithm to build an accurate 3D corn field map, which can be used to dynamically update the growth parameters of each corn plant and realize real-time monitoring of the corn growth process. By integrating phenotype acquisition, multi-object tracking, and pose estimation algorithms into the 3D map construction process, the system will provide powerful data support for smart agricultural applications, and help intelligent management in areas such as automated irrigation, precision fertilization, and crop health monitoring. In conclusion, this paper proposes a number of innovative solutions in the application of deep learning in corn planting, which significantly improves the efficiency and accuracy of these algorithms. These technological advances not only improve the deep learning technology in smart agriculture, but also lay a solid foundation for the further development of smart farmland management systems, and promote the grand vision of smart agriculture.九州工業大学博士学位論文 学位記番号:工博甲第606号 学位授与年月日:令和7年3月25日doctoral thesi
A Longitudinal Study on Japanese Learners’ Written Complexity, Accuracy, and Fluency
Get PDFMost traditional EFL writing classes in Japan, have over-emphasized data collection of exam scores, completion of homework or e-learning modules (Harwood, 2019; Iwasaki et al., 2019). Little research has been conducted about improvement in students’ writing over a period of time (Hokamura’s (2018); thus, this paper reports on the results of changes in Japanese EFL students’ writing complexity, accuracy, and fluency (CAF) in a span of one academic school year. Research questions focused on differences in grammatical errors and syntactic complexity between a control group, wherein students wrote three essays, and a treatment group, wherein students wrote eight papers over an academic semester. Specifically, the study aimed to find out if there were significant improvements in grammar accuracy and syntactic complexity between the first and second written drafts as well as, if there was any significant difference with the use of self-editing and grammar online checkers between the two groups. A significant difference was found between the groups in regard to syntactic complexity, and fluency, which oscillated with clauses per T-unit, increased 3.2% on average. Furthermore, grammatical errors decreased over the year for the treatment group, and improvements in syntactic complexity were found to be significant for both groups. The use of online grammar checkers was confirmed to result in fewer errors. Overall, the study indicates that EFL writing (CAF) is impacted by instruction and that more attention is warranted regarding EFL writing classes.従来のEFLライティングの授業では、ほとんどの場合、試験の点数や宿題の完成度、Eラーニングのモジュールなどのデータ収集が過度に重視されてきた。一定期間にわたる生徒のライティング向上に関する研究は、ほとんど行われていない。本報告は、1年間における日本語EFL生徒のライティングの複雑さ、正確さ、流暢さ（CAF）の変化に関する研究である。研究課題は、対照群（1学期間に3本の小論文を書いた生徒）と処理群（8本の小論文を書いた生徒）の文法的誤りと構文の複雑さの違いに焦点を当てた。具体的には、第1稿と第2稿で文法の正確さと構文の複雑さに有意な改善が見られたかどうか、また、自己校正と文法オンラインチェッカーの使用について両群の間に有意な差が見られるかどうかを調べることを目的とした。構文の複雑さに関しては、両群間に有意差が認められ、流暢さはTユニットあたりの節数により揺れが見られたが、平均3.2％増加した。また、処理群では、文法的ミスは1年間で減少した。構文の複雑さについては、対照群、処理群ともに、有意に向上した。また、オンライン文法チェッカーの使用により、間違いが少なくなることが確認された。全般的に、本研究は、EFLライティング（CAF）が指導による影響を受けており、EFLライティングの授業に関して更なる注意を払う必要があることを示している。journal articl
Review of simplified testing method for performance evaluation to assist in the selection of chemical protective gloves
Get PDFObjective: There is a demand for information on the proper selection, use, and maintenance of impermeable chemical protective gloves to prevent direct skin contact with hazardous substances. This review aims to summarize simplified testing methods for evaluating glove performance. Methods: The survey highlighted a lack of awareness regarding permeation resistance in glove selection. Various simplified testing methods were developed, such as real-time monitoring and gas chromatography, to evaluate the permeation resistance of chemical protective gloves, including the efficacy of multilayer films in reducing permeation. Results: The investigation revealed significant flaws in glove selection regarding permeation resistance to chemicals. Analysis showed that thin nitrile gloves offer inadequate protection against chloroform, while laminated film gloves demonstrated strong resistance to various chemicals. Real-time monitoring facilitated glove performance evaluation and confirmed that commonly used gloves may still allow harmful substances to permeate. Conclusion: The review underscores the urgent need for simplified permeation testing methods, enabling workers to make informed choices about glove materials based on their specific workplace hazards. Implementing these testing methodologies and adhering to updated safety regulations will better protect workers from chemical exposure, particularly in environments handling hazardous substances. Further research and development of glove materials with improved permeation resistance are recommended to enhance occupational safety.journal articl
Geotechnical Investigation and Stability Assessment of Geogrid Reinforced Soil Wall Damaged by The 2024 Noto Peninsula Earthquake
Get PDF2024年1月1日16時10分に石川県能登地方を震源とする，マグニチュード7.6，最大震度7の地震（令和6年能登半島地震）が発生した．この地震により石川県輪島市に位置するジオグリッド補強土壁に壁面の滑動や前倒れ，目地開き，路面のクラックなどの変状が生じた．盛土材のこぼれ出しに至るような致命的な損傷は確認されなかったが，本補強土壁の地震後の安定性は不明確であったため，壁面の3次元測量や標準貫入試験，2次元表面波探査等の地盤調査を行った．本論文では，これらの地盤調査に基づいた安定性評価の結果について報告する．The 2024 Noto Peninsula Earthquake with a magnitude of 7.6 occurred on January 1, 2024, at 16:10. In Wajima City, Ishikawa Prefecture, the geogrid reinforced soil wall was deformed as sliding, joint opening of wall facing and pavement crack. Although the critical damage of the wall did not occur, its structural stability remained unclear. Authors conducted the geotechnical investigations such as three-dimensional surveying, standard penetration test and surface-wave method for the wall. This paper reports the assessment of wall’ stability based on the geotechnical investigations.journal articl
DNA Reaction System That Acquires Classical Conditioning
Get PDFBiochemical reaction networks can exhibit plastic adaptation to alter their functions in response to environmental changes. This capability is derived from the structure and dynamics of the reaction networks and the functionality of the biomolecule. This plastic adaptation in biochemical reaction systems is essentially related to memory and learning capabilities, which have been studied in DNA computing applications for the past decade. However, designing DNA reaction systems with memory and learning capabilities using the dynamic properties of biochemical reactions remains challenging. In this study, we propose a basic DNA reaction system design that acquires classical conditioning, a phenomenon underlying memory and learning, as a typical learning task. Our design is based on a simple mechanism of five DNA strand displacement reactions and two degradative reactions. The proposed DNA circuit can acquire or lose a new function under specific conditions, depending on the input history formed by repetitive stimuli, by exploiting the dynamic properties of biochemical reactions induced by different input timings.journal articl
Content Search Method Utilizing the Metadata Matching Characteristics of Both Spatio-Temporal Content and User Request in the IoT Era
Get PDFCross-domain data fusion is becoming a key driver in the growth of numerous and diverse applications in the Internet of Things (IoT) era. We have proposed the concept of a new information platform, Geo-Centric Information Platform (GCIP), that enables IoT data fusion based on geolocation, i.e., produces spatio-temporal content (STC), and then provides the STC to users. In this environment, users cannot know in advance “when,” “where,” or “what type” of STC is being generated because the type and timing of STC generation vary dynamically with the diversity of IoT data generated in each geographical area. This makes it difficult to directly search for a specific STC requested by the user using the content identifier (domain name of URI or content name). To solve this problem, a new content discovery method that does not directly specify content identifiers is needed while taking into account (1) spatial and (2) temporal constraints. In our previous study, we proposed a content discovery method that considers only spatial constraints and did not consider temporal constraints. This paper proposes a new content discovery method that matches user requests with content metadata (topic) characteristics while taking into account spatial and temporal constraints. Simulation results show that the proposed method successfully discovers appropriate STC in response to a user request.journal articl
Fabrication of quantum dot-immobilized Y2O3 microspheres with effective photoluminescence for cancer radioembolization therapy
Get PDFMicrospheres composed of Y-containing materials are effective agents for cancer radioembolization therapy using β-rays. The distribution and dynamics of these microspheres in tissues can be easily determined by providing the microspheres with an imaging function. In addition, the use of quantum dots will enable the detection of microspheres at the individual particle level with high sensitivity. In this study, core – shell quantum dots were bound to chemically modified yttria microspheres under various conditions, and the effect of reaction conditions on the photoluminescence properties of the microspheres was investigated. The quantum dots were immobilized on the surfaces of the microspheres through dehydration – condensation reactions between the carboxy groups of quantum dots and the amino groups of silane-treated microspheres. As the reaction time increased, the photoluminescence peak blue shifted, and the photoluminescence intensity and lifetime decreased. Therefore, a moderate period of the immobilization process was optimal for imparting effective photoluminescence properties. This study is expected to facilitate particle-level tracking of microsphere dynamics in biological tissues for the development of minimally invasive cancer radiotherapy of deep-seated tumors.journal articl
Design of Scatterer Configuration for Spectral Optimization of Random Lasers
Get PDFThe two-dimensional structure of a random gain medium was designed to obtain the specified emission spectrum from a random laser. Structural optimization was performed using a direct binary search method. The simulation results showed that the emitted light can be concentrated within one or more specific wavelength ranges. The effect of the fabrication errors on the optimized laser emission spectrum was also examined.2022 Conference on Lasers and Electro-Optics Pacific Rim (CLEO-PR), 31 July - 05 August, 2022, Sapporo, Japanjournal articl