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Using LiDAR sensors for detection flood and landslide in West Nusa Tenggara

AIP Conference Proceedings 2024年第1期3026卷

作者： Made Sutha Yadnya I. Wayan Sudiarta I. G. P. Wedashwara Wedarama Electrical Enginnering Enginnering Fakulty University of Mataram Mataram 80125 Indonesia Informatics Engineering Faculty of Engineering University of Mataram Mataram Indonesia Physic Study Program Faculty of Mathematics and Natural Science University of Mataram Mataram 80125 Indonesia

In this pre-research, this is an initial study using LiDAR to detect weather conditions in real time. In 5G communication, the opportunity to use an integrated IoT connection is given because the path is used, one of which is millimeter wave. This is applied to disaster conditions, namely flood and landslide detection. Data obtained briefly within one month in data processing needs to be added so that the real sensor power is obtained in the outdoor position because the sensor is used as needed. LiDAR has problems when used in rainy conditions which form polarization scattering or light scattering is formed by moving raindrops, especially when the rain is getting heavier. The position of LiDAR in this study is able to detect sunny conditions with an available level of 97.99% and rain outage is still 0.3%, this in heavy rainy conditions needs further research.

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Hypoglycemic activity of curcuma mangga val. Extract via modulation of GLUT4 and ppar-γ mrna expression in 3T3-L1 adipocytes

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Journal of Experimental Pharmacology 2020年 12卷 363-369页

作者： Pujimulyani, Dwiyati Yulianto, Wisnu Adi Setyowati, Astuti Arumwardana, Seila Kusuma, Hanna Sari Widya Sholihah, Ika Adhani Rizal, Rizal Widowati, Wahyu Maruf, Ali Faculty of Agroindustry University of Mercu Buana Yogyakarta Yogyakarta 55753 Indonesia Biomolecular and Biomedical Research Center Aretha Medika Utama Bandung 40163 Indonesia Biomedical Engineering Study Program Department of Electrical Engineering Faculty of Engineering University of Indonesia Jakarta 16424 Indonesia Medical Research Center Faculty of Medicine Maranatha Christian University Bandung 40164 Indonesia Key Laboratory for Biorheological Science and Technology of Ministry of Education State and Local Joint Engineering Laboratory for Vascular Implants Bioengineering College Faculty of Medicine Chongqing University Chongqing 400030 China

Background: There would be over 600 million people living with diabetes by 2040 as predicted by the World Health Organization. Diabetes is characterized by raised blood sugar and insulin resistance. Insulin regulates the influx of glucose into the cell by upregulating the glucose transporter type 4 (GLUT4) expression on the plasma membrane. Besides, PPAR-γ also controls the metabolism of glucose in adipose tissues. Curcuma mangga Val., denoted as C. mangga, is a native Indonesian medicinal plant that has many beneficial effects, including an antidiabetic potential. Purpose: In this research, we aimed to disclose the hypoglycemic activity of ethanol extract of C. mangga (EECM) in 3T3-L1 fibroblasts-derived adipocyte cells in regulating glucose uptake as confirmed by the GLUT4 and PPAR-γ gene expression. Methods: The uptake of glucose was determined using radioactive glucose, while the gene expression of GLUT4, PPAR-γ, and β-actin was quantified using mRNA segregation and real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). Results: We discovered that EECM interventions (200 and 50 μg/mL) increased glucose uptake in lipid-laden 3T3-L1 cells by 14.75 and 8.86 fold compared to the control noninsulin, respectively (p < 0.05). At the same doses, they also increased GLUT4 mRNA expression by 8.41 and 11.18 fold compared to the control non-insulin, respectively (p < 0.05). In contrast, EECM interventions (200 and 50 μg/mL) showed lower levels of PPAR-γ mRNA expression compared to the control metformin, indicating the anti-adipogenic potentials of EECM. Conclusion: EECM showed hypoglycemic activity in lipid-laden 3T3-L1 cells by improving glucose ingestion into the cells, which was mediated by increased GLUT4 expression and downregulated PPAR-γ expression. © 2020 Pujimulyani et al.

关键词： 3T3-L1 adipocytes Curcuma mangga Val Glucose uptake GLUT4 PPAR-γ

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Mechanically reprogrammable Pancharatnam-Berry metasurface for microwaves

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Advanced Photonics 2022年第1期4卷 69-79页

作者： Quan Xu Xiaoqiang Su Xueqian Zhang Lijuan Dong Lifeng Liu Yunlong Shi Qiu Wang Ming Kang Andrea Alù Shuang Zhang Jiaguang Han Weili Zhang Tianjin University Center for Terahertz Waves and College of Precision Instrument and Optoelectronics EngineeringKey Laboratory of Optoelectronic Information Technology(Ministry of Education of China)TianjinChina Shanxi Datong University Institute of Solid State Physics and College of Physics and Electronic ScienceShanxi Province Key Laboratory of Microstructure Electromagnetic Functional MaterialsDatongChina Wuhan University of Technology School of Information EngineeringWuhanChina Tianjin Normal University College of Physics and Materials ScienceTianjinChina City University of New York Advanced Science Research CenterPhotonics InitiativeNew YorkUnited States City University of New York Graduate CenterPhysics ProgramNew YorkUnited States University of Hong Kong Faculty of ScienceDepartment of PhysicsHong KongChina University of Hong Kong Department of Electrical and Electronic EngineeringHong KongChina Guilin University of Electronic Technology Guangxi Key Laboratory of Optoelectronic Information ProcessingSchool of Optoelectronic EngineeringGuilinChina Oklahoma State University School of Electrical and Computer EngineeringStillwaterOklahomaUnited States

Metasurfaces have enabled the realization of several optical functionalities over an ultrathin platform,fostering the exciting field of flat *** metasurfaces are achieved by arranging a layout of static meta-atoms to imprint a desired operation on the impinging wavefront,but their functionality cannot be *** and programmability of metasurfaces are the next important step to broaden their impact,adding customized on-demand functionality in which each meta-atom can be individually *** demonstrate a mechanical metasurface platform with controllable rotation at the meta-atom level,which can implement continuous Pancharatnam–Berry phase control of circularly polarized *** the proof-of-concept experiments,we demonstrate metalensing,focused vortex beam generation,and holographic imaging in the same metasurface template,exhibiting versatility and superior *** dynamic control of electromagnetic waves using a single,low-cost metasurface paves an avenue towards practical applications,driving the field of reprogrammable intelligent metasurfaces for a variety of applications.

关键词： reprogrammable metasurfaces Pancharatnam-Berry phase mechanical metasurfaces microwaves

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Fuzzy Logic Method Design for Landslide Vulnerability 4

Fuzzy Logic Method Design for Landslide Vulnerability

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4th International Conference on Energy, Environment, Epidemiology and Information System, ICENIS 2019

作者： Wardhana, Made Dandy Sofwan, Aghus Setiawan, Iwan Magister Program of Electrical Engineering Diponegoro University Semarang Indonesia Department of Electrical Engineering Faculty of Engineering Diponegoro University Semarang Indonesia

Landslide is one of the most frequently happened disasters in Indonesia due to weather and climate characteristics, regional topography, and geological structures that make this country have many potential landslide areas. The main goal of this study is to apply fuzzy logic to the landslide detection sensor so that it is easier to find out areas prone to landslides. The fuzzy logic method uses five parameters to analyze the landslide area. These parameters are rainfall, land slope, moisture content in two different soil depths, and ground vibration. They are used to determine the vulnerability level of landslide area is very safe, relatively safe, relatively potential, potentially and very potential. Fuzzification, inference, and defuzzification performed on each data in the analysis process to determine the vulnerability of landslides, and the parameters and weighting rules are according to government regulations. From the results of the study, it was concluded that intelligent systems based on fuzzy logic can be used to determine the level of vulnerability of landslides in a specified area. © The Authors, published by EDP Sciences, 2019.

关键词： Landslides

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Simulation of arrow-shaped micromixer with obstacles in blood plasma mixing

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AIP Conference Proceedings 2024年第1期3080卷

作者： Ziyan Muhammad Aqsha Basari Mohammad Akita Indianto Ridho Irwansyah Muhammad Satrio Utomo Siti Fauziyah Rahman Biomedical Engineering Study Program Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Research Center for Biomedical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Energy Systems Engineering Graduate Program Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Department of Mechanical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Research Center for Metallurgy National Research and Innovation Agency Komplek PUSPIPTEK Setu Tangerang Selatan Banten 15314 Indonesia

In recent years, several applications of micromixers have been reported to have a number of advantages, including the use of small amounts of plasma, short reaction times, and good reaction efficiency. The samples analyzed in this study were blood plasma and distilled water. The process is carried out by passive mixing which is based on a microchannel structure to enhance the diffusion of molecules for efficient mixing. The arrow shape was chosen as the micromixer design because it has a better blending performance than the T and Y shapes. The types of obstacles also used to improve the mixing process. The simulation was carried out on COMSOL Multiphysics software version 5.6. The results showed better mixing results for the micromixer design with triangle right facing obstacles with the highest Reynolds number was 9.4326. Then followed by ellips obstacles with a value of 9.4322, then without obstacles that is 9.4309, after that the triangle left facing with a value of 9.4006, and finally the lowest Reynolds number is a design with a diamond obstacles of 9.2514.

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Sequential minimum optimization algorithm with small sample size estimators

arXiv

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arXiv 2023年

作者： Roga, Wojciech Ono, Takafumi Takeoka, Masahiro Department of Electronics and Electrical Engineering Keio University 3-14-1 Hiyoshi Kohoku Kanagawa Yokohama223-8522 Japan Program in Advanced Materials Science Faculty of Engineering and Design Kagawa University 2217-20 Hayashi-cho Kagawa Takamatsu761-0396 Japan JST PRESTO 4-1-8 Honcho Saitama Kawaguchi332-0012 Japan 4-2-1 Nukuikita Koganei Tokyo184-8795 Japan

Sequential minimum optimization is a machine-learning global search training algorithm. It is applicable when the functional dependence of the cost function on a tunable parameter given the other parameters can be cheaply determined. This assumption is satisfied by quantum circuits built of known gates. We apply it to photonics circuits where the additional challenge appears: low frequency of coincidence events lowers the speed of the algorithm. We propose to modify the algorithm such that small sample size estimators are enough to successfully run the machine learning task. We demonstrate the effectiveness of the modified algorithm applying it to a quantum optics classifier with data reuploading. © 2023, CC BY.

关键词： Machine learning

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Thruster-assisted Center Manifold Shaping in Bipedal Legged Locomotion

Thruster-assisted Center Manifold Shaping in Bipedal Legged ...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Arthur C. B. de Oliveira Alireza Ramezani PhD student in Electrical and Computer Engineering Northeastern University Boston MA USA Faculty of Electrical and Computer Engineering Northeastern University Boston MA USA

ISBN: (数字)9781728167947

ISBN: (纸本)9781728167954

This work tries to contribute to the design of legged robots with capabilities boosted through thrusterassisted locomotion. Our long-term goal is the development of robots capable of negotiating unstructured environments, including land and air, by leveraging legs and thrusters collaboratively. These robots could be used in a broad number of applications including search and rescue operations, space exploration, automated package handling in residential spaces and digital agriculture, to name a few. In all of these examples, the unique capability of thruster-assisted mobility greatly broadens the locomotion designs possibilities for these systems. In an effort to demonstrate thrusters effectiveness in the robustification and efficiency of bipedal locomotion gaits, this work explores their effects on the gait limit cycles and proposes new design paradigms based on shaping these center manifolds with strong foliations. Unilateral contact force feasibility conditions are resolved in an optimal control scheme.

关键词： Legged locomotion Limit-cycles Manifolds Robustness Dynamics Force

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Brain Tumor Detection and Segmentation Using Deep Learning Models

Brain Tumor Detection and Segmentation Using Deep Learning M...

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Artificial Intelligence (WSAI), World Symposium on

作者： Moses Kazeem Abiodun Abidemi Emmanuel Adeniyi Joseph Bamidele Awotunde Halleluyah Aworinde George Tinuoye Agbotiname Lucky Imoize Chun-Ta Li Cheng-Chi Lee Department of Computer Science Landmark University Omu-Aran Kwara State Nigeria Department of Computer Science Bowen University Iwo Osun State Nigeria Department of Computer Science University of Ilorin Ilorin Kwara State Nigeria Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Akoka Nigeria Bachelor's Program of Artificial Intelligence and Information Security Fu Jen Catholic University New Taipei City Taiwan Department of Library and Information Science Fu Jen Catholic University New Taipei City Taiwan

ISBN: (数字)9798350374162

ISBN: (纸本)9798350374179

This study focuses on brain tumor detection and segmentation using Convolutional Neural Networks (CNN) with architectures of Fully Convolutional Net-work (FCN) and VGG16. The dataset imported for this study consists of brain MRI images, which were preprocessed to improve the overall image resolution. Data augmentation techniques were applied to heighten the variability and volume of the training data. For feature extraction, CNN models were utilized, specifically the VGG16 architectures. This model was trained on a preprocessed dataset to learn the important features associated with the presence of brain tumor. Image segmentation was performed to precisely outline and identify the tumor region within the brain images. FCN architecture was employed for this task, which allowed pixel-level classification of tumor regions. Finally, image classification was carried out to group brain images based on the absence or presence of a tumor. The trained models were evaluated using accuracy, precision, recall and F1score as the performance metrics. The results of the study demonstrated promising outcomes, achieving an accuracy score of 93% and a precision, recall and f1score ranging from 75% to 100% based on the specific type of tumor enlisted. This indicates that the developed CNN models, with the FCN and VGG16 architectures, effectively detect and segment brain tumors from MRI images. The findings of this study contribute to the field of medical image analysis and gives a foundation for further research and development in brain tumor diagnosis and treatment. The study recommends the use of more deep learning algorithms for the process of detecting brain tumors.

关键词： Deep learning Image segmentation Accuracy Magnetic resonance imaging Computational modeling Brain tumors Brain modeling Distance measurement Classification algorithms Convolutional neural networks

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Speech recognition approach using descend-delta-mean and MFCC algorithm 16

Speech recognition approach using descend-delta-mean and MFC...

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16th International Conference on electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2019

作者： Nosan, Anuruk Sitjongsataporn, Suchada Mahanakorn University of Technology Electrical Engineering Graduate Program Faculty of Engineering Bangkok10530 Thailand

ISBN: (纸本)9781728133614

In this paper, we present the improving the feature extraction method of the MFCC algorithm for noise robustness when there is interference in the speech input signal. The various parameter extraction with new technique as the descend-delta-mean and mel frequency cepstral coefficients is called the DDMMFCC. The purpose is to require the noise robustness of feature vector extracted from the speech signal with the characteristic coefficients of the DDM-MFCC algorithm. In order to increase the speech and speakers recognition accuracy rate, the DDM technique is a new method of finding the average value of a descendant of power spectrum magnitude. The process consisting method of rearranging magnitude of the spectral power is reduced to a minimum in each frequency band of the speech signal, and to find the difference in the arrangement. Finally, to determine the value of mean. The experiment results of the proposed robustness feature extraction DDM-MFCC algorithm and the conventional of MFCC algorithm is compared, when the training and testing dataset is the 0-9 Isolated THAI digits speech of 10 THAI speakers recognition. With additive random white Gaussian noise is added for testing dataset with signal to noise ratio (SNR) as 0, 5, 10, 15 and 20 dB, respectively. Simulation results of proposed DMM-MFCC algorithm are shown higher rate of recognition accuracy rate than the conventional MFCC algorithm. © 2019 IEEE.

关键词： Signal to noise ratio

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Renewable Biodiesel Production from Oleaginous Yeast Biomass Using Industrial Wastes

Renewable Biodiesel Production from Oleaginous Yeast Biomass...

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2019 Research, Invention, and Innovation Congress, RI2C 2019

作者： Kongruang, Sasithorn Roytrakul, Sittiruk Sriariyanun, Malinee Bioprocess Engineering and Biotechnology Center Department of Biotechnology Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut' S University of Technology North Bangkok Bangkok Thailand Chemical and Process Engineering Program Sirindhorn International Thai-German Graduate School of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand

The accumulation lipid from oleaginous microorganisms is recognized as a second generation fuel. Biooil is known to as intracellular product of oily yeast utilizing various carbon substrates and converting different quantities of lipids in the form of triacylglycerols. This second generation fuel can be used to make biodiesel via a transesterification process. This study investigated the morphological characteristics of eight strains of Thai oleaginous yeasts via microscopy and analyzed the fatty acid profiling of yeasts cultured in three carbon sources: glucose, sugar cane molasses and crude glycerol in order to estimate biodiesel properties. To approach this goal, batch fermentations were used to culture eight yeast strains, Rhodosporidium toruloides TISTR 5123, TISTR 5154, TISTR 5149, Yarrowia lipolytica TISTR 5054, TISTR 5151, TISTR 5621, Rhodotorula glutinis TISTR 5159 and Rhodotorula graminis TISTR 5124 for 96 h under 30°C at 250 rpm. Result revealed that eight yeast strains contained significant amounts of fatty acids and lipids and accumulated mainly palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C 18:1) and linoleic acid (C18:2), and they are suitable for the production of biodiesel. Fatty acid productions and profiles indicated that these yeast strains can be potentially used as the triacylglycerols producers for biodiesel production. © 2020 The Authors, published by EDP Sciences.

关键词： Lipids

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