Showing 321 - 340 results of 1,675 for search '((spinnae OR ((pinge OR (hinge OR hing)) OR fine)) OR (((pina OR spinn) OR (aina OR anna)) OR pin))', query time: 0.23s Refine Results
  1. 321
  2. 322

    Measuring membrane capacitance during a depolarizing stimulus by Chen, Peng., Gillis, Kevin., Xue, Renhao., Pui, Tze Sian.

    Published 2010
    “…It is critical to resolve the highly dynamic kinetic steps along the molecular cascade of exocytosis in order to pin down the specific actions of regulatory molecules and eventually decipher this complex and fundamental process.…”
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    Research Report
  3. 323

    Observation of an acoustic octupole topological insulator by Xue, Haoran, Ge, Yong, Sun, Hong-Xiang, Wang, Qiang, Jia, Ding, Guan, Yi-Jun, Yuan, Shou-Qi, Chong, Yidong, Zhang, Baile

    Published 2021
    “…We observe zero-dimensional topological corner states, one-dimensional gapped hinge states, two-dimensional gapped surface states, and three-dimensional gapped bulk states, representing the hierarchy of octupole, quadrupole and dipole moments. …”
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    Journal Article
  4. 324

    Development of a counter-UAV system by Tang, Wen Yue

    Published 2022
    “…Upon testing, the firing pin mechanism was found to be unable to reliably puncture the CO2 canister, even after improvements. …”
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    Final Year Project (FYP)
  5. 325
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  8. 328

    Soil-water characteristic curves of hydrophobic sand by Tan, Nicole Shi Qi

    Published 2022
    “…In this project, the effect of hydrophobicity is investigated using fine and coarse sands. Fine sand was made hydrophobic and mixed with either fine or coarse sand such that sand mixtures of hydrophobicity 20%, 50% and 80% by mass were obtained. …”
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    Final Year Project (FYP)
  9. 329

    Anomaly detection in aerosol jet printing via computer vision & machine learning by Ang, Ryan Wei Hao

    Published 2023
    “…Hence, this paper aims to develop, and more importantly, fine-tune, an in-situ monitoring algorithm that will be implemented into the Aerosol Jet Printing system with the help of an Object Detection Model, which hinges upon the principles of Deep Learning (DL), and Computer Vision (CV). …”
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    Final Year Project (FYP)
  10. 330

    Structural performance of recycled aggregate concrete-filled stainless steel tube columns by Tan, Chia Wei

    Published 2020
    “…The experiment involved 12 RACFSST columns tested under pin-ended condition, as well as material tests and initial global geometric imperfection measurements. …”
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    Final Year Project (FYP)
  11. 331

    Design and 3D printing of reconfigurable structures by Teo, Ee Hian

    Published 2021
    “…The structure is made up of single modular units being repeatedly fixed together, this leads to the structure to isolate single modular units that are damaged, allowing it to be easily pin-pointed and replaced by fabricating another similar single unit, this cut cost as the structure can be salvaged by replacing a single unit instead of the whole structure.…”
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    Final Year Project (FYP)
  12. 332

    Tie the knot - a step by step wedding planner by Alex Arvin S Susaipillai

    Published 2018
    “…The creation comprises essential management tools such as wedding checklist, reminders, budget tracker, guestlist, online electronic invitation and RSVP system with SMS function, seating plan, calendar function, vendor list, pin board, wedding day scheduler and chat function…”
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    Final Year Project (FYP)
  13. 333

    Investigation of the contribution of bioaerosol loading to indoor PM pollution on university campus in Singapore by Lee, Brandon Jia Hao

    Published 2022
    “…Fine particles could be mitigated safely for occupants with an electrostatic precipitator and future work could expound on elevated fungi concentrations in an indoor environment and fine particle mitigation strategies.…”
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    Final Year Project (FYP)
  14. 334

    Interpreting learned feedback patterns in large language models by Marks, L, Abdullah, A, Neo, C, Arike, R, Krueger, D, Torr, P, Barez, F

    Published 2024
    “…To test this, we train probes to estimate the feedback signal implicit in the activations of a fine-tuned LLM. We then compare these estimates to the true feedback, measuring how accurate the LFPs are to the fine-tuning feedback. …”
    Conference item
  15. 335
  16. 336

    Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits by Evangelou, Evangelos, Warren, Helen R., Mosen-Ansorena, David, Mifsud, Borbala, Pazoki, Raha, Gao, He, Ntritsos, Georgios, Dimou, Niki, Cabrera, Claudia P., Ibrahim Karaman, Ng, Fu Liang, Evangelou, Marina, Witkowska, Katarzyna, Tzanis, Evan, Hellwege, Jacklyn N., Giri, Ayush, Edwards, Digna R. Velez, Sun, Yan V., Cho, Kelly, Gaziano, J. Michael, Wilson, Peter W. F., Tsao, Philip S., Kovesdy, Csaba P., Esko, Tonu, Mägi, Reedik, Milani, Lili, Almgren, Peter, Boutin, Thibaud, Debette, Stéphanie, Ding, Jun, Giulianini, Franco, Holliday, Elizabeth G., Jackson, Anne U., Li-Gao, Ruifang, Lin, Wei-Yu, Luan, Jian'an, Mangino, Massimo, Oldmeadow, Christopher, Prins, Bram Peter, Qian, Yong, Sargurupremraj, Muralidharan, Shah, Nabi, Surendran, Praveen, Thériault, Sébastien, Verweij, Niek, Willems, Sara M., Zhao, Jing-Hua, Amouyel, Philippe, Connell, John, de Mutsert, Renée, Doney, Alex S. F., Farrall, Martin, Menni, Cristina, Morris, Andrew D., Raymond Noordam, Paré, Guillaume, Poulter, Neil R., Shields, Denis C., Stanton, Alice, Thom, Simon, Abecasis, Gonçalo, Najaf Amin, Arking, Dan E., Ayers, Kristin L., Barbieri, Caterina M., Batini, Chiara, Bis, Joshua C. M., Blake, Tineka, Bochud, Murielle, Boehnke, Michael, Boerwinkle, Eric, Boomsma, Dorret I., Bottinger, Erwin P., Braund, Peter S., Brumat, Marco, Campbell, Archie, Campbell, Harry, Chakravarti, Aravinda, Chambers, John Campbell, Chauhan, Ganesh, Ciullo, Marina, Cocca, Massimiliano, Collins, Francis, Cordell, Heather J., Davies, Gail, de Borst, Martin H., de Geus, Eco J., Deary, Ian J., Deelen, Joris, Del Greco M., Fabiola, Demirkale, Cumhur Yusuf, Dörr, Marcus, Ehret, Georg B., Elosua, Roberto, Enroth, Stefan, Erzurumluoglu, A. Mesut, Ferreira, Teresa, Frånberg, Mattias, Franco, Oscar H., Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Goel, Anuj, Gow, Alan J., Gudnason, Vilmundur, Guo, Xiuqing, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B., Harris, Sarah E., Hartman, Catharina A., Havulinna, Aki S., Hicks, Andrew A., Hofer, Edith, Hofman, Albert, Hottenga, Jouke-Jan, Huffman, Jennifer E., Hwang, Shih-Jen, Ingelsson, Erik, James, Alan, Jansen, Rick, Jarvelin, Marjo-Riitta, Joehanes, Roby, Johansson, Åsa, Johnson, Andrew D., Joshi, Peter K., Jousilahti, Pekka, Jukema, J. Wouter, Jula, Antti, Kähönen, Mika, Kathiresan, Sekar, Keavney, Bernard D., Khaw, Kay-Tee, Knekt, Paul, Knight, Joanne, Kolcic, Ivana, Kooner, Jaspal S., Koskinen, Seppo, Kristiansson, Kati, Kutalik, Zoltan, Laan, Maris, Larson, Marty, Launer, Lenore J., Lehne, Benjamin, Lehtimäki, Terho, Liewald, David C. M., Lin, Li, Lind, Lars, Lindgren, Cecilia M., Liu, YongMei, Loos, Ruth J. F., Lopez, Lorna M., Lu, Yingchang, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamasoula, Chrysovalanto, Marrugat, Jaume, Marten, Jonathan, Milaneschi, Yuri, Morgan, Anna, Morris, Andrew P., Morrison, Alanna C., Munson, Peter J., Nalls, Mike A., Nandakumar, Priyanka, Nelson, Christopher P., Niiranen, Teemu, Nolte, Ilja M., Nutile, Teresa, Oldehinkel, Albertine J., Oostra, Ben A., O'Reilly, Paul F., Org, Elin, Padmanabhan, Sandosh, Palmas, Walter, Palotie, Aarno, Pattie, Alison, Penninx, Brenda W. J. H., Perola, Markus, Peters, Annette, Polasek, Ozren, Pramstaller, Peter P., Nguyen, Quang Tri, Raitakari, Olli T., Ren, Meixia, Rettig, Rainer, Rice, Kenneth, Ridker, Paul M., Ried, Janina S., Riese, Harriëtte, Ripatti, Samuli, Robino, Antonietta, Rose, Lynda M., Rotter, Jerome I., Rudan, Igor, Ruggiero, Daniela, Saba, Yasaman, Sala, Cinzia F., Salomaa, Veikko, Samani, Nilesh J., Sarin, Antti-Pekka, Schmidt, Reinhold, Schmidt, Helena, Shrine, Nick, Siscovick, David, Smith, Albert V., Snieder, Harold, Sõber, Siim, Sorice, Rossella, Starr, John M., Stott, David J., Strachan, David P., Strawbridge, Rona J., Sundström, Johan, Swertz, Morris A., Taylor, Kent D., Teumer, Alexander, Tobin, Martin D., Tomaszewski, Maciej, Toniolo, Daniela, Traglia, Michela, Trompet, Stella, Tuomilehto, Jaakko, Tzourio, Christophe, Uitterlinden, André G., Vaez, Ahmad, van der Most, Peter J., van Duijn, Cornelia M., Vergnaud, Anne-Claire, Verwoert, Germaine C., Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Vuckovic, Dragana, Watkins, Hugh, Wild, Sarah H., Willemsen, Gonneke, Wilson, James F., Wright, Alan F., Yao, Jie, Zemunik, Tatijana, Zhang, Weihua, Attia, John R., Butterworth, Adam S., Chasman, Daniel I., Conen, David, Cucca, Francesco, Danesh, John, Hayward, Caroline, Howson, Joanna M. M., Laakso, Markku, Lakatta, Edward G., Langenberg, Claudia, Melander, Olle, Mook-Kanamori, Dennis O., Palmer, Colin N. A., Risch, Lorenz, Scott, Robert A., Scott, Rodney J., Sever, Peter, Spector, Tim D., van der Harst, Pim, Wareham, Nicholas J., Zeggini, Eleftheria, Levy, Daniel, Munroe, Patricia B., Newton-Cheh, Christopher, Brown, Morris J., Metspalu, Andres, Hung, Adriana M., O'Donnell, Christopher J., Edwards, Todd L., Psaty, Bruce M., Tzoulaki, Ioanna, Barnes, Michael R., Wain, Louise V., Elliott, Paul, Caulfield, Mark J.

    Published 2020
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    Journal Article
  17. 337

    Genetic algorithm based deep learning model adaptation for improvising the motor imagery classification by R, Vishnupriya, Robinson, Neethu, M, Ramasubba Reddy

    Published 2024
    “…Transfer learning methods such as adaptation or fine-tuning can be used on the pre-trained model to improve the performance. …”
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    Journal Article
  18. 338

    SimSC: a simple framework for semantic correspondence with temperature learning by Li, X, Han, K, Wan, X, Prisacariu, VA

    Published 2023
    “…We discover that when fine-tuning ImageNet pre-trained backbone on the semantic matching task, L2 normalization of the feature map, a standard procedure in feature matching, produces an overly smooth matching distribution and significantly hinders the fine-tuning process. …”
    Conference item
  19. 339

    Finite element analysis on post-buckling of thin-walled structures using ANSYS by Theint, Yi Mon

    Published 2015
    “…The results obtained were checked against experimental data and led to the development and the revision of design procedures for the pin-ended lipped column and hollow box section.…”
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    Final Year Project (FYP)
  20. 340

    Field instrumentation for performance assessment of Geobarrier System by Rahardjo, Harianto, Qian, Zhai, Satyanaga, Alfrendo, Leong, Eng Choon, Wang, Chien Looi, Wong, Johnny Liang Heng

    Published 2019
    “…The saturated hydraulic conductivity of a coarse-grained material is normally higher than that of a fine-grained material. However, the unsaturated hydraulic conductivity of the coarse-grained material decreases much faster than that of the fine-grained material with increasing matric suction and consequently the coarse-grained material can be less permeable than the fine-grained material in unsaturated condition. …”
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    Journal Article