Multi-bounce Returns for Specular Surface Mapping from Consumer-grade Flash LiDAR by Lin, Tsung-Han

“…In addition to 3D reconstruction, we show multi-bounce returns help to enhance performances on applications such as segmentation and novel view synthesis. Our method can be combined with these state-of-the-art learned-based model, enhancing its robustness by discerning ambiguous scenarios. …”
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Phonetic Faithfulness in Phonological Opacity by Kim, Yeong-Joon

“…The results of typological surveys encompassing 87 counterfeeding and 65 counterbleeding interactions across languages support this prediction, revealing that opacified processes are subject to a narrow range of markedness conditions, such as coarticulatory assimilation (e.g., palatalization) and durational adjustments (e.g., segmental weakening). Other types of phonological processes, particularly non-natural ones, are only rarely, if ever, opacified. …”
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Game of drones by Wei, LuoBin

“…Augmentation of data-points within gate position via gate segmentation for a more effective trajectory planning is also explored. …”
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Deep learning-based algorithm for synthetic aperture radar despeckling by Wang, Yuxuan

“…However, SAR images inherently suffer from speckle noise, which severely hinders the effective implementation of subsequent tasks such as image segmentation and target detection. Therefore, research on SAR image denoising and target detection technologies is of great significance. …”
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Universal machine learning classifier using extreme learning machines by Chen, Jinnan

“…Also, it can give us some accurate prediction based on the currently collected data and then automatically realize the objective of trend prediction, pattern recognition or segmentation like the development of autonomous vehicles, or the stock market forecasting. …”
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Image processing and machine learning techniques for Chagas disease detection and identification by Rada, Lavdie, Azzawi, Inass, Kumar, Preet, Brito-Loeza, Carlos Francisco, Karabağ, Cefa, Reyes-Aldasoro, Constantino C.

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Building fabric improvement and heat pump deployment: a set of policy conundrums by Killip, G, Topouzi, M, Fawcett, T

“…</p> <br> <p>The paper examines building interventions through the concept of 'trigger points.' It evaluates a segmented market approach and proposes a policy framework that emphasises 'understanding first' as a strategy to facilitate informed decision-making, rather than imposing specific measures. …”

Enhanced Approach of Decision Making in Determining Contemporary Critical Preferential Factors and Location Decisions for Residential Project using MCDM Technique (S/O 13903) by Lamsali, Hendrik, Mad Lazim, Halim, Abdul Rahim, Mohd Kamarul Irwan, Osman, Wan Nadzri, Salleh, Mohamed Najib

“…The study can be further expanded by conducting consumers’ and markets’ segmentation analysis. Developers’ preferences and priorities can also be explored further using the Multiple-criteriadecision-making (MCDM) techniques.…”
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Treatment options to support the elimination of Hepatitis C: an open label, factorial randomised controlled trial by Cooke, G, Le Manh, H, Flower, B, McCabe, L, Vu Thu Kim, H, Vo Thi, T, Dang Trong, T, Nguyen Thanh, D, Le Thanh, P, Dao Bach, K, Nguyen Thi Chau, A, Pham Ngoc, T, Vu Thu Thu, H, Dang Thi, B, Nguyen Kim, T, Ansari, A, Le Ngoc, C, Vo Minh, Q, Nguyen Thi Ngoc, P, Le Thi, T, Nguyen Bao, T, Kestelyn, E, Kingsley, C, Van Doorn, R, Rahman, M, Pett, S, Thwaites, G, Barnes, E, Day, J, Nguyen Van Vinh, C, Walker, AS

“…No randomised trials have compared these regimens and high cure rates may be achievable with shorter durations of therapy.…”

A study on giant panda recognition based on images of a large proportion of captive pandas by Chen, Peng, Swarup, Pranjal, Matkowski, Wojciech Michal, Kong, Adams Wai Kin, Han, Su, Zhang, Zhihe, Rong, Hou

“…For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. …”
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Improved 5G network slicing for enhanced QoS against attack in SDN environment using deep learning by Abood, Mohammed Salah, Hua, Wang, Virdee, Bal Singh, He, Dongxuan, Fathy, Maha, Yusuf, Abdulganiyu Abdu, Jamal, Omar, Elwi, Taha A., Alibakhshikenari, Mohammad, Kouhalvandi, Lida, Ahmad, Ashfaq

“…Moreover, network slicing significantly enhances Quality of Service (QoS) by segmenting services based on bandwidth. Future research will concentrate on real-world implementation, encompassing diverse dataset evaluations, and assessing the model's adaptability across varied scenarios.…”
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Modélisation des interactions en Italie du Nord au premier âge du Fer: de la circulation de parures aux réseaux d’influences culturelles by Cicolani, V, Huet, T, Zamboni, L

“…Applied for each period, this segmentation is represented on a map by assigning the color of the groups (clusters) to the sites, thus facilitating spatial reading and geographical interpretation of the results. …”

An investigation into real-time surface crack classification and measurement for structural health monitoring using transfer learning convolutional neural networks and Otsu method by Mazleenda Mazni, Mazleenda Mazni, Husain, Abdul Rashid, Shapiai, Mohd. Ibrahim, Ibrahim, Izni Syahrizal, Devi Willieam Anggara, Devi Willieam Anggara, Zulkifli, Riyadh

“…Incorporating the Otsu method for image segmentation, our system accurately assesses individual crack sizes. …”
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Drug interaction between acetyltanshinone IIA and rapamycin in breast cancer cells by Wong, De Pin

“…Developing in vitro drug combination study is essential for the development of new and effective combination regimens. In this project, the objective is to investigate the synergistic potential between two anti breast cancer agent, rapamycin and acetyltanshinone IIA (ATA) in breast cancer cells. …”
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In Vivo RNA Delivery to Hematopoietic Stem and Progenitor Cells via Targeted Lipid Nanoparticles by Shi, Dennis, Toyonaga, Sho, Anderson, Daniel G

“…However, these therapies have several limitations owing to the manufacturing complexities and toxicity resulting from required conditioning regimens. Here, we developed a c-kit (CD117) antibody-targeted lipid nanoparticle (LNP) that, following a single intravenous injection, can deliver RNA (both siRNA and mRNA) to HSCs in vivo in rodents. …”
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Disposition kinetics of tylosin administered intravenously and intramuscularly in Desert Sheep and Nubian Goats by Taha, A.A., Elsheikh, H.A., Khalafalla, A.E., Osman, I. A. M., Abdullah, A. Salam

“…The present study has shown that, despite the significant differences in some of the drug pharmacokinetic parameters between sheep and goats for the i.v. route, identical intravenous and intramuscular dosage regimens of tylosin may be recommended for the two species.…”
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Targeted hematopoietic stem cell depletion through SCF-blockade by Chan, Yan Y., Ho, Pui Y., Dib, Carla, Swartzrock, Leah, Rayburn, Maire, Willner, Hana, Ko, Ethan, Ho, Katie, Down, Julian D., Wilkinson, Adam C., Nakauchi, Hiro, Denis, Morgane, Cool, Taylor, Czechowicz, Agnieszka

“…Further, to augment efficacy, combination regimens were also explored. Results We confirm that only ACK2 inhibits SCF binding fully and prevents HSC proliferation in vitro. …”
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Impacts of ancillary services on airline revenue management by Lu, Yuxuan(Aeronautics scientist)Massachusetts Institute of Technology.

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EyeTrAES: Fine-grained, Low-Latency Eye Tracking via Adaptive Event Slicing by Sen, Argha, Bandara, Nuwan, Gokarn, Ila, Kandappu, Thivya, Misra, Archan

“…EyeTrAES then applies lightweight image processing functions over accumulated event frames from just a single eye to perform pupil segmentation and tracking (as opposed to gaze-based techniques that require simultaneous tracking of both eyes). …”
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Deep neural network technique for automated detection of ADHD and CD using ECG signal by Loh, Hui Wen, Ooi, Chui Ping, Oh, Shu Lih, Barua, Prabal Datta, Tan, Yi Ren, Molinari, Filippo, March, Sonja, Acharya, U. Rajendra, Fung, Daniel Shuen Sheng

“…Methods: The dataset used in this study consist of ECG data collected from 45 ADHD, 62 ADHD+CD, and 16 CD patients at the Child Guidance Clinic in Singapore. The ECG data were segmented into 2 s epochs and directly used to train our 1-dimensional (1D) convolutional neural network (CNN) model. …”
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