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Статті в журналах з теми "Deep CCA"

Автор: Grafiati

Опубліковано: 6 вересня 2023

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1

Lindenbaum, Ofir, Neta Rabin, Yuri Bregman, and Amir Averbuch. "Seismic Event Discrimination Using Deep CCA." IEEE Geoscience and Remote Sensing Letters 17, no. 11 (2020): 1856–60. http://dx.doi.org/10.1109/lgrs.2019.2959554.

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2

Karami, Mahdi, and Dale Schuurmans. "Deep Probabilistic Canonical Correlation Analysis." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (2021): 8055–63. http://dx.doi.org/10.1609/aaai.v35i9.16982.

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We propose a deep generative framework for multi-view learning based on a probabilistic interpretation of canonical correlation analysis (CCA). The model combines a linear multi-view layer in the latent space with deep generative networks as observation models, to decompose the variability in multiple views into a shared latent representation that describes the common underlying sources of variation and a set of viewspecific components. To approximate the posterior distribution of the latent multi-view layer, an efficient variational inference procedure is developed based on the solution of pr

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3

Gao, Quanxue, Huanhuan Lian, Qianqian Wang, and Gan Sun. "Cross-Modal Subspace Clustering via Deep Canonical Correlation Analysis." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 3938–45. http://dx.doi.org/10.1609/aaai.v34i04.5808.

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For cross-modal subspace clustering, the key point is how to exploit the correlation information between cross-modal data. However, most hierarchical and structural correlation information among cross-modal data cannot be well exploited due to its high-dimensional non-linear property. To tackle this problem, in this paper, we propose an unsupervised framework named Cross-Modal Subspace Clustering via Deep Canonical Correlation Analysis (CMSC-DCCA), which incorporates the correlation constraint with a self-expressive layer to make full use of information among the inter-modal data and the intra

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4

Li, Bin, and Yuqing He. "Computational Logistics for Container Terminal Handling Systems with Deep Learning." Computational Intelligence and Neuroscience 2021 (April 26, 2021): 1–18. http://dx.doi.org/10.1155/2021/5529914.

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Container terminals are playing an increasingly important role in the global logistics network; however, the programming, planning, scheduling, and decision of the container terminal handling system (CTHS) all are provided with a high degree of nonlinearity, coupling, and complexity. Given that, a combination of computational logistics and deep learning, which is just about container terminal-oriented neural-physical fusion computation (CTO-NPFC), is proposed to discuss and explore the pattern recognition and regression analysis of CTHS. Because the liner berthing time (LBT) is the central ind

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5

Jain, Pankaj K., Abhishek Dubey, Luca Saba, et al. "Attention-Based UNet Deep Learning Model for Plaque Segmentation in Carotid Ultrasound for Stroke Risk Stratification: An Artificial Intelligence Paradigm." Journal of Cardiovascular Development and Disease 9, no. 10 (2022): 326. http://dx.doi.org/10.3390/jcdd9100326.

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Stroke and cardiovascular diseases (CVD) significantly affect the world population. The early detection of such events may prevent the burden of death and costly surgery. Conventional methods are neither automated nor clinically accurate. Artificial Intelligence-based methods of automatically detecting and predicting the severity of CVD and stroke in their early stages are of prime importance. This study proposes an attention-channel-based UNet deep learning (DL) model that identifies the carotid plaques in the internal carotid artery (ICA) and common carotid artery (CCA) images. Our experimen

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6

Jiang, Guoping, Wu Zhang, Ting Wang, et al. "Characteristics of genomic alterations in Chinese cholangiocarcinoma patients." Japanese Journal of Clinical Oncology 50, no. 10 (2020): 1117–25. http://dx.doi.org/10.1093/jjco/hyaa088.

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Abstract Objective Cholangiocarcinoma (CCA) is a primary malignancy, which is often diagnosed as advanced and inoperable due to the lack of effective biomarkers and poor sensitivity of clinical diagnosis. Here, we aimed to identify the genomic profile of CCA and provided molecular evidence for further biomarker development. Methods The formalin-fixed paraffin-embedded and matching blood samples were sequenced by deep sequencing targeting 450 cancer genes and genomic alteration analysis was performed. Tumor mutational burden (TMB) was measured by an algorithm developed in-house. Correlation ana

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7

Yuan, Fei, Xiaoquan Ke, and En Cheng. "Joint Representation and Recognition for Ship-Radiated Noise Based on Multimodal Deep Learning." Journal of Marine Science and Engineering 7, no. 11 (2019): 380. http://dx.doi.org/10.3390/jmse7110380.

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Ship recognition based on ship-radiated noise is one of the most important and challenging subjects in underwater acoustic signal processing. The recognition methods for ship-radiated noise recognition include traditional methods and deep learning (DL) methods. Developing from the DL methods and inspired by audio–video speech recognition (AVSR), the paper further introduces multimodal deep learning (multimodal-DL) methods for the recognition of ship-radiated noise. In this paper, ship-radiated noise (acoustics modality) and visual observation of the ships (visual modality) are two different mo

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8

Chapman, James, and Hao-Ting Wang. "CCA-Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic CCA methods in a scikit-learn style framework." Journal of Open Source Software 6, no. 68 (2021): 3823. http://dx.doi.org/10.21105/joss.03823.

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9

Yu, Yi, Suhua Tang, Kiyoharu Aizawa, and Akiko Aizawa. "Category-Based Deep CCA for Fine-Grained Venue Discovery From Multimodal Data." IEEE Transactions on Neural Networks and Learning Systems 30, no. 4 (2019): 1250–58. http://dx.doi.org/10.1109/tnnls.2018.2856253.

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10

Peng, Yun, Shenyi Zhao, and Jizhan Liu. "Fused Deep Features-Based Grape Varieties Identification Using Support Vector Machine." Agriculture 11, no. 9 (2021): 869. http://dx.doi.org/10.3390/agriculture11090869.

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Proper identification of different grape varieties by smart machinery is of great importance to modern agriculture production. In this paper, a fast and accurate identification method based on Canonical Correlation Analysis (CCA), which can fuse different deep features extracted from Convolutional Neural Network (CNN), plus Support Vector Machine (SVM) is proposed. In this research, based on an open dataset, three types of state-of-the-art CNNs, seven species of deep features, and a multi-class SVM classifier were studied. First, the images were resized to meet the input requirements of a CNN.

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11

Zeng, Donghuo, Yi Yu, and Keizo Oyama. "Deep Triplet Neural Networks with Cluster-CCA for Audio-Visual Cross-Modal Retrieval." ACM Transactions on Multimedia Computing, Communications, and Applications 16, no. 3 (2020): 1–23. http://dx.doi.org/10.1145/3387164.

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12

Koźlenia, Dawid, Jarosław Domaradzki, and Izabela Trojanowska. "MULTIVARIATE RELATIONSHIPS BETWEEN MORPHOLOGY, MOVEMENT PATTERNS AND SPEED ABILITIES IN ELITE YOUNG, MALE ATHLETES." Kinesiologia Slovenica 26, no. 1 (2020): 33–45. http://dx.doi.org/10.52165/kinsi.26.1.33-45.

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Speed and agility are crucial abilities in many team sports such as soccer, basketball or handball. Therefore determing factors affect speed abilities is relevant. To investigate multidimensional correlations of the FMS test results with speed abilities. 35 male team sport players, aged 21.31±0.93. Body weight and body height were measured and BMI was calculated (kg/m2 ). Three modules of the FMS test were used to analyse: Deep Squat, Hurdle Step, In-line Lunge. Linear speed was measured based on the 20m Linear Speed test, agility was evaluated using the Agility T-test. Data were analysed by C

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13

Sun, Shiying, Ning An, Xiaoguang Zhao, and Min Tan. "A PCA–CCA network for RGB-D object recognition." International Journal of Advanced Robotic Systems 15, no. 1 (2018): 172988141775282. http://dx.doi.org/10.1177/1729881417752820.

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Object recognition is one of the essential issues in computer vision and robotics. Recently, deep learning methods have achieved excellent performance in red-green-blue (RGB) object recognition. However, the introduction of depth information presents a new challenge: How can we exploit this RGB-D data to characterize an object more adequately? In this article, we propose a principal component analysis–canonical correlation analysis network for RGB-D object recognition. In this new method, two stages of cascaded filter layers are constructed and followed by binary hashing and block histograms.

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14

Al-Mohannadi, Aisha, Somaya Al-Maadeed, Omar Elharrouss, and Kishor Kumar Sadasivuni. "Encoder-Decoder Architecture for Ultrasound IMC Segmentation and cIMT Measurement." Sensors 21, no. 20 (2021): 6839. http://dx.doi.org/10.3390/s21206839.

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Cardiovascular diseases (CVDs) have shown a huge impact on the number of deaths in the world. Thus, common carotid artery (CCA) segmentation and intima-media thickness (IMT) measurements have been significantly implemented to perform early diagnosis of CVDs by analyzing IMT features. Using computer vision algorithms on CCA images is not widely used for this type of diagnosis, due to the complexity and the lack of dataset to do it. The advancement of deep learning techniques has made accurate early diagnosis from images possible. In this paper, a deep-learning-based approach is proposed to appl

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15

Czech, Andreas. "Deep sequencing of tRNA's 3′-termini sheds light on CCA-tail integrity and maturation." RNA 26, no. 2 (2019): 199–208. http://dx.doi.org/10.1261/rna.072330.119.

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16

Liu, Qianqian, Yong Jiao, Yangyang Miao, et al. "Efficient representations of EEG signals for SSVEP frequency recognition based on deep multiset CCA." Neurocomputing 378 (February 2020): 36–44. http://dx.doi.org/10.1016/j.neucom.2019.10.049.

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17

Lamichhane, Aastha, Muhamad Khoiru Zaki, Emmanuel Okiria, and Keigo Noda. "Decision-making in climate change adaptation through a cross-sectoral approach: review." IOP Conference Series: Earth and Environmental Science 1016, no. 1 (2022): 012034. http://dx.doi.org/10.1088/1755-1315/1016/1/012034.

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Abstract Climate change adaptation (CCA) is an emerging topic in recent years since global temperature is continuing to rise and posing threats to natural biodiversity and human life. Its diverse nature requires efforts from a broad range of sectors to cope or adjust. This review paper aims to systematically study the cross-sectoral approaches in CCA decision making and develop probable strengths and shortcomings of those approaches. Literatures concerned with Multi-Criteria Decision-Making Method, or Multi-Criteria Analysis (MCA) are reviewed since it is considered as a holistic approach to i

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18

Wang, Dongqing, Carrie A. Karvonen-Gutierrez, Elizabeth A. Jackson, et al. "Western Dietary Pattern Derived by Multiple Statistical Methods Is Prospectively Associated with Subclinical Carotid Atherosclerosis in Midlife Women." Journal of Nutrition 150, no. 3 (2019): 579–91. http://dx.doi.org/10.1093/jn/nxz270.

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ABSTRACT Background The menopause has adverse effects on cardiometabolic profiles that are linked to an increased risk of atherosclerosis in women. A healthy diet during the menopausal transition may counteract the menopause-induced atherosclerotic risk. Objective This prospective cohort study aimed to examine the associations between empirically derived dietary patterns and subclinical carotid atherosclerosis in midlife women. Methods A total of 1246 midlife women (average age at baseline: 46.3 y) from the Study of Women's Health Across the Nation who completed dietary assessments and had a c

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19

Iqtait, Musab, Fatma Susilawati Mohamad, and Fadi Alsuhimat. "Active Appearance Model for Age Prediction: A Comparison." International Journal of Engineering & Technology 7, no. 4.15 (2018): 539. http://dx.doi.org/10.14419/ijet.v7i4.15.28364.

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Individual age gives key demographic data. It is viewed as a paramount delicate biometric characteristic for individual identification, contrasted with other pattern recognition issues. Age estimation is a complex issue particularly in relation to facial pictures with different ages, since the aging procedure varies extraordinarily across different age groups. In this work, we investigate deep learning techniques for age prediction based on Active Appearance Models (AAM) and six classifiers: Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Support Vector Regression (SVR), Canonical Corr

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20

Siamandoura, Paraskevi, and Constantina Tzia. "Comparative Study of Novel Methods for Olive Leaf Phenolic Compound Extraction Using NADES as Solvents." Molecules 28, no. 1 (2023): 353. http://dx.doi.org/10.3390/molecules28010353.

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Natural deep eutectic solvents (NADES) composed of choline chloride with maltose (CMA), glycerol (CGL), citric (CCA) and lactic acid (CLA) combined with microwave (MAE), ultrasound (UAE), homogenate (HAE) and high hydrostatic pressure (HHPAE)-assisted extraction methods were applied to recover and compare olive leaf phenolic compounds. The resultant extracts were evaluated for their total phenol content (TPC), phenolic profile and antioxidant activity and compared with those of water and ethanol:water 70% v/v extracts. HAE was proven to be the most efficient method for the recovery of olive le

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21

Varghese, Anna M., Juber Ahamad A. Patel, Yelena Yuriy Janjigian, et al. "Non-invasive detection of acquired resistance to FGFR inhibition in patients with cholangiocarcinoma harboring FGFR2 alterations." Journal of Clinical Oncology 37, no. 15_suppl (2019): 4096. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.4096.

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4096 Background: FGFR2 alterations are present in 14% of cholangiocarcinomas (CCA) and are promising targets of investigational FGFR-directed therapies. Cell-free DNA profiling has emerged as a non-invasive approach to monitor disease and longitudinally characterize tumor evolution. We describe the use of circulating tumor DNA (ctDNA) among patients (pts) with FGFR2-altered CCA receiving FGFR-targeted therapy in the identification of acquired FGFR2 mutations (mut) at resistance. Methods: Serial blood samples were collected from 8 pts with FGFR-altered CCA for ctDNA isolation and next generatio

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22

Webster, Nicole S., Luke D. Smith, Andrew J. Heyward, et al. "Metamorphosis of a Scleractinian Coral in Response to Microbial Biofilms." Applied and Environmental Microbiology 70, no. 2 (2004): 1213–21. http://dx.doi.org/10.1128/aem.70.2.1213-1221.2004.

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ABSTRACT Microorganisms have been reported to induce settlement and metamorphosis in a wide range of marine invertebrate species. However, the primary cue reported for metamorphosis of coral larvae is calcareous coralline algae (CCA). Herein we report the community structure of developing coral reef biofilms and the potential role they play in triggering the metamorphosis of a scleractinian coral. Two-week-old biofilms induced metamorphosis in less than 10% of larvae, whereas metamorphosis increased significantly on older biofilms, with a maximum of 41% occurring on 8-week-old microbial films.

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23

Rukavina, Iva, Maria João Rodrigues, Catarina G. Pereira, et al. "Greener Is Better: First Approach for the Use of Natural Deep Eutectic Solvents (NADES) to Extract Antioxidants from the Medicinal Halophyte Polygonum maritimum L." Molecules 26, no. 20 (2021): 6136. http://dx.doi.org/10.3390/molecules26206136.

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In this study, natural deep eutectic solvents (NADES) formed by choline chloride (ChCl), sucrose, fructose, glucose, and xylose, were used to extract antioxidants from the halophyte Polygonum maritimum L. (sea knotgrass) and compared with conventional solvents (ethanol and acetone). NADES and conventional extracts were made by an ultrasound-assisted procedure and evaluated for in vitro antioxidant properties by the radical scavenging activity (RSA) on the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical, oxygen radical absorbance capacity (ORAC), and copper chelating activity (CCA). Samples were p

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24

Jia, Hongfei, Yu Wang, Yifan Duan, and Hongbing Xiao. "Alzheimer’s Disease Classification Based on Image Transformation and Features Fusion." Computational and Mathematical Methods in Medicine 2021 (December 28, 2021): 1–11. http://dx.doi.org/10.1155/2021/9624269.

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It has become an inevitable trend for medical personnel to analyze and diagnose Alzheimer’s disease (AD) in different stages by combining functional magnetic resonance imaging (fMRI) and artificial intelligence technologies such as deep learning in the future. In this paper, a classification method was proposed for AD based on two different transformation images of fMRI and improved the 3DPCANet model and canonical correlation analysis (CCA). The main ideas include that, firstly, fMRI images were preprocessed, and subsequently, mean regional homogeneity (mReHo) and mean amplitude of low-freque

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25

Khalilzad, Zahra, and Chakib Tadj. "Using CCA-Fused Cepstral Features in a Deep Learning-Based Cry Diagnostic System for Detecting an Ensemble of Pathologies in Newborns." Diagnostics 13, no. 5 (2023): 879. http://dx.doi.org/10.3390/diagnostics13050879.

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Crying is one of the means of communication for a newborn. Newborn cry signals convey precious information about the newborn’s health condition and their emotions. In this study, cry signals of healthy and pathologic newborns were analyzed for the purpose of developing an automatic, non-invasive, and comprehensive Newborn Cry Diagnostic System (NCDS) that identifies pathologic newborns from healthy infants. For this purpose, Mel-frequency Cepstral Coefficients (MFCC) and Gammatone Frequency Cepstral Coefficients (GFCC) were extracted as features. These feature sets were also combined and fused

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26

Sun, J., X. Y. Gu, Y. Y. Feng, et al. "Summer and winter living coccolithophores in the Yellow Sea and the East China Sea." Biogeosciences 11, no. 3 (2014): 779–806. http://dx.doi.org/10.5194/bg-11-779-2014.

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Abstract. This paper describes the distribution of living coccolithophores (LCs) in the Yellow Sea and the East China Sea in summer and winter, and its relationship with environmental factors by canonical correspondence analysis (CCA). We carried out a series of investigations on LCs distribution in the Yellow Sea and the East China Sea in July and December 2011. 210 samples from different depths were collected from 44 stations in summer and 217 samples were collected from 45 stations in winter. Totally 20 taxa belonging to coccolithophyceae were identified using a polarized microscope at the

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27

Yacob, Yasmin Mohd, Hiam Alquran, Wan Azani Mustafa, Mohammed Alsalatie, Harsa Amylia Mat Sakim, and Muhamad Safiih Lola. "H. pylori Related Atrophic Gastritis Detection Using Enhanced Convolution Neural Network (CNN) Learner." Diagnostics 13, no. 3 (2023): 336. http://dx.doi.org/10.3390/diagnostics13030336.

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Atrophic gastritis (AG) is commonly caused by the infection of the Helicobacter pylori (H. pylori) bacteria. If untreated, AG may develop into a chronic condition leading to gastric cancer, which is deemed to be the third primary cause of cancer-related deaths worldwide. Precursory detection of AG is crucial to avoid such cases. This work focuses on H. pylori-associated infection located at the gastric antrum, where the classification is of binary classes of normal versus atrophic gastritis. Existing work developed the Deep Convolution Neural Network (DCNN) of GoogLeNet with 22 layers of the p

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28

Schuler, Paul A. "MOBEX Cayenne 2013: Lessons Learned & Response Enhancements Derived from the International Mobilization, Preparedness & Response Exercise in French Guiana." International Oil Spill Conference Proceedings 2014, no. 1 (2014): 42–49. http://dx.doi.org/10.7901/2169-3358-2014.1.42.

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ABSTRACT Oil Spill Response Limited (OSRL) and Clean Caribbean & Americas (CCA) conducted the first International Mobilization, Preparedness & Response Exercise (MOBEX) since the 2010 Gulf of Mexico “Macondo” incident and since the merger of CCA and OSRL in January 2013. The exercise was hosted by Shell Exploration & Production France SAS (Shell E&P), the operating partner of the Zaedyus joint venture drilling prospect offshore French Guiana. It was the first MOBEX to support a deep water exploratory drilling scenario. MOBEX Cayenne 2013, was conducted in French Guiana, May 15–

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29

Garibaldi-Márquez, Francisco, Gerardo Flores, Diego A. Mercado-Ravell, Alfonso Ramírez-Pedraza, and Luis M. Valentín-Coronado. "Weed Classification from Natural Corn Field-Multi-Plant Images Based on Shallow and Deep Learning." Sensors 22, no. 8 (2022): 3021. http://dx.doi.org/10.3390/s22083021.

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Crop and weed discrimination in natural field environments is still challenging for implementing automatic agricultural practices, such as weed control. Some weed control methods have been proposed. However, these methods are still restricted as they are implemented under controlled conditions. The development of a sound weed control system begins by recognizing the crop and the different weed plants presented in the field. In this work, a classification approach of Zea mays L. (Crop), narrow-leaf weeds (NLW), and broadleaf weeds (BLW) from multi-plant images are presented. Moreover, a large i

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30

Yu, Tianwei. "AIME: Autoencoder-based integrative multi-omics data embedding that allows for confounder adjustments." PLOS Computational Biology 18, no. 1 (2022): e1009826. http://dx.doi.org/10.1371/journal.pcbi.1009826.

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In the integrative analyses of omics data, it is often of interest to extract data representation from one data type that best reflect its relations with another data type. This task is traditionally fulfilled by linear methods such as canonical correlation analysis (CCA) and partial least squares (PLS). However, information contained in one data type pertaining to the other data type may be complex and in nonlinear form. Deep learning provides a convenient alternative to extract low-dimensional nonlinear data embedding. In addition, the deep learning setup can naturally incorporate the effect

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Church, Sarah E., Cheryl London, Christine M. Toedebusch, Ben Sutton, Sarah Weigel, and Erin Piazza. "Abstract 46: High-plex spatial transcriptomic characterization of canine tumor tissue." Cancer Research 83, no. 7_Supplement (2023): 46. http://dx.doi.org/10.1158/1538-7445.am2023-46.

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Abstract Background: Combination therapy to treat hematological and solid malignancies including chemotherapy, radiation, targeted and immunotherapy all hold huge potential for eliciting clinical responses. Informative pre-clinical testing of these approaches can be greatly facilitated using immune competent animals with spontaneous tumors. Pet dogs are immunologically outbred, immune competent and develop spontaneous tumors such as non Hodgkin’s lymphoma, glioblastoma, osteosarcoma, urothelial carcinoma and melanoma that share remarkable clinical, biological and genetic features with their hu

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S. Garea, Alberto S., Dora B. Heras, and Francisco Argüello. "TCANet for Domain Adaptation of Hyperspectral Images." Remote Sensing 11, no. 19 (2019): 2289. http://dx.doi.org/10.3390/rs11192289.

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The use of Convolutional Neural Networks (CNNs) to solve Domain Adaptation (DA) image classification problems in the context of remote sensing has proven to provide good results but at high computational cost. To avoid this problem, a deep learning network for DA in remote sensing hyperspectral images called TCANet is proposed. As a standard CNN, TCANet consists of several stages built based on convolutional filters that operate on patches of the hyperspectral image. Unlike the former, the coefficients of the filter are obtained through Transfer Component Analysis (TCA). This approach has two

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33

Chanioti, Sofia, Maria Katsouli, and Constantina Tzia. "Novel Processes for the Extraction of Phenolic Compounds from Olive Pomace and Their Protection by Encapsulation." Molecules 26, no. 6 (2021): 1781. http://dx.doi.org/10.3390/molecules26061781.

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Olive pomace, the solid by-product derived from olive oil production consists of a high concentration of bioactive compounds with antioxidant activity, such as phenolic compounds, and their recovery by applying innovative techniques is a great opportunity and challenge for the olive oil industry. This study aimed to point out a new approach for the integrated valorization of olive pomace by extracting the phenolic compounds and protecting them by encapsulation or incorporation in nanoemulsions. Innovative assisted extraction methods were evaluated such as microwave (MAE), homogenization (HAE),

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34

Hussen, Dalia F., Alaa K. Kamel, Mona K. Mekkawy, Engy A. Ashaat, and Mona O. El Ruby. "Phenotypic and Molecular Cytogenetic Analysis of a Case of Monosomy 1p36 Syndrome due to Unbalanced Translocation." Molecular Syndromology 11, no. 5-6 (2020): 284–95. http://dx.doi.org/10.1159/000510428.

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Monosomy 1p36 syndrome is one of the most common submicroscopic deletion syndromes, which is characterized by the presence of delayed developmental milestones, intellectual disability, and clinically recognizable dysmorphic craniofacial features. The syndrome comprises 4 cytogenetic groups including pure terminal deletions, interstitial deletions, complex rearrangements, and derivative chromosomes 1 due to unbalanced translocations, where unbalanced translocations represent the least percentage of all cases of monosomy 1p36 (7%). Most patients with monosomy 1p36 due to an unbalanced translocat

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Maksyukov, S. Yu, Nadezhda D. Pilipenko, and K. D. Pilipenko. "Comparative characteristics of the results of facial morphometry in patients with deep incisal overlap in the treatment of bracket systems and eliners." Russian Journal of Dentistry 24, no. 2 (2020): 95–98. http://dx.doi.org/10.17816/1728-2802-2020-24-2-95-98.

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The relevance of studying the problem of deep incisal overlap (HF) among dentofacial anomalies (CCA) is due to the high prevalence of this pathology. Among modern methods of orthodontic treatment of pathology, the use of bracket systems and aligners is highlighted. The effectiveness of these techniques can be compared in determining the morphometric characteristics obtained by tele-radiography (TEG).Material and methods. The study involved 118 people with hydraulic fracturing, the average age was 38.7 8.5 years (64 women; 54 men). The first group consisted of 49 patients who underwent correcti

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Cai, He Long, Jun Sheng Mou, and Zi Yong Hou. "Microstructure, Texture and Property of Interstitial-Free (IF) Steel after Ultra-Fast Annealing." Advanced Materials Research 1120-1121 (July 2015): 1003–7. http://dx.doi.org/10.4028/www.scientific.net/amr.1120-1121.1003.

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In this paper, common continous annealing (CCA) and ultra-fast annealing (UFA) were carried out on a cold-rolled interstitial-free (IF) steel, respectively. The microstructure of the annealed IF steel was characterized by means of scanning electron microscopy (SEM), electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM). The mechanical property was examined using tensile test. The optimum annealing process parameters were then obtained. The results showed that, the recrystallization occurs at the temperature in the range of 780-830°C. The fraction of equiaxed grain

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Gargot, T. "Sensory and Motor Difficulties in Autism." European Psychiatry 65, S1 (2022): S64. http://dx.doi.org/10.1192/j.eurpsy.2022.208.

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Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by difficulties in social interaction and communication, and by restricted and repetitive behaviors. A meta-analysis describes motor difficulties in ASD (Downey and Rapport, 2012) in 85% to 90% of cases (Liu et al. 2010). Electronic devices will help to better characterize these movement impairments (Gargot et al., in press). Another meta-analysis shows difficulties in sensorial integration in ASD, with a prevalence ranging from 45 to 95% (Ben Sasson, 2009). Sensorimotor contigencies are learned interactively (Jacque

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Valmir Júnior, Manoel, Raimundo Nonato Távora Costa, and José Vanglésio de Aguiar. "ANÁLISE DE COMPONENTES DO BALANÇO HÍDRICO EM CULTURA DE CAUPI (Vigna unguiculata (L) Walp), SOB CONDIÇÕES DE RECARGA HÍDRICA NATURAL." IRRIGA 6, no. 3 (2001): 91–103. http://dx.doi.org/10.15809/irriga.2001v6n3p91-103.

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ANÁLISE DE COMPONENTES DO BALANÇO HÍDRICO EM CULTURA DE CAUPI (Vigna unguiculata (L) Walp), SOB CONDIÇÕES DE RECARGA HÍDRICA NATURAL Manoel Valnir JúniorRaimundo Nonato Távora Costa José Vanglésio de AguiarUniversidade Federal do Ceará – Departamento de Engenharia Agrícola. Campus do Pici. Bloco 804. CEP 60455-760 – Fortaleza-CE 1 RESUMO O estudo foi desenvolvido no período de 15.05 a 10.06.1997 com o objetivo de estimar e analisar os principais componentes do balanço hídrico na cultura do caupi (Vigna unguiculata L. Walp.), em solo de textura franco-arenosa, na área do Laboratório de Hidráuli

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Geng, Qiang, Huifeng Yan, and Xingru Lu. "Optimization of a Deep Learning Algorithm for Security Protection of Big Data from Video Images." Computational Intelligence and Neuroscience 2022 (March 8, 2022): 1–17. http://dx.doi.org/10.1155/2022/3394475.

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With the rapid development of communication technology, digital technology has been widely used in all walks of life. Nevertheless, with the wide dissemination of digital information, there are many security problems. Aiming at preventing privacy disclosure and ensuring the safe storage and sharing of image and video data in the cloud platform, the present work proposes an encryption algorithm against neural cryptography based on deep learning. Primarily, the image saliency detection algorithm is used to identify the significant target of the video image. According to the significant target, t

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40

Hamani, Clement, Helen Mayberg, Brian Snyder, Peter Giacobbe, Sidney Kennedy, and Andres M. Lozano. "Deep brain stimulation of the subcallosal cingulate gyrus for depression: anatomical location of active contacts in clinical responders and a suggested guideline for targeting." Journal of Neurosurgery 111, no. 6 (2009): 1209–15. http://dx.doi.org/10.3171/2008.10.jns08763.

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Object Deep brain stimulation (DBS) of the subcallosal cingulate gyrus (SCG), including Brodmann area 25, is currently being investigated for the treatment of major depressive disorder (MDD). As a potential emerging therapy, optimal target selection within the SCG has still to be determined. The authors compared the location of the electrode contacts in responders and nonresponders to DBS of the SCG and correlated the results with clinical outcome to help in identifying the optimal target within the region. Based on the location of the active contacts used for long-term stimulation in responde

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Wang, L. Y., R. Y. Duan, J. F. Liu, S. Z. Yang, J. D. Gu, and B. Z. Mu. "Molecular analysis of the microbial community structures in water-flooding petroleum reservoirs with different temperatures." Biogeosciences Discussions 9, no. 4 (2012): 5177–203. http://dx.doi.org/10.5194/bgd-9-5177-2012.

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Abstract. Temperature is one of the most important environmental factors regulating the activity and determining the composition of the microbial community. Analysis of microbial communities from six water-flooding petroleum reservoirs at temperatures from 20 to 63 °C by 16S rRNA gene clone libraries indicates the presence of physiologically diverse and temperature-dependent microorganisms in these subterrestrial ecosystems. In high-temperature petroleum reservoirs, most of the archaeal sequences belong to the thermophilic archaea including the genera Thermococcus, Methanothermobacter and Ther

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Alquran, Hiam, Mohammed Alsalatie, Wan Azani Mustafa, Rabah Al Abdi, and Ahmad Rasdan Ismail. "Cervical Net: A Novel Cervical Cancer Classification Using Feature Fusion." Bioengineering 9, no. 10 (2022): 578. http://dx.doi.org/10.3390/bioengineering9100578.

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Cervical cancer, a common chronic disease, is one of the most prevalent and curable cancers among women. Pap smear images are a popular technique for screening cervical cancer. This study proposes a computer-aided diagnosis for cervical cancer utilizing the novel Cervical Net deep learning (DL) structures and feature fusion with Shuffle Net structural features. Image acquisition and enhancement, feature extraction and selection, as well as classification are the main steps in our cervical cancer screening system. Automated features are extracted using pre-trained convolutional neural networks

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Maksyukov, S. Yu, N. D. Pilipenko, and K. D. Pilipenko. "Features of clinical manifestations in patients suffering from dental abnormality." Russian Journal of Dentistry 24, no. 1 (2020): 19–22. http://dx.doi.org/10.18821/1728-2802-2020-24-1-19-22.

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Anomalies of the dentition represent one of the most common groups of pathologies in dentistry. Many complaints made by patients with dentofacial anomalies (CCA) make this problem quite relevant. In this regard, of particular interest is a more detailed study of the features of clinical manifestations in patients suffering from RF.Material and methods. The study involved 118 people with deep incisal overlap (hydraulic fracturing), the average age was 38.7 8.5 years; women accounted for 54.24%; men-45.76%. Determining the dental status for studying the clinical manifestations of abnormalities i

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Elsonbaty, Amr, A. A. Elsadany, and Waleed Adel. "On Reservoir Computing Approach for Digital Image Encryption and Forecasting of Hyperchaotic Finance Model." Fractal and Fractional 7, no. 4 (2023): 282. http://dx.doi.org/10.3390/fractalfract7040282.

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Forecasting the dynamical behaviors of nonlinear systems over long time intervals represents a great challenge for scientists and has become a very active area of research. The employment of the well-known artificial recurrent neural networks (RNNs)-based models requires a high computational cost, and they usually maintain adequate accuracy for complicated dynamics over short intervals only. In this work, an efficient reservoir-computing (RC) approach is presented to predict the time evolution of the complicated dynamics of a fractional order hyperchaotic finance model. Compared with the well-

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Baig, Raheel, Abdur Rehman, Abdullah Almuhaimeed, Abdulkareem Alzahrani, and Hafiz Tayyab Rauf. "Detecting Malignant Leukemia Cells Using Microscopic Blood Smear Images: A Deep Learning Approach." Applied Sciences 12, no. 13 (2022): 6317. http://dx.doi.org/10.3390/app12136317.

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Leukemia is a form of blood cancer that develops when the human body’s bone marrow contains too many white blood cells. This medical condition affects adults and is considered a prevalent form of cancer in children. Treatment for leukaemia is determined by the type and the extent to which cancer has developed across the body. It is crucial to diagnose leukaemia early in order to provide adequate care and to cure patients. Researchers have been working on advanced diagnostics systems based on Machine Learning (ML) approaches to diagnose leukaemia early. In this research, we employ deep learning

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Ernst, Thomas, Mathias Schmidt, Jenny Rinke, et al. "Molecularly Defined Clonal Evolution in Patients with Chronic Myeloid Leukemia Independent of the BCR-ABL Status." Blood 124, no. 21 (2014): 4513. http://dx.doi.org/10.1182/blood.v124.21.4513.4513.

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Abstract Molecularly defined clonal evolution has been identified as a key phenomenon in the biology of acute myeloid leukemia. Molecular aberrations may be markers of individual subclones of the disease, but also responsible for treatment resistance. In most patients with chronic myeloid leukemia (CML), treatment with tyrosine kinase inhibitors (TKI) induces complete cytogenetic remissions (CCyR) characterized by polyclonal hematopoiesis. However, some CML patients show emergence of clonal cytogenetic abnormalities (CCA) in Philadelphia (Ph) negative cells during treatment indicating clonal h

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Dantas, Ênio W., Ariadne N. Moura, and Maria do Carmo Bittencourt-Oliveira. "Cyanobacterial blooms in stratified and destratified eutrophic reservoirs in semi-arid region of Brazil." Anais da Academia Brasileira de Ciências 83, no. 4 (2011): 1327–38. http://dx.doi.org/10.1590/s0001-37652011000400019.

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This study investigated the dynamics of cyanobacteria in two deep, eutrophic reservoirs in a semi-arid region of Brazil during periods of stratification and destratification. Four collections were carried out at each reservoir at two depths at three-month intervals. The following abiotic variables were analyzed: water temperature, dissolved oxygen, pH, turbidity, water transparency, total phosphorus, total dissolved phosphorus, orthophosphate and total nitrogen. Phytoplankton density was quantified for the determination of the biomass of cyanobacteria. The data were analyzed using CCA. Higher

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Gajigan, Andrian P., Aletta T. Yñiguez, Cesar L. Villanoy, Maria Lourdes San Diego-McGlone, Gil S. Jacinto, and Cecilia Conaco. "Diversity and community structure of marine microbes around the Benham Rise underwater plateau, northeastern Philippines." PeerJ 6 (May 16, 2018): e4781. http://dx.doi.org/10.7717/peerj.4781.

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Microbes are central to the structuring and functioning of marine ecosystems. Given the remarkable diversity of the ocean microbiome, uncovering marine microbial taxa remains a fundamental challenge in microbial ecology. However, there has been little effort, thus far, to describe the diversity of marine microorganisms in the region of high marine biodiversity around the Philippines. Here, we present data on the taxonomic diversity of bacteria and archaea in Benham Rise, Philippines, Western Pacific Ocean, using 16S V4 rRNA gene sequencing. The major bacterial and archaeal phyla identified in

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Moon, Jaeyoung, Il Bae, and Shiho Kim. "Automatic Parking Controller with a Twin Artificial Neural Network Architecture." Mathematical Problems in Engineering 2019 (September 19, 2019): 1–18. http://dx.doi.org/10.1155/2019/4801985.

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We propose an artificial deep neural network- (ANN-) based automatic parking controller that overcomes a stubborn restriction prevalent in traditional approaches. The proposed ANN learns human-like control laws for automatic parking through supervised learning from a training database generated by computer-aided optimizations or real experiments. By learning the relationships between the instantaneous vehicle states and the corresponding maneuver parameters, the proposed twin controller yields lateral and longitudinal maneuvering parameters for executing automatic parking tasks in confined spa

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Sheidai, Masoud, Mohammad Mohebi Anabat, Fahimeh Koohdar, and Zahra Noormohammadi. "Identifying potential adaptive SNPs within combined DNA sequences in Genus Crocus L. (Iridaceae family): A multiple analytical approach." Caryologia 75, no. 3 (2023): 159–67. http://dx.doi.org/10.36253/caryologia-1560.

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The genus Crocus L. of Iridaceae family contains about 160 species and is considered as a complex group of plant taxa with regard to evolutionary and phylogenetic events. Inter-specific hybridization and gene flow contribute to species genetic homogeneity in one hand and high within species genetic variability and species genetic content overlaps caused species resolution a problem. In spite of extensive molecular phylogenetic studies in this genus, nothing is known about DNA sequences or Single nucleotide polymorphisms (SNPs) which are of adaptive nature. Moreover, nothing is known about whic

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