Log in

Relevant bibliographies by topics / Sparsity-awareness / Journal articles

To see the other types of publications on this topic, follow the link: Sparsity-awareness.

Journal articles on the topic 'Sparsity-awareness'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 44 journal articles for your research on the topic 'Sparsity-awareness.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Zhou, Deyu, Meng Zhang, Linhai Zhang, and Yulan He. "A Neural Group-wise Sentiment Analysis Model with Data Sparsity Awareness." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 16 (2021): 14594–601. http://dx.doi.org/10.1609/aaai.v35i16.17715.

Full text

Abstract:

Sentiment analysis on user-generated content has achieved notable progress by introducing user information to consider each individual’s preference and language usage. However, most existing approaches ignore the data sparsity problem, where the content of some users is limited and the model fails to capture discriminative features of users. To address this issue, we hypothesize that users could be grouped together based on their rating biases as well as degree of rating consistency and the knowledge learned from groups could be employed to analyze the users with limited data. Therefore, in th

APA, Harvard, Vancouver, ISO, and other styles

2

Wu, Yunfa, Bin Zhang, Anbo Meng, Yong-Hua Liu, and Chun-Yi Su. "A Hybrid Framework Combining Data-Driven and Catenary-Based Methods for Wide-Area Powerline Sag Estimation." Energies 15, no. 14 (2022): 5245. http://dx.doi.org/10.3390/en15145245.

Full text

Abstract:

This paper is concerned with the airborne-laser-data-based sag estimation for wide-area transmission lines. A systematic data processing framework is established for multi-source data collected from power lines, which is applicable to various operating conditions. Subsequently, a k-means-based clustering approach is employed to handle the spatial heterogeneity and sparsity of powerline corridor data after comprehensive performance comparisons. Furthermore, a hybrid model of the catenary and XGBoost (HMCX) method is proposed for sag estimation, which improves the accuracy of sag estimation by i

APA, Harvard, Vancouver, ISO, and other styles

3

Alvaro, Lopez Paredes, Heredia Conde Miguel, and Loffeld Otmar. "Sparsity-aware 3D ToF Sensing." IEEE Sensors Journal 23, no. 4 (2023): 3973–89. https://doi.org/10.1109/JSEN.2023.3234533.

Full text

Abstract:

In this work, we propose several time-of-flight (ToF) sensing schemes which tackle the challenge of covering very-wide areas and long ranges in nearly real time, with relatively simple implementation and low associated computational load. We thoroughly describe two methodologies for the resolution of the inverse problem. First, we extend a greedy algorithm, such as orthogonal matching pursuit (OMP), by considering an initial refinement of the spatial domain in which the signal recovery is performed. Then, we propose various nonadaptive techniques for the construction of the sensing matrices, r

APA, Harvard, Vancouver, ISO, and other styles

4

Wu, Zhijun, Zhuoning Bai, Lizhe Zhang, and Kenian Wang. "Feature Extraction Method Based on Sparse Autoencoder for Air Traffic Management System Security Situation Awareness." Security and Communication Networks 2022 (September 5, 2022): 1–14. http://dx.doi.org/10.1155/2022/3757662.

Full text

Abstract:

In wide-area distributed scenarios, it is particularly important to carry out information security situational awareness for the air traffic management (ATM) system with integrated air-ground structure. The operation data of the communication, navigation and surveillance (CNS) equipment of ATM system have the characteristics of multi-dimension, complexity, and strong correlation. In the process of situation awareness feature extraction, there are problems such as poor model accuracy, weak feature expression ability, and low classification performance. A feature association algorithm is designe

APA, Harvard, Vancouver, ISO, and other styles

5

Asabere, Nana Yaw, and Amevi Acakpovi. "ROPPSA: TV Program Recommendation Based on Personality and Social Awareness." Mathematical Problems in Engineering 2020 (June 8, 2020): 1–15. http://dx.doi.org/10.1155/2020/1971286.

Full text

Abstract:

The rapid growth of mobile television (TV), smart TV, and Internet Protocol Television (IPTV) content due to the convergence of broadcasting and the Internet requires effective recommendation methods to select appropriate TV programs/channels. Many previous methods have been proposed to address this issue. However, imperative factors such as the utilization of personality traits and social properties to recommend programs for TV viewers remain a challenge. Consequently, in this paper, we propose a recommender algorithm called Recommendation of Programs via Personality and Social Awareness (ROP

APA, Harvard, Vancouver, ISO, and other styles

6

Javed, Arifa, Hongying Zan, Orken Mamyrbayev, et al. "Transformer-Based Re-Ranking Model for Enhancing Contextual and Syntactic Translation in Low-Resource Neural Machine Translation." Electronics 14, no. 2 (2025): 243. https://doi.org/10.3390/electronics14020243.

Full text

Abstract:

Neural machine translation (NMT) plays a vital role in modern communication by bridging language barriers and enabling effective information exchange across diverse linguistic communities. Due to the limited availability of data in low-resource languages, NMT faces significant translation challenges. Data sparsity limits NMT models’ ability to learn, generalize, and produce accurate translations, which leads to low coherence and poor context awareness. This paper proposes a transformer-based approach incorporating an encoder–decoder structure, bilingual curriculum learning, and contrastive re-

APA, Harvard, Vancouver, ISO, and other styles

7

Rodrigues, Tânia F., Ricardo Silva, Fernando Fernández-Aranda, and Paulo P. P. Machado. "Emotion Regulation, Eating Psychopathology, and Putative Transdiagnostic Psychological Processes: Findings from an Exploratory Network Analysis in a College Sample." Nutrients 16, no. 20 (2024): 3452. http://dx.doi.org/10.3390/nu16203452.

Full text

Abstract:

Objective: Considering the prevalence of ED-related prodromal symptoms among higher education students (making them a population at risk for developing EDs), the main goals of this study were to conduct a network analysis in a college sample and to explore multivariate dependencies between a selection of empirically informed variables of interest to eating psychopathology, namely difficulties in emotion regulation and psychological processes (e.g., interoceptive awareness, self-compassion, self-criticism, mindfulness, and experiential avoidance). Methods: The sample included 294 college studen

APA, Harvard, Vancouver, ISO, and other styles

8

Shi, Meihui, Derong Shen, Yue Kou, Tiezheng Nie, and Ge Yu. "Next point-of-interest recommendation by sequential feature mining and public preference awareness." Journal of Intelligent & Fuzzy Systems 40, no. 3 (2021): 4075–90. http://dx.doi.org/10.3233/jifs-200465.

Full text

Abstract:

With the widespread of location-based social networks (LBSNs), the amount of check-in data grows rapidly, which helps to recommend the next point-of-interest (POI). Extracting sequential patterns from check-in data has become a meaningful way for next POI recommendation, since human movement exhibits sequential patterns in LBSNs. However, due to the check-ins’ sparsity problem, exploiting sequential patterns in next POI recommendation is a challenging issue, which makes the learned sequential patterns unreliable. Inspired by the fact that auxiliary information can be incorporated to alleviate

APA, Harvard, Vancouver, ISO, and other styles

9

Li, Changyong, Shunchun Zhang, and Zhijie Ma. "RF-YOLOv7: A Model for the Detection of Poor-Quality Grapes in Natural Environments." Agriculture 15, no. 4 (2025): 387. https://doi.org/10.3390/agriculture15040387.

Full text

Abstract:

This study addresses the challenges of detecting inferior fruits in table grapes in natural environments, focusing on subtle appearance differences, occlusions, and fruit overlaps. We propose an enhanced green grape fruit disease detection model named RF-YOLOv7. The model is trained on a dataset comprising images of small fruits, sunburn, excess grapes, fruit fractures, and poor-quality grape bunches. RF-YOLOv7 builds upon the YOLOv7 architecture by integrating four Contextual Transformer (CoT) modules to improve target-detection accuracy, employing the Wise-IoU (WIoU) loss function to enhance

APA, Harvard, Vancouver, ISO, and other styles

10

Zhao, Xin, Chong Li, Linghong Wang, Chao Dong, and Zhaoxuan Meng. "Application of Health Education Program based on Intelligent Recommendation Algorithm in the Development of School-age Children's Hand Hygiene Behavior." Scalable Computing: Practice and Experience 25, no. 4 (2024): 2876–88. http://dx.doi.org/10.12694/scpe.v25i4.2855.

Full text

Abstract:

The cultivation of hand hygiene behavior among school-age children is an important way to prevent the spread of diseases and ensure children’s health. However, traditional health education methods lack personalized programs tailored to each child, which cannot effectively improve their hand hygiene awareness and behavior. In response to this issue, the study combines multi-objective particle swarm optimization algorithm to provide personalized hand hygiene behavior development recommendations for school-age children, improving their hand hygiene awareness and behavioral level. The study adopte

APA, Harvard, Vancouver, ISO, and other styles

11

Nguyen, Van Tinh, and Dang Hung Tran. "Predicting Long Non-coding RNA-disease Associations using Multiple Features and Deep Learning." Research and Development on Information and Communication Technology 2022, no. 2 (2022): 82–91. http://dx.doi.org/10.32913/mic-ict-research.v2022.n2.1069.

Full text

Abstract:

Various long non-coding RNAs have been shownto play crucial roles in different biological processes includingcell cycle control, transcription, translation, epigenetic regulation, splicing, differentiation, immune response and so forthin the human body. Discovering lncRNA-disease associationspromotes the awareness of human complex disease at molecular level and support the diagnosis, treatment and prevention of complex diseases. It is costly, laboratory and timeconsuming to discover and verify lncRNA-disease associationsby biological experiments. Therefore, it is crucial to develop acomputatio

APA, Harvard, Vancouver, ISO, and other styles

12

Hunt, Kieran M. R., Gwyneth R. Matthews, Florian Pappenberger, and Christel Prudhomme. "Using a long short-term memory (LSTM) neural network to boost river streamflow forecasts over the western United States." Hydrology and Earth System Sciences 26, no. 21 (2022): 5449–72. http://dx.doi.org/10.5194/hess-26-5449-2022.

Full text

Abstract:

Abstract. Accurate river streamflow forecasts are a vital tool in the fields of water security, flood preparation and agriculture, as well as in industry more generally. Traditional physics-based models used to produce streamflow forecasts have become increasingly sophisticated, with forecasts improving accordingly. However, the development of such models is often bound by two soft limits: empiricism – many physical relationships are represented empirical formulae; and data sparsity – long time series of observational data are often required for the calibration of these models. Artificial neur

APA, Harvard, Vancouver, ISO, and other styles

13

Wang, Hongyang, Qingfei Meng, Ju Fan, et al. "Social Influence Does Matter: User Action Prediction for In-Feed Advertising." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (2020): 246–53. http://dx.doi.org/10.1609/aaai.v34i01.5357.

Full text

Abstract:

   Social in-feed advertising delivers ads that seamlessly fit inside a user’s feed, and allows users to engage in social actions (likes or comments) with the ads. Many businesses pay higher attention to “engagement marketing” that maximizes social actions, as social actions can effectively promote brand awareness. This paper studies social action prediction for in-feed advertising. Most existing works overlook the social influence as a user’s action may be affected by her friends’ actions. This paper introduces an end-to-end approach that leverages social influence for actio

APA, Harvard, Vancouver, ISO, and other styles

14

Ableidinger, Severin, and Brigitte Holzinger. "Sleep Paralysis and Lucid Dreaming—Between Waking and Dreaming: A Review about Two Extraordinary States." Journal of Clinical Medicine 12, no. 10 (2023): 3437. http://dx.doi.org/10.3390/jcm12103437.

Full text

Abstract:

Background: Sleep paralysis and lucid dreams are two states of consciousness that are connected to REM sleep but are defined by higher awareness in contrast to regular REM sleep. Despite these similarities, the two states differ widely in their emotional tone and their perceived controllability. This review aims to summarize the current research containing sleep paralysis and lucid dreams. However, given the sparsity of the research, one single topic cannot be chosen. Methods: Articles containing both lucid dreams as well as sleep paralysis were searched for in the following databanks: MEDLINE

APA, Harvard, Vancouver, ISO, and other styles

15

Abou Ali, Mohamad, Fadi Dornaika, and Ignacio Arganda-Carreras. "Towards Self-Conscious AI Using Deep ImageNet Models: Application for Blood Cell Classification." Machine Learning and Knowledge Extraction 6, no. 4 (2024): 2400–2421. http://dx.doi.org/10.3390/make6040118.

Full text

Abstract:

The exceptional performance of ImageNet competition winners in image classification has led AI researchers to repurpose these models for a whole range of tasks using transfer learning (TL). TL has been hailed for boosting performance, shortening learning time and reducing computational effort. Despite these benefits, issues such as data sparsity and the misrepresentation of classes can diminish these gains, occasionally leading to misleading TL accuracy scores. This research explores the innovative concept of endowing ImageNet models with a self-awareness that enables them to recognize their o

APA, Harvard, Vancouver, ISO, and other styles

16

Coughlan de Perez, Erin, Elisabeth Stephens, Konstantinos Bischiniotis, et al. "Should seasonal rainfall forecasts be used for flood preparedness?" Hydrology and Earth System Sciences 21, no. 9 (2017): 4517–24. http://dx.doi.org/10.5194/hess-21-4517-2017.

Full text

Abstract:

Abstract. In light of strong encouragement for disaster managers to use climate services for flood preparation, we question whether seasonal rainfall forecasts should indeed be used as indicators of the likelihood of flooding. Here, we investigate the primary indicators of flooding at the seasonal timescale across sub-Saharan Africa. Given the sparsity of hydrological observations, we input bias-corrected reanalysis rainfall into the Global Flood Awareness System to identify seasonal indicators of floodiness. Results demonstrate that in some regions of western, central, and eastern Africa with

APA, Harvard, Vancouver, ISO, and other styles

17

Gyilbag, Amatus, Martial Amou, Roberto Xavier Supe Tulcan, Lei Zhang, Tsedale Demelash, and Yinlong Xu. "Characteristics of Enhanced Heatwaves over Tanzania and Scenario Projection in the 21st Century." Atmosphere 12, no. 8 (2021): 1026. http://dx.doi.org/10.3390/atmos12081026.

Full text

Abstract:

Extreme hot temperature is dangerous to the bioeconomy, and would worsen with time. Ambient heatwaves accompanied by unusual droughts are major threats to poverty eradication in Tanzania. Due to sparsity of observation data and proper heatwave detection metrics, there has been a paucity of knowledge about heatwave events in Tanzania. In this study, the Heatwave Magnitude Index daily (HWMId) was adopted to quantitatively analyze heatwave characteristics throughout Tanzania at mid-21st century (2041–2070) and end of 21st century (2071–2100), relative to the reference period (1983–2012) using the

APA, Harvard, Vancouver, ISO, and other styles

18

Rana, Muhammad Qasim, Shadia Fahim, Mohammed Saad, Angela Lee, Olugbenga Timo Oladinrin, and Lekan Damilola Ojo. "Exploring the Underlying Barriers for the Successful Transition for Women from Higher Education to Employment in Egypt: A Focus Group Study." Social Sciences 13, no. 4 (2024): 195. http://dx.doi.org/10.3390/socsci13040195.

Full text

Abstract:

Education is the foundation of culture and the engine of economies; it is an essential part of life. However, it remains inaccessible or unavailable in some parts of developing nations. Moreover, such barriers for girls and women can extend beyond education and into the workplace, and this is a bone of contention based on erroneous beliefs and other factors. Barriers for girls’ and women’s education are debatable in the literature; however, there is a sparsity of literature that focuses on the bridge to the workplace. Therefore, through a focus group study, this study explores the barriers tha

APA, Harvard, Vancouver, ISO, and other styles

19

Dr. Firoj Ahamad and Dr. Vineet Kumar Singh. "AI-Driven Predictive Modeling for Real-Time Seismic Activity Monitoring and Earthquake Risk Assessment." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 3913–20. https://doi.org/10.32628/cseit25112769.

Full text

Abstract:

Real-time seismic activity monitoring and earthquake risk assessment have long been critical aspects of disaster mitigation and urban resilience planning. Traditional models based on statistical or geophysical methods often fail to capture the complexity and dynamic nature of seismic phenomena. In recent years, artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has revolutionized predictive modeling by enabling data-driven approaches for seismic signal analysis, ground motion prediction, and structural vulnerability assessment. This review paper presents a

APA, Harvard, Vancouver, ISO, and other styles

20

Adewumi, Samson. "Employees’ green behaviour initiatives and green human resource management implementation challenges." International Journal of Academe and Industry Research 5, no. 4 (2024): 53–80. http://dx.doi.org/10.53378/ijair.353111.

Full text

Abstract:

The green behaviour and green human resource management literature shows a sparsity of studies related to employee green behaviour initiatives and green human resource management implementation challenges, specifically in the context of Nigeria’s manufacturing organisations. Hence, this study seeks to address this gap by interrogating employees’ perception and understanding of green behaviour, green behaviour initiatives and green human resource management implementation challenges from the perspective of a manufacturing organization in Lagos, Nigeria. The case study research design was adopte

APA, Harvard, Vancouver, ISO, and other styles

21

Hassan, Ghassan Muslim, Abdu Gumaei, Abed Alanazi, and Samah M. Alzanin. "A Network Intrusion Detection Approach Using Extreme Gradient Boosting with Max-Depth Optimization and Feature Selection." International Journal of Interactive Mobile Technologies (iJIM) 17, no. 15 (2023): 120–34. http://dx.doi.org/10.3991/ijim.v17i15.37969.

Full text

Abstract:

Network intrusion detection system (NIDS) has become a vital tool to protect information anddetect attacks in computer networks. The performance of NIDSs can be evaluated by the numberof detected attacks and false alarm rates. Machine learning (ML) methods are commonly usedfor developing intrusion detection systems and combating the rapid evolution in the pattern ofattacks. Although there are several methods proposed in the state-of-the-art, the development ofthe most effective method is still of research interest and needs to be developed. In this paper,we develop an optimized approach using

APA, Harvard, Vancouver, ISO, and other styles

22

Xie, Tianbao, Yuqi Han, Ganglong Duan, Siyu Yang, Shaoyang Zhang, and Yongcheng Shao. "Section Recommendation of Online Medical Platform Based on Keyword Expansion with Self-Adaptive-Attention-Prompt-BERT-RCNN Modeling." Applied Sciences 15, no. 12 (2025): 6746. https://doi.org/10.3390/app15126746.

Full text

Abstract:

Background: Implementing automatic classification of short texts in online healthcare platforms is crucial to increase the efficiency of their services and improve the user experience. A short text classification method combining the keyword expansion technique and a deep learning model is constructed to solve the problems of feature sparsity and semantic ambiguity in short text classification. Methods: First, we use web crawlers to obtain patient data from the online medical platform “Good Doctor”; then, we use TF-IWF to weight the keyword importance and Word2vec to calculate the keyword simi

APA, Harvard, Vancouver, ISO, and other styles

23

Hawkins-Daarud, Andrea, Hyunsoo Yoon, Dileep Monie, et al. "NIMG-39. REVEALING THE TUMOR-IMMUNE LANDSCAPE THROUGH SPATIALLY-RESOLVED RADIOMICS: CASE STUDIES." Neuro-Oncology 21, Supplement_6 (2019): vi169—vi170. http://dx.doi.org/10.1093/neuonc/noz175.709.

Full text

Abstract:

Abstract BACKGROUND Conventional magnetic resonance imaging (MR) guides patient care in GBM. However, there is mounting awareness that MR enhancement is non-specific reflecting either tumor progression or non-tumoral inflammatory changes. Histological evaluation of GBM is held as the gold standard for disease assessment. However, the invasiveness of this methodology and the sample sparsity limit its usefulness. Methods to infer histological underpinnings of MRI are needed to improve clinical care. METHODS A transfer learning mixed effects model based on T1Gd and FLAIR MR voxel based image feat

APA, Harvard, Vancouver, ISO, and other styles

24

Hu, Yuheng, and Yili Hong. "SHEDR: An End-to-End Deep Neural Event Detection and Recommendation Framework for Hyperlocal News Using Social Media." INFORMS Journal on Computing 34, no. 2 (2022): 790–806. http://dx.doi.org/10.1287/ijoc.2021.1112.

Full text

Abstract:

Residents often rely on newspapers and television to gather hyperlocal news for community awareness and engagement. More recently, social media have emerged as an increasingly important source of hyperlocal news. Thus far, the literature on using social media to create desirable societal benefits, such as civic awareness and engagement, is still in its infancy. One key challenge in this research stream is to timely and accurately distill information from noisy social media data streams to community members. In this work, we develop SHEDR (social media–based hyperlocal event detection and recom

APA, Harvard, Vancouver, ISO, and other styles

25

Xin, Mingjun, Lijun Wu, and Shunxian Li. "A User Profile Awareness Service Collaborative Recommendation Algorithm Under LBSN Environment." International Journal of Cooperative Information Systems 28, no. 03 (2019): 1950008. http://dx.doi.org/10.1142/s0218843019500084.

Full text

Abstract:

Nowadays, location-based social network (LBSN) has become one of the most popular applications with the rapid development of mobile Internet. However, due to the spatial and real-time properties, mobile service recommendation under LBSN environment faces too many challenges especially data sparsity problem. To tackle these challenges, a recommendation framework is proposed in this paper which has four layers defined as data collection layer, user profile modeling layer, information processing layer and recommendation feedback layer, respectively. Furthermore, the ISC-CF algorithm is implemente

APA, Harvard, Vancouver, ISO, and other styles

26

de Kemp, Eric A. "Spatial agents for geological surface modelling." Geoscientific Model Development 14, no. 11 (2021): 6661–80. http://dx.doi.org/10.5194/gmd-14-6661-2021.

Full text

Abstract:

Abstract. Increased availability and use of 3D-rendered geological models have provided society with predictive capabilities, supporting natural resource assessments, hazard awareness, and infrastructure development. The Geological Survey of Canada, along with other such institutions, has been trying to standardize and operationalize this modelling practice. Knowing what is in the subsurface, however, is not an easy exercise, especially when it is difficult or impossible to sample at greater depths. Existing approaches for creating 3D geological models involve developing surface components tha

APA, Harvard, Vancouver, ISO, and other styles

27

Tang, Zhiyi, Yuequan Bao, and Hui Li. "Group sparsity-aware convolutional neural network for continuous missing data recovery of structural health monitoring." Structural Health Monitoring, July 4, 2020, 147592172093174. http://dx.doi.org/10.1177/1475921720931745.

Full text

Abstract:

In structural health monitoring, data quality is crucial to the performance of data-driven methods for structural damage identification, condition assessment, and safety warning. However, structural health monitoring systems often suffer from data imperfection, resulting in some entries being unusable in a data matrix. Discrete missing points are relatively easy to recover based on known adjacent points, whereas segments of continuous missing data are more common and also more challenging to recover in a practical scenario. Formulating the data recovery task as an optimization problem for matr

APA, Harvard, Vancouver, ISO, and other styles

28

Tsai, Tsung-Han, and Ding-Bang Lin. "An On-Chip Fully Connected Neural Network Training Hardware Accelerator Based on Brain Float Point and Sparsity Awareness." IEEE Open Journal of Circuits and Systems, 2023, 1. http://dx.doi.org/10.1109/ojcas.2023.3245061.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Wang, Keqiang, Yuanyuan Jin, Haofen Wang, Hongwei Peng, and Xiaoling Wang. "Personalized Time-Aware Tag Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence 32, no. 1 (2018). http://dx.doi.org/10.1609/aaai.v32i1.11259.

Full text

Abstract:

Personalized tag recommender systems suggest a list of tags to a user when he or she wants to annotate an item. They utilize users’ preferences and the features of items. Tensorfactorization techniques have been widely used in tag recommendation. Given the user-item pair, although the classic PITF (Pairwise Interaction Tensor Factorization) explicitly models the pairwise interactions among users, items and tags, it overlooks users’ short-term interests and suffers from data sparsity. On the other hand, given the user-item-time triple, time-aware approaches like BLL (Base-Level Learning) utiliz

APA, Harvard, Vancouver, ISO, and other styles

30

Kurumety, Sasha K., Jacob T. Howshar, and Vilert A. Loving. "Breast Cancer Screening and Outcomes Disparities Persist for Native American Women." Journal of Breast Imaging, December 16, 2022. http://dx.doi.org/10.1093/jbi/wbac080.

Full text

Abstract:

Abstract Over the past three decades, mortality rates from breast cancer have decreased for multiple racial groups but have remained constant for American Indian and Alaskan Native (AI/AN) women. Additionally, AI/AN women are less likely to receive timely breast cancer screening and are more likely to be diagnosed with advanced stage breast cancer at younger ages than their White counterparts. These disparities can be explained, in part, by the unique barriers to accessing care faced by AI/AN women. The Indian Health Service provides care to many AI/AN patients; however, their scope of practic

APA, Harvard, Vancouver, ISO, and other styles

31

Achanta, M., P. Kasetti, M. Fortune‐Ely, T. Ross, T. Magos, and J. G. Manjaly. "Adverse Effects of Steroid Therapy in Sudden Sensorineural Hearing Loss: A Scoping Review." Clinical Otolaryngology, May 30, 2025. https://doi.org/10.1111/coa.14339.

Full text

Abstract:

ABSTRACTObjectiveSudden sensorineural hearing loss (SSNHL) is an otologic emergency and is treated with steroid therapy. Despite adverse events (AEs) associated with long‐term steroid use being well evidenced, there is sparsity of literature regarding the AEs of short‐course prescriptions in the SSNHL cohort, which limits the quality of patient counselling and informed consent.MethodA literature search was performed on the Medline and Embase databases for studies assessing AEs in adults with SSNHL managed with oral (OST), intratympanic (ITS) and intravenous steroid therapy (IVS). Two authors s

APA, Harvard, Vancouver, ISO, and other styles

32

Amaad, Hafiz, Naveed Jhamat, Kashif Riaz, and Zeeshan Arshad. "Context-Aware and Sequential Pattern Mining based recommendations for Research Papers: A Hybrid Approach." Journal of Information Communication Technologies and Robotic Applications, December 30, 2020. http://dx.doi.org/10.51239/jictra.v0i0.240.

Full text

Abstract:

The availability of huge volumes of online research papers over scholarly communities has been increasing rapidly with the evolution of the Internet. Meanwhile, several researchers confront troubles while retrieving suitable and relevant research papers according to their research necessities due to information overload. Besides, the research necessities vary from researcher to researcher according to their contextual state and the online behavior in sequential access. Conventional recommendation approaches for instance content-based filtering (CBF) and collaborative filtering (CF) utilize con

APA, Harvard, Vancouver, ISO, and other styles

33

Polo, Jennifer, Melissa J. Basile, Meng Zhang, et al. "Application of the RE-AIM framework to evaluate the implementation of telehealth pulmonary rehabilitation in a randomized controlled trial among African-American and Hispanic patients with advanced stage Chronic Obstructive Pulmonary Disease." BMC Health Services Research 23, no. 1 (2023). http://dx.doi.org/10.1186/s12913-023-09492-7.

Full text

Abstract:

Abstract Background Pulmonary rehabilitation (PR) decreases rehospitalization for people with COPD. However, less than 2% receive PR, partly due to lack of referral and sparsity of PR facilities. This disparity is particularly pronounced in African American and Hispanic persons with COPD. Telehealth-provided PR could increase access and improve health outcomes. Methods We applied the RE-AIM framework in a post-hoc analysis of our mixed methods RCT comparing referral to Telehealth-delivered PR (TelePR) versus standard PR (SPR) for African American and Hispanic COPD patients hospitalized for COP

APA, Harvard, Vancouver, ISO, and other styles

34

Chen, Yuwei, and Shiyong Chu. "On the adversarial robustness of aerial detection." Frontiers in Computer Science 6 (November 21, 2024). http://dx.doi.org/10.3389/fcomp.2024.1349206.

Full text

Abstract:

Deep learning-based aerial detection is an essential component in modern aircraft, providing fundamental functions such as navigation and situational awareness. Though promising, aerial detection has been shown to be vulnerable to adversarial attacks, posing significant safety concerns. The sparsity of a comprehensive analysis on the robustness of aerial detection exacerbates these vulnerabilities, increasing the risks associated with the practical application of these systems. To bridge this gap, this paper comprehensively studies the potential threats caused by adversarial attacks on aerial

APA, Harvard, Vancouver, ISO, and other styles

35

Landschützer, Peter, Toste Tanhua, Jacqueline Behncke, and Lydia Keppler. "Sailing through the southern seas of air–sea CO ₂ flux uncertainty." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 381, no. 2249 (2023). http://dx.doi.org/10.1098/rsta.2022.0064.

Full text

Abstract:

The Southern Ocean is among the largest contemporary sinks of atmospheric carbon dioxide on our planet; however, remoteness, harsh weather and other circumstances have led to an undersampling of the ocean basin, compared with its northern hemispheric counterparts. While novel data interpolation methods can in part compensate for such data sparsity, recent studies raised awareness that we have hit a wall of unavoidable uncertainties in air–sea CO 2 flux reconstructions. Here, we present results from autonomous observing campaigns using a novel platform to observe remote ocean regions: sailboats

APA, Harvard, Vancouver, ISO, and other styles

36

van der Marel, Annemarie, Sanjay Prasher, Chelsea Carminito, et al. "A framework to evaluate whether to Pool or separate behaviors in a multilayer network." Current Zoology, December 26, 2020. http://dx.doi.org/10.1093/cz/zoaa077.

Full text

Abstract:

Abstract A multilayer network approach combines different network layers, which are connected by interlayer edges, to create a single mathematical object. These networks can contain a variety of information types and represent different aspects of a system. However, the process for selecting which information to include is not always straightforward. Using data on two agonistic behaviors in a captive population of monk parakeets (Myiopsitta monachus), we developed a framework for investigating how pooling or splitting behaviors at the scale of dyadic relationships (between two individuals) aff

APA, Harvard, Vancouver, ISO, and other styles

37

ArifPrabowo, Setya Budi, Subiyanto Subiyanto, and Nur AzisSalim. "Collaborative Filtering Modification Technology for Recommendation Systems in Smart Digital Agribusiness Marketplace." Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, June 13, 2025. https://doi.org/10.22219/kinetik.v10i3.2264.

Full text

Abstract:

The rapid transformation in the agribusiness sector, driven by globalization and digitalization, necessitates the adoption of intelligent systems to enhance performance, market accessibility, and decision-making processes. Despite the growing use of personalized recommender systems in e-commerce, geographical context remains insufficiently integrated into recommendation processes. This lack of geolocation awareness diminishes recommendation relevance and accuracy by overlooking geographical factors that influence user preferences. To address this limitation, this work aims to enhance the perfo

APA, Harvard, Vancouver, ISO, and other styles

38

Gautam, Devendra, Anurag Dixit, Lathabanda, S. B. Goyal, Chaman Verma, and Manoj Kumar. "A novel approach to enhance the quality of health care recommender system using fuzzy-genetic approach." Journal of Intelligent & Fuzzy Systems, July 13, 2023, 1–14. http://dx.doi.org/10.3233/jifs-224257.

Full text

Abstract:

In recent generations of the digital world medical data in Recommender Systems. Health Care Recommender System (HCRS) analyses the medical data and then predicts the user’s or patient’s illness. Nowadays, healthcare data is used by various users or patients in recommendation systems which are useful for everyone. Analysing and predicting medical data provides awareness to users and these data predictions may be enriched using various techniques of RS. Machine learning techniques are used to make sure that health data is reliable and of high quality. In every RS the issues are targeted such as

APA, Harvard, Vancouver, ISO, and other styles

39

Thomas, Joel Abraham, Riya Mariam Mathew, Devafrey Devaraj Angela, Harshit Chauhan, and Pamela Alice Kingsley. "Pregnancy and Unilateral Krukenberg Tumour: Factual or Fictious – A Case Report." Indian Cancer Awareness Journal, July 15, 2024, 1–5. http://dx.doi.org/10.25259/icaj_14_2024.

Full text

Abstract:

Krukenburg tumor, a secondary ovarian neoplasm, arises from various primary sites. It’s occurrence during pregnancy is extremely rare. We are reporting the case of a 24 year old G2P1L1 lady with a unilateral Krukenberg tumor diagnosed in first trimester of pregnancy. The case posed as a diagnostic challenge as the presentation is non-specific and radiological diagnosis is very challenging owing to the similarity of the tumour to ectopic pregnancy on imaging. The sparsity of data and unique presentation of the patient inspired us to write this report. This is a 24 year old lady who presented to

APA, Harvard, Vancouver, ISO, and other styles

40

Shehu, Edlira, Daniel Zantedeschi, and Prasad A. Naik. "A Method for Asynchronous Time Series Analysis with Marketing Applications." Management Science, July 21, 2025. https://doi.org/10.1287/mnsc.2024.04336.

Full text

Abstract:

Many time series data evolve asynchronously. In marketing, for example, we observe ad liking every second, hourly clickstreams, daily sales, weekly brand awareness, or monthly ad expenditures. Thus, the question arises: how to estimate dynamic models when metrics evolve at different frequencies? To this end, we develop a new method for estimation and inference of state space models for asynchronous data. In contrast to existing approaches, the proposed method does not require any data preprocessing to align frequencies. We derive the optimal gain factor from first principles and demonstrate in

APA, Harvard, Vancouver, ISO, and other styles

41

Yazdanian, Ramtin, Robert West, and Pierre Dillenbourg. "Keeping Up with the Trends: Analyzing the Dynamics of Online Learning and Hiring Platforms in the Software Programming Domain." International Journal of Artificial Intelligence in Education, December 8, 2020. http://dx.doi.org/10.1007/s40593-020-00231-1.

Full text

Abstract:

AbstractThe Fourth Industrial Revolution has considerably sped up the pace of skill changes in many professional domains, with scores of new skills emerging and many old skills moving towards obsolescence. For these domains, identifying the new necessary skills in a timely manner is a difficult task, where existing methods are inadequate. Understanding the process, by which these new skills and technologies appear in and diffuse through a professional domain, could give training providers more time to identify these new skills and react. For this purpose, in the present work, we look at the dy

APA, Harvard, Vancouver, ISO, and other styles

42

Hassig, S., C. Wanderling, and J. S. Gabrielsen. "(152) A Case of Penile Neoplasm Masquerading as Acute Peyronie's Disease." Journal of Sexual Medicine 20, Supplement_1 (2023). http://dx.doi.org/10.1093/jsxmed/qdad060.147.

Full text

Abstract:

Abstract Introduction Painful erections with curvature is pathognomonic for acute Peyronie’s Disease (PD). While resolution of pain and stabilization of curvature define the transition from acute to stable PD, there is high variability in the time from symptom onset to resolution. Thus, when to image and consider alternative diagnoses is poorly defined. We present a case of persistent distal penile pain and curvature with erections, initially diagnosed as acute PD, but subsequently found to be epithelioid hemangioendothelioma (EHE), a rare vascular neoplasm on the spectrum between a hemangioma

APA, Harvard, Vancouver, ISO, and other styles

43

Li, Ruixia, Wei Peng, and Chenxi Zhang. "A CS-Based Grant-Free Media Access Scheme for NOMA-Based Industrial IoTs with Location Awareness." International Journal of Wireless Information Networks, September 5, 2021. http://dx.doi.org/10.1007/s10776-021-00527-6.

Full text

Abstract:

AbstractGrant-free media access is vital for applications in Industrial IoTs (IIoTs), where stringent delays are required. Recently, due to the capability of supporting parallel receptions, Non-Orthogonal Multiple Access (NOMA) has gained research interests in IIoTs. Obviously, combining them organically is beneficial for enhancing the delay performances. In this paper, for a typical convergecast wireless network where its data sink is NOMA-based, we propose a grant-free MAC (Media Access Contention) scheme based on Compressive Sensing in Busy Tone Channel (CSiBTC), by exploiting the transmiss

APA, Harvard, Vancouver, ISO, and other styles

44

Bonthuis, Marjolein, Anneke Kramer, Alberto Ortiz, Kitty J. Jager, and Vianda Stel. "#520 Trends in kidney replacement therapy in Central and Eastern Europe—data from the ERA Registry." Nephrology Dialysis Transplantation 39, Supplement_1 (2024). http://dx.doi.org/10.1093/ndt/gfae069.812.

Full text

Abstract:

Abstract Background and Aims Despite huge efforts to accomplish equitable access to high-quality healthcare, large disparities in kidney care delivery remain across Europe. Economic factors are considered to be the driving force behind differences in access to kidney replacement therapy (KRT), with lower access in lower-income countries. There is a sparsity of epidemiological data on KRT in Central and Eastern Europe. Therefore, we aimed to examine time trends in incidence and prevalence of KRT in Central and Eastern Europe from 2010 to 2021. Method We included incidence and prevalence data on

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!