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Journal articles on the topic 'ID. Knowledge representation'

Author: Grafiati

Published: 10 March 2023

Last updated: 31 July 2025

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1

Li, Jiachen, and Xiaojin Gong. "Unleashing the Potential of Pre-Trained Diffusion Models for Generalizable Person Re-Identification." Sensors 25, no. 2 (2025): 552. https://doi.org/10.3390/s25020552.

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Domain-generalizable re-identification (DG Re-ID) aims to train a model on one or more source domains and evaluate its performance on unseen target domains, a task that has attracted growing attention due to its practical relevance. While numerous methods have been proposed, most rely on discriminative or contrastive learning frameworks to learn generalizable feature representations. However, these approaches often fail to mitigate shortcut learning, leading to suboptimal performance. In this work, we propose a novel method called diffusion model-assisted representation learning with a correla

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Chen, Jiankang, Tong Zhang, Wei-Shi Zheng, and Ruixuan Wang. "TagFog: Textual Anchor Guidance and Fake Outlier Generation for Visual Out-of-Distribution Detection." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 2 (2024): 1100–1109. http://dx.doi.org/10.1609/aaai.v38i2.27871.

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Out-of-distribution (OOD) detection is crucial in many real-world applications. However, intelligent models are often trained solely on in-distribution (ID) data, leading to overconfidence when misclassifying OOD data as ID classes. In this study, we propose a new learning framework which leverage simple Jigsaw-based fake OOD data and rich semantic embeddings (`anchors') from the ChatGPT description of ID knowledge to help guide the training of the image encoder. The learning framework can be flexibly combined with existing post-hoc approaches to OOD detection, and extensive empirical evaluati

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Anigala, Omeshamisu, Kwanghee Won, and Chulwoo Pack. "PEARL: Perceptual and Analytical Representation Learning for Video Anomaly Detection." ACM SIGAPP Applied Computing Review 25, no. 1 (2025): 5–15. https://doi.org/10.1145/3727257.3727258.

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Video anomaly detection is crucial for applications like surveillance and autonomous systems. Traditional methods often rely solely on visual cues, missing valuable contextual data. This paper presents Perceptual and Analytical Representation Learning (PEARL), a novel method that combines perceptual (raw sensory input) and analytical (higher-level context) modalities. Specifically, we integrate visual information with object tracking data, along with the tracking data-specialized normalization method, DOT-Norm , leveraging ID switching to capture high-level contexts of abnormal movements. We e

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Farooq, Ammarah, Muhammad Awais, Josef Kittler, and Syed Safwan Khalid. "AXM-Net: Implicit Cross-Modal Feature Alignment for Person Re-identification." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (2022): 4477–85. http://dx.doi.org/10.1609/aaai.v36i4.20370.

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Cross-modal person re-identification (Re-ID) is critical for modern video surveillance systems. The key challenge is to align cross-modality representations conforming to semantic information present for a person and ignore background information. This work presents a novel convolutional neural network (CNN) based architecture designed to learn semantically aligned cross-modal visual and textual representations. The underlying building block, named AXM-Block, is a unified multi-layer network that dynamically exploits the multi-scale knowledge from both modalities and re-calibrates each modalit

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Wu, Guile, and Shaogang Gong. "Generalising without Forgetting for Lifelong Person Re-Identification." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (2021): 2889–97. http://dx.doi.org/10.1609/aaai.v35i4.16395.

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Existing person re-identification (Re-ID) methods mostly prepare all training data in advance, while real-world Re-ID data are inherently captured over time or from different locations, which requires a model to be incrementally generalised from sequential learning of piecemeal new data without forgetting what is already learned. In this work, we call this lifelong person Re-ID, characterised by solving a problem of unseen class identification subject to continuous new domain generalisation and adaptation with class imbalanced learning. We formulate a new Generalising without Forgetting method

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Vlaeminck, H., J. Vennekens, M. Denecker, and M. Bruynooghe. "An approximative inference method for solving ∃∀SO satisfiability problems." Journal of Artificial Intelligence Research 45 (September 25, 2012): 79–124. http://dx.doi.org/10.1613/jair.3658.

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This paper considers the fragment ∃∀SO of second-order logic. Many interesting problems, such as conformant planning, can be naturally expressed as finite domain satisfiability problems of this logic. Such satisfiability problems are computationally hard (ΣP2) and many of these problems are often solved approximately. In this paper, we develop a general approximative method, i.e., a sound but incomplete method, for solving ∃∀SO satisfiability problems. We use a syntactic representation of a constraint propagation method for first-order logic to transform such an ∃∀SO satisfiability problem to

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Dani Manesah. "Analisis Id Ego dan Super Ego pada Iklan Televisi Gojek Mempersembahkan: Cerdikiawan." Abstrak : Jurnal Kajian Ilmu seni, Media dan Desain 1, no. 3 (2024): 44–56. http://dx.doi.org/10.62383/abstrak.v1i3.272.

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This study analyzes the representation of the Id, Ego, and Superego in Gojek's television commercial titled "Gojek Presents: Cerdikiawan" using Sigmund Freud's psychoanalytic theory. The study aims to identify how these three components of personality are depicted in the advertisement's narrative and their impact on the audience. The research employs a qualitative case study design, with data collected through observation and content analysis. The results show that the advertisement successfully portrays the conflict between the Id, Ego, and Superego through characters and scenes reflecting pr

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Bharara, Reva, Aryan Rathore, and Krishna Kumar Tiwari. "Language Agnostic Ontology Extension Framework." Asian Journal of Research in Computer Science 16, no. 4 (2023): 327–35. http://dx.doi.org/10.9734/ajrcos/2023/v16i4394.

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Ontologies are powerful structures used to define the schema and organization of knowledge. They provide a framework for precisely and explicitly organizing concepts, entities, attributes, and relationships within a domain, enabling effective data management, knowledge sharing, and intelligent decisionmaking. Knowledge graphs, on the other hand, store data in a graphical form, facilitating semantically rich and interconnected data analysis, management, and exploration. Nodes represent entities, edges depict relationships between nodes, and attributes showcase node properties. Combining the str

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Buchnat, Marzena, and Aleksandra Jasielska. "Knowledge about anger in children with a mild intellectual disability." International Journal of Special Education (IJSE) 37, no. 2 (2022): 92–105. http://dx.doi.org/10.52291/ijse.2022.37.43.

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"The knowledge of children with a mild intellectual disability (ID) is less complex and poorer than that of their peers in the intellectual norm (IN). The aim of this study was to characterize knowledge about anger in children with mild intellectual disabilities. The study used the authoring tool to measure children’s knowledge of emotions, including anger. This tool facilitated the exploration of the cognitive representation of the basic emotions available in three codes (which perform the functions of perception, expression, and understanding) and the interconnections between them. Children

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Humayun, Shamim, Shabana Sartaj, and Waqar Ali Shah. "Exploring Linguistic Representation of Women on Facebook: A Study in Pakistani Context." Advances in Language and Literary Studies 10, no. 2 (2019): 152. http://dx.doi.org/10.7575/aiac.alls.v.10n.2p.152.

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Facebook is an online platform where people form a self-presentation and construct an identity through a personal ID or profile. Use of this social website fully depicts the norms and perceptions of patriarchal society. This study aims to explore the waymen of society speaks to the women as well as the speaking of women with other women that reflects an idea of women in Pakistani society on Facebook through quantitative study. The Analysis revealed that the women, in Pakistani society in particular and elsewhere in general is linguistically expressed as a being that is not equal to men in inte

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HOU, PING, BROES DE CAT, and MARC DENECKER. "FO(FD): Extending classical logic with rule-based fixpoint definitions." Theory and Practice of Logic Programming 10, no. 4-6 (2010): 581–96. http://dx.doi.org/10.1017/s1471068410000293.

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AbstractWe introduce fixpoint definitions, a rule-based reformulation of fixpoint constructs. The logic FO(FD), an extension of classical logic with fixpoint definitions, is defined. We illustrate the relation between FO(FD) and FO(ID), which is developed as an integration of two knowledge representation paradigms. The satisfiability problem for FO(FD) is investigated by first reducing FO(FD) to difference logic and then using solvers for difference logic. These reductions are evaluated in the computation of models for FO(FD) theories representing fairness conditions and we provide potential a

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Wang, Di, Yujuan Si, Weiyi Yang, Gong Zhang, and Jia Li. "A Novel Electrocardiogram Biometric Identification Method Based on Temporal-Frequency Autoencoding." Electronics 8, no. 6 (2019): 667. http://dx.doi.org/10.3390/electronics8060667.

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For good performance, most existing electrocardiogram (ECG) identification methods still need to adopt a denoising process to remove noise interference beforehand. This specific signal preprocessing technique requires great efforts for algorithm engineering and is usually complicated and time-consuming. To more conveniently remove the influence of noise interference and realize accurate identification, a novel temporal-frequency autoencoding based method is proposed. In particular, the raw data is firstly transformed into the wavelet domain, where multi-level time-frequency representation is a

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Lv, Kai, Yunlong Li, Zhuo Chen, Shuo Wang, Sheng Han, and Youfang Lin. "Infer the Whole from a Glimpse of a Part: Keypoint-Based Knowledge Graph for Vehicle Re-Identification." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 6 (2025): 5901–9. https://doi.org/10.1609/aaai.v39i6.32630.

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Vehicle re-identification aims to match vehicles across non-overlapping camera views. Many existing methods extract features from one specific image, and these methods lack view-invariance when comparing vehicles of different orientations. As a result, discriminative parts obscured by viewpoint changes cannot contribute effectively to matching. This work presents a novel keypoint-based framework for vehicle Re-ID. We propose to explicitly model the intrinsic structural relationships between vehicle components via knowledge graph. By establishing connection between keypoints, our approach aims

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Garneau, William, Benjamin Martin, Kelly Gebo, et al. "76 Lessons learned during implementation of OMOP common data model across multiple health systems." Journal of Clinical and Translational Science 8, s1 (2024): 20. http://dx.doi.org/10.1017/cts.2024.77.

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OBJECTIVES/GOALS: Adoption of the Observational Medical Outcomes Partnership (OMOP) common data model promises to transform large-scale observational health research. However, there are diverse challenges for operationalizing OMOP in terms of interoperability and technical skills among coordinating centers throughout the US. METHODS/STUDY POPULATION: A team from the Critical Path Institute (C-Path) collaborated with the informatics team members at Johns Hopkins to provide technical support to participating sites as part of the Extract, Transform, and Load (ETL) process linking existing concept

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Anand, Tara V., Adele H. Ribeiro, Jin Tian, and Elias Bareinboim. "Causal Effect Identification in Cluster DAGs." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 10 (2023): 12172–79. http://dx.doi.org/10.1609/aaai.v37i10.26435.

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Reasoning about the effect of interventions and counterfactuals is a fundamental task found throughout the data sciences. A collection of principles, algorithms, and tools has been developed for performing such tasks in the last decades. One of the pervasive requirements found throughout this literature is the articulation of assumptions, which commonly appear in the form of causal diagrams. Despite the power of this approach, there are significant settings where the knowledge necessary to specify a causal diagram over all variables is not available, particularly in complex, high-dimensional d

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Wang, Zhifeng, Wenxing Yan, Chunyan Zeng, Yuan Tian, and Shi Dong. "A Unified Interpretable Intelligent Learning Diagnosis Framework for Learning Performance Prediction in Intelligent Tutoring Systems." International Journal of Intelligent Systems 2023 (February 20, 2023): 1–20. http://dx.doi.org/10.1155/2023/4468025.

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Intelligent learning diagnosis is a critical engine of intelligent tutoring systems, which aims to estimate learners’ current knowledge mastery status and predict their future learning performance. The significant challenge with traditional learning diagnosis methods is the inability to balance diagnostic accuracy and interpretability. Although the existing psychometric-based learning diagnosis methods provide some domain interpretation through cognitive parameters, they have insufficient modeling capability with a shallow structure for large-scale learning data. While the deep learning-based

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Manziuk, E. A., O. V. Barmak, Iu V. Krak, O. A. Pasichnyk, P. M. Radiuk, and O. V. Mazurets. "Semantic alignment of ontologies meaningful categories with the generalization of descriptive structures." PROBLEMS IN PROGRAMMING, no. 3-4 (December 2022): 355–63. http://dx.doi.org/10.15407/pp2022.03-04.355.

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The presented work addresses the issue of semantic alignment of ontology components with a generalized structured corpus. The field of research refers to the sphere of determining the features of trust in artificial intelligence. An alignment method is proposed at the level of semantic components of the general alignment system. The method is a component of a broader alignment system and compares entities at the level of meaningful correspondence. Moreover, only the alignment entities’ descriptive content is considered within the proposed technique. Descriptive contents can be represented by v

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Muhammad Iqbal Zamzami and Dailatus Syamsiyah. "The Material Analysis and Learning Method of Nahwu in the Book of Qawa'id Al-Asasiyyah Li Al-Lughah Al-'Arabiyyah." al Mahāra: Jurnal Pendidikan Bahasa Arab 6, no. 2 (2020): 257–78. http://dx.doi.org/10.14421/almahara.2020.062.06.

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The learning materials are knowledge, behavior, and competence that students must learn to achieve the established standards of competence. A learning method is used as lesson materials presented to students in the class, both individually and in groups. These are essential learning components to discuss, for the right learning methods will make it easier for students to receive the given learning materials. It aims to know the material's content and the methods of learning Nahwu book Qawa 'id Al-Asasiyyah Li Al-Lughah Al-Arabiyyah. The study is a library study (library research), a descriptiv

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Bekdache, Carine, Heather Vandermeulen, Grace Tang, Angela C. Weyand, and Michelle Sholzberg. "Facilitators and Barriers to Accessing Antifibrinolytic and Iron Therapies for Patients Who Menstruate - a Global Healthcare Provider Survey." Blood 142, Supplement 1 (2023): 5071. http://dx.doi.org/10.1182/blood-2023-190501.

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Background: Heavy menstrual bleeding (HMB) negatively impacts quality of life directly and indirectly due to symptoms associated with resultant iron deficiency (ID) and iron deficiency anemia (IDA). Antifibrinolytics, to decrease blood loss, and iron supplementation, to replace deficits, should be cornerstones of HMB management. Despite an abundance of evidence supporting their effectiveness and safety, clear, consistent guidance on treating HMB and secondary ID/IDA is lacking which renders access to care suboptimal and inequitable. Objective: To identify barriers and facilitators to health ca

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Teng, Jackson Horlick, Thian Song Ong, Tee Connie, Kalaiarasi Sonai Muthu Anbananthen, and Pa Pa Min. "Optimized Score Level Fusion for Multi-Instance Finger Vein Recognition." Algorithms 15, no. 5 (2022): 161. http://dx.doi.org/10.3390/a15050161.

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The finger vein recognition system uses blood vessels inside the finger of an individual for identity verification. The public is in favor of a finger vein recognition system over conventional passwords or ID cards as the biometric technology is harder to forge, misplace, and share. In this study, the histogram of oriented gradients (HOG) features, which are robust against changes in illumination and position, are extracted from the finger vein for personal recognition. To further increase the amount of information that can be used for recognition, different instances of the finger vein, rangi

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Podungge, Rusni, Rosma Kadir, Irmawaty Umar, and Andre Niode. "The Transformation of the Character Einar Wegener to A Transgender Woman in the Film ‘The Danish Girl’: A Psychological Point of View." TRANS-KATA: Journal of Language, Literature, Culture and Education 3, no. 2 (2023): 71–83. http://dx.doi.org/10.54923/jllce.v3i2.11.

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This present work aimed to determine the process of transforming one’s identity from a man to a woman when one must overcome obstacles in a real-life condition depicted in the film The Danish Girl. It is based on Freud’s theory about the human psychological level, with the addition of Queer Theory in completing this research. This descriptive qualitative research obtained data source from the biographical film The Danish Girl directed by Tom Hopper, released in 2015. The subject studied is limited on the main character analysis, who later became Transgender and changed his name to Lili Elbe. I

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Moerdisuroso, Indro. "Reading Children's Drawings Through Analysis of Three Metafunctions." JPUD - Jurnal Pendidikan Usia Dini 16, no. 1 (2022): 186–99. http://dx.doi.org/10.21009/jpud.161.13.

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For researchers, early childhood educators, and art educators, the contribution of this article is to expand meaning in drawing activities. Perspective in reading pictures using visual culture theory, especially visual grammar. This study aims to share knowledge and experiences in reading early childhood pictures from different perspectives. This research method uses a qualitative descriptive approach through visual material data collection techniques and analysis of three metafunctions. The objects of research are three pictures of children aged 7-8 years, namely the works of winners of the I

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Otoluwa, Moon Hidayati, Rasuna Rasid Talib, Rosalin Tanaiyo, and Herlina Usman. "Enhancing Children's Vocabulary Mastery Through Storytelling." JPUD - Jurnal Pendidikan Usia Dini 16, no. 2 (2022): 249–60. http://dx.doi.org/10.21009/jpud.162.05.

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Significant language development differences occur in preschoolers, resolving these differences is a key objective of preschool education because young children's language abilities at the start of school, particularly their vocabulary abilities, are a strong predictor of later academic ability. Storytelling is one of the methods used to teach English, it makes the learning environment more interesting, energetic, and conversational. This study aims to examine storytelling in increasing children's vocabulary. The research method is a case study that uses observation, interviews, and documentat

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Xu, Haoxin, Jiaqi Yin, Changyong Qi, Xiaoqing Gu, Bo Jiang, and Longwei Zheng. "Bridging the Vocabulary Gap: Using Side Information for Deep Knowledge Tracing." Applied Sciences 14, no. 19 (2024): 8927. http://dx.doi.org/10.3390/app14198927.

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Knowledge tracing is a crucial task in personalized learning that models student mastery based on historical data to predict future performance. Currently, deep learning models in knowledge tracing predominantly use one-hot encodings of question, knowledge, and student IDs, showing promising results. However, they face a significant limitation: a vocabulary gap that impedes the processing of new IDs not seen during training. To address this, our paper introduces a novel method that incorporates aggregated features, termed ‘side information’, that captures essential attributes such as student a

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Kennedy, Jessica, Pranisha Gautam-Goyal, Robin V. Koshy, Thien-Ly Doan, Neha Paralkar, and Karen Friedman. "972. Antimicrobial Stewardship Educational Needs of Residents in an Internal Medicine Program." Open Forum Infectious Diseases 8, Supplement_1 (2021): S578. http://dx.doi.org/10.1093/ofid/ofab466.1167.

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Abstract Background Antibiotic stewardship continues to be health concern that physicians often acknowledge, but whose real-life practices do not reflect that awareness. There is a wide range of opinions on the efficacy of the type of modality that is most effective to teach stewardship. Our project addresses resident needs specifically, with coverage in four topics—proper antibiotic dosing, IV to PO transitioning, duplicate coverage, and antibiotic time outs. Methods Categorical Internal Medicine residents in PGY 1-3 were sent an optional 48-question Likert survey querying needs in the above

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Vinayakumar, R., K. P. Soman, and Prabaharan Poornachandran. "Evaluation of Recurrent Neural Network and its Variants for Intrusion Detection System (IDS)." International Journal of Information System Modeling and Design 8, no. 3 (2017): 43–63. http://dx.doi.org/10.4018/ijismd.2017070103.

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This article describes how sequential data modeling is a relevant task in Cybersecurity. Sequences are attributed temporal characteristics either explicitly or implicitly. Recurrent neural networks (RNNs) are a subset of artificial neural networks (ANNs) which have appeared as a powerful, principle approach to learn dynamic temporal behaviors in an arbitrary length of large-scale sequence data. Furthermore, stacked recurrent neural networks (S-RNNs) have the potential to learn complex temporal behaviors quickly, including sparse representations. To leverage this, the authors model network traf

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Martin-Fernandez, Judith, Aurelie Affret, Emma Martel, et al. "Realist evaluation of a theory-based life skills programme aiming to prevent addictive behaviours in adolescents: the ERIEAS study protocol." BMJ Open 10, no. 6 (2020): e034530. http://dx.doi.org/10.1136/bmjopen-2019-034530.

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IntroductionAdolescence is a sensitive life stage during which tobacco, alcohol and cannabis are used as ways to learn and adopt roles. There is a great deal of interest in substance use (SU) prevention programmes for young people that work to change representations of these products and help with mobilisation of life skills. Unfortunately, few existing programmes are evidence-based.In France, a programme called Expériences Animées (EA, Animated Experiences) has been developed, inspired by life skills development programmes that have been proven to be successful. The EA programme uses animated

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Chandrawati, Titi, and Siti Aisyah. "ECE Educator Training: How to Develop Literacy and Environment Education for Children?" JPUD - Jurnal Pendidikan Usia Dini 16, no. 1 (2022): 133–48. http://dx.doi.org/10.21009/jpud.161.09.

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Loving the environment is a character that must be instilled in children from an early age. This study aims to describe how efforts to instil love for the environment in preschool. This research uses a collaboration action research method with the intervention of providing information and motivation about the importance of environmental education for ECE educators. The participants were the ECE community represented by eleven ECE teachers in the Tangerang, Sawangan Bogor, Medan, and Batam areas. Data collection was carried out by focus group discussions and interviews as well as the delivery o

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Vasishta, Shilpa, Raagini Jawa, Sarah Kurz, and Nathan Nolan. "2002. Infectious Diseases fellowship training on caring for people who use drugs: A national survey-based needs assessment." Open Forum Infectious Diseases 10, Supplement_2 (2023). http://dx.doi.org/10.1093/ofid/ofad500.129.

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Abstract Background Infectious complications of substance use are rising nationally among people who use drugs (PWUD), highlighting the need to integrate Infectious Diseases (ID) practice with addiction care. Training experiences among ID fellows, whose practice patterns are likely to be impacted by this syndemic, remain unknown. We conducted a national survey to understand U.S. ID fellows’ training, practices, and perspectives regarding care of PWUD. Methods An 18-item survey was developed to assess program characteristics, clinical practices, and perspectives regarding knowledge, comfort, an

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Baine-Savanhu, Fiona, Shelley Macaulay, Nadja Louw, et al. "Identifying the genetic causes of developmental disorders and intellectual disability in Africa: a systematic literature review." Frontiers in Genetics 14 (May 10, 2023). http://dx.doi.org/10.3389/fgene.2023.1137922.

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Objective: Genetic variants cause a significant portion of developmental disorders and intellectual disabilities (DD/ID), but clinical and genetic heterogeneity makes identification challenging. Compounding the issue is a lack of ethnic diversity in studies into the genetic aetiology of DD/ID, with a dearth of data from Africa. This systematic review aimed to comprehensively describe the current knowledge from the African continent on this topic.Method: Applicable literature published up until July 2021 was retrieved from PubMed, Scopus and Web of Science databases, following PRISMA guidelines

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"11.H. Workshop: Epidemiology of diseases and health inequalities in people with and without intellectual disabilities." European Journal of Public Health 31, Supplement_3 (2021). http://dx.doi.org/10.1093/eurpub/ckab164.831.

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Abstract All people have a right to equal healthcare without discrimination on the basis of disabilities. In practice, however, health inequalities still remain. Ideally we would define future public health having sufficient attention to minority groups and their specific needs. One of these groups is people with intellectual disabilities (ID), defined by severe limitations in adaptive and functional behaviour. As a result of these limitations, people with ID suffer from worse health, higher hospitalisation rates and higher premature mortality compared to people without ID. In reducing these h

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Ramadhanty, Dea, and Nur Maghfirah Aesthetika. "Self-Image and Beauty Standards in the Drama My ID is Gangnam Beauty." Academia Open 8, no. 2 (2024). https://doi.org/10.21070/acopen.8.2023.2920.

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General Background the representation of self-image in media plays a significant role in shaping societal beauty standards. Specific Background this study focuses on the perceptions of audiences regarding self-image in the South Korean drama My ID is Gangnam Beauty, which addresses issues of beauty and self-esteem. Knowledge Gapw while existing literature examines beauty standards, there is limited research on audience reception and the impact of specific media portrayals on self-image perceptions. Aims the research aims to explore how young adults interpret the concept of self-image as presen

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Tang, Zuoli, Zhaoxin Huan, Zihao Li, et al. "One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems." ACM Transactions on Information Systems, November 26, 2024. http://dx.doi.org/10.1145/3705727.

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Sequential recommendation systems aim to predict users’ next likely interaction based on their history. However, these systems face data sparsity and cold-start problems. Utilizing data from other domains, known as multi-domain methods, is useful for alleviating these problems. However, traditional multi-domain methods rely on meaningless ID-based item representation, which makes it difficult to align items with similar meanings from different domains, yielding sup-optimal knowledge transfer. This paper introduces LLM-Rec , a framework that utilizes pre-trained large language models (LLMs) for

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Durant, Kathleen, Linda Jarmulowicz, and Leigh Harrell-Williams. "Spanish Phonological Awareness in Kindergarten Uniquely Supports Second-Grade English Morphological Awareness in Spanish–English Dual Language Learners." Language, Speech, and Hearing Services in Schools, November 27, 2023, 1–20. http://dx.doi.org/10.1044/2023_lshss-23-00027.

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Purpose: This study investigated the longitudinal, cross-linguistic developmental relationships of phonological awareness (PA), letter identification (letter ID), and morphological awareness (MA) in 71 heritage Spanish–English dual language learners (DLLs) in kindergarten and second grade. Method: Multiple linear regression was used to test if kindergarten Spanish and English PA (sound elision and sound matching) and letter ID significantly predicted later English MA (oral derived word stress judgment, oral derivational morpheme blending, written derived word decomposition, and morphologically

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Hung, Nguyen Manh, Nguyen Anh Tuan, and Nguyen Thi Nhu. "TOWARDS SEMANTIC NETWORK OF PHILOSOPHY TERMINOLOGIES FOR LEARNING IN UNIVERSITY IN VIETNAM." European Journal of Political Science Studies 4, no. 2 (2021). http://dx.doi.org/10.46827/ejpss.v4i2.1003.

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<p>Semantic network is so far an effective way for knowledge representation, especially if the matter deals with complexity of terminologies and concepts, which are not standalone, but connected by various relations. One among these fields of knowledge is philosophy, and one fact that the study students of university always face with difficulties when address the system of terminologies and concepts of philosophy. In practice, various tools are using by teachers for helping students understand philosophy terminologies and concepts, i.e. using mindmap tools. In this paper, we suggest a us

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Yuan, Wei, Chaoqun Yang, Guanhua Ye, Tong Chen, Nguyen Quoc Viet Hung, and Hongzhi Yin. "FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services." ACM Transactions on Information Systems, December 20, 2024. https://doi.org/10.1145/3709138.

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Sequential recommendation has been widely studied in the recommendation domain since it can capture users’ temporal preferences and provide more accurate and timely recommendations. To address user privacy concerns, the combination of federated learning and sequential recommender systems (FedSeqRec) has gained growing attention. Unfortunately, the performance of FedSeqRec is still unsatisfactory because the models used in FedSeqRec have to be lightweight to accommodate communication bandwidth and clients’ on-device computational resource constraints. Recently, large language models (LLMs) have

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Ribeiro, Marlese, and Francisco Providência. "Design Ecosystem in Portugal. Education, Research and Entrepreneurship." Diid 1, Digital Special Issue 1 (2024). http://dx.doi.org/10.30682/diiddsi23t5t.

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The article aims to frame the Design Ecosystem in Portugal, presenting data on education, research and employability in design, and identify possible causes for the still fragile connection between design and the industry. In Portugal, the extinction of the Portuguese Design Center, in 2013, exacerbates this lack of representation of design among companies, the public administration, and the general public, an space that is urgent to occupy. Oriented to observe, discuss, and think about the schools and research in design in the context of the national ecosystem, the REDE — Meeting of Design Sc

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Nishikawa, Akihito, Tomu Yanabe, Yuiko Sakuma, Yuma Okuda, and Hiroaki Nishi. "pvFed: Personalized Vertical Federated learning for Client‐Specific Tasks." IEEJ Transactions on Electrical and Electronic Engineering, March 12, 2024. http://dx.doi.org/10.1002/tee.24049.

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Federated Learning (FL) is a distributed machine learning paradigm that enables multiple data holders to collaborate on building machine learning models while preserving the privacy of their data. FL can be categorized as horizontal or vertical, depending on the distribution characteristics of the data. Specifically, horizontal FL uses data partitioned in the sample space, whereas vertical FL uses data partitioned in the feature space. Traditional vertical FL methods aim to facilitate collaboration among clients to infer a single global target. However, these methods may be impractical because

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Zeng, Guo-Hua, Xing-Zheng Zhu, Hong-Rui Yang, Yong-Jia Liang, Yu-Jia Zhai, and Ying-Ying Xu. "Knowledge enhanced protein subcellular localization prediction from 3D fluorescence microscope images." Bioinformatics, June 3, 2025. https://doi.org/10.1093/bioinformatics/btaf331.

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Abstract Motivation Pinpointing the subcellular location of proteins is essential for studying protein function and related diseases. Advances in spatial proteomics have shown that automatic recognition of protein subcellular localization from images could highly facilitate protein translocation analysis and biomarker discovery, but existing machine learning works have been mostly limited to processing 2D images. By contrast, 3D images have higher spatial resolution and allow researchers to observe cellular structures in their natural context, but currently there are only a few studies of 3D i

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Lu, Ziang, Lei Guo, Xu Yu, Zhiyong Cheng, Xiaohui Han, and Lei Zhu. "Federated Semantic Learning for Privacy-preserving Cross-domain Recommendation." ACM Transactions on Information Systems, April 8, 2025. https://doi.org/10.1145/3728359.

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In the evolving landscape of recommender systems, the challenge of effectively conducting privacy-preserving Cross-Domain Recommendation (CDR), especially under strict non-overlapping constraints, has emerged as a key focus. Despite extensive research has made significant progress, several limitations still exist: 1) Previous semantic-based methods fail to deeply exploit rich textual information, since they quantize the text into codes, losing its original rich semantics. 2) The current solution solely relies on the text-modality, while the synergistic effects with the ID-modality are ignored.

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Gliozzi, Valentina, Gian Luca Pozzato, Gabriele Tessore, and Alberto Valese. "Sequent calculi and an efficient theorem prover for conditional logics with selection function semantics." Journal of Logic and Computation, July 29, 2024. http://dx.doi.org/10.1093/logcom/exae037.

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Abstract In this paper we present our final solution to the problem of designing an efficient theorem prover for Conditional Logics with the selection function semantics. Conditional Logics recently have received a renewed attention and have found several applications in knowledge representation and artificial intelligence. In order to provide an efficient theorem prover for Conditional Logics, we introduce labelled sequent calculi for the logics characterized by well-established axioms systems including the axiom of strong centering CS, the axiom of conditional identity ID, the axiom of condi

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Alghadari, Fiki, Bayu Jaya Tama, Sudirman Sudirman, Arie Purwa Kusuma, and Syafa'at Ariful Huda. "Completion for a Geometric-Function Problem: Process and Resources in Efficiency Consideration." Formatif: Jurnal Ilmiah Pendidikan MIPA 12, no. 2 (2022). http://dx.doi.org/10.30998/formatif.v12i2.10365.

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<span id="docs-internal-guid-5ecda03a-7fff-4511-8377-3818966e9cd8"><span>The cognitive level between teachers and students is clearly different in problem-solving. In the mathematics context, especially the function problem was only in geometric expression form, for knowledge construction and student's learning should use their cognitive level capacity. Not only the solving process is based on that, but also learning should be efficient for all students, and analyzing those processes is the purpose of identification inefficient issues in this study. This investigative study was hel

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LaPlante, Abigail, Renata W. Yen, Talia Isaacs, et al. "Enrollment, retention, and strategies for including disadvantaged populations in randomized controlled trials: a systematic review protocol." Systematic Reviews 10, no. 1 (2021). http://dx.doi.org/10.1186/s13643-021-01790-7.

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Abstract Background Many randomized controlled trials fail to reach their target sample size. When coupled with the omission and underrepresentation of disadvantaged groups in randomized controlled trials, many trials fail to obtain data that accurately represents the true diversity of their target population. Policies and practices have been implemented to increase representation of disadvantaged groups in many randomized controlled trials, with some trials specifically targeting such groups. To our knowledge, no systematic review has quantified the enrollment metrics and effectiveness of inc

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Wu, Yiqing, Ruobing Xie, Zhao Zhang, et al. "ID-centric pre-training for recommendation." ACM Transactions on Information Systems, May 19, 2025. https://doi.org/10.1145/3735128.

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Classical sequential recommendation models generally adopt ID embeddings to store knowledge learned from user historical behaviors and represent items. However, these unique IDs are challenging to be transferred to new domains. With the thriving of pre-trained language model (PLM), some pioneer works adopt PLM for pre-trained recommendation, where modality information is considered universal across domains via PLM. Unfortunately, the behavioral information in ID embeddings is verified to currently dominate in recommendation compared to modality information and thus limits these models’ perform

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Kunnari, Sari, Susana Sanduvete Chaves, Salvador Chacon‐Moscoso, et al. "Intervention studies with group design targeting expressive phonology for children with developmental speech and language disorder: A systematic review and meta‐analysis." International Journal of Language & Communication Disorders, August 30, 2024. http://dx.doi.org/10.1111/1460-6984.13110.

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AbstractBackgroundPhonological difficulties are prevalent in children with speech and/or language disorders and may hamper their later language outcomes and academic achievements. These children often form a significant proportion of speech and language therapists’ caseloads. There is a shortage of information on evidence‐based interventions for improving phonological skills in children and adolescents with speech and language disorder.AimsThe aim of this systematic literature review and meta‐analysis was to systematically examine the effects of different intervention approaches on speech prod

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Riggs, Damien. "Who Wants to Be a 'Good Parent'?" M/C Journal 8, no. 1 (2005). http://dx.doi.org/10.5204/mcj.2321.

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   In this paper, I will be looking at how the news media may be both helpful (‘good’) and a hindrance (‘bad’) to lesbian and gay parents. While I acknowledge the incommensurable differences between the experiences of lesbian parents and gay parents, I do believe that representations of both lesbian and gay parents in the media tend to focus on any similarities that exist between (and within) the two groups, rather than looking at the important differences. I would suggest that this is the result of the hetero-normative assumptions that inform the news media, which take heter

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Alhwaiti, Mohammed. "Phonological Awareness and Rapid Automatized Naming: The Mediating Effect of Word Reading and Spelling in Children with Developmental Dyslexia, Attention Deficit Hyperactivity Disorder, and Mild Intellectual Disability." Folia Phoniatrica et Logopaedica, June 16, 2023, 1. http://dx.doi.org/10.1159/000531221.

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<b><i>Introduction:</i></b> In learning to read, children learn to integrate orthographic, phonological, and semantic codes into highly specified and redundant lexical representations. The aim is to test a proposed model for the relationship between phonological awareness (PA) and rapid automatized naming (RAN) as mediated by word reading (WR) and spelling (SP) in children with developmental dyslexia (DD), attention deficit hyperactivity disorder (ADHD), and mild intellectual disability (ID). <b><i>Methods:</i></b> The relation between PA and RAN

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Tercedor-Sánchez, María Isabel, and Francisco Abadía-Molina. "The Role of Images in the Translation of Technical and Scientific Texts1." Meta 50, no. 4 (2009). http://dx.doi.org/10.7202/019857ar.

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Abstract The information transmitted by images accompanying technical and scientific texts id supposed to lead to a better, visually-oriented understanding of the concepts and descriptions contained in the text. Given that conceptualising scientific information entails creating mental representations of the concepts, and since the function of images is complementary to the function of texts, cultural attitudes might well influence many aspects of an image ranging from its contents, to shape or colour. One might ask if the translation process should include the adaptation of original images in

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Abdul-Jabbar, Wisam Khalid. "Pedagogical Reflections on Internalizing Geopolitical Representations in Print Media." Canadian Journal for the Scholarship of Teaching and Learning 6, no. 2 (2015). http://dx.doi.org/10.5206/cjsotl-rcacea.2015.2.4.

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This essay explores how print media conceals implicit hegemonic texts that common readers unsuspectingly tend to internalize. These geopolitically infused texts are set to appropriate the reader’s worldviews by sublimating the kind of perceptions and notions they want to promote. This paper raises questions and awareness about how academia responds to these acts of internalization. These geopolitical texts, which dominate most of the print media and other resources, function at an imperceptible level to legitimize presuppositions and mould the world based on its own political imaginaries. To d

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Lehmann, Marco, Nadine Janis Pohontsch, Thomas Zimmermann, Martin Scherer, and Bernd Löwe. "Diagnostic and treatment barriers to persistent somatic symptoms in primary care – representative survey with physicians." BMC Family Practice 22, no. 1 (2021). http://dx.doi.org/10.1186/s12875-021-01397-w.

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Abstract Background Many patients consult their primary care physician with persistent somatic symptoms such as pain or sickness. Quite often these consultations and further diagnostic measures yield no medical explanation for the symptoms – patients and physicians are left in uncertainty. In fact, diagnostic and treatment barriers in primary care hinder timely health-care provision for patients suffering from persistent somatic symptoms (PSS). The significance of individual barriers is still unknown. We compare and quantify these barriers from the perspective of primary care physicians and id

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