检索结果-内蒙古大学图书馆

Moral Dilemmas of Dutch Prison Staff;a Thematic Overview from All Professional Disciplines

Corrections: Policy, Practice, and Research 2024年第2期9卷 246-263页

作者： Schaap, A.I. Ligtenberg, W.M.R. de Vet, H.C.W. Molewijk, A.C. Stolper, M.M. Department of Ethics Law and Medical Humanities Amsterdam University Medical Center Amsterdam Netherlands Department of Epidemiology and Data Science Amsterdam University Medical Center Amsterdam Netherlands Centre for Medical Ethics Institute of Health and Society Faculty of Medicine University of Oslo Oslo Norway

Prison staff face situations with conflicting interests and values. To strengthen craftsmanship Dutch prison staff reflected upon personal moral dilemmas during Moral Case Deliberation (MCD) sessions. This research aims to gain systematic insight into themes and moral dilemmas Dutch prison staff encounter. Evaluation-forms of 171 MCD-sessions were collected (N = 1065 MCD-participants, N = 171 MCD-facilitators) from 22 teams of different professional disciplines at 3 locations. Our qualitative thematic content analysis included 154 moral dilemmas. We noted the organizational level and professional disciplines the moral dilemmas related to, and how dilemmas were formulated. All professional disciplines within prison work show to encounter a wide range of moral dilemmas, which emerge in and between all organizational levels. “Security” and “cooperation” were frequently mentioned themes, while dilemmas relating to the rehabilitation of prisoners were underrepresented. Some formulations of moral dilemmas were based on frustrations toward colleagues or the organization, expressed “powerlessness” to change practice, or contained normative arguments instead of an open formulation. These insights call for structural facilitation of methods for prison staff to deal with moral dilemmas. Ethics Support Services (ESS), such as MCD-sessions, can be used to further strengthen the moral craftsmanship of prison staff. © 2022 The Author(s). Published with license by Taylor & Francis Group, LLC.

关键词： jails Prisons

来源：评论

学校读者我要写书评

暂无评论

Spatio-Temporal Reasoning on Stratigraphic data in Archaeology: Formalization of the Harris Laws as Inferences Using CIDOC CRM 4

Spatio-Temporal Reasoning on Stratigraphic Data in Archaeolo...

引用

4th Edition of the International Workshop on Semantic Web and Ontology Design for Cultural Heritage, SWODCH 2024

作者： Guillem, Anaïs van Ruymbeke, Muriel Eide, Øyvind de Luca, Livio CNRS UPR MAP 2002 France Munich Germany C2DH University of Luxembourg Luxembourg Department for Digital Humanities University of Cologne Germany Center for Data and Simulation Science University of Cologne Germany

Excavation documentation aims at recording the materiality of the archaeological site uncovered and partially destroyed by the excavation process, with an emphasis on spatial information. The knowledge about the past is built on the recording of physical materiality and its spatiality. In archaeological knowledge production, temporal information is inferred from material and spatial relations. The main objective of this paper is to model the spatio-temporal reasoning process applied on excavation documentation of stratigraphic units and interfaces with the CIDOC CRM family of models, thereby enabling the mapping of Harris matrices to CIDOC CRM, while clarifying the distinction between process documentation and reasoning. We apply a methodology of knowledge representation on the Harris laws. The result is a formal modelling of the Harris matrix laws in the CIDOC CRM family of models, with competency questions (CQs) and associated queries. © 2024 Copyright for this paper by its authors.

关键词： Stratigraphy

来源：评论

学校读者我要写书评

暂无评论

Lookee: Gaze Tracking-based Infant Vocabulary Comprehension Assessment and Analysis 25

Lookee: Gaze Tracking-based Infant Vocabulary Comprehension ...

引用

2025 CHI Conference on Human Factors in Computing Systems, CHI 2025

作者： Kim, Minji Shim, Minkyu Chai, Jun Ho Ko, Eon-Suk Lee, Youngki Computer Science and Engineering Seoul National University Seoul Korea Republic of Sunway University Kuala Lumpur Malaysia Center for Data Science in Humanities Institute of Humanities Chosun University Gwangju Korea Republic of English Language and Literature Chosun University Gwangju Korea Republic of

ISBN: (纸本)9798400713941

Measuring preverbal vocabulary comprehension of young children is vital for early intervention and developmental evaluation, yet challenging due to their limited communication abilities. We introduce Lookee, an AI-powered vocabulary comprehension assessment tool through gaze tracking for toddlers in the preverbal stage. Lookee incorporates the Intermodal Preferential Looking Paradigm (IPLP), which is one of the prominent word comprehension measures for toddlers and estimates word comprehension through a random forest model analysis. We design and validate Lookee through user studies involving 19 toddlers and their parents. Then we identify necessary design requirements from potential stakeholders' perspectives through in-depth interviews including researchers, clinicians, and parents. As a result, Lookee achieves considerable estimation accuracy with sufficient system usability and demonstrates key design requirements for each stakeholder group. From our study, we highlight necessary design implications in developing and validating AI-powered clinical tools for toddlers. © 2025 Copyright held by the owner/author(s).

关键词： Nutrition

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Domain Adaptation for Music Transcription: Exploiting Cross-Version Consistency

Unsupervised Domain Adaptation for Music Transcription: Expl...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Lele Liu Christof Weiß Computational Humanities Center for Artificial Intelligence and Data Science (CAIDAS) University of Würzburg Würzburg Germany

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

With the omnipresence of deep learning approaches in modern signal processing, the generalization of models to unseen domains is of crucial importance. Various strategies have been proposed to address such unsupervised domain adaptation including reconstruction autoencoders and adversarial training. In this paper, we propose another strategy using teacher–student learning, where we train a student model for the target domain using pseudo-labels generated by a teacher model trained on the source domain. To improve the adaptation, we propose to exploit cross-version data, i.e., target-domain data without labels but existing in different versions, which are expected to share the same labels. We process the pseudo-labels from the teacher model by keeping only consistent labels or by interpolating conflicting labels. In this paper, we demonstrate the proposed strategy for a music transcription subtask (multi-pitch estimation) using different performances of the same composition. We compare this strategy with a baseline method using a reconstruction autoencoder. Furthermore, we combine our strategy with the baseline method by enforcing the cross-version consistency of the target domain predictions. Our results show that our strategy helps to improve the unsupervised domain adaptation from one instrument (piano) to other instruments (singing and orchestra). Especially for the difficult transfer from piano music to complex orchestral music, we obtain substantial improvements using the proposed approach.

关键词： Training Deep learning Adaptation models Interpolation Instruments Autoencoders Estimation Signal processing Multiple signal classification Speech processing

来源：评论

学校读者我要写书评

暂无评论

Estimation of Local Geometric Structure on Manifolds from Noisy data

arXiv

引用

arXiv 2025年

作者： Aizenbud, Yariv Sober, Barak Department of Mathematics Tel Aviv University Department of Statistics and Data Science Center of Digital Humanities The Hebrew University of Jerusalem

A common observation in data-driven applications is that high-dimensional data have a low intrinsic dimension, at least locally. In this work, we consider the problem of point estimation for manifold-valued data. Namely, given a finite set of noisy samples of M, a d dimensional submanifold of RD, and a point r near the manifold we aim to project r onto the manifold. Assuming that the data was sampled uniformly from a tubular neighborhood of a k-times smooth boundaryless and compact manifold, we present an algorithm that takes r from this neighborhood and outputs pˆn ∈ RD, and (Formula Presented) an element in the Grassmannian Gr(d,D). We prove that as the number of samples n → ∞, the point pˆn converges to p ∈ M, the projection of r onto M, and (Formula Presented) converges to TpM (the tangent space at that point) with high probability. Furthermore, we show that pˆn approaches the manifold with an asymptotic rate of n−k/2k+d, and that (Formula Presented) approach p and TpM correspondingly with asymptotic rates of n−k/2k+d Copyright © 2025, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving 16

Keyword-based Natural Language Premise Selection for an Auto...

引用

16th Workshop on Graph-Based Methods for Natural Language Processing, TextGraphs 2022, in conjunction with the 29th International Conference on Computational Linguistics, COLING 2022

作者： Dastgheib, Doratossadat Asgari, Ehsaneddin Language Processing and Digital Humanities Lab Tehran Iran Department of Computer and Data Science Shahid Beheshti University Tehran Iran NLP Expert Center Data:Lab Volkswagen AG Munich Germany

Extraction of supportive premises for a mathematical problem can contribute to profound success in improving automatic reasoning systems. One bottleneck in automated theorem proving is the lack of a proper semantic information retrieval system for mathematical texts. In this paper, we show the effect of keyword extraction in the natural language premise selection (NLPS) shared task proposed in TextGraph-16 that seeks to select the most relevant sentences supporting a given mathematical statement. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Extraction

来源：评论

学校读者我要写书评

暂无评论

Value Identification in Multistakeholder Recommender Systems for humanities and Historical Research: The Case of the Digital Archive *** 2

Value Identification in Multistakeholder Recommender Systems...

引用

2nd Workshop on the Normative Design and Evaluation of Recommender Systems, NORMalize 2024

作者： Atzenhofer-Baumgartner, Florian Geiger, Bernhard C. Vogeler, Georg Kowald, Dominik Institute of Interactive Systems and Data Science Graz University of Technology Graz Austria Department of Digital Humanities University of Graz Graz Austria Know Center Research GmbH Graz Austria Signal Processing and Speech Communication Laboratory Graz University of Technology Graz Austria

Recommender systems remain underutilized in humanities and historical research, despite their potential to enhance the discovery of cultural records. This paper offers an initial value identification of the multiple stakeholders that might be impacted by recommendations in ***, a digital archive for historical legal documents. Specifically, we discuss the diverse values and objectives of its stakeholders, such as editors, aggregators, platform owners, researchers, publishers, and funding agencies. These in-depth insights into the potentially conflicting values of stakeholder groups allow designing and adapting recommender systems to enhance their usefulness for humanities and historical research. Additionally, our findings will support deeper engagement with additional stakeholders to refine value models and evaluation metrics for recommender systems in the given domains. Our conclusions are embedded in and applicable to other digital archives and a broader cultural heritage context. © 2024 Copyright for this paper by its authors.

关键词： Embedded systems

来源：评论

学校读者我要写书评

暂无评论

Overview of EvaHan2024: The First International Evaluation on Ancient Chinese Sentence Segmentation and Punctuation 3

Overview of EvaHan2024: The First International Evaluation o...

引用

3rd Workshop on Language Technologies for Historical and Ancient Languages, LT4HALA 2024

作者： Li, Bin Chang, Bolin Xu, Zhixing Feng, Minxuan Xu, Chao Qu, Weiguang Shen, Si Wang, Dongbo School of Chinese Language and Literature Nanjing Normal University China Center for Language Big Data and Computational Humanities Nanjing Normal University China Faculty of Arts and Humanities University of Macau China School of Computer and Electronic Information Nanjing Normal University China School of Economics and Management Nanjing University of Science and Technology China College of Information Management Nanjing Agricultural University China

ISBN: (纸本)9782493814463

Ancient Chinese texts have no sentence boundaries and punctuation. Adding modern Chinese punctuation to theses texts requires expertise, time and efforts. Automatic sentence segmentation and punctuation is considered as a basic task for Ancient Chinese processing, but there is no shared task to evaluate the performances of different systems. This paper presents the results of the first ancient Chinese sentence segmentation and punctuation bakeoff, which is held at the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) 2024. The contest uses metrics for detailed evaluations of 4 genres of unpublished texts with 11 punctuation types. Six teams submitted 32 running results. In the closed modality, the participants are only allowed to use the training data, the highest obtained F1 scores are respectively 88.47% and 75.29% in sentence segmentation and sentence punctuation. The perfermances on the unseen data is 10 percent lower than the published common data, which means there is still space for further improvement. The large language models outperform the traditional models, but LLM changes the original characters around 1-2%, due to over-generation. Thus, post-processing is needed to keep the text consistancy. © 2024 ELRA Language Resources Association: CC BY-NC 4.0.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Can Lexicon-Based Sentiment Analysis Boost Performances of Transformer-Based Models? 7

Can Lexicon-Based Sentiment Analysis Boost Performances of T...

引用

7th International Conference on New Media Studies, CONMEDIA 2023

作者： Manik, Lindung Parningotan Susianto, Harry Dinakaramani, Arawinda Pramanik, Niken Suhardijanto, Totok National Research and Innovation Agency Research Center for Data and Information Sciences Bandung Indonesia University of Nusa Mandiri Department of Computer Science Jakarta Indonesia University of Indonesia Faculty of Psychology Depok Indonesia University of Indonesia Faculty of Computer Science Depok Indonesia University of Indonesia Faculty of Humanities Department of Linguistics Depok Indonesia

ISBN: (纸本)9798350307504

An essential endeavor in natural language processing, sentiment analysis entails determining the sentiment expressed in a text. Transformer-based models like BERT have attained state-of-the-art performance in sentiment analysis tasks. However, these algorithms may have difficulty distinguishing sentiment-laden words. In response, we proposed combining lexicon-based sentiment analysis and transformer-based models. This study investigates the effect of lexicon-based sentiment analysis, particularly SentiStrength, on BERT's efficacy in sentiment analysis tasks. Experimental evaluations reveal that incorporating sentiment lexicons enhances the accuracy and F1-score of classical sentiment analysis compared to the baseline BERT model. Our findings demonstrate the value of incorporating external knowledge sources into transformer-based sentiment analysis models. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

AI Fairness-From Machine Learning to Federated Learning

引用

Computer Modeling in Engineering & sciences 2024年第5期139卷 1203-1215页

作者： Lalit Mohan Patnaik Wenfeng Wang Consciousness Studies Program School of HumanitiesNational Institute of Advanced StudiesBangalore560012India Research Institute of Intelligent Engineering and Data Applications Shanghai Institute of TechnologyShanghai201418China Research Center of Ecology and Environment of Central Asia Chinese Academy of SciencesUrumqi830011China Applied Nonlinear Science Lab Anand International College of EngineeringJaipur391320India London Institute of Technology The ASE-London CTI of SCOLondonCR26EQUK Sino-Indian Joint Research Center of AI and Robotics The IMT InstituteBhubaneswar752054India

This article reviews the theory of fairness in AI-frommachine learning to federated learning,where the constraints on precision AI fairness and perspective solutions are also *** a reliable and quantitative evaluation of AI fairness,many associated concepts have been proposed,formulated and ***,the inexplicability of machine learning systems makes it almost impossible to include all necessary details in the modelling stage to ensure *** privacy worries induce the data unfairness and hence,the biases in the datasets for evaluating AI fairness are *** imbalance between algorithms’utility and humanization has further reinforced *** for federated learning systems,these constraints on precision AI fairness still *** solution is to reconcile the federated learning processes and reduce biases and imbalances accordingly.

关键词： Formulation evaluation classification constraints imbalance biases

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：