1167 research outputs found
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Research data to "Digital assistance systems to implement Machine Learning in manufacturing: A systematic review"
No full textImplementing machine learning technologies in manufacturing environment relies heavily on human expertise in terms of domain and machine learning knowledge. Yet, the required machine learning knowledge is often not available in manufacturing companies. A possible solution to overcome this competence gap and let domain experts with limited machine learning programming skills build viable applications are digital assistance systems that support the implementation. At the present, there is no comprehensive overview over corresponding assistance systems. Thus, within this study a systematic literature review based on the PRISMA-P process was conducted. Twenty-nine papers were identified and analyzed in depth regarding machine learning use case, required resources and research outlook. The available data show the procedure and explain how the authors arrived at the results of the accompanying paper.
MeCP2-driven chromatin organization controls nuclear stiffness
No full textDNA organization on chromatin has been largely studied for its consequences in gene expression, but its contribution to the cell mechanics is often neglected despite the nucleus being the stiffest organelle in the cell. Here, we show that MeCP2 directly increases the nuclear stiffness in a similar fashion as it clusters the heterochromatin. Moreover, we show how this phenomenon occurs during cellular differentiation and how it can be disrupted by mutations related to diseases
Re3: A Holistic Framework and Dataset for Modeling Collaborative Document Revision
No full textA dataset of aligned scientific paper revisions manually labeled according to their action and intent, and supplemented with the respective peer reviews and human-written edit summaries. For more details, please refer to the paper -- Re3: A Holistic Framework and Dataset for Modeling Collaborative Document Revision (https://arxiv.org/abs/2406.00197).Re3-Sci_v
Motion of a rigid sphere entering and penetrating a deep pool. Prasanna Kumar Billa, Tejaswi Josyula and Cameron Tropea, Pallab Sinha Mahapatra. under review at Journal of Fluid Mechanics
No full textThe PDF Repository_plan gives an overview of the data and files contained in this repository item.
The Manuscript_readme.txt file describes what is in the zip file "Manuscript_data" and the Supplementary_information.txt file describes what is contained in the zip file "Supplementary_Information"
The End of the Canonical IoT Botnet: A Measurement Study of Mirai's Descendants
No full textThis dataset contains the scripts and data to reproduce the experiments and results presented in the paper "The End of the Canonical IoT Botnet: A Measurement Study of Mirai's Descendants
Laser Writing of Block-Copolymer Images into Mesopores UsingSBDC-Initiated Visible-Light-Induced Polymerization:Public_Data
No full textPowerPoint File of the public data of the paper, including responsive Origin Data. (In addition, there is a zip-archive including the raw data for the figures.
Emotional Eyes for Automated Vehicles: Investigating Design Dimensions and Pedestrian Acceptance - Supplementary Material
No full textThis dataset is supplementary material to a publication of an online survey investigating emotional eyes of automated vehicles (AVs) for AV-pedestrian interaction. The online survey included a study section on emotion recognition in abstract eye design and a study section on the acceptance of an AV expressing emotions on its avatar head in interaction with pedestrians. In the first study section, participants watched eighteen videos of the eye designs devoid of vehicle context and were tasked with assigning the correct emotions to them using a forced-choice paradigm. For each of Ekman's six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise), specifications for the design dimensions shape, color and motion were used to create three eye designs building on each other: design 1: shape; design 2: shape and color; design 3: shape, color and motion. The second study section comprised the description of six short user scenarios with interactions between an anthropomorphic AV (EDAG CityBot) and a pedestrian in road traffic, each accompanied by a video created in a virtual reality environment showing the AV expressing the situation-specific emotion using eye design 3 on its avatar head. The eighteen videos (Eye_Design_1/2/3_Anger.mp4, Eye_Design_1/2/3_Disgust.mp4, Eye_Design_1/2/3_Fear.mp4, Eye_Design_1/2/3_Happiness.mp4, Eye_Design_1/2/3_Sadness.mp4, Eye_Design_1/2/3_Surprise.mp4) from the first study section on emotion recognition and the six videos (AV_Eye_Design_3_Anger.mp4, AV_Eye_Design_3_Disgust.mp4, AV_Eye_Design_3_Fear.mp4, AV_Eye_Design_3_Happiness.mp4, AV_Eye_Design_3_Sadness.mp4, AV_Eye_Design_3_Surprise.mp4) as well as six scenario descriptions (Scenario_Descriptions.pdf) from the second study section on emotion acceptance can be viewed here
Grafting and controlled release of antimicrobial peptides from mesoporous silica: Public data
No full textPowerPoint File of the public data of the paper, including responsive Origin Data. (In addition, there is a zip-archive including the raw data for the figures.
Common Vulnerability Scoring System Prediction Based on Open Source Intelligence Information Sources [Data Set & Models]
No full textThis repository contains the dataset used to train BERT-based models based on open information sources. We aimed to build a more robust model to predict the Common Vulnerability Scoring System (CVSS) score. The repository with the source code used to train and evaluate the models can be found in [this repository](https://github.com/PEASEC/Open-Information-CVSS-Prediction). Please cite the original paper when using this data: "Kuehn, P., Relke, D. N., & Reuter, C. (2023). Common vulnerability scoring system prediction based on open source intelligence information sources. Computers & Security
Outputs for Fine-Tuning with Divergent Chains of Thought Boosts Reasoning Through Self-Correction in Language Models
No full textRaw responses from the models, clean answers, post-processed predictions and evaluation results for each model and dataset using in the publication Fine-Tuning with Divergent Chains of Thought Boosts Reasoning Through Self-Correction in Language Models1.