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Integration of Artificial Intelligence in the Organizational Adoption – A Configurational Perspective 42

Integration of Artificial Intelligence in the Organizational...

42nd International Conference on Information Systems: Building Sustainability and Resilience with IS: A Call for Action, ICIS 2021 TREOs

作者： Laut, Philipp Dumbach, Philipp Eskofier, Bjoern M. University of Bamberg Kärntenstraße 7 Bamberg96047 Germany Machine Learning and Data Analytics Lab Carl-Thiersch-Straße 2b Erlangen91052 Germany

ISBN: (纸本)9781713893608

The adoption of artificial intelligence (AI) within organizations is experiencing growing interest. Since AI has distinctive characteristics (automation – augmentation), it is unclear how both characteristics influence the adoption. Besides, current research calls for a configurational perspective within the adoption theory. Building on these research gaps, we use the technology-organization-environment framework (TOE) and combine the AI characteristics ‘automation – augmentation’ and ‘product or service – process’ with the organizational and environmental characteristics: differentiation strategy, resources, entrepreneurial orientation, and network support. We collected a sample of 104 questionnairesfrom top-levelandmiddle-levelmanagersaswellas IT experts. Using fuzzy set Qualitative Comparative Analysis (fsQCA), we reveal four different solutions, namely internal integrator, supportive provider, powerful innovator, and rising enthusiast, that explain the adoption of AI. Moreover, we show that organizations adopting AI have an explicit focus on AI characteristics. Furthermore, we underline the importance of configurational thinking within the adoption. © 2021 42nd International Conference on Information Systems, ICIS 2021 TREOs: "Building Sustainability and Resilience with IS: A Call for Action". All Rights Reserved.

关键词： Automation

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Reducing over-smoothness in speech synthesis using Generative Adversarial Networks

Reducing over-smoothness in speech synthesis using Generativ...

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IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering, SIBIRCON

作者： Leyuan Sheng Evgeniy N. Pavlovskiy Novosibirsk State University Novosibirsk Russia Stream Data Analytics and Machine Learning laboratory Novosibirsk State University Novosibirsk Russia

Speech synthesis is widely used in many practical applications. In recent years, speech synthesis technology has developed rapidly. However, one of the reasons why synthetic speech is unnatural is that it often has over-smoothness. In order to improve the naturalness of synthetic speech, we first extract the mel-spectrogram of speech and convert it into a real image, then take the over-smooth mel-spectrogram image as input, and use image-to-image translation Generative Adversarial Networks(GANs) framework to generate a more realistic mel-spectrogram. Finally, the results show that this method greatly reduces the over-smoothness of synthesized speech and is more close to the mel-spectrogram of real speech.

关键词： Generative adversarial networks Speech synthesis Spectrogram Generators Hidden Markov models Training

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Development of an Application for Audio-Visual-Tactile Brainwave Entrainment in Patients with Affective and Psychosomatic Disorders

Development of an Application for Audio-Visual-Tactile Brain...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Vadim A. Korshunov Grigory R. Khazankin Dmitry S. Ivanishkin Novosibirsk State University Novosibirsk Russia Stream Data Analytics and Machine Learning laboratory Novosibirsk State University Novosibirsk Russia

Brainwave entrainment is used in different types of treatment, one of which is treating affective and psychosomatic disorders. The better result is achieved if individual alpha-peak frequency is taken into account during entrainment and when it includes audio visual and tactile stimulation. The program which allows running stimulation scenarios is required to be available on different platforms because patients need to continue the procedures even after finishing them in hospital. So they need to be able to download and install this control program on their personal computers. The required application was developed as a multiplatform one using. NET Core framework in order to reduce costs of further maintenance.

关键词： Headphones Visualization Neuroscience Hospitals Operating systems Linux Microcomputers

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Exploration of Process Mining Opportunities In Educational Software Engineering - The Gitlab Analyser 13

Exploration of Process Mining Opportunities In Educational S...

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13th International Conference on Educational data Mining, EDM 2020

作者： Dumbach, Philipp Aly, Alexander Zrenner, Markus Eskofier, Bjoern M. Machine Learning and Data Analytics Lab Department of Computer Science Friedrich-Alexander-Universität Erlangen-Nürnberg Carl-Thiersch-Str. 2b Erlangen91052 Germany

ISBN: (纸本)9781733673617

The increasing complexity in software development leads to the necessity for a detailed data analysis. Literature illustrates a stronger research focus on Educational Process Mining (EPM) being applied to the fields of e-learning and professional training. In this work, the opportunities of Process Mining (PM) are further examined by the evaluation of software engineering (SE) courses. The methodology follows the five stages of the L* life cycle model for PM projects using data from software repositories. The event log data was analyzed with the PM tool Disco to examine the students’ work following an agile development process. The new tool Gitlab Analyser supports supervisors to visualize educational processes and still extracts event logs for the further analysis and application of PM techniques. © 2020 Proceedings of the 13th International Conference on Educational data Mining, EDM 2020. All rights reserved.

关键词： data mining

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OculusGraphy: Description and Time Domain Analysis of Full-Field Electroretinograms database

OculusGraphy: Description and Time Domain Analysis of Full-F...

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2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2023

作者： Albasu, Faisal B. Dey, Subhankar Dolganov, Anton Yu. Hamzaoui, Oussama El Mustafa, Wisam M. Zhdanov, Aleksei E. Eng. Sch. of Info. Technologies Telecommunications and Control Systems Ural Federal University Yekaterinburg Russia University of Erlangen-Nuremberg Machine Learning and Data Analytics Lab Erlangen Germany

ISBN: (纸本)9798350336054

Electroretinography is an established electrophysiological technique for clinical investigation of visual health function. The test involves the non-invasive assessment of the retinal function using light stimulation. This study presents a comprehensive database of five types of signals, including Scotopic 2.0 ERG response, Photopic 2.0 ERG response, Maximum 2.0 ERG response, Photopic 2.0 EGR Flicker response and Scotopic 2.0 ERG Oscillatory Potentials. The database includes 1975 signals from 323 patients, consisting of both adults and children. This study seeks to evaluate and analyze the classical parameters of three of the five signals, specifically Scotopic 2.0 ERG response, Photopic 2.0 ERG response, and Maximum 2.0 ERG response, using time-domain analysis. Correlation analysis was conducted in order to gain insights into the potential relationship between a patient's age and the classical parameters. However, the results suggest little to no correlation between these factors. The database presented in this study will serve as a useful resource for further research in the field of electrophysiology. Future research in this area could explore the use of other advanced analysis methods, such as frequency and time-frequency domain analyses, in order to gain further insights into the nuances of these signals and to better differentiate between healthy patients and those with pathologies. Additionally, further research is needed to establish norms for pediatric signals in order to better understand retinal health in children. © 2023 IEEE.

关键词： database systems

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Cascaded Training Pipeline for 3D Brain Tumor Segmentation 7th

Cascaded Training Pipeline for 3D Brain Tumor Segmentation

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7th International Brain Lesion Workshop (BrainLes)

作者： Luu, Minh Sao Khue Pavlovskiy, Evgeniy Novosibirsk State Univ Dept Math & Mech 1 Pirogova St Novosibirsk 630090 Russia Novosibirsk State Univ Stream Data Analyt & Machine Learning Lab 1 Pirogova St Novosibirsk 630090 Russia Innoflex Technol Brisbane Qld Australia

ISBN: (纸本)9783031089992;9783031089985

We apply a cascaded training pipeline for the 3DU-Net to segment each brain tumor sub-region separately and chronologically. Firstly, the volumetric data of four modalities are used to segment the whole tumor in the first round of training. Then, our model combines the whole tumor segmentation with the mpMRI images to segment the tumor core. Finally, the network uses whole tumor and tumor core segmentations to predict enhancing tumor regions. Unlike the standard 3D U-Net, we use Group Normalization and Randomized Leaky Rectified Linear Unit in the encoding and decoding blocks. We achieved dice scores on the validation set of 88.84, 81.97, and 75.02 for whole tumor, tumor core, and enhancing tumor, respectively.

关键词： 3D U-Net Brain tumor segmentation Medical image segmentation

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End-to-End learning for Human Pose Estimation from Raw Millimeter Wave Radar data 58

End-to-End Learning for Human Pose Estimation from Raw Milli...

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58th Asilomar Conference on Signals, Systems and Computers, ACSSC 2024

作者： Mueller, Jonas Engel, Lukas Krauss, Daniel Ullmann, Ingrid Vossiek, Martin Eskofier, Bjoern M. Dorschky, Eva Friedrich-Alexander-Universität Erlangen-Nürnber Machine Learning and Data Analytics Lab Erlangen Germany Friedrich-Alexander-Universität Erlangen-Nürnber Institute of Microwaves and Photonics Erlangen Germany

ISBN: (纸本)9798350354058

Millimeter wave radar has gained considerable attention for its potential to analyze human motion, for example, within home environments. Here, radar offers a privacy-preserving and lighting-insensitive alternative to vision-based systems, particularly in smart home applications such as gesture control or human activity monitoring. Current methods involve pre-processing the raw radar data through multiple Fourier transforms, extracting essential parameters such as range, Doppler, azimuth, and elevation information, and applying a constant false alarm rate algorithm for point cloud extraction. However, this approach relies on numerous hyperparameters, requires expert knowledge, and may result in information loss. Our novel approach involves end-to-end learning of neural networks, resulting in a trainable, data-driven, and sparse method. This method automatically extracts important features from the raw radar data, which increases overall accuracy. First, a neural network architecture incorporating attention mechanism is introduced to train an encoder to represent raw radar data as features in an informative low-dimensional vector space. Second, the mean per joint position error of human poses estimated from these features is evaluated using a dataset encompassing a diverse range of human motions. Third, the results are discussed, and conclusions about large-scale attention-based modeling in the radar-based human pose estimation domain are given. © 2024 IEEE.

关键词： Convolutional neural networks

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Reducing over-smoothness in speech synthesis using Generative Adversarial Networks

arXiv

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arXiv 2018年

作者： Sheng, Leyuan Pavlovskiy, Evgeniy N. Department of Mathematics and Mechanics Novosibirsk State University Novosibirsk Russia Stream Data Analytics and Machine Learning laboratory Novosibirsk State University Novosibirsk Russia

关键词： Generative adversarial networks

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Sensor-based Stride Segmentation and Gait Parameter Extraction Using a Hidden Markov Model in Patients with Hereditary Spastic Paraplegia

Sensor-based Stride Segmentation and Gait Parameter Extracti...

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IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES)

作者： Alzhraa A. Ibrahim Veronika Koch Verena Jakob Arne Küderle Malte Ollenschlager Kathrin Kotter Bjoern M. Eskofier Martin Regensburger Jürgen Winkler Heiko Gaßner Department of Molecular Neurology University Hospital Erlangen Erlangen Germany Fraunhofer IIS Machine Learning and Data Analytics Lab FAU Fraunhofer Institute for Integrated Circuits Erlangen Germany Machine Learning and Data Analytics Lab FAU Erlangen Germany

ISBN: (数字)9798350383409

ISBN: (纸本)9798350383416

Hereditary Spastic Paraplegia (HSP) comprises a group of neurodegenerative disorders causing progressive lower limb symptoms primarily affecting gait functions. Progressive symmetric gait spasticity poses challenges for gait analysis. Traditional motion capture systems offer precise gait parameters but are confined to laboratory settings. In contrast, wearable sensor technology allows for gait analysis settings in real-world environments. Yet, accurate segmentation of gait cycles and ex-traction of temporal parameters remain challenging, particularly in the context of HSP. This paper introduces a comprehensive approach for gait analysis in patients with HSP, comprising two main components: stride segmentation utilizing a Hidden Markov Model (HMM), enabling robust identification of gait cycles from sensor data, and event detection and temporal gait parameter extraction. By leveraging the inherent temporal dynamics of gait patterns captured by wearable sensors, our method aims to overcome the limitations of existing techniques and provide reliable insights into the gait characteristics of HSP patients. Validation of this approach reveals promising results, with an F1 score of 89% for segmentation achieved through to-fold cross-validation. Additionally, our method demonstrates a mean absolute error of 0.008 seconds for stride time estimation compared to a gold standard motion capture system indicating the validity of our approach and its potential utility in hospital and real-world settings.

关键词： Accuracy Event detection Motion segmentation Hidden Markov models Motion capture Reliability Gait recognition Wearable sensors Parameter extraction Foot

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ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing

ProbSAINT: Probabilistic Tabular Regression for Used Car Pri...

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IEEE International Conference on Big data

作者： Kiran Madhusudhanan Gunnar Behrens Maximilian Stubbemann Lars Schmidt-Thieme Information Systems and Machine Learning Lab VWFS Data Analytics Research Center University Of Hildesheim Data Analytics & AI Engineering Volkswagen Financial Services AG

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Used car pricing is a critical aspect of the automotive industry, influenced by many economic factors and market dynamics. With the recent surge in online marketplaces and increased demand for used cars, accurate pricing would benefit both buyers and sellers by ensuring fair transactions. However, the transition towards automated pricing algorithms using machine learning necessitates the comprehension of model uncertainties, specifically the ability to flag predictions that the model is unsure about. Although recent literature proposes the use of boosting algorithms or nearest neighbor-based approaches for swift and precise price predictions, encapsulating model uncertainties with such algorithms presents a complex challenge. We introduce ProbSAINT, a model that offers a principled approach for uncertainty quantification of its price predictions, along with accurate point predictions that are comparable to state-of-the-art boosting techniques. Furthermore, acknowledging that the business prefers pricing used cars based on the number of days the vehicle was listed for sale, we show how ProbSAINT can be used as a dynamic forecasting model for predicting price probabilities for different expected offer durations. Our experiments further indicate that ProbSAINT is especially accurate in instances where it is highly certain. This proves the applicability of its probabilistic predictions in real-world scenarios where trustworthiness is crucial.

关键词： Industries Accuracy Uncertainty machine learning algorithms Pricing Predictive models Probabilistic logic Prediction algorithms Automobiles Vehicle dynamics

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