IT-Information Technology最新文献

Wildfire prediction for California using and comparing Spatio-Temporal Knowledge Graphs 基于时空知识图的加州野火预测与比较

IT-Information Technology Pub Date : 2023-11-09 DOI: 10.1515/itit-2023-0061

Martin Böckling, Heiko Paulheim, Sarah Detzler

引用次数: 0

Machine learning in AI Factories – five theses for developing, managing and maintaining data-driven artificial intelligence at large scale 人工智能工厂中的机器学习——关于大规模开发、管理和维护数据驱动的人工智能的五篇论文

IT-Information Technology Pub Date : 2023-11-09 DOI: 10.1515/itit-2023-0028

Wolfgang Hildesheim, Taras Holoyad, Thomas Schmid

{"title":"Machine learning in AI Factories – five theses for developing, managing and maintaining data-driven artificial intelligence at large scale","authors":"Wolfgang Hildesheim, Taras Holoyad, Thomas Schmid","doi":"10.1515/itit-2023-0028","DOIUrl":"https://doi.org/10.1515/itit-2023-0028","url":null,"abstract":"Abstract The use of artificial intelligence (AI) is today’s dominating technological trend across all industries. With the maturing of deep learning and other data-driven techniques, AI has over the last decade become an essential component for an increasing number of products and services. In parallel to this development, technological advances have been accelerating the production of novel AI models from large-scale datasets. This global phenomenon has been driving the need for an efficient industrialized approach to develop, manage and maintain AI models at large scale. Such an approach is provided by the state-of-the-art operational concept termed AI Factory, which refers to an infrastructure for AI models and implements the idea of AI as a Service (AIaaS). Moreover, it ensures performance, transparency and reproducibility of AI models at any point in the continuous AI development process. This concept, however, does not only require new technologies and architectures, but also new job roles. Here, we discuss current trends, outline requirements and identify success factors for AI Factories. We conclude with recommendations for their successful use in practice as well as perspectives on future developments.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135192945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning applications 机器学习应用

IT-Information Technology Pub Date : 2023-11-06 DOI: 10.1515/itit-2023-0109

Natanael Arndt, Paul Molitor, Ricardo Usbeck

引用次数: 0

Machine learning in sensor identification for industrial systems 工业系统传感器识别中的机器学习

IT-Information Technology Pub Date : 2023-10-09 DOI: 10.1515/itit-2023-0051

Lucas Weber, Richard Lenz

引用次数: 0

Machine learning and cyber security 机器学习和网络安全

IF 0.9

IT-Information Technology Pub Date : 2023-09-04 DOI: 10.1515/itit-2023-0050

S. Karius, Mandy Knöchel, Sascha Heße, Tim Reiprich

{"title":"Machine learning and cyber security","authors":"S. Karius, Mandy Knöchel, Sascha Heße, Tim Reiprich","doi":"10.1515/itit-2023-0050","DOIUrl":"https://doi.org/10.1515/itit-2023-0050","url":null,"abstract":"Abstract Cyber Security has gained a significant amount of perceived importance when talking about the risks and challenges that lie ahead in the field of information technology. A recent increase in high-profile incidents involving any form of cyber criminality have raised the awareness of threats that were formerly often hidden from public perception, e.g., with openly carried out attacks against critical infrastructure to accompany traditional forms of warfare, extending those to the cyberspace. Add to that very personal experience of everyday social engineering attacks, which are cast out like a fishing net on a large scale, e.g., to catch anyone not careful enough to double-check a suspicious email. But as the threat level rises and the attacks become even more sophisticated, so do the methods to mitigate (or at least recognize) them. Of central importance here are methods from the field of machine learning (ML). This article provides a comprehensive overview of applied ML methods in cyber security, illustrates the importance of ML for cyber security, and discusses issues and methods for generating good datasets for the training phase of ML methods used in cyber security. This includes own work on the topics of network traffic classification, the collection of real-world attacks using honeypot systems as well as the use of ML to generate artificial network traffic.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48414742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning in computational literary studies 计算机文学研究中的机器学习

IF 0.9

IT-Information Technology Pub Date : 2023-08-25 DOI: 10.1515/itit-2023-0041

Hans Ole Hatzel, Haimo Stiemer, Chris Biemann, Evelyn Gius

{"title":"Machine learning in computational literary studies","authors":"Hans Ole Hatzel, Haimo Stiemer, Chris Biemann, Evelyn Gius","doi":"10.1515/itit-2023-0041","DOIUrl":"https://doi.org/10.1515/itit-2023-0041","url":null,"abstract":"Abstract In this article, we provide an overview of machine learning as it is applied in computational literary studies, the field of computational analysis of literary texts and literature related phenomena. We survey a number of scientific publications for the machine learning methodology the scholars used and explain concepts of machine learning and natural language processing while discussing our findings. We establish that besides transformer-based language models, researchers still make frequent use of more traditional, feature-based machine learning approaches; possible reasons for this are to be found in the challenging application of modern methods to the literature domain and in the more transparent nature of traditional approaches. We shed light on how machine learning-based approaches are integrated into a research process, which often proceeds primarily from the non-quantitative, interpretative approaches of non-digital literary studies. Finally, we conclude that the application of large language models in the computational literary studies domain may simplify the application of machine learning methodology going forward, if adequate approaches for the analysis of literary texts are found.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46585101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial intelligence for molecular communication 用于分子通信的人工智能

IF 0.9

IT-Information Technology Pub Date : 2023-08-03 DOI: 10.1515/itit-2023-0029

Max Bartunik, J. Kirchner, Oliver Keszöcze

{"title":"Artificial intelligence for molecular communication","authors":"Max Bartunik, J. Kirchner, Oliver Keszöcze","doi":"10.1515/itit-2023-0029","DOIUrl":"https://doi.org/10.1515/itit-2023-0029","url":null,"abstract":"Abstract Molecular communication is a novel approach for data transmission between miniaturised devices, especially in contexts where electrical signals are to be avoided. The communication is based on sending molecules (or other particles) at nanoscale through a typically fluid channel instead of the “classical” approach of sending electrons over a wire. Molecular communication devices have a large potential in future medical applications as they offer an alternative to antenna-based transmission systems that may not be applicable due to size, temperature, or radiation constraints. The communication is achieved by transforming a digital signal into concentrations of molecules that represent the signal. These molecules are then detected at the other end of the communication channel and transformed back into a digital signal. Accurately modeling the transmission channel is often not possible which may be due to a lack of data or time-varying parameters of the channel (e.g., the movements of a person wearing a medical device). This makes the process of demodulating the signal (i.e., signal classification) very difficult. Many approaches for demodulation have been discussed in the literature with one particular approach having tremendous success – artificial neural networks. These artificial networks imitate the decision process in the human brain and are capable of reliably classifying even rather noisy input data. Training such a network relies on a large set of training data. As molecular communication as a technology is still in its early development phase, this data is not always readily available. In this paper, we discuss neural network-based demodulation approaches relying on synthetic simulation data based on theoretical channel models as well as works that base their network on actual measurements produced by a prototype test bed. In this work, we give a general overview over the field molecular communication, discuss the challenges in the demodulations process of transmitted signals, and present approaches to these challenges that are based on artificial neural networks.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46443869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Machine learning in run-time control of multicore processor systems 多核处理器系统运行时控制中的机器学习

IF 0.9

IT-Information Technology Pub Date : 2023-08-02 DOI: 10.1515/itit-2023-0056

F. Maurer, Moritz Thoma, A. Surhonne, Bryan Donyanavard, A. Herkersdorf

引用次数: 0

Design of an IoPT approach to create a cocktail robot station with robotic arm: components, interfaces and control 用IoPT方法制造带有机械臂的鸡尾酒机器人工作站:组件、接口和控制

IF 0.9

IT-Information Technology Pub Date : 2023-06-01 DOI: 10.1515/itit-2023-0006

Nataliia Klievtsova, M. Fuschlberger

{"title":"Design of an IoPT approach to create a cocktail robot station with robotic arm: components, interfaces and control","authors":"Nataliia Klievtsova, M. Fuschlberger","doi":"10.1515/itit-2023-0006","DOIUrl":"https://doi.org/10.1515/itit-2023-0006","url":null,"abstract":"Abstract Successful and profitable companies in the 21st century have to integrate and adapt modern technologies to reach productivity and sustainability goals. While large enterprises have the resources (human, knowledge, and technology) to incorporate automation hardware and the required computational means to support automation, for small and medium enterprises (SMEs) finding the necessary resources is much more difficult. Even though benefits from such modifications are obvious (i.e., gain new clients, improve current process performance or break into new market), SMEs often lack the human resources and knowledge to implement automation. With the development of the Internet of Things (IoT), devices, sensors and platforms are becoming more affordable and available for companies and businesses, that are not connected with IT technologies, industrial sector, etc. In order to simplify automation for SMEs, simple and standardized integration procedures and best practice examples are important. In this paper we propose the concept and design of a smart bar system that is based on the Internet of Processes and Things (IoPT) concept which is able to prepare and serve drinks to clients based on smart features.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42255145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IoT-enriched event log generation and quality analytics: a case study 物联网丰富的事件日志 生成与质量分析：一个案例研究

IF 0.9

IT-Information Technology Pub Date : 2023-06-01 DOI: 10.1515/itit-2022-0077

J. Grüger, Lukas Malburg, Ralph Bergmann

引用次数: 1