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LLSDA: Design and Implementation of Lightning Location data Analysis and Visualization

Meteorological and Environmental Research 2023年第5期14卷 36-41,44页

作者： Rong FAN Jingxiao LI Mingyuan LIU Nanjing University of Information Science and Technology Nanjing 210044China Beijing Meteorological Observation Center Beijing 100176China Key Laboratory of Middle Atmosphere and Global Environment Observation(LAGEO) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

Visualizing lightning location data is necessary in analyzing and researching lightning activity *** article uses C#and the *** framework to develop a lightning location data analysis class library and the data-driven client to help lightning researchers improve work efficiency by avoiding repeated wheel *** Location System data Analyzer(LLSDA)is a suite of software tools that includes *** class library for software developers and a desktop application for end *** supports a wide range of lightning location data formats,such as the University of Washington Global Lightning Location System(WWLLN)and Beijing Huayun Dongfang ADTD Lightning Location System data format,and maintains *** class library can easily read,parse,and analyze lightning location data,and combined with third-party frameworks can realize grid *** desktop application can be combined with MeteoInfo(a GIS open-source project)for secondary development.

关键词： Lightning location system The World Wide Lightning Location Network(WWLLN) ADTD MeteoInfo Global Lightning Detection Network(GLD360) Austrian Lightning Detection&Information System(ALDIS) data-driven development Reusable software library

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DESCRIPTIVE ATTRIBUTES OF ANALYSIS USE CASES IN THE data-driven VALIDATION OF ELEMENTS IN THE SYSTEM OF OBJECTIVES

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Proceedings of the Design Society 2023年 3卷 1207-1216页

Usage data of reference systems can be analyzed in the development process for the validation of system elements. The process model for data-driven validation of elements in the system of objectives aids developers in performing such data analyses. The conducted studies show that the basis for an efficient analysis process is a common understanding of the system and the goal of the analysis. Therefore, a template was derived over the course of case studies describing the elements in the system of objectives. The template covers the three descriptive dimensions general information, technical system and data. It allows a comprehensive description of analysis use cases. On average it takes 11 minutes for developers to aggregate all necessary information and consequently fill out the template. An A/B-Test confirmed the comprehensibility and applicability of the template even for developers of different domain knowledge. Through its contribution to a sustainable knowledge management the template provides an added value for the developers for conducting analysis.

关键词： Big data Complexity New product development data-driven development

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Time Series Segmentation for Driving Scenario Detection with Fully Convolutional Networks 7

Time Series Segmentation for Driving Scenario Detection with...

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7th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS)

作者： Elspas, Philip Klose, Yannick Isele, Simon Bach, Johannes Sax, Eric Dr Ing Hc F Porsche AG Weissach Germany FZI Res Ctr Informat Technol Karlsruhe Germany

ISBN: (纸本)9789897585135

Leveraging measurement data for Advanced Driver Assistant Systems and Automated Driving Systems requires reliable meta information about covered driving scenarios. With domain expertise, rule-based detectors can be a scalable way to detect scenarios in large amounts of recorded data. However, rules might struggle with noisy data, large number of variations or corner cases and might miss valuable scenarios of interest. Finding missing scenarios manually is challenging and hardly scalable. Therefore we suggest to complement rule-based scenario detection with a data-driven approach. In this work rule-based detections are used as labels to train Fully Convolutional Networks (RCN) in a weakly supervised setup. Experiments show, that FCNs generalize well and identify additional scenarios of interest. The main contribution of this paper is twofold: First, the scenario detection is formulated as a time series segmentation problem and the capability to learn a meaningful scenario detection is demonstrated. Secondly. we show how the disagreement between the rule-based method and the learned detection method can be analyzed to find wrong or missing detections. We conclude, that the FCNs provide a scalable way to assess the quality of a rule based scenario detection without the need of large amounts of ground truth infromation.

关键词： Scenario Detection data-driven development Time Series Segmentation Fully Convolutional Networks Driving Scenarios

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A data-driven approach for recommending UI element layout

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Science China(Information Sciences) 2020年第9期63卷 61-63页

作者： Yonghao LONG Xiangping CHEN Yuting XIE School of Information Science and Technology National Engineering Research Center of Digital LifeSun Yat-sen University Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion School of Communication and Design Sun Yat-sen University

Dear editor,Smartphones and tablets with rich graphical user interfaces (GUI) are becoming increasingly popular. GUI design plays an important role in offering a smooth user experience. The complexity of the apps often depends on the user interface (UI)[1]with minor data processing or data processing delegates to the backend component.

关键词： UI development Software mining Layout recommendation data-driven development Intelligent Software development

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The Online Controlled Experiment Lifecycle

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IEEE SOFTWARE 2020年第2期37卷 60-67页

作者： Fabijan, Aleksander Dmitriev, Pavel Olsson, Helena Bosch, Jan Malmo Univ Malmo Sweden Outreach Data Sci Seattle WA USA Malmo Univ Dept Comp Sci & Media Technol Malmo Sweden Chalmers Univ Technol Software Engn Gothenburg Sweden

Unlike other techniques for learning from customers, online controlled experiments (OCEs) establish an accurate and causal relationship between a change and the impact observed. We show that OCEs help optimize infrastructure needs and aid in project planning and measuring team efforts. We conclude that product development should fully integrate the experiment lifecycle to benefit from the OCEs.

关键词： Measurement Companies Software Computer science Product development Media Planning data-driven development A B tests online controlled experiments experiment lifecycle

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Leveraging Regular Expressions for Flexible Scenario Detection in Recorded Driving data 6

Leveraging Regular Expressions for Flexible Scenario Detecti...

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6th IEEE International Symposium on Systems Engineering (IEEE ISSE)

作者： Elspas, Philip Langner, Jacob Aydinbas, Michael Bach, Johannes Sax, Eric Dr Ing hcF Porsche AG Weissach Germany FZI Res Ctr Informat Technol Karlsruhe Germany Exxeta AG Karlsruhe Germany

ISBN: (纸本)9781728186023

For the development of Advanced Driver Assistant Systems (ADAS) and Automated Driving Systems (ADS) large amounts of driving data are collected. Storing, processing and analyzing this data requires significant efforts. For these efforts to pay off, data must be made accessible and reusable for different development phases from specification to testing. However, raw measurement data can largely vary in format, configuration and comprehensiveness. Adding meaningful, semantic labels to the data, also called data enrichment, is a promising way to improve searchability and to compute aggregating statistics over large databases. In this work we identify challenges and define requirements for data enrichment of real world measurement data for ADAS and ADS. We suggest a framework as a general and modular processing pipeline to tackle common challenges of real world data. Within this framework we support Boolean expressions to reduce multivariate time series to states of interest. Finally regular expressions are used as a deterministic method to identify semantically meaningful sequences. We demonstrate the flexibility of this approach by detecting lane change and cut-in maneuvers. The proposed methods prove to be well suited for robust maneuver detection with varying durations.

关键词： data-driven development regular expressions scenario detection maneuver detection data programming automated labeling

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Skuld: A self-learning tool for impact-driven technical debt management 3

Skuld: A self-learning tool for impact-driven technical debt...

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3rd IEEE/ACM International Conference on Technical Debt (TechDebt)

作者： Burgaya Pujols, Josep Bas, Pieter Martinez-Fernandez, Silverio Martini, Antonio Trendowicz, Adam Skuld Technol Barcelona Barcelona Spain Fraunhofer IESE Kaiserslautern Germany UPC Kaiserslautern Germany Skuld & Univ Oslo Oslo Norway

ISBN: (纸本)9781450379601

As the development progresses, software projects tend to accumulate Technical Debt and become harder to maintain. Multiple tools exist with the mission to help practitioners to better manage Technical Debt. Despite this progress, there is a lack of tools providing actionable and self-learned suggestions to practitioners aimed at mitigating the impact of Technical Debt in real projects. We aim to create a data-driven, lightweight, and self-learning tool positioning highly impactful refactoring proposals on a Jira backlog. Bearing this goal in mind, the first two authors have founded a startup, called ***, with the vision of becoming the go-to software renovation company. In this tool paper, we present the software architecture and demonstrate the main functionalities of our tool. It has been showcased to practitioners, receiving positive feedback. Currently, its release to the market is underway thanks to an industry-research institute collaboration with Fraunhofer IESE to incorporate self-learning technical debt capabilities.

关键词： Technical Debt Project Management Tool data-driven development

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From Efficiency to Effectiveness: Delivering Business Value Through Software 1

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10th International Conference on Software Business (ICSOB)

作者： Bosch, Jan Chalmers Univ Technol Dept Comp Sci & Engn S-41296 Gothenburg Sweden

ISBN: (数字)9783030337421

ISBN: (纸本)9783030337421;9783030337414

Connected products and DevOps allow for a fundamentally different way of working in R&D. Rather than focusing on efficiency of teams, often expressed in terms of flow and number of features per sprint, we are now able to focus on the effectiveness of R&D as expressed in the amount of value created per unit of R&D. We have developed several solutions, such as HYPEX, HoliDev and hierarchical value models, but companies still experience challenges. In this paper, we provide an overview of the trends driving the transition to focusing on effectiveness, discuss the challenges that companies experience as well as the requirements for a successful transformation.

关键词： Efficiency Effectiveness data-driven development AI-driven development

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Towards a Digital Business Operating System 12th

Towards a Digital Business Operating System

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12th International Joint Conference on Software Technologies (ICSOFT)

作者： Bosch, Jan Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9783319936413;9783319936406

With the increasingly important role of software in industry and society overall, the traditional ways of organizing are becoming increasingly outdated. To remain competitive, companies need to adopt a new, digital business operating mechanism. In this paper, we present such a system consisting of four dimensions, i.e. speed, data, ecosystems and empowerment, and three scopes of work, i.e. operations, development and innovation.

关键词： Agile practices data-driven development Software ecosystems Empowerment

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Challenges and Strategies for Undertaking Continuous Experimentation to Embedded Systems: Industry and Research Perspectives 19th

Challenges and Strategies for Undertaking Continuous Experim...

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19th International Conference on Agile Software development (XP)

作者： Mattos, David Issa Bosch, Jan Olsson, Helena Holmstrom Chalmers Univ Technol Dept Comp Sci & Engn Horselgangen 11 S-41296 Gothenburg Sweden Malmo Univ Dept Comp Sci & Media Technol S-21119 Malmo Sweden

ISBN: (纸本)9783319916026;9783319916019

Context: Continuous experimentation is frequently used in web-facing companies and it is starting to gain the attention of embedded systems companies. However, embedded systems companies have different challenges and requirements to run experiments in their systems. Objective: This paper explores the challenges during the adoption of continuous experimentation in embedded systems from both industry practice and academic research. It presents strategies, guidelines, and solutions to overcome each of the identified challenges. Method: This research was conducted in two parts. The first part is a literature review with the aim to analyze the challenges in adopting continuous experimentation from the research perspective. The second part is a multiple case study based on interviews and workshop sessions with five companies to understand the challenges from the industry perspective and how they are working to overcome them. Results: This study found a set of twelve challenges divided into three areas;technical, business, and organizational challenges and strategies grouped into three categories, architecture, data handling and development processes. Conclusions: The set of identified challenges are presented with a set of strategies, guidelines, and solutions. To the knowledge of the authors, this paper is the first to provide an extensive list of challenges and strategies for continuous experimentation in embedded systems. Moreover, this research points out open challenges and the need for new tools and novel solutions for the further development of experimentation in embedded systems.

关键词： Continuous experimentation data-driven development Controlled experiments Embedded systems

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