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11th Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2024

作者： Saklamaeva, Vasilka Pavlič, Luka University of Maribor Faculty of Electrical Engineering and Computer Science Koroška cesta 46 Maribor2000 Slovenia

Effort estimation in agile software development serves as a helpful step to estimate the progress expected in the future development iteration (sprint). Using different estimation methods, developers can estimate how much they can get done, and their assigned project managers can forward this information to the customer. This, in turn, helps to achieve better customer collaboration, respond to changes and deliver a working software in the determined time. With the rising adoption of Artificial Intelligence (AI) in nearly all steps of the Software Development Life Cycle (SDLC), our research motivation was to examine the addition of AI into the planning process of the SDLC, especially regarding effort estimation. This paper encompasses the difference between widespread and AI-driven estimation methods in agile development, as well as the results of their use in an experiment. Our findings suggest that the chosen AI tool significantly overestimated the time required for task implementation. Additionally, users expressed a preference for utilizing AI as a complement to their own expertise, rather than relying on it exclusively. © 2024 Copyright for this paper by its authors.

关键词： CAI conversational AI convo-AI GAI generative AI sprint planning

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Implementing domains in Neo4j

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International Journal of Intelligent Information and Database Systems 2024年第3期16卷 258-285页

作者： Cerjan, Maja Rabuzin, Kornelije Šestak, Martina Faculty of Organization and Informatics Varaždin University of Zagreb Pavlinska 2 Varaždin42000 Croatia Faculty of Electrical Engineering and Computer Science Universiti of Maribor Koroška cesta 46 Maribor2000 Slovenia

Data growth has led to the need to apply new ways to process data. Graph databases are increasing their use, which can be seen over the years, with the Neo4j system being the most common. The biggest problem is the small number of implemented constraints that can be used. One of the shortcomings to be explored is the need to create domains, which are used when large amounts of data are manipulated and where the value needs to be limited or when multiple attributes have the same restrictions and data types. The creation of domains can be applied multiple times. This paper summarises the implementation of domains using Neo4j and the Java programming language. © 2024 Inderscience Enterprises Ltd.

关键词： Graph Databases

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A Cascade of Consequences: Improving an Accident Analysis Method by Learning from a Real Life Telecommunications Accident 13

A Cascade of Consequences: Improving an Accident Analysis Me...

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13th International Conference on Data science, Technology and Applications, DATA 2024

作者： Wienen, Hans C.A. Bukhsh, Faiza A. Vriezekolk, Eelco Pires, Luís Ferreira Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands Dutch Authority for Digital Infrastructure Netherlands

ISBN: (纸本)9789897587078

Telecommunications networks are vital enablers of modern society. Large accidents in these networks that cause their unavailability can therefore have a severe impact on the functioning of society. Learning from these accidents can help prevent them and thus make our society more resilient. In this paper, we present an accident analysis method (TRAM) which we have developed by extending the AcciMap method and we report on its application to analyse a severe accident in a telecommunications network. We validate notation for representing and breaking positive feedback loops in a network breakdown, and we suggest a method to enhance the prioritisation of recommendations derived from our analysis. Furthermore, our research reveals that splitting the analysis based on the expertise of the method’s participants negatively impacts the efficiency of the overall process. © 2024 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Accident Analysis Incident Analysis Telecommunications

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Misuse of Wi-Fi Data to Analyze User Behaviour 15

Misuse of Wi-Fi Data to Analyze User Behaviour

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15th International Conference Elektro, ELEKTRO 2024

作者： Kapicak, Lukas Stipal, Jiri Trubak, Kamil Machnik, Petr Burdiak, Patrik Rozhon, Jan VSB-Technical University of Ostrava Faculty of Electrical Engineering and Computer Science Department of Telecommunications Ostrava Czech Republic

ISBN: (纸本)9798350372359

There has been a huge increase in the number of mobile devices over the past few years. Many mobile users own more than one mobile device. Compared to conventional laptops, mobile devices are constantly active and their users use them outdoors more often than personal computers. Compared to desktop computers, mobile devices accompany their owners on their travels and therefore there is a significant risk of tracking and eavesdropping on user data without a user being aware of it. This paper describes techniques how the attacker could track users by using the Wireless Fidelity (Wi-Fi) network. Every mobile device generates traffic that can be divided into 'Automatic' and 'User'. When' Automatic' traffic is generated, the device can be found because of its pattern. The paper also describes how the attacker can get into the victim's Wi-Fi network without being in its range. When breaching the Wi-Fi network security, the attacker can connect to the victim's network during his first appearance in range of this network. Security pre-cautions and possible directions of future work are discussed at the end of this paper. © 2024 IEEE.

关键词： Personal computers

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GPR Acquisition Methods Comparison 16

GPR Acquisition Methods Comparison

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16th International Conference on Advanced Technologies, Systems and Services in Telecommunications, TELSIKS 2023

作者： Gleich, Dusan Vovk, Marko Smogavec, Primoz Kafedziski, Venceslav Doncov, Nebojsa Faculty of Electrical Engineering and Computer Science Maribor Slovenia Faculty of Electrical Engineering and Information Technologies 1000 Macedonia University of Nis Faculty of Electronic Engineering Nis18000 Serbia

ISBN: (纸本)9798350347029

This paper presents a study for subsurface object detection using different scanning acquisition paths. The air coupled system is considered, which can be easily attached to the unnamed aerial vehicle (UAV). The objective is to determine which acquisition scenario can acquire the largest area of interest. The SFCW radar can generate 200 samples within a frequency range of 500MHz-2.5GHz with pulse repetition interval of 100ms. The TEM antennas are used for transmitting and receiving signals. The following configurations of air coupled GPR are presented: monostatic down-looking and side-looking configurations, bistatic configuration, where antennas were separated for 2 meters, circular configuration with platform rotating along its vertical axis and circular configuration with platform moving along trajectory. The experiments were conducted using a polygon of 3×3×0.5 meters with homogeneous clay structure. Experiments showed that bistatic and circular acquisitions can be used for scanning ground areas of interest between 1 and 1.5 meters, when platform is placed 0.75 m above surface. © 2023 IEEE.

关键词： Landmine detection

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Odometry-Less Indoor Dynamic Object Detection and Localization with Spatial Anticipation

Odometry-Less Indoor Dynamic Object Detection and Localizati...

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2024 IEEE/SICE International Symposium on System Integration, SII 2024

作者： Shen, Zhengcheng Gao, Yi Kästner, Linh Lambrecht, Jens Berlin Institute of Technology Industry Grade Networks and Clouds Faculty of Electrical Engineering and Computer Science Berlin Germany

ISBN: (纸本)9798350312072

The continually evolving image segmentation methods in computer vision can further broaden the cognitive abilities of the robot. As humans, we won't judge if the object is moving by accuracy speed estimation but through semantic information based on visual input. With the existing video segmentation method, the robot can pay more attention to the foreground objects, which are more important for path planning and navigation in most cases. The proposed methods try to deploy the first-person view segmentation method with an RGBD sensor and get the location information and locally egocentric map. The error of the segmentation methods will cause unexpected objects in the egocentric map, and the self-occlusion will influence the location and distance estimation. To further improve the methods, a spatial anticipate unit is embedded into the framework. We improve 5.6% the localization accuracy(RMSE), 12.9% the distance estimation(MAE) with the trained object, and 28.9% the recall for the trained object. The methods also show the margin on the untrained object dataset for similar objects. © 2024 IEEE.

关键词： Semantics

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A Comparative Analysis of the Junction Formation Mechanisms of the Boron on Silicon Junction 33

A Comparative Analysis of the Junction Formation Mechanisms ...

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33rd International Scientific Conference Electronics, ET 2024

作者： Fang, Piet Nihtianov, Stoyan TU Delft Faculty of Electrical Engineering Mathematics and Computer Science Department of Microelectronics Mekelweg 4 Delft Netherlands

ISBN: (纸本)9798350376449

Photodiodes based on the Boron on Silicon junction (B-Si) show excellent responsivity to DUV and VUV photons, radiation hardness, and impressive electrical characteristics. However, the proposed models describing the junction formation mechanism do not sufficiently predict the junction's properties. We analyze two previously proposed models: the ultra-shallow p-n junction model and the charge transfer heterojunction model. We additionally apply the Schottky-Mott theory, a semiconductor-metal heterojunction model. Both the commonalities and incompatibilities between these models are discussed. © 2024 IEEE.

关键词： Heterojunctions

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Impact of Skin Lesion Segmentation Labeling Errors on Convolutional Neural Networks 66

Impact of Skin Lesion Segmentation Labeling Errors on Convol...

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66th International Symposium ELMAR, ELMAR 2024

作者： Sojo, Robert Bencevic, Marin Habijan, Marija Galic, Irena Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Croatia

ISBN: (纸本)9798350375411

Accurate segmentation of skin lesions is critical for dermatological diagnosis and treatment. This study investigates the impact of label errors on the performance of convolutional neural networks in skin lesion segmentation. We conducted experiments using ground truth and simulated erroneous labels to train models and analyzed the effects of the errors using regression analysis. To simulate errors, we assume that errors are more likely to occur in more complex border regions. In addition, we add parameters to bias the errors towards either false positives or false negative regions. The overall effect of the false positive and false negative errors on the Dice coefficient is deceptively low. However, when we observe the false negative or false positive rate of the predictions, we see that they are significantly influenced by the bias of the label errors. In addition, label false positives have a more severe impact on prediction results than label false negatives. We recommend focusing on minimizing label false positives and suggest moving beyond mean Dice Score Coefficients for model evaluation. © 2024 IEEE.

关键词： Convolutional neural networks

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The Effectiveness of CNN-Based Models in Macroscopic Motion Direction Detection 6

The Effectiveness of CNN-Based Models in Macroscopic Motion ...

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6th International Conference on Robotics and computer Vision, ICRCV 2024

作者： Qiu, Zhiyu Chen, Tianqi Hua, Yuxiao Todo, Yuki Graduate School of Natural Science & Technology Kanazawa University Division of Electrical Engineering and Computer Science Kanazawa Japan Kanazawa University Faculty of Electrical Information and Communication Engineering Kanazawa Japan

ISBN: (纸本)9798331527426

Convolutional Neural Networks (CNNs) have revolutionized the field of computer vision, offering significant advancements in image and video recognition, classification, and segmentation tasks. Leveraging hierarchical pattern recognition capabilities, CNNs have demonstrated superior performance over traditional machine learning methods. One particularly critical application of CNNs is in motion direction detection, which is essential for enhancing security in surveillance systems, ensuring safe navigation in autonomous vehicles, and providing valuable insights in sports analytics. In this study, our primary goal was to investigate how different types of input data impact the accuracy of motion direction detection. We applied five distinct preprocessing methods to test the effect of input data on accuracy. Furthermore, we conducted experiments in various object and background scenarios to evaluate adaptability of simple 4-layer CNN, EfficientNetBO and ResNet50 in detecting motion direction. Finally, we tested the noise resistance of these three models. The results indicate that CNNs are capable of extracting the macroscopic motion direction of objects in images. Our study highlights the potential of CNN-based models for efficient and effective motion direction detection. © 2024 IEEE.

关键词： Convolutional neural networks

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In Search for Model-Driven eXplainable Artificial Intelligence 1

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10th IFIP International Workshop on Artificial Intelligence for Knowledge Management, AI4KMES 2023

作者： Ligęza, Antoni Sepiolo, Dominik Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Applied Computer Science AGH University of Krakow al. Mickiewicza 30 Krakow30-059 Poland

ISBN: (数字)9783031610691

ISBN: (纸本)9783031610684

This paper reports on ongoing and innovative research in the area of eXplainable Artificial Intelligence (XAI). A classical XAI task is considered as finding an explanation of the model generated via Machine Learning by identifying the most influential variables for local decision-making. Such an approach suffers from severe limitations. The proposed approach moves the explanatory process to a new, knowledge-level dimension. It is oriented towards Model Discovery, i.e. the internal structure and functions of the components. The concept of Model-Driven XAI is put forward and explained with examples. An experiment on Function Discovery via Grammatical Evolution is reported in brief. © IFIP International Federation for Information Processing 2024.

关键词： Decision making

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