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Construction of Investor Profiles Based on Risk Tolerance Prediction 24

Construction of Investor Profiles Based on Risk Tolerance Pr...

2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence, DEAI 2024

作者： Zhang, Bing Zhou, Ye Yu, Shuai Zhang, Kan Suzhou International Development Group Limited Suzhou215000 China Software Technology Co. Ltd. Suzhou215000 China

ISBN: (纸本)9798400717147

As the complexity of financial markets continues to increase, offering personalized investment strategies to investors becomes increasingly important. This study employs trustworthy artificial intelligence technologies to predict investors' risk tolerance and construct their profiles, with the aim of identifying the most suitable investment strategies. The research takes into account investors' demographic information, net assets, and financial and non-financial assets, establishing a reliable investor classification model through the application of LIME and SHAP methods to interpret model predictions. The model aids in enhancing decision-making efficiency for investment managers and optimizing the asset allocation process, offering valuable practical experience for the application of trustworthy AI in the financial sector. © 2024 ACM.

关键词： Forecasting

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Yolo Target Detection Algorithm in Road Scene Based on Computer Vision

Yolo Target Detection Algorithm in Road Scene Based on Compu...

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2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2022

作者： He, Haomin Foxconn Technology Group Visual Software Development Department Shenzhen518110 China

ISBN: (纸本)9781665409025

Using artificial intelligence, computer vision and other technologies, cars can monitor driving conditions to ensure safety or assist driving. As a driver's primary task, finding a parking space is equivalent to 'eyes', which need to identify cars and pedestrians in front of the road. The purpose of this paper is to study the Yolo object detection algorithm for road scenes based on computer vision. This paper expounds the research basis and importance of road object detection, as well as the status quo of traditional road object detection, and deeply studies the progress of road object detection optimization. For the analysis of related technologies, firstly, the grayscale of the image is introduced, then the binarization of the image is introduced, and finally the YOLOv4 is analyzed in detail. The software and hardware environment used in the experiment is introduced, the image collection and label labeling process in the data set used in the experiment is described, and the evaluation indicators commonly used to evaluate target detection algorithms are introduced. Through the comparison of FasterR-CNN, SSD and YOLOv4, The average accuracy rate (mAP) of YOLOv4 reaches 87.2%, which meets the requirements of autonomous vehicles. © 2022 IEEE.

关键词： Computer vision

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Image dehazing based on mist concentration estimation and nonlocal similarity constraint 9

Image dehazing based on mist concentration estimation and no...

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9th Symposium on Novel Photoelectronic Detection technology and Applications

作者： Liu, Yan Wang, Xingchen Wu, Bin Zhang, Xinlei Engineering Hohai University Changzhou China Intelligent Home Software Development Department I ZTE Corporation Nanjing China The 32nd Research Institute of China Electronics Technology Group Corporation Shanghai China

ISBN: (纸本)9781510664432

The atmospheric light scattering and absorption from the aerosols usually cause visible light imaging quality decline. The dark channel prior method is a dehazing method to estimate transmittance or background light, which is suitable for foggy image restoration with the influence of suspended particles. Based on the DCP model, the proposed method combines mist concentration level estimation and nonlocal similarity constraint to improve transmittance estimation accuracy. Firstly, the mist concentration level is calculated from natural scene statistical characteristics of the image. Then the corresponding regularization factor is chosen for transmittance estimation. The local structure similarity constraint is introduced into simplified DCP method to decreasing the uneven transmission estimation error. Weighted quadtree searching method is used to estimate the background light. Finally, the image dehazing model is conducted with the transmission map and background light. The comparative experiments are carried out among the original DCP method, the classical image enhancement method MSRCR and the neural network defogging method PDR-NET. The experimental results show that the mist concentration level prior and nonlocal similarity constraints can optimize the solution of the transmittance. The proposed method has significant effect on increasing the image contrast, reducing mist concentration, keeping texture clarity and edge intensity. © 2023 SPIE.

关键词： Image enhancement

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software fault localization based on eigenvector centrality in complex network theory 24

Software fault localization based on eigenvector centrality ...

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24th IEEE International Conference on software Quality, Reliability and Security Companion, QRS-C 2024

作者： Wu, Wentao Wang, Shihai Shao, Yuanxun Xie, Wandong School of Reliability and Systems Engineering Beihang University Beijing100191 China Science and Technology on Reliability and Environmental Engineering Laboratory China State Key Laboratory of Software Development Environment China Aerospace Science and Engineering Network Information Development CO. Ltd Beijing China Information Center of China North Industries Group Corporation Beijing China

ISBN: (纸本)9798350365658

software debugging plays a crucial role in fault localization tasks, and spectrum-based fault localization (SBFL) is a hot topic in software automation debugging research. However, existing SBFL technologies are generally limited by tie within ranks, where a large number of elements share the same suspiciousness, which in turn severely limits the performance of SBFL. To this end, we propose an SBFL model based on eigenvector centrality (FLEC). This algorithm first utilizes the statement coverage information in the program spectrum to construct a statement network, and adopts the correlation between statements as edge weights. Then, FLEC takes statement suspiciousness as node weight. On this basis, the algorithm utilizes the eigenvector centrality to calculate the weighted suspiciousness of each statement while considering both node importance and correlation between nodes. Finally, FLEC conducted experimental validation on 3 datasets of Defects4J, and the results showed an average improvement of 10.7% in ACC@N compared to the optimal baseline. © 2024 IEEE.

关键词： Program debugging

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Digital agriculture for urban crops: design of an IoT platform for monitoring variables. 25

Digital agriculture for urban crops: design of an IoT platfo...

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2022 IEEE International Conference on Automation/25th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2022

作者： Tovar-Soto, J.P. Gonzalez, Mateo Orrego Sanchez, Jonathan Antonio Sierra The Research Group Gia of Universidad Pedagógica y Tecnológica de Colombia Boyacá Tunja Colombia San Buenaventura University Software Development Technology Bogotá Colombia

ISBN: (纸本)9781665494083

This article presents the design of the hardware and software architecture of a monitoring system for some agroclimatic variables (light radiation and humidity of soil) through a set of technologies based on the Internet of Things (IoT). First, the state of the art is show for identify the more relevant research in the application of the digital agriculture concept. Second, the general architecture of the project is presented, making a description of the hardware and software used in it. Then, the information is broken down into the layers of the architecture, such as: perception layer, network layer and application layer, and the operation of each layer is detailed. Finally, the feasibility information is presented, and some recommendations are presented on future developments and what is expected to be improved in the presented prototype. © 2022 IEEE.

关键词： Agriculture

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Towards Fully Decoupled End-to-End Person Search

Towards Fully Decoupled End-to-End Person Search

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2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023

作者： Zhang, Pengcheng Bai, Xiao Zheng, Jin Ning, Xin Jiangxi Research Institute Beihang University School of Computer Science and Engineering State Key Laboratory of Software Development Environment Beijing China Institute of Semiconductors Chinese Academy of Sciences Cognitive Computing Technology Joint Laboratory Wave Group Beijing China

ISBN: (纸本)9798350382204

End-to-end person search aims to jointly detect and re-identify a target person in raw scene images with a unified model. The detection task unifies all persons while the re-id task discriminates different identities, resulting in conflict optimal objectives. Existing works proposed to decouple end-to-end person search to alleviate such conflict. Yet these methods are still sub-optimal on one or two of the sub-tasks due to their partially decoupled models, which limits the overall person search performance. In this paper, we propose to fully decouple person search towards optimal person search. A task-incremental person search network is proposed to incrementally construct an end-to-end model for the detection and re-id sub-task, which decouples the model architecture for the two sub-tasks. The proposed task-incremental network allows task-incremental training for the two conflicting tasks. This enables independent learning for different objectives thus fully decoupled the model for personsearch. Comprehensive experimental evaluations demonstrate the effectiveness of the proposed fully decoupled models for end-to-end person search. © 2023 IEEE.

关键词： Computer vision

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Behavior Trees and State Machines in Robotics Applications

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IEEE Transactions on software Engineering 2023年第9期49卷 4243-4267页

作者： Ghzouli, Razan Berger, Thorsten Johnsen, Einar Broch Wasowski, Andrzej Dragule, Swaib Chalmers University of Technology Department of Computer Science and Engineering Gothenburg40530 Sweden Ruhr University Bochum Faculty of Computer Science Bochum44801 Germany Chalmers University of Gothenburg Department of Computer Science and Engineering Gothenburg40530 Sweden University of Oslo Department of Informatics Oslo0316 Norway IT University of Copenhagen Software Development Group Copenhagen2300 Denmark

Autonomous robots combine skills to form increasingly complex behaviors, called missions. While skills are often programmed at a relatively low abstraction level, their coordination is architecturally separated and often expressed in higher-level languages or frameworks. State machines have been the go-to language to model behavior for decades, but recently, behavior trees have gained attention among roboticists. Originally designed to model autonomous actors in computer games, behavior trees offer an extensible tree-based representation of missions and are claimed to support modular design and code reuse. Although several implementations of behavior trees are in use, little is known about their usage and scope in the real world. How do concepts offered by behavior trees relate to traditional languages, such as state machines? How are concepts in behavior trees and state machines used in actual applications? This paper is a study of the key language concepts in behavior trees as realized in domain-specific languages (DSLs), internal and external DSLs offered as libraries, and their use in open-source robotic applications supported by the Robot Operating System (ROS). We analyze behavior-tree DSLs and compare them to the standard language for behavior models in robotics: state machines. We identify DSLs for both behavior-modeling languages, and we analyze five in-depth. We mine open-source repositories for robotic applications that use the analyzed DSLs and analyze their usage. We identify similarities between behavior trees and state machines in terms of language design and the concepts offered to accommodate the needs of the robotics domain. We observed that the usage of behavior-tree DSLs in open-source projects is increasing rapidly. We observed similar usage patterns at model structure and at code reuse in the behavior-tree and state-machine models within the mined open-source projects. We contribute all extracted models as a dataset, hoping to inspire the commu

关键词： Modeling languages

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MAEON: An Efficient Weather-Aware Ocean Network Routing Scheme based on Multi-Agent Reinforcement Learning

MAEON: An Efficient Weather-Aware Ocean Network Routing Sche...

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International Workshop on Quality of Service

作者： Shu Yang Yaofeng Liu Laizhong Cui Runsu Zhu College of Computer Science and Software Engineering Shenzhen University Shenzhen China Shenzhen Smart City Technology Development Group Co. Ltd Shenzhen China

ISBN: (数字)9798350350128

ISBN: (纸本)9798350350135

Ocean network communication is more and more important nowadays. However, it faces significant challenges due to its heterogeneity, low reliability, and narrow bandwidth. Compared with traditional networks, the problem worsens under severe weather conditions because communication channels, e.g., microwave links, may degrade badly due to weather changes. While many ocean applications put higher QoS (Quality of Service) requirements on communications, it is difficult to meet them due to fluctuating weather changes. Thus, it is more challenging to model and operate the ocean network as more factors may influence the ***, artificial intelligence opens up new possibilities to meet the challenges because it can adapt to the dynamic changes of the network. In this paper, we formulate the problem by establishing a model between network performance and weather conditions. We try to optimize network utility given the traffic matrix and important weather factors, such as rain, atmospheric absorption, and clouds. To solve the problem, we propose a two-stage and multi-agent optimization algorithm named MAEON (Multi-Agent Efficient Ocean Network). We conduct a comprehensive simulation using generated network topology traffic and real-world weather datasets. We also carry out a case study with datasets from a real-world scenario. The results show that MAEON can improve performance by 21.5% compared with traditional algorithms.

关键词： Adaptation models Network topology Oceans Atmospheric modeling Quality of service Bandwidth Routing

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Strategies for Semi-Automated Registration of Historic Aerial Photographs Utilizing Street and Roof Segmentations as Durable Landmarks 34

Strategies for Semi-Automated Registration of Historic Aeria...

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34th European Modeling and Simulation Symposium, EMSS 2022

作者： Zwettler, Gerald A. Ono, Yuta Stradner, Michael Praschl, Christoph Research Group Advanced Information Systems and Technology Research and Development Department University of Applied Sciences Upper Austria Graduate School of Software and Information Science Iwate Prefectural University Japan Department of Software Engineering School of Informatics Communications and Media University of Applied Sciences Upper Austria

Historical and current aerial photographs are only of great value if the geolocation or address of the photographed areas is also available. In Western Europe, especially Austria, Germany and Czech Republic, there is a market for the sale of aerial photographs of one’s own private residential building. Automated geolocation is a feasible way to enable the sales agents to assign the addresses for the sale more quickly. In the course of this research work, a process chain is modeled that allows the assignment of aerial photographs to residential addresses using machine vision. After model-based rectifying the aerial images to compensate for perspective distortions, larger image blocks get assembled using image stitching. The assignment to a 2D reference map, such as satellite imagery via Google Maps, is done by applying a U-Net CNN after extracting durable image features such as roads or buildings. The mapping of aerial imagery to two-dimensional cartography is either automated via registration approaches or based on manually placed corresponding landmarks and homography. Test runs on imagery between the years 1969 and 2020 show that the labor-intensive process of geolocation of aerial imagery can be solved by the proposed process model in a hybrid way. © 2022 The Authors.

关键词： Antennas

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Towards an Automated System for Reverse Geocoding of Aerial Photographs 30

Towards an Automated System for Reverse Geocoding of Aerial ...

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30th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2022

作者： Praschl, Christoph Stradner, Michael Ono, Yuta Zwettler, Gerald Research Group Advanced Information Systems and Technology Research and Development Department University of Applied Sciences Upper Austria Austria Graduate School of Software and Information Science Iwate Prefectural University Japan Department of Software Engineering School of Informatics Communications and Media University of Applied Sciences Upper Austria Austria

ISBN: (纸本)9788086943336

Aerial photographs of buildings are often used as memorabilia sold by trading companies. Such photographs come with an issue regarding the address of the shown buildings, since the recording location of the camera may be known, but shows a spatial distance to the actual subject of the image. In addition to that, also this recording location is often not known in detail but only roughly in the form of the flight route/area. To address this problem, a methodology for reverse geocoding is proposed, allowing to identify the position of buildings that are photographed from aerial vehicles. This is done using a process for extending recording locations and a second process based on the registration of invariant features within aerial shots compared to maps. © 2022 University of West Bohemia. All rights reserved.

关键词： Aerial photography

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