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检索条件"丛书名=Lecture Notes in Networks and Systems"

共 9894 条记录，以下是3901-3910 订阅

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Production Portfolio Theory II-First Steps Towards a General Portfolio Theory and Numerical Examplifications

Production Portfolio Theory II-First Steps Towards a General...

引用

Intelligent systems Conference (IntelliSys)

作者： Heiden, Bernhard Tonino-Heiden, Bianca Univ Appl Sci Villach Austria Karl Franzens Univ Graz Graz Austria

ISBN: (纸本)9783031477201;9783031477218

This paper formalises the Production Portfolio Theory in more statistical and application-oriented detail, gives the first steps towards a General Portfolio Theory and shows some connections to self-organisational theory and cybernetic informational systems. The paper further demonstrates the Production Portfolio Theory with examples. Above this, we analyse the possible applications of this theory, show similarities and differences to Portfolio Theory from Markowitz, where it is inherited from, and give connections to future cybernetics and numerical information computational systems and an outlook for further research questions in the field.

关键词： Optimisation Computational Intelligence Economic Application Markowitz Portfolio Theory Economy Production Statistics Production Portfolio Theory General Portfolio Theory

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Data Analysis Methods: Comparative Review and Selection of the Best Approach 13th

Data Analysis Methods: Comparative Review and Selection of t...

引用

13th Computer Science Online Conference

作者： Tynchenko, Yadviga Gantimurov, Andrei Kukartsev, Vladislav Gladkov, Alexey Borodulin, Aleksey Siberian Fed Univ Lab Biofuel Composit Krasnoyarsk 660041 Russia Reshetnev Siberian State Univ Sci & Technol Dept Syst Anal & Operat Res Krasnoyarsk 660037 Russia Bauman Moscow State Tech Univ Artificial Intelligence Technol Sci & Educ Ctr Moscow 105005 Russia Reshetnev Siberian State Univ Sci & Technol Inst Engn & Econ Dept Informat Econ Syst Krasnoyarsk 660037 Russia Siberian Fed Univ Inst Space & Informat Technol Dept Informat Krasnoyarsk 660041 Russia

ISBN: (纸本)9783031705946;9783031705953

This paper aims to develop skills in data processing and analysis, as well as contribute to a deeper understanding of the problem or phenomenon that is reflected in the provided dataset. The results of this paper can not only serve as a basis for decision making in a particular area, but also provide new research opportunities for future studies and projects.

关键词： Socio-Economic Development Equal Wages Economic Development Policy Minimum Wages Modern Slavery

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Surveying Strategies: Detecting Sinkhole Attacks in IoT networks 5th

Surveying Strategies: Detecting Sinkhole Attacks in IoT Netw...

引用

5th International Conference on Communication and Intelligent systems (ICCIS)

作者： Shanthini, S. Hitha Joice, C. Sheeba Saveetha Engn Coll Chennai Tamil Nadu India

ISBN: (纸本)9789819720811;9789819720828

In the IoT sphere, sinkhole attacks pose serious threats to the network layer, risking both its integrity and security. These attacks reroute network traffic to an unauthorized node, allowing malicious entities to intercept and manipulate sensitive data. Detecting and mitigating sinkhole attacks is crucial to safeguarding the network infrastructure and maintaining data confidentiality. This survey systematically examines various approaches to detect sinkhole attacks, covering implementation methods, detection strategies, and software applications. It also aims to uncover emerging trends and highlight ongoing research challenges in sinkhole attack detection. Serving as a valuable resource, this survey equips network security practitioners, administrators, and researchers with the necessary knowledge to make informed decisions about identifying and implementing sinkhole attack detection systems. Furthermore, it enhances understanding of these mechanisms, contributing to overall improvements in network security.

关键词： Sinkhole attack IoT Network security Detection strategy Intrusion detection

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Leadership Effectiveness in Public Administration Remote Workers 1

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Sousa, Maria Jose Sousa, Miguel Rocha, Alvaro Inst Univ Lisboa Business Res Unit Lisbon Portugal Univ Essex Colchester Essex England Univ Lisbon ISEG Lisbon Portugal

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

The main goal of this research is to identify the leadership styles that can be more effective in leading remote workers from Public Organizations. The research question can have a significant meaning because leadership is a significant issue for the effectiveness of the organizations, and in the current Pandemic situation, it has assumed even more importance. In this context, the research question is, "Which are the leadership styles that can unleash the potential of remote workers in Portuguese Public Organizations?" The methodology used was quantitatively based on a survey applied to a sample of 109 Public Organizations remote workers, and the results show that the leadership characteristics identified were grouped in sets - forming 5 leadership styles: a) Challenger - Transactional;b) Communicator - Transformational;c) Visionary - Democratic;d) Developer - Servant;and e) Innovator - Charismatic. These leadership styles emerge not separately but as a mix.

关键词： Leadership Leadership Styles Remote Work Public Organizations

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An Educational Kit for Simulated Robot Learning in ROS 2 6th

An Educational Kit for Simulated Robot Learning in ROS 2

引用

6th Iberian Robotics Conference (Robot)

作者： Almeida, Filipe Leao, Goncalo Sousa, Armando Univ Porto FEUP Fac Engn P-4200465 Porto Portugal Inst Syst & Comp Engn Technol & Sci INESC TEC P-4200465 Porto Portugal

ISBN: (纸本)9783031591662;9783031591679

Robot Learning is one of the most important areas in Robotics and its relevance has only been increasing. The Robot Operating System (ROS) has been one of the most used architectures in Robotics but learning it is not a simple task. Additionally, ROS 1 is reaching its end-of-life and a lot of users are yet to make the transition to ROS 2. Reinforcement Learning (RL) and Robotics are rarely taught together, creating greater demand for tools to teach all these components. This paper aims to develop a learning kit that can be used to teach Robot Learning to students with different levels of expertise in Robotics. This kit works with the Flatland simulator using open-source free software, namely the OpenAI Gym and Stable-Baselines3 packages, and contains tutorials that introduce the user to the simulation environment as well as how to use RL to train the robot to perform different tasks. User tests were conducted to better understand how the kit performs, showing very positive feedback, with most participants agreeing that the kit provided a productive learning experience.

关键词： ROS Robot Learning Educational Robotics

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Geo-Tagged 3D Geometric Modeling of Urban Structures by Mitigating Reflected GPS Signals Using a Laser Range Sensor

Geo-Tagged 3D Geometric Modeling of Urban Structures by Miti...

引用

Computing Conference

作者： Kumar, Ashwani St Longowal Inst Engn & Technol Longowal India

ISBN: (纸本)9783031622830;9783031622816;9783031622809

In this paper, estimation of GPS position in urban scenario is improved using statistical approach and by mitigating reflected GPS signals using geometry of environment around measurement point for 3D modeling. Statistical approach works by considering satellite conditions, distribution of the position estimates followed by RANSAC and Hill Climbing approach. The reflected signals that are major cause of GPS position error in the urban scenario are identified using laser range data taken with laser scanner and are sacked from estimation of position calculation. A weighted non-linear least square solution is obtained for the position estimation using trilateration excluding non line of sight satellites. Implausible results obtained from experiments done in urban scenario during a span of time and over a span of several weeks validate the applicability and the feasibility of proposed method.

关键词： Geo-tagging 3D modeling Urban structures GPS signals Laser range sensor Reflected signals

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Comparative Analysis of Vehicle Deceleration Measurement Devices 10th

Comparative Analysis of Vehicle Deceleration Measurement Dev...

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Sehovic, Jasmin Trobradovic, Mirsad Univ Sarajevo Fac Mech Engn Dept Engines & Vehicles Vilsonovo Setaliste 9 Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031662676;9783031662683

Analysis of vehicle deceleration as one of the key parameters of vehicle safety and performance, and the method of determining it, is a very common topic. This paper provides a theoretical analysis of deceleration as one of the vehicle parameters, and emphasizes various applications of this parameter. Deceleration as a parameter is not only important when determining the vehicle's braking efficiency but its analysis can also provide additional interesting information. The key item is the correct determination of the deceleration under experimental conditions. Thus far, inertial devices for measuring deceleration,which are quite impractical for handling, maintaining and analyzing the measured data, have been used the most. In this paper, a comparative analysis of this device is performed with new devices for measuring deceleration based on GPS and MEMS (Micro Electro Mechanical System) technology. The result of this research provides an answer as to whether the use of devices based on new data acquisition and processing technologies is justified, or whether outdated technologies should still be used.

关键词： Deceleration Vehicle Inertia Decelerometer GPS MEMS

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Exploring Advantage Estimation with Higher-Order Summation of State Values in Deep Reinforcement Learning: Experimental Insights for Online Temporal Difference Approach 1

引用

13th Computer Science Online Conference

作者： Kaloev, Martin Krastev, Georgi Univ Ruse Ruse Bulgaria

ISBN: (数字)9783031705182

ISBN: (纸本)9783031705175;9783031705182

This study investigates the potential advantages of redefining advantage calculation in actor-critic deep reinforcement learning. Departing from the conventional temporal difference approach, where the advantage is determined by the difference between the values of two consecutive states, we investigate an alternative method. Our approach involves computing the advantage as the difference between the value of the current state and the summation of multiple discounted values of subsequent states. Through a series of experiments, we explore the implications of this alternative advantage calculation on the training dynamics of actor-critic networks. Furthermore, we extend the actor's loss function by incorporating the summation of even multiple discounted rewards with appropriate gamma discounts. The experiments aim to discern whether this extended loss function enhances the learning capabilities of the actor in complex reinforcement learning tasks. We find that the advantages are contingent upon the task's reward horizon-indicating the frequency of rewards and the presence of negative rewards. Notably, the effectiveness of extended discounting is highly dependent on selecting an appropriate order of calculation, signifying the number of state values considered after initial. This order, akin to context, proves crucial in determining the efficacy of the extended discounting approach.

关键词： Deep Reinforcement Learning Advantage Loss Function Temporal Difference Experimental Insights Computational Efficiency Neural Network Training Artificial Intelligence Optimization

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3D Liver Segmentation from CT-Scan Images 1

引用

20th International Conference on Computing and Information Technology (IC2IT2)

作者： Sutiratanapong, Nateepat Sucontphunt, Tanasai Natl Inst Dev Adm 148 Seri Thai Rd Bangkok 10240 Thailand

ISBN: (数字)9783031585616

ISBN: (纸本)9783031585609;9783031585616

Segmenting the liver from volumetric radiographs is a time-intensive task. Machine learning can be utilized to automate this process when precision is not the primary goal. The development of machine learning models is mainly constrained by GPU memory. To preserve spatial localization in segmentation, processing the entire volumetric image at once is ideal, but this approach is memory-intensive. Sophisticated models can extract more detailed features, but may require dividing the volumetric image into smaller segments to fit within memory constraints. Conversely, simpler models, while less memory-intensive, might not capture all necessary features for accurate segmentation. These three requirements - precision, memory usage, and feature extraction - have their own trade-offs and thus become the focus of this research. In this paper, a simple U-Net model is employed to process the entire volumetric image, thereby preserving spatial localization. This non-complex model is enhanced by a special technique, Organ-Centric Resampling, introduced for data preprocessing. Independent Random Fields Deformation is also applied to increase the variety of the generated image.

关键词： Organ-Centric Resampling Organ Segmentation Volumetric Segmentation

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Handheld Spectroscopy for Dairy Quality Control: Towards a Real Time Milk Spoilage Classification Model 1

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16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Gillespie, James Vincent, Jordan Dib, Omar Heiden, Matthias Condell, Joan Ulster Univ Intelligent Syst Res Ctr Derry Londonderry North Ireland Ulster Univ Artificial Intelligence Res Grp Belfast Antrim North Ireland Nantes Univ CNRS GEPEA Nantes France Tsenso GmbH Stuttgart Germany

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

In response to efforts to reduce food waste, some leading UK supermarkets have removed expiration dates from a variety of dairy products, such as milk, encouraging consumers to rely on the subjective 'sniff test' for assessing freshness. While this approach aims to extend the shelf life of dairy items, it inadvertently creates uncertainty among consumers about the freshness of their products in the absence of quantifiable information from producers. To address this issue, this work explores a proof of principle experiment leveraging machine learning techniques on spectral data recorded by the consumer-friendly FreshDetect BFD-100 3D Fluorescence spectrometer to perform quantitative, on-the-fly assessment of milk quality. A spectral dataset of twelve milk samples deteriorating over 48 h was collected and correlated with an increase in acidity, an indicator of milk spoilage. Seven classification algorithms were tested to classify the milk samples as fresh or spoiled based on a defined pH cut-off. Among these, a Naive Bayes classifier was the best performing model, achieving an average accuracy of 92.2% using 10-fold cross-validation for training and 95.4% on an independent test set. These findings highlight the potential of using machine learning and spectral data to provide consumers with reliable, real-time assessments of milk freshness.

关键词： Milk spoilage Fluorescence spectroscopy Handheld spectroscopy Classification Machine Learning

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