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

共 9905 条记录，以下是2641-2650 订阅

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Artificial Intelligence Algorithm for Optimizing PID Parameters to Control Weakly Damped systems

Artificial Intelligence Algorithm for Optimizing PID Paramet...

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Intelligent systems Conference (IntelliSys)

作者： Buchi, Roland Zurich Univ Appl Sci Sch Engn Winterthur Switzerland

ISBN: (纸本)9783031477201;9783031477218

The step responses of many systems to be controlled show an overshoot behavior. This is the case, for example, with active vibration damping with spring-mass systems. This document provides PID controller tables for overshooting systems. Such systems can be approximated with second-order systems. The parameters were calculated with the simulation and optimized with a search for the best values according to the minimum ITAE criterion. For this purpose, parameter sets were calculated using hill climbing, an approach from artificial intelligence. It minimizes the criterion in transient response over time. The publication provides tables for systems with different system damping. So that the sets can be used in general, a way of easily identifying such systems is also presented. The controller parameters are then verified using the position control of a weakly damped spring-mass system.

关键词： PID Artificial intelligence ITAE Weakly damped

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Effective Feature Extraction and Classification Method for Backlash Anomaly in Missiles via Machine Learning

Effective Feature Extraction and Classification Method for B...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Ozcelik, Ceren Guven, Ali Sazak, Doganay Melih Roketsan Inc Ankara Turkiye

ISBN: (纸本)9783031671913;9783031671920

Missiles can fail on many failures such as backlash, autopilot failure, and inertial navigation system saturation in every flight part. Some of them are predictable and avoidable, but most of them occur after firing. The main purpose is to create a perfect device. However, small or big errors generally come true. This article finds out why the backlash error occurs and the variables that are most affected by it. Backlash is one of the most important issues that can be encountered during the design of high-precision systems. This issue is more significant than the others because it directly affects the missile's rotation velocity. Thus, the system shows an anomaly which is the points different from the normal state of existence. These anomalies can affect other dynamics on missiles directly or indirectly. In this paper, a dataset was prepared with Monte Carlo simulations of flights and Random Forest Algorithms, Extreme Gradient Boosting, Light Gradient Boosting, Categorical Boosting, and our combined algorithm were performed for classification. The labeling of the dataset was done by assigning all samples of flights that had backlash anomalies and assigning all samples of flights that did not have backlash anomalies in different classes. Grid Search was used for all algorithms hyperparameters tuning. After all calculations, results are presented with a benchmark, and show that the developed model outperformed. Our state-of-the-art model also gives results about flight has backlash anomaly or not and also gives feature importance.

关键词： Backlash Anomaly Machine Learning Random Forest Extreme Gradient Boosting Light Gradient Boosting CatBoost Feature Extraction Feature Importance

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Energy Efficient Multilevel Hierarchical Routing Protocol in Green Internet of Things 4th

Energy Efficient Multilevel Hierarchical Routing Protocol in...

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4th Congress on Intelligent systems (CIS)

作者： Mann, Garima Singh, Rishipal Guru Jambheshwar Univ Sci & Technol Dept Comp Sci & Engn Hisar Haryana India

ISBN: (纸本)9789819990429;9789819990436

IoTs are a distributed network which assists the sensor nodes in joining or departing the network in accordance with their requirement. These nodes are deployed at the places which are located at distance and their size is small. Consequently, the issue of energy usage is faced in the IoT. The base station (BS) is exploited to transmit the data among several sensor nodes (SNs). The similarity is recognized and removed among data of diverse SNs to execute the process of decision-making. Furthermore, the sink node is responsible for exploiting the data at local level and transmitting it to the network's places at distance. The earlier work implements an energy efficient protocol (EEP) called VGDRA to prolong the existence of network. This protocol leads to move sink closer to the clusters so that the data is collected. The present work suggested improved VGDRA protocol which utilizes cache nodes and considers cluster heads (CHs) for transmitting the information to cache nodes. The sink node is moved closer to the cache and helps in gathering the sensor data. MATLAB is executed to simulate the suggested protocol. Various metrics, including amount of dead motes, alive nodes, and packets whose transmission is performed to BS are employed to analyze results.

关键词： IoT Clustering Cluster head VGDRA

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Efficient PAPR Reduction Techniques and Performance of DWT-OFDM 4th

Efficient PAPR Reduction Techniques and Performance of DWT-O...

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4th Congress on Intelligent systems (CIS)

作者： Thilagaraj, M. Murugan, C. Arul Kottaimalai, R. MVJ Coll Engn Bengaluru India Karpagam Coll Engn Coimbatore India Kalasalingam Acad Res & Educ Krishnankoil India

ISBN: (纸本)9789819990368;9789819990375

Wideband digital communication can benefit from the effective wideband OFDM modulation technique, which is used for high-speed data requirement. Some important properties of OFDM are high bandwidth efficiency, robustness to channel fading, capability of handling strong echoes, and immunity to impulse response. High peak-to-average power ratio (PAPR) is the main disadvantage of OFDM, which restricts its use in communication systems. FFT is typically used to implement OFDM. Orthogonal wavelets are being used in recent research to switch from FFT-based OFDM to DWT-based OFDM in order to achieve high performance and high-speed integrated data. By incorporating DWT into OFDM, we can improve spectral efficiency and reduce bit error rates. This work is introduced to compare the performance of DWT-OFDM with traditional FFT-based OFDM examining the performance of PAPR. Additionally, it is suggested that effective PAPR reduction techniques maintain the adverse impacts induced within the allowable limits.

关键词： Wavelet-based OFDM (WOFDM) Orthogonal Channel Modulation Transforms

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Feature Extraction Methods in Alzheimer's Disease: A Comparative Assessment

Feature Extraction Methods in Alzheimer's Disease: A Compara...

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2024 International Conference on Computing, Communication, Cybersecurity and AI

作者： Arora, Nidhi Sharma, Ashok Kumar, Dinesh Lovely Profess Univ Sch CSE Phagwara Punjab India Univ Jammu Dept Comp Sci & IT Jammu India MRSPTU Dept Comp Sci & Engn Bathinda Punjab India

ISBN: (纸本)9783031744426;9783031744433

Cognitive decline and structural alterations in the brain are hallmarks of Alzheimer's disease (AD). It is a neurodegenerative illness which progresses over time. One of the most important diagnostics and tracking tools for AD is Magnetic Resonance Imaging (MRI). The image processing method used to identify Alzheimer disease involves multiple steps such as pre-processing, segmentation, feature extraction, and classification. A crucial part of understanding illness causes and facilitating early diagnosis is feature extraction from MRI images. This paper reviews a variety of feature extraction approaches and a thorough assessment is conducted on several research papers that address feature extraction and classification methods used in image processing for identification of Alzheimer disease. The importance of feature extraction in Alzheimer's MRI analysis along with the steps for detection of Alzheimer disease are briefly touched upon in the paper.

关键词： Alzheimer's disease (AD) Magnetic Resonance Images (MRI) Feature extraction Comparative analysis Image processing

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A Presentation Mining Framework: From Text Mining to to Mind Mapping 6th

A Presentation Mining Framework: From Text Mining to to Mind...

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6th International Conference on Soft Computing and Data Mining (SCDM)

作者： Kasinathan, Vinothini Mustapha, Aida Asia Pacific Univ Technol & Innovat Sch Comp Taman Teknol Malaysia Kuala Lumpur 57000 Malaysia Univ Tun Hussein Onn Malaysia Fac Appl Sci & Technol KM1 Jalan Pagoh Pagoh 84600 Kagawa Malaysia

ISBN: (纸本)9783031669644;9783031669651

Slide-based presentations, such as those created using PowerPoint, have become ubiquitous in educational settings, offering educators a convenient tool for conveying information to students. However, a significant challenge arises from the inherent linear structure of these presentations, which may not align with the non-linear process of knowledge reconstruction undertaken by students. This discrepancy often leads to variations in students' understanding and interpretation of the presented material, potentially resulting in misinterpretation of the original content sequence of the slides. Recognizing this challenge, this paper proposes a presentation mining framework to address the gap between the linear knowledge construction by presenters and the non-linear knowledge reconstruction by students. By leveraging text mining techniques, the framework aims to uncover keywords and key phrases embedded within slide content, facilitating the generation of a visual representation in the form of mind map that captures the underlying structure and relationships of the extracted information. The mind maps generated are then evaluated against a domain ontology, a dictionary, and subject matter experts based on averaged precision, recall, and F-measure score. The results showed that the proposed framework is able to extract and generate reasonable visualization from presentation slides.

关键词： presentation mining keyphrase extraction concept map

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Autoencoder-Based Solution for Intrusion Detection in Industrial Control System

Autoencoder-Based Solution for Intrusion Detection in Indust...

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Computing Conference

作者： Russo, Silvio Zanasi, Claudio Marasco, Isabella Colajanni, Michele Univ Bologna Dept Comp Sci & Engn Bologna Italy

ISBN: (纸本)9783031622793;9783031622779;9783031622762

The threat landscape for industrial systems is in rapid evolution, with cyber-attacks becoming increasingly sophisticated, targeted, and motivated. This situation should raise many concerns because of the growing interconnection of industrial control systems with the Internet, as well as the proliferation of cyber-physical systems and the Industrial Internet of Things. In these scenarios, an accurate detection of attacks is of utmost importance. Unavailability of large industrial datasets represents one of the primary obstacles to the application of traditional machine learning techniques to early and accurate identification of cyber attacks. We propose an autoencoder-based anomaly detector that leverages unsupervised learning algorithms thus enabling the detection of various classes of cyber threats without the need for attack-specific training activities. Our model can take advantage of the intrinsic predictability of industrial settings that allow it to learn the inherent characteristics of standard traffic probability distribution. Based on our experimental results, the considered model exhibits robust generalization capabilities and demonstrates high proficiency in detecting different types of attacks as anomalies, including those previously unknown during the training phase.

关键词： Cybersecurity Industrial systems ML

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On Object Detection Based on Similarity Measures from Digital Maps 1

引用

Intelligent systems Conference (IntelliSys)

作者： Marzinkowski, Arthur Benferhat, Salem Paparrizou, Anastasia Piette, Cedric Univ Artois CRIL CNRS UMR F-81881 Arras France Univ Montpellier LIRMM CNRS UMR F-5506 Montpellier France

ISBN: (数字)9783031477157

ISBN: (纸本)9783031477140;9783031477157

This paper deals with the problem of object detection from digital maps. We are interested in detecting objects in a map which are defined in the legend. We will explore different similarity measures to compare the legend objects to those detected in different areas of the map. Our object detection method is evaluated on maps representing wastewater networks. In particular, we are interested in the detection of objects that represent lifting stations and manholes. The ultimate goal, after detecting correctly the target objects, is to repair misfunctions or inconsistencies in the water supply or evacuation network. The experimental results show that our similarity measures give good accuracy results on the detection of the objects of the legends.

关键词： Object detection Maps Similarity measures Wastewater networks' data

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Will My Job Be Automated? Fathoming Current and Persisting Impediments for Automation 21st

Will My Job Be Automated? Fathoming Current and Persisting I...

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21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Prell, Bastian Wilbers, Simon Guenther, Norman Reiff-Stephan, Joerg Univ Appl Sci Wildau Hsch Ring 1 D-15745 Wildau Germany

ISBN: (纸本)9783031618901;9783031618918

The fear of mass unemployment due to automation has been looming since the first use of automation. At least the last two decades were characterized by the emergence of technological innovation that brought the possibilities of automation to most professions. More recently, AI promises to broaden the use of automation across many industries. Contrary to popular scientific predictions, employment has not yet declined as feared. Therefore, technology has not replaced the inherent human aspects of work. This raises the question of the reasons why it has not succeeded in doing so, and for general limitations of automation. This paper enriches the stream of research in this field by proposing a bottom-up approach. Eleven exemplary professions were chosen, representing roughly 60% of the US employees. Fourteen categories were developed to pay tribute to reasons of untapped automation potential. To overcome those obstacles, the authors propose the use of a checklist, conflating shop floor reality and strategic visions for automation. Hence, this work proposes a tool that is consistent with the paradigm shift towards a more human centered approach, rooted in the updated human, technology, organization model. This advances strategical considerations of the curriculum for automation education as well as insights of socio-economic factors that ought to be considered in automation projects.

关键词： Automation Acceptance Socio-Economic Work AI

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Synergizing Artificial Intelligence and Human Factors in Hybrid Intelligence Dentistry for Automatic Prototyping 8th

Synergizing Artificial Intelligence and Human Factors in Hyb...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Pavlova, Diana Dovramadjiev, Tihomir Daskalov, Dimo Peev, Ivan Mirchev, Nikolay Dimova, Rozalina Radeva, Julia Dentaprime Dent Clin St St Constantine & Helena271Villa Area Varna 9006 Bulgaria Tech Univ Varna Studentska 1 Varna 9010 Bulgaria

ISBN: (纸本)9789819713257;9789819713264

This article bridges theory and practice, spotlighting the powerful synergy between artificial intelligence (AI) and human factors within the context of Hybrid Intelligence Dentistry. The theoretical introduction underscores the transformative potential of this collaboration in the realm of Automatic Prototyping using 3D printing and computer numerical control (CNC) technology. The practical aspect, embodied by the state-of-the-art AI software with the technological capacity to bring the theoretical principles to tangible reality, is exemplified by Diagnocat. As the selected state-of-the-art software, Diagnocat reads Cone Beam Computed Tomography (CBCT) scans with high precision, generating comprehensive 3D models, and meticulously converting them into critical STL files. This article serves as more than an intellectual exercise;it is a testament to the potential of modern dentistry. Through the utilization of Diagnocat, the selected state-of-the-art software, it propels dental practice into the future, significantly benefiting the global dental community. The article aims to enhance precision and efficiency in dental care, advancing the field and positively impacting stakeholders, from dental professionals to patients, ushering in a new era of healthcare innovation and progress.

关键词： Artificial intelligence Human factors HID Diagnocat Digitalization CBCT 3D CNC

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