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

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DeepLeaf: Plant Species Classification Using Leaf Images and GPS Data with Convolution Neural Network 8th

DeepLeaf: Plant Species Classification Using Leaf Images and...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Lakshmi, S. Mahalakshmi, M. Sandhiya, M. Rajalakshmi Engn Coll Dept Informat Technol Chennai Tamil Nadu India

ISBN: (纸本)9789819713257;9789819713264

In the realm of botanical research, understanding and classifying plant species are fundamental tasks with vast ecological and conservation implications. "DeepLeaf" emerged as a groundbreaking project that leverages deep learning, mainly convolutional neural networks (CNNs), to revolutionize plant species identification and geographical mapping. The core of this project involves a multi-step approach. The initial phase centers on the collection of extensive datasets comprising high-resolution leaf images and their corresponding GPS coordinates from various geographic locations. These datasets provide the foundation for training and validating our deep learning model. The heart of the project lies in the implementation of CNNs, which excel in feature extraction from visual data. The model learns to recognize intricate patterns in leaf structures, enabling precise plant species classification. What sets "DeepLeaf" apart is the integration of GPS location data. This addition not only bolsters classification accuracy but also adds a geospatial dimension to the project. The incorporation of location data allows for insights into the geographical distribution of plant species, contributing to ecological and environmental research. "DeepLeaf" represents a vital tool for a wide range of professionals and enthusiasts, including ecologists, botanists, and conservationists. This project streamlines plant species identification, facilitating rapid, and accurate cataloging. Furthermore, it yields data that informs conservation efforts, biodiversity research, and ecological studies by unveiling geographical distribution patterns. It stands as a pioneering project with the potential to reshape how we identify and understand plant species while offering valuable insights into their geographic prevalence.

关键词： Plant species classification Convolution neural network GPS Deep learning Feed forward learning

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Grasper-Needle Coordination in Robotic Laparoscopic Surgery: Potential Fields Approach 6th

Grasper-Needle Coordination in Robotic Laparoscopic Surgery:...

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6th Iberian Robotics Conference (Robot)

作者： Fonturbel, Carlos Carlos Fraile, Juan Perez Turiel, Javier Univ Valladolid Inst Tecnologias Avanzadas Producc ITAP Med Robot Grp Escuela Ingn Ind Valladolid Spain

ISBN: (纸本)9783031591662;9783031591679

This paper proposes a Potential Fields-based approach for coordinating a laparoscopic needle holder and grasper to achieve autonomous suturing in robotic laparoscopic surgery. This method allows seamless transition to teleoperated control based on Virtual Fixtures. The study presents three stages of suture, and experiments conducted in a controlled surgical scenario test the feasibility of the proposed approach. The results indicate successful coordination between the needle holder and grasper, achieving a smooth and logical motion with minimal undesirable effects. The study also discusses challenges such as slow convergence towards attractive points and the need for accurate position determination, suggesting potential solutions and future research directions. Experiments demonstrate successful coordination between the tools, enabling smooth motion with minimal undesirable effects. The approach shows responsiveness and adaptability, promising enhanced autonomous robotic laparoscopy for various surgical tasks.

关键词： Robotic Laparoscopic Surgery Autonomous Suturing Potential Fields Multi-Robot Coordination Minimally Invasive Surgery

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HR Development Strategy Through Training Towards Superior Tourism on the Department of Tourism, Youth and Sports at Bulukumba Regency, Indonesia 9th

HR Development Strategy Through Training Towards Superior To...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Mustari, Nuryanti Junaedi, Rosdianti Razak Ahmad, Andi Jusdiana Herman Univ Muhammadiyah Makassar Makassar Indonesia

ISBN: (纸本)9789819732982;9789819732999

Human resources are an asset or driving force in an organization. This study aims to analyze the strategy for developing human resources in tourism sector on the Department of Tourism, Youth and Sports at Bulukumba Regency. This study used qualitative method with a case study type. The data collection techniques used observation, interviews and documentation with 14 informants (8 employees from Department of Tourism, Youth and Sports at Bulukumba Regency, 2 employees from Personnel and Human Resources Development Agency Office and 4 people from community). Data analysis techniques were assisted by software nvivo 12 plus. The results of this research indicate that HR development strategies in the tourism sector can be carried out by improving the training process. The recruitment process requires an even distribution of employees so that the strength of human resources becomes more balanced. Through formal education, employees have a basic starting point so they can easily complete the work they are entrusted with. However, when an employee has an educational background that is not appropriate to the fieldwork can be compensated by some experiences that have been undertaken and following training that can develop the employee's skills. Besides, the role of the community was very important for the progress of tourism in Bulukumba Regency, the community has a lot of participation in developing tourist attractions in Bulukumba, both in the form of ecotourism managed by the local village, cultural tourism and also existing marine tourism.

关键词： Human resources Training Tourism

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Intuitionistic Fuzzy Information Aggregation Based on Sugeno-Weber Triangular Norms

Intuitionistic Fuzzy Information Aggregation Based on Sugeno...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Ullah, Kifayat Hussain, Abrar Yin, Shi Pamucar, Dragan Riphah Int Univ Dept Math Lahore Campus Lahore 54000 Pakistan Hebei Agr Univ Coll Econ & Management Baoding 071001 Peoples R China Univ Belgrade Fac Org Sci Dept Operat Res & Stat Belgrade Serbia

ISBN: (纸本)9783031671944;9783031671951

This presented research work is used to develop some viable mathematical approaches to fuse unpredictable and vague type information of human opinion. Numerous mathematical strategies and results were introduced by different mathematicians under considering different fuzzy domains. The uniqueness of existing approaches is to resolve genuine real-life applications. In this article, the authors explore some realistic operational laws of Sugeno-Weber t-norms and t-conorms in light of intuitionistic fuzzy information. To illustrate prioritization among different attributes information, we develop some flexible mathematical approaches by incorporating the system of intuitionistic fuzzy information including intuitionistic fuzzy Sugeno-Weber prioritized average (IFSWPrA) and intuitionistic fuzzy Sugeno-Weber prioritized weighted average (IFSWPrWA). A numerical example is also designed to reveal the applicability and validity of proposed approaches.

关键词： Sugeno-Weber triangular norms intuitionistic fuzzy information prioritized operators and multi-attribute decision-making process

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Computer Vision for Terrain Mapping and 3D Printing In-situ of Extra/-terrestrial Habitats

Computer Vision for Terrain Mapping and 3D Printing In-situ ...

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Intelligent systems Conference

作者： Calabrese, Giuseppe Hidding, Arwin Bier, Henriette van Engelenburg, Casper Khademi, Seyran Aslaminezhad, Atousa Univ G DAnnunzio Int Res Sch Planetary Sci Pescara Italy Delft Univ Technol Delft Netherlands Univ Sydney Sydney NSW Australia Univ Antwerp Antwerp Belgium Heriot Watt Univ Dubai U Arab Emirates

ISBN: (纸本)9783031664304;9783031664311

This paper addresses the complexities inherent in constructing sustainable extraterrestrial habitats within lava tubes that are envisioned as promising locations for human habitation and scientific inquiry. These environments are characterized by various challenges, which are addressed in this case by integrating computer vision (CV) techniques and 3D printing in-situ. The CV component generates a detailed depth map from synthetic imagery to combine this depth map with an adaptive 3D printing process, which is proposed to ensure level surfaces at various depths, facilitating precise foundation and habitat placement within the demanding context of lava tubes. Significantly, synthetic imagery is employed due to the absence of real lava tube photos at this early stage of the current exploration. The focal point lies in utilizing advanced deep learning (DL) algorithms and convolutional neural networks (CNN) to generate depth maps for extra/-terrestrial environments. This research represents a platform for further knowledge development in the fields of CV and its application to 3D printing in-situ, hence opening new avenues for sustainable extraterrestrial habitats.

关键词： Lava tube habitats Computer vision 3D printing Depth map Robotic construction Adaptive filling Real-time mapping Surface irregularities Habitability

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Navigating the Technological Frontier: Machine Learning Infused with Fuzzy Logic for Control System Advancements

Navigating the Technological Frontier: Machine Learning Infu...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Hanilci, Furkan Cakir, Emre Kuyu, Yigit Cagatay R&D Dept Karsan Automot Bursa Turkiye

ISBN: (纸本)9783031671913;9783031671920

In the realm of artificial intelligence, fuzzy logic is emerging as a pivotal tool for addressing intricate problems. Fuzzy systems, seamlessly harmonizing with human understanding, act as a practical link for navigating real-world challenges where precise definitions pose difficulties. By blending the intricacies of mathematical modeling in machine learning with human-centric logic, fuzzy systems bolster adaptability. This symbiotic relationship between fuzzy logic and machine learning serves as a pragmatic tool, merging the complexities of mathematical modeling with human-focused reasoning, marking a pioneering step in computational intelligence and heralding a new era in problem-solving. The primary goal of this study is to scrutinize machine learning techniques grounded in fuzzy logic within control systems, explore the forefront of fuzzy logic and machine learning methodologies, and analyze their interactions. Our aim is to furnish readers intrigued by the intricate interplay between fuzzy systems and machine learning in control systems with insights into the fundamental components, methodologies, and advancements in this domain.

关键词： Fuzzy systems Machine Learning Control systems

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A Social Profile-Based Recommendation Architecture for E-Learning systems

A Social Profile-Based Recommendation Architecture for E-Lea...

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Computing Conference

作者： Ntlangula, Xola Leung, Wai Sze Univ Johannesburg Johannesburg South Africa

ISBN: (纸本)9783031622793;9783031622779;9783031622762

The increased reliance of education institutions on e-learning systems to provide learning and teaching activities and resources has prompted a need for innovative strategies that deliver effective learning to students. One approach being considered involves enhancing personalized learning experiences through the implementation of personalized learning paths. Personalized learning paths have proven highly beneficial for students;however, they are predominantly guided by learning objectives rather than the unique attributes of each student. Additionally, the inflexibility observed in e-learning systems poses a challenge in integrating customization options. This paper proposes an architecture for a recommendation system that creates personalized learning paths from a student's profile. The resulting architecture enhances an e-learning system's personalization by using external student data to create a more comprehensive student profile, thereby improving the system's ability to generate learning paths and deliver technology-enhanced learning experiences.

关键词： Personalized learning paths Social profile Recommendation systems

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Improved Technique for Dimensionality Reduction: Star and Quasar Classification with Typical Testors 1

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Intelligent systems Conference (IntelliSys)

作者： Martinez-Mejia, Mateo Ibarra-Fiallo, Julio Univ San Francisco Quito Colegio Ciencia Ingenieria Quito Ecuador

ISBN: (数字)9783031477249

ISBN: (纸本)9783031477232;9783031477249

This work compares the feature selection technique offered by Testor Theory, using the Yablonski and Compatible Sets (YYC) algorithm for the calculation of a fitting typical testor, against the dimensionality reduction given by the principal component analysis (PCA) calculation. Using the results obtained from the previous algorithms and using a Support Vector Machine (SVM) as a classification model, we acquire the classification results of stars and quasars. Lastly, we analyze the advantages shown by typical testors from the experimental results obtained over the ones obtained from the PCA technique.

关键词： Testor Theory Typical Testor Dimensionality Reduction Classification Model

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IoT-Based Smart Indoor Navigation System with Voice Assistance for Museums 5th

IoT-Based Smart Indoor Navigation System with Voice Assistan...

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

作者： Manju Singh, Samayveer Kumar, Sandeep Jaypee Inst Informat Technol Dept Comp Sci & Engn & Informat Technol Noida India Dr BR Ambedkar Natl Inst Technol Jalandhar Dept Comp Sci & Engn Jalandhar Punjab India Christ Deemed Univ Sch Engn & Technol Dept Comp Sci & Engn Kengeri Campus Bangalore 560074 Karnataka India

ISBN: (纸本)9789819720521;9789819720538

In the current era of smart heterogenous devices, the surrounding environment too needs to be smarter to match the gravity of such devices. Such advanced environment can be built with the technology called Internet of Things (IoT). Due to the presence of such vivid thing devices in the Internet of Things (IoT) environment, the task of automatically predicting the end users' desires can play an important role when it comes to match the pace of modern society with too much diverse aspects. Since last decade, people have deviated their attention towards Indian ancient culture and Museums are eye catching attraction where our ancient cultural heritage exist. To improvise the slow pace growth of the tourism sector, there is the crucial requirement of technological improvement especially due to the restrictions on installations of external hardware within the close proximity. One prominent way of improving tourists experience at museums is to renovate existing museums with IoT-based smart devices which is programmed such a way to automatically navigate the user indoor and briefs the associated information about artwork without any user intervention. In this paper, we propose an IoT-based smart indoor navigation system along with voice assistance which can enhance the tourists experience in a museum. In addition, the proposed design also delivers the very personalized cultural contents related to the visited artworks.

关键词： Internet of Things Navigation system Bluetooth low energy Smart indoor systems

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Manipulation of Deformable Objects with a Multi-robot System 6th

Manipulation of Deformable Objects with a Multi-robot System

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6th Iberian Robotics Conference (Robot)

作者： Valdeolmillos, Alejandro Sagues, Carlos Herguedas, Rafael Inst Invest Ingn Aragon Dpto Inform Ingen Sistema Unizar C-Maria Luna 1 Zaragoza 50018 Spain Inst Tecnol Aragon C-Maria Luna 7 Zaragoza 50018 Spain

ISBN: (纸本)9783031586750;9783031586767

When dealing with object manipulation, they can be too large, heavy or difficult for a single robot to grasp. Therefore, to improve the performance when these tasks are executed, multiple robotic manipulators could be considered. This paper presents a cooperative multi-robot system capable of manipulating deformable objects in a coordinated and controlled manner, making the object also acquire the desired shape and configuration in space. Additionally, strategies that avoid collision of obstacles with the transported object and the mobile robots are implemented, extending its application in dynamic and unstructured environments. The algorithm is flexible with respect to the shape of the transported object and the number of manipulator robots, making it a versatile solution capable of being applied in many different contexts depending on the needs. The PyBullet simulator visualises in real time the movement of the robots and obstacles, as well as the behaviour of the deformable object being transported.

关键词： Nonlinear cooperative control Multi agent systems Robots manipulators Autonomous robotic systems Mobile robots Networked robotic system modeling and control

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