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Towards 3D Path Planning for Free Climbing Robots 27th

Towards 3D Path Planning for Free Climbing Robots

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27th International Conference on Climbing and Walking Robots and Mobile Machine Support Technologies (CLAWAR)

作者： Graaf, Friedrich Schnell, Tristan Heppner, Georg Dillmann, Rdiger FZI Res Ctr Informat Technol Dept Interact Diag & Serv Syst IDS Haid & Neu Str 10-14 D-76131 Karlsruhe Germany

ISBN: (纸本)9783031713002;9783031713019

With the increasing capabilities of robotic hardware, the demand for software to fully utilize these becomes apparent. To better utilize the full movement potential, a planning concept for free climbing motions is introduced. For this, classical approaches like rapidly-exploring random trees (RRT) are combined with the versatility of neural networks and reinforcement learning. With this, the traceability of classical algorithms, combined with the versatility of neural networks, can be used to generate complex climbing motion paths.

关键词： global planning local planning 3D climbing robots path planning

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Maritime Supply Chain Cybersecurity: A Brief Review Uncovering Challenges 7th

Maritime Supply Chain Cybersecurity: A Brief Review Uncoveri...

引用

7th International Conference on Logistics Operations Management (GOL)

作者： Samiri, Mohamed Yassine Chefira, Reda Belkeziz, Radia Bouain, Abdelhadi Cadi Ayyad Univ Fac Legal Econ & Social Sci El Kelaa des Sraghna Lab Comp & Syst Engn El Kelaa Des Sraghna Morocco Cadi Ayyad Univ Lab Comp & Syst Engn Marrakech Morocco Ibn Zohr Univ Polydisciplinary Fac Engn Sci Lab LabSI Ouarzazate Morocco

ISBN: (纸本)9783031686276;9783031686283

In the modern era, the logistics and supply chain sector is undergoing a significant digital transformation, redefining operations and efficiency. However, with this transformation comes an array of cybersecurity challenges that demand urgent attention. This paper endeavors to provide a brief comprehensive overview of the current state of cybersecurity in logistics, emphasizing the maritime industry's digital evolution and the associated cybersecurity implications. Through insights from leading scholars, we identify prevailing threats and vulnerabilities. As we outline best practices in addressing these threats, the paper also sheds light on the specific challenges and solutions pertinent to the maritime sector. Highlighting gaps in current knowledge and research, the paper underscores the pressing need for unified regulatory frameworks. In conclusion, we advocate for a systemic and adaptive approach to cybersecurity, ensuring that as the logistics sector evolves digitally, it remains fortified against potential cyber threats.

关键词： Cybersecurity Logistics Maritime supply chain Digital Transformation

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RecipeRadar: An AI-Powered Recipe Recommendation System

RecipeRadar: An AI-Powered Recipe Recommendation System

引用

Intelligent systems Conference

作者： Xing, Tianxiang Gao, Jinzhu Univ Pacific Stockton CA 95209 USA

ISBN: (纸本)9783031664304;9783031664311

This paper presents the development of an advanced recipe recommendation system powered by natural language processing (NLP). To address the challenges posed by the overwhelming abundance of online recipes, this system provides personalized recipe suggestions based on user inputs, dietary preferences, and ingredient restrictions. The core of the system is a multi-input neural network model that processes and categorizes recipes using various textual inputs such as ingredients, recipe names, and descriptions. The model adeptly handles multi-label classification and multi-input data, two primary challenges in the domain of digital gastronomy. Extensive data preprocessing, including text normalization, tokenization, and vectorization, was conducted to prepare the dataset sourced from Kaggle. The model's performance was rigorously evaluated through training and validation accuracy metrics, displaying its capability to categorize and recommend recipes effectively. The system's potential applications span from personal cooking assistance to professional culinary platforms, highlighting its significance in enhancing digital culinary experiences. Future work includes expanding the dataset for greater diversity, integrating models that are more complex for improved NLP, and developing a user-centric mobile application. This study contributes to the growing field of AI in gastronomy, demonstrating the practical application of machine learning in everyday life domains.

关键词： Multi-input neural networks Machine learning Recipe recommendation Chatbot

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A Transformer and Federated Learning Techniques for Detecting DDoS Attacks in IoT Environments 1

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

作者： Aleyead, Saud Al-Ahmadi, Saad Prince Sattam Bin Abdulaziz Univ Kharj Saudi Arabia King Saud Univ Riyadh Saudi Arabia

ISBN: (数字)9789819735594

ISBN: (纸本)9789819735587;9789819735594

Distributed Denial-of-Service (DDoS) attacks pose a significant threat to Internet of Things (IoT) networks, emphasizing the importance of deploying effective intrusion detection systems (IDS) to identify and mitigate these attacks. Deep learning (DL) techniques have proven efficient in detecting DDoS attacks in IoT, as reported in numerous studies. Recently, Transformers and Federated Learning (FL) techniques have gained attention in the cybersecurity community for enhancing IDS performance. In this research, we propose a novel, efficient, and lightweight scheme for detecting and mitigating DDoS attacks in IoT networks using transformer-based on FL technology. In our study, we utilize three recently published datasets, namely TON-IoT, CICDDoS2019, and LATAM-DDoS-IoT, to assess the performance of our scheme. These datasets provide invaluable real-world scenarios and provide insightful perspectives on DDoS attacks in IoT environments. By utilizing these contemporary datasets, we aim to enhance the validity and relevance of our research findings, as well as compare the performance of our scheme with existing approaches. Our experimental findings reveal that the proposed scheme achieves a significantly higher accuracy rate compared to state-of-the-art-methods. Specifically, our approach achieves an accuracy rate of 99.62% using the TON-IoT dataset, 99.91% using the CICDDoS2019 dataset, and 99.11% using the LATAM-DDoS-IoT dataset.

关键词： Internet of Things (IoT) Distributed Denial-of-Service (DDoS) Network-based intrusion detection system (NIDS) Deep learning Federated Learning Transformers TabTransformer based on FL (TTFL)

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Lane Segmentation and Turn Prediction Using CNN and SVM Approach 2nd

Lane Segmentation and Turn Prediction Using CNN and SVM Appr...

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2nd International Conference on Forthcoming networks and Sustainability in the AIoT Era (FoNeS-AIoT)

作者： Al-Fadhli, Sarah Kadhim Hwaidi Inan, Timur Altinbas Univ Istanbul Turkiye Marmara Univ Technol Fac Comp Engn Dept Istanbul Turkiye

ISBN: (纸本)9783031628801;9783031628818

As the automotive industry continually evolves towards the realization of autonomous vehicles, the critical task of real-time lane detection and road segmentation using computer vision assumes paramount significance. Achieving reliable and accurate lane marking detection and road region segmentation represents a cornerstone for the safe and efficient operation of smart cars. This problem statement seeks to elucidate the multifaceted challenges encompassing this domain, taking into account the complexities of real-world driving scenarios, diverse environmental conditions, and the imperative need for robust and adaptive algorithms. This paper aims To develop a comprehensive understanding of the state-of-the-art techniques and methodologies in computer vision, with a specific focus on lane segmentation and road detection in the context of smart car vision. To investigate the integration of Deep Convolutional Neural networks (CNNs) and Support Vector Machine (SVM) classification for enhancing the accuracy and robustness of lane segmentation and road detection in smart car environments.

关键词： Machine learning Deep learning MLP Segmentation

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Evaluation Study on Digitalized Administrative Approval Reform: Example of the Economic and Technological Development Zone 9th

Evaluation Study on Digitalized Administrative Approval Refo...

引用

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

作者： Li, Na Zhang, Tong Yang, Qingshou Guo, Jingli Northwestern Polytech Univ Sch Publ Policy & Adm Xian 710129 Peoples R China

ISBN: (纸本)9789819735556;9789819735563

The advancement of administrative approval digitalization has brought about several challenges during its implementation. This study focuses on the Economic and Technological Development Zone (ETDZ) as a case study to examine the digital reform of administrative approval. This study examines the digital reform of administrative approval in the Economic and Technological Development Zone (ETDZ). Through a comprehensive evaluation using questionnaires and internal evaluations, the research identifies current challenges in the digitalization process. Based on the findings, this paper proposes feasible solutions in three key areas. Firstly, it advocates for the digital and intelligent upgrading of government service centers. Secondly, the study emphasizes the importance of data sharing and business synergy. Lastly, the paper highlights the significance of admitting scenario-based personalized approval services to enhance user experience and satisfaction. The insights gained from this research contribute to optimizing administrative processes and advancing public service delivery in the context of digital transformation.

关键词： Digital transformation Economic and Technological Development Zone Administrative examination and approval reform Hierarchical analysis

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Chemical Characterization and Potential Health Benefits of Wild Mushrooms from Eastern Bosnia 10th

Chemical Characterization and Potential Health Benefits of W...

引用

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

作者： Sapcanin, Aida Pehlic, Ekrem Jancan, Gordan Uzunovic, Alija Univ Sarajevo Fac Pharm Zmaja Od Bosne 8 Sarajevo 71000 Bosnia & Herceg Univ Bihac Fac Hlth Studies Bihac 77000 Bosnia & Herceg Chemilab Doo Ljubljana Slovenia Agcy Med Prod & Med Devices Bosnia & Herzegovina Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031662706;9783031662713

Biologically active compounds found in mushrooms have long been the subject of interest of researchers for the preparation of natural-based medicinal supplements. Mushrooms are traditionally used and collected in our area from spring to autumn. The aim of this work is to perform a chemical characterization of mushrooms: Tricholomageorgii, Craterelluscornucopioides and Laetiporussulphureus (collected in the mountains of Jahorina and Sjeme.c, Eastern Bosnia) on the content of different fatty acids, vitamins and carbohydrates. Metals: Cu, Zn, Ca, K, Co, Mg, Na, Fe, Se, Cu, As, Co, Ni, Cr, Pb and Cd) were measured in lyophylised and microwave digested samples by using an atomic absorption spectrometry (AAS). Mushrooms are well known potential source of accumulated heavy metals. Furthermore, wild mushrooms are protein rich food. Interelemental correlation and a health risk assessment was made due to the accumulation of metals in the investigated wild mushroom species, and parameter like HI has been calculated. The results pointed the validity of the hypothesis that the selected species are potential sources of nutraceuticals. It is necessary to continue further research on these species.

关键词： wild mushrooms chemical characterization health benefit

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Microbial Metabolites and Recent Advancement 1

引用

4th Congress on Intelligent systems (CIS)

作者： Garia, Prakash Chaubey, Kundan Kumar Rawat, Harish Sinha, Aashna Sharma, Shweta Goyal, Urvashi Mittal, Amit Graph Era Hill Univ Sch Management Bhimtal 263139 Uttarakhand India Uttaranchal Univ Sch Appl & Life Sci Dehra Dun 248007 Uttarakhand India Dhanauri PG Coll Dhanauri Dept Bot Haridwar 247667 Uttarakhand India Sanskriti Univ Sch Appl & Life Sci Mathura 281401 Uttar Pradesh India DUVASU Coll Biotechnol Mathura Uttar Pradesh India Sanjay Gandhi Postgrad Inst Med Sci Lucknow 226014 Uttar Pradesh India Graph Era Hill Univ Dept Allied Sci Bhimtal 263139 Uttarakhand India

ISBN: (数字)9789819990375

ISBN: (纸本)9789819990368;9789819990375

Microbes have attracted a lot of attention due to their potential in the development of bioprocess technologies for the limitless manufacture of foods and supplements, which could help to meet the ever-increasing demands of the world's population. Additionally, since microorganism-based technologies do not constitute a sizable source of pollution, they are preferred options for resolving large environmental problems caused by conventional chemical treatments. Enzyme inhibitors are used to treat infectious and deadly diseases all over the world. These inhibitors are produced by antibiotics, anticancer medications, immune suppressants, alkaloids, and microorganisms. Additionally, they greatly influence human life expectancy and the reduction of mortality. To meet the demands of a population that is constantly growing, microbial enzymes (Enz) provide immense potential for a variety of industries, including medicine, cosmetics (CSM), food, feed, beverages, detergents, leather processing, and paper and pulp;use of Enz has been developing steadily. Microbial-derived growth regulators and pesticides have demonstrated considerable potential for the development of sustainable agriculture, and as a result, a greener world. It should be noted and understood microbes are a source of a range of essential micronutrients and natural compounds. In brief, microbes produce two types of metabolites, primary and secondary whose uses are discussed later. This review discusses and explains various metabolites produced by microbes and their use in daily life.

关键词： Microorganisms Metabolites CSM Fermentation Wastewater treatment Antibiotics Antimicrobial advancement

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Bi-directional LSTM for Monitoring Biceps Brachii Muscle Activity of Healthy Subjects Using sEMG Signals

Bi-directional LSTM for Monitoring Biceps Brachii Muscle Act...

引用

Intelligent systems Conference (IntelliSys)

作者： Subhash, K. M. Paul, Joseph K. Pournami, P. N. Natl Inst Technol Calicut Kozhikode 673601 Kerala India

ISBN: (纸本)9783031477171;9783031477188

In recent decades, EMG (Electromyogram) pattern recognition systems focus primarily on feature engineering techniques. Recently, feature learning has demonstrated better recognition accuracy in many research fields than the well-established hand-crafted features. The proposed research work demonstrates designing an EMG pattern recognition system for characterizing slow and fast muscle activities of 40 healthy subjects and monitoring their muscle functions. The analysis used a network of Bidirectional long-short-term memory (Bi-LSTM) with five layers. Feature Learning using Bi-LSTM is performed to monitor muscle activities during continuous forearm extension 5 times with slow and fast movements, using a medium-sized dataset extracted from 40 healthy male subjects. Simulation experiments were conducted with and without cross-validation, which reported an accuracy of 92.86% and 93.75%, respectively, suggesting that the proposed model can be developed as a generalised model for EMG analysis.

关键词： Electromyogram Bi-directional LSTM Feature learning Neuromuscular condition Classification

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The Transformation of the Digital Communication of Educational Organizations in the Pandemic Period: New Practices and Challenges 1

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

作者： Miguel, Ines Silva, Marcia IADE ISCTE IUL Lisbon Portugal Commun & Soc Res Ctr Braga Portugal

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

The digital transformation caused by COVID-19 broke with classic communication models and brought about profound changes in institutional and marketing communication in educational organizations. In order to respond to this transformation, educational organizations had to quickly change and adapt different communication strategies in view of the current pandemic context. This article specifically focuses on the description of the transformation of digital communication that took place in two private education educational organizations in Portugal, before the pandemic (January-March 2020) and during the pandemic/confinement (March-June 2020). Following a quantitative and qualitative methodology, in the form of a multiple case study, we focused on listening through semi-structured interviews with directors, IT and communication technicians and questionnaire surveys with parents (n = 172) of both educational institutions. The results indicate that the crisis context raised by the COVID-19 pandemic has reinforced the role of communication in educational organizations and has profoundly changed the way of communicating. We conclude that regularity, proximity, clarity, and sincerity of communication increase trust in relation to the service provided. It is recommended that educational organisations adopt strategic co-communication plans and that they favour the use of social media and other online media, with a view to streamlining and flexibilities communication.

关键词： Digital Communication Educational Organizations Pandemic COVID-19

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