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

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Leveraging Blockchain Technologies for Secure and Efficient Patient Data Management in Disaster Scenarios 12th

Leveraging Blockchain Technologies for Secure and Efficient ...

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Khalid, Muhammad Irfan Ahmed, Mansoor Ansar, Kainat Helfert, Markus Univ Sialkot Fac Comp & Informat Technol Dept Informat Technol Sialkot Pakistan Maynooth Univ Innovat Value Inst ADAPT Ctr Maynooth Ireland COMSATS Univ Dept Comp Sci Islamabad Pakistan

ISBN: (纸本)9783031603273;9783031603280

This paper offers a proof-of-concept system for patient drug prescriptions, utilizing blockchain technology to minimize the sharing of patient data between hospitals and pharmacies. Ensuring security and privacy guarantees is crucial for adopting healthcare management systems, with specific data protection requirements mandated by regulations like the General Data Protection Regulation (GDPR). This work emphasizes the drawbacks of traditional centralized electronic healthcare systems. To minimize data sharing while maintaining patient data confidentiality, we leverage the Hyperledger Fabric blockchain to establish private data channels and incorporate client identity query features. Our approach demonstrates effective monitoring, prevention, and management of potential disasters arising from centralized systems, which pose a single point of failure risk for servers housing sensitive patient data and can compromise the confidentiality of such data.

关键词： Blockchain Technologies Data Management Disaster Management Decentralized systems Drug Prescriptions Information Sharing

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Transient Motions of Solid Propellant Motor Casing at Launch Vehicle Liftoff

Transient Motions of Solid Propellant Motor Casing at Launch...

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International Scientific and Technical Conference on Integrated Computer Technologies in Mechanical Engineering - Synergetic Engineering (ICTM)

作者： Chernobryvko, Maryna Avramov, Konstantin Marshuba, Igor Vasechko, Viktor Kyrpikin, Anatolii Natl Aerosp Univ Dept Aircraft Strength KhAI St Chkalov 17 UA-61070 Kharkiv Ukraine Natl Acad Sci Ukraine A Pidhornyi Inst Mech Engn Problems St Pozharskoho 2-10 UA-61046 Kharkiv Ukraine Kharkiv Natl Univ Radio Elect Kharkiv Ukraine

ISBN: (纸本)9783031614149;9783031614156

Use of the composite materials for manufacturing of thin-walled elements of launch vehicle gives several advantages in comparison with traditional materials. The main advantages are high strength of the structure with small mass. Solid propellant motor casing manufactured from carbon-filled plastic is considered. This material is orthotropic. The purpose of this study is development of numerical methods for dynamic deformation of solid propellant motor casing, which is considered as thin-walled structure. The internal impulse excitation acts on the casing of launch vehicle. The compound spherical-cylindrical-spherical shell describes the considered casing under the action of impact pressure. The shear theory is used in simulation. The software for this problem calculation is developed. The verification of the software is carried out by comparison of the obtained results with finite element calculations in the commercial software ANSYS. Dynamic stress state of the motor casing is carried out. The behavior of displacements projections and stress tensor in time are the results of this analysis. Time of growth of impact pressure is equal to 5 ms, Note, that the maximal values of displacements and elements of strain tensor are observed at 10 ms. Thus, the displacements and stresses continue to increase, when the impact pressure stops to increase.

关键词： Stress State Orthotropic Material Equations of Thin-Walled Structure Compound Shell

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A Novel Experimental and Computational Study on the VOC Water Filters Using Tree Bark 9th

A Novel Experimental and Computational Study on the VOC Wate...

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

作者： Lee, Jungwoo Seoul Int Sch Seongnam Si Gyeonggi Do South Korea

ISBN: (纸本)9789819735587;9789819735594

Volatile organic compounds (VOCs) such as THMs, PCE, and MTBE have been shown to cause leukemia and liver cancer in humans and ecological damage when released into water supplies. This study proposes an alternative VOC filter based on lignin derived from tree bark, a waste product in the wood industry. This study compared filters made from hydrophobic, heat-treated fir and pine bark powder with conventional activated carbon filters. While the BET surface area of tree bark powder is minute at 3.13-6.22 m(2)/g, it adsorbs organic compounds at a satisfactory rate. The tree bark filters showed effectiveness, reaching 95% of that of activated carbon filters and an 85% adsorption rate of chloroform in water, proving its viability as a means for removing waterborne VOCs. Filters made from otherwise wasted tree bark will have a lower environmental impact and disposal cost due to their low production carbon footprint and biodegradability after use. It also has attractive potential as an appropriate technology for regions that lack drinkingwater due toVOC contamination. A computational study was also performed on the VOC molecules and heated lignin particles.

关键词： Volatile organic compounds (VOCs) VOC filter Pine bark Lignin Optimized shape Polarity EPM

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FarmSage: AI-Driven Solutions for Agriculture with Focus on Terrace Farming 8th

FarmSage: AI-Driven Solutions for Agriculture with Focus on ...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Suvarna, Shashwath Krishna, Bandaru Bhaskar Sai Madhava Sindhu, C. Reddy, Kakanuru Yoga Sreedhar Geethesh, Dinnepati Reddy Sai Reddy, Nandimandalam Saketh SRM Inst Sci & Technol Dept Comp Technol Sch Comp Kattankulathur 603203 India

ISBN: (纸本)9789819713127;9789819713134

FarmSage is an advanced deep learning application that revolutionizes both conventional agricultural practices and urban terrace farming. The project encompasses four distinct models, each addressing a pivotal aspect of farming. The first model, a crop selection facilitator, utilizes soil and weather parameters to guide the choice of the most suitable crop for cultivation. The second model, a fertilizer guidance system, employs both crop and soil parameters to suggest appropriate fertilizers. The third model is a disease identification system that detects plant diseases, enabling timely intervention. The fourth model is a terrace farming advisory system, which provides guidance on the optimal soil type and contents for vegetable growth, making it particularly useful for urban dwellers interested in terrace farming. The crop selection facilitator employs a deep sequential neural network. Similar in construction to the crop selection facilitator, the fertilizer guidance system also has a learning rate scheduler and a bigger network. The advisory models for terrace farming and disease identification considerably extend FarmSage's capabilities. Through their individual features, these models add to a wide range of instruments aimed at improving agricultural methods and facilitating urban terrace farming. FarmSage represents a significant advancement in the application of deep learning to agriculture and urban farming. By providing a suite of decision facilitation tools, it empowers both farmers and urban dwellers to make data-driven decisions, thereby enhancing efficiency and productivity in both rural and urban settings.

关键词： Deep learning Sequential neural network Data-driven decision-making Crop selection model Fertilizer guidance model Terrace farming advisory

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Sentiment Analysis on Umrah Packages Review in Malaysia 6th

Sentiment Analysis on Umrah Packages Review in Malaysia

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

作者： Dewi, Deshinta Arrova Kurniawan, Tri Basuki Zakaria, Mohd Zaki Kasim, Shahreen Mustapa, Nur Qasheeh INTI Int Univ Jalan Persiaran Perdana Bandar Baru Nilai 71800 Negeri Sembilan Malaysia Univ Bina Darma Jl. Jenderal Ahmad Yani.39-10 Ulu Palembang Indonesia Univ Teknol Mara UiTM Shah Alam Jalan Ilmu 1-1 Shah Alam 40450 Selangor Malaysia Univ Tun Hussain Onn Malaysia Jalan Persiaran Tun Dr Ismail Parit Raja 86400 Kagawa Malaysia

ISBN: (纸本)9783031669644;9783031669651

Umrah is a well-known pilgrimage site where individuals from around the world come together to receive good fortune from God in the here and now. In Malaysia, there are numerous sorts of Umrah packages promoted by many firms such as Andalusia Travel & Tours, Tiram Travel & Tours, Tabung Haji, and beyond. Because there are so many organizations offering Umrah trips, there are issues when careless people or organizations encourage fraud in Umrah packages to benefit from it. In 2023, the Police in Malaysia have confirmed that they have received 399 allegations regarding suspected Umrah package scams by a local company. The reports include 1,614 pilgrims around the country who are believed to have lost approximately RM14 million. With the world's technological advancements happening at a quick pace, individuals are more comfortable sharing their ideas and opinions on touchy themes on social media, including the experience with the fraud Umrah package. Performing a classification study from these resources develops the sentiment analysis against the available Umrah package. This classification approach can be used in searching applications to assist people in finding better Umrah packages. In this paper, Na ve Bayes, Random Forest, and Support Vector Machine are the classifiers that were employed in the study. The outcomes demonstrate that, out of all the classifiers, the Support Vector Machine has the highest accuracy. The Support Vector Machine (SVM) had a 90.92% accuracy rate. Ninety percent of the results were precise. It displays 90% overall for the fl-score and 91% overall for the total recall. Compared to Na ve Bayes, SVM has greater accuracy.

关键词： Umrah Sentiment Analysis Process Innovation Reviews Text Analysis

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Racist and Abusive Memes Classification Using Deep Learning Techniques 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Thilak, K. Deepa Kalaiselvi, K. Devi, K. Lalitha SRM Inst Sci & Technol Chennai Tamil Nadu India Sathyabama Inst Sci & Technol Chennai Tamil Nadu India

ISBN: (数字)9789819713264

ISBN: (纸本)9789819713257;9789819713264

Memes have grown significance as social media has grown in popularity. Memes are challenging to categorize using conventional techniques since they are typically constructed using a combination of images and text, and their content is frequently hilarious or sarcastic. We suggest a deep learning-based method for classifying memes into a variety of categories, such as sexism, politics, and criticism. This highlights the necessity for a system that can evaluate memes automatically before they raise controversy or spread humor. Before judging the text as racist and abusive or not, it will first extract the text from the supplied image. If the language is found to be unacceptable, the third phase will further categorize the information into three categories: mildly racist and abusive, very racist and abusive, and hateful racist and abusive. The five thousand memes that made up the dataset for this study were divided into four categories: hateful racist and abusive, highly racist and abusive, slightly racist and abusive, and not racist and abusive at all. In current history, there has been an upsurge in concern over the propagation of inappropriate memes on social media. The proposed project provides a deep learning-based approach to categorizing objectionable memes using CNNs, RoBERTa, and BERT. We enhanced pre-trained algorithms using a dataset of racist and abusive and non-racist and abusive memes. Utilizing various assessment metrics, like accuracy, precision, recall, and F1-score, we assessed each model's performance.

关键词： Social media Emotions Multi-lingual BERT Telugu YouTube comments Deep learning

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Bridging Language Barriers: Exploring Hindi-to-English Speech-to-Speech Translation for Multilingual Communication 1

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4th Congress on Intelligent systems (CIS)

作者： Phogat, Divith Prashanth, Karnati Sai Rishith, Mangamuru Sai Sai, Rachure Charith Karthikeya, Sajja Bala Lal, G. Jyothish Premjith, B. Amrita Vishwa Vidyapeetham Amrita Sch Artificial Intelligence Coimbatore Tamil Nadu India

ISBN: (数字)9789819990436

ISBN: (纸本)9789819990429;9789819990436

The increasing need for effective cross-lingual communication has highlighted the vital role of speech-to-speech (S2S) translation systems. These systems hold immense potential, particularly in multilingual countries like India, which boasts 22 official languages, with Hindi being the predominant one. This study is centered around the creation of a Hindi-to-English S2S translation model. Comprising three essential components-speech-to-text (STT), text translation, and text-to-speech (TTS) modules-the model's development takes a structured approach. The STT module leverages CLSRIL-23 + Wav2Vec2, an innovative self-supervised learning technique developed by Facebook AI Research. Through pre-training on substantial amounts of unlabeled speech data, the model captures valuable speech representations, followed by fine-tuning to align with our specific requirements. The output text generated by the STT module undergoes subsequent processing using a transformer-based methodology, ensuring precise translation into English. The final phase involves TTS translation using the Tacotron 2 model. The outcome is an S2S translation model capable of directly producing the target speech (English) from the source language (Hindi). The model achieves an average Mean Opinion Score (MOS) of 3.8, marking a significant advancement in bridging language barriers and facilitating effective multilingual communication.

关键词： Speech-to-speech translation Automatic speech recognition Speech-to-text Machine translation Text-to-speech

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Application of the Learning Factory Morphology to Integrate a Hydrogen Energy System into the E³-factory 14th

Application of the Learning Factory Morphology to Integrate ...

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14th International Conference on Learning Factories (CLF)

作者： Zumpe, Florian Zumpe, Martin Muennich, Marc Suesse, Marian Ihlenfeldt, Steffen Fraunhofer Inst Machine Tools & Forming Technol I Chemnitz Germany Tech Univ Dresden Inst Mechatron Engn Dresden Germany

ISBN: (纸本)9783031653995;9783031654008

Mitigating climate change is one of the greatest challenges on a global scale. The uncertain and intermittent nature of renewable energy sources, such as wind speed and solar radiation, makes it difficult to ensure a constant supply of energy. This problem can be overcome by a renewable hydrogen energy system when coupled with energy conversion and storage devices. Currently, hydrogen technologies are rarely used in industry due to high barriers to entry in terms of cost and expertise. In this context, a hydrogen energy system testbed (H-2-testbed) in a Learning Factory (LF) for research, education and testing of hydrogen technologies would be beneficial to support companies and thus show another way to a CO2-neutral factory. The aim of this paper is to develop a supporting concept for the integration of an H-2-testbed in the E-3-factory environment at Fraunhofer IWU. To achieve this, the learning factory morphology is applied to identify the current status, open gaps, and future development goals and application scenarios. It was found that the current scenario represents a well-defined technical concept for the integration of the H-2-testbed. However, the results also show that there is a lack of a didactic strategy regarding the development of competency-oriented learning modules.

关键词： hydrogen energy system testbed learning factory morphology

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Prompt Engineering for Personalized Assessment and Formative Assessment in Technical Education

Prompt Engineering for Personalized Assessment and Formative...

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2024 International Conference on Computing, Communication, Cybersecurity and AI

作者： Raikwar, Sunny Pathak, Deepika Prajapat, Shaligram Dr APJ Abdul Kalam Univ Indore Indore India Devi Ahilya Univ Indore Indore India

ISBN: (纸本)9783031744426;9783031744433

This work presents a template for using a prompt engineering process to develop a formative assessment plan for the simplified course of "Fundamentals of Computers and Information Technology". The awareness and effectiveness of prompt engineering towards enhancing the formative assessment procedures in Technical Education (Higher Education) is the aim of this paper. By utilizing the virtues of prompt engineering and Complex Large Language Models faculty members can carefully craft prompts. With this support, any teacher or instructor can personalize the formative assessment procedure according to the learners' class. The paper also discusses the flow and sample structure to understand the prompt engineering process.

关键词： Prompt engineering Technical Education Higher Education Complex Large Language Models

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Comparative Analyses of ROS Local Planners for Quadrupedal Locomotion: A Study in Real and Simulated Environments 27th

Comparative Analyses of ROS Local Planners for Quadrupedal L...

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

作者： Bermudez, Gabriel Goncalves Pedro, Gabriel Duarte Medeiros, Vivian Suzano Boaventura, Thiago Univ Sao Paulo Sao Carlos SP Brazil

ISBN: (纸本)9783031713002;9783031713019

Advancements in hardware, computation, and algorithms are driving a revolution in the field of mobile robots. This study compares the ROS-based local planner navigation algorithms Dynamic Window Approach (DWA), Timed Elastic Band (TEB), and Trajectory Rollout for application in legged locomotion. The tests were performed in simulation and on a real quadruped robot using a small maze-type environment. The experiments measured the total time and distance achieved for each local planner. The results reveal a comparable performance among navigation algorithms in real and simulated environments. Specifically, the Timed Elastic Band (TEB) algorithm demonstrates superior performance, exhibiting an average traversal duration of 31.3 s in simulated environments and 30.8 s in real-world conditions, coupled with an average traversal distance of 14.5 m (simulated) and 13.7 m (real-world).

关键词： Quadruped robot Local path planning Navigation

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