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

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Sign Language Text Translator Using YOLOV7 Algorithm 9th

Sign Language Text Translator Using YOLOV7 Algorithm

引用

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

作者： Mendoza, Paula Jean C. Salo, Arceli F. Santiago, Nila D. Mauricio, Keila Marie S. Cano, Adrian Gabriel C. Technol Inst Philippines Quezon City Manila Philippines

ISBN: (纸本)9789819735556;9789819735563

The Filipino deaf community's native language is Filipino sign language (FSL). However, communication hurdles exist between deaf people who use FSL and hearing people who do not understand the language. To bridge this gap, researchers developed a mobile app that uses the YoloV7 algorithm to translate FSL into real-time text. The you only look once (YOLO) technique is used in the app's deep learning model. In real time, our model recognizes and records human hand gestures. YOLOv7 was chosen for its object detection accuracy and real-time processing. The technology captures FSL user hand motions with the phone's camera, which are then processed and transformed into text. The trained YoloV7 model had an accuracy of 97.9%. The project was evaluated by 7 technical and 30 non-technical people using ISO 25010 criteria. User evaluations yielded an average score of 4.45, demonstrating ISO 25010 compliance in functional suitability, usability, and reliability. In conclusion, the program has the potential to transform communication between deaf and hearing people by providing effective FSL-to-text conversion. This accessibility can help deaf people in education, healthcare, and social relationships.

关键词： YoloV7 algorithm Deep learning Object detection Sign language Mute FSL Deaf Hand gestures Mobile application

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Prediction of Subsonic Flutter Speeds for Composite Missile Fins Using Machine Learning 1

引用

2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI)

作者： Dinulovic, Mirko Univ Belgrade Aerosp Dept MIT Module Fac Mech Engn Kraljice Marije 16 Belgrade 11120 Serbia

ISBN: (数字)9783031608407

ISBN: (纸本)9783031608391;9783031608407

In the present paper, using machine learning techniques (ML), the prediction of flutter speeds for composite material missile fins is estimated for the subsonic flight regimes. Several types of composite materials are investigated (Kevlar, carbon, and E-glass S) for different fin geometries that are used nowadays in the aerospace industry as a building block for fly-worthy primary structural components. For flutter speeds data collection, the hybrid methodology is deployed, experimental, by performing tests in the subsonic wind tunnel, whereas the synthetic data for the ML model is generated using modified NACA flutter boundary equations. These equations were modified for orthotropic materials manufactured in the form of thin-walled structures. Based on this dataset, several algorithms were analyzed in order to create the ML flutter model, and it was found that for the problem on hand, the LightGBM regression approach renders the most accurate results (max coefficient of determination values) when compared to other investigated algorithms. Using ML Net technologies, a bespoke flutter software was developed. The results obtained were compared to the results obtained by experiments, known flutter binary models, and finally, numerical models based on structural, aerodynamic spline finite element approach. Agood agreement between flutter speeds models was obtained, and it was concluded that the ML approach based on the LightGBM regression can be successfully used for problems where the subsonic flutter speeds estimate for composite missile fins is sought.

关键词： flutter stability loss composites fins machine learning wind tunnel

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Challenges, Communications, Routing Protocols and Applications of FANETs-A Systematic Review 5th

Challenges, Communications, Routing Protocols and Applicatio...

引用

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

作者： Sharma, Mohini Dubey, Ghanshyam Prasad Batham, Diksha Yadav, Mohit Singh, Ayush Raj Sharma, Anushka Amity Univ Amity Sch Engn & Technol Dept CSE Gwalior Madhya Pradesh India

ISBN: (纸本)9789819720811;9789819720828

The Flying Ad hoc Network (FANET) is a network of self-organizing wireless nodes that mostly consists of Unmanned Aerial Vehicles (UAVs) and other flying nodules that interact nearby. It diverges from other ad hoc networks with an abundant number of additional features. One type of decentralized wireless network is an ad-hoc network, occasionally referred to as a MANET (mobile ad hoc network). The network is ad hoc as there isn't any fixed infrastructure, for instance routers or wireless access points. Rather, every node aids in routing by transmitting information to other nodes. Another name for UAVs is Unmanned Aircraft systems (UAS). The reason for this is because flying ad hoc networks with high speed necessitate extremely dynamic routing protocols. Routing protocol design is hard due to different characteristics such as traffic monitoring, load balancing, and so on. This paper discusses FANET, its communication and routing protocols, applications, and challenges.

关键词： FANET VANET MANET Ad hoc networks Routing protocols UAVs Wireless networks

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AI Solutions for Inter-organisational Care: A Case Based Analysis 1

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

作者： Lindeberg, Joran Henkel, Martin Perjons, Erik Johannesson, Paul Lappalainen, Katarina Fast Stockholm Univ Dept Comp & Syst Sci Stockholm Sweden Stockholm Univ Dept Law Stockholm Sweden

ISBN: (数字)9783031456428

ISBN: (纸本)9783031456411;9783031456428

Health care is a complex domain containing large amounts of data, including clinical and administrative data. Furthermore, the domain includes advanced decision-making utilising the collected data. Various IT systems based on AI technologies, such as machine learning, have been promoted as a way to improve both the quality and efficiency of health care. So far, the focus has been on supporting quite narrow and data-intensive activities carried out by a single actor, such as interpreting X-ray images and performing triage. However, providing health care for a single patient can involve a comprehensive process with numerous actors, ranging from home care and primary care to specialist care. In this paper, we examine how existing AI solutions can support a complex care process involving several collaborating actors. We base the examination on a health care case from Swedish elderly care. The case is used to identify multiple problem areas, which are then compared to existing AI solutions.

关键词： AI Inter-organisational Collaboration HealthcareHealth Informatics Elderly Care

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Real-Time Estimation of Calories from Indian Food Pictures Using Image Processing Techniques 8th

Real-Time Estimation of Calories from Indian Food Pictures U...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Bongirwar, Vrushali Baghele, Shivam Kashyap, Vikram Chharra, Sahil Mundhada, Pranjal Shri Ramdeobaba Coll Engn & Management Nagpur Maharashtra India

ISBN: (纸本)9789819713127;9789819713134

Indian food is one of the most popular cuisines in the world and comprises uniquely flavored preparations using traditional recipes and spices. Across India's 28 states, 135 billion population, and hundreds of years of the cultural heritage of our Country has resulted in a huge number of sub-cuisines and a vast number of unique dishes. In this paper, a system for detecting the calorie count of Indian food by detecting food items in images using You Only Look Once (YOLO) algorithm is presented. The calorie count of food items is an important parameter that needs to be considered while maintaining a healthy lifestyle. However, manually counting calories can be a tedious and time-consuming task. The proposed system uses deep learning to automatically detect the food items in an image and estimate their calorie count. This system can be used to create a calorie-counting app that can help individuals maintain a healthy diet.

关键词： Food recognition Deep learning Image processing

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Solving Multi-capacitated Facility Location Problem in Traffic Control systems Using Lagrangian Relaxation and Decomposition Approach 7th

Solving Multi-capacitated Facility Location Problem in Traff...

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7th International Conference on Logistics Operations Management (GOL)

作者： El Amrani, Mohammed Bouanane, Khaoula Abba, Khalil Benadada, Youssef Mohammed V Univ Rabat Fac Sci Algorithms Networks Intelligent Syst & Software E Rabat Morocco Ecole Marocaine Ingn Polytech Smart Lab Rabat Morocco Mohammed V Univ Rabat ENSIAS Rabat IT Ctr Smart Syst Lab Rabat Morocco

ISBN: (纸本)9783031686337;9783031686344

The Budget-Constraint Multi-Capacitated Location Problem represents a generalized extension of the classical p-median location problems. It involves the allocation of predetermined capacity levels constraints to each facility while efficiently assigning customers within a network to minimize total connection costs. In this study, we explore the application of this model in the domain of road traffic regulation to optimize network installation and determine the appropriate server configurations required for processing data collected from sensors. In the second section of this paper, we address the problem through a new approach rooted in Lagrangian relaxation and decomposition. This innovative approach facilitates parallel computing, resulting in a notable reduction in execution time. The resolution of this complex problem encompasses two key stages: the calculation of Lagrange multipliers and the implementation of a heuristic method to ensure solution feasibility. Ultimately, we present computational results obtained by solving new instances derived from p-median problems found in the existing literature. Our research contributes to addressing real-world traffic management challenges by optimizing facility placement and resource allocation, with practical implications for improving traffic control systems.

关键词： Facility Location Lagrangian Relaxation SubGradient Road Traffic Control

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Analysis of Early Cancer Diagnosis Using Machine Learning 13th

Analysis of Early Cancer Diagnosis Using Machine Learning

引用

13th Computer Science Online Conference

作者： Gjosheva, Marija Bogoevski, Zlate Velichkovska, Bojana Efnusheva, Danijela Jakimovski, Goran Atanasova, Sanja Ss Cyril & Methodius Univ Dedicated Comp Syst Dept Fac Elect Engn & Informat Technol Skopje North Macedonia

ISBN: (纸本)9783031705175;9783031705182

Cancer is a group of diseases with similar symptoms, all involving uncontrolled growth and reproduction of cells. With around 8 million deaths each year, it is the second leading cause of death worldwide in developing countries and the first in the developed world. In contemporary medicine, early cancer diagnosis for every known type is essential. Machine learning has the potential to completely transform the process and increase the number of lives saved. In order to make predictions, computers develop complex data models and search for patterns. Early cancer diagnosis could undergo a revolution because of machine learning. This research's goal is to outline the issue surrounding cancer diagnoses in patients and all the difficulties they experience. Asuitable strategy will be to model the risk of cancer and patient outcomes given the growing trend of employing machine learning technics in cancer research. Aspecific model has been developed that, if applied appropriately, can reduce the number of lost lives and, at the same time, increase the number of individuals capable of coping with this disease. The results indicate that the created model can be used by professionals to identify lung cancer with efficiency. If the prediction is accurate, the doctor may be able to develop a better treatment plan and provide the patient with an early diagnosis. The study's findings show that the number of patients has been rising recently, yet early detection is crucial because it can help avert serious complications.

关键词： machine learning diagnosis analysis cancer transformation lungs

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POMA: Propagation-Based Obstacle Negotiation Control for Multi-segmented Robot Adaptation 27th

POMA: Propagation-Based Obstacle Negotiation Control for Mul...

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

作者： Nantareekurn, Worameth Leung, Binggwong Srisuchinnawong, Arthicha Homchanthanakul, Jettanan Pewkliang, Suppachai Manoonpong, Poramate Vidyasirimedhi Inst Sci & Technol Rayong Thailand PTT Explorat & Prod Publ Co Ltd Bangkok Thailand

ISBN: (纸本)9783031707216;9783031707223

This paper presents Propagation-based Obstacle negotiation control for Multi-segmented robot Adaptation (POMA) in complex environments. POMA integrates three neural control mechanisms: central pattern generator (CPG)-based leg control for generating gaits, horizontal body control for avoiding high obstacles, and vertical body control for climbing ramps and small obstacles. We validated the performance of POMA in a physical simulation. Our experimental results show that POMA enables a bio-inspired multi-segmented, legged robot to adaptively and successfully navigate through a maze with up and down ramps without a map of the environment. This demonstrates the effectiveness of integrating different neural control mechanisms for multi-segmented robots to deal with complex environments.

关键词： Legged robots Neural control Body adaptation Neural dynamics Bio-inspired robots

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Blockchain and AI for Optimizing Bank Data Security

Blockchain and AI for Optimizing Bank Data Security

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Intelligent systems Conference (IntelliSys)

作者： Souare, Ibrahima Keita, Khadidiatou Wane Univ Cheikh Anta Diop Dakar Dakar Senegal Polytech Inst Dakar Senegal

ISBN: (纸本)9783031477201;9783031477218

Online banking has become one of the most important applications on the Internet, being provided by most banks around the world. Banking payment systems are based on the progress of technology. Technology is a key driver for banks. Despite this technological progress, bank data remains the real target of cyber attacks. With the use of these two technologies in SouareTech ensures data sharing in a cooperative environment: blockchain guarantees reliable data sharing in a large-scale environment to form real megadata;AI ensures strict access control, prediction of attacks and more intelligent security in the architecture, which help to establish the banking system more reliable. We adopt the combination of these fuzzy logic (FL) and Private Data Center (PDC) mechanisms in SouareTech allows to get these better performances in terms of the impact of attacks on the banking system and the reliability of the data. In this paper, we have proposed SouareTech, an intelligent architecture that shares, computes and stores data securely in different servers, aiming to thwart cybercriminals. In addition, we have presented the SouareTech architecture and the role of its devices and then an analysis of its effectiveness from the point of view of network security has been made.

关键词： Blockchain AI Security Cyberattacks Banks Data

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Enterprise Intelligent Management Analysis and Visualization Based on Data Mining 1

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

作者： Miao, Zhuang Yu, Xiaoyang Zhang, Haoran Jian, Muwei Univ New South Wales Business Sch Sydney NSW Australia Shandong Univ Finance & Econ Sch Comp Sci & Technol Jinan Peoples R China

ISBN: (数字)9789819735624

ISBN: (纸本)9789819735617;9789819735624

Business intelligence is a data analysis software integrating data warehousing, online analysis, data mining, and visualization techniques. In this paper, we propose a visual analysis framework for enterprise intelligent management based on data clustering and mining, and the designed business intelligent system initially preprocesses and models business data generated from financial statements and stock trading, etc., and then uses a variety of methods including financial analysis, corporate valuation, and machine learning, so as to achieve the visualization analysis and to provide decision support for internal and external information users. Experimental analysis is conducted using BYHEALTH and other four comparable companies as typical examples, and the results demonstrate that the devised framework is all-inclusive, user-friendly, and practical.

关键词： Business intelligence Data analysis Data mining Data visualization

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