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

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A Comprehensive Exploration of Cryptographic Solutions for Securing Medical Images 4th

A Comprehensive Exploration of Cryptographic Solutions for S...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Ben Hssain, Idriss Bencherqui, Ahmed Karmouni, Hicham Moustabchir, Hassane Sayyouri, Mhamed Hafid, Abdelatif Sidi Mohamed Ben Abdellah Fez Univ Natl Sch Appl Sci Engn Syst & Applicat Lab Fes Morocco Higher Sch Engn Appl Sci ESISA Analyt Lab Fes Morocco

ISBN: (纸本)9783031686740;9783031686757

The sensitivity of medical images (MI) requires them to be protected in order to preserve patients' privacy and guarantee a reliable and correct diagnosis. To prevent unwanted access and unauthorized manipulation of this crucial data, MI encryption (MIE) is considered as one of the most effective ways to protect medical data. For this purpose, an overview of the principles, requirements, evaluation standards and typical attacks associated with MIE is provided in this article. Various encryption techniques, such as post-quantum cryptography (PQC), elliptic curve cryptography (ECC), chaotic systems (CS), and DNA-based encryption are presented in this paper describing their advantages and disadvantages. Additionally, it covers some features of each MIE technique and compares them to each other as it suggests future avenues of research for further studies and development in this rapidly developing sector while addressing the complexities of transmitting and safeguarding MIs information online.

关键词： MI Image encryption (IE) CS Symmetric encryption (SE) DNA ECC PQC

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Decision Fusion-Based System for Automatic Face Emotions Recognition

Decision Fusion-Based System for Automatic Face Emotions Rec...

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Intelligent systems Conference (IntelliSys)

作者： Ichim, Loretta Dinu, Silviu Popescu, Dan Univ Politehn Bucuresti Fac Automat Control & Comp Bucharest Romania Stefan S Nicolau Inst Virol Bucharest Romania

ISBN: (纸本)9783031477232;9783031477249

Facial expressions play an important role in communication and interpersonal relationships. That is why a variety of applications have been developed in various fields inwhich they must be recognized, such as security, medicine, psychology, marketing, education, gaming, etc. There are generally six basic emotions that can be identified from facial images and a few derived emotions. Thus, the paper proposes a system based on the collective intelligence of five neural networks (MobileNetV2, MobileNetV3 Large, EfficientNet B0, EfficientNet B2, and EfficientNet B5) for the recognition of emotions with the goal of early detection of mental illness and rapid introduction of a therapeutic scheme. The decision fusion method considers the maximum sum of the individual predictions of the 5 networks per class and the validation of the resulting class by at least two individual networks. The testing of the global system was done on three emotions, sad, angry, and happy using images from the public database, and the accuracy obtained was 84.73%, better than the individual neural networks. The results obtained are promising and lead to the use of this system and other categories of facial expressions.

关键词： Facial Expression Emotion Recognition Decision Fusion Machine Learning Neural Network

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A Survey of Automatic Number Plate Recognition and Parking Management System 8th

A Survey of Automatic Number Plate Recognition and Parking M...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Alekar, Samruddhi Kulkarni, Yash Gavhane, Vedant Jadhav, Rajsing Lambhate, Divya Kakade, Mandar SCTR Pune Inst Comp Technol Pune India

ISBN: (纸本)9789819713226;9789819713233

Automatic Number Plate Recognition (ANPR) is a real-time embedded system designed to automatically identify and extract license plate information from vehicles. This research focuses on the unique challenges presented by Indian conditions, where license plate standards are often not followed. The system incorporates several specialized algorithms, including "feature-based number plate localization" to locate the license plate, "image scissoring" for character segmentation, and statistical feature extraction for character recognition, all tailored to Indian number plates. This study aims to not only evaluate existing methods but also introduce our own algorithm. It includes a brief overview of various approaches used in license plate recognition. Ultimately, the goal of ANPR is to retrieve license plate details from vehicles.

关键词： Vehicle number plate detection OpenCV Optical character recognition Template matching License plate localization PostgreSQL

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Using Knowledge Graph and KD-Tree Random Forest for Image Retrieval 12th

Using Knowledge Graph and KD-Tree Random Forest for Image Re...

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

作者： Nguyen Thi Dinh Thanh Manh Le Thanh The Van Ho Chi Minh City Univ Ind & Trade Ho Chi Minh City Vietnam Hue Univ Univ Sci Hue Vietnam HCMC Univ Educ Ho Chi Minh City Vietnam

ISBN: (纸本)9783031602269;9783031602276

Semantic-based image retrieval has recently become popular and contains many challenges. Thiswork proposes a framework for semantic-based image retrieval by using a Knowledge Graph and a KD-Tree Random Forest. In the pre-processing phase, firstly, we use the R-CNN network to segment the image set into object images, extract features for object images, and classify object images by using the KD-Tree. Secondly, a KD-Tree Random Forest is used to classify the visual relationship of each pair of objects. Thirdly, a Relationship Graph is created based on object images and their visual relationships. Finally, a Knowledge Graph is built and applied to a semantic-based image retrieval system. After segmenting the objects using the R-CNN network for each query image, the KD-Tree is used to classify the objects, and a KD-Tree Random Forest is used to predict their visual relationships. Then, a SPARQL query is generated to retrieve based on a Knowledge Graph and extract similar images. The experiment results with the Oxford Flower-17 and Flickr image sets showed that the precision achieved scores of 0.8586 and 0.8189, respectively. These results are compared with other works to demonstrate the correctness of the proposed method.

关键词： KD-Tree Random Forest Relationship graph Knowledge Graph Image retrieval

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A Study on the Effect of Measurement Distance on the Accuracy of Millimeter-Wave Radar Sensing for Heartbeat Measurement 1

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18th International Conference on Intelligent Autonomous systems (IAS)

作者： Yuan, Haihang Lu, Yuxi Yang, Tianyi Yu, Wenwei Chiba Univ Dept Med Syst Engn Chiba Japan Chiba Univ Ctr Frontier Med Engn Chiba Japan

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

Millimeter-wave radar (mm-wave radar) sensing has great potential for non-contact heartbeat measurement in home monitoring. However, most of the current radar-based measurement is inaccurate. There have been studies reporting signal analysis and processing methods for improving the measuring accuracy. However, the signal-to-noise ratio (SNR) of measured signals needs further improvement. This study aims to explore the possibility of measurement distance between a mm-wave radar and the person to be measured as a key factor to improve the SNR, and thus the measurement accuracy. Two novel evaluation indexes for the quality of radar signals, reflection intensity and the SNR, were proposed, and verified with experiments. The results demonstrated a correlation between these indexes and measurement accuracy, offering insight into determining an appropriate measurement distance for improving accuracy of heartbeat measurement in home monitoring applications.

关键词： Mm-wave radar Signal evaluation Measurement distance

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SAMSEF: An Agile Software Maintenance Leveraging Scrum Framework for Improved Efficiency and Effectiveness 12th

SAMSEF: An Agile Software Maintenance Leveraging Scrum Frame...

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

作者： Ali, Muhammad Cheema, Sehrish Munawar Naz, Ammerha Pires, Ivan Miguel Super Univ Lahore Dept Software Engn Lahore Pakistan Univ Management & Technol Dept Comp Sci Lahore Pakistan Univ Sialkot Dept Comp Sci Sialkot Pakistan Univ Aveiro Escola Super Tecnol & Gestao Agueda Inst Telecomunicacoes Agueda Portugal

ISBN: (纸本)9783031602269;9783031602276

Agile methodologies have gained widespread recognition for their ability to produce high-quality software systems. Given that over half of all job, roles are associated with maintenance activities throughout a program system's entire lifecycle, researchers and engineers are actively exploring utilizing agile methods to ensure the continued robustness of the software. The agile software development lifecycle lacks a dedicated maintenance plan, prompting the need for a set of agile maintenance principles derived from both theoretical foundations and practical experience. These established standards encompass maintenance planning, customer involvement, incremental maintenance execution, documentation updates at each stage, and thorough testing of maintenance tasks. This study proposes an efficient framework named SAMSEF-based. It is a hybrid of Model-Based Software Engineering and Agile methodology, successfully used in a pilot study on health technology systems. It can improve project progression and system design documentation, enhancing agile capabilities.

关键词： Software Agility scrum efficiency accelerated maintenance software life cycle MBSE

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A Collaborative Robot-Assisted Manufacturing Assembly Process 6th

A Collaborative Robot-Assisted Manufacturing Assembly Proces...

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6th Iberian Robotics Conference (Robot)

作者： Neves, Miguel Duarte, Laura Neto, Pedro Univ Coimbra Dept Mech Engn CEMMPRE ARISE P-3030788 Coimbra Portugal

ISBN: (纸本)9783031586750;9783031586767

An effective human-robot collaborative process results in the reduction of the operator's workload, promoting a more efficient, productive, safer and less error-prone working environment. However, the implementation of collaborative robots in industry is still challenging. In this work, we compare manual and robot-assisted assembly processes to evaluate the effectiveness of collaborative robots while featuring different modes of operation (coexistence, cooperation and collaboration). Results indicate an improvement in ergonomic conditions and ease of execution without substantially compromising assembly time. Furthermore, the robot is intuitive to use and guides the user on the proper sequencing of the process.

关键词： Human-robot Interaction Collaborative robotics Manufacturing Assembly

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Simulating the Effect of Economic Development on the Use of Renewable Energy in Southeast European Union Countries 10th

Simulating the Effect of Economic Development on the Use of ...

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

作者： Djedovic, Irfan Imamovic, Jasna Sehanovic, Lejla Tandir, Natasa Int Burch Univ Fac Econ & Social Sci Dept Banking & Finance Ilidza 71210 Bosnia & Herceg Int Burch Univ Fac Econ & Social Sci Dept Management Ilidza 71210 Bosnia & Herceg

ISBN: (纸本)9783031662676;9783031662683

This article employs a quantitative approach to examine how the nations in the Southeastern European Union (EU)-Bulgaria, Croatia, Greece, Slovenia, Slovakia, Hungary, and Romaniaare affected by economic growth in terms of their use of renewable energy. The study employs panel data models to examine the connection between the use of renewable energy sources and economic expansion from 2007 to 2020. This research uses Fully Modified Ordinary Least Squares, or FMOLS. The FMOLS results revealed that the utilization of renewable energy is not statistically significantly impacted by real GDP per capita., having enough evidence to not support the conservative hypothesis. Analysis is done using R, SPPS and EViews software programs. The article contributes to existing literature by exploring how economic development influences implementation and usage of sustainable energy in the Southeastern EU countries.

关键词： use of renewable energy economic expansion metric tons of CO2 emissions per person

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Domestic Solid Waste Prediction with an Enhanced LSTM with SigmoReLU and RAdam Optimizer 6th

Domestic Solid Waste Prediction with an Enhanced LSTM with S...

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

作者： Fadhel, Abdulrahman Sharaf Mohammed Ghazali, Rozaida Tomari, Mohd Razali Md Hassim, Yana Mazwin Mohmad Hassan, Abdullahi Abdi Abubakar Ismail, Lokman Hakim Univ Tun Hussein Onn Malaysia Fac Comp Sci & Informat Technol Batu Pahat Kagawa Malaysia Univ Tun Hussein Onn Malaysia Fac Elect & Elect Engn Batu Pahat Kagawa Malaysia Univ Tun Hussein Onn Malaysia Fac Civil Engn & Built Environm Batu Pahat Kagawa Malaysia

ISBN: (纸本)9783031669644;9783031669651

A novel approach is presented to address the prediction challenge in domestic solid waste generation through the application of machine learning techniques. To overcome the limitations inherent in capturing intricate temporal patterns faced by conventional Long Short-Term Memory (LSTM) models designed for time series forecasting, an enhanced variant, termed e-LSTM, is introduced. This model incorporates crucial enhancements to rectify standard LSTM shortcomings. Introducing a hybrid activation function, SigmoRelu, bolsters the model's capacity to grasp complex time series patterns. Furthermore, the RAdam optimizer is employed to optimize the learning process and improve convergence. Dropout layers are seamlessly integrated within the LSTM architecture to counter overfitting, ensuring robust generalization to novel data. A series of comprehensive experiments is conducted to compare the performance of the e-LSTM model against standard LSTM and GRU models, showcasing its noteworthy advancements. Notably, the e-LSTM model demonstrates superior predictive accuracy in forecasting waste generation compared to standard LSTM and GRU models. In essence, the proposed e-LSTM model represents a significant stride in domestic solid waste prediction, effectively mitigating the limitations of traditional LSTM models. The synergistic integration of SigmoRelu activation, RAdam optimization, and dropout mechanisms results in a resilient and accurate predictive framework. Empirical results affirm the model's superiority, establishing it as a valuable tool for waste management applications and decision-making processes.

关键词： Domestic Solid Waste Time series forecasting Hybrid activation function LSTM RADAM Machine learning

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A Deep Learning Approach for Traffic Flow Prediction in City of Sarajevo 10th

A Deep Learning Approach for Traffic Flow Prediction in City...

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

作者： Kamenjasevic, Nedim Eljazovic, Maida Sarajlic, Mirzet Cantonal Adm Inspect Issues Canton Sarajevo Sarajevo 71000 Bosnia & Herceg Nelt Ltd Sarajevo 71000 Bosnia & Herceg Univ Sarajevo Fac Traff & Commun Sarajevo 7100 Bosnia & Herceg

ISBN: (纸本)9783031662706;9783031662713

Constant traffic jams and congestion in the City of Sarajevo reduce efficiency of road infrastructure and increase travel time and air pollution. Achieving a satisfactory level of road network service, which will lead to greater satisfaction of traffic participants, as well as all citizens, requires short-term planning of traffic flows in the City of Sarajevo. Deep learning techniques can be used with technological progress to collect information from real time and to predict future traffic flow in the City of Sarajevo.

关键词： traffic jams traffic congestions traffic flow deep learning

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