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检索条件"丛书名=Advances in Intelligent Systems and Computing"

共 33564 条记录，以下是2051-2060 订阅

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Analysis of Spatial Domain Image Steganography Based on Pixel-Value Differencing Method 8th

Analysis of Spatial Domain Image Steganography Based on Pixe...

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8th International Conference on Soft computing for Problem Solving (SocProS)

作者： Nisha, C. D. Monoth, Thomas Kannur Univ Dept Informat Technol Kannur 670567 Kerala India Kannur Univ Mary Matha Arts & Sci Coll Dept Comp Sci Wayanad 670645 Kerala India

ISBN: (纸本)9789811501845;9789811501838

Image steganography is a technique of embedding secret information inside a cover image and transmits through a public channel without revealing the presence of a message. So that no one except the intended recipient can recognize secret message within the carrier image. Image steganography based on pixel value differencing (PVD) is one of the most important steganographic methods in spatial domain. To embed secret information, PVD method utilizes the difference value of each pixel pair on cover image. In this paper, we study the basic concepts of image steganography based on PVD method and latest research developments in image steganography using PVD. We also presented a detailed analysis of these techniques on the basis of some performance parameters such as payload capacity, imperceptibility, and robustness.

关键词： Steganography Image steganography Spatial domain image steganography Pixel-value differencing

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A Fuzzy Logic Technique for Optimizing Follicular Units Measurement of Hair Transplantation 4th

A Fuzzy Logic Technique for Optimizing Follicular Units Meas...

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4th International Conference on Soft computing and Data Mining (SCDM)

作者： Mostafa, Salama A. Alsobiae, Abdullah S. Ramli, Azizul Azhar Mustapha, Aida Ali, Rabei Raad Univ Tun Hussein Onn Malaysia Fac Comp Sci & Informat Technol Batu Pahat Johor Malaysia Univ Tenaga Nas Coll Comp & Informat Kajang 43000 Selangor Malaysia

ISBN: (纸本)9783030360566;9783030360559

Hair transplantation medical procedure is one of the main methods that are at present utilized in the treatment of balding of the scalp. It is essentially a procedure of extricating or taking a particular number of Follicular Units (FUs) from the back of the head which serves as the contributor or donor region and transplanting them in the region of the scalp that is going bald. A FU comprises one to five normally occurring human skin hairs. The most mainstream techniques designed for hair transplantation dependent on the FUs idea is the Follicular Units Extraction (FUE). Past endeavors to calculate the needed number of FUs for the FUE failed to put into consideration various metrics or indices (parameters) associated with the determination procedure. This paper expounds a Fuzzy Logic Follicular Units Measurement (FL-FUM) strategy for hair transplantation of the FUT and FUE techniques. The FL-FUM technique gives a progressively exact estimation of the needed FUs number by envisaging about three fuzzy metrics of Age, Race and Donor Area Density (DAD). Its objective is to help hair reclamation people who utilize the FUT and FUE techniques in assessing the needed number of necessary grafts that fulfill a patient's baldness state. The FL-FUM strategy employs a Fuzzy Logic system on the three metrics (fuzzy sets) to defuzzify the assessment of the FUs dependent on Visualized Male Pattern Baldness Schema. The strategy is tried and assessed by contrasting its outcomes and the comparable existing strategies and is observed to be highly productive for real estimation cases.

关键词： Hair transplantation Follicular units transplantation Follicular units extraction Follicular units measurement Fuzzy logic

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An Approach to Analysis of Useful Quality Service Indicator and Traffic Service with Fuzzy Logic 10th

An Approach to Analysis of Useful Quality Service Indicator ...

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10th International Conference on Theory and Application of Soft computing, computing with Words and Perceptions (ICSCCW)

作者： Ibrahimov, Bayram G. Alieva, Almaz A. Azerbaijan Tech Univ Huseyn Javid 25 Baku Azerbaijan Mmgechaur State Univ Zahid Khalilov 23 Mingechaur Azerbaijan

ISBN: (纸本)9783030352493;9783030352486

The indicators of the multimedia traffic quality service and the tasks managing the distribution resources in multiservice telecommunication networks are analyzed in the presence of the incoming load self-similarity property. The aim of the work is to consider an approach of controlling the quality of service (QoS) indicator in terms of the self-similar traffic based on the prediction of the Hurst coefficient using fuzzy logic. Based on the network traffic structure study, a new approach of analyzing the quality of useful service index and service traffic has been proposed, which is based on the theory of fuzzy sets.

关键词： Fuzzy logic Self-similar traffic QoS Information and network resource Hurst coefficient Fuzzy set Membership function

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2nd International Conference on Human systems Engineering and Design (IHSED) - Future Trends and Applications

作者： Hecht, Tobias Darlagiannis, Emilia Bengler, Klaus Tech Univ Munich Chair Ergon Boltzmannstr 15 D-85748 Garching Germany

ISBN: (纸本)9783030279288;9783030279271

Automated driving allows the driver to deal with non-driving related activities (NDRA). Surveys, observations in other modes of transportation and driving simulator studies reveal a high variance in possible activities and activity durations. An online study was thus conducted to investigate factors influencing the choice of NDRA. Privacy, storage option, travel duration and purpose were found to have an impact on the attractiveness of certain activities. Furthermore, we investigated the changing need for information that comes with activity engagement. When performing an intense NDRA such as working, results of the online survey indicate that information about current and upcoming maneuvers, surrounding traffic and current speed become less important, while reliability, system status and especially remaining time in current automation mode remain important for people engaged in a NDRA.

关键词： Non-driving related activities Automated driving Human factors

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Infrastructure of RFID-Based Smart City Traffic Control System

Infrastructure of RFID-Based Smart City Traffic Control Syst...

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International Conference on Automation (AUTOMATION)

作者： Pawlowicz, Bartosz Salach, Mateusz Trybus, Bartosz Rzeszow Univ Technol Al Powstancow Warszawy 12 PL-35959 Rzeszow Poland

ISBN: (纸本)9783030132736;9783030132729

Taking as a basis the concept of urban development referred to as smart city 2.0, the article presents the possibilities offered by modern urban infrastructure in the field of intelligent traffic control. In particular, this applies to algorithms of optimal traffic distribution and rapid response to emergency situations. Various scenarios for improving this control using RFID (Radio-Frequency IDentification) technology are discussed. Thanks to RFID it is possible to control access to zones with traffic restrictions, including city centers, areas available for specific types of vehicles or for vehicles meeting certain environmental standards. An important novelty is the solution involving the installation of RFID readers in vehicles, and not only in road infrastructure. A hybrid solution that could be used during the transitional period is also presented.

关键词： Smart City Traffic management RFID

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Application of Metaverses as an Evaluation Tool in the Baccalaureate 2nd

Application of Metaverses as an Evaluation Tool in the Bacca...

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22nd International Conference on Interactive Collaborative Learning (ICL) / 48th IGIP International Conference on Engineering Pedagogy - Impact of the 4th Industrial Revolution on Engineering Education

作者： Alvaro-Farfan, Aroca Sanchez-Guerrero, Javier Gavilanes-Lopez, Wilma Santiago-Chavez, Nora Tech Univ Ambato Educ Informat Ambato Ecuador Univ Tecn Ambato Fac Ciencias Humanas & Educ Ambato Ecuador Univ Tecn Ambato Ambato Ecuador

ISBN: (纸本)9783030402716;9783030402709

Based on the technological development and the possibility to take advance of the capabilities that it offers on education, the purpose of this article is to study the usage of virtual worlds (Metaverses) as evaluational tool on students cursing the unified general bachelorship, appraisal applied to the third-year pupils at (Unidad Educativa Santa Mariana de Jesus) in the subjects of Mathematics, Language-Literature, and Chemistry, considering the stratified groups with parallels A, B, and C, performing the evaluations in the classroom, as well in the Metaverse, through a theoretical conceptualization of the main aspects and the creation of a virtual world in "OpenSim" with its own server both for the Metaverse and for "Moodie" and its connection with "Sloodle", in this way contributing with statistical data on the obtained results.

关键词： Education Metaverse Evaluation OpenSim Sloodle

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Building Robust Prediction Models for Defective Sensor Data Using Artificial Neural Networks 14th

Building Robust Prediction Models for Defective Sensor Data ...

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14th International Conference on Soft computing Models in Industrial and Environmental Applications (SOCO)

作者： de Sa, Claudio Rebelo Shekar, Arvind Kumar Ferreira, Hugo Soares, Carlos Twente Univ Enschede Netherlands Robert Bosch GmbH Stuttgart Germany INESC TEC Porto Portugal Univ Porto Fac Engn Porto Portugal

ISBN: (纸本)9783030200558;9783030200541

Sensors are susceptible to failure when exposed to extreme conditions over long periods of time. Besides they can be affected by noise or electrical interference. Models (Machine Learning or others) obtained from these faulty and noisy sensors may be less reliable. In this paper, we propose a data augmentation approach for making neural networks more robust to missing and faulty sensor data. This approach is shown to be effective in a real life industrial application that uses data of various sensors to predict the wear of an automotive fuel-system component. Empirical results show that the proposed approach leads to more robust neural network in this particular application than existing methods.

关键词： Neural networks

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Study Effort and Student Success: A MOOC Case Study 21st

Study Effort and Student Success: A MOOC Case Study

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21st International Conference on Interactive Collaborative Learning (ICL) / 47th IGIP International Conference on Engineering Pedagogy - Teaching and Learning in a Digital World

作者： Samuelsen, Jeanette Khalil, Mohammad Univ Bergen Bergen Norway

ISBN: (纸本)9783030119324;9783030119317

Learning was once defined as the function of efforts spent in relation to efforts needed [3]. Provided that effort is closely linked to time, previous research has found a positive relationship between student effort over time and student success, both in university education and Massive Open Online Courses (MOOCs). With the complex environment of tracing and identifying relevant data of student learning processes in MOOCs, this study employs learning analytics to examine this relationship for MITx 6.00x, an introductory programming and computer science MOOC hosted on the edX MOOC platform. A population sample from the MOOC (N = 32,621) was examined using logistic regression, controlling for variables that may also influence the outcome. Conversely, the outcome of this research study suggests that there is a curvilinear relationship between effort over time and student success, meaning those who exert effort for the longest amount of time in the MOOC actually have a lower probability of obtaining a certificate than others who exert effort over somewhat less time. Finally, research implications are discussed.

关键词： Massive open online course (MOOC) Efforts Learning analytics Logistic regression Total time Study success

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Technological Literacy Through Outreach with Educational Robotics 10th

Technological Literacy Through Outreach with Educational Rob...

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10th International Conference on Robotics in Education (RiE)

作者： Jaeggle, Georg Lammer, Lara Hieber, Hannah Vincze, Markus Vienna Univ Technol ACIN Inst Automat & Control Vienna Austria

ISBN: (纸本)9783030269456;9783030269449

Educational robotics has gained increased importance and attention worldwide as an excellent teaching tool for STEM (Science, Technology, Engineering, Mathematics). However, catching the enthusiasm of young learners who are not already interested in STEM remains challenging. In this paper, we describe our outreach concept where young people from Vienna and surroundings visit the technical university with their teachers for a three-hour program. Our focus is on technological literacy, the understanding of what a robot is and how it works and may look like, as well as different robotic application areas. Theory and hands-on are combined in an age-appropriate concept based on constructivism. In order to evaluate our approach, we have developed a short post-questionnaire. Our results with 255 young people ages 7 to 17 show that after the visit 84% are more interested in technology and 80% are more interested in robotics. 85% of the young learners find that robots are complex machines after the visit. Despite that fact, 85% of those who find robots complex are more interested in robotics, 85% want to come back to learn more about robotics, and 91% will tell their families about these activities.

关键词： Educational robotics Technological literacy Interest in STEM Perception of robots STEM career

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A System for the Study of Emotions with EEG Signals Using Machine Learning and Deep Learning 1

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International Conference on Cognitive Informatics and Soft computing (CISC)

作者： Jaswanth, Vasupalli Naren, J. SASTRA Deemed Univ Thanjavur Tamil Nadu India

ISBN: (数字)9789811514517

ISBN: (纸本)9789811514517;9789811514500

Human life deals with a lot of emotions. Analyzing the emotions using EEG signals plays a pivotal role in determining the internal/inner state of a particular human. EEG deals with the spontaneous electrical activity of neurons as recorded from multiple electrodes placed in the interior region of the brain. Initially, EEG signals are captured and preprocessed for the removal of noise signals. Selection of appropriate classification techniques in emotion analysis is an important task. The classifiers like k-nearest neighbor (k-NN), SVM, LDA were evaluated. Performances of the classifiers in analyzing a wide range of emotions (arousal and valence emotions) were examined. The results examined demonstrated that emotion analysis using EEG signals is highly advantageous and efficient than the existing traditional recognition systems.

关键词： EEG Machine learning Feature extraction Classification

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