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

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Identifying and Mitigating Bias in AI-Generated Image Datasets for Better Cognitive Understanding 1

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Marathe, Aboli Desai, Aditya Walambe, Rahee Kotecha, Ketan Carnegie Mellon Univ Pittsburgh PA 15213 USA Symbiosis Int Univ Symbiosis Inst Technol Pune Maharashtra India Symbiosis Int Univ SCAAI Pune Maharashtra India

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

Cognitive behaviour and the effect of synthetically generated data are highly correlated. Also, human cognition is highly influenced by the bias in the data - be it visual, audio or textual data. With the new and improved tools for generating-AI content, it is very challenging to ensure unbiased cognitive understanding. To that end, in this work, we focus on the image data which synthetically generated and how bias creeps into it. Modern text-to-image models with their ever-growing capabilities have been gaining traction for the quality, text-faithfulness and perceived "realism" observed in their generated outputs. Do these models truly produce realistic creations? Is an underlying bias inadvertently present in these synthetic datasets? And how can we assess the "realism" of these images? Exploring these questions and their solution is the key contribution of this paper. We propose a series of experiments for understanding the human and artificial perceptions of "realism" in synthetic data and the real world. Additionally, open questions like unprompted gender and age bias present in synthetic datasets are investigated and techniques for mitigating similar concerns in future datasets are addressed. The WEDGE dataset is used for the experimentation. Our results show that realism classification is highly dependent on human annotations within the distributions in Fig. 1. We found strong age bias in selected synthetic data and proposed simple state-of-the-art generative methods for mitigation of age, gender and realism bias.

关键词： computer vision bias text-to-image generative models

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Towards Building Multi-factor Authentication Scheme for Users in the Healthcare Sector Based on Blockchain Technology 13th

Towards Building Multi-factor Authentication Scheme for User...

引用

13th Computer Science Online Conference

作者： Jawad, Muwafaq Yassin, Ali A. AL-Asadi, Hamid Ali Abed Abduljabbar, Zaid Ameen Nyangaresi, Vincent Omollo Univ Basrah Dept Comp Sci Coll Educ Pure Sci Basrah 61004 Iraq Jaramogi Oginga Odinga Univ Sci & Technol Dept Comp Sci & Software Engn Bondo 40601 Kenya SIMATS Saveetha Sch Engn Dept Appl Elect Chennai 602105 Tamil Nadu India

ISBN: (纸本)9783031702990;9783031703003

The Internet of Healthcare Things (IoHT) has led to significant growth in the field of digital health research. Protecting patient privacy is difficult since patient data is sensitive. Presently, patient data is commonly maintained in cloud-based healthcare systems, restricting users' authority over their personal information. The healthcare issues cannot function without secure user authentication to verify user identity over possibly unsafe routes. As a result, numerous methods of remote authenticating have evolved, each with its own set of advantages and disadvantages. Privacy, security, and threat concerns are major roadblocks in the healthcare system. This study introduces a secure user authentication system utilizing blockchain technology for healthcare users. Our proposed scheme utilizes blockchain technology, ECC, and symmetric encryption with a crypto-hash function to provide anomalies in user identity and generate One-Time Passwords (OTPs). The solution addresses existing vulnerabilities and validates its security using the Scyther tool, a formal security tool. Our work in the healthcare field focuses on building a system that can establish, record, store, search, and verify information. In addition, we obtained a lower execution time for the proposed scheme, approximately 0.3021 ms compared to other authentication mechanisms. Moreover, the throughputs of our work were very good and increased linearly as the number of users increased. Finally, our suggested work complies with the security standards.

关键词： Blockchain Multi-Factor Authentication IoHT Healthcare

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Kernelized Extension for Multiple-Expert-Learning Classifiers Using Support Vector Machines 1

引用

Computing Conference

作者： Bajja, Mohammed Aalaila, Yahya Umaquinga-Criollo, Ana C. Guachi-Guachi, Lorena Peluffo-Ordonez, Diego H. SDAS Res Grp Ben Guerir 43150 Morocco Mohammed VI Polytech Univ Coll Comp Lot 660 Ben Guerir 43150 Morocco Inst Super Tecnol Ibarra Ave Atahualpa Ibarra 100101 Ecuador Univ Tecn Norte Ave 17 Julio Ibarra 100105 Ecuador Univ Int Ecuador Dept Mechatron Ave Simon Bolivar Quito 70411 Ecuador

ISBN: (数字)9783031622731

ISBN: (纸本)9783031622755;9783031622731;9783031622724

The primary goal for supervised machine learning techniques is to make accurate predictions or classifications based on prior knowledge about the relationships between the input features and their corresponding label assignment. The latter is often difficult to be determine, especially when the ground truth is not unique but instead, a combined decision from a group of experts is given. One way to tackle this challenge is by using Multiple Expert Learning (MEL)-driven classifiers. In this regard, approaches based on Soft-margin support vector machines (SM-SVM) including penalty factors for each labeler have shown to be a suitable alternative as they can learn from experts holding different levels of trustworthiness. Nonetheless, dealing with nonlinear (complex structure) and hardly separable data is still an open issue. To address these problems, this work presents mathematical developments on SVM for MEL scenarios in a fully matrix formulation. As a remarkable contribution, we introduce a kernel extension of the SM-SVM problem for MEL scenarios together with a complete solution following from a quadratic programming approach.

关键词： Supervised learning Support vector machines Multiple expert learning Kernel trick

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The Influence of Smart City Factors on the Economy in the Tourism Sector of Bandung City, Indonesia 9th

The Influence of Smart City Factors on the Economy in the To...

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

作者： Hidayat, Muhammad Taufik Sunarharum, Tri Mulyani Univ Gadjah Mada Jl Grafika 2 Yogyakarta 55281 Indonesia

ISBN: (纸本)9789819733019;9789819733026

Bandung City is known as one of the tourism destination cities in Indonesia. The tourism sector is one of the economic drivers of the city of Bandung. Apart from being known for tourism, since 2014 Bandung has also developed the smart city concept. The Bandung smart city program is dominated by innovation programs in the smart branding dimension which contribute to an increase in the number of tourists and contribute to an increase in local sources of revenue in the tourism sector. This shows that the smart city is driving the tourism sector in Bandung and contributing to its economy. This research focuses upon the influence of smart city factors on the economy of Bandung City in the tourism sector. Smart city factors are seen from leadership, organizational management, innovation, funding, and collaboration. This research uses a qualitative deductive approach with time series analysis methods and qualitative descriptive analysis. The research results show that the development of Bandung City's Local Own Source Revenue in the tourism sector has experienced fluctuations due to the impact of the pandemic and the smart city innovation program that was built has had implications for increasing the number of tourists and Local Own Source Revenue in the tourism sector. Smart city factors lead to an increase in the number of tourists and indirectly influence the increase in Bandung City's local source of revenue in the tourism sector.

关键词： Smart city factors Economy Tourism sector Local own source revenue Bandung City

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A Novel Approach of Making French Language Learning Platform via Brain-Computer Interface and Deep Learning 9th

A Novel Approach of Making French Language Learning Platform...

引用

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

作者： Aoyon, Rifat Sarker Hossain, Ismail Brac Univ Dhaka Bangladesh George Mason Univ Fairfax VA 22030 USA

ISBN: (纸本)9789819732982;9789819732999

Brain-computer interface (BCI) is a fast-growing technology where brain-waves are used to control the computer. Because of its potential, researchers are doing research to apply the knowledge of the brain-computer interface (BCI) in many sectors. In this research, we have proposed an approach to utilise the brain-computer interface (BCI) to assist French language learners. Besides, the deep learning algorithm is also implemented in this research. On our platform, users will be able to learn the language by reading the articles with their French translations and a virtual conversational partner is also included here to practice French. Generally, users like to read those articles which are interesting to them. To figure out the preferred types of articles for a particular user, BCI and deep learning algorithm are applied here. Since a user will be able to learn French by reading the articles, and when a user gets his or her preferred types of articles, then this particular person will like to spend a lot of time on French language learning, which will be beneficial for a user to learn French quickly. But there are lots of vocabularies and grammatical rules available in a language, and it is so tough to adopt these rules and vocabularies without having regular communications via French. On the other hand, the possibility is too low to find a French-speaking person from a non-francophone country. For this reason, we thought of adding a virtual conversational partner to this platform to practice French and have added this feature in such a way that users will find a proper environment to keep practising the knowledge of French that they have achieved from reading articles or anywhere else. Along with this, the users will also learn new rules of French from this kind of textual conversations.

关键词： Brain-computer interface French language Virtual conversational partner Translations Deep learning

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Digital Empathy 2nd

Digital Empathy

引用

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

作者： Maslikovic, Dejan Grubisic, Durad Inst Drustvenih Nauka Kraljice Natlije 45 Beograd Serbia Evropski Ctr Mir & Razvoj Beograd Serbia

ISBN: (纸本)9783031608391;9783031608407

Robots with artificial intelligence have their place in medicine and patient care as therapists or patient assistants. This is particularly applicable to people with various types of disabilities, and the greatest application is for patients with various neurodegenerative pathologies (Parkinson's disease, Alzheimer's disease, multiple sclerosis, etc.). Also, artificial intelligence is gaining ground in gerontology and telemedicine. The paper is based on the fact that the world's population, especially in developed countries, is getting older and that in the next few decades, almost a third of the population will be over 60, which makes it a challenge to provide care and medical services for such a large population. This led to the coining of the term social and emotional robotics. This segment of robotics should be in charge of creating a therapeutic assistant or even some kind of patient supervision. So far, the greatest need has been expressed among people with disabilities-blind, visually impaired, wheelchair users, or those with neurodegenerative changes. This direction of development and use of artificial intelligence opens up the question of empathy, emotional interaction, and social intelligence, i.e., whether it is possible to develop these features of artificial intelligence, which until now were only characteristic of living beings. The paper will define certain problems with the use of artificial intelligence and interaction with people, that is, with users of services, in this case, patients. The importance of giving robots, i.e., artificial intelligence, the ability to understand emotions and interpret human behavior will be highlighted. In recent decades, in parallel with the development of robotics and artificial intelligence, neuroscience and cognitive psychology have been developed with the aim of investigating human emotions and behavior in detail. Important for science and AAI is the definition of artificial intelligence mechanisms that would allo

关键词： medicine gerontology telemedicine empathy ethics artificial intelligence inclusion

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Automatic Hemorrhage Detection in Magnetic Resonance Imaging in Cerebral Amyloid Angiopathy 1

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

作者： Jesus, Tiago Palma, Claudia Oliveira, Tiago Gil Alves, Victor Univ Minho ALGORITMI Res Ctr LASI Braga Portugal Univ Minho ICVS Life & Hlth Sci Res Inst Braga Portugal

ISBN: (数字)9783031456428

ISBN: (纸本)9783031456411;9783031456428

Cerebral hemorrhages, or intracranial hemorrhages, can be caused by the rupture of blood vessels inside the skull. One of the most common causes of brain hemorrhage is cerebral amyloid angiopathy, which can also be associated with Alzheimer's disease. However, theMagnetic Resonance Imaging (MRI) scans in which the hemorrhages can be found must be manually examined and segmented which is very challenging due to the difficult differentiation between hemorrhages and iron deposits or calcifications which makes this a tiresome process susceptible to human error. To improve and automate the detection of brain hemorrhages, deep artificial neural networks were used as they have shown good results in similar applications. The dataset used in this work contains MRI data from 65 patients, using only T2* scans. We propose a two-stage approach in which manual annotation of T2* examinations were used to train a network to identify exams that contain a specific type of hemorrhage, either micro- or macrohemorrhages. The developed approach achieved an accuracy of 0.94 and 0.9 in detecting slices containing macro and micro hemorrhage, respectively, by using a DenseNet architecture. In the second stage, the identified scans are segmented using an AttentionUnet network which achieved a Dice Score of 0.77 for macro hemorrhages and 0.66 formicrowas achieved. This solution provides good results, which proved sufficient for individual detection of hemorrhages however, it still has room for further improvement.

关键词： Macrohemorrhage Microhemorrhage Deep Learning MRI Object detection Segmentation

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A Deep Learning Approach for Sustainable Ad Hoc Vehicular Network 8th

A Deep Learning Approach for Sustainable Ad Hoc Vehicular Ne...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Thorat, Samrat Subodh Rojatkar, Dinesh Vitthalrao Deshmukh, Prashant R. Govt Coll Engn Yavatmal Elect & Telecommun Engn Yavatmal India Govt Coll Engn Amravati Elect Engn Amravati India

ISBN: (纸本)9789819713226;9789819713233

In the era of autonomous vehicles and Google cars, Vehicular Ad Hoc networks are slowly and steadily becoming a reality. V2V and V2I are two prominent and important variants of vehicular networks. RSUs are not available wherever due to any constraint like geographical terrain, so V2V is the only form available, and it should be sustainable not only for geographical constraint but also for intrusion in the network. Many AI algorithms are used for classification, but performance does not necessarily increase with an increase in data size since saturation is reached. In deep learning with an increase in data size, performance increases manifold as compared to machine learning algorithms.

关键词： 5G-VANET Deep neural network Controller area network Intrusion detection system Datasets for ad hoc vehicular system Deep belief network Long-term term short-term memory IoT-based dataset

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Robust Attitude Control of a Disturbed Multi-rotor Aircraft: Experimental Comparisons 4th

Robust Attitude Control of a Disturbed Multi-rotor Aircraft:...

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

作者： Hassani, Hamid Mansouri, Anass Ahaitouf, Ali Sidi Mohamed Ben Abdellah Univ Fac Sci Dhar El Mahraz Dept Phys LISAC Lab Fes Morocco Sidi Mohammed Ben Abdellah Univ Fac Sci & Technol SIGER Lab Fes Morocco Sidi Mohammed Ben Abdellah Univ Sch Appl Sci SIGER Lab Fes Morocco

ISBN: (纸本)9783031686528;9783031686535

In this work, a robust nonlinear attitude control is developed for a perturbed quadrotor aircraft. The proposed control scheme combines a finite-time sliding mode control with a smooth-reaching law to achieve the stability of the closed-loop system. The suggested method can provide precise tracking of the predefined trajectories while compensating for the impact of wind disturbances. Experimental comparisons with other recent controllers are conducted to highlight the outperformance of the suggested method in terms of trajectory tracking, robustness, and chattering alleviation.

关键词： Quadrotor smooth reaching law wind disturbances experimental comparisons

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Insights into Age-Related Macular Degeneration Detection: A Comprehensive Review of OCT Image Analysis 1

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4th Congress on Intelligent systems (CIS)

作者： Nejkar, Rahul Sukumar Sayyad, Shabnam Farook Savitribai Phule Pune Univ AISSMS Coll Engn Dept Comp Engn Pune 411001 Maharashtra India Sanjeevan Engn & Technol Inst Panhala 416201 Maharashtra India

ISBN: (数字)9789819990436

ISBN: (纸本)9789819990429;9789819990436

Age-related macular degeneration (AMD) and diabetic retinopathy (DR) are eye disorders that affect the macula, the center of the retina, and can harm an elderly person's vision. The severity of these conditions can require immediate eye care, and each case requires a different treatment. Optical coherence tomography (OCT) is a method for evaluating AMD diagnosis. The early treatment depends on the correct finding of wet and dry AMD. This paper deliberates state-of-the-art methods for automatic and faster classification of wet and dry AMD with deep convolutional neural networks, evaluating their performance results for AMD diagnosis and grading. The main objective of this research is to investigate and evaluate computer-aided diagnostic (CAD) methods for diagnosing and rating AMDs.

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