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AI-Aided Game: Enhancing the Defense Performance of Scale-Free Network via Deep Reinforcement learning 22

AI-Aided Game: Enhancing the Defense Performance of Scale-Fr...

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22nd IEEE international conference on High Performance Computing and Communications, 18th IEEE international conference on Smart City and 6th IEEE international conference on data Science and Systems, HPCC-SmartCity-DSS 2020

作者： Lu, Ziyue Tang, Guoming Chen, Baochao Ren, Bangbang Chen, Sheng Guo, Deke Tianjin University College of Intelligence and Computing Tianjin300350 China Peng Cheng Laboratory Shenzhen518055 China National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory Changsha410073 China

ISBN: (纸本)9781728176499

Scale-free network, as a type of complex network, is prone to various target attacks. Some researches characterize the attack and defense problem of complex network as a game problem, and design the optimal defense strategy from the perspective of achieving the game equilibrium. However, such a game problem in the scale-free network space is very difficult to solve because the strategy space is too large. An effective way to achieve the equilibrium is to train a growing population of player strategies and use heuristic methods to guide the population evolution. The deep reinforcement learning (DRL) has been used to guide the population evolution due to its strong ability to explore new strategies. Inspired by this fact, in this paper we apply an AI-Aided game framework, Policy Space Response Oracle (PSRO), to solve the above game problem. We first abstract the scale-free network as a game environment and design a set of game rules. The confrontation game occurs between two agents acting as the attacker and the defender in the network, respectively. We then use the convolutional neural network (CNN) to evaluate values of actions in deep Q-network (DQN) and extract game states into tensor forms as CNN's inputs. To tackle the targeted attacks against the scale-free networks, we carefully design a specific action value for the defender combining the node weight and network connectivity parameters of a node in CNN. The simulation results show that the defender agent using CNN as strategies can delay the attacker's intrusions under equilibrium, and achieve a balance between protecting high-weight nodes and keeping the network connectivity. © 2020 IEEE.

关键词： Network security

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Communication Support Utilizing AAC for Verbally Challenged Children in Developing Countries During COVID-19 Pandemic 22nd

Communication Support Utilizing AAC for Verbally Challenged ...

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22nd international conference on Human-Computer Interaction, HCI international 2020

作者： Farzana, Walia Sarker, Farhana Vaidyanathan, Ravi Chau, Tom Mamun, Khondaker A. Advanced Intelligent Multidisciplinary Systems Lab Department of Computer Science and Engineering United International University Dhaka Bangladesh Department of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka Bangladesh Department of Mechanical Engineering Imperial College London London United Kingdom Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto Canada

ISBN: (纸本)9783030607029

Functional communication is indispensable for child development at all times but during this COVID-19, non-verbal children become more anxious about social distancing and self-quarantine due to sudden aberration on daily designed practices and professional support. These verbally challenged children require the support of Augmentative and Alternative Communication (AAC) for intercommunication. Therefore, during COVID-19, assistance must be provided remotely to these users by a AAC team involving caregivers, teachers, Speech Language Therapist (SLT) to ensure collaborative learning and development of non-verbal child communication skills. However, most of the advanced AAC, such as Speech Generating Devices (SGD), Picture Exchange Communication System (PECS) based mobile applications (Android & iOS) are designed considering the scenario of developed countries and less accessible in developing countries. Therefore, in this study, we are focusing on representing feasible short term strategies, prospective challenges and as long term strategy, a cloud based framework entitled as "Bolte Chai+", which is an intelligent integrated collaborative learning platform for non-verbal children, parents, caregivers, teachers and SLT. The intelligent analytics within the platform monitors child overall progress by tracking child activity in mobile application and conversely support parents and AAC team to concentrate on individual child ubiquitous abilities. We believe, the proposed framework and strategies will empower non-verbal children and assist researchers, policy makers to acknowledge a definitive solution to implement AAC as communication support in developing countries during COVID-19 pandemic. © 2020, Springer Nature Switzerland AG.

关键词： intelligent systems

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Third Eye: Assistance for Reading Disability 2nd

Third Eye: Assistance for Reading Disability

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2nd international conference on Soft Computing and Signal Processing, ICSCSP 2019

作者： Navya, Y. SriDevi, S. Akhila, P. Amudha, J. Jyotsna, C. Department of Computer Science & Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9789811524745

Around 5–20% of students across the world have learning difficulties which occur due to several reasons. Dyslexia is the most common form of learning difficulty associated with difficulties in reading, writing, spelling and organization. Researchers show that the eye movements can reflect the difficulties faced by an individual while reading. Third eye uses eye gaze information from the eye tracker and analyzes it to extract features which can identify the reading skills of the subject and further broadly categorizes them based on their reading skills. An automated report is generated which depicts the areas of difficulty faced by the reader through various visualization techniques. A correlation study done between normal readers and dyslexic readers showcases significant differences in their eye movements in terms of fixation duration, fixation count and regressions. This platform can be used to identify the reading skills of the student which improves their self-confidence and motivates them toward further augmentation. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Eye movements

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Information Security Analysis as data Fusion 22

Information Security Analysis as Data Fusion

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22nd international conference on Information Fusion (FUSION)

作者： De Shon, Markus Netflix Inc Los Gatos CA 95032 USA

ISBN: (纸本)9780996452786

engineering of detection systems for Information Security (InfoSec) is still an emerging field, when compared to Multisensor data Fusion (MSDF). The two fields share important features: diverse data sources, a need for automated assistance in timely situation assessment, and an operational dimension with real consequences. There is an important difference: InfoSec operates mostly in an information space, so much of the MSDF literature on low-level data fusion is not transferable to the InfoSec domain. Application of advanced analytic approaches such as Machine learning to InfoSec problems in intrusion detection has been uneven at best, with many projects failing to yield clean signals, and deep and widespread (and generally justified) skepticism among subject matter experts. [1] [2] It is vital to construct a useful model of what Security Analysis is, if we hope to automate the process, or even augment human effort with better automated support. The conceptual frameworks in use in InfoSec today focus on the operational dimension without providing a clear roadmap for building automation. In this paper, we present a framework for automation of security analysis based on the Dasarathy model of data Fusion, as extended by Steinberg and Bowman [3] (DSB). Adapting the DSB framework to Information Security contextualizes much of the existing work in security automation, exposes its limitations and gaps, and provides a roadmap to closing those gaps. It is the goal of this work to guide data Scientists and Engineers in how to develop semantic and contextual information in an automated data fusion system, to enable effective application of machine learning approaches to problems in detection & response.

关键词： Information security Intrusion detection Big data applications

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Deep learning based multiple energy harvesting users cooperative task execution 22

Deep learning based multiple energy harvesting users coopera...

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作者： Huang, Binbin Yu, Dongjin Pan, Linxuan Li, Zhongjin Hu, Haiyang Chang, Victor Hangzhou Dianzi University School of Computer Hangzhou China Software Institute Nanjing University Nanjing China Teesside University School of Computer Engineering and Digital Technologies Middlesbrough United Kingdom

ISBN: (纸本)9781728176499

Device to device (D2D) networks coupling energy harvesting technology is a promising paradigm to enable sustainable computing for mobile devices. In energy harvesting enabled D2D networks, it is a big challenge to cooperate to execute various advanced applications by multiple energy harvesting users in a dynamically changing environment, including the available battery energy of mobile devices, the channel gain between mobile devices and the power beacon, and the number of arrival tasks. To address these challenges, we investigate multi-user cooperative task execution problem in energy harvesting enabled D2D networks with the aim to minimize the long-Term cost (the weighted sum of the average latency of tasks processing, the number of dropped tasks and the battery energy penalty) for cooperative task execution. We formulate the multi-user cooperative task execution problem as a partial observable markov decision (POMDP). To solve this kind of stochastic optimization problem, we adopt a multi-Agent deterministic policy gradient (MADDPG) algorithm. To demonstrate the effectiveness of the MADDPG algorithm, we firstly do experiment to analyze this algorithm ' s convergence. Then, we compare the MADDPG algorithm with Local and ECLB two baseline algorithms in terms of the total reward, the total average latency of tasks processing, the total number of dropped tasks and the total battery energy penalty. The results show that the MADDPG algorithm can converge to an optimal policy and outperforms two baseline algorithms in these performance metrics. © 2020 IEEE.

关键词： Energy harvesting

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Meta-Modelling Meta-learning 22

Meta-Modelling Meta-Learning

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22nd ACM/IEEE international conference on Model Driven engineering Languages and Systems (MODELS)

作者： Hartmann, Thomas Moawad, Assaad Schockaert, Cedric Fouquet, Francois Le Traon, Yves DataThings Luxembourg Luxembourg Univ Luxembourg Luxembourg Luxembourg Paul Wurth Luxembourg Luxembourg

ISBN: (纸本)9781728125350

Although artificial intelligence and machine learning are currently extremely fashionable, applying machine learning on real-life problems remains very challenging. data scientists need to evaluate various learning algorithms and tune their numerous parameters, based on their assumptions and experience, against concrete problems and training data sets. This is a long, tedious, and resource expensive task. Meta-learning is a recent technique to overcome, i.e. automate this problem. It aims at using machine learning itself to automatically learn the most appropriate algorithms and parameters for a machine learning problem. As it turns out, there are many parallels between metamodelling-in the sense of model-driven engineering-and meta-learning. Both rely on abstractions, the meta data, to model a predefined class of problems and to define the variabilities of the models conforming to this definition. Both are used to define the output and input relationships and then fitting the right models to represent that behaviour. In this paper, we envision how a meta-model for meta-learning can look like. We discuss possible variabilities, for what types of learning it could be appropriate for, how concrete learning models can be generated from it, and how models can be finally selected. Last but not least, we discuss a possible integration into existing modelling tools.

关键词： meta-learning meta-modelling AutoML modelling framework

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Exploring the Impact of Social Media on Mental Health and Well-Being: A Multi-dimensional Analysis 22nd

Exploring the Impact of Social Media on Mental Health and...

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22nd international conference on Scientific Computing and Bioinformatics, CSC 2024, and 25th international conference on Computational Biology, BIOCOMP 2024, held as part of the World Congress in Computer Science, Computer engineering and Applied Computing, CSCE 2024

作者： Ali, Vasit Muntean, Cristina Hava Yaqoob, Abid School of Computing National College of Ireland Dublin Ireland School of Electronic Engineering Dublin City University Dublin Ireland

ISBN: (纸本)9783031859014

Over the past decade, the popularity and adoption of social media have increased globally, making it an inevitable part of daily communication and connection. However, the widespread use of social platforms introduces significant challenges to mental well-being. Ongoing state-of-the-art research demonstrates a robust correlation between extensive social media usage and the worsening of medical conditions such as depression and anxiety. These approaches often struggle because they fail to adequately model key health-related information and screen usage frequency in their analyses. Moreover, most of the existing methods do not fully leverage data analytics and machine learning technologies to effectively model the influence of social media algorithms on different age groups. In this paper, we employ a multi-model analysis, utilizing techniques such as decision trees, random forests, support vector machines (SVMs), and convolutional neural networks (CNNs), to gain a deeper understanding of the intricate relationship between social media use and mental health. In particular, we present four case studies exploring demographic risk factors, broader health consequences and specific health behaviors, and depression predictors associated with the use of social media. These analyses provide a comprehensive view of social media’s multi-dimensional impact on mental health and offer critical understandings for designing targeted interventions and policies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： mHealth

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Computer-Based Neuropsychological Theory of Mind Assessment: A Validation Study 17th

Computer-Based Neuropsychological Theory of Mind Assessment:...

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17th international conference on engineering Psychology and Cognitive Ergonomics (EPCE) Held as Part of the 22nd international conference on Human-Computer Interaction (HCII)

作者： Galindo-Aldana, Gilberto Moran, Alberto L. Torres-Gonzalez, Cynthia Cabero, Lesdly Meza-Kubo, Victoria Autonomous Univ Baja California Mental Hlth Profess & Soc Res Grp Lab Neurosci & Cognit Mexicali Baja California Mexico Autonomous Univ Baja California Res Grp Techol Intelligent Environm Res Grp Fac Sci Ensenada Baja California Mexico CETYS Univ Mexicali Baja California Mexico

ISBN: (纸本)9783030490430;9783030490447

Theory of mind is defined as the ability to attribute mental states to oneself and others, this psychological capacity is referred like one of cornerstones of efficient social interaction. The goal of the present study was to create an adapted computer-based version of the Reading the Mind in the Eyes Test (RMET), and to measure its validity in a sample of children Mexico. Method. Instruments: Computer-Based RMET preparation. The test consisted on a 28 trial of visual stimuli based on the Baron-Cohen, et al. version [1], containing eyes section from the face of male and female. The application was developed in Java, following a modular, iterative and incremental software development process based on requirements gathering, analysis, design, construction and testing. Participants. A total of 54 participants mean age 10.78 years old (SD =.74), voluntarily accepted to respond the test. The results were divided into three sections: i) comparative findings between paper and computer-based versions for total scores, showed no significant differences;ii) KR20 showed strong internal consistency inter-item correlations;iii) general scores also showed a significant correlation between the versions. Discussion. Other studies in Latin-America, had shown internal validity of the paper-based RMET. However, this is the first to demonstrate the internal validity of a computerbased variant of this test for the adult version. Future statistical analysis should include mean difference analysis for data dispersion, and normative data for the target children population for clinical purposes validity.

关键词： Assessment Clinical-Neuropsychology Executive-Function

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Explainable Classification of EEG data for an Active Touch Task Using Shapley Values 22nd

Explainable Classification of EEG Data for an Active Touch T...

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22nd international conference on Human Computer Interaction,HCII 2020

作者： Alsuradi, Haneen Park, Wanjoo Eid, Mohamad New York University Tandon School of Engineering New YorkNY11201 United States Engineering Division New York University Abu Dhabi Saadiyat Island Abu Dhabi129188 United Arab Emirates

ISBN: (纸本)9783030601164

Machine learning has been used in the last decade to solve many problems in the haptics field. In particular, EEG data that is recorded during haptic interactions was used to train machine learning (ML) models to answer questions that are of interest to the neurohaptics community. However, the behavior of machine learning models in taking out their decisions is treated as black box hindering the interpretability of these decisions. In this paper, we used Shapley values, a concept from game theory, to explain the behavior of a tree-based classifier model in classifying electroencephalography data that was collected during an interaction with a surface haptic device under two conditions: with and without tactile feedback. We trained a tree-based ML model to classify data based on the presence or absence of tactile feedback. Using Shapley values, we identified the features (across and within channels) that contribute the most to the classification decision. Results showed channel AF3 and neural activity after 700 ms from the onset contributed the most in recognizing tactile feedback in the interaction. This study demonstrates the use of explainable machine learning in the field of Neurohaptics. © 2020, Springer Nature Switzerland AG.

关键词： Electroencephalography

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A Sociable Robotic Platform to Make Career Advices for Undergraduates 22nd

A Sociable Robotic Platform to Make Career Advices for Under...

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22nd international conference on Human Computer Interaction,HCII 2020

作者： Mithsara, W. K. Malithi Manawadu, Udaka A. De Silva, P. Ravindra S. Robotics and Intelligent Systems Laboratory Department of Computer Science University of Sri Jayewardenepura Nugegoda Sri Lanka Robot Engineering Laboratory Graduate School of Computer Science and Engineering University of Aizu Aizuwakamatsu Japan

ISBN: (纸本)9783030601164

Most of the undergraduates couldn’t figure out a proper direction for their future careers since advising depends on the person and students show aversion in revealing their information to other humans. This research focused on creating a social robotic platform to interact with undergraduates in the field of computer science to realize possible career paths, as recent researches show social companion robots tend to form a stronger bond, which helps the addressee to share their information easily. The robot was created as a tabletop robot employing minimalistic design with a friendly view attached with speech synthesis for communicating purposes. data was collected from 202 persons, who followed a degree in computer science. data contains their experience, qualifications, and skills. Thereafter an artificial neural network was created using supervised learning to predict the career path with 95% performance accuracy. The experiment was performed by engaging 15 students from the final year who are a doing degree in computer science and they were asked to provide feedback on the interactions with the robot. The gathered responses highlighted robot animacy, interaction, technology and usefulness. Therefore, from the results it can be concluded that a majority of the students accepted the robot, interacted without hesitation and had friendly conversations with the robot where they valued the generated output from the robot. © 2020, Springer Nature Switzerland AG.

关键词： Neural networks

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