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检索条件"任意字段=24th International Conference on Control Systems and Computer Science, CSCS 2023"

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A Measurement-Derived Functional Model for the Interaction Between Congestion control and QoE in Video Conferencing 24th

A Measurement-Derived Functional Model for the Interaction B...

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24th Annual international conference on Passive and Active Measurement (PAM)

作者： He, Jia Ammar, Mostafa Zegura, Ellen Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9783031284854;9783031284861

Video Conferencing Applications (VCAs) that support remote work and education have increased in use over the last two years, contributing to Internet bandwidth usage. VCA clients transmit video and audio to each other in peer-to-peer mode or through a bridge known as a Selective Forwarding Unit (SFU). Popular VCAs implement congestion control in the application layer over UDP and accomplish rate adjustment through video rate control, ultimately affecting end user Quality of Experience (QoE). Researchers have reported on the throughput and video metric performance of specific VCAs using structured experiments. Yet prior work rarely examines the interaction between congestion control mechanisms and rate adjustment techniques that produces the observed throughput and QoE metrics. Understanding this interaction at a functional level paves the way to explain observed performance, to pinpoint commonalities and key functional differences across VCAs, and to contemplate opportunities for innovation. To that end, we first design and conduct detailed measurements of three VCAs (WebRTC/Jitsi, Zoom, BlueJeans) to develop understanding of their congestion and video rate control mechanisms. We then use the measurement results to derive our functional models for the VCA client and SFU. Our models reveal the complexity of these systems and demonstrate how, despite some uniformity in function deployment, there is significant variability among the VCAs in the implementation of these functions.

关键词： Video conferencing

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A Blockchain based Framework for Verifying Drug Authenticity 24

A Blockchain based Framework for Verifying Drug Authenticity

引用

24th international Arab conference on Information Technology, ACIT 2023

作者： Hamid, Soomaiya Bawany, Narmeen Zakaria Fatima, Kiran Jinnah University for Women Center for Computing Research Department of Computer Science and Software Engineering Karachi Pakistan

ISBN: (纸本)9798350384307

Counterfeit drugs are fake medicines that are potentially harmful for health. Safeguarding the integrity of pharmaceutical distribution plays a crucial role in preventing the circulation of counterfeit drugs. Traditional drug supply chain systems have no effective mechanism to ensure the traceability and integrity of the drug supply chain process. Various ICT-based solutions have been adopted previously and numerous regulations were passed by drug regulatory authorities to ensure interoperable and traceable drug distribution process. However, these solutions could not guarantee a tamper-proof history of supply chain process. Blockchain technology has gained traction in many diverse fields including real-estate, identity management, digital voting, healthcare, etc. therefore, we have proposed a decentralized framework to insure the authenticity and traceability of the drugs. Moreover, this study presents an overview of how blockchain technology can be employed to counter the fake medicines circulation by embedding the traceability in drug supply chain process. Comparison of various blockchain-based solutions and open research challenges in this regard are also presented. © 2023 IEEE.

关键词： Blockchain Technology Counterfeit Drugs decentralized framework Drug Supply Chain Traceability of Drugs Traditional Pharmaceutical Supply Chain

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Tutorial: Educational Recommender systems 1

引用

24th international conference on Artificial Intelligence in Education (AIED)

作者： Zheng, Yong IIT Dept Informat Technol & Management Chicago IL 60616 USA

ISBN: (数字)9783031363368

ISBN: (纸本)9783031363351;9783031363368

Recommender systems (RecSys) have found widespread use in a variety of applications, including e-commerce platforms like *** and eBay, online streaming services such as YouTube, Netflix, and Spotify, and social media sites like Facebook and Twitter. the success of these applications in improving user experience and decision making by providing personalized recommendations highlights the effectiveness of RecSys. Over the past few decades, RecSys has also made its way into the field of education, which results in the development of educational recommender systems (EdRec). Its applications in this field include personalized learning experiences, recommending appropriate formal or informal learning materials, suggesting learning peers, and adapting learning to context-aware or mobile environments, and so forth. Recently, the development of RecSys has been advanced by a series of interesting and promising topics, such as multi-task learning, multi-objective optimization, multi-stakeholder considerations, concerns of fairness, accountability, and transparency, etc. However, this progress made in the field of recommender systems was not adequately disseminated to the education community or the development of EdRec. In this tutorial, we will introduce the background, motivations, knowledge & skills associated with the current development of EdRec, and discuss a set of emerging topics and open challenges, along with case studies in EdRec.

关键词： education recommender system educational recommender system EdRec

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Model and Computation of traffic Resilience 23

Model and Computation of traffic Resilience

引用

24th international conference on computer systems and Technologies, CompSysTech 2023

作者： Rothkrantz, Leon Faculty of Electronic Engineering Mathematics and Computer Science Delft University of Technology Netherlands and Faculty of Transportation Sciences Czech Technical University in Prague Czech Republic

ISBN: (纸本)9798400700477

At many times we observed disturbances of traffic flow on highways. this may be caused by traffic accidents, bad weather conditions, road maintenance or rush hours. the Road Traffic Management takes many rules and regulation, to make road sections more robust to disturbances and improve the recovery from disturbances in traffic flow (traffic resilience). To study the effect and impact of these rules and regulations assessment models of traffic resilience was needed. In this paper, we designed and tested such an assessment model. the model is inspired by the well-known Resilience Triangle. the assessment of traffic resilience was based on measurements of the speed of traffic flow on highways. Neural Networks were used to model and smooth recorded speed data. the Traffic Resilience model has been tested on real life data. © 2023 Owner/Author.

关键词： Roads and streets

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CAPRIO with Inclusive Pedestrian Path Recommendations 24

CAPRIO with Inclusive Pedestrian Path Recommendations

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24th IEEE international conference on Mobile Data Management, MDM 2023

作者： Nixon, Brian T. Chen, Zhiyong Konduru, Sai Liu, Yuxin Costa, Constantinos Chrysanthis, Panos K. University of Pittsburgh Dept. of Computer Science Pittsburgh United States Rinnoco Ltd Limassol3047 Cyprus

ISBN: (纸本)9798350341010

Accessibility and usability have been key concerns in the design of computer interfaces through which users interact with applications and systems. Recently, chatbots have gained popularity with service providers for improvements in this area. In this paper, we present our experience in designing and implementing CAPRIO's inclusive chatbot-based interface for pedestrian path recommendations. Our CAPRIO system provides inclusive usability by extracting user preferences in a non-intrusive dialog and using them to build a more accurate model for the user's intent. It uses the Microsoft Bot Framework (MBF) and NLP modeling to support text and voice dialog. © 2023 IEEE.

关键词： User interfaces

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RoboboITS: A Simulation-Based Tutoring System to Support AI Education through Robotics 24th

RoboboITS: A Simulation-Based Tutoring System to Support AI ...

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24th international conference on Artificial Intelligence in Education (AIED)

作者： Guerreiro-Santalla, S. Crompton, H. Bellas, F. Univ A Coruna CITIC Res Ctr La Coruna Spain Old Dominion Univ Norfolk VA USA

ISBN: (纸本)9783031363351;9783031363368

this paper presents a novel tutoring system to educate pre-university students about AI, a key issue to develop AI in Education for Sustainable Society. With the aim of following a learning-by-doing approach to AI, we decided to focus on robotics as the main application domain for the students' activities. Specifically, the tutoring system is based on the Robobo educational robot, and its simulation environment. A prototype version of the tutoring system, called RoboboITS, has been released and tested in two in-person sessions with 17 students in a secondary school at Virginia (USA), leading to and promising outcomes for future development.

关键词： AI education AI for K12 Personalized Learning Tutoring systems Learning by Doing Autonomous Robotics Robotic Simulation

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Optimizing Connection Weights in Neural Networks Using Ali Baba and the Forty thieves Algorithm 24

Optimizing Connection Weights in Neural Networks Using Ali B...

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24th international Arab conference on Information Technology, ACIT 2023

作者： Al-Hiary, Heba Braik, Malik Al-Betar, Mohammed Azmi Al-Balqa Applied University Department of Computer Information Systems Al-salt Jordan Al-Balqa Applied University Department of Computer Science Al-salt Jordan Department of Information Technology Ajman United Arab Emirates Al-Balqa Applied University Irbid Jordan

ISBN: (纸本)9798350384307

Learning neural networks (NNs) is one of the most challenging problems in machine learning and has lately drawn the attention of many academics. the nonlinear structure of NNs and the unknown optimal set of key governing parameters (biases and weights) make training NNs particularly challenging. the primary drawbacks of conventional training methods are delayed convergence and local optima stagnation. Due to this, stochastic optimization techniques are dependable substitutes for addressing these problems. this study presents a new training method on the basis of the newly announced ali Baba and the forty thieves (AFT) algorithm. It has been shown that this algorithm can tackle a variety of optimization problems and can outperform many existing algorithms. Our efforts to measure its performance were prompted by this when training NNs. the proposed AFT-based trainer was tested using a bunch of 15 datasets that vary in intricacy. A comparison of AFT-based training NNs with other meta-heuristics presented for the same purpose was conducted to explore the efficiency of this training method. In most datasets, the training method-based AFT converged faster and was more adept at avoiding local optima than other rival methods. © 2023 IEEE.

关键词： AFT algorithm Classification Multilayer perceptron Neural networks

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Brain Tumor Segmentation of MRI Images Based on K-Means and White Shark Optimizer 24

Brain Tumor Segmentation of MRI Images Based on K-Means and ...

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24th international Arab conference on Information Technology, ACIT 2023

作者： Braik, Malik Al-Hiary, Heba Al-Betar, Mohammed Azmi Al-Balqa Applied University Department of Computer Science Al-salt Jordan Al-Balqa Applied University Department of Computer Information Systems Al-salt Jordan Department of Information Technology Ajman United Arab Emirates Al-Balqa Applied University Irbid Jordan

ISBN: (纸本)9798350384307

Due to the intricacy of the process involved in segmenting and extracting the tumor regions in magnetic resonance imaging (MRI), it is quite difficult to successfully detect the diseases. Due to its critical significance in subsequent image processing phases, this creates a requirement for a suitable clustering algorithm. In this study, a clustering method is presented that may address a variety problems for MRI brain tumor segmentation. One of the most well-known conventional clustering methods that is simple to use, quick to process, and ensures convergence is k-means (KM). Its weakness, which is defined by its susceptibility to the initial center's random initialization, is present. Because of this, the KM was optimized in this study using the white shark optimizer (WSO) to address this weak side of the KM. the KM would set the starting point for WSO's final position. Evaluation results of WSO-based KM were judged on a publicly available datasets in terms of several relevant evaluation methods and contrasted with outcomes of KM, fuzzy c-means (FCM), and other meta-heuristics when practiced to cluster the same datasets. the WSO-based KM clustering approach outperformed the standard KM and other competing algorithms-based KM. © 2023 IEEE.

关键词： FCM Image segmentation K-means White shark optimizer

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Intrinsic Phase Difference between Cone and Melanopsin Signals in the Pupillary Pathway

Intrinsic Phase Difference between Cone and Melanopsin Signa...

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international conference on control systems and computer science (cscs)

作者： Sei-Ich Tsujimura Akiko Matsumoto Wakayo Yamashita Faculty of Design and Architecture Nagoya City University Nagoya Japan Department of Information Science and Biomedical Engineering Kagoshima University Kagoshima Japan

Humans have adapted to a light environment with natural light in the course of evolution. A novel light environment control system is needed to address the problems of inadequate adaptation to the modern artificial light environment. For a long time, only cone and rod cells were thought to be photoreceptors in the retina (i.e. light sensors in human), but a new photoreceptor was discovered around 2000. these photoreceptors are called melanopsin ganglion cells (ipRGCs: intrinsically photoreceptive retinal ganglion cells). However, at present, the understanding of the functions of melanopsin cells is extremely limited and little is known. For example, many people are getting more sunlight in the morning to improve their sleep quality, wearing blue light-cutting glasses or using the Night Shift function in iOS, suggesting that it is important to activate or inhibit melanopsin cells depending on the light environment, but it is necessary to understand the function of melanopsin cells in order to make appropriate decisions on when to activate or inhibit melanopsin cells. Melanopsin cells have a slower response than cones. they receive signals from classical photoreceptors, indicating that cone and melanopsin signals are integrated at the retina. In the present study, we measured the intrinsic phase difference between cone and melanopsin signals in the pupillary pathway using a silent-substitution technique. the goal of the present study was to investigate how these signals are temporally integrated. We used three different test stimuli: (i) varying melanopsin stimulation without changing L-, M-, and S-cone stimulation (melanopsin stimulus); (ii) varying L-, M-, and Scone stimulation only, without changing melanopsin stimulation (cone stimulus); and (iii) varying the radiant flux of the stimuli, without changing the spectral composition, which reduces or increases the radiant flux uniformly at all wavelengths (lightflux stimulus). Consistent with previous studies, we foun

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Detecting Bias in LLMs' Natural Language Inference Using Metamorphic Testing 24

Detecting Bias in LLMs' Natural Language Inference Using Met...

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24th IEEE international conference on Software Quality, Reliability and Security Companion, QRS-C 2024

作者： Li, Zhahao Chen, Jinfu Chen, Haibo Xu, Leyang Guo, Wuhao School of Computer Science & Communication Engineering Jiangsu University Zhenjiang212013 China Jiangsu University Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace Zhenjiang212013 China Asiainfo Security Technology Co. Ltd Nanjing210012 China

ISBN: (纸本)9798350365658

the increasing integration of Large Language Mod-els (LLMs) into pivotal decision-making contexts highlights the necessity for rigorous scrutiny to ensure fairness, especially in tasks involving Natural Language Processing (NLP). this paper introduces a novel method employing Metamorphic Testing (MT) to discern bias within the Natural Language Inference (NLI) task performed by LLMs. Our approach establishes a structured framework for generating test cases using Metamorphic Relations (MRs), incorporating nuanced demographic attributes such as sex, race, occupation, age, and socioeconomic status into textual inputs. We conduct prelimi-nary experiment with 3 common datasets, over 400k test cases in 4 state-of-art LLMs. through evaluation of model predictions across these MRs, we unveil potential biases indicative of fairness violations. Preliminary investigations conducted with prominent LLMs underscore the effectiveness of our method in illuminating disparities in model performance, thus providing valuable insights into the bias implications of LLMs in NLI tasks. Our method is intuitive and adaptable for other NLP tasks. To the best of our knowledge, this represents the first application of MT to NLI bias detection. © 2024 IEEE.

关键词： Natural language processing systems

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