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2nd International Multidisciplinary inf.rmation Technology and engineering Conference, IMITEC 2020

作者： Ezekiel Makhoere, Christopher Thabo Jokonya, Osden Gorejena, Koga Sol Plaatjie University Computer Science and Inf. Technology Department Kimberley South Africa University of Western Cape Information Systems Department Bellville Cape Town South Africa North West University Information Systems Department Mafikeng South Africa

ISBN: (纸本)9781728195209

Portable Mobile Device(PMD's) have the potential to elevate higher educational institutions(HEI), by the way in which students and lectures communicate using these devices thus presenting the students with perceptions of learning using these devices and also taking advantage of other platforms of social media for collaboration and self-directed learning. According to research studies on social media for learning, it has been found that new opportunities are created for innovative ideas and at the same time generating students of 21st Century. The emergence on the use of social platforms encourages active interaction of internet usage amongst students. However, opportunities for online networking and communities to facilitate multi-directional communication and knowledge exchange are offered by social media. Theories of social learning inf.rms the design of participatory social interaction to support learning. In addition, the collection of data for this study was intended to be done through student focus group interviews. This was however not possible due to the recent decision of changing traditional learning(face-to-face) to online learning this current academic year, although this study was intentionally done to evaluate how mobile device will benefit on-line learning. It is argued in the reviewed literature that youth of the 21st century might have a tendency to resist traditional methods of teaching and learning. The usage of social platforms like WhatsApp, Facebook, Slack and others allows for interaction and sharing of experiences and interests on the web and are valuable for collaborative learning through constant internet connectivity. The findings of this study will be used to guide lecturing staff at SPU to identify social networking resources and other emerging technologies for the delivery of learning content that are freely and instantaneously available to students. © 2020 IEEE.

关键词： Students

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DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks-a Case Study for Covid-19 Spread and Interventions

DeepABM: Scalable and Efficient Agent-Based Simulations Via ...

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2021 Winter Simulation Conference, WSC 2021

作者： Chopra, Ayush Raskar, Ramesh Subramanian, Jayakumar Krishnamurthy, Balaji Gel, Esma S. Romero-Brufau, Santiago Pasupathy, Kalyan S. Kingsley, Thomas C. Massachusetts Institute of Technology Media Lab MA02139 United States Adobe Media and Data Science Research Lab Uttar Pradesh Noida201304 India School of Comp. Inf. and Decision Systems Eng. Arizona State University AZ85281 United States Mayo Clinic Department of Healthcare Systems Engineering MN55905 United States Alix School of Science and Medicine Mayo Clinic MN55905 United States

ISBN: (纸本)9781665433112

We introduce DeepABM, a computational framework for agent-based modeling that leverages geometric message passing for simulating action and interactions over large agent populations. Using DeepABM allows scaling simulations to large agent populations in real-time and running them efficiently on GPU architectures. Using the DeepABM framework, we build DeepABM-COVID simulator to provide support for various non-pharmaceutical interventions (quarantine, exposure notification, vaccination, testing) for the COVID-19 pandemic, and can scale to populations of representative size in real-time on a GPU. DeepABM-COVID can model 200 million interactions (over 100,000 agents across 180 time-steps) in 90 seconds, and is made available online to help researchers with modeling and analysis of various interventions. We explain various components of the framework and discuss results from one research study to evaluate the impact of delaying the second dose of the COVID-19 vaccine in collaboration with clinical and public health experts. © 2021 IEEE.

关键词： COVID-19

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Interpreting Object-level Foundation Models via Visual Precision Search

arXiv

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arXiv 2024年

作者： Chen, Ruoyu Liang, Siyuan Li, Jingzhi Liu, Shiming Li, Maosen Huang, Zhen Zhang, Hua Cao, Xiaochun Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China School of Computing NUS Singapore RAMS Lab Huawei Technologies Co. Ltd. China IAS BU Huawei Technologies Co. Ltd. China College of Computer NUDT China Key Lab. of Edu. Inf. for Nationalities YNNU Ministry of Education Kunming China School of Cyber Science and Technology Sun Yat-sen University Shenzhen Campus Shenzhen518107 China

Advances in multimodal pre-training have propelled object-level foundation models, such as Grounding DINO and Florence-2, in tasks like visual grounding and object detection. However, interpreting these models’ decisions has grown increasingly challenging. Existing interpretable attribution methods for object-level task interpretation have notable limitations: (1) gradient-based methods lack precise localization due to visual-textual fusion in foundation models, and (2) perturbation-based methods produce noisy saliency maps, limiting fine-grained interpretability. To address these, we propose a Visual Precision Search method that generates accurate attribution maps with fewer regions. Our method bypasses internal model parameters to overcome attribution issues from multimodal fusion, dividing inputs into sparse sub-regions and using consistency and collaboration scores to accurately identify critical decision-making regions. We also conducted a theoretical analysis of the boundary guarantees and scope of applicability of our method. Experiments on RefCOCO, MS COCO, and LVIS show our approach enhances object-level task interpretability over SOTA for Grounding DINO and Florence-2 across various evaluation metrics, with faithfulness gains of 23.7%, 31.6%, and 20.1% on MS COCO, LVIS, and RefCOCO for Grounding DINO, and 50.7% and 66.9% on MS COCO and RefCOCO for Florence-2. Additionally, our method can interpret failures in visual grounding and object detection tasks, surpassing existing methods across multiple evaluation metrics. The code is released at https://***/RuoyuChen10/VPS. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Robustness and Diversity Seeking Data-Free Knowledge Distillation

Robustness and Diversity Seeking Data-Free Knowledge Distill...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Pengchao Han Jihong Park Shiqiang Wang Yejun Liu School of Computer Science and Engineering Northeastern University China School of Information Technology Deakin University Geelong VIC Australia IBM T. J. Watson Research Center Yorktown Heights NY USA School of Comm. & Inf. Engineering Chongqing University of Posts and Telecommunications China

Knowledge distillation (KD) has enabled remarkable progress in model compression and knowledge transfer. However, KD requires a large volume of original data or their representation statistics that are not usually available in practice. Data-free KD has recently been proposed to resolve this problem, wherein teacher and student models are fed by a synthetic sample generator trained from the teacher. Nonetheless, existing data-free KD methods rely on fine-tuning of weights to balance multiple losses, and ignore the diversity of generated samples, resulting in limited accuracy and robustness. To overcome this challenge, we propose robustness and diversity seeking data-free KD (RDSKD) in this paper. The generator loss function is crafted to produce samples with high authenticity, class diversity, and inter-sample diversity. Without real data, the objectives of seeking high sample authenticity and class diversity often conflict with each other, causing frequent loss fluctuations. We mitigate this by exponentially penalizing loss increments. With MNIST, CIFAR-10, and SVHN datasets, our experiments show that RDSKD achieves higher accuracy with more robustness over different hyperparameter settings, compared to other data-free KD methods such as DAFL, MSKD, ZSKD, and DeepInversion.

关键词： Fluctuations Conferences Training data Signal processing Robustness Generators Acoustics

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MetaMIML: Meta multi-instance multi-label learning

arXiv

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arXiv 2021年

作者： Yang, Yuanlin Yu, Guoxian Wang, Jun Liu, Lei Domeniconi, Carlotta Guo, Maozu College of Computer and Information Sciences Southwest University Chongqing China School of Software Shandong University Jinan China Joint SDU-NTU Centre for Artificial Intelligence Research Shandong University Jinan China Department of Computer Science George Mason University VA United States College of Elec. & Inf. Eng. Beijing Univ. of Civil Eng. and Arch. Beijing China

Multi-Instance Multi-Label learning (MIML) models complex objects (bags), each of which is associated with a set of interrelated labels and composed with a set of instances. Current MIML solutions still focus on a single-type of objects and assumes an IID distribution of training data. But these objects are linked with objects of other types, which also encode the semantics of target objects. In addition, they generally need abundant labeled data for training. To effectively mine interdependent MIML objects of different types, we propose a network embedding and meta learning based approach (MetaMIML). MetaMIML introduces the context learner with network embedding to capture semantic inf.rmation of objects of different types, and the task learner to extract the meta knowledge for fast adapting to new tasks. In this way, MetaMIML can naturally deal with MIML objects at data level improving, but also exploit the power of meta-learning at the model enhancing. Experiments on benchmark datasets demonstrate that MetaMIML achieves a significantly better performance than state-of-the-art algorithms. © 2021, CC BY-NC-ND.

关键词： Network embeddings

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URLLC in Large-Scale Wireless Networks With Time and Frequency Diversities

URLLC in Large-Scale Wireless Networks With Time and Frequen...

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IEEE Global Communications Conference

作者： Meifang Wu Yi Zhong Gang Wang Changyang She Xiaohu Ge Han-Chieh Chao School of Electron. Inf. & Commun. Huazhong University of Science and Technology Wuhan China School of Electrical & Inf. Engineering University of Sydney Sydney Australia School of Computer Science & Inf. Engineering National Dong Hwa University Taiwan

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Emerging wireless applications starve for the realization of the ultra-reliable and low-latency communication (URLLC). The reliability and latency requirements of URLLC for a specific single link have been explored extensively, but a comprehensive evaluation of the URLLC in a large-scale wireless network is still lacking. In this paper, by using the point process theory we evaluate the probability that the delay and reliability requirement of a typical URLLC user can be satisfied in the large-scale wireless network. This probability is also the ratio of users with satisfactory delay and reliability in the wireless network. In order to improve the performance of URLLC, we propose two retransmission policies, corresponding to time diversity and frequency diversity, in which the retransmissions are silenced randomly to reduce the interference correlation in different frames so to reduce the effect of correlations between d-ifferent retransmissions. Simulation and numerical results reveal that both of the proposed two retransmission policies improve the performance of URLLC, and the retransmission policy of frequency diversity is better than that of the time diversity.

关键词： Delays Transmitters Reliability Fading channels Interference Receivers Wireless networks

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Stabilization of THz waves using chaos supremacy

Stabilization of THz waves using chaos supremacy

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International Conference on Smart Green Technology in Electrical and inf.rmation Systems (ICSGTEIS)

作者： Fumiyoshi Kuwashima Mona Jarrahi Semih Cakmakyapan Kenji Wada Masanobu Haraguchi Yuki Kawakami Takeshi Moriyasu Osamu Morikawa Kazuyoshi Kurihara Hideaki Kitahara Takashi Furuya Makoto Nakajima Masahiko Tani Dep. of Electr. and Electron. Eng. Fukui University of Technology Fukui Japan Electrical and Computer Eng. UCLA Los Angeles CA USA Dep. of Physics and Electronics Osaka Metropolitan University Osaka Japan Industrial and Social Science Grad. Sch. of Tech. Tokushima Univ. Tokushima Japan Dep. of Elec. and Inf. Eng. Natl. Inst. of Tech. Fukui Col. Fukui Japan Faculty of Engineering University of Fukui Fukui Japan Chair of Liberal Arts Japan Coast Guard Academy Kure Japan School of Education University. of Fukui Fukui Japan FIR-UF University of Fukui Fukui Japan Inst. of Laser Engineering Osaka Univ. Osaka Japan

We apply the chaos supremacy of laser chaos system to the high stabilization of THz waves. Stability was demonstrated by down converting the optical beats between laser longitudinal modes in the THz domain to the radio frequency domain and comparing a conventional free running CW laser diode to a chaotically oscillating laser diode. Because of their exceptional stability, chaotically oscillating lasers are attractive options for optical pump sources in terahertz time-domain spectroscopy systems.

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Robustness and diversity seeking data-free knowledge distillation

arXiv

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arXiv 2020年

作者： Han, Pengchao Park, Jihong Wang, Shiqiang Liu, Yejun School of Computer Science and Engineering Northeastern University China School of Information Technology Deakin University GeelongVIC3220 Australia IBM T. J. Watson Research Center Yorktown HeightsNY United States School of Comm. & Inf. Engineering Chongqing University of Posts and Telecommunications China

关键词： Knowledge management

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Markov and Conditionally Markov Processes: From Gaussian to Elliptical 22

Markov and Conditionally Markov Processes: From Gaussian to ...

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22nd International Conference on inf.rmation Fusion, FUSION 2019

作者： Tang, Mengjiao Rong, Yao Rong Li, X.R. Center for Inf. Eng. Science Research Xi'an Jiaotong University Xi'an Shaanxi710049 China College of Mathematics Sichuan University Chengdu Sichuan610064 China University of New Orleans Department of Electrical Engineering New OrleansLA70148 United States

ISBN: (纸本)9780996452786

Conditionally Markov (CM) processes, including the reciprocal processes as an important subclass, are gaining momentum as a generalization of the Markov process based on conditioning. This paper aims to extend the concept of the Gaussian CM process and some of its key results to the elliptical case. An elliptical process describes a stochastic process having jointly elliptically contoured distributions, which is the largest class of processes ensuring linearity of conditional expectation. However, it is shown in this paper that a nonsingular elliptical process is CM if and only if it is a Gaussian CM process. Towards the goal of extension, we first define a new property of processes, called weaker Markov, by relaxing the strict independence for the Markov property to a weaker condition of semi-independence. We then combine it with conditioning and the elliptical randomness to define the conditionally weaker Markov (CWM) elliptical process. The newly defined process is much larger than the Gaussian CM process, but can be characterized by a linear model of the same form as in the Gaussian case. Moreover, it is proven that the two processes also share almost the same results in optimal filtering and smoothing. © 2019 ISIF-International Society of inf.rmation Fusion.

关键词： Markov processes

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Using the PerFECt Framework to Establish an Onlife Community for Theatre in Mathematics to Teach Principles of Computing

Using the PerFECt Framework to Establish an Onlife Community...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Nektarios Moumoutzis Dessislava Paneva-Marinova Chara Xanthaki Polyxeni Arapi Nikos Pappas Stavros Christodoulakis Institute of Mathematics & Informatics Bulgarian Academy of Sciences (IMI-BAS) Institute of Mathematics & Informatics Bulgarian Academy of Sciences (IMI-BAS) Sofia Bulgaria Computer Science Teacher in Secondary Education Chania Greece Lab. of Distr. Multimedia Inf. Systems & Applications School of Electrical and Computer Engineering Technical University of Crete (TUC/MUSIC) Chania Greece

ISBN: (数字)9781728173030

ISBN: (纸本)9781728173047

The new reality brought about by digital technologies is characterized by new qualities, new opportunities for action, new community affordances, that are captures by the term onlife. This term was initially proposed in the Onlife Manifesto and used in this paper to signify certain qualities that are important in understanding modern digital platforms and applications as well as guide the efforts for effectively extending to provide new capabilities to their users. Specific design principles are presented exemplified by the presentation of the design of a Community of Practice for teachers involved in the pilot activities of the Erasmus+ project TIM - Theatre in Mathematics that promote the adoption of Theatre in teaching Mathematics in Primary and Lower Secondary Education targeting 8-14 years old students.

关键词： Mathematics Education Electronic mail computers Software Conferences inf.rmatics

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