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9th Annual International Computing Education Research Conference, ICER 2013

作者： Kothiyal, Aditi Majumdar, Rwitajit Murthy, Sahana Iyer, Sridhar Inter-disciplinary Programme in Educational Technology IIT Bombay India Department of Computer Science and Engineering IIT Bombay India

ISBN: (纸本)9781450322430

Think-Pair-Share (TPS) is a classroom-based active learning strategy, in which students work on a problem posed by the instructor, first individually, then in pairs, and finally as a classwide discussion. TPS has been recommended for its benefits of allowing students to express their reasoning, reflect on their thinking, and obtain immediate feedback on their understanding. While TPS is intended to promote student engagement, there is a need for research based evidence on the nature of this engagement. In this study, we investigate the quantity and quality of student engagement in a large CSl class during the implementation of TPS activities. We did classroom observations of students over a period of ten weeks and thirteen TPS activities. We determined patterns of student engagement in the three phases using a real-time classroom observation protocol that we developed and validated. We found that 83% of students on average were fully or mostly engaged. Predominant behaviors displayed were writing the solution to the problem (Think), discussing with neighbor or writing (Pair), and following class discussion (Share). We triangulated results with survey data of student perceptions. We find that students report being highly engaged for 62% during Think phase and 70% during Pair phase. Copyright © 2013 ACM.

关键词： Students

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Nonlinear Model Predictive Control of a Dual-Axis Tilting Quadcopter 10

Nonlinear Model Predictive Control of a Dual-Axis Tilting Qu...

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10th IEEE International Conference on Cybernetics and Intelligent Systems and IEEE Conference on Robotics, Automation and Mechatronics, CIS-RAM 2023

作者： Chuah, Jonathan Liang, Xiaoling Ge, Shuzhi Sam National University of Singapore Engineering Science Programme Singapore117576 Singapore National University of Singapore Department of Electrical and Computer Engineering Singapore117576 Singapore

ISBN: (纸本)9798350303087

The dual-axis tilting quadcopter holds great promise for applications that demand both high performance and full actuation in a 6DOF Cartesian task space;however, control system design is complicated by its complex dynamics and over-actuation. In this paper, we propose a real-time optimization-based framework for controlling this system. Our formulation, which combines Nonlinear Model Predictive Control (NMPC) with a control allocation stage, allows the optimizer to fully exploit the rotors' tilt actuation despite their strongly nonlinear dynamics, input constraints, and actuator redundancy. Numerical simulation is provided to illustrate the performance of the proposed control algorithm. © 2023 IEEE.

关键词： Model predictive control

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Stacking Ensemble Learning Based Detection of Cross-Site Scripting Attack 6th

Stacking Ensemble Learning Based Detection of Cross-Site Scr...

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6th International Conference on Information Systems and Management science, ISMS 2023

作者： Das, Barasha Bhowmick, Sreya Aier, Liaren Emani Boruah, Arpita Nath Goswami, Mrinal Programme of Computer Science and Engineering Faculty of Engineering Assam Down Town University Sankar Madhab Path Gandhi Nagar Panikhaiti Assam Guwahati India

ISBN: (纸本)9783031707889

In accordance with Cybersecurity statistics, a total average of 2,200 cyber-attacks occur per day. Cross-site Scripting (XSS) is one of the most notable weaknesses in web security. It belongs to the injection category. For an attacker to gain access to the user's systems the user has to interact with malicious links. This usually occurs when the victim visits any link from a website that may contain XSS payload or when visiting a vulnerable website that may trick the victim into sharing cookies resulting in a compromise of the security in the web application. In this regard, we concentrated on creating an advanced technique for identifying cross-site scripting attacks using the Stacking Ensemble Learning method is proposed. The model is implemented with a combination of different classifiers, namely Random Forest, Gaussian Naïve Bayes, SVM, and KNN, where Logistic Regression is used as the meta-model. This model has achieved a remarkable 99% accuracy rate while maintaining a high level of precision and Recall. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Cyber attacks

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The Response of EEG Signal on Brain Relaxation Meditation Using Different Type of Zikr

The Response of EEG Signal on Brain Relaxation Meditation Us...

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2021 International Conference on Biomedical engineering, ICoBE 2021

作者： Razak, N.N. Abd Sidek, K.A. Alaa, K.Y.D. Nasir, N.F. Mohd Department of Electrical and Computer Engineering Kulliyyah of Engineering International Islamic University Malaysia Department of Computer Engineering College of Computer Science and Engineering University of Ha’il Saudi Arabia Biomedical Electronic Engineering Programme Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Malaysia

Depression and stress are increasingly prevalent in today’s society, owing to people's hectic, competitive, and demanding lifestyles. These illnesses had become very common, particularly among young and middle-aged people, and suicidal ideation had been identified as one of the leading causes of death by the World Health Organization (WHO). Nature sound (sound of downpours or beach) has been linked to depression and anxiety in neurology research, and it has been shown to be an alternative to alleviate anxiety. The electroencephalogram (EEG) waveform has been discovered to possess the potential in identifying information from the brain signal as well as data from the past via Bluetooth communication. The waveform use in the study are the result of a few experiments. In this study, EEG data were collected from eight subjects, four males and four females, in between the age of 20 to 30 years old and in good health, using the BrainLink device. The participants were asked to listen to two playlists of zikr, Allah, Ya Allah, and SubhanAllah, during the experiments. To smooth the signal, the Butterworth filter was used. Later, the extracted features were Alpha, Beta, and Delta waves, which were segmented based on the filtered signal. To complete the decision-making stage, the average value of amplitude differences and the p-value test were performed in the final phase. Based on the results of the experiments, it is clear that zikr is dominant in Delta wave. In terms of data hypothesis analysis, the results of both experiment were differentiated to determine which brain signal was dominant, and p-value testing was performed. Furthermore, this research is an alternative to current methods because it suggest that zikr has the tendency to alter a person's brain state to be either in a relaxed or calm mode regardless of the type of zikr recitation. As an outcome, the study recommends the relationship of the reaction of EEG signal on brain relaxation with different types of zikr

关键词： Electroencephalography

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Adaptive Spectrum Handoff Scheme in Cognitive Radio Ad-Hoc Networks

Adaptive Spectrum Handoff Scheme in Cognitive Radio Ad-Hoc N...

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2018 International Conference on Advances in Computing and Communication engineering, ICACCE 2018

作者： Shakeel, Atif Hussain, Riaz Iqbal, Adeel Latif, Irfan Malik, Shahzad A. Omoniwa, Babatunji Department of Electrical Engineering COMSATS Institute of Information Technology Islamabad Pakistan Computer Science Programme National Mathematical Centre Abuja Nigeria

ISBN: (纸本)9781538644850

Cognitive radio improves the spectrum utilization by permitting the secondary users in accessing the underutilized spectrum band of the primary network in an opportunistic manner. Spectrum handoff is considered as one of the important phases in cognitive cycle, where the secondary users have to vacate the occupied channel on the appearance of primary user for maintaining the QoS requirements of both primary and secondary communication. It also helps secondary users to find an appropriate target channel to resume its undone transmission either through switching handoff scheme or non-switching handoff process. The process of spectrum handoff becomes more critical in cognitive radio ad-hoc networks, as the coordination among the secondary users is a challenging task. This research presents an analytical model for the performance evaluation of secondary users, in terms of extended data delivery time for both switching and non-switching spectrum handoff in ad-hoc network environment. Channel rendezvous among secondary users is achieved usings of common control channel. The results achieved are based on preemptive resume priority M/M/1 queuing network, considering varying number of secondary users, their average arrival and service time. An adaptive spectrum handoff is proposed based on the primary user traffic intensity, number of SU and total number of primary channels. © 2018 IEEE.

关键词： Switching

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Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization 37

Trusted-Maximizers Entropy Search for Efficient Bayesian Opt...

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37th Conference on Uncertainty in Artificial Intelligence, UAI 2021

作者： Nguyen, Quoc Phong Wu, Zhaoxuan Low, Bryan Kian Hsiang Jaillet, Patrick Department of Computer Science National University of Singapore Singapore Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology United States Institute of Data Science National University of Singapore Singapore NUSGS Integrative Sciences and Engineering Programme National University of Singapore Singapore

Information-based Bayesian optimization (BO) algorithms have achieved state-of-the-art performance in optimizing a black-box objective function. However, they usually require several approximations or simplifying assumptions (without clearly understanding their effects on the BO performance) and/or their generalization to batch BO is computationally unwieldy, especially with an increasing batch size. To alleviate these issues, this paper presents a novel trusted-maximizers entropy search (TES) acquisition function: It measures how much an input query contributes to the information gain on the maximizer over a finite set of trusted maximizers, i.e., inputs optimizing functions that are sampled from the Gaussian process posterior belief of the objective function. Evaluating TES requires either only a stochastic approximation with sampling or a deterministic approximation with expectation propagation, both of which are investigated and empirically evaluated using synthetic benchmark objective functions and real-world optimization problems, e.g., hyperparameter tuning of a convolutional neural network and synthesizing 'physically realizable' faces to fool a black-box face recognition system. Though TES can naturally be generalized to a batch variant with either approximation, the latter is amenable to be scaled to a much larger batch size in our experiments. © 2021 37th Conference on Uncertainty in Artificial Intelligence, UAI 2021. All Rights Reserved.

关键词： Entropy

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Telematic dinner party: Designing for togetherness through play and performance 12

Telematic dinner party: Designing for togetherness through p...

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Designing Interactive Systems Conference, DIS '12

作者： Barden, Pollie Comber, Rob Green, David Jackson, Daniel Ladha, Cassim Bartindale, Tom Bryan-Kinns, Nick Stockman, Tony Olivier, Patrick Queen Mary University of London Media and Arts Technology Programme Electronic Engineering and Computer Science London United Kingdom Newcastle University Culture Lab. School of Computer Science Newcastle United Kingdom

ISBN: (纸本)9781450312103

There is an increasing desire to remain connected when physically distant and computer-mediated communication (CMC) is one means of satisfying this desire. In particular, there is a growing trend for individuals to use commercially available technology to connect with friends and family in social and leisure settings. Drawing on this trend, performative arts and existing telecommunications research, we identify the social practice of sharing a meal together as ripe for reinterpretation within CMC. We explore the opportunities to design a technology platform that supports remote guests in experiencing togetherness and playfulness within the practices of a traditional dinner party. Through both visual and aural channels as well as remote agency, the dinner guests were able to share a holistic telematic dining experience comparable to a traditional co-presence dinner. Based on the findings, we propose that one must consider the social structure and cultural background of users to inform the design of a technological intervention. © 2012 ACM.

关键词： Telematics

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Detection of Fake Reviews on Products Using Machine Learning 7th

Detection of Fake Reviews on Products Using Machine Learning

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7th International Conference on Information and Communication Technology for Competitive Strategies, ICTCS 2022

作者： Narayana Royal, M. Reddy, Rajula Pavan Kalyan Sangathya, Gokina Sri Sai Madesh Pretam, B. Kaliappan, Jayakumar Suganthan, C. School of Computer Science and Engineering Vellore Institute of Technology Vellore India Institute of Industry and International Programme Vellore Institute of Technology Vellore India

ISBN: (纸本)9789811993039

It is hard to exaggerate how crucial user reviews are in figuring out an organization’s e-commerce income. Before purchasing any goods or service, online customers rely on product and service reviews. As a result, firms must consider how reliable Internet reviews are because they might directly affect their reputation and bottom line. Because of this, some businesses pay spammers to post false reviews. These false reviews profit from consumer buying choices. As a result, during the past twelve years, there has been substantial study into techniques for spotting false reviews. However, there is still a need for a survey that can analyze and summarize the diverse techniques. In this paper, we are going to put the SVM and Naive Bayesian machine learning model system into place that can spot false reviews with an accuracy of 0.801 and 0.687. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electronic commerce

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Gestural system based on multi-functional sensors and ZigBee networks for squad communication

Gestural system based on multi-functional sensors and ZigBee...

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2011 Defense science Research Conference and Expo, DSR 2011

作者： Tongrod, Nattapong Lokavee, Shongpun Kerdcharoen, Teerakiat Watthanawisuth, Natthapol Tuantranont, Adisorn Materials Science and Engineering Programme Faculty of Science Mahidol University Bangkok 10400 Thailand Nanoelectronic and MEMS Lab National Electronic and Computer Technology Center Pathumthani 12120 Thailand

ISBN: (纸本)9781424492763

In this paper, we have developed a communication system for military based on hand gestures which will be useful for squad communication. In particular, we present an electronic soldier glove that employs wireless networks based on low-cost ZigBee technology, multi-functional sensors such as accelerometer and flex sensor based input device for collecting and classifying hand gestures. This system delivers data output through computer display. Experimental results have proved the success of the proposed hand gesture recognition system that can adapt to communicate with multimodal signals to enhance visual signal in difficult and stressful environments where visual communication may not be possible. © 2011 IEEE.

关键词： Visual communication

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Artificial intelligence for modelling infectious disease epidemics

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Nature 2025年第8051期638卷 623-635页

作者： Kraemer, Moritz U. G. Tsui, Joseph L.-H. Chang, Serina Y. Lytras, Spyros Khurana, Mark P. Vanderslott, Samantha Bajaj, Sumali Scheidwasser, Neil Curran-Sebastian, Jacob Liam Semenova, Elizaveta Zhang, Mengyan Unwin, H. Juliette T. Watson, Oliver J. Mills, Cathal Dasgupta, Abhishek Ferretti, Luca Scarpino, Samuel V. Koua, Etien Morgan, Oliver Tegally, Houriiyah Paquet, Ulrich Moutsianas, Loukas Fraser, Christophe Ferguson, Neil M. Topol, Eric J. Duchêne, David A. Stadler, Tanja Kingori, Patricia Parker, Michael J. Dominici, Francesca Shadbolt, Nigel Suchard, Marc A. Ratmann, Oliver Flaxman, Seth Holmes, Edward C. Gomez-Rodriguez, Manuel Schölkopf, Bernhard Donnelly, Christl A. Pybus, Oliver G. Cauchemez, Simon Bhatt, Samir Pandemic Sciences Institute University of Oxford Oxford United Kingdom Department of Biology University of Oxford Oxford United Kingdom Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA United States UCSF UC Berkeley Joint Program in Computational Precision Health Berkeley CA United States Division of Systems Virology Department of Microbiology and Immunology The Institute of Medical Science The University of Tokyo Tokyo Japan Section of Epidemiology Department of Public Health University of Copenhagen Copenhagen Denmark Oxford Vaccine Group University of Oxford and NIHR Oxford Biomedical Research Centre Oxford United Kingdom Department of Epidemiology and Biostatistics Imperial College London London United Kingdom Department of Computer Science University of Oxford Oxford United Kingdom School of Mathematics University of Bristol Bristol United Kingdom MRC Centre for Global Infectious Disease Analysis School of Public Health Imperial College London London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Doctoral Training Centre University of Oxford Oxford United Kingdom Institute for Experiential AI Northeastern University MA Boston Thailand Santa Fe Institute Santa Fe NM United States World Health Organization Regional Office for Africa Brazzaville Congo WHO Hub for Pandemic and Epidemic Intelligence Health Emergencies Programme World Health Organization Berlin Germany Centre for Epidemic Response and Innovation (CERI) School for Data Science and Computational Thinking Stellenbosch University Stellenbosch South Africa African Institute for Mathematical Sciences (AIMS) South Africa Muizenberg Cape Town South Africa Genomics England London United Kingdom Scripps Research La Jolla CA United States Department of Biosystems Science and Engineering ETH Zürich Basel Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland The Ethox Centre Nuffield

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI. © Springer Nature Limited 2025.

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