We provide an example from our integrated math and science curriculum where students explore the ... more We provide an example from our integrated math and science curriculum where students explore the mathematical relationships underlying various science phenomena. We present the tasks we designed for exploring the covariation relationships that underlie the concept of gravity and discuss the generalizations students made as they interacted with those tasks.
2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
Bandwidth reservation was initially designed to provide QoS for real-time multimedia applications... more Bandwidth reservation was initially designed to provide QoS for real-time multimedia applications, and has been widely used since because of its proved high efficiency and effectiveness. It was recently started being used for big data transfers in high-performance networks from the data generation center to remotely located collaborating sites for data storage, mining and analysis. Most existing work on big data transfer using bandwidth reservation service focuses on addressing various data transfer problems on one or two network paths. In this paper, we study three important problems regarding data transfers using bandwidth reservation through multiple (node-and edge-)disjoint paths in dynamic high-performance networks: (i) achieve the earliest completion time for a given data transfer request through multiple variable disjoint paths, (ii) achieve the earliest completion time for a given data transfer request through multiple fixed disjoint paths with fixed bandwidths, and (iii) achieve the minimum number of fixed disjoint paths with fixed bandwidths to finish the given data transfer by its deadline. We prove all of these problems to be NP-complete and then propose one heuristic algorithm for each. We compare the heuristic algorithms with existing scheduling algorithms, and conduct extensive simulations. The simulation results show that our proposed heuristic algorithms have much better overall scheduling performance.
2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)
In this paper, we consider the server allocation problem for edge computing system deployment whe... more In this paper, we consider the server allocation problem for edge computing system deployment where each edge cloud is modeled as an M/M/c queue. Our goal is to minimize the overall average system response time of application requests generated by all mobile devices/users. We consider two approaches for edge cloud deployment: the flat deployment, where all edge clouds are co-located with the base stations, and the hierarchical deployment, where edge clouds can be co-located with other system components besides the base stations. In flat deployment, we demonstrate that the allocation of edge cloud servers should be balanced across all the base stations, if the application request arrival rates at the base stations are equal to each other; if the application request arrival rates are not the same, we propose a Largest Weighted Reduction Time First (LWRTF) algorithm to assign servers to edge clouds. Numerical comparisons of the proposed algorithm against several other reasonably designed heuristics verify that algorithm LWRTF has very good performances in terms of minimizing the average system response time. We also conduct preliminary study on hierarchical deployment for edge computing and show that the hierarchical deployment approach has great potentials in minimizing the overall average system response time.
We designed an instructional module that seamlessly integrates mathematics, environmental science... more We designed an instructional module that seamlessly integrates mathematics, environmental science, and technology to help students think critically about climate change. The results from a design experiment in a sixth-grade classroom show that our tasks not only enhanced students’ covariational reasoning in mathematics but also helped students identify the different traits of climate change they encounter every day in the news media.
The digital technology plays a vital role for improving student learning and engagement. This is ... more The digital technology plays a vital role for improving student learning and engagement. This is especially true in STEM education where teaching scientific concepts for K-12 education requires engaging platform to encourage inquiry-based learning, and it has been shown that the use of computer simulations can increase student achievement and their interest in STEM. In this paper, we present an interactive cloud-based web system that enables teachers in middle schools to effectively teach earth and environmental science using interactive simulations. To achieve on-demand accessibility and high reliability, our system is hosted on Amazon Elastic Compute Cloud platform that allows users, with an Internet connection and a Web browser, to access the course and do assignments. Additionally, we demonstrate teacher-role’s functionality regarding managing course content, identifying low-performing students and achieving improved student learning outcomes. With the seamless integration of interactive simulations, user-friendly interfaces and transparent functionalities, our system aims to make learning more fun and engaging. Teachers who have used our system found it to be very helpful in engaging their students.
This paper presents our recent work in progress aiming to design effective learning simulations o... more This paper presents our recent work in progress aiming to design effective learning simulations of day/night and seasons and lunar phases using web technology for K-12 Earth and Environmental science curriculum. Two interactive simulations using HTML5, JavaScript and CSS are developed with steerable parameters for students to interact and manipulate. The design and development details are discussed in this paper. We are currently in the process of designing the lesson plans with various investigations to engage students with the seasons and lunar phases concepts as well as assessments to evaluate their learning outcomes.
2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2021
Due to the rising popularity and interest in autonomous vehicles, it is beneficial to build a low... more Due to the rising popularity and interest in autonomous vehicles, it is beneficial to build a low-cost prototype autonomous vehicle for educational purposes. Thus, more students would be able to acquire hands-on experiences in designing and implementing critical smart navigational functionalities for autonomous vehicles. In this study, Proportional-Integral-Derivative (PID) control and steering control algorithms are developed to maneuver a 1/10-scale autonomous vehicle in a real-world scaled-down driving environment. An obstacle detection system is also designed. The state-of-the-art Robot Operating System (ROS) is employed in the software development and vehicle control to communicate between components. This paper, as part of a few related papers on autonomous vehicle from our research group, focuses on the control algorithms design and implementation, which incorporates continuous real-time feedback to generate a correction value to keep the vehicle on track. The algorithm combines the lane tracking, stop sign detection, and obstacle detection of the vehicle and sends data values to motors. Experimental results suggest the efficacy of our developed approaches. The future work of this study is discussed.
Diabetic retinopathy (DR) is a retinal microvascular condition that emerges in diabetic patients.... more Diabetic retinopathy (DR) is a retinal microvascular condition that emerges in diabetic patients. DR will continue to be a leading cause of blindness worldwide, with a predicted 191.0 million globally diagnosed patients in 2030. Microaneurysms, hemorrhages, exudates, and cotton wool spots are common signs of DR. However, they can be small and hard for human eyes to detect. Early detection of DR is crucial for effective clinical treatment. Existing methods to classify images require much time for feature extraction and selection, and are limited in their performance. Convolutional Neural Networks (CNNs), as an emerging deep learning (DL) method, have proven their potential in image classification tasks. In this paper, comprehensive experimental studies of implementing state-of-the-art CNNs for the detection and classification of DR are conducted in order to determine the top performing classifiers for the task. Five CNN classifiers, namely Inception-V3, VGG19, VGG16, ResNet50, and In...
Colossal amounts of data are being generated in extreme-scale e-Sciences with the advent of new c... more Colossal amounts of data are being generated in extreme-scale e-Sciences with the advent of new computation tools and experimental infrastructures. Such extremely large and complex data sets normally need to be transferred remotely for data storage and analysis. Reserving bandwidth as needed along selected paths in high-performance networks (HPNs) has proved to be an effective way to satisfy the high-demanding requirements of such data transfer. The most common data transfer requirement from users is the data transfer deadline. However, users oftentimes want to achieve other data transfer performance parameters, such as the earliest completion time (ECT) and the shortest duration (SD). For the bandwidth reservation service provider, all bandwidth reservation requests (BRRs) in one batch should be scheduled for high scheduling efficiency and system throughput. In this paper, we study the problem of scheduling all BRRs in one batch while achieving their best average transfer performan...
Abstract We explored the impact of a daytrip for children aged 10-13 (n = 40) to assess perceptio... more Abstract We explored the impact of a daytrip for children aged 10-13 (n = 40) to assess perception of nature. Those who perceived risk in nature were 11.25 times more likely to indicate disinterest in spending time outdoors. Those interested in spending time outdoors were 6.9 times more likely to think people should care more about the environment. Experiences before the daytrip and demographics were explored further; composters were less fearful than their counterparts (p = 0.009), as were older children (p = 0.049). These findings suggest introducing tactile experiences and earlier interventions may support children’s comfort in nature and environmental stewardship.
With the increasing employment of robots in multiple areas such as smart manufacturing and intell... more With the increasing employment of robots in multiple areas such as smart manufacturing and intelligent transportation, both undergraduate and graduate students from computing related majors (e.g., computer science and information technology) demonstrated strong interests in learning robotics technology to broaden their career opportunities. However, instilling computing students with robotics knowledge remains a challenge since most of them have limited pre-training in engineering subjects such as electronics and mechatronics. Therefore, robotics education for computing students demands an immersive real-world learning environment by considering both theories and intensive hands-on projects. Different from traditional textbook-directed robotics learning, in this study, a situated learning-based robotics education pedagogy is proposed for computing students to equip them with robotics expertise and foster their problem-solving skills in real-world human–robot interaction contexts. To...
Green Services Engineering, Optimization, and Modeling in the Technological Age
Due to the increasing deployment of data centers around the globe escalated by the higher electri... more Due to the increasing deployment of data centers around the globe escalated by the higher electricity price, the energy cost on running the computing, communication and cooling together with the amount of CO2 emissions have skyrocketed. In order to maintain sustainable Cloud computing facing with ever-increasing problem complexity and big data size in the next decades, this chapter presents vision and challenges for energy-aware management of Cloud computing environments. We design and develop energy-aware scientific workflow scheduling algorithm to minimize energy consumption and CO2 emission while still satisfying certain Quality of Service (QoS). Furthermore, we also apply Dynamic Voltage and Frequency Scaling (DVFS) and DNS scheme to further reduce energy consumption within acceptable performance bounds. The effectiveness of our algorithm is evaluated under various performance metrics and experimental scenarios using software adapted from open source CloudSim simulator.
We provide an example from our integrated math and science curriculum where students explore the ... more We provide an example from our integrated math and science curriculum where students explore the mathematical relationships underlying various science phenomena. We present the tasks we designed for exploring the covariation relationships that underlie the concept of gravity and discuss the generalizations students made as they interacted with those tasks.
We provide an example from our integrated math and science curriculum where students explore the ... more We provide an example from our integrated math and science curriculum where students explore the mathematical relationships underlying various science phenomena. We present the tasks we designed for exploring the covariation relationships that underlie the concept of gravity and discuss the generalizations students made as they interacted with those tasks.
2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
Bandwidth reservation was initially designed to provide QoS for real-time multimedia applications... more Bandwidth reservation was initially designed to provide QoS for real-time multimedia applications, and has been widely used since because of its proved high efficiency and effectiveness. It was recently started being used for big data transfers in high-performance networks from the data generation center to remotely located collaborating sites for data storage, mining and analysis. Most existing work on big data transfer using bandwidth reservation service focuses on addressing various data transfer problems on one or two network paths. In this paper, we study three important problems regarding data transfers using bandwidth reservation through multiple (node-and edge-)disjoint paths in dynamic high-performance networks: (i) achieve the earliest completion time for a given data transfer request through multiple variable disjoint paths, (ii) achieve the earliest completion time for a given data transfer request through multiple fixed disjoint paths with fixed bandwidths, and (iii) achieve the minimum number of fixed disjoint paths with fixed bandwidths to finish the given data transfer by its deadline. We prove all of these problems to be NP-complete and then propose one heuristic algorithm for each. We compare the heuristic algorithms with existing scheduling algorithms, and conduct extensive simulations. The simulation results show that our proposed heuristic algorithms have much better overall scheduling performance.
2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)
In this paper, we consider the server allocation problem for edge computing system deployment whe... more In this paper, we consider the server allocation problem for edge computing system deployment where each edge cloud is modeled as an M/M/c queue. Our goal is to minimize the overall average system response time of application requests generated by all mobile devices/users. We consider two approaches for edge cloud deployment: the flat deployment, where all edge clouds are co-located with the base stations, and the hierarchical deployment, where edge clouds can be co-located with other system components besides the base stations. In flat deployment, we demonstrate that the allocation of edge cloud servers should be balanced across all the base stations, if the application request arrival rates at the base stations are equal to each other; if the application request arrival rates are not the same, we propose a Largest Weighted Reduction Time First (LWRTF) algorithm to assign servers to edge clouds. Numerical comparisons of the proposed algorithm against several other reasonably designed heuristics verify that algorithm LWRTF has very good performances in terms of minimizing the average system response time. We also conduct preliminary study on hierarchical deployment for edge computing and show that the hierarchical deployment approach has great potentials in minimizing the overall average system response time.
We designed an instructional module that seamlessly integrates mathematics, environmental science... more We designed an instructional module that seamlessly integrates mathematics, environmental science, and technology to help students think critically about climate change. The results from a design experiment in a sixth-grade classroom show that our tasks not only enhanced students’ covariational reasoning in mathematics but also helped students identify the different traits of climate change they encounter every day in the news media.
The digital technology plays a vital role for improving student learning and engagement. This is ... more The digital technology plays a vital role for improving student learning and engagement. This is especially true in STEM education where teaching scientific concepts for K-12 education requires engaging platform to encourage inquiry-based learning, and it has been shown that the use of computer simulations can increase student achievement and their interest in STEM. In this paper, we present an interactive cloud-based web system that enables teachers in middle schools to effectively teach earth and environmental science using interactive simulations. To achieve on-demand accessibility and high reliability, our system is hosted on Amazon Elastic Compute Cloud platform that allows users, with an Internet connection and a Web browser, to access the course and do assignments. Additionally, we demonstrate teacher-role’s functionality regarding managing course content, identifying low-performing students and achieving improved student learning outcomes. With the seamless integration of interactive simulations, user-friendly interfaces and transparent functionalities, our system aims to make learning more fun and engaging. Teachers who have used our system found it to be very helpful in engaging their students.
This paper presents our recent work in progress aiming to design effective learning simulations o... more This paper presents our recent work in progress aiming to design effective learning simulations of day/night and seasons and lunar phases using web technology for K-12 Earth and Environmental science curriculum. Two interactive simulations using HTML5, JavaScript and CSS are developed with steerable parameters for students to interact and manipulate. The design and development details are discussed in this paper. We are currently in the process of designing the lesson plans with various investigations to engage students with the seasons and lunar phases concepts as well as assessments to evaluate their learning outcomes.
2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2021
Due to the rising popularity and interest in autonomous vehicles, it is beneficial to build a low... more Due to the rising popularity and interest in autonomous vehicles, it is beneficial to build a low-cost prototype autonomous vehicle for educational purposes. Thus, more students would be able to acquire hands-on experiences in designing and implementing critical smart navigational functionalities for autonomous vehicles. In this study, Proportional-Integral-Derivative (PID) control and steering control algorithms are developed to maneuver a 1/10-scale autonomous vehicle in a real-world scaled-down driving environment. An obstacle detection system is also designed. The state-of-the-art Robot Operating System (ROS) is employed in the software development and vehicle control to communicate between components. This paper, as part of a few related papers on autonomous vehicle from our research group, focuses on the control algorithms design and implementation, which incorporates continuous real-time feedback to generate a correction value to keep the vehicle on track. The algorithm combines the lane tracking, stop sign detection, and obstacle detection of the vehicle and sends data values to motors. Experimental results suggest the efficacy of our developed approaches. The future work of this study is discussed.
Diabetic retinopathy (DR) is a retinal microvascular condition that emerges in diabetic patients.... more Diabetic retinopathy (DR) is a retinal microvascular condition that emerges in diabetic patients. DR will continue to be a leading cause of blindness worldwide, with a predicted 191.0 million globally diagnosed patients in 2030. Microaneurysms, hemorrhages, exudates, and cotton wool spots are common signs of DR. However, they can be small and hard for human eyes to detect. Early detection of DR is crucial for effective clinical treatment. Existing methods to classify images require much time for feature extraction and selection, and are limited in their performance. Convolutional Neural Networks (CNNs), as an emerging deep learning (DL) method, have proven their potential in image classification tasks. In this paper, comprehensive experimental studies of implementing state-of-the-art CNNs for the detection and classification of DR are conducted in order to determine the top performing classifiers for the task. Five CNN classifiers, namely Inception-V3, VGG19, VGG16, ResNet50, and In...
Colossal amounts of data are being generated in extreme-scale e-Sciences with the advent of new c... more Colossal amounts of data are being generated in extreme-scale e-Sciences with the advent of new computation tools and experimental infrastructures. Such extremely large and complex data sets normally need to be transferred remotely for data storage and analysis. Reserving bandwidth as needed along selected paths in high-performance networks (HPNs) has proved to be an effective way to satisfy the high-demanding requirements of such data transfer. The most common data transfer requirement from users is the data transfer deadline. However, users oftentimes want to achieve other data transfer performance parameters, such as the earliest completion time (ECT) and the shortest duration (SD). For the bandwidth reservation service provider, all bandwidth reservation requests (BRRs) in one batch should be scheduled for high scheduling efficiency and system throughput. In this paper, we study the problem of scheduling all BRRs in one batch while achieving their best average transfer performan...
Abstract We explored the impact of a daytrip for children aged 10-13 (n = 40) to assess perceptio... more Abstract We explored the impact of a daytrip for children aged 10-13 (n = 40) to assess perception of nature. Those who perceived risk in nature were 11.25 times more likely to indicate disinterest in spending time outdoors. Those interested in spending time outdoors were 6.9 times more likely to think people should care more about the environment. Experiences before the daytrip and demographics were explored further; composters were less fearful than their counterparts (p = 0.009), as were older children (p = 0.049). These findings suggest introducing tactile experiences and earlier interventions may support children’s comfort in nature and environmental stewardship.
With the increasing employment of robots in multiple areas such as smart manufacturing and intell... more With the increasing employment of robots in multiple areas such as smart manufacturing and intelligent transportation, both undergraduate and graduate students from computing related majors (e.g., computer science and information technology) demonstrated strong interests in learning robotics technology to broaden their career opportunities. However, instilling computing students with robotics knowledge remains a challenge since most of them have limited pre-training in engineering subjects such as electronics and mechatronics. Therefore, robotics education for computing students demands an immersive real-world learning environment by considering both theories and intensive hands-on projects. Different from traditional textbook-directed robotics learning, in this study, a situated learning-based robotics education pedagogy is proposed for computing students to equip them with robotics expertise and foster their problem-solving skills in real-world human–robot interaction contexts. To...
Green Services Engineering, Optimization, and Modeling in the Technological Age
Due to the increasing deployment of data centers around the globe escalated by the higher electri... more Due to the increasing deployment of data centers around the globe escalated by the higher electricity price, the energy cost on running the computing, communication and cooling together with the amount of CO2 emissions have skyrocketed. In order to maintain sustainable Cloud computing facing with ever-increasing problem complexity and big data size in the next decades, this chapter presents vision and challenges for energy-aware management of Cloud computing environments. We design and develop energy-aware scientific workflow scheduling algorithm to minimize energy consumption and CO2 emission while still satisfying certain Quality of Service (QoS). Furthermore, we also apply Dynamic Voltage and Frequency Scaling (DVFS) and DNS scheme to further reduce energy consumption within acceptable performance bounds. The effectiveness of our algorithm is evaluated under various performance metrics and experimental scenarios using software adapted from open source CloudSim simulator.
We provide an example from our integrated math and science curriculum where students explore the ... more We provide an example from our integrated math and science curriculum where students explore the mathematical relationships underlying various science phenomena. We present the tasks we designed for exploring the covariation relationships that underlie the concept of gravity and discuss the generalizations students made as they interacted with those tasks.
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Papers by Michelle Zhu