Human brain can perform many tasks much better than classical electronic computers, such as face recognition, reasoning based on vague information, and learning from experience, to name a few. Recently, brain-inspired algorithms have promoted in the rapid development of artificial intelligence, however, they cannot work well in classical computers. In this talk, Dr. Can Li will present his recent works on building brain-inspired computers to fit better with brain-inspired algorithms. Those computers are based on an emerging nanoelectronics device – a memristor – which can store information and compute simultaneously, similar to synapses and neurons in our brain. The built hardware can function similar to human brains, for example, it can tolerate hardware defects, make full use of the nonlinearity of devices, learn from rare samples, and so on.
TechTalk is a series of forums and dialogues given by engineering researchers of diverse academic backgrounds to share their insights on innovation-related topics.
TechTalk – Non-Fourier Phonon Heat Conduction: Ballistic, Coherent, Localized, Hydrodynamic, and Divergent Modes
Beyond the Fourier diffusion theory on heat conduction, the classical size effects—the Casimir regime—caused by phonon boundary scattering is well known and extensively studied. However, over the last three decades, new regimes beyond the Fourier and the Casimir pictures of heat conduction have been demonstrated. In this talk, I will discuss different phonon heat conduction regimes, including the Knudsen regime, the hydrodynamic regime, the quantization regime, the coherence and localization regimes, and the divergence regime. The Knudsen regime expands Casimir’s picture to many other quasi-ballistic transport geometries, and is being exploited to develop phonon mean free path spectroscopy techniques. Phonon hydrodynamic transport happens when the normal scattering dominates over the resistive scattering, which is a condition difficult to satisfy and only observed at a narrow temperature range less than 20K. However, our recent experiments have observed second sound—a consequence of phonon hydrodynamic transport—at as high at 200K, while simulations point to possibility of observing hydrodynamic heat conduction even at room temperature. Quantized phonon transport was observed at very low temperatures. Signatures of coherent heat conduction, including localization, will be discussed, together with experimental evidences. Divergent thermal conductivity, implying thermal superconductors, is predicted to be possible in low-dimensional materials, although no experiments have provided conclusive evidence. These different phonon heat conduction regimes will be summarized in a regime map, demonstrating the rich phonon transport physics rivaling that of electrons.
TechTalk – (RE)-Ba-Cu-O Single Grain Bulk Superconductors with Improved Superconducting and Mechanical Properties
Extensive research has been carried out over the last three decades, in general, and over last 10 years, in particular, to produce single-grain, high-performance RE-Ba-Cu-O [(RE)BCO bulk superconductors, where RE is a rare earth element or yttrium, for a variety of high field engineering applications. Sample assemblies of bulk (RE)BCO bulk superconductors reinforced under different configurations, remarkably, have enabled trapped fields of more than 17.5 T to be achieved, which is the current world record. More recently, hybrid (RE)BCO bulk superconductors containing Ag, composite and fibre-reinforcements are being developed specifically for both conventional, static devices and more challenging engineering applications where the presence of large electromagnetic stresses has been of concern for the operation of these ceramic-like materials. This seminar will describe the key developments in the processing and properties of high-performance, state-of-the-art (RE)BCO bulk superconductors with a view to develop practical applications over the next 5 years.
The classical subjects of solid mechanics, structural mechanics and mechanics of materials have played important roles in helping develop structural and functional materials, giving rise to recent advances in nanostructured materials, biomedical materials, mechanical metamaterials, soft actuators, flexible electronics, tunable mechanochromics, regenerative mechanomedicine, etc. While these classical subjects often focus on passive access to mechanical properties of materials in existing forms, a paradigm shift, referred to as mechanomaterials, is emerging toward proactive programming of materials’ properties and functionalities during the manufacturing process by leveraging the force–geometry–property relationships. Here, we provide a couple of examples that illustrate this emerging paradigm, which include overcoming some of the long-standing or recent challenges in the developments of fatigue-resistant metals, mechanics-guided shape morphing electronics, strong and switchable adhesives, epicardial patches for the treatment of heart attack and membrane-active nanomedicine.
TechTalk – An Innovative Way of Water Resources Management for Sustainable Development: Utilization of Atmospheric Water Resources
Due to rapid population growth and climate change, there are severe spatiotemporal variations of water resources in the globe, and our society is facing serious challenges in securing sufficient water. To tackle the water shortage, we need to find other water sources. An effective and possible way is to utilize atmospheric water resources, which are the precipitable water in the atmosphere. With relatively stable temporal and spatial distribution, this part of water resources can be exploited and utilized through artificial precipitation enhancement operations which is also known as cloud seeding. In this talk, Professor Chen will introduce the situation of atmospheric water resources and the method that implements low frequency acoustic waves to stimulate and enhance precipitation. Through indoor experimental analysis and a large number of field tests, the effect has been tested. The development and utilization of atmospheric water resources would provide an innovative measure to obtain more freshwater for a certain region. He will also discuss the atmospheric water resources in the Greater Bay Area.
Substantial material resource recovery opportunities exist in the urban environment to support more sustainable urban development. However, the ability to produce safe and quality recoverable requires in-depth environmental materials studies and state-of-the-art fabrication and characterization technologies. For example, the quantitative X-ray diffraction (QXRD) technique has accurately monitored the transfer and behavior of targeted hazardous metals when being beneficially used for ceramic products in the construction industry. The work of recovering metallic lead from waste cathode ray tube (CRT) glass serves as an excellent example to reflect how environmental materials techniques assisted the development of transforming urban electronic waste into new metal resources. Lastly, the demonstration of recovering phosphorus from wastewater streams as quality slow-releasing fertilizer for agriculture applications leads to new solutions to tackle critical resource challenges with the fast-developing urban mining concept around the world.
Machine learning and deep neural networks have revolutionized various fields, most obvious examples are computer vision and natural language processing. Apart from the surging sizes of sophisticated models, an emerging trend is to go down the opposite route of deploying lightweight models on the edge (terminal or user end) for relatively simple AI tasks. This is named edge AI which is often constrained to run under restrictive compute and storage resources. In this talk, we will explore the latest theory in neural network modeling that allows the total avoidance of AI training that used to be slow, daunting or even impossible for the edge. Specifically, we will scratch the surface of the neural tangent kernel, and try to establish (well…. qualitatively) the equivalence of data and network, such that once the data are ready, the network is instantly ready, too.
Many large earth structures (e.g. slopes, dams, and artificial islands) are made up of sand or sandy soil. The stability of these structures is a major concern of the public as well as the professional. The bitter memories of the deadly slope failures in Hong Kong in 1972 remind us of the importance of proper stability evaluation. The difficulty in predicting the mechanical behavior of sand and sandy soil mainly comes from the granular nature of these materials. A sand or sandy soil is an assembly of numerous small grains of varying size, shape and even mineral composition. It can exist over a spectrum of states that corresponds to a variety of responses, ranging from fluid-like flow to solid-like strain hardening. The groundwater brings additional difficulty and uncertainty. This talk will present some results and findings yielded from our long-term research endeavor at HKU, which is aimed to advance scientific understanding of the complex behaviors of granular earth materials and thereby provide better engineering solutions. Focus will be placed on the fascinating roles played by the small constituent particles. The significance of these findings to engineering practice will be open to discussion.
Identifying cause-effect relations is a fundamental primitive in a variety of areas of science and technology. The identification of causal relations is generally accomplished through statistical trials where alternative hypotheses about the causal relations are tested against each other. Traditionally, such trials have been based on classical statistics. But while classical statistics effectively describes the behavior of macroscopic variables, it becomes inadequate at the microscopic scale, described by quantum mechanics, where a richer spectrum of causal relations is accessible. In the past years, there has been an increasing interest in the study of causal relations among quantum variables. In this talk, Professor Giulio Chiribella will show that the counterintuitive features of quantum mechanics can be turned to our advantage, providing speed-ups in the identification of causal relations. These speed-ups have applications to the design of automated quantum machines and new quantum communication protocols.
Engineers traditionally construct networks of drains and pipes to efficiently divert rainwater away from urban areas. However, such conventional approaches do not focus on addressing environmental issues caused by urbanization, such as water quality degradation and reduced groundwater recharge. Nature-based solutions (NBS) are urban rainwater management approaches that support the natural cycle of water and utilize ecosystems’ functions. Commonly used NBS include bioretention cells, porous pavements, and river hyporheic restoration measures. NBS can simultaneously provide multiple benefits in addition to rainwater quantity and quality management, such as promoting biodiversity, increasing aesthetic values, and reducing urban heat island effects. In this TechTalk, Dr. Chui will introduce some NBS and discuss the opportunities and challenges of implementing them in Hong Kong.
This TechTalk panel discussion will first brief the participants on the basic information on the exciting National Manned Space Programme Recruitment of Payloads Specialists in HKSAR. This will be followed up by panel discussion on overseas experience of payload specialists and potential aerospace experiment ideas.
More information about the programme can be found in https://www.itib.gov.hk/en/psrecruitment/.
A rapidly aging population is one of the grand challenges facing the society. It is estimated that by 2050, the global population of people aged 65 or older will reach 1.6 billion. This is a major difficulty that many elders are experiencing severe limitations in mobility and manipulability in their daily lives, resulting in tremendous social and economic challenges. This talk will discuss a User-Centric Co-Creation (UC³) approach to develop intelligent robotic systems to assist mobility and manipulability as well as prevent falls. The UC³ methodology lays down a theoretical foundation for multi-disciplinary approach to the development of personalized wearable assistive systems. It will pave a new avenue to advance the ergonomics and gerontechnology beyond current horizons.
Autonomous excavators are an essential part of the goal of “building the robots that build the world”. One unique problem in autonomous excavation is how to deal with the granular materials like soils and sands, which is seldom studied in robotics. In this talk, Dr. Pan will present his team’s recent work about how to achieve efficient manipulation of soils by optimizing the trajectory of the excavator’s bucket, and how to enable the excavator to be aware of the objects buried in the soils by using a proximity sensing mechanism based on jamming in granular materials.
Conventional mechatronic, hydraulic and pneumatic motors and actuators are used for large-scale robots from ≥10 cm to the human size. At the other, nanometric end of the length scale, nano-robots are powered by molecular motors. However, a number of applications in compact environments require robotic devices in the size range of 10 µm to 10 mm, but these are too small to be powered by the conventional mechatronic systems, and too large for molecular motors. Such a length scale ideally suits a few types of high-performance stimuli-responsive actuating materials that are emerging out of a very active research field in the past two decades, with examples including shape-memory polymers and metals, nanoporous noble metals, reactive polymers and liquid-crystal elastomers, carbon-based materials and transitional metal oxides. In addition to high actuating power densities, some of these materials also offer built-in sensory functions such as resistivity responses to mechanical, heat and humidity changes in the environment, and even energy generation capabilities. Integration of these materials and their signal flows in compact designs thus poses a novel strategy for robotics at the micro length scale. This talk will review some recent progress in this field.
The vision of “Cyber-Physical Internet (CPI)” is to establish a new paradigm for sending and receiving manufactured goods just like sending and receiving instant messages over the internet using online chatting platforms. Four innovations are critical to achieve this ultimate vision: (1) digitization architecture for entangling the flows of information and materials into one flow of cyber-physical objects for manufacturing and logistics operations; (2) network services for configuring local aera network (LAN), wide area network (WAN) and catchment area network (CAN); (3) value mechanisms to motivate and facilitate participation and collaboration between multiple stakeholders including shippers, carriers, forwarders; and (4) decision analytics for synchronized logistics planning, scheduling and execution. These innovations are based upon some fundamental breakthroughs of CPI routers and TCP/PIP protocols that are yet to be developed.
Tech Talk – Innovation of Originality for Solving Sand Shortage Crisis around the World including Hong Kong
Sand is the most exploited raw solid material in the world and used for construction of buildings, roads, railways, bridges, tunnels and beaches. It is also used to make the glass and silicon chips. The annual consumption for use in glass, concrete and construction materials has reached 50 billion tones, which is extremely high. Consequently, according to United Nations’ reports, the world is facing a shortage crisis of sand, as one of the greatest sustainability challenges of the 21st century. Such sand shortage crisis around the world has affected the use of sand in Hong Kong since Hong Kong does not produce any sand and all the sand used in Hong Kong is imported from Mainland China. In this Teck Talk, Professor Yue will present his technological innovation of originality. His innovation can solve this global sand shortage crisis. More importantly, his innovation can provide a stable supply of quality sand for construction and industry and offer new raw material resources for developing new industry in Hong Kong. Professor Yue has discovered that the local ordinary soil in Hong Kong can be converted into the materials of sand and clay. The sand is silica sand and mainly quartz mineral. The clay is mainly kaolinite mineral. Both materials can be used as the raw solid materials in construction and other industry. Professor Yue will demonstrate that his technical innovation is simple, environmental-friendly, sustainable and cost-effective and can be applied to many places around the world for producing quality sand materials.
In the past 10+ years, laser microscopy has successfully made it permeated not only in biochemistry and cell/molecular biology research, but also in numerous preclinical and clinical applications. However, our understanding of health and disease is still very limited. This lecture will introduce the latest breakthrough in laser microscopy technologies developed at HKU that can address some of these challenges. Especially these technologies can generate unprecedented views and understanding of the living biological cells. They include: capturing high-resolution motion picture of the swift-flying brain signals in a living animal; visualizing the inner workings of biological cells and organisms in 3D without killing them; and detecting rare cancer cells in millions of blood cells. Not only can these technologies impact new biological discovery (e.g. neuroscience), but also creating many new opportunities in cost-effective clinical diagnosis, especially cancer screening.
The diamond has been well known as the gem stones in jewellery market, and the same material with various atomic defects, i.e., fluorescent impurities in diamond lattice, shows unique quantum behaviors even at ambient conditions. A diamond, not just a best friend of ladies, but also the best friend of scientists. Due to their unique quantum properties, these atomic defects has been demonstrated to achieve nanometric measurement of various physical quantities such as electromagnetic fields, temperature and etc. with unprecedented precision. Here, I will firstly review the development of diamond-based science and technology, and discuss its potential applications in diverse fields. Specifically, I will introduce the on-going research activities in my group, mainly including the high figure-of-merit diamond materials synthesis, advanced quantum diamond microscope development and diamond quantum sensing in single living cells. In addition, I will also share my journey in exploring beyond academics, e.g., we apply quantum diamond microscope for authenticity identification in local jewellery industry.
Membrane separation technology is increasingly used for water and energy related applications. Pressure-driven membrane processes, such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO), have received great attention, fueled by the increasing needs for water purification, wastewater treatment and reclamation, and seawater desalination. In parallel, many novel membranes and membrane processes are being developed. In this TechTalk, Prof. Chuyang Tang will share his personal journey in the amazing membrane world. He will highlight some of his previous and ongoing research works covering topics on water reuse, seawater desalination, resource recovery, energy production, and beyond.
Precision manipulation of various liquids is essential in many fields, including DNA analysis, proteomics, cell assay and clinical diagnosis, chemical synthesis, and drug discovery. Their divisible, sticky, and sometime infectious features impose, however, great challenges on processing them, particularly when their volume is down to nano-/subnano-liter. A blood droplet from an Ebola patient can for example infect medical workers through the skin. For diagnosis, medial workers have to crash, filter, and purify a patient’s blood sample to obtain the virus’s genetic materials. This series of operations, very often in a fluidic medium, is highly infectious. Moreover, fluids stick to surfaces, which will contaminate containers and handling tools, causing potential dangers if the medical wastes are not properly managed. In this talk, Prof. Wang shall demonstrate how a simple light or fiber touch functions as a “magic” wetting-proof hand to navigate, fuse, pinch, and cleave fluids on demand, being capable of reducing and even replacing the usage of disposable plastics in the biomedical and pharmaceutical industries.
Spare parts management is a vital supporting function in aviation Maintenance, Repair,and Overhaul (MRO). Spare parts intralogistics (SPI), the operational perspective of spare parts management, significantly affects performance of MRO activities. This study proposes Cyber-Physical Spare Parts Intralogistics System (CPSPIS) to address the synchronization problems associated with the SPI business process and SPI resources. The proposed system applies Internet-of-Things technologies and unified representations to provide resources and operations traceability and visibility. Further, CPSPIS contributes several services with self-X abilities for real-time synchronization throughout the SPI process. In addition, CPSPIS develops applications and visualization tools for real-time cooperation between execution and decision-making. Finally, this study conducts a real-life case study in one of the largest aviation MRO organizations in Hong Kong, and discusses the quantitative and qualitative improvements of CPSPIS.
In computer science, a graph is a network modeling objects and their unique interactions. The graph learning model is a specialized machine learning model that learns on graphs. Similar to traditional machine learning models, a well-performed graph learning model can capture the global data distribution with sufficient and unbiased training data. However, in a distributed subgraph system, most data owners only possess small amounts of the data (small subgraphs) in their local systems and can have unpredictable biases.
In this talk, the speaker will introduce this novel yet realistic setting – subgraph federated learning, which aims to let distributed data owners collaboratively train a powerful and generalized graph learning model without directly sharing their subgraphs. Towards this setting, two major techniques are proposed by the research team. (1) FedSage, which trains a GraphSage model based on FedAvg to integrate node features, link structures, and task labels on multiple local subgraphs; (2) FedSage+, which trains a missing neighbor generator along FedSage to deal with missing links across local subgraphs. Empirical results and theoretical analysis of proposed models respectively demonstrate the effectiveness and prove the generalization ability.
Stainless steel (SS) is one of the most extensively used materials in many public areas and hygiene facilities but has no inherent antimicrobial properties. Additionally, the SARS-CoV-2 exhibits strong stability on regular SS surfaces, with viable viruses detected even after three days. Undoubtedly, this has created a high possibility of virus transmission among people using these areas and facilities. Here, this talk presents the inactivation of pathogen microbes (especially the SARS-CoV-2) on SS surface by tuning the chemical composition and microstructure of regular SS. It is discovered that Pathogen viruses like H1N1 and SARS-CoV-2 exhibit good stability on the surface of pure Ag and Cu-contained SS of low Cu content, but are rapidly inactivated on the surface of pure Cu and Cu-contained SS of high Cu content. Significantly, the developed anti-pathogen SS with 20 wt% Cu can distinctly reduce 99.75% and 99.99% of viable SARS-CoV-2 on its surface within 3 and 6 h, respectively. Lift buttons made of the present anti-pathogen SS are produced using mature powder metallurgy technique, demonstrating its potential applications in public areas and fighting the transmission of SARS-CoV-2 and other pathogens via surface touching.
Tech Talk – dPRO: A Generic Performance Diagnosis and Optimization Toolkit for Expediting Distributed DNN Training
Distributed training using multiple devices (i.e., GPU servers) has been widely adopted for learning DNN models over large datasets. However, the performance of large-scale distributed training tends to be far from linear speed-up in practice. Given the complexity of distributed systems, it is challenging to identify the root cause(s) of inefficiency and exercise effective performance optimizations when unexpected low training speed occurs. To date, there exists no software tool which diagnoses performance issues and helps expedite distributed DNN training, while the training can be run using different machine learning frameworks. This paper proposes dPRO, a toolkit that includes: (1) an efficient profiler that collects runtime traces of distributed DNN training across multiple frameworks, especially fine-grained communication traces, and constructs global data flow graphs including detailed communication operations for accurate replay; (2) an optimizer that effectively identifies performance bottlenecks and explores optimization strategies (from computation, communication and memory aspects) for training acceleration. We implement dPRO on multiple deep learning frameworks (PyTorch, TensorFlow, MXNet) and representative communication schemes (AllReduce and Parameter Server architecture). Extensive experiments show that dPRO predicts performance of distributed training in various settings with<5% errors in most cases and finds optimization strategies with up to87.1%speed-up over the baselines.
Prefabricated construction is an emerging construction approach to produce prefabricated components in the off-site factory and transport them to the construction site for assembly, which provides enhanced quality, productivity, and sustainability. On-site assembly is an uncertain and complex stage in prefabrication projects, due to high variability of outside conditions, organization of multi-contractors, and geographic dispersion of activities. Information technology is adopted for the management of precast on-site assembly, such as Internet-of-Things (IoT), Cyber-Physical Internet (CPS), and cloud computing, which generate massive digital twins of construction resources and activities. This tech talk introduces a digital twin-enabled real-time synchronization system (DT-SYNC) with a robotic testbed demonstration for smart prefabricated on-site assembly. On-site resources are converted into Smart Construction Objects (SCOs) attaching with UWB and RFID devices to collect and integrate real-time nD data (e.g. identity, location, cost, and construction progress). Through smart mobile gateway, various on-site resources and activities could be real-timely interoperated with their corresponding digital twins. Cloud-based services are provided for real-time monitoring through high-fidelity virtual models, and robotic control with automatic navigations and alerts. Supported by the cyber-physical visibility and traceability provided by digital twins, a real-time synchronization model is designed to organize and coordinate operations and resources with simplicity and resilience, which guarantees that the appropriate resources are spatiotemporally allocated to the appropriate activities.
Balance ability is human’s basic physiological ability that ensures stable standing and walking. Falls are major threats to the health and independent living of the elderly. 10% of the falls in the elderly are associated with fractures, and some can lead to head injuries and deaths. A highly effective human balance sensor is invented, which can capture high-resolution dynamic pressure distribution under human feet. The variation of the pressure distribution can be used to solve the dynamics of human motion while standing on the balance sensor. The algorithms using artificial intelligence are developed to assess the risk of falling for elderly people to help them prevent falls. Furthermore, this sensor can be used to measure balance ability of athletes, such as weightlifting, golf and gymnastics. In medical diagnosis, balance ability tests can provide important information for diagnostics of neural disease. It can also be used to identify drunk driving.
Debate and scientific inquiries regarding airborne transmission of respiratory infections such as COVID-19 and influenza continue. Exposure was investigated under a face-to-face scenario, where people experience the highest risk of respiratory infection. The short-range airborne route was found to dominate exposure during close contact. Based on the fact that most of the outbreaks occurred in indoor environments, we built the link between long-range airborne transmission and short-range airborne route. Results suggest that effective environmental prevention strategies for respiratory infections require appropriate increases in the ventilation rate while maintaining a sufficiently low occupancy.
The application of stainless steel (SS) as an alternative construction material has been developing in the last decade. SS construction has an outstanding structural performance, excellent corrosion resistance, and long-term durability. Moreover, the SS construction has a relatively low maintenance cost with possibility of a longer occupancy period, and thus it promotes sustainability in the construction industry. In combination with the cold-forming technique during the fabrication process, SS structures offer additional strength and a faster construction speed. However, the available international design standards for cold-formed stainless steel (CFSS) structures have not been developed thoroughly, specifically on the strength prediction of a member under concentrated bearing loads, which causes a web crippling. Therefore, a series of laboratory testing and computational simulations were conducted in this research to evaluate the existing design standards. The reliability analysis shows that the available strength predictions in the design standards are not safely used even though they are conservative. This research proposes new strength predictions that are safe and conservative, and it can be used for an improvement of the design standards.
Diamond, the most famed of all gemstones, is unique in many ways. However, beyond the sparkle, diamonds have many unique properties for copious applications. In particular, nanoscale diamond particles, generally known as nanodiamonds (NDs), have several outstanding material qualities, offering a wide range of potential for basic science and industrial applications. The practical applications of the quantum NDs are highly dependent on obtaining a well-defined surface through cleaning. Here, this talk will first present a simple, reliable, and reproducible purification method, namely, the salt-assisted air oxidation treatment, which enables scale-up manufacturing of clean NDs. At the same time, it is discovered that NDs could work as an effective agent against oral infections. These findings will significantly enhance the scope of these little gemstones in diverse scientific and industrial fields, particularly in demanding areas such as biomedical and quantum sensing.