A new and efficient intelligent collaboration scheme for fashion design

Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time–cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance

Accretion-induced Collapse of Dark Matter-admixed Rotating White Dwarfs: Dynamics and Gravitational-wave Signals

We present two-dimensional hydrodynamic simulations of the accretion-induced collapse (AIC) of rotating white dwarfs admixed with an extended component of dark matter (DM) comprising of sub-GeV degenerate fermionic DM particles. We find that the DM component would follow the collapse of the normal matter (NM) component to become a bound DM core. Thus, we demonstrate how a DM-admixed neutron star could form through DM-admixed AIC (DMAIC) for the first time, with the dynamics of DM taken into account. The gravitational-wave (GW) signature from the DMAIC shows distinctive features. In the diffusive DM limit, the DM admixture indirectly suppresses the post-bounce spectral peak of the NM GWs. In the compact DM limit, the collapse dynamics of the DM in a Milky Way event generate GWs that are strong enough to be detectable by Advanced LIGO as continuous low-frequency ($< 1000$ Hz) signals after the NM core bounce. Our study not only is the first-ever computation of GW from a collapsing DM object but also provides the key features to identify DM in AIC events through future GW detections.Comment: 14 pages, 13 figure

Drive care: System for monitoring driver’s concentration and consciousness using consumer grade electonnencephalogram (EEG) headset 護駕: 利用消費級可裝載腦波監測儀實現實時監控駕駛者專注度系統

As people increasingly drive cars for both work and personal purposes, the dangers posed by drug driving, drink driving or sleep-deprived driving are growing threats to society. Highly dangerous driving behaviour and numerous traffic accidents occur because drivers are insufficiently conscious or inadequately focused while driving... 不論是為了工作還是個人需要，不少人都愛自行駕車，但藥後駕駛、醉酒駕駛、或駕駛前睡眠不足，往往容易對巿民的安全構成威脅。司機無法保持清醒或專注地駕駛而導致高危駕駛行為或交通意外，屢見不鮮... Award: Silver奬項: 銀

Smart elderly care robot 智能長者護理機械人

...This project aims to design a companion robot to take care of elderly people’s social and mental needs. A movable robot, named the ‘Intelligent Elderly Care Robot’, is built to serve this purpose. The robot uses currently available technologies, including simultaneous localisation and mapping (SLAM), face recognition, voice dialog with machine learning AI, and an Android application for direct, easy user control... ...鑒於未來的長者服務需求殷切，這個項目旨在設計一款名為「智能長者護理機械人」的機械夥伴，以滿足長者的社交及精神需要。機械人配備多項現有科技，包括同步定位與地圖構建（SLAM）、臉部辨識、配備人工學習智能的語音對話、方便使用者直接操作的安卓應用程式等... Award: Silver奬項: 銀

Adaptive Identification of SIS Models

Effective containment of spreading processes such as epidemics requires accurate knowledge of several key parameters that govern their dynamics. In this work, we first show that the problem of identifying the underlying parameters of epidemiological spreading processes is often ill-conditioned and lacks the persistence of excitation required for the convergence of adaptive learning schemes. To tackle this challenge, we leverage a relaxed property called initial excitation combined with a recursive least squares algorithm to design an online adaptive identifier to learn the parameters of the susceptible-infected-susceptible (SIS) epidemic model from the knowledge of its states. We prove that the iterates generated by the proposed algorithm minimize an auxiliary weighted least squares cost function. We illustrate the convergence of the error of the estimated epidemic parameters via several numerical case studies and compare it with results obtained using conventional approaches

Speculating China economic growth through Hong Kong? Evidence from the stock market IPO and real estate markets

This paper argues that since China closes her asset markets, investors turn to Hong Kong instead. The initial public offerings (IPO) of Chinese firms in the Hong Kong stock market and the local housing market of Hong Kong improve the prediction of each other, as they may serve as a coordinator of herds among investors. Alternative explanations such as the “production conjecture” and “underlying factor conjecture” are found to be inconsistent with the data. Our results are also consistent with the increasing importance of Chinese tourists in the world. Directions for future research are also discussed

Availability, Affordability and Volatility: the case of Hong Kong Housing Market

Housing prices in Hong Kong have gained international attention. This study suggests that the housing supply may be insufficient. Consistent with previous studies, we confirm that merely increasing the land supply may not increase the housing supply. We also find preliminary evidence for widening income inequality, which, when combined with unavailability, can lead to unaffordability in the housing market. Given the current housing supply elasticity with respect to price, Hong Kong is not more volatile than major cities in the United States. Thus, improving housing availability and thereby increasing housing supply elasticity, could effectively decrease housing price volatility