Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention

Deep neural networks, including recurrent networks, have been successfully applied to human activity recognition. Unfortunately, the final representation learned by recurrent networks might encode some noise (irrelevant signal components, unimportant sensor modalities, etc.). Besides, it is difficult to interpret the recurrent networks to gain insight into the models' behavior. To address these issues, we propose two attention models for human activity recognition: temporal attention and sensor attention. These two mechanisms adaptively focus on important signals and sensor modalities. To further improve the understandability and mean F1 score, we add continuity constraints, considering that continuous sensor signals are more robust than discrete ones. We evaluate the approaches on three datasets and obtain state-of-the-art results. Furthermore, qualitative analysis shows that the attention learned by the models agree well with human intuition.Comment: 8 pages. published in The International Symposium on Wearable Computers (ISWC) 201

Optical difference engine for defect inspection in highly-parallel manufacturing processes

Traditional defect inspection for highly-parallel manufacturing processes requires the processing of large measurement datasets, which is often not fast enough for in-situ inspection of large areas with high resolution. This study develops an all-optical difference engine for fast defect detection in highly-parallel manufacturing processes, where the detection of defects (differences from nominal) is performed optically and in real-time. Identification of defects is achieved through an optical Fourier transform and spatial filtering, detecting differences between two real objects by nulling information that is repeated in each object. The developed prototype device is demonstrated using geometric patterns of similar scale to components in printed electronic circuit

Occurrence and Control of Soybean Aphid, Aphis glycines Matsumura

The soybean aphid, Aphis glycines Matsumura, is one of the most important pests of soybean. The A. glycines outbreak in 1998 followed another aphid outbreak after 1989, which caused enormous economic losses. The aphid infested areas exceeded 200 thousand mu, and the soybean yields decreased by 20%. Among aphid infested areas, 78 thousand mu were severely infested with a yield loss of 46%. More than 3,000 mu had no yield at all.Originating text in Chinese.Citation: Wu, Xiaobing, Ni, Wenjun, Liu, Peijing. (1999). Occurrence and Control of Soybean Aphid, Aphis glycines Matsumura. How Peasants Can Increase Wealth, 6, 20

Unravelling the Correlation of Electronic Structure and Carrier Dynamics in CuInS\u3csub\u3e2\u3c/sub\u3e Nanoparticles

In this work, we report the direct correlation of photoinduced carrier dynamics and electronic structure of CuInS2 (CIS) nanoparticles (NPs) using the combination of multiple spectroscopic techniques including steady-state X-ray absorption spectroscopy (XAS), optical transient absorption (OTA), and X-ray transient (XTA) absorption spectroscopy. XAS results show that CIS NPs contain a large amount of surface Cu atoms with ≪four-coordination, which is more severe in CIS NPs with shorter nucleation times, indicating the presence of more Cu defect states in CIS NPs with smaller size particles. Using the combination of OTA and XTA spectroscopy, we show that electrons are trapped at states with mainly In or S nature while holes are trapped in sites characteristic of Cu. While there is no direct correlation of ultrafast trapping dynamics with NP nucleation time, charge recombination is significantly inhibited in CIS NPs with larger particles. These results suggest the key roles that Cu defect sites play in carrier dynamics and imply the possibility to control the carrier dynamics by controlling the surface structure at the Cu site in CIS NPs

Fast and cost-effective in-process defect inspection for printed electronics based on coherent optical processing

This paper presents an all-optical difference engine (AODE) sensor for detecting the defects in printed electronics produced with roll-to-roll processes. The sensor is based on the principle of coherent optical subtraction and is able to achieve high-speed inspection by minimising data post-processing. A self-comparison inspection strategy is introduced to allow defect detection by comparing the printed features and patterns that have the same nominal dimensions. In addition, potential applications of the AODE sensor in an on-the-fly pass-orreject production control scenario are presented. A prototype AODE sensor using a digital camera is developed and demonstrated by detecting defects on several industrial printed electrical circuitry samples. The camera can be easily replaced by a low-cost photodiode to realise high-speed all-optical information processing and inspection. The developed sensor is capable of inspecting areas of 4 mm width with a resolution of the order of several micrometres, and can be duplicated in parallel to inspect larger areas without significant cost

Unravelling the Correlation of Electronic Structure and Carrier Dynamics in CuInS2 Nanoparticles

In this work, we report the direct correlation of photoinduced carrier dynamics and electronic structure of CuInS2 (CIS) nanoparticles (NPs) using the combination of multiple spectroscopic techniques including steady-state X-ray absorption spectroscopy (XAS), optical transient absorption (OTA), and X-ray transient (XTA) absorption spectroscopy. XAS results show that CIS NPs contain a large amount of surface Cu atoms with ≪four-coordination, which is more severe in CIS NPs with shorter nucleation times, indicating the presence of more Cu defect states in CIS NPs with smaller size particles. Using the combination of OTA and XTA spectroscopy, we show that electrons are trapped at states with mainly In or S nature while holes are trapped in sites characteristic of Cu. While there is no direct correlation of ultrafast trapping dynamics with NP nucleation time, charge recombination is significantly inhibited in CIS NPs with larger particles. These results suggest the key roles that Cu defect sites play in carrier dynamics and imply the possibility to control the carrier dynamics by controlling the surface structure at the Cu site in CIS NPs