Manipulation of Defect Formation in Semiconductor Nanocrystals for Photocatalysis and Magneto-optics

Defects play a significant role in semiconductor nanocrystals (NCs) as they can influence their electrical and optical properties via vacancy doping or aliovalent doping. Localized surface plasmon resonance (LSPR), the phenomenon of collective oscillation of free electrons, allows for degenerately doped metal oxide NCs to be used as infrared plasmonic materials with promising applications in photovoltaics, sensing, electrochemistry photocatalysis and magneto-optics. In this study, sub-stoichiometric WO3-x NCs were used for plasmon-induced photodegradation of rhodamine-590 (Rh-590), with the advantages of facile synthetic method and simple configuration, as well as the potential to efficiently absorb NIR to MIR portion of solar radiation relative to the typical single-phase semiconductor and heterostructured photocatalysts reported. WO3-x NCs exhibit enhanced photocatalytic activity in contrast to bulk stoichiometric WO3 and sub-stoichiometric WO2.9 powders as well as annealed WO3-x NCs with nearly complete Rh-590 degradation (97.8%) within 2 hours in the dark at 20 ℃. Photocatalytic performance of WO3-x NCs increases with temperature because the wavelength of the blackbody radiation approaches to LSPR peak maximum. The WO3-x NCs show good recyclability with degradation percentage of ca. 82.6% after 3 cycles at 30 ℃. Scavengers were used to study the mechanism of photocatalytic degradation by WO3-x, suggesting that reactive radicals (superoxide radicals and hydroxyl radicals) make significant contribution to Rh-590 photodegradation. The results of this work demonstrate the important role of LSPR-associated free electrons in single-phase plasmonic semiconductor NCs for efficient photodegradation of dyes. Additionally, the single-phase plasmonic semiconductor NCs have emerged as promising materials for carrier polarization as magneto-optical materials. ZnO NCs, as an environmentally benign, cost effective material with abundant availability and reduced toxicity, are proposed as a model system to systematically investigate the effect of defect formation on plasmonic properties and charge carrier polarization in the presence of an external magnetic field. The defect concentration, responsible for plasmonic properties, was manipulated via changing synthesis conditions and doping with Mg ions and evaluated with the help of photoluminescence (PL) spectroscopy. Importantly, the Curie-type decay associated with unpaired localized electrons can also be manipulated by controlling defect concentration as indicated by magnetic circular dichroism (MCD) spectra. The defect-correlated band splitting monitored by MCD spectroscopy in Mg-doped ZnO NCs would be an intriguing topic for further study. The ability to control exciton polarization in pure (undoped) ZnO NCs using individual electrons localized on point defects enable the potential technological applications including spintronics and quantum information processing

Weakly-Supervised Video Anomaly Detection with Snippet Anomalous Attention

With a focus on abnormal events contained within untrimmed videos, there is increasing interest among researchers in video anomaly detection. Among different video anomaly detection scenarios, weakly-supervised video anomaly detection poses a significant challenge as it lacks frame-wise labels during the training stage, only relying on video-level labels as coarse supervision. Previous methods have made attempts to either learn discriminative features in an end-to-end manner or employ a twostage self-training strategy to generate snippet-level pseudo labels. However, both approaches have certain limitations. The former tends to overlook informative features at the snippet level, while the latter can be susceptible to noises. In this paper, we propose an Anomalous Attention mechanism for weakly-supervised anomaly detection to tackle the aforementioned problems. Our approach takes into account snippet-level encoded features without the supervision of pseudo labels. Specifically, our approach first generates snippet-level anomalous attention and then feeds it together with original anomaly scores into a Multi-branch Supervision Module. The module learns different areas of the video, including areas that are challenging to detect, and also assists the attention optimization. Experiments on benchmark datasets XDViolence and UCF-Crime verify the effectiveness of our method. Besides, thanks to the proposed snippet-level attention, we obtain a more precise anomaly localization

Parameterization of LSB in Self-Recovery Speech Watermarking Framework in Big Data Mining

The privacy is a major concern in big data mining approach. In this paper, we propose a novel self-recovery speech watermarking framework with consideration of trustable communication in big data mining. In the framework, the watermark is the compressed version of the original speech. The watermark is embedded into the least significant bit (LSB) layers. At the receiver end, the watermark is used to detect the tampered area and recover the tampered speech. To fit the complexity of the scenes in big data infrastructures, the LSB is treated as a parameter. This work discusses the relationship between LSB and other parameters in terms of explicit mathematical formulations. Once the LSB layer has been chosen, the best choices of other parameters are then deduced using the exclusive method. Additionally, we observed that six LSB layers are the limit for watermark embedding when the total bit layers equaled sixteen. Experimental results indicated that when the LSB layers changed from six to three, the imperceptibility of watermark increased, while the quality of the recovered signal decreased accordingly. This result was a trade-off and different LSB layers should be chosen according to different application conditions in big data infrastructures

Carotid Atherosclerosis Detected by Ultrasonography: A National Cross‐Sectional Study

Background: Carotid atherosclerosis (CA) is a reflector of generalized atherosclerosis that is associated with systemic vascular disease. Data are limited on the epidemiology of carotid lesions in a large, nationally representative population sample. We aimed to evaluate the prevalence of CA detected by carotid ultrasonography and related risk factors based on a national survey in China. Methods and Results: A total of 107 095 residents aged ≥40 years from the China National Stroke Prevention Project underwent carotid ultrasound examination. Participants with carotid endarterectomy or carotid stenting and those with stroke or coronary heart disease were excluded. Data from 84 880 participants were included in the analysis. CA was defined as increased intima–media thickness (IMT) ≥1 mm or presence of plaques. Of the 84 880 participants, 46.4% were men, and the mean age was 60.7±10.3 years. The standardized prevalence of CA was 36.2% overall, increased with age, and was higher in men than in women. Prevalence of CA was higher among participants living in rural areas than in urban areas. Approximately 26.5% of participants had increased IMT, and 13.9% presented plaques. There was an age‐related increase in participants with increased IMT, plaque presence, and stenosis. In multiple logistic regression analysis, older age, male sex, residence in rural areas, smoking, alcohol consumption, physical inactivity, obesity, hypertension, diabetes mellitus, and dyslipidemia were associated with CA. Conclusions: CA was highly prevalent in a middle‐aged and older Chinese population. This result shows the potential clinical importance of focusing on primary prevention of atherosclerosis progression

Ontology‐aware Course Management for Curriculum Evolution Process in Higher Education

6th VERITE : JAIST/TRUST-AIST/CVS joint workshop on VERIfication Technologyでの発表資料, 開催：3月12日～13日, 開催場所：JAIST 田町サテライトキャンパス2階多目的室

International Semantic Mapping of Copyright Law : A Conceptualization Supporting System with Capability of “Intention” and Ontology

The copyright issue is very important in education industry all along. Especially while coming into contact with global sharing of educational resources, mutual well-understood of the copyright laws is worthy of attention. However, there is a lack of systemic knowledge management methodology for the issue; closely connected to this problem is that most of intelligent laws systems are undesirable and ineffective for international semantic mapping of laws knowledge. Hence, this research aims to design a conceptualization supporting system with the capability of “Intention” and ontology for searching and mapping laws from different nations based on senamtic component of law. We focus on the intention behind the different copyright laws because the semantic similarity among the laws can be well recognized based on the intention, and we propose a “Intention Oriented ” Model (“IOM”). The value of “intention-oriented” prespective is obviously not noly in formulating intention behind the law, but also in providing a uniform criterion for integrating laws component from different national laws. The capability of IOM makes this system to take on verifiable reasoning. Meanwhile, we adopt ontological engineering approach for appropriately representing among different national laws and international treaties. Ontology clarifies systematic semantics of the vocabulary with which queries and assertions are exchanged among agents. The capability of ontology is provide “subclass-link” to identify concept subsumption relationship, which facilitates this system flexible matching. Moreover, in this research the copyright law ontology provides well-organized concept to clarify the commonality and the difference among different national laws and internatioanal treaties.The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.htmlIFSR 2005 : Proceedings of the First World Congress of the International Federation for Systems Research : The New Roles of Systems Sciences For a Knowledge-based Society : Nov. 14-17, 2149, Kobe, JapanSymposium 1, Session 7 : Technology Creation Based on Knowledge Science Modeling and Systems(1