Real-Time Recognition Non-Intrusive Electrical Appliance Monitoring Algorithm for a Residential Building Energy Management System

The concern of energy price hikes and the impact of climate change because of energy generation and usage forms the basis for residential building energy conservation. Existing energy meters do not provide much information about the energy usage of the individual appliance apart from its power rating. The detection of the appliance energy usage will not only help in energy conservation, but also facilitate the demand response (DR) market participation as well as being one way of building energy conservation. However, energy usage by individual appliance is quite difficult to estimate. This paper proposes a novel approach: an unsupervised disaggregation method, which is a variant of the hidden Markov model (HMM), to detect an appliance and its operation state based on practicable measurable parameters from the household energy meter. Performing experiments in a practical environment validates our proposed method. Our results show that our model can provide appliance detection and power usage information in a non-intrusive manner, which is ideal for enabling power conservation efforts and participation in the demand response market.1176Ysciescopu

A Simplified Identification Method of Dynamic Stiffness for the Heavy-Load and Low-Speed Journal Bearings

Journal bearing is an essential part of the propulsion shafting system, whose performance directly affects the safety and performance of the shaft and even the entire ship. It is an important, but also a difficult task to obtain the accurate dynamic stiffness values. In order to determine the dynamic characteristics of the journal bearing with specific structural characteristics under specific working conditions, an inverted test platform with multiple sensors for the dynamic stiffness of the heavy-load, low-speed journal bearings (HLLSJBs) was developed, and a novel dynamic test system calibration method was proposed to obtain accurate baseline data, and then the effective characteristic frequency response was gotten based on a refined fast Fourier transform method (RFFT). The present study proposed a simplified identification method to analyze the constitutive relationships between the oil film dynamic parameters and the dynamic stiffness under different rotation and loading conditions in the journal bearing, and then the accurate values of the oil film dynamic stiffness of HLLSJBs were obtained. Furthermore, the values of the structural dynamic stiffness of HLLSJBs were also obtained using a hammer impact method. A comparison with the classic theoretical analysis results reveals that the method proposed is more accurate and effective

Endometrial Response to Conceptus-Derived Estrogen and Interleukin-1β at the Time of Implantation in Pigs

The establishment of pregnancy is a complex process that requires a well-coordinated interaction between the implanting conceptus and the maternal uterus. In pigs, the conceptus undergoes dramatic morphological and functional changes at the time of implantation and introduces various factors, including estrogens and cytokines, interleukin-1β2 (IL1B2), interferon-γ (IFNG), and IFN-δ (IFND), into the uterine lumen. In response to ovarian steroid hormones and conceptus-derived factors, the uterine endometrium becomes receptive to the implanting conceptus by changing its expression of cell adhesion molecules, secretory activity, and immune response. Conceptus-derived estrogens act as a signal for maternal recognition of pregnancy by changing the direction of prostaglandin (PG) F2α from the uterine vasculature to the uterine lumen. Estrogens also induce the expression of many endometrial genes, including genes related to growth factors, the synthesis and transport of PGs, and immunity. IL1B2, a pro-inflammatory cytokine, is produced by the elongating conceptus. The direct effect of IL1B2 on endometrial function is not fully understood. IL1B activates the expression of endometrial genes, including the genes involved in IL1B signaling and PG synthesis and transport. In addition, estrogen or IL1B stimulates endometrial expression of IFN signaling molecules, suggesting that estrogen and IL1B act cooperatively in priming the endometrial function of conceptus-produced IFNG and IFND that, in turn, modulate endometrial immune response during early pregnancy. This review addresses information about maternal-conceptus interactions with respect to endometrial gene expression in response to conceptus-derived factors, focusing on the roles of estrogen and IL1B during early pregnancy in pigs

Evaluating GPT-3 Generated Explanations for Hateful Content Moderation

Recent research has focused on using large language models (LLMs) to generate explanations for hate speech through fine-tuning or prompting. Despite the growing interest in this area, these generated explanations' effectiveness and potential limitations remain poorly understood. A key concern is that these explanations, generated by LLMs, may lead to erroneous judgments about the nature of flagged content by both users and content moderators. For instance, an LLM-generated explanation might inaccurately convince a content moderator that a benign piece of content is hateful. In light of this, we propose an analytical framework for examining hate speech explanations and conducted an extensive survey on evaluating such explanations. Specifically, we prompted GPT-3 to generate explanations for both hateful and non-hateful content, and a survey was conducted with 2,400 unique respondents to evaluate the generated explanations. Our findings reveal that (1) human evaluators rated the GPT-generated explanations as high quality in terms of linguistic fluency, informativeness, persuasiveness, and logical soundness, (2) the persuasive nature of these explanations, however, varied depending on the prompting strategy employed, and (3) this persuasiveness may result in incorrect judgments about the hatefulness of the content. Our study underscores the need for caution in applying LLM-generated explanations for content moderation. Code and results are available at https://github.com/Social-AI-Studio/GPT3-HateEval.Comment: 9 pages, 2 figures, Accepted by International Joint Conference on Artificial Intelligence(IJCAI

Prevalence and heritability of handedness in a Hong Kong Chinese twin and singleton sample

Funding: Research Grants Council of the Hong Kong Special Administration Region (CUHK8/CRF/13G & C4054-17WF), by an internal grant entitled “Reading Development in Chinese and in English: Genetics and Neuroscience Correlates”(4930703) from The Chinese University of Hong Kong (CM is the PI on both grants), by a Hong Kong: Scotland Collaborative Research Partnership award from the Hong Kong Grants Council (CMis the PI for the Hong Kong side) and the Scottish Funding Council (SP is the PI for the Scotland side). It was additionally funded by an International Exchange Kan Tongo Po Visiting Fellowship to SP. SP is a Royal Society University Research Fellow.Background Left-handedness prevalence has been consistently reported at around 10% with heritability estimates at around 25%. Higher left-handedness prevalence has been reported in males and in twins. Lower prevalence has been reported in Asia, but it remains unclear whether this is due to biological or cultural factors. Most studies are based on samples with European ethnicities and using the preferred hand for writing as key assessment. Here, we investigated handedness in a sample of Chinese school children in Hong Kong, including 426 singletons and 205 pairs of twins, using both the Edinburgh Handedness Inventory and Pegboard Task. Results Based on a binary definition of writing hand, we found a higher prevalence of left-handedness (8%) than what was previously reported in Asian datasets. We found no evidence of increased left-handedness in twins, but our results were in line with previous findings showing that males have a higher tendency to be left-handed than females. Heritability was similar for both hand preference (21%) and laterality indexes (22%). However, these two handedness measures present only a moderate correlation (.42) and appear to be underpinned by different genetic factors. Conclusion In summary, we report new reference data for an ethnic group usually underrepresented in the literature. Our heritability analysis supports the idea that different measures will capture different components of handedness and, as a consequence, datasets assessed with heterogeneous criteria are not easily combined or compared.PreprintPublisher PDFPeer reviewe

NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension

One-shot neural architecture search (NAS) substantially improves the search efficiency by training one supernet to estimate the performance of every possible child architecture (i.e., subnet). However, the inconsistency of characteristics among subnets incurs serious interference in the optimization, resulting in poor performance ranking correlation of subnets. Subsequent explorations decompose supernet weights via a particular criterion, e.g., gradient matching, to reduce the interference; yet they suffer from huge computational cost and low space separability. In this work, we propose a lightweight and effective local intrinsic dimension (LID)-based method NAS-LID. NAS-LID evaluates the geometrical properties of architectures by calculating the low-cost LID features layer-by-layer, and the similarity characterized by LID enjoys better separability compared with gradients, which thus effectively reduces the interference among subnets. Extensive experiments on NASBench-201 indicate that NAS-LID achieves superior performance with better efficiency. Specifically, compared to the gradient-driven method, NAS-LID can save up to 86% of GPU memory overhead when searching on NASBench-201. We also demonstrate the effectiveness of NAS-LID on ProxylessNAS and OFA spaces. Source code: https://github.com/marsggbo/NAS-LID.Comment: Accepted by AAAI2023, AutoML, NA