Data-Driven Power Control for State Estimation: A Bayesian Inference Approach

We consider sensor transmission power control for state estimation, using a Bayesian inference approach. A sensor node sends its local state estimate to a remote estimator over an unreliable wireless communication channel with random data packet drops. As related to packet dropout rate, transmission power is chosen by the sensor based on the relative importance of the local state estimate. The proposed power controller is proved to preserve Gaussianity of local estimate innovation, which enables us to obtain a closed-form solution of the expected state estimation error covariance. Comparisons with alternative non data-driven controllers demonstrate performance improvement using our approach

DPF-Nutrition: Food Nutrition Estimation via Depth Prediction and Fusion

A reasonable and balanced diet is essential for maintaining good health. With the advancements in deep learning, automated nutrition estimation method based on food images offers a promising solution for monitoring daily nutritional intake and promoting dietary health. While monocular image-based nutrition estimation is convenient, efficient, and economical, the challenge of limited accuracy remains a significant concern. To tackle this issue, we proposed DPF-Nutrition, an end-to-end nutrition estimation method using monocular images. In DPF-Nutrition, we introduced a depth prediction module to generate depth maps, thereby improving the accuracy of food portion estimation. Additionally, we designed an RGB-D fusion module that combined monocular images with the predicted depth information, resulting in better performance for nutrition estimation. To the best of our knowledge, this was the pioneering effort that integrated depth prediction and RGB-D fusion techniques in food nutrition estimation. Comprehensive experiments performed on Nutrition5k evaluated the effectiveness and efficiency of DPF-Nutrition

RAPS: A Novel Few-Shot Relation Extraction Pipeline with Query-Information Guided Attention and Adaptive Prototype Fusion

Few-shot relation extraction (FSRE) aims at recognizing unseen relations by learning with merely a handful of annotated instances. To generalize to new relations more effectively, this paper proposes a novel pipeline for the FSRE task based on queRy-information guided Attention and adaptive Prototype fuSion, namely RAPS. Specifically, RAPS first derives the relation prototype by the query-information guided attention module, which exploits rich interactive information between the support instances and the query instances, in order to obtain more accurate initial prototype representations. Then RAPS elaborately combines the derived initial prototype with the relation information by the adaptive prototype fusion mechanism to get the integrated prototype for both train and prediction. Experiments on the benchmark dataset FewRel 1.0 show a significant improvement of our method against state-of-the-art methods.Comment: 9 pages, 2 figure

Mining Cross-Person Cues for Body-Part Interactiveness Learning in HOI Detection

Human-Object Interaction (HOI) detection plays a crucial role in activity understanding. Though significant progress has been made, interactiveness learning remains a challenging problem in HOI detection: existing methods usually generate redundant negative H-O pair proposals and fail to effectively extract interactive pairs. Though interactiveness has been studied in both whole body- and part- level and facilitates the H-O pairing, previous works only focus on the target person once (i.e., in a local perspective) and overlook the information of the other persons. In this paper, we argue that comparing body-parts of multi-person simultaneously can afford us more useful and supplementary interactiveness cues. That said, to learn body-part interactiveness from a global perspective: when classifying a target person's body-part interactiveness, visual cues are explored not only from herself/himself but also from other persons in the image. We construct body-part saliency maps based on self-attention to mine cross-person informative cues and learn the holistic relationships between all the body-parts. We evaluate the proposed method on widely-used benchmarks HICO-DET and V-COCO. With our new perspective, the holistic global-local body-part interactiveness learning achieves significant improvements over state-of-the-art. Our code is available at https://github.com/enlighten0707/Body-Part-Map-for-Interactiveness.Comment: To appear in ECCV 202

Spatiotemporal Variations of City-Level Carbon Emissions in China during 2000–2017 Using Nighttime Light Data

China is one of the largest carbon emitting countries in the world. Numerous strategies have been considered by the Chinese government to mitigate carbon emissions in recent years. Accurate and timely estimation of spatiotemporal variations of city-level carbon emissions is of vital importance for planning of low-carbon strategies. For an assessment of the spatiotemporal variations of city-level carbon emissions in China during the periods 2000–2017, we used nighttime light data as a proxy from two sources: Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data and the Suomi National Polar-orbiting Partnership satellite’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The results show that cities with low carbon emissions are located in the western and central parts of China. In contrast, cities with high carbon emissions are mainly located in the Beijing-Tianjin-Hebei region (BTH) and Yangtze River Delta (YRD). Half of the cities of China have been making eorts to reduce carbon emissions since 2012, and regional disparities among cities are steadily decreasing. Two clusters of high-emission cities located in the BTH and YRD followed two dierent paths of carbon emissions owing to the diverse political status and pillar industries. We conclude that carbon emissions in China have undergone a transformation to decline, but a very slow balancing between the spatial pattern of high-emission versus low-emission regions in China can be presumed

Smart solar concentrators for building integrated photovoltaic façades

In this study a novel static concentrating photovoltaic (PV) system, suitable for use in windows or glazing façades, has been designed. The developed smart Concentrating PV (CPV) system is lightweight, low cost and able to generate electricity. Additionally, this system automatically responds to climate by varying the balance of electricity generated from the PV with the amount of solar light and heat permitted through it into the building. It therefore offers the potential to contribute to, and control, energy consumption within buildings. A comprehensive optical analysis of the smart CPV is undertaken via 3-D ray tracing technique. To obtain optimal overall optical performance of the novel smart CPV analysis has been based upon all necessary design parameters including the average reflectivity of the thermotropic reflective layer, the glazing cover dimension, the glazing cover materials as well as the dimensions of the solar cells. In addition, a hydroxypropyl cellulose (HPC) hydrogel polymer, suitable for use as the reflective thermotropic layer for the smart CPV system, was synthesized and experimentally studied

Competitiveness assessment for real estate enterprises in china: A model‐procedure

China's accession to the World Trade Organization (WTO) in 2001 has allowed both domestic and overseas real estate enterprises to compete under the same market conditions. This has led to a more rigorous competition in the Chinese real estate market. Understanding this challenge is essential as it enables real estate enterprises to assess their competitiveness properly, and therefore adapt to their competition environment by applying adequate methods to improve their competitiveness. This paper presents an understanding on the applicability of various established competitiveness assessment methods. The characteristics of real estate firms are also presented with the appreciation of the Chinese environment. The study investigates the applicability of various established competitiveness assessment methods for real estate organizations in China considering the characteristics of real estate industry and the comments of the interviewees. The understanding on this applicability leads to the development of a model‐procedure for assessing the competitiveness of real estate firms. The model‐procedure employs various assessment methods in different stages in the process of examining the competitiveness of real estate businesses. The effectiveness of the application of the model‐procedure is evidenced through discussions with senior professionals. Then a case study is presented to illustrate how the model‐procedure can be applied. The findings of the study provide valuable references to study competitiveness assessment in other country's real estate industries. Santruka Nuo 2001 metu, kai Kinija tapo Pasaulines prekybos organizacijos (PPO) nare, ir vietines, ir užsienio nekilnojamojo turto imones gali konkuruoti tomis pačiomis rinkos salygomis. Del to konkurencija Kinijos nekilnojamojo turto rinkoje tapo tik aršesne. Ši iššūki būtina suprasti, nes jis nekilnojamojo turto imonems leidžia tinkamai ivertinti savo konkurencinguma, prisitai kyti prie konkurencines aplinkos bei pasirinkti adekva čius metodus konkurencingumui didinti. Straipsnyje apžvelgiama, kaip suprantamas ivairiu pripažin tu konkurencingumo vertinimo metodu tinkamumas. Pateikiamos Kinijos nekilnojamojo turto imoniu charakteristikos. Remiantis atlikto tyrimo rezultatais, nekilnojamojo turto sektoriaus charakteristikomis ir apklausoje dalyvavusiu asmenu komentarais, nagrinejamas ivairiu pripažin tu konkurencingumo vertinimo metodu tinkamumas Kinijoje veikiančioms nekilnojamojo turto organizacijoms. Suvokiant ši tinkamuma, galima sukurti procedūros modeli, kuri naudojant būtu vertinamas nekilnojamojo turto imoniu konkurencingumas. Ivairiais nekilnojamojo turto imoniu konkurencingumo tyrinejimo proceso etapais taikant procedūros modeli naudojami skirtingi vertinimo metodai. Mineto modelio taikymo efektyvumas aptariamas su šios srities profesionalais. Tada pateikiamas konkretaus atvejo, parodančio procedūros modelio taikyma, tyrimas, o jo išvados suteikia vertingos informacijos, kuria galima naudoti tyrinejant konkurencingumo vertinima kitos šalies nekilnojamojo turto sektoriuose. First Publish Online: 18 Oct 201

Development of a Ground Based Remote Sensing Approach for Direct Evaluation of Aerosol-Cloud Interaction

The possible interaction and modification of cloud properties due to aerosols is one of the most poorly understood mechanisms within climate studies, resulting in the most significant uncertainty as regards radiation budgeting. In this study, we explore direct ground based remote sensing methods to assess the Aerosol-Cloud Indirect Effect directly, as space-borne retrievals are not directly suitable for simultaneous aerosol/cloud retrievals. To illustrate some of these difficulties, a statistical assessment of existing multispectral imagers on geostationary (e.g., GOES)/Moderate Resolution Imaging Spectroradiometer (MODIS) satellite retrievals of the Cloud Droplet Effective Radius (Reff) showed significant biases especially at larger solar zenith angles, further motivating the use of ground based remote sensing approaches. In particular, we discuss the potential of using a combined Microwave Radiometer (MWR)—Multi-Filter Rotating Shadowband Radiometer (MFRSR) system for real-time monitoring of Cloud Optical Depth (COD) and Cloud Droplet Effective Radius (Reff), which are combined with aerosol vertical properties from an aerosol lidar. An iterative approach combining the simultaneous observations from MFRSR and MWR are used to retrieve the COD and Reff for thick cloud cases and are extensively validated using the DoE Southern Great Plains (SGP) retrievals as well as regression based parameterized model retrievals. In addition, we account for uncertainties in background aerosol, surface albedo and the combined measurement uncertainties from the MWR and MFRSR in order to provide realistic uncertainty estimates, which is found to be ~10% for the parameter range of interest in Aerosol-Cloud Interactions. Finally, we analyze a particular case of possible aerosol-cloud interaction described in the literature at the SGP site and demonstrate that aerosol properties obtained at the surface can lead to inconclusive results in comparison to lidar-derived aerosol properties near the cloud base

A high performance flexible recyclable supercapacitor with polyaniline by casting in unconventional proportion

Abstract(#br)A new type of recyclable flexible solid-state supercapacitor with good electrochemical performance and folder ability is produced through a facile method. Polyvinylidene fluoride - acetylene black - polyethylene glycol - polyaniline (PVDF-AB-PEG-PANI) film electrode with excellent processability and tailorability is prepared by casting strategy, which uses large amount of PVDF as film former. The new electrode has good performance with excellent flexibility (d r < 1 mm and capacity retention 97.4 % after folding 1000 times) and electrochemical performance (It can utilize the active substance efficiently that it closes to the theoretical value, with high areal capacitance of 890.44 mF cm −2 and volumetric capacitance of 89.04 F cm −3 ). A capacitance retention of 72.5 % is obtained for the supercapacitor based on this electrode after 5000 charging/discharging cycles, even polyaniline is synthesized by conventional method. The most interesting thing is that, the supercapacitor based on this electrode can easily be recycled and reused (capacity retention 97.1 % after 4 recycle times)