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Architects welcome double skin facade (DSF) due to its aesthetic quality. The first DSF structure was intended to prevent cold weather and strong winds. Nowadays, the application of DSF under different climates has been investigated in many previous studies. However, little work had been done on the behaviour of DSF in hot and humid climates. Therefore, this paper aimed to extend the application into this specific climate and Guangzhou was selected as the sample city. Both the climate and the design influence the performance of DSF. In this paper, rather than explore how each design parameter influences the performance, the design was evaluated from an overall aspect. The Designbuilder software was used to build the single skin facade (SSF) and double skin facade base model. Annual HVAC energy consumption for both the two models was calculated and compared. An optimisation process was conducted to figure out what kinds of parameter combination could make the design more energy-saving and thermally comfortable. The results indicated that it was possible to design an energy-saving DSF system applied in hot and humid climates compared with the SSF model. The efficiency of the DSF could be further enhanced with a better parameter combination. The optimised options had some features in common, which could provide some inspirations for the application of DSF in hot and humid climates.

Bees not only produce honey but also provide the main pollination for most crops, while long maturation cycle, low yield of honey and even mass death of bees are observed in traditional hives due to the unfriendly internal thermal condition. In the present paper, a new beehive system integrated with solar thermal/PV system was introduced to optimize the internal thermal condition of the beehive and then to improve the yield and quality of honey. A local bee farm was selected to evaluate the operating performance of the solar beehive in a real natural environment. Comparative filed testing of the solar hive and traditional hive were carried out under different operating modes depending on the weather conditions all the year round. The variation of hive temperature, the quantity of honey collected, Baume degree and the amount of sugar feed consumption were measured and analyzed. The results showed that the air temperature in solar beehive was higher than that in traditional beehive in winter and transition seasons and lower in summer. The quantity of collected honey in the solar beehive was 15.8% more than that in the traditional beehive. The Baume degree indicated that honey can mature 2 days earlier in solar beehive. As to sugar feed consumption in winter, the corresponding quality in solar beehive was lower than that in traditional hive. These results indicated the feasibility of the conjunctive use of solar thermal/photovoltaic technology with the beehive that enlarges the solar energy applications.

It has been a focus to reduce the energy consumption and improve the space heating performance of high-altitude buildings in winter seasons. In view of the abundant solar energy resources of the high-altitude region, the establishment of passive solar houses should be an effective strategy to deal with the problem of thermal comfort. Both window to wall ratio (WWR) and sunspace depth are of vital importance to determine the thermal comfort level of passive solar houses, while there are limited studies on analyzing their impacts on passive solar houses in high-altitude regions. Therefore, this study is designed to examine how WWR and sunspace depth affect space heating of passive solar houses in the Qinghai-Tibetan region. To be specific, the hourly radiation temperature variations and percentages of dissatisfaction of the residential building with different sunspace depth/WWR (including 0.9m/33%, 0.9m/45%, 0.9m/60%, 1.2m/33% and 1.5m/33%) were quantitatively examined. Results indicated that under the condition of 0.9m/45%, the overall average radiation temperature of the building was approximately 16°C during the entire heating season, which could better satisfy the heating requirements. Meanwhile, the average temperature was higher, and the thermal comfort level was better under the ratio of 45% or the depth of 1.5 m, when only an individual factor in either ratio or depth was considered. These findings can provide references for the determination of dimensions of passive solar houses in high-altitude regions.

Energy poverty is prominent in rural Qinghai-Tibet region, China. In sacrifice of thermal comfort and health, residents adaptively choose the biomass fuels and cheap coal for heating and cooking, as an approach to energy expenditure reduction. Considering renewable energy utilization is effective to replace the utilization of conventional fuel, this paper aims to examine the potential of using solar house for energy poverty alleviation. Based on a novel hybrid heating system, we renovated a rural building into a solar house in Wangtun village, Qinghai-Tibet region. The energy consumption and indoor air temperature of the building before and after reconstruction were field measured and comparatively analysed. Results indicate that the energy consumed by solar house with the hybrid heating system was 153.3 kWh/day lower than that by the old building. The average air temperature of the living room and two bedrooms in the solar house reached 12.8°C, 11.0°C and 10.2°C, about 8.78°C, 7.61°C and 6.82°C higher than temperatures of the rooms in the old building. Overall, the solar house has considerably improved indoor environments and provided people with better thermal comfort. It is concluded that solar house can be an effective approach to mitigate domestic energy poverty of the rural Qinghai-Tibet region. The findings may also instruct other rural regions in either China or other developing countries to address the issue of energy poverty.

In recent years, convolutional neural networks (CNN) have been widely used in image denoising for their high performance. One difficulty in applying the CNN to medical image denoising such as speckle reduction in the optical coherence tomography (OCT) image is that a large amount of high-quality data is required for training, which is an inherent limitation for OCT despeckling. Recently, deep image prior (DIP) networks have been proposed for image restoration without pre-training since the CNN structures have the intrinsic ability to capture the low-level statistics of a single image. However, the DIP has difficulty finding a good balance between maintaining details and suppressing speckle noise. Inspired by DIP, in this paper, a sorted non-local statics which measures the signal autocorrelation in the differences between the constructed image and the input image is proposed for OCT image restoration. By adding the sorted non-local statics as a regularization loss in the DIP learning, more low-level image statistics are captured by CNN networks in the process of OCT image restoration. The experimental results demonstrate the superior performance of the proposed method over other state-of-the-art despeckling methods, in terms of objective metrics and visual quality.

To meet the heating demand in north China and reduce the pollution of traditional Chinese kang, a novel combined heating system consists of solar kang system and solar air heating system is proposed. The solar air system is built for the residents’ daily heating demand. The solar kang system can store the solar energy collected in the daytime and provide a good sleeping environment at night. In this study, demonstration buildings are built in Huzhu, Qinghai province and one of them is chosen to test its thermal performance. Three different operation modes: only the solar air system works, only the solar kang system works and the whole combined system works are tested. A mathematic model of the room and combined system is built based on the demonstrating building. Output simulation results are compared with experiment data. The result shows the combined system can rise the indoor air temperature significantly and the simulation result can fit the experiment well. The indoor air temperature can keep about 18 °C when the ambient average temperature is 5 °C. Kang surface temperature can keep above 26 °C during the night at the same condition. The study proves the excellent heating performance of the combined system.

How to design water-in-glass evacuated tube solar water heater (WGET-SWH) with high heat collection rates has long been a question. Here, we propose a high-throughput screening (HTS) method based on machine learning to design and screen 3.538125 × 108 possible combinations of extrinsic properties of WGET-SWH, to discover promising WGET-SWHs by comparing their predicted heat collection rates. Two new-designed WGET-SWHs were installed experimentally and showed higher heat collection rates (11.32 and 11.44 MJ/m2, respectively) than all the 915 measured samples in our previous database. This study shows that we can use the HTS method to modify the design of WGET-SWH with just few knowledge about the highly complicated correlations between the extrinsic properties and heat collection rates of solar water heaters.

The present work investigated a solar assisted heat pump system for drying Chinese wolfberry. The kinetic characteristic was firstly analyzed through a series of lab experiments. It was concluded that the Page model was the most suitable for predicting the heat and mass transfer of the wolfberry. Based on the wolfberry kinetic model, solar collector model and chamber air model, the coupled drying system model was developed. The accuracy of the mathematic model was determined through comparing with the preliminary experimental results. The influence of operating conditions on the thermal and energy performance of the dryer for the different operating mode was discussed. The drying weight of no more than 75 kg may be preferable in the stand-alone solar drying mode, and less than 15 h was needed to be dried. The electric energy consumption in the solar assisted the heat pump drying mode was lower than that in the stand-alone heat pump mode, and it was recommended that about 50 kg of wolfberry to be dried in the solar assisted heat pump system. Compared to the autumn drying, the reduction in the electric energy consumption was around 9.1 kWh during the 11 h summer drying process. The obtained results demonstrated the feasibility of the combined system for drying wolfberry, and also can provide the basic theoretical and experimental data support for the following research.

To promote the application of renewable energy in low-energy buildings in Alpine regions, a solar-air source heat pump (SASHP) system was investigated based on a low-energy residential building in Xining City. First, a solar fresh air (SFA) heating system simulation model was established in TRNSYS software, and the reliability of the model was verified with measured values. In addition, based on the SFA heating system model, a SASHP system model was further realized. The operating characteristics of the SASHP system were explored in depth and compared with those of the single-ASHP system in the heating season. The results show that the SFA heating system model is reliable, with relative errors that can be controlled within 15%. The indoor average temperature (Tave) can be maintained from 16.13 to 19.61 °C. The SASHP system can leads to Tave fluctuations within the range of 21.4–22.9 °C, and the solar fraction can reach 55% in the heating season. Furthermore, the SASHP system can reduce energy consumption by 55.38% compared to the ASHP system; additionally, the COP of the SASHP system is 109.43% higher than that of the ASHP system, and the annual cost is 9.7% lower. Moreover, the SASHP system produces 55.48% less carbon emissions than the ASHP system. These results provide guidance for the application of SASHP systems in Alpine regions.

We introduce a new class of twisted partially coherent beams with a non-uniform correlation structure. These beams, called twisted Hermite Gaussian Schell model (THGSM) beams, have a correlation structure related to Hermite functions and a twist factor in their degree of coherence. The spectral density and total average orbital angular momentum per photon of these beams strongly depend on the distortions applied to their degree of coherence. On propagation through free space, they exhibit both self-splitting and rotation of their spectral density profile, combining the interesting effects of twisted beams and non-uniformly correlated beams. We demonstrate that we can adjust both the beam order and the twist factor of THGSM beams to improve their resistance to turbulence.

This paper presents a fast algorithm for texture-less object recognition, which is designed to be robust to cluttered backgrounds and small transformations. At its core, the proposed method demonstrates a two-stage template-based procedure using an orientation compressing map and discriminative regional weight (OCM-DRW) to effectively detect texture-less objects. In the first stage, the proposed method quantizes and compresses all the orientations in a neighborhood to obtain the orientation compressing map which then is used to generate a set of possible object locations. To recognize the object in these possible object locations, the second stage computes the similarity of each possible object location with the learned template by using discriminative regional weight, which can effectively distinguish different categories of objects with similar parts. Experiments on publiclyavailable, texture-less object datasets indicate that apart from yielding efficient computational performance, the proposed method also attained remarkable recognition rates surpassing recent state-of-the-art texture-less object detectors in the presence of high-clutter, occlusion and scale-rotation changes. It improves the accuracy and speed by 8% and 370% respectively, relative to the previous best result on D-Textureless dataset.

This paper presents an efficient edge-based bilateral filter for real noisy image restoration. By dividing all pixels of a noisy image into edge region or non-edge region, the different strategies and parameters are adopted in the edge-based bilateral filter to balance the conservation of image features and the reduction of noise level. Extensive experimental results are shown that this filter achieves very competitive performance in restoring real noisy images, compared with other state-of-the-art denoising algorithm.

An improved Trombe wall is proposed to adapt to building construction with selective thermo-insulation facades (internal and cavity wall insulation, but not external wall insulation system). The case study is conducted in Xining, Capital city of Qinghai province in China, where the general building facades are mostly selective thermo-insulation facades to fight against the severe cold. A numerical analysis is undertaken to show the effects on the improvement of the building’s thermal environment by comparing the improved Trombe wall system with the classical Trombe wall system. The operating efficiency of the improved Trombe wall can be up to 33.85%, an increase of 56%. The results show that the improved Trombe wall works more effectively than the classical Trombe wall system in utilizing solar energy for the sample building.

In this letter, we present an efficient algorithm for the removal of random-valued impulse noise from a corrupted image by using a reference image. The proposed method uses a statistic of rank-ordered relative differences to identify pixels which are likely to be corrupted by impulse noise. Once a noisy pixel is identified, its value is restored by a simple weighted mean filter. Simulation results indicate that our algorithm provides a significant improvement over many other existing techniques.

In this paper, we proposed a fast algorithm for circle detection and measurement, which uses a lookup table and bitwise center accumulator (LUT-BCA). The LUT-BCA is a two-stage procedure. The first stage determines the candidate circle centers with normal lines produced by the lookup table and recorded by the bitwise center accumulator. The second stage computes the radius of each candidate circle center and validates these centers, which eliminates the false detections. The proposed LUT-BCA can also be easily implemented on massively parallel high-performance graphics hardware using the compute unified device architecture. Experimental results indicate that the LUT-BCA can locate circle centers and measure their radii accurately and is very suitable for real-time circle detection and measurement.

In this Letter, a probability-based non-local means filter is proposed for speckle reduction in optical coherence tomography (OCT). Originally developed for additive white Gaussian noise, the non-local means filter is not suitable for multiplicative speckle noise suppression. This Letter presents a two-stage non-local means algorithm using the uncorrupted probability of each pixel to effectively reduce speckle noise in OCT. Experiments on real OCT images demonstrate that the proposed filter is competitive with other state-of-the-art speckle removal techniques and able to accurately preserve edges and structural details with small computational cost.

An efficient denoising procedure for magnetic resonance imaging is presented. It is well known that the noise in magnetic resonance imaging has a Rician distribution. Unlike additive Gaussian noise, Rician noise is signal dependent, and separating signal from noise is a difficult task. This paper presents an iterative method based on wavelet shrinkage for Rician noise removal. Experiments show that the proposed method better suppresses noise and preserves edges than other magnetic resonance image denoising methods.