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Photovoltaic (PV) air conditioning (AC) is an effective way to solve the problems of energy consumption of office buildings. In this study, a set of parameters were designed for PV AC, including PV capacity, AC parameter, and inverter parameter. Then, the parameters were applied to a 20-m2 office building, and a PV AC system test platform was built. The test lasted for one year; the corresponding data including typical daily data and annual data were collected and analyzed. The results show that the PV AC system quickly decreases or increases the room temperature by ~9.5% and 17% in 1 h of cooling and heating periods, respectively, thus maintaining the room temperature within the set temperature range of ±0.9 °C. The data also show that by proper design of parameters, a PV AC system can satisfy the electricity demand of AC. In the cooling period, heating period, and annual operation conditions, the PV system provided 114%, 73%, and 188% of the energy for the AC system, respectively. Next, economic calculations show that PV AC is suitable for office buildings. The local payback period is only 7.5 years; both the energy saving and emission reduction are significant.

Photovoltaic (PV) power generation technology is the main renewable energy utilization technology. However, dust deposition severely affects the PV power generation efficiency and decreases the production capacity of PV power plants. In this study, the factors affecting PV technology were divided into the following three types: occlusion, corrosion, and temperature rise. A dust-collecting PV model considering dust deposition and rainfall scouring was established; a PV performance index was proposed. By conducting experiments with different dust mass densities, it was found that the short-circuit current (SCC), open-circuit voltage (OCV), and PV output power of PV decreased with the increase in dust mass density. In the initial stage of dust deposition, dust exhibited the greatest effect on the performance of PV. In the later stage of dust deposition, the effect of dust deposition became stable. The initial 10 g/m2 dust decreased the PV output power by 34%. In addition, the conversion efficiency and fill factor (FF) decreased with the increase in dust mass density; both of them were exponential functions. When the dust mass density was low (less than 30 g/m2), the dust mass density increased by 10 g/m2, and the conversion efficiency decreased by an average of 3.4%. Finally, by conducting economic calculations, it was found that a PV power plant where dust has not removed for one year will cause 12% loss of power generation.

This research presents a design method of photovoltaic direct-drive air conditioning system, and arranges the photovoltaic direct-drive air conditioning system in an office building in hot-humid regions, the system mainly includes photovoltaic array, storage battery, confluence unit, PWM controller, and air conditioner. Through the test, we found that photovoltaic direct cur-rent air conditioning system is still able to better meet the indoor thermal environment needs even in hot weather. Besides, in the test day, the amount of photovoltaic power generation apart from meeting the demand for air conditioning and there are remaining. The excessively power generation is stored in the battery, it can be self-sufficient for the system, no municipal power grid supplement and energy efficiency is more significant.

Low latitude isolated islands have the climate characteristic of high temperature and high humidity, but in short of conventional energy. This study proposes a novel hybrid solar powered rotary desiccant wheel air conditioning (SRDAC) system to improve the indoor temperature of buildings on low latitude isolated islands. The SRDAC system combines photovoltaic power generation, solar thermal collector, vapor compressed cooling system and a two stage rotary desiccant wheel system. In this study, mathematical models of the subsystems of the SRDAC system are established firstly. MATLAB was used to analyze the performance of the SRDAC system, which includes the dehumidification capacity, cooling capacity, condensation heat quantity and thermodynamic performance coefficient. Then, the photovoltaic area and solar thermal collector area of the SRDAC system were matched and optimized based on meteorological parameters of low latitude isolated islands. Finally, the SRDAC system’s economic performance was analyzed. The results show that, for every 10 ℃ increase in regeneration temperature, the dehumidification capacity and cooling capacity increase by 0.9 g/kg-2.7 g/kg and 0.4 kW-1.9 kW, respectively. For every 1 g/kg increase of outdoor air moisture content, the total installed area increased by 2.2%-2.3%. The SRDAC system shows a good operating performance, can better adapt to the climate characteristics of low latitude isolated islands, and effectively reduces the temperature and moisture content of the air. This study serves as a reference for the application of SRDAC system in extremely hot and humid climates.

A cloud server spent a lot of time, energy and money to train a Viola-Jones type object detector with high accuracy. Clients can upload their photos to the cloud server to find objects. However, the client does not want the leakage of the content of his/her photos. In the meanwhile, the cloud server is also reluctant to leak any parameters of the trained object detectors. 10 years ago, Avidan & Butman introduced Blind Vision, which is a method for securely evaluating a Viola-Jones type object detector. Blind Vision uses standard cryptographic tools and is painfully slow to compute, taking a couple of hours to scan a single image. The purpose of this work is to explore an efficient method that can speed up the process. We propose the Random Base Image (RBI) Representation. The original image is divided into random base images. Only the base images are submitted randomly to the cloud server. Thus, the content of the image can not be leaked. In the meanwhile, a random vector and the secure Millionaire protocol are leveraged to protect the parameters of the trained object detector. The RBI makes the integral-image enable again for the great acceleration. The experimental results reveal that our method can retain the detection accuracy of that of the plain vision algorithm and is significantly faster than the traditional blind vision, with only a very low probability of the information leakage theoretically., 6 pages, 3 figures, To appear in the proceedings of the IEEE International Conference on Multimedia and Expo (ICME), Jul 10, 2017 - Jul 14, 2017, Hong Kong, Hong Kong

Recently, storage and processing large-scale visual media data are being outsourced to Cloud Data Centres CDCs. However, the CDCs are always third party entities. Thus the privacy of the users' visual media data may be leaked to the public or unauthorized parties. In this paper we propose a method of privacy preserving foreground extraction of video surveillance through chaotic mapping based encryption in the cloud. The client captures surveillance videos, which are then encrypted by our proposed chaotic mapping based encryption method. The encrypted surveillance videos are transmitted to the cloud server, in which the foreground extraction algorithm is running on the encrypted videos. The results are transmitted back to the client, in which the extraction results are decrypted to get the extraction results in plain videos. The extraction correctness in the encryption videos is similar as that in the plain videos. The proposed method has several advantages: 1 The server only learns the obfuscated extraction results and can not recognize anything from the results. 2 Based on our encryption method, the original extraction method in the plain videos need not be changed. 3 The chaotic mapping ensure high level security and the ability to resistant several attacks.

Nowadays, with tremendous visual media stored and even processed in the cloud, the privacy of visual media is also exposed to the cloud. In this paper we propose a private face identification method based on sparse representation. The identification is done in a secure way which protects both the privacy of the subjects and the confidentiality of the database. The face identification server in the cloud contains a list of registered faces. The surveillance client captures a face image and require the server to identify if the client face matches one of the suspects, but otherwise reveals no information to neither of the two parties. This is the first work that introduces sparse representation to the secure protocol of private face identification, which reduces the dimension of the face representation vector and avoid the patch based attack of a previous work. Besides, we introduce a secure Euclidean distance algorithm for the secure protocol. The experimental results reveal that the cloud server can return the identification results to the surveillance client without knowing anything about the client face image.

To protect the contents of images in the mobile internet era during image storage and transmission, image encryption has achieved a tremendous success during the last decades. Currently, little attention has been paid to non-RGB color spaces such as HSV, YUV and L*a*b* color spaces in the color image encryption community. In this paper we use high level encryption schemes in more informative channels and low level encryption schemes in less informative channels. This paper is the first time to encrypt color image in CIE L*a*b* color space. First we convert RGB to L*a*b* color space. The 2D Arnold’s cat map followed by the 3D Lu chaotic map are conducted in the L* channel. The less complicated DNA coding and 1D logistic map based encryption scheme is leveraged in the a* and b* channels, which contain less information than that in the L* channel. The experimental results reveal that our method achieves similar results with the method that conducts the same scheme in each channel of the RGB color space, while consuming less time. In addition, our method can resistant several attacks such as brute-force attack, statistic attack, correlation attack.