Flexible Yet Secure De-Duplication Service for Enterprise Data on Cloud Storage

The cloud storage services bring forth infinite storage capacity and flexible access capability to store and share large-scale content. The convenience brought forth has attracted both individual and enterprise users to outsource data service to a cloud provider. As the survey shows 56% of the usages of cloud storage applications are for data back up and up to 68% of data backup are user assets. Enterprise tenants would need to protect their data privacy before uploading them to the cloud and expect a reasonable performance while they try to reduce the operation cost in terms of cloud storage, capacity and I/Os matter as well as systems’ performance, bandwidth and data protection. Thus, enterprise tenants demand secure and economic data storage yet flexible access on their cloud data. In this paper, we propose a secure de-duplication solution for enterprise tenants to leverage the benefits of cloud storage while reducing operation cost and protecting privacy. First, the solution uses a proxy to do flexible group access control which supports secure de-duplication within a group; Second, the solution supports scalable clustering of proxies to support large-scale data access; Third, the solution can be integrated with cloud storage seamlessly. We implemented and tested our solution by integrating it with Dropbox. Secure de-duplication in a group is performed at low data transfer latency and small storage overhead as compared to de-duplication on plaintext

A Cloud Authentication Protocol using One-Time Pad

There is a significant increase in the amount of data breaches in corporate servers in the cloud environments. This includes username and password compromise in the cloud and account hijacking, thus leading to severe vulnerabilities of the cloud service provisioning. Traditional authentication schemes rely on the users to use their credentials to gain access to cloud service. However once the credential is compromised, the attacker will gain access to the cloud service easily. This paper proposes a novel scheme that does not require the user to present his credentials, and yet is able to prove ownership of access to the cloud service using a variant of zero-knowledge proof. A challenge-response protocol is devised to authenticate the user, requiring the user to compute a one-time pad (OTP) to authenticate himself to the server without revealing password to the server. A prototype has been implemented to facilitate the authentication of the user when accessing Dropbox, and the experiment results showed that the overhead incurred is insignificant

Modelling the electromagnetic separation of non-metallic particles from liquid metal flowing through a two-stage multichannel

A two-stage multichannel was designed to increase the efficiency of separating non-metallic particles from liquid metal flowing through an alternating magnetic field. Numerical method was developed to calculate the particle concentration and separation efficiency of a zinc melt containing dross particles and verified by the experimental results. The distribution of particle concentration and axial fluid velocity changed significantly due to the added walls in the sub-channel, resulting in an abrupt increase in the residence time of the inner bulk melt with high particle concentrations and a remarkable increase in particle separation efficiency when flowing through the single-channel to sub-channels. A multistage and multichannel arrangement is hence recommended for further increase in the separation efficiency of an electromagnetic separator

Flexible Yet Secure De-Duplication Service for Enterprise Data on Cloud Storage

The cloud storage services bring forth infinite storage capacity and flexible access capability to store and share large-scale content. The convenience brought forth has attracted both individual and enterprise users to outsource data service to a cloud provider. As the survey shows 56% of the usages of cloud storage applications are for data back up and up to 68% of data backup are user assets. Enterprise tenants would need to protect their data privacy before uploading them to the cloud and expect a reasonable performance while they try to reduce the operation cost in terms of cloud storage, capacity and I/Os matter as well as systems’ performance, bandwidth and data protection. Thus, enterprise tenants demand secure and economic data storage yet flexible access on their cloud data. In this paper, we propose a secure de-duplication solution for enterprise tenants to leverage the benefits of cloud storage while reducing operation cost and protecting privacy. First, the solution uses a proxy to do flexible group access control which supports secure de-duplication within a group; Second, the solution supports scalable clustering of proxies to support large-scale data access; Third, the solution can be integrated with cloud storage seamlessly. We implemented and tested our solution by integrating it with Dropbox. Secure de-duplication in a group is performed at low data transfer latency and small storage overhead as compared to de-duplication on plaintext

A sustainable biogas model in China: The case study of Beijing Deqingyuan biogas project

According to the Paris Agreement, China has the ambition to develop non-fossil energy which will account for 20% of the total energy consumption in 2030. China has abundant biomass potential implying the bioenergy should be an important option of non-fossil energy. In this analysis, we present an representative biogas project (the Deqingyuan project, DQY) in Beijing and conduct a cost-benefit analysis for the whole value chain. DQY is the first large-scale biogas project in China that utilizes 100% chicken manure as a feedstock and integrates biogas production with ecological agriculture using advanced technologies. DQY uses 80,000 t of chicken manure and 100,000 t of sewage each year to produce biogas, which generates 14 million KWh of power annually, and obtains an additional revenue of RMB 8 million yuan each year through the Clean Development Mechanism (CDM). Operating as an example of a sustainable bioenergy model, DQY accomplishes the full use of a recycled resource while showing consideration for animal welfare during the entire production, which is a fundamental component of the new rural energy strategy. The circular economy model of DQY plays a prominent role in reducing greenhouse gas emissions, mitigating pollution, and increasing employment, among other benefits. This paper aims to conduct a comprehensive analysis of the typical demonstration model (DQY) in utilization of agricultural waste in China, and further proposes a general development model of Chinese biogas in the future

Building Ubiquitous Computing Environment by Using RFID in Aircraft MRO Process

The implementation of RFID had aroused discussion in every area. Experts believe that the emergence of RFID will cause another business revolution. Many industries had deployed RFID, like aviation industry, in which RFID is used in maintenance materials and baggage management. This paper discusses the implementation of RFID in MRO process and the building of a ubiquitous computing environment. We believe that our proposal has three merits to MRO (1) anti-counterfeit parts (2) MRO liability (3) efficient and effective inspection. The architecture can address the competition pressure that aviation industry faces and consequently enhance competition advantages

CLiF-VQA: Enhancing Video Quality Assessment by Incorporating High-Level Semantic Information related to Human Feelings

Video Quality Assessment (VQA) aims to simulate the process of perceiving video quality by the human visual system (HVS). The judgments made by HVS are always influenced by human subjective feelings. However, most of the current VQA research focuses on capturing various distortions in the spatial and temporal domains of videos, while ignoring the impact of human feelings. In this paper, we propose CLiF-VQA, which considers both features related to human feelings and spatial features of videos. In order to effectively extract features related to human feelings from videos, we explore the consistency between CLIP and human feelings in video perception for the first time. Specifically, we design multiple objective and subjective descriptions closely related to human feelings as prompts. Further we propose a novel CLIP-based semantic feature extractor (SFE) which extracts features related to human feelings by sliding over multiple regions of the video frame. In addition, we further capture the low-level-aware features of the video through a spatial feature extraction module. The two different features are then aggregated thereby obtaining the quality score of the video. Extensive experiments show that the proposed CLiF-VQA exhibits excellent performance on several VQA datasets

Ultrasound cavitation induced nucleation in metal solidification: an analytical model and validation by real-time experiments

Microstructural refinement of metallic alloys via ultrasonic melt processing (USMP) is an environmentally friendly and promising method. However, so far there has been no report in open literature on how to predict the solidified microstructures and grain size based on the ultrasound processing parameters.In this paper, an analytical model is developed to calculate the cavitation enhanced undercooling and the USMP refined solidification microstructure and grain size for Al-Cu alloys. Ultrafast synchrotron X-ray imaging and tomography techniques were used to collect the real-time experimental data for validating the model and the calculated results. The comparison between modeling and experiments reveal that there exists an effective ultrasound input power intensity for maximizing the grain refinement effects for the Al-Cu alloys, which is in the range of 20-45 MW/m2. In addition, a monotonous increase in temperature during USMP has negative effect on producing new nuclei, deteriorating the benefit of microstructure refinement due to the application of ultrasound

Inferring High-level Geographical Concepts via Knowledge Graph and Multi-scale Data Integration: A Case Study of C-shaped Building Pattern Recognition

Effective building pattern recognition is critical for understanding urban form, automating map generalization, and visualizing 3D city models. Most existing studies use object-independent methods based on visual perception rules and proximity graph models to extract patterns. However, because human vision is a part-based system, pattern recognition may require decomposing shapes into parts or grouping them into clusters. Existing methods may not recognize all visually aware patterns, and the proximity graph model can be inefficient. To improve efficiency and effectiveness, we integrate multi-scale data using a knowledge graph, focusing on the recognition of C-shaped building patterns. First, we use a property graph to represent the relationships between buildings within and across different scales involved in C-shaped building pattern recognition. Next, we store this knowledge graph in a graph database and convert the rules for C-shaped pattern recognition and enrichment into query conditions. Finally, we recognize and enrich C-shaped building patterns using rule-based reasoning in the built knowledge graph. We verify the effectiveness of our method using multi-scale data with three levels of detail (LODs) collected from the Gaode Map. Our results show that our method achieves a higher recall rate of 26.4% for LOD1, 20.0% for LOD2, and 9.1% for LOD3 compared to existing approaches. We also achieve recognition efficiency improvements of 0.91, 1.37, and 9.35 times, respectively

Investment in carbon dioxide capture and storage combined with enhanced water recovery

Carbon dioxide capture and storage combined with enhanced deep saline water recovery (CCS-EWR) is a potential approach to mitigate climate change. However, its investment has been a dilemma due to high costs and various uncertainties. In this study, a trinomial tree modelling-based real options approach is constructed to assess the investment in CCS-EWR retrofitting for direct coal liquefaction in China from the investor perspective. In this approach, the uncertainties in CO2 prices, capital subsidies, water resource fees, the residual lifetime of direct coal liquefaction plants, electricity prices, CO2 and freshwater transport distance, and the amount of certified emission reductions (CERs) are considered. The results show that the critical CER price for CCS-EWR retrofits is 7.15 Chinese yuan per ton (CNY/ton) higher than that (141.95 CNY/ton) for CCS retrofits. However, the exemption from water resource fees for freshwater recovered from saline water and a subsidy of 26% of the capital cost are sufficient to eliminate the negative impact of enhanced deep saline water recovery (EWR) on the investment economy of CCS-EWR. In addition, when the residual lifetime is less than 14 years, CCS-EWR projects are still unable to achieve profitability, even with flexible management and decision making; therefore, investors should abandon CCS-EWR investments. On the whole, the investment feasibility for CCS-EWR technology is not optimistic despite access to preferential policies from the government. It is necessary to establish a carbon market with a high and stable CER price