Search

The increasing social problems on population, resources and environment enable the interaction between nature and humanity to become one of the most active research fields in the world. In this paper, we propose a novel framework of human–land sustainable computational system, which fully advances the progress of the development of our society utilizing the cloud computing and big data analysis technologies. Particularly, the study on quality of land management has attracted much attention. With the proposed framework, multi-user multi-cloud environment (MUMCE) is firstly presented, and evaluation of land quality is regarded as various services, such as soil acidity and alkalinity, soil thickness, soil texture, smoothness and field layout. Then, this paper formulates the problem of formal concept analysis-based multi-cloud composition recommendation with regard to multiple users. To address this problem, this paper first adopts the collaborative filtering to obtain the services request of the target user, then the service–provider concept lattices are constructed, and finally the best multi-cloud composition is selected and further recommended for the target user. Meanwhile, the corresponding algorithm is also devised. A case study is conducted for evaluating the feasibility and effectiveness of the proposed approach.

Nowadays, many countries are actively seeking ways to solve the energy crisis and environmental pollution. New Energy Vehicle (NEV) has become an important way to solve these problems. With the rapid development of NEV, its batteries need to be replaced with new batteries after 5&ndash, 8 years. Therefore, whether the second use of NEV&rsquo, s battery has commercial or social value becomes a research hotspot. The innovation of this paper is to use the cost-benefit method to determine the value influencing factors of NEV&rsquo, s battery second use, and use system dynamics to perform scenario simulation analysis. The methods used in this paper are the cost-benefit method and system dynamics method. Firstly, this paper systematically analyzes the cost and benefit factors that affect the second use value of China&rsquo, s NEV batteries and uses system dynamics to establish the relationship and value model among various factors. Then, this paper compares the value of battery energy storage between old batteries and new batteries. According to the cost-income factor analysis, this paper eventually selects specific factors and uses VENSIM software to carry out the multi-scenario simulation. The results show that NEV&rsquo, s battery second use has commercial and social value compared to new battery energy storage. Moreover, battery cost, government subsidies, and electricity prices are three important factors that affect the second use value of China&rsquo, s NEV battery. Changing the government&rsquo, s cash subsidy methods, such as providing free batteries or combining new energy to reduce on-grid tariffs, will help increase the second use value of the NEV battery. In the future, the second use value of China&rsquo, s NEV battery industry will be more significant, with the update of the technology, the surge in the number of NEV&rsquo, s used batteries, and government support.

Multi-cloud composed by multiple clouds environment can take advantages of cloud computing which is becoming increasingly popular among new scientific and technological undertakings. The requested services of users could often be distributed across some providers hosted by several clouds. The multi-cloud services composition problem requires new scalable approaches to efficiently perform searching to reduce the energy consumption and monetary cost for fulfilling user's request. In this paper, we present a sustainable strategy for multi-cloud service composition, using Formal Concept Analysis and social network by considering some critical factors such as energy consumption between clouds, monetary cost and trust between users and clouds. In addition, a novel algorithm is proposed regarding to the sustainable multi-cloud service composition. We also evaluated the proposed approach through experiments and the results reveal the feasibility and effectiveness of our approach. Finally, we point out future directions for the selection of cloud providers.

In the process of rapid urbanization, air environment quality has become a hot issue. Aerosol optical depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) can be used to monitor air pollution effectively. In this paper, the Spearman coefficient is used to analyze the correlations between AOD and urban development, construction factors, and geographical environment factors in Shandong Province. The correlation between AOD and local climatic conditions in Shandong Province is analyzed by geographic weight regression (GWR). The results show that in the time period from 2007 to 2017, the AOD first rose and then fell, reaching its highest level in 2012, which is basically consistent with the time when the national environmental protection decree was issued. In terms of quarterly and monthly changes, AOD also rose first and then fell, the highest level in summer, with the highest monthly value occurring in June. In term of the spatial distribution, the high-value area is located in the northwestern part of Shandong Province, and the low-value area is located in the eastern coastal area. In terms of social factors, the correlation between pollutant emissions and AOD is much greater the correlations between AOD and population, economy, and construction indicators. In terms of environmental factors, the relationship between digital elevation model (DEM), temperature, precipitation, and AOD is significant, but the regulation of air in coastal areas is even greater. Finally, it was found that there are no obvious differences in AOD among cities with different development levels, which indicates that urban development does not inevitably lead to air pollution. Reasonable development planning and the introduction of targeted environmental protection policies can effectively alleviate pollution-related problems in the process of urbanization.

The continuous deterioration of environmental problems and the energy crisis has prompted countries and regions to increase research and development and support for new energy vehicles (NEV). NEV’s battery as the core components play an essential role in the cruising range and manufacturing cost in terms of energy, specific power, new materials, and battery safety. In order to know the development of NEV’s batteries, as well as research hotspots and technology trends, this paper analyses the market performance and technology trend of China NEV’s battery industry. Firstly, this paper analyses the policy and market, then clarify the macro environment of China’s NEV battery industry development. Secondly, this paper uses CITESPACE software to analyze the scientific knowledge of the literature data, such as research hotspots, research institutions, and technology development trends. In the end, this paper proposes policy recommendations for the future development of China’s NEV’s battery industry from the perspectives of technology, market, and industrial chain.

The development of mobile edge computing (MEC) is accelerating the popularity of 5G applications. In the 5G era, aiming to reduce energy consumption and latency, most applications or services are conducted on both edge cloud servers and cloud servers. However, the existing multi-cloud composition recommendation approaches are studied in the context of resources provided by a single cloud or multiple clouds. Hence, these approaches cannot cope with services requested by the composition of multiple clouds and edge clouds jointly in MEC. To this end, this paper firstly expands the structure of the multi-cloud service system and further constructs a multi-cloud multi-edge cloud (MCMEC) environment. Technically, we model this problem with formal concept analysis (FCA) by building the service&ndash, provider lattice and provider&ndash, cloud lattice, and select the candidate cloud composition that satisfies the user&rsquo, s requirements. In order to obtain an optimized cloud combination that can efficiently reduce the energy consumption, money cost, and network latency, the skyline query mechanism is utilized for extracting the optimized cloud composition. We evaluate our approach by comparing the proposed algorithm to the random-based service composition approach. A case study is also conducted for demonstrating the effectiveness and superiority of our proposed approach.

Leading edge ICT facilitates obtaining and interoperating information within collaborative networks (CNs), providing the base to tackle more advanced challenges. The paper addresses provision of transparent federated information/knowledge within administrative CNs. We introduce a methodology and mechanisms for incremental ontology development. The paper first identifies four typical sources of information/knowledge at the organizations involved in targeted emerging CNs, including: (i) database schemas, (ii) mission statements and main application scenarios, (iii) textual communications, and (iv) governance policies. It then introduces a systematic methodology to develop their meta-data and unify them into an ontology. This methodology consists of four semi-automated steps to gradually develop and enhance an ontology for the environment. The paper describes and exemplifies these steps and their mechanisms. An example real emerging case in the field of higher education administration in China is presented to serve as the proof of concept and verification of our proposed solution approach.

Detecting risk factors during freight period and making prevention or emergency measures is very important for reducing the probability of freight delay. In literatures, the operating time of function is considered as the fatal factor which affect freight period. More time the operation occupy, more important the function. But operating time of function can't reflect primary reason which results in freight delay. In our research, we take risk factors affecting freight period into consideration. From the perspective of transit scenario, we systematically analyze risk factors, mine the relationship among risk factors, and realize the dynamic merge of different freight scenario. This method can truly reflect fundamental factors affecting the freight period. So the management of freight period forewarning can be procedural, fine and dynamic.

A flexible inclination measurement system based on wireless sensor network (WSN) is proposed, and the structure of the system, the principle of inclination measurement and the hardware design of the system are described in details. The system that includes accelerometer, MCU, A/D converter and 2.4G wireless transceiver has achieved inclination measurement of high precision in a wide range. Two practical application examples are suggested.