Intelligent manufacturing is a general concept that is under continuous development. It can be categorized into three basic paradigms: digital manufacturing, digital-networked manufacturing, and new-generation intelligent manufacturing. New-generation intelligent manufacturing represents an in-depth integration of new-generation artificial intelligence (AI) technology and advanced manufacturing technology. It runs through every link in the full life-cycle of design, production, product, and service. The concept also relates to the optimization and integration of corresponding systems; the continuous improvement of enterprises’ product quality, performance, and service levels; and reduction in resources consumption. New-generation intelligent manufacturing acts as the core driving force of the new industrial revolution and will continue to be the main pathway for the transformation and upgrading of the manufacturing industry in the decades to come. Human-cyber-physical systems (HCPSs) reveal the technological mechanisms of new-generation intelligent manufacturing and can effectively guide related theoretical research and engineering practice. Given the sequential development, cross interaction, and iterative upgrading characteristics of the three basic paradigms of intelligent manufacturing, a technology roadmap for “parallel promotion and integrated development” should be developed in order to drive forward the intelligent transformation of the manufacturing industry in China.
Recommendation systems are crucially important for the delivery of personalized services to users. With personalized recommendation services, users can enjoy a variety of targeted recommendations such as movies, books, ads, restaurants, and more. In addition, personalized recommendation services have become extremely effective revenue drivers for online business. Despite the great benefits, deploying personalized recommendation services typically requires the collection of users’ personal data for processing and analytics, which undesirably makes users susceptible to serious privacy violation issues. Therefore, it is of paramount importance to develop practical privacy-preserving techniques to maintain the intelligence of personalized recommendation services while respecting user privacy. In this paper, we provide a comprehensive survey of the literature related to personalized recommendation services with privacy protection. We present the general architecture of personalized recommendation systems, the privacy issues therein, and existing works that focus on privacy-preserving personalized recommendation services. We classify the existing works according to their underlying techniques for personalized recommendation and privacy protection, and thoroughly discuss and compare their merits and demerits, especially in terms of privacy and recommendation accuracy. We also identity some future research directions.
With the development of sophisticated image editing and manipulation tools, the originality and authenticity of a digital image is usually hard to determine visually. In order to detect digital image forgeries, various kinds of digital image forensics techniques have been proposed in the last decade. Compared with active forensics approaches that require embedding additional information, passive forensics approaches are more popular due to their wider application scenario, and have attracted increasing academic and industrial research interests. Generally speaking, passive digital image forensics detects image forgeries based on the fact that there are certain intrinsic patterns in the original image left during image acquisition or storage, or specific patterns in image forgeries left during the image storage or editing. By analyzing the above patterns, the originality of an image can be authenticated. In this paper, a brief review on passive digital image forensic methods is presented in order to provide a comprehensive introduction on recent advances in this rapidly developing research area. These forensics approaches are divided into three categories based on the various kinds of traces they can be used to track—that is, traces left in image acquisition, traces left in image storage, and traces left in image editing. For each category, the forensics scenario, the underlying rationale, and state-of-the-art methodologies are elaborated. Moreover, the major limitations of the current image forensics approaches are discussed in order to point out some possible research directions or focuses in these areas.
Social influence analysis (SIA) is a vast research field that has attracted research interest in many areas. In this paper, we present a survey of representative and state-of-the-art work in models, methods, and evaluation aspects related to SIA. We divide SIA models into two types: microscopic and macroscopic models. Microscopic models consider human interactions and the structure of the influence process, whereas macroscopic models consider the same transmission probability and identical influential power for all users. We analyze social influence methods including influence maximization, influence minimization, flow of influence, and individual influence. In social influence evaluation, influence evaluation metrics are introduced and social influence evaluation models are then analyzed. The objectives of this paper are to provide a comprehensive analysis, aid in understanding social behaviors, provide a theoretical basis for influencing public opinion, and unveil future research directions and potential applications.
Given the challenges facing the cyberspace of the nation, this paper presents the tripartite theory of cyberspace, based on the status quo of cyberspace. Corresponding strategies and a research architecture are proposed for common public networks (C space), secure classified networks (S space), and key infrastructure networks (K space), based on their individual characteristics. The features and security requirements of these networks are then discussed. Taking C space as an example, we introduce the SMCRC (which stands for “situation awareness, monitoring and management, cooperative defense, response and recovery, and countermeasures and traceback”) loop for constructing a cyberspace security ecosystem. Following a discussion on its characteristics and information exchange, our analysis focuses on the critical technologies of the SMCRC loop. To obtain more insight into national cyberspace security, special attention should be paid to global sensing and precise mapping, continuous detection and active management, cross-domain cooperation and systematic defense, autonomous response and rapid processing, and accurate traceback and countermeasure deterrence.
Cyberattack forms are complex and varied, and the detection and prediction of dynamic types of attack are always challenging tasks. Research on knowledge graphs is becoming increasingly mature in many fields. At present, it is very significant that certain scholars have combined the concept of the knowledge graph with cybersecurity in order to construct a cybersecurity knowledge base. This paper presents a cybersecurity knowledge base and deduction rules based on a quintuple model. Using machine learning, we extract entities and build ontology to obtain a cybersecurity knowledge base. New rules are then deduced by calculating formulas and using the path-ranking algorithm. The Stanford named entity recognizer (NER) is also used to train an extractor to extract useful information. Experimental results show that the Stanford NER provides many features and the useGazettes parameter may be used to train a recognizer in the cybersecurity domain in preparation for future work.
The biggest bottleneck in DNA computing is exponential explosion, in which the DNA molecules used as data in information processing grow exponentially with an increase of problem size. To overcome this bottleneck and improve the processing speed, we propose a DNA computing model to solve the graph vertex coloring problem. The main points of the model are as follows: ① The exponential explosion problem is solved by dividing subgraphs, reducing the vertex colors without losing the solutions, and ordering the vertices in subgraphs; and ② the bio-operation times are reduced considerably by a designed parallel polymerase chain reaction (PCR) technology that dramatically improves the processing speed. In this article, a 3-colorable graph with 61 vertices is used to illustrate the capability of the DNA computing model. The experiment showed that not only are all the solutions of the graph found, but also more than 99% of false solutions are deleted when the initial solution space is constructed. The powerful computational capability of the model was based on specific reactions among the large number of nanoscale oligonucleotide strands. All these tiny strands are operated by DNA self-assembly and parallel PCR. After thousands of accurate PCR operations, the solutions were found by recognizing, splicing, and assembling. We also prove that the searching capability of this model is up to O(359). By means of an exhaustive search, it would take more than 896 000 years for an electronic computer (5 × 1014 s−1) to achieve this enormous task. This searching capability is the largest among both the electronic and non-electronic computers that have been developed since the DNA computing model was proposed by Adleman’s research group in 2002 (with a searching capability of O(220)).
The service and application of a network is a behavioral process that is oriented toward its operations and tasks, whose metrics and evaluation are still somewhat of a rough comparison. This paper describes scenes of network behavior as differential manifolds. Using the homeomorphic transformation of smooth differential manifolds, we provide a mathematical definition of network behavior and propose a mathematical description of the network behavior path and behavior utility. Based on the principle of differential geometry, this paper puts forward the function of network behavior and a calculation method to determine behavior utility, and establishes the calculation principle of network behavior utility. We also provide a calculation framework for assessment of the network’s attack-defense confrontation on the strength of behavior utility. Therefore, this paper establishes a mathematical foundation for the objective measurement and precise evaluation of network behavior.
With the development of online social networks (OSNs) and modern smartphones, sharing photos with friends has become one of the most popular social activities. Since people usually prefer to give others a positive impression, impression management during photo sharing is becoming increasingly important. However, most of the existing privacy-aware solutions have two main drawbacks: ① Users must decide manually whether to share each photo with others or not, in order to build the desired impression; and ② users run a high risk of leaking sensitive relational information in group photos during photo sharing, such as their position as part of a couple, or their sexual identity. In this paper, we propose a social relation impression-management (SRIM) scheme to protect relational privacy and to automatically recommend an appropriate photo-sharing policy to users. To be more specific, we have designed a lightweight face-distance measurement that calculates the distances between users’ faces within group photos by relying on photo metadata and face-detection results. These distances are then transformed into relations using proxemics. Furthermore, we propose a relation impression evaluation algorithm to evaluate and manage relational impressions. We developed a prototype and employed 21 volunteers to verify the functionalities of the SRIM scheme. The evaluation results show the effectiveness and efficiency of our proposed scheme.
Although many different views of social media coexist in the field of information systems (IS), such theories are usually not introduced in a consistent framework based on philosophical foundations. This paper introduces the dimensions of lifeworld and consideration of others. The concept of lifeworld includes Descartes’ rationality and Heidegger’s historicity, and consideration of others is based on instrumentalism and Heidegger’s “being-with.” These philosophical foundations elaborate a framework where different archetypal theories applied to social media may be compared: Goffman’s presentation of self, Bourdieu’s social capital, Sartre’s existential project, and Heidegger’s “shared-world.” While Goffman has become a frequent reference in social media, the three other references are innovative in IS research. The concepts of these four theories of social media are compared with empirical findings in IS literature. While some of these concepts match the empirical findings, some other concepts have not yet been investigated in the use of social media, suggesting future research directions.
Given the increasingly notable segmentation of underground space by existing subway tunnels, it is difficult to effectively and adequately develop and utilize underground space in busy parts of a city. This study presents a combined construction technology that has been developed for use in underground spaces; it includes a deformation buffer layer, a special grouting technique, jump excavation by compartment, back-pressure portal frame technology, a reinforcement technique, and the technology of a steel portioning drum or plate. These technologies have been successfully used in practical engineering. The combined construction technology presented in this paper provides a new method of solving key technical problems in underground spaces in effectively used cross-subway tunnels. As this technology has achieved significant economic and social benefits, it has valuable future applications.
The total length of the second stage of the water supply project in the northern areas of the Xinjiang Uygur Autonomous Region is 540 km, of which the total length of the tunnels is 516 km. The total tunneling mileage is 569 km, which includes 49 slow-inclined shafts and vertical shafts. Among the tunnels constructed in the project, the Ka-Shuang tunnel, which is a single tunnel with a length of 283 km, is currently the longest water-conveyance tunnel in the world. The main tunnel of the Ka-Shuang tunnel is divided into 18 tunnel-boring machine (TBM) sections, and 34 drilling-and-blasting sections, with 91 tunnel faces. The construction of the Ka-Shuang tunnel has been regarded as an unprecedented challenge for project construction management, risk control, and safe and efficient construction; it has also presented higher requirements for the design, manufacture, operation, and maintenance of the TBMs and their supporting equipment. Based on the engineering characteristics and adverse geological conditions, it is necessary to analyze the major problems confronted by the construction and systematically locate disaster sources. In addition, the risk level should be reasonably ranked, responsibility should be clearly identified, and a hierarchical-control mechanism should be established. Several techniques are put forward in this paper to achieve the objectives mentioned above; these include advanced geological prospecting techniques, intelligent tunneling techniques combined with the sensing and fusion of information about rock parameters and mechanical parameters, monitoring and early-warning techniques, and modern information technologies. The application of these techniques offers scientific guidance for risk control and puts forward technical ideas about improving the efficiency of safe tunneling. These techniques and ideas have great significance for the development of modern tunneling technologies and research into major construction equipment.
The New Austrian Tunneling Method (NATM) has been widely used in the construction of mountain tunnels, urban metro lines, underground storage tanks, underground power houses, mining roadways, and so on. The variation patterns of advance geological prediction data, stress-strain data of supporting structures, and deformation data of the surrounding rock are vitally important in assessing the rationality and reliability of construction schemes, and provide essential information to ensure the safety and scheduling of tunnel construction. However, as the quantity of these data increases significantly, the uncertainty and discreteness of the mass data make it extremely difficult to produce a reasonable construction scheme; they also reduce the forecast accuracy of accidents and dangerous situations, creating huge challenges in tunnel construction safety. In order to solve this problem, a novel data service system is proposed that uses data-association technology and the NATM, with the support of a big data environment. This system can integrate data resources from distributed monitoring sensors during the construction process, and then identify associations and build relations among data resources under the same construction conditions. These data associations and relations are then stored in a data pool. With the development and supplementation of the data pool, similar relations can then be used under similar conditions, in order to provide data references for construction schematic designs and resource allocation. The proposed data service system also provides valuable guidance for the construction of similar projects.
An increasing number of tunnels are being constructed with tunnel-boring machines (TBMs) due to the increased efficiency and shorter completion time resulting from their use. However, when a TBM encounters adverse geological conditions in the course of tunnel construction (e.g., karst caves, faults, or fractured zones), disasters such as water and mud inrush, collapse, or machine blockage may result, and may severely imperil construction safety. Therefore, the advance detection of adverse geology and water-bearing conditions in front of the tunnel face is of great importance. This paper uses the TBM tunneling of the water conveyance project from Songhua River as a case study in order to propose a comprehensive forward geological prospecting technical system that is suitable for TBM tunnel construction under complicated geological conditions. By combining geological analysis with forward geological prospecting using a three-dimensional (3D) induced polarization method and a 3D seismic method, a comprehensive forward geological prospecting technical system can accurately forecast water inrush geo-hazards or faults in front of the TBM tunnel face. In this way, disasters such as water and mud inrush, collapse, or machine blockage can be avoided. This prospecting technical system also has reference value for carrying out the forward prospecting of adverse geology for potential TBM tunneling and for ensuring that a TBM can work efficiently.
A principal difficulty with island megalopolises is the transport problem, which results from limited surface land on an already developed island, on which roads and car parking can be placed. This limitation leads to traffic jams on the small number of roads and to intrusive car parking in any available surface location, resulting in safety issues. The city of Vladivostok is located on the Muravyov-Amursky Peninsula in the Russia Far East region (the Primorsky Krai). This city is essentially the third capital of Russia because of its important geopolitical location. To address the car traffic problems in Vladivostok, and because of the absence of places to build new roads, the city administration has proposed the usage of the beaches and waterfronts along the sea coast in this regard. This decision is in sharp conflict with Vladivostok’s ecological and social aspirations to be recognized as a world-class city. It also neglects the lessons that have been learned in many other waterfront cities around the world, as such cities have first built aboveground waterfront highways and later decided to remove them at great expense, in order to allow their citizens to properly enjoy the environmental and historical assets of their waterfronts. A key alternative would be to create an independent tunneled transport system along with added underground parking so that the transport problems can be addressed in a manner that enhances the ecology and livability of the city. A comparison of the two alternatives for solving the transport problem, that is, underground versus aboveground, shows the significant advantages of the independent tunnel system. Complex efficiency criteria have been developed in order to quantify the estimation of the alternative variants of the Vladivostok transport system. It was determined that the underground project is almost 1.8 times more advantageous than the aboveground alternative.
In the past 20 years, great progress has been achieved in China in the construction of concrete-filled steel tube (CFST) arch bridges and concrete arch bridges with a CFST skeleton. The span of these bridges has been increasing rapidly, which is rare in the history of bridge development. The large-scale construction of expressways and high-speed railways demands the development of long-span arch bridges, and advances in design and construction techniques have made it possible to construct such bridges. In the present study, the current status, development, and major innovative technologies of CFST arch bridges and concrete arch bridges with a CFST skeleton in China are elaborated. This paper covers the key construction technologies of CFST arch bridges, such as the design, manufacture, and installation of steel tube arch trusses, the preparation and pouring of in-tube concrete, and the construction of the world’s longest CFST arch bridge—the First Hejiang Yangtze River Bridge. The main construction technologies of reinforced concrete arch bridges are also presented, which include cable-stayed fastening-hanging cantilever assembly, adjusting the load by means of stay cables, surrounding the concrete for arch rib pouring, and so forth. In addition, the construction of two CFST skeleton concrete arch bridges—the Guangxi Yongning Yong River Bridge and the Yunnan-Guangxi Railway Nanpan River Bridge—is discussed. CFST arch bridges in China have already gained a world-leading position; with the continuous innovation of key technologies, China will become the new leader in promoting the development of arch bridges.
Sea level rise (SLR) is a major projected threat of climate change that is expected to affect developing coastal cities located in estuarine delta regions. Shanghai is one such city, being located in the Yangtze River Delta (YRD). It is difficult, however, for decision-makers to implement adaptation due to the uncertain causes, magnitudes, and timings of SLR behaviors. This paper attempts to map the causes and magnitudes of SLR behaviors on a decadal scale. We analyze the tidal level records from 11 tidal gauge stations and the corresponding bathymetry measurements around these stations since 1921. We identify three new SLR behaviors along the Shanghai coast due to anthropogenic geomorphologic changes (AGCs), besides the well-known eustatic sea level rise (ESLR), tectonic subsidence (TS), and urban land subsidence (ULS). The first new behavior is regional sea level rise (RSLR), which occurs as a result of land reclamation and deep waterway regulation. The second is regional sea level fall (RSLF), which occurs because the channel bed is eroded due to sediment supply decline in the river catchment. The last SLR behavior is local tidal datum rise (LTDR). Thus, we project that the magnitude of SLR for the Shanghai coast ranges from 10 cm to 16 cm from 2011 to 2030. Clarifying SLR behaviors is important to aid local decision-makers in planning structural and non-structural measures to combat escalating flood damage costs in an estuarine delta system; this field is full of future challenges.
