As electronic detection technology advances and the need for secure communication in terminal devices grows, traditional methods such as spread spectrum and overlapping communication are becoming ...inadequate for covert satellite communication. This paper introduces an enhanced approach by integrating the CA security protocol with satellite overlapping clandestine communication techniques. A network protocol stack, based on the TCP/IP reference model, is developed with a focus on the network layer and the data link layer. This study leverages the CSMA/CA key access technology at the link layer and proposes a method to mitigate interference in overlapping communication. It employs the LSTM algorithm to hypothesize the spectral posture of covert signals. It utilizes the least fitting degree method to minimize the impact of cover signals on the sub-spectrum of covert signals. The efficacy of this approach is assessed through simulation experiments, which provide a statistical analysis of the generated satellite overlapping covert signals. The results demonstrate a high anti-jamming probability, with complex envelope amplitude values ranging from 0.5 to 1.0, nearing a likelihood of 1. Additionally, the covert signals maintain a noise power spectral density similarity in the −2 to 2 Hz range, thereby enhancing their camouflaging effect.
As a basic query function, range query has been exploited in many scenarios such as SQL retrieves, location-based services, and computational geometry. Meanwhile, with explosive growth of data ...volume, users are increasingly inclining to store data on the cloud for saving local storage and computational cost. However, a long-standing problem is that the user's data may be completely revealed to the cloud server because it has full data access right. To cope with this problem, a frequently-used method is to encrypt raw data before outsourcing them, but the availability and operability of data will be reduced significantly. In this paper, we propose an efficient and geometric range query scheme (EGRQ) supporting searching and data access control over encrypted spatial data. We employ secure KNN computation, polynomial fitting technique, and order-preserving encryption to achieve secure, efficient, and accurate geometric range query over cloud data. Then, we propose a novel spatial data access control strategy to refine user's rights in our EGRQ. To improve the efficiency, R-tree is adopted to reduce the searching space and matching times in whole search process. Finally, we theoretically prove the security of our proposed scheme in terms of confidentiality of spatial data, privacy protection of index and trapdoor, and the unlinkability of trapdoors. In addition, extensive experiments demonstrate the high efficiency of our proposed model compared with existing schemes.
Dynamic recrystallization (DRX), heterogeneous deformation and mechanical responses at the levels of single grain and grains aggregate concurrently occur and interact with each other in hot-working ...processes of titanium alloys. The interaction has been partly taken into account in our previous work by creating a crystal plasticity finite element method (CPFEM) with DRX considered, but the morphological characteristics of DRX that are crucial to the performance of the formed part failed to be captured. In addition, the existing visualization approaches (e.g., cellular automata, CA) for modeling the morphology evolution treated DRX as a product of deformation and thus separated the interaction. To address these issues, combining the advantages of the above two methods, this work proposes a new concept by treating the morphological evolution of DRX as one intrinsic part of the constitutive behavior, which is realized by establishing a 3D CACPFEM model through the full coupling of CA and CPFEM. During the modeling, the CA algorithm accounting for the DRX evolution is built into the CPFEM framework that accounts for multiscale heterogeneous deformation. Based on the microstructure-based 3D grids acting as both finite elements and cells and the explicit consideration of grain boundary softening, the heterogeneous deformation and the induced non-uniform distribution of the dislocation density at the levels of the slip system, grain interior and boundary are calculated with CPFEM. The obtained results dominate the evolution of DRX synchronizing with the deformation, which is calculated with CA through a semi-probabilistic switch rule that considers the effects of the deformed grain morphology and misorientation between the adjacent matrix grain and recrystallized grain. The DRX-induced changes in the dislocation density, grain boundary, and grain size are returned to CPFEM to determine the slip resistance of the dislocations. Consequently, not only the mechanical response but also the subsequent plastic deformation is determined. With this model, the coupled effect of the heterogeneous deformation, mechanical response and DRX microstructural evolution during the isothermal compression of the TA15 alloy is well captured and analyzed, which is verified by experiments. It is shown that the framework of this model allows the integrated prediction of the macroscale forming, mesoscale deformation mechanism and microscale microstructural evolution of materials, and that it is capable of being extended and applied to other problems (e.g., phase transformation and lamellar spheroidization) in the hot-working processes of materials.
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•A new idea treating DRX as one intrinsic part of constitutive behavior is proposed.•A 3D microstructure-based CACPFEM is created by the full coupling of CA and CPFEM.•Interaction of deformation-microstructure evolution-mechanical response is captured.
Graphene, which has good electrical/thermal conductivity, excellent mechanical properties and large specific surface area, is promising in various fields. However, the easy aggregation of graphene ...limits its application. Silica, including mesoporous silica, has potential applications in many fields due to its characteristics of good chemical stability, easy modification, high-temperature resistance and low cytotoxicity. The combination of the two exciting materials to form silica/graphene (SiO2/G) composites not only overcomes the aggregation problem but also leads to enhanced or even new physical/chemical properties and high performance due to their synergic effects. Designing and constructing a reasonable structure of SiO2/G composite material is vital for its practical application. In this review, the synthesis strategy of SiO2/G-based composites is highlighted. This strategy includes growing silica layers on graphene nanosheets to form sandwich structures, growing silica spheres on graphene nanosheets, and wrapping graphene layers on silica spheres. This review focuses on the superior application of the nanocomposites in the fields of energy storage, catalysis, environmental protection, biomedicine and polymer composites. Furthermore, the challenges and the new future research directions of these emerging nanocomposites are provided.
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•Recent progress in silica/graphene composites is reviewed.•Advantages and current applications of silica/graphene composites are described.•Strategies to fabricate silica/graphene composites are evaluated.•Enhanced properties are obtained from the synergic effects of graphene and silica.
Low temperature district heating with reduced network supply and return temperature provides better match of the low quality building heating demand and the low quality heating supply from waste heat ...or renewable energy. In this paper, a hypothetical low temperature district heating network is designed to supply heating for 30 low energy detached residential houses. The network operational supply/return temperature is set as 55 °C/25 °C, which is in line with a pilot project carried out in Denmark. Two types of in-house substations are analyzed to supply the consumer domestic hot water demand. The space heating demand is supplied through floor heating in the bathroom and low temperature radiators in the rest of rooms. The network thermal and hydraulic conditions are simulated under steady state. A district heating network design and simulation code is developed to incorporate the network optimization procedure and the network simultaneous factor. Through the simulation, the overall system energy and exergy efficiencies are calculated and the exergy losses for the major district heating system components are identified. Based on the results, suggestions are given to further reduce the system energy/exergy losses and increase the quality match between the consumer heating demand and the district heating supply.
Sediment quality guidelines (SQGs) are a fundamental component of sediment quality assessment framework, frequently used in the first tier of assessment to predict the potential risks of contaminants ...in sediment. A recognized weakness of SQGs concerns the bioavailability of sediment contaminants, which may vary considerably with different physical-chemical properties. To better evaluate the ecological risks and predict the toxicity of the heavy metals (Cd, Cu, Ni, Pb, Zn) in the sediments of Haihe River of China, the risk quotients derived from total metal concentrations and SQG values were modified using multiple linear regressions with sediment properties, i.e. total organic carbon (TOC), acid-volatile sulfide (AVS), and particle size distribution (PSD). Then, the sediment toxicity was tested with the benthic organisms of chironomids and tubificids, and the relationships between the observed toxicity with the modified risk quotients were investigated. We found that the risk quotient modified with TOC and AVS displayed significantly improved relationship with the toxicity (p < 0.001) compared to the original risk quotient without modification (p = 0.062–0.074 > 0.05). Risk assessment indicated that although the heavy metals in the sediments of Haihe River of China are at a relatively low level, potential ecological risks caused by Ni and Zn still exist in some area, especially in the lower reaches along the estuary. The results indicated that the risk quotient and SQG values modified with sediment properties are promising for risk assessment of the metal contaminants in sediments.
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•Sediment properties influence the bioavailability and toxicity of heavy metals in the sediments.•Risk quotients based on sediment quality guidelines did not correlate well with sediment toxicity.•Risk quotients modified by sediment properties displayed significantly improved correlations.•Potential ecological risks caused by sediment heavy metals exist in Haihe River of China.
Electrically-assisted manufacturing (EAM) is used for forming difficult-to-form materials such as the Ni-based superalloy in recent years. Compared to the hot deformation, EAM is a more convenient ...and effective method. However, the mechanism for the macro and micro behaviors of the materials with EAM is still a controversial issue. Thus, in this work, the electrically-assisted (EA) tension tests of the Ni-based superalloy were carried out with different parameters, and the macro and micro behaviors of the material were studied and discussed. Besides the reduction of yield strength (YS) and flow stress, the Portevin-Le Chatelier (PLC) effect appears during the EA tension and is more significant than that during the hot tension at the same temperature. The critical temperature for the PLC effect is the same with different strain rates under a fixed peak current density. Essentially, the directional distribution of dislocations and the earlier precipitation of the second phase can also be the main causes for the PLC effect. According to the existing theories and the electric treatment experiments that the higher percentage of defects or the second phase in metal result in more significant temperature rise, the local high temperature which induced by local Joule heating effect exists in the critical areas. It may be the main mechanism resulting in the macro and micro behaviors of alloy during the EA tension. Furthermore, recrystallization is experimentally observed when the measured temperature is much lower than the critical temperature for recrystallization due to the local Joule heating effect.
•More obvious PLC effect during the EA tension than that in hot tension.•Directional distribution of dislocations is observed during the EA tension.•The second phase precipitates earlier with pulse current applying.•The mechanism of the uncommon phenomenon is specified as local Joule heating.
Secure Multi-Party Computation (SMPC) is a generic cryptographic primitive that enables distributed parties to jointly compute an arbitrary functionality without revealing their own private inputs ...and outputs. Since Yao’s seminal work in 1982, 30 years of research on SMPC has been conducted, proceeding from pure theoretical research into real-world applications. Recently, the increasing prevalence of the newly emerging technologies such as cloud computing, mobile computing and the Internet of Thing has resulted in a re-birth of SMPC’s popularity. This has occurred mainly because, as a generic tool for computing on private data, SMPC has a natural advantage in solving security and privacy issues in these areas. Accordingly, many application-oriented SMPC protocols have been constructed. This paper presents a comprehensive survey on the theoretical and practical aspects of SMPC protocols. Specifically, we start by demonstrating the underlying concepts of SMPC, including its security requirements and basic construction techniques. Then, we present the research advances regarding construction techniques for generic SMPC protocols, and also the cutting-edge approaches to cloud-assisted SMPC protocols. Then, we summarize the concrete application-oriented protocols that are currently available, and finally, we present a discussion of the current literature and conclude this survey.
The conventional coal-to-methanol (CTM) process suffers from large CO2 emission. The additional hydrogen supplement to the CTM process can effectively improve the carbon utilization efficiency. ...However, the CO2 emission intensity and cost of existing hydrogen production technologies based on fossil resources are extremely high. This paper proposes a green hydrogen (GH) production integrated with CO2 utilization of the CTM process. The new process is called GH-CTM process, which can achieve intensive material coupling, improve carbon efficiency, and increase methanol productivity. Process modeling, parameters optimization, and simulation results showed that the energy efficiency, CO2 emission, and methanol output of the proposed process were 10.52% higher, 85.64% lower, and 124.67% higher than those of the conventional CTM process, respectively; moreover, the production cost of the proposed process was 23.95% lower than that of the CTM process, and the payback period of investment (2.8 years) was lower than that of the CTM process (7.2 years). In addition, the internal rate of return of the proposed process was increased by 47.37% compared with that of traditional CTM process. The proposed process provides a promising method for the introduction of green hydrogen to realize CO2 utilization and the sustainable conversion of coal to chemicals.
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•Green hydrogen integrated with CO2 utilization of CTM process is proposed.•Methanol production is increased by 124.67% through CO2 utilization.•Green hydrogen supplement makes 85.64% reduction of CO2 emission and 10.52% increase of energy efficiency.•Production cost is decreased by 23.95% resulting of 47.37% increase of internal rate of return.•Introduction of green hydrogen realizes CO2 utilization and clean conversion of coal.
With the ongoing development and improvement of deep learning technology, autonomous vehicles (AVs) have made tremendous progress in recent years. Despite its great potential, AV supported by deep ...learning technology still faces numerous security threats, which prevent AV from being putting into large-scale practice. Aiming at this challenging situation, in this paper, we would like to exploit two attacks against deep learning algorithms in traffic sign recognition system by leveraging particle swarm optimization. Specifically, we first exploit the PAPSO (poisoning attack with particle swarm optimization) which focuses on the training process of the deep learning algorithms in the traffic sign recognition system, i.e., the attacker injects crafted samples into the training dataset, causing a reduction in classification accuracy of the traffic sign recognition system. Then, we also explore the EAPSO (evasion attack with particle swarm optimization) which on the other hand focuses on the interference process of the deep learning algorithms, i.e., the attacker adds some hardly perceptible perturbations to the targeted test sample, leading to a misclassification on it. Extensive experiments are conducted to shed light on the effectiveness of our attacks, and some corresponding defense strategies are also presented.
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