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To address the issues of limited one-time loading capacity, single functionality, and low automation level in existing square straw bale pickers, a large automated square straw bale pick-up-and-stack truck that integrates picking, stacking, transporting, and bundling functions has been developed, combining the technical advantages of one-time field removal and storage of bales. We innovatively designed a side-pulling traction mechanism that can realize the rapid transition between the transporting state and working state of the machine; a picking device that can complete the continuous action of forking, lifting, turning positioning, and de-forking; and a bundling device that can realize the adjustment of the attitude of square straw bales. Response surface tests were conducted on the prototype to determine the key structural and operational parameters, using the bundle completion rate and regular bale rate as evaluation indicators. Regression and significance tests were performed on the machine’s forward speed, chassis frame offset, and the ground clearance of the fork tine to determine the influence and priority of these factors on the evaluation indicators. Through multi-objective function optimization of the regression model, the optimal parameter combination was found to be a machine forward speed of 15.5 km/h, a chassis frame offset of 2126 mm, and a fork tine ground clearance of 225 mm, resulting in a bundle completion rate of 98.85% and a regular bale rate of 96.96%. Subsequent field tests with the optimized parameters showed that at a machine forward speed of 15.5 km/h, a chassis frame offset of 2126 mm, and a fork tine ground clearance of 225 mm, the bundle completion rate was 98.37% and the regular bale rate was 95.83%, meeting the relevant design requirements. This study can provide a reference for the design and development of straw collection and storage machinery.

We propose and verify a method for analyzing the randomization capacity in a 160 km quantum noise randomized cipher system with different data modulation formats. The randomization capacity is defined as the difference in mutual information between Alice and Bob while the randomization level is at 0 and at its maximum, under the condition of error-free transmission. Our experimental analysis examines the capacity of quantum noise randomized cipher systems under different optical signal-to-noise ratios for each modulation format. Additionally, we analyze the noise masking values while the randomization reaches its capacity. The experimental results indicate that the binary phase shift-keying-based quantum noise randomized cipher system achieves the highest randomization capacity and highest noise masking value.

The use of recycled asphalt mixtures in regions with seasonal freeze-thaw cycles is becoming more popular. However, strict requirements for low-temperature cracking resistance limit their widespread application. This study designed thirteen types of recycled asphalt mixtures to explore factors affecting low-temperature performance in seasonal freeze-thaw regions and potential optimization methods. The three-point bending test assessed the low-temperature cracking performance of mixtures with varying recycled asphalt pavement (RAP) content, asphalt-aggregate ratios, asphalt types, and gradations under both conventional and freeze-thaw conditions. Results show that destructive strain and fracture energy decrease with higher RAP content, but increase with higher asphalt-aggregate ratios and 4.75 mm sieve passing rates. Adding rubber powder significantly enhances both destructive strain and fracture energy. Furthermore, the destructive strain remains insensitive to factors under both and freeze-thaw conditions, while fracture energy effectively distinguishes differences in low-temperature crack resistance. Analysis of variance reveals that RAP content, asphalt-aggregate ratio, asphalt type, and gradation significantly affect fracture energy after freeze-thaw cycles. Optimizing gradation is recommended to improve low-temperature performance of recycled asphalt mixtures in freeze-thaw regions.

Driven by economic interests, adding adulterations in chili powder is a problem which threatens people’s health. Thanks to its nondestructive, rapid, and portable advantages, electronic nose has more potential to be used for adulteration detection than the traditional methods. An approach for identifying the adulterants in chili powder was proposed in this paper. Firstly, an electronic nose system with 10 gas sensors was designed, and then the response images were drawn based on the response signals of the electronic nose. Afterwards, gas features were extracted from those response images by using a histogram of oriented gradients (HOG) algorithm. Finally, an SVM-based identification model was constructed to achieve the identification of plant adulterants in chili powder. The experimental results showed that the identification accuracy of the adulterant categories (almond shell, red beetroot, and tomato peel) based on the HOG features could reach up to 98.3%, and the identification results for adulterant content were 94.2%, 93.3%, and 95%, respectively. Furthermore, in order to compare the efficiency of the proposed identification approach, the widely used model AlexNet was also investigated and discussed.

The computing power network (CPN) is expected to realize the efficient provisioning of heterogeneous computing power through the collaboration between cloud computing and edge computing. Heterogeneous computing resources consist of CPU, GPU, and other types of computing power. Different types of applications may have diverse requirements for heterogeneous computing resources, such as general applications, CPU-intensive applications, and GPU-intensive applications. Service providers are concerned about how to dynamically provide heterogeneous computing resources for different applications in a cost-effective manner, and how to deploy more applications as much as possible with limited resources. In this paper, the concept of the benefit–cost ratio (BCR) is proposed to quantify the usage efficiency of CPU and GPU in CPNs. An application-aware resource allocation (AARA) algorithm is designed for processing different types of applications. With massive simulations, we compare the performance of the AARA algorithm with a benchmark. In terms of blocking probability, resource utilization, and BCR, AARA achieves better performance than the benchmark. The simulation results indicate that more computing tasks can be accommodated by reducing 3.7% blocking probability through BCR-based resource allocation.

Establishing an excellent recycling mechanism for containers is of great importance for environmental protection, so many technical approaches applied during the whole recycling stage have become popular research issues. Among them, classification is considered a key step, but this work is mostly achieved manually in practical applications. Due to the influence of human subjectivity, the classification accuracy often varies significantly. In order to overcome this shortcoming, this paper proposes an identification method based on a Recursive Feature Elimination-Light Gradient Boosting Machine (RFE-LightGBM) algorithm using electronic nose. Firstly, odor features were extracted, and feature datasets were then constructed based on the response data of the electronic nose to the detected gases. Afterwards, a principal component analysis (PCA) and the RFE-LightGBM algorithm were applied to reduce the dimensionality of the feature datasets, and the differences between these two methods were analyzed, respectively. Finally, the differences in the classification accuracies on the three datasets (the original feature dataset, PCA dimensionality reduction dataset, and RFE-LightGBM dimensionality reduction dataset) were discussed. The results showed that the highest classification accuracy of 95% could be obtained by using the RFE-LightGBM algorithm in the classification stage of recyclable containers, compared to the original feature dataset (88.38%) and PCA dimensionality reduction dataset (92.02%).

Quantum key distribution (QKD) is a promising technique to resist the threat against quantum computers. However, the high loss of quantum signals over a long-distance optical fiber is an obstacle for QKD in the intercontinental domain. In this context, the quantum satellite network is preferred over the terrestrial quantum optical network. Due to the mobility of satellites, the satellite topology is dynamic in the quantum satellite network, which remains a challenge for routing. In hybrid geostationary-earth-orbit (GEO)/low-earth-orbit (LEO) quantum satellite networks, the lack of an efficient scheduling scheme for GEO/LEO satellites also limits the construction of quantum satellite networks. Therefore, this paper provides a topology abstraction-based routing scheme for secret-key provisioning, where the dynamic physical topology is translated into a quasi-static abstracted topology. This scheme contributes to saving the precious secret key resources. In order to improve the success probability of long-distance QKD requests, three novel resource-scheduling heuristic algorithms are proposed in hybrid GEO/LEO quantum satellite networks. Simulation results indicate that the proposed algorithms can improve the success probability of QKD requests by 47% compared to the benchmark.

The inherent cross-sensitivity of semiconductor gas sensors makes them extremely challenging to accurately detect mixed gases. In order to solve this problem, this paper designed an electronic nose (E-nose) with seven gas sensors and proposed a rapid method for identifying CH4, CO, and their mixtures. Most reported methods for E-nose were based on analyzing the entire response process and employing complex algorithms, such as neural network, which result in long time-consuming processes for gas detection and identification. To overcome these shortcomings, this paper firstly proposes a way to shorten the gas detection time by analyzing only the start stage of the E-nose response instead of the entire response process. Subsequently, two polynomial fitting methods for extracting gas features are designed according to the characteristics of the E-nose response curves. Finally, in order to shorten the time consumption of calculation and reduce the complexity of the identification model, linear discriminant analysis (LDA) is introduced to reduce the dimensionality of the extracted feature datasets, and an XGBoost-based gas identification model is trained using the LDA optimized feature datasets. The experimental results show that the proposed method can shorten the gas detection time, obtain sufficient gas features, and achieve nearly 100% identification accuracy for CH4, CO, and their mixed gases.

As the acquisition unit of gas information, the sensor array directly determines the overall performance of the electronic nose system (E-nose). This paper proposed a new method for optimizing the sensor array. Firstly, four evaluation indicators (sensitivity, selectivity, correlation, and repeatability) were selected to evaluate the sensor array. Subsequently, different evaluation indicators were assigned different weight values according to their contributions to the overall performance of the E-nose. Finally, a comprehensive evaluation model was established based on the EWM-TOPSIS algorithm to optimize the sensor array. In order to verify the effectiveness of the as-proposed model, it was applied to the optimization of the E-nose sensor array composed of 10 gas sensors, and the influence of the sensor array optimization on the gas recognition ability of the E-nose was investigated. The experimental results showed that the optimized sensor array can identify the CO-CH4 gas mixtures with an accuracy of 96.5%, which a significant improvement compared with the accuracy of 78.3% before the sensor array optimization.

This study aims to develop a new index to evaluate the low-temperature cracking performance (LTCP) of recycled asphalt mixtures. To achieve this, the assumption that fracture energy has limitation in evaluating the LTCP of mixtures was put forward firstly. To reveal this limitation theoretically, a concept of energy absorption rate that characterized the fracture energy of the mixtures was then given. Thirdly, an equivalent fracture temperature (EFT) corresponding to the critical cracking temperature in a thermal stress restrained specimen test (TSRST) was proposed to evaluate the LTCP of mixtures based on a three-point bending beam (3PBB) test. Finally, some data derived from previous work were collected to verify the proposed assumption, and the 3PBB test and TSRST were conducted to investigate the LTCP of five recycled mixtures with different reclaimed asphalt pavement (RAP) material contents and to verify the rationality of the proposed EFT. The results confirmed that fracture energy had some limitations in predicting the LTCP of mixtures. The EFT was as accurate as the critical cracking temperature in evaluating the LTCP of mixtures. Compared to fracture energy and critical cracking temperature, EFT had bigger absolute change and relative change between different mixtures, meaning it was better to differentiate the LTCP of mixtures. Compared to failure strain, EFT was also more definite and less variable when processed by different data analysts, meaning it was more objective.

Mixed-Fixed/Flex-Grid Optical Networks (MFGONs) are a new paradigm that emerged during the brown-field migration from fixed-grid Wavelength Division Multiplexing (WDM) optical networks to flex-grid Elastic Optical Networks (EONs). Based on the flex-grid, we can accommodate IP traffic directly to the optical layer by configuration. Considering the different granularities of spectrum resources and complex constraints in MFGONs, it is difficult to apply Routing and Wavelength/Spectrum Allocation (RWA/RSA) algorithms proposed in either fixed-grid or flex-grid optical networks. This paper first proposes two concepts, i.e., Link Spectrum Compactness (LSC) and Radiancy of Nodes (RoNs), to evaluate different scenarios of candidate paths for the end-to-end requests in MFGONs. Then, based on these two concepts, a Spectrum Entropy (SE) model is proposed in MFGONs. Here, the SE is the metric that combines LSC and RoNs to judge the fragmentation of network resources, and the value of SE is treated as the cost of candidate paths during the RSA operation. Finally, an SE-minimized RSA algorithm in MFGONs is designed. Simulation results prove that the proposed algorithm can effectively reduce the Bandwidth Blocking Ratio (BBR) and increase the revenues for upgrading the nodes compared to the state-of-the-art RSA algorithm. Particularly, the performance improvement is more obvious for highly connected networks.

A high-speed centrifugal pump with a fully sealed structure has the advantages of a small size, no external leakage, and being pollution-free. The inner leakage passage of a pump with a fully sealed structure includes the tip clearance and the hub clearance. The hub clearance, the lubrication passage of the bearing, and the clearance between the stator and the rotor of the built-in motor constitute the internal flow channel. As a consequence of hub leakage, the complexity of the flow field increases and performance of the pump is affected. However, hub leakage also lubricates the bearing and cools the motor by flowing through the internal flow channel. To obtain the actual flow field distribution and external characteristics of the pump, a coupling calculation based on a conventional CFX simulation and MATLAB was carried out. The results show that hub leakage promotes an increase in tip leakage and changes the distribution of the main flow field. Moreover, hub leakage also significantly affects the efficiency of the pump. Compared with hub leakage, the internal flow has a greater impact on the performance of the pump. The numerical simulation results of the internal flow model are similar to the experimental results, with the maximum absolute error of the head at 0.3 m and the maximum absolute error of the efficiency at 1.7%, indicating that the internal flow model is effective at predicting the performance of the high-speed centrifugal pump with a fully sealed structure.

Quantum key distribution (QKD) can protect the exchange process of confidential information between communicating parties. By using the basic principles of quantum mechanics and combined with “one-time pad” cipher encryption, information can be unconditionally secure. The BB84 protocol first describes the method of transmitting information by photon polarization state, and it expounds the transmission process of services between trusted relays. However, due to the defects of real experimental devices, there are security vulnerabilities in QKD in a real system. The birth of measurement-device-independent quantum key distribution (MDI-QKD) protocol solves the problem, providing immunity to hacker attacks at the end of the detector. It can enable both sides of the transmission service to establish a connection and generate secret keys through an untrusted relay node to ensure information security. However, the types and properties of link nodes in quantum key distribution network (QKDN) based on partially trusted relay are more complex, which can easily result in network fault. Therefore, how to prevent the impact of failure on QKDN has become an urgent problem. In this paper, we propose a protection scheme for QKDN with partially trusted relays. The method deals with trusted and untrusted relays differently and constructs the working and protection paths of the secret key for each service. It reduces resource conflict between the protection and working paths by establishing a key protection threshold, which realizes the resource trade-off between the two factors. Simulation results show that the scheme provides effective protection to the services, and it improves the stability and reliability of QKDN based on partially trusted relay.

With the development of optical networks technology, broad attention has been paid to flexible grid technology in optical networks due to its ability to carry large-capacity information as well as provide flexible and fine-grained services through on-demand spectrum resource allocation. However, a one-time green-field deployment of a flexible grid network may not be practical. The transition technology called the fixed/flex-grid optical networks is more applicable and highly pragmatic. In such network, many nodes would likely be upgraded from a fixed-grid to flex-grid. In fact, dynamic service provisioning during the process of a node upgrade in fixed/flex-grid optical networks have become a challenge because the service connection can be easily interrupted, which leads to considerable data loss because of node upgrade. To overcome this challenge, we propose a brown-field migration aware routing and spectrum assignment (BMA-RSA) algorithm in fixed/flex-grid optical networks. The aim is to construct a probabilistic migration label (PML) model. The well-designed label setting of PML can balance the relationship between distance and node-upgrade probability. Dynamic service provisioning operations are undertaken based on the PML model to achieve a migration-aware dynamic connection before network migration occurs. We also evaluate the performance of different service provisioning strategies under different traffic models. The simulation results show that the BMA-RSA algorithm can achieve: (1) the tradeoff between distance and node upgrade probability during the process of service provisioning; (2) lower service interruption compared with the traditional non-migration aware K-shortest-path routing and spectrum assignment algorithm.

In the era of the interconnection of all things, the security of the Internet of Things (IoT) has become a new challenge. The theoretical basis of unconditional security can be guaranteed by using quantum keys, which can form a QKD network-based security protection system of quantum Internet of Things (Q-IoT). However, due to the low generation rate of the quantum keys, the lack of a reasonable key allocation scheme can reduce the overall service quality. Therefore, this paper proposes a dynamic on-demand key allocation scheme, named DDKA-QKDN, to better meet the requirements of lightweight in the application scenario of Q-IoT and make efficient use of quantum key resources. Taking the two processes of the quantum key pool (QKP) key allocation and the QKP key supplement into account, the scheme dynamically allocates quantum keys and supplements the QKP on demand, which quantitatively weighs the quantum key quantity and security requirements of key requests in proportion. The simulation results show that the system efficiency and the ability of QKP to provide key request services are significantly improved by this scheme.

Increasing the content of reclaimed asphalt pavement material (RAP) in hot-mix recycled asphalt mixture (RHMA) with a satisfactory performance has been a hot topic in recent years. In this study, the performances of Trinidad lake asphalt (TLA), virgin asphalt binder, and aged asphalt binder were first compared, and then the modification mechanism of TLA on virgin asphalt and aged asphalt was explored. Furthermore, the RHMA was designed in accordance with the French norm NF P 98-140 containing 50% and 100% RAP, and their high-temperature stability, low-temperature cracking resistance, and fatigue performances were tested to be compared with the conventional dense gradation AC-20 asphalt mixture. The results show that the addition of TLA changes the component proportion of virgin asphalt binder, but no new functional groups are produced. The hard asphalt binder modified by TLA has a better rutting resistance, while the fatigue and cracking resistance is lower, compared to both aged and virgin asphalt. The high-modulus design concept of RHMA is a promising way to increase the RAP content in RHMA with acceptable performance. Generally, the RHMA with 50% RAP has similar properties to AC-20. And, when the RAP content reaches 100%, the high- and low-temperature performance and anti-fatigue performance of RHMA are better than AC-20 mixture. Thus, recycling aged asphalt using hard asphalt binder for hot-mixing recycled asphalt mixture to increase the RAP content is feasible.

Currently, with the continuous advancement of network and communication technology, the amount of data carried by the optical network is very huge. The security of high-speed and large-capacity information in optical networks has attracted more and more attention. Quantum key distribution (QKD) provides information-theoretic security based on the laws of quantum mechanics. Introducing QKD into an optical network can greatly improve the security of the optical network. In order to reduce the cost of deployment on QKD infrastructure, quantum signals in QKD and classical signals in optical networks are multiplexed in the same fiber by wavelength-division manner. Moreover, due to the limited wavelength resources in an optical fiber, time-division technology is adopted to construct different kinds of channels in QKD system for efficient utilization of wavelength resources. Under such situation, how to satisfy the security requirements of service requests and complete the efficient scheduling of multi-dimensional resources, i.e., wavelengths and timeslots, is a challenging problem. This paper addresses this problem by considering multi-dimensional routing, wavelength, and timeslot allocation (RWTA) in short-distance quantum key distribution optical networks (QKD-ON), in which any two nodes can directly establish a quantum channel, and the maximum distance between any two nodes is less than the distance that can carry out point-to-point quantum key distribution process. While accommodating services with security requirements in QKD optical networks, to avoid the wavelength time-slot fragmentation caused by the constraints of wavelength consistency and time-slot continuity, we propose a time-window-based security orchestration strategy as well as relative-loss of time continuous compactness based RWTA strategy. We conducted the simulations under various scenarios, e.g., different key updating periods and different distributions on wavelength resources, etc., and the results show that the proposed strategy can achieve better performance compared with the baselines in terms of key success rate, key-updating delay, and blocking probability.

Quantum-key-distribution (QKD) networks can provide absolutely secure keys for the entire communication system in theory. At present, the key-distribution rate is relatively low, and the key-distribution rate decreases exponentially as the distribution distance increases. The trusted-relay scheme commonly used in existing QKD networks achieves the purpose of extending the security distance by consuming additional keys. Since the channel is unreliable, the key-relay process will accumulate system errors to a certain extent, increasing the probability of key-relay failure. In some high-bit-error-rate network scenarios such as wireless networks and disaster environments, the channel-error rate is as high as 30–50%. And in these scenarios, there are usually a large number of confidential messages that need to be delivered. However, the key-management mechanism of the current QKD system does not consider the scenario of key-relay failure. If the key is not successfully relayed, all the keys participating in the relay process will be destroyed, including the key that has been successfully relayed before. This situation causes the key to be wasted and reduces the encryption capability of the system. In this paper, we proposed the quantum-key-recycling (QKR) mechanism to increase the number of keys available in the network and introduced a secure service grading mechanism to properly reuse the recycled keys. The QKR mechanism can be regarded as a key-management mechanism acting on the point-to-point QKD system, and the mechanism is designed for a classical channel to reuse the key resources. A post-processing method for recycled keys is proposed to improve the security of the keys. Simulation results show that the QKD network using the key-recycling strategy is about 20% higher in key-utilization rate than the traditional QKD network without the QKR mechanism, and about 10% higher in-service security coverage.

As an important support for quantum communication, quantum key distribution (QKD) networks have achieved a relatively mature level of development, and they face higher requirements for multi-user end-to-end networking capabilities. Thus, QKD networks need an effective management plane to control and coordinate with the QKD resources. As a promising technology, software defined networking (SDN) can separate the control and management of QKD networks from the actual forwarding of the quantum keys. This paper systematically introduces QKD networks enabled by SDN, by elaborating on its overall architecture, related interfaces, and protocols. Then, three-use cases are provided as important paradigms with their corresponding schemes and simulation performances.