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The attitude accuracy of high-resolution satellite images is the main factor affecting their geometric positioning accuracy. Bundle block adjustment is the main method for realizing the simultaneous estimation of attitude models for overlapping images over a large area. In the current research on the joint positioning of high-resolution multi-line array satellite images, the adjustment is usually carried out with the view or load as a unit without considering the consistency of the error of the same platform. In this paper, we develop a self-calibration strip bundle adjustment scheme that considers the boresight misalignment among multiple cameras. By introducing the installation angle between multiple loads, we fully utilized their geometric constraint relationship with the same platform to establish a unified attitude compensation model for multiple loads. The experimental results of the ZiYuan3 (ZY-3) satellite image show that, when the ground control points (GCPs) are laid only at four corner points of the image, the image plane and elevation accuracies are 1.85 m and 1.87 m after an adjustment using this method, which can achieve comparable accuracies with those obtained by a traditional program based on an adjustment with more GCPs. [ABSTRACT FROM AUTHOR]

Understanding the regional variations and mechanisms of rural hollowing-out in the Yellow River Basin (YRB) is crucial to guiding regional rural revitalization. However, further quantitative evaluation and analysis are essential to address the issue of rural hollowing-out caused by the decrease in rural population and expansion of residential land in the YRB at different spatio-temporal scales. Based on China's census data and residential areas extracted from remote sensing images, the rural hollowing-out in the YRB is classified into five types: smart development type (SDT), human–-land recession type (HRT), population loss type (PLT), land expansion type (LET), and human–land–vacant waste type (HLW). Then, the influential features shaping the spatial diversity of rural hollowing-out types are examined, and the feature importance values at different spatio-temporal scales are assessed using the XGBoost model. The results of rural hollowing-out in the YBR indicate that (1) the geographical types of rural hollowing-out in the YRB are dominated by the HRT type and show significant heterogeneity and distribution at different spatio-temporal scales. At different time stages, the number of counties dominated by HRT in lower reaches accounts for 57% of the total counties, whereas the number of counties in the middle reaches is only 37%. Compared to the rural hollowing-out results from 2000 to 2010, the number of counties dominated by PLT and HLW from 2010 to 2020 in the middle reaches increased by 19% and 16%, respectively. (2) Precipitation had a positive effect on the variability of the rural hollowing-out distribution results based on the feature importance values, whereas agricultural productivity had a negative effect and exhibited a decreasing trend. In the entire study area, economic non-agriculturalization had a negative impact, but the topographic relief was positively correlated with the rural hollowing-out results of regional areas, and the intensity of its effect showed an increased trend from 2000 to 2020. (3) The evaluation results in the entire study area show that the main functional type and the distance from provincial capitals are the most important factors affecting rural hollowing out. Compared to other factors, the level of non-agricultural economic development has a greater impact on the spatio-temporal differentiation of rural hollowing types in different Yellow River basins. Given the significant effect of non-agricultural economic development in the evaluation of regional rural hollowing-out, it can provide methodological and indicator references for the evaluation of rural hollowing-out in different regions. [ABSTRACT FROM AUTHOR]

Many applications suitable for multicast transmission, such as video conferencing and live e-commerce, demand high Quality of Service (QoS) and require data delivery to be completed within specified delay constraints. Some methods have been proposed for constructing delay-constrained multicast routing based on network state. However, obtaining precise network latency can be challenging, resulting in inaccuracies in delay-constrained routing calculations and, ultimately, the inability to meet application requirements. Additionally, many methods engage in an indiscriminate exploration of potential paths in the network, causing significant message processing overhead. This paper proposes an Information-Centric Networking (ICN)-based approach for delay-constrained multicast routing. Our method dynamically constructs multicast paths from tree nodes to receivers based on real-time path status detection during the join message propagation phase. Additionally, we present a method for acquiring neighborhood state information to facilitate real-time routing decisions. To curtail indiscriminate path exploration, our approach uses the ICN Name Resolution System (NRS) to obtain and select potential optimal tree nodes. For this purpose, we design a multicast service registration and resolution mechanism using the ICN Name Resolution System (NRS). Simulation results indicate that our approach exhibits a higher success ratio and concurrently incurs lower message processing overhead than some other methods, particularly in situations with stringent delay constraints. [ABSTRACT FROM AUTHOR]

With the rapid growth of internet traffic, the traditional host-to-host TCP/IP architecture is subject to many service limitations faced with content-oriented applications. Various novel network architectures have been proposed to solve these limitations, among which Information-Centric Networking (ICN) is one of the most prominent. ICN features the decoupling of content (service) from the physical devices storing (providing) it through location-independent naming, and offers inherent enhancement to network performance, such as multicast and in-network caching. ICN in-network caching has been extensively studied, and we believe that it may also be the main incentive for ISPs to deploy ICN. A CDN (content delivery network) is a typical content-oriented network paradigm that aims to provide the fast delivery of content. In this paper, we leverage the advantages of the in-network caching of ICN to enhance the content delivery efficiency of CDN by integrating ICN as a service. First, we present our design of a content delivery network enhanced with ICN, called IECDN. Additionally, we formulate a mathematical model to optimize the performance of our proposed design and conduct a series of evaluations. The results indicate that our proposed design provides significant performance gains while reducing bandwidth consumption and shows better resilience to traffic surge. [ABSTRACT FROM AUTHOR]

Intelligent manufacturing workshop uses automatic guided vehicles as an important logistics and transportation carrier, and most of the existing research adopts the intelligent manufacturing workshop layout and Automated Guided Vehicle (AGV) path step-by-step optimization, which leads to problems such as low AGV operation efficiency and inability to achieve the optimal layout. For this reason, a smart manufacturing assembly line layout optimization model considering AGV path planning with the objective of minimizing the amount of material flow and the shortest AGV path is designed for the machining shop of a discrete manufacturing enterprise of a smart manufacturing company. Firstly, the information of the current node, the next node and the target node is added to the heuristic information, and the dynamic adjustment factor is added to make the heuristic information guiding in the early stage and the pheromone guiding in the later stage of iteration; secondly, the Laplace distribution is introduced to regulate the volatilization of the pheromone in the pheromone updating of the ant colony algorithm, which speeds up the speed of convergence; the path obtained by the ant colony algorithm is subjected to the deletion of the bi-directional redundant nodes, which enhances the path smoothing degree; and finally, the improved ant colony algorithm is fused with the improved dynamic window algorithm, so as to enable the robots to arrive at the end point safely. Simulation shows that in the same map environment, the ant colony algorithm compared with the basic ant colony algorithm reduces the path length by 40% to 67% compared to the basic ant colony algorithm and reduces the path inflection points by 34% to 60%, which is more suitable for complex environments. It also verifies the feasibility and superiority of the conflict-free path optimization strategy in solving the production scheduling problem of the flexible machining operation shop. [ABSTRACT FROM AUTHOR]

In the Industry 4.0 environment, an ideal smart factory should be intelligent, green, and humanized, and the logistics transportation from raw materials to final products in the factory should be completed by smart logistics. In order to address the problems of low efficiency, poor workstation service satisfaction, high distribution costs, and non-greening during the logistics distribution processes in discrete smart manufacturing workshops are required. A mathematical model of optimized multi-objective green logistics distribution paths in a smart manufacturing workshop has been constructed in this study, with low costs, high efficiency, and workstation service satisfaction taken into consideration. Then, this mathematical model was solved with an improved ant colony optimization algorithm. A "time window span" was introduced in the basic ant colony optimization algorithm to prioritize the services to workstations with a relatively high urgency in material demand, with the aim of improving workstation service satisfaction. Lastly, in order to verify the effectiveness of the model and algorithm proposed in this study, a simulation experiment has been conducted on the workstation logistics distribution system in a smart manufacturing workshop to provide convincing evidence for optimizing workstation logistics distribution paths in workshops of discrete manufacturing enterprises. [ABSTRACT FROM AUTHOR]

As an important means of improving positioning accuracy, block adjustment has been used in the improvement and assessment of accuracy for the Chinese Gaofen-7 (GF-7) satellite. However, there is little research on what factors affect accuracy without ground control points (GCPs). The correlation between accuracy and the images participating in the adjustment is not clear. This paper proposes the correlation coefficients and canonical correlation analysis between five accuracy indicators and three sets of ten adjustment factors, including topographic factors, participating image factors, and tie points (TPs) factors, to quantify the influence of adjustment factors on accuracy. Block adjustment without GCPs for GF-7 stereo imagery is verified in three study areas to evaluate the relationship between accuracy and adjustment factors. The results show that block adjustment without GCPs can improve direct positioning accuracy with an average improvement of 1.27 m in the planar direction and 0.13 m in the elevation direction. Moreover, plane accuracy is more easily affected by three sets of factors, while the influence on elevation accuracy is more balanced. The set of TP factors has the greatest influence on accuracy, and the image overlap is more critical than the image coverage area, number, and time periods. Topographic factors also play an important role, and the influence of the elevation factor with the highest canonical correlation coefficient (−0.71) is more significant than the other two factors, roughness, and slope. The results provide a reference for the improvement of adjustment accuracy without GCPs, the reasonable selection of adjustment images, the optimization of TPs, and the strategy of the partition processing of large-area block adjustment for GF-7 stereo imagery. [ABSTRACT FROM AUTHOR]

In order to solve the problems of high carbon emissions, low distribution efficiency and high costs related to the process of material distribution in manufacturing workshops, a multi-objective workshop material distribution path optimization problem model is established, and the model is solved using an improved genetic algorithm. The problem is processed using Gray code and crossover and variation operations with a genetic algorithm. To improve the search accuracy and convergence speed of the algorithm, an adaptive mutation method is proposed to enhance the diversity of the population and to achieve global optimal path objective finding. The improved algorithm is applied to workshop path multi-station logistics path planning, which effectively solves the transport path optimization and station solving problems in workshop logistics distribution, and the convergence speed and convergence accuracy of the algorithm are significantly improved. Finally, a simulation analysis is carried out on the optimization of the production material distribution of a smart gas meter workshop owned by K Company, which is an electronic assembly manufacturing company. We used MATLAB software for the case company logistics distribution route model for data analysis and solving. Due to the consideration of carbon emissions, we did not consider two kinds of experiments, which were two different cases of the optimal path. The experimental results verify that the distribution optimization scheduling model can meet the demands for immediate material distribution in the production workshop, which is conducive to improving material distribution efficiency, reducing logistics costs and achieving the goal of lowering carbon emissions. This optimization model has a certain utility in that in the current context of aiming for carbon neutral and carbon peaking, early low carbon distribution layout can reduce the environmental cost of the enterprise, making material distribution a more environmental economic path. [ABSTRACT FROM AUTHOR]

Information-Centric Networking (ICN) has revolutionized the manner of content acquisition by shifting the communication mode from host-centric to information-centric. Considering the existing, large amount of IP infrastructure in current networks, the new ICN architecture is proposed to be compatible with existing networks in order to reduce deployment cost. However, due to compatibility with IP networks, ICN data packets must be transmitted through the default path provided by IP routing regulations, which also limits the transmission efficiency and reliability of ICN. In order to address this issue, this paper introduces a multipath transmission method applied in ICN which takes full advantage of the functions and characteristics of ICN and builds multiple end-to-end relay paths by using the ICN routers as relay nodes. We then propose a relay-node-selection algorithm based on path correlation to minimize the impact of overlapping links. Moreover, we comprehensively calculate the path state value by combining the round-trip time and packet loss rate and propose a multipath data-scheduling algorithm based on the path state value. Simulation experiments show that the proposed method can maintain high bandwidth utilization while reducing the number of out-of-order packets. [ABSTRACT FROM AUTHOR]

Reducing carbon emission and raising efficient production are the important goals of modern enterprise production process. The same product can be produced by a variety of equipment, and the carbon emissions and processing time of different equipment vary greatly. Choosing suitable production equipment is an important method for manufacturing enterprises to achieve the efficient emission reduction of production process. However, the traditional production equipment selection mode only gives qualitative results, and it is difficult to provide effective advice for enterprises to choose suitable equipment under the needs of carbon neutrality. To solve this problem, this paper systematically analyzes carbon emission and the time of the turning production process, and a unified calculation model for carbon emission and efficient production of multi-type processing equipment is established. The important point of the article is to research the diversity among between carbon emissions and efficiency levels of the same product produced by different devices. The carbon emissions and efficiency levels of different kinds of equipment can be calculated by the BAS algorithm. By turning a shaft part as an example, the results show that this method can calculate the optimal value of carbon emissions and efficiency of the same product produced by different equipment and can provide suggestions for enterprises to select appropriate equipment for low-carbon and efficient production. This paper provides a reference for further research on the quantitative calculation model for the selection of high-efficiency and low-carbon production equipment. [ABSTRACT FROM AUTHOR]

In the context of Industry 4.0, the lean–green manufacturing system has brought many advantages and challenges to industrial participants. Security is one of the main challenges encountered in the new industrial environment, because smart factory applications can easily expose the vulnerability of manufacturing and threaten the operational security of the whole system. It is difficult to address the problem of the brittleness factor in manufacturing systems. Therefore, building on vulnerability theory, this study proposes a vulnerability index system for lean–green manufacturing systems in a manufacturing company in the context of Industry 4.0. The index has four dimensions: human factors, equipment factors, environmental factors, and other factors. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach was used to calculate the degree of influence, the degree of being influenced, and the centrality and causes of the factors. The causal relationships and key influences between the factors were identified. Then, the dependence and hierarchy of each of the key influencing factors were analyzed using the Matrix-Based Cross-Impact Multiplication Applied to Classification (MICMAC) and Interpretative Structural Model (ISM) methods, and a hierarchical structural model of the factors was constructed. Finally, an intelligent manufacturing system that produces a micro-acoustic material and device was used as an example to verify the accuracy of the proposed method. The results show that the method not only identifies the key brittleness factors in a lean–green manufacturing system but can also provide a guarantee for the safe operation of a manufacturing system. This study provides theoretical guidance for the effective management of intelligent manufacturing systems; moreover, it lays a foundation and provides a new methodology for assessing the vulnerability of manufacturing systems. [ABSTRACT FROM AUTHOR]

Aiming at resolving the problem of low assembly accuracy and the difficulty of guaranteeing assembly quality of remanufactured parts, an optimization classification method for the assembly sequence of remanufactured parts based on different accuracy levels is proposed. By studying the characteristics of recycled parts, based on the requirement that the quality of remanufactured products not be lower than that of the assembly quality of new products, the classification selection matching constraints of remanufactured parts are determined, and the classification selection matching optimization models of remanufactured parts with different precision levels is established. An algorithm combining particle swarm optimization and a genetic algorithm is proposed to solve the model and obtain the optimal assembly sequence. Taking the remanufacturing assembling of a 1.4 TGDI engine crank and a connecting rod mechanism as an example, the comparison of quality data shows that this method can effectively improve the qualified rate of assembly, reduce the cost of after-sale claims, provide new theories and methods for remanufacturing enterprises that need hierarchical assembly, and provide effective guidance for the development of the remanufacturing industry. [ABSTRACT FROM AUTHOR]

Due to the overload of IP semantics, the traditional TCP/IP network has a number of problems in scalability, mobility, and security. In this context, information-centric networking (ICN) is proposed to solve these problems. To reduce the cost of deployment and smoothly evolve, the ICN architecture needs to be compatible with existing IP infrastructure. However, the rigid underlying IP routing regulation limits the data transmission efficiency of ICN. In this paper, we propose a novel multipath transmission scheme by utilizing the characteristics and functions of ICN to enhance data transmission. The process of multipath transmission can be regarded as a service, and a multipath transmission service ID (MPSID) is assigned. By using the ICN routers bound to the MPSID as relay nodes, multiple parallel paths between the data source and the receiver are constructed. Moreover, we design a path management mechanism, including path selection and path switching. It can determine the initial path based on historical transmission information and switch to other optimal paths according to the congestion degree during transmission. The experimental results show that our proposed method can improve the average throughput and reduce the average flow completion time and the average chunk completion time. [ABSTRACT FROM AUTHOR]

The spread of SARS-CoV-2 and its variants leads to a heavy burden on healthcare and the global economy, highlighting the need for developing vaccines that induce broad immunity against coronavirus. Here, we explored the immunogenicity of monovalent or bivalent spike (S) trimer subunit vaccines derived from SARS-CoV-2 B.1.351 (S1-2P) or/and B.1. 618 (S2-2P) in Balb/c mice. Both S1-2P and S2-2P elicited anti-spike antibody responses, and alum adjuvant induced higher levels of antibodies than Addavax adjuvant. The dose responses of the vaccines on immunogenicity were evaluated in vivo. A low dose of 5 μg monovalent recombinant protein or 2.5 μg bivalent vaccine triggered high-titer antibodies that showed cross-activity to Beta, Delta, and Gamma RBD in mice. The third immunization dose could boost (1.1 to 40.6 times) high levels of cross-binding antibodies and elicit high titers of neutralizing antibodies (64 to 1024) prototype, Beta, Delta, and Omicron variants. Furthermore, the vaccines were able to provoke a Th1-biased cellular immune response. Significantly, at the same antigen dose, S1-2P immune sera induced stronger broadly neutralizing antibodies against prototype, Beta, Delta, and Omicron variants compared to that induced by S2-2P. At the same time, the low dose of bivalent vaccine containing S2-2P and S1-2P (2.5 μg for each antigen) significantly improved the cross-neutralizing antibody responses. In conclusion, our results showed that monovalent S1-2P subunit vaccine or bivalent vaccine (S1-2P and S2-2P) induced potent humoral and cellular responses against multiple SARS-CoV-2 variants and provided valuable information for the development of recombinant protein-based SARS-CoV-2 vaccines that protect against emerging SARS-CoV-2 variants. [ABSTRACT FROM AUTHOR]

The existing research and practices have shown that the coordinated implementation of lean-green manufacturing can have a positive impact on the economic and environmental benefits, which is an effective means to ensure the environmental protection of the production process of manufacturing without damaging their profitability. Within the field of lean-green research, there is still a lack of research to analyze the driving factors for the collaborative implementation of integrated lean and green integration. Although, some scholars and researchers have studied lean and green integration paradigms, their research has mostly focused on lean-green integration practices and their impact on environmental performance and their respective operations. In the context of Industry 4.0, this article investigates the driving forces behind the collaborative integration implementation of a lean-green manufacturing system from the viewpoint of stakeholders. Specifically addressing the issues of correlation and ambiguity in the identification of driving factors, this manuscript proposes an Interpretation Structure Model (ISM) of fuzzy comprehensive Analytic Hierarchy Process (AHP), based on Decision-Making Trial and Evaluation Laboratory (DEMATEL), to determine the importance of the driving factors. Combined with the complex network theory, the evaluation index system is divided into four levels from eight factor categories, including endogenous lean-green driving factors and exogenous driving factors. The fuzzy AHP-DEMATEL-ISM is used to analyze the relationship between indicators and the structure of the indicator system. The complex network which is composed of the indicator system is divided into different levels. The importance of indicators is analyzed from the perspective of the global network, and key factors affecting the driving of lean-green system is analyzed. The integration of the lean-green manufacturing system and organizational synergy are promoted to jointly lead the enterprise toward sustainable development by paying particular attention to the primary impact indicators and aggressively cultivating the key impact indicators. [ABSTRACT FROM AUTHOR]

Considering that, in the context of the ecological restoration of a large number of exposed rock slopes, it is difficult for existing artificial soil to meet the requirements of mechanical properties and ecological construction at the same time, this paper investigates the stabilization benefits of polyvinyl acetate and attapulgite-treated clayey soil through a series of laboratory experiments. To study the effectiveness of polyvinyl acetate (PVA) and attapulgite as soil stabilizer, a triaxial strength test, an evaporation test and a vegetation growth test were carried out on improved soil with different amounts of PVA content (0, 1%, 2%, 3%, and 4%) and attapulgite replacement (0, 2%, 4%, 6%, and 8%). The results show that the single and composite materials of polyvinyl acetate and attapulgite can increase the peak deviator stress of the sample. The addition of polyvinyl acetate can improve the soil strength by increasing the cohesion of the sample; the addition of attapulgite improves the soil strength mainly by increasing the internal friction angle of the sample. The strength of the composite is greatly improved by increasing the cohesion and internal friction angle of the sample at the same time. The effect of adding materials increased significantly with increasing curing age. Moreover, polyvinyl acetate and attapulgite improve the soil water retention of the soil by improving the water-holding capacity, so that the soil can still ensure the good growth of vegetation under long-term drought conditions. The scanning electron microscopy (SEM) images indicated that the PVA and attapulgite of soil affect the strength characteristics of soil specimens by the reaction of PVA and water, which changes the structure of the soil and, by the interweaving of attapulgite soil particles, acts as the skeleton of the aggregate. Overall, PVA and attapulgite can effectively increase clayey soil stability by improving the cohesive force and internal friction angle of clayey soil. [ABSTRACT FROM AUTHOR]

Clay is one of the important base materials in slope restoration. The adhesion of clay–rock interface plays a decisive role in the repairing effect on rock slopes. Fibers and polymers are widely used as a clay improvement method in rock slope repair. In this paper, the friction effect of sisal fiber and polyvinyl acetate (PVAc)-reinforced clay was studied through the design of an indoor rock-like interface sliding model test. Using modelled test results and scanning electron microscope (SEM) images, the reinforced clay was analyzed. The test results showed that the critical sliding angle and maximum static friction force of clay decreased with the increase of moisture content. An excess of fiber content and moisture content weakens the coupling effect of fiber-anchoring clay. Fiber content of 0.8% and PVAc content of 2% had the best effect on enhancing the sliding resistance of clay and provided good adhesion for dangerous interfaces of rock slope at 35° and 45°, respectively. PVAc formed a three-dimensional networked elastic membrane structure to improve the skid resistance and dynamic friction coefficient of the clay. The results provide an effective way for soil improvement and ecological restoration. [ABSTRACT FROM AUTHOR]

The anisotropic mechanical behavior and associated microstructure evolution in annealed Zircaloy-4 were investigated at room temperature, using quasi-in situ tensile tests along the typical direction, rolling direction (RD), and transverse direction (TD). Herein, the in-grain misorientation axes (IGMA) and the nominal Schmid factors were evaluated to analyze the slip mode based on the electron backscatter diffraction. The IGMA result shows that there were anisotropic slip modes within grains, whose basal poles were parallel with the TD (TB) and placed within 40 to 50 degrees from the normal direction (ND) to the transverse direction (N (40°–50°) TB)), under different loading directions. When loading along the RD, the basal slips were activated in the N (40°–50°) TB and TB orientation grains, while the second-order pyramidal slips were activated in the grains when loading along the TD. The relatively higher ultimate tensile strength and elongation in Zircaloy-4 when tensile along RD occurs due to its much higher frequency of soft grains (88.54%) than the TD sample (64.29%), and the synergy deformation among local grains. The present study demonstrated that the anisotropic mechanical behavior of Zircaloy-4 was attributed to the combined effects that exist between the anisotropic slip behavior and the different compatible deformation capabilities. Many shallow dimples and cleavage regions were observed on the fracture surface in the TD sample. Such fracture features are consistent with the lower ultimate tensile strength ~470 MPa and elongation ~14.5% in the deformed tensile Zircaloy-4 along the TD. [ABSTRACT FROM AUTHOR]

In order to solve the problem that the existing low-carbon vehicle scheduling model ignores the economic benefits of enterprises and cannot fully reflect the fuzzy needs of customers, the green simultaneous pick-up and delivery vehicle scheduling problem is studied here. With the goal of minimizing the total cost composed of service cost, fuel consumption cost, and carbon emission cost, a multi-objective comprehensive model of green simultaneous pick-up and delivery under fuzzy demand is established. In order to fully consider the objective uncertainty of customer demand and customer service time, triangular fuzzy numbers are introduced and simultaneous delivery demand is considered. An improved genetic tabu search algorithm is proposed to solve this problem. In the improved GA-TS algorithm, the penalty factor is introduced into the fitness function, the selection operator combined with elite strategy is adopted, and a mutation operator combined with tabu search algorithm is proposed. The Taguchi analysis method is used to obtain reasonable parameter settings of the GA-TS algorithm. Finally, a case study is used to verify the effectiveness of the model and hybrid algorithm. The experimental results show that the proposed comprehensive model can effectively optimize the scheduling of low-carbon simultaneous pick-up and delivery vehicles under fuzzy demand, and the effectiveness and feasibility of genetic tabu search algorithm are verified by comparing the experimental results of different algorithms and different case sizes. [ABSTRACT FROM AUTHOR]

Sustainable blank dimension design is the key to the implementation of green industrial development. However, blank dimension design only considers the blank production factor of the blank dimension design stage, which cannot guarantee the blank production stage and the use stage's overall goal. In this paper, based on the guiding thinking of a business compass, a low-carbon and low-energy consumption blank dimension optimization design model was proposed. Taking the process parameters of the production and the use of the blank as the variables, the grey wolf optimization algorithm was adopted to solve the problem. Taking the gear blanks dimension as an example, the optimized blank dimension is 98.6, compared with the standard blank dimension of 100, 105, the energy consumption is 95.7% and 93.1%, the carbon emission is 92.6% and 90.2%, and the material consumption is 96.5% and 87.5%, respectively. The sustainable blank dimension design has obvious advantages in terms of low energy consumption and low carbon, and it can save a lot of materials; it can also promote product sustainability. [ABSTRACT FROM AUTHOR]

The optimal selection of machine equipment can reduce the energy consumption and processing time of the parts processing process in enterprises. The energy consumption and time of using different equipment to process the same product vary greatly. Traditional equipment selection is only through qualitative analysis comparing the process characteristics of using different equipment or optimizing parameters for a single piece of equipment. It does not take into account the dynamics of the production process and does not consider the impact of process factors on production decisions. To solve this problem, we established a production equipment selection model based on the business compass model and proposed a calculation method that considered energy consumption and time objectives in the production process. Quantitative analysis can be performed for different equipment. The energy consumption and processing time of different equipment are calculated by the beetle antennae search (BAS) algorithm. A case study of machining end cap holes was carried out. The results showed that this method can calculate the optimal energy consumption and the optimal time of different equipment for producing the same product, which has good theoretical and practical significance for enterprises and governments to choose energy-saving and efficient production equipment. [ABSTRACT FROM AUTHOR]

Energy consumption and carbon emission levels in the production process constitute an important basis for the selection of production equipment. The energy consumption and carbon emission levels of the same product produced by different kinds equipment vary greatly from one tool to another. Unfortunately, traditional modes of selection only give qualitative results, so that it is difficult to provide a quantitative reference to enable enterprises to choose appropriate modes of production in the context of the green development concept (GDC). In order to solve this problem, a calculation method for multiple energy consumption and carbon-emission objectives for commodity production is proposed. The focus of this paper is to research the difference between the energy consumption and carbon emission levels of the same product produced by different kinds of equipment. The energy consumption and carbon emissions of different kinds of equipment can be calculated by gray wolf algorithm. The results show that the proposed method can calculate the optimal values of energy consumption and carbon emissions in the same kinds of products produced by different equipment, which can provide assistance for enterprises in choosing the production equipment that best conforms to the green development concept. [ABSTRACT FROM AUTHOR]

As a new network architecture, information-centric networking (ICN) decouples the identifiers and locators of network entities and makes full use of in-network cache technology to improve the content distribution efficiency. For reliable multicast, ICN in-network cache can help reduce the loss recovery delay. However, with the development of applications and services, a multicast tree node often serves multiple reliable multicast groups. How to reasonably allocate cache resources for each multicast group will greatly affect the performance of reliable multicast. In order to improve the overall loss recovery performance of reliable multicast, this paper designs a dynamic cache allocation mechanism (DCAM). DCAM considers the packet loss probability, the node depth of the multicast tree, and the multicast transmission rate of multicast group, and then allocates cache space for multicast group based on the normalized cache quota weight. We also explore the performance of three cache allocation mechanisms (DCAM, AARM, and Equal) combined with four cache strategies (LCE, CAPC, Prob, and ProbCache), respectively. Experimental results show that DCAM can adjust cache allocation results in time according to network changes, and its combinations with various cache strategies outperform other combinations. Moreover, the combination of DCAM and CAPC can achieve optimal performance in loss recovery delay, cache hit ratio, transmission completion time, and overhead. [ABSTRACT FROM AUTHOR]

The Ziyuan3-01 (ZY3-01) satellite is China's first civilian stereo surveying and mapping satellite to meet the 1:50,000 scale mapping requirements, and has been operated in orbit for 10 years. The boresight misalignment of the three-line camera (TLC) is an essential factor affecting the geolocation accuracy, which is a principal concern for stereo mapping satellites. However, the relative relationships of TLC are often regarded as fixed for the same ground scene in most traditional geometric calibrations, without considering the on-orbit long-periodic changes. In this paper, we propose a long-periodic method to analyze and estimate the boresight misalignments between three cameras, with the attitude estimation of a nadir (NAD) camera as the benchmark. Offsets and drifts of the three cameras were calculated and calibrated with different compensation models using scale invariant feature transform (SIFT) points as the ground control. Ten simultaneous NAD–Forward (FWD)–Backward (BWD) imagery of the ZY3-01 satellite acquired from 2012 to 2020 were selected to verify the long-periodic changes in TLC boresight misalignments. The results indicate that the boresight alignment angles of ZY3-01 TLC are dynamic during the long-periodic flight, but the structure of TLC is stable for the misalignments of both FWD and BWD within only 7 arc seconds, which can provide a positive reference for subsequent satellite design and long-periodic on-orbit geometric calibration. [ABSTRACT FROM AUTHOR]

Information-centric networking (ICN) is expected to be a candidate for future internet architecture, and it supports features such as multicast that improves bandwidth utilization and transmission efficiency. However, multicast itself does not provide congestion control. When multiple multicast groups coexist, multicast traffic may exhaust all network resources, and cause network congestion and packet loss. Additionally, traditional IP multicast congestion control mechanisms cannot be directly applied to ICN architecture. Therefore, it is necessary to consider an effective congestion control mechanism for ICN multicast. This paper proposes a single-rate multicast congestion control mechanism, called SRMCC. It supports router-assisted awareness of the network congestion state and congestion control message aggregation. Moreover, the fair shared rate estimation method is innovatively proposed to achieve protocol fairness. Most importantly, it adjusts the rate according to different congestion states indicated by the queue occupancy ratio. By introducing a rate selection factor, it can achieve a balance between packet loss rate and throughput. Experimental results show that our proposal outperforms other mechanisms in throughput, packet loss rate, total bandwidth utilization, and overhead, and achieves protocol fairness and better TCP friendliness. [ABSTRACT FROM AUTHOR]

Digital Surface Model (DSM) derived from high resolution satellite imagery is important for various applications. GFDM is China's first civil optical remote sensing satellite with multiple agile imaging modes and sub-meter resolution. Its panchromatic resolution is 0.5 m and 1.68 m for multi-spectral images. Compared with the onboard stereo viewing instruments (0.8 m for forward image, 0.65 m for back image, and 2.6 m for back multi-spectrum images) of GF-7, a mapping satellite of China in the same period, their accuracy is very similar. However, the accuracy of GFDM DSM has not yet been verified or fully characterized, and the detailed difference between the two has not yet been assessed either. This paper evaluates the DSM accuracy generated by GFDM and GF-7 satellite imagery using high-precision reference DSM and the observations of Ground Control Points (GCPs) as the reference data. A method to evaluate the DSM accuracy based on regional DSM errors and GCPs errors is proposed. Through the analysis of DSM subtraction, profile lines, strips detection and residuals coupling differences, the differences of DSM overall accuracy, vertical accuracy, horizontal accuracy and the strips errors between GFDM DSM and GF-7 DSM are evaluated. The results show that the overall accuracy of both is close while the vertical accuracy is slightly different. When regional DSM is used as the benchmark, the GFDM DSM has a slight advantage in elevation accuracy, but there are some regular fluctuation strips with small amplitude. When GCPs are used as the reference, the elevation Root Mean Square Error (RMSE) of GFDM DSM is about 0.94 m, and that of GF-7 is 0.67 m. GF-7 DSM is more accurate, but both of the errors are within 1 m. The DSM image residuals of the GF-7 are within 0.5 pixel, while the residuals of GFDM are relatively large, reaching 0.8 pixel. [ABSTRACT FROM AUTHOR]

Many information-centric services have emerged, such as IPTV and video conferencing. These services put a lot of demands on scalable multicast communication. However, traditional IP multicast has low adoption because of its poor scalability. Therefore, some stateless multicast methods were proposed, which encapsulate the destination's information into the packet header without requiring routers to maintain the multicast forwarding state. However, stateless multicast also faces some problems, such as ingress router overload, high forwarding overhead, packet redundancy, etc. In addition, most multicast methods cannot optimize the multicast tree because the multicast flow is simply forwarded along the shortest path tree from the source to receivers. This paper proposes an Adaptive Hierarchical Hybrid Multicast (AHHM) based on Information-Centric Networking. To balance the forwarding states and forwarding overhead, AHHM is designed as a two-layer structure, in which the upper layer establishes a stateful main tree and the lower layer establishes several stateless sub trees. The router on the main tree is defined as the multicast join node (MJN), and AHHM uses the Name Resolution System to maintain the mapping between each multicast group name and corresponding MJNs. To optimize the multicast transmission path, we designed the minimum cost selection strategy for users to select the appropriate MJN to join. Simulation results show that compared with Source-Specific Multicast (SSM) and Bit Index Explicit Replication (BIER), AHHM can not only reduce the multicast forwarding states but also reduce the control overhead and link load. [ABSTRACT FROM AUTHOR]

As one of the candidates for future network architecture, Information-Centric Networking (ICN) has revolutionized the manner of content retrieval by transforming the communication mode from host-centric to information-centric. Unlike a traditional TCP/IP network, ICN uses a location-independent name to identify content and takes a receiver-driven model to retrieve the content. Moreover, ICN routers not only perform a forwarding function but also act as content providers due to pervasive in-network caching. The network traffic is more complicated and routers are more prone to congestion. These distinguished characteristics pose new challenges to ICN transmission control mechanism. In this paper, we propose an effective transmission scheme by combining the receiver-driven transport protocol and the router-driven congestion detection mechanism. We first outline the process of content retrieval and transmission in an IP-compatible ICN architecture and propose a practical receiver-driven transport protocol. Then, we present an early congestion detection mechanism applied on ICN routers based on an improved Active Queue Management (AQM) algorithm and design a receiver-driven congestion control algorithm. Finally, experiment results show that the proposed transmission scheme can maintain high bandwidth utilization and significantly reduce transmission delay and packet loss rate. [ABSTRACT FROM AUTHOR]

In this paper, the design procedure and optimization process of a multi-phase flux-switching permanent magnet (FSPM) generator for wind power generation system is investigated. Two different optimization methods—stepwise optimization and global optimization—are implemented and applied to the optimization of the proposed nine-phase FSPM generator-based wind power system. Both the advantages and disadvantages of two optimization methods are compared and analyzed. The results indicate that the stepwise optimization can achieve good effects on individual optimization objectives, whereas the global optimization can not only achieve a good optimization effect on a single objective, but also can find design point on the Pareto front, which can effectively optimize different multi-objects. The electromagnetic performance of the nine-phase FSPM generator is verified by experiments on a prototyped machine and the measured results show that the proposed generator exhibits the favorable characteristics of high torque, low torque ripple, and high efficiency. [ABSTRACT FROM AUTHOR]

Reliable multicast distribution is essential for some applications such as Internet of Things (IoT) alarm information and important file distribution. Traditional IP reliable multicast usually relies on multicast source retransmission for recovery losses, causing huge recovery delay and redundancy. Moreover, feedback implosion tends to occur towards multicast source as the number of receivers grows. Information-Centric Networking (ICN) is an emerging network architecture that is efficient in content distribution by supporting multicast and in-network caching. Although ubiquitous in-network caching provides nearby retransmission, the design of cache strategy greatly affects the performance of loss recovery. Therefore, how to recover losses efficiently and quickly is an urgent problem to be solved in ICN reliable multicast. In this paper, we first propose an overview architecture of ICN-based reliable multicast and formulate a problem using recovery delay as the optimization target. Based on the architecture, we present a Congestion-Aware Probabilistic Cache (CAPC) strategy to reduce recovery delay by caching recently transmitted chunks during multicast transmission. Then, we propose NACK feedback aggregation and recovery isolation scheme to decrease recovery overhead. Finally, experimental results show that our proposal can achieve fully reliable multicast and outperforms other approaches in recovery delay, cache hit ratio, transmission completion time, and overhead. [ABSTRACT FROM AUTHOR]

As an emerging network architecture, Information-Centric Networking (ICN) is considered to have the potential to meet the new requirements of the Fifth Generation (5G) networks. ICN uses a name decoupled from location to identify content, supports the in-network caching technology, and adopts a receiver-driven model for data transmission. Existing ICN congestion control mechanisms usually first select a nearby replica by opportunistic cache-hits and then insist on adjusting the transmission rate regardless of the congestion state, which cannot fully utilize the characteristics of ICN to improve the performance of data transmission. To solve this problem, this paper proposes a two-level congestion control mechanism, called 2LCCM. It switches the replica location based on a node state table to avoid congestion paths when heavy congestion happens. This 2LCCM mechanism also uses a receiver-driven congestion control algorithm to adjust the request sending rate, in order to avoid link congestion under light congestion. In this paper, the design and implementation of the proposed mechanism are described in detail, and the experimental results show that 2LCCM can effectively reduce the transmission delay when heavy congestion occurs, and the bandwidth-delay product-based congestion control algorithm has better transmission performance compared with a loss-based algorithm. [ABSTRACT FROM AUTHOR]

Fifth generation (5G) networks have a high requirement for low latency of data delivery. Information-centric networking (ICN) adopts the paradigm of separation of the identifier and locator. It is efficient in content distribution by supporting in-network caching and has the potential to satisfy the low latency requirement in 5G. Replica selection is a key problem to retrieving content in ICN. Prior research usually utilizes the nearest replica. However, using the nearest replica cannot guarantee the smallest content download delay. To exploit in-network caching better, we propose an enhanced replica selection approach, called ERS. ERS first uses a distance-constrained-based name resolution system to discover the nearby replicas. Then, the most appropriate replica is chosen according to a local state table that maintains the state of replica nodes within a limited domain. In addition to network distance and replica node load, ERS innovatively introduces the path congestion degree between requester and replica nodes to assist replica selection. With extensive simulations, the proposed approach shows better performance than the state-of-the-art methods in terms of average content download delay. Finally, the overhead of the proposed method is analyzed. [ABSTRACT FROM AUTHOR]

In this paper, an interior permanent magnet (IPM) synchronous machine with multiflux barriers is proposed to meet the wide speed regulation application requirements of electric vehicles. Based on the flux barrier characteristic, an electromagnetic–mechanical coupling optimization strategy is employed for the machine design. In order to facilitate the optimization design, the rotor barriers are divided into two optimization zones, the maximum stress zone and the maximum deformation zone. The electromagnetic–mechanical coupling optimization strategy is divided into two stages accordingly. In the first stage, the machine is regarded as a synchronous reluctance machine by ignoring permanent magnets, where the dimensions of the arc-shaped barriers are optimized to achieve a large reluctance torque and small stress. In the second stage, the dimensions of the arc-shaped PMs and the elliptical barrier are optimized with three objectives of minimum torque ripple, minimum flux linkage, and minimum deformation. After machine optimization, the comparison investigations are carried out on the basis of finite-element analysis by considering both the electromagnetic performances and mechanical performances. [ABSTRACT FROM AUTHOR]

The double-stator permanent-magnet doubly salient (DS-PMDS) machine is an interesting candidate motor for electric vehicle (EV) applications because of its high torque output and flexible working modes. Due to the complexity of the motor structure, optimization of the DS-PMDS for EVs requires more research efforts to meet multiple specifications. Effective multi-objective optimization to increase torque output, reduce torque ripple, and improve PM material utilization and motor efficiency is implemented in this paper. In the design process, a multi-objective comprehensive function is established. By using parametric sensitivity analysis (PSA) and the sequential quadratic programming (NLPQL) method, the influence extent of each size parameter for different performance is effectively evaluated and optimal results are determined. By adopting the finite element method (FEM), the electromagnetic performances of the optimal DS-PMDS motor is investigated. Moreover, a multi-physical field analysis is included to describe stress, deformation of the rotor, and temperature distribution of the proposed motor. The theoretical analysis verified the rationality of the motor investigated and the effectiveness of the proposed optimization method. [ABSTRACT FROM AUTHOR]