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The lattice-based CRYSTALS-Dilithium scheme is one of the three thirdround digital signature finalists in the National Institute of Standards and Technology Post-Quantum Cryptography Standardization Process. Due to the complex calculations and highly individualized functions in Dilithium, its hardware implementations face the problems of large area requirements and low efficiency. This paper proposes several optimization methods to achieve a compact and high-performance hardware architecture for round 3 Dilithium. Specifically, a segmented pipelined processing method is proposed to reduce both the storage requirements and the processing time. Moreover, several optimized modules are designed to improve the efficiency of the proposed architecture, including a pipelined number theoretic transform module, a SampleInBall module, a Decompose module, and three modular reduction modules. Compared with state-of-the-art designs for Dilithium on similar platforms, our implementation requires 1.4×/1.4×/3.0×/4.5× fewer LUTs/FFs/BRAMs/DSPs, respectively, and 4.4×/1.7×/1.4× less time for key generation, signature generation, and signature verification, respectively, for NIST security level 5.

The low-cost, highly efficient online finance credit provides underfunded individuals and small and medium enterprises (SMEs) with an indispensable credit channel. Most of the previous studies focus on the client crediting and screening of online finance. Few have studied the risk rating under a complete credit risk management system. This paper introduces the improved neural network technology to the credit risk rating of online finance. Firstly, the study period was divided into the early phase and late phase after the launch of an online finance credit product. In the early phase, there are few manually labeled samples and many unlabeled samples. Therefore, a cold start method was designed for the credit risk rating of online finance, and the similarity and abnormality of credit default were calculated. In the late phase, there are few unlabeled samples. Hence, the backpropagation neural network (BPNN) was improved for online finance credit risk rating. Our strategy was proved valid through experiments.

With the innovation and integration of technology, inkjet printing has been successfully applied in the field of microelectronics production. However, it poses a great challenge to the motion control ability of inkjet printer. The traditional inkjet printing adopts semi-closed loop control, which ensures print accuracy by controlling the printing head to move at a uniform speed. This is not applicable in the field of microelectronics production, especially some flexible electronic products. In addition, the traditional inkjet printing is to print line by line or column by column, which is not suitable for some occasions where continuous inkjet oblique lines or curves are required in the field of microelectronics production. Based on the above problems, the design scheme of applying the EtherCAT protocol to the motion control system of inkjet printer is proposed. Nowadays, in the field of microelectronics production, it is generally cooperate with image processing technology to perform closed-loop control of servo motors. In order to reduce the time-consuming image processing, it is necessary to transfer the image recognition work to a high-performance computer outside the servo motor controller. The EtherCAT protocol has a high real-time performance, which ensures that the controller can quickly receive commands from the host computer, which is helpful to improve the working efficiency of the inkjet printer. Drawing the slashes and curves requires controlling the two axes of the inkjet printer synchronously; just right the specific function of the EtherCAT can help multiple controllers achieve time synchronization. Obviously, the ink-jet printer using the motion control system based on the EtherCAT protocol has a great application prospect.

Orbital Angular Momentum (OAM) multiplexing at radio has been proven as a potential way of enhancing channel capacity. In this paper, we analyze the spatial propagation characteristic of OAM beams and the channel capacity of different receiving antenna array configurations in OAM multiplexing transmission system. Simulation results reveal that an OAM beam becomes more and more divergent as the transmission distance and OAM mode order increases. Moreover, the capacity with one receiving Uniform Circular Array (UCA) outperforms the capacity with multiple receiving UCAs regardless of transmission distance and Transmit-Receive (TX-RX) lateral displacement distance, which provides a reference for receiving antenna design of OAM multiplexing transmission system. Furthermore, we verify that multiplexing more OAM modes can improve system robustness.

Dynamic time division duplex (TDD) is one promising way to improve the spectrum efficiency of the wireless communication networks since flexible traffic adaptation can be achieved by dynamically changing uplink (UL) or downlink (DL) transmission direction. However, it also brings some new challenges because of the introduction of cross-link interference, including DL-to-UL interference (e.g., gNB-to-gNB interference) and UL-to-DL interference (UE-to-UE interference). Besides, fully dynamic TDD is promising for 5G, which makes the interference management more intractable. In this paper, we investigate the interference management schemes for 5G dynamic TDD and propose a new interference suppression schemes using advanced receivers, e.g., minimum mean square error interference rejection and cancellation (MMSE-IRC) receiver and enhanced MMSE-IRC (eMMSE-IRC) receiver. The analytic expressions of MMSE-IRC and eMMSE-IRC receiver for dynamic TDD interference suppression are given by theoretical analysis. Also, one interference measurement scheme is proposed to support the proposed interference suppression schemes. The simulation results confirm the performance gain of the proposed interference suppression schemes compared with the baseline minimum mean square error (MMSE) receiver and show promising performance gain of dynamic TDD.

With the rapid economic growth and urbanization, China is suffering from serious challenges on energy security and the problems regarding waste treatment and emissions mitigation. Converting urban wastes into energy has been recognized as a promising way to achieve circular economy. In this study, combustible waste, food waste, industrial organic wastewater, and breeding-farm manure are considered to be utilized for energy recovery through waste-to-energy (WtE) technologies. Accordingly, four WtE sectors for power generation are formed and introduced into the socioeconomic activities. A methodological framework is established by combining econometrics, physical input-output model and baseline method of clean development mechanism to evaluate the energy and environmental benefits in China’s 31 provincial regions during the period 2016–2025. The results reveal that the regions with more waste generation and power generation are Guangdong (11.82 billion kWh in 2025) and Jiangsu (11.43 billion kWh in 2025). Hebei has the largest accumulative mitigation potentials for the emissions of greenhouse gases, sulfur dioxide, nitrogen oxides, and soot and dust (577.57 Mt carbon dioxide equivalent, 1.79 Mt, 0.89 Mt and 16.22 Mt, respectively), followed by Guangdong and Zhejiang. Less developed regions in northwestern China such as Gansu, Qinghai and Ningxia have less energy recovery and mitigation potentials. Meanwhile, the changes in industrial structure contribute to more mitigations in the sectors of power and heat, coal mining, and oil and gas extraction. The quantification of the energy and environmental benefits and revelation of the features and disparities of waste utilization for energy recovery across regions can provide insights and managerial implications for better policy-making regarding regional waste management.

The safety of railway permanent way is what the railway department highly concern about, railway permanent way department is one of the most important departments, it manages all railway infrastructure, railway infrastructure's good condition and normal operation is the foundation of railway transport safety. In this paper, management information system of railway permanent way safety risks and comprehensive evaluation is built through the integration of existing resources of the railway permanent way department, to achieve scientific and standardized management. It provides the effective solution for innovation of railway permanent way management and the mode of administration. This system is operational in February, 2008 in the Kunming railway bureau.

Railway distributed system integration needs to realize information exchange, resources sharing and coordination process across fields, departments and application systems. And railway data integration is essential to implement this integration. In order to resolve the problem of heterogeneity of data models among data sources of different railway operation systems, this paper has brought forth the concept of metadata dictionary that abstracts related information and information content of each data source. Based on the metadata dictionary, this paper presents a novel integration data model of spatial structure, a XML-oriented 3-dimension common data model. The proposed model accommodates both the flexibility of level relationship and syntax expression in data integration. In this model, a spatial data pattern is used to describe and express the characteristic relationship of data items among all types of data. Based on the data model with rooted directed graph and the organization of level as well as the flexibility of the expression, the model can represent the mapping between different data models, including relationship model and object-oriented model. A consistent concept and algebraic description of the data set is given to function as the metadata in data integration, so that the algebraic manipulation of data integration is standardized to support the data integration of distributed system.

As an important component of China’s transportation data sharing system, high-speed railway data sharing is a typical application of data-intensive computing. Currently, most high-speed railway data is shared in cloud computing environment. Thus, there is an urgent need for an effective cloud-computing-based data placement strategy in high-speed railway. In this paper, a new data placement strategy named hierarchical structure data placement strategy is proposed. The proposed method combines the semidefinite programming algorithm with the dynamic interval mapping algorithm. The semi-definite programming algorithm is suitable for the placement of files with various replications, ensuring that different replications of a file are placed on different storage devices, while the dynamic interval mapping algorithm ensures better self-adaptability of the data storage system. A hierarchical data placement strategy is proposed for large-scale networks. In this paper, a new theoretical analysis is provided, which is put in comparison with several other previous data placement approaches, showing the efficacy of the new analysis in several experiments.

This paper presents single event effect (SEE) characteristics of UC1845AJ pulse width modulators (PWMs) by laser testing. In combination with analysis to map PWM circuitry in the microchip dies, the typical SEE response waveforms for laser pulses located in different circuit blocks of UC1845AJ are obtained and the SEE mechanisms are analyzed. The laser SEE test results show that there are some differences in the SEE mechanisms of different circuit blocks, and phase shifts or changes in the duty cycles of few output pulses are the main SEE behaviors for UC1845AJ. In addition, a new SEE behavior which manifests as changes in the duty cycles of many output pulses is revealed. This means that an SEE hardened design should be considered.

The characteristic of crowd movement is reflected in two aspects, i.e., crowd behaviour and individual behaviour. The existing models, either macroscopic or microscopic model can simulate only one of them. In order to simulate both in one model, we propose a hybrid model for simulating human crowd. In the proposed model, we use macroscopic model to simulate the factors from external environment, and microscopic for agent’s behaviour. Agent can choose its movement speed and direction by its own desire, under the constraints from those external factors. In each simulation time step, the macroscopic and microscopic model are executed sequentially, and at the end of each time step, the information for macroscopic model will be updated from the simulation result by the microscopic one. Case study is also conducted for the proposed model. From the simulation result, it indicates that the proposed model is able to simulate the crowd and agent behaviour in dynamic environment.

Excellent condition of track geometry status is the foundation to ensure train travel security. The detection data of track inspection car contains many valuable features of the track status. The technique of gray forecast and Kalman filtering can be used to investigate the problem and predict the status change of the track geometry. In this paper, gray forecast is used in qualitative analysis of track geometry status changes, and we predict the development of track geometry status change using the Kalman filter prediction model and specific recursive algorithm, established prediction model of the track geometry to make an emulation experiment to analyze the data that track inspection car has detected, and predict changing trends of track geometry the state. Experiment results show that the application model of improved Kalman filter to predict the track geometry status changes gets a higher accuracy, and it can reflect the real change tendency of the track status.Copyright © 2011 by ASME

The paper proposes a roaming key (RK) based protocol for fast and secure intra- and inter-domain handover in wireless local area networks (WLANs) based on IEEE 802.11. A number of security requirements are also presented and the fulfillment of these requirements by the proposed protocol is also studied.

In the environment of cloud computing, real-time mass data about high-speed rail which is based on the intense monitoring of large scale perceived equipment provides strong support for the safety and maintenance of high-speed rail. In this paper, we focus on the Top- k algorithm of continuous distribution based on Multisource distributed data stream for high-speed rail monitoring. Specifically, we formalized Top- k monitoring model of high-speed rail and proposed DTMR that is the Top- k monitoring algorithm with random, continuous, or strictly monotone aggregation functions. The DTMR was proved to be valid by lots of experiments.