Dynamic data security in embedded systems is raising more and more concerns in numerous safety-critical applications. In particular, the data exchanges in embedded Systems-on-Chip (SoCs) using main ...memory are exposing many security vulnerabilities to external attacks, which will cause confidential information leakages and program execution failures for SoCs at key points. Therefore, this paper presents a security SoC architecture with integrating a four-parallel Advanced Encryption Standard-Galois/Counter Mode (AES-GCM) cryptographic accelerator for achieving high-efficiency data processing to guarantee data exchange security between the SoC and main memory against bus monitoring, off-line analysis, and data tampering attacks. The architecture design has been implemented and verified on a Xilinx Virtex-5 Field Programmable Gate Array (FPGA) platform. Based on evaluation of the cryptographic accelerator in terms of performance overhead, security capability, processing efficiency, and resource consumption, experimental results show that the parallel cryptographic accelerator does not incur significant performance overhead on providing confidentiality and integrity protections for exchanged data; its average performance overhead reduces to as low as 2.65% on typical 8-KB I/D-Caches, and its data processing efficiency is around 3 times that of the pipelined AES-GCM construction. The reinforced SoC under the data tampering attacks and benchmark tests confirms the effectiveness against external physical attacks and satisfies a good trade-off between high-efficiency and hardware overhead.
With the outbreak of the coronavirus disease 2019 (COVID-19) epidemic in China, the general public but also medical staff were confronted with psychological challenges, suffering from the highly ...infectious and unknown characteristics of COVID-19. In this study, we surveyed psychological symptoms including anxiety, depression, and sleep disorders in medical staff.
A questionnaire star/WeChat link-based survey assessing the Generalized Anxiety Disorder 7-item scale, Patient Health Questionnaire-9 depression, the Insomnia Severity Index, Social Support scales in addition to lifestyle, and income level was conducted and included 8,288 medical staff from 24 provinces in China. Pearson Chi-square and Mann-Whitney
-tests were used to evaluate single risk factors and significant differences in psychological symptoms before and during the outbreak of COVID-19. Binary logistic regression analyses were conducted for the risk factors of anxiety, depression, and sleep disorder symptoms.
Medical staff had a high incidence of psychological symptoms, which was more prominent during the COVID-19 epidemic. Comparatively, females, nurses, first-line department, never exercised, and low income were risk factors for psychological symptoms. Social support including objective support, subjective support, support utility, and regular sports over 3 times per week were protective and manageable elements that could protect from and manage the psychological symptoms of medical staff.
The susceptibility of psychological symptoms among medical staff should be of concern to policymakers and the public in the long-term, and the aggravation of mental health problems of medical staff could be eased by providing adequate social support during and after the COVID-19 outbreak.
To perform better future trend prediction for an economy-energy-environment (3E) system and address the shortcomings of traditional multivariate grey models, this paper introduces a spatial ...correlation term into the multivariate discrete grey model, thus creating the SLDGM(1,n) model, and improves the final calculation of the model according to the priority of new information. The validity of the SLDGM(1,n) model is assessed using data from the 3E system in North China, and the SLDGM(1,n) model is applied to predict the future trends of the 3E system in North China. The following conclusions are obtained. First, the introduction of the spatial correlation term and the improvement of the final calculation method are reasonable; the prediction accuracy of the multivariate grey model is improved, and multiple systems are modeled simultaneously. Second, the SLDGM(1,n) model calculates the spatial spillover effect, and according to the simulation results for North China from 2010 to 2019, Hebei's energy consumption and carbon emissions are subject to the largest influence from other provinces, while its economic development level is subject to the smallest influence, and the carbon emissions of Shanxi and Inner Mongolia are subject to a negative spatial influence effect. Third, the prediction results indicate that under the effect of spatial correlation, the energy consumption of all five provinces in North China will continue to rise; the carbon emissions of Beijing will gradually decline while the carbon emissions of the other four provinces will all gradually rise, and the per capita GDP of the five provinces is expected to increase by more than 50% by 2025.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
A subwavelength metamaterial perfect absorber (MPA) in optical communication band was proposed and tested using the finite-difference time-domain method. The absorber is periodic and comprises a top ...layer of diamond silicon surrounded by L-shaped silicon and a gold layer on the substrate. It can achieve dual-band perfect absorption, and one of the peaks is in the optical communication band. By changing the gap (g) between two adjacent pieces of L-shaped silicon, and the thickness (h) of the silicon layer, the resonance wavelength of absorption peak can be tuned. When the incident electromagnetic wave entered the absorber, the metamaterial absorber could almost completely consume the incident electromagnetic waves, thereby achieving more than 99% perfect absorption. The absorption peak reaches 99.986% at 1310 nm and 99.421% at 1550 nm. Moreover, the MPA exposed to different ambient refraction indexes can be applied as plasma sensors, and can achieve multi-channel absorption with high figure of merit (FOM*) value and refractive index (RI) sensitivity. The FOM* values at 1310 nm and 1550 nm are 6615 and 168, respectively, and both resonance peaks have highly RI sensitivity. The results confirm that the MPA is a dual-band, polarization-independent, wide-angle absorber and insensitive to incident angle. Thence it can be applied in the fields of optical communication, used as a light-wave filter and plasma sensor, and so on.
•A new conformable fractional opposite-direction accumulation is proposed.•The CFGNOM (1,1) model is more reliable and effective than other fractional grey models.•The application idea of a grey ...model for emergencies is accurate.•The CFGNOM (1,1) model is used to predict the per capita primary energy consumption of South and Central America.
To better reflect the principle of new information priority, this paper proposes a new conformable fractional opposite-direction accumulation operator and constructs a new grey prediction model, the CFGNOM (1,1) model. Three cases are used to verify the effectiveness of the CFGNOM (1,1) model, and a grey modeling prediction idea for emergencies is proposed. The CFGNOM (1,1) model is used to predict the per capita primary energy consumption of South and Central America over the next three years. The following conclusions can be drawn. First, the new conformable fractional opposite-direction accumulation method is effective and reasonable and can make full use of the information contained in the latest data to form new sequences. Second, compared with other existing fractional grey models and the BP and SVM models, the CFGNOM (1,1) model has higher prediction accuracy and can make better use of new information for modeling. Third, the application idea of a grey model for emergencies is accurate and can also be applied to the future economic and social prediction affected by the pandemic situation. Fourth, the prediction results show that the per capita energy consumption of South and Central America in 2021 is 49.9–52.7 gigajoules, the per capita energy consumption in 2022 is 48.4–51.8 gigajoules, and the per capita energy consumption in 2023 is 46.8–50.1 gigajoules.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Significant progress has been made in object tracking tasks thanks to the application of deep learning. However, current deep neural network-based object tracking methods often rely on stacking ...sub-modules and introducing complex structures to improve tracking accuracy. Unfortunately, these approaches are inefficient and limit the feasibility of deploying efficient trackers on drone AI devices. To address these challenges, this paper introduces ConcatTrk, a high-speed object tracking method designed specifically for drone AI devices. ConcatTrk utilizes a lightweight network architecture, enabling real-time tracking on edge devices. Specifically, the proposed method primarily uses the concatenation operation to construct its core tracking steps, including multi-scale feature fusion, intra-frame feature matching, and dynamic template updating, which aim to reduce the computational overhead of the tracker. To ensure tracking performance in UAV tracking scenarios, ConcatTrk implements a learnable feature matching operator along with a simple and efficient template constraint branch, which enables accurate tracking by discriminatively matching features and incorporating periodic template updates. Results of comprehensive experiments on popular benchmarks, including UAV123, OTB100, and LaSOT, show that ConcatTrk has achieved promising accuracy and attained a tracking speed of 41 FPS on an edge AI device, Nvidia AGX Xavier. ConcatTrk runs 8× faster than the SOTA tracker TransT while using 4.9× fewer FLOPs. Real-world tests on the drone platform have strongly validated its practicability, including real-time tracking speed, reliable accuracy, and low power consumption.
The hardware security of embedded systems is raising more and more concerns in numerous safety-critical applications, such as in the automotive, aerospace, avionic, and railway systems. Embedded ...systems are gaining popularity in these safety-sensitive sectors with high performance, low power, and great reliability, which are ideal control platforms for executing instruction operation and data processing. However, modern embedded systems are still exposing many potential hardware vulnerabilities to malicious attacks, including software-level and hardware-level attacks; these can cause program execution failure and confidential data leakage. For this reason, this paper presents a novel embedded system by integrating a hardware-assisted security monitoring unit (SMU), for achieving a reinforced system-on-chip (SoC) on ensuring program execution and data processing security. This architecture design was implemented and evaluated on a Xilinx Virtex-5 FPGA development board. Based on the evaluation of the SMU hardware implementation in terms of performance overhead, security capability, and resource consumption, the experimental results indicate that the SMU does not lead to a significant speed degradation to processor while executing different benchmarks, and its average performance overhead reduces to 2.18% on typical 8-KB I/D-Caches. Security capability evaluation confirms the monitoring effectiveness of SMU against both instruction and data tampering attacks. Meanwhile, the SoC satisfies a good balance between high-security and resource overhead.
As technology evolves, embedded systems access more networks and devices, which means more security threats. Existing security-monitoring methods with a single parameter (data or control flow) are ...not effective in detecting attackers tampering with the data or control flow of an embedded system. However, simply overlaying multiple security methods will result in excessive performance overhead for embedded systems. In this paper, we propose a novel hardware security-monitoring architecture that extracts DI (data integrity) digests and CFI (control flow integrity) tags to generate reference information when the program is offline. To monitor the indirect jumping behavior, this paper maps the legal target addresses into the bitmap, thus saving the search time. When the program is loaded, the reference information and the bitmap are safely loaded into the on-chip memory. The hardware monitoring module designed in this paper will check the DI summary and CFI tags in real time while executing the program. The architecture proposed in this paper has been implemented on the Xilinx Virtex 5 FPGA platform. Experimental results show that, compared with existing protection methods, the proposed approach in this paper can effectively detect multiple tampering-type attacks on the data and control flow of the embedded system, with a performance overhead of about 6%.
To realize accurate predictions for a system with a new disturbance, the concept of a time breakpoint is introduced, and the grey breakpoint prediction model GBPM(1,1,t) and corresponding optimized ...model OGBPM(1,1,t) are established. A variety of methods are introduced to calculate the model coefficients. The results show that with the establishment of time breakpoints and accurately estimated parameters, the grey breakpoint prediction model can effectively capture the system changes caused by changes in the external environment to achieve accurate system predictions. Additionally, the application of the grey breakpoint prediction model in policy evaluation is discussed. The new model requires only a small amount of data to evaluate policy effectiveness. Compared with traditional policy evaluation methods such as the double difference and breakpoint regression methods, the proposed approach is more convenient. Finally, the validity of the new model for forecasting and policy evaluation is verified using four practical cases. In comparisons with the BP, ARIMA, GM(1,1), and FGM(1,1) models, the grey breakpoint model, especially OGBPM(1,1,t), displays the best modeling performance, the best fitting accuracy and the highest precision. Through four cases, it is found that the grey breakpoint prediction model displays good applicability and superiority in forecasting and policy evaluation tasks.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Understanding the conversion characteristics of pore water is crucial for investigating the mechanism of hydrate accumulation; however, research in this area remains limited. This study conducted ...methane hydrate formation experiments in unconsolidated sands using an in-house low-field nuclear magnetic resonance (NMR) system. It focused on pore water conversion characteristics and influencing factors such as initial water saturation and sand particle sizes. Results show that methane hydrate formation enhances the homogeneity of the effective pore structure within sand samples. The conversion rate of pore water is significantly influenced by differences in heat and mass transfer capacity, decreasing as initial water saturation and sand size increase. Pore water cannot be fully converted into hydrates in unconsolidated sands. The final conversion ratio of pore water in water-poor sand samples nears 97%, while in water-rich sand samples, it is only 65.80%. Sand particle size variation has a negligible impact on the final conversion ratio of pore water, with ratios exceeding 94% across different particle sizes, differing by less than 3%.
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