Driving risk assessment and prevention strategies for autonomous vehicle in open-pits

Driving risk assessment and protection is the critical technology of unmanned transportation systems in open-pits. In order to warrant the safe operation of unmanned vehicles in open-pits, the Driving Security Model (DSM) based on the vehicle-road-cloud transportation system is established. Based on the multi-source information from the vehicle, roadside, and cloud platform, the DSM can assess the driving risk level of driverless vehicles and provide corresponding driving risk prevention strategies. The DSM comprises driving state awareness, driving risk assessment, and driving risk protection. In terms of driving risk assessment, the threshold of pre-collision time is corrected through the road slope ahead of the vehicle, and the minimum braking safety distance is modified by the information of road slope and vehicle load state. In the meantime, a comprehensive driving risk assessment strategy is proposed, which can quantify the real-time collision risk of autonomous vehicles in open-pits. Then, a collision risk protection system that considers different driving risks is then designed based on a finite state machine. A smooth braking control strategy is developed to meet the minimum safety distance. Finally, a digital twin simulation system that corresponds to the autonomous vehicle in an open-pit is built based on the PreScan and Matlab co-simulation technology and some simulation tests in the horizontal, uphill-downhill road and full load scenes are carried out. The simulation results show that the DSM’s comprehensive risk assessment strategy can evaluate suitable risk levels in advance and timely brake, which indicates that the introduction of road slope information can improve the driving safety of the vehicle up and downhill scenes. By introducing vehicle load information, the designed minimum safe braking distance index can detect potential collision risk in time. The DSM’s emergency braking control strategy can smoothly stop the vehicle before 10 m safe distance, which improves the stability of heavy-duty vehicles during emergency braking

A decision analysis model for KEGG pathway analysis

The knowledge base-driven pathway analysis is becoming the first choice for many investigators, in that it not only can reduce the complexity of functional analysis by grouping thousands of genes into just several hundred pathways, but also can increase the explanatory power for the experiment by identifying active pathways in different conditions. However, current approaches are designed to analyze a biological system assuming that each pathway is independent of the other pathways. A decision analysis model is developed in this article that accounts for dependence among pathways in time-course experiments and multiple treatments experiments. This model introduces a decision coefficient—a designed index, to identify the most relevant pathways in a given experiment by taking into account not only the direct determination factor of each Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway itself, but also the indirect determination factors from its related pathways. Meanwhile, the direct and indirect determination factors of each pathway are employed to demonstrate the regulation mechanisms among KEGG pathways, and the sign of decision coefficient can be used to preliminarily estimate the impact direction of each KEGG pathway. The simulation study of decision analysis demonstrated the application of decision analysis model for KEGG pathway analysis. A microarray dataset from bovine mammary tissue over entire lactation cycle was used to further illustrate our strategy. The results showed that the decision analysis model can provide the promising and more biologically meaningful results. Therefore, the decision analysis model is an initial attempt of optimizing pathway analysis methodology.https://doi.org/10.1186/s12859-016-1285-

COVERT COMMUNICATION FOR COOPERATIVE NOMA WITH TWO PHASES DETECTION

This paper investigates the covert communication of cooperative non-orthogonal multiple access (NOMA) systems, where the near user serves as a decode-and-forward (DF) relay and the far user receives the covert information from both the source and the near user. To improve the covertness performance, cooperative jamming and power randomness are adopted. Specifically, we derive detection error probability (DEP) of Willie and the minimum detection error probability (MDEP) at the optimal decision threshold for each phase. In addition, the reliability of the proposed system is investigated by deriving closed-form expressions for the outage probability (OP) of the two users. Under the covertness and reliability constraints, an optimization algorithm to maximize the effective covert rate is designed. Simulation results have confirmed the correctness of the theoretical analysis, and the proposed scheme can achieve a better covert communication

Guardian spirit of be (Shaman) and Culture tradition : For ongdin - taban - tnger ritual

This file provide the detailed impact direction data of selected KEGG pathway categories, subcategories and the secondary pathways from− 15 to 300 vs.− 30d in bovine mammary tissue during lactation in Table S2 (a) and (b), respectively. The numbers colored in red color are the filled data by the average of all the other impact values in this pathway, which is the missing data originally. (DOCX 35 kb

SVSI: Fast and Powerful Set-Valued System Identification Approach to Identifying Rare Variants in Sequencing Studies for Ordered Categorical Traits: SVSIfor Genetic Association Studies

For genetic association studies that involve an ordered categorical phenotype, we usually either regroup multiple categories of the phenotype into two categories (“cases” and “controls”) and then apply the standard logistic regression (LG), or apply ordered logistic (oLG) or ordered probit (oPRB) regression which accounts for the ordinal nature of the phenotype. However, these approaches may lose statistical power or may not control type I error rate due to their model assumption and/or instable parameter estimation algorithm when the genetic variant is rare or sample size is limited. Here to solve this problem, we propose a set-valued (SV) system model, which assumes that an underlying continuous phenotype follows a normal distribution, to identify genetic variants associated with an ordinal categorical phenotype. We couple this model with a set-valued system identification algorithm to identify all the key system parameters. Simulations and two real data analyses show that SV and LG accurately controlled the Type I error rate even at a significance level of 10−6 but not oLG and oPRB in some cases. LG had significantly smaller power than the other three methods due to disregarding of the ordinal nature of the phenotype, and SV had similar or greater power than oLG and oPRB. For instance, in a simulation with data generated from an additive SV model with odds ratio of 7.4 for a phenotype with three categories, a single nucleotide polymorphism with minor allele frequency of 0.75% and sample size of 999 (333 per category), the power of SV, oLG and LG models were 70%, 40% and <1%, respectively, at a significance level of 10−6. Thus, SV should be employed in genetic association studies for ordered categorical phenotype

Benzene-like N 6 Rings in Be 2 N 6 Monolayer: a Stable 2D Semiconductor with High Carrier Mobility

Designing new two-dimensional (2D) semiconductors with high carrier mobilities is highly desirable for material innovation, especially when the configuration has novel topological properties. Here, we proposed a first-principles-based design of a 2D crystal, namely a Be2N6 monolayer. In which, each N atom is shared by two neighboring N atoms and one Be atom, forming a novel moiety of benzene-like N6 rings. Rather than the instability of hexazine, the Be2N6 monolayer has a moderate cohesive energy, good kinetic and thermodynamic stability, due to the stabilization effect of the Be element by forming twelve classical two-centre–two-electron (2c–2e) σ-bonds and five multicenter 6c–2e π-bonds. There are ten π electrons in a unit cell, which satisfies the Hückel rule [4n + 2] (n = 2), indicating the Be2N6 monolayer aromaticity. As a result, the Be2N6 monolayer has an ultra-high mechanical strength of up to 200 J m−2. Particle-swarm optimization (PSO) computations reveal that a cyclo-N6-containing Be2N6 monolayer is the lowest-energy configuration in 2D forms with a stoichiometry of 1 : 3, and therefore could be synthesized experimentally. Furthermore, the Be2N6 monolayer is an indirect semiconductor with a band gap of 1.71 eV at the hybrid functional level, close to that of the bulk amorphous silicon ∼1.6 eV widely used in solar cells. At this point, the high electron mobility of up to ∼104 cm2 V−1 s−1 and visible-light absorption of ∼105 cm−1 are observed for the Be2N6 monolayer. If realized, it will not only enrich the knowledge of the bonding nature of nitrogen but could also have potential applications in electronics and optoelectronics

Back analysis of long-term stability of a 92 m span ancient quarrying cavern

Long-term stability of large-span caverns is a challenging issue for design and construction of underground rock engineering. The Heidong cavern group consisting of 21 caverns was constructed about 1400 years ago for quarrying in massive Cretaceous tuff. The cavern No. 5 of the Heidong cavern group is characterized by an unsupported span up to 92 m, with the overburden thickness of only 3–25 m. To analyze its long-term stability, a detailed investigation was conducted to obtain its geometry and rock mass characteristics, and to monitor surrounding rock displacements. Based on field survey and laboratory tests, numerical simulations were performed using the finite difference code FLAC3D. The analysis results revealed that for the long-term stability of the cavern No. 5, some major factors should be carefully considered, such as cavern excavation method in hard massive rocks, site investigation using trial pits, tools like short iron chisel and hammer for manual excavation, geometric dome roof, and waste rocks within abutment or on the floor. The highlights of the technologies obtained from this large-scale ancient underground project can provide reference for other similar project excavations in practice

Preliminary Discussion on Monitoring of Steel Support Axis Force in Metro Engineering

Axial force monitoring of steel support is one of the important factors for foundation pit safety monitoring. In the monitoring of steel support, there are many problems, such as unreasonable installation of axonometer, irregular monitoring behavior of axonometer, incomplete analysis of axial force and imperfect early warning system. Collecting many engineering cases, and in-depth analysis and research on the problems and irregular behavior of steel support axial force monitoring in every link. The influencing factors and control measures of steel support axial force are discussed in detail, and some useful conclusions are obtained. It has been applied in the actual monitoring work and achieved good results. It is of great significance to guide subway safety construction and promote the development of axle force monitoring industry