Importance Ranking of Accident Factors of Construction Tower Crane by AHP Technique

In Korea construction industry, the increase of tower crane’s usage continuously and the accidents of tower crane are increasing simultaneously. But research on tower crane is insufficient for reducing the tower crane accident. This study aims to derive the importance ranking of accident factors of cab-control tower crane by AHP analysis. AHP survey was conducted on experts such as construction engineer, construction manager, safety engineer, and tower crane operator, who have more than 10-year career. The results of AHP analysis reveal that top ranking factor of cab-control tower crane’s accident is erection work. Therefore, the derived factors should be managed, and the priority measures taken for reducing the tower crane accidents according to the ranking of accident factors.

A Web-Based Approach for the Efficient Management of Massive Multi-source 3D Models

Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development of real-scene 3D applications in China.In this paper,we address this challenge by reorganizing spatial and temporal information into a 3D geospatial grid.It introduces the Global 3D Geocoding System(G_(3)DGS),leveraging neighborhood similarity and uniqueness for efficient storage,retrieval,updating,and scheduling of these models.A combination of G_(3)DGS and non-relational databases is implemented,enhancing data storage scalability and flexibility.Additionally,a model detail management scheduling strategy(TLOD)based on G_(3)DGS and an importance factor T is designed.Compared with mainstream commercial and open-source platforms,this method significantly enhances the loadable capacity of massive multi-source real-scene 3D models in the Web environment by 33%,improves browsing efficiency by 48%,and accelerates invocation speed by 40%.

Mutagenesis reveals that the rice OsMPT3 gene is an important osmotic regulatory factor

Plant mitochondrial phosphate transporters regulate phosphate transport and ATP synthesis. Determining whether they function in abiotic stress response process would shed light on their response to salt stress. We used the CRISPR/Cas9 gene-editing system to mutagenize two mitochondrial phosphate transporters, OsMPT3;1 and OsMPT3;2, to investigate their regulatory roles under salt stress. Two cas9(CRISPR-associated protein9)-free homozygous mutants, mpt33 and mpt30, were confirmed to be stable. Both OsMPT3;1 and OsMPT3;2 were markedly induced by salt stress, and their mutagenesis strongly inhibited growth and development, especially under salt stress. Mutagenesis sharply reduced the accumulation of ATP, phosphate, calcium, soluble sugar, and proline and increased osmotic potential, malondialdehyde, and Na^+ /K^+ ratio under salt stress. Both mutants demonstrate normal growth and development in the presence of ATP, revealing high sensitivity to exogenous ATP under salt stress. The mutants showed lowered rates of Na^+ efflux but also of K^+ and Ca^(2+) influx under salt stress. Mutagenesis of OsMPT3;2 altered the enrichment profiles of differentially expressed genes involved mainly in synthesis of secondary metabolites, metabolism of glycolysis, pyruvate, tricarboxylic acid cycle, in response to salt stress. The mutant displayed significant accumulation differences in 14 metabolites involved in 17 metabolic pathways, and strongly up-regulated the accumulation of glutamine, a precursor in proline synthesis, under salt stress. These findings suggest that the OsMPT3 gene modulates phosphate transport and energy supply for ATP synthesis and triggers changes in accumulation of ions and metabolites participating in osmotic regulation in rice under salt stress, thus increasing rice salt tolerance. This study demonstrates the effective application of CRISPR/Cas9 gene-editing to the investigation of plant functional genes.

Generating Decision Trees Method Based on Improved ID3 Algorithm

The ID3 algorithm is a classical learning algorithm of decision tree in data mining.The algorithm trends to choosing the attribute with more values,affect the efficiency of classification and prediction for building a decision tree.This article proposes a new approach based on an improved ID3 algorithm.The new algorithm introduces the importance factor λ when calculating the information entropy.It can strengthen the label of important attributes of a tree and reduce the label of non-important attributes.The algorithm overcomes the flaw of the traditional ID3 algorithm which tends to choose the attributes with more values,and also improves the efficiency and flexibility in the process of generating decision trees.

Roads and Ways to Better Listening

Wilga M.Rivers points out that people get 45% information in life by listening while 30% by speaking, which proves that listening is a very important aspect of linguistic communication, and that listening is an important method for studying and mastering a language. As is known to all, language is an important tool for communication, while speaking and listening are the most original, important and basic parts of the language and are also important ways for the human to know the world and the inner minds of ourselves. Listening, speaking, reading and writing are so important that we put them in the first position. Listening ability refers not only to the direct listening skill, but also to the learners＇ linguistic ability, the cultural knowledge and the thinking ability. Improving listening ability is a complicated process; therefore, we should develop our skills, enrich our knowledge and improve our analyzing and inferring abilities.

Identification of important factors influencing nonlinear counting systems

Identifying factors that exert more influence on system output from data is one of the most challenging tasks in science and engineering.In this work,a sensitivity analysis of the generalized Gaussian process regression(SA-GGPR)model is proposed to identify important factors of the nonlinear counting system.In SA-GGPR,the GGPR model with Poisson likelihood is adopted to describe the nonlinear counting system.The GGPR model with Poisson likelihood inherits the merits of nonparametric kernel learning and Poisson distribution,and can handle complex nonlinear counting systems.Nevertheless,understanding the relationships between model inputs and output in the GGPR model with Poisson likelihood is not readily accessible due to its nonparametric and kernel structure.SA-GGPR addresses this issue by providing a quantitative assessment of how different inputs affect the system output.The application results on a simulated nonlinear counting system and a real steel casting-rolling process have demonstrated that the proposed SA-GGPR method outperforms several state-of-the-art methods in identification accuracy.

Numerical Study of Bifurcated Blood Flow in Three Different Blood Viscosity Models

This study aimed to analyze the hemodynamic effects of bifurcated vessels using different bloodviscosity models.Three-dimensional models of bifurcated vessels in the popliteal artery were constructed basedon CT images,and hemodynamic parameters of the Newtonian,Casson,and two-phase models were calculatedby the computational fluid dynamics method.Blood flowed through the popliteal artery.Blood flow velocitychanged after the bifurcated vessel,with accelerated blood flow velocity in the anterior tibial artery.A lowvelocity vortex region with a region of low wall shear stress(WSS)was generated outside the bifurcated vessel.Local non-Newtonian importance factors of great than 1(i.e.,I_(L)>1)occurred during the cardiac cycle,andI_(L)>1.75 occurred at the beginning and end of the cycle.Compared with the Casson and two-phase models,theNewtonian model has a larger vortex region and lower WSS.Low-velocity vortex regions and low WSS regionsin the bifurcated vessels may contribute to the development of atherosclerosis.Blood exhibited non-Newtonianfluid properties in bifurcated vessels(I_(L)>1),and the effect of non-Newtonian properties was more pronouncedat the beginning and end of heartbeats(I_(L)>1.75).The Newtonian model predicts a higher risk of atherosclerosisformation and the effect of non-Newtonian properties of blood should be considered in hemodynamic studies.

Risk-Identification-Based Hybrid Method for Estimating the System Reliability of Existing Jacket Platforms Under Fire

This paper proposes a risk-identification-based hybrid method for estimating the system reliability of steel jacket structures under fire.The proposed method starts with risk identification;according to the results of hazard identification and Dow’s fire and explosion index(F&EI) methodology,the most dangerous hazard sources are determined.In term of each equipment layout in steel jacket structures,fire load is imposed and elasto-plastic analysis is performed.According to the deformed state of steel jacket structures,the weakest failure mode of steel jacket structures is identified.In order to know the effect on ultimate bearing capacity of the offshore structural system,a series of elasto-plastic analyses are performed in which single failure element contained in the weakest failure mode is removed from the whole offshore platform structural system.Finally,the failure function of the steel jacket structure is generated and the failure probability of the steel jacket structure system is estimated under fire by genetic algorithm via MATLAB program.