Influence Of Human Factors Research Articles

Comparative analysis of spatial variation in forest fire drivers between boreal and subtropical ecosystems in China

Drivers of forest fire are complex and may spatially vary between different ecosystems; thus their identification is critical for the development of effective fire management strategies. Here we identified the spatial distribution trend and drivers of forest fire over the period of 2000–2016 in the boreal and subtropical forest ecosystems in China using trend analysis and the geographically weighted negative binomial regression model (GWNBR). The results reveal that forest fires were generally shifting from the boreal to sub-tropical region and that there were significant (p < 0.05) spatial differences in fire drivers between boreal and subtropical forest ecosystems. Forest fires in the boreal ecosystem were driven by meteorological, topographic and human factors that had clear spatial variation. In contrast, forest fire occurrence in subtropical forest ecosystem was spatially stationary; i.e., constant throughout the area. Our results suggest that as socio-economy continues developing, the influence of human factors on forest fires in different ecosystems will be more complex. Future national forest fire management policies should consider local condition to establish region-specific management strategies due to significant spatial differences in major forest fire drivers between different ecosystems.

Quantitative assessment of radiographic control informativeness using ROC analysis

In industrial radiography the issue of replacment film detectors by digital ones becomes increasingly relevant. Also remains unresolved the question of an objective comparison of various radiographic testing (RT). This article presents the results of research, aimed at obtaining a quantitative assessment of RT technology informativeness.In order to construct ROC curves, characterizing the quality of binary classification, using a specific RT technology, there was designed and manufactured a sample test, containing a simulation of the most difficult to detect discontinuities. Such test sample was made using additive technology. Developed manufacturing technology made it possible to ensure sufficient accuracy of linear dimensions, taking into account the product’s design features.After exposure of test object to various detectors, there was a decoding procedure, conducted by experts, whose task was to establish the presence / absence of a defect in analyzed element of the image. Applying such technique, used in results analysis of deciphering the images of sample test, made it possible to minimize the influence of human factor and obtain ROC curves, reflecting the capabilities of RT technology only. The subsequent determination of ROC curves parameters allows to conduct a comparative analysis of informativeness of the technologies under consideration.

Degradation feature extraction method for piezoelectric ceramic of ultrasonic motor based on DCT-SV cross entropy

Crack on piezoelectric ceramic is the main reason leading to failure of ultrasonic motors. A novel degradation feature extraction method based on discrete cosine transform (DCT) -singular value (SV) cross entropy was proposed in this paper. In order to improve the correlation with the crack, the DCT coefficients with the property of energy aggregation, were used to extract fault information. To avoid the influence of human factors in traditional DCT de-noising method, a matrix composed of DCT coefficients was constructed, and the SV cross entropy of the matrix was taken as the degradation feature for ultrasonic motor. A numerical simulated noise was added to the measured signal to verify the anti-noise performance of the feature. Analysis of the experimental results demonstrates that the proposed DCT-SV cross entropy is feasible and effective in indicating the degradation of piezoelectric ceramic in ultrasonic motor.

Relationship of Neotropical otter vestiges with environmental and anthropogenic factors

ABSTRACT The Neotropical otter, Lontra longicaudis (Mustelidae) is a semi-aquatic mustelid that exploits a variety of freshwater habitats. To understand the relative influence of human activities and environmental factors affecting its distribution and habitat use, we conducted systematic, seasonal surveys of otter signs along the middle Guamá River, in Pará state in the eastern Brazilian Amazon. We applied generalized additive models to compare distribution of otters along the river with data collected on environmental factors (landcover type derived from satellite imagery, and in situ measurements of physicochemical water characteristics) and anthropogenic factors (fishing gear in the river and human habitation along the river). Most otter signs (indicators of otter habitat use) occurred along the shoreline of the main river channel during the dry season; we observed fewer signs during peak flow, probably because the shoreline and floodplain are flooded, which hid signs and made access to the floodplain difficult. The best-fit model included variables for proportion of forest, presence of fishing gear and boats, bank steepness, and presence of rock formations and sand banks. Otter occurrence was negatively related to forested area and positively related to the presence of fishing gear and boats. Otters are likely attracted to fish trapped in fishing gear because they can easily predate on the trapped fish.

A hybrid artificial bee colony algorithm for flexible job shop scheduling with worker flexibility

The traditional flexible job shop scheduling problem (FJSP) considers machine flexibility but not worker flexibility. Given the influence and potential of human factors in improving production efficiency and decreasing the cost in practical production systems, we propose a mathematical model of an extended FJSP with worker flexibility (FJSPW). A hybrid artificial bee colony algorithm (HABCA) is presented to solve the proposed FJSPW. For the HABCA, effective encoding, decoding, crossover and mutation operators are designed, and a new effective local search method is developed to improve the speed and exploitation ability of the algorithm. The Taguchi method of Design of Experiments is used to obtain the best combination of key parameters of the HABCA. Extensive computational experiments carried out to compare the HABCA with some well-performing algorithms from the literature confirm that the proposed HABCA is more effective than these algorithms, especially on large-scale FJSPW instances.

Temporal and Spatial Dynamics of Monkeypox in Democratic Republic of Congo, 2000-2015.

Monkeypox is a viral disease with a clinical presentation resembling that of smallpox. Although monkeypox is considered to be an important zoonotic viral disease, its epidemiology remains poorly understood, especially the spatial and temporal distribution of the disease. The present study examined weekly reports of monkeypox cases collected from 2000 to 2015 at the health zone scale in the Democratic Republic of Congo. SaTScan® was performed to identify spatial and temporal clusters of monkeypox cases. Significant primary spatial clusters were detected in the districts of Sankuru and Tshuapa. A centrifugal pattern was found, with significant primary spatial clusters extending over time from Sankuru and Tshuapa to several neighboring districts. Peaks of cases occurred from July to September for the 2000-2002 and 2003-2009 sub-periods and from January to March for the 2010-2015 sub-period. Despite the lack of additional data for confirmation, the increasing of monkeypox reported incidence was observed in the Democratic Republic of Congo during 2000-2015 period and this increase cannot be explain only by the improvements of surveillance systems. The detected spatial clusters were located in the dense rainforest of the Congo basin. The reasons for the excess incidence of monkeypox cases in the central region of the country are unknown, and the relative influence of ecological, environmental, and human factors on the mechanism of emergence of monkeypox has yet to be identified.

Optimization of sand casting performance parameters and missing data prediction.

Due to a wide range of applications, sand casting occupies an important position in modern casting practice. The main purpose of this study was to optimize the performance parameters of sand casting based on grey relational analysis and predict the missing data using back propagation (BP) neural network. First, the influence of human factors was eliminated by adopting the objective entropy weight method, which also saved manpower. The larger variation degree in the evaluation indicators, indicating that the evaluated projects had good discrimination in this regard, the larger weight should be given to these evaluation indicators. Second, the performance parameters of sand casting were optimized based on grey relational analysis, providing a reference for sand milling. The larger the grey relational degree, the closer the evaluated project was to the ideal project. Third, this paper provided a new method for determining the number of hidden neurons in a network according to the mean square error of training samples, and venting quality was predicted based on BP neural network. The relevant theory was deduced before predicting missing data, such that there will be a general understanding regarding the prediction principle of BP neural network. Fourth, to demonstrate the validity of BP neural network adopted in the process of missing data prediction, grey system theory was applied to compare the result of missing data prediction.

Application of machine learning to laboratory safety management assessment

This paper proposes a new method to evaluate laboratory safety management based on machine learning that aims to address the shortcomings of traditional laboratory safety evaluation methods, including poor accuracy, large influence of human factors, and lack of a unified evaluation system. In this paper, the safety data of laboratories in Southwest University were collected using a safety checklist, and the weight of each factor affecting laboratory safety was analyzed using a Fuzzy Analytic Hierarchy Process (FAHP). The simulation results showed that the model gave a more accurate and reasonable safety risk level of the laboratory, verified the rationality and feasibility of the established method, and realized potential loopholes in the process of laboratory management and college students' operations. According to the evaluation results, the machine learning principle and the existing maintenance knowledge of the evaluation knowledge base are applied to provide effective measures and suggestions for users to complete the process of risk assessment. Through risk assessment, the professional skill and the incident control could be improved. The model was easy to operate and has a good application value for ensuring the personal and property safety of laboratory users.

Pengaruh Faktor Manusia keatas Ketidakpastian Projek-Projek Pembaikpulihan: Pendekatan Konseptual

The number of building refurbishment projects has increased significantly over the past few years in Malaysia. The key features of such projects are that these are unique, with high uncertainties especially when these involve structural modifications with sensitive, dangerous and difficult operations as well as the high number of building services involved. From many past studies, uncertainty has always been identified as one of the reasons for poor performance in such projects. This seems to be the case because few considerations were given to the human factor compared to the technical issues. This emphasis is however questionable in the real world. This conceptually based paper therefore aims to determine and understand the influence of human factor on the uncertainties of refurbishment projects. The method used for this study is based on a comprehensive review of related journal papers, book chapters and conference papers from 1997 to 2017. The exercise identified 146 articles initially. 57 papers were subsequently included for further analysis after screening and assessment for eligibility. This study concludes that the human impact element is indeed one of the most important factors that tends to influence the levels of uncertainties in building refurbishment projects. As a result, there is still room for improving the performance of building refurbishment projects. The findings of this study form the basis for an extended investigation to identify the effect of human factors on the uncertainties of building refurbishment projects in Malaysia.

Novel Stenotic Microchannels to Study Thrombus Formation in Shear Gradients: Influence of Shear Forces and Human Platelet-Related Factors.

Thrombus formation in hemostasis or thrombotic disease is initiated by the rapid adhesion, activation, and aggregation of circulating platelets in flowing blood. At arterial or pathological shear rates, for example due to vascular stenosis or circulatory support devices, platelets may be exposed to highly pulsatile blood flow, while even under constant flow platelets are exposed to pulsation due to thrombus growth or changes in vessel geometry. The aim of this study is to investigate platelet thrombus formation dynamics within flow conditions consisting of either constant or variable shear. Human platelets in anticoagulated whole blood were exposed ex vivo to collagen type I-coated microchannels subjected to constant shear in straight channels or variable shear gradients using different stenosis geometries (50%, 70%, and 90% by area). Base wall shears between 1800 and 6600 s−1, and peak wall shears of 3700 to 29,000 s−1 within stenoses were investigated, representing arterial-pathological shear conditions. Computational flow-field simulations and stenosis platelet thrombi total volume, average volume, and surface coverage were analysed. Interestingly, shear gradients dramatically changed platelet thrombi formation compared to constant base shear alone. Such shear gradients extended the range of shear at which thrombi were formed, that is, platelets became hyperthrombotic within shear gradients. Furthermore, individual healthy donors displayed quantifiable differences in extent/formation of thrombi within shear gradients, with implications for future development and testing of antiplatelet agents. In conclusion, here, we demonstrate a specific contribution of blood flow shear gradients to thrombus formation, and provide a novel platform for platelet functional testing under shear conditions.

Biogeographic freshwater fish pattern legacy revealed despite rapid socio‐economic changes in China

AbstractUnderstanding drivers of freshwater fish assemblages is critically important for biodiversity conservation strategies, especially in rapidly developing countries, which often have environmental protections lagging behind economic development. The influences of natural and human factors in structuring fish assemblages and their relative contributions are likely to change given the increasing magnitude of human activities. To discriminate natural and human drivers of fish diversity and assemblage patterns in developing countries with rapid socio‐economic development, a dataset of 908 freshwater fish species and 13 metrics including three categories of both natural (i.e., biogeographic) and human drivers (i.e., economic growth, inland fisheries) in China were analysed with machine learning algorithms (i.e., self‐organizing map, random forest). Here, we found that biogeographic drivers explained 21.8% of the observed fish assemblage patterns in China and remained stronger predictors when compared to human drivers (i.e., 15.6%, respectively). Freshwater fish species richness was positively correlated to rainfall, air temperature, surface water area and inland fisheries production but negatively correlated with urbanization. In addition, the strong structuring effects of climatic variables on Chinese fish richness patterns suggested that the fish assemblages could be particularly vulnerable to climate change. Our results showed that natural biogeographic factors still dominate in driving freshwater fish assemblage patterns despite increased human disturbances on aquatic ecosystems in a rapidly developing country. These findings consequently suggested that we should consider both natural (e.g., climate) and human (e.g., urbanization, inland fisheries) factors when establishing aquatic conservation strategies and priorities for developing countries that are experiencing rapid socio‐economic changes.

Contrasting human influences and macro-environmental factors on fire activity inside and outside protected areas of North America

Human activities threaten the effectiveness of protected areas (PAs) in achieving their conservation goals across the globe. In this study, we contrast the influence of human and macro-environmental factors driving fire activity inside and outside PAs. Using area burned between 1984 and 2014 for 11 ecoregions in Canada and the United States, we built and compared statistical models of fire likelihood using the MaxEnt software and a set of 11 key anthropogenic, climatic, and physical variables. Overall, the full model (i.e. including all variables) performed better (adjusted area under the curve ranging from 0.71 to 0.95 for individual ecoregions) than the model that excluded anthropogenic variables. Both model types (with and without anthropogenic variables) generally performed better inside than outside the PAs. Climatic variables were usually of foremost importance in explaining fire activity inside and outside PAs, with anthropogenic variables being the second most important predictors, even inside PAs. While the individual contributions of anthropogenic variables indicate that fire activity decreased as of function of increasing human footprint, the anthropogenic effects were often substantially greater than those of physical features and were comparable to or even greater than climatic effects in some densely developed ecoregions, both outside and within PAs (e.g. Mediterranean California, Eastern Temperate Forest, and Tropical Wet Forests). Together, these results show the pervasive impact of humans on fire regimes inside PAs, as well as outside PAs. Given the increasing attractiveness of PAs, the implications for adaptive fire management beyond the concept of naturalness in the PAs are discussed. Our assessment of human-altered fire activity could serve as an indicator of human pressure in PAs; however, we suggest that further analysis is needed to understand specific interactions among fire, human pressures, and the environmental conditions at the scale of PAs.

APPROACHES GOING TO DETERMINATION PERIODS OF THE HUMAN FACTOR OF NAVIGATORS DURING SUPERNUMERARY SITUATIONS

Context. The problem of identifying the manifestation of the human factor in the context of utility in maritime transport during emergency situations is considered. The aim of the study is to increase safety in maritime transport by identifying positive and negative human factors, as well as analyzing the behavioral reactions affecting the vessel’s passage parameters. Objective. The aim of the work is to determine the approaches and the construction of software tools to identify periods of manifestation of the human factor of the navigators during abnormal situations. Method. The study identified the types of manifestations of the human factor in the form of intuitive (illogical) behavior of the navigator. The dependence of intuitive behavior, as a reaction, on exceeding the detection threshold of perception of service information, is given. It was determined that the distribution of information load among members of the navigation watch will significantly reduce the detection threshold of the navigator at the time of making management decisions. It was established that the detection step is to determine the balance of information effects on the navigator and his individual polar reactions. The cycle of updating the navigator model is determined by analyzing his individual behavior model of previous intellectual activity. A formal description of the space of alternatives and reactions of the navigator in the form of polar groups at the moment of vessel management is proposed. Software has been developed that allows the analysis of the vessel’s passage trajectory for collision detection and the identification of periods of occurrence of the detection threshold of the navigator. Analysis of the trajectories made it possible to conclude that before the collision the navigator was in active/passive polar states of action, which directly proportional to the speed of the vessel, which confirms the main hypothesis of the study. As a mathematical tool for solving the problem of classifying individual reactions of the navigator, the factor analysis and a training sample are offered – more than nine typical situations, which make it possible to adequately determine polar reactions according to the principle of utility. Results. In order to confirm the adequacy of the proposed formal-logical approaches, an experiment was conducted using the Trainer Professional 5000 navigation simulator (NTPRO 5000). The results of the experiment, as well as the developed software, made it possible to identify the time periods of the negative human factor manifestation of the navigator caused by the information overload and to determine its individual stimulus factors. At the same time, the moment of occurrence of an extraordinary situation was determined by analyzing the passage trajectory of the vessel by means of processing log files by passing the Bosporus strait location. In addition, an algorithm was developed for the formation of the navigator’s model and its updating on the basis of individual periods of the negative manifestation of the human factor. The features of the occurrence of informational imbalance between members of the navigation watch in the event of an emergency situation and features of its identification during the passage of the vessel are considered. The obtained results will allow at a qualitatively new level to approach the analysis of the problem of the influence of human factor on the adequate managerial decisions of the navigator. Conclusions. The proposed formal approaches and the developed software will allow identifying the transition from the controlled adequate state of the navigator to the uncontrolled state with intuitive reactions. The scientific novelty consists in the fact that the developed algorithm of forming a navigator model in a discrete time, which allows to identify its polar reactions during extraordinary situations. The practical significance lies in the fact that the results of the experiment allowed identifying the time periods of the manifestation of the negative human factor of the navigator, caused by the information overload and identifying its individual factors-incentives. Prospects for further research may be the development of software in the form of an expert system defining deviations from a given course during the sea passage, as well as inadequate reactions in the performance of classical maneuvers in case of divergence of ships in constrained areas.

Identifying the gaps in project success research

PurposeThe purpose of this paper is to review the existing literature on project success in academic journals, specifically within the context of construction engineering and management (CEM). It also aims to provide a holistic picture of existing research and to identify research implications in this specific area.Design/methodology/approachThe paper is an extensive literature review of a total of 164 peer-reviewed journal papers between 2007 and 2017, using a mixed bibliographic and bibliometric method that considers annual circulation, institutional and regional contributions, author contributions, citations, categories of research methods and keywords networking.FindingsThere has been an increasing research interest in CEM project success. The largest number of published studies targets the developed regions, especially in Hong Kong, whereas the papers related to the developing economies remain weak. Questionnaire, interview and case study have comprised the main data collection methods, and descriptive data analysis was performed in most of the case/field studies. The subtopic related to the critical success factors (CSFs) is considered as the most popular in the keywords network in the targeted research area. Four implications, namely, megaproject success, project success in developing countries, relationships between CSFs and success outcomes, and the influence of human factors are highlighted in future research.Originality/valueThis paper departs from earlier research by using a mixed bibliographic and bibliometric method, especially facilitating to analyze and illustrate the interlinkages between keywords effectively. Additionally, it provides a clear picture of the existing literature on CEM project success, which contributes to insights for successful construction project management. Finally, the holistic analysis identifies gaps in the body of knowledge, revealing avenues for future research.

Geostatistical analysis of hydrochemical variations and nitrate pollution causes of groundwater in an alluvial fan plain

Geostatistics was used in a typical alluvial fan to reveal its applicability to spatial distribution analysis and controlling mechanisms of groundwater chemistry. Normal distribution test and optimal geostatistical interpolation models for various groundwater quality indicators were discussed in this study. The optimal variogram model of each indicator was determined using prediction error analysis. The influences of human activities and structural factors on the groundwater chemistry were also determined by variability intensity and the sill ratio. The results showed that nitrate content can be served as groundwater quality indicator, which was most sensitive to human activities. The nitrate concentration of both shallow and deep groundwater showed a decreasing trend from the northwest to the southeast. In addition, the spatial distribution of groundwater nitrate was associated with the land-use type and the lithological properties of aquifer. Rapid urbanization in the northwestern part intensified groundwater extraction and aggravated the pollutant input. The central area showed little increase in nitrate content in the shallow and deep groundwater, and the effect of lateral recharge from the upstream water on the deep groundwater in the central area was greater than that of the vertical recharge from shallow groundwater. The present study suggests that geostatistics is helpful for analyzing the spatial distribution and distinguishing the influences of anthropogenic and natural factors on groundwater chemistry.

QUANTITATIVE ASSESSMENT OF RADIOGRAPHIC CONTROL INFORMATIVENESS USING ROC ANALYSIS

In industrial radiography the issue of replacing film detectors with digital ones is becoming increasingly relevant. Also remains unresolved the question of an objective comparison of various radiographic testing (RT). This article presents the results of research, aimed at obtaining a quantitative assessment of RT technology informativeness. In order to construct ROC curves, characterizing the quality of binary classification, using a specific RT technology, there was designed and manufactured a sample test, containing a simulation of the most difficult to detect by RK results (U-shaped grooves 0.1 mm wide and various depths) randomly distributed discontinuities. Such test sample was made using additive technology. Developed manufacturing technology made it possible to ensure sufficient accuracy of linear dimensions, taking into account the product’s design features. After exposure of test object to various detectors, there was a decoding procedure, conducted by experts, whose task was to establish the presence / absence of a defect in analyzed element of the image. Applying such technique, used in results analysis of deciphering the images of sample test, made it possible to minimize the influence of human factor and obtain ROC curves, reflecting the capabilities of RT technology only. The subsequent determination of ROC curves parameters allows to conduct a comparative analysis of informativeness of the technologies under consideration. The example of comparison between detectors Agfa D4 and Agfa D7, given in article’s conclusion, demonstrates the possibilities of presented technique.

СОВЕРШЕНСТВОВАНИЕ ТЕХНОЛОГИИ ПРОВЕДЕНИЯ СТРОИТЕЛЬНО-ТЕХНИЧЕСКИХ ЭКСПЕРТИЗ С ИСПОЛЬЗОВАНИЕМ АППАРАТНО-ПРОГРАММНОГО КОМПЛЕКСА АВТОМАТИЗИРОВАННОЙ ДЕФЕКТОСКОПИИ

In the construction and technical expertise of buildings, inspection is an important and crucial part in the conclusions about the technical condition of the object. It is carried out visually and instrumentally with the interpretation of results by subjective expert methods. The current performance standard of construction and technical inspection has several disadvantages: essential schematics of collection algorithms, simplified diagnostics and coarsening of the analysis of field research results for geometrically extended or constructively complex real estate objects, which are caused by negative influence of human factors on the process of inspection , weather conditions, inaccessibility of the object, low information culture of documenting and archiving survey results. This complicates the dynamic monitoring of the object and is characterized by significant increase in the cost and timing of the repair work due to the delayed diagnosis of defects and the selectivity of the scope of expert research. &#x0D; The proposed system is designed to improve the reliability, objectivity, unification of approaches and information flows associated with the construction and technical expertise of buildings and structures. It is based on photo and video filming of long and hard to reach surfaces of buildings and structures using unmanned aerial vehicles with subsequent automated processing of the material obtained, its intellectual analysis, automated recognition, classification, quantification of installed defects; as well as innovative technology for documenting and automating the adoption of rational organizational and technological decisions in the practice of technical operation and monitoring of the functional reliability of the surveyed real estate.

An Observational Case-Control Study to Determine Human Immunodeficiency Virus and Host Factor Influence on Biomarker Distribution and Serodiagnostic Potential in Adult Pulmonary Tuberculosis.

Influence of host factors, including human immunodeficiency virus (HIV) co-infection, on the distribution and diagnostic potential of previously evaluated biomarkers of pulmonary tuberculosis (PTB), such as anti-antigen 60 (A60) immunoglobulin (Ig) G, anti-A60 IgA, and C-reactive protein (CRP), remain unclear. Anti-A60 IgG, anti-A60 IgA, and CRP in PTB and non-PTB patient sera (n = 404, including smear-positive/negative, culture-positive (SPCP/SNCP) and HIV+ve/−ve) were measured by enzyme-linked immunoassay and statistically analysed. In multinomial logistic regression, expectoration, chest pain, wasting, and culture count positively associated with CRP (p < 0.001), while smear count positively associated with anti-A60 IgG (p = 0.090). Expectoration and enlarged lymph nodes negatively associated with anti-A60 IgA (p = 0.018). Biomarker distribution and diagnostic potential varied significantly by symptoms and bacilli burden, and across different PTB subpopulations. CRP was correlated poorly with anti-A60 antibodies, while anti-A60 IgA and IgG were correlated in non-tuberculosis (TB) and SPCP patients (p < 0.001). When combined, anti-A60 IgG and CRP best discriminated SPCP/HIV−ve from non-TB (AUC: 0.838, 95% CI: 0.783–0.894), while anti-A60 IgA and CRP performed best in discriminating HIV+ve PTB from non-TB (AUC: 0.687, 95% CI: 0.598–0.777). Combined CRP and anti-A60 antibodies had significantly reduced accuracy in SNCP and SNCP/HIV+ve compared to SPCP/HIV−ve subpopulations. The complex relationships between host factors and biomarkers suggest their limited utility, especially in SNCP/HIV+ve subpopulations, highlighting the importance of examining host response and immune biomarkers across relevant patient subpopulations.

Research on Spatial Correlations and Influencing Factors of Logistics Industry Development Level

The logistics industry plays a greater role in the sustainable development of regional economies. The development of the logistics industry between regions is not independent, and there is a spatial correlation due to the existence of spatial spillover effect or spatial expansion among regions. This paper uses the method of entropy weight to evaluate the development level of the logistics industry in 31 provinces in China. On this basis, Moran’s index (Moran’s I), Moran’s I scatter plot, and local indicators of spatial association (LISA) agglomeration plot are used to analyze the overall and local spatial agglomeration characteristics of the logistics industry. Four main factors affecting the spatial relationship of the logistics industry are analyzed by choosing the fixed effect of the spatial error model. We find that: (i) There is spatial agglomeration effect in the development level of the logistics industry from the overall perspective; (ii) regional differentiation of the spatial agglomeration effect of logistics industry development level is obvious from the local perspective; and (iii) the influence of human resource factors on the spatial relationship of logistics development level is declining.

Comparison and Selection of Bridge Type Schemes Based on AHP and Grey Correlation TOPSIS

Determination of the optimal bridge scheme is crucial in the preliminary design stage of bridge construction, and the scientific decision results directly affect the construction and implementation of the whole project. At present, the determination of bridge schemes in mountainous areas is mainly based on empirical judgment, and few theoretical methods can be adopted. Therefore, a comprehensive evaluation model was built for mountainous bridge type scheme by the basic AHP theory, grey relational analysis, and TOPSIS. The model comprehensively considered the various factors affecting the selection of bridge type from the aspects of economy, technology, and society, and 12 evaluation indexes were selected to build a comprehensive evaluation system for the bridge type scheme in mountainous areas. Weight vector of valuation indexes of bridge type was calculated by AHP to reduce the influence of human subjective factors. Then, a weighted grey correlation coefficient decision matrix was constructed by fuzzy mathematics theory and grey correlation analysis, and the relative closeness coefficient between the alternative schemes and the Grey correlation ideal solution was calculated by TOPSIS. Finally, the optimal bridge type scheme was determined based on the relative closeness coefficient. The evaluation model was used to judge three alternative bridge type schemes (A1-A3) of a highway in the mountainous area of Pu'an County, Guizhou Province. The relative closeness coefficients of continuous PC T beam bridge (A1), PC continuous rigid frame bridge (A2), and PC dwarf-tower cable-stayed bridge (A3) were respectively 0.597 7, 0.315 6, and 0.400 3, indicating the first scheme is the best optimized bridge type. Thus, the first bridge scheme was applied to actual bridge construction and achieved good economic and social values. The results show that the evaluation model provides a feasible theoretical method for the decision-making of mountain bridge type.