Human Factors Analysis in Software Engineering

The general human factors analysis analyzes human functions, effects and influence in a system. But in a narrow sense, it analyzes human influence upon the reliability of a system, it includes traditional human reliability analysis, human error analysis, man-machine interface analysis, human character analysis, and others. A software development project in software engineering is successful or not to be completely determined by human factors. In this paper, we discuss the human factors intensions, declare the importance of human factors analysis for software engineering by listed some instances. At last, we probe preliminarily into the mentality that a practitioner in software engineering should possess. Key words human factors analysis - software engineering - software reliability CLC number TP 311.5 Foundation item: Supported by the National Natural Science Foundation of China (60173013)Biography: Xu Ren-zuo (1946-), male, Professor, research direction: software engineering, software reliability engineering, software safety and software testing.

Stability and Influence Factors Analysis of Wharf Slope on Slippery Stratum

With the growing tension of port shoreline resource in Three Gorges Reservoir area, many wharfs can only be constructed on slippery stratum with poor geological condition, which means buckling failure occurs easily. FEM strength reduction method is used in analyzing slope stability of a wharf in Chongqing, and its accuracy is verified by comparing the acquired results with the computation of traditional limit equilibrium method. On this basis, the influences of reservoir water level variation, overload and backfill material behind the retaining wall, and soil share strength of wharf slope on slippery stratum are analyzed. Analysis shows that, there＇ s a most adverse water level in wharf slope, and the engineering proposals with a certain practical significance such as improve the drainage behind retaining wall, controll overload and improve the strength of backfill soil and subsoil are suggested.

Evaluation of Yarn Quality and Optimization of Cotton Spinning Parameter Based on Factors Analysis

In this paper, the spinning parameters are optimized by using the method of factor analysis. The yarns obtained from four different spinning parameters are evaluated by this method. Two common factors, fineness unevenness and tenacity level, are extracted from the seven yarn-quality indexes. The accumulative contribution percentage of the two factors is up to 91.813%,and much information in the yarn-quality indexes is reflected by the two factors. Then the score of each factor is calculated to evaluate the quality of yarn. Based on that, the techniques are optimized. The result is well in line with spinning practices, so it is testified feasibly to use this method to optimize spinning parameter.

Modeling Analysis of Factors Influencing Wind-Borne Seed Dispersal: A Case Study on Dandelion

A weed is a plant that thrives in areas of human disturbance, such as gardens, fields, pastures, waysides, and waste places where it is not intentionally cultivated. Dispersal affects community dynamics and vegetation response to global change. The process of seed disposal is influenced by wind, which plays a crucial role in determining the distance and probability of seed dispersal. Existing models of seed dispersal consider wind direction but fail to incorporate wind intensity. In this paper, a novel seed disposal model was proposed in this paper, incorporating wind intensity based on relevant references. According to various climatic conditions, including temperate, arid, and tropical regions, three specific regions were selected to establish a wind dispersal model that accurately reflects the density function distribution of dispersal distance. Additionally, dandelions growth is influenced by a multitude of factors, encompassing temperature, humidity, climate, and various environmental variables that necessitate meticulous consideration. Based on Factor Analysis model, which completely considers temperature, precipitation, solar radiation, wind, and land carrying capacity, a conclusion is presented, indicating that the growth of seeds is primarily influenced by plant attributes and climate conditions, with the former exerting a relatively stronger impact. Subsequently, the remaining two plants were chosen based on seed weight, yielding consistent conclusion.

Comparative Analysis of the Factors Influencing Metro Passenger Arrival Volumes in Wuhan, China, and Lagos, Nigeria: An Application of Association Rule Mining and Neural Network Models

This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfaction. It addresses a significant research gap in understanding metro passengers’ dynamics across cultural and geographical contexts. It employs questionnaires, field observations, and advanced data analysis techniques like association rule mining and neural network modeling. Key findings include a correlation between rainy weather, shorter waiting times, and higher arrival volumes. Neural network models showed high predictive accuracy, with waiting time, metro satisfaction, and weather being significant factors in Lagos Light Rail Blue Line Metro. In contrast, arrival patterns, weather, and time of day were more influential in Wuhan Metro Line 5. Results suggest that improving metro satisfaction and reducing waiting times could increase arrival volumes in Lagos Metro while adjusting schedules for weather and peak times could optimize flow in Wuhan Metro. These insights are valuable for transportation planning, passenger arrival volume management, and enhancing user experiences, potentially benefiting urban transportation sustainability and development goals.

Using Factor Analysis to Determine the Factors Impacting Learning Python for Non-Technical Business Analytics Graduate Students

This pioneering research represents a unique and singular study conducted within the United States, with a specific focus on non-technical graduate students pursuing degrees in business analytics. The primary impetus behind this study stems from the escalating demand for data-driven professionals, the diverse academic backgrounds of students, the imperative for adaptable pedagogical methods, the ever-evolving landscape of curriculum designs, and the overarching commitment to fostering educational equity. To investigate these multifaceted dynamics, we employed a data collection method that included the distribution of an online survey on platforms such as LinkedIn. Our survey reached and engaged 74 graduate students actively pursuing degrees in Business Analytics within the United States. This comprehensive research is the first and only one of its kind conducted in this context, and it serves as a vanguard exploration into the challenges and influences that shape the learning journey of Python among non-technical graduate Business Analytics students. The analytical insights derived from this research underscore the pivotal role of hands-on learning strategies, exemplified by practice exercises and assignments. Moreover, the study highlights the positive and constructive influence of collaboration and peer support in the process of learning Python. These invaluable findings significantly augment the existing body of knowledge in the field of business analytics. Furthermore, they offer an essential resource for educators and institutions seeking to optimize the educational experiences of non-technical students as they acquire essential Python skills.

Identifying the best common factor model via exploratory eactor analysis

Currently,there is no solid criterion for judging the quality of the estimators in factor analysis.This paper presents a new evaluation method for exploratory factor analysis that pinpoints an appropriate number of factors along with the best method for factor extraction.The proposed technique consists of two steps:testing the normality of the residuals from the fitted model via the Shapiro-Wilk test and using an empirical quantified index to judge the quality of the factor model.Examples are presented to demonstrate how the method is implemented and to verify its effectiveness.

Status quo and factors of depression and anxiety in patients with non-muscle invasive bladder cancer after plasma electrocision

BACKGROUND Bladder cancer is a type of cancer with a high incidence in men.Plasma electrosurgery(PES)is often used in the treatment of bladder cancer.Postoperative complications often cause depression and anxiety in patients after surgery.AIM To investigate the current state of depression and anxiety after PES in patients with non-muscle-invasive bladder cancer and analyze the factors affecting them.METHODS A retrospective study was conducted to compare the baseline data of patients by collecting their medical history and grouping them according to their mental status into negative and normal groups.Logistic regression analysis was used to explore the risk factors affecting the occurrence of anxiety and depression after surgery in patients with bladder cancer.RESULTS Comparative analyses of baseline differences showed that the patients in the negative and normal groups differed in terms of their first surgery,economic status,educational level,and marital status.A logistic regression analysis showed that it affected the occurrence of anxiety in patients with bladder cancer,and the results showed that whether the risk factors were whether or not it was the first surgery,monthly income between 3000 and 3000-6000,secondary or junior high school education level,single,divorced,and widowed statuses.CONCLUSION The risk factors affecting the onset of anxiety and depression in bladder cancer patients after PES are the number of surgeries,economic status,level of education,and marital status.This study provides a reference for the clinical treatment and prognosis of bladder cancer patients in the future.

Examining the Hypothesis of Common Factors Shared by Different Addictive Behaviors and Gender Effects on Propensity to Addiction Type

Background: From the two facts reported by previous research: 1) frequent co-occurrence of more than one addictive behavior, 2) childhood adversities identified as origins of different types of addictive behaviors, it is assumed that all types of addictive behaviors, regardless of substance, behavioral, or relationship, share common factors which have not yet been proven by epidemiological research. The Shorter PROMIS Questionnaire (SPQ) was previously developed to assess 16 types of addictive behaviors. Its factor structure, however, has not been fully investigated. Confirming the factor structure will enable us to hypothesize the common factor(s) shared by all, or if not all, most types of addictive behaviors. Aims: This study aimed at 1) examining the factor structure of the SPQ, 2) confirming the reliability of the questionnaire, and 3) examining the impacts of gender and age on each addictive behavior. Methods: Data obtained from 232 Japanese adults who completed all items of the SPQ were used for the analyses. After confirming the one-factor structure model for each of the 16 subscales, the validity of the one-factor structure of the SPQ was evaluated using Confirmatory Factor Analysis (CFA), by adapting 16 subscale scores as observed variables. If its validity was not confirmed, another model which showed better compatibility to the data was explored. The reliability of the SPQ as well as that of all 16 subscales was evaluated. Also, the impacts of gender and age on each subscale score were examined. Results: The one-factor structure for each of the 16 subscales was confirmed. The compatibility of the SPQ one-factor model was not acceptable. The best fit model was a bi-factor model in which one main factor was shared by all 16 subscales, and three factors were shared by some specific addictive behaviors. Male respondents were more likely than female respondents to show high scores in Alcohol, Tobacco, Gambling, Sex, and Recreational Drugs, and low scores only in Shopping. Respondents’ age did not impact any of the 16 subscale scores. Conclusion: It was demonstrated that there are common factors shared by all different types, as well as selected types of addictive behaviors, by conducting CFAs of the SPQ. Reliability was proven for the SPQ and for all 16 subscales. Male respondents were more likely to show physically hedonic addictive behaviors.

Analysis of the Employment Situation of Non Private Enterprises in Various Regions of China

In the past 30 years, Chinese enterprises have been a hot topic of discussion and concern among the general public in terms of economic and social status, ownership structure, business mechanism, and management level. Solving the problem of employment for the people is an important prerequisite for their peaceful living and work, as well as a prerequisite and foundation for building a harmonious society. The employment situation of private enterprises has always been of great concern to the outside world, and these two major jobs have always occupied an important position in the employment field of China that cannot be ignored. With the establishment of the market economy system, individual and private enterprises have become important components of the socialist economy, making significant contributions to economic development and social progress. The rapid development of China’s economy, on the one hand, is the embodiment of the superiority of China’s socialist market economic system, and on the other hand, it is the role of the tertiary industry and private enterprises in promoting the national economy. Since the 1990s, China’s private enterprises have become a new economic growth point for local and even national countries, and are one of the important ways to arrange employment and achieve social stability. This paper studies the employment of private enterprises and individuals from the perspective of statistics, extracts relevant data from China statistical Yearbook, uses the relevant knowledge of statistics to process the data, obtains the conclusion and puts forward relevant constructive suggestions.

Analysis on Fuji Apple Tree Structures and Related Factors under Different Pruning Modes

To determine the correlations between the tree structuresof Fuji apple with different pruning modes and each factor, the data about 3 tree structures which were free spindle short shoot, free spindle long shoot and slenderspindle short shoot in Xingtang County of Hebai Province were investigated, then by SPSS anal- ysis, the correlations between the taperingness and each growth factor of inserted small branch were compared. The results showed that the taperingness of central trunk of free spindle dwarf-shoot Fuji apple treeshad negative correlations with each factor of inserted small branch, while the taperingness of central trunk of free spin- dle long-shoot Fuji apple treeshad positive correlations with each factor of inserted small branch, the taperingness of central trunk of slenderspindle short-shootFuji ap- ple treeshad negative correlation with total thickness of inserted small branch, but had positive correlations with other factors. This study can provide a scientifictheo- retical basis for the pruning technology of high-density planting trees grafting by dwarfing self-rooted rootstock.

Rutting influencing factors and prediction model for asphalt pavements based on the factor analysis method

To clarify the importance of various influencing factors on asphalt pavement rutting deformation and determine a screening method of model indicators,the data of the RIOHTrack full-scale track were examined using the factor analysis method(FAM).Taking the standard test pavement structure of RIOHTrack as an example,four rutting influencing factors from different aspects were determined through statistical analysis.Furthermore,the common influencing factors among the rutting influencing factors were studied based on FAM.Results show that the common factor can well characterize accumulative ESALs,center-point deflection,and temperature,besides humidity,which indicates that these three influencing factors can have an important impact on rutting.Moreover,an empirical rutting prediction model was established based on the selected influencing factors,which proved to exhibit high prediction accuracy.These analysis results demonstrate that the FAM is an effective screening method for rutting prediction model indicators,which provides a reference for the selection of independent model indicators in other rutting prediction model research when used in other areas and is of great significance for the prediction and control of rutting distress.

3D Modeling and Determination of Factors Responsible for Zinc-Lead Mineralization in the Mehdiabad Deposit,Central Iran,based on Statistical Analysis of Geochemical Data

Although the Mehdiabad zinc-lead deposit is one of the most well-known deposits in the central Iran structural zone,the genesis of the deposit remains controversial.The host rock of the ore is a dolomitic limestone of the Lower Cretaceous Taft Formation.In the two main orebodies of the deposit,which includes the Black Hill and East Ridge ore zones,the oxide and sulfide ores are observed at the surface and at depth,respectively.The elements Zn,Fe,Mn and Mg are more abundant in the East Ridge ore zone(in both sulfide and oxide ores),with Ba,Pb,Ag and Cu being more abundant in the Black Hill oxide ore.Based on the distribution of elements and their correlation with each other in these ore zones,the elements are divided into three general groups,that of terrigenous elements,chemically-deposited elements and oreforming(hydrothermally deposited)elements,a division that is supported by the results of factor analyses.The spatial distribution of elements is jointly affected by contact with host rocks,the boundary of oxide-sulfide ores and fault zones.The main factors governing the distribution of elements are the mechanical transfer of detrital sediments,chemical sedimentation,transfer by hydrothermal fluids,oxidation and surface dissolution,all of which affected the spatial distribution of elements.The ore-forming elements are mostly affected by hydrothermal fluids and oxidation.This study not only provides additional information about the genesis of the Mehdiabad deposit,but also could assist in the exploitation of ore and further exploration purposes.The results of this study can aid in the exploration and exploitation of the Mehdiabad deposit and similar deposits in the region.

Main Controlling Factors and Dominant Reservoir Series Analysis of Es_3 in the Qibei Area of Qikou Sag

Based on analysis of geophysical data such as core observation, rock slices identification, physical property, scanning electron microscope, X-ray diffraction, logging data etc., 16 factors of sedimentation, diagenesis, fluid pressure, and their relationships with reservoir physical property were analyzed, and the results indicate sedimentation is the internal factor controlling the reservoir property, diagenesis is the external and final decisive factor and abnormal fluid pressure is an important factor preserving the deep reservoir property. Quantitative characterization of diagenesis indicates that compaction and dissolution are more important than cementation and they respectively cause porosity change of-23.6% and 7.7% and -6.2%. Through optimizing 11 main controlling factors and constructing reservoir evaluation index （REI） according to the hierarchical cluster and principal component analysis, reservoir classification standard was established and reservoirs were divided into four classes. The studies show that Es~ SQ4 consists mainly of class I and II, while Es~ SQ6 is mainly of class III and II; the favorable zone is the north and south slope of Qibei sub-sag and the Liujianfang fault-nose. The successful application of the quantitative and comprehensive evaluation in the Qibei area verifies the advanced, practicable method of less artificial factor is suitable for the low porosity and permeability reservoir.

Analysis and Optimisation of Halomonas Growth Factors Based on PCA and RSM

The biomass of petroleum-degrading bacteria, such as Halomonas spp., is crucial to the alleviation of severe oil spills through bioremediation. In this paper, the bacterium(HDMP1) was isolated and identified. Growth factors were analysed and optimised through the single-factor experiments, the factor analysis(FA), the principal component analysis(PCA), and the response surface methodology(RSM). Results indicated that HDMP1 was identified as genus Halomonas. In the single-factor experiments, the range of suitable growth conditions for HDMP1 covered: a salt concentration of 2%-4%, a medium pH value of approximately 9, an inoculum concentration of 1.0%, a substrate concentration of 1.0%-1.4%, and a rotation rate of 140 r/min. The evaluation by FA and PCA indicated that three significant growth factors were the salt concentration, the pH value, and the rotation rate. A maximum biomass of HDMP1 was obtained under the conditions covering a salt concentration of 3.5%, a medium pH of 8, and a rotation rate of 151 r/min by optimization.

Transarterial Chemoembolization Combined with Apatinib for Treatment of Advanced Hepatocellular Carcinoma:Analysis of Survival and Prognostic Factors

Objective Apatinib is a novel inhibitor of vascular endothelial growth factor receptor-2.The goal of this study was to evaluate overall survival(OS)after a combination of transarterial chemoembolization(TACE)and apatinib in patients with advanced hepatocellular carcinoma(HCC)and to identify the factors affecting patient survival.Methods Fifty-one patients with advanced HCC who received TACE in combination with apatinib in our hospital from June 2015 to May 2017 were enrolled.The OS and progression-free survival(PFS)were calculated using the Kaplan-Meier method.The log-rank test and Cox regression model were used to determine the factors affecting OS.Results The median OS and PFS of the patients were 15 months and 10 months,respectively.The 1-,2-,and 3-year survival rates were 64.7%,23.5%,and 1.8%,respectively.Univariate survival analysis showed that patients with Child-Pugh A(P=0.006),reduction rate of proper hepatic artery(P=0.016),hand-foot syndrome(P=0.005),secondary hypertension(P=0.050),and without ascites(P=0.010)had a better OS.Multivariate analysis showed that hand-foot syndrome(P=0.014),secondary hypertension(P=0.017),and reduction rate of proper hepatic artery(P=0.025)were independent predictors of better OS.Conclusion TACE combined with apatinib is a promising treatment for advanced HCC.Hand-foot syndrome,secondary hypertension,and the reduction rate of proper hepatic artery were associated with a better OS.

Analysis of factors influencing the Henry Hub natural gas price based on factor analysis

Henry Hub as an important transaction hub for natural gas sets the gas price standard in the USA. In this paper, the factors influencing Henry Hub natural gas prices are analyzed, and the major factors determining the price levels in the period between January 1997 and December 2016 are studied. It is found that economic conditions, total energy demand, US dollar exchange rate and gas consumption are the major factors. The mechanism of each factor influencing the Henry Hub natural gas price is also explored in the paper.

An Analysis of Water Environment Factors and an Evaluation of Water Quantity of Liangzi Lake

The experiments of single factor evaluation method, principal component analysis and voronoi area weighting factor method on the sample data of Liangzi Lake in October 2012 combined with the national surface water environment quality standards can get the map of comprehensive water quality distribution by Kriging interpolation. The analysis shows, the grades of comprehensive water quality gained by three methods are all only class III or class IV, and the quality of water is different from east and west that the water quality of east is better. However, the percent of IV class water is higher in the result of single factor evaluation method means class IV is the main grade of water quality. The result of principal component analysis shows the percent of class Ⅲ water is higher than other classes. The result of voronoi area weighting factor method shows the percent of IV class is higher than other classes. CODMn is the main factor that influences the method of singal factor evaluation and reduces the grade of water quality overall. The effect of single factor is reduced by principal component analysis, and the analysis on water quality is more accurate. The voronoi area weighing factor method reduces the effect of single factor and extends the content, can make a comprehensive evaluation on water quality.

Analysis on Nutritional Risk Screening and Influencing Factors of Hospitalized Patients in Central Urban Area

Rational nutritional support shall be based on nutritional screening and nutritional assessment. This study is aimed to explore nutritional risk screening and its influencing factors of hospitalized patients in central urban area. It is helpful for the early detection of problems in nutritional supports, nutrition management and the implementation of intervention measures, which will contribute a lot to improving the patient＇s poor clinical outcome. A total of three tertiary medical institutions were enrolled in this study. From October 2015 to June 2016, 1202 hospitalized patients aged ≥18 years were enrolled in Nutrition Risk Screening 2002（NRS2002） for nutritional risk screening, including 8 cases who refused to participate, 5 cases of same-day surgery and 5 cases of coma. A single-factor chi-square test was performed on 312 patients with nutritional risk and 872 hospitalized patients without nutritional risk. Logistic regression analysis was performed with univariate analysis（P〈0.05）, to investigate the incidence of nutritional risk and influencing factors. The incidence of nutritional risk was 26.35% in the inpatients, 25.90% in male and 26.84% in female, respectively. The single-factor analysis showed that the age ≥60, sleeping disorder, fasting, intraoperative bleeding, the surgery in recent month, digestive diseases, metabolic diseases and endocrine system diseases had significant effects on nutritional risk（P〈0.05）. Having considered the above-mentioned factors as independent variables and nutritional risk（Y=1, N=0） as dependent variable, logistic regression analysis revealed that the age ≥60, fasting, sleeping disorders, the surgery in recent month and digestive diseases are hazardous factors for nutritional risk. Nutritional risk exists in hospitalized patients in central urban areas. Nutritional risk screening should be conducted for inpatients. Nutritional intervention programs should be formulated in consideration of those influencing factors, which enable to reduce the nutritional risk and to promote the rehabilitation of inpatients.

Analysis of the Current Status and Influencing Factors of the Readiness for Discharge of Patients after Prostate Cancer Surgery Based on the Concept of Enhanced Recovery after Surgery (ERAS)

Objective To investigate the level of readiness for discharge of patients after prostate cancer surgery based on the concept of Enhanced Recovery After Surgery (ERAS), and to explore its influencing factors, so as to provide references for improving the readiness for discharge of patients after prostate cancer surgery. Methods The general information questionnaire, the discharge preparation scale, and the discharge guidance quality scale were used to investigate 119 patients discharged from the urological surgery department of a tertiary A-level hospital in Guangzhou after radical prostatectomy. Results The total score of discharge readiness of patients after radical prostatectomy was 147.74 ± 35.71 points, which was at a lower middle level and the total score of discharge guidance quality was 180.68 ± 38.91 points, which was at a medium level. Multiple linear regression analysis showed that education level, family monthly income, Gleason score, whether to perform lymphatic dissection, whether to discharge with a urinary catheter, and the quality of discharge guidance were the main factors influencing the readiness for discharge of patients after prostate cancer surgery. Conclusion In clinical nursing work, it is necessary to implement individualized health education according to the characteristics and needs of different patients to improve the level of preparation for discharge of patients after prostate cancer surgery.