HV Process Model of Software Development

Software Development Life Cycle (SDLC) is one of the major ingredients for the development of efficient software systems within a time frame and low-cost involvement. From the literature, it is evident that there are various kinds of process models that are used by the software industries for the development of small, medium and long-term software projects, but many of them do not cover risk management. It is quite obvious that the improper selection of the software development process model leads to failure of the software products as it is time bound activity. In the present work, a new software development process model is proposed which covers the risks at any stage of the development of the software product. The model is named a Hemant-Vipin (HV) process model and may be helpful for the software industries for development of the efficient software products and timely delivery at the end of the client. The efficiency of the HV process model is observed by considering various kinds of factors like requirement clarity, user feedback, change agility, predictability, risk identification, practical implementation, customer satisfaction, incremental development, use of ready-made components, quick design, resource organization and many more and found through a case study that the presented approach covers many of parameters in comparison of the existing process models. .

Constructing a Triangular Linkage Model of Government Audit,Social Audit,and Internal Audit to Promote High-Quality Development of Audit Services

It is a complex and important topic to study the linkage mechanism of government audit,social audit,and internal audit in the context of China’s high-quality economic development.The implementation of measures,such as establishing a sound and perfect organizational safeguard mechanism,strengthening project collaborative audit mechanism,enhancing the mechanism for utilizing audit results,and establishing an audit and rectification joint mechanism can promote the efficient operation of the audit supervision system and the high-quality development of audit services.

Comparison of the Development Model of DTP Pharmacy between China and the United States and Its Enlightenment

Objective To systematically analyze the development status of DTP pharmacy in the United States and China,and to find out the problems in China’s DTP pharmacy and put forward some countermeasures and suggestions.Methods Relevant literature was searched and reviewed to study the history,market scale and development trend of DTP pharmacy in the United States and China.Then,the problems in China’s DTP pharmacy were found out.Results and Conclusion DTP pharmacy model in the U.S.has taken shape and is maturing.The high degree of industry concentration is an important feature of the U.S.pharmacy.In contrast,China’s DTP pharmacy started late,and the industry pattern has not yet been finalized.There are still some problems in the DTP pharmacy certification and quality management.It is recommended to promote the rapid development of DTP pharmacies in China by encouraging the outflow of prescription drugs,establishing a third-party pharmacy accreditation organization and strengthening the team of licensed pharmacists and other personnel.

Data-driven casting defect prediction model for sand casting based on random forest classification algorithm

The complex sand-casting process combined with the interactions between process parameters makes it difficult to control the casting quality,resulting in a high scrap rate.A strategy based on a data-driven model was proposed to reduce casting defects and improve production efficiency,which includes the random forest(RF)classification model,the feature importance analysis,and the process parameters optimization with Monte Carlo simulation.The collected data includes four types of defects and corresponding process parameters were used to construct the RF model.Classification results show a recall rate above 90% for all categories.The Gini Index was used to assess the importance of the process parameters in the formation of various defects in the RF model.Finally,the classification model was applied to different production conditions for quality prediction.In the case of process parameters optimization for gas porosity defects,this model serves as an experimental process in the Monte Carlo method to estimate a better temperature distribution.The prediction model,when applied to the factory,greatly improved the efficiency of defect detection.Results show that the scrap rate decreased from 10.16% to 6.68%.

Impact of Hinterland Manufacturing on the Development of Container Ports: Evidence from the Pearl River Delta, China

Container ports and hinterland manufacturing are two important forces of the local participation in economic globalization.This study,taking the Pearl River Delta(PRD),China with an export-oriented economy as an example,applies Huff and panel regres-sion models to evaluate the impact of hinterland manufacturing on the development of container ports during the period of 1993–2019.The results show that 1)the spatial patterns of hinterlands for hub ports help to determine the distribution range and scale of economic variables that affect port throughput;2)the hinterland’s gross manufacturing output has universally positive influence on port through-put,wherein export-oriented processing and the entire manufacturing industry have significantly positive impact on port throughput in 1993–2011 and 2001–2019,respectively;3)the two internal structural factors related to an export-oriented economy,labor-intensive sectors and foreign-funded terminals,have positively moderate the direct influence of hinterland manufacturing on port throughput.Our results highlight the importance of local context in understanding port-manufacturing relationship in developing economies.Based on our findings,policy implications are further proposed to enhance port network organization in PRD.

The generation and properties of human cortical organoids as a disease model for malformations of cortical development

As three-dimensional“organ-like”aggregates,human cortical organoids have emerged as powerful models for studying human brain evolution and brain disorders with unique advantages of humanspecificity,fidelity and manipulation.Human cortical organoids derived from human pluripotent stem cells can elaborately replicate many of the key properties of human cortical development at the molecular,cellular,structural,and functional levels,including the anatomy,functional neural network,and interaction among different brain regions,thus facilitating the discovery of brain development and evolution.In addition to studying the neuro-electrophysiological features of brain cortex development,human cortical organoids have been widely used to mimic the pathophysiological features of cortical-related disease,especially in mimicking malformations of cortical development,thus revealing pathological mechanism and identifying effective drugs.In this review,we provide an overview of the generation of human cortical organoids and the properties of recapitulated cortical development and further outline their applications in modeling malformations of cortical development including pathological phenotype,underlying mechanisms and rescue strategies.

A new production component method for natural gas development planning

Based on an analysis of the limitations of conventional production component methods for natural gas development planning,this study proposes a new one that uses life cycle models for the trend fitting and prediction of production.In this new method,the annual production of old and new wells is predicted by year first and then is summed up to yield the production for the planning period.It shows that the changes in the production of old wells in old blocks can be fitted and predicted using the vapor pressure model(VPM),with precision of 80%e95%,which is 6.6%e13.2%higher than that of other life cycle models.Furthermore,a new production prediction process and method for new wells have been established based on this life cycle model to predict the production of medium-to-shallow gas reservoirs in western Sichuan Basin,with predication error of production rate in 2021 and 2022 being 6%and 3%respectively.The new method can be used to guide the medium-and long-term planning or annual scheme preparation for gas development.It is also applicable to planning for large single gas blocks that require continuous infill drilling and adjustment to improve gas recovery.

Interaction and coordinated development between desertification control and social economy in Xizang,China

Based on the general requirements of the coordinated development of"ecological livable"and"affluent life"in the rural revitalization strategy,the evaluation index system of desertification control was constructed,the interaction between desertification control and regional social economy and the internal space-time coordination mechanism were explored,and the quality of desertification control and its coordination degree with regional economic development were quantitatively analyzed.The decoupling mechanism of desertification governance society economy system were analyzed,and the high level for the government to promote desertification governance,constructing ecological economy coordinated development pattern to provide decision basis to Xizang desertification governance-social economic system interaction and coupling coordination development as the research object,introducing the coupling decoupling model to measure the coupling coordination model and system coordination and decoupling decoupling.Desertification control in Xizang shows a trend of gradual improvement,but the overall level is still not high and there is a lot of room for optimization.The coupling coordination degree of desertification control-social and economic system is in a steady fluctuation trend,rising from D value less than 0.55 in 2004 to 0.87 in 2018,in a state of coordinated development(good),and grey prediction analysis shows that D value is in a continuous rise.The coupling coordination degree of the six prefecture-level cities in Xizang and Ngari region is different in time and space,but the overall development trend is coordinated.The development index of desertification control and the socio-economic development index show the interaction of strong decoupling,strong negative decoupling and weak decoupling,and there are interaction effects of desertification control,economic development and social development at different scales.

Rapid Prototype Development Approach for Genetic Programming

Genetic Programming (GP) is an important approach to deal with complex problem analysis and modeling, and has been applied in a wide range of areas. The development of GP involves various aspects, including design of genetic operators, evolutionary controls and implementations of heuristic strategy, evaluations and other mechanisms. When designing genetic operators, it is necessary to consider the possible limitations of encoding methods of individuals. And when selecting evolutionary control strategies, it is also necessary to balance search efficiency and diversity based on representation characteristics as well as the problem itself. More importantly, all of these matters, among others, have to be implemented through tedious coding work. Therefore, GP development is both complex and time-consuming. To overcome some of these difficulties that hinder the enhancement of GP development efficiency, we explore the feasibility of mutual assistance among GP variants, and then propose a rapid GP prototyping development method based on πGrammatical Evolution (πGE). It is demonstrated through regression analysis experiments that not only is this method beneficial for the GP developers to get rid of some tedious implementations, but also enables them to concentrate on the essence of the referred problem, such as individual representation, decoding means and evaluation. Additionally, it provides new insights into the roles of individual delineations in phenotypes and semantic research of individuals.

An Approach to Detect Structural Development Defects in Object-Oriented Programs

Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.

Research on the Interactive Impact of Transportation Systems on Socio-Economic Development

This paper aims to explore the interactive impact between transportation systems and socio-economic development,employing Structural Equation Modeling(SEM)to analyze data from 31 provincial-level administrative regions in China from 2013 to 2022.It comprehensively considers key indicators from the economic,social,and transportation sectors.The paper constructs a model encompassing 5 latent variables and 15 observed variables.Through in-depth analysis,it reveals the promoting role of transportation systems on economic growth and social development,as well as the demand for transportation system construction and optimization driven by socio-economic development levels.The results indicate that an efficient transportation system can not only directly drive economic growth but also indirectly promote social development by improving social welfare and enhancing quality of life.This paper provides new insights into understanding the complex relationship between transportation systems and socio-economic development and holds significant implications for policymakers in optimizing transportation infrastructure to foster economic and social development.

Evaluation of Green Development Efficiency in Chongqing Municipality Based on Super-SBM and Malmquist Models

The green development of Chongqing municipality is crucial in establishing a major ecological shield in the upper reaches of the Yangtze River.By developing a Super-SBM model and using the Malmquist index to analyze and calculate the green development efficiency and its influencing factors in Chongqing from 2011 to 2021,this study reveals an accelerating trend in the overall green development efficiency in Chongqing.The significant enhancement of green development efficiency in Chongqing is primarily attributed to changes in returns to scale.Pure technical efficiency and technological advancements have a considerable potential impact on improving green development efficiency in Chongqing.Furthermore,there are discernible disparities in green development efficiency among districts and counties in Chongqing,with different factors influencing these variations.Chongqing is suggested to promote clean and efficient energy utilization,bolster the application and commercialization of scientific and technological advancements,consistently advance ecological restoration and management,and elevate the quality of green development to a higher level.

Optimized Allocation Model for Regional Agricultural Fertilizer Resources in Southern Xinjiang from the Perspective of Sustainable Development

[Objective] This study was to establish an optimized model for the allocation of agricultural fertilizer resources in Southern Xinjiang from the perspective of sustainable development.[Method] An optimized model for the allocation of agricultural fertilizer resources was established based on their allocation structure.Combined with the actual agricultural production in Aksu areas of Southern Xinjiang,by establishing a rational evaluation index system,under the premise of considering the planting area constraints,the total water resources constraints and the security constraints of food production,we established the empirical optimal allocation model of the regional agricultural fertilizer resources in Aksu area of Southern Xinjiang.Moreover,we solved the model by using the search algorithm of computer and lingo programming.[Result] The increased economic benefit was near to 1.8 billion Yuan by adopting the optimal allocation methods,with a relative increment of about 34.4%.[Conclusion] Our results provided theoretical basis for achieving the sustainable development of agricultural economy in Southern Xinjiang.

Discussion on the Current Situation and Development Model of Sightseeing Agriculture in Zhenjiang

Zhenjiang has distinct advantages to develop sightseeing agriculture as it possesses outstanding agricultural features, superior geographical locations and abundant cultural resources. At present, the situation of sightseeing agriculture in Zhenjiang is complicated. Though the development is going fast, it is quite blindfold for there is no reasonable overall plan; the production is at low level and requires more cultural connotation; the investment source is thin while the cooperation management hasn't been accomplished; a rudiment mode of varied sightseeing agriculture is forming rapidly. Based on this situation, five development modes are put forward for Zhenjiang's sightseeing agriculture, including: "enterprises as the main body of management" mode, "village committees as the main body of management" mode, "villagers as the main body of management" mode, government operating mode and joint development mode.

Low-carbon Agriculture Development Models in Southern Jiangsu Province

[Objective] To investigate the appropriate low-carbon agriculture model in Southern Jiangsu Province. [Method] Through the analysis of regional features in Southern Jiangsu and several matured low-carbon agriculture development models at present, the low-carbon agriculture development modes suitable for Southern Jiangsu were investigated, and corresponding supporting measures for the development of the models were put forward. [Result] Low-carbon agriculture is the environment- friendly agriculture which achieves low emissions, low pollution, high efficiency and high-yield through efficient recycling of energy and resources and continuous im- provements on ecological environment. With a variety of development models, the specific development model for practical use should be determined according to the local conditions, and supported by corresponding supporting measures, to achieve the rapid development of low-carbon agriculture. [Conclusion] This study laid the foundation for the development of low-carbon agriculture model in Southern Jiangsu.

The Training Model and Development Route of Market-oriented Professional Farmers

To cultivate new professional farmers is a key way for rural labor development, resolving existing problems such as how to farming. It is notable that government and market take advantages in training of new professional farmers. Therefore, it is necessary to guarantee government and market playing the roles. The research explored market-oriented farmer training model and the characteristics and investigated training routes for new professional farmers.

Shale gas production evaluation framework based on data-driven models

Increasing the production and utilization of shale gas is of great significance for building a clean and low-carbon energy system.Sharp decline of gas production has been widely observed in shale gas reservoirs.How to forecast shale gas production is still challenging due to complex fracture networks,dynamic fracture properties,frac hits,complicated multiphase flow,and multi-scale flow as well as data quality and uncertainty.This work develops an integrated framework for evaluating shale gas well production based on data-driven models.Firstly,a comprehensive dominated-factor system has been established,including geological,drilling,fracturing,and production factors.Data processing and visualization are required to ensure data quality and determine final data set.A shale gas production evaluation model is developed to evaluate shale gas production levels.Finally,the random forest algorithm is used to forecast shale gas production.The prediction accuracy of shale gas production level is higher than 95%based on the shale gas reservoirs in China.Forty-one wells are randomly selected to predict cumulative gas production using the optimal regression model.The proposed shale gas production evaluation frame-work overcomes too many assumptions of analytical or semi-analytical models and avoids huge computation cost and poor generalization for numerical modelling.

Data-driven intelligent modeling framework for the steam cracking process

Steam cracking is the dominant technology for producing light olefins,which are believed to be the foundation of the chemical industry.Predictive models of the cracking process can boost production efficiency and profit margin.Rapid advancements in machine learning research have recently enabled data-driven solutions to usher in a new era of process modeling.Meanwhile,its practical application to steam cracking is still hindered by the trade-off between prediction accuracy and computational speed.This research presents a framework for data-driven intelligent modeling of the steam cracking process.Industrial data preparation and feature engineering techniques provide computational-ready datasets for the framework,and feedstock similarities are exploited using k-means clustering.We propose LArge-Residuals-Deletion Multivariate Adaptive Regression Spline(LARD-MARS),a modeling approach that explicitly generates output formulas and eliminates potentially outlying instances.The framework is validated further by the presentation of clustering results,the explanation of variable importance,and the testing and comparison of model performance.

Prediction models of hepatocellular carcinoma development in chronic hepatitis B patients

Chronic hepatitis B virus(HBV) infection is a major cause of cirrhosis and hepatocellular carcinoma(HCC). Applying the same strategies for antiviral therapy and HCC surveillance to all chronic hepatitis B(CHB) patients would be a burden worldwide. To properly manage CHB patients, it is necessary to identify and classify the risk for HCC development in such patients. Several HCC risk scores based on risk factors such as cirrhosis, age, male gender, and high viral load have been used, and have negative predictive values of ≥ 95%. Most of these have been derived from, and internally validated in, treatment-na?ve Asian CHB patients. Herein, we summarized various HCC prediction models, including IPM(Individual Prediction Model), CU-HCC(Chinese University-HCC), GAG-HCC(Guide with Age, Gender, HBV DNA, Core Promoter Mutations and Cirrhosis-HCC), NGM-HCC(NomogramHCC), REACH-B(Risk Estimation for Hepatocellular Carcinoma in Chronic Hepatitis B), and Page-B score. To develop a noninvasive test of liver fibrosis, we also introduced a new scoring system that uses liver stiffness values from transient elastography, including an LSM(Liver Stiffness Measurement)-based model, LSM-HCC, and mR EACH-B(modified REACH-B).