Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely h...Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate data.In addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation process.Consequently,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns.This study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these challenges.The proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry experts.This article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost estimation.Evaluating the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing state-of-the-artmodels.The findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.展开更多
Recent studies on tropical cyclone(TC)intensity change indicate that the development of a vertically aligned TC circulation is a key feature of its rapid intensification(RI),however,understanding how vortex alignment ...Recent studies on tropical cyclone(TC)intensity change indicate that the development of a vertically aligned TC circulation is a key feature of its rapid intensification(RI),however,understanding how vortex alignment occurs remains a challenging topic in TC intensity change research.Based on the simulation outputs of North Atlantic Hurricane Wilma(2005)and western North Pacific Typhoon Rammasun(2014),vortex track oscillations at different vertical levels and their associated role in vortex alignment are examined to improve our understanding of the vortex alignment during RI of TCs with initial hurricane intensity.It is found that vortex tracks at different vertical levels oscillate consistently in speed and direction during the RI of the two simulated TCs.While the consistent track oscillation reduces the oscillation tilt during RI,the reduction of vortex tilt results mainly from the mean track before RI.It is also found that the vortex tilt is primarily due to the mean vortex track before and after RI.The track oscillations are closely associated with wavenumber-1 vortex Rossby waves that are dominant wavenumber-1 circulations in the TC inner-core region.This study suggests that the dynamics of the wavenumber-1 vortex Rossby waves play an important role in the regulation of the physical processes associated with the track oscillation and vertical alignment of TCs.展开更多
When data privacy is imposed as a necessity,Federated learning(FL)emerges as a relevant artificial intelligence field for developing machine learning(ML)models in a distributed and decentralized environment.FL allows ...When data privacy is imposed as a necessity,Federated learning(FL)emerges as a relevant artificial intelligence field for developing machine learning(ML)models in a distributed and decentralized environment.FL allows ML models to be trained on local devices without any need for centralized data transfer,thereby reducing both the exposure of sensitive data and the possibility of data interception by malicious third parties.This paradigm has gained momentum in the last few years,spurred by the plethora of real-world applications that have leveraged its ability to improve the efficiency of distributed learning and to accommodate numerous participants with their data sources.By virtue of FL,models can be learned from all such distributed data sources while preserving data privacy.The aim of this paper is to provide a practical tutorial on FL,including a short methodology and a systematic analysis of existing software frameworks.Furthermore,our tutorial provides exemplary cases of study from three complementary perspectives:i)Foundations of FL,describing the main components of FL,from key elements to FL categories;ii)Implementation guidelines and exemplary cases of study,by systematically examining the functionalities provided by existing software frameworks for FL deployment,devising a methodology to design a FL scenario,and providing exemplary cases of study with source code for different ML approaches;and iii)Trends,shortly reviewing a non-exhaustive list of research directions that are under active investigation in the current FL landscape.The ultimate purpose of this work is to establish itself as a referential work for researchers,developers,and data scientists willing to explore the capabilities of FL in practical applications.展开更多
The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and labor.In previous software defect predicti...The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and labor.In previous software defect prediction studies,transfer learning was effective in solving the problem of inconsistent project data distribution.However,target projects often lack sufficient data,which affects the performance of the transfer learning model.In addition,the presence of uncorrelated features between projects can decrease the prediction accuracy of the transfer learning model.To address these problems,this article propose a software defect prediction method based on stable learning(SDP-SL)that combines code visualization techniques and residual networks.This method first transforms code files into code images using code visualization techniques and then constructs a defect prediction model based on these code images.During the model training process,target project data are not required as prior knowledge.Following the principles of stable learning,this paper dynamically adjusted the weights of source project samples to eliminate dependencies between features,thereby capturing the“invariance mechanism”within the data.This approach explores the genuine relationship between code defect features and labels,thereby enhancing defect prediction performance.To evaluate the performance of SDP-SL,this article conducted comparative experiments on 10 open-source projects in the PROMISE dataset.The experimental results demonstrated that in terms of the F-measure,the proposed SDP-SL method outperformed other within-project defect prediction methods by 2.11%-44.03%.In cross-project defect prediction,the SDP-SL method provided an improvement of 5.89%-25.46% in prediction performance compared to other cross-project defect prediction methods.Therefore,SDP-SL can effectively enhance within-and cross-project defect predictions.展开更多
Objective: To investigate the nursing effects of rapid recovery care measures on lung cancer surgery patients. Methods: 42 cases of lung cancer surgery patients were divided into control group and study group, with 21...Objective: To investigate the nursing effects of rapid recovery care measures on lung cancer surgery patients. Methods: 42 cases of lung cancer surgery patients were divided into control group and study group, with 21 cases in each group. The sleep quality and postoperative recovery indicators were compared between the two groups. Results: The study group showed better results than the control group in terms of PSQI scores, venting time, extubation time, time to getting out of bed, and duration of antibiotic use, with P Conclusion: Rapid recovery nursing has a positive impact on improving sleep quality and promoting postoperative recovery in lung cancer surgery patients.展开更多
The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software toenhance production efficiency. In this rapidly evolving market, software development is an ongoing process thatmu...The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software toenhance production efficiency. In this rapidly evolving market, software development is an ongoing process thatmust be tailored to meet the dynamic needs of enterprises. However, internal research and development can beprohibitively expensive, driving many enterprises to outsource software development and upgrades to externalservice providers. This paper presents a software upgrade outsourcing model for enterprises and service providersthat accounts for the impact of market fluctuations on software adaptability. To mitigate the risk of adverseselection due to asymmetric information about the service provider’s cost and asymmetric information aboutthe enterprise’s revenues, we propose pay-per-time and revenue-sharing contracts in two distinct informationasymmetry scenarios. These two contracts specify the time and transfer payments for software upgrades. Througha comparative analysis of the optimal solutions under the two contracts and centralized decision-making withfull-information, we examine the characteristics of the solutions under two information asymmetry scenarios andanalyze the incentive effects of the two contracts on the various stakeholders. Overall, our study offers valuableinsights for firms seeking to optimize their outsourcing strategies and maximize their returns on investment insoftware upgrades.展开更多
The 2D sandwich model serves as a potent tool in exploring the influence of surface geometry on the combustion attributes of Ammonium perchlorate/Hydroxyl-terminated polybutadiene(AP/HTPB)propellant under rapid pressu...The 2D sandwich model serves as a potent tool in exploring the influence of surface geometry on the combustion attributes of Ammonium perchlorate/Hydroxyl-terminated polybutadiene(AP/HTPB)propellant under rapid pressure decay.The thickness of the sandwich propellant is derived from slicing the 3D random particle packing,an approach that enables a more effective examination of the micro-flame structure.Comparative analysis of the predicted burning characteristics has been performed with experimental studies.The findings demonstrate a reasonable agreement,thereby validating the precision and soundness of the model.Based on the typical rapid depressurization environment of solid rocket motor(initial combustion pressure is 3 MPa and the maximum depressurization rate is 1000 MPa/s).A-type(a flatter surface),B-type(AP recesses from the combustion surface),and C-type(AP protrudes from the combustion surface)propellant combustion processes are numerically simulated.Upon comparison of the evolution of gas-phase flame between 0.1 and 1 ms,it is discerned that the flame strength and form created by the three sandwich models differ significantly at the beginning stage of depressurization,with the flame structures gradually becoming harmonized over time.Conclusions are drawn by comparison extinction times:the surface geometry plays a pivotal role in the combustion process,with AP protrusion favoring combustion the most.展开更多
Objective: To explore the application value of rapid rehabilitation concept in patients with extrahepatic bile duct stones under laparoscopy during perioperative period. Methods: 90 patients with extrahepatic bile duc...Objective: To explore the application value of rapid rehabilitation concept in patients with extrahepatic bile duct stones under laparoscopy during perioperative period. Methods: 90 patients with extrahepatic bile duct stones treated in our hospital from January 2022 to February 2023 were selected as the research object and randomly divided into the study group and the control group. The control group was given routine care, and the observation group was given rapid surgical rehabilitation care. The postoperative anal exhaust time, first meal time, early activity time, pain time, abdominal drainage tube removal time, hospitalization time and complication rate were compared between the two groups. The independent sample T test was used for the measurement data, and the x<sup>2</sup> test was used for the counting data, and the difference was statistically significant (P Results: The postoperative anal exhaust time, first meal time, early activity time, pain time, abdominal drainage tube removal time and hospitalization time in the study group were shorter than those in the control group (all P Conclusion: The concept of rapid rehabilitation can significantly improve the perioperative nursing effect of patients with extrahepatic bile duct stones and accelerate their rehabilitation, which is worth improving and popularizing.展开更多
Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements.Researchers are exploring machine learn...Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements.Researchers are exploring machine learning to predict software bugs,but a more precise and general approach is needed.Accurate bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning methods.However,these studies are not generalized and efficient when extended to other datasets.Therefore,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification problems.The methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a model.Four National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were combined.It reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.展开更多
Background and Objective: HIV, hepatitis B virus (HBV) and hepatitis C virus (HCV) are very widespread in the world, however, less than 20% of the people affected are diagnosed and treated. This study aimed to determi...Background and Objective: HIV, hepatitis B virus (HBV) and hepatitis C virus (HCV) are very widespread in the world, however, less than 20% of the people affected are diagnosed and treated. This study aimed to determine the prevalence of HIV, HCV and HBV co-infections in pregnant women at Bangui Community University Hospital and the cost of screening. Methods: A cross-sectional study involving consenting pregnant women who came for antenatal care was performed. HIV, HCV antibodies and HBV antigens were detected using Exacto Triplex<sup>?</sup> HIV/HCV/HBsAg rapid test, cross-validated by ELISA tests. Sociodemographic and professional data, the modes of transmission and prevention of HIV and both hepatitis viruses were collected in a standard sheet and analyzed using the Epi-Info software version 7. Results: Pregnant women aged 15 to 24 were the most affected (45.3%);high school girls (46.0%), and pregnant women living in cohabitation (65.3%) were the most represented. Twenty-five (16.7%) worked in the formal sector, 12.7% were unemployed housewives and the remainder in the informal sector. The prevalence of HIV, HBV, and HCV viruses was 11.8%, 21.9% and 22.2%, respectively. The prevalence of co-infections was 8.6% for HIV-HBV, 10.2% for HIV-HCV, 14.7% for HBV-HCV and 6.5% for HIV-HBV-HCV. All positive results and 10% of negative results by the rapid test were confirmed by ELISA tests. The serology of the three viruses costs 39,000 FCFA (60 Euros) by ELISA compared to 10,000 FCFA (15.00 Euros) with Exacto Triplex<sup>?</sup> HIV/HCV/AgHBs (BioSynex, Strasbourg, France). Conclusion: The low level of education and awareness of hepatitis are barriers to development and indicate the importance of improving the literacy rate of women in the Central African Republic (CAR). Likewise, the high prevalence of the three viruses shows the need for the urgent establishment of a national program to combat viral hepatitis in the CAR.展开更多
Aim: This study evaluates the impact of Enhanced Recovery After Surgery (ERAS) nursing on postoperative complications and quality of life in patients undergoing robot-assisted minimally invasive esophagectomy (RAMIE)....Aim: This study evaluates the impact of Enhanced Recovery After Surgery (ERAS) nursing on postoperative complications and quality of life in patients undergoing robot-assisted minimally invasive esophagectomy (RAMIE). Methods: A total of 150 patients who underwent RAMIE from January 2020 to January 2022 at our hospital were randomly assigned to either the observation group or the control group, with 75 patients in each. The control group received standard perioperative management and nursing care, while the observation group was treated with ERAS nursing strategies. Interventions continued until discharge, and outcomes such as postoperative complications, quality of life, and nutritional status were compared between the groups. Results: The observation group exhibited a significantly lower incidence of postoperative adverse reactions compared to the control group (P ionally, all dimension scores of the Short-Form 36 Health Survey (SF-36), including the total score, were higher in the observation group (P < 0.05). Furthermore, the Nutritional Risk Screening (NRS) scores for impaired nutritional status and disease severity, along with the total NRS score, were significantly lower in the observation group compared to the control group (P Conclusion: Implementing ERAS nursing in the perioperative care of patients undergoing RAMIE is associated with reduced postoperative complications and enhanced postoperative quality of life and nutritional status. .展开更多
In this study,the impact of different reaction times on the preparation of powdered activated carbon(PAC)using a one-step rapid activation method under flue gas atmosphere is investigated,and the underlying reaction m...In this study,the impact of different reaction times on the preparation of powdered activated carbon(PAC)using a one-step rapid activation method under flue gas atmosphere is investigated,and the underlying reaction mechanism is summarized.Results indicate that the reaction process of this method can be divided into three stages:stage I is the rapid release of volatiles and the rapid consumption of O_(2),primarily occurring within a reaction time range of 0-0.5 s;stage II is mainly the continuous release and diffusion of volatiles,which is the carbonization and activation coupling reaction stage,and the carbonization process is the main in this stage.This stage mainly occurs at the reaction time range of 0.5 -2.0 s when SL-coal is used as material,and that is 0.5-3.0 s when JJ-coal is used as material;stage III is mainly the activation stage,during which activated components diffuse to both the surface and interior of particles.This stage mainly involves the reaction stage of CO_(2)and H2O(g)activation,and it mainly occurs at the reaction time range of 2.0-4.0 s when SL-coal is used as material,and that is 3.0-4.0 s when JJ-coal is used as material.Besides,the main function of the first two stages is to provide more diffusion channels and contact surfaces/activation sites for the diffusion and activation of the activated components in the third stage.Mastering the reaction mechanism would serve as a crucial reference and foundation for designing the structure,size of the reactor,and optimal positioning of the activator nozzle in PAC preparation.展开更多
The use of interactive audience software,such as audience response systems(ARS),in medical education has become increasingly popular in recent years.This technology allows instructors to engage students in real time,e...The use of interactive audience software,such as audience response systems(ARS),in medical education has become increasingly popular in recent years.This technology allows instructors to engage students in real time,encouraging active participation and promoting effective learning.The benefits of interactive audience software in medical education include increased student engagement,promotion of active learning,and enhanced learning outcomes.However,there are also several challenges to its implementation,including technical difficulties,careful planning and preparation,over-reliance on technology,and ethical concerns related to privacy and data security.The cost of implementing interactive audience software may also be a barrier for some institutions.This paper specifically reviews six interactive software platforms,including Socrative,Quizizz,Pear Deck,Slido,Wooclap and ClassPoint.These platforms allow for real-time assessment of student understanding,feedback,and participation.They also enable instructors to adjust their teaching strategies based on student responses and feedback.Overall,interactive audience software has shown great potential to enhance learning and engagement in medical education.It is important for instructors to carefully consider the benefits and challenges of its implementation.While the cost of implementing interactive audience software may be a barrier for some institutions,there are free and low-cost options available.展开更多
The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are ...The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are widely used in healthcare systems,as they ensure effective resource utilization,safety,great network management,and monitoring.In this sector,due to the value of thedata,SDNs faceamajor challengeposed byawide range of attacks,such as distributed denial of service(DDoS)and probe attacks.These attacks reduce network performance,causing the degradation of different key performance indicators(KPIs)or,in the worst cases,a network failure which can threaten human lives.This can be significant,especially with the current expansion of portable healthcare that supports mobile and wireless devices for what is called mobile health,or m-health.In this study,we examine the effectiveness of using SDNs for defense against DDoS,as well as their effects on different network KPIs under various scenarios.We propose a threshold-based DDoS classifier(TBDC)technique to classify DDoS attacks in healthcare SDNs,aiming to block traffic considered a hazard in the form of a DDoS attack.We then evaluate the accuracy and performance of the proposed TBDC approach.Our technique shows outstanding performance,increasing the mean throughput by 190.3%,reducing the mean delay by 95%,and reducing packet loss by 99.7%relative to normal,with DDoS attack traffic.展开更多
The developed auxiliary software serves to simplify, standardize and facilitate the software loading of the structural organization of a complex technological system, as well as its further manipulation within the pro...The developed auxiliary software serves to simplify, standardize and facilitate the software loading of the structural organization of a complex technological system, as well as its further manipulation within the process of solving the considered technological system. Its help can be especially useful in the case of a complex structural organization of a technological system with a large number of different functional elements grouped into several technological subsystems. This paper presents the results of its application for a special complex technological system related to the reference steam block for the combined production of heat and electricity.展开更多
Under the influence of anthropogenic and climate change,the problems caused by urban heat island(UHI)has become increasingly prominent.In order to promote urban sustainable development and improve the quality of human...Under the influence of anthropogenic and climate change,the problems caused by urban heat island(UHI)has become increasingly prominent.In order to promote urban sustainable development and improve the quality of human settlements,it is significant for exploring the evolution characteristics of urban thermal environment and analyzing its driving forces.Taking the Landsat series images as the basic data sources,the winter land surface temperature(LST)of the rapid urbanization area of Fuzhou City in China was quantitatively retrieved from 2001 to 2021.Combing comprehensively the standard deviation ellipse model,profile analysis and GeoDetector model,the spatio-temporal evolution characteristics and influencing factors of the winter urban thermal environment were systematically analyzed.The results showed that the winter LST presented an increasing trend in the study area during 2001–2021,and the winter LST of the central urban regions was significantly higher than the suburbs.There was a strong UHI effect from 2001 to 2021with an expansion trend from the central urban regions to the suburbs and coastal areas in space scale.The LST of green lands and wetlands are significantly lower than croplands,artificial surface and unvegetated lands.Vegetation and water bodies had a significant mitigation effect on UHI,especially in the micro-scale.The winter UHI had been jointly driven by the underlying surface and socio-economic factors in a nonlinear or two-factor interactive enhancement mode,and socio-economic factors had played a leading role.This research could provide data support and decision-making references for rationally planning urban layout and promoting sustainable urban development.展开更多
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 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.展开更多
The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software w...The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.展开更多
Rapid bridge inspection and evaluation mainly uses information technology to test the quality of bridge infrastructure and structures,integrates the test results with the existing management system,completes the bridg...Rapid bridge inspection and evaluation mainly uses information technology to test the quality of bridge infrastructure and structures,integrates the test results with the existing management system,completes the bridge status assessment,establishes information management files to provide bridge disease problem inspection and analysis,and provides support for the application of disposal measures.This paper briefly discusses the necessity of applying rapid inspection and evaluation technology and analyzes the bridge’s rapid inspection and evaluation content,inspection system,and application process.We look forward to the future application prospects of this technology and supporting those in this field.展开更多
With the rapid development of information technology,the demand for talents in the field of software engineering is growing.In order to cultivate high-quality software engineering talents who meet the market demand,un...With the rapid development of information technology,the demand for talents in the field of software engineering is growing.In order to cultivate high-quality software engineering talents who meet the market demand,universities have continuously carried out the construction of software engineering majors.Accreditation Board for Engineering and Technology(ABET)certification,as an internationally recognized higher education quality assurance system,provides important reference and guidance for the construction of software engineering majors.Guided by student learning outcomes and core competencies,combined with the characteristics of software engineering talent cultivation,the innovation of talent cultivation mode takes industry-education integration and school-enterprise cooperation as the main development paths and explores comprehensive reform of the major in terms of professional positioning and goals,curriculum system,teaching conditions,and teachers.This comprehensive reform model has effectively promoted the development of major construction and improved the quality of talent cultivation.展开更多
文摘Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate data.In addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation process.Consequently,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns.This study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these challenges.The proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry experts.This article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost estimation.Evaluating the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing state-of-the-artmodels.The findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.
基金National Natural Science Foundation of China(Grant Nos:42150710531,42192551,61827901)supported this study.
文摘Recent studies on tropical cyclone(TC)intensity change indicate that the development of a vertically aligned TC circulation is a key feature of its rapid intensification(RI),however,understanding how vortex alignment occurs remains a challenging topic in TC intensity change research.Based on the simulation outputs of North Atlantic Hurricane Wilma(2005)and western North Pacific Typhoon Rammasun(2014),vortex track oscillations at different vertical levels and their associated role in vortex alignment are examined to improve our understanding of the vortex alignment during RI of TCs with initial hurricane intensity.It is found that vortex tracks at different vertical levels oscillate consistently in speed and direction during the RI of the two simulated TCs.While the consistent track oscillation reduces the oscillation tilt during RI,the reduction of vortex tilt results mainly from the mean track before RI.It is also found that the vortex tilt is primarily due to the mean vortex track before and after RI.The track oscillations are closely associated with wavenumber-1 vortex Rossby waves that are dominant wavenumber-1 circulations in the TC inner-core region.This study suggests that the dynamics of the wavenumber-1 vortex Rossby waves play an important role in the regulation of the physical processes associated with the track oscillation and vertical alignment of TCs.
基金the R&D&I,Spain grants PID2020-119478GB-I00 and,PID2020-115832GB-I00 funded by MCIN/AEI/10.13039/501100011033.N.Rodríguez-Barroso was supported by the grant FPU18/04475 funded by MCIN/AEI/10.13039/501100011033 and by“ESF Investing in your future”Spain.J.Moyano was supported by a postdoctoral Juan de la Cierva Formación grant FJC2020-043823-I funded by MCIN/AEI/10.13039/501100011033 and by European Union NextGenerationEU/PRTR.J.Del Ser acknowledges funding support from the Spanish Centro para el Desarrollo Tecnológico Industrial(CDTI)through the AI4ES projectthe Department of Education of the Basque Government(consolidated research group MATHMODE,IT1456-22)。
文摘When data privacy is imposed as a necessity,Federated learning(FL)emerges as a relevant artificial intelligence field for developing machine learning(ML)models in a distributed and decentralized environment.FL allows ML models to be trained on local devices without any need for centralized data transfer,thereby reducing both the exposure of sensitive data and the possibility of data interception by malicious third parties.This paradigm has gained momentum in the last few years,spurred by the plethora of real-world applications that have leveraged its ability to improve the efficiency of distributed learning and to accommodate numerous participants with their data sources.By virtue of FL,models can be learned from all such distributed data sources while preserving data privacy.The aim of this paper is to provide a practical tutorial on FL,including a short methodology and a systematic analysis of existing software frameworks.Furthermore,our tutorial provides exemplary cases of study from three complementary perspectives:i)Foundations of FL,describing the main components of FL,from key elements to FL categories;ii)Implementation guidelines and exemplary cases of study,by systematically examining the functionalities provided by existing software frameworks for FL deployment,devising a methodology to design a FL scenario,and providing exemplary cases of study with source code for different ML approaches;and iii)Trends,shortly reviewing a non-exhaustive list of research directions that are under active investigation in the current FL landscape.The ultimate purpose of this work is to establish itself as a referential work for researchers,developers,and data scientists willing to explore the capabilities of FL in practical applications.
基金supported by the NationalNatural Science Foundation of China(Grant No.61867004)the Youth Fund of the National Natural Science Foundation of China(Grant No.41801288).
文摘The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and labor.In previous software defect prediction studies,transfer learning was effective in solving the problem of inconsistent project data distribution.However,target projects often lack sufficient data,which affects the performance of the transfer learning model.In addition,the presence of uncorrelated features between projects can decrease the prediction accuracy of the transfer learning model.To address these problems,this article propose a software defect prediction method based on stable learning(SDP-SL)that combines code visualization techniques and residual networks.This method first transforms code files into code images using code visualization techniques and then constructs a defect prediction model based on these code images.During the model training process,target project data are not required as prior knowledge.Following the principles of stable learning,this paper dynamically adjusted the weights of source project samples to eliminate dependencies between features,thereby capturing the“invariance mechanism”within the data.This approach explores the genuine relationship between code defect features and labels,thereby enhancing defect prediction performance.To evaluate the performance of SDP-SL,this article conducted comparative experiments on 10 open-source projects in the PROMISE dataset.The experimental results demonstrated that in terms of the F-measure,the proposed SDP-SL method outperformed other within-project defect prediction methods by 2.11%-44.03%.In cross-project defect prediction,the SDP-SL method provided an improvement of 5.89%-25.46% in prediction performance compared to other cross-project defect prediction methods.Therefore,SDP-SL can effectively enhance within-and cross-project defect predictions.
文摘Objective: To investigate the nursing effects of rapid recovery care measures on lung cancer surgery patients. Methods: 42 cases of lung cancer surgery patients were divided into control group and study group, with 21 cases in each group. The sleep quality and postoperative recovery indicators were compared between the two groups. Results: The study group showed better results than the control group in terms of PSQI scores, venting time, extubation time, time to getting out of bed, and duration of antibiotic use, with P Conclusion: Rapid recovery nursing has a positive impact on improving sleep quality and promoting postoperative recovery in lung cancer surgery patients.
文摘The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software toenhance production efficiency. In this rapidly evolving market, software development is an ongoing process thatmust be tailored to meet the dynamic needs of enterprises. However, internal research and development can beprohibitively expensive, driving many enterprises to outsource software development and upgrades to externalservice providers. This paper presents a software upgrade outsourcing model for enterprises and service providersthat accounts for the impact of market fluctuations on software adaptability. To mitigate the risk of adverseselection due to asymmetric information about the service provider’s cost and asymmetric information aboutthe enterprise’s revenues, we propose pay-per-time and revenue-sharing contracts in two distinct informationasymmetry scenarios. These two contracts specify the time and transfer payments for software upgrades. Througha comparative analysis of the optimal solutions under the two contracts and centralized decision-making withfull-information, we examine the characteristics of the solutions under two information asymmetry scenarios andanalyze the incentive effects of the two contracts on the various stakeholders. Overall, our study offers valuableinsights for firms seeking to optimize their outsourcing strategies and maximize their returns on investment insoftware upgrades.
基金supported by the National Natural Science Foundation of China(Grant No.51176076)。
文摘The 2D sandwich model serves as a potent tool in exploring the influence of surface geometry on the combustion attributes of Ammonium perchlorate/Hydroxyl-terminated polybutadiene(AP/HTPB)propellant under rapid pressure decay.The thickness of the sandwich propellant is derived from slicing the 3D random particle packing,an approach that enables a more effective examination of the micro-flame structure.Comparative analysis of the predicted burning characteristics has been performed with experimental studies.The findings demonstrate a reasonable agreement,thereby validating the precision and soundness of the model.Based on the typical rapid depressurization environment of solid rocket motor(initial combustion pressure is 3 MPa and the maximum depressurization rate is 1000 MPa/s).A-type(a flatter surface),B-type(AP recesses from the combustion surface),and C-type(AP protrudes from the combustion surface)propellant combustion processes are numerically simulated.Upon comparison of the evolution of gas-phase flame between 0.1 and 1 ms,it is discerned that the flame strength and form created by the three sandwich models differ significantly at the beginning stage of depressurization,with the flame structures gradually becoming harmonized over time.Conclusions are drawn by comparison extinction times:the surface geometry plays a pivotal role in the combustion process,with AP protrusion favoring combustion the most.
文摘Objective: To explore the application value of rapid rehabilitation concept in patients with extrahepatic bile duct stones under laparoscopy during perioperative period. Methods: 90 patients with extrahepatic bile duct stones treated in our hospital from January 2022 to February 2023 were selected as the research object and randomly divided into the study group and the control group. The control group was given routine care, and the observation group was given rapid surgical rehabilitation care. The postoperative anal exhaust time, first meal time, early activity time, pain time, abdominal drainage tube removal time, hospitalization time and complication rate were compared between the two groups. The independent sample T test was used for the measurement data, and the x<sup>2</sup> test was used for the counting data, and the difference was statistically significant (P Results: The postoperative anal exhaust time, first meal time, early activity time, pain time, abdominal drainage tube removal time and hospitalization time in the study group were shorter than those in the control group (all P Conclusion: The concept of rapid rehabilitation can significantly improve the perioperative nursing effect of patients with extrahepatic bile duct stones and accelerate their rehabilitation, which is worth improving and popularizing.
基金This Research is funded by Researchers Supporting Project Number(RSPD2024R947),King Saud University,Riyadh,Saudi Arabia.
文摘Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements.Researchers are exploring machine learning to predict software bugs,but a more precise and general approach is needed.Accurate bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning methods.However,these studies are not generalized and efficient when extended to other datasets.Therefore,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification problems.The methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a model.Four National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were combined.It reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.
文摘Background and Objective: HIV, hepatitis B virus (HBV) and hepatitis C virus (HCV) are very widespread in the world, however, less than 20% of the people affected are diagnosed and treated. This study aimed to determine the prevalence of HIV, HCV and HBV co-infections in pregnant women at Bangui Community University Hospital and the cost of screening. Methods: A cross-sectional study involving consenting pregnant women who came for antenatal care was performed. HIV, HCV antibodies and HBV antigens were detected using Exacto Triplex<sup>?</sup> HIV/HCV/HBsAg rapid test, cross-validated by ELISA tests. Sociodemographic and professional data, the modes of transmission and prevention of HIV and both hepatitis viruses were collected in a standard sheet and analyzed using the Epi-Info software version 7. Results: Pregnant women aged 15 to 24 were the most affected (45.3%);high school girls (46.0%), and pregnant women living in cohabitation (65.3%) were the most represented. Twenty-five (16.7%) worked in the formal sector, 12.7% were unemployed housewives and the remainder in the informal sector. The prevalence of HIV, HBV, and HCV viruses was 11.8%, 21.9% and 22.2%, respectively. The prevalence of co-infections was 8.6% for HIV-HBV, 10.2% for HIV-HCV, 14.7% for HBV-HCV and 6.5% for HIV-HBV-HCV. All positive results and 10% of negative results by the rapid test were confirmed by ELISA tests. The serology of the three viruses costs 39,000 FCFA (60 Euros) by ELISA compared to 10,000 FCFA (15.00 Euros) with Exacto Triplex<sup>?</sup> HIV/HCV/AgHBs (BioSynex, Strasbourg, France). Conclusion: The low level of education and awareness of hepatitis are barriers to development and indicate the importance of improving the literacy rate of women in the Central African Republic (CAR). Likewise, the high prevalence of the three viruses shows the need for the urgent establishment of a national program to combat viral hepatitis in the CAR.
文摘Aim: This study evaluates the impact of Enhanced Recovery After Surgery (ERAS) nursing on postoperative complications and quality of life in patients undergoing robot-assisted minimally invasive esophagectomy (RAMIE). Methods: A total of 150 patients who underwent RAMIE from January 2020 to January 2022 at our hospital were randomly assigned to either the observation group or the control group, with 75 patients in each. The control group received standard perioperative management and nursing care, while the observation group was treated with ERAS nursing strategies. Interventions continued until discharge, and outcomes such as postoperative complications, quality of life, and nutritional status were compared between the groups. Results: The observation group exhibited a significantly lower incidence of postoperative adverse reactions compared to the control group (P ionally, all dimension scores of the Short-Form 36 Health Survey (SF-36), including the total score, were higher in the observation group (P < 0.05). Furthermore, the Nutritional Risk Screening (NRS) scores for impaired nutritional status and disease severity, along with the total NRS score, were significantly lower in the observation group compared to the control group (P Conclusion: Implementing ERAS nursing in the perioperative care of patients undergoing RAMIE is associated with reduced postoperative complications and enhanced postoperative quality of life and nutritional status. .
基金supported by the Qingdao Postdoctoral Program Funding(QDBSH20220202045)Shandong provincial Natural Science Foundation(ZR2021ME049,ZR2022ME176)+1 种基金National Natural Science Foundation of China(22078176)Taishan Industrial Experts Program(TSCX202306135).
文摘In this study,the impact of different reaction times on the preparation of powdered activated carbon(PAC)using a one-step rapid activation method under flue gas atmosphere is investigated,and the underlying reaction mechanism is summarized.Results indicate that the reaction process of this method can be divided into three stages:stage I is the rapid release of volatiles and the rapid consumption of O_(2),primarily occurring within a reaction time range of 0-0.5 s;stage II is mainly the continuous release and diffusion of volatiles,which is the carbonization and activation coupling reaction stage,and the carbonization process is the main in this stage.This stage mainly occurs at the reaction time range of 0.5 -2.0 s when SL-coal is used as material,and that is 0.5-3.0 s when JJ-coal is used as material;stage III is mainly the activation stage,during which activated components diffuse to both the surface and interior of particles.This stage mainly involves the reaction stage of CO_(2)and H2O(g)activation,and it mainly occurs at the reaction time range of 2.0-4.0 s when SL-coal is used as material,and that is 3.0-4.0 s when JJ-coal is used as material.Besides,the main function of the first two stages is to provide more diffusion channels and contact surfaces/activation sites for the diffusion and activation of the activated components in the third stage.Mastering the reaction mechanism would serve as a crucial reference and foundation for designing the structure,size of the reactor,and optimal positioning of the activator nozzle in PAC preparation.
文摘The use of interactive audience software,such as audience response systems(ARS),in medical education has become increasingly popular in recent years.This technology allows instructors to engage students in real time,encouraging active participation and promoting effective learning.The benefits of interactive audience software in medical education include increased student engagement,promotion of active learning,and enhanced learning outcomes.However,there are also several challenges to its implementation,including technical difficulties,careful planning and preparation,over-reliance on technology,and ethical concerns related to privacy and data security.The cost of implementing interactive audience software may also be a barrier for some institutions.This paper specifically reviews six interactive software platforms,including Socrative,Quizizz,Pear Deck,Slido,Wooclap and ClassPoint.These platforms allow for real-time assessment of student understanding,feedback,and participation.They also enable instructors to adjust their teaching strategies based on student responses and feedback.Overall,interactive audience software has shown great potential to enhance learning and engagement in medical education.It is important for instructors to carefully consider the benefits and challenges of its implementation.While the cost of implementing interactive audience software may be a barrier for some institutions,there are free and low-cost options available.
基金extend their appreciation to Researcher Supporting Project Number(RSPD2023R582)King Saud University,Riyadh,Saudi Arabia.
文摘The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are widely used in healthcare systems,as they ensure effective resource utilization,safety,great network management,and monitoring.In this sector,due to the value of thedata,SDNs faceamajor challengeposed byawide range of attacks,such as distributed denial of service(DDoS)and probe attacks.These attacks reduce network performance,causing the degradation of different key performance indicators(KPIs)or,in the worst cases,a network failure which can threaten human lives.This can be significant,especially with the current expansion of portable healthcare that supports mobile and wireless devices for what is called mobile health,or m-health.In this study,we examine the effectiveness of using SDNs for defense against DDoS,as well as their effects on different network KPIs under various scenarios.We propose a threshold-based DDoS classifier(TBDC)technique to classify DDoS attacks in healthcare SDNs,aiming to block traffic considered a hazard in the form of a DDoS attack.We then evaluate the accuracy and performance of the proposed TBDC approach.Our technique shows outstanding performance,increasing the mean throughput by 190.3%,reducing the mean delay by 95%,and reducing packet loss by 99.7%relative to normal,with DDoS attack traffic.
文摘The developed auxiliary software serves to simplify, standardize and facilitate the software loading of the structural organization of a complex technological system, as well as its further manipulation within the process of solving the considered technological system. Its help can be especially useful in the case of a complex structural organization of a technological system with a large number of different functional elements grouped into several technological subsystems. This paper presents the results of its application for a special complex technological system related to the reference steam block for the combined production of heat and electricity.
基金Under the auspices of the Social Science and Humanity on Young Fund of the Ministry of Education of China(No.21YJCZH100)the Scientific Research Project on Outstanding Young of the Fujian Agriculture and Forestry University(No.XJQ201920)+1 种基金the Science and Technology Innovation Special Fund Project of Fujian Agriculture and Forestry University(No.CXZX2021032)the Forestry Peak Discipline Construction Project of Fujian Agriculture and Forestry University(No.72202200205)。
文摘Under the influence of anthropogenic and climate change,the problems caused by urban heat island(UHI)has become increasingly prominent.In order to promote urban sustainable development and improve the quality of human settlements,it is significant for exploring the evolution characteristics of urban thermal environment and analyzing its driving forces.Taking the Landsat series images as the basic data sources,the winter land surface temperature(LST)of the rapid urbanization area of Fuzhou City in China was quantitatively retrieved from 2001 to 2021.Combing comprehensively the standard deviation ellipse model,profile analysis and GeoDetector model,the spatio-temporal evolution characteristics and influencing factors of the winter urban thermal environment were systematically analyzed.The results showed that the winter LST presented an increasing trend in the study area during 2001–2021,and the winter LST of the central urban regions was significantly higher than the suburbs.There was a strong UHI effect from 2001 to 2021with an expansion trend from the central urban regions to the suburbs and coastal areas in space scale.The LST of green lands and wetlands are significantly lower than croplands,artificial surface and unvegetated lands.Vegetation and water bodies had a significant mitigation effect on UHI,especially in the micro-scale.The winter UHI had been jointly driven by the underlying surface and socio-economic factors in a nonlinear or two-factor interactive enhancement mode,and socio-economic factors had played a leading role.This research could provide data support and decision-making references for rationally planning urban layout and promoting sustainable urban development.
文摘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.
文摘The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.
文摘Rapid bridge inspection and evaluation mainly uses information technology to test the quality of bridge infrastructure and structures,integrates the test results with the existing management system,completes the bridge status assessment,establishes information management files to provide bridge disease problem inspection and analysis,and provides support for the application of disposal measures.This paper briefly discusses the necessity of applying rapid inspection and evaluation technology and analyzes the bridge’s rapid inspection and evaluation content,inspection system,and application process.We look forward to the future application prospects of this technology and supporting those in this field.
基金Digital Twin and Acoustic Perception Research Team(2021XJTD06)。
文摘With the rapid development of information technology,the demand for talents in the field of software engineering is growing.In order to cultivate high-quality software engineering talents who meet the market demand,universities have continuously carried out the construction of software engineering majors.Accreditation Board for Engineering and Technology(ABET)certification,as an internationally recognized higher education quality assurance system,provides important reference and guidance for the construction of software engineering majors.Guided by student learning outcomes and core competencies,combined with the characteristics of software engineering talent cultivation,the innovation of talent cultivation mode takes industry-education integration and school-enterprise cooperation as the main development paths and explores comprehensive reform of the major in terms of professional positioning and goals,curriculum system,teaching conditions,and teachers.This comprehensive reform model has effectively promoted the development of major construction and improved the quality of talent cultivation.
