Enhancing Software Effort Estimation:A Hybrid Model Combining LSTM and Random Forest

Effort estimation plays a crucial role in software development projects,aiding in resource allocation,project planning,and risk management.Traditional estimation techniques often struggle to provide accurate estimates due to the complex nature of software projects.In recent years,machine learning approaches have shown promise in improving the accuracy of effort estimation models.This study proposes a hybrid model that combines Long Short-Term Memory(LSTM)and Random Forest(RF)algorithms to enhance software effort estimation.The proposed hybrid model takes advantage of the strengths of both LSTM and RF algorithms.To evaluate the performance of the hybrid model,an extensive set of software development projects is used as the experimental dataset.The experimental results demonstrate that the proposed hybrid model outperforms traditional estimation techniques in terms of accuracy and reliability.The integration of LSTM and RF enables the model to efficiently capture temporal dependencies and non-linear interactions in the software development data.The hybrid model enhances estimation accuracy,enabling project managers and stakeholders to make more precise predictions of effort needed for upcoming software projects.

The Influence of Academic Self-Efficacy on Learning Engagement in Online Education in China:The Mediating Role of Effort

The shift towards online intelligent learning has become the norm in education and is now a fundamental part of modern educational activities.However,this new model can influence students’learning behavior and lead to changes in their approach to learning.Based on online intelligent learning,we investigated how the academic self-efficacy of nursing students affects their engagement with learning and explored the role of academic attribution as a mediator.Five hundred fifty-three nursing college students from Hebei and Hunan provinces in China participated in the online questionnaire.The results revealed that effort plays a mediating role in the relationship between academic self-efficacy and learning engagement.

The relationship between age,acceptable noise level,and listening effort in middle-aged and older-aged individuals

Objective:The purpose of the study was to evaluate listening effort in adults who experience varied annoyance towards noise.Materials and methods:Fifty native Kannada-speaking adults aged 41e68 years participated.We evaluated the participant's acceptable noise level while listening to speech.Further,a sentence-final wordidentification and recall test at 0 dB SNR(less favorable condition)and 4 dB SNR(relatively favorable condition)was used to assess listening effort.The repeat and recall scores were obtained for each condition.Results:The regression model revealed that the listening effort increased by 0.6%at 0 dB SNR and by 0.5%at 4 dB SNR with every one-year advancement in age.Listening effort increased by 0.9%at 0 dB SNR and by 0.7%at 4 dB SNR with every one dB change in the value of Acceptable Noise Level(ANL).At 0 dB SNR and 4 dB SNR,a moderate and mild negative correlation was noted respectively between listening effort and annoyance towards noise when the factor age was controlled.Conclusion:Listening effort increases with age,and its effect is more in less favorable than in relatively favorable conditions.However,if the annoyance towards noise was controlled,the impact of age on listening effort was reduced.Listening effort correlated with the level of annoyance once the age effect was controlled.Furthermore,the listening effort was predicted from the ANL to a moderate degree.

An Artificial Neural Network-Based Model for Effective Software Development Effort Estimation

In project management,effective cost estimation is one of the most cru-cial activities to efficiently manage resources by predicting the required cost to fulfill a given task.However,finding the best estimation results in software devel-opment is challenging.Thus,accurate estimation of software development efforts is always a concern for many companies.In this paper,we proposed a novel soft-ware development effort estimation model based both on constructive cost model II(COCOMO II)and the artificial neural network(ANN).An artificial neural net-work enhances the COCOMO model,and the value of the baseline effort constant A is calibrated to use it in the proposed model equation.Three state-of-the-art publicly available datasets are used for experiments.The backpropagation feed-forward procedure used a training set by iteratively processing and training a neural network.The proposed model is tested on the test set.The estimated effort is compared with the actual effort value.Experimental results show that the effort estimated by the proposed model is very close to the real effort,thus enhanced the reliability and improving the software effort estimation accuracy.

Logical Effort理论在电路设计中的应用

介绍了一种对于包含较长互连线的CMOS电路的优化方法,该方法是在Logical Effort理论基础上加入互联电阻模型得到的。这是一种简单的延迟模型,非常适合于快速而又有效的手工计算。有助于快速的预测电路的最小延迟,并以此优化电路的结构和逻辑门的尺寸。通过仿真证明了,当逻辑结构不是简单的反相器时,一样可以通过带互联电阻模型的Logical Effort模型得到简单的优化方案。

面向Best Effort业务的IEEE 802.16m休眠模式及性能评估

针对IEEE 802.16m提出的新的休眠模式,为了定量刻画系统参数对系统性能的影响、优化设计系统参数,将有数据传输的扩展监听窗口抽象为忙期,无数据传输的监听窗口及之后的休眠窗口抽象为休假期,建立一个多重休假排队模型.结合Best Effort业务,考虑忙期长度与休假期长度之间的相互依赖关系,令首个休假长度随机变化,之后的休假长度按照指数方式增长.利用嵌入马尔科夫链方法,导出排队系统的稳态解,给出能量节省率及响应时间等性能指标的表达式.结合数值实验与仿真实验,揭示不同性能指标之间的折衷关系.构造成本函数,对休眠周期等系统参数进行优化设置,为IEEE 802.16m休眠模式的算法改进提供理论依据.

Case Study of Unbalanced Effort Distribution in E-C Consecutive Interpreting

Under the guidance of Daniel Gile's Effort Model, the paper makes an illustration of unbalanced effort distribution in the first phase of E-C consecutive interpretation through case studies, which are based on field interpretation practices. The paper explores the causes of improper effort distribution from three perspectives, namely knowledge of the language, extra-linguistic knowledge, and note-taking method. Then it renders several strategies to address improper effort distribution problems, aiming to offer some inspirations for the future field practice.

基于Logical Effort理论的集成电路延迟优化工具的研究

本文介绍了一种基于LogicalEffort理论研发的集成电路延迟优化工具,该工具综合考虑了互联引线的影响,通过计算比较不同的逻辑结构延迟来确定最佳的电路结构,同时提供逻辑门的最佳晶体管尺寸。我们以六种不同电路为设计实例,在90纳米设计中与SPICE模拟结果进行了比较,其误差在5%以内。鉴于该方法不依赖于版图级寄生参数信息的特点,我们认为该工具可以提供在电路设计的早期对延迟的可信评估,非常适用于快速CMOS电路设计构架的遴选。

Seismic effort of blasting wave transmitted in coal-rock mass associated with mining operation

Microseismic effects during the transmission of seismic waves in coal and rock mass associated with mining operation were studied by on-site blasting tests and microseismic monitoring in LW704 of Southern Colliery,Australia,by using spread velocities,amplitudes and frequency contents as the main analysis parameters.The results show that the average P-wave velocity,mean values of combined maximal amplitudes and frequencies of the first arrivals are all reduced significantly along with goaf expanding and intensity weakening of overlying strata during mining process.A full roof fracturing can make the average P-wave velocities,combined maximal amplitudes and frequencies of first arrivals reduce to about 69.8%,92.2% and 60.0%,respectively.The reduction of the above seismic parameters reveals dynamic effects of the variation of strata structure and property to the wave transmission and energy dissipation of blasting wave.The research greatly benefits further study on stability of surrounding rock under the destructive effort by mine tremor,blasting,etc,and provides experimental basis for source relocation and parameter optimization of seismic monitoring as well.

Study on Effect of Zhixinkang Capsule(脂欣康胶囊)in TreatingUnstable Effort Angina and Hyperlipidemia and Its Function in Vascular Endothelium Protection

Objective:To observe the clinical effect and protection of vascular endothelium of Zhixin-kang Capsule (ZXKC) in middle-aged and old people with unstable effort angina and hyperlipidemia. Methods: Sixty-five patients with unstable effort angina were randomly divided into ZXKC group (34 cases) and control group (31 cases). Conventional western medical therapy was given to both groups, with ZXKC group receiving additional ZXKC treatment. Data of 20 healthy persons were taken as normal group. Forty-eight patients with hyperlipidemia were divided into ZXKC group treated with ZXKC (31 cases) and control group treated with Yixintong (17 cases). The changes of clinical symptoms and laboratory indexes in all the patients were observed before and after treatment. Results: In patients with unstable effort angina, the efficacy of treatment of ZXKC, the withdrawal rate of nitroglycerin, the relieving of symptoms, the improvement of the electrocardiogram, the counts of circulating endothelial cells, the content of platelet P-selectin, the content of plasma endothelin (ET), the activity of superoxide dismutase (SOD) and the activity of malonyldialdehyde (MDA) were all better than those in the control group. In patients with hyperlipidemia, there was no significant difference in lipids reduction between ZXKC group and the control group. In both groups, the total cholesterol (TC), triglyceride (TG), low density lipo-protein-cholesterol (LDL-C), lipoprotein(a) [Lp(a)] , ET, oxidized low density lipoprotein, MDA, arte-riosclerotic index (AI) all lowered obviously, while the SOD, HDL-C and calcitonin gene-related peptide (CGRP) were all elevated markedly. In the ZXKC group, the nitric oxide(NO) increased significantly whereas the ET/CGRP and ET/NO decreased markedly. The total effective rate in symptom relieving, the markedly effective rate, the reduction of TC, ET and ET/CGRP, and the elevation of SOD in ZXKC group were all superior to those in the control group. Conclusion: ZXKC could effectively resist myocardial ischemia, relieve angina, reduce blood lipids, protect vascular endothelial cells, inhibit the activation of platelets, and resist lipid peroxidation.

Grey Prediction Based Software Stage-Effort Estimation

The software stage-effort estimation can be used to dynamically adjust software project schedule, further to help make the project finished on budget. This paper presents a grey model Verhulst based method for stage-effort estimation during software development process, a bias correction technology was used to improve the estimation accuracy. The proposed method was evaluated with a large-scale industrial software engineering database. The results are very encouraging and indicate the method has considerable potential.

Co-effect of Demand-control-support Model and Effort-reward Imbalance Model on Depression Risk Estimation in Humans: Findings from Henan Province of China

Objective To investigate the co-effect of Demand-control-support （DCS） model and Effort-reward Imbalance （ERI） model on the risk estimation of depression in humans in comparison with the effects when they are used respectively. Methods A total of 3 632 males and 1 706 females from 13 factories and companies in Henan province were recruited in this cross-sectional study. Perceived job stress was evaluated with the Job Content Questionnaire and Effort-Reward Imbalance Questionnaire （Chinese version）. Depressive symptoms were assessed by using the Center for Epidemiological Studies Depression Scale （CES-D）. Results DC （demands/job control ratio） and ERI were shown to be independently associated with depressive symptoms. The outcome of low social support and overcommitment were similar. High DC and low social support （SS）, high ERI and high overcommitment, and high DC and high ERI posed greater risks of depressive symptoms than each of them did alone. ERI model and SS model seem to be effective in estimating the risk of depressive symptoms if they are used respectively. Conclusion The DC had better performance when it was used in combination with low SS. The effect on physical demands was better than on psychological demands. The combination of DCS and ERI models could improve the risk estimate of depressive symptoms in humans.

Prevalence of Major Cardiovascular Risk Factors and Cardiovascular Disease in Women in China: Surveillance Efforts

In this study, we aimed to assess the relationship of socioeconomic status and acculturation with cardiovascular disease （CVD） risk profiles and CVD and examine the CVD risk factors associated with CVD. We used data from the 2010 China Chronic Disease and Risk Factor Surveillance surveys, which consisted of a nationally representative sample of women. The following prevalence was found： myocardial infarction （MI）：

Incorporating S-shaped testing-effort functions into NHPP software reliability model with imperfect debugging

Testing-effort（TE） and imperfect debugging（ID） in the reliability modeling process may further improve the fitting and prediction results of software reliability growth models（SRGMs）. For describing the S-shaped varying trend of TE increasing rate more accurately, first, two S-shaped testing-effort functions（TEFs）, i.e.,delayed S-shaped TEF（DS-TEF） and inflected S-shaped TEF（IS-TEF）, are proposed. Then these two TEFs are incorporated into various types（exponential-type, delayed S-shaped and inflected S-shaped） of non-homogeneous Poisson process（NHPP）SRGMs with two forms of ID respectively for obtaining a series of new NHPP SRGMs which consider S-shaped TEFs as well as ID. Finally these new SRGMs and several comparison NHPP SRGMs are applied into four real failure data-sets respectively for investigating the fitting and prediction power of these new SRGMs.The experimental results show that：（i） the proposed IS-TEF is more suitable and flexible for describing the consumption of TE than the previous TEFs;（ii） incorporating TEFs into the inflected S-shaped NHPP SRGM may be more effective and appropriate compared with the exponential-type and the delayed S-shaped NHPP SRGMs;（iii） the inflected S-shaped NHPP SRGM considering both IS-TEF and ID yields the most accurate fitting and prediction results than the other comparison NHPP SRGMs.

Is the severity of obstructive sleep apnea or the magnitude of respiratory effort associated with gastroesophageal reflux?

In a recent issue ot World Journal of Gastroenterology, Demeter et al., reported that in patients having both gastro-esophageal reflux disease （GERD） and obstructive sleep apnea （OSA）, there was a positive correlation between endoscopic findings of GERD and the number of apneas and hypopneas per hour, namely apnea hypopnea index. They proposed that the severity of OSA and GERD are parallel to each other. The study of Demeter and colleagues is very important, not only for assessing reflux-induced esophageal damage in OSA,

NHPP-based software reliability model considering testing effort and multivariate fault detection rate

In recent decades,many software reliability growth models（SRGMs） have been proposed for the engineers and testers in measuring the software reliability precisely.Most of them is established based on the non-homogeneous Poisson process（NHPP）,and it is proved that the prediction accuracy of such models could be improved by adding the describing of characterization of testing effort.However,some research work indicates that the fault detection rate（FDR） is another key factor affects final software quality.Most early NHPPbased models deal with the FDR as constant or piecewise function,which does not fit the different testing stages well.Thus,this paper first incorporates a multivariate function of FDR,which is bathtub-shaped,into the NHPP-based SRGMs considering testing effort in order to further improve performance.A new model framework is proposed,and a stepwise method is used to apply the framework with real data sets to find the optimal model.Experimental studies show that the obtained new model can provide better performance of fitting and prediction compared with other traditional SRGMs.

Study on Communication Effect of Food Safety Risk in Social Media:the Influence of Response Effort Level on Consumption Willingness Change

By constructing influence model for communication effect of food safety risk in social media environment,the influences of different response manners taken by relevant enterprises on consumers' cognition and purchasing intention are analyzed,and influence mechanisms of response effort level,interaction and content reliability on consumers' attitudes are revealed. Based on quasi-experimental study with three kinds of response effort levels,it is found that content reliability,interaction and effort degree of enterprise response under negative information of food safety event have significant impacts on communication effect and consumers' purchasing intention.

听力康复中的新概念“Listening Effort”

虽然汉语关于听觉方面的术语不少，包括听觉、听力、聆听等，但目前汉语尚无能表达英文“listening effort”相对应的术语，本文在分析不同译法的基础上，试图提出笔者个人的建议，抛砖引玉，望国内学者能对此关注，并完善此领域的研究。

Case-Based Reasoning for Reducing Software Development Effort

How can we best find project changes that most improve project estimates? Prior solutions to this problem required the use of standard software process models that may not be relevant to some new project. Also, those prior solutions suffered from limited verification (the only way to assess the results of those studies was to run the recommendations back through the standard process models). Combining case-based reasoning and contrast set learning, the W system requires no underlying model. Hence, it is widely applicable (since there is no need for data to conform to some software process models). Also, W’s results can be verified (using holdout sets). For example, in the experiments reported here, W found changes to projects that greatly reduced estimate median and variance by up to 95% and 83% (respectively).

Optimizing Software Effort Estimation Models Using Firefly Algorithm

Software development effort estimation is considered a fundamental task for software development life cycle as well as for managing project cost, time and quality. Therefore, accurate estimation is a substantial factor in projects success and reducing the risks. In recent years, software effort estimation has received a considerable amount of attention from researchers?and became a challenge for software industry. In the last two decades, many researchers and practitioners proposed statistical and machine learning-based models for software effort estimation. In this work, Firefly Algorithm is proposed as a metaheuristic optimization method for optimizing the parameters of three COCOMO-based models. These models include the basic COCOMO model and other two models proposed in the literature as extensions of the basic COCOMO model. The developed estimation models are evaluated using different evaluation metrics. Experimental results show high accuracy and significant error minimization of Firefly Algorithm over other metaheuristic optimization algorithms including Genetic Algorithms and Particle Swarm Optimization.