Relationship between Project Consultants’ Performance and Project Success in the Rwandan Construction Industry

As discovered, today’s Rwandan construction industry is developing day by day, which plays a very important role in the country’s economic growth. In the construction industry, project consultants play a very significant role in providing services for such projects. The project consultants provide services from the beginning of the project to the completion of the project. Using project consultants is very useful for construction projects because it can ameliorate project efficiency and effectiveness. The main purpose of this paper is to investigate the relationship between project consultants’ performance and project success in the Rwandan construction industry. The data used in this study were obtained from primary and secondary sources. The secondary data was attained through an elaborated literature review of various books, articles, and papers related to this research to outlining and describing the chief ideas of this research title. The primary data was compiled through a questionnaire survey that was directed to 110 selected professionals in the construction projects in Rwanda to collect data from the site for statistical analysis of the research to test the hypothesis. However, a total of 90 usable responses were received within the scheduled period representing the response rate of 81.82%, which is likely to be representative and acceptable. Data collected from the questionnaire surveys were analyzed using the Statistical Package for Social Scientists (SPSS), excel spreadsheets, and Relative Importance Index (RII), which provide more merit presentations. The survey results show that even if there are many obstacles in the use of project consultants in the Rwandan construction industry such as lack of knowledge and practice in project consulting, lack of well-trained project consulting professionals, lack of training opportunities in project consulting, lack of knowledge and experience in addition to the senior management opposition, and lack of local project consulting guidelines and information;they are needed in the construction project to make it more successful through reducing and saving the overall project’s life cycle cost according to client’s wishes, keeping time of construction project, improving quality of the project products in the present and future, removing major variations that affect construction project with its attendant cost overrun, and advising on construction project process. Therefore, it is more important to remark that the good performance of the project consultants in any industry especially in the construction industry will contribute to the successful implementation of the project. From the results of the study, the performance of project consultants is closely related to the success of the construction industry in Rwanda. The project consultants’ leading skills and knowledge automatically guide the project to complete with accurate time, budget, and quality to make the project successful. In this paper, we will also consider the project success criteria;the role and responsibility of project consultants;the factors affecting the performance of project consultants;and the reasons that hinder the implementation of project consulting in the Rwandan construction industry.

The Relationship between Financial Reporting System and Project Success: A Case of Construction Projects in UAE

The purpose of this paper is to deliver a better perception of the project success,and how reporting system might increase the probability of project success in construction projects in UAE.Further,it aims at exploring the relationship between effective reporting system in terms of the characteristic of its outputs(mainly effectiveness of financial reporting system)and project success.Semi-structured interviews with a number of interior auditors,accountants,and chief financial officers(CFOs)from different corporations in construction sector in UAE in order to recognize how effective reporting system in terms of the characteristic of its outputs(broad scope,timeliness,aggregation,and integration)might contribute to increase the probability of project success.There are several success factors in construction projects in UAE,thus it is very hard to capture all these factors in one paper.Hence,this paper is not considering all project success factors rather it focuses on the characteristic of outputs of the reporting system generally and the financial reporting system particularly(broad scope,timeliness,aggregation,and integration),as most of the studies in the literature considered the reporting system as a key factor of project success.This paper adds to both project management and accounting research by evidencing results from an exploration how effective reporting might impact the project success,with valuable implications for standard officials,customers,investors,stakeholders,sponsors,shareholders,CFOs,project developer,consultants,internal auditors,and accounting academics.The effective reporting system in United Arab Emirates(UAE)construction projects enables possessors,customers,and contractors of projects to get timely information about the progress of project in a brief and significant format which in turn improve the decision-making process and contribute to project success.This paper implies a contribution for both project management literature and accounting research by investigative the effectiveness of reporting system in project successes from historical point of view and contemporary point of view.

A Suggested Theoretical Framework for Software Project Success

Current literature on software project management indicates that the majority of software projects either are considered a failure or challenged. These projects are characterized by exceeding budget, exceeding time, and failing to meet customer expectations. The fact that most projects fail highlights the need for research regarding the factors that lead to software project success or failure. This paper presents a theoretical framework for software project success. Based on deep analysis of current literature on software success factors, a theoretical framework is formulating. The suggested framework shows factors that have to be carefully considered in order to achieve software project success. The factors included in the framework are dividing into four categories: organizational factors, technical factors, people factors, and culture factors. The suggested framework is new in the sense that it includes many factors that are not founding together in any of the previous similar frameworks.

A Successful Integrated Project

In recent years,the Juxian County Family Planning Association of Shandong Province has vigorously initiated various income-generating activities and achieved encouraging results in integrating the family plan-ning programme with the development of the rural cconomny,improving living standards and building up the mental civilization of the people.

Sino-Japanese Cooperation Project in Tarim Basin Successfully Wound up

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Successful Completion of AI-Ahmadi Refinery Restoration Project in Kuwait

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紫外吸收光谱结合SPA-ELM算法的水体磷酸根离子检测研究

在工业锅炉中随着水蒸气蒸发,大量的钙镁离子留在炉水中,如果不加处理,在水冷管中会形成水垢,造成爆管停炉。为了保障设备的安全运行,消除安全隐患,工业上通过维持水中一定含量的磷酸根离子来去除锅炉中的钙、镁水垢。传统的磷酸根离子检测技术主要有比色法、分光光度法、色谱法、电位法等,这些方法前期处理步骤较繁琐且耗时较长。光谱法是通过测定物质的吸收光谱并建立和浓度关系的数学模型,对物质浓度定量的一种分析方法。为了满足磷酸根离子快速、实时测量的要求,提出了一种基于紫外吸收光谱结合SPA-ELM算法快速测量磷酸根离子的方法。按照我国《工业锅炉水质GB/T 1576—2018》中所规定的进入热水锅炉前的水质参数要求,配置37份浓度范围在5~100 mg·L^(-1)磷酸根溶液,使用搭建的实验装置,采集紫外吸收光谱。使用SPXY将样品按照7∶3的比例随机划分训练集、测试集;使用Savitzky-Golay(S-G)滤波对数据预处理以提高光谱的信噪比;通过连续投影算法(SPA)压缩光谱数据,筛选出5个与磷酸根强相关的特征波长;使用极限学习机(ELM)将特征波长处的吸光度与样本浓度进行拟合,以决定系数R2和均方根误差RMSE作为模型评价指标,建立磷酸根离子的回归模型。采用所提出的建模方法所建立的模型训练集的R2与RMSE分别为0.9972和1.3015 mg·L^(-1),测试集的R^(2)与RMSE分别为0.9995和0.5174 mg·L^(-1)。为了验证所提出的SPA-ELM预测模型效果,另外建立了LASSO-ELM、PCA-ELM、SPA-PLS和SPA-SVR四种预测模型进行对比。实验结果表明,SPA-ELM建立的预测模型的R2和RMSE均优于其他四种预测模型,说明采用的特征选择方法和回归方法均为最优,能够对磷酸根浓度范围为5~100 mg·L^(-1)的水体进行准确预测,为水中磷酸根离子的检测提供了一种新的解决方法。

基于SPA-GA-SVR模型的土壤水分及温度预测

土壤湿度和温度是影响水文循环和气候变化的重要参数,在农业实践活动和生态平衡中起着重要作用。为及时、准确地监测土壤含水量(Soil Moisture Content,SMC)及温度,提出了一种基于高光谱数据的预测方法。实验数据集来自为期5天的实地测量,所获得的高光谱数据包含大量的噪声及冗余信息,因此首先用Savitzky-Golay卷积平滑对光谱数据进行降噪处理,利用连续投影算法(Successive Projection Algorithm,SPA)提取数据特征波长,然后通过遗传算法(Genetic Algorithm,GA)对支持向量机回归(Support Vector Regression,SVR)的超参数权值和偏置进行优化,构建SPA-GASVR混合算法模型对土壤水分和温度进行预测,并与BP神经网络(Back Propagation Neural Network,BPNN)、SPA-BP、SVR、SPA-SVR、GA-SVR这5种模型的预测性能进行比较。实验结果表明:各模型在土壤湿度低于30%的情况下,表现出的预测能力差异并不显著。但整体上,复合模型相比于单一的神经网络或机器学习模型具有明显的优势,且经过连续投影算法优化的模型进一步的提高其预测能力,最终SPA-GA-SVR算法在各项指标上均优于其他模型,土壤水分预测模型的R^(2)=0.981、RMSE=0.473%,土壤温度预测模型R^(2)=0.963、RMSE=0.883℃。实验证明基于高光谱数据,经过SPA和GA优化的SVR模型能实现对土壤湿度和温度精准的预测。该方法具有一定的应用价值和现实意义,可应用于便携式高光谱仪和无人机上,实现对土壤水分和温度的实时监测,为今后的播种及灌溉提供理论参考。

“一村一名大学生计划”对农村创业成功的影响研究

兴大业,必先用人。人才振兴是推进乡村振兴的重要引擎力量。本文基于教育部“一村一名大学生计划”评选出的69个案例,运用扎根理论,通过开放式编码、主轴式编码以及选择式编码,分析出“一村一名大学生计划”对农村创业成功的核心影响因素,并结合社会资本理论与自我效能理论,探究了“一村一名大学生计划”实现农村创业成功的路径。结果发现:“一村一名大学生计划”的开展,具有增加农村创业者社会资本和专业知识、提高创业者个人能力的功能,从而帮助农村创业者有效地识别创业机会,获取更优质的创业资源,做出科学正确的创业行为,最终实现创业成功。同时,基于所得结果,归纳、构建出“一村一名大学生计划”影响农村创业成功的机理模型,据此提出未来助力“乡村振兴”的相关建议。

基于变量筛选与机器学习算法的渭-库绿洲土壤有机质含量估测研究

选择合适的变量筛选方法和模型可有效提升土壤有机质含量的估测精度。本研究以新疆渭干河-库车河绿洲为研究区,基于哨兵2号(Sentinel-2)卫星影像和实测土壤有机质,通过对土壤有机质与遥感影像波段及多种光谱指数进行相关分析,结合Boruta算法和连续投影算法(Successive Projections Algorithm,SPA)进行变量筛选,构建随机森林(Random Forest,RF)模型和BP神经网络(Back Propagation Neural Network,BPNN)模型进行表层土壤有机质含量的估测。结果表明:(1)波段B3、B4、B5、B7和B8A以及转换植被指数(Transformed Vegetation Index,TVI)、颜色指数(Color Index,CI)对土壤有机质含量的估测具有重要作用;(2)单独使用Boruta算法和SPA算法筛选的变量集建模效果要优于全变量集以及结合算法筛选的变量集,Boruta算法优于SPA算法;(3)RF模型的估测能力优于BPNN模型,最优估测模型训练集和验证集的决定系数(R^(2))均大于0.74,模型拟合效果较好,均方根误差(RMSE)小于2.0 g/kg,相对分析误差(RPD)大于1.6,能够较好地进行土壤有机质含量的估测。采用Boruta算法结合随机森林模型可较好地反演绿洲表层土壤有机质的空间分布,为该区域土壤养分评价提供参考。

拉曼光谱结合机器学习对植物油的分类鉴别

该研究采集了六类(38个品牌)常见植物油的551份拉曼光谱,并根据光谱数据分别建立了正交偏最小二乘判别和支持向量机模型,对比了连续投影法和竞争性自适应重加权采样法对模型识别正确率的影响。基于算法改进的偏最小二乘判别模型的总体预测准确率为82.53%、83.13%,低于基于全光谱数据建立的偏最小二乘判别模型。竞争性自适应重加权采样法结合支持向量机对玉米油、橄榄油、葵花籽油和芝麻油的品牌分类测试集正确率均达到100%;椰子油和花生油的测试集正确率为22.22%、63.64%。两类特征提取算法均可以减少建立分类模型所需的变量数目和计算资源,但以提取后变量建立分类模型可能会导致识别正确率下降。在解决样本间相似度较高的多分类问题时,支持向量机模型优于正交偏最小二乘判别模型。正确率差异可能和生产商所使用的生产工艺以及植物油原料相关。面对案件侦办中品牌种类多样的油脂物证,基于拉曼光谱分析和特征提取算法的支持向量机模型可为可食用植物油的无损快速检验提供一定的参考与借鉴。

基于高光谱成像的烟丝中梗签分类识别研究

针对烟丝中梗签分类识别检测问题,利用高光谱成像技术,结合机器学习方法对烟丝中掺杂的梗签进行分类快速识别。首先,基于短波近红外高光谱成像技术,采用标准正态变化(SNV)对烟丝和梗签光谱数据进行预处理,消除光谱散射和漫反射的影响,减少检测干扰信息。然后,利用连续投影算法(SPA)进行特征波长选择,融合极端梯度提升(XGBoost)算法,提出了1种基于XGboost算法的烟丝中梗签分类模型。最后,采用Mean-shift均值漂移算法和形态学梯度算法相结合的方式作为后处理方法,对模型的分类结果进行后处理,实现烟丝中梗签的快速智能检测。结果表明:建立的SNV-SPA-XGBoost分类模型,训练集和测试集准确率分别达到100%和99.32%,经后处理后对A_(1)(1.0~1.5 cm)、A_(2)(0.5~1.0 cm)、A_(3)(<0.5 cm)梗签检测准确率分别达100%、95.50%和86%。

陕西互联网众筹发展的现状、问题与对策

互联网众筹为创业者的项目融资提供了一种新的选择。基于国内具有代表性的四个众筹平台,收集整理了46个陕西省互联网众筹项目数据。从项目数量、筹资金额、行业分布、地区分布、众筹成功率等角度对陕西互联网众筹发展现状进行分析。发现陕西互联网众筹存在着众筹项目融资金额不足、众筹项目类型单一、缺乏特色、众筹方案设计质量不高、宣传互动不足等问题。提出了推动创业者和企业众筹融资意识、注重特色项目培育优化项目方案、加强项目的推广与上线后的持续宣传等促进陕西互联网众筹发展的对策建议。

The continuous wavelet projections algorithm: A practical spectral-feature-mining approach for crop detection

Spectroscopy can be used for detecting crop characteristics. A goal of crop spectrum analysis is to extract effective features from spectral data for establishing a detection model. An ideal spectral feature set should have high sensitivity to target parameters but low information redundancy among features.However, feature-selection methods that satisfy both requirements are lacking. To address this issue,in this study, a novel method, the continuous wavelet projections algorithm(CWPA), was developed,which has advantages of both continuous wavelet analysis(CWA) and the successive projections algorithm(SPA) for generating optimal spectral feature set for crop detection. Three datasets collected for crop stress detection and retrieval of biochemical properties were used to validate the CWPA under both classification and regression scenarios. The CWPA generated a feature set with fewer features yet achieving accuracy comparable to or even higher than those of CWA and SPA. With only two to three features identified by CWPA, an overall accuracy of 98% in classifying tea plant stresses was achieved, and high coefficients of determination were obtained in retrieving corn leaf chlorophyll content(R^(2)= 0.8521)and equivalent water thickness(R^(2)= 0.9508). The mechanism of the CWPA ensures that the novel algorithm discovers the most sensitive features while retaining complementarity among features. Its ability to reduce the data dimension suggests its potential for crop monitoring and phenotyping with hyperspectral data.

Design-Stage Prediction of Project Correctness or Incorrectness

The success of a software development project requires the early objective determination of the project’s correctness or incorrectness and the identification of the most effective solution for project management. However, few studies have been conducted on the reliable quantitative early judgment of correctness or incorrectness. In recent years, the collection and accumulation of actual attribute data from Japanese domestic software development projects have been conducted by the Software Engineering Centre of the Information-Technology Promotion Agency of Japan. In a previous article, we proposed a precise definition of project correctness or incorrectness and identified the important factors in successful projects;we also proposed a quantitative decision-making method for judging project correctness or incorrectness objectively and quantitatively on the basis of discriminant analysis using project completion attribute data. On the basis of the previous results, we propose a quantitative decision-making technique for the early judging of project correctness or incorrectness based on the attribute data of design stage as early stage of development.

Influence of Farmer Capacity Building in Institutional Linkages on Performance of Smallholder Irrigation Projects in Migori County, Kenya

The smallholder irrigation sector in Kenya is considered inadequately developed. The study views unawareness of critical success factors in the smallholder irrigation sector as contributing to poor performance of smallholder irrigation projects. Consequently, the study investigated influence of farmer capacity building in institutional linkages on performance of smallholder irrigation projects in Migori County, Kenya. The study embraced a pragmatic view of philosophy, and used cross sectional and correlation research design. The target population was 2815, and comprised farmers drawn from fifteen smallholder irrigation projects that receive water from River Kuja through Lower Kuja Project. The sample size was 341. The study used systematic random sampling procedure to draw the sample, and collected data using questionnaire. Data was analysed using descriptive and inferential statistics. The study established that farmer capacity building in institutional linkages has a significant influence on performance of smallholder irrigation projects (r = 0.803, R2 = 0.645, F (5, 331) = 120.254 and p < 0.000 < 0.05). Thus, the study recommends that Migori County Government come up with policies that link smallholder irrigation projects in Lower Kuja Project to institutions that provide land ploughing services, certified seeds and fertilisers, control of crop pests and diseases, transportation of farm produce and marketing of farm produce.

基于连续投影算法的土壤全氮和碱解氮含量高光谱估测

基于高光谱数据构建土壤全氮和碱解氮含量估测模型,为准确快速检测植烟土壤全氮和碱解氮含量提供新方法。以会东县和会理市植烟土壤为研究对象,利用高光谱成像获取土壤光谱反射率数据,应用连续投影算法(SPA)和相关分析法(CA)筛选特征波段,并分别采用全波段和特征波段构建偏最小二乘回归(PLSR)、岭回归(RR)和核岭回归(KRR)模型来估测土壤全氮和碱解氮含量。结果表明:(1)原始光谱经4种预处理方法处理后,建立的估测模型精度均有提高;其中经一阶导数(D1)组合标准正态分布(SNV)预处理后,使用全波段建立的全氮和碱解氮含量估测模型精度均较高。(2)SPA筛选出了10个土壤全氮特征波段,13个土壤碱解氮特征波段,分别占全波段数量的2.58%和1.98%。(3)原始光谱经D1-SNV预处理后,用SPA筛选特征波段构建的全氮和碱解氮含量KRR估测模型性能均较好;全氮估测模型验证集决定系数(R^(2))为0.87,均方根误差(RMSEV)为0.23,相对分析误差(RPD)为2.77;碱解氮估测模型验证集的R^(2)为0.91,RMSEV为14.15,RPD为3.39。运用SPA结合KRR构建的模型能较好地估测研究区土壤全氮和碱解氮含量,D1-SNV-SPA-KRR方法可实现该地区全氮和碱解氮含量的准确估测。

基于近红外光谱的SSA-RELM的菠萝含水率快速检测

目的:建立快速无损检测菠萝含水率的方法。方法:提出一种基于连续投影法的特征波长选择和麻雀搜索算法(SSA)优化正则化极限学习机(RELM)的菠萝含水率检测模型。针对菠萝近红外光谱数据具有维度高、冗余信息多的特点,分别对比连续投影法、主成分分析法和全波段等筛选特征波长的结果,确定菠萝近红外光谱特征波长筛选方法;针对RELM模型性能受其输入层权值和隐含层偏置的影响,运用麻雀搜索算法优化RELM模型的输入层权值和隐含层偏置,提出一种基于麻雀搜索算法改进正则化极限学习机的菠萝含水率检测模型。结果:与遗传算法改进正则化极限学习机(GA-RELM)、粒子群算法改进正则化极限学习机(PSO-RELM)和RELM相比,基于麻雀算法改进正则化极限学习机(SSA-RELM)的菠萝含水率检测模型的检测精度最高。结论:麻雀搜索算法优化RELM模型可以有效提高RELM模型的菠萝含水率检测精度。