Project Size Research Articles

EspressoDB: A scientific database for managing high-performance computing workflows

Leadership computing facilities around the world support cutting-edge scientific research across a broad spectrum of disciplines including understanding climate change, combating opioid addiction, or simulating the decay of a neutron. While the increase in computational power has allowed scientists to better evaluate the underlying model, the size of these computational projects have grown to a point where a framework is desired to facilitate managing the workflow. A typical scientific computing workflow includes: Defining all input parameters for every step of the computation; Defining dependencies of computational tasks; Storing some of the output data; Post-processing these data files; Performing data analysis on output. EspressoDB is a programmatic object-relational data management framework implemented in Python and based on the Django web framework. EspressoDB was developed to streamline data management workflows, centralize and guarantee data integrity, while providing domain flexibility and ease of use. The framework provided by EspressoDB aims to support the ever increasing complexity of workflows of scientific computing at leadership computing facilities, with the goal of reducing the amount of human time required to manage the jobs, thus giving scientists more time to focus on science.

Recognition of Polymer Terminus by Metal-Organic Frameworks Enabling Chromatographic Separation of Polymers.

Unlike commonly used molecular recognition techniques, recognition of polymer structures requires an additional aspect of extremely high recognition ability, by which marginal structural differences can be identified in a large polymer chain. Herein we show that metal-organic frameworks (MOFs) can recognize polymer terminal structures, thus enabling the first reported chromatographic separation of polymers. End-functionalized polyethylene glycols (PEGs) are selectively inserted into the MOF channel, the insertion kinetics being dependent on the projection size of the PEG terminus. This size-selective insertion mechanism facilitates precise discrimination of end-functionalized PEGs using liquid chromatography (LC). An MOF-packed column thus provides an efficient and easily accessible method for the separation of such end-functionalized polymers using conventional LC systems.

Business models and financial characteristics of community energy in the UK

Community energy projects take a decentralized and participatory approach to low-carbon energy. Here we present a quantitative analysis of business models, financing mechanisms and financial performance of UK community energy projects, based on a new survey. We find that business models depend on technology, project size and the fine-tuning of operations to local contexts. Although larger projects rely more on loans, community shares are the most common and cheapest financial instrument in the sector. Community energy has pioneered low-cost citizen finance for renewables, but its future is threatened by reductions, and instability, in policy support. Over 90% of the projects in our sample make a financial surplus during our single-year snapshot, but this falls to just 20% if we remove income from price guarantee mechanisms, such as the Feed-in Tariff scheme. Renewed support and/or business model innovations are therefore needed for the sector to realize its potential contribution to the low-carbon energy transition. Community energy is a promising alternative to large-scale energy provision that could support decarbonization efforts. This study analyses business models, financing mechanisms and the financial performance of community energy projects in the UK to understand what is needed to better support the sector.

Machine Learning Classification of Cerebral Aneurysm Rupture Status with Morphologic Variables and Hemodynamic Parameters.

To construct a classification model of rupture status and to clarify the importance of morphologic variables and hemodynamic parameters on rupture status by applying a machine learning (ML) algorithm to morphologic and hemodynamic data of cerebral aneurysms. Between 2011 and 2019, 226 (112 ruptured and 114 unruptured) cerebral aneurysms in 188 consecutive patients were retrospectively analyzed with computational fluid dynamics (CFD). A random forest ML algorithm was applied to the results to create three classification models consisting of only morphologic variables (model 1), only hemodynamic parameters (model 2), and both morphologic variables and hemodynamic parameters (model 3). The accuracy of rupture status classification and the importance of each variable or parameter in the models were computed. The accuracy was 77.0% in model 1, 71.2% in model 2, and 78.3% in model 3. The three most important features were projection ratio, size ratio, and aspect ratio in model 1; low shear area ratio, oscillatory shear index, and oscillatory velocity index in model 2; and projection ratio, irregular shape, and size ratio in model 3. Classification models of rupture status of cerebral aneurysms were constructed by applying an ML algorithm to morphologic variables and hemodynamic parameters. The model worked with relatively high accuracy, in which projection ratio, irregular shape, and size ratio were important for the discrimination of ruptured aneurysms.Supplemental material is available for this article.© RSNA, 2020.

Association of Number of Bidders and Minimum Bid Ratio (AEr) with Effect of E-bidding of Different Project

The purpose of this research is to analyze the relation between the number of bidders versus the minimum bid ratio (AEr)/percentage below the initial engineer’s estimate to type and size of project within Road Divisions Butwal and Shivapur. Bidding data of four consecutive fiscal years starting from 072/73 of two Road Divisions which are already completed its procurement stage were analyzed. The percentage below/contract awarded cost is directly proportional or a significant correlation was found with the number of the participated bidder in any project s of both divisions during the data study period. Bidders have to bid below 20% of the initial estimate that was found to get a project in hand by contractors and they are willing to bid low for the utilization of resources, types of equipment, manpower, and also to get experiences. This research revealed correlation coefficients between the number of bidders and percentage below engineers' estimates are 0.61 for the Butwal division and 0.67 for the Shivapur division. Correlation coefficients 0.82 and 0.83 was found in Nepalgunj and Mahendranagar. Percentage below engineers' estimate depends on 67 and 69% on the number of bidders in Nepalgunj and Mahendranagar respectively. E-bidding helped to promote competition along with low bidding. As there is 17% below with only hardcopy bidding but with e-bid the below percentages rises to 28% with more number of bidder per project. Improvement in existing offer granting framework with additional capability rules ought to be engaged by doling out the weight in the monitory term, soliciting a technique from the proclamation, upgraded e-offering framework, and affirmation for venture exhibitions of the undertaking before execution. This research would be useful for those who are involving in policy making and governing agencies like Public Procurement Monitoring Office and for making necessary amendments in existing rules.

Optimal timing and capacity choice under the rate-of-return renewable energy support

This article presents a stylized renewable energy (RE) investment project profitability analysis under a rate-of-return RE support type. We use a dynamic programming approach to value the real options. While the method is widely used in RE policy analysis, the rate-of-return support is presented in this framework for the first time. We formulate a stylized RE project under the rate-of-return regulation in the dynamic programming framework and solve for optimal investment timing and project size.•A stylized renewable energy (RE) investment under rate-of-return RE support is presented in the dynamic programming framework;•The system is solved for optimal capacity choice in the presence of the electricity price uncertainty. We also comment on the optimal investment timing, which turns out to be a now-or-never decision in this case.

Challenges Facing Local Contractors Working with Chinese Contractors in Addis Ababa Building Projects

Building construction projects particularly represents one of the largest sectors of the construction industry. Currently, the rise in construction of high rising buildings are observed in Addis Ababa, the capital city of Ethiopia. The number and size of building construction projects that are being constructed in the city are increasing through time and most of these projects were being carried out by Chinese contractors. Local contractors are also involved in those projects via a subcontracting strategy. However, it is not easy for local contractors to succeed by working with their foreign counterparts who have massive international experience and capacity. The aim of this study was assessing and identifying the challenging factors affecting local contractors’ performance in Chinese building projects in Addis Ababa. In order to achieve the objectives of this study, both quantitative and qualitative research approach were used with primary and secondary source of data. This study employed three types of data collection techniques such as a questionnaire surveys, interviews and observations. The target population for this study are local contractors and consultants involved in building projects that are carried out by Chinese contractors. In this study the researcher used Census/Parametric method of survey. That mean all target population of this study are included in this investigation, based on the consent and willingness of the participants. The Relative Importance Index (RII) was used as an instrument for analyzing data collected through questionnaire in tabular form by using Likert’s scale of five ordinal measures. Based on the analysis, it was found that the most challenging factors affecting local contractors’ performance in Chinese building projects were financial constraints, information exchange problems, cultural differences, unfamiliarity with Chinese work methodology and project complexity with a RII value of 0.84, 0.81, 0.77, 0.73 and 0.71 respectively. This study also identified and discussed the major cause and impact of those challenges and proposed measures to minimize their effect on the local performance in the upcoming projects through interviews from respondents and analyzed by using content analysis.

ICO vs. Equity Financing Under Imperfect, Complex and Asymmetric Information

This paper offers a model of a firm that raises funds for financing an innovative business project and chooses between ICO (initial coin offering) and equity financing. The model is based on information problems associated with both ICO and equity financing well documented in literature. The model provides several implications that have not yet been tested. For example we find that the message complexity can be benefitial for firms conducting ICOs. Also high-quality projects can use ICO as a signal of quality. Thirdly the average size of projects undertaking equity financing is larger than that of firms conducting ICO.

Reclamation pathway of waste piles: A case study in Shanghai

Reclaiming waste driven piles to use as the foundations of new buildings is an innovative and effective approach to manage waste driven piles for cleaner construction. A reclamation pathway for waste driven piles is proposed based on a renewal project in Shanghai. A detailed evaluation of the durability and bearing capacity of the waste driven piles is performed. Post-construction settlement in a normal building and a building with a foundation constructed with a combination of new and waste piles is compared to evaluate the performance of the waste piles. Technical suggestions are summarized to improve the reclamation pathway based on the findings of the renewal project. The results show that both the durability and bearing capacity of the waste piles meet the requirements of engineering applications. Reuse of waste piles reduced average settlement but increased the uneven settlement of the new buildings. Economic analysis indicates that reuse of waste driven piles in foundations of new buildings can save approximately $573,672 in construction costs and 1017.6 m3 in concrete for a project the size of the renewal project. Both technical and economic assessments corroborate the reclamation pathway for waste driven pile is necessary and appropriate for Shanghai. The proposed reclamation pathway benefits the management of waste piles and facilitates the cleaner production of construction industry.

Priority based Agile Estimation for Size and Time (PAEST)

Agile estimation process is an emerging research area because of agile practice of accepting requirements at any stage. Some agile practitioners are using agile estimation of size and time based on expert opinion and planning poker game. These methods are non-algorithmic method whereas algorithmic method of estimation always useful for novice estimator as it is based on empirical study. In this paper, we have proposed algorithmic method, Priority based Agile Estimation for Size and Time (PAEST) for projects using agile practices. PAEST incorporates the identification of factors estimating size of projects based on its priority and impact on the project. Size and Time estimation are computed as function of priority factor of project attributes and uncertainty in requirements of the projects. Paper also elaborates the case studies of various domain of software projects along with priority and intensity level of factors affecting the project estimation. We have incorporated three domains: web application, MIS project and critical software and seven project attributes out of 21 attributes used by generalized estimation method in our case studies. Number of project attributes can be scalable to any number depending on project domain. Algorithm prioritizes the project attributes and generates the estimates of the project more realistic. Introduction of prioritization helps novice to get estimates more precise. In our study we observed that uncertainty in project have more impact than project attributes.

Alternating Agency and Organizational Loyalty

We study a two-stage agency model in which the players take the role of the principal in turn. In the first stage, the board of the firm decides payment to the manager to induce him to set up and implement a project. In the second stage, the board evaluates the project to learn its value, and the manager decides the project size based on the board's report on its evaluation. The firm's payment policy to the manager trades off fine-tuning the project size according to its project evaluation and opportunity to exploit the manager's loyalty to the organization. We show that, when the variation of the project value is small enough, the outcome is pooling, regardless of the manager's loyalty level. When the variation is not too small, the outcome depends on the manager's loyalty level - the prevailing outcome entails separating when the manager's loyalty level is low and pooling when it is high.

A simulation – Optimization models for multi-reservoir hydropower systems design at watershed scale

Hydropower energy is one of the most economical and cleanest energies in the world. Due to the huge investment in hydropower projects, economic feasibility and determining the main design parameters related to plant sizing of hydro projects are extremely important. In this research, a simulation–optimization model for optimal design of hydropower systems with a systematic view of the basin (which is a complex nonlinear problem) has been developed. For water resources planning and management in the water basin, WEAP model has been used. Despite various capabilities, there are also limitations for hydropower systems modeling in WEAP. In this regard, a hydropower computation module has been employed to resolve these disadvantages. Then, PSO algorithm, linked to the simulation model and the developed optimization-simulation model has been used to solve the problem of optimal design of Garsha, Kuran Buzan, Sazbon and Tange mashoore power plant projects in Karkhe river basin. Objective function has been formulated based on two conventional methods in the economic analysis of hydro projects, i.e. electricity market price method and alternative thermal plant method. The objective function is maximization of net benefits of hydropower projects considering all resources, uses, and demands in the basin. Normal water level (NWL), Minimum Operation Level (MOL), Installed Capacity (IC) of dams and power-plants were chosen as decision variables of the problem. Finally, the results of optimal design of hydropower system have been discussed for both economic objective functions, followed by comparison and analysis of the results. the total generated energy and firm energy of the hydropower system is calculated bigger in alternative thermal plant method compared to market price method. However, the peak generated energy is computed larger in the market price.

Bundling in public–private partnership projects – a conceptual framework

PurposeThe performance of public–private partnership (PPP) projects depends on how the project has been structured. The traditional PPP option analysis for structuring project scope and size relating to the bundling of functions concerning a single component of the value chain will need to be extended to handle multi-component sectors such as municipal solid waste (MSW) in formulating the project scope. This analysis is currently missing in the extant literature. The paper aims to discuss these issues.Design/methodology/approachThrough a comprehensive literature review as the methodological backbone, this study develops a testable holistic framework for the procurement of MSW PPP projects that examines how various factors of bundling affect the performance of the PPP projects.FindingsUsing transaction cost economics, agency and auction theories, the review identifies that innovation, maturity, quality specifiability, scope, competition, information asymmetries and transaction attributes have a significant influence on the performance and success of the PPP projects.Research limitations/implicationsAlternative supply chain management possibilities and firm-level organisational ways can be predicted using this framework to strategize the solutions for the municipal infrastructure. Based on this contribution, future research can test the framework to increase the knowledge of bundling theory about how to structure network infrastructure PPP projects.Originality/valueStudies on how to bundle/unbundle the projects having components of the value chain are in a nascent stage. The present study attempts to extend the body of knowledge on PPP to the complexity of bundling both the functions and components of the value chain in structuring the PPP project scope.

Buyer preferences for auction pricing rules in online outsourcing markets: fixed price vs. open price

Fixed-price and open-price are two mechanisms with different auction pricing rules that are popularly used in online outsourcing markets. This research empirically examines the determinants of buyers’ choices between the two mechanisms with secondary data from an online outsourcing market. We found that buyers tend to use open-price auctions with large size projects, while their propensity to use fixed-price auctions increases when they are more familiar with the project, have more trading experience in the market, or less trust in the service providers. Moreover, buyer experience has significant moderating effects on the impact of project size and buyer distrust. Our empirical results reveal a unique insight that incomplete information and information asymmetry, rather than the expected buyer surplus, are critical factors to buyers’ preferences on bid dimensionality.

Potential impact of climate change on solar resource in Africa for photovoltaic energy: analyses from CORDEX-AFRICA climate experiments

The development of renewable electricity in Africa could be massive in coming decades, as a response to the rapid rising electricity demand while complying with the Paris Agreements. This study shows that in the high-resolution climate experiments of CORDEX-AFRICA, the annual mean solar potential is expected to decrease on average by 4% over most of the continent by the end of the century, reaching up to 6% over the Horn of Africa, as a direct result of decrease in solar radiation and increase in air surface temperature. These projections are associated with large uncertainties, in particular over the Sahel and the elevated terrains of eastern Africa. While the expected decrease may affect the sizing of the numerous solar projects planned in Africa for the next decades, this study suggests that it does not endanger their viability. At last, this study indicates that the design of such projects also needs to account for the non-negligible uncertainties associated with the resource.

Assessment of Cost and Extent of Delays in Public Sector Construction Projects in Aseer Region, KSA

The time performance of projects i.e. delay of construction projects is considered as one of the alarming problems around the world that has passive effect on the society development as well as on the country economy. The time performance of construction projects varies with country, region, project type and the perspectives of various stakeholders. The purpose of the paper is to know the extent of delay in the government sector projects in Aseer region, KSA and identifying whether the delay extent is natural or large compared to other areas. A total number of 228 public sector construction projects awarded in one decade have considered for the study purpose. The methodology for the project delays studies is as follows, collection of projects information from the main sources, classifying them according to the project size limits, analyzing the available data, knowing the delay size in every sector and comparing the delays of the different projects to identify the most delayed projects as well as those completed on time. Analysis of delays shows that the majority of construction projects in the Aseer region have exceeded their time and the most significant delay among government sectors was the Directorate-General for Health Affairs. The extent of delay in construction project decreases with the progress of country.

Moderating claims and disputes through collaborative procurement

Purpose Following the global financial crisis in 2008, the construction sector in UAE has been facing emergent criticisms for growing adversarial culture and rising prevalent claims and disputes between stakeholders. The complex, large size and fast track nature of construction projects in UAE, make project management very challenging under the commonly used traditional procurement routes. This paper aims to examine whether implementing collaborative procurement approaches can facilitate resolving the escalating number of claims and disputes in the UAE construction industry. Design/methodology/approach Considering the nature of the study, a quantitative method was selected to realize the research objectives. The questionnaire was uploaded using an online survey facility and distributed through e-mails and professional networks. The questionnaire was piloted with experts to assess whether the questions are unambiguous, easy to respond and intelligible. The feedback received was mostly positive with few comments and recommendations. The pilot responses were incorporated and the questionnaire was modified before the final sending out. The questionnaire survey consisted of six main sections to fulfill the research objectives. Findings Around three-quarters of the experts believe that the relationship is adversarial, with a lack of trust, win-lose attitude, with dismissive and opportunistic behavior. The survey reveals that the top causes of claims and disputes comprise the following: variations because clients initiated change requests; contractors selection on low bid only rather than including quality and performance considerations; and unfair risk allocation where majority of risks are transferred to contractors. The findings also identify eight collaborative practices, which have crucial positive impacts such as early identification of problems, better communication and enhanced trust and teamwork. Originality/value This research contributes to the enhancement of the management of claims and disputes for construction projects, which encompasses the following: the key characteristics of collaborative arrangements to improve the adversarial construction culture comprise: mutual respect, openness, fairness and non-opportunistic behaviors; the foremost roles of collaborative procurement in reducing claims and disputes embrace: early identification and resolution of problems, enhanced trust and teamwork spirit, improved relationships and better quality communication; the major practical barriers of implementing collaborative approaches incorporate: lack of awareness of their benefits, primitive legal framework of partnering arrangements and lack of transparency in procurement processes.

Supporting successful data sharing practices in earthquake engineering

Purpose Prior studies identified a need for further comparison of data-sharing practices across different disciplines and communities. Toward addressing this need, the purpose of this paper is to examine the data-sharing practices of the earthquake engineering (EE) community, which could help inform data-sharing policies in EE and provide different stakeholders of the EE community with suggestions regarding data management and curation. Design/methodology/approach This study conducted qualitative semi-structured interviews with 16 EE researchers to gain an understanding of which data might be shared, with whom, under what conditions and why; and their perceptions of data ownership. Findings This study identified 29 data-sharing factors categorized into five groups. Requirements from funding agencies and academic genealogy were frequent impacts on EE researchers’ data-sharing practices. EE researchers were uncertain of data ownership and their perceptions varied. Originality/value Based on the findings, this study provides funding agencies, research institutions, data repositories and other stakeholders of the EE community with suggestions, such as allowing researchers to adjust the timeframe they can withhold data based on project size and the amount of experimental data generated; expanding the types and states of data required to share; defining data ownership in grant requirements; integrating data sharing and curation into curriculum; and collaborating with library and information schools for curriculum development.

Contract bidding and quality of industrial and civil construction

Quality in construction industry can be defined as the attainment of acceptable levels of performance from construction activities. This performance would be attained when the activity meets or exceeds the requirement of the client or the owner. The quality of any product or service is achieved when it conforms to the desired specifications. Achieving quality in construction industry in long run is a tough issue and has been a problem. Inefficient or no practice of quality management procedures will result in great loss of time, money, material, resources. As a result of the size and cost of most construction projects, these efforts must fit into the legal framework governing the particular property. This framework will incorporate governmental regulations on the use of the property and various obligations that are created during the process of the construction. This bidding system is the most relevant today, because it allows you to create competitive conditions for applicants for construction, choose the best contractor and conclude a contract with him on the most favorable terms, while respecting the quality of both the bidding procedure and the construction process

Software defect prediction using over-sampling and feature extraction based on Mahalanobis distance

As the size of software projects becomes larger, software defect prediction (SDP) will play a key role in allocating testing resources reasonably, reducing testing costs, and speeding up the development process. Most SDP methods have used machine learning techniques based on common software metrics such as Halstead and McCabe’s cyclomatic. Datasets produced by these metrics usually do not follow Gaussian distribution, and also, they have overlaps in defect and non-defect classes. In addition, in many of software defect datasets, the number of defective modules (minority class) is considerably less than non-defective modules (majority class). In this situation, the performance of machine learning methods is reduced dramatically. Therefore, we first need to create a balance between minority and majority classes and then transfer the samples into a new space in which pair samples with same class (must-link set) are near to each other as close as possible and pair samples with different classes (cannot-link) stay as far as possible. To achieve the mentioned objectives, in this paper, Mahalanobis distance in two manners will be used. First, the minority class is oversampled based on the Mahalanobis distance such that generated synthetic data are more diverse from other minority data, and minority class distribution is not changed significantly. Second, a feature extraction method based on Mahalanobis distance metric learning is used which try to minimize distances of sample pairs in must-links and maximize the distance of sample pairs in cannot-links. To demonstrate the effectiveness of the proposed method, we performed some experiments on 12 publicly available datasets which are collected NASA repositories and compared its result by some powerful previous methods. The performance is evaluated in F-measure, G-Mean, and Matthews correlation coefficient. Generally, the proposed method has better performance as compared to the mentioned methods.