derhan/semantic-scholar-manajemen-proyek huggingface dataset:
Agile Requirements Engineering: From User Stories to Software Architectures
Authors: F. Dalpiaz; S. Brinkkemper
Year: 2021

Most agile practitioners employ user stories for capturing requirements, also thanks to the embedding of this notation within development and project management tools. Among user story users, circa 70% follow a simple template: As a role, I want to action, so that benefit. User stories’ popularity among practitioners and their template-based structure make them ideal candidates for the application of natural language processing techniques. In our research, we have found that circa 50% of real-world user stories contain easily preventable linguistic defects. To mitigate this problem, we have created tool-supported methods that facilitate the creation of better user stories. This tutorial combines previous work of the RE-Lab@UU into a pipeline for working with user stories: (1) The basics of creating user stories and their use in requirements engineering; (2) How to improve user story quality with the Quality User Story Framework and the AQUSA tool; (3) How to generate conceptual models from user stories using the Visual Narrator tool and analyze them for possible ambiguity and inconsistency; and (4) How to link requirements to architectures via the RE4SA model. Our approach is demonstrated with results obtained from 20+ software companies employing user stories.
A Multi-Feature Semantic Fusion and Bipartite Graph-Based Risk Identification Approach for Project Participation
Authors: Yue Wang; Yujie Hu; Wenjing Chang; Jianjun Yu
Year: 2024

: In the complex landscape of project management, ensuring the authenticity of participant involvement is paramount to achieving fairness, enforceability, and desired outcomes. Addressing the challenges posed by the heterogeneous nature of graphs, the underutilization of rich attribute information, and the scarcity of anomaly labels, we propose a Project Participation Authenticity Risk Identification Graph Neural Network (PARI-GNN), a novel architecture leveraging graph-based anomaly detection techniques to assess authenticity risks in project participation. PARI-GNN include a novel framework for risk identification using heterogeneous graphs. This method transforms heterogeneous graphs into bipartite graphs and combines multi-feature semantic fusion techniques with bipartite graph structures, providing a robust solution for identifying inauthentic participation. We evaluate our proposed model using real-world data. The experimental outcomes affirm the superior performance of PARI-GNN in accurately discerning authenticity risks, demonstrating the efficacy and competitive advantage of the proposed framework over a variety of state-of-the-art methodologies.
Antecedents and Consequences of Sustainable Project Management: Evidence from the Construction Industry in China
Authors: Shih-Wei Wu; Yifan Yan; Jialiang Pan; Kun-Shan Wu
Year: 2023

SPM (sustainable project management) is vital to enhancing the success of projects. Despite several studies dealing with the connection between SPM and project success, this nexus is still insufficiently addressed. Steered by institutional theory and resource-based value theory, the purpose of this article is to investigate not only the link between SPM and SPS (sustainable project success), but also the mediating effect of SPP (sustainable project planning) on this connection, and the antecedent role of the institutional pressures (mimetic isomorphism pressure, MIP; normative isomorphism pressure, NIP) on SPM. To test the proposed hypotheses, this article applies PLS-SEM (partial least squares structural equation modeling) and recruited 365 project professionals who have experience in participating in SPM projects in China’s construction industry. The results confirm that both MIP and NIP significantly affect SPM, with NIP being the most significant. Moreover, the findings evidence that SPM had a significantly positive impact on SPS and SPP, and SPP had a significantly positive effect on SPS. Furthermore, the results also evidence that SPP mediates the effect of SPM on SPS. These findings provide empirical evidence for construction companies to understand SPM in the Chinese construction industry. They may also help policymakers to formulate proper policies to promote SPM to achieve sustainable development.
American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange: From Inception to First Data Release and Beyond—Lessons Learned and Member Institutions’ Perspectives
Authors: Christine M Micheel; S. Sweeney; M. LeNoue-Newton; F. André; Philippe Bédard; J. Guinney; G. Meijer; B. Rollins; C. Sawyers; N. Schultz; K. Shaw; V. Velculescu; M. Levy
Year: 2018

The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international data-sharing consortium focused on enabling advances in precision oncology through the gathering and sharing of tumor genetic sequencing data linked with clinical data. The project’s history, operational structure, lessons learned, and institutional perspectives on participation in the data-sharing consortium are reviewed. Individuals involved with the inception and execution of AACR Project GENIE from each member institution described their experiences and lessons learned. The consortium was conceived in January 2014 and publicly released its first data set in January 2017, which consisted of 18,804 samples from 18,324 patients contributed by the eight founding institutions. Commitment and contributions from many individuals at AACR and the member institutions were crucial to the consortium’s success. These individuals filled leadership, project management, informatics, data curation, contracts, ethics, and security roles. Many lessons were learned during the first 3 years of the consortium, including on how to gather, harmonize, and share data; how to make decisions and foster collaboration; and how to set the stage for continued participation and expansion of the consortium. We hope that the lessons shared here will assist new GENIE members as well as others who embark on the journey of forming a genomic data–sharing consortium.
Flexible, classic and hybrid project management methodologies: advantages and disadvantages
Authors: R. K. Nigmatullin; A. G. Dmitriev
Year: 2023

The purpose of the work. Nowadays, competition in the market is increasing, which requires organizations to ensure advanced positions for survival. As practice shows, project management method is one of the most demanded and effective management methods. This study aims to examine the efficacy of flexible project management methodologies by contrasting them with conventional methodologies and evaluating the feasibility of integrating them into a hybrid methodology.Methods and Materials: The complex, systemic and comparative approaches are the methodological basis of the study and are mainly based on methods of analysis and systematization.Results: The article describes the analysis of the most demanding flexible project management methods. Each method has its own characteristics and specific criteria for comparison. Moreover, a comparison between flexible and traditional project management approaches was carried out, and the concept of method hybridization was introduced to integrate diverse methodologies at distinct phases of the project.Conclusion: The choice of project management methodology depends on many conditions, such as the complexity of the task, the presence of an experienced team and methodology of its work, the established interaction with the customer, and many other details. Each of them shows its effectiveness under different conditions. Using a hybrid methodology that combines the advantages of different methods allows them to be applied in practice in project management.
Estimation of forest above‐ground biomass in Guangxi, China, by integrating forest age and stack learning
Authors: Ting Ju; Bo Liu; Y. Yue; H. Du; Qian Li; Xu Wang; Kelin Wang
Year: 2023

With the implementation of large‐scale ecological restoration projects, Southwest China has become one of the fastest forest growth areas in the world in terms of vegetation cover and above‐ground biomass (AGB). It is expected to be a potential area for achieving the carbon neutrality target in China. Accurate estimation of forest AGB is becoming an increasingly urgent necessity for carbon neutrality and forest management. However, due to the complex geological background, there is significant uncertainty in estimating forest AGB in the southwestern region, which generally results in underestimating carbon sinks from forest restoration. To address the issue, we propose a method by incorporating forest age information and stack learning technique to estimate forest AGB. Based on remote sensing, forest inventory and in situ forest biomass data, three fundamental methods (Multiple regression, Random forest and Support vector machine) are employed and compared to build the AGB estimation model with vegetation indices, texture feature factors and forest age. Optimal basic models are further enhanced by integration learning to improve the estimation performance and then applied to the study area Guangxi to obtain regional AGB information of different forest types. The results show that: (1) forest age plays a vital role in reducing the uncertainty of AGB estimation. By incorporating forest age information, R2 of AGB estimation is improved by 0.07–0.27 and RMSE is decreased by 16.35%–47.47% for different forest types; (2) with R2 value >0.78, random forest model outperforms support vector machine and multiple linear regression models. Compared with the single optimal model, integration model by stack learning further enhances R2 of estimation by 0.02–0.03 and decreases RMSE by 5.20%–14.89%. (3) The total forest AGB in Guangxi is 988.17 Tg and the average forest AGB level is 73.30 t/ha. Natural broadleaf forest has the highest AGB level (86.75 t/ha), followed by natural coniferous forest (81.19 t/ha), planted coniferous forest (63.23 t/ha) and planted eucalyptus forest (49.71 t/ha). AGB level in karst areas is lower than that in non‐karst areas due to soil and water constraints. The majority of plantation forests in Guangxi is in the early and middle stages of forest succession, with the rapid growth of forest AGB, and has hence significant potential as carbon sinks. This study indicates that stack learning and incorporation of forest age could significantly decrease the uncertainty of forest AGB estimation. Our study helps to provide more accurate AGB information for karst ecological project management and regional carbon neutrality assessment.
Integrative project and asset management strategies to maximize gas production: A review of best practices
Authors: Emmanuella Onyinye Nwulu; Tari Yvonne Elete; Ovie Vincent Erhueh; Oluwaseyi Ayotunde Akano; Adeoye Taofik Aderamo
Year: 2022

The growing demand for natural gas as a cleaner energy source has driven the need for optimized production strategies in the oil and gas sector. This paper reviews integrative project and asset management strategies designed to maximize gas production, drawing from best practices in the industry. The review highlights the critical role of strategic alignment between project management and asset optimization in achieving sustainable and efficient gas production. Key areas explored include the integration of predictive maintenance, digital twin technologies, and data analytics to improve decision-making and operational performance. Emphasizing a life-cycle approach to asset management, the paper discusses how proactive asset monitoring, risk management, and performance tracking contribute to long-term production efficiency. The importance of stakeholder collaboration and interdisciplinary coordination across technical, operational, and financial teams is also underscored, as it facilitates the seamless execution of projects from exploration to production. This review further examines case studies where digital tools and advanced project management methodologies have been successfully implemented to reduce downtime, optimize resource allocation, and enhance production capacity. Techniques such as Lean project management and Six Sigma are highlighted as effective in streamlining operations and reducing inefficiencies. The study concludes by discussing the future trends in gas production management, including the adoption of artificial intelligence (AI) and machine learning (ML) for predictive asset optimization and the integration of real-time monitoring systems for enhanced production forecasting. In summary, integrating advanced project and asset management strategies, with a focus on technology and collaboration, can significantly enhance gas production efficiency. By adopting these best practices, gas producers can meet rising global energy demands while maintaining operational sustainability and cost-effectiveness.
A living lab for professional skills development in Software Engineering Management at U.Porto
Authors: G. Gonçalves; R. Meneses; J. Faria; R. M. Vidal
Year: 2020

Over the past decades, software engineering has reached a level of maturity which entails great challenges in its education. Universities must prepare students to real-life challenges by offering courses to aid students in developing several vital skills which go beyond hard skills (e.g., communication skills and self-management). At the Faculty of Engineering of the University of Porto, a pioneering course, dubbed Project Management Laboratory, offers the proper environment for students to develop such skills by inviting industry to be closely involved in the education of the students. This course integrates practice and theory in a setting close to what the students will face when they move into industry. This paper reports on the experience, results, and benefits of this innovative course.
Towards minimizing space-time conflicts between site activities using simple generic algorithm - the best execution strategy
Authors: Z. Mallasi
Year: 2009

Construction planners on every project are faced with a unique task of spatially organizing site activities with effective space utilization. This is a crucial planning exercise that if effectively rehearsed then can attribute to increased workers productivity, minimized construction accidents, improved delivery of project on time. One of the major issues in traditional project management tools is that they do not convey workspace occupied as the project progresses as well as space availability and needs.This paper presents a research investigation based on using generic workspace strategies which extends related research and analytical tools dealing with project space-time planning. In particular, a 4D (3D + time) visualization system has been developed which embeds simple Genetic Algorithm (GA) to search for the best execution strategy to optimize workspace conflicts between activities. The optimization approach specifies the main structure of a simple GA model to derive solutions near optimal (i.e. best execution strategies). The main three semantics of a construction activity execution used in this work mainly: (1) execution of work direction, (2) the activity work rate distribution type, and (3) quantity of work per week. It should be mentioned that these semantics were encoded within the genetic string structure for the chromosomes to achieve the effect of altering the execution pattern in search of minimum workspace usage. Among the other generic space strategies included is the product Assembly Sequence Constraints (ASC) which governs the construction logic dependencies.The work presented here concludes that the definition of an activitys execution pattern semantics is an important element in next generation 4D visualization tools. It plays a major part in facilitating realistic visualization and is an important feature to simulate interaction between site activities shaping the site in different ways. Further benefit of such approach is the ability to rehearse different what if scenarios for coordinating site activities and to allow planners to better communicate project schedules. The difficulties and the opportunities that are addressed by the development of a visual planning 4D tool in this research are recognised. The paper presents an experimental execution patterns simulation run with results, and shows how they are used to minimize space-time conflicts. Finally, the paper highlights the added value from using the VRML approach, as there is greater demand for integrating CAD with VR technology
Nurse managers' challenges in project management.
Authors: Marjo Suhonen; Leena Paasivaara
Year: 2011

AIM
To analyse the challenges that nurse managers meet in project management.


BACKGROUND
Project management done by nurse managers has a significant role in the success of projects conducted in work units.


METHODS
The data were collected by open interviews (n = 14). The participants were nurse managers, nurses and public health nurses. Data analysis was carried out using qualitative content analysis.


RESULTS
The three main challenges nurse managers faced in project management in health-care work units were: (1) apathetic organization and management, (2) paralysed work community and (3) cooperation between individuals being discouraged.


CONCLUSIONS
Nurse managers' challenges in project management can be viewed from the perspective of the following paradoxes: (1) keeping up projects-ensuring patient care, (2) enthusiastic management-effective management of daily work and (3) supporting the work of a multiprofessional team-leadership of individual employees.


IMPLICATIONS FOR NURSING MANAGEMENT
It is important for nurse managers to learn to relate these paradoxes to one another in a positive way. Further research is needed, focusing on nurse managers' ability to promote workplace spirituality, nurse managers' emotional intelligence and their enthusiasm in small projects.
Legal Analysis of Default in Construction Projects Involving Individuals: A Case Study of Guesthouse Construction.
Authors: Didik Prasetyo; R. Putranto; Agnes Harvelian
Year: 2024

In the realm of construction, contracts form the fundamental basis of projects involving multiple parties with clear responsibilities and obligations. This research explores a case of breach of contract (wanprestasi) in a construction project involving an individual, which not only caused financial and reputational harm to other parties involved but also compromised the integrity and quality of the project. The legal framework governing construction services and contracts, including Article 1 paragraph (3) of Law Number 2 of 2017 concerning Construction Services, sets the ground for understanding obligations and rights under Indonesian civil law. 
  
The methodology employed in this study is a qualitative analysis, focusing on the application of legal principles, relevant regulations, and real-life practices related to cases of breach of contract using literature reviews and case document analysis. This approach has allowed for an in-depth understanding of the legal norms and the actual enforcement of laws in similar situations. 
  
The findings reveal that the specific breaches included not meeting agreed specifications and delays in project completion, which are deemed as wanprestasi under Article 1243 of the Indonesian Civil Code. These violations stem from poor project management, opaque fund usage, and unilateral decisions by the executing party, highlighting the need for stringent legal enforcement and protection for the aggrieved parties. 
  
Keywords: Construction Law, Breach of Contract, Legal Enforcement, Project Management, Civil Law
Sustainable project management for humanitarian disasters and refugee crisis management: Bibliometric analysis
Authors: Shahbaz Ahmad Saadi; Uygur Gokce; A. Dunay
Year: 2023

This study conducted a bibliometric analysis of the literature on sustainable project management in crisis management, particularly in humanitarian disasters, using the Scopus database. After filtration and abstract screening of 115,737 (1980–2022), only 544 related articles were identified and analyzed graphically using VoSviewer (visualization of similarities) to create maps of co-occurrence, co-authorship, and citations. The analysis provided an understanding of the most frequent keywords, key authors, journals, affiliations, and contributing countries in the literature on project management and crisis management. The trends observed in this study’s results highlight the significance of sustainable project management within the realm of disaster management. This study examines the bibliometric parameters and indices as measures of research success and their potential implications for grant funding sources, universities, governments, and organizations. The findings suggest that bibliometric parameters and indices could be increasingly utilized by grant funding sources as metrics to evaluate research success. Universities and research institutions may consider incorporating benchmarking standards based on bibliometric data into promotion and tenure guidelines to determine academic achievement. Furthermore, governments and organizations may also benefit from establishing benchmark standards to enhance sustainability in disaster management projects. Although Scopus has limitations that prefer certain fields, this study provides avenues for future research, including using other databases and conducting a comparative study between Scopus and WoS (Web of Science) to determine their strengths and weaknesses.