The innovation of building information modelling (BIM) technology provides a new means of predicting, managing and monitoring the environmental impacts of project construction and development through ...virtual prototyping/visualisation technology. This paper aims to provide thought-provoking insights into the shortcomings in the scope of the existing green BIM literature, and outlines the most important directions for future research. A total of 84 green-BIM-related papers have been reviewed and compared. Most green BIM research, centres on environmental performance at the design (44 papers) and construction stages (25 papers) of building lifecycles. Few studies concentrated on the development of BIM-based tools for managing environmental performance during the building maintenance, retrofitting (8 papers), and demolition (12 papers) stages. It is suggested that a ‘one-stop-shop’ BIM for environmental sustainability monitoring and management over a building's full life cycle should be considered in future research. Future green BIM tools should also include the three R's concept (reduce, reuse and recycle) in their sustainability analysis for both new development and retrofitting projects. The system should offer better integration with facility operation maintenance manuals for more effective low-carbon management. The use of cloud-based BIM technology to enable the management of building sustainability using ‘big data’ is also needed. Despite these potential developments, it is argued that the lack of computer tools and the complications of the BIM models are hindering the adoption of green BIM.
•Shortcomings of current green BIM studies and future research directions are listed.•Existing literature has focused heavily on design and construction stages.•Future BIM tool needs to incorporate the concept of ‘reduce, reuse and recycle’.•Integrating facility operation maintenance manuals with green BIM is required.•Extending cloud computing application and managing big data in green BIM is needed.
PurposeThis paper compares impact of Industry 4.0 / emerging information and communication Technologies (ICTs), for example, Internet of things (IOT), machine learning, artificial intelligence (AI), ...robotics and cloud computing, on 22 organisational performance indicators under nine combinations of Lean Six Sigma (LSS) and quality management systems (QMS).Design/methodology/approachSurvey of 105 Indian organisations was done about their experience of using QMS, Lean Six Sigma and emerging ICTs. Respondents included both manufacturing and service enterprises of different scales and sectors. The responses collected were compared, and statistically significant difference among them was evaluated using chi-square test.FindingsThe study confirmed statistically significant difference among 20 organisational performance indicators under different combinations of QMS, LSS and ICTs. These indicators include quality performance, delivery performance, sales turnover, inventory level and so forth. However, for two indicators, namely, absenteeism and throughput, significant difference in responses was not established.Research limitations/implicationsAll possible combinations of QMS, LSS, only LSS tools and ICTs were not studied because of either theoretical impossibility (e.g. using LSS without LSS tools) or practically rare situations (e.g. organisations using ICTs and LSS without QMS). Furthermore, the impact from different sequences of implementing QMS, LSS and ICTs can be studied.Practical implicationsUsing this study, practitioners can identify which LSS, Quality System and ICT combination results in best performance and quick success. On theoretical front, the study confirms impact of LSS and QMS on organisational performance.Originality/valueThis study evaluates organisational performance under several possible combinations of QMS, LSS, and emerging ICTs, which was so far unexplored.
In particle physics, workflow management systems are primarily used as tailored solutions in dedicated areas such as Monte Carlo production. However, physicists performing data analyses are usually ...required to steer their individual, complex workflows manually, frequently involving job submission in several stages and interaction with distributed storage systems by hand. This process is not only time-consuming and error-prone, but also leads to undocumented relations between particular workloads, rendering the steering of an analysis a serious challenge. This article presents the Luigi Analysis Workflow (Law) Python package which is based on the open-source pipelining tool Luigi, originally developed by Spotify. It establishes a generic design pattern for analyses of arbitrary scale and complexity, and shifts the focus from executing to defining the analysis logic. Law provides the building blocks to seamlessly integrate with interchangeable remote resources without, however, limiting itself to a specific choice of infrastructure. In particular, it introduces the concept of complete separation between analysis algorithms on the one hand, and run locations, storage locations, and software environments on the other hand. To cope with the sophisticated demands of end-to-end HEP analyses, Law supports job execution on WLCG infrastructure (ARC, gLite, CMS-CRAB) as well as on local computing clusters (HTCondor, Slurm, LSF), remote file access via various protocols using the Grid File Access Library (GFAL2), and an environment sandboxing mechanism with support for sub-shells and virtual environments, as well as Docker and Singularity containers. Moreover, the novel approach ultimately aims for analysis preservation out-of-the-box. Law is developed opensource and independent of any experiment or the language of executed code, and its user-base increased steadily over the past years.
lThe critical thermal issues of lithium-ion batteries are introduced.lThe design principles for batteries thermal management are presented.lThe latest advances on battery thermal management systems ...are summarized.lEmerging technologies for next-generation power batteries are discussed.
Replacing conventional gasoline-powered cars with electric vehicles (EVs) can reduce not only pollution emissions but also the dependence on fossil fuels. As the most widely used power source to propel EVs, lithium-ion batteries are highly sensitive to the operating temperatures, rendering battery thermal management indispensable to ensure their high performance, long cycle life and safe operation. In this review, we summarize the recent advances in thermal management for lithium-ion batteries. The critical thermal issues caused by high temperature, low temperature and temperature non-uniformity are firstly discussed. The design principles and the existing thermal management systems are then presented and elaborated extensively. Emerging technologies such as thermoelectric devices and internal heating methods for future battery thermal management are analyzed. We highlight that the combination of passive and active cooling/heating methods is promising to meet the stringent thermal requirements, particularly under dynamic conditions with drastic power fluctuations. Finally, the remaining challenges and perspectives of thermal management systems with high efficiency and durability are provided. This review offers comprehensive guidance on the design of advanced thermal management system for next-generation power batteries.
Purpose Documentation plays a key role in navigating the costs of construction projects. Traditional document management systems (TDMS) used in developing countries, however, hinder the achievement ...of expected cost targets. Although the electronic document management system (EDMS) has been implemented to improve documentation, the Sri Lankan construction industry has failed to effectively adapt to it. Hence, this study aims to provide strategies for the effective application of EDMS to the cost management of Sri Lankan mega construction projects. Design/methodology/approach This study uses a qualitative approach followed by 12 semi-structured expert interviews. Quantity surveying experts were selected through judgemental sampling. Manual content analysis was used to analyse the data. Findings The EDMS is more suitable for megaprojects than traditional methods of documentation in terms of functionality, neutrality, interoperability, space, reversibility and delivery speed. However, there are contradictory views about cost and security. Furthermore, five transitional challenges of EDMS have been identified under the three key themes of cost, stakeholder perception and technical difficulties. Four reasons were also identified as causing these five challenges. Seven suggestions were made to deal with these transitional challenges and three key feasible solutions for the Sri Lankan construction industry regarding the EDMS were identified. Development of Sri Lankan software with low initial cost was highlighted as the most feasible solution. Originality/value This is a novel study to investigate the applicability of EDMS to cost management mechanisms of megaprojects in Sri Lanka. The findings reveal transitional challenges and appropriate feasible solutions for EDMS adaptation. This can be applied to the cost management of megaprojects in other developing countries as well.
We survey foundational features underlying modern graph query languages. We first discuss two popular graph data models: edge-labelled graphs, where nodes are connected by directed, labelled edges, ...and property graphs, where nodes and edges can further have attributes. Next we discuss the two most fundamental graph querying functionalities: graph patterns and navigational expressions. We start with graph patterns, in which a graph-structured query is matched against the data. Thereafter, we discuss navigational expressions, in which patterns can be matched recursively against the graph to navigate paths of arbitrary length; we give an overview of what kinds of expressions have been proposed and how they can be combined with graph patterns. We also discuss several semantics under which queries using the previous features can be evaluated, what effects the selection of features and semantics has on complexity, and offer examples of such features in three modern languages that are used to query graphs: SPARQL, Cypher, and Gremlin. We conclude by discussing the importance of formalisation for graph query languages; a summary of what is known about SPARQL, Cypher, and Gremlin in terms of expressivity and complexity; and an outline of possible future directions for the area.
Unmanned aerial vehicles (UAVs) will be an integral part of the next generation wireless communication networks. Their adoption in various communication-based applications is expected to improve ...coverage and spectral efficiency, as compared to traditional ground-based solutions. However, this new degree of freedom that will be included in the network will also add new challenges. In this context, the machine-learning (ML) framework is expected to provide solutions for the various problems that have already been identified when UAVs are used for communication purposes. In this article, we provide a detailed survey of all relevant research works, in which ML techniques have been used on UAV-based communications for improving various design and functional aspects such as channel modeling, resource management, positioning, and security.
Small private online courses (SPOCs) have influenced teaching and learning in China's higher education. Learning management systems (LMSs) are important components in SPOCs. They can collect various ...data related to student behavior and support pedagogical interventions. This research used feature engineering and nearest neighbor smoothing models to predict the performance of students. Five learning behavior features were selected based on their Spearman's rank correlation coefficients with students' final grades. Through testing with data from the fall semester of 2020, the model attained the highest ROC-AUC value of 0.9390. Based on these models, the researchers conducted an engagement intervention that displayed learning behavior dashboards to students in the fall of 2021. During the intervention, the course platform updated the dashboards and notified students weekly. This intervention was further investigated through a randomized controlled trial. The experimental results suggested that the intervention could improve the students' learning behavior in terms of total study time, tutorial reading, and video viewing. In addition, this study used a modified dynamic key-value memory network (DKVMN) model to depict a student's knowledge state and to calculate the probability of solving an exercise by mining numerous exercise records. Based on the predicted probability, instructors could recommend personalized exercises for each student. In the fall of 2021, the researchers also conducted a randomized controlled trial on this intervention, demonstrating that this personalized exercise recommendation could increase students' concept mastery. Experiments revealed that the proposed models and interventions had a positive effect on students' learning of course content.
Abstract
As cloud-network integration, 5G and 6G, all-optical network, and IP-based services evolve, operational systems of operators face new challenges. The current operational systems suffer from ...inconsistent technical architecture, insufficient data sharing, lack of decoupling capability, and inadequate intelligence, leading to a high maintenance workload and poor customer experience. This paper analyzes the requirements of intelligent operation systems for operators and innovatively proposes an architecture and design scheme for intelligent operational systems based on cloud-network integration. The paper summarizes the practical experience of the new generation of cloud-network operation and maintenance systems and proposes improvements and outlooks for the development of the next generation of operational management systems.
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