scholarly journals Rethinking of Construction Robot in the Whole Project Life Cycle

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Yvkai Zhang
Keyword(s):  
Evaluation System ◽  
Large Scale ◽  
Global Optimum ◽  
Building Performance ◽  
Future Directions ◽  
Modular Systems ◽  
Project Life Cycle ◽  
Complete Set ◽  
Optimum Solution ◽  
Project Life

Assistive technology and evaluation system are expected to effectively solve the challenges of using robots in construction activities and improve the efficiency and building performance. Still, challenges are still need to be addressed before using robots for construction on a large scale. This Studies were corresponded to the identified areas for further critical review, and the development of research and application in each area was systematically analyzed to identify future directions for both the academia and the industry. More speci?cally, this review focus on determining the requirement of technology and application profile for robots, and based on the above analysis, a complete set of construction framework for robot was proposed, which integrates robots and activities with the various modular systems and digital technology to get global optimum solution.

An Extended Model of Decision Making

2011 ◽  
pp. 1738-1747
Author(s):  
David Sammon
Keyword(s):  
Enterprise Resource Planning ◽  
Major Part ◽  
Large Scale ◽  
Resource Planning ◽  
Project Managers ◽  
Extended Model ◽  
Project Life Cycle ◽  
It Innovation ◽  
Project Life ◽  
Specific Project

Enterprise resource planning (ERP) packages can be described as the most sought after means of organisational transformation and IT innovation since the mid 1990s. Over the past decade, ERP packages have become a major part of the organisational landscape and form the cornerstone of IS architectures for an ever increasing percentage of organisations. Despite the strong push toward enterprise-wide ERP systems in the wider organisational community and the experience accumulated over 20 years of large scale integrated systems implementations, there is, in relation to ERP deployment, a lack of understanding of the specific project management required to counter the difficulties that can arise when organisations fail to ensure that all the required factors of success are present in their projects. Therefore, novel ideas to help managers and project managers to better prepare for enterprise-wide ERP projects are badly needed. This entry presents a method of practical relevance for organisational decision-makers by introducing the concept of a devil’s advocate workshop—reminiscent of Klein’s premortem sessions (Klein, 1993, 2002), but tailor-made for large scale Information Systems projects—which leverages the concept of sense-making, in introducing a preplanning “intelligence” phase in any enterprise-wide ERP project life-cycle.

scholarly journals Integrating BIM with building performance analysis in project life-cycle

2019 ◽  
Vol 106 ◽  
pp. 102861 ◽  
Author(s):  
Ruoyu Jin ◽  
Botao Zhong ◽  
Ling Ma ◽  
Arman Hashemi ◽  
Lieyun Ding
Keyword(s):  
Life Cycle ◽  
Performance Analysis ◽  
Building Performance ◽  
Project Life Cycle ◽  
Project Life

An Extended Model of Decision Making

2011 ◽  
pp. 348-355
Author(s):  
David Sammon
Keyword(s):  
Enterprise Resource Planning ◽  
Major Part ◽  
Large Scale ◽  
Resource Planning ◽  
Project Managers ◽  
Extended Model ◽  
Project Life Cycle ◽  
It Innovation ◽  
Project Life ◽  
Specific Project

Enterprise resource planning (ERP) packages can be described as the most sought after means of organisational transformation and IT innovation since the mid 1990s. Over the past decade, ERP packages have become a major part of the organisational landscape and form the cornerstone of IS architectures for an ever increasing percentage of organisations. Despite the strong push toward enterprise-wide ERP systems in the wider organisational community and the experience accumulated over 20 years of large scale integrated systems implementations, there is, in relation to ERP deployment, a lack of understanding of the specific project management required to counter the difficulties that can arise when organisations fail to ensure that all the required factors of success are present in their projects. Therefore, novel ideas to help managers and project managers to better prepare for enterprise-wide ERP projects are badly needed. This entry presents a method of practical relevance for organisational decision-makers by introducing the concept of a devil’s advocate workshop—reminiscent of Klein’s premortem sessions (Klein, 1993, 2002), but tailor-made for large scale Information Systems projects—which leverages the concept of sense-making, in introducing a preplanning “intelligence” phase in any enterprise-wide ERP project life-cycle.

Development of Multi-Stage and Hybrid Real-Coded Genetic Algorithms With Active Constraints

2002 ◽  
Author(s):  
Yasunari Mimura ◽  
Shinobu Yoshimura ◽  
Tomoyuki Hiroyasu ◽  
Mitsunori Miki
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Initial Point ◽  
Global Optimum ◽  
Feasible Region ◽  
Active Constraints ◽  
Multi Stage ◽  
Design Variables ◽  
Real Coded Genetic Algorithm ◽  
Optimum Solution

In this study, we propose multi-stage and hybrid real-coded genetic algorithm. In the proposed algorithm, there are two stages. In the first stage, Real-coded Genetic Algorithm with Active Constraints (RGAAC) is applied to find a solution that is close to the global optimum. In RGAAC, indviduals who are out of the feasible region are pulled back into feasible region. Therefore, the effective search can be carried out even in the constraints problems. In the second stage, Feasible Region Limiting Method (FRLM) is applied to obtain an optimum solution. FRLM uses the solution that is derived in the first stager as an initial point. In this study, RGAAC is applied to solve the truss structure problems. Through these problems, the effectiveness and the searching mechanism of RGAAC is discussed. The, the proposed algorithm is also applied to 2D problem. In this problem, there are about 1000 design variables. The proposed method can derive the reasonable solution. From these results, it is concluded that the proposed method is effective to solve optimzation problems of large scale structures.

scholarly journals Identifikasi Risiko Proyek Konstruksi Flyover dan Underpass di Indonesia (Kajian Literatur)

2020 ◽  
Vol 14 (2) ◽  
pp. 104-111
Author(s):  
Vederieq Yahya Enderzon ◽  
Keyword(s):  
Urban Areas ◽  
Construction Projects ◽  
Large Scale ◽  
Health And Safety ◽  
Planning Stage ◽  
Project Life Cycle ◽  
Risk Event ◽  
Project Life ◽  
Large Scale Project ◽  
Implementation Stage

Flyover and underpass is one of the options to reduce congestion especially in urban areas. These flyover and underpass construction projects have unique and very complex characteristics, so they face various types of risks that may occur during the project life cycle. Risk event may occur due to several risk agents that cause it. Since the construction of flyover and underpass is very important and is a very strategic and usually large-scale project, a study of the types of risk factors that might occur during the construction of flyovers and underpass in Indonesia is needed. This research is dedicated to answering this problem. This study uses the literature review method for data collection. Based on the results of the study it was found that the risk of the conception stage is an obstacle in land acquisition, the planning stage is a change in design, the implementation stage is Occupational Health and Safety (OHS).

Opinion Dynamics Optimization by Varying Susceptibility to Persuasion via Non-Convex Local Search

2021 ◽  
Vol 16 (2) ◽  
pp. 1-34
Author(s):  
Rediet Abebe ◽  
T.-H. HUBERT Chan ◽  
Jon Kleinberg ◽  
Zhibin Liang ◽  
David Parkes ◽  
...  
Keyword(s):  
Local Search ◽  
Objective Function ◽  
Iterative Process ◽  
Large Scale ◽  
Opinion Dynamics ◽  
Theoretical Models ◽  
Global Optimum ◽  
Local Optimum ◽  
Opinion Formation ◽  
Long Line

A long line of work in social psychology has studied variations in people’s susceptibility to persuasion—the extent to which they are willing to modify their opinions on a topic. This body of literature suggests an interesting perspective on theoretical models of opinion formation by interacting parties in a network: in addition to considering interventions that directly modify people’s intrinsic opinions, it is also natural to consider interventions that modify people’s susceptibility to persuasion. In this work, motivated by this fact, we propose an influence optimization problem. Specifically, we adopt a popular model for social opinion dynamics, where each agent has some fixed innate opinion, and a resistance that measures the importance it places on its innate opinion; agents influence one another’s opinions through an iterative process. Under certain conditions, this iterative process converges to some equilibrium opinion vector. For the unbudgeted variant of the problem, the goal is to modify the resistance of any number of agents (within some given range) such that the sum of the equilibrium opinions is minimized; for the budgeted variant, in addition the algorithm is given upfront a restriction on the number of agents whose resistance may be modified. We prove that the objective function is in general non-convex. Hence, formulating the problem as a convex program as in an early version of this work (Abebe et al., KDD’18) might have potential correctness issues. We instead analyze the structure of the objective function, and show that any local optimum is also a global optimum, which is somehow surprising as the objective function might not be convex. Furthermore, we combine the iterative process and the local search paradigm to design very efficient algorithms that can solve the unbudgeted variant of the problem optimally on large-scale graphs containing millions of nodes. Finally, we propose and evaluate experimentally a family of heuristics for the budgeted variant of the problem.

scholarly journals A Survey on Contrastive Self-Supervised Learning

Technologies ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 2
Author(s):  
Ashish Jaiswal ◽  
Ashwin Ramesh Babu ◽  
Mohammad Zaki Zadeh ◽  
Debapriya Banerjee ◽  
Fillia Makedon
Keyword(s):  
Computer Vision ◽  
Supervised Learning ◽  
Language Processing ◽  
Large Scale ◽  
Performance Comparison ◽  
Extensive Review ◽  
Future Directions ◽  
Dominant Component ◽  
Supervised Methods ◽  
The Cost

Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets. It is capable of adopting self-defined pseudolabels as supervision and use the learned representations for several downstream tasks. Specifically, contrastive learning has recently become a dominant component in self-supervised learning for computer vision, natural language processing (NLP), and other domains. It aims at embedding augmented versions of the same sample close to each other while trying to push away embeddings from different samples. This paper provides an extensive review of self-supervised methods that follow the contrastive approach. The work explains commonly used pretext tasks in a contrastive learning setup, followed by different architectures that have been proposed so far. Next, we present a performance comparison of different methods for multiple downstream tasks such as image classification, object detection, and action recognition. Finally, we conclude with the limitations of the current methods and the need for further techniques and future directions to make meaningful progress.

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