scholarly journals Measurement and Analysis of Settlement Induced by Rectangular Pipe Jacking in Silt Stratum

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Jun Tang ◽  
Shengcai Li ◽  
Yongfu Zhu
Keyword(s):  
Large Scale ◽  
Random Medium ◽  
Research Work ◽  
Ground Settlement ◽  
Stochastic Medium ◽  
Medium Theory ◽  
Measurement And Analysis ◽  
Prediction And Control ◽  
Pipe Jacking ◽  
And Control

The large-scale rectangular pipe jacking technology has attracted more and more attention in the construction of urban underground pipe galleries, especially the problem of prediction and control of the surface settlement. Taking the pipe gallery project of Chengbei Road in Suzhou as an example, the settlement values of three groups of monitoring sections under the conditions of natural settlement and synchronous grouting are monitored, and the measured settlement values are compared with Peck formula and random medium theory. The results show that the Peck formula is more accurate in predicting the natural settlement within 1.5 times the pipe jacking width, while the stochastic medium theory is more accurate in predicting the settlement beyond the width. By comparing the field test and theory, the suggestions on the prediction of ground settlement of rectangular pipe jacking of large scale are put forward. The results of this study provide a basis for subsequent related research work and engineering applications.

scholarly journals Reduced Order Modeling for Prediction and Control of Large-Scale Systems.

2014 ◽  
Author(s):  
Irina Kalashnikova ◽  
Srinivasan Arunajatesan ◽  
Matthew Franklin Barone ◽  
Bart Gustaaf van Bloemen Waanders ◽  
Jeffrey A. Fike
Keyword(s):  
Large Scale ◽  
Reduced Order Modeling ◽  
Large Scale Systems ◽  
Reduced Order ◽  
Prediction And Control ◽  
And Control

Collaboration, Power, Participation and Control on a Large Scale Research Team: Multiple Perspectives from the Oxford House Research Project

2001 ◽  
Author(s):  
Bradley Olson ◽  
Leonard Jason ◽  
Joseph R. Ferrari ◽  
Leon Venable ◽  
Bertel F. Williams ◽  
...  
Keyword(s):  
Large Scale ◽  
Research Team ◽  
Multiple Perspectives ◽  
Research Project ◽  
Oxford House ◽  
And Control

Interference mitigation in point to point wireless sensor networks using LSP protocol and time division multiplexing approach

2020 ◽  
Vol 39 (4) ◽  
pp. 5449-5458
Author(s):  
A. Arokiaraj Jovith ◽  
S.V. Kasmir Raja ◽  
A. Razia Sulthana
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Control Parameter ◽  
Interference Mitigation ◽  
Wireless Sensor ◽  
Point To Point ◽  
A Minor ◽  
Two Stages ◽  
Time Division ◽  
And Control

Interference in Wireless Sensor Network (WSN) predominantly affects the performance of the WSN. Energy consumption in WSN is one of the greatest concerns in the current generation. This work presents an approach for interference measurement and interference mitigation in point to point network. The nodes are distributed in the network and interference is measured by grouping the nodes in the region of a specific diameter. Hence this approach is scalable and isextended to large scale WSN. Interference is measured in two stages. In the first stage, interference is overcome by allocating time slots to the node stations in Time Division Multiple Access (TDMA) fashion. The node area is split into larger regions and smaller regions. The time slots are allocated to smaller regions in TDMA fashion. A TDMA based time slot allocation algorithm is proposed in this paper to enable reuse of timeslots with minimal interference between smaller regions. In the second stage, the network density and control parameter is introduced to reduce interference in a minor level within smaller node regions. The algorithm issimulated and the system is tested with varying control parameter. The node-level interference and the energy dissipation at nodes are captured by varying the node density of the network. The results indicate that the proposed approach measures the interference and mitigates with minimal energy consumption at nodes and with less overhead transmission.

An insight into Case Management and Challenges in Veteran Suicide Prevention

2020 ◽  
pp. 14-25
Author(s):  
Tamara Green
Keyword(s):  
Case Management ◽  
Suicide Prevention ◽  
Suicide Risk ◽  
Digital Transformation ◽  
Prevention Science ◽  
Historical Records ◽  
Military Members ◽  
Prediction And Control ◽  
And Control ◽  
Insight Into

Much of the literature, policies, programs, and investment has been made on mental health, case management, and suicide prevention of veterans. The Australian “veteran community is facing a suicide epidemic for the reasons that are extremely complex and beyond the scope of those currently dealing with them.” (Menz, D: 2019). Only limited work has considered the digital transformation of loosely and manual-based historical records and no enablement of Artificial Intelligence (A.I) and machine learning to suicide risk prediction and control for serving military members and veterans to date. This paper presents issues and challenges in suicide prevention and management of veterans, from the standing of policymakers to stakeholders, campaigners of veteran suicide prevention, science and big data, and an opportunity for the digital transformation of case management.

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