Time and Energy Savings in Leak Detection in WSN-Based Water Pipelines: A Novel Parametric Optimization-Based Approach

2019 ◽  
Vol 33 (6) ◽  
pp. 2057-2071 ◽  
Author(s):  
Muhammad Mysorewala
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Christie D. Lavallée ◽  
Saeedeh Bani Assadi ◽  
Alicia M. Korpach ◽  
James D. Ray ◽  
Jason D. Fischer ◽  
...  

Abstract Background The migration patterns of land birds can generally be divided into those species that migrate principally during the day and those that migrate during the night. Some species may show individual plasticity in the use of day or night flight, particularly when crossing large, open-water or desert barriers. However, individual plasticity in circadian patterns of migratory flights in diurnally migrating songbirds has never been investigated. Methods We used high precision GPS tracking of a diurnal, migratory swallow, the purple martin (Progne subis), to determine whether individuals were flexible in their spring migration strategies to include some night flight, particularly at barrier crossing. Results Most (91%) of individuals made large (sometimes > 1000 km), open-water crossings of the Caribbean Sea and the Gulf of Mexico that included the use of night flight. 32% of all water crossings were initiated at night, demonstrating that night flight is not only used to complete large crossings but may confer other advantages for diurnal birds. Birds were not more likely to initiate crossings with supportive winds, however crossings were more likely when they reduced travel distances. Our results are consistent with diurnal birds using night flight to help achieve time- and energy-savings through ‘short cuts’ at barrier crossings, at times and locations when foraging opportunities are not available. Conclusions Overall, our results demonstrate the use of nocturnal flight and a high degree of individual plasticity in migration strategies on a circadian scale in a species generally considered to be a diurnal migrant. Nocturnal flights at barrier crossing may provide time and energy savings where foraging opportunities are low in an otherwise diurnal strategy. Future research should target how diel foraging and refueling strategies support nocturnal flights and barrier crossing in this and other diurnal species.


Author(s):  
Lan Ren ◽  
Kunnayut Eiamsa-ard ◽  
Jianzhong Ruan ◽  
Frank Liou

At present, part remanufacturing technology is gaining more interest from the military and industries due to the benefits of cost reduction as well as time and energy savings. This paper presents the research on one main component of part remanufacturing technology, which is part repairing. Traditionally, part repairing is done in the repair department using welding processes. However, the limitations of the traditional welding process are becoming more and more noticeable when accuracy and reliability are required. Part repairing strategies have been developed utilizing a hybrid manufacturing system in which the laser-aided deposition and CNC cutting processes are integrated. Part repairing software is developed in order to facilitate the users. The system and the software elevate the repairing process to the next level, in which accuracy, reliability, and efficiency can be achieved. The concept of the repairing process is presented in this paper, and verification and experimental results are also discussed.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 188673-188687
Author(s):  
Mati-Ur-Rasool Ashraf Virk ◽  
Muhammad Faizan Mysorewala ◽  
Lahouari Cheded ◽  
Ibrahim Mohamed Ali

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1247
Author(s):  
Mingyang Liu ◽  
Jin Yang ◽  
Wei Zheng

Numerous novel improved support vector machine (SVM) methods are used in leak detection of water pipelines at present. The least square twin K-class support vector machine (LST-KSVC) is a novel simple and fast multi-classification method. However, LST-KSVC has a non-negligible drawback that it assigns the same classification weights to leak samples, including outliers that affect classification, these outliers are often situated away from the main leak samples. To overcome this shortcoming, the maximum entropy (MaxEnt) version of the LST-KSVC is proposed in this paper, called the MLT-KSVC algorithm. In this classification approach, classification weights of leak samples are calculated based on the MaxEnt model. Different sample points are assigned different weights: large weights are assigned to primary leak samples and outliers are assigned small weights, hence the outliers can be ignored in the classification process. Leak recognition experiments prove that the proposed MLT-KSVC algorithm can reduce the impact of outliers on the classification process and avoid the misclassification color block drawback in linear LST-KSVC. MLT-KSVC is more accurate compared with LST-KSVC, TwinSVC, TwinKSVC, and classic Multi-SVM.


Foods ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1846
Author(s):  
Varvara Andreou ◽  
Ioanna Thanou ◽  
Marianna Giannoglou ◽  
Maria C. Giannakourou ◽  
George Katsaros

This study concerns the implementation of osmotic dehydration (OD) as a pre-treatment of air-drying in fig halves, aiming at drying acceleration, energy savings and product quality improvement. The effect of solid/liquid mass ratio, process temperature (25–45 °C) and duration (up to 300 min) on water activity (aw) and transport phenomena during OD, was modelled. The effective diffusion coefficients, drying time and energy consumption, were also calculated during air-drying at 50–70 °C. At optimum OD conditions (90 min, 45 °C), the highest water loss and solid gain ratio were achieved, while the aw (equal to an initial value 0.986) was decreased to 0.929. Air-drying time of OD- and control samples was estimated at 12 and 21 h, at 60 °C, respectively, decreasing the required energy by up to 31.1%. Quality of dried figs was systematically monitored during storage. OD-assisted air-drying led to a product of improved quality and extended shelf-life.


2017 ◽  
Vol 14 (1) ◽  
pp. 46-55 ◽  
Author(s):  
Sepideh Yazdekhasti ◽  
Kalyan R. Piratla ◽  
Sez Atamturktur ◽  
Abdul Khan

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