scholarly journals Automated safe control of a Self-propelled Mine Counter Charge in an underwater environment

Author(s):  
P. Szymak
Helia ◽  
2001 ◽  
Vol 24 (34) ◽  
pp. 77-82 ◽  
Author(s):  
Rauf Bhutta ◽  
M.H. Rahber Bhatti ◽  
Ahmad Iftikhar

SUMMARYAll four seed diffusates used for treatment of sunflower seeds, Azadirachtaindica, Capsicum annuum, Coriandrum sativum and Eugenia jambulana, reduced the populations of seed-borne fungi: Alternaria alternata, Drechslera tetramera, Emericellopsis terricola, Fusarium moniliforme, F.semitectum, Macrophomina phaseolina and Phoma oleracea. Of four seed diffusates, those from A.indica and C.sativum controlled the fungal populations almost 100%. Seed germination was increased in seed samples of both sunflower cultivars under study, HO-1 and NK-212. The obtained results indicate that seed diffusates could substitute costly chemicals for safe control of seed-borne diseases, protecting at the same time the environment from chemical pollution.


2013 ◽  
Vol 690-693 ◽  
pp. 2621-2624
Author(s):  
Bo Chen ◽  
Ji Cai Feng

Underwater weld technology is urgently needed for the widely development of marine recourses, and weld automation technology is the inevitable choice because of the underwater environment. Because of the influence of the rigorous environment, the weld seam forming of underwater wet welding is very poor. To control the weld seam forming automatically, the model between the weld parameters and the weld seam shape must be built. This paper used arc sensor to monitor the electrical information of underwater wet welding process, and regression method was used to model the process, and the factors that influence the weld seam forming mostly were analyzed.


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4116
Author(s):  
Nighat Usman ◽  
Omar Alfandi ◽  
Saeeda Usman ◽  
Asad Masood Khattak ◽  
Muhammad Awais ◽  
...  

Nowadays, there is a growing trend in smart cities. Therefore, Terrestrial and Internet of Things (IoT) enabled Underwater Wireless Sensor Networks (TWSNs and IoT-UWSNs) are mostly used for observing and communicating via smart technologies. For the sake of collecting the desired information from the underwater environment, multiple acoustic sensors are deployed with limited resources, such as memory, battery, processing power, transmission range, etc. The replacement of resources for a particular node is not feasible due to the harsh underwater environment. Thus, the resources held by the node needs to be used efficiently to improve the lifetime of a network. In this paper, to support smart city vision, a terrestrial based “Away Cluster Head with Adaptive Clustering Habit” (ACH) 2 is examined in the specified three dimensional (3-D) region inside the water. Three different cases are considered, which are: single sink at the water surface, multiple sinks at water surface,, and sinks at both water surface and inside water. “Underwater (ACH) 2 ” (U-(ACH) 2 ) is evaluated in each case. We have used depth in our proposed U-(ACH) 2 to examine the performance of (ACH) 2 in the ocean environment. Moreover, a comparative analysis is performed with state of the art routing protocols, including: Depth-based Routing (DBR) and Energy Efficient Depth-based Routing (EEDBR) protocol. Among all of the scenarios followed by case 1 and case 3, the number of packets sent and received at sink node are maximum using DEEC-(ACH) 2 protocol. The packets drop ratio using TEEN-(ACH) 2 protocol is less when compared to other algorithms in all scenarios. Whereas, for dead nodes DEEC-(ACH) 2 , LEACH-(ACH) 2 , and SEP-(ACH) 2 protocols’ performance is different for every considered scenario. The simulation results shows that the proposed protocols outperform the existing ones.


2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Yakun Gao ◽  
Haibin Li ◽  
Shuhuan Wen

This paper proposed a new method of underwater images restoration and enhancement which was inspired by the dark channel prior in image dehazing field. Firstly, we proposed the bright channel prior of underwater environment. By estimating and rectifying the bright channel image, estimating the atmospheric light, and estimating and refining the transmittance image, eventually underwater images were restored. Secondly, in order to rectify the color distortion, the restoration images were equalized by using the deduced histogram equalization. The experiment results showed that the proposed method could enhance the quality of underwater images effectively.


2012 ◽  
Vol 8 (10) ◽  
pp. 567959 ◽  
Author(s):  
Mingzhong Yan ◽  
Daqi Zhu ◽  
Simon X. Yang

A real-time map-building system is proposed for an autonomous underwater vehicle (AUV) to build a map of an unknown underwater environment. The system, using the AUV's onboard sensor information, includes a neurodynamics model proposed for complete coverage path planning and an evidence theoretic method proposed for map building. The complete coverage of the environment guarantees that the AUV can acquire adequate environment information. The evidence theory is used to handle the noise and uncertainty of the sensor data. The AUV dynamically plans its path with obstacle avoidance through the landscape of neural activity. Concurrently, real-time sensor data are “fused” into a two-dimensional (2D) occupancy grid map of the environment using evidence inference rule based on the Dempster-Shafer theory. Simulation results show a good quality of map-building capabilities and path-planning behaviors of the AUV.


2015 ◽  
Vol 44 ◽  
pp. 243-259 ◽  
Author(s):  
Salam Hajjar ◽  
Emil Dumitrescu ◽  
Laurent Pietrac ◽  
Eric Niel

2017 ◽  
Vol 42 (3) ◽  
pp. 22-23 ◽  
Author(s):  
Mario Gleirscher ◽  
Stefan Kugele ◽  
Jonathan Sprinkle

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