A structural health monitoring (SHM) system is an approach for identifying the damages caused to various kinds of structures using different system functions and providing the necessary feedback about structure’s conditions. As civil structures are the backbone of our society, to determine its daily operations is a very important issue. The performance measurement of those structures is manual whereas a computer-based monitoring system could automatically assess the structural damages and identify its exact location. Recently, wireless sensor networks (WSNs) have attracted a great deal of attention for remote sensing applications due to flexibility to measure of various activity of large scale network. Since technology is advancing day by day, the overall cost of a monitoring system is also decreased. However, the major challenging fact of a WSNs is to provide scalability for covering a large area. The main question is arisen how much capable have of a monitoring system to turn off unnecessary nodes to save energy while there are no events detected. To support the scalability required of an existing network and save the node energy for future use, we propose a topology maintenance protocol integrated with construction to address the issue of a node’s energy consumption by placing it optimally and extending the monitoring system’s lifetime. As per the authors’ acknowledgement that, a little attention has been paid to developing such a hybrid approach. To mitigate node energy consumption issue with large scale support, an Internet of Things (IoT)-based maintenance approach is the best candidate for obtaining better system lifetime responses. Therefore, the main goal of this work is to develop an ‘on-the-fly’-based topology maintenance monitoring system, which can maintain a network’s infrastructure while gathering a node’s information to switch its state regularly when the present network is no longer optimal.
| Poultry farming in South-East Asia has been rapidly progressing to meet the demands of population growth and reducing malnutrition. However, the diseases and the indiscriminate use of antibiotics in poultry threaten the industry posing public health risks. A clinico-epidemiological study was therefore conducted at the District Veterinary Hospital, Kishoreganj, Bangladesh during October-November 2019 to determine the overall disease prevalence, prescription patterns, and disease associated factors in different bird types. Data were obtained through interviews and inspections and then stored in MS Excel 2010. Data were coded, recorded, and checked for consistency before exporting to STATA-13 software for statistical analysis. ArcGIS Desktop Version 10.4.1 was used to produce a map showing geographical case distribution. In total, 552 cases (182 exotic broilers, 118 Sonali, and 252 exotic layers) were included during the study period. Visceral gout (42.4%), coccidiosis (49.2%), and colibacillosis (24.2%) were the most frequent disease in broiler, Sonali, and layers, respectively. The study also showed the single application of watch group antibiotics was the highest in broilers (88.3%), followed by Sonali (67.4%) and layers (56.5%). Doxycycline (72.7%) was the most common antibiotic for treating visceral gout in broilers, whereas ciprofloxacin was highly used in Sonali for infectious bursal disease (84.4%), and coccidiosis (58.6%) respectively, and tiamulin (6.4%) for salmonellosis in layers. This disease prevalence suggests poor farm hygiene and bio-security in the study areas. Special care should be taken around younger chickens' as visceral gout and infectious bursal disease were the most common. Antibiotics should be used more judiciously to curb the growing multidrug resistance pattern among zoonotic bacteria.
In recent years, quantum image computing draws a lot of attention due to storing and processing image data faster compared to classical computers. A number of approaches have been proposed to represent the quantum image inside a quantum computer. Representing and compressing medium and big-size images inside the quantum computer is still challenging. To address this issue, we have proposed a block-wise DCT-EFRQI (Direct Cosine Transform Efficient Flexible Representation of Quantum Image) approach to represent and compress the gray-scale image efficiently to save computational time and reduce the quantum bits (qubits) for the state preparation. In this work, we have demonstrated the capability of block-wise DCT and DWT transformation inside the quantum domain to investigate their relative performances. The Quirk simulation tool is used to design the corresponding quantum image circuit. In the proposed DCT-EFRQI approach, a total of 17 qubits are used to represent the coefficients, the connection between coefficients and state (i.e., auxiliary), and their position for representing and compressing grayscale images inside a quantum computer. Among those, 8 qubits are used to map the coefficient values and the rest are used to generate the corresponding coefficient XY-coordinate position including one auxiliary qubit. Theoretical analysis and experimental results show that the proposed DCT-EFRQI scheme provides better representation and compression compared to DCT-GQIR, DWT-GQIR, and DWT-EFRQI in terms of rate-distortion performance.
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