Radio Frequency Toolbox for Drone Detection and Classification

The continuous development of inexpensive embedded sensors has led to the rapid proliferation of new civilian use of unmanned aerial vehicle (UAVs) or drones. It is now easier for civilians to own drones as the cost falls. As we all know drones have a variety of important applications and can also be used for negative effects too. These drones can pose a threat to the security of the population either civilian, organization or industry. There is a need for Radio Frequency Signal Classification (RF-Class) toolbox which can monitor, detect, and classify RF signals from drone communication system. The ability to accurately classify over-the-air radio signals will provide insights into spectrum utilization, device fingerprinting and protocol identification. These insights can help the Warfighter to constantly be informed about adversaries transmitters capabilities without their knowledge. The advantage of the drone detection and classification toolbox is extracting information about transmitters and providing receivers information about transmitted signals. The classification of RF signals will be done based on the modulation scheme, in this case, orthogonal frequency division multiplexing (OFDM). The signal energy and features from the signals leveraging its orthogonal frequency division multiplexing (OFDM) parameter information will be used to classify the signal. This classification will be done using the capabilities of machine learning to train and test the information collected. The content of this thesis discusses how drone detection and classification can be achieved using software defined radio. GNU radio and other hardware components will be used to implement a simulation of the module

Strategies for Adoption of Circular Economy in the Nigeria Construction Industry

The concept of circular economy has gained recognition as a way to manage waste and conserve resources sustainably, and has the potential to transform the construction industry. This is particularly relevant in the construction industry due to the significant amounts of waste generated during the construction and demolition process. This study examines the perceived importance and effectiveness of strategies related to the circular economy in the construction industry. The data were collected through a survey administered to professionals in the construction sector, capturing their perceptions of various strategies. The results reveal that most strategies received high mean ratings, indicating their perceived significance. Strategies such as waste management and recycling facilities, design for disassembly, and prioritising the use of renewable and sustainable materials were highly valued by the respondents. Additionally, statistical analyses confirmed the significance of these strategies. However, some strategies received comparatively lower ratings, suggesting the need for further attention and improvement. The findings have important implications for policymakers, industry professionals, and stakeholders, guiding decision-making and resource allocation. By prioritising and implementing the identified strategies, stakeholders can drive the adoption of circular economy principles, enhance resource efficiency, and reduce waste in construction practices. Furthermore, this study lays the foundation for future research, highlighting the importance of exploring barriers to implementation, understanding synergies and trade-offs among strategies, conducting longitudinal studies to assess long-term impact, and broadening the participant pool for a more comprehensive understanding. Overall, this study contributes to the growing body of knowledge on the circular economy in the construction industry and provides valuable insights for promoting sustainability and circularity within the sector

Antioxidant and alpha‐amylase inhibitory potentials of Cocos nucifera husk

Concoctions containing extract from Cocos nucifera husk fiber are used in Nigeria by traditional medicine practitioners for management of diabetes and its associated complications. Preliminary antidiabetic study was designed to validate the folkloric usage of the plant extract. Dried coconut husk fiber was pulverized and extracted with methanol, followed by partitioning of the methanolic extract in ethyl acetate. Phenolic content, radical scavenging activity and antioxidant capacity as well as inhibitory effects of C. nucifera methanolic (CN‐M) extract and its ethyl acetate (CN‐E) fraction on pancreatic α‐amylase and lipid peroxidation were determined. Total phenolic content and antioxidant capacity of CN‐E fraction were significantly higher than that of CN‐M extract, whereas there was no significant difference in their ability to scavenge free radicals. The CN‐E fraction also exhibited higher in vitro and in vivo inhibitory effects on α‐amylase activity and lipid peroxidation; reducing blood glucose level within 5 days following intraperitoneal administration of the C. nucifera extract to alloxan‐induced hyperglycemic rats. The phenolic‐rich extracts from coconut husk can be further explored as nutraceutical supplement in food formulation for diabetic patients