Target detection and localization using thermal camera, mmWave radar and deep learning

Reliable detection, and localization of tiny unmanned aerial vehicles (UAVs), birds, and other aerial vehicles with small cross-sections is an ongoing challenge. The detection task becomes even more challenging in harsh weather conditions such as snow, fog, and dust. RGB camera-based sensing is widely used for some tasks, especially navigation. However, the RGB camera's performance degrades in poor lighting conditions. On the other hand, mmWave radars perform very well in harsh weather conditions also. Additionally, thermal cameras perform reliably in low lighting conditions too. The combination of these two sensors makes an excellent choice for many of these applications. In this work, a model to detect and localize UAVs is made using an integrated system of a thermal camera and mmWave radar. Data collected with the integrated sensors are used to train a model for object detection using the yolov5 algorithm. The model detects and classifies objects such as humans, cars and UAVs. The images from the thermal camera are used in combination with the trained model to localize UAVs in the cameras Field of View(FOV)

Restorative Justice In Education Practices As Interventions That Support Teachers In Creating A Better Climate And Culture In Their Classrooms

Behavior management in schools is constantly changing. School-wide and classroom behavior processes are striving to find and create ways to reduce negative or unwelcomed behavior while increasing the school’s climate and culture. Schools committed to following Restorative Justice practices have reported stronger school community, reduced suspensions, and increased problem-solving skills during conflicts. This capstone uses a combination of research, assessment, testimonials, and pilot school studies to help answer the research question, What restorative justice in education interventions can be used to support teachers in creating better climate and culture in their classrooms? The research concludes Restorative Justice in Education practices is successful when used as interventions to create a better climate and culture in classrooms

Naturlig konservering av kjøtt

Bearbeidete kjøttprodukter som skinker og pølser tilsettes vanligvis det omdiskuterte stoffet natriumnitritt for konservering. Etter tre års arbeid har danske forskere nå funnet frem til forskjellige urter og bær som fungerer som et naturlig alternativ til konservering

A Computational Chemistry Study of Spin Traps.

Many defects in physiological processes are due to free radical damage: reactive oxygen species, nitric oxide, and hydroxyl radicals have been implicated in the parthenogenesis of cancer, diabetes mellitus, and rheumatoid arthritis. We herein characterize the phenyl-N-ter-butyl nitrone (PBN) type spin traps in conjunction with the most studied dimethyl-1-pyrroline-N-oxide (DMPO) type spin traps using the hydroxyl radical. In this study, theoretical calculations are carried out on the two main types of spin traps (DMPO and PBN) at the density functional theory level (DFT). The energies of the optimized structures, hyperfine calculations in gaseous and aqueous phases of the spin traps and the hydroxyl radical adduct are calculated at the B3LYP correlation and at the 6-31G (d) and 6-311G (2df, p) basis sets respectively. The dielectric effect on the performance of the spin trap is determined using the polarized continuum model. Calculations show a localization of spin densities in both cases. However, DMPO spin traps are shown to be more stable and more interactive in aqueous environment

Confinement Effects of Solvation on a Molecule Physisorbed on a Metal Particle

We describe and present results of the implementation of the surface and volume polarization for electrostatics~(SVPE) and the iso-density surface solvation models. Unlike most other implementation of the solvation models where the solute and the solvent are described with multiple numerical representation, our implementation uses a multiresolution, adaptive multiwavelet basis to describe both solute and the solvent. This requires reformulation to use integral equations throughout as well as a conscious management of numerical properties of the basis. Likewise, we investigate the effects of solvation on the static properties of a molecule physisorbed on a spherical particle, modeled as a polarizable continuum colloid with a static dielectric constant. The effective polarizability of the physisorbed molecule is enhanced by a factor of 105 in vacuo and by only 102 when solvated. The variation of the polarizability of the molecules with respect to the changes in their environment illustrates the importance of electrostatic interaction in the enhancement of the effective polarizability. Finally, we investigated the optical properties of 1.4-phenylenedinitrene and 4,4\u27-stilbenedinitrene biraradical molecules. Using our computational model, we establish the structure property relationship in biradical organic compounds. The spin splitting is shown to be inversely proportional to the separation between the two spin carrying centers and is partly driven by the Coulombic interaction. The intense peaks on the absorption spectra is the result of the mixing of transitions from the spin carrying centers with those of pi origin

AN APPRAISAL ON THE PREDICAMENT OF INTERNALLY DISPLACED PERSONS (IDPS) AND REFUGEES OF THE ANGLOPHONE ARMED CONFLICT IN CAMEROON

As a result of the outbreak of the contemporary Anglophone crisis in late 2016, an armed conflict broke out in the Anglophone North-West and South-West Regions of Cameroon between the military and Ambazonians separatists called “Amba Boys”.The unprecedented violence and egregious violations of human rights and humanitarian norms in the armed conflict led to a daunting and grave humanitarian crisis in the Anglophone regions (South West and North West Region), with tens of thousands forcefully displaced as Internally Displaced Persons (IDPs) and hundreds of thousands as refugees in neighbouring Benue and the Cross River State of Nigeria living under dire conditions. United Nations humanitarian agencies and several national and international non-governmental humanitarian agencies have been concerned and overwhelmed by the scale and gravity of the humanitarian disaster in the Anglophone regions, which they have qualified as one of the fastest-growing humanitarian crises South of the Sahara. This paper is meant to examine the predicament of Anglophone IDPs in Cameroon and Anglophone refugees in Nigeria, with emphasis on the humanitarian relief efforts undertaken by various stakeholders to alleviate their plight. The paper is essentially a case study and adopts the qualitative research approach with data obtained from secondary sources through the desk research method

Target detection and localization using thermal camera, mmWave radar and deep learning.

Reliable detection, and localization of tiny unmanned aerial vehicles (UAVs), birds, and other aerial vehicles with small cross-sections is an ongoing challenge. The detection task becomes even more challenging in harsh weather conditions such as snow, fog, and dust. RGB camera-based sensing is widely used for some tasks, especially navigation. However, the RGB camera's performance degrades in poor lighting conditions. On the other hand, mmWave radars perform very well in harsh weather conditions also. Additionally, thermal cameras perform reliably in low lighting conditions too. The combination of these two sensors makes an excellent choice for many of these applications. In this work, a model to detect and localize UAVs is made using an integrated system of a thermal camera and mmWave radar. Data collected with the integrated sensors are used to train a model for object detection using the yolov5 algorithm. The model detects and classifies objects such as humans, cars and UAVs. The images from the thermal camera are used in combination with the trained model to localize UAVs in the cameras Field of View(FOV)