Recognizing Construction Equipment Activities Using a Smartphone

The purpose of this research is to develop a smartphone based system to continually analyze construction equipment activity (e.g. a skid loader moving forward, side-ways, or raising its bucket) using a variety of different sensors and give feedback to the equipment operator or the supervisor. Such a system could detect inefficiencies in construction operations and provide valuable information to project managers. The results have demonstrated that DTW is effective at identifying typical rotation patterns. It has been less effective for slow rotations over long duration or very fast rotations with short durations. The accuracy of DTW is improved when the data is accurately segmented. Use of standard deviation to segment the data is very promising. Current work involves determining the most effective window to calculate standard deviation on, and an appropriate threshold value to use for segmentation

Recognizing Construction Equipment Activities Using a Smartphone

The purpose of this research is to develop a smartphone based system to continually analyze construction equipment activity (e.g. a skid loader moving forward, side-ways, or raising its bucket) using a variety of different sensors and give feedback to the equipment operator or the supervisor. Such a system could detect inefficiencies in construction operations and provide valuable information to project managers. The results have demonstrated that DTW is effective at identifying typical rotation patterns. It has been less effective for slow rotations over long duration or very fast rotations with short durations. The accuracy of DTW is improved when the data is accurately segmented. Use of standard deviation to segment the data is very promising. Current work involves determining the most effective window to calculate standard deviation on, and an appropriate threshold value to use for segmentation

Population identity of North Atlantic humpback whales:An ocean-wide analysis of genetic population structure

North Atlantic (NA) humpback whales (Megaptera novaeangliae) undertake seasonal migrations between high latitude feeding areas (ranging from the US coast to the Barents Sea) and low latitude winter breeding grounds in the Caribbean and the eastern NA (e.g., the Cabo Verde Archipelago). We assessed the genetic structure in the NA analyzing genetic data from ~3,000 humpback whales sampled in 14 different locations across the NA as well as off Gabon, a South Atlantic breeding ground. Each individual was sexed, genotyped at 19 microsatellite loci and the mitochondrial control region (mtCR) was sequenced. Bayesian cluster analyses and fixation indices detected two breeding populations within the NA and an additional population off Gabon. A high degree of genetic divergence was detected among the mtCR sequences between the western and eastern NA high latitude summer feeding areas indicative of long-term maternal site-fidelity to these two regions. Kinship-based analyses revealed the high latitude feeding areas in the NA as the summer destination for individuals wintering in the Cabo Verde Archipelago. There were clear signs of gene flow and introgression into the eastern NA breeding population from the Caribbean breeding population; evident by immigrants from the Caribbean breeding population and admixed individuals. The individuals on the eastern NA breeding grounds with a 100% eastern NA ancestry, all shared the same, unique mtCR haplotype; i.e., all belonging to the same single matrilineal lineage. This maternal lineage is endemic to the eastern NA, highlighting the rarity, and thus endangered, of the eastern NA breeding population. Furthermore, the study uncovered evidence of migration from the Southern to the Northern Hemisphere. Overall, our results provide a comprehensive overview of the population structure of NA humpback whales throughout the ocean basin

Population identity of North Atlantic humpback whales:An ocean-wide analysis of genetic population structure

North Atlantic (NA) humpback whales (Megaptera novaeangliae) undertake seasonal migrations between high latitude feeding areas (ranging from the US coast to the Barents Sea) and low latitude winter breeding grounds in the Caribbean and the eastern NA (e.g., the Cabo Verde Archipelago). We assessed the genetic structure in the NA analyzing genetic data from ~3,000 humpback whales sampled in 14 different locations across the NA as well as off Gabon, a South Atlantic breeding ground. Each individual was sexed, genotyped at 19 microsatellite loci and the mitochondrial control region (mtCR) was sequenced. Bayesian cluster analyses and fixation indices detected two breeding populations within the NA and an additional population off Gabon. A high degree of genetic divergence was detected among the mtCR sequences between the western and eastern NA high latitude summer feeding areas indicative of long-term maternal site-fidelity to these two regions. Kinship-based analyses revealed the high latitude feeding areas in the NA as the summer destination for individuals wintering in the Cabo Verde Archipelago. There were clear signs of gene flow and introgression into the eastern NA breeding population from the Caribbean breeding population; evident by immigrants from the Caribbean breeding population and admixed individuals. The individuals on the eastern NA breeding grounds with a 100% eastern NA ancestry, all shared the same, unique mtCR haplotype; i.e., all belonging to the same single matrilineal lineage. This maternal lineage is endemic to the eastern NA, highlighting the rarity, and thus endangered, of the eastern NA breeding population. Furthermore, the study uncovered evidence of migration from the Southern to the Northern Hemisphere. Overall, our results provide a comprehensive overview of the population structure of NA humpback whales throughout the ocean basin