Development of UAS-Based Construction Stormwater Inspections & Soil Loss Model

Erosion and sediment control practices on construction sites provide vital protection for the environment, minimizing the impact from sediment-laden runoff associated with construction activities. Federal, state, and local regulations require regular inspections of erosion and sediment control practices to ensure their performance is adequate. This study developed an innovative approach to stormwater inspections and design guidance by integrating tools and guidance into aerial stormwater inspection outcomes. Aerial inspections were integrated with photogrammetry, geospatial information systems, and deep learning-based object detection applications to assist in performing inspections and develop site plans, hydrologic analyses, practice detection, and soil loss modeling. Orthomosaic views were used for creating site plans and developing object detection data sources. Digital Surface Models (DSMs) were developed as datasets for evaluating the performance of the E&SC practices on site. These surface models were used for running hydrologic analyses and developing soil loss models. The use of DSMs improves stormwater inspections and design approaches since DSMs serve as datasets for evaluating design efficiency with the incorporation of aerial inspection outcomes. Trial inspections were performed at the U.S. highway 30 construction site in Tama County, Iowa. Preliminary results were prepared to demonstrate a comprehensive framework for aerial inspections in future studies. This research introduces aerial inspections as an effective method to streamline inspection procedures. This could be in the form of using fewer inspectors, providing better record keeping, having faster inspection procedures and developing efficient outcomes to evaluate the performance of practices. The study highlights the potential for this technology and developed approaches to be used in the construction industry

ALTERNATIVE VOCABULARY ASSESSMENT: USING CONCORDANCE LINE ACTIVITIES FOR TESTING LEXICAL KNOWLEDGE

The last decade has witnessed a strong impact of emerging technologies on language pedagogy due to the developments in the computer technologies. The use of authentic linguistic examples through corpora and concordance based activities is defined as data-driven learning and it exposes the students to examples of more realistic language than invented or artificial examples. Therefore, this experimental study aimed to investigate the effectiveness of the use of a concordance software and concordance lines as a pedagogical tool in vocabulary assessment at a state university in Turkey in 2015 academic year. The materials used in the study were specialized corpora, a concordance software and treatment handouts. The corpora were analyzed by means of AntConc 3.2.4w. An independent samples T-test, was conducted over the students’ GPAs, MANOVA and Standard Multiple Regression Analysis were conducted to see whether experimental and control groups were equivalent in terms of the knowledge of target vocabulary items.  Thirdly, Independent Samples T-test for the three semi-controlled paragraph writing assessment and lastly descriptive statistics of the student questionnaire were administered. By the use of computer-generated concordances in the classroom, students explored regularities of patterning in L2. Corpus-based DDL is a great alternative since it emphasizes the exploration and discovery of learning process. By integrating technology into curricular programs, the lust of digital natives for hands-on learning is satisfied as well. Key words: corpus-based approach; concordance lines; vocabulary instruction; data-driven learning

Breaking seed dormancy in oil rose (Rosa damascena Mill.) by microbial inoculation

This study was carried out to determine the effects of microbial inoculation in breaking seed dormancy and on the germination of Rosa damascena Mill. Seeds of R. damascena Mill. are the most used scented rose species in rose oil production. The most important production centers around the world are Turkey and Bulgaria. The seeds were subjected to 4 weeks of warm stratification at 25°C, followed by 150 days of cold stratification at 4 ± 1°C. Before stratification, 4 different microbial fertilizers, EM•1®, B:speel™, BioplinTM and Phosfert™ were inoculated to the seeds. In the study, the microbial inoculation treatments significantly (p < 0.01) promoted the premature germination percentage during cold stratification. During the stratification, the highest premature germination percentage was obtained from the EM•1® (69.3%). The highest germination percentage in terms of cumulative germination percentage was determined in EM•1® (100.0%), followed by Phosfert™ (84.0%) and B: seepel™ (84.0%), whereas the lowest germination percentage was found in the control treatment (69.3%). The EM•1® shortened the mean germination time by 1.7 days in comparison to the control. In conclusion, it was observed that with microbial inoculation (particularly EM•1®) to oil rose seeds and a stratification time of 150 days, dormancy was broken and germination highly improved.Key words: Rosa damascena Mill, dormancy, germination, microbial inoculation, stratification