Search results for: academic speed and accuracy

Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

Procedia PDF Downloads 286

Authors: Kolade Olawande Owoeye, George Weir

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Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.

Keywords: sentiposit, classification, extremism, terrorism

Procedia PDF Downloads 282

Authors: M. Yousefi, N. Nasirzadeh

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In this paper, dynamic comparator structure employing two methods for power consumption reduction with applications in low-power high-speed analog-to-digital converters have been presented. The proposed comparator has low consumption thanks to power reduction methods. They have the ability for offset adjustment. The comparator consumes 14.3 μW at 100 MHz which is equal to 11.8 fJ. The comparator has been designed and simulated in 180 nm CMOS. Layouts occupy 210 μm².

Keywords: efficiency, comparator, power, low

Procedia PDF Downloads 363

Authors: Ingrid R. Avanzi, Marcela dos P. G. Baltazar, Louise H. Gracioso, Luciana J. Gimenes, Bruno Karolski, Elen A. Perpetuo, Claudio Auguto Oller do Nascimento

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In this study was developed a natural process using a biological system for the uptake of Copper and possible removal of copper from wastewater by dead biomass of the strain Burkholderia cenocepacia. Dead and live biomass of Burkholderia cenocepacia was used to analyze the equilibrium and kinetics of copper biosorption by this strain in function of the pH. Living biomass exhibited the highest biosorption capacity of copper, 50 mg g−1, which was achieved within 5 hours of contact, at pH 7.0, temperature of 30°C, and agitation speed of 150 rpm. The dead biomass of Burkholderia cenocepacia may be considered an efficiently bioprocess, being fast and low-cost to production of copper and also a probably nano-adsorbent of this metal ion in wastewater in bioremediation process. In this study was developed a natural process using a biological system for the uptake of Copper and possible removal of copper from wastewater by dead biomass of the strain Burkholderia cenocepacia. Dead and live biomass of Burkholderia cenocepacia was used to analyze the equilibrium and kinetics of copper biosorption by this strain in function of the pH. Living biomass exhibited the highest biosorption capacity of copper, 50 mg g−1, which was achieved within 5 hours of contact, at pH 7.0, temperature of 30°C, and agitation speed of 150 rpm. The dead biomass of Burkholderia cenocepacia may be considered an efficiently bioprocess, being fast and low-cost to production of copper and also a probably nano-adsorbent of this metal ion in wastewater in bioremediation process.

Keywords: biosorption, dead biomass, biotechnology, copper recovery

Procedia PDF Downloads 341

Authors: S. Hutasavi, D. Chen

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The built-up area is a significant proxy to measure regional economic growth and reflects the Gross Provincial Product (GPP). However, an up-to-date and reliable database of built-up areas is not always available, especially in developing countries. The cloud-based geospatial analysis platform such as Google Earth Engine (GEE) provides an opportunity with accessibility and computational power for those countries to generate the built-up data. Therefore, this study aims to extract the built-up areas in Eastern Economic Corridor (EEC), Thailand using day and nighttime satellite imagery based on GEE facilities. The normalized indices were generated from Landsat 8 surface reflectance dataset, including Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Modified Built-up Index (MBUI). These indices were applied to identify built-up areas in EEC. The result shows that MBUI performs better than BUI and NDBI, with the highest accuracy of 0.85 and Kappa of 0.82. Moreover, the overall accuracy of classification was improved from 79% to 90%, and error of total built-up area was decreased from 29% to 0.7%, after night-time light data from the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB). The results suggest that MBUI with night-time light imagery is appropriate for built-up area extraction and be utilize for further study of socioeconomic impacts of regional development policy over the EEC region.

Keywords: built-up area extraction, google earth engine, adaptive thresholding method, rapid mapping

Procedia PDF Downloads 129

Authors: Policarpio Jr. Joves

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Physicians in most teaching hospitals are commonly promoted into managerial roles, yet their training is mostly in clinical and scientific skills but not in leadership competencies. When they shift into roles of physician leadership, the majority hold on to their primary identity of physicians. These conflicting roles affect their identity and eventually their work. The physician leaders also face additional challenges related to academics which include incorporation of new knowledge into the existing curriculum, use of technology in the delivery of teaching, the need to train medical students outside of hospital wards, etc. The study aims to explore how physician leaders in teaching hospitals of private medical schools enact their leadership roles and how they face the challenges as physician leaders. The study setting shall be teaching hospitals of three private medical schools situated in the National Capital Region, Philippines. A multiple case study design shall be adopted in this research. Physicians shall be eligible to participate in the study if they are practicing clinicians limited to the five major clinical specialty: Internal Medicine, Pediatrics, Family Medicine, Surgery, Obstetrics and Gynecology. They must be teaching in the College of Medicine prior to their appointments as physician leaders in both medical school and teaching hospital. Semi-structured face-to-face interviews shall be utilized as a means of data collection, with open-ended questions, enabling physician leaders to present narratives about their identity, role enactment, conflicts, reaction of colleagues, and the challenges encountered in their day-to-day work as physician leaders. Interviews shall be combined with observations and review of records to gain more insights into how the physician leaders are 'doing' management. Within-case analysis shall be done initially followed by a thematic analysis across the cases, referred to as cross–case analysis or cross-case synthesis.

Keywords: academic leaders, academic managers, physician leaders, physician managers

Procedia PDF Downloads 348

Authors: Juan de Ona, Esperanza Estevez, Rocío de Ona

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Urban traffic levels can be reduced by drawing travelers away from private vehicles over to using public transport. This modal change can be achieved by either introducing restrictions on private vehicles or by introducing measures which increase people’s satisfaction with public transport. For public transport users, quality of service affects customer satisfaction, which, in turn, influences the behavioral intentions towards the service. This paper intends to identify the main attributes which influence the perception private vehicle users have about the public transport services provided in five European cities: Berlin, Lisbon, London, Madrid and Rome. Ordinal logit models have been applied to an online panel survey with a sample size of 2,500 regular private vehicle users (approximately 500 inhabitants per city). To achieve a comprehensive analysis and to deal with heterogeneity in perceptions, 15 models have been developed for the entire sample and 14 user segments. The results show differences between the cities and among the segments. Madrid was taken as reference city and results indicate that the inhabitants are satisfied with public transport in Madrid and that the most important public transport service attributes for private vehicle users are frequency, speed and intermodality. Frequency is an important attribute for all the segments, while speed and intermodality are important for most of the segments. An analysis by segments has identified attributes which, although not important in most cases, are relevant for specific segments. This study also points out important differences between the five cities. Findings from this study can be used to develop policies and recommendations for persuading.

Keywords: service quality, satisfaction, public transportation, private vehicle users, car users, segmentation, ordered logit

Procedia PDF Downloads 122

Authors: Mohamed Karodia

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Accountancy as a subject is one of the sciences that for many years has been perceived as a difficult subject to study and teach. Yet, it continuously attracts scholars graduating from school and entering Higher Education Institutions as a subject of choice and career. The teaching and learning of this subject have not been easy and has evolved and progressed over the past few decades however students still find it difficult to study and this has resulted in poor student achievement. In search of solutions, this study has considered the effect and efficacy that study skills have on the performance of Accountancy students and in particular students studying Second Year Diploma in Accountancy at the University of Johannesburg. These students appear to have a lack of appropriate study skills and as a result of these impacts on their performance in the courses, they are studying. This study also focuses on strategies to enhance Second Year Diploma Accountancy students’ academic performance. A literature review was conducted to investigate what scholarly literature suggests about study skills, in general, and in particular for Accountancy to be successful. In order to determine what study skills Second Year Accountancy students are applying when they learn and why they are failing the Accountancy examinations and formal class tests, the study adopted the quantitative research method. A questionnaire addressing various aspects of study skills, studying accountancy and studying, in general, was provided to 800 students studying Second Year Diploma in Accountancy at the University of Johannesburg’s Soweto Campus. The quantitative data collected were analyzed using descriptive statistics in the form of proportions, frequencies, means, and standard deviations, t-tests to compare differences between two groups as well as correlations between variables. Based on the findings of this study, it is recommended that students are provided with courses in time management, procrastination, reading, note taking and writing, test preparation techniques as well as study attitude. Lecturers spend more time teaching students how to study in general as well as accountancy specifically preferably at the first-year level before proceeding to the second year. It is also recommended that the University implements a study skills course to assist the students with studying.

Keywords: accountancy, skills, strategies, study

Procedia PDF Downloads 135

Authors: Paul R Armstrong

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Doubled haploids (DHs) have become an important breeding tool for creating maize inbred lines, although several bottlenecks in the DH production process limit wider development, application, and adoption of the technique. DH kernels are typically sorted manually and represent about 10% of the seeds in a much larger pool where the remaining 90% are hybrid siblings. This introduces time constraints on DH production and manual sorting is often not accurate. Automated sorting based on the chemical composition of the kernel can be effective, but devices, namely NMR, have not achieved the sorting speed to be a cost-effective replacement to manual sorting. This study evaluated a single kernel near-infrared reflectance spectroscopy (skNIR) platform to accurately identify DH kernels based on oil content. The skNIR platform is a higher-throughput device, approximately 3 seeds/s, that uses spectra to predict oil content of each kernel from maize crosses intentionally developed to create larger than normal oil differences, 1.5%-2%, between DH and hybrid kernels. Spectra from the skNIR were used to construct a partial least squares regression (PLS) model for oil and for a categorical reference model of 1 (DH kernel) or 2 (hybrid kernel) and then used to sort several crosses to evaluate performance. Two approaches were used for sorting. The first used a general PLS model developed from all crosses to predict oil content and then used for sorting each induction cross, the second was the development of a specific model from a single induction cross where approximately fifty DH and one hundred hybrid kernels used. This second approach used a categorical reference value of 1 and 2, instead of oil content, for the PLS model and kernels selected for the calibration set were manually referenced based on traditional commercial methods using coloration of the tip cap and germ areas. The generalized PLS oil model statistics were R2 = 0.94 and RMSE = .93% for kernels spanning an oil content of 2.7% to 19.3%. Sorting by this model resulted in extracting 55% to 85% of haploid kernels from the four induction crosses. Using the second method of generating a model for each cross yielded model statistics ranging from R2s = 0.96 to 0.98 and RMSEs from 0.08 to 0.10. Sorting in this case resulted in 100% correct classification but required models that were cross. In summary, the first generalized model oil method could be used to sort a significant number of kernels from a kernel pool but was not close to the accuracy of developing a sorting model from a single cross. The penalty for the second method is that a PLS model would need to be developed for each individual cross. In conclusion both methods could find useful application in the sorting of DH from hybrid kernels.

Keywords: NIR, haploids, maize, sorting

Procedia PDF Downloads 307

Authors: Mohamed Ahmed Fouad

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Background: Stroke is the most leading cause to functional disability and gait problems. Objectives: The purpose of this study was to determine the effect of rhythmic auditory stimulation combined with treadmill training on selected gait kinematics in stroke patients. Methods: Thirty male stroke patients participated in this study. The patients were assigned randomly into two equal groups, (study and control). Patients in the study group received treadmill training combined with rhythmic auditory stimulation in addition to selected physical therapy program for hemiparetic patients. Patients in the control group received treadmill training in addition to the same selected physical therapy program including strengthening, stretching, weight bearing, balance exercises and gait training. Biodex gait trainer 2 TM was used to assess selected gait kinematics (step length, step cycle, walking speed, time on each foot and ambulation index) before and after six weeks training period (end of treatment) for both groups. Results: There was a statistically significant increase in walking speed, step cycle, step length, percent of the time on each foot and ambulation index in both groups post-treatment. The improvement in gait parameters post-treatment was significantly higher in the study group compared to the control. Conclusion: Rhythmic auditory stimulation combined with treadmill training is effective in improving selected gait kinematics in stroke patients when added to the selected physical therapy program.

Keywords: stroke, rhythmic auditory stimulation, treadmill training, gait kinematics

Procedia PDF Downloads 246

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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The assessment of disease levels in crop fields is an important and time-consuming task that generally relies on expert knowledge of trained individuals. Image classification in agriculture problems historically has been based on classical machine learning strategies that make use of hand-engineered features in the top of a classification algorithm. This approach tends to not produce results with high accuracy and generalization to the classes classified by the system when the nature of the elements has a significant variability. The advent of deep convolutional neural networks has revolutionized the field of machine learning, especially in computer vision tasks. These networks have great resourcefulness of learning and have been applied successfully to image classification and object detection tasks in the last years. The objective of this work was to propose a new method based on deep learning convolutional neural networks towards the task of disease level monitoring. Common RGB images of winter wheat were obtained during a growing season. Five categories of disease levels presence were produced, in collaboration with agronomists, for the algorithm classification. Disease level tasks performed by experts provided ground truth data for the disease score of the same winter wheat plots were RGB images were acquired. The system had an overall accuracy of 84% on the discrimination of the disease level classes.

Keywords: crop disease assessment, deep learning, precision agriculture, residual neural networks

Procedia PDF Downloads 340

Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

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Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

Procedia PDF Downloads 462

Authors: M. R. Kamandar, J. Massah

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The information of the impact cutting behavior of plants stalk plays an important role in the design and fabrication of plants cutting equipment. It is difficult to investigate a theoretical method for defining cutting properties of plants stalks because the cutting process is complex. Thus, it is necessary to set up an experimental approach to determine cutting parameters for a single stalk. To measure the shear force, shear energy and shear strength of plant stalk, a special impact cutting tester was fabricated. It was similar to an Izod impact cutting tester for metals but a cutting blade and data acquisition system were attached to the end of pendulum's arm. The apparatus was included four strain gages and a digital indicator to show the real-time cutting force of plant stalk. To measure the shear force and also testing the apparatus, two plants’ stalks, like buxus and privet, were selected. The samples (buxus and privet stalks) were cut under impact cutting process at four loading rates 1, 2, 3 and 4 m.s^-1 and three internodes fifth, tenth and fifteenth by the apparatus. At buxus cutting analysis: the minimum value of cutting energy was obtained at fifth internode and loading rate 4 m.s^-1 and the maximum value of shear energy was obtained at fifteenth internode and loading rate 1 m.s^-1. At privet cutting analysis: the minimum value of shear consumption energy was obtained at fifth internode and loading rate: 4 m.s^-1 and the maximum value of shear energy was obtained at fifteenth internode and loading rate: 1 m.s^-1. The statistical analysis at both plants showed that the increase of impact cutting speed would decrease the shear consumption energy and shear strength. In two scenarios, the results showed that with increase the cutting speed, shear force would decrease.

Keywords: Buxus, Privet, impact cutting, shear energy

Procedia PDF Downloads 130

Authors: Calvin Stephen, Biswajit Basu, Aonghus McNabola

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Market liberalization in the power sector has led to the emergence of micro-hydropower schemes that are dependent on the use of pumps-as-turbines in applications that were not suitable as potential hydropower sites in earlier years. These applications include energy recovery in water supply networks, sewage systems, irrigation systems, alcohol breweries, underground mining and desalination plants. As a result, there has been an accelerated adoption of pumpsas-turbine technology due to the economic advantages it presents in comparison to the conventional turbines in the micro-hydropower space. The performance of this machines under cavitation conditions, however, is not well understood as there is a deficiency of knowledge in literature focused on their turbine mode of operation. In hydraulic machines, cavitation is a common occurrence which needs to be understood to safeguard them and prolong their operation life. The overall purpose of this study is to investigate the effects of cavitation on the performance of a pumps-as-turbine system over its entire operating range. At various operating speeds, the cavitating region is identified experimentally while monitoring the effects this has on the power produced by the machine. Initial results indicate occurrence of cavitation at higher flow rates for lower operating speeds and at lower flow rates at higher operating speeds. This implies that for cavitation free operation, low speed pumps-as-turbine must be used for low flow rate conditions whereas for sites with higher flow rate conditions high speed turbines should be adopted. Such a complete understanding of pumps-as-turbine suction performance can aid avoid cavitation induced failures hence improved reliability of the micro-hydropower plant.

Keywords: cavitation, micro-hydropower, pumps-as-turbine, system design

Procedia PDF Downloads 126

Authors: Naohiro Nakamura

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Analysis methods to accurately estimate the behavior of buildings when earthquakes occur is very important for improving the seismic safety of such buildings. Recently, the use of damping devices has increased significantly and there is a particular need to appropriately evaluate the behavior of buildings with such devices during earthquakes in the design stage. At present, however, the accuracy of the analysis evaluations is not sufficient. One reason is that the accuracy of current analysis methods has not been appropriately verified because there is very limited data on the behavior of actual buildings during earthquakes. Many types of shaking table test of large structures are performed at the '3-Dimensional Full-Scale Earthquake Testing Facility' (nicknamed 'E-Defense') operated by the National Research Institute of Earth Science and Disaster Prevention (NIED). In this study, simulations using 3- dimensional analysis models were conducted on shaking table test of a 5-story steel-frame structure with dampers. The results of the analysis correspond favorably to the test results announced afterward by the committee. However, the suitability of the parameters and models used in the analysis and the influence they had on the responses remain unclear. Hence, we conducted additional analysis and studies on these models and parameters. In this paper, outlines of the test are shown and the utilized analysis model is explained. Next, the analysis results are compared with the test results. Then, the additional analyses, concerning with the hysteresis curve of the dampers and the beam-end stiffness of the frame, are investigated.

Keywords: three-dimensional analysis, E-defense, full-scale experimen, vibration control damper

Procedia PDF Downloads 198

Authors: Amine M. Benmehaia, Amine Oulmane

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The supply response of agricultural commodities to changes in price incentives is an important issue for the success of any policy reform in the agricultural sector. This study aims to quantify the responsiveness of producers of some livestock commodities to price incentives in Algerian context. Time series analysis is used on annual data for a period of 52 years (1966-2018). Both co-integration and vector error correction model (VECM) are used through the Nerlove model of partial adjustment. The study attempts to determine the long-run and short-run relationships along with the magnitudes of disequilibria in the selected commodities. Results show that the short-run price elasticities are low in cow and sheep meat sectors (8.7 and 8% respectively), while their respective long-run elasticities are 16.5 and 10.5, whereas eggs and milk have very high short-run price elasticities (82 and 90% respectively) with long-run elasticities of 40 and 46 respectively. The error correction coefficient, reflecting the speed of adjustment towards the long-run equilibrium, is statistically significant and have the expected negative sign. Its estimates are 12.7 for cow meat, 33.5 for sheep meat, 46.7 for eggs and 8.4 for milk. It seems that cow meat and milk producers have a weak feedback of about 12.7% and 8.4% respectively of the previous year's disequilibrium from the long-run price elasticity, whereas sheep meat and eggs producers adjust to correct long run disequilibrium with a high speed of adjustment (33.5% and 46.7 % respectively). The implication of this is that much more in-depth research is needed to identify those factors that affect agricultural supply and to describe the effect of factors that shift supply in response to price incentives. This could provide valuable information for government in the use of appropriate policy measures.

Keywords: Algeria, cointegration, livestock, supply response, vector error correction model

Procedia PDF Downloads 145

Authors: R. N. Karthik Babu, R. Sarvesh, A. Rajendra Prasad, G. Swaminathan

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M42 is a molybdenum-series high-speed alloy steel widely used because of its better hot-hardness and wear resistance. These steels are conventionally heat treated in a salt bath furnace with up to three stages of preheating with predetermined soaking and holding periods. Such methods often involve long periods of processing with a large amount of energy consumed. In this study, the M42 steel samples were heat-treated by rapidly heating the specimens to the austenising temperature of 1260 °C and cooled conventionally by quenching in a neutral salt bath at a temperature of 550 °C with the aid of a hybrid microwave furnace. As metals reflect microwaves, they cannot directly be heated up when placed in a microwave furnace. The technology used herein requires the specimens to be placed in a crucible lined with SiC which is a good absorber of microwaves and the SiC lining heats the metal through radiation which facilitates the volumetric heating of the metal. A sample of similar dimensions was heat treated conventionally and cooled in the same manner. Conventional tempering process was then carried out on both these samples and analysed for various parameters such as micro-hardness, processing time, etc. Microstructure analysis and scanning electron microscopy was also carried out. The objective of the study being that similar or better properties, with substantial time and energy saving and cost cutting are achievable by rapid heat treatment through hybrid microwave furnaces. It is observed that the heat treatment is done with substantial time and energy savings, and also with minute improvement in mechanical properties of the tool steel heat treated.

Keywords: rapid heating, heat treatment, metal processing, microwave heating

Procedia PDF Downloads 288

Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

Procedia PDF Downloads 155

Authors: Areti Angeliki Veroniki, Sofia Tsokani, Evangelos Paraskevaidis, Dimitris Mavridis

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The plethora of diagnostic test accuracy (DTA) studies has led to the increased use of systematic reviews and meta-analysis of DTA studies. Clinicians and healthcare professionals often consult DTA meta-analyses to make informed decisions regarding the optimum test to choose and use for a given setting. For example, the human papilloma virus (HPV) DNA, mRNA, and cytology can be used for the cervical intraepithelial neoplasia grade 2+ (CIN2+) diagnosis. But which test is the most accurate? Studies directly comparing test accuracy are not always available, and comparisons between multiple tests create a network of DTA studies that can be synthesized through a network meta-analysis of diagnostic tests (DTA-NMA). The aim is to summarize the DTA-NMA methods for at least three index tests presented in the methodological literature. We illustrate the application of the methods using a real data set for the comparative accuracy of HPV DNA, HPV mRNA, and cytology tests for cervical cancer. A search was conducted in PubMed, Web of Science, and Scopus from inception until the end of July 2019 to identify full-text research articles that describe a DTA-NMA method for three or more index tests. Since the joint classification of the results from one index against the results of another index test amongst those with the target condition and amongst those without the target condition are rarely reported in DTA studies, only methods requiring the 2x2 tables of the results of each index test against the reference standard were included. Studies of any design published in English were eligible for inclusion. Relevant unpublished material was also included. Ten relevant studies were finally included to evaluate their methodology. DTA-NMA methods that have been presented in the literature together with their advantages and disadvantages are described. In addition, using 37 studies for cervical cancer obtained from a published Cochrane review as a case study, an application of the identified DTA-NMA methods to determine the most promising test (in terms of sensitivity and specificity) for use as the best screening test to detect CIN2+ is presented. As a conclusion, different approaches for the comparative DTA meta-analysis of multiple tests may conclude to different results and hence may influence decision-making. Acknowledgment: This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Extension of Network Meta-Analysis for the Comparison of Diagnostic Tests ” (MIS 5047640).

Keywords: colposcopy, diagnostic test, HPV, network meta-analysis

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Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: Amirhossein Lotfi, Huaizhong Li, Dzung Viet Dao

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Interest in natural fiber-reinforced composites (NFRC) is progressively growing both in terms of academia research and industrial applications thanks to their abundant advantages such as low cost, biodegradability, eco-friendly nature and relatively good mechanical properties. However, their widespread use is still presumed as challenging because of the specificity of their non-homogeneous structure, limited knowledge on their machinability characteristics and parameter settings, to avoid defects associated with the machining process. The present work is aimed to investigate the effect of the cutting tool geometry and material on the drilling-induced delamination, thrust force and hole quality produced when drilling a fully biodegradable flax/poly (lactic acid) composite laminate. Three drills with different geometries and material were used at different drilling conditions to evaluate the machinability of the fabricated composites. The experimental results indicated that the choice of cutting tool, in terms of material and geometry, has a noticeable influence on the cutting thrust force and subsequently drilling-induced damages. The lower value of thrust force and better hole quality was observed using high-speed steel (HSS) drill, whereas Carbide drill (with point angle of 130^o) resulted in the highest value of thrust force. Carbide drill presented higher wear resistance and stability in variation of thrust force with a number of holes drilled, while HSS drill showed the lower value of thrust force during the drilling process. Finally, within the selected cutting range, the delamination damage increased noticeably with feed rate and moderately with spindle speed.

Keywords: natural fiber reinforced composites, delamination, thrust force, machinability

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Authors: Mauricio E. Cruz, Ilse Cervantes, Manuel J. Fabela

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The evaluation of the maneuverability of road vehicles is generally carried out through the use of specialized computer programs due to the advantages they offer compared to the experimental method. These programs are based on purely geometric considerations of the characteristics of the vehicles, such as main dimensions, the location of the axles, and points of articulation, without considering parameters such as weight distribution and magnitude, tire properties, etc. In this paper, we address the problem of maneuverability in a semi-trailer truck to navigate urban streets, maneuvering yards, and parking lots, using the Ackerman principle to propose a kinematic model that, through geometric considerations, it is possible to determine the space necessary to maneuver safely. The model was experimentally validated by conducting maneuverability tests with an articulated vehicle. The measurements were made through a GPS that allows us to know the position, trajectory, and speed of the vehicle, an inertial motion unit (IMU) that allows measuring the accelerations and angular speeds in the semi-trailer, and an instrumented steering wheel that allows measuring the angle of rotation of the flywheel, the angular velocity and the torque applied to the flywheel. To obtain the steering angle of the tires, a parameterization of the complete travel of the steering wheel and its equivalent in the tires was carried out. For the tests, 3 different angles were selected, and 3 turns were made for each angle in both directions of rotation (left and right turn). The results showed that the proposed kinematic model achieved 95% accuracy for speeds below 5 km / h. The experiments revealed that that tighter maneuvers increased significantly the space required and that the vehicle maneuverability was limited by the size of the semi-trailer. The maneuverability was also tested as a function of the vehicle load and 3 different load levels we used: light, medium, and heavy. It was found that the internal turning radii also increased with the load, probably due to the changes in the tires' adhesion to the pavement since heavier loads had larger contact wheel-road surfaces. The load was found as an important factor affecting the precision of the model (up to 30%), and therefore I should be considered. The model obtained is expected to be used to improve maneuverability through a robust control system.

Keywords: articuled vehicle, experimental validation, kinematic model, maneuverability, semi-trailer truck

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Authors: Nuray Baltaci, Kursat Cagiltay

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University rankings which can be seen as nouveau topic are at the center of focus and followed closely by different parties. Students are interested in university rankings in order to make informed decisions about the selection of their candidate future universities. University administrators and academicians can utilize them to see and evaluate their universities’ relative performance compared to other institutions in terms of including but not limited to academic, economic, and international outlook issues. Local institutions may use those ranking systems, as TUBITAK (The Scientific and Technological Research Council of Turkey) and YOK (Council of Higher Education) do in Turkey, to support students and give scholarships when they want to apply for undergraduate and graduate studies abroad. When it is considered that the ranking systems are concerned by this many different parties, the importance of having clear, easy to use and well-designed websites by ranking institutions will be apprehended. In this paper, a usability study for the websites of four different global university ranking institutions, namely Academic Ranking of World Universities (ARWU), Times Higher Education, QS and University Ranking by Academic Performance (URAP), was conducted. User-based approach was adopted and usability tests were conducted with 10 graduate students at Middle East Technical University in Ankara, Turkey. Before performing the formal usability tests, a pilot study had been completed to reflect the necessary changes to the settings of the study. Participants’ demographics, task completion times, paths traced to complete tasks, and their satisfaction levels on each task and website were collected. According to the analyses of the collected data, those ranking websites were compared in terms of efficiency, effectiveness and satisfaction dimensions of usability as pointed in ISO 9241-11. Results showed that none of the selected ranking websites is superior to other ones in terms of overall effectiveness and efficiency of the website. However the only remarkable result was that the highest average task completion times for two of the designed tasks belong to the Times Higher Education Rankings website. Evaluation of the user satisfaction on each task and each website produced slightly different but rather similar results. When the satisfaction levels of the participants on each task are examined, it was seen that the highest scores belong to ARWU and URAP websites. The overall satisfaction levels of the participants for each website showed that the URAP website has highest score followed by ARWU website. In addition, design problems and powerful design features of those websites reported by the participants are presented in the paper. Since the study mainly tackles about the design problems of the URAP website, the focus is on this website. Participants reported 3 main design problems about the website which are unaesthetic and unprofessional design style of the website, improper map location on ranking pages, and improper listing of the field names on field ranking page.

Keywords: university ranking, user-based approach, website usability, design

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Authors: Shohreh Ghasemi

Abstract:

Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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Authors: Kirolos Gerges Yakoub Gerges

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Self-sustaining agricultural machines act in stochastic surroundings and therefore, should be capable of perceive the surroundings in real time. This notion can be done using image sensors blended with superior device learning, mainly Deep mastering. Deep convolutional neural networks excel in labeling and perceiving colour pix and since the fee of RGB-cameras is low, the hardware cost of accurate notion relies upon heavily on memory and computation power. This paper investigates the opportunity of designing lightweight convolutional neural networks for semantic segmentation (pixel clever class) with reduced hardware requirements, to allow for embedded usage in self-reliant agricultural machines. The usage of compression techniques, a lightweight convolutional neural community is designed to carry out actual-time semantic segmentation on an embedded platform. The community is skilled on two big datasets, ImageNet and Pascal Context, to apprehend as much as four hundred man or woman instructions. The 400 training are remapped into agricultural superclasses (e.g. human, animal, sky, road, area, shelterbelt and impediment) and the capacity to provide correct actual-time perception of agricultural environment is studied. The network is carried out to the case of self-sufficient grass mowing the usage of the NVIDIA Tegra X1 embedded platform. Feeding case-unique pics to the community consequences in a fully segmented map of the superclasses within the picture. As the network remains being designed and optimized, handiest a qualitative analysis of the technique is entire on the abstract submission deadline. intending this cut-off date, the finalized layout is quantitatively evaluated on 20 annotated grass mowing pictures. Light-weight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show aggressive performance on the subject of accuracy and speed. It’s miles viable to offer value-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: centrifuge pump, hydraulic energy, agricultural applications, irrigationaxial flux machines, axial flux applications, coreless machines, PM machinesautonomous agricultural machines, deep learning, safety, visual perception

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Authors: Sukhdev Singh, Baljinder Singh Bal, Amandeep Singh, Kanchan Thappa

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A nation's future almost certainly rests on the future of its children, and a nation's wellbeing can be greatly improved by providing for the right upbringing of its children. Participating in physical education and sports programmes is crucial for reaching one's full potential. As we are all aware, sports have recently become incredibly popular on a global scale. Sports are continually becoming more and more popular, and this positive trend is probably going to last for some time to come. Motor abilities will provide more accurate information on the developmental process of children. Motor fitness is a component of physical fitness that includes strength, speed, flexibility, and agility, and is related to enhanced performance and the development of motor skills. In recent years, there has been increased interest in the differences in child growth between urban and rural environments. Differences in student growth, body dimensions, body composition, and fitness levels due to urban and rural environmental disparities have come into focus in recent years. The main aim of this study is to know the differentials of motor fitness components among the school children of rural and urban areas of the Jammu region. Material and Methods: In total, sixty male subjects (mean ± SD; age, 16.475 ± 1.0124 yrs.; height, 172.8 ± 2.0153 cm; Weight, 59.75 ± 3.628 kg) from the Jammu region took part in the study. A minimum sample size of 40 subjects was obtained and was derived from Rural (N1=20) and Urban (N2=20) school-going children. Statistical Applications: The Statistical Package for the Social Sciences (SPSS) version 14.0 was used for all analyses. The differences in the mean of each group for the selected variable were tested for the significance of difference by an independent samples t-test. For testing the hypotheses, the level of significance was set at 0.05. Results: Results revealed that there were significant differences of leg explosive strength (p=0.0040*), dynamic balance (p=0.0056*), and Agility (p=0.0176*) among the School Children of the rural and urban areas of the Jammu region. However, Results further revealed that there were not significant differences of cardio respiratory endurance (p=0.8612), speed (p=0.2231), Low Back/Hamstring Flexibility (p=0.6478), and Two Hand Coordination. (p= 0.0953) among the School Children of the rural and urban areas of the Jammu region. Conclusion: The results of study showed that there is significance difference between Rural and Urban School children of the Jammu region with regards to a variable," leg explosive strength, dynamic balance, Agility” and the there is no significance difference between Rural and Urban School children of the Jammu region with regards variable “cardio-respiratory endurance, speed, Low Back/Hamstring Flexibility, Two Hand Coordination”.

Keywords: motor fitness, rural areas, school children, urban areas

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Authors: Omid Ataei Nia, Karim Salahshoor

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In this paper, a new precise and reliable sensor network methodology is introduced for unit processes and operations using the Constriction Coefficient Particle Swarm Optimization (CPSO) method. CPSO is introduced as a new search engine for optimal sensor network design purposes. Furthermore, a Square Root Unscented Kalman Filter (SRUKF) algorithm is employed as a new data reconciliation technique to enhance the stability and accuracy of the filter. The proposed design procedure incorporates precision, cost, observability, reliability together with importance-of-variables (IVs) as a novel measure in Instrumentation Criteria (IC). To the best of our knowledge, no comprehensive approach has yet been proposed in the literature to take into account the importance of variables in the sensor network design procedure. In this paper, specific weight is assigned to each sensor, measuring a process variable in the sensor network to indicate the importance of that variable over the others to cater to the ultimate sensor network application requirements. A set of distinct scenarios has been conducted to evaluate the performance of the proposed methodology in a simulated Continuous Stirred Tank Reactor (CSTR) as a highly nonlinear process plant benchmark. The obtained results reveal the efficacy of the proposed method, leading to significant improvement in accuracy with respect to other alternative sensor network design approaches and securing the definite allocation of sensors to the most important process variables in sensor network design as a novel achievement.

Keywords: constriction coefficient PSO, importance of variable, MRMSE, reliability, sensor network design, square root unscented Kalman filter

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Authors: Mohamed Zakareia Ghazy Aly Belal

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Commercial law is the set of legal rules that apply to business and regulates the trade of trade. The meaning of this is that the commercial law regulates certain relations only that arises as a result of carrying out certain businesses. which are business, as it regulates the activity of a specific sect, the sect of merchants, and the commercial law as other branches of the law has characteristics that distinguish it from other laws and various, and various sources from which its basis is derived from It is the objective or material source. the historical source, the official source and the interpretative source, and we are limited to official sources and explanatory sources. so what do you see what these sources are, and what is their degree and strength in taking it in commercial disputes. The first topic / characteristics of commercial law. Commercial law has become necessary for the world of trade and economics, which cannot be dispensed with, given the reasons that have been set as legal rules for commercial field. In fact, it is sufficient to refer to the stability and stability of the environment, and in exchange for the movement and the speed in which the commercial environment is in addition to confidence and credit. the characteristic of speed and the characteristic of trust, and credit are the ones that justify the existence of commercial law. Business is fast, while civil business is slow, stable and stability. The person concludes civil transactions in his life only a little. And before doing any civil action. he must have a period of thinking and scrutiny, and the investigation is the person who wants the husband, he must have a period of thinking and scrutiny. as if the person who wants to acquire a house to live with with his family, he must search and investigate Discuss the price before the conclusion of a purchase contract. In the commercial field, transactions take place very quickly because the time factor has an important role in concluding deals and achieving profits. This is because the merchant in contracting about a specific deal would cause a loss to the merchant due to the linkage of the commercial law with the fluctuations of the economy and the market. The merchant may also conclude more than one deal in one and short time. And that is due to the absence of commercial law from the formalities and procedures that hinder commercial transactions.

Keywords: law, commercial law, business, commercial field

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Authors: Afaf Manzoor, Abdul Hameed

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Children with hearing impairment face several challenges in accessing primary and secondary education in general and higher education in particular in Pakistan. A large number of these children are excluded from formal education system through segregated special institutions. The enrollment rate of these children at school level is very low and it continues decreasing as they move on the ladder of education. Negligible number of students with hearing impairment gets any chance to be enrolled at tertiary or higher education institutes. The segregated system of education at primary and secondary level makes it even more difficult to adjust in an inclusive classroom at a higher level not only for students with hearing impairment but for their teachers and peers as well. A false belief of teachers and parents about low academic profile of students with hearing impairment is one of the major challenges to overcome for their participation at higher education. This case study was conducted to document an innovative step taken by the Department of Special Education Needs, University of Management & Technology, Lahore Pakistan. The prime objective of this study was to assess the satisfaction level of students with hearing impairment in BS 4 Years and MA Special Education programs at Lahore campus. Structured interviews were of 40 students with hearing impairment to assess the satisfaction on service delivery (admission process, classroom pedagogy, content, assessment/results, access to other services centers i.e. library, cafeteria, hostel, co-curricular activities) and campus life. Their peers without disabilities were also interviewed to assess their acceptance level. The findings of the study revealed positive results about their educational as well as social inclusion in the university. The students also shared their fears at the time of admission and how fear eventually faded out with the passage of time due to the proper academic support system. The findings of the study will be shared in detail with the audience during the presentation.

Keywords: students with hearing impairment, higher education, inclusive education, marginalization

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Authors: Leigh Ann Wilson, Melanie Borrego

Abstract:

The purpose of institutional learning outcomes (ILOs) is to assess what students across the university know and what they do not. The issue is gathering this information in a systematic and usable way. This presentation will explain how one institution has engineered this process for both student success and maximum faculty curriculum and course design input. At Brandman University, there are three levels of learning outcomes: course, program, and institutional. Institutional Learning Outcomes (ILOs) are mapped to specific courses. Faculty course developers write the signature assignments (SAs) in alignment with the Institutional Learning Outcomes for each course. These SAs use a specific rubric that is applied consistently by every section and every instructor. Each year, the 12-member General Education Team (GET), as a part of their work, conducts the calibration and assessment of the university-wide SAs and the related rubrics for one or two of the five ILOs. GET members, who are senior faculty and administrators who represent each of the university's schools, lead the calibration meetings. Specifically, calibration is a process designed to ensure the accuracy and reliability of evaluating signature assignments by working with peer faculty to interpret rubrics and compare scoring. These calibration meetings include the full time and adjunct faculty members who teach the course to ensure consensus on the application of the rubric. Each calibration session is chaired by a GET representative as well as the course custodian/contact where the ILO signature assignment resides. The overall calibration process GET follows includes multiple steps, such as: contacting and inviting relevant faculty members to participate; organizing and hosting calibration sessions; and reviewing and discussing at least 10 samples of student work from class sections during the previous academic year, for each applicable signature assignment. Conversely, the commitment for calibration teams consist of attending two virtual meetings lasting up to three hours in duration. The first meeting focuses on interpreting the rubric, and the second meeting involves comparing scores for sample work and sharing feedback about the rubric and assignment. Next, participants are expected to follow all directions provided and participate actively, and respond to scheduling requests and other emails within 72 hours. The virtual meetings are recorded for future institutional use. Adjunct faculty are paid a small stipend after participating in both calibration meetings. Full time faculty can use this work on their annual faculty report for "internal service" credit.

Keywords: assessment, assurance of learning, course design, institutional learning outcomes, rubrics, signature assignments

Procedia PDF Downloads 283