Influence of High Impact Teaching Skills on the Teaching - Learning Process in Engineering Education

Teaching in higher education institutions is becoming more and more critical and intricate with each new generation of students entering the portals of higher education. Academic Staff College at VIT University, from time to time, has been organizing a range of training programmes and faculty empowerment workshops for its faculty, newly recruited and faculty who are already serving. During the training sessions, it has been observed that there are some specific soft skills desired to be possessed by engineering teachers, in addition to their disciplinary knowledge and subject matter expertise. These skills are: creating a positive impression, simplifying complex information, use of analogies, communicating with greater impact, responding to difficult class room situations and inspiring peers and students to embrace change. In addition, generic communication skills such as use of appropriate body language and gestures, confidence, presentation of information in a logical and methodical manner, showing empathy and concern and listening skills are also required for engineering teachers. The authors have designed and implemented a model in a training environment to impart these soft skills and training in a comprehensive manner. The training methodology adopted, analysis of the observations made, the key learnings and the challenges that lie ahead for the successful development of soft skills amongst the engineering educators and teacher trainers are presented in this paper. Keywords: engineering education, training, soft skills, communication skills, using analogies, class room situations, inspiring to embrace change

Analysis of HbA1c in Type II Diabetes Mellitus and Its Impact on Complications of Anterior Wall Stemi

BACKGROUND: Hyperglycemia on admission is a powerful predictor of adverse events in patients presenting with ST-elevation myocardial infarction (STEMI). Poor glycemic control have proven to be a predictor in diabetic patients with acute myocardial infarction and elevated glycosylated hemoglobin A1c (HbA1c) is associated with an increased risk of cardiovascular complications. HbA1c is an easy marker of long term glucose regulation as it provides a good reflection of plasma glucose concentrations over 8 – 12 weeks. High blood sugar is associated with increased mortality and complications following STEMI. OBJECTIVES: To find out the impact of HbA1c levels on the severity, complications and outcome in 200 diabetic patients with Anterior Wall ST Elevation Myocardial infarction (STEMI) admitted to the Intensive Coronary Care Unit (ICCU) of Government Coimbatore Medical College Hospital. MATERIALS AND METHODS: 200 type II diabetic patients admitted with Anterior Wall STEMI in Government coimbatore medical college hospital were cross sectionally studied between May 2018 to April 2019 and evaluated clinically and with the investigatory facilities available at this institution. Their HbA1C levels were measured at the laboratory of Government Coimbatore Medical College Hospital. The clinical features and investigation results were noted. HbA1C levels are analysed with the complications like regional wall motion abnormalities, ejection fraction, dilated cardiomyopathy, bundle branch block, reinfarct, arrhythmias, cardiac failure, cardiogenic shock also were studied and the data analysed. RESULTS: Out of 200 diabetic patients, 79% were males and 21% females. Mean age was 52.79. And duration of diabetes is 7.7 years. 31% had HbA1c less than 7.5% and 32% had HbA1C greater than 9%. 37% had HbA1c level between 7.5% and 9%. Cardiogenic shock occurs as a complication in the first 24 hrs with increase in HbA1C levels >9%. in the second day left ventricular clot occurs mainly and it occurs in patients with HbA1c > 9% and in the third day dilated cardiomyopathy occurs mostly and it occurs mainly in patients with HbA1c > 9%. CONCLUSION: Patients with high HbA1C levels were associated with more severe disease and complication rate was also higher

Multimodal spatio-temporal deep learning framework for 3D object detection in instrumented vehicles

This thesis presents the utilization of multiple modalities, such as image and lidar, to incorporate spatio-temporal information from sequence data into deep learning architectures for 3Dobject detection in instrumented vehicles. The race to autonomy in instrumented vehicles or self-driving cars has stimulated significant research in developing autonomous driver assistance systems (ADAS) technologies related explicitly to perception systems. Object detection plays a crucial role in perception systems by providing spatial information to its subsequent modules; hence, accurate detection is a significant task supporting autonomous driving. The advent of deep learning in computer vision applications and the availability of multiple sensing modalities such as 360° imaging, lidar, and radar have led to state-of-the-art 2D and 3Dobject detection architectures. Most current state-of-the-art 3D object detection frameworks consider single-frame reference. However, these methods do not utilize temporal information associated with the objects or scenes from the sequence data. Thus, the present research hypothesizes that multimodal temporal information can contribute to bridging the gap between 2D and 3D metric space by improving the accuracy of deep learning frameworks for 3D object estimations. The thesis presents understanding multimodal data representations and selecting hyper-parameters using public datasets such as KITTI and nuScenes with Frustum-ConvNet as a baseline architecture. Secondly, an attention mechanism was employed along with convolutional-LSTM to extract spatial-temporal information from sequence data to improve 3D estimations and to aid the architecture in focusing on salient lidar point cloud features. Finally, various fusion strategies are applied to fuse the modalities and temporal information into the architecture to assess its efficacy on performance and computational complexity. Overall, this thesis has established the importance and utility of multimodal systems for refined 3D object detection and proposed a complex pipeline incorporating spatial, temporal and attention mechanisms to improve specific, and general class accuracy demonstrated on key autonomous driving data sets

The incidence of symptomatic deep vein thrombosis and pulmonary embolism, following THA in patients, with postoperative chemoprophylaxis in Indian population

Background: Deep vein thrombosis (DVT) and pulmonary embolism (PE) can occur in patients after elective total hip arthroplasties (THA). Indian population appears to have low incidence of DVT and PE in comparison with Western population due to difference in ethnicity, genetic make-up, social life styles. The study intends to find the incidence of symptomatic DVT and PE in postoperative THA patients. The aim of the study was to study the incidence of symptomatic DVT and PE, in post-THA patients in Indian Population.Methods: Retrospective study conducted from 1st January, 2017 to 31st July, 2018 in BIRRD (T) Hospital. All patients who underwent THA are included, after fulfilling inclusion and exclusion criteria. Patients were evaluated for symptoms during the hospital stay and after discharge for 3 Months.Results: Total number of patients who had THA were 447 (n=447). The symptomatic DVT was found in 1 (n=1) patient. He developed DVT (n=1) during the study period, in first 48 hours postoperatively and recovered with ICU management. The same patient showed symptoms of PE but recovered fully. All patients were on a prophylactic regimen.Conclusions: Our results suggest incidence of DVT and PE are low in the Indian population with a prophylactic regimen

Proximal femur fractures - effect of preoperative mental status of patients on postoperative mobility of patients

Background: In the elderly population, proximal femur fractures are most common which can result in increase of morbidity and mortality. Pre and postoperative mobility patterns, also depends upon the Mental Status of the patient. Incidence of Mental health disorders of patient can increases with age and co morbidities. The aim of the study was to evaluate the effect and relationship of preoperative mental status, on postoperative mobility in proximal femur fracture patients. On null hypothesis; there exists no co-relation between pre-operative mental status on pre and postoperative mobility those had surgery for proximal femur fractures.Methods: This is a retrospective study, carried out during the period of 14th March, 2016 to 14th March, 2017 at BIRRD (T) Hospital. All the patients who underwent proximal femur fracture surgeries were included in the study. Patients were evaluated for Abbreviated Mental Score Test pre-operatively. Mobility patterns were before injury and after surgery evaluated in patients with proximal femur fractures. Postoperatively patients were followed up to one year.Results: 50 patients were included into the study, where 12 patients could not present to follow-up due to various reasons, thus we have complete data of 38 patients. There is significant reduction in mobility status of individuals i.e. from 6.18 (preoperative pre fracture mobility) to 5.36 (postoperative mobility). Average abbreviated mental test score is 7.55. There exists a correlation between the variables.Conclusions: Null hypothesis remains rejected. There is statistically significant relationship between the variables (pre and postoperative mobility, and abbreviated mental test score), which appears to be positive correlation

Urban footpath image dataset to assess pedestrian mobility

This paper presents an urban footpath image dataset captured through crowdsourcing using the mapillary service (mobile ap- plication) and demonstrating its use for data analytics applications by employing object detection and image segmentation. The study was motivated by the unique, individual mobility challenges that many people face in navigating public footpaths, in particular those who use mobility aids such as long cane, guide digs, crutches, wheelchairs, etc., when faced with changes in pavement surface (tactile pavements) or obstacles such as bollards and other street furniture. Existing image datasets are generally captured from an instrumented vehicle and do not provide sufficient or adequate images of the footpaths from the pedestrian perspective. A citizen science project (Crowd4Access) worked with user groups and volunteers to gather a sample image dataset resulting in a set of 39,642 images collected in a range of different conditions. Preliminary studies to detect tactile pavements and perform semantic segmentation using state-of-the-art computer vision models demonstrate the utility of this dataset to enable better understanding of urban mobility issues

Performance of Sweet Sorghum Varieties and Hybrids During Post Rainy Season (maghi) in Vertisols of Scarce Rainfall Zone in Andhra Pradesh

Sweet sorghum is a new generation bioenergy crop with considerable tolerance to drought and salinity, water logging and amenable for multiple uses. A total of 6 improves sweet sorghum varieties and 8 hybrids were evaluated during 2009–2010 at Nandyal, the centre of scare rainfall zone in the state of Andra Pradesh, India. Genotypic differences for various agronomic and sugar yield related traits was significant across all the three phenological stages i.e. flowering, dough and physiological maturity, while season has little influence on cultivar performance. This study conclude that the varieties urja and ICSV 25274 and the hybrids ICSSH 25, ICSSH 30 and ICSSH 31 are best adapted to scarce rainfall region of Andhra Pradesh for cultivation in early postrainy season (maghi)

Object polygonization in traffic scenes using small Eigenvalue analysis

Shape polygonization is an effective and convenient method to compress the storage requirements of a shape curve. Polygonal approximation offers an invariant representation of local properties even after digitization of a shape curve. In this paper, we propose to use universal threshold for polygonal approximation of any two-dimensional object boundary by exploiting the strength of small eigenvalues. We also propose to adapt the Jaccard Index as a metric to measure the effectiveness of shape polygonization. In the context of this paper, we have conducted extensive experiments on the semantically segmented images from Cityscapes dataset to polygonize the objects in the traffic scenes. Further, to corroborate the efficacy of the proposed method, experiments on the MPEG-7 shape database are conducted. Results obtained by the proposed technique are encouraging and can enable greater compression of annotation documents. This is particularly critical in the domain of instrumented vehicles where large volumes of high quality video must be exhaustively annotated without loss of accuracy and least man-hours