Analyzing the Effects of Incentives and Model Attributes on CAD Model Creation and Alteration

Modern computer-aided design (CAD) systems have contributed significantly towards product development cycle time reduction and product quality improvement. To enhance the performance of CAD systems engineers must be able to create CAD models of conceptual designs quickly; at the same time CAD models must be easy to alter, so as to accommodate the rapid changes that the design undergoes through the lifecycle. However, there is no agreement in the way CAD models should be created to accomplish these goals. This work attempts to assess the effects of incentives on CAD model attributes during model creation and alteration; the effects of CAD model attributes on alteration are also investigated. Its aim is to derive prescriptions based on empirical evidence to improve CAD model creation and alteration efficiency. The CAD models under study are created by three sets of participants – students from a junior level CAD course, students from a senior level CAD course and experienced engineers involved in product development activities. The participants are incentivized to create and alter CAD models of designs they are provided with. The results indicate that upon removal of incentives, engineers (both students and professionals) tend to compromise on proper modeling procedures. Experts are quicker and adhere to commonly agreed correct modeling procedures during CAD model creation and alteration than students. The results also indicate that it is beneficial for alteration to construct a model with several simple features as opposed to a few complex features and that these features be fully constrained. Maintaining the traditional feature sequence improves the perception of the model. The retention and alteration of features (as opposed to deletion) is also shown to be positively correlated with model perception ratings

Neonatal resuscitation guidelines - A survey among pediatricians attending a newborn conference in North Kerala

Background: Meticulous understanding and adequate skills for prompt neonatal resuscitation by health-care personnel working in the labor, maternity, and newborn units is important. Various studies have identified areas of non-uniformity among pediatricians regarding neonatal resuscitation practices. Aim: The aim is to evaluate the knowledge among pediatricians regarding the current neonatal resuscitation guidelines and the practices they follow in their unit. Materials and Methods: A cross-sectional survey of 17 questions, based on guidelines of Neonatal Resuscitation Program (NRP) 2015 and Navjaat Shishu Suraksha Karyakram, wasconducted using a questionnaire distributed to pediatricians attending a neonatology conference. The responses were noted andanalyzed using SPSS. The relation of knowledge score with demographic profile and status of training was assessed. Results: The response rate was 66%. Majority (52%) of the participants were working in private hospitals. Neonatal intensive care unit with mechanical ventilation facilities was available for 60% of respondents. Nearly 40% were trained in neonatal resuscitation. About 85% reported correct knowledge regarding effective chest compressions. Nearly 50% reported the use of room air for bag and maskventilation during resuscitation in babies more than or equal to 35 weeks. Tracheal suction was practiced by 54% in meconiumstained liquor, and 55% practiced delayed cord clamping for 30-60 s. Nearly 62% did not have oxygen blender in the resuscitation corner, whereas 33% had cardiac monitor. No significant association was found between the place of work and knowledge score (using Chi-square test for association, p=0.280). Designation of the delegate did not have a significant association with knowledge score (p=0.300). Knowledge score of delegates from teaching hospitals was not superior to those from the non-teaching hospitals.No significant association was found between knowledge score and training (p=0.999). Conclusions: Knowledge about neonatal resuscitative practices in pediatricians as well as infrastructural facilities needs to be improved with regular NRP training.&nbsp

A survey on 3D CAD model quality assurance and testing

[EN] A new taxonomy of issues related to CAD model quality is presented, which distinguishes between explicit and procedural models. For each type of model, morphologic, syntactic, and semantic errors are characterized. The taxonomy was validated successfully when used to classify quality testing tools, which are aimed at detecting and repairing data errors that may affect the simplification, interoperability, and reusability of CAD models. The study shows that low semantic level errors that hamper simplification are reasonably covered in explicit representations, although many CAD quality testers are still unaffordable for Small and Medium Enterprises, both in terms of cost and training time. Interoperability has been reasonably solved by standards like STEP AP 203 and AP214, but model reusability is not feasible in explicit representations. Procedural representations are promising, as interactive modeling editors automatically prevent most morphologic errors derived from unsuitable modeling strategies. Interoperability problems between procedural representations are expected to decrease dramatically with STEP AP242. Higher semantic aspects of quality such as assurance of design intent, however, are hardly supported by current CAD quality testers. (C) 2016 Elsevier Ltd. All rights reserved.This work was supported by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund, through the ANNOTA project (Ref. TIN2013-46036-C3-1-R).González-Lluch, C.; Company, P.; Contero, M.; Camba, J.; Plumed, R. (2017). A survey on 3D CAD model quality assurance and testing. Computer-Aided Design. 83:64-79. https://doi.org/10.1016/j.cad.2016.10.003S64798

Extremely rare giant retroperitoneal fibrolipoma: A case report

Lipomas are common benign adipose tumors generally located at superficial locations. Mostly they measure a few centimeters in size; however, giant lipomas measuring more than 10 cm in size or weighing 1000 g are also seen. Deep seated lipomas are rather infrequent out of which retroperitoneal location of giant lipoma is rare. Fibrolipoma is one of the uncommon variant of lipomas. A giant retroperitoneal fibrolipoma is extremely rare and only five case reports of such tumors are there in the literature. We herein present one such case in a 36-years-old female

Analysis of Rainfall Data for Arni Station

Rainfall is an important part of hydrological cycle and this proves to be a vital variable in dry-land areas. In order to develop an effective management it important to understand this resource by analyzing the data recorded by Indian Meteorological Society. In this study, monthly rainfall data from 1973-2002 is collected for Arni station, Thiruvannamalai district and observed. Analysis of yearly rainfall data is done and also analysis of variation of rainfall in time and amounts is performed. These analysis will help us in interpreting the rainfall variations among different seasons in the year. The average yearly rainfall in Arni ranges from 80mm to 85mm in recent years. This results in scarcity of water which leads to problems in agricultural purposes. However during monsoon months ,which is from July to October, the average rainfall intensity ranges from 120mm- 175mm.Water resources in Arni are rare and the surface run-off is often low because of high evaporation rates. Although rainfall is a natural resource, but with the rainfall analysis data from past years can be really helpful in deduction of approximate rainfall data for the following years. Rain in excess is very rare in Arni although when it does occur it causes serious consequences such as flash flooding, human catastrophes and land degradation. From this analysis, the seasons such as Pre-Monsoon, Monsoon, Post-Monsoon and their variations are compared for three decades from1973-2002. Also the Maximum and Minimum rainfall intensity in these thirty years is also calculated.nbs