Expectations of Student Engaged in Tertiary Education on Engineering Courses from Their Teachers of Choice

Although several learning theories ranging from behaviourism to cognitive to humanistic education have been proposed to choose the appropriate effective teaching models, none can be applied across the board to all learners in all situations; nevertheless some commonalities emerge. A combination of pedagogical and andragogical, “middle of the road” approaches meet the need of a larger segment of the audience. Our experiences and many surveys confirmed that the theory of behaviourism may be well suitable to first and second year students and the cognitive approach may be well fit to third and fourth year students. Only for supervising final year project work, based on the theory of teachers and students working together, humanistic may be adoptable. The survey was conducted among the students enrolled for engineering courses in Curtin University, Sarawak to assess the grade of importance on twelve basic aspects of knowledge, communication skill and planning potentials expected from the teachers.This paper describes the analysis of the action survey results and summaries of the recommendations for effective teaching. The survey concludes that each well defined lecture arranged in right sequences should be orally presented in a simple constructive language with the consistent flow speed optimum suitable to majority of the audience for better learning outcomes. Language proficiency and fluency are not the barriers for successful teaching to multicultural classroom in tertiary education. It concludes that “Teachers of student choice” are not born but they are trained by acquiring the required relevant knowledge and sincere practice of delivering the lectures in an optimum suitable way to the audience for effective learning

Modelling of Multicomponent Fuel Sprays

The use of fuel blends (conventional fuels blended with renewable ones) has gained importance in the automotive industry as an option to reduce emissions and dependence on fossil fuels. In order to make the fuel blends commercially viable, computational fluid dynamics (CFD) is used to complement the experiments (done\ua0on engines or spray chambers) by providing fundamental insight into spray formation. The work presented in this thesis is focused on modelling and CFD simulation of\ua0multicomponent fuel sprays.The spray model used in this work is the stochastic blob and bubble model (VSB2) which is a discrete multicomponent fuel spray model. One of the strengths of the\ua0model is that it uses thermodynamic equilibrium to calculate heat and mass transfer to ensure that there is no over- or under-estimation of the temperature or evaporated mass. The VSB2 also uses minimal tuning parameters for modelling. The present work extended the spray model to handle multicomponent fuels. One of the main\ua0challenges in modelling multicomponent fuels is to handle differential evaporation correctly. To address this, a non-linear equation solver was implemented . The solver\ua0interfaces with the OpenFOAM code containing the spray model. One of the main benefits of the newly implemented solver is that it can be scaled to handle a large\ua0number of fuel components with minimal effort. The multicomponent fuel spray model was validated with experimental data for one, two and three fuel components respectively in three separate cases and showedreasonably good agreement. Apart from this, the model was used to study the influence of non-ideal vapor liquid equilibrium (VLE) and showed that it is important to consider non-ideal VLE for fuels with polar molecules. The model was also used to study the influence of resolving the injector orifice and the counterbore of a gasoline direct engine (GDI) injector in two separate studies. The results of all the studies\ua0can be found in the appended manuscripts.Having thus established the multicomponent fuel spray model in through this work, in future, it can be combined with detailed chemical mechanisms and combustion\ua0models to extend the studies to investigate combustion of multicomponent fuels

Lactate dehydrogenase as surrogate marker of preeclampsia and eclampsia

Background: Hypertensive disorders of pregnancy is a spectrum of disorder which include chronic hypertension that antedates pregnancy and gestational hypertension or pre-eclampsia that is unique to human pregnancy. It is still a poorly understood condition. The clinical course is progressive and characterized by continuous deterioration that is arrested only by termination of pregnancy. Hence the disease must be detected in early stage and managed appropriately for improved maternal and fetal outcome.Methods: The study consists of 173 antenatal patients of gestational age 28 weeks and above. Study population was divided into two groups, Group 1 consists of 50 antenatal women of normotensive nature served as controls and group 2 consists of 123 antenatal women with confirmed hypertension. Venous blood samples were collected used for the estimation of lactate dehydrogenase enzyme.Results: Out of the total 173 patients 104 women delivered by C-section, 67 by normal vaginal delivery and 2 by assisted breech delivery. Among the women who delivered by caesarean 60 (57.69%) had serum LDH less than 600, 18 (17.30%) had serum LDH between 600 and 800 and 26 (25.00%) had LDH above 800. Among the women who delivered vaginally 61 (91.04%) had LDH less than 600, 1 (1.49%) had LDH between 600 and 800 and 5 (7.46%) had LDH above 800. Only 2 women delivered by assisted breech delivery one with LDH between 600 and 800 and another with S. LDH above 800.Conclusions: The study was done in search of a valuable marker for preeclampsia and Eclampsia which would reflect the severity of the disease and would predict the maternal and fetal outcome. Such markers can help in decision making and can influence the current management protocols in order to achieve a better maternal and perinatal outcome.

Seal and Sea lion Whiskers Detect Slips of Vortices Similar as Rats Sense Textures

Pinnipeds like seals and sea lions use their whiskers in hunting their prey in dark and turbid conditions. There is no theoretical model or a hypothesis to explain the interaction of whiskers with hydrodynamic fish trails. The present work provides insight into the mechanism behind the Strouhal frequency identification from a Von-Karman vortex street behind bluff bodies, similar to the inverted hydrodynamic fish trail. Flow over 3D printed sea lion head with integrated whiskers of similar geometrical and material properties was investigated when being exposed to vortex streets behind cylindrical bluff bodies. It is found that the whiskers respond to the vortices by a jerky motion similar to the stick-slip response of rat whiskers on different surface textures. The Strouhal frequency of the upstream wake is clearly decoded with the time-derivative of the whisker response rather than the displacement response, which increases the sensing efficiency in noisy environments. It is hypothesized from the work that the time derivative of the bending moment of the whiskers is the best physical variable, which can be used as the input to the neural system of the pinnipeds

Experimental studies on treated sub-base soil with fly ash and cement for sustainable design recommendations

The pavement constructions on soft and expansive soils are not durable and unable to sustain heavy traffic loading. As a result, pavement failures and settlement problems will occur very often even under light traffic loading due to cyclic and rolling effects. Geotechnical engineers have dwelled deeply into this matter, and adopt various methods to improve the engineering characteristics of soft fine-grained soils and expansive soils. The problematic soils are either replaced by good and better quality material or treated by using chemical stabilization with various binding materials. Increased the strength and durability are also the part of the sustainability drive to reduce the environment footprint of the built environment by the efficient use of resources and waste recycle materials. This paper presents a series of laboratory tests and evaluates the effect of cement and fly ash on the strength and drainage characteristics of soil in Miri. The tests were performed at different percentages of cement and fly ash by dry weight of soil. Additional tests were also performed on soils treated with the combinations of fly ash with cement and lime. The results of this study indicate an increase in unconfined compression strength and a decrease in hydraulic conductivity of the treated soil

A Comprehensive Analysis of Password Authentication for Enhancing Security in Internet of Things (Iot)

Recently, there has been a significant increase in customer demands and the variety of services provided due to the increasing use of mobile devices and the development of new networking technologies such as the Internet of Things (IoTs) and Big data networking. The proliferation of future smart cities, smart transport systems, and other Internet of Things (IoT) application areas presents a significant vulnerability to a multitude of security risks that can have detrimental impacts on the economy, the environment, and society. This vast range of functions raises several security concerns, such as data protection, virtualization vulnerabilities, segregation risks, network connectivity issues, and monitoring challenges. The objective of identity and access management is to ensure that the right individuals have access to the right resources. Implementing user identification and identity verification establishes a robust security measure that effectively separates potential attackers from accessing sensitive data. This study use a Systematic Literature Review (SLR) methodology to conduct a comprehensive review of security concerns and various computing approaches to mitigate them. Despite the existence of various approaches to address the specific challenges related to application design, security, and privacy, there is still a need for a comprehensive research study. This study should focus on the challenges and requirements of targeted applications, which currently have limited security enhancement solutions

The hydrogen peroxide-sensitive proteome of the chloroplast in vitro and in vivo

Muthuramalingam M, Matros A, Scheibe R, Mock H-P, Dietz K-J. The hydrogen peroxide-sensitive proteome of the chloroplast in vitro and in vivo. Frontiers in Plant Science. 2013;4:54-1-54-14.Hydrogen peroxide (H2O2) evolves during cellular metabolism and accumulates under various stresses causing serious redox imbalances. Many proteomics studies aiming to identify proteins sensitive to H2O2 used concentrations that were above the physiological range. Here the chloroplast proteins were subjected to partial oxidation by exogenous addition of H2O2 equivalent to 10% of available protein thiols which allowed for the identification of the primary targets of oxidation. The chosen redox proteomic approach employed differential labeling of non-oxidized and oxidized thiols using sequential alkylation with N-ethylmaleimide and biotin maleimide. The in vitro identified proteins are involved in carbohydrate metabolism, photosynthesis, redox homeostasis, and nitrogen assimilation. By using methyl viologen that induces oxidative stress in vivo, mostly the same primary targets of oxidation were identified and several oxidation sites were annotated. Ribulose-1,5-bisphosphate (RubisCO) was a primary oxidation target. Due to its high abundance, RubisCO is suggested to act as a chloroplast redox buffer to maintain a suitable redox state, even in the presence of increased reactive oxygen species release. 2-cysteine peroxiredoxins (2-Cys Prx) undergo redox-dependent modifications and play important roles in antioxidant defense and signaling. The identification of 2-Cys Prx was expected based on its high affinity to H2O2 and is considered as a proof of concept for the approach. Targets of Trx, such as phosphoribulokinase, glyceraldehyde-3-phosphate dehydrogenase, transketolase, and sedoheptulose-1,7-bisphosphatase have at least one regulatory disulfide bridge which supports the conclusion that the identified proteins undergo reversible thiol oxidation. In conclusion, the presented approach enabled the identification of early targets of H2O2 oxidation within the cellular proteome under physiological experimental conditions

Prevalence and outcome of gestational diabetes mellitus in women from rural population attending antenatal clinic at a teaching hospital, Tamil Nadu, India

Background: Prevalence of gestational diabetes mellitus shows wide variation across our country. From the recent studies, it is observed that incidence of gestational diabetes mellitus in antenatal women is increasing globally and India is not an exception from this. Gestational diabetes mellitus should be considered as a serious risk factor for both mother and baby as it affects two generations by having chance of developing diabetes and its related complications in future.Methods: A total of 585 pregnant women with 24 to 28 weeks of gestational age were recruited for the study. The study population was divided into four groups based on the age range; Group I include antenatal women with age <20 years, Group II includes antenatal women of age range 21-24 years, Group III includes antenatal women of age range 25-29 years, and Group IV includes antenatal women of age range ≥30 years.Results: In the present study GDM was diagnosed in 94 women among 585 antenatal women screened for GDM (16.06%). Majority of the studied population are in the age range of 20-29 years (441/585, 75.38%). The mean age of participants was 27.54±3.58 years (range 18-34 years). The prevalence of GDM was higher in the group of women aged ≥30 years (Group IV) followed by ≤20 years (Group I) (23.21% and 15.62% respectively) compared to the groups II and III (14.78% and 13.74% respectively). This observation was found to be statistically significant (p<0.001). Among 585 patients, delivery outcome was 100% successful, all delivered live babies, among them 64 patients delivered babies with macrosomia (11%).Conclusions: The study showed GDM prevalence of 16.06% from the neighboring rural villages attending our teaching hospital

A Deep-Learning Model for Underwater Position Sensing of a Wake's Source Using Artificial Seal Whiskers

Various marine animals possess the ability to track their preys and navigate dark aquatic environments using hydrodynamic sensing of the surrounding flow. In the present study, a deep-learning model is applied to a biomimetic sensor for underwater position detection of a wake-generating body. The sensor is composed of a bundle of spatially-distributed optical fibers that act as artificial seal-like whiskers and interact with the body's wake in the form of time-variant (bending) deflections. Supervised learning is employed to relate the vibrations of the artificial whiskers to the position of an upstream cylinder. The labeled training data are prepared based on the processing and reduction of the recorded bending responses of the artificial whiskers while the cylinder is placed at various locations. An iterative training algorithm is performed on two neural-network models while using the 10-fold cross-validation technique. The models are able to predict the coordinates of the cylinder in the two-dimensional (2D) space with a high degree of accuracy. The current implementation of the sensor can passively sense the wake generated by the cylinder at Re ≃ 6000 and estimate its position with an average error smaller than the characteristic diameter D of the cylinder and for inter-distances (in the water tunnel) up to 25-times D

COMPARATIVE AND PERFORMANCE ANALYSIS OF INDUCTION MOTOR WITH ANN CONTROLLER

A novel design of an adaptive artificial neural network technique (ANN) for controlling of the essential parameters, like as speed,  torque, flux, voltage, current, and power etc of the induction motor is presented in this paper. Induction motors are characterized by way of incredibly non-linear, complicated and time-various dynamics and inaccessibility of its states and outputs for measurements. Thus it can be considered as a challenging engineering difficulty in the industrial sector. A few of them, such as PI, fuzzy strategies, Fuzzy logic based controllers are regarded as capability candidates for such application for operating induction motor. Hence of which, the outcome of the controller is also random and high-rated results are probably not obtained. Resolution of the proper rule base application upon the drawback can be achieved by the use of an ANN controller, which becomes a built-in system of method for the manipulate purposes and yields results, which is the focus of this paper. Within the designed ANN scheme, neural community tactics are used to prefer an appropriate rule base, which is utilizing the back propagation algorithm. The simulation outcome provided on this paper is exhibit the effectiveness of the developed approach, which has acquired faster response time or settling times. Additionally, the procedure developed has got a huge number of benefits within the industrial sector will also be converted into a real time application making use of some interfacing cards