103 research outputs found
Investigation and detection of crack formations during Micro-electromechanical Systems (MEMS) resonator manufacturing and use
Time reference devices have been widely used in the industry for the past decades due to their important role in different devices applications such as portable and wearable device. With the rapid technology improvements in the semiconductor industry, Micro-electromechanical systems (MEMS) resonators were presented as a time reference devices which offer a reduced cost and small size that facilitate the integration with the other electronics.
Because of the microfabrication processes and operational modes for MEMS-resonators, defects are expected to be formed in different stages of the manufacturing and use. Those defects would be costly if have not been detected in early stages, hence, industry dedicates time and resources for better detection of defects. With the mass production of MEMS-resonator, manual inspection of defects is becoming an impractical solution, that led to develop automation systems for defects’ detection.
This work studies the defects that may occur in MEMS-resonator in different stages and a studies defects detection methods. The study aims to investigate the microfabrication induced defects, the defects formation during the device operation and to develop an automatic defects inspection tool. To fulfil the study objectives, different MEMS-resonator devices were designed in order to study the effect of different parameters such as the geometry and dimensions on the robustness of the device. Standard microfabrication processes were implemented to observe the risk of defects formation during manufacturing. For the operation stage, FEM simulations were executed, and different mode shapes were selected to study the likelihood of mode shapes to produce defects for the device fragile parts. The last stage for defects inspection included implementation of automatic optical inspection (AOI) tool with a hardware setup for image collection and a software part for image processing and defection/robustness decision making, the result of the AOI was validated by the percentage of the detected defects and the occurrence of false-positives.
The MEMS-resonators designs considered 2 frequencies of 24MHz and 32MHz, 3 different anchors and 7 different beam widths with average resulting quality factor(Q) of 11.68x10e3. Common defects of AlN particles residuals were observed with SEM as a microfabrication caused defects. 8.4% of the devices were defected electrically by resonating in specific spurious modes, 19.89% of the resonator were defected after performing the tape-peeling test. AOI tool was successful to reach 85.5% detection rate with 7.1% false-positive occurrences
Universal Data Logger System for Environmental Monitoring Applications
Collecting huge amount of data in long time acquisition systems like in environmental monitoring, there is a need to collect and save data over time for further use or analysis. A data logger is an electronic device that records data over time or in a relation to location either with a built-in instrument, sensor or via an external instruments and sensor. In this paper, a data logger system is designed to use as a stand-alone or computer based device. When used as a standalone system, all data acquired are saved in SD memory card, which must be copied and erased periodically depending on the memory size. When used as computer based device, all the data sent to the computer via the serial port and stored automatically in achieved files. The limit of those files size only restricted by the capacity of the disk. The data logger is designed using an Arduino UNO board and LabView software, and it has the flexibility to set it up for different user options. With this system, the user could be able to record and read back sensory data to or from existing files, or in automatically generated files and plot these readings in a graph. Also, the user have the ability to choose the periodic time at which a sample record in a file in term of seconds, minutes or hours. The system designed to monitor and record a single channel data, but it could be adapted to monitor more than one channel
The Effect Of Lighting Design And Application On Limar Textile In Terengganu State Museum
The lighting application of a textile museum combines art, science, and
engineering, whereby the lighting integrates the aesthetic value and the exhibition
preservation requirements. Lighting can evoke sensations and emotions. It controls the
perception of specific exhibitions, such as textiles. The quality of the lighting in the
galleries is not determined solely by the source of the lighting, but also by the
characters and the space configuration. The means by which the lighting hits the object
and the architecture results in light penetration and reflected light, as well as how such
lighting is accepted by the minds and eyes of the viewers. This research focuses on the
lighting application of the limar textile exhibition gallery. This research emphasizes
the lighting application in the Terengganu State Museum to help maintain better
conservation of limar textiles by investigating the adverse effects of the lighting
design. The selection of limar textile, by reason, is the essential cultural value that
limar has in representing the history and culture of Malaysia. Therefore, this delicate
and worthy textile needs to be conserved to preserve it for the upcoming
generation
Exploring Students' Perspectives on the Purpose of Engineering Higher Education in the US
This full paper builds on the work of the first author's PhD dissertation that explores undergraduate Chemical Engineering students' perspectives on why they chose to enroll at a higher education institution in the US. The research brings together capabilities approach and engineering higher education literature in the aim of highlighting students voices. Current literature tends to discuss engineering as a profession, and the history of that profession, and less focused on the purpose of engineering as a degree in itself, which this work aims to change. Capabilities Approach framework, also referred to as the Human Development Approach is concerned with the question of what a person is able to do and be. It also provides a perspective on thinking about purpose of education in terms of instrumental, intrinsic, and social values.The paper draws on data from a larger project which is focused on the experiences of students studying Chemistry and Chemical Engineering in England, South Africa and the United States of America. We use some of the data from the Chemical Engineering students in the United States in order to explore students' perspectives on the purpose of enrolling in a higher education institution and obtaining an engineering degree. Each case is built around a higher education institution, whereas the embedded units of analysis focus on the students' narratives. The study particularly explores the phenomena from a longitudinal perspective by analyzing data from four different students from the time they enroll in those institutions to the time they graduate, summing up to a total of sixteen interviews. The paper particularly focuses on answering the following research question:RQ: What are the held perspectives of undergraduate Chemical Engineering students towards the purpose of higher education in the US?Primary results show a variety of perspectives and reasoning why students pursue an engineering degree. Conforming to societal expectations, securing a job, as well as learning and developing on personal levels all came up and will need to be further investigated. This research is set to address the problem of the neglect of the students' voices in the literature, and to address the lack of research on higher education within the engineering education space
Neutrosophic rule-based prediction system for toxicity effects assessment of biotransformed hepatic drugs
Measuring toxicity is an important step in drug development. However, the current experimental meth- ods which are used to estimate the drug toxicity are expensive and need high computational efforts. Therefore, these methods are not suitable for large-scale evaluation of drug toxicity. As a consequence, there is a high demand to implement computational models that can predict drug toxicity risks. In this paper, we used a dataset that consists of 553 drugs that biotransformed in the liver
Assessment of left ventricular function by global longitudinal strain in patients with non-ST elevation myocardial infarction: Comparative study with conventional method
Background: Left ventricular ejection fraction (LVEF) is a strong prognostic parameter in patients with heart disease. The assessment of global longitudinal strain (GLS) from speckle-tracking analysis of 2-dimensional echocardiography has become a clinically feasible alternative to LVEF for the measurement of myocardial function.Objective: The aim of the current work was to compare between GLS speckle tracking echocardiography and Simpson’s biplane methods for assessment of left ventricular function in non-STEMI patients.Patients and methods: This study was carried out in Cardiology Department, Faculty of Medicine, Zagazig University on 44 non‐ST‐elevation myocardial infarction (NSTEMI) patients scheduled for assessment of Left ventricular function by GLS and biplane Simpson method.Result: Mean systolic blood pressure was 122.05±18.37 mmHg. No statistically significant difference in systolic blood pressure was found across GLS groups (P= 0.17). Mean diastolic blood pressure was 73.41±12.00 mmHg. No statistically significant difference in diastolic blood pressure was found across GLS groups (P= 0.35). Mean heart rate was 68.84±7.13 bpm, and a statistically significant difference was found in heart rate across GLS groups (P= 0.039).Conclusion: It could be concluded that GLS speckle tracking echocardiography and Simpson’s biplane methods can be used as alternative different parameters for assessment of left ventricular function in non-STEMI patients
Reliability Analysis Approach For Operations Planning Of Hydropower Systems
Many existing hydropower storage facilities were built decades ago and components of these aging infrastructure facilities have higher risk of failure. Insufficient capacity or forced outages of the spillway and other waterway passage facilities during flooding incident could potentially increase the probability of dam safety incidents leading to public safety concerns. Currently approaches used to assess the risk and uncertainty in operational decision making are mainly based on qualitative assessment and expert judgment and can be significantly improved by the development of a framework that formally incorporates both qualitative and quantitative reliability analysis methods. Event tree analysis and fault tree analysis have traditionally been used in dam safety risk analysis, with results subject to data adequacy and availability. Our research shows that other methods, such as nonparametric analysis and Monte Carlo simulation techniques can yield good results as well. This study investigated the application of reliability analysis methods to existing hydropower storage facilities, with the objective of developing a new systems engineering based approach for risk and uncertainty analysis to assess and manage the risks of hydropower system operations. Our approach integrates reliability-based methods with hydro system optimization modeling to develop an operational reliability-based modeling framework and to formally treat risk and uncertainty in operations planning. This approach incorporates different sources of uncertainty that are typically encountered in operations planning of these systems, including failure probability of hydro system components such as non-power release structures and turbine facilities. This paper presents the framework we have developed and illustrates the application of our investigation for a hydropower system facility in British Columbia, Canada
A Multi-Objective Optimization Model For Operations Planning Of Multi-Reservoir Systems
This paper presents the development and evaluation of a multi-objective linear programming (LP) optimization tool for an operations planning platform (OPP). The LP optimization model is coded using a high level programming language called AMPL (A Mathematical Programming Language) and solved using a solver called CPLEX. This model was developed by closely working with operations planning engineers at BC Hydro, in Canada, with the support of a research team from the University of British Columbia. The optimization model incorporates two objectives to optimize the operation of a multi reservoir system: maximize revenue from power generation, and to minimize penalties resulting from deviations of reservoir elevations and spill releases from a preferred operating regime. Several multi-objective optimization techniques are being investigated including traditional methods such as the Weighting Method and the Constraint Method, as well as Goal Programming (GP) techniques. These methods would be tested for optimality and computational efficiency and would be generalized and used to study a number of multi-reservoir systems in British Columbia. Stochastic inflows would be considered in the model making use of chance-constraints and probability distribution functions based on historical inflow records. The model also incorporates features which simulate maintenance outages on hydropower plants. The goal is to determine the optimal maintenance schedules that minimize the cost of these outages. We present results of a case study to illustrate the capabilities of the model to provide decision makers with timely information on trade-off between different objectives. Maintenance schedules of generating units with and without optimization are also considered
Adherence to Immunosuppressive Medications in Kidney Transplant Patients at Three Centers in Khartoum State, Sudan: A Cross-sectional Hospital Study
Background: Graft survival post-kidney transplantation is of paramount importance to patients and nephrologists. Nonadherence to immunosuppressive therapy can be associated with deterioration of renal function and graft rejection. This study aimed to evaluate the adherence to immunosuppressive medications in kidney transplant patients at three centers in Khartoum, Sudan.
Methods: In this descriptive cross-sectional hospital-based survey, 277 post-kidneytransplant patients were recruited. Data were collected using a questionnaire and analyzed using the SPSS v.23. Our scoring method was calculated based on Morisky Medication Adherence Scale (MMAS-8) related to immunosuppressive medications and was expressed as questions in the questionnaire; every correct answer was given one mark, then the marks were gathered and their summation was expressed.
Results: Overall, 33% ,45%, and 22% of the studied participants reported high, medium, and low adherence, respectively. The major factor for nonadherence was forgetfulness affecting 36.1% of those who did not adhere. The cost of the immunosuppressive medications did not negatively affect any of the participants’ adherence (100%). However, a significant association was seen between adherence and occupational status, duration of transplantation, shortage of immunosuppressants, recognizing the name of immunosuppressant, side effect, and forgetfulness (P-values = 0.002, 0.01, 0.006 , 0.000, 0.022, and 0.000, respectively). Logistic regression analysis showed a significant association with occupational status, side effects, and forgetfulness
Conclusion: Only one-third of the participants were classed as “highly adherent” to their immunosuppressant medications. Factors that can affect adherence to immunosuppressant medications were occupational status, side effects, and forgetfulness
Hemodialysis associated dysautonomia; Effect of optimization of dialysis and nutrition: A prospective study
Background: Autonomic neuropathy is common among hemodialysis patients, even if they are asymptomatic. The aim of this study is to assess the effect of optimization of patients' dialysis and nutrition on the presence of autonomic dysfunction in these patients guided by sympathetic skin response (SSR) test.
Methods: Fifteen patients on maintenance hemodialysis (12 males and 3 females) their age ranged from 24 to 67 years, most of them were on bicarbonate dialysis were included in our study. Initially, the patients were assessed clinically and by laboratory investigations and their dialysis was assessed by studying their urea kinetic modeling. Their nutrition was assessed by laboratory parameters and by calculating the normalized protein catabolic rate (nPCR). Their autonomic functions were assessed by clinical examination, hand grip and SSR test. Dialysis dose was readjusted to achieve a target kt/v value of 1.3/session thrice weekly. Also, their nutrition was reviewed to achieve nPCR of 1.2 gm/kg/day and caloric intake of 30-40 KCal/kg/day through diet manipulation and support. They were reassessed after 3 months.
Results: Analysis of the data showed a statistically significant improvement of the observed subclinical autonomic neuropathy evidenced by a significant change in the hand grip (p = 0.044), and a high statistically significant improvement in the sympathetic skin response test parameters (both amplitude and latency) (p=0.001) after optimization of both hemodialysis and nutrition status.
Conclusion: Improving dialysis and patients nutrition by using urea kinetic modeling is valuable in improving their autonomic functions as assessed by SSR test
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