Spice simulation of crystal at 49,12 m-hz

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マルツエレック株式会社 marutsuelec

Engineering

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In this study, using the fuzzy logic method, a stress detection tool was created with body temperature and blood pressure parameters as indicators to determine a person's stress level. This tool uses the LM35DZ sensor to detect body temperature, the MPX5100GP sensor to read blood pressure values, and Arduino Uno as a data processor from sensor readings which are then calculated using the fuzzy logic method as a stress level decisionmaker. The resulting output measures blood pressure, body temperature, and the stress level experienced by a person, which will be displayed on the liquid crystal display. Based on the results of testing the body temperature parameter, the highest error generated was 1.17%, and for the blood pressure parameter, the highest error was 2.5% for systole and 0.93% for diastole. Furthermore, testing the stress level displayed on the tool is compared to the depression, anxiety, and stress scales 42 (DASS 42), a psychological stress measuring instrument. From the results of testing the tool with the questionnaire, the average conformity level is 74%.

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IJECEIAES

This presentation, crafted with expertise from the oil and gas industry, details the imperative techniques and tools used in the process of incident investigation. The presentation highlights the structured methods involving interviews with engaged parties, the importance of gathering documentary evidence, employing structured forms and checklists, the value of reviewing surveillance footage, the power of modern technology, and synergizing with subject-matter experts. It is designed for industry professionals keen on enhancing safety practices, regulatory compliance, and preventive measures within their operational environment. Valuable for health & safety officers, compliance managers, and operation leaders, it prioritises continuous learning and adherence to best practices to ensure workplace safety and operational excellence.

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A Coordinate Measuring Machine (CMM) is a precision measuring metrology machine used in manufacturing and quality control processes to precisely measure the geometric characteristics of objects. It operates on the principle of coordinate geometry, employing a probe to collect data points from the surface of an object to determine the dimensions, shapes, and positions of features, such as holes, slots, and surfaces. CMMs are essential tools for ensuring that manufactured parts meet design specifications and quality standards.

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This simple Python software is designed to assist Civil and Geotechnical Engineers in performing site-specific seismic hazard assessments. The program calculates the seismic response spectrum based on user-provided geotechnical and seismic parameters, generating a comprehensive technical report that includes the response spectrum data and figures. The analysis adheres to Eurocode 8 and the Greek Annex, ensuring compliance with international standards for earthquake-resistant design.

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This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.

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IJECEIAES

21scheme vtu syllabus of visveraya technological university

Mohd Saifudeen

The project entitled as “Insurance Management System” is developed in a manner to help all the Insurance Agency Members. It is developed using Visual Basic 6.0 as Front-End and MS Access as the Back-End tool. The system is designed in such a way that it accepts and stores the input data, process and produce output under the direction of a detailed step by step stored programmed instruction. This system includes Client Dairy, Client Details, Add new Client, Policy Details and Payment Details information’s and gives details based on the policy Number of the client. This system is necessary for Storing Information, assessing Workload and hence their efficiency. The System provides the adequate information to the concern for its smooth run.

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