Electronic thermodynamics part 1: Thermo-electromechanical system modeling, instrumentation, and simulation

This research proposes to obtain a mathematical model that describes the dynamic operation of a brushed DC motor, to obtain a state function considering the electrical, mechanical, and thermal effects of the DC motor. The dynamic evolution of the proposed function is evaluated by simulation using Matlab software, and by applying different values of the step type inputs for the brushed motor excitation employing pulse width modulation (PWM) to obtain a wide range of operations. Experimental results show that the developed state function, provides a reliable approximation to estimate the voltage, armature current, mechanical torque, and temperature of the brushed DC motor, showing an error percentage of 0.2%.

Designing a Mouse for Disabilities Using the MPU-6050 Sensor with the Kalman Filter Method as a Noise Reducer

Problems that are often faced by people with physical disabilities are those who have limited hands, one of which is when they will use the computer. His inability to grip and use the mouse is often a barrier in using the computer. The purpose of the design of the tool is to provide facilities for people with disabilities to be able to use a mouse that will be moved based on head movements without noise interference caused by the MPU-6050 sensor. The results of the tests carried out show that designing a mouse with the MPU-6050 sensor has been successfully carried out, the MPU-6050 sensor by implementing a kalman filter as a noise reducer on the X axis has an accuracy value with an average error percentage of 0.09% and at Y angle is 0.12%. Data transmission from the mouse to the computer is done wirelessly using bluetooth HC-05 can receive data well as far as 12.5 meters with an error percentage of 0%. The button on the mouse that functions to perform the left click function when the button is bitten 1x, right click when the button is bitten 2x and click and hold to do a left click 2x or double click can run according to the command, has a 100% success rate.

Preparation of Antihypertensive Drugs in Biological Matrix with Solvent Front Position Extraction for LC–MS/MS Analysis

Solvent front position extraction procedure was used to prepare biological samples containing selected antihypertensive drugs (ramipril, lercanidipine, indapamide, valsartan, hydrochlorothiazide, perindopril, and nebivolol). Substances separated from the biological matrix components (bovine serum albumin) were quantified by means of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Sample preparation process was performed with the use of a prototype horizontal chamber with a moving pipette driven by a 3D printer mechanism enabling a controlled eluent flow velocity. Application of this device was advantageous for simultaneous preparation of several samples for further quantitative analysis, with a synchronized reduction of manual operations and solvent consumption. Quantitative results obtained for the majority of the investigated antihypertensive drugs in a complex biological matrix were satisfactory. The values of the %RSD were around 5% for six of the seven substances (with the exception of indapamide). The method exhibits a suitable accuracy (the relative error percentage was below 10% for most drugs). The values of LOD and LOQ were in the range of 1.19 µg/L–8.53 µg/L and 3.61 µg/L–25.8 µg/L, respectively.

Modelling of Auxetic Woven Structures for Composite Reinforcement

The current research is focused on the design and development of auxetic woven structures. Finite element analysis based on computational modeling and prediction of axial strain as well as Poisson’s ratio was carried out. Further, an analytical model was used to calculate the same parameters by a foldable zig-zag geometry. In the analytical model, Poisson’s ratio is based on the crimp percentage, bending modulus, yarn spacing, and coefficient of friction. In this yarn, properties and fabric parameters were also considered. Experimental samples were evaluated for the actual performance of the defined auxetic material. Auxetic fabric was developed with foldable strips created in a zig-zag way in the vertical (warp) direction. It is based on the principle that when the fabric is stretched, the unfolding of the folds takes place, leading to an increase in transverse dimensions. Both the analytical and computational models gave close predictions to the experimental results. The fabric with foldable strips created in a zig-zag way in the vertical (warp) direction produced negative Poisson’s ratio (NPR), up to 8.7% of axial strain, and a maximum Poisson’s ratio of −0.41 produced at an axial strain of around 1%. The error percentage in the analytical model was 37.14% for the experimental results. The computational results also predict the Poisson’s ratio with an error percentage of 22.26%. Such predictions are useful for estimating the performance of auxetic woven structures in composite reinforcement. The auxetic structure exhibits remarkable stress-strain behavior in the longitudinal as well as transverse directions. This performance is useful for energy absorption in composite reinforcement.

Novel Approach to Computing Critical and Normal Depth in Circular Channels

The critical depth and normal depth computation are essential for hydraulic engineers to understanding the characteristics of varied flow in open channels. These depths are fundamental to analyze the flow for irrigation, drainage, and sewer pipes. Several explicit solutions to calculate critical and normal depths in different shape open channels were discovered over time. Regardless of the complexity of using these explicit solutions, these formulas have a significant error percentage compared to the exact solution. Therefore, this research explicitly calculates the normal and critical depth in circular channels and finds simple, fast, and accurate equations. First, the dimensional analysis was used to propose an analytical equation for measuring the circular channels' critical and normal depths. Then, regression analysis has been carried for 2160 sets of discharge versus critical and normal depths data in a circular open channel. The results show that this study's proposed equation for measuring the circular channels' critical and normal depths overcomes the error percentage in previous studies. Furthermore, the proposed equation offers efficiency and precision compared with other previous solutions.

Hardware efficient circuit for low error logarithmic converter

The need to implement high-speed Signal processing applications in which multiplication and division play a vital role made logarithmic arithmetic a prominent contender over the traditional arithmetic operations in recent years. But the logarithm and antilogarithm converters are the bottlenecks. In order to reduce the logarithmic conversion complexity, several works have been introduced from time to time for correcting the error in Mitchell’s algorithm but at the cost of hardware. In this work, we propose a 32-bit binary to the binary logarithmic converter with a simple correction circuit compared with existing techniques. Unlike the current methods that use the linear piece-wise approximation in the mantissa, we propose a weighted average method to correct the error in Mitchell’s approximation. The maximum error percentage from the proposed work is 0.91%, which is 16.9% of Mitchell’s error percentage.

A Pragmatic Approach for Detecting nCOVID-19 using Pervasive Computing Based on Dual Diagnostic Measures

Our regular way of life has been disrupted by the COVID-19, and we have been obliged to accept the procedures that are in place under the new normal regime. It is envisaged that the standard diagnostic technique will evolve throughout the course of the procedure. As a help to this type of diagnostic technique, our research group is developing a tool. In this article, the group discusses the importance of employing two diagnostic metrics that have proven to be pivotal in many diagnoses for doctors, and how they might be used to their advantage. Together, natural language processing-based symptoms measures and a machine learning-based strategy that takes into account medical vitals can help to minimise the error percentage of detection by as much as 50%. The technique suggested in this study is the first of its type, and the authors have obtained findings that are satisfactory in terms of accuracy. A further justification for suggesting such a strategy is the manner in which a fusion algorithm might arrive at the correct results from two concurrent algorithms performing the same task. One of the group's other objectives was to give the doctor a valuable opinion in the form of such an architectural design. The suggested design may be employed at any point of care facility without the need for any additional infrastructure or escalation of the current amenities to accommodate the proposed architecture.

Static Strength Analysis of Meat Grinder Frame

Meat is one of the agricultural commodities needed to meet protein needs, because meat contains high quality protein, which is able to contribute complete essential amino acids. The purpose of this paper is to design, analyze the static strength of the frame based on theoretical calculations and simulations on solidwork 2018 software. This machine consists of a frame, reservoir, grinding shaft, transmission, and electric motor. The results of the design obtained a Meat Grinding Machine with Length: 610 mm, Width: 500 mm and Height: 750 mm. The material used is 2024-O Alloy with a modulus of elasticity of 72,400 N/mm2. The load force obtained is 576.32 N. And the value from the analysis is the displacement value of 0.174 mm and for theoretical calculations, the displacement value is 0.176 mm. So, the value of the percentage error is 1.176%. For the von Mises value of 68,970 MPa, and for calculations based on the theory, the von Mises value is 52,499 MPa. So, the value of the error percentage is 0.238%. And for the value of the safety factor obtained a value of 1,087, and for calculations based on the theory, the value of the safety factor is 1.428. So, the value of the error percentage is 0.313%.

Adaptive Neuro-Fuzzy Inference System For Forecasting Traffic Volume(Case Study Of National Road Km 41 Kamal)

The effect of the development of an infrastructure such as shopping centers, settlements, and so on is one study that is generally considered in the governance of a region. Typically, this construction has a major traffic impact. Combined with the effects of population growth, which is constantly growing every year, the flow of traffic is increasingly congested. This is because many of these people choose to own personal vehicles. Tremendous congestion would result from a road capacity that is not proportional to vehicle growth. A traffic analysis was conducted using road traffic volume data to prevent this. This research will attempt to survey a road on National road KM 41 Kamal and use the neuro fuzzy method to forecast traffic volume. The amount of traffic that will be studied is only motorcycles. The results show that with an error percentage of 16.0793%, neuro fuzzy can predict motorcycle traffic volume. It can be inferred from this that Neuro Fuzzy can forecast traffic volume on a road quite well.

Infant Warmer Equipped with Digital Weight Scales

Scales Scales in the world of health are used to measure human body weight such as baby scales. Newborns are very important to be weighed because it is used as a measure of the baby's health indication ranging from 2.4 kg to 4.2 kg. The author makes a tool for this to make it easier for users to weigh with a 7 segment display on the Infant Warmer tool and external calibration. By using a loadcell sensor with a maximum capacity of 5 kg, the loadcell can detect the weight of the load where the voltage generated by the loadcell of 0.7 mV at a load of 1 kg is amplified to 0.62 V by the PSA circuit using the AD620 IC and then processed by Arudino UNO as a microcontroller. The weight results will be displayed on the 7Segment display located on the Infant Warmer tool. In the study, the measured load included a weight of 0 kg to a maximum weight of 5 kg. The measurement of the data results was carried out 5 times each by comparing the modules that had been made with the standard weight, namely (lead). The data from the measurement results of the research module shows that when the weight of the measurement at 1 kg has an error percentage of 0.08%. Measurements at a weight of 2 kg have an error percentage of 0.05%. Measurement of weight 3 kg has a presentation error of 0.01%. Measurements at a weight of 4 kg have a presentation error of 0.02%. And measurements at a weight of 5 kg have an error percentage of 0.04%. Then the data from the measurement results of the research module shows the largest error presentation of 0.08% at a weight of 1 kg. And the data from the measurement results of the research module shows the smallest error presentation of 0.01% at a weight of 3 kg. Making a research module in the form of a scale placed on an infant warmer can make it easier for the wearer.