Analog Instruments Research Articles

Updating a Didactical Piston Engine Test Bench, from Analogue Instrumentation to Digital

Updating a Didactical Piston Engine Test Bench, from Analogue Instrumentation to Digital

EMG Instrumentation Modeling and Feature Processing Based On Discrete Wavelet Transform

Electromyography (EMG) instrumentation is essential in generating electrical signals from skeletal muscles. EMG sensors are helpful in various cases requiring the detection of human muscle contractions, neuromuscular disorders, and rehabilitation. EMG instrumentation is divided into two parts, namely, the analogue part and the digital part. The EMG instrumentation design comprises a digital-to-analog converter (DAC), instrumentation amplifier, filter, and analog-to-digital converter (ADC). Meanwhile, in digital signal processing adopting the Discrete Wavelet Transform (DWT) method, frequency analysis using DWT has proven superior. It is used in various research and has exceptionally detailed coefficient features for classifying neuromuscular disease signals. Therefore, this research aims to design analogue and digital EMG instrumentation and identify features in the form of detailed coefficients. The data used are two Physionet signals from the anterior tibialis body with myopathy and neuropathy disorders. The results obtained for EMG analogue instrumentation provide the expected results until they reach the filter component stage. The resulting signal forms a block in the filter component, different from the initial EMG signal. Meanwhile, the DWT decomposition results are of the Daubechies4 wavelet type with the highest level 17, which has a high detail coefficient at low frequencies, high dilation and the result of a mixture of neuropathy and myopathy EMG signals, or in other words, at low energies, this result is by the DWT theorem. Determining the efficiency of the DWT detailed coefficient feature requires further study with the same signal subject. The DWT features obtained can then be developed for various needs in EMG signal recognition.

Research on Wireless Weather Station Using IoT

Abstract: This project's suggested system is a cutting-edge method of keeping an eye on the local weather and disseminating the data anywhere in the globe. This is made possible by Internet of Things (IoT) technology, which is a sophisticated and effective way to link objects to the internet and to link everything in the world together in a network. Anywhere in the world can access the updated data from the established system over the internet. During some weather dangers, it will be extremely difficult to examineand monitor the weather parameters in the agriculture zone using cables and analog instruments. Here, wireless sensors are utilizedto examine and monitor the meteorological data in order to solve this issue.

Early Detection of Livestock Fever, Estrus, and Parturition Using Wearable Tail Sensor

The advancement of technology paved the way for the wearable tail sensor to be developed as livestock owners depend on analog measurements for detecting fever, estrus, and parturition. Hence, these advancements help farm and livestock management. This study aimed to design and develop a wearable tail sensor that integrates heat, motion, and pulse sensors for the early detection of livestock fever, estrus, and parturition. This study utilized a Research and Development (R&D) design employing the 4D Model of device development, which encompasses four distinct phases: define, design, develop, and disseminate. The study successfully designed and developed a device that integrates four sensors to detect fever, estrus, and parturition in livestock. The results revealed that the device has a high level of acceptability and adaptability. Statistical analysis also showed that there is no significant difference between the measurements of the analog instruments and the wearable tail sensor in terms of temperature and pulse rate for both cattle and pigs. The researchers successfully constructed a wearable device integrating four sensors to detect fever, estrus, and parturition in livestock that transmits real-time data over the web server and accurate measurements of temperature, pulse, and motion of livestock. This advancement benefits the livestock owners by making it less difficult to track the livestock’s fever, estrus, and parturition.

Selected Research and Dramatic Surgery Fish Cases of Incisive Complete in Fish Surgical

Abstract
 Health problems which can be treated exclusively by surgical means are relatively uncommon in fish. Fish surgery feat is vital essential and inevitable for the at fish diseases treatment and fish recovery. Consequently, only a limited number of procedures have been developed and reported in the literature. Despite use of analogous surgical instruments and surgical techniques to those employed in other animals, fish are a very diverse taxon and specific anatomy and physiology should be reviewed before surgical procedures are performed. Surgical planning often requires advanced diagnostics such as ultrasonography and imaging. Essantial surgical procedures include cutaneous and intracoelomic mass excision, ophthalmic procedures, reproductive surgery, brain surgery, visceral organs surgery, gastrointestinal foreign body removal, visceral organs examples, and buoyancy concerns. This article reviews several surgical procedures that have been performed in fish and highlight various aspects of surgical care which relate specifically to fishes. In this review article, administration of sedation and anesthesia, anaesthetic agents, pain in fish, obtrusive fish cases surgery, fish cases surgery operations examples, frequently used anesthetics and preoperative considerations, underwater surgery, out of water surgery, specific surgery procedures, microsurgery techniques, laparoscopy, catheter implantation and laparotomy were discussed for fish researchers. Suggestions for appropriate postoperative management are also discussed.

Introduction to the Digitization of Seismic Data: A User’s Guide

Abstract Modern seismic data are collected, distributed, and analyzed using digital formats, and this has become a standard for the field. Although most modern seismometers still make use of analog electronic circuits, their data are converted from an analog voltage output to time-tagged counts by way of digitization. Although much of the digitization process is not complicated to conceptualize, there is a fair bit of jargon in digitizer specifications, and a few pitfalls that can arise in the processes of recording and analyzing ground-motion data. In this article, we review some of the fundamental physical properties of data acquisition systems and the basic steps in digitizing data from an analog instrument (specifically a seismometer). We then briefly discuss the digitization process and some of the key properties needed to make these data useful for seismological applications. Finally, we discuss some of the filtering processes that naturally arise from digitization and how it can affect the processing workflow. The end goal is to provide a user guide that will enable seismologists to have a working knowledge of the digitization process. We focus on aspects central to seismological applications and have tried to avoid getting bogged down in signal processing formalism.

Digital assessment of peripheral blood and bone marrow aspirate smears.

The diagnosis of benign and neoplastic hematologic disorders relies on analysis of peripheral blood and bone marrow aspirate smears. As demonstrated by the widespread laboratory adoption of hematology analyzers for automated assessment of peripheral blood, digital analysis of these samples provides many significant benefits compared to relying solely on manual review. Nonetheless, analogous instruments for digital bone marrow aspirate smear assessment have yet to be clinically implemented. In this review, we first provide a historical overview detailing the implementation of hematology analyzers for digital peripheral blood assessment in the clinical laboratory, including the improvements in accuracy, scope, and throughput of current instruments over prior generations. We also describe recent research in digital peripheral blood assessment, particularly in the development of advanced machine learning models that may soon be incorporated into commercial instruments. Next, we provide an overview of recent research in digital assessment of bone marrow aspirate smears and how these approaches could soon lead to development and clinical adoption of instrumentation for automated bone marrow aspirate smear analysis. Finally, we describe the relative advantages and provide our vision for the future of digital assessment of peripheral blood and bone marrow aspirate smears, including what improvements we can soon expect in the hematology laboratory.

Assimilation of data from the MWHS‐II onboard the first early morning satellite FY‐3E into the CMA global 4D‐Var system

AbstractRadiance data from satellite microwave radiometers are becoming increasingly important in the assimilation of numerical prediction systems. FengYun‐3E (FY‐3E), which was launched in July 2021, as the first early morning orbital satellite among FY‐3 polar‐orbiting meteorological satellite series, can greatly enhance the atmospheric sounding capacity in three orbits compared with the two‐orbit system that is distributed in morning or afternoon orbit. Focusing on MicroWave Humidity Sounder‐2 (MWHS‐II) onboard it, the schemes for thinning, quality control, bias correction and observational error calculation are developed. The scan‐position‐dependent biases are assessed in each channel and increasing biases near the edges of scanline are found in several temperature‐sounding channels. The data quality is compared with four analogous instruments used in Global/Regional Assimilation and Prediction System–Global Forecast System (CMA_GFS), and the performance improvements are confirmed relative to the previous FY‐3C/D MWHS‐II. Three batch experiments were implemented in CMA_GFS with four‐dimensional variational (4D‐Var) system—assimilating only the humidity‐sounding channels, the temperature‐sounding channels and the combined channels—to reveal the impact of assimilation by different channel groupings. Analysis results conclude that FY‐3E MWHS‐II radiances are beneficial to the humidity and temperature analysis fields. These results emphasize the advantage of simultaneously assimilating the humidity/temperature‐sounding channels, in which the former dominates the improvement above 700 hPa while the latter have a positive impact below 700 hPa. The forecast results also show that assimilating both the 183‐ and 118‐GHz channels further improves the forecast skills, especially short‐ to medium‐term forecasts in both hemispheres. FY‐3E MWHS‐II also improves the short‐term prediction of heavy rain, which is always weakly predicted in global forecast systems. This study shows that a three polar orbits system that FY‐3E began can produce marked effects in the numerical prediction system. This study also shines light on the application potential of the distinctive 118‐GHz channels of MWHS‐II.

Analogical Reasoning in Mathematical Theorems

Analogical reasoning is one of the most powerful tools of mathematical thinking. For example, to prove a theorem it is necessary to see similarities with the previous theorem. This study aims to classify analogies in mathematics courses and examples. This classification is based on research results. The research was conducted use qualitative research. The research subjects are 12 lecturers who teach mathematics courses and study program managers. Analogical reasoning instruments are unstructured interview guidelines and observation sheets. Interview guides and observation sheets were made to be able to reveal mathematics analogical reasoning in the Mathematics Education Study Program course. The results of the research show that there are 3 types of analogy classifications in mathematics courses, namely definition analogy, theorem-defining analogy, and theorem analogy. First, the definition of similarity in the same or different courses. Second, the similarities between definitions and theorems in the same or different courses. Third, the theorem similarities in the same or different subjects. Our classification is related to theorems and analogical properties in several courses in the curriculum of the Mathematics Education Study Program. The analogy can be applied to certain mathematical topics related to real life. Meanwhile, to analyze other aspects of reasoning through analogy needs to be studied further.

A Deep Ultraviolet Raman and Fluorescence Spectral Library of 51 Organic Compounds for the SHERLOC Instrument Onboard Mars 2020.

We report deep ultraviolet (DUV) Raman and Fluorescence spectra obtained on a SHERLOC (Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals) analog instrument for 51 pure organic compounds, including 5 carboxylic acids, 10 polycyclic aromatic hydrocarbons, 24 amino acids, 6 nucleobases, and 6 different grades of macromolecular carbon from humic acid to graphite. Organic mixtures were not investigated. We discuss how the DUV fluorescence and Raman spectra exhibited by different organic compounds allow for detection, classification, and identification of organics by SHERLOC. We find that 1- and 2-ring aromatic compounds produce detectable fluorescence within SHERLOC's spectral range (250-355 nm), but fluorescence spectra are not unique enough to enable easy identification of particular compounds. However, both aromatic and aliphatic compounds can be identified by their Raman spectra, with the number of Raman peaks and their positions being highly specific to chemical structure, within SHERLOC's reported spectral uncertainty of ±5 cm-1. For compounds that are not in the Library, classification is possible by comparing the general number and position of dominant Raman peaks with trends for different kinds of organic compounds.

Entrepreneurial Curiosity, Innovativeness of the Entrepreneur, and Company Growth

Researchers have studied entrepreneurial curiosity and innovativeness as determinants of entrepreneurial behavior but have not linked them with company growth in a model. The intention of this enquiry was to examine the associations between the entrepreneur's psychological constructs of entrepreneurial curiosity and innovativeness and business growth, as examined by the conceptualization and analysis of hypotheses. For this research, data were obtained via a survey questionnaire. The sample consisted of 851 entrepreneurs of companies in three European countries. Each company had 250 workers or fewer. This study contributes to the entrepreneurship knowledge base by presenting empirical testimony on the associations between entrepreneurial curiosity, entrepreneurial innovativeness, and firm growth, as well as presenting advanced cross-nationally analogous measurement instruments of entrepreneurial curiosity and innovativeness. The entrepreneur's curiosity is important for their innovativeness, and this innovativeness is essential for business growth.

Analog instrument pointer monitoring and parameter estimation via line scan vision

Analog instruments are widely used in energy engineering. However, an analog instrument is only human-readable because it does not have a built-in digital communication interface. In power system, it is necessary not only to record the final output value but also to monitor the associated dynamic power process. The present paper develops an analog instrument pointer monitoring and parameter estimation system via line scan vision. A line scan camera is used to collect the dynamic process data of the analog instrument. The captured images can be regarded as a discrete temporal sequence. The light-spot centroid method is implemented to extract the initial pointer position. Data normalization is used to process the initial data. By analysing the system step response function, we construct a cost function, and Least-squares identification algorithm is used to estimate the damp and natural frequency. The proposed method monitors the dynamic process of the analog instrument with various inputs, such as sine signals and random signals, thereby enabling condition monitoring. Experimental prediction results show that the proposed estimation method is effective and robust.

Global shockwaves of the Hunga Tonga-Hunga Ha’apai volcano eruption measured at ground stations

The eruption of the Tonga volcano created globally propagating spherical shockwaves in the atmosphere. Analyses are done to data from two southern U.S. stations of the author sampling at 3-21s intervals and 189 weather stations at 1-5min intervals. The shockwaves arrived from two routes in the atmosphere: the shortest spherical arc and the longer spherical arc through the antipole. In most stations, signals up to the 6th path of shockwaves were recorded as the waves traveled around the globe multiple times. The speed of shockwaves is estimated to be 309.5± 2.9m/s, consistent with the speed of sound at the top of the troposphere where a waveguide exists. Discussion is made on the post-shockwave ringing of 4-8min as higher amplitude oscillations above the level of pre-shockwaves background noise. A theoretical wave dispersion is derived which verifies that the spherical shockwave's phase speed is the same as the speed of sound.

A Smart Alcoholmeter Sensor Based on Deep Learning Visual Perception.

Process automation, in general, enables the enhancement of productivity, product quality, and consistency alongside other production metrics. Liquor production on an industrial scale also follows the automation trend. However, small and medium producers lag with equipment modernization due to the high costs of industrial equipment. One of the important sensors in automation equipment for distilleries is the alcohol concentration sensor used for fraction separation, process automation, and supervision. This paper proposes a novel low-cost approach to alcohol concentration sensing by employing deep learning on the visual perception of traditional alcoholmeter. For purposes of the training model, dataset acquisition apparatus is developed and a large dataset of labeled images of alcoholmeter readings is acquired. The problem of reading alcohol concentration from an alcoholometer image is treated as a regression and classification problem. Performances of both regression and classification models were investigated with Resnet18 as an architecture of choice. Both models achieved satisfying performance metrics demonstrating the feasibility of the proposed approaches. The proposed system implemented on Raspberry Pi with a camera can be integrated into new distillation equipment. Additionally, it can be used for retrofitting existing equipment due to its non-invasive nature of reading. The scope of use can be further expanded to the reading of other types of analog instruments simply by retraining the model.

Instrument-Agnostizing Methodology for Liquid Chromatography-Mass Spectrometry Systems.

Mass spectrometry is a powerful analytical technique used to identify unknown compounds, to quantify known compounds, and to elucidate the structure and chemical properties of molecules. Nevertheless, the transfer of data from one instrument to another is one of the main problems, and obtaining the same or similar information from an analogous instrument but from a different manufacturer or even with the same instrument after carrying out the analyses in different times spacing is not possible. Hence, a general methodology to provide a chromatographic signal (or chromatogram) independent of the instrument is needed. In this sense, this book chapter describes the standardization procedure of chromatographic signals obtained from mass spectrometry platforms to obtain instrument-agnostic chromatographic signals for the determination of standard retention scores. This parameter may be used for the quantification of compounds when different mass spectrometry platforms coupled to ultrahigh-performance liquid chromatography are employed.

Face and content validity of analog surgical instruments on a novel physics-driven minimally invasive spinal fusion surgical simulator

Medical simulators are a modern-day technology that allow clinicians to acquire the skills and knowledge needed to perform complex surgical procedures. Validating these simulators is crucial prior to their integration in surgical training programs. However, surgical simulators are typically validated as a whole, without emphasizing validation of the instruments themselves. The purpose of this study was to design and validate analog surgical instruments for a novel, minimally invasive spinal fusion simulator. The surgical procedure was performed on cadavers and on a surgical simulator by experienced spine surgeons to compare and validate the analog instruments. Observations were made to assess the duration of each task and the participants' interaction with each instrument, judged by finger position and location. Immediately after the completion of the simulator trial, participants completed a questionnaire on a 5-point Likert scale. The duration of each task in the surgical procedure varied between participants and training platforms (cadaver versus simulator), while participants' interaction with the instruments was similar, regardless of the training platform. Questionnaire results yielded an average score of 3.7/5 for the instrument-related questions. Subsequently, face and content validity were established. The results suggest feasibility and value in independently validating the analog instruments used in simulator training.

An Integrated Risk Assessment Process of Safety-Related Digital I&C Systems in Nuclear Power Plants

Upgrading the existing analog instrumentation and control (I&C) systems to state-of-the-art digital I&C (DI&C) systems will greatly benefit existing light water reactors. However, the issue of software common cause failure (CCF) remains an obstacle in terms of qualification for digital technologies. Existing analyses of CCFs in I&C systems mainly focus on hardware failures. With the application and upgrading of new DI&C systems, design flaws could cause software CCFs to become a potential threat to plant safety, considering that most redundancy designs use similar digital platforms or software in their operating and application systems. With complex multilayer redundancy designs to meet the single failure criterion, these I&C safety systems are of particular concern in U.S. Nuclear Regulatory Commission licensing procedures. In Fiscal Year 2019, the Risk-Informed Systems Analysis (RISA) Pathway of the U.S. Department of Energy’s Light Water Reactor Sustainability Program initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades and designs. An integrated risk assessment for the DI&C process was proposed for this strategy to identify potential key digital-induced failures, implement reliability analyses of related digital safety I&C systems, and evaluate the unanalyzed sequences introduced by these failures (particularly software CCFs) at the plant level. This paper summarizes these RISA efforts in the risk analysis of safety-related DI&C systems at Idaho National Laboratory.

Study on Temperature Field Evolution and Frozen Wall Closure Judgment Criteria of Inclined Shaft under Inclined Holes Freezing Condition

A similarity experiment study is conducted to investigate the evolution characteristics of temperature field and frozen wall closure judgment criteria for the inclined shaft, under inclined holes freezing condition using an adjustable-angle freeze sinking analogous instrument. The changes of temperature and frozen wall thickness with the freezing time in the inclined shaft section, are recorded in real time, and the water pressure of axial and radial hydrological holes are measured. The results demonstrate that the soil temperature change can be divided into three stages under the conditions of salt-water temperature of -32°C and flow rate of 3.18 m/s: rapid cooling before reaching the freezing point, slow cooling in the process of freezing latent heat release, and accelerated cooling and stabilization after freezing latent heat release. The distance from the freezing pipe is the main factor affecting the freezing wall temperature. Affected by the arched arrangement of frozen pipes, the freezing speed in the position of arch crown and arch baseline is slower than the position of wall corner and base plate. A new judgment criterion of frozen wall closure based on the water pressure of the axial hydrological pipe is recommended. In all, this paper has an enlightenment significance for understanding the evolution of the soil temperature field, and predicting the frozen wall closure time in applications of the inclined holes freezing method for the inclined shaft.

Adoption of Blockchain Technology Based Accounting Platform

Accounting has always been influenced by digital technology, although most of it has been replacing analogue instruments with digital versions. A blockchain is a digital ledger that is used to record transactions between different participants in a network. It is an internet-based, peer-to-peer distributed ledger that contains all transactions since its inception. Blockchain technology has the potential to revolutionize the world humanity implementing in the business based on the concept of transmitting valuable digital assets like bitcoin without the need of a third-party intermediary. Blockchain is considered as a type of database or a sort of digital ledger, which is widely used by many financial organizations. It's a distributed ledger which keeps records of immutable and verifiable data. This blockchain technology permits decentralized ledger transactions to be produced without the intervention of a third party. Because of its decentralization, networks have a high degree of protection. The aim of the study is to investigate various decisions making factors, affecting in adopting blockchain technology in the field of accounting. The result showed that secure and private, transparent and auditable, immutable, better transparency, reduce cost, transparency, real-time transaction, and flexible are most likely influencing factors in adoption of blockchain technology. The result indicates that the Quorum, Sap Hana, and Ethereum, platforms are most consistent and trusted platforms for block chain technology and the blockchain platforms are found most suitable, secured and stronger platform.
 
 Received: 25 October 2021 / Accepted: 2 February 2022 / Published: 5 March 2022

ECG Generator for Educational Biomedical Engineering Laboratory

The aim of this work is to design and implement an ECG generator for didactic biomedical engineering laboratory. The proposed generator provides analog ECG signals using synthesized or experimental records. The technique used in this work consists to generate the desired ECG waveforms through the PWM outputs of an Arduino board and low-pass filter. To provide many educational functions in both analog instrumentation and digital processing, the generator supplies output voltages in asymmetric or differential mode. To allow the user to setup the ECG signal to be generated, a LabVIEW application has been implemented. Experimentations on proposed generator and results were accomplished using the NI USB 6009 acquisition module and NI MAX software.