Counting Machine Research Articles

Distribution and risk factors of Trichomonas vaginalis infection with relevance to interleukin profile among population in Duhok city, Iraq

BackgroundVaginal trichomoniasis is a sexually transmitted disease causes adverse health outcomes, the causative agent is Tichomonas vaginalis. Infected women develop abnormal vaginal discharge with vaginitis. While, men mostly suffer from prostatitis and urethritis. ObjectivesThis study aimed to detect the rate of T.vaginalis infection in association with risk factors, measurement of blood parameters, interleukine-2 (IL-2) and interleukine-8(IL-8) levels among individuals. MethodsA total of 500 females were tested, a vaginal swab and blood were collected from the participants, and they were within the age range of 18–70 years old. High vaginal swabs were examined microscopically using wet mount preparation, the blood used for measurement of blood parameters using coulter count machine and IL-2 and IL-8 levels were evaluated using ELISA technique. ResultsOut of 500 individuals, the prevalence of T. vaginalis infection was 45(9.0 %). The maximum infection rates were reported among age group (18–28) years, rural residents, illiterates, married women (16.7 %), (15.9 %),(30.0 %),(11.7 %),respectively. Moreover, high positivity of infection revealed among low economical level 12.5 % compared to only 1.7 % in high economy group. Unemployed women, those with bad vaginal hygiene showed high incidence of infection 10.5 % and 6.3 %, respectively. It was noted a significant decrease in red blood cells and hemoglobin concentration, however, there was a significantly increased in white blood cells among infected subjects. Furthermore, the levels of both interleukin-2 and interleukin-8 were significantly higher among infected individuals compared to healthy ones. ConclusionsEffective strategies for disease awareness are needed and should include health promotion, education, and prevention.

ВКЛАД ОТЕЧЕСТВЕННЫХ УЧЕНЫХ В РАЗВИТИЕ УСТРОЙСТВ ВЫЧИСЛИТЕЛЬНОЙ ТЕХНИКИ

The study reflected two stages of digital computing, when discrete counting devices and analog computers were created. (Research purpose) The research purpose is identifying the design features of computers in which the ideas of domestic scientists were implemented at the mechanical and electromechanical stages of the development of computer technology. (Materials and methods) Conducted a historical and scientific analysis of literary sources, original works of Russian scientists, descriptions of inventions and patents related to the mechanical and electromechanical stage of the development of computer technology. We studied materials from the Archive of the USSR Academy of Sciences, descriptions of serial computers manufactured in the USSR. (Results and discussion) We considered the outstanding role played by academician P.L. Chebyshev in the history of the construction of continuous counting machines. The design features of the adding machine created by V.T. Odner and further developments of adding machines by domestic engineers (adding machine "Soyuz") were presented. It was noted that with the invention of the Odner adding machine in 1890, the stage of serial production of computer equipment in Russia began. It was shown that in the field of analog computing, a significant contribution was made in the construction of hydraulic integrators by engineer V.S. Lukyanov; electrical integrators by academicians A.N. Krylov, I.S. Bruk. The first electronic analog computers were created at the Electrotechnical Institute of the USSR Academy of Sciences under the leadership of L.I. Gutenmacher. (Conclusions) The ideas and design features of mechanical and analog computing devices were reflected in the works of domestic scientists and engineers. We have traced the continuity in the creation of mechanical and electromechanical calculating machines. We have studied unique samples of computer technology, such as the integrator by A.N. Krylov, the hydraulic integrator by V.S. Lukyanov, the electrical integrators by I.S. Bruk, L.I. Gutenmacher, the electro-optical reading machine by engineer V.E. Agapov.

Enabling active visitor management: local, short-term occupancy prediction at a touristic point of interest

After the temporary shock of the Covid-19 pandemic, the rapid recovery and resumed growth of the tourism sectors accelerates unsustainable tourism, resulting in local (over-)crowding, environmental damage, increased emissions, and diminished tourism acceptance. Addressing these challenges requires an active visitor management system at points of interest (POI), which requires local and timely POI-specific occupancy predictions to predict and mitigate crowding. Therefore, we present a new approach to measure visitor movement at an open-spaced, and freely accessible POI and evaluate the prediction performance of multiple occupancy and visitor count machine learning prediction models. We analyze multiple case combinations regarding spatial granularity, time granularity, and prediction time horizons. With an analysis of the SHAP values we determine the influence of the most important features on the prediction and extract transferable knowledge for similar regions lacking visitor movement data. The results underline that POI-specific prediction is achievable with a moderate relation for occupancy prediction and a strong relation for visitor count prediction. Across all cases, XGBoost and Random Forest outperform other models, with prediction accuracy increasing as the prediction time horizon shortens. For effective active visitor management, combining multiple models with different spatial aggregations and prediction time horizons provides the best information basis to identify appropriate steering measures. This innovative application of digital technologies facilitates information exchange between destination management organizations and tourists, promoting sustainable destination development and enhancing tourism experience.

Design and Fabrication of Automated Counting Machine

Abstract: The design and fabrication of an automatic counting device specifically for wedges are presented in this work. The device effectively counts wedges in a variety of industrial processes by utilizing electronic control systems and precise engineering concepts. The design incorporates a user-friendly interface for smooth operation and sensors for precise detection. In order to assure dependable operation, fabrication entails programming embedded systems and assembling specialized components. For businesses producing wedges, the automated counting machine provides a workable way to improve efficiency and quality assurance.

تحســــين أداء آلــــة عـــد الأمـــــوال باستبدال المحرك التيار المتردد بمحرك تيار مستمر، مع دمج حساس الأشعة تحت الحمراء والأردوينو

In the implementation of a money counting mechanism for a money-counting machine, I attempted to control the machine by replacing its control panel with Arduino control. This allowed for monitoring the movement and counting of money, controlling its stopping and starting, and taking readings from its sensors to employ it as a money counting machine. The process was very successful and yielded impressive results despite encountering some problems that were resolved. Among these issues was the difficulty in controlling the AC motor responsible for the mechanical movement of pulling the money. It was replaced with a DC motor, which offered greater flexibility in terms of stopping, starting, and speed control. This was very beneficial in ensuring the process of determining the desired amount of money by the counting machine. Replacing the AC motor with a DC motor in the money counting machine and using it in this project was a unique experience. Despite continuous research on related topics, I found no one who had used this idea. The results were highly reliable and stable. The following will discuss the results and explain the process. Arduino was primarily used in this process, with movement control using a DC motor driver and the existing infrared sensors in the money counting machine, along with other sensors such as the currency denomination sensor and counterfeit detection sensor. These components will be listed in this paper to clarify the process and how satisfactory results were achieved. Keywords: Arduino-based control systems, DC motor technology, Cash counting machine,AC motor, Infrared sensors.

Evaluation of the Risk Associated with Drinkable Water Sources Through Analysis of Gross Alpha and Beta Radioactivity Levels in Chosen Locations, Mubi – North

Ionizing radiation refers to a form of radiation with sufficient energy to dislodge tightly bound electrons from atoms, resulting in the formation of ions. It encompasses alpha particles, beta particles, and gamma rays. Exposure to ionizing radiation, especially through ingestion, can have detrimental effects on living organisms, including humans. The primary goal of this research is to measure and analyze the levels of alpha and beta radiation in water samples, using the obtained results to evaluate radiation concentrations. Water samples were collected from five different locations within Mubi-North Metropolis and analyzed using a desktop Alpha/Beta counting machine or detector (MPC 2000B-DP). The analysis results present the alpha and beta radiation activities in each sample location. For example, alpha activities ranged from 0.009844 Bq/L to 0.1821 Bq/L, and beta activities ranged from 0.04922 Bq/L to 10.21 Bq/L across different locations. Sample D recorded the highest alpha effective equivalent dose of 0.037mSv/y, while the lowest dose of 0.002mSv/y was recorded from sample D. Sample C had the highest beta effective equivalent dose of 5.143mSv/y, and the lowest dose of 0.329mSv/y was recorded from sample E. Sample C also recorded the highest total effective dose of 516mSv/y, while the lowest dose of 0.34mSv/y was from sample E. Only sample D exceeded the recommended screening level of 0.1mSv/y for Alpha, and only sample E recorded the lowest effective dose of 0.329mSv/y below the screening limit of 1.0mSv/y, indicating potential cancer risk for all samples except sample E. In summary, the study concludes that alpha activities in all collected samples are below the recommended screening levels for drinking water radioactivity set by organizations such as EPA, WHO, and GEG-FAO. However, beta activities in the samples, except for the one from Federal Polytechnic Reservoir, surpass the recommended screening levels, suggesting a potential health risk for individuals consuming water from those sources. Overall, the research provides valuable insights into alpha and beta radiation levels in water samples from various locations in Mubi-North Metropolis, highlighting the safety of alpha levels but indicating potential hazards in beta radiation levels.

IR Sensor Optimization on Microcontroller-Based Coin Sorting and Counting Machine

The advancement of technology has greatly influenced every human task, where tasks that were once very time-consuming or laborious can now be easily and quickly accomplished thanks to technology. Take, for example, the activity of counting and sorting coins or tokens. If this activity were done in a traditional manner, which involves counting and separating each denomination, it would be very cumbersome and time-consuming. However, if the process of counting and sorting coins or tokens is done using technology, it can be easily and quickly completed. This research is conducted to analyze the performance optimization results on the IR sensor part of a coin sorting and counting machine that has been made based on a microcontroller. After several tests, it can be concluded that the machine can sort and count coins with denominations of 100, 200, 500, and 1000 rupiah. From 50 coins with four denominations, it can be inferred that the machine experienced an increase in accuracy in sorting coins from 98.6% to 99.6%. This increase in accuracy was achieved by optimizing the IR sensor, thus making the IR sensor readings more optimal.

Polymath Prof. Wilhelm Schickard (1592-1635): Inventor of the mechanical calculating machine and the world’s first academic UFO-witness and investigator

Dear Editor, with this letter I would like to point out the early results of my research into the so far little known UFO/UAP-sighting of one of the most famous German polymaths, contemporary and befriended astronomy-colleague of Johannes Kepler, Wilhelm Schickard (1592–1635). This sighting was so far undescribed even in most of UFO research literature. Not only holds the sighting itself many fascinating parallels to modern days UFO encounters; almost 400 years old, the account most likely represents the world’s first and earliest form of a detailed description and discussion of a UAP-sighting by a full and respected academic. The German government just honored Schickard with a special 20-Euro collector’s coin that celebrates the 400th anniversary of his invention of the first mechanical counting machine. Less known, if known at all, is the fact that Professor Schickard could be rightfully considered the first academic UFO/UAP researcher in history. The observation he encountered and described also set himself up for vehement criticism and outrage from his colleagues through his advocacy for the most precise description of the “miraculous sign” he observed and described in 1630.

Accurate COVID-19 detection using full blood count data and machine learning

COVID-19 has spread rapidly worldwide in the past three years, triggering partial and full lockdowns globally. The successful control of the COVID-19 pandemic on a global scale depended heavily upon the accurate detection of COVID-19. However, the main diagnostic tests for COVID-19 have some significant limitations, e.g. the major nucleic acid (RT-PCR) tests while having a high sensitivity are time-consuming and require expensive equipment with the shortage of test kits in many countries. Antigen lateral flow tests have a lower sensitivity and they cannot be used during the early pandemic as well as usually more expensive than the full or complete blood count test used in this paper which can be potentially performed using a finger blood sample. The last decade has seen rapid growth of AI, particularly deep learning, which has found wide applications in medical image analysis, with results comparable to and even surpassing human expert performance. There have been several machine learning models reported for COVID-19 diagnostics or prognosis predictions, most of them based on CT and X-ray images. In this paper we have applied traditional machine learning and convolutional neural networks (CNNs) based deep learning to the blood test data obtained from hematology analyzers and demonstrated that the AI models can be used to detect COVID-19 with a high degree of accuracy (>97%). The performance of different classifiers will be compared and discussed. The work should have potential applications in current COVID-19 and future pandemics.

Complete Blood Count and MDW-based Machine Learning Algorithms for Sepsis Detection: a Multicentric Development and External Validation Study (Preprint)

Complete Blood Count and MDW-based Machine Learning Algorithms for Sepsis Detection: a Multicentric Development and External Validation Study (Preprint)

Comparative Analysis of Mortality Predictions from Lassa Fever in Nigeria: A Study Using Count Regression and Machine Learning Methods

Comparative Analysis of Mortality Predictions from Lassa Fever in Nigeria: A Study Using Count Regression and Machine Learning Methods

Artificial Intelligence RBC Recognition Program for Schistocyte Screening in Cytopenic Patients

Schistocyte identification is critical for the diagnosis of thrombotic microangiopathies (TMA). It is one of the most common consultative problems for hematologists. The count of schistocytes is poorly defined by automated complete blood count (CBC) machines. Furthermore, morphological evaluation using peripheral blood smear (PBS) staining is time-consuming and exhibits high variability among inexperienced internists. Our aim is to develop and assess the effectiveness of an in-house AI program for recognizing schistocytes. In phase I of this study, we developed an AI program using deep convolutional neural networks trained from schistocyte in blood smear pictures total 1066 pictures of 1066 patients and divided into training set and validation set. In the training set, 10,377 schistocytes were identified, resulting in an accuracy of 0.76977, precision of 0.78487, recall (sensitivity) of 0.97562, and F1-score (harmonic mean of precision and recall) of 0.86991. And in the validation set, 3,564 schistocytes were identified, resulting in an accuracy of 0.68462, precision of 0.73850, recall (sensitivity) of 0.90370, and F1-score of 0.81279. Then, during phase II, PBS from 133 patients from hematology consultation service due to anemia and/or thrombocytopenia were included and scanned by an automated, cell-locating image analysis system. The program's effectiveness was validated by comparing its detection of an increased in schistocytes from patient glass slides (>1%) with the conclusion from at least two out of three hematologists who conducted conventional microscopy readings. The Cohen's kappa agreement between the AI and hematologist readings was 0.583 (p < 0.001), representing moderate agreement. There were 58 slides with schistocytes >1% as determined by AI reading, while 34 PBSs were identified as showing a significant increase in schistocytes by hematologists. The sensitivity and specificity of significantly increased schistocyte detection were 97.1% and 74.7%, respectively. Blood smears with significantly increased schistocytes detected by the program had positive predictive and negative predictive values of 43.1% and 93.3%, respectively. Poikilocytosis from thalassemic red cells were the most misinterpreted. In sum, the developed AI program for schistocyte detection showed high sensitivity and acceptable specificity, especially in high prevalence thalassemia populations, indicating its potential to assist inexperienced clinicians and reduce the need for hematologist consultations. Adding more schistocyte samples could improve the program's specificity and efficiency of TMA diagnosis in the future.

Development of smart Sorting and counting machine for industrial application

Development of smart Sorting and counting machine for industrial application

Cleaning validation of electronic counting machine with two different cleaning agents

Cleaning validation of electronic counting machine with two different cleaning agents

Increasing the accuracy of the process of automated counting of thin long products

Vibrating hopper feeders with an electromagnetic drive for automating the process of counting parts have become widely used. This process is necessary when transferring them to another workshop for the next technological operation. Also, it is necessary to count artificial products on the lot when packing them for packaging. Vibrating feeders are used to feed miniature, small, or medium-sized parts to the counting position of counting or packing machines. In this case, the parts supplied to these positions should be arranged in one layer. In addition, they should have a certain gap between them for reliable operation of the counting device. Basically, counters for such machines are made on the basis of photoelectric or inductive sensors. The disadvantage of inductive sensors is that they can only be used for metal objects. Photoelectric sensors are more versatile, so they have gained the most distribution for counting or filling machines. The principle of operation of the automatic counting position is that when the object to be counted is applied to it, it crosses the working area of the counting position and the sensor sends an impulse to the counting device. When using photoelectric sensors, parts or products cross the beam of the sensor and it supplies a counting pulse to the electronic counter at each crossing of the working beam. Basically, when using vibrating hopper feeders, the counting position is located either directly at the exit part of the transporting tray, or at the exit from it of the transported objects. The speed of transporting parts or products increases when moving up, because the amplitude of the horizontal component of oscillations increases when the diameter of the transporting tray increases. This is because the hopper of the vibratory feeder has a conical shape. This allows the parts to be refined in one layer. In addition, before the counting position, the parts must be separated from each other to create the necessary gap between them. This is necessary for the reliable operation of the photoelectric sensor. This system works reliably when the dimensions of the parts to be counted are larger than the diameter of the working beam of the sensor. But, when automating the counting of thin, long parts or products whose thickness is close to the size of the working beam of the sensor, the latter may cross it several times when passing through the zone of the counting position. This sharply reduces the accuracy of the counting process. This happens because the parts on the conveyor tray move with a small bounce due to the vertical component of the hopper's vibrations. Therefore, it became necessary to develop a new counting position system in order to increase the accuracy of the counting device for counting long thin parts or products (pins for electrical connectors, needles, matches, etc). The work considers a set of elements that affect the productivity and efficiency of counting devices based on vibrating hopper feeders with electromagnetic drives, for counting long thin parts or products of this shape.

PERANCANGAN SISTEM INFORMASI PENJUALAN TOKO ROTI ME TIME BERBASIS WEB

ABSTRACT: Technological developments mean that from time to time technology continues to develop in a more sophisticated direction. This development is based on human innovation and creativity, especially in the business field, many sales have been made on-line, this Me Time Bakery has not yet developed on-line sales, online developments or online stores through internet media have mushroomed in Indonesia, even already very well known by the general public. The number of various conveniences in shopping and the various types of products and services offered, make Indonesian people make online shops as one of the new "shopping places" besides shopping centers. this makes many online shop sellers competing to offer their products in various ways to attract consumers to shop, they take advantage of the situation where online shopping is currently in demand by the Indonesian people until now. The analysis of the old system at the Me Time Bakery is still manual by using a manual counting machine with a receipt system so that sales and purchases of stock items are re-corrected and recorded only on that day how many breads were sold, how many purchases and stock sales. To find out the availability of information products, with the Web-Based Me Time Bakery Sales Information System, it can facilitate the promotion process which has been conventional in nature. can use the application in accordance with accurate and good commands.

Count Regression and Machine Learning Techniques for Zero-Inflated Overdispersed Count Data: Application to Ecological Data

The aim of this study is to investigate the overdispersion problem that is rampant in ecological count data. In order to explore this problem, we consider the most commonly used count regression models: the Poisson, the negative binomial, the zero-inflated Poisson and the zero-inflated negative binomial models. The performance of these count regression models is compared with the four proposed machine learning (ML) regression techniques: random forests, support vector machines, k-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$k-$$\\end{document}nearest neighbors and artificial neural networks. The mean absolute error was used to compare the performance of count regression models and ML regression models. The results suggest that ML regression models perform better compared to count regression models. The performance shown by ML regression techniques is a motivation for further research in improving methods and applications in ecological studies.

COIN SORTING AND COUNTING MACHINE

The design was entitled Automatic Coin Sorting Machine for it is to sort the Indian coin denomination. This was done to be able to help different Institutions that deal with large number of coins in their daily operation. Some of these are banks, churches, charitable institutions and the transport sector. The sorting part of the design is basically mechanical as it sorts the coin through their physical size then counts them as they pass through the Arduino. An automatic coin counting and sorting machine prototype is developed by using ARDUINO-UNO as the main controller. This work included design the display panel to show total quantity of each coin and total amount. The coin acceptor has been used as it acts as coin selector to determine the denomination of coins in sorting system is designed by using DC motor to hold and distributes coin to the corresponding slot. Key Words: Denomination, coin slot, rotating plate, microcontroller

A comparison of platelet indices in children with urinary tract and tonsillitis infection

Introduction and Aim: Platelet indices are used as diagnostic markers in many diseases and disorders. Urinary tract infections and tonsillitis are common among children. In this study we aimed to investigate whether platelet indices could be used as a marker of UTI and tonsillitis in children. Materials and Methods: This study included 120 children aged between 1-10 years, who were divided into 3 groups (G1-G3). The group G1 included children suffering from UTI (n=40), G2 with only tonsillitis (n=40) and G3 only healthy children (n=40). UTI and tonsillitis were diagnosed based on different parameters including C - reactive protein, erythrocyte sedimentation rate and complete blood counts. The platelet indices (PLT count, MPV, PDW, PCT, P-LCR, P-LCC) were measured using an automatic CBC blood counting and analysis machine. Results: The results in this study showed a high significant increase in (127.22), (7.179), (0.122) platelet count, PDW % and PCT% respectively and non-significant increase of P-LCC count. The results also revealed a high significant decrease in values of MPV, PDW and P-LCR (2.210), (2.315) and (6.427) respectively. Conclusion: Our study suggests the platelet indices could be used as a diagnostic marker in diagnosing urinary tract infection and tonsillitis in children.

PENGEMBANGAN POTENSI MASYARAKAT DENGAN PENERAPAN TEKNOLOGI MESIN PENCACAH SAMPAH ANORGANIK DI KELURAHAN TANJUNG PINGGIR

This community service activity aims to train and assist the Tanjung Pinggir village community in developing community potential through the use of inorganic waste counting machine technology. This activity's target audience consists of ten people from the Tanjung Pinggir village community in Pematangsiantar city. This activity is trained and mentored through lectures, demonstrations, and exercises, which are supplemented by questions and answers. The lecture method is used to explain business concepts and theories that are based on technology. The demonstration method is used to explain a future technology work process. While the training method is used to practice technology-based media, the question and answer method allows participants to consult on media development problems. The enthusiasm of the participants, pangulu, and activity funds aided in the implementation of this activity. The participants did not have prior knowledge of technology, and there was limited time for training. Participants can benefit from this service activity by increasing participant business sales