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Young, C., N. Ravida, M. Rochford, and B. Durrant. "92 Sperm Cryopreservation in the Burmese Python (Python bivittatus) as a Model for Endangered Snakes." Reproduction, Fertility and Development 30, no. 1 (2018): 185. http://dx.doi.org/10.1071/rdv30n1ab92.
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The Burmese python (Python bivittatus) is listed as vulnerable by the International Union for Conservation of Nature (IUCN). Released pet Burmese pythons have detrimental effects on fauna native to southern Florida and are responsible for localised declines of several species in some parts of the Everglades National Park (IUCN, 2012; 10.2305/IUCN.UK.2012-1.RLTS.T193451A2237271.en). As part of an invasive species monitoring program, Burmese pythons were captured in the Florida Everglades and used as a model for the development of sperm cryopreservation protocols for endangered snakes. Sperm was collected by flushing the vas deferens postmortem and initial motility score (IMS; % motile × speed of progression2), plasma membrane integrity (IPL), and acrosome integrity (IAC) were recorded before cryopreservation. Sperm was extended in TEST-yolk buffer with final dimethyl sulfoxide (DMSO) or glycerol (GLY) concentrations of 8, 12, or 16%, or combinations of DMSO and GLY with final concentrations of 4:4, 6:6, or 8:8%. Sperm in 500 µL of extender was frozen in vials at 0.3°C/min to –40°C before storage in liquid nitrogen. For each treatment, triplicate vials from each of 3 males were thawed at 37°C for 90 s. Cryoprotectant was removed by centrifugation and the sperm pellet was resuspended in TCM-199+HEPES. Sperm was evaluated at 22°C immediately following resuspension (T0) and at 60 (T60) minutes. All data were expressed as a percentage of initial (%IMS, %IPL, and %IAC). The effects of freeze method on %IMS, %IPL and %IAC were analysed by ANOVA and Tukey’s HSD test. Freeze method significantly affected %IMS at T0 (P = 0.0004) and T60 (P = 0.0001), with sperm frozen in the 6%DMSO:6%GLY and 4%DMSO:4%GLY treatments resulting in the highest %IMS at both T0 (19.4% and 17.7%, respectively) and T60 (26.7% and 14.4%, respectively). Regardless of cryoprotectant concentrations, sperm frozen in a combination of DMSO and GLY exhibited significantly higher %IMS than all treatments of DMSO or GLY alone (P < 0.0001 at T0 and T60). The %IPL was significantly affected by freeze method at T0 (P < 0.0001) and T60 (P = 0.0266). Sperm frozen in 8%DMSO:8%GLY and 6%DMSO:6%GLY retained greater %IPL at both T0 (69.1% and 65.7%, respectively) and T60 (47.8% and 49.9%, respectively). Acrosome integrity was significantly affected by freeze method at T0 (P < 0.0001) and sperm frozen in 8% DMSO resulted in the greatest %IAC (56.4%). In addition, all DMSO and DMSO:GLY treatments preserved a significantly greater proportion of intact acrosomes than GLY alone (P < 0.0001). To simplify these analyses and to determine the best overall freeze method for this species, a sperm quality index (SQI) was calculated, giving equal weight to each of the 3 measured indicators of cryosurvival. The SQI analysis revealed that Burmese python sperm frozen at 0.3°C/min in either 6%DMSO:6%GLY or 4%DMSO:4%GLY exhibited significantly higher post-thaw viability at T0 and T60 than all other treatments. This study represents the first comparative, comprehensive attempt to develop a sperm cryopreservation protocol for any snake species.
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Helmstetter, Cécile, Robert K. Pope, Mathieu T’Flachebba, Stephen M. Secor, and Jean-Hervé Lignot. "The effects of feeding on cell morphology and proliferation of the gastrointestinal tract of juvenile Burmese pythons (Python molurus)." Canadian Journal of Zoology 87, no. 12 (December 2009): 1255–67. http://dx.doi.org/10.1139/z09-110.
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The gastrointestinal tract of Burmese pythons ( Python molurus (L., 1758)) exhibits large morphological and physiological changes in response to feeding and extended periods of fasting. In this study the mucosa of the stomach, small intestine, and colon were examined for changes in structure and cellular proliferation. The mucosa of fasting pythons exhibited low levels of cellular replication, but after feeding, cellular replication was evident as early as 12 h in the small intestine and colon and 24 h in the stomach. Replication peaked 3 days postfeeding for the small intestine and colon, but was still increasing at 6 days postfeeding in the stomach. Interestingly, cell proliferation was still evident after 45 days in the colon. In these tissues, a stock of “ready-to-use” primary lysosomes is found in the mucosal cells of fasting animals, whereas profound intracellular recycling is typical of animals that have been fed. These findings indicate that during the postprandial period, the intestinal mucosa undergoes extensive remodelling in anticipation of the next fasting and feeding period. One key adaptive factor for the python’s ability to cope with infrequent feeding is a well-prepared digestive system in fasting animals that can quickly start functioning again when food becomes available.
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Oikawa, K., H. Sato, K. Watanabe, Y. H. Su, T. Shinohara, T. Kai, Y. Kiyanagi, and H. Hasemi. "Update of Bragg edge analysis software “GUI-RITS”." Journal of Physics: Conference Series 2605, no. 1 (September 1, 2023): 012013. http://dx.doi.org/10.1088/1742-6596/2605/1/012013.
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Abstract The energy-resolved neutron imaging system, RADEN at J-PARC, has been providing to users a Rietveld-type analysis code, RITS, for pulsed neutron Bragg-edge transmission (BET) imaging with a graphical user interface (GUI) version, for fitting spectral data obtained with this instrument. In the last year, we updated the computational platform of GUI-RITS software from Scientific Linux 6 (SL6) and Python 2 to Windows 10 and Python 3, and added some functions to improve usability. The license agreement for this updated software is the Berkeley Software Distribution (BSD) 2-Clause License (non-copyleft) and is currently available for download from the RADEN website.
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Sembiring, Feby Wulandari. "MENGUKUR TINGKAT AKURASI 6 MODEL REGRESI DALAM MACHINE LEARNING UNTUK ESTIMASI PENYAKIT DIABETES." JURNAL TEKNISI 4, no. 1 (February 28, 2024): 23. http://dx.doi.org/10.54314/teknisi.v4i1.1805.
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Abstract: This research aims to develop a companion application that uses the regression method as a warning system for the public in maintaining blood sugar levels to minimize the risk of diabetes based on machine learning. Diabetes is one of the diseases with the highest death rate in Indonesia, but the public's low awareness of checking blood sugar levels regularly is due to the high cost of controlling it at hospitals or clinics. This has an impact on increasing the prevalence of diabetes and state losses. This research utilizes the linear regression method with 6 regression models and 3 testing methods to find the best and most accurate model in predicting diabetes levels. Data was processed using Jupyter Notebook tools with the Python programming language. It is hoped that the results of this research can contribute to increasing public awareness of the importance of maintaining healthy blood sugar to prevent diabetes.Keywords: machine learning; regression; diabetes; warning system. Abstrak: Penelitian ini bertujuan untuk mengembangkan sebuah aplikasi pendamping yang menggunakan metode regresi sebagai warning system bagi masyarakat dalam menjaga kadar gula darah untuk meminimalisir risiko diabetes berbasis machine learning. Diabetes merupakan salah satu penyakit dengan angka kematian tertinggi di Indonesia, namun rendahnya kesadaran masyarakat dalam memeriksa kadar gula darah secara berkala disebabkan oleh mahalnya biaya pengontrolan di rumah sakit atau klinik. Hal ini berdampak pada meningkatnya prevalensi diabetes dan kerugian negara. Penelitian ini memanfaatkan metode regresi linier dengan 6 model regresi dan 3 metode pengujian untuk mencari model yang paling baik dan akurat dalam memprediksi kadar diabetes. Data diproses menggunakan tools Jupyter Notebook dengan bahasa pemrograman Python. Hasil penelitian ini diharapkan dapat memberikan kontribusi dalam meningkatkan kesadaran masyarakat akan pentingnya menjaga kesehatan gula darah untuk mencegah diabetes.Kata Kunci: machine learning; regresi; diabetes; warning system.
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Nikandrov, A. A. "Multifunctional and flexible online platforms for creating educational materials." Informatics and education 37, no. 6 (January 21, 2023): 22–29. http://dx.doi.org/10.32517/0234-0453-2022-37-6-22-29.
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The article actualizes the need to use multifunctional flexible online platforms to promote educational activities, in particular the discipline “Machine Learning”. The main characteristic features of the discipline “Machine Learning” are described, the teaching of which consists in a task-based approach through writing program codes in a programming language, which is the Python 3 interpreter with a bundle of libraries selected: NumPy, Pandas, Matplotlib and Seaborn for data processing and visualization. The Scikit-learn library is used directly for machine learning. In addition to the Python 3 interpreter, coding tools are involved, namely: the PyCharm Community cross-platform development environment and the Jupyter Notebook open source web application. The potential of educational multifunctional flexible online platforms including designers of open online courses to facilitate independent learning of students is evaluated. According to the versions of various domestic and foreign scientific publications, the most mentioned online platforms are identified, their functionality regarding the placement of material in the fields of programming and machine learning was analyzed. Based on the analysis of the functional, a group of potential basic requirements for educational platforms in teaching programming within the discipline “Machine Learning” was identified, analyzed and discussed.
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Abidin, Zaenal. "PELATIHAN DASAR-DASAR ALGORITMA DAN PEMOGRAMAN UNTUK MEMBANGKITKAN MINAT SISWA-SISWI SMK PADA DUNIA PEMOGRAMAN." Journal of Social Sciences and Technology for Community Service (JSSTCS) 2, no. 2 (September 15, 2021): 54. http://dx.doi.org/10.33365/jsstcs.v2i2.1326.
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Salah satu jurusan yang ada SMK PGRI 1 Limau yaitu jurusan Multimedia. Kegiatan PKM khusus di jurusan Multimedia dilakukan adalah Pelatihan Dasar-dasar Algoritma dan Pemograman bagi siswa SMK PGRI 1 Limau. Pelatihan ini bertujuan agar membuka cakrawala awal dan ketertarikan mereka akan dunia programming. Materi pelatihan yang telah diberikan adalah (1) Pretest, (2) Sesi 1 : Bedah Potensi Dunia Kerja bidang Komputer, (3) Sesi 2 : Algoritma dan Pemograman Dasar Runtunan di Python, (4) Sesi 3 : Algoritma dan Pemograman Dasar tentang pencabangan di Python, (5) Sesi 4 : Algoritma dan Pemograman dasar tentang perulangan di Python, dan (6) Posttest. Pelaksanaan PKM Sekolah Binaan telah dilaksanakan dengan metode ceramah di kelas dan latihan pemogragraman di laboratorium komputer milik SMK PGRI 1 Limau. Secara umum kunjungan ke SMK PGRI 1 Limau 4 kali kunjungan sesuai dengan rincian dan jadwal kegiatan yang telah dibuat. Hasi pelatihan ini terlihat dari peningkatan nilai rata-rata siswa-siswi pretest yaitu Di awal pertemuan dengan siswa-siswi SMK PGRI 1 Limau, para peserta diberikan 10 soal essay yang jawabannya bersifat open answering dan closed answering. Delapan soal open answering dan dua closed answering. Pertanyaan dibuat sesuai dengan tingkat pengetahuan siswa-siswa SMK akan soal-soal mendasar dan sederhana tentang algoritma dan pemograman. Hasil pretest menunjukannya minimnya kemampuan awal mereka yaitu rata-rata siswa-siswi mampu menjawab 1.67 pertanyaan. Kemudian hasil posttest menunjukan nilai rata-rata siswa-siswi mampu menjawab 8.33 pertanyaan. Perningkatan kemampuan siswa dalam menyelesaikan posttest meningkat sebesar 66.67 %.
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Matisakov, Zh, Zh Mambetov, and Zh Matisakov. "Modeling the Determination of Wavelength Using a Diffraction Grating in Python." Bulletin of Science and Practice 10, no. 7 (July 15, 2024): 21–25. http://dx.doi.org/10.33619/2414-2948/104/02.
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To model a laboratory experiment for determining the wavelength of light using a diffraction grating in Python, it is proposed to use the libraries numpy, matplotlib, and ipywidgets. A simulation is created to model the positions of maxima on the screen. The developed code can be run in an environment that supports ipywidgets, such as Jupyter Notebook, to obtain an interactive simulation for determining the wavelength of light using a diffraction grating. The code includes the following steps: 1. Import the necessary libraries: numpy for numerical calculations, matplotlib for plotting graphs, ipywidgets for creating interactive widgets. 2. Define constants: d - the distance between the slits of the diffraction grating, L - the distance from the grating to the screen. 3. Create the function calculate_maxima to calculate the positions of the maxima. 4. Create the function plot_diffraction_pattern to plot the diffraction pattern. 5. Create interactive widgets: wavelength_slider to change the wavelength of light, order_max_slider to change the maximum order of the interference maxima. 6. Run the interactive simulation, which allows parameters to be adjusted and results to be observed in real-time.
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Pachpute, Rushikesh, Abhishek Jadhav, Aditya Shinde, Kaustubh Naik, and S. V. Gawai. "A Survey on “Medicines at Your Fingertips”." Data Analytics and Artificial Intelligence 3, no. 2 (February 1, 2023): 144–49. http://dx.doi.org/10.46632/daai/3/2/26.
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Medicines at Your Fingertips is a website aimed to provide all the information about any medicine, it’s side effects and all the other health related information. All the data of the medicines is stored in our database and it is fetched during the execution of user’s request. We have created the frontend using HTML, CSS, JS, JQUERY, JQUERY UI and Bootstrap. The Backend is built using Django Framework of Python. Our website contains 6 main components which are: Chatbot: An intelligent chatbot which will give any information that the user has asked. The AI chatbot is created using the Pytorch library of python. It will also help the user to navigate from the whole website. Drugs a to Z, a drug dictionary to give all the information about the desired medicine. There are 2 ways to search the medicine. Pill Finder: To search the medicine alphabetically or using the search bar Phonetic Search: To search the medicine using voice command. Drugs By Condition: It contains the information about all types of health conditions, their causes and treatment along with some medicines which are used to treat them. Side Effects: It also has alphabetically sorted medicines which gives the information about the side effects of the particular medicine along with a search bar. First Aid: This part consists of 3 components which gives the information about first aid treatments and My Med List to set reminders for the doses of your medicine.
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I Komang Setia Buana. "Implementasi Aplikasi Speech to Text untuk Memudahkan Wartawan Mencatat Wawancara dengan Python." Jurnal Sistem dan Informatika (JSI) 14, no. 2 (August 4, 2020): 135–42. http://dx.doi.org/10.30864/jsi.v14i2.293.
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Wawancara merupakan kegiatan komunikasi melalui proses pertukaran informasi antara reporter dan sumber berita. Banyak wartawan lebih sibuk mencatat pada saat wawancara sehingga hasil wawancara tidak efektif. Oleh karena itu dibutuhkan alat perekam untuk merekam jawaban dari narasumber. Akan tetapi alat perekam dibutuhkan waktu untuk mendengarkan hasil rekaman, kemudian mencatatnya. Padahal dituntut untuk mengumpulkan 3 sampai 4 berita dalam sehari. Dalam ilmu komputer terdapat bidang ilmu yaitu Speech to Text, teori ini akan bermanfaat untuk kondisi tersebut. Speech to text merupakan fitur untuk mengubah suara menjadi teks. Keunggulannya adalah layanan pengenalan suara. Speech to Text berfungsi untuk memanajemen waktu agar lebih efektif. Umumnya kecepatan berbicara dengan kecepatan mencatat berbeda. Sehingga hal tersebut menyulitkan wartawan yang bertugas. Disisi lain, teori ini akan sangat berguna bagi kaum disabilitas. Karena user atau pengguna hanya perlu menggunakan suara untuk melakukan aktivitas mengetik selayaknya orang normal pada umumnya. Dari permasalahan tersebut, dibuatkan aplikasi yang bisa mengubah suara ke dalam suatu teks/tulisan dengan menggunakan bahasa pemrograman Python. Untuk melakukan proses mengubah suara menjadi teks menggunakan modul speech recognition. Uji coba menggunakan 6 sample audio hasil rekaman, didapat bahwa dengan menggunakan bahasa pemrograman Python, mampu mengonversi suara ke tulisan dengan tingkat keberhasilan mencapai 94,75 %.
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Weise, Thomas. "Software - motipy: the Metaheuristic Optimization in Python Library." ACM SIGEVOlution 16, no. 4 (December 2023): 1–2. http://dx.doi.org/10.1145/3638461.3638464.
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We are thankful for the opportunity to announce our Python package "moptipy," which offers a rich set of tools for implementing, applying, and experimenting with metaheuristic optimization algorithms. Our package has been designed with benchmarking in mind and thus provides very comprehensive experimentation, data collection, and evaluation facilities out of the box. moptipy has the following features: 1. Very comprehensive documentation with many examples, reaching down to literature references inside the code and up to complex example experiments. 2. Several standard search spaces (bit strings, permutations, real vectors), operators, and algorithms, including randomized local search/hill climbers, simulated annealing, evolutionary algorithms, memetic algorithms, NSGA-II, several numerical optimization algorithms, etc., are already implemented and ready for use. 3. It is very easy to implement new algorithms using moptipy, be they general black-box methods or tailored for specific optimization problems. 4. It is also easy to integrate algorithms from external libraries and unify them under our API, which we did as proof-of-concept with CMA-ES, BOBYQA, as well as for the algorithms from SciPy. 5. Data can be collected at different verbosity levels, ranging from only providing the final result and its quality via the API (without creating any files) to creating log files with all (or all improving) steps of an algorithm, the result, the algorithm and problem parameters, the system setup, non-dominated solutions, and the random seed for fully-reproducible experiments. [1] 6. An experiment execution facility for very simple and robust parallel and distributed experimentation is provided. Parallelization and distribution works out-of-the-box based on shared folders and thus does not require additional libraries or programming effort [1]. 7. Stopping criteria for optimization processes can be defined based on goal solution qualities, clock time, and/or consumed objective function evaluations. 8. All experiments are fully reproducible, i.e., from a log file an algorithm and problem can be configured such that, in the replication experiment, exactly the same search steps are performed as in the original setting [1]. 9. The experiment evaluation facility can parse the log files and generate progress plots, result tables, ERT and ECDF plots, statistical test tables, and export data towards Excel or the popular IOHanalyzer. 10. Both single-objective and multi-objective optimization are supported under the same unified API. 11. The package has a good unit test coverage and pre-defined tools to unit test your own code. When implementing new objective functions, algorithms, encodings, oder operators, it is possible to use these tools to look for errors.
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Widaningrum, Ida, Dyah Mustikasari, Rizal Arifin, and Erika Dyah Cahyani. "Analisa Penggunaan K-Gram pada Karakter, Kata dan Kalimat untuk Mendeteksi Kesamaan Dokumen." Prosiding Seminar Nasional Teknoka 5 (December 20, 2020): 59–64. http://dx.doi.org/10.22236/teknoka.v5i.333.
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Pemanfaatan teknologi digital menjadi sebuah kebutuhan saat ini, salah satu komponennya berupa dokumen. Pendeteksian kesamaan bisa menggunakan berbagi macam cara, diantaranya adalah metode fingerprinting. Fingerprint memiliki prinsip kerja menggunakan teknik hashing dan K-gram. Penelitian ini difokuskan pada model deteksi menggunakan K-gram dengan menggunakan algoritma winnowing dan python sebagai bahasa pemrograman. Pengujian parsing k-gram menggunakan 5 buah k yaitu k=2 k=3 k=4 k=5 k=6. Hasilnya, parsing karakter mendapatkan presentase lebih besar dari presentase manual karakter. Presentase parsing kata, memiliki presentase yang paling mendekati dari presentase manual. Sedangkan pada kalimat, presentasenya paling rendah dari presentase manual
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Attwood, Ben, and James Robinson. "Performing Automated, High-Speed Photometry on Occulting, Small Outer Solar System Bodies." Edinburgh Student Journal of Science 1, no. 1 (July 4, 2024): 9–13. http://dx.doi.org/10.2218/esjs.9682.
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Monitoring stellar occultations provides a powerful means to measure the shapes and sizes of small Solar System bodies, but produces large quantities of image data which can be laborious to analyse. An automated Python-based software, occ_find, was written for performing high-speed aperture photometry on spool files packed with large volumes of images from the 1.54m Danish Telescope. occ_find processed 11 spool files at a maximum rate of around 4–6 minutes per spool file, without image reduction. From these files, 3 occultation events were detected. The measured chord lengths are consistent with prior size measurements of these small bodies.
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Kopei, Volodymyr B., Oleh R. Onysko, and Vitalii G. Panchuk. "Component-oriented acausal modeling of the dynamical systems in Python language on the example of the model of the sucker rod string." PeerJ Computer Science 5 (October 28, 2019): e227. http://dx.doi.org/10.7717/peerj-cs.227.
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Typically, component-oriented acausal hybrid modeling of complex dynamic systems is implemented by specialized modeling languages. A well-known example is the Modelica language. The specialized nature, complexity of implementation and learning of such languages somewhat limits their development and wide use by developers who know only general-purpose languages. The paper suggests the principle of developing simple to understand and modify Modelica-like system based on the general-purpose programming language Python. The principle consists in: (1) Python classes are used to describe components and their systems, (2) declarative symbolic tools SymPy are used to describe components behavior by difference or differential equations, (3) the solution procedure uses a function initially created using the SymPy lambdify function and computes unknown values in the current step using known values from the previous step, (4) Python imperative constructs are used for simple events handling, (5) external solvers of differential-algebraic equations can optionally be applied via the Assimulo interface, (6) SymPy package allows to arbitrarily manipulate model equations, generate code and solve some equations symbolically. The basic set of mechanical components (1D translational “mass”, “spring-damper” and “force”) is developed. The models of a sucker rods string are developed and simulated using these components. The comparison of results of the sucker rod string simulations with practical dynamometer cards and Modelica results verify the adequacy of the models. The proposed approach simplifies the understanding of the system, its modification and improvement, adaptation for other purposes, makes it available to a much larger community, simplifies integration into third-party software.
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ТУРКІН, Ігор, В’ячеслав ЛЕЗНОВСЬКИЙ, Андрій ЗЕЛЕНКОВ, and Вікторія ТУРКІНА. "МЕТОД КАЛІБРУВАННЯ АКСЕЛЕРОМЕТРІВ ДЛЯ ВІБРОДІАГНОСТИКИ ПРОМИСЛОВОГО ОБЛАДНАННЯ." Information Technology: Computer Science, Software Engineering and Cyber Security, no. 3 (June 19, 2023): 41–49. http://dx.doi.org/10.32782/it/2022-3-6.
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Предметом дослідження в статті є методика калібрування акселерометрів у складі цифрової платформи вібраційної діагностики промислового обладнання. Мета – підвищити інформативність процесів вібродіагностики промислового обладнання шляхом розробки та впровадження IoT-орієнтованих рішень на основі інтелектуальних датчиків та актуаторів за стандартом IEEE 1451.0-2007. Завдання: обґрунтувати доцільність використання платформено-орієнтованих технологій для вібраційної діагностики промислового обладнання та вибрати хмарний сервіс для реалізації платформи; розробити програмно-технічні рішення платформи IoT для вібраційної діагностики промислового обладнання; відкалібрувати систему вібродіагностики та перевірити точність вимірювань. Використані методи - мікросервісний підхід, багаторівнева архітектура та оцінка стану обладнання на основі даних про вібрацію. Ми отримали наступні результати. Розроблена та представлена в статті архітектура системи IoT для вібродіагностики промислового обладнання є трирівневою. Рівень автономних датчиків забезпечує зчитування індикаторів віброприскорення та передає дані на рівень Hub, який реалізований на базі одноплатного мікрокомп’ютера BeagleBone через цифровий бездротовий канал передачі даних BLE. Обчислювальна потужність BeagleBone забезпечує роботу з алгоритмами штучного інтелекту. На третьому рівні серверної платформи вирішуються задачі діагностики та прогнозування стану обладнання, для чого застосований алгоритм Dictionary Learning, реалізований мовою програмування Python. Перевірку методики калібрування акселерометра для вібраційної діагностики промислового обладнання проведено на унікальному стенді. Висновки. Коректна робота всієї системи підтверджується збігом очікуваних і виміряних результатів. На наступному етапі ми плануємо розробку додаткових мікросервісів, які забезпечать можливість використання методів аналізу часових рядів і сучасних технологій штучного інтелекту для комплексної діагностики та прогнозування стану обладнання.
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Ryzhkova, Yuliya E., Michail N. Elinson, Anatoly N. Vereshchagin, Kirill A. Karpenko, Fedor V. Ryzhkov, Ivan E. Ushakov, and Mikhail P. Egorov. "Multicomponent Electrocatalytic Selective Approach to Unsymmetrical Spiro[furo[3,2-c]pyran-2,5′-pyrimidine] Scaffold under a Column Chromatography-Free Protocol at Room Temperature." Chemistry 4, no. 2 (June 19, 2022): 615–29. http://dx.doi.org/10.3390/chemistry4020044.
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Electrochemical synthesis suggested a mild, green and atom-efficient route to interesting and useful molecules, thus avoiding harsh chemical oxidizing and reducing agents used in traditional synthetic methods. Organic electrochemistry offers an excellent alternative to conventional methods of organic synthesis and creates a modern tool for carrying out organic synthesis, including cascade and multicomponent ones. In this research, a novel electrocatalytic multicomponent transformation was found: the electrochemical multicomponent assembly of arylaldehydes, N,N′-dimethylbarbituric acid and 4-hydroxy-6-methyl-2H-pyran-2-one in one pot reaction was carried out in alcohols in an undivided cell in the presence of alkali metal halides with the selective formation of substituted unsymmetrical 1′,3′,6-trimethyl-3-aryl-2′H,3H,4H-spiro[furo[3,2-c]pyran-2,5′-pyrimidine]-2′,4,4′,6′(1′H,3′H)-tetraones in 73–82% yields. This new electrocatalytic process is a selective, facile and efficient way to obtain spiro[furo[3,2-c]pyran-2,5′-pyrimidines]. According to screening molecular docking data using a self-made Python script in Flare, all synthesized compounds may be prominent for different medical applications, such as breast cancer, neurodegenerative diseases and treatments connected with urinary tract, bones and the cardiovascular system.
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Brata, I. Wayan, Kadek Oky Sanjaya, and Ida Ayu Utari Dewi. "Implementasi Metode WASPAS pada SPK Berbasis Python dalam Pemilihan Karyawan Berprestasi pada LPD Desa Adat Penatih." RESI : Jurnal Riset Sistem Informasi 2, no. 2 (January 28, 2024): 148–61. http://dx.doi.org/10.32795/resi.v2i2.4106.
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Penilaian kinerja karyawan merupakan aspek penting dalam SDM yang harus mampu menyeimbangkan hasil kinerja dengan kemampuan dan pengalaman karyawan, meninjau hasil kerja, memahami kecenderungan perilaku, dan menyeimbangkan target kerja dengan tujuan bisnis. Untuk efektivitas pengambilan keputusan yang sering kali berhadapan dengan banyaknya kriteria dan pilihan karyawan berprestasi, maka digunakan bantuan SPK dalam penentuan karyawan berprestasi di LPD Desa Adat Penatih. Penelitian ini menggunakan metode WASPAS. Penelitian ini menggunakan 8 kriteria yaitu kualitas dan kuantitas kerja, efektivitas kinerja, kepemimpinan, disiplin, komunikasi, kerjasama, absensi serta kekurangan target. Penelitian ini menggunakan 10 karyawan sebagai alternatif pilihan. Hasil dari penelitian ini adalah perhitungan manual menggunakan metode WASPAS untuk pemberian rekomendasi karyawan berprestasi untuk LPD Desa Adat Penatih, perhitungan akurasi dan hasil penerapan menggunakan python. Berdasarkan 8 kriteria yang telah disediakan, pembobotan terbesar padaa kriteria kualitas kerja yang mencapai 18,25%. Karyawan berprestasi yang direkomendasikan berprestasi adalah IGK Suryantara yang mendapatkan nilai sebesar 0,95236. Akurasi mencapai 100% pada rekomendasi 3 teratas, dan menjadi 80% pada rekomendasi 4,5, dan 6 teratas. Penerapan menggunakan pyhton telah berhasil dilaksanakan dengan baik. Secara menyeluruh, penelitian ini telah berhasil dilaksanakan dengan baik.
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Fuller, Thomas F., and Leshinka Molel. "(Invited) Application of Open-Source, Python-Based Tools for the Simulation of Electrochemical Systems." ECS Meeting Abstracts MA2023-01, no. 25 (August 28, 2023): 1630. http://dx.doi.org/10.1149/ma2023-01251630mtgabs.
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There is a rich history of mathematical modeling of electrochemical systems. These simulations are useful 1) to refine our understanding of systems that contain complex, coupled phenomena, 2) to design and control electrochemical devices, and 3) to help novices in developing confidence and intuition for the behavior of electrochemical systems. Regardless of the application, cyclic voltammetry, storage batteries, secondary current distributions, or corrosion to name a few, elucidating the relationship between current and potential is central to understanding how electrochemical systems behave. Here, we report on historical and future perspectives of simulating electrochemical systems with open-source, python-based tools. The presentation includes a tutorial of the formulation of problems based on underlying engineering and electrochemistry principles. Within R1 universities in the United States, excellent resources are available at little to no cost for the simulation of electrochemical systems. However, the price for these tools can be prohibitive for most engineers and scientists working in industry. Access to these tools is even worse in low- and lower-middle-income countries. Actively supporting open-source software promotes a more inclusive scientific and research community that is essential to confronting the challenges facing society. Python was chosen because it is open-source. FEniCSx, a popular open-source computing platform for solving partial differential equations,1-2 is applied to the solution of primary and secondary current distributions for two- and three-dimensional geometries. FEniCSx is used on both desktop computers as well as within high performance computing environments, such as Georgia Tech’s PACE. Simulations have long been known to increase interactions between instructors and teachers as well as to help students visualize content.3-4 Recently, tools developed in python have been applied to simple electrochemical systems. 5-6. Because of the low barrier to entry and access to numerous computational packages, such as numpy, matplotlib, and scipy, the Anaconda distribution of python is promoted. A series of dynamic simulations are designed to help students improve their understanding of electrochemical systems. These simulations feature animation and extensive use of widgets that allow students to adjust parameters and immediately observe the results. A. Logg, K. A. Mardal, G. N. Wells. Automated solution of differential equations by the finite element method, Lecture Notes in Computational Science and Engineering, 84 LNCSE (2012). A, Logg and G. N. Wells. DOLFIN: Automated finite element computing, ACM Transactions on Mathematical Software, 37.2 (2010). T. de Jong, W. R. van Joolingen, Scientific Discovery Learning with Computer Simulations of Conceptual Domains, Review of Educational Research, 68, 179-201 (1998). R. E. West, C. R. Graham, Five Powerful Ways Technology Can Enhance Teaching and Learning in Higher Education, Educational Technology, 45, 20-27 (2005). X. Wang, Z. Wang, Animated Electrochemistry Simulation Modules, J. Chem. Educ., 99, 752-758 (2022). T.F. Fuller, J.N. Harb, Using Python Simulations for Inquiry-Based Learning of Electrochemical Systems, ECS Meeting Abstracts, (2021). DOI 10.1149/MA2021-02511503mtgabs
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Pakhomova, V., and A. Vydish. "Study of the combined variant of determination of attacks using neural network technologies." System technologies 3, no. 140 (April 8, 2022): 79–86. http://dx.doi.org/10.34185/1562-9945-3-140-2022-08.
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The modern world is impossible to imagine without computer networks: both local and global; therefore, the issue of network security is becoming increasingly topical. Currently, methods of detecting attacks can be strengthened by using neural networks, which confirms the relevance of the topic. The aim of the study is a comparative analysis of the quality parameters of network attacks using a combined variant consisting of different neural networks. As research methods used: neural network; multilayer perceptron; Kohonen's self-organizing map. The software implementation of the Kohonen self-organizing map is carried out in Python with a wide range of modern standard tools, creation of a multilayer perceptron and a fuzzy network - using Neural Network Toolbox packages, and Fuzzy Logic Toolbox system MatLAB. On the created neural networks separately and on their combined variant researches of parameters of quality of definition of network attacks are carried out. It was determined that the error of the first kind was 11%, 4%, 10% and 0%, the error of the second kind - 7%, 6%, 9% and 6% on the fuzzy network, multilayer perceptron, self-organizing Kohonen map and their combined version, respectively, which proves the feasibility of using the combined option.
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Hafizh Achmad Dinan, Youllia Indrawaty N, and Kurnia Ramadhan Putra. "Sistem Pembelajaran Hukum Baca Al-Qur’an Menggunakan Algoritma LPC dan KNN." Systemic: Information System and Informatics Journal 6, no. 1 (January 25, 2021): 29–37. http://dx.doi.org/10.29080/systemic.v6i1.927.
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Seorang muslim harus dapat membaca ayat-ayat Al-Quran dengan baik sesuai yang diajarkan oleh Rasulullah saw. Membaca Al-Quran sesuai ilmu tajwid hukumnya wajib bagi setiap orang muslim, apabila seseorang membaca Al-Quran dengan tidak memakai tajwid, hukumnya berdosa. Pengembangan Aplikasi Pembelajaran Tajwid Al-Qur’an ini bertujuan untuk membantu seorang muslim agar pandai membaca al-Qur’an yang baik dan benar. Surat yang di pakai dalam aplikasi ini adalah surat Al-Fatihah. Aplikasi Pembelajaran Tajwid Al-Qur’an menggunakan Bahasa pemrograman Python dengan metode Linear Predictive Coding (LPC) sebagai ekstraksi ciri suara dan metode K-Nearest Neigbor sebagai pencocokan denan data latih. Untuk pengujian pengucapan ayat ke-1 didapatkan akurasi data sebesar 83.3%, ayat ke-2 sebesar 86.7%, ayat ke-3 sebesar 85%, ayat ke-4 sebesar 80%, ayat ke-5 sebesar 88.3%, ayat ke-6 sebesar 93.3%
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Kurniadewi, Herwinda, Rijal Abdul Hakim, Mohamad Jajuli, and Jajam Haerul Jaman. "Pemetaan UMKM dalam Upaya Pengentasan Kemiskinan dan Penyerapan Tenaga Kerja Menggunakan Algoritma K-Means." Journal of Applied Informatics and Computing 6, no. 2 (August 30, 2022): 113–19. http://dx.doi.org/10.30871/jaic.v6i2.4227.
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Pandemi Covid menciptakan krisis ekonomi. Meningkatkan angka kemiskinan sebanyak dua digit dalam satu tahun di Indonesia. Pandemi Covid juga berdampak terhadap kondisi ketenagakerjaan Indonesia seperti mulai sulit mencari pekerjaan. Penyerapan tenaga kerja memiliki korelasi yang erat dengan kemiskinan. Tenaga kerja mempunyai pengaruh yang signifikan terhadap tingkat kemiskinan salah satu Kabupaten di Jawa Barat yang memiliki angka kemiskinan dan pencari tenaga kerja yang cukup tinggi meningkat dibanding tahun sebelumnya adalah Kabupaten Purwakarta. Pengentasan kemiskinan dengan mengembangkan UMKM memiliki potensi yang cukup baik. Pengembangan UMKM akan dapat menyerap lebih banyak tenaga kerja dan meningkatkan pendapatan masyarakat sehingga dapat mendorong laju pertumbuhan ekonomi. Dalam Penelitian ini menggunakan metodologi CRISP-DM. Pada penelitian ini dilakukan pengelompokan UMKM di Kabupaten Purwakarta berdasarkan lokasi, jumlah UMKM, jumlah penduduk miskin dan jumlah pencari kerja dengan menggunakan algoritma k-means dan dilakukan pemetaan menggunakan bahasa pemrograman python. Hasil pengelompokkan didapatkan 3 cluster yaitu cluster prioritas tinggi yaitu sebanyak 6 kecamatan, cluster prioritas rendah sebanyak 8 kecamatan dan cluster prioritas rendah sebanyak 3 kecamatan. Untuk mengetahui performa dari model, dilakukan evaluasi silhouette coefficient yang didapatkan nilai sebesar 0.45
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Guyard, Kévin Cédric, Stéphane Montavon, Jonathan Bertolaccini, and Michel Deriaz. "Validation of Alogo Move Pro: A GPS-Based Inertial Measurement Unit for the Objective Examination of Gait and Jumping in Horses." Sensors 23, no. 9 (April 22, 2023): 4196. http://dx.doi.org/10.3390/s23094196.
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Quantitative information on how well a horse clears a jump has great potential to support the rider in improving the horse’s jumping performance. This study investigated the validation of a GPS-based inertial measurement unit, namely Alogo Move Pro, compared with a traditional optical motion capture system. Accuracy and precision of the three jumping characteristics of maximum height (Zmax), stride/jump length (lhorz), and mean horizontal speed (vhorz) were compared. Eleven horse–rider pairs repeated two identical jumps (an upright and an oxer fence) several times (n = 6 to 10) at different heights in a 20 × 60 m tent arena. The ground was a fiber sand surface. The 24 OMC (Oqus 7+, Qualisys) cameras were rigged on aluminum rails suspended 3 m above the ground. The Alogo sensor was placed in a pocket on the protective plate of the saddle girth. Reflective markers placed on and around the Alogo sensor were used to define a rigid body for kinematic analysis. The Alogo sensor data were collected and processed using the Alogo proprietary software; stride-matched OMC data were collected using Qualisys Track Manager and post-processed in Python. Residual analysis and Bland–Altman plots were performed in Python. The Alogo sensor provided measures with relative accuracy in the range of 10.5–20.7% for stride segments and 5.5–29.2% for jump segments. Regarding relative precision, we obtained values in the range of 6.3–14.5% for stride segments and 2.8–18.2% for jump segments. These accuracy differences were deemed good under field study conditions where GPS signal strength might have been suboptimal.
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Urban, Gregor, Christophe N. Magnan, and Pierre Baldi. "SSpro/ACCpro 6: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, deep learning and structural similarity." Bioinformatics 38, no. 7 (February 2, 2022): 2064–65. http://dx.doi.org/10.1093/bioinformatics/btac019.
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Abstract Motivation Accurately predicting protein secondary structure and relative solvent accessibility is important for the study of protein evolution, structure and an early-stage component of typical protein 3D structure prediction pipelines. Results We present a new improved version of the SSpro/ACCpro suite of predictors for the prediction of protein secondary structure (in three and eight classes) and relative solvent accessibility. The changes include improved, TensorFlow-trained, deep learning predictors, a richer set of profile features (232 features per residue position) and sequence-only features (71 features per position), a more recent Protein Data Bank (PDB) snapshot for training, better hyperparameter tuning and improvements made to the HOMOLpro module, which leverages structural information from protein segment homologs in the PDB. The new SSpro 6 outperforms the previous version (SSpro 5) by 3–4% in Q3 accuracy and, when used with HOMOLPRO, reaches accuracy in the 95–100% range. Availability and implementation The predictors’ software, data and web servers are available through the SCRATCH suite of protein structure predictors at http://scratch.proteomics.ics.uci.edu. To maximize comptatibility and ease of use, the deep learning predictors are re-implemented as pure Python/numpy code without TensorFlow dependency. Supplementary information Supplementary data are available at Bioinformatics online.
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MARSUKI, AMINAH INDAHSARI. "The Performance of Visible Light Communication Bit Error Rate with Power Allocation Strategy." [CEPAT] Journal of Computer Engineering: Progress, Application and Technology 1, no. 01 (May 31, 2022): 1. http://dx.doi.org/10.25124/cepat.v1i01.4818.
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Visible Light Communication (VLC) is a communication system that uses visible light as its transmission medium to transmit information signals with Light Emitting Diode (LED) and LASER light sources using visible light between 400 THz (375 nm) to 800 THz (780 nm). VLC has several advantages over the use of radio frequencies in a system. Performance analysis is needed to prove these advantages. Performance analysis was carried out using a mathematical computational simulation using google colab with the python programming language. By taking into account the power allocation (?) strategy in the form of gain ratio power allocation (GRPA) and static power allocation (SPA). The interesting thing from this research is that the power allocation in the VLC system greatly influences the resulting performance. So, it can be locked that the SPA power allocation strategy can be adjusted by producing ?? = 1 and finding the optimal BER value in the range of 10-6 to 10^-3.
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Sopany, Mitchell Ryu, Dyah Erny Herwindiati, and Janson Hendryli. "Prediksi Kelembapan Tanah Pada Tingkat Kecamatan di Wilayah Bogor Dengan Metode CNN LSTM." Computatio : Journal of Computer Science and Information Systems 6, no. 1 (June 9, 2022): 1. http://dx.doi.org/10.24912/computatio.v6i1.15740.
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Kelembapan tanah pada kecamatan di wilayah Bogor perlu diperhatikan sebagai acuan sumber air bersih untuk mencukupi kebutuhan air bersih yang tinggi di wilayah Jakarta. Aplikasi prediksi kelembapan tanah dibuat menggunakan bahasa pemrograman Python dengan metode CNN LSTM bertujuan untuk memprediksi kelembapan tanah pada tingkat kecamatan wilayah Bogor dalam kelompok kelembapan tanah tinggi, kelembapan tanah rendah, dan kering menggunakan data citra satelit Landsat 8. Citra satelit Landsat 8 dilakukan preprocessing dengan transformasi menjadi bernilai 8 bit dan pemotongan tiap kecamatan dalam wilayah Bogor terhadap band 2, 3, 4, 5, 6, dan 7. Prediksi kelembapan tanah dilakukan menggunakan metode CNN lSTM dengan input berupa nilai kelembapan tanah menggunakan nilai NDVI citra satelit Landsat 8. Output berupa citra prediksi kelembapan tanah yang dikelompokkan pada kelembapan tanah tinggi, kelembapan tanah rendah, dan kering. Hasil penelitian menunjukkan model prediksi kelembapan tanah memiliki nilai rata-rata R2 Score 0.7422, MAE 0.0798, dan MSE 0.0416 sehingga model dapat memprediksi kelembapan tanah dengan baik.
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Bukreeva, A. S., K. A. Malsagova, A. A. Izotov, A. V. Lisitsa, and A. L. Kaisheva. "BioVitrina web repository — access to data on bioresource collections." Cardiovascular Therapy and Prevention 22, no. 11 (December 10, 2023): 3720. http://dx.doi.org/10.15829/1728-8800-2023-3720.
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Aim. To develop the BioVitrina web repository for visualizing data on biological samples available in the organization (https://bb.ibmc.msk.ru).Material and methods. The following set of tools was used: PostgreSQL 12, Python 3.8 scripting language, Django 3.2.7, Angular 12.2.13, Nginx, Docker 3, Redis 6.Results. Biological samples are systematized according to the International Classification of Diseases, 10th revision (ICD-10). After selecting the most suitable biosamples, the User has the opportunity to submit a request for their receipt. A necessary condition for obtaining biological samples is the subsequent publication of the results of experimental studies in the BioVitrina web repository. Such an exchange of analytical research results will avoid repetition of similar studies and will contribute to the conservation of material resources.Conclusion. "BioVitrina" was developed to optimize the infrastructure of biobanks of organizations and ensure the availability of information about their existing bioresource collections. This will solve many issues related to the use of different types of biomaterials, both for research and clinical purposes in personalized biomedicine.
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МАНОЙЛЕНКО, О. П., К. Р. КАЛІНІНА, Ю. О. ЛЕБЕДЕНКО, and М. А. ДІДИК. "ІНТЕЛЕКТУАЛЬНІ СИСТЕМИ УПРАВЛІННЯ МЕХАТРОНИМИ СИСТЕМАМИ ТИПУ "COBOT" З ВИКОРИСТАННЯМ ML-ТЕХНОЛОГІЙ." Technologies and Engineering, no. 6 (February 5, 2024): 31–40. http://dx.doi.org/10.30857/2786-5371.2023.6.3.
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Мета. Роботи є дослідження та розроблення конструкції руки-маніпулятора, його мехатронної системи та програмного керування, з особливим акцентом на розгорнутій кінематиці біонічної кисті руки типу "Cobot" [1, 2]. Вдосконалення методів управління мехатронними системами та розроблення алгоритмів системи керування для створення інноваційної системи управління рукою-маніпулятором типу "Cobot", заснованої на ML-технологіях машинного зору та платформі Arduino.
Розробка керуючих алгоритмів на мові програмування Python та їх інтеграція з Arduino, використовуючи стандартні фреймворки: "CV2", "МediaРipe", "Numpy" та "Serial" [3–6]. Кодування біомеханічних суглобів для застосування в комп'ютерному імітаційному моделюванні та дистанційному керуванні з використанням технологій штучного зору.
Методика. Методика дослідження включала в себе використання математичних методів для аналізу кінематики біонічної кисті руки та розрахунку координат та кінематики механічної системи. Розробка програмних алгоритмів керування базувалася на мові програмування Python. Для оптимізації коду застосовані стандартні фреймворки: "CV2", "МediaРipe", "Numpy" та "Serial". Також використовувалася інтеграція програмного забезпечення з мікроконтролером Arduino для управління мехатронічною системою.
Результати. Розроблено інноваційну систему керування на базі руки-маніпулята типу "Cobot", яка реагує на рухи та жести кисті руки перед web-камерою. Розроблена блок-схема взаємодія електронних та електромеханічних пристроїв блоку керування кисті руки-маніпулятора "Cobot". Реалізовано керуючі алгоритми, які можуть застосовуватися в різних галузях машинобудування, включаючи медицину, промисловість та область доповненої та віртуальної реальності. Представлені алгоритми для розпізнавання жестів, розширюючи можливості використання методів машинного навчання в різних галузях. Наведені залежності кінематики пальців біонічної кисті руки типу "Cobot".
Практична значимість. Отримані результати вказують на потужний потенціал використання інтелектуальних систем управління мехатронними пристроями. Система може бути застосована в медицині, промисловості та області доповненої та віртуальної реальності. Робота сприяє розвитку наукових платформ і є корисною для подальших досліджень у сфері мехатроніки та інтелектуального управління.
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Hendrizal, A., P. E. Plaimo, Y. Harjoyudanto, and M. Fauzi. "Clustering Lakes in Kampar by Using Morphometry Data and Machine Learning Analysis." IOP Conference Series: Earth and Environmental Science 934, no. 1 (November 1, 2021): 012078. http://dx.doi.org/10.1088/1755-1315/934/1/012078.
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Abstract Lakes have an important role in hydrological and biochemical cycle. It also has some other crucial role such as domestic and industrial water use as well as irigation. The monitoring and management of this aquatic resources is crucial. But with many numbers of lakes, it is very challenging to manage them all. Clustering lakes can provide the answer so the management of the same cluster lakes may be done efficiently. Within this study, morphometry data of 6 lakes in Kampar Regency, Riau Province, were analyzed by using one of artificial intelligence branch which is machine learning. Morphometrical data are collected by using information geographic system. These data then categorized by using python language. This categorization based on data mining categorization algorithm named K-means. Based on the K-means machine learning clustering, the optimum cluster based on Elbow methid is k=3. But there is a possibility to look around for k=2. Based on K=3, cluster 3 is defined as the lowest values of all atribute. Based on k=2, the lowest value of morphometry data wiil be in the cluster 1.. These data will not only provide basic data such as total area, shape, width and length, but also help to understand the large scale hydrological models.
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Tynterova, A. M. "Immunological status of patients in the acute period of ischemic stroke." Russian neurological journal 29, no. 3 (July 24, 2024): 24–31. http://dx.doi.org/10.30629/2658-7947-2024-29-3-24-31.
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The purpose of this study was to assess immunological status and correlations of cytokines of diff erent groups in patients in the acute period of ischemic stroke (IS). Material and methods. 80 patients with IS (treatment group) and 20 patients with cardiovascular diseases (control group) were examined. All patients were assessed for comorbidity, cognitive function and demographic characteristics. The following were assessed in patients with IS: IS subtype, functional status using Barthel Index (BI), Ranking scale (mRS), National Institutes of Health Stroke Scale (NIHSS), neuroimaging parameters. Laboratory diagnosis included assessment of serum concentrations of interleukins, interferons, CXC- and CC-chemokines, MIF, GM-CSF and TNF-α. Statistical analyses were performed using Python and its libraries Pandas and SciPy. Results. Higher levels of IFN-γ, CXCL1, and CCL23 were determined in patients with IS. CXCL1 was found to correlate with BI, NIHSS, MoCA, foci size; IL — 6 — with BI, NIHSS, presence of diabetes, overweight; IFN-γ — with hyperlipidemia, BI, NIHSS. CCL23 levels were associated with mRS at day 14, presence of atherosclerosis, atherothrombotic subtype of IS; CCL2 — with BI, presence of atherosclerosis, leukoaraiosis, and hypertension; CXCL8 — with MoCA, NIHSS, diabetes. Conclusion. The research of the level and differential expression of cytokines in patients in the acute period of IS is an actual direction of clinical medicine. The verifi cation of cytokines CXCL1, CXCL8, CCL23, CCL2, IL-6 and IFN-γ as potential biomarkers of severity, course and outcomes of AI requires clarifi cation through further studies.
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Yang, Junru, Tongle Zhang, Chuijiang Kong, Boyu Sun, and Ran Zhu. "Application of Python-Based Abaqus Secondary Development in Laser Shock Forming of Aluminum Alloy 6082-T6." Micromachines 15, no. 4 (March 25, 2024): 439. http://dx.doi.org/10.3390/mi15040439.
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Aluminum alloy 6082-T6 is an important material for manufacturing the outer skin of high-speed trains, and laser shock forming can realize the rapid forming of complex-shaped plates. In order to improve the efficiency of the simulation modeling of laser shock forming for aluminum alloy 6082-T6, Python scripting language was used for the secondary development of Abaqus. A plugin was utilized to simulate and analyze the laser shock forming process of aluminum alloy 6082-T6. The coordinates of the plate after laser impact molding were measured using a coordinate measuring machine to calculate the arc bow height of the plate. The accuracy of the simulation model was verified by comparing with the simulation results. The deformation characteristics of plastic strain and arc height of aluminum alloy 6082-T6 under different laser process parameters were analyzed. The simulation plugin has a concise interface, high operability, and accurate results with the other parameters unchanged. When the laser energy is 5 J, 6 J, and 7 J, the corresponding arc heights are 5.9 mm, 6.6 mm, and 7.2 mm, respectively. As the thickness of the sheet increases, the deformation changes from concave at 1 mm to convex at 2 mm, 3 mm, 4 mm, and 5 mm. As the spot size increases from 1 mm to 5 mm, the transmission mode of the shock wave gradually changes from spherical wave to planar wave, and the arc height of the sheet increases from 4.6 mm to 8.2 mm. With the increase in the spot overlap rate, the impact area accumulates residual stress, and the arc height of the sheet is 5.7 mm, 6.6 mm, 7.3 mm, and 8.5 mm, respectively. The secondary development of ABAQUS 2021 using Python 3.6 scripting language has improved the efficiency of simulation modeling and provided reference for rapidly predicting the deformation characteristics of aluminum alloy 6082-T6 under different laser process parameters.
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Belachsen, Idit, and David M. Broday. "Imputation of Missing PM2.5 Observations in a Network of Air Quality Monitoring Stations by a New kNN Method." Atmosphere 13, no. 11 (November 21, 2022): 1934. http://dx.doi.org/10.3390/atmos13111934.
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Statistical analyses often require unbiased and reliable data completion. In this work, we imputed missing fine particulate matter (PM2.5) observations from eight years (2012–2019) of records in 59 air quality monitoring (AQM) stations in Israel, using no auxiliary data but the available PM2.5 observations. This was achieved by a new k-Nearest Neighbors multivariate imputation method (wkNNr) that uses the correlations between the AQM stations’ data to weigh the distance between the observations. The model was evaluated against an iterative imputation with an Ensemble of Extremely randomized decision Trees (iiET) on artificially and randomly removed data intervals of various lengths: very short (0.5–3 h, corresponding to 1–6 missing values), short (6–24 h), medium-length (36–72 h), long (10–30 d), and very long (30 d–2 y). The new wkNNr model outperformed the iiET in imputing very short missing-data intervals when the adjacent lagging and leading observations were added as model inputs. For longer missing-data intervals, despite its simplicity and the smaller number of hyperparameters required for tuning, the new model showed an almost comparable performance to the iiET. A parallel Python implementation of the new kNN-based multivariate imputation method is available on github.
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Zavoykin, V. A. "Implementation of the extended diagnostics domestic system for wheeled vehicles using the UDS protocol in the CAN data bus." Trudy NAMI, no. 3 (October 3, 2022): 6–16. http://dx.doi.org/10.51187/0135-3152-2022-3-6-16.
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Introduction (problem statement and relevance). This work is devoted to the peculiarities of developing and building a general diagnostic structure for the domestic vehicles, the requirements for it and the description of the necessary diagnostic services in the process of its implementing. The purpose of the work was to develop domestic software diagnostic system for the wheeled vehicles and their environment to meet the international standards of the Unified Diagnostic Services protocol according to ISO 14229 and could implement various diagnostic services.Methodology and research methods. The basic requirements and specifications of the CAN bus (ISO 15765) and the UDS protocol (ISO 14229) were described. The developed system was implemented in the Python programming environment, with the algorithm, logic of the application and the directly received data were considered and sent to the CAN data bus during the reading procedure at the address.Scientifi c novelty and results. To diagnose vehicle malfunctions the principles of testing and validating software as part of the electronic control units equipment structure of a wheeled vehicle and necessary to complete the development and implementation of the diagnostic system software in real operating conditions were suggested. The principles of carrying out software tests, as well as the documentation data and analysis of the results obtained were described, together with the formulated conclusions on the work.Practical significance. The paper presents the diagnostic software development results and their implementation in production to meet the requirements of ISO 14229 and ISO 15765. The software is designed to improve the efficiency of the production process to detect and localize vehicle malfunctions during their maintenance work in a service center.
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Pavlenko, Oleh, Anatolii Tymoshenko, and Oksana Tymoshenko. "SET OF INTEGERS WITH UNIQUE SUMS OF TWO ELEMENTS." Інфокомунікаційні та комп’ютерні технології, no. 2(6) (2023): 74–77. http://dx.doi.org/10.36994/2788-5518-2023-02-06-08.
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The problem of creating a set of natural numbers with unique sums of any two elements is considered. The elements can be taken from the natural series (1, 2... n) or start from zero (0, 1, 2... n). In the first case, even sums necessarily mean the sum of two elements. For example, for a set of 4 elements, the obtained series (1, 2, 3, 5) has the following unique even sums (1+2=3; 1+3=4; 1+5=6; 2+3=5; 2+5=7; 3+5=8). In the second case, each element of the series can be considered as an even sum with zero. Then, for a set of 4 elements (0, 1, 2, 4), we have all possible unique even sums (0+1=1; 0+2=2; 0+4=4; 1+2=3; 1+4=5; 2+4=6). Thus, in this case, the sum of two significant elements should not coincide with any element of the set or with other even sums. These examples illustrate that these are different problems, and the work focuses on the second variant. The proposed algorithm for finding a set of natural numbers for different numbers of elements is discussed. The criteria for optimal series construction include the minimum sum of elements and the minimum value of the last element. The algorithm and program for creating such a series are provided. The obtained result is for 8 elements of the set. The program is written in the Python programming language using the itertools library, which makes it compact. The research results are presented in a table for various numbers of significant elements in the set. For the largest number of elements, several results are obtained, as the series are chosen based on two criteria. In the presented research results, these criteria coincide for numbers of elements n<8. For eight elements of the set, different sets of natural numbers are obtained for each minimal criterion.
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Kim, Cho-Myong, A.-Ram Jo, and Yang-Kyun Kim. "Reviews Analysis of Korean Clinics Using LDA Topic Modeling." Journal of Korean Medicine 43, no. 1 (March 1, 2022): 73–86. http://dx.doi.org/10.13048/jkm.22007.
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Objectives: In the health care industry, the influence of online reviews is growing. As medical services are provided mainly by providers, those services have been managed by hospitals and clinics. However, direct promotions of medical services by providers are legally forbidden. Due to this reason, consumers, like patients and clients, search a lot of reviews on the Internet to get any information about hospitals, treatments, prices, etc. It can be determined that online reviews indicate the quality of hospitals, and that analysis should be done for sustainable hospital marketing.Method: Using a Python-based crawler, we collected reviews, written by real patients, who had experienced Korean medicine, about more than 14,000 reviews. To extract the most representative words, reviews were divided by positive and negative; after that reviews were pre-processed to get only nouns and adjectives to get TF(Term Frequency), DF(Document Frequency), and TF-IDF(Term Frequency – Inverse Document Frequency). Finally, to get some topics about reviews, aggregations of extracted words were analyzed by using LDA(Latent Dirichlet Allocation) methods. To avoid overlap, the number of topics is set by Davis visualization.Results and Conclusions: 6 and 3 topics extracted in each positive/negative review, analyzed by LDA Topic Model. The main factors, consisting of topics were 1) Response to patients and customers. 2) Customized treatment (consultation) and management. 3) Hospital/Clinic’s environments.
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Shiddiq, Minarni, Annisa Fadlillah, Sinta Afria Ningsih, and Ikhsan Raahaman Husein. "Rancang Bangun Sistem Hidung Elektronik Berbasis Sensor Gas MQ untuk Mengevaluasi Kualitas Madu." Jurnal Teori dan Aplikasi Fisika 9, no. 2 (July 31, 2021): 143–52. http://dx.doi.org/10.23960/jtaf.v9i2.2722.
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Honeys come in many varieties based on quality attributes and region origin. Electronic nose systems have been adopted and used to classify honey types based on physicochemical parameters. This study was aimed to build a low cost electronic nose (e-nose) based on metal oxide semiconductor (MOS) gas sensors, and then used to evaluate the qualities of two types of honeys and one non honey based on sugar contents and pH values. Six gas sensors of MQ modules namely MQ2, MQ3, MQ4, MQ5, MQ6, MQ9, and an Arduino microcontroller were used in this system. Software of Arduino IDE, PLX-DAQ, and Python were applied to record output voltages of each sensor, saved in Excel format, and to calculate trapezoid areas respectively. Honey samples were named as A, B, and C which were. a national brand honey, a local forest honey, and date syrup respectively. The results show higher output voltages for MQ 3, MQ 4, and MQ 6 sensors. The six sensors are able to differentiate between the two honey types and non honey. Sample A has the highest trapezoid area while sample C has the lowest area. This could be caused by higher pH value of sample C.
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Emekeeva, Daria D., Tomiris T. Kusainova, Lev I. Levitsky, Elizaveta M. Kazakova, Mark V. Ivanov, Irina P. Olkhovskaya, Mikhail L. Kuskov, et al. "Morley: Image Analysis and Evaluation of Statistically Significant Differences in Geometric Sizes of Crop Seedlings in Response to Biotic Stimulation." Agronomy 13, no. 8 (August 15, 2023): 2134. http://dx.doi.org/10.3390/agronomy13082134.
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Image analysis is widely applied in plant science for phenotyping and monitoring botanic and agricultural species. Although a lot of software is available, tools integrating image analysis and statistical assessment of seedling growth in large groups of plants are limited or absent, and do not cover the needs of researchers. In this study, we developed Morley, a free, open-source graphical user interface written in Python. Morley automates the following workflow: (1) group-wise analysis of a few thousand seedlings from multiple images; (2) recognition of seeds, shoots, and roots in seedling images; (3) calculation of shoot and root lengths and surface area; (4) evaluation of statistically significant differences between plant groups; (5) calculation of germination rates; and (6) visualization and interpretation. Morley is designed for laboratory studies of biotic effects on seedling growth, when the molecular mechanisms underlying the morphometric changes are analyzed. The performance was tested using cultivars of Triticum aestivum and Pisum sativum on seedlings of up to 1 week old. The accuracy of the measured morphometric parameters was comparable with that obtained using ImageJ and manual measurements. Possible applications of Morley include dose-dependent laboratory tests for germination affected by new bioactive compounds and fertilizers.
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Zadorozhnyi, Bohdan, Oleksandr Mitsa, and Petro Stetsyuk. "On the Improvement of the Heuristic Algorithm for Packing Circles into a Circle of Minimum Radius." Cybernetics and Computer Technologies, no. 2 (July 28, 2023): 32–45. http://dx.doi.org/10.34229/2707-451x.23.2.4.
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The article is devoted to investigation of a heuristic algorithm for solving the competitive problem "Circles Dense packing into a circle of minimum radius" and development of its improved version using Shor's r-algorithm with step dichotomy. The heuristic algorithm was developed by Bohdan Zadorozhnyi, a third-year student of Uzhhorod National University. The program implemented on its basis took second place in the competition and used less time than the maximum time, which, according to the competition, was allocated for a one-time launch of the program for 50 competitive tasks. The article describes the research results of how the Shor r-algorithm can be used to improve efficiency of the heuristic algorithm. The algorithm for improving the heuristic solution is implemented according to the following scheme. We start from the best arrangement of circles found by the heuristic algorithm. Then, we perform the following four stages of the algorithm: Stage 1. We set a rather large value of the initial step (we determine it depending on the input data or simply choose it as a large step); Stage 2. We run the r-algorithm from the starting point and find the local minimum of the corresponding nonlinear programming problem; Stage 3. If the local minimum found guarantees a smaller radius of the outer circle, then the local minimum point becomes the starting point; the local minimum found does not guarantee a smaller radius of the outer circle, then the size of the step h is reduced by half. Stage 4. If the step value is greater than the specified value, then we proceed to Stage 2. Otherwise, we finish work of the algorithm with solution improvement. Python 3.9.5 programming language and NumPy 1.24.2 library were used for software implementation of both algorithms. For 50 competitive tests and different number of iterations of the heuristic algorithm (10, 20, 30, 40 and 50 iterations), the analysis of the obtained results was conducted according to three parameters: the number of points obtained, program execution time and the number of exchanges of circles in one iteration of the heuristic algorithm. For most of the competitive tests, the refined algorithm allows you to get better results in points, in particular, in most cases the improvement is up to 2 points, and in some cases – from 3 to 6 points. The biggest improvements (6 points) are seen in tests, where the circles have the same or close radii. Here, the heuristic algorithm works not so effectively, therefore, for such tests, due to the algorithm with refinement, it is possible to significantly improve the results of competitive tasks in terms of points. Keywords: circle packing, heuristics, r-algorithm, Python 3.9.5, NumPy 1.24.2.
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King, Rachel, Eva Muhanguzi, Miriam Nakitto, Miriam Mirembe, Francis Xavier Kasujja, Daniel Bagiire, and Janet Seeley. "Mobility study of young women who exchange sex for money or commodities using Google Maps and qualitative methods in Kampala, Uganda." BMJ Open 11, no. 5 (May 2021): e043078. http://dx.doi.org/10.1136/bmjopen-2020-043078.
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ObjectivesWe aimed to assess mobility patterns and reasons for high mobility among young women engaged in sex work within a randomised controlled trial to gauge how mobility may hinder access to health services and enhance HIV risk in a highly vulnerable population.SettingParticipants were recruited from a clinic in Kampala, Uganda set up for women at high risk of HIV infection.ParticipantsAdolescent girls and young women engaged in sex for money and/or commodities are at particular risk in countries with high HIV prevalence and high fertility rates. High mobility increases exposure to HIV risk. Women participants were eligible for the parent study if aged 15–24 years, HIV negative and engaged in sex work. For this substudy, 34 qualitative interviews were held with 14 sex workers (6 HIV positive, 8 HIV negative), 6 health worker/policy makers, 3 peer educators, 5 ‘queen mothers’ and 6 male partnersMeasuresParticipants used Google Maps to identify work venues at 12-month and 18-month study visits. We also conducted 34 interviews on mobility with: high-risk women, male partners, health workers and sex-worker managers. Topics included: distance, frequency and reasons for mobility. We used Python software to analyse mapping data.ResultsInterviews found in depth narratives describing lack of education and employment opportunities, violence, lack of agency, social, sexual and familial support networks and poverty as a complex web of reasons for high mobility among young sex workers.ConclusionsYoung women at high risk are highly mobile. Reasons for mobility impact access and retention to health services and research activities. Strategies to improve retention in care should be cognisant and tailored to suit mobility patterns.Trial registration numberNCT03203200.
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Lovelace, Robin, Martijn Tennekes, and Dustin Carlino. "ClockBoard: A zoning system for urban analysis." Journal of Spatial Information Science, no. 24 (June 20, 2022): 63–85. http://dx.doi.org/10.5311/josis.2022.24.172.
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Zones are the building blocks of urban analysis. Fields ranging from demographics to transport planning routinely use zones - spatially contiguous areal units that break-up continuous space into discrete chunks - as the foundation for diverse analysis techniques. Key methods such as origin-destination analysis and choropleth mapping rely on zones with appropriate sizes, shapes and coverage. However, existing zoning systems are sub-optimal in many urban analysis contexts, for three main reasons: 1) administrative zoning systems are often based on somewhat arbitrary factors; 2) zoning systems that are evidence-based (e.g., based on equal population size) are often highly variable in size and shape, reducing their utility for inter-city comparison; and 3) official zoning systems in many places simply do not exist or are unavailable. We set out to develop a flexible, open and scalable solution to these problems. The result is the zonebuilder project (with R, Rust and Python implementations), which was used to create the ClockBoard zoning system. ClockBoard consists of 12 segments emanating from a central place and divided by concentric rings with radii that increase in line with the triangular number sequence (1, 3, 6 km etc). 'ClockBoards' thus create a consistent visual frame of reference for monocentric cities that is reminiscent of clocks and a dartboard. This paper outlines the design and potential uses of the ClockBoard zoning system in the historical context, and discusses future avenues for research into the design and assessment of zoning systems.
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Rosyid, Mas’ud Abdur, Yusuf Suhaimi Daulay, Denden Mohamad Arifin, Ardian Infantono, Arief Suryadi Satyawan, Ema Ema, and Raden Aditya Satria Nugraha. "Pengembangan Algoritma Pereduksi Noise Pada Point Cloud Data LiDAR Dua Dimensi Untuk Aplikasi Kendaraan Listrik Otonom Sederhana." Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (SENASTINDO) 3 (December 21, 2021): 145–56. http://dx.doi.org/10.54706/senastindo.v3.2021.146.
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Penerapan teknologi LiDAR 2 dimensi (Light Detection And Rangging) terkadang terkendala oleh adanya anomaly data atau noise sehingga mempengaruhi keakuratan dalam mendeteksi objek yang sesungguhnya. Jika tidak diatasi dengan baik maka dapat menggangu operasional kerjanya, terlebih lagi jika diterapkan pada kendaraan listrik otonom. Oleh sebab itu perlu upaya untuk mereduksi noise yang diimplementasikan pada software pemroses data LiDAR. Pada penelitian ini dilakukan pengembangan teknologi pereduksi noise yang muncul pada point cloud data LiDAR dua dimensi. Adapun konsep yang diterapkan adalah pengembangan algoritma pengolahan data LiDAR secara sistematis. Desain algoritma ini berisikan visualiasi dari pendeteksian objek, penyimpanan point cloud data LiDAR sebagai informasi objek yang terdeteksi, serta metode pengurangan noise pada point cloud data LiDAR dua dimensi tersebut. Algoritma ini di realisasikan dalam bentuk software pada perangkat keras Raspberry Pi 4, dengan menggunakan bahasa pemrograman Python. Terdapat enam Algoritma yang digunakan untuk mereduksi atau menghilangkan noise, yaitu Algoritma 1, Algoritma 2, Algoritma 3, Algoritma 4, Algoritma 5, Algoritma 6. Hasil percobaan memperlihatkan bahwa dari keenam Algoritma yang di buat mampu menampilkan visualisasi data berdasarkan sistem pemetaan 2 dimensi yang terkoreksi dari noise. Keenam Algoritma tersebut berhasil menyeleksi noise hingga 100%, meskipun kurang lebih 80% data yang dianggap benar tidak dapat disajikan. Meskipun hanya dengan 20% data benar, namun struktur objek masih dapat dikenali.
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Nwaneri, S. C., J. O. Ezeagbor, D. O. T. Orunsholu, and C. O. Anyaeche. "Optimisation of Patient Flow and Scheduling in an Outpatient Haemodialysis Clinic." Nigerian Journal of Technological Development 18, no. 2 (August 13, 2021): 119–28. http://dx.doi.org/10.4314/njtd.v18i2.6.
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The demand for renal replacement therapy (RRT) from the growing number of patients suffering from chronic kidney disease (CKD) and end stage renal disease (ESRD) in Nigeria is reported to be on the rise. However, dialysis clinics are few with limited facilities to meet the increasing demand leading to congestion, long waiting time and increased length of stay (LOS) in dialysis clinics. This paper presents an optimisation model for scheduling patient flow in an outpatient haemodialysis clinic. The objective is to minimize patient LOS using Genetic Algorithm (GA), implemented in Python programming language with Spyder Integrated Development Environment (IDE). The model was tested using data obtained from a haemodialysis clinic, in Lagos, Nigeria. The model generated optimum LOS values (193.01, 275.02 and 390.01) minutes compared to the mean LOS values at the haemodialysis clinic (235.50, 296.62 and 424.50) minutes for the 3-hour, 4-hour and 6-hour dialysis sessions. Furthermore, a simulation experiment of patient flow in a typical haemodialysis clinic was performed by gradual variations in patient arrival rates, λ. Simulation results at (λ=0.1,0.2,0.3,0.4) revealed mean LOS (minutes) as (312.85 ± 73.45, 348.18 ± 84.89, 342.18 ± 81.30, 305, 28 ± 63.67) respectively. The optimisation model was effective in reducing patient LOS.
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de Keijzer, Brian, Pol de Visser, Víctor García Romillo, Víctor Gómez Muñoz, Daan Boesten, Megan Meezen, and Tadeo Baldiri Salcedo Rahola. "Forecasting residential gas consumption with machine learning algorithms on weather data." E3S Web of Conferences 111 (2019): 05019. http://dx.doi.org/10.1051/e3sconf/201911105019.
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Machine learning models have proven to be reliable methods in the forecasting of energy use in commercial and office buildings. However, little research has been done on energy forecasting in dwellings, mainly due to the difficulty of obtaining household level data while keeping the privacy of inhabitants in mind. Gaining insight into the energy consumption in the near future can be helpful in balancing the grid and insights in how to reduce the energy consumption can be received. In collaboration with OPSCHALER, a measurement campaign on the influence of housing characteristics on energy costs and comfort, several machine learning models were compared on forecasting performance and the computational time needed. Nine months of data containing the mean gas consumption of 52 dwellings on a one hour resolution was used for this research. The first 6 months were used for training, whereas the last 3 months were used to evaluate the models. The results showed that the Deep Neural Network (DNN) performed best with a 50.1 % Mean Absolute Percentage Error (MAPE) on a one hour resolution. When comparing daily and weekly resolutions, the Multivariate Linear Regression (MVLR) outperformed other models, with a 20.1 % and 17.0 % MAPE, respectively. The models were programmed in Python.
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Berliana, Dafa Rosi, and Budi Santoso. "ELEKTABILITAS RIDWAN KAMIL DAN ANIES BASWEDAN DALAM SIMULASI PILPRES 2024 DI TWITTER (ANALISIS JARINGAN MEDIA SOSIAL DAN ANALISIS SENTIMEN PENGGUNA TWITTER TERHADAP #RIDWANKAMIL DAN #ANIESBASWEDAN)." Mediakom : Jurnal Ilmu Komunikasi 6, no. 2 (2022): 150–62. http://dx.doi.org/10.35760/mkm.2022.v6i2.6962.
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Penelitian ini bertujuan untuk mengetahui Elektabilitas Ridwan Kamil dan Anies Baswedan diTwitter menggunakan Sentiment Analysis dan Social Media Network Analysis, yang menjadi 2 kandidat yang paling banyak dipilih di Jawa Barat. #AniesBaswedan dan #RidwanKamil menjadi acuan pengguna Twitter untuk mengutarakan opini. Tagar memberi kesempatan publik untuk memberikan opini secara spontan, berkaitan dengan Teori Digital Movement of Opinion (DMO). Metode yang digunakan pendekatan kuantitatif dan paradigma positivistik. Data diambil menggunakan Netlytic.org pada 16-22 Maret 2022. keyword yang digunakan adalah #AniesBaswedan dengan sampel 10000tweet yang berhasil ditarik dan #RidwanKamil dengan sampel sebanyak 9815tweet. Data akan melalui Preprocessing menggunakan Python, dan klasifikasi sentimen Lexicon Based. Hasil Penelitian menunjukkan Anies memiliki volume percakapan lebih besar dibandingkan Ridwan. Anies memiliki 29% tweet negatif, 65% positif, 6% netral, sementara Ridwan dengan 8% tweet negatif, 89% positif, 3% netral. Kesimpulan, pembicaraan figur politik diTwitter membentuk opini publik berupa sentimen positif, negatif, dan netral. Pembicaraan terkait Anies lebih banyak dilakukan buzzer, sementara terkait Ridwan lebih banyak dilakukan pendukungnya. Elektabilitas dilihat dari analisis sentimen, Anies memiliki popularitas tinggi dibandingkan Ridwan, yang sejalan dengan tingginya sentimen negatif. Penelitian selanjutnya diharapkan mengembangkan konseptualisasi menggunakan metode kritis dan melakukan wawancara untuk mengkaji fenomena. Pengguna Twitter sebaiknya lebih bijaksana dalam beropini, khususnya isu politik.
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Serezvin, I. S., A. O. Avetisyan, M. B. Potievskiy, A. A. Rodin, N. A. Rodin, G. K. Savon, D. K. Grabetskii, and P. K. Yablonskiy. "Model for Predicting the Risk of Bronchopleural Fistula After Pneumonectomy for Destructive Pulmonary Tuberculosis." Innovative Medicine of Kuban, no. 4 (November 16, 2023): 60–67. http://dx.doi.org/10.35401/2541-9897-2023-8-4-60-67.
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Introduction: Predicting various events based on influencing factors is important for statistical analysis in medical research. Unfortunately, mathematical models are rarely built on the identified factors.Objective: To develop a model to predict the risk of bronchopleural fistula after pneumonectomy for destructive pulmonary tuberculosis.Materials and methods: We analyzed medical records of 198 patients who underwent pneumonectomy. Of them 6 patients (3%) developed a bronchopleural fistula. We used machine learning algorithms such as ridge regression, support vector machine, random forest, and CatBoost, the Jupyter opensource development environment, and Python 3.6 to build prediction models. ROC analysis was used to evaluate the quality of the binary classification.Results: We built 4 models to predict the risk of bronchopleural fistula. Their ROC AUC were as follows: ridge regression – 0.88, support vector machine – 0.87, CatBoost – 0.75, and random forest – 0.74. The model based on the ridge regression showed the best ROC AUC. Based on the coordinates of the ROC curve, the threshold value of 1.9% provides the maximum total sensitivity and specificity (100% and 68.8%, respectively).Conclusions: The developed model has a high predictive ability, which allows focusing on the patient group with an increased risk of bronchopleural fistula and justifying the need for preventive measures.
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Muhiddin, Syurawasti, Griselda Maria Ancela Wodong, Afga Yudistikhar, Azmul Fuady Idham, Audrey Alya Vanessa, and Patricia Cecilia Soharto. "#WMHD Talks: Analyses of Mental Health Conversations Among Indonesian Community on Twitter." Gadjah Mada Journal of Psychology (GamaJoP) 10, no. 1 (May 31, 2024): 49. http://dx.doi.org/10.22146/gamajop.81922.
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One of the right moments to comprehend people’s understanding of mental health topics is through World Mental Health Day (WMHD). This study aimed to explore themes related to mental health that are the conversation topics on Twitter as social reactions to WMHD 2021. We collected and analyzed Indonesian tweets that contained #WMHD or Mental Health keywords. From October 1 to 23, 2021, a total of 12,500 tweets were collected utilizing tweepy and request, a python programming-based library. Data cleaning processes left 7,126 tweets to be further analyzed with inductive thematic analysis. This study found seven themes from the most to the least frequently discussed, namely (1) positive mental health, (2) social network and social capital, (3) mental health literacy, (4) stressful events, (5) material economic well-being, (6) mental illness and (7) physical wellbeing. This research showed that social media has the capacity to investigate users’ knowledge and perception which might then serve as the foundation for providing relevant mental health education on various platforms to support the improvement of community well-being. Furthermore, knowing the topics of mental health-related conversations on twitter can be a precursor to the development of a measurement tool related to mental health understanding.
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Chen, Chaolan, and Xi Wu. "Research on pricing and replenishment based on optimal programming model." Highlights in Business, Economics and Management 29 (March 29, 2024): 141–48. http://dx.doi.org/10.54097/csmsgm04.
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This paper studies the law and correlatoin of different categories of vegetable commodities, and makes the total amount of replenishment and pricing strategy of each vegetable category in the next week, so as to maximize the profit of supermarket. Firstly, the correlatoin between different categories of vegetable products was analyzed based on Pearson correlatoin analysis. The results showed that flower-leaf, cauliflower, pepper had strong correlatoin with edible fungi, while aquatic rhizome and solanaceae had relatively low correlatoin with other categories of vegetables. Then, the monthly and daily sales volume of each category and single vegetable were counted, and the monthly, weekly and daily distribution function of each category and single vegetable was obtained by fitting with Python software using the least square method. The vegetable category cluster analysis based on systematic clustering was used to cluster 6 categories of vegetables, and the 6 categories of vegetables were divided into 3 categories. Then the least square method was used to fit the processed data, and the fitting function expression between the sales volume and the cost plus pricing of each category of vegetables was obtained. The replenishment quantity decision model based on time series was established, and the daily replenishment quantity decision of each vegetable category in the next week was obtained. Finally, according to the correlatoin between sales volume and price, the optimal pricing model based on dynamic market demand is established, and the most reasonable pricing is obtained and the optimal replenishment decision is made to maximize the profit of supermarket.
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Pu, Junwei, Xiaoqing Zhao, Pinliang Dong, Qian Wang, and Qifa Yue. "Extracting Information on Rocky Desertification from Satellite Images: A Comparative Study." Remote Sensing 13, no. 13 (June 26, 2021): 2497. http://dx.doi.org/10.3390/rs13132497.
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Rocky desertification occurs in many karst terrains of the world and poses major challenges for regional sustainable development. Remotely sensed data can provide important information on rocky desertification. In this study, three common open-access satellite image datasets (Sentinel-2B, Landsat-8, and Gaofen-6) were used for extracting information on rocky desertification in a typical karst region (Guangnan County, Yunnan) of southwest China, using three machine-learning algorithms implemented in the Python programming language: random forest (RF), bagged decision tree (BDT), and extremely randomized trees (ERT). Comparative analyses of the three data sources and three algorithms show that: (1) The Sentinel-2B image has the best capability for extracting rocky desertification information, with an overall accuracy (OA) of 85.21% using the ERT method. This can be attributed to the higher spatial resolution of the Sentinel-2B image than that of Landsat-8 and Gaofen-6 images and Gaofen-6’s lack of the shortwave infrared (SWIR) bands suitable for mapping carbonate rocks. (2) The ERT method has the best classification results of rocky desertification. Compared with the RF and BDT methods, the ERT method has stronger randomness in modeling and can effectively identify important feature factors for extracting information on rocky desertification. (3) The combination of the Sentinel-2B images and the ERT method provides an effective, efficient, and free approach to information extraction for mapping rocky desertification. The study can provide a useful reference for effective mapping of rocky desertification in similar karst environments of the world, in terms of both satellite image sources and classification algorithms. It also provides important information on the total area and spatial distribution of different levels of rocky desertification in the study area to support decision making by local governments for sustainable development.
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Sherer, Michael V., Diana Lin, Kartikeya Puri, Neil Panjwani, Zhigang Zhang, James D. Murphy, and Erin F. Gillespie. "Development and Usage of eContour, a Novel, Three-Dimensional, Image-Based Web Site to Facilitate Access to Contouring Guidelines at the Point of Care." JCO Clinical Cancer Informatics, no. 3 (December 2019): 1–9. http://dx.doi.org/10.1200/cci.19.00041.
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PURPOSE Variation in contouring quality by radiation oncologists is common and can have significant clinical consequences. Image-based guidelines can improve contour accuracy but are underused. We sought to develop a free, online, easily accessible contouring resource that allows users to scroll through cases with 3-dimensional images and access relevant evidence-based contouring information. MATERIALS AND METHODS eContour ( http://econtour.org ) was developed using modern Web technologies, primarily HTML5, Python, and JavaScript, to display JPEGs generated from DICOM files from real patient cases. The viewer has standard tools for image manipulation as well as toggling of contours and overlayed images and radiation dose distributions. Brief written content references published guidelines for contour delineation. Mixpanel software was used to collect Web page usage statistics. RESULTS In the first 3 years of operation (March 8, 2016 to March 7, 2019), a total of 13,391 users from 128 countries registered on the Web site, including 2,358 physicians from the United States. High-frequency users were more likely to be physicians ( P < .001) and from the United States ( P < .001). In one 6-month period, there were 68,642 individual case page views, with head-and-neck the most commonly viewed disease site (32%). Users who accessed a head-and-neck case were more likely to be high-frequency users, and 67% of repeat users accessed the same case more than once. CONCLUSION The large, diverse user base and steady growth in Web site traffic over the first 3 years of eContour demonstrate its strong potential to address the unmet need for dissemination and use of evidence-based contouring information at the point of care.
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Lee, Huikyo, Alexander Goodman, Lewis McGibbney, Duane E. Waliser, Jinwon Kim, Paul C. Loikith, Peter B. Gibson, and Elias C. Massoud. "Regional Climate Model Evaluation System powered by Apache Open Climate Workbench v1.3.0: an enabling tool for facilitating regional climate studies." Geoscientific Model Development 11, no. 11 (November 5, 2018): 4435–49. http://dx.doi.org/10.5194/gmd-11-4435-2018.
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Abstract. The Regional Climate Model Evaluation System (RCMES) is an enabling tool of the National Aeronautics and Space Administration to support the United States National Climate Assessment. As a comprehensive system for evaluating climate models on regional and continental scales using observational datasets from a variety of sources, RCMES is designed to yield information on the performance of climate models and guide their improvement. Here, we present a user-oriented document describing the latest version of RCMES, its development process, and future plans for improvements. The main objective of RCMES is to facilitate the climate model evaluation process at regional scales. RCMES provides a framework for performing systematic evaluations of climate simulations, such as those from the Coordinated Regional Climate Downscaling Experiment (CORDEX), using in situ observations, as well as satellite and reanalysis data products. The main components of RCMES are (1) a database of observations widely used for climate model evaluation, (2) various data loaders to import climate models and observations on local file systems and Earth System Grid Federation (ESGF) nodes, (3) a versatile processor to subset and regrid the loaded datasets, (4) performance metrics designed to assess and quantify model skill, (5) plotting routines to visualize the performance metrics, (6) a toolkit for statistically downscaling climate model simulations, and (7) two installation packages to maximize convenience of users without Python skills. RCMES website is maintained up to date with a brief explanation of these components. Although there are other open-source software (OSS) toolkits that facilitate analysis and evaluation of climate models, there is a need for climate scientists to participate in the development and customization of OSS to study regional climate change. To establish infrastructure and to ensure software sustainability, development of RCMES is an open, publicly accessible process enabled by leveraging the Apache Software Foundation's OSS library, Apache Open Climate Workbench (OCW). The OCW software that powers RCMES includes a Python OSS library for common climate model evaluation tasks as well as a set of user-friendly interfaces for quickly configuring a model evaluation task. OCW also allows users to build their own climate data analysis tools, such as the statistical downscaling toolkit provided as a part of RCMES.
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Degeling, Koen, Maarten J. IJzerman, Mariel S. Lavieri, Mark Strong, and Hendrik Koffijberg. "Introduction to Metamodeling for Reducing Computational Burden of Advanced Analyses with Health Economic Models: A Structured Overview of Metamodeling Methods in a 6-Step Application Process." Medical Decision Making 40, no. 3 (April 2020): 348–63. http://dx.doi.org/10.1177/0272989x20912233.
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Metamodels can be used to reduce the computational burden associated with computationally demanding analyses of simulation models, although applications within health economics are still scarce. Besides a lack of awareness of their potential within health economics, the absence of guidance on the conceivably complex and time-consuming process of developing and validating metamodels may contribute to their limited uptake. To address these issues, this article introduces metamodeling to the wider health economic audience and presents a process for applying metamodeling in this context, including suitable methods and directions for their selection and use. General (i.e., non–health economic specific) metamodeling literature, clinical prediction modeling literature, and a previously published literature review were exploited to consolidate a process and to identify candidate metamodeling methods. Methods were considered applicable to health economics if they are able to account for mixed (i.e., continuous and discrete) input parameters and continuous outcomes. Six steps were identified as relevant for applying metamodeling methods within health economics: 1) the identification of a suitable metamodeling technique, 2) simulation of data sets according to a design of experiments, 3) fitting of the metamodel, 4) assessment of metamodel performance, 5) conducting the required analysis using the metamodel, and 6) verification of the results. Different methods are discussed to support each step, including their characteristics, directions for use, key references, and relevant R and Python packages. To address challenges regarding metamodeling methods selection, a first guide was developed toward using metamodels to reduce the computational burden of analyses of health economic models. This guidance may increase applications of metamodeling in health economics, enabling increased use of state-of-the-art analyses (e.g., value of information analysis) with computationally burdensome simulation models.
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Kalibek, Ruslan, and Daria Sopyryaeva. "Design of magnetic field sensor with software for a wide range of applications." Technobius Physics 2, no. 1 (March 24, 2024): 0008. http://dx.doi.org/10.54355/tbusphys/2.1.2024.0008.
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The abstract of the paper outlines a highly efficient wirelessly magnetic field-based information transmission method, enabling real-time data acquisition. Emphasizing stringent demands on magnetic devices for high sensitivity across a wide range of field strengths, it highlights the need for rapid response times and minimal power consumption. The paper introduces a prefabricated magnetic sensor programmed on an Arduino board using Hall’s Effect. This principle exploits electron transfer within a conductor under a magnetic field, inducing a transverse potential difference. Meticulously chosen solid-state materials and geometries generate detectable pulses, subsequently amplified for measuring various magnetic field components. Operating within a voltage range of 2.7-6.5V, aligned with the Arduino's 5V standard, the sensor demonstrates zero signal levels at 2.25-2.75V. Sensitivity ranges from 1.0-1.75 mV/gauss, mandating pre-calibration for accuracy, facilitated by a pre-calibration function or reset button. Output voltage ranges from 1.0-4.0V when powered by 5V, suitable for analog-to-digital conversion. With a minimum measurement range of ±650 gauss, typically extending to ±1000 gauss, and a swift response time of 3 ms, the sensor allows measurements up to tens of kHz. Operating currents between 6-10 mA are suitable for battery-powered applications, while a temperature-induced error of 0.1%/°C equates to 3 mT. Notably, the sensor measures magnetic fields along and perpendicular to the axis. To enhance accessibility and accuracy, a specialized Python-based software tool has been developed, featuring automatic sensor identification. This abstract encapsulates the paper's focus on advancing magnetic field measurement technology with practical implications for diverse applications.