bluuebunny/crossref_metadata_2025_split huggingface dataset:
Healthcare Cost Patterns and Prediction: Investigating Personal Datasets using Data Analytics
Authors: Islam Md Aminul , Nag Anindya , Chandra Pretam , Fahim SM Firoz Ahmed , Hoque Md Mozammel 
Published: November 2023

<p>The present study introduces a health insurance prediction system that leverages machine learning methodologies. In contemporary times, there has been a notable increase in endeavors focused on tackling this matter since the significance of health insurance as a research topic has markedly escalated following the pandemic. The dataset employed in this research comprises 1338 observations 7 columns and corresponds to individual medical expenditures in the United States, available at the Kaggle platform. The dataset encompasses a variety of variables utilized in the prediction of insurance prices, including age, gender, BMI, smoking status, and number of children. The researchers used machine learning models, including neural networks, XAI, and auto modeling, to determine the correlation between pricing and the attributes. The training process involved partitioning the dataset into an 80-20 ratio for training and evaluation. Consequently, the system achieved an accuracy rate of 97% by Gradient Boosting, but we corrected it to 92% by Gradient Boosting Regressor by encoding and hyper-tuning. Also, among predictive machine learning models, Random Forest had the best accuracy i.e., of 83.44%. </p>
Clinical IoT in Practice: A Novel Design and Implementation of a Multi-functional Digital Stethoscope for Remote Health Monitoring
Authors: Baraeinejad Bardia , Shams Morteza , Saberi Hamedani Mohammad , Nasiri-Valikboni Amirhossein , Forouzesh Maryam , Fakhraeelotfabadi Shayan , Karimian Radmehr , Babaei Saba , Rashidi Diba , Germchi Danesh , Torabi Yasaman , Gorji Pouya , Vashaee Daryoosh 
Published: November 2023

<p>This study introduces a cutting-edge digital stethoscope optimized for remote health monitoring. Integrating Micro-Electromechanical Systems (MEMS) microphones with Bluetooth Low Energy (BLE) 5, the device ensures high-fidelity, real-time audio transmission. It seamlessly connects to an Internet of Things (IoT) platform through an embedded system, highlighting its potential in remote healthcare scenarios, especially during global health emergencies. Advanced features encompass Active Noise Cancellation, extended battery life, and intricate internal sound filtration. Paired with a dedicated Android application, the stethoscope streamlines the capture, storage, and visualization of auscultation data. Crucially, its integration with Electronic Health Records (EHRs) and its capability to generate vast datasets can significantly advance diagnostic precision, leveraging Digital Signal Processing and Artificial Intelligence methodologies. </p>
FairXAI - A Taxonomy and Framework for Fairness and Explainability Synergy in Machine Learning
Authors: Ramachandranpillai Resmi , Baeza-Yates Ricardo , Heintz Fredrik 
Published: November 2023

<p>Explainable Artificial Intelligence (XAI) and Fair Learning have made significant strides in various application domains, including criminal recidivism predictions, healthcare settings, toxic comment detection, automatic speech detection, recommendation systems, and image segmentation. However, these two fields have largely evolved independently. Recent studies have demonstrated that incorporating explanations into decision-making processes enhances the transparency and trustworthiness of AI systems. In light of this, our objective is to conduct a systematic review of FairXAI, which explores the interplay between fairness and explainability frameworks. To commence, we propose a taxonomy of FairXAI that utilizes XAI as a means to both mitigate and evaluate bias. This taxonomy will serve as a base for machine learning researchers operating in diverse domains. Additionally, we will undertake an extensive review of existing articles, taking into account factors such as the purpose of the interaction, target audience, and domain and context. Moreover, we outline an interaction framework for FairXAI considering various fairness perceptions and propose a FairXAI wheel that encompasses four core properties that must be verified and evaluated. This will serve as a practical tool for researchers and practitioners, ensuring the fairness and transparency of their AI systems. Furthermore, we will identify challenges and conflicts in the interactions between fairness and explainability, which could potentially pave the way for enhancing the responsibility of AI systems. As the inaugural review of its kind, we hope that this survey will inspire scholars to address these challenges by scrutinizing current research in their respective domains. </p>
Non-Invasive Continuous Glucose Monitoring using Near Infrared Sensors and PSO-ANN Algorithm
Authors: Raghavan Dharini , K V Suma , Karki Maya V , Sharma Narayana , Rao Gundu 
Published: November 2023

<p>Blood glucose is typically measured using invasive methods such as finger pricking, which although accurate are not suitable for frequent use as they cause extreme pain, and do not provide provisions for continuous glucose monitoring. Recent studies have proposed non-invasive glucometers that are based on scientific principles such as optical polarimetry, thermal emission, and electromagnetic approaches, but are expensive, highly sensitive to external noise and environmental variations, have low signal-to-noise ratio (SNR), and poor glucose selectivity. Although developments in Near-Infrared Spectroscopy (NIRS) have overcome these limitations to a certain extent, they do not produce reliable measurements due to large calibration errors that often result in incorrect glucose readings. In this paper, we propose a robust particle-swarm optimization-based artificial neural network for non-invasive continuous glucose monitoring using the principles of NIRS. We show that the PSO-ANN approach outperforms the traditional backpropagation algorithm used in ANN training and several other regression algorithms with the lowest error metrics: MAE- 1.01, MSE-2.16, RMSE-0.97, R-sqaured score -0.976 and modified R-squared score -0.973. The paper also provides insights into the circuit design, sensors used, hardware-software integration, and clinical validation alongside providing an overview of HbA1c computation.The accuracy and reliability of the proposed system are analyzed using the Clarke Error Grid (CEG) with 93.9% of the obtained readings falling within zone A and 100% of the readings falling in the clinically accepted range (zones A and B). The paper also explores potential enhancements such as miniaturization of the prototype device for wearable applications and wireless connectivity. </p>
A hardware-friendly low-bit post-training quantization algorithm for lightweight networks
Authors: Li Jixing , Zhao Zhiyuan , Chen Gang , Jin Ming , Lu Huaxiang 
Published: November 2023

<p>Lightweight convolutional neural networks (LCNNs) are commonly quantized and deployed on edge devices to fulfill the requirements of low-power, high-performance tasks. Utilizing uniform, symmetric, per-tensor quantization with power-of-two scale factors can enhance hardware efficiency, albeit at the cost of significant accuracy degradation. In this work, we present a hardware-friendly post-training quantization (HFPTQ) framework to address this problem. HFPTQ employs a synergistic combination of established techniques, including Cross-Layer Equalization (CLE), Absorbing High Bias (AHB), and Adaptive Rounding. Furthermore, HFPTQ introduces quantization-aware equalization by optimizing the equalization scale and absorption vector to minimize block reconstruction error and network prediction difference. Additionally, HFPTQ introduces an adaptive bias correction mechanism. While optimizing weight rounding, bias term is co-optimized to rectify the mean shift in activations induced by quantization. Experimental results, based on the ImageNet dataset, demonstrate that HFPTQ significantly enhances the low-bit hardware-friendly quantization performance of lightweight networks.</p>
Identifikasi Bahaya dan Penilaian Risiko Keselamatan dan Kesehatan Kerja (K3) Pada Proyek Runway dan Taxiway Bandara Lolak Bolaang Mongondow Menggunakan Metode Hirarc
Authors: Lalenoh Djoni Hermanus , Dundu Ariestides K. Torry , Lefrandt Lucia. I. R. 
Published: November 2023

Keselamatan dan Kesehatan Kerja (K3) yang merupakan bagian dari beragam upaya pencegahan kecelakaan kerja yang dapat meningkatkan produktifitas tenaga kerja dan efisiensi, diterapkan dengan baik di proyek tersebut apabila menggunakan salah satu pendekatan metode yaitu Hazard Identification and Risk Assessment Risk Control (HIRARC). Tujuan penelitian ini mengidentifikasi bahaya, menganalisis risiko keselamatan kerja, dan mengendalikan risiko pada proyek Runway dan Taxiway bandara Lolak Bolaang Mongondow, sehingga dapat mengurangi atau menghilangkan kecelakaan di tempat kerja. Data yang didapat melalui observasi dan wawancara kepada penyedia jasa dan kontraktor pelaksana konstruksi sebanyak 63 responden. Untuk menentukan klasifikasi tingkat risiko rendah sedang dan tinggi, maka dilakukanlah analisis risiko keselamatan kerja dengan mengidentifikasi bahaya dan risiko dari seluruh item pekerjaan yang didapat melalui hasil observasi dan wawancara, sedangkan nilai risiko didapat dengan mengalikan kemungkinan terjadinya bahaya dan tingkat keparahan bilah mana bahaya tersebut hadir. Nilai peluang kemungkinan terjadinya bahaya dan tingkat keparahan akan dianalisa berpedoman pada standar Australia/Standars New Zealand (AS/NZS 4360): 2004). Hasil analisis dengan 69 sub item pekerjaan dengan tingkat risiko tertinggi terletak pada konstruksi pekerjaan runway sebesar 53% atau 9 risiko dari 17 resiko yang teridentifikasi, tertinggi ke dua terletak pada pekerjaan PKP-PK sebesar 40% atau 4 risiko dari 40 risiko yang teridentifikasi, tertinggi ketiga adalah konstruksi perkerasan jalan operasi sebesar 31%. Pengendalian risiko dilakukan setelah identifikasi dan penilaian risiko selesai, ini merupakan tahapan terakhir dalam pengelohan data dengan pendekatan metode HIRARC.
ABOUT ONE APPROACH TO SOLVING THE PROBLEM OF FORECASTING THE AMOUNT OF ELECTRICITY CONSUMPTION USING MACHINE LEARNING METHODS
Authors: Олейникова С.А. , Бидненко К.А. , Малюгин А.В. 
Published: November 2023

рассматривается задача прогнозирования объема потребления электроэнергии для энергосетевых компаний на примере ООО «Донская Энергосетевая компания» («ДЭК»). Абонентам (физическим и юридическим лицам) прогноз почасового потребления необходим для понимания целесообразности использования именно данного тарифа или тех или иных мощностей. Руководство компании еще больше заинтересовано в прогнозе, поскольку наличие данной информации позволяет точнее оценивать требуемые объемы и минимизировать риски при принятии управленческих решений. Специфика предметной области, особенность факторов, влияющих на результат, а также анализ возможных подходов к прогнозированию позволили определить наилучший способ к оценке потребляемых мощностей. Он основывается на использовании аппарата искусственных нейронных сетей. Специфика задачи определила структуру сети: была предложена рекуррентная нейронная сеть с двумя скрытыми слоями, которая способна обучаться долгосрочным зависимостям. В результате решены следующие задачи: определены входные данные, которые будут оказывать влияние на объем потребления электроэнергии; осуществлена предобработка данных; спроектирована структура искусственной нейронной сети, позволяющей получить прогнозируемое значение; реализовано приложение, которое с использованием обученной нейронной сети позволяет предсказывать объем потребляемой электроэнергии
the work is devoted to solving the problem of forecasting the volume of electricity consumption for energy grid companies using the example of LLC «DEK». Subscribers (individuals and legal entities) need a forecast of hourly consumption to understand the advisability of using a particular tariff or certain capacities. The company's management is even more interested in this forecast, since the availability of this information makes it possible to more accurately assess the required volumes and minimize risks when making management decisions. The specifics of the subject area, the characteristics of the factors influencing the result, as well as the analysis of possible approaches to forecasting made it possible to determine the best way to estimate power consumption. It is based on the use of artificial neural networks. The specifics of the problem determined the structure of the network: a recurrent neural network with two hidden layers was proposed, which is capable of learning long-term dependencies. As a result, the following tasks were solved: input data that will influence the volume of electricity consumption was determined; data preprocessing was carried out; the structure of an artificial neural network has been designed to obtain the predicted value; an application has been implemented that, using a trained neural network, allows you to predict the amount of electricity consumed
MICROSTRIP IMPLANTATION ANTENNA RANGE MICS/ISM FOR MEDICAL AND PLATINUM COMMUNICATIONS SYSTEMS
Authors: Егорова Е.Д. , Журавлёв Д.В. 
Published: November 2023

рассматривается исследование микрополосковой имплантационной антенны диапазона MICS/ISM, предназначенной для использования в системах связи медицинских имплантов. Ее преимущества заключаются в возможности передачи данных на большие расстояния с минимальными потерями сигнала, обеспечивая качественную связь между устройствами внутри организма. Антенна была разработана с учетом особенностей работы внутри тела человека, где присутствует множество помех, вызванных тканями и жидкостями. Использование диапазона MICS/ISM позволяет обеспечить высокую степень защищенности от внешних помех и гарантировать надежную связь между имплантами и внешними устройствами. В рамках исследования сделаны общие оценки рабочих диапазонов, выделенных для медицинских приложений, геометрии излучения имплантационных антенн и ограничений по удельной скорости поглощения. Также приводятся результаты экспериментальных исследований, проведенных на фантомах, моделирующих тело человека. Благодаря своим компактным размерам и низкой массе антенна может быть использована в широком спектре медицинских имплантов, включая кардиостимуляторы, датчики и другие устройства. Таким образом, разработанная микрополосковая имплантационная антенна диапазона MICS/ISM представляет собой перспективное решение для создания надежных систем связи медицинских имплантов, способных обеспечить высокую эффективность передачи данных
the article considers the study of a microstrip implantation antenna of MICS/ISM range, designed for use in communication systems of medical implants. Its advantages lie in the ability to transmit data over long distances with minimal signal loss, providing high-quality communication between devices inside the body. The antenna was designed to operate inside the human body, where there is a lot of interference caused by tissues and fluids. The MICS/ISM band provides a high degree of immunity to external interference and ensures reliable communications between the implants and external devices. Within the study, general evaluations are made of the operating bands allocated for medical applications, the radiation geometry of the implant antennas, and the limits on the specific absorption rate. The results of experimental studies performed on phantoms simulating the human body are also presented. Due to its compact size and low mass, the antenna can be used in a wide range of medical implants, including pacemakers, sensors and other devices. Thus, the developed MICS/ISM band microstrip implantation antenna represents a promising solution for reliable medical implant communication systems capable of high data transmission efficiency
Immune Response after Covid 19 Vaccination as an effort to prevent infection and Herd Immunity
Authors: Kusbaryanto Kusbaryanto 
Published: November 2023

Vaccination programs are one of the most cost-effective and efficient medical therapies in history. This study aims to elicit an immune response after the COVID-19 vaccination and the occurrence of herd immunity. This research is a literature review research by conducting journal searches carried out with the keys: immune response to Covid 19, Covid 19 Vaccination and Herd Immunity. Articles are collected using search engines such as google pubmed, schooler, EBSCO, Sciencedirect, and Proquest. The criteria for the articles used are those published in 2020 – 20232. The Covid 19 virus is a member of the Sarbecovirus subgenus and is distinguished by a stick-shaped spike protein that protrudes from the virion's surface. Global immunization initiatives boost immune systems. Immune cells and proteins that circulate in the body have the ability to provide protection from illness. Prior to immunization, antibodies from patients who had already been exposed to the virus resembled those produced following the first vaccination in healthy individuals. In people who were previously infected after the first vaccination, the level is the same as in people who were not infected after the second vaccination, booster administration has been shown to increase immunity with a 1.5 to 2-fold increase in titers and herd immunity is the only way to end the Covid 19 pandemic.
Infographics as a method of developing critical thinking in Russian as a Foreign Language classes on the example of the topic «Verbs of movement»
Authors: Савина И.С. 
Published: November 2023

Теоретический материал, обосновывающий значимость инфографики, сопровождается примерами практических заданий, которые используются при изучении глаголов движения на занятиях по русскому языку как иностранному. Актуальность выбора практических заданий по данной теме обусловлена сложностью лексико-грамматического материала, вызывающего трудности понимания у иностранных учащихся. Изучение данной темы предполагает формирование грамматических и речевых компетенций на основе функционально-коммуникативного подхода, а использование инфографики способствует формированию критического мышления.
The article considers the importance of infographics as a method of forming critical thinking among foreign students studying Russian at a preparatory course in a higher educational institution. The theoretical material justifying the importance of infographics is accompanied by examples of practical tasks that are used in the study of verbs of movement in classes in Russian as a foreign language. The relevance of the choice of practical tasks on this topic is due to the complexity of the lexical and grammatical material, which causes difficulties of understanding among foreign students. The study of this topic involves the formation of grammatical and speech competencies based on a functional and communicative approach, and the use of infographics contributes to the formation of critical thinking.
SPEECH PORTRAIT OF A GHANAIAN STUDENT STUDYING RUSSIAN
Authors: Нкетия Ю. 
Published: November 2023

В статье представлен анализ речевого портрета ганских студентов, изучающих русский язык в Республике Гана. Анализ основан на влиянии культуры, норм, государственного языка и языков коренных народов на процесс обучения ганского студента русскому языку. Также рассматривается влияние последствий колониализма на менталитет народа Ганы в области образования. Даны методические и педагогические рекомендации для поддержки ганцев, изучающих русский язык.
The article presents an analysis of the speech portrait of Ghanaian students studying Russian language in the Republic of Ghana. The analysis is based on the influence of the culture, norms, the official and indigenous languages on the process of teaching the Ghanaian student Russian language. The effects of the aftermath of colonialism on the mentality of the people of Ghana in the area of education is also examined. Methodological and pedagogical recommendations are made to support Ghanaians studying Russian language.
Factores de riesgo asociados a parto pretérmino del servicio de obstetricia en Latinoamérica
Authors: De León Piñones José Vidal , Sánchez Villalobos Ana Daniela , Rangel Calderón Jessica Lizet , Pérez Ramírez Armando , Olvera Mérida Jehoshua Noé 
Published: November 2023

El parto pretérmino ocasionó 900,000 muertes en 2019 por lo que el reconocimiento de los factores de riesgo beneficia al binomio Objetivo: Realizar una revisión sistemática de estudios de los factores de riesgo asociados al parto pretérmino comprendido en el periodo 2018-2023. Se identificaron a partir de: Google académico, Scielo, Medigraphic, Journal, Archivos Venezolanos de Farmacología y Terapéutica, Repositorio. Los estudios se seleccionaron bajo la verificación de los 5 autores del artículo. Los criterios de inclusión fueron estudios clínicos que encontraron una relación estadísticamente significativa, un OR >1 y que fueran realizados en Latinoamérica Resultado: Se encontraron 15 factores de riesgo, siendo IVU, preeclampsia, tabaquismo, enfermedad periodontal, vaginosis, ruptura prematura de membranas, modificaciones cervicales, placenta previa y oligohidramnios los de más fuerza de asociación Conclusiones: El parto pretérmino posee diversos factores de riesgo por lo que los descritos en las revisiones amplían el panorama para la detección oportuna de la patología y poder prevenir y/o tratar la causa subyacente así como incentivar la búsqueda de factores no descritos
Comunidad Virtual Educativa y Competencias de Aprendizaje del Inglés en la I. E. Libertador Simón Bolívar
Authors: Rosas Villena Fernando René , Castillo Yánac Roos Mery , Soto Rodríguez Iván Dennys , Valencia Chacón Raphael Félix 
Published: November 2023

La investigación demuestra que la variable comunidad virtual educativa se correlaciona con la variable competencias de aprendizaje del idioma inglés. Se comprueba que la comunidad virtual educativa se correlaciona con las dimensiones intercomunicación oral, lectura de documentos escritos y escritura de documentos diversos de la variable competencias de aprendizaje del idioma inglés. Debido a que estas variables no cumplieron con tener una distribución normal por ser de naturaleza cualitativa de tipo ordinal, se aplicó la prueba de correlación Tau de Kendall. Se diseñó un cuestionario de 20 preguntas para mensurar la variable comunidad virtual educativa y una guía de observación de 20 preguntas para mensurar la variable competencias de aprendizaje del idioma inglés. Se verificó el requisito de fiabilidad del instrumento utilizando el indicador alfa de Cronbach y el requisito de validez a través del juicio de 3 profesionales expertos. La caracterización del estudio fue cuantitativa, el diseño utilizado fue no experimental de carácter transversal y el alcance de tipo relacional. La población considerada fue de 260 estudiantes y la muestra de 133 estudiantes de segundo, tercer y cuarto grado de la I.E. Libertador Simón Bolívar – Pativilca – Barranca - Lima Provincias.