bluuebunny/crossref_metadata_2025 huggingface dataset:
A review of animal recognition in urban environments
Authors: He ChuBO
Published: July 2023

This paper describes the importance of animal recognition in the context of increasing animal participation in daily life. The progress in this field is reviewed and the basic methods used in animal recognition are introduced. This paper collects some free and open source data sets for deep learning and introduces statistical indicators for beginners to train and evaluate their own models. This paper collected a statistical chart of the number of papers in the field over the past 60 years, and analyzed the changes and preferences in the field of animal recognition. Finally, the problems faced by the field of animal recognition and the possible future development direction and advantages are summarized. Aiming at the animal recognition in the urban environment, a multi-task network method is recommended to solve the problem of lack of animal recognition data and the resource occupation of neural network in the urban environment.
Review of variational autoencoders model
Authors: Liu Junhong
Published: July 2023

Variational autoencoder is one of the deep latent space generation models, which has become increasingly popular in image generation and anomaly detection in recent years. In this paper, we first review the development and research status of traditional variational autoencoders and their variants, and summarize and compare the performance of all variational autoencoders. then give a possible development direction of VAE.
House price prediction based on machine learning
Authors: Li Hanwen
Published: July 2023

Machine learning is commonly used in the real estate market. It is vital to apply the idea of machine learning in this field to predict house prices based on various features. The paper will focus on how to use the most appropriate machine learning models for house price prediction. It will use LightGBM(Light Gradient Boosting Machine), Gradient Boosting, and XGBoost(Extreme Gradient Boosting) to train models to predict house prices using the existing data from the Kaggle website. After three models make predictions, they will get an RMSE (root mean square error), whichis0.02975, 0.02537, and 0.01364. Based on the result, the XGBoost model is the best one among these three models used for house price prediction.
Using sequence-to-sequence LSTM to predict RNA virus mutations
Authors: Chen Lianghong
Published: July 2023

Infection with viruses is one of the main causes of human illness and even death in today's society. Vaccination can help people fight the virus. However, virus mutation will always cause vaccines to fail. Predicting the mutations of viral could help detect the mutated virus early and develop new vaccines so to reduce the rate of infection and death from the virus. The common strategy used to predict virus mutation is determining the important components of the virus, like amino acids and proteins, then using deep learning or machine learning methods to construct models. It is an effective strategy. However, using this strategy always cause people to spend lots of time and money studying the component of the virus, like amino acids, proteins, nucleic acid and so on. To increase efficiency and reduce the cost of research, a new method that can predict virus mutation based on nucleotide sequence alone is something people looking forward to. In recent years, in natural language processing, building a sequence-to-sequence model is becoming a popular and effective method to deal with textual data. As a type of text data, using the idea of sequence to sequence should be good to deal with the RNA sequence. In addition, in terms of the past study of predicting virus mutation, RNA sequence as a kind of time sequence, people generally use long short-term memory (LSTM) methods to handle it. Thus, in this study, we would combine the idea of the sequence-to-sequence model with LSTM method to predict the possible mutation of the virus. This experiment studies the mutation of two typical influenza viruses and achieves encouraging results.
Speech emotion detection based on MFCC and CNN-LSTM architecture
Authors: Ouyang Qianhe
Published: July 2023

Emotion detection techniques have been applied to multiple cases mainly from facial image features and vocal audio features, of which the latter aspect is disputed yet not only due to the complexity of speech audio processing but also the difficulties of extracting appropriate features. Part of the SAVEE and RAVDESS datasets are selected and combined as the dataset, containing seven sorts of common emotions (i.e. happy, neutral, sad, anger, disgust, fear, and surprise) and thousands of samples. Based on the Librosa package, this paper processes the initial audio input into waveplot and spectrum for analysis and concentrates on multiple features including MFCC as targets for feature extraction. The hybrid CNN-LSTM architecture is adopted by virtue of its strong capability to deal with sequential data and time series, which mainly consists of four convolutional layers and three long short-term memory layers. As a result, the architecture achieved an accuracy of 61.07% comprehensively for the test set, among which the detection of anger and neutral reaches a performance of 75.31% and 71.70% respectively. It can also be concluded that the classification accuracy is dependent on the properties of emotion to some extent, with frequently-used and distinct-featured emotions having less probability to be misclassified into other categories. Emotions like surprise whose meaning depends on the specific context are more likely to confuse with positive or negative emotions, and negative emotions also have a possibility to get mixed with each other.
Comparing supervised and unsupervised learning in image denoising
Authors: Wang Hanyun
Published: July 2023

Recent studies on unsupervised learning have attracted people's increasing attention. In particular, Deep learning has developed rapidly in recent years. With the development of media images, people's demand for image noise reduction is increasing, and the requirements are becoming more and more strict. The traditional methods used for image noise reduction are far from meeting people's requirements, and people are eager to find a more efficient image noise reduction technology. In recent years, the technology of using a convolutional neural network for image noise reduction has become more and more skilled. This paper explores the reliability of image noise reduction technology using a convolutional neural network as an autoencoder, and whether good performance is maintained without using clean images. The article aims to compare the performance with supervised learning and unsupervised learning by deep learning in image denoising.
The relationship between blockchain and government regulation and governanceThe distinctions between different countries
Authors: Chen Pingxin
Published: July 2023

Blockchain technology, derived from the underlying technology of Bitcoin, is a decentralized infrastructure and distributed computing paradigm that has emerged with the growing use of digital technology in the financial sector[1]. This digital ledgers for distributed storage has brought technological innovation for governments to control in areas such as various financial institutions and technology companies. Blockchain is being developed in major countries around the world, and this technology does bring opportunities for innovation in government governance as well as challenges for government regulation of ICOs. In the era of economic globalization, to develop blockchain technology comprehensively also needs to face policies and regulations in different countries. This paper will explore the relationship and impact between blockchain and government regulation and governance through directed analysis method, combined with application cases, and compare the regulatory system under different countries' policies and national conditions.
A study on dyslexia detection using machine learning techniques for checklist, questionnaire and online game based datasets
Authors: Santhiya S , KanimozhiSelvi C S
Published: July 2023

Learning disabilities are one of the most common developmental disorders in children. Learning is fundamental to a child's overall development. Children struggle with daily activities such as reading, speaking, organizing things, and so on. The specific learning disorders are classified into dyslexia, dysgraphia, and dyscalculia. Children who find difficulty in reading and are unable to differentiate speech sounds are said to have dyslexia. Dysgraphia and dyscalculia deal with written and mathematical calculations. Early diagnosis and detection are essential for early recovery from diseases. The proposed article presents methodologies and techniques used for detecting dyslexia. The primary contribution of this paper is a comparative analysis of various machine learning algorithms for diagnosing dyslexia, including SVM, KNN, Logistic Regression, K-mean Clustering, Oversampling, and Ensemble methods. Deep learning methods such as CNN and LeNet architecture have been used to identify dyslexia. The proposed study examines recent advances in detecting dyslexia using machine learning and deep learning approaches and identifies prospective research areas for the future.
SLAM based vision self-navigation robot with RTAB-MAP algorithm
Authors: Wen Z.
Published: July 2023

The classic 2D SLAM are not good enough in nowadays environment. This report uses virtual machine with Ubuntu based Slam_bot package, based on the RTAB-MAP algorithm and Vision SLAM mapping to simulate the four-wheeled robot to autonomously navigate to the target point in various environments. Also, this report introduces a RGBD-SLAM based algorithm which combines the visual and depth data to process the data collect from the sensors. This robot has many sensors like, lidar sensors, RGB vision camera and odometry sensors. To see how the RTAB-MAP algorithm with RGB-D sensor replace for the 2D SALM. As results, the robot with RGB-D and RTAB-MAP algorithms have very good performance. The results show that the navigation system can complete the navigation and localization in lots of complex situations. However, some problems still exist, the speed of the robot is not fast. This may limit the application of the self-navigation robot to a certain extent, like some emergency occasion.
Research on using AdaBoost with K-Means and SMOTE to predict the incidence of diabetes
Authors: Gao Hongquan , Zuo Dan
Published: July 2023

Diabetes is one of the most diseases in the world. In the last 40 years, the number of persons worldwide with diabetes has tripled. There were 108 million patients over the age of 18 in 1980 and 422 million in 2014, accounting for 8.5% of the entire population at that time. Diabetes directly caused 1.5 million fatalities worldwide in 2012, with hyperglycemia-related illnesses accounting for 2.2 million deaths. Diabetes is expected to be the 7th greatest cause of death by 2030 according to the World Health Organization. As the risk of diabetes increases, machine learning algorithms are used to improve early diagnosis of diabetes, and various researchers have also done some corresponding algorithms for predicting diabetes machine learning. As a commonly used machine learning algorithm, AdaBoost integrated learning algorithm is superior in the diagnosis and prediction of diabetes mellitus. In this paper, it is proposed that a hybrid model to detect the risk of diabetes. This hybrid model is detected and eliminated by K-means-based outliers, synthesizing the distribution of minority data oversampling techniques (SMOTE), and Adaboost to classify diabetes. According to the final experimental result, the model prediction accuracy is 0.950 after using the hybrid model in the PIMA dataset. In the future, if a larger number of sample training data are utilized for training, the model's accuracy will improve.
Construct stochastic processes model to solve graphic and math problems
Authors: Ding Shuyang
Published: July 2023

The use of probabilistic reasoning has been used to a variety of applications, such as image identification, computer diagnostics, stock price prediction, movie recommendation, and cyber intrusion detection. However, the range of probabilistic programming was limited until recently (partly due to the low computing capacity), and the bulk of inference techniques needed to be developed manually for each task. However, in 2015, using a 50-line probabilistic computer vision program, 3D representations of human faces were produced from 2D images of those faces.Use a computer to model various complex stochastic phenomena. All projects are programmed in java language. Find the actual number of 1s in a binary number. Formulate and analyze mathematical models to real life phenomena like Data Matrix and QR code. Those code mentioned above can provide a link to the real-life website or some certain message needed to be shown. using some random numbers to model uncertainty. To model some fractals. The first fractal maybe not self-avoiding. But the second one will never meet the same path for twice. To apply the concept stochastic processes. More java features and some random fractals and regression. Multiple factor analysis.
Machine learning algorithm and training in GoTake three influential program as example
Authors: Zhang Qiao
Published: July 2023

In 2017, AlphaGo, an artificial intelligence in Go, beat KeJie----the No.1 Go player in 3-0, which have surprised the world, and artificial intelligence came to the attention of the public again. In this article, we take three influential artificial intelligence Go----AlphaGo, AlphaGo Zero and KataGo, as example to discuss how artificial intelligence Go work. We discuss them about their structures and training methods one by one in chronological order, which can also show the process of their development. In addition, some of the structures and training methods are enlightening to us, and we expect them can work in other fields.
Motion estimation algorithm and architecture survey
Authors: Chen Shengyang
Published: July 2023

Motion estimation is a key part of video temporal characteristics analysis including video filter and compression. Increasing requirements for high-quality video image processing have confirmed the necessity of researching motion estimation. Current motion estimation methods, including high-efficient fast motion estimation algorithms and hardware architecture designs, achieved different performances from different perspectives. In this paper, we focus on analyzing typical fast algorithms and hardware architecture designs for motion estimation, comparing the used methods, and pointing out the basic ideas of motion estimation research schemes. In terms of theoretical implications, the research contributed to a more comprehensive reference for fast motion estimation algorithms and their hardware architecture designs.
Research on the application of artificial intelligence to auto-driving cars
Authors: Lin Ziyang
Published: July 2023

Since the concept of artificial intelligence was introduced in the 1950s, artificial intelligence technologies have emerged more and more frequently. Besides, the application of artificial intelligence technologies in driverless cars has increased, especially in the field of image recognition. Many deep learning methods of image recognition have emerged in the field of autonomous driving. The primary purpose of this paper is to highlight the importance and functionality of using neural networks and image recognition in artificial intelligence for driverless functions. This paper also provides a comprehensive review of the core aspects of driverless technology, the role of image recognition and person recognition in environment perception, the impact of deep learning on driverless behavior decisions, and driverless vehicle kinetic energy control systems. Although the driverless car technology is now being updated, all three modes have great accuracy and results. However, each subsystem still faces many problems and challenges, which may be solved in future research. The driverless car technology would be promoted on a large scale after its safety and suitability are ensured.
Research of the methods on facial expression recognition
Authors: Chen Xuanyi , Ding Yuyao , Li Zhaoheng
Published: July 2023

As traditional machine learning and deep learning have developed recently, the recognition of facial expressions has been paid more attention by domestic and foreign scholars. First of all, this paper introduced the common data sets of single mode, traditional feature extraction methods and more common expression classification methods in detail, pointing out that the present single-mode expression recognition does not perform well in practical application scenarios, and cannot obtain good recognition results in complex environments. At the same time, the data sets are relatively simple and the number is small. Then, three recognition methods based on multimodality are introduced: Fusion at the feature, decision, and hybrid levels. The advantages and disadvantages of the three measures are minute described respectively. Finally, the thesis is summarized. In addition, the future development of more general and richer high-quality expression datasets is prospected and the improvement of current multimodal fusion technology are prospected.
Research of target detection method YOLO
Authors: Nie Rongyu
Published: July 2023

Regression theory is used by YOLO technology to build the one stage detection technique. It merely employs a trunk CNN to predict various targets using the "feature extraction-direct regression" method. In comparison to previous algorithms, it detects things much faster and with far higher accuracy. Researchers have become interested in the YOLO model because it is widely employed in sectors such as autonomous driving, camera display, video surveillance, vehicle identification, face recognition, remote sensing satellite, infrared detection, and others. In this study, the model structural properties of the yolo model and the yolov1-v7 models are primarily analyzed and contrasted. According to the model design perspective, it compares and summarizes the structural enhancement and corresponding performance optimization of each model in the model structure, assesses the benefits and drawbacks of each model, and assesses their performance in light of the actual application impact of each model and the primary application fields, serving as a reference for the study of related topics. The article's summary and future direction are provided at the end.
A study on the application and limitations of artificial intelligence in the treatment of lung cancer
Authors: Zhou Yuhao
Published: July 2023

Lung cancer in China has the highest incidence rate and mortality rate. One reason is that it is difficult to make an early diagnosis. Artificial intelligence (AI) is a revolutionary technology rising at present. Combined with medical images and mechanical systems, it can diagnose and predict diseases through retrospective machine learning training of large sample cases. In this paper, the author studies the current application and limitations of AI in the medical treatment of lung cancer. Conclusions can be drawn that AI technology can be used for medical treatment because it has strong computing power and is more accurate than human beings. It can be used to operate some clinical operations that human beings cannot complete. Additionally, in order to achieve a comprehensive and standardized clinical application of AI in medical treatment, prospective, multi-center, and large sample studies are also needed to verify the robustness, accuracy, and generalization of the model.
Patient-Reported Outcome Measurement and Minimal Clinically Important Difference for Hand Surgeons
Authors: Garcia Brittany N. , Tyser Andrew , Roca Hernan , Kazmers Nikolas H.
Published: July 2023

Patient-reported outcome measurement (PROM) tools are used to evaluate health status and response to treatment and have been integral in the effort to improve the quality of care provided. Patient reported outcomes (PROs) have garnered additional attention since becoming a priority of the National Institutes of Health in the early part of this century, and their use in both clinical practice and research has subsequently increased. In the upper extremity, a variety of PRO instruments exist that can assist physicians in their ability to track and/or prognosticate outcomes, make comparisons between treatments as well as strengthen research methodologies, and help determine the value of care. A more complete interpretation of the clinical significance of patient-reported outcome measurements is informed by parameters such as minimal clinically important difference, substantial clinical benefit and patient acceptable symptom state
Comparison of Mean Retinal Nerve Fiber Layer Thickness on Optical Coherence Tomography (OCT) in Patients of Primary Open Angle Glaucoma (POAG) After Trabeculectomy vs Anti Glaucoma Medication
Authors: Latif Sidra , Riaz Rashida , Qamar Anjisha , Anjum Misra , Bibi Irfana , Shoukat Tahir , Zafar Humera
Published: July 2023

Trabeculotomy is a surgical procedure in which a fistula is created between anterior chamber and sub-conjunctival space for drainage of aqueous. Glaucoma is a chronic disease. Objective: To compare the mean retinal nerve fibre layer thickness in patients of primary open angle glaucoma after trabeculectomy versus anti glaucoma medication. Methods: This Randomized controlled study done in Institute of Ophthalmology, Eye Unit III, KEMU, Mayo Hospital, Lahore from 10th Nov 2021 to 10th May 2022. Non-Probability Convenient Sampling technique used for sample size calculation. 60 patients were selected fulfilling the inclusion and exclusion criteria. They were divided into two groups of 30 patients each. Group A patient were given topical anti-glaucoma treatment while Group B patients underwent trabeculectomy. Pre and three months post anti-glaucoma medication/trabeculectomy, OCT test was done and thickness of retinal nerve fibre layer documented. Results: In group A, mean post-treatment RNFL thickness was 0.076 ± 0.052 microns after three months of topical treatment.  In group B, mean post-treatment RNFL thickness was 0.080 ± 0.0048 microns three months after trabeculectomy. Conclusions: Trabeculectomy increases the mean retinal nerve fibre layer thickness more than anti-glaucoma medication when measured on OCT.
Fecal Continence in Patients with Low Rectal Malformation After Anoplasty
Authors: Baloch Abdul Jabbar , Perveen Shazia , Kumari Nitu , Aslam Sana
Published: July 2023

Anorectal malformations (ARMs) affect between 1:2000-2500 births comprising a heterogenous spectrum of malformations that vary considerably in their anatomical characteristics, complexity, and functional prognosis. Occasionally, the diagnosis is delayed to later infancy especially in cases where the bowel outlet is stenotic but at or near the proper anal position. Objective: To determine the frequency of fecal continence in patients with low rectal malformation after anoplasty. Methods: This was prospective Cross-Sectional Study conducted at Department Pediatric Surgery, National Institute of Child Health (NICH), Karachi, Pakistan from September, 2020 to March, 2021. All patients who fulfilled the inclusion criteria and visited to NICH, Karachi were included in the study. Informed consent was taken from parents / guardians after explaining the procedure, risks and benefits of the study. Parents/Guardian of patients were asked to fill the study questionnaire containing the Kelly Scoring System to assess the status of fecal continence of the patients. All the collected data were entered into the proforma and analyzed on SPSS. Results: Out of 189 patients, 63% were male and 37% were female. Fecal continence was found in 71.4% patients, statically significant with Body Mass Index. Mean ± SD of age was 3.7 ± 1.5 days. Conclusions: It is to be concluded that fecal continence is a frequent finding of low rectal malformation. Patients with low rectal malformation should be worked up for the fecal continence after anoplasty.
Impact of Endurance Exercises on Knocked Knees as a General Health Concern
Authors: Munzer Muhammad , Khan Alamgir , Jamil Muhammad , Iqbal Butt Muhammad Zafar , Soomro Javed Ali , Basit Abdul , Inamullah . , Ahmad Adnan
Published: July 2023

Knocked knees are a problem in children and adults, making it challenging to walk or run and causing knee pain. In this problem, the knees gradient inward while the ankles remain spaced apart. Objective: To analyse the impact of endurance exercises on knocked knees as a general health concern. Methods: The study participants were randomly selected from the department of sports science and physical education, University of Punjab, Pakistan. Subjects were categorized as a control group (CG) and an experiential group (EG). Each group was comprised of twenty subjects. All the subjects were informed about the risk and benefits of participation in the study. Thus, written informed consent was taken from each subject. In addition, Ethical approval (293/SPS) was also obtained from the University of the Punjab, Lahore, Pakistan. Results: The mean and standard deviation during the pre-test were 50.60±2.35, and the mean and standard deviation during the post-test was 53.05±2.33. The t value was 1.788, and Sig was .96. Therefore, the table shows no significant difference in CG in knee-knocking before and after training sessions imposed upon EG. The mean and standard deviation of EG during the pre-test was 50.00±2.07, and the mean and standard deviation of EG during the post-test was 58.35±2.20. The t value was 17.376, and Sig was .000. Therefore, there was a significant difference during pre- and post-test EG analysis in knee-knocking. Conclusion: Based on the analysis, the researcher concluded that exercise has a vital role in rehabilitating the knocked knee.
ANALYSIS OF THE NATURE OF FINAL AND BINDING DECISIONS OF THE NATIONAL SHARIA ARBITRATION BOARD (BASYARNAS) IN SHARIA ECONOMIC DISPUTES
Authors: Tehedi Tehedi
Published: July 2023

The national sharia arbitration body (Basyarnas) is a non-litigation sharia economic dispute resolution institution that is considered capable of resolving disputes quickly, fairly and providing a win-win solution for the disputing parties. In addition, the decision is final and binding, meaning that the decision is a final decision that must be obeyed, the decision is binding on the parties to the dispute and there are no legal remedies for appeal, cassation or review as contained in litigation dispute resolution in court. However, at the practical level, the Basyarnas decision can be pursued by legal remedies to cancel the decision by submitting it to the court as also stated in Law Number 30 of 1999 concerning arbitration and alternative dispute resolution in article 70. This raises an indication of legal uncertainty or unclear nature of the final and binding contained in the Basyarnas decision. This study uses a normative juridical approach with a juridical descriptive analysis. This means that the approach taken is by examining the approaches to theories, concepts, studying the laws and regulations concerned with this research or the statutory approach. The results of this study conclude that the decision of the National Sharia Arbitration Board cannot be said to be final and binding because legal remedies can still be made through cancellation of the decision to the Court. The existence of the elements contained in Article 70 of Law Number 30 of 1999 the request for annulment causes uncertainty or unclear meaning of the final and binding nature and is contrary to the basic purpose of law, namely to provide justice, benefit and legal certainty.
Об одной смешанной 3D задаче теории упругости для ортотропной пластинки
Authors: Япуджян В. Т.
Published: July 2023

Рассмотрена смешанная трехмерная задача для ортотропной прямоугольной пластинки. Верхней кромке пластинки сообщено нормальное перемещение, а тангенциальные компоненты напряжений равны нулю. Асимптотическим методом решения сингулярно возмущенных дифференциальных уравнений найдено решение внешней задачи. Выявлены случаи, когда это решение становится математически точным. Приведен иллюстрационный пример, учитывающий также вес пластинки.
Օրթոտրոպ ուղղանկյուն սալի համար դիտարկված է խառը եռաչափ խնդիր: Սալի վերին նիստին հաղորդված է նորմալ տեղափոխություն, իսկ լարումների տանգենցիալ բաղադրիչները հավասար են զրոյի: Սինգուլյար գրգռված դիֆերենցիալ հավասարումների լուծման ասիմպտոտիկ մեթոդով որոշված է արտաքին խնդրի լուծումը: Ի հայտ են բերված դեպքեր, երբ այդ լուծումը դառնում է մաթեմատիկորեն ճշգրիտ: Առկա է իլյուստրացիոն օրինակ, որը հաշվի է առնում նաև սալի կշիռը:
A mixed 3D problem is considered for the orthotropic rectangular plate. Normal displacement is transmitted to the upper edge of the plate, and tangent components of tensions are equal to zero. The solution of the outer problem is found by the asymptotic method of solving singularly perturbated differential equations. Cases, when that solution becomes mathematically precise are revealed. An illustrative example, which takes into account also the weight of the plate is given.
FINANCIAMENTO DO SISTEMA ÚNICO DE SAÚDE: REFLEXOS DA EC 95/2016 NA GARANTIA DO DIREITO À SAÚDE NO HOSPITAL MUNICIPAL DE ALTA FLORESTA D’OESTE - RONDÔNIA
Authors: Ferreira Andréia Dantas Pinto , Fuzari Claudinéia Pereira , Vieira Cleudson da Silva
Published: July 2023

O presente artigo tem como objetivo analisar os reflexos da limitação orçamentária definida com a entrada em vigor da Emenda Constitucional N° 95 de 2016 no financiamento do Sistema Único de Saúde (SUS). Para isso, verificou-se quais foram os impactos negativos no orçamento da saúde destinado para o atendimento na Média e Alta Complexidade do Município de Alta Floresta d’Oeste - RO, bem como, as possibilidades de desestruturação das políticas públicas relacionadas ao atendimento à demanda do município. Para a realização dessa análise foram utilizados materiais bibliográficos e informativos disponibilizados nos portais de transparência. Dessa forma, os resultados obtidos foram compilados de forma qualitativa, onde foi possível concluir que a limitação orçamentária trazida pela Emenda Constitucional N° 95 aumentou a defasagem no orçamento da saúde, inclusive, nas receitas oriundas das transferências federais. Consequentemente, esse investimento inferior a real necessidade e demanda pelo sistema fez com que o município tivesse que investir mais em saúde do que sua capacidade financeira para isso, e mesmo com todo esse esforço dos gestores municipais, a saúde no município encontra dificuldades para atender toda a demanda da população.
The Great Tzotzil Dictionary of Santo Domingo Zinacantan with Grammatical Analysis and Historical Commentary, Volume III: Spanish-Tzotzil
Authors: Laughlin Robert M. , Haviland John B.
Published: July 2023

This dictionary of Tzotzil (Mayan) vocabulary from the town of Zinacantan, Chiapas, Mexico, was edited by the author over a period of nine years. The original manuscript, compiled by an anonymous Domimcan friar, probably at the close of the 16th century, disappeared during the Mexican Revolution but a manuscript copy of 351 pages survives. It was made around 1906 at the behest of the Bishop of Chiapas, Francisco Orozco y Jimenez. The approximately 11,000 Spanish-Tzotzil entnes have been translated into English. Following the format of The Great Tzotzil Dictionary of San Lorenzo Zinacantan. the colonial Tzotzil has been ordered by roots. The spelling has been corrected and modernized. Doubtful interpretations are stated and problems are brought to the reader's attention, with frequent reference to the existing colonial Tzeltal dictionaries. Ea.ch entry is analyzed grammatically according to a system devised by John B. Haviland. All entries are keyed to their original location in the manuscript copy. A second section provides an English-Tzotzil dictionary and index for the thesaurus that follows. To make the cultural contents of this dictionary more readily available to anthropologists and historians, the thesaurus groups the Tzotzil terms under 36 cultural categories such as world, movement, life cycle, emotions, agriculture, ailments, religion, etc. Of special interest is metaphoric speech, subdivided into 10 categories. A third section presents the Spanish-Tzotzil dictionary slightly abbreviated and with the spelling of both languages modernized. A facsimile of the manuscript copy is also offered. Preceding the dictionaries is a historical sketch that places the original in its colonial setting, compares it to other 16th and 17th century lexicographic efforts, and suggests a possible author. The lives of the five individuals responsible for the preservation of the manuscript copy are traced. John B. Haviland, drawing upon the contents of the manuscript, provides a detailed analysis of the grammatical changes that have occurred in Tzotzil over the past four centuries.
RELATIONS BETWEEN MENTAL DISEASES, PER CAPITA INCOME AND SOME SOCIO-ECONOMIC VARIABLES: RESEARCHES ON BRICS-T COUNTRIES
Authors: GÜLTEKİN Ömer Faruk , EMSEN Ömer Selçuk
Published: July 2023

Mental illnesses are one of the great social problems of the last period. Mental diseases, which are an important public health problem in the changing and developing world, can be considered as an output of the economic development process. From this point of view, the relationship between mental diseases, which is one of the outputs of the economic development process, and some socioeconomic variables in the BRICS-T countries, which have an important place in the world economy, has been investigated in the study. In this study, the effects of variables representing the level of income per capita and education, health, democracy, and income distribution on mental diseases for the period 1990-2019 were investigated with the help of the Kuznets model. Firstly, descriptive statistics, heteroscedasticity, autocorrelation, and cross-section dependency tests were applied. Secondly, GLS and Driscoll-Kraay estimation tests used in the estimation process, and it was determined that there was a U-shaped relationship between mental illnesses and per capita income in the BRICS-T country group. Konya causality test applied to determine the causality relationships between the variables. According to the results, it has been determined that there are some unidirectional and bidirectional causality relationships both in some country groups and between some variables.
Modelo de predicción de deserción: Un estudio de caso de estudiantes de la Universidad Politécnica Estatal del Carchi
Authors: Montalvo Márquez Francisco Javier , Sánchez Pozo Nadia Nathaly
Published: July 2023

Introducción: La tasa de abandono estudiantil en las instituciones de educación superior es un problema global que requiere soluciones personalizadas y adaptadas a cada institución. El presente artículo se realiza en la Universidad Politécnica Estatal del Carchi (UPEC) en Ecuador.
Objetivo: Identificar los factores determinantes del abandono universitario mediante un modelo logístico que permita predecir si un estudiante puede abandonar la universidad de manera prematura.
Métodos: Como técnica de modelado estadístico multivariante se utiliza un modelo de regresión logística LR. La muestra de estudiantes corresponde a 3821 registros de matrículas en la UPEC.
Resultados: Los resultados evidencian que el modelo logístico propuesto presenta una precisión del 90%. Además, se identificó una relación inversa entre la deserción estudiantil, el número de miembros en el hogar y el nivel educativo del padre y la madre; por lo que se evidencia la necesidad de instaurar medidas de apoyo y prevención específicas para los estudiantes de hogares con menores niveles educativos y mayores cargas familiares.
Conclusiones: El abandono estudiantil en la UPEC ocurre principalmente durante el primer nivel de carrera, determinando además que los factores relevantes que influyen en la deserción estudiantil en esta universidad son: la edad, el número de miembros en el hogar, el nivel de estudio y el promedio académico. Esta información permitirá a las autoridades universitarias plantear medidas preventivas para mejorar la permanencia y el éxito académico de sus estudiantes.
Guía metodológica para mejorar el uso de las TIC del docente en el proceso de enseñanza-aprendizaje de la Unidad Educativa “Rosa Herlinda Zambrano Ganchozo”
Authors: Vélez Bravo Pepina Elizabeth , Santana Sardi Gustavo Adolfo
Published: July 2023

Introducción: El presente articulo está relacionado a las Tecnologías de Información y Comunicación donde se consideran en la actualidad un recurso necesario tanto en la educación como para otros ámbitos educativos. Objetivo: diseñar una guía metodológica para mejorar el uso de las TIC del docente en el proceso de enseñanza y aprendizaje de la Unidad Educativa “Rosa Herlinda Zambrano Ganchozo”. Método: esta investigación posee un enfoque mixto, ya que se utilizaron métodos, técnicas e instrumentos para el procesamiento de la información desde una perspectiva tanto cualitativa como cuantitativa. Los instrumentos aplicados fueron la entrevista y la encuesta, se involucró a 1 directora, 4 docentes y 30 estudiantes de básica superior de la Unidad Educativa. Resultados: Se obtuvo que los docentes a pesar de tener conocimientos básicos de las TIC, no están suficientemente capacitados para darle al estudiante una enseñanza innovadora.  Conclusión: el uso de la tecnología en el proceso de enseñanza y aprendizaje en el apoyo docente es muy fundamental, ya que permite que los conocimientos impartidos hacia los estudiantes sean más productivos y de fácil adquisición.
Fluoruro diamino de plata como terapia para la inactivación de lesiones de caries cavitadas en dientes primarios
Authors: Sotillo Virginia , Limongi Isabella , Medina A. Carolina , Martínez Vásquez María Gabriela
Published: July 2023

La caries dental es una enfermedad de etiología multifactorial mediada por la biopelícula, que se activa con períodos prolongados de pH bajo, causando la pérdida y disolución de los minerales del diente. El fluoruro de diamino de plata (FDP) es un medicamento tópico utilizado para retrasar o detener el avance de la caries dental. Se caracteriza por ser un líquido incoloro compuesto por plata y fluoruro. La plata tiene propiedades antibacterianas mientras que el fluoruro remineraliza el esmalte dental afectado. El siguiente trabajo tiene como objetivo describir la acción y eficacia del FDP como terapia para la inactivación de lesiones de caries cavitadas de dientes primarios en pacientes pediátricos; corresponde a un estudio de revisión narrativa basado en la búsqueda de artículos científicos en las bases de datos: PubMed, Scielo, ResearchGate, ScienceDirect y Scopus. Se concluyó que el uso del FDP, no sólo limitará el avance de la caries dental, sino disminuirá costos, tiempos de trabajo y la ejecución de procedimientos que puedan incomodar al paciente; además, se considera una terapia mínimamente invasiva que puede ser utilizada en pacientes de corta edad, pacientes con alguna discapacidad y de difícil comportamiento.
The Smart Performance Analysis of Network Scheduling Framework for Mobile Systems in Cloud Communication Networks
Authors: Logeshwaran J. , Kiruthiga T.
Published: July 2023

This paper presents a smart performance analysis of a network scheduling framework for mobile systems in cloud communication networks. It begins by introducing the concept of cloud communication networks and then discussing the key features of the network scheduling mechanism. Following that, the paper presents an overview of existing scheduling algorithms for cloud communication networks and discusses their relative advantages and disadvantages. The paper then outlines a smart network scheduling framework proposed to address the problems associated with existing scheduling mechanisms. The proposed framework is evaluated through extensive simulations to explore its performance in different scenarios. The results demonstrate that the proposed network scheduling framework performs better than existing algorithms with regards to system accuracy, precision, recall and F1-score. The paper proposes a few future directions for further research and development in this area.
AI Cloud Computing in Education
Authors: Rinkey Dr. , Bhatia Dr. Raino
Published: July 2023

Cloud AI is a growing field that focuses on creating intelligent solutions countless industries. AI Cloud Computing provides machine learning and statistical tools that can work advanced calculations that companies can use to build dynamic applications. AI Cloud Computing focuses create smart applications, help companies use Big Data, implement advanced application algorithms functionality, as well as predicting and anticipating future growth, which greatly contributes to the profitability and Longevity. This article examines the evolution of artificial intelligence in cloud services and its benefits. There is no denying that AI and cloud computing have enhanced innumerable lives. People use digital assistants like Siri, Google Home, and Amazon's Alexa on a daily basis. These assistants enable simple spoken commands that, among other things, can buy an item, change the temperature in a smart home, or play music on a linked speaker. AI approaches are used on current cloud computing platforms to add value. To give users more functionality, SaaS (Software-as-a-Service) providers integrate AI technologies into larger software packages.
Vibrio hollisae isolated in a Hydropneumothorax
Authors:   Bacteriology, Virology and Hygiene Laboratory department, Ibn Rochd University Hospital of Casablanca,, WAHBI Hind , OUFASKA Sara ,   Bacteriology, Virology and Hygiene Laboratory department, Ibn Rochd University Hospital of Casablanca,
Published: July 2023

Introduction: Vibrio hollisae is a bacterium that is commonly responsible of digestive infections but in very rare cases, it can be isolated in other biological liquid. Case report: This case report is about a young man who suffered from an hydropneumothorax infected by Vibrio hollisae, following a chylous pleurisy drainage. The patient improved after surgical drainage and adequate antibiotherapy. Discussion and conclusion: Our case rises awareness of the exra-intersinal localisation of vibrio hollisae. The microbiologist should know that it may not grow in MacConkey plate agar even if it’s a gram-negative bacillus. The best growth is obtained with sheep blood agar plate.
CHANGES IN BAUL’S TRADITIONAL TRENDS: AN EXPERIMENTAL STUDY AT LALON AKHRA IN KUSHTIA
Authors:   Rabindra Maitree University, Kushtia, Bangladesh, Zalil M. A. , Samsujjoha M. ,   Dhaka Imperial College, Bangladesh, Islam M. S. ,   Trust University, Barishal, Bangladesh
Published: July 2023

Identifying the development of traditional Baul inclinations and their underlying reasons was the aim of this investigation. The major goal of this study was to determine how historic trends in Baul had changed. Baul’s trends refer to a particular cult that originates from the diverse folk beliefs and ideas of a particular group of people who are considered the ambassadors of folk religious activities, beliefs, and thoughts. This Baul group has some original and traditional trends. With the passage of time, the Bauls have begun to mix with the non-Bauls and lead lives like them, and their traditional trends are changing for some specific reasons. Therefore, this study has attempted to focus on the changes in Baul’s traditional trends in relation to their basic and original trends through empirical data collected through interviews and survey activities with a view to finding out what the causes are behind all such changes. This study was conducted at Kushtia district from October 2022 to March 2023. For the investigation of this present study, 40 Bauls were randomly selected from Lalon Akhra of Kushtia district. A number of pieces of literature related to this study have been reviewed to corroborate and support the primary data of this study. The data have been analyzed using descriptive and contextual methods. The findings of this study reflect that the Bauls are influenced by modernism, technology, media, and greed. The traditional trends of the Bauls are changing because of these influencing factors. This study has presented good findings on the causes of changes in Baul’s traditional trends. Thus, this study provides insightful information regarding the changes in Baul’s traditional trends.
The Importance of the Management of Micropollutants in an Advanced Wastewater Treatment Plant in the Amazon
Authors: Ribas Priscila Pauly , Santos Erickson Oliveira dos , Costa Cleideane Cunha , Sosa González Pedro Luiz
Published: July 2023

Objetivo do estudo: O estudo visa determinar a dinâmica de descarga de micropoluentes no rio Amazonas a partir de uma ETE avançada e discutir a importância da gestão na minimização dos impactos.Metodologia: Foram analisados 13 micropoluentes: ibuprofeno (IBP), paracetamol (PCM), atenolol (ATL), loratadina (LTD), cloridrato de fexofenadina (FXF), amoxicilina (AMX), 17α-ethynil estradiol (EE2), cafeína (CAF), diclofenaco de sódio (DCF), estrona (E1), estriol (E3), bisfenol A (BPA), and bis(2-etilexil) ftalato (DEHP) em amostras de efluente vindas de diferentes estágios de tratamento de uma ETE com tecnologias de tratamento avançado, em diferentes períodos do dia. A presença de micropoluentes e sua quantificação foram realizadas usando técnicas de CL-EM e CG-EM.Originalidade/Relevância: Este é o primeiro estudo realizado em uma ETE de Manaus, cidade brasileira que está localizada em um dos mais extensos sistemas fluviais do mundo. Os dados obtidos são importantes para compreender o comportamento da descarga de micropoluentes no rio Amazonas e suas implicações.Principais resultados: Depois do tratamento, os micropoluentes paracetamol, cloridrato de fexofenadina, cafeína, diclofenaco de sódio, e, bis (2-etilexil) ftalato foram detectados no efluente final.Contribuições: Os resultados obtidos neste estudo indicam a necessidade de um gerenciamento integrado, considerando abordagens técnicas, governamentais, organizacionais e comunitárias para minimizar os efeitos da descarga de micropoluentes no meio ambiente.