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Selecting the Optimal Morse Falls Scale Cut-Off Point for Patient Fall Risk

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Health 2019年第7期11卷 924-931页

作者： Sikha bagui Tyler Long Subhash bagui Department of Computer Science University of West Florida Pensacola FL USA Department of Mathematics and Statistics University of West Florida Pensacola FL USA

Patient falls have long been a difficult problem and topic of research in the inpatient hospital environment. Hospitals experience heavy financial burden due to patient falls. Preventing falls can improve patient outcomes as well as reduce financial burden on both the patient as well as the healthcare organization. In this study, we determine the optimal cut-off value for patients at risk for falls using a Falls Screening Tool, the Morse Falls Scale. This study was conducted at a community-owned hospital with 256 acute care private rooms and 36 critical care rooms. This study used only the admission Morse Falls Scale (MFS) score in its analysis.

关键词： Patient Falls Morse Falls Scale Preventing Falls Falls Risk Assessment Falls Prevention

Sentiment Analysis on Twitter Data Using Term Frequency-Inverse Document Frequency

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Journal of Computer and Communications 2022年第8期10卷 117-128页

作者： Akash Addiga Sikha bagui Department of Computer Science University of West Florida Pensacola FL USA

This study is an exploratory analysis of applying natural language processing techniques such as Term Frequency-Inverse Document Frequency and Sentiment Analysis on Twitter data. The uniqueness of this work is established by determining the overall sentiment of a politician’s tweets based on TF-IDF values of terms used in their published tweets. By calculating the TF-IDF value of terms from the corpus, this work displays the correlation between TF-IDF score and polarity. The results of this work show that calculating the TF-IDF score of the corpus allows for a more accurate representation of the overall polarity since terms are given a weight based on their uniqueness and relevance rather than just the frequency at which they appear in the corpus.

关键词： Sentiment Analysis Twitter Data Term Frequency Inverse Term Frequency Term Frequency-Inverse Document Frequency (TF-IDF) Social Media

Neurotropic effects of aspartame, stevia and sucralose on memory retention and on the histology of the hippocampus of the ICR mice(Mus musculus)

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Asian Pacific Journal of Tropical Biomedicine 2016年第2期6卷 114-118页

作者： Lejan Miguel Alabastro Villareal Rachelle Anne Montes Cruz Michael bagui Ples Rodel Jonathan Santos Vitor Ⅱ Biology Department College of Science De La Salle University

Objective: To identify the effects of the consumption of non-nutritive sweeteners on memory retention and on the histology of the ***: In this study, 20 mice were used to determine if there is an effect of consuming the maximum allowable dose of the non-nutritive sweeteners on the memory retention and on the histology of the hippocampus. The mice were distributed into four groups and the treatments were given via oral gavage: Group 1(water), Group 2(aspartame: 1 000 mg/kg), Group 3(stevia: 1 000 mg/kg) and Group 4(sucralose:16 000 mg/kg). Treatments were administered to the different experimental groups for 32 days, after which memory retention was tested using the two-day water maze *** the tests, the mice were sacrificed and the brain was analyzed histologically for neurotrophic ***: Based on the results of the two-day water maze protocol, there were no differences between the non-nutritive sweeteners and the control group. However, stevia showed high cellular apoptosis followed by aspartame, sucralose and control ***: There was no significant effect on the memory of the mice. It showed histologically however, that stevia had a significant neurotropic effect compared to the other sweeteners.

关键词： Aspartame Hippocampus Learning Memory Mus musculus Stevia Sucralose

Hematological effects of Ipomoea batatas(camote) and Phyllanthus niruri(sampa-sampalukan) from Philippines in the ICR mice(Mus musculus)

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Asian Pacific Journal of Tropical Biomedicine 2015年第1期5卷 29-33页

作者： Jessa Fidel Montejo Juan Arturo Burgos Mondonedo Matthew Genesis Aguila Lee Michael bagui Ples Rodel Jonathan Santos Vitor Ⅱ Biology Department College of ScienceDe La Salle University

Objective:To analyze the hematological effects of administering Ipomoea batatas(***)and Phyllanthus niruri(***) in the ICR ***:Powdered leaves of /.batatas and *** were fed to mice for 4 weeks.A total of six groups were used to determine the effect of the plants to the complete blood count of the *** A(blank control) mice were feed with pellets only;Group B(negative control) mice were fed with pellets coated with honey;Group C(low dosage) mice were fed with honey-coated pellets and powdered leaves of *** at 10 g/kg body weight of the mouse;Group D(high dosage) mice were fed with honey-coated pellets and powdered leaves of I,batatas at 20 g/kg body weight of the mouse;Group E(low dosage) mice were fed with honey-coated pellets and powdered leaves of *** at 10 g/kg body weight of the mouse:and Group F(high dosage) mice were fed with honey-coated pellets and powdered leaves of *** at 20 g/kg body weight of the *** blood count was performed on Days 0.14 and ***:It was shown that *** can increase the values of hematocrit and hemoglobin on both the low dose and high dose at Day 28 and red blood cells(RBC) on both Days 14 and28 of *** the other *** can increase *** and hemoglobin on Day 28 with only the low *** were no significant differences with white blood cell,absolute granulocyte,lymphocyte and monocyte,and platelet counts observed for both plant ***:*** and *** have effects on the hematocrit,RBC and hemoglobin levels in mice.

关键词： Camote Hematology ICR mice Ipomea batatas Phyllanthus niruri Sampa-sampalukan

Towards Enhanced Program Comprehension for Service Oriented Architecture (SOA) Systems

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Journal of Software Engineering and Applications 2013年第9期6卷 435-445页

作者： Eman El-Sheikh Thomas Reichherzer Laura White Norman Wilde John Coffey Sikha bagui George Goehring Arthur Baskin Department of Computer Science University of West Florida Pensacola USA Intelligent Information Technologies Corporation Indianapolis USA

Service Oriented Architecture (SOA) is an emerging paradigm for orchestrating software components to build new composite applications that enable businesses, government agencies and other organizations to collaborate across institutional boundaries. SOA offers new languages and a variety of software development tools that enable software engineers to configure software as services and to interconnect services with other services independent of differences in operating platform and programming and communicating languages. However, SOA composite applications introduce additional complexity into the construction, deployment and maintenance of software, for the purpose of aggravating the issue of program comprehension, which is at the heart of software maintenance. This article describes the challenges in SOA program comprehension and reports on the results of a two-part case study aimed at identifying information that would help a SOA software maintainer. Analysis of the results indicates a need for higher-level abstractions and visualizations that can enhance conventional text-based search to support SOA program understanding. This paper then reports on several specific abstractions, visualization methods, and the development of an intelligent search tool to enhance comprehension of the relationships and data within a SOA composite application.

关键词： Service Oriented Architecture Software Maintenance Program Comprehension Intelligent Search Abstraction Visualization Web Services

Structured Imagery Processing Strategies for Spectroscopic Measurement in Dense Solutions

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Open Journal of Applied Sciences 2017年第6期7卷 262-281页

作者： Thomas Koffi Guy-Oscar Regnima Jocelyne Bosson Olivier bagui Mensah Edoé Jérémie T. Zoueu Laboratoire d’Instrumentation Image et Spectroscopie(L2IS) Institut National Polytechnique Felix Houphou&euml t-Boigny Departementde Formation et de Recherche du Genie Electrique et Electronique Yamoussoukro C&ocirc te d’Ivoire Laboratoire de physique Fondamantale Appliquée(LPFA) Université NanguiAbrogoua Unité de Formation et de Recherche des Sciences Fondamentales Appliquées Abidjan C&ocirc te d’Ivoire

Absorbance measurement in dense media via conventional optical spectroscopy techniques leads to inaccurate results. This is mainly due to multiple scattering phenomena that contribute to the overall light extinction in the interrogated sample. This limitation imposes the use of dilute solutions for absorption spectroscopy. However, depending on the polarity of the solvent used, the absorption spectrum may vary over a given solution. Structured illumination technique offers an alternative to this problem, and provides the ability to calculate in-situ optical properties in dense media. In this paper, we propose two processing methods applied to images acquired by structured laser illumination planar imaging (SLIPI) technique to extract extinction coefficients μ_e of probed solutions: The first is based on the implementation of principal component analysis (PCA) and the second, on the calculation of Mean Value. In practice, two kinds of studies were carried out: one quantitative set of measurements within chlorophyll liquid solutions and a second set with concentrated coffee solutions, with controlled proportion and concentrations for each sample. These two proposed analytical techniques are advantageous because they are very easy to implement and provide a much simpler alternative to the previous one. Both methods offer satisfactory results, similar to those obtained with the original method which is based on 1D Fourier transform.

关键词： Spectrophotometry Dense Media Extinction Coefficient Structured Illumination Principal Component Analysis

Classification of African Mosaic Virus Infected Cassava Leaves by the Use of Multi-Spectral Imaging

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Optics and Photonics Journal 2015年第8期5卷 261-272页

作者： Mama Sangare Thérèse Atcham Agneroh Olivier Kossan bagui Issiaka Traore Abdramane Ba Jeremie Thouakesseh Zoueu Laboratoire d’Optique de Spectroscopie et des Sciences de l’Atmosphere Université des Sciences Techniques et Technologies de Bamako (USTTB) Bamako Mali Laboratoire de Phytopathologie et Biologie Végétale Institut National Polytechnique Felix Houphou&#235 t-Boigny Yamoussoukro Cote d’Ivoire Laboratoire d’Instrumentation Image et Spectroscopie Institut National Polytechnique Felix Houphou&#235 t-Boigny Yamoussoukro Cote d’Ivoire

In this work, we have used multispectral imaging technology to classify cassava leaves infected by African mosaic virus by the use of their unique spectral finger print. The spectra are extracted from transmission, reflection and diffusion of their multispectral images;they have been then analyzed with statistical multivariate analysis techniques. Principal component analysis (PCA) has been used followed by K-means and Ascending Hierarchical Classification (AHC) to endorse the classification. The contribution of this work is the use of multispectral imagery which binds both spatial and spectral information to differentiate and sort infected leaves. The results show that the multimodal and imaging spectroscopy may allow blind identification and characterization of infected leaves.

关键词： Classification Infected Leaves African Cassava Mosaic Virus Multispectral Imaging

基于随机秩次k近邻规则的不平衡数据分类算法

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应用数学进展 2020年第5期9卷 622-629页

作者：沈怡欣 SubhashC. bagui 马双鸽太原理工大学数学学院山西晋中西佛罗里达大学数学与统计系佛罗里达彭萨科拉

针对不平衡数据分类问题,为提高二分类任务中少数类样本分类准确率低的问题,本文提出一种随机秩次k近邻集成学习算法——REKRNN。该方法将秩次k近邻算法应用于Bagging集成学习框架中,同时采用混合重采样和随机子空间法平衡训练集,增加... 详细信息

针对不平衡数据分类问题,为提高二分类任务中少数类样本分类准确率低的问题,本文提出一种随机秩次k近邻集成学习算法——REKRNN。该方法将秩次k近邻算法应用于Bagging集成学习框架中,同时采用混合重采样和随机子空间法平衡训练集,增加基学习器差异性。仿真实验证明,该算法在处理不平衡数据分类任务时性能良好。

关键词：不平衡数据分类秩次k近邻集成学习重采样随机子空间法

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基于XGBoost算法的短期交通流预测

应用数学进展 2020年第9期9卷 1364-1376页

作者：刘伟 SubhashC. bagui 贾宏恩太原理工大学数学学院山西晋中西佛罗里达大学数学与统计系佛罗里达彭萨克拉美国

针对短期交通流预测问题,为完成实时精准预测,建立了一种基于Huber损失的极端梯度上升(Extreme Gradient Boosting, XGBoost)短时交通流预测模型。通过对交通流数据周期性、关联性的分析,提取时间特征,并进行时间特征重要性分析。利用... 详细信息

针对短期交通流预测问题,为完成实时精准预测,建立了一种基于Huber损失的极端梯度上升(Extreme Gradient Boosting, XGBoost)短时交通流预测模型。通过对交通流数据周期性、关联性的分析,提取时间特征,并进行时间特征重要性分析。利用该模型以及提取的特征进行交通流预测,实验结果表明:该模型优于基于均方误差损失的极端梯度上升模型以及基于平均绝对误差损失的极端梯度上升模型。同时,该模型较梯度提升回归模型、支持向量机回归模型具有更高的预测精度,各误差指标小,且模型训练时间短,符合短时交通流预测所要求的时效性。

关键词：交通流预测极端梯度提升(XGBoost) Huber损失函数特征重要性分析