Physical Sciences and Mathematics Commons^™

Prevalence And Determinants Of Pre-Lacteal Feeding: Insights From The 2017 Indonesia Demographic And Health Survey, Siti Nurokhmah, Siti Masitoh, Kusuma Estu Werdani

Kesmas

Pre-lacteal feeding is widely known as a distraction to exclusive breastfeeding, and the malpractice continues to be prevalent in Indonesia. Therefore, this study aimed to explore the potential determinants of pre-lacteal feeding among mothers of infants below 24 months. A sample of 6,455 mother-infant pairs from the 2017 Indonesia Demographic and Health Survey (IDHS) was used. Also, multivariate logistic regression was employed to identify factors associated with pre-lacteal feeding practice. In Indonesia, 44% of infants were introduced to solid/liquid feeds in their first three days of life. Infant formula was the most common pre-lacteal feed given, followed by any other …

The Significance Of Super Depo Sutorejo: Waste Management Project In Surabaya Municipality, Indonesia, Yohanes Kambaru Windi, Dyah Wijayanti, Eko Rustamaji Wiyatno, Loetfia Dwi Rahariyani

Kesmas

The Super Depo Sutorejo Surabaya (SDSS) Project was created to separate household waste into fractions, but its separation effect is unknown. This study assessed the significance of the project in sorting general waste into biodegradable, non-biodegradable, and assorted. The t-test compared the means of general and biodegradable waste (normally distributed). The non-biodegradable and assorted waste were not significantly distributed; therefore, the Wilcoxon Signed Ranks Test was used to compare their medians against general waste. The multivariate analysis compared the significance level of each waste fraction. Each statistical analysis showed that the SDSS significantly sorts the general waste. The p-values were …

Inter-Related Factors Influencing Sexual Quality Of Life Among Women Living With Hiv In Banten Province, Indonesia: A Mixed Methods Study, Dyah Juliastuti, Judith Dean, Yati Afiyanti, Lisa Fitzgerald

Kesmas

Socio-cultural concerns often restrict women's sexual rights and well-being living with HIV (WLHIV) in developing countries. These convergent parallel mixed methods study combined quantitative and qualitative approaches to explore factors influencing WLHIV sexual quality of life in Banten Province, Indonesia. A 2017 cross-sectional survey of 207 reproductive-aged WLHIV was analyzed using univariate and multivariate logistic regression statistics. Furthermore, in-depth interviews with a sub-sample of survey participants (n = 30) were thematically analyzed. Most of the women (60%) involved reported loss of sexual pleasure and depressed sexual life. Meanwhile, 48% affirmed low sexual quality of life which was associated with unemployment …

Improving Multi-Threaded Qos In Clouds, Weiwei Jia

Dissertations

Multi-threading and resource sharing are pervasive and critical in clouds and data-centers. In order to ease management, save energy and improve resource utilization, multi-threaded applications from different tenants are often encapsulated in virtual machines (VMs) and consolidated on to the same servers. Unfortunately, despite much effort, it is still extremely challenging to maintain high quality of service (QoS) for multi-threaded applications of different tenants in clouds, and these applications often suffer severe performance degradation, poor scalability, unfair resource allocation, and so on.

The dissertation identifies the causes of the QoS problems and improves the QoS of multi-threaded execution with three …

Mechanisms Of Oscillations And Polyglot Entrainment In Neuronal And Circadian Models, Emel Khan

Dissertations

Entrainment is a type of synchronization in which the period of an endogenous oscillator matches the period of an external forcing signal and a stable phase relationship is maintained between them. Entrainment patterns are described in terms of the number of input oscillations (N) that are phase-locked to a number of output oscillations (M), referred to as N:M patterns. Arnold tongue diagrams are used to depict the regions of N:M entrainment patterns in the input period-amplitude parameter space. Although the entrainment of self-sustained oscillators by periodic forcing are well investigated is a well-studied problem, entrainment of damped oscillators has been …

A Cancelable Biometric Authentication System Based On Feature-Adaptive Random Projection, Wencheng Yang, Song Wang, Muhammad Shahzad, Wei Zhou

Research outputs 2014 to 2021

© 2020 Elsevier Ltd Biometric template data protection is critical in preventing user privacy and identity from leakage. Random projection based cancelable biometrics is an efficient and effective technique to achieve biometric template protection. However, traditional random projection based cancelable template design suffers from the attack via record multiplicity (ARM), where an adversary obtains multiple transformed templates from different applications and the associated parameter keys so as to assemble them into a full-rank linear equation system, thereby retrieving the original feature vector. To address this issue, in this paper we propose a feature-adaptive random projection based method, in which the …

Land Cover Image Segmentation Based On Individual Class Binary Segmentation, Sathyanarayanan Somasunder

Theses

Remote sensing techniques have been developed over the past decades to acquire data without being in contact of the target object or data source. Their application on land-cover image segmentation has attracted significant attention in recent years. With the help of satellites, scientists and researchers can collect and store high resolution image data that can be further processed, segmented, and classified. However, these research results have not yet been synthesized to provide coherent guidance on the effect of variant land-cover segmentation processes. In this paper, we present a novel model that augments segmentation using smaller networks to segment individual classes. …

Dimensionless Analysis Of Trajectories Of Cylindrical Objects Dropped Into Water In Two Dimensions, Yi Zhen

University of New Orleans Theses and Dissertations

Nondimensionalization is powerful technique and is widely applied in the study of fluid mechanics and engineering because it helps to reduce the number of free parameters, identify the relative size of effects of parameters, and gain a deeper insight of the essential nature of phenomena. The nondimensionalization of 2D theory has been completed by the author (Zhen et.al.,2020) and new dimensionless equations of motion were obtained. In this study, new dimensionless dynamic equations are extended by incorporating new parameters to cope with various environmental conditions. The new dimensionless analysis of dropped cylindrical objects is consisted of four parts.

Part 1, …

Sounds Of Silence: A Study Of Stability And Diversity Of Web Audio Fingerprints, Shekhar Chalise

University of New Orleans Theses and Dissertations

Browser fingerprinting presents a grave threat to privacy as it allows user tracking even in private browsing modes. Prior measurement studies on HTML5-based fingerprinting have been limited to Canvas and WebGL but not Web Audio APIs. We aim to fill this gap by conducting the first large-scale systematic study of web audio fingerprints and studying their stability as well as diversity properties. Using MTurk and social media platforms, we collected 8 different audio fingerprints from 694 users.

Firstly, we show that the audio fingerprints are unstable unlike other fingerprinting methods with some users having as many as 20 different fingerprints. …

Stock Markets Performance During A Pandemic: How Contagious Is Covid-19?, Yara Abushahba

Theses and Dissertations

Background and Motivation: The coronavirus (“COVID-19”) pandemic, the subsequent policies and lockdowns have unarguably led to an unprecedented fluid circumstance worldwide. The panic and fluctuations in the stock markets were unparalleled. It is inarguable that real-time availability of news and social media platforms like Twitter played a vital role in driving the investors’ sentiment during such global shock.

Purpose:The purpose of this thesis is to study how the investor sentiment in relation to COVID-19 pandemic influenced stock markets globally and how stock markets globally are integrated and contagious. We analyze COVID-19 sentiment through the Twitter posts and investigate its …

Assembly And Detection Of 3-D Qr Codes Through Additive Manufacturing And Terahertz Imaging, Patrick Dunn

Theses

Automatic identification and data capture, or AIDC, plays a substantial role in contemporary business, advertising, and military needs. The purpose of this study is to generate a potential alternative to current AIDC approaches by constructing three-dimensional plastic tags (or ‘3D QR codes’) using additive manufacturing techniques and interrogate them using Terahertz radiation. 3D Quick Response (QR) codes are designed in 3D computer-aided design software. The QR codes are 3D structures embedded in the printed plastic in which an air gap in the plastic (or an air gap filled in with another type of plastic) indicates a bit of information. Information …

Brown Treesnake Mortality After Aerial Application Of Toxic Baits, Scott M. Goetz, Eric T. Hileman, Melia G. Nafus, Amy A. Yackel Adams, Amanda R. Bryant, Robert N. Reed, Shane R. Siers

United States Department of Agriculture Wildlife Services: Staff Publications

Quantitative evaluation of control tools for managing invasive species is necessary to assess overall effectiveness and individual variation in treatment susceptibility. Invasive brown treesnakes (Boiga irregularis) on Guam have caused severe ecological and economic effects, pose a risk of accidental introduction to other islands, and are the greatest impediment to the reestablishment of extirpated native fauna. An aerial delivery system for rodent‐based toxic baits can reduce brown treesnake abundance and heterogeneity among individuals may influence bait attraction or toxicant susceptibility. Previous baiting trials have either been simulated aerial treatments or relied on slightly different bait capsule compositions and the results …

Investigating Which Elements Of Ecs Teaching Motivate Subsequent Computer Science Course Taking, Steven Mcgee, Randi Mcgee-Tekula, Lucia Dettori, Ronald I. Greenberg, John Wachen, Mark Johnson

Computer Science: Faculty Publications and Other Works

A key strategy for broadening computer science participation in a large urban school district has been the enactment of a high school computer science graduation requirement. The Exploring Computer Science (ECS) curriculum and professional development program serves as a core foundation for supporting the enactment of this policy. ECS seeks to foster broadening participation in computer science through activities designed to engage students in computer science inquiry connected to meaningful problems. Prior research has shown that student motivation is an important mediating factor for the impact of ECS on broadening participation in future CS coursework. The current study was undertaken …

Rm-Net: Rasterizing Markov Signals To Images For Deep Learning, Kajal Gupta

Theses

Statistical machine learning approaches are quite famous for processing Markov signal data. They can model unobserved states and learn certain characteristics particular to a signal with good accuracy. However, with the advent of Deep learning the novice ways of solving a problem has shifted towards this more sophisticated algorithm, which is much better, powerful and more accurate. Specifically, Convolutional Neural Nets (CNN) have shown many promising results on images and videos. Here we illustrate how CNN can be applied to a 1D numeric signal using signal rasterization technique. We start by rasterizing a 1D numeric Markov signal into an image …

Finite Element Modeling Of Underwater Acoustic Environments And Domain Decomposition Methods, General Ozochiawaeze

Theses

Underwater acoustic scattering problems have several important applications ranging from sonar imaging in target detection to providing information for sediment classification and geoacoustic inversion. This work presents numerical methods for time-harmonic acoustic scattering problems, specifically, finite element methods for the Helmholtz equation. Furthermore, an iterative domain decomposition formulation is introduced for acoustic scattering problems where the physical domain consists of multiple layers of different materials.

Short Term Temperature Forecasting Using Lstms, And Cnn, Darshan Shah

Theses

Weather forecasting is a vital application in present times. We can use the predictions to minimize the weather related loss. Use of machine learning and deep learning algorithms for forecasting, can eliminate or reduce the necessity of big data and high computation dependent process of parameterization. Long Short-Term Memory (LSTM) is a widely used deep learning architecture for time series forecasting. In this paper, we aim to predict one day ahead average temperature using a 2-layer neural network consisting of one layer of LSTM and one layer of 1D convolution. The input is pre-processed using a smoothing technique and output …

Attitudes Concerning Sexual Behavior Towards Risky Sexual Behavior Of Sexual Transmitted Infections Among Male Adolescents In Indonesia, Helda Helda, Nurul Muchlisa

Kesmas

There has been an increase of sexually transmitted infections (STIs) such as HIV/AIDS worldwide, especially in Indonesia. Several studies on adolescent behavior, especially the male as the main predictor, reported increased in STIs’ cases due to risky sexual behavior. This study aimed to show the relationship between attitudes, sexual behavior, and the risks of STIs among male adolescents in Indonesia based on the Indonesia Demographic and Health Survey (IDHS) data in 2017. This cross-sectional study involved 10,547 male adolescents using the total sampling method according to the inclusion and exclusion criteria. Data were analyzed using a complex sample logistic regression …

Empowering Health Cadres To Support Drug-Resistant Tuberculosis (Dr-Tb) Patient To Enroll In Treatment, Esty Febriani, Adik Wibowo, Neeraj Kak, Hala Jassim Al Mossawi

Kesmas

Tuberculosis (TB) remains a big challenge globally, while the involvement of health cadres’ constitutes one of the key strategies for the TB program in Indonesia. These roles were further expanded to providing support to DR-TB patients. This study was a qualitative study, conducted in 2015 to explore the various factors which influence the performance of health cadres’ in supporting DR-TB patients to enroll in treatment. A total of 39 informants consisting of 24 health cadres, three nurses, four DR-TB patients, and three family members, two peer support, a head of primary health care, and two TB staffs from the District …

National Health Insurance Scheme: Internal And External Barriers In The Use Of Reproductive Health Services Among Women, Evi Martha, Herna Lestari, Resvi Siti Zulfa, Yoslien Sopamena

Kesmas

Lack of familiarity among the community, medical workers, and administrative staff regarding reproductive health services covered by Badan Penyelenggara Jaminan Sosial (BPJS) or the National Health Insurance (NHI) in Indonesia remained a problem. Therefore, this resulted in sub-optimal use of the medical services, as shown by surveys from the Women's Health Foundation for three consecutive years (2015-2017). This qualitative study was conducted with a Rapid Assessment Procedure design in three cities within Indonesia: Padang Pariaman, Manado, and Kupang. Data were collected through IDIs (n = 47informants) and 6 FGDs (7 persons/group). Participants also consisted of NHI RHS users (mothers and …

Isolation And Determination Of The Composition And Structural Components That Comprise Dissolved Organic Matter Using Normal Phase Liquid Chromatography, Jonathan A. Long Jr

University of New Orleans Theses and Dissertations

A comprehensive understanding of the reactivity associated with organic carbon is critical for recognizing the behavior of newly formed compounds in aquatic environments. In an effort to study the reactivity of complex mixtures, understanding the different processes affiliated with them are key. Understanding the reactivity associated with organic carbon can help to improve chromatographic separation. Using a combination of light and heavy crude oil, a separation procedure was developed to obtain a complete representation of the aromatic subfraction of the crude oil sample. The crude oils were separated into four distinct fractions based on the number of condensed aromatic rings …

Convolutional Neural Networks For Deflate Data Encoding Classification Of High Entropy File Fragments, Nehal Ameen

University of New Orleans Theses and Dissertations

Data reconstruction is significantly improved in terms of speed and accuracy by reliable data encoding fragment classification. To date, work on this problem has been successful with file structures of low entropy that contain sparse data, such as large tables or logs. Classifying compressed, encrypted, and random data that exhibit high entropy is an inherently difficult problem that requires more advanced classification approaches. We explore the ability of convolutional neural networks and word embeddings to classify deflate data encoding of high entropy file fragments after establishing ground truth using controlled datasets. Our model is designed to either successfully classify file …

The Kati Module System: Modular Design For Delivering Character Focused Dialogue In Games, Stephen J. Marcel

University of New Orleans Theses and Dissertations

The Kati Module System is an interconnected set of programming modules intended to facilitate dynamic text authoring for interactive experiences (for example, games). It is a long-standing goal for interactive experiences to dynamically adapt their textual output based on the user or player's choices and predilections, but to account for this vast possibility space requires an amount of authoring that is frequently untenable, especially for small studios. Advances in machine learning have produced incredible progress in the field of Natural Language Generation (NLG). Though this produces impressive surface level text, it does so without an internal representation that can be …

Machine Learning Based Restaurant Sales Forecasting, Austin B. Schmidt

University of New Orleans Theses and Dissertations

To encourage proper employee scheduling for managing crew load, restaurants have a need for accurate sales forecasting. We predict partitions of sales days, so each day is broken up into three sales periods: 10:00 AM-1:59 PM, 2:00 PM-5:59 PM, and 6:00 PM-10:00 PM. This study focuses on the middle timeslot, where sales forecasts should extend for one week. We gather three years of sales between 2016-2019 from a local restaurant, to generate a new dataset for researching sales forecasting methods.

Outlined are methodologies used when going from raw data to a workable dataset. We test many machine learning models on …

Machine Learning For Terminal Procedure Chart Change Detection, Anthony M. Marchiafava

University of New Orleans Theses and Dissertations

Terminal Procedure Charts are a constantly updated and necessary tool for aircraft personnel to approach and take off from airport runways safely. Detecting changes within these charts is a time-consuming and laborious process. Here machine learning techniques were used to predict regions of change in charts based on detecting the charts image regions and comparing features extracted from those regions. Outlined are methodologies to detect differences between two separate charts to produce images with changed regions clearly indicated. Both more conventional computer vision and machine learning techniques were applied. For images with minor shifts, the proposed model is able to …

The Essence Of Telemedicine For Bridging The Gap In Health Services, Budi Wiweko, Sarah Chairani Zakirah, Atha Luthfi

Kesmas

This study aimed to review the essence of telemedicine in this modern era of technology and innovation, especially in developing countries. It also investigated the regulation aspect as the main component for healthcare services. There were five main categories of telemedicine: revenue stream and technology literacy, health facilities, human resources, data authorization and security, and health protocol. Furthermore, when combined with wearable devices, it enhanced healthcare delivery opportunities. There were two major components of global electronic health, namely telehealth and health informatics, based one-commerce and e-learning systems. The World Health Organization (WHO) has been able to describe the roles of …

The Effect Of Smoking On Carbon Monoxide Respiration Among Active Smokers In Palembang City, Indonesia, Rico Januar Sitorus, Imelda Gernauli Purba, Merry Natalia, Kraichat Tantrakarnapa

Kesmas

Smoking leads to disease and disability as well as harm nearly every organ of the body. Furthermore, smoking of tobacco is known to cause pulmonary dysfunction and lead to complications, pain, or even death. This study aimed to measure the risk factors for the respiration of carbon monoxide among smokers. A cross-sectional design was implemented by involving 156 smokers in Karyajaya Subdistrict, Palembang City. The dependent variable was carbon monoxide levels (ppm), while the independent variables were smoking frequency, duration, and the last period of smoking. The carbon monoxide levels (ppm) measured with a PiCO + Smokerlyzer® device from Bedfont …

Stationary Probability Distributions Of Stochastic Gradient Descent And The Success And Failure Of The Diffusion Approximation, William Joseph Mccann

Theses

In this thesis, Stochastic Gradient Descent (SGD), an optimization method originally popular due to its computational efficiency, is analyzed using Markov chain methods. We compute both numerically, and in some cases analytically, the stationary probability distributions (invariant measures) for the SGD Markov operator over all step sizes or learning rates. The stationary probability distributions provide insight into how the long-time behavior of SGD samples the objective function minimum.

A key focus of this thesis is to provide a systematic study in one dimension comparing the exact SGD stationary distributions to the Fokker-Planck diffusion approximation equations —which are commonly used in …

Time Series Forecasting With Applications To Finance, Viswapriya Misra

Theses

In finance, many phenomena are modeled as time series. This thesis investigates time series forecasting problems in finance, precisely the stock price prediction problem. We employ and compare traditional statistical algorithms like MA, ARIMA, and ARMA-GARCH with newly developed deep learning-based algorithms such RNNs, LSTMs, GRUs, TCNs, and bidirectional LSTMs and GRUs for predicting stock prices. We perform a comprehensive study and present all the experimental results on different datasets. We find that ARIMA and GRU perform better for single-step stock price prediction than other deep learning architectures. Adding market and economic indicators do not improve the performance of the …

The Effect Of Additives And Mixed Treatment On Red Clover Silage Quality, Lian Tao, Zhu Yu, Liying Han

IGC Proceedings (1993-2023)

No abstract provided.

Distribution Of Crude Fat For A Halophyte (Suaeda Glauca) Growing In The Songnen Grassland, H. X. Sun, Ch. L. Liu, Ch. Sh. L.

IGC Proceedings (1993-2023)

No abstract provided.