Data Science Commons^™

Neural Network Classification Of Brainwave Alpha Signalsin Cognitive Activities, Ahmad Azhari, Adhi Susanto, Andri Pranolo, Yingchi Mao

Knowledge Engineering and Data Science

The signal produced by human brain waves is one unique feature. Signals carry information and are represented in electrical signals generated from the brain in a typical waveform. Human brain wave activity will always be active even when sleeping. Brain waves will produce different characteristics in different individuals. Physical and behavioral characteristics can be identified from patterns of brain wave activity. This study aims to distinguish signals from each individual based on the characteristics of alpha signals from brain waves produced. Brain wave signals are generated by giving several mental perception tasks measured using an Electroencephalogram (EEG). To get different …

Optimisation Of Rice Fertiliser Composition Using Genetic Algorithms, Retno Dewi Anissa, Wayan Firdaus Mahmudy, Agus Wahyu Widodo

Knowledge Engineering and Data Science

There are so many problems with food scarcity. One of them is not too good rice quality. So, an enhancement in rice production through an optimal fertiliser composition. Genetic algorithm is used to optimise the composition for a more affordable price. The process of genetic algorithm is done by using a representation of a real code chromosome. The reproduction process using a one-cut point crossover and random mutation, while for the selection using binary tournament selection process for each chromosome. The test results showed the optimum results are obtained on the size of the population of 10, the crossover rate …

Comparison Of Indonesian Imports Forecastingby Limited Period Using Sarima Method, Harits Ar Rosyid, Mutyara Whening Aniendya, Heru Wahyu Herwanto

Knowledge Engineering and Data Science

The development of Indonesia's imports fluctuate over years. Inability to anticipate such rapid changes can cause economic slump due to inappropriate policy. For instance, recent years imports in rice led to the extermination of rice reserves. The reason is to maintain the market price of rice in Indonesia. To overcome these changes, forecasting the amount of imports should assist the Government in determining the optimum policy. This can be done by utilizing an algorithm to forecast time series data, in this case the amount of imports in the next few months with a high degree of accuracy. This study uses …

Comparison Of Naïve Bayes Algorithm And Decision Tree C4.5for Hospital Readmission Diabetes Patientsusing Hba1c Measurement, Utomo Pujianto, Asa Luki Setiawan, Harits Ar Rosyid, Ali M. Mohammad Salah

Knowledge Engineering and Data Science

Diabetes is a metabolic disorder disease in which the pancreas does not produce enough insulin or the body cannot use insulin produced effectively. The HbA1c examination, which measures the average glucose level of patients during the last 2-3 months, has become an important step to determine the condition of diabetic patients. Knowledge of the patient's condition can help medical staff to predict the possibility of patient readmissions, namely the occurrence of a patient requiring hospitalization services back at the hospital. The ability to predict patient readmissions will ultimately help the hospital to calculate and manage the quality of patient care. …

Handwriting Character Recognition Usingvector Quantization Technique, Haviluddin Haviluddin, Rayner Alfred, Ni’Mah Moham, Herman Santoso Pakpahan, Islamiyah Islamiyah, Hario Jati Setyadi

Knowledge Engineering and Data Science

This paper seeks to explore Learning Vector Quantization (LVQ) processing stage to recognize The Buginese Lontara script from Makassar as well as explaining its accuracy. The testing results of LVQ obtained an accuracy degree of 66.66 %. The most optimal variant of network architecture in the recognition process is a variation of learning rate of 0.02, a maximum epoch of 5000 and a hidden layer of 90 neurons which was the result of recognition based on feature 8. Based on these variations, the obtained performance with a mean square error (MSE) of 0.0306 and the time required during the learning …

The Application Of Gray-Scale Level-Set Method In Segmentation Of Concrete Deck Delamination Using Infrared Images, Chongsheng Cheng, Zhigang Shen

Department of Construction Engineering and Management: Faculty Publications

Conventional nondestructive delamination detection of concrete pavements through thermography is often based on temperature contrasts between delaminated and sound areas. Non-uniform backgrounds caused by the environmental conditions are often challenging for contrast-based methods to robustly differentiate the delaminated areas from the sound areas. Instead of focusing on the temperature contrast, this study proposes a temperature gradient-based level set method (LSM) to detect boundaries for delamination segmentations. A modified edge indicator function is developed to represent the normalized temperature gradient of a thermal image. The experimental study was conducted to evaluate its applicability and stability for boundary detection in terms of …

Information Extraction From Primary Care Visits To Support Patient-Provider Interactions, Daniel Baruch Gutstein

College of Computing and Digital Media Dissertations

The extent of electronic health record systems usage in clinical settings has affected the dynamic between clinicians and patients and has thus been connected to physician morale and the quality of care patients receive. Recent research has also uncovered a correlation between physician burnout and negative physician attitudes electronic health record systems. In order to begin exploring the nature of the relationship between electronic health record usage, physician burnout, and patient care, it is necessary to first analyze patient-provider interactions within the context of verbal features such as turn-taking and non-verbal features such as eye-contact. While previous works have sought …

Numerical, Secondary Big Data Quality Issues, Quality Threshold Establishment, & Guidelines For Journal Policy Development, Anita Lee-Post, Ram Pakath

Marketing & Supply Chain Faculty Publications

An IS researcher may obtain Big Data from primary or secondary data sources. Sometimes, acquiring primary Big Data is infeasible due to availability, accessibility, cost, time, and/or complexity considerations. In this paper, we focus on Big Data-based IS research and discuss ways in which one may, post hoc, establish quality thresholds for numerical Big Data obtained from secondary sources. We also present guidelines for developing journal policies aimed at ensuring the veracity and verifiability of such data when used for research purposes.

Enhancing Clinical Concept Extraction With Contextual Embeddings, Yuqi Si, Jingqi Wang, Hua Xu, Kirk Roberts

Faculty, Staff and Student Publications

OBJECTIVE: Neural network-based representations ("embeddings") have dramatically advanced natural language processing (NLP) tasks, including clinical NLP tasks such as concept extraction. Recently, however, more advanced embedding methods and representations (eg, ELMo, BERT) have further pushed the state of the art in NLP, yet there are no common best practices for how to integrate these representations into clinical tasks. The purpose of this study, then, is to explore the space of possible options in utilizing these new models for clinical concept extraction, including comparing these to traditional word embedding methods (word2vec, GloVe, fastText).

MATERIALS AND METHODS: Both off-the-shelf, open-domain embeddings and …

Automated Morgan Keenan Classification Of Observed Stellar Spectra Collected By The Sloan Digital Sky Survey Using A Single Classifier, Michael J. Brice, Răzvan Andonie

All Faculty Scholarship for the College of the Sciences

The classification of stellar spectra is a fundamental task in stellar astrophysics. Stellar spectra from the Sloan Digital Sky Survey are applied to standard classification methods, k-nearest neighbors and random forest, to automatically classify the spectra. Stellar spectra are high dimensional data and the dimensionality is reduced using astronomical knowledge because classifiers work in low dimensional space. These methods are utilized to classify the stellar spectra into a complete Morgan Keenan classification (spectral and luminosity) using a single classifier. The motion of stars (radial velocity) causes machine-learning complications through the feature matrix when classifying stellar spectra. Due to the nature …

What About The Environment?: Exploring The Neglected Third Dimension Of Antimicrobial Resistance, Paige E. Montfort

Independent Study Project (ISP) Collection

Antimicrobial resistance (AMR) is one of the most urgent and complex health risks of our time, with links to human health, animal health, and the environment. The majority of research and policy related to AMR, however, has been dedicated to human and animal health. The third dimension — the environment — has been relatively neglected. Conversations about this problem have begun, but gaps in understanding remain. This study explores the key barriers that have hindered developments related to the environmental aspect of AMR and some of the solutions that have begun to or could be utilized to overcome these barriers. …

Eavesdropping Hackers: Detecting Software Vulnerability Communication On Social Media Using Text Mining, Susan Mckeever, Brian Keegan, Andrei Quieroz

Conference papers

Abstract—Cyber security is striving to find new forms of protection against hacker attacks. An emerging approach nowadays is the investigation of security-related messages exchanged on Deep/Dark Web and even Surface Web channels. This approach can be supported by the use of supervised machine learning models and text mining techniques. In our work, we compare a variety of machine learning algorithms, text representations and dimension reduction approaches for the detection accuracies of software-vulnerability-related communications. Given the imbalanced nature of the three public datasets used, we investigate appropriate sampling approaches to boost detection accuracies of our models. In addition, we examine how …

Integrating Intelligent Decision Support Services Into Analytical Management Systems, Mastura Zaynutdinova, Odilbek Asqaraliyev

Bulletin of TUIT: Management and Communication Technologies

The article discusses the approach to creating projects of organizational management systems that allow to use the theoretical and practical results of research in the field of artificial intelligence in their design. The importance of using the experience gained to support decision-making in the organizational management system was emphasized. In addition, appropriate recommendations will be developed for the intellectual support of decision-making in integrated management systems, as well as the introduction of service technologies. In the example of supporting management decisions, optimal solutions are put forward for the intellectual processing of information, the creation of services appropriate to expert systems. …

Precision Agriculture Gis Technologies For Mississippi, 1st. Edition, Amelia A.A. Fox

CALS Publications

Precision agriculture is meant to improve on-farm efficiency in hopes of ultimately increasing profitability while also protecting the environment. However, this difficult process almost always includes the proper management and interpretation of data. Therefore, it is imperative that those individuals involved in making such decisions are educated on these processes. In a data-driven world, this textbook is a great resource for those wanting to learn how to utilize their data in hopes of making better informed on-farm decisions.

Development Of An Algorithm For The Intelligent Decision Support Systems In The Field Of Tax Authorities, Odilbek Аskaraliev

Bulletin of TUIT: Management and Communication Technologies

An algorithm for the intellectual support of decisions in integrated management systems has been developed, its main components have been described, its structure has been formed, and algorithms have been developed to work in several modes that increase management efficiency on the example of tax authorities. An alternative solution structure has been designed and developed for management decision making. An integrated functional structure has been developed for the overall decision-making system. The process of operation of the proposed intelligent decision-making system for an integrated management system is shown. Issues of improving management efficiency by supporting intelligent decision-making are analyzed. An …

Model Of The State Of Threats To The Access Control System, ‪Durdona Irgasheva

Bulletin of TUIT: Management and Communication Technologies

This article is devoted to the presentation of the threat state model of access control, which allows calculating the probabilities of the impact of threats on the access control system and the probability of opening this system based on taking into account the generalized algorithm for the implementation of external threats, and determines the need to develop additional components of the access control system designed to identify and classify attacks.

Methodology Of Management Monitoring For Flow Rivers Issue Issue, Toshtemir Khojakulov

Bulletin of TUIT: Management and Communication Technologies

The article reviewed the development of the all the goals of the UzB are “... shaped in the form of global aspirations, and each government sets its own national goals, in cases where several states are monitoring a single trans boundary watershed, efforts should be made to agree on targets for all countries. Water quality comparison.

Innovative Solutions For State Medicaid Programs To Leverage Their Data, Build Their Analytic Capacity, And Create Evidence-Based Policy, Lauren Adams, Susan Kennedy, Lindsay Allen, Andrew Barnes, Tom Bias, Dushka Crane, Paul Lanier, Rachel Mauk, Shamis Mohamoud, Nathan Pauly, Jeffery C. Talbert, Cynthia Woodcock, Kara Zivin, Julie Donohue

Pharmacy Practice and Science Faculty Publications

As states have embraced additional flexibility to change coverage of and payment for Medicaid services, they have also faced heightened expectations for delivering high-value care. Efforts to meet these new expectations have increased the need for rigorous, evidence-based policy, but states may face challenges finding the resources, capacity, and expertise to meet this need. By describing state-university partnerships in more than 20 states, this commentary describes innovative solutions for states that want to leverage their own data, build their analytic capacity, and create evidence-based policy. From an integrated web-based system to improve long-term care to evaluating the impact of permanent …

Data-Driven Decision-Support For Process Improvement Through Predictions Of Bed Occupancy Rates, Kar Way Tan, Qi You Ng, Francis Ngoc Hoang Long Nguyen, Sean Shao Wei Lam

Research Collection School Of Computing and Information Systems

Managing bed utilization and ensuring the supply keeps up with the demand is not an easy task in a large public hospital with many medical disciplines. The bed managers who makes decisions on reserving and allocating beds centrally require high-dimensional data from several hospital information systems supporting emergency room, specialized clinics and bed management processes. In this work, we put together an automated process for cleaning, consolidating and integrating data from several hospital information systems to several reports required by the bed managers to analyse the bed occupancy situations across more than thirty medical disciplines. To prevent bed crunch situations …

Mathematical And Computer Simulation Of The Processes Of Two-Phase Joint Gas Filtration And Water In A Porous Environment, Elmira Nazirova

Bulletin of TUIT: Management and Communication Technologies

A mathematical model, methods and algorithms for the numerical solution of problems of joint gas-water filtration in porous media are considered. The mathematical model of the process of non-stationary joint gas-water filtration in a porous medium is described by a system of nonlinear differential equations of parabolic type. In the numerical solution of the boundary value problem of gas displacement by water in a porous medium, the differential sweeping method is used for systems of differential-difference equations. The system of differential-difference equations with respect to the gas pressure function is nonlinear, therefore, an iterative method is used for it, based …