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Articles 1 - 30 of 62
Full-Text Articles in Data Storage Systems
Interpretable Deep Neural Network For Cancer Survival Analysis By Integrating Genomic And Clinical Data, Jie Hao, Youngsoon Kim, Tejaswini Mallavarapu, Jung Hun Oh, Mingon Kang
Interpretable Deep Neural Network For Cancer Survival Analysis By Integrating Genomic And Clinical Data, Jie Hao, Youngsoon Kim, Tejaswini Mallavarapu, Jung Hun Oh, Mingon Kang
Computer Science Faculty Research
Background: Understanding the complex biological mechanisms of cancer patient survival using genomic and clinical data is vital, not only to develop new treatments for patients, but also to improve survival prediction. However, highly nonlinear and high-dimension, low-sample size (HDLSS) data cause computational challenges to applying conventional survival analysis. Results: We propose a novel biologically interpretable pathway-based sparse deep neural network, named Cox-PASNet, which integrates high-dimensional gene expression data and clinical data on a simple neural network architecture for survival analysis. Cox-PASNet is biologically interpretable where nodes in the neural network correspond to biological genes and pathways, while capturing the nonlinear …
Neural Network Classification Of Brainwave Alpha Signalsin Cognitive Activities, Ahmad Azhari, Adhi Susanto, Andri Pranolo, Yingchi Mao
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
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 …
Handwriting Character Recognition Usingvector Quantization Technique, Haviluddin Haviluddin, Rayner Alfred, Ni’Mah Moham, Herman Santoso Pakpahan, Islamiyah Islamiyah, Hario Jati Setyadi
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 …
Comparison Of Indonesian Imports Forecastingby Limited Period Using Sarima Method, Harits Ar Rosyid, Mutyara Whening Aniendya, Heru Wahyu Herwanto
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
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. …
Effective Fuzzing Framework For The Sleuthkit Tools, Shravya Paruchuri
Effective Fuzzing Framework For The Sleuthkit Tools, Shravya Paruchuri
LSU Master's Theses
The fields of digital forensics and incident response have seen significant growth over the last decade due to the increasing threats faced by organizations and the continued reliance on digital platforms and devices by criminals. In the past, digital investigations were performed manually by expert investigators, but this approach has become no longer viable given the amount of data that must be processed compared to the relatively small number of trained investigators. These resource constraints have led to the development and reliance on automated processing and analysis systems for digital evidence. In this paper, we present our effort to develop …
Algorithms For Designing Processes Of Electronic Interactive Services, Ozod Radjabov
Algorithms For Designing Processes Of Electronic Interactive Services, Ozod Radjabov
Bulletin of TUIT: Management and Communication Technologies
Today, the integration of electronic interactive services is based on the correct placement of algorithms to ensure solidarity in information systems, the design stages of information systems based on interactive services and the corresponding events, the implementation of functions in a strict sequence.
On I/O Performance And Cost Efficiency Of Cloud Storage: A Client's Perspective, Binbing Hou
On I/O Performance And Cost Efficiency Of Cloud Storage: A Client's Perspective, Binbing Hou
LSU Doctoral Dissertations
Cloud storage has gained increasing popularity in the past few years. In cloud storage, data are stored in the service provider’s data centers; users access data via the network and pay the fees based on the service usage. For such a new storage model, our prior wisdom and optimization schemes on conventional storage may not remain valid nor applicable to the emerging cloud storage.
In this dissertation, we focus on understanding and optimizing the I/O performance and cost efficiency of cloud storage from a client’s perspective. We first conduct a comprehensive study to gain insight into the I/O performance behaviors …
Electronic Data Capture And Study Management, William A. Mattingly
Electronic Data Capture And Study Management, William A. Mattingly
Division of Infectious Diseases
Electronic Data Capture (EDC) is the process of recording data from a primary data source into a computerized system for improved reliability, security, and convenience. Data stored in EDC systems are used for analysis and, in the case of clinical studies, are an important part of the development pipeline for new drugs and medical devices. This text provides an introduction to data capture and the management of a scientific study using the popular EDC solution REDCap.
Performance Of Lambda@Edge Vs. Lambda Environment, Sam Dotson, Wei Hao
Performance Of Lambda@Edge Vs. Lambda Environment, Sam Dotson, Wei Hao
Posters-at-the-Capitol
Abstract
The purpose of this research has been to observe how performance of the Lambda@EDGE environment compares to the base Lambda environment. This is in an effort to determine viability of the EDGE environment. 15 tests were conducted over a matter of days in each environment whereby the Fibonacci sequence was calculated to 20 terms. Performance metrics including RAM usage and response time were measured. Lambda@EDGE was determined to have not only a slightly higher average response time but also an average RAM usage of 1MB more in the aggregate tests.
Deep Hashing By Discriminating Hard Examples, Cheng Yan, Guansong Pang, Xiao Bai, Chunhua Shen, Jun Zhou, Edwin Hancock
Deep Hashing By Discriminating Hard Examples, Cheng Yan, Guansong Pang, Xiao Bai, Chunhua Shen, Jun Zhou, Edwin Hancock
Research Collection School Of Computing and Information Systems
This paper tackles a rarely explored but critical problem within learning to hash, i.e., to learn hash codes that effectively discriminate hard similar and dissimilar examples, to empower large-scale image retrieval. Hard similar examples refer to image pairs from the same semantic class that demonstrate some shared appearance but have different fine-grained appearance. Hard dissimilar examples are image pairs that come from different semantic classes but exhibit similar appearance. These hard examples generally have a small distance due to the shared appearance. Therefore, effective encoding of the hard examples can well discriminate the relevant images within a small Hamming distance, …
Predicting The Hardness Of Turf Surfaces From A Soil Moisture Sensor Using Iot Technologies, Ann Marie Mckeon
Predicting The Hardness Of Turf Surfaces From A Soil Moisture Sensor Using Iot Technologies, Ann Marie Mckeon
Other
In horseracing, “the going” is a term to describe the racetrack ground conditions. In Ireland presently, a groundskeeper or course clerk walks the racecourse poking it with a blackthorn stick, assesses conditions, and declares the going – it is a subjective measurement.
This thesis will propose using remote low-cost soil moisture sensors to gather high frequency data about the soil water content in the ground and to enable informed decisions to be made. This will remove the subjective element from the ground hardness, and look at the data in an objective way.
The soil moisture sensor will systematically collect high …
Confusion And Information Triggered By Photos In Persona Profiles, Joni Salminen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Lene Nielsen, Bernard J. Jansen
Confusion And Information Triggered By Photos In Persona Profiles, Joni Salminen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Lene Nielsen, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
We investigate whether additional photos beyond a single headshot makes a persona profile more informative without confusing the end user. We conduct an eye-tracking experiment and qualitative interviews with digital content creators after varying the persona in photos via a single headshot, a headshot and photo of the persona in different contexts, and a headshot with photos of different people with key persona attributes the gender and age. Findings show that contextual photos provide significantly more persona information to end users; however, showing photos of multiple people engenders confusion and lowers informativeness. Also, as anticipated, viewing additional photos requires more …
Centralizing Energy Consumption Data In State Energy Data Centers, Zach Sibley
Centralizing Energy Consumption Data In State Energy Data Centers, Zach Sibley
Minnesota Journal of Law, Science & Technology
No abstract provided.
Model-Driven Engineering For Big Data, Belachew Regane
Model-Driven Engineering For Big Data, Belachew Regane
African Conference on Information Systems and Technology
Accessing heterogeneous and huge amount of data through different sources heavily impacts users of data nowadays worldwide. Thus, Big Data has now become a hot emerging paradigm in computing environments. Issues in scalability, interoperability, platform independency, adaptability and reusability in big data systems are considered the main current challenges. This raises the need for appropriate software engineering approaches to develop effective and efficient Big Data system models, i.e. an approach which reduce investment cost and development time. Today, software engineering has emerged advanced methodologies to solve problems from different perspectives, while still further research is needed to overcome new challenges …
Design Of Personnel Big Data Management System Based On Blockchain, Houbing Song, Jian Chen, Zhihan Lv
Design Of Personnel Big Data Management System Based On Blockchain, Houbing Song, Jian Chen, Zhihan Lv
Publications
With the continuous development of information technology, enterprises, universities and governments are constantly stepping up the construction of electronic personnel information management system. The information of hundreds of thousands or even millions of people’s information are collected and stored into the system. So much information provides the cornerstone for the development of big data, if such data is tampered with or leaked, it will cause irreparable serious damage. However, in recent years, electronic archives have exposed a series of problems such as information leakage, information tampering, and information loss, which has made the reform of personnel information management more and …
Do Grant Funding And Pro-Environmental Spillovers Influence Household Hazardous Waste Collection?, Kustini Lim-Wavde, Robert J Kauffman, Tin Seong Kam, Gregory S. Dawsond
Do Grant Funding And Pro-Environmental Spillovers Influence Household Hazardous Waste Collection?, Kustini Lim-Wavde, Robert J Kauffman, Tin Seong Kam, Gregory S. Dawsond
Research Collection School Of Computing and Information Systems
Agency and state grant funding should be disseminated in ways so it will result in better management of household hazardous waste (HHW) and environmental sustainability. Since location seems to matter in HHW collection activities, it is important to consider pro-environmental spatial spillovers that occur, based on agency actions and waste collection behavior taking place in other locations. These may influence HHW-related practices in close-by regions. Using a county-level spatio-temporal dataset that consists of economic, demographic, and HHW data in California from 2004 to 2015, we evaluate the impact of HHW grants on HHW collection activities while considering pro-environmental spillovers. We …
Crude Palm Oil Prediction Based On Back Propagation Neutral Network Approach, Hijratul Aini, Haviluddin Haviluddin
Crude Palm Oil Prediction Based On Back Propagation Neutral Network Approach, Hijratul Aini, Haviluddin Haviluddin
Knowledge Engineering and Data Science
Crude palm oil (CPO) production at PT. Perkebunan Nusantara (PTPN) XIII from January 2015 to January 2018 have been treated. This paper aims to predict CPO production using intelligent algorithms called Backpropagation Neural Network (BPNN). The accuracy of prediction algorithms have been measured by mean square error (MSE). The experiment showed that the best hidden layer architecture (HLA) is 5-10-11-12-13-1 with learning function (LF) of trainlm, activation function (AF) of logsig and purelin, and learning rate (LR) of 0.5. This architecture has a good accuracy with MSE of 0.0643. The results showed that this model can predict CPO production in …
The Diffusion Of Ict For Corruption Detectionin Open Government Data, Darusalam Darusalam, Jamaliah Said, Normah Omar, Marijn Janssen, Kazi Sohag
The Diffusion Of Ict For Corruption Detectionin Open Government Data, Darusalam Darusalam, Jamaliah Said, Normah Omar, Marijn Janssen, Kazi Sohag
Knowledge Engineering and Data Science
Corruption occurs in many places within the government. To tackle the issue, open data can be used as one of the tools in creating more insight into the government. The premise of this paper is to support the notion that data opening can bring up new ways of fighting corruption. The current paper aimed at investigating how open data can be employed to detect corruption. This open data is trivial due to challenges like information asymmetry among stakeholders, data might only be opened partly, different sources of data need to be combined, and data might not be easy to use, …
Adam Optimization Algorithmfor Wide And Deep Neural Network, Imran Khan Mohd Jais, Amelia Ritahani Ismail
Adam Optimization Algorithmfor Wide And Deep Neural Network, Imran Khan Mohd Jais, Amelia Ritahani Ismail
Knowledge Engineering and Data Science
The objective of this research is to evaluate the effects of Adam when used together with a wide and deep neural network. The dataset used was a diagnostic breast cancer dataset taken from UCI Machine Learning. Then, the dataset was fed into a conventional neural network for a benchmark test. Afterwards, the dataset was fed into the wide and deep neural network with and without Adam. It was found that there were improvements in the result of the wide and deep network with Adam. In conclusion, Adam is able to improve the performance of a wide and deep neural network.
Selection Of Marine Security Policyusing Fuzzy-Ahp Topsis Hybrid Approach, Hozairi Hozairi, Buhari Buhari, Heru Lumaksono, Marcus Tukan
Selection Of Marine Security Policyusing Fuzzy-Ahp Topsis Hybrid Approach, Hozairi Hozairi, Buhari Buhari, Heru Lumaksono, Marcus Tukan
Knowledge Engineering and Data Science
The research was focused on the integration of Fuzzy set theory with Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to choose the optimum maritime security policy to achieve Indonesia recognition as the world's maritime axis. The method used is AHP with fuzzy based enhancement. Here, the weight of each criterion is calculated to overcome the criticism of the scale of unbalanced rating, uncertainty, and inaccuracy in the pairwise of comparison process. The best recommendation for Indonesian maritime policies is multi task single agency which is greatly infuenced by several factors such as …
High Dimensional Data Clustering Using Self-Organized Map, Ruth Ema Febrita, Wayan Firdaus Mahmudy, Aji Prasetya Wibawa
High Dimensional Data Clustering Using Self-Organized Map, Ruth Ema Febrita, Wayan Firdaus Mahmudy, Aji Prasetya Wibawa
Knowledge Engineering and Data Science
As the population grows and e economic development, houses could be one of basic needs of every family. Therefore, housing investment has promising value in the future. This research implements the Self-Organized Map (SOM) algorithm to cluster house data for providing several house groups based on the various features. K-means is used as the baseline of the proposed approach. SOM has higher silhouette coefficient (0.4367) compared to its comparison (0.236). Thus, this method outperforms k-means in terms of visualizing high-dimensional data cluster. It is also better in the cluster formation and regulating the data distribution.
Table Of Contents Jitim Vol 28 Issue 2, 2019
Table Of Contents Jitim Vol 28 Issue 2, 2019
Journal of International Technology and Information Management
Table of Contents JITIM 2, 2019
A Longitudinal Analysis Of The Impact Of The Indicators In The Networked Readiness Index (Nri), Satya Pratipatti, Ahmed Gomaa
A Longitudinal Analysis Of The Impact Of The Indicators In The Networked Readiness Index (Nri), Satya Pratipatti, Ahmed Gomaa
Journal of International Technology and Information Management
World Economic Forum publishes the Networked Readiness Index (NRI) annually, to reflect the Information and Communication Technology (ICT) status of different countries. The NRI is developed by aggregating 53 indicators. The study identifies the most critical indicators to focus on, to improve the NRI status of countries at different stages of economic development. It uses data from 117 countries and analyzes the changes in the indicators along with their impacts between the years 2012 and 2016. The study explores the differences between countries by grouping them into four groups based on their NRI status. The analysis identifies six indicators with …
The Impact Of Changes Mislabeled By Szz On Just-In-Time Defect Prediction, Yuanrui Fan, Xin Xia, Daniel A. Costa, David Lo, Ahmed E. Hassan, Shanping Li
The Impact Of Changes Mislabeled By Szz On Just-In-Time Defect Prediction, Yuanrui Fan, Xin Xia, Daniel A. Costa, David Lo, Ahmed E. Hassan, Shanping Li
Research Collection School Of Computing and Information Systems
Just-in-Time (JIT) defect prediction—a technique which aims to predict bugs at change level—has been paid more attention. JIT defect prediction leverages the SZZ approach to identify bug-introducing changes. Recently, researchers found that the performance of SZZ (including its variants) is impacted by a large amount of noise. SZZ may considerably mislabel changes that are used to train a JIT defect prediction model, and thus impact the prediction accuracy. In this paper, we investigate the impact of the mislabeled changes by different SZZ variants on the performance and interpretation of JIT defect prediction models. We analyze four SZZ variants (i.e., B-SZZ, …
Secure And Efficient Bft Consensus For Blockchains, Mohammad Mussadiq Jalalzai
Secure And Efficient Bft Consensus For Blockchains, Mohammad Mussadiq Jalalzai
LSU Doctoral Dissertations
Blockchains are simple data structures, containing transactions organized into blocks, in which each block points to a previous block using its hash. Thus, by following the chain, we can follow the history of transactions. Blocks are added to the chain through a consensus mechanism. Byzantine Fault Tolerant (BFT) consensus protocols that were designed before blockchains were introduced are usually considered appropriate for use in small scale networks of size 10-20 replicas. Blockchains have changed this trend as the blockchain networks usually require a larger number of replicas and classic BFT protocols cannot provide acceptable performance in large networks. One of …
Are You Experienced? - Simple Timesheets For Experiential Learning Courses, Eleanor C. Lanier, Leslie Grove
Are You Experienced? - Simple Timesheets For Experiential Learning Courses, Eleanor C. Lanier, Leslie Grove
Presentations
ABA Standards require students to complete six credit hours of experiential learning. Hours must be tracked, and field placements in particular require students to keep logs of their activities to document compliance. Various web-based solutions are used, including “high-end suites like CORE ELMS, the Symplicity experiential learning module, and the basic and free Dropbox and Google Suite” as well as Canvas, and a time-tracking program called Tick. Here at the University of Georgia School of Law, we decided to add simple timesheet functionality to our Drupal-based student portal, allowing students to securely log their hours and activities, and faculty to …
A Database For Indexable Carbide Inserts, Andrew Yoder
A Database For Indexable Carbide Inserts, Andrew Yoder
Computer Engineering
The indexable inserts project is a collaborative effort to aggregate into a single database as many indexable carbide inserts from as many manufacturers as possible. Inserts are generally labeled with a part number following a specific standard determined by shapes and measurements, however specifications for certain aspects of carbide inserts—such as which materials they can cut—can vary by manufacturer. There currently is not a way to search a comprehensive database containing tools from multiple manufacturers for a handful of inserts that would satisfy some necessary parameters, making finding the correct tool in a shop a much more time-consuming process than …
Quorum Blockchain Stress Evaluation In Different Environments, Daniel P. Mera
Quorum Blockchain Stress Evaluation In Different Environments, Daniel P. Mera
Student Theses
In today’s world, the Blockchain technology is used for different purposes has brought an increment in the development of different Blockchain platforms, services, and utilities for storing data securely and efficiently. Quorum Blockchain, an Ethereum fork created by JPMorgan Chase, has placed itself in one of the widely used, efficient and trustful Blockchain platforms available today. Because of the importance which Quorum is contributing to the world, it is important to test and measure different aspects of the platform, not only to prove how efficient the software can be but as well as to have a clear view on what …