Computer Engineering Commons^™

Large Scale Electronic Health Record Data And Echocardiography Video Analysis For Mortality Risk Prediction, Alvaro Emilio Ulloa Cerna

Electrical and Computer Engineering ETDs

Electronic health records contain the clinical history of patients. The enormous potential for discovery in such a rich dataset is hampered by their complexity. We hypothesize that machine learning models trained on EHR data can predict future clinical events significantly better than current models. We analyze an EHR database of 594,862 Echocardiography studies from 272,280 unique patients with both unsupervised and supervised machine learning techniques.

In the unsupervised approach, we first develop a simulation framework to evaluate a family of different clustering pipelines. We apply the optimized approach to 41,645 patients with heart failure without providing any survival information to …

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 …

Features Of Designing The Architecture Of Intelligent Transport Systems, Jaffar Daeibal, Vyacheslav Lapshin, Dmitry Elkin, Sergey A. Kucherov

Karbala International Journal of Modern Science

In the global experience, intelligent transport systems (ITS) are recognized as a general transport ideology for integrating the achievements of telematics in all types of transport activities to solve economic and social problems: reducing accidents, improving the efficiency of public transport and cargo transportation, ensuring overall transport security, and improving environmental performance. Considering the design features of the intelligent transport system (ITS), there is a need to develop requirements for the functional and physical architecture as the main part of the ITS development. The creation of functional and physical architecture touches upon issues such as: the scheme of interaction between …

Gpu-Based Graph Traversal On Compressed Graphs, Mo Sha, Yuchen Li, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

Graph processing on GPUs received much attention in theindustry and the academia recently, as the hardware accelerator offers attractive potential for performance boost. However, the high-bandwidth device memory on GPUs has limited capacity that constrains the size of the graph to be loadedon chip. In this paper, we introduce GPU-based graph traversal on compressed graphs, so as to enable the processingof graphs having a larger size than the device memory. Designed towards GPU’s SIMT architecture, we propose twonovel parallel scheduling strategies Two-Phase Traversal andTask-Stealing to handle thread divergence and workload imbalance issues when decoding the compressed graph. Wefurther optimize our …

Evaluation Of Field Of View Width In Stereo-Vision-Based Visual Homing, Damian Lyons, Benjamin Barriage, Luca Del Signore

Faculty Publications

Visual homing is a local navigation technique used to direct a robot to a previously seen location by comparing the image of the original location with the current visual image. Prior work has shown that exploiting depth cues such as image scale or stereo-depth in homing leads to improved homing performance. While it is not unusual to use a panoramic field of view (FOV) camera in visual homing, it is unusual to have a panoramic FOV stereo-camera. So, while the availability of stereo-depth information may improve performance, the concomitant-restricted FOV may be a detriment to performance, unless specialized stereo hardware …

Personalized Product Evaluation Based On Gra-Topsis And Kansei Engineering, Huafeng Quan, Shaobo Li, Hongjing Wei, Jianjun Hu

Faculty Publications

With the improvement of human living standards, users’ requirements have changed from function to emotion. Helping users pick out the most suitable product based on their subjective requirements is of great importance for enterprises. This paper proposes a Kansei engineering-based grey relational analysis and techniques for order preference by similarity to ideal solution (KE-GAR-TOPSIS) method to make a subjective user personalized ranking of alternative products. The KE-GRA-TOPSIS method integrates five methods, including Kansei Engineering (KE), analytic hierarchy process (AHP), entropy, game theory, and grey relational analysis-TOPSIS (GRA-TOPSIS). First, an evaluation system is established by KE and AHP. Second, we define …

A Half- Yearly E-Newsletter Of The Department Of Computer Science And Engineering, Manipal Institute Of Technology - Jul 2019, Ashalatha Nayak

Faculty work

No abstract provided.

Towards Lakosian Multilingual Software Design Principles, Damian Lyons, Saba Zahra, Thomas Marshall

Faculty Publications

Large software systems often comprise programs written in different programming languages. In the case when cross-language interoperability is accomplished with a Foreign Function Interface (FFI), for example pybind11, Boost.Python, Emscripten, PyV8, or JNI, among many others, common software engineering tools, such as call-graph analysis, are obstructed by the opacity of the FFI. This complicates debugging and fosters potential inefficiency and security problems. One contributing issue is that there is little rigorous software design advice for multilingual software. In this paper, we present our progress towards a more rigorous design approach to multilingual software. The approach is based on the existing …

Chatbots: Conversation Killers Or Makers?, Jing Jiang

MITB Thought Leadership Series

Whether you’re aware of it or not, the chances are you’ve been chatting to robots of late. While these bots are faceless and unseen, don’t be fooled into thinking they aren’t there. In fact, chatbots, have been around since the 1960s at least, but with the progress in artificial intelligence, cloud computing and voice recognition, they’ve received both a functionality and a popularity boost. From the cosmetic to the life-changing, nowadays, chatbots can do anything from helping a person lose weight to assisting refugees applying for asylum.

Da-Drls: Drift Adaptive Deep Reinforcement Learning Based Scheduling For Iot Resource Management, Abishi Chowdhury, Shital A. Raut, Husnu S. Narman

Computer Sciences and Electrical Engineering Faculty Research

In order to fulfill the tremendous resource demand by diverse IoT applications, the large-scale resource-constrained IoT ecosystem requires a robust resource management technique. An optimum resource provisioning in IoT ecosystem deals with an efficient request-resource mapping which is difficult to achieve due to the heterogeneity and dynamicity of IoT resources and IoT requests. In this paper, we investigate the scheduling and resource allocation problem for dynamic user requests with varying resource requirements. Specifically, we formulate the complete problem as an optimization problem and try to generate an optimal policy with the objectives to minimize the overall energy consumption and to …

Improving 3d Printed Prosthetics With Sensors And Motors, Rachel Zarin

Honors Projects

A 3D printed hand and arm prosthetic was created from the idea of adding bionic elements while keeping the cost low. It was designed based on existing models, desired functions, and materials available. A tilt sensor keeps the hand level, two motors move the wrist in two different directions, a limit switch signals the fingers to open and close, and another motor helps open and close the fingers. All sensors and motors were built on a circuit board, programmed using an Arduino, and powered by a battery. Other supporting materials include metal brackets, screws, guitar strings, elastic bands, small clamps, …

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

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

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.

User Privacy Leakage In Location-Based Mobile Ad Services, Qicheng Lin

School of Computing: Dissertations, Theses, and Student Research

The online advertising ecosystem leverages its massive data collection capability to learn the properties of users for targeted ad deliveries. Many Android app developers include ad libraries in their apps as a way of monetization. These ad libraries contain advertisements from the sell-side platforms, which collect an extensive set of sensitive information to provide more relevant advertisements for their customers. Existing efforts have investigated the increasingly pervasive private data collection of mobile ad networks over time. However, there lacks a measurement study to evaluate the scale of privacy leakage of ad networks across different geographical areas. In this work, we …

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

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.

Intelligent Software Tools For Recruiting, Swatee B. Kulkarni, Xiangdong Che

Journal of International Technology and Information Management

In this paper, we outline how recruiting and talent acquisition gained importance within HRM field, then give a brief introduction to the newest tools used by the professionals for recruiting and lastly, describe the Artificial Intelligence-based tools that have started playing an increasingly important role. We also provide further research suggestions for using artificial intelligence-based tools to make recruiting more efficient and cost-effective.

Table Of Contents Jitim Vol 28 Issue 2, 2019

Journal of International Technology and Information Management

Table of Contents JITIM 2, 2019

Developing 5gl Concepts From User Interactions, David Stuckless Meyer

Masters Theses

In the fulfilling of the contracts generated in Test Driven Development, a developer could be said to act as a constraint solver, similar to those used by a 5th Generation Language(5GL). This thesis presents the hypothesis that 5GL linguistic mechanics, such as facts, rules and goals, will be emergent in the communications of developer pairs performing Test Driven Development, validating that 5GL syntax is congruent with the ways that practitioners communicate. Along the way, nomenclatures and linguistic patterns may be observed that could inform the design of future 5GL languages.

Survival Theory Modelling For Information Diffusion, Akshay Aravamudan

Theses and Dissertations

Information diffusion is the spread of information within a network. In this thesis, we model information diffusion as a survival process. We have adopted an existing algorithm called NetRate for modelling information diffusion. This model involves finding the distribution of trasmission time between two nodes in the network. We modify NetRate’s concave-down log-likelihood expression by adding partial parentage information and formulate an Expectation-Minimization (EM) algorithm to learn the parameters. We also describe a simulation scheme for NetRate inspired by point process simulation strategies. Using the assumptions of the NetRate model, we derive a a method to model popularity as a …

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

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, …

Exact Analytical Formula For The Excess Noise Factor For Mixed Carrier Injection Avalanche Photodiodes, Md. Mottaleb Hossain, John P.R. David, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

The well-known analytical formula for the excess noise factor associated with avalanche photodiodes (APDs), developed by R. J. McIntyre in 1966, assumes the injection of either an electron or a hole at the edge of the APD's avalanche region. This formula is based on the statistics of the probabilities of carriers gaining and losing energy subject to high electric fields. However, this analytical formula, is not applicable in cases when photons are absorbed inside the avalanche region (even though the physics of the high field transport remains the same), and its use may severely underestimate or overestimate the actual excess …

Nonlinear Observer For Visual-Inertial Navigation Using Intermittent Landmark Measurements, Miaomiao Wang

Western Research Forum

The development of reliable orientation, position and linear velocity estimation algorithms for the 3D visual-inertial navigation system (VINS) is instrumental in many applications, such as autonomous underwater vehicles (AUVs), and unmanned aerial vehicles (UAVs). It is extremely important when the global position system (GPS) is not available in GPS-denied environments. Recently, observers design for VINS using landmark position measurements from Kinect sensors or stereo cameras has been increasingly investigated in the literature.

The aim of this work is to design a nonlinear observer for VINS under the assumption that landmark position measurements are intermittent. In practice, the landmark measurements are …

A Resource Constrained Shortest Paths Approach To Reducing Personal Pollution Exposure, Elling Payne

REU Final Reports

As wildfires surge in frequency and impact in the Pacific Northwest, in tandem with increasingly traffic-choked roads, personal exposure to harmful airborne pollutants is a rising concern. Particularly at risk are school-age children, especially those living in disadvantaged communities near major motorways and industrial centers. Many of these children must walk to school, and the choice of route can effect exposure. Route-planning applications and frameworks utilizing computational shortest paths methods have been proposed which consider personal exposure with reasonable success, but few have focused on pollution exposure, and all have been limited in scalability or geographic scope. This paper addresses …

Large-Scale Data Analysis And Deep Learning Using Distributed Cyberinfrastructures And High Performance Computing, Richard Dodge Platania

LSU Doctoral Dissertations

Data in many research fields continues to grow in both size and complexity. For instance, recent technological advances have caused an increased throughput in data in various biological-related endeavors, such as DNA sequencing, molecular simulations, and medical imaging. In addition, the variance in the types of data (textual, signal, image, etc.) adds an additional complexity in analyzing the data. As such, there is a need for uniquely developed applications that cater towards the type of data. Several considerations must be made when attempting to create a tool for a particular dataset. First, we must consider the type of algorithm required …

Influence Spread In Two-Layer Interdependent Networks: Designed Single-Layer Or Random Two-Layer Initial Spreaders?, Hana Khamfroush, Nathaniel Hudson, Samuel Iloo, Mahshid R. Naeini

Computer Science Faculty Publications

Influence spread in multi-layer interdependent networks (M-IDN) has been studied in the last few years; however, prior works mostly focused on the spread that is initiated in a single layer of an M-IDN. In real world scenarios, influence spread can happen concurrently among many or all components making up the topology of an M-IDN. This paper investigates the effectiveness of different influence spread strategies in M-IDNs by providing a comprehensive analysis of the time evolution of influence propagation given different initial spreader strategies. For this study we consider a two-layer interdependent network and a general probabilistic threshold influence spread model …

Sparse General Non-Negative Matrix Factorization Based On Left Semi-Tensor Product, Zigang Chen, Lixiang Li, Haipeng Peng, Yuhong Liu, Haihua Zhu, Yixian Yang

Computer Science and Engineering

The dimension reduction of large scale high-dimensional data is a challenging task, especially the dimension reduction of face data and the accuracy increment of face recognition in the large scale face recognition system, which may cause large storage space and long recognition time. In order to further reduce the recognition time and the storage space in the large scale face recognition systems, on the basis of the general non-negative matrix factorization based on left semi-tensor (GNMFL) without dimension matching constraints proposed in our previous work, we propose a sparse GNMFL/L (SGNMFL/L) to decompose a large number of face data sets …

Authentication And Sql-Injection Prevention Techniques In Web Applications, Cagri Cetin

USF Tampa Graduate Theses and Dissertations

This dissertation addresses the top two “most critical web-application security risks” by combining two high-level contributions.

The first high-level contribution introduces and evaluates collaborative authentication, or coauthentication, a single-factor technique in which multiple registered devices work together to authenticate a user. Coauthentication provides security benefits similar to those of multi-factor techniques, such as mitigating theft of any one authentication secret, without some of the inconveniences of multi-factor techniques, such as having to enter passwords or biometrics. Coauthentication provides additional security benefits, including: preventing phishing, replay, and man-in-the-middle attacks; basing authentications on high-entropy secrets that can be generated and updated automatically; …