Computer Engineering Commons^™

Visualising The Complex Features Of Source Code, Ivan Bacher

Doctoral

Software development is a complex undertaking composed of several activities that include reading, writing, and modifying source code. Indeed, previous studies have shown that the majority of the effort invested in software development is dedicated to understanding code. This includes understanding the static structure, dynamic behaviour, and evolution of the code. Given these particular characteristics, as well as the high complexity of source code, it is reasonable to consider how visualisation can facilitate source code understanding. This work proposes to extend existing software development tools with visualisations that can be used to encode the various complex features within a source …

State Feedback Of Complex Systems Using Fuzzy Cognitive Maps, Vassiliki Mpelogianni, Ioannis Arvanitakis, Peter P. Groumpos

International Journal of Business and Technology

Complex systems have become a research area with increasing interest over the last years. The emergence of new technologies, the increase in computational power with reduced resources and cost, the integration of the physical world with computer based systems has created the possibility of significantly improving the quality of life of humans. While a significant degree of automation within these systems exists and has been provided in the past decade with examples of the smart homes and energy efficient buildings, a paradigm shift towards autonomy has been noted. The need for autonomy requires the extraction of a model; while a …

Maturity Level Of Kosovo Manufacturing Industry With Regard To Industry 4.0, Fatmir Azemi, Edmond Hajrizi, Bekim Maloku

International Journal of Business and Technology

In this paper the concept of Maturity Level of Kosovo Industry will be presented according to the Industry 4.0. Digitalization of factory has impact the entire business environment and lead to Smart Enterprises. To create a model of Smart Factory, first we have analyzed the existing situation of Kosovo Manufacturing Industry with regard to revolution of Industry. In this paper we will describe the results of a recent research at the Kosovo manufacturing companies and are included metalworking and furniture industry, where is developed a Maturity Level for Kosovo Industry. To describe the Maturity Level of Kosovo Industry we have …

Decision Making Based On Data Analyses Using Data Warehouses, Valdrin Haxhiu

International Journal of Business and Technology

Data warehouses are a collection of several databases, whose goal is to help different companies and corporations make important decisions about their activities. These decisions are taken from the analyses that are made to the data within the data warehouse. These data are taken from data that companies and corporations collect on daily basis from their branches that may be located in different cities, regions, states and continents. Data that are entered to data warehouses are historical data and they represent that part of data that is important for making decisions. These data go under a transformation process in order …

Characteristics And Temporal Behavior Of Internet Backbone Traffic, Artan Salihu, Muharrem Shefkiu, Arianit Maraj

International Journal of Business and Technology

With the rapid increase demand for data usage, Internet has become complex and harder to analyze. Characterizing the Internet traffic might reveal information that are important for Network Operators to formulate policy decisions, develop techniques to detect network anomalies, help better provision network resources (capacity, buffers) and use workload characteristics for simulations (typical packet sizes, flow durations, common protocols).

In this paper, using passive monitoring and measurements, we show collected data traffic at Internet backbone routers. First, we reveal main observations on patterns and characteristics of this dataset including packet sizes, traffic volume for inter and intra domain and protocol …

Permission-Based Privacy Analysis For Android Applications, Erza Gashi, Zhilbert Tafa

International Journal of Business and Technology

While Information and Communication Technology (ICT) trends are moving towards the Internet of Things (IoT), mobile applications are becoming more and more popular. Mostly due to their pervasiveness and the level of interaction with the users, along with the great number of advantages, the mobile applications bring up a great number of privacy related issues as well. These platforms can gather our very sensitive private data by only granting them a list of permissions during the installation process. Additionally, most of the users can find it difficult, or even useless, to analyze system permissions. Thus, their guess of app’s safety …

A Need For An Integrative Security Model For Semantic Stream Reasoning Systems, Admirim Aliti, Edmond Jajaga, Kozeta Sevrani

International Journal of Business and Technology

State-of-the-art security frameworks have been extensively addressing security issues for web resources, agents and services in the Semantic Web. The provision of Stream Reasoning as a new area spanning Semantic Web and Data Stream Management Systems has eventually opened up new challenges. Namely, their decentralized nature, the metadata descriptions, the number of users, agents, and services, make securing Stream Reasoning systems difficult to handle. Thus, there is an inherent need of developing new security models which will handle security and automate security mechanisms to a more autonomous system that supports complex and dynamic relationships between data, clients and service providers. …

Fc2: Cloud-Based Cluster Provisioning For Distributed Machine Learning, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

Training large, complex machine learning models such as deep neural networks with big data requires powerful computing clusters, which are costly to acquire, use and maintain. As a result, many machine learning researchers turn to cloud computing services for on-demand and elastic resource provisioning capabilities. Two issues have arisen from this trend: (1) if not configured properly, training models on cloud-based clusters could incur significant cost and time, and (2) many researchers in machine learning tend to focus more on model and algorithm development, so they may not have the time or skills to deal with system setup, resource selection …

Discovering Cancer Subtypes Via An Accurate Fusion Strategy On Multiple Profile Data, Limin Jiang, Yongkang Xiao, Yijie Ding, Jijun Tang, Fei Guo

Faculty Publications

Discovering cancer subtypes is useful for guiding clinical treatment of multiple cancers. Progressive profile technologies for tissue have accumulated diverse types of data. Based on these types of expression data, various computational methods have been proposed to predict cancer subtypes. It is crucial to study how to better integrate these multiple profiles of data. In this paper, we collect multiple profiles of data for five cancers on The Cancer Genome Atlas (TCGA). Then, we construct three similarity kernels for all patients of the same cancer by gene expression, miRNA expression and isoform expression data. We also propose a novel unsupervised …

Towards Multi-Lingual Pneumonia Research Data Collection Using The Community-Acquired Pneumonia International Cohort Study Database, William A. Mattingly, Kimberley A. Buckner, Senen Pena

The University of Louisville Journal of Respiratory Infections

Background: Although multilingual interfaces are preferred by most users when they have a choice, organizations are often unable to support and troubleshoot problems involving multiple user languages. Software that has been structured with multiple languages and data interlinking considerations early in its development is more likely to be easily maintained. We describe the process of adding multilingual support to the CAPO international Cohort study database using REDCap.

Methods: Using Google Translate API we extend the supported Spanish language version of REDCap to the most recent version used by CAPO, 8.1.4. We then translate the English data dictionary for CAPO to …

Clinical Research In Pneumonia: Role Of Artificial Intelligence, Timothy L. Wiemken, Robert R. Kelley, William A. Mattingly, Julio A. Ramirez

The University of Louisville Journal of Respiratory Infections

No abstract provided.

A Comparative Study Of Wireless Star Networks Implemented With Current Wireless Protocols, Sizen Neupane

Masters Theses

Wireless communication is one of the most advanced technological developments of this era. Wireless technology enables both short-range and long-range services. Today, there are several different wireless communication technologies in existence. Each has its characteristics different from another one. This thesis will implement three short-range wireless technologies in star connection and compare the performance in the wireless network.

For this thesis, the performance of three different RF protocols - a proprietary packet protocol called Enhanced ShockBurst in nRF24L01+, Bluetooth Low Energy, and a special Wi- Fi protocol ESP-Now was compared. The general concept was to establish a star network for …

A Coordination Framework For Multi-Agent Persuasion And Adviser Systems, Budhitama Subagdja, Ah-Hwee Tan, Yilin Kang

Research Collection School Of Computing and Information Systems

Assistive agents have been used to give advices to the users regarding activities in daily lives. Although adviser bots are getting smarter and gaining more popularity these days they are usually developed and deployed independent from each other. When several agents operate together in the same context, their advices may no longer be effective since they may instead overwhelm or confuse the user if not properly arranged. Only little attentions have been paid to coordinating different agents to give different advices to a user within the same environment. However, aligning the advices on-the-fly with the appropriate presentation timing at the …

Deception In Finitely Repeated Security Games, Thanh H. Nguyen, Yongzhao Wang, Arunesh Sinha, Michael P. Wellman

Research Collection School Of Computing and Information Systems

Allocating resources to defend targets from attack is often complicated by uncertainty about the attacker’s capabilities, objectives, or other underlying characteristics. In a repeated interaction setting, the defender can collect attack data over time to reduce this uncertainty and learn an effective defense. However, a clever attacker can manipulate the attack data to mislead the defender, influencing the learning process toward its own benefit. We investigate strategic deception on the part of an attacker with private type information, who interacts repeatedly with a defender. We present a detailed computation and analysis of both players’ optimal strategies given the attacker may …

Topical Co-Attention Networks For Hashtag Recommendation On Microblogs, Yang Li, Ting Liu, Jingwen Hu, Jing Jiang

Research Collection School Of Computing and Information Systems

Hashtags provide a simple and natural way of organizing content in microblog services. Along with the fast growing of microblog services, the task of recommending hashtags for microblogs has been given increasing attention in recent years. However, much of the research depends on hand-crafted features. Motivated by the successful use of neural models for many natural language processing tasks, in this paper, we adopt an attention based neural network to learn the representation of a microblog post. Unlike previous works, which only focus on content attention of microblogs, we propose a novel Topical CoAttention Network (TCAN) that jointly models content …

Permanent Magnet Vernier Machine: A Review, Fan Wu, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

Permanent magnet vernier machines (PMVMs) gained a lot of interest over the past couple of decades. This is mainly due to their high torque density enabled by the magnetic gearing effect. This study will provide a thorough review of recent advances in PMVMs. This review will cover the principle of operation and nature of magnetic gearing in PMVMs, and a better understanding of novel PMVM topologies using different winding configuration as well as different modulation poles and rotor structures. Detailed discussions on the choice of gear ratio, slot-pole combinations, design optimisation and role of advanced materials in PMVMs will be …

The Scientific Information Exchange General Model At Digital Library Context: Internet Of Things, Nayere Soleimanzade, Asefeh Asemi, Mozafar Cheshmehsohrabi, Ahmad Shabani

Library Philosophy and Practice (e-journal)

Introduction: This paper aims to develop a Scientific Information Exchange General Model at Digital Library in Context of Internet of things, which would enable automated and efficient library services. To accomplish its objective, the main classes (Concepts), sub-classes, attributes are identified in order to introduce an appropriate model.

Methodology: The approach of this study is basic, exploratory, and developmental and is run through a mixed method consisting of documentary, Delphi, and data modeling methods. The study population in the documentary section includes the study of information resources retrieved in related subjects. The study population in the Delphi section is …

Novel Test Fixture For Characterizing Mems Switch Microcontact Reliability And Performance, Protap Mahanta, Farhana Anwar, Ronald A. Coutu Jr.

Electrical and Computer Engineering Faculty Research and Publications

In microelectromechanical systems (MEMS) switches, the microcontact is crucial in determining reliability and performance. In the past, actual MEMS devices and atomic force microscopes (AFM)/scanning probe microscopes (SPM)/nanoindentation-based test fixtures have been used to collect relevant microcontact data. In this work, we designed a unique microcontact support structure for improved post-mortem analysis. The effects of contact closure timing on various switching conditions (e.g., cold-switching and hot-switching) was investigated with respect to the test signal. Mechanical contact closing time was found to be approximately 1 us for the contact force ranging from 10–900 μN. On the other hand, for the 1 …

Two-Stage Bagging Pruning For Reducing The Ensemble Size And Improving The Classification Performance, Hua Zhang, Yujie Song, Bo Jiang, Bi Chen, Guogen Shan

Environmental & Global Health Faculty Research

Ensemble methods, such as the traditional bagging algorithm, can usually improve the performance of a single classifier. However, they usually require large storage space as well as relatively time-consuming predictions. Many approaches were developed to reduce the ensemble size and improve the classification performance by pruning the traditional bagging algorithms. In this article, we proposed a two-stage strategy to prune the traditional bagging algorithm by combining two simple approaches: accuracy-based pruning (AP) and distance-based pruning (DP). These two methods, as well as their two combinations, “AP+DP” and “DP+AP” as the two-stage pruning strategy, were all examined. Comparing with the single …

Influence Propagation For Social Graph-Based Recommendations, Avni Gulati, Magdalini Eirinaki

Faculty Publications

Social networking is an inevitable behavior of humans living in a society. In recent years, and with the rise of online social networks, personalized recommendations that leverage the social aspect have become a very intriguing domain for researchers. In this work, we explore how influence propagation and the decay in the cascading effect of influence from influential users can be leveraged to generate social graph-based recommendations. Understanding how influence propagates within a social network is itself a challenging problem. Few researchers have considered influence propagation and even fewer have considered decay in the cascading effect of influence in a social …

Finding Truth In Fake News: Reverse Plagiarism And Other Models Of Classification, Matthew Przybyla, David Tran, Amber Whelpley, Daniel W. Engels

SMU Data Science Review

As the digital age creates new ways of spreading news, fake stories are propagated to widen audiences. A majority of people obtain both fake and truthful news without knowing which is which. There is not currently a reliable and efficient method to identify “fake news”. Several ways of detecting fake news have been produced, but the various algorithms have low accuracy of detection and the definition of what makes a news item ‘fake’ remains unclear. In this paper, we propose a new method of detecting on of fake news through comparison to other news items on the same topic, as …

Comparative Study Of Sentiment Analysis With Product Reviews Using Machine Learning And Lexicon-Based Approaches, Heidi Nguyen, Aravind Veluchamy, Mamadou Diop, Rashed Iqbal

SMU Data Science Review

In this paper, we present a comparative study of text sentiment classification models using term frequency inverse document frequency vectorization in both supervised machine learning and lexicon-based techniques. There have been multiple promising machine learning and lexicon-based techniques, but the relative goodness of each approach on specific types of problems is not well understood. In order to offer researchers comprehensive insights, we compare a total of six algorithms to each other. The three machine learning algorithms are: Logistic Regression (LR), Support Vector Machine (SVM), and Gradient Boosting. The three lexicon-based algorithms are: Valence Aware Dictionary and Sentiment Reasoner (VADER), Pattern, …

Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater

SMU Data Science Review

The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide best …

Project Insight: A Granular Approach To Enterprise Cybersecurity, Sunna Quazi, Adam Baca, Sam Darsche

SMU Data Science Review

In this paper, we disambiguate risky activity corporate users are propagating with their software in real time by creating an enterprise security visualization solution for system administrators. The current problem in this domain is the lag in cyber intelligence that inhibits preventative security measure execution. This is partially due to the overemphasis of network activity, which is a nonfinite dataset and is difficult to comprehensively ingest with analytics. We address these concerns by elaborating on the beta of a software called "Insight" created by Felix Security. The overall solution leverages endpoint data along with preexisting whitelist/blacklist designations to unambiguously communicate …

Direct-To-Patient Survey For Diagnosis Of Benign Paroxysmal Positional Vertigo, Heidi Richburg, Richard J. Povinelli, David Friedland

Electrical and Computer Engineering Faculty Research and Publications

Given the high incidence of dizziness and its frequent misdiagnosis, we aim to create a clinical support system to classify the presence or absence of benign paroxysmal positional vertigo with high accuracy and specificity. This paper describes a three-phase study currently underway for classification of benign paroxysmal positional vertigo, which includes diagnosis by a specialist in a clinical setting. Patient background information is collected by a survey on an Android tablet and machine learning techniques are applied for classification. Decision trees and wrappers are employed for their ability to provide information about the question set. One goal of the study …

Multivariate Information Fusion With Fast Kernel Learning To Kernel Ridge Regression In Predicting Lncrna-Protein Interactions, Cong Shen, Yijie Ding, Jijun Tang, Fei Guo

Faculty Publications

Long non-coding RNAs (lncRNAs) constitute a large class of transcribed RNA molecules. They have a characteristic length of more than 200 nucleotides which do not encode proteins. They play an important role in regulating gene expression by interacting with the homologous RNA-binding proteins. Due to the laborious and time-consuming nature of wet experimental methods, more researchers should pay great attention to computational approaches for the prediction of lncRNA-protein interaction (LPI). An in-depth literature review in the state-of-the-art in silico investigations, leads to the conclusion that there is still room for improving the accuracy and velocity. This paper propose a novel …

A Deep Recurrent Q Network Towards Self-Adapting Distributed Microservices Architecture (In Press), Basel Magableh

Articles

One desired aspect of microservices architecture is the ability to self-adapt its own architecture and behaviour in response to changes in the operational environment. To achieve the desired high levels of self-adaptability, this research implements the distributed microservices architectures model, as informed by the MAPE-K model. The proposed architecture employs a multi adaptation agents supported by a centralised controller, that can observe the environment and execute a suitable adaptation action. The adaptation planning is managed by a deep recurrent Q-network (DRQN). It is argued that such integration between DRQN and MDP agents in a MAPE-K model offers distributed microservice architecture …

Design And Evaluation Of Iot-Enabled Instrumentation For A Soil-Bentonite Slurry Trench Cutoff Wall, Jeffrey C. Evans, Alan Marchiori, Yadong Li

Faculty Journal Articles

In this work, we describe our approach and experiences bringing an instrumented soil-bentonite slurry trench cutoff wall into a modern IoT data collection and visualization pipeline. Soil-bentonite slurry trench cutoff walls have long been used to control ground water flow and contaminant transport. A Raspberry Pi computer on site periodically downloads the sensor data over a serial interface from an industrial datalogger and transmits the data wirelessly to a gateway computer located 1.3 km away using a reliable transmission protocol. The resulting time-series data is stored in a MongoDB database and data is visualized in real-time by a custom web …

Application Of Virtual Reality In Rehabilitation Of Special Populations, Tingting Liu, Liu Zhen, Ping'an Qian, Rongrong Xuan, Wang Jin, Yanjie Chai

Journal of System Simulation

Abstract: With the continuous development of urbanization and the trend of population aging, the number of people who need physical and mental rehabilitation continues to increase. Using information technology to assist the rehabilitation process has the important practical significance. The existing studies about the application of virtual reality (VR) technology in the rehabilitation, psychological problems and children with autism for stroke are reviewed. A framework for the intelligent rehabilitation system is proposed. Virtual agent, the technology of somatosensory and voice recognition are advised to be used. Based on the proposed framework, a prototype rehabilitation game for autism and an upper …

A Review Of Rare Event Simulation, Liping Wang, Wenhui Fan

Journal of System Simulation

Abstract: Rare-event has a great significance for its lower probability of occurrence and greater harmfulness, the traditional Monte Carlo method is difficult to analyze it effectively. Rare-event simulation technique which is developed quickly and applied in many areas can sample the rare-event effectively with variance reduction methods and can estimate the occurrence probability of rare-event. The research status of rare-event simulation technique is summarized firstly; the principles, problems and progress of the main methods are analyzed and concluded secondly; after that the application fields of the technique are elaborated and summarized; the future development tendency of rare event simulation technique …