Computer Engineering Commons^™

Implementing Security-Enhanced Phr System In The Cloud Using Fame, Zuobin Ying, Wenjie Jiang, Ximeng Liu, Shengmin Xu

Research Collection School Of Computing and Information Systems

Personal Health Record (PHR) plays an important role in realizing the exchange and interaction of medical information as well as in managing chronic diseases. In the recent decade, plenty of researches have been carried out to resolve the secure sharing issue of PHR in the cloud via access control schemes. Attribute-based Encryption (ABE) is a promising technique, which implements access control by introducing the access policy. When ABE is used to construct access control scheme in the cloud, hiding and updating access policy have always been two research hotspots. However, all of the existing solutions only consider one of these …

Finding Needles In A Haystack: Leveraging Co-Change Dependencies To Recommend Refactorings, Marcos César De Oliveira, Davi Freitas, Rodrigo Bonifacio, Gustavo Pinto, David Lo

Research Collection School Of Computing and Information Systems

A fine-grained co-change dependency arises when two fine-grained source-code entities, e.g., a method,change frequently together. This kind of dependency is relevant when considering remodularization efforts (e.g., to keep methods that change together in the same class). However, existing approaches forrecommending refactorings that change software decomposition (such as a move method) do not explorethe use of fine-grained co-change dependencies. In this paper we present a novel approach for recommending move method and move field refactorings, which removes co-change dependencies and evolutionary smells, a particular type of dependency that arise when fine-grained entities that belong to different classes frequently change together. First …

Machine Learning In The State Design Pattern, Timothy Matthew Von Friesen

Theses and Dissertations

As the Internet of Things revolution continues to become more prevalent in humanity's daily routine, securing these devices is paramount. Society has seen a substantial increase in activity in the cyber-warfare battle space, resulting in an increasing amount of security breaches every year. The responsibility of securing our devices can no longer rely solely on cyber-security engineers keeping systems hardened through Security Technical Implementation Guides and vulnerability scans; it must shift towards the developer. Previous research has been done in this area of securing our devices. However, these solutions rely heavily on cloud computing resources to perform computationally expensive algorithms. …

Ldakm-Eiot: Lightweight Device Authentication And Key Management Mechanism For Edge-Based Iot Deployment, Mohammad Wazid, Ashok Kumar Das, Sachin Shetty, Joel J. P. C. Rodrigues, Youngho Park

VMASC Publications

In recent years, edge computing has emerged as a new concept in the computing paradigm that empowers several future technologies, such as 5G, vehicle-to-vehicle communications, and the Internet of Things (IoT), by providing cloud computing facilities, as well as services to the end users. However, open communication among the entities in an edge based IoT environment makes it vulnerable to various potential attacks that are executed by an adversary. Device authentication is one of the prominent techniques in security that permits an IoT device to authenticate mutually with a cloud server with the help of an edge node. If authentication …

Extending The Capabilities Of Von Neumann With A Dataflow Sub-Isa, Martin Cowley

Masters Theses

Instruction set architectures (ISAs) such as x86, ARM, and RISC-V follow the control flow model of computation, where a program is defined as a sequence of instructions. Early processors executed instructions one-by-one based on the control flow of a program. Dataflow is an alternative model of computation that uses the availability of data to drive instruction execution. Any instruction can be chosen for execution, independent of the instruction order, as long as the data is available for that instruction. While modern processors incorporate concepts of the dataflow model in the microarchitecture, the implementation of the ISA, the amount of instruction …

Tuning Networks For Prosocial Behavior: From Senseless Swarms To Smart Mobs [Commentary], Sun Sun Lim, Roland Bouffanais

Research Collection College of Integrative Studies

Social media have been seen to accelerate the spread of negative content such as disinformation and hate speech, often unleashing a reckless herd mentality within networks, further aggravated by malicious entities using bots for amplification. So far, the response to this emerging global crisis has centered around social media platform companies making reactive moves that appear to have greater symbolic value than practical utility. Proposes a solution to favor prosocial behavior via social networks.

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 …

Extracting Social Network From Literary Prose, Tarana Tasmin Bipasha

Graduate Theses and Dissertations

This thesis develops an approach to extract social networks from literary prose, namely, Jane Austen’s published novels from eighteenth- and nineteenth- century. Dialogue interaction plays a key role while we derive the networks, thus our technique relies upon our ability to determine when two characters are in conversation. Our process involves encoding plain literary text into the Text Encoding Initiative’s (TEI) XML format, character name identification, conversation and co-occurrence detection, and social network construction. Previous work in social network construction for literature have focused on drama, specifically manually TEI-encoded Shakespearean plays in which character interactions are much easier to track …

Evaluation And Analysis Of Null Convention Logic Circuits, John Davis Brady

Graduate Theses and Dissertations

Integrated circuit (IC) designers face many challenges in utilizing state-of-the-art technology nodes, such as the increased effects of process variation on timing analysis and heterogeneous multi-die architectures that span across multiple technologies while simultaneously increasing performance and decreasing power consumption. These challenges provide opportunity for utilization of asynchronous design paradigms due to their inherent flexibility and robustness.

While NULL Convention Logic (NCL) has been implemented in a variety of applications, current literature does not fully encompass the intricacies of NCL power performance across a variety of applications, technology nodes, circuit scale, and voltage scaling, thereby preventing further adoption and utilization …

Pixel-Level Deep Multi-Dimensional Embeddings For Homogeneous Multiple Object Tracking, Mateusz Mittek

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The goal of Multiple Object Tracking (MOT) is to locate multiple objects and keep track of their individual identities and trajectories given a sequence of (video) frames. A popular approach to MOT is tracking by detection consisting of two processing components: detection (identification of objects of interest in individual frames) and data association (connecting data from multiple frames). This work addresses the detection component by introducing a method based on semantic instance segmentation, i.e., assigning labels to all visible pixels such that they are unique among different instances. Modern tracking methods often built around Convolutional Neural Networks (CNNs) and additional, …

Digitalization In Practice: The Fifth Discipline Advantage, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

Purpose The purpose of this paper is to provide advice to organizations on how to become successful in the digital age. The paper revisits Peter Senge's (1990) notion of the learning organization and discusses the relevance of systems thinking and the other four disciplines, namely, personal mastery, mental models, shared vision and team learning in the context of the current digitalization megatrend. Design/methodology/approach This paper is based on content analysis of essays from international organizations, strategy experts and management scholars, and insights gained from the author's consulting experience. A comparative case study from the health and social sector is also …

Seer: An Explainable Deep Learning Midi-Based Hybrid Song Recommender System, Khalil Damak, Olfa Nasraoui

Faculty and Staff Scholarship

State of the art music recommender systems mainly rely on either matrix factorization-based collaborative filtering approaches or deep learning architectures. Deep learning models usually use metadata for content-based filtering or predict the next user interaction by learning from temporal sequences of user actions. Despite advances in deep learning for song recommendation, none has taken advantage of the sequential nature of songs by learning sequence models that are based on content. Aside from the importance of prediction accuracy, other significant aspects are important, such as explainability and solving the cold start problem. In this work, we propose a hybrid deep learning …

Iomt Malware Detection Approaches: Analysis And Research Challenges, Mohammad Wazid, Ashok Kumar Das, Joel J.P.C. Rodrigues, Sachin Shetty, Youngho Park

VMASC Publications

The advancement in Information and Communications Technology (ICT) has changed the entire paradigm of computing. Because of such advancement, we have new types of computing and communication environments, for example, Internet of Things (IoT) that is a collection of smart IoT devices. The Internet of Medical Things (IoMT) is a specific type of IoT communication environment which deals with communication through the smart healthcare (medical) devices. Though IoT communication environment facilitates and supports our day-to-day activities, but at the same time it has also certain drawbacks as it suffers from several security and privacy issues, such as replay, man-in-the-middle, impersonation, …

Mitigating Pilot Contamination Through Optimizing Pilot Allocation In Massive Mimo Systems, Rand Abdul Hussain

Theses and Dissertations

This dissertation has proposed several algorithms to optimize the allocation of pilots to the users’ equipment (UEs) to mitigate the effect of the pilot contamination problem in the massive MIMO systems. Pilot contamination reduces the performance of massive MIMO systems due to the reduction in the quality of the estimated channel between a UE and the serving base station (BS). The limitation of the number of samples in a coherence block limits the number of unique mutually orthogonal pilots, and hence, reusing the set of pilots across the cells causes inter-cell interference during pilot transmission, which is called pilot contamination. …

Comparative Study Of Winding Configurations Of A Five-Phase Flux-Switching Pm Machine, Hao Chen, Xiangdong Liu, Ayman M. El-Refaie, Jing Zhao, Nabeel Demerdash, Jiangbiao He

Electrical and Computer Engineering Faculty Research and Publications

This paper introduces a general method for determination of the most suitable winding configurations for five-phase flux-switching permanent magnet (FSPM) machines, associated with feasible stator/rotor-pole combinations. Consequently, the effect of winding configurations on the performance of a five-phase outer-rotor FSPM machine is thoroughly investigated, including non-overlapping concentrated windings (single-layer, double-layer, and multi-layer) as well as distributed winding. The electromagnetic characteristics in the low-speed region, the flux-weakening capability in the high-speed region, and the fault-tolerant capability under faulty situations are evaluated and compared in detail. This work shows that compared with the conventional single-layer or double-layer concentrated windings, the FSPM machine …

Identifying Regional Trends In Avatar Customization, Peter Mawhorter, Sercan Sengun, Haewoon Kwak, D. Fox Harrell

Research Collection School Of Computing and Information Systems

Since virtual identities such as social media profiles and avatars have become a common venue for self-expression, it has become important to consider the ways in which existing systems embed the values of their designers. In order to design virtual identity systems that reflect the needs and preferences of diverse users, understanding how the virtual identity construction differs between groups is important. This paper presents a new methodology that leverages deep learning and differential clustering for comparative analysis of profile images, with a case study of almost 100 000 avatars from a large online community using a popular avatar creation …

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. …

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 …

Of Promoting Networking And Protecting Privacy: Effects Of Defaults And Regulatory Focus On Social Media Users’ Preference Settings, Hichang Cho, Sungjong Roh, Byungho Park

Research Collection Lee Kong Chian School Of Business

Privacyresearch has debated whether privacy decision-making is determined by users'stable preferences (i.e., individual traits), privacy calculus (i.e.,cost-benefit analysis), or “responses on the spot” that vary across contexts.This study focuses on two factors—default setting as a contextual factor andregulatory focus as an individual difference factor—and examines the degree towhich these factors affect social media users' decisionmaking when usingprivacy preference settings in a fictitious social networking site. Theresults, based on two experimental studies (study 1, n = 414; study 2, n =213), show that default settings significantly affect users' privacypreferences, such that users choose the defaults or alternatives proximal tothem. Study 2 …

Robot Simulation Analysis, Jacob Miller, Jeremy Evert

Student Research

• Simulate virtual robot for test and analysis

• Analyze SLAM solutions using ROS

• Assemble a functional Turtlebot

• Emphasize projects related to current research trajectories for NASA, and general robotics applications