Computer Engineering Commons^™

Assessing Learning Outcomes Of A Mooc Incorporated Into An On-Campus Management Information Systems Class, Manying Qiu, Yaquan Xu

Journal of International Technology and Information Management

Massive open source online course (MOOC) platform enables enterprises to introduce their new innovations and deliver basic knowledge to handle the new products. We incorporated an openSAP course into a management information systems (MIS) class. Students learned the latest development of SAP customer relationship management (CRM) solutions along with the SAP enterprise resource planning (ERP) business processes integration that they learned in the classroom. 46.2% of the students obtained Record of Achievement and Confirmation of Participation certificates, which is higher than the average success rate of MOOCs. More importantly, the students experienced a way of sustainable and lifelong learning.

The Impact Of Personal Privacy On The Acceptance Of Mobile Phone Technology: A Case Of Tanzanian Smes, Renatus Michael Mushi

Journal of International Technology and Information Management

The adoption of mobile technology has gained a serious attention in organizations and individuals. SMEs in the developing countries have hugely been relying on mobile phone technology in performing their activities. The main reasons for the popularity of mobile phones include their perceived low cost, less learning curve, mobility and its compatibility with the usage at the SMEs level as compared to the desktop computers. Despite existence on studies on adoption of mobile technology in different contexts, few of them have explicitly explored the way personal privacy can affect its acceptance to be used at the workplaces.

This study covers …

Table Of Contents Jitim Vol 27 Issue 1, 2018

Journal of International Technology and Information Management

Table of Contents JITIM volume 27, issue 1 - 2018

Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi

Electronic Theses and Dissertations

The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage, …

A Graphical File System Visualization Tool For Operating Systems, Jacob Bundt

Honors Program Theses

Fileshark was developed for the primary purpose of aiding in the teaching of students in file system related courses, particularly at the undergraduate level, by providing a visual representation of often abstract file system ideas. Many teachers find it difficult to teach the file system in detail in a typical operating systems classroom environment due to its abstract nature and the inability to truly observe what is occurring within the file system. Fileshark provides an easy to use interface that can be used by both students and professors to visualize the internal workings of the file system and the processes …

Developing A Recurrent Neural Network With High Accuracy For Binary Sentiment Analysis, Kevin Cunanan

CMC Senior Theses

Sentiment analysis has taken on various machine learning approaches in order to optimize accuracy, precision, and recall. However, Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) account for the context of a sentence by using previous predictions as additional input for future sentence predictions. Our approach focused on developing an LSTM RNN that could perform binary sentiment analysis for positively and negatively labeled sentences. In collaboration with Mariam Salloum, I developed a collection of programs to classify individual sentences as either positive or negative. This paper additionally looks into machine learning, neural networks, data preprocessing, implementation, and resulting comparisons.

Categorical Range Reporting In 2d Using Wavelet Tree, Swathi Kanthareddy Sumithra

Electronic Theses and Dissertations

The research involved optimizing the space and bounding the output time by the output size in categorical range reporting of points within the given rectangle query Q in two dimension using wavelet trees and range counting. The time taken to report those points and space to tore n points in set S can be done using wavelet tree and range counting. Consider set S consisting of n points in two-dimension. An orthogonal range reporting query rectangle Q = [a,b] x [c,d] on set S is sent to report the set of points in S which interacts with the query rectangle[Q]. …

Toward Biologically-Inspired Self-Healing, Resilient Architectures For Digital Instrumentation And Control Systems And Embedded Devices, Shawkat Sabah Khairullah

Theses and Dissertations

Digital Instrumentation and Control (I&C) systems in safety-related applications of next generation industrial automation systems require high levels of resilience against different fault classes. One of the more essential concepts for achieving this goal is the notion of resilient and survivable digital I&C systems. In recent years, self-healing concepts based on biological physiology have received attention for the design of robust digital systems. However, many of these approaches have not been architected from the outset with safety in mind, nor have they been targeted for the automation community where a significant need exists. This dissertation presents a new self-healing digital …

Managing Io Resource For Co-Running Data Intensive Applications In Virtual Clusters, Dan Huang

Electronic Theses and Dissertations

Today Big Data computer platforms employ resource management systems such as Yarn, Torque, Mesos, and Google Borg to enable sharing the physical computing among many users or applications. Given virtualization and resource management systems, users are able to launch their applications on the same node with low mutual interference and management overhead on CPU and memory. However, there are still challenges to be addressed before these systems can be fully adopted to manage the IO resources in Big Data File Systems (BDFS) and shared network facilities. In this study, we mainly study on three IO management problems systematically, in terms …

A Scale Space Local Binary Pattern (Sslbp) – Based Feature Extraction Framework To Detect Bones From Knee Mri Scans, Jinyeong Mun

Electronic Theses and Dissertations

The medical industry is currently working on a fully autonomous surgical system, which is considered a novel modality to go beyond technical limitations of conventional surgery. In order to apply an autonomous surgical system to knees, one of the primarily responsible areas for supporting the total weight of human body, accurate segmentation of bones from knee Magnetic Resonance Imaging (MRI) scans plays a crucial role. In this paper, we propose employing the Scale Space Local Binary Pattern (SSLBP) feature extraction, a variant of local binary pattern extractions, for detecting bones from knee images. The proposed methods consist of two phases. …

Blockchain For Trustful Collaborations Between Immigrants, Citizens And Governments, Chun-Wei Chiang

Graduate Theses, Dissertations, and Problem Reports (ETD)

Immigrants usually are pro-social towards their hometowns and try to improve them. However, the lack of trust in their government can drive immigrants to work individually. As a result, their pro-social activities are usually limited in impact and scope. Although blockchain technology have the potential to solve the trust issue, people are not familiar with the technology and they have no idea why it is trustworthy. Previous research showed that the adopting user interface properly can increase people's trust in technology. This paper studies the interface factors that ease collaborations between immigrants and their home governments. We specifically focus on …

Insulting Words: "They Are Animals!", Carolyn A. Ristau

Animal Sentience

As Chapman & Huffman state, creating divisive human categories has rationalized atrocities committed against the “other.” Labeling neighboring warring villagers as “animals” is considered a despicable insult. Yet contemporary scientific views of many animals grant them thinking and conscious faculties, and the capacity for impressive achievements, many unattainable by humans. Robots, too, can accomplish many similar feats. But the essential reason we must protect animals is not because of their admirable abilities, but their capacity for consciousness, for suffering. Robots are not conscious. Participants in the human-animal debate should not complain about changing criteria for determining human uniqueness. New and …

How Children With Autism Spectrum Disorder Recognize Facial Expressions Displayed By A Rear-Projection Humanoid Robot, Farzaneh Askari, Huanghao Feng, Anibal Gutierrez, Timothy Sweeny, Mohammad H. Mahoor

Electrical and Computer Engineering: Graduate Student Scholarship

Background: Children with Autism Spectrum Disorder (ASD) experience reduced ability to perceive crucial nonverbal communication cues such as eye gaze, gestures, and facial expressions. Recent studies suggest that social robots can be used as effective tools to improve communication and social skills in children with ASD. One explanation has been put forward by several studies that children with ASD feel more contented and motivated in systemized and predictable environment, like interacting with robots.

Objectives: There have been few research studies evaluating how children with ASD perceive facial expression in humanoid robots but no research evaluating facial expression perception …

A Pilot Study On Facial Expression Recognition Ability Of Autistic Children Using Ryan, A Rear-Projected Humanoid Robot, Farzaneh Askari, Huanghao Feng, Timothy D. Sweeny, Mohammad H. Mahoor

Electrical and Computer Engineering: Graduate Student Scholarship

Rear-projected robots use computer graphics technology to create facial animations and project them on a mask to show the robot’s facial cues and expressions. These types of robots are becoming commercially available, though more research is required to understand how they can be effectively used as a socially assistive robotic agent. This paper presents the results of a pilot study on comparing the facial expression recognition abilities of children with Autism Spectrum Disorder (ASD) with typically developing (TD) children using a rear-projected humanoid robot called Ryan. Six children with ASD and six TD children participated in this research, where Ryan …

Mpart: Miss Ratio Curve Guided Partitioning In Key-Value Stores, Daniel Byrne

Dissertations, Master's Theses and Master's Reports

Web applications employ key-value stores to cache the data that is most commonly accessed. The cache improves an web application’s performance by serving its requests from memory, avoiding fetching them from the backend database. Since the memory space is limited, maximizing the memory utilization is a key to delivering the best performance possible. This has lead to the use of multi-tenant systems, allowing applications to share cache space. In addition, application data access patterns change over time, so the system should be adaptive in its memory allocation. In this thesis, we address both multi-tenancy (where a single cache is used …

Adaptive Dynamic Programming With Eligibility Traces And Complexity Reduction Of High-Dimensional Systems, Seaar Jawad Kadhim Al-Dabooni

Doctoral Dissertations

"This dissertation investigates the application of a variety of computational intelligence techniques, particularly clustering and adaptive dynamic programming (ADP) designs especially heuristic dynamic programming (HDP) and dual heuristic programming (DHP). Moreover, a one-step temporal-difference (TD(0)) and n-step TD (TD(λ)) with their gradients are utilized as learning algorithms to train and online-adapt the families of ADP. The dissertation is organized into seven papers. The first paper demonstrates the robustness of model order reduction (MOR) for simulating complex dynamical systems. Agglomerative hierarchical clustering based on performance evaluation is introduced for MOR. This method computes the reduced order denominator of the transfer …

Machine Learning Techniques Implementation In Power Optimization, Data Processing, And Bio-Medical Applications, Khalid Khairullah Mezied Al-Jabery

Doctoral Dissertations

"The rapid progress and development in machine-learning algorithms becomes a key factor in determining the future of humanity. These algorithms and techniques were utilized to solve a wide spectrum of problems extended from data mining and knowledge discovery to unsupervised learning and optimization. This dissertation consists of two study areas. The first area investigates the use of reinforcement learning and adaptive critic design algorithms in the field of power grid control. The second area in this dissertation, consisting of three papers, focuses on developing and applying clustering algorithms on biomedical data. The first paper presents a novel modelling approach for …

Gender Effects Of Robotics Programs On Stem-Related Self-Efficacy Of High School Students, Sandra Hall-Lay

Walden Dissertations and Doctoral Studies

Lack of STEM-related self-efficacy has impeded the growth of women in STEM fields. Out of school (OST) robotics programs and other STEM-related OST programs provide secondary students with opportunities to work in groups, brainstorm, and formulate ideas that require communication and teamwork. The purpose of this quantitative, quasi-experimental study was to compare STEM-related self-efficacy scores among male and female students who participated in OST robotics programs or other OST STEM-related programming. Independent variables were type of OST STEM program and gender. The dependent variable was students' STEM-related self-efficacy as measured by the Coping Self-Efficacy Scale. Responses from 149 students in …

A Time-Efficient Cmos-Memristive Programmable Circuit Realizing Logic Functions In Generalized And-Xor Structures, Muayad Aljafar, Marek Perkowski, John M. Acken, Robin Tan

Electrical and Computer Engineering Faculty Publications and Presentations

This paper describes a CMOS-memristive Programmable Logic Device connected to CMOS XOR gates (mPLD-XOR) for realizing multi-output functions well-suited for two-level {NAND, AND, NOR, OR}-XOR based design. This structure is a generalized form of AND-XOR logic where any combination of NAND, AND, NOR, OR, and literals can replace the AND level. For mPLD-XOR, the computational delay, which is measured as the number of clock cycles, equals the maximum number of inputs to any output XOR gate of a function assuming that the number of XOR gates is large enough to calculate the outputs of the function simultaneously. The input levels …

Application Of 3d Delaunay Triangulation In Fingerprint Authentication System, Wencheng Yang, Ahmed Ibrahim, Junaid Chaudhry, Song Wang, Jiankun Hu, Craig Valli

Research outputs 2014 to 2021

Biometric security has found many applications in Internet of Things (IoT) security. Many mobile devices including smart phones have supplied fingerprint authentication function. However, the authentication performance in such restricted environment has been downgraded significantly. A number of methods based on Delaunay triangulation have been proposed for minutiae-based fingerprint matching, due to some favorable properties of the Delaunay triangulation under image distortion. However, all existing methods are based on 2D pattern, of which each unit, a Delaunay triangle, can only provide limited discrimination ability and could cause low matching performance. In this paper, we propose a 3D Delaunay triangulation based …

A Security Review Of Local Government Using Nist Csf: A Case Study, Ahmed Ibrahim, Craig Valli, Ian Mcateer, Junaid Chaudhry

Research outputs 2014 to 2021

Evaluating cyber security risk is a challenging task regardless of an organisation’s nature of business or size, however, an essential activity. This paper uses the National Institute of Standards and Technology (NIST) cyber security framework (CSF) to assess the cyber security posture of a local government organisation in Western Australia. Our approach enabled the quantification of risks for specific NIST CSF core functions and respective categories and allowed making recommendations to address the gaps discovered to attain the desired level of compliance. This has led the organisation to strategically target areas related to their people, processes, and technologies, thus mitigating …

Review Of Deep Learning Methods In Robotic Grasp Detection, Shehan Caldera, Alexander Rassau, Douglas Chai

Research outputs 2014 to 2021

For robots to attain more general-purpose utility, grasping is a necessary skill to master. Such general-purpose robots may use their perception abilities to visually identify grasps for a given object. A grasp describes how a robotic end-effector can be arranged to securely grab an object and successfully lift it without slippage. Traditionally, grasp detection requires expert human knowledge to analytically form the task-specific algorithm, but this is an arduous and time-consuming approach. During the last five years, deep learning methods have enabled significant advancements in robotic vision, natural language processing, and automated driving applications. The successful results of these methods …

Patient Friendly Kidney Function Screening, Ragwa El Sayed, Rathna Ramesh, Alessandro Bellofiore, David Anastasiu, Melinda Simon

Faculty Publications

No abstract provided.

Teaching With Jupyter In-Class Activities: Lessons Learned And Next Steps, David Anastasiu

Faculty Publications

No abstract provided.

Real-Time Communication In Wireless Sensor Networks, Jeongcheol Lee, Babar Shah, Giovanni Pau, Javier Prieto, Ki Il Kim

All Works

No abstract provided.

Ms. An (Meeting Students’ Academic Needs): A Socially Adaptive Robot Tutor For Student Engagement In Math Education, Karina Liles

Theses and Dissertations

This research presents a new, socially adaptive robot tutor, Ms. An (Meeting Students’ Academic Needs). The goal of this research was to use a decision tree model to develop a socially adaptive robot tutor that predicted and responded to student emotion and performance to actively engage students in mathematics education. The novelty of this multi-disciplinary project is the combination of the fields of HRI, AI, and education. In this study we 1) implemented a decision tree model to classify student emotion and performance for use in adaptive robot tutoring-an approach not applied to educational robotics; 2) presented an intuitive interface …

Tracking, Detection And Registration In Microscopy Material Images, Hongkai Yu

Theses and Dissertations

Fast and accurate characterization of fiber micro-structures plays a central role for material scientists to analyze physical properties of continuous fiber reinforced composite materials. In materials science, this is usually achieved by continuously crosssectioning a 3D material sample for a sequence of 2D microscopic images, followed by a fiber detection/tracking algorithm through the obtained image sequence.

To speed up this process and be able to handle larger-size material samples, we propose sparse sampling with larger inter-slice distance in cross sectioning and develop a new algorithm that can robustly track large-scale fibers from such a sparsely sampled image sequence. In particular, …

A Proposal For A Technological Solution To Improve User Experience In A Shopping Center Based On Indoor Geolocation Services, Luinel Andrade, Johan Quintero, Eric Gamess, Antonio Russoniello

Research, Publications & Creative Work

For shopping centers, mobile devices and their associated technologies represent great business opportunities and a way to improve the user experience within their facilities. These types of constructions are usually quite large, multi-story, and with a significant number of shops, services, where the visitors may find themselves having difficulties to have a complete and up-to-date list of the stores, determine which stores and services are those that meet the characteristics or specifications they seek, know the location of the shops or how to reach them. This research studies and contemplates different technologies, tools, and approaches for the development of a …

If I Had A Million Cryptos: Cryptowallet Application Analysis And A Trojan Proof-Of-Concept, Trevor Haigh, Frank Breitinger, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Cryptocurrencies have gained wide adoption by enthusiasts and investors. In this work, we examine seven different Android cryptowallet applications for forensic artifacts, but we also assess their security against tampering and reverse engineering. Some of the biggest benefits of cryptocurrency is its security and relative anonymity. For this reason it is vital that wallet applications share the same properties. Our work, however, indicates that this is not the case. Five of the seven applications we tested do not implement basic security measures against reverse engineering. Three of the applications stored sensitive information, like wallet private keys, insecurely and one was …

การจําแนกรอยโรควัณโรคปอดด้วยโครงข่ายแคปซูล, ตะวันส่องแสง การย์กวินพงศ์

Chulalongkorn University Theses and Dissertations (Chula ETD)

การประยุกต์ใช้เทคนิคการเรียนรู้เชิงลึกสำหรับการจำแนกภาพทางการแพทย์ได้มีการขยายตัวเติบโตเป็นอย่างมากในช่วงหลายปีที่ผ่านมา โครงข่ายประสาทคอนโวลูชันหรือซีเอ็นเอ็นเป็นหนึ่งในหลายแบบจำลองสมรรถนะสูงที่รู้จักกันดีสำหรับการจำแนกและการแบ่งส่วนภาพ งานวิจัยนี้เสนอแนวคิดการใช้คอมพิวเตอร์ที่สามารถช่วยวินิจฉัยในเบื้องต้นการติดเชื้อวัณโรค ผู้วิจัยได้ปรับแต่งสถาปัตยกรรมซีเอ็นเอ็นสามโครงสร้างประกอบด้วย อเล็กซ์เน็ต วีจีจี-16 และ แคปส์เน็ต เพื่อจำแนกรอยโรควัณโรคบนภาพเอกซเรย์ทรวงอกหรือซีเอกซ์อาร์ที่ได้มาจากไลบรารีทางการแพทย์แห่งชาติและชุดข้อมูลไทยส่วนตัว ตัววัดที่ใช้ประเมินสมรรถนะตัวจำแนกประเภททั้งสาม ได้แก่ ความแม่นยำ ความไว และความจำเพาะ การทดสอบแบบจำลองทั้งสามบนชุดข้อมูลที่เพิ่มจำนวนด้วยการสุ่มตัวอย่างแบบสับเปลี่ยนให้ผลลัพธ์ค่าความแม่นยำที่เพิ่มขึ้นทุกแบบจำลอง นอกจากนี้ ยังได้มีการประเมินสมรรถนะแบบจำลองบนชุดข้อมูลที่เพิ่มจำนวนตัวอย่างด้วยการหมุนภาพ เนื่องจากในความเป็นจริงภาพซีเอกซ์อาร์อาจไม่ได้ตั้งตรงในแนวดิ่ง ผลการประเมินพบว่า แคปส์เน็ตให้ค่าตัววัดที่ดีกว่าแบบจำลองอเล็กซ์เน็ต และวีจีจี-16 เมื่อทำนายภาพแอฟฟีน