Computer Engineering Commons^™

A Comparison Of Two Generalizations To The Linear Sampling Method For Inverse Scattering, Yeasmin Sultana, James E. Richie

Electrical and Computer Engineering Faculty Research and Publications

The linear sampling method (LSM) is a very popular method for determining the boundary of an object from the scattered field. However, there are instances where LSM provides the convex hull of the boundary rather than the true boundary. There are two common generalizations to LSM: the Generalized Linear Sampling Method (GLSM) and the Multipoles-based Linear Sampling Method (MLSM). In this paper, the ability of GLSM and MLSM to overcome some of the deficiencies of LSM are investigated. It is found that GLSM may be ideal for imaging thin features of scatterers and that MLSM can provide an improvement over …

Artificial Intelligence (Ai): The New Look Of Customer Service In A Cybersecurity World, Sharon L. Burton

Publications

Cybersecurity leaders are not adequately developed to guide the re-engineering of quality customer service (QCS) workflows, designed with automation and AI, that interrelate with people through customers’ perceptions. Realizing re-engineering processes should be a team effort with well-versed leadership and stakeholders guiding the successful design through a follow-up process. Leaders must shape compelling and straightforward needs to learn and teach employees and chat boxes indispensable customer service skills demonstrating patience, self-discipline, flexibility, and resourcefulness in communication with irritated customers or difficult circumstances. Whether the analysis, design, development, and implementation struggles are vacuums in cybersecurity knowledge, skill, and abilities or a …

Backlog Burner: An Adventure Into Automated Scheduling, Anjolaoluwa J. Olubusi

Senior Independent Study Theses

The focus of this independent study is to explain the nurse scheduling problem (NSP) and use it as a basis to create an automated scheduling program. The nurse scheduling problem is an operational research problem that sets to find an optimal hospital schedule that fulfills the needs of the hospital and the personal requests of the nurses. The majority of solutions for the nurse scheduling problem are often designed within a hospital setting. The objective of this independent study is to use the solutions of the nurse scheduling problem to develop an automated scheduling program for the College of Wooster …

Towards Cloud-Based Cost-Effective Serverless Information System, Isaac C. Angle

EWU Masters Thesis Collection

E-commerce information systems are becoming increasingly popular for businesses to adopt. In this work, we propose a serverless information system that will reduce costs for small businesses trying to create an e-commerce website. The proposed serverless system is built entirely in Amazon Web Services (AWS). The proposed serverless system allows businesses to pay for the use of cloud resources on a per-order granularity. This model reduces the cost of the information system when compared to a traditional cloud-based system. As e-commerce websites become more vital for small businesses, a cost effective serverless approach is promising.

Computer Vision Based Classification Of Fruits And Vegetables For Self-Checkout At Supermarkets, Khurram Hameed

Theses: Doctorates and Masters

The field of machine learning, and, in particular, methods to improve the capability of machines to perform a wider variety of generalised tasks are among the most rapidly growing research areas in today’s world. The current applications of machine learning and artificial intelligence can be divided into many significant fields namely computer vision, data sciences, real time analytics and Natural Language Processing (NLP). All these applications are being used to help computer based systems to operate more usefully in everyday contexts. Computer vision research is currently active in a wide range of areas such as the development of autonomous vehicles, …

Statistics-Based Anomaly Detection And Correction Method For Amazon Customer Reviews, Ishani Chatterjee

Dissertations

People nowadays use the Internet to project their assessments, impressions, ideas, and observations about various subjects or products on numerous social networking sites. These sites serve as a great source of gathering information for data analytics, sentiment analysis, natural language processing, etc. The most critical challenge is interpreting this data and capturing the sentiment behind these expressions. Sentiment analysis is analyzing, processing, concluding, and inferencing subjective texts with the views. Companies use sentiment analysis to understand public opinions, perform market research, analyze brand reputation, recognize customer experiences, and study social media influence. According to the different needs for aspect granularity, …

Machine Learning Techniques For Network Analysis, Irfan Lateef

Dissertations

The network's size and the traffic on it are both increasing exponentially, making it difficult to look at its behavior holistically and address challenges by looking at link level behavior. It is possible that there are casual relationships between links of a network that are not directly connected and which may not be obvious to observe. The goal of this dissertation is to study and characterize the behavior of the entire network by using eigensubspace based techniques and apply them to network traffic engineering applications.

A new method that uses the joint time-frequency interpretation of eigensubspace representation for network statistics …

On Resource-Efficiency And Performance Optimization In Big Data Computing And Networking Using Machine Learning, Wuji Liu

Dissertations

Due to the rapid transition from traditional experiment-based approaches to large-scale, computational intensive simulations, next-generation scientific applications typically involve complex numerical modeling and extreme-scale simulations. Such model-based simulations oftentimes generate colossal amounts of data, which must be transferred over high-performance network (HPN) infrastructures to remote sites and analyzed against experimental or observation data on high-performance computing (HPC) facility. Optimizing the performance of both data transfer in HPN and simulation-based model development on HPC is critical to enabling and accelerating knowledge discovery and scientific innovation. However, such processes generally involve an enormous set of attributes including domain-specific model parameters, network transport …

A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko

Dissertations

To repair an incorrect program does not mean to make it correct; it only means to make it more-correct, in some sense, than it is. In the absence of a concept of relative correctness, i.e. the property of a program to be more-correct than another with respect to a specification, the discipline of program repair has resorted to various approximations of absolute (traditional) correctness, with varying degrees of success. This shortcoming is concealed by the fact that most program repair tools are tested on basic cases, whence making them absolutely correct is not clearly distinguishable from making them relatively more-correct. …

Scalable Scientific Data Management On High-Performance Computing Systems, Zhenbo Qiao

Dissertations

As high-performance computing (HPC) is being scaled up to exascale to accommodate new modeling and simulation needs, I/O has continued to be a major bottleneck in the end-to-end scientific processes. To bridge the widening gap between compute and I/O, and enable data to be more efficiently stored and analyzed, simulation outputs need to be refactored, reduced, and appropriately mapped to storage tiers. Also, a major question that the community is striving to answer is how to co-design data storage and complex physics-rich analytics in a way that the time to knowledge can be minimized in post-processing. As HPC storage systems …

Lapindo Embankment Security Monitoring System Based On Iot, Shazana Dhiya Ayuni, Syamsudduha Syahrorini, Jamaaluddin Jamaaluddin

Elinvo (Electronics, Informatics, and Vocational Education)

Since 2006 Lapindo mudflow caused by natural gas drilling in Sidoarjo. Nowdays the mudflow still can't be stopped, and to prevent it from resident's houses, embankments were built. Eventough the embankments and guardrails has been built but sometimes the mud flowing into resident's houses while its raining or the embankments were subsidence or reep. Severity, the distance between the embankment and the residents' houses is about 500 m. So far, the handling action while embankments ware subsidence is residents report the accidents to related parties, namely PPLS. But the response is too late and take a long time to occur …

The Automatic Monitoring System For Wpp, Spp, And Pln Based On The Internet Of Things (Iot) Using Sonoff Pow R2, Yosi Apriani, Muhammad Rama Bagaskara, Ian Mochamad Sofian, Wiwin A. Oktaviani, Muhammad Hurairoh

Elinvo (Electronics, Informatics, and Vocational Education)

The usefulness of monitoring systems in the electric power system supports the importance of people's work today. One of which is the monitoring system at the generator. The monitoring system for Wind Power Plant (WPP), Solar Power Plant (SPP), and electricity from State Electricity Company (PLN) use IoT (Internet of Things) in the form of Sonoff Pow R2. With the monitoring system on this tool, the parameter values for WPP, SPP, and PLN can be seen and monitored online via a smartphone. The purpose of this research is to design a monitoring system for WPP, SPP, and PLN based on …

Crowd Detection System Using Blimp Drones As An Effort To Mitigate The Spread Of Covid-19 Based On Internet Of Things, Mashoedah Mashoedah, Oktaf Agni Dhewa, Zulhakim Seftiyana Roviyan, Dheni Leo, Silvia Larasatul Masyitoh

Elinvo (Electronics, Informatics, and Vocational Education)

The application of health protocols is a regulation that is applied to prevent the spread of Covid-19. Public awareness of the implementation of health protocols is still lacking. This study aims to determine the performance of the detection system using the Blimp Drone as an effort to mitigate the spread of Covid-19 based on the Internet of Things. The method used in system development consists of literature review, needs analysis, design, manufacture, and testing. This system uses the Blimp Drone as a vehicle to carry out flight missions. Raspberry pi camera as a component for distance detection in …

Power Monitoring And Passenger Classification On Logistics Elevator, Isa Hafidz, Aldhitiansyah Putra, Billy Montolalu, Dimas Adiputra, Rifky Dwi Putranto, Rafly Daffaldi, Dinda Karisma Ulfa

Elinvo (Electronics, Informatics, and Vocational Education)

The elevator has an important role in assisting transportation and logistics activities in a building. However, if the elevator is not used wisely, then the power consumption will be inefficient. A policy of elevator usage is necessary to ensure the effectiveness of elevator power consumption. Therefore, in this study, elevator power consumption monitoring is proposed. The power consumption behavior can be learned so a suitable policy can be made accordingly. Two elevators in Telkom Campus Surabaya are monitored to understand the daily electrical energy usage. Internet of Things (IoT) based real-time power monitoring system is used to monitor the electrical …

The Evolution Of The Internet And Social Media: A Literature Review, Charles Alves De Castro, Isobel O'Reilly Dr, Aiden Carthy

Articles

This article reviews and analyses factors impacting the evolution of the internet, the web, and social media channels, charting historic trends and highlight recent technological developments. The review comprised a deep search using electronic journal databases. Articles were chosen according to specific criteria with a group of 34 papers and books selected for complete reading and deep analysis. The 34 elements were analysed and processed using NVIVO 12 Pro, enabling the creation of dimensions and categories, codes and nodes, identifying the most frequent words, cluster analysis of the terms, and creating a word cloud based on each word's frequency. The …

Stress Classification Using Deep Learning With 1d Convolutional Neural Networks, Abdulrazak Yahya Saleh, Lau Khai Xian

Knowledge Engineering and Data Science

Stress has been a major problem impacting people in various ways, and it gets serious every day. Identifying whether someone is suffering from stress is crucial before it becomes a severe illness. Artificial Intelligence (AI) interprets external data, learns from such data, and uses the learning to achieve specific goals and tasks. Deep Learning (DL) has created an impact in the field of Artificial Intelligence as it can perform tasks with high accuracy. Therefore, the primary purpose of this paper is to evaluate the performance of 1D Convolutional Neural Networks (1D CNNs) for stress classification. A Psychophysiological stress (PS) dataset …

Algorithm Hardware Codesign For High Performance Neuromorphic Computing, Haowen Fang

Dissertations - ALL

Driven by the massive application of Internet of Things (IoT), embedded system and Cyber Physical System (CPS) etc., there is an increasing demand to apply machine intelligence on these power limited scenarios. Though deep learning has achieved impressive performance on various realistic and practical tasks such as anomaly detection, pattern recognition, machine vision etc., the ever-increasing computational complexity and model size of Deep Neural Networks (DNN) make it challenging to deploy them onto aforementioned scenarios where computation, memory and energy resource are all limited. Early studies show that biological systems' energy efficiency can be orders of magnitude higher than that …

Comparative Analysis Of Rgb-Based Eye-Tracking For Large-Scale Human-Machine Applications, Brett Thaman, Trung Cao

Posters-at-the-Capitol

Gaze tracking has become an established technology that enables using an individual’s gaze as an input signal to support a variety of applications in the context of Human-Computer Interaction. Gaze tracking primarily relies on sensing devices such as infrared (IR) cameras. Nevertheless, in the recent years, several attempts have been realized at detecting gaze by acquiring and processing images acquired from standard RGB cameras. Nowadays, there are only a few publicly available open-source libraries and they have not been tested extensively. In this paper, we present the result of a comparative analysis that studied a commercial eye-tracking device using IR …

Assessing The Alignment Of Social Robots With Trustworthy Ai Design Guidelines: A Preliminary Research Study, Abdikadar Ali, Danielle Thaxton, Ankur Chattopadhyay

Posters-at-the-Capitol

The last couple of years have seen a strong movement supporting the need of having intelligent consumer products align with specific design guidelines for trustworthy artificial intelligence (AI). This global movement has led to multiple institutional recommendations for ethically aligned trustworthy design of the AI driven technologies, like consumer robots and autonomous vehicles. There has been prior research towards finding security and privacy related vulnerabilities within various types of social robots. However, none of these previous works has studied the implications of these vulnerabilities in terms of the robot design aligning with trustworthy AI. In an attempt to address this …

Trip Based Modeling Of Fuel Consumption In Modern Heavy-Duty Vehicles Using Artificial Intelligence, Sasanka Katreddi, Arvind Thiruvengadam

Faculty & Staff Scholarship

Heavy-duty trucks contribute approximately 20% of fuel consumption in the United States of America (USA). The fuel economy of heavy-duty vehicles (HDV) is affected by several real-world parameters like road parameters, driver behavior, weather conditions, and vehicle parameters, etc. Although modern vehicles comply with emissions regulations, potential malfunction of the engine, regular wear and tear, or other factors could affect vehicle performance. Predicting fuel consumption per trip based on dynamic on-road data can help the automotive industry to reduce the cost and time for on-road testing. Data modeling can easily help to diagnose the reason behind fuel consumption with a …

Enhanced Security Utilizing Side Channel Data Analysis, Michael Taylor

Computer Science and Engineering Theses and Dissertations

The physical state of a system is affected by the activities and processes in which it is tasked with carrying out. In the past there have been many instances where such physical changes have been exploited by bad actors in order to gain insight into the operational state and even the data being held on a system. This method of side channel exploitation is very often effective due to the relative difficulty of obfuscating activity on a physical level. However, in order to take advantage of side channel data streams one must have a detailed working knowledge of how a …

Robotic Olfactory-Based Navigation With Mobile Robots, Lingxiao Wang

Doctoral Dissertations and Master's Theses

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. It has been viewed as challenging due to the turbulent nature of airflows and the resulting odor plume characteristics. The key to correctly finding an odor source is designing an effective olfactory-based navigation algorithm, which guides the robot to detect emitted odor plumes as cues in finding the source. This dissertation proposes three kinds of olfactory-based navigation methods to improve search efficiency while maintaining a low computational cost, incorporating different machine learning and artificial intelligence methods.

A. …

Graph Based Management Of Temporal Data, Alex Fotso

Master of Science in Computer Science Theses

In recent decades, there has been a significant increase in the use of smart devices and sensors that led to high-volume temporal data generation. Temporal modeling and querying of this huge data have been essential for effective querying and retrieval. However, custom temporal models have the problem of generalizability, whereas the extended temporal models require users to adapt to new querying languages. In this thesis, we propose a method to improve the modeling and retrieval of temporal data using an existing graph database system (i.e., Neo4j) without extending with additional operators. Our work focuses on temporal data represented as intervals …

Development Of A Model For Control Of A Flexible Production Sewage System, Shalala Jafarova

Scientific-technical journal

This article discusses the development of a production module management model for one area of the technological process. New modeling methods are used for this purpose. Mathematical modeling and research is one of the key issues in the early stages of designing automated and automated systems operating in uncertain or fuzzy environments. Efficient modeling devices are used to solve these problems, taking into account the specific features of the process. The article builds the management model of the production module and obtains the results.

Tooth Position Determination By Automatic Cutting And Marking Of Dental Panoramic X-Ray Film In Medical Image Processing, Yen-Cheng Huang, Chiung-An Chen, Tsung-Yi Chen, He-Sheng Chou, Wei-Chi Lin, Tzu-Chien Li, Jia-Jun Yuan, Szu-Yin Lin, Chun-Wei Li, Shih-Lun Chen, Yi-Cheng Mao, Patricia Angela R. Abu, Wei-Yuan Chiang, Wen-Shen Lo

Department of Information Systems & Computer Science Faculty Publications

This paper presents a novel method for automatic segmentation of dental X-ray images into single tooth sections and for placing every segmented tooth onto a precise corresponding position table. Moreover, the proposed method automatically determines the tooth’s position in a panoramic X-ray film. The image-processing step incorporates a variety of image-enhancement techniques, including sharpening, histogram equalization, and flat-field correction. Moreover, image processing was implemented iteratively to achieve higher pixel value contrast between the teeth and cavity. The next image-enhancement step is aimed at detecting the teeth cavity and involves determining the segment and points separating the upper and lower jaw, …

Defining And Detecting Toxicity On Social Media: Context And Knowledge Are Key, Amit Sheth, Valerie Shalin, Ugur Kursuncu

Publications

As the role of online platforms has become increasingly prominent for communication, toxic behaviors, such as cyberbullying and harassment, have been rampant in the last decade. On the other hand, online toxicity is multi-dimensional and sensitive in nature, which makes its detection challenging. As the impact of exposure to online toxicity can lead to serious implications for individuals and communities, reliable models and algorithms are required for detecting and understanding such communications. In this paper We define toxicity to provide a foundation drawing social theories. Then, we provide an approach that identifies multiple dimensions of toxicity and incorporates explicit knowledge …

A Systematic Review On Blockchain In Education: Opportunities And Challenges, Navin Duwadi, Navin Duwadi

School of Information Systems and Technology Publications

This study focuses on bloackchain as an emerging technology regarding its use to restructure the systems and advance education upon quality outcomes. What are the benefits of integrating blockchain in education concerning system reformation and advancement in developing better educational process for all encompassing learning outcomes? With the recent developments of blockchain applications across multiple domains, the education industry seems to be benefited from this technology in considerable degree. Transcripts and certificates play a vital role in individual’s life so it needs to be stored in tamper-proof and long term available ledger. In pursuant to addressing afore stated question, this …

A Systematic Review On Blockchain In Education: Opportunities And Challenges, Navin Duwadi

Walden Faculty and Staff Publications

This study focuses on bloackchain as an emerging technology regarding its use to restructure the systems and advance education upon quality outcomes. What are the benefits of integrating blockchain in education concerning system reformation and advancement in developing better educational process for all encompassing learning outcomes? With the recent developments of blockchain applications across multiple domains, the education industry seems to be benefited from this technology in considerable degree. Transcripts and certificates play a vital role in individual’s life so it needs to be stored in tamper-proof and long term available ledger. In pursuant to addressing afore stated question, this …

The Application Of Design Thinking On Evaluating A User Self-Service Data Analytics/Science Platform, Aheeka Pattnaik

Dissertations and Theses

This thesis is aimed at utilising design thinking and the first half of the double diamond framework to i) set-up a research and select the appropriate participants, ii) gather requirements and define user personas from those eligible participants, and then iii) define the framework for evaluating a user self-service data analytics/science platform. Derived from the author’s own experiences, both as a Business Analyst (BA) and Citizen Data Scientist, with no-, low-, and code-based data analytics and science platforms are being implemented for enabling user self-service analytics – for users who are completely new to the space of data analysis and …

Detecting Malware In Memory With Memory Object Relationships, Demarcus M. Thomas Sr.

Theses and Dissertations

Malware is a growing concern that not only affects large businesses but the basic consumer as well. As a result, there is a need to develop tools that can identify the malicious activities of malware authors. A useful technique to achieve this is memory forensics. Memory forensics is the study of volatile data and its structures in Random Access Memory (RAM). It can be utilized to pinpoint what actions have occurred on a computer system.

This dissertation utilizes memory forensics to extract relationships between objects and supervised machine learning as a novel method for identifying malicious processes in a system …