Computer Engineering Commons^™

Context-Aware Event Forecasting Via Graph Disentanglement, Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Event forecasting has been a demanding and challenging task throughout the entire human history. It plays a pivotal role in crisis alarming and disaster prevention in various aspects of the whole society. The task of event forecasting aims to model the relational and temporal patterns based on historical events and makes forecasting to what will happen in the future. Most existing studies on event forecasting formulate it as a problem of link prediction on temporal event graphs. However, such pure structured formulation suffers from two main limitations: 1) most events fall into general and high-level types in the event ontology, …

Towards Intelligent Runtime Framework For Distributed Heterogeneous Systems, Polykarpos Thomadakis

Computer Science Theses & Dissertations

Scientific applications strive for increased memory and computing performance, requiring massive amounts of data and time to produce results. Applications utilize large-scale, parallel computing platforms with advanced architectures to accommodate their needs. However, developing performance-portable applications for modern, heterogeneous platforms requires lots of effort and expertise in both the application and systems domains. This is more relevant for unstructured applications whose workflow is not statically predictable due to their heavily data-dependent nature. One possible solution for this problem is the introduction of an intelligent Domain-Specific Language (iDSL) that transparently helps to maintain correctness, hides the idiosyncrasies of lowlevel hardware, and …

Cyberinet: Integrated Semi-Modular Sensors For The Computer-Augmented Clarinet, Matthew Bardin

LSU Doctoral Dissertations

The Cyberinet is a new Augmented instrument designed to easily and intuitively provide a method of computer-enhanced performance to the Clarinetist to allow for greater control and expressiveness in a performance. A performer utilizing the Cyberinet is able to seamlessly switch between a traditional performance setting and an augmented one. Towards this, the Cyberinet is a hardware replacement for a portion of a Clarinet containing a variety of sensors embedded within the unit. These sensors collect various real time data motion data of the performer and air fow within the instrument. Additional sensors can be connected to the Cyberinet to …

Accurate Orientation Control Of Tendon Driven Continuum Robots That Exhibit Elasticity, Manu Srivastava

All Dissertations

This dissertation makes new contributions to the modeling and implementation of Tendon Driven Continuum Robots (TDCRs). Specifically, motivated by 3D printing of concrete using a continuum hose robot in construction applications, we focus on TDCRs featuring compliance in the robot backbone and actuating tendons, e.g. surgical robots/endoscopes/catheters with tendon actuation. We expand previous mechanics-based models to show how and why such compliance significantly restricts performance when traditional kinematics-based planning and control techniques are applied.

The main contribution of this work is a new Elasticity Compensation(EC) model that explains why the ad hoc approach of preloading/pretensioning the tendons compensates for compliance …

The Heterogeneous Vehicle Routing Problem With Multiple Time Windows For The E-Waste Collection Problem, Aldy Gunawan, Minh P.K Nguyen, Vincent F. Yu, Dang Viet Anh Nguyen

Research Collection School Of Computing and Information Systems

Waste from electrical and electronic equipment (WEEE) or e-waste describes end-of-life electronic products that are discarded. Due to their toxic and negative impacts to humans' health, many publications have been proposed to handle, however, studies related to e-waste collection and transportation to waste disposal sites are not widely studied so far. This study proposes a mixed integer linear programming (MILP) model to solve the e-waste collecting problem by formulating it as the heterogeneous vehicle routing problem with multiple time windows (HVRPMTW). The model is validated with newly developed benchmark instances that are solved by commercial software, CPLEX. The model is …

Deep Learning For Multi-Structured Javanese Gamelan Note Generator, Arik Kurniawati, Eko Mulyanto Yuniarno, Yoyon Kusnendar Suprapto

Knowledge Engineering and Data Science

Javanese gamelan, a traditional Indonesian musical style, has several song structures called gendhing. Gendhing (songs) are written in conventional notation and require gamelan musicians to recognize patterns in the structure of each song. Usually, previous research on gendhing focuses on artistic and ethnomusicological perspectives, but this study is to explore the correlation between gendhing as traditional music in Indonesia and deep learning technology that replaces the task of gamelan composers. This research proposes CNN-LSTM to generate notation of ricikan struktural instruments as an accompaniment to Javanese gamelan music compositions based on balungan notation, rhythm, song structure, and gatra …

Finchain: Adaptation Of Blockchain Technology In Finance And Business - An Ethical Analysis Of Applications, Challenges, Issues And Solutions, Naresh Kshetri, Keith Miller, Gaurango Banerjee, Bikesh Raj Upreti

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

Blockchain Technology is a distributed database technology that has emerged as a ground-breaking technology with several possible solutions to critical applications, say from supply chain management, agribusiness, marketing to healthcare industry including internet of medical things. Although it started as a digital coin (popularly known as bitcoin), it is slowly influencing business, marketing policy and society. We have presented an in-depth study and ethical analysis of how blockchain is applied over the economic and financial sector including banks, credit unions and other retail giants. During our research, we have also investigated how blockchain technology can affect financial institutions around the …

Designing Intelligent Energy Efficient Scheduling Algorithm To Support Massive Iot Communication In Lora Networks, Jui Mhatre

Master of Science in Computer Science Theses

We are about to enter a new world with sixth sense ability – “Network as a sensor -6G”. The driving force behind digital sensing abilities is IoT. Due to their capacity to work in high frequency, 6G devices have voracious energy demand. Hence there is a growing need to work on green solutions to support the underlying 6G network by making it more energy efficient. Low cost, low energy, and long-range communication capability make LoRa the most adopted and promising network for IoT devices. Since LoRaWAN uses ALOHA for multi-access of channels, collision management is an important task. Moreover, in …

Using Machine Learning To Assist Auditory Processing Evaluation, Hasitha Wimalarathna, Sangamanatha Veeranna, Minh Vu Duong, Chris Allan Prof, Sumit K. Agrawal, Prudence Allen, Jagath Samarabandu, Hanif M. Ladak

Electrical and Computer Engineering Publications

Introduction: Approximately 0.2–5% of school-age children complain of listening difficulties in the absence of hearing loss. These children are often referred to an audiologist for an auditory processing disorder (APD) assessment. Adequate experience and training is necessary to arrive at an accurate diagnosis due to the heterogeneity of the disorder.

Objectives: The main goal of the study was to determine if machine learning (ML) can be used to analyze data from the APD clinical test battery to accurately categorize children with suspected APD into clinical sub-groups, similar to expert labels.

Methods: The study retrospectively collected data from 134 children referred …

Multi-Scale Attention Networks For Pavement Defect Detection, Junde Chen, Yuxin Wen, Yaser Ahangari Nanehkaran, Defu Zhang, Adan Zeb

Engineering Faculty Articles and Research

Pavement defects such as cracks, net cracks, and pit slots can cause potential traffic safety problems. The timely detection and identification play a key role in reducing the harm of various pavement defects. Particularly, the recent development in deep learning-based CNNs has shown competitive performance in image detection and classification. To detect pavement defects automatically and improve effects, a multi-scale mobile attention-based network, which we termed MANet, is proposed to perform the detection of pavement defects. The architecture of the encoder-decoder is used in MANet, where the encoder adopts the MobileNet as the backbone network to extract pavement defect features. …

Practical Approaches And Guidance To Small Business Organization Cyber Risk And Threat Assessments, Stanley Mierzwa, Aneta Klepacka

Center for Cybersecurity

Cyber-attacks and breaches can occur in any organization type, and the areas of small businesses are not exempt from this nefarious activity. This research note and rapid review provide various cybersecurity tools, guidelines, and frameworks that a small business can consider when embarking on the action to assess its cybersecurity hygiene and defensive stance. The content was pulled together in response to the need for an easy-to-digest approach that a small business utilizes to gain valuable confidence to undertake a self-assessment or third-party review of an organization’s cybersecurity plans. Regarding cybersecurity concerns, doing nothing is not an option, and taking …

Ki-Cook: Clustering Multimodal Cooking Representations Through Knowledge-Infused Learning, Revathy Venkataramanan, Swati Padhee, Saini Rohan Rao, Ronak Kaoshik, Anirudh Sundara Rajan, Amit Sheth

Publications

Cross-modal recipe retrieval has gained prominence due to its ability to retrieve a text representation given an image representation and vice versa. Clustering these recipe representations based on similarity is essential to retrieve relevant information about unknown food images. Existing studies cluster similar recipe representations in the latent space based on class names. Due to inter-class similarity and intraclass variation, associating a recipe with a class name does not provide sufficient knowledge about recipes to determine similarity. However, recipe title, ingredients, and cooking actions provide detailed knowledge about recipes and are a better determinant of similar recipes. In this study, …

A Unified Switched Nonlinear Dynamic Model Of An Electric Vehicle For Performance Evaluation, Dibyendu Khan, Kuntal Mandal, Anjan Kumar Ray, Abdelali El Aroudi

Department of Electrical and Computer Engineering: Faculty Publications

The advanced modeling and estimation of overall system dynamics play a vital role in electric vehicles (EVs), as the selection of components in the powertrain and prediction of performance are the key market qualifiers. The state-space averaged model and small-signal transfer function model are useful for assessing long-term behavior in system-level analysis and for designing the controller parameters, respectively. Both models take less computation time but ignore the high-frequency switching dynamics. Therefore, these two models could be impractical for the development and testing of EV prototypes. On the other hand, the multi-domain model in available simulation tools gives in-depth information …

An Ai-Based Intervention For Improving Undergraduate Stem Learning, Mohammad Rashedul Hasan, Bilal Khan

Department of Electrical and Computer Engineering: Faculty Publications

We present results from a small-scale randomized controlled trial that evaluates the impact of just-in-time interventions on the academic outcomes of N = 65 undergraduate students in a STEM course. Intervention messaging content was based on machine learning forecasting models of data collected from 537 students in the same course over the preceding 3 years. Trial results show that the intervention produced a statistically significant increase in the proportion of students that achieved a passing grade. The outcomes point to the potential and promise of just-in-time interventions for STEM learning and the need for larger fully-powered randomized controlled trials.

An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif

Future Computing and Informatics Journal

This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …

Risk Assessment Approaches In Banking Sector –A Survey, Mona Sharaf, Shimaa Mohamed Ouf, Amira M. Idrees Ami

Future Computing and Informatics Journal

Prediction analysis is a method that makes predictions based on the data currently available. Bank loans come with a lot of risks to both the bank and the borrowers. One of the most exciting and important areas of research is data mining, which aims to extract information from vast amounts of accumulated data sets. The loan process is one of the key processes for the banking industry, and this paper examines various prior studies that used data mining techniques to extract all served entities and attributes necessary for analytical purposes, categorize these attributes, and forecast the future of their business …

News’ Credibility Detection On Social Media Using Machine Learning Algorithms, Farah Yasser, Sayed Abdelmawgoud, Amira M. Idrees Ami

Future Computing and Informatics Journal

Social media is essential in many aspects of our lives. Social media allows us to find news for free. anyone can access it easily at any time. However, social media may also facilitate the rapid spread of misleading news. As a result, there is a probability that low-quality news, including incorrect and fake information, will spread over social media. As well as detecting news credibility on social media becomes essential because fake news can affect society negatively, and the spread of false news has a considerable impact on personal reputation and public trust. In this research, we conducted a model …

Visual Question Answering: A Survey, Gehad Assem El-Naggar

Future Computing and Informatics Journal

Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …

Human-Machine Communication: Complete Volume. Volume 6

Human-Machine Communication

This is the complete volume of HMC Volume 6.

Boundary Regulation Processes And Privacy Concerns With (Non-)Use Of Voice-Based Assistants, Jessica Vitak, Priya C. Kumar, Yuting Liao, Michael Zimmer

Human-Machine Communication

An exemplar of human-machine communication, voice-based assistants (VBAs) embedded in smartphones and smart speakers simplify everyday tasks while collecting significant data about users and their environment. In recent years, devices using VBAs have continued to add new features and collect more data—in potentially invasive ways. Using Communication Privacy Management theory as a guiding framework, we analyze data from 11 focus groups with 65 US adult VBA users and nonusers. Findings highlight differences in attitudes and concerns toward VBAs broadly and provide insights into how attitudes are influenced by device features. We conclude with considerations for how to address boundary regulation …