Digital Commons Network^™

Improving Writing Quality Of Capstone Reports, Fred Berry, Margaret Phillips, James Condron, Phillip Sanger

Libraries Faculty and Staff Scholarship and Research

Abstract-Contributions: The main contribution is to share a series of practical methods that improve the writing quality of capstone reports. Background: The ability to write well is critical to the success of an engineering technology graduate. However, the evidence points to the fact that industries are disappointed with the quality of writing skills graduates demonstrate. Intended Outcomes: A faculty review of capstone reports showed little improvement in writing quality from the first course to the second in a two-semester capstone sequence. Therefore, the instructors explored what actions were needed to improve the writing quality of the capstone reports. Application Design: …

An Adaptive Model To Support Biofeedback In Ami Environments: A Case Study In Breathing Training For Autism, Arturo Morales, Franceli L. Cibrian, Luis A. Castro, Monica Tentori

Engineering Faculty Articles and Research

Biofeedback systems have shown promising clinical results in regulating the autonomic nervous system (ANS) of individuals. However, they typically offer a “one-size-fits-all” solution in which the personalization of the stimuli to the needs and capabilities of its users has been largely neglected. Personalization is paramount in vulnerable populations like children with autism given their sensory diversity. Ambient intelligence (AmI) environments enable creating effective adaptive mechanisms in biofeedback to adjust the stimuli to each user’s performance. Yet, biofeedback models with adaptive mechanisms are scarce in the AmI literature. In this paper, we propose an adaptive model to support biofeedback that takes …

Transdisciplinary Ai Observatory—Retrospective Analyses And Future-Oriented Contradistinctions, Nadisha Marie Aliman, Leon Kester, Roman Yampolskiy

Faculty and Staff Scholarship

In the last years, artificial intelligence (AI) safety gained international recognition in the light of heterogeneous safety-critical and ethical issues that risk overshadowing the broad beneficial impacts of AI. In this context, the implementation of AI observatory endeavors represents one key research direction. This paper motivates the need for an inherently transdisciplinary AI observatory approach integrating diverse retrospective and counterfactual views. We delineate aims and limitations while providing hands-on-advice utilizing concrete practical examples. Distinguishing between unintentionally and intentionally triggered AI risks with diverse socio-psycho-technological impacts, we exemplify a retrospective descriptive analysis followed by a retrospective counterfactual risk analysis. Building on …

Optimization Of A Customized Leadership Development Program Upskilling English Language Fluency In Brazil Aviation Leaders, Robin A. Roberts

Publications

Objective: The present study explored how a customized leadership development program (LDP) with coursework taught in English to non-native English speakers could optimize English language fluency in Brazil airline leaders.

Background: Currently, problems exist with a myriad of native language accents and phraseology interfering with cognitive reflexes especially for aircrews and air traffic controllers to safely do their work. Executives from four Brazilian airlines proactively implemented a 14-month LDP focused on English language fluency and leadership enhancements collectively for leaders within their firms.

Method: Blended learning as proposed by the International Civil Aviation Organization provided the experiential …

A Literature Survey And Bibliometric Analysis Of Application Of Artificial Intelligence Techniques On Wireless Mesh Networks, Smita R. Mahajan Mrs., Harikrishnan R Dr., Ketan Kotecha Dr.

Library Philosophy and Practice (e-journal)

Recent years have seen a surge in the use of technology for executing transactions in both online and offline modes. Various industries like banking, e-commerce, and private organizations use networks for the exchange of confidential information and resources. Network security is thus of utmost importance, with the expectation of effective and efficient analysis of the network traffic. Wireless Mesh Networks are effective in communicating information over a vast span with minimal costs. A network is evaluated based on its security, accessibility, and extent of interoperability. Artificial Intelligence techniques like machine learning and deep learning have found widespread use to solve …

Examining The Modelling Capabilities Of Defeasible Argumentation And Non-Monotonic Fuzzy Reasoning, Luca Longo, Lucas Rizzo, Pierpaolo Dondio

Articles

Knowledge-representation and reasoning methods have been extensively researched within Artificial Intelligence. Among these, argumentation has emerged as an ideal paradigm for inference under uncertainty with conflicting knowledge. Its value has been predominantly demonstrated via analyses of the topological structure of graphs of arguments and its formal properties. However, limited research exists on the examination and comparison of its inferential capacity in real-world modelling tasks and against other knowledge-representation and non-monotonic reasoning methods. This study is focused on a novel comparison between defeasible argumentation and non-monotonic fuzzy reasoning when applied to the representation of the ill-defined construct of human mental workload …

Investigating The Use Of An Adaptive Neuro-Fuzzy Inferencesystem In Software Development Effort Estimation, Zainab Rustum Mohsin

Iraqi Journal for Computer Science and Mathematics

Modeling software development effort estimation models has been a hot research topic over the lastthree decades. Numerous models were proposed in these decades to predict the effort. The key challenges for futuresoftware development is providing accurate software estimation. Failure to acknowledge the accuracy of effortestimation can cause inaccurate estimation, customer disappointment, and poor software development or projectfailure. This research presents a novel computational technique, named adaptive neuro-fuzzy inference system(ANFIS), for the modeling of software effort estimation. It was developed utilizing the Constructive Cost Model(COCOMO) dataset. The data were randomly divided into two sets: 83% for training and 17% for testing. …

Exploiting Bert And Roberta To Improve Performance For Aspect Based Sentiment Analysis, Gagan Reddy Narayanaswamy

Dissertations

Sentiment Analysis also known as opinion mining is a type of text research that analyses people’s opinions expressed in written language. Sentiment analysis brings together various research areas such as Natural Language Processing (NLP), Data Mining, and Text Mining, and is fast becoming of major importance to companies and organizations as it is started to incorporate online commerce data for analysis. Often the data on which sentiment analysis is performed will be reviews. The data can range from reviews of a small product to a big multinational corporation. The goal of performing sentiment analysis is to extract information from those …

Finetuning Bert And Xlnet For Sentiment Analysis Of Stock Market Tweets Using Mixout And Dropout Regularization, Shubham Jangir

Dissertations

Sentiment analysis is also known as Opinion mining or emotional mining which aims to identify the way in which sentiments are expressed in text and written data. Sentiment analysis combines different study areas such as Natural Language Processing (NLP), Data Mining, and Text Mining, and is quickly becoming a key concern for businesses and organizations, especially as online commerce data is being used for analysis. Twitter is also becoming a popular microblogging and social networking platform today for information among people as they contribute their opinions, thoughts, and attitudes on social media platforms over the years. Because of the large …

Medical Surge Capability: Performance Modeling Of Hospital Emergency Departments, Egbe-Etu Emmanuel Etu

Wayne State University Dissertations

Hospitals are faced with significant challenges during and after natural or human-caused disasters. Surge planning is a critical component of every healthcare facility’s emergency plan and response system. The process of managing and allocating scarce resources by tackling the vulnerability inherent to patients means that defining improvement priorities is one of the main challenges healthcare systems face when responding to a medical surge event (e.g., COVID-19). The consequences of these challenges include increased patient mortality, ambulance diversion, long wait times, and unavailability of beds. Previous efforts in hospital operations management have successfully applied operations research techniques in analyzing and optimizing …

Complex Interactions Between Multiple Goal Operations In Agent Goal Management, Sravya Kondrakunta

Browse all Theses and Dissertations

A significant issue in cognitive systems research is to make an agent formulate and manage its own goals. Some cognitive scientists have implemented several goal operations to support this issue, but no one has implemented more than a couple of goal operations within a single agent. One of the reasons for this limitation is the lack of knowledge about how various goals operations interact with one another. This thesis addresses this knowledge gap by implementing multiple-goal operations, including goal formulation, goal change, goal selection, and designing an algorithm to manage any positive or negative interaction between them. These are integrated …

Should Acoustic Simulation Technology Be Utilised In Architectural Practice? Does It Have The Potential For Bim Integration?, Bim Tudublin, Keith Harvey

Capstone Reports

The research presented in this paper, firstly, aims to convey the importance of our acoustic environment through focusing on the effects of undesirable acoustic conditions on cognitive abilities in spaces where cognitive performance is of the utmost concern, our learning environments. Secondly, it aims to investigate current state-of-the-art acoustic simulation methods, available platforms, and their levels of interoperability with architectural BIM authoring software. Structured interviews were carried out with 7 Irish architects and architectural technologists to determine if a disconnection between architectural design and acoustic performance exists and to identify the advantages and disadvantages of current workflows for acoustic performance …

Complex Interactions Between Multiple Goal Operations In Agent Goal Management, Sravya Kondrakunta

Browse all Theses and Dissertations

A significant issue in cognitive systems research is to make an agent formulate and manage its own goals. Some cognitive scientists have implemented several goal operations to support this issue, but no one has implemented more than a couple of goal operations within a single agent. One of the reasons for this limitation is the lack of knowledge about how various goals operations interact with one another. This thesis addresses this knowledge gap by implementing multiple-goal operations, including goal formulation, goal change, goal selection, and designing an algorithm to manage any positive or negative interaction between them. These are integrated …

A Method Of Identifying Allographs In Undeciphered Scripts And Its Application To The Indus Valley Script, Shruti Daggumati, Peter Revesz

Department of Mechanical and Materials Engineering: Faculty Publications

This work describes a general method of testing for redundancies in the sign lists of ancient scripts by data mining the positions of the signs within the inscriptions. The redundant signs are allographs of the same grapheme. The method is applied to the undeciphered Indus Valley Script, which stands out from other ancient scripts by having a large proposed sign list that contains dozens of asymmetric signs that have mirrored pairs. By a statistical analysis of mirrored asymmetric signs, this paper shows that the Indus Valley Script was multi-directional and the mirroring of signs often denotes only the direction of …

Scalable Approaches For Auditing The Completeness Of Biomedical Ontologies, Fengbo Zheng

Theses and Dissertations--Computer Science

An ontology provides a formalized representation of knowledge within a domain. In biomedicine, ontologies have been widely used in modern biomedical applications to enable semantic interoperability and facilitate data exchange. Given the important roles that biomedical ontologies play, quality issues such as incompleteness, if not addressed, can affect the quality of downstream ontology-driven applications. However, biomedical ontologies often have large sizes and complex structures. Thus, it is infeasible to uncover potential quality issues through manual effort. In this dissertation, we introduce automated and scalable approaches for auditing the completeness of biomedical ontologies. We mainly focus on two incompleteness issues -- …

Integrating The Humanities With Engineering Through A Global Case Study Course, Kirsten A. Davis, Siddhant S. Joshi, Lori Czerwionka, Francisco Montalvo, Gabriel O. Rios-Rojas, Joe Tort, Jennifer Marston William, E. Nauman

Journal of International Engineering Education

As the world becomes more connected and globalized, the problems that engineers are called upon to solve are increasingly complex and interdependent. Unfortunately, engineering coursework has traditionally focused on abstract and closed-ended problem solving, offering few opportunities for students to develop these skills. In this practice paper, we argue for the importance of integrating the humanities and engineering to understand the multiple and intersecting layers of context in an engineering project. We then describe the Humanities-Informed Engineering Projects course, which we developed to help students acquire this perspective. The course was piloted in Spring 2021 in response to the obstacles …

Spectral And Latent Representation Distortion For Tts Evaluation, Thananchai Kongthaworn

Chulalongkorn University Theses and Dissertations (Chula ETD)

One of the main problems in the development of text-to-speech (TTS) systems is its reliance on subjective measures, typically the Mean Opinion Score (MOS). MOS requires a large number of people to reliably rate each utterance, making the development process slow and expensive. Recent research on speech quality assessment tends to focus on training models to estimate MOS, which requires a large number of training data, something that might not be available in low-resource languages. We propose an objective assessment metric based on the DTW distance using the spectrogram and the high-level features from an Automatic Speech Recognition (ASR) model …

Machine Learning For Measuring And Analyzing Online Social Communications, Chris Bronk, Amaury Lendasse, Peggy Lindner, Dan S. Wallach, Barbara Hammer

Engineering Management and Systems Engineering Faculty Research & Creative Works

In This Paper, We Propose a Framework for Application of a Novel Machine Learning-Based System for Analyzing Online Social Communications. as an Example, We Are Targeting Anti-Semitic Graphical Memes Posted to Social Media. We Presented Very Promising Preliminary Results on a Facebook Dataset that Consists of a Total of 10000 Labeled Memes. We Can Conclude that Machine Learning Will Soon Be Able to Successfully Analyze and Monitor Complex Social Communications.

การสร้างความต้องการเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันของซอฟต์แวร์จากการจำแนกบทวิจารณ์ของผู้ใช้งานโมไบล์แอปพลิเคชัน, ธนัชชา พันธ์ธรรม

Chulalongkorn University Theses and Dissertations (Chula ETD)

บทวิจารณ์ของผู้ใช้งานเป็นแหล่งข้อมูลที่สำคัญสำหรับนักพัฒนาโมไบล์แอปพลิเคชัน เพื่อใช้ในการปรับปรุงและวิวัฒนาการแอปพลิเคชันหลังจากที่ได้ปล่อยให้ใช้งานไปแล้ว เนื่องจากข้อมูลบทวิจารณ์ของผู้ใช้งานมีจำนวนมากจึงเป็นเรื่องยุ่งยากสำหรับทีมนักพัฒนาโมไบล์แอปพลิเคชันที่จะระบุว่าบทวิจารณ์ของผู้ใช้งานใดประกอบไปด้วยข้อมูลที่เป็นประโยชน์ต่อการปรับปรุงและวิวัฒนาการโมไบล์แอปพลิเคชันเพิ่มเติม วิทยานิพนธ์นี้นำเสนอความพยายามที่จะอำนวยความสะดวกให้แก่ทีมนักพัฒนาในขั้นต้นด้วยการสร้างความต้องการเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันโดยอัตโนมัติจากข้อมูลบทวิจารณ์ของผู้ใช้งานโมไบล์แอปพลิเคชันบนแอปสโตร์และเพลย์สโตร์ แนวทางที่นำเสนอประกอบด้วยสามขั้นตอน เริ่มจากการใช้อัลกอริทึมการจำแนกข้อความเพื่อจำแนกบทวิจารณ์ของผู้ใช้งานออกเป็นบทวิจารณ์ของผู้ใช้งานเชิงฟังก์ชันหรือที่ไม่ใช่เชิงฟังก์ชัน ขั้นตอนที่สองบทวิจารณ์ของผู้ใช้งานที่ไม่ซ้ำกันจะถูกระบุโดยใช้เทคนิคการจัดกลุ่มและการวิเคราะห์ความคล้ายคลึงกันของข้อความ ในขั้นตอนสุดท้ายข้อมูลที่มีความสำคัญจะถูกสกัดจากบทวิจารณ์ของผู้ใช้งานเพื่อใช้สร้างความต้องการเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันโดยใช้แบบรูปข้อมูลบทวิจารณ์ของผู้ใช้งานและแม่แบบความต้องการ ในส่วนของการประเมินผล ความต้องการที่ถูกสร้างขึ้นจากแนวทางที่นำเสนอได้รับคะแนนต่ำถึงสูงแตกต่างกันไปในแง่ของความสามารถในการอ่านได้ง่าย ความไม่กำกวม ความสมบูรณ์ และความสมเหตุสมผล ซึ่งแนวทางที่วิทยานิพนธ์นำเสนอนี้สามารถช่วยทีมนักพัฒนาระบุถึงความต้องการการเปลี่ยนแปลงทั้งในเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันจากเสียงสะท้อนโดยตรงของผู้ใช้งานซึ่งควรได้รับการพิจารณาเพื่อใช้ในการปรับปรุงและวิวัฒนาการโมไบล์แอปพลิเคชันต่อไป

Speed-Sensorless Predictive Torque Controlled Induction Motor Drive Withfeed-Forward Control Of Load Torque For Electric Vehicle Applications, Emrah Zerdali̇, Ridvan Demi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Nowadays, the global trend is towards reducing CO2 emissions and one solution is to replace internal combustion vehicles with electric vehicles. To this end, electric drive system, the most crucial part of an electric vehicle, has gained importance and has become a major research field. The induction motor (IM) is one of the best candidates for electric vehicle applications due to its advantages such as having simple and robust design, its low cost maintenance requirements and the ability to operate in harsh environments. However, it has a highly nonlinear model with timevarying electrical and mechanical parameters making them difficult to …

A Study Of Factors That Influence Symbol Selection On Augmentative And Alternative Communication Devices For Individuals With Autism Spectrum Disorder, William Todd Dauterman

CCAC Theses and Dissertations

According to the American Academy of Pediatrics (AAP), 1 in 59 children are diagnosed with Autism Spectrum Disorder (ASD) each year. Given the complexity of ASD and how it is manifested in individuals, the execution of proper interventions is difficult. One major area of concern is how individuals with ASD who have limited communication skills are taught to communicate using Augmentative and Alternative Communication devices (AAC). AACs are portable electronic devices that facilitate communication by using audibles, signs, gestures, and picture symbols. Traditionally, Speech-Language Pathologists (SLPs) are the primary facilitators of AAC devices and help establish the language individuals with …

Mapping Of Auditory Cortical Functions Using Electrocorticography, James Robert Swift

Legacy Theses & Dissertations (2009 - 2024)

Communication is a dynamic process through which we translate our inner thoughts in such a way that they can be shared with another person. This complex neurological phenomenon is a key predictor of our productivity and health. When our ability to communicate is compromised, our quality of life suffers. Although numerous methods to investigate the neuroscientific underpinnings of human language exist, our understanding of this process remains incomplete. Improving our understanding of where, when, and how auditory cortical activity occurs can enhance diagnostic techniques and improve treatment methods for neurological conditions that can impact auditory processing, such as epilepsy, or …

Detecting And Correcting Automatic Speech Recognition Errors With A New Model, Recep Si̇nan Arslan, Necaatti̇n Barişçi, Nursal Arici, Sabri̇ Koçer

Turkish Journal of Electrical Engineering and Computer Sciences

The purpose of automatic speech recognition (ASR) systems is to recognize speech signals obtained from people and convert them into text so that they can be processed by a computer. Although many ASR applications are versatile and widely used in the real world, they still generate relatively inaccurate results. They tend to generate spelling errors in recognized words, especially in noisy environments, in situations where the vocabulary size is increased, and at times when the input speech is of poor quality. The permanent presence of errors in ASR systems has led to the need to find alternative methods for automatic …

Attention-Based End-To-End Cnn Framework For Content-Based X-Ray Imageretrieval, Şaban Öztürk, Adi Alhudhaif, Kemal Polat

Turkish Journal of Electrical Engineering and Computer Sciences

The widespread use of medical imaging devices allows deep analysis of diseases. However, the task of examining medical images increases the burden of specialist doctors. Computer-assisted systems provide an effective management tool that enables these images to be analyzed automatically. Although these tools are used for various purposes, today, they are moving towards retrieval systems to access increasing data quickly. In hospitals, the need for content-based image retrieval systems is seriously evident in order to store all images effectively and access them quickly when necessary. In this study, an attention-based end-to-end convolutional neural network (CNN)framework that can provide effective access …

A Novel Fibonacci Hash Method For Protein Family Identification By Usingrecurrent Neural Networks, Talha Burak Alakuş, İbrahi̇m Türkoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Identification and classification of protein families are one of the most significant problem in bioinformatics and protein studies. It is essential to specify the family of a protein since proteins are highly used in smart drug therapies, protein functions, and, in some cases, phylogenetic trees. Some sequencing techniques provide researchers to identify the biological similarities of protein families and functions. Yet, determining these families with sequencing applications requires huge amount of time. Thus, a computer and artificial intelligence based classification system is needed to save time and avoid complexity in protein classification process. In order to designate the protein families …

Neural Relation Extraction: A Review, Mehmet Aydar, Özge Bozal, Furkan Özbay

Turkish Journal of Electrical Engineering and Computer Sciences

Neural relation extraction discovers semantic relations between entities from unstructured text using deeplearning methods. In this study, we make a clear categorization of the existing relation extraction methods in termsof data expressiveness and data supervision, and present a comprehensive and comparative review. We describe theevaluation methodologies and the datasets used for model assessment. We explicitly state the common challenges inrelation extraction task and point out the potential of the pretrained models to solve them. Accordingly, we investigateadditional research directions and improvement ideas in this field.

Turkish Sign Language Recognition Based On Multistream Data Fusion, Cemi̇l Gündüz, Hüseyi̇n Polat

Turkish Journal of Electrical Engineering and Computer Sciences

Sign languages are nonverbal, visual languages that hearing- or speech-impaired people use for communication.Aside from hands, other communication channels such as body posture and facial expressions are also valuable insign languages. As a result of the fact that the gestures in sign languages vary across countries, the significance ofcommunication channels in each sign language also differs. In this study, representing the communication channels usedin Turkish sign language, a total of 8 different data streams-4 RGB, 3 pose, 1 optical flow-were analyzed. Inception3D was used for RGB and optical flow; and LSTM-RNN was used for pose data streams. Experiments were conductedby …

Mcnair Scholars Research Journal 2021, Calyha Brown, Caroline Carter, Kalvry Cooper, Perla Rodriguez, Huu Trung Tran, Jose A. Cortes, Orion Wynne, Johnathan Alexander Andres, Joshua Perez, Allison Fenske, Chasidah Fried, Giles Fitzwilliams

McNair Scholars Research Journal-Archive

No abstract provided.

Key Success Factors Identification For Logistics Outsourcing In Myanmar, Pyae Sone Htoon

Chulalongkorn University Theses and Dissertations (Chula ETD)

The purpose of this paper is to identify the key success factors that have a profound effect on the service quality of outsourced logistics functions in the import/export sector of trade business in Myanmar and rank them accordingly to their importance when outsourcing logistics functions. The paper states the critical elements required for logistics service providers to compete for high customer satisfaction in Yangon, Myanmar. Fuzzy TOPSIS methodology with triangular fuzzy numbers is used to identify the key success factors and rank them in order of their relative closeness to the ideal solution. The findings suggest that soft factors such …

Analysis Of Sign Language Facial Expressions And Deaf Students' Retention Using Machine Learning And Agent-Based Modeling, Marie Alaghband

Electronic Theses and Dissertations, 2020-2023

There are currently about 466 million people worldwide who have a hearing disability, and that number is expected to increase to 900 million by 2050. About 15% of adult Americans have hearing disabilities and about every three in 1,000 U.S. children are born with hearing loss in one or both ears. The World Health Organization (WHO) estimates that unaddressed hearing loss poses an annual global cost of $980 billion, including cost of educational support, loss of productivity, and societal costs. These are all evident that people with hearing loss are experiencing several kinds and levels of difficulties. In this dissertation, …